Option universe resolution improvements (#8324)

* Option universe improvements

- Improvement for resolution handling of option universes, affecting
  performance in live mode. Adding regression algorithm

* Minor fix for research test

.devcontainer/Dockerfile

@@ -0,0 +1,8 @@
+# Use QuantConnect Research as the base
+FROM quantconnect/research:latest
+
+# Install dos2unix utility for converting pesky windows formatting when needed
+RUN apt-get update && apt-get install -y dos2unix
+
+# Install QuantConnect Stubs for Python Autocomplete
+RUN pip install --no-cache-dir quantconnect-stubs

.devcontainer/devcontainer.json

@@ -0,0 +1,34 @@
+{
+	"name": "Lean Development Container",
+
+	"workspaceMount": "source=${localWorkspaceFolder},target=/Lean,type=bind",
+	"workspaceFolder": "/Lean",
+
+	// Use devcontainer Dockerfile that is based on Lean foundation image
+	"build": { "dockerfile": "Dockerfile" },
+	
+	// Set *default* container specific settings.json values on container create.
+	"settings": { 
+		"terminal.integrated.profiles.linux": {
+			"bash": {
+				"path": "bash",
+				"icon": "terminal-bash"
+			}
+		}
+	},
+
+	// Add the IDs of extensions you want installed when the container is created.
+	"extensions": ["ms-dotnettools.csharp", "ms-python.python", "ms-python.vscode-pylance", "formulahendry.dotnet-test-explorer", "eamodio.gitlens", "yzhang.markdown-all-in-one"],
+
+	// Use 'forwardPorts' to make a list of ports inside the container available locally.
+	// "forwardPorts": [],
+
+	// Uncomment the next line to run commands after the container is created - for example installing curl.
+	"postCreateCommand": "dotnet nuget add source /Lean/LocalPackages;chmod u+x /Lean/.vscode/launch_research.sh;dos2unix /Lean/.vscode/launch_research.sh",
+
+	// Add mounts to docker container
+	"mounts": [ 
+		// Example data mount from local machine, must use target directory in Config.json
+		// "source=C:/Users/XXXXXXXXXXXX/Lean/Data,target=/Data,type=bind,consistency=cached" 
+	]
+}

.github/workflows/api-tests.yml

@@ -0,0 +1,30 @@
+name: API Tests
+
+on:
+  push:
+    branches: ['*']
+    tags: ['*']
+  pull_request:
+    branches: [master]
+
+jobs:
+  build:
+    runs-on: ubuntu-20.04
+    # Only run on push events (not on pull_request) for security reasons in order to be able to use secrets
+    if: ${{ github.event_name == 'push' }}
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Free space
+        run: df -h && rm -rf /usr/share/dotnet && sudo rm -rf /usr/local/lib/android && sudo rm -rf /opt/ghc && rm -rf /opt/hostedtoolcache* && df -h
+      - name: Run API Tests
+        uses: addnab/docker-run-action@v3
+        with:
+          image: quantconnect/lean:foundation
+          options: --workdir /__w/Lean/Lean -v /home/runner/work:/__w -e GITHUB_REF=${{ github.ref }} -e QC_JOB_USER_ID=${{ secrets.QC_JOB_USER_ID }} -e QC_API_ACCESS_TOKEN=${{ secrets.QC_API_ACCESS_TOKEN }} -e QC_JOB_ORGANIZATION_ID=${{ secrets.QC_JOB_ORGANIZATION_ID }}
+          shell: bash
+          run: |
+            # Build
+            dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
+            # Run Projects tests
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --blame-hang-timeout 300seconds --blame-crash --filter "FullyQualifiedName=QuantConnect.Tests.API.ProjectTests|ObjectStoreTests" -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\)

.github/workflows/gh-actions.yml

@@ -10,23 +10,21 @@ on:
 jobs:
   build:
     runs-on: ubuntu-20.04
-    container:
-        image: quantconnect/lean:foundation
     steps:
-      - uses: actions/checkout@v2
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Free space
+        run: df -h && rm -rf /usr/share/dotnet && sudo rm -rf /usr/local/lib/android && sudo rm -rf /opt/ghc && rm -rf /opt/hostedtoolcache* && df -h
 
-      - name: Build
-        run: dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
-
-      - name: Run Tests
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "TestCategory!=TravisExclude&TestCategory!=ResearchRegressionTests" -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\)
-
-      - name: Generate & Publish python stubs
-        if: startsWith(github.ref, 'refs/tags/')
-        run: |
-          chmod +x ci_build_stubs.sh
-          ./ci_build_stubs.sh -t -g -p
-        env:
-          PYPI_API_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
-          ADDITIONAL_STUBS_REPOS: ${{ secrets.ADDITIONAL_STUBS_REPOS }}
-          QC_GIT_TOKEN: ${{ secrets.QC_GIT_TOKEN }}
+      - uses: addnab/docker-run-action@v3
+        with:
+          image: quantconnect/lean:foundation
+          options: --workdir /__w/Lean/Lean -v /home/runner/work:/__w -e GITHUB_REF=${{ github.ref }} -e PYPI_API_TOKEN=${{ secrets.PYPI_API_TOKEN }} -e ADDITIONAL_STUBS_REPOS=${{ secrets.ADDITIONAL_STUBS_REPOS }} -e QC_GIT_TOKEN=${{ secrets.QC_GIT_TOKEN }}
+          shell: bash
+          run: |
+            # Build
+            dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln && \
+            # Run Tests
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --blame-hang-timeout 300seconds --blame-crash --filter "TestCategory!=TravisExclude&TestCategory!=ResearchRegressionTests" -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\) && \
+            # Generate & Publish python stubs
+            echo "GITHUB_REF $GITHUB_REF" && if [[ $GITHUB_REF = refs/tags/* ]]; then (chmod +x ci_build_stubs.sh && ./ci_build_stubs.sh -t -g -p); else echo "Skipping stub generation"; fi

.github/workflows/regression-tests.yml

@@ -10,13 +10,19 @@ on:
 jobs:
   build:
     runs-on: ubuntu-20.04
-    container:
-        image: quantconnect/lean:foundation
     steps:
-      - uses: actions/checkout@v2
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Free space
+        run: df -h && rm -rf /usr/share/dotnet && sudo rm -rf /usr/local/lib/android && sudo rm -rf /opt/ghc && rm -rf /opt/hostedtoolcache* && df -h
 
-      - name: Build
-        run: dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
-
-      - name: Run Tests
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter TestCategory=RegressionTests -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\) TestRunParameters.Parameter\(name=\"reduced-disk-size\", value=\"true\"\)
+      - uses: addnab/docker-run-action@v3
+        with:
+          image: quantconnect/lean:foundation
+          options: --workdir /__w/Lean/Lean -v /home/runner/work:/__w
+          shell: bash
+          run: |
+            # Build
+            dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
+            # Run Tests
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter TestCategory=RegressionTests -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\) TestRunParameters.Parameter\(name=\"reduced-disk-size\", value=\"true\"\)

.github/workflows/report-generator.yml

@@ -0,0 +1,30 @@
+name: Report Generator Tests
+
+on:
+  push:
+    branches: ['*']
+    tags: ['*']
+  pull_request:
+    branches: [master]
+
+jobs:
+  build:
+    runs-on: ubuntu-20.04
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Free space
+        run: df -h && rm -rf /usr/share/dotnet && sudo rm -rf /usr/local/lib/android && sudo rm -rf /opt/ghc && rm -rf /opt/hostedtoolcache* && df -h
+
+      - uses: addnab/docker-run-action@v3
+        with:
+          image: quantconnect/lean:foundation
+          options: --workdir /__w/Lean/Lean -v /home/runner/work:/__w
+          shell: bash
+          run: |
+            # Build
+            dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
+            # Run Backtest
+            cd ./Launcher/bin/Release && dotnet QuantConnect.Lean.Launcher.dll && cd ../../../
+            # Run Report
+            cd ./Report/bin/Release && dotnet ./QuantConnect.Report.dll --backtest-data-source-file ../../../Launcher/bin/Release/BasicTemplateFrameworkAlgorithm.json --close-automatically true

.github/workflows/research-regression-tests.yml

@@ -10,26 +10,27 @@ on:
 jobs:
   build:
     runs-on: ubuntu-20.04
-    container:
-        image: quantconnect/lean:foundation
     steps:
-      - uses: actions/checkout@v2
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Free space
+        run: df -h && rm -rf /usr/share/dotnet && sudo rm -rf /usr/local/lib/android && sudo rm -rf /opt/ghc && rm -rf /opt/hostedtoolcache* && df -h
 
-      - name: install dependencies
-        run: |
-          pip3 install papermill==2.4.0 clr-loader==0.1.6
-
-      - name: install kernel
-        run: dotnet tool install --global Microsoft.dotnet-interactive --version 1.0.340501
-
-      - name: Add dotnet tools to Path
-        run: echo "$HOME/.dotnet/tools" >> $GITHUB_PATH
-
-      - name: activate kernel for jupyter
-        run: dotnet interactive jupyter install
-
-      - name: Build
-        run: dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
-
-      - name: Run Tests
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter TestCategory=ResearchRegressionTests -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\) TestRunParameters.Parameter\(name=\"reduced-disk-size\", value=\"true\"\)
+      - uses: addnab/docker-run-action@v3
+        with:
+          image: quantconnect/lean:foundation
+          options: --workdir /__w/Lean/Lean -v /home/runner/work:/__w
+          shell: bash
+          run: |
+            # install dependencies
+            pip3 install papermill==2.4.0 clr-loader==0.1.6
+            # install kernel
+            dotnet tool install --global Microsoft.dotnet-interactive --version 1.0.340501
+            # Add dotnet tools to Path
+            export PATH="$HOME/.dotnet/tools:$PATH"
+            # activate kernel for jupyter
+            dotnet interactive jupyter install
+            # Build
+            dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
+            # Run Tests
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter TestCategory=ResearchRegressionTests -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\) TestRunParameters.Parameter\(name=\"reduced-disk-size\", value=\"true\"\)

.github/workflows/virtual-environments.yml

@@ -10,49 +10,48 @@ on:
 jobs:
   build:
     runs-on: ubuntu-20.04
-    container:
-        image: quantconnect/lean:foundation
     steps:
-      - uses: actions/checkout@v2
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Free space
+        run: df -h && rm -rf /usr/share/dotnet && sudo rm -rf /usr/local/lib/android && sudo rm -rf /opt/ghc && rm -rf /opt/hostedtoolcache* && df -h
 
-      - name: Build
-        run: dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
-
-      - name: Python Virtual Environment System Packages
-        run: python -m venv /lean-testenv --system-site-packages && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.99 && deactivate
-
-      - name: Run Virtual Environment Test System Packages
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment"
-
-      - name: Python Virtual Environment
-        run: rm -rf /lean-testenv && python -m venv /lean-testenv && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.99 && deactivate
-
-      - name: Run Virtual Environment Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment"
-
-      - name: Run Python Package Tests
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests"
-
-      - name: Run Pomegranate Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.PomegranateTest"
-
-      - name: Run Tensorforce Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorforceTests"
-
-      - name: Run StableBaselines Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.StableBaselinesTest"
-
-      - name: Run AxPlatform Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.AxPlatformTest"
-
-      - name: Run NeuralTangents Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.NeuralTangentsTest"
-
-      - name: Run NBeats Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.NBeatsTest"
-
-      - name: Run Tensorly Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorlyTest"
-
-      - name: Run Ignite Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.IgniteTest"
+      - uses: addnab/docker-run-action@v3
+        with:
+          image: quantconnect/lean:foundation
+          options: --workdir /__w/Lean/Lean -v /home/runner/work:/__w
+          shell: bash
+          run: |
+            # Build
+            dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln && \
+            # Python Virtual Environment System Packages
+            python -m venv /lean-testenv --system-site-packages && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.185 && deactivate && \
+            # Run Virtual Environment Test System Packages
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment" && \
+            # Python Virtual Environment
+            rm -rf /lean-testenv && python -m venv /lean-testenv && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.185 && deactivate && \
+            # Run Virtual Environment Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment" && \
+            # Run Python Package Tests
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run StableBaselines Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.StableBaselinesTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run AxPlatform Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.AxPlatformTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run TensorlyTest Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorlyTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run NeuralTangents, Ignite Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.NeuralTangentsTest|IgniteTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run TensorflowTest
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorflowTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run TensorflowProbability
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorflowProbabilityTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run Hvplot Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.HvplotTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run Keras Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.KerasTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run Transformers
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.Transformers" --blame-hang-timeout 120seconds --blame-crash && \
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.XTransformers" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run Shap
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.ShapTest" --blame-hang-timeout 120seconds --blame-crash

.gitignore

@@ -1,3 +1,6 @@
+# OS Files
+.DS_Store
+
 # Object files
 *.o
 *.ko

.vs/readme.md

@@ -20,8 +20,8 @@ To use Lean CLI follow the instructions for installation and tutorial for usage
 
 1. Install [.Net 6](https://dotnet.microsoft.com/download) for the project
 
-2. (Optional) Get [Python 3.6.8](https://www.python.org/downloads/release/python-368/) for running Python algorithms
-    - Follow Python instructions [here](https://github.com/QuantConnect/Lean/tree/master/Algorithm.Python#installing-python-36) for your platform
+2. (Optional) Get [Python 3.8.13](https://www.python.org/downloads/release/python-3813/) for running Python algorithms
+    - Follow Python instructions [here](https://github.com/QuantConnect/Lean/tree/master/Algorithm.Python#installing-python-38) for your platform
 
 3. Get [Visual Studio](https://visualstudio.microsoft.com/vs/)
 

.vscode/launch.json

@@ -26,7 +26,7 @@
             "program": "${workspaceFolder}/Launcher/bin/Debug/QuantConnect.Lean.Launcher.dll",
             "args": [
                 "--config",
-                "${workspaceFolder}/Launcher/config.json"
+                "${workspaceFolder}/Launcher/bin/Debug/config.json"
             ],
             "cwd": "${workspaceFolder}/Launcher/bin/Debug/",
             "stopAtEntry": false,

.vscode/launch_research.sh

@@ -0,0 +1,15 @@
+# Realpath polyfill, notably absent macOS and some debian distros
+absolute_path() {
+  echo "$(cd "$(dirname "${1}")" && pwd)/$(basename "${1}")"
+}
+
+# Get build directory from args position 1, or use default
+DEFAULT_BUILD_DIR=../Launcher/bin/Debug/
+BUILD_DIR=${1:-$DEFAULT_BUILD_DIR}
+BUILD_DIR=$(absolute_path "${BUILD_DIR}")
+
+#Add our build directory to python path for python kernel
+export PYTHONPATH="${PYTHONPATH}:${BUILD_DIR}"
+
+# Launch jupyter-lab
+jupyter-lab --allow-root --no-browser --notebook-dir=$BUILD_DIR --LabApp.token=''

.vscode/readme.md

@@ -4,6 +4,8 @@ This document contains information regarding ways to use Visual Studio Code to w
 
 - Using Lean CLI -> A great tool for working with your algorithms locally, while still being able to deploy to the cloud and have access to Lean data. It is also able to run algorithms locally through our official docker images **Recommended for algorithm development.
 
+- Using a Lean Dev container -> A docker environment with all dependencies pre-installed to allow seamless Lean development across platforms. Great for open source contributors.
+
 - Locally installing all dependencies to run Lean with Visual Studio Code on your OS.
 
 <br />
@@ -12,32 +14,63 @@ This document contains information regarding ways to use Visual Studio Code to w
 
 <h2>Option 1: Lean CLI</h2>
 
-To use Lean CLI follow the instructions for installation and tutorial for usage in our [documentation](https://www.quantconnect.com/docs/v2/lean-cli/getting-started/lean-cli)
+To use Lean CLI follow the instructions for installation and tutorial for usage in our [documentation](https://www.quantconnect.com/docs/v2/lean-cli/key-concepts/getting-started)
 
 <br />
 
-<h2>Option 2: Install Dependencies Locally</h2>
+<h2>Option 2: Lean Development Container</h2>
 
-1. Install [.Net 6](https://dotnet.microsoft.com/download) for the project
+Before anything we need to ensure a few things have been done for either option:
 
-2. (Optional) Get [Python 3.6.8](https://www.python.org/downloads/release/python-368/) for running Python algorithms
-    - Follow Python instructions [here](https://github.com/QuantConnect/Lean/tree/master/Algorithm.Python#installing-python-36) for your platform
+1. Get [Visual Studio Code](https://code.visualstudio.com/download)
+    - Get [Remote Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) Extension
+
+2. Get [Docker](https://docs.docker.com/get-docker/):
+    - Follow the instructions for your Operating System
+    - New to Docker? Try [docker getting-started](https://docs.docker.com/get-started/)
+
+3. Pull Lean’s latest research image from a terminal
+    - `docker pull quantconnect/research:latest`
+
+4. Get Lean into VS Code
+    - Download the repo or clone it using: `git clone [https://github.com/QuantConnect/Lean](https://github.com/QuantConnect/Lean)`
+    - Open the folder using VS Code
+
+5. Open Development Container
+    - In VS Code, either:
+        - Select "Reopen in Container" from pop up box.
+
+            OR
+
+        - Ctrl+Shift+P (Command Palette) and select "Remote-Containers: Rebuild and Reopen in Container"
+
+You should now be in the development container, give VS Code a moment to prepare and you will be ready to go!
+If you would like to mount any additional local files to your container, checkout [devcontainer.json "mounts" section](https://containers.dev/implementors/json_reference/) for an example! Upon any mount changes you must rebuild the container using Command Palette as in step 5.
+
+<br />
+
+<h2>Option 3: Install Dependencies Locally</h2>
+
+1. Install [.NET 6](https://dotnet.microsoft.com/en-us/download/dotnet/6.0) for the project
+
+2. (Optional) Get [Python 3.8.13](https://www.python.org/downloads/release/python-3813/) for running Python algorithms
+    - Follow Python instructions [here](https://github.com/QuantConnect/Lean/tree/master/Algorithm.Python#installing-python-38) for your platform
 
 3. Get [Visual Studio Code](https://code.visualstudio.com/download)
     - Get the Extension [C#](https://marketplace.visualstudio.com/items?itemName=ms-dotnettools.csharp) for C# Debugging
     - Get the Extension [Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python) for Python Debugging
 
 4. Get Lean into VS Code
-    - Download the repo or clone it using: _git clone [https://github.com/QuantConnect/Lean](https://github.com/QuantConnect/Lean)_
+    - Download the repo or clone it using: `git clone [https://github.com/QuantConnect/Lean](https://github.com/QuantConnect/Lean)`
     - Open the folder using VS Code
 
-Your environment is prepared and ready to run lean
+Your environment is prepared and ready to run Lean.
 
 <br />
 
 <h1>How to use Lean</h1>
 
-This section will cover configuring, building, launching and debugging lean. This is only applicable to option 2 from above. This does not apply to Lean CLI, please refer to [CLI documentation](https://www.quantconnect.com/docs/v2/lean-cli/getting-started/lean-cli)
+This section will cover configuring, building, launching and debugging lean. This is only applicable to option 2 from above. This does not apply to Lean CLI, please refer to [CLI documentation](https://www.quantconnect.com/docs/v2/lean-cli/key-concepts/getting-started)
 
 <br />
 
@@ -73,7 +106,6 @@ In VS Code run build task (Ctrl+Shift+B or "Terminal" dropdown); there are a few
 
 - __Build__ - basic build task, just builds Lean once
 - __Rebuild__ - rebuild task, completely rebuilds the project. Use if having issues with debugging symbols being loaded for your algorithms.
-- __Autobuilder__ - Starts a script that builds then waits for files to change and rebuilds appropriately
 - __Clean__ - deletes out all project build files
 
 <br />
@@ -123,5 +155,6 @@ _Figure 2: Python Debugger Messages_
 <h1>Common Issues</h1>
 Here we will cover some common issues with setting this up. This section will expand as we get user feedback!
 
-- Autocomplete and reference finding with omnisharp can sometimes bug, if this occurs use the command palette to restart omnisharp. (Ctrl+Shift+P "OmniSharp: Restart OmniSharp")
+- The "project file cannot be loaded" and "nuget packages not found" errors occurs when the project files are open by another process in the host. Closing all applications and/or restarting the computer solve the issue.
+- Autocomplete and reference finding with omnisharp can sometimes be buggy, if this occurs use the command palette to restart omnisharp. (Ctrl+Shift+P "OmniSharp: Restart OmniSharp")
 - Any error messages about building in VSCode that point to comments in JSON. Either select **ignore** or follow steps described [here](https://stackoverflow.com/questions/47834825/in-vs-code-disable-error-comments-are-not-permitted-in-json) to remove the errors entirely.

.vscode/settings.json

@@ -0,0 +1,7 @@
+{
+    "files.eol": "\n",
+    "python.analysis.extraPaths": [
+        "/Lean/Algorithm.Python",
+        "/opt/miniconda3/lib/python3.8/site-packages"
+    ]
+}

.vscode/tasks.json

@@ -50,6 +50,18 @@
                 "reveal": "silent"
             },
             "problemMatcher": "$msCompile"
+        },
+        {
+            "label": "start research",
+            "type": "shell",
+            "dependsOn": ["build"],
+            "group": "build",
+            "isBackground": true,
+            "command" : "${workspaceFolder}/.vscode/launch_research.sh",
+            "args" : [
+                "${workspaceFolder}/Launcher/bin/Debug"
+            ],
+            "problemMatcher": "$msCompile"
         }
     ]
 }

Algorithm.CSharp/AccumulativeInsightPortfolioRegressionAlgorithm.cs

@@ -55,7 +55,7 @@ namespace QuantConnect.Algorithm.CSharp
                 ||
                 Portfolio.TotalHoldingsValue < Portfolio.TotalPortfolioValue * 0.01m)
             {
-                throw new Exception($"Unexpected Total Holdings Value: {Portfolio.TotalHoldingsValue}");
+                throw new RegressionTestException($"Unexpected Total Holdings Value: {Portfolio.TotalHoldingsValue}");
             }
         }
 
@@ -67,7 +67,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -79,53 +79,43 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "199"},
+            {"Total Orders", "199"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
             {"Compounding Annual Return", "-12.611%"},
             {"Drawdown", "0.200%"},
             {"Expectancy", "-0.585"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99827.80"},
             {"Net Profit", "-0.172%"},
-            {"Sharpe Ratio", "-10.169"},
+            {"Sharpe Ratio", "-11.13"},
+            {"Sortino Ratio", "-16.704"},
             {"Probabilistic Sharpe Ratio", "12.075%"},
             {"Loss Rate", "78%"},
             {"Win Rate", "22%"},
             {"Profit-Loss Ratio", "0.87"},
-            {"Alpha", "-0.149"},
+            {"Alpha", "-0.156"},
             {"Beta", "0.035"},
             {"Annual Standard Deviation", "0.008"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-9.603"},
             {"Tracking Error", "0.215"},
-            {"Treynor Ratio", "-2.264"},
+            {"Treynor Ratio", "-2.478"},
             {"Total Fees", "$199.00"},
             {"Estimated Strategy Capacity", "$26000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.002"},
-            {"Kelly Criterion Estimate", "38.796"},
-            {"Kelly Criterion Probability Value", "0.228"},
-            {"Sortino Ratio", "-22.493"},
-            {"Return Over Maximum Drawdown", "-77.93"},
-            {"Portfolio Turnover", "1.211"},
-            {"Total Insights Generated", "100"},
-            {"Total Insights Closed", "99"},
-            {"Total Insights Analysis Completed", "99"},
-            {"Long Insight Count", "100"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$135639.1761"},
-            {"Total Accumulated Estimated Alpha Value", "$21852.9784"},
-            {"Mean Population Estimated Insight Value", "$220.7372"},
-            {"Mean Population Direction", "53.5354%"},
-            {"Mean Population Magnitude", "53.5354%"},
-            {"Rolling Averaged Population Direction", "58.2788%"},
-            {"Rolling Averaged Population Magnitude", "58.2788%"},
-            {"OrderListHash", "3c4c4085810cc5ecdb927d3647b9bbf3"}
+            {"Portfolio Turnover", "119.89%"},
+            {"OrderListHash", "d06c26f557b83d8d42ac808fe2815a1e"}
         };
     }
 }

Algorithm.CSharp/AddAlphaModelAlgorithm.cs

@@ -66,7 +66,7 @@ namespace QuantConnect.Algorithm.CSharp
                 || insightsCollection.Insights.Count(insight => insight.Symbol == _spy) != 1
                 || insightsCollection.Insights.Count(insight => insight.Symbol == _ibm) != 1)
             {
-                throw new Exception("Unexpected insights were emitted");
+                throw new RegressionTestException("Unexpected insights were emitted");
             }
         }
 
@@ -103,7 +103,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -115,53 +115,43 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "9"},
+            {"Total Orders", "9"},
             {"Average Win", "0.86%"},
             {"Average Loss", "-0.27%"},
-            {"Compounding Annual Return", "184.364%"},
+            {"Compounding Annual Return", "206.404%"},
             {"Drawdown", "1.700%"},
             {"Expectancy", "1.781"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101441.92"},
             {"Net Profit", "1.442%"},
-            {"Sharpe Ratio", "4.86"},
+            {"Sharpe Ratio", "4.836"},
+            {"Sortino Ratio", "10.481"},
             {"Probabilistic Sharpe Ratio", "59.497%"},
             {"Loss Rate", "33%"},
             {"Win Rate", "67%"},
             {"Profit-Loss Ratio", "3.17"},
-            {"Alpha", "4.181"},
+            {"Alpha", "4.164"},
             {"Beta", "-1.322"},
             {"Annual Standard Deviation", "0.321"},
             {"Annual Variance", "0.103"},
             {"Information Ratio", "-0.795"},
             {"Tracking Error", "0.532"},
-            {"Treynor Ratio", "-1.18"},
+            {"Treynor Ratio", "-1.174"},
             {"Total Fees", "$14.78"},
-            {"Estimated Strategy Capacity", "$47000000.00"},
+            {"Estimated Strategy Capacity", "$120000000.00"},
             {"Lowest Capacity Asset", "IBM R735QTJ8XC9X"},
-            {"Fitness Score", "0.408"},
-            {"Kelly Criterion Estimate", "16.559"},
-            {"Kelly Criterion Probability Value", "0.316"},
-            {"Sortino Ratio", "12.447"},
-            {"Return Over Maximum Drawdown", "106.327"},
-            {"Portfolio Turnover", "0.411"},
-            {"Total Insights Generated", "3"},
-            {"Total Insights Closed", "3"},
-            {"Total Insights Analysis Completed", "3"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "3"},
-            {"Long/Short Ratio", "0%"},
-            {"Estimated Monthly Alpha Value", "$20784418.6104"},
-            {"Total Accumulated Estimated Alpha Value", "$3579538.7607"},
-            {"Mean Population Estimated Insight Value", "$1193179.5869"},
-            {"Mean Population Direction", "100%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "100%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9da9afe1e9137638a55db1676adc2be1"}
+            {"Portfolio Turnover", "41.18%"},
+            {"OrderListHash", "713c956deb193bed2290e9f379c0f9f9"}
         };
     }
 }

Algorithm.CSharp/AddAndRemoveOptionContractRegressionAlgorithm.cs

@@ -40,8 +40,8 @@ namespace QuantConnect.Algorithm.CSharp
 
             var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
 
-            _contract = OptionChainProvider.GetOptionContractList(aapl, Time)
-                .OrderBy(symbol => symbol.ID.Symbol)
+            _contract = OptionChain(aapl)
+                .OrderBy(x => x.ID.Symbol)
                 .FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
                     && optionContract.ID.OptionStyle == OptionStyle.American);
             AddOptionContract(_contract);
@@ -59,7 +59,7 @@ namespace QuantConnect.Algorithm.CSharp
                 }
                 else
                 {
-                    throw new Exception("Expect a single call to OnData where we removed the option and underlying");
+                    throw new RegressionTestException("Expect a single call to OnData where we removed the option and underlying");
                 }
             }
         }
@@ -68,7 +68,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (!_hasRemoved)
             {
-                throw new Exception("Expect a single call to OnData where we removed the option and underlying");
+                throw new RegressionTestException("Expect a single call to OnData where we removed the option and underlying");
             }
         }
 
@@ -80,7 +80,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -90,21 +90,29 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 0;
+        public int AlgorithmHistoryDataPoints => 1;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "0"},
+            {"Total Orders", "0"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -119,25 +127,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", ""},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
+            {"Portfolio Turnover", "0%"},
             {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
         };
     }

Algorithm.CSharp/AddAndRemoveSecuritySameLoopRegressionAlgorithm.cs

@@ -39,8 +39,8 @@ namespace QuantConnect.Algorithm.CSharp
 
             var aapl = AddEquity("AAPL").Symbol;
 
-            _contract = OptionChainProvider.GetOptionContractList(aapl, Time)
-                .OrderBy(symbol => symbol.ID.Symbol)
+            _contract = OptionChain(aapl)
+                .OrderBy(x => x.ID.Symbol)
                 .FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
                     && optionContract.ID.OptionStyle == OptionStyle.American);
         }
@@ -49,7 +49,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (_hasRemoved)
             {
-                throw new Exception("Expect a single call to OnData where we removed the option and underlying");
+                throw new RegressionTestException("Expect a single call to OnData where we removed the option and underlying");
             }
 
