Revert some changes and adds pandas memory allocator

* Updates CI for Arrow
  * Updates DockerfileLeanFoundation
  * Adds Arrow to Python packages tests

.github/workflows/gh-actions.yml

@@ -1,31 +0,0 @@
-name: Build & Test Lean
-
-on:
-  push:
-    branches: ['*']
-  pull_request:
-    branches: [master]
-
-jobs:
-  build:
-    runs-on: ubuntu-16.04
-    container:
-        image: quantconnect/lean:foundation
-    steps:
-      - uses: actions/checkout@v2
-
-      - name: Restore nuget dependencies
-        run: |
-          nuget restore QuantConnect.Lean.sln -v quiet
-          nuget install NUnit.Runners -Version 3.11.1 -OutputDirectory testrunner
-
-      - name: Build
-        run: msbuild /p:Configuration=Release /p:VbcToolExe=vbnc.exe /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
-
-      - name: Run Tests
-        run: mono ./testrunner/NUnit.ConsoleRunner.3.11.1/tools/nunit3-console.exe ./Tests/bin/Release/QuantConnect.Tests.dll --where "cat != TravisExclude" --labels=Off --params:log-handler=ConsoleErrorLogHandler
-
-      - name: Generate & Publish python stubs
-        run: |
-          chmod +x ci_build_stubs.sh
-          ./ci_build_stubs.sh -d -t -g #Ignore Publish as of since credentials are missing on CI

.gitignore

@@ -144,7 +144,6 @@ $tf/
 # ReSharper is a .NET coding add-in
 _ReSharper*/
 *.[Rr]e[Ss]harper
-*.DotSettings
 *.DotSettings.user
 
 # JustCode is a .NET coding addin-in

.idea/workspace.xml

@@ -3,7 +3,7 @@
   <component name="RunManager" selected="Python Debug Server.Debug in Container">
     <configuration name="Debug Local" type="PyRemoteDebugConfigurationType" factoryName="Python Remote Debug">
       <module name="LEAN" />
-      <option name="PORT" value="6000" />
+      <option name="PORT" value="5678" />
       <option name="HOST" value="localhost" />
       <PathMappingSettings>
         <option name="pathMappings">
@@ -16,7 +16,7 @@
     </configuration>
     <configuration name="Debug in Container" type="PyRemoteDebugConfigurationType" factoryName="Python Remote Debug">
       <module name="LEAN" />
-      <option name="PORT" value="6000" />
+      <option name="PORT" value="5678" />
       <option name="HOST" value="localhost" />
       <PathMappingSettings>
         <option name="pathMappings">

.travis.yml

@@ -5,7 +5,7 @@ mono:
 solution: QuantConnect.Lean.sln
 before_install:
   - export PATH="$HOME/miniconda3/bin:$PATH"
-  - wget -q https://cdn.quantconnect.com/miniconda/Miniconda3-4.5.12-Linux-x86_64.sh
+  - wget https://cdn.quantconnect.com/miniconda/Miniconda3-4.5.12-Linux-x86_64.sh
   - bash Miniconda3-4.5.12-Linux-x86_64.sh -b
   - rm -rf Miniconda3-4.5.12-Linux-x86_64.sh
   - sudo ln -s $HOME/miniconda3/lib/libpython3.6m.so /usr/lib/libpython3.6m.so
@@ -16,11 +16,12 @@ before_install:
   - conda install -y cython=0.29.15
   - conda install -y scipy=1.4.1
   - conda install -y wrapt=1.12.1
+  - pip install pyarrow==1.0.1
 install:
-  - nuget restore QuantConnect.Lean.sln -v quiet
+  - nuget restore QuantConnect.Lean.sln
   - nuget install NUnit.Runners -Version 3.11.1 -OutputDirectory testrunner
 script:
-  - msbuild /p:Configuration=Release /p:VbcToolExe=vbnc.exe /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
-  - mono ./testrunner/NUnit.ConsoleRunner.3.11.1/tools/nunit3-console.exe ./Tests/bin/Release/QuantConnect.Tests.dll --where "cat != TravisExclude" --labels=Off --params:log-handler=ConsoleErrorLogHandler
+  - msbuild /p:Configuration=Release /p:VbcToolExe=vbnc.exe QuantConnect.Lean.sln
+  - mono ./testrunner/NUnit.ConsoleRunner.3.11.1/tools/nunit3-console.exe ./Tests/bin/Release/QuantConnect.Tests.dll --where "cat != TravisExclude" --labels=Off
   - chmod +x ci_build_stubs.sh
   - sudo -E ./ci_build_stubs.sh -d -t -g -p

.vscode/readme.md

@@ -13,7 +13,7 @@ Before anything we need to ensure a few things have been done:
 
 
 1. Get [Visual Studio Code](https://code.visualstudio.com/download)
-    *   Get the Extension [Mono Debug **15.8**](https://marketplace.visualstudio.com/items?itemName=ms-vscode.mono-debug) for C# Debugging
+    *   Get the Extension [Mono Debug](https://marketplace.visualstudio.com/items?itemName=ms-vscode.mono-debug) for C# Debugging
     *   Get the Extension [Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python) for Python Debugging
 
 2. Get [Docker](https://docs.docker.com/get-docker/):
@@ -35,8 +35,7 @@ Before anything we need to ensure a few things have been done:
     *   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
 
-**NOTES**: 
-- Mono Extension Version 16 and greater fails to debug the docker container remotely, please install **Version 15.8**. To install an older version from within VS Code go to the extensions tab, search "Mono Debug", and select "Install Another Version...".
+
 <br />
 
 <h1>Develop Algorithms Locally, Run in Container</h1>
@@ -113,12 +112,6 @@ In VS Code click on the debug/run icon on the left toolbar, at the top you shoul
 
 As defaults these are all great! Feel free to change them as needed for your setup.
 
-**NOTE:** VSCode may try and throw errors when launching this way regarding build on `QuantConnect.csx` and `Config.json` these errors can be ignored by selecting "*Debug Anyway*". To stop this error message in the future select "*Remember my choice in user settings*". 
-
-If using C# algorithms ensure that msbuild can build them successfully.  
-
-
-
 <br />
 
 <h3>Option 2</h3>
@@ -201,6 +194,4 @@ _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!
 
-*   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.
-*   `Errors exist after running preLaunchTask 'run-docker'`This VSCode error appears to warn you of CSharp errors when trying to use `Debug in Container` select "Debug Anyway" as the errors are false flags for JSON comments as well as `QuantConnect.csx` not finding references. Neither of these will impact your debugging. 
-*   `The container name "/LeanEngine" is already in use by container "****"` This Docker error implies that another instance of lean is already running under the container name /LeanEngine. If this error appears either use Docker Desktop to delete the container or use `docker kill LeanEngine` from the command line.
+*   Error messages about build in VSCode points 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/tasks.json

@@ -20,34 +20,6 @@
             },
             "problemMatcher": "$msCompile"
         },
-        {
-            "label": "rebuild",
-            "type": "shell",
-            "command": "msbuild",
-            "args": [
-                "/p:Configuration=Debug",
-                "/p:DebugType=portable",
-                "/t:rebuild",
-            ],
-            "group": "build",
-            "presentation": {
-                "reveal": "silent"
-            },
-            "problemMatcher": "$msCompile"
-        },
-        {
-            "label": "clean",
-            "type": "shell",
-            "command": "msbuild",
-            "args": [
-                "/t:clean",
-            ],
-            "group": "build",
-            "presentation": {
-                "reveal": "silent"
-            },
-            "problemMatcher": "$msCompile"
-        },
         {
             "label": "force build linux",
             "type": "shell",

Algorithm.CSharp/AccumulativeInsightPortfolioRegressionAlgorithm.cs

@@ -113,7 +113,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "54.5455%"},
             {"Rolling Averaged Population Direction", "59.8056%"},
             {"Rolling Averaged Population Magnitude", "59.8056%"},
-            {"OrderListHash", "0a28eedf6304023f5002ef672b489b88"}
+            {"OrderListHash", "1256341962"}
         };
     }
 }

Algorithm.CSharp/AddAlphaModelAlgorithm.cs

@@ -149,7 +149,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "100%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "506e9fe18984ba6e569b2e327030de3a"}
+            {"OrderListHash", "-887015098"}
         };
     }
 }

Algorithm.CSharp/AddFutureOptionContractDataStreamingRegressionAlgorithm.cs

@@ -204,7 +204,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "35738733ff791eeeaf508faec804cab0"}
+            {"OrderListHash", "1074366800"}
         };
     }
 }

Algorithm.CSharp/AddFutureOptionSingleOptionChainSelectedInUniverseFilterRegressionAlgorithm.cs

@@ -238,7 +238,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9347e3b610cfa21f7cbd968a0135c8af"}
+            {"OrderListHash", "1532330301"}
         };
     }
 }

Algorithm.CSharp/AddOptionContractExpiresRegressionAlgorithm.cs

@@ -131,13 +131,13 @@ namespace QuantConnect.Algorithm.CSharp
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
             {"Profit-Loss Ratio", "0.92"},
-            {"Alpha", "-0.021"},
-            {"Beta", "-0.01"},
+            {"Alpha", "-0.023"},
+            {"Beta", "0.005"},
             {"Annual Standard Deviation", "0.006"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "-3.374"},
-            {"Tracking Error", "0.058"},
-            {"Treynor Ratio", "2.133"},
+            {"Information Ratio", "-3.424"},
+            {"Tracking Error", "0.057"},
+            {"Treynor Ratio", "-4.775"},
             {"Total Fees", "$2.00"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
@@ -158,7 +158,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "486118a60d78f74811fe8d927c2c6b43"}
+            {"OrderListHash", "-1185639451"}
         };
     }
 }

Algorithm.CSharp/AddOptionContractFromUniverseRegressionAlgorithm.cs

@@ -210,7 +210,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "ae0b430e9c728966e3736fb352a689c6"}
+            {"OrderListHash", "721476625"}
         };
     }
 }

Algorithm.CSharp/AddRemoveOptionUniverseRegressionAlgorithm.cs

@@ -249,7 +249,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "cf8f76fa441c2a5e3b2dbbabcab32cd2"}
+            {"OrderListHash", "731140098"}
         };
     }
 }

Algorithm.CSharp/AddRemoveSecurityRegressionAlgorithm.cs

@@ -150,7 +150,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "5f7ba8b5defb310a2eaf98b11abd3b74"}
+            {"OrderListHash", "1779055144"}
         };
     }
 }

Algorithm.CSharp/AddRiskManagementAlgorithm.cs

@@ -103,7 +103,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "54.5455%"},
             {"Rolling Averaged Population Direction", "59.8056%"},
             {"Rolling Averaged Population Magnitude", "59.8056%"},
-            {"OrderListHash", "0b8cbbafdb77bae2f7abe3cf5e05ac5c"}
+            {"OrderListHash", "-887190565"}
         };
     }
 }

Algorithm.CSharp/AddUniverseSelectionModelAlgorithm.cs

@@ -122,7 +122,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "8971c92ba163cec8526379865d9b9ee4"}
+            {"OrderListHash", "1917702312"}
         };
     }
 }

Algorithm.CSharp/AddUniverseSelectionModelCoarseAlgorithm.cs

@@ -129,7 +129,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "ce59e51c8e404b5dbbc02911473aed1c"}
+            {"OrderListHash", "-1674230481"}
         };
     }
 }

