/* * 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 NUnit.Framework; using QuantConnect.Statistics; using System.Collections.Generic; namespace QuantConnect.Tests.Common { [TestFixture] public class PythonSliceGetByTypeTests { [Test] public void RunPythonSliceGetByTypeRegressionAlgorithm() { var parameter = new RegressionTests.AlgorithmStatisticsTestParameters("SliceGetByTypeRegressionAlgorithm", new Dictionary { {PerformanceMetrics.TotalOrders, "1"}, {"Average Win", "0%"}, {"Average Loss", "0%"}, {"Compounding Annual Return", "284.284%"}, {"Drawdown", "2.200%"}, {"Expectancy", "0"}, {"Net Profit", "1.736%"}, {"Sharpe Ratio", "8.86"}, {"Probabilistic Sharpe Ratio", "67.609%"}, {"Loss Rate", "0%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "-0.004"}, {"Beta", "0.997"}, {"Annual Standard Deviation", "0.222"}, {"Annual Variance", "0.049"}, {"Information Ratio", "-14.547"}, {"Tracking Error", "0.001"}, {"Treynor Ratio", "1.972"}, {"Total Fees", "$3.45"}, {"OrderListHash", "275925e122dc6f40501d1e3f35339e26"} }, Language.Python, AlgorithmStatus.Completed); AlgorithmRunner.RunLocalBacktest(parameter.Algorithm, parameter.Statistics, parameter.Language, parameter.ExpectedFinalStatus); } } }