Update readme.md

* Refactor multi IDQH frontier

- Fix for multi IDQH frontier support, specially for IB + QC
- Adding new CompositeTimeProvide. Adding unit tests

* Adjust solution to fix new data available event

.devcontainer/Dockerfile

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

.devcontainer/devcontainer.json

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

.github/workflows/benchmarks.yml

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

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

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

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

@@ -17,10 +17,10 @@ jobs:
 
       - name: install dependencies
         run: |
-          pip3 install papermill clr-loader
+          pip3 install papermill==2.4.0 clr-loader==0.1.6
 
       - name: install kernel
-        run: dotnet tool install --global Microsoft.dotnet-interactive --version 1.0.317502
+        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

.github/workflows/virtual-environments.yml

@@ -0,0 +1,61 @@
+name: Python Virtual Environments
+
+on:
+  push:
+    branches: ['*']
+    tags: ['*']
+  pull_request:
+    branches: [master]
+
+jobs:
+  build:
+    runs-on: ubuntu-20.04
+    container:
+        image: quantconnect/lean:foundation
+    steps:
+      - uses: actions/checkout@v2
+
+      - name: Build
+        run: dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
+
+      - name: Python Virtual Environment System Packages
+        run: python -m venv /lean-testenv --system-site-packages && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.99 && deactivate
+
+      - name: Run Virtual Environment Test System Packages
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment"
+
+      - name: Python Virtual Environment
+        run: rm -rf /lean-testenv && python -m venv /lean-testenv && . /lean-testenv/bin/activate && pip install --no-cache-dir lean==1.0.99 && deactivate
+
+      - name: Run Virtual Environment Test
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonVirtualEnvironmentTests.AssertVirtualEnvironment"
+
+      - name: Run Python Package Tests
+        run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests"
+
+      - 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"

.vs/readme.md

@@ -18,7 +18,7 @@ To use Lean CLI follow the instructions for installation and tutorial for usage
 
 <h2>Option 2: Install Locally</h2>
 
-1. Install [.Net 5](https://dotnet.microsoft.com/download) for the project
+1. Install [.Net 6](https://dotnet.microsoft.com/download) for the project
 
 2. (Optional) Get [Python 3.6.8](https://www.python.org/downloads/release/python-368/) for running Python algorithms
     - Follow Python instructions [here](https://github.com/QuantConnect/Lean/tree/master/Algorithm.Python#installing-python-36) for your platform

.vscode/launch.json

@@ -3,8 +3,8 @@
         VS Code Launch configurations for the LEAN engine
 
         Launch:
-        Builds the project with dotnet 5 and then launches the program using coreclr; supports debugging.
-        In order to use this you need dotnet 5 on your system path, As well as the C# extension from the 
+        Builds the project with dotnet 6 and then launches the program using coreclr; supports debugging.
+        In order to use this you need dotnet 6 on your system path, As well as the C# extension from the 
         marketplace.
 
         Attach to Python:
@@ -26,7 +26,7 @@
             "program": "${workspaceFolder}/Launcher/bin/Debug/QuantConnect.Lean.Launcher.dll",
             "args": [
                 "--config",
-                "${workspaceFolder}/Launcher/config.json"
+                "${workspaceFolder}/Launcher/bin/Debug/config.json"
             ],
             "cwd": "${workspaceFolder}/Launcher/bin/Debug/",
             "stopAtEntry": false,

.vscode/launch_research.sh

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

.vscode/readme.md

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

.vscode/settings.json

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

.vscode/tasks.json

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

Algorithm.CSharp/AddFutureContractWithContinuousRegressionAlgorithm.cs

@@ -116,7 +116,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 59;
+        public long DataPoints => 63;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -131,31 +131,31 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "3"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.03%"},
-            {"Compounding Annual Return", "-2.503%"},
+            {"Compounding Annual Return", "-2.594%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "-1"},
-            {"Net Profit", "-0.032%"},
-            {"Sharpe Ratio", "0"},
-            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Net Profit", "-0.034%"},
+            {"Sharpe Ratio", "-7.854"},
+            {"Probabilistic Sharpe Ratio", "1.216%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0"},
-            {"Beta", "0"},
-            {"Annual Standard Deviation", "0"},
+            {"Alpha", "-0.022"},
+            {"Beta", "0.004"},
+            {"Annual Standard Deviation", "0.003"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-0.678"},
-            {"Tracking Error", "0.243"},
-            {"Treynor Ratio", "0"},
-            {"Total Fees", "$7.40"},
-            {"Estimated Strategy Capacity", "$2100000.00"},
+            {"Information Ratio", "-0.768"},
+            {"Tracking Error", "0.241"},
+            {"Treynor Ratio", "-4.689"},
+            {"Total Fees", "$8.60"},
+            {"Estimated Strategy Capacity", "$5500000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.419"},
+            {"Fitness Score", "0.417"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-81.557"},
-            {"Portfolio Turnover", "0.837"},
+            {"Return Over Maximum Drawdown", "-81.518"},
+            {"Portfolio Turnover", "0.834"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -169,7 +169,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "68775c18eb40c1bde212653faec4016e"}
+            {"OrderListHash", "802a335b5c355e83b8cd2174f053c1b9"}
         };
     }
 }

Algorithm.CSharp/AddFutureOptionContractDataStreamingRegressionAlgorithm.cs

@@ -41,7 +41,7 @@ namespace QuantConnect.Algorithm.CSharp
         public override void Initialize()
         {
             SetStartDate(2020, 1, 4);
-            SetEndDate(2020, 1, 6);
+            SetEndDate(2020, 1, 8);
 
             _es20h20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(Futures.Indices.SP500EMini, Market.CME, new DateTime(2020, 3, 20)),
@@ -51,8 +51,9 @@ namespace QuantConnect.Algorithm.CSharp
                 QuantConnect.Symbol.CreateFuture(Futures.Indices.SP500EMini, Market.CME, new DateTime(2020, 6, 19)),
                 Resolution.Minute).Symbol;
 
+            // Get option contract lists for 2020/01/05 (Time.AddDays(1)) because Lean has local data for that date
             var optionChains = OptionChainProvider.GetOptionContractList(_es20h20, Time.AddDays(1))
-                .Concat(OptionChainProvider.GetOptionContractList(_es19m20, Time));
+                .Concat(OptionChainProvider.GetOptionContractList(_es19m20, Time.AddDays(1)));
 
             foreach (var optionContract in optionChains)
             {
@@ -163,7 +164,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 210329;
+        public long DataPoints => 311879;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -178,31 +179,31 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "116.059%"},
-            {"Drawdown", "0.600%"},
+            {"Compounding Annual Return", "5512.811%"},
+            {"Drawdown", "1.000%"},
             {"Expectancy", "0"},
-            {"Net Profit", "0.635%"},
-            {"Sharpe Ratio", "17.16"},
-            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Net Profit", "5.333%"},
+            {"Sharpe Ratio", "64.137"},
+            {"Probabilistic Sharpe Ratio", "95.977%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "2.25"},
-            {"Beta", "-1.665"},
-            {"Annual Standard Deviation", "0.071"},
-            {"Annual Variance", "0.005"},
-            {"Information Ratio", "5.319"},
-            {"Tracking Error", "0.114"},
-            {"Treynor Ratio", "-0.735"},
-            {"Total Fees", "$7.40"},
-            {"Estimated Strategy Capacity", "$24000000.00"},
+            {"Alpha", "25.72"},
+            {"Beta", "2.914"},
+            {"Annual Standard Deviation", "0.423"},
+            {"Annual Variance", "0.179"},
+            {"Information Ratio", "66.11"},
+            {"Tracking Error", "0.403"},
+            {"Treynor Ratio", "9.315"},
+            {"Total Fees", "$8.60"},
+            {"Estimated Strategy Capacity", "$22000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UK0MYO1"},
             {"Fitness Score", "1"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
             {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "2.133"},
+            {"Portfolio Turnover", "2.035"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -216,7 +217,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "35738733ff791eeeaf508faec804cab0"}
+            {"OrderListHash", "e7021bd385f366771ae00abd3a46a22e"}
         };
     }
 }

Algorithm.CSharp/AddFutureOptionContractFromFutureChainRegressionAlgorithm.cs

@@ -0,0 +1,152 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using System.Collections.Generic;
+using System.Linq;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This regression algorithm tests we can add future option contracts from contracts in the future chain
+    /// </summary>
+    public class AddFutureOptionContractFromFutureChainRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private bool _addedOptions;
+
+        public override void Initialize()
+        {
+            SetStartDate(2020, 1, 4);
+            SetEndDate(2020, 1, 6);
+
+            var es = AddFuture(Futures.Indices.SP500EMini, Resolution.Minute, Market.CME);
+            es.SetFilter((futureFilter) =>
+            {
+                return futureFilter.Expiration(0, 365).ExpirationCycle(new[] { 3, 6 });
+            });
+        }
+
+        public override void OnData(Slice data)
+        {
+            if (!_addedOptions)
+            {
+                _addedOptions = true;
+                foreach (var futuresContracts in data.FutureChains.Values)
+                {
+                    foreach (var contract in futuresContracts)
+                    {
+                        var option_contract_symbols = OptionChainProvider.GetOptionContractList(contract.Symbol, Time).ToList();
+                        if(option_contract_symbols.Count == 0)
+                        {
+                            continue;
+                        }
+
+                        foreach (var option_contract_symbol in option_contract_symbols.OrderBy(x => x.ID.Date)
+                            .ThenBy(x => x.ID.StrikePrice)
+                            .ThenBy(x => x.ID.OptionRight).Take(5))
+                        {
+                            AddOptionContract(option_contract_symbol);
+                        }
+                    }
+                }
+            }
+
+            if (Portfolio.Invested)
+            {
+                return;
+            }
+
+            foreach (var chain in data.OptionChains.Values)
+            {
+                foreach (var option in chain.Contracts.Keys)
+                {
+                    MarketOrder(option, 1);
+                    MarketOrder(option.Underlying, 1);
+                }
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public Language[] Languages { get; } = { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 12164;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "20"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "386219349.202%"},
+            {"Drawdown", "5.200%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "11.912%"},
+            {"Sharpe Ratio", "1604181.92"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "2144881.34"},
+            {"Beta", "31.223"},
+            {"Annual Standard Deviation", "1.337"},
+            {"Annual Variance", "1.788"},
+            {"Information Ratio", "1657259.526"},
+            {"Tracking Error", "1.294"},
+            {"Treynor Ratio", "68696.045"},
+            {"Total Fees", "$35.70"},
+            {"Estimated Strategy Capacity", "$2600000.00"},
+            {"Lowest Capacity Asset", "ES 31C3JQS9D84PW|ES XCZJLC9NOB29"},
+            {"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"}
+        };
+    }
+}

Algorithm.CSharp/AddFutureOptionSingleOptionChainSelectedInUniverseFilterRegressionAlgorithm.cs

@@ -43,7 +43,7 @@ namespace QuantConnect.Algorithm.CSharp
         public override void Initialize()
         {
             SetStartDate(2020, 1, 4);
-            SetEndDate(2020, 1, 6);
+            SetEndDate(2020, 1, 8);
 
             _es = AddFuture(Futures.Indices.SP500EMini, Resolution.Minute, Market.CME);
             _es.SetFilter((futureFilter) =>
@@ -164,8 +164,6 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void OnEndOfAlgorithm()
         {
-            base.OnEndOfAlgorithm();
-
             if (!_optionFilterRan)
             {
                 throw new InvalidOperationException("Option chain filter was never ran");
@@ -222,7 +220,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 779544;
+        public long DataPoints => 608437;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -237,31 +235,31 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-10.708%"},
-            {"Drawdown", "0.200%"},
+            {"Compounding Annual Return", "347.065%"},
+            {"Drawdown", "0.900%"},
             {"Expectancy", "0"},
-            {"Net Profit", "-0.093%"},
-            {"Sharpe Ratio", "-10.594"},
-            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Net Profit", "1.951%"},
+            {"Sharpe Ratio", "15.548"},
+            {"Probabilistic Sharpe Ratio", "95.977%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.261"},
-            {"Beta", "0.244"},
-            {"Annual Standard Deviation", "0.01"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-22.456"},
-            {"Tracking Error", "0.032"},
-            {"Treynor Ratio", "-0.454"},
-            {"Total Fees", "$3.70"},
-            {"Estimated Strategy Capacity", "$41000.00"},
-            {"Lowest Capacity Asset", "ES 31C3JQTOYO9T0|ES XCZJLC9NOB29"},
-            {"Fitness Score", "0.273"},
+            {"Alpha", "1.885"},
+            {"Beta", "1.066"},
+            {"Annual Standard Deviation", "0.155"},
+            {"Annual Variance", "0.024"},
+            {"Information Ratio", "13.528"},
+            {"Tracking Error", "0.142"},
+            {"Treynor Ratio", "2.258"},
+            {"Total Fees", "$3.57"},
+            {"Estimated Strategy Capacity", "$760000.00"},
+            {"Lowest Capacity Asset", "ES XCZJLDQX2SRO|ES XCZJLC9NOB29"},
+            {"Fitness Score", "0.403"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-123.159"},
-            {"Portfolio Turnover", "0.547"},
+            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
+            {"Portfolio Turnover", "0.403"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -275,7 +273,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9347e3b610cfa21f7cbd968a0135c8af"}
+            {"OrderListHash", "738240babf741f1bf79f85ea5026ec4c"}
         };
     }
 }

Algorithm.CSharp/Alphas/ShareClassMeanReversionAlpha.cs

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

Algorithm.CSharp/Alphas/VixDualThrustAlpha.cs

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

Algorithm.CSharp/AutomaticIndicatorWarmupDataTypeRegressionAlgorithm.cs

@@ -34,8 +34,8 @@ namespace QuantConnect.Algorithm.CSharp
         {
             UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
             EnableAutomaticIndicatorWarmUp = true;
-            SetStartDate(2013, 10, 07);
-            SetEndDate(2013, 10, 09);
+            SetStartDate(2013, 10, 08);
+            SetEndDate(2013, 10, 10);
 
             var SP500 = QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME);
             _symbol = FutureChainProvider.GetFutureContractList(SP500, StartDate).First();
@@ -146,7 +146,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 14531;
+        public long DataPoints => 6426;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -161,31 +161,31 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-100.000%"},
-            {"Drawdown", "19.800%"},
+            {"Compounding Annual Return", "733913.744%"},
+            {"Drawdown", "15.900%"},
             {"Expectancy", "0"},
-            {"Net Profit", "-10.353%"},
-            {"Sharpe Ratio", "-1.379"},
+            {"Net Profit", "6.828%"},
+            {"Sharpe Ratio", "203744786353.302"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "3.004"},
-            {"Beta", "5.322"},
-            {"Annual Standard Deviation", "0.725"},
-            {"Annual Variance", "0.525"},
-            {"Information Ratio", "-0.42"},
-            {"Tracking Error", "0.589"},
-            {"Treynor Ratio", "-0.188"},
-            {"Total Fees", "$20.35"},
-            {"Estimated Strategy Capacity", "$13000000.00"},
+            {"Alpha", "456382350698.561"},
+            {"Beta", "9.229"},
+            {"Annual Standard Deviation", "2.24"},
+            {"Annual Variance", "5.017"},
+            {"Information Ratio", "228504036840.953"},
+            {"Tracking Error", "1.997"},
+            {"Treynor Ratio", "49450701625.718"},
+            {"Total Fees", "$23.65"},
+            {"Estimated Strategy Capacity", "$200000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.125"},
+            {"Fitness Score", "0.518"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-2.162"},
-            {"Return Over Maximum Drawdown", "-8.144"},
-            {"Portfolio Turnover", "3.184"},
+            {"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"},
@@ -199,7 +199,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "7ff48adafe9676f341e64ac9388d3c2c"}
+            {"OrderListHash", "dd38e7b94027d20942a5aa9ac31a9a7f"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateCfdAlgorithm.cs

@@ -0,0 +1,72 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Algorithm demonstrating CFD asset types and requesting history.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="history" />
+    /// <meta name="tag" content="cfd" />
+    public class BasicTemplateCfdAlgorithm : QCAlgorithm
+    {
+        private Symbol _symbol;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetAccountCurrency("EUR");
+
+            SetStartDate(2019, 2, 20);
+            SetEndDate(2019, 2, 21);
+            SetCash("EUR", 100000);
+
+            _symbol = AddCfd("DE30EUR").Symbol;
+
+            // Historical Data
+            var history = History(_symbol, 60, Resolution.Daily);
+            Log($"Received {history.Count()} bars from CFD historical data call.");
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            // Access Data
+            if (slice.QuoteBars.ContainsKey(_symbol))
+            {
+                var quoteBar = slice.QuoteBars[_symbol];
+                Log($"{quoteBar.EndTime} :: {quoteBar.Close}");
+            }
+
+            if (!Portfolio.Invested)
+                SetHoldings(_symbol, 1);
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug($"{Time} {orderEvent.ToString()}");
+        }
+    }
+}

Algorithm.CSharp/BasicTemplateContinuousFutureAlgorithm.cs

@@ -83,7 +83,8 @@ namespace QuantConnect.Algorithm.CSharp
                 Liquidate();
             }
 
-            if (_currentContract != null && _currentContract.Symbol != _continuousContract.Mapped)
+            // We check exchange hours because the contract mapping can call OnData outside of regular hours.
+            if (_currentContract != null && _currentContract.Symbol != _continuousContract.Mapped && _continuousContract.Exchange.ExchangeOpen)
             {
                 Log($"{Time} - rolling position from {_currentContract.Symbol} to {_continuousContract.Mapped}");
 
@@ -117,7 +118,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 875590;
+        public long DataPoints => 284403;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -131,31 +132,31 @@ namespace QuantConnect.Algorithm.CSharp
         {
             {"Total Trades", "2"},
             {"Average Win", "0%"},
-            {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "-0.007%"},
+            {"Average Loss", "-0.02%"},
+            {"Compounding Annual Return", "-0.033%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "-1"},
-            {"Net Profit", "-0.004%"},
-            {"Sharpe Ratio", "-0.369"},
-            {"Probabilistic Sharpe Ratio", "10.640%"},
+            {"Net Profit", "-0.017%"},
+            {"Sharpe Ratio", "-1.173"},
+            {"Probabilistic Sharpe Ratio", "0.011%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
             {"Alpha", "-0"},
-            {"Beta", "0"},
+            {"Beta", "-0"},
             {"Annual Standard Deviation", "0"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-2.751"},
+            {"Information Ratio", "-2.752"},
             {"Tracking Error", "0.082"},
-            {"Treynor Ratio", "-0.616"},
-            {"Total Fees", "$3.70"},
+            {"Treynor Ratio", "1.883"},
+            {"Total Fees", "$4.30"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.007"},
+            {"Fitness Score", "0.006"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-0.738"},
+            {"Return Over Maximum Drawdown", "-1.993"},
             {"Portfolio Turnover", "0.01"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -170,7 +171,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "bd7fbe57802dfedb36c85609b7234016"}
+            {"OrderListHash", "1fd4b49e9450800981c6dead2bbca995"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateContinuousFutureWithExtendedMarketAlgorithm.cs

