Add optimization-id for optimization backtests (#7202)

* add organizatin-id in backtests

* self review

.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/benchmarks.yml

@@ -0,0 +1,39 @@
+name: Benchmarks
+
+on:
+  push:
+    branches: ['*']
+    tags: ['*']
+  pull_request:
+    branches: [master]
+
+jobs:
+  build:
+    runs-on: self-hosted
+    container:
+        image: quantconnect/lean:foundation
+        volumes:
+          - /nas:/Data
+    steps:
+      - uses: actions/checkout@v2
+
+      - name: Checkout Lean Master
+        uses: actions/checkout@v2
+        with:
+          repository: QuantConnect/Lean
+          path: LeanMaster
+          ref: 'master'
+      - name: Build Lean Master
+        run: dotnet build --verbosity q /p:Configuration=Release /p:WarningLevel=1 LeanMaster/QuantConnect.Lean.sln
+
+      - name: Run Benchmarks Master
+        run: cp run_benchmarks.py LeanMaster/run_benchmarks.py && cd LeanMaster && python run_benchmarks.py /Data && cd ../
+
+      - name: Build
+        run: dotnet build --verbosity q /p:Configuration=Release /p:WarningLevel=1 QuantConnect.Lean.sln
+
+      - name: Run Benchmarks
+        run: python run_benchmarks.py /Data
+
+      - name: Compare Benchmarks
+        run: python compare_benchmarks.py LeanMaster/benchmark_results.json benchmark_results.json

.github/workflows/gh-actions.yml

@@ -19,7 +19,7 @@ jobs:
         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 -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\)
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --blame-hang-timeout 300seconds --blame-crash --filter "TestCategory!=TravisExclude&TestCategory!=ResearchRegressionTests" -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\)
 
       - name: Generate & Publish python stubs
         if: startsWith(github.ref, 'refs/tags/')
@@ -28,3 +28,5 @@ jobs:
           ./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 }}

.github/workflows/rebase-org-branches.yml

@@ -0,0 +1,21 @@
+name: Rebase Organization Branches
+
+on:
+  push:
+    branches:
+      - 'master'
+
+jobs:
+  build:
+    runs-on: ubuntu-20.04
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+
+      - name: Rebase Organization Branches
+        run: |
+          chmod +x rebase_organization_branches.sh
+          ./rebase_organization_branches.sh
+        env:
+          QC_GIT_TOKEN: ${{ secrets.QC_GIT_TOKEN }}

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

@@ -0,0 +1,35 @@
+name: Research Regression Tests
+
+on:
+  push:
+    branches: ['*']
+    tags: ['*']
+  pull_request:
+    branches: [master]
+
+jobs:
+  build:
+    runs-on: ubuntu-20.04
+    container:
+        image: quantconnect/lean:foundation
+    steps:
+      - uses: actions/checkout@v2
+
+      - 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\(name=\"reduced-disk-size\", value=\"true\"\)

.github/workflows/virtual-environments.yml

@@ -0,0 +1,70 @@
+name: Python Virtual Environments
+
+on:
+  push:
+    branches: ['*']
+    tags: ['*']
+  pull_request:
+    branches: [master]
+
+jobs:
+  build:
+    runs-on: ubuntu-20.04
+    container:
+        image: quantconnect/lean:foundation
+    steps:
+      - uses: actions/checkout@v2
+
+      - 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" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run Pomegranate & Tigramite Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.PomegranateTest|Tigramite" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run StableBaselines Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.StableBaselinesTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run AxPlatform Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.AxPlatformTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run NBeats Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.NBeatsTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run TensorlyTest Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorlyTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run NeuralTangents, Ignite Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.NeuralTangentsTest|IgniteTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run TensorflowTest
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorflowTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run TensorflowProbability
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorflowProbabilityTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run Hvplot Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.HvplotTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run Hvplot Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.StellargraphTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run Keras Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.KerasTest" --blame-hang-timeout 120seconds --blame-crash
+
+      - name: Run Keras Python Package Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.ScikerasTest" --blame-hang-timeout 120seconds --blame-crash

.vs/readme.md

@@ -18,10 +18,10 @@ To use Lean CLI follow the instructions for installation and tutorial for usage
 
 <h2>Option 2: Install Locally</h2>
 
-1. Install [.Net 5](https://dotnet.microsoft.com/download) for the project
+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

@@ -3,13 +3,13 @@
         VS Code Launch configurations for the LEAN engine
 
         Launch:
-        Builds the project with dotnet 5 and then launches the program using coreclr; supports debugging.
-        In order to use this you need dotnet 5 on your system path, As well as the C# extension from the 
+        Builds the project with dotnet 6 and then launches the program using coreclr; supports debugging.
+        In order to use this you need dotnet 6 on your system path, As well as the C# extension from the 
         marketplace.
 
         Attach to Python:
-        Will attempt to attach to LEAN running locally using PTVSD. Requires that the process is
-        actively running and config is set: "debugging": true, "debugging-method": "PTVSD",
+        Will attempt to attach to LEAN running locally using DebugPy. Requires that the process is
+        actively running and config is set: "debugging": true, "debugging-method": "DebugPy",
         Requires Python extension from the marketplace. Currently only works with algorithms in
         Algorithm.Python directory. This is because we map that directory to our build directory
         that contains the py file at runtime. If using another location change "localRoot" value 
@@ -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 5](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 />
@@ -95,7 +127,7 @@ Python algorithms require a little extra work in order to be able to debug them.
 First in order to debug a Python algorithm in VS Code we must make the following change to our configuration (Launcher\config.json) under the comment debugging configuration:
 
     "debugging": true,
-    "debugging-method": "PTVSD",
+    "debugging-method": "DebugPy",
 
 In setting this we are telling Lean to expect a debugger connection using ‘Python Tools for Visual Studio Debugger’. Once this is set Lean will stop upon initialization and await a connection to the debugger via port 5678.
 
@@ -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

@@ -69,6 +69,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { 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>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -96,25 +106,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "119.89%"},
             {"OrderListHash", "3c4c4085810cc5ecdb927d3647b9bbf3"}
         };
     }

Algorithm.CSharp/AddAlphaModelAlgorithm.cs

@@ -105,6 +105,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 58;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -117,40 +127,22 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "1.700%"},
             {"Expectancy", "1.781"},
             {"Net Profit", "1.442%"},
-            {"Sharpe Ratio", "4.017"},
-            {"Probabilistic Sharpe Ratio", "59.636%"},
+            {"Sharpe Ratio", "4.86"},
+            {"Probabilistic Sharpe Ratio", "59.497%"},
             {"Loss Rate", "33%"},
             {"Win Rate", "67%"},
             {"Profit-Loss Ratio", "3.17"},
-            {"Alpha", "1.53"},
-            {"Beta", "-0.292"},
-            {"Annual Standard Deviation", "0.279"},
-            {"Annual Variance", "0.078"},
-            {"Information Ratio", "-0.743"},
-            {"Tracking Error", "0.372"},
-            {"Treynor Ratio", "-3.845"},
+            {"Alpha", "4.181"},
+            {"Beta", "-1.322"},
+            {"Annual Standard Deviation", "0.321"},
+            {"Annual Variance", "0.103"},
+            {"Information Ratio", "-0.795"},
+            {"Tracking Error", "0.532"},
+            {"Treynor Ratio", "-1.18"},
             {"Total Fees", "$14.78"},
             {"Estimated Strategy Capacity", "$47000000.00"},
             {"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%"},
+            {"Portfolio Turnover", "41.18%"},
             {"OrderListHash", "9da9afe1e9137638a55db1676adc2be1"}
         };
     }

Algorithm.CSharp/AddAndRemoveOptionContractRegressionAlgorithm.cs

@@ -82,6 +82,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 24;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -103,31 +113,13 @@ namespace QuantConnect.Algorithm.CSharp
             {"Beta", "0"},
             {"Annual Standard Deviation", "0"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "0"},
-            {"Tracking Error", "0"},
+            {"Information Ratio", "-9.486"},
+            {"Tracking Error", "0.008"},
             {"Treynor Ratio", "0"},
             {"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

@@ -0,0 +1,123 @@
+/*
+ * 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.Interfaces;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm reproducing GH issue #5971 where we add and remove an option in the same loop
+    /// </summary>
+    public class AddAndRemoveSecuritySameLoopRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _contract;
+        private bool _hasRemoved;
+
+        public override void Initialize()
+        {
+            SetStartDate(2014, 06, 06);
+            SetEndDate(2014, 06, 09);
+
+            UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
+            UniverseSettings.MinimumTimeInUniverse = TimeSpan.Zero;
+
+            var aapl = AddEquity("AAPL").Symbol;
+
+            _contract = OptionChainProvider.GetOptionContractList(aapl, Time)
+                .OrderBy(symbol => symbol.ID.Symbol)
+                .FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
+                    && optionContract.ID.OptionStyle == OptionStyle.American);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (_hasRemoved)
+            {
+                throw new Exception("Expect a single call to OnData where we removed the option and underlying");
+            }
+
+            _hasRemoved = true;
+            AddOptionContract(_contract);
+
+            // changed my mind!
+            RemoveOptionContract(_contract);
+            RemoveSecurity(_contract.Underlying);
+
+            RemoveSecurity(AddEquity("SPY", Resolution.Daily).Symbol);
+        }
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_hasRemoved)
+            {
+                throw new Exception("We did not remove the option contract!");
+            }
+        }
+
+        /// <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 => 24;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe 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", "-9.486"},
+            {"Tracking Error", "0.008"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/AddBetaIndicatorRegressionAlgorithm.cs

@@ -0,0 +1,143 @@
+/*
+ * 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.Indicators;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression test to explain how Beta indicator works
+    /// </summary>
+    public class AddBetaIndicatorRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Beta _beta;
+        private SimpleMovingAverage _sma;
+        private decimal _lastSMAValue;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 07);
+            SetEndDate(2013, 10, 15);
+            SetCash(10000);
+
+            AddEquity("IBM");
+            AddEquity("SPY");
+
+            EnableAutomaticIndicatorWarmUp = true;
+            _beta = B("IBM", "SPY", 3, Resolution.Daily);
+            _sma = SMA("SPY", 3, Resolution.Daily);
+            _lastSMAValue = 0;
+
+            if (!_beta.IsReady)
+            {
+                throw new Exception("_beta indicator was expected to be ready");
+            }
+        }
+
+        public override void OnData(Slice data)
+        {
+            if (!Portfolio.Invested)
+            {
+                var price = data["IBM"].Close;
+                Buy("IBM", 10);
+                LimitOrder("IBM", 10, price * 0.1m);
+                StopMarketOrder("IBM", 10, price / 0.1m);
+            }
+            
+            if (_beta.Current.Value < 0m || _beta.Current.Value > 2.80m)
+            {
+                throw new Exception($"_beta value was expected to be between 0 and 2.80 but was {_beta.Current.Value}");
+            }
+
+            Log($"Beta between IBM and SPY is: {_beta.Current.Value}");
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            var order = Transactions.GetOrderById(orderEvent.OrderId);
+            var goUpwards = _lastSMAValue < _sma.Current.Value;
+            _lastSMAValue = _sma.Current.Value;
+
+            if (order.Status == OrderStatus.Filled)
+            {
+                if (order.Type == OrderType.Limit && Math.Abs(_beta.Current.Value - 1) < 0.2m && goUpwards)
+                {
+                    Transactions.CancelOpenOrders(order.Symbol);
+                }
+            }
+
+            if (order.Status == OrderStatus.Canceled)
+            {
+                Log(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 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 Language[] Languages { get; } = { Language.CSharp};
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 10977;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 11;
+
+        /// <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"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "12.939%"},
+            {"Drawdown", "0.300%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0.289%"},
+            {"Sharpe Ratio", "4.233"},
+            {"Probabilistic Sharpe Ratio", "68.349%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.035"},
+            {"Beta", "0.122"},
+            {"Annual Standard Deviation", "0.024"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-3.181"},
+            {"Tracking Error", "0.142"},
+            {"Treynor Ratio", "0.842"},
+            {"Total Fees", "$1.00"},
+            {"Estimated Strategy Capacity", "$35000000.00"},
+            {"Lowest Capacity Asset", "IBM R735QTJ8XC9X"},
+            {"Portfolio Turnover", "1.51%"},
+            {"OrderListHash", "bd88c6a0e10c7e146b05377205101a12"}
+        };
+    }
+}

Algorithm.CSharp/AddFutureContractWithContinuousRegressionAlgorithm.cs

@@ -0,0 +1,157 @@
+/*
+ * 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.Securities;
+using System.Collections.Generic;
+using QuantConnect.Securities.Future;
+using QuantConnect.Data.UniverseSelection;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Continuous Futures Regression algorithm. Asserting and showcasing the behavior of adding a continuous future
+    /// and a future contract at the same time
+    /// </summary>
+    public class AddFutureContractWithContinuousRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _currentMappedSymbol;
+        private Future _continuousContract;
+        private Future _futureContract;
+        private bool _ended;
+
+        /// <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, 6);
+            SetEndDate(2013, 10, 10);
+
+            _continuousContract = AddFuture(Futures.Indices.SP500EMini,
+                dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
+                dataMappingMode: DataMappingMode.LastTradingDay,
+                contractDepthOffset: 0
+            );
+
+            _futureContract = AddFutureContract(FutureChainProvider.GetFutureContractList(_continuousContract.Symbol, Time).First());
+        }
+
+        /// <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)
+        {
+            if (_ended)
+            {
+                throw new Exception($"Algorithm should of ended!");
+            }
+            if (data.Keys.Count > 2)
+            {
+                throw new Exception($"Getting data for more than 2 symbols! {string.Join(",", data.Keys.Select(symbol => symbol))}");
+            }
+            if (UniverseManager.Count != 3)
+            {
+                throw new Exception($"Expecting 3 universes (chain, continuous and user defined) but have {UniverseManager.Count}");
+            }
+
+            if (!Portfolio.Invested)
+            {
+                Buy(_futureContract.Symbol, 1);
+                Buy(_continuousContract.Mapped, 1);
+
+                RemoveSecurity(_futureContract.Symbol);
+                RemoveSecurity(_continuousContract.Symbol);
+
+                _ended = true;
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            if (orderEvent.Status == OrderStatus.Filled)
+            {
+                Log($"{orderEvent}");
+            }
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            Debug($"{Time}-{changes}");
+
+            if (changes.AddedSecurities.Any(security => security.Symbol != _continuousContract.Symbol && security.Symbol != _futureContract.Symbol)
+                || changes.RemovedSecurities.Any(security => security.Symbol != _continuousContract.Symbol && security.Symbol != _futureContract.Symbol))
+            {
+                throw new Exception($"We got an unexpected security changes {changes}");
+            }
+        }
+
+        /// <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 => 63;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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"},
+            {"Average Win", "0%"},
+            {"Average Loss", "-0.03%"},
+            {"Compounding Annual Return", "-2.594%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "-0.034%"},
+            {"Sharpe Ratio", "-7.854"},
+            {"Probabilistic Sharpe Ratio", "1.216%"},
+            {"Loss Rate", "100%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.022"},
+            {"Beta", "0.004"},
+            {"Annual Standard Deviation", "0.003"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-0.768"},
+            {"Tracking Error", "0.241"},
+            {"Treynor Ratio", "-4.689"},
+            {"Total Fees", "$8.60"},
+            {"Estimated Strategy Capacity", "$5500000.00"},
+            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
+            {"Portfolio Turnover", "66.80%"},
+            {"OrderListHash", "802a335b5c355e83b8cd2174f053c1b9"}
+        };
+    }
+}

Algorithm.CSharp/AddFutureOptionContractDataStreamingRegressionAlgorithm.cs

@@ -40,8 +40,8 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void Initialize()
         {
-            SetStartDate(2020, 1, 5);
-            SetEndDate(2020, 1, 6);
+            SetStartDate(2020, 1, 4);
+            SetEndDate(2020, 1, 8);
 
             _es20h20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(Futures.Indices.SP500EMini, Market.CME, new DateTime(2020, 3, 20)),
@@ -51,8 +51,9 @@ namespace QuantConnect.Algorithm.CSharp
                 QuantConnect.Symbol.CreateFuture(Futures.Indices.SP500EMini, Market.CME, new DateTime(2020, 6, 19)),
                 Resolution.Minute).Symbol;
 
-            var optionChains = OptionChainProvider.GetOptionContractList(_es20h20, Time)
-                .Concat(OptionChainProvider.GetOptionContractList(_es19m20, Time));
+            // Get option contract lists for 2020/01/05 (Time.AddDays(1)) because Lean has local data for that date
+            var optionChains = OptionChainProvider.GetOptionContractList(_es20h20, Time.AddDays(1))
+                .Concat(OptionChainProvider.GetOptionContractList(_es19m20, Time.AddDays(1)));
 
             foreach (var optionContract in optionChains)
             {
@@ -160,6 +161,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 311879;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -168,45 +179,27 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "217.585%"},
-            {"Drawdown", "0.600%"},
+            {"Compounding Annual Return", "5512.811%"},
+            {"Drawdown", "1.000%"},
             {"Expectancy", "0"},
-            {"Net Profit", "0.635%"},
-            {"Sharpe Ratio", "0"},
-            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Net Profit", "5.333%"},
+            {"Sharpe Ratio", "64.137"},
+            {"Probabilistic Sharpe Ratio", "95.977%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0"},
-            {"Beta", "0"},
-            {"Annual Standard Deviation", "0"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-14.395"},
-            {"Tracking Error", "0.043"},
-            {"Treynor Ratio", "0"},
-            {"Total Fees", "$7.40"},
-            {"Estimated Strategy Capacity", "$28000000.00"},
+            {"Alpha", "25.72"},
+            {"Beta", "2.914"},
+            {"Annual Standard Deviation", "0.423"},
+            {"Annual Variance", "0.179"},
+            {"Information Ratio", "66.11"},
+            {"Tracking Error", "0.403"},
+            {"Treynor Ratio", "9.315"},
+            {"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", "3.199"},
-            {"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", "35738733ff791eeeaf508faec804cab0"}
+            {"Portfolio Turnover", "122.11%"},
+            {"OrderListHash", "e7021bd385f366771ae00abd3a46a22e"}
         };
     }
 }

