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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using System;
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using System.Linq;
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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 QuantConnect.Securities;
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using QuantConnect.Data.Market;
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using System.Collections.Generic;
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using QuantConnect.Securities.Future;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Continuous Futures Back Month #1 Regression algorithm. Asserting and showcasing the behavior of adding a continuous future
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/// </summary>
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public class ContinuousFutureBackMonthRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private List<SymbolChangedEvent> _mappings = new();
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private Future _continuousContract;
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private DateTime _lastDateLog;
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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(2013, 7, 1);
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SetEndDate(2014, 1, 1);
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try
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{
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AddFuture(Futures.Indices.SP500EMini,
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dataNormalizationMode: DataNormalizationMode.BackwardsPanamaCanal,
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dataMappingMode: DataMappingMode.OpenInterest,
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contractDepthOffset: 5
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);
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throw new RegressionTestException("Expected out of rage exception. We don't support that many back months");
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}
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catch (ArgumentOutOfRangeException)
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{
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// expected
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}
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_continuousContract = AddFuture(Futures.Indices.SP500EMini,
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dataNormalizationMode: DataNormalizationMode.BackwardsPanamaCanal,
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dataMappingMode: DataMappingMode.OpenInterest,
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contractDepthOffset: 1
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);
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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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if (slice.Keys.Count != 1)
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{
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throw new RegressionTestException($"We are getting data for more than one symbols! {string.Join(",", slice.Keys.Select(symbol => symbol))}");
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}
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foreach (var changedEvent in slice.SymbolChangedEvents.Values)
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{
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if (changedEvent.Symbol == _continuousContract.Symbol)
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{
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_mappings.Add(changedEvent);
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Log($"SymbolChanged event: {changedEvent}");
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var backMonthExpiration = changedEvent.Symbol.Underlying.ID.Date;
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var frontMonthExpiration = FuturesExpiryFunctions.FuturesExpiryFunction(_continuousContract.Symbol)(Time.AddMonths(1));
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if (backMonthExpiration <= frontMonthExpiration.Date)
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{
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throw new RegressionTestException($"Unexpected current mapped contract expiration {backMonthExpiration}" +
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$" @ {Time} it should be AFTER front month expiration {frontMonthExpiration}");
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}
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if (_continuousContract.Mapped != changedEvent.Symbol.Underlying)
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{
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throw new RegressionTestException($"Unexpected mapped continuous contract {_continuousContract.Mapped} expected {changedEvent.Symbol.Underlying}");
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}
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}
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}
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if (_lastDateLog.Month != Time.Month && _continuousContract.HasData)
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{
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_lastDateLog = Time;
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Log($"{Time}- {Securities[_continuousContract.Symbol].GetLastData()}");
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if (_continuousContract.Exchange.ExchangeOpen)
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{
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if (Portfolio.Invested)
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{
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Liquidate();
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}
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else
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{
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Buy(_continuousContract.Mapped, 1);
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}
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}
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if(Time.Month == 1 && Time.Year == 2013)
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{
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var response = History(new[] { _continuousContract.Symbol }, 60 * 24 * 90);
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if (!response.Any())
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{
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throw new RegressionTestException("Unexpected empty history response");
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}
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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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if (orderEvent.Status == OrderStatus.Filled)
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{
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Log($"{orderEvent}");
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}
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}
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public override void OnEndOfAlgorithm()
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{
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var expectedMappingCounts = 2;
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if (_mappings.Count != expectedMappingCounts)
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{
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throw new RegressionTestException($"Unexpected symbol changed events: {_mappings.Count}, was expecting {expectedMappingCounts}");
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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 };
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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 => 172698;
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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", "3"},
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{"Average Win", "6.43%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "14.898%"},
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{"Drawdown", "1.600%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "107241.4"},
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{"Net Profit", "7.241%"},
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{"Sharpe Ratio", "1.511"},
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{"Sortino Ratio", "1.208"},
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{"Probabilistic Sharpe Ratio", "74.255%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "100%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0.075"},
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{"Beta", "0.096"},
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{"Annual Standard Deviation", "0.063"},
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{"Annual Variance", "0.004"},
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{"Information Ratio", "-1.256"},
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{"Tracking Error", "0.097"},
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{"Treynor Ratio", "0.996"},
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{"Total Fees", "$6.45"},
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{"Estimated Strategy Capacity", "$240000000.00"},
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{"Lowest Capacity Asset", "ES VP274HSU1AF5"},
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{"Portfolio Turnover", "1.37%"},
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{"Drawdown Recovery", "16"},
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{"OrderListHash", "c2eacc46e837feb8bf019c43f5c03f40"}
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};
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}
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}
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