Algorithm.CSharp/AllShortableSymbolsCoarseSelectionRegressionAlgorithm.cs

@@ -1,236 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using QuantConnect.Brokerages;
-using QuantConnect.Data;
-using QuantConnect.Data.Shortable;
-using QuantConnect.Data.UniverseSelection;
-using QuantConnect.Interfaces;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Tests filtering in coarse selection by shortable quantity
-    /// </summary>
-    public class AllShortableSymbolsCoarseSelectionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        private static readonly DateTime _20140325 = new DateTime(2014, 3, 25);
-        private static readonly DateTime _20140326 = new DateTime(2014, 3, 26);
-        private static readonly DateTime _20140327 = new DateTime(2014, 3, 27);
-        private static readonly DateTime _20140328 = new DateTime(2014, 3, 28);
-        private static readonly DateTime _20140329 = new DateTime(2014, 3, 29);
-
-        private static readonly Symbol _aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
-        private static readonly Symbol _bac = QuantConnect.Symbol.Create("BAC", SecurityType.Equity, Market.USA);
-        private static readonly Symbol _gme = QuantConnect.Symbol.Create("GME", SecurityType.Equity, Market.USA);
-        private static readonly Symbol _goog = QuantConnect.Symbol.Create("GOOG", SecurityType.Equity, Market.USA);
-        private static readonly Symbol _qqq = QuantConnect.Symbol.Create("QQQ", SecurityType.Equity, Market.USA);
-        private static readonly Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
-        private DateTime _lastTradeDate;
-
-        private static readonly Dictionary<DateTime, bool> _coarseSelected = new Dictionary<DateTime, bool>
-        {
-            { _20140325, false },
-            { _20140326, false },
-            { _20140327, false },
-            { _20140328, false },
-        };
-
-        private static readonly Dictionary<DateTime, Symbol[]> _expectedSymbols = new Dictionary<DateTime, Symbol[]>
-        {
-            { _20140325, new[]
-                {
-                    _bac,
-                    _qqq,
-                    _spy
-                }
-            },
-            { _20140326, new[]
-                {
-                    _spy
-                }
-            },
-            { _20140327, new[]
-                {
-                    _aapl,
-                    _bac,
-                    _gme,
-                    _qqq,
-                    _spy,
-                }
-            },
-            { _20140328, new[]
-                {
-                    _goog
-                }
-            },
-            { _20140329, new Symbol[0] }
-        };
-
-        public override void Initialize()
-        {
-            SetStartDate(2014, 3, 25);
-            SetEndDate(2014, 3, 29);
-            SetCash(10000000);
-
-            AddUniverse(CoarseSelection);
-            UniverseSettings.Resolution = Resolution.Daily;
-
-            SetBrokerageModel(new AllShortableSymbolsRegressionAlgorithmBrokerageModel());
-        }
-
-        public override void OnData(Slice data)
-        {
-            if (Time.Date == _lastTradeDate)
-            {
-                return;
-            }
-
-            foreach (var symbol in ActiveSecurities.Keys)
-            {
-                if (!Portfolio.ContainsKey(symbol) || !Portfolio[symbol].Invested)
-                {
-                    if (!Shortable(symbol))
-                    {
-                        throw new Exception($"Expected {symbol} to be shortable on {Time:yyyy-MM-dd}");
-                    }
-
-                    // Buy at least once into all Symbols. Since daily data will always use
-                    // MOO orders, it makes the testing of liquidating buying into Symbols difficult.
-                    MarketOrder(symbol, -(decimal)ShortableQuantity(symbol));
-                    _lastTradeDate = Time.Date;
-                }
-            }
-        }
-
-        private IEnumerable<Symbol> CoarseSelection(IEnumerable<CoarseFundamental> coarse)
-        {
-            var shortableSymbols = AllShortableSymbols();
-            var selectedSymbols = coarse
-                .Select(x => x.Symbol)
-                .Where(s => shortableSymbols.ContainsKey(s) && shortableSymbols[s] >= 500)
-                .OrderBy(s => s)
-                .ToList();
-
-            var expectedMissing = 0;
-            if (Time.Date == _20140327)
-            {
-                var gme = QuantConnect.Symbol.Create("GME", SecurityType.Equity, Market.USA);
-                if (!shortableSymbols.ContainsKey(gme))
-                {
-                    throw new Exception("Expected unmapped GME in shortable symbols list on 2014-03-27");
-                }
-                if (!coarse.Select(x => x.Symbol.Value).Contains("GME"))
-                {
-                    throw new Exception("Expected mapped GME in coarse symbols on 2014-03-27");
-                }
-
-                expectedMissing = 1;
-            }
-
-            var missing = _expectedSymbols[Time.Date].Except(selectedSymbols).ToList();
-            if (missing.Count != expectedMissing)
-            {
-                throw new Exception($"Expected Symbols selected on {Time.Date:yyyy-MM-dd} to match expected Symbols, but the following Symbols were missing: {string.Join(", ", missing.Select(s => s.ToString()))}");
-            }
-
-            _coarseSelected[Time.Date] = true;
-            return selectedSymbols;
-        }
-
-        public override void OnEndOfAlgorithm()
-        {
-            if (!_coarseSelected.Values.All(x => x))
-            {
-                throw new AggregateException($"Expected coarse selection on all dates, but didn't run on: {string.Join(", ", _coarseSelected.Where(kvp => !kvp.Value).Select(kvp => kvp.Key.ToStringInvariant("yyyy-MM-dd")))}");
-            }
-        }
-
-        private class AllShortableSymbolsRegressionAlgorithmBrokerageModel : DefaultBrokerageModel
-        {
-            public AllShortableSymbolsRegressionAlgorithmBrokerageModel() : base()
-            {
-                ShortableProvider = new RegressionTestShortableProvider();
-            }
-        }
-
-        private class RegressionTestShortableProvider : LocalDiskShortableProvider
-        {
-            public RegressionTestShortableProvider() : base(SecurityType.Equity, "testbrokerage", Market.USA)
-            {
-            }
-        }
-
-        /// <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>
-        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
-        /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
-        {
-            {"Total Trades", "5"},
-            {"Average Win", "0%"},
-            {"Average Loss", "0%"},
-            {"Compounding Annual Return", "36.294%"},
-            {"Drawdown", "0%"},
-            {"Expectancy", "0"},
-            {"Net Profit", "0.340%"},
-            {"Sharpe Ratio", "21.2"},
-            {"Probabilistic Sharpe Ratio", "99.990%"},
-            {"Loss Rate", "0%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.274"},
-            {"Beta", "0.138"},
-            {"Annual Standard Deviation", "0.011"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "7.202"},
-            {"Tracking Error", "0.068"},
-            {"Treynor Ratio", "1.722"},
-            {"Total Fees", "$307.50"},
-            {"Fitness Score", "0.173"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "79228162514264337593543950335"},
-            {"Portfolio Turnover", "0.173"},
-            {"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", "6b1b205e5a6461ffd5bed645099714cd"}
-        };
-    }
-}

Algorithm.CSharp/Alphas/MortgageRateVolatilityAlpha.cs

@@ -19,27 +19,28 @@ using QuantConnect.Indicators;
 using QuantConnect.Orders.Fees;
 using QuantConnect.Data.Custom;
 using System.Collections.Generic;
+using QuantConnect.Algorithm.Framework;
 using QuantConnect.Algorithm.Framework.Alphas;
 using QuantConnect.Algorithm.Framework.Execution;
 using QuantConnect.Algorithm.Framework.Portfolio;
 using QuantConnect.Algorithm.Framework.Risk;
 using QuantConnect.Algorithm.Framework.Selection;
 
-namespace QuantConnect.Algorithm.CSharp.Alphas
+namespace QuantConnect.Algorithm.CSharp
 {
-    ///<summary>
-    /// This Alpha Model uses Wells Fargo 30-year Fixed Rate Mortgage data from Quandl to
-    /// generate Insights about the movement of Real Estate ETFs. Mortgage rates can provide information
-    /// regarding the general price trend of real estate, and ETFs provide good continuous-time instruments
-    /// to measure the impact against. Volatility in mortgage rates tends to put downward pressure on real
-    /// estate prices, whereas stable mortgage rates, regardless of true rate, lead to stable or higher real
-    /// estate prices. This Alpha model seeks to take advantage of this correlation by emitting insights
-    /// based on volatility and rate deviation from its historic mean.
-    ///
-    /// This alpha is part of the Benchmark Alpha Series created by QuantConnect which are open
+	/// <summary>
+	/// This Alpha Model uses Wells Fargo 30-year Fixed Rate Mortgage data from Quandl to 
+	/// generate Insights about the movement of Real Estate ETFs. Mortgage rates can provide information 
+	/// regarding the general price trend of real estate, and ETFs provide good continuous-time instruments 
+	/// to measure the impact against. Volatility in mortgage rates tends to put downward pressure on real 
+	/// estate prices, whereas stable mortgage rates, regardless of true rate, lead to stable or higher real
+	/// estate prices. This Alpha model seeks to take advantage of this correlation by emitting insights
+	/// based on volatility and rate deviation from its historic mean.
+	
+	/// This alpha is part of the Benchmark Alpha Series created by QuantConnect which are open
     /// sourced so the community and client funds can see an example of an alpha.
-    ///</summary>
-    public class MortgageRateVolatilityAlgorithm : QCAlgorithm
+	/// <summary>
+    public class MortgageRateVolatilityAlgorithm : QCAlgorithmFramework
     {
         public override void Initialize()
         {
@@ -50,8 +51,8 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
             SetSecurityInitializer(security => security.FeeModel = new ConstantFeeModel(0));
 
             // Basket of 6 liquid real estate ETFs
-            Func<string, Symbol> toSymbol = x => QuantConnect.Symbol.Create(x, SecurityType.Equity, Market.USA);
-            var realEstateETFs = new[] { "VNQ", "REET", "TAO", "FREL", "SRET", "HIPS" }.Select(toSymbol).ToArray();
+            Func<string, Symbol> ToSymbol = x => QuantConnect.Symbol.Create(x, SecurityType.Equity, Market.USA);
+            var realEstateETFs = new[] { "VNQ", "REET", "TAO", "FREL", "SRET", "HIPS" }.Select(ToSymbol).ToArray();
             SetUniverseSelection(new ManualUniverseSelectionModel(realEstateETFs));
 
             SetAlpha(new MortgageRateVolatilityAlphaModel(this));
@@ -63,6 +64,8 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
             SetRiskManagement(new NullRiskManagementModel());
 
         }
+        
+        public void OnData(QuandlMortgagePriceColumns data) {  }
 
         private class MortgageRateVolatilityAlphaModel : AlphaModel
         {
@@ -76,7 +79,7 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
             private readonly StandardDeviation _mortgageRateStd;
 
             public MortgageRateVolatilityAlphaModel(
-                QCAlgorithm algorithm,
+                QCAlgorithmFramework algorithm,
                 int indicatorPeriod = 15,
                 double insightMagnitude = 0.0005,
                 int deviations = 2,
@@ -99,7 +102,7 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
                 WarmUpIndicators(algorithm);
             }
             
-            public override IEnumerable<Insight> Update(QCAlgorithm algorithm, Slice data)
+            public override IEnumerable<Insight> Update(QCAlgorithmFramework algorithm, Slice data)
             {
                 var insights = new List<Insight>();
                 
@@ -138,7 +141,7 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
                 return insights;
             }
 
-            private void WarmUpIndicators(QCAlgorithm algorithm)
+            private void WarmUpIndicators(QCAlgorithmFramework algorithm)
             {
             	// Make a history call and update the indicators
                 algorithm.History(new[] { _mortgageRate }, _indicatorPeriod, _resolution).PushThrough(bar =>

