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 QuantConnect.Algorithm;
+using QuantConnect.Algorithm.Framework.Alphas;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.DataLibrary.Tests
+{
+    /// <summary>
+    /// Example algorithm of using MeanReversionPortfolioConstructionModel
+    /// </summary>
+    public class MeanReversionPortfolioAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2020, 9, 1);
+            SetEndDate(2021, 2, 28);
+            SetCash(100000);
+            
+            SetSecurityInitializer(security => security.SetMarketPrice(GetLastKnownPrice(security)));
+
+            foreach (var ticker in new List<string>{"SPY", "AAPL"})
+            {
+                AddEquity(ticker, Resolution.Daily);
+            }
+            
+            AddAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(1)));
+            SetPortfolioConstruction(new MeanReversionPortfolioConstructionModel());
+        }
+
+        /// <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 => 1113;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 52;
+
+        /// <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", "60"},
+            {"Average Win", "1.88%"},
+            {"Average Loss", "-0.79%"},
+            {"Compounding Annual Return", "8.069%"},
+            {"Drawdown", "11.900%"},
+            {"Expectancy", "0.748"},
+            {"Start Equity", "100000"},
+            {"End Equity", "103872.25"},
+            {"Net Profit", "3.872%"},
+            {"Sharpe Ratio", "0.349"},
+            {"Sortino Ratio", "0.375"},
+            {"Probabilistic Sharpe Ratio", "28.925%"},
+            {"Loss Rate", "48%"},
+            {"Win Rate", "52%"},
+            {"Profit-Loss Ratio", "2.37"},
+            {"Alpha", "-0.085"},
+            {"Beta", "1.234"},
+            {"Annual Standard Deviation", "0.238"},
+            {"Annual Variance", "0.057"},
+            {"Information Ratio", "-0.331"},
+            {"Tracking Error", "0.16"},
+            {"Treynor Ratio", "0.067"},
+            {"Total Fees", "$114.36"},
+            {"Estimated Strategy Capacity", "$700000000.00"},
+            {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "18.24%"},
+            {"Drawdown Recovery", "63"},
+            {"OrderListHash", "22337335b8bbfb4fc1093879c3ddd4d8"}
+        };
+    }
+}