             _hasRemoved = true;
@@ -65,7 +65,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (!_hasRemoved)
             {
-                throw new Exception("We did not remove the option contract!");
+                throw new RegressionTestException("We did not remove the option contract!");
             }
         }
 
@@ -77,7 +77,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -87,21 +87,29 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 0;
+        public int AlgorithmHistoryDataPoints => 1;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "0"},
+            {"Total Orders", "0"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -116,25 +124,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", ""},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
+            {"Portfolio Turnover", "0%"},
             {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
         };
     }

Algorithm.CSharp/AddBetaIndicatorRegressionAlgorithm.cs

@@ -47,15 +47,15 @@ namespace QuantConnect.Algorithm.CSharp
 
             if (!_beta.IsReady)
             {
-                throw new Exception("_beta indicator was expected to be ready");
+                throw new RegressionTestException("_beta indicator was expected to be ready");
             }
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
-                var price = data["IBM"].Close;
+                var price = slice["IBM"].Close;
                 Buy("IBM", 10);
                 LimitOrder("IBM", 10, price * 0.1m);
                 StopMarketOrder("IBM", 10, price / 0.1m);
@@ -63,7 +63,7 @@ namespace QuantConnect.Algorithm.CSharp
             
             if (_beta.Current.Value < 0m || _beta.Current.Value > 2.80m)
             {
-                throw new Exception($"_beta value was expected to be between 0 and 2.80 but was {_beta.Current.Value}");
+                throw new RegressionTestException($"_beta value was expected to be between 0 and 2.80 but was {_beta.Current.Value}");
             }
 
             Log($"Beta between IBM and SPY is: {_beta.Current.Value}");
@@ -97,7 +97,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp};
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -109,53 +109,43 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 11;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "3"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "12.939%"},
             {"Drawdown", "0.300%"},
             {"Expectancy", "0"},
+            {"Start Equity", "10000"},
+            {"End Equity", "10028.93"},
             {"Net Profit", "0.289%"},
-            {"Sharpe Ratio", "4.233"},
+            {"Sharpe Ratio", "3.924"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "68.349%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.035"},
+            {"Alpha", "0.028"},
             {"Beta", "0.122"},
             {"Annual Standard Deviation", "0.024"},
             {"Annual Variance", "0.001"},
             {"Information Ratio", "-3.181"},
             {"Tracking Error", "0.142"},
-            {"Treynor Ratio", "0.842"},
+            {"Treynor Ratio", "0.78"},
             {"Total Fees", "$1.00"},
             {"Estimated Strategy Capacity", "$35000000.00"},
             {"Lowest Capacity Asset", "IBM R735QTJ8XC9X"},
-            {"Fitness Score", "0.022"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "8.508"},
-            {"Return Over Maximum Drawdown", "58.894"},
-            {"Portfolio Turnover", "0.022"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "bd88c6a0e10c7e146b05377205101a12"}
+            {"Portfolio Turnover", "1.51%"},
+            {"OrderListHash", "1db1ce949db995bba20ed96ea5e2438a"}
         };
     }
 }

Algorithm.CSharp/AddFutureContractWithContinuousRegressionAlgorithm.cs

@@ -31,7 +31,6 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class AddFutureContractWithContinuousRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private Symbol _currentMappedSymbol;
         private Future _continuousContract;
         private Future _futureContract;
         private bool _ended;
@@ -56,20 +55,20 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
             if (_ended)
             {
-                throw new Exception($"Algorithm should of ended!");
+                throw new RegressionTestException($"Algorithm should of ended!");
             }
-            if (data.Keys.Count > 2)
+            if (slice.Keys.Count > 2)
             {
-                throw new Exception($"Getting data for more than 2 symbols! {string.Join(",", data.Keys.Select(symbol => symbol))}");
+                throw new RegressionTestException($"Getting data for more than 2 symbols! {string.Join(",", slice.Keys.Select(symbol => symbol))}");
             }
             if (UniverseManager.Count != 3)
             {
-                throw new Exception($"Expecting 3 universes (chain, continuous and user defined) but have {UniverseManager.Count}");
+                throw new RegressionTestException($"Expecting 3 universes (chain, continuous and user defined) but have {UniverseManager.Count}");
             }
 
             if (!Portfolio.Invested)
@@ -99,7 +98,7 @@ namespace QuantConnect.Algorithm.CSharp
             if (changes.AddedSecurities.Any(security => security.Symbol != _continuousContract.Symbol && security.Symbol != _futureContract.Symbol)
                 || changes.RemovedSecurities.Any(security => security.Symbol != _continuousContract.Symbol && security.Symbol != _futureContract.Symbol))
             {
-                throw new Exception($"We got an unexpected security changes {changes}");
+                throw new RegressionTestException($"We got an unexpected security changes {changes}");
             }
         }
 
@@ -111,65 +110,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 63;
+        public long DataPoints => 73;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "3"},
+            {"Total Orders", "3"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.03%"},
             {"Compounding Annual Return", "-2.594%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99966.4"},
             {"Net Profit", "-0.034%"},
-            {"Sharpe Ratio", "-7.854"},
+            {"Sharpe Ratio", "-10.666"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "1.216%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.022"},
+            {"Alpha", "-0.029"},
             {"Beta", "0.004"},
             {"Annual Standard Deviation", "0.003"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-0.768"},
             {"Tracking Error", "0.241"},
-            {"Treynor Ratio", "-4.689"},
+            {"Treynor Ratio", "-6.368"},
             {"Total Fees", "$8.60"},
             {"Estimated Strategy Capacity", "$5500000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.417"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-81.518"},
-            {"Portfolio Turnover", "0.834"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "802a335b5c355e83b8cd2174f053c1b9"}
+            {"Portfolio Turnover", "66.80%"},
+            {"OrderListHash", "579e2e83dd7e5e7648c47e9eff132460"}
         };
     }
 }

Algorithm.CSharp/AddFutureOptionContractDataStreamingRegressionAlgorithm.cs

@@ -66,9 +66,9 @@ namespace QuantConnect.Algorithm.CSharp
             }
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
-            if (!data.HasData)
+            if (!slice.HasData)
             {
                 return;
             }
@@ -76,7 +76,7 @@ namespace QuantConnect.Algorithm.CSharp
             _onDataReached = true;
 
             var hasOptionQuoteBars = false;
-            foreach (var qb in data.QuoteBars.Values)
+            foreach (var qb in slice.QuoteBars.Values)
             {
                 if (qb.Symbol.SecurityType != SecurityType.FutureOption)
                 {
@@ -99,7 +99,7 @@ namespace QuantConnect.Algorithm.CSharp
                 return;
             }
 
-            if (data.ContainsKey(_es20h20) && data.ContainsKey(_es19m20))
+            if (slice.ContainsKey(_es20h20) && slice.ContainsKey(_es19m20))
             {
                 SetHoldings(_es20h20, 0.2);
                 SetHoldings(_es19m20, 0.2);
@@ -114,7 +114,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             if (!_onDataReached)
             {
-                throw new Exception("OnData() was never called.");
+                throw new RegressionTestException("OnData() was never called.");
             }
             if (_symbolsReceived.Count != _expectedSymbolsReceived.Count)
             {
@@ -132,7 +132,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             if (missingSymbols.Count > 0)
             {
-                throw new Exception($"Symbols: \"{string.Join(", ", missingSymbols)}\" were not found in OnData");
+                throw new RegressionTestException($"Symbols: \"{string.Join(", ", missingSymbols)}\" were not found in OnData");
             }
 
             foreach (var expectedSymbol in _expectedSymbolsReceived)
@@ -146,7 +146,7 @@ namespace QuantConnect.Algorithm.CSharp
 
                 if (nonDupeDataCount < 1000)
                 {
-                    throw new Exception($"Received too few data points. Expected >=1000, found {nonDupeDataCount} for {expectedSymbol}");
+                    throw new RegressionTestException($"Received too few data points. Expected >=1000, found {nonDupeDataCount} for {expectedSymbol}");
                 }
             }
         }
@@ -159,7 +159,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -171,53 +171,43 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "5512.811%"},
             {"Drawdown", "1.000%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "105332.8"},
             {"Net Profit", "5.333%"},
-            {"Sharpe Ratio", "64.137"},
+            {"Sharpe Ratio", "64.084"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "95.977%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "25.72"},
+            {"Alpha", "25.763"},
             {"Beta", "2.914"},
             {"Annual Standard Deviation", "0.423"},
             {"Annual Variance", "0.179"},
             {"Information Ratio", "66.11"},
             {"Tracking Error", "0.403"},
-            {"Treynor Ratio", "9.315"},
+            {"Treynor Ratio", "9.308"},
             {"Total Fees", "$8.60"},
             {"Estimated Strategy Capacity", "$22000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UK0MYO1"},
-            {"Fitness Score", "1"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "2.035"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "e7021bd385f366771ae00abd3a46a22e"}
+            {"Portfolio Turnover", "122.11%"},
+            {"OrderListHash", "d744fa8beaa60546c84924ed68d945d9"}
         };
     }
 }

Algorithm.CSharp/AddFutureOptionContractFromFutureChainRegressionAlgorithm.cs

@@ -40,16 +40,16 @@ namespace QuantConnect.Algorithm.CSharp
             });
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!_addedOptions)
             {
                 _addedOptions = true;
-                foreach (var futuresContracts in data.FutureChains.Values)
+                foreach (var futuresContracts in slice.FutureChains.Values)
                 {
                     foreach (var contract in futuresContracts)
                     {
-                        var option_contract_symbols = OptionChainProvider.GetOptionContractList(contract.Symbol, Time).ToList();
+                        var option_contract_symbols = OptionChain(contract.Symbol).ToList();
                         if(option_contract_symbols.Count == 0)
                         {
                             continue;
@@ -70,7 +70,7 @@ namespace QuantConnect.Algorithm.CSharp
                 return;
             }
 
-            foreach (var chain in data.OptionChains.Values)
+            foreach (var chain in slice.OptionChains.Values)
             {
                 foreach (var option in chain.Contracts.Keys)
                 {
@@ -88,36 +88,44 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 12164;
+        public long DataPoints => 12169;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "20"},
+            {"Total Orders", "20"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "386219349.202%"},
             {"Drawdown", "5.200%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "111911.55"},
             {"Net Profit", "11.912%"},
-            {"Sharpe Ratio", "1604181.92"},
+            {"Sharpe Ratio", "1604181.904"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "2144881.34"},
+            {"Alpha", "2144882.02"},
             {"Beta", "31.223"},
             {"Annual Standard Deviation", "1.337"},
             {"Annual Variance", "1.788"},
@@ -127,26 +135,8 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$35.70"},
             {"Estimated Strategy Capacity", "$2600000.00"},
             {"Lowest Capacity Asset", "ES 31C3JQS9D84PW|ES XCZJLC9NOB29"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "64221a660525c4259d5bd852eef1299c"}
+            {"Portfolio Turnover", "495.15%"},
+            {"OrderListHash", "85257286f088992d599c1ad0799a6237"}
         };
     }
 }

Algorithm.CSharp/AddFutureOptionSingleOptionChainSelectedInUniverseFilterRegressionAlgorithm.cs

@@ -55,10 +55,10 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 _optionFilterRan = true;
 
-                var expiry = new HashSet<DateTime>(optionContracts.Select(x => x.Underlying.ID.Date)).SingleOrDefault();
-                // Cast to IEnumerable<Symbol> because OptionFilterContract overrides some LINQ operators like `Select` and `Where`
+                var expiry = new HashSet<DateTime>(optionContracts.Select(x => x.Symbol.Underlying.ID.Date)).SingleOrDefault();
+                // Cast to List<Symbol> because OptionFilterContract overrides some LINQ operators like `Select` and `Where`
                 // and cause it to mutate the underlying Symbol collection when using those operators.
-                var symbol = new HashSet<Symbol>(((IEnumerable<Symbol>)optionContracts).Select(x => x.Underlying)).SingleOrDefault();
+                var symbol = new HashSet<Symbol>(((List<Symbol>)optionContracts).Select(x => x.Underlying)).SingleOrDefault();
 
                 if (expiry == null || symbol == null)
                 {
@@ -75,9 +75,9 @@ namespace QuantConnect.Algorithm.CSharp
             });
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
-            if (!data.HasData)
+            if (!slice.HasData)
             {
                 return;
             }
@@ -85,7 +85,7 @@ namespace QuantConnect.Algorithm.CSharp
             _onDataReached = true;
 
             var hasOptionQuoteBars = false;
-            foreach (var qb in data.QuoteBars.Values)
+            foreach (var qb in slice.QuoteBars.Values)
             {
                 if (qb.Symbol.SecurityType != SecurityType.FutureOption)
                 {
@@ -108,7 +108,7 @@ namespace QuantConnect.Algorithm.CSharp
                 return;
             }
 
-            foreach (var chain in data.OptionChains.Values)
+            foreach (var chain in slice.OptionChains.Values)
             {
                 var futureInvested = false;
                 var optionInvested = false;
@@ -122,7 +122,7 @@ namespace QuantConnect.Algorithm.CSharp
 
                     var future = option.Underlying;
 
-                    if (!optionInvested && data.ContainsKey(option))
+                    if (!optionInvested && slice.ContainsKey(option))
                     {
                         var optionContract = Securities[option];
                         var marginModel = optionContract.BuyingPowerModel as FuturesOptionsMarginModel;
@@ -131,16 +131,16 @@ namespace QuantConnect.Algorithm.CSharp
                             || marginModel.MaintenanceIntradayMarginRequirement == 0
                             || marginModel.MaintenanceOvernightMarginRequirement == 0)
                         {
-                            throw new Exception("Unexpected margin requirements");
+                            throw new RegressionTestException("Unexpected margin requirements");
                         }
 
                         if (marginModel.GetInitialMarginRequirement(optionContract, 1) == 0)
                         {
-                            throw new Exception("Unexpected Initial Margin requirement");
+                            throw new RegressionTestException("Unexpected Initial Margin requirement");
                         }
                         if (marginModel.GetMaintenanceMargin(optionContract) != 0)
                         {
-                            throw new Exception("Unexpected Maintenance Margin requirement");
+                            throw new RegressionTestException("Unexpected Maintenance Margin requirement");
                         }
 
                         MarketOrder(option, 1);
@@ -149,10 +149,10 @@ namespace QuantConnect.Algorithm.CSharp
 
                         if (marginModel.GetMaintenanceMargin(optionContract) == 0)
                         {
-                            throw new Exception("Unexpected Maintenance Margin requirement");
+                            throw new RegressionTestException("Unexpected Maintenance Margin requirement");
                         }
                     }
-                    if (!futureInvested && data.ContainsKey(future))
+                    if (!futureInvested && slice.ContainsKey(future))
                     {
                         MarketOrder(future, 1);
                         _invested = true;
@@ -170,7 +170,7 @@ namespace QuantConnect.Algorithm.CSharp
             }
             if (!_onDataReached)
             {
-                throw new Exception("OnData() was never called.");
+                throw new RegressionTestException("OnData() was never called.");
             }
             if (_symbolsReceived.Count != _expectedSymbolsReceived.Count)
             {
@@ -188,7 +188,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             if (missingSymbols.Count > 0)
             {
-                throw new Exception($"Symbols: \"{string.Join(", ", missingSymbols)}\" were not found in OnData");
+                throw new RegressionTestException($"Symbols: \"{string.Join(", ", missingSymbols)}\" were not found in OnData");
             }
 
             foreach (var expectedSymbol in _expectedSymbolsReceived)
@@ -202,7 +202,7 @@ namespace QuantConnect.Algorithm.CSharp
 
                 if (nonDupeDataCount < 1000)
                 {
-                    throw new Exception($"Received too few data points. Expected >=1000, found {nonDupeDataCount} for {expectedSymbol}");
+                    throw new RegressionTestException($"Received too few data points. Expected >=1000, found {nonDupeDataCount} for {expectedSymbol}");
                 }
             }
         }
@@ -215,65 +215,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 608437;
+        public long DataPoints => 608377;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "347.065%"},
             {"Drawdown", "0.900%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101950.53"},
             {"Net Profit", "1.951%"},
-            {"Sharpe Ratio", "15.548"},
+            {"Sharpe Ratio", "15.402"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "95.977%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "1.885"},
+            {"Alpha", "1.886"},
             {"Beta", "1.066"},
             {"Annual Standard Deviation", "0.155"},
             {"Annual Variance", "0.024"},
             {"Information Ratio", "13.528"},
             {"Tracking Error", "0.142"},
-            {"Treynor Ratio", "2.258"},
+            {"Treynor Ratio", "2.237"},
             {"Total Fees", "$3.57"},
             {"Estimated Strategy Capacity", "$760000.00"},
             {"Lowest Capacity Asset", "ES XCZJLDQX2SRO|ES XCZJLC9NOB29"},
-            {"Fitness Score", "0.403"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0.403"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "738240babf741f1bf79f85ea5026ec4c"}
+            {"Portfolio Turnover", "32.31%"},
+            {"OrderListHash", "7a04f66a30d793bf187c2695781ad3ee"}
         };
     }
 }

Algorithm.CSharp/AddOptionContractExpiresRegressionAlgorithm.cs

@@ -42,12 +42,12 @@ namespace QuantConnect.Algorithm.CSharp
             AddUniverse("my-daily-universe-name", time => new List<string> { "AAPL" });
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (_option == null)
             {
-                var option = OptionChainProvider.GetOptionContractList(_twx, Time)
-                    .OrderBy(symbol => symbol.ID.Symbol)
+                var option = OptionChain(_twx)
+                    .OrderBy(x => x.ID.Symbol)
                     .FirstOrDefault(optionContract => optionContract.ID.Date == _expiration
                                                       && optionContract.ID.OptionRight == OptionRight.Call
                                                       && optionContract.ID.OptionStyle == OptionStyle.American);
@@ -68,11 +68,11 @@ namespace QuantConnect.Algorithm.CSharp
 
                     if (!config.Any())
                     {
-                        throw new Exception($"Was expecting configurations for {symbol}");
+                        throw new RegressionTestException($"Was expecting configurations for {symbol}");
                     }
                     if (config.Any(dataConfig => dataConfig.DataNormalizationMode != DataNormalizationMode.Raw))
                     {
-                        throw new Exception($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
+                        throw new RegressionTestException($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
                     }
                 }
             }
@@ -81,14 +81,14 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_option).Any())
                 {
-                    throw new Exception($"Unexpected configurations for {_option} after it has been delisted");
+                    throw new RegressionTestException($"Unexpected configurations for {_option} after it has been delisted");
                 }
 
                 if (Securities[_twx].Invested)
                 {
                     if (!SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any())
                     {
-                        throw new Exception($"Was expecting configurations for {_twx}");
+                        throw new RegressionTestException($"Was expecting configurations for {_twx}");
                     }
 
                     // first we liquidate the option exercised position
@@ -99,7 +99,7 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any())
                 {
-                    throw new Exception($"Unexpected configurations for {_twx} after it has been liquidated");
+                    throw new RegressionTestException($"Unexpected configurations for {_twx} after it has been liquidated");
                 }
             }
         }
@@ -112,7 +112,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -122,55 +122,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 0;
+        public int AlgorithmHistoryDataPoints => 1;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "3"},
+            {"Total Orders", "3"},
             {"Average Win", "2.73%"},
             {"Average Loss", "-2.98%"},
             {"Compounding Annual Return", "-4.619%"},
             {"Drawdown", "0.300%"},
             {"Expectancy", "-0.042"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99668"},
             {"Net Profit", "-0.332%"},
-            {"Sharpe Ratio", "-3.149"},
+            {"Sharpe Ratio", "-4.614"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0.427%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
             {"Profit-Loss Ratio", "0.92"},
-            {"Alpha", "-0.015"},
+            {"Alpha", "-0.022"},
             {"Beta", "-0.012"},
             {"Annual Standard Deviation", "0.005"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-2.823"},
             {"Tracking Error", "0.049"},
-            {"Treynor Ratio", "1.372"},
+            {"Treynor Ratio", "2.01"},
             {"Total Fees", "$2.00"},
-            {"Estimated Strategy Capacity", "$67000000.00"},
+            {"Estimated Strategy Capacity", "$5700000.00"},
             {"Lowest Capacity Asset", "AOL VRKS95ENLBYE|AOL R735QTJ8XC9X"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-43.418"},
-            {"Return Over Maximum Drawdown", "-14.274"},
-            {"Portfolio Turnover", "0.007"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "4f50b8360ea317ef974801649088bd06"}
+            {"Portfolio Turnover", "0.55%"},
+            {"OrderListHash", "24191a4a3bf11c07622a21266618193d"}
         };
     }
 }

Algorithm.CSharp/AddOptionContractFromUniverseRegressionAlgorithm.cs

@@ -13,12 +13,12 @@
  * limitations under the License.
 */
 
-using System;
-using System.Collections.Generic;
-using System.Linq;
 using QuantConnect.Data;
 using QuantConnect.Data.UniverseSelection;
 using QuantConnect.Interfaces;
+using System;
+using System.Collections.Generic;
+using System.Linq;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -50,7 +50,7 @@ namespace QuantConnect.Algorithm.CSharp
                 enumerable => new[] { Time.Date <= new DateTime(2014, 6, 5) ? _twx : _aapl });
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (_option != null && Securities[_option].Price != 0 && !_traded)
             {
@@ -66,7 +66,7 @@ namespace QuantConnect.Algorithm.CSharp
                     // assert underlying still there after the universe selection removed it, still used by the manually added option contract
                     if (!configs.Any())
                     {
-                        throw new Exception($"Was expecting configurations for {_twx}" +
+                        throw new RegressionTestException($"Was expecting configurations for {_twx}" +
                                             $" even after it has been deselected from coarse universe because we still have the option contract.");
                     }
                 }
@@ -83,7 +83,7 @@ namespace QuantConnect.Algorithm.CSharp
                         var configs = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol);
                         if (configs.Any())
                         {
-                            throw new Exception($"Unexpected configuration for {symbol} after it has been deselected from coarse universe and option contract is removed.");
+                            throw new RegressionTestException($"Unexpected configuration for {symbol} after it has been deselected from coarse universe and option contract is removed.");
                         }
                     }
                 }
@@ -94,11 +94,11 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (_securityChanges.RemovedSecurities.Intersect(changes.RemovedSecurities).Any())
             {
-                throw new Exception($"SecurityChanges.RemovedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!");
+                throw new RegressionTestException($"SecurityChanges.RemovedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!");
             }
             if (_securityChanges.AddedSecurities.Intersect(changes.AddedSecurities).Any())
             {
-                throw new Exception($"SecurityChanges.AddedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!");
+                throw new RegressionTestException($"SecurityChanges.AddedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!");
             }
             // keep track of all removed and added securities
             _securityChanges += changes;
@@ -110,24 +110,24 @@ namespace QuantConnect.Algorithm.CSharp
 
             foreach (var addedSecurity in changes.AddedSecurities)
             {
-                var option = OptionChainProvider.GetOptionContractList(addedSecurity.Symbol, Time)
-                    .OrderBy(symbol => symbol.ID.Symbol)
+                var option = OptionChain(addedSecurity.Symbol)
+                    .OrderBy(contractData => contractData.ID.Symbol)
                     .First(optionContract => optionContract.ID.Date == _expiration
                                                       && optionContract.ID.OptionRight == OptionRight.Call
                                                       && optionContract.ID.OptionStyle == OptionStyle.American);
                 AddOptionContract(option);
 
-                foreach (var symbol in new[] { option, option.Underlying })
+                foreach (var symbol in new[] { option.Symbol, option.Underlying.Symbol })
                 {
                     var config = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol).ToList();
 
                     if (!config.Any())
                     {
-                        throw new Exception($"Was expecting configurations for {symbol}");
+                        throw new RegressionTestException($"Was expecting configurations for {symbol}");
                     }
                     if (config.Any(dataConfig => dataConfig.DataNormalizationMode != DataNormalizationMode.Raw))
                     {
-                        throw new Exception($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
+                        throw new RegressionTestException($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
                     }
                 }
 
@@ -143,16 +143,16 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (SubscriptionManager.Subscriptions.Any(dataConfig => dataConfig.Symbol == _twx || dataConfig.Symbol.Underlying == _twx))
             {
-                throw new Exception($"Was NOT expecting any configurations for {_twx} or it's options, since we removed the contract");
+                throw new RegressionTestException($"Was NOT expecting any configurations for {_twx} or it's options, since we removed the contract");
             }
 
             if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol != _aapl))
             {
-                throw new Exception($"Was expecting configurations for {_aapl}");
+                throw new RegressionTestException($"Was expecting configurations for {_aapl}");
             }
             if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol.Underlying != _aapl))
             {
-                throw new Exception($"Was expecting options configurations for {_aapl}");
+                throw new RegressionTestException($"Was expecting options configurations for {_aapl}");
             }
         }
 
@@ -164,65 +164,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 5797;
+        public long DataPoints => 5798;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 0;
+        public int AlgorithmHistoryDataPoints => 2;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.23%"},
             {"Compounding Annual Return", "-15.596%"},
             {"Drawdown", "0.200%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99768"},
             {"Net Profit", "-0.232%"},
-            {"Sharpe Ratio", "-7.739"},
+            {"Sharpe Ratio", "-8.903"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "1.216%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.024"},
+            {"Alpha", "0.015"},
             {"Beta", "-0.171"},
             {"Annual Standard Deviation", "0.006"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-11.082"},
             {"Tracking Error", "0.043"},
-            {"Treynor Ratio", "0.291"},
+            {"Treynor Ratio", "0.335"},
             {"Total Fees", "$2.00"},
             {"Estimated Strategy Capacity", "$2800000.00"},
             {"Lowest Capacity Asset", "AOL VRKS95ENLBYE|AOL R735QTJ8XC9X"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-19.883"},
-            {"Return Over Maximum Drawdown", "-67.224"},
-            {"Portfolio Turnover", "0.014"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "ae0b430e9c728966e3736fb352a689c6"}
+            {"Portfolio Turnover", "1.14%"},
+            {"OrderListHash", "cde7b518b7ad6d86cff6e5e092d9a413"}
         };
     }
 }

Algorithm.CSharp/AddOptionContractTwiceRegressionAlgorithm.cs

@@ -39,12 +39,12 @@ namespace QuantConnect.Algorithm.CSharp
             UniverseSettings.MinimumTimeInUniverse = TimeSpan.Zero;
             UniverseSettings.FillForward = false;
 
-            AddEquity("SPY", Resolution.Daily);
+            AddEquity("SPY", Resolution.Hour);
 
             var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
 
-            _contract = OptionChainProvider.GetOptionContractList(aapl, Time)
-                .OrderBy(symbol => symbol.ID.Symbol)
+            _contract = OptionChain(aapl)
+                .OrderBy(x => x.ID.StrikePrice)
                 .FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
                     && optionContract.ID.OptionStyle == OptionStyle.American);
             AddOptionContract(_contract);
@@ -56,7 +56,7 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 if (!_reAdded && slice.ContainsKey(_contract) && slice.ContainsKey(_contract.Underlying))
                 {
-                    throw new Exception("Getting data for removed option and underlying!");
+                    throw new RegressionTestException("Getting data for removed option and underlying!");
                 }
 
                 if (!Portfolio.Invested && _reAdded)
@@ -95,11 +95,11 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (!_hasRemoved)
             {
-                throw new Exception("We did not remove the option contract!");
+                throw new RegressionTestException("We did not remove the option contract!");
             }
             if (!_reAdded)
             {
-                throw new Exception("We did not re add the option contract!");
+                throw new RegressionTestException("We did not re add the option contract!");
             }
         }
 
@@ -111,31 +111,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 4677;
+        public long DataPoints => 3814;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 0;
+        public int AlgorithmHistoryDataPoints => 1;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
-            {"Average Loss", "-0.05%"},
-            {"Compounding Annual Return", "-4.548%"},
-            {"Drawdown", "0.100%"},
+            {"Average Loss", "-0.50%"},
+            {"Compounding Annual Return", "-39.406%"},
+            {"Drawdown", "0.700%"},
             {"Expectancy", "-1"},
-            {"Net Profit", "-0.051%"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99498"},
+            {"Net Profit", "-0.502%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
@@ -148,28 +156,10 @@ namespace QuantConnect.Algorithm.CSharp
             {"Tracking Error", "0.008"},
             {"Treynor Ratio", "0"},
             {"Total Fees", "$2.00"},
-            {"Estimated Strategy Capacity", "$30000.00"},
-            {"Lowest Capacity Asset", "AAPL VXBK4Q9ZIFD2|AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-89.181"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "546b6182e1df2d222178454d8f311566"}
+            {"Estimated Strategy Capacity", "$5000000.00"},
+            {"Lowest Capacity Asset", "AAPL VXBK4R62CXGM|AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "22.70%"},
+            {"OrderListHash", "29fd1b75f6db05dd823a6db7e8bd90a9"}
         };
     }
 }