Algorithm.CSharp/AutoRegressiveIntegratedMovingAverageRegressionAlgorithm.cs

@@ -1,123 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System;
-using System.Collections.Generic;
-using QuantConnect.Data;
-using QuantConnect.Indicators;
-using QuantConnect.Interfaces;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Regression algorithm to test the behaviour of ARMA versus AR models at the same order of differencing.
-    /// In particular, an ARIMA(1,1,1) and ARIMA(1,1,0) are instantiated while orders are placed if their difference
-    /// is sufficiently large (which would be due to the inclusion of the MA(1) term).
-    /// </summary>
-    public class AutoRegressiveIntegratedMovingAverageRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        private AutoRegressiveIntegratedMovingAverage _arima;
-        private AutoRegressiveIntegratedMovingAverage _ar;
-        private decimal _last;
-
-        public override void Initialize()
-        {
-            SetStartDate(2013, 1, 07);
-            SetEndDate(2013, 12, 11);
-
-            EnableAutomaticIndicatorWarmUp = true;
-            AddEquity("SPY", Resolution.Daily);
-            _arima = ARIMA("SPY", 1, 1, 1, 50);
-            _ar = ARIMA("SPY", 1, 1, 0, 50);
-        }
-
-        public override void OnData(Slice slice)
-        {
-            if (_arima.IsReady)
-            {
-                if (Math.Abs(_ar.Current.Value - _arima.Current.Value) > 1) // Difference due to MA(1) being included.
-                {
-                    if (_arima.Current.Value > _last)
-                    {
-                        MarketOrder("SPY", 1);
-                    }
-                    else
-                    {
-                        MarketOrder("SPY", -1);
-                    }
-                }
-
-                _last = _arima.Current.Value;
-            }
-        }
-
-        /// <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>
-        /// 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", "65"},
-            {"Average Win", "0.00%"},
-            {"Average Loss", "0.00%"},
-            {"Compounding Annual Return", "0.145%"},
-            {"Drawdown", "0.100%"},
-            {"Expectancy", "2.190"},
-            {"Net Profit", "0.134%"},
-            {"Sharpe Ratio", "0.993"},
-            {"Probabilistic Sharpe Ratio", "49.669%"},
-            {"Loss Rate", "29%"},
-            {"Win Rate", "71%"},
-            {"Profit-Loss Ratio", "3.50"},
-            {"Alpha", "0.001"},
-            {"Beta", "0"},
-            {"Annual Standard Deviation", "0.001"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-2.168"},
-            {"Tracking Error", "0.099"},
-            {"Treynor Ratio", "-5.187"},
-            {"Total Fees", "$65.00"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "1.51"},
-            {"Return Over Maximum Drawdown", "1.819"},
-            {"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", "c4c9c272037cfd8f6887052b8d739466"}
-        };
-    }
-}

Algorithm.CSharp/AutomaticIndicatorWarmupDataTypeRegressionAlgorithm.cs

@@ -187,7 +187,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "7c841ca58a4385f42236838e5bf0c382"}
+            {"OrderListHash", "-1453269600"}
         };
     }
 }

Algorithm.CSharp/AutomaticIndicatorWarmupRegressionAlgorithm.cs

@@ -149,7 +149,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "25885f979ca8c7b44f5d0f7daf00b241"}
+            {"OrderListHash", "491919591"}
         };
     }
 }

Algorithm.CSharp/BacktestingBrokerageRegressionAlgorithm.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -303,39 +303,21 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "0.400%"},
             {"Expectancy", "-1"},
             {"Net Profit", "-0.323%"},
-            {"Sharpe Ratio", "-11.098"},
+            {"Sharpe Ratio", "-0.888"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.002"},
-            {"Beta", "0.099"},
-            {"Annual Standard Deviation", "0.002"},
+            {"Alpha", "0.035"},
+            {"Beta", "0.183"},
+            {"Annual Standard Deviation", "0.004"},
             {"Annual Variance", "0"},
-            {"Information Ratio", "9.899"},
-            {"Tracking Error", "0.019"},
-            {"Treynor Ratio", "-0.23"},
+            {"Information Ratio", "12.058"},
+            {"Tracking Error", "0.017"},
+            {"Treynor Ratio", "-0.018"},
             {"Total Fees", "$2.00"},
             {"Fitness Score", "0.213"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-73.456"},
-            {"Portfolio Turnover", "0.426"},
-            {"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", "72a6ced0ed0c2da7136f3be652eb4744"}
+            {"OrderListHash", "904167951"}
         };
     }
 }

Algorithm.CSharp/BasicSetAccountCurrencyAlgorithm.cs

@@ -107,7 +107,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "18dc611407abec4ea47092e71f33f983"}
+            {"OrderListHash", "-1575550889"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateAlgorithm.cs

@@ -116,7 +116,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "25885f979ca8c7b44f5d0f7daf00b241"}
+            {"OrderListHash", "491919591"}
         };
     }
-}
+}

Algorithm.CSharp/BasicTemplateCryptoAlgorithm.cs

@@ -242,7 +242,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "1bf1a6d9dd921982b72a6178f9e50e68"}
+            {"OrderListHash", "956597072"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateDailyAlgorithm.cs

@@ -107,7 +107,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "82fee25cd17100c53bb173834ab5f0b2"}
+            {"OrderListHash", "1268340653"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFrameworkAlgorithm.cs

@@ -128,7 +128,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "54.5455%"},
             {"Rolling Averaged Population Direction", "59.8056%"},
             {"Rolling Averaged Population Magnitude", "59.8056%"},
-            {"OrderListHash", "17e29d58e5dabd93569da752c4552c70"}
+            {"OrderListHash", "951346025"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesAlgorithm.cs

@@ -166,7 +166,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "35b3f4b7a225468d42ca085386a2383e"}
+            {"OrderListHash", "-1197265007"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesFrameworkAlgorithm.cs

@@ -174,7 +174,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "18ffd3a774c68da83d867e3b09e3e05d"}
+            {"OrderListHash", "-1624258832"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesHistoryAlgorithm.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -179,7 +179,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
-}
+}

Algorithm.CSharp/BasicTemplateOptionStrategyAlgorithm.cs

@@ -153,7 +153,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "5484aef1443064c826e0071f757cb0f7"}
+            {"OrderListHash", "-702975961"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsAlgorithm.cs

@@ -150,7 +150,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9d9f9248ee8fe30d87ff0a6f6fea5112"}
+            {"OrderListHash", "1130102123"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsFilterUniverseAlgorithm.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -102,7 +102,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Trades", "2"},
+            {"Total Trades", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
             {"Compounding Annual Return", "0%"},
@@ -141,7 +141,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "92d8a50efe230524512404dab66b19dd"}
+            {"OrderListHash", "687310345"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateOptionsFrameworkAlgorithm.cs

@@ -160,7 +160,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Information Ratio", "0"},
             {"Tracking Error", "0"},
             {"Treynor Ratio", "0"},
-            {"Total Fees", "$3.00"},
+            {"Total Fees", "$4.00"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0.327"},
             {"Kelly Criterion Probability Value", "1"},
@@ -180,7 +180,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "50.0482%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "ce06ddfa4b2ffeb666a8910ac8836992"}
+            {"OrderListHash", "352959406"}
         };
     }
 }

Algorithm.CSharp/BlackLittermanPortfolioOptimizationFrameworkAlgorithm.cs

@@ -113,7 +113,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "50%"},
             {"Rolling Averaged Population Direction", "12.6429%"},
             {"Rolling Averaged Population Magnitude", "12.6429%"},
-            {"OrderListHash", "3edd51956c7c97af4863aa6059c11f1a"}
+            {"OrderListHash", "-2004493274"}
         };
     }
 }

Algorithm.CSharp/CBOECustomDataConsolidationRegressionAlgorithm.cs

@@ -1,180 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System;
-using System.Collections.Generic;
-using System.IO;
-using QuantConnect.Data;
-using QuantConnect.Data.Custom.CBOE;
-using QuantConnect.Indicators;
-using QuantConnect.Interfaces;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Tests the consolidation of custom data with random data
-    /// </summary>
-    public class CBOECustomDataConsolidationRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        private Symbol _vix;
-        private BollingerBands _bb;
-        private bool _invested;
-
-        /// <summary>
-        /// Initializes the algorithm with fake VIX data
-        /// </summary>
-        public override void Initialize()
-        {
-            SetStartDate(2013, 10, 7);
-            SetEndDate(2013, 10, 11);
-            SetCash(100000);
-
-            _vix = AddData<IncrementallyGeneratedCustomData>("VIX", Resolution.Daily).Symbol;
-            _bb = BB(_vix, 30, 2, MovingAverageType.Simple, 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)
-        {
-            if (_bb.Current.Value == 0)
-            {
-                throw new Exception("Bollinger Band value is zero when we expect non-zero value.");
-            }
-
-            if (!_invested && _bb.Current.Value > 0.05m)
-            {
-                MarketOrder(_vix, 1);
-                _invested = true;
-            }
-        }
-
-        /// <summary>
-        /// Incrementally updating data
-        /// </summary>
-        private class IncrementallyGeneratedCustomData : CBOE
-        {
-            private const decimal _start = 10.01m;
-            private static decimal _step;
-
-            /// <summary>
-            /// Gets the source of the subscription. In this case, we set it to existing
-            /// equity data so that we can pass fake data from Reader
-            /// </summary>
-            /// <param name="config">Subscription configuration</param>
-            /// <param name="date">Date we're making this request</param>
-            /// <param name="isLiveMode">Is live mode</param>
-            /// <returns>Source of subscription</returns>
-            public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)
-            {
-                return new SubscriptionDataSource(Path.Combine(Globals.DataFolder, "equity", "usa", "minute", "spy", $"{date:yyyyMMdd}_trade.zip#{date:yyyyMMdd}_spy_minute_trade.csv"), SubscriptionTransportMedium.LocalFile, FileFormat.Csv);
-            }
-
-            /// <summary>
-            /// Reads the data, which in this case is fake incremental data
-            /// </summary>
-            /// <param name="config">Subscription configuration</param>
-            /// <param name="line">Line of data</param>
-            /// <param name="date">Date of the request</param>
-            /// <param name="isLiveMode">Is live mode</param>
-            /// <returns>Incremental BaseData instance</returns>
-            public override BaseData Reader(SubscriptionDataConfig config, string line, DateTime date, bool isLiveMode)
-            {
-                var vix = new CBOE();
-                _step += 0.10m;
-                var open = _start + _step;
-                var close = _start + _step + 0.02m;
-                var high = close;
-                var low = open;
-
-                return new IncrementallyGeneratedCustomData
-                {
-                    Open = open,
-                    High = high,
-                    Low = low,
-                    Close = close,
-                    Time = date,
-                    Symbol = new Symbol(
-                        SecurityIdentifier.GenerateBase(typeof(IncrementallyGeneratedCustomData), "VIX", Market.USA, false),
-                        "VIX"),
-                    Period = vix.Period,
-                    DataType = vix.DataType
-                };
-            }
-        }
-
-        /// <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>
-        /// <remarks>
-        /// Unable to be tested in Python, due to pythonnet not supporting overriding of methods from Python
-        /// </remarks>
-        public Language[] Languages { get; } = { Language.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>
-        {
-            {"Total Trades", "1"},
-            {"Average Win", "0%"},
-            {"Average Loss", "0%"},
-            {"Compounding Annual Return", "0.029%"},
-            {"Drawdown", "0%"},
-            {"Expectancy", "0"},
-            {"Net Profit", "0.000%"},
-            {"Sharpe Ratio", "28.4"},
-            {"Probabilistic Sharpe Ratio", "88.597%"},
-            {"Loss Rate", "0%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0"},
-            {"Beta", "0"},
-            {"Annual Standard Deviation", "0"},
-            {"Annual Variance", "0"},
-            {"Information Ratio", "-7.067"},
-            {"Tracking Error", "0.193"},
-            {"Treynor Ratio", "7.887"},
-            {"Total Fees", "$0.00"},
-            {"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", "918912ee4f64cd0290f3d58deca02713"}
-        };
-    }
-}

Algorithm.CSharp/CancelOpenOrdersRegressionAlgorithm.cs

@@ -166,7 +166,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "aea2e321d17414c1f3c6fa2491f10c88"}
+            {"OrderListHash", "1349023435"}
         };
     }
 }

Algorithm.CSharp/CfdTimeZonesRegressionAlgorithm.cs

@@ -114,7 +114,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "6ea6184a2a8d0d69e552ad866933bfb6"}
+            {"OrderListHash", "1456907343"}
         };
     }
 }

Algorithm.CSharp/CoarseFineFundamentalRegressionAlgorithm.cs

@@ -200,7 +200,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "edd9e9ffc8a1cdfb7a1e6ae601e61b12"}
+            {"OrderListHash", "-1465929889"}
         };
     }
 }

Algorithm.CSharp/CoarseFineOptionUniverseChainRegressionAlgorithm.cs

@@ -183,7 +183,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "12470afd9a74ad9c9802361f6f092777"}
+            {"OrderListHash", "1630141557"}
         };
     }
 }

