Make SignalExportManager skip non-tradeable securities (#8453)

* First approach

* Fix bug

* Address requests

* Address requests

.github/workflows/virtual-environments.yml

@@ -48,10 +48,10 @@ jobs:
             dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.TensorflowProbabilityTest" --blame-hang-timeout 120seconds --blame-crash && \
             # Run Hvplot Python Package Test
             dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.HvplotTest" --blame-hang-timeout 120seconds --blame-crash && \
-            # Run Keras Python Package Test
-            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.KerasTest" --blame-hang-timeout 120seconds --blame-crash && \
             # Run Transformers
             dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.Transformers" --blame-hang-timeout 120seconds --blame-crash && \
             dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.XTransformers" --blame-hang-timeout 120seconds --blame-crash && \
             # Run Shap
-            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.ShapTest" --blame-hang-timeout 120seconds --blame-crash
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.ShapTest|KerasTest|PyvinecopulibTest" --blame-hang-timeout 120seconds --blame-crash && \
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.Mlforecast" --blame-hang-timeout 120seconds --blame-crash && \
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.MlxtendTest|Thinc" --blame-hang-timeout 120seconds --blame-crash

Algorithm.CSharp/AddFutureContractWithContinuousRegressionAlgorithm.cs

@@ -115,7 +115,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 73;
+        public long DataPoints => 76;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/AddFutureOptionContractDataStreamingRegressionAlgorithm.cs

@@ -164,7 +164,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 311879;
+        public long DataPoints => 311881;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/AddFutureOptionContractFromFutureChainRegressionAlgorithm.cs

@@ -93,7 +93,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 12169;
+        public long DataPoints => 12172;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/AddFutureOptionSingleOptionChainSelectedInUniverseFilterRegressionAlgorithm.cs

@@ -220,7 +220,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 608377;
+        public long DataPoints => 608380;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/AddOptionContractFromUniverseRegressionAlgorithm.cs

@@ -117,7 +117,7 @@ namespace QuantConnect.Algorithm.CSharp
                                                       && optionContract.ID.OptionStyle == OptionStyle.American);
                 AddOptionContract(option);
 
-                foreach (var symbol in new[] { option.Symbol, option.Underlying.Symbol })
+                foreach (var symbol in new[] { option.Symbol, option.UnderlyingSymbol })
                 {
                     var config = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol).ToList();
 

Algorithm.CSharp/BasicTemplateContinuousFutureAlgorithm.cs

@@ -118,7 +118,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 713369;
+        public long DataPoints => 713375;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/BasicTemplateContinuousFutureWithExtendedMarketAlgorithm.cs

@@ -123,7 +123,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 2217299;
+        public long DataPoints => 2217328;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/BasicTemplateEurexFuturesAlgorithm.cs

@@ -190,7 +190,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 133945;
+        public long DataPoints => 133947;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/BasicTemplateFutureRolloverAlgorithm.cs

@@ -176,7 +176,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 1190;
+        public long DataPoints => 1199;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/BasicTemplateFuturesDailyAlgorithm.cs

@@ -117,7 +117,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 12452;
+        public virtual long DataPoints => 12455;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -134,33 +134,33 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Orders", "32"},
+            {"Total Orders", "34"},
             {"Average Win", "0.33%"},
             {"Average Loss", "-0.04%"},
-            {"Compounding Annual Return", "0.110%"},
+            {"Compounding Annual Return", "0.106%"},
             {"Drawdown", "0.300%"},
-            {"Expectancy", "0.184"},
+            {"Expectancy", "0.178"},
             {"Start Equity", "1000000"},
-            {"End Equity", "1001108"},
-            {"Net Profit", "0.111%"},
-            {"Sharpe Ratio", "-1.688"},
-            {"Sortino Ratio", "-0.772"},
-            {"Probabilistic Sharpe Ratio", "14.944%"},
+            {"End Equity", "1001066.2"},
+            {"Net Profit", "0.107%"},
+            {"Sharpe Ratio", "-1.695"},
+            {"Sortino Ratio", "-0.804"},
+            {"Probabilistic Sharpe Ratio", "14.797%"},
             {"Loss Rate", "88%"},
             {"Win Rate", "12%"},
-            {"Profit-Loss Ratio", "8.47"},
+            {"Profit-Loss Ratio", "9.01"},
             {"Alpha", "-0.007"},
             {"Beta", "0.002"},
             {"Annual Standard Deviation", "0.004"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-1.353"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "-4.099"},
-            {"Total Fees", "$72.00"},
+            {"Treynor Ratio", "-4.112"},
+            {"Total Fees", "$76.30"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
-            {"Portfolio Turnover", "0.87%"},
-            {"OrderListHash", "168731c8f3a19f230cc1410818b3b573"}
+            {"Portfolio Turnover", "0.92%"},
+            {"OrderListHash", "7afa589d648c3f24253cd59156a2014e"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesFrameworkWithExtendedMarketAlgorithm.cs

@@ -41,7 +41,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 163415;
+        public override long DataPoints => 163416;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm

Algorithm.CSharp/BasicTemplateFuturesHourlyAlgorithm.cs

@@ -41,7 +41,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 87289;
+        public override long DataPoints => 87292;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketDailyAlgorithm.cs

@@ -14,14 +14,7 @@
  *
 */
 
-using System;
 using System.Collections.Generic;
-using System.Linq;
-using QuantConnect.Data;
-using QuantConnect.Interfaces;
-using QuantConnect.Orders;
-using QuantConnect.Securities;
-using QuantConnect.Securities.Future;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -43,40 +36,40 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 14790;
+        public override long DataPoints => 14884;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
         public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Orders", "36"},
+            {"Total Orders", "32"},
             {"Average Win", "0.33%"},
-            {"Average Loss", "-0.03%"},
-            {"Compounding Annual Return", "0.102%"},
+            {"Average Loss", "-0.04%"},
+            {"Compounding Annual Return", "0.110%"},
             {"Drawdown", "0.300%"},
-            {"Expectancy", "0.171"},
+            {"Expectancy", "0.184"},
             {"Start Equity", "1000000"},
-            {"End Equity", "1001024.4"},
-            {"Net Profit", "0.102%"},
-            {"Sharpe Ratio", "-1.702"},
-            {"Sortino Ratio", "-0.836"},
-            {"Probabilistic Sharpe Ratio", "14.653%"},
-            {"Loss Rate", "89%"},
-            {"Win Rate", "11%"},
-            {"Profit-Loss Ratio", "9.54"},
+            {"End Equity", "1001108"},
+            {"Net Profit", "0.111%"},
+            {"Sharpe Ratio", "-1.688"},
+            {"Sortino Ratio", "-0.772"},
+            {"Probabilistic Sharpe Ratio", "14.944%"},
+            {"Loss Rate", "88%"},
+            {"Win Rate", "12%"},
+            {"Profit-Loss Ratio", "8.47"},
             {"Alpha", "-0.007"},
             {"Beta", "0.002"},
             {"Annual Standard Deviation", "0.004"},
             {"Annual Variance", "0"},
             {"Information Ratio", "-1.353"},
             {"Tracking Error", "0.089"},
-            {"Treynor Ratio", "-4.126"},
-            {"Total Fees", "$80.60"},
+            {"Treynor Ratio", "-4.099"},
+            {"Total Fees", "$72.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "ES VRJST036ZY0X"},
-            {"Portfolio Turnover", "0.97%"},
-            {"OrderListHash", "52c852d720692fab1e12212b2aba03d4"}
+            {"Portfolio Turnover", "0.87%"},
+            {"OrderListHash", "ef59fd5e4a7ae483a60d25736cf5d2d8"}
         };
     }
 }

Algorithm.CSharp/BasicTemplateFuturesWithExtendedMarketHourlyAlgorithm.cs

@@ -41,7 +41,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 228834;
+        public override long DataPoints => 228935;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm

Algorithm.CSharp/CallbackCommandRegressionAlgorithm.cs

@@ -0,0 +1,159 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using QuantConnect.Commands;
+using QuantConnect.Interfaces;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting the behavior of different callback commands call
+    /// </summary>
+    public class CallbackCommandRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 07);
+            SetEndDate(2013, 10, 11);
+
+            AddEquity("SPY");
+            AddEquity("BAC");
+            AddEquity("IBM");
+            AddCommand<BoolCommand>();
+            AddCommand<VoidCommand>();
+
+            var potentialCommand = new VoidCommand
+            {
+                Target = new[] { "BAC" },
+                Quantity = 10,
+                Parameters = new() { { "tag", "Signal X" } }
+            };
+            var commandLink = Link(potentialCommand);
+            Notify.Email("email@address", "Trade Command Event", $"Signal X trade\nFollow link to trigger: {commandLink}");
+
+            var commandLink2 = Link(new { Symbol = "SPY", Parameters = new Dictionary<string, int>() { { "Quantity", 10 } } });
+            Notify.Email("email@address", "Untyped Command Event", $"Signal Y trade\nFollow link to trigger: {commandLink2}");
+        }
+
+        /// <summary>
+        /// Handle generic command callback
+        /// </summary>
+        public override bool? OnCommand(dynamic data)
+        {
+            Buy(data.Symbol, data.parameters["quantity"]);
+            return true;
+        }
+
+        private class VoidCommand : Command
+        {
+            public DateTime TargetTime { get; set; }
+            public string[] Target { get; set; }
+            public decimal Quantity { get; set; }
+            public Dictionary<string, string> Parameters { get; set; }
+            public override bool? Run(IAlgorithm algorithm)
+            {
+                if (TargetTime != algorithm.Time)
+                {
+                    return null;
+                }
+
+                ((QCAlgorithm)algorithm).Order(Target[0], Quantity, tag: Parameters["tag"]);
+                return null;
+            }
+        }
+        private class BoolCommand : Command
+        {
+            public bool? Result { get; set; }
+            public override bool? Run(IAlgorithm algorithm)
+            {
+                var shouldTrade = MyCustomMethod();
+                if (shouldTrade.HasValue && shouldTrade.Value)
+                {
+                    ((QCAlgorithm)algorithm).Buy("IBM", 1);
+                }
+                return shouldTrade;
+            }
+
+            private bool? MyCustomMethod()
+            {
+                return Result;
+            }
+        }
+
+        /// <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; }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 3943;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "1"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "271.453%"},
+            {"Drawdown", "2.200%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "101691.92"},
+            {"Net Profit", "1.692%"},
+            {"Sharpe Ratio", "8.854"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "67.609%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.005"},
+            {"Beta", "0.996"},
+            {"Annual Standard Deviation", "0.222"},
+            {"Annual Variance", "0.049"},
+            {"Information Ratio", "-14.565"},
+            {"Tracking Error", "0.001"},
+            {"Treynor Ratio", "1.97"},
+            {"Total Fees", "$3.44"},
+            {"Estimated Strategy Capacity", "$56000000.00"},
+            {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
+            {"Portfolio Turnover", "19.93%"},
+            {"OrderListHash", "3da9fa60bf95b9ed148b95e02e0cfc9e"}
+        };
+    }
+}

Algorithm.CSharp/ConsolidateHourBarsIntoDailyBarsRegressionAlgorithm.cs

@@ -0,0 +1,166 @@
+/*
+ * 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.Indicators;
+using QuantConnect.Interfaces;
+using System;
+using System.Collections.Generic;
+using QuantConnect.Data.Market;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This regression algorithm asserts the consolidated US equity daily bars from the hour bars exactly matches
+    /// the daily bars returned from the database
+    /// </summary>
+    public class ConsolidateHourBarsIntoDailyBarsRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _spy;
+        private RelativeStrengthIndex _rsi;
+        private RelativeStrengthIndex _rsiTimeDelta;
+        private Dictionary<DateTime, decimal> _values = new();
+        private int _count;
+        private bool _indicatorsCompared;
+
+        public override void Initialize()
+        {
+            SetStartDate(2020, 5, 1);
+            SetEndDate(2020, 6, 5);
+
+            _spy = AddEquity("SPY", Resolution.Hour).Symbol;
+
+            // We will use these two indicators to compare the daily consolidated bars equals
+            // the ones returned from the database. We use this specific type of indicator as
+            // it depends on its previous values. Thus, if at some point the bars received by
+            // the indicators differ, so will their final values
+            _rsi = new RelativeStrengthIndex("FIRST", 15, MovingAverageType.Wilders);
+            RegisterIndicator(_spy, _rsi, Resolution.Daily, selector: (bar) =>
+            {
+                var tradeBar = (TradeBar)bar;
+                return (tradeBar.Close + tradeBar.Open) / 2;
+            });
+
+            // We won't register this indicator as we will update it manually at the end of the
+            // month, so that we can compare the values of the indicator that received consolidated
+            // bars and the values of this one
+            _rsiTimeDelta = new RelativeStrengthIndex("SECOND" ,15, MovingAverageType.Wilders);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (IsWarmingUp) return;
+
+            if (slice.ContainsKey(_spy) && slice[_spy] != null)
+            {
+                if (Time.Month == EndDate.Month)
+                {
+                    var history = History(_spy, _count, Resolution.Daily);
+                    foreach (var bar in history)
+                    {
+                        var time = bar.EndTime.Date;
+                        var average = (bar.Close + bar.Open) / 2;
+                        _rsiTimeDelta.Update(bar.EndTime, average);
+                        if (_rsiTimeDelta.Current.Value != _values[time])
+                        {
+                            throw new RegressionTestException($"Both {_rsi.Name} and {_rsiTimeDelta.Name} should have the same values, but they differ. {_rsi.Name}: {_values[time]} | {_rsiTimeDelta.Name}: {_rsiTimeDelta.Current.Value}");
+                        }
+                    }
+                    _indicatorsCompared = true;
+                    Quit();
+                }
+                else
+                {
+                    _values[Time.Date] = _rsi.Current.Value;
+
+                    // Since the symbol resolution is hour and the symbol is equity, we know the last bar received in a day will
+                    // be at the market close, this is 16h. We need to count how many daily bars were consolidated in order to know
+                    // how many we need to request from the history
+                    if (Time.Hour == 16)
+                    {
+                        _count++;
+                    }
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_indicatorsCompared)
+            {
+                throw new RegressionTestException($"Indicators {_rsi.Name} and {_rsiTimeDelta.Name} should have been compared, but they were not. Please make sure the indicators are getting SPY data");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 290;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 20;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-5.215"},
+            {"Tracking Error", "0.159"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/ConsolidateRegressionAlgorithm.cs

@@ -22,6 +22,7 @@ using QuantConnect.Data.Market;
 using QuantConnect.Indicators;
 using QuantConnect.Interfaces;
 using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -31,69 +32,83 @@ namespace QuantConnect.Algorithm.CSharp
     public class ConsolidateRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
         private List<int> _consolidationCounts;
+        private List<int> _expectedConsolidationCounts;
         private List<SimpleMovingAverage> _smas;
         private List<DateTime> _lastSmaUpdates;
-        private int _expectedConsolidations;
-        private int _customDataConsolidator;
-        private Symbol _symbol;
+        private int _customDataConsolidatorCount;
+        private Future _future;
 
         /// <summary>
         /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
         /// </summary>
         public override void Initialize()
         {
-            SetStartDate(2013, 10, 08);
-            SetEndDate(2013, 10, 20);
+            SetStartDate(2020, 01, 05);
+            SetEndDate(2020, 01, 20);
 
             var SP500 = QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME);
-            _symbol = FutureChainProvider.GetFutureContractList(SP500, StartDate).First();
-            var security = AddFutureContract(_symbol);
+            var symbol = FutureChainProvider.GetFutureContractList(SP500, StartDate).First();
+            _future = AddFutureContract(symbol);
 
-            _consolidationCounts = Enumerable.Repeat(0, 9).ToList();
+            var tradableDatesCount = QuantConnect.Time.EachTradeableDayInTimeZone(_future.Exchange.Hours,
+                StartDate,
+                EndDate,
+                _future.Exchange.TimeZone,
+                false).Count();
+            _expectedConsolidationCounts = new(10);
+
+            Consolidate<QuoteBar>(symbol, time => new CalendarInfo(time.RoundDown(TimeSpan.FromDays(1)), TimeSpan.FromDays(1)),
+                bar => UpdateQuoteBar(bar, 0));
+            // The consolidator will respect the full 1 day bar span and will not consolidate the last tradable date,
+            // since scan will not be called at 202/01/21 12am
+            _expectedConsolidationCounts.Add(tradableDatesCount - 1);
+
+            Consolidate<QuoteBar>(symbol, time => new CalendarInfo(time.RoundDown(TimeSpan.FromDays(1)), TimeSpan.FromDays(1)),
+                TickType.Quote, bar => UpdateQuoteBar(bar, 1));
+            _expectedConsolidationCounts.Add(tradableDatesCount - 1);
+
+            Consolidate<QuoteBar>(symbol, TimeSpan.FromDays(1), bar => UpdateQuoteBar(bar, 2));
+            _expectedConsolidationCounts.Add(tradableDatesCount - 1);
+
+            Consolidate(symbol, Resolution.Daily, TickType.Quote, (Action<QuoteBar>)(bar => UpdateQuoteBar(bar, 3)));
+            _expectedConsolidationCounts.Add(tradableDatesCount);
+
+            Consolidate(symbol, TimeSpan.FromDays(1), bar => UpdateTradeBar(bar, 4));
+            _expectedConsolidationCounts.Add(tradableDatesCount - 1);
+
+            Consolidate<TradeBar>(symbol, TimeSpan.FromDays(1), bar => UpdateTradeBar(bar, 5));
+            _expectedConsolidationCounts.Add(tradableDatesCount - 1);
+
+            // Test using abstract T types, through defining a 'BaseData' handler
+
+            Consolidate(symbol, Resolution.Daily, null, (Action<BaseData>)(bar => UpdateBar(bar, 6)));
+            _expectedConsolidationCounts.Add(tradableDatesCount);
+
+            Consolidate(symbol, TimeSpan.FromDays(1), null, (Action<BaseData>)(bar => UpdateBar(bar, 7)));
+            _expectedConsolidationCounts.Add(tradableDatesCount - 1);
+
+            Consolidate(symbol, TimeSpan.FromDays(1), (Action<BaseData>)(bar => UpdateBar(bar, 8)));
+            _expectedConsolidationCounts.Add(tradableDatesCount - 1);
+
+            _consolidationCounts = Enumerable.Repeat(0, _expectedConsolidationCounts.Count).ToList();
             _smas = _consolidationCounts.Select(_ => new SimpleMovingAverage(10)).ToList();
             _lastSmaUpdates = _consolidationCounts.Select(_ => DateTime.MinValue).ToList();
 