Algorithm.CSharp/AddFutureOptionContractFromFutureChainRegressionAlgorithm.cs

@@ -0,0 +1,134 @@
+/*
+ * 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.Interfaces;
+using QuantConnect.Securities;
+using System.Collections.Generic;
+using System.Linq;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This regression algorithm tests we can add future option contracts from contracts in the future chain
+    /// </summary>
+    public class AddFutureOptionContractFromFutureChainRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private bool _addedOptions;
+
+        public override void Initialize()
+        {
+            SetStartDate(2020, 1, 4);
+            SetEndDate(2020, 1, 6);
+
+            var es = AddFuture(Futures.Indices.SP500EMini, Resolution.Minute, Market.CME);
+            es.SetFilter((futureFilter) =>
+            {
+                return futureFilter.Expiration(0, 365).ExpirationCycle(new[] { 3, 6 });
+            });
+        }
+
+        public override void OnData(Slice data)
+        {
+            if (!_addedOptions)
+            {
+                _addedOptions = true;
+                foreach (var futuresContracts in data.FutureChains.Values)
+                {
+                    foreach (var contract in futuresContracts)
+                    {
+                        var option_contract_symbols = OptionChainProvider.GetOptionContractList(contract.Symbol, Time).ToList();
+                        if(option_contract_symbols.Count == 0)
+                        {
+                            continue;
+                        }
+
+                        foreach (var option_contract_symbol in option_contract_symbols.OrderBy(x => x.ID.Date)
+                            .ThenBy(x => x.ID.StrikePrice)
+                            .ThenBy(x => x.ID.OptionRight).Take(5))
+                        {
+                            AddOptionContract(option_contract_symbol);
+                        }
+                    }
+                }
+            }
+
+            if (Portfolio.Invested)
+            {
+                return;
+            }
+
+            foreach (var chain in data.OptionChains.Values)
+            {
+                foreach (var option in chain.Contracts.Keys)
+                {
+                    MarketOrder(option, 1);
+                    MarketOrder(option.Underlying, 1);
+                }
+            }
+        }
+
+        /// <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 => 12164;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "386219349.202%"},
+            {"Drawdown", "5.200%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "11.912%"},
+            {"Sharpe Ratio", "1604181.92"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "2144881.34"},
+            {"Beta", "31.223"},
+            {"Annual Standard Deviation", "1.337"},
+            {"Annual Variance", "1.788"},
+            {"Information Ratio", "1657259.526"},
+            {"Tracking Error", "1.294"},
+            {"Treynor Ratio", "68696.045"},
+            {"Total Fees", "$35.70"},
+            {"Estimated Strategy Capacity", "$2600000.00"},
+            {"Lowest Capacity Asset", "ES 31C3JQS9D84PW|ES XCZJLC9NOB29"},
+            {"Portfolio Turnover", "495.15%"},
+            {"OrderListHash", "64221a660525c4259d5bd852eef1299c"}
+        };
+    }
+}

Algorithm.CSharp/AddFutureOptionSingleOptionChainSelectedInUniverseFilterRegressionAlgorithm.cs

@@ -42,8 +42,8 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void Initialize()
         {
-            SetStartDate(2020, 1, 5);
-            SetEndDate(2020, 1, 6);
+            SetStartDate(2020, 1, 4);
+            SetEndDate(2020, 1, 8);
 
             _es = AddFuture(Futures.Indices.SP500EMini, Resolution.Minute, Market.CME);
             _es.SetFilter((futureFilter) =>
@@ -164,8 +164,6 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void OnEndOfAlgorithm()
         {
-            base.OnEndOfAlgorithm();
-
             if (!_optionFilterRan)
             {
                 throw new InvalidOperationException("Option chain filter was never ran");
@@ -219,6 +217,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 612882;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -227,45 +235,27 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-15.625%"},
-            {"Drawdown", "0.200%"},
+            {"Compounding Annual Return", "347.065%"},
+            {"Drawdown", "0.900%"},
             {"Expectancy", "0"},
-            {"Net Profit", "-0.093%"},
-            {"Sharpe Ratio", "-11.181"},
-            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Net Profit", "1.951%"},
+            {"Sharpe Ratio", "15.548"},
+            {"Probabilistic Sharpe Ratio", "95.977%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.002"},
-            {"Beta", "-0.016"},
-            {"Annual Standard Deviation", "0.001"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-14.343"},
-            {"Tracking Error", "0.044"},
-            {"Treynor Ratio", "0.479"},
-            {"Total Fees", "$3.70"},
-            {"Estimated Strategy Capacity", "$41000.00"},
-            {"Lowest Capacity Asset", "ES 31C3JQTOYO9T0|ES XCZJLC9NOB29"},
-            {"Fitness Score", "0.41"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-185.654"},
-            {"Portfolio Turnover", "0.821"},
-            {"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", "9347e3b610cfa21f7cbd968a0135c8af"}
+            {"Alpha", "1.885"},
+            {"Beta", "1.066"},
+            {"Annual Standard Deviation", "0.155"},
+            {"Annual Variance", "0.024"},
+            {"Information Ratio", "13.528"},
+            {"Tracking Error", "0.142"},
+            {"Treynor Ratio", "2.258"},
+            {"Total Fees", "$3.57"},
+            {"Estimated Strategy Capacity", "$760000.00"},
+            {"Lowest Capacity Asset", "ES XCZJLDQX2SRO|ES XCZJLC9NOB29"},
+            {"Portfolio Turnover", "32.31%"},
+            {"OrderListHash", "738240babf741f1bf79f85ea5026ec4c"}
         };
     }
 }

Algorithm.CSharp/AddOptionContractExpiresRegressionAlgorithm.cs

@@ -114,6 +114,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 37597;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -126,41 +136,23 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "0.300%"},
             {"Expectancy", "-0.042"},
             {"Net Profit", "-0.332%"},
-            {"Sharpe Ratio", "-3.7"},
-            {"Probabilistic Sharpe Ratio", "0.563%"},
+            {"Sharpe Ratio", "-3.149"},
+            {"Probabilistic Sharpe Ratio", "0.427%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
             {"Profit-Loss Ratio", "0.92"},
-            {"Alpha", "-0.021"},
-            {"Beta", "-0.011"},
-            {"Annual Standard Deviation", "0.006"},
+            {"Alpha", "-0.015"},
+            {"Beta", "-0.012"},
+            {"Annual Standard Deviation", "0.005"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-3.385"},
-            {"Tracking Error", "0.058"},
-            {"Treynor Ratio", "2.117"},
+            {"Information Ratio", "-2.823"},
+            {"Tracking Error", "0.049"},
+            {"Treynor Ratio", "1.372"},
             {"Total Fees", "$2.00"},
-            {"Estimated Strategy Capacity", "$45000000.00"},
-            {"Lowest Capacity Asset", "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", "b006bb7864c0b2f1a6552fb2aa7f03b8"}
+            {"Estimated Strategy Capacity", "$67000000.00"},
+            {"Lowest Capacity Asset", "AOL VRKS95ENLBYE|AOL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "0.55%"},
+            {"OrderListHash", "568fe7c2a11960436660db1231f2cfd2"}
         };
     }
 }

Algorithm.CSharp/AddOptionContractFromUniverseRegressionAlgorithm.cs

@@ -166,6 +166,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 5797;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -193,25 +203,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "1.14%"},
             {"OrderListHash", "ae0b430e9c728966e3736fb352a689c6"}
         };
     }

Algorithm.CSharp/AddOptionContractTwiceRegressionAlgorithm.cs

@@ -0,0 +1,157 @@
+/*
+ * 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.Interfaces;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm reproducing GH issue #6073 where we remove and re add an option and expect it to work
+    /// </summary>
+    public class AddOptionContractTwiceRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _contract;
+        private bool _hasRemoved;
+        private bool _reAdded;
+
+        public override void Initialize()
+        {
+            SetStartDate(2014, 06, 06);
+            SetEndDate(2014, 06, 09);
+
+            UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
+            UniverseSettings.MinimumTimeInUniverse = TimeSpan.Zero;
+            UniverseSettings.FillForward = false;
+
+            AddEquity("SPY", Resolution.Daily);
+
+            var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
+
+            _contract = OptionChainProvider.GetOptionContractList(aapl, Time)
+                .OrderBy(symbol => symbol.ID.Symbol)
+                .FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
+                    && optionContract.ID.OptionStyle == OptionStyle.American);
+            AddOptionContract(_contract);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (_hasRemoved)
+            {
+                if (!_reAdded && slice.ContainsKey(_contract) && slice.ContainsKey(_contract.Underlying))
+                {
+                    throw new Exception("Getting data for removed option and underlying!");
+                }
+
+                if (!Portfolio.Invested && _reAdded)
+                {
+                    var option = Securities[_contract];
+                    var optionUnderlying = Securities[_contract.Underlying];
+                    if (option.IsTradable && optionUnderlying.IsTradable
+                        && slice.ContainsKey(_contract) && slice.ContainsKey(_contract.Underlying))
+                    {
+                        Buy(_contract, 1);
+                    }
+                }
+
+                if (!Securities[_contract].IsTradable
+                    && !Securities[_contract.Underlying].IsTradable
+                    && !_reAdded)
+                {
+                    // ha changed my mind!
+                    AddOptionContract(_contract);
+                    _reAdded = true;
+                }
+            }
+
+            if (slice.ContainsKey(_contract) && slice.ContainsKey(_contract.Underlying))
+            {
+                if (!_hasRemoved)
+                {
+                    RemoveOptionContract(_contract);
+                    RemoveSecurity(_contract.Underlying);
+                    _hasRemoved = true;
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_hasRemoved)
+            {
+                throw new Exception("We did not remove the option contract!");
+            }
+            if (!_reAdded)
+            {
+                throw new Exception("We did not re add the option contract!");
+            }
+        }
+
+        /// <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 => 4677;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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", "-0.05%"},
+            {"Compounding Annual Return", "-4.548%"},
+            {"Drawdown", "0.100%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "-0.051%"},
+            {"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", "-9.486"},
+            {"Tracking Error", "0.008"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$2.00"},
+            {"Estimated Strategy Capacity", "$30000.00"},
+            {"Lowest Capacity Asset", "AAPL VXBK4Q9ZIFD2|AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "0.07%"},
+            {"OrderListHash", "546b6182e1df2d222178454d8f311566"}
+        };
+    }
+}

Algorithm.CSharp/AddOptionWithOnMarketOpenOnlyFilterRegressionAlgorithm.cs

@@ -0,0 +1,129 @@
+/*
+ * 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.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);
+
+            // Susbtract one minute to get the actual market open. If market open is at 9:30am, this will be invoked at 9:31am
+            var expectedTime = Time.TimeOfDay - TimeSpan.FromMinutes(1);
+            var allOptionsWereChangedOnMarketOpen = changeOptions.All(s =>
+            {
+                var firstMarketSegment = s.Exchange.Hours.MarketHours[Time.DayOfWeek].Segments
+                                                         .First(segment => segment.State == MarketHoursState.Market);
+
+                return firstMarketSegment.Start == expectedTime;
+            });
+
+            if (!allOptionsWereChangedOnMarketOpen)
+            {
+                throw new Exception("Expected options filter to be run only on market open");
+            }
+        }
+
+        /// <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 time slices of algorithm
+        /// </summary>
+        public long DataPoints => 6023980;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe 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

@@ -40,8 +40,8 @@ namespace QuantConnect.Algorithm.CSharp
         private int _expectedContractIndex;
         private readonly List<Symbol> _expectedContracts = new List<Symbol>
         {
-            SymbolRepresentation.ParseOptionTickerOSI("GOOG  151224P00750000"),
             SymbolRepresentation.ParseOptionTickerOSI("GOOG  151224P00747500"),
+            SymbolRepresentation.ParseOptionTickerOSI("GOOG  151224P00750000"),
             SymbolRepresentation.ParseOptionTickerOSI("GOOG  151224P00752500")
         };
 
@@ -109,6 +109,11 @@ namespace QuantConnect.Algorithm.CSharp
                 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)
+                    {
+                        throw new Exception($"Unexpected underlying data point {u.Underlying.EndTime} {u.Underlying}");
+                    }
                     // find first put above market price
                     return u.IncludeWeeklys()
                         .Strikes(+1, +1)
@@ -205,6 +210,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 200618;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -231,27 +246,9 @@ namespace QuantConnect.Algorithm.CSharp
             {"Treynor Ratio", "0"},
             {"Total Fees", "$6.00"},
             {"Estimated Strategy Capacity", "$2000.00"},
-            {"Lowest Capacity Asset", "GOOCV 305RBQ2BZBZT2|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", "1e7b3e90918777b9dbf46353a96f3329"}
+            {"Lowest Capacity Asset", "GOOCV 305RBR0BSWIX2|GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "1.19%"},
+            {"OrderListHash", "550a99c482106defd8ba15f48183768e"}
         };
     }
 }

Algorithm.CSharp/AddRemoveSecurityCacheRegressionAlgorithm.cs

@@ -0,0 +1,124 @@
+/*
+ * 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.Interfaces;
+using System.Collections.Generic;
+using QuantConnect.Orders;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm making sure the securities cache is reset correctly once it's removed from the algorithm
+    /// </summary>
+    public class AddRemoveSecurityCacheRegressionAlgorithm : 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(2013, 10, 07);  //Set Start Date
+            SetEndDate(2013, 10, 11);    //Set End Date
+            SetCash(100000);             //Set Strategy Cash
+
+            AddEquity("SPY", Resolution.Minute, extendedMarketHours: true);
+        }
+
+        /// <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)
+        {
+            if (!Portfolio.Invested)
+            {
+                SetHoldings("SPY", 1);
+            }
+
+            if (Time.Day == 11)
+            {
+                return;
+            }
+            if (!ActiveSecurities.ContainsKey("AIG"))
+            {
+                var aig = AddEquity("AIG", Resolution.Minute);
+
+                var ticket = MarketOrder("AIG", 1);
+
+                if (ticket.Status != OrderStatus.Invalid)
+                {
+                    throw new Exception("Expected order to always be invalid because there is no data yet!");
+                }
+            }
+            else
+            {
+                RemoveSecurity("AIG");
+            }
+        }
+
+        /// <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 => 11202;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0.00%"},
+            {"Compounding Annual Return", "271.720%"},
+            {"Drawdown", "2.500%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "1.754%"},
+            {"Sharpe Ratio", "11.994"},
+            {"Probabilistic Sharpe Ratio", "74.160%"},
+            {"Loss Rate", "100%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.618"},
+            {"Beta", "0.81"},
+            {"Annual Standard Deviation", "0.185"},
+            {"Annual Variance", "0.034"},
+            {"Information Ratio", "3.961"},
+            {"Tracking Error", "0.061"},
+            {"Treynor Ratio", "2.746"},
+            {"Total Fees", "$21.45"},
+            {"Estimated Strategy Capacity", "$830000.00"},
+            {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
+            {"Portfolio Turnover", "20.49%"},
+            {"OrderListHash", "6ee62edf1ac883882b0fcef8cb3e9bae"}
+        };
+    }
+}

Algorithm.CSharp/AddRemoveSecurityRegressionAlgorithm.cs

@@ -106,6 +106,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 7063;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -133,25 +143,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "29.88%"},
             {"OrderListHash", "ac3f4dfcdeb98b488b715412ad2d6c4f"}
         };
     }

Algorithm.CSharp/AddRiskManagementAlgorithm.cs

@@ -59,6 +59,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { 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>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -86,25 +96,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "59.74%"},
             {"OrderListHash", "af3a9c98c190d1b6b36fad184e796b0b"}
         };
     }

Algorithm.CSharp/AddTwoAndRemoveOneOptionContractRegressionAlgorithm.cs

@@ -0,0 +1,142 @@
+/*
+ * 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.Interfaces;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm reproducing issue where underlying option contract would be removed with the first call
+    /// too RemoveOptionContract
+    /// </summary>
+    public class AddTwoAndRemoveOneOptionContractRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _contract1;
+        private Symbol _contract2;
+        private bool _hasRemoved;
+
+        public override void Initialize()
+        {
+            SetStartDate(2014, 06, 06);
+            SetEndDate(2014, 06, 06);
+
+            UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
+            UniverseSettings.MinimumTimeInUniverse = TimeSpan.Zero;
+
+            var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
+
+            var contracts = OptionChainProvider.GetOptionContractList(aapl, Time)
+                .OrderBy(symbol => symbol.ID.Symbol)
+                .Where(optionContract => optionContract.ID.OptionRight == OptionRight.Call
+                    && optionContract.ID.OptionStyle == OptionStyle.American)
+                .Take(2)
+                .ToList();
+
+            _contract1 = contracts[0];
+            _contract2 = contracts[1];
+            AddOptionContract(_contract1);
+            AddOptionContract(_contract2);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (slice.HasData)
+            {
+                if (!_hasRemoved)
+                {
+                    RemoveOptionContract(_contract1);
+                    _hasRemoved = true;
+                }
+                else
+                {
+                    var subscriptions =
+                        SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs("AAPL");
+                    if (subscriptions.Count == 0)
+                    {
+                        throw new Exception("No configuration for underlying was found!");
+                    }
+
+                    if (!Portfolio.Invested)
+                    {
+                        Buy(_contract2, 1);
+                    }
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_hasRemoved)
+            {
+                throw new Exception("Expect a single call to OnData where we removed the option and underlying");
+            }
+        }
+
+        /// <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 => 1578;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe 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", "$2.00"},
+            {"Estimated Strategy Capacity", "$230000.00"},
+            {"Lowest Capacity Asset", "AAPL VXBK4QQIRLZA|AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "0.25%"},
+            {"OrderListHash", "228194dcc6fd8689a67f383577ee2d85"}
+        };
+    }
+}

Algorithm.CSharp/AddUniverseSelectionModelAlgorithm.cs

@@ -78,6 +78,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 53;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -90,40 +100,22 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "3.300%"},
             {"Expectancy", "-1"},
             {"Net Profit", "-0.168%"},
-            {"Sharpe Ratio", "-0.126"},
-            {"Probabilistic Sharpe Ratio", "45.081%"},
+            {"Sharpe Ratio", "62.513"},
+            {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-2.896"},
-            {"Beta", "0.551"},
-            {"Annual Standard Deviation", "0.385"},
-            {"Annual Variance", "0.148"},
-            {"Information Ratio", "-13.66"},
-            {"Tracking Error", "0.382"},
-            {"Treynor Ratio", "-0.088"},
+            {"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"},
             {"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%"},
+            {"Portfolio Turnover", "26.96%"},
             {"OrderListHash", "a7a0983c8413ff241e7d223438f3d508"}
         };
     }

