wehub-resource-sync
402 lines
18 KiB
C#
402 lines
18 KiB
C#
/*
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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 aaplicable 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.Collections.Generic;
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using System.Linq;
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using NUnit.Framework;
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using Python.Runtime;
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using QuantConnect.Algorithm;
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using QuantConnect.Algorithm.Framework.Alphas;
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using QuantConnect.Algorithm.Framework.Portfolio;
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using QuantConnect.Data;
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using QuantConnect.Data.Market;
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using QuantConnect.Lean.Engine.DataFeeds;
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using QuantConnect.Lean.Engine.HistoricalData;
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using QuantConnect.Packets;
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using QuantConnect.Tests.Common.Data.UniverseSelection;
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using QuantConnect.Tests.Engine.DataFeeds;
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namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
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{
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[TestFixture]
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public class MeanReversionPortfolioConstructionModelTests
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{
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private DateTime _nowUtc;
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private QCAlgorithm _algorithm;
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private List<double> _simplexTestArray;
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private double[] _simplexExpectedArray1, _simplexExpectedArray2;
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[SetUp]
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public virtual void SetUp()
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{
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_nowUtc = new DateTime(2021, 1, 10);
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_algorithm = new AlgorithmStub();
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_algorithm.SetFinishedWarmingUp();
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_algorithm.Settings.MinimumOrderMarginPortfolioPercentage = 0;
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_algorithm.Settings.FreePortfolioValue = 250;
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_algorithm.SetDateTime(_nowUtc.ConvertToUtc(_algorithm.TimeZone));
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_algorithm.SetCash(1200);
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var historyProvider = new SubscriptionDataReaderHistoryProvider();
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_algorithm.SetHistoryProvider(historyProvider);
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historyProvider.Initialize(new HistoryProviderInitializeParameters(
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new BacktestNodePacket(),
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null,
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TestGlobals.DataProvider,
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TestGlobals.DataCacheProvider,
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TestGlobals.MapFileProvider,
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TestGlobals.FactorFileProvider,
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i => { },
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true,
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new DataPermissionManager(),
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_algorithm.ObjectStore,
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_algorithm.Settings));
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_simplexTestArray = new List<double> {0.2d, 0.5d, 0.4d, -0.1d, 0d};
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_simplexExpectedArray1 = new double[] {1d/6, 7d/15, 11d/30, 0d, 0d};
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_simplexExpectedArray2 = new double[] {0d, 0.3d, 0.2d, 0d, 0d};
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}
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[TestCase(Language.CSharp)]
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[TestCase(Language.Python)]
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public void DoesNotReturnTargetsIfSecurityPriceIsZero(Language language)
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{
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_algorithm.AddEquity(Symbols.SPY.Value);
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_algorithm.SetDateTime(_nowUtc.ConvertToUtc(_algorithm.TimeZone));
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SetPortfolioConstruction(language, PortfolioBias.Long);
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var insights = new[] { new Insight(_nowUtc, Symbols.SPY, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null) };
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var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
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Assert.AreEqual(0, actualTargets.Count());
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}
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[TestCase(Language.CSharp, PortfolioBias.Long)]
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[TestCase(Language.Python, PortfolioBias.Long)]
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[TestCase(Language.CSharp, PortfolioBias.Short)]
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[TestCase(Language.Python, PortfolioBias.Short)]
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public void PortfolioBiasIsRespected(Language language, PortfolioBias bias)
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{
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if (bias == PortfolioBias.Short)
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{
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var throwsConstraint = language == Language.CSharp
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? Throws.InstanceOf<ArgumentException>()
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: Throws.InstanceOf<ClrBubbledException>().With.InnerException.InstanceOf<ArgumentException>();
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Assert.That(() => GetPortfolioConstructionModel(language, bias, Resolution.Daily),
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throwsConstraint.And.Message.EqualTo("Long position must be allowed in MeanReversionPortfolioConstructionModel."));
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return;
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}
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var targets = GeneratePortfolioTargets(language, InsightDirection.Up, InsightDirection.Up, 1, 1);
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foreach (var target in targets)
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{
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if (target.Quantity == 0)
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{
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continue;
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}
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Assert.AreEqual(Math.Sign((int)bias), Math.Sign(target.Quantity));
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}
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}
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[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, null, null, 47, 47)]
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[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, null, null, 47, 47)]
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[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0, 0, 47, 47)]
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[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0, 0, 47, 47)]
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[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 1, -0.5, 31, 63)]
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[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 1, -0.5, 31, 63)]
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[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Down, 1, 0.5, 31, 63)]
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[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Down, 1, 0.5, 31, 63)]
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[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0, -0.5, 47, 47)]
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[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0, -0.5, 47, 47)]
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[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0, 1, 94, 0)]
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[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0, 1, 94, 0)]
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[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0.5, -1, 47, 47)]
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[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0.5, -1, 47, 47)]
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public void CorrectWeightings(Language language,
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InsightDirection direction1,
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InsightDirection direction2,
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double? magnitude1,
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double? magnitude2,
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decimal expectedQty1,
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decimal expectedQty2)
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{