Algorithm.CSharp/AddOptionWithOnMarketOpenOnlyFilterRegressionAlgorithm.cs

@@ -0,0 +1,126 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Algorithm asserting that using OnlyApplyFilterAtMarketOpen along with other dynamic filters will make the filters be applied only on market
+    /// open, regardless of the order of configuration of the filters
+    /// </summary>
+    public class AddOptionWithOnMarketOpenOnlyFilterRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2014, 6, 5);
+            SetEndDate(2014, 6, 10);
+
+            // OnlyApplyFilterAtMarketOpen as first filter
+            AddOption("AAPL", Resolution.Minute).SetFilter(u =>
+                u.OnlyApplyFilterAtMarketOpen()
+                 .Strikes(-5, 5)
+                 .Expiration(0, 100)
+                 .IncludeWeeklys());
+
+            // OnlyApplyFilterAtMarketOpen as last filter
+            AddOption("TWX", Resolution.Minute).SetFilter(u =>
+                u.Strikes(-5, 5)
+                 .Expiration(0, 100)
+                 .IncludeWeeklys()
+                 .OnlyApplyFilterAtMarketOpen());
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            // This will be the first call, the underlying securities are added.
+            if (changes.AddedSecurities.All(s => s.Type != SecurityType.Option))
+            {
+                return;
+            }
+
+            var changeOptions = changes.AddedSecurities.Concat(changes.RemovedSecurities)
+                                                                        .Where(s => s.Type == SecurityType.Option);
+
+            if (Time != Time.Date)
+            {
+                throw new RegressionTestException($"Expected options filter to be run only at midnight. Actual was {Time}");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all time slices of algorithm
+        /// </summary>
+        public long DataPoints => 470217;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-10.144"},
+            {"Tracking Error", "0.033"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/AddRemoveOptionUniverseRegressionAlgorithm.cs

@@ -29,20 +29,21 @@ namespace QuantConnect.Algorithm.CSharp
     public class AddRemoveOptionUniverseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
         private const string UnderlyingTicker = "GOOG";
-        public readonly Symbol Underlying = QuantConnect.Symbol.Create(UnderlyingTicker, SecurityType.Equity, Market.USA);
-        public readonly Symbol OptionChainSymbol = QuantConnect.Symbol.Create(UnderlyingTicker, SecurityType.Option, Market.USA);
+        private readonly Symbol Underlying = QuantConnect.Symbol.Create(UnderlyingTicker, SecurityType.Equity, Market.USA);
+        private readonly Symbol OptionChainSymbol = QuantConnect.Symbol.Create(UnderlyingTicker, SecurityType.Option, Market.USA);
         private readonly HashSet<Symbol> _expectedSecurities = new HashSet<Symbol>();
         private readonly HashSet<Symbol> _expectedData = new HashSet<Symbol>();
         private readonly HashSet<Symbol> _expectedUniverses = new HashSet<Symbol>();
         private bool _expectUniverseSubscription;
+        private DateTime _universeSubscriptionTime;
 
         // order of expected contract additions as price moves
         private int _expectedContractIndex;
         private readonly List<Symbol> _expectedContracts = new List<Symbol>
         {
-            SymbolRepresentation.ParseOptionTickerOSI("GOOG  151224P00747500"),
             SymbolRepresentation.ParseOptionTickerOSI("GOOG  151224P00750000"),
-            SymbolRepresentation.ParseOptionTickerOSI("GOOG  151224P00752500")
+            SymbolRepresentation.ParseOptionTickerOSI("GOOG  151224P00752500"),
+            SymbolRepresentation.ParseOptionTickerOSI("GOOG  151224P00755000")
         };
 
         public override void Initialize()
@@ -59,16 +60,16 @@ namespace QuantConnect.Algorithm.CSharp
             _expectedUniverses.Add(UserDefinedUniverse.CreateSymbol(SecurityType.Equity, Market.USA));
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             // verify expectations
             if (SubscriptionManager.Subscriptions.Count(x => x.Symbol == OptionChainSymbol)
                 != (_expectUniverseSubscription ? 1 : 0))
             {
                 Log($"SubscriptionManager.Subscriptions:  {string.Join(" -- ", SubscriptionManager.Subscriptions)}");
-                throw new Exception($"Unexpected {OptionChainSymbol} subscription presence");
+                throw new RegressionTestException($"Unexpected {OptionChainSymbol} subscription presence");
             }
-            if (!data.ContainsKey(Underlying))
+            if (Time != _universeSubscriptionTime && !slice.ContainsKey(Underlying))
             {
                 // TODO : In fact, we're unable to properly detect whether or not we auto-added or it was manually added
                 // this is because when we auto-add the underlying we don't mark it as an internal security like we do with other auto adds
@@ -77,46 +78,46 @@ namespace QuantConnect.Algorithm.CSharp
                 // of the internal flag's purpose, so kicking this issue for now with a big fat note here about it :) to be considerd for any future
                 // refactorings of how we manage subscription/security data and track various aspects about the security (thinking a flags enum with
                 // things like manually added, auto added, internal, and any other boolean state we need to track against a single security)
-                throw new Exception("The underlying equity data should NEVER be removed in this algorithm because it was manually added");
+                throw new RegressionTestException("The underlying equity data should NEVER be removed in this algorithm because it was manually added");
             }
-            if (_expectedSecurities.AreDifferent(Securities.Keys.ToHashSet()))
+            if (_expectedSecurities.AreDifferent(Securities.Total.Select(x => x.Symbol).ToHashSet()))
             {
                 var expected = string.Join(Environment.NewLine, _expectedSecurities.OrderBy(s => s.ToString()));
                 var actual = string.Join(Environment.NewLine, Securities.Keys.OrderBy(s => s.ToString()));
-                throw new Exception($"{Time}:: Detected differences in expected and actual securities{Environment.NewLine}Expected:{Environment.NewLine}{expected}{Environment.NewLine}Actual:{Environment.NewLine}{actual}");
+                throw new RegressionTestException($"{Time}:: Detected differences in expected and actual securities{Environment.NewLine}Expected:{Environment.NewLine}{expected}{Environment.NewLine}Actual:{Environment.NewLine}{actual}");
             }
             if (_expectedUniverses.AreDifferent(UniverseManager.Keys.ToHashSet()))
             {
                 var expected = string.Join(Environment.NewLine, _expectedUniverses.OrderBy(s => s.ToString()));
                 var actual = string.Join(Environment.NewLine, UniverseManager.Keys.OrderBy(s => s.ToString()));
-                throw new Exception($"{Time}:: Detected differences in expected and actual universes{Environment.NewLine}Expected:{Environment.NewLine}{expected}{Environment.NewLine}Actual:{Environment.NewLine}{actual}");
+                throw new RegressionTestException($"{Time}:: Detected differences in expected and actual universes{Environment.NewLine}Expected:{Environment.NewLine}{expected}{Environment.NewLine}Actual:{Environment.NewLine}{actual}");
             }
-            if (_expectedData.AreDifferent(data.Keys.ToHashSet()))
+            if (Time != _universeSubscriptionTime && _expectedData.AreDifferent(slice.Keys.ToHashSet()))
             {
                 var expected = string.Join(Environment.NewLine, _expectedData.OrderBy(s => s.ToString()));
-                var actual = string.Join(Environment.NewLine, data.Keys.OrderBy(s => s.ToString()));
-                throw new Exception($"{Time}:: Detected differences in expected and actual slice data keys{Environment.NewLine}Expected:{Environment.NewLine}{expected}{Environment.NewLine}Actual:{Environment.NewLine}{actual}");
+                var actual = string.Join(Environment.NewLine, slice.Keys.OrderBy(s => s.ToString()));
+                throw new RegressionTestException($"{Time}:: Detected differences in expected and actual slice data keys{Environment.NewLine}Expected:{Environment.NewLine}{expected}{Environment.NewLine}Actual:{Environment.NewLine}{actual}");
             }
 
             // 10AM add GOOG option chain
-            if (Time.TimeOfDay.Hours == 10 && Time.TimeOfDay.Minutes == 0)
+            if (Time.TimeOfDay.Hours == 10 && Time.TimeOfDay.Minutes == 0 && !_expectUniverseSubscription)
             {
                 if (Securities.ContainsKey(OptionChainSymbol))
                 {
-                    throw new Exception("The option chain security should not have been added yet");
+                    throw new RegressionTestException("The option chain security should not have been added yet");
                 }
 
                 var googOptionChain = AddOption(UnderlyingTicker);
                 googOptionChain.SetFilter(u =>
                 {
                     // we added the universe at 10, the universe selection data should not be from before
-                    if (u.Underlying.EndTime.Hour < 10)
+                    if (u.LocalTime.Hour < 10)
                     {
-                        throw new Exception($"Unexpected underlying data point {u.Underlying.EndTime} {u.Underlying}");
+                        throw new RegressionTestException($"Unexpected selection time {u.LocalTime}");
                     }
                     // find first put above market price
                     return u.IncludeWeeklys()
-                        .Strikes(+1, +1)
+                        .Strikes(+1, +3)
                         .Expiration(TimeSpan.Zero, TimeSpan.FromDays(1))
                         .Contracts(c => c.Where(s => s.ID.OptionRight == OptionRight.Put));
                 });
@@ -124,6 +125,7 @@ namespace QuantConnect.Algorithm.CSharp
                 _expectedSecurities.Add(OptionChainSymbol);
                 _expectedUniverses.Add(OptionChainSymbol);
                 _expectUniverseSubscription = true;
+                _universeSubscriptionTime = Time;
             }
 
             // 11:30AM remove GOOG option chain
@@ -141,16 +143,6 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void OnSecuritiesChanged(SecurityChanges changes)
         {
-            if (changes.AddedSecurities.Count > 1)
-            {
-                // added event fired for underlying since it was added to the option chain universe
-                if (changes.AddedSecurities.All(s => s.Symbol != Underlying))
-                {
-                    var securities = string.Join(Environment.NewLine, changes.AddedSecurities.Select(s => s.Symbol));
-                    throw new Exception($"This algorithm intends to add a single security at a time but added: {changes.AddedSecurities.Count}{Environment.NewLine}{securities}");
-                }
-            }
-
             if (changes.AddedSecurities.Any())
             {
                 foreach (var added in changes.AddedSecurities)
@@ -161,7 +153,7 @@ namespace QuantConnect.Algorithm.CSharp
                         var expectedContract = _expectedContracts[_expectedContractIndex];
                         if (added.Symbol != expectedContract)
                         {
-                            throw new Exception($"Expected option contract {expectedContract} to be added but received {added.Symbol}");
+                            throw new RegressionTestException($"Expected option contract {expectedContract.Value} to be added but received {added.Symbol}");
                         }
 
                         _expectedContractIndex++;
@@ -182,7 +174,7 @@ namespace QuantConnect.Algorithm.CSharp
                 // receive removed event next timestep at 11:31AM
                 if (Time.TimeOfDay.Hours != 11 || Time.TimeOfDay.Minutes != 31)
                 {
-                    throw new Exception($"Expected option contracts to be removed at 11:31AM, instead removed at: {Time}");
+                    throw new RegressionTestException($"Expected option contracts to be removed at 11:31AM, instead removed at: {Time}");
                 }
 
                 if (changes.RemovedSecurities
@@ -190,13 +182,13 @@ namespace QuantConnect.Algorithm.CSharp
                     .ToHashSet(s => s.Symbol)
                     .AreDifferent(_expectedContracts.ToHashSet()))
                 {
-                    throw new Exception("Expected removed securities to equal expected contracts added");
+                    throw new RegressionTestException("Expected removed securities to equal expected contracts added");
                 }
             }
 
             if (Securities.ContainsKey(Underlying))
             {
-                Console.WriteLine($"{Time:o}:: PRICE:: {Securities[Underlying].Price} CHANGES:: {changes}");
+                Log($"{Time:o}:: PRICE:: {Securities[Underlying].Price} CHANGES:: {changes}");
             }
         }
 
@@ -208,31 +200,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 200618;
+        public long DataPoints => 3502;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "6"},
+            {"Total Orders", "6"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "98784"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -245,28 +245,10 @@ namespace QuantConnect.Algorithm.CSharp
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
             {"Total Fees", "$6.00"},
-            {"Estimated Strategy Capacity", "$2000.00"},
-            {"Lowest Capacity Asset", "GOOCV 305RBR0BSWIX2|GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "550a99c482106defd8ba15f48183768e"}
+            {"Estimated Strategy Capacity", "$4000.00"},
+            {"Lowest Capacity Asset", "GOOCV 305RBQ2BZBZT2|GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "2.58%"},
+            {"OrderListHash", "09f766c470a8bcf4bb6862da52bf25a7"}
         };
     }
 }

Algorithm.CSharp/AddRemoveSecurityCacheRegressionAlgorithm.cs

@@ -41,8 +41,8 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -61,7 +61,7 @@ namespace QuantConnect.Algorithm.CSharp
 
                 if (ticket.Status != OrderStatus.Invalid)
                 {
-                    throw new Exception("Expected order to always be invalid because there is no data yet!");
+                    throw new RegressionTestException("Expected order to always be invalid because there is no data yet!");
                 }
             }
             else
@@ -78,7 +78,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -90,53 +90,43 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "19"},
+            {"Total Orders", "19"},
             {"Average Win", "0%"},
             {"Average Loss", "0.00%"},
             {"Compounding Annual Return", "271.720%"},
             {"Drawdown", "2.500%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101753.84"},
             {"Net Profit", "1.754%"},
-            {"Sharpe Ratio", "11.994"},
+            {"Sharpe Ratio", "11.954"},
+            {"Sortino Ratio", "29.606"},
             {"Probabilistic Sharpe Ratio", "74.160%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.618"},
+            {"Alpha", "0.616"},
             {"Beta", "0.81"},
             {"Annual Standard Deviation", "0.185"},
             {"Annual Variance", "0.034"},
             {"Information Ratio", "3.961"},
             {"Tracking Error", "0.061"},
-            {"Treynor Ratio", "2.746"},
+            {"Treynor Ratio", "2.737"},
             {"Total Fees", "$21.45"},
             {"Estimated Strategy Capacity", "$830000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.204"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "43.135"},
-            {"Return Over Maximum Drawdown", "261.238"},
-            {"Portfolio Turnover", "0.204"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "6ee62edf1ac883882b0fcef8cb3e9bae"}
+            {"Portfolio Turnover", "20.49%"},
+            {"OrderListHash", "6ebe462373e2ecc22de8eb2fe114d704"}
         };
     }
 }

Algorithm.CSharp/AddRemoveSecurityRegressionAlgorithm.cs

@@ -18,6 +18,7 @@ using System.Collections.Generic;
 using QuantConnect.Data.Market;
 using QuantConnect.Orders;
 using QuantConnect.Interfaces;
+using QuantConnect.Data;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -51,7 +52,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public void OnData(TradeBars data)
+        public override void OnData(Slice slice)
         {
             if (lastAction.Date == Time.Date) return;
 
@@ -104,7 +105,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -116,53 +117,43 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "5"},
+            {"Total Orders", "5"},
             {"Average Win", "0.46%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "296.356%"},
             {"Drawdown", "1.400%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101776.32"},
             {"Net Profit", "1.776%"},
-            {"Sharpe Ratio", "13.013"},
+            {"Sharpe Ratio", "12.966"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "80.409%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.68"},
+            {"Alpha", "0.678"},
             {"Beta", "0.707"},
             {"Annual Standard Deviation", "0.16"},
             {"Annual Variance", "0.026"},
             {"Information Ratio", "1.378"},
             {"Tracking Error", "0.072"},
-            {"Treynor Ratio", "2.946"},
+            {"Treynor Ratio", "2.935"},
             {"Total Fees", "$28.30"},
             {"Estimated Strategy Capacity", "$4700000.00"},
             {"Lowest Capacity Asset", "AIG R735QTJ8XC9X"},
-            {"Fitness Score", "0.374"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "372.086"},
-            {"Portfolio Turnover", "0.374"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "ac3f4dfcdeb98b488b715412ad2d6c4f"}
+            {"Portfolio Turnover", "29.88%"},
+            {"OrderListHash", "6061ecfbb89eb365dff913410d279b7c"}
         };
     }
 }

Algorithm.CSharp/AddRiskManagementAlgorithm.cs

@@ -57,7 +57,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -69,53 +69,43 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "3"},
+            {"Total Orders", "3"},
             {"Average Win", "1.02%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "296.066%"},
             {"Drawdown", "2.200%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101775.37"},
             {"Net Profit", "1.775%"},
-            {"Sharpe Ratio", "9.373"},
+            {"Sharpe Ratio", "9.34"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "68.302%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.105"},
+            {"Alpha", "0.106"},
             {"Beta", "1.021"},
             {"Annual Standard Deviation", "0.227"},
             {"Annual Variance", "0.052"},
             {"Information Ratio", "25.083"},
             {"Tracking Error", "0.006"},
-            {"Treynor Ratio", "2.086"},
+            {"Treynor Ratio", "2.079"},
             {"Total Fees", "$10.33"},
             {"Estimated Strategy Capacity", "$38000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.747"},
-            {"Kelly Criterion Estimate", "38.796"},
-            {"Kelly Criterion Probability Value", "0.228"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "107.013"},
-            {"Portfolio Turnover", "0.747"},
-            {"Total Insights Generated", "100"},
-            {"Total Insights Closed", "99"},
-            {"Total Insights Analysis Completed", "99"},
-            {"Long Insight Count", "100"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$135639.1761"},
-            {"Total Accumulated Estimated Alpha Value", "$21852.9784"},
-            {"Mean Population Estimated Insight Value", "$220.7372"},
-            {"Mean Population Direction", "53.5354%"},
-            {"Mean Population Magnitude", "53.5354%"},
-            {"Rolling Averaged Population Direction", "58.2788%"},
-            {"Rolling Averaged Population Magnitude", "58.2788%"},
-            {"OrderListHash", "af3a9c98c190d1b6b36fad184e796b0b"}
+            {"Portfolio Turnover", "59.74%"},
+            {"OrderListHash", "5d7657ec9954875eca633bed711085d3"}
         };
     }
 }

Algorithm.CSharp/AddTwoAndRemoveOneOptionContractRegressionAlgorithm.cs

@@ -41,8 +41,8 @@ namespace QuantConnect.Algorithm.CSharp
 
             var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
 
-            var contracts = OptionChainProvider.GetOptionContractList(aapl, Time)
-                .OrderBy(symbol => symbol.ID.Symbol)
+            var contracts = OptionChain(aapl)
+                .OrderBy(x => x.ID.StrikePrice)
                 .Where(optionContract => optionContract.ID.OptionRight == OptionRight.Call
                     && optionContract.ID.OptionStyle == OptionStyle.American)
                 .Take(2)
@@ -69,7 +69,7 @@ namespace QuantConnect.Algorithm.CSharp
                         SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs("AAPL");
                     if (subscriptions.Count == 0)
                     {
-                        throw new Exception("No configuration for underlying was found!");
+                        throw new RegressionTestException("No configuration for underlying was found!");
                     }
 
                     if (!Portfolio.Invested)
@@ -84,7 +84,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (!_hasRemoved)
             {
-                throw new Exception("Expect a single call to OnData where we removed the option and underlying");
+                throw new RegressionTestException("Expect a single call to OnData where we removed the option and underlying");
             }
         }
 
@@ -96,7 +96,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -106,21 +106,29 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 0;
+        public int AlgorithmHistoryDataPoints => 1;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99238"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -133,28 +141,10 @@ namespace QuantConnect.Algorithm.CSharp
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
             {"Total Fees", "$2.00"},
-            {"Estimated Strategy Capacity", "$230000.00"},
-            {"Lowest Capacity Asset", "AAPL VXBK4QQIRLZA|AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "228194dcc6fd8689a67f383577ee2d85"}
+            {"Estimated Strategy Capacity", "$6200000.00"},
+            {"Lowest Capacity Asset", "AAPL VXBK4QA5EM92|AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "90.27%"},
+            {"OrderListHash", "a111609c2c64554268539b5798e5b31f"}
         };
     }
 }

Algorithm.CSharp/AddUniverseSelectionModelAlgorithm.cs

@@ -57,14 +57,14 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (UniverseManager.Count != 3)
             {
-                throw new Exception("Unexpected universe count");
+                throw new RegressionTestException("Unexpected universe count");
             }
             if (UniverseManager.ActiveSecurities.Count != 3
                 || UniverseManager.ActiveSecurities.Keys.All(symbol => symbol.Value != "SPY")
                 || UniverseManager.ActiveSecurities.Keys.All(symbol => symbol.Value != "AAPL")
                 || UniverseManager.ActiveSecurities.Keys.All(symbol => symbol.Value != "FB"))
             {
-                throw new Exception("Unexpected active securities");
+                throw new RegressionTestException("Unexpected active securities");
             }
         }
 
@@ -76,65 +76,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 53;
+        public long DataPoints => 50;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "11"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-14.217%"},
-            {"Drawdown", "3.300%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-0.168%"},
-            {"Sharpe Ratio", "62.513"},
+            {"Total Orders", "6"},
+            {"Average Win", "0.01%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "1296.838%"},
+            {"Drawdown", "0.400%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "102684.23"},
+            {"Net Profit", "2.684%"},
+            {"Sharpe Ratio", "34.319"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "1.118"},
-            {"Beta", "1.19"},
-            {"Annual Standard Deviation", "0.213"},
-            {"Annual Variance", "0.046"},
-            {"Information Ratio", "70.862"},
-            {"Tracking Error", "0.043"},
-            {"Treynor Ratio", "11.209"},
-            {"Total Fees", "$23.21"},
-            {"Estimated Strategy Capacity", "$340000000.00"},
+            {"Alpha", "-5.738"},
+            {"Beta", "1.381"},
+            {"Annual Standard Deviation", "0.246"},
+            {"Annual Variance", "0.06"},
+            {"Information Ratio", "-26.937"},
+            {"Tracking Error", "0.068"},
+            {"Treynor Ratio", "6.106"},
+            {"Total Fees", "$18.61"},
+            {"Estimated Strategy Capacity", "$980000000.00"},
             {"Lowest Capacity Asset", "FB V6OIPNZEM8V9"},
-            {"Fitness Score", "0.147"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "1"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-4.352"},
-            {"Portfolio Turnover", "0.269"},
-            {"Total Insights Generated", "15"},
-            {"Total Insights Closed", "12"},
-            {"Total Insights Analysis Completed", "12"},
-            {"Long Insight Count", "15"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "a7a0983c8413ff241e7d223438f3d508"}
+            {"Portfolio Turnover", "25.56%"},
+            {"OrderListHash", "5ee20c8556d706ab0a63ae41b6579c62"}
         };
     }
 }

Algorithm.CSharp/AddUniverseSelectionModelCoarseAlgorithm.cs

@@ -68,14 +68,14 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (UniverseManager.Count != 3)
             {
-                throw new Exception("Unexpected universe count");
+                throw new RegressionTestException("Unexpected universe count");
             }
             if (UniverseManager.ActiveSecurities.Count != 3
                 || UniverseManager.ActiveSecurities.Keys.All(symbol => symbol.Value != "SPY")
                 || UniverseManager.ActiveSecurities.Keys.All(symbol => symbol.Value != "AAPL")
                 || UniverseManager.ActiveSecurities.Keys.All(symbol => symbol.Value != "FB"))
             {
-                throw new Exception("Unexpected active securities");
+                throw new RegressionTestException("Unexpected active securities");
             }
         }
 
@@ -87,65 +87,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 234018;
+        public long DataPoints => 234015;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "27"},
+            {"Total Orders", "21"},
             {"Average Win", "0.01%"},
             {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-75.320%"},
-            {"Drawdown", "5.800%"},
-            {"Expectancy", "-0.731"},
-            {"Net Profit", "-5.588%"},
-            {"Sharpe Ratio", "-3.252"},
-            {"Probabilistic Sharpe Ratio", "5.526%"},
-            {"Loss Rate", "86%"},
-            {"Win Rate", "14%"},
-            {"Profit-Loss Ratio", "0.89"},
-            {"Alpha", "-0.499"},
-            {"Beta", "1.483"},
-            {"Annual Standard Deviation", "0.196"},
-            {"Annual Variance", "0.039"},
-            {"Information Ratio", "-3.844"},
-            {"Tracking Error", "0.142"},
-            {"Treynor Ratio", "-0.43"},
-            {"Total Fees", "$37.25"},
-            {"Estimated Strategy Capacity", "$520000000.00"},
+            {"Compounding Annual Return", "-77.566%"},
+            {"Drawdown", "6.000%"},
+            {"Expectancy", "-0.811"},
+            {"Start Equity", "100000"},
+            {"End Equity", "94042.73"},
+            {"Net Profit", "-5.957%"},
+            {"Sharpe Ratio", "-3.345"},
+            {"Sortino Ratio", "-3.766"},
+            {"Probabilistic Sharpe Ratio", "4.557%"},
+            {"Loss Rate", "89%"},
+            {"Win Rate", "11%"},
+            {"Profit-Loss Ratio", "0.70"},
+            {"Alpha", "-0.519"},
+            {"Beta", "1.491"},
+            {"Annual Standard Deviation", "0.2"},
+            {"Annual Variance", "0.04"},
+            {"Information Ratio", "-3.878"},
+            {"Tracking Error", "0.147"},
+            {"Treynor Ratio", "-0.449"},
+            {"Total Fees", "$29.11"},
+            {"Estimated Strategy Capacity", "$680000000.00"},
             {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0.004"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "1"},
-            {"Sortino Ratio", "-4.469"},
-            {"Return Over Maximum Drawdown", "-13.057"},
-            {"Portfolio Turnover", "0.084"},
-            {"Total Insights Generated", "33"},
-            {"Total Insights Closed", "30"},
-            {"Total Insights Analysis Completed", "30"},
-            {"Long Insight Count", "33"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "f837879b96f5e565b60fd040299d2123"}
+            {"Portfolio Turnover", "7.48%"},
+            {"OrderListHash", "2c814c55e7d7c56482411c065b861b33"}
         };
     }
 }

Algorithm.CSharp/AdjustedVolumeRegressionAlgorithm.cs

@@ -63,21 +63,21 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
                 SetHoldings(_aapl, 1);
             }
 
-            if (data.Splits.ContainsKey(_aapl))
+            if (slice.Splits.ContainsKey(_aapl))
             {
-                Log(data.Splits[_aapl].ToString());
+                Log(slice.Splits[_aapl].ToString());
             }
 
-            if (data.Bars.ContainsKey(_aapl))
+            if (slice.Bars.ContainsKey(_aapl))
             {
-                var aaplData = data.Bars[_aapl];
+                var aaplData = slice.Bars[_aapl];
 
                 // Assert our volume matches what we expect
                 if (_expectedAdjustedVolume.MoveNext() && _expectedAdjustedVolume.Current != aaplData.Volume)
@@ -99,9 +99,9 @@ namespace QuantConnect.Algorithm.CSharp
                 }
             }
 
-            if (data.QuoteBars.ContainsKey(_aapl))
+            if (slice.QuoteBars.ContainsKey(_aapl))
             {
-                var aaplQuoteData = data.QuoteBars[_aapl];
+                var aaplQuoteData = slice.QuoteBars[_aapl];
 
                 // Assert our askSize matches what we expect
                 if (_expectedAdjustedAskSize.MoveNext() && _expectedAdjustedAskSize.Current != aaplQuoteData.LastAskSize)
@@ -151,7 +151,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -163,19 +163,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100146.57"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -190,26 +198,8 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$21.60"},
             {"Estimated Strategy Capacity", "$42000000.00"},
             {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "18e41dded4f8cee548ee02b03ffb0814"}
+            {"Portfolio Turnover", "99.56%"},
+            {"OrderListHash", "60f03c8c589a4f814dc4e8945df23207"}
         };
     }
 }

Algorithm.CSharp/AlgorithmModeAndDeploymentTargetAlgorithm.cs

@@ -0,0 +1,119 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using System.Collections.Generic;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Algorithm asserting the correct values for the deployment target and algorithm mode.
+    /// </summary>
+    public class AlgorithmModeAndDeploymentTargetAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 07);
+            SetEndDate(2013, 10, 07);
+            SetCash(100000);
+
+            Debug($"Algorithm Mode: {AlgorithmMode}. Is Live Mode: {LiveMode}. Deployment Target: {DeploymentTarget}.");
+
+            if (AlgorithmMode != AlgorithmMode.Backtesting)
+            {
+                throw new RegressionTestException($"Algorithm mode is not backtesting. Actual: {AlgorithmMode}");
+            }
+
+            if (LiveMode)
+            {
+                throw new RegressionTestException("Algorithm should not be live");
+            }
+
+            if (DeploymentTarget != DeploymentTarget.LocalPlatform)
+            {
+                throw new RegressionTestException($"Algorithm deployment target is not local. Actual{DeploymentTarget}");
+            }
+
+            // For a live deployment these checks should pass:
+            //if (AlgorithmMode != AlgorithmMode.Live) throw new RegressionTestException("Algorithm mode is not live");
+            //if (!LiveMode) throw new RegressionTestException("Algorithm should be live");
+
+            // For a cloud deployment these checks should pass:
+            //if (DeploymentTarget != DeploymentTarget.CloudPlatform) throw new RegressionTestException("Algorithm deployment target is not cloud");
+
+            Quit();
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 0;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/AllShortableSymbolsCoarseSelectionRegressionAlgorithm.cs

@@ -17,10 +17,12 @@ using System;
 using System.Collections.Generic;
 using System.Linq;
 using QuantConnect.Brokerages;
+using QuantConnect.Securities;
 using QuantConnect.Data;
 using QuantConnect.Data.Shortable;
 using QuantConnect.Data.UniverseSelection;
 using QuantConnect.Interfaces;
+using System.IO;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -82,11 +84,15 @@ namespace QuantConnect.Algorithm.CSharp
             { _20140329, new Symbol[0] }
         };
 
+        private Security _security;
+
         public override void Initialize()
         {
             SetStartDate(2014, 3, 25);
             SetEndDate(2014, 3, 29);
             SetCash(10000000);
+            _security = AddEquity(_spy);
+            _security.SetShortableProvider(new RegressionTestShortableProvider());
 
