/* * 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.UniverseSelection; using QuantConnect.Interfaces; using QuantConnect.Securities; namespace QuantConnect.Algorithm.CSharp { /// /// Regression algorithm testing the behavior of the algorithm when a security is removed and re-added. /// It asserts that the securities are marked as non-tradable when removed and that they are tradable when re-added. /// It also asserts that the algorithm receives the correct security changed events for the added and removed securities. /// /// Additionally, it tests that the security is initialized after every addition, and no more. /// /// This specific algorithm tests this behavior for securities selected, deselected and re-selected from universes. /// public class SecurityInitializationOnReAdditionForUniverseSelectionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private List _symbolsToSelect; private List _selectedSymbols; private int _selectionsCount; private Dictionary _securityInializationCounts = new(); public override void Initialize() { SetStartDate(2014, 03, 24); SetEndDate(2014, 04, 07); SetCash(100000); UniverseSettings.Resolution = Resolution.Daily; var seeder = new FuncSecuritySeeder((security) => { if (!_securityInializationCounts.TryGetValue(security, out var count)) { count = 0; } _securityInializationCounts[security] = count + 1; Debug($"[{Time}] Seeding {security.Symbol}"); return GetLastKnownPrices(security); }); SetSecurityInitializer(security => seeder.SeedSecurity(security)); _symbolsToSelect = new List() { QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA), QuantConnect.Symbol.Create("IWM", SecurityType.Equity, Market.USA), QuantConnect.Symbol.Create("QQQ", SecurityType.Equity, Market.USA), QuantConnect.Symbol.Create("AIG", SecurityType.Equity, Market.USA), QuantConnect.Symbol.Create("BAC", SecurityType.Equity, Market.USA), QuantConnect.Symbol.Create("IBM", SecurityType.Equity, Market.USA), }; AddUniverse("MyUniverse", Resolution.Daily, SelectionFunction); } private IEnumerable SelectionFunction(DateTime dateTime) { _securityInializationCounts.Clear(); _selectionsCount++; _selectedSymbols = _symbolsToSelect.Skip(dateTime.Day % 2 == 0 ? 0 : 3).Take(3).ToList(); return _selectedSymbols.Select(x => x.Value); } public override void OnSecuritiesChanged(SecurityChanges changes) { foreach (var security in changes.AddedSecurities) { if (!security.IsTradable) { throw new RegressionTestException($"Expected the security to be tradable. Symbol: {security.Symbol}"); } } foreach (var security in changes.RemovedSecurities) { if (security.IsTradable) { throw new RegressionTestException($"Expected the security to be not tradable. Symbol: {security.Symbol}"); } } if (changes.AddedSecurities.Count != _selectedSymbols.Count || changes.AddedSecurities.Any(x => !_selectedSymbols.Contains(x.Symbol))) { throw new RegressionTestException($"Expected the added securities to be the selected ones. " + $"Added: {string.Join(", ", changes.AddedSecurities.Select(x => x.Symbol.Value))}, " + $"Selected: {string.Join(", ", _selectedSymbols)}"); } if (changes.AddedSecurities.Count != _securityInializationCounts.Count || changes.AddedSecurities.Any(x => !_securityInializationCounts.TryGetValue(x, out var count) || count != 1)) { throw new RegressionTestException($"Expected all contracts to be initialized. " + $"Added: {string.Join(", ", changes.AddedSecurities.Select(x => x.Symbol.Value))}, " + $"Initialized: {string.Join(", ", _securityInializationCounts.Select(x => $"{x.Key.Symbol.Value} - {x.Value}"))}"); } if (changes.RemovedSecurities.Count > 0) { var expectedDeselectedSymbols = _symbolsToSelect.Where(x => !_selectedSymbols.Contains(x)).ToList(); if (changes.RemovedSecurities.Count != expectedDeselectedSymbols.Count || changes.RemovedSecurities.Any(x => !expectedDeselectedSymbols.Contains(x.Symbol))) { throw new RegressionTestException($"Expected the removed securities to be the deselected ones. " + $"Removed: {string.Join(", ", changes.RemovedSecurities.Select(x => x.Symbol.Value))}, " + $"Deselected: {string.Join(", ", expectedDeselectedSymbols)}"); } } } public override void OnEndOfAlgorithm() { if (_selectionsCount < 2) { throw new RegressionTestException("Expected at least two selections"); } } /// /// 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 => 128; /// /// Data Points count of the algorithm history /// public int AlgorithmHistoryDataPoints => 150; /// /// 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", "0.97"}, {"Tracking Error", "0.097"}, {"Treynor Ratio", "0"}, {"Total Fees", "$0.00"}, {"Estimated Strategy Capacity", "$0"}, {"Lowest Capacity Asset", ""}, {"Portfolio Turnover", "0%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"} }; } }