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 System.Linq;
+using QuantConnect.Algorithm.Framework.Alphas;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Data.Fundamental;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm used to test a fine and coarse selection methods
+    /// returning <see cref="Universe.Unchanged"/>
+    /// </summary>
+    public class UniverseUnchangedRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private const int NumberOfSymbolsFine = 2;
+
+        public override void Initialize()
+        {
+            UniverseSettings.Resolution = Resolution.Daily;
+
+            // Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
+            // Commented so regression algorithm is more sensitive
+            //Settings.MinimumOrderMarginPortfolioPercentage = 0.005m;
+
+            SetStartDate(2014, 03, 25);
+            SetEndDate(2014, 04, 07);
+
+            SetAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(1), 0.025, null));
+            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
+            AddUniverse(CoarseSelectionFunction, FineSelectionFunction);
+        }
+
+        public IEnumerable<Symbol> CoarseSelectionFunction(IEnumerable<CoarseFundamental> coarse)
+        {
+            // the first and second selection
+            if (Time.Date <= new DateTime(2014, 3, 26))
+            {
+                return new List<Symbol>
+                {
+                    QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA),
+                    QuantConnect.Symbol.Create("AIG", SecurityType.Equity, Market.USA),
+                    QuantConnect.Symbol.Create("IBM", SecurityType.Equity, Market.USA)
+                };
+            }
+            // will skip fine selection
+            return Universe.Unchanged;
+        }
+
+        public IEnumerable<Symbol> FineSelectionFunction(IEnumerable<FineFundamental> fine)
+        {
+            // just the first selection
+            if (Time.Date == new DateTime(2014, 3, 25))
+            {
+                var sortedByPeRatio = fine.OrderByDescending(x => x.ValuationRatios.PERatio);
+                var topFine = sortedByPeRatio.Take(NumberOfSymbolsFine);
+                return topFine.Select(x => x.Symbol);
+            }
+            // the second selection will return unchanged, in the following fine selection will be skipped
+            return Universe.Unchanged;
+        }
+
+        // assert security changes, throw if called more than once
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            if (changes.AddedSecurities.Count != 2
+                || Time != new DateTime(2014, 3, 25)
+                || changes.AddedSecurities.All(security => security.Symbol != QuantConnect.Symbol.Create("IBM", SecurityType.Equity, Market.USA))
+                || changes.AddedSecurities.All(security => security.Symbol != QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA)))
+            {
+                throw new RegressionTestException("Unexpected security changes");
+            }
+            Log($"OnSecuritiesChanged({Time:o}):: {changes}");
+        }
+
+        /// <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 => 63891;
+
+        /// <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", "8"},
+            {"Average Win", "0%"},
+            {"Average Loss", "-0.01%"},
+            {"Compounding Annual Return", "-45.405%"},
+            {"Drawdown", "2.300%"},
+            {"Expectancy", "-1"},
+            {"Start Equity", "100000"},
+            {"End Equity", "97705.34"},
+            {"Net Profit", "-2.295%"},
+            {"Sharpe Ratio", "-3.77"},
+            {"Sortino Ratio", "-4.881"},
+            {"Probabilistic Sharpe Ratio", "10.272%"},
+            {"Loss Rate", "100%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.233"},
+            {"Beta", "0.705"},
+            {"Annual Standard Deviation", "0.097"},
+            {"Annual Variance", "0.009"},
+            {"Information Ratio", "-2.374"},
+            {"Tracking Error", "0.075"},
+            {"Treynor Ratio", "-0.52"},
+            {"Total Fees", "$19.98"},
+            {"Estimated Strategy Capacity", "$100000000.00"},
+            {"Lowest Capacity Asset", "IBM R735QTJ8XC9X"},
+            {"Portfolio Turnover", "7.33%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "62cae7349a5294699d7d71ac4ec42b09"}
+        };
+    }
+}