wehub-resource-sync
102 lines
3.9 KiB
C#
102 lines
3.9 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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using QuantConnect.Orders.OptionExercise;
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using QuantConnect.Orders;
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using QuantConnect.Orders.Fees;
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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 exercise model
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/// </summary>
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public class CustomOptionExerciseModelRegressionAlgorithm : 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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option?.SetOptionExerciseModel(new CustomOptionExerciseModel());
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});
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base.Initialize();
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}
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private class CustomOptionExerciseModel : DefaultExerciseModel
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{
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public override IEnumerable<OrderEvent> OptionExercise(Option option, OptionExerciseOrder order)
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{
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yield return new OrderEvent(order.Id,
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option.Symbol,
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option.LocalTime.ConvertToUtc(option.Exchange.TimeZone),
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OrderStatus.Filled,
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Extensions.GetOrderDirection(order.Quantity),
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0.0m,
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order.Quantity,
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OrderFee.Zero,
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"Tag")
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{
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IsAssignment = false
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};
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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 List<Language> Languages { get; } = new() { 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 Orders", "32"},
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{"Average Win", "6.14%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "26116903817855100000000000000%"},
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{"Drawdown", "0.500%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "257114"},
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{"Net Profit", "157.114%"},
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{"Sharpe Ratio", "107.743"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "95.613%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "100%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "60.088"},
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{"Beta", "-19.374"},
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{"Annual Standard Deviation", "0.593"},
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{"Annual Variance", "0.351"},
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{"Information Ratio", "106.234"},
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{"Tracking Error", "0.603"},
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{"Treynor Ratio", "-3.295"},
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{"Total Fees", "$16.00"},
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{"Estimated Strategy Capacity", "$87000.00"},
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{"Lowest Capacity Asset", "GOOCV 305RBQ20WLZZA|GOOCV VP83T1ZUHROL"},
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{"Portfolio Turnover", "10.93%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "19b8f2a8081c3cfa8f6bc02b5d045765"}
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};
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}
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}
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