Algorithm.CSharp/AddUniverseSelectionModelCoarseAlgorithm.cs

@@ -89,6 +89,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 234018;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -101,40 +111,22 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "5.800%"},
             {"Expectancy", "-0.731"},
             {"Net Profit", "-5.588%"},
-            {"Sharpe Ratio", "-3.272"},
-            {"Probabilistic Sharpe Ratio", "5.825%"},
+            {"Sharpe Ratio", "-3.252"},
+            {"Probabilistic Sharpe Ratio", "5.526%"},
             {"Loss Rate", "86%"},
             {"Win Rate", "14%"},
             {"Profit-Loss Ratio", "0.89"},
-            {"Alpha", "-0.594"},
-            {"Beta", "0.707"},
-            {"Annual Standard Deviation", "0.203"},
-            {"Annual Variance", "0.041"},
-            {"Information Ratio", "-2.929"},
-            {"Tracking Error", "0.193"},
-            {"Treynor Ratio", "-0.942"},
+            {"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"},
             {"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%"},
+            {"Portfolio Turnover", "7.34%"},
             {"OrderListHash", "f837879b96f5e565b60fd040299d2123"}
         };
     }

Algorithm.CSharp/AdjustedVolumeRegressionAlgorithm.cs

@@ -30,7 +30,7 @@ namespace QuantConnect.Algorithm.CSharp
     {
         private Symbol _aapl;
         private const string Ticker = "AAPL";
-        private FactorFile _factorFile;
+        private CorporateFactorProvider _factorFile;
         private readonly IEnumerator<decimal> _expectedAdjustedVolume = new List<decimal> { 6164842, 3044047, 3680347, 3468303, 2169943, 2652523,
             1499707, 1518215, 1655219, 1510487 }.GetEnumerator();
         private readonly IEnumerator<decimal> _expectedAdjustedAskSize = new List<decimal> { 215600, 5600, 25200, 8400, 5600, 5600, 2800,
@@ -56,7 +56,7 @@ namespace QuantConnect.Algorithm.CSharp
             factorFileProvider.Initialize(mapFileProvider, dataProvider);
 
 
-            _factorFile = factorFileProvider.Get(_aapl);
+            _factorFile = factorFileProvider.Get(_aapl) as CorporateFactorProvider;
         }
 
         /// <summary>
@@ -83,7 +83,7 @@ namespace QuantConnect.Algorithm.CSharp
                 if (_expectedAdjustedVolume.MoveNext() && _expectedAdjustedVolume.Current != aaplData.Volume)
                 {
                     // Our values don't match lets try and give a reason why
-                    var dayFactor = _factorFile.GetSplitFactor(aaplData.Time);
+                    var dayFactor = _factorFile.GetPriceScale(aaplData.Time, DataNormalizationMode.SplitAdjusted);
                     var probableAdjustedVolume = aaplData.Volume / dayFactor;
 
                     if (_expectedAdjustedVolume.Current == probableAdjustedVolume)
@@ -107,7 +107,7 @@ namespace QuantConnect.Algorithm.CSharp
                 if (_expectedAdjustedAskSize.MoveNext() && _expectedAdjustedAskSize.Current != aaplQuoteData.LastAskSize)
                 {
                     // Our values don't match lets try and give a reason why
-                    var dayFactor = _factorFile.GetSplitFactor(aaplQuoteData.Time);
+                    var dayFactor = _factorFile.GetPriceScale(aaplQuoteData.Time, DataNormalizationMode.SplitAdjusted);
                     var probableAdjustedAskSize = aaplQuoteData.LastAskSize / dayFactor;
 
                     if (_expectedAdjustedAskSize.Current == probableAdjustedAskSize)
@@ -126,7 +126,7 @@ namespace QuantConnect.Algorithm.CSharp
                 if (_expectedAdjustedBidSize.MoveNext() && _expectedAdjustedBidSize.Current != aaplQuoteData.LastBidSize)
                 {
                     // Our values don't match lets try and give a reason why
-                    var dayFactor = _factorFile.GetSplitFactor(aaplQuoteData.Time);
+                    var dayFactor = _factorFile.GetPriceScale(aaplQuoteData.Time, DataNormalizationMode.SplitAdjusted);
                     var probableAdjustedBidSize = aaplQuoteData.LastBidSize / dayFactor;
 
                     if (_expectedAdjustedBidSize.Current == probableAdjustedBidSize)
@@ -153,6 +153,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 795;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -180,25 +190,7 @@ 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%"},
+            {"Portfolio Turnover", "99.56%"},
             {"OrderListHash", "18e41dded4f8cee548ee02b03ffb0814"}
         };
     }

Algorithm.CSharp/AllShortableSymbolsCoarseSelectionRegressionAlgorithm.cs

@@ -186,6 +186,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 35410;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -198,40 +208,22 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
             {"Net Profit", "0.192%"},
-            {"Sharpe Ratio", "31.331"},
-            {"Probabilistic Sharpe Ratio", "88.448%"},
+            {"Sharpe Ratio", "231.673"},
+            {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.138"},
-            {"Beta", "0.04"},
-            {"Annual Standard Deviation", "0.004"},
+            {"Alpha", "0.163"},
+            {"Beta", "-0.007"},
+            {"Annual Standard Deviation", "0.001"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "4.767"},
-            {"Tracking Error", "0.077"},
-            {"Treynor Ratio", "3.223"},
+            {"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%"},
+            {"Portfolio Turnover", "10.61%"},
             {"OrderListHash", "0069f402ffcd2d91b9018b81badfab81"}
         };
     }

Algorithm.CSharp/AlphaStreamsBasicTemplateAlgorithm.cs

@@ -13,13 +13,12 @@
  * limitations under the License.
 */
 
-using System.Linq;
-using QuantConnect.Data;
 using QuantConnect.Orders;
 using QuantConnect.Interfaces;
+using QuantConnect.Securities;
 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;
 
@@ -30,8 +29,6 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class AlphaStreamsBasicTemplateAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private Dictionary<Symbol, HashSet<Symbol>> _symbolsPerAlpha = new Dictionary<Symbol, HashSet<Symbol>>();
-
         /// <summary>
         /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
         /// </summary>
@@ -40,9 +37,12 @@ namespace QuantConnect.Algorithm.CSharp
             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" })
             {
@@ -50,59 +50,11 @@ 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)
-        {
-            foreach (var portfolioState in data.Get<AlphaStreamsPortfolioState>().Values)
-            {
-                var alphaId = portfolioState.Symbol;
-                var currentSymbols = _symbolsPerAlpha[alphaId];
-
-                var newSymbols = new HashSet<Symbol>(currentSymbols.Count);
-                foreach (var symbol in portfolioState.PositionGroups?.SelectMany(positionGroup => positionGroup.Positions).Select(state => state.Symbol) ?? Enumerable.Empty<Symbol>())
-                {
-                    // only add it if it's not used by any alpha (already added check)
-                    if (newSymbols.Add(symbol) && !UsedBySomeAlpha(symbol))
-                    {
-                        AddSecurity(symbol, resolution: UniverseSettings.Resolution);
-                    }
-                }
-                _symbolsPerAlpha[alphaId] = newSymbols;
-
-                foreach (var symbol in currentSymbols.Where(symbol => !UsedBySomeAlpha(symbol)))
-                {
-                    RemoveSecurity(symbol);
-                }
-            }
-        }
-
         public override void OnOrderEvent(OrderEvent orderEvent)
         {
             Log($"OnOrderEvent: {orderEvent}");
         }
 
-        public override void OnSecuritiesChanged(SecurityChanges changes)
-        {
-            changes.FilterCustomSecurities = false;
-            foreach (var addedSecurity in changes.AddedSecurities)
-            {
-                if (addedSecurity.Symbol.IsCustomDataType<AlphaStreamsPortfolioState>())
-                {
-                    _symbolsPerAlpha[addedSecurity.Symbol] = new HashSet<Symbol>();
-                }
-            }
-
-            Log($"OnSecuritiesChanged: {changes}");
-        }
-
-        private bool UsedBySomeAlpha(Symbol asset)
-        {
-            return _symbolsPerAlpha.Any(pair => pair.Value.Contains(asset));
-        }
-
         /// <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>
@@ -113,6 +65,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </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>
@@ -140,25 +102,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "2.31%"},
             {"OrderListHash", "2b94bc50a74caebe06c075cdab1bc6da"}
         };
     }

Algorithm.CSharp/AlphaStreamsDifferentAccountCurrencyBasicTemplateAlgorithm.cs

@@ -41,52 +41,44 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 6202;
+
+        /// <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%"},
-            {"Average Loss", "-0.84%"},
-            {"Compounding Annual Return", "-78.502%"},
+            {"Average Win", "0.01%"},
+            {"Average Loss", "0.00%"},
+            {"Compounding Annual Return", "-78.519%"},
             {"Drawdown", "3.100%"},
-            {"Expectancy", "-1"},
+            {"Expectancy", "7.797"},
             {"Net Profit", "-1.134%"},
             {"Sharpe Ratio", "-2.456"},
             {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.008"},
-            {"Beta", "1.012"},
+            {"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", "-0.57"},
+            {"Information Ratio", "-0.859"},
             {"Tracking Error", "0.004"},
-            {"Treynor Ratio", "-0.831"},
-            {"Total Fees", "$2.89"},
-            {"Estimated Strategy Capacity", "$8900000000.00"},
+            {"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%"},
+            {"Portfolio Turnover", "33.78%"},
             {"OrderListHash", "a9dd0a0ab6070455479d1b9caaa4e69c"}
         };
     }

Algorithm.CSharp/AlphaStreamsUniverseSelectionTemplateAlgorithm.cs

@@ -14,9 +14,11 @@
 */
 
 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;
@@ -26,7 +28,7 @@ namespace QuantConnect.Algorithm.CSharp
     /// <summary>
     /// Example algorithm consuming an alpha streams portfolio state and trading based on it
     /// </summary>
-    public class AlphaStreamsUniverseSelectionTemplateAlgorithm : AlphaStreamsBasicTemplateAlgorithm
+    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.
@@ -36,6 +38,7 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2018, 04, 04);
             SetEndDate(2018, 04, 06);
 
+            SetAlpha(new AlphaStreamAlphaModule());
             SetExecution(new ImmediateExecutionModel());
             Settings.MinimumOrderMarginPortfolioPercentage = 0.01m;
             SetPortfolioConstruction(new EqualWeightingAlphaStreamsPortfolioConstructionModel());
@@ -65,23 +68,55 @@ namespace QuantConnect.Algorithm.CSharp
             }
         }
 
+        /// <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 override Dictionary<string, string> ExpectedStatistics
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            get
-            {
-                var result = base.ExpectedStatistics;
-                result["Compounding Annual Return"] = "-13.200%";
-                result["Information Ratio"] = "2.827";
-                result["Tracking Error"] = "0.248";
-                result["Fitness Score"] = "0.011";
-                result["Return Over Maximum Drawdown"] = "-113.513";
-                result["Portfolio Turnover"] = "0.023";
-                return result;
-            }
-        }
+            {"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"},
+            {"Portfolio Turnover", "2.31%"},
+            {"OrderListHash", "2b94bc50a74caebe06c075cdab1bc6da"}
+        };
     }
 }

Algorithm.CSharp/AlphaStreamsWithHoldingsBasicTemplateAlgorithm.cs

@@ -27,7 +27,6 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class AlphaStreamsWithHoldingsBasicTemplateAlgorithm : AlphaStreamsBasicTemplateAlgorithm
     {
-        private decimal _initialCash = 100000;
         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.
@@ -36,7 +35,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             SetStartDate(2018, 04, 04);
             SetEndDate(2018, 04, 06);
-            SetCash(_initialCash);
+            SetCash(100000);
 
             SetExecution(new ImmediateExecutionModel());
             UniverseSettings.Resolution = Resolution.Hour;
@@ -46,23 +45,23 @@ namespace QuantConnect.Algorithm.CSharp
             // 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(100, 10);
+            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(100, -10);
+            spy.Holdings.SetHoldings(246, -10);
 
             AddData<AlphaStreamsPortfolioState>("94d820a93fff127fa46c15231d");
         }
 
         public override void OnOrderEvent(OrderEvent orderEvent)
         {
-            if (_expectedSpyQuantity == 0 && orderEvent.Symbol == "SPY")
+            if (_expectedSpyQuantity == 0 && orderEvent.Symbol == "SPY" && orderEvent.Status == OrderStatus.Filled)
             {
                 var security = Securities["SPY"];
-                var priceInAccountCurrency = security.AskPrice * security.QuoteCurrency.ConversionRate;
-                _expectedSpyQuantity = (_initialCash * (1 - Settings.FreePortfolioValuePercentage) - priceInAccountCurrency) / priceInAccountCurrency;
+                var priceInAccountCurrency = Portfolio.CashBook.ConvertToAccountCurrency(security.AskPrice, security.QuoteCurrency.Symbol);
+                _expectedSpyQuantity = (Portfolio.TotalPortfolioValue - Settings.FreePortfolioValue) / priceInAccountCurrency;
                 _expectedSpyQuantity = _expectedSpyQuantity.DiscretelyRoundBy(1, MidpointRounding.ToZero);
             }
 
@@ -76,7 +75,8 @@ namespace QuantConnect.Algorithm.CSharp
                 throw new Exception("We should no longer hold AAPL since the alpha does not");
             }
 
-            if (Securities["SPY"].Holdings.Quantity != _expectedSpyQuantity)
+            // 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}");
             }
@@ -92,23 +92,33 @@ namespace QuantConnect.Algorithm.CSharp
         /// </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%"},
-            {"Average Loss", "-1.03%"},
+            {"Average Win", "0.01%"},
+            {"Average Loss", "0.00%"},
             {"Compounding Annual Return", "-87.617%"},
             {"Drawdown", "3.100%"},
-            {"Expectancy", "-1"},
+            {"Expectancy", "8.518"},
             {"Net Profit", "-1.515%"},
             {"Sharpe Ratio", "-2.45"},
             {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
+            {"Loss Rate", "50%"},
+            {"Win Rate", "50%"},
+            {"Profit-Loss Ratio", "18.04"},
             {"Alpha", "0.008"},
             {"Beta", "1.015"},
             {"Annual Standard Deviation", "0.344"},
@@ -119,25 +129,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "34.12%"},
             {"OrderListHash", "788eb2c74715a78476ba0db3b2654eb6"}
         };
     }

Algorithm.CSharp/Alphas/MortgageRateVolatilityAlpha.cs

@@ -1,162 +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 System.Linq;
-using QuantConnect.Data;
-using QuantConnect.Indicators;
-using QuantConnect.Orders.Fees;
-using QuantConnect.Data.Custom;
-using System.Collections.Generic;
-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;
-
-namespace QuantConnect.Algorithm.CSharp.Alphas
-{
-    ///<summary>
-    /// This Alpha Model uses Wells Fargo 30-year Fixed Rate Mortgage data from Quandl to
-    /// generate Insights about the movement of Real Estate ETFs. Mortgage rates can provide information
-    /// regarding the general price trend of real estate, and ETFs provide good continuous-time instruments
-    /// to measure the impact against. Volatility in mortgage rates tends to put downward pressure on real
-    /// estate prices, whereas stable mortgage rates, regardless of true rate, lead to stable or higher real
-    /// estate prices. This Alpha model seeks to take advantage of this correlation by emitting insights
-    /// based on volatility and rate deviation from its historic mean.
-    ///
-    /// This alpha is part of the Benchmark Alpha Series created by QuantConnect which are open
-    /// sourced so the community and client funds can see an example of an alpha.
-    ///</summary>
-    public class MortgageRateVolatilityAlgorithm : QCAlgorithm
-    {
-        public override void Initialize()
-        {
-            SetStartDate(2017, 1, 1);  //Set Start Date
-            SetCash(100000);             //Set Strategy Cash
-
-            UniverseSettings.Resolution = Resolution.Daily;
-            SetSecurityInitializer(security => security.FeeModel = new ConstantFeeModel(0));
-
-            // Basket of 6 liquid real estate ETFs
-            Func<string, Symbol> toSymbol = x => QuantConnect.Symbol.Create(x, SecurityType.Equity, Market.USA);
-            var realEstateETFs = new[] { "VNQ", "REET", "TAO", "FREL", "SRET", "HIPS" }.Select(toSymbol).ToArray();
-            SetUniverseSelection(new ManualUniverseSelectionModel(realEstateETFs));
-
-            SetAlpha(new MortgageRateVolatilityAlphaModel(this));
-
-            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
-
-            SetExecution(new ImmediateExecutionModel());
-
-            SetRiskManagement(new NullRiskManagementModel());
-
-        }
-
-        private class MortgageRateVolatilityAlphaModel : AlphaModel
-        {
-            private readonly int _indicatorPeriod;
-            private readonly Resolution _resolution;
-            private readonly TimeSpan _insightDuration;
-            private readonly int _deviations;
-            private readonly double _insightMagnitude;
-            private readonly Symbol _mortgageRate;
-            private readonly SimpleMovingAverage _mortgageRateSma;
-            private readonly StandardDeviation _mortgageRateStd;
-
-            public MortgageRateVolatilityAlphaModel(
-                QCAlgorithm algorithm,
-                int indicatorPeriod = 15,
-                double insightMagnitude = 0.0005,
-                int deviations = 2,
-                Resolution resolution = Resolution.Daily
-                )
-            {
-            	// Add Quandl data for a Well's Fargo 30-year Fixed Rate mortgage
-                _mortgageRate = algorithm.AddData<QuandlMortgagePriceColumns>("WFC/PR_GOV_30YFIXEDVA_APR").Symbol;
-                _indicatorPeriod = indicatorPeriod;
-                _resolution = resolution;
-                _insightDuration = resolution.ToTimeSpan().Multiply(indicatorPeriod);
-                _insightMagnitude = insightMagnitude;
-                _deviations = deviations;
-                
-                // Add indicators for the mortgage rate -- Standard Deviation and Simple Moving Average
-                _mortgageRateStd = algorithm.STD(_mortgageRate, _indicatorPeriod, resolution);
-                _mortgageRateSma = algorithm.SMA(_mortgageRate, _indicatorPeriod, resolution);
-                
-                // Use a history call to warm-up the indicators
-                WarmUpIndicators(algorithm);
-            }
-            
-            public override IEnumerable<Insight> Update(QCAlgorithm algorithm, Slice data)
-            {
-                var insights = new List<Insight>();
-                
-                // Return empty list if data slice doesn't contain monrtgage rate data
-                if (!data.Keys.Contains(_mortgageRate))
-                {
-                    return insights;
-                }
-				// Extract current mortgage rate, the current STD indicator value, and current SMA value
-                var rate = data[_mortgageRate].Value;
-                var deviation = _deviations * _mortgageRateStd;
-                var sma = _mortgageRateSma;
-
-				// Loop through all Active Securities to emit insights
-                foreach (var security in algorithm.ActiveSecurities.Keys)
-                {
-                	// Mortgage rate Symbol will be in the collection, so skip it
-                    if (security == _mortgageRate)
-                    {
-                        return insights;
-                    }
-
-					// If volatility in mortgage rates is high, then we emit an Insight to sell
-                    if ((rate < sma - deviation) || (rate > sma + deviation))
-                    {
-                        insights.Add(Insight.Price(security, _insightDuration, InsightDirection.Down, _insightMagnitude));
-                    }
-                    
-                    // If volatility in mortgage rates is low, then we emit an Insight to buy
-                    if ((rate < sma - (decimal)deviation/2) || (rate > sma + (decimal)deviation/2))
-                    {
-                        insights.Add(Insight.Price(security, _insightDuration, InsightDirection.Up, _insightMagnitude));
-                    }
-                }
-
-                return insights;
-            }
-
-            private void WarmUpIndicators(QCAlgorithm algorithm)
-            {
-            	// Make a history call and update the indicators
-                algorithm.History(new[] { _mortgageRate }, _indicatorPeriod, _resolution).PushThrough(bar =>
-                {
-                    _mortgageRateSma.Update(bar.EndTime, bar.Value);
-                    _mortgageRateStd.Update(bar.EndTime, bar.Value);
-                });
-            }
-        }
-        public class QuandlMortgagePriceColumns : Quandl
-        {
-            public QuandlMortgagePriceColumns()
-            
-            // Rename the Quandl object column to the data we want, which is the 'Value' column
-	        // of the CSV that our API call returns
-                : base(valueColumnName: "Value")
-            {
-            }
-        }
-    }
-}