-            Consolidate<QuoteBar>(_symbol, time => new CalendarInfo(time.RoundDown(TimeSpan.FromDays(1)), TimeSpan.FromDays(1)),
-                bar => UpdateQuoteBar(bar, 0));
-
-            Consolidate<QuoteBar>(_symbol, time => new CalendarInfo(time.RoundDown(TimeSpan.FromDays(1)), TimeSpan.FromDays(1)),
-                TickType.Quote, bar => UpdateQuoteBar(bar, 1));
-
-            Consolidate<QuoteBar>(_symbol, TimeSpan.FromDays(1), bar => UpdateQuoteBar(bar, 2));
-
-            Consolidate(_symbol, Resolution.Daily, TickType.Quote, (Action<QuoteBar>)(bar => UpdateQuoteBar(bar, 3)));
-
-            Consolidate(_symbol, TimeSpan.FromDays(1), bar => UpdateTradeBar(bar, 4));
-
-            Consolidate<TradeBar>(_symbol, TimeSpan.FromDays(1), bar => UpdateTradeBar(bar, 5));
-
             // custom data
-            var symbol = AddData<CustomDataRegressionAlgorithm.Bitcoin>("BTC", Resolution.Minute).Symbol;
-            Consolidate<TradeBar>(symbol, TimeSpan.FromDays(1), bar => _customDataConsolidator++);
+            var customSecurity = AddData<CustomDataRegressionAlgorithm.Bitcoin>("BTC", Resolution.Minute);
+            Consolidate<TradeBar>(customSecurity.Symbol, TimeSpan.FromDays(1), bar => _customDataConsolidatorCount++);
 
             try
             {
-                Consolidate<QuoteBar>(symbol, TimeSpan.FromDays(1), bar => { UpdateQuoteBar(bar, -1); });
+                Consolidate<QuoteBar>(customSecurity.Symbol, TimeSpan.FromDays(1), bar => { UpdateQuoteBar(bar, -1); });
                 throw new RegressionTestException($"Expected {nameof(ArgumentException)} to be thrown");
             }
             catch (ArgumentException)
             {
                 // will try to use BaseDataConsolidator for which input is TradeBars not QuoteBars
             }
-
-            // Test using abstract T types, through defining a 'BaseData' handler
-            Consolidate(_symbol, Resolution.Daily, null, (Action<BaseData>)(bar => UpdateBar(bar, 6)));
-
-            Consolidate(_symbol, TimeSpan.FromDays(1), null, (Action<BaseData>)(bar => UpdateBar(bar, 7)));
-
-            Consolidate(_symbol, TimeSpan.FromDays(1), (Action<BaseData>)(bar => UpdateBar(bar, 8)));
-
-            _expectedConsolidations = QuantConnect.Time.EachTradeableDayInTimeZone(security.Exchange.Hours,
-                StartDate,
-                EndDate,
-                security.Exchange.TimeZone,
-                false).Count();
         }
+
         private void UpdateBar(BaseData tradeBar, int position)
         {
             if (!(tradeBar is TradeBar))
@@ -119,16 +134,27 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void OnEndOfAlgorithm()
         {
-            if (_consolidationCounts.Any(i => i != _expectedConsolidations) || _customDataConsolidator == 0)
+            for (var i = 0; i < _consolidationCounts.Count; i++)
             {
-                throw new RegressionTestException("Unexpected consolidation count");
+                var consolidationCount = _consolidationCounts[i];
+                var expectedConsolidationCount = _expectedConsolidationCounts[i];
+
+                if (consolidationCount != expectedConsolidationCount)
+                {
+                    throw new RegressionTestException($"Expected {expectedConsolidationCount} consolidations for consolidator {i} but received {consolidationCount}");
+                }
+            }
+
+            if (_customDataConsolidatorCount == 0)
+            {
+                throw new RegressionTestException($"Unexpected custom data consolidation count: {_customDataConsolidatorCount}");
             }
 
             for (var i = 0; i < _smas.Count; i++)
             {
-                if (_smas[i].Samples != _expectedConsolidations)
+                if (_smas[i].Samples != _expectedConsolidationCounts[i])
                 {
-                    throw new RegressionTestException($"Expected {_expectedConsolidations} samples in each SMA but found {_smas[i].Samples} in SMA in index {i}");
+                    throw new RegressionTestException($"Expected {_expectedConsolidationCounts} samples in each SMA but found {_smas[i].Samples} in SMA in index {i}");
                 }
 
                 if (_smas[i].Current.Time != _lastSmaUpdates[i])
@@ -144,9 +170,9 @@ namespace QuantConnect.Algorithm.CSharp
         /// <param name="data">Slice object keyed by symbol containing the stock data</param>
         public override void OnData(Slice slice)
         {
-            if (!Portfolio.Invested)
+            if (!Portfolio.Invested && _future.HasData)
             {
-                SetHoldings(_symbol, 0.5);
+                SetHoldings(_future.Symbol, 0.5);
             }
         }
 
@@ -163,7 +189,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 12244;
+        public long DataPoints => 14228;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -183,30 +209,30 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "6636.699%"},
-            {"Drawdown", "15.900%"},
+            {"Compounding Annual Return", "665.524%"},
+            {"Drawdown", "1.500%"},
             {"Expectancy", "0"},
             {"Start Equity", "100000"},
-            {"End Equity", "116177.7"},
-            {"Net Profit", "16.178%"},
-            {"Sharpe Ratio", "640.313"},
+            {"End Equity", "109332.4"},
+            {"Net Profit", "9.332%"},
+            {"Sharpe Ratio", "9.805"},
             {"Sortino Ratio", "0"},
-            {"Probabilistic Sharpe Ratio", "99.824%"},
+            {"Probabilistic Sharpe Ratio", "93.474%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "636.164"},
-            {"Beta", "5.924"},
-            {"Annual Standard Deviation", "1.012"},
-            {"Annual Variance", "1.024"},
-            {"Information Ratio", "696.123"},
-            {"Tracking Error", "0.928"},
-            {"Treynor Ratio", "109.404"},
-            {"Total Fees", "$23.65"},
-            {"Estimated Strategy Capacity", "$210000000.00"},
-            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Portfolio Turnover", "81.19%"},
-            {"OrderListHash", "dfd9a280d3c6470b305c03e0b72c234e"}
+            {"Alpha", "3.164"},
+            {"Beta", "0.957"},
+            {"Annual Standard Deviation", "0.383"},
+            {"Annual Variance", "0.146"},
+            {"Information Ratio", "8.29"},
+            {"Tracking Error", "0.379"},
+            {"Treynor Ratio", "3.917"},
+            {"Total Fees", "$15.05"},
+            {"Estimated Strategy Capacity", "$2100000000.00"},
+            {"Lowest Capacity Asset", "ES XCZJLC9NOB29"},
+            {"Portfolio Turnover", "64.34%"},
+            {"OrderListHash", "d814db6d5a9c97ee6de477ea06cd3834"}
         };
     }
 }

Algorithm.CSharp/ContinuousBackMonthRawFutureRegressionAlgorithm.cs

@@ -139,7 +139,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 713369;
+        public long DataPoints => 713371;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/ContinuousFutureBackMonthRegressionAlgorithm.cs

@@ -155,7 +155,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 723496;
+        public long DataPoints => 723498;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/ContinuousFutureImmediateUniverseSelectionRegressionAlgorithm.cs

@@ -184,7 +184,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 596356;
+        public long DataPoints => 596358;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/ContinuousFutureLimitIfTouchedOrderRegressionAlgorithm.cs

@@ -78,7 +78,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 19886;
+        public long DataPoints => 19888;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/ContinuousFutureOpenPositionsLiquidationOnDelistingRegressionAlgorithm.cs

@@ -0,0 +1,237 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Future;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm reproducing GH issue #8386 and other related bugs.
+    /// It asserts that open positions are liquidated when a contract is delisted, even if the contract was added as an internal subscription.
+    /// It also asserts that the contract is not tradable after being delisted.
+    /// </summary>
+    public class ContinuousFutureOpenPositionsLiquidationOnDelistingRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Future _continuousContract;
+        private Symbol _prevContractSymbol;
+        private bool _traded;
+        private bool _mapped;
+        private bool _delistedContractChecked;
+        private DateTime _firstMappedContractRemovalTime;
+        private int _removalCount;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 08);
+            SetEndDate(2013, 12, 30);
+
+            _continuousContract = AddFuture(Futures.Indices.SP500EMini,
+                dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
+                dataMappingMode: DataMappingMode.OpenInterest,
+                contractDepthOffset: 0
+            );
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (!_traded && _continuousContract.HasData)
+            {
+                var ticket = MarketOrder(_continuousContract.Mapped, 1);
+                if (ticket.Status == OrderStatus.Invalid)
+                {
+                    throw new RegressionTestException($"Order should be valid: {ticket}");
+                }
+                _traded = true;
+            }
+
+            if (slice.SymbolChangedEvents.Count > 0)
+            {
+                foreach (var change in slice.SymbolChangedEvents.Values)
+                {
+                    Debug($"[{Time}] :: Mapping: {change}");
+                    _prevContractSymbol = Symbol(change.OldSymbol);
+                    _mapped = true;
+                }
+            }
+
+            if (!_delistedContractChecked &&
+                _prevContractSymbol  != null &&
+                Time.Date > _prevContractSymbol.ID.Date &&
+                IsMarketOpen(_prevContractSymbol))
+            {
+                _delistedContractChecked = true;
+                var delistedContract = Securities.Total.Single(sec => sec.Symbol == _prevContractSymbol);
+
+                if (delistedContract.Invested)
+                {
+                    throw new RegressionTestException($"Position should be closed when {_prevContractSymbol} got delisted {_prevContractSymbol.ID.Date}");
+                }
+
+                if (!delistedContract.IsDelisted)
+                {
+                    throw new RegressionTestException($"Contract should be delisted: {delistedContract.Symbol}");
+                }
+
+                if (delistedContract.IsTradable)
+                {
+                    throw new RegressionTestException($"Contract should not be tradable: {delistedContract.Symbol}");
+                }
+
+                var ticket = MarketOrder(_prevContractSymbol, 1);
+
+                if (ticket.Status != OrderStatus.Invalid)
+                {
+                    throw new RegressionTestException($"Delisted contract order should be invalid: {ticket}");
+                }
+            }
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            if (_prevContractSymbol != null)
+            {
+                if (changes.RemovedSecurities.Any(x => x.Symbol == _prevContractSymbol))
+                {
+                    throw new RegressionTestException($"Previous contract symbol {_prevContractSymbol} should not be removed as a non-internal security");
+                }
+
+                changes.FilterInternalSecurities = false;
+
+                if (!changes.RemovedSecurities.Any(x => x.Symbol == _prevContractSymbol))
+                {
+                    throw new RegressionTestException($"Previous contract symbol {_prevContractSymbol} should be removed as an internal security");
+                }
+
+                _firstMappedContractRemovalTime = Time;
+                _removalCount++;
+            }
+
+            changes.FilterInternalSecurities = false;
+            Debug($"[{Time}] :: {changes}");
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug($"[{Time}] :: Order event: {orderEvent}");
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_traded)
+            {
+                throw new RegressionTestException("No trades have been made");
+            }
+
+            if (!_mapped)
+            {
+                throw new RegressionTestException("No mapping events have been fired");
+            }
+
+            if (!_delistedContractChecked)
+            {
+                throw new RegressionTestException("No delisted contract has been checked");
+            }
+
+            if (_prevContractSymbol == null)
+            {
+                throw new RegressionTestException("No previous contract symbol has been set");
+            }
+
+            var tradedContract = Securities.Total.Single(sec => sec.Symbol == _prevContractSymbol);
+            if (tradedContract.Invested)
+            {
+                throw new RegressionTestException($"Position should be closed when {_prevContractSymbol} got delisted on {_prevContractSymbol.ID.Date}");
+            }
+
+            if (_firstMappedContractRemovalTime == default || _firstMappedContractRemovalTime >= _prevContractSymbol.ID.Date)
+            {
+                throw new RegressionTestException($"First mapped contract should have been removed before it's expiry date");
+            }
+
+            if (_removalCount != 1)
+            {
+                throw new RegressionTestException($"The mapped contract should have been removed once only");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 396945;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "2"},
+            {"Average Win", "7.02%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "34.386%"},
+            {"Drawdown", "1.500%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "107016.6"},
+            {"Net Profit", "7.017%"},
+            {"Sharpe Ratio", "3.217"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "99.828%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.227"},
+            {"Beta", "0.109"},
+            {"Annual Standard Deviation", "0.084"},
+            {"Annual Variance", "0.007"},
+            {"Information Ratio", "-1.122"},
+            {"Tracking Error", "0.112"},
+            {"Treynor Ratio", "2.49"},
+            {"Total Fees", "$2.15"},
+            {"Estimated Strategy Capacity", "$1700000000.00"},
+            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
+            {"Portfolio Turnover", "2.01%"},
+            {"OrderListHash", "838e662caaa5a385c43ef27df1efbaf4"}
+        };
+    }
+}

Algorithm.CSharp/ContinuousFutureRegressionAlgorithm.cs

@@ -19,7 +19,6 @@ using QuantConnect.Data;
 using QuantConnect.Orders;
 using QuantConnect.Interfaces;
 using QuantConnect.Securities;
-using QuantConnect.Data.Market;
 using System.Collections.Generic;
 using QuantConnect.Securities.Future;
 using QuantConnect.Data.UniverseSelection;
@@ -31,7 +30,7 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class ContinuousFutureRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private List<SymbolChangedEvent> _mappings = new();
+        private List<Symbol> _previousMappedContractSymbols = new();
         private Symbol _currentMappedSymbol;
         private Future _continuousContract;
         private DateTime _lastMonth;
@@ -77,7 +76,7 @@ namespace QuantConnect.Algorithm.CSharp
             {
                 if (changedEvent.Symbol == _continuousContract.Symbol)
                 {
-                    _mappings.Add(changedEvent);
+                    _previousMappedContractSymbols.Add(Symbol(changedEvent.OldSymbol));
                     Log($"{Time} - SymbolChanged event: {changedEvent}");
 
                     if (_currentMappedSymbol == _continuousContract.Mapped)
@@ -144,15 +143,20 @@ namespace QuantConnect.Algorithm.CSharp
         public override void OnEndOfAlgorithm()
         {
             var expectedMappingCounts = 2;
-            if (_mappings.Count != expectedMappingCounts)
+            if (_previousMappedContractSymbols.Count != expectedMappingCounts)
             {
-                throw new RegressionTestException($"Unexpected symbol changed events: {_mappings.Count}, was expecting {expectedMappingCounts}");
+                throw new RegressionTestException($"Unexpected symbol changed events: {_previousMappedContractSymbols.Count}, was expecting {expectedMappingCounts}");
             }
 
-            var securities = Securities.Total.Where(sec => !sec.IsTradable && !sec.Symbol.IsCanonical() && sec.Symbol.SecurityType == SecurityType.Future).ToList();
-            if (securities.Count != 1)
+            var delistedSecurities = _previousMappedContractSymbols
+                .Select(x => Securities.Total.Single(sec => sec.Symbol == x))
+                .Where(x => x.Symbol.ID.Date < Time)
+                .ToList();
+            var markedDelistedSecurities = delistedSecurities.Where(x => x.IsDelisted && !x.IsTradable).ToList();
+            if (markedDelistedSecurities.Count != delistedSecurities.Count)
             {
-                throw new RegressionTestException($"We should have a single non tradable future contract security! found: {securities.Count}");
+                throw new RegressionTestException($"Not all delisted contracts are properly market as delisted and non-tradable: " +
+                    $"only {markedDelistedSecurities.Count} are marked, was expecting {delistedSecurities.Count}");
             }
         }
 
@@ -169,7 +173,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 713369;
+        public long DataPoints => 713375;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -186,18 +190,18 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
-            {"Total Orders", "3"},
-            {"Average Win", "1.50%"},
+            {"Total Orders", "4"},
+            {"Average Win", "0.84%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "3.337%"},
+            {"Compounding Annual Return", "3.380%"},
             {"Drawdown", "1.600%"},
             {"Expectancy", "0"},
             {"Start Equity", "100000"},
-            {"End Equity", "101666.4"},
-            {"Net Profit", "1.666%"},
-            {"Sharpe Ratio", "0.594"},
-            {"Sortino Ratio", "0.198"},
-            {"Probabilistic Sharpe Ratio", "44.801%"},
+            {"End Equity", "101687.3"},
+            {"Net Profit", "1.687%"},
+            {"Sharpe Ratio", "0.605"},
+            {"Sortino Ratio", "0.202"},
+            {"Probabilistic Sharpe Ratio", "45.198%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "100%"},
             {"Profit-Loss Ratio", "0"},
@@ -205,14 +209,14 @@ namespace QuantConnect.Algorithm.CSharp
             {"Beta", "0.134"},
             {"Annual Standard Deviation", "0.027"},
             {"Annual Variance", "0.001"},
-            {"Information Ratio", "-2.69"},
+            {"Information Ratio", "-2.687"},
             {"Tracking Error", "0.075"},
-            {"Treynor Ratio", "0.119"},
+            {"Treynor Ratio", "0.121"},
             {"Total Fees", "$6.45"},
-            {"Estimated Strategy Capacity", "$8000000000.00"},
+            {"Estimated Strategy Capacity", "$2600000000.00"},
             {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Portfolio Turnover", "1.39%"},
-            {"OrderListHash", "40c1137e0bc83b2bc920495af119c8fc"}
+            {"Portfolio Turnover", "1.88%"},
+            {"OrderListHash", "1287c3b983c5bac6491bb5ac296c4b55"}
         };
     }
 }

