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chore: import upstream snapshot with attribution

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2026-07-13 13:02:50 +08:00
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Tests/Algorithm/Framework/Portfolio/AccumulativeInsightPortfolioConstructionModelTests.cs
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/*
* 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 System.Linq;
using NodaTime;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Securities;
using QuantConnect.Securities.Equity;
using QuantConnect.Tests.Common.Data.UniverseSelection;
using QuantConnect.Tests.Engine.DataFeeds;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class AccumulativeInsightPortfolioConstructionModelTests
{
private QCAlgorithm _algorithm;
private const decimal _startingCash = 100000;
private const double DefaultPercent = 0.03;
[SetUp]
public void SetUp()
{
_algorithm = new QCAlgorithm();
_algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(_algorithm));
var prices = new Dictionary<Symbol, decimal>
{
{ Symbol.Create("AIG", SecurityType.Equity, Market.USA), 55.22m },
{ Symbol.Create("IBM", SecurityType.Equity, Market.USA), 145.17m },
{ Symbol.Create("SPY", SecurityType.Equity, Market.USA), 281.79m },
};
foreach (var kvp in prices)
{
var symbol = kvp.Key;
var security = GetSecurity(symbol);
security.SetMarketPrice(new Tick(_algorithm.Time, symbol, kvp.Value, kvp.Value));
_algorithm.Securities.Add(symbol, security);
}
}
[Test]
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void EmptyInsightsReturnsEmptyTargets(Language language)
{
SetPortfolioConstruction(language, _algorithm);
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]);
Assert.AreEqual(0, actualTargets.Count());
}
[Test]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
public void InsightsReturnsTargetsConsistentWithDirection(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language, _algorithm);
var amount = _algorithm.Portfolio.TotalPortfolioValue * (decimal)DefaultPercent;
var expectedTargets = _algorithm.Securities
.Select(x => new PortfolioTarget(x.Key, (int)direction
* Math.Floor(amount / x.Value.Price)));
var insights = _algorithm.Securities.Keys.Select(x => GetInsight(x, direction, _algorithm.UtcTime));
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights.ToArray());
AssertTargets( expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void LongTermInsightCanceledByNew(Language language)
{
SetPortfolioConstruction(language, _algorithm);
// First emit long term insight
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime) };
var targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
var expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, -1m * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// One minute later, emits short term insight to cancel long
SetUtcTime(_algorithm.Time.AddMinutes(1));
insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Up, _algorithm.UtcTime, Time.OneMinute) };
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, 0) };
AssertTargets(expectedTargets, targets);
// One minute later, emit empty insights array, short term insight expires but should stay -1 since long term insight is still valid
SetUtcTime(_algorithm.Time.AddMinutes(1.1));
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, -1m * (decimal)DefaultPercent) };
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]);
AssertTargets(expectedTargets, actualTargets);
// should stay 0 *after* the long expires
SetUtcTime(_algorithm.Time.AddYears(1));
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, 0) };
actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
public void LongTermInsightAccumulatesByNew(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language, _algorithm);
// First emit long term insight
var insights = new[] { GetInsight(Symbols.SPY, direction, _algorithm.UtcTime) };
var targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
var expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// One minute later, emits short term insight to add long
SetUtcTime(_algorithm.UtcTime.AddMinutes(1));
insights = new[] { GetInsight(Symbols.SPY, direction, _algorithm.UtcTime, Time.OneMinute) };
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * 2 * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// One minute later, emit empty insights array, should return to nomral after the long expires
SetUtcTime(_algorithm.UtcTime.AddMinutes(1.1));
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * (decimal)DefaultPercent) };
// Create target from an empty insights array
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
public void FlatUndoesAccumulation(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language, _algorithm);
// First emit long term insight
var insights = new[] { GetInsight(Symbols.SPY, direction, _algorithm.UtcTime) };
var targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
var expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// One minute later, emits insight to add to portfolio
SetUtcTime(_algorithm.UtcTime.AddMinutes(1));
insights = new[] { GetInsight(Symbols.SPY, direction, _algorithm.UtcTime) };
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * 2 * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// One minute later, emits flat insight
SetUtcTime(_algorithm.UtcTime.AddMinutes(1));
insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Flat, _algorithm.UtcTime) };
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// now we should reach 0 percent
insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Flat, _algorithm.UtcTime) };
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, 0) };
AssertTargets(expectedTargets, targets);
}
[Test]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
public void InsightExpirationUndoesAccumulationBySteps(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language, _algorithm);
// First emit long term insight
SetUtcTime(_algorithm.Time);
var insights = new[] { GetInsight(Symbols.SPY, direction, _algorithm.UtcTime, TimeSpan.FromMinutes(10)) };
var targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
var expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// One minute later, emits insight to add to portfolio
SetUtcTime(_algorithm.Time.AddMinutes(1));
insights = new[] { GetInsight(Symbols.SPY, direction, _algorithm.UtcTime, TimeSpan.FromMinutes(10)) };
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * 2 * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// the first insight should expire
SetUtcTime(_algorithm.Time.AddMinutes(10));
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]).ToList();
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// the second insight should expire
SetUtcTime(_algorithm.Time.AddMinutes(1));
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]).ToList();
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, 0) };
AssertTargets(expectedTargets, targets);
}
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
public void RespectsRebalancingPeriod(Language language, InsightDirection direction)
{
PortfolioConstructionModel model = new AccumulativeInsightPortfolioConstructionModel(Resolution.Daily);
if (language == Language.Python)
{
using (Py.GIL())
{
var name = nameof(AccumulativeInsightPortfolioConstructionModel);
dynamic instance = Py.Import(name).GetAttr(name);
model = new PortfolioConstructionModelPythonWrapper(instance(Resolution.Daily));
}
}
model.RebalanceOnSecurityChanges = false;
model.RebalanceOnInsightChanges = false;
SetUtcTime(new DateTime(2018, 7, 31));
// First emit long term insight
var insights = new[] { GetInsight(Symbols.SPY, direction, _algorithm.UtcTime, TimeSpan.FromDays(10)) };
AssertTargets(new List<IPortfolioTarget>(), model.CreateTargets(_algorithm, insights).ToList());
// One minute later, emits insight to add to portfolio
SetUtcTime(_algorithm.Time.AddMinutes(1));
insights = new[] { GetInsight(Symbols.SPY, direction, _algorithm.UtcTime, TimeSpan.FromMinutes(10)) };
AssertTargets(new List<IPortfolioTarget>(), model.CreateTargets(_algorithm, insights));
// the second insight should expire
SetUtcTime(_algorithm.Time.AddMinutes(1));
AssertTargets(new List<IPortfolioTarget>(), model.CreateTargets(_algorithm, insights));
// the rebalancing period is due and the first insight is still valid
SetUtcTime(_algorithm.Time.AddDays(1));
var targets = model.CreateTargets(_algorithm, new Insight[0]);
var expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// the rebalancing period is due and no insight is valid
SetUtcTime(_algorithm.Time.AddDays(10));
AssertTargets(
new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, 0) },
model.CreateTargets(_algorithm, new Insight[0]));
AssertTargets(new List<IPortfolioTarget>(), model.CreateTargets(_algorithm, new Insight[0]));
}
[Test]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
public void InsightExpirationUndoesAccumulation(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language, _algorithm);
// First emit long term insight
SetUtcTime(_algorithm.Time);
var insights = new[]
{
GetInsight(Symbols.SPY, direction, _algorithm.UtcTime, TimeSpan.FromMinutes(10)),
GetInsight(Symbols.SPY, direction, _algorithm.UtcTime, TimeSpan.FromMinutes(10))
};
var targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
var expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, (int)direction * 1m * 2 * (decimal)DefaultPercent) };
AssertTargets(expectedTargets, targets);
// both insights should expire
SetUtcTime(_algorithm.Time.AddMinutes(11));
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]).ToList();
expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, 0) };
AssertTargets(expectedTargets, targets);
// we expect no target
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]).ToList();
AssertTargets(new List<IPortfolioTarget>(), targets);
}
[Test]
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void WeightsProportionally(Language language)
{
SetPortfolioConstruction(language, _algorithm);
var insights = new[]
{
GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime),
GetInsight(Symbol.Create("IBM", SecurityType.Equity, Market.USA),
InsightDirection.Down, _algorithm.UtcTime)
};
// they will each share, proportionally, the total portfolio value
var amount = _algorithm.Portfolio.TotalPortfolioValue * (decimal)DefaultPercent;
var expectedTargets = _algorithm.Securities.Where(pair => insights.Any(insight => pair.Key == insight.Symbol))
.Select(x => new PortfolioTarget(x.Key, (int)InsightDirection.Down * Math.Floor(amount / x.Value.Price)));
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(2, actualTargets.Count);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void GeneratesTargetsForInsightsWithNoConfidence(Language language)
{
SetPortfolioConstruction(language, _algorithm);
var insights = new[]
{
GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime, confidence:null)
};
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(1, actualTargets.Count);
}
[Test]
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void GeneratesNormalTargetForZeroInsightConfidence(Language language)
{
SetPortfolioConstruction(language, _algorithm);
var insights = new[]
{
GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime, confidence:0)
};
// they will each share, proportionally, the total portfolio value
var amount = _algorithm.Portfolio.TotalPortfolioValue * (decimal)DefaultPercent;
var expectedTargets = _algorithm.Securities.Where(pair => insights.Any(insight => pair.Key == insight.Symbol))
.Select(x => new PortfolioTarget(x.Key, (int)InsightDirection.Down * Math.Floor(amount / x.Value.Price)));
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
AssertTargets(expectedTargets, actualTargets);
}
[TestCase(Language.CSharp, PortfolioBias.Long)]
[TestCase(Language.Python, PortfolioBias.Long)]
[TestCase(Language.CSharp, PortfolioBias.Short)]
[TestCase(Language.Python, PortfolioBias.Short)]
public void PortfolioBiasIsRespected(Language language, PortfolioBias bias)
{
SetPortfolioConstruction(language, _algorithm, bias);
var now = new DateTime(2018, 7, 31);
SetUtcTime(now.ConvertFromUtc(_algorithm.TimeZone));
var appl = _algorithm.AddEquity("AAPL");
appl.SetMarketPrice(new Tick(now, appl.Symbol, 10, 10));
var spy = _algorithm.AddEquity("SPY");
spy.SetMarketPrice(new Tick(now, spy.Symbol, 20, 20));
var ibm = _algorithm.AddEquity("IBM");
ibm.SetMarketPrice(new Tick(now, ibm.Symbol, 30, 30));
var aig = _algorithm.AddEquity("AIG");
aig.SetMarketPrice(new Tick(now, aig.Symbol, 30, 30));
var qqq = _algorithm.AddEquity("QQQ");
qqq.SetMarketPrice(new Tick(now, qqq.Symbol, 30, 30));
var insights = new[]
{
new Insight(now, appl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, 0.1d, null),
new Insight(now, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Down, -0.1d, null),
new Insight(now, ibm.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Down, 0d, null),
new Insight(now, aig.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Down, -0.1d, null),
new Insight(now, qqq.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, 0.1d, null)
};
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(appl, spy, ibm, aig, qqq));
var createdValidTarget = false;
_algorithm.Insights.AddRange(insights);
foreach (var target in _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights))
{
QuantConnect.Logging.Log.Trace($"{target.Symbol}: {target.Quantity}");
if (target.Quantity == 0)
{
continue;
}
createdValidTarget = true;
Assert.AreEqual(Math.Sign((int)bias), Math.Sign(target.Quantity));
}
Assert.IsTrue(createdValidTarget);
}
private Security GetSecurity(Symbol symbol)
{
var exchangeHours = MarketHoursDatabase.FromDataFolder().GetExchangeHours(symbol.ID.Market, symbol, symbol.SecurityType);
return new Equity(
symbol,
exchangeHours,
new Cash(Currencies.USD, 0, 1),
SymbolProperties.GetDefault(Currencies.USD),
ErrorCurrencyConverter.Instance,
RegisteredSecurityDataTypesProvider.Null,
new SecurityCache()
);
}
