chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
5008 changed files with 910633 additions and 0 deletions
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+/*
+ * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+ * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+*/
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression test algorithm simply fetch and compare data of minute resolution around daylight saving period
+    /// reproduces issue reported in GB issue GH issue https://github.com/QuantConnect/Lean/issues/4925
+    /// related issues https://github.com/QuantConnect/Lean/issues/3707; https://github.com/QuantConnect/Lean/issues/4630
+    /// </summary>
+    public class FillForwardEnumeratorOutOfOrderBarRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private decimal _exptectedClose = 84.09m;
+        private DateTime _exptectedTime = new DateTime(2008, 3, 10, 9, 30, 0);
+        private Symbol _shy;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2008, 3, 7);
+            SetEndDate(2008, 3, 10);
+            _shy = AddEquity("SHY", Resolution.Minute).Symbol;
+            // just to make debugging easier, less subscriptions
+            SetBenchmark(time => 1);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            var trackingBar = slice.Bars.Values.FirstOrDefault(s => s.Time.Equals(_exptectedTime));
+
+            if (trackingBar != null)
+            {
+                if (!Portfolio.Invested)
+                {
+                    SetHoldings(_shy, 1);
+                }
+
+                if (trackingBar.Close != _exptectedClose)
+                {
+                    throw new RegressionTestException(
+                        $"Bar at {_exptectedTime.ToStringInvariant()} closed at price {trackingBar.Close.ToStringInvariant()}; expected {_exptectedClose.ToStringInvariant()}");
+                }
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 1561;
+
+        /// <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", "16.086%"},
+            {"Drawdown", "0.100%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100148.25"},
+            {"Net Profit", "0.148%"},
+            {"Sharpe Ratio", "7.182"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0.014"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "9.758"},
+            {"Tracking Error", "0.014"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$5.93"},
+            {"Estimated Strategy Capacity", "$150000.00"},
+            {"Lowest Capacity Asset", "SHY 2T"},
+            {"Portfolio Turnover", "24.91%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "9d00701591b363edda102536ec5e75e0"}
+        };
+    }
+}