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.Collections.Generic;
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using QuantConnect.Algorithm.Framework.Portfolio.SignalExports;
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using QuantConnect.Data;
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using QuantConnect.Indicators;
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using QuantConnect.Interfaces;
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namespace QuantConnect.Algorithm.CSharp.RegressionTests
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{
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public class Collective2IndexOptionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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/// <summary>
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/// Collective2 APIv4 KEY: This value is provided by Collective2 in your account section (See https://collective2.com/account-info)
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/// See API documentation at https://trade.collective2.com/c2-api
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/// </summary>
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private const string _collective2ApiKey = "YOUR APIV4 KEY";
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/// <summary>
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/// Collective2 System ID: This value is found beside the system's name (strategy's name) on the main system page
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/// </summary>
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private const int _collective2SystemId = 0;
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private ExponentialMovingAverage _fast;
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private ExponentialMovingAverage _slow;
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private Symbol _symbol;
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private bool _firstCall = true;
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public override void Initialize()
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{
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SetStartDate(2021, 1, 4);
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SetEndDate(2021, 1, 18);
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SetCash(100000);
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var underlying = AddIndex("SPX", Resolution.Minute).Symbol;
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// Create an SPXW option contract with a specific strike price and expiration date
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var option = QuantConnect.Symbol.CreateOption(
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underlying,
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"SPXW",
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Market.USA,
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OptionStyle.European,
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OptionRight.Call,
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3800m,
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new DateTime(2021, 1, 04));
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_symbol = AddIndexOptionContract(option, Resolution.Minute).Symbol;
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_fast = EMA(underlying, 10, Resolution.Minute);
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_slow = EMA(underlying, 50, Resolution.Minute);
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// Disable automatic exports as we manually set them
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SignalExport.AutomaticExportTimeSpan = null;
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// Set up the Collective2 Signal Export with the provided API key and system ID
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SignalExport.AddSignalExportProvider(new Collective2SignalExport(_collective2ApiKey, _collective2SystemId));
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// Set warm-up period for the indicators
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SetWarmUp(50);
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}
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public override void OnData(Slice slice)
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{
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// Execute only on the first data call to set initial portfolio
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if (_firstCall)
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{
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SetHoldings(_symbol, 0.1);
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SignalExport.SetTargetPortfolioFromPortfolio();
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_firstCall = false;
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}
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// If the fast EMA crosses above the slow EMA, open a long position
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if (_fast > _slow && !Portfolio.Invested)
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{
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MarketOrder(_symbol, 1);
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SignalExport.SetTargetPortfolioFromPortfolio();
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}
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// If the fast EMA crosses below the slow EMA, open a short position
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else if (_fast < _slow && Portfolio.Invested)
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{
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MarketOrder(_symbol, -1);
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SignalExport.SetTargetPortfolioFromPortfolio();
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}
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}
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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 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 };
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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 => 4544;
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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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/// 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", "55"},
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{"Average Win", "0%"},
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{"Average Loss", "-0.01%"},
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{"Compounding Annual Return", "-0.468%"},
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{"Drawdown", "0.000%"},
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{"Expectancy", "-1"},
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{"Start Equity", "100000"},
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{"End Equity", "99985"},
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{"Net Profit", "-0.015%"},
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{"Sharpe Ratio", "-15.229"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0.000%"},
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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", "-0.003"},
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{"Beta", "-0.001"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-5.216"},
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{"Tracking Error", "0.103"},
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{"Treynor Ratio", "5.946"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$20000.00"},
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{"Lowest Capacity Asset", "SPXW XKX6S2GMDZSE|SPX 31"},
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{"Portfolio Turnover", "0.00%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "a15fe0e8fc66f7d6a83433525c33a2c1"}
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};
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}
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}
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