private Insight GetInsight(Symbol symbol, InsightDirection direction, DateTime generatedTimeUtc, TimeSpan? period = null, double? confidence = DefaultPercent)
{
period ??= TimeSpan.FromDays(1);
var insight = Insight.Price(symbol, period.Value, direction, confidence: confidence);
insight.GeneratedTimeUtc = generatedTimeUtc;
insight.CloseTimeUtc = generatedTimeUtc.Add(period.Value);
_algorithm.Insights.Add(insight);
return insight;
}
private void SetPortfolioConstruction(Language language, QCAlgorithm algorithm, PortfolioBias bias= PortfolioBias.LongShort)
{
algorithm.SetPortfolioConstruction(new AccumulativeInsightPortfolioConstructionModel((Func<DateTime,DateTime>)null, bias));
if (language == Language.Python)
{
using (Py.GIL())
{
var name = nameof(AccumulativeInsightPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name).Invoke(((object)null).ToPython(), ((int)bias).ToPython());
var model = new PortfolioConstructionModelPythonWrapper(instance);
algorithm.SetPortfolioConstruction(model);
}
}
foreach (var kvp in _algorithm.Portfolio)
{
kvp.Value.SetHoldings(kvp.Value.Price, 0);
}
_algorithm.Portfolio.SetCash(_startingCash);
SetUtcTime(new DateTime(2018, 7, 31));
var changes = SecurityChangesTests.AddedNonInternal(_algorithm.Securities.Values.ToArray());
algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, changes);
}
private void SetUtcTime(DateTime dateTime)
{
_algorithm.SetDateTime(dateTime.ConvertToUtc(_algorithm.TimeZone));
}
private void AssertTargets(IEnumerable<IPortfolioTarget> expectedTargets, IEnumerable<IPortfolioTarget> actualTargets)
{
var list = actualTargets.ToList();
Assert.AreEqual(expectedTargets.Count(), list.Count);
foreach (var expected in expectedTargets)
{
var actual = list.FirstOrDefault(x => x.Symbol == expected.Symbol);
Assert.IsNotNull(actual);
Assert.AreEqual(expected.Quantity, actual.Quantity);
}
}
}
}
Tests/Algorithm/Framework/Portfolio/BaseWeightingPortfolioConstructionModelTests.cs
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/*
* 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 NodaTime;
using NUnit.Framework;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Securities;
using QuantConnect.Securities.Equity;
using QuantConnect.Tests.Engine.DataFeeds;
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Tests.Common.Data.UniverseSelection;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public abstract class BaseWeightingPortfolioConstructionModelTests
{
protected decimal StartingCash => 100000;
protected QCAlgorithm Algorithm { get; set; }
public virtual double? Weight => Algorithm.Securities.Count == 0 ? default(double) : 1d / Algorithm.Securities.Count;
[OneTimeSetUp]
public virtual void SetUp()
{
Algorithm = new QCAlgorithm();
Algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(Algorithm));
}
[TearDown]
public void TearDown() => Algorithm.Insights.Clear(Algorithm.Securities.Keys.ToArray());
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void AutomaticallyRemoveInvestedWithoutNewInsights(Language language)
{
SetPortfolioConstruction(language);
// Let's create a position for SPY
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Up, Algorithm.UtcTime) };
foreach (var target in Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights))
{
var holding = Algorithm.Portfolio[target.Symbol];
holding.SetHoldings(holding.Price, target.Quantity);
Algorithm.Portfolio.SetCash(StartingCash - holding.HoldingsValue);
}
SetUtcTime(Algorithm.UtcTime.AddDays(2));
var expectedTargets = new List<IPortfolioTarget> { new PortfolioTarget(Symbols.SPY, 0) };
// Create target from an empty insights array
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, new Insight[0]);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void DelistedSecurityEmitsFlatTargetWithoutNewInsights(Language language)
{
SetPortfolioConstruction(language);
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Down, Algorithm.UtcTime) };
var targets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights).ToList();
Assert.AreEqual(1, targets.Count);
var changes = SecurityChangesTests.RemovedNonInternal(Algorithm.Securities[Symbols.SPY]);
Algorithm.PortfolioConstruction.OnSecuritiesChanged(Algorithm, changes);
var expectedTargets = new List<IPortfolioTarget> { new PortfolioTarget(Symbols.SPY, 0) };
// Create target from an empty insights array
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, new Insight[0]);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void DoesNotReturnTargetsIfSecurityPriceIsZero(Language language)
{
var algorithm = new QCAlgorithm();
algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(algorithm));
algorithm.AddEquity(Symbols.SPY.Value);
algorithm.SetDateTime(DateTime.MinValue.ConvertToUtc(Algorithm.TimeZone));
SetPortfolioConstruction(language);
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Up, algorithm.UtcTime) };
var actualTargets = algorithm.PortfolioConstruction.CreateTargets(algorithm, insights);
Assert.AreEqual(0, actualTargets.Count());
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void DoesNotThrowWithAlternativeOverloads(Language language)
{
Assert.DoesNotThrow(() => SetPortfolioConstruction(language, Resolution.Minute));
Assert.DoesNotThrow(() => SetPortfolioConstruction(language, TimeSpan.FromDays(1)));
Assert.DoesNotThrow(() => SetPortfolioConstruction(language, Expiry.EndOfWeek));
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void EmptyInsightsReturnsEmptyTargets(Language language)
{
SetPortfolioConstruction(language);
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, new Insight[0]);
Assert.AreEqual(0, actualTargets.Count());
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void LongTermInsightPreservesPosition(Language language)
{
SetPortfolioConstruction(language);
// First emit long term insight
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Down, Algorithm.UtcTime) };
var targets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights).ToList();
Assert.AreEqual(1, targets.Count);
// One minute later, emits short term insight
SetUtcTime(Algorithm.UtcTime.AddMinutes(1));
insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Up, Algorithm.UtcTime, Time.OneMinute) };
targets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights).ToList();
Assert.AreEqual(1, targets.Count);
// One minute later, emit empty insights array
SetUtcTime(Algorithm.UtcTime.AddMinutes(1.1));
var expectedTargets = GetTargetsForSPY();
// Create target from an empty insights array
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, new Insight[0]);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public abstract void AutomaticallyRemoveInvestedWithNewInsights(Language language, InsightDirection direction);
[Test]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public abstract void DelistedSecurityEmitsFlatTargetWithNewInsights(Language language, InsightDirection direction);
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public abstract void FlatDirectionNotAccountedToAllocation(Language language, InsightDirection direction);
public abstract IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, dynamic paramenter = null);
public abstract Insight GetInsight(Symbol symbol, InsightDirection direction, DateTime generatedTimeUtc, TimeSpan? period = null, double? weight = 0.01);
public void AssertTargets(IEnumerable<IPortfolioTarget> expectedTargets, IEnumerable<IPortfolioTarget> actualTargets)
{
var list = actualTargets.ToList();
Assert.AreEqual(expectedTargets.Count(), list.Count);
foreach (var expected in expectedTargets)
{
var actual = list.FirstOrDefault(x => x.Symbol == expected.Symbol);
Assert.IsNotNull(actual);
Assert.AreEqual(expected.Quantity, actual.Quantity);
}
}
protected Security GetSecurity(Symbol symbol) =>
new Equity(
symbol,
SecurityExchangeHours.AlwaysOpen(DateTimeZone.Utc),
new Cash(Currencies.USD, 0, 1),
SymbolProperties.GetDefault(Currencies.USD),
ErrorCurrencyConverter.Instance,
RegisteredSecurityDataTypesProvider.Null,
new SecurityCache()
);
public virtual List<IPortfolioTarget> GetTargetsForSPY()
{
return new List<IPortfolioTarget> { PortfolioTarget.Percent(Algorithm, Symbols.SPY, -1m) };
}
protected void SetPortfolioConstruction(Language language, dynamic paramenter = null)
{
var model = GetPortfolioConstructionModel(language, paramenter ?? Resolution.Daily);
Algorithm.SetPortfolioConstruction(model);
foreach (var kvp in Algorithm.Portfolio)
{
kvp.Value.SetHoldings(kvp.Value.Price, 0);
}
Algorithm.Portfolio.SetCash(StartingCash);
SetUtcTime(new DateTime(2018, 7, 31));
var changes = SecurityChangesTests.AddedNonInternal(Algorithm.Securities.Values.ToArray());
Algorithm.PortfolioConstruction.OnSecuritiesChanged(Algorithm, changes);
}
protected void SetUtcTime(DateTime dateTime) => Algorithm.SetDateTime(dateTime.ConvertToUtc(Algorithm.TimeZone));
}
}
Tests/Algorithm/Framework/Portfolio/BlackLittermanOptimizationPortfolioConstructionModelTests.cs
+546
View File
@@ -0,0 +1,546 @@
/*
* 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 Accord.Math;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Securities;
using System;
using System.Linq;
using QuantConnect.Algorithm;
using QuantConnect.Tests.Engine.DataFeeds;
using System.Collections.Generic;
using QuantConnect.Tests.Common.Data.UniverseSelection;
using QuantConnect.Interfaces;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class BlackLittermanOptimizationPortfolioConstructionModelTests
{
private QCAlgorithm _algorithm;
private Insight[] _view1Insights;
private Insight[] _view2Insights;
[SetUp]
public void SetUp()
{
_algorithm = new QCAlgorithm();
_algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(_algorithm));
SetUtcTime(new DateTime(2018, 8, 7));
// Germany will outperform the other European markets by 5%
_view1Insights = new[]
{
GetInsight("View 1", "AUS", 0),
GetInsight("View 1", "CAN", 0),
GetInsight("View 1", "FRA", -0.01475),
GetInsight("View 1", "GER", 0.05000),
GetInsight("View 1", "JAP", 0),
GetInsight("View 1", "UK" , -0.03525),
GetInsight("View 1", "USA", 0)
};
// Canadian Equities will outperform US equities by 3 %
_view2Insights = new[]
{
GetInsight("View 2", "AUS", 0),
GetInsight("View 2", "CAN", 0.03),
GetInsight("View 2", "FRA", 0),
GetInsight("View 2", "GER", 0),
GetInsight("View 2", "JAP", 0),
GetInsight("View 2", "UK" , 0),
GetInsight("View 2", "USA", -0.03)
};
foreach (var symbol in _view1Insights.Select(x => x.Symbol))
{
var security = GetSecurity(symbol, Resolution.Daily);
security.SetMarketPrice(new Tick(_algorithm.Time, symbol, 1m, 1m));
_algorithm.Securities.Add(symbol, security);
}
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void EmptyInsightsReturnsEmptyTargets(Language language)
{
SetPortfolioConstruction(language);
var insights = new Insight[0];
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
Assert.AreEqual(0, actualTargets.Count());
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void OneViewTest(Language language)
{
SetPortfolioConstruction(language);
// Add outdated insight to check if only the latest one was considered
var outdatedInsight = GetInsight("View 1", "CAN", 0.05);
outdatedInsight.GeneratedTimeUtc -= TimeSpan.FromHours(1);
outdatedInsight.CloseTimeUtc -= TimeSpan.FromHours(1);
// Results from http://www.blacklitterman.org/code/hl_py.html (View 1)
var expectedTargets = new[]
{
PortfolioTarget.Percent(_algorithm, GetSymbol("AUS"), 0.0152381),
PortfolioTarget.Percent(_algorithm, GetSymbol("CAN"), 0.02095238),
PortfolioTarget.Percent(_algorithm, GetSymbol("FRA"), -0.03948465),
PortfolioTarget.Percent(_algorithm, GetSymbol("GER"), 0.35410454),
PortfolioTarget.Percent(_algorithm, GetSymbol("JAP"), 0.11047619),
PortfolioTarget.Percent(_algorithm, GetSymbol("UK"), -0.09461989),
PortfolioTarget.Percent(_algorithm, GetSymbol("USA"), 0.58571429)
};
var insights = _view1Insights.Concat(new[] { outdatedInsight }).ToArray();
Clear();
_algorithm.Insights.AddRange(insights);
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
Assert.AreEqual(expectedTargets.Length, actualTargets.Count());
foreach (var expected in expectedTargets)
{
var actual = actualTargets.FirstOrDefault(x => x.Symbol == expected.Symbol);
Assert.IsNotNull(actual);
Assert.AreEqual(expected.Quantity, actual.Quantity);
}
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void TwoViewsTest(Language language)
{
SetPortfolioConstruction(language);
// Results from http://www.blacklitterman.org/code/hl_py.html (View 1+2)
var expectedTargets = new[]
{
PortfolioTarget.Percent(_algorithm, GetSymbol("AUS"), 0.0152381),
PortfolioTarget.Percent(_algorithm, GetSymbol("CAN"), 0.41863571),
PortfolioTarget.Percent(_algorithm, GetSymbol("FRA"), -0.03409321),
PortfolioTarget.Percent(_algorithm, GetSymbol("GER"), 0.33582847),
PortfolioTarget.Percent(_algorithm, GetSymbol("JAP"), 0.11047619),
PortfolioTarget.Percent(_algorithm, GetSymbol("UK"), -0.08173526),
PortfolioTarget.Percent(_algorithm, GetSymbol("USA"), 0.18803095)
};
// Add outdated insight to check if only the latest one was considered
var outdatedInsight = GetInsight("View 2", "USA", 0.05);
outdatedInsight.GeneratedTimeUtc -= TimeSpan.FromHours(1);
outdatedInsight.CloseTimeUtc -= TimeSpan.FromHours(1);
var insights = _view1Insights.Concat(_view2Insights).Concat(new[] { outdatedInsight });
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights.ToArray());
Assert.AreEqual(expectedTargets.Length, actualTargets.Count());
foreach (var expected in expectedTargets)
{
var actual = actualTargets.FirstOrDefault(x => x.Symbol == expected.Symbol);
Assert.IsNotNull(actual);
Assert.AreEqual(expected.Quantity, actual.Quantity);
}
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void OneViewDimensionTest(Language language)
{
SetPortfolioConstruction(language);
if (language == Language.CSharp)
{
double[,] P;
double[] Q;
((BLOPCM)_algorithm.PortfolioConstruction).TestTryGetViews(_view1Insights, out P, out Q);
Assert.AreEqual(P.GetLength(0), 1);
Assert.AreEqual(P.GetLength(1), 7);
Assert.AreEqual(Q.GetLength(0), 1);
return;
}
using (Py.GIL())
{
