Jhonathan Abreu
bc05aa03f9
* Add ITM option assignment trade as win in trade statistics * Add TradeStatistics unit tests * Add unit tests * Add OptionTrade class to abstract IsWin method * Keep track of winning/losing trades * Add more unit tests * Change Trade.IsWin to a property calculated by the trade builder * Improve regression algorithm * Handle ITM option sell win/loss statistics * Update regression algorithms statistics * Revert accidental unwanted changes * Address peer review * Keep track of winning and losing transactions for portfolio statistics * Add more SecurityPortfolioModel unit tests * Fix failing unit tests * Minor changes * Address peer review * Minor fix
89 lines
3.5 KiB
C#
89 lines
3.5 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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*/
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using System.Collections.Generic;
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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 asserting we can specify a custom option assignment
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/// </summary>
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public class CustomOptionAssignmentRegressionAlgorithm : OptionAssignmentRegressionAlgorithm
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{
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public override void Initialize()
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{
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SetSecurityInitializer((security) =>
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{
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var option = security as Option;
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// we have to be 10% in the money to get assigned
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option?.SetOptionAssignmentModel(new CustomOptionAssignmentModel(0.1m));
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});
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base.Initialize();
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}
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private class CustomOptionAssignmentModel : DefaultOptionAssignmentModel
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{
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public CustomOptionAssignmentModel(decimal requiredInTheMoneyPercent) : base (requiredInTheMoneyPercent)
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{
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}
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public override OptionAssignmentResult GetAssignment(OptionAssignmentParameters parameters)
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{
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var result = base.GetAssignment(parameters);
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result.Tag = "Custom Option Assignment";
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return result;
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}
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}
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
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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 Trades", "4"},
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{"Average Win", "9.48%"},
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{"Average Loss", "-16.73%"},
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{"Compounding Annual Return", "-25.790%"},
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{"Drawdown", "0.600%"},
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{"Expectancy", "-0.478"},
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{"Net Profit", "-0.462%"},
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{"Sharpe Ratio", "7.173"},
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{"Probabilistic Sharpe Ratio", "95.713%"},
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{"Loss Rate", "67%"},
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{"Win Rate", "33%"},
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{"Profit-Loss Ratio", "0.57"},
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{"Alpha", "0.003"},
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{"Beta", "-0.096"},
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{"Annual Standard Deviation", "0.003"},
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{"Annual Variance", "0"},
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{"Information Ratio", "10.577"},
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{"Tracking Error", "0.019"},
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{"Treynor Ratio", "-0.219"},
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{"Total Fees", "$2.00"},
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{"Estimated Strategy Capacity", "$4800000.00"},
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{"Lowest Capacity Asset", "GOOCV 305RBQ20WHPNQ|GOOCV VP83T1ZUHROL"},
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{"Portfolio Turnover", "26.72%"},
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{"OrderListHash", "bf5a09c30e03454434904ea6071540cf"}
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};
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}
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}
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