Option universe resolution improvements (#8324)

* Option universe improvements

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

* Minor fix for research test

.devcontainer/devcontainer.json

@@ -24,7 +24,7 @@
 	// "forwardPorts": [],
 
 	// Uncomment the next line to run commands after the container is created - for example installing curl.
-	"postCreateCommand": "dotnet nuget add source /Lean/LocalPackages; dos2unix /Lean/.vscode/launch_research.sh",
+	"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": [ 

.github/workflows/api-tests.yml

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

.github/workflows/gh-actions.yml

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

.github/workflows/regression-tests.yml

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

.github/workflows/report-generator.yml

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

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

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

.github/workflows/virtual-environments.yml

@@ -10,52 +10,48 @@ on:
 jobs:
   build:
     runs-on: ubuntu-20.04
-    container:
-        image: quantconnect/lean:foundation
     steps:
-      - uses: actions/checkout@v2
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Free space
+        run: df -h && rm -rf /usr/share/dotnet && sudo rm -rf /usr/local/lib/android && sudo rm -rf /opt/ghc && rm -rf /opt/hostedtoolcache* && df -h
 
-      - name: Build
-        run: dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
-
-      - name: Python Virtual Environment System Packages
-        run: python -m venv /lean-testenv --system-site-packages && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.99 && deactivate
-
-      - name: Run Virtual Environment Test System Packages
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment"
-
-      - name: Python Virtual Environment
-        run: rm -rf /lean-testenv && python -m venv /lean-testenv && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.99 && deactivate
-
-      - name: Run Virtual Environment Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment"
-
-      - name: Run Python Package Tests
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests"
-
-      - name: Run Pomegranate Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.PomegranateTest"
-
-      - name: Run Tensorforce Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorforceTests"
-
-      - name: Run StableBaselines Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.StableBaselinesTest"
-
-      - name: Run AxPlatform Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.AxPlatformTest"
-
-      - name: Run NeuralTangents Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.NeuralTangentsTest"
-
-      - name: Run NBeats Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.NBeatsTest"
-
-      - name: Run Tensorly Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorlyTest"
-
-      - name: Run Ignite Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.IgniteTest"
-
-      - name: Run Hvplot Python Package Test
-        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.HvplotTest"
+      - uses: addnab/docker-run-action@v3
+        with:
+          image: quantconnect/lean:foundation
+          options: --workdir /__w/Lean/Lean -v /home/runner/work:/__w
+          shell: bash
+          run: |
+            # Build
+            dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln && \
+            # Python Virtual Environment System Packages
+            python -m venv /lean-testenv --system-site-packages && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.185 && deactivate && \
+            # Run Virtual Environment Test System Packages
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment" && \
+            # Python Virtual Environment
+            rm -rf /lean-testenv && python -m venv /lean-testenv && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.185 && deactivate && \
+            # Run Virtual Environment Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment" && \
+            # Run Python Package Tests
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run StableBaselines Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.StableBaselinesTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run AxPlatform Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.AxPlatformTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run TensorlyTest Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorlyTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run NeuralTangents, Ignite Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.NeuralTangentsTest|IgniteTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run TensorflowTest
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorflowTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run TensorflowProbability
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorflowProbabilityTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run Hvplot Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.HvplotTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run Keras Python Package Test
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.KerasTest" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run Transformers
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.Transformers" --blame-hang-timeout 120seconds --blame-crash && \
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.XTransformers" --blame-hang-timeout 120seconds --blame-crash && \
+            # Run Shap
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.ShapTest" --blame-hang-timeout 120seconds --blame-crash

.gitignore

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

.vs/readme.md

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

.vscode/readme.md

@@ -156,5 +156,5 @@ _Figure 2: Python Debugger Messages_
 Here we will cover some common issues with setting this up. This section will expand as we get user feedback!
 
 - 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 bug, if this occurs use the command palette to restart omnisharp. (Ctrl+Shift+P "OmniSharp: Restart OmniSharp")
+- 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.

Algorithm.CSharp/AccumulativeInsightPortfolioRegressionAlgorithm.cs

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

Algorithm.CSharp/AddAlphaModelAlgorithm.cs

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

Algorithm.CSharp/AddAndRemoveOptionContractRegressionAlgorithm.cs

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

Algorithm.CSharp/AddAndRemoveSecuritySameLoopRegressionAlgorithm.cs

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

Algorithm.CSharp/AddBetaIndicatorRegressionAlgorithm.cs

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

Algorithm.CSharp/AddFutureContractWithContinuousRegressionAlgorithm.cs

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

Algorithm.CSharp/AddFutureOptionContractDataStreamingRegressionAlgorithm.cs

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

Algorithm.CSharp/AddFutureOptionContractFromFutureChainRegressionAlgorithm.cs

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

Algorithm.CSharp/AddFutureOptionSingleOptionChainSelectedInUniverseFilterRegressionAlgorithm.cs

@@ -55,10 +55,10 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 _optionFilterRan = true;
 
-                var expiry = new HashSet<DateTime>(optionContracts.Select(x => x.Underlying.ID.Date)).SingleOrDefault();
-                // Cast to IEnumerable<Symbol> because OptionFilterContract overrides some LINQ operators like `Select` and `Where`
+                var expiry = new HashSet<DateTime>(optionContracts.Select(x => x.Symbol.Underlying.ID.Date)).SingleOrDefault();
+                // Cast to List<Symbol> because OptionFilterContract overrides some LINQ operators like `Select` and `Where`
                 // and cause it to mutate the underlying Symbol collection when using those operators.
-                var symbol = new HashSet<Symbol>(((IEnumerable<Symbol>)optionContracts).Select(x => x.Underlying)).SingleOrDefault();
+                var symbol = new HashSet<Symbol>(((List<Symbol>)optionContracts).Select(x => x.Underlying)).SingleOrDefault();
 
                 if (expiry == null || symbol == null)
                 {
@@ -75,9 +75,9 @@ namespace QuantConnect.Algorithm.CSharp
             });
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
-            if (!data.HasData)
+            if (!slice.HasData)
             {
                 return;
             }
@@ -85,7 +85,7 @@ namespace QuantConnect.Algorithm.CSharp
             _onDataReached = true;
 
             var hasOptionQuoteBars = false;
-            foreach (var qb in data.QuoteBars.Values)
+            foreach (var qb in slice.QuoteBars.Values)
             {
                 if (qb.Symbol.SecurityType != SecurityType.FutureOption)
                 {
@@ -108,7 +108,7 @@ namespace QuantConnect.Algorithm.CSharp
                 return;
             }
 
-            foreach (var chain in data.OptionChains.Values)
+            foreach (var chain in slice.OptionChains.Values)
             {
                 var futureInvested = false;
                 var optionInvested = false;
@@ -122,7 +122,7 @@ namespace QuantConnect.Algorithm.CSharp
 
                     var future = option.Underlying;
 
-                    if (!optionInvested && data.ContainsKey(option))
+                    if (!optionInvested && slice.ContainsKey(option))
                     {
                         var optionContract = Securities[option];
                         var marginModel = optionContract.BuyingPowerModel as FuturesOptionsMarginModel;
@@ -131,16 +131,16 @@ namespace QuantConnect.Algorithm.CSharp
                             || marginModel.MaintenanceIntradayMarginRequirement == 0
                             || marginModel.MaintenanceOvernightMarginRequirement == 0)
                         {
-                            throw new Exception("Unexpected margin requirements");
+                            throw new RegressionTestException("Unexpected margin requirements");
                         }
 
                         if (marginModel.GetInitialMarginRequirement(optionContract, 1) == 0)
                         {
-                            throw new Exception("Unexpected Initial Margin requirement");
+                            throw new RegressionTestException("Unexpected Initial Margin requirement");
                         }
                         if (marginModel.GetMaintenanceMargin(optionContract) != 0)
                         {
-                            throw new Exception("Unexpected Maintenance Margin requirement");
+                            throw new RegressionTestException("Unexpected Maintenance Margin requirement");
                         }
 
                         MarketOrder(option, 1);
@@ -149,10 +149,10 @@ namespace QuantConnect.Algorithm.CSharp
 
                         if (marginModel.GetMaintenanceMargin(optionContract) == 0)
                         {
-                            throw new Exception("Unexpected Maintenance Margin requirement");
+                            throw new RegressionTestException("Unexpected Maintenance Margin requirement");
                         }
                     }
-                    if (!futureInvested && data.ContainsKey(future))
+                    if (!futureInvested && slice.ContainsKey(future))
                     {
                         MarketOrder(future, 1);
                         _invested = true;
@@ -170,7 +170,7 @@ namespace QuantConnect.Algorithm.CSharp
             }
             if (!_onDataReached)
             {
-                throw new Exception("OnData() was never called.");
+                throw new RegressionTestException("OnData() was never called.");
             }
             if (_symbolsReceived.Count != _expectedSymbolsReceived.Count)
             {
@@ -188,7 +188,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             if (missingSymbols.Count > 0)
             {
-                throw new Exception($"Symbols: \"{string.Join(", ", missingSymbols)}\" were not found in OnData");
+                throw new RegressionTestException($"Symbols: \"{string.Join(", ", missingSymbols)}\" were not found in OnData");
             }
 
             foreach (var expectedSymbol in _expectedSymbolsReceived)
@@ -202,7 +202,7 @@ namespace QuantConnect.Algorithm.CSharp
 
                 if (nonDupeDataCount < 1000)
                 {
-                    throw new Exception($"Received too few data points. Expected >=1000, found {nonDupeDataCount} for {expectedSymbol}");
+                    throw new RegressionTestException($"Received too few data points. Expected >=1000, found {nonDupeDataCount} for {expectedSymbol}");
                 }
             }
         }
@@ -215,65 +215,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 612882;
+        public long DataPoints => 608377;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "347.065%"},
             {"Drawdown", "0.900%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101950.53"},
             {"Net Profit", "1.951%"},
-            {"Sharpe Ratio", "15.548"},
+            {"Sharpe Ratio", "15.402"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "95.977%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "1.885"},
+            {"Alpha", "1.886"},
             {"Beta", "1.066"},
             {"Annual Standard Deviation", "0.155"},
             {"Annual Variance", "0.024"},
             {"Information Ratio", "13.528"},
             {"Tracking Error", "0.142"},
-            {"Treynor Ratio", "2.258"},
+            {"Treynor Ratio", "2.237"},
             {"Total Fees", "$3.57"},
             {"Estimated Strategy Capacity", "$760000.00"},
             {"Lowest Capacity Asset", "ES XCZJLDQX2SRO|ES XCZJLC9NOB29"},
-            {"Fitness Score", "0.403"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0.403"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "738240babf741f1bf79f85ea5026ec4c"}
+            {"Portfolio Turnover", "32.31%"},
+            {"OrderListHash", "7a04f66a30d793bf187c2695781ad3ee"}
         };
     }
 }