var name = nameof(BLOPCM);
var instance = PyModule.FromString(name, GetPythonBLOPCM()).GetAttr(name).Invoke(((int)PortfolioBias.LongShort).ToPython());
var result = PyList.AsList(instance.InvokeMethod("get_views", _view1Insights.ToPython()));
Assert.AreEqual(result[0].Length(), 1);
Assert.AreEqual(result[0][0].Length(), 7);
Assert.AreEqual(result[1].Length(), 1);
}
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void TwoViewsDimensionTest(Language language)
{
SetPortfolioConstruction(language);
// Test if a symbol has no view in one of the source models
var insights = _view1Insights.Concat(_view2Insights.Skip(1)).ToList();
if (language == Language.CSharp)
{
double[,] P;
double[] Q;
((BLOPCM)_algorithm.PortfolioConstruction).TestTryGetViews(insights, out P, out Q);
Assert.AreEqual(P.GetLength(0), 2);
Assert.AreEqual(P.GetLength(1), 7);
Assert.AreEqual(Q.GetLength(0), 2);
return;
}
using (Py.GIL())
{
var name = nameof(BLOPCM);
var instance = PyModule.FromString(name, GetPythonBLOPCM()).GetAttr(name).Invoke(((int)PortfolioBias.LongShort).ToPython());
var result = PyList.AsList(instance.InvokeMethod("get_views", insights.ToPython()));
Assert.AreEqual(result[0].Length(), 2);
Assert.AreEqual(result[0][0].Length(), 7);
Assert.AreEqual(result[1].Length(), 2);
}
}
[Test]
[TestCase(Language.CSharp, 11, true)]
[TestCase(Language.CSharp, -11, true)]
[TestCase(Language.CSharp, 0.001d, true)]
[TestCase(Language.CSharp, -0.001d, true)]
[TestCase(Language.CSharp, 0.1, false)]
[TestCase(Language.CSharp, -0.1, false)]
[TestCase(Language.CSharp, 0.011d, false)]
[TestCase(Language.CSharp, -0.011d, false)]
[TestCase(Language.CSharp, 0, true)]
[TestCase(Language.Python, 0, true)]
[TestCase(Language.Python, 11, true)]
[TestCase(Language.Python, -11, true)]
[TestCase(Language.Python, 0.001d, true)]
[TestCase(Language.Python, -0.001d, true)]
[TestCase(Language.Python, 0.1, false)]
[TestCase(Language.Python, -0.1, false)]
[TestCase(Language.Python, 0.011d, false)]
[TestCase(Language.Python, -0.011d, false)]
public void IgnoresInsightsWithInvalidMagnitudeValue(Language language, double magnitude, bool expectZero)
{
SetPortfolioConstruction(language);
_algorithm.Settings.MaxAbsolutePortfolioTargetPercentage = 10;
_algorithm.Settings.MinAbsolutePortfolioTargetPercentage = 0.01m;
Clear();
var insights = new[]
{
GetInsight("View 1", "AUS", magnitude),
GetInsight("View 1", "CAN", magnitude),
GetInsight("View 1", "FRA", magnitude),
GetInsight("View 1", "GER", magnitude),
GetInsight("View 1", "JAP", magnitude),
GetInsight("View 1", "UK" , magnitude),
GetInsight("View 1", "USA", magnitude)
};
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
if (expectZero)
{
Assert.AreEqual(0, actualTargets.Count());
}
else
{
Assert.AreNotEqual(0, actualTargets.Count());
}
}
[TestCase(Language.CSharp, PortfolioBias.Long)]
[TestCase(Language.Python, PortfolioBias.Long)]
[TestCase(Language.CSharp, PortfolioBias.Short)]
[TestCase(Language.Python, PortfolioBias.Short)]
public void PortfolioBiasIsRespected(Language language, PortfolioBias bias)
{
SetPortfolioConstruction(language, bias);
var insights = new[]
{
GetInsight("View 1", "AUS", -10.1),
GetInsight("View 1", "CAN", -0.1),
GetInsight("View 1", "FRA", 0.1),
GetInsight("View 1", "GER", -0.1),
GetInsight("View 1", "JAP", -0.1),
GetInsight("View 1", "UK" , 0.1),
GetInsight("View 1", "USA", -0.1)
};
var createdValidTarget = false;
foreach (var target in _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights))
{
QuantConnect.Logging.Log.Trace($"{target.Symbol}: {target.Quantity}");
if (target.Quantity == 0)
{
continue;
}
createdValidTarget = true;
Assert.AreEqual(Math.Sign((int)bias), Math.Sign(target.Quantity));
}
Assert.IsTrue(createdValidTarget);
}
[Test]
public void NewSymbolPortfolioConstructionModelDoesNotThrow()
{
var algorithm = new QCAlgorithm();
var timezone = algorithm.TimeZone;
algorithm.SetDateTime(new DateTime(2018, 8, 7).ConvertToUtc(timezone));
algorithm.SetPortfolioConstruction(new NewSymbolPortfolioConstructionModel());
var spySymbol = Symbols.SPY;
var spy = GetSecurity(spySymbol, Resolution.Daily);
spy.SetMarketPrice(new Tick(algorithm.Time, spySymbol, 1m, 1m));
algorithm.Securities.Add(spySymbol, spy);
algorithm.PortfolioConstruction.OnSecuritiesChanged(algorithm, SecurityChangesTests.AddedNonInternal(spy));
var insights = new[] { Insight.Price(spySymbol, Time.OneMinute, InsightDirection.Up, .1) };
Assert.DoesNotThrow(() => algorithm.PortfolioConstruction.CreateTargets(algorithm, insights));
algorithm.SetDateTime(algorithm.Time.AddDays(1));
var aaplSymbol = Symbols.AAPL;
var aapl = GetSecurity(spySymbol, Resolution.Daily);
aapl.SetMarketPrice(new Tick(algorithm.Time, aaplSymbol, 1m, 1m));
algorithm.Securities.Add(aaplSymbol, aapl);
algorithm.PortfolioConstruction.OnSecuritiesChanged(algorithm, SecurityChangesTests.AddedNonInternal(aapl));
insights = new[] { spySymbol, aaplSymbol }
.Select(x => Insight.Price(x, Time.OneMinute, InsightDirection.Up, .1)).ToArray();
Assert.DoesNotThrow(() => algorithm.PortfolioConstruction.CreateTargets(algorithm, insights));
}
private Security GetSecurity(Symbol symbol, Resolution resolution)
{
var timezone = _algorithm.TimeZone;
var exchangeHours = SecurityExchangeHours.AlwaysOpen(timezone);
var config = new SubscriptionDataConfig(typeof(TradeBar), symbol, resolution, timezone, timezone, true, false, false);
return new Security(
exchangeHours,
config,
new Cash(Currencies.USD, 0, 1),
SymbolProperties.GetDefault(Currencies.USD),
ErrorCurrencyConverter.Instance,
RegisteredSecurityDataTypesProvider.Null,
new SecurityCache()
);
}
private Symbol GetSymbol(string ticker) => Symbol.Create(ticker, SecurityType.Equity, Market.USA);
private Insight GetInsight(string SourceModel, string ticker, double magnitude)
{
var period = Time.OneDay;
var direction = (InsightDirection)Math.Sign(magnitude);
var insight = Insight.Price(GetSymbol(ticker), period, direction, magnitude, sourceModel: SourceModel);
insight.GeneratedTimeUtc = _algorithm.UtcTime;
insight.CloseTimeUtc = _algorithm.UtcTime.Add(insight.Period);
_algorithm.Insights.Add(insight);
return insight;
}
private void SetPortfolioConstruction(Language language, PortfolioBias portfolioBias = PortfolioBias.LongShort)
{
_algorithm.SetPortfolioConstruction(new BLOPCM(new UnconstrainedMeanVariancePortfolioOptimizer(), portfolioBias));
if (language == Language.Python)
{
try
{
using (Py.GIL())
{
var name = nameof(BLOPCM);
var instance = PyModule.FromString(name, GetPythonBLOPCM()).GetAttr(name).Invoke(((int)portfolioBias).ToPython());
var model = new PortfolioConstructionModelPythonWrapper(instance);
_algorithm.SetPortfolioConstruction(model);
}
}
catch (Exception e)
{
Assert.Ignore(e.Message);
}
}
var changes = SecurityChangesTests.AddedNonInternal(_algorithm.Securities.Values.ToList().ToArray());
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, changes);
}
private void SetUtcTime(DateTime dateTime)
{
_algorithm.SetDateTime(dateTime.ConvertToUtc(_algorithm.TimeZone));
}
private class BLOPCM : BlackLittermanOptimizationPortfolioConstructionModel
{
public BLOPCM(IPortfolioOptimizer optimizer, PortfolioBias portfolioBias)
: base(optimizer: optimizer, portfolioBias: portfolioBias)
{
}
public override double[] GetEquilibriumReturns(double[,] returns, out double[,] Σ)
{
// Take the values from He & Litterman, 1999.
var C = new[,]
{
{ 1.000, 0.488, 0.478, 0.515, 0.439, 0.512, 0.491 },
{ 0.488, 1.000, 0.664, 0.655, 0.310, 0.608, 0.779 },
{ 0.478, 0.664, 1.000, 0.861, 0.355, 0.783, 0.668 },
{ 0.515, 0.655, 0.861, 1.000, 0.354, 0.777, 0.653 },
{ 0.439, 0.310, 0.355, 0.354, 1.000, 0.405, 0.306 },
{ 0.512, 0.608, 0.783, 0.777, 0.405, 1.000, 0.652 },
{ 0.491, 0.779, 0.668, 0.653, 0.306, 0.652, 1.000 }
};
var σ = new[] { 0.160, 0.203, 0.248, 0.271, 0.210, 0.200, 0.187 };
var w = new[] { 0.016, 0.022, 0.052, 0.055, 0.116, 0.124, 0.615 };
var delta = 2.5;
// Equilibrium covariance matrix
Σ = Elementwise.Multiply(C, σ.Outer(σ));
return w.Dot(Σ.Multiply(delta));
}
public bool TestTryGetViews(ICollection<Insight> insights, out double[,] P, out double[] Q)
{
return base.TryGetViews(insights, out P, out Q);
}
public override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
{
}
}
private string GetPythonBLOPCM()
{
return @"
from AlgorithmImports import *
from Portfolio.BlackLittermanOptimizationPortfolioConstructionModel import BlackLittermanOptimizationPortfolioConstructionModel
from Portfolio.UnconstrainedMeanVariancePortfolioOptimizer import UnconstrainedMeanVariancePortfolioOptimizer
def GetSymbol(ticker):
return str(Symbol.Create(ticker, SecurityType.Equity, Market.USA))
class BLOPCM(BlackLittermanOptimizationPortfolioConstructionModel):
def __init__(self, portfolioBias):
super().__init__(portfolio_bias = portfolioBias, optimizer = UnconstrainedMeanVariancePortfolioOptimizer())
def get_equilibrium_return(self, returns):
# Take the values from He & Litterman, 1999.
weq = np.array([0.016, 0.022, 0.052, 0.055, 0.116, 0.124, 0.615])
C = np.array([[ 1.000, 0.488, 0.478, 0.515, 0.439, 0.512, 0.491],
[0.488, 1.000, 0.664, 0.655, 0.310, 0.608, 0.779],
[0.478, 0.664, 1.000, 0.861, 0.355, 0.783, 0.668],
[0.515, 0.655, 0.861, 1.000, 0.354, 0.777, 0.653],
[0.439, 0.310, 0.355, 0.354, 1.000, 0.405, 0.306],
[0.512, 0.608, 0.783, 0.777, 0.405, 1.000, 0.652],
[0.491, 0.779, 0.668, 0.653, 0.306, 0.652, 1.000]])
Sigma = np.array([0.160, 0.203, 0.248, 0.271, 0.210, 0.200, 0.187])
refPi = np.array([0.039, 0.069, 0.084, 0.090, 0.043, 0.068, 0.076])
assets= [GetSymbol(x) for x in ['AUS', 'CAN', 'FRA', 'GER', 'JAP', 'UK', 'USA']]
delta = 2.5
# Equilibrium covariance matrix
V = np.multiply(np.outer(Sigma,Sigma), C)
return weq.dot(V * delta), pd.DataFrame(V, columns=assets, index=assets)
def on_securities_changed(self, algorithm, changes):
pass";
}
private void Clear() => _algorithm.Insights.Clear(_algorithm.Securities.Keys.ToArray());
private class NewSymbolPortfolioConstructionModel : BlackLittermanOptimizationPortfolioConstructionModel
{
private readonly Dictionary<Symbol, ReturnsSymbolData> _symbolDataDict = new Dictionary<Symbol, ReturnsSymbolData>();
public override IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
{
// Updates the ReturnsSymbolData with insights
foreach (var insight in insights)
{
ReturnsSymbolData symbolData;
if (_symbolDataDict.TryGetValue(insight.Symbol, out symbolData))
{
symbolData.Add(algorithm.Time, .1m);
}
}
double[,] returns = null;
Assert.DoesNotThrow(() => returns = _symbolDataDict.FormReturnsMatrix(insights.Select(x => x.Symbol)));
// Calculate posterior estimate of the mean and uncertainty in the mean
double[,] Σ;
var Π = GetEquilibriumReturns(returns, out Σ);
Assert.IsFalse(double.IsNaN(Π[0]));
return Enumerable.Empty<PortfolioTarget>();
}
public override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
{
const int period = 2;
var reference = algorithm.Time.AddDays(-period);
foreach (var security in changes.AddedSecurities)
{
var symbol = security.Symbol;
var symbolData = new ReturnsSymbolData(symbol, 1, period);
for (var i = 0; i <= period * 2; i++)
{
symbolData.Update(reference.AddDays(i), i);
}
_symbolDataDict[symbol] = symbolData;
}
}
}
}
}
Tests/Algorithm/Framework/Portfolio/ConfidenceWeightedPortfolioConstructionModelTests.cs
+438
View File
@@ -0,0 +1,438 @@
/*
* 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 System.Linq;
using NodaTime;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Orders.Fees;
using QuantConnect.Securities;
using QuantConnect.Securities.Equity;
using QuantConnect.Tests.Common.Data.UniverseSelection;
using QuantConnect.Tests.Engine.DataFeeds;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class ConfidenceWeightedPortfolioConstructionModelTests
{
private QCAlgorithm _algorithm;
private const decimal _startingCash = 100000;
private const double Confidence = 0.01;
[OneTimeSetUp]
public void SetUp()
{
_algorithm = new QCAlgorithm();
_algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(_algorithm));
var prices = new Dictionary<Symbol, decimal>
{
{ Symbol.Create("AIG", SecurityType.Equity, Market.USA), 55.22m },
{ Symbol.Create("IBM", SecurityType.Equity, Market.USA), 145.17m },
{ Symbol.Create("SPY", SecurityType.Equity, Market.USA), 281.79m },
};
foreach (var kvp in prices)
{
var symbol = kvp.Key;
var security = GetSecurity(symbol);
security.SetMarketPrice(new Tick(_algorithm.Time, symbol, kvp.Value, kvp.Value));
_algorithm.Securities.Add(symbol, security);
}
}
[TearDown]
public void TearDown() => _algorithm.Insights.Clear(_algorithm.Securities.Keys.ToArray());
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void EmptyInsightsReturnsEmptyTargets(Language language)
{
SetPortfolioConstruction(language, _algorithm);
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]);
Assert.AreEqual(0, actualTargets.Count());
}
[Test]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public void InsightsReturnsTargetsConsistentWithDirection(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language, _algorithm);
var amount = _algorithm.Portfolio.TotalPortfolioValue * (decimal)Confidence;
var expectedTargets = _algorithm.Securities
.Select(x => new PortfolioTarget(x.Key, (int)direction
* Math.Floor(amount * (1 - _algorithm.Settings.FreePortfolioValuePercentage)
/ x.Value.Price)));
var insights = _algorithm.Securities.Keys.Select(x => GetInsight(x, direction, _algorithm.UtcTime));
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights.ToArray());
AssertTargets(expectedTargets, actualTargets);
}
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public void FlatDirectionNotAccountedToAllocation(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language, _algorithm);
// Modifying fee model for a constant one so numbers are simplified
foreach (var security in _algorithm.Securities)
{
security.Value.FeeModel = new ConstantFeeModel(1);
}
// Equity, minus $1 for fees
var amount = (_algorithm.Portfolio.TotalPortfolioValue - 1 * (_algorithm.Securities.Count - 1)) * (decimal)Confidence;
var expectedTargets = _algorithm.Securities.Select(x =>
{
