chore: import upstream snapshot with attribution
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wehub-resource-sync
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/*
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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;
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using System.Collections.Generic;
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using QuantConnect.Algorithm.Framework.Alphas;
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using QuantConnect.Algorithm.Framework.Execution;
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using QuantConnect.Algorithm.Framework.Portfolio;
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using QuantConnect.Algorithm.Framework.Risk;
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using QuantConnect.Algorithm.Framework.Selection;
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using QuantConnect.Interfaces;
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using QuantConnect.Securities;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Basic template options framework algorithm uses framework components to define an algorithm
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/// that trades options.
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/// </summary>
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public class BasicTemplateOptionsFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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public override void Initialize()
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{
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UniverseSettings.Resolution = Resolution.Minute;
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SetStartDate(2014, 06, 05);
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SetEndDate(2014, 06, 09);
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SetCash(100000);
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// set framework models
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SetUniverseSelection(new EarliestExpiringWeeklyAtTheMoneyPutOptionUniverseSelectionModel(SelectOptionChainSymbols));
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SetAlpha(new ConstantOptionContractAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromHours(0.5)));
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SetPortfolioConstruction(new SingleSharePortfolioConstructionModel());
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SetExecution(new ImmediateExecutionModel());
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SetRiskManagement(new NullRiskManagementModel());
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}
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// option symbol universe selection function
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private static IEnumerable<Symbol> SelectOptionChainSymbols(DateTime utcTime)
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{
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var newYorkTime = utcTime.ConvertFromUtc(TimeZones.NewYork);
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if (newYorkTime.Date < new DateTime(2014, 06, 06))
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{
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yield return QuantConnect.Symbol.Create("TWX", SecurityType.Option, Market.USA, "?TWX");
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}
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if (newYorkTime.Date >= new DateTime(2014, 06, 06))
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{
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yield return QuantConnect.Symbol.Create("AAPL", SecurityType.Option, Market.USA, "?AAPL");
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}
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}
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/// <summary>
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/// Creates option chain universes that select only the earliest expiry ATM weekly put contract
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/// and runs a user defined optionChainSymbolSelector every day to enable choosing different option chains
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/// </summary>
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class EarliestExpiringWeeklyAtTheMoneyPutOptionUniverseSelectionModel : OptionUniverseSelectionModel
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{
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public EarliestExpiringWeeklyAtTheMoneyPutOptionUniverseSelectionModel(Func<DateTime, IEnumerable<Symbol>> optionChainSymbolSelector)
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: base(TimeSpan.FromDays(1), optionChainSymbolSelector)
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{
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}
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/// <summary>
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/// Defines the option chain universe filter
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/// </summary>
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protected override OptionFilterUniverse Filter(OptionFilterUniverse filter)
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{
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return filter
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.Strikes(+1, +1)
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// Expiration method accepts TimeSpan objects or integer for days.
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// The following statements yield the same filtering criteria
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.Expiration(0, 7)
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//.Expiration(TimeSpan.Zero, TimeSpan.FromDays(7))
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.WeeklysOnly()
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.PutsOnly()
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.OnlyApplyFilterAtMarketOpen();
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}
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}
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/// <summary>
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/// Implementation of a constant alpha model that only emits insights for option symbols
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/// </summary>
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class ConstantOptionContractAlphaModel : ConstantAlphaModel
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{
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public ConstantOptionContractAlphaModel(InsightType type, InsightDirection direction, TimeSpan period)
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: base(type, direction, period)
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{
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}
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protected override bool ShouldEmitInsight(DateTime utcTime, Symbol symbol)
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{
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// only emit alpha for option symbols and not underlying equity symbols
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if (symbol.SecurityType != SecurityType.Option)
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{
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return false;
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}
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return base.ShouldEmitInsight(utcTime, symbol);
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}
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}
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/// <summary>
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/// Portfolio construction model that sets target quantities to 1 for up insights and -1 for down insights
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/// </summary>
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class SingleSharePortfolioConstructionModel : PortfolioConstructionModel
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{
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public override IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
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{
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foreach (var insight in insights)
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{
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yield return new PortfolioTarget(insight.Symbol, (int) insight.Direction);
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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 if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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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 List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
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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 long DataPoints => 17487;
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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 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 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 Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "5"},
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{"Average Win", "0.13%"},
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{"Average Loss", "-0.30%"},
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{"Compounding Annual Return", "-46.395%"},
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{"Drawdown", "1.600%"},
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{"Expectancy", "0.429"},
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{"Start Equity", "100000"},
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{"End Equity", "99149.50"},
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{"Net Profit", "-0.850%"},
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{"Sharpe Ratio", "-4.298"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "14.867%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "100%"},
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{"Profit-Loss Ratio", "0.43"},
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{"Alpha", "-0.84"},
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{"Beta", "0.986"},
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{"Annual Standard Deviation", "0.098"},
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{"Annual Variance", "0.01"},
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{"Information Ratio", "-9.299"},
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{"Tracking Error", "0.091"},
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{"Treynor Ratio", "-0.428"},
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{"Total Fees", "$4.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
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{"Portfolio Turnover", "13.50%"},
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{"Drawdown Recovery", "2"},
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{"OrderListHash", "2ab4ffc0944a2888a3be0568c2570a79"}
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};
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}
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}
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