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var targets = GeneratePortfolioTargets(language, direction1, direction2, magnitude1, magnitude2);
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var quantities = targets.ToDictionary(target => {
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QuantConnect.Logging.Log.Debug($"{target.Symbol}: {target.Quantity}");
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return target.Symbol.Value;
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},
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target => target.Quantity);
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Assert.AreEqual(expectedQty1, quantities["AAPL"]);
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Assert.AreEqual(expectedQty2, quantities.ContainsKey("SPY") ? quantities["SPY"] : 0);
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}
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[Test]
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public void CumulativeSum()
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{
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var list = new List<double>{1.1d, 2.5d, 0.7d, 13.6d, -5.2d, 3.9d, -1.6d};
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var expected = new List<double>{1.1d, 3.6d, 4.3d, 17.9d, 12.7d, 16.6d, 15.0d};
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var result = MeanReversionPortfolioConstructionModel.CumulativeSum(list)
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.Select(x => Math.Round(x, 1));
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Assert.AreEqual(expected, result);
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}
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[Test]
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public void GetPriceRelatives()
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{
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var model = new TestMeanReversionPortfolioConstructionModel();
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SetPortfolioConstruction(Language.CSharp, PortfolioBias.Long, model);
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var aapl = _algorithm.AddEquity("AAPL");
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var spy = _algorithm.AddEquity("SPY");
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var insights = new List<Insight>
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{
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new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
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new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
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};
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_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(aapl, spy));
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var history = _algorithm.History<TradeBar>(new[] {aapl.Symbol, spy.Symbol}, 2, Resolution.Daily);
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var aaplHist = history.Select(slice => slice[aapl.Symbol].Close);
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var spyHist = history.Select(slice => slice[spy.Symbol].Close);
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var aaplRelative = (double) (aaplHist.Last() / aaplHist.Average());
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var spyRelative = (double) (spyHist.Last() / spyHist.Average());
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var result = model.TestGetPriceRelatives(insights).Select(x => Math.Round(x, 8)).ToArray();
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var expected = new double[] {aaplRelative, spyRelative};
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expected = expected.Select(x => Math.Round(x, 8)).ToArray();
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Assert.AreEqual(expected, result);
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}
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[Test]
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public void GetPriceRelativesPython()
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{
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SetPortfolioConstruction(Language.Python, PortfolioBias.Long);
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var aapl = _algorithm.AddEquity("AAPL");
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var spy = _algorithm.AddEquity("SPY");
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var insights = new List<Insight>
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{
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new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
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new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
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};
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var history = _algorithm.History<TradeBar>(new[] {aapl.Symbol, spy.Symbol}, 2, Resolution.Daily);
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var aaplHist = history.Select(slice => slice[aapl.Symbol].Close);
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var spyHist = history.Select(slice => slice[spy.Symbol].Close);
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var aaplRelative = (double) (aaplHist.Last() / aaplHist.Average());
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var spyRelative = (double) (spyHist.Last() / spyHist.Average());
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using (Py.GIL())
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{
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const string name = nameof(MeanReversionPortfolioConstructionModel);
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var model = Py.Import(name).GetAttr(name).Invoke(((int)Resolution.Daily).ToPython(), ((int)PortfolioBias.LongShort).ToPython(), 1.ToPython(), 2.ToPython());
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model.InvokeMethod("OnSecuritiesChanged", _algorithm.ToPython(), SecurityChangesTests.AddedNonInternal(aapl, spy).ToPython());
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var result = PyList.AsList(model.InvokeMethod("GetPriceRelatives", insights.ToPython()));
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var resultArray = result.Select(x => Math.Round(Convert.ToDouble(x), 8)).ToArray();
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var expected = new double[] {aaplRelative, spyRelative};
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expected = expected.Select(x => Math.Round(x, 8)).ToArray();
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Assert.AreEqual(expected, resultArray);
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}
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}
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[Test]
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public void GetPriceRelativesWithInsightMagnitude()
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{
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var model = new TestMeanReversionPortfolioConstructionModel();
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SetPortfolioConstruction(Language.CSharp, PortfolioBias.Long, model);
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var aapl = _algorithm.AddEquity("AAPL");
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var spy = _algorithm.AddEquity("SPY");
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var insights = new List<Insight>
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{
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new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, 1, null),
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new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, -0.5, null),
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};
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_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(aapl, spy));
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var result = model.TestGetPriceRelatives(insights);
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var expected = new double[] {2d, 0.5d};
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Assert.AreEqual(expected, result);
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}
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[Test]
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public void GetPriceRelativesWithInsightMagnitudePython()
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{
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SetPortfolioConstruction(Language.Python, PortfolioBias.Long);
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var aapl = _algorithm.AddEquity("AAPL");
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var spy = _algorithm.AddEquity("SPY");
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var insights = new List<Insight>
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{
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new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, 1, null),
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new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, -0.5, null),
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};
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using (Py.GIL())
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{
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const string name = nameof(MeanReversionPortfolioConstructionModel);
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var model = Py.Import(name).GetAttr(name).Invoke(((int)Resolution.Daily).ToPython());
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model.InvokeMethod("OnSecuritiesChanged", _algorithm.ToPython(), SecurityChangesTests.AddedNonInternal(aapl, spy).ToPython());
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var result = PyList.AsList(model.InvokeMethod("GetPriceRelatives", insights.ToPython()));
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var resultArray = result.Select(x => Convert.ToDouble(x)).ToArray();
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var expected = new double[] {2d, 0.5d};