// Expected target quantity for SPY is zero, since its insight will have flat direction
var quantity = x.Key.Value == "SPY" ? 0 : (int)direction
* Math.Floor(amount * (1 - _algorithm.Settings.FreePortfolioValuePercentage)
/ x.Value.Price);
return new PortfolioTarget(x.Key, quantity);
});
var insights = _algorithm.Securities.Keys.Select(x =>
{
// SPY insight direction is flat
var actualDirection = x.Value == "SPY" ? InsightDirection.Flat : direction;
return GetInsight(x, actualDirection, _algorithm.UtcTime);
});
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights.ToArray());
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public void AutomaticallyRemoveInvestedWithNewInsights(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language, _algorithm);
// Let's create a position for SPY
var insights = new[] { GetInsight(Symbols.SPY, direction, _algorithm.UtcTime) };
foreach (var target in _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights))
{
var holding = _algorithm.Portfolio[target.Symbol];
holding.SetHoldings(holding.Price, target.Quantity);
_algorithm.Portfolio.SetCash(_startingCash - holding.HoldingsValue);
}
SetUtcTime(_algorithm.UtcTime.AddDays(2));
var amount = _algorithm.Portfolio.TotalPortfolioValue * (decimal)Confidence;
var expectedTargets = _algorithm.Securities.Select(x =>
{
// Expected target quantity for SPY is zero, since it will be removed
var quantity = x.Key.Value == "SPY" ? 0 : (int)direction
* Math.Floor(amount * (1 - _algorithm.Settings.FreePortfolioValuePercentage)
/ x.Value.Price);
return new PortfolioTarget(x.Key, quantity);
});
// Do no include SPY in the insights
insights = _algorithm.Securities.Keys.Where(x => x.Value != "SPY")
.Select(x => GetInsight(x, direction, _algorithm.UtcTime)).ToArray();
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void AutomaticallyRemoveInvestedWithoutNewInsights(Language language)
{
SetPortfolioConstruction(language, _algorithm);
// Let's create a position for SPY
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Up, _algorithm.UtcTime) };
foreach (var target in _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights))
{
var holding = _algorithm.Portfolio[target.Symbol];
holding.SetHoldings(holding.Price, target.Quantity);
_algorithm.Portfolio.SetCash(_startingCash - holding.HoldingsValue);
}
SetUtcTime(_algorithm.UtcTime.AddDays(2));
var expectedTargets = new List<IPortfolioTarget> { new PortfolioTarget(Symbols.SPY, 0) };
// Create target from an empty insights array
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void LongTermInsightPreservesPosition(Language language)
{
SetPortfolioConstruction(language, _algorithm);
// First emit long term insight
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime) };
var targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(1, targets.Count);
// One minute later, emits short term insight
SetUtcTime(_algorithm.UtcTime.AddMinutes(1));
insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Up, _algorithm.UtcTime, Time.OneMinute) };
targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(1, targets.Count);
// One minute later, emit empty insights array
SetUtcTime(_algorithm.UtcTime.AddMinutes(1.1));
var expectedTargets = new List<IPortfolioTarget> { PortfolioTarget.Percent(_algorithm, Symbols.SPY, -1m * (decimal)Confidence) };
// Create target from an empty insights array
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void DelistedSecurityEmitsFlatTargetWithoutNewInsights(Language language)
{
SetPortfolioConstruction(language, _algorithm);
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime) };
var targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(1, targets.Count);
var changes = SecurityChangesTests.RemovedNonInternal(_algorithm.Securities[Symbols.SPY]);
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, changes);
var expectedTargets = new List<IPortfolioTarget> { new PortfolioTarget(Symbols.SPY, 0) };
// Create target from an empty insights array
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, new Insight[0]);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public void DelistedSecurityEmitsFlatTargetWithNewInsights(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language, _algorithm);
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime) };
var targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(1, targets.Count);
// Removing SPY should clear the key in the insight collection
var changes = SecurityChangesTests.RemovedNonInternal(_algorithm.Securities[Symbols.SPY]);
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, changes);
var amount = _algorithm.Portfolio.TotalPortfolioValue * (decimal)Confidence;
var expectedTargets = _algorithm.Securities.Select(x =>
{
// Expected target quantity for SPY is zero, since it will be removed
var quantity = x.Key.Value == "SPY" ? 0 : (int)direction
* Math.Floor(amount * (1 - _algorithm.Settings.FreePortfolioValuePercentage)
/ x.Value.Price);
return new PortfolioTarget(x.Key, quantity);
});
// Do no include SPY in the insights
insights = _algorithm.Securities.Keys.Where(x => x.Value != "SPY")
.Select(x => GetInsight(x, direction, _algorithm.UtcTime)).ToArray();
// Create target from an empty insights array
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void WeightsProportionally(Language language)
{
SetPortfolioConstruction(language, _algorithm);
// create two insights whose confidences sums up to 2
var insights = new[]
{
GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime, confidence:1),
GetInsight(Symbol.Create("IBM", SecurityType.Equity, Market.USA),
InsightDirection.Down, _algorithm.UtcTime, confidence:1)
};
// they will each share, proportionally, the total portfolio value
var amount = _algorithm.Portfolio.TotalPortfolioValue * (decimal)0.5;
var expectedTargets = _algorithm.Securities.Where(pair => insights.Any(insight => pair.Key == insight.Symbol))
.Select(x => new PortfolioTarget(x.Key, (int)InsightDirection.Down
* Math.Floor(amount * (1 - _algorithm.Settings.FreePortfolioValuePercentage)
/ x.Value.Price)));
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(2, actualTargets.Count);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void GeneratesNoTargetsForInsightsWithNoConfidence(Language language)
{
SetPortfolioConstruction(language, _algorithm);
var insights = new[]
{
GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime, confidence:null)
};
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(0, actualTargets.Count);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void GeneratesZeroTargetForZeroInsightConfidence(Language language)
{
SetPortfolioConstruction(language, _algorithm);
var insights = new[]
{
GetInsight(Symbols.SPY, InsightDirection.Down, _algorithm.UtcTime, confidence:0)
};
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(1, actualTargets.Count);
AssertTargets(actualTargets, new[] {new PortfolioTarget(Symbols.SPY, 0)});
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void DoesNotThrowWithAlternativeOverloads(Language language)
{
Assert.DoesNotThrow(() => SetPortfolioConstruction(language, _algorithm, Resolution.Minute));
Assert.DoesNotThrow(() => SetPortfolioConstruction(language, _algorithm, TimeSpan.FromDays(1)));
Assert.DoesNotThrow(() => SetPortfolioConstruction(language, _algorithm, Expiry.EndOfWeek));
}
private Security GetSecurity(Symbol symbol)
{
var config = SecurityExchangeHours.AlwaysOpen(DateTimeZone.Utc);
return new Equity(
symbol,
config,
new Cash(Currencies.USD, 0, 1),
SymbolProperties.GetDefault(Currencies.USD),
ErrorCurrencyConverter.Instance,
RegisteredSecurityDataTypesProvider.Null,
new SecurityCache()
);
}
private Insight GetInsight(Symbol symbol, InsightDirection direction, DateTime generatedTimeUtc, TimeSpan? period = null, double? confidence = Confidence)
{
period ??= TimeSpan.FromDays(1);
var insight = Insight.Price(symbol, period.Value, direction, confidence: confidence);
insight.GeneratedTimeUtc = generatedTimeUtc;
insight.CloseTimeUtc = generatedTimeUtc.Add(period.Value);
_algorithm.Insights.Add(insight);
return insight;
}
private void SetPortfolioConstruction(Language language, QCAlgorithm algorithm, dynamic paramenter = null)
{
paramenter = paramenter ?? Resolution.Daily;
algorithm.SetPortfolioConstruction(new ConfidenceWeightedPortfolioConstructionModel(paramenter));
if (language == Language.Python)
{
using (Py.GIL())
{
var name = nameof(ConfidenceWeightedPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name).Invoke(((object)paramenter).ToPython());
var model = new PortfolioConstructionModelPythonWrapper(instance);
algorithm.SetPortfolioConstruction(model);
}
}
foreach (var kvp in _algorithm.Portfolio)
{
kvp.Value.SetHoldings(kvp.Value.Price, 0);
}
_algorithm.Portfolio.SetCash(_startingCash);
SetUtcTime(new DateTime(2018, 7, 31));
var changes = SecurityChangesTests.AddedNonInternal(_algorithm.Securities.Values.ToArray());
algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, changes);
}
private void SetUtcTime(DateTime dateTime)
{
_algorithm.SetDateTime(dateTime.ConvertToUtc(_algorithm.TimeZone));
}
private void AssertTargets(IEnumerable<IPortfolioTarget> expectedTargets, IEnumerable<IPortfolioTarget> actualTargets)
{
var list = actualTargets.ToList();
Assert.AreEqual(expectedTargets.Count(), list.Count);
foreach (var expected in expectedTargets)
{
var actual = list.FirstOrDefault(x => x.Symbol == expected.Symbol);
Assert.IsNotNull(actual);
Assert.AreEqual(expected.Quantity, actual.Quantity);
}
}
}
}
Tests/Algorithm/Framework/Portfolio/EqualWeightingPortfolioConstructionModelTests.cs
+243
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@@ -0,0 +1,243 @@
/*
* 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 NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Tests.Common.Data.UniverseSelection;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class EqualWeightingPortfolioConstructionModelTests : BaseWeightingPortfolioConstructionModelTests
{
public override double? Weight => Algorithm.Securities.Count == 0 ? default(double) : 1d / Algorithm.Securities.Count;
public virtual PortfolioBias PortfolioBias => PortfolioBias.LongShort;
[OneTimeSetUp]
public override void SetUp()
{
base.SetUp();
var prices = new Dictionary<Symbol, decimal>
{
{ Symbol.Create("AIG", SecurityType.Equity, Market.USA), 55.22m },
{ Symbol.Create("IBM", SecurityType.Equity, Market.USA), 145.17m },
{ Symbol.Create("SPY", SecurityType.Equity, Market.USA), 281.79m },
};
foreach (var kvp in prices)
{
var symbol = kvp.Key;
var security = GetSecurity(symbol);
security.SetMarketPrice(new Tick(Algorithm.Time, symbol, kvp.Value, kvp.Value));
Algorithm.Securities.Add(symbol, security);
}
}
[Test]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public override void AutomaticallyRemoveInvestedWithNewInsights(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language);
if (PortfolioBias != PortfolioBias.LongShort && (int)direction != (int)PortfolioBias)
{
direction = InsightDirection.Flat;
}
// Let's create a position for SPY
var insights = new[] { GetInsight(Symbols.SPY, direction, Algorithm.UtcTime) };
foreach (var target in Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights))
{
var holding = Algorithm.Portfolio[target.Symbol];
holding.SetHoldings(holding.Price, target.Quantity);
Algorithm.Portfolio.SetCash(StartingCash - holding.HoldingsValue);
}
SetUtcTime(Algorithm.UtcTime.AddDays(2));
// Equity will be divided by all securities minus 1, since SPY is already invested and we want to remove it
var amount = Algorithm.Portfolio.TotalPortfolioValue / (decimal)(1 / Weight - 1) *
(1 - Algorithm.Settings.FreePortfolioValuePercentage);
var expectedTargets = Algorithm.Securities.Select(x =>
{
// Expected target quantity for SPY is zero, since it will be removed
var quantity = x.Key.Value == "SPY" ? 0 : (int)direction * Math.Floor(amount / x.Value.Price);
return new PortfolioTarget(x.Key, quantity);
});
// Do no include SPY in the insights
insights = Algorithm.Securities.Keys.Where(x => x.Value != "SPY")
.Select(x => GetInsight(x, direction, Algorithm.UtcTime)).ToArray();
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public override void DelistedSecurityEmitsFlatTargetWithNewInsights(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language);
if (PortfolioBias != PortfolioBias.LongShort && (int)direction != (int)PortfolioBias)
{
direction = InsightDirection.Flat;
}
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Down, Algorithm.UtcTime) };
var targets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights).ToList();
Assert.AreEqual(1, targets.Count);
// Removing SPY should clear the key in the insight collection
var changes = SecurityChangesTests.RemovedNonInternal(Algorithm.Securities[Symbols.SPY]);
Algorithm.PortfolioConstruction.OnSecuritiesChanged(Algorithm, changes);
// Equity will be divided by all securities minus 1, since SPY is already invested and we want to remove it
var amount = Algorithm.Portfolio.TotalPortfolioValue / (decimal)(1 / Weight - 1) *
(1 - Algorithm.Settings.FreePortfolioValuePercentage);
var expectedTargets = Algorithm.Securities.Select(x =>
{
// Expected target quantity for SPY is zero, since it will be removed
var quantity = x.Key.Value == "SPY" ? 0 : (int)direction * Math.Floor(amount / x.Value.Price);
return new PortfolioTarget(x.Key, quantity);
});
// Do no include SPY in the insights
insights = Algorithm.Securities.Keys.Where(x => x.Value != "SPY")
.Select(x => GetInsight(x, direction, Algorithm.UtcTime)).ToArray();
// Create target from an empty insights array
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights);
AssertTargets(expectedTargets, actualTargets);
}
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public override void FlatDirectionNotAccountedToAllocation(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language);
if (PortfolioBias != PortfolioBias.LongShort && (int)direction != (int)PortfolioBias)
{
direction = InsightDirection.Flat;
}
// Equity, minus $1 for fees, will be divided by all securities minus 1, since its insight will have flat direction