Algorithm.CSharp/AddOptionContractExpiresRegressionAlgorithm.cs

@@ -42,12 +42,12 @@ namespace QuantConnect.Algorithm.CSharp
             AddUniverse("my-daily-universe-name", time => new List<string> { "AAPL" });
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (_option == null)
             {
-                var option = OptionChainProvider.GetOptionContractList(_twx, Time)
-                    .OrderBy(symbol => symbol.ID.Symbol)
+                var option = OptionChain(_twx)
+                    .OrderBy(x => x.ID.Symbol)
                     .FirstOrDefault(optionContract => optionContract.ID.Date == _expiration
                                                       && optionContract.ID.OptionRight == OptionRight.Call
                                                       && optionContract.ID.OptionStyle == OptionStyle.American);
@@ -68,11 +68,11 @@ namespace QuantConnect.Algorithm.CSharp
 
                     if (!config.Any())
                     {
-                        throw new Exception($"Was expecting configurations for {symbol}");
+                        throw new RegressionTestException($"Was expecting configurations for {symbol}");
                     }
                     if (config.Any(dataConfig => dataConfig.DataNormalizationMode != DataNormalizationMode.Raw))
                     {
-                        throw new Exception($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
+                        throw new RegressionTestException($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
                     }
                 }
             }
@@ -81,14 +81,14 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_option).Any())
                 {
-                    throw new Exception($"Unexpected configurations for {_option} after it has been delisted");
+                    throw new RegressionTestException($"Unexpected configurations for {_option} after it has been delisted");
                 }
 
                 if (Securities[_twx].Invested)
                 {
                     if (!SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any())
                     {
-                        throw new Exception($"Was expecting configurations for {_twx}");
+                        throw new RegressionTestException($"Was expecting configurations for {_twx}");
                     }
 
                     // first we liquidate the option exercised position
@@ -99,7 +99,7 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any())
                 {
-                    throw new Exception($"Unexpected configurations for {_twx} after it has been liquidated");
+                    throw new RegressionTestException($"Unexpected configurations for {_twx} after it has been liquidated");
                 }
             }
         }
@@ -112,7 +112,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -122,55 +122,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 0;
+        public int AlgorithmHistoryDataPoints => 1;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "3"},
+            {"Total Orders", "3"},
             {"Average Win", "2.73%"},
             {"Average Loss", "-2.98%"},
             {"Compounding Annual Return", "-4.619%"},
             {"Drawdown", "0.300%"},
             {"Expectancy", "-0.042"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99668"},
             {"Net Profit", "-0.332%"},
-            {"Sharpe Ratio", "-3.149"},
+            {"Sharpe Ratio", "-4.614"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0.427%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
             {"Profit-Loss Ratio", "0.92"},
-            {"Alpha", "-0.015"},
+            {"Alpha", "-0.022"},
             {"Beta", "-0.012"},
             {"Annual Standard Deviation", "0.005"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-2.823"},
             {"Tracking Error", "0.049"},
-            {"Treynor Ratio", "1.372"},
+            {"Treynor Ratio", "2.01"},
             {"Total Fees", "$2.00"},
-            {"Estimated Strategy Capacity", "$67000000.00"},
+            {"Estimated Strategy Capacity", "$5700000.00"},
             {"Lowest Capacity Asset", "AOL VRKS95ENLBYE|AOL R735QTJ8XC9X"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-43.418"},
-            {"Return Over Maximum Drawdown", "-14.274"},
-            {"Portfolio Turnover", "0.007"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "568fe7c2a11960436660db1231f2cfd2"}
+            {"Portfolio Turnover", "0.55%"},
+            {"OrderListHash", "24191a4a3bf11c07622a21266618193d"}
         };
     }
 }

Algorithm.CSharp/AddOptionContractFromUniverseRegressionAlgorithm.cs

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

Algorithm.CSharp/AddOptionContractTwiceRegressionAlgorithm.cs

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

Algorithm.CSharp/AddOptionWithOnMarketOpenOnlyFilterRegressionAlgorithm.cs

@@ -13,7 +13,6 @@
  * limitations under the License.
 */
 
-using System;
 using System.Collections.Generic;
 using System.Linq;
 using QuantConnect.Data.UniverseSelection;
@@ -59,19 +58,9 @@ namespace QuantConnect.Algorithm.CSharp
             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 =>
+            if (Time != Time.Date)
             {
-                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");
+                throw new RegressionTestException($"Expected options filter to be run only at midnight. Actual was {Time}");
             }
         }
 
@@ -83,31 +72,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all time slices of algorithm
         /// </summary>
-        public long DataPoints => 6023980;
+        public long DataPoints => 470217;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "0"},
+            {"Total Orders", "0"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -122,25 +119,7 @@ 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/AddRemoveOptionUniverseRegressionAlgorithm.cs

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

Algorithm.CSharp/AddRemoveSecurityCacheRegressionAlgorithm.cs

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

Algorithm.CSharp/AddRemoveSecurityRegressionAlgorithm.cs

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

Algorithm.CSharp/AddRiskManagementAlgorithm.cs

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

Algorithm.CSharp/AddTwoAndRemoveOneOptionContractRegressionAlgorithm.cs

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

Algorithm.CSharp/AddUniverseSelectionModelAlgorithm.cs

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

Algorithm.CSharp/AddUniverseSelectionModelCoarseAlgorithm.cs

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

Algorithm.CSharp/AdjustedVolumeRegressionAlgorithm.cs

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

Algorithm.CSharp/AlgorithmModeAndDeploymentTargetAlgorithm.cs

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

Algorithm.CSharp/AllShortableSymbolsCoarseSelectionRegressionAlgorithm.cs

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

Algorithm.CSharp/AlphaStreamsBasicTemplateAlgorithm.cs

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

Algorithm.CSharp/AlphaStreamsDifferentAccountCurrencyBasicTemplateAlgorithm.cs

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

Algorithm.CSharp/AlphaStreamsUniverseSelectionTemplateAlgorithm.cs

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

Algorithm.CSharp/AlphaStreamsWithHoldingsBasicTemplateAlgorithm.cs

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

Algorithm.CSharp/Alphas/GreenblattMagicFormulaAlpha.cs

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

Algorithm.CSharp/Alphas/RebalancingLeveragedETFAlpha.cs

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

Algorithm.CSharp/AsynchronousUniverseRegressionAlgorithm.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -13,19 +13,21 @@
  * limitations under the License.
 */
 
-namespace QuantConnect.Algorithm.Framework.Alphas.Analysis
+namespace QuantConnect.Algorithm.CSharp
 {
     /// <summary>
-    /// Retrieves the registered scoring function for the specified insight/score type
+    /// Example algorithm using the asynchronous universe selection functionality
     /// </summary>
-    public interface IInsightScoreFunctionProvider
+    public class AsynchronousUniverseRegressionAlgorithm : FundamentalRegressionAlgorithm
     {
         /// <summary>
-        /// Gets the insight scoring function for the specified insight type and score type
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
         /// </summary>
-        /// <param name="insightType">The insight's type</param>
-        /// <param name="scoreType">The scoring type</param>
-        /// <returns>A function to be used to compute insight scores</returns>
-        IInsightScoreFunction GetScoreFunction(InsightType insightType, InsightScoreType scoreType);
+        public override void Initialize()
+        {
+            base.Initialize();
+
+            UniverseSettings.Asynchronous = true;
+        }
     }
-}
+}

Algorithm.CSharp/AutoRegressiveIntegratedMovingAverageRegressionAlgorithm.cs

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

Algorithm.CSharp/AutomaticIndicatorWarmupDataTypeRegressionAlgorithm.cs

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

Algorithm.CSharp/AutomaticIndicatorWarmupOptionIndicatorsMirrorContractsRegressionAlgorithm.cs

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

Algorithm.CSharp/AutomaticIndicatorWarmupRegressionAlgorithm.cs

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

Algorithm.CSharp/AuxiliaryDataHandlersRegressionAlgorithm.cs

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

Algorithm.CSharp/BacktestingBrokerageRegressionAlgorithm.cs

@@ -151,12 +151,12 @@ namespace QuantConnect.Algorithm.CSharp
                 case OrderStatus.PartiallyFilled:
                     if (order.LastFillTime == null)
                     {
-                        throw new Exception("LastFillTime should not be null");
+                        throw new RegressionTestException("LastFillTime should not be null");
                     }
 
                     if (order.Quantity / 2 != orderEvent.FillQuantity)
                     {
-                        throw new Exception("Order size should be half");
+                        throw new RegressionTestException("Order size should be half");
                     }
                     break;
 
@@ -164,7 +164,7 @@ namespace QuantConnect.Algorithm.CSharp
                 case OrderStatus.Filled:
                     if (order.SecurityType == SecurityType.Equity && order.CreatedTime == order.LastFillTime)
                     {
-                        throw new Exception("Order should not finish during the CreatedTime bar");
+                        throw new RegressionTestException("Order should not finish during the CreatedTime bar");
                     }
                     break;
 
@@ -182,12 +182,12 @@ namespace QuantConnect.Algorithm.CSharp
             // If the option price isn't the same as the strike price, its incorrect
             if (order.Price != _optionStrikePrice)
             {
-                throw new Exception("OptionExercise order price should be strike price!!");
+                throw new RegressionTestException("OptionExercise order price should be strike price!!");
             }
 
             if (orderEvent.Quantity != -1)
             {
-                throw new Exception("OrderEvent Quantity should be -1");
+                throw new RegressionTestException("OrderEvent Quantity should be -1");
             }
         }
 
@@ -198,14 +198,14 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (!Portfolio.ContainsKey(_optionBuy.Symbol) || !Portfolio.ContainsKey(_optionBuy.Symbol.Underlying) || !Portfolio.ContainsKey(_equityBuy.Symbol))
             {
-                throw new Exception("Portfolio does not contain the Symbols we purchased");
+                throw new RegressionTestException("Portfolio does not contain the Symbols we purchased");
             }
 
             //Check option holding, should not be invested since it expired, profit should be -400
             var optionHolding = Portfolio[_optionBuy.Symbol];
             if (optionHolding.Invested || optionHolding.Profit != -400)
             {
-                throw new Exception("Options holding does not match expected outcome");
+                throw new RegressionTestException("Options holding does not match expected outcome");
             }
 
             //Check the option underlying symbol since we should have bought it at exercise
@@ -213,7 +213,7 @@ namespace QuantConnect.Algorithm.CSharp
             var optionExerciseHolding = Portfolio[_optionBuy.Symbol.Underlying];
             if (!optionExerciseHolding.Invested || optionExerciseHolding.Quantity != 100 || optionExerciseHolding.AveragePrice != _optionBuy.Symbol.ID.StrikePrice)
             {
-                throw new Exception("Equity holding for exercised option does not match expected outcome");
+                throw new RegressionTestException("Equity holding for exercised option does not match expected outcome");
             }
 
             //Check equity holding, should be invested, profit should be
@@ -221,7 +221,7 @@ namespace QuantConnect.Algorithm.CSharp
             var equityHolding = Portfolio[_equityBuy.Symbol];
             if (!equityHolding.Invested || equityHolding.Quantity != 52 || equityHolding.AveragePrice != _equityBuy.AverageFillPrice)
             {
-                throw new Exception("Equity holding does not match expected outcome");
+                throw new RegressionTestException("Equity holding does not match expected outcome");
             }
         }
 
