chore: import upstream snapshot with attribution
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wehub-resource-sync
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/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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*/
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using QuantConnect.Data;
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using QuantConnect.Orders;
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using QuantConnect.Interfaces;
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using System.Collections.Generic;
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using QuantConnect.Data.UniverseSelection;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Demonstration of using the Delisting event in your algorithm. Assets are delisted on their last day of trading, or when their contract expires.
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/// This data is not included in the open source project.
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="data event handlers" />
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/// <meta name="tag" content="delisting event" />
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public class DelistingEventsAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private bool _receivedDelistedWarningEvent;
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private bool _receivedDelistedEvent;
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private int _receivedSecurityChangesEvent;
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private int _dataCount;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2007, 05, 15); //Set Start Date
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SetEndDate(2007, 05, 25); //Set End Date
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SetCash(100000); //Set Strategy Cash
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// Find more symbols here: http://quantconnect.com/data
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AddSecurity(SecurityType.Equity, "AAA.1", Resolution.Daily);
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AddSecurity(SecurityType.Equity, "SPY", Resolution.Daily);
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="slice">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice slice)
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{
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_dataCount += slice.Bars.Count;
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if (Transactions.OrdersCount == 0)
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{
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SetHoldings("AAA.1", 1);
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Debug("Purchased Stock");
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}
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foreach (var kvp in slice.Bars)
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{
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var symbol = kvp.Key;
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var tradeBar = kvp.Value;
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Debug($"OnData(Slice): {Time}: {symbol}: {tradeBar.Close.ToStringInvariant("0.00")}");
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}
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// the slice can also contain delisting data: data.Delistings in a dictionary string->Delisting
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var aaa = Securities["AAA.1"];
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if (aaa.IsDelisted && aaa.IsTradable)
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{
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throw new RegressionTestException("Delisted security must NOT be tradable");
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}
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if (!aaa.IsDelisted && !aaa.IsTradable)
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{
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throw new RegressionTestException("Securities must be marked as tradable until they're delisted or removed from the universe");
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}
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foreach (var kvp in slice.Delistings)
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{
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var symbol = kvp.Key;
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var delisting = kvp.Value;
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if (delisting.Type == DelistingType.Warning)
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{
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_receivedDelistedWarningEvent = true;
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Debug($"OnData(Delistings): {Time}: {symbol} will be delisted at end of day today.");
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// liquidate on delisting warning
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SetHoldings(symbol, 0);
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}
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if (delisting.Type == DelistingType.Delisted)
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{
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_receivedDelistedEvent = true;
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Debug($"OnData(Delistings): {Time}: {symbol} has been delisted.");
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// fails because the security has already been delisted and is no longer tradable
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SetHoldings(symbol, 1);
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}
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}
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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Debug($"OnOrderEvent(OrderEvent): {Time}: {orderEvent}");
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}
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public override void OnSecuritiesChanged(SecurityChanges changes)
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{
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foreach (var removedSecurity in changes.RemovedSecurities)
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{
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if (removedSecurity.Symbol.Value == "AAA.1")
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{
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_receivedSecurityChangesEvent++;
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}
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (!_receivedDelistedEvent)
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{
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throw new RegressionTestException("Did not receive expected delisted event");
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}
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if (!_receivedDelistedWarningEvent)
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{
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throw new RegressionTestException("Did not receive expected delisted warning event");
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}
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if (_dataCount != 13)
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{
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throw new RegressionTestException($"Unexpected data count {_dataCount}. Expected 13");
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}
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if (_receivedSecurityChangesEvent != 1)
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{
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throw new RegressionTestException($"Did not receive expected security changes removal! Got {_receivedSecurityChangesEvent}");
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}
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public long DataPoints => 87;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "2"},
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{"Average Win", "0%"},
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{"Average Loss", "-5.58%"},
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{"Compounding Annual Return", "-85.973%"},
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{"Drawdown", "5.600%"},
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{"Expectancy", "-1"},
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{"Start Equity", "100000"},
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{"End Equity", "94421.6"},
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{"Net Profit", "-5.578%"},
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{"Sharpe Ratio", "-5.495"},
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{"Sortino Ratio", "-10.306"},
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{"Probabilistic Sharpe Ratio", "0.000%"},
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{"Loss Rate", "100%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "-0.585"},
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{"Beta", "-1.085"},
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{"Annual Standard Deviation", "0.15"},
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{"Annual Variance", "0.023"},
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{"Information Ratio", "-5.081"},
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{"Tracking Error", "0.206"},
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{"Treynor Ratio", "0.76"},
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{"Total Fees", "$36.70"},
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{"Estimated Strategy Capacity", "$110000.00"},
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{"Lowest Capacity Asset", "AAA SEVKGI6HF885"},
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{"Portfolio Turnover", "18.33%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "1450ea23a3a1ef4ee2398ec757c39223"}
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};
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}
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}
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