             AddUniverse(CoarseSelection);
             UniverseSettings.Resolution = Resolution.Daily;
@@ -94,33 +100,31 @@ namespace QuantConnect.Algorithm.CSharp
             SetBrokerageModel(new AllShortableSymbolsRegressionAlgorithmBrokerageModel());
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (Time.Date == _lastTradeDate)
             {
                 return;
             }
 
-            foreach (var symbol in ActiveSecurities.Keys.OrderBy(symbol => symbol))
+            foreach (var (symbol, security) in ActiveSecurities.Where(kvp => !kvp.Value.Invested).OrderBy(kvp => kvp.Key))
             {
-                if (!Portfolio.ContainsKey(symbol) || !Portfolio[symbol].Invested)
+                var shortableQuantity = security.ShortableProvider.ShortableQuantity(symbol, Time);
+                if (shortableQuantity == null)
                 {
-                    if (!Shortable(symbol))
-                    {
-                        throw new Exception($"Expected {symbol} to be shortable on {Time:yyyy-MM-dd}");
-                    }
-
-                    // Buy at least once into all Symbols. Since daily data will always use
-                    // MOO orders, it makes the testing of liquidating buying into Symbols difficult.
-                    MarketOrder(symbol, -(decimal)ShortableQuantity(symbol));
-                    _lastTradeDate = Time.Date;
+                    throw new RegressionTestException($"Expected {symbol} to be shortable on {Time:yyyy-MM-dd}");
                 }
+
+                // Buy at least once into all Symbols. Since daily data will always use
+                // MOO orders, it makes the testing of liquidating buying into Symbols difficult.
+                MarketOrder(symbol, -(decimal)shortableQuantity);
+                _lastTradeDate = Time.Date;
             }
         }
 
         private IEnumerable<Symbol> CoarseSelection(IEnumerable<CoarseFundamental> coarse)
         {
-            var shortableSymbols = AllShortableSymbols();
+            var shortableSymbols = (_security.ShortableProvider as dynamic).AllShortableSymbols(Time);
             var selectedSymbols = coarse
                 .Select(x => x.Symbol)
                 .Where(s => shortableSymbols.ContainsKey(s) && shortableSymbols[s] >= 500)
@@ -133,11 +137,11 @@ namespace QuantConnect.Algorithm.CSharp
                 var gme = QuantConnect.Symbol.Create("GME", SecurityType.Equity, Market.USA);
                 if (!shortableSymbols.ContainsKey(gme))
                 {
-                    throw new Exception("Expected unmapped GME in shortable symbols list on 2014-03-27");
+                    throw new RegressionTestException("Expected unmapped GME in shortable symbols list on 2014-03-27");
                 }
                 if (!coarse.Select(x => x.Symbol.Value).Contains("GME"))
                 {
-                    throw new Exception("Expected mapped GME in coarse symbols on 2014-03-27");
+                    throw new RegressionTestException("Expected mapped GME in coarse symbols on 2014-03-27");
                 }
 
                 expectedMissing = 1;
@@ -146,7 +150,7 @@ namespace QuantConnect.Algorithm.CSharp
             var missing = _expectedSymbols[Time.Date].Except(selectedSymbols).ToList();
             if (missing.Count != expectedMissing)
             {
-                throw new Exception($"Expected Symbols selected on {Time.Date:yyyy-MM-dd} to match expected Symbols, but the following Symbols were missing: {string.Join(", ", missing.Select(s => s.ToString()))}");
+                throw new RegressionTestException($"Expected Symbols selected on {Time.Date:yyyy-MM-dd} to match expected Symbols, but the following Symbols were missing: {string.Join(", ", missing.Select(s => s.ToString()))}");
             }
 
             _coarseSelected[Time.Date] = true;
@@ -165,15 +169,60 @@ namespace QuantConnect.Algorithm.CSharp
         {
             public AllShortableSymbolsRegressionAlgorithmBrokerageModel() : base()
             {
-                ShortableProvider = new RegressionTestShortableProvider();
+            }
+            public override IShortableProvider GetShortableProvider(Security security)
+            {
+                return new RegressionTestShortableProvider();
             }
         }
 
         private class RegressionTestShortableProvider : LocalDiskShortableProvider
         {
-            public RegressionTestShortableProvider() : base(SecurityType.Equity, "testbrokerage", Market.USA)
+            public RegressionTestShortableProvider() : base("testbrokerage")
             {
             }
+
+            /// <summary>
+            /// Gets a list of all shortable Symbols, including the quantity shortable as a Dictionary.
+            /// </summary>
+            /// <param name="localTime">The algorithm's local time</param>
+            /// <returns>Symbol/quantity shortable as a Dictionary. Returns null if no entry data exists for this date or brokerage</returns>
+            public Dictionary<Symbol, long> AllShortableSymbols(DateTime localTime)
+            {
+                var shortableDataDirectory = Path.Combine(Globals.DataFolder, SecurityType.Equity.SecurityTypeToLower(), Market.USA, "shortable", Brokerage);
+                var allSymbols = new Dictionary<Symbol, long>();
+
+                // Check backwards up to one week to see if we can source a previous file.
+                // If not, then we return a list of all Symbols with quantity set to zero.
+                var i = 0;
+                while (i <= 7)
+                {
+                    var shortableListFile = Path.Combine(shortableDataDirectory, "dates", $"{localTime.AddDays(-i):yyyyMMdd}.csv");
+
+                    foreach (var line in DataProvider.ReadLines(shortableListFile))
+                    {
+                        var csv = line.Split(',');
+                        var ticker = csv[0];
+
+                        var symbol = new Symbol(
+                                SecurityIdentifier.GenerateEquity(ticker, QuantConnect.Market.USA,
+                                    mappingResolveDate: localTime), ticker);
+                        var quantity = Parse.Long(csv[1]);
+
+                        allSymbols[symbol] = quantity;
+                    }
+
+                    if (allSymbols.Count > 0)
+                    {
+                        return allSymbols;
+                    }
+
+                    i++;
+                }
+
+                // Return our empty dictionary if we did not find a file to extract
+                return allSymbols;
+            }
         }
 
         /// <summary>
@@ -184,65 +233,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 35410;
+        public long DataPoints => 36573;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "5"},
+            {"Total Orders", "8"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "19.147%"},
-            {"Drawdown", "0%"},
+            {"Compounding Annual Return", "11.027%"},
+            {"Drawdown", "0.000%"},
             {"Expectancy", "0"},
-            {"Net Profit", "0.192%"},
-            {"Sharpe Ratio", "231.673"},
+            {"Start Equity", "10000000"},
+            {"End Equity", "10011469.88"},
+            {"Net Profit", "0.115%"},
+            {"Sharpe Ratio", "11.963"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.163"},
-            {"Beta", "-0.007"},
-            {"Annual Standard Deviation", "0.001"},
+            {"Alpha", "0.07"},
+            {"Beta", "-0.077"},
+            {"Annual Standard Deviation", "0.008"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "4.804"},
-            {"Tracking Error", "0.098"},
-            {"Treynor Ratio", "-22.526"},
-            {"Total Fees", "$307.50"},
-            {"Estimated Strategy Capacity", "$2600000.00"},
-            {"Lowest Capacity Asset", "GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0.106"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0.106"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "0069f402ffcd2d91b9018b81badfab81"}
+            {"Information Ratio", "3.876"},
+            {"Tracking Error", "0.105"},
+            {"Treynor Ratio", "-1.215"},
+            {"Total Fees", "$282.50"},
+            {"Estimated Strategy Capacity", "$61000000000.00"},
+            {"Lowest Capacity Asset", "NB R735QTJ8XC9X"},
+            {"Portfolio Turnover", "3.62%"},
+            {"OrderListHash", "0ea806c53bfa2bdca2504ba7155ef130"}
         };
     }
 }

Algorithm.CSharp/AlphaStreamsBasicTemplateAlgorithm.cs

@@ -1,127 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using QuantConnect.Orders;
-using QuantConnect.Interfaces;
-using QuantConnect.Securities;
-using System.Collections.Generic;
-using QuantConnect.Data.Custom.AlphaStreams;
-using QuantConnect.Algorithm.Framework.Alphas;
-using QuantConnect.Algorithm.Framework.Execution;
-using QuantConnect.Algorithm.Framework.Portfolio;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Example algorithm consuming an alpha streams portfolio state and trading based on it
-    /// </summary>
-    public class AlphaStreamsBasicTemplateAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        /// <summary>
-        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
-        /// </summary>
-        public override void Initialize()
-        {
-            SetStartDate(2018, 04, 04);
-            SetEndDate(2018, 04, 06);
-
-            SetAlpha(new AlphaStreamAlphaModule());
-            SetExecution(new ImmediateExecutionModel());
-            Settings.MinimumOrderMarginPortfolioPercentage = 0.01m;
-            SetPortfolioConstruction(new EqualWeightingAlphaStreamsPortfolioConstructionModel());
-            SetSecurityInitializer(new BrokerageModelSecurityInitializer(BrokerageModel,
-                new FuncSecuritySeeder(GetLastKnownPrices)));
-
-            foreach (var alphaId in new [] { "623b06b231eb1cc1aa3643a46", "9fc8ef73792331b11dbd5429a" })
-            {
-                AddData<AlphaStreamsPortfolioState>(alphaId);
-            }
-        }
-
-        public override void OnOrderEvent(OrderEvent orderEvent)
-        {
-            Log($"OnOrderEvent: {orderEvent}");
-        }
-
-        /// <summary>
-        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
-        /// </summary>
-        public bool CanRunLocally { get; } = true;
-
-        /// <summary>
-        /// This is used by the regression test system to indicate which languages this algorithm is written in.
-        /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
-
-        /// <summary>
-        /// Data Points count of all timeslices of algorithm
-        /// </summary>
-        public virtual long DataPoints => 890;
-
-        /// <summary>
-        /// Data Points count of the algorithm history
-        /// </summary>
-        public virtual int AlgorithmHistoryDataPoints => 12;
-
-        /// <summary>
-        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
-        /// </summary>
-        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
-        {
-            {"Total Trades", "2"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-0.12%"},
-            {"Compounding Annual Return", "-14.722%"},
-            {"Drawdown", "0.200%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-0.116%"},
-            {"Sharpe Ratio", "0"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0"},
-            {"Beta", "0"},
-            {"Annual Standard Deviation", "0"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "2.474"},
-            {"Tracking Error", "0.339"},
-            {"Treynor Ratio", "0"},
-            {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$83000.00"},
-            {"Lowest Capacity Asset", "BTCUSD XJ"},
-            {"Fitness Score", "0.017"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-138.588"},
-            {"Portfolio Turnover", "0.034"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "2b94bc50a74caebe06c075cdab1bc6da"}
-        };
-    }
-}

Algorithm.CSharp/AlphaStreamsDifferentAccountCurrencyBasicTemplateAlgorithm.cs

@@ -1,103 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System.Collections.Generic;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Example algorithm with existing holdings consuming an alpha streams portfolio state and trading based on it
-    /// </summary>
-    public class AlphaStreamsDifferentAccountCurrencyBasicTemplateAlgorithm : AlphaStreamsWithHoldingsBasicTemplateAlgorithm
-    {
-        /// <summary>
-        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
-        /// </summary>
-        public override void Initialize()
-        {
-            SetAccountCurrency("EUR");
-            base.Initialize();
-        }
-
-        /// <summary>
-        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
-        /// </summary>
-        public bool CanRunLocally { get; } = true;
-
-        /// <summary>
-        /// This is used by the regression test system to indicate which languages this algorithm is written in.
-        /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
-
-        /// <summary>
-        /// Data Points count of all timeslices of algorithm
-        /// </summary>
-        public override long DataPoints => 6214;
-
-        /// <summary>
-        /// Data Points count of the algorithm history
-        /// </summary>
-        public override int AlgorithmHistoryDataPoints => 61;
-
-        /// <summary>
-        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
-        /// </summary>
-        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
-        {
-            {"Total Trades", "2"},
-            {"Average Win", "0.01%"},
-            {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "-78.502%"},
-            {"Drawdown", "3.100%"},
-            {"Expectancy", "7.797"},
-            {"Net Profit", "-1.134%"},
-            {"Sharpe Ratio", "-2.456"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "50%"},
-            {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "16.59"},
-            {"Alpha", "0.006"},
-            {"Beta", "1.011"},
-            {"Annual Standard Deviation", "0.343"},
-            {"Annual Variance", "0.117"},
-            {"Information Ratio", "-0.859"},
-            {"Tracking Error", "0.004"},
-            {"Treynor Ratio", "-0.832"},
-            {"Total Fees", "€2.89"},
-            {"Estimated Strategy Capacity", "€8900000000.00"},
-            {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0.506"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0.506"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "€0"},
-            {"Total Accumulated Estimated Alpha Value", "€0"},
-            {"Mean Population Estimated Insight Value", "€0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "a9dd0a0ab6070455479d1b9caaa4e69c"}
-        };
-    }
-}

Algorithm.CSharp/AlphaStreamsUniverseSelectionTemplateAlgorithm.cs

@@ -1,140 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System;
-using QuantConnect.Interfaces;
-using System.Collections.Generic;
-using QuantConnect.Data.UniverseSelection;
-using QuantConnect.Data.Custom.AlphaStreams;
-using QuantConnect.Algorithm.Framework.Alphas;
-using QuantConnect.Algorithm.Framework.Execution;
-using QuantConnect.Algorithm.Framework.Portfolio;
-using QuantConnect.Algorithm.Framework.Selection;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Example algorithm consuming an alpha streams portfolio state and trading based on it
-    /// </summary>
-    public class AlphaStreamsUniverseSelectionTemplateAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        /// <summary>
-        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
-        /// </summary>
-        public override void Initialize()
-        {
-            SetStartDate(2018, 04, 04);
-            SetEndDate(2018, 04, 06);
-
-            SetAlpha(new AlphaStreamAlphaModule());
-            SetExecution(new ImmediateExecutionModel());
-            Settings.MinimumOrderMarginPortfolioPercentage = 0.01m;
-            SetPortfolioConstruction(new EqualWeightingAlphaStreamsPortfolioConstructionModel());
-
-            SetUniverseSelection(new ScheduledUniverseSelectionModel(
-                DateRules.EveryDay(),
-                TimeRules.Midnight,
-                SelectAlphas,
-                new UniverseSettings(UniverseSettings)
-                {
-                    SubscriptionDataTypes = new List<Tuple<Type, TickType>>
-                        {new(typeof(AlphaStreamsPortfolioState), TickType.Trade)},
-                    FillForward = false,
-                }
-            ));
-        }
-
-        private IEnumerable<Symbol> SelectAlphas(DateTime dateTime)
-        {
-            Log($"SelectAlphas() {Time}");
-            foreach (var alphaId in new[] {"623b06b231eb1cc1aa3643a46", "9fc8ef73792331b11dbd5429a"})
-            {
-                var alphaSymbol = new Symbol(SecurityIdentifier.GenerateBase(typeof(AlphaStreamsPortfolioState), alphaId, Market.USA),
-                        alphaId);
-
-                yield return alphaSymbol;
-            }
-        }
-
-        /// <summary>
-        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
-        /// </summary>
-        public bool CanRunLocally { get; } = true;
-
-        /// <summary>
-        /// This is used by the regression test system to indicate which languages this algorithm is written in.
-        /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
-
-        /// <summary>
-        /// Data Points count of all timeslices of algorithm
-        /// </summary>
-        public long DataPoints => 893;
-
-        /// <summary>
-        /// Data Points count of the algorithm history
-        /// </summary>
-        public int AlgorithmHistoryDataPoints => 2;
-
-        /// <summary>
-        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
-        /// </summary>
-        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
-        {
-            {"Total Trades", "2"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-0.12%"},
-            {"Compounding Annual Return", "-13.200%"},
-            {"Drawdown", "0.200%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-0.116%"},
-            {"Sharpe Ratio", "0"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0"},
-            {"Beta", "0"},
-            {"Annual Standard Deviation", "0"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "2.474"},
-            {"Tracking Error", "0.339"},
-            {"Treynor Ratio", "0"},
-            {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$83000.00"},
-            {"Lowest Capacity Asset", "BTCUSD XJ"},
-            {"Fitness Score", "0.011"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-113.513"},
-            {"Portfolio Turnover", "0.023"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "2b94bc50a74caebe06c075cdab1bc6da"}
-        };
-    }
-}

Algorithm.CSharp/AlphaStreamsWithHoldingsBasicTemplateAlgorithm.cs

@@ -1,154 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System;
-using QuantConnect.Orders;
-using System.Collections.Generic;
-using QuantConnect.Data.Custom.AlphaStreams;
-using QuantConnect.Algorithm.Framework.Execution;
-using QuantConnect.Algorithm.Framework.Portfolio;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Example algorithm with existing holdings consuming an alpha streams portfolio state and trading based on it
-    /// </summary>
-    public class AlphaStreamsWithHoldingsBasicTemplateAlgorithm : AlphaStreamsBasicTemplateAlgorithm
-    {
-        private decimal _expectedSpyQuantity;
-        /// <summary>
-        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
-        /// </summary>
-        public override void Initialize()
-        {
-            SetStartDate(2018, 04, 04);
-            SetEndDate(2018, 04, 06);
-            SetCash(100000);
-
-            SetExecution(new ImmediateExecutionModel());
-            UniverseSettings.Resolution = Resolution.Hour;
-            Settings.MinimumOrderMarginPortfolioPercentage = 0.001m;
-            SetPortfolioConstruction(new EqualWeightingAlphaStreamsPortfolioConstructionModel());
-
-            // AAPL should be liquidated since it's not hold by the alpha
-            // This is handled by the PCM
-            var aapl = AddEquity("AAPL", Resolution.Hour);
-            aapl.Holdings.SetHoldings(40, 10);
-
-            // SPY will be bought following the alpha streams portfolio
-            // This is handled by the PCM + Execution Model
-            var spy = AddEquity("SPY", Resolution.Hour);
-            spy.Holdings.SetHoldings(246, -10);
-
-            AddData<AlphaStreamsPortfolioState>("94d820a93fff127fa46c15231d");
-        }
-
-        public override void OnOrderEvent(OrderEvent orderEvent)
-        {
-            if (_expectedSpyQuantity == 0 && orderEvent.Symbol == "SPY" && orderEvent.Status == OrderStatus.Filled)
-            {
-                var security = Securities["SPY"];
-                var priceInAccountCurrency = Portfolio.CashBook.ConvertToAccountCurrency(security.AskPrice, security.QuoteCurrency.Symbol);
-                _expectedSpyQuantity = (Portfolio.TotalPortfolioValue - Settings.FreePortfolioValue) / priceInAccountCurrency;
-                _expectedSpyQuantity = _expectedSpyQuantity.DiscretelyRoundBy(1, MidpointRounding.ToZero);
-            }
-
-            base.OnOrderEvent(orderEvent);
-        }
-
-        public override void OnEndOfAlgorithm()
-        {
-            if (Securities["AAPL"].HoldStock)
-            {
-                throw new Exception("We should no longer hold AAPL since the alpha does not");
-            }
-
-            // we allow some padding for small price differences
-            if (Math.Abs(Securities["SPY"].Holdings.Quantity - _expectedSpyQuantity) > _expectedSpyQuantity * 0.03m)
-            {
-                throw new Exception($"Unexpected SPY holdings. Expected {_expectedSpyQuantity} was {Securities["SPY"].Holdings.Quantity}");
-            }
-        }
-
-        /// <summary>
-        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
-        /// </summary>
-        public bool CanRunLocally { get; } = true;
-
-        /// <summary>
-        /// This is used by the regression test system to indicate which languages this algorithm is written in.
-        /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
-
-        /// <summary>
-        /// Data Points count of all timeslices of algorithm
-        /// </summary>
-        public override long DataPoints => 2313;
-
-        /// <summary>
-        /// Data Points count of the algorithm history
-        /// </summary>
-        public override int AlgorithmHistoryDataPoints => 1;
-
-        /// <summary>
-        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
-        /// </summary>
-        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
-        {
-            {"Total Trades", "2"},
-            {"Average Win", "0.01%"},
-            {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "-87.617%"},
-            {"Drawdown", "3.100%"},
-            {"Expectancy", "8.518"},
-            {"Net Profit", "-1.515%"},
-            {"Sharpe Ratio", "-2.45"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "50%"},
-            {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "18.04"},
-            {"Alpha", "0.008"},
-            {"Beta", "1.015"},
-            {"Annual Standard Deviation", "0.344"},
-            {"Annual Variance", "0.118"},
-            {"Information Ratio", "-0.856"},
-            {"Tracking Error", "0.005"},
-            {"Treynor Ratio", "-0.83"},
-            {"Total Fees", "$3.09"},
-            {"Estimated Strategy Capacity", "$8900000000.00"},
-            {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0.511"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "6113.173"},
-            {"Portfolio Turnover", "0.511"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "788eb2c74715a78476ba0db3b2654eb6"}
-        };
-    }
-}

Algorithm.CSharp/Alphas/GreenblattMagicFormulaAlpha.cs

@@ -195,11 +195,11 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
             private const int _numberOfSymbolsFine = 20;
             private const int _numberOfSymbolsInPortfolio = 10;
             private int _lastMonth = -1;
-            private Dictionary<Symbol, decimal> _dollarVolumeBySymbol;
+            private Dictionary<Symbol, double> _dollarVolumeBySymbol;
 
             public GreenBlattMagicFormulaUniverseSelectionModel() : base(true)
             {
-                _dollarVolumeBySymbol = new Dictionary<Symbol, decimal>();
+                _dollarVolumeBySymbol = new ();
             }
 
             /// <summary>
@@ -245,7 +245,7 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
                     where x.CompanyReference.CountryId == "USA"
                     where x.CompanyReference.PrimaryExchangeID == "NYS" || x.CompanyReference.PrimaryExchangeID == "NAS"
                     where (algorithm.Time - x.SecurityReference.IPODate).TotalDays > 180
-                    where x.EarningReports.BasicAverageShares.ThreeMonths * x.EarningReports.BasicEPS.TwelveMonths * x.ValuationRatios.PERatio > 5e8m
+                    where x.EarningReports.BasicAverageShares.ThreeMonths * x.EarningReports.BasicEPS.TwelveMonths * x.ValuationRatios.PERatio > 5e8
                     select x;
 
                 double count = filteredFine.Count();
@@ -287,4 +287,4 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
             }
         }
     }
-}
+}

Algorithm.CSharp/Alphas/RebalancingLeveragedETFAlpha.cs

@@ -80,7 +80,7 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -92,12 +92,17 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2465"},
+            {"Total Orders", "2465"},
             {"Average Win", "0.26%"},
             {"Average Loss", "-0.24%"},
             {"Compounding Annual Return", "7.848%"},

Algorithm.CSharp/AsynchronousUniverseRegressionAlgorithm.cs

@@ -1,10 +1,9 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
- *
  * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
  *
  * Unless required by applicable law or agreed to in writing, software
@@ -14,21 +13,21 @@
  * limitations under the License.
 */
 
-using System;
-using System.Globalization;
-
-namespace QuantConnect.ToolBox.CoinApiDataConverter
+namespace QuantConnect.Algorithm.CSharp
 {
     /// <summary>
-    /// Coin API Main entry point for ToolBox.
+    /// Example algorithm using the asynchronous universe selection functionality
     /// </summary>
-    public static class CoinApiDataConverterProgram
+    public class AsynchronousUniverseRegressionAlgorithm : FundamentalRegressionAlgorithm
     {
-        public static void CoinApiDataProgram(string date, string rawDataFolder, string destinationFolder, string market)
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
         {
-            var processingDate = DateTime.ParseExact(date, DateFormat.EightCharacter, CultureInfo.InvariantCulture);
-            var converter  = new CoinApiDataConverter(processingDate, rawDataFolder, destinationFolder, market);
-            converter.Run();
+            base.Initialize();
+
+            UniverseSettings.Asynchronous = true;
         }
     }
 }

Algorithm.CSharp/AutoRegressiveIntegratedMovingAverageRegressionAlgorithm.cs

@@ -37,7 +37,7 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2013, 1, 07);
             SetEndDate(2013, 12, 11);
 
-            EnableAutomaticIndicatorWarmUp = true;
+            Settings.AutomaticIndicatorWarmUp = true;
             AddEquity("SPY", Resolution.Daily);
             _arima = ARIMA("SPY", 1, 1, 1, 50);
             _ar = ARIMA("SPY", 1, 1, 0, 50);
@@ -71,7 +71,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -83,53 +83,43 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 100;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "52"},
+            {"Total Orders", "53"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "0.096%"},
+            {"Compounding Annual Return", "0.076%"},
             {"Drawdown", "0.100%"},
-            {"Expectancy", "3.321"},
-            {"Net Profit", "0.089%"},
-            {"Sharpe Ratio", "0.798"},
-            {"Probabilistic Sharpe Ratio", "40.893%"},
-            {"Loss Rate", "24%"},
-            {"Win Rate", "76%"},
-            {"Profit-Loss Ratio", "4.67"},
-            {"Alpha", "-0.001"},
+            {"Expectancy", "2.933"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100070.90"},
+            {"Net Profit", "0.071%"},
+            {"Sharpe Ratio", "-9.164"},
+            {"Sortino Ratio", "-9.852"},
+            {"Probabilistic Sharpe Ratio", "36.417%"},
+            {"Loss Rate", "27%"},
+            {"Win Rate", "73%"},
+            {"Profit-Loss Ratio", "4.41"},
+            {"Alpha", "-0.008"},
             {"Beta", "0.008"},
             {"Annual Standard Deviation", "0.001"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-1.961"},
             {"Tracking Error", "0.092"},
-            {"Treynor Ratio", "0.08"},
-            {"Total Fees", "$52.00"},
-            {"Estimated Strategy Capacity", "$32000000000.00"},
+            {"Treynor Ratio", "-0.911"},
+            {"Total Fees", "$53.00"},
+            {"Estimated Strategy Capacity", "$16000000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "1.266"},
-            {"Return Over Maximum Drawdown", "1.622"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "cf43585a8d1781f04b53a4f1ee3380cb"}
+            {"Portfolio Turnover", "0.02%"},
+            {"OrderListHash", "685c37df6e4c49b75792c133be189094"}
         };
     }
 }

Algorithm.CSharp/AutomaticIndicatorWarmupDataTypeRegressionAlgorithm.cs

@@ -33,7 +33,7 @@ namespace QuantConnect.Algorithm.CSharp
         public override void Initialize()
         {
             UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
-            EnableAutomaticIndicatorWarmUp = true;
+            Settings.AutomaticIndicatorWarmUp = true;
             SetStartDate(2013, 10, 08);
             SetEndDate(2013, 10, 10);
 
@@ -82,7 +82,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             if (!sma11.Current.Equals(sma1.Current))
             {
-                throw new Exception("Expected SMAs warmed up before and after adding the Future to the algorithm to have the same current value. " +
+                throw new RegressionTestException("Expected SMAs warmed up before and after adding the Future to the algorithm to have the same current value. " +
                                     "The result of 'WarmUpIndicator' shouldn't change if the symbol is or isn't subscribed");
             }
 
@@ -94,7 +94,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             if (!smaSpy.Current.Equals(sma.Current))
             {
-                throw new Exception("Expected SMAs warmed up before and after adding the Equity to the algorithm to have the same current value. " +
+                throw new RegressionTestException("Expected SMAs warmed up before and after adding the Equity to the algorithm to have the same current value. " +
                                     "The result of 'WarmUpIndicator' shouldn't change if the symbol is or isn't subscribed");
             }
         }
@@ -103,7 +103,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (indicator.IsReady != isReady)
             {
-                throw new Exception($"Expected indicator state, expected {isReady} but was {indicator.IsReady}");
+                throw new RegressionTestException($"Expected indicator state, expected {isReady} but was {indicator.IsReady}");
             }
         }
 
@@ -111,7 +111,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -141,7 +141,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -153,53 +153,43 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 84;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "733913.744%"},
             {"Drawdown", "15.900%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "106827.7"},
             {"Net Profit", "6.828%"},
-            {"Sharpe Ratio", "203744786353.302"},
+            {"Sharpe Ratio", "203744786353.299"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "456382350698.561"},
+            {"Alpha", "456382350698.622"},
             {"Beta", "9.229"},
             {"Annual Standard Deviation", "2.24"},
             {"Annual Variance", "5.017"},
             {"Information Ratio", "228504036840.953"},
             {"Tracking Error", "1.997"},
-            {"Treynor Ratio", "49450701625.718"},
+            {"Treynor Ratio", "49450701625.717"},
             {"Total Fees", "$23.65"},
             {"Estimated Strategy Capacity", "$200000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.518"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-7.708"},
-            {"Portfolio Turnover", "5.277"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "dd38e7b94027d20942a5aa9ac31a9a7f"}
+            {"Portfolio Turnover", "351.80%"},
+            {"OrderListHash", "dfd9a280d3c6470b305c03e0b72c234e"}
         };
     }
 }

Algorithm.CSharp/AutomaticIndicatorWarmupOptionIndicatorsMirrorContractsRegressionAlgorithm.cs