@@ -291,65 +291,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 1748811;
+        public long DataPoints => 27071;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "3"},
+            {"Total Orders", "3"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.40%"},
-            {"Compounding Annual Return", "-22.717%"},
+            {"Compounding Annual Return", "-21.378%"},
             {"Drawdown", "0.400%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99671.06"},
             {"Net Profit", "-0.329%"},
-            {"Sharpe Ratio", "-7.887"},
+            {"Sharpe Ratio", "-14.095"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "1.216%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.001"},
+            {"Alpha", "-0.01"},
             {"Beta", "0.097"},
             {"Annual Standard Deviation", "0.002"},
             {"Annual Variance", "0"},
             {"Information Ratio", "7.39"},
             {"Tracking Error", "0.015"},
-            {"Treynor Ratio", "-0.131"},
+            {"Treynor Ratio", "-0.234"},
             {"Total Fees", "$2.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0.212"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-73.334"},
-            {"Portfolio Turnover", "0.425"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "85cbf92f01c2c91b5f710b7eeefecbe1"}
+            {"Portfolio Turnover", "17.02%"},
+            {"OrderListHash", "b1e5e72fb766ab894204bc4b1300912b"}
         };
     }
 }

Algorithm.CSharp/BaseFrameworkRegressionAlgorithm.cs

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

Algorithm.CSharp/BasicPythonIntegrationTemplateAlgorithm.cs

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

Algorithm.CSharp/BasicSetAccountCurrencyAlgorithm.cs

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

Algorithm.CSharp/BasicSetAccountCurrencyWithAmountAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateAxosAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateContinuousFutureAlgorithm.cs

@@ -51,7 +51,7 @@ namespace QuantConnect.Algorithm.CSharp
                 contractDepthOffset: 0
             );
 
-            _fast = SMA(_continuousContract.Symbol, 3, Resolution.Daily);
+            _fast = SMA(_continuousContract.Symbol, 4, Resolution.Daily);
             _slow = SMA(_continuousContract.Symbol, 10, Resolution.Daily);
         }
 
@@ -59,14 +59,14 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
-            foreach (var changedEvent in data.SymbolChangedEvents.Values)
+            foreach (var changedEvent in slice.SymbolChangedEvents.Values)
             {
                 Debug($"{Time} - SymbolChanged event: {changedEvent}");
                 if (Time.TimeOfDay != TimeSpan.Zero)
                 {
-                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                    throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
                 }
             }
 
@@ -113,65 +113,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 709638;
+        public long DataPoints => 713369;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-0.02%"},
-            {"Compounding Annual Return", "-0.033%"},
-            {"Drawdown", "0.000%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-0.017%"},
-            {"Sharpe Ratio", "-1.173"},
-            {"Probabilistic Sharpe Ratio", "0.011%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
+            {"Total Orders", "5"},
+            {"Average Win", "2.48%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "11.325%"},
+            {"Drawdown", "1.500%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "105549.6"},
+            {"Net Profit", "5.550%"},
+            {"Sharpe Ratio", "1.332"},
+            {"Sortino Ratio", "879.904"},
+            {"Probabilistic Sharpe Ratio", "79.894%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0"},
-            {"Beta", "-0"},
-            {"Annual Standard Deviation", "0"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-2.752"},
-            {"Tracking Error", "0.082"},
-            {"Treynor Ratio", "1.883"},
-            {"Total Fees", "$4.30"},
-            {"Estimated Strategy Capacity", "$0"},
+            {"Alpha", "0.075"},
+            {"Beta", "-0.017"},
+            {"Annual Standard Deviation", "0.053"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-1.48"},
+            {"Tracking Error", "0.099"},
+            {"Treynor Ratio", "-4.187"},
+            {"Total Fees", "$10.75"},
+            {"Estimated Strategy Capacity", "$7100000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.006"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-1.996"},
-            {"Portfolio Turnover", "0.01"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "1fd4b49e9450800981c6dead2bbca995"}
+            {"Portfolio Turnover", "2.33%"},
+            {"OrderListHash", "9c524830ffc7354327638142ae62acd2"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateContinuousFutureWithExtendedMarketAlgorithm.cs

@@ -52,22 +52,22 @@ namespace QuantConnect.Algorithm.CSharp
                 extendedMarketHours: true
             );
 
-            _fast = SMA(_continuousContract.Symbol, 3, Resolution.Daily);
+            _fast = SMA(_continuousContract.Symbol, 4, Resolution.Daily);
             _slow = SMA(_continuousContract.Symbol, 10, Resolution.Daily);
         }
 
         /// <summary>
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
-        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
         {
-            foreach (var changedEvent in data.SymbolChangedEvents.Values)
+            foreach (var changedEvent in slice.SymbolChangedEvents.Values)
             {
                 Debug($"{Time} - SymbolChanged event: {changedEvent}");
                 if (Time.TimeOfDay != TimeSpan.Zero)
                 {
-                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                    throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
                 }
             }
 
@@ -118,65 +118,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 2202510;
+        public long DataPoints => 2217299;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-0.02%"},
-            {"Compounding Annual Return", "-0.033%"},
-            {"Drawdown", "0.000%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-0.017%"},
-            {"Sharpe Ratio", "-1.173"},
-            {"Probabilistic Sharpe Ratio", "0.011%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
+            {"Total Orders", "5"},
+            {"Average Win", "2.86%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "12.959%"},
+            {"Drawdown", "1.100%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "106337.1"},
+            {"Net Profit", "6.337%"},
+            {"Sharpe Ratio", "1.41"},
+            {"Sortino Ratio", "1.242"},
+            {"Probabilistic Sharpe Ratio", "77.992%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0"},
-            {"Beta", "-0"},
-            {"Annual Standard Deviation", "0"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-2.752"},
-            {"Tracking Error", "0.082"},
-            {"Treynor Ratio", "1.883"},
-            {"Total Fees", "$4.30"},
-            {"Estimated Strategy Capacity", "$0"},
+            {"Alpha", "0.071"},
+            {"Beta", "0.054"},
+            {"Annual Standard Deviation", "0.059"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-1.392"},
+            {"Tracking Error", "0.097"},
+            {"Treynor Ratio", "1.518"},
+            {"Total Fees", "$10.75"},
+            {"Estimated Strategy Capacity", "$890000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.006"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-1.985"},
-            {"Portfolio Turnover", "0.01"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "adb237703e65b93da5961c0085109732"}
+            {"Portfolio Turnover", "2.32%"},
+            {"OrderListHash", "f60fc7dcba2c1ff077afeb191aee5008"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateCryptoAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateCryptoFutureAlgorithm.cs

@@ -45,7 +45,7 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2022, 12, 13); // Set Start Date
             SetEndDate(2022, 12, 13); // Set End Date
 
-            SetTimeZone(NodaTime.DateTimeZone.Utc);
+            SetTimeZone(TimeZones.Utc);
 
             try
             {
@@ -79,9 +79,9 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
-            var interestRates = data.Get<MarginInterestRate>();
+            var interestRates = slice.Get<MarginInterestRate>();
             foreach (var interestRate in interestRates)
             {
                 _interestPerSymbol[interestRate.Key]++;
@@ -89,7 +89,7 @@ namespace QuantConnect.Algorithm.CSharp
                 var cachedInterestRate = Securities[interestRate.Key].Cache.GetData<MarginInterestRate>();
                 if (cachedInterestRate != interestRate.Value)
                 {
-                    throw new Exception($"Unexpected cached margin interest rate for {interestRate.Key}!");
+                    throw new RegressionTestException($"Unexpected cached margin interest rate for {interestRate.Key}!");
                 }
             }
 
@@ -100,7 +100,7 @@ namespace QuantConnect.Algorithm.CSharp
                     var ticket = Buy(_btcUsd.Symbol, 50);
                     if (ticket.Status != OrderStatus.Invalid)
                     {
-                        throw new Exception($"Unexpected valid order {ticket}, should fail due to margin not sufficient");
+                        throw new RegressionTestException($"Unexpected valid order {ticket}, should fail due to margin not sufficient");
                     }
 
                     Buy(_btcUsd.Symbol, 1);
@@ -113,17 +113,17 @@ namespace QuantConnect.Algorithm.CSharp
 
                     if (Math.Abs(btcUsdHoldings.TotalSaleVolume - holdingsValueBtcUsd) > 1)
                     {
-                        throw new Exception($"Unexpected TotalSaleVolume {btcUsdHoldings.TotalSaleVolume}");
+                        throw new RegressionTestException($"Unexpected TotalSaleVolume {btcUsdHoldings.TotalSaleVolume}");
                     }
                     if (Math.Abs(btcUsdHoldings.AbsoluteHoldingsCost - holdingsValueBtcUsd) > 1)
                     {
-                        throw new Exception($"Unexpected holdings cost {btcUsdHoldings.HoldingsCost}");
+                        throw new RegressionTestException($"Unexpected holdings cost {btcUsdHoldings.HoldingsCost}");
                     }
                     // margin used is based on the maintenance rate
                     if (Math.Abs(btcUsdHoldings.AbsoluteHoldingsCost * 0.05m - marginUsed) > 1
                         || _btcUsd.BuyingPowerModel.GetMaintenanceMargin(_btcUsd) != marginUsed)
                     {
-                        throw new Exception($"Unexpected margin used {marginUsed}");
+                        throw new RegressionTestException($"Unexpected margin used {marginUsed}");
                     }
 
                     Buy(_adaUsdt.Symbol, 1000);
@@ -136,28 +136,28 @@ namespace QuantConnect.Algorithm.CSharp
 
                     if (Math.Abs(adaUsdtHoldings.TotalSaleVolume - holdingsValueUsdt) > 1)
                     {
-                        throw new Exception($"Unexpected TotalSaleVolume {adaUsdtHoldings.TotalSaleVolume}");
+                        throw new RegressionTestException($"Unexpected TotalSaleVolume {adaUsdtHoldings.TotalSaleVolume}");
                     }
                     if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
                     {
-                        throw new Exception($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                        throw new RegressionTestException($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
                     }
                     if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost * 0.05m - marginUsed) > 1
                         || _adaUsdt.BuyingPowerModel.GetMaintenanceMargin(_adaUsdt) != marginUsed)
                     {
-                        throw new Exception($"Unexpected margin used {marginUsed}");
+                        throw new RegressionTestException($"Unexpected margin used {marginUsed}");
                     }
 
                     // position just opened should be just spread here
                     var profit = Portfolio.TotalUnrealizedProfit;
                     if ((5 - Math.Abs(profit)) < 0)
                     {
-                        throw new Exception($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                        throw new RegressionTestException($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
                     }
 
                     if (Portfolio.TotalProfit != 0)
                     {
-                        throw new Exception($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                        throw new RegressionTestException($"Unexpected TotalProfit {Portfolio.TotalProfit}");
                     }
                 }
             }
@@ -172,7 +172,7 @@ namespace QuantConnect.Algorithm.CSharp
 
                     if (Math.Abs(btcUsdHoldings.AbsoluteHoldingsCost - 100 * 2) > 1)
                     {
-                        throw new Exception($"Unexpected holdings cost {btcUsdHoldings.HoldingsCost}");
+                        throw new RegressionTestException($"Unexpected holdings cost {btcUsdHoldings.HoldingsCost}");
                     }
 
