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
@@ -0,0 +1,131 @@
+/*
+ * 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.Algorithm.Framework.Alphas;
+using QuantConnect.Algorithm.Framework.Execution;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Test algorithm using <see cref="QCAlgorithm.AddUniverseSelection(IUniverseSelectionModel)"/>
+    /// </summary>
+    public class AddUniverseSelectionModelAlgorithm : 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()
+        {
+            // Set requested data resolution
+            UniverseSettings.Resolution = Resolution.Daily;
+
+            SetStartDate(2013, 10, 08);  //Set Start Date
+            SetEndDate(2013, 10, 11);    //Set End Date
+            SetCash(100000);             //Set Strategy Cash
+
+            // set algorithm framework models
+            SetAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromMinutes(20), 0.025, null));
+            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
+            SetExecution(new ImmediateExecutionModel());
+
+            SetUniverseSelection(new ManualUniverseSelectionModel(QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA)));
+            AddUniverseSelection(new ManualUniverseSelectionModel(QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA)));
+            AddUniverseSelection(new ManualUniverseSelectionModel(
+                QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA), // duplicate will be ignored
+                QuantConnect.Symbol.Create("FB", SecurityType.Equity, Market.USA)));
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (UniverseManager.Count != 3)
+            {
+                throw new RegressionTestException("Unexpected universe count");
+            }
+            if (UniverseManager.ActiveSecurities.Count != 3
+                || UniverseManager.ActiveSecurities.Keys.All(symbol => symbol.Value != "SPY")
+                || UniverseManager.ActiveSecurities.Keys.All(symbol => symbol.Value != "AAPL")
+                || UniverseManager.ActiveSecurities.Keys.All(symbol => symbol.Value != "FB"))
+            {
+                throw new RegressionTestException("Unexpected active securities");
+            }
+        }
+
+        /// <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 => 50;
+
+        /// <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", "6"},
+            {"Average Win", "0.01%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "1296.838%"},
+            {"Drawdown", "0.400%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "102684.23"},
+            {"Net Profit", "2.684%"},
+            {"Sharpe Ratio", "34.319"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-5.738"},
+            {"Beta", "1.381"},
+            {"Annual Standard Deviation", "0.246"},
+            {"Annual Variance", "0.06"},
+            {"Information Ratio", "-26.937"},
+            {"Tracking Error", "0.068"},
+            {"Treynor Ratio", "6.106"},
+            {"Total Fees", "$18.61"},
+            {"Estimated Strategy Capacity", "$980000000.00"},
+            {"Lowest Capacity Asset", "FB V6OIPNZEM8V9"},
+            {"Portfolio Turnover", "25.56%"},
+            {"Drawdown Recovery", "1"},
+            {"OrderListHash", "5ee20c8556d706ab0a63ae41b6579c62"}
+        };
+    }
+}