/* * 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.Data.UniverseSelection; using QuantConnect.Interfaces; using System; using System.Collections.Generic; using System.Linq; 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 slice) { 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 RegressionTestException($"Was expecting configurations for {_twx}" + $" even after it has been deselected from coarse universe because we still have the option contract."); } } else if (Time == new DateTime(2014, 6, 6, 14, 0, 0)) { // liquidate & remove the option RemoveOptionContract(_option); } // assert underlying was finally removed else if(Time > new DateTime(2014, 6, 6, 14, 0, 0)) { foreach (var symbol in new[] { _option, _option.Underlying }) { var configs = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol); if (configs.Any()) { throw new RegressionTestException($"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 RegressionTestException($"SecurityChanges.RemovedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!"); } if (_securityChanges.AddedSecurities.Intersect(changes.AddedSecurities).Any()) { throw new RegressionTestException($"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 = OptionChain(addedSecurity.Symbol) .OrderBy(contractData => contractData.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.Symbol, option.UnderlyingSymbol }) { var config = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol).ToList(); if (!config.Any()) { throw new RegressionTestException($"Was expecting configurations for {symbol}"); } if (config.Any(dataConfig => dataConfig.DataNormalizationMode != DataNormalizationMode.Raw)) { throw new RegressionTestException($"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 RegressionTestException($"Was NOT expecting any configurations for {_twx} or it's options, since we removed the contract"); } if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol != _aapl)) { throw new RegressionTestException($"Was expecting configurations for {_aapl}"); } if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol.Underlying != _aapl)) { throw new RegressionTestException($"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 List Languages { get; } = new() { Language.CSharp, Language.Python }; /// /// Data Points count of all timeslices of algorithm /// public long DataPoints => 5798; /// /// Data Points count of the algorithm history /// public int AlgorithmHistoryDataPoints => 2; /// /// 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 Dictionary ExpectedStatistics => new Dictionary { {"Total Orders", "2"}, {"Average Win", "0%"}, {"Average Loss", "-0.23%"}, {"Compounding Annual Return", "-15.596%"}, {"Drawdown", "0.200%"}, {"Expectancy", "-1"}, {"Start Equity", "100000"}, {"End Equity", "99768"}, {"Net Profit", "-0.232%"}, {"Sharpe Ratio", "-8.903"}, {"Sortino Ratio", "0"}, {"Probabilistic Sharpe Ratio", "1.216%"}, {"Loss Rate", "100%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0.015"}, {"Beta", "-0.171"}, {"Annual Standard Deviation", "0.006"}, {"Annual Variance", "0"}, {"Information Ratio", "-11.082"}, {"Tracking Error", "0.043"}, {"Treynor Ratio", "0.335"}, {"Total Fees", "$2.00"}, {"Estimated Strategy Capacity", "$2800000.00"}, {"Lowest Capacity Asset", "AOL VRKS95ENLBYE|AOL R735QTJ8XC9X"}, {"Portfolio Turnover", "1.14%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "cde7b518b7ad6d86cff6e5e092d9a413"} }; } }