/* * 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.Market; using QuantConnect.Orders; using QuantConnect.Interfaces; namespace QuantConnect.Algorithm.CSharp { /// /// This regression algorithm checks if all the option chain data coming to the algo is consistent with current securities manager state /// /// /// /// /// public class OptionChainConsistencyRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private const string UnderlyingTicker = "GOOG"; private readonly Symbol _optionSymbol = QuantConnect.Symbol.Create(UnderlyingTicker, SecurityType.Option, Market.USA); public override void Initialize() { SetStartDate(2015, 12, 24); SetEndDate(2015, 12, 24); SetCash(10000); var equity = AddEquity(UnderlyingTicker); var option = AddOption(UnderlyingTicker); // set our strike/expiry filter for this option chain option.SetFilter(u => u.IncludeWeeklys() .Strikes(-2, +2) .Expiration(TimeSpan.Zero, TimeSpan.FromDays(10))); // use the underlying equity as the benchmark SetBenchmark(equity.Symbol); } /// /// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event /// /// The current slice of data keyed by symbol string public override void OnData(Slice slice) { if (!Portfolio.Invested) { OptionChain chain; if (slice.OptionChains.TryGetValue(_optionSymbol, out chain)) { // check if data is consistent foreach (var o in chain) { if (!Securities.ContainsKey(o.Symbol)) { // inconsistency found: option chains contains contract information that is not available in securities manager and not available for trading throw new RegressionTestException("inconsistency found: option chains contains contract " + $"{o.Symbol.Value} that is not available in securities manager and not available for trading" ); } } // trade var contract = ( from optionContract in chain.OrderByDescending(x => x.Strike) where optionContract.Right == OptionRight.Call where optionContract.Expiry == Time.Date where optionContract.Strike < chain.Underlying.Price select optionContract ).Skip(2).FirstOrDefault(); if (contract != null) { MarketOrder(contract.Symbol, 1); MarketOnCloseOrder(contract.Symbol, -1); } } } } /// /// Order fill event handler. On an order fill update the resulting information is passed to this method. /// /// Order event details containing details of the events /// This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects public override void OnOrderEvent(OrderEvent orderEvent) { Log(orderEvent.ToString()); } /// /// 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 => 14325; /// /// Data Points count of the algorithm history /// public int AlgorithmHistoryDataPoints => 0; /// /// 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%"}, {"Compounding Annual Return", "0%"}, {"Drawdown", "0%"}, {"Expectancy", "0"}, {"Start Equity", "10000"}, {"End Equity", "9613"}, {"Net Profit", "0%"}, {"Sharpe Ratio", "0"}, {"Sortino Ratio", "0"}, {"Probabilistic Sharpe Ratio", "0%"}, {"Loss Rate", "0%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0"}, {"Beta", "0"}, {"Annual Standard Deviation", "0"}, {"Annual Variance", "0"}, {"Information Ratio", "0"}, {"Tracking Error", "0"}, {"Treynor Ratio", "0"}, {"Total Fees", "$2.00"}, {"Estimated Strategy Capacity", "$5000.00"}, {"Lowest Capacity Asset", "GOOCV W6NBKPFL0ACM|GOOCV VP83T1ZUHROL"}, {"Portfolio Turnover", "9.93%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "8887ac32d29175b21e40f335437cee61"} }; } }