/* * 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.Data.Market; using QuantConnect.Orders; using QuantConnect.Interfaces; namespace QuantConnect.Algorithm.CSharp { /// /// Demonstration of using the Delisting event in your algorithm. Assets are delisted on their last day of trading, or when their contract expires. /// This data is not included in the open source project. /// /// /// /// public class DelistingEventsAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private bool _receivedDelistedWarningEvent; private bool _receivedDelistedEvent; private int _dataCount; /// /// 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(2007, 05, 16); //Set Start Date SetEndDate(2007, 05, 25); //Set End Date SetCash(100000); //Set Strategy Cash // Find more symbols here: http://quantconnect.com/data AddSecurity(SecurityType.Equity, "AAA", Resolution.Daily); AddSecurity(SecurityType.Equity, "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) { _dataCount += data.Bars.Count; if (Transactions.OrdersCount == 0) { SetHoldings("AAA", 1); Debug("Purchased Stock"); } foreach (var kvp in data.Bars) { var symbol = kvp.Key; var tradeBar = kvp.Value; Debug($"OnData(Slice): {Time}: {symbol}: {tradeBar.Close.ToString("0.00")}"); } // the slice can also contain delisting data: data.Delistings in a dictionary string->Delisting var aaa = Securities["AAA"]; if (aaa.IsDelisted && aaa.IsTradable) { throw new Exception("Delisted security must NOT be tradable"); } if (!aaa.IsDelisted && !aaa.IsTradable) { throw new Exception("Securities must be marked as tradable until they're delisted or removed from the universe"); } } public void OnData(Delistings data) { foreach (var kvp in data) { var symbol = kvp.Key; var delisting = kvp.Value; if (delisting.Type == DelistingType.Warning) { _receivedDelistedWarningEvent = true; Debug($"OnData(Delistings): {Time}: {symbol} will be delisted at end of day today."); // liquidate on delisting warning SetHoldings(symbol, 0); } if (delisting.Type == DelistingType.Delisted) { _receivedDelistedEvent = true; Debug($"OnData(Delistings): {Time}: {symbol} has been delisted."); // fails because the security has already been delisted and is no longer tradable SetHoldings(symbol, 1); } } } public override void OnOrderEvent(OrderEvent orderEvent) { Debug($"OnOrderEvent(OrderEvent): {Time}: {orderEvent}"); } public override void OnEndOfAlgorithm() { if (!_receivedDelistedEvent) { throw new Exception("Did not receive expected delisted event"); } if (!_receivedDelistedWarningEvent) { throw new Exception("Did not receive expected delisted warning event"); } if (_dataCount != 13) { throw new Exception($"Unexpected data count {_dataCount}. Expected 13"); } } /// /// 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, Language.Python }; /// /// 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", "2"}, {"Average Win", "0%"}, {"Average Loss", "-5.58%"}, {"Compounding Annual Return", "-87.694%"}, {"Drawdown", "5.600%"}, {"Expectancy", "-1"}, {"Net Profit", "-5.578%"}, {"Sharpe Ratio", "-10.227"}, {"Loss Rate", "100%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "-1.953"}, {"Beta", "23.587"}, {"Annual Standard Deviation", "0.156"}, {"Annual Variance", "0.024"}, {"Information Ratio", "-10.33"}, {"Tracking Error", "0.156"}, {"Treynor Ratio", "-0.067"}, {"Total Fees", "$36.70"} }; } }