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 System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Data.Market;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities.Option;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm to test the creation and usage of a custom option price model
+    /// </summary>
+    public class CustomOptionPriceModelRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _optionSymbol;
+        private CustomOptionPriceModel _optionPriceModel;
+
+        public override void Initialize()
+        {
+            SetStartDate(2015, 12, 24);
+            SetEndDate(2015, 12, 24);
+
+            var option = AddOption("GOOG");
+            _optionSymbol = option.Symbol;
+
+            option.SetFilter(u => u.StandardsOnly().Strikes(-2, +2).Expiration(0, 180));
+            _optionPriceModel = new CustomOptionPriceModel();
+            option.SetPriceModel(_optionPriceModel);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (Portfolio.Invested)
+            {
+                return;
+            }
+
+            if (slice.OptionChains.TryGetValue(_optionSymbol, out var chain))
+            {
+                var underlyingPrice = chain.Underlying.Price;
+                var atmContract = chain
+                    .OrderByDescending(x => x.Expiry)
+                    .ThenBy(x => Math.Abs(chain.Underlying.Price - x.Strike))
+                    .ThenByDescending(x => x.Right)
+                    .FirstOrDefault();
+
+                if (atmContract != null && atmContract.TheoreticalPrice > 0)
+                {
+                    MarketOrder(atmContract.Symbol, 1);
+                }
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_optionPriceModel.EvaluationCount == 0)
+            {
+                throw new RegressionTestException("CustomOptionPriceModel.Evaluate() was never called");
+            }
+        }
+
+        private class CustomOptionPriceModel : IOptionPriceModel
+        {
+            public int EvaluationCount { get; private set; }
+            public OptionPriceModelResult Evaluate(OptionPriceModelParameters parameters)
+            {
+                EvaluationCount++;
+                var contract = parameters.Contract;
+                var underlying = contract.UnderlyingLastPrice;
+                var strike = contract.Strike;
+                var greeks = new Greeks(0.5m, 0.2m, 0.15m, 0.05m, 0.1m, 2.0m);
+
+                decimal intrinsicValue;
+                if (contract.Right == OptionRight.Call)
+                {
+                    intrinsicValue = Math.Max(0, underlying - strike);
+                }
+                else
+                {
+                    intrinsicValue = Math.Max(0, strike - underlying);
+                    // Delta and Rho are negative for a put
+                    greeks.Delta *= -1;
+                    greeks.Rho *= -1;
+                }
+                var theoreticalPrice = intrinsicValue + 1.0m;
+                var impliedVolatility = 0.2m;
+
+                return new OptionPriceModelResult(theoreticalPrice, impliedVolatility, greeks);
+            }
+        }
+
+        /// <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 => 15023;
+
+        /// <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%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99799"},
+            {"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", "$1.00"},
+            {"Estimated Strategy Capacity", "$2600000.00"},
+            {"Lowest Capacity Asset", "GOOCV 30AKMEIPOX2DI|GOOCV VP83T1ZUHROL"},
+            {"Portfolio Turnover", "5.49%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "1925127010d4a935c1efe4bce0375c15"}
+        };
+    }
+}