@@ -0,0 +1,182 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+using QuantConnect.Interfaces;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Indicators;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+using Futures = QuantConnect.Securities.Futures;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Basic Continuous Futures Template Algorithm with extended market hours
+    /// </summary>
+    public class BasicTemplateContinuousFutureWithExtendedMarketAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Future _continuousContract;
+        private Security _currentContract;
+        private SimpleMovingAverage _fast;
+        private SimpleMovingAverage _slow;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 7, 1);
+            SetEndDate(2014, 1, 1);
+
+            _continuousContract = AddFuture(Futures.Indices.SP500EMini,
+                dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
+                dataMappingMode: DataMappingMode.LastTradingDay,
+                contractDepthOffset: 0,
+                extendedMarketHours: true
+            );
+
+            _fast = SMA(_continuousContract.Symbol, 3, Resolution.Daily);
+            _slow = SMA(_continuousContract.Symbol, 10, Resolution.Daily);
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice data)
+        {
+            foreach (var changedEvent in data.SymbolChangedEvents.Values)
+            {
+                Debug($"{Time} - SymbolChanged event: {changedEvent}");
+                if (Time.TimeOfDay != TimeSpan.Zero)
+                {
+                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                }
+            }
+
+            if (!IsMarketOpen(_continuousContract.Symbol))
+            {
+                return;
+            }
+
+            if (!Portfolio.Invested)
+            {
+                if(_fast > _slow)
+                {
+                    _currentContract = Securities[_continuousContract.Mapped];
+                    Buy(_currentContract.Symbol, 1);
+                }
+            }
+            else if(_fast < _slow)
+            {
+                Liquidate();
+            }
+
+            if (_currentContract != null && _currentContract.Symbol != _continuousContract.Mapped)
+            {
+                Log($"{Time} - rolling position from {_currentContract.Symbol} to {_continuousContract.Mapped}");
+
+                var currentPositionSize = _currentContract.Holdings.Quantity;
+                Liquidate(_currentContract.Symbol);
+                Buy(_continuousContract.Mapped, currentPositionSize);
+                _currentContract = Securities[_continuousContract.Mapped];
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug($"{orderEvent}");
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            Debug($"{Time}-{changes}");
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 884815;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "2"},
+            {"Average Win", "0%"},
+            {"Average Loss", "-0.02%"},
+            {"Compounding Annual Return", "-0.033%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "-0.017%"},
+            {"Sharpe Ratio", "-1.173"},
+            {"Probabilistic Sharpe Ratio", "0.011%"},
+            {"Loss Rate", "100%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0"},
+            {"Beta", "-0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-2.752"},
+            {"Tracking Error", "0.082"},
+            {"Treynor Ratio", "1.883"},
+            {"Total Fees", "$4.30"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
+            {"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"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFutureOptionAlgorithm.cs

@@ -0,0 +1,95 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Algorithm demonstrating FutureOption asset types and requesting history.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="history" />
+    /// <meta name="tag" content="future option" />
+    public class BasicTemplateFutureOptionAlgorithm : QCAlgorithm
+    {
+        private Symbol _symbol;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2022, 1, 1);
+            SetEndDate(2022, 2, 1);
+            SetCash(100000);
+
+            var gold_futures = AddFuture(Futures.Metals.Gold, Resolution.Minute);
+            gold_futures.SetFilter(0, 180);
+            _symbol = gold_futures.Symbol;
+            AddFutureOption(_symbol, universe => universe.Strikes(-5, +5)
+                                                        .CallsOnly()
+                                                        .BackMonth()
+                                                        .OnlyApplyFilterAtMarketOpen());
+
+            // Historical Data
+            var history = History(_symbol, 60, Resolution.Daily);
+            Log($"Received {history.Count()} bars from {_symbol} FutureOption historical data call.");
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            // Access Data
+            foreach(var kvp in slice.OptionChains)
+            {
+                var underlyingFutureContract = kvp.Key.Underlying;
+                var chain = kvp.Value;
+
+                if (chain.Count() == 0) continue;
+
+                foreach(var contract in chain)
+                {
+                    Log($@"Canonical Symbol: {kvp.Key}; 
+                        Contract: {contract}; 
+                        Right: {contract.Right}; 
+                        Expiry: {contract.Expiry}; 
+                        Bid price: {contract.BidPrice}; 
+                        Ask price: {contract.AskPrice}; 
+                        Implied Volatility: {contract.ImpliedVolatility}");
+                }
+
+                if (!Portfolio.Invested)
+                {
+                    var atmStrike = chain.OrderBy(x => Math.Abs(chain.Underlying.Price - x.Strike)).First().Strike;
+                    var selectedContract = chain.Where(x => x.Strike == atmStrike).OrderByDescending(x => x.Expiry).First();
+                    MarketOrder(selectedContract.Symbol, 1);
+                }
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug($"{Time} {orderEvent.ToString()}");
+        }
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesAlgorithm.cs

@@ -59,7 +59,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             // set our expiry filter for this futures chain
             // SetFilter method accepts TimeSpan objects or integer for days.
-            // The following statements yield the same filtering criteria 
+            // The following statements yield the same filtering criteria
             futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
             futureGold.SetFilter(0, 182);
 
@@ -151,46 +151,46 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 203367;
+        public long DataPoints => 68645;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 518;
+        public int AlgorithmHistoryDataPoints => 340;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "8220"},
+            {"Total Trades", "2700"},
             {"Average Win", "0.00%"},
             {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "-100.000%"},
-            {"Drawdown", "13.500%"},
-            {"Expectancy", "-0.818"},
-            {"Net Profit", "-13.517%"},
-            {"Sharpe Ratio", "-98.781"},
+            {"Compounding Annual Return", "-99.777%"},
+            {"Drawdown", "4.400%"},
+            {"Expectancy", "-0.724"},
+            {"Net Profit", "-4.430%"},
+            {"Sharpe Ratio", "-31.389"},
             {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "89%"},
-            {"Win Rate", "11%"},
-            {"Profit-Loss Ratio", "0.69"},
-            {"Alpha", "-1.676"},
-            {"Beta", "0.042"},
-            {"Annual Standard Deviation", "0.01"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-73.981"},
-            {"Tracking Error", "0.233"},
-            {"Treynor Ratio", "-23.975"},
-            {"Total Fees", "$15207.00"},
-            {"Estimated Strategy Capacity", "$8000.00"},
+            {"Loss Rate", "83%"},
+            {"Win Rate", "17%"},
+            {"Profit-Loss Ratio", "0.65"},
+            {"Alpha", "-3.059"},
+            {"Beta", "0.128"},
+            {"Annual Standard Deviation", "0.031"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-81.232"},
+            {"Tracking Error", "0.212"},
+            {"Treynor Ratio", "-7.618"},
+            {"Total Fees", "$6237.00"},
+            {"Estimated Strategy Capacity", "$14000.00"},
             {"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
-            {"Fitness Score", "0.033"},
+            {"Fitness Score", "0.001"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-8.62"},
-            {"Return Over Maximum Drawdown", "-7.81"},
-            {"Portfolio Turnover", "302.321"},
+            {"Sortino Ratio", "-58.725"},
+            {"Return Over Maximum Drawdown", "-32.073"},
+            {"Portfolio Turnover", "98.477"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -204,7 +204,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "35b3f4b7a225468d42ca085386a2383e"}
+            {"OrderListHash", "8f92e1528c6477a156449fd1e86527e7"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesDailyAlgorithm.cs

@@ -19,7 +19,9 @@ using System.Collections.Generic;
 using System.Linq;
 using QuantConnect.Data;
 using QuantConnect.Interfaces;
+using QuantConnect.Orders;
 using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -31,14 +33,16 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="futures" />
     public class BasicTemplateFuturesDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private Symbol _contractSymbol;
         protected virtual Resolution Resolution => Resolution.Daily;
+        protected virtual bool ExtendedMarketHours => false;
 
         // S&P 500 EMini futures
         private const string RootSP500 = Futures.Indices.SP500EMini;
 
         // Gold futures
         private const string RootGold = Futures.Metals.Gold;
+        private Future _futureSP500;
+        private Future _futureGold;
 
         /// <summary>
         /// Initialize your algorithm and add desired assets.
@@ -49,14 +53,14 @@ namespace QuantConnect.Algorithm.CSharp
             SetEndDate(2014, 10, 10);
             SetCash(1000000);
 
-            var futureSP500 = AddFuture(RootSP500, Resolution);
-            var futureGold = AddFuture(RootGold, Resolution);
+            _futureSP500 = AddFuture(RootSP500, Resolution, extendedMarketHours: ExtendedMarketHours);
+            _futureGold = AddFuture(RootGold, Resolution, extendedMarketHours: ExtendedMarketHours);
 
             // set our expiry filter for this futures chain
             // SetFilter method accepts TimeSpan objects or integer for days.
-            // The following statements yield the same filtering criteria 
-            futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
-            futureGold.SetFilter(0, 182);
+            // The following statements yield the same filtering criteria
+            _futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
+            _futureGold.SetFilter(0, 182);
         }
 
         /// <summary>
@@ -76,15 +80,17 @@ namespace QuantConnect.Algorithm.CSharp
                         select futuresContract
                     ).FirstOrDefault();
 
-                    // if found, trade it
-                    if (contract != null && IsMarketOpen(contract.Symbol))
+                    // 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))
                     {
-                        _contractSymbol = contract.Symbol;
-                        MarketOrder(_contractSymbol, 1);
+                        MarketOrder(contract.Symbol, 1);
                     }
                 }
             }
-            else
+            // Same as above, check for cases like trading on a friday night.
+            else if (Securities.Values.Where(x => x.Invested).All(x => x.Exchange.Hours.IsOpen(Time, true)))
             {
                 Liquidate();
             }
@@ -111,7 +117,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 13559;
+        public virtual long DataPoints => 11709;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -123,34 +129,34 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "152"},
+            {"Total Trades", "118"},
             {"Average Win", "0.09%"},
             {"Average Loss", "-0.01%"},
-            {"Compounding Annual Return", "-0.638%"},
-            {"Drawdown", "0.600%"},
-            {"Expectancy", "-0.871"},
-            {"Net Profit", "-0.643%"},
-            {"Sharpe Ratio", "-2.323"},
+            {"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", "99%"},
-            {"Win Rate", "1%"},
-            {"Profit-Loss Ratio", "8.83"},
-            {"Alpha", "-0.004"},
+            {"Loss Rate", "98%"},
+            {"Win Rate", "2%"},
+            {"Profit-Loss Ratio", "8.76"},
+            {"Alpha", "-0.003"},
             {"Beta", "-0.001"},
             {"Annual Standard Deviation", "0.002"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.408"},
+            {"Information Ratio", "-1.397"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "3.612"},
-            {"Total Fees", "$281.20"},
+            {"Treynor Ratio", "5.665"},
+            {"Total Fees", "$263.30"},
             {"Estimated Strategy Capacity", "$1000.00"},
             {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
-            {"Fitness Score", "0.013"},
+            {"Fitness Score", "0.01"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.45"},
+            {"Sortino Ratio", "-1.059"},
             {"Return Over Maximum Drawdown", "-0.992"},
-            {"Portfolio Turnover", "0.04"},
+            {"Portfolio Turnover", "0.031"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -164,7 +170,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "909088689d7030fa33c5da3c15fba98e"}
+            {"OrderListHash", "b75b224669c374dcbacc33f946a1cc7c"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesFrameworkAlgorithm.cs

@@ -31,9 +31,12 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class BasicTemplateFuturesFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
+        protected virtual bool ExtendedMarketHours => false;
+
         public override void Initialize()
         {
             UniverseSettings.Resolution = Resolution.Minute;
+            UniverseSettings.ExtendedMarketHours = ExtendedMarketHours;
 
             SetStartDate(2013, 10, 07);
             SetEndDate(2013, 10, 11);
@@ -123,70 +126,70 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
         /// </summary>
-        public bool CanRunLocally { get; } = true;
+        public virtual bool CanRunLocally { get; } = true;
 
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 123378;
+        public virtual long DataPoints => 43786;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 0;
+        public virtual int AlgorithmHistoryDataPoints => 0;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-92.656%"},
-            {"Drawdown", "5.000%"},
+            {"Compounding Annual Return", "-81.734%"},
+            {"Drawdown", "4.100%"},
             {"Expectancy", "0"},
-            {"Net Profit", "-3.312%"},
-            {"Sharpe Ratio", "-6.305"},
-            {"Probabilistic Sharpe Ratio", "9.342%"},
+            {"Net Profit", "-2.169%"},
+            {"Sharpe Ratio", "-10.195"},
+            {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-1.465"},
-            {"Beta", "0.312"},
-            {"Annual Standard Deviation", "0.134"},
-            {"Annual Variance", "0.018"},
-            {"Information Ratio", "-14.77"},
-            {"Tracking Error", "0.192"},
-            {"Treynor Ratio", "-2.718"},
-            {"Total Fees", "$3.70"},
-            {"Estimated Strategy Capacity", "$52000000.00"},
+            {"Alpha", "-1.206"},
+            {"Beta", "0.238"},
+            {"Annual Standard Deviation", "0.072"},
+            {"Annual Variance", "0.005"},
+            {"Information Ratio", "-15.404"},
+            {"Tracking Error", "0.176"},
+            {"Treynor Ratio", "-3.077"},
+            {"Total Fees", "$4.62"},
+            {"Estimated Strategy Capacity", "$17000000.00"},
             {"Lowest Capacity Asset", "GC VL5E74HP3EE5"},
-            {"Fitness Score", "0.009"},
-            {"Kelly Criterion Estimate", "-112.972"},
-            {"Kelly Criterion Probability Value", "0.671"},
-            {"Sortino Ratio", "-8.425"},
-            {"Return Over Maximum Drawdown", "-35.219"},
-            {"Portfolio Turnover", "0.548"},
-            {"Total Insights Generated", "6"},
-            {"Total Insights Closed", "5"},
-            {"Total Insights Analysis Completed", "5"},
-            {"Long Insight Count", "6"},
+            {"Fitness Score", "0.006"},
+            {"Kelly Criterion Estimate", "-50.022"},
+            {"Kelly Criterion Probability Value", "0.711"},
+            {"Sortino Ratio", "-9.907"},
+            {"Return Over Maximum Drawdown", "-50.79"},
+            {"Portfolio Turnover", "0.54"},
+            {"Total Insights Generated", "5"},
+            {"Total Insights Closed", "4"},
+            {"Total Insights Analysis Completed", "4"},
+            {"Long Insight Count", "5"},
             {"Short Insight Count", "0"},
             {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$-96.12923"},
-            {"Total Accumulated Estimated Alpha Value", "$-15.621"},
-            {"Mean Population Estimated Insight Value", "$-3.1242"},
-            {"Mean Population Direction", "0%"},
+            {"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", "0%"},
+            {"Rolling Averaged Population Direction", "25%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "18ffd3a774c68da83d867e3b09e3e05d"}
+            {"OrderListHash", "323b899ae80aa839e320806411665ce7"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesFrameworkWithExtendedMarketAlgorithm.cs

@@ -0,0 +1,95 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using System.Collections.Generic;
+using QuantConnect.Algorithm.Framework.Alphas;
+using QuantConnect.Algorithm.Framework.Execution;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Algorithm.Framework.Risk;
+using QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Basic template futures framework algorithm uses framework components to define an algorithm
+    /// that trades futures.
+    /// </summary>
+    public class BasicTemplateFuturesFrameworkWithExtendedMarketAlgorithm : BasicTemplateFuturesFrameworkAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 123753;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "2"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "-92.667%"},
+            {"Drawdown", "5.000%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "-3.314%"},
+            {"Sharpe Ratio", "-6.303"},
+            {"Probabilistic Sharpe Ratio", "9.333%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-1.465"},
+            {"Beta", "0.312"},
+            {"Annual Standard Deviation", "0.134"},
+            {"Annual Variance", "0.018"},
+            {"Information Ratio", "-14.77"},
+            {"Tracking Error", "0.192"},
+            {"Treynor Ratio", "-2.718"},
+            {"Total Fees", "$4.62"},
+            {"Estimated Strategy Capacity", "$52000000.00"},
+            {"Lowest Capacity Asset", "GC VL5E74HP3EE5"},
+            {"Fitness Score", "0.009"},
+            {"Kelly Criterion Estimate", "-112.972"},
+            {"Kelly Criterion Probability Value", "0.671"},
+            {"Sortino Ratio", "-8.421"},
+            {"Return Over Maximum Drawdown", "-35.2"},
+            {"Portfolio Turnover", "0.548"},
+            {"Total Insights Generated", "6"},
+            {"Total Insights Closed", "5"},
+            {"Total Insights Analysis Completed", "5"},
+            {"Long Insight Count", "6"},
+            {"Short Insight Count", "0"},
+            {"Long/Short Ratio", "100%"},
+            {"Estimated Monthly Alpha Value", "$-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"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesHistoryAlgorithm.cs

@@ -36,6 +36,9 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="futures" />
     public class BasicTemplateFuturesHistoryAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
+        protected virtual bool ExtendedMarketHours => false;
+        protected virtual int ExpectedHistoryCallCount => 42;
+
         // S&P 500 EMini futures
         private string [] roots = new []
         {
@@ -44,7 +47,6 @@ namespace QuantConnect.Algorithm.CSharp
         };
 
         private int _successCount = 0;
-
         public override void Initialize()
         {
             SetStartDate(2013, 10, 8);
@@ -54,7 +56,7 @@ namespace QuantConnect.Algorithm.CSharp
             foreach (var root in roots)
             {
                 // set our expiry filter for this futures chain
-                AddFuture(root, Resolution.Minute).SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
+                AddFuture(root, Resolution.Minute, extendedMarketHours: ExtendedMarketHours).SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
             }
 
             SetBenchmark(d => 1000000);
@@ -74,7 +76,7 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void OnEndOfAlgorithm()
         {
-            if (_successCount < 49)
+            if (_successCount < ExpectedHistoryCallCount)
             {
                 throw new Exception($"Scheduled Event did not assert history call as many times as expected: {_successCount}/49");
             }
@@ -118,7 +120,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {
@@ -128,27 +130,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
         /// </summary>
-        public bool CanRunLocally { get; } = true;
+        public virtual bool CanRunLocally { get; } = true;
 
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+        public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 133616;
+        public virtual long DataPoints => 44184;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 5539;
+        public virtual int AlgorithmHistoryDataPoints => 4818;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "0"},
             {"Average Win", "0%"},

Algorithm.CSharp/BasicTemplateFuturesHistoryWithExtendedMarketHoursAlgorithm.cs

@@ -0,0 +1,106 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+using QuantConnect.Securities;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to get access to futures history for a given root symbol with extended market hours.
+    /// It also shows how you can prefilter contracts easily based on expirations, and inspect the futures
+    /// chain to pick a specific contract to trade.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="history and warm up" />
+    /// <meta name="tag" content="history" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesHistoryWithExtendedMarketHoursAlgorithm : BasicTemplateFuturesHistoryAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+        protected override int ExpectedHistoryCallCount => 49;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 134096;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 5539;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"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", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesHourlyAlgorithm.cs

@@ -31,14 +31,8 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="futures" />
     public class BasicTemplateFuturesHourlyAlgorithm : BasicTemplateFuturesDailyAlgorithm
     {
-        private Symbol _contractSymbol;
         protected override Resolution Resolution => Resolution.Hour;
 
-        /// <summary>
-        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
-        /// </summary>
-        public override bool CanRunLocally { get; } = true;
-
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
@@ -47,46 +41,41 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 205645;
-
-        /// <summary>
-        /// Data Points count of the algorithm history
-        /// </summary>
-        public override int AlgorithmHistoryDataPoints => 0;
+        public override long DataPoints => 73252;
 
