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 QuantConnect.Data;
+using QuantConnect.Data.Market;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression test for asserting that splits are applied to the <see cref="QCAlgorithm.TradeBuilder"/>
+    /// </summary>
+    public class SplitOnTradeBuilderRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _symbol;
+        private Split _split;
+        private OrderEvent _buyFillEvent;
+
+        public override void Initialize()
+        {
+            SetStartDate(2014, 6, 6);
+            SetEndDate(2014, 6, 11);
+            SetCash(100000);
+            SetBenchmark(x => 0);
+
+            _symbol = AddEquity("AAPL", Resolution.Hour, dataNormalizationMode: DataNormalizationMode.Raw).Symbol;
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (slice.Splits.TryGetValue(_symbol, out var split) && split.Type == SplitType.SplitOccurred)
+            {
+                _split = split;
+                Debug($"Split occurred on {split.Time}: {split}");
+            }
+
+            if (slice.ContainsKey(_symbol))
+            {
+                if (!Portfolio.Invested)
+                {
+                    if (_split == null)
+                    {
+                        Buy(_symbol, 100);
+                    }
+                }
+                else if (_split != null)
+                {
+                    Liquidate(_symbol);
+                }
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            if (orderEvent.Status == OrderStatus.Filled && orderEvent.Direction == OrderDirection.Buy)
+            {
+                _buyFillEvent = orderEvent;
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_split == null)
+            {
+                throw new RegressionTestException("No split occurred.");
+            }
+
+            if (_buyFillEvent == null)
+            {
+                throw new RegressionTestException("Buy order either never filled or was never placed.");
+            }
+
+            if (TradeBuilder.ClosedTrades.Count != 1)
+            {
+                throw new RegressionTestException($"Expected 1 closed trade, but found {TradeBuilder.ClosedTrades.Count}");
+            }
+
+            var trade = TradeBuilder.ClosedTrades[0];
+
+            var expectedEntryPrice = _buyFillEvent.FillPrice * _split.SplitFactor;
+            if (trade.EntryPrice != expectedEntryPrice)
+            {
+                throw new RegressionTestException($"Expected closed trade entry price of {expectedEntryPrice}, but found {trade.EntryPrice}");
+            }
+
+            var expectedTradeQuantity = (int)(_buyFillEvent.FillQuantity / _split.SplitFactor);
+            if (trade.Quantity != expectedTradeQuantity)
+            {
+                throw new RegressionTestException($"Expected closed trade quantity of {expectedTradeQuantity}, but found {trade.Quantity}");
+            }
+        }
+
+        /// <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 => 31;
+
+        /// <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", "2"},
+            {"Average Win", "0.09%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "6.103%"},
+            {"Drawdown", "0.400%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100092.01"},
+            {"Net Profit", "0.092%"},
+            {"Sharpe Ratio", "7.379"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "93.608%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "100%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0.023"},
+            {"Annual Variance", "0.001"},
+            {"Information Ratio", "7.707"},
+            {"Tracking Error", "0.023"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$4.50"},
+            {"Estimated Strategy Capacity", "$61000000.00"},
+            {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "21.61%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "be48105b9ce730de7bd4e4908f8c3ef5"}
+        };
+    }
+}