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 QuantConnect.Orders;
+using QuantConnect.Interfaces;
+using QuantConnect.Data.Market;
+using QuantConnect.Orders.Fills;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Example of custom fill model for security to only fill bars of data obtained after the order was placed. This is to encourage more
+    /// pessimistic fill models and eliminate the possibility to fill on old market data that may not be relevant.
+    /// </summary>
+    public class ForwardDataOnlyFillModelAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 01);
+            SetEndDate(2013, 10, 31);
+
+            var security = AddEquity("SPY", Resolution.Hour);
+            security.SetFillModel(new ForwardDataOnlyFillModel());
+
+            Schedule.On(DateRules.WeekStart(), TimeRules.AfterMarketOpen(security.Symbol), Trade);
+        }
+
+        public void Trade()
+        {
+            if (!Portfolio.Invested)
+            {
+                if(Time.TimeOfDay != new TimeSpan(9, 30, 0))
+                {
+                    throw new RegressionTestException($"Unexpected event time {Time}");
+                }
+
+                var ticket = Buy("SPY", 1);
+                if(ticket.Status != OrderStatus.Submitted)
+                {
+                    throw new RegressionTestException($"Unexpected order status {ticket.Status}");
+                }
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            Debug($"OnOrderEvent:: {orderEvent}");
+            if (orderEvent.Status == OrderStatus.Filled && (Time.Hour != 10 || Time.Minute != 0))
+            {
+                throw new RegressionTestException($"Unexpected fill time {Time}");
+            }
+        }
+
+        public class ForwardDataOnlyFillModel : EquityFillModel
+        {
+            public override Fill Fill(FillModelParameters parameters)
+            {
+                var orderLocalTime = parameters.Order.Time.ConvertFromUtc(parameters.Security.Exchange.TimeZone);
+                foreach (var dataType in new[] { typeof(QuoteBar), typeof(TradeBar), typeof(Tick)})
+                {
+                    if(parameters.Security.Cache.TryGetValue(dataType, out var data) && data.Count > 0 && orderLocalTime <= data[data.Count - 1].EndTime)
+                    {
+                        return base.Fill(parameters);
+                    }
+                }
+                return new Fill(new List<OrderEvent>());
+            }
+        }
+
+        /// <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 => 330;
+
+        /// <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", "1"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0.071%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100005.93"},
+            {"Net Profit", "0.006%"},
+            {"Sharpe Ratio", "-47.299"},
+            {"Sortino Ratio", "-100.304"},
+            {"Probabilistic Sharpe Ratio", "0.000%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.007"},
+            {"Beta", "0.001"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-3.425"},
+            {"Tracking Error", "0.107"},
+            {"Treynor Ratio", "-5.375"},
+            {"Total Fees", "$1.00"},
+            {"Estimated Strategy Capacity", "$62000000000.00"},
+            {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
+            {"Portfolio Turnover", "0.00%"},
+            {"Drawdown Recovery", "3"},
+            {"OrderListHash", "86f6dc102fded318c6264e36a56567b7"}
+        };
+    }
+}