         /// <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", "1988"},
-            {"Average Win", "0.01%"},
-            {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "-4.120%"},
-            {"Drawdown", "4.200%"},
-            {"Expectancy", "-0.870"},
-            {"Net Profit", "-4.150%"},
-            {"Sharpe Ratio", "-6.061"},
-            {"Probabilistic Sharpe Ratio", "0%"},
-            {"Loss Rate", "97%"},
-            {"Win Rate", "3%"},
-            {"Profit-Loss Ratio", "2.92"},
-            {"Alpha", "-0.027"},
-            {"Beta", "-0.006"},
-            {"Annual Standard Deviation", "0.005"},
+            {"Total Trades", "638"},
+            {"Average Win", "0.02%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "-1.610%"},
+            {"Drawdown", "1.600%"},
+            {"Expectancy", "-0.841"},
+            {"Net Profit", "-1.622%"},
+            {"Sharpe Ratio", "-5.105"},
+            {"Probabilistic Sharpe Ratio", "0.000%"},
+            {"Loss Rate", "96%"},
+            {"Win Rate", "4%"},
+            {"Profit-Loss Ratio", "3.21"},
+            {"Alpha", "-0.01"},
+            {"Beta", "-0.003"},
+            {"Annual Standard Deviation", "0.002"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-1.66"},
+            {"Information Ratio", "-1.473"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "4.919"},
-            {"Total Fees", "$3677.80"},
-            {"Estimated Strategy Capacity", "$2000.00"},
+            {"Treynor Ratio", "3.179"},
+            {"Total Fees", "$1456.18"},
+            {"Estimated Strategy Capacity", "$6000.00"},
             {"Lowest Capacity Asset", "ES VP274HSU1AF5"},
-            {"Fitness Score", "0.128"},
+            {"Fitness Score", "0.045"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-6.856"},
-            {"Return Over Maximum Drawdown", "-0.995"},
-            {"Portfolio Turnover", "0.648"},
+            {"Sortino Ratio", "-4.326"},
+            {"Return Over Maximum Drawdown", "-0.994"},
+            {"Portfolio Turnover", "0.205"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -100,7 +89,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "87d2b127c9859cad9d2c65ac9d76deb5"}
+            {"OrderListHash", "8842e0b890f721371ebf3c25328dee5b"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketAlgorithm.cs

@@ -0,0 +1,210 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add futures for a given underlying asset.
+    /// It also shows how you can prefilter contracts easily based on expirations, and how you
+    /// can inspect the futures chain to pick a specific contract to trade.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesWithExtendedMarketAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _contractSymbol;
+
+        // S&P 500 EMini futures
+        private const string RootSP500 = Futures.Indices.SP500EMini;
+        public Symbol SP500 = QuantConnect.Symbol.Create(RootSP500, SecurityType.Future, Market.CME);
+
+        // Gold futures
+        private const string RootGold = Futures.Metals.Gold;
+        public Symbol Gold = QuantConnect.Symbol.Create(RootGold, SecurityType.Future, Market.COMEX);
+
+        /// <summary>
+        /// Initialize your algorithm and add desired assets.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 08);
+            SetEndDate(2013, 10, 10);
+            SetCash(1000000);
+
+            var futureSP500 = AddFuture(RootSP500, extendedMarketHours: true);
+            var futureGold = AddFuture(RootGold, extendedMarketHours: true);
+
+            // set our expiry filter for this futures chain
+            // SetFilter method accepts TimeSpan objects or integer for days.
+            // The following statements yield the same filtering criteria
+            futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
+            futureGold.SetFilter(0, 182);
+
+            var benchmark = AddEquity("SPY");
+            SetBenchmark(benchmark.Symbol);
+
+            var seeder = new FuncSecuritySeeder(GetLastKnownPrices);
+            SetSecurityInitializer(security => seeder.SeedSecurity(security));
+        }
+
+        /// <summary>
+        /// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
+        /// </summary>
+        /// <param name="slice">The current slice of data keyed by symbol string</param>
+        public override void OnData(Slice slice)
+        {
+            foreach (var changedEvent in slice.SymbolChangedEvents.Values)
+            {
+                Debug($"{Time} - SymbolChanged event: {changedEvent}");
+                if (Time.TimeOfDay != TimeSpan.Zero)
+                {
+                    throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
+                }
+            }
+
+            if (!Portfolio.Invested)
+            {
+                foreach(var chain in slice.FutureChains)
+                {
+                    // find the front contract expiring no earlier than in 90 days
+                    var contract = (
+                        from futuresContract in chain.Value.OrderBy(x => x.Expiry)
+                        where futuresContract.Expiry > Time.Date.AddDays(90)
+                        select futuresContract
+                    ).FirstOrDefault();
+
+                    // if found, trade it
+                    if (contract != null)
+                    {
+                        _contractSymbol = contract.Symbol;
+                        MarketOrder(_contractSymbol, 1);
+                    }
+                }
+            }
+            else
+            {
+                Liquidate();
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            // Get the margin requirements
+            var buyingPowerModel = Securities[_contractSymbol].BuyingPowerModel;
+            var futureMarginModel = buyingPowerModel as FutureMarginModel;
+            if (buyingPowerModel == null)
+            {
+                throw new Exception($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
+            }
+            var initialOvernight = futureMarginModel.InitialOvernightMarginRequirement;
+            var maintenanceOvernight = futureMarginModel.MaintenanceOvernightMarginRequirement;
+            var initialIntraday = futureMarginModel.InitialIntradayMarginRequirement;
+            var maintenanceIntraday = futureMarginModel.MaintenanceIntradayMarginRequirement;
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            foreach (var addedSecurity in changes.AddedSecurities)
+            {
+                if (addedSecurity.Symbol.SecurityType == SecurityType.Future
+                    && !addedSecurity.Symbol.IsCanonical()
+                    && !addedSecurity.HasData)
+                {
+                    throw new Exception($"Future contracts did not work up as expected: {addedSecurity.Symbol}");
+                }
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 204087;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 340;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "8282"},
+            {"Average Win", "0.00%"},
+            {"Average Loss", "0.00%"},
+            {"Compounding Annual Return", "-100.000%"},
+            {"Drawdown", "13.900%"},
+            {"Expectancy", "-0.824"},
+            {"Net Profit", "-13.874%"},
+            {"Sharpe Ratio", "-19.202"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "89%"},
+            {"Win Rate", "11%"},
+            {"Profit-Loss Ratio", "0.64"},
+            {"Alpha", "2.477"},
+            {"Beta", "-0.215"},
+            {"Annual Standard Deviation", "0.052"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-58.37"},
+            {"Tracking Error", "0.295"},
+            {"Treynor Ratio", "4.66"},
+            {"Total Fees", "$19131.42"},
+            {"Estimated Strategy Capacity", "$130000.00"},
+            {"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
+            {"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"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketDailyAlgorithm.cs

@@ -0,0 +1,97 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This example demonstrates how to add futures with daily resolution and extended market hours.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesWithExtendedMarketDailyAlgorithm : BasicTemplateFuturesDailyAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 13559;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "152"},
+            {"Average Win", "0.09%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "-0.644%"},
+            {"Drawdown", "0.600%"},
+            {"Expectancy", "-0.872"},
+            {"Net Profit", "-0.649%"},
+            {"Sharpe Ratio", "-2.343"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "99%"},
+            {"Win Rate", "1%"},
+            {"Profit-Loss Ratio", "8.76"},
+            {"Alpha", "-0.004"},
+            {"Beta", "-0.001"},
+            {"Annual Standard Deviation", "0.002"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.409"},
+            {"Tracking Error", "0.089"},
+            {"Treynor Ratio", "3.618"},
+            {"Total Fees", "$338.96"},
+            {"Estimated Strategy Capacity", "$1000.00"},
+            {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
+            {"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"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketHourlyAlgorithm.cs

@@ -0,0 +1,95 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This regressions tests the BasicTemplateFuturesDailyAlgorithm with hour data and extended market hours
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="benchmarks" />
+    /// <meta name="tag" content="futures" />
+    public class BasicTemplateFuturesWithExtendedMarketHourlyAlgorithm : BasicTemplateFuturesHourlyAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 205645;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "1982"},
+            {"Average Win", "0.01%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "-4.666%"},
+            {"Drawdown", "4.700%"},
+            {"Expectancy", "-0.911"},
+            {"Net Profit", "-4.700%"},
+            {"Sharpe Ratio", "-5.792"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "97%"},
+            {"Win Rate", "3%"},
+            {"Profit-Loss Ratio", "2.04"},
+            {"Alpha", "-0.031"},
+            {"Beta", "-0.008"},
+            {"Annual Standard Deviation", "0.005"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.701"},
+            {"Tracking Error", "0.09"},
+            {"Treynor Ratio", "4.096"},
+            {"Total Fees", "$4521.78"},
+            {"Estimated Strategy Capacity", "$2000.00"},
+            {"Lowest Capacity Asset", "ES VP274HSU1AF5"},
+            {"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"}
+        };
+    }
+}

Algorithm.CSharp/BasicTemplateIndiaAlgorithm.cs

@@ -43,13 +43,13 @@ namespace QuantConnect.Algorithm.CSharp
             // Equities Resolutions: Tick, Second, Minute, Hour, Daily.
             AddEquity("YESBANK", Resolution.Minute, Market.India);
 
-            //Set Order Prperties as per the requirements for order placement
+            //Set Order Properties as per the requirements for order placement
             DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE);
             //override default productType value set in config.json if needed - order specific productType value
             //DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE, IndiaOrderProperties.IndiaProductType.CNC);
 
             // General Debug statement for acknowledgement
-            Debug("Intialization Done");
+            Debug("Initialization Done");
         }
 
         /// <summary>

Algorithm.CSharp/BasicTemplateIndiaIndexAlgorithm.cs

@@ -52,7 +52,7 @@ namespace QuantConnect.Algorithm.CSharp
             //Trade Index based ETF
             NiftyETF = AddEquity("JUNIORBEES", Resolution.Minute, Market.India).Symbol;
 
-            //Set Order Prperties as per the requirements for order placement
+            //Set Order Properties as per the requirements for order placement
             DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE);
 
             _emaSlow = EMA(Nifty, 80);

Algorithm.CSharp/BasicTemplateIntrinioEconomicData.cs

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

Algorithm.CSharp/BasicTemplateMultiAssetAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateOptionEquityStrategyAlgorithm.cs

@@ -82,7 +82,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {

Algorithm.CSharp/BasicTemplateOptionStrategyAlgorithm.cs

@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {

Algorithm.CSharp/BasicTemplateOptionTradesAlgorithm.cs

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

Algorithm.CSharp/BasicTemplateOptionsAlgorithm.cs

@@ -89,7 +89,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {

Algorithm.CSharp/BasicTemplateOptionsDailyAlgorithm.cs

@@ -81,7 +81,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {

Algorithm.CSharp/BasicTemplateOptionsHourlyAlgorithm.cs

@@ -89,7 +89,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Order fill event handler. On an order fill update the resulting information is passed to this method.
         /// </summary>
-        /// <param name="orderEvent">Order event details containing details of the evemts</param>
+        /// <param name="orderEvent">Order event details containing details of the events</param>
         /// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
         public override void OnOrderEvent(OrderEvent orderEvent)
         {

Algorithm.CSharp/Benchmarks/BasicTemplateBenchmark.cs

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

Algorithm.CSharp/Benchmarks/CoarseFineUniverseSelectionBenchmark.cs

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

Algorithm.CSharp/Benchmarks/EmptyEquityAndOptions400Benchmark.cs

@@ -0,0 +1,87 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using QuantConnect.Data;
+
+namespace QuantConnect.Algorithm.CSharp.Benchmarks
+{
+    /// <summary>
+    /// Benchmark Algorithm: Loading and synchronization of 500 equity minute symbols and their options.
+    /// </summary>
+    public class EmptyEquityAndOptions400Benchmark : QCAlgorithm
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2022, 5, 11);
+            SetEndDate(2022, 5, 12);
+
+            var equity_symbols = new[] {
+
+"MARK", "TSN", "DT", "RDW", "CVE", "NXPI", "FIVN", "CLX", "SPXL", "BKSY", "NUGT", "CF", "NEGG",
+"RH", "SIRI", "ITUB", "CSX", "AUR", "LIDR", "CMPS", "DHI", "GLW", "NTES", "CIFR", "S", "HSBC",
+"HIPO", "WTRH", "AMRN", "BIIB", "RIO", "EDIT", "TEAM", "CNK", "BUD", "MILE", "AEHR", "DOCN",
+"CLSK", "BROS", "MLCO", "SBLK", "ICLN", "OPK", "CNC", "SKX", "SESN", "VRM", "ASML", "BBAI",
+"HON", "MRIN", "BLMN", "NTNX", "POWW", "FOUR", "HOG", "GOGO", "MGNI", "GENI", "XPDI",
+"DG", "PSX", "RRC", "CORT", "MET", "UMC", "INMD", "RBAC", "ISRG", "BOX", "DVAX", "CRVS", "HLT",
+"BKNG", "BENE", "CLVS", "ESSC", "PTRA", "BE", "FPAC", "YETI", "DOCS", "DB", "EBON", "RDS.B",
+"ERIC", "BSIG", "INTU", "MNTS", "BCTX", "BLU", "FIS", "MAC", "WMB", "TTWO", "ARDX", "SWBI",
+"ELY", "INDA", "REAL", "ACI", "APRN", "BHP", "CPB", "SLQT", "ARKF", "TSP", "OKE", "NVTA", "META",
+"CSTM", "KMX", "IBB", "AGEN", "WOOF", "MJ", "HYZN", "RSI", "JCI", "EXC", "HPE", "SI", "WPM",
+"PRTY", "BBD", "FVRR", "CANO", "INDI", "MDLZ", "KOLD", "AMBA", "SOXS", "RSX", "ZEN", "PUBM",
+"VLDR", "CI", "ISEE", "GEO", "BKR", "DHR", "GRPN", "NRXP", "ACN", "MAT", "BODY", "ENDP",
+"SHPW", "AVIR", "GPN", "BILL", "BZ", "CERN", "ARVL", "DNMR", "NTR", "FSM", "BMBL", "PAAS",
+"INVZ", "ANF", "CL", "XP", "CS", "KD", "WW", "AHT", "GRTX", "XLC", "BLDP", "HTA", "APT", "BYSI",
+"ENB", "TRIT", "VTNR", "AVCT", "SLI", "CP", "CAH", "ALLY", "FIGS", "PXD", "TPX", "ZI", "BKLN", "SKIN",
+"LNG", "NU", "CX", "GSM", "NXE", "REI", "MNDT", "IP", "BLOK", "IAA", "TIP", "MCHP", "EVTL", "BIGC",
+"IGV", "LOTZ", "EWC", "DRI", "PSTG", "APLS", "KIND", "BBIO", "APPH", "FIVE", "LSPD", "SHAK",
+"COMM", "NAT", "VFC", "AMT", "VRTX", "RGS", "DD", "GBIL", "LICY", "ACHR", "FLR", "HGEN", "TECL",
+"SEAC", "NVS", "NTAP", "ML", "SBSW", "XRX", "UA", "NNOX", "SFT", "FE", "APP", "KEY", "CDEV",
+"DPZ", "BARK", "SPR", "CNQ", "XL", "AXSM", "ECH", "RNG", "AMLP", "ENG", "BTI", "REKR",
+"STZ", "BK", "HEAR", "LEV", "SKT", "HBI", "ALB", "CAG", "MNKD", "NMM", "BIRD", "CIEN", "SILJ",
+"STNG", "GUSH", "GIS", "PRPL", "SDOW", "GNRC", "ERX", "GES", "CPE", "FBRX", "WM", "ESTC",
+"GOED", "STLD", "LILM", "JNK", "BOIL", "ALZN", "IRBT", "KOPN", "AU", "TPR", "RWLK", "TROX",
+"TMO", "AVDL", "XSPA", "JKS", "PACB", "LOGI", "BLK", "REGN", "CFVI", "EGHT", "ATNF", "PRU",
+"URBN", "KMB", "SIX", "CME", "ENVX", "NVTS", "CELH", "CSIQ", "GSL", "PAA", "WU", "MOMO",
+"TOL", "WEN", "GTE", "EXAS", "GDRX", "PVH", "BFLY", "SRTY", "UDOW", "NCR", "ALTO", "CRTD",
+"GOCO", "ALK", "TTM", "DFS", "VFF", "ANTM", "FREY", "WY", "ACWI", "PNC", "SYY", "SNY", "CRK",
+"SO", "XXII", "PBF", "AER", "RKLY", "SOL", "CND", "MPLX", "JNPR", "FTCV", "CLR", "XHB", "YY",
+"POSH", "HIMS", "LIFE", "XENE", "ADM", "ROST", "MIR", "NRG", "AAP", "SSYS", "KBH", "KKR", "PLAN",
+"DUK", "WIMI", "DBRG", "WSM", "LTHM", "OVV", "CFLT", "EWT", "UNFI", "TX", "EMR", "IMGN", "K",
+"ONON", "UNIT", "LEVI", "ADTX", "UPWK", "DBA", "VOO", "FATH", "URI", "MPW", "JNUG", "RDFN",
+"OSCR", "WOLF", "SYF", "GOGL", "HES", "PHM", "CWEB", "ALDX", "BTWN", "AFL", "PPL", "CIM"
+
+            };
+            Settings.DataSubscriptionLimit = 1000000;
+            SetWarmUp(TimeSpan.FromDays(1));
+            foreach(var ticker in equity_symbols)
+            {
+                var option = AddOption(ticker);
+                option.SetFilter(1, 7, 0, 90);
+            }
+
+            AddEquity("SPY");
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (IsWarmingUp)
+            {
+                return;
+            }
+            Quit("The end!");
+        }
+    }
+}

Algorithm.CSharp/Benchmarks/EmptyMinute400EquityBenchmark.cs

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

Algorithm.CSharp/Benchmarks/EmptySingleSecuritySecondEquityBenchmark.cs

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

Algorithm.CSharp/Benchmarks/HistoryRequestBenchmark.cs

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

Algorithm.CSharp/Benchmarks/IndicatorRibbonBenchmark.cs

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

Algorithm.CSharp/Benchmarks/ScheduledEventsBenchmark.cs

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

Algorithm.CSharp/Benchmarks/StatefulCoarseUniverseSelectionBenchmark.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -29,8 +29,8 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
         {
             UniverseSettings.Resolution = Resolution.Daily;
 
-            SetStartDate(2017, 11, 01);
-            SetEndDate(2018, 01, 01);
+            SetStartDate(2017, 1, 01);
+            SetEndDate(2019, 1, 01);
             SetCash(50000);
 
             AddUniverse(CoarseSelectionFunction);

Algorithm.CSharp/Benchmarks/StatelessCoarseUniverseSelectionBenchmark.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -27,8 +27,8 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
         {
             UniverseSettings.Resolution = Resolution.Daily;
 
-            SetStartDate(2017, 11, 01);
-            SetEndDate(2018, 01, 01);
+            SetStartDate(2017, 1, 01);
+            SetEndDate(2019, 1, 01);
             SetCash(50000);
 
             AddUniverse(CoarseSelectionFunction);

Algorithm.CSharp/BubbleAlgorithm.cs

@@ -166,7 +166,7 @@ namespace QuantConnect.Algorithm.CSharp
                     }
 
                 }
-                // Cape Ratio is missing from orignial data
+                // Cape Ratio is missing from original data
                 // Most recent cape data is most likely to be missing
                 else if (_currCape == 0)
                 {
@@ -246,7 +246,7 @@ namespace QuantConnect.Algorithm.CSharp
         }
 
         /// <summary>
-        /// Reader Method :: using set of arguements we specify read out type. Enumerate
+        /// Reader Method :: using set of arguments we specify read out type. Enumerate
         /// until the end of the data stream or file. E.g. Read CSV file line by line and convert
         /// into data types.
         /// </summary>