@@ -0,0 +1,126 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using QuantConnect.Indicators;
+using QuantConnect.Interfaces;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting the behavior of the AutomaticIndicatorWarmUp on option greeks
+    /// </summary>
+    public class AutomaticIndicatorWarmupOptionIndicatorsMirrorContractsRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2015, 12, 24);
+            SetEndDate(2015, 12, 24);
+
+            Settings.AutomaticIndicatorWarmUp = true;
+
+            var underlying = "GOOG";
+            var resolution = Resolution.Minute;
+
+            var expiration = new DateTime(2015, 12, 24);
+            var strike = 650m;
+
+            var equity = AddEquity(underlying, resolution).Symbol;
+            var option = QuantConnect.Symbol.CreateOption(underlying, Market.USA, OptionStyle.American, OptionRight.Put, strike, expiration);
+            AddOptionContract(option, resolution);
+            // add the call counter side of the mirrored pair
+            var mirrorOption = QuantConnect.Symbol.CreateOption(underlying, Market.USA, OptionStyle.American, OptionRight.Call, strike, expiration);
+            AddOptionContract(mirrorOption, resolution);
+
+            var impliedVolatility = IV(option, mirrorOption);
+            var delta = D(option, mirrorOption, optionModel: OptionPricingModelType.BinomialCoxRossRubinstein, ivModel: OptionPricingModelType.BlackScholes);
+            var gamma = G(option, mirrorOption, optionModel: OptionPricingModelType.ForwardTree, ivModel: OptionPricingModelType.BlackScholes);
+            var vega = V(option, mirrorOption, optionModel: OptionPricingModelType.ForwardTree, ivModel: OptionPricingModelType.BlackScholes);
+            var theta = T(option, mirrorOption, optionModel: OptionPricingModelType.ForwardTree, ivModel: OptionPricingModelType.BlackScholes);
+            var rho = R(option, mirrorOption, optionModel: OptionPricingModelType.ForwardTree, ivModel: OptionPricingModelType.BlackScholes);
+
+            if (impliedVolatility == 0m || delta == 0m || gamma == 0m || vega == 0m || theta == 0m || rho == 0m)
+            {
+                throw new RegressionTestException("Expected IV/greeks calculated");
+            }
+            if (!impliedVolatility.IsReady || !delta.IsReady || !gamma.IsReady || !vega.IsReady || !theta.IsReady || !rho.IsReady)
+            {
+                throw new RegressionTestException("Expected IV/greeks to be ready");
+            }
+
+            Quit($"Implied Volatility: {impliedVolatility}, Delta: {delta}, Gamma: {gamma}, Vega: {vega}, Theta: {theta}, Rho: {rho}");
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally => true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 0;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 21;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/AutomaticIndicatorWarmupRegressionAlgorithm.cs

@@ -34,14 +34,14 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2013, 10, 07);
             SetEndDate(2013, 10, 11);
 
-            EnableAutomaticIndicatorWarmUp = true;
+            Settings.AutomaticIndicatorWarmUp = true;
 
             // Test case 1
             _spy = AddEquity("SPY").Symbol;
             var sma = SMA(_spy, 10);
             if (!sma.IsReady)
             {
-                throw new Exception("Expected SMA to be warmed up");
+                throw new RegressionTestException("Expected SMA to be warmed up");
             }
 
             // Test case 2
@@ -50,20 +50,20 @@ namespace QuantConnect.Algorithm.CSharp
 
             if (indicator.IsReady)
             {
-                throw new Exception("Expected CustomIndicator Not to be warmed up");
+                throw new RegressionTestException("Expected CustomIndicator Not to be warmed up");
             }
             WarmUpIndicator(_spy, indicator);
             if (!indicator.IsReady)
             {
-                throw new Exception("Expected CustomIndicator to be warmed up");
+                throw new RegressionTestException("Expected CustomIndicator to be warmed up");
             }
         }
 
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -72,7 +72,7 @@ namespace QuantConnect.Algorithm.CSharp
                 // we expect 1 consolidator per indicator
                 if (subscription.Consolidators.Count != 2)
                 {
-                    throw new Exception($"Unexpected consolidator count for subscription: {subscription.Consolidators.Count}");
+                    throw new RegressionTestException($"Unexpected consolidator count for subscription: {subscription.Consolidators.Count}");
                 }
                 SetHoldings(_spy, 1);
             }
@@ -88,7 +88,7 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 if (_previous != null && input.EndTime == _previous.EndTime)
                 {
-                    throw new Exception($"Unexpected indicator double data point call: {_previous}");
+                    throw new RegressionTestException($"Unexpected indicator double data point call: {_previous}");
                 }
                 _previous = input;
                 return base.ComputeNextValue(window, input);
@@ -103,7 +103,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -115,19 +115,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 40;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "271.453%"},
             {"Drawdown", "2.200%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101691.92"},
             {"Net Profit", "1.692%"},
-            {"Sharpe Ratio", "8.888"},
+            {"Sharpe Ratio", "8.854"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "67.609%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -138,30 +146,12 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.049"},
             {"Information Ratio", "-14.565"},
             {"Tracking Error", "0.001"},
-            {"Treynor Ratio", "1.978"},
+            {"Treynor Ratio", "1.97"},
             {"Total Fees", "$3.44"},
             {"Estimated Strategy Capacity", "$56000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.248"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "93.728"},
-            {"Portfolio Turnover", "0.248"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9e4bfd2eb0b81ee5bc1b197a87ccedbe"}
+            {"Portfolio Turnover", "19.93%"},
+            {"OrderListHash", "3da9fa60bf95b9ed148b95e02e0cfc9e"}
         };
     }
 }

Algorithm.CSharp/AuxiliaryDataHandlersRegressionAlgorithm.cs

@@ -0,0 +1,168 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using QuantConnect.Interfaces;
+using QuantConnect.Data.Market;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Example algorithm using and asserting the behavior of auxiliary Data handlers
+    /// </summary>
+    public class AuxiliaryDataHandlersRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private bool _onSplits;
+        private bool _onDividends;
+        private bool _onDelistingsCalled;
+        private bool _onSymbolChangedEvents;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2007, 05, 16);
+            SetEndDate(2015, 1, 1);
+
+            UniverseSettings.Resolution = Resolution.Daily;
+
+            // will get delisted
+            AddEquity("AAA.1");
+
+            // get's remapped
+            AddEquity("SPWR");
+
+            // has a split & dividends
+            AddEquity("AAPL");
+        }
+
+        public override void OnDelistings(Delistings delistings)
+        {
+            if (!delistings.ContainsKey("AAA.1"))
+            {
+                throw new RegressionTestException("Unexpected OnDelistings call");
+            }
+            _onDelistingsCalled = true;
+        }
+
+        public override void OnSymbolChangedEvents(SymbolChangedEvents symbolsChanged)
+        {
+            if (!symbolsChanged.ContainsKey("SPWR"))
+            {
+                throw new RegressionTestException("Unexpected OnSymbolChangedEvents call");
+            }
+            _onSymbolChangedEvents = true;
+        }
+
+        public override void OnSplits(Splits splits)
+        {
+            if (!splits.ContainsKey("AAPL"))
+            {
+                throw new RegressionTestException("Unexpected OnSplits call");
+            }
+            _onSplits = true;
+        }
+
+        public override void OnDividends(Dividends dividends)
+        {
+            if (!dividends.ContainsKey("AAPL"))
+            {
+                throw new RegressionTestException("Unexpected OnDividends call");
+            }
+            _onDividends = true;
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_onDelistingsCalled)
+            {
+                throw new RegressionTestException("OnDelistings was not called!");
+            }
+            if (!_onSymbolChangedEvents)
+            {
+                throw new RegressionTestException("OnSymbolChangedEvents was not called!");
+            }
+            if (!_onSplits)
+            {
+                throw new RegressionTestException("OnSplits was not called!");
+            }
+            if (!_onDividends)
+            {
+                throw new RegressionTestException("OnDividends was not called!");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 126221;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-0.332"},
+            {"Tracking Error", "0.183"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/BacktestingBrokerageRegressionAlgorithm.cs

@@ -151,12 +151,12 @@ namespace QuantConnect.Algorithm.CSharp
                 case OrderStatus.PartiallyFilled:
                     if (order.LastFillTime == null)
                     {
-                        throw new Exception("LastFillTime should not be null");
+                        throw new RegressionTestException("LastFillTime should not be null");
                     }
 
                     if (order.Quantity / 2 != orderEvent.FillQuantity)
                     {
-                        throw new Exception("Order size should be half");
+                        throw new RegressionTestException("Order size should be half");
                     }
                     break;
 
@@ -164,7 +164,7 @@ namespace QuantConnect.Algorithm.CSharp
                 case OrderStatus.Filled:
                     if (order.SecurityType == SecurityType.Equity && order.CreatedTime == order.LastFillTime)
                     {
-                        throw new Exception("Order should not finish during the CreatedTime bar");
+                        throw new RegressionTestException("Order should not finish during the CreatedTime bar");
                     }
                     break;
 
@@ -182,12 +182,12 @@ namespace QuantConnect.Algorithm.CSharp
             // If the option price isn't the same as the strike price, its incorrect
             if (order.Price != _optionStrikePrice)
             {
-                throw new Exception("OptionExercise order price should be strike price!!");
+                throw new RegressionTestException("OptionExercise order price should be strike price!!");
             }
 
             if (orderEvent.Quantity != -1)
             {
-                throw new Exception("OrderEvent Quantity should be -1");
+                throw new RegressionTestException("OrderEvent Quantity should be -1");
             }
         }
 
@@ -198,14 +198,14 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (!Portfolio.ContainsKey(_optionBuy.Symbol) || !Portfolio.ContainsKey(_optionBuy.Symbol.Underlying) || !Portfolio.ContainsKey(_equityBuy.Symbol))
             {
-                throw new Exception("Portfolio does not contain the Symbols we purchased");
+                throw new RegressionTestException("Portfolio does not contain the Symbols we purchased");
             }
 
             //Check option holding, should not be invested since it expired, profit should be -400
             var optionHolding = Portfolio[_optionBuy.Symbol];
             if (optionHolding.Invested || optionHolding.Profit != -400)
             {
-                throw new Exception("Options holding does not match expected outcome");
+                throw new RegressionTestException("Options holding does not match expected outcome");
             }
 
             //Check the option underlying symbol since we should have bought it at exercise
@@ -213,7 +213,7 @@ namespace QuantConnect.Algorithm.CSharp
             var optionExerciseHolding = Portfolio[_optionBuy.Symbol.Underlying];
             if (!optionExerciseHolding.Invested || optionExerciseHolding.Quantity != 100 || optionExerciseHolding.AveragePrice != _optionBuy.Symbol.ID.StrikePrice)
             {
-                throw new Exception("Equity holding for exercised option does not match expected outcome");
+                throw new RegressionTestException("Equity holding for exercised option does not match expected outcome");
             }
 
             //Check equity holding, should be invested, profit should be
@@ -221,7 +221,7 @@ namespace QuantConnect.Algorithm.CSharp
             var equityHolding = Portfolio[_equityBuy.Symbol];
             if (!equityHolding.Invested || equityHolding.Quantity != 52 || equityHolding.AveragePrice != _equityBuy.AverageFillPrice)
             {
-                throw new Exception("Equity holding does not match expected outcome");
+                throw new RegressionTestException("Equity holding does not match expected outcome");
             }
         }
 
@@ -291,65 +291,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 1748811;
+        public long DataPoints => 27071;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "3"},
+            {"Total Orders", "3"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.40%"},
-            {"Compounding Annual Return", "-22.717%"},
+            {"Compounding Annual Return", "-21.378%"},
             {"Drawdown", "0.400%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99671.06"},
             {"Net Profit", "-0.329%"},
-            {"Sharpe Ratio", "-7.887"},
+            {"Sharpe Ratio", "-14.095"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "1.216%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.001"},
+            {"Alpha", "-0.01"},
             {"Beta", "0.097"},
             {"Annual Standard Deviation", "0.002"},
             {"Annual Variance", "0"},
             {"Information Ratio", "7.39"},
             {"Tracking Error", "0.015"},
-            {"Treynor Ratio", "-0.131"},
+            {"Treynor Ratio", "-0.234"},
             {"Total Fees", "$2.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0.212"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-73.334"},
-            {"Portfolio Turnover", "0.425"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "f67306bc706a2cf66288f1cadf6148ed"}
+            {"Portfolio Turnover", "17.02%"},
+            {"OrderListHash", "b1e5e72fb766ab894204bc4b1300912b"}
         };
     }
 }

Algorithm.CSharp/BaseFrameworkRegressionAlgorithm.cs

@@ -0,0 +1,100 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Algorithm.Framework.Alphas;
+using QuantConnect.Algorithm.Framework.Execution;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Algorithm.Framework.Risk;
+using QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Abstract regression framework algorithm for multiple framework regression tests
+    /// </summary>
+    public abstract class BaseFrameworkRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2014, 6, 1);
+            SetEndDate(2014, 6, 30);
+
+            UniverseSettings.Resolution = Resolution.Hour;
+            UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
+
+            var symbols = new[] { "AAPL", "AIG", "BAC", "SPY" }
+                .Select(ticker => QuantConnect.Symbol.Create(ticker, SecurityType.Equity, Market.USA))
+                .ToList();
+
+            // Manually add AAPL and AIG when the algorithm starts
+            SetUniverseSelection(new ManualUniverseSelectionModel(symbols.Take(2)));
+
+            // At midnight, add all securities every day except on the last data
+            // With this procedure, the Alpha Model will experience multiple universe changes
+            AddUniverseSelection(new ScheduledUniverseSelectionModel(
+                DateRules.EveryDay(), TimeRules.Midnight,
+                dt => dt < EndDate.AddDays(-1) ? symbols : Enumerable.Empty<Symbol>()));
+
+            SetAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(31), 0.025, null));
+            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
+            SetExecution(new ImmediateExecutionModel());
+            SetRiskManagement(new NullRiskManagementModel());
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            // The base implementation checks for active insights
+            var insightsCount = Insights.GetInsights(insight => insight.IsActive(UtcTime)).Count;
+            if (insightsCount != 0)
+            {
+                throw new RegressionTestException($"The number of active insights should be 0. Actual: {insightsCount}");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 765;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public abstract Dictionary<string, string> ExpectedStatistics { get; }
+    }
+}

Algorithm.CSharp/BasicPythonIntegrationTemplateAlgorithm.cs

@@ -49,7 +49,7 @@ namespace QuantConnect.Algorithm.CSharp
 
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// Slice object keyed by symbol containing the stock data
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -63,4 +63,4 @@ namespace QuantConnect.Algorithm.CSharp
             }
         }
     }
-}
+}

Algorithm.CSharp/BasicSetAccountCurrencyAlgorithm.cs

@@ -35,18 +35,22 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2018, 04, 04);  //Set Start Date
             SetEndDate(2018, 04, 04);    //Set End Date
             SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash);
+            SetAccountCurrency();
+            _btcEur = AddCrypto("BTCEUR").Symbol;
+        }
+
+        public virtual void SetAccountCurrency()
+        {
             //Before setting any cash or adding a Security call SetAccountCurrency
             SetAccountCurrency("EUR");
             SetCash(100000);             //Set Strategy Cash
-
-            _btcEur = AddCrypto("BTCEUR").Symbol;
         }
 
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -63,31 +67,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 4324;
+        public long DataPoints => 4319;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 120;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000.00"},
+            {"End Equity", "92395.59"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -101,27 +113,9 @@ namespace QuantConnect.Algorithm.CSharp
             {"Treynor Ratio", "0"},
             {"Total Fees", "€298.35"},
             {"Estimated Strategy Capacity", "€85000.00"},
-            {"Lowest Capacity Asset", "BTCEUR XJ"},
-            {"Fitness Score", "0.506"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-13.614"},
-            {"Portfolio Turnover", "1.073"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "€0"},
-            {"Total Accumulated Estimated Alpha Value", "€0"},
-            {"Mean Population Estimated Insight Value", "€0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "2ba443899dcccc79dc0f04441f797bf9"}
+            {"Lowest Capacity Asset", "BTCEUR 2XR"},
+            {"Portfolio Turnover", "107.64%"},
+            {"OrderListHash", "6819dc936b86af6e4b89b6017b7d5284"}
         };
     }
 }

Algorithm.CSharp/BasicSetAccountCurrencyWithAmountAlgorithm.cs

@@ -0,0 +1,91 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System.Collections.Generic;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Basic algorithm using SetAccountCurrency with an amount
+    /// </summary>
+    public class BasicSetAccountCurrencyWithAmountAlgorithm : BasicSetAccountCurrencyAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void SetAccountCurrency()
+        {
+            //Before setting any cash or adding a Security call SetAccountCurrency
+            SetAccountCurrency("EUR", 200000);
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 4319;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 120;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "1"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "200000.00"},
+            {"End Equity", "184791.19"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "€596.71"},
+            {"Estimated Strategy Capacity", "€85000.00"},
+            {"Lowest Capacity Asset", "BTCEUR 2XR"},
+            {"Portfolio Turnover", "107.64%"},
+            {"OrderListHash", "3d450fd418a0e845b3eaaac17fcd13fc"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateAlgorithm.cs

@@ -53,7 +53,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -70,7 +70,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -82,19 +82,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "271.453%"},
             {"Drawdown", "2.200%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101691.92"},
             {"Net Profit", "1.692%"},
-            {"Sharpe Ratio", "8.888"},
+            {"Sharpe Ratio", "8.854"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "67.609%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -105,30 +113,12 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.049"},
             {"Information Ratio", "-14.565"},
             {"Tracking Error", "0.001"},
-            {"Treynor Ratio", "1.978"},
+            {"Treynor Ratio", "1.97"},
             {"Total Fees", "$3.44"},
             {"Estimated Strategy Capacity", "$56000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.248"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "93.728"},
-            {"Portfolio Turnover", "0.248"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9e4bfd2eb0b81ee5bc1b197a87ccedbe"}
+            {"Portfolio Turnover", "19.93%"},
+            {"OrderListHash", "3da9fa60bf95b9ed148b95e02e0cfc9e"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateAxosAlgorithm.cs

@@ -14,7 +14,6 @@
 */
 
 using QuantConnect.Data;
-using QuantConnect.Orders;
 using QuantConnect.Interfaces;
 using QuantConnect.Brokerages;
 using System.Collections.Generic;
@@ -22,12 +21,12 @@ using System.Collections.Generic;
 namespace QuantConnect.Algorithm.CSharp
 {
     /// <summary>
-    /// Basic template algorithm for the Atreyu brokerage
+    /// Basic template algorithm for the Axos brokerage
     /// </summary>
     /// <meta name="tag" content="using data" />
     /// <meta name="tag" content="using quantconnect" />
     /// <meta name="tag" content="trading and orders" />
-    public class BasicTemplateAtreyuAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    public class BasicTemplateAxosAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
         /// <summary>
         /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
@@ -38,21 +37,15 @@ namespace QuantConnect.Algorithm.CSharp
             SetEndDate(2013, 10, 11);
             SetCash(100000);
 
-            SetBrokerageModel(BrokerageName.Atreyu);
+            SetBrokerageModel(BrokerageName.Axos);
             AddEquity("SPY", Resolution.Minute);
-
-            DefaultOrderProperties = new AtreyuOrderProperties
-            {
-                // Currently only support order for the day
-                TimeInForce = TimeInForce.Day
-            };
         }
 
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -71,7 +64,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -83,19 +76,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "39.143%"},
             {"Drawdown", "0.500%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100423.24"},
             {"Net Profit", "0.423%"},
-            {"Sharpe Ratio", "5.634"},
+            {"Sharpe Ratio", "5.498"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "67.498%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -110,26 +111,8 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$0.60"},
             {"Estimated Strategy Capacity", "$150000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.062"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "71.634"},
-            {"Portfolio Turnover", "0.062"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d549c64ee7f5e3866712b3c7dbd64caa"}
+            {"Portfolio Turnover", "4.98%"},
+            {"OrderListHash", "8774049eb5141a2b6956d9432426f837"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateContinuousFutureAlgorithm.cs

@@ -51,7 +51,7 @@ namespace QuantConnect.Algorithm.CSharp
                 contractDepthOffset: 0
             );
 
-            _fast = SMA(_continuousContract.Symbol, 3, Resolution.Daily);
+            _fast = SMA(_continuousContract.Symbol, 4, Resolution.Daily);
             _slow = SMA(_continuousContract.Symbol, 10, Resolution.Daily);
         }
 
@@ -59,14 +59,14 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
-            foreach (var changedEvent in data.SymbolChangedEvents.Values)
+            foreach (var changedEvent in slice.SymbolChangedEvents.Values)
             {
                 Debug($"{Time} - SymbolChanged event: {changedEvent}");
                 if (Time.TimeOfDay != TimeSpan.Zero)
                 {
-                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                    throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
                 }
             }
 
@@ -113,65 +113,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 284403;
+        public long DataPoints => 713369;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-0.02%"},
-            {"Compounding Annual Return", "-0.033%"},
-            {"Drawdown", "0.000%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-0.017%"},
-            {"Sharpe Ratio", "-1.173"},
-            {"Probabilistic Sharpe Ratio", "0.011%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
+            {"Total Orders", "5"},
+            {"Average Win", "2.48%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "11.325%"},
+            {"Drawdown", "1.500%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "105549.6"},
+            {"Net Profit", "5.550%"},
+            {"Sharpe Ratio", "1.332"},
+            {"Sortino Ratio", "879.904"},
+            {"Probabilistic Sharpe Ratio", "79.894%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0"},
-            {"Beta", "-0"},
-            {"Annual Standard Deviation", "0"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-2.752"},
-            {"Tracking Error", "0.082"},
-            {"Treynor Ratio", "1.883"},
-            {"Total Fees", "$4.30"},
-            {"Estimated Strategy Capacity", "$0"},
+            {"Alpha", "0.075"},
+            {"Beta", "-0.017"},
+            {"Annual Standard Deviation", "0.053"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-1.48"},
+            {"Tracking Error", "0.099"},
+            {"Treynor Ratio", "-4.187"},
+            {"Total Fees", "$10.75"},
+            {"Estimated Strategy Capacity", "$7100000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.006"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-1.993"},
-            {"Portfolio Turnover", "0.01"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "1fd4b49e9450800981c6dead2bbca995"}
+            {"Portfolio Turnover", "2.33%"},
+            {"OrderListHash", "9c524830ffc7354327638142ae62acd2"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateContinuousFutureWithExtendedMarketAlgorithm.cs

@@ -52,22 +52,22 @@ namespace QuantConnect.Algorithm.CSharp
                 extendedMarketHours: true
             );
 
-            _fast = SMA(_continuousContract.Symbol, 3, Resolution.Daily);
+            _fast = SMA(_continuousContract.Symbol, 4, Resolution.Daily);
             _slow = SMA(_continuousContract.Symbol, 10, Resolution.Daily);
         }
 
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
-            foreach (var changedEvent in data.SymbolChangedEvents.Values)
+            foreach (var changedEvent in slice.SymbolChangedEvents.Values)
             {
                 Debug($"{Time} - SymbolChanged event: {changedEvent}");
                 if (Time.TimeOfDay != TimeSpan.Zero)
                 {
-                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                    throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
                 }
             }
 
@@ -118,65 +118,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 884815;
+        public long DataPoints => 2217299;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-0.02%"},
-            {"Compounding Annual Return", "-0.033%"},
-            {"Drawdown", "0.000%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-0.017%"},
-            {"Sharpe Ratio", "-1.173"},
-            {"Probabilistic Sharpe Ratio", "0.011%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
+            {"Total Orders", "5"},
+            {"Average Win", "2.86%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "12.959%"},
+            {"Drawdown", "1.100%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "106337.1"},
+            {"Net Profit", "6.337%"},
+            {"Sharpe Ratio", "1.41"},
+            {"Sortino Ratio", "1.242"},
+            {"Probabilistic Sharpe Ratio", "77.992%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0"},
-            {"Beta", "-0"},
-            {"Annual Standard Deviation", "0"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-2.752"},
-            {"Tracking Error", "0.082"},
-            {"Treynor Ratio", "1.883"},
-            {"Total Fees", "$4.30"},
-            {"Estimated Strategy Capacity", "$0"},
+            {"Alpha", "0.071"},
+            {"Beta", "0.054"},
+            {"Annual Standard Deviation", "0.059"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-1.392"},
+            {"Tracking Error", "0.097"},
+            {"Treynor Ratio", "1.518"},
+            {"Total Fees", "$10.75"},
+            {"Estimated Strategy Capacity", "$890000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.006"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-1.985"},
-            {"Portfolio Turnover", "0.01"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "adb237703e65b93da5961c0085109732"}
+            {"Portfolio Turnover", "2.32%"},
+            {"OrderListHash", "f60fc7dcba2c1ff077afeb191aee5008"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateCryptoAlgorithm.cs

@@ -79,8 +79,8 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
             if (Portfolio.CashBook["EUR"].ConversionRate == 0
                 || Portfolio.CashBook["BTC"].ConversionRate == 0
@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
                 Log($"LTC conversion rate: {Portfolio.CashBook["LTC"].ConversionRate}");
                 Log($"ETH conversion rate: {Portfolio.CashBook["ETH"].ConversionRate}");
 
-                throw new Exception("Conversion rate is 0");
+                throw new RegressionTestException("Conversion rate is 0");
             }
             if (Time.Hour == 1 && Time.Minute == 0)
             {
@@ -196,31 +196,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 12970;
+        public long DataPoints => 12965;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 240;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "10"},
+            {"Total Orders", "12"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "31588.24"},
+            {"End Equity", "30866.71"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -234,27 +242,9 @@ namespace QuantConnect.Algorithm.CSharp
             {"Treynor Ratio", "0"},
             {"Total Fees", "$85.34"},
             {"Estimated Strategy Capacity", "$0"},
-            {"Lowest Capacity Asset", "BTCEUR XJ"},
-            {"Fitness Score", "0.5"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-43.943"},
-            {"Portfolio Turnover", "1.028"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "1bf1a6d9dd921982b72a6178f9e50e68"}
+            {"Lowest Capacity Asset", "BTCEUR 2XR"},
+            {"Portfolio Turnover", "118.08%"},
+            {"OrderListHash", "26b9a07ace86b6a0e0eb2ff8c168cee0"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateCryptoFutureAlgorithm.cs

@@ -0,0 +1,282 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+using QuantConnect.Brokerages;
+using QuantConnect.Indicators;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using QuantConnect.Data.Market;
+using System.Collections.Generic;
+using QuantConnect.Securities.CryptoFuture;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Minute resolution regression algorithm trading Coin and USDT binance futures long and short asserting the behavior
+    /// </summary>
+    public class BasicTemplateCryptoFutureAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Dictionary<Symbol, int> _interestPerSymbol = new();
+        private CryptoFuture _btcUsd;
+        private CryptoFuture _adaUsdt;
+        private ExponentialMovingAverage _fast;
+        private ExponentialMovingAverage _slow;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2022, 12, 13); // Set Start Date
+            SetEndDate(2022, 12, 13); // Set End Date
+
+            SetTimeZone(TimeZones.Utc);
+
+            try
+            {
+                SetBrokerageModel(BrokerageName.BinanceFutures, AccountType.Cash);
+            }
+            catch (InvalidOperationException)
+            {
+                // expected, we don't allow cash account type
+            }
+            SetBrokerageModel(BrokerageName.BinanceFutures, AccountType.Margin);
+
+            _btcUsd = AddCryptoFuture("BTCUSD");
+            _adaUsdt = AddCryptoFuture("ADAUSDT");
+
+            _fast = EMA(_btcUsd.Symbol, 30, Resolution.Minute);
+            _slow = EMA(_btcUsd.Symbol, 60, Resolution.Minute);
+
+            _interestPerSymbol[_btcUsd.Symbol] = 0;
+            _interestPerSymbol[_adaUsdt.Symbol] = 0;
+
+            // Default USD cash, set 1M but it wont be used
+            SetCash(1000000);
+
+            // the amount of BTC we need to hold to trade 'BTCUSD'
+            _btcUsd.BaseCurrency.SetAmount(0.005m);
+            // the amount of USDT we need to hold to trade 'ADAUSDT'
+            _adaUsdt.QuoteCurrency.SetAmount(200);
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            var interestRates = slice.Get<MarginInterestRate>();
+            foreach (var interestRate in interestRates)
+            {
+                _interestPerSymbol[interestRate.Key]++;
+
+                var cachedInterestRate = Securities[interestRate.Key].Cache.GetData<MarginInterestRate>();
+                if (cachedInterestRate != interestRate.Value)
+                {
+                    throw new RegressionTestException($"Unexpected cached margin interest rate for {interestRate.Key}!");
+                }
+            }
+
+            if (_fast > _slow)
+            {
+                if (!Portfolio.Invested && Transactions.OrdersCount == 0)
+                {
+                    var ticket = Buy(_btcUsd.Symbol, 50);
+                    if (ticket.Status != OrderStatus.Invalid)
+                    {
+                        throw new RegressionTestException($"Unexpected valid order {ticket}, should fail due to margin not sufficient");
+                    }
+
+                    Buy(_btcUsd.Symbol, 1);
+
+                    var marginUsed = Portfolio.TotalMarginUsed;
+                    var btcUsdHoldings = _btcUsd.Holdings;
+
+                    // Coin futures value is 100 USD
+                    var holdingsValueBtcUsd = 100;
+
+                    if (Math.Abs(btcUsdHoldings.TotalSaleVolume - holdingsValueBtcUsd) > 1)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalSaleVolume {btcUsdHoldings.TotalSaleVolume}");
+                    }
+                    if (Math.Abs(btcUsdHoldings.AbsoluteHoldingsCost - holdingsValueBtcUsd) > 1)
+                    {
+                        throw new RegressionTestException($"Unexpected holdings cost {btcUsdHoldings.HoldingsCost}");
+                    }
+                    // margin used is based on the maintenance rate
+                    if (Math.Abs(btcUsdHoldings.AbsoluteHoldingsCost * 0.05m - marginUsed) > 1
+                        || _btcUsd.BuyingPowerModel.GetMaintenanceMargin(_btcUsd) != marginUsed)
+                    {
+                        throw new RegressionTestException($"Unexpected margin used {marginUsed}");
+                    }
+
+                    Buy(_adaUsdt.Symbol, 1000);
+
+                    marginUsed = Portfolio.TotalMarginUsed - marginUsed;
+                    var adaUsdtHoldings = _adaUsdt.Holdings;
+
+                    // USDT/BUSD futures value is based on it's price
+                    var holdingsValueUsdt = _adaUsdt.Price * _adaUsdt.SymbolProperties.ContractMultiplier * 1000;
+
+                    if (Math.Abs(adaUsdtHoldings.TotalSaleVolume - holdingsValueUsdt) > 1)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalSaleVolume {adaUsdtHoldings.TotalSaleVolume}");
+                    }
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
+                    {
+                        throw new RegressionTestException($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                    }
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost * 0.05m - marginUsed) > 1
+                        || _adaUsdt.BuyingPowerModel.GetMaintenanceMargin(_adaUsdt) != marginUsed)
+                    {
+                        throw new RegressionTestException($"Unexpected margin used {marginUsed}");
+                    }
+
+                    // position just opened should be just spread here
+                    var profit = Portfolio.TotalUnrealizedProfit;
+                    if ((5 - Math.Abs(profit)) < 0)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                    }
+
+                    if (Portfolio.TotalProfit != 0)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                    }
+                }
+            }
+            else
+            {
+                // let's revert our position and double
+                if (Time.Hour > 10 && Transactions.OrdersCount == 3)
+                {
+                    Sell(_btcUsd.Symbol, 3);
+
+                    var btcUsdHoldings = _btcUsd.Holdings;
+
+                    if (Math.Abs(btcUsdHoldings.AbsoluteHoldingsCost - 100 * 2) > 1)
+                    {
+                        throw new RegressionTestException($"Unexpected holdings cost {btcUsdHoldings.HoldingsCost}");
+                    }
+
+                    Sell(_adaUsdt.Symbol, 3000);
+
+                    var adaUsdtHoldings = _adaUsdt.Holdings;
+
+                    // USDT/BUSD futures value is based on it's price
+                    var holdingsValueUsdt = _adaUsdt.Price * _adaUsdt.SymbolProperties.ContractMultiplier * 2000;
+
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
+                    {
+                        throw new RegressionTestException($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                    }
+
+                    // position just opened should be just spread here
+                    var profit = Portfolio.TotalUnrealizedProfit;
+                    if ((5 - Math.Abs(profit)) < 0)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                    }
+                    // we barely did any difference on the previous trade
+                    if ((5 - Math.Abs(Portfolio.TotalProfit)) < 0)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                    }
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_interestPerSymbol[_adaUsdt.Symbol] != 1)
+            {
+                throw new RegressionTestException($"Unexpected interest rate count {_interestPerSymbol[_adaUsdt.Symbol]}");
+            }
+
+            if (_interestPerSymbol[_btcUsd.Symbol] != 3)
+            {
+                throw new RegressionTestException($"Unexpected interest rate count {_interestPerSymbol[_btcUsd.Symbol]}");
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug(Time + " " + orderEvent);
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 7205;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "5"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "1000200.00"},
+            {"End Equity", "1000278.02"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.65"},
+            {"Estimated Strategy Capacity", "$500000000.00"},
+            {"Lowest Capacity Asset", "ADAUSDT 18R"},
+            {"Portfolio Turnover", "0.16%"},
+            {"OrderListHash", "dcc4f964b5549c753123848c32eaee41"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateCryptoFutureHourlyAlgorithm.cs

@@ -0,0 +1,245 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+using QuantConnect.Indicators;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using QuantConnect.Brokerages;
+using QuantConnect.Data.Market;
+using System.Collections.Generic;
+using QuantConnect.Securities.CryptoFuture;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Hourly regression algorithm trading ADAUSDT binance futures long and short asserting the behavior
+    /// </summary>
+    public class BasicTemplateCryptoFutureHourlyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Dictionary<Symbol, int> _interestPerSymbol = new();
+        private CryptoFuture _adaUsdt;
+        private ExponentialMovingAverage _fast;
+        private ExponentialMovingAverage _slow;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2022, 12, 13);
+            SetEndDate(2022, 12, 13);
+
+            SetTimeZone(TimeZones.Utc);
+
+            try
+            {
+                SetBrokerageModel(BrokerageName.BinanceCoinFutures, AccountType.Cash);
+            }
+            catch (InvalidOperationException)
+            {
+                // expected, we don't allow cash account type
+            }
+            SetBrokerageModel(BrokerageName.BinanceCoinFutures, AccountType.Margin);
+
+            _adaUsdt = AddCryptoFuture("ADAUSDT", Resolution.Hour);
+
+            _fast = EMA(_adaUsdt.Symbol, 3, Resolution.Hour);
+            _slow = EMA(_adaUsdt.Symbol, 6, Resolution.Hour);
+
+            _interestPerSymbol[_adaUsdt.Symbol] = 0;
+
+            // Default USD cash, set 1M but it wont be used
+            SetCash(1000000);
+
+            // the amount of USDT we need to hold to trade 'ADAUSDT'
+            _adaUsdt.QuoteCurrency.SetAmount(200);
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            var interestRates = slice.Get<MarginInterestRate>();
+            foreach (var interestRate in interestRates)
+            {
+                _interestPerSymbol[interestRate.Key]++;
+
+                var cachedInterestRate = Securities[interestRate.Key].Cache.GetData<MarginInterestRate>();
+                if (cachedInterestRate != interestRate.Value)
+                {
+                    throw new RegressionTestException($"Unexpected cached margin interest rate for {interestRate.Key}!");
+                }
+            }
+
+            if (_fast > _slow)
+            {
+                if (!Portfolio.Invested && Transactions.OrdersCount == 0)
+                {
+                    var ticket = Buy(_adaUsdt.Symbol, 100000);
+                    if(ticket.Status != OrderStatus.Invalid)
+                    {
+                        throw new RegressionTestException($"Unexpected valid order {ticket}, should fail due to margin not sufficient");
+                    }
+
+                    Buy(_adaUsdt.Symbol, 1000);
+
+                    var marginUsed = Portfolio.TotalMarginUsed;
+                    var adaUsdtHoldings = _adaUsdt.Holdings;
+
+                    // USDT/BUSD futures value is based on it's price
+                    var holdingsValueUsdt = _adaUsdt.Price * _adaUsdt.SymbolProperties.ContractMultiplier * 1000;
+
+                    if (Math.Abs(adaUsdtHoldings.TotalSaleVolume - holdingsValueUsdt) > 1)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalSaleVolume {adaUsdtHoldings.TotalSaleVolume}");
+                    }
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
+                    {
+                        throw new RegressionTestException($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                    }
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost * 0.05m - marginUsed) > 1
+                        || _adaUsdt.BuyingPowerModel.GetMaintenanceMargin(_adaUsdt) != marginUsed)
+                    {
+                        throw new RegressionTestException($"Unexpected margin used {marginUsed}");
+                    }
+
+                    // position just opened should be just spread here
+                    var profit = Portfolio.TotalUnrealizedProfit;
+                    if ((5 - Math.Abs(profit)) < 0)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                    }
+
+                    if (Portfolio.TotalProfit != 0)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                    }
+                }
+            }
+            else
+            {
+                // let's revert our position and double
+                if (Time.Hour > 10 && Transactions.OrdersCount == 2)
+                {
+                    Sell(_adaUsdt.Symbol, 3000);
+
+                    var adaUsdtHoldings = _adaUsdt.Holdings;
+
+                    // USDT/BUSD futures value is based on it's price
+                    var holdingsValueUsdt = _adaUsdt.Price * _adaUsdt.SymbolProperties.ContractMultiplier * 2000;
+
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
+                    {
+                        throw new RegressionTestException($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                    }
+
+                    // position just opened should be just spread here
+                    var profit = Portfolio.TotalUnrealizedProfit;
+                    if ((5 - Math.Abs(profit)) < 0)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                    }
+                    // we barely did any difference on the previous trade
+                    if ((5 - Math.Abs(Portfolio.TotalProfit)) < 0)
+                    {
+                        throw new RegressionTestException($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                    }
+                }
+
+                if (Time.Hour >= 22 && Transactions.OrdersCount == 3)
+                {
+                    Liquidate();
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_interestPerSymbol[_adaUsdt.Symbol] != 1)
+            {
+                throw new RegressionTestException($"Unexpected interest rate count {_interestPerSymbol[_adaUsdt.Symbol]}");
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug(Time + " " + orderEvent);
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 50;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "3"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "1000200"},
+            {"End Equity", "1000189.47"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.61"},
+            {"Estimated Strategy Capacity", "$370000000.00"},
+            {"Lowest Capacity Asset", "ADAUSDT 18R"},
+            {"Portfolio Turnover", "0.12%"},
+            {"OrderListHash", "50a51d06d03a5355248a6bccef1ca521"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateDailyAlgorithm.cs

@@ -43,8 +43,8 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -61,65 +61,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 73;
+        public long DataPoints => 72;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "246.546%"},
-            {"Drawdown", "1.200%"},
+            {"Compounding Annual Return", "424.375%"},
+            {"Drawdown", "0.800%"},
             {"Expectancy", "0"},
-            {"Net Profit", "3.464%"},
-            {"Sharpe Ratio", "19.148"},
-            {"Probabilistic Sharpe Ratio", "97.754%"},
+            {"Start Equity", "100000"},
+            {"End Equity", "104486.22"},
+            {"Net Profit", "4.486%"},
+            {"Sharpe Ratio", "17.304"},
+            {"Sortino Ratio", "35.217"},
+            {"Probabilistic Sharpe Ratio", "96.835%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.005"},
-            {"Beta", "0.998"},
-            {"Annual Standard Deviation", "0.138"},
-            {"Annual Variance", "0.019"},
-            {"Information Ratio", "-34.028"},
-            {"Tracking Error", "0"},
-            {"Treynor Ratio", "2.651"},
-            {"Total Fees", "$3.45"},
-            {"Estimated Strategy Capacity", "$970000000.00"},
+            {"Alpha", "-0.249"},
+            {"Beta", "1.015"},
+            {"Annual Standard Deviation", "0.141"},
+            {"Annual Variance", "0.02"},
+            {"Information Ratio", "-19"},
+            {"Tracking Error", "0.011"},
+            {"Treynor Ratio", "2.403"},
+            {"Total Fees", "$3.49"},
+            {"Estimated Strategy Capacity", "$1200000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.112"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "53.951"},
-            {"Return Over Maximum Drawdown", "209.464"},
-            {"Portfolio Turnover", "0.112"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "33d01821923c397f999cfb2e5b5928ad"}
+            {"Portfolio Turnover", "10.01%"},
+            {"OrderListHash", "70f21e930175a2ec9d465b21edc1b6d9"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateEurexFuturesAlgorithm.cs

@@ -0,0 +1,239 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using QuantConnect.Data;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This algorithm tests and demonstrates EUREX futures subscription and trading:
+    /// - It tests contracts rollover by adding a continuous future and asserting that mapping happens at some point.
+    /// - It tests basic trading by buying a contract and holding it until expiration.
+    /// - It tests delisting and asserts the holdings are liquidated after that.
+    /// </summary>
+    public class BasicTemplateEurexFuturesAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Future _continuousContract;
+        private Symbol _mappedSymbol;
+        private Symbol _contractToTrade;
+        private int _mappingsCount;
+        private decimal _boughtQuantity;
+        private decimal _liquidatedQuantity;
+        private bool _delisted;
+
+        public override void Initialize()
+        {
+            SetStartDate(2024, 5, 30);
+            SetEndDate(2024, 6, 23);
+
+            SetAccountCurrency(Currencies.EUR);
+            SetCash(1000000);
+
+            _continuousContract = AddFuture(Futures.Indices.EuroStoxx50, Resolution.Minute,
+                dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
+                dataMappingMode: DataMappingMode.FirstDayMonth,
+                contractDepthOffset: 0);
+            _continuousContract.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(180));
+            _mappedSymbol = _continuousContract.Mapped;
+
+            var benchmark = AddIndex("SX5E", market: Market.EUREX);
+            SetBenchmark(benchmark.Symbol);
+
+            var seeder = new FuncSecuritySeeder(GetLastKnownPrices);
+            SetSecurityInitializer(security => seeder.SeedSecurity(security));
+        }
+
+        public override void OnData(Slice slice)
+        {
+            foreach (var changedEvent in slice.SymbolChangedEvents.Values)
+            {
+                if (++_mappingsCount > 1)
+                {
+                    throw new RegressionTestException($"{Time} - Unexpected number of symbol changed events (mappings): {_mappingsCount}. " +
+                        $"Expected only 1.");
+                }
+
+                Debug($"{Time} - SymbolChanged event: {changedEvent}");
+
+                if (changedEvent.OldSymbol != _mappedSymbol.ID.ToString())
+                {
+                    throw new RegressionTestException($"{Time} - Unexpected symbol changed event old symbol: {changedEvent}");
+                }
+
+                if (changedEvent.NewSymbol != _continuousContract.Mapped.ID.ToString())
+                {
+                    throw new RegressionTestException($"{Time} - Unexpected symbol changed event new symbol: {changedEvent}");
+                }
+
+                // Let's trade the previous mapped contract, so we can hold it until expiration for testing
+                // (will be sooner than the new mapped contract)
+                _contractToTrade = _mappedSymbol;
+                _mappedSymbol = _continuousContract.Mapped;
+            }
+
+            // Let's trade after the mapping is done
+            if (_contractToTrade != null && _boughtQuantity == 0 && Securities[_contractToTrade].Exchange.ExchangeOpen)
+            {
+                Buy(_contractToTrade, 1);
+            }
+
+            if (_contractToTrade != null && slice.Delistings.TryGetValue(_contractToTrade, out var delisting))
+            {
+                if (delisting.Type == DelistingType.Delisted)
+                {
+                    _delisted = true;
+
+                    if (Portfolio.Invested)
+                    {
+                        throw new RegressionTestException($"{Time} - Portfolio should not be invested after the traded contract is delisted.");
+                    }
+                }
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            if (orderEvent.Symbol != _contractToTrade)
+            {
+                throw new RegressionTestException($"{Time} - Unexpected order event symbol: {orderEvent.Symbol}. Expected {_contractToTrade}");
+            }
+
+            if (orderEvent.Direction == OrderDirection.Buy)
+            {
+                if (orderEvent.Status == OrderStatus.Filled)
+                {
+                    if (_boughtQuantity != 0 && _liquidatedQuantity != 0)
+                    {
+                        throw new RegressionTestException($"{Time} - Unexpected buy order event status: {orderEvent.Status}");
+                    }
+                    _boughtQuantity = orderEvent.Quantity;
+                }
+            }
+            else if (orderEvent.Direction == OrderDirection.Sell)
+            {
+                if (orderEvent.Status == OrderStatus.Filled)
+                {
+                    if (_boughtQuantity <= 0 && _liquidatedQuantity != 0)
+                    {
+                        throw new RegressionTestException($"{Time} - Unexpected sell order event status: {orderEvent.Status}");
+                    }
+                    _liquidatedQuantity = orderEvent.Quantity;
+
+                    if (_liquidatedQuantity != -_boughtQuantity)
+                    {
+                        throw new RegressionTestException($"{Time} - Unexpected liquidated quantity: {_liquidatedQuantity}. Expected: {-_boughtQuantity}");
+                    }
+                }
+            }
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            foreach (var addedSecurity in changes.AddedSecurities)
+            {
+                if (addedSecurity.Symbol.SecurityType == SecurityType.Future && addedSecurity.Symbol.IsCanonical())
+                {
+                    _mappedSymbol = _continuousContract.Mapped;
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_mappingsCount == 0)
+            {
+                throw new RegressionTestException($"Unexpected number of symbol changed events (mappings): {_mappingsCount}. Expected 1.");
+            }
+
+            if (!_delisted)
+            {
+                throw new RegressionTestException("Contract was not delisted");
+            }
+
+            // Make sure we traded and that the position was liquidated on delisting
+            if (_boughtQuantity <= 0 || _liquidatedQuantity >= 0)
+            {
+                throw new RegressionTestException($"Unexpected sold quantity: {_boughtQuantity} and liquidated quantity: {_liquidatedQuantity}");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 133945;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 26;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "2"},
+            {"Average Win", "0%"},
+            {"Average Loss", "-0.11%"},
+            {"Compounding Annual Return", "-1.667%"},
+            {"Drawdown", "0.100%"},
+            {"Expectancy", "-1"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "998849.48"},
+            {"Net Profit", "-0.115%"},
+            {"Sharpe Ratio", "-34.455"},
+            {"Sortino Ratio", "-57.336"},
+            {"Probabilistic Sharpe Ratio", "0.002%"},
+            {"Loss Rate", "100%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0.002"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-6.176"},
+            {"Tracking Error", "0.002"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "€1.02"},
+            {"Estimated Strategy Capacity", "€2300000000.00"},
+            {"Lowest Capacity Asset", "FESX YJHOAMPYKRS5"},
+            {"Portfolio Turnover", "0.40%"},
+            {"OrderListHash", "54040d29a467becaedcf59d79323321b"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFillForwardAlgorithm.cs

@@ -13,6 +13,7 @@
  * limitations under the License.
 */
 
+using QuantConnect.Data;
 using QuantConnect.Data.Market;
 
 namespace QuantConnect.Algorithm.CSharp
@@ -41,8 +42,8 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">TradeBars IDictionary object with your stock data</param>
-        public void OnData(TradeBars data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {

Algorithm.CSharp/BasicTemplateForexAlgorithm.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -59,14 +59,14 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
                 SetHoldings("EURUSD", .5);
                 SetHoldings("NZDUSD", .5);
-                Log(string.Join(", ", data.Values));
+                Log(string.Join(", ", slice.Values));
             }
         }
     }
-}
+}

Algorithm.CSharp/BasicTemplateFrameworkAlgorithm.cs

@@ -82,7 +82,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -94,19 +94,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "3"},
+            {"Total Orders", "3"},
             {"Average Win", "0%"},
             {"Average Loss", "-1.01%"},
             {"Compounding Annual Return", "261.134%"},
             {"Drawdown", "2.200%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101655.30"},
             {"Net Profit", "1.655%"},
-            {"Sharpe Ratio", "8.505"},
+            {"Sharpe Ratio", "8.472"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "66.840%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
@@ -117,30 +125,12 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.05"},
             {"Information Ratio", "-33.445"},
             {"Tracking Error", "0.002"},
-            {"Treynor Ratio", "1.893"},
+            {"Treynor Ratio", "1.885"},
             {"Total Fees", "$10.32"},
             {"Estimated Strategy Capacity", "$27000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.747"},
-            {"Kelly Criterion Estimate", "38.796"},
-            {"Kelly Criterion Probability Value", "0.228"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "85.095"},
-            {"Portfolio Turnover", "0.747"},
-            {"Total Insights Generated", "100"},
-            {"Total Insights Closed", "99"},
-            {"Total Insights Analysis Completed", "99"},
-            {"Long Insight Count", "100"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$135639.1761"},
-            {"Total Accumulated Estimated Alpha Value", "$21852.9784"},
-            {"Mean Population Estimated Insight Value", "$220.7372"},
-            {"Mean Population Direction", "53.5354%"},
-            {"Mean Population Magnitude", "53.5354%"},
-            {"Rolling Averaged Population Direction", "58.2788%"},
-            {"Rolling Averaged Population Magnitude", "58.2788%"},
-            {"OrderListHash", "ad2216297c759d8e5aef48ff065f8919"}
+            {"Portfolio Turnover", "59.86%"},
+            {"OrderListHash", "f209ed42701b0419858e0100595b40c0"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFutureOptionAlgorithm.cs

@@ -92,4 +92,4 @@ namespace QuantConnect.Algorithm.CSharp
             Debug($"{Time} {orderEvent.ToString()}");
         }
     }
-}
+}

Algorithm.CSharp/BasicTemplateFutureRolloverAlgorithm.cs

@@ -0,0 +1,225 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System.Collections.Generic;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Indicators;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Example algorithm for trading continuous future
+    /// </summary>
+    public class BasicTemplateFutureRolloverAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Dictionary<Symbol, SymbolData> _symbolDataBySymbol = new();
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 8);
+            SetEndDate(2013, 12, 10);
+            SetCash(1000000);
+
+            var futures = new List<string> {
+                Futures.Indices.SP500EMini
+            };
+
+            foreach (var future in futures)
+            {
+                // Requesting data
+                var continuousContract = AddFuture(future,
+                    resolution: Resolution.Daily,
+                    extendedMarketHours: true,
+                    dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
+                    dataMappingMode: DataMappingMode.OpenInterest,
+                    contractDepthOffset: 0
+                );
+
+                var symbolData = new SymbolData(this, continuousContract);
+                _symbolDataBySymbol.Add(continuousContract.Symbol, symbolData);
+            }
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            foreach (var kvp in _symbolDataBySymbol)
+            {
+                var symbol = kvp.Key;
+                var symbolData = kvp.Value;
+
+                // Call SymbolData.Update() method to handle new data slice received
+                symbolData.Update(slice);
+
+                // Check if information in SymbolData class and new slice data are ready for trading
+                if (!symbolData.IsReady || !slice.Bars.ContainsKey(symbol))
+                {
+                    return;
+                }
+
+                var emaCurrentValue = symbolData.EMA.Current.Value;
+                if (emaCurrentValue < symbolData.Price && !symbolData.IsLong)
+                {
+                    MarketOrder(symbolData.Mapped, 1);
+                }
+                else if (emaCurrentValue > symbolData.Price && !symbolData.IsShort)
+                {
+                    MarketOrder(symbolData.Mapped, -1);
+                }
+            }
+        }
+
+        /// <summary>
+        /// Abstracted class object to hold information (state, indicators, methods, etc.) from a Symbol/Security in a multi-security algorithm
+        /// </summary>
+        public class SymbolData
+        {
+            private QCAlgorithm _algorithm;
+            private Future _future;
+            public ExponentialMovingAverage EMA { get; set; }
+            public decimal Price { get; set; }
+            public bool IsLong { get; set; }
+            public bool IsShort { get; set; }
+            public Symbol Symbol => _future.Symbol;
+            public Symbol Mapped => _future.Mapped;
+
+            /// <summary>
+            /// Check if symbolData class object are ready for trading
+            /// </summary>
+            public bool IsReady => Mapped != null && EMA.IsReady;
+
+            /// <summary>
+            /// Constructor to instantiate the information needed to be hold
+            /// </summary>
+            public SymbolData(QCAlgorithm algorithm, Future future)
+            {
+                _algorithm = algorithm;
+                _future = future;
+                EMA = algorithm.EMA(future.Symbol, 20, Resolution.Daily);
+
+                Reset();
+            }
+
+            /// <summary>
+            /// Handler of new slice of data received
+            /// </summary>
+            public void Update(Slice slice)
+            {
+                if (slice.SymbolChangedEvents.TryGetValue(Symbol, out var changedEvent))
+                {
+                    var oldSymbol = changedEvent.OldSymbol;
+                    var newSymbol = changedEvent.NewSymbol;
+                    var tag = $"Rollover - Symbol changed at {_algorithm.Time}: {oldSymbol} -> {newSymbol}";
+                    var quantity = _algorithm.Portfolio[oldSymbol].Quantity;
+
+                    // Rolling over: to liquidate any position of the old mapped contract and switch to the newly mapped contract
+                    _algorithm.Liquidate(oldSymbol, tag: tag);
+                    _algorithm.MarketOrder(newSymbol, quantity, tag: tag);
+
+                    Reset();
+                }
+
+                Price = slice.Bars.ContainsKey(Symbol) ? slice.Bars[Symbol].Price : Price;
+                IsLong = _algorithm.Portfolio[Mapped].IsLong;
+                IsShort = _algorithm.Portfolio[Mapped].IsShort;
+            }
+
+            /// <summary>
+            /// Reset RollingWindow/indicator to adapt to newly mapped contract, then warm up the RollingWindow/indicator
+            /// </summary>
+            private void Reset()
+            {
+                EMA.Reset();
+                _algorithm.WarmUpIndicator(Symbol, EMA, Resolution.Daily);
+            }
+
+            /// <summary>
+            /// Disposal method to remove consolidator/update method handler, and reset RollingWindow/indicator to free up memory and speed
+            /// </summary>
+            public void Dispose()
+            {
+                EMA.Reset();
+            }
+        }
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 1190;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 2;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "1"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "-0.010%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "999983.2"},
+            {"Net Profit", "-0.002%"},
+            {"Sharpe Ratio", "-225.214"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0.135%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.008"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-5.146"},
+            {"Tracking Error", "0.083"},
+            {"Treynor Ratio", "-542.359"},
+            {"Total Fees", "$2.15"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
+            {"Portfolio Turnover", "0.13%"},
+            {"OrderListHash", "273dd05b937c075b75baf8af46d3c7de"}
+        };
+    }  
+}

Algorithm.CSharp/BasicTemplateFuturesAlgorithm.cs

@@ -39,11 +39,9 @@ namespace QuantConnect.Algorithm.CSharp
 
         // S&P 500 EMini futures
         private const string RootSP500 = Futures.Indices.SP500EMini;
-        public Symbol SP500 = QuantConnect.Symbol.Create(RootSP500, SecurityType.Future, Market.CME);
 
         // Gold futures
         private const string RootGold = Futures.Metals.Gold;
-        public Symbol Gold = QuantConnect.Symbol.Create(RootGold, SecurityType.Future, Market.COMEX);
 
         /// <summary>
         /// Initialize your algorithm and add desired assets.
@@ -81,7 +79,7 @@ namespace QuantConnect.Algorithm.CSharp
                 Debug($"{Time} - SymbolChanged event: {changedEvent}");
                 if (Time.TimeOfDay != TimeSpan.Zero)
                 {
-                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                    throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
                 }
             }
 
@@ -117,7 +115,7 @@ namespace QuantConnect.Algorithm.CSharp
             var futureMarginModel = buyingPowerModel as FutureMarginModel;
             if (buyingPowerModel == null)
             {
-                throw new Exception($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
+                throw new RegressionTestException($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
             }
             var initialOvernight = futureMarginModel.InitialOvernightMarginRequirement;
             var maintenanceOvernight = futureMarginModel.MaintenanceOvernightMarginRequirement;
@@ -133,7 +131,7 @@ namespace QuantConnect.Algorithm.CSharp
                     && !addedSecurity.Symbol.IsCanonical()
                     && !addedSecurity.HasData)
                 {
-                    throw new Exception($"Future contracts did not work up as expected: {addedSecurity.Symbol}");
+                    throw new RegressionTestException($"Future contracts did not work up as expected: {addedSecurity.Symbol}");
                 }
             }
         }
@@ -146,65 +144,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 68645;
+        public long DataPoints => 75403;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 340;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2700"},
+            {"Total Orders", "2700"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
             {"Compounding Annual Return", "-99.777%"},
             {"Drawdown", "4.400%"},
             {"Expectancy", "-0.724"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "955700.5"},
             {"Net Profit", "-4.430%"},
-            {"Sharpe Ratio", "-31.389"},
+            {"Sharpe Ratio", "-31.63"},
+            {"Sortino Ratio", "-31.63"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "83%"},
             {"Win Rate", "17%"},
             {"Profit-Loss Ratio", "0.65"},
-            {"Alpha", "-3.059"},
+            {"Alpha", "-3.065"},
             {"Beta", "0.128"},
             {"Annual Standard Deviation", "0.031"},
             {"Annual Variance", "0.001"},
             {"Information Ratio", "-81.232"},
             {"Tracking Error", "0.212"},
-            {"Treynor Ratio", "-7.618"},
+            {"Treynor Ratio", "-7.677"},
             {"Total Fees", "$6237.00"},
             {"Estimated Strategy Capacity", "$14000.00"},
             {"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
-            {"Fitness Score", "0.001"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-58.725"},
-            {"Return Over Maximum Drawdown", "-32.073"},
-            {"Portfolio Turnover", "98.477"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "8f92e1528c6477a156449fd1e86527e7"}
+            {"Portfolio Turnover", "9912.69%"},
+            {"OrderListHash", "6e0f767a46a54365287801295cf7bb75"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesConsolidationAlgorithm.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -33,7 +33,6 @@ namespace QuantConnect.Algorithm.CSharp
     public class BasicTemplateFuturesConsolidationAlgorithm : QCAlgorithm
     {
         private const string RootSP500 = Futures.Indices.SP500EMini;
-        public Symbol SP500 = QuantConnect.Symbol.Create(RootSP500, SecurityType.Future, Market.CME);
         private HashSet<Symbol> _futureContracts = new HashSet<Symbol>();
 
         public override void Initialize()
@@ -78,4 +77,4 @@ namespace QuantConnect.Algorithm.CSharp
             Log(quoteBar.ToString());
         }
     }
-}
+}