                     Sell(_adaUsdt.Symbol, 3000);
@@ -184,19 +184,19 @@ namespace QuantConnect.Algorithm.CSharp
 
                     if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
                     {
-                        throw new Exception($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                        throw new RegressionTestException($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
                     }
 
                     // position just opened should be just spread here
                     var profit = Portfolio.TotalUnrealizedProfit;
                     if ((5 - Math.Abs(profit)) < 0)
                     {
-                        throw new Exception($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                        throw new RegressionTestException($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
                     }
                     // we barely did any difference on the previous trade
                     if ((5 - Math.Abs(Portfolio.TotalProfit)) < 0)
                     {
-                        throw new Exception($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                        throw new RegressionTestException($"Unexpected TotalProfit {Portfolio.TotalProfit}");
                     }
                 }
             }
@@ -206,12 +206,12 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (_interestPerSymbol[_adaUsdt.Symbol] != 1)
             {
-                throw new Exception($"Unexpected interest rate count {_interestPerSymbol[_adaUsdt.Symbol]}");
+                throw new RegressionTestException($"Unexpected interest rate count {_interestPerSymbol[_adaUsdt.Symbol]}");
             }
 
             if (_interestPerSymbol[_btcUsd.Symbol] != 3)
             {
-                throw new Exception($"Unexpected interest rate count {_interestPerSymbol[_btcUsd.Symbol]}");
+                throw new RegressionTestException($"Unexpected interest rate count {_interestPerSymbol[_btcUsd.Symbol]}");
             }
         }
 
@@ -228,7 +228,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -240,19 +240,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "4"},
+            {"Total Orders", "5"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "1000200.00"},
+            {"End Equity", "1000278.02"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -264,29 +272,11 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$1.63"},
-            {"Estimated Strategy Capacity", "$630000000.00"},
+            {"Total Fees", "$0.65"},
+            {"Estimated Strategy Capacity", "$500000000.00"},
             {"Lowest Capacity Asset", "ADAUSDT 18R"},
-            {"Fitness Score", "0.001"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0.001"},
-            {"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", "d4520985f69c915060f6bee3b7926cf5"}
+            {"Portfolio Turnover", "0.16%"},
+            {"OrderListHash", "dcc4f964b5549c753123848c32eaee41"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateCryptoFutureHourlyAlgorithm.cs

@@ -44,7 +44,7 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2022, 12, 13);
             SetEndDate(2022, 12, 13);
 
-            SetTimeZone(NodaTime.DateTimeZone.Utc);
+            SetTimeZone(TimeZones.Utc);
 
             try
             {
@@ -74,9 +74,9 @@ namespace QuantConnect.Algorithm.CSharp
         /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
         /// </summary>
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
-            var interestRates = data.Get<MarginInterestRate>();
+            var interestRates = slice.Get<MarginInterestRate>();
             foreach (var interestRate in interestRates)
             {
                 _interestPerSymbol[interestRate.Key]++;
@@ -84,7 +84,7 @@ namespace QuantConnect.Algorithm.CSharp
                 var cachedInterestRate = Securities[interestRate.Key].Cache.GetData<MarginInterestRate>();
                 if (cachedInterestRate != interestRate.Value)
                 {
-                    throw new Exception($"Unexpected cached margin interest rate for {interestRate.Key}!");
+                    throw new RegressionTestException($"Unexpected cached margin interest rate for {interestRate.Key}!");
                 }
             }
 
@@ -95,7 +95,7 @@ namespace QuantConnect.Algorithm.CSharp
                     var ticket = Buy(_adaUsdt.Symbol, 100000);
                     if(ticket.Status != OrderStatus.Invalid)
                     {
-                        throw new Exception($"Unexpected valid order {ticket}, should fail due to margin not sufficient");
+                        throw new RegressionTestException($"Unexpected valid order {ticket}, should fail due to margin not sufficient");
                     }
 
                     Buy(_adaUsdt.Symbol, 1000);
@@ -108,28 +108,28 @@ namespace QuantConnect.Algorithm.CSharp
 
                     if (Math.Abs(adaUsdtHoldings.TotalSaleVolume - holdingsValueUsdt) > 1)
                     {
-                        throw new Exception($"Unexpected TotalSaleVolume {adaUsdtHoldings.TotalSaleVolume}");
+                        throw new RegressionTestException($"Unexpected TotalSaleVolume {adaUsdtHoldings.TotalSaleVolume}");
                     }
                     if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
                     {
-                        throw new Exception($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                        throw new RegressionTestException($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
                     }
                     if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost * 0.05m - marginUsed) > 1
                         || _adaUsdt.BuyingPowerModel.GetMaintenanceMargin(_adaUsdt) != marginUsed)
                     {
-                        throw new Exception($"Unexpected margin used {marginUsed}");
+                        throw new RegressionTestException($"Unexpected margin used {marginUsed}");
                     }
 
                     // position just opened should be just spread here
                     var profit = Portfolio.TotalUnrealizedProfit;
                     if ((5 - Math.Abs(profit)) < 0)
                     {
-                        throw new Exception($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                        throw new RegressionTestException($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
                     }
 
                     if (Portfolio.TotalProfit != 0)
                     {
-                        throw new Exception($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                        throw new RegressionTestException($"Unexpected TotalProfit {Portfolio.TotalProfit}");
                     }
                 }
             }
@@ -147,19 +147,19 @@ namespace QuantConnect.Algorithm.CSharp
 
                     if (Math.Abs(adaUsdtHoldings.AbsoluteHoldingsCost - holdingsValueUsdt) > 1)
                     {
-                        throw new Exception($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
+                        throw new RegressionTestException($"Unexpected holdings cost {adaUsdtHoldings.HoldingsCost}");
                     }
 
                     // position just opened should be just spread here
                     var profit = Portfolio.TotalUnrealizedProfit;
                     if ((5 - Math.Abs(profit)) < 0)
                     {
-                        throw new Exception($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
+                        throw new RegressionTestException($"Unexpected TotalUnrealizedProfit {Portfolio.TotalUnrealizedProfit}");
                     }
                     // we barely did any difference on the previous trade
                     if ((5 - Math.Abs(Portfolio.TotalProfit)) < 0)
                     {
-                        throw new Exception($"Unexpected TotalProfit {Portfolio.TotalProfit}");
+                        throw new RegressionTestException($"Unexpected TotalProfit {Portfolio.TotalProfit}");
                     }
                 }
 
@@ -174,7 +174,7 @@ namespace QuantConnect.Algorithm.CSharp
         {
             if (_interestPerSymbol[_adaUsdt.Symbol] != 1)
             {
-                throw new Exception($"Unexpected interest rate count {_interestPerSymbol[_adaUsdt.Symbol]}");
+                throw new RegressionTestException($"Unexpected interest rate count {_interestPerSymbol[_adaUsdt.Symbol]}");
             }
         }
 
@@ -191,7 +191,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
@@ -203,19 +203,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "3"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "1000200"},
+            {"End Equity", "1000189.47"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -227,29 +235,11 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$1.23"},
-            {"Estimated Strategy Capacity", "$520000000.00"},
+            {"Total Fees", "$0.61"},
+            {"Estimated Strategy Capacity", "$370000000.00"},
             {"Lowest Capacity Asset", "ADAUSDT 18R"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-364.162"},
-            {"Portfolio Turnover", "0.001"},
-            {"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", "17f99ecc3f35f94fff1ea5694c40d32c"}
+            {"Portfolio Turnover", "0.12%"},
+            {"OrderListHash", "50a51d06d03a5355248a6bccef1ca521"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateDailyAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateEurexFuturesAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateFillForwardAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateForexAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateFrameworkAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateFutureOptionAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateFutureRolloverAlgorithm.cs

@@ -98,10 +98,10 @@ namespace QuantConnect.Algorithm.CSharp
         {
             private QCAlgorithm _algorithm;
             private Future _future;
-            public ExponentialMovingAverage EMA;
-            public decimal Price;
-            public bool IsLong;
-            public bool IsShort;
+            public ExponentialMovingAverage EMA { get; set; }
+            public decimal Price { get; set; }
+            public bool IsLong { get; set; }
+            public bool IsShort { get; set; }
             public Symbol Symbol => _future.Symbol;
             public Symbol Mapped => _future.Mapped;
 
@@ -171,65 +171,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 1345;
+        public long DataPoints => 1190;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 4;
+        public int AlgorithmHistoryDataPoints => 2;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
-            {"Average Win", "0.53%"},
+            {"Total Orders", "1"},
+            {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "3.011%"},
+            {"Compounding Annual Return", "-0.010%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "0"},
-            {"Net Profit", "0.528%"},
-            {"Sharpe Ratio", "1.999"},
-            {"Probabilistic Sharpe Ratio", "83.704%"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "999983.2"},
+            {"Net Profit", "-0.002%"},
+            {"Sharpe Ratio", "-225.214"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0.135%"},
             {"Loss Rate", "0%"},
-            {"Win Rate", "100%"},
+            {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.023"},
-            {"Beta", "-0.004"},
-            {"Annual Standard Deviation", "0.011"},
+            {"Alpha", "-0.008"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-4.774"},
-            {"Tracking Error", "0.084"},
-            {"Treynor Ratio", "-4.853"},
-            {"Total Fees", "$4.30"},
-            {"Estimated Strategy Capacity", "$5900000000.00"},
+            {"Information Ratio", "-5.146"},
+            {"Tracking Error", "0.083"},
+            {"Treynor Ratio", "-542.359"},
+            {"Total Fees", "$2.15"},
+            {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.002"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "1792.236"},
-            {"Portfolio Turnover", "0.002"},
-            {"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", "40e4b91ec89383f6501d9ba324e50eb9"}
+            {"Portfolio Turnover", "0.13%"},
+            {"OrderListHash", "273dd05b937c075b75baf8af46d3c7de"}
         };
     }  
 }

Algorithm.CSharp/BasicTemplateFuturesAlgorithm.cs

@@ -39,11 +39,9 @@ namespace QuantConnect.Algorithm.CSharp
 
         // S&P 500 EMini futures
         private const string RootSP500 = Futures.Indices.SP500EMini;
-        public Symbol SP500 = QuantConnect.Symbol.Create(RootSP500, SecurityType.Future, Market.CME);
 
         // Gold futures
         private const string RootGold = Futures.Metals.Gold;
-        public Symbol Gold = QuantConnect.Symbol.Create(RootGold, SecurityType.Future, Market.COMEX);
 
         /// <summary>
         /// Initialize your algorithm and add desired assets.
@@ -81,7 +79,7 @@ namespace QuantConnect.Algorithm.CSharp
                 Debug($"{Time} - SymbolChanged event: {changedEvent}");
                 if (Time.TimeOfDay != TimeSpan.Zero)
                 {
-                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                    throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
                 }
             }
 