var amount = (Algorithm.Portfolio.TotalPortfolioValue - 1 * (Algorithm.Securities.Count - 1)) * 1 /
(decimal)((1 / Weight) - 1) * (1 - Algorithm.Settings.FreePortfolioValuePercentage);
var expectedTargets = Algorithm.Securities.Select(x =>
{
// Expected target quantity for SPY is zero, since its insight will have flat direction
var quantity = x.Key.Value == "SPY" ? 0 : (int)direction * Math.Floor(amount / x.Value.Price);
return new PortfolioTarget(x.Key, quantity);
});
var insights = Algorithm.Securities.Keys.Select(x =>
{
// SPY insight direction is flat
var actualDirection = x.Value == "SPY" ? InsightDirection.Flat : direction;
return GetInsight(x, actualDirection, Algorithm.UtcTime);
});
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights.ToArray());
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp, InsightDirection.Up, 1)]
[TestCase(Language.CSharp, InsightDirection.Up, -1)]
[TestCase(Language.CSharp, InsightDirection.Down, 1)]
[TestCase(Language.CSharp, InsightDirection.Down, -1)]
[TestCase(Language.CSharp, InsightDirection.Flat, 1)]
[TestCase(Language.CSharp, InsightDirection.Flat, -1)]
[TestCase(Language.Python, InsightDirection.Up, 1)]
[TestCase(Language.Python, InsightDirection.Up, -1)]
[TestCase(Language.Python, InsightDirection.Down, 1)]
[TestCase(Language.Python, InsightDirection.Down, -1)]
[TestCase(Language.Python, InsightDirection.Flat, 1)]
[TestCase(Language.Python, InsightDirection.Flat, -1)]
public virtual void InsightsReturnsTargetsConsistentWithDirection(Language language, InsightDirection direction, int weightSign)
{
SetPortfolioConstruction(language);
if (PortfolioBias != PortfolioBias.LongShort && (int)direction != (int)PortfolioBias)
{
direction = InsightDirection.Flat;
}
// Equity will be divided by all securities
var amount = Algorithm.Portfolio.TotalPortfolioValue * (decimal)Weight *
(1 - Algorithm.Settings.FreePortfolioValuePercentage);
var expectedTargets = Algorithm.Securities
.Select(x => new PortfolioTarget(x.Key, (int)direction * Math.Floor(amount / x.Value.Price)));
var insights = Algorithm.Securities.Keys.Select(x => GetInsight(x, direction, Algorithm.UtcTime, weight: weightSign * Weight));
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights.ToArray());
AssertTargets(expectedTargets, actualTargets);
}
public override Insight GetInsight(Symbol symbol, InsightDirection direction, DateTime generatedTimeUtc, TimeSpan? period = null, double? weight = 0.01)
{
period ??= TimeSpan.FromDays(1);
var insight = Insight.Price(symbol, period.Value, direction, weight: Math.Max(0.01, Algorithm.Securities.Count));
insight.GeneratedTimeUtc = generatedTimeUtc;
insight.CloseTimeUtc = generatedTimeUtc.Add(period.Value);
Algorithm.Insights.Add(insight);
return insight;
}
public override IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, dynamic paramenter = null)
{
if (language == Language.CSharp)
{
return new EqualWeightingPortfolioConstructionModel(paramenter);
}
using (Py.GIL())
{
const string name = nameof(EqualWeightingPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name).Invoke(((object)paramenter).ToPython());
return new PortfolioConstructionModelPythonWrapper(instance);
}
}
}
}
Tests/Algorithm/Framework/Portfolio/InsightWeightingPortfolioConstructionModelTests.cs
+123
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/*
* 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 NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using System;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class InsightWeightingPortfolioConstructionModelTests : EqualWeightingPortfolioConstructionModelTests
{
private const double _weight = 0.01;
public override double? Weight => _weight;
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void WeightsProportionally(Language language)
{
SetPortfolioConstruction(language);
// create two insights whose weights sums up to 2
var insights = new[]
{
GetInsight(Symbols.SPY, InsightDirection.Up, Algorithm.UtcTime, weight:1),
GetInsight(Symbol.Create("IBM", SecurityType.Equity, Market.USA),
InsightDirection.Up, Algorithm.UtcTime, weight:1)
};
// they will each share, proportionally, the total portfolio value
var amount = Algorithm.Portfolio.TotalPortfolioValue * (decimal)0.5;
var expectedTargets = Algorithm.Securities.Where(pair => insights.Any(insight => pair.Key == insight.Symbol))
.Select(x => new PortfolioTarget(x.Key, (int)InsightDirection.Up
* Math.Floor(amount * (1 - Algorithm.Settings.FreePortfolioValuePercentage)
/ x.Value.Price)));
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights).ToList();
Assert.AreEqual(2, actualTargets.Count);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void GeneratesNoTargetsForInsightsWithNoWeight(Language language)
{
SetPortfolioConstruction(language);
var insights = new[]
{
GetInsight(Symbols.SPY, InsightDirection.Down, Algorithm.UtcTime, weight:null)
};
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights).ToList();
Assert.AreEqual(0, actualTargets.Count);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void GeneratesZeroTargetForZeroInsightWeight(Language language)
{
SetPortfolioConstruction(language);
var insights = new[]
{
GetInsight(Symbols.SPY, InsightDirection.Down, Algorithm.UtcTime, weight:0)
};
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights).ToList();
Assert.AreEqual(1, actualTargets.Count);
AssertTargets(actualTargets, new[] {new PortfolioTarget(Symbols.SPY, 0)});
}
public override IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, dynamic paramenter = null)
{
if (language == Language.CSharp)
{
return new InsightWeightingPortfolioConstructionModel(paramenter);
}
using (Py.GIL())
{
const string name = nameof(InsightWeightingPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name).Invoke(((object)paramenter).ToPython());
return new PortfolioConstructionModelPythonWrapper(instance);
}
}
public override Insight GetInsight(Symbol symbol, InsightDirection direction, DateTime generatedTimeUtc, TimeSpan? period = null, double? weight = _weight)
{
period ??= TimeSpan.FromDays(1);
var insight = Insight.Price(symbol, period.Value, direction, weight: weight);
insight.GeneratedTimeUtc = generatedTimeUtc;
insight.CloseTimeUtc = generatedTimeUtc.Add(period.Value);
Algorithm.Insights.Add(insight);
return insight;
}
public override List<IPortfolioTarget> GetTargetsForSPY()
{
return new List<IPortfolioTarget> { PortfolioTarget.Percent(Algorithm, Symbols.SPY, -_weight) };
}
}
}
Tests/Algorithm/Framework/Portfolio/LongOnlyEqualWeightingPortfolioConstructionModelTests.cs
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/*
* 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 NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm.Framework.Portfolio;
using System.Collections.Generic;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class LongOnlyEqualWeightingPortfolioConstructionModelTests : EqualWeightingPortfolioConstructionModelTests
{
public override PortfolioBias PortfolioBias => PortfolioBias.Long;
public override IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, dynamic paramenter = null)
{
if (language == Language.CSharp)
{
return new EqualWeightingPortfolioConstructionModel(paramenter, PortfolioBias.Long);
}
using (Py.GIL())
{
const string name = nameof(EqualWeightingPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name).Invoke(((object)paramenter).ToPython(), ((int) PortfolioBias.Long).ToPython());
return new PortfolioConstructionModelPythonWrapper(instance);
}
}
public override List<IPortfolioTarget> GetTargetsForSPY()
{
return new List<IPortfolioTarget> { PortfolioTarget.Percent(Algorithm, Symbols.SPY, 0m) };
}
}
}
Tests/Algorithm/Framework/Portfolio/LongOnlyInsightWeightingPortfolioConstructionModelTests.cs
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/*
* 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 NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm.Framework.Portfolio;
using System.Collections.Generic;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class LongOnlyInsightWeightingPortfolioConstructionModelTests : InsightWeightingPortfolioConstructionModelTests
{
public override PortfolioBias PortfolioBias => PortfolioBias.Long;
public override IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, dynamic paramenter = null)
{
if (language == Language.CSharp)
{
return new InsightWeightingPortfolioConstructionModel(paramenter, PortfolioBias.Long);
}
using (Py.GIL())
{
const string name = nameof(InsightWeightingPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name).Invoke(((object)paramenter).ToPython(), ((int)PortfolioBias.Long).ToPython());
return new PortfolioConstructionModelPythonWrapper(instance);
}
}
public override List<IPortfolioTarget> GetTargetsForSPY()
{
return new List<IPortfolioTarget> { PortfolioTarget.Percent(Algorithm, Symbols.SPY, 0m) };
}
}
}
Tests/Algorithm/Framework/Portfolio/MaximumSharpeRatioPortfolioOptimizerTests.cs
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/*
* 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 aaplicable 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 Accord.Math;
using Accord.Statistics;
using NUnit.Framework;
using QuantConnect.Algorithm.Framework.Portfolio;
using System;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class MaximumSharpeRatioPortfolioOptimizerTests : PortfolioOptimizerTestsBase
{
[OneTimeSetUp]
public void SetUp()
{
HistoricalReturns = new List<double[,]>
{
new double[,] { { 0.02, -0.02, 0.28 }, { -0.50, -0.29, -0.13 }, { 0.81, 0.29, 0.31 }, { -0.03, -0.00, 0.01 } },
new double[,] { { 0.10, 0.20, 0.4 }, { 0.12, 0.25, 0.4 }, { 0.11, 0.22, 0.4 } },
new double[,] { { -0.19, 0.50, 0.45 }, { -0.62, -0.65, 0.07 }, { -0.14, 1.02, 0.01 }, { 0.00, -0.03, 0.01 } },
new double[,] { { 0.46, 0.28, 0.58, 0.26, 0.14 }, { 0.52, 0.31, 0.43, 7.43, -0.00 }, { 0.13, 0.65, 0.52, 0.50, -0.08 }, { -0.41, -0.39, -0.28, -0.65, -0.20 }, { 0.77, 0.58, 0.58, 1.02, 0.03 }, { -0.03, -0.01, -0.01, -0.03, 0.07 } },
new double[,] { { -0.50, -0.13 }, { 0.81, 0.31 }, { -0.02, 0.01 } },
new double[,] { { 0.31, 0.25, 0.43 }, { 0.65, 0.60, 0.52 }, { -0.39, -0.22, -0.28 }, { 0.58, 0.13, 0.58 }, { -0.01, -0.00, -0.01 } },
new double[,] { { 0.13, 0.65, 1.25 }, { -0.41, -0.39, -0.50 }, { 0.77, 0.58, 2.39 }, { -0.03, -0.01, 0.04 } },
new double[,] { { 0.31, 0.43, 1.22, 0.03 }, { 0.65, 0.52, 1.25, 0.67 }, { -0.39, -0.28, -0.50, -0.10 }, { 0.58, 0.58, 2.39, -0.41 }, { -0.01, -0.01, 0.04, 0.03 } }
};
ExpectedReturns = new List<double[]>
{
new double[] { 0.08, -0.01, 0.12 },
new double[] { 0.11, 0.23, 0.4 },
new double[] { -0.24, 0.21, 0.14 },
null,
new double[] { 0.10, 0.06 },
new double[] { 0.23, 0.15, 0.25 },
null,
new double[] { 0.23, 0.25, 0.88, 0.04 }
};
Covariances = new List<double[,]>
{
new double[,] { { 0.29, 0.13, 0.10 }, { 0.13, 0.06, 0.04 }, { 0.10, 0.04, 0.05 } },
null,
new double[,] { { 0.07, 0.12, -0.00 }, { 0.12, 0.51, 0.03 }, { -0.00, 0.03, 0.04 } },
null,
new double[,] { { 0.44, 0.15 }, { 0.15, 0.05 } },
new double[,] { { 0.19, 0.11, 0.16 }, { 0.11, 0.09, 0.09 }, { 0.16, 0.09, 0.14 } },
new double[,] { { 0.24, 0.20, 0.61 }, { 0.20, 0.25, 0.58 }, { 0.61, 0.58, 1.67 } },
new double[,] { { 0.19, 0.16, 0.44, 0.05 }, { 0.16, 0.14, 0.40, 0.02 }, { 0.44, 0.40, 1.29, -0.06 }, { 0.05, 0.02, -0.06, 0.15 } }
};
ExpectedResults = new List<double[]>
{
new double[] { -0.5, 0.5, 1 },
new double[] { 0, 0, 1 },
new double[] { -0.404692, 0.404692, 1 },
new double[] { -0.418338, 0.023261, 1, 0.040668, 0.35441 },
new double[] { 0.5, 0.5 },
new double[] { -0.670213, 0.670213, 1 },
new double[] { -1, 1, 1 },
new double[] { -1, 0.315476, 0.684524, 1 },
};
}
protected override IPortfolioOptimizer CreateOptimizer()
{
return new MaximumSharpeRatioPortfolioOptimizer();
}
[TestCase(0)]
[TestCase(1)]
[TestCase(2)]
[TestCase(3)]
[TestCase(4)]
[TestCase(5)]
[TestCase(6)]
[TestCase(7)]
public override void OptimizeWeightings(int testCaseNumber)
{
base.OptimizeWeightings(testCaseNumber);
}
[TestCase(0)]
public void OptimizeWeightingsSpecifyingLowerBoundAndRiskFreeRate(int testCaseNumber)
{
var testOptimizer = new MaximumSharpeRatioPortfolioOptimizer(lower: 0, riskFreeRate: 0.04);
var expectedResult = new double[] { 0, 0, 1 };
var result = testOptimizer.Optimize(HistoricalReturns[testCaseNumber]);
Assert.AreEqual(expectedResult, result.Select(x => Math.Round(x, 6)));
}
[Test]
public void SingleSecurityPortfolioReturnsFullWeight()
{
var testOptimizer = new MaximumSharpeRatioPortfolioOptimizer();
var historicalReturns = new double[,] { { -0.1 } };
var expectedReturns = new double[] { -0.1 };
// With a single security the budget constraint Σw = 1 leaves it fully invested
var expectedResult = new double[] { 1 };
var result = testOptimizer.Optimize(historicalReturns, expectedReturns);
Assert.AreEqual(result, expectedResult);
}
[Test]
public void EqualWeightingsWhenNoSolutionFound()
{
var testOptimizer = new MaximumSharpeRatioPortfolioOptimizer();
var historicalReturns = new double[,] { { -0.10, -0.20 }, { -0.12, -0.25 } };
var expectedReturns = new double[] { -0.10, -0.25 };
var covariance = new double[,] { { 0.25, 0.12 }, { 0.45, 0.2 } }; // non positive definite
var expectedResult = new double[] { 0.5, 0.5 };
var result = testOptimizer.Optimize(historicalReturns, expectedReturns, covariance);
Assert.AreEqual(result, expectedResult);
}
[Test]
public void BoundariesAreNotViolated()
{
var testCaseNumber = 1;
var lower = 0d;
var upper = 0.5d;
var testOptimizer = new MaximumSharpeRatioPortfolioOptimizer(lower, upper);
var result = testOptimizer.Optimize(HistoricalReturns[testCaseNumber], null, Covariances[testCaseNumber]);
foreach (var x in result)
{
var rounded = Math.Round(x, 6);
Assert.GreaterOrEqual(rounded, lower);
Assert.LessOrEqual(rounded, upper);
};
}
// Every case whose maximum Sharpe ratio portfolio is well defined. Case 1 has a
// zero-variance asset (the ratio is unbounded) and case 4 an indefinite covariance
// (it falls back to equal weights), so neither has a finite interior optimum and
// both are excluded.
