/* * 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.Interfaces; namespace QuantConnect.Algorithm.CSharp { /// /// Algorithm asserting the correct values for the deployment target and algorithm mode. /// public class AlgorithmModeAndDeploymentTargetAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { public override void Initialize() { SetStartDate(2013, 10, 07); SetEndDate(2013, 10, 07); SetCash(100000); Debug($"Algorithm Mode: {AlgorithmMode}. Is Live Mode: {LiveMode}. Deployment Target: {DeploymentTarget}."); if (AlgorithmMode != AlgorithmMode.Backtesting) { throw new RegressionTestException($"Algorithm mode is not backtesting. Actual: {AlgorithmMode}"); } if (LiveMode) { throw new RegressionTestException("Algorithm should not be live"); } if (DeploymentTarget != DeploymentTarget.LocalPlatform) { throw new RegressionTestException($"Algorithm deployment target is not local. Actual{DeploymentTarget}"); } // For a live deployment these checks should pass: //if (AlgorithmMode != AlgorithmMode.Live) throw new RegressionTestException("Algorithm mode is not live"); //if (!LiveMode) throw new RegressionTestException("Algorithm should be live"); // For a cloud deployment these checks should pass: //if (DeploymentTarget != DeploymentTarget.CloudPlatform) throw new RegressionTestException("Algorithm deployment target is not cloud"); Quit(); } /// /// 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, Language.Python }; /// /// Data Points count of all timeslices of algorithm /// public long DataPoints => 0; /// /// 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", "0"}, {"Average Win", "0%"}, {"Average Loss", "0%"}, {"Compounding Annual Return", "0%"}, {"Drawdown", "0%"}, {"Expectancy", "0"}, {"Start Equity", "100000"}, {"End Equity", "100000"}, {"Net Profit", "0%"}, {"Sharpe Ratio", "0"}, {"Sortino Ratio", "0"}, {"Probabilistic Sharpe Ratio", "0%"}, {"Loss Rate", "0%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0"}, {"Beta", "0"}, {"Annual Standard Deviation", "0"}, {"Annual Variance", "0"}, {"Information Ratio", "0"}, {"Tracking Error", "0"}, {"Treynor Ratio", "0"}, {"Total Fees", "$0.00"}, {"Estimated Strategy Capacity", "$0"}, {"Lowest Capacity Asset", ""}, {"Portfolio Turnover", "0%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"} }; } }