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;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting data returned by a history requests uses internal subscriptions correctly
+    /// </summary>
+    public class InternalSubscriptionHistoryRequestAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 07);
+            SetEndDate(2013, 10, 11);
+
+            AddEquity("AAPL", Resolution.Hour);
+            SetBenchmark("SPY");
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                SetHoldings("AAPL", 1);
+
+                var spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
+
+                var history = History(new[] { spy }, TimeSpan.FromDays(10));
+                if (!history.Any() || !history.All(slice => slice.Bars.All(pair => pair.Value.Period == TimeSpan.FromHours(1))))
+                {
+                    throw new RegressionTestException("Unexpected history result for internal subscription");
+                }
+
+                // we add SPY using Daily > default benchmark using hourly
+                AddEquity("SPY", Resolution.Daily);
+
+                history = History(new[] { spy }, TimeSpan.FromDays(10));
+                if (!history.Any() || !history.All(slice => slice.Bars.All(pair => pair.Value.Period == TimeSpan.FromHours(6.5))))
+                {
+                    throw new RegressionTestException("Unexpected history result for user subscription");
+                }
+            }
+        }
+
+        /// <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 => 108;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 48;
+
+        /// <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", "34.768%"},
+            {"Drawdown", "2.300%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100382.23"},
+            {"Net Profit", "0.382%"},
+            {"Sharpe Ratio", "5.446"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "59.920%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "-0.107"},
+            {"Beta", "0.548"},
+            {"Annual Standard Deviation", "0.179"},
+            {"Annual Variance", "0.032"},
+            {"Information Ratio", "-6.047"},
+            {"Tracking Error", "0.165"},
+            {"Treynor Ratio", "1.78"},
+            {"Total Fees", "$32.11"},
+            {"Estimated Strategy Capacity", "$66000000.00"},
+            {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
+            {"Portfolio Turnover", "20.08%"},
+            {"Drawdown Recovery", "2"},
+            {"OrderListHash", "fa51af977e55213dc007a38a3d681b62"}
+        };
+    }
+}