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.Market;
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using QuantConnect.Securities.Option;
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using QuantConnect.Securities.Positions;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This algorithm demonstrate how to use OptionStrategies helper class to batch send orders for common strategies.
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/// In this case, the algorithm tests the Butterfly Call and Short Butterfly Call strategies.
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/// </summary>
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public class LongAndShortButterflyCallStrategiesAlgorithm : OptionStrategyFactoryMethodsBaseAlgorithm
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{
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protected override int ExpectedOrdersCount { get; } = 6;
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private OptionStrategy _butterflyCall;
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private OptionStrategy _shortButterflyCall;
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protected override void TradeStrategy(OptionChain chain)
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{
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var contractsByExpiry = chain.Where(x => x.Right == OptionRight.Call).GroupBy(x => x.Expiry);
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foreach (var group in contractsByExpiry)
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{
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var expiry = group.Key;
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var contracts = group.ToList();
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if (contracts.Count < 3)
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{
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continue;
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}
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var strikes = contracts.Select(x => x.Strike).OrderBy(x => x).ToArray();
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var atmStrike = contracts.MinBy(x => Math.Abs(x.Strike - chain.Underlying.Value)).Strike;
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var spread = Math.Min(atmStrike - strikes[0], strikes[^1] - atmStrike);
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var itmStrike = atmStrike - spread;
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var otmStrike = atmStrike + spread;
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if (strikes.Contains(otmStrike) && strikes.Contains(itmStrike))
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{
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// Ready to trade
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_butterflyCall = OptionStrategies.ButterflyCall(_optionSymbol, otmStrike, atmStrike, itmStrike, expiry);
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_shortButterflyCall = OptionStrategies.ShortButterflyCall(_optionSymbol, otmStrike, atmStrike, itmStrike, expiry);
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Buy(_butterflyCall, 2);
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break;
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}
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}
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}
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protected override void AssertStrategyPositionGroup(IPositionGroup positionGroup)
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{
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if (positionGroup.Positions.Count() != 3)
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{
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throw new RegressionTestException($"Expected position group to have 3 positions. Actual: {positionGroup.Positions.Count()}");
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}
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var higherStrike = _butterflyCall.OptionLegs.Max(leg => leg.Strike);
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var higherStrikePosition = positionGroup.Positions
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.Single(x => x.Symbol.ID.OptionRight == OptionRight.Call && x.Symbol.ID.StrikePrice == higherStrike);
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if (higherStrikePosition.Quantity != 2)
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{
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throw new RegressionTestException($"Expected higher strike position quantity to be 2. Actual: {higherStrikePosition.Quantity}");
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}
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var lowerStrike = _butterflyCall.OptionLegs.Min(leg => leg.Strike);
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var lowerStrikePosition = positionGroup.Positions
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.Single(x => x.Symbol.ID.OptionRight == OptionRight.Call && x.Symbol.ID.StrikePrice == lowerStrike);
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if (lowerStrikePosition.Quantity != 2)
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{
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throw new RegressionTestException($"Expected lower strike position quantity to be 2. Actual: {lowerStrikePosition.Quantity}");
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}
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var middleStrike = _butterflyCall.OptionLegs.Single(leg => leg.Strike < higherStrike && leg.Strike > lowerStrike).Strike;
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var middleStrikePosition = positionGroup.Positions
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.Single(x => x.Symbol.ID.OptionRight == OptionRight.Call && x.Symbol.ID.StrikePrice == middleStrike);
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if (middleStrikePosition.Quantity != -4)
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{
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throw new RegressionTestException($"Expected middle strike position quantity to be -4. Actual: {middleStrikePosition.Quantity}");
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}
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}
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protected override void LiquidateStrategy()
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{
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// We should be able to close the position using the inverse strategy (a short butterfly call)
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Buy(_shortButterflyCall, 2);
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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 override 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 override 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 override long DataPoints => 2298;
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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", "6"},
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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", "1000000"},
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{"End Equity", "999229.6"},
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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", "$10.40"},
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{"Estimated Strategy Capacity", "$7000.00"},
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{"Lowest Capacity Asset", "GOOCV W78ZFMEBFLDY|GOOCV VP83T1ZUHROL"},
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{"Portfolio Turnover", "2.17%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "819b008b902a1a0013646a12d31f4ae4"}
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};
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}
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}
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