[TestCase(0)]
[TestCase(2)]
[TestCase(3)]
[TestCase(5)]
[TestCase(6)]
[TestCase(7)]
public void OptimizedWeightsMaximizeSharpeRatio(int testCaseNumber)
{
// Independent of the hardcoded ExpectedResults: the returned portfolio must
// achieve a Sharpe ratio no lower than equal weights or any other feasible
// portfolio drawn from the constraint set. The mean and covariance are
// reconstructed exactly as the optimizer does so the check uses the same inputs.
var testOptimizer = new MaximumSharpeRatioPortfolioOptimizer();
var historicalReturns = HistoricalReturns[testCaseNumber];
var expectedReturns = ExpectedReturns[testCaseNumber] ?? historicalReturns.Mean(0);
var covariance = Covariances[testCaseNumber] ?? historicalReturns.Covariance();
var result = testOptimizer.Optimize(historicalReturns, ExpectedReturns[testCaseNumber], Covariances[testCaseNumber]);
var optimalSharpe = SharpeRatio(result, expectedReturns, covariance);
var size = result.Length;
var equalWeights = Enumerable.Repeat(1.0 / size, size).ToArray();
Assert.GreaterOrEqual(optimalSharpe, SharpeRatio(equalWeights, expectedReturns, covariance));
// The Sharpe ratio cannot exceed the unconstrained tangency portfolio, a hard
// analytic ceiling (Cauchy-Schwarz) that no feasible portfolio can beat.
Assert.LessOrEqual(optimalSharpe, TangencySharpe(expectedReturns, covariance) + 1e-6);
var random = new Random(0);
for (var i = 0; i < 10000; i++)
{
var candidate = RandomFeasibleWeights(random, size, lower: -1.0, upper: 1.0);
Assert.GreaterOrEqual(optimalSharpe + 1e-6, SharpeRatio(candidate, expectedReturns, covariance));
}
}
private static double SharpeRatio(double[] weights, double[] expectedReturns, double[,] covariance)
{
var size = weights.Length;
var portfolioReturn = 0.0;
var portfolioVariance = 0.0;
for (var i = 0; i < size; i++)
{
portfolioReturn += weights[i] * expectedReturns[i];
for (var j = 0; j < size; j++)
{
portfolioVariance += weights[i] * covariance[i, j] * weights[j];
}
}
return portfolioReturn / Math.Sqrt(portfolioVariance);
}
private static double TangencySharpe(double[] expectedReturns, double[,] covariance)
{
// The unconstrained maximum Sharpe ratio is sqrt(mu' inv(S) mu), the largest
// value any portfolio can reach regardless of the budget or weight bounds.
var inverse = covariance.Inverse();
var size = expectedReturns.Length;
var quadraticForm = 0.0;
for (var i = 0; i < size; i++)
{
for (var j = 0; j < size; j++)
{
quadraticForm += expectedReturns[i] * inverse[i, j] * expectedReturns[j];
}
}
return Math.Sqrt(quadraticForm);
}
private static double[] RandomFeasibleWeights(Random random, int size, double lower, double upper)
{
// Draw weights uniformly from the box and keep only those summing to one.
while (true)
{
var weights = new double[size];
var sum = 0.0;
for (var i = 0; i < size - 1; i++)
{
weights[i] = lower + random.NextDouble() * (upper - lower);
sum += weights[i];
}
var last = 1.0 - sum;
if (last >= lower && last <= upper)
{
weights[size - 1] = last;
return weights;
}
}
}
}
}
Tests/Algorithm/Framework/Portfolio/MeanReversionPortfolioConstructionModelTest.cs
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/*
* 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 aaplicable 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 System.Linq;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Lean.Engine.DataFeeds;
using QuantConnect.Lean.Engine.HistoricalData;
using QuantConnect.Packets;
using QuantConnect.Tests.Common.Data.UniverseSelection;
using QuantConnect.Tests.Engine.DataFeeds;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class MeanReversionPortfolioConstructionModelTests
{
private DateTime _nowUtc;
private QCAlgorithm _algorithm;
private List<double> _simplexTestArray;
private double[] _simplexExpectedArray1, _simplexExpectedArray2;
[SetUp]
public virtual void SetUp()
{
_nowUtc = new DateTime(2021, 1, 10);
_algorithm = new AlgorithmStub();
_algorithm.SetFinishedWarmingUp();
_algorithm.Settings.MinimumOrderMarginPortfolioPercentage = 0;
_algorithm.Settings.FreePortfolioValue = 250;
_algorithm.SetDateTime(_nowUtc.ConvertToUtc(_algorithm.TimeZone));
_algorithm.SetCash(1200);
var historyProvider = new SubscriptionDataReaderHistoryProvider();
_algorithm.SetHistoryProvider(historyProvider);
historyProvider.Initialize(new HistoryProviderInitializeParameters(
new BacktestNodePacket(),
null,
TestGlobals.DataProvider,
TestGlobals.DataCacheProvider,
TestGlobals.MapFileProvider,
TestGlobals.FactorFileProvider,
i => { },
true,
new DataPermissionManager(),
_algorithm.ObjectStore,
_algorithm.Settings));
_simplexTestArray = new List<double> {0.2d, 0.5d, 0.4d, -0.1d, 0d};
_simplexExpectedArray1 = new double[] {1d/6, 7d/15, 11d/30, 0d, 0d};
_simplexExpectedArray2 = new double[] {0d, 0.3d, 0.2d, 0d, 0d};
}
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void DoesNotReturnTargetsIfSecurityPriceIsZero(Language language)
{
_algorithm.AddEquity(Symbols.SPY.Value);
_algorithm.SetDateTime(_nowUtc.ConvertToUtc(_algorithm.TimeZone));
SetPortfolioConstruction(language, PortfolioBias.Long);
var insights = new[] { new Insight(_nowUtc, Symbols.SPY, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null) };
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
Assert.AreEqual(0, actualTargets.Count());
}
[TestCase(Language.CSharp, PortfolioBias.Long)]
[TestCase(Language.Python, PortfolioBias.Long)]
[TestCase(Language.CSharp, PortfolioBias.Short)]
[TestCase(Language.Python, PortfolioBias.Short)]
public void PortfolioBiasIsRespected(Language language, PortfolioBias bias)
{
if (bias == PortfolioBias.Short)
{
var throwsConstraint = language == Language.CSharp
? Throws.InstanceOf<ArgumentException>()
: Throws.InstanceOf<ClrBubbledException>().With.InnerException.InstanceOf<ArgumentException>();
Assert.That(() => GetPortfolioConstructionModel(language, bias, Resolution.Daily),
throwsConstraint.And.Message.EqualTo("Long position must be allowed in MeanReversionPortfolioConstructionModel."));
return;
}
var targets = GeneratePortfolioTargets(language, InsightDirection.Up, InsightDirection.Up, 1, 1);
foreach (var target in targets)
{
if (target.Quantity == 0)
{
continue;
}
Assert.AreEqual(Math.Sign((int)bias), Math.Sign(target.Quantity));
}
}
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, null, null, 47, 47)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, null, null, 47, 47)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0, 0, 47, 47)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0, 0, 47, 47)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 1, -0.5, 31, 63)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 1, -0.5, 31, 63)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Down, 1, 0.5, 31, 63)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Down, 1, 0.5, 31, 63)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0, -0.5, 47, 47)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0, -0.5, 47, 47)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0, 1, 94, 0)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0, 1, 94, 0)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0.5, -1, 47, 47)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0.5, -1, 47, 47)]
public void CorrectWeightings(Language language,
InsightDirection direction1,
InsightDirection direction2,
double? magnitude1,
double? magnitude2,
decimal expectedQty1,
decimal expectedQty2)
{
var targets = GeneratePortfolioTargets(language, direction1, direction2, magnitude1, magnitude2);
var quantities = targets.ToDictionary(target => {
QuantConnect.Logging.Log.Debug($"{target.Symbol}: {target.Quantity}");
return target.Symbol.Value;
},
target => target.Quantity);
Assert.AreEqual(expectedQty1, quantities["AAPL"]);
Assert.AreEqual(expectedQty2, quantities.ContainsKey("SPY") ? quantities["SPY"] : 0);
}
[Test]
public void CumulativeSum()
{
var list = new List<double>{1.1d, 2.5d, 0.7d, 13.6d, -5.2d, 3.9d, -1.6d};
var expected = new List<double>{1.1d, 3.6d, 4.3d, 17.9d, 12.7d, 16.6d, 15.0d};
var result = MeanReversionPortfolioConstructionModel.CumulativeSum(list)
.Select(x => Math.Round(x, 1));
Assert.AreEqual(expected, result);
}
[Test]
public void GetPriceRelatives()
{
var model = new TestMeanReversionPortfolioConstructionModel();
SetPortfolioConstruction(Language.CSharp, PortfolioBias.Long, model);
var aapl = _algorithm.AddEquity("AAPL");
var spy = _algorithm.AddEquity("SPY");
var insights = new List<Insight>
{
new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
};
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(aapl, spy));
var history = _algorithm.History<TradeBar>(new[] {aapl.Symbol, spy.Symbol}, 2, Resolution.Daily);
var aaplHist = history.Select(slice => slice[aapl.Symbol].Close);
var spyHist = history.Select(slice => slice[spy.Symbol].Close);
var aaplRelative = (double) (aaplHist.Last() / aaplHist.Average());
var spyRelative = (double) (spyHist.Last() / spyHist.Average());
var result = model.TestGetPriceRelatives(insights).Select(x => Math.Round(x, 8)).ToArray();
var expected = new double[] {aaplRelative, spyRelative};
expected = expected.Select(x => Math.Round(x, 8)).ToArray();
Assert.AreEqual(expected, result);
}
[Test]
public void GetPriceRelativesPython()
{
SetPortfolioConstruction(Language.Python, PortfolioBias.Long);
var aapl = _algorithm.AddEquity("AAPL");
var spy = _algorithm.AddEquity("SPY");
var insights = new List<Insight>
{
new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
};
var history = _algorithm.History<TradeBar>(new[] {aapl.Symbol, spy.Symbol}, 2, Resolution.Daily);
var aaplHist = history.Select(slice => slice[aapl.Symbol].Close);
var spyHist = history.Select(slice => slice[spy.Symbol].Close);
var aaplRelative = (double) (aaplHist.Last() / aaplHist.Average());
var spyRelative = (double) (spyHist.Last() / spyHist.Average());
using (Py.GIL())
{
const string name = nameof(MeanReversionPortfolioConstructionModel);
var model = Py.Import(name).GetAttr(name).Invoke(((int)Resolution.Daily).ToPython(), ((int)PortfolioBias.LongShort).ToPython(), 1.ToPython(), 2.ToPython());
model.InvokeMethod("OnSecuritiesChanged", _algorithm.ToPython(), SecurityChangesTests.AddedNonInternal(aapl, spy).ToPython());
var result = PyList.AsList(model.InvokeMethod("GetPriceRelatives", insights.ToPython()));
var resultArray = result.Select(x => Math.Round(Convert.ToDouble(x), 8)).ToArray();
var expected = new double[] {aaplRelative, spyRelative};
expected = expected.Select(x => Math.Round(x, 8)).ToArray();
Assert.AreEqual(expected, resultArray);
}
}
[Test]
public void GetPriceRelativesWithInsightMagnitude()
{
var model = new TestMeanReversionPortfolioConstructionModel();
SetPortfolioConstruction(Language.CSharp, PortfolioBias.Long, model);
var aapl = _algorithm.AddEquity("AAPL");
var spy = _algorithm.AddEquity("SPY");
var insights = new List<Insight>
{
new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, 1, null),
new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, -0.5, null),
};
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(aapl, spy));
var result = model.TestGetPriceRelatives(insights);
var expected = new double[] {2d, 0.5d};
Assert.AreEqual(expected, result);
}
[Test]
public void GetPriceRelativesWithInsightMagnitudePython()
{
SetPortfolioConstruction(Language.Python, PortfolioBias.Long);
var aapl = _algorithm.AddEquity("AAPL");
var spy = _algorithm.AddEquity("SPY");
var insights = new List<Insight>
{
new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, 1, null),
new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, -0.5, null),
};
using (Py.GIL())
{
const string name = nameof(MeanReversionPortfolioConstructionModel);
var model = Py.Import(name).GetAttr(name).Invoke(((int)Resolution.Daily).ToPython());
model.InvokeMethod("OnSecuritiesChanged", _algorithm.ToPython(), SecurityChangesTests.AddedNonInternal(aapl, spy).ToPython());
var result = PyList.AsList(model.InvokeMethod("GetPriceRelatives", insights.ToPython()));
var resultArray = result.Select(x => Convert.ToDouble(x)).ToArray();
var expected = new double[] {2d, 0.5d};
Assert.AreEqual(expected, resultArray);
}
}
[TestCase(1)]
[TestCase(0.5)]
[TestCase(0)]
[TestCase(-0.5)]
public void SimplexProjection(double regulator)
{
if (regulator <= 0)
{
var exception = Assert.Throws<ArgumentException>(() => MeanReversionPortfolioConstructionModel.SimplexProjection(_simplexTestArray, regulator));
