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.Indicators;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm to test the behaviour of ARMA versus AR models at the same order of differencing.
+    /// In particular, an ARIMA(1,1,1) and ARIMA(1,1,0) are instantiated while orders are placed if their difference
+    /// is sufficiently large (which would be due to the inclusion of the MA(1) term).
+    /// </summary>
+    public class AutoRegressiveIntegratedMovingAverageRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private AutoRegressiveIntegratedMovingAverage _arima;
+        private AutoRegressiveIntegratedMovingAverage _ar;
+        private decimal _last;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 1, 07);
+            SetEndDate(2013, 12, 11);
+
+            Settings.AutomaticIndicatorWarmUp = true;
+            AddEquity("SPY", Resolution.Daily);
+            _arima = ARIMA("SPY", 1, 1, 1, 50);
+            _ar = ARIMA("SPY", 1, 1, 0, 50);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (_arima.IsReady)
+            {
+                if (Math.Abs(_ar.Current.Value - _arima.Current.Value) > 1) // Difference due to MA(1) being included.
+                {
+                    if (_arima.Current.Value > _last)
+                    {
+                        MarketOrder("SPY", 1);
+                    }
+                    else
+                    {
+                        MarketOrder("SPY", -1);
+                    }
+                }
+
+                _last = _arima.Current.Value;
+            }
+        }
+
+        /// <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 => 1893;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 100;
+
+        /// <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", "53"},
+            {"Average Win", "0.00%"},
+            {"Average Loss", "0.00%"},
+            {"Compounding Annual Return", "0.076%"},
+            {"Drawdown", "0.100%"},
+            {"Expectancy", "2.933"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100070.90"},
+            {"Net Profit", "0.071%"},
+            {"Sharpe Ratio", "-9.164"},
+            {"Sortino Ratio", "-9.852"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "27%"},
+            {"Win Rate", "73%"},
+            {"Profit-Loss Ratio", "4.41"},
+            {"Alpha", "-0.008"},
+            {"Beta", "0.008"},
+            {"Annual Standard Deviation", "0.001"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.961"},
+            {"Tracking Error", "0.092"},
+            {"Treynor Ratio", "-0.911"},
+            {"Total Fees", "$53.00"},
+            {"Estimated Strategy Capacity", "$16000000000.00"},
+            {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
+            {"Portfolio Turnover", "0.02%"},
+            {"Drawdown Recovery", "50"},
+            {"OrderListHash", "685c37df6e4c49b75792c133be189094"}
+        };
+    }
+}