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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using System;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Orders;
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using QuantConnect.Interfaces;
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using QuantConnect.Securities;
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using System.Collections.Generic;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This regression algorithm tests using FutureOptions daily resolution
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/// </summary>
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public class FutureOptionDailyRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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protected OrderTicket Ticket { get; set; }
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protected Symbol ESOption { get; set; }
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protected virtual Resolution Resolution => Resolution.Daily;
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protected virtual DateTime StartDate => new DateTime(2020, 1, 6);
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protected virtual DateTime EndDate => new DateTime(2020, 1, 8);
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public override void Initialize()
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{
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SetStartDate(StartDate);
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SetEndDate(EndDate);
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// Add our underlying future contract
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var futureContract = AddFutureContract(
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QuantConnect.Symbol.CreateFuture(
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Futures.Indices.SP500EMini,
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Market.CME,
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new DateTime(2020, 3, 20)),
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Resolution).Symbol;
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// Attempt to fetch a specific future option contract
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ESOption = OptionChain(futureContract)
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.Where(x => x.ID.StrikePrice == 3200m && x.ID.OptionRight == OptionRight.Call)
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.Select(x => AddFutureOptionContract(x, Resolution).Symbol)
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.FirstOrDefault();
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// Validate it is the expected contract
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var expectedContract = QuantConnect.Symbol.CreateOption(futureContract, Market.CME, OptionStyle.American,
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OptionRight.Call, 3200m,
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new DateTime(2020, 3, 20));
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if (ESOption != expectedContract)
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{
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throw new RegressionTestException($"Contract {ESOption} was not the expected contract {expectedContract}");
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}
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ScheduleBuySell();
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}
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protected virtual void ScheduleBuySell()
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{
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// On daily resolution the order fills at the daily close, so a same-day buy + liquidate cannot work
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// (the buy would not fill until after the liquidation). Buy on the first day with available data and
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// liquidate the next day, once the purchase has filled at the previous close.
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Schedule.On(DateRules.On(2020, 1, 7), TimeRules.At(10, 0, 0), () =>
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{
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Ticket = MarketOrder(ESOption, 1);
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});
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Schedule.On(DateRules.On(2020, 1, 8), TimeRules.At(14, 0, 0), () =>
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{
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Liquidate();
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});
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}
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public override void OnData(Slice slice)
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{
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// Assert we are only getting data at 5PM NY, for ES future market closes at 17pm NY
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if (slice.Time.Hour != 17)
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{
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throw new ArgumentException($"Expected data at 4PM each day; instead was {slice.Time}");
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}
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}
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/// <summary>
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/// Ran at the end of the algorithm to ensure the algorithm has no holdings
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/// </summary>
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/// <exception cref="RegressionTestException">The algorithm has holdings</exception>
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public override void OnEndOfAlgorithm()
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{
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if (Portfolio.Invested)
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{
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throw new RegressionTestException($"Expected no holdings at end of algorithm, but are invested in: {string.Join(", ", Portfolio.Keys)}");
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}
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if (Ticket.Status != OrderStatus.Filled)
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{
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throw new RegressionTestException("Future option order failed to fill correctly");
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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 virtual 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 virtual 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 virtual long DataPoints => 36;
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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 virtual int AlgorithmHistoryDataPoints => 1;
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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 virtual 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", "1.50%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "640.945%"},
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{"Drawdown", "0.000%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "101497.16"},
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{"Net Profit", "1.497%"},
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{"Sharpe Ratio", "32.826"},
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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", "100%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "4.881"},
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{"Beta", "1.842"},
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{"Annual Standard Deviation", "0.168"},
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{"Annual Variance", "0.028"},
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{"Information Ratio", "67.238"},
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{"Tracking Error", "0.077"},
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{"Treynor Ratio", "3"},
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{"Total Fees", "$2.84"},
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{"Estimated Strategy Capacity", "$66000.00"},
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{"Lowest Capacity Asset", "ES XCZJLCEYO5XG|ES XCZJLC9NOB29"},
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{"Portfolio Turnover", "3.30%"},
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{"Drawdown Recovery", "1"},
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{"OrderListHash", "ca2b881524d4b9307e19a4f84ab4f5d7"}
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};
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}
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}
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