/* * 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.Risk; using QuantConnect.Algorithm.Framework.Selection; using QuantConnect.Interfaces; using QuantConnect.Securities; namespace QuantConnect.Algorithm.CSharp { /// /// Basic template futures framework algorithm uses framework components to define an algorithm /// that trades futures. /// public class BasicTemplateFuturesFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { public override void Initialize() { UniverseSettings.Resolution = Resolution.Minute; SetStartDate(2013, 10, 07); SetEndDate(2013, 10, 11); SetCash(100000); // set framework models SetUniverseSelection(new FrontMonthFutureUniverseSelectionModel(SelectFutureChainSymbols)); SetAlpha(new ConstantFutureContractAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(1))); SetPortfolioConstruction(new SingleSharePortfolioConstructionModel()); SetExecution(new ImmediateExecutionModel()); SetRiskManagement(new NullRiskManagementModel()); } // future symbol universe selection function private static IEnumerable SelectFutureChainSymbols(DateTime utcTime) { var newYorkTime = utcTime.ConvertFromUtc(TimeZones.NewYork); if (newYorkTime.Date < new DateTime(2013, 10, 09)) { yield return QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.USA); } if (newYorkTime.Date >= new DateTime(2013, 10, 09)) { yield return QuantConnect.Symbol.Create(Futures.Metals.Gold, SecurityType.Future, Market.USA); } } /// /// 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); } } /// /// Portfolio construction model that sets target quantities to 1 for up insights and -1 for down insights /// class SingleSharePortfolioConstructionModel : PortfolioConstructionModel { public override IEnumerable CreateTargets(QCAlgorithm algorithm, Insight[] insights) { foreach (var insight in insights) { yield return new PortfolioTarget(insight.Symbol, (int) insight.Direction); } } } /// /// 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 Language[] Languages { get; } = { Language.CSharp, Language.Python }; /// /// 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 Trades", "2"}, {"Average Win", "0%"}, {"Average Loss", "0%"}, {"Compounding Annual Return", "-92.656%"}, {"Drawdown", "5.000%"}, {"Expectancy", "0"}, {"Net Profit", "-3.312%"}, {"Sharpe Ratio", "-16.986"}, {"Loss Rate", "0%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "-0.828"}, {"Beta", "-77.873"}, {"Annual Standard Deviation", "0.099"}, {"Annual Variance", "0.01"}, {"Information Ratio", "-17.076"}, {"Tracking Error", "0.099"}, {"Treynor Ratio", "0.022"}, {"Total Fees", "$3.70"}, {"Total Insights Generated", "6"}, {"Total Insights Closed", "5"}, {"Total Insights Analysis Completed", "5"}, {"Long Insight Count", "6"}, {"Short Insight Count", "0"}, {"Long/Short Ratio", "100%"}, {"Estimated Monthly Alpha Value", "$-96.12923"}, {"Total Accumulated Estimated Alpha Value", "$-15.621"}, {"Mean Population Estimated Insight Value", "$-3.1242"}, {"Mean Population Direction", "0%"}, {"Mean Population Magnitude", "0%"}, {"Rolling Averaged Population Direction", "0%"}, {"Rolling Averaged Population Magnitude", "0%"} }; } }