Algorithm.CSharp/CoarseFundamentalTop3Algorithm.cs

@@ -155,7 +155,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "3d1ae61492b34c39115b76757510c058"}
+            {"OrderListHash", "-1623759093"}
         };
     }
 }

Algorithm.CSharp/CoarseNoLookAheadBiasAlgorithm.cs

@@ -133,7 +133,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
 }

Algorithm.CSharp/CoarseSelectionTimeRegressionAlgorithm.cs

@@ -139,7 +139,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "718d73fbddccb63aeacbf4659938b4b8"}
+            {"OrderListHash", "-1959413055"}
         };
     }
 }

Algorithm.CSharp/CompositeAlphaModelFrameworkAlgorithm.cs

@@ -110,7 +110,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "ba44309886ea8ff515ef593a24456c47"}
+            {"OrderListHash", "-28636839"}
         };
     }
 }

Algorithm.CSharp/CompositeRiskManagementModelFrameworkAlgorithm.cs

@@ -104,7 +104,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "54.5455%"},
             {"Rolling Averaged Population Direction", "59.8056%"},
             {"Rolling Averaged Population Magnitude", "59.8056%"},
-            {"OrderListHash", "e0f388bf9e88b34388c866150b292573"}
+            {"OrderListHash", "-1225025518"}
         };
     }
 }

Algorithm.CSharp/ConfidenceWeightedFrameworkAlgorithm.cs

@@ -113,7 +113,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "54.5455%"},
             {"Rolling Averaged Population Direction", "59.8056%"},
             {"Rolling Averaged Population Magnitude", "59.8056%"},
-            {"OrderListHash", "07eb3e2c199575b547459a534057eb5e"}
+            {"OrderListHash", "501060991"}
         };
     }
 }

Algorithm.CSharp/ConsolidateRegressionAlgorithm.cs

@@ -183,7 +183,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "7c841ca58a4385f42236838e5bf0c382"}
+            {"OrderListHash", "-1453269600"}
         };
     }
 }

Algorithm.CSharp/ConstituentsUniverseRegressionAlgorithm.cs

@@ -209,7 +209,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "71984e154883ece4aef1d71bafbfccaf"}
+            {"OrderListHash", "-611289773"}
         };
     }
 }

Algorithm.CSharp/ConvertToFrameworkAlgorithm.cs

@@ -144,7 +144,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.027"},
             {"Information Ratio", "-0.391"},
             {"Tracking Error", "0.239"},
-            {"Treynor Ratio", "-1.435"},
+            {"Treynor Ratio", "-1.416"},
             {"Total Fees", "$755.29"},
             {"Fitness Score", "0.024"},
             {"Kelly Criterion Estimate", "-0.84"},
@@ -165,7 +165,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "48.2217%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "95f34359f25a7a7a2725f0343a75a105"}
+            {"OrderListHash", "1370210213"}
         };
     }
 }

Algorithm.CSharp/CustomBenchmarkAlgorithm.cs

@@ -38,10 +38,6 @@ namespace QuantConnect.Algorithm.CSharp
             // Find more symbols here: http://quantconnect.com/data
             AddSecurity(SecurityType.Equity, "SPY", Resolution.Second);
 
-            // Disabling the benchmark / setting to a fixed value
-            // SetBenchmark(time => 0);
-
-            // Set the benchmark to AAPL US Equity
             SetBenchmark("AAPL");
         }
 
@@ -118,7 +114,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9cd604d2c1e3c273697e2ff2cc7faef1"}
+            {"OrderListHash", "2069976135"}
         };
     }
 }

Algorithm.CSharp/CustomBenchmarkRegressionAlgorithm.cs

@@ -115,7 +115,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "be3334e4aeb9dd7cca4ecc07419d0f95"}
+            {"OrderListHash", "519536519"}
         };
     }
 }

Algorithm.CSharp/CustomBuyingPowerModelAlgorithm.cs

@@ -132,7 +132,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "b88362c462e9ab2942cbcb8dfddc6ce0"}
+            {"OrderListHash", "639761089"}
         };
     }
 }

Algorithm.CSharp/CustomDataAddDataCoarseSelectionRegressionAlgorithm.cs

@@ -138,7 +138,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "6b05339bfcb5bd93bfd66e32a1d2181a"}
+            {"OrderListHash", "559673838"}
         };
     }
 }

Algorithm.CSharp/CustomDataAddDataOnSecuritiesChangedRegressionAlgorithm.cs

@@ -143,7 +143,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "6b05339bfcb5bd93bfd66e32a1d2181a"}
+            {"OrderListHash", "559673838"}
         };
     }
 }

Algorithm.CSharp/CustomDataAddDataRegressionAlgorithm.cs

@@ -150,7 +150,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "214f38f9084bc350c93010aa2fb69822"}
+            {"OrderListHash", "1531253381"}
         };
     }
 }

Algorithm.CSharp/CustomDataPropertiesRegressionAlgorithm.cs

@@ -1,260 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System;
-using System.Collections.Generic;
-using System.Globalization;
-using Newtonsoft.Json;
-using QuantConnect.Data;
-using QuantConnect.Interfaces;
-using QuantConnect.Securities;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Regression test to demonstrate setting custom Symbol Properties and Market Hours for a custom data import
-    /// </summary>
-    /// <meta name="tag" content="using data" />
-    /// <meta name="tag" content="custom data" />
-    /// <meta name="tag" content="crypto" />
-    /// <meta name="tag" content="regression test" />
-    public class CustomDataPropertiesRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        private string _ticker = "BTC";
-        private Security _bitcoin;
-
-        /// <summary>
-        /// Initialize 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(2011, 9, 13);
-            SetEndDate(2015, 12, 01);
-
-            //Set the cash for the strategy:
-            SetCash(100000);
-
-            // Define our custom data properties and exchange hours
-            var properties = new SymbolProperties("Bitcoin", "USD", 1, 0.01m, 0.01m, _ticker);
-            var exchangeHours = SecurityExchangeHours.AlwaysOpen(TimeZones.NewYork);
-
-            // Add the custom data to our algorithm with our custom properties and exchange hours
-            _bitcoin = AddData<Bitcoin>(_ticker, properties, exchangeHours);
-
-            //Verify our symbol properties were changed and loaded into this security
-            if (_bitcoin.SymbolProperties != properties)
-            {
-                throw new Exception("Failed to set and retrieve custom SymbolProperties for BTC");
-            }
-
-            //Verify our exchange hours were changed and loaded into this security
-            if (_bitcoin.Exchange.Hours != exchangeHours)
-            {
-                throw new Exception("Failed to set and retrieve custom ExchangeHours for BTC");
-            }
-
-            // For regression purposes on AddData overloads, this call is simply to ensure Lean can accept this
-            // with default params and is not routed to a breaking function.
-            AddData<Bitcoin>("BTCUSD");
-        }
-
-        /// <summary>
-        /// Event Handler for Bitcoin Data Events: These Bitcoin objects are created from our
-        /// "Bitcoin" type below and fired into this event handler.
-        /// </summary>
-        /// <param name="data">One(1) Bitcoin Object, streamed into our algorithm synchronized in time with our other data streams</param>
-        public void OnData(Bitcoin data)
-        {
-            //If we don't have any bitcoin "SHARES" -- invest"
-            if (!Portfolio.Invested)
-            {
-                //Bitcoin used as a tradable asset, like stocks, futures etc.
-                if (data.Close != 0)
-                {
-                    //Access custom data symbols using <ticker>.<custom-type>
-                    Order("BTC.Bitcoin", Portfolio.MarginRemaining / Math.Abs(data.Close + 1));
-                }
-            }
-        }
-
-        public override void OnEndOfAlgorithm()
-        {
-            // Reset our Symbol property value, for testing purposes.
-            SymbolPropertiesDatabase.SetEntry(Market.USA, MarketHoursDatabase.GetDatabaseSymbolKey(_bitcoin.Symbol), SecurityType.Base,
-                SymbolProperties.GetDefault("USD"));
-        }
-
-        /// <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>
-        /// 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", "155.262%"},
-            {"Drawdown", "84.800%"},
-            {"Expectancy", "0"},
-            {"Net Profit", "5123.242%"},
-            {"Sharpe Ratio", "2.067"},
-            {"Probabilistic Sharpe Ratio", "68.833%"},
-            {"Loss Rate", "0%"},
-            {"Win Rate", "0%"},
-            {"Profit-Loss Ratio", "0"},
-            {"Alpha", "1.732"},
-            {"Beta", "0.037"},
-            {"Annual Standard Deviation", "0.841"},
-            {"Annual Variance", "0.707"},
-            {"Information Ratio", "1.902"},
-            {"Tracking Error", "0.848"},
-            {"Treynor Ratio", "46.992"},
-            {"Total Fees", "$0.00"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "2.238"},
-            {"Return Over Maximum Drawdown", "1.832"},
-            {"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", "1f54fb75ebcc0daafa5d45bfbaa4fbcb"}
-        };
-
-        /// <summary>
-        /// Custom Data Type: Bitcoin data from Quandl - http://www.quandl.com/help/api-for-bitcoin-data
-        /// </summary>
-        public class Bitcoin : BaseData
-        {
-            [JsonProperty("timestamp")]
-            public int Timestamp = 0;
-            [JsonProperty("open")]
-            public decimal Open = 0;
-            [JsonProperty("high")]
-            public decimal High = 0;
-            [JsonProperty("low")]
-            public decimal Low = 0;
-            [JsonProperty("last")]
-            public decimal Close = 0;
-            [JsonProperty("bid")]
-            public decimal Bid = 0;
-            [JsonProperty("ask")]
-            public decimal Ask = 0;
-            [JsonProperty("vwap")]
-            public decimal WeightedPrice = 0;
-            [JsonProperty("volume")]
-            public decimal VolumeBTC = 0;
-            public decimal VolumeUSD = 0;
-
-            /// <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".
-            /// </summary>
-            public Bitcoin()
-            {
-                Symbol = "BTC";
-            }
-
-            /// <summary>
-            /// 2. RETURN THE STRING URL SOURCE LOCATION FOR YOUR DATA:
-            /// This is a powerful and dynamic select source file method. If you have a large dataset, 10+mb we recommend you break it into smaller files. E.g. One zip per year.
-            /// We can accept raw text or ZIP files. We read the file extension to determine if it is a zip file.
-            /// </summary>
-            /// <param name="config">Configuration object</param>
-            /// <param name="date">Date of this source file</param>
-            /// <param name="isLiveMode">true if we're in live mode, false for backtesting mode</param>
-            /// <returns>String URL of source file.</returns>
-            public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)
-            {
-                if (isLiveMode)
-                {
-                    return new SubscriptionDataSource("https://www.bitstamp.net/api/ticker/", SubscriptionTransportMedium.Rest);
-                }
-
-                //return "http://my-ftp-server.com/futures-data-" + date.ToString("Ymd") + ".zip";
-                // OR simply return a fixed small data file. Large files will slow down your backtest
-                return new SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc&api_key=WyAazVXnq7ATy_fefTqm", SubscriptionTransportMedium.RemoteFile);
-            }
-
-            /// <summary>
-            /// 3. READER METHOD: Read 1 line from data source and convert it into Object.
-            /// Each line of the CSV File is presented in here. The backend downloads your file, loads it into memory and then line by line
-            /// feeds it into your algorithm
-            /// </summary>
-            /// <param name="line">string line from the data source file submitted above</param>
-            /// <param name="config">Subscription data, symbol name, data type</param>
-            /// <param name="date">Current date we're requesting. This allows you to break up the data source into daily files.</param>
-            /// <param name="isLiveMode">true if we're in live mode, false for backtesting mode</param>
-            /// <returns>New Bitcoin Object which extends BaseData.</returns>
-            public override BaseData Reader(SubscriptionDataConfig config, string line, DateTime date, bool isLiveMode)
-            {
-                var coin = new Bitcoin();
-                if (isLiveMode)
-                {
-                    //Example Line Format:
-                    //{"high": "441.00", "last": "421.86", "timestamp": "1411606877", "bid": "421.96", "vwap": "428.58", "volume": "14120.40683975", "low": "418.83", "ask": "421.99"}
-                    try
-                    {
-                        coin = JsonConvert.DeserializeObject<Bitcoin>(line);
-                        coin.EndTime = DateTime.UtcNow.ConvertFromUtc(config.ExchangeTimeZone);
-                        coin.Value = coin.Close;
-                    }
-                    catch { /* Do nothing, possible error in json decoding */ }
-                    return coin;
-                }
-
-                //Example Line Format:
-                //Date      Open   High    Low     Close   Volume (BTC)    Volume (Currency)   Weighted Price
-                //2011-09-13 5.8    6.0     5.65    5.97    58.37138238,    346.0973893944      5.929230648356
-                try
-                {
-                    string[] data = line.Split(',');
-                    coin.Time = DateTime.Parse(data[0], CultureInfo.InvariantCulture);
-                    coin.Open = Convert.ToDecimal(data[1], CultureInfo.InvariantCulture);
-                    coin.High = Convert.ToDecimal(data[2], CultureInfo.InvariantCulture);
-                    coin.Low = Convert.ToDecimal(data[3], CultureInfo.InvariantCulture);
-                    coin.Close = Convert.ToDecimal(data[4], CultureInfo.InvariantCulture);
-                    coin.VolumeBTC = Convert.ToDecimal(data[5], CultureInfo.InvariantCulture);
-                    coin.VolumeUSD = Convert.ToDecimal(data[6], CultureInfo.InvariantCulture);
-                    coin.WeightedPrice = Convert.ToDecimal(data[7], CultureInfo.InvariantCulture);
-                    coin.Value = coin.Close;
-                }
-                catch { /* Do nothing, skip first title row */ }
-
-                return coin;
-            }
-        }
-    }
-}

