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* Implement indicator-based option price model This model uses IV and Greeks indicators to implement Lean's own option pricing model * Minor fixes * Address peer review * Minor tests fixes * Make the indicator based price model the default for options * Address peer review * Cleanup and minor changes * Support indicators configuration for new pricing model * Some cleanup * Add QL option price model example algorithm * Return lean models from static helpers * Minor tests fixes * Minor test fixes * Address peer review * Cleanup * Fix unit tests * Move QL models to OptionPriceModels.QuantLib.* * Add forward tree helper method
94 lines
3.6 KiB
C#
94 lines
3.6 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using System.Collections.Generic;
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using QuantConnect.Indicators;
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using QuantConnect.Securities.Option;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm exercising an equity covered American style option, using an option price model that does not support American style options and asserting that the option price model is not used.
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/// </summary>
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public class OptionPriceModelForUnsupportedAmericanOptionRegressionAlgorithm : OptionPriceModelForOptionStylesBaseRegressionAlgorithm
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{
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public override void Initialize()
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{
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SetStartDate(2014, 6, 9);
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SetEndDate(2014, 6, 9);
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var option = AddOption("AAPL", Resolution.Minute);
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option.SetFilter(u => u.StandardsOnly().Strikes(-1, 1).Expiration(0, 35));
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// QL BlackSholes model does not support American style options
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option.PriceModel = OptionPriceModels.QuantLib.BlackScholes();
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SetWarmup(2, Resolution.Daily);
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Init(option, optionStyleIsSupported: false);
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}
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public override long DataPoints => 15787;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public override int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public override AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "0"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "100000"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "0"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Lowest Capacity Asset", ""},
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{"Portfolio Turnover", "0%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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