@@ -117,7 +115,7 @@ namespace QuantConnect.Algorithm.CSharp
             var futureMarginModel = buyingPowerModel as FutureMarginModel;
             if (buyingPowerModel == null)
             {
-                throw new Exception($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
+                throw new RegressionTestException($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
             }
             var initialOvernight = futureMarginModel.InitialOvernightMarginRequirement;
             var maintenanceOvernight = futureMarginModel.MaintenanceOvernightMarginRequirement;
@@ -133,7 +131,7 @@ namespace QuantConnect.Algorithm.CSharp
                     && !addedSecurity.Symbol.IsCanonical()
                     && !addedSecurity.HasData)
                 {
-                    throw new Exception($"Future contracts did not work up as expected: {addedSecurity.Symbol}");
+                    throw new RegressionTestException($"Future contracts did not work up as expected: {addedSecurity.Symbol}");
                 }
             }
         }
@@ -146,65 +144,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 68645;
+        public long DataPoints => 75403;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 340;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2700"},
+            {"Total Orders", "2700"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
             {"Compounding Annual Return", "-99.777%"},
             {"Drawdown", "4.400%"},
             {"Expectancy", "-0.724"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "955700.5"},
             {"Net Profit", "-4.430%"},
-            {"Sharpe Ratio", "-31.389"},
+            {"Sharpe Ratio", "-31.63"},
+            {"Sortino Ratio", "-31.63"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "83%"},
             {"Win Rate", "17%"},
             {"Profit-Loss Ratio", "0.65"},
-            {"Alpha", "-3.059"},
+            {"Alpha", "-3.065"},
             {"Beta", "0.128"},
             {"Annual Standard Deviation", "0.031"},
             {"Annual Variance", "0.001"},
             {"Information Ratio", "-81.232"},
             {"Tracking Error", "0.212"},
-            {"Treynor Ratio", "-7.618"},
+            {"Treynor Ratio", "-7.677"},
             {"Total Fees", "$6237.00"},
             {"Estimated Strategy Capacity", "$14000.00"},
             {"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
-            {"Fitness Score", "0.001"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-58.8"},
-            {"Return Over Maximum Drawdown", "-32.114"},
-            {"Portfolio Turnover", "98.477"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "8f92e1528c6477a156449fd1e86527e7"}
+            {"Portfolio Turnover", "9912.69%"},
+            {"OrderListHash", "6e0f767a46a54365287801295cf7bb75"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesConsolidationAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateFuturesDailyAlgorithm.cs

@@ -83,7 +83,7 @@ namespace QuantConnect.Algorithm.CSharp
                     // if found, trade it.
                     // Also check if exchange is open for regular or extended hours. Since daily data comes at 8PM, this allows us prevent the
                     // algorithm from trading on friday when there is not after-market.
-                    if (contract != null && Securities[contract.Symbol].Exchange.Hours.IsOpen(Time, true))
+                    if (contract != null)
                     {
                         MarketOrder(contract.Symbol, 1);
                     }
@@ -99,7 +99,7 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 if (Time.TimeOfDay != TimeSpan.Zero)
                 {
-                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                    throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
                 }
             }
         }
@@ -112,65 +112,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 15217;
+        public virtual long DataPoints => 12452;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public virtual int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "118"},
-            {"Average Win", "0.09%"},
-            {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-0.479%"},
-            {"Drawdown", "0.500%"},
-            {"Expectancy", "-0.835"},
-            {"Net Profit", "-0.483%"},
-            {"Sharpe Ratio", "-1.938"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "98%"},
-            {"Win Rate", "2%"},
-            {"Profit-Loss Ratio", "8.76"},
-            {"Alpha", "-0.003"},
-            {"Beta", "-0.001"},
-            {"Annual Standard Deviation", "0.002"},
+            {"Total Orders", "32"},
+            {"Average Win", "0.33%"},
+            {"Average Loss", "-0.04%"},
+            {"Compounding Annual Return", "0.110%"},
+            {"Drawdown", "0.300%"},
+            {"Expectancy", "0.184"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1001108"},
+            {"Net Profit", "0.111%"},
+            {"Sharpe Ratio", "-1.688"},
+            {"Sortino Ratio", "-0.772"},
+            {"Probabilistic Sharpe Ratio", "14.944%"},
+            {"Loss Rate", "88%"},
+            {"Win Rate", "12%"},
+            {"Profit-Loss Ratio", "8.47"},
+            {"Alpha", "-0.007"},
+            {"Beta", "0.002"},
+            {"Annual Standard Deviation", "0.004"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.397"},
+            {"Information Ratio", "-1.353"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "5.665"},
-            {"Total Fees", "$263.30"},
-            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Treynor Ratio", "-4.099"},
+            {"Total Fees", "$72.00"},
+            {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
-            {"Fitness Score", "0.01"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.059"},
-            {"Return Over Maximum Drawdown", "-0.992"},
-            {"Portfolio Turnover", "0.031"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "b75b224669c374dcbacc33f946a1cc7c"}
+            {"Portfolio Turnover", "0.87%"},
+            {"OrderListHash", "168731c8f3a19f230cc1410818b3b573"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesFrameworkAlgorithm.cs

@@ -131,65 +131,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 43786;
+        public virtual long DataPoints => 57759;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public virtual int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "-81.734%"},
             {"Drawdown", "4.100%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "97830.76"},
             {"Net Profit", "-2.169%"},
-            {"Sharpe Ratio", "-10.195"},
+            {"Sharpe Ratio", "-10.299"},
+            {"Sortino Ratio", "-10.299"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-1.206"},
+            {"Alpha", "-1.212"},
             {"Beta", "0.238"},
             {"Annual Standard Deviation", "0.072"},
             {"Annual Variance", "0.005"},
             {"Information Ratio", "-15.404"},
             {"Tracking Error", "0.176"},
-            {"Treynor Ratio", "-3.077"},
+            {"Treynor Ratio", "-3.109"},
             {"Total Fees", "$4.62"},
             {"Estimated Strategy Capacity", "$17000000.00"},
             {"Lowest Capacity Asset", "GC VL5E74HP3EE5"},
-            {"Fitness Score", "0.006"},
-            {"Kelly Criterion Estimate", "-50.022"},
-            {"Kelly Criterion Probability Value", "0.711"},
-            {"Sortino Ratio", "-10.107"},
-            {"Return Over Maximum Drawdown", "-51.815"},
-            {"Portfolio Turnover", "0.54"},
-            {"Total Insights Generated", "5"},
-            {"Total Insights Closed", "4"},
-            {"Total Insights Analysis Completed", "4"},
-            {"Long Insight Count", "5"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$-4434.791"},
-            {"Total Accumulated Estimated Alpha Value", "$-720.6535"},
-            {"Mean Population Estimated Insight Value", "$-180.1634"},
-            {"Mean Population Direction", "25%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "25%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "323b899ae80aa839e320806411665ce7"}
+            {"Portfolio Turnover", "43.23%"},
+            {"OrderListHash", "c0fc1bcdc3008a8d263521bbc9d7cdbd"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesFrameworkWithExtendedMarketAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateFuturesHistoryAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateFuturesHistoryWithExtendedMarketHoursAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateFuturesHourlyAlgorithm.cs

@@ -36,60 +36,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 96027;
+        public override long DataPoints => 87289;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "638"},
-            {"Average Win", "0.02%"},
+            {"Total Orders", "716"},
+            {"Average Win", "0.03%"},
             {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-1.610%"},
-            {"Drawdown", "1.600%"},
-            {"Expectancy", "-0.841"},
-            {"Net Profit", "-1.622%"},
-            {"Sharpe Ratio", "-5.105"},
+            {"Compounding Annual Return", "-1.716%"},
+            {"Drawdown", "1.700%"},
+            {"Expectancy", "-0.770"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "982718.38"},
+            {"Net Profit", "-1.728%"},
+            {"Sharpe Ratio", "-8.845"},
+            {"Sortino Ratio", "-5.449"},
             {"Probabilistic Sharpe Ratio", "0.000%"},
             {"Loss Rate", "96%"},
             {"Win Rate", "4%"},
-            {"Profit-Loss Ratio", "3.21"},
-            {"Alpha", "-0.01"},
-            {"Beta", "-0.003"},
+            {"Profit-Loss Ratio", "4.89"},
+            {"Alpha", "-0.018"},
+            {"Beta", "-0.002"},
             {"Annual Standard Deviation", "0.002"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.473"},
+            {"Information Ratio", "-1.483"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "3.179"},
-            {"Total Fees", "$1456.18"},
-            {"Estimated Strategy Capacity", "$6000.00"},
+            {"Treynor Ratio", "9.102"},
+            {"Total Fees", "$1634.12"},
+            {"Estimated Strategy Capacity", "$8000.00"},
             {"Lowest Capacity Asset", "ES VP274HSU1AF5"},
-            {"Fitness Score", "0.045"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-4.328"},
-            {"Return Over Maximum Drawdown", "-0.995"},
-            {"Portfolio Turnover", "0.205"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "8842e0b890f721371ebf3c25328dee5b"}
+            {"Portfolio Turnover", "20.10%"},
+            {"OrderListHash", "aa7e574f86b70428ca0afae381be80ba"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketDailyAlgorithm.cs

@@ -38,60 +38,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 17431;
+        public override long DataPoints => 14790;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "152"},
-            {"Average Win", "0.09%"},
-            {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-0.644%"},
-            {"Drawdown", "0.600%"},
-            {"Expectancy", "-0.872"},
-            {"Net Profit", "-0.649%"},
-            {"Sharpe Ratio", "-2.343"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "99%"},
-            {"Win Rate", "1%"},
-            {"Profit-Loss Ratio", "8.76"},
-            {"Alpha", "-0.004"},
-            {"Beta", "-0.001"},
-            {"Annual Standard Deviation", "0.002"},
+            {"Total Orders", "36"},
+            {"Average Win", "0.33%"},
+            {"Average Loss", "-0.03%"},
+            {"Compounding Annual Return", "0.102%"},
+            {"Drawdown", "0.300%"},
+            {"Expectancy", "0.171"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1001024.4"},
+            {"Net Profit", "0.102%"},
+            {"Sharpe Ratio", "-1.702"},
+            {"Sortino Ratio", "-0.836"},
+            {"Probabilistic Sharpe Ratio", "14.653%"},
+            {"Loss Rate", "89%"},
+            {"Win Rate", "11%"},
+            {"Profit-Loss Ratio", "9.54"},
+            {"Alpha", "-0.007"},
+            {"Beta", "0.002"},
+            {"Annual Standard Deviation", "0.004"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.409"},
+            {"Information Ratio", "-1.353"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "3.618"},
-            {"Total Fees", "$338.96"},
-            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Treynor Ratio", "-4.126"},
+            {"Total Fees", "$80.60"},
+            {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
-            {"Fitness Score", "0.013"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.464"},
-            {"Return Over Maximum Drawdown", "-0.992"},
-            {"Portfolio Turnover", "0.04"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "48bfc4d255420cb589e00cf582554e0a"}
+            {"Portfolio Turnover", "0.97%"},
+            {"OrderListHash", "52c852d720692fab1e12212b2aba03d4"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketHourlyAlgorithm.cs