Algorithm.CSharp/ConsolidateRegressionAlgorithm.cs

@@ -40,7 +40,7 @@ namespace QuantConnect.Algorithm.CSharp
         public override void Initialize()
         {
             SetStartDate(2013, 10, 08);
-            SetEndDate(2013, 10, 09);
+            SetEndDate(2013, 10, 11);
 
             var SP500 = QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME);
             _symbol = FutureChainProvider.GetFutureContractList(SP500, StartDate).First();
@@ -142,7 +142,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 8091;
+        public long DataPoints => 5450;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -157,31 +157,31 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "0%"},
-            {"Drawdown", "0%"},
+            {"Compounding Annual Return", "87589624.963%"},
+            {"Drawdown", "15.900%"},
             {"Expectancy", "0"},
-            {"Net Profit", "0%"},
-            {"Sharpe Ratio", "0"},
+            {"Net Profit", "16.178%"},
+            {"Sharpe Ratio", "43229388091.465"},
             {"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", "$20.35"},
-            {"Estimated Strategy Capacity", "$19000000.00"},
+            {"Alpha", "69177566862.121"},
+            {"Beta", "8.93"},
+            {"Annual Standard Deviation", "1.6"},
+            {"Annual Variance", "2.561"},
+            {"Information Ratio", "48583550955.512"},
+            {"Tracking Error", "1.424"},
+            {"Treynor Ratio", "7746445590.006"},
+            {"Total Fees", "$23.65"},
+            {"Estimated Strategy Capacity", "$210000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.138"},
+            {"Fitness Score", "0.999"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-1.727"},
-            {"Return Over Maximum Drawdown", "-12.061"},
-            {"Portfolio Turnover", "4.916"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "6752050.52"},
+            {"Portfolio Turnover", "2.638"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -195,7 +195,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "7c841ca58a4385f42236838e5bf0c382"}
+            {"OrderListHash", "dd38e7b94027d20942a5aa9ac31a9a7f"}
         };
     }
 }

Algorithm.CSharp/ContinuousBackMonthRawFutureRegressionAlgorithm.cs

@@ -134,7 +134,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 815242;
+        public long DataPoints => 264153;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -147,32 +147,32 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "2"},
-            {"Average Win", "1.21%"},
+            {"Average Win", "1.50%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "2.412%"},
+            {"Compounding Annual Return", "2.993%"},
             {"Drawdown", "1.600%"},
             {"Expectancy", "0"},
-            {"Net Profit", "1.209%"},
-            {"Sharpe Ratio", "0.782"},
-            {"Probabilistic Sharpe Ratio", "40.528%"},
+            {"Net Profit", "1.496%"},
+            {"Sharpe Ratio", "0.814"},
+            {"Probabilistic Sharpe Ratio", "42.511%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
             {"Alpha", "-0.005"},
-            {"Beta", "0.099"},
-            {"Annual Standard Deviation", "0.022"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-2.724"},
+            {"Beta", "0.114"},
+            {"Annual Standard Deviation", "0.026"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-2.672"},
             {"Tracking Error", "0.076"},
-            {"Treynor Ratio", "0.171"},
-            {"Total Fees", "$3.70"},
-            {"Estimated Strategy Capacity", "$810000000.00"},
+            {"Treynor Ratio", "0.184"},
+            {"Total Fees", "$4.30"},
+            {"Estimated Strategy Capacity", "$2200000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
             {"Fitness Score", "0.007"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0.587"},
-            {"Return Over Maximum Drawdown", "1.952"},
+            {"Sortino Ratio", "0.275"},
+            {"Return Over Maximum Drawdown", "2.603"},
             {"Portfolio Turnover", "0.01"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -187,7 +187,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "95c62255290b4ad375579b398290230c"}
+            {"OrderListHash", "ebeeac4c57ccacef7b458b6160190f5b"}
         };
     }
 }

Algorithm.CSharp/ContinuousFutureBackMonthRegressionAlgorithm.cs

@@ -97,13 +97,16 @@ namespace QuantConnect.Algorithm.CSharp
                 _lastDateLog = Time;
 
                 Log($"{Time}- {Securities[_continuousContract.Symbol].GetLastData()}");
-                if (Portfolio.Invested)
+                if (_continuousContract.Exchange.ExchangeOpen)
                 {
-                    Liquidate();
+                    if (Portfolio.Invested)
+                    {
+                        Liquidate();
+                    }
+                    else
+                    {
+                        Buy(_continuousContract.Mapped, 1);
                 }
-                else
-                {
-                    Buy(_continuousContract.Mapped, 1);
                 }
 
                 if(Time.Month == 1 && Time.Year == 2013)
@@ -147,7 +150,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 875590;
+        public long DataPoints => 284403;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -160,32 +163,32 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "1.21%"},
+            {"Average Win", "1.50%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "2.392%"},
+            {"Compounding Annual Return", "2.959%"},
             {"Drawdown", "1.600%"},
             {"Expectancy", "0"},
-            {"Net Profit", "1.199%"},
-            {"Sharpe Ratio", "0.775"},
-            {"Probabilistic Sharpe Ratio", "40.287%"},
+            {"Net Profit", "1.479%"},
+            {"Sharpe Ratio", "0.805"},
+            {"Probabilistic Sharpe Ratio", "42.183%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.006"},
-            {"Beta", "0.099"},
-            {"Annual Standard Deviation", "0.022"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-2.726"},
+            {"Alpha", "-0.005"},
+            {"Beta", "0.114"},
+            {"Annual Standard Deviation", "0.026"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-2.676"},
             {"Tracking Error", "0.076"},
-            {"Treynor Ratio", "0.169"},
-            {"Total Fees", "$5.55"},
-            {"Estimated Strategy Capacity", "$67000000.00"},
+            {"Treynor Ratio", "0.181"},
+            {"Total Fees", "$6.45"},
+            {"Estimated Strategy Capacity", "$180000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
             {"Fitness Score", "0.01"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0.516"},
-            {"Return Over Maximum Drawdown", "1.935"},
+            {"Sortino Ratio", "0.32"},
+            {"Return Over Maximum Drawdown", "2.573"},
             {"Portfolio Turnover", "0.016"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -200,7 +203,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "5fc26c7f1f2d9fff97d36a5b58853840"}
+            {"OrderListHash", "88e74055be58b3759f493b2c47e4c097"}
         };
     }
 }

Algorithm.CSharp/ContinuousFutureHistoryRegressionAlgorithm.cs

@@ -114,7 +114,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 40881;
+        public virtual long DataPoints => 9949;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -124,7 +124,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "1"},
             {"Average Win", "0%"},
@@ -145,15 +145,15 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$290000000.00"},
+            {"Total Fees", "$2.15"},
+            {"Estimated Strategy Capacity", "$3600000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.408"},
+            {"Fitness Score", "0.414"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
             {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0.408"},
+            {"Portfolio Turnover", "0.414"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -167,7 +167,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9408389924d9b7333a9f0a4f64b08d27"}
+            {"OrderListHash", "1fcd459f69177160b35f7daf96b01a0d"}
         };
     }
 }

Algorithm.CSharp/ContinuousFutureHistoryTimeSpanWarmupRegressionAlgorithm.cs

@@ -0,0 +1,39 @@
+/*
+ * 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;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Continuous Futures History Regression algorithm. Asserting and showcasing the behavior of adding a continuous future
+    /// </summary>
+    public class ContinuousFutureHistoryTimeSpanWarmupRegressionAlgorithm : ContinuousFutureHistoryRegressionAlgorithm
+    {
+        public override void Initialize()
+        {
+            base.Initialize();
+            // We want to match the start time of the base algorithm. ES futures data time zone is UTC, algorithm time zone is new york (default).
+            // Base algorithm warmup is 1 bar of daily resolution starts at 8 PM new york time of T-1. So to match the same start time
+            // we go back a 1 day + 4 hours. This is calculated by 'Time.GetStartTimeForTradeBars'
+            SetWarmup(TimeSpan.FromHours(24 + 4));
+        }
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 14915;
+    }
+}

Algorithm.CSharp/ContinuousFutureLimitIfTouchedOrderRegressionAlgorithm.cs

@@ -0,0 +1,137 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using System.Collections.Generic;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Continuous Futures Regression algorithm reproducing GH issue #6490 asserting limit if touched order works as expected
+    /// </summary>
+    public class ContinuousFutureLimitIfTouchedOrderRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private OrderTicket _ticket;
+        private Future _continuousContract;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 6);
+            SetEndDate(2013, 10, 10);
+
+            _continuousContract = AddFuture(Futures.Indices.SP500EMini,
+                dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
+                dataMappingMode: DataMappingMode.LastTradingDay
+            );
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice data)
+        {
+            if (_ticket == null)
+            {
+                _ticket = LimitIfTouchedOrder(_continuousContract.Mapped, -1, _continuousContract.Price, _continuousContract.Price);
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_ticket == null || _ticket.Status != OrderStatus.Filled)
+            {
+                throw new Exception("Order ticket was not placed or filled!");
+            }
+        }
+
+        /// <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 => 19876;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "1"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "-99.258%"},
+            {"Drawdown", "6.300%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "-6.129%"},
+            {"Sharpe Ratio", "-2.182"},
+            {"Probabilistic Sharpe Ratio", "5.175%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.976"},
+            {"Beta", "-0.022"},
+            {"Annual Standard Deviation", "0.449"},
+            {"Annual Variance", "0.202"},
+            {"Information Ratio", "-2.231"},
+            {"Tracking Error", "0.513"},
+            {"Treynor Ratio", "43.626"},
+            {"Total Fees", "$2.15"},
+            {"Estimated Strategy Capacity", "$2600000000.00"},
+            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
+            {"Fitness Score", "0.028"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "-1.662"},
+            {"Return Over Maximum Drawdown", "-18.253"},
+            {"Portfolio Turnover", "0.206"},
+            {"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", "f0e1235ff2d29030e374d966b3e225fa"}
+        };
+    }
+}

Algorithm.CSharp/ContinuousFutureRegressionAlgorithm.cs

@@ -148,6 +148,12 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 throw new Exception($"Unexpected symbol changed events: {_mappings.Count}, was expecting {expectedMappingCounts}");
             }
+
+            var securities = Securities.Values.Where(sec => !sec.IsTradable && !sec.Symbol.IsCanonical() && sec.Symbol.SecurityType == SecurityType.Future).ToList();
+            if (securities.Count != 1)
+            {
+                throw new Exception("We should have a non tradable future contract security!");
+            }
         }
 
         /// <summary>
@@ -163,7 +169,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 875590;
+        public long DataPoints => 284403;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -176,32 +182,32 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "1.21%"},
+            {"Average Win", "1.50%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "2.392%"},
+            {"Compounding Annual Return", "2.959%"},
             {"Drawdown", "1.600%"},
             {"Expectancy", "0"},
-            {"Net Profit", "1.199%"},
-            {"Sharpe Ratio", "0.775"},
-            {"Probabilistic Sharpe Ratio", "40.287%"},
+            {"Net Profit", "1.479%"},
+            {"Sharpe Ratio", "0.805"},
+            {"Probabilistic Sharpe Ratio", "42.183%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.006"},
-            {"Beta", "0.099"},
-            {"Annual Standard Deviation", "0.022"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-2.726"},
+            {"Alpha", "-0.005"},
+            {"Beta", "0.114"},
+            {"Annual Standard Deviation", "0.026"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-2.676"},
             {"Tracking Error", "0.076"},
-            {"Treynor Ratio", "0.169"},
-            {"Total Fees", "$5.55"},
-            {"Estimated Strategy Capacity", "$67000000.00"},
+            {"Treynor Ratio", "0.181"},
+            {"Total Fees", "$6.45"},
+            {"Estimated Strategy Capacity", "$180000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
             {"Fitness Score", "0.01"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "0.516"},
-            {"Return Over Maximum Drawdown", "1.935"},
+            {"Sortino Ratio", "0.32"},
+            {"Return Over Maximum Drawdown", "2.573"},
             {"Portfolio Turnover", "0.016"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -216,7 +222,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "8ad040c62ad255e4f9cd423364147e85"}
+            {"OrderListHash", "88e74055be58b3759f493b2c47e4c097"}
         };
     }
 }

Algorithm.CSharp/CryptoBaseCurrencyFeeRegressionAlgorithm.cs

@@ -73,12 +73,12 @@ namespace QuantConnect.Algorithm.CSharp
                     || filledEvent.FillQuantity != ticket.QuantityFilled
                     || (0.1m - filledEvent.OrderFee.Value.Amount) != ticket.QuantityFilled)
                 {
-                    throw new Exception($"Unexpected BaseCurrency porfoltio status. Event {filledEvent}. CashBook: {Portfolio.CashBook}. ");
+                    throw new Exception($"Unexpected BaseCurrency portfolio status. Event {filledEvent}. CashBook: {Portfolio.CashBook}. ");
                 }
 
                 if (Portfolio.CashBook[quoteCurrency].Amount != (initialQuoteCurrency - 0.1m * filledEvent.FillPrice))
                 {
-                    throw new Exception($"Unexpected QuoteCurrency porfoltio status. Event {filledEvent}. CashBook: {Portfolio.CashBook}. ");
+                    throw new Exception($"Unexpected QuoteCurrency portfolio status. Event {filledEvent}. CashBook: {Portfolio.CashBook}. ");
                 }
 
                 if (Securities[_symbol].Holdings.Quantity != (0.1m - filledEvent.OrderFee.Value.Amount))

Algorithm.CSharp/CustomDataBitcoinAlgorithm.cs

@@ -92,6 +92,16 @@ namespace QuantConnect.Algorithm.CSharp
             public decimal VolumeBTC = 0;
             public decimal VolumeUSD = 0;
 
+            /// <summary>
+            /// The end time of this data. Some data covers spans (trade bars)
+            /// and as such we want to know the entire time span covered
+            /// </summary>
+            /// <remarks>
+            /// This property is overriden to allow different values for Time and EndTime
+            /// if they are set in the Reader. In the base implementation EndTime equals Time
+            /// </remarks>
+            public override DateTime EndTime { get; set; }
+
             /// <summary>
             /// 1. DEFAULT CONSTRUCTOR: Custom data types need a default constructor.
             /// We search for a default constructor so please provide one here. It won't be used for data, just to generate the "Factory".

Algorithm.CSharp/CustomDataPropertiesRegressionAlgorithm.cs

@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 10489;
+        public long DataPoints => 10491;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -124,30 +124,30 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "157.498%"},
+            {"Compounding Annual Return", "155.211%"},
             {"Drawdown", "84.800%"},
             {"Expectancy", "0"},
-            {"Net Profit", "5319.081%"},
-            {"Sharpe Ratio", "2.086"},
-            {"Probabilistic Sharpe Ratio", "69.456%"},
+            {"Net Profit", "5123.242%"},
+            {"Sharpe Ratio", "2.067"},
+            {"Probabilistic Sharpe Ratio", "68.833%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "1.747"},
-            {"Beta", "0.047"},
-            {"Annual Standard Deviation", "0.84"},
-            {"Annual Variance", "0.706"},
-            {"Information Ratio", "1.922"},
+            {"Alpha", "1.732"},
+            {"Beta", "0.043"},
+            {"Annual Standard Deviation", "0.841"},
+            {"Annual Variance", "0.707"},
+            {"Information Ratio", "1.902"},
             {"Tracking Error", "0.848"},
-            {"Treynor Ratio", "37.47"},
+            {"Treynor Ratio", "40.467"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "BTC.Bitcoin 2S"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "2.269"},
-            {"Return Over Maximum Drawdown", "1.858"},
+            {"Sortino Ratio", "2.236"},
+            {"Return Over Maximum Drawdown", "1.83"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -190,6 +190,16 @@ namespace QuantConnect.Algorithm.CSharp
             public decimal VolumeBTC = 0;
             public decimal VolumeUSD = 0;
 
+            /// <summary>
+            /// The end time of this data. Some data covers spans (trade bars)
+            /// and as such we want to know the entire time span covered
+            /// </summary>
+            /// <remarks>
+            /// This property is overriden to allow different values for Time and EndTime
+            /// if they are set in the Reader. In the base implementation EndTime equals Time
+            /// </remarks>
+            public override DateTime EndTime { get; set; }
+
             /// <summary>
             /// 1. DEFAULT CONSTRUCTOR: Custom data types need a default constructor.
             /// We search for a default constructor so please provide one here. It won't be used for data, just to generate the "Factory".

Algorithm.CSharp/CustomDataRegressionAlgorithm.cs

@@ -110,7 +110,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 8942;
+        public long DataPoints => 8943;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -125,30 +125,30 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "157.655%"},
+            {"Compounding Annual Return", "155.365%"},
             {"Drawdown", "84.800%"},
             {"Expectancy", "0"},
-            {"Net Profit", "5319.007%"},
-            {"Sharpe Ratio", "2.123"},
-            {"Probabilistic Sharpe Ratio", "70.581%"},
+            {"Net Profit", "5123.170%"},
+            {"Sharpe Ratio", "2.103"},
+            {"Probabilistic Sharpe Ratio", "69.967%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "1.776"},
-            {"Beta", "0.059"},
+            {"Alpha", "1.76"},
+            {"Beta", "0.055"},
             {"Annual Standard Deviation", "0.84"},
             {"Annual Variance", "0.706"},
-            {"Information Ratio", "1.962"},
-            {"Tracking Error", "0.847"},
-            {"Treynor Ratio", "30.455"},
+            {"Information Ratio", "1.942"},
+            {"Tracking Error", "0.848"},
+            {"Treynor Ratio", "32.317"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "BTC.Bitcoin 2S"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "2.271"},
-            {"Return Over Maximum Drawdown", "1.86"},
+            {"Sortino Ratio", "2.238"},
+            {"Return Over Maximum Drawdown", "1.832"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -191,6 +191,16 @@ namespace QuantConnect.Algorithm.CSharp
             public decimal VolumeBTC = 0;
             public decimal VolumeUSD = 0;
 
+            /// <summary>
+            /// The end time of this data. Some data covers spans (trade bars)
+            /// and as such we want to know the entire time span covered
+            /// </summary>
+            /// <remarks>
+            /// This property is overriden to allow different values for Time and EndTime
+            /// if they are set in the Reader. In the base implementation EndTime equals Time
+            /// </remarks>
+            public override DateTime EndTime { get; set; }
+
             /// <summary>
             /// 1. DEFAULT CONSTRUCTOR: Custom data types need a default constructor.
             /// We search for a default constructor so please provide one here. It won't be used for data, just to generate the "Factory".

