/* * 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 test reproduces the issue where a Cash instance is added /// during execution by the BrokerageTransactionHandler, in this case the /// algorithm will be adding it in OnData() to reproduce the same scenario. /// public class SetCashOnDataRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA); private bool _added; /// /// 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(2014, 12, 01); //Set Start Date SetEndDate(2014, 12, 21); //Set End Date SetCash(100000); //Set Strategy Cash AddEquity("SPY", Resolution.Daily); } /// /// 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 data) { if (!_added) { _added = true; // this should not be done by users but could be done by the BrokerageTransactionHandler // Users: see and use SetCash() Portfolio.CashBook.Add("EUR", 10,0); } else { var cash = Portfolio.CashBook["EUR"]; if (cash.ConversionRateSecurity == null || cash.ConversionRate == 0) { throw new Exception("Expected 'EUR' Cash to be fully set"); } var eurUsdSubscription = SubscriptionManager.SubscriptionDataConfigService .GetSubscriptionDataConfigs(QuantConnect.Symbol.Create("EURUSD", SecurityType.Forex, Market.Oanda), includeInternalConfigs: true) .Single(); if (!eurUsdSubscription.IsInternalFeed) { throw new Exception("Unexpected not internal 'EURUSD' Subscription"); } } if (!Portfolio.Invested) { SetHoldings(_spy, 1); Debug("Purchased Stock"); } } /// /// 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 Language[] Languages { get; } = { Language.CSharp }; /// /// 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 Trades", "1"}, {"Average Win", "0%"}, {"Average Loss", "0%"}, {"Compounding Annual Return", "16.445%"}, {"Drawdown", "4.800%"}, {"Expectancy", "0"}, {"Net Profit", "0.913%"}, {"Sharpe Ratio", "0.903"}, {"Probabilistic Sharpe Ratio", "48.314%"}, {"Loss Rate", "0%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0.113"}, {"Beta", "0.203"}, {"Annual Standard Deviation", "0.156"}, {"Annual Variance", "0.024"}, {"Information Ratio", "0.001"}, {"Tracking Error", "0.198"}, {"Treynor Ratio", "0.697"}, {"Total Fees", "$2.60"}, {"Fitness Score", "0.041"}, {"Kelly Criterion Estimate", "0"}, {"Kelly Criterion Probability Value", "0"}, {"Sortino Ratio", "1.617"}, {"Return Over Maximum Drawdown", "3.406"}, {"Portfolio Turnover", "0.052"}, {"Total Insights Generated", "0"}, {"Total Insights Closed", "0"}, {"Total Insights Analysis Completed", "0"}, {"Long Insight Count", "0"}, {"Short Insight Count", "0"}, {"Long/Short Ratio", "100%"}, {"Estimated Monthly Alpha Value", "$0"}, {"Total Accumulated Estimated Alpha Value", "$0"}, {"Mean Population Estimated Insight Value", "$0"}, {"Mean Population Direction", "0%"}, {"Mean Population Magnitude", "0%"}, {"Rolling Averaged Population Direction", "0%"}, {"Rolling Averaged Population Magnitude", "0%"}, {"OrderListHash", "150018942"} }; } }