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.Indicators;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Algorithm illustrating the usage of the <see cref="OptionIndicatorBase"/> indicators
+    /// </summary>
+    public class OptionIndicatorsRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private ImpliedVolatility _impliedVolatility;
+        private Delta _delta;
+        private Gamma _gamma;
+        private Vega _vega;
+        private Theta _theta;
+        private Rho _rho;
+
+        protected virtual string ExpectedGreeks { get; set; } = "Implied Volatility: 0.44529,Delta: -0.00921,Gamma: 0.00036,Vega: 0.03636,Theta: -0.03747,Rho: 0.00047";
+
+        public override void Initialize()
+        {
+            SetStartDate(2014, 6, 5);
+            SetEndDate(2014, 6, 7);
+            SetCash(100000);
+
+            AddEquity("AAPL", Resolution.Minute);
+            var option = QuantConnect.Symbol.CreateOption("AAPL", Market.USA, OptionStyle.American, OptionRight.Put, 505m, new DateTime(2014, 6, 27));
+            AddOptionContract(option, Resolution.Minute);
+
+            InitializeIndicators(option);
+        }
+
+        protected void InitializeIndicators(Symbol option)
+        {
+            _impliedVolatility = IV(option);
+            _delta = D(option, optionModel: OptionPricingModelType.BinomialCoxRossRubinstein, ivModel: OptionPricingModelType.BlackScholes);
+            _gamma = G(option, optionModel: OptionPricingModelType.ForwardTree, ivModel: OptionPricingModelType.BlackScholes);
+            _vega = V(option, optionModel: OptionPricingModelType.ForwardTree, ivModel: OptionPricingModelType.BlackScholes);
+            _theta = T(option, optionModel: OptionPricingModelType.ForwardTree, ivModel: OptionPricingModelType.BlackScholes);
+            _rho = R(option, optionModel: OptionPricingModelType.ForwardTree, ivModel: OptionPricingModelType.BlackScholes);
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_impliedVolatility == 0m || _delta == 0m || _gamma == 0m || _vega == 0m || _theta == 0m || _rho == 0m)
+            {
+                throw new RegressionTestException("Expected IV/greeks calculated");
+            }
+            var result = @$"Implied Volatility: {_impliedVolatility},Delta: {_delta},Gamma: {_gamma},Vega: {_vega},Theta: {_theta},Rho: {_rho}";
+
+            Debug(result);
+            if (result != ExpectedGreeks)
+            {
+                throw new RegressionTestException($"Unexpected greek values {result}. Expected {ExpectedGreeks}");
+            }
+        }
+
+        /// <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 => 1974;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public virtual 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", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}