chore: import upstream snapshot with attribution
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wehub-resource-sync
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/*
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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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*/
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Data.Market;
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using QuantConnect.Orders;
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using QuantConnect.Interfaces;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This example demonstrates how to add options for a given underlying equity security.
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/// It also shows how you can prefilter contracts easily based on strikes and expirations, and how you
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/// can inspect the option chain to pick a specific option contract to trade.
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="options" />
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/// <meta name="tag" content="filter selection" />
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public class BasicTemplateOptionsDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private const string UnderlyingTicker = "AAPL";
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private Symbol _optionSymbol;
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private bool _optionExpired;
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public override void Initialize()
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{
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SetStartDate(2015, 12, 15);
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SetEndDate(2016, 2, 1);
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SetCash(100000);
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var equity = AddEquity(UnderlyingTicker, Resolution.Daily);
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var option = AddOption(UnderlyingTicker, Resolution.Daily);
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_optionSymbol = option.Symbol;
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option.SetFilter(x => x.CallsOnly().Expiration(0, 60));
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// use the underlying equity as the benchmark
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SetBenchmark(equity.Symbol);
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}
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/// <summary>
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/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
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/// </summary>
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/// <param name="slice">The current slice of data keyed by symbol string</param>
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public override void OnData(Slice slice)
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{
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if (!Portfolio.Invested)
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{
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OptionChain chain;
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if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
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{
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// Grab us the contract nearest expiry that is not today
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var contractsByExpiration = chain.Where(x => x.Expiry != Time.Date).OrderBy(x => x.Expiry);
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var contract = contractsByExpiration.FirstOrDefault();
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if (contract != null)
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{
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// if found, trade it
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MarketOrder(contract.Symbol, 1);
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}
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}
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}
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}
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/// <summary>
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/// Order fill event handler. On an order fill update the resulting information is passed to this method.
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/// </summary>
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/// <param name="orderEvent">Order event details containing details of the events</param>
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/// <remarks>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</remarks>
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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Log(orderEvent.ToString());
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// Check for our expected OTM option expiry
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if (orderEvent.Message.Contains("OTM", StringComparison.InvariantCulture))
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{
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// Assert it is at midnight (5AM UTC)
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if (orderEvent.UtcTime != new DateTime(2016, 1, 16, 5, 0, 0))
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{
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throw new ArgumentException($"Expiry event was not at the correct time, {orderEvent.UtcTime}");
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}
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_optionExpired = true;
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}
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}
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public override void OnEndOfAlgorithm()
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{
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// Assert we had our option expire and fill a liquidation order
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if (_optionExpired != true)
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{
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throw new ArgumentException("Algorithm did not process the option expiration like expected");
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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, Language.Python };
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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 => 308;
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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 => 0;
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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", "2"},
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{"Average Win", "0%"},
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{"Average Loss", "-1.16%"},
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{"Compounding Annual Return", "-8.351%"},
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{"Drawdown", "1.200%"},
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{"Expectancy", "-1"},
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{"Start Equity", "100000"},
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{"End Equity", "98844"},
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{"Net Profit", "-1.156%"},
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{"Sharpe Ratio", "-4.04"},
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{"Sortino Ratio", "-2.422"},
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{"Probabilistic Sharpe Ratio", "0.008%"},
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{"Loss Rate", "100%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "-0.058"},
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{"Beta", "0.021"},
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{"Annual Standard Deviation", "0.017"},
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{"Annual Variance", "0"},
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{"Information Ratio", "1.49"},
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{"Tracking Error", "0.289"},
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{"Treynor Ratio", "-3.212"},
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{"Total Fees", "$1.00"},
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{"Estimated Strategy Capacity", "$72000.00"},
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{"Lowest Capacity Asset", "AAPL W78ZEO29CFS6|AAPL R735QTJ8XC9X"},
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{"Portfolio Turnover", "0.02%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "5639c19a7d56ec312f61029b943903b8"}
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};
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}
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}
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