/* * 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.Linq; using QuantConnect.Data; using QuantConnect.Interfaces; using System.Collections.Generic; namespace QuantConnect.Algorithm.CSharp { /// /// Regression algorithm testing doing some history requests outside market hours, reproducing GH issue #4783 /// public class ExtendedMarketHoursHistoryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private int _minuteHistoryCount; private int _hourHistoryCount; private int _dailyHistoryCount; /// /// 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(2013, 10, 07); SetEndDate(2013, 10, 09); SetCash(100000); AddEquity("SPY", Resolution.Minute, extendedMarketHours:true, fillForward:false); Schedule.On("RunHistoryCall", DateRules.EveryDay(), TimeRules.Every(TimeSpan.FromHours(1)), RunHistoryCall); } private void RunHistoryCall() { var spy = Securities["SPY"]; var regularHours = spy.Exchange.Hours.IsOpen(Time, false); var extendedHours = !regularHours && spy.Exchange.Hours.IsOpen(Time, true); if (regularHours) { _minuteHistoryCount++; var history = History(spy.Symbol, 5, Resolution.Minute).Count(); if (history != 5) { throw new RegressionTestException($"Unexpected Minute data count: {history}"); } } else { if (extendedHours) { _hourHistoryCount++; var history = History(spy.Symbol, 5, Resolution.Hour).Count(); if (history != 5) { throw new RegressionTestException($"Unexpected Hour data count {history}"); } } else { _dailyHistoryCount++; var history = History(spy.Symbol, 5, Resolution.Daily).Count(); if (history != 5) { throw new RegressionTestException($"Unexpected Daily data count {history}"); } } } } /// /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. /// /// Slice object keyed by symbol containing the stock data public override void OnData(Slice slice) { if (!Portfolio.Invested) { SetHoldings("SPY", 1); } } public override void OnEndOfAlgorithm() { if (_minuteHistoryCount != 3 * 6) { throw new RegressionTestException($"Unexpected minute history requests count {_minuteHistoryCount}"); } // 6 pre market from 4am to 9am + 4 post market 4pm to 7pm if (_hourHistoryCount != 3 * 10) { throw new RegressionTestException($"Unexpected hour history requests count {_hourHistoryCount}"); } // 0am to 3am + 8pm to 11pm, last day ends at 8pm if (_dailyHistoryCount != (2 * 8 + 5)) { throw new RegressionTestException($"Unexpected Daily history requests count: {_dailyHistoryCount}"); } } /// /// 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 => 5215; /// /// Data Points count of the algorithm history /// public int AlgorithmHistoryDataPoints => 435; /// /// 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", "19"}, {"Average Win", "0%"}, {"Average Loss", "0.00%"}, {"Compounding Annual Return", "-73.997%"}, {"Drawdown", "2.500%"}, {"Expectancy", "-1"}, {"Start Equity", "100000"}, {"End Equity", "98959.88"}, {"Net Profit", "-1.040%"}, {"Sharpe Ratio", "-9.402"}, {"Sortino Ratio", "-9.402"}, {"Probabilistic Sharpe Ratio", "0%"}, {"Loss Rate", "100%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "-0.286"}, {"Beta", "0.55"}, {"Annual Standard Deviation", "0.075"}, {"Annual Variance", "0.006"}, {"Information Ratio", "0.914"}, {"Tracking Error", "0.061"}, {"Treynor Ratio", "-1.28"}, {"Total Fees", "$21.45"}, {"Estimated Strategy Capacity", "$830000.00"}, {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"}, {"Portfolio Turnover", "34.15%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "6ebe462373e2ecc22de8eb2fe114d704"} }; } }