Algorithm.CSharp/CustomDataRegressionAlgorithm.cs

@@ -120,7 +120,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "0e7d560d0db2829adb19d3e403c30d97"}
+            {"OrderListHash", "-541549381"}
         };
 
         /// <summary>

Algorithm.CSharp/CustomDataUsingMapFileRegressionAlgorithm.cs

@@ -160,7 +160,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "1c319ae4b15416184a247bb47b31aabc"}
+            {"OrderListHash", "-1014157203"}
         };
 
         /// <summary>

Algorithm.CSharp/CustomModelsAlgorithm.cs

@@ -231,7 +231,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "71c17655bd0731eb25433727526e95ba"}
+            {"OrderListHash", "852026186"}
         };
     }
 }

Algorithm.CSharp/CustomUniverseSelectionRegressionAlgorithm.cs

@@ -122,7 +122,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "82fee25cd17100c53bb173834ab5f0b2"}
+            {"OrderListHash", "1268340653"}
         };
     }
 }

Algorithm.CSharp/CustomUniverseWithBenchmarkRegressionAlgorithm.cs

@@ -212,7 +212,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
 }

Algorithm.CSharp/DailyHistoryForDailyResolutionRegressionAlgorithm.cs

@@ -137,7 +137,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
 }

Algorithm.CSharp/DailyHistoryForMinuteResolutionRegressionAlgorithm.cs

@@ -137,7 +137,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
 }

Algorithm.CSharp/DaylightSavingTimeHistoryRegressionAlgorithm.cs

@@ -1,4 +1,4 @@
-/*
+/*
  * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  *
@@ -112,7 +112,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
 }

Algorithm.CSharp/DefaultResolutionRegressionAlgorithm.cs

@@ -155,7 +155,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
 }

Algorithm.CSharp/DelistedFutureLiquidateRegressionAlgorithm.cs

@@ -100,25 +100,25 @@ namespace QuantConnect.Algorithm.CSharp
             {"Drawdown", "1.300%"},
             {"Expectancy", "0"},
             {"Net Profit", "1.634%"},
-            {"Sharpe Ratio", "2.495"},
-            {"Probabilistic Sharpe Ratio", "92.298%"},
+            {"Sharpe Ratio", "2.476"},
+            {"Probabilistic Sharpe Ratio", "92.194%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
             {"Alpha", "0.006"},
             {"Beta", "0.158"},
-            {"Annual Standard Deviation", "0.033"},
+            {"Annual Standard Deviation", "0.032"},
             {"Annual Variance", "0.001"},
-            {"Information Ratio", "-4.942"},
+            {"Information Ratio", "-4.89"},
             {"Tracking Error", "0.08"},
-            {"Treynor Ratio", "0.517"},
+            {"Treynor Ratio", "0.509"},
             {"Total Fees", "$3.70"},
             {"Fitness Score", "0.019"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "1.362"},
             {"Return Over Maximum Drawdown", "9.699"},
-            {"Portfolio Turnover", "0.023"},
+            {"Portfolio Turnover", "0.022"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -132,7 +132,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "00d6dc8775da38f7f79defad06de240a"}
+            {"OrderListHash", "-1252326142"}
         };
     }
 }

Algorithm.CSharp/DelistingEventsAlgorithm.cs

@@ -45,7 +45,7 @@ namespace QuantConnect.Algorithm.CSharp
             SetEndDate(2007, 05, 25);    //Set End Date
             SetCash(100000);             //Set Strategy Cash
             // Find more symbols here: http://quantconnect.com/data
-            AddSecurity(SecurityType.Equity, "AAA.1", Resolution.Daily);
+            AddSecurity(SecurityType.Equity, "AAA", Resolution.Daily);
             AddSecurity(SecurityType.Equity, "SPY", Resolution.Daily);
         }
 
@@ -58,7 +58,7 @@ namespace QuantConnect.Algorithm.CSharp
             _dataCount += data.Bars.Count;
             if (Transactions.OrdersCount == 0)
             {
-                SetHoldings("AAA.1", 1);
+                SetHoldings("AAA", 1);
                 Debug("Purchased Stock");
             }
 
@@ -71,7 +71,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             // the slice can also contain delisting data: data.Delistings in a dictionary string->Delisting
 
-            var aaa = Securities["AAA.1"];
+            var aaa = Securities["AAA"];
             if (aaa.IsDelisted && aaa.IsTradable)
             {
                 throw new Exception("Delisted security must NOT be tradable");
@@ -179,7 +179,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "61f4d3c109fc4b6b9eb14d2e4eec4843"}
+            {"OrderListHash", "-2022527947"}
         };
     }
 }

Algorithm.CSharp/DelistingFutureOptionRegressionAlgorithm.cs

@@ -1,148 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System;
-using QuantConnect.Data;
-using QuantConnect.Interfaces;
-using QuantConnect.Securities;
-using System.Collections.Generic;
-using System.Linq;
-
-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
-    /// </summary>
-    public class DelistingFutureOptionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        private bool _traded;
-        private int _lastMonth;
-
-        public override void Initialize()
-        {
-            SetStartDate(2012, 1, 1);
-            SetEndDate(2013, 1, 1);
-            SetCash(10000000);
-
-            var dc = AddFuture(Futures.Dairy.ClassIIIMilk, Resolution.Minute, Market.CME);
-            dc.SetFilter(1, 120);
-
-            AddFutureOption(dc.Symbol, universe => universe.Strikes(-2, 2));
-            _lastMonth = -1;
-        }
-
-        public override void OnData(Slice data)
-        {
-            if (Time.Month != _lastMonth)
-            {
-                _lastMonth = Time.Month;
-                var investedSymbols = Securities.Values
-                    .Where(security => security.Invested)
-                    .Select(security => security.Symbol)
-                    .ToList();
-
-                var delistedSecurity = investedSymbols.Where(symbol => symbol.ID.Date.AddDays(1) < Time).ToList();
-                if (delistedSecurity.Count > 0)
-                {
-                    throw new Exception($"[{UtcTime}] We hold a delisted securities: {string.Join(",", delistedSecurity)}");
-                }
-                Log($"Holdings({Time}): {string.Join(",", investedSymbols)}");
-            }
-
-            if (Portfolio.Invested)
-            {
-                return;
-            }
-
-            foreach (var chain in data.OptionChains.Values)
-            {
-                foreach (var contractsValue in chain.Contracts.Values)
-                {
-                    MarketOrder(contractsValue.Symbol, 1);
-                    _traded = true;
-                }
-            }
-        }
-
-        public override void OnEndOfAlgorithm()
-        {
-            if (!_traded)
-            {
-                throw new Exception("We expected some FOP trading to happen");
-            }
-            if (Portfolio.Invested)
-            {
-                throw new Exception("We shouldn't be invested anymore");
-            }
-        }
-
-        /// <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>
-        /// 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", "16"},
-            {"Average Win", "0.01%"},
-            {"Average Loss", "-0.02%"},
-            {"Compounding Annual Return", "-0.111%"},
-            {"Drawdown", "0.100%"},
-            {"Expectancy", "-0.679"},
-            {"Net Profit", "-0.112%"},
-            {"Sharpe Ratio", "-1.052"},
-            {"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", "-1.187"},
-            {"Tracking Error", "0.115"},
-            {"Treynor Ratio", "1.545"},
-            {"Total Fees", "$37.00"},
-            {"Fitness Score", "0"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.128"},
-            {"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", "de309ab56d2fcd80ff03df2802d9feda"}
-        };
-    }
-}

Algorithm.CSharp/DisplacedMovingAverageRibbon.cs

@@ -205,7 +205,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "7c4fcd79dd817a9cd3bf44525eaed96c"}
+            {"OrderListHash", "-807056289"}
         };
     }
 }

Algorithm.CSharp/DropboxBaseDataUniverseSelectionAlgorithm.cs

@@ -223,7 +223,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "0b6746b5759ecd45ab21360fd40858bb"}
+            {"OrderListHash", "-75671425"}
         };
     }
 }

Algorithm.CSharp/DropboxUniverseSelectionAlgorithm.cs

@@ -196,7 +196,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "a7a893a17a5afa7c2f73a444a7aea507"}
+            {"OrderListHash", "1142077166"}
         };
     }
 }

Algorithm.CSharp/DuplicateSecurityWithBenchmarkRegressionAlgorithm.cs

@@ -129,7 +129,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
 }

Algorithm.CSharp/EmitInsightCryptoCashAccountType.cs

@@ -110,7 +110,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "21ac8e4179b36d9658f0080868c0e552"}
+            {"OrderListHash", "1296183675"}
         };
     }
 }

Algorithm.CSharp/EmitInsightNoAlphaModelAlgorithm.cs

@@ -150,7 +150,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "17245c38f1b192d2041ca1f3e88250be"}
+            {"OrderListHash", "1300818910"}
         };
     }
 }

Algorithm.CSharp/EmitInsightsAlgorithm.cs

@@ -146,7 +146,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "50%"},
             {"Rolling Averaged Population Direction", "50%"},
             {"Rolling Averaged Population Magnitude", "50%"},
-            {"OrderListHash", "4178a84209934b1eb6d03c2267654f32"}
+            {"OrderListHash", "-218498072"}
         };
     }
 }

Algorithm.CSharp/EqualWeightingPortfolioConstructionModelFutureRegressionAlgorithm.cs

@@ -167,7 +167,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "25.058%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "f4c4b763b5ade918cfb7932e276d069f"}
+            {"OrderListHash", "-1105779454"}
         };
     }
 }

