/* * 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 QuantConnect.Securities; using System.Collections.Generic; 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 Security _es19m20; private Option _esOption; private Symbol _expectedOptionContract; public override void Initialize() { SetStartDate(2020, 1, 5); SetEndDate(2020, 6, 30); _es19m20 = AddFutureContract( QuantConnect.Symbol.CreateFuture( Futures.Indices.SP500EMini, Market.CME, new DateTime(2020, 6, 19)), Resolution.Minute); // We must set the volatility model on the underlying, since the defaults are // too strict to calculate greeks with when we only have data for a single day _es19m20.VolatilityModel = new StandardDeviationOfReturnsVolatilityModel( 60, Resolution.Minute, TimeSpan.FromMinutes(1)); // Select a future option expiring ITM, and adds it to the algorithm. _esOption = AddFutureOptionContract(OptionChain(_es19m20.Symbol) .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.Symbol, Market.CME, OptionStyle.American, OptionRight.Call, 3200m, new DateTime(2020, 6, 19)); if (_esOption.Symbol != _expectedOptionContract) { throw new RegressionTestException($"Contract {_expectedOptionContract} was not found in the chain"); } } public override void OnData(Slice slice) { // Let the algo warmup, but without using SetWarmup. Otherwise, we get // no contracts in the option chain if (_invested || _onDataCalls++ < 40) { return; } if (slice.OptionChains.Count == 0) { return; } if (slice.OptionChains.Values.All(o => o.Contracts.Values.Any(c => !slice.ContainsKey(c.Symbol)))) { return; } if (slice.OptionChains.Values.First().Contracts.Count == 0) { throw new RegressionTestException($"No contracts found in the option {slice.OptionChains.Keys.First()}"); } var deltas = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Delta).ToList(); var gammas = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Gamma).ToList(); var lambda = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Lambda).ToList(); var rho = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Rho).ToList(); var theta = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Theta).ToList(); var vega = slice.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) { // the margin requirement for the FOPs is less than the one of the underlying so we can't allocate all our buying power // into FOPs else we won't be able to exercise SetHoldings(slice.OptionChains.Values.First().Contracts.Values.First().Symbol, 0.25); _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 RegressionTestException($"Expected no holdings at end of algorithm, but are invested in: {string.Join(", ", Portfolio.Keys)}"); } if (!_invested) { throw new RegressionTestException($"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 List Languages { get; } = new() { Language.CSharp }; /// /// Data Points count of all timeslices of algorithm /// public long DataPoints => 212196; /// /// Data Points count of the algorithm history /// public int AlgorithmHistoryDataPoints => 1; /// /// 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", "3"}, {"Average Win", "16.44%"}, {"Average Loss", "-35.38%"}, {"Compounding Annual Return", "-44.262%"}, {"Drawdown", "26.200%"}, {"Expectancy", "-0.268"}, {"Start Equity", "100000"}, {"End Equity", "75242.9"}, {"Net Profit", "-24.757%"}, {"Sharpe Ratio", "-0.965"}, {"Sortino Ratio", "0"}, {"Probabilistic Sharpe Ratio", "0.060%"}, {"Loss Rate", "50%"}, {"Win Rate", "50%"}, {"Profit-Loss Ratio", "0.46"}, {"Alpha", "-0.303"}, {"Beta", "0.016"}, {"Annual Standard Deviation", "0.313"}, {"Annual Variance", "0.098"}, {"Information Ratio", "-0.649"}, {"Tracking Error", "0.483"}, {"Treynor Ratio", "-18.59"}, {"Total Fees", "$7.10"}, {"Estimated Strategy Capacity", "$24000000.00"}, {"Lowest Capacity Asset", "ES XFH59UPBIJ7O|ES XFH59UK0MYO1"}, {"Portfolio Turnover", "12.22%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "355dbab2e93d7a62b073b6e6cd4557c2"} }; } }