/* * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ using QuantConnect.Data; using QuantConnect.Interfaces; using QuantConnect.Securities; using System.Collections.Generic; using System.Linq; namespace QuantConnect.Algorithm.CSharp { /// /// Regression algorithm reproducing issue #5160 where delisting order would be cancelled because it was placed at the market close on the delisting day /// public class DelistingFutureOptionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { protected virtual Resolution Resolution => Resolution.Minute; private bool _traded; private int _lastMonth; public override void Initialize() { SetStartDate(2012, 1, 1); SetEndDate(2013, 1, 1); SetCash(10000000); var dc = AddFuture(Futures.Dairy.ClassIIIMilk, Resolution, Market.CME); dc.SetFilter(1, 120); AddFutureOption(dc.Symbol, universe => universe.Strikes(-2, 2)); _lastMonth = -1; // This is required to prevent the algorithm from automatically delisting the underlying. Without this, future options will be subscribed // with resolution default to Minute insted of this.Resolution. This could be replaced after GH issue #6491 is implemented. UniverseSettings.Resolution = Resolution; } public override void OnData(Slice slice) { if (Time.Month != _lastMonth) { _lastMonth = Time.Month; var investedSymbols = Securities.Values .Where(security => security.Invested) .Select(security => security.Symbol) .ToList(); var delistedSecurity = investedSymbols.Where(symbol => symbol.ID.Date.AddDays(1) < Time).ToList(); if (delistedSecurity.Count > 0) { throw new RegressionTestException($"[{UtcTime}] We hold a delisted securities: {string.Join(",", delistedSecurity)}"); } Log($"Holdings({Time}): {string.Join(",", investedSymbols)}"); } if (Portfolio.Invested) { return; } foreach (var chain in slice.OptionChains.Values) { foreach (var contractsValue in chain.Contracts.Values) { MarketOrder(contractsValue.Symbol, 1); _traded = true; } } } public override void OnEndOfAlgorithm() { if (!_traded) { throw new RegressionTestException("We expected some FOP trading to happen"); } if (Portfolio.Invested) { throw new RegressionTestException("We shouldn't be invested anymore"); } } /// /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm. /// public bool CanRunLocally { get; } = true; /// /// This is used by the regression test system to indicate which languages this algorithm is written in. /// public List Languages { get; } = new() { Language.CSharp }; /// /// Data Points count of all timeslices of algorithm /// public virtual long DataPoints => 761073; /// /// Data Points count of the algorithm history /// public int AlgorithmHistoryDataPoints => 0; /// /// Final status of the algorithm /// public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed; /// /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm /// public virtual Dictionary ExpectedStatistics => new Dictionary { {"Total Orders", "16"}, {"Average Win", "0.01%"}, {"Average Loss", "-0.02%"}, {"Compounding Annual Return", "-0.111%"}, {"Drawdown", "0.100%"}, {"Expectancy", "-0.678"}, {"Start Equity", "10000000"}, {"End Equity", "9988880.24"}, {"Net Profit", "-0.111%"}, {"Sharpe Ratio", "-10.416"}, {"Sortino Ratio", "-0.959"}, {"Probabilistic Sharpe Ratio", "0.000%"}, {"Loss Rate", "80%"}, {"Win Rate", "20%"}, {"Profit-Loss Ratio", "0.61"}, {"Alpha", "-0.008"}, {"Beta", "-0.001"}, {"Annual Standard Deviation", "0.001"}, {"Annual Variance", "0"}, {"Information Ratio", "-1.076"}, {"Tracking Error", "0.107"}, {"Treynor Ratio", "14.634"}, {"Total Fees", "$19.76"}, {"Estimated Strategy Capacity", "$1400000000.00"}, {"Lowest Capacity Asset", "DC V5E8PHPRCHJ8|DC V5E8P9SH0U0X"}, {"Portfolio Turnover", "0.00%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "6448bae646ab35724a0cd23936d94a48"} }; } }