@@ -36,60 +36,45 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 248521;
+        public override long DataPoints => 228834;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "1982"},
+            {"Total Orders", "1992"},
             {"Average Win", "0.01%"},
             {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-4.666%"},
+            {"Compounding Annual Return", "-4.687%"},
             {"Drawdown", "4.700%"},
             {"Expectancy", "-0.911"},
-            {"Net Profit", "-4.700%"},
-            {"Sharpe Ratio", "-5.792"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "952789.22"},
+            {"Net Profit", "-4.721%"},
+            {"Sharpe Ratio", "-7.183"},
+            {"Sortino Ratio", "-5.14"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "97%"},
             {"Win Rate", "3%"},
             {"Profit-Loss Ratio", "2.04"},
-            {"Alpha", "-0.031"},
+            {"Alpha", "-0.038"},
             {"Beta", "-0.008"},
             {"Annual Standard Deviation", "0.005"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.701"},
+            {"Information Ratio", "-1.702"},
             {"Tracking Error", "0.09"},
-            {"Treynor Ratio", "4.096"},
-            {"Total Fees", "$4521.78"},
-            {"Estimated Strategy Capacity", "$2000.00"},
+            {"Treynor Ratio", "5.054"},
+            {"Total Fees", "$4543.28"},
+            {"Estimated Strategy Capacity", "$3000.00"},
             {"Lowest Capacity Asset", "ES VP274HSU1AF5"},
-            {"Fitness Score", "0.131"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-6.211"},
-            {"Return Over Maximum Drawdown", "-0.995"},
-            {"Portfolio Turnover", "0.649"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "2402a307b20aee195b77b8478d7ca64d"}
+            {"Portfolio Turnover", "56.73%"},
+            {"OrderListHash", "424536177e9be5895bab50638ef43a9d"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateHourlyAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateIndexAlgorithm.cs

@@ -30,8 +30,8 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="indexes" />
     public class BasicTemplateIndexAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        protected Symbol Spx;
-        protected Symbol SpxOption;
+        protected Symbol Spx { get; set; }
+        protected Symbol SpxOption { get; set; }
         private ExponentialMovingAverage _emaSlow;
         private ExponentialMovingAverage _emaFast;
 
@@ -61,8 +61,10 @@ namespace QuantConnect.Algorithm.CSharp
 
             AddIndexOptionContract(SpxOption, Resolution);
 
-            _emaSlow = EMA(Spx, 80);
-            _emaFast = EMA(Spx, 200);
+            _emaSlow = EMA(Spx, Resolution > Resolution.Minute ? 6 : 80);
+            _emaFast = EMA(Spx, Resolution > Resolution.Minute ? 2 : 200);
+
+            Settings.DailyPreciseEndTime = true;
         }
 
         /// <summary>
@@ -91,12 +93,25 @@ namespace QuantConnect.Algorithm.CSharp
             }
         }
 
+        /// <summary>
+        /// Asserts indicators are ready
+        /// </summary>
+        /// <exception cref="RegressionTestException"></exception>
+        protected void AssertIndicators()
+        {
+            if (!_emaSlow.IsReady || !_emaFast.IsReady)
+            {
+                throw new RegressionTestException("Indicators are not ready!");
+            }
+        }
+
         public override void OnEndOfAlgorithm()
         {
             if (Portfolio[Spx].TotalSaleVolume > 0)
             {
-                throw new Exception("Index is not tradable.");
+                throw new RegressionTestException("Index is not tradable.");
             }
+            AssertIndicators();
         }
 
         /// <summary>
@@ -107,65 +122,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 16690;
+        public virtual long DataPoints => 16199;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public virtual int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "4"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-53.10%"},
-            {"Compounding Annual Return", "-92.544%"},
-            {"Drawdown", "10.100%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-9.915%"},
-            {"Sharpe Ratio", "-3.845"},
-            {"Probabilistic Sharpe Ratio", "0.053%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
+            {"Total Orders", "3"},
+            {"Average Win", "7.08%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "603.355%"},
+            {"Drawdown", "3.400%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1064395"},
+            {"Net Profit", "6.440%"},
+            {"Sharpe Ratio", "-4.563"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0.781%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.558"},
-            {"Beta", "0.313"},
-            {"Annual Standard Deviation", "0.112"},
-            {"Annual Variance", "0.013"},
-            {"Information Ratio", "-6.652"},
-            {"Tracking Error", "0.125"},
-            {"Treynor Ratio", "-1.379"},
+            {"Alpha", "-0.169"},
+            {"Beta", "0.073"},
+            {"Annual Standard Deviation", "0.028"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-6.684"},
+            {"Tracking Error", "0.099"},
+            {"Treynor Ratio", "-1.771"},
             {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$13000000.00"},
+            {"Estimated Strategy Capacity", "$3000.00"},
             {"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
-            {"Fitness Score", "0.039"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.763"},
-            {"Return Over Maximum Drawdown", "-9.371"},
-            {"Portfolio Turnover", "0.278"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "3b71b146c15d234b4dc9e201838b551c"}
+            {"Portfolio Turnover", "23.97%"},
+            {"OrderListHash", "51f1bc2ea080df79748dc66c2520b782"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexDailyAlgorithm.cs

@@ -1,6 +1,24 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
 using System;
-using System.Collections.Generic;
+using System.Linq;
 using QuantConnect.Data;
+using System.Collections.Generic;
+using QuantConnect.Data.Market;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -12,9 +30,9 @@ namespace QuantConnect.Algorithm.CSharp
         protected override Resolution Resolution => Resolution.Daily;
         protected override int StartDay => 1;
 
-        // two complete weeks starting from the 5th plus the 18th bar
-        protected virtual int ExpectedBarCount => 2 * 5 + 1;
-        protected int BarCounter = 0;
+        // two complete weeks starting from the 5th. The 18th bar is not included since it is a holiday
+        protected virtual int ExpectedBarCount => 2 * 5;
+        protected int BarCounter { get; set; }
 
         /// <summary>
         /// Purchase a contract when we are not invested, liquidate otherwise
@@ -44,6 +62,35 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 throw new ArgumentException($"Bar Count {BarCounter} is not expected count of {ExpectedBarCount}");
             }
+            AssertIndicators();
+
+            if (Resolution != Resolution.Daily)
+            {
+                return;
+            }
+
+            var openInterest = Securities[SpxOption].Cache.GetAll<OpenInterest>();
+            if (openInterest.Single().EndTime != new DateTime(2021, 1, 15, 23, 0, 0))
+            {
+                throw new ArgumentException($"Unexpected open interest time: {openInterest.Single().EndTime}");
+            }
+
+            foreach (var symbol in new[] { SpxOption, Spx })
+            {
+                var history = History(symbol, 10).ToList();
+                if (history.Count != 10)
+                {
+                    throw new RegressionTestException($"Unexpected history count: {history.Count}");
+                }
+                if (history.Any(x => x.Time.TimeOfDay != new TimeSpan(8, 30, 0)))
+                {
+                    throw new RegressionTestException($"Unexpected history data start time");
+                }
+                if (history.Any(x => x.EndTime.TimeOfDay != new TimeSpan(15, 15, 0)))
+                {
+                    throw new RegressionTestException($"Unexpected history data end time");
+                }
+            }
         }
 
         /// <summary>
@@ -54,65 +101,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp };
+        public override List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 122;
+        public override long DataPoints => 121;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public override int AlgorithmHistoryDataPoints => 0;
+        public override int AlgorithmHistoryDataPoints => 30;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "9"},
+            {"Total Orders", "11"},
             {"Average Win", "0%"},
-            {"Average Loss", "-39.42%"},
-            {"Compounding Annual Return", "394.321%"},
-            {"Drawdown", "0.200%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "8.219%"},
-            {"Sharpe Ratio", "6.812"},
-            {"Probabilistic Sharpe Ratio", "91.380%"},
-            {"Loss Rate", "100%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "621.484%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1084600"},
+            {"Net Profit", "8.460%"},
+            {"Sharpe Ratio", "9.923"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "93.682%"},
+            {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "2.236"},
-            {"Beta", "-1.003"},
-            {"Annual Standard Deviation", "0.317"},
-            {"Annual Variance", "0.101"},
-            {"Information Ratio", "5.805"},
-            {"Tracking Error", "0.359"},
-            {"Treynor Ratio", "-2.153"},
+            {"Alpha", "3.61"},
+            {"Beta", "-0.513"},
+            {"Annual Standard Deviation", "0.359"},
+            {"Annual Variance", "0.129"},
+            {"Information Ratio", "8.836"},
+            {"Tracking Error", "0.392"},
+            {"Treynor Ratio", "-6.937"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
-            {"Fitness Score", "0.027"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "1776.081"},
-            {"Portfolio Turnover", "0.027"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "0ee6860210d55051c38e494bd24bb6de"}
+            {"Portfolio Turnover", "2.42%"},
+            {"OrderListHash", "61e8517ac3da6bed414ef23d26736fef"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexHourlyAlgorithm.cs

@@ -18,65 +18,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp };
+        public override List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 408;
+        public override long DataPoints => 401;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public override int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "70"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-0.23%"},
-            {"Compounding Annual Return", "-34.441%"},
-            {"Drawdown", "2.000%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-2.028%"},
-            {"Sharpe Ratio", "-11.139"},
-            {"Probabilistic Sharpe Ratio", "0.000%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.269"},
-            {"Beta", "0.086"},
-            {"Annual Standard Deviation", "0.023"},
-            {"Annual Variance", "0.001"},
-            {"Information Ratio", "-3.624"},
-            {"Tracking Error", "0.094"},
-            {"Treynor Ratio", "-3.042"},
+            {"Total Orders", "81"},
+            {"Average Win", "1.28%"},
+            {"Average Loss", "-0.06%"},
+            {"Compounding Annual Return", "-20.546%"},
+            {"Drawdown", "1.800%"},
+            {"Expectancy", "-0.402"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "990775"},
+            {"Net Profit", "-0.922%"},
+            {"Sharpe Ratio", "-2.903"},
+            {"Sortino Ratio", "-6.081"},
+            {"Probabilistic Sharpe Ratio", "22.230%"},
+            {"Loss Rate", "97%"},
+            {"Win Rate", "3%"},
+            {"Profit-Loss Ratio", "19.95"},
+            {"Alpha", "-0.157"},
+            {"Beta", "0.025"},
+            {"Annual Standard Deviation", "0.053"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-2.07"},
+            {"Tracking Error", "0.121"},
+            {"Treynor Ratio", "-6.189"},
             {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$310000.00"},
+            {"Estimated Strategy Capacity", "$300000.00"},
             {"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
-            {"Fitness Score", "0.002"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-14.51"},
-            {"Return Over Maximum Drawdown", "-17.213"},
-            {"Portfolio Turnover", "0.299"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "0c74daf716d7782a7e89c7a0ea57856f"}
+            {"Portfolio Turnover", "24.63%"},
+            {"OrderListHash", "44325fc1fdebb8e54f64a3f6e8a4bcd7"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexOptionsAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateIndexOptionsDailyAlgorithm.cs

