Overall Statistics |
Total Trades 1874 Average Win 0.23% Average Loss -0.24% Compounding Annual Return -0.313% Drawdown 10.400% Expectancy -0.011 Net Profit -3.073% Sharpe Ratio -0.056 Probabilistic Sharpe Ratio 0.003% Loss Rate 50% Win Rate 50% Profit-Loss Ratio 0.98 Alpha -0.001 Beta -0.004 Annual Standard Deviation 0.03 Annual Variance 0.001 Information Ratio -0.661 Tracking Error 0.148 Treynor Ratio 0.464 Total Fees $4196.30 Estimated Strategy Capacity $120000000.00 Lowest Capacity Asset SPY R735QTJ8XC9X |
/* * 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 QuantConnect.Algorithm.Framework.Alphas; using QuantConnect.Algorithm.Framework.Portfolio; using QuantConnect.Algorithm.Framework.Selection; using RiskLibrary; namespace QuantConnect.Algorithm.CSharp { /// <summary> /// Framework algorithm that uses the <see cref="EmaCrossUniverseSelectionModel"/> to /// select the universe based on a moving average cross. /// </summary> public class EmaCrossUniverseSelectionFrameworkAlgorithm : QCAlgorithm { public override void Initialize() { SetStartDate(2013, 01, 01); SetCash(100000); var fastSMAPeriod = 20; var slowSMAPeriod= 60; Resolution resolution = Resolution.Hour; UniverseSettings.Leverage = 2.0m; UniverseSettings.Resolution = resolution; SetUniverseSelection(new ManualUniverseSelectionModel(QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA))); SetAlpha(new EmaCrossAlphaModel(fastSMAPeriod,slowSMAPeriod,resolution)); SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel()); AddRiskManagement(new ATRTrailingStopRiskManagementModel(20,3,resolution)); } } }