/* * 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 { /// /// This regression algorithm has two different Universe using the same SubscriptionDataConfig. /// One of them will add and remove it in a toggle fashion but since it will still be consumed /// by the other Universe it should not be removed. /// /// public class UniverseSharingSubscriptionRequestRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private readonly Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA); private int _onDataCalls; private bool _restOneDay; /// /// 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, 01); //Set Start Date SetEndDate(2013, 10, 30); //Set End Date SetCash(100000); //Set Strategy Cash AddEquity("SPY", Resolution.Daily); UniverseSettings.Resolution = Resolution.Daily; AddUniverse(SecurityType.Equity, "SecondUniverse", Resolution.Daily, Market.USA, UniverseSettings, time => time.Day % 3 == 0 ? new[] { "SPY" } : Enumerable.Empty() ); } /// /// 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 (slice.Count != 1) { throw new RegressionTestException($"Unexpected data count {slice.Count}"); } Debug($"{slice.Time}. Data count {slice.Count}. Data {slice.Bars.First().Value}"); _onDataCalls++; if (_restOneDay) { // let a day pass before trading again, this will cause // "SecondUniverse" remove request to be applied _restOneDay = false; } else if(!Portfolio.Invested) { SetHoldings(_spy, 1); Debug("Purchased Stock"); } else { SetHoldings(_spy, 0); Debug("Sell Stock"); _restOneDay = true; } } public override void OnEndOfAlgorithm() { if (_onDataCalls != 22) { throw new RegressionTestException($"Unexpected OnData() calls count {_onDataCalls}"); } } /// /// 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 => 206; /// /// 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", "15"}, {"Average Win", "0.30%"}, {"Average Loss", "0%"}, {"Compounding Annual Return", "29.578%"}, {"Drawdown", "0.700%"}, {"Expectancy", "0"}, {"Start Equity", "100000"}, {"End Equity", "102128.38"}, {"Net Profit", "2.128%"}, {"Sharpe Ratio", "4.345"}, {"Sortino Ratio", "7.134"}, {"Probabilistic Sharpe Ratio", "91.767%"}, {"Loss Rate", "0%"}, {"Win Rate", "100%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0.073"}, {"Beta", "0.292"}, {"Annual Standard Deviation", "0.045"}, {"Annual Variance", "0.002"}, {"Information Ratio", "-2.681"}, {"Tracking Error", "0.083"}, {"Treynor Ratio", "0.666"}, {"Total Fees", "$47.53"}, {"Estimated Strategy Capacity", "$760000000.00"}, {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"}, {"Portfolio Turnover", "46.41%"}, {"Drawdown Recovery", "7"}, {"OrderListHash", "224b0ff29c5b287ecffaaa257e594ef3"} }; } }