Algorithm.CSharp/Alphas/RebalancingLeveragedETFAlpha.cs

@@ -82,6 +82,16 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
         /// </summary>
         public Language[] Languages { get; } = { 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>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -195,4 +205,4 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
             UltraShort = ultraShort;
         }
     }
-}
+}

Algorithm.CSharp/Alphas/ShareClassMeanReversionAlpha.cs

@@ -31,7 +31,7 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
     /// A number of companies publicly trade two different classes of shares
     /// in US equity markets. If both assets trade with reasonable volume, then
     /// the underlying driving forces of each should be similar or the same. Given
-    /// this, we can create a relatively dollar-netural long/short portfolio using
+    /// this, we can create a relatively dollar-neutral long/short portfolio using
     /// the dual share classes. Theoretically, any deviation of this portfolio from
     /// its mean-value should be corrected, and so the motivating idea is based on
     /// mean-reversion. Using a Simple Moving Average indicator, we can

Algorithm.CSharp/Alphas/VixDualThrustAlpha.cs

@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
             int barsToConsolidate = 1
             )
         {
-            // coefficient that used to determinte upper and lower borders of a breakout channel
+            // coefficient that used to determine upper and lower borders of a breakout channel
             _k1 = k1;
             _k2 = k2;
 
@@ -202,7 +202,7 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
                 SymbolData symbolData;
                 if (_symbolDataBySymbol.TryGetValue(removed.Symbol, out symbolData))
                 {
-                    // unsibscribe consolidator from data updates
+                    // unsubscribe consolidator from data updates
                     algorithm.SubscriptionManager.RemoveConsolidator(removed.Symbol, symbolData.GetConsolidator());
 
                     // remove item from dictionary collection

Algorithm.CSharp/AutoRegressiveIntegratedMovingAverageRegressionAlgorithm.cs

@@ -73,6 +73,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 1893;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 100;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -85,40 +95,22 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "0.100%"},
             {"Expectancy", "3.321"},
             {"Net Profit", "0.089%"},
-            {"Sharpe Ratio", "0.868"},
-            {"Probabilistic Sharpe Ratio", "44.482%"},
+            {"Sharpe Ratio", "0.798"},
+            {"Probabilistic Sharpe Ratio", "40.893%"},
             {"Loss Rate", "24%"},
             {"Win Rate", "76%"},
             {"Profit-Loss Ratio", "4.67"},
-            {"Alpha", "0.001"},
-            {"Beta", "-0"},
+            {"Alpha", "-0.001"},
+            {"Beta", "0.008"},
             {"Annual Standard Deviation", "0.001"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-2.148"},
-            {"Tracking Error", "0.101"},
-            {"Treynor Ratio", "-4.168"},
+            {"Information Ratio", "-1.961"},
+            {"Tracking Error", "0.092"},
+            {"Treynor Ratio", "0.08"},
             {"Total Fees", "$52.00"},
             {"Estimated Strategy Capacity", "$32000000000.00"},
             {"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%"},
+            {"Portfolio Turnover", "0.02%"},
             {"OrderListHash", "cf43585a8d1781f04b53a4f1ee3380cb"}
         };
     }

Algorithm.CSharp/AutomaticIndicatorWarmupDataTypeRegressionAlgorithm.cs

@@ -35,7 +35,7 @@ namespace QuantConnect.Algorithm.CSharp
             UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
             EnableAutomaticIndicatorWarmUp = true;
             SetStartDate(2013, 10, 08);
-            SetEndDate(2013, 10, 09);
+            SetEndDate(2013, 10, 10);
 
             var SP500 = QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME);
             _symbol = FutureChainProvider.GetFutureContractList(SP500, StartDate).First();
@@ -67,7 +67,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             // Test case: custom IndicatorBase<QuoteBar> indicator using Future subscribed symbol
             var indicator = new CustomIndicator();
-            var consolidator = CreateConsolidator(TimeSpan.FromMinutes(1), typeof(QuoteBar));
+            var consolidator = CreateConsolidator(TimeSpan.FromMinutes(2), typeof(QuoteBar));
             RegisterIndicator(_symbol, indicator, consolidator);
 
             AssertIndicatorState(indicator, isReady: false);
@@ -143,6 +143,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 6426;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 84;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -151,45 +161,27 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-99.999%"},
-            {"Drawdown", "16.100%"},
+            {"Compounding Annual Return", "733913.744%"},
+            {"Drawdown", "15.900%"},
             {"Expectancy", "0"},
-            {"Net Profit", "-6.366%"},
-            {"Sharpe Ratio", "1.194"},
+            {"Net Profit", "6.828%"},
+            {"Sharpe Ratio", "203744786353.302"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "5.56"},
-            {"Beta", "-71.105"},
-            {"Annual Standard Deviation", "0.434"},
-            {"Annual Variance", "0.188"},
-            {"Information Ratio", "1.016"},
-            {"Tracking Error", "0.44"},
-            {"Treynor Ratio", "-0.007"},
-            {"Total Fees", "$20.35"},
-            {"Estimated Strategy Capacity", "$19000000.00"},
+            {"Alpha", "456382350698.561"},
+            {"Beta", "9.229"},
+            {"Annual Standard Deviation", "2.24"},
+            {"Annual Variance", "5.017"},
+            {"Information Ratio", "228504036840.953"},
+            {"Tracking Error", "1.997"},
+            {"Treynor Ratio", "49450701625.718"},
+            {"Total Fees", "$23.65"},
+            {"Estimated Strategy Capacity", "$200000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.138"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.727"},
-            {"Return Over Maximum Drawdown", "-12.061"},
-            {"Portfolio Turnover", "4.916"},
-            {"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", "7c841ca58a4385f42236838e5bf0c382"}
+            {"Portfolio Turnover", "351.80%"},
+            {"OrderListHash", "dd38e7b94027d20942a5aa9ac31a9a7f"}
         };
     }
 }

Algorithm.CSharp/AutomaticIndicatorWarmupRegressionAlgorithm.cs

@@ -105,6 +105,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp };
 
+        /// <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 => 40;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -132,25 +142,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "19.93%"},
             {"OrderListHash", "9e4bfd2eb0b81ee5bc1b197a87ccedbe"}
         };
     }

Algorithm.CSharp/BacktestingBrokerageRegressionAlgorithm.cs

@@ -293,6 +293,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 1341291;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -305,41 +315,23 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "0.400%"},
             {"Expectancy", "-1"},
             {"Net Profit", "-0.329%"},
-            {"Sharpe Ratio", "-11.083"},
-            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Sharpe Ratio", "-7.887"},
+            {"Probabilistic Sharpe Ratio", "1.216%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.003"},
+            {"Alpha", "-0.001"},
             {"Beta", "0.097"},
             {"Annual Standard Deviation", "0.002"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "9.742"},
-            {"Tracking Error", "0.021"},
-            {"Treynor Ratio", "-0.26"},
+            {"Information Ratio", "7.39"},
+            {"Tracking Error", "0.015"},
+            {"Treynor Ratio", "-0.131"},
             {"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", "7f99e1a8ce4675a1e8bbe1ba45967ccd"}
+            {"Portfolio Turnover", "17.02%"},
+            {"OrderListHash", "85cbf92f01c2c91b5f710b7eeefecbe1"}
         };
     }
 }

Algorithm.CSharp/BaseFrameworkRegressionAlgorithm.cs

@@ -0,0 +1,95 @@
+/*
+ * 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 Exception($"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 Language[] Languages { get; } = { 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>
+        /// 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/BasicSetAccountCurrencyAlgorithm.cs

@@ -14,6 +14,7 @@
 */
 
 using System.Collections.Generic;
+using QuantConnect.Brokerages;
 using QuantConnect.Data;
 using QuantConnect.Interfaces;
 
@@ -33,6 +34,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             SetStartDate(2018, 04, 04);  //Set Start Date
             SetEndDate(2018, 04, 04);    //Set End Date
+            SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash);
             //Before setting any cash or adding a Security call SetAccountCurrency
             SetAccountCurrency("EUR");
             SetCash(100000);             //Set Strategy Cash
@@ -63,6 +65,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { 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>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -87,29 +99,11 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$85000.00"},
+            {"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", "-14.148"},
-            {"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", "18dc611407abec4ea47092e71f33f983"}
+            {"Portfolio Turnover", "107.64%"},
+            {"OrderListHash", "2ba443899dcccc79dc0f04441f797bf9"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateAlgorithm.cs

@@ -72,6 +72,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { 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>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -99,25 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "19.93%"},
             {"OrderListHash", "9e4bfd2eb0b81ee5bc1b197a87ccedbe"}
         };
     }

Algorithm.CSharp/BasicTemplateAtreyuAlgorithm.cs

@@ -43,9 +43,6 @@ namespace QuantConnect.Algorithm.CSharp
 
             DefaultOrderProperties = new AtreyuOrderProperties
             {
-                // Can specify the default exchange to execute an order on.
-                // If not specified will default to the primary exchange
-                Exchange = Exchange.NASDAQ,
                 // Currently only support order for the day
                 TimeInForce = TimeInForce.Day
             };
@@ -59,10 +56,8 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (!Portfolio.Invested)
             {
-                // will set 25% of our buying power with a market order that will be routed to exchange set in the default order properties (NASDAQ)
+                // will set 25% of our buying power with a market order
                 SetHoldings("SPY", 0.25m);
-                // will increase our SPY holdings to 50% of our buying power with a market order that will be routed to ARCA
-                SetHoldings("SPY", 0.50m, orderProperties: new AtreyuOrderProperties { Exchange = Exchange.ARCA });
 
                 Debug("Purchased SPY!");
             }
@@ -78,53 +73,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 3901;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <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 Trades", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "93.443%"},
-            {"Drawdown", "1.100%"},
+            {"Compounding Annual Return", "39.143%"},
+            {"Drawdown", "0.500%"},
             {"Expectancy", "0"},
-            {"Net Profit", "0.847%"},
-            {"Sharpe Ratio", "6.515"},
-            {"Probabilistic Sharpe Ratio", "67.535%"},
+            {"Net Profit", "0.423%"},
+            {"Sharpe Ratio", "5.634"},
+            {"Probabilistic Sharpe Ratio", "67.498%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
             {"Alpha", "0"},
             {"Beta", "0"},
-            {"Annual Standard Deviation", "0.11"},
-            {"Annual Variance", "0.012"},
-            {"Information Ratio", "6.515"},
-            {"Tracking Error", "0.11"},
+            {"Annual Standard Deviation", "0.055"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "5.634"},
+            {"Tracking Error", "0.055"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$0.52"},
-            {"Estimated Strategy Capacity", "$8600000.00"},
+            {"Total Fees", "$0.60"},
+            {"Estimated Strategy Capacity", "$150000000.00"},
             {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
-            {"Fitness Score", "0.124"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "78.376"},
-            {"Portfolio Turnover", "0.124"},
-            {"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", "cb542eaaeab5eac3bcae5d915ded30da"}
+            {"Portfolio Turnover", "4.98%"},
+            {"OrderListHash", "d549c64ee7f5e3866712b3c7dbd64caa"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateCfdAlgorithm.cs

@@ -0,0 +1,72 @@
+/*
+ * 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;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Algorithm demonstrating CFD asset types and requesting history.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="history" />
+    /// <meta name="tag" content="cfd" />
+    public class BasicTemplateCfdAlgorithm : QCAlgorithm
+    {
+        private Symbol _symbol;
+
+        /// <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");
+
+            SetStartDate(2019, 2, 20);
+            SetEndDate(2019, 2, 21);
+            SetCash("EUR", 100000);
+
+            _symbol = AddCfd("DE30EUR").Symbol;
+
+            // Historical Data
+            var history = History(_symbol, 60, Resolution.Daily);
+            Log($"Received {history.Count()} bars from CFD historical data call.");
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            // Access Data
+            if (slice.QuoteBars.ContainsKey(_symbol))
+            {
+                var quoteBar = slice.QuoteBars[_symbol];
+                Log($"{quoteBar.EndTime} :: {quoteBar.Close}");
+            }
+
+            if (!Portfolio.Invested)
+                SetHoldings(_symbol, 1);
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug($"{Time} {orderEvent.ToString()}");
+        }
+    }
+}

Algorithm.CSharp/BasicTemplateContinuousFutureAlgorithm.cs

@@ -0,0 +1,159 @@
+/*
+ * 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.Interfaces;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Indicators;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+using Futures = QuantConnect.Securities.Futures;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Basic Continuous Futures Template Algorithm
+    /// </summary>
+    public class BasicTemplateContinuousFutureAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Future _continuousContract;
+        private Security _currentContract;
+        private SimpleMovingAverage _fast;
+        private SimpleMovingAverage _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(2013, 7, 1);
+            SetEndDate(2014, 1, 1);
+
+            _continuousContract = AddFuture(Futures.Indices.SP500EMini,
+                dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
+                dataMappingMode: DataMappingMode.LastTradingDay,
+                contractDepthOffset: 0
+            );
+
+            _fast = SMA(_continuousContract.Symbol, 3, 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)
+        {
+            foreach (var changedEvent in data.SymbolChangedEvents.Values)
+            {
+                Debug($"{Time} - SymbolChanged event: {changedEvent}");
+                if (Time.TimeOfDay != TimeSpan.Zero)
+                {
+                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                }
+            }
+
+            if (!Portfolio.Invested)
+            {
+                if(_fast > _slow)
+                {
+                    _currentContract = Securities[_continuousContract.Mapped];
+                    Buy(_currentContract.Symbol, 1);
+                }
+            }
+            else if(_fast < _slow)
+            {
+                Liquidate();
+            }
+
+            // We check exchange hours because the contract mapping can call OnData outside of regular hours.
+            if (_currentContract != null && _currentContract.Symbol != _continuousContract.Mapped && _continuousContract.Exchange.ExchangeOpen)
+            {
+                Log($"{Time} - rolling position from {_currentContract.Symbol} to {_continuousContract.Mapped}");
+
+                var currentPositionSize = _currentContract.Holdings.Quantity;
+                Liquidate(_currentContract.Symbol);
+                Buy(_continuousContract.Mapped, currentPositionSize);
+                _currentContract = Securities[_continuousContract.Mapped];
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug($"{orderEvent}");
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            Debug($"{Time}-{changes}");
+        }
+
+        /// <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, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 709638;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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%"},
+            {"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"},
+            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
+            {"Portfolio Turnover", "0.92%"},
+            {"OrderListHash", "1fd4b49e9450800981c6dead2bbca995"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateContinuousFutureWithExtendedMarketAlgorithm.cs

@@ -0,0 +1,164 @@
+/*
+ * 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.Interfaces;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Indicators;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+using Futures = QuantConnect.Securities.Futures;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Basic Continuous Futures Template Algorithm with extended market hours
+    /// </summary>
+    public class BasicTemplateContinuousFutureWithExtendedMarketAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Future _continuousContract;
+        private Security _currentContract;
+        private SimpleMovingAverage _fast;
+        private SimpleMovingAverage _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(2013, 7, 1);
+            SetEndDate(2014, 1, 1);
+
+            _continuousContract = AddFuture(Futures.Indices.SP500EMini,
+                dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
+                dataMappingMode: DataMappingMode.LastTradingDay,
+                contractDepthOffset: 0,
+                extendedMarketHours: true
+            );
+
+            _fast = SMA(_continuousContract.Symbol, 3, 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)
+        {
+            foreach (var changedEvent in data.SymbolChangedEvents.Values)
+            {
+                Debug($"{Time} - SymbolChanged event: {changedEvent}");
+                if (Time.TimeOfDay != TimeSpan.Zero)
+                {
+                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                }
+            }
+
+            if (!IsMarketOpen(_continuousContract.Symbol))
+            {
+                return;
+            }
+
+            if (!Portfolio.Invested)
+            {
+                if(_fast > _slow)
+                {
+                    _currentContract = Securities[_continuousContract.Mapped];
+                    Buy(_currentContract.Symbol, 1);
+                }
+            }
+            else if(_fast < _slow)
+            {
+                Liquidate();
+            }
+
+            if (_currentContract != null && _currentContract.Symbol != _continuousContract.Mapped)
+            {
+                Log($"{Time} - rolling position from {_currentContract.Symbol} to {_continuousContract.Mapped}");
+
+                var currentPositionSize = _currentContract.Holdings.Quantity;
+                Liquidate(_currentContract.Symbol);
+                Buy(_continuousContract.Mapped, currentPositionSize);
+                _currentContract = Securities[_continuousContract.Mapped];
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug($"{orderEvent}");
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            Debug($"{Time}-{changes}");
+        }
+
+        /// <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, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 2202510;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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%"},
+            {"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"},
+            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
+            {"Portfolio Turnover", "0.92%"},
+            {"OrderListHash", "adb237703e65b93da5961c0085109732"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateCryptoAlgorithm.cs