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Assert.AreEqual(expected, resultArray);
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}
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}
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[TestCase(1)]
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[TestCase(0.5)]
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[TestCase(0)]
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[TestCase(-0.5)]
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public void SimplexProjection(double regulator)
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{
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if (regulator <= 0)
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{
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var exception = Assert.Throws<ArgumentException>(() => MeanReversionPortfolioConstructionModel.SimplexProjection(_simplexTestArray, regulator));
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Assert.That(exception.Message, Is.EqualTo("Total must be > 0 for Euclidean Projection onto the Simplex."));
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return;
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}
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double[] expected;
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if (regulator == 1d)
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{
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expected = _simplexExpectedArray1;
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}
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else
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{
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expected = _simplexExpectedArray2;
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}
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expected = expected.Select(x => Math.Round(x, 8)).ToArray();
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var result = MeanReversionPortfolioConstructionModel.SimplexProjection(_simplexTestArray, regulator);
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result = result.Select(x => Math.Round(x, 8)).ToArray();
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Assert.AreEqual(expected, result);
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}
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[TestCase(1)]
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[TestCase(0.5)]
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[TestCase(0)]
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[TestCase(-0.5)]
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public void SimplexProjectionPython(double regulator)
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{
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using (Py.GIL())
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{
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const string name = nameof(MeanReversionPortfolioConstructionModel);
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var model = Py.Import(name).GetAttr(name).Invoke(((int)Resolution.Daily).ToPython());
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if (regulator <= 0)
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{
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Assert.That(() => model.InvokeMethod("SimplexProjection", _simplexTestArray.ToPython(), new PyFloat(regulator)),
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Throws.InstanceOf<ClrBubbledException>()
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.With.InnerException.InstanceOf<ArgumentException>()
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.And.Message.EqualTo("Total must be > 0 for Euclidean Projection onto the Simplex."));
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return;
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}
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double[] expected;
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if (regulator == 1d)
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{
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expected = _simplexExpectedArray1;
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}
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else
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{
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expected = _simplexExpectedArray2;
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}
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var expectedArray = expected.Select(x => Math.Round(x, 8)).ToArray();
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var result = PyList.AsList(model.InvokeMethod("SimplexProjection", _simplexTestArray.ToPython(), new PyFloat(regulator)));
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var resultArray = result.Select(x => Math.Round(Convert.ToDouble(x), 8)).ToArray();
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Assert.AreEqual(expectedArray, resultArray);
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}
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}
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private IEnumerable<IPortfolioTarget> GeneratePortfolioTargets(Language language, InsightDirection direction1, InsightDirection direction2, double? magnitude1, double? magnitude2)
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{
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SetPortfolioConstruction(language, PortfolioBias.Long);
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var aapl = _algorithm.AddEquity("AAPL");
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var spy = _algorithm.AddEquity("SPY");
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foreach (var equity in new[] { aapl, spy })
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{
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equity.SetMarketPrice(new Tick(_nowUtc, equity.Symbol, 10, 10));
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}
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var insights = new[]
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{
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new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, direction1, magnitude1, null),
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new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, direction2, magnitude2, null),
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};
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_algorithm.Insights.AddRange(insights);
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_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(aapl, spy));
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return _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
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}
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protected void SetPortfolioConstruction(Language language, PortfolioBias bias, IPortfolioConstructionModel defaultModel = null)
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{
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var model = defaultModel ?? GetPortfolioConstructionModel(language, bias, Resolution.Daily);
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_algorithm.SetPortfolioConstruction(model);
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foreach (var kvp in _algorithm.Portfolio)
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{
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kvp.Value.SetHoldings(kvp.Value.Price, 0);
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}
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var changes = SecurityChangesTests.AddedNonInternal(_algorithm.Securities.Values.ToArray());
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_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, changes);
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}
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public IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, PortfolioBias bias, Resolution resolution)
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{
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if (language == Language.CSharp)
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{
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return new MeanReversionPortfolioConstructionModel(resolution, bias, 1, 1, resolution);
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}
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using (Py.GIL())
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{
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const string name = nameof(MeanReversionPortfolioConstructionModel);
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var instance = Py.Import(name).GetAttr(name)
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.Invoke(((int)resolution).ToPython(), ((int)bias).ToPython(), 1.ToPython(), 1.ToPython(), ((int)resolution).ToPython());
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return new PortfolioConstructionModelPythonWrapper(instance);
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}
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}
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private class TestMeanReversionPortfolioConstructionModel : MeanReversionPortfolioConstructionModel
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{
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public TestMeanReversionPortfolioConstructionModel()
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: base(Resolution.Daily, windowSize: 2)
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{
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}
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public double[] TestGetPriceRelatives(List<Insight> insights)
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{
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return base.GetPriceRelatives(insights);
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}
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}
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}
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}
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