@@ -14,10 +14,9 @@
  *
 */
 
-using System;
-using System.Collections.Generic;
 using System.Linq;
 using QuantConnect.Data;
+using System.Collections.Generic;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -63,65 +62,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp };
+        public override List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 381;
+        public override long DataPoints => 356;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public override int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "9"},
+            {"Total Orders", "11"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-0.091%"},
+            {"Compounding Annual Return", "-0.092%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "999920"},
             {"Net Profit", "-0.008%"},
-            {"Sharpe Ratio", "-4.033"},
+            {"Sharpe Ratio", "-19.865"},
+            {"Sortino Ratio", "-175397.15"},
             {"Probabilistic Sharpe Ratio", "0.013%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.001"},
+            {"Alpha", "-0.003"},
             {"Beta", "0"},
             {"Annual Standard Deviation", "0"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-0.447"},
-            {"Tracking Error", "0.136"},
-            {"Treynor Ratio", "-4.612"},
+            {"Information Ratio", "-0.454"},
+            {"Tracking Error", "0.138"},
+            {"Treynor Ratio", "-44.954"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "SPX XL80P59H5E6M|SPX 31"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-50718.291"},
-            {"Return Over Maximum Drawdown", "-11.386"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "607d309c5fb52a8b88310720b4a867e1"}
+            {"Portfolio Turnover", "0.00%"},
+            {"OrderListHash", "285cec32c0947f0e8cf90ccb672cfa43"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndexOptionsHourlyAlgorithm.cs

@@ -33,65 +33,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public override Language[] Languages { get; } = { Language.CSharp };
+        public override List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 2212;
+        public override long DataPoints => 1269;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public override int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "70"},
+            {"Total Orders", "81"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "0%"},
+            {"Compounding Annual Return", "-0.006%"},
             {"Drawdown", "0.000%"},
-            {"Expectancy", "0.000"},
-            {"Net Profit", "0%"},
-            {"Sharpe Ratio", "0"},
-            {"Probabilistic Sharpe Ratio", "36.504%"},
+            {"Expectancy", "-0.486"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "999995"},
+            {"Net Profit", "0.000%"},
+            {"Sharpe Ratio", "-101.77"},
+            {"Sortino Ratio", "-9053542.758"},
+            {"Probabilistic Sharpe Ratio", "17.439%"},
             {"Loss Rate", "97%"},
             {"Win Rate", "3%"},
-            {"Profit-Loss Ratio", "34.00"},
-            {"Alpha", "0"},
+            {"Profit-Loss Ratio", "17.50"},
+            {"Alpha", "-0.003"},
             {"Beta", "-0"},
             {"Annual Standard Deviation", "0"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-0.449"},
             {"Tracking Error", "0.138"},
-            {"Treynor Ratio", "-0"},
+            {"Treynor Ratio", "116.921"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "SPX XL80P59H5E6M|SPX 31"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "cc19277c90eb3b1f1e09ee15dfa7029b"}
+            {"Portfolio Turnover", "0.00%"},
+            {"OrderListHash", "75e6584cb26058b09720c3a828b9fbda"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateIndiaAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateIndiaIndexAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateIntrinioEconomicData.cs

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

Algorithm.CSharp/BasicTemplateOptionEquityStrategyAlgorithm.cs

@@ -32,7 +32,7 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="trading and orders" />
     public class BasicTemplateOptionEquityStrategyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        protected Symbol _optionSymbol;
+        private Symbol _optionSymbol;
 
         public override void Initialize()
         {
@@ -97,31 +97,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 884208;
+        public long DataPoints => 15023;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "3"},
+            {"Total Orders", "3"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "98024"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -133,29 +141,11 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$7.50"},
-            {"Estimated Strategy Capacity", "$84000.00"},
+            {"Total Fees", "$26.00"},
+            {"Estimated Strategy Capacity", "$69000.00"},
             {"Lowest Capacity Asset", "GOOCV W78ZERHAOVVQ|GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "92610619a10e30863020cc84aa30be3b"}
+            {"Portfolio Turnover", "61.31%"},
+            {"OrderListHash", "35d406df401e5b27244e20f5ec57346e"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionStrategyAlgorithm.cs

@@ -107,31 +107,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp };
+        public List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 884616;
+        public long DataPoints => 15130;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "778"},
+            {"Total Orders", "420"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
             {"Drawdown", "0%"},
             {"Expectancy", "0"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "952636.6"},
             {"Net Profit", "0%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
@@ -143,29 +151,11 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$778.00"},
-            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Total Fees", "$543.40"},
+            {"Estimated Strategy Capacity", "$4000.00"},
             {"Lowest Capacity Asset", "GOOCV W78ZFMEBBB2E|GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "c9e110f2122451dabefcfe24287cadcf"}
+            {"Portfolio Turnover", "338.60%"},
+            {"OrderListHash", "301c15063f6e269023d144ca69a765da"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateOptionsConsolidationAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateOptionsDailyAlgorithm.cs

@@ -34,21 +34,21 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="filter selection" />
     public class BasicTemplateOptionsDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private const string UnderlyingTicker = "GOOG";
-        public Symbol OptionSymbol;
+        private const string UnderlyingTicker = "AAPL";
+        private Symbol _optionSymbol;
         private bool _optionExpired;
 
         public override void Initialize()
         {
-            SetStartDate(2015, 12, 23);
-            SetEndDate(2016, 1, 20);
+            SetStartDate(2015, 12, 15);
+            SetEndDate(2016, 2, 1);
             SetCash(100000);
 
             var equity = AddEquity(UnderlyingTicker, Resolution.Daily);
             var option = AddOption(UnderlyingTicker, Resolution.Daily);
-            OptionSymbol = option.Symbol;
+            _optionSymbol = option.Symbol;
 
-            option.SetFilter(x => x.CallsOnly().Strikes(0, 1).Expiration(0, 30));
+            option.SetFilter(x => x.CallsOnly().Expiration(0, 60));
 
             // use the underlying equity as the benchmark
             SetBenchmark(equity.Symbol);
@@ -63,13 +63,13 @@ namespace QuantConnect.Algorithm.CSharp
             if (!Portfolio.Invested)
             {
                 OptionChain chain;
-                if (slice.OptionChains.TryGetValue(OptionSymbol, out chain))
+                if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
                 {
                     // Grab us the contract nearest expiry that is not today
                     var contractsByExpiration = chain.Where(x => x.Expiry != Time.Date).OrderBy(x => x.Expiry);
                     var contract = contractsByExpiration.FirstOrDefault();
 
-                    if (contract != null && IsMarketOpen(contract.Symbol))
+                    if (contract != null)
                     {
                         // if found, trade it
                         MarketOrder(contract.Symbol, 1);
@@ -117,65 +117,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 39654;
+        public long DataPoints => 308;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
-            {"Average Loss", "-1.31%"},
-            {"Compounding Annual Return", "-15.304%"},
-            {"Drawdown", "1.300%"},
+            {"Average Loss", "-1.16%"},
+            {"Compounding Annual Return", "-8.351%"},
+            {"Drawdown", "1.200%"},
             {"Expectancy", "-1"},
-            {"Net Profit", "-1.311%"},
-            {"Sharpe Ratio", "-3.31"},
-            {"Probabilistic Sharpe Ratio", "0.035%"},
+            {"Start Equity", "100000"},
+            {"End Equity", "98844"},
+            {"Net Profit", "-1.156%"},
+            {"Sharpe Ratio", "-4.04"},
+            {"Sortino Ratio", "-2.422"},
+            {"Probabilistic Sharpe Ratio", "0.099%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0"},
-            {"Beta", "0"},
-            {"Annual Standard Deviation", "0.034"},
-            {"Annual Variance", "0.001"},
-            {"Information Ratio", "-3.31"},
-            {"Tracking Error", "0.034"},
-            {"Treynor Ratio", "0"},
+            {"Alpha", "-0.058"},
+            {"Beta", "0.021"},
+            {"Annual Standard Deviation", "0.017"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "1.49"},
+            {"Tracking Error", "0.289"},
+            {"Treynor Ratio", "-3.212"},
             {"Total Fees", "$1.00"},
-            {"Estimated Strategy Capacity", "$18000.00"},
-            {"Lowest Capacity Asset", "GOOCV W78ZFMML01JA|GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.496"},
-            {"Return Over Maximum Drawdown", "-11.673"},
-            {"Portfolio Turnover", "0"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "0b52bbe98ade8e3aab943e64fcf4abfe"}
+            {"Estimated Strategy Capacity", "$72000.00"},
+            {"Lowest Capacity Asset", "AAPL W78ZEO2985GM|AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "0.02%"},
+            {"OrderListHash", "b3125e0af79da0f5eea4cfda09806324"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsFilterUniverseAlgorithm.cs

@@ -14,7 +14,6 @@
  *
 */
 
-using System;
 using System.Collections.Generic;
 using System.Linq;
 using QuantConnect.Data;
@@ -36,7 +35,7 @@ namespace QuantConnect.Algorithm.CSharp
     public class BasicTemplateOptionsFilterUniverseAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
         private const string UnderlyingTicker = "GOOG";
-        public Symbol OptionSymbol;
+        private Symbol _optionSymbol;
 
         public override void Initialize()
         {
@@ -46,7 +45,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             var equity = AddEquity(UnderlyingTicker);
             var option = AddOption(UnderlyingTicker);
-            OptionSymbol = option.Symbol;
+            _optionSymbol = option.Symbol;
 
             // Set our custom universe filter, Expires today, is a call, and is within 10 dollars of the current price
             option.SetFilter(universe => from symbol in universe.WeeklysOnly().Expiration(0, 1)
@@ -64,7 +63,7 @@ namespace QuantConnect.Algorithm.CSharp
             if (!Portfolio.Invested)
             {
                 OptionChain chain;
-                if (slice.OptionChains.TryGetValue(OptionSymbol, out chain))
+                if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
                 {
                     // Get the first ITM call expiring today
                     var contract = (
@@ -95,31 +94,39 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 1722373;
+        public long DataPoints => 12290;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Orders", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.40%"},
-            {"Compounding Annual Return", "-21.622%"},
+            {"Compounding Annual Return", "-20.338%"},
             {"Drawdown", "0.300%"},
             {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99689"},
             {"Net Profit", "-0.311%"},
             {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
@@ -134,26 +141,8 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Fees", "$1.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "GOOCV VP83T1ZUHROL"},
-            {"Fitness Score", "0.188"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-73.268"},
-            {"Portfolio Turnover", "0.376"},
-            {"Total Insights Generated", "0"},
-            {"Total Insights Closed", "0"},
-            {"Total Insights Analysis Completed", "0"},
-            {"Long Insight Count", "0"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$0"},
-            {"Total Accumulated Estimated Alpha Value", "$0"},
-            {"Mean Population Estimated Insight Value", "$0"},
-            {"Mean Population Direction", "0%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "0%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "0f8537495f5744c02191656d6b3f9205"}
+            {"Portfolio Turnover", "15.08%"},
+            {"OrderListHash", "db6a1134ad325bce31c2bdd2e87ff5f4"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsFrameworkAlgorithm.cs

