wehub-resource-sync
129 lines
4.8 KiB
C#
129 lines
4.8 KiB
C#
/*
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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.Interfaces;
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using QuantConnect.Securities;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm illustrating the usage of the <see cref="QCAlgorithm.OptionChain(Symbol)"/> method
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/// to get a future option chain.
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/// </summary>
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public class FutureOptionChainFullDataRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _optionContract;
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public override void Initialize()
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{
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SetStartDate(2020, 1, 6);
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SetEndDate(2020, 1, 6);
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var futureContract = AddFutureContract(
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QuantConnect.Symbol.CreateFuture(Futures.Indices.SP500EMini, Market.CME, new DateTime(2020, 3, 20)),
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Resolution.Minute).Symbol;
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_optionContract = OptionChain(futureContract)
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// Get contracts expiring within 4 months
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.Where(contractData => contractData.Expiry - Time <= TimeSpan.FromDays(120))
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// Get the contract with the latest expiration date, highest strike and lowest price
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.OrderByDescending(x => x.Expiry)
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.ThenByDescending(x => x.Strike)
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.ThenBy(x => x.LastPrice)
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.First();
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AddFutureOptionContract(_optionContract);
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}
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public override void OnData(Slice slice)
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{
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// Do some trading with the selected contract for sample purposes
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if (!Portfolio.Invested)
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{
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SetHoldings(_optionContract, 0.5);
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}
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else
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{
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Liquidate();
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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 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 long DataPoints => 1817;
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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 => 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 Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "304"},
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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", "100000"},
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{"End Equity", "75031.84"},
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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", "$25095.66"},
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{"Estimated Strategy Capacity", "$0"},
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{"Lowest Capacity Asset", "ES XCZJLCGM7IF8|ES XCZJLC9NOB29"},
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{"Portfolio Turnover", "76.32%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "1e039ca8743895c1c57d53138cb06ae4"}
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};
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}
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}
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