Algorithm.CSharp/CustomUniverseSelectionModelRegressionAlgorithm.cs

@@ -0,0 +1,144 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Data;
+using QuantConnect.Data.Fundamental;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm showing how to implement a custom universe selection model and asserting it's behavior
+    /// </summary>
+    public class CustomUniverseSelectionModelRegressionAlgorithm : 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(2014, 3, 24);
+            SetEndDate(2014, 4, 7);
+
+            UniverseSettings.Resolution = Resolution.Daily;
+            SetUniverseSelection(new CustomUniverseSelectionModel());
+        }
+
+        public override void OnData(Slice data)
+        {
+            if (!Portfolio.Invested)
+            {
+                foreach (var kvp in ActiveSecurities)
+                {
+                    SetHoldings(kvp.Key, 0.1);
+                }
+            }
+        }
+
+        private class CustomUniverseSelectionModel : FundamentalUniverseSelectionModel
+        {
+            private bool _selected;
+            public CustomUniverseSelectionModel(): base(true, null)
+            {
+            }
+            public override IEnumerable<Symbol> SelectCoarse(QCAlgorithm algorithm, IEnumerable<CoarseFundamental> coarse)
+            {
+                return new[] { QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA) };
+            }
+            public override IEnumerable<Symbol> SelectFine(QCAlgorithm algorithm, IEnumerable<FineFundamental> fine)
+            {
+                if (!_selected)
+                {
+                    _selected = true;
+                    return fine.Select(x => x.Symbol);
+                }
+                return Data.UniverseSelection.Universe.Unchanged;
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 7208;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "1"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "-7.765%"},
+            {"Drawdown", "0.400%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "-0.332%"},
+            {"Sharpe Ratio", "-5.288"},
+            {"Probabilistic Sharpe Ratio", "5.408%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.049"},
+            {"Beta", "0.1"},
+            {"Annual Standard Deviation", "0.011"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0.413"},
+            {"Tracking Error", "0.087"},
+            {"Treynor Ratio", "-0.578"},
+            {"Total Fees", "$2.89"},
+            {"Estimated Strategy Capacity", "$1600000000.00"},
+            {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
+            {"Fitness Score", "0"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "-8.448"},
+            {"Return Over Maximum Drawdown", "-19.517"},
+            {"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", "9b40745cd4c47eb3f442071c2a841821"}
+        };
+    }
+}

Algorithm.CSharp/DelistedFutureLiquidateDailyRegressionAlgorithm.cs

@@ -0,0 +1,82 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm which reproduces GH issue 4446, in the case of daily resolution.
+    /// </summary>
+    public class DelistedFutureLiquidateDailyRegressionAlgorithm : DelistedFutureLiquidateRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Daily;
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 1450;
+
+        /// <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", "7.78%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "38.033%"},
+            {"Drawdown", "0.200%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "7.779%"},
+            {"Sharpe Ratio", "3.2"},
+            {"Probabilistic Sharpe Ratio", "99.459%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.149"},
+            {"Beta", "0.271"},
+            {"Annual Standard Deviation", "0.08"},
+            {"Annual Variance", "0.006"},
+            {"Information Ratio", "-1.446"},
+            {"Tracking Error", "0.098"},
+            {"Treynor Ratio", "0.946"},
+            {"Total Fees", "$2.15"},
+            {"Estimated Strategy Capacity", "$60000000000.00"},
+            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
+            {"Fitness Score", "0.019"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "28.065"},
+            {"Return Over Maximum Drawdown", "246.484"},
+            {"Portfolio Turnover", "0.019"},
+            {"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", "bbd8ee011b21ef33f4b15b0509c96bbb"}
+        };
+    }
+}

Algorithm.CSharp/DelistedFutureLiquidateRegressionAlgorithm.cs

@@ -30,6 +30,7 @@ namespace QuantConnect.Algorithm.CSharp
     public class DelistedFutureLiquidateRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
         private Symbol _contractSymbol;
+        protected virtual Resolution Resolution => Resolution.Minute;
 
         /// <summary>
         /// Initialize your algorithm and add desired assets.
@@ -39,7 +40,7 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2013, 10, 08);
             SetEndDate(2013, 12, 30);
 
-            var futureSP500 = AddFuture(Futures.Indices.SP500EMini);
+            var futureSP500 = AddFuture(Futures.Indices.SP500EMini, Resolution);
             futureSP500.SetFilter(0, 182);
         }
 
@@ -91,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 1224778;
+        public virtual long DataPoints => 398985;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -101,35 +102,35 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "2"},
-            {"Average Win", "1.64%"},
+            {"Average Win", "1.48%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "7.329%"},
+            {"Compounding Annual Return", "6.608%"},
             {"Drawdown", "1.300%"},
             {"Expectancy", "0"},
-            {"Net Profit", "1.642%"},
-            {"Sharpe Ratio", "2.36"},
-            {"Probabilistic Sharpe Ratio", "94.555%"},
+            {"Net Profit", "1.479%"},
+            {"Sharpe Ratio", "2.544"},
+            {"Probabilistic Sharpe Ratio", "96.625%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.006"},
-            {"Beta", "0.158"},
-            {"Annual Standard Deviation", "0.03"},
+            {"Alpha", "0.014"},
+            {"Beta", "0.175"},
+            {"Annual Standard Deviation", "0.033"},
             {"Annual Variance", "0.001"},
-            {"Information Ratio", "-4.44"},
+            {"Information Ratio", "-4.246"},
             {"Tracking Error", "0.075"},
-            {"Treynor Ratio", "0.441"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$170000000.00"},
+            {"Treynor Ratio", "0.483"},
+            {"Total Fees", "$2.15"},
+            {"Estimated Strategy Capacity", "$1800000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Fitness Score", "0.019"},
+            {"Fitness Score", "0.022"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "1.369"},
-            {"Return Over Maximum Drawdown", "9.749"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "5.652"},
             {"Portfolio Turnover", "0.023"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -144,7 +145,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "4c5e32aedcd5bb67642d1629628fe615"}
+            {"OrderListHash", "d93bc642994899d48dd9e00232d444bc"}
         };
     }
 }

Algorithm.CSharp/DelistingFutureOptionDailyRegressionAlgorithm.cs

@@ -0,0 +1,83 @@
+/*
+ * 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.Orders;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm reproducing issue #5160 where delisting order would be cancelled because it was placed at the market close on the delisting day,
+    /// in the case of daily resolution.
+    /// </summary>
+    public class DelistingFutureOptionDailyRegressionAlgorithm : DelistingFutureOptionRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Daily;
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 13223;
+
+        /// <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", "16"},
+            {"Average Win", "0.01%"},
+            {"Average Loss", "-0.02%"},
+            {"Compounding Annual Return", "-0.111%"},
+            {"Drawdown", "0.100%"},
+            {"Expectancy", "-0.678"},
+            {"Net Profit", "-0.111%"},
+            {"Sharpe Ratio", "-0.951"},
+            {"Probabilistic Sharpe Ratio", "0.000%"},
+            {"Loss Rate", "80%"},
+            {"Win Rate", "20%"},
+            {"Profit-Loss Ratio", "0.61"},
+            {"Alpha", "-0.001"},
+            {"Beta", "-0.001"},
+            {"Annual Standard Deviation", "0.001"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.075"},
+            {"Tracking Error", "0.107"},
+            {"Treynor Ratio", "1.338"},
+            {"Total Fees", "$19.76"},
+            {"Estimated Strategy Capacity", "$2300000.00"},
+            {"Lowest Capacity Asset", "DC V5E8PHPRCHJ8|DC V5E8P9SH0U0X"},
+            {"Fitness Score", "0"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "-0.126"},
+            {"Return Over Maximum Drawdown", "-0.995"},
+            {"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", "2152bd1d4f1770068595a4c3bc8585ee"}
+        };
+    }
+}

Algorithm.CSharp/DelistingFutureOptionRegressionAlgorithm.cs

@@ -19,6 +19,7 @@ using QuantConnect.Interfaces;
 using QuantConnect.Securities;
 using System.Collections.Generic;
 using System.Linq;
+using QuantConnect.Orders;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -27,6 +28,7 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class DelistingFutureOptionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
+        protected virtual Resolution Resolution => Resolution.Minute;
         private bool _traded;
         private int _lastMonth;
 
@@ -36,11 +38,15 @@ namespace QuantConnect.Algorithm.CSharp
             SetEndDate(2013, 1, 1);
             SetCash(10000000);
 
-            var dc = AddFuture(Futures.Dairy.ClassIIIMilk, Resolution.Minute, Market.CME);
+            var dc = AddFuture(Futures.Dairy.ClassIIIMilk, Resolution, Market.CME);
             dc.SetFilter(1, 120);
 
             AddFutureOption(dc.Symbol, universe => universe.Strikes(-2, 2));
             _lastMonth = -1;
+
+            // This is required to prevent the algorithm from automatically delisting the underlying. Without this, future options will be subscribed
+            // with resolution default to Minute insted of this.Resolution. This could be replaced after GH issue #6491 is implemented.
+            UniverseSettings.Resolution = Resolution;
         }
 
         public override void OnData(Slice data)
@@ -100,8 +106,8 @@ namespace QuantConnect.Algorithm.CSharp
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
-        /// </summary>
-        public long DataPoints => 15228955;
+        /// </summary>0
+        public virtual long DataPoints => 5117455;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -111,7 +117,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "16"},
             {"Average Win", "0.01%"},
@@ -132,14 +138,14 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "-1.075"},
             {"Tracking Error", "0.107"},
             {"Treynor Ratio", "1.353"},
-            {"Total Fees", "$14.80"},
-            {"Estimated Strategy Capacity", "$860000000.00"},
-            {"Lowest Capacity Asset", "DC V5E8P9SH0U0X"},
+            {"Total Fees", "$19.76"},
+            {"Estimated Strategy Capacity", "$1300000000.00"},
+            {"Lowest Capacity Asset", "DC V5E8PHPRCHJ8|DC V5E8P9SH0U0X"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.128"},
-            {"Return Over Maximum Drawdown", "-0.995"},
+            {"Sortino Ratio", "-0.129"},
+            {"Return Over Maximum Drawdown", "-0.997"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},

Algorithm.CSharp/DisplacedMovingAverageRibbon.cs

@@ -64,7 +64,7 @@ namespace QuantConnect.Algorithm.CSharp
                 // define an indicator that takes the output of the sma and pipes it into our delay indicator
                 var delayedSma = delay.Of(sma);
 
-                // register our new 'delayedSma' for automaic updates on a daily resolution
+                // register our new 'delayedSma' for automatic updates on a daily resolution
                 RegisterIndicator(_spy, delayedSma, Resolution.Daily, data => data.Value);
 
                 return delayedSma;

Algorithm.CSharp/DropboxBaseDataUniverseSelectionAlgorithm.cs

@@ -23,7 +23,7 @@ using QuantConnect.Interfaces;
 namespace QuantConnect.Algorithm.CSharp
 {
     /// <summary>
-    /// In this algortihm we show how you can easily use the universe selection feature to fetch symbols
+    /// In this algorithm we show how you can easily use the universe selection feature to fetch symbols
     /// to be traded using the BaseData custom data system in combination with the AddUniverse{T} method.
     /// AddUniverse{T} requires a function that will return the symbols to be traded.
     /// </summary>

Algorithm.CSharp/DropboxUniverseSelectionAlgorithm.cs

@@ -24,7 +24,7 @@ using QuantConnect.Interfaces;
 namespace QuantConnect.Algorithm.CSharp
 {
     /// <summary>
-    /// In this algortihm we show how you can easily use the universe selection feature to fetch symbols
+    /// In this algorithm we show how you can easily use the universe selection feature to fetch symbols
     /// to be traded using the AddUniverse method. This method accepts a function that will return the
     /// desired current set of symbols. Return Universe.Unchanged if no universe changes should be made
     /// </summary>

Algorithm.CSharp/ETFConstituentsFrameworkAlgorithm.cs

@@ -0,0 +1,122 @@
+/*
+ * 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.Portfolio;
+using QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Example algorithm of using ETFConstituentsUniverseSelectionModel
+    /// </summary>
+    public class ETFConstituentsFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2020, 12, 1);
+            SetEndDate(2020, 12, 7);
+            SetCash(100000);
+
+            UniverseSettings.Resolution = Resolution.Daily;
+            var symbol = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
+            AddUniverseSelection(new ETFConstituentsUniverseSelectionModel(symbol, UniverseSettings, ETFConstituentsFilter));
+
+            AddAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(1)));
+
+            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
+        }
+
+        private IEnumerable<Symbol> ETFConstituentsFilter(IEnumerable<ETFConstituentData> constituents)
+        {
+            // Get the 10 securities with the largest weight in the index
+            return constituents.OrderByDescending(c => c.Weight).Take(8).Select(c => c.Symbol);
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 565;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "8"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0.00%"},
+            {"Compounding Annual Return", "60.921%"},
+            {"Drawdown", "0.900%"},
+            {"Expectancy", "-1"},
+            {"Net Profit", "0.917%"},
+            {"Sharpe Ratio", "4.712"},
+            {"Probabilistic Sharpe Ratio", "67.398%"},
+            {"Loss Rate", "100%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.62"},
+            {"Beta", "-0.348"},
+            {"Annual Standard Deviation", "0.1"},
+            {"Annual Variance", "0.01"},
+            {"Information Ratio", "0.399"},
+            {"Tracking Error", "0.127"},
+            {"Treynor Ratio", "-1.361"},
+            {"Total Fees", "$8.02"},
+            {"Estimated Strategy Capacity", "$350000000.00"},
+            {"Lowest Capacity Asset", "GOOCV VP83T1ZUHROL"},
+            {"Fitness Score", "0.159"},
+            {"Kelly Criterion Estimate", "4.164"},
+            {"Kelly Criterion Probability Value", "0.444"},
+            {"Sortino Ratio", "19.028"},
+            {"Return Over Maximum Drawdown", "70.879"},
+            {"Portfolio Turnover", "0.16"},
+            {"Total Insights Generated", "20"},
+            {"Total Insights Closed", "16"},
+            {"Total Insights Analysis Completed", "16"},
+            {"Long Insight Count", "20"},
+            {"Short Insight Count", "0"},
+            {"Long/Short Ratio", "100%"},
+            {"Estimated Monthly Alpha Value", "$-875816.5"},
+            {"Total Accumulated Estimated Alpha Value", "$-210439.3"},
+            {"Mean Population Estimated Insight Value", "$-13152.45"},
+            {"Mean Population Direction", "37.5%"},
+            {"Mean Population Magnitude", "0%"},
+            {"Rolling Averaged Population Direction", "82.1399%"},
+            {"Rolling Averaged Population Magnitude", "0%"},
+            {"OrderListHash", "018dc981190b94fdbae00e75b1bbe2c2"}
+        };
+    }
+}

Algorithm.CSharp/EqualWeightingPortfolioConstructionModelFutureRegressionAlgorithm.cs

@@ -130,7 +130,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 208361;
+        public long DataPoints => 72192;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -142,48 +142,48 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "7"},
-            {"Average Win", "0%"},
-            {"Average Loss", "-1.40%"},
-            {"Compounding Annual Return", "-99.829%"},
-            {"Drawdown", "29.500%"},
-            {"Expectancy", "-1"},
-            {"Net Profit", "-7.888%"},
-            {"Sharpe Ratio", "-0.593"},
-            {"Probabilistic Sharpe Ratio", "34.346%"},
-            {"Loss Rate", "100%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-15.391"},
-            {"Beta", "7.259"},
-            {"Annual Standard Deviation", "1.679"},
-            {"Annual Variance", "2.818"},
-            {"Information Ratio", "-2.032"},
-            {"Tracking Error", "1.466"},
-            {"Treynor Ratio", "-0.137"},
-            {"Total Fees", "$40.70"},
-            {"Estimated Strategy Capacity", "$4000000.00"},
+            {"Total Trades", "8"},
+            {"Average Win", "0.69%"},
+            {"Average Loss", "-2.47%"},
+            {"Compounding Annual Return", "-99.966%"},
+            {"Drawdown", "28.600%"},
+            {"Expectancy", "-0.680"},
+            {"Net Profit", "-9.786%"},
+            {"Sharpe Ratio", "-0.598"},
+            {"Probabilistic Sharpe Ratio", "30.082%"},
+            {"Loss Rate", "75%"},
+            {"Win Rate", "25%"},
+            {"Profit-Loss Ratio", "0.28"},
+            {"Alpha", "-15.867"},
+            {"Beta", "7.498"},
+            {"Annual Standard Deviation", "1.669"},
+            {"Annual Variance", "2.787"},
+            {"Information Ratio", "-2.061"},
+            {"Tracking Error", "1.447"},
+            {"Treynor Ratio", "-0.133"},
+            {"Total Fees", "$52.01"},
+            {"Estimated Strategy Capacity", "$1800000.00"},
             {"Lowest Capacity Asset", "GC VL5E74HP3EE5"},
-            {"Fitness Score", "0.072"},
-            {"Kelly Criterion Estimate", "-9.366"},
-            {"Kelly Criterion Probability Value", "0.607"},
-            {"Sortino Ratio", "-5.172"},
-            {"Return Over Maximum Drawdown", "-5.25"},
-            {"Portfolio Turnover", "4.987"},
+            {"Fitness Score", "0.213"},
+            {"Kelly Criterion Estimate", "-24.978"},
+            {"Kelly Criterion Probability Value", "0.773"},
+            {"Sortino Ratio", "-0.966"},
+            {"Return Over Maximum Drawdown", "-5.15"},
+            {"Portfolio Turnover", "5.36"},
             {"Total Insights Generated", "10"},
             {"Total Insights Closed", "8"},
             {"Total Insights Analysis Completed", "8"},
             {"Long Insight Count", "10"},
             {"Short Insight Count", "0"},
             {"Long/Short Ratio", "100%"},
-            {"Estimated Monthly Alpha Value", "$-78.89231"},
-            {"Total Accumulated Estimated Alpha Value", "$-12.82"},
-            {"Mean Population Estimated Insight Value", "$-1.6025"},
-            {"Mean Population Direction", "25%"},
+            {"Estimated Monthly Alpha Value", "$13142.3631"},
+            {"Total Accumulated Estimated Alpha Value", "$2135.634"},
+            {"Mean Population Estimated Insight Value", "$266.9542"},
+            {"Mean Population Direction", "50%"},
             {"Mean Population Magnitude", "0%"},
-            {"Rolling Averaged Population Direction", "25.058%"},
+            {"Rolling Averaged Population Direction", "50.0384%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "874fc945335aa8d93f2e3734641f9890"}
+            {"OrderListHash", "525af9e5e2ca7ebdee6c9deeec326a3e"}
         };
     }
 }

Algorithm.CSharp/FutureContractsExtendedMarketHoursRegressionAlgorithm.cs

@@ -0,0 +1,162 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using System.Linq;
+using System.Collections.Generic;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This regression algorithm asserts that futures have data at extended market hours when this is enabled.
+    /// </summary>
+    public class FutureContractsExtendedMarketHoursRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Future _es;
+        private Future _gc;
+        private bool _esRanOnRegularHours;
+        private bool _esRanOnExtendedHours;
+        private bool _gcRanOnRegularHours;
+        private bool _gcRanOnExtendedHours;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 6);
+            SetEndDate(2013, 10, 11);
+
+            var esFutureSymbol = QuantConnect.Symbol.CreateFuture(Futures.Indices.SP500EMini, Market.CME, new DateTime(2013, 12, 20));
+            _es = AddFutureContract(esFutureSymbol, Resolution.Hour, fillDataForward: true, extendedMarketHours: true);
+
+            var gcFutureSymbol = QuantConnect.Symbol.CreateFuture(Futures.Metals.Gold, Market.COMEX, new DateTime(2013, 10, 29));
+            _gc = AddFutureContract(gcFutureSymbol, Resolution.Hour, fillDataForward: true, extendedMarketHours: false);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            var sliceSymbols = new HashSet<Symbol>(slice.Keys);
+            sliceSymbols.UnionWith(slice.Bars.Keys);
+            sliceSymbols.UnionWith(slice.Ticks.Keys);
+            sliceSymbols.UnionWith(slice.QuoteBars.Keys);
+
+            var esIsInRegularHours = _es.Exchange.Hours.IsOpen(Time, false);
+            var esIsInExtendedHours = !esIsInRegularHours && _es.Exchange.Hours.IsOpen(Time, true);
+            var sliceHasESData = sliceSymbols.Any(symbol => symbol == _es.Symbol || symbol.Canonical == _es.Symbol);
+            _esRanOnRegularHours |= esIsInRegularHours && sliceHasESData;
+            _esRanOnExtendedHours |= esIsInExtendedHours && sliceHasESData;
+
+            var gcIsInRegularHours = _gc.Exchange.Hours.IsOpen(Time, false);
+            var gcIsInExtendedHours = !gcIsInRegularHours && _gc.Exchange.Hours.IsOpen(Time, true);
+            var sliceHasGCData = sliceSymbols.Any(symbol => symbol == _gc.Symbol || symbol.Canonical == _gc.Symbol);
+            _gcRanOnRegularHours |= gcIsInRegularHours && sliceHasGCData;
+            _gcRanOnExtendedHours |= gcIsInExtendedHours && sliceHasGCData;
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_esRanOnRegularHours)
+            {
+                throw new Exception($"Algorithm should have run on regular hours for {_es.Symbol} future, which enabled extended market hours");
+            }
+
+            if (!_esRanOnExtendedHours)
+            {
+                throw new Exception($"Algorithm should have run on extended hours for {_es.Symbol} future, which enabled extended market hours");
+            }
+
+            if (!_gcRanOnRegularHours)
+            {
+                throw new Exception($"Algorithm should have run on regular hours for {_gc.Symbol} future, which did not enable extended market hours");
+            }
+
+            if (_gcRanOnExtendedHours)
+            {
+                throw new Exception($"Algorithm should have not run on extended hours for {_gc.Symbol} future, which did not enable extended market hours");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 525;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-2.564"},
+            {"Tracking Error", "0.214"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Fitness Score", "0"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
+            {"Portfolio Turnover", "0"},
+            {"Total Insights Generated", "0"},
+            {"Total Insights Closed", "0"},
+            {"Total Insights Analysis Completed", "0"},
+            {"Long Insight Count", "0"},
+            {"Short Insight Count", "0"},
+            {"Long/Short Ratio", "100%"},
+            {"Estimated Monthly Alpha Value", "$0"},
+            {"Total Accumulated Estimated Alpha Value", "$0"},
+            {"Mean Population Estimated Insight Value", "$0"},
+            {"Mean Population Direction", "0%"},
+            {"Mean Population Magnitude", "0%"},
+            {"Rolling Averaged Population Direction", "0%"},
+            {"Rolling Averaged Population Magnitude", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/FutureMarketOpenAndCloseRegressionAlgorithm.cs

