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.Linq;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using System.Collections.Generic;
+using QuantConnect.Data.Fundamental;
+using QuantConnect.Data.UniverseSelection;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting the behavior of Universe.Selected collection
+    /// </summary>
+    public class UniverseSelectedRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private int _selectionCount;
+        private Universe _universe;
+
+        private readonly Queue<List<Symbol>> _expectedSymbols = new(new[]
+        {
+            new List<Symbol> { GetSymbol("SPY") },
+            new List<Symbol> { GetSymbol("AAPL"), GetSymbol("IWM") },
+            new List<Symbol> { GetSymbol("FB"), GetSymbol("AAPL"), GetSymbol("QQQ") },
+        });
+
+        public override void Initialize()
+        {
+            UniverseSettings.Resolution = Resolution.Daily;
+
+            SetStartDate(2014, 03, 25);
+            SetEndDate(2014, 03, 27);
+
+            _universe = AddUniverse(SelectionFunction);
+        }
+
+        public IEnumerable<Symbol> SelectionFunction(IEnumerable<Fundamental> fundamentals)
+        {
+            var sortedByDollarVolume = fundamentals.OrderByDescending(x => x.DollarVolume);
+
+            var top = sortedByDollarVolume.Skip(_selectionCount++).Take(_selectionCount).ToList();
+
+            return top.Select(x => x.Symbol);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (_universe.Selected.Contains(QuantConnect.Symbol.Create("TSLA", SecurityType.Equity, Market.USA)))
+            {
+                throw new RegressionTestException($"TSLA shouldn't of been selected");
+            }
+
+            if (Time.Date < new DateTime(2014, 03, 28))
+            {
+                var expectedSymbols = _expectedSymbols.Dequeue();
+
+                if (!Enumerable.SequenceEqual(expectedSymbols, _universe.Selected))
+                {
+                    throw new RegressionTestException($"Unexpected selected symbols");
+                }
+            }
+
+            Buy(_universe.Selected.First(), 1);
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_selectionCount != 3)
+            {
+                throw new RegressionTestException($"Unexpected selection count {_selectionCount}");
+            }
+            if (_universe.Selected.Count != 3 || _universe.Selected.Count == _universe.Members.Count)
+            {
+                throw new RegressionTestException($"Unexpected universe selected count {_universe.Selected.Count}");
+            }
+        }
+
+        private static Symbol GetSymbol(string ticker) => QuantConnect.Symbol.Create(ticker, SecurityType.Equity, Market.USA);
+
+        /// <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 => 28319;
+
+        /// <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", "3"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "-0.508%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99995.81"},
+            {"Net Profit", "-0.004%"},
+            {"Sharpe Ratio", "-83.691"},
+            {"Sortino Ratio", "-83.691"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.011"},
+            {"Beta", "0.003"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "12.051"},
+            {"Tracking Error", "0.057"},
+            {"Treynor Ratio", "-4.776"},
+            {"Total Fees", "$2.00"},
+            {"Estimated Strategy Capacity", "$390000000000.00"},
+            {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "0.06%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "15ad776b527fdd43aae394badef6d206"}
+        };
+    }
+}