/* * 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.Collections.Generic; using System.Linq; using QuantConnect.Data; using QuantConnect.Data.UniverseSelection; using QuantConnect.Interfaces; namespace QuantConnect.Algorithm.CSharp { /// /// We add an option contract using and place a trade, the underlying /// gets deselected from the universe selection but should still be present since we manually added the option contract. /// Later we call and expect both option and underlying to be removed. /// public class AddOptionContractFromUniverseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private DateTime _expiration = new DateTime(2014, 06, 21); private SecurityChanges _securityChanges = SecurityChanges.None; private Symbol _option; private Symbol _aapl; private Symbol _twx; private bool _traded; public override void Initialize() { _twx = QuantConnect.Symbol.Create("TWX", SecurityType.Equity, Market.USA); _aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA); UniverseSettings.Resolution = Resolution.Minute; UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw; SetStartDate(2014, 06, 05); SetEndDate(2014, 06, 09); AddUniverse(enumerable => new[] { Time.Date <= new DateTime(2014, 6, 5) ? _twx : _aapl }, enumerable => new[] { Time.Date <= new DateTime(2014, 6, 5) ? _twx : _aapl }); } public override void OnData(Slice data) { if (_option != null && Securities[_option].Price != 0 && !_traded) { _traded = true; Buy(_option, 1); } if (Time.Date > new DateTime(2014, 6, 5)) { if (Time < new DateTime(2014, 6, 6, 14, 0, 0)) { var configs = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx); // assert underlying still there after the universe selection removed it, still used by the manually added option contract if (!configs.Any()) { throw new Exception($"Was expecting configurations for {_twx}" + $" even after it has been deselected from coarse universe because we still have the option contract."); } } else if (Time == new DateTime(2014, 6, 6, 14, 0, 0)) { // liquidate & remove the option RemoveOptionContract(_option); } // assert underlying was finally removed else if(Time > new DateTime(2014, 6, 6, 14, 0, 0)) { foreach (var symbol in new[] { _option, _option.Underlying }) { var configs = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol); if (configs.Any()) { throw new Exception($"Unexpected configuration for {symbol} after it has been deselected from coarse universe and option contract is removed."); } } } } } public override void OnSecuritiesChanged(SecurityChanges changes) { if (_securityChanges.RemovedSecurities.Intersect(changes.RemovedSecurities).Any()) { throw new Exception($"SecurityChanges.RemovedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!"); } if (_securityChanges.AddedSecurities.Intersect(changes.AddedSecurities).Any()) { throw new Exception($"SecurityChanges.AddedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!"); } // keep track of all removed and added securities _securityChanges += changes; if (changes.AddedSecurities.Any(security => security.Symbol.SecurityType == SecurityType.Option)) { return; } foreach (var addedSecurity in changes.AddedSecurities) { var option = OptionChainProvider.GetOptionContractList(addedSecurity.Symbol, Time) .OrderBy(symbol => symbol.ID.Symbol) .First(optionContract => optionContract.ID.Date == _expiration && optionContract.ID.OptionRight == OptionRight.Call && optionContract.ID.OptionStyle == OptionStyle.American); AddOptionContract(option); 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}"); } } // just keep the first we got if (_option == null) { _option = option; } } } public override void OnEndOfAlgorithm() { if (SubscriptionManager.Subscriptions.Any(dataConfig => dataConfig.Symbol == _twx || dataConfig.Symbol.Underlying == _twx)) { throw new Exception($"Was NOT expecting any configurations for {_twx} or it's options, since we removed the contract"); } if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol != _aapl)) { throw new Exception($"Was expecting configurations for {_aapl}"); } if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol.Underlying != _aapl)) { throw new Exception($"Was expecting options configurations for {_aapl}"); } } /// /// 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", "2"}, {"Average Win", "0%"}, {"Average Loss", "-0.23%"}, {"Compounding Annual Return", "-15.596%"}, {"Drawdown", "0.200%"}, {"Expectancy", "-1"}, {"Net Profit", "-0.232%"}, {"Sharpe Ratio", "-7.739"}, {"Probabilistic Sharpe Ratio", "1.216%"}, {"Loss Rate", "100%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0.027"}, {"Beta", "-0.174"}, {"Annual Standard Deviation", "0.006"}, {"Annual Variance", "0"}, {"Information Ratio", "-11.586"}, {"Tracking Error", "0.042"}, {"Treynor Ratio", "0.286"}, {"Total Fees", "$2.00"}, {"Fitness Score", "0"}, {"Kelly Criterion Estimate", "0"}, {"Kelly Criterion Probability Value", "0"}, {"Sortino Ratio", "-19.883"}, {"Return Over Maximum Drawdown", "-67.224"}, {"Portfolio Turnover", "0.014"}, {"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", "721476625"} }; } }