@@ -25,39 +25,43 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class FutureMarketOpenAndCloseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private static List<DateTime> _afterMarketOpen = new List<DateTime>() {
-            new DateTime(2022, 02, 01, 16, 30, 0),
-            new DateTime(2022, 02, 02, 16, 30, 0),
-            new DateTime(2022, 02, 03, 16, 30, 0),
-            new DateTime(2022, 02, 04, 16, 30, 0),
-            new DateTime(2022, 02, 06, 18, 0, 0),
-            new DateTime(2022, 02, 07, 16, 30, 0),
-            new DateTime(2022, 02, 08, 16, 30, 0)
+        protected virtual bool ExtendedMarketHours => false;
+
+        protected virtual List<DateTime> AfterMarketOpen => new List<DateTime>() {
+            new DateTime(2022, 02, 01, 9, 30, 0),
+            new DateTime(2022, 02, 02, 9, 30, 0),
+            new DateTime(2022, 02, 03, 9, 30, 0),
+            new DateTime(2022, 02, 04, 9, 30, 0),
+            new DateTime(2022, 02, 07, 9, 30, 0),
+            new DateTime(2022, 02, 08, 9, 30, 0)
         };
-        private static List<DateTime> _beforeMarketClose = new List<DateTime>()
+        protected virtual List<DateTime> BeforeMarketClose => new List<DateTime>()
         {
-            new DateTime(2022, 02, 01, 16, 15, 0),
-            new DateTime(2022, 02, 02, 16, 15, 0),
-            new DateTime(2022, 02, 03, 16, 15, 0),
-            new DateTime(2022, 02, 04, 16, 15, 0),
-            new DateTime(2022, 02, 07, 16, 15, 0),
-            new DateTime(2022, 02, 08, 16, 15, 0)
+            new DateTime(2022, 02, 01, 17, 0, 0),
+            new DateTime(2022, 02, 02, 17, 0, 0),
+            new DateTime(2022, 02, 03, 17, 0, 0),
+            new DateTime(2022, 02, 04, 17, 0, 0),
+            new DateTime(2022, 02, 07, 17, 0, 0),
+            new DateTime(2022, 02, 08, 17, 0, 0)
         };
-        private Queue<DateTime> _afterMarketOpenQueue = new Queue<DateTime>(_afterMarketOpen);
-        private Queue<DateTime> _beforeMarketCloseQueue = new Queue<DateTime>(_beforeMarketClose);
+        private Queue<DateTime> _afterMarketOpenQueue;
+        private Queue<DateTime> _beforeMarketCloseQueue;
 
         public override void Initialize()
         {
             SetStartDate(2022, 02, 01);
             SetEndDate(2022, 02, 08);
-            var esFuture = AddFuture("ES").Symbol;
+            var esFuture = AddFuture("ES", extendedMarketHours: ExtendedMarketHours).Symbol;
+
+            _afterMarketOpenQueue = new Queue<DateTime>(AfterMarketOpen);
+            _beforeMarketCloseQueue = new Queue<DateTime>(BeforeMarketClose);
 
             Schedule.On(DateRules.EveryDay(esFuture),
-                TimeRules.AfterMarketOpen(esFuture),
+                TimeRules.AfterMarketOpen(esFuture, extendedMarketOpen: ExtendedMarketHours),
                 EveryDayAfterMarketOpen);
 
             Schedule.On(DateRules.EveryDay(esFuture),
-                TimeRules.BeforeMarketClose(esFuture),
+                TimeRules.BeforeMarketClose(esFuture, extendedMarketClose: ExtendedMarketHours),
                 EveryDayBeforeMarketClose);
         }
 
@@ -91,12 +95,12 @@ 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 virtual Language[] Languages { get; } = { Language.CSharp};
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 7;
+        public virtual long DataPoints => 7;
 
         /// </summary>
         /// Data Points count of the algorithm history
@@ -106,7 +110,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "0"},
             {"Average Win", "0%"},

Algorithm.CSharp/FutureMarketOpenAndCloseWithExtendedMarketRegressionAlgorithm.cs

@@ -0,0 +1,106 @@
+/*
+ * 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.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm to check we are getting the correct market open and close times when extended market hours are used
+    /// </summary>
+    public class FutureMarketOpenAndCloseWithExtendedMarketRegressionAlgorithm : FutureMarketOpenAndCloseRegressionAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+        protected override List<DateTime> AfterMarketOpen => new List<DateTime>() {
+            new DateTime(2022, 02, 01, 18, 0, 0), // Tuesday
+            new DateTime(2022, 02, 02, 18, 0, 0),
+            new DateTime(2022, 02, 03, 18, 0, 0),
+            new DateTime(2022, 02, 06, 18, 0, 0),
+            new DateTime(2022, 02, 07, 18, 0, 0),
+            new DateTime(2022, 02, 08, 18, 0, 0)
+        };
+        protected override List<DateTime> BeforeMarketClose => new List<DateTime>()
+        {
+            new DateTime(2022, 02, 01, 17, 0, 0),
+            new DateTime(2022, 02, 02, 17, 0, 0),
+            new DateTime(2022, 02, 03, 17, 0, 0),
+            new DateTime(2022, 02, 04, 17, 0, 0),
+            new DateTime(2022, 02, 07, 17, 0, 0),
+            new DateTime(2022, 02, 08, 17, 0, 0)
+        };
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public override Language[] Languages { get; } = { Language.CSharp};
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 7;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"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", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/FutureMarketOpenConsolidatorRegressionAlgorithm.cs

@@ -27,44 +27,65 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class FutureMarketOpenConsolidatorRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private static List<DateTime> _expectedOpens = new List<DateTime>(){
-            new DateTime(2013, 10, 06, 18, 00, 0),
-            new DateTime(2013, 10, 07, 16, 30, 0),
-            new DateTime(2013, 10, 08, 16, 30, 0),
-            new DateTime(2013, 10, 09, 16, 30, 0),
-            new DateTime(2013, 10, 10, 16, 30, 0),
-            new DateTime(2013, 10, 11, 16, 30, 0),
-            new DateTime(2013, 10, 13, 18, 00, 0),
+        protected virtual bool ExtendedMarketHours => false;
+        protected virtual List<DateTime> ExpectedOpens => new List<DateTime>()
+        {
+            new DateTime(2013, 10, 07, 9, 30, 0),
+            new DateTime(2013, 10, 08, 9, 30, 0),
+            new DateTime(2013, 10, 09, 9, 30, 0),
+            new DateTime(2013, 10, 10, 9, 30, 0),
+            new DateTime(2013, 10, 11, 9, 30, 0),
+            new DateTime(2013, 10, 14, 9, 30, 0),
+            new DateTime(2013, 10, 14, 9, 30, 0),
         };
-        private static List<DateTime> _expectedCloses = new List<DateTime>(){
-            new DateTime(2013, 10, 07, 16, 15, 0),
-            new DateTime(2013, 10, 08, 16, 15, 0),
-            new DateTime(2013, 10, 09, 16, 15, 0),
-            new DateTime(2013, 10, 10, 16, 15, 0),
-            new DateTime(2013, 10, 11, 16, 15, 0),
-            new DateTime(2013, 10, 14, 16, 15, 0),
-            new DateTime(2013, 10, 14, 16, 15, 0),
+        protected virtual List<DateTime> ExpectedCloses => new List<DateTime>()
+        {
+            new DateTime(2013, 10, 07, 17, 0, 0),
+            new DateTime(2013, 10, 08, 17, 0, 0),
+            new DateTime(2013, 10, 09, 17, 0, 0),
+            new DateTime(2013, 10, 10, 17, 0, 0),
+            new DateTime(2013, 10, 11, 17, 0, 0),
+            new DateTime(2013, 10, 14, 17, 0, 0),
+            new DateTime(2013, 10, 14, 17, 0, 0),
         };
 
-        private Queue<DateTime> _expectedOpensQueue = new Queue<DateTime>(_expectedOpens);
-        private Queue<DateTime> _expectedClosesQueue = new Queue<DateTime>(_expectedCloses);
+        private Queue<DateTime> _expectedOpensQueue;
+        private Queue<DateTime> _expectedClosesQueue;
 
         public override void Initialize()
         {
             SetStartDate(2013, 10, 06);
             SetEndDate(2013, 10, 14);
 
-            var es = AddSecurity(SecurityType.Future, "ES");
+            var es = AddSecurity(SecurityType.Future, "ES", extendedMarketHours: ExtendedMarketHours);
+
+            _expectedOpensQueue = new Queue<DateTime>(ExpectedOpens);
+            _expectedClosesQueue = new Queue<DateTime>(ExpectedCloses);
 
             Consolidate<BaseData>(es.Symbol, dataTime =>
             {
-                var start = es.Exchange.Hours.GetPreviousMarketOpen(dataTime, false);
-                var end = es.Exchange.Hours.GetNextMarketClose(start, false);
+                var start = es.Exchange.Hours.GetPreviousMarketOpen(dataTime, ExtendedMarketHours);
+                var end = es.Exchange.Hours.GetNextMarketClose(start, ExtendedMarketHours);
 
-                // market might open at 16:30 and close again at 17:00 but we are not interested in using the close so we skip it here
-                while (end.Date == start.Date)
+                if (ExtendedMarketHours)
                 {
-                    end = es.Exchange.Hours.GetNextMarketClose(end, false);
+                    // market might open at 16:30 and close again at 17:00 but we are not interested in using the close so we skip it here
+                    while (end.Date == start.Date)
+                    {
+                        end = es.Exchange.Hours.GetNextMarketClose(end, ExtendedMarketHours);
+                    }
+                } else
+                {
+                    // Let's not consider regular market gaps like when market closes at 16:15 and opens again at 16:30
+                    while (true)
+                    {
+                        var potentialEnd = es.Exchange.Hours.GetNextMarketClose(end, ExtendedMarketHours);
+                        if (potentialEnd.Date != end.Date)
+                        {
+                            break;
+                        }
+                        end = potentialEnd;
+                    }
                 }
 
                 var period = end - start;
@@ -92,12 +113,12 @@ 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 virtual Language[] Languages { get; } = { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 94112;
+        public virtual long DataPoints => 29802;
 
         /// </summary>
         /// Data Points count of the algorithm history
@@ -107,7 +128,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "0"},
             {"Average Win", "0%"},

Algorithm.CSharp/FutureMarketOpenConsolidatorWithExtendedMarketRegressionAlgorithm.cs

@@ -0,0 +1,106 @@
+/*
+ * 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.Consolidators;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm using a consolidator to check GetNextMarketClose() and GetNextMarketOpen()
+    /// are returning the correct market close and open times, when extended market hours are used
+    /// </summary>
+    public class FutureMarketOpenConsolidatorWithExtendedMarketRegressionAlgorithm : FutureMarketOpenConsolidatorRegressionAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+        protected override List<DateTime> ExpectedOpens => new List<DateTime>(){
+            new DateTime(2013, 10, 06, 18, 0, 0), // Sunday
+            new DateTime(2013, 10, 07, 18, 0, 0),
+            new DateTime(2013, 10, 08, 18, 0, 0),
+            new DateTime(2013, 10, 09, 18, 0, 0),
+            new DateTime(2013, 10, 10, 18, 0, 0),
+            new DateTime(2013, 10, 13, 18, 0, 0),
+        };
+        protected override List<DateTime> ExpectedCloses => new List<DateTime>(){
+            new DateTime(2013, 10, 07, 17, 0, 0),
+            new DateTime(2013, 10, 08, 17, 0, 0),
+            new DateTime(2013, 10, 09, 17, 0, 0),
+            new DateTime(2013, 10, 10, 17, 0, 0),
+            new DateTime(2013, 10, 11, 17, 0, 0),
+            new DateTime(2013, 10, 14, 17, 0, 0),
+        };
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public override Language[] Languages { get; } = { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 95102;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-3.108"},
+            {"Tracking Error", "0.163"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Fitness Score", "0"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
+            {"Portfolio Turnover", "0"},
+            {"Total Insights Generated", "0"},
+            {"Total Insights Closed", "0"},
+            {"Total Insights Analysis Completed", "0"},
+            {"Long Insight Count", "0"},
+            {"Short Insight Count", "0"},
+            {"Long/Short Ratio", "100%"},
+            {"Estimated Monthly Alpha Value", "$0"},
+            {"Total Accumulated Estimated Alpha Value", "$0"},
+            {"Mean Population Estimated Insight Value", "$0"},
+            {"Mean Population Direction", "0%"},
+            {"Mean Population Magnitude", "0%"},
+            {"Rolling Averaged Population Direction", "0%"},
+            {"Rolling Averaged Population Magnitude", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/FutureNoTimeInUniverseRegressionAlgorithm.cs

@@ -0,0 +1,149 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting the behavior of a zero time in universe setting. Related to GH issue #6653
+    /// </summary>
+    public class FutureNoTimeInUniverseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Dictionary<DateTime, Symbol> _seenSymbols = new();
+        private Symbol _sp500;
+
+        /// <summary>
+        /// Initialize your algorithm and add desired assets.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 08);
+            SetEndDate(2013, 10, 10);
+
+            UniverseSettings.MinimumTimeInUniverse = TimeSpan.Zero;
+            var futureSP500 = AddFuture(Futures.Indices.SP500EMini);
+
+            _sp500 = futureSP500.Symbol;
+            futureSP500.SetFilter(u =>
+            {
+                return u.Where(s =>
+                {
+                    if (_seenSymbols.ContainsKey(Time) || _seenSymbols.ContainsValue(s))
+                    {
+                        // for each timestamp we select a single symbol which we haven't selected before
+                        return false;
+                    }
+                    _seenSymbols[Time] = s;
+                    return true;
+                });
+            });
+        }
+
+        /// <summary>
+        /// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
+        /// </summary>
+        /// <param name="slice">The current slice of data keyed by symbol string</param>
+        public override void OnData(Slice slice)
+        {
+            var futureContracts = slice.FutureChains.GetValue(_sp500);
+            if(futureContracts == null)
+            {
+                return;
+            }
+            var futureSymbols = futureContracts.Select(future => future.Symbol).ToHashSet();
+
+            if (futureSymbols.Count > 1)
+            {
+                throw new Exception($"At {Time} found {futureSymbols.Count}. Future symbols: [{string.Join(",", futureSymbols)}]");
+            }
+        }
+
+        /// <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 => 14931;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-66.775"},
+            {"Tracking Error", "0.243"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Fitness Score", "0"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
+            {"Portfolio Turnover", "0"},
+            {"Total Insights Generated", "0"},
+            {"Total Insights Closed", "0"},
+            {"Total Insights Analysis Completed", "0"},
+            {"Long Insight Count", "0"},
+            {"Short Insight Count", "0"},
+            {"Long/Short Ratio", "100%"},
+            {"Estimated Monthly Alpha Value", "$0"},
+            {"Total Accumulated Estimated Alpha Value", "$0"},
+            {"Mean Population Estimated Insight Value", "$0"},
+            {"Mean Population Direction", "0%"},
+            {"Mean Population Magnitude", "0%"},
+            {"Rolling Averaged Population Direction", "0%"},
+            {"Rolling Averaged Population Magnitude", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/FutureOptionBuySellCallIntradayRegressionAlgorithm.cs

@@ -85,10 +85,6 @@ namespace QuantConnect.Algorithm.CSharp
                 MarketOrder(esOptions[0], 1);
                 MarketOrder(esOptions[1], -1);
             });
-            Schedule.On(DateRules.Tomorrow, TimeRules.Noon, () =>
-            {
-                Liquidate();
-            });
         }
 
         /// <summary>
@@ -116,7 +112,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 939460;
+        public long DataPoints => 308080;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -129,33 +125,33 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "6"},
-            {"Average Win", "2.94%"},
-            {"Average Loss", "-4.15%"},
-            {"Compounding Annual Return", "-5.589%"},
-            {"Drawdown", "5.600%"},
-            {"Expectancy", "-0.145"},
-            {"Net Profit", "-2.760%"},
-            {"Sharpe Ratio", "-0.45"},
-            {"Probabilistic Sharpe Ratio", "9.306%"},
+            {"Average Win", "3.37%"},
+            {"Average Loss", "-4.34%"},
+            {"Compounding Annual Return", "-4.637%"},
+            {"Drawdown", "5.200%"},
+            {"Expectancy", "-0.111"},
+            {"Net Profit", "-2.284%"},
+            {"Sharpe Ratio", "-0.413"},
+            {"Probabilistic Sharpe Ratio", "9.827%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.71"},
-            {"Alpha", "-0.036"},
-            {"Beta", "-0.013"},
-            {"Annual Standard Deviation", "0.08"},
-            {"Annual Variance", "0.006"},
-            {"Information Ratio", "-0.149"},
-            {"Tracking Error", "0.387"},
-            {"Treynor Ratio", "2.865"},
-            {"Total Fees", "$3.70"},
-            {"Estimated Strategy Capacity", "$140000000.00"},
+            {"Profit-Loss Ratio", "0.78"},
+            {"Alpha", "-0.03"},
+            {"Beta", "-0.011"},
+            {"Annual Standard Deviation", "0.072"},
+            {"Annual Variance", "0.005"},
+            {"Information Ratio", "-0.134"},
+            {"Tracking Error", "0.385"},
+            {"Treynor Ratio", "2.816"},
+            {"Total Fees", "$2.84"},
+            {"Estimated Strategy Capacity", "$120000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPBIJ7O|ES XFH59UK0MYO1"},
-            {"Fitness Score", "0.017"},
+            {"Fitness Score", "0.021"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.096"},
-            {"Return Over Maximum Drawdown", "-0.993"},
-            {"Portfolio Turnover", "0.043"},
+            {"Sortino Ratio", "-0.08"},
+            {"Return Over Maximum Drawdown", "-0.896"},
+            {"Portfolio Turnover", "0.051"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -169,7 +165,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "1f521247474162d17ff94fbaa654385b"}
+            {"OrderListHash", "6ae724ba0dbcbd1ca49dcfcdf94e0319"}
         };
     }
 }

Algorithm.CSharp/FutureOptionCallITMExpiryRegressionAlgorithm.cs

@@ -200,7 +200,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 644315;
+        public long DataPoints => 211475;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -213,33 +213,33 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "1.26%"},
-            {"Average Loss", "-7.41%"},
-            {"Compounding Annual Return", "-12.424%"},
-            {"Drawdown", "6.300%"},
-            {"Expectancy", "-0.415"},
-            {"Net Profit", "-6.252%"},
-            {"Sharpe Ratio", "-1.226"},
-            {"Probabilistic Sharpe Ratio", "0.002%"},
+            {"Average Win", "2.28%"},
+            {"Average Loss", "-6.80%"},
+            {"Compounding Annual Return", "-9.373%"},
+            {"Drawdown", "5.300%"},
+            {"Expectancy", "-0.332"},
+            {"Net Profit", "-4.676%"},
+            {"Sharpe Ratio", "-1.002"},
+            {"Probabilistic Sharpe Ratio", "0.165%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.17"},
-            {"Alpha", "-0.086"},
+            {"Profit-Loss Ratio", "0.34"},
+            {"Alpha", "-0.064"},
             {"Beta", "0.003"},
-            {"Annual Standard Deviation", "0.07"},
-            {"Annual Variance", "0.005"},
-            {"Information Ratio", "-0.283"},
-            {"Tracking Error", "0.379"},
-            {"Treynor Ratio", "-25.997"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$140000000.00"},
+            {"Annual Standard Deviation", "0.064"},
+            {"Annual Variance", "0.004"},
+            {"Information Ratio", "-0.226"},
+            {"Tracking Error", "0.378"},
+            {"Treynor Ratio", "-18.824"},
+            {"Total Fees", "$1.42"},
+            {"Estimated Strategy Capacity", "$120000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPBIJ7O|ES XFH59UK0MYO1"},
-            {"Fitness Score", "0.008"},
+            {"Fitness Score", "0.017"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.205"},
-            {"Return Over Maximum Drawdown", "-1.989"},
-            {"Portfolio Turnover", "0.023"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "-1.769"},
+            {"Portfolio Turnover", "0.027"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -253,7 +253,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "c61ac689d112eab8fde5f2b1f715b7d3"}
+            {"OrderListHash", "02b16807a77a858047996f15597ff145"}
         };
     }
 }

Algorithm.CSharp/FutureOptionCallITMGreeksExpiryRegressionAlgorithm.cs

@@ -50,8 +50,8 @@ namespace QuantConnect.Algorithm.CSharp
             // We must set the volatility model on the underlying, since the defaults are
             // too strict to calculate greeks with when we only have data for a single day
             _es19m20.VolatilityModel = new StandardDeviationOfReturnsVolatilityModel(
-                60, 
-                Resolution.Minute, 
+                60,
+                Resolution.Minute,
                 TimeSpan.FromMinutes(1));
 
             // Select a future option expiring ITM, and adds it to the algorithm.
@@ -165,7 +165,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 644315;
+        public long DataPoints => 211475;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -178,33 +178,33 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "8.93%"},
-            {"Average Loss", "-34.88%"},
-            {"Compounding Annual Return", "-50.632%"},
-            {"Drawdown", "29.100%"},
-            {"Expectancy", "-0.372"},
-            {"Net Profit", "-29.072%"},
-            {"Sharpe Ratio", "-0.978"},
-            {"Probabilistic Sharpe Ratio", "0.012%"},
+            {"Average Win", "16.44%"},
+            {"Average Loss", "-35.38%"},
+            {"Compounding Annual Return", "-44.262%"},
+            {"Drawdown", "26.200%"},
+            {"Expectancy", "-0.268"},
+            {"Net Profit", "-24.757%"},
+            {"Sharpe Ratio", "-0.932"},
+            {"Probabilistic Sharpe Ratio", "0.060%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.26"},
-            {"Alpha", "-0.339"},
-            {"Beta", "0.017"},
-            {"Annual Standard Deviation", "0.347"},
-            {"Annual Variance", "0.12"},
-            {"Information Ratio", "-0.714"},
-            {"Tracking Error", "0.505"},
-            {"Treynor Ratio", "-19.672"},
-            {"Total Fees", "$9.25"},
-            {"Estimated Strategy Capacity", "$50000000.00"},
+            {"Profit-Loss Ratio", "0.46"},
+            {"Alpha", "-0.292"},
+            {"Beta", "0.016"},
+            {"Annual Standard Deviation", "0.313"},
+            {"Annual Variance", "0.098"},
+            {"Information Ratio", "-0.649"},
+            {"Tracking Error", "0.483"},
+            {"Treynor Ratio", "-17.96"},
+            {"Total Fees", "$7.10"},
+            {"Estimated Strategy Capacity", "$24000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPBIJ7O|ES XFH59UK0MYO1"},
-            {"Fitness Score", "0.055"},
+            {"Fitness Score", "0.108"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.155"},
-            {"Return Over Maximum Drawdown", "-1.743"},
-            {"Portfolio Turnover", "0.152"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "-1.692"},
+            {"Portfolio Turnover", "0.171"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -218,7 +218,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "ed0cbd8487dd45519e5d0225e51ba29c"}
+            {"OrderListHash", "c1c4c793696f75c528527334563ae8df"}
         };
     }
 }

Algorithm.CSharp/FutureOptionCallOTMExpiryRegressionAlgorithm.cs

@@ -71,6 +71,7 @@ namespace QuantConnect.Algorithm.CSharp
                 throw new Exception($"Contract {_expectedContract} was not found in the chain");
             }
 
+            // Place order after regular market opens
             Schedule.On(DateRules.Tomorrow, TimeRules.AfterMarketOpen(_es19m20, 1), () =>
             {
                 MarketOrder(_esOption, 1);
@@ -175,7 +176,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 644315;
+        public long DataPoints => 211475;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -189,31 +190,31 @@ namespace QuantConnect.Algorithm.CSharp
         {
             {"Total Trades", "2"},
             {"Average Win", "0%"},
-            {"Average Loss", "-4.02%"},
-            {"Compounding Annual Return", "-8.099%"},
-            {"Drawdown", "4.000%"},
+            {"Average Loss", "-3.85%"},
+            {"Compounding Annual Return", "-7.754%"},
+            {"Drawdown", "4.300%"},
             {"Expectancy", "-1"},
-            {"Net Profit", "-4.027%"},
-            {"Sharpe Ratio", "-1.175"},
-            {"Probabilistic Sharpe Ratio", "0.009%"},
+            {"Net Profit", "-3.851%"},
+            {"Sharpe Ratio", "-1.023"},
+            {"Probabilistic Sharpe Ratio", "0.131%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.056"},
-            {"Beta", "0.002"},
-            {"Annual Standard Deviation", "0.047"},
-            {"Annual Variance", "0.002"},
-            {"Information Ratio", "-0.206"},
-            {"Tracking Error", "0.376"},
-            {"Treynor Ratio", "-23.833"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$99000000.00"},
+            {"Alpha", "-0.053"},
+            {"Beta", "0.003"},
+            {"Annual Standard Deviation", "0.052"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-0.198"},
+            {"Tracking Error", "0.377"},
+            {"Treynor Ratio", "-19.331"},
+            {"Total Fees", "$1.42"},
+            {"Estimated Strategy Capacity", "$180000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPHGV9G|ES XFH59UK0MYO1"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.184"},
-            {"Return Over Maximum Drawdown", "-2.013"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "-1.798"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -228,7 +229,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "498c9958139b70d42ebecc65c4eceeee"}
+            {"OrderListHash", "29bb2f59fa2ee3dab8ed2aecf6544189"}
         };
     }
 }

Algorithm.CSharp/FutureOptionDailyRegressionAlgorithm.cs

@@ -32,7 +32,7 @@ namespace QuantConnect.Algorithm.CSharp
         protected OrderTicket Ticket;
         protected Symbol DcOption;
         protected virtual Resolution Resolution => Resolution.Daily;
-        
+
         public override void Initialize()
         {
             SetStartDate(2012, 1, 3);
@@ -51,30 +51,30 @@ namespace QuantConnect.Algorithm.CSharp
                 .Where(x => x.ID.StrikePrice == 17m && x.ID.OptionRight == OptionRight.Call)
                 .Select(x => AddFutureOptionContract(x, Resolution).Symbol)
                 .FirstOrDefault();
-            
+
             // Validate it is the expected contract
             var expectedContract = QuantConnect.Symbol.CreateOption(dc, Market.CME, OptionStyle.American,
                 OptionRight.Call, 17m,
                 new DateTime(2012, 4, 01));
-            
+
             if (DcOption != expectedContract)
             {
                 throw new Exception($"Contract {DcOption} was not the expected contract {expectedContract}");
             }
-            
+
             ScheduleBuySell();
         }
-        
+
         protected virtual void ScheduleBuySell()
         {
-            // Schedule a purchase of this contract tomorrow at 1AM
-            Schedule.On(DateRules.Tomorrow, TimeRules.At(1,0,0), () =>
+            // Schedule a purchase of this contract tomorrow at 10AM when the market is open
+            Schedule.On(DateRules.Tomorrow, TimeRules.At(10,0,0), () =>
             {
                 Ticket = MarketOrder(DcOption, 1);
             });
-            
-            // Schedule liquidation tomorrow at 6PM
-            Schedule.On(DateRules.Tomorrow, TimeRules.At(18,0,0), () =>
+
+            // Schedule liquidation tomorrow at 2PM when the market is open
+            Schedule.On(DateRules.Tomorrow, TimeRules.At(14,0,0), () =>
             {
                 Liquidate();
             });
@@ -99,7 +99,7 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 throw new Exception($"Expected no holdings at end of algorithm, but are invested in: {string.Join(", ", Portfolio.Keys)}");
             }
-            
+
             if (Ticket.Status != OrderStatus.Filled)
             {
                 throw new Exception("Future option order failed to fill correctly");
@@ -134,30 +134,30 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "-0.82%"},
-            {"Compounding Annual Return", "-66.089%"},
+            {"Compounding Annual Return", "-66.144%"},
             {"Drawdown", "0.800%"},
             {"Expectancy", "-1"},
-            {"Net Profit", "-0.824%"},
-            {"Sharpe Ratio", "-6.993"},
+            {"Net Profit", "-0.825%"},
+            {"Sharpe Ratio", "-6.988"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.466"},
-            {"Beta", "-7.501"},
-            {"Annual Standard Deviation", "0.092"},
+            {"Alpha", "0.467"},
+            {"Beta", "-7.512"},
+            {"Annual Standard Deviation", "0.093"},
             {"Annual Variance", "0.009"},
-            {"Information Ratio", "-7.586"},
+            {"Information Ratio", "-7.581"},
             {"Tracking Error", "0.105"},
             {"Treynor Ratio", "0.086"},
-            {"Total Fees", "$3.70"},
+            {"Total Fees", "$4.94"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "DC V5E8P9VAH3IC|DC V5E8P9SH0U0X"},
             {"Fitness Score", "0.006"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-80.233"},
+            {"Return Over Maximum Drawdown", "-80.18"},
             {"Portfolio Turnover", "0.013"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -172,7 +172,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "f00013930ab4c104a6177485d8090b31"}
+            {"OrderListHash", "dfcf673b46b9054a15babe1b0d734c35"}
         };
     }
 }

Algorithm.CSharp/FutureOptionHourlyRegressionAlgorithm.cs

@@ -38,9 +38,9 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 Ticket = MarketOrder(DcOption, 1);
             });
-            
-            // Schedule liquidation at 6PM
-            Schedule.On(DateRules.Today, TimeRules.At(18,0,0), () =>
+
+            // Schedule liquidation at 2PM when the market is open
+            Schedule.On(DateRules.Today, TimeRules.At(14,0,0), () =>
             {
                 Liquidate();
             });
@@ -68,7 +68,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 180;
+        public override long DataPoints => 88;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -99,15 +99,15 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$3.70"},
+            {"Total Fees", "$4.94"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "DC V5E8P9VAH3IC|DC V5E8P9SH0U0X"},
-            {"Fitness Score", "0.01"},
+            {"Fitness Score", "0.021"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-101.911"},
-            {"Portfolio Turnover", "0.02"},
+            {"Return Over Maximum Drawdown", "-135.888"},
+            {"Portfolio Turnover", "0.043"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -121,7 +121,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "665d06e4f758724b5b9576b14fd18743"}
+            {"OrderListHash", "aa0827b2e3105a09c7308382ac0512aa"}
         };
     }
 }

Algorithm.CSharp/FutureOptionMultipleContractsInDifferentContractMonthsWithSameUnderlyingFutureRegressionAlgorithm.cs

@@ -37,10 +37,13 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void Initialize()
         {
+            // Required for FOPs to use extended hours, until GH #6491 is addressed
+            UniverseSettings.ExtendedMarketHours = true;
+
             SetStartDate(2020, 1, 4);
             SetEndDate(2020, 1, 6);
 
-            var goldFutures = AddFuture("GC", Resolution.Minute, Market.COMEX);
+            var goldFutures = AddFuture("GC", Resolution.Minute, Market.COMEX, extendedMarketHours: true);
             goldFutures.SetFilter(0, 365);
 
             AddFutureOption(goldFutures.Symbol);
@@ -50,7 +53,8 @@ namespace QuantConnect.Algorithm.CSharp
         {
             foreach (var symbol in data.QuoteBars.Keys)
             {
-                if (_expectedSymbols.ContainsKey(symbol))
+                // Check that we are in regular hours, we can place a market order (on extended hours, limit orders should be used)
+                if (_expectedSymbols.ContainsKey(symbol) && IsInRegularHours(symbol))
                 {
                     var invested = _expectedSymbols[symbol];
                     if (!invested)
@@ -76,6 +80,11 @@ namespace QuantConnect.Algorithm.CSharp
             }
         }
 
+        private bool IsInRegularHours(Symbol symbol)
+        {
+            return Securities[symbol].Exchange.ExchangeOpen;
+        }
+
         private static Symbol CreateOption(DateTime expiry, OptionRight optionRight, decimal strikePrice)
         {
             return QuantConnect.Symbol.CreateOption(
@@ -115,31 +124,31 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "4"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-5.605%"},
-            {"Drawdown", "3.500%"},
+            {"Compounding Annual Return", "-25.338%"},
+            {"Drawdown", "0.200%"},
             {"Expectancy", "0"},
-            {"Net Profit", "-0.047%"},
-            {"Sharpe Ratio", "-10.898"},
+            {"Net Profit", "-0.240%"},
+            {"Sharpe Ratio", "-9.692"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.135"},
-            {"Beta", "0.124"},
-            {"Annual Standard Deviation", "0.005"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-17.984"},
-            {"Tracking Error", "0.038"},
-            {"Treynor Ratio", "-0.467"},
-            {"Total Fees", "$7.40"},
-            {"Estimated Strategy Capacity", "$25000000.00"},
+            {"Alpha", "0.127"},
+            {"Beta", "-0.629"},
+            {"Annual Standard Deviation", "0.027"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-12.58"},
+            {"Tracking Error", "0.07"},
+            {"Treynor Ratio", "0.415"},
+            {"Total Fees", "$9.88"},
+            {"Estimated Strategy Capacity", "$31000000.00"},
             {"Lowest Capacity Asset", "OG 31BFX0QKBVPGG|GC XE1Y0ZJ8NQ8T"},
-            {"Fitness Score", "0.012"},
+            {"Fitness Score", "0.013"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-126.806"},
-            {"Portfolio Turnover", "0.025"},
+            {"Return Over Maximum Drawdown", "-112.343"},
+            {"Portfolio Turnover", "0.026"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -153,7 +162,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "979e3995c0dbedc46eaf3705e0438bf5"}
+            {"OrderListHash", "ebde540d026c0bf7055caf5bf2eeded5"}
         };
     }
 }

Algorithm.CSharp/FutureOptionPutITMExpiryRegressionAlgorithm.cs

@@ -201,7 +201,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 644315;
+        public long DataPoints => 211475;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -214,33 +214,33 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "4.18%"},
-            {"Average Loss", "-8.26%"},
-            {"Compounding Annual Return", "-8.884%"},
-            {"Drawdown", "4.400%"},
-            {"Expectancy", "-0.247"},
-            {"Net Profit", "-4.427%"},
-            {"Sharpe Ratio", "-1.283"},
-            {"Probabilistic Sharpe Ratio", "0.001%"},
+            {"Average Win", "3.13%"},
+            {"Average Loss", "-8.06%"},
+            {"Compounding Annual Return", "-10.371%"},
+            {"Drawdown", "5.200%"},
+            {"Expectancy", "-0.306"},
+            {"Net Profit", "-5.189%"},
+            {"Sharpe Ratio", "-1.353"},
+            {"Probabilistic Sharpe Ratio", "0.000%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.51"},
-            {"Alpha", "-0.061"},
+            {"Profit-Loss Ratio", "0.39"},
+            {"Alpha", "-0.072"},
             {"Beta", "0.002"},
-            {"Annual Standard Deviation", "0.048"},
-            {"Annual Variance", "0.002"},
-            {"Information Ratio", "-0.221"},
-            {"Tracking Error", "0.376"},
-            {"Treynor Ratio", "-28.081"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$170000000.00"},
+            {"Annual Standard Deviation", "0.053"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-0.248"},
+            {"Tracking Error", "0.377"},
+            {"Treynor Ratio", "-31.761"},
+            {"Total Fees", "$1.42"},
+            {"Estimated Strategy Capacity", "$79000000.00"},
             {"Lowest Capacity Asset", "ES 31EL5FAOOQON8|ES XFH59UK0MYO1"},
-            {"Fitness Score", "0.008"},
+            {"Fitness Score", "0.009"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.225"},
-            {"Return Over Maximum Drawdown", "-2.009"},
-            {"Portfolio Turnover", "0.023"},
+            {"Sortino Ratio", "-0.264"},
+            {"Return Over Maximum Drawdown", "-2.001"},
+            {"Portfolio Turnover", "0.027"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -254,7 +254,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "1d90a4ed7fc218fe364435359358b2d5"}
+            {"OrderListHash", "621491b86f9d0e1a6abf4a882f73a38b"}
         };
     }
 }

Algorithm.CSharp/FutureOptionPutOTMExpiryRegressionAlgorithm.cs

@@ -174,7 +174,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 644315;
+        public long DataPoints => 211475;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -188,31 +188,31 @@ namespace QuantConnect.Algorithm.CSharp
         {
             {"Total Trades", "2"},
             {"Average Win", "0%"},
-            {"Average Loss", "-5.11%"},
-            {"Compounding Annual Return", "-10.226%"},
-            {"Drawdown", "5.100%"},
+            {"Average Loss", "-5.25%"},
+            {"Compounding Annual Return", "-10.492%"},
+            {"Drawdown", "5.300%"},
             {"Expectancy", "-1"},
-            {"Net Profit", "-5.114%"},
-            {"Sharpe Ratio", "-1.164"},
-            {"Probabilistic Sharpe Ratio", "0.009%"},
+            {"Net Profit", "-5.251%"},
+            {"Sharpe Ratio", "-1.289"},
+            {"Probabilistic Sharpe Ratio", "0.001%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.07"},
+            {"Alpha", "-0.072"},
             {"Beta", "0.003"},
-            {"Annual Standard Deviation", "0.06"},
-            {"Annual Variance", "0.004"},
-            {"Information Ratio", "-0.243"},
-            {"Tracking Error", "0.378"},
-            {"Treynor Ratio", "-23.592"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$180000000.00"},
+            {"Annual Standard Deviation", "0.056"},
+            {"Annual Variance", "0.003"},
+            {"Information Ratio", "-0.249"},
+            {"Tracking Error", "0.377"},
+            {"Treynor Ratio", "-28.519"},
+            {"Total Fees", "$1.42"},
+            {"Estimated Strategy Capacity", "$290000000.00"},
             {"Lowest Capacity Asset", "ES 31EL5FBZBMXES|ES XFH59UK0MYO1"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.182"},
-            {"Return Over Maximum Drawdown", "-2.002"},
+            {"Sortino Ratio", "-0.23"},
+            {"Return Over Maximum Drawdown", "-2"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -227,7 +227,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "76a3f4adc886f92b2f996d7e45e77dad"}
+            {"OrderListHash", "05dcd0b935d8206ca42ffc325fec4302"}
         };
     }
 }

Algorithm.CSharp/FutureOptionShortCallITMExpiryRegressionAlgorithm.cs

@@ -185,7 +185,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 644315;
+        public long DataPoints => 211475;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -198,33 +198,33 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "10.05%"},
-            {"Average Loss", "-5.60%"},
-            {"Compounding Annual Return", "8.148%"},
-            {"Drawdown", "0.500%"},
-            {"Expectancy", "0.397"},
-            {"Net Profit", "3.886%"},
-            {"Sharpe Ratio", "1.088"},
-            {"Probabilistic Sharpe Ratio", "53.421%"},
+            {"Average Win", "10.24%"},
+            {"Average Loss", "-6.46%"},
+            {"Compounding Annual Return", "6.498%"},
+            {"Drawdown", "0.900%"},
+            {"Expectancy", "0.292"},
+            {"Net Profit", "3.111%"},
+            {"Sharpe Ratio", "0.935"},
+            {"Probabilistic Sharpe Ratio", "45.614%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "1.79"},
-            {"Alpha", "0.057"},
+            {"Profit-Loss Ratio", "1.58"},
+            {"Alpha", "0.046"},
             {"Beta", "-0.003"},
-            {"Annual Standard Deviation", "0.053"},
-            {"Annual Variance", "0.003"},
-            {"Information Ratio", "0.094"},
-            {"Tracking Error", "0.379"},
-            {"Treynor Ratio", "-20.601"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$150000000.00"},
+            {"Annual Standard Deviation", "0.049"},
+            {"Annual Variance", "0.002"},
+            {"Information Ratio", "0.064"},
+            {"Tracking Error", "0.378"},
+            {"Treynor Ratio", "-16.913"},
+            {"Total Fees", "$1.42"},
+            {"Estimated Strategy Capacity", "$13000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UP5K75W|ES XFH59UK0MYO1"},
-            {"Fitness Score", "0.02"},
+            {"Fitness Score", "0.024"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "17.34"},
-            {"Portfolio Turnover", "0.02"},
+            {"Return Over Maximum Drawdown", "7.532"},
+            {"Portfolio Turnover", "0.025"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -238,7 +238,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "5358f87044d3f8dc5d67cb7362b12cea"}
+            {"OrderListHash", "bf5fe7396dd65efe92326817647d2350"}
         };
     }
 }

Algorithm.CSharp/FutureOptionShortCallOTMExpiryRegressionAlgorithm.cs

@@ -168,7 +168,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 644315;
+        public long DataPoints => 211475;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -181,32 +181,32 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "2"},
-            {"Average Win", "1.81%"},
+            {"Average Win", "1.74%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "3.756%"},
-            {"Drawdown", "0.000%"},
+            {"Compounding Annual Return", "3.600%"},
+            {"Drawdown", "0.300%"},
             {"Expectancy", "0"},
-            {"Net Profit", "1.811%"},
-            {"Sharpe Ratio", "1.183"},
-            {"Probabilistic Sharpe Ratio", "60.811%"},
+            {"Net Profit", "1.736%"},
+            {"Sharpe Ratio", "1.008"},
+            {"Probabilistic Sharpe Ratio", "49.736%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.026"},
+            {"Alpha", "0.025"},
             {"Beta", "-0.001"},
-            {"Annual Standard Deviation", "0.022"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "0.012"},
+            {"Annual Standard Deviation", "0.025"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "0.009"},
             {"Tracking Error", "0.375"},
-            {"Treynor Ratio", "-23.475"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$39000000.00"},
+            {"Treynor Ratio", "-18.666"},
+            {"Total Fees", "$1.42"},
+            {"Estimated Strategy Capacity", "$100000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPNF7B8|ES XFH59UK0MYO1"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "95.594"},
+            {"Return Over Maximum Drawdown", "11.26"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -221,7 +221,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "3e2637348e4985e9398811e0a9ba62ff"}
+            {"OrderListHash", "5c9cb56b3d08ac28a51d146ef6be7669"}
         };
     }
 }

Algorithm.CSharp/FutureOptionShortPutITMExpiryRegressionAlgorithm.cs

@@ -182,7 +182,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 644315;
+        public long DataPoints => 211475;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -195,33 +195,33 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "10.19%"},
-            {"Average Loss", "-8.02%"},
-            {"Compounding Annual Return", "2.790%"},
-            {"Drawdown", "0.500%"},
-            {"Expectancy", "0.135"},
-            {"Net Profit", "1.348%"},
-            {"Sharpe Ratio", "0.862"},
-            {"Probabilistic Sharpe Ratio", "42.945%"},
+            {"Average Win", "10.89%"},
+            {"Average Loss", "-7.10%"},
+            {"Compounding Annual Return", "6.286%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "0.267"},
+            {"Net Profit", "3.011%"},
+            {"Sharpe Ratio", "1.642"},
+            {"Probabilistic Sharpe Ratio", "85.803%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "1.27"},
-            {"Alpha", "0.02"},
+            {"Profit-Loss Ratio", "1.53"},
+            {"Alpha", "0.044"},
             {"Beta", "-0.001"},
-            {"Annual Standard Deviation", "0.023"},
+            {"Annual Standard Deviation", "0.026"},
             {"Annual Variance", "0.001"},
-            {"Information Ratio", "-0.006"},
+            {"Information Ratio", "0.058"},
             {"Tracking Error", "0.375"},
-            {"Treynor Ratio", "-15.363"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$100000000.00"},
+            {"Treynor Ratio", "-54.73"},
+            {"Total Fees", "$1.42"},
+            {"Estimated Strategy Capacity", "$12000000.00"},
             {"Lowest Capacity Asset", "ES 31EL5FAOUP0P0|ES XFH59UK0MYO1"},
-            {"Fitness Score", "0.021"},
+            {"Fitness Score", "0.026"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "5.859"},
-            {"Portfolio Turnover", "0.022"},
+            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
+            {"Portfolio Turnover", "0.026"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -235,7 +235,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "e8b27b23cb2bc65318696257af42b82e"}
+            {"OrderListHash", "cdf689416d6e6e04739cbaa7fb2f8b80"}
         };
     }
 }

Algorithm.CSharp/FutureOptionShortPutOTMExpiryRegressionAlgorithm.cs

@@ -167,7 +167,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 644315;
+        public long DataPoints => 211475;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -180,32 +180,32 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "2"},
-            {"Average Win", "3.29%"},
+            {"Average Win", "3.42%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "6.869%"},
+            {"Compounding Annual Return", "7.162%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "0"},
-            {"Net Profit", "3.286%"},
-            {"Sharpe Ratio", "1.205"},
-            {"Probabilistic Sharpe Ratio", "61.483%"},
+            {"Net Profit", "3.424%"},
+            {"Sharpe Ratio", "1.371"},
+            {"Probabilistic Sharpe Ratio", "73.287%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.048"},
+            {"Alpha", "0.05"},
             {"Beta", "-0.002"},
-            {"Annual Standard Deviation", "0.04"},
-            {"Annual Variance", "0.002"},
-            {"Information Ratio", "0.07"},
+            {"Annual Standard Deviation", "0.036"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "0.075"},
             {"Tracking Error", "0.377"},
-            {"Treynor Ratio", "-24.023"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$40000000.00"},
+            {"Treynor Ratio", "-30.322"},
+            {"Total Fees", "$1.42"},
+            {"Estimated Strategy Capacity", "$110000000.00"},
             {"Lowest Capacity Asset", "ES 31EL5FAJQ6SBO|ES XFH59UK0MYO1"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "150.849"},
+            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -220,7 +220,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9213af45c30119e0a53c3b57d3c553de"}
+            {"OrderListHash", "5895d7c6447d4b1487e4705bc32b50a6"}
         };
     }
 }

Algorithm.CSharp/FutureSharingTickerRegressionAlgorithm.cs

@@ -80,7 +80,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 135885;
+        public long DataPoints => 44671;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -95,31 +95,31 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-98.645%"},
-            {"Drawdown", "5.400%"},
+            {"Compounding Annual Return", "-99.356%"},
+            {"Drawdown", "4.500%"},
             {"Expectancy", "0"},
-            {"Net Profit", "-3.474%"},
-            {"Sharpe Ratio", "-68.954"},
+            {"Net Profit", "-3.675%"},
+            {"Sharpe Ratio", "-15.427"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-1.896"},
-            {"Beta", "0.058"},
-            {"Annual Standard Deviation", "0.014"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-75.062"},
-            {"Tracking Error", "0.229"},
-            {"Treynor Ratio", "-16.736"},
-            {"Total Fees", "$1.85"},
-            {"Estimated Strategy Capacity", "$93000000.00"},
+            {"Alpha", "3.273"},
+            {"Beta", "-0.263"},
+            {"Annual Standard Deviation", "0.064"},
+            {"Annual Variance", "0.004"},
+            {"Information Ratio", "-56.095"},
+            {"Tracking Error", "0.306"},
+            {"Treynor Ratio", "3.744"},
+            {"Total Fees", "$2.47"},
+            {"Estimated Strategy Capacity", "$19000000.00"},
             {"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
-            {"Fitness Score", "0.005"},
+            {"Fitness Score", "0.007"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-10.938"},
-            {"Return Over Maximum Drawdown", "-25.528"},
-            {"Portfolio Turnover", "0.445"},
+            {"Sortino Ratio", "-10.333"},
+            {"Return Over Maximum Drawdown", "-53.15"},
+            {"Portfolio Turnover", "0.665"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -133,7 +133,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "c627a8c7156e3ab378f2ab13d21b5737"}
+            {"OrderListHash", "fea761e839af44276dd9c4bdca1ef7bb"}
         };
     }
 }

Algorithm.CSharp/FuturesAndFuturesOptionsExpiryTimeAndLiquidationRegressionAlgorithm.cs

@@ -178,7 +178,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 645061;
+        public long DataPoints => 212221;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -191,33 +191,33 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "10.15%"},
-            {"Average Loss", "-11.34%"},
-            {"Compounding Annual Return", "-2.573%"},
-            {"Drawdown", "2.300%"},
-            {"Expectancy", "-0.052"},
-            {"Net Profit", "-2.341%"},
-            {"Sharpe Ratio", "-0.867"},
-            {"Probabilistic Sharpe Ratio", "0.001%"},
+            {"Average Win", "10.36%"},
+            {"Average Loss", "-10.99%"},
+            {"Compounding Annual Return", "-1.942%"},
+            {"Drawdown", "2.000%"},
+            {"Expectancy", "-0.028"},
+            {"Net Profit", "-1.766%"},
+            {"Sharpe Ratio", "-0.763"},
+            {"Probabilistic Sharpe Ratio", "0.020%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.90"},
+            {"Profit-Loss Ratio", "0.94"},
             {"Alpha", "-0.014"},
             {"Beta", "0.001"},
-            {"Annual Standard Deviation", "0.016"},
+            {"Annual Standard Deviation", "0.017"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-0.603"},
+            {"Information Ratio", "-0.602"},
             {"Tracking Error", "0.291"},
-            {"Treynor Ratio", "-13.292"},
-            {"Total Fees", "$3.70"},
-            {"Estimated Strategy Capacity", "$45000000.00"},
+            {"Treynor Ratio", "-11.14"},
+            {"Total Fees", "$3.57"},
+            {"Estimated Strategy Capacity", "$16000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UK0MYO1"},
-            {"Fitness Score", "0.005"},
+            {"Fitness Score", "0.009"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.181"},
-            {"Return Over Maximum Drawdown", "-1.1"},
-            {"Portfolio Turnover", "0.013"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "-0.977"},
+            {"Portfolio Turnover", "0.014"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -231,7 +231,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "67d8ad460ff796937ee252c3e4340e62"}
+            {"OrderListHash", "271484857fd3dbf4e4a332485bcfa773"}
         };
     }
 }

Algorithm.CSharp/FuturesExpiredContractRegression.cs

@@ -1,4 +1,4 @@
-/* 
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -46,6 +46,14 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void OnData(Slice data)
         {
+            foreach (var point in data)
+            {
+                if (point.Value.IsFillForward)
+                {
+                    throw new Exception("We requested no fill forwarding!");
+                }
+            }
+
             foreach (var chain in data.FutureChains)
             {
                 _receivedData = true;
@@ -81,7 +89,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 972466;
+        public long DataPoints => 136444;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/FuturesExtendedMarketHoursRegressionAlgorithm.cs

@@ -0,0 +1,172 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using System.Linq;
+using System.Collections.Generic;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This regression algorithm asserts that futures have data at extended market hours when this is enabled.
+    /// </summary>
+    public class FuturesExtendedMarketHoursRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Future _es;
+        private Future _gc;
+        private bool _esRanOnRegularHours;
+        private bool _esRanOnExtendedHours;
+        private bool _gcRanOnRegularHours;
+        private bool _gcRanOnExtendedHours;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 6);
+            SetEndDate(2013, 10, 11);
+
+            _es = AddFuture(Futures.Indices.SP500EMini, Resolution.Hour, fillDataForward: true, extendedMarketHours: true);
+            _es.SetFilter(0, 180);
+
+            _gc = AddFuture(Futures.Metals.Gold, Resolution.Hour, fillDataForward: true, extendedMarketHours: false);
+            _gc.SetFilter(0, 180);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            var sliceSymbols = new HashSet<Symbol>(slice.Keys);
+            sliceSymbols.UnionWith(slice.Bars.Keys);
+            sliceSymbols.UnionWith(slice.Ticks.Keys);
+            sliceSymbols.UnionWith(slice.QuoteBars.Keys);
+
+            var esIsInRegularHours = _es.Exchange.Hours.IsOpen(Time, false);
+            var esIsInExtendedHours = !esIsInRegularHours && _es.Exchange.Hours.IsOpen(Time, true);
+            var sliceHasESData = sliceSymbols.Any(symbol => symbol == _es.Symbol || symbol.Canonical == _es.Symbol);
+            _esRanOnRegularHours |= esIsInRegularHours && sliceHasESData;
+            _esRanOnExtendedHours |= esIsInExtendedHours && sliceHasESData;
+
+            var gcIsInRegularHours = _gc.Exchange.Hours.IsOpen(Time, false);
+            var gcIsInExtendedHours = !gcIsInRegularHours && _gc.Exchange.Hours.IsOpen(Time, true);
+            var sliceHasGCData = sliceSymbols.Any(symbol => symbol == _gc.Symbol || symbol.Canonical == _gc.Symbol);
+            _gcRanOnRegularHours |= gcIsInRegularHours && sliceHasGCData;
+            _gcRanOnExtendedHours |= gcIsInExtendedHours && sliceHasGCData;
+
+            var currentTimeIsRegularHours = (Time.TimeOfDay >= new TimeSpan(9, 30, 0) && Time.TimeOfDay < new TimeSpan(16, 15, 0)) ||
+                (Time.TimeOfDay >= new TimeSpan(16, 30, 0) && Time.TimeOfDay < new TimeSpan(17, 0, 0));
+            var currentTimeIsExtendedHours = !currentTimeIsRegularHours
+                && (Time.TimeOfDay < new TimeSpan(9, 30, 0) || Time.TimeOfDay >= new TimeSpan(18, 0, 0));
+
+            if (esIsInRegularHours != currentTimeIsRegularHours || esIsInExtendedHours != currentTimeIsExtendedHours)
+            {
+                throw new Exception($"At {Time}, {_es.Symbol} is either in regular hours but current time is in extended hours, or viceversa");
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_esRanOnRegularHours)
+            {
+                throw new Exception($"Algorithm should have run on regular hours for {_es.Symbol} future, which enabled extended market hours");
+            }
+
+            if (!_esRanOnExtendedHours)
+            {
+                throw new Exception($"Algorithm should have run on extended hours for {_es.Symbol} future, which enabled extended market hours");
+            }
+
+            if (!_gcRanOnRegularHours)
+            {
+                throw new Exception($"Algorithm should have run on regular hours for {_gc.Symbol} future, which did not enable extended market hours");
+            }
+
+            if (_gcRanOnExtendedHours)
+            {
+                throw new Exception($"Algorithm should have not run on extended hours for {_gc.Symbol} future, which did not enable extended market hours");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 3387;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-2.564"},
+            {"Tracking Error", "0.214"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Fitness Score", "0"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "79228162514264337593543950335"},
+            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
+            {"Portfolio Turnover", "0"},
+            {"Total Insights Generated", "0"},
+            {"Total Insights Closed", "0"},
+            {"Total Insights Analysis Completed", "0"},
+            {"Long Insight Count", "0"},
+            {"Short Insight Count", "0"},
+            {"Long/Short Ratio", "100%"},
+            {"Estimated Monthly Alpha Value", "$0"},
+            {"Total Accumulated Estimated Alpha Value", "$0"},
+            {"Mean Population Estimated Insight Value", "$0"},
+            {"Mean Population Direction", "0%"},
+            {"Mean Population Magnitude", "0%"},
+            {"Rolling Averaged Population Direction", "0%"},
+            {"Rolling Averaged Population Magnitude", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/GetParameterRegressionAlgorithm.cs

@@ -0,0 +1,132 @@
+/*
+ * 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>
+    /// Regression algorithm for testing parameterized regression algorithms get valid parameters.
+    /// </summary>
+    public class GetParameterRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 07);
+
+            CheckParameter((string)null, GetParameter("non-existing"), "GetParameter(\"non-existing\")");
+            CheckParameter("100", GetParameter("non-existing", "100"), "GetParameter(\"non-existing\", \"100\")");
+            CheckParameter(100, GetParameter("non-existing", 100), "GetParameter(\"non-existing\", 100)");
+            CheckParameter(100d, GetParameter("non-existing", 100d), "GetParameter(\"non-existing\", 100d)");
+            CheckParameter(100m, GetParameter("non-existing", 100m), "GetParameter(\"non-existing\", 100m)");
+
+            CheckParameter("10", GetParameter("ema-fast"), "GetParameter(\"ema-fast\")");
+            CheckParameter(10, GetParameter("ema-fast", 100), "GetParameter(\"ema-fast\", 100)");
+            CheckParameter(10d, GetParameter("ema-fast", 100d), "GetParameter(\"ema-fast\", 100d)");
+            CheckParameter(10m, GetParameter("ema-fast", 100m), "GetParameter(\"ema-fast\", 100m)");
+
+            Quit();
+        }
+
+        private void CheckParameter<T, P>(T expected, P actual, string call)
+        {
+            if (expected == null && actual != null)
+            {
+                throw new Exception($"{call} should have returned null but returned {actual} ({actual.GetType()})");
+            }
+
+            if (expected != null && actual == null)
+            {
+                throw new Exception($"{call} should have returned {expected} ({expected.GetType()}) but returned null");
+            }
+
+            if (expected != null && actual != null && (expected.GetType() != actual.GetType() || !expected.Equals(actual)))
+            {
+                throw new Exception($"{call} should have returned {expected} ({expected.GetType()}) but returned {actual} ({actual.GetType()})");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 0;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Fitness Score", "0"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "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", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/HistoryTickRegressionAlgorithm.cs

@@ -0,0 +1,121 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.Market;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting that tick history request includes both trade and quote data
+    /// </summary>
+    public class HistoryTickRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _symbol;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 11);
+            SetEndDate(2013, 10, 11);
+
+            _symbol = AddEquity("SPY", Resolution.Tick).Symbol;
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            var history = History<Tick>(_symbol, StartDate, EndDate, Resolution.Tick);
+            var quotes = history.Where(x => x.TickType == TickType.Quote).ToList();
+            var trades = history.Where(x => x.TickType == TickType.Trade).ToList();
+
+            if (quotes.Count == 0 || trades.Count == 0)
+            {
+                throw new Exception("Expected to find at least one tick of each type (quote and trade)");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public Language[] Languages { get; } = { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 2741747;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 2741732;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Trades", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Fitness Score", "0"},
+            {"Kelly Criterion Estimate", "0"},
+            {"Kelly Criterion Probability Value", "0"},
+            {"Sortino Ratio", "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", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}