/* * 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.Data; using QuantConnect.Interfaces; using QuantConnect.Scheduling; namespace QuantConnect.Algorithm.CSharp { /// /// Regression algorithm which reproduces GH issue 4131, we assert order events are executed in order /// event outside market ours /// public class ScheduledEventsOrderRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private int _scheduledEventCount; private int _afterMarketOpenEventCount; private Symbol _spy; private DateTime _lastTime = DateTime.MinValue; /// /// 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, 11); _spy = AddEquity("SPY").Symbol; var test = 0; var dateRule = DateRules.EveryDay(_spy); var aEventCount = 0; var bEventCount = 0; var cEventCount = 0; var symbol = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA); Schedule.On(DateRules.WeekStart(symbol), TimeRules.AfterMarketOpen(symbol), AfterMarketOpen); // we add each twice and assert the order in which they are added is also respected for events at the same time for (var i = 0; i < 2; i++) { var id = i; Schedule.On(dateRule, TimeRules.At(9, 25), (name, time) => { // for id 0 event count should always be 0, for id 1 should be 1 if (aEventCount != id) { throw new RegressionTestException($"Scheduled event triggered out of order: {Time} expected id {id} but was {aEventCount}"); } aEventCount++; // goes from 0 to 1 aEventCount %= 2; AssertScheduledEventTime(); Debug($"{Time} :: Test: {test}"); test++; }); Schedule.On(dateRule, TimeRules.BeforeMarketClose(_spy, 5), (name, time) => { // for id 0 event count should always be 0, for id 1 should be 1 if (bEventCount != id) { throw new RegressionTestException($"Scheduled event triggered out of order: {Time} expected id {id} but was {bEventCount}"); } bEventCount++; // goes from 0 to 1 bEventCount %= 2; AssertScheduledEventTime(); Debug($"{Time} :: Test: {test}"); test++; }); Schedule.On(dateRule, TimeRules.At(16, 5), (name, time) => { // for id 0 event count should always be 0, for id 1 should be 1 if (cEventCount != id) { throw new RegressionTestException($"Scheduled event triggered out of order: {Time} expected id {id} but was {cEventCount}"); } cEventCount++; // goes from 0 to 1 cEventCount %= 2; AssertScheduledEventTime(); Debug($"{Time} :: Test: {test}"); test = 0; }); } } private void AssertScheduledEventTime() { if (_lastTime > Time) { throw new RegressionTestException($"Scheduled event time shouldn't go backwards, last time {_lastTime}, current {Time}"); } _lastTime = Time; _scheduledEventCount++; } private void AfterMarketOpen() { _afterMarketOpenEventCount++; if (Time.TimeOfDay != TimeSpan.FromHours(9.5)) { throw new RegressionTestException($"AfterMarketOpen unexpected event time: {Time}"); } } public override void OnEndOfAlgorithm() { if (_scheduledEventCount != 28) { throw new RegressionTestException($"OnEndOfAlgorithm expected scheduled events but was {_scheduledEventCount}"); } if (_afterMarketOpenEventCount != 1) { throw new RegressionTestException($"OnEndOfAlgorithm expected after MarketOpenEvent count {_afterMarketOpenEventCount}"); } } /// /// 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); } } /// /// 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 => 3943; /// /// 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", "271.453%"}, {"Drawdown", "2.200%"}, {"Expectancy", "0"}, {"Start Equity", "100000"}, {"End Equity", "101691.92"}, {"Net Profit", "1.692%"}, {"Sharpe Ratio", "8.854"}, {"Sortino Ratio", "0"}, {"Probabilistic Sharpe Ratio", "67.609%"}, {"Loss Rate", "0%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "-0.005"}, {"Beta", "0.996"}, {"Annual Standard Deviation", "0.222"}, {"Annual Variance", "0.049"}, {"Information Ratio", "-14.565"}, {"Tracking Error", "0.001"}, {"Treynor Ratio", "1.97"}, {"Total Fees", "$3.44"}, {"Estimated Strategy Capacity", "$56000000.00"}, {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"}, {"Portfolio Turnover", "19.93%"}, {"Drawdown Recovery", "3"}, {"OrderListHash", "3da9fa60bf95b9ed148b95e02e0cfc9e"} }; } }