Algorithm.CSharp/EquityTickQuoteAdjustedModeRegressionAlgorithm.cs

@@ -85,11 +85,11 @@ namespace QuantConnect.Algorithm.CSharp
         {
             {"Total Trades", "2"},
             {"Average Win", "0%"},
-            {"Average Loss", "-0.12%"},
-            {"Compounding Annual Return", "-9.062%"},
-            {"Drawdown", "0.100%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "-0.500%"},
+            {"Drawdown", "0.000%"},
             {"Expectancy", "-1"},
-            {"Net Profit", "-0.121%"},
+            {"Net Profit", "-0.006%"},
             {"Sharpe Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0%"},
             {"Loss Rate", "100%"},
@@ -103,12 +103,12 @@ namespace QuantConnect.Algorithm.CSharp
             {"Tracking Error", "0.22"},
             {"Treynor Ratio", "0"},
             {"Total Fees", "$6.41"},
-            {"Fitness Score", "0.249"},
+            {"Fitness Score", "0.248"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-79.031"},
-            {"Portfolio Turnover", "0.498"},
+            {"Return Over Maximum Drawdown", "-82.815"},
+            {"Portfolio Turnover", "0.497"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -122,7 +122,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "af92d7f4e0810bc4a95d5ccb5542b438"}
+            {"OrderListHash", "1213851303"}
         };
     }
 }

Algorithm.CSharp/EquityTradeAndQuotesRegressionAlgorithm.cs

@@ -203,7 +203,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "2cd87d138f8f9f5fcab28b6f983f68b1"}
+            {"OrderListHash", "1040964928"}
         };
     }
 }

Algorithm.CSharp/ExtendedMarketHoursHistoryRegressionAlgorithm.cs

@@ -166,7 +166,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "9f381f81ea9939f285b432207fa0d024"}
+            {"OrderListHash", "-1961710414"}
         };
     }
 }

Algorithm.CSharp/ExtendedMarketTradingRegressionAlgorithm.cs

@@ -141,7 +141,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "ee79a87e6a386f5ee620d77b7bfbd964"}
+            {"OrderListHash", "1717552327"}
         };
     }
 }

Algorithm.CSharp/FeeModelNotUsingAccountCurrency.cs

@@ -193,7 +193,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "c84d1ceacb0da30c1c1c0314f9fc850c"}
+            {"OrderListHash", "-1116140375"}
         };
     }
 }

Algorithm.CSharp/FillForwardEnumeratorOutOfOrderBarRegressionAlgorithm.cs

@@ -1,123 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using QuantConnect.Data;
-using QuantConnect.Interfaces;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Regression test algorithm simply fetch and compare data of minute resolution around daylight saving period
-    /// reproduces issue reported in GB issue GH issue https://github.com/QuantConnect/Lean/issues/4925
-    /// related issues https://github.com/QuantConnect/Lean/issues/3707; https://github.com/QuantConnect/Lean/issues/4630
-    /// </summary>
-    public class FillForwardEnumeratorOutOfOrderBarRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        private decimal _exptectedClose = 84.09m;
-        private DateTime _exptectedTime = new DateTime(2008, 3, 10, 9, 30, 0);
-        private Symbol _shy;
-
-        /// <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(2008, 3, 7);
-            SetEndDate(2008, 3, 10);
-            _shy = AddEquity("SHY", Resolution.Minute).Symbol;
-            // just to make debugging easier, less subscriptions
-            SetBenchmark(time => 1);
-        }
-
-        public override void OnData(Slice slice)
-        {
-            var trackingBar = slice.Bars.Values.FirstOrDefault(s => s.Time.Equals(_exptectedTime));
-
-            if (trackingBar != null)
-            {
-                if (!Portfolio.Invested)
-                {
-                    SetHoldings(_shy, 1);
-                }
-
-                if (trackingBar.Close != _exptectedClose)
-                {
-                    throw new Exception(
-                        $"Bar at {_exptectedTime.ToStringInvariant()} closed at price {trackingBar.Close.ToStringInvariant()}; expected {_exptectedClose.ToStringInvariant()}");
-                }
-            }
-        }
-
-        /// <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>
-        /// 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", "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", "$5.93"},
-            {"Fitness Score", "0.499"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-105.726"},
-            {"Portfolio Turnover", "0.998"},
-            {"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", "5315f54b62b2eaf9d587602137d641a5"}
-        };
-    }
-}

Algorithm.CSharp/FillForwardUntilExpiryRegressionAlgorithm.cs

@@ -1,169 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using QuantConnect.Data;
-using QuantConnect.Data.UniverseSelection;
-using QuantConnect.Interfaces;
-using QuantConnect.Securities.Option;
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using QuantConnect.Data.Market;
-using QuantConnect.Securities;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// Regression algorithm checks FillForwardEnumerator should FF the data until it reaches the delisting date
-    /// replicates GH issue https://github.com/QuantConnect/Lean/issues/4872
-    /// </summary>
-    public class FillForwardUntilExpiryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        private DateTime _realEndDate = new DateTime(2014, 06, 07);
-        private SecurityExchange _exchange;
-        private Dictionary<Symbol, HashSet<DateTime>> _options;
-
-        private string[] _contracts =
-        {
-            "TWX   140621P00067500",
-            "TWX   140621C00067500",
-            "TWX   140621C00070000",
-            "TWX   140621P00070000"
-        };
-
-        public override void Initialize()
-        {
-            SetStartDate(2014, 06, 05);
-            SetEndDate(2014, 06, 30);
-
-            _options = new Dictionary<Symbol, HashSet<DateTime>>();
-            var _twxOption = AddOption("TWX", Resolution.Minute);
-            _exchange = _twxOption.Exchange;
-            _twxOption.SetFilter((x) => x
-                .Contracts(c => c.Where(s => _contracts.Contains(s.Value))));
-            SetBenchmark(t => 1);
-        }
-
-        public override void OnData(Slice data)
-        {
-            foreach (var value in data.OptionChains.Values)
-            {
-                foreach (var contact in value.Contracts)
-                {
-                    BaseData bar = null;
-                    QuoteBar quoteBar;
-                    if (bar == null && value.QuoteBars.TryGetValue(contact.Key, out quoteBar))
-                    {
-                        bar = quoteBar;
-                    }
-                    TradeBar tradeBar;
-                    if (bar == null && value.TradeBars.TryGetValue(contact.Key, out tradeBar))
-                    {
-                        bar = tradeBar;
-                    }
-                    if (bar.IsFillForward)
-                    {
-                        _options[contact.Key].Add(value.Time.Date);
-                    }
-                }
-            }
-        }
-
-        public override void OnSecuritiesChanged(SecurityChanges changes)
-        {
-            foreach (var security in changes.AddedSecurities.OfType<Option>())
-            {
-                _options.Add(security.Symbol, new HashSet<DateTime>());
-            }
-        }
-
-        public override void OnEndOfAlgorithm()
-        {
-            if (_options.Count != _contracts.Length)
-            {
-                throw new Exception($"Options weren't setup properly. Expected: {_contracts.Length}");
-            }
-
-            foreach (var option in _options)
-            {
-                for (DateTime date = _realEndDate; date < option.Key.ID.Date; date = date.AddDays(1))
-                {
-                    if (_exchange.Hours.IsDateOpen(date) &&
-                        !option.Value.Contains(date))
-                    {
-                        throw new Exception("Delisted security should be FF until expiry date");
-                    }
-                }
-            }
-        }
-
-        /// <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>
-        /// 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"},
-            {"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/FineFundamentalFilteredUniverseRegressionAlgorithm.cs

@@ -124,7 +124,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "189eee984d524162b9676b83dab4d73c"}
+            {"OrderListHash", "-423205673"}
         };
     }
 }

Algorithm.CSharp/ForexInternalFeedOnDataHigherResolutionRegressionAlgorithm.cs

@@ -172,7 +172,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
 }

Algorithm.CSharp/ForexInternalFeedOnDataSameResolutionRegressionAlgorithm.cs

@@ -176,7 +176,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+            {"OrderListHash", "371857150"}
         };
     }
 }

Algorithm.CSharp/FractionalQuantityRegressionAlgorithm.cs

@@ -137,7 +137,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "2b3ac55337ce5619fc0388ccdac72c54"}
+            {"OrderListHash", "-89452746"}
         };
     }
 }

Algorithm.CSharp/FreePortfolioValueRegressionAlgorithm.cs

@@ -92,12 +92,12 @@ namespace QuantConnect.Algorithm.CSharp
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
             {"Alpha", "0.093"},
-            {"Beta", "-0.099"},
+            {"Beta", "-0.1"},
             {"Annual Standard Deviation", "0.18"},
             {"Annual Variance", "0.032"},
             {"Information Ratio", "-0.001"},
             {"Tracking Error", "0.267"},
-            {"Treynor Ratio", "-0.847"},
+            {"Treynor Ratio", "-0.846"},
             {"Total Fees", "$41.17"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "38.884"},
@@ -118,7 +118,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "43.2962%"},
             {"Rolling Averaged Population Direction", "48.763%"},
             {"Rolling Averaged Population Magnitude", "48.763%"},
-            {"OrderListHash", "0ae9067022a716a31e7bc1cd6dbc3746"}
+            {"OrderListHash", "-1756838669"}
         };
     }
 }

Algorithm.CSharp/FutureOptionBuySellCallIntradayRegressionAlgorithm.cs

@@ -43,6 +43,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             var es20h20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -119,31 +124,31 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "6"},
-            {"Average Win", "2.93%"},
+            {"Average Win", "2.94%"},
             {"Average Loss", "-4.15%"},
-            {"Compounding Annual Return", "-6.023%"},
-            {"Drawdown", "5.700%"},
-            {"Expectancy", "-0.148"},
-            {"Net Profit", "-2.802%"},
-            {"Sharpe Ratio", "-0.501"},
-            {"Probabilistic Sharpe Ratio", "10.679%"},
+            {"Compounding Annual Return", "-5.601%"},
+            {"Drawdown", "5.600%"},
+            {"Expectancy", "-0.146"},
+            {"Net Profit", "-2.771%"},
+            {"Sharpe Ratio", "-0.49"},
+            {"Probabilistic Sharpe Ratio", "10.583%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.70"},
-            {"Alpha", "-0.045"},
+            {"Profit-Loss Ratio", "0.71"},
+            {"Alpha", "-0.043"},
             {"Beta", "-0.001"},
-            {"Annual Standard Deviation", "0.089"},
+            {"Annual Standard Deviation", "0.087"},
             {"Annual Variance", "0.008"},
-            {"Information Ratio", "0.966"},
-            {"Tracking Error", "0.195"},
-            {"Treynor Ratio", "55.977"},
+            {"Information Ratio", "0.96"},
+            {"Tracking Error", "0.192"},
+            {"Treynor Ratio", "58.394"},
             {"Total Fees", "$14.80"},
             {"Fitness Score", "0.018"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.103"},
-            {"Return Over Maximum Drawdown", "-1.063"},
-            {"Portfolio Turnover", "0.045"},
+            {"Sortino Ratio", "-0.096"},
+            {"Return Over Maximum Drawdown", "-0.993"},
+            {"Portfolio Turnover", "0.043"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -157,7 +162,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "fc9eb9b0a644e4890d5ec3d40367d0e1"}
+            {"OrderListHash", "-290004562"}
         };
     }
 }

