/* * 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 example demonstrates how to add options for a given underlying equity security. /// It also shows how you can prefilter contracts easily based on strikes and expirations, and how you /// can inspect the option chain to pick a specific option contract to trade. /// /// /// /// public class BasicTemplateOptionsHourlyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private const string UnderlyingTicker = "AAPL"; private Symbol _optionSymbol; public override void Initialize() { SetStartDate(2014, 6, 6); SetEndDate(2014, 6, 9); SetCash(100000); var equity = AddEquity(UnderlyingTicker, Resolution.Hour); var option = AddOption(UnderlyingTicker, Resolution.Hour); _optionSymbol = option.Symbol; // set our strike/expiry filter for this option chain option.SetFilter(u => u.Strikes(-2, +2) // Expiration method accepts TimeSpan objects or integer for days. // The following statements yield the same filtering criteria .Expiration(0, 180)); // .Expiration(TimeSpan.Zero, TimeSpan.FromDays(180))); // 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 && IsMarketOpen(_optionSymbol)) { OptionChain chain; if (slice.OptionChains.TryGetValue(_optionSymbol, out chain)) { // we find at the money (ATM) put contract with farthest expiration var atmContract = chain .OrderByDescending(x => x.Expiry) .ThenBy(x => Math.Abs(chain.Underlying.Price - x.Strike)) .ThenByDescending(x => x.Right) .FirstOrDefault(); if (atmContract != null && IsMarketOpen(atmContract.Symbol)) { // if found, trade it MarketOrder(atmContract.Symbol, 1); MarketOnCloseOrder(atmContract.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 => 9504; /// /// 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", "5"}, {"Average Win", "0%"}, {"Average Loss", "-0.07%"}, {"Compounding Annual Return", "-11.517%"}, {"Drawdown", "0.200%"}, {"Expectancy", "-1"}, {"Start Equity", "100000"}, {"End Equity", "99866"}, {"Net Profit", "-0.134%"}, {"Sharpe Ratio", "-9.78"}, {"Sortino Ratio", "0"}, {"Probabilistic Sharpe Ratio", "0%"}, {"Loss Rate", "100%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0.075"}, {"Beta", "-0.054"}, {"Annual Standard Deviation", "0.008"}, {"Annual Variance", "0"}, {"Information Ratio", "-18.699"}, {"Tracking Error", "0.155"}, {"Treynor Ratio", "1.434"}, {"Total Fees", "$4.00"}, {"Estimated Strategy Capacity", "$1000.00"}, {"Lowest Capacity Asset", "AAPL 2ZTXYMUAHCIAU|AAPL R735QTJ8XC9X"}, {"Portfolio Turnover", "2.28%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "7804b3dcf20d3096a2265a289fa81cd3"} }; } }