Algorithm.CSharp/BasicTemplateFuturesDailyAlgorithm.cs

@@ -83,7 +83,7 @@ namespace QuantConnect.Algorithm.CSharp
                     // if found, trade it.
                     // Also check if exchange is open for regular or extended hours. Since daily data comes at 8PM, this allows us prevent the
                     // algorithm from trading on friday when there is not after-market.
-                    if (contract != null && Securities[contract.Symbol].Exchange.Hours.IsOpen(Time, true))
+                    if (contract != null)
                     {
                         MarketOrder(contract.Symbol, 1);
                     }
@@ -99,7 +99,7 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 if (Time.TimeOfDay != TimeSpan.Zero)
                 {
-                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                    throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
                 }
             }
         }
@@ -112,65 +112,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 11709;
+        public virtual long DataPoints => 12452;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public virtual int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "118"},
-            {"Average Win", "0.09%"},
-            {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-0.479%"},
-            {"Drawdown", "0.500%"},
-            {"Expectancy", "-0.835"},
-            {"Net Profit", "-0.483%"},
-            {"Sharpe Ratio", "-1.938"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "98%"},
-            {"Win Rate", "2%"},
-            {"Profit-Loss Ratio", "8.76"},
-            {"Alpha", "-0.003"},
-            {"Beta", "-0.001"},
-            {"Annual Standard Deviation", "0.002"},
+            {"Total Orders", "32"},
+            {"Average Win", "0.33%"},
+            {"Average Loss", "-0.04%"},
+            {"Compounding Annual Return", "0.110%"},
+            {"Drawdown", "0.300%"},
+            {"Expectancy", "0.184"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1001108"},
+            {"Net Profit", "0.111%"},
+            {"Sharpe Ratio", "-1.688"},
+            {"Sortino Ratio", "-0.772"},
+            {"Probabilistic Sharpe Ratio", "14.944%"},
+            {"Loss Rate", "88%"},
+            {"Win Rate", "12%"},
+            {"Profit-Loss Ratio", "8.47"},
+            {"Alpha", "-0.007"},
+            {"Beta", "0.002"},
+            {"Annual Standard Deviation", "0.004"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.397"},
+            {"Information Ratio", "-1.353"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "5.665"},
-            {"Total Fees", "$263.30"},
-            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Treynor Ratio", "-4.099"},
+            {"Total Fees", "$72.00"},
+            {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
-            {"Fitness Score", "0.01"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.059"},
-            {"Return Over Maximum Drawdown", "-0.992"},
-            {"Portfolio Turnover", "0.031"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "b75b224669c374dcbacc33f946a1cc7c"}
+            {"Portfolio Turnover", "0.87%"},
+            {"OrderListHash", "168731c8f3a19f230cc1410818b3b573"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesFrameworkAlgorithm.cs

@@ -131,65 +131,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 43786;
+        public virtual long DataPoints => 57759;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public virtual int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "-81.734%"},
             {"Drawdown", "4.100%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "97830.76"},
             {"Net Profit", "-2.169%"},
-            {"Sharpe Ratio", "-10.195"},
+            {"Sharpe Ratio", "-10.299"},
+            {"Sortino Ratio", "-10.299"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-1.206"},
+            {"Alpha", "-1.212"},
             {"Beta", "0.238"},
             {"Annual Standard Deviation", "0.072"},
             {"Annual Variance", "0.005"},
             {"Information Ratio", "-15.404"},
             {"Tracking Error", "0.176"},
-            {"Treynor Ratio", "-3.077"},
+            {"Treynor Ratio", "-3.109"},
             {"Total Fees", "$4.62"},
             {"Estimated Strategy Capacity", "$17000000.00"},
             {"Lowest Capacity Asset", "GC VL5E74HP3EE5"},
-            {"Fitness Score", "0.006"},
-            {"Kelly Criterion Estimate", "-50.022"},
-            {"Kelly Criterion Probability Value", "0.711"},
-            {"Sortino Ratio", "-9.907"},
-            {"Return Over Maximum Drawdown", "-50.79"},
-            {"Portfolio Turnover", "0.54"},
-            {"Total Insights Generated", "5"},
-            {"Total Insights Closed", "4"},
-            {"Total Insights Analysis Completed", "4"},
-            {"Long Insight Count", "5"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$-4434.791"},
-            {"Total Accumulated Estimated Alpha Value", "$-720.6535"},
-            {"Mean Population Estimated Insight Value", "$-180.1634"},
-            {"Mean Population Direction", "25%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "25%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "323b899ae80aa839e320806411665ce7"}
+            {"Portfolio Turnover", "43.23%"},
+            {"OrderListHash", "c0fc1bcdc3008a8d263521bbc9d7cdbd"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesFrameworkWithExtendedMarketAlgorithm.cs

@@ -36,60 +36,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 123753;
+        public override long DataPoints => 163415;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "-92.667%"},
             {"Drawdown", "5.000%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "96685.76"},
             {"Net Profit", "-3.314%"},
-            {"Sharpe Ratio", "-6.303"},
+            {"Sharpe Ratio", "-6.359"},
+            {"Sortino Ratio", "-11.237"},
             {"Probabilistic Sharpe Ratio", "9.333%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-1.465"},
+            {"Alpha", "-1.47"},
             {"Beta", "0.312"},
             {"Annual Standard Deviation", "0.134"},
             {"Annual Variance", "0.018"},
             {"Information Ratio", "-14.77"},
             {"Tracking Error", "0.192"},
-            {"Treynor Ratio", "-2.718"},
+            {"Treynor Ratio", "-2.742"},
             {"Total Fees", "$4.62"},
             {"Estimated Strategy Capacity", "$52000000.00"},
             {"Lowest Capacity Asset", "GC VL5E74HP3EE5"},
-            {"Fitness Score", "0.009"},
-            {"Kelly Criterion Estimate", "-112.972"},
-            {"Kelly Criterion Probability Value", "0.671"},
-            {"Sortino Ratio", "-8.421"},
-            {"Return Over Maximum Drawdown", "-35.2"},
-            {"Portfolio Turnover", "0.548"},
-            {"Total Insights Generated", "6"},
-            {"Total Insights Closed", "5"},
-            {"Total Insights Analysis Completed", "5"},
-            {"Long Insight Count", "6"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$-96.12923"},
-            {"Total Accumulated Estimated Alpha Value", "$-15.621"},
-            {"Mean Population Estimated Insight Value", "$-3.1242"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "18ffd3a774c68da83d867e3b09e3e05d"}
+            {"Portfolio Turnover", "43.77%"},
+            {"OrderListHash", "dcdaafcefa47465962ace2759ed99c91"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesHistoryAlgorithm.cs

@@ -69,7 +69,7 @@ namespace QuantConnect.Algorithm.CSharp
             var history = History(10, Resolution.Minute);
             if (history.Count() < 10)
             {
-                throw new Exception($"Empty history at {Time}");
+                throw new RegressionTestException($"Empty history at {Time}");
             }
             _successCount++;
         }
@@ -78,7 +78,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (_successCount < ExpectedHistoryCallCount)
             {
-                throw new Exception($"Scheduled Event did not assert history call as many times as expected: {_successCount}/49");
+                throw new RegressionTestException($"Scheduled Event did not assert history call as many times as expected: {_successCount}/49");
             }
         }
 
@@ -135,31 +135,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 44184;
+        public virtual long DataPoints => 48690;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public virtual int AlgorithmHistoryDataPoints => 4818;
+        public virtual int AlgorithmHistoryDataPoints => 5305;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "0"},
+            {"Total Orders", "0"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1000000"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -174,25 +182,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", ""},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
+            {"Portfolio Turnover", "0%"},
             {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
         };
     }

Algorithm.CSharp/BasicTemplateFuturesHistoryWithExtendedMarketHoursAlgorithm.cs

@@ -42,31 +42,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 134096;
+        public override long DataPoints => 147771;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public override int AlgorithmHistoryDataPoints => 5539;
+        public override int AlgorithmHistoryDataPoints => 6112;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "0"},
+            {"Total Orders", "0"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1000000"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -81,25 +89,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", ""},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
+            {"Portfolio Turnover", "0%"},
             {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
         };
     }

Algorithm.CSharp/BasicTemplateFuturesHourlyAlgorithm.cs

@@ -36,60 +36,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 73252;
+        public override long DataPoints => 87289;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "638"},
-            {"Average Win", "0.02%"},
+            {"Total Orders", "716"},
+            {"Average Win", "0.03%"},
             {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-1.610%"},
-            {"Drawdown", "1.600%"},
-            {"Expectancy", "-0.841"},
-            {"Net Profit", "-1.622%"},
-            {"Sharpe Ratio", "-5.105"},
+            {"Compounding Annual Return", "-1.716%"},
+            {"Drawdown", "1.700%"},
+            {"Expectancy", "-0.770"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "982718.38"},
+            {"Net Profit", "-1.728%"},
+            {"Sharpe Ratio", "-8.845"},
+            {"Sortino Ratio", "-5.449"},
             {"Probabilistic Sharpe Ratio", "0.000%"},
             {"Loss Rate", "96%"},
             {"Win Rate", "4%"},
-            {"Profit-Loss Ratio", "3.21"},
-            {"Alpha", "-0.01"},
-            {"Beta", "-0.003"},
+            {"Profit-Loss Ratio", "4.89"},
+            {"Alpha", "-0.018"},
+            {"Beta", "-0.002"},
             {"Annual Standard Deviation", "0.002"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.473"},
+            {"Information Ratio", "-1.483"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "3.179"},
-            {"Total Fees", "$1456.18"},
-            {"Estimated Strategy Capacity", "$6000.00"},
+            {"Treynor Ratio", "9.102"},
+            {"Total Fees", "$1634.12"},
+            {"Estimated Strategy Capacity", "$8000.00"},
             {"Lowest Capacity Asset", "ES VP274HSU1AF5"},
-            {"Fitness Score", "0.045"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-4.326"},
-            {"Return Over Maximum Drawdown", "-0.994"},
-            {"Portfolio Turnover", "0.205"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "8842e0b890f721371ebf3c25328dee5b"}
+            {"Portfolio Turnover", "20.10%"},
+            {"OrderListHash", "aa7e574f86b70428ca0afae381be80ba"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketAlgorithm.cs

@@ -39,11 +39,9 @@ namespace QuantConnect.Algorithm.CSharp
 
         // S&P 500 EMini futures
         private const string RootSP500 = Futures.Indices.SP500EMini;
-        public Symbol SP500 = QuantConnect.Symbol.Create(RootSP500, SecurityType.Future, Market.CME);
 
         // Gold futures
         private const string RootGold = Futures.Metals.Gold;
-        public Symbol Gold = QuantConnect.Symbol.Create(RootGold, SecurityType.Future, Market.COMEX);
 
         /// <summary>
         /// Initialize your algorithm and add desired assets.
@@ -81,7 +79,7 @@ namespace QuantConnect.Algorithm.CSharp
                 Debug($"{Time} - SymbolChanged event: {changedEvent}");
                 if (Time.TimeOfDay != TimeSpan.Zero)
                 {
-                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                    throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
                 }
             }
 
@@ -117,7 +115,7 @@ namespace QuantConnect.Algorithm.CSharp
             var futureMarginModel = buyingPowerModel as FutureMarginModel;
             if (buyingPowerModel == null)
             {
-                throw new Exception($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
+                throw new RegressionTestException($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
             }
             var initialOvernight = futureMarginModel.InitialOvernightMarginRequirement;
             var maintenanceOvernight = futureMarginModel.MaintenanceOvernightMarginRequirement;
@@ -133,7 +131,7 @@ namespace QuantConnect.Algorithm.CSharp
                     && !addedSecurity.Symbol.IsCanonical()
                     && !addedSecurity.HasData)
                 {
-                    throw new Exception($"Future contracts did not work up as expected: {addedSecurity.Symbol}");
+                    throw new RegressionTestException($"Future contracts did not work up as expected: {addedSecurity.Symbol}");
                 }
             }
         }
@@ -146,65 +144,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 204087;
+        public long DataPoints => 224662;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 340;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "8282"},
+            {"Total Orders", "8282"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
             {"Compounding Annual Return", "-100.000%"},
             {"Drawdown", "13.900%"},
             {"Expectancy", "-0.824"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "861260.7"},
             {"Net Profit", "-13.874%"},
-            {"Sharpe Ratio", "-19.202"},
+            {"Sharpe Ratio", "-19.346"},
+            {"Sortino Ratio", "-19.346"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "89%"},
             {"Win Rate", "11%"},
             {"Profit-Loss Ratio", "0.64"},
-            {"Alpha", "2.477"},
+            {"Alpha", "2.468"},
             {"Beta", "-0.215"},
             {"Annual Standard Deviation", "0.052"},
             {"Annual Variance", "0.003"},
             {"Information Ratio", "-58.37"},
             {"Tracking Error", "0.295"},
-            {"Treynor Ratio", "4.66"},
+            {"Treynor Ratio", "4.695"},
             {"Total Fees", "$19131.42"},
             {"Estimated Strategy Capacity", "$130000.00"},
             {"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
-            {"Fitness Score", "0.032"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-9.217"},
-            {"Return Over Maximum Drawdown", "-7.692"},
-            {"Portfolio Turnover", "304.869"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "85cdd035d7c7a3da178d1c2dff31f1bd"}
+            {"Portfolio Turnover", "32523.20%"},
+            {"OrderListHash", "0664a72652a19956ea3c4915269cc4b9"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketDailyAlgorithm.cs

@@ -38,60 +38,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 13559;
+        public override long DataPoints => 14790;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "152"},
-            {"Average Win", "0.09%"},
-            {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-0.644%"},
-            {"Drawdown", "0.600%"},
-            {"Expectancy", "-0.872"},
-            {"Net Profit", "-0.649%"},
-            {"Sharpe Ratio", "-2.343"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "99%"},
-            {"Win Rate", "1%"},
-            {"Profit-Loss Ratio", "8.76"},
-            {"Alpha", "-0.004"},
-            {"Beta", "-0.001"},
-            {"Annual Standard Deviation", "0.002"},
+            {"Total Orders", "36"},
+            {"Average Win", "0.33%"},
+            {"Average Loss", "-0.03%"},
+            {"Compounding Annual Return", "0.102%"},
+            {"Drawdown", "0.300%"},
+            {"Expectancy", "0.171"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1001024.4"},
+            {"Net Profit", "0.102%"},
+            {"Sharpe Ratio", "-1.702"},
+            {"Sortino Ratio", "-0.836"},
+            {"Probabilistic Sharpe Ratio", "14.653%"},
+            {"Loss Rate", "89%"},
+            {"Win Rate", "11%"},
+            {"Profit-Loss Ratio", "9.54"},
+            {"Alpha", "-0.007"},
+            {"Beta", "0.002"},
+            {"Annual Standard Deviation", "0.004"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.409"},
+            {"Information Ratio", "-1.353"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "3.618"},
-            {"Total Fees", "$338.96"},
-            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Treynor Ratio", "-4.126"},
+            {"Total Fees", "$80.60"},
+            {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
-            {"Fitness Score", "0.013"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.464"},
-            {"Return Over Maximum Drawdown", "-0.992"},
-            {"Portfolio Turnover", "0.04"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "48bfc4d255420cb589e00cf582554e0a"}
+            {"Portfolio Turnover", "0.97%"},
+            {"OrderListHash", "52c852d720692fab1e12212b2aba03d4"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketHourlyAlgorithm.cs

@@ -36,60 +36,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 205645;
+        public override long DataPoints => 228834;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1982"},
+            {"Total Orders", "1992"},
             {"Average Win", "0.01%"},
             {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-4.666%"},
+            {"Compounding Annual Return", "-4.687%"},
             {"Drawdown", "4.700%"},
             {"Expectancy", "-0.911"},
-            {"Net Profit", "-4.700%"},
-            {"Sharpe Ratio", "-5.792"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "952789.22"},
+            {"Net Profit", "-4.721%"},
+            {"Sharpe Ratio", "-7.183"},
+            {"Sortino Ratio", "-5.14"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "97%"},
             {"Win Rate", "3%"},
             {"Profit-Loss Ratio", "2.04"},
-            {"Alpha", "-0.031"},
+            {"Alpha", "-0.038"},
             {"Beta", "-0.008"},
             {"Annual Standard Deviation", "0.005"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.701"},
+            {"Information Ratio", "-1.702"},
             {"Tracking Error", "0.09"},
-            {"Treynor Ratio", "4.096"},
-            {"Total Fees", "$4521.78"},
-            {"Estimated Strategy Capacity", "$2000.00"},
+            {"Treynor Ratio", "5.054"},
+            {"Total Fees", "$4543.28"},
+            {"Estimated Strategy Capacity", "$3000.00"},
             {"Lowest Capacity Asset", "ES VP274HSU1AF5"},
-            {"Fitness Score", "0.131"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-6.211"},
-            {"Return Over Maximum Drawdown", "-0.995"},
-            {"Portfolio Turnover", "0.649"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "2402a307b20aee195b77b8478d7ca64d"}
+            {"Portfolio Turnover", "56.73%"},
+            {"OrderListHash", "424536177e9be5895bab50638ef43a9d"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateHourlyAlgorithm.cs

@@ -52,8 +52,8 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -70,7 +70,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -82,19 +82,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "227.693%"},
             {"Drawdown", "2.000%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101529.08"},
             {"Net Profit", "1.529%"},
-            {"Sharpe Ratio", "8.889"},
+            {"Sharpe Ratio", "8.855"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "67.609%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -105,30 +113,12 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.049"},
             {"Information Ratio", "-14.564"},
             {"Tracking Error", "0.001"},
-            {"Treynor Ratio", "1.978"},
+            {"Treynor Ratio", "1.971"},
             {"Total Fees", "$3.44"},
             {"Estimated Strategy Capacity", "$110000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.247"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "12.105"},
-            {"Return Over Maximum Drawdown", "112.047"},
-            {"Portfolio Turnover", "0.249"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "f409be3a7c63d9c1394c2e6c005a15ee"}
+            {"Portfolio Turnover", "19.96%"},
+            {"OrderListHash", "966f8355817adbc8c724d1062691a60b"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexAlgorithm.cs

@@ -30,11 +30,11 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="indexes" />
     public class BasicTemplateIndexAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        protected Symbol Spx;
-        protected Symbol SpxOption;
+        protected Symbol Spx { get; set; }
+        protected Symbol SpxOption { get; set; }
         private ExponentialMovingAverage _emaSlow;
         private ExponentialMovingAverage _emaFast;
-        
+
         protected virtual Resolution Resolution => Resolution.Minute;
         protected virtual int StartDay => 4;
 
@@ -61,8 +61,10 @@ namespace QuantConnect.Algorithm.CSharp
 
             AddIndexOptionContract(SpxOption, Resolution);
 
-            _emaSlow = EMA(Spx, 80);
-            _emaFast = EMA(Spx, 200);
+            _emaSlow = EMA(Spx, Resolution > Resolution.Minute ? 6 : 80);
+            _emaFast = EMA(Spx, Resolution > Resolution.Minute ? 2 : 200);
+
+            Settings.DailyPreciseEndTime = true;
         }
 
         /// <summary>
@@ -91,12 +93,25 @@ namespace QuantConnect.Algorithm.CSharp
             }
         }
 
+        /// <summary>
+        /// Asserts indicators are ready
+        /// </summary>
+        /// <exception cref="RegressionTestException"></exception>
+        protected void AssertIndicators()
+        {
+            if (!_emaSlow.IsReady || !_emaFast.IsReady)
+            {
+                throw new RegressionTestException("Indicators are not ready!");
+            }
+        }
+
         public override void OnEndOfAlgorithm()
         {
             if (Portfolio[Spx].TotalSaleVolume > 0)
             {
-                throw new Exception("Index is not tradable.");
+                throw new RegressionTestException("Index is not tradable.");
             }
+            AssertIndicators();
         }
 
         /// <summary>
@@ -107,65 +122,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 16690;
+        public virtual long DataPoints => 16199;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public virtual int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "4"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-53.10%"},
-            {"Compounding Annual Return", "-92.544%"},
-            {"Drawdown", "10.100%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-9.915%"},
-            {"Sharpe Ratio", "-3.845"},
-            {"Probabilistic Sharpe Ratio", "0.053%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
+            {"Total Orders", "3"},
+            {"Average Win", "7.08%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "603.355%"},
+            {"Drawdown", "3.400%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1064395"},
+            {"Net Profit", "6.440%"},
+            {"Sharpe Ratio", "-4.563"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0.781%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.558"},
-            {"Beta", "0.313"},
-            {"Annual Standard Deviation", "0.112"},
-            {"Annual Variance", "0.013"},
-            {"Information Ratio", "-6.652"},
-            {"Tracking Error", "0.125"},
-            {"Treynor Ratio", "-1.379"},
+            {"Alpha", "-0.169"},
+            {"Beta", "0.073"},
+            {"Annual Standard Deviation", "0.028"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-6.684"},
+            {"Tracking Error", "0.099"},
+            {"Treynor Ratio", "-1.771"},
             {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$13000000.00"},
+            {"Estimated Strategy Capacity", "$3000.00"},
             {"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
-            {"Fitness Score", "0.039"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.763"},
-            {"Return Over Maximum Drawdown", "-9.371"},
-            {"Portfolio Turnover", "0.278"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "0668385036aba3e95127607dfc2f1a59"}
+            {"Portfolio Turnover", "23.97%"},
+            {"OrderListHash", "51f1bc2ea080df79748dc66c2520b782"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexDailyAlgorithm.cs

@@ -1,6 +1,24 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
 using System;
-using System.Collections.Generic;
+using System.Linq;
 using QuantConnect.Data;
+using System.Collections.Generic;
+using QuantConnect.Data.Market;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -12,10 +30,10 @@ namespace QuantConnect.Algorithm.CSharp
         protected override Resolution Resolution => Resolution.Daily;
         protected override int StartDay => 1;
 
-        // two complete weeks starting from the 5th plus the 18th bar
-        protected virtual int ExpectedBarCount => 2 * 5 + 1;
-        protected int BarCounter = 0;
-        
+        // two complete weeks starting from the 5th. The 18th bar is not included since it is a holiday
+        protected virtual int ExpectedBarCount => 2 * 5;
+        protected int BarCounter { get; set; }
+
         /// <summary>
         /// Purchase a contract when we are not invested, liquidate otherwise
         /// </summary>
@@ -30,7 +48,7 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 Liquidate();
             }
-            
+
             // Count how many slices we receive with SPX data in it to assert later
             if (slice.ContainsKey(Spx))
             {
@@ -44,6 +62,35 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 throw new ArgumentException($"Bar Count {BarCounter} is not expected count of {ExpectedBarCount}");
             }
+            AssertIndicators();
+
+            if (Resolution != Resolution.Daily)
+            {
+                return;
+            }
+
+            var openInterest = Securities[SpxOption].Cache.GetAll<OpenInterest>();
+            if (openInterest.Single().EndTime != new DateTime(2021, 1, 15, 23, 0, 0))
+            {
+                throw new ArgumentException($"Unexpected open interest time: {openInterest.Single().EndTime}");
+            }
+
+            foreach (var symbol in new[] { SpxOption, Spx })
+            {
+                var history = History(symbol, 10).ToList();
+                if (history.Count != 10)
+                {
+                    throw new RegressionTestException($"Unexpected history count: {history.Count}");
+                }
+                if (history.Any(x => x.Time.TimeOfDay != new TimeSpan(8, 30, 0)))
+                {
+                    throw new RegressionTestException($"Unexpected history data start time");
+                }
+                if (history.Any(x => x.EndTime.TimeOfDay != new TimeSpan(15, 15, 0)))
+                {
+                    throw new RegressionTestException($"Unexpected history data end time");
+                }
+            }
         }
 
         /// <summary>
@@ -54,65 +101,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 122;
+        public override long DataPoints => 121;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public override int AlgorithmHistoryDataPoints => 0;
+        public override int AlgorithmHistoryDataPoints => 30;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "9"},
+            {"Total Orders", "11"},
             {"Average Win", "0%"},
-            {"Average Loss", "-39.42%"},
-            {"Compounding Annual Return", "394.321%"},
-            {"Drawdown", "0.200%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "8.219%"},
-            {"Sharpe Ratio", "6.812"},
-            {"Probabilistic Sharpe Ratio", "91.380%"},
-            {"Loss Rate", "100%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "621.484%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1084600"},
+            {"Net Profit", "8.460%"},
+            {"Sharpe Ratio", "9.923"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "93.682%"},
+            {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "2.236"},
-            {"Beta", "-1.003"},
-            {"Annual Standard Deviation", "0.317"},
-            {"Annual Variance", "0.101"},
-            {"Information Ratio", "5.805"},
-            {"Tracking Error", "0.359"},
-            {"Treynor Ratio", "-2.153"},
+            {"Alpha", "3.61"},
+            {"Beta", "-0.513"},
+            {"Annual Standard Deviation", "0.359"},
+            {"Annual Variance", "0.129"},
+            {"Information Ratio", "8.836"},
+            {"Tracking Error", "0.392"},
+            {"Treynor Ratio", "-6.937"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
-            {"Fitness Score", "0.027"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "1776.081"},
-            {"Portfolio Turnover", "0.027"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "474e8e0e28ee84c869f8c69ec3efe371"}
+            {"Portfolio Turnover", "2.42%"},
+            {"OrderListHash", "61e8517ac3da6bed414ef23d26736fef"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexHourlyAlgorithm.cs

@@ -18,65 +18,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp };
+        public override List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 408;
+        public override long DataPoints => 401;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public override int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "70"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-0.23%"},
-            {"Compounding Annual Return", "-34.441%"},
-            {"Drawdown", "2.000%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-2.028%"},
-            {"Sharpe Ratio", "-11.139"},
-            {"Probabilistic Sharpe Ratio", "0.000%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.269"},
-            {"Beta", "0.086"},
-            {"Annual Standard Deviation", "0.023"},
-            {"Annual Variance", "0.001"},
-            {"Information Ratio", "-3.624"},
-            {"Tracking Error", "0.094"},
-            {"Treynor Ratio", "-3.042"},
+            {"Total Orders", "81"},
+            {"Average Win", "1.28%"},
+            {"Average Loss", "-0.06%"},
+            {"Compounding Annual Return", "-20.546%"},
+            {"Drawdown", "1.800%"},
+            {"Expectancy", "-0.402"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "990775"},
+            {"Net Profit", "-0.922%"},
+            {"Sharpe Ratio", "-2.903"},
+            {"Sortino Ratio", "-6.081"},
+            {"Probabilistic Sharpe Ratio", "22.230%"},
+            {"Loss Rate", "97%"},
+            {"Win Rate", "3%"},
+            {"Profit-Loss Ratio", "19.95"},
+            {"Alpha", "-0.157"},
+            {"Beta", "0.025"},
+            {"Annual Standard Deviation", "0.053"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-2.07"},
+            {"Tracking Error", "0.121"},
+            {"Treynor Ratio", "-6.189"},
             {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$310000.00"},
+            {"Estimated Strategy Capacity", "$300000.00"},
             {"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
-            {"Fitness Score", "0.002"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-14.51"},
-            {"Return Over Maximum Drawdown", "-17.213"},
-            {"Portfolio Turnover", "0.299"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "3eb56c551f20e2ffa1c56c47c5ee6667"}
+            {"Portfolio Turnover", "24.63%"},
+            {"OrderListHash", "44325fc1fdebb8e54f64a3f6e8a4bcd7"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexOptionsAlgorithm.cs

@@ -14,7 +14,6 @@
  *
 */
 
-using System;
 using QuantConnect.Data;
 using System.Collections.Generic;
 using QuantConnect.Indicators;
@@ -48,8 +47,10 @@ namespace QuantConnect.Algorithm.CSharp
             var spxOptions = AddIndexOption(_spx, Resolution);
             spxOptions.SetFilter(filterFunc => filterFunc.CallsOnly());
 
-            _emaSlow = EMA(_spx, 80);
-            _emaFast = EMA(_spx, 200);
+            _emaSlow = EMA(_spx, Resolution > Resolution.Minute ? 6 : 80);
+            _emaFast = EMA(_spx, Resolution > Resolution.Minute ? 2 : 200);
+
+            Settings.DailyPreciseEndTime = true;
         }
 
         /// <summary>
@@ -102,12 +103,13 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (Portfolio[_spx].TotalSaleVolume > 0)
             {
-                throw new Exception("Index is not tradable.");
+                throw new RegressionTestException("Index is not tradable.");
             }
             if (Portfolio.TotalSaleVolume == 0)
             {
-                throw new Exception("Trade volume should be greater than zero by the end of this algorithm");
+                throw new RegressionTestException("Trade volume should be greater than zero by the end of this algorithm");
             }
+            AssertIndicators();
         }
 
         public Symbol InvertOption(Symbol symbol)
@@ -121,6 +123,18 @@ namespace QuantConnect.Algorithm.CSharp
                 symbol.ID.Date);
         }
 
+        /// <summary>
+        /// Asserts indicators are ready
+        /// </summary>
+        /// <exception cref="RegressionTestException"></exception>
+        protected void AssertIndicators()
+        {
+            if (!_emaSlow.IsReady || !_emaFast.IsReady)
+            {
+                throw new RegressionTestException("Indicators are not ready!");
+            }
+        }
+
         /// <summary>
         /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
         /// </summary>
@@ -129,7 +143,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -141,12 +155,17 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public virtual int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "8220"},
+            {"Total Orders", "8220"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
             {"Compounding Annual Return", "-100.000%"},

