/* * 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 System.Linq; using QuantConnect.Data; using QuantConnect.Interfaces; namespace QuantConnect.Algorithm.CSharp { /// /// Regression test algorithm simply fetch and compare data of minute resolution around daylight saving period /// reproduces issue reported in GB issue GH issue https://github.com/QuantConnect/Lean/issues/4925 /// related issues https://github.com/QuantConnect/Lean/issues/3707; https://github.com/QuantConnect/Lean/issues/4630 /// public class FillForwardEnumeratorOutOfOrderBarRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private decimal _exptectedClose = 84.09m; private DateTime _exptectedTime = new DateTime(2008, 3, 10, 9, 30, 0); private Symbol _shy; /// /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized. /// public override void Initialize() { SetStartDate(2008, 3, 7); SetEndDate(2008, 3, 10); _shy = AddEquity("SHY", Resolution.Minute).Symbol; // just to make debugging easier, less subscriptions SetBenchmark(time => 1); } public override void OnData(Slice slice) { var trackingBar = slice.Bars.Values.FirstOrDefault(s => s.Time.Equals(_exptectedTime)); if (trackingBar != null) { if (!Portfolio.Invested) { SetHoldings(_shy, 1); } if (trackingBar.Close != _exptectedClose) { throw new RegressionTestException( $"Bar at {_exptectedTime.ToStringInvariant()} closed at price {trackingBar.Close.ToStringInvariant()}; expected {_exptectedClose.ToStringInvariant()}"); } } } /// /// 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 => 1561; /// /// 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", "1"}, {"Average Win", "0%"}, {"Average Loss", "0%"}, {"Compounding Annual Return", "16.086%"}, {"Drawdown", "0.100%"}, {"Expectancy", "0"}, {"Start Equity", "100000"}, {"End Equity", "100148.25"}, {"Net Profit", "0.148%"}, {"Sharpe Ratio", "7.182"}, {"Sortino Ratio", "0"}, {"Probabilistic Sharpe Ratio", "0%"}, {"Loss Rate", "0%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0"}, {"Beta", "0"}, {"Annual Standard Deviation", "0.014"}, {"Annual Variance", "0"}, {"Information Ratio", "9.758"}, {"Tracking Error", "0.014"}, {"Treynor Ratio", "0"}, {"Total Fees", "$5.93"}, {"Estimated Strategy Capacity", "$150000.00"}, {"Lowest Capacity Asset", "SHY 2T"}, {"Portfolio Turnover", "24.91%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "9d00701591b363edda102536ec5e75e0"} }; } }