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.Interfaces;
+using System.Collections.Generic;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Data;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Assert that CoarseFundamentals universe selection happens right away after algorithm starts
+    /// </summary>
+    public class CoarseFundamentalImmediateSelectionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private const int NumberOfSymbols = 3;
+
+        private bool _initialSelectionDone;
+
+        public override void Initialize()
+        {
+            UniverseSettings.Resolution = Resolution.Daily;
+
+            SetStartDate(2014, 03, 25);
+            SetEndDate(2014, 03, 30);
+            SetCash(100000);
+
+            AddUniverse(CoarseSelectionFunction);
+        }
+
+        // sort the data by daily dollar volume and take the top 'NumberOfSymbols'
+        public IEnumerable<Symbol> CoarseSelectionFunction(IEnumerable<CoarseFundamental> coarse)
+        {
+            if (!_initialSelectionDone)
+            {
+                if (Time != StartDate)
+                {
+                    throw new RegressionTestException($"CoarseSelectionFunction called at unexpected time. " +
+                        $"Expected it to be called on {StartDate} but was called on {Time}");
+                }
+            }
+
+            // sort descending by daily dollar volume
+            var sortedByDollarVolume = coarse.OrderByDescending(x => x.DollarVolume);
+
+            // take the top entries from our sorted collection
+            var top = sortedByDollarVolume.Take(NumberOfSymbols);
+
+            // we need to return only the symbol objects
+            return top.Select(x => x.Symbol);
+        }
+
+        public void OnData(Slice data)
+        {
+            Log($"OnData({UtcTime:o}): Keys: {string.Join(", ", data.Keys.OrderBy(x => x))}");
+        }
+
+        public override void OnSecuritiesChanged(SecurityChanges changes)
+        {
+            Log($"OnSecuritiesChanged({UtcTime:o}):: {changes}");
+
+            // This should also happen right away
+            if (!_initialSelectionDone)
+            {
+                _initialSelectionDone = true;
+
+                if (Time != StartDate)
+                {
+                    throw new RegressionTestException($"OnSecuritiesChanged called at unexpected time. " +
+                        $"Expected it to be called on {StartDate} but was called on {Time}");
+                }
+
+                if (changes.AddedSecurities.Count != NumberOfSymbols)
+                {
+                    throw new RegressionTestException($"Unexpected number of added securities. " +
+                        $"Expected {NumberOfSymbols} but was {changes.AddedSecurities.Count}");
+                }
+
+                if (changes.RemovedSecurities.Count != 0)
+                {
+                    throw new RegressionTestException($"Unexpected number of removed securities. " +
+                        $"Expected 0 but was {changes.RemovedSecurities.Count}");
+                }
+            }
+        }
+
+        /// <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 => 35402;
+
+        /// <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", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "3.134"},
+            {"Tracking Error", "0.097"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}