@@ -198,6 +198,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 12965;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 240;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -225,25 +235,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "118.08%"},
             {"OrderListHash", "1bf1a6d9dd921982b72a6178f9e50e68"}
         };
     }

Algorithm.CSharp/BasicTemplateCryptoFutureAlgorithm.cs

@@ -0,0 +1,274 @@
+/*
+ * 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(NodaTime.DateTimeZone.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 data)
+        {
+            var interestRates = data.Get<MarginInterestRate>();
+            foreach (var interestRate in interestRates)
+            {
+                _interestPerSymbol[interestRate.Key]++;
+
+                var cachedInterestRate = Securities[interestRate.Key].Cache.GetData<MarginInterestRate>();
+                if (cachedInterestRate != interestRate.Value)
+                {
+                    throw new Exception($"Unexpected cached margin interest rate for {interestRate.Key}!");
+                }
+            }
+
+            if (_fast > _slow)
+            {
+                if (!Portfolio.Invested && Transactions.OrdersCount == 0)
+                {
+                    var ticket = Buy(_btcUsd.Symbol, 50);
+                    if (ticket.Status != OrderStatus.Invalid)
+                    {
+                        throw new Exception($"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 Exception($"Unexpected TotalSaleVolume {btcUsdHoldings.TotalSaleVolume}");
+                    }
+                    if (Math.Abs(btcUsdHoldings.AbsoluteHoldingsCost - holdingsValueBtcUsd) > 1)
+                    {
+                        throw new Exception($"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 Exception($"Unexpected margin used {marginUsed}");
+                    }
+
+                    Buy(_adaUsdt.Symbol, 1000);
+
+                    marginUsed = Portfolio.TotalMarginUsed - marginUsed;
+                    var adaUsdtHoldings = _adaUsdt.Holdings;
+
+                    // USDT/BUSD futures value is based on it's price
+                    var holdingsValueUsdt = _adaUsdt.Price * _adaUsdt.SymbolProperties.ContractMultiplier * 1000;
+
+                    if (Math.Abs(adaUsdtHoldings.TotalSaleVolume - holdingsValueUsdt) > 1)
+                    {
+                        throw new Exception($"Unexpected TotalSaleVolume {adaUsdtHoldings.TotalSaleVolume}");
+                    }
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
+                    {
+                        throw new Exception($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                    }
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost * 0.05m - marginUsed) > 1
+                        || _adaUsdt.BuyingPowerModel.GetMaintenanceMargin(_adaUsdt) != marginUsed)
+                    {
+                        throw new Exception($"Unexpected margin used {marginUsed}");
+                    }
+
+                    // position just opened should be just spread here
+                    var profit = Portfolio.TotalUnrealizedProfit;
+                    if ((5 - Math.Abs(profit)) < 0)
+                    {
+                        throw new Exception($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                    }
+
+                    if (Portfolio.TotalProfit != 0)
+                    {
+                        throw new Exception($"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 Exception($"Unexpected holdings cost {btcUsdHoldings.HoldingsCost}");
+                    }
+
+                    Sell(_adaUsdt.Symbol, 3000);
+
+                    var adaUsdtHoldings = _adaUsdt.Holdings;
+
+                    // USDT/BUSD futures value is based on it's price
+                    var holdingsValueUsdt = _adaUsdt.Price * _adaUsdt.SymbolProperties.ContractMultiplier * 2000;
+
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
+                    {
+                        throw new Exception($"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 Exception($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                    }
+                    // we barely did any difference on the previous trade
+                    if ((5 - Math.Abs(Portfolio.TotalProfit)) < 0)
+                    {
+                        throw new Exception($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                    }
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_interestPerSymbol[_adaUsdt.Symbol] != 1)
+            {
+                throw new Exception($"Unexpected interest rate count {_interestPerSymbol[_adaUsdt.Symbol]}");
+            }
+
+            if (_interestPerSymbol[_btcUsd.Symbol] != 3)
+            {
+                throw new Exception($"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 Language[] Languages { get; } = { Language.CSharp };
+
+        /// <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>
+        /// 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%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe 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", "254f39d98378b1e7aa397b1f1e49c6cc"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateCryptoFutureHourlyAlgorithm.cs

@@ -0,0 +1,237 @@
+/*
+ * 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(NodaTime.DateTimeZone.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 data)
+        {
+            var interestRates = data.Get<MarginInterestRate>();
+            foreach (var interestRate in interestRates)
+            {
+                _interestPerSymbol[interestRate.Key]++;
+
+                var cachedInterestRate = Securities[interestRate.Key].Cache.GetData<MarginInterestRate>();
+                if (cachedInterestRate != interestRate.Value)
+                {
+                    throw new Exception($"Unexpected cached margin interest rate for {interestRate.Key}!");
+                }
+            }
+
+            if (_fast > _slow)
+            {
+                if (!Portfolio.Invested && Transactions.OrdersCount == 0)
+                {
+                    var ticket = Buy(_adaUsdt.Symbol, 100000);
+                    if(ticket.Status != OrderStatus.Invalid)
+                    {
+                        throw new Exception($"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 Exception($"Unexpected TotalSaleVolume {adaUsdtHoldings.TotalSaleVolume}");
+                    }
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
+                    {
+                        throw new Exception($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                    }
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost * 0.05m - marginUsed) > 1
+                        || _adaUsdt.BuyingPowerModel.GetMaintenanceMargin(_adaUsdt) != marginUsed)
+                    {
+                        throw new Exception($"Unexpected margin used {marginUsed}");
+                    }
+
+                    // position just opened should be just spread here
+                    var profit = Portfolio.TotalUnrealizedProfit;
+                    if ((5 - Math.Abs(profit)) < 0)
+                    {
+                        throw new Exception($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                    }
+
+                    if (Portfolio.TotalProfit != 0)
+                    {
+                        throw new Exception($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                    }
+                }
+            }
+            else
+            {
+                // let's revert our position and double
+                if (Time.Hour > 10 && Transactions.OrdersCount == 2)
+                {
+                    Sell(_adaUsdt.Symbol, 3000);
+
+                    var adaUsdtHoldings = _adaUsdt.Holdings;
+
+                    // USDT/BUSD futures value is based on it's price
+                    var holdingsValueUsdt = _adaUsdt.Price * _adaUsdt.SymbolProperties.ContractMultiplier * 2000;
+
+                    if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
+                    {
+                        throw new Exception($"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 Exception($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                    }
+                    // we barely did any difference on the previous trade
+                    if ((5 - Math.Abs(Portfolio.TotalProfit)) < 0)
+                    {
+                        throw new Exception($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                    }
+                }
+
+                if (Time.Hour >= 22 && Transactions.OrdersCount == 3)
+                {
+                    Liquidate();
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_interestPerSymbol[_adaUsdt.Symbol] != 1)
+            {
+                throw new Exception($"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 Language[] Languages { get; } = { Language.CSharp };
+
+        /// <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>
+        /// 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%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe 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", "d2c6198197a4d18fa0a81f5933d935a6"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateDailyAlgorithm.cs

@@ -63,6 +63,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 73;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -75,40 +85,22 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "1.200%"},
             {"Expectancy", "0"},
             {"Net Profit", "3.464%"},
-            {"Sharpe Ratio", "9.933"},
-            {"Probabilistic Sharpe Ratio", "82.470%"},
+            {"Sharpe Ratio", "19.148"},
+            {"Probabilistic Sharpe Ratio", "97.754%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "1.957"},
-            {"Beta", "-0.125"},
-            {"Annual Standard Deviation", "0.164"},
-            {"Annual Variance", "0.027"},
-            {"Information Ratio", "-4.577"},
-            {"Tracking Error", "0.225"},
-            {"Treynor Ratio", "-13.006"},
+            {"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"},
             {"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%"},
+            {"Portfolio Turnover", "10.09%"},
             {"OrderListHash", "33d01821923c397f999cfb2e5b5928ad"}
         };
     }

Algorithm.CSharp/BasicTemplateFrameworkAlgorithm.cs

@@ -84,6 +84,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public virtual Language[] Languages { get; } = { 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>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -111,25 +121,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"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%"},
+            {"Portfolio Turnover", "59.86%"},
             {"OrderListHash", "ad2216297c759d8e5aef48ff065f8919"}
         };
     }

Algorithm.CSharp/BasicTemplateFutureOptionAlgorithm.cs

@@ -0,0 +1,95 @@
+/*
+ * 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.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Algorithm demonstrating FutureOption asset types and requesting history.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="history" />
+    /// <meta name="tag" content="future option" />
+    public class BasicTemplateFutureOptionAlgorithm : QCAlgorithm
+    {
+        private Symbol _symbol;
+
+        /// <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, 1, 1);
+            SetEndDate(2022, 2, 1);
+            SetCash(100000);
+
+            var gold_futures = AddFuture(Futures.Metals.Gold, Resolution.Minute);
+            gold_futures.SetFilter(0, 180);
+            _symbol = gold_futures.Symbol;
+            AddFutureOption(_symbol, universe => universe.Strikes(-5, +5)
+                                                        .CallsOnly()
+                                                        .BackMonth()
+                                                        .OnlyApplyFilterAtMarketOpen());
+
+            // Historical Data
+            var history = History(_symbol, 60, Resolution.Daily);
+            Log($"Received {history.Count()} bars from {_symbol} FutureOption historical data call.");
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            // Access Data
+            foreach(var kvp in slice.OptionChains)
+            {
+                var underlyingFutureContract = kvp.Key.Underlying;
+                var chain = kvp.Value;
+
+                if (chain.Count() == 0) continue;
+
+                foreach(var contract in chain)
+                {
+                    Log($@"Canonical Symbol: {kvp.Key}; 
+                        Contract: {contract}; 
+                        Right: {contract.Right}; 
+                        Expiry: {contract.Expiry}; 
+                        Bid price: {contract.BidPrice}; 
+                        Ask price: {contract.AskPrice}; 
+                        Implied Volatility: {contract.ImpliedVolatility}");
+                }
+
+                if (!Portfolio.Invested)
+                {
+                    var atmStrike = chain.OrderBy(x => Math.Abs(chain.Underlying.Price - x.Strike)).First().Strike;
+                    var selectedContract = chain.Where(x => x.Strike == atmStrike).OrderByDescending(x => x.Expiry).First();
+                    MarketOrder(selectedContract.Symbol, 1);
+                }
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug($"{Time} {orderEvent.ToString()}");
+        }
+    }
+}

Algorithm.CSharp/BasicTemplateFutureRolloverAlgorithm.cs

@@ -0,0 +1,217 @@
+/*
+ * 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;
+            public decimal Price;
+            public bool IsLong;
+            public bool IsShort;
+            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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 1345;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 4;
+
+        /// <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", "0.53%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "3.011%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0.528%"},
+            {"Sharpe Ratio", "1.999"},
+            {"Probabilistic Sharpe Ratio", "83.704%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.023"},
+            {"Beta", "-0.004"},
+            {"Annual Standard Deviation", "0.011"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-4.774"},
+            {"Tracking Error", "0.084"},
+            {"Treynor Ratio", "-4.853"},
+            {"Total Fees", "$4.30"},
+            {"Estimated Strategy Capacity", "$5900000000.00"},
+            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
+            {"Portfolio Turnover", "0.27%"},
+            {"OrderListHash", "40e4b91ec89383f6501d9ba324e50eb9"}
+        };
+    }  
+}

Algorithm.CSharp/BasicTemplateFuturesAlgorithm.cs

@@ -18,6 +18,7 @@ using System;
 using System.Collections.Generic;
 using System.Linq;
 using QuantConnect.Data;
+using QuantConnect.Data.UniverseSelection;
 using QuantConnect.Interfaces;
 using QuantConnect.Securities;
 using QuantConnect.Securities.Future;
@@ -58,12 +59,15 @@ namespace QuantConnect.Algorithm.CSharp
 
             // set our expiry filter for this futures chain
             // SetFilter method accepts TimeSpan objects or integer for days.
-            // The following statements yield the same filtering criteria 
+            // The following statements yield the same filtering criteria
             futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
             futureGold.SetFilter(0, 182);
 
             var benchmark = AddEquity("SPY");
             SetBenchmark(benchmark.Symbol);
+
+            var seeder = new FuncSecuritySeeder(GetLastKnownPrices);
+            SetSecurityInitializer(security => seeder.SeedSecurity(security));
         }
 
         /// <summary>
@@ -72,6 +76,15 @@ namespace QuantConnect.Algorithm.CSharp
         /// <param name="slice">The current slice of data keyed by symbol string</param>
         public override void OnData(Slice slice)
         {
+            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}!");
+                }
+            }
+
             if (!Portfolio.Invested)
             {
                 foreach(var chain in slice.FutureChains)
@@ -112,6 +125,19 @@ namespace QuantConnect.Algorithm.CSharp
             var maintenanceIntraday = futureMarginModel.MaintenanceIntradayMarginRequirement;
         }
 
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            foreach (var addedSecurity in changes.AddedSecurities)
+            {
+                if (addedSecurity.Symbol.SecurityType == SecurityType.Future
+                    && !addedSecurity.Symbol.IsCanonical()
+                    && !addedSecurity.HasData)
+                {
+                    throw new Exception($"Future contracts did not work up as expected: {addedSecurity.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>
@@ -122,53 +148,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 68645;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 340;
+
         /// <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", "8220"},
+            {"Total Trades", "2700"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "-100.000%"},
-            {"Drawdown", "13.500%"},
-            {"Expectancy", "-0.818"},
-            {"Net Profit", "-13.517%"},
-            {"Sharpe Ratio", "-2.678"},
+            {"Compounding Annual Return", "-99.777%"},
+            {"Drawdown", "4.400%"},
+            {"Expectancy", "-0.724"},
+            {"Net Profit", "-4.430%"},
+            {"Sharpe Ratio", "-31.389"},
             {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "89%"},
-            {"Win Rate", "11%"},
-            {"Profit-Loss Ratio", "0.69"},
-            {"Alpha", "4.469"},
-            {"Beta", "-0.961"},
-            {"Annual Standard Deviation", "0.373"},
-            {"Annual Variance", "0.139"},
-            {"Information Ratio", "-13.191"},
-            {"Tracking Error", "0.507"},
-            {"Treynor Ratio", "1.04"},
-            {"Total Fees", "$15207.00"},
-            {"Estimated Strategy Capacity", "$8000.00"},
+            {"Loss Rate", "83%"},
+            {"Win Rate", "17%"},
+            {"Profit-Loss Ratio", "0.65"},
+            {"Alpha", "-3.059"},
+            {"Beta", "0.128"},
+            {"Annual Standard Deviation", "0.031"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-81.232"},
+            {"Tracking Error", "0.212"},
+            {"Treynor Ratio", "-7.618"},
+            {"Total Fees", "$6237.00"},
+            {"Estimated Strategy Capacity", "$14000.00"},
             {"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
-            {"Fitness Score", "0.033"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-8.62"},
-            {"Return Over Maximum Drawdown", "-7.81"},
-            {"Portfolio Turnover", "302.321"},
-            {"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", "35b3f4b7a225468d42ca085386a2383e"}
+            {"Portfolio Turnover", "9912.69%"},
+            {"OrderListHash", "8f92e1528c6477a156449fd1e86527e7"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesDailyAlgorithm.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;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add futures with daily resolution.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        protected virtual Resolution Resolution => Resolution.Daily;
+        protected virtual bool ExtendedMarketHours => false;
+
+        // S&P 500 EMini futures
+        private const string RootSP500 = Futures.Indices.SP500EMini;
+
+        // Gold futures
+        private const string RootGold = Futures.Metals.Gold;
+        private Future _futureSP500;
+        private Future _futureGold;
+
+        /// <summary>
+        /// Initialize your algorithm and add desired assets.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 08);
+            SetEndDate(2014, 10, 10);
+            SetCash(1000000);
+
+            _futureSP500 = AddFuture(RootSP500, Resolution, extendedMarketHours: ExtendedMarketHours);
+            _futureGold = AddFuture(RootGold, Resolution, extendedMarketHours: ExtendedMarketHours);
+
+            // set our expiry filter for this futures chain
+            // SetFilter method accepts TimeSpan objects or integer for days.
+            // The following statements yield the same filtering criteria
+            _futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
+            _futureGold.SetFilter(0, 182);
+        }
+
+        /// <summary>
+        /// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
+        /// </summary>
+        /// <param name="slice">The current slice of data keyed by symbol string</param>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                foreach(var chain in slice.FutureChains)
+                {
+                    // find the front contract expiring no earlier than in 90 days
+                    var contract = (
+                        from futuresContract in chain.Value.OrderBy(x => x.Expiry)
+                        where futuresContract.Expiry > Time.Date.AddDays(90)
+                        select futuresContract
+                    ).FirstOrDefault();
+
+                    // 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))
+                    {
+                        MarketOrder(contract.Symbol, 1);
+                    }
+                }
+            }
+            // Same as above, check for cases like trading on a friday night.
+            else if (Securities.Values.Where(x => x.Invested).All(x => x.Exchange.Hours.IsOpen(Time, true)))
+            {
+                Liquidate();
+            }
+
+            foreach (var changedEvent in slice.SymbolChangedEvents.Values)
+            {
+                if (Time.TimeOfDay != TimeSpan.Zero)
+                {
+                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                }
+            }
+        }
+
+        /// <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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 15217;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 0;
+
+        /// <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"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.397"},
+            {"Tracking Error", "0.089"},
+            {"Treynor Ratio", "5.665"},
+            {"Total Fees", "$263.30"},
+            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
+            {"Portfolio Turnover", "3.15%"},
+            {"OrderListHash", "b75b224669c374dcbacc33f946a1cc7c"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesFrameworkAlgorithm.cs