Algorithm.CSharp/ContinuousFutureRolloverBaseRegressionAlgorithm.cs

@@ -0,0 +1,262 @@
+/*
+ * 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.Securities;
+using QuantConnect.Securities.Future;
+using System;
+using QuantConnect.Util;
+using System.Linq;
+using NodaTime;
+using QuantConnect.Interfaces;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data, regardless of the
+    /// offset between the exchange time zone and the data time zone.
+    /// </summary>
+    public abstract class ContinuousFutureRolloverBaseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        const string Ticker = Futures.Indices.SP500EMini;
+
+        private Future _continuousContract;
+
+        private DateTime _rolloverTime;
+
+        private MarketHoursDatabase.Entry _originalMhdbEntry;
+
+        protected abstract Resolution Resolution { get; }
+
+        protected abstract Offset ExchangeToDataTimeZoneOffset { get; }
+
+        private DateTimeZone DataTimeZone => TimeZones.Utc;
+
+        private DateTimeZone ExchangeTimeZone => DateTimeZone.ForOffset(ExchangeToDataTimeZoneOffset);
+
+        private bool RolloverHappened => _rolloverTime != DateTime.MinValue;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 8);
+            SetEndDate(2013, 12, 20);
+
+            _originalMhdbEntry = MarketHoursDatabase.GetEntry(Market.CME, Ticker, SecurityType.Future);
+            var exchangeHours = new SecurityExchangeHours(ExchangeTimeZone,
+                _originalMhdbEntry.ExchangeHours.Holidays,
+                _originalMhdbEntry.ExchangeHours.MarketHours.ToDictionary(),
+                _originalMhdbEntry.ExchangeHours.EarlyCloses,
+                _originalMhdbEntry.ExchangeHours.LateOpens);
+            MarketHoursDatabase.SetEntry(Market.CME, Ticker, SecurityType.Future, exchangeHours, DataTimeZone);
+
+            SetTimeZone(ExchangeTimeZone);
+
+            _continuousContract = AddFuture(Ticker,
+                Resolution,
+                extendedMarketHours: true,
+                dataNormalizationMode: DataNormalizationMode.Raw,
+                dataMappingMode: DataMappingMode.OpenInterest,
+                contractDepthOffset: 0
+            );
+
+            SetBenchmark(x => 0);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            try
+            {
+                var receivedRollover = false;
+                foreach (var (symbol, symbolChangedEvent) in slice.SymbolChangedEvents)
+                {
+                    if (RolloverHappened)
+                    {
+                        throw new RegressionTestException($"[{Time}] -- Unexpected symbol changed event for {symbol}. Expected only one mapping.");
+                    }
+
+                    receivedRollover = true;
+                    _rolloverTime = symbolChangedEvent.EndTime;
+
+                    var oldSymbol = symbolChangedEvent.OldSymbol;
+                    var newSymbol = symbolChangedEvent.NewSymbol;
+                    Debug($"[{Time}] -- Rollover: {oldSymbol} -> {newSymbol}");
+
+                    if (symbol != _continuousContract.Symbol)
+                    {
+                        throw new RegressionTestException($"[{Time}] -- Unexpected symbol changed event for {symbol}");
+                    }
+
+                    var expectedMappingDate = new DateTime(2013, 12, 18);
+                    if (_rolloverTime != expectedMappingDate)
+                    {
+                        throw new RegressionTestException($"[{Time}] -- Unexpected date {_rolloverTime}. Expected {expectedMappingDate}");
+                    }
+
+                    var expectedMappingOldSymbol = "ES VMKLFZIH2MTD";
+                    var expectedMappingNewSymbol = "ES VP274HSU1AF5";
+                    if (symbolChangedEvent.OldSymbol != expectedMappingOldSymbol || symbolChangedEvent.NewSymbol != expectedMappingNewSymbol)
+                    {
+                        throw new RegressionTestException($"[{Time}] -- Unexpected mapping. " +
+                            $"Expected {expectedMappingOldSymbol} -> {expectedMappingNewSymbol} " +
+                            $"but was {symbolChangedEvent.OldSymbol} -> {symbolChangedEvent.NewSymbol}");
+                    }
+                }
+
+                var mappedFuture = Securities[_continuousContract.Mapped];
+                var mappedFuturePrice = mappedFuture.Price;
+
+                var otherFuture = Securities.Values.SingleOrDefault(x => !x.Symbol.IsCanonical() && x.Symbol != _continuousContract.Mapped);
+                var otherFuturePrice = otherFuture?.Price;
+
+                var continuousContractPrice = _continuousContract.Price;
+
+                Debug($"[{Time}] Contracts prices:\n" +
+                    $"  -- Mapped future: {mappedFuture.Symbol} :: {mappedFuture.Price} :: {mappedFuture.GetLastData()}\n" +
+                    $"  -- Other future: {otherFuture?.Symbol} :: {otherFuture?.Price} :: {otherFuture?.GetLastData()}\n" +
+                    $"  -- Mapped future from continuous contract: {_continuousContract.Symbol} :: {_continuousContract.Mapped} :: " +
+                    $"{_continuousContract.Price} :: {_continuousContract.GetLastData()}\n");
+
+                if (receivedRollover)
+                {
+                    if (continuousContractPrice != otherFuturePrice)
+                    {
+                        var continuousContractLastData = _continuousContract.GetLastData();
+                        throw new RegressionTestException($"[{Time}] -- Prices do not match. " +
+                            $"At the time of the rollover, expected continuous future price to be the same as " +
+                            $"the previously mapped contract since no data for the new mapped contract has been received:\n" +
+                            $"   Continuous contract ({_continuousContract.Symbol}) price: " +
+                            $"{continuousContractPrice} :: {continuousContractLastData.Symbol.Underlying} :: " +
+                            $"{continuousContractLastData.Time} - {continuousContractLastData.EndTime} :: {continuousContractLastData}. \n" +
+                            $"   Mapped contract ({mappedFuture.Symbol}) price: {mappedFuturePrice} :: {mappedFuture.GetLastData()}. \n" +
+                            $"   Other contract ({otherFuture?.Symbol}) price: {otherFuturePrice} :: {otherFuture?.GetLastData()}\n");
+                    }
+                }
+                else if (mappedFuturePrice != 0 || !RolloverHappened)
+                {
+                    if (continuousContractPrice != mappedFuturePrice)
+                    {
+                        var continuousContractLastData = _continuousContract.GetLastData();
+                        throw new RegressionTestException($"[{Time}] -- Prices do not match. " +
+                            $"Expected continuous future price to be the same as the mapped contract:\n" +
+                            $"   Continuous contract ({_continuousContract.Symbol}) price: {continuousContractPrice} :: " +
+                            $"{continuousContractLastData.Symbol.Underlying} :: {continuousContractLastData}. \n" +
+                            $"   Mapped contract ({mappedFuture.Symbol}) price: {mappedFuturePrice} :: {mappedFuture.GetLastData()}. \n" +
+                            $"   Other contract ({otherFuture?.Symbol}) price: {otherFuturePrice} :: {otherFuture?.GetLastData()}\n");
+                    }
+                }
+                // No data for the mapped future yet after rollover
+                else
+                {
+                    if (otherFuture == null)
+                    {
+                        throw new RegressionTestException($"[{Time}] --" +
+                            $" Mapped future price is 0 (no data has arrived) so the previous mapped contract is expected to be there");
+                    }
+
+                    var continuousContractLastData = _continuousContract.GetLastData();
+
+                    if (continuousContractLastData.EndTime > _rolloverTime)
+                    {
+                        throw new RegressionTestException($"[{Time}] -- Expected continuous future contract last data to be from the previously " +
+                            $"mapped contract until the new mapped contract gets data:\n" +
+                            $"   Rollover time: {_rolloverTime}\n" +
+                            $"   Continuous contract ({_continuousContract.Symbol}) last data: " +
+                            $"{continuousContractLastData.Symbol.Underlying} :: " +
+                            $"{continuousContractLastData.Time} - {continuousContractLastData.EndTime} :: {continuousContractLastData}.");
+                    }
+                }
+            }
+            catch (Exception ex)
+            {
+                ResetMarketHoursDatabase();
+                throw;
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            ResetMarketHoursDatabase();
+
+            if (!RolloverHappened)
+            {
+                throw new RegressionTestException($"[{Time}] -- Rollover did not happen.");
+            }
+        }
+
+        private void ResetMarketHoursDatabase()
+        {
+            MarketHoursDatabase.SetEntry(Market.CME, Ticker, SecurityType.Future, _originalMhdbEntry.ExchangeHours, _originalMhdbEntry.DataTimeZone);
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 0;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+    }
+}

Algorithm.CSharp/ContinuousFutureRolloverDailyExchangeTimeZoneAheadOfDataRegressionAlgorithm.cs

@@ -0,0 +1,38 @@
+/*
+ * 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 NodaTime;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data.
+    /// The algorithms asserts the behavior for the case when the exchange time zone is ahead of the data time zone.
+    /// </summary>
+    public class ContinuousFutureRolloverDailyExchangeTimeZoneAheadOfDataRegressionAlgorithm
+        : ContinuousFutureRolloverBaseRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Daily;
+
+        protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(2);
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 1022;
+    }
+}

Algorithm.CSharp/ContinuousFutureRolloverDailyExchangeTimeZoneBehindOfDataRegressionAlgorithm.cs

@@ -0,0 +1,38 @@
+/*
+ * 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 NodaTime;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data.
+    /// The algorithms asserts the behavior for the case when the exchange time zone is behind of the data time zone.
+    /// </summary>
+    public class ContinuousFutureRolloverDailyExchangeTimeZoneBehindOfDataRegressionAlgorithm
+        : ContinuousFutureRolloverBaseRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Daily;
+
+        protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(-2);
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 1017;
+    }
+}

Algorithm.CSharp/ContinuousFutureRolloverDailyExchangeTimeZoneSameAsDataRegressionAlgorithm.cs

@@ -0,0 +1,38 @@
+/*
+ * 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 NodaTime;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data.
+    /// The algorithms asserts the behavior for the case when the data time zone is the same as the exchange time zone.
+    /// </summary>
+    public class ContinuousFutureRolloverDailyExchangeTimeZoneSameAsDataRegressionAlgorithm
+        : ContinuousFutureRolloverBaseRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Daily;
+
+        protected override Offset ExchangeToDataTimeZoneOffset => Offset.Zero;
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 1015;
+    }
+}

Algorithm.CSharp/ContinuousFutureRolloverHourExchangeTimeZoneAheadOfDataRegressionAlgorithm.cs

@@ -0,0 +1,38 @@
+/*
+ * 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 NodaTime;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data.
+    /// The algorithms asserts the behavior for the case when the exchange time zone is ahead of the data time zone.
+    /// </summary>
+    public class ContinuousFutureRolloverHourExchangeTimeZoneAheadOfDataRegressionAlgorithm
+        : ContinuousFutureRolloverBaseRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Hour;
+
+        protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(2);
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 18850;
+    }
+}

Algorithm.CSharp/ContinuousFutureRolloverHourExchangeTimeZoneBehindOfDataRegressionAlgorithm.cs

@@ -0,0 +1,38 @@
+/*
+ * 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 NodaTime;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data.
+    /// The algorithms asserts the behavior for the case when the exchange time zone is behind of the data time zone.
+    /// </summary>
+    public class ContinuousFutureRolloverHourExchangeTimeZoneBehindOfDataRegressionAlgorithm
+        : ContinuousFutureRolloverBaseRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Hour;
+
+        protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(-2);
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 18844;
+    }
+}

Algorithm.CSharp/ContinuousFutureRolloverHourExchangeTimeZoneSameAsDataRegressionAlgorithm.cs

@@ -0,0 +1,38 @@
+/*
+ * 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 NodaTime;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data.
+    /// The algorithms asserts the behavior for the case when the data time zone is the same as the exchange time zone.
+    /// </summary>
+    public class ContinuousFutureRolloverHourExchangeTimeZoneSameAsDataRegressionAlgorithm
+        : ContinuousFutureRolloverBaseRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Hour;
+
+        protected override Offset ExchangeToDataTimeZoneOffset => Offset.Zero;
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 18846;
+    }
+}

Algorithm.CSharp/ContinuousFutureRolloverMinuteExchangeTimeZoneAheadOfDataRegressionAlgorithm.cs

@@ -0,0 +1,38 @@
+/*
+ * 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 NodaTime;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data.
+    /// The algorithms asserts the behavior for the case when the exchange time zone is ahead of the data time zone.
+    /// </summary>
+    public class ContinuousFutureRolloverMinuteExchangeTimeZoneAheadOfDataRegressionAlgorithm
+        : ContinuousFutureRolloverBaseRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Minute;
+
+        protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(2);
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 1127376;
+    }
+}

Algorithm.CSharp/ContinuousFutureRolloverMinuteExchangeTimeZoneBehindOfDataRegressionAlgorithm.cs

@@ -0,0 +1,38 @@
+/*
+ * 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 NodaTime;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data.
+    /// The algorithms asserts the behavior for the case when the exchange time zone is behind of the data time zone.
+    /// </summary>
+    public class ContinuousFutureRolloverMinuteExchangeTimeZoneBehindOfDataRegressionAlgorithm
+        : ContinuousFutureRolloverBaseRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Minute;
+
+        protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(-2);
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 1127374;
+    }
+}

Algorithm.CSharp/ContinuousFutureRolloverMinuteExchangeTimeZoneSameAsDataRegressionAlgorithm.cs

@@ -0,0 +1,38 @@
+/*
+ * 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 NodaTime;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Base class for regression algorithms testing that when a continuous future rollover happens,
+    /// the continuous contract is updated correctly with the new contract data.
+    /// The algorithms asserts the behavior for the case when the data time zone is the same as the exchange time zone.
+    /// </summary>
+    public class ContinuousFutureRolloverMinuteExchangeTimeZoneSameAsDataRegressionAlgorithm
+        : ContinuousFutureRolloverBaseRegressionAlgorithm
+    {
+        protected override Resolution Resolution => Resolution.Minute;
+
+        protected override Offset ExchangeToDataTimeZoneOffset => Offset.Zero;
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 1127488;
+    }
+}

Algorithm.CSharp/ContinuousFuturesDailyRegressionAlgorithm.cs

@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 1267;
+        public long DataPoints => 1268;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/CorrelationTypeComparisonRegressionAlgorithm.cs

@@ -0,0 +1,134 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ * 
+ * Licensed under the Apache License, Version 2.0 (the "License"); 
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System.Collections.Generic;
+using QuantConnect.Data;
+using QuantConnect.Indicators;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Compares two correlation types and asserts they are not equal during the algorithm's execution.
+    /// </summary>
+    public class CorrelationTypeComparisonRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Correlation _correlationPearson;
+        private Correlation _correlationSpearman;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 08);  //Set Start Date
+            SetEndDate(2013, 10, 17);    //Set End Date
+            var symbol = AddEquity("AAPL", Resolution.Daily).Symbol;
+            var spy = AddEquity("SPY", Resolution.Daily).Symbol;
+            _correlationPearson = C(symbol, spy, 5, CorrelationType.Pearson);
+            _correlationSpearman = C(symbol, spy, 5, CorrelationType.Spearman);
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            if (_correlationPearson.IsReady && _correlationSpearman.IsReady)
+            {
+                var pearsonValue = _correlationPearson.Current.Value;
+                var spearmanValue = _correlationSpearman.Current.Value;
+
+                // Check that the correlation values are not the same
+                if (pearsonValue == spearmanValue)
+                {
+                    // Throw an exception if the correlation values are equal
+                    throw new RegressionTestException($"Error: Pearson and Spearman correlation values are the same: Pearson = {pearsonValue}, Spearman = {spearmanValue}. This should not happen.");
+                }
+            }
+        }
+
+        /// <summary>
+        /// End of algorithm run event handler. This method is called at the end of a backtest or live trading operation. Intended for closing out logs.
+        /// </summary>
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_correlationPearson.IsReady || !_correlationSpearman.IsReady)
+            {
+                throw new RegressionTestException("Error: Both correlation values should be ready at the end of the algorithm.");
+            }
+        }
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally => true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 80;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-19.184"},
+            {"Tracking Error", "0.138"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/CustomDataPropertiesRegressionAlgorithm.cs

@@ -40,8 +40,8 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public override void Initialize()
         {
-            SetStartDate(2011, 9, 13);
-            SetEndDate(2015, 12, 01);
+            SetStartDate(2020, 01, 05);
+            SetEndDate(2020, 01, 10);
 
             //Set the cash for the strategy:
             SetCash(100000);
@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 10491;
+        public long DataPoints => 57;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -129,30 +129,30 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "155.211%"},
-            {"Drawdown", "84.800%"},
+            {"Compounding Annual Return", "34781.071%"},
+            {"Drawdown", "4.300%"},
             {"Expectancy", "0"},
             {"Start Equity", "100000"},
-            {"End Equity", "5223241.65"},
-            {"Net Profit", "5123.242%"},
-            {"Sharpe Ratio", "2.058"},
-            {"Sortino Ratio", "2.492"},
-            {"Probabilistic Sharpe Ratio", "68.833%"},
+            {"End Equity", "110102.2"},
+            {"Net Profit", "10.102%"},
+            {"Sharpe Ratio", "283.719"},
+            {"Sortino Ratio", "1123.876"},
+            {"Probabilistic Sharpe Ratio", "81.716%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "1.724"},
-            {"Beta", "0.043"},
-            {"Annual Standard Deviation", "0.841"},
-            {"Annual Variance", "0.707"},
-            {"Information Ratio", "1.902"},
-            {"Tracking Error", "0.848"},
-            {"Treynor Ratio", "40.293"},
+            {"Alpha", "184.11"},
+            {"Beta", "-6.241"},
+            {"Annual Standard Deviation", "0.635"},
+            {"Annual Variance", "0.403"},
+            {"Information Ratio", "260.511"},
+            {"Tracking Error", "0.689"},
+            {"Treynor Ratio", "-28.849"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "BTC.Bitcoin 2S"},
-            {"Portfolio Turnover", "0.06%"},
-            {"OrderListHash", "999305e00ec9861f5ff261794e81213d"}
+            {"Portfolio Turnover", "16.73%"},
+            {"OrderListHash", "b890a8e73bf118e943ad2f2e712f12d0"}
         };
 
         /// <summary>
@@ -168,6 +168,7 @@ namespace QuantConnect.Algorithm.CSharp
             public decimal High { get; set; }
             [JsonProperty("low")]
             public decimal Low { get; set; }
+            public decimal Mid { get; set; }
             [JsonProperty("last")]
             public decimal Close { get; set; }
             [JsonProperty("bid")]
@@ -217,7 +218,10 @@ namespace QuantConnect.Algorithm.CSharp
 
                 //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);
+                return new SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/nasdaq/api/v3/datatables/QDL/BITFINEX.csv?code=BTCUSD&api_key=WyAazVXnq7ATy_fefTqm")
+                {
+                    Sort = true
+                };
             }
 
             /// <summary>
@@ -248,20 +252,20 @@ namespace QuantConnect.Algorithm.CSharp
                 }
 
                 //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
+                // code    date        high     low      mid      last     bid      ask      volume
+                // BTCUSD  2024-10-08  63248.0  61940.0  62246.5  62245.0  62246.0  62247.0       5.929230648356
                 try
                 {
                     string[] data = line.Split(',');
-                    coin.Time = DateTime.Parse(data[0], CultureInfo.InvariantCulture);
+                    coin.Time = DateTime.Parse(data[1], CultureInfo.InvariantCulture);
                     coin.EndTime = coin.Time.AddDays(1);
-                    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.Mid = Convert.ToDecimal(data[4], CultureInfo.InvariantCulture);
+                    coin.Close = Convert.ToDecimal(data[5], CultureInfo.InvariantCulture);
+                    coin.Bid = Convert.ToDecimal(data[6], CultureInfo.InvariantCulture);
+                    coin.Ask = Convert.ToDecimal(data[7], CultureInfo.InvariantCulture);
+                    coin.VolumeBTC = Convert.ToDecimal(data[8], CultureInfo.InvariantCulture);
                     coin.Value = coin.Close;
                 }
                 catch { /* Do nothing, skip first title row */ }

Algorithm.CSharp/CustomDataRegressionAlgorithm.cs

@@ -33,15 +33,15 @@ namespace QuantConnect.Algorithm.CSharp
     /// <meta name="tag" content="regression test" />
     public class CustomDataRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private bool _warmedUpChecked = false;
+        private bool _warmedUpChecked;
 
         /// <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(2011, 9, 14);
-            SetEndDate(2015, 12, 01);
+            SetStartDate(2020, 01, 05);
+            SetEndDate(2020, 01, 10);
 
             //Set the cash for the strategy:
             SetCash(100000);
@@ -110,7 +110,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 8943;
+        public long DataPoints => 50;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -130,30 +130,30 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "155.365%"},
-            {"Drawdown", "84.800%"},
+            {"Compounding Annual Return", "27587.925%"},
+            {"Drawdown", "4.200%"},
             {"Expectancy", "0"},
             {"Start Equity", "100000"},
-            {"End Equity", "5223170.23"},
-            {"Net Profit", "5123.170%"},
-            {"Sharpe Ratio", "2.094"},
-            {"Sortino Ratio", "2.535"},
-            {"Probabilistic Sharpe Ratio", "69.967%"},
+            {"End Equity", "109685"},
+            {"Net Profit", "9.685%"},
+            {"Sharpe Ratio", "238.834"},
+            {"Sortino Ratio", "945.079"},
+            {"Probabilistic Sharpe Ratio", "81.660%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "1.753"},
-            {"Beta", "0.055"},
-            {"Annual Standard Deviation", "0.84"},
-            {"Annual Variance", "0.706"},
-            {"Information Ratio", "1.942"},
-            {"Tracking Error", "0.848"},
-            {"Treynor Ratio", "32.18"},
+            {"Alpha", "149.482"},
+            {"Beta", "-6.002"},
+            {"Annual Standard Deviation", "0.61"},
+            {"Annual Variance", "0.371"},
+            {"Information Ratio", "218.36"},
+            {"Tracking Error", "0.664"},
+            {"Treynor Ratio", "-24.253"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "BTC.Bitcoin 2S"},
-            {"Portfolio Turnover", "0.06%"},
-            {"OrderListHash", "e69e78cd6fe7bc4627da2f51e25539d0"}
+            {"Portfolio Turnover", "16.03%"},
+            {"OrderListHash", "dde8821614d33c89e6e75c536447b7da"}
         };
 
         /// <summary>
@@ -169,6 +169,8 @@ namespace QuantConnect.Algorithm.CSharp
             public decimal High { get; set; }
             [JsonProperty("low")]
             public decimal Low { get; set; }
+            public decimal Mid { get; set; }
+
             [JsonProperty("last")]
             public decimal Close { get; set; }
             [JsonProperty("bid")]
@@ -179,7 +181,6 @@ namespace QuantConnect.Algorithm.CSharp
             public decimal WeightedPrice { get; set; }
             [JsonProperty("volume")]
             public decimal VolumeBTC { get; set; }
-            public decimal VolumeUSD { get; set; }
 
             /// <summary>
             /// The end time of this data. Some data covers spans (trade bars)
@@ -218,7 +219,10 @@ namespace QuantConnect.Algorithm.CSharp
 
                 //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);
+                return new SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/nasdaq/api/v3/datatables/QDL/BITFINEX.csv?code=BTCUSD&api_key=qAWKpUfmSVFnU3bRQwKy")
+                {
+                    Sort = true
+                };
             }
 
             /// <summary>
@@ -249,20 +253,20 @@ namespace QuantConnect.Algorithm.CSharp
                 }
 
                 //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
+                // code    date        high     low      mid      last     bid      ask      volume
+                // BTCUSD  2024-10-08  63248.0  61940.0  62246.5  62245.0  62246.0  62247.0  477.91102114
                 try
                 {
                     string[] data = line.Split(',');
-                    coin.Time = DateTime.Parse(data[0], CultureInfo.InvariantCulture);
+                    coin.Time = DateTime.Parse(data[1], CultureInfo.InvariantCulture);
                     coin.EndTime = coin.Time.AddDays(1);
-                    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.Mid = Convert.ToDecimal(data[4], CultureInfo.InvariantCulture);
+                    coin.Close = Convert.ToDecimal(data[5], CultureInfo.InvariantCulture);
+                    coin.Bid = Convert.ToDecimal(data[6], CultureInfo.InvariantCulture);
+                    coin.Ask = Convert.ToDecimal(data[7], CultureInfo.InvariantCulture);
+                    coin.VolumeBTC = Convert.ToDecimal(data[8], CultureInfo.InvariantCulture);
                     coin.Value = coin.Close;
                 }
                 catch { /* Do nothing, skip first title row */ }

Algorithm.CSharp/DelistedFutureLiquidateDailyRegressionAlgorithm.cs

@@ -28,7 +28,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 1679;
+        public override long DataPoints => 1681;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm

Algorithm.CSharp/DelistedFutureLiquidateRegressionAlgorithm.cs

@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 525809;
+        public virtual long DataPoints => 525811;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/DescendingCustomDataObjectStoreRegressionAlgorithm.cs

@@ -0,0 +1,211 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Linq;
+using QuantConnect.Data;
+using System.Globalization;
+using QuantConnect.Interfaces;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// The regression algorithm showcases the utilization of a custom data source with the Sort flag set to true.
+    /// This means that the source initially provides data in descending order, which is then organized into ascending order and returned in the <see cref="OnData(Slice)"/> function.
+    /// </summary>
+    public class DescendingCustomDataObjectStoreRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        protected virtual string CustomDataKey => "CustomData/SortCustomData";
+
+        protected readonly static string[] descendingCustomData = new string[]
+        {
+            "2024-10-03 19:00:00,173.5,176.0,172.0,175.2,120195681,4882.29",
+            "2024-10-02 18:00:00,174.0,177.0,173.0,175.8,116275729,4641.97",
+            "2024-10-01 17:00:00,175.0,178.0,172.5,174.5,127707078,6591.27",
+            "2024-09-30 11:00:00,174.8,176.5,172.8,175.0,127707078,6591.27",
+            "2024-09-27 10:00:00,172.5,175.0,171.5,173.5,120195681,4882.29",
+            "2024-09-26 09:00:00,171.0,172.5,170.0,171.8,117516350,4820.53",
+            "2024-09-25 08:00:00,169.5,172.0,169.0,171.0,110427867,4661.55",
+            "2024-09-24 07:00:00,170.0,171.0,168.0,169.5,127624733,4823.52",
+            "2024-09-23 06:00:00,172.0,173.5,169.5,171.5,123586417,4303.93",
+            "2024-09-20 05:00:00,168.0,171.0,167.5,170.5,151929179,5429.87",
+            "2024-09-19 04:00:00,170.5,171.5,166.0,167.0,160523863,5219.24",
+            "2024-09-18 03:00:00,173.0,174.0,169.0,172.0,145721790,5163.09",
+            "2024-09-17 02:00:00,171.0,173.5,170.0,172.5,144794030,5405.72",
+            "2024-09-16 01:00:00,168.0,171.0,167.0,170.0,214402430,8753.33",
+            "2024-09-13 16:00:00,173.5,176.0,172.0,175.2,120195681,4882.29",
+            "2024-09-12 15:00:00,174.5,177.5,173.5,176.5,171728134,7774.83",
+            "2024-09-11 14:00:00,175.0,178.0,174.0,175.5,191516153,8349.59",
+            "2024-09-10 13:00:00,174.5,176.0,173.0,174.0,151162819,5915.8",
+            "2024-09-09 12:00:00,176.0,178.0,175.0,177.0,116275729,4641.97"
+        };
+
+        private Symbol _customSymbol;
+
+        private List<SortCustomData> _receivedData = new();
+
+        public override void Initialize()
+        {
+            SetStartDate(2024, 09, 09);
+            SetEndDate(2024, 10, 03);
+            SetCash(100000);
+
+            SetBenchmark(x => 0);
+
+            SortCustomData.CustomDataKey = CustomDataKey;
+
+            _customSymbol = AddData<SortCustomData>("SortCustomData", Resolution.Daily).Symbol;
+
+            // Saving data here for demonstration and regression testing purposes.
+            // In real scenarios, data has to be saved to the object store before the algorithm starts.
+            ObjectStore.Save(CustomDataKey, string.Join("\n", descendingCustomData));
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (slice.ContainsKey(_customSymbol))
+            {
+                var sortCustomData = slice.Get<SortCustomData>(_customSymbol);
+                if (sortCustomData.Open == 0 || sortCustomData.High == 0 || sortCustomData.Low == 0 || sortCustomData.Close == 0 || sortCustomData.Price == 0)
+                {
+                    throw new RegressionTestException("One or more custom data fields (Open, High, Low, Close, Price) are zero.");
+                }
+
+                _receivedData.Add(sortCustomData);
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_receivedData.Count == 0)
+            {
+                throw new RegressionTestException("Custom data was not fetched");
+            }
+
+            var history = History<SortCustomData>(_customSymbol, StartDate, EndDate, Resolution.Hour).ToList();
+
+            if (history.Count != _receivedData.Count)
+            {
+                throw new RegressionTestException("History request returned different data than expected");
+            }
+
+            // Iterate through the history collection, checking if the EndTime is in ascending order.
+            for (int i = 0; i < history.Count - 1; i++)
+            {
+                if (history[i].EndTime > history[i + 1].EndTime)
+                {
+                    throw new RegressionTestException($"Order failure: {history[i].EndTime} > {history[i + 1].EndTime} at index {i}.");
+                }
+            }
+        }
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally => true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages => new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all TimeSlices of algorithm
+        /// </summary>
+        public long DataPoints => 20;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 19;
+
+        /// <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 ()
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+
+    public class SortCustomData : BaseData
+    {
+        public static string CustomDataKey { get; set; }
+
+        public decimal Open { get; set; }
+        public decimal High { get; set; }
+        public decimal Low { get; set; }
+        public decimal Close { get; set; }
+
+        public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)
+        {
+            return new SubscriptionDataSource(CustomDataKey, SubscriptionTransportMedium.ObjectStore, FileFormat.Csv)
+            {
+                // Indicate that the data from the subscription will be returned in descending order.
+                Sort = true
+            };
+        }
+
+        public override BaseData Reader(SubscriptionDataConfig config, string line, DateTime date, bool isLiveMode)
+        {
+            var csv = line.Split(",");
+            var data = new SortCustomData()
+            {
+                Symbol = config.Symbol,
+                Time = DateTime.ParseExact(csv[0], DateFormat.DB, CultureInfo.InvariantCulture),
+                Value = csv[4].ToDecimal(),
+                Open = csv[1].ToDecimal(),
+                High = csv[2].ToDecimal(),
+                Low = csv[3].ToDecimal(),
+                Close = csv[4].ToDecimal()
+            };
+
+            return data;
+        }
+    }
+}

Algorithm.CSharp/FutureMarketOpenAndCloseWithExtendedMarketRegressionAlgorithm.cs

@@ -50,7 +50,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 41466;
+        public override long DataPoints => 41467;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm

Algorithm.CSharp/FutureMarketOpenConsolidatorRegressionAlgorithm.cs

@@ -93,7 +93,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public virtual long DataPoints => 32071;
+        public virtual long DataPoints => 32073;
 
         /// </summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/FutureMarketOpenConsolidatorWithExtendedMarketRegressionAlgorithm.cs

@@ -52,7 +52,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 103816;
+        public override long DataPoints => 103818;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm

Algorithm.CSharp/FutureOptionBuySellCallIntradayRegressionAlgorithm.cs

@@ -112,7 +112,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 309280;
+        public long DataPoints => 309282;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -150,7 +150,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.005"},
             {"Information Ratio", "-0.134"},
             {"Tracking Error", "0.385"},
-            {"Treynor Ratio", "3.784"},
+            {"Treynor Ratio", "3.785"},
             {"Total Fees", "$2.84"},
             {"Estimated Strategy Capacity", "$120000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPBIJ7O|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureOptionCallITMExpiryRegressionAlgorithm.cs

@@ -200,7 +200,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -238,7 +238,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.004"},
             {"Information Ratio", "-0.226"},
             {"Tracking Error", "0.378"},
-            {"Treynor Ratio", "-21.838"},
+            {"Treynor Ratio", "-21.841"},
             {"Total Fees", "$1.42"},
             {"Estimated Strategy Capacity", "$120000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPBIJ7O|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureOptionCallITMGreeksExpiryRegressionAlgorithm.cs

@@ -165,7 +165,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -203,7 +203,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.098"},
             {"Information Ratio", "-0.649"},
             {"Tracking Error", "0.483"},
-            {"Treynor Ratio", "-18.589"},
+            {"Treynor Ratio", "-18.59"},
             {"Total Fees", "$7.10"},
             {"Estimated Strategy Capacity", "$24000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPBIJ7O|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureOptionCallOTMExpiryRegressionAlgorithm.cs

@@ -176,7 +176,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -214,7 +214,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.003"},
             {"Information Ratio", "-0.198"},
             {"Tracking Error", "0.377"},
-            {"Treynor Ratio", "-23.06"},
+            {"Treynor Ratio", "-23.065"},
             {"Total Fees", "$1.42"},
             {"Estimated Strategy Capacity", "$180000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPHGV9G|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureOptionMultipleContractsInDifferentContractMonthsWithSameUnderlyingFutureRegressionAlgorithm.cs

@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 24378;
+        public long DataPoints => 24379;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/FutureOptionPutITMExpiryRegressionAlgorithm.cs

@@ -201,7 +201,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -239,7 +239,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.003"},
             {"Information Ratio", "-0.248"},
             {"Tracking Error", "0.377"},
-            {"Treynor Ratio", "-36.295"},
+            {"Treynor Ratio", "-36.3"},
             {"Total Fees", "$1.42"},
             {"Estimated Strategy Capacity", "$79000000.00"},
             {"Lowest Capacity Asset", "ES 31EL5FAOOQON8|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureOptionPutOTMExpiryRegressionAlgorithm.cs

@@ -174,7 +174,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -212,7 +212,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.003"},
             {"Information Ratio", "-0.249"},
             {"Tracking Error", "0.377"},
-            {"Treynor Ratio", "-32.551"},
+            {"Treynor Ratio", "-32.556"},
             {"Total Fees", "$1.42"},
             {"Estimated Strategy Capacity", "$290000000.00"},
             {"Lowest Capacity Asset", "ES 31EL5FBZBMXES|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureOptionShortCallITMExpiryRegressionAlgorithm.cs

@@ -185,7 +185,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -223,7 +223,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.002"},
             {"Information Ratio", "0.064"},
             {"Tracking Error", "0.378"},
-            {"Treynor Ratio", "-13.132"},
+            {"Treynor Ratio", "-13.127"},
             {"Total Fees", "$1.42"},
             {"Estimated Strategy Capacity", "$13000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UP5K75W|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureOptionShortCallOTMExpiryRegressionAlgorithm.cs

@@ -168,7 +168,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -194,7 +194,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Start Equity", "100000"},
             {"End Equity", "101736.08"},
             {"Net Profit", "1.736%"},
-            {"Sharpe Ratio", "0.597"},
+            {"Sharpe Ratio", "0.596"},
             {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "49.736%"},
             {"Loss Rate", "0%"},
@@ -206,7 +206,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.001"},
             {"Information Ratio", "0.009"},
             {"Tracking Error", "0.375"},
-            {"Treynor Ratio", "-11.057"},
+            {"Treynor Ratio", "-11.048"},
             {"Total Fees", "$1.42"},
             {"Estimated Strategy Capacity", "$100000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPNF7B8|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureOptionShortPutITMExpiryRegressionAlgorithm.cs

@@ -182,7 +182,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -220,7 +220,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.001"},
             {"Information Ratio", "0.058"},
             {"Tracking Error", "0.375"},
-            {"Treynor Ratio", "-41.846"},
+            {"Treynor Ratio", "-41.831"},
             {"Total Fees", "$1.42"},
             {"Estimated Strategy Capacity", "$12000000.00"},
             {"Lowest Capacity Asset", "ES 31EL5FAOUP0P0|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureOptionShortPutOTMExpiryRegressionAlgorithm.cs

@@ -167,7 +167,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -193,7 +193,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Start Equity", "100000"},
             {"End Equity", "103423.58"},
             {"Net Profit", "3.424%"},
-            {"Sharpe Ratio", "1.089"},
+            {"Sharpe Ratio", "1.088"},
             {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "73.287%"},
             {"Loss Rate", "0%"},
@@ -205,7 +205,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.001"},
             {"Information Ratio", "0.075"},
             {"Tracking Error", "0.377"},
-            {"Treynor Ratio", "-24.083"},
+            {"Treynor Ratio", "-24.076"},
             {"Total Fees", "$1.42"},
             {"Estimated Strategy Capacity", "$110000000.00"},
             {"Lowest Capacity Asset", "ES 31EL5FAJQ6SBO|ES XFH59UK0MYO1"},

Algorithm.CSharp/FutureStopMarketOrderOnExtendedHoursRegressionAlgorithm.cs

@@ -113,7 +113,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all time slices of algorithm
         /// </summary>
-        public long DataPoints => 75960;
+        public long DataPoints => 75961;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/FuturesAndFuturesOptionsExpiryTimeAndLiquidationRegressionAlgorithm.cs

@@ -178,7 +178,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212941;
+        public long DataPoints => 212942;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -204,7 +204,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Start Equity", "100000"},
             {"End Equity", "98233.93"},
             {"Net Profit", "-1.766%"},
-            {"Sharpe Ratio", "-1.14"},
+            {"Sharpe Ratio", "-1.141"},
             {"Sortino Ratio", "0"},
             {"Probabilistic Sharpe Ratio", "0.020%"},
             {"Loss Rate", "50%"},
@@ -216,7 +216,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0"},
             {"Information Ratio", "-0.602"},
             {"Tracking Error", "0.291"},
-            {"Treynor Ratio", "-16.64"},
+            {"Treynor Ratio", "-16.65"},
             {"Total Fees", "$3.57"},
             {"Estimated Strategy Capacity", "$16000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UK0MYO1"},

Algorithm.CSharp/FuturesExpiredContractRegression.cs

@@ -89,7 +89,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 268273;
+        public long DataPoints => 268275;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/FuturesExtendedMarketHoursRegressionAlgorithm.cs

@@ -113,7 +113,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 3630;
+        public long DataPoints => 3631;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/ImmediateExecutionModelWorksWithBinanceFeeModel.cs

@@ -0,0 +1,119 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using QuantConnect.Algorithm.Framework.Alphas;
+using QuantConnect.Algorithm.Framework.Execution;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+using System;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm to test ImmediateExecutionModel places orders with the
+    /// correct quantity (taking into account the fee's) so that the fill quantity
+    /// is the expected one.
+    /// </summary>
+    public class ImmediateExecutionModelWorksWithBinanceFeeModel: QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2022, 12, 13);
+            SetEndDate(2022, 12, 14);
+            SetAccountCurrency("BUSD");
+            SetCash("BUSD", 100000, 1);
+
+            UniverseSettings.Resolution = Resolution.Minute;
+
+            var symbols = new List<Symbol>() { QuantConnect.Symbol.Create("BTCBUSD", SecurityType.Crypto, Market.Binance) };
+            SetUniverseSelection(new ManualUniverseSelectionModel(symbols));
+            SetAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromMinutes(20), 0.025, null));
+
+            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel(Resolution.Minute));
+            SetExecution(new ImmediateExecutionModel());
+            SetBrokerageModel(Brokerages.BrokerageName.Binance, AccountType.Margin);
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            if (orderEvent.Status == OrderStatus.Filled)
+            {
+                if (Math.Abs(orderEvent.Quantity - 5.8m) > 0.01m)
+                {
+                    throw new RegressionTestException($"The expected quantity was {5.8m} but the quantity from the order was {orderEvent.Quantity}");
+                }
+            }
+        }
+
+        public bool CanRunLocally => true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 2882;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 60;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "1"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000.00"},
+            {"End Equity", "103411.39"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "BUSD99.75"},
+            {"Estimated Strategy Capacity", "BUSD600000.00"},
+            {"Lowest Capacity Asset", "BTCBUSD 18N"},
+            {"Portfolio Turnover", "48.18%"},
+            {"OrderListHash", "2ad07f12d7c80fd4a904269d62794e9e"}
+        };
+    }
+}

Algorithm.CSharp/IndexOptionChainApisConsistencyRegressionAlgorithm.cs

@@ -0,0 +1,40 @@
+/*
+ * 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.Securities.Option;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting that the option chain APIs return consistent values for index options
+    /// See <see cref="QCAlgorithm.OptionChain(Symbol)"/> and <see cref="QCAlgorithm.OptionChainProvider"/>
+    /// </summary>
+    public class IndexOptionChainApisConsistencyRegressionAlgorithm : OptionChainApisConsistencyRegressionAlgorithm
+    {
+        protected override DateTime TestDate => new DateTime(2021, 1, 4);
+
+        protected override Option GetOption()
+        {
+            return AddIndexOption("SPX");
+        }
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 2862;
+    }
+}

Algorithm.CSharp/IndicatorSelectorsWorkWithDifferentOptions.cs

@@ -186,7 +186,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 1575423;
+        public long DataPoints => 1575425;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/LimitOrdersAreFilledAfterHoursForFuturesRegressionAlgorithm.cs

@@ -113,7 +113,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 82371;
+        public long DataPoints => 82372;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/MarketOrdersAreSupportedOnExtendedHoursForFuturesRegressionAlgorithm.cs

@@ -90,7 +90,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 82371;
+        public long DataPoints => 82372;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/OptionChainApisConsistencyRegressionAlgorithm.cs

@@ -0,0 +1,138 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Option;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting that the option chain APIs return consistent values.
+    /// See <see cref="QCAlgorithm.OptionChain(Symbol)"/> and <see cref="QCAlgorithm.OptionChainProvider"/>
+    /// </summary>
+    public class OptionChainApisConsistencyRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        protected virtual DateTime TestDate => new DateTime(2015, 12, 25);
+
+        public override void Initialize()
+        {
+            SetStartDate(TestDate);
+            SetEndDate(TestDate);
+
+            var option = GetOption();
+
+            var optionChainFromAlgorithmApi = OptionChain(option.Symbol).Contracts.Values.Select(x => x.Symbol).ToList();
+
+            var exchangeTime = UtcTime.ConvertFromUtc(option.Exchange.TimeZone);
+            var optionChainFromProviderApi = OptionChainProvider.GetOptionContractList(option.Symbol, exchangeTime).ToList();
+
+            if (optionChainFromAlgorithmApi.Count == 0)
+            {
+                throw new RegressionTestException("No options in chain from algorithm API");
+            }
+
+            if (optionChainFromProviderApi.Count == 0)
+            {
+                throw new RegressionTestException("No options in chain from provider API");
+            }
+
+            if (optionChainFromAlgorithmApi.Count != optionChainFromProviderApi.Count)
+            {
+                throw new RegressionTestException($"Expected {optionChainFromProviderApi.Count} options in chain from provider API, " +
+                    $"but got {optionChainFromAlgorithmApi.Count}");
+            }
+
+            for (var i = 0; i < optionChainFromAlgorithmApi.Count; i++)
+            {
+                var symbol1 = optionChainFromAlgorithmApi[i];
+                var symbol2 = optionChainFromProviderApi[i];
+
+                if (symbol1 != symbol2)
+                {
+                    throw new RegressionTestException($"Expected {symbol2} in chain from provider API, but got {symbol1}");
+                }
+            }
+        }
+
+        protected virtual Option GetOption()
+        {
+            return AddOption("GOOG");
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public virtual bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 2021;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual int AlgorithmHistoryDataPoints => 2;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public virtual AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/OptionChainsMultipleFullDataRegressionAlgorithm.cs

@@ -0,0 +1,142 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.Market;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm illustrating the usage of the <see cref="QCAlgorithm.OptionChains(IEnumerable{Symbol})"/> method
+    /// to get multiple option chains, which contains additional data besides the symbols, including prices, implied volatility and greeks.
+    /// It also shows how this data can be used to filter the contracts based on certain criteria.
+    /// </summary>
+    public class OptionChainsMultipleFullDataRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _googOptionContract;
+        private Symbol _spxOptionContract;
+
+        public override void Initialize()
+        {
+            SetStartDate(2015, 12, 24);
+            SetEndDate(2015, 12, 24);
+            SetCash(100000);
+
+            var goog = AddEquity("GOOG").Symbol;
+            var spx = AddIndex("SPX").Symbol;
+
+            var chains = OptionChains(new[] { goog, spx });
+
+            _googOptionContract = GetContract(chains, goog, TimeSpan.FromDays(10));
+            _spxOptionContract = GetContract(chains, spx, TimeSpan.FromDays(60));
+
+            AddOptionContract(_googOptionContract);
+            AddIndexOptionContract(_spxOptionContract);
+        }
+
+        private Symbol GetContract(OptionChains chains, Symbol underlying, TimeSpan expirySpan)
+        {
+            return chains
+                .Where(kvp => kvp.Key.Underlying == underlying)
+                .Select(kvp => kvp.Value)
+                .Single()
+                // Get contracts expiring within a given span, with an implied volatility greater than 0.5 and a delta less than 0.5
+                .Where(contractData => contractData.ID.Date - Time <= expirySpan &&
+                    contractData.ImpliedVolatility > 0.5m &&
+                    contractData.Greeks.Delta < 0.5m)
+                // Get the contract with the latest expiration date
+                .OrderByDescending(x => x.ID.Date)
+                .First();
+        }
+
+        public override void OnData(Slice slice)
+        {
+            // Do some trading with the selected contract for sample purposes
+            if (!Portfolio.Invested)
+            {
+                MarketOrder(_googOptionContract, 1);
+            }
+            else
+            {
+                Liquidate();
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 1059;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 2;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "210"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "96041"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$209.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", "GOOCV W6U7PD1F2WYU|GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "85.46%"},
+            {"OrderListHash", "a7ab1a9e64fe9ba76ea33a40a78a4e3b"}
+        };
+    }
+}

Algorithm.CSharp/OptionEquityCallBackspreadRegressionAlgorithm.cs

@@ -0,0 +1,128 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.Market;
+using QuantConnect.Securities.Option;
+using QuantConnect.Securities.Option.StrategyMatcher;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm exercising an equity Long Call Backspread option strategy and asserting it's being detected by Lean and works as expected
+    /// </summary>
+    public class OptionEquityCallBackspreadRegressionAlgorithm : OptionEquityBaseStrategyRegressionAlgorithm
+    {
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                OptionChain chain;
+                if (IsMarketOpen(_optionSymbol) && slice.OptionChains.TryGetValue(_optionSymbol, out chain))
+                {
+                    var callContracts = chain
+                        .Where(contract => contract.Right == OptionRight.Call);
+                    var expiry = callContracts.Min(x => x.Expiry);
+                    callContracts = callContracts.Where(x => x.Expiry == expiry)
+                        .OrderBy(x => x.Strike)
+                        .ToList();
+
+                    var strike = callContracts.Select(x => x.Strike).Distinct();
+                    if (strike.Count() < 2) return;
+
+                    var lowStrikeCall = callContracts.First();
+                    var highStrikeCall = callContracts.First(contract => contract.Strike > lowStrikeCall.Strike && contract.Expiry == expiry);
+
+                    var initialMargin = Portfolio.MarginRemaining;
+
+                    var optionStrategy = OptionStrategies.CallBackspread(_optionSymbol, lowStrikeCall.Strike, highStrikeCall.Strike, expiry);
+                    Buy(optionStrategy, 5);
+                    var freeMarginPostTrade = Portfolio.MarginRemaining;
+
+                    // It is a combination of bear call spread and long call
+                    AssertOptionStrategyIsPresent(OptionStrategyDefinitions.BearCallSpread.Name, 5);
+                    AssertOptionStrategyIsPresent(OptionStrategyDefinitions.NakedCall.Name, 5);
+
+                    // Should only involve the bear call spread part
+                    var expectedMarginUsage = (highStrikeCall.Strike - lowStrikeCall.Strike) * Securities[highStrikeCall.Symbol].SymbolProperties.ContractMultiplier * 5;
+
+                    if (expectedMarginUsage != Portfolio.TotalMarginUsed)
+                    {
+                        throw new Exception($"Unexpect margin used!:{Portfolio.TotalMarginUsed}");
+                    }
+
+                    // we payed the ask and value using the assets price
+                    var priceLadderDifference = GetPriceSpreadDifference(lowStrikeCall.Symbol, highStrikeCall.Symbol);
+                    if (initialMargin != (freeMarginPostTrade + expectedMarginUsage + _paidFees - priceLadderDifference))
+                    {
+                        throw new Exception("Unexpect margin remaining!");
+                    }
+                }
+            }
+        }
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 15023;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "2"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "200000"},
+            {"End Equity", "198565.25"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$9.75"},
+            {"Estimated Strategy Capacity", "$47000.00"},
+            {"Lowest Capacity Asset", "GOOCV W78ZERHAOVVQ|GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "11.81%"},
+            {"OrderListHash", "6ece6c59826ea66fa7b0a1094a0021c7"}
+        };
+    }
+}

Algorithm.CSharp/OptionEquityPutBackspreadRegressionAlgorithm.cs

@@ -0,0 +1,128 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.Market;
+using QuantConnect.Securities.Option;
+using QuantConnect.Securities.Option.StrategyMatcher;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm exercising an equity Long Put Backspread option strategy and asserting it's being detected by Lean and works as expected
+    /// </summary>
+    public class OptionEquityPutBackspreadRegressionAlgorithm : OptionEquityBaseStrategyRegressionAlgorithm
+    {
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                OptionChain chain;
+                if (IsMarketOpen(_optionSymbol) && slice.OptionChains.TryGetValue(_optionSymbol, out chain))
+                {
+                    var putContracts = chain
+                        .Where(contract => contract.Right == OptionRight.Put);
+                    var expiry = putContracts.Min(x => x.Expiry);
+                    putContracts = putContracts.Where(x => x.Expiry == expiry)
+                        .OrderBy(x => x.Strike)
+                        .ToList();
+
+                    var strike = putContracts.Select(x => x.Strike).Distinct();
+                    if (strike.Count() < 2) return;
+
+                    var lowStrikePut = putContracts.First();
+                    var highStrikePut = putContracts.First(contract => contract.Strike > lowStrikePut.Strike && contract.Expiry == lowStrikePut.Expiry);
+
+                    var initialMargin = Portfolio.MarginRemaining;
+
+                    var optionStrategy = OptionStrategies.PutBackspread(_optionSymbol, highStrikePut.Strike, lowStrikePut.Strike, expiry);
+                    Buy(optionStrategy, 5);
+                    var freeMarginPostTrade = Portfolio.MarginRemaining;
+
+                    // It is a combination of bull put spread and long put
+                    AssertOptionStrategyIsPresent(OptionStrategyDefinitions.BullPutSpread.Name, 5);
+                    AssertOptionStrategyIsPresent(OptionStrategyDefinitions.NakedPut.Name, 5);
+
+                    // Should only involve the bull put spread part
+                    var expectedMarginUsage = (highStrikePut.Strike - lowStrikePut.Strike) * Securities[highStrikePut.Symbol].SymbolProperties.ContractMultiplier * 5;
+
+                    if (expectedMarginUsage != Portfolio.TotalMarginUsed)
+                    {
+                        throw new Exception("Unexpect margin used!");
+                    }
+
+                    // we payed the ask and value using the assets price
+                    var priceLadderDifference = GetPriceSpreadDifference(lowStrikePut.Symbol, highStrikePut.Symbol);
+                    if (initialMargin != (freeMarginPostTrade + expectedMarginUsage + _paidFees - priceLadderDifference))
+                    {
+                        throw new Exception("Unexpect margin remaining!");
+                    }
+                }
+            }
+        }
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 15023;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "2"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "200000"},
+            {"End Equity", "199015.25"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$9.75"},
+            {"Estimated Strategy Capacity", "$1100000.00"},
+            {"Lowest Capacity Asset", "GOOCV 306CZL2DIL4G6|GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "9.15%"},
+            {"OrderListHash", "1a51f04db9201f960dc04668b7f5d41d"}
+        };
+    }
+}

Algorithm.CSharp/OptionEquityShortCallBackspreadRegressionAlgorithm.cs

@@ -0,0 +1,130 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.Market;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Option;
+using QuantConnect.Securities.Option.StrategyMatcher;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm exercising an equity Short Call Backspread option strategy and asserting it's being detected by Lean and works as expected
+    /// </summary>
+    public class OptionEquityShortCallBackspreadRegressionAlgorithm : OptionEquityBaseStrategyRegressionAlgorithm
+    {
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                OptionChain chain;
+                if (IsMarketOpen(_optionSymbol) && slice.OptionChains.TryGetValue(_optionSymbol, out chain))
+                {
+                    var callContracts = chain
+                        .Where(contract => contract.Right == OptionRight.Call);
+                    var expiry = callContracts.Min(x => x.Expiry);
+                    callContracts = callContracts.Where(x => x.Expiry == expiry)
+                        .OrderBy(x => x.Strike)
+                        .ToList();
+
+                    var strike = callContracts.Select(x => x.Strike).Distinct();
+                    if (strike.Count() < 2) return;
+
+                    var lowStrikeCall = callContracts.First();
+                    var highStrikeCall = callContracts.First(contract => contract.Strike > lowStrikeCall.Strike && contract.Expiry == lowStrikeCall.Expiry);
+
+                    var initialMargin = Portfolio.MarginRemaining;
+
+                    var optionStrategy = OptionStrategies.ShortCallBackspread(_optionSymbol, lowStrikeCall.Strike, highStrikeCall.Strike, expiry);
+                    Buy(optionStrategy, 5);
+                    var freeMarginPostTrade = Portfolio.MarginRemaining;
+
+                    // It is a combination of bull call spread and naked call
+                    AssertOptionStrategyIsPresent(OptionStrategyDefinitions.BullCallSpread.Name, 5);
+                    AssertOptionStrategyIsPresent(OptionStrategyDefinitions.NakedCall.Name, 5);
+
+                    // Should only involve the naked call part
+                    var security = Securities[highStrikeCall.Symbol];
+                    var expectedMarginUsage = security.BuyingPowerModel.GetMaintenanceMargin(MaintenanceMarginParameters.ForQuantityAtCurrentPrice(security, -5)).Value;
+
+                    if (expectedMarginUsage != Portfolio.TotalMarginUsed)
+                    {
+                        throw new Exception("Unexpect margin used!");
+                    }
+
+                    // we payed the ask and value using the assets price
+                    var priceLadderDifference = GetPriceSpreadDifference(lowStrikeCall.Symbol, highStrikeCall.Symbol);
+                    if (initialMargin != (freeMarginPostTrade + expectedMarginUsage + _paidFees - priceLadderDifference))
+                    {
+                        throw new Exception("Unexpect margin remaining!");
+                    }
+                }
+            }
+        }
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 15023;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "2"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "200000"},
+            {"End Equity", "199915.25"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$9.75"},
+            {"Estimated Strategy Capacity", "$53000.00"},
+            {"Lowest Capacity Asset", "GOOCV W78ZERHAOVVQ|GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "11.48%"},
+            {"OrderListHash", "357f13ed9e71c4dd8bb8e51e339ba7c5"}
+        };
+    }
+}

Algorithm.CSharp/OptionEquityShortPutBackspreadRegressionAlgorithm.cs

@@ -0,0 +1,130 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.Market;
+using QuantConnect.Securities;
+using QuantConnect.Securities.Option;
+using QuantConnect.Securities.Option.StrategyMatcher;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm exercising an equity Short Put Backspread option strategy and asserting it's being detected by Lean and works as expected
+    /// </summary>
+    public class OptionEquityShortPutBackspreadRegressionAlgorithm : OptionEquityBaseStrategyRegressionAlgorithm
+    {
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                OptionChain chain;
+                if (IsMarketOpen(_optionSymbol) && slice.OptionChains.TryGetValue(_optionSymbol, out chain))
+                {
+                    var putContracts = chain
+                        .Where(contract => contract.Right == OptionRight.Put);
+                    var expiry = putContracts.Min(x => x.Expiry);
+                    putContracts = putContracts.Where(x => x.Expiry == expiry)
+                        .OrderBy(x => x.Strike)
+                        .ToList();
+
+                    var strike = putContracts.Select(x => x.Strike).Distinct();
+                    if (strike.Count() < 2) return;
+
+                    var lowStrikePut = putContracts.First();
+                    var highStrikePut = putContracts.First(contract => contract.Strike > lowStrikePut.Strike && contract.Expiry == lowStrikePut.Expiry);
+
+                    var initialMargin = Portfolio.MarginRemaining;
+
+                    var optionStrategy = OptionStrategies.ShortPutBackspread(_optionSymbol, highStrikePut.Strike, lowStrikePut.Strike, expiry);
+                    Buy(optionStrategy, 5);
+                    var freeMarginPostTrade = Portfolio.MarginRemaining;
+
+                    // It is a combination of bear put spread and naked put
+                    AssertOptionStrategyIsPresent(OptionStrategyDefinitions.BearPutSpread.Name, 5);
+                    AssertOptionStrategyIsPresent(OptionStrategyDefinitions.NakedPut.Name, 5);
+
+                    // Should only involve the naked put part
+                    var security = Securities[lowStrikePut.Symbol];
+                    var expectedMarginUsage = security.BuyingPowerModel.GetMaintenanceMargin(MaintenanceMarginParameters.ForQuantityAtCurrentPrice(security, -5)).Value;
+
+                    if (expectedMarginUsage != Portfolio.TotalMarginUsed)
+                    {
+                        throw new Exception("Unexpect margin used!");
+                    }
+
+                    // we payed the ask and value using the assets price
+                    var priceLadderDifference = GetPriceSpreadDifference(lowStrikePut.Symbol, highStrikePut.Symbol);
+                    if (initialMargin != (freeMarginPostTrade + expectedMarginUsage + _paidFees - priceLadderDifference))
+                    {
+                        throw new Exception("Unexpect margin remaining!");
+                    }
+                }
+            }
+        }
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 15023;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "2"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "200000"},
+            {"End Equity", "199165.25"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$9.75"},
+            {"Estimated Strategy Capacity", "$1200000.00"},
+            {"Lowest Capacity Asset", "GOOCV 306CZL2DIL4G6|GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "8.84%"},
+            {"OrderListHash", "7294da06231632975e97c57721d26442"}
+        };
+    }
+}

Algorithm.CSharp/OptionOTMExpiryOrderHasZeroPriceRegressionAlgorithm.cs

@@ -153,7 +153,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 212195;
+        public long DataPoints => 212196;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -191,7 +191,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Annual Variance", "0.003"},
             {"Information Ratio", "-0.198"},
             {"Tracking Error", "0.377"},
-            {"Treynor Ratio", "-23.06"},
+            {"Treynor Ratio", "-23.065"},
             {"Total Fees", "$1.42"},
             {"Estimated Strategy Capacity", "$180000000.00"},
             {"Lowest Capacity Asset", "ES XFH59UPHGV9G|ES XFH59UK0MYO1"},

Algorithm.CSharp/OptionPriceModelForOptionStylesBaseRegressionAlgorithm.cs

@@ -86,7 +86,7 @@ namespace QuantConnect.Algorithm.CSharp
 
             foreach (var contract in contracts)
             {
-                Greeks greeks = new Greeks();
+                Greeks greeks = null;
                 try
                 {
                     greeks = contract.Greeks;
@@ -110,7 +110,8 @@ namespace QuantConnect.Algorithm.CSharp
                 // Greeks should be valid if they were successfuly accessed for supported option style
                 if (_optionStyleIsSupported)
                 {
-                    if (greeks.Delta == 0m && greeks.Gamma == 0m && greeks.Theta == 0m && greeks.Vega == 0m && greeks.Rho == 0m)
+                    if (greeks == null ||
+                        (greeks.Delta == 0m && greeks.Gamma == 0m && greeks.Theta == 0m && greeks.Vega == 0m && greeks.Rho == 0m))
                     {
                         throw new RegressionTestException($"Expected greeks to not be zero simultaneously for {contract.Symbol.Value}, an {_option.Style} style option, using {_option?.PriceModel.GetType().Name}, but they were");
                     }

Algorithm.CSharp/OptionPriceModelForSupportedEuropeanOptionRegressionAlgorithm.cs

@@ -41,7 +41,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 175;
+        public override long DataPoints => 177;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/OptionPriceModelForUnsupportedEuropeanOptionRegressionAlgorithm.cs

@@ -42,7 +42,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 175;
+        public override long DataPoints => 177;
 
         /// <summary>
         /// Data Points count of the algorithm history

Algorithm.CSharp/QuantConnect.Algorithm.CSharp.csproj

@@ -34,7 +34,7 @@
     <DebugType>portable</DebugType>
   </PropertyGroup>
   <ItemGroup>
-    <PackageReference Include="QuantConnect.pythonnet" Version="2.0.38" />
+    <PackageReference Include="QuantConnect.pythonnet" Version="2.0.41" />
     <PackageReference Include="Accord" Version="3.6.0" />
     <PackageReference Include="Accord.Fuzzy" Version="3.6.0" />
     <PackageReference Include="Accord.MachineLearning" Version="3.6.0" />

Algorithm.CSharp/RegisterIndicatorRegressionAlgorithm.cs

@@ -37,8 +37,8 @@ namespace QuantConnect.Algorithm.CSharp
         /// </summary>
         public override void Initialize()
         {
-            SetStartDate(2013, 10, 07);
-            SetEndDate(2013, 10, 09);
+            SetStartDate(2020, 01, 05);
+            SetEndDate(2020, 01, 10);
 
             var SP500 = QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME);
             _symbol = FutureChainProvider.GetFutureContractList(SP500, StartDate.AddDays(1)).First();
@@ -160,7 +160,7 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 4090;
+        public long DataPoints => 6803;
 
         /// <summary>
         /// Data Points count of the algorithm history
@@ -180,30 +180,30 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Orders", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-100.000%"},
-            {"Drawdown", "19.500%"},
+            {"Compounding Annual Return", "22662.692%"},
+            {"Drawdown", "1.700%"},
             {"Expectancy", "0"},
             {"Start Equity", "100000"},
-            {"End Equity", "88402.7"},
-            {"Net Profit", "-11.597%"},
-            {"Sharpe Ratio", "-0.687"},
+            {"End Equity", "109332.4"},
+            {"Net Profit", "9.332%"},
+            {"Sharpe Ratio", "157.927"},
             {"Sortino Ratio", "0"},
-            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Probabilistic Sharpe Ratio", "95.713%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "7.176"},
-            {"Beta", "10.771"},
-            {"Annual Standard Deviation", "1.467"},
-            {"Annual Variance", "2.151"},
-            {"Information Ratio", "-0.186"},
-            {"Tracking Error", "1.331"},
-            {"Treynor Ratio", "-0.094"},
-            {"Total Fees", "$23.65"},
-            {"Estimated Strategy Capacity", "$290000000.00"},
-            {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
-            {"Portfolio Turnover", "309.20%"},
-            {"OrderListHash", "448896f610140b728419d56313cc61bc"}
+            {"Alpha", "103.354"},
+            {"Beta", "1.96"},
+            {"Annual Standard Deviation", "0.663"},
+            {"Annual Variance", "0.439"},
+            {"Information Ratio", "159.787"},
+            {"Tracking Error", "0.651"},
+            {"Treynor Ratio", "53.381"},
+            {"Total Fees", "$15.05"},
+            {"Estimated Strategy Capacity", "$1900000000.00"},
+            {"Lowest Capacity Asset", "ES XCZJLC9NOB29"},
+            {"Portfolio Turnover", "171.57%"},
+            {"OrderListHash", "d814db6d5a9c97ee6de477ea06cd3834"}
         };
     }
 }

Algorithm.CSharp/StochasticIndicatorWarmsUpProperlyRegressionAlgorithm.cs

@@ -0,0 +1,177 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using QuantConnect.Data;
+using QuantConnect.Data.Consolidators;
+using QuantConnect.Indicators;
+using QuantConnect.Interfaces;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm that asserts Stochastic indicator, registered with a different resolution consolidator,
+    /// is warmed up properly by calling QCAlgorithm.WarmUpIndicator
+    /// </summary>
+    public class StochasticIndicatorWarmsUpProperlyRegressionAlgorithm: QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private bool _dataPointsReceived;
+        private Symbol _spy;
+        private RelativeStrengthIndex _rsi;
+        private RelativeStrengthIndex _rsiHistory;
+        private Stochastic _sto;
+        private Stochastic _stoHistory;
+
+        public override void Initialize()
+        {
+            SetStartDate(2020, 1, 1);
+            SetEndDate(2020, 2, 1);
+
+            _spy = AddEquity("SPY", Resolution.Hour).Symbol;
+
+            var dailyConsolidator = new TradeBarConsolidator(TimeSpan.FromDays(1));
+            _rsi = new RelativeStrengthIndex(14, MovingAverageType.Wilders);
+            _sto = new Stochastic("FIRST", 14, 3, 3);
+            RegisterIndicator(_spy, _rsi, dailyConsolidator);
+            RegisterIndicator(_spy, _sto, dailyConsolidator);
+
+            WarmUpIndicator(_spy, _rsi, TimeSpan.FromDays(1));
+            WarmUpIndicator(_spy, _sto, TimeSpan.FromDays(1));
+
+            _rsiHistory = new RelativeStrengthIndex(14, MovingAverageType.Wilders);
+            _stoHistory = new Stochastic("SECOND", 14, 3, 3);
+            RegisterIndicator(_spy, _rsiHistory, dailyConsolidator);
+            RegisterIndicator(_spy, _stoHistory, dailyConsolidator);
+
+            var history = History(_spy, Math.Max(_rsiHistory.WarmUpPeriod, _stoHistory.WarmUpPeriod), Resolution.Daily);
+
+            // Warm up RSI indicator
+            foreach (var bar in history)
+            {
+                _rsiHistory.Update(bar.EndTime, bar.Close);
+            }
+
+            // Warm up STO indicator
+            foreach (var bar in history.TakeLast(_stoHistory.WarmUpPeriod))
+            {
+                _stoHistory.Update(bar);
+            }
+
+            var indicators = new List<IIndicator>() { _rsi, _sto, _rsiHistory, _stoHistory };
+
+            foreach (var indicator in indicators)
+            {
+                if (!indicator.IsReady)
+                {
+                    throw new RegressionTestException($"{indicator.Name} should be ready, but it is not. Number of samples: {indicator.Samples}");
+                }
+            }
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (IsWarmingUp) return;
+
+            if (slice.ContainsKey(_spy))
+            {
+                _dataPointsReceived = true;
+
+                if (_rsi.Current.Value != _rsiHistory.Current.Value)
+                {
+                    throw new RegressionTestException($"Values of indicators differ: {_rsi.Name}: {_rsi.Current.Value} | {_rsiHistory.Name}: {_rsiHistory.Current.Value}");
+                }
+
+                if (_sto.StochK.Current.Value != _stoHistory.StochK.Current.Value)
+                {
+                    throw new RegressionTestException($"Stoch K values of indicators differ: {_sto.Name}.StochK: {_sto.StochK.Current.Value} | {_stoHistory.Name}.StochK: {_stoHistory.StochK.Current.Value}");
+                }
+
+                if (_sto.StochD.Current.Value != _stoHistory.StochD.Current.Value)
+                {
+                    throw new RegressionTestException($"Stoch D values of indicators differ: {_sto.Name}.StochD: {_sto.StochD.Current.Value} | {_stoHistory.Name}.StochD: {_stoHistory.StochD.Current.Value}");
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_dataPointsReceived)
+            {
+                throw new Exception("No data points received");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 302;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 44;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-0.016"},
+            {"Tracking Error", "0.101"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/StrictEndTimeLowerResolutionFillForwardRegressionAlgorithm.cs

@@ -0,0 +1,253 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.Consolidators;
+using QuantConnect.Data.Market;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using QuantConnect.Util;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting fill forwarded data behavior for consolidators and indicators.
+    /// 1. Test that the on-consolidated event is not called for fill forwarded data in identity and higher period consolidators
+    /// 2. Test that the intra-day fill-forwarded data is not fed to indicators
+    /// </summary>
+    public class StrictEndTimeLowerResolutionFillForwardRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Security _aapl;
+
+        private BaseData _lastNonFilledForwardedData;
+        private int _dataCount;
+        private int _indicatorUpdateCount;
+
+        protected virtual bool ExtendedMarketHours => false;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 07);
+            SetEndDate(2013, 10, 30);
+
+            Settings.DailyPreciseEndTime = true;
+
+            // Fill forward resolution will be minute
+            AddEquity("SPY", Resolution.Minute);
+            _aapl = AddEquity("AAPL", Resolution.Daily, extendedMarketHours: ExtendedMarketHours);
+
+            var tradableDates = QuantConnect.Time.EachTradeableDayInTimeZone(_aapl.Exchange.Hours, StartDate, EndDate,
+                _aapl.Exchange.TimeZone, _aapl.IsExtendedMarketHours).ToList();
+
+            TestIdentityConsolidator(tradableDates);
+            TestHigherPeriodConsolidator(tradableDates);
+            TestIndicator(tradableDates);
+        }
+
+        private void TestIdentityConsolidator(List<DateTime> tradableDates)
+        {
+            var i = 0;
+            var consolidator = Consolidate<TradeBar>(_aapl.Symbol, TimeSpan.FromDays(1), (bar) =>
+            {
+                var expectedDate = tradableDates[i++];
+                var schedule = LeanData.GetDailyCalendar(expectedDate.AddDays(1), _aapl.Exchange, false);
+
+                if (bar.Time != schedule.Start || bar.EndTime != schedule.End)
+                {
+                    throw new RegressionTestException($"Unexpected consolidated bar time. " +
+                        $"Expected: [{schedule.Start} - {schedule.End}], Actual: [{bar.Time} - {bar.EndTime}]");
+                }
+
+                Debug($"Consolidated (identity) :: {bar}");
+            });
+
+            if (consolidator is not IdentityDataConsolidator<TradeBar>)
+            {
+                throw new RegressionTestException($"Unexpected consolidator type. " +
+                    $"Expected {typeof(IdentityDataConsolidator<TradeBar>)} but was {consolidator.GetType()}");
+            }
+        }
+
+        private void TestHigherPeriodConsolidator(List<DateTime> tradableDates)
+        {
+            var i = 0;
+            // Add a consolidator to assert that fill forward data is not used
+            Consolidate<TradeBar>(_aapl.Symbol, TimeSpan.FromDays(2), (bar) =>
+            {
+                var expectedStartDate = tradableDates[i++];
+                var startDateSchedule = LeanData.GetDailyCalendar(expectedStartDate.AddDays(1), _aapl.Exchange, false);
+
+                var expectedStartTime = startDateSchedule.Start;
+                var expectedEndTime = expectedStartTime.AddDays(2);
+
+                if (bar.Time != expectedStartTime || bar.EndTime != expectedEndTime)
+                {
+                    throw new RegressionTestException($"Unexpected consolidated bar time. " +
+                        $"Expected: [{expectedStartTime} - {expectedEndTime}], Actual: [{bar.Time} - {bar.EndTime}]");
+                }
+
+                if (tradableDates[i] == expectedStartDate.AddDays(1))
+                {
+                    i++;
+                }
+
+                Debug($"Consolidated (2 days) :: {bar}");
+            });
+        }
+
+        private void TestIndicator(List<DateTime> tradableDates)
+        {
+            var i = 0;
+            EMA(_aapl.Symbol, 3, Resolution.Daily).Updated += (sender, data) =>
+            {
+                _indicatorUpdateCount++;
+
+                var expectedEndTime = _aapl.Exchange.Hours.GetNextMarketClose(tradableDates[i++], false);
+                if (data.EndTime != expectedEndTime)
+                {
+                    throw new RegressionTestException($"Unexpected EMA time. Expected: {expectedEndTime}, Actual: {data.EndTime}");
+                }
+
+                Debug($"EMA :: [{data.EndTime}] {data}");
+            };
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (slice.TryGetValue(_aapl.Symbol, out var data))
+            {
+                var baseData = data as BaseData;
+                if (!baseData.IsFillForward)
+                {
+                    _lastNonFilledForwardedData = baseData;
+                }
+
+                var timeInExchangeTz = UtcTime.ConvertFromUtc(_aapl.Exchange.TimeZone);
+                var daySchedule = LeanData.GetDailyCalendar(timeInExchangeTz, _aapl.Exchange, false);
+
+                if (timeInExchangeTz == daySchedule.End)
+                {
+                    if (baseData.IsFillForward)
+                    {
+                        throw new RegressionTestException("End of day data should not be fill forward for daily subscription when data is available");
+                    }
+                }
+                else
+                {
+                    if (!baseData.IsFillForward
+                        || _lastNonFilledForwardedData == null
+                        || _lastNonFilledForwardedData.Time.Date != baseData.Time.Date
+                        || _lastNonFilledForwardedData.EndTime.Date != baseData.EndTime.Date)
+                    {
+                        throw new RegressionTestException("Data should be fill forward to minute resolution during the day");
+                    }
+                }
+
+                _dataCount++;
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            var tradableDates = QuantConnect.Time.EachTradeableDay(_aapl, StartDate.AddDays(1), EndDate, ExtendedMarketHours);
+            var tradableDatesCount = 1;
+            var expectedDataCount = 1; // One for the first day
+            foreach (var date in tradableDates)
+            {
+                tradableDatesCount++;
+                var hours = _aapl.Exchange.Hours.GetMarketHours(date);
+                foreach (var segment in hours.Segments)
+                {
+                    if (ExtendedMarketHours || segment.State == MarketHoursState.Market)
+                    {
+                        expectedDataCount += (int)(segment.End - segment.Start).TotalMinutes;
+                    }
+                }
+            }
+
+            if (_dataCount != expectedDataCount)
+            {
+                throw new RegressionTestException($"Unexpected data count. Expected: {expectedDataCount}, Actual: {_dataCount}");
+            }
+
+            if (_indicatorUpdateCount != tradableDatesCount)
+            {
+                throw new RegressionTestException($"Unexpected indicator update count. Expected: {tradableDatesCount}, Actual: {_indicatorUpdateCount}");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 20805;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-7.12"},
+            {"Tracking Error", "0.109"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/StrictEndTimeLowerResolutionFillForwardWithExtendedMarketHoursRegressionAlgorithm.cs

@@ -0,0 +1,29 @@
+/*
+ * 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.
+*/
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting fill forwarded data behavior for consolidators and indicators.
+    /// 1. Test that the on-consolidated event is not called for fill forwarded data in identity and higher period consolidators
+    /// 2. Test that the intra-day fill-forwarded data is not fed to indicators
+    /// </summary>
+    public class StrictEndTimeLowerResolutionFillForwardWithExtendedMarketHoursRegressionAlgorithm : StrictEndTimeLowerResolutionFillForwardRegressionAlgorithm
+    {
+        protected override bool ExtendedMarketHours => true;
+
+        public override long DataPoints => 30495;
+    }
+}

Algorithm.CSharp/VolumeShareSlippageModelAlgorithm.cs

@@ -0,0 +1,135 @@
+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Data;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders.Slippage;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Example algorithm implementing VolumeShareSlippageModel.
+    /// </summary>
+    public class VolumeShareSlippageModelAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private List<Symbol> _longs = new();
+        private List<Symbol> _shorts = new();
+
+        public override void Initialize()
+        {
+            SetStartDate(2020, 11, 29);
+            SetEndDate(2020, 12, 2);
+            // To set the slippage model to limit to fill only 30% volume of the historical volume, with 5% slippage impact.
+            SetSecurityInitializer((security) => security.SetSlippageModel(new VolumeShareSlippageModel(0.3m, 0.05m)));
+
+            // Create SPY symbol to explore its constituents.
+            var spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
+
+            UniverseSettings.Resolution = Resolution.Daily;
+            // Add universe to trade on the most and least weighted stocks among SPY constituents.
+            AddUniverse(Universe.ETF(spy, universeFilterFunc: Selection));
+        }
+
+        private IEnumerable<Symbol> Selection(IEnumerable<ETFConstituentUniverse> constituents)
+        {
+            var sortedByDollarVolume = constituents.OrderBy(x => x.Weight).ToList();
+            // Add the 10 most weighted stocks to the universe to long later.
+            _longs = sortedByDollarVolume.TakeLast(10)
+                .Select(x => x.Symbol)
+                .ToList();
+            // Add the 10 least weighted stocks to the universe to short later.
+            _shorts = sortedByDollarVolume.Take(10)
+                .Select(x => x.Symbol)
+                .ToList();
+
+            return _longs.Union(_shorts);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            // Equally invest into the selected stocks to evenly dissipate capital risk.
+            // Dollar neutral of long and short stocks to eliminate systematic risk, only capitalize the popularity gap.
+            var targets = _longs.Select(symbol => new PortfolioTarget(symbol, 0.05m)).ToList();
+            targets.AddRange(_shorts.Select(symbol => new PortfolioTarget(symbol, -0.05m)).ToList());
+
+            // Liquidate the ones not being the most and least popularity stocks to release fund for higher expected return trades.
+            SetHoldings(targets, liquidateExistingHoldings: true);
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 1035;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "4"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "20.900%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100190.84"},
+            {"Net Profit", "0.191%"},
+            {"Sharpe Ratio", "9.794"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.297"},
+            {"Beta", "-0.064"},
+            {"Annual Standard Deviation", "0.017"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-18.213"},
+            {"Tracking Error", "0.099"},
+            {"Treynor Ratio", "-2.695"},
+            {"Total Fees", "$4.00"},
+            {"Estimated Strategy Capacity", "$4400000000.00"},
+            {"Lowest Capacity Asset", "GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "4.22%"},
+            {"OrderListHash", "9d2bd0df7c094c393e77f72b7739bfa0"}
+        };
+    }
+}

Algorithm.CSharp/WarmupFutureTimeSpanWarmupRegressionAlgorithm.cs

@@ -36,6 +36,6 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public override long DataPoints => 28889;
+        public override long DataPoints => 28892;
     }
 }

Algorithm.CSharp/ZeroDTEIndexOptionsRegressionAlgorithm.cs

@@ -0,0 +1,98 @@
+/*
+ * 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;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Algorithm asserting that options are selected every day and that selection for 0DTE contracts works as expected,
+    /// always including the contracts that expire the same date the option chain belongs to.
+    /// </summary>
+    public class ZeroDTEIndexOptionsRegressionAlgorithm : ZeroDTEOptionsRegressionAlgorithm
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2021, 01, 15);
+            SetEndDate(2021, 01, 15);
+            SetCash(100000);
+
+            var index = AddIndex("SPX");
+            var indexOption = AddIndexOption(index.Symbol);
+
+            indexOption.SetFilter(u => u.IncludeWeeklys().Expiration(0, 0));
+            _option = indexOption;
+
+            // use the underlying equity as the benchmark
+            SetBenchmark(index.Symbol);
+
+            _selectionDays = new List<DateTime>()
+            {
+                new DateTime(2021, 01, 15),
+            };
+        }
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public override long DataPoints => 27;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public override int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public override AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.CSharp/ZeroDTEOptionsRegressionAlgorithm.cs

@@ -20,6 +20,7 @@ using System.Linq;
 using QuantConnect.Interfaces;
 using QuantConnect.Data.UniverseSelection;
 using QuantConnect.Securities;
+using QuantConnect.Securities.Option;
 
 namespace QuantConnect.Algorithm.CSharp
 {
@@ -29,10 +30,13 @@ namespace QuantConnect.Algorithm.CSharp
     /// </summary>
     public class ZeroDTEOptionsRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
     {
-        private List<DateTime> _selectionDays;
+        protected List<DateTime> _selectionDays;
         private int _currentSelectionDayIndex;
 
         private int _previouslyAddedContracts;
+        private bool _selectionChecked;
+
+        protected Option _option;
 
         public override void Initialize()
         {
@@ -44,6 +48,7 @@ namespace QuantConnect.Algorithm.CSharp
             var option = AddOption(equity.Symbol);
 
             option.SetFilter(u => u.IncludeWeeklys().Expiration(0, 0));
+            _option = option;
 
             // use the underlying equity as the benchmark
             SetBenchmark(equity.Symbol);
@@ -62,27 +67,43 @@ namespace QuantConnect.Algorithm.CSharp
 
         public override void OnSecuritiesChanged(SecurityChanges changes)
         {
-            // We expect selection every trading day
-            if (Time.Date != _selectionDays[_currentSelectionDayIndex++])
+            var exchangeTime = UtcTime.ConvertFromUtc(_option.Exchange.TimeZone);
+
+            // Selection happens at midnight
+            if (exchangeTime.TimeOfDay == TimeSpan.Zero)
             {
-                throw new RegressionTestException($"Unexpected date. Expected {_selectionDays[_currentSelectionDayIndex]} but was {Time.Date}");
+                _selectionChecked = true;
+
+                // We expect selection every trading day
+                if (Time.Date != _selectionDays[_currentSelectionDayIndex++])
+                {
+                    throw new RegressionTestException($"Unexpected date. Expected {_selectionDays[_currentSelectionDayIndex]} but was {Time.Date}");
+                }
+
+                var addedOptions = changes.AddedSecurities.Where(x => x.Symbol.SecurityType == _option.Symbol.SecurityType && !x.Symbol.IsCanonical()).ToList();
+
+                if (addedOptions.Count == 0)
+                {
+                    throw new RegressionTestException("No options were added");
+                }
+
+                var removedOptions = changes.RemovedSecurities.Where(x => x.Symbol.SecurityType == _option.Symbol.SecurityType && !x.Symbol.IsCanonical()).ToList();
+
+                // Since we are selecting only 0DTE contracts, they must be deselected that same day
+                if (removedOptions.Count != _previouslyAddedContracts)
+                {
+                    throw new RegressionTestException($"Unexpected number of removed contracts. Expected {_previouslyAddedContracts} but was {removedOptions.Count}");
+                }
+                _previouslyAddedContracts = addedOptions.Count;
             }
+        }
 
-            var addedOptions = changes.AddedSecurities.Where(x => x.Symbol.SecurityType == SecurityType.Option && !x.Symbol.IsCanonical()).ToList();
-
-            if (addedOptions.Count == 0)
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_selectionChecked)
             {
-                throw new RegressionTestException("No options were added");
+                throw new RegressionTestException("Selection was not checked");
             }
-
-            var removedOptions = changes.RemovedSecurities.Where(x => x.Symbol.SecurityType == SecurityType.Option && !x.Symbol.IsCanonical()).ToList();
-
-            // Since we are selecting only 0DTE contracts, they must be deselected that same day
-            if (removedOptions.Count != _previouslyAddedContracts)
-            {
-                throw new RegressionTestException($"Unexpected number of removed contracts. Expected {_previouslyAddedContracts} but was {removedOptions.Count}");
-            }
-            _previouslyAddedContracts = addedOptions.Count;
         }
 
         /// <summary>
@@ -93,27 +114,27 @@ namespace QuantConnect.Algorithm.CSharp
         /// <summary>
         /// This is used by the regression test system to indicate which languages this algorithm is written in.
         /// </summary>
-        public List<Language> Languages { get; } = new() { Language.CSharp };
+        public virtual List<Language> Languages { get; } = new() { Language.CSharp };
 
         /// <summary>
         /// Data Points count of all timeslices of algorithm
         /// </summary>
-        public long DataPoints => 227;
+        public virtual long DataPoints => 227;
 
         /// <summary>
         /// Data Points count of the algorithm history
         /// </summary>
-        public int AlgorithmHistoryDataPoints => 0;
+        public virtual int AlgorithmHistoryDataPoints => 0;
 
         /// <summary>
         /// Final status of the algorithm
         /// </summary>
-        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+        public virtual AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
 
         /// <summary>
         /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
         /// </summary>
-        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
         {
             {"Total Orders", "0"},
             {"Average Win", "0%"},

Algorithm.Framework/QuantConnect.Algorithm.Framework.csproj

@@ -30,7 +30,7 @@
     <PackageLicenseFile>LICENSE</PackageLicenseFile>
   </PropertyGroup>
   <ItemGroup>
-    <PackageReference Include="QuantConnect.pythonnet" Version="2.0.38" />
+    <PackageReference Include="QuantConnect.pythonnet" Version="2.0.41" />
     <PackageReference Include="Accord" Version="3.6.0" />
     <PackageReference Include="Accord.Math" Version="3.6.0" />
     <PackageReference Include="Accord.Statistics" Version="3.6.0" />

Algorithm.Framework/Selection/OpenInterestFutureUniverseSelectionModel.cs

@@ -70,11 +70,12 @@ namespace QuantConnect.Algorithm.Framework.Selection
         }
 
         /// <summary>
-        ///     Defines the future chain universe filter
+        /// Defines the future chain universe filter
         /// </summary>
         protected override FutureFilterUniverse Filter(FutureFilterUniverse filter)
         {
-            return filter.Contracts(FilterByOpenInterest(filter.ToDictionary(x => x, x => _marketHoursDatabase.GetEntry(x.ID.Market, x, x.ID.SecurityType))));
+            // Remove duplicated keys
+            return filter.Contracts(FilterByOpenInterest(filter.DistinctBy(x => x).ToDictionary(x => x, x => _marketHoursDatabase.GetEntry(x.ID.Market, x, x.ID.SecurityType))));
         }
 
         /// <summary>

Algorithm.Python/BaseFrameworkRegressionAlgorithm.py

@@ -35,7 +35,7 @@ class BaseFrameworkRegressionAlgorithm(QCAlgorithm):
         # With this procedure, the Alpha Model will experience multiple universe changes
         self.add_universe_selection(ScheduledUniverseSelectionModel(
             self.date_rules.every_day(), self.time_rules.midnight,
-            lambda dt: symbols if dt.replace(tzinfo=None) < self.end_date - timedelta(1) else []))
+            lambda dt: symbols if dt < self.end_date - timedelta(1) else []))
 
         self.set_alpha(ConstantAlphaModel(InsightType.PRICE, InsightDirection.UP, timedelta(31), 0.025, None))
         self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel())

Algorithm.Python/CallbackCommandRegressionAlgorithm.py

@@ -0,0 +1,100 @@
+# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from AlgorithmImports import *
+
+class InvalidCommand():
+    variable = 10
+
+class VoidCommand():
+    quantity = 0
+    target = []
+    parameters = {}
+    targettime = None
+
+    def run(self, algo: QCAlgorithm) -> bool | None:
+        if not self.targettime or self.targettime != algo.time:
+            return
+        tag = self.parameters["tag"]
+        algo.order(self.target[0], self.get_quantity(), tag=tag)
+
+    def get_quantity(self):
+        return self.quantity
+
+class BoolCommand(Command):
+    something_else = {}
+    array_test = []
+    result = False
+
+    def run(self, algo: QCAlgorithm) -> bool | None:
+        trade_ibm = self.my_custom_method()
+        if trade_ibm:
+            algo.debug(f"BoolCommand.run: {str(self)}")
+            algo.buy("IBM", 1)
+        return trade_ibm
+
+    def my_custom_method(self):
+        return self.result
+
+### <summary>
+### Regression algorithm asserting the behavior of different callback commands call
+### </summary>
+class CallbackCommandRegressionAlgorithm(QCAlgorithm):
+    def initialize(self):
+        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
+
+        self.set_start_date(2013, 10, 7)
+        self.set_end_date(2013, 10, 11)
+
+        self.add_equity("SPY")
+        self.add_equity("IBM")
+        self.add_equity("BAC")
+
+        self.add_command(VoidCommand)
+        self.add_command(BoolCommand)
+
+        threw_exception = False
+        try:
+            self.add_command(InvalidCommand)
+        except:
+            threw_exception = True
+        if not threw_exception:
+            raise ValueError('InvalidCommand did not throw!')
+
+        bool_command = BoolCommand()
+        bool_command.result = True
+        bool_command.something_else = { "Property": 10 }
+        bool_command.array_test = [ "SPY", "BTCUSD" ]
+        link = self.link(bool_command)
+        if "&command[array_test][0]=SPY&command[array_test][1]=BTCUSD&command[result]=True&command[something_else][Property]=10&command[$type]=BoolCommand" not in link:
+            raise ValueError(f'Invalid link was generated! {link}')
+
+        potential_command = VoidCommand()
+        potential_command.target = [ "BAC" ]
+        potential_command.quantity = 10
+        potential_command.parameters = { "tag": "Signal X" }
+
+        command_link = self.link(potential_command)
+        if "command[target][0]=BAC&command[quantity]=10&command[parameters][tag]=Signal+X&command[$type]=VoidCommand" not in command_link:
+            raise ValueError(f'Invalid link was generated! {command_link}')
+        self.notify.email("email@address", "Trade Command Event", f"Signal X trade\nFollow link to trigger: {command_link}")
+
+        untyped_command_link = self.link({ "symbol": "SPY", "parameters": { "quantity": 10 } })
+        if "&command[symbol]=SPY&command[parameters][quantity]=10" not in untyped_command_link:
+            raise ValueError(f'Invalid link was generated! {untyped_command_link}')
+        self.notify.email("email@address", "Untyped Command Event", f"Signal Y trade\nFollow link to trigger: {untyped_command_link}")
+
+    def on_command(self, data):
+        self.debug(f"on_command: {str(data)}")
+        self.buy(data.symbol, data.parameters["quantity"])
+        return True # False, None

Algorithm.Python/ConsolidateHourBarsIntoDailyBarsRegressionAlgorithm.py

@@ -0,0 +1,69 @@
+# 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.
+
+from AlgorithmImports import *
+
+### <summary>
+### This regression algorithm asserts the consolidated US equity daily bars from the hour bars exactly matches
+### the daily bars returned from the database
+### </summary>
+class ConsolidateHourBarsIntoDailyBarsRegressionAlgorithm(QCAlgorithm):
+    def initialize(self):
+        self.set_start_date(2020, 5, 1)
+        self.set_end_date(2020, 6, 5)
+
+        self.spy = self.add_equity("SPY", Resolution.HOUR).symbol
+
+        # We will use these two indicators to compare the daily consolidated bars equals
+        # the ones returned from the database. We use this specific type of indicator as
+        # it depends on its previous values. Thus, if at some point the bars received by
+        # the indicators differ, so will their final values
+        self._rsi = RelativeStrengthIndex("First", 15, MovingAverageType.WILDERS)
+        self.register_indicator(self.spy, self._rsi, Resolution.DAILY, selector= lambda bar: (bar.close + bar.open) / 2)
+
+        # We won't register this indicator as we will update it manually at the end of the
+        # month, so that we can compare the values of the indicator that received consolidated
+        # bars and the values of this one
+        self._rsi_timedelta = RelativeStrengthIndex("Second", 15, MovingAverageType.WILDERS)
+        self._values = {}
+        self.count = 0;
+        self._indicators_compared = False;
+
+    def on_data(self, data: Slice):
+        if self.is_warming_up:
+            return
+
+        if data.contains_key(self.spy) and data[self.spy] != None:
+            if self.time.month == self.end_date.month:
+                history = self.history[TradeBar](self.spy, self.count, Resolution.DAILY)
+                for bar in history:
+                    time = bar.end_time.strftime('%Y-%m-%d')
+                    average = (bar.close + bar.open) / 2
+                    self._rsi_timedelta.update(bar.end_time, average)
+                    if self._rsi_timedelta.current.value != self._values[time]:
+                        raise Exception(f"Both {self._rsi.name} and {self._rsi_timedelta.name} should have the same values, but they differ. {self._rsi.name}: {self._values[time]} | {self._rsi_timedelta.name}: {self._rsi_timedelta.current.value}")
+                self._indicators_compared = True
+                self.quit()
+            else:
+                time = self.time.strftime('%Y-%m-%d')
+                self._values[time] = self._rsi.current.value
+
+                # Since the symbol resolution is hour and the symbol is equity, we know the last bar received in a day will
+                # be at the market close, this is 16h. We need to count how many daily bars were consolidated in order to know
+                # how many we need to request from the history
+                if self.time.hour == 16:
+                    self.count += 1
+
+    def on_end_of_algorithm(self):
+        if not self._indicators_compared:
+            raise Exception(f"Indicators {self._rsi.name} and {self._rsi_timedelta.name} should have been compared, but they were not. Please make sure the indicators are getting SPY data")

Algorithm.Python/ConsolidateRegressionAlgorithm.py

@@ -21,14 +21,44 @@ class ConsolidateRegressionAlgorithm(QCAlgorithm):
 
     # Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
     def initialize(self):
-        self.set_start_date(2013, 10, 8)
-        self.set_end_date(2013, 10, 20)
+        self.set_start_date(2020, 1, 5)
+        self.set_end_date(2020, 1, 20)
 
         SP500 = Symbol.create(Futures.Indices.SP_500_E_MINI, SecurityType.FUTURE, Market.CME)
-        self._symbol = _symbol = self.future_chain_provider.get_future_contract_list(SP500, self.start_date)[0]
-        self.add_future_contract(_symbol)
+        symbol = self.future_chain_provider.get_future_contract_list(SP500, self.start_date)[0]
+        self._future = self.add_future_contract(symbol)
 
-        self._consolidation_counts = [0] * 6
+        tradable_dates_count = len(list(Time.each_tradeable_day_in_time_zone(self._future.exchange.hours,
+                                                                             self.start_date,
+                                                                             self.end_date,
+                                                                             self._future.exchange.time_zone,
+                                                                             False)));
+        self._expected_consolidation_counts = [];
+
+        self.consolidate(symbol, Calendar.MONTHLY, lambda bar: self.update_monthly_consolidator(bar, -1)) # shouldn't consolidate
+
+        self.consolidate(symbol, Calendar.WEEKLY, TickType.TRADE, lambda bar: self.update_weekly_consolidator(bar))
+
+        self.consolidate(symbol, Resolution.DAILY, lambda bar: self.update_trade_bar(bar, 0))
+        self._expected_consolidation_counts.append(tradable_dates_count)
+
+        self.consolidate(symbol, Resolution.DAILY, TickType.QUOTE, lambda bar: self.update_quote_bar(bar, 1))
+        self._expected_consolidation_counts.append(tradable_dates_count)
+
+        self.consolidate(symbol, timedelta(1), lambda bar: self.update_trade_bar(bar, 2))
+        self._expected_consolidation_counts.append(tradable_dates_count - 1)
+
+        self.consolidate(symbol, timedelta(1), TickType.QUOTE, lambda bar: self.update_quote_bar(bar, 3))
+        self._expected_consolidation_counts.append(tradable_dates_count - 1)
+
+        # sending None tick type
+        self.consolidate(symbol, timedelta(1), None, lambda bar: self.update_trade_bar(bar, 4))
+        self._expected_consolidation_counts.append(tradable_dates_count - 1)
+
+        self.consolidate(symbol, Resolution.DAILY, None, lambda bar: self.update_trade_bar(bar, 5))
+        self._expected_consolidation_counts.append(tradable_dates_count)
+
+        self._consolidation_counts = [0] * len(self._expected_consolidation_counts)
         self._smas = [SimpleMovingAverage(10) for x in self._consolidation_counts]
         self._last_sma_updates = [datetime.min for x in self._consolidation_counts]
         self._monthly_consolidator_sma = SimpleMovingAverage(10)
@@ -37,26 +67,9 @@ class ConsolidateRegressionAlgorithm(QCAlgorithm):
         self._weekly_consolidation_count = 0
         self._last_weekly_sma_update = datetime.min
 
-        self.consolidate(_symbol, Calendar.MONTHLY, lambda bar: self.update_monthly_consolidator(bar, -1)) # shouldn't consolidate
-
-        self.consolidate(_symbol, Calendar.WEEKLY, TickType.TRADE, lambda bar: self.update_weekly_consolidator(bar))
-
-        self.consolidate(_symbol, Resolution.DAILY, lambda bar: self.update_trade_bar(bar, 0))
-
-        self.consolidate(_symbol, Resolution.DAILY, TickType.QUOTE, lambda bar: self.update_quote_bar(bar, 1))
-
-        self.consolidate(_symbol, timedelta(1), lambda bar: self.update_trade_bar(bar, 2))
-
-        self.consolidate(_symbol, timedelta(1), TickType.QUOTE, lambda bar: self.update_quote_bar(bar, 3))
-
-        # sending None tick type
-        self.consolidate(_symbol, timedelta(1), None, lambda bar: self.update_trade_bar(bar, 4))
-
-        self.consolidate(_symbol, Resolution.DAILY, None, lambda bar: self.update_trade_bar(bar, 5))
-
         # custom data
         self._custom_data_consolidator = 0
-        custom_symbol = self.add_data(Bitcoin, "BTC", Resolution.MINUTE).symbol
+        custom_symbol = self.add_data(Bitcoin, "BTC", Resolution.DAILY).symbol
         self.consolidate(custom_symbol, timedelta(1), lambda bar: self.increment_counter(1))
 
         self._custom_data_consolidator2 = 0
@@ -87,18 +100,25 @@ class ConsolidateRegressionAlgorithm(QCAlgorithm):
         self._last_weekly_sma_update = bar.end_time
         self._weekly_consolidation_count += 1
 
-    def  OnEndOfAlgorithm(self):
-        expected_consolidations = 9
-        expected_weekly_consolidations = 1
-        if (any(i != expected_consolidations for i in self._consolidation_counts) or
-            self._weekly_consolidation_count != expected_weekly_consolidations or
-            self._custom_data_consolidator == 0 or
-            self._custom_data_consolidator2 == 0):
-            raise ValueError("Unexpected consolidation count")
+    def on_end_of_algorithm(self):
+        for i, expected_consolidation_count in enumerate(self._expected_consolidation_counts):
+            consolidation_count = self._consolidation_counts[i]
+            if consolidation_count != expected_consolidation_count:
+                raise ValueError(f"Unexpected consolidation count for index {i}: expected {expected_consolidation_count} but was {consolidation_count}")
+
+        expected_weekly_consolidations = (self.end_date - self.start_date).days // 7
+        if self._weekly_consolidation_count != expected_weekly_consolidations:
+            raise ValueError(f"Expected {expected_weekly_consolidations} weekly consolidations but found {self._weekly_consolidation_count}")
+
+        if self._custom_data_consolidator == 0:
+            raise ValueError("Custom data consolidator did not consolidate any data")
+
+        if self._custom_data_consolidator2 == 0:
+            raise ValueError("Custom data consolidator 2 did not consolidate any data")
 
         for i, sma in enumerate(self._smas):
-            if sma.samples != expected_consolidations:
-                raise Exception(f"Expected {expected_consolidations} samples in each SMA but found {sma.samples} in SMA in index {i}")
+            if sma.samples != self._expected_consolidation_counts[i]:
+                raise Exception(f"Expected {self._expected_consolidation_counts[i]} samples in each SMA but found {sma.samples} in SMA in index {i}")
 
             last_update = self._last_sma_updates[i]
             if sma.current.time != last_update:
@@ -115,5 +135,5 @@ class ConsolidateRegressionAlgorithm(QCAlgorithm):
 
     # on_data event is the primary entry point for your algorithm. Each new data point will be pumped in here.
     def on_data(self, data):
-        if not self.portfolio.invested:
-           self.set_holdings(self._symbol, 0.5)
+        if not self.portfolio.invested and self._future.has_data:
+           self.set_holdings(self._future.symbol, 0.5)

Algorithm.Python/ContinuousFutureRegressionAlgorithm.py

@@ -25,7 +25,7 @@ class ContinuousFutureRegressionAlgorithm(QCAlgorithm):
         self.set_start_date(2013, 7, 1)
         self.set_end_date(2014, 1, 1)
 
-        self._mappings = []
+        self._previous_mapped_contract_symbols = []
         self._last_date_log = -1
         self._continuous_contract = self.add_future(Futures.Indices.SP_500_E_MINI,
                                                   data_normalization_mode = DataNormalizationMode.BACKWARDS_RATIO,
@@ -45,7 +45,7 @@ class ContinuousFutureRegressionAlgorithm(QCAlgorithm):
 
         for changed_event in data.symbol_changed_events.values():
             if changed_event.symbol == self._continuous_contract.symbol:
-                self._mappings.append(changed_event)
+                self._previous_mapped_contract_symbols.append(self.symbol(changed_event.old_symbol))
                 self.log(f"SymbolChanged event: {changed_event}")
 
                 if self._current_mapped_symbol == self._continuous_contract.mapped:
@@ -77,5 +77,14 @@ class ContinuousFutureRegressionAlgorithm(QCAlgorithm):
 
     def on_end_of_algorithm(self):
         expected_mapping_counts = 2
-        if len(self._mappings) != expected_mapping_counts:
-            raise ValueError(f"Unexpected symbol changed events: {self._mappings.count()}, was expecting {expected_mapping_counts}")
+        if len(self._previous_mapped_contract_symbols) != expected_mapping_counts:
+            raise ValueError(f"Unexpected symbol changed events: {len(self._previous_mapped_contract_symbols)}, was expecting {expected_mapping_counts}")
+
+        delisted_securities = [
+            [security for security in self.securities.total if security.symbol == symbol][0]
+            for symbol in self._previous_mapped_contract_symbols
+        ]
+        marked_delisted_securities = [security for security in delisted_securities if security.is_delisted and not security.is_tradable]
+        if len(marked_delisted_securities) != len(delisted_securities):
+            raise ValueError(f"Not all delisted contracts are properly marked as delisted and non-tradable: "
+                             f"only {len(marked_delisted_securities)} are marked, was expecting {len(delisted_securities)}")

Algorithm.Python/CustomDataPropertiesRegressionAlgorithm.py

@@ -24,8 +24,8 @@ from AlgorithmImports import *
 class CustomDataPropertiesRegressionAlgorithm(QCAlgorithm):
 
     def initialize(self):
-        self.set_start_date(2011,9,13)   # Set Start Date
-        self.set_end_date(2015,12,1)     # Set End Date
+        self.set_start_date(2020, 1, 5)   # Set Start Date
+        self.set_end_date(2020, 1, 10)     # Set End Date
         self.set_cash(100000)           # Set Strategy Cash
 
         # Define our custom data properties and exchange hours
@@ -70,7 +70,9 @@ class Bitcoin(PythonData):
 
         #return "http://my-ftp-server.com/futures-data-" + date.to_string("Ymd") + ".zip"
         # OR simply return a fixed small data file. Large files will slow down your backtest
-        return SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc&api_key=WyAazVXnq7ATy_fefTqm", SubscriptionTransportMedium.REMOTE_FILE)
+        subscription = SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/nasdaq/api/v3/datatables/QDL/BITFINEX.csv?code=BTCUSD&api_key=WyAazVXnq7ATy_fefTqm")
+        subscription.Sort = True
+        return subscription
 
 
     def reader(self, config, line, date, is_live_mode):
@@ -103,22 +105,22 @@ class Bitcoin(PythonData):
                 return None
 
         # 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
-        if not (line.strip() and line[0].isdigit()): return None
+        #code    date        high     low      mid      last     bid      ask      volume
+        #BTCUSD  2024-10-08  63248.0  61940.0  62246.5  62245.0  62246.0  62247.0       5.929230648356
+        if not (line.strip() and line[7].isdigit()): return None
 
         try:
             data = line.split(',')
-            coin.time = datetime.strptime(data[0], "%Y-%m-%d")
+            coin.time = datetime.strptime(data[1], "%Y-%m-%d")
             coin.end_time = coin.time + timedelta(days=1)
-            coin.value = float(data[4])
-            coin["Open"] = float(data[1])
+            coin.value = float(data[5])
             coin["High"] = float(data[2])
             coin["Low"] = float(data[3])
-            coin["Close"] = float(data[4])
-            coin["VolumeBTC"] = float(data[5])
-            coin["VolumeUSD"] = float(data[6])
-            coin["WeightedPrice"] = float(data[7])
+            coin["Mid"] = float(data[4])
+            coin["Close"] = float(data[5])
+            coin["Bid"] = float(data[6])
+            coin["Ask"] = float(data[7])
+            coin["VolumeBTC"] = float(data[8])
             return coin
 
         except ValueError:

Algorithm.Python/CustomDataRegressionAlgorithm.py

@@ -25,8 +25,8 @@ class CustomDataRegressionAlgorithm(QCAlgorithm):
 
     def initialize(self):
 
-        self.set_start_date(2011,9,14)   # Set Start Date
-        self.set_end_date(2015,12,1)     # Set End Date
+        self.set_start_date(2020,1,5)   # Set Start Date
+        self.set_end_date(2020,1,10)     # Set End Date
         self.set_cash(100000)           # Set Strategy Cash
 
         resolution = Resolution.SECOND if self.live_mode else Resolution.DAILY
@@ -54,7 +54,7 @@ class CustomDataRegressionAlgorithm(QCAlgorithm):
             raise ValueError("Security was not warmed up!")
 
 class Bitcoin(PythonData):
-    '''Custom Data Type: Bitcoin data from Quandl - http://www.quandl.com/help/api-for-bitcoin-data'''
+    '''Custom Data Type: Bitcoin data from Quandl - https://data.nasdaq.com/databases/BCHAIN'''
 
     def get_source(self, config, date, is_live_mode):
         if is_live_mode:
@@ -62,7 +62,9 @@ class Bitcoin(PythonData):
 
         #return "http://my-ftp-server.com/futures-data-" + date.to_string("Ymd") + ".zip"
         # OR simply return a fixed small data file. Large files will slow down your backtest
-        return SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc&api_key=WyAazVXnq7ATy_fefTqm", SubscriptionTransportMedium.REMOTE_FILE)
+        subscription = SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/nasdaq/api/v3/datatables/QDL/BITFINEX.csv?code=BTCUSD&api_key=WyAazVXnq7ATy_fefTqm")
+        subscription.Sort = True
+        return subscription
 
 
     def reader(self, config, line, date, is_live_mode):
@@ -95,22 +97,22 @@ class Bitcoin(PythonData):
                 return None
 
         # 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
-        if not (line.strip() and line[0].isdigit()): return None
+        # code    date        high     low      mid      last     bid      ask      volume
+        # BTCUSD  2024-10-08  63248.0  61940.0  62246.5  62245.0  62246.0  62247.0  477.91102114
+        if not (line.strip() and line[7].isdigit()): return None
 
         try:
             data = line.split(',')
-            coin.time = datetime.strptime(data[0], "%Y-%m-%d")
+            coin.time = datetime.strptime(data[1], "%Y-%m-%d")
             coin.end_time = coin.time + timedelta(days=1)
-            coin.value = float(data[4])
-            coin["Open"] = float(data[1])
+            coin.value = float(data[5])
             coin["High"] = float(data[2])
             coin["Low"] = float(data[3])
-            coin["Close"] = float(data[4])
-            coin["VolumeBTC"] = float(data[5])
-            coin["VolumeUSD"] = float(data[6])
-            coin["WeightedPrice"] = float(data[7])
+            coin["Mid"] = float(data[4])
+            coin["Close"] = float(data[5])
+            coin["Bid"] = float(data[6])
+            coin["Ask"] = float(data[7])
+            coin["VolumeBTC"] = float(data[8])
             return coin
 
         except ValueError:

Algorithm.Python/DescendingCustomDataObjectStoreRegressionAlgorithm.py

@@ -0,0 +1,109 @@
+# 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
+
+from AlgorithmImports import *
+
+
+### <summary>
+### The regression algorithm showcases the utilization of a custom data source with the Sort flag set to true.
+### This means that the source initially provides data in descending order, which is then organized into ascending order and returned in the 'on_data' function.
+### </summary>
+class DescendingCustomDataObjectStoreRegressionAlgorithm(QCAlgorithm):
+    descending_custom_data = [
+        "2024-10-03 19:00:00,173.5,176.0,172.0,175.2,120195681,4882.29",
+        "2024-10-02 18:00:00,174.0,177.0,173.0,175.8,116275729,4641.97",
+        "2024-10-01 17:00:00,175.0,178.0,172.5,174.5,127707078,6591.27",
+        "2024-09-30 11:00:00,174.8,176.5,172.8,175.0,127707078,6591.27",
+        "2024-09-27 10:00:00,172.5,175.0,171.5,173.5,120195681,4882.29",
+        "2024-09-26 09:00:00,171.0,172.5,170.0,171.8,117516350,4820.53",
+        "2024-09-25 08:00:00,169.5,172.0,169.0,171.0,110427867,4661.55",
+        "2024-09-24 07:00:00,170.0,171.0,168.0,169.5,127624733,4823.52",
+        "2024-09-23 06:00:00,172.0,173.5,169.5,171.5,123586417,4303.93",
+        "2024-09-20 05:00:00,168.0,171.0,167.5,170.5,151929179,5429.87",
+        "2024-09-19 04:00:00,170.5,171.5,166.0,167.0,160523863,5219.24",
+        "2024-09-18 03:00:00,173.0,174.0,169.0,172.0,145721790,5163.09",
+        "2024-09-17 02:00:00,171.0,173.5,170.0,172.5,144794030,5405.72",
+        "2024-09-16 01:00:00,168.0,171.0,167.0,170.0,214402430,8753.33",
+        "2024-09-13 16:00:00,173.5,176.0,172.0,175.2,120195681,4882.29",
+        "2024-09-12 15:00:00,174.5,177.5,173.5,176.5,171728134,7774.83",
+        "2024-09-11 14:00:00,175.0,178.0,174.0,175.5,191516153,8349.59",
+        "2024-09-10 13:00:00,174.5,176.0,173.0,174.0,151162819,5915.8",
+        "2024-09-09 12:00:00,176.0,178.0,175.0,177.0,116275729,4641.97"
+    ]
+
+    def initialize(self):
+        self.set_start_date(2024, 9, 9)
+        self.set_end_date(2024, 10, 3)
+        self.set_cash(100000)
+
+        self.set_benchmark(lambda x: 0)
+
+        SortCustomData.custom_data_key = self.get_custom_data_key()
+
+        self.custom_symbol = self.add_data(SortCustomData, "SortCustomData", Resolution.DAILY).symbol
+
+        # Saving data here for demonstration and regression testing purposes.
+        # In real scenarios, data has to be saved to the object store before the algorithm starts.
+        self.object_store.save(self.get_custom_data_key(), "\n".join(self.descending_custom_data))
+
+        self.received_data = []
+
+    def on_data(self, slice: Slice):
+        if slice.contains_key(self.custom_symbol):
+            custom_data = slice.get(SortCustomData, self.custom_symbol)
+            if custom_data.open == 0 or custom_data.high == 0 or custom_data.low == 0 or custom_data.close == 0 or custom_data.price == 0:
+                raise Exception("One or more custom data fields (open, high, low, close, price) are zero.")
+
+            self.received_data.append(custom_data)
+
+    def on_end_of_algorithm(self):
+        if not self.received_data:
+            raise Exception("Custom data was not fetched")
+
+        # Make sure history requests work as expected
+        history = self.history(SortCustomData, self.custom_symbol, self.start_date, self.end_date, Resolution.DAILY)
+
+        if history.shape[0] != len(self.received_data):
+            raise Exception("History request returned more or less data than expected")
+
+        # Iterate through the history collection, checking if the time is in ascending order.
+        for i in range(len(history) - 1):
+            # [1] - time
+            if history.index[i][1] > history.index[i + 1][1]:
+                raise RegressionTestException(
+                    f"Order failure: {history.index[i][1]} > {history.index[i + 1][1]} at index {i}.")
+
+    def get_custom_data_key(self):
+        return "CustomData/SortCustomData"
+
+
+class SortCustomData(PythonData):
+    custom_data_key = ""
+
+    def get_source(self, config, date, is_live):
+        subscription = SubscriptionDataSource(self.custom_data_key, SubscriptionTransportMedium.OBJECT_STORE,
+                                              FileFormat.CSV)
+        # Indicate that the data from the subscription will be returned in descending order.
+        subscription.Sort = True
+        return subscription
+
+    def reader(self, config, line, date, is_live):
+        data = line.split(',')
+        obj_data = SortCustomData()
+        obj_data.symbol = config.symbol
+        obj_data.time = datetime.strptime(data[0], '%Y-%m-%d %H:%M:%S')
+        obj_data.value = float(data[4])
+        obj_data["Open"] = float(data[1])
+        obj_data["High"] = float(data[2])
+        obj_data["Low"] = float(data[3])
+        obj_data["Close"] = float(data[4])
+        return obj_data

Algorithm.Python/ETFConstituentUniverseFrameworkRegressionAlgorithm.py

@@ -125,12 +125,9 @@ class ETFConstituentUniverseFrameworkRegressionAlgorithm(QCAlgorithm):
         self.universe_settings.resolution = Resolution.HOUR
         universe = self.add_universe(self.universe.etf(spy, self.universe_settings, self.filter_etf_constituents))
 
-        historical_data = self.history(universe, 1)
-        if len(historical_data) != 1:
-            raise ValueError(f"Unexpected history count {len(historical_data)}! Expected 1")
-        for universe_data_collection in historical_data:
-            if len(universe_data_collection) < 200:
-               raise ValueError(f"Unexpected universe DataCollection count {len(universe_data_collection)}! Expected > 200")
+        historical_data = self.history(universe, 1, flatten=True)
+        if len(historical_data) < 200:
+               raise ValueError(f"Unexpected universe DataCollection count {len(historical_data)}! Expected > 200")
 
     ### <summary>
     ### Filters ETF constituents

Algorithm.Python/FundamentalRegressionAlgorithm.py

@@ -49,7 +49,7 @@ class FundamentalRegressionAlgorithm(QCAlgorithm):
             raise ValueError(f"Unexpected Fundamental count {len(fundamentals)}! Expected 2")
 
         # Request historical fundamental data for symbols
-        history = self.history(Fundamental, TimeSpan(2, 0, 0, 0))
+        history = self.history(Fundamental, timedelta(days=2))
         if len(history) != 4:
             raise ValueError(f"Unexpected Fundamental history count {len(history)}! Expected 4")
 
@@ -69,26 +69,28 @@ class FundamentalRegressionAlgorithm(QCAlgorithm):
 
     def assert_fundamental_universe_data(self):
         # Case A
-        universe_data_per_time = self.history(self._universe.data_type, [self._universe.symbol], TimeSpan(2, 0, 0, 0))
-        if len(universe_data_per_time) != 2:
-            raise ValueError(f"Unexpected Fundamentals history count {len(universe_data_per_time)}! Expected 2")
-
-        for universe_data_collection in universe_data_per_time:
-            self.assert_fundamental_enumerator(universe_data_collection, "A")
+        universe_data = self.history(self._universe.data_type, [self._universe.symbol], timedelta(days=2), flatten=True)
+        self.assert_fundamental_history(universe_data, "A")
 
         # Case B (sugar on A)
-        universe_data_per_time = self.history(self._universe, TimeSpan(2, 0, 0, 0))
-        if len(universe_data_per_time) != 2:
-            raise ValueError(f"Unexpected Fundamentals history count {len(universe_data_per_time)}! Expected 2")
-
-        for universe_data_collection in universe_data_per_time:
-            self.assert_fundamental_enumerator(universe_data_collection, "B")
+        universe_data_per_time = self.history(self._universe, timedelta(days=2), flatten=True)
+        self.assert_fundamental_history(universe_data_per_time, "B")
 
         # Case C: Passing through the unvierse type and symbol
         enumerable_of_data_dictionary = self.history[self._universe.data_type]([self._universe.symbol], 100)
         for selection_collection_for_a_day in enumerable_of_data_dictionary:
             self.assert_fundamental_enumerator(selection_collection_for_a_day[self._universe.symbol], "C")
 
+    def assert_fundamental_history(self, df, case_name):
+        dates = df.index.get_level_values('time').unique()
+        if dates.shape[0] != 2:
+            raise ValueError(f"Unexpected Fundamental universe dates count {dates.shape[0]}! Expected 2")
+
+        for date in dates:
+            sub_df = df.loc[date]
+            if sub_df.shape[0] < 7000:
+                raise ValueError(f"Unexpected historical Fundamentals data count {sub_df.shape[0]} case {case_name}! Expected > 7000")
+
     def assert_fundamental_enumerator(self, enumerable, case_name):
         data_point_count = 0
         for fundamental in enumerable:

Algorithm.Python/ImmediateExecutionModelWorksWithBinanceFeeModel.py

@@ -0,0 +1,51 @@
+# 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.
+
+# region imports
+from AlgorithmImports import *
+from Execution.ImmediateExecutionModel import ImmediateExecutionModel
+from QuantConnect.Orders import OrderEvent
+# endregion
+
+### <summary>
+### Regression algorithm to test ImmediateExecutionModel places orders with the
+### correct quantity (taking into account the fee's) so that the fill quantity
+### is the expected one.
+### </summary>
+class ImmediateExecutionModelWorksWithBinanceFeeModel(QCAlgorithm):
+
+    def Initialize(self):
+        # *** initial configurations and backtest ***
+        self.SetStartDate(2022, 12, 13)  # Set Start Date
+        self.SetEndDate(2022, 12, 14)  # Set End Date
+        self.SetAccountCurrency("BUSD") # Set Account Currency
+        self.SetCash("BUSD", 100000, 1)  # Set Strategy Cash
+
+        self.universe_settings.resolution = Resolution.MINUTE
+
+        symbols = [ Symbol.create("BTCBUSD", SecurityType.CRYPTO, Market.BINANCE) ]
+
+        # set algorithm framework models
+        self.set_universe_selection(ManualUniverseSelectionModel(symbols))
+        self.set_alpha(ConstantAlphaModel(InsightType.PRICE, InsightDirection.UP, timedelta(minutes = 20), 0.025, None))
+
+        self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel(Resolution.MINUTE))
+        self.set_execution(ImmediateExecutionModel())
+        
+        
+        self.SetBrokerageModel(BrokerageName.Binance, AccountType.Margin)
+    
+    def on_order_event(self, order_event: OrderEvent) -> None:
+        if order_event.status == OrderStatus.FILLED:
+            if abs(order_event.quantity - 5.8) > 0.01:
+                raise Exception(f"The expected quantity was 5.8 but the quantity from the order was {order_event.quantity}")

Algorithm.Python/IndexOptionChainApisConsistencyRegressionAlgorithm.py

@@ -0,0 +1,29 @@
+# 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.
+
+from datetime import datetime
+from AlgorithmImports import *
+
+from OptionChainApisConsistencyRegressionAlgorithm import OptionChainApisConsistencyRegressionAlgorithm
+
+### <summary>
+### Regression algorithm asserting that the option chain APIs return consistent values for index options.
+### See QCAlgorithm.OptionChain(Symbol) and QCAlgorithm.OptionChainProvider
+### </summary>
+class IndexOptionChainApisConsistencyRegressionAlgorithm(OptionChainApisConsistencyRegressionAlgorithm):
+
+    def get_test_date(self) -> datetime:
+        return datetime(2021, 1, 4)
+
+    def get_option(self) -> Option:
+        return self.add_index_option("SPX")

Algorithm.Python/OptionChainApisConsistencyRegressionAlgorithm.py

@@ -0,0 +1,57 @@
+# 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.
+
+from datetime import datetime
+from AlgorithmImports import *
+
+### <summary>
+### Regression algorithm asserting that the option chain APIs return consistent values.
+### See QCAlgorithm.OptionChain(Symbol) and QCAlgorithm.OptionChainProvider
+### </summary>
+class OptionChainApisConsistencyRegressionAlgorithm(QCAlgorithm):
+
+    def initialize(self) -> None:
+        test_date = self.get_test_date()
+
+        self.set_start_date(test_date)
+        self.set_end_date(test_date)
+
+        option = self.get_option()
+
+        option_chain_from_algorithm_api = [x.symbol for x in self.option_chain(option.symbol).contracts.values()]
+
+        exchange_time = Extensions.convert_from_utc(self.utc_time, option.exchange.time_zone)
+        option_chain_from_provider_api = list(self.option_chain_provider.get_option_contract_list(option.symbol, exchange_time))
+
+        if len(option_chain_from_algorithm_api) == 0:
+            raise AssertionError("No options in chain from algorithm API")
+
+        if len(option_chain_from_provider_api) == 0:
+            raise AssertionError("No options in chain from provider API")
+
+        if len(option_chain_from_algorithm_api) != len(option_chain_from_provider_api):
+            raise AssertionError(f"Expected {len(option_chain_from_provider_api)} options in chain from provider API, "
+                                 f"but got {len(option_chain_from_algorithm_api)}");
+
+        for i in range(len(option_chain_from_algorithm_api)):
+            symbol1 = option_chain_from_algorithm_api[i]
+            symbol2 = option_chain_from_provider_api[i]
+
+            if symbol1 != symbol2:
+                raise AssertionError(f"Expected {symbol2} in chain from provider API, but got {symbol1}")
+
+    def get_test_date(self) -> datetime:
+        return datetime(2015, 12, 25)
+
+    def get_option(self) -> Option:
+        return self.add_option("GOOG")

Algorithm.Python/OptionChainFullDataRegressionAlgorithm.py

@@ -12,6 +12,7 @@
 # limitations under the License.
 
 from AlgorithmImports import *
+from datetime import timedelta
 
 ### <summary>
 ### Regression algorithm illustrating the usage of the <see cref="QCAlgorithm.OptionChain(Symbol)"/> method
@@ -27,14 +28,16 @@ class OptionChainFullDataRegressionAlgorithm(QCAlgorithm):
 
         goog = self.add_equity("GOOG").symbol
 
+        option_chain = self.option_chain(goog, flatten=True)
+
+        # Demonstration using data frame:
+        df = option_chain.data_frame
         # Get contracts expiring within 10 days, with an implied volatility greater than 0.5 and a delta less than 0.5
-        contracts = [
-            contract_data
-            for contract_data in self.option_chain(goog)
-            if contract_data.id.date - self.time <= timedelta(days=10) and contract_data.implied_volatility > 0.5 and contract_data.greeks.delta < 0.5
-        ]
-        # Get the contract with the latest expiration date
-        self._option_contract = sorted(contracts, key=lambda x: x.id.date, reverse=True)[0]
+        contracts = df.loc[(df.expiry <= self.time + timedelta(days=10)) & (df.impliedvolatility > 0.5) & (df.delta < 0.5)]
+
+        # Get the contract with the latest expiration date.
+        # Note: the result of df.loc[] is a series, and its name is a tuple with a single element (contract symbol)
+        self._option_contract = contracts.loc[contracts.expiry.idxmax()].name
 
         self.add_option_contract(self._option_contract)
 

Algorithm.Python/OptionChainedUniverseSelectionModelRegressionAlgorithm.py

@@ -23,7 +23,7 @@ class OptionChainedUniverseSelectionModelRegressionAlgorithm(QCAlgorithm):
         self.set_start_date(2014, 6, 6)
         self.set_end_date(2014, 6, 6)
         self.set_cash(100000)
-        
+
         universe = self.add_universe("my-minute-universe-name", lambda time: [ "AAPL", "TWX" ])
         self.add_universe_selection(
             OptionChainedUniverseSelectionModel(
@@ -34,9 +34,9 @@ class OptionChainedUniverseSelectionModelRegressionAlgorithm(QCAlgorithm):
                                      .expiration(0, 180))
             )
         )
-        
+
     def on_data(self, slice):
-        if self.portfolio.invested or not (self.is_market_open("AAPL") and self.is_market_open("AAPL")): return
+        if self.portfolio.invested or not (self.is_market_open("AAPL") and self.is_market_open("TWX")): return
         values = list(map(lambda x: x.value, filter(lambda x: x.key == "?AAPL" or x.key == "?TWX",  slice.option_chains)))
         for chain in values:
             # we sort the contracts to find at the money (ATM) contract with farthest expiration