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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*/
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using QuantConnect.Interfaces;
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using QuantConnect.Data.UniverseSelection;
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using QuantConnect.Securities;
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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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/// Algorithm asserting that options are selected every day and that selection for 0DTE contracts works as expected,
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/// always including the contracts that expire the same date the option chain belongs to.
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/// </summary>
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public class ZeroDTEOptionsRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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protected List<DateTime> _selectionDays;
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private int _currentSelectionDayIndex;
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private int _previouslyAddedContracts;
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private bool _selectionChecked;
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protected Option _option;
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public override void Initialize()
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{
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SetStartDate(2024, 01, 01);
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SetEndDate(2024, 01, 10);
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SetCash(100000);
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var equity = AddEquity("SPY");
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var option = AddOption(equity.Symbol);
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option.SetFilter(u => u.IncludeWeeklys().Expiration(0, 0));
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_option = option;
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// use the underlying equity as the benchmark
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SetBenchmark(equity.Symbol);
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_selectionDays = new List<DateTime>()
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{
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new DateTime(2024, 01, 01), // Sunday midnight, already Monday 1st, it's a holiday. Selection happens for Tuesday here
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new DateTime(2024, 01, 03), // Wednesday, midnight
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new DateTime(2024, 01, 04),
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new DateTime(2024, 01, 05),
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new DateTime(2024, 01, 06), // Friday midnight, selection happens for Monday here
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new DateTime(2024, 01, 09), // Monday midnight, already Tuesday, selection happens for Tuesday here
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new DateTime(2024, 01, 10),
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};
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}
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public override void OnSecuritiesChanged(SecurityChanges changes)
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{
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var exchangeTime = UtcTime.ConvertFromUtc(_option.Exchange.TimeZone);
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// Selection happens at midnight
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if (exchangeTime.TimeOfDay == TimeSpan.Zero)
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{
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_selectionChecked = true;
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// We expect selection every trading day
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if (Time.Date != _selectionDays[_currentSelectionDayIndex++])
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{
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throw new RegressionTestException($"Unexpected date. Expected {_selectionDays[_currentSelectionDayIndex]} but was {Time.Date}");
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}
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var addedOptions = changes.AddedSecurities.Where(x => x.Symbol.SecurityType == _option.Symbol.SecurityType && !x.Symbol.IsCanonical()).ToList();
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if (addedOptions.Count == 0)
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{
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throw new RegressionTestException("No options were added");
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}
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var removedOptions = changes.RemovedSecurities.Where(x => x.Symbol.SecurityType == _option.Symbol.SecurityType && !x.Symbol.IsCanonical()).ToList();
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// Since we are selecting only 0DTE contracts, they must be deselected that same day
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if (removedOptions.Count != _previouslyAddedContracts)
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{
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throw new RegressionTestException($"Unexpected number of removed contracts. Expected {_previouslyAddedContracts} but was {removedOptions.Count}");
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}
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_previouslyAddedContracts = addedOptions.Count;
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (!_selectionChecked)
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{
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throw new RegressionTestException("Selection was not checked");
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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 virtual List<Language> Languages { get; } = new() { Language.CSharp };
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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 virtual long DataPoints => 227;
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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 virtual 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 virtual 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 virtual 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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