@@ -31,9 +31,12 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class BasicTemplateFuturesFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
+        protected virtual bool ExtendedMarketHours => false;
+
         public override void Initialize()
         {
             UniverseSettings.Resolution = Resolution.Minute;
+            UniverseSettings.ExtendedMarketHours = ExtendedMarketHours;
 
             SetStartDate(2013, 10, 07);
             SetEndDate(2013, 10, 11);
@@ -123,60 +126,52 @@ namespace QuantConnect.Algorithm.CSharp
         /// <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;
+        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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 43786;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 0;
 
         /// <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>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-92.656%"},
-            {"Drawdown", "5.000%"},
+            {"Compounding Annual Return", "-81.734%"},
+            {"Drawdown", "4.100%"},
             {"Expectancy", "0"},
-            {"Net Profit", "-3.312%"},
-            {"Sharpe Ratio", "-7.795"},
-            {"Probabilistic Sharpe Ratio", "0.164%"},
+            {"Net Profit", "-2.169%"},
+            {"Sharpe Ratio", "-10.195"},
+            {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-1.362"},
-            {"Beta", "0.257"},
-            {"Annual Standard Deviation", "0.109"},
-            {"Annual Variance", "0.012"},
-            {"Information Ratio", "-14.947"},
-            {"Tracking Error", "0.19"},
-            {"Treynor Ratio", "-3.309"},
-            {"Total Fees", "$3.70"},
-            {"Estimated Strategy Capacity", "$52000000.00"},
+            {"Alpha", "-1.206"},
+            {"Beta", "0.238"},
+            {"Annual Standard Deviation", "0.072"},
+            {"Annual Variance", "0.005"},
+            {"Information Ratio", "-15.404"},
+            {"Tracking Error", "0.176"},
+            {"Treynor Ratio", "-3.077"},
+            {"Total Fees", "$4.62"},
+            {"Estimated Strategy Capacity", "$17000000.00"},
             {"Lowest Capacity Asset", "GC VL5E74HP3EE5"},
-            {"Fitness Score", "0.009"},
-            {"Kelly Criterion Estimate", "-112.972"},
-            {"Kelly Criterion Probability Value", "0.671"},
-            {"Sortino Ratio", "-8.425"},
-            {"Return Over Maximum Drawdown", "-35.219"},
-            {"Portfolio Turnover", "0.548"},
-            {"Total Insights Generated", "6"},
-            {"Total Insights Closed", "5"},
-            {"Total Insights Analysis Completed", "5"},
-            {"Long Insight Count", "6"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$-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", "43.23%"},
+            {"OrderListHash", "323b899ae80aa839e320806411665ce7"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesFrameworkWithExtendedMarketAlgorithm.cs

@@ -0,0 +1,77 @@
+/*
+ * 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.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;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Basic template futures framework algorithm uses framework components to define an algorithm
+    /// that trades futures.
+    /// </summary>
+    public class BasicTemplateFuturesFrameworkWithExtendedMarketAlgorithm : BasicTemplateFuturesFrameworkAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+
+        /// <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 };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 123753;
+
+        /// <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%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "-92.667%"},
+            {"Drawdown", "5.000%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "-3.314%"},
+            {"Sharpe Ratio", "-6.303"},
+            {"Probabilistic Sharpe Ratio", "9.333%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-1.465"},
+            {"Beta", "0.312"},
+            {"Annual Standard Deviation", "0.134"},
+            {"Annual Variance", "0.018"},
+            {"Information Ratio", "-14.77"},
+            {"Tracking Error", "0.192"},
+            {"Treynor Ratio", "-2.718"},
+            {"Total Fees", "$4.62"},
+            {"Estimated Strategy Capacity", "$52000000.00"},
+            {"Lowest Capacity Asset", "GC VL5E74HP3EE5"},
+            {"Portfolio Turnover", "43.77%"},
+            {"OrderListHash", "18ffd3a774c68da83d867e3b09e3e05d"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesHistoryAlgorithm.cs

@@ -36,6 +36,9 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="futures" />
     public class BasicTemplateFuturesHistoryAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
+        protected virtual bool ExtendedMarketHours => false;
+        protected virtual int ExpectedHistoryCallCount => 42;
+
         // S&P 500 EMini futures
         private string [] roots = new []
         {
@@ -44,7 +47,6 @@ namespace QuantConnect.Algorithm.CSharp
         };
 
         private int _successCount = 0;
-
         public override void Initialize()
         {
             SetStartDate(2013, 10, 8);
@@ -54,7 +56,7 @@ namespace QuantConnect.Algorithm.CSharp
             foreach (var root in roots)
             {
                 // set our expiry filter for this futures chain
-                AddFuture(root, Resolution.Minute).SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
+                AddFuture(root, Resolution.Minute, extendedMarketHours: ExtendedMarketHours).SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
             }
 
             SetBenchmark(d => 1000000);
@@ -74,7 +76,7 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void OnEndOfAlgorithm()
         {
-            if (_successCount < 49)
+            if (_successCount < ExpectedHistoryCallCount)
             {
                 throw new Exception($"Scheduled Event did not assert history call as many times as expected: {_successCount}/49");
             }
@@ -118,7 +120,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {
@@ -128,17 +130,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// <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;
+        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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 44184;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 4818;
 
         /// <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>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "0"},
             {"Average Win", "0%"},
@@ -162,25 +174,7 @@ 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

@@ -0,0 +1,88 @@
+/*
+ * 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.Securities;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to get access to futures history for a given root symbol with extended market hours.
+    /// It also shows how you can prefilter contracts easily based on expirations, and inspect the futures
+    /// chain to pick a specific contract to trade.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="history and warm up" />
+    /// <meta name="tag" content="history" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesHistoryWithExtendedMarketHoursAlgorithm : BasicTemplateFuturesHistoryAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+        protected override int ExpectedHistoryCallCount => 49;
+
+        /// <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 };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 134096;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 5539;
+
+        /// <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"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe 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/BasicTemplateFuturesHourlyAlgorithm.cs

@@ -0,0 +1,77 @@
+/*
+ * 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 QuantConnect.Interfaces;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This regressions tests the BasicTemplateFuturesDailyAlgorithm with hour data
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesHourlyAlgorithm : BasicTemplateFuturesDailyAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Hour;
+
+        /// <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 };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 96027;
+
+        /// <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%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "-1.610%"},
+            {"Drawdown", "1.600%"},
+            {"Expectancy", "-0.841"},
+            {"Net Profit", "-1.622%"},
+            {"Sharpe Ratio", "-5.105"},
+            {"Probabilistic Sharpe Ratio", "0.000%"},
+            {"Loss Rate", "96%"},
+            {"Win Rate", "4%"},
+            {"Profit-Loss Ratio", "3.21"},
+            {"Alpha", "-0.01"},
+            {"Beta", "-0.003"},
+            {"Annual Standard Deviation", "0.002"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.473"},
+            {"Tracking Error", "0.089"},
+            {"Treynor Ratio", "3.179"},
+            {"Total Fees", "$1456.18"},
+            {"Estimated Strategy Capacity", "$6000.00"},
+            {"Lowest Capacity Asset", "ES VP274HSU1AF5"},
+            {"Portfolio Turnover", "17.91%"},
+            {"OrderListHash", "8842e0b890f721371ebf3c25328dee5b"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketAlgorithm.cs

@@ -0,0 +1,192 @@
+/*
+ * 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 QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add futures for a given underlying asset.
+    /// It also shows how you can prefilter contracts easily based on expirations, and how you
+    /// can inspect the futures chain to pick a specific contract to trade.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesWithExtendedMarketAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _contractSymbol;
+
+        // 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.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 08);
+            SetEndDate(2013, 10, 10);
+            SetCash(1000000);
+
+            var futureSP500 = AddFuture(RootSP500, extendedMarketHours: true);
+            var futureGold = AddFuture(RootGold, extendedMarketHours: true);
+
+            // set our expiry filter for this futures chain
+            // SetFilter method accepts TimeSpan objects or integer for days.
+            // The following statements yield the same filtering criteria
+            futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
+            futureGold.SetFilter(0, 182);
+
+            var benchmark = AddEquity("SPY");
+            SetBenchmark(benchmark.Symbol);
+
+            var seeder = new FuncSecuritySeeder(GetLastKnownPrices);
+            SetSecurityInitializer(security => seeder.SeedSecurity(security));
+        }
+
+        /// <summary>
+        /// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
+        /// </summary>
+        /// <param name="slice">The current slice of data keyed by symbol string</param>
+        public override void OnData(Slice slice)
+        {
+            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}!");
+                }
+            }
+
+            if (!Portfolio.Invested)
+            {
+                foreach(var chain in slice.FutureChains)
+                {
+                    // find the front contract expiring no earlier than in 90 days
+                    var contract = (
+                        from futuresContract in chain.Value.OrderBy(x => x.Expiry)
+                        where futuresContract.Expiry > Time.Date.AddDays(90)
+                        select futuresContract
+                    ).FirstOrDefault();
+
+                    // if found, trade it
+                    if (contract != null)
+                    {
+                        _contractSymbol = contract.Symbol;
+                        MarketOrder(_contractSymbol, 1);
+                    }
+                }
+            }
+            else
+            {
+                Liquidate();
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            // Get the margin requirements
+            var buyingPowerModel = Securities[_contractSymbol].BuyingPowerModel;
+            var futureMarginModel = buyingPowerModel as FutureMarginModel;
+            if (buyingPowerModel == null)
+            {
+                throw new Exception($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
+            }
+            var initialOvernight = futureMarginModel.InitialOvernightMarginRequirement;
+            var maintenanceOvernight = futureMarginModel.MaintenanceOvernightMarginRequirement;
+            var initialIntraday = futureMarginModel.InitialIntradayMarginRequirement;
+            var maintenanceIntraday = futureMarginModel.MaintenanceIntradayMarginRequirement;
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            foreach (var addedSecurity in changes.AddedSecurities)
+            {
+                if (addedSecurity.Symbol.SecurityType == SecurityType.Future
+                    && !addedSecurity.Symbol.IsCanonical()
+                    && !addedSecurity.HasData)
+                {
+                    throw new Exception($"Future contracts did not work up as expected: {addedSecurity.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 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, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 204087;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 340;
+
+        /// <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"},
+            {"Average Win", "0.00%"},
+            {"Average Loss", "0.00%"},
+            {"Compounding Annual Return", "-100.000%"},
+            {"Drawdown", "13.900%"},
+            {"Expectancy", "-0.824"},
+            {"Net Profit", "-13.874%"},
+            {"Sharpe Ratio", "-19.202"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "89%"},
+            {"Win Rate", "11%"},
+            {"Profit-Loss Ratio", "0.64"},
+            {"Alpha", "2.477"},
+            {"Beta", "-0.215"},
+            {"Annual Standard Deviation", "0.052"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-58.37"},
+            {"Tracking Error", "0.295"},
+            {"Treynor Ratio", "4.66"},
+            {"Total Fees", "$19131.42"},
+            {"Estimated Strategy Capacity", "$130000.00"},
+            {"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
+            {"Portfolio Turnover", "32523.20%"},
+            {"OrderListHash", "85cdd035d7c7a3da178d1c2dff31f1bd"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketDailyAlgorithm.cs

@@ -0,0 +1,79 @@
+/*
+ * 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 QuantConnect.Interfaces;
+using QuantConnect.Orders;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add futures with daily resolution and extended market hours.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesWithExtendedMarketDailyAlgorithm : BasicTemplateFuturesDailyAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+
+        /// <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 };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 17431;
+
+        /// <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"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.409"},
+            {"Tracking Error", "0.089"},
+            {"Treynor Ratio", "3.618"},
+            {"Total Fees", "$338.96"},
+            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
+            {"Portfolio Turnover", "4.07%"},
+            {"OrderListHash", "48bfc4d255420cb589e00cf582554e0a"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketHourlyAlgorithm.cs

@@ -0,0 +1,77 @@
+/*
+ * 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 QuantConnect.Interfaces;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This regressions tests the BasicTemplateFuturesDailyAlgorithm with hour data and extended market hours
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesWithExtendedMarketHourlyAlgorithm : BasicTemplateFuturesHourlyAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+
+        /// <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 };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 248521;
+
+        /// <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"},
+            {"Average Win", "0.01%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "-4.666%"},
+            {"Drawdown", "4.700%"},
+            {"Expectancy", "-0.911"},
+            {"Net Profit", "-4.700%"},
+            {"Sharpe Ratio", "-5.792"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "97%"},
+            {"Win Rate", "3%"},
+            {"Profit-Loss Ratio", "2.04"},
+            {"Alpha", "-0.031"},
+            {"Beta", "-0.008"},
+            {"Annual Standard Deviation", "0.005"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.701"},
+            {"Tracking Error", "0.09"},
+            {"Treynor Ratio", "4.096"},
+            {"Total Fees", "$4521.78"},
+            {"Estimated Strategy Capacity", "$2000.00"},
+            {"Lowest Capacity Asset", "ES VP274HSU1AF5"},
+            {"Portfolio Turnover", "56.49%"},
+            {"OrderListHash", "2402a307b20aee195b77b8478d7ca64d"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateHourlyAlgorithm.cs

@@ -0,0 +1,116 @@
+/*
+ * 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;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Basic template algorithm simply initializes the date range and cash. This is a skeleton
+    /// framework you can use for designing an algorithm.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="using quantconnect" />
+    /// <meta name="tag" content="trading and orders" />
+    public class BasicTemplateHourlyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
+
+        /// <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, 07);  //Set Start Date
+            SetEndDate(2013, 10, 11);    //Set End Date
+            SetCash(100000);             //Set Strategy Cash
+
+            // Find more symbols here: http://quantconnect.com/data
+            // Forex, CFD, Equities Resolutions: Tick, Second, Minute, Hour, Daily.
+            // Futures Resolution: Tick, Second, Minute
+            // Options Resolution: Minute Only.
+            AddEquity("SPY", Resolution.Hour);
+
+            // There are other assets with similar methods. See "Selecting Options" etc for more details.
+            // AddFuture, AddForex, AddCfd, AddOption
+        }
+
+        /// <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)
+        {
+            if (!Portfolio.Invested)
+            {
+                SetHoldings(_spy, 1);
+                Debug("Purchased Stock");
+            }
+        }
+
+        /// <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 => 78;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "227.693%"},
+            {"Drawdown", "2.000%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "1.529%"},
+            {"Sharpe Ratio", "8.889"},
+            {"Probabilistic Sharpe Ratio", "67.609%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.005"},
+            {"Beta", "0.996"},
+            {"Annual Standard Deviation", "0.222"},
+            {"Annual Variance", "0.049"},
+            {"Information Ratio", "-14.564"},
+            {"Tracking Error", "0.001"},
+            {"Treynor Ratio", "1.978"},
+            {"Total Fees", "$3.44"},
+            {"Estimated Strategy Capacity", "$110000000.00"},
+            {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
+            {"Portfolio Turnover", "19.96%"},
+            {"OrderListHash", "f409be3a7c63d9c1394c2e6c005a15ee"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateIndexAlgorithm.cs

@@ -30,36 +30,39 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="indexes" />
     public class BasicTemplateIndexAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private Symbol _spx;
-        private Symbol _spxOption;
+        protected Symbol Spx;
+        protected Symbol SpxOption;
         private ExponentialMovingAverage _emaSlow;
         private ExponentialMovingAverage _emaFast;
 
+        protected virtual Resolution Resolution => Resolution.Minute;
+        protected virtual int StartDay => 4;
+
         /// <summary>
         /// Initialize your algorithm and add desired assets.
         /// </summary>
         public override void Initialize()
         {
-            SetStartDate(2021, 1, 4);
-            SetEndDate(2021, 1, 15);
+            SetStartDate(2021, 1, StartDay);
+            SetEndDate(2021, 1, 18);
             SetCash(1000000);
 
             // Use indicator for signal; but it cannot be traded
-            _spx = AddIndex("SPX", Resolution.Minute).Symbol;
+            Spx = AddIndex("SPX", Resolution).Symbol;
 
             // Trade on SPX ITM calls
-            _spxOption = QuantConnect.Symbol.CreateOption(
-                _spx,
+            SpxOption = QuantConnect.Symbol.CreateOption(
+                Spx,
                 Market.USA,
                 OptionStyle.European,
                 OptionRight.Call,
                 3200m,
                 new DateTime(2021, 1, 15));
 
-            AddIndexOptionContract(_spxOption, Resolution.Minute);
+            AddIndexOptionContract(SpxOption, Resolution);
 
-            _emaSlow = EMA(_spx, 80);
-            _emaFast = EMA(_spx, 200);
+            _emaSlow = EMA(Spx, 80);
+            _emaFast = EMA(Spx, 200);
         }
 
         /// <summary>
@@ -67,7 +70,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public override void OnData(Slice slice)
         {
-            if (!slice.Bars.ContainsKey(_spx) || !slice.Bars.ContainsKey(_spxOption))
+            if (!slice.Bars.ContainsKey(Spx) || !slice.Bars.ContainsKey(SpxOption))
             {
                 return;
             }
@@ -80,7 +83,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             if (_emaFast > _emaSlow)
             {
-                SetHoldings(_spxOption, 1);
+                SetHoldings(SpxOption, 1);
             }
             else
             {
@@ -90,7 +93,7 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void OnEndOfAlgorithm()
         {
-            if (Portfolio[_spx].TotalSaleVolume > 0)
+            if (Portfolio[Spx].TotalSaleVolume > 0)
             {
                 throw new Exception("Index is not tradable.");
             }
@@ -99,60 +102,52 @@ namespace QuantConnect.Algorithm.CSharp
         /// <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;
+        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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 16049;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 0;
 
