chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
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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.Alphas;
+using QuantConnect.Algorithm.Framework.Execution;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Algorithm.Framework.Risk;
+using QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Show cases how to use the <see cref="CompositeAlphaModel"/> to define
+    /// </summary>
+    public class CompositeAlphaModelFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 07);
+            SetEndDate(2013, 10, 11);
+
+            // even though we're using a framework algorithm, we can still add our securities
+            // using the AddEquity/Forex/Crypto/ect methods and then pass them into a manual
+            // universe selection model using Securities.Keys
+            AddEquity("SPY");
+            AddEquity("IBM");
+            AddEquity("BAC");
+            AddEquity("AIG");
+
+            // define a manual universe of all the securities we manually registered
+            SetUniverseSelection(new ManualUniverseSelectionModel());
+
+            // define alpha model as a composite of the rsi and ema cross models
+            SetAlpha(new CompositeAlphaModel(
+                new RsiAlphaModel(),
+                new EmaCrossAlphaModel()
+            ));
+
+            // default models for the rest
+            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
+            SetExecution(new ImmediateExecutionModel());
+            SetRiskManagement(new NullRiskManagementModel());
+        }
+
+        /// <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 => 15643;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 208;
+
+        /// <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", "16"},
+            {"Average Win", "0.01%"},
+            {"Average Loss", "-0.18%"},
+            {"Compounding Annual Return", "-35.728%"},
+            {"Drawdown", "1.700%"},
+            {"Expectancy", "-0.690"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99436.42"},
+            {"Net Profit", "-0.564%"},
+            {"Sharpe Ratio", "-2.767"},
+            {"Sortino Ratio", "-3.388"},
+            {"Probabilistic Sharpe Ratio", "32.075%"},
+            {"Loss Rate", "70%"},
+            {"Win Rate", "30%"},
+            {"Profit-Loss Ratio", "0.03"},
+            {"Alpha", "-0.771"},
+            {"Beta", "0.296"},
+            {"Annual Standard Deviation", "0.068"},
+            {"Annual Variance", "0.005"},
+            {"Information Ratio", "-13.734"},
+            {"Tracking Error", "0.157"},
+            {"Treynor Ratio", "-0.632"},
+            {"Total Fees", "$39.85"},
+            {"Estimated Strategy Capacity", "$4700000.00"},
+            {"Lowest Capacity Asset", "AIG R735QTJ8XC9X"},
+            {"Portfolio Turnover", "60.79%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "7a65de0f613e5c6161e410d499f45445"}
+        };
+    }
+}