Assert.That(exception.Message, Is.EqualTo("Total must be > 0 for Euclidean Projection onto the Simplex."));
return;
}
double[] expected;
if (regulator == 1d)
{
expected = _simplexExpectedArray1;
}
else
{
expected = _simplexExpectedArray2;
}
expected = expected.Select(x => Math.Round(x, 8)).ToArray();
var result = MeanReversionPortfolioConstructionModel.SimplexProjection(_simplexTestArray, regulator);
result = result.Select(x => Math.Round(x, 8)).ToArray();
Assert.AreEqual(expected, result);
}
[TestCase(1)]
[TestCase(0.5)]
[TestCase(0)]
[TestCase(-0.5)]
public void SimplexProjectionPython(double regulator)
{
using (Py.GIL())
{
const string name = nameof(MeanReversionPortfolioConstructionModel);
var model = Py.Import(name).GetAttr(name).Invoke(((int)Resolution.Daily).ToPython());
if (regulator <= 0)
{
Assert.That(() => model.InvokeMethod("SimplexProjection", _simplexTestArray.ToPython(), new PyFloat(regulator)),
Throws.InstanceOf<ClrBubbledException>()
.With.InnerException.InstanceOf<ArgumentException>()
.And.Message.EqualTo("Total must be > 0 for Euclidean Projection onto the Simplex."));
return;
}
double[] expected;
if (regulator == 1d)
{
expected = _simplexExpectedArray1;
}
else
{
expected = _simplexExpectedArray2;
}
var expectedArray = expected.Select(x => Math.Round(x, 8)).ToArray();
var result = PyList.AsList(model.InvokeMethod("SimplexProjection", _simplexTestArray.ToPython(), new PyFloat(regulator)));
var resultArray = result.Select(x => Math.Round(Convert.ToDouble(x), 8)).ToArray();
Assert.AreEqual(expectedArray, resultArray);
}
}
private IEnumerable<IPortfolioTarget> GeneratePortfolioTargets(Language language, InsightDirection direction1, InsightDirection direction2, double? magnitude1, double? magnitude2)
{
SetPortfolioConstruction(language, PortfolioBias.Long);
var aapl = _algorithm.AddEquity("AAPL");
var spy = _algorithm.AddEquity("SPY");
foreach (var equity in new[] { aapl, spy })
{
equity.SetMarketPrice(new Tick(_nowUtc, equity.Symbol, 10, 10));
}
var insights = new[]
{
new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, direction1, magnitude1, null),
new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, direction2, magnitude2, null),
};
_algorithm.Insights.AddRange(insights);
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(aapl, spy));
return _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
}
protected void SetPortfolioConstruction(Language language, PortfolioBias bias, IPortfolioConstructionModel defaultModel = null)
{
var model = defaultModel ?? GetPortfolioConstructionModel(language, bias, Resolution.Daily);
_algorithm.SetPortfolioConstruction(model);
foreach (var kvp in _algorithm.Portfolio)
{
kvp.Value.SetHoldings(kvp.Value.Price, 0);
}
var changes = SecurityChangesTests.AddedNonInternal(_algorithm.Securities.Values.ToArray());
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, changes);
}
public IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, PortfolioBias bias, Resolution resolution)
{
if (language == Language.CSharp)
{
return new MeanReversionPortfolioConstructionModel(resolution, bias, 1, 1, resolution);
}
using (Py.GIL())
{
const string name = nameof(MeanReversionPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name)
.Invoke(((int)resolution).ToPython(), ((int)bias).ToPython(), 1.ToPython(), 1.ToPython(), ((int)resolution).ToPython());
return new PortfolioConstructionModelPythonWrapper(instance);
}
}
private class TestMeanReversionPortfolioConstructionModel : MeanReversionPortfolioConstructionModel
{
public TestMeanReversionPortfolioConstructionModel()
: base(Resolution.Daily, windowSize: 2)
{
}
public double[] TestGetPriceRelatives(List<Insight> insights)
{
return base.GetPriceRelatives(insights);
}
}
}
}
Tests/Algorithm/Framework/Portfolio/MeanVarianceOptimizationPortfolioConstructionModelTests.cs
+324
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/*
* 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 System.Linq;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Lean.Engine.DataFeeds;
using QuantConnect.Lean.Engine.HistoricalData;
using QuantConnect.Packets;
using QuantConnect.Tests.Common.Data.UniverseSelection;
using QuantConnect.Tests.Engine.DataFeeds;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class MeanVarianceOptimizationPortfolioConstructionModelTests
{
private DateTime _nowUtc;
private QCAlgorithm _algorithm;
[SetUp]
public virtual void SetUp()
{
_nowUtc = new DateTime(2013, 10, 8);
_algorithm = new QCAlgorithm();
_algorithm.SetFinishedWarmingUp();
_algorithm.SetPandasConverter();
_algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(_algorithm));
_algorithm.SetDateTime(_nowUtc.ConvertToUtc(_algorithm.TimeZone));
var historyProvider = new SubscriptionDataReaderHistoryProvider();
_algorithm.SetHistoryProvider(historyProvider);
historyProvider.Initialize(new HistoryProviderInitializeParameters(
null,
null,
TestGlobals.DataProvider,
TestGlobals.DataCacheProvider,
TestGlobals.MapFileProvider,
TestGlobals.FactorFileProvider,
i => { },
true,
new DataPermissionManager(),
_algorithm.ObjectStore,
_algorithm.Settings));
}
private void Clear() => _algorithm.Insights.Clear(_algorithm.Securities.Keys.ToArray());
[TestCase(Language.CSharp, PortfolioBias.Long, 0.1, -0.1)]
[TestCase(Language.Python, PortfolioBias.Long, 0.1, -0.1)]
[TestCase(Language.CSharp, PortfolioBias.Short, -0.1, 0.1)]
[TestCase(Language.Python, PortfolioBias.Short, -0.1, 0.1)]
[TestCase(Language.CSharp, PortfolioBias.Long, -0.1, 0.1)]
[TestCase(Language.Python, PortfolioBias.Long, -0.1, 0.1)]
[TestCase(Language.CSharp, PortfolioBias.Short, 0.1, -0.1)]
[TestCase(Language.Python, PortfolioBias.Short, 0.1, -0.1)]
public void PortfolioBiasIsRespected(Language language, PortfolioBias bias, double magnitude1, double magnitude2)
{
var targets = GeneratePortfolioTargets(language, InsightDirection.Up, InsightDirection.Down, magnitude1, magnitude2, bias);
foreach (var target in targets)
{
QuantConnect.Logging.Log.Trace($"{target.Symbol}: {target.Quantity}");
if (target.Quantity == 0)
{
continue;
}
Assert.AreEqual(Math.Sign((int)bias), Math.Sign(target.Quantity));
}
}
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0, 0, 4155, 2493)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0, 0, 4155, 2493)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Down, 0.1, 0.05, 4155, 2493)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Down, 0.1, 0.05, 4155, 2493)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0.1, 0, 4155, 2493)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0.1, 0, 4155, 2493)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Down, 0, 0.1, 4155, 2493)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Down, 0, 0.1, 4155, 2493)]
public void CorrectWeightings(Language language,
InsightDirection direction1,
InsightDirection direction2,
double? magnitude1,
double? magnitude2,
decimal expectedQty1,
decimal expectedQty2)
{
var targets = GeneratePortfolioTargets(language, direction1, direction2, magnitude1, magnitude2).ToList();
Clear();
var quantities = targets.ToDictionary(target => {
QuantConnect.Logging.Log.Trace($"{target.Symbol}: {target.Quantity}");
return target.Symbol.Value;
},
target => target.Quantity);
Assert.AreEqual(expectedQty1, quantities["AAPL"]);
Assert.AreEqual(expectedQty2, quantities.ContainsKey("SPY") ? quantities["SPY"] : 0);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void DoesNotReturnTargetsIfNoInsightMagnitude(Language language)
{
SetPortfolioConstruction(language, PortfolioBias.LongShort);
var appl = _algorithm.AddEquity("AAPL");
var insights = new[]
{
new Insight(_nowUtc, appl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null)
};
var actualTargets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToList();
Assert.AreEqual(0, actualTargets.Count);
}
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0.1, 0.1)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0.1, 0.1)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0.1, -0.1)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0.1, -0.1)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Up, 0.1, 0)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Up, 0.1, 0)]
[TestCase(Language.CSharp, InsightDirection.Up, InsightDirection.Down, 0.1, 0.1)]
[TestCase(Language.Python, InsightDirection.Up, InsightDirection.Down, 0.1, 0.1)]
public void ObeyBudgetConstraint(Language language,
InsightDirection direction1,
InsightDirection direction2,
double? magnitude1,
double? magnitude2)
{
var targets = GeneratePortfolioTargets(language, direction1, direction2, magnitude1, magnitude2);
var totalCost = targets.Sum(x => Math.Abs(x.Quantity) * 10); // Set market price at $10 in the helper method
Assert.LessOrEqual(totalCost, _algorithm.Portfolio.TotalPortfolioValue);
}
[TestCase(1)]
[TestCase(2)]
[TestCase(3)]
[TestCase(4)]
[TestCase(5)]
[TestCase(6)]
[TestCase(7)]
public void PythonConstructorWorksWithDifferentArguments(int arguments)
{
using (Py.GIL())
{
var module = PyModule.FromString(Guid.NewGuid().ToString(),
@"
from AlgorithmImports import *
timeDelta = timedelta(days=1)
class CustomPortfolioOptimizer:
def Optimize(self, historicalReturns, expectedReturns, covariance):
return [0.5]*(np.array(historicalReturns)).shape[1]"
);
var timeDelta = module.GetAttr("timeDelta");
var portfolioBias = PortfolioBias.LongShort;
var lookback = 1;
var period = 63;
var resolution = Resolution.Daily;
var targetReturn = 0.02;
var optimizer = module.GetAttr("CustomPortfolioOptimizer").Invoke();
switch (arguments)
{
case 1:
Assert.DoesNotThrow(() => new MeanVarianceOptimizationPortfolioConstructionModel(timeDelta));
break;
case 2:
Assert.DoesNotThrow(() => new MeanVarianceOptimizationPortfolioConstructionModel(timeDelta, portfolioBias));
break;
case 3:
Assert.DoesNotThrow(() => new MeanVarianceOptimizationPortfolioConstructionModel(timeDelta, portfolioBias, lookback));
break;
case 4:
Assert.DoesNotThrow(() => new MeanVarianceOptimizationPortfolioConstructionModel(timeDelta, portfolioBias, lookback, period));
break;
case 5:
Assert.DoesNotThrow(() => new MeanVarianceOptimizationPortfolioConstructionModel(timeDelta, portfolioBias, lookback, period, resolution));
break;
case 6:
Assert.DoesNotThrow(() => new MeanVarianceOptimizationPortfolioConstructionModel(timeDelta, portfolioBias, lookback, period, resolution, targetReturn));
break;
case 7:
Assert.DoesNotThrow(() => new MeanVarianceOptimizationPortfolioConstructionModel(timeDelta, portfolioBias, lookback, period, resolution, targetReturn, optimizer));
break;
}
}
}
[TestCase("timeDelta")]
[TestCase("pyFunc")]
public void PythonConstructorWorksWithDifferentArgumentRebalance(string rebalanceName)
{
using (Py.GIL())
{
var module = PyModule.FromString(Guid.NewGuid().ToString(),
@"from AlgorithmImports import *
timeDelta = timedelta(days=1)
pyFunc = lambda x: x + timedelta(days=1)");
var rebalance = module.GetAttr(rebalanceName);
Assert.DoesNotThrow(() => new MeanReversionPortfolioConstructionModel(rebalance));
}
}
[TestCase("CustomPortfolioOptimizer")]
[TestCase("csharpOptimizer")]
public void PythonConstructorWorksWithDifferentOptimizers(string optimizerName)
{
using (Py.GIL())
{
var module = PyModule.FromString(Guid.NewGuid().ToString(),
@"from AlgorithmImports import *
rebalance = timedelta(days=1)
csharpOptimizer = MinimumVariancePortfolioOptimizer()
class CustomPortfolioOptimizer:
def Optimize(self, historicalReturns, expectedReturns, covariance):
pass");
var rebalance = module.GetAttr("rebalance");
var optimizer = module.GetAttr(optimizerName);
if (optimizerName == "customOptimizer")
{
optimizer = optimizer.Invoke();
}
Assert.DoesNotThrow(() => new MeanVarianceOptimizationPortfolioConstructionModel(rebalance, optimizer: optimizer));
}
}
[Test]
public void PythonConstructorFailsWhenOptimizerTypeIsInvalid()
{
using (Py.GIL())
{
var module = PyModule.FromString(Guid.NewGuid().ToString(),
@"from AlgorithmImports import *
rebalance = timedelta(days=1)
class CustomPortfolioOptimizer:
pass");
var rebalance = module.GetAttr("rebalance");
var optimizer = module.GetAttr("CustomPortfolioOptimizer").Invoke();
var message = Assert.Throws<NotImplementedException>(() => new MeanVarianceOptimizationPortfolioConstructionModel(rebalance, optimizer: optimizer));
}
}
protected void SetPortfolioConstruction(Language language, PortfolioBias bias)
{