@@ -134,65 +134,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 990979;
+        public long DataPoints => 17486;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "4"},
-            {"Average Win", "0.14%"},
-            {"Average Loss", "-0.28%"},
-            {"Compounding Annual Return", "0%"},
-            {"Drawdown", "385.400%"},
-            {"Expectancy", "-0.249"},
-            {"Net Profit", "-386.489%"},
-            {"Sharpe Ratio", "-0.033"},
-            {"Probabilistic Sharpe Ratio", "1.235%"},
-            {"Loss Rate", "50%"},
-            {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.50"},
-            {"Alpha", "-95.983"},
-            {"Beta", "263.726"},
-            {"Annual Standard Deviation", "30.617"},
-            {"Annual Variance", "937.371"},
-            {"Information Ratio", "-0.044"},
-            {"Tracking Error", "30.604"},
-            {"Treynor Ratio", "-0.004"},
-            {"Total Fees", "$3.00"},
+            {"Total Orders", "5"},
+            {"Average Win", "0.13%"},
+            {"Average Loss", "-0.30%"},
+            {"Compounding Annual Return", "-46.395%"},
+            {"Drawdown", "1.600%"},
+            {"Expectancy", "0.429"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99149.50"},
+            {"Net Profit", "-0.850%"},
+            {"Sharpe Ratio", "-4.298"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "15.319%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
+            {"Profit-Loss Ratio", "0.43"},
+            {"Alpha", "-0.84"},
+            {"Beta", "0.986"},
+            {"Annual Standard Deviation", "0.098"},
+            {"Annual Variance", "0.01"},
+            {"Information Ratio", "-9.299"},
+            {"Tracking Error", "0.091"},
+            {"Treynor Ratio", "-0.428"},
+            {"Total Fees", "$4.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
-            {"Fitness Score", "0.168"},
-            {"Kelly Criterion Estimate", "0.327"},
-            {"Kelly Criterion Probability Value", "1"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "0"},
-            {"Portfolio Turnover", "0.224"},
-            {"Total Insights Generated", "28"},
-            {"Total Insights Closed", "24"},
-            {"Total Insights Analysis Completed", "24"},
-            {"Long Insight Count", "28"},
-            {"Short Insight Count", "0"},
-            {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$13.64796"},
-            {"Total Accumulated Estimated Alpha Value", "$1.89555"},
-            {"Mean Population Estimated Insight Value", "$0.07898125"},
-            {"Mean Population Direction", "50%"},
-            {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "50.0482%"},
-            {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "83c9fb13ee32284702779eff8d11c608"}
+            {"Portfolio Turnover", "13.50%"},
+            {"OrderListHash", "cf14a7ce9c86e6844051820fd4c9394c"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsHourlyAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateSPXWeeklyIndexOptionsAlgorithm.cs

@@ -43,14 +43,12 @@ namespace QuantConnect.Algorithm.CSharp
             SetEndDate(2021, 1, 10);
             SetCash(1000000);
 
-            var spx = AddIndex("SPX").Symbol;
-
             // regular option SPX contracts
-            var spxOptions = AddIndexOption(spx);
+            var spxOptions = AddIndexOption("SPX");
             spxOptions.SetFilter(u => u.Strikes(0, 1).Expiration(0, 30));
 
             // weekly option SPX contracts
-            var spxw = AddIndexOption(spx, "SPXW");
+            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)
@@ -100,65 +98,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 65830;
+        public virtual long DataPoints => 21467;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public virtual int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "5"},
+            {"Total Orders", "5"},
             {"Average Win", "0%"},
-            {"Average Loss", "-0.75%"},
-            {"Compounding Annual Return", "44.538%"},
-            {"Drawdown", "0.500%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "0.474%"},
-            {"Sharpe Ratio", "-12.503"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
+            {"Average Loss", "-0.69%"},
+            {"Compounding Annual Return", "54.478%"},
+            {"Drawdown", "0.400%"},
+            {"Expectancy", "-0.5"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1006025"},
+            {"Net Profit", "0.602%"},
+            {"Sharpe Ratio", "2.62"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "63.221%"},
+            {"Loss Rate", "50%"},
+            {"Win Rate", "50%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.846"},
-            {"Beta", "-0.141"},
-            {"Annual Standard Deviation", "0.013"},
+            {"Alpha", "0.067"},
+            {"Beta", "-0.013"},
+            {"Annual Standard Deviation", "0.004"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-91.834"},
-            {"Tracking Error", "0.08"},
-            {"Treynor Ratio", "1.143"},
+            {"Information Ratio", "-50.808"},
+            {"Tracking Error", "0.086"},
+            {"Treynor Ratio", "-0.725"},
             {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$7500000.00"},
+            {"Estimated Strategy Capacity", "$580000.00"},
             {"Lowest Capacity Asset", "SPXW 31K54PVWHUJHQ|SPX 31"},
-            {"Fitness Score", "0.006"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "48.874"},
-            {"Return Over Maximum Drawdown", "332.561"},
-            {"Portfolio Turnover", "0.006"},
-            {"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", "846032599f3c31838f5fe6c63ec12d3c"}
+            {"Portfolio Turnover", "0.40%"},
+            {"OrderListHash", "07a085baedb37bb7c8d460558ea77e88"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateSPXWeeklyIndexOptionsStrategyAlgorithm.cs

@@ -48,7 +48,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             // weekly option SPX contracts
             var spxw = AddIndexOption(spx, "SPXW");
-            spxw.SetFilter(u => u.Strikes(0, 1)
+            spxw.SetFilter(u => u.Strikes(-1, +1)
                  // single week ahead since there are many SPXW contracts and we want to preserve performance
                  .Expiration(0, 7)
                  .IncludeWeeklys());
@@ -66,7 +66,7 @@ namespace QuantConnect.Algorithm.CSharp
             OptionChain chain;
             if (slice.OptionChains.TryGetValue(_spxOption, out chain))
             {
-                // we find the first expiration group of call options and order them in ascending strike 
+                // 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)
@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
             Debug(orderEvent.ToString());
             if (orderEvent.Symbol.ID.Symbol != "SPXW")
             {
-                throw new Exception("Unexpected order event symbol!");
+                throw new RegressionTestException("Unexpected order event symbol!");
             }
         }
 
@@ -104,65 +104,55 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public virtual Language[] Languages { get; } = { Language.CSharp };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 35611;
+        public virtual long DataPoints => 16680;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
         public virtual int AlgorithmHistoryDataPoints => 0;
 
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "4"},
-            {"Average Win", "0.46%"},
-            {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "42.201%"},
+            {"Total Orders", "10"},
+            {"Average Win", "0.47%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "101.998%"},
             {"Drawdown", "0.100%"},
-            {"Expectancy", "115.281"},
-            {"Net Profit", "0.452%"},
-            {"Sharpe Ratio", "7.967"},
-            {"Probabilistic Sharpe Ratio", "95.977%"},
+            {"Expectancy", "24.484"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1009050"},
+            {"Net Profit", "0.905%"},
+            {"Sharpe Ratio", "8.44"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "95.546%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "231.56"},
-            {"Alpha", "0.029"},
-            {"Beta", "-0.003"},
-            {"Annual Standard Deviation", "0.001"},
+            {"Profit-Loss Ratio", "49.97"},
+            {"Alpha", "-2.01"},
+            {"Beta", "0.307"},
+            {"Annual Standard Deviation", "0.021"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-102.62"},
-            {"Tracking Error", "0.07"},
-            {"Treynor Ratio", "-2.462"},
+            {"Information Ratio", "-144.654"},
+            {"Tracking Error", "0.048"},
+            {"Treynor Ratio", "0.589"},
             {"Total Fees", "$0.00"},
-            {"Estimated Strategy Capacity", "$4100000.00"},
+            {"Estimated Strategy Capacity", "$13000000.00"},
             {"Lowest Capacity Asset", "SPXW XKX6S2GM9PGU|SPX 31"},
-            {"Fitness Score", "0.001"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0.001"},
-            {"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", "4b25b40cc766201845f66b3b613d1444"}
+            {"Portfolio Turnover", "0.28%"},
+            {"OrderListHash", "c1a9bc141ae25c9542b93a887e79dafe"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateTradableIndexAlgorithm.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 QuantConnect.Data;
+using System.Collections.Generic;
+using QuantConnect.Orders;
+using System.Linq;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add index asset types and change the tradable condition
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="indexes" />
+    public class BasicTemplateTradableIndexAlgorithm : BasicTemplateIndexAlgorithm
+    {
+        private OrderTicket _ticket;
+
+        /// <summary>
+        /// Initialize your algorithm and add desired assets.
+        /// </summary>
+        public override void Initialize()
+        {
+            base.Initialize();
+            Securities[Spx].IsTradable = true;
+        }
+
+        /// <summary>
+        /// Index EMA Cross trading underlying.
+        /// </summary>
+        public override void OnData(Slice slice)
+        {
+            base.OnData(slice);
+            _ticket ??= MarketOrder(Spx, 1);
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_ticket.Status.IsFill())
+            {
+                throw new RegressionTestException("Index is tradable.");
+            }
+        }
+
+        /// <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()
+        {
+            {"Total Orders", "5"},
+            {"Average Win", "7.08%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "602.278%"},
+            {"Drawdown", "3.400%"},
+            {"Expectancy", "677.669"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1064342.82"},
+            {"Net Profit", "6.434%"},
+            {"Sharpe Ratio", "-4.563"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0.781%"},
+            {"Loss Rate", "50%"},
+            {"Win Rate", "50%"},
+            {"Profit-Loss Ratio", "1356.34"},
+            {"Alpha", "-0.169"},
+            {"Beta", "0.073"},
+            {"Annual Standard Deviation", "0.028"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-6.684"},
+            {"Tracking Error", "0.099"},
+            {"Treynor Ratio", "-1.771"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$3000.00"},
+            {"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
+            {"Portfolio Turnover", "24.03%"},
+            {"OrderListHash", "fcd6fddb0a315e21095c2b35eb633e2b"}
+        };
+    }
+}

Algorithm.CSharp/Benchmarks/BasicTemplateBenchmark.cs

@@ -33,7 +33,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
             AddEquity("SPY");
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
             if (!Portfolio.Invested)
             {

Algorithm.CSharp/Benchmarks/CoarseFineUniverseSelectionBenchmark.cs

@@ -15,6 +15,7 @@
 
 using System.Collections.Generic;
 using System.Linq;
+using QuantConnect.Data;
 using QuantConnect.Data.Fundamental;
 using QuantConnect.Data.Market;
 using QuantConnect.Data.UniverseSelection;
@@ -68,8 +69,8 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
             return topFine.Select(x => x.Symbol);
         }
 
-        //Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol.
-        public void OnData(TradeBars data)
+        //Data Event Handler: New data arrives here.
+        public override void OnData(Slice slice)
         {
             // if we have no changes, do nothing
             if (_changes == SecurityChanges.None) return;

Algorithm.CSharp/Benchmarks/EmptyEquityAndOptions400Benchmark.cs

@@ -64,7 +64,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
 "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)
             {

Algorithm.CSharp/Benchmarks/EmptySingleSecuritySecondEquityBenchmark.cs

@@ -32,7 +32,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
             AddEquity("SPY", Resolution.Second);
         }
 
-        public override void OnData(Slice data)
+        public override void OnData(Slice slice)
         {
         }
     }