Algorithm.CSharp/BasicTemplateIndexOptionsDailyAlgorithm.cs

@@ -14,10 +14,9 @@
  *
 */
 
-using System;
-using System.Collections.Generic;
 using System.Linq;
 using QuantConnect.Data;
+using System.Collections.Generic;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -63,65 +62,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp };
+        public override List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 381;
+        public override long DataPoints => 356;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public override int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "9"},
+            {"Total Orders", "11"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-0.091%"},
+            {"Compounding Annual Return", "-0.092%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "999920"},
             {"Net Profit", "-0.008%"},
-            {"Sharpe Ratio", "-4.033"},
+            {"Sharpe Ratio", "-19.865"},
+            {"Sortino Ratio", "-175397.15"},
             {"Probabilistic Sharpe Ratio", "0.013%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.001"},
+            {"Alpha", "-0.003"},
             {"Beta", "0"},
             {"Annual Standard Deviation", "0"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-0.447"},
-            {"Tracking Error", "0.136"},
-            {"Treynor Ratio", "-4.612"},
+            {"Information Ratio", "-0.454"},
+            {"Tracking Error", "0.138"},
+            {"Treynor Ratio", "-44.954"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "SPX XL80P59H5E6M|SPX 31"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-50718.291"},
-            {"Return Over Maximum Drawdown", "-11.386"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "5f5df233d68d9115a0d81785de54e71d"}
+            {"Portfolio Turnover", "0.00%"},
+            {"OrderListHash", "285cec32c0947f0e8cf90ccb672cfa43"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexOptionsHourlyAlgorithm.cs

@@ -33,65 +33,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp };
+        public override List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 2212;
+        public override long DataPoints => 1269;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public override int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "70"},
+            {"Total Orders", "81"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "0%"},
+            {"Compounding Annual Return", "-0.006%"},
             {"Drawdown", "0.000%"},
-            {"Expectancy", "0.000"},
-            {"Net Profit", "0%"},
-            {"Sharpe Ratio", "0"},
-            {"Probabilistic Sharpe Ratio", "36.504%"},
+            {"Expectancy", "-0.486"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "999995"},
+            {"Net Profit", "0.000%"},
+            {"Sharpe Ratio", "-101.77"},
+            {"Sortino Ratio", "-9053542.758"},
+            {"Probabilistic Sharpe Ratio", "17.439%"},
             {"Loss Rate", "97%"},
             {"Win Rate", "3%"},
-            {"Profit-Loss Ratio", "34.00"},
-            {"Alpha", "0"},
+            {"Profit-Loss Ratio", "17.50"},
+            {"Alpha", "-0.003"},
             {"Beta", "-0"},
             {"Annual Standard Deviation", "0"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-0.449"},
             {"Tracking Error", "0.138"},
-            {"Treynor Ratio", "-0"},
+            {"Treynor Ratio", "116.921"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "SPX XL80P59H5E6M|SPX 31"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "f21910eb98ceaa39e02020de95354d86"}
+            {"Portfolio Turnover", "0.00%"},
+            {"OrderListHash", "75e6584cb26058b09720c3a828b9fbda"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndiaAlgorithm.cs

@@ -56,7 +56,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {
@@ -80,7 +80,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -92,19 +92,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1"},
+            {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "-0.010%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99992.45"},
             {"Net Profit", "-0.008%"},
-            {"Sharpe Ratio", "-1.183"},
+            {"Sharpe Ratio", "-497.389"},
+            {"Sortino Ratio", "-73.22"},
             {"Probabilistic Sharpe Ratio", "0.001%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -119,26 +127,8 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "₹6.00"},
             {"Estimated Strategy Capacity", "₹61000000000.00"},
             {"Lowest Capacity Asset", "YESBANK UL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.247"},
-            {"Return Over Maximum Drawdown", "-1.104"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "₹0"},
-            {"Total Accumulated Estimated Alpha Value", "₹0"},
-            {"Mean Population Estimated Insight Value", "₹0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "6cc69218edd7bd461678b9ee0c575db5"}
+            {"Portfolio Turnover", "0.00%"},
+            {"OrderListHash", "7a0257f08e3bb9143b825e07ab47fea0"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndiaIndexAlgorithm.cs

@@ -31,8 +31,8 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="indexes" />
     public class BasicTemplateIndiaIndexAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        protected Symbol Nifty;
-        protected Symbol NiftyETF;
+        protected Symbol Nifty { get; set; }
+        protected Symbol NiftyETF { get; set; }
         private ExponentialMovingAverage _emaSlow;
         private ExponentialMovingAverage _emaFast;
 
@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (Portfolio[Nifty].TotalSaleVolume > 0)
             {
-                throw new Exception("Index is not tradable.");
+                throw new RegressionTestException("Index is not tradable.");
             }
         }
 
@@ -104,7 +104,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -116,19 +116,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "6"},
+            {"Total Orders", "6"},
             {"Average Win", "0%"},
             {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "-0.395%"},
+            {"Compounding Annual Return", "-0.386%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "999961.17"},
             {"Net Profit", "-0.004%"},
-            {"Sharpe Ratio", "-23.595"},
+            {"Sharpe Ratio", "-328.371"},
+            {"Sortino Ratio", "-328.371"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
@@ -141,28 +149,10 @@ namespace QuantConnect.Algorithm.CSharp
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
             {"Total Fees", "₹36.00"},
-            {"Estimated Strategy Capacity", "₹74000.00"},
+            {"Estimated Strategy Capacity", "₹84000.00"},
             {"Lowest Capacity Asset", "JUNIORBEES UL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-29.6"},
-            {"Return Over Maximum Drawdown", "-123.624"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "₹0"},
-            {"Total Accumulated Estimated Alpha Value", "₹0"},
-            {"Mean Population Estimated Insight Value", "₹0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "4637f26543287548b28a3c296db055d3"}
+            {"Portfolio Turnover", "0.04%"},
+            {"OrderListHash", "79ab9ec506959c562be8b3cdbb174c39"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIntrinioEconomicData.cs

@@ -32,8 +32,8 @@ namespace QuantConnect.Algorithm.CSharp
     public class BasicTemplateIntrinioEconomicData : QCAlgorithm
     {
         // Set your Intrinio user and password.
-        public string _user = "";
-        public string _password = "";
+        private string _user = string.Empty;
+        private string _password = string.Empty;
 
         private Symbol _uso; // United States Oil Fund LP
         private Symbol _bno; // United States Brent Oil Fund LP
@@ -81,9 +81,9 @@ namespace QuantConnect.Algorithm.CSharp
         ///     OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
-            var customData = data.Get<IntrinioEconomicData>();
+            var customData = slice.Get<IntrinioEconomicData>();
             if (customData.Count == 0) return;
 
             foreach (var economicData in customData.Values)
@@ -116,7 +116,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "91"},
+            {"Total Orders", "91"},
             {"Average Win", "0.09%"},
             {"Average Loss", "-0.01%"},
             {"Compounding Annual Return", "5.732%"},

Algorithm.CSharp/BasicTemplateOptionEquityStrategyAlgorithm.cs

@@ -32,7 +32,7 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="trading and orders" />
     public class BasicTemplateOptionEquityStrategyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        protected Symbol _optionSymbol;
+        private Symbol _optionSymbol;
 
         public override void Initialize()
         {
@@ -97,31 +97,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 884208;
+        public long DataPoints => 15023;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "3"},
+            {"Total Orders", "3"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "98024"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -133,29 +141,11 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$10.00"},
-            {"Estimated Strategy Capacity", "$84000.00"},
+            {"Total Fees", "$26.00"},
+            {"Estimated Strategy Capacity", "$69000.00"},
             {"Lowest Capacity Asset", "GOOCV W78ZERHAOVVQ|GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "82c29cc9db9a300074d6ff136253f4ac"}
+            {"Portfolio Turnover", "61.31%"},
+            {"OrderListHash", "35d406df401e5b27244e20f5ec57346e"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionStrategyAlgorithm.cs

@@ -107,31 +107,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 884616;
+        public long DataPoints => 15130;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "778"},
+            {"Total Orders", "420"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "952636.6"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -143,29 +151,11 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$778.00"},
-            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Total Fees", "$543.40"},
+            {"Estimated Strategy Capacity", "$4000.00"},
             {"Lowest Capacity Asset", "GOOCV W78ZFMEBBB2E|GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "6a88f302b7f29a2c59e4b1e978161da1"}
+            {"Portfolio Turnover", "338.60%"},
+            {"OrderListHash", "301c15063f6e269023d144ca69a765da"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsAlgorithm.cs

@@ -35,7 +35,7 @@ namespace QuantConnect.Algorithm.CSharp
     public class BasicTemplateOptionsAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
         private const string UnderlyingTicker = "GOOG";
-        public Symbol OptionSymbol;
+        private Symbol _optionSymbol;
 
         public override void Initialize()
         {
@@ -45,7 +45,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             var equity = AddEquity(UnderlyingTicker);
             var option = AddOption(UnderlyingTicker);
-            OptionSymbol = option.Symbol;
+            _optionSymbol = option.Symbol;
 
             // set our strike/expiry filter for this option chain
             option.SetFilter(u => u.Strikes(-2, +2)
@@ -64,10 +64,10 @@ namespace QuantConnect.Algorithm.CSharp
         /// <param name="slice">The current slice of data keyed by symbol string</param>
         public override void OnData(Slice slice)
         {
-            if (!Portfolio.Invested && IsMarketOpen(OptionSymbol))
+            if (!Portfolio.Invested && IsMarketOpen(_optionSymbol))
             {
                 OptionChain chain;
-                if (slice.OptionChains.TryGetValue(OptionSymbol, out chain))
+                if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
                 {
                     // we find at the money (ATM) put contract with farthest expiration
                     var atmContract = chain
@@ -104,31 +104,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 884197;
+        public long DataPoints => 15012;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99718"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -143,26 +151,8 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$2.00"},
             {"Estimated Strategy Capacity", "$1300000.00"},
             {"Lowest Capacity Asset", "GOOCV 30AKMEIPOSS1Y|GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9d9f9248ee8fe30d87ff0a6f6fea5112"}
+            {"Portfolio Turnover", "10.71%"},
+            {"OrderListHash", "8a36462ee0349c04d01d464e592dd347"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsConsolidationAlgorithm.cs

@@ -0,0 +1,151 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using QuantConnect.Data;
+using QuantConnect.Data.Consolidators;
+using QuantConnect.Data.Market;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+using System;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// A demonstration of consolidating options data into larger bars for your algorithm.
+    /// </summary>
+    public class BasicTemplateOptionsConsolidationAlgorithm: QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Dictionary<Symbol, IDataConsolidator> _consolidators = new();
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 7);
+            SetEndDate(2013, 10, 11);
+            SetCash(1000000);
+
+            var option = AddOption("SPY");
+            option.SetFilter(-2, 2, 0, 189);
+        }
+
+        public void OnQuoteBarConsolidated(object sender, QuoteBar quoteBar)
+        {
+            Log($"OnQuoteBarConsolidated called on {Time}");
+            Log(quoteBar.ToString());
+        }
+
+        public void OnTradeBarConsolidated(object sender, TradeBar tradeBar)
+        {
+            Log($"OnTradeBarConsolidated called on {Time}");
+            Log(tradeBar.ToString());
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            foreach(var security in changes.AddedSecurities)
+            {
+                IDataConsolidator consolidator;
+                if (security.Type == SecurityType.Equity)
+                {
+                    consolidator = new TradeBarConsolidator(TimeSpan.FromMinutes(5));
+                    (consolidator as TradeBarConsolidator).DataConsolidated += OnTradeBarConsolidated;
+                }
+                else
+                {
+                    consolidator = new QuoteBarConsolidator(new TimeSpan(0, 5, 0));
+                    (consolidator as QuoteBarConsolidator).DataConsolidated += OnQuoteBarConsolidated;
+                }
+
+                SubscriptionManager.AddConsolidator(security.Symbol, consolidator);
+                _consolidators[security.Symbol] = consolidator;
+            }
+
+            foreach(var security in changes.RemovedSecurities)
+            {
+                _consolidators.Remove(security.Symbol, out var consolidator);
+                SubscriptionManager.RemoveConsolidator(security.Symbol, consolidator);
+
+                if (security.Type == SecurityType.Equity)
+                {
+                    (consolidator as TradeBarConsolidator).DataConsolidated -= OnTradeBarConsolidated;
+                }
+                else
+                {
+                    (consolidator as QuoteBarConsolidator).DataConsolidated -= OnQuoteBarConsolidated;
+                }
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 3943;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1000000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-8.91"},
+            {"Tracking Error", "0.223"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateOptionsDailyAlgorithm.cs

@@ -34,21 +34,21 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="filter selection" />
     public class BasicTemplateOptionsDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private const string UnderlyingTicker = "GOOG";
-        public Symbol OptionSymbol;
+        private const string UnderlyingTicker = "AAPL";
+        private Symbol _optionSymbol;
         private bool _optionExpired;
 
         public override void Initialize()
         {
-            SetStartDate(2015, 12, 23);
-            SetEndDate(2016, 1, 20);
+            SetStartDate(2015, 12, 15);
+            SetEndDate(2016, 2, 1);
             SetCash(100000);
 
             var equity = AddEquity(UnderlyingTicker, Resolution.Daily);
             var option = AddOption(UnderlyingTicker, Resolution.Daily);
-            OptionSymbol = option.Symbol;
+            _optionSymbol = option.Symbol;
 
-            option.SetFilter(x => x.CallsOnly().Strikes(0, 1).Expiration(0, 30));
+            option.SetFilter(x => x.CallsOnly().Expiration(0, 60));
 
             // use the underlying equity as the benchmark
             SetBenchmark(equity.Symbol);
@@ -63,13 +63,13 @@ namespace QuantConnect.Algorithm.CSharp
             if (!Portfolio.Invested)
             {
                 OptionChain chain;
-                if (slice.OptionChains.TryGetValue(OptionSymbol, out chain))
+                if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
                 {
                     // Grab us the contract nearest expiry that is not today
                     var contractsByExpiration = chain.Where(x => x.Expiry != Time.Date).OrderBy(x => x.Expiry);
                     var contract = contractsByExpiration.FirstOrDefault();
 
-                    if (contract != null && IsMarketOpen(contract.Symbol))
+                    if (contract != null)
                     {
                         // if found, trade it
                         MarketOrder(contract.Symbol, 1);
@@ -88,7 +88,7 @@ namespace QuantConnect.Algorithm.CSharp
             Log(orderEvent.ToString());
 
             // Check for our expected OTM option expiry
-            if (orderEvent.Message == "OTM")
+            if (orderEvent.Message.Contains("OTM", StringComparison.InvariantCulture))
             {
                 // Assert it is at midnight (5AM UTC)
                 if (orderEvent.UtcTime != new DateTime(2016, 1, 16, 5, 0, 0))
@@ -117,65 +117,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 39654;
+        public long DataPoints => 308;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
-            {"Average Loss", "-1.31%"},
-            {"Compounding Annual Return", "-15.304%"},
-            {"Drawdown", "1.300%"},
+            {"Average Loss", "-1.16%"},
+            {"Compounding Annual Return", "-8.351%"},
+            {"Drawdown", "1.200%"},
             {"Expectancy", "-1"},
-            {"Net Profit", "-1.311%"},
-            {"Sharpe Ratio", "-3.31"},
-            {"Probabilistic Sharpe Ratio", "0.035%"},
+            {"Start Equity", "100000"},
+            {"End Equity", "98844"},
+            {"Net Profit", "-1.156%"},
+            {"Sharpe Ratio", "-4.04"},
+            {"Sortino Ratio", "-2.422"},
+            {"Probabilistic Sharpe Ratio", "0.099%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0"},
-            {"Beta", "0"},
-            {"Annual Standard Deviation", "0.034"},
-            {"Annual Variance", "0.001"},
-            {"Information Ratio", "-3.31"},
-            {"Tracking Error", "0.034"},
-            {"Treynor Ratio", "0"},
+            {"Alpha", "-0.058"},
+            {"Beta", "0.021"},
+            {"Annual Standard Deviation", "0.017"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "1.49"},
+            {"Tracking Error", "0.289"},
+            {"Treynor Ratio", "-3.212"},
             {"Total Fees", "$1.00"},
-            {"Estimated Strategy Capacity", "$18000.00"},
-            {"Lowest Capacity Asset", "GOOCV W78ZFMML01JA|GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.496"},
-            {"Return Over Maximum Drawdown", "-11.673"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "c6d089f1fb86379c74a7413a9c2f8553"}
+            {"Estimated Strategy Capacity", "$72000.00"},
+            {"Lowest Capacity Asset", "AAPL W78ZEO2985GM|AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "0.02%"},
+            {"OrderListHash", "b3125e0af79da0f5eea4cfda09806324"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsFilterUniverseAlgorithm.cs

@@ -14,7 +14,6 @@
  *
 */
 
-using System;
 using System.Collections.Generic;
 using System.Linq;
 using QuantConnect.Data;
@@ -36,7 +35,7 @@ namespace QuantConnect.Algorithm.CSharp
     public class BasicTemplateOptionsFilterUniverseAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
         private const string UnderlyingTicker = "GOOG";
-        public Symbol OptionSymbol;
+        private Symbol _optionSymbol;
 
         public override void Initialize()
         {
@@ -46,7 +45,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             var equity = AddEquity(UnderlyingTicker);
             var option = AddOption(UnderlyingTicker);
-            OptionSymbol = option.Symbol;
+            _optionSymbol = option.Symbol;
 
             // Set our custom universe filter, Expires today, is a call, and is within 10 dollars of the current price
             option.SetFilter(universe => from symbol in universe.WeeklysOnly().Expiration(0, 1)
@@ -64,7 +63,7 @@ namespace QuantConnect.Algorithm.CSharp
             if (!Portfolio.Invested)
             {
                 OptionChain chain;
-                if (slice.OptionChains.TryGetValue(OptionSymbol, out chain))
+                if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
                 {
                     // Get the first ITM call expiring today
                     var contract = (
@@ -95,31 +94,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 1722373;
+        public long DataPoints => 12290;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.40%"},
-            {"Compounding Annual Return", "-21.622%"},
+            {"Compounding Annual Return", "-20.338%"},
             {"Drawdown", "0.300%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99689"},
             {"Net Profit", "-0.311%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
@@ -134,26 +141,8 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$1.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0.188"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-73.268"},
-            {"Portfolio Turnover", "0.376"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "452e7a36e0a95e33d3457a908add3ead"}
+            {"Portfolio Turnover", "15.08%"},
+            {"OrderListHash", "db6a1134ad325bce31c2bdd2e87ff5f4"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsFrameworkAlgorithm.cs

@@ -134,65 +134,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 990979;
+        public long DataPoints => 17486;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "4"},
-            {"Average Win", "0.14%"},
-            {"Average Loss", "-0.28%"},
-            {"Compounding Annual Return", "0%"},
-            {"Drawdown", "385.400%"},
-            {"Expectancy", "-0.249"},
-            {"Net Profit", "-386.489%"},
-            {"Sharpe Ratio", "-0.033"},
-            {"Probabilistic Sharpe Ratio", "1.235%"},
-            {"Loss Rate", "50%"},
-            {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.50"},
-            {"Alpha", "-95.983"},
-            {"Beta", "263.726"},
-            {"Annual Standard Deviation", "30.617"},
-            {"Annual Variance", "937.371"},
-            {"Information Ratio", "-0.044"},
-            {"Tracking Error", "30.604"},
-            {"Treynor Ratio", "-0.004"},
-            {"Total Fees", "$3.00"},
+            {"Total Orders", "5"},
+            {"Average Win", "0.13%"},
+            {"Average Loss", "-0.30%"},
+            {"Compounding Annual Return", "-46.395%"},
+            {"Drawdown", "1.600%"},
+            {"Expectancy", "0.429"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99149.50"},
+            {"Net Profit", "-0.850%"},
+            {"Sharpe Ratio", "-4.298"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "15.319%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
+            {"Profit-Loss Ratio", "0.43"},
+            {"Alpha", "-0.84"},
+            {"Beta", "0.986"},
+            {"Annual Standard Deviation", "0.098"},
+            {"Annual Variance", "0.01"},
+            {"Information Ratio", "-9.299"},
+            {"Tracking Error", "0.091"},
+            {"Treynor Ratio", "-0.428"},
+            {"Total Fees", "$4.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0.168"},
-            {"Kelly Criterion Estimate", "0.327"},
-            {"Kelly Criterion Probability Value", "1"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0.224"},
-            {"Total Insights Generated", "28"},
-            {"Total Insights Closed", "24"},
-            {"Total Insights Analysis Completed", "24"},
-            {"Long Insight Count", "28"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$13.64796"},
-            {"Total Accumulated Estimated Alpha Value", "$1.89555"},
-            {"Mean Population Estimated Insight Value", "$0.07898125"},
-            {"Mean Population Direction", "50%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "50.0482%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "87603bd45898dd9c456745fa51f989a5"}
+            {"Portfolio Turnover", "13.50%"},
+            {"OrderListHash", "cf14a7ce9c86e6844051820fd4c9394c"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsHourlyAlgorithm.cs

@@ -35,7 +35,7 @@ namespace QuantConnect.Algorithm.CSharp
     public class BasicTemplateOptionsHourlyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
         private const string UnderlyingTicker = "AAPL";
-        public Symbol OptionSymbol;
+        private Symbol _optionSymbol;
 
         public override void Initialize()
         {
@@ -45,7 +45,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             var equity = AddEquity(UnderlyingTicker, Resolution.Hour);
             var option = AddOption(UnderlyingTicker, Resolution.Hour);
-            OptionSymbol = option.Symbol;
+            _optionSymbol = option.Symbol;
 
             // set our strike/expiry filter for this option chain
             option.SetFilter(u => u.Strikes(-2, +2)
@@ -64,10 +64,10 @@ namespace QuantConnect.Algorithm.CSharp
         /// <param name="slice">The current slice of data keyed by symbol string</param>
         public override void OnData(Slice slice)
         {
-            if (!Portfolio.Invested && IsMarketOpen(OptionSymbol))
+            if (!Portfolio.Invested && IsMarketOpen(_optionSymbol))
             {
                 OptionChain chain;
-                if (slice.OptionChains.TryGetValue(OptionSymbol, out chain))
+                if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
                 {
                     // we find at the money (ATM) put contract with farthest expiration
                     var atmContract = chain
@@ -104,65 +104,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 32492;
+        public long DataPoints => 9504;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "4"},
+            {"Total Orders", "5"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.07%"},
-            {"Compounding Annual Return", "-12.496%"},
+            {"Compounding Annual Return", "-11.517%"},
             {"Drawdown", "0.200%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99866"},
             {"Net Profit", "-0.134%"},
-            {"Sharpe Ratio", "-8.839"},
+            {"Sharpe Ratio", "-9.78"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.083"},
+            {"Alpha", "0.075"},
             {"Beta", "-0.054"},
             {"Annual Standard Deviation", "0.008"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-18.699"},
             {"Tracking Error", "0.155"},
-            {"Treynor Ratio", "1.296"},
+            {"Treynor Ratio", "1.434"},
             {"Total Fees", "$4.00"},
             {"Estimated Strategy Capacity", "$1000.00"},
             {"Lowest Capacity Asset", "AAPL 2ZTXYMUAHCIAU|AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0.04"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-118.28"},
-            {"Portfolio Turnover", "0.081"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "81e8a822d43de2165c1d3f52964ec312"}
+            {"Portfolio Turnover", "2.28%"},
+            {"OrderListHash", "7804b3dcf20d3096a2265a289fa81cd3"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateSPXWeeklyIndexOptionsAlgorithm.cs

@@ -0,0 +1,152 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+using QuantConnect.Interfaces;
+using QuantConnect.Data.Market;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add and trade SPX index weekly options
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="options" />
+    /// <meta name="tag" content="indexes" />
+    public class BasicTemplateSPXWeeklyIndexOptionsAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _spxOption;
+
+        /// <summary>
+        /// Initialize your algorithm and add desired assets.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2021, 1, 4);
+            SetEndDate(2021, 1, 10);
+            SetCash(1000000);
+
+            // regular option SPX contracts
+            var spxOptions = AddIndexOption("SPX");
+            spxOptions.SetFilter(u => u.Strikes(0, 1).Expiration(0, 30));
+
+            // weekly option SPX contracts
+            var spxw = AddIndexOption("SPX", "SPXW");
+            spxw.SetFilter(u => u.Strikes(0, 1)
+                 // single week ahead since there are many SPXW contracts and we want to preserve performance
+                 .Expiration(0, 7)
+                 .IncludeWeeklys());
+
+            _spxOption = spxw.Symbol;
+        }
+
+        /// <summary>
+        /// Index EMA Cross trading underlying.
+        /// </summary>
+        public override void OnData(Slice slice)
+        {
+            if (Portfolio.Invested)
+            {
+                return;
+            }
+
+            OptionChain chain;
+            if (slice.OptionChains.TryGetValue(_spxOption, out chain))
+            {
+                // we find at the money (ATM) put contract with closest expiration
+                var atmContract = chain
+                    .OrderBy(x => x.Expiry)
+                    .ThenBy(x => Math.Abs(chain.Underlying.Price - x.Strike))
+                    .ThenByDescending(x => x.Right)
+                    .FirstOrDefault();
+
+                if (atmContract != null)
+                {
+                    // if found, buy until it expires
+                    MarketOrder(atmContract.Symbol, 1);
+                }
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug(orderEvent.ToString());
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public virtual bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 21467;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "5"},
+            {"Average Win", "0%"},
+            {"Average Loss", "-0.69%"},
+            {"Compounding Annual Return", "54.478%"},
+            {"Drawdown", "0.400%"},
+            {"Expectancy", "-0.5"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1006025"},
+            {"Net Profit", "0.602%"},
+            {"Sharpe Ratio", "2.62"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "63.221%"},
+            {"Loss Rate", "50%"},
+            {"Win Rate", "50%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.067"},
+            {"Beta", "-0.013"},
+            {"Annual Standard Deviation", "0.004"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-50.808"},
+            {"Tracking Error", "0.086"},
+            {"Treynor Ratio", "-0.725"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$580000.00"},
+            {"Lowest Capacity Asset", "SPXW 31K54PVWHUJHQ|SPX 31"},
+            {"Portfolio Turnover", "0.40%"},
+            {"OrderListHash", "07a085baedb37bb7c8d460558ea77e88"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateSPXWeeklyIndexOptionsStrategyAlgorithm.cs

@@ -0,0 +1,158 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+using QuantConnect.Interfaces;
+using QuantConnect.Data.Market;
+using System.Collections.Generic;
+using QuantConnect.Securities.Option;
+using System;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add and trade SPX index weekly option strategy
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="options" />
+    /// <meta name="tag" content="indexes" />
+    public class BasicTemplateSPXWeeklyIndexOptionsStrategyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _spxOption;
+
+        /// <summary>
+        /// Initialize your algorithm and add desired assets.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2021, 1, 4);
+            SetEndDate(2021, 1, 10);
+            SetCash(1000000);
+
+            var spx = AddIndex("SPX").Symbol;
+
+            // weekly option SPX contracts
+            var spxw = AddIndexOption(spx, "SPXW");
+            spxw.SetFilter(u => u.Strikes(-1, +1)
+                 // single week ahead since there are many SPXW contracts and we want to preserve performance
+                 .Expiration(0, 7)
+                 .IncludeWeeklys());
+
+            _spxOption = spxw.Symbol;
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (Portfolio.Invested)
+            {
+                return;
+            }
+
+            OptionChain chain;
+            if (slice.OptionChains.TryGetValue(_spxOption, out chain))
+            {
+                // we find the first expiration group of call options and order them in ascending strike
+                var contracts = chain
+                    .Where(x => x.Right == OptionRight.Call)
+                    .OrderBy(x => x.Expiry)
+                    .GroupBy(x => x.Expiry)
+                    .First()
+                    .OrderBy(x => x.Strike)
+                    .ToList();
+
+                if (contracts.Count > 1)
+                {
+                    var smallerStrike = contracts[0];
+                    var higherStrike = contracts[1];
+
+                    // if found, buy until it expires
+                    var optionStrategy = OptionStrategies.BearCallSpread(_spxOption, smallerStrike.Strike, higherStrike.Strike, smallerStrike.Expiry);
+                    Buy(optionStrategy, 1);
+                }
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug(orderEvent.ToString());
+            if (orderEvent.Symbol.ID.Symbol != "SPXW")
+            {
+                throw new RegressionTestException("Unexpected order event symbol!");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public virtual bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 16680;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "10"},
+            {"Average Win", "0.47%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "101.998%"},
+            {"Drawdown", "0.100%"},
+            {"Expectancy", "24.484"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1009050"},
+            {"Net Profit", "0.905%"},
+            {"Sharpe Ratio", "8.44"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "95.546%"},
+            {"Loss Rate", "50%"},
+            {"Win Rate", "50%"},
+            {"Profit-Loss Ratio", "49.97"},
+            {"Alpha", "-2.01"},
+            {"Beta", "0.307"},
+            {"Annual Standard Deviation", "0.021"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-144.654"},
+            {"Tracking Error", "0.048"},
+            {"Treynor Ratio", "0.589"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$13000000.00"},
+            {"Lowest Capacity Asset", "SPXW XKX6S2GM9PGU|SPX 31"},
+            {"Portfolio Turnover", "0.28%"},
+            {"OrderListHash", "c1a9bc141ae25c9542b93a887e79dafe"}
+        };
+    }
+}