/* * 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 System; using System.Linq; using QuantConnect.Data; using QuantConnect.Interfaces; using System.Collections.Generic; namespace QuantConnect.Algorithm.CSharp { /// /// We add an option contract using and place a trade and wait till it expires /// later will liquidate the resulting equity position and assert both option and underlying get removed /// public class AddOptionContractExpiresRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private DateTime _expiration = new DateTime(2014, 06, 21); private Symbol _option; private Symbol _twx; private bool _traded; public override void Initialize() { SetStartDate(2014, 06, 05); SetEndDate(2014, 06, 30); _twx = QuantConnect.Symbol.Create("TWX", SecurityType.Equity, Market.USA); AddUniverse("my-daily-universe-name", time => new List { "AAPL" }); } public override void OnData(Slice data) { if (_option == null) { var option = OptionChainProvider.GetOptionContractList(_twx, Time) .OrderBy(symbol => symbol.ID.Symbol) .FirstOrDefault(optionContract => optionContract.ID.Date == _expiration && optionContract.ID.OptionRight == OptionRight.Call && optionContract.ID.OptionStyle == OptionStyle.American); if (option != null) { _option = AddOptionContract(option).Symbol; } } if (_option != null && Securities[_option].Price != 0 && !_traded) { _traded = true; Buy(_option, 1); foreach (var symbol in new [] { _option, _option.Underlying }) { var config = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol).ToList(); if (!config.Any()) { throw new Exception($"Was expecting configurations for {symbol}"); } if (config.Any(dataConfig => dataConfig.DataNormalizationMode != DataNormalizationMode.Raw)) { throw new Exception($"Was expecting DataNormalizationMode.Raw configurations for {symbol}"); } } } if (Time.Date > _expiration) { if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_option).Any()) { throw new Exception($"Unexpected configurations for {_option} after it has been delisted"); } if (Securities[_twx].Invested) { if (!SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any()) { throw new Exception($"Was expecting configurations for {_twx}"); } // first we liquidate the option exercised position Liquidate(_twx); } } else if (Time.Date > _expiration && !Securities[_twx].Invested) { if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any()) { throw new Exception($"Unexpected configurations for {_twx} after it has been liquidated"); } } } /// /// 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 Language[] Languages { get; } = { Language.CSharp, Language.Python }; /// /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm /// public Dictionary ExpectedStatistics => new Dictionary { {"Total Trades", "3"}, {"Average Win", "2.73%"}, {"Average Loss", "-2.98%"}, {"Compounding Annual Return", "-4.619%"}, {"Drawdown", "0.300%"}, {"Expectancy", "-0.042"}, {"Net Profit", "-0.332%"}, {"Sharpe Ratio", "-3.7"}, {"Probabilistic Sharpe Ratio", "0.563%"}, {"Loss Rate", "50%"}, {"Win Rate", "50%"}, {"Profit-Loss Ratio", "0.92"}, {"Alpha", "-0.023"}, {"Beta", "0.005"}, {"Annual Standard Deviation", "0.006"}, {"Annual Variance", "0"}, {"Information Ratio", "-3.424"}, {"Tracking Error", "0.057"}, {"Treynor Ratio", "-4.775"}, {"Total Fees", "$2.00"}, {"Fitness Score", "0"}, {"Kelly Criterion Estimate", "0"}, {"Kelly Criterion Probability Value", "0"}, {"Sortino Ratio", "-43.418"}, {"Return Over Maximum Drawdown", "-14.274"}, {"Portfolio Turnover", "0.007"}, {"Total Insights Generated", "0"}, {"Total Insights Closed", "0"}, {"Total Insights Analysis Completed", "0"}, {"Long Insight Count", "0"}, {"Short Insight Count", "0"}, {"Long/Short Ratio", "100%"}, {"Estimated Monthly Alpha Value", "$0"}, {"Total Accumulated Estimated Alpha Value", "$0"}, {"Mean Population Estimated Insight Value", "$0"}, {"Mean Population Direction", "0%"}, {"Mean Population Magnitude", "0%"}, {"Rolling Averaged Population Direction", "0%"}, {"Rolling Averaged Population Magnitude", "0%"}, {"OrderListHash", "-1185639451"} }; } }