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.Linq;
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using QuantConnect.Data;
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using QuantConnect.Data.Market;
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using System.Collections.Generic;
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using QuantConnect.Securities.Option.StrategyMatcher;
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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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/// Regression algorithm exercising an equity Reverse Conversion option strategy and asserting it's being detected by Lean and works as expected
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/// </summary>
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public class OptionEquityReverseConversionRegressionAlgorithm : OptionEquityBaseStrategyRegressionAlgorithm
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{
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="slice">Slice object keyed by symbol containing the stock data</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 (IsMarketOpen(_optionSymbol) && slice.OptionChains.TryGetValue(_optionSymbol, out chain))
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{
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var contracts = chain
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.OrderByDescending(x => x.Expiry)
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.ThenBy(x => x.Strike)
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.ToList();
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var call = contracts.Last(contract => contract.Right == OptionRight.Call);
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var put = contracts.Single(contract => contract.Right == OptionRight.Put && contract.Expiry == call.Expiry
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&& contract.Strike == call.Strike);
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var underlying = call.Symbol.Underlying;
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var initialMargin = Portfolio.MarginRemaining;
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MarketOrder(underlying, -100);
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MarketOrder(call.Symbol, 1);
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MarketOrder(put.Symbol, -1);
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var freeMarginPostTrade = Portfolio.MarginRemaining;
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AssertOptionStrategyIsPresent(OptionStrategyDefinitions.ReverseConversion.Name, 1);
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var putInTheMoneyAmount = ((Option)Securities[put.Symbol]).GetIntrinsicValue(Securities[underlying].Price);
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var expectedMarginUsage = (putInTheMoneyAmount + 0.1m * call.Strike) * 100;
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if (expectedMarginUsage != Portfolio.TotalMarginUsed)
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{
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throw new RegressionTestException("Unexpect margin used!");
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}
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// we payed the ask and value using the assets price
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var priceSpreadDifference = GetPriceSpreadDifference(call.Symbol, put.Symbol, underlying);
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if (initialMargin != (freeMarginPostTrade + expectedMarginUsage + _paidFees - priceSpreadDifference))
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{
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throw new RegressionTestException("Unexpect margin remaining!");
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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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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public override long DataPoints => 15023;
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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 override 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 override 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", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Start Equity", "200000"},
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{"End Equity", "199801"},
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{"Net Profit", "0%"},
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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", "0%"},
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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", "0"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$3.00"},
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{"Estimated Strategy Capacity", "$7400000.00"},
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{"Lowest Capacity Asset", "GOOCV W78ZFMML4BUU|GOOCV VP83T1ZUHROL"},
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{"Portfolio Turnover", "38.84%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "5e0bf1da18d2ef159f3771de4bdcc4b9"}
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};
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}
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}
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