chore: import upstream snapshot with attribution
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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 System.Collections.Generic;
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using QuantConnect.Securities.Future;
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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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/// Continuous Futures Regression algorithm. Asserting and showcasing the behavior of adding a continuous future
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/// </summary>
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public class ContinuousFutureRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private List<Symbol> _previousMappedContractSymbols = new();
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private Symbol _currentMappedSymbol;
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private Future _continuousContract;
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private DateTime _lastMonth;
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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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_continuousContract = AddFuture(Futures.Indices.SP500EMini,
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dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
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dataMappingMode: DataMappingMode.LastTradingDay,
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contractDepthOffset: 0
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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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// we subtract a minute cause we can get data on the market close, from the previous minute
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if (!_continuousContract.Exchange.DateTimeIsOpen(Time.AddMinutes(-1)))
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{
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if (slice.Bars.Count > 0 || slice.QuoteBars.Count > 0)
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{
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throw new RegressionTestException($"We are getting data during closed market!");
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}
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}
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var currentlyMappedSecurity = Securities[_continuousContract.Mapped];
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if (slice.Keys.Count != 1)
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{
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throw new RegressionTestException($"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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_previousMappedContractSymbols.Add(Symbol(changedEvent.OldSymbol));
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Log($"{Time} - SymbolChanged event: {changedEvent}");
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if (_currentMappedSymbol == _continuousContract.Mapped)
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{
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throw new RegressionTestException($"Continuous contract current symbol did not change! {_continuousContract.Mapped}");
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}
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var currentExpiration = changedEvent.Symbol.Underlying.ID.Date;
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var frontMonthExpiration = FuturesExpiryFunctions.FuturesExpiryFunction(_continuousContract.Symbol)(Time.AddMonths(1));
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if (currentExpiration != frontMonthExpiration.Date)
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{
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throw new RegressionTestException($"Unexpected current mapped contract expiration {currentExpiration}" +
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$" @ {Time} it should be AT front month expiration {frontMonthExpiration}");
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}
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}
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}
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if (_lastMonth.Month != Time.Month && currentlyMappedSecurity.HasData)
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{
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_lastMonth = Time;
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Log($"{Time}- {currentlyMappedSecurity.GetLastData()}");
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if (Portfolio.Invested)
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{
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Liquidate();
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}
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else
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{
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// This works because we set this contract as tradable, even if it's a canonical security
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Buy(currentlyMappedSecurity.Symbol, 1);
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}
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if(Time.Month == 1 && Time.Year == 2013)
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{
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var response = History(new[] { _continuousContract.Symbol }, 60 * 24 * 90);
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if (!response.Any())
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{
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throw new RegressionTestException("Unexpected empty history response");
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}
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}
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}
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_currentMappedSymbol = _continuousContract.Mapped;
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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if (orderEvent.Status == OrderStatus.Filled)
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{
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Log($"{orderEvent}");
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}
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}
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public override void OnSecuritiesChanged(SecurityChanges changes)
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{
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Debug($"{Time}-{changes}");
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if (changes.AddedSecurities.Any(security => security.Symbol != _continuousContract.Symbol)
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|| changes.RemovedSecurities.Any(security => security.Symbol != _continuousContract.Symbol))
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{
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throw new RegressionTestException($"We got an unexpected security changes {changes}");
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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 (_previousMappedContractSymbols.Count != expectedMappingCounts)
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{
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throw new RegressionTestException($"Unexpected symbol changed events: {_previousMappedContractSymbols.Count}, was expecting {expectedMappingCounts}");
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}
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var delistedSecurities = _previousMappedContractSymbols
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.Select(x => Securities.Total.Single(sec => sec.Symbol == x))
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.Where(x => x.Symbol.ID.Date < Time)
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.ToList();
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var markedDelistedSecurities = delistedSecurities.Where(x => x.IsDelisted && !x.IsTradable).ToList();
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if (markedDelistedSecurities.Count != delistedSecurities.Count)
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{
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throw new RegressionTestException($"Not all delisted contracts are properly market as delisted and non-tradable: " +
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$"only {markedDelistedSecurities.Count} are marked, was expecting {delistedSecurities.Count}");
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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 => 162575;
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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", "4"},
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{"Average Win", "3.31%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "13.589%"},
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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", "106624.8"},
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{"Net Profit", "6.625%"},
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{"Sharpe Ratio", "1.696"},
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{"Sortino Ratio", "1.497"},
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{"Probabilistic Sharpe Ratio", "77.443%"},
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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", "0.049"},
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{"Beta", "0.171"},
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{"Annual Standard Deviation", "0.051"},
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{"Annual Variance", "0.003"},
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{"Information Ratio", "-1.571"},
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{"Tracking Error", "0.084"},
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{"Treynor Ratio", "0.504"},
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{"Total Fees", "$6.45"},
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{"Estimated Strategy Capacity", "$2900000000.00"},
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{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
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{"Portfolio Turnover", "1.84%"},
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{"Drawdown Recovery", "19"},
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{"OrderListHash", "93ec1ff41936971c765cd3a1e3613f09"}
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};
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}
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}
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