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
@@ -0,0 +1,137 @@
+/*
+ * 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 QuantConnect.Data.Consolidators;
+using QuantConnect.Data.Market;
+using QuantConnect.Interfaces;
+using System;
+using System.Collections.Generic;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Example algorithm of how to use RangeConsolidator
+    /// </summary>
+    public class RangeConsolidatorAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private RangeBar _firstDataConsolidated;
+        protected virtual int Range => 100;
+        protected virtual Resolution Resolution => Resolution.Daily;
+
+        public override void Initialize()
+         {
+            SetStartAndEndDates();
+            AddEquity("SPY", Resolution);
+            var rangeConsolidator = CreateRangeConsolidator();
+            rangeConsolidator.DataConsolidated += OnDataConsolidated;
+            _firstDataConsolidated = null;
+
+            SubscriptionManager.AddConsolidator("SPY", rangeConsolidator);
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_firstDataConsolidated == null)
+            {
+                throw new RegressionTestException("The consolidator should have consolidated at least one RangeBar, but it did not consolidated any one");
+            }
+        }
+
+        protected virtual void OnDataConsolidated(Object sender, RangeBar rangeBar)
+        {
+            if (_firstDataConsolidated == null)
+            {
+                _firstDataConsolidated = rangeBar;
+            }
+            // Log($"{rangeBar.Open} {rangeBar.High} {rangeBar.Low} {rangeBar.Close}");
+
+            if (Math.Round(rangeBar.High - rangeBar.Low, 2) != (Range * 0.01m)) // The minimum price change for SPY is 0.01, therefore the range size of each bar equals Range * 0.01
+            {
+                throw new RegressionTestException($"The difference between the High and Low for all RangeBar's should be {Range * 0.01m}, but for this RangeBar was {Math.Round(rangeBar.High - rangeBar.Low), 2}");
+            }
+        }
+
+        protected virtual void SetStartAndEndDates()
+        {
+            SetStartDate(2013, 10, 07);
+            SetEndDate(2013, 10, 11);
+        }
+
+        protected virtual RangeConsolidator CreateRangeConsolidator()
+        {
+            return new RangeConsolidator(Range);
+        }
+
+        /// <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 virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public virtual long DataPoints => 48;
+
+        /// <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 virtual 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", "-8.91"},
+            {"Tracking Error", "0.223"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}