/* * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ using System; using System.Collections.Generic; using QuantConnect.Algorithm.Framework.Alphas; using QuantConnect.Algorithm.Framework.Execution; using QuantConnect.Algorithm.Framework.Portfolio; using QuantConnect.Algorithm.Framework.Selection; using QuantConnect.Interfaces; using QuantConnect.Orders; using QuantConnect.Securities; namespace QuantConnect.Algorithm.CSharp { /// /// Futures regression algorithm intended to test the behavior of the framework models. See GH issue 4027. /// public class EqualWeightingPortfolioConstructionModelFutureRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private int _fillCount; public override void Initialize() { SetStartDate(2013, 10, 07); SetEndDate(2013, 10, 11); SetUniverseSelection(new FrontMonthFutureUniverseSelectionModel(SelectFutureChainSymbols)); SetAlpha(new ConstantFutureContractAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(1))); SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel()); SetExecution(new ImmediateExecutionModel()); // Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees. // Commented so regression algorithm is more sensitive //Settings.MinimumOrderMarginPortfolioPercentage = 0.005m; } // future symbol universe selection function private static IEnumerable SelectFutureChainSymbols(DateTime utcTime) { return new [] { QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME), QuantConnect.Symbol.Create(Futures.Metals.Gold, SecurityType.Future, Market.COMEX) }; } /// /// Creates futures chain universes that select the front month contract and runs a user /// defined futureChainSymbolSelector every day to enable choosing different futures chains /// class FrontMonthFutureUniverseSelectionModel : FutureUniverseSelectionModel { public FrontMonthFutureUniverseSelectionModel(Func> futureChainSymbolSelector) : base(TimeSpan.FromDays(1), futureChainSymbolSelector) { } /// /// Defines the future chain universe filter /// protected override FutureFilterUniverse Filter(FutureFilterUniverse filter) { return filter .FrontMonth() .OnlyApplyFilterAtMarketOpen(); } } /// /// Implementation of a constant alpha model that only emits insights for future symbols /// class ConstantFutureContractAlphaModel : ConstantAlphaModel { public ConstantFutureContractAlphaModel(InsightType type, InsightDirection direction, TimeSpan period) : base(type, direction, period) { } protected override bool ShouldEmitInsight(DateTime utcTime, Symbol symbol) { // only emit alpha for future symbols and not underlying equity symbols if (symbol.SecurityType != SecurityType.Future) { return false; } return base.ShouldEmitInsight(utcTime, symbol); } } public override void OnOrderEvent(OrderEvent orderEvent) { Log($"{orderEvent}"); if (orderEvent.Status == OrderStatus.Filled) { _fillCount++; if (_fillCount == 2) { if (Portfolio.TotalHoldingsValue / Portfolio.TotalPortfolioValue < 10) { throw new RegressionTestException("Expected to be trading using the futures margin leverage"); } } } } /// /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm. /// public bool CanRunLocally { get; } = true; /// /// This is used by the regression test system to indicate which languages this algorithm is written in. /// public List Languages { get; } = new() { Language.CSharp }; /// /// Data Points count of all timeslices of algorithm /// public long DataPoints => 36213; /// /// Data Points count of the algorithm history /// public int AlgorithmHistoryDataPoints => 0; /// /// Final status of the algorithm /// public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed; /// /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm /// public Dictionary ExpectedStatistics => new Dictionary { {"Total Orders", "8"}, {"Average Win", "0.69%"}, {"Average Loss", "-2.47%"}, {"Compounding Annual Return", "-99.946%"}, {"Drawdown", "28.600%"}, {"Expectancy", "-0.680"}, {"Start Equity", "100000"}, {"End Equity", "90213.76"}, {"Net Profit", "-9.786%"}, {"Sharpe Ratio", "-0.603"}, {"Sortino Ratio", "-0.892"}, {"Probabilistic Sharpe Ratio", "30.082%"}, {"Loss Rate", "75%"}, {"Win Rate", "25%"}, {"Profit-Loss Ratio", "0.28"}, {"Alpha", "-15.818"}, {"Beta", "7.498"}, {"Annual Standard Deviation", "1.669"}, {"Annual Variance", "2.787"}, {"Information Ratio", "-2.061"}, {"Tracking Error", "1.447"}, {"Treynor Ratio", "-0.134"}, {"Total Fees", "$52.01"}, {"Estimated Strategy Capacity", "$1800000.00"}, {"Lowest Capacity Asset", "GC VL5E74HP3EE5"}, {"Portfolio Turnover", "475.60%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "91aeb0d6f6a18df9fd755fc473183395"} }; } }