var model = GetPortfolioConstructionModel(language, Resolution.Daily, bias);
_algorithm.SetPortfolioConstruction(model);
foreach (var kvp in _algorithm.Portfolio)
{
kvp.Value.SetHoldings(kvp.Value.Price, 0);
}
var changes = SecurityChangesTests.AddedNonInternal(_algorithm.Securities.Values.ToArray());
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, changes);
}
public IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, Resolution resolution, PortfolioBias bias)
{
if (language == Language.CSharp)
{
return new MeanVarianceOptimizationPortfolioConstructionModel(resolution, bias, 1, 63, Resolution.Daily, 0.0001);
}
using (Py.GIL())
{
const string name = nameof(MeanVarianceOptimizationPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name)
.Invoke(((int)resolution).ToPython(), ((int)bias).ToPython(), 1.ToPython(), 63.ToPython(), ((int)Resolution.Daily).ToPython(), 0.0001.ToPython());
return new PortfolioConstructionModelPythonWrapper(instance);
}
}
private IEnumerable<IPortfolioTarget> GeneratePortfolioTargets(Language language, InsightDirection direction1, InsightDirection direction2,
double? magnitude1, double? magnitude2, PortfolioBias bias = PortfolioBias.LongShort)
{
SetPortfolioConstruction(language, bias);
var aapl = _algorithm.AddEquity("AAPL");
var spy = _algorithm.AddEquity("SPY");
aapl.SetMarketPrice(new Tick(_nowUtc, aapl.Symbol, 10, 10));
spy.SetMarketPrice(new Tick(_nowUtc, spy.Symbol, 10, 10));
aapl.SetMarketPrice(new Tick(_nowUtc.AddDays(1), aapl.Symbol, 8, 8));
spy.SetMarketPrice(new Tick(_nowUtc.AddDays(1), spy.Symbol, 15, 15));
aapl.SetMarketPrice(new Tick(_nowUtc.AddDays(2), aapl.Symbol, 12, 12));
spy.SetMarketPrice(new Tick(_nowUtc.AddDays(2), spy.Symbol, 20, 20));
var insights = new[]
{
new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, direction1, magnitude1, null),
new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, direction2, magnitude2, null),
};
_algorithm.Insights.AddRange(insights);
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(aapl, spy));
return _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights);
}
}
}
Tests/Algorithm/Framework/Portfolio/MinimumVariancePortfolioOptimizerTests.cs
+181
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/*
* 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 aaplicable 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 NUnit.Framework;
using QuantConnect.Algorithm.Framework.Portfolio;
using System;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class MinimumVariancePortfolioOptimizerTests : PortfolioOptimizerTestsBase
{
private Dictionary<int, double> _targetReturns;
[OneTimeSetUp]
public void Setup()
{
var historicalReturns1 = new double[,] { { 0.76, -0.06, 1.22, 0.17 }, { 0.02, 0.28, 1.25, -0.00 }, { -0.50, -0.13, -0.50, -0.03 }, { 0.81, 0.31, 2.39, 0.26 }, { -0.02, 0.02, 0.06, 0.01 } };
var historicalReturns2 = new double[,] { { -0.15, 0.67, 0.45 }, { -0.44, -0.10, 0.07 }, { 0.04, -0.41, 0.01 }, { 0.01, 0.03, 0.02 } };
var historicalReturns3 = new double[,] { { -0.02, 0.65, 1.25 }, { -0.29, -0.39, -0.50 }, { 0.29, 0.58, 2.39 }, { 0.00, -0.01, 0.06 } };
var historicalReturns4 = new double[,] { { 0.76, 0.25, 0.21 }, { 0.02, -0.15, 0.45 }, { -0.50, -0.44, 0.07 }, { 0.81, 0.04, 0.01 }, { -0.02, 0.01, 0.02 } };
var expectedReturns1 = new double[] { 0.21, 0.08, 0.88, 0.08 };
var expectedReturns2 = new double[] { -0.13, 0.05, 0.14 };
var expectedReturns3 = (double[])null;
var expectedReturns4 = (double[])null;
var covariance1 = new double[,] { { 0.31, 0.05, 0.55, 0.07 }, { 0.05, 0.04, 0.18, 0.01 }, { 0.55, 0.18, 1.28, 0.12 }, { 0.07, 0.01, 0.12, 0.02 } };
var covariance2 = new double[,] { { 0.05, -0.02, -0.01 }, { -0.02, 0.21, 0.09 }, { -0.01, 0.09, 0.04 } };
var covariance3 = new double[,] { { 0.06, 0.09, 0.28 }, { 0.09, 0.25, 0.58 }, { 0.28, 0.58, 1.66 } };
var covariance4 = (double[,])null;
HistoricalReturns = new List<double[,]>
{
historicalReturns1,
historicalReturns2,
historicalReturns3,
historicalReturns4,
historicalReturns1,
historicalReturns2,
historicalReturns3,
historicalReturns4
};
ExpectedReturns = new List<double[]>
{
expectedReturns1,
expectedReturns2,
expectedReturns3,
expectedReturns4,
expectedReturns1,
expectedReturns2,
expectedReturns3,
expectedReturns4
};
Covariances = new List<double[,]>
{
covariance1,
covariance2,
covariance3,
covariance4,
covariance1,
covariance2,
covariance3,
covariance4
};
ExpectedResults = new List<double[]>
{
new double[] { -0.089212, 0.23431, -0.040975, 0.635503 },
new double[] { 0.366812, -0.139738, 0.49345 },
new double[] { 0.562216, 0.36747, -0.070314 },
new double[] { -0.119241, 0.443464, 0.437295 },
new double[] { -0.215505, 0.130699, 0.084806, 0.56899 },
new double[] { -0.275, 0.275, 0.45 },
new double[] { -0.129512, 0.551139, 0.319349 },
new double[] { 0.052859, 0.144177, 0.802964 },
};
_targetReturns = new Dictionary<int, double>
{
{ 4, 0.15d },
{ 5, 0.25d },
{ 6, 0.5d },
{ 7, 0.125d }
};
}
protected override IPortfolioOptimizer CreateOptimizer()
{
return new MinimumVariancePortfolioOptimizer();
}
[TestCase(0)]
[TestCase(1)]
[TestCase(2)]
[TestCase(3)]
public override void OptimizeWeightings(int testCaseNumber)
{
base.OptimizeWeightings(testCaseNumber);
}
[TestCase(4)]
[TestCase(5)]
[TestCase(6)]
[TestCase(7)]
public void OptimizeWeightingsSpecifyingTargetReturns(int testCaseNumber)
{
var testOptimizer = new MinimumVariancePortfolioOptimizer(targetReturn: _targetReturns[testCaseNumber]);
var result = testOptimizer.Optimize(
HistoricalReturns[testCaseNumber],
ExpectedReturns[testCaseNumber],
Covariances[testCaseNumber]);
Assert.AreEqual(ExpectedResults[testCaseNumber], result.Select(x => Math.Round(x, 6)));
Assert.AreEqual(1d, result.Select(x => Math.Round(Math.Abs(x), 6)).Sum());
}
[TestCase(0)]
public void EqualWeightingsWhenNoSolutionFound(int testCaseNumber)
{
var testOptimizer = new MinimumVariancePortfolioOptimizer(upper: -1);
var expectedResult = new double[] { 0.25, 0.25, 0.25, 0.25 };
var result = testOptimizer.Optimize(HistoricalReturns[testCaseNumber]);
Assert.AreEqual(expectedResult, result);
}
[TestCase(0)]
[TestCase(1)]
[TestCase(2)]
[TestCase(3)]
public void BoundariesAreNotViolated(int testCaseNumber)
{
var lower = 0d;
var upper = 0.5d;
var testOptimizer = new MinimumVariancePortfolioOptimizer(lower, upper);
var result = testOptimizer.Optimize(
HistoricalReturns[testCaseNumber],
ExpectedReturns[testCaseNumber],
Covariances[testCaseNumber]);
foreach (var x in result)
{
var rounded = Math.Round(x, 6);
Assert.GreaterOrEqual(rounded, lower);
Assert.LessOrEqual(rounded, upper);
};
}
[Test]
public void SingleSecurityPortfolioReturnsOne()
{
var testOptimizer = new MinimumVariancePortfolioOptimizer();
var historicalReturns = new double[,] { { 0.76 }, { 0.02 }, { -0.50 } };
var expectedResult = new double[] { 1 };
var result = testOptimizer.Optimize(historicalReturns);
Assert.AreEqual(expectedResult, result);
}
}
}
Tests/Algorithm/Framework/Portfolio/PortfolioConstructionModelPythonWrapperTests.cs
+167
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/*
* 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.Linq;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Tests.Common.Data.UniverseSelection;
using QuantConnect.Tests.Engine.DataFeeds;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class PortfolioConstructionModelPythonWrapperTests
{
[Test]
public void PythonCompleteImplementation()
{
var algorithm = new AlgorithmStub();
using (Py.GIL())
{
dynamic model = PyModule.FromString(
"TestPCM",
@"
from AlgorithmImports import *
class PyPCM(EqualWeightingPortfolioConstructionModel):
def __init__(self):
super().__init__()
self.CreateTargets_WasCalled = False
self.OnSecuritiesChanged_WasCalled = False
self.ShouldCreateTargetForInsight_WasCalled = False
self.IsRebalanceDue_WasCalled = False
self.GetTargetInsights_WasCalled = False
self.DetermineTargetPercent_WasCalled = False
def CreateTargets(self, algorithm, insights):
self.CreateTargets_WasCalled = True
return super().CreateTargets(algorithm, insights)
def OnSecuritiesChanged(self, algorithm, changes):
self.OnSecuritiesChanged_WasCalled = True
super().OnSecuritiesChanged(algorithm, changes)
def ShouldCreateTargetForInsight(self, insight):
self.ShouldCreateTargetForInsight_WasCalled = True
return super().ShouldCreateTargetForInsight(insight)
def IsRebalanceDue(self, insights, algorithmUtc):
self.IsRebalanceDue_WasCalled = True
return True
def GetTargetInsights(self):
self.GetTargetInsights_WasCalled = True
return super().GetTargetInsights()
def DetermineTargetPercent(self, activeInsights):
self.DetermineTargetPercent_WasCalled = True
return super().DetermineTargetPercent(activeInsights)
"
).GetAttr("PyPCM").Invoke();
var now = new DateTime(2020, 1, 10);
var wrappedModel = new PortfolioConstructionModelPythonWrapper(model);
var aapl = algorithm.AddEquity("AAPL");
aapl.SetMarketPrice(new Tick(now, aapl.Symbol, 10, 10));
algorithm.SetDateTime(now);
wrappedModel.OnSecuritiesChanged(algorithm, new SecurityChanges(SecurityChangesTests.AddedNonInternal(aapl)));
Assert.IsTrue((bool)model.OnSecuritiesChanged_WasCalled);
var insight = new Insight(now, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Down, null, null);
algorithm.Insights.Add(insight);
var result = wrappedModel.CreateTargets(algorithm, new[] { insight }).ToList();
Assert.AreEqual(1, result.Count);
Assert.IsTrue((bool)model.CreateTargets_WasCalled);
Assert.IsTrue((bool)model.GetTargetInsights_WasCalled);
Assert.IsTrue((bool)model.IsRebalanceDue_WasCalled);
Assert.IsTrue((bool)model.ShouldCreateTargetForInsight_WasCalled);
Assert.IsTrue((bool)model.DetermineTargetPercent_WasCalled);
}
}
[Test]
public void PythonDoesNotImplementDetermineTargetPercent()
{
var algorithm = new AlgorithmStub();
using (Py.GIL())
{
dynamic model = PyModule.FromString(
"TestPCM",
@"
from clr import AddReference
AddReference(""QuantConnect.Algorithm.Framework"")
from QuantConnect.Algorithm.Framework.Portfolio import *
class PyPCM(EqualWeightingPortfolioConstructionModel):
def __init__(self):
super().__init__()
self.CreateTargets_WasCalled = False
self.OnSecuritiesChanged_WasCalled = False
self.ShouldCreateTargetForInsight_WasCalled = False
self.IsRebalanceDue_WasCalled = False
self.GetTargetInsights_WasCalled = False
def CreateTargets(self, algorithm, insights):
self.CreateTargets_WasCalled = True
return super().CreateTargets(algorithm, insights)
def OnSecuritiesChanged(self, algorithm, changes):
self.OnSecuritiesChanged_WasCalled = True
super().OnSecuritiesChanged(algorithm, changes)
def ShouldCreateTargetForInsight(self, insight):
self.ShouldCreateTargetForInsight_WasCalled = True
return super().ShouldCreateTargetForInsight(insight)
def IsRebalanceDue(self, insights, algorithmUtc):
self.IsRebalanceDue_WasCalled = True
return True
def GetTargetInsights(self):
self.GetTargetInsights_WasCalled = True
return super().GetTargetInsights()
"
).GetAttr("PyPCM").Invoke();
var now = new DateTime(2020, 1, 10);
var wrappedModel = new PortfolioConstructionModelPythonWrapper(model);
var aapl = algorithm.AddEquity("AAPL");
aapl.SetMarketPrice(new Tick(now, aapl.Symbol, 10, 10));
algorithm.SetDateTime(now);
wrappedModel.OnSecuritiesChanged(algorithm, new SecurityChanges(SecurityChangesTests.AddedNonInternal(aapl)));
Assert.IsTrue((bool)model.OnSecuritiesChanged_WasCalled);
var insight = new Insight(now, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Down, null, null);
algorithm.Insights.Add(insight);
var result = wrappedModel.CreateTargets(algorithm, new[] { insight }).ToList();
Assert.AreEqual(1, result.Count);
Assert.IsTrue((bool)model.CreateTargets_WasCalled);
Assert.IsTrue((bool)model.GetTargetInsights_WasCalled);
Assert.IsTrue((bool)model.IsRebalanceDue_WasCalled);
Assert.IsTrue((bool)model.ShouldCreateTargetForInsight_WasCalled);
}
}
}
}
Tests/Algorithm/Framework/Portfolio/PortfolioConstructionModelTests.cs
+433
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/*
* 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 NodaTime;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Scheduling;
using QuantConnect.Securities;
using QuantConnect.Tests.Common.Data.UniverseSelection;
using DateTime = System.DateTime;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class PortfolioConstructionModelTests
{
private QCAlgorithm _algorithm;
[SetUp]
public void SetUp()
{
_algorithm = new QCAