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.Collections.Generic;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Validates that SetHoldings returns the correct number of order tickets on each execution.
+    /// </summary>
+    public class SetHoldingReturnsOrderTicketsRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _spy;
+        private Symbol _ibm;
+        public override void Initialize()
+        {
+            SetStartDate(2018, 1, 4);
+            SetEndDate(2018, 1, 10);
+            _spy = AddEquity("SPY", Resolution.Daily).Symbol;
+            _ibm = AddEquity("IBM", Resolution.Daily).Symbol;
+        }
+
+        public override void OnData(Slice slice)
+        {
+            var tickets = SetHoldings(new List<PortfolioTarget> { new(_spy, 0.8m), new(_ibm, 0.2m) });
+
+            if (!Portfolio.Invested)
+            {
+                // Ensure exactly 2 tickets are created when the portfolio is not yet invested
+                if (tickets.Count != 2)
+                {
+                    throw new RegressionTestException("Expected 2 tickets, got " + tickets.Count);
+                }
+            }
+            else if (tickets.Count != 0)
+            {
+                // Ensure no tickets are created when the portfolio is already invested
+                throw new RegressionTestException("Expected 0 tickets, got " + tickets.Count);
+            }
+        }
+
+        /// <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 { 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 => 53;
+
+        /// <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", "2"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "43.490%"},
+            {"Drawdown", "0.100%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100661.71"},
+            {"Net Profit", "0.662%"},
+            {"Sharpe Ratio", "12.329"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "95.183%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.108"},
+            {"Beta", "0.424"},
+            {"Annual Standard Deviation", "0.024"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "-5.097"},
+            {"Tracking Error", "0.03"},
+            {"Treynor Ratio", "0.707"},
+            {"Total Fees", "$2.56"},
+            {"Estimated Strategy Capacity", "$170000000.00"},
+            {"Lowest Capacity Asset", "IBM R735QTJ8XC9X"},
+            {"Portfolio Turnover", "14.24%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "587e1a69d3c83cbd9907f9f9586697e1"}
+        };
+    }
+}