wehub-resource-sync
217 lines
9.3 KiB
C#
217 lines
9.3 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using System;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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using QuantConnect.Securities;
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using System.Collections.Generic;
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using QuantConnect.Securities.Option;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This regression algorithm tests In The Money (ITM) future option expiry for calls.
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/// We test to make sure that FOPs have greeks enabled, same as equity options.
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/// </summary>
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public class FutureOptionCallITMGreeksExpiryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private bool _invested;
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private int _onDataCalls;
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private Security _es19m20;
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private Option _esOption;
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private Symbol _expectedOptionContract;
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public override void Initialize()
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{
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SetStartDate(2020, 1, 5);
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SetEndDate(2020, 6, 30);
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_es19m20 = AddFutureContract(
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QuantConnect.Symbol.CreateFuture(
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Futures.Indices.SP500EMini,
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Market.CME,
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new DateTime(2020, 6, 19)),
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Resolution.Minute);
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// We must set the volatility model on the underlying, since the defaults are
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// too strict to calculate greeks with when we only have data for a single day
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_es19m20.VolatilityModel = new StandardDeviationOfReturnsVolatilityModel(
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60,
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Resolution.Minute,
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TimeSpan.FromMinutes(1));
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// Select a future option expiring ITM, and adds it to the algorithm.
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_esOption = AddFutureOptionContract(OptionChain(_es19m20.Symbol)
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.Where(x => x.ID.StrikePrice <= 3200m && x.ID.OptionRight == OptionRight.Call)
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.OrderByDescending(x => x.ID.StrikePrice)
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.Take(1)
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.Single(), Resolution.Minute);
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_esOption.PriceModel = OptionPriceModels.QuantLib.BjerksundStensland();
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_expectedOptionContract = QuantConnect.Symbol.CreateOption(_es19m20.Symbol, Market.CME, OptionStyle.American, OptionRight.Call, 3200m, new DateTime(2020, 6, 19));
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if (_esOption.Symbol != _expectedOptionContract)
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{
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throw new RegressionTestException($"Contract {_expectedOptionContract} was not found in the chain");
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}
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}
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public override void OnData(Slice slice)
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{
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// Let the algo warmup, but without using SetWarmup. Otherwise, we get
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// no contracts in the option chain
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if (_invested || _onDataCalls++ < 40)
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{
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return;
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}
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if (slice.OptionChains.Count == 0)
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{
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return;
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}
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if (slice.OptionChains.Values.All(o => o.Contracts.Values.Any(c => !slice.ContainsKey(c.Symbol))))
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{
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return;
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}
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if (slice.OptionChains.Values.First().Contracts.Count == 0)
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{
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throw new RegressionTestException($"No contracts found in the option {slice.OptionChains.Keys.First()}");
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}
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var deltas = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Delta).ToList();
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var gammas = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Gamma).ToList();
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var lambda = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Lambda).ToList();
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var rho = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Rho).ToList();
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var theta = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Theta).ToList();
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var vega = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Vega).ToList();
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// The commented out test cases all return zero.
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// This is because of failure to evaluate the greeks in the option pricing model.
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// For now, let's skip those.
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if (deltas.Any(d => d == 0))
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{
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throw new AggregateException("Option contract Delta was equal to zero");
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}
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if (gammas.Any(g => g == 0))
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{
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throw new AggregateException("Option contract Gamma was equal to zero");
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}
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if (lambda.Any(l => l == 0))
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{
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throw new AggregateException("Option contract Lambda was equal to zero");
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}
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if (rho.Any(r => r == 0))
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{
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throw new AggregateException("Option contract Rho was equal to zero");
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}
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if (theta.Any(t => t == 0))
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{
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throw new AggregateException("Option contract Theta was equal to zero");
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}
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if (vega.Any(v => v == 0))
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{
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throw new AggregateException("Option contract Vega was equal to zero");
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}
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if (!_invested)
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{
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// the margin requirement for the FOPs is less than the one of the underlying so we can't allocate all our buying power
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// into FOPs else we won't be able to exercise
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SetHoldings(slice.OptionChains.Values.First().Contracts.Values.First().Symbol, 0.25);
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_invested = true;
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}
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}
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/// <summary>
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/// Ran at the end of the algorithm to ensure the algorithm has no holdings
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/// </summary>
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/// <exception cref="RegressionTestException">The algorithm has holdings</exception>
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public override void OnEndOfAlgorithm()
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{
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if (Portfolio.Invested)
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{
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throw new RegressionTestException($"Expected no holdings at end of algorithm, but are invested in: {string.Join(", ", Portfolio.Keys)}");
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}
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if (!_invested)
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{
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throw new RegressionTestException($"Never checked greeks, maybe we have no option data?");
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}
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public List<Language> Languages { get; } = new() { Language.CSharp };
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public long DataPoints => 212198;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public int AlgorithmHistoryDataPoints => 1;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "3"},
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{"Average Win", "16.44%"},
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{"Average Loss", "-35.38%"},
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{"Compounding Annual Return", "-44.262%"},
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{"Drawdown", "26.200%"},
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{"Expectancy", "-0.268"},
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{"Start Equity", "100000"},
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{"End Equity", "75242.9"},
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{"Net Profit", "-24.757%"},
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{"Sharpe Ratio", "-0.965"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0.037%"},
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{"Loss Rate", "50%"},
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{"Win Rate", "50%"},
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{"Profit-Loss Ratio", "0.46"},
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{"Alpha", "-0.303"},
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{"Beta", "0.016"},
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{"Annual Standard Deviation", "0.313"},
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{"Annual Variance", "0.098"},
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{"Information Ratio", "-0.649"},
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{"Tracking Error", "0.483"},
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{"Treynor Ratio", "-18.59"},
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{"Total Fees", "$7.10"},
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{"Estimated Strategy Capacity", "$24000000.00"},
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{"Lowest Capacity Asset", "ES XFH59UPBMTJ8|ES XFH59UK0MYO1"},
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{"Portfolio Turnover", "12.22%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "1d4a9403cd69b8510f15d100acdffa26"}
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};
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}
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}
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