/* * 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 System.Reflection; using QuantConnect.Data; using QuantConnect.Interfaces; using QuantConnect.Orders; using QuantConnect.Securities; using QuantConnect.Securities.Option; namespace QuantConnect.Algorithm.CSharp { /// /// This regression algorithm tests In The Money (ITM) future option expiry for calls. /// We test to make sure that FOPs have greeks enabled, same as equity options. /// public class FutureOptionCallITMGreeksExpiryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private bool _invested; private int _onDataCalls; private Symbol _es19m20; private Option _esOption; private Symbol _expectedOptionContract; public override void Initialize() { SetStartDate(2020, 1, 5); SetEndDate(2020, 6, 30); // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872 // which causes delisting events to never be processed, thus leading to options that might never // be exercised until the next data point arrives. AddEquity("AAPL", Resolution.Daily); _es19m20 = AddFutureContract( QuantConnect.Symbol.CreateFuture( Futures.Indices.SP500EMini, Market.CME, new DateTime(2020, 6, 19)), Resolution.Minute).Symbol; // Select a future option expiring ITM, and adds it to the algorithm. _esOption = AddFutureOptionContract(OptionChainProvider.GetOptionContractList(_es19m20, new DateTime(2020, 1, 5)) .Where(x => x.ID.StrikePrice <= 3200m && x.ID.OptionRight == OptionRight.Call) .OrderByDescending(x => x.ID.StrikePrice) .Take(1) .Single(), Resolution.Minute); _esOption.PriceModel = OptionPriceModels.BjerksundStensland(); _expectedOptionContract = QuantConnect.Symbol.CreateOption(_es19m20, Market.CME, OptionStyle.American, OptionRight.Call, 3200m, new DateTime(2020, 6, 19)); if (_esOption.Symbol != _expectedOptionContract) { throw new Exception($"Contract {_expectedOptionContract} was not found in the chain"); } } public override void OnData(Slice data) { // Let the algo warmup, but without using SetWarmup. Otherwise, we get // no contracts in the option chain if (_invested || _onDataCalls++ < 40) { return; } if (data.OptionChains.Count == 0) { return; } if (data.OptionChains.Values.All(o => o.Contracts.Values.Any(c => !data.ContainsKey(c.Symbol)))) { return; } if (data.OptionChains.Values.First().Contracts.Count == 0) { throw new Exception($"No contracts found in the option {data.OptionChains.Keys.First()}"); } var deltas = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Delta).ToList(); var gammas = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Gamma).ToList(); var lambda = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Lambda).ToList(); var rho = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Rho).ToList(); var theta = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Theta).ToList(); var vega = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Vega).ToList(); // The commented out test cases all return zero. // This is because of failure to evaluate the greeks in the option pricing model. // For now, let's skip those. if (deltas.Any(d => d == 0)) { throw new AggregateException("Option contract Delta was equal to zero"); } if (gammas.Any(g => g == 0)) { throw new AggregateException("Option contract Gamma was equal to zero"); } //if (lambda.Any(l => l == 0)) //{ // throw new AggregateException("Option contract Lambda was equal to zero"); //} if (rho.Any(r => r == 0)) { throw new AggregateException("Option contract Rho was equal to zero"); } //if (theta.Any(t => t == 0)) //{ // throw new AggregateException("Option contract Theta was equal to zero"); //} //if (vega.Any(v => v == 0)) //{ // throw new AggregateException("Option contract Vega was equal to zero"); //} if (!_invested) { SetHoldings(data.OptionChains.Values.First().Contracts.Values.First().Symbol, 1); _invested = true; } } /// /// Ran at the end of the algorithm to ensure the algorithm has no holdings /// /// The algorithm has holdings public override void OnEndOfAlgorithm() { if (Portfolio.Invested) { throw new Exception($"Expected no holdings at end of algorithm, but are invested in: {string.Join(", ", Portfolio.Keys)}"); } if (!_invested) { throw new Exception($"Never checked greeks, maybe we have no option data?"); } } /// /// 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 }; /// /// 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", "28.04%"}, {"Average Loss", "-62.81%"}, {"Compounding Annual Return", "-78.165%"}, {"Drawdown", "52.400%"}, {"Expectancy", "-0.277"}, {"Net Profit", "-52.379%"}, {"Sharpe Ratio", "-0.865"}, {"Probabilistic Sharpe Ratio", "0.019%"}, {"Loss Rate", "50%"}, {"Win Rate", "50%"}, {"Profit-Loss Ratio", "0.45"}, {"Alpha", "-0.596"}, {"Beta", "-0.031"}, {"Annual Standard Deviation", "0.681"}, {"Annual Variance", "0.463"}, {"Information Ratio", "-0.514"}, {"Tracking Error", "0.703"}, {"Treynor Ratio", "18.748"}, {"Total Fees", "$66.60"}, {"Fitness Score", "0.157"}, {"Kelly Criterion Estimate", "0"}, {"Kelly Criterion Probability Value", "0"}, {"Sortino Ratio", "-0.133"}, {"Return Over Maximum Drawdown", "-1.492"}, {"Portfolio Turnover", "0.411"}, {"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", "151392833"} }; } }