chore: import upstream snapshot with attribution
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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 is an option split regression algorithm
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/// </summary>
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/// <meta name="tag" content="regression test" />
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/// <meta name="tag" content="options" />
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public class OptionSplitRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _optionSymbol;
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public override void Initialize()
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{
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// this test opens position in the first day of trading, lives through stock split (7 for 1), and closes adjusted position on the second day
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SetStartDate(2014, 06, 06);
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SetEndDate(2014, 06, 09);
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SetCash(1000000);
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var option = AddOption("AAPL");
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_optionSymbol = option.Symbol;
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// set our strike/expiry filter for this option chain
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option.SetFilter(u => u.IncludeWeeklys()
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.Strikes(-2, +2)
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.Expiration(TimeSpan.Zero, TimeSpan.FromDays(365 * 2)));
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// use the underlying equity as the benchmark
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SetBenchmark("AAPL");
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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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if (Time.Hour > 9 && Time.Minute > 0)
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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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var contract =
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chain.OrderBy(x => x.Expiry)
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.Where(x => x.Right == OptionRight.Call && x.Strike == 650)
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.Skip(1)
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.FirstOrDefault();
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if (contract != null)
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{
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Buy(contract.Symbol, 1);
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}
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}
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}
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}
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else
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{
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if (Time.Day > 6 && Time.Hour > 14 && Time.Minute > 0)
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{
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Liquidate();
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}
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}
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if (Portfolio.Invested)
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{
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var holdings = Portfolio.Securities.Where(x => x.Value.Holdings.AbsoluteQuantity != 0).First().Value.Holdings.AbsoluteQuantity;
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if (Time.Day == 6 && holdings != 1)
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{
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throw new RegressionTestException($"Expected position quantity of 1 but was {holdings.ToStringInvariant()}");
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}
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if (Time.Day == 9 && holdings != 7)
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{
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throw new RegressionTestException($"Expected position quantity of 7 but was {holdings.ToStringInvariant()}");
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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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}
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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 => 124202;
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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", "-0.02%"},
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{"Compounding Annual Return", "-1.512%"},
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{"Drawdown", "0.000%"},
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{"Expectancy", "-1"},
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{"Start Equity", "1000000"},
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{"End Equity", "999833"},
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{"Net Profit", "-0.017%"},
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{"Sharpe Ratio", "0"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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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"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-19.236"},
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{"Tracking Error", "0.147"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$2.00"},
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{"Estimated Strategy Capacity", "$88000.00"},
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{"Lowest Capacity Asset", "AAPL VRCWOCTRVDJA|AAPL R735QTJ8XC9X"},
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{"Portfolio Turnover", "0.04%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "6753be1c117f9528f920eb84976a070f"}
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};
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}
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}
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