Algorithm.CSharp/FutureOptionCallITMExpiryRegressionAlgorithm.cs

@@ -16,6 +16,7 @@
 using System;
 using System.Collections.Generic;
 using System.Linq;
+using System.Reflection;
 using QuantConnect.Data;
 using QuantConnect.Interfaces;
 using QuantConnect.Orders;
@@ -45,6 +46,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             _es19m20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -126,7 +132,12 @@ namespace QuantConnect.Algorithm.CSharp
 
         private void AssertFutureOptionOrderExercise(OrderEvent orderEvent, Security future, Security optionContract)
         {
-            var expectedLiquidationTimeUtc = new DateTime(2020, 6, 19, 20, 0, 0);
+            // We expect the liquidation to occur on the day of the delisting (while the market is open),
+            // but currently we liquidate at the next market open (AAPL open) which happens to be
+            // at 9:30:00 Eastern Time. For unknown reasons, the delisting happens two minutes after the
+            // market open.
+            // Read more about the issue affecting this test here: https://github.com/QuantConnect/Lean/issues/4980
+            var expectedLiquidationTimeUtc = new DateTime(2020, 6, 22, 13, 32, 0);
 
             if (orderEvent.Direction == OrderDirection.Sell && future.Holdings.Quantity != 0)
             {
@@ -203,31 +214,31 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "1.22%"},
+            {"Average Win", "1.25%"},
             {"Average Loss", "-7.42%"},
-            {"Compounding Annual Return", "-13.222%"},
+            {"Compounding Annual Return", "-12.413%"},
             {"Drawdown", "6.300%"},
-            {"Expectancy", "-0.417"},
-            {"Net Profit", "-6.282%"},
-            {"Sharpe Ratio", "-1.345"},
-            {"Probabilistic Sharpe Ratio", "0.005%"},
+            {"Expectancy", "-0.416"},
+            {"Net Profit", "-6.257%"},
+            {"Sharpe Ratio", "-1.325"},
+            {"Probabilistic Sharpe Ratio", "0.004%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
             {"Profit-Loss Ratio", "0.17"},
-            {"Alpha", "-0.105"},
+            {"Alpha", "-0.102"},
             {"Beta", "-0.003"},
-            {"Annual Standard Deviation", "0.078"},
+            {"Annual Standard Deviation", "0.076"},
             {"Annual Variance", "0.006"},
-            {"Information Ratio", "0.678"},
-            {"Tracking Error", "0.191"},
-            {"Treynor Ratio", "33.18"},
+            {"Information Ratio", "0.673"},
+            {"Tracking Error", "0.188"},
+            {"Treynor Ratio", "33.559"},
             {"Total Fees", "$7.40"},
             {"Fitness Score", "0.008"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.217"},
-            {"Return Over Maximum Drawdown", "-2.105"},
-            {"Portfolio Turnover", "0.024"},
+            {"Sortino Ratio", "-0.205"},
+            {"Return Over Maximum Drawdown", "-1.983"},
+            {"Portfolio Turnover", "0.023"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -241,7 +252,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "c59d790b89d76f1ad3bb7738b28567c9"}
+            {"OrderListHash", "23301049"}
         };
     }
 }

Algorithm.CSharp/FutureOptionCallITMGreeksExpiryRegressionAlgorithm.cs

@@ -42,6 +42,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             _es19m20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -161,31 +166,31 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "27.44%"},
+            {"Average Win", "28.04%"},
             {"Average Loss", "-62.81%"},
-            {"Compounding Annual Return", "-80.444%"},
-            {"Drawdown", "52.600%"},
-            {"Expectancy", "-0.282"},
-            {"Net Profit", "-52.604%"},
-            {"Sharpe Ratio", "-0.867"},
-            {"Probabilistic Sharpe Ratio", "0.021%"},
+            {"Compounding Annual Return", "-78.165%"},
+            {"Drawdown", "52.400%"},
+            {"Expectancy", "-0.277"},
+            {"Net Profit", "-52.379%"},
+            {"Sharpe Ratio", "-0.865"},
+            {"Probabilistic Sharpe Ratio", "0.019%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.44"},
-            {"Alpha", "-0.611"},
-            {"Beta", "-0.033"},
-            {"Annual Standard Deviation", "0.695"},
-            {"Annual Variance", "0.484"},
-            {"Information Ratio", "-0.513"},
-            {"Tracking Error", "0.718"},
-            {"Treynor Ratio", "18.473"},
+            {"Profit-Loss Ratio", "0.45"},
+            {"Alpha", "-0.596"},
+            {"Beta", "-0.031"},
+            {"Annual Standard Deviation", "0.681"},
+            {"Annual Variance", "0.463"},
+            {"Information Ratio", "-0.514"},
+            {"Tracking Error", "0.703"},
+            {"Treynor Ratio", "18.748"},
             {"Total Fees", "$66.60"},
-            {"Fitness Score", "0.162"},
+            {"Fitness Score", "0.157"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.136"},
-            {"Return Over Maximum Drawdown", "-1.529"},
-            {"Portfolio Turnover", "0.427"},
+            {"Sortino Ratio", "-0.133"},
+            {"Return Over Maximum Drawdown", "-1.492"},
+            {"Portfolio Turnover", "0.411"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -199,7 +204,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "a7f76d1e2d6f27651465217c92deea80"}
+            {"OrderListHash", "151392833"}
         };
     }
 }

Algorithm.CSharp/FutureOptionCallOTMExpiryRegressionAlgorithm.cs

@@ -26,13 +26,11 @@ namespace QuantConnect.Algorithm.CSharp
 {
     /// <summary>
     /// This regression algorithm tests Out of The Money (OTM) future option expiry for calls.
-    /// We expect 2 orders from the algorithm, which are:
+    /// We expect 1 order from the algorithm, which are:
     ///
     ///   * Initial entry, buy ES Call Option (expiring OTM)
     ///     - contract expires worthless, not exercised, so never opened a position in the underlying
     ///
-    ///   * Liquidation of worthless ES call option (expiring OTM)
-    ///
     /// Additionally, we test delistings for future options and assert that our
     /// portfolio holdings reflect the orders the algorithm has submitted.
     /// </summary>
@@ -51,6 +49,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             _es19m20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -180,28 +183,28 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "-4.03%"},
-            {"Compounding Annual Return", "-8.595%"},
+            {"Compounding Annual Return", "-8.088%"},
             {"Drawdown", "4.000%"},
             {"Expectancy", "-1"},
             {"Net Profit", "-4.029%"},
-            {"Sharpe Ratio", "-1.294"},
-            {"Probabilistic Sharpe Ratio", "0.017%"},
+            {"Sharpe Ratio", "-1.274"},
+            {"Probabilistic Sharpe Ratio", "0.015%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.069"},
+            {"Alpha", "-0.066"},
             {"Beta", "-0.002"},
-            {"Annual Standard Deviation", "0.053"},
+            {"Annual Standard Deviation", "0.052"},
             {"Annual Variance", "0.003"},
-            {"Information Ratio", "0.911"},
-            {"Tracking Error", "0.182"},
-            {"Treynor Ratio", "28.46"},
+            {"Information Ratio", "0.9"},
+            {"Tracking Error", "0.179"},
+            {"Treynor Ratio", "28.537"},
             {"Total Fees", "$3.70"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.195"},
-            {"Return Over Maximum Drawdown", "-2.134"},
+            {"Sortino Ratio", "-0.183"},
+            {"Return Over Maximum Drawdown", "-2.007"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -216,7 +219,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "5dc2591837f882d173d2d4852b3b0626"}
+            {"OrderListHash", "-1116221764"}
         };
     }
 }

Algorithm.CSharp/FutureOptionMultipleContractsInDifferentContractMonthsWithSameUnderlyingFutureRegressionAlgorithm.cs

@@ -1,147 +0,0 @@
-/*
- * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
- * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
-*/
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using QuantConnect.Data;
-using QuantConnect.Interfaces;
-
-namespace QuantConnect.Algorithm.CSharp
-{
-    /// <summary>
-    /// This regression test tests for the loading of futures options contracts with a contract month of 2020-03 can live
-    /// and be loaded from the same ZIP file that the 2020-04 contract month Future Option contract lives in.
-    /// </summary>
-    public class FutureOptionMultipleContractsInDifferentContractMonthsWithSameUnderlyingFutureRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
-    {
-        private readonly Dictionary<Symbol, bool> _expectedSymbols = new Dictionary<Symbol, bool>
-        {
-            { CreateOption(new DateTime(2020, 3, 26), OptionRight.Call, 1650), false },
-            { CreateOption(new DateTime(2020, 3, 26), OptionRight.Put, 1540), false },
-            { CreateOption(new DateTime(2020, 2, 25), OptionRight.Call, 1600), false },
-            { CreateOption(new DateTime(2020, 2, 25), OptionRight.Put, 1545), false }
-        };
-
-        public override void Initialize()
-        {
-            SetStartDate(2020, 1, 5);
-            SetEndDate(2020, 1, 6);
-
-            var goldFutures = AddFuture("GC", Resolution.Minute, Market.COMEX);
-            goldFutures.SetFilter(0, 365);
-
-            AddFutureOption(goldFutures.Symbol);
-        }
-
-        public override void OnData(Slice data)
-        {
-            foreach (var symbol in data.QuoteBars.Keys)
-            {
-                if (_expectedSymbols.ContainsKey(symbol))
-                {
-                    var invested = _expectedSymbols[symbol];
-                    if (!invested)
-                    {
-                        MarketOrder(symbol, 1);
-                    }
-
-                    _expectedSymbols[symbol] = true;
-                }
-            }
-        }
-
-        public override void OnEndOfAlgorithm()
-        {
-            var notEncountered = _expectedSymbols.Where(kvp => !kvp.Value).ToList();
-            if (notEncountered.Any())
-            {
-                throw new Exception($"Expected all Symbols encountered and invested in, but the following were not found: {string.Join(", ", notEncountered.Select(kvp => kvp.Value.ToStringInvariant()))}");
-            }
-            if (!Portfolio.Invested)
-            {
-                throw new Exception("Expected holdings at the end of algorithm, but none were found.");
-            }
-        }
-
-        private static Symbol CreateOption(DateTime expiry, OptionRight optionRight, decimal strikePrice)
-        {
-            return QuantConnect.Symbol.CreateOption(
-                QuantConnect.Symbol.CreateFuture("GC", Market.COMEX, new DateTime(2020, 4, 28)),
-                Market.COMEX,
-                OptionStyle.American,
-                optionRight,
-                strikePrice,
-                expiry);
-        }
-
-        /// <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>
-        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
-        /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
-        {
-            {"Total Trades", "4"},
-            {"Average Win", "0%"},
-            {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-8.289%"},
-            {"Drawdown", "3.500%"},
-            {"Expectancy", "0"},
-            {"Net Profit", "-0.047%"},
-            {"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", "-14.395"},
-            {"Tracking Error", "0.043"},
-            {"Treynor Ratio", "0"},
-            {"Total Fees", "$7.40"},
-            {"Fitness Score", "0.019"},
-            {"Kelly Criterion Estimate", "0"},
-            {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-194.237"},
-            {"Portfolio Turnover", "0.038"},
-            {"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", "979e3995c0dbedc46eaf3705e0438bf5"}
-        };
-    }
-}

Algorithm.CSharp/FutureOptionPutITMExpiryRegressionAlgorithm.cs

@@ -46,6 +46,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             _es19m20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -127,7 +132,12 @@ namespace QuantConnect.Algorithm.CSharp
 
         private void AssertFutureOptionOrderExercise(OrderEvent orderEvent, Security future, Security optionContract)
         {
-            var expectedLiquidationTimeUtc = new DateTime(2020, 6, 19, 20, 0, 0);
+            // We expect the liquidation to occur on the day of the delisting (while the market is open),
+            // but currently we liquidate at the next market open (AAPL open) which happens to be
+            // at 9:30:00 Eastern Time. For unknown reasons, the delisting happens two minutes after the
+            // market open.
+            // Read more about the issue affecting this test here: https://github.com/QuantConnect/Lean/issues/4980
+            var expectedLiquidationTimeUtc = new DateTime(2020, 6, 22, 13, 32, 0);
 
             if (orderEvent.Direction == OrderDirection.Buy && future.Holdings.Quantity != 0)
             {
@@ -204,31 +214,31 @@ namespace QuantConnect.Algorithm.CSharp
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Trades", "3"},
-            {"Average Win", "4.15%"},
+            {"Average Win", "4.18%"},
             {"Average Loss", "-8.27%"},
-            {"Compounding Annual Return", "-9.486%"},
-            {"Drawdown", "4.500%"},
-            {"Expectancy", "-0.249"},
-            {"Net Profit", "-4.457%"},
-            {"Sharpe Ratio", "-1.412"},
+            {"Compounding Annual Return", "-8.879%"},
+            {"Drawdown", "4.400%"},
+            {"Expectancy", "-0.247"},
+            {"Net Profit", "-4.432%"},
+            {"Sharpe Ratio", "-1.391"},
             {"Probabilistic Sharpe Ratio", "0.002%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
-            {"Profit-Loss Ratio", "0.50"},
-            {"Alpha", "-0.076"},
+            {"Profit-Loss Ratio", "0.51"},
+            {"Alpha", "-0.073"},
             {"Beta", "-0.002"},
-            {"Annual Standard Deviation", "0.053"},
+            {"Annual Standard Deviation", "0.052"},
             {"Annual Variance", "0.003"},
-            {"Information Ratio", "0.871"},
-            {"Tracking Error", "0.183"},
-            {"Treynor Ratio", "37.798"},
+            {"Information Ratio", "0.863"},
+            {"Tracking Error", "0.179"},
+            {"Treynor Ratio", "38.46"},
             {"Total Fees", "$7.40"},
             {"Fitness Score", "0.008"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.238"},
-            {"Return Over Maximum Drawdown", "-2.128"},
-            {"Portfolio Turnover", "0.024"},
+            {"Sortino Ratio", "-0.224"},
+            {"Return Over Maximum Drawdown", "-2.003"},
+            {"Portfolio Turnover", "0.023"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -242,7 +252,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "d3fa88c3acadb9345ceac76a2dd3b520"}
+            {"OrderListHash", "-675079082"}
         };
     }
 }