         /// <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>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "4"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-53.10%"},
-            {"Compounding Annual Return", "-96.172%"},
-            {"Drawdown", "10.100%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-9.915%"},
-            {"Sharpe Ratio", "-4.217"},
-            {"Probabilistic Sharpe Ratio", "0.052%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
+            {"Total Trades", "3"},
+            {"Average Win", "6.15%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "435.569%"},
+            {"Drawdown", "3.400%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "5.516%"},
+            {"Sharpe Ratio", "-6.262"},
+            {"Probabilistic Sharpe Ratio", "0.011%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.908"},
-            {"Beta", "0.468"},
-            {"Annual Standard Deviation", "0.139"},
-            {"Annual Variance", "0.019"},
-            {"Information Ratio", "-9.003"},
-            {"Tracking Error", "0.142"},
-            {"Treynor Ratio", "-1.251"},
+            {"Alpha", "-0.223"},
+            {"Beta", "0.02"},
+            {"Annual Standard Deviation", "0.034"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-7.032"},
+            {"Tracking Error", "0.107"},
+            {"Treynor Ratio", "-10.779"},
             {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$14000000.00"},
+            {"Estimated Strategy Capacity", "$2000.00"},
             {"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
-            {"Fitness Score", "0.044"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.96"},
-            {"Return Over Maximum Drawdown", "-10.171"},
-            {"Portfolio Turnover", "0.34"},
-            {"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", "52521ab779446daf4d38a7c9bbbdd893"}
+            {"Portfolio Turnover", "24.07%"},
+            {"OrderListHash", "5dbee236086bb2c39e2fbeac068280fd"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexDailyAlgorithm.cs

@@ -0,0 +1,93 @@
+/*
+ * 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 System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression for running an Index algorithm with Daily data
+    /// </summary>
+    public class BasicTemplateIndexDailyAlgorithm : BasicTemplateIndexAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Daily;
+        protected override int StartDay => 1;
+
+        // 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 = 0;
+
+        /// <summary>
+        /// Purchase a contract when we are not invested, liquidate otherwise
+        /// </summary>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                // SPX Index is not tradable, but we can trade an option
+                MarketOrder(SpxOption, 1);
+            }
+            else
+            {
+                Liquidate();
+            }
+
+            // Count how many slices we receive with SPX data in it to assert later
+            if (slice.ContainsKey(Spx))
+            {
+                BarCounter++;
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (BarCounter != ExpectedBarCount)
+            {
+                throw new ArgumentException($"Bar Count {BarCounter} is not expected count of {ExpectedBarCount}");
+            }
+        }
+
+        /// <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 override bool CanRunLocally { get; } = true;
+
+        /// <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 };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 0;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 0;
+
+        /// <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>
+        {
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateIndexHourlyAlgorithm.cs

@@ -0,0 +1,64 @@
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression for running an Index algorithm with Hourly data
+    /// </summary>
+    public class BasicTemplateIndexHourlyAlgorithm : BasicTemplateIndexDailyAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Hour;
+        protected override int ExpectedBarCount => base.ExpectedBarCount * 7;
+
+        /// <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 override bool CanRunLocally { get; } = true;
+
+        /// <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 };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 391;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 0;
+
+        /// <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", "71"},
+            {"Average Win", "1.28%"},
+            {"Average Loss", "-0.06%"},
+            {"Compounding Annual Return", "-20.546%"},
+            {"Drawdown", "1.800%"},
+            {"Expectancy", "-0.402"},
+            {"Net Profit", "-0.922%"},
+            {"Sharpe Ratio", "-2.856"},
+            {"Probabilistic Sharpe Ratio", "22.230%"},
+            {"Loss Rate", "97%"},
+            {"Win Rate", "3%"},
+            {"Profit-Loss Ratio", "19.95"},
+            {"Alpha", "-0.155"},
+            {"Beta", "0.025"},
+            {"Annual Standard Deviation", "0.053"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-2.07"},
+            {"Tracking Error", "0.121"},
+            {"Treynor Ratio", "-6.089"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$200000.00"},
+            {"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
+            {"Portfolio Turnover", "24.63%"},
+            {"OrderListHash", "9e974939d13fd3255c6291a65d2c1eb9"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateIndexOptionsAlgorithm.cs

@@ -30,20 +30,22 @@ namespace QuantConnect.Algorithm.CSharp
         private Symbol _spx;
         private ExponentialMovingAverage _emaSlow;
         private ExponentialMovingAverage _emaFast;
+        protected virtual Resolution Resolution => Resolution.Minute;
+        protected virtual int StartDay => 4;
 
         /// <summary>
         /// Initialize your algorithm and add desired assets.
         /// </summary>
         public override void Initialize()
         {
-            SetStartDate(2021, 1, 4);
+            SetStartDate(2021, 1, StartDay);
             SetEndDate(2021, 2, 1);
             SetCash(1000000);
 
             // Use indicator for signal; but it cannot be traded.
             // We will instead trade on SPX options
-            _spx = AddIndex("SPX", Resolution.Minute).Symbol;
-            var spxOptions = AddIndexOption(_spx, Resolution.Minute);
+            _spx = AddIndex("SPX", Resolution).Symbol;
+            var spxOptions = AddIndexOption(_spx, Resolution);
             spxOptions.SetFilter(filterFunc => filterFunc.CallsOnly());
 
             _emaSlow = EMA(_spx, 80);
@@ -122,17 +124,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// <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; } = false;
+        public virtual bool CanRunLocally { get; } = false;
 
         /// <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 virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 0;
+
+        /// </summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 0;
 
         /// <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>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "8220"},
             {"Average Win", "0.00%"},

Algorithm.CSharp/BasicTemplateIndexOptionsDailyAlgorithm.cs

@@ -0,0 +1,85 @@
+/*
+ * 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 System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression for running an IndexOptions algorithm with Daily data
+    /// </summary>
+    public class BasicTemplateIndexOptionsDailyAlgorithm : BasicTemplateIndexOptionsAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Daily;
+        protected override int StartDay => 1;
+        
+        /// <summary>
+        /// Index EMA Cross trading index options of the index.
+        /// </summary>
+        public override void OnData(Slice slice)
+        {
+            foreach (var chain in slice.OptionChains.Values)
+            {
+                // Select the contract with the lowest AskPrice
+                var contract = chain.Contracts.OrderBy(x => x.Value.AskPrice).FirstOrDefault().Value;
+
+                if (contract == null)
+                {
+                    return;
+                }
+                
+                if (Portfolio.Invested)
+                {
+                    Liquidate();
+                }
+                else
+                {
+                    MarketOrder(contract.Symbol, 1);
+                }
+            }
+        }
+
+        /// <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 override bool CanRunLocally { get; } = true;
+
+        /// <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 };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 0;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 0;
+
+        /// <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>
+        {
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateIndexOptionsHourlyAlgorithm.cs

@@ -0,0 +1,79 @@
+/*
+ * 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>
+    /// Regression for running an IndexOptions algorithm with Hourly data
+    /// </summary>
+    public class BasicTemplateIndexOptionsHourlyAlgorithm : BasicTemplateIndexOptionsDailyAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Hour;
+
+        /// <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 override bool CanRunLocally { get; } = true;
+
+        /// <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 };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 2143;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 0;
+
+        /// <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", "72"},
+            {"Average Win", "0.00%"},
+            {"Average Loss", "0.00%"},
+            {"Compounding Annual Return", "-0.006%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "-0.486"},
+            {"Net Profit", "0.000%"},
+            {"Sharpe Ratio", "-1.628"},
+            {"Probabilistic Sharpe Ratio", "17.439%"},
+            {"Loss Rate", "97%"},
+            {"Win Rate", "3%"},
+            {"Profit-Loss Ratio", "17.50"},
+            {"Alpha", "-0"},
+            {"Beta", "-0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-0.449"},
+            {"Tracking Error", "0.138"},
+            {"Treynor Ratio", "1.87"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", "SPX XL80P59H5E6M|SPX 31"},
+            {"Portfolio Turnover", "0.00%"},
+            {"OrderListHash", "0df3713aeb32e9c0738200f2a109e2f9"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateIndiaAlgorithm.cs

@@ -14,8 +14,9 @@
 */
 
 using QuantConnect.Data;
-using QuantConnect.Orders;
 using System.Collections.Generic;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -26,29 +27,29 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="using data" />
     /// <meta name="tag" content="using quantconnect" />
     /// <meta name="tag" content="trading and orders" />
-    public class BasicTemplateIndiaAlgorithm : QCAlgorithm
+    public class BasicTemplateIndiaAlgorithm : 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(2003, 10, 07);  //Set Start Date
-            SetEndDate(2003, 10, 11);    //Set End Date
-            SetCash(100000);             //Set Strategy Cash
+            SetAccountCurrency("INR");  //Set Account Currency
+            SetStartDate(2019, 1, 23);  //Set Start Date
+            SetEndDate(2019, 10, 31);   //Set End Date
+            SetCash(100000);            //Set Strategy Cash
 
             // Find more symbols here: http://quantconnect.com/data
             // Equities Resolutions: Tick, Second, Minute, Hour, Daily.
-            AddEquity("UNIONBANK", Resolution.Second, Market.India);
-            
-            //Set Order Prperties as per the requirements for order placement
-            DefaultOrderProperties = new ZerodhaOrderProperties(exchange: Exchange.NSE);
+            AddEquity("YESBANK", Resolution.Minute, Market.India);
+
+            //Set Order Properties as per the requirements for order placement
+            DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE);
             //override default productType value set in config.json if needed - order specific productType value
-            //DefaultOrderProperties = new ZerodhaOrderProperties(exchange: "nse",ZerodhaOrderProperties.KiteProductType.CNC);
+            //DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE, IndiaOrderProperties.IndiaProductType.CNC);
 
             // General Debug statement for acknowledgement
-            Debug("Intialization Done");
-
+            Debug("Initialization Done");
         }
 
         /// <summary>
@@ -59,11 +60,10 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (!Portfolio.Invested)
             {
-                var marketTicket = MarketOrder("UNIONBANK", 1);
+                var marketTicket = MarketOrder("YESBANK", 1);
             }
         }
 
-    
         public override void OnOrderEvent(OrderEvent orderEvent)
         {
             if (orderEvent.Status.IsFill())
@@ -75,60 +75,52 @@ namespace QuantConnect.Algorithm.CSharp
         /// <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; } = false;
+        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 };
+        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 29524;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
 
         /// <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 Trades", "1"},
             {"Average Win", "0%"},
-            {"Average Loss", "-1.01%"},
-            {"Compounding Annual Return", "261.134%"},
-            {"Drawdown", "2.200%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "1.655%"},
-            {"Sharpe Ratio", "8.505"},
-            {"Probabilistic Sharpe Ratio", "66.840%"},
-            {"Loss Rate", "100%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "-0.010%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "-0.008%"},
+            {"Sharpe Ratio", "-1.183"},
+            {"Probabilistic Sharpe Ratio", "0.001%"},
+            {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.091"},
-            {"Beta", "1.006"},
-            {"Annual Standard Deviation", "0.224"},
-            {"Annual Variance", "0.05"},
-            {"Information Ratio", "-33.445"},
-            {"Tracking Error", "0.002"},
-            {"Treynor Ratio", "1.893"},
-            {"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"}
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.183"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "₹6.00"},
+            {"Estimated Strategy Capacity", "₹61000000000.00"},
+            {"Lowest Capacity Asset", "YESBANK UL"},
+            {"Portfolio Turnover", "0.00%"},
+            {"OrderListHash", "6cc69218edd7bd461678b9ee0c575db5"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndiaIndexAlgorithm.cs

@@ -0,0 +1,150 @@
+/*
+ * 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 System.Collections.Generic;
+using QuantConnect.Indicators;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add index asset types.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="indexes" />
+    public class BasicTemplateIndiaIndexAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        protected Symbol Nifty;
+        protected Symbol NiftyETF;
+        private ExponentialMovingAverage _emaSlow;
+        private ExponentialMovingAverage _emaFast;
+
+        /// <summary>
+        /// Initialize your algorithm and add desired assets.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetAccountCurrency("INR"); //Set Account Currency
+            SetStartDate(2019, 1, 1);  //Set End Date
+            SetEndDate(2019, 1, 5);    //Set End Date
+            SetCash(1000000);          //Set Strategy Cash
+
+            // Use indicator for signal; but it cannot be traded
+            Nifty = AddIndex("NIFTY50", Resolution.Minute, Market.India).Symbol;
+
+            //Trade Index based ETF
+            NiftyETF = AddEquity("JUNIORBEES", Resolution.Minute, Market.India).Symbol;
+
+            //Set Order Properties as per the requirements for order placement
+            DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE);
+
+            _emaSlow = EMA(Nifty, 80);
+            _emaFast = EMA(Nifty, 200);
+        }
+
+        /// <summary>
+        /// Index EMA Cross trading underlying.
+        /// </summary>
+        public override void OnData(Slice slice)
+        {
+            if (!slice.Bars.ContainsKey(Nifty) || !slice.Bars.ContainsKey(NiftyETF))
+            {
+                return;
+            }
+
+            // Warm up indicators
+            if (!_emaSlow.IsReady)
+            {
+                return;
+            }
+
+            if (_emaFast > _emaSlow)
+            {
+                if (!Portfolio.Invested)
+                {
+                    var marketTicket = MarketOrder(NiftyETF, 1);
+                }
+            }
+            else
+            {
+                Liquidate();
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (Portfolio[Nifty].TotalSaleVolume > 0)
+            {
+                throw new Exception("Index is not tradable.");
+            }
+        }
+
+        /// <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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 2882;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0.00%"},
+            {"Compounding Annual Return", "-0.386%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "-0.004%"},
+            {"Sharpe Ratio", "-23.595"},
+            {"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", "-23.595"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "₹36.00"},
+            {"Estimated Strategy Capacity", "₹84000.00"},
+            {"Lowest Capacity Asset", "JUNIORBEES UL"},
+            {"Portfolio Turnover", "0.04%"},
+            {"OrderListHash", "57558324bc9b67b36ae33c3e1c191740"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateIntrinioEconomicData.cs

@@ -31,7 +31,7 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="trading and orders" />
     public class BasicTemplateIntrinioEconomicData : QCAlgorithm
     {
-        // Set your Intrinino user and password.
+        // Set your Intrinio user and password.
         public string _user = "";
         public string _password = "";
 
@@ -41,7 +41,7 @@ namespace QuantConnect.Algorithm.CSharp
         private readonly Identity _brent = new Identity("Brent");
         private readonly Identity _wti = new Identity("WTI");
 
-        private CompositeIndicator<IndicatorDataPoint> _spread;
+        private CompositeIndicator _spread;
 
         private ExponentialMovingAverage _emaWti;
 
@@ -55,7 +55,7 @@ namespace QuantConnect.Algorithm.CSharp
             SetEndDate(year: 2013, month: 12, day: 31); //Set End Date
             SetCash(startingCash: 100000); //Set Strategy Cash
 
-            // Set your Intrinino user and password.
+            // Set your Intrinio user and password.
             IntrinioConfig.SetUserAndPassword(_user, _password);
 
             // Set Intrinio config to make 1 call each minute, default is 1 call each 5 seconds.

Algorithm.CSharp/BasicTemplateMultiAssetAlgorithm.cs

@@ -212,7 +212,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {

Algorithm.CSharp/BasicTemplateOptionEquityStrategyAlgorithm.cs

@@ -82,7 +82,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {
@@ -99,6 +99,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 475788;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -123,29 +133,11 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$10.00"},
+            {"Total Fees", "$75.00"},
             {"Estimated Strategy Capacity", "$84000.00"},
             {"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", "61.34%"},
+            {"OrderListHash", "cee5cc2b0f80c308b496cac0b8668163"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionStrategyAlgorithm.cs

@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {
@@ -109,12 +109,22 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 476196;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <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 Trades", "418"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
@@ -133,29 +143,11 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$778.00"},
-            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Total Fees", "$418.00"},
+            {"Estimated Strategy Capacity", "$3000.00"},
             {"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", "338.56%"},
+            {"OrderListHash", "e0289a2989c91934656ff7e578f5e810"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionTradesAlgorithm.cs

@@ -87,7 +87,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {

Algorithm.CSharp/BasicTemplateOptionsAlgorithm.cs

@@ -89,7 +89,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {
@@ -106,6 +106,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 475777;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -133,26 +143,8 @@ 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", "838e313ba57850227ec810ed8fb85a23"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsDailyAlgorithm.cs

@@ -0,0 +1,163 @@
+/*
+ * 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 QuantConnect.Data.Market;
+using QuantConnect.Orders;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add options for a given underlying equity security.
+    /// It also shows how you can prefilter contracts easily based on strikes and expirations, and how you
+    /// can inspect the option chain to pick a specific option contract to trade.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="options" />
+    /// <meta name="tag" content="filter selection" />
+    public class BasicTemplateOptionsDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private const string UnderlyingTicker = "GOOG";
+        public Symbol OptionSymbol;
+        private bool _optionExpired;
+
+        public override void Initialize()
+        {
+            SetStartDate(2015, 12, 23);
+            SetEndDate(2016, 1, 20);
+            SetCash(100000);
+
+            var equity = AddEquity(UnderlyingTicker, Resolution.Daily);
+            var option = AddOption(UnderlyingTicker, Resolution.Daily);
+            OptionSymbol = option.Symbol;
+
+            option.SetFilter(x => x.CallsOnly().Strikes(0, 1).Expiration(0, 30));
+
+            // use the underlying equity as the benchmark
+            SetBenchmark(equity.Symbol);
+        }
+
+        /// <summary>
+        /// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
+        /// </summary>
+        /// <param name="slice">The current slice of data keyed by symbol string</param>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                OptionChain 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 found, trade it
+                        MarketOrder(contract.Symbol, 1);
+                    }
+                }
+            }
+        }
+
+        /// <summary>
+        /// Order fill event handler. On an order fill update the resulting information is passed to this method.
+        /// </summary>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
+        /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Log(orderEvent.ToString());
+
+            // Check for our expected OTM option expiry
+            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))
+                {
+                    throw new ArgumentException($"Expiry event was not at the correct time, {orderEvent.UtcTime}");
+                }
+
+                _optionExpired = true;
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            // Assert we had our option expire and fill a liquidation order
+            if (_optionExpired != true)
+            {
+                throw new ArgumentException("Algorithm did not process the option expiration like expected");
+            }
+        }
+
+        /// <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, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 39654;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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", "-1.31%"},
+            {"Compounding Annual Return", "-15.304%"},
+            {"Drawdown", "1.300%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "-1.311%"},
+            {"Sharpe Ratio", "-3.31"},
+            {"Probabilistic Sharpe Ratio", "0.035%"},
+            {"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"},
+            {"Total Fees", "$1.00"},
+            {"Estimated Strategy Capacity", "$18000.00"},
+            {"Lowest Capacity Asset", "GOOCV W78ZFMML01JA|GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "0.05%"},
+            {"OrderListHash", "0b52bbe98ade8e3aab943e64fcf4abfe"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateOptionsFilterUniverseAlgorithm.cs

@@ -41,7 +41,7 @@ namespace QuantConnect.Algorithm.CSharp
         public override void Initialize()
         {
             SetStartDate(2015, 12, 24);
-            SetEndDate(2015, 12, 24);
+            SetEndDate(2015, 12, 28);
             SetCash(100000);
 
             var equity = AddEquity(UnderlyingTicker);
@@ -97,6 +97,16 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 1322413;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
@@ -104,14 +114,14 @@ namespace QuantConnect.Algorithm.CSharp
         {
             {"Total Trades", "2"},
             {"Average Win", "0%"},
-            {"Average Loss", "0%"},
-            {"Compounding Annual Return", "0%"},
-            {"Drawdown", "0%"},
-            {"Expectancy", "0"},
-            {"Net Profit", "0%"},
+            {"Average Loss", "-0.40%"},
+            {"Compounding Annual Return", "-21.622%"},
+            {"Drawdown", "0.300%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "-0.311%"},
             {"Sharpe Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "0%"},
+            {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
             {"Alpha", "0"},
@@ -124,26 +134,8 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$1.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "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", "92d8a50efe230524512404dab66b19dd"}
+            {"Portfolio Turnover", "15.08%"},
+            {"OrderListHash", "0f8537495f5744c02191656d6b3f9205"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsFrameworkAlgorithm.cs

@@ -36,7 +36,7 @@ namespace QuantConnect.Algorithm.CSharp
             UniverseSettings.Resolution = Resolution.Minute;
 
             SetStartDate(2014, 06, 05);
-            SetEndDate(2014, 06, 06);
+            SetEndDate(2014, 06, 09);
             SetCash(100000);
 
             // set framework models
@@ -136,53 +136,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 990979;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
         /// <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%"},
-            {"Average Loss", "0%"},
+            {"Average Win", "0.14%"},
+            {"Average Loss", "-0.28%"},
             {"Compounding Annual Return", "0%"},
-            {"Drawdown", "0%"},
-            {"Expectancy", "0"},
-            {"Net Profit", "0%"},
-            {"Sharpe 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"},
+            {"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"},
-            {"Estimated Strategy Capacity", "$74000.00"},
-            {"Lowest Capacity Asset", "AAPL 2ZQGWTSSZ0WLI|AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0.327"},
-            {"Kelly Criterion Probability Value", "1"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "26"},
-            {"Total Insights Closed", "24"},
-            {"Total Insights Analysis Completed", "24"},
-            {"Long Insight Count", "26"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$31.01809"},
-            {"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", "ce06ddfa4b2ffeb666a8910ac8836992"}
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "13.46%"},
+            {"OrderListHash", "83c9fb13ee32284702779eff8d11c608"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsHourlyAlgorithm.cs

@@ -0,0 +1,150 @@
+/*
+ * 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 QuantConnect.Data.Market;
+using QuantConnect.Orders;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add options for a given underlying equity security.
+    /// It also shows how you can prefilter contracts easily based on strikes and expirations, and how you
+    /// can inspect the option chain to pick a specific option contract to trade.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="options" />
+    /// <meta name="tag" content="filter selection" />
+    public class BasicTemplateOptionsHourlyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private const string UnderlyingTicker = "AAPL";
+        public Symbol OptionSymbol;
+
+        public override void Initialize()
+        {
+            SetStartDate(2014, 6, 6);
+            SetEndDate(2014, 6, 9);
+            SetCash(100000);
+
+            var equity = AddEquity(UnderlyingTicker, Resolution.Hour);
+            var option = AddOption(UnderlyingTicker, Resolution.Hour);
+            OptionSymbol = option.Symbol;
+
+            // set our strike/expiry filter for this option chain
+            option.SetFilter(u => u.Strikes(-2, +2)
+                                   // Expiration method accepts TimeSpan objects or integer for days.
+                                   // The following statements yield the same filtering criteria
+                                   .Expiration(0, 180));
+            // .Expiration(TimeSpan.Zero, TimeSpan.FromDays(180)));
+
+            // use the underlying equity as the benchmark
+            SetBenchmark(equity.Symbol);
+        }
+
+        /// <summary>
+        /// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
+        /// </summary>
+        /// <param name="slice">The current slice of data keyed by symbol string</param>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested && IsMarketOpen(OptionSymbol))
+            {
+                OptionChain chain;
+                if (slice.OptionChains.TryGetValue(OptionSymbol, out chain))
+                {
+                    // we find at the money (ATM) put contract with farthest expiration
+                    var atmContract = chain
+                        .OrderByDescending(x => x.Expiry)
+                        .ThenBy(x => Math.Abs(chain.Underlying.Price - x.Strike))
+                        .ThenByDescending(x => x.Right)
+                        .FirstOrDefault();
+
+                    if (atmContract != null && IsMarketOpen(atmContract.Symbol))
+                    {
+                        // if found, trade it
+                        MarketOrder(atmContract.Symbol, 1);
+                        MarketOnCloseOrder(atmContract.Symbol, -1);
+                    }
+                }
+            }
+        }
+
+        /// <summary>
+        /// Order fill event handler. On an order fill update the resulting information is passed to this method.
+        /// </summary>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
+        /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Log(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 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, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 32492;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <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%"},
+            {"Average Loss", "-0.07%"},
+            {"Compounding Annual Return", "-12.496%"},
+            {"Drawdown", "0.200%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "-0.134%"},
+            {"Sharpe Ratio", "-8.839"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "100%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.083"},
+            {"Beta", "-0.054"},
+            {"Annual Standard Deviation", "0.008"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-18.699"},
+            {"Tracking Error", "0.155"},
+            {"Treynor Ratio", "1.296"},
+            {"Total Fees", "$4.00"},
+            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Lowest Capacity Asset", "AAPL 2ZTXYMUAHCIAU|AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "2.28%"},
+            {"OrderListHash", "81e8a822d43de2165c1d3f52964ec312"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateSPXWeeklyIndexOptionsAlgorithm.cs

@@ -0,0 +1,146 @@
+/*
+ * 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);
+
+            var spx = AddIndex("SPX").Symbol;
+
+            // 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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 65536;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 0;
+
+        /// <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", "5"},
+            {"Average Win", "0%"},
+            {"Average Loss", "-0.69%"},
+            {"Compounding Annual Return", "58.005%"},
+            {"Drawdown", "0.400%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "0.588%"},
+            {"Sharpe Ratio", "1.448"},
+            {"Probabilistic Sharpe Ratio", "51.980%"},
+            {"Loss Rate", "100%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.288"},
+            {"Beta", "-0.04"},
+            {"Annual Standard Deviation", "0.004"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-98.963"},
+            {"Tracking Error", "0.072"},
+            {"Treynor Ratio", "-0.149"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$8400000.00"},
+            {"Lowest Capacity Asset", "SPXW 31K54PVWHUJHQ|SPX 31"},
+            {"Portfolio Turnover", "0.48%"},
+            {"OrderListHash", "174bd0a99916d58ca3f12139306940db"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateSPXWeeklyIndexOptionsStrategyAlgorithm.cs

@@ -0,0 +1,150 @@
+/*
+ * 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(0, 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 Exception("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 Language[] Languages { get; } = { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 35451;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 0;
+
+        /// <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", "0.12%"},
+            {"Average Loss", "0.00%"},
+            {"Compounding Annual Return", "8.975%"},
+            {"Drawdown", "0.100%"},
+            {"Expectancy", "62.078"},
+            {"Net Profit", "0.110%"},
+            {"Sharpe Ratio", "-7.925"},
+            {"Probabilistic Sharpe Ratio", "1.216%"},
+            {"Loss Rate", "50%"},
+            {"Win Rate", "50%"},
+            {"Profit-Loss Ratio", "125.16"},
+            {"Alpha", "-0.012"},
+            {"Beta", "0.001"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-103.223"},
+            {"Tracking Error", "0.069"},
+            {"Treynor Ratio", "-2.449"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$1800000.00"},
+            {"Lowest Capacity Asset", "SPXW XKX6S2GM9PGU|SPX 31"},
+            {"Portfolio Turnover", "0.03%"},
+            {"OrderListHash", "38db27781e4df93687d0895df9796c7d"}
+        };
+    }
+}

Algorithm.CSharp/Benchmarks/BasicTemplateBenchmark.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -28,7 +28,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
         public override void Initialize()
         {
             SetStartDate(2000, 01, 01);
-            SetEndDate(2017, 01, 01);
+            SetEndDate(2022, 01, 01);
             SetBenchmark(dt => 1m);
             AddEquity("SPY");
         }
@@ -42,4 +42,4 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
             }
         }
     }
-}
+}

Algorithm.CSharp/Benchmarks/CoarseFineUniverseSelectionBenchmark.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -34,7 +34,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
             UniverseSettings.Resolution = Resolution.Minute;
 
             SetStartDate(2017, 11, 01);
-            SetEndDate(2018, 01, 01);
+            SetEndDate(2018, 3, 01);
             SetCash(50000);
 
             AddUniverse(CoarseSelectionFunction, FineSelectionFunction);
@@ -98,4 +98,4 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
             _changes = changes;
         }
     }
-}
+}

Algorithm.CSharp/Benchmarks/EmptyEquityAndOptions400Benchmark.cs

@@ -0,0 +1,87 @@
+/*
+ * 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;
+
+namespace QuantConnect.Algorithm.CSharp.Benchmarks
+{
+    /// <summary>
+    /// Benchmark Algorithm: Loading and synchronization of 500 equity minute symbols and their options.
+    /// </summary>
+    public class EmptyEquityAndOptions400Benchmark : QCAlgorithm
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2022, 5, 11);
+            SetEndDate(2022, 5, 12);
+
+            var equity_symbols = new[] {
+
+"MARK", "TSN", "DT", "RDW", "CVE", "NXPI", "FIVN", "CLX", "SPXL", "BKSY", "NUGT", "CF", "NEGG",
+"RH", "SIRI", "ITUB", "CSX", "AUR", "LIDR", "CMPS", "DHI", "GLW", "NTES", "CIFR", "S", "HSBC",
+"HIPO", "WTRH", "AMRN", "BIIB", "RIO", "EDIT", "TEAM", "CNK", "BUD", "MILE", "AEHR", "DOCN",
+"CLSK", "BROS", "MLCO", "SBLK", "ICLN", "OPK", "CNC", "SKX", "SESN", "VRM", "ASML", "BBAI",
+"HON", "MRIN", "BLMN", "NTNX", "POWW", "FOUR", "HOG", "GOGO", "MGNI", "GENI", "XPDI",
+"DG", "PSX", "RRC", "CORT", "MET", "UMC", "INMD", "RBAC", "ISRG", "BOX", "DVAX", "CRVS", "HLT",
+"BKNG", "BENE", "CLVS", "ESSC", "PTRA", "BE", "FPAC", "YETI", "DOCS", "DB", "EBON", "RDS.B",
+"ERIC", "BSIG", "INTU", "MNTS", "BCTX", "BLU", "FIS", "MAC", "WMB", "TTWO", "ARDX", "SWBI",
+"ELY", "INDA", "REAL", "ACI", "APRN", "BHP", "CPB", "SLQT", "ARKF", "TSP", "OKE", "NVTA", "META",
+"CSTM", "KMX", "IBB", "AGEN", "WOOF", "MJ", "HYZN", "RSI", "JCI", "EXC", "HPE", "SI", "WPM",
+"PRTY", "BBD", "FVRR", "CANO", "INDI", "MDLZ", "KOLD", "AMBA", "SOXS", "RSX", "ZEN", "PUBM",
+"VLDR", "CI", "ISEE", "GEO", "BKR", "DHR", "GRPN", "NRXP", "ACN", "MAT", "BODY", "ENDP",
+"SHPW", "AVIR", "GPN", "BILL", "BZ", "CERN", "ARVL", "DNMR", "NTR", "FSM", "BMBL", "PAAS",
+"INVZ", "ANF", "CL", "XP", "CS", "KD", "WW", "AHT", "GRTX", "XLC", "BLDP", "HTA", "APT", "BYSI",
+"ENB", "TRIT", "VTNR", "AVCT", "SLI", "CP", "CAH", "ALLY", "FIGS", "PXD", "TPX", "ZI", "BKLN", "SKIN",
+"LNG", "NU", "CX", "GSM", "NXE", "REI", "MNDT", "IP", "BLOK", "IAA", "TIP", "MCHP", "EVTL", "BIGC",
+"IGV", "LOTZ", "EWC", "DRI", "PSTG", "APLS", "KIND", "BBIO", "APPH", "FIVE", "LSPD", "SHAK",
+"COMM", "NAT", "VFC", "AMT", "VRTX", "RGS", "DD", "GBIL", "LICY", "ACHR", "FLR", "HGEN", "TECL",
+"SEAC", "NVS", "NTAP", "ML", "SBSW", "XRX", "UA", "NNOX", "SFT", "FE", "APP", "KEY", "CDEV",
+"DPZ", "BARK", "SPR", "CNQ", "XL", "AXSM", "ECH", "RNG", "AMLP", "ENG", "BTI", "REKR",
+"STZ", "BK", "HEAR", "LEV", "SKT", "HBI", "ALB", "CAG", "MNKD", "NMM", "BIRD", "CIEN", "SILJ",
+"STNG", "GUSH", "GIS", "PRPL", "SDOW", "GNRC", "ERX", "GES", "CPE", "FBRX", "WM", "ESTC",
+"GOED", "STLD", "LILM", "JNK", "BOIL", "ALZN", "IRBT", "KOPN", "AU", "TPR", "RWLK", "TROX",
+"TMO", "AVDL", "XSPA", "JKS", "PACB", "LOGI", "BLK", "REGN", "CFVI", "EGHT", "ATNF", "PRU",
+"URBN", "KMB", "SIX", "CME", "ENVX", "NVTS", "CELH", "CSIQ", "GSL", "PAA", "WU", "MOMO",
+"TOL", "WEN", "GTE", "EXAS", "GDRX", "PVH", "BFLY", "SRTY", "UDOW", "NCR", "ALTO", "CRTD",
+"GOCO", "ALK", "TTM", "DFS", "VFF", "ANTM", "FREY", "WY", "ACWI", "PNC", "SYY", "SNY", "CRK",
+"SO", "XXII", "PBF", "AER", "RKLY", "SOL", "CND", "MPLX", "JNPR", "FTCV", "CLR", "XHB", "YY",
+"POSH", "HIMS", "LIFE", "XENE", "ADM", "ROST", "MIR", "NRG", "AAP", "SSYS", "KBH", "KKR", "PLAN",
+"DUK", "WIMI", "DBRG", "WSM", "LTHM", "OVV", "CFLT", "EWT", "UNFI", "TX", "EMR", "IMGN", "K",
+"ONON", "UNIT", "LEVI", "ADTX", "UPWK", "DBA", "VOO", "FATH", "URI", "MPW", "JNUG", "RDFN",
+"OSCR", "WOLF", "SYF", "GOGL", "HES", "PHM", "CWEB", "ALDX", "BTWN", "AFL", "PPL", "CIM"
+
+            };
+            Settings.DataSubscriptionLimit = 1000000;
+            SetWarmUp(TimeSpan.FromDays(1));
+            foreach(var ticker in equity_symbols)
+            {
+                var option = AddOption(ticker);
+                option.SetFilter(1, 7, 0, 90);
+            }
+
+            AddEquity("SPY");
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (IsWarmingUp)
+            {
+                return;
+            }
+            Quit("The end!");
+        }
+    }
+}

Algorithm.CSharp/Benchmarks/EmptyMinute400EquityBenchmark.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -30,8 +30,8 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
     {
         public override void Initialize()
         {
-            SetStartDate(2015, 10, 1);
-            SetEndDate(2015, 11, 15);
+            SetStartDate(2015, 9, 1);
+            SetEndDate(2015, 12, 1);
             foreach (var symbol in Symbols.Equity.All.Take(400))
             {
                 AddSecurity(SecurityType.Equity, symbol);
@@ -402,4 +402,4 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
             #endregion
         }
     }
-}
+}

Algorithm.CSharp/Benchmarks/EmptySingleSecuritySecondEquityBenchmark.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -27,7 +27,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
         public override void Initialize()
         {
             SetStartDate(2008, 01, 01);
-            SetEndDate(2009, 01, 01);
+            SetEndDate(2008, 06, 01);
             SetBenchmark(dt => 1m);
             AddEquity("SPY", Resolution.Second);
         }
@@ -36,4 +36,4 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
         {
         }
     }
-}
+}

Algorithm.CSharp/Benchmarks/HistoryRequestBenchmark.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -23,7 +23,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
         public override void Initialize()
         {
             SetStartDate(2010, 01, 01);
-            SetEndDate(2018, 01, 01);
+            SetEndDate(2022, 01, 01);
             SetCash(10000);
             _symbol = AddEquity("SPY").Symbol;
         }
@@ -38,4 +38,4 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
             var dailyOpen = dailyHistory.Open;
         }
     }
-}
+}

Algorithm.CSharp/Benchmarks/IndicatorRibbonBenchmark.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -32,7 +32,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
         public override void Initialize()
         {
             SetStartDate(2010, 01, 01);
-            SetEndDate(2018, 01, 01);
+            SetEndDate(2022, 01, 01);
 
             AddSecurity(SecurityType.Equity, "SPY", Resolution.Minute);
 
@@ -51,7 +51,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
                 // define an indicator that takes the output of the sma and pipes it into our delay indicator
                 var delayedSma = delay.Of(sma);
 
-                // register our new 'delayedSma' for automaic updates on a daily resolution
+                // register our new 'delayedSma' for automatic updates on a daily resolution
                 RegisterIndicator(_spy, delayedSma, Resolution.Daily, data => data.Value);
 
                 return delayedSma;
@@ -68,4 +68,4 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
             }
         }
     }
-}
+}

Algorithm.CSharp/Benchmarks/ScheduledEventsBenchmark.cs

@@ -1,4 +1,4 @@
-/*
+/*
 /*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
@@ -24,7 +24,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
         public override void Initialize()
         {
             SetStartDate(2011, 1, 1);
-            SetEndDate(2018, 1, 1);
+            SetEndDate(2022, 1, 1);
             SetCash(100000);
             AddEquity("SPY");
             foreach (int period in Enumerable.Range(0, 300))
@@ -37,4 +37,4 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
         public override void OnData(Slice data) { }
         private void Rebalance() { }
     }
-}
+}