Algorithm.CSharp/FutureOptionPutOTMExpiryRegressionAlgorithm.cs

@@ -26,13 +26,11 @@ namespace QuantConnect.Algorithm.CSharp
 {
     /// <summary>
     /// This regression algorithm tests Out of The Money (OTM) future option expiry for puts.
-    /// We expect 2 orders from the algorithm, which are:
+    /// We expect 1 order from the algorithm, which are:
     ///
     ///   * Initial entry, buy ES Put Option (expiring OTM)
     ///     - contract expires worthless, not exercised, so never opened a position in the underlying
     ///
-    ///   * Liquidation of worthless ES Put OTM contract
-    ///
     /// Additionally, we test delistings for future options and assert that our
     /// portfolio holdings reflect the orders the algorithm has submitted.
     /// </summary>
@@ -50,6 +48,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             _es19m20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -179,28 +182,28 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "2"},
             {"Average Win", "0%"},
             {"Average Loss", "-5.12%"},
-            {"Compounding Annual Return", "-10.844%"},
+            {"Compounding Annual Return", "-10.212%"},
             {"Drawdown", "5.100%"},
             {"Expectancy", "-1"},
             {"Net Profit", "-5.116%"},
-            {"Sharpe Ratio", "-1.28"},
-            {"Probabilistic Sharpe Ratio", "0.017%"},
+            {"Sharpe Ratio", "-1.26"},
+            {"Probabilistic Sharpe Ratio", "0.016%"},
             {"Loss Rate", "100%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.086"},
+            {"Alpha", "-0.084"},
             {"Beta", "-0.003"},
-            {"Annual Standard Deviation", "0.067"},
+            {"Annual Standard Deviation", "0.066"},
             {"Annual Variance", "0.004"},
-            {"Information Ratio", "0.794"},
-            {"Tracking Error", "0.187"},
-            {"Treynor Ratio", "28.078"},
+            {"Information Ratio", "0.785"},
+            {"Tracking Error", "0.184"},
+            {"Treynor Ratio", "28.158"},
             {"Total Fees", "$3.70"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
-            {"Sortino Ratio", "-0.193"},
-            {"Return Over Maximum Drawdown", "-2.12"},
+            {"Sortino Ratio", "-0.181"},
+            {"Return Over Maximum Drawdown", "-1.995"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -215,7 +218,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "a35054d03fd2caa0a96cbe12e427e928"}
+            {"OrderListHash", "515984318"}
         };
     }
 }

Algorithm.CSharp/FutureOptionShortCallITMExpiryRegressionAlgorithm.cs

@@ -46,6 +46,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             _es19m20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -189,29 +194,29 @@ namespace QuantConnect.Algorithm.CSharp
         {
             {"Total Trades", "3"},
             {"Average Win", "10.05%"},
-            {"Average Loss", "-5.63%"},
-            {"Compounding Annual Return", "8.619%"},
+            {"Average Loss", "-5.60%"},
+            {"Compounding Annual Return", "8.121%"},
             {"Drawdown", "0.500%"},
-            {"Expectancy", "0.393"},
-            {"Net Profit", "3.855%"},
-            {"Sharpe Ratio", "1.212"},
-            {"Probabilistic Sharpe Ratio", "59.039%"},
+            {"Expectancy", "0.396"},
+            {"Net Profit", "3.880%"},
+            {"Sharpe Ratio", "1.192"},
+            {"Probabilistic Sharpe Ratio", "58.203%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
             {"Profit-Loss Ratio", "1.79"},
-            {"Alpha", "0.071"},
+            {"Alpha", "0.069"},
             {"Beta", "0.003"},
-            {"Annual Standard Deviation", "0.058"},
+            {"Annual Standard Deviation", "0.057"},
             {"Annual Variance", "0.003"},
-            {"Information Ratio", "1.663"},
-            {"Tracking Error", "0.183"},
-            {"Treynor Ratio", "22.266"},
+            {"Information Ratio", "1.641"},
+            {"Tracking Error", "0.18"},
+            {"Treynor Ratio", "22.101"},
             {"Total Fees", "$7.40"},
             {"Fitness Score", "0.021"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "18.319"},
+            {"Return Over Maximum Drawdown", "17.255"},
             {"Portfolio Turnover", "0.021"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -226,7 +231,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "8e380e4d5c5e3e145ba388f7853829bb"}
+            {"OrderListHash", "1118389718"}
         };
     }
 }

Algorithm.CSharp/FutureOptionShortCallOTMExpiryRegressionAlgorithm.cs

@@ -26,13 +26,11 @@ namespace QuantConnect.Algorithm.CSharp
 {
     /// <summary>
     /// This regression algorithm tests Out of The Money (OTM) future option expiry for short calls.
-    /// We expect 2 orders from the algorithm, which are:
+    /// We expect 1 order from the algorithm, which are:
     ///
     ///   * Initial entry, sell ES Call Option (expiring OTM)
     ///     - Profit the option premium, since the option was not assigned.
     ///
-    ///   * Liquidation of ES call OTM contract on the last trade date
-    ///
     /// Additionally, we test delistings for future options and assert that our
     /// portfolio holdings reflect the orders the algorithm has submitted.
     /// </summary>
@@ -47,6 +45,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             _es19m20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -173,28 +176,28 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "2"},
             {"Average Win", "1.81%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "3.996%"},
+            {"Compounding Annual Return", "3.745%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "0"},
             {"Net Profit", "1.809%"},
-            {"Sharpe Ratio", "1.315"},
-            {"Probabilistic Sharpe Ratio", "66.818%"},
+            {"Sharpe Ratio", "1.292"},
+            {"Probabilistic Sharpe Ratio", "65.890%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.032"},
+            {"Alpha", "0.031"},
             {"Beta", "0.001"},
             {"Annual Standard Deviation", "0.024"},
             {"Annual Variance", "0.001"},
-            {"Information Ratio", "1.516"},
-            {"Tracking Error", "0.176"},
-            {"Treynor Ratio", "27.339"},
+            {"Information Ratio", "1.496"},
+            {"Tracking Error", "0.173"},
+            {"Treynor Ratio", "27.281"},
             {"Total Fees", "$3.70"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "101.571"},
+            {"Return Over Maximum Drawdown", "95.176"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -209,7 +212,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "35baadd70ec72c735eadbf55d702fe04"}
+            {"OrderListHash", "1364902860"}
         };
     }
 }

Algorithm.CSharp/FutureOptionShortPutITMExpiryRegressionAlgorithm.cs

@@ -46,6 +46,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             _es19m20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -186,30 +191,30 @@ namespace QuantConnect.Algorithm.CSharp
         {
             {"Total Trades", "3"},
             {"Average Win", "10.18%"},
-            {"Average Loss", "-8.05%"},
-            {"Compounding Annual Return", "2.902%"},
+            {"Average Loss", "-8.02%"},
+            {"Compounding Annual Return", "2.773%"},
             {"Drawdown", "0.500%"},
-            {"Expectancy", "0.133"},
-            {"Net Profit", "1.318%"},
-            {"Sharpe Ratio", "0.95"},
-            {"Probabilistic Sharpe Ratio", "47.360%"},
+            {"Expectancy", "0.135"},
+            {"Net Profit", "1.343%"},
+            {"Sharpe Ratio", "0.939"},
+            {"Probabilistic Sharpe Ratio", "46.842%"},
             {"Loss Rate", "50%"},
             {"Win Rate", "50%"},
             {"Profit-Loss Ratio", "1.27"},
-            {"Alpha", "0.024"},
+            {"Alpha", "0.023"},
             {"Beta", "0.002"},
             {"Annual Standard Deviation", "0.025"},
             {"Annual Variance", "0.001"},
-            {"Information Ratio", "1.467"},
-            {"Tracking Error", "0.176"},
-            {"Treynor Ratio", "14.729"},
+            {"Information Ratio", "1.45"},
+            {"Tracking Error", "0.173"},
+            {"Treynor Ratio", "14.62"},
             {"Total Fees", "$7.40"},
-            {"Fitness Score", "0.022"},
+            {"Fitness Score", "0.021"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "6.087"},
-            {"Portfolio Turnover", "0.023"},
+            {"Return Over Maximum Drawdown", "5.815"},
+            {"Portfolio Turnover", "0.022"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
             {"Total Insights Analysis Completed", "0"},
@@ -223,7 +228,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "519cc7c39703b6e6913dbe98468da872"}
+            {"OrderListHash", "980293281"}
         };
     }
 }

Algorithm.CSharp/FutureOptionShortPutOTMExpiryRegressionAlgorithm.cs

@@ -26,13 +26,11 @@ namespace QuantConnect.Algorithm.CSharp
 {
     /// <summary>
     /// This regression algorithm tests Out of The Money (OTM) future option expiry for short puts.
-    /// We expect 2 order from the algorithm, which are:
+    /// We expect 1 order from the algorithm, which are:
     ///
     ///   * Initial entry, sell ES Put Option (expiring OTM)
     ///     - Profit the option premium, since the option was not assigned.
     ///
-    ///   * Liquidation of ES put OTM contract on the last trade date
-    ///
     /// Additionally, we test delistings for future options and assert that our
     /// portfolio holdings reflect the orders the algorithm has submitted.
     /// </summary>
@@ -47,6 +45,11 @@ namespace QuantConnect.Algorithm.CSharp
             SetStartDate(2020, 1, 5);
             SetEndDate(2020, 6, 30);
 
+            // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
+            // which causes delisting events to never be processed, thus leading to options that might never
+            // be exercised until the next data point arrives.
+            AddEquity("AAPL", Resolution.Daily);
+
             _es19m20 = AddFutureContract(
                 QuantConnect.Symbol.CreateFuture(
                     Futures.Indices.SP500EMini,
@@ -172,28 +175,28 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "2"},
             {"Average Win", "3.28%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "7.317%"},
+            {"Compounding Annual Return", "6.852%"},
             {"Drawdown", "0.000%"},
             {"Expectancy", "0"},
             {"Net Profit", "3.284%"},
-            {"Sharpe Ratio", "1.343"},
-            {"Probabilistic Sharpe Ratio", "67.503%"},
+            {"Sharpe Ratio", "1.319"},
+            {"Probabilistic Sharpe Ratio", "66.574%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "0.06"},
+            {"Alpha", "0.058"},
             {"Beta", "0.002"},
-            {"Annual Standard Deviation", "0.044"},
+            {"Annual Standard Deviation", "0.043"},
             {"Annual Variance", "0.002"},
-            {"Information Ratio", "1.636"},
-            {"Tracking Error", "0.179"},
-            {"Treynor Ratio", "28.253"},
+            {"Information Ratio", "1.614"},
+            {"Tracking Error", "0.176"},
+            {"Treynor Ratio", "28.2"},
             {"Total Fees", "$3.70"},
             {"Fitness Score", "0"},
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "160.505"},
+            {"Return Over Maximum Drawdown", "150.252"},
             {"Portfolio Turnover", "0"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -208,7 +211,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "5571280f1efb15dd3899896fb72385ff"}
+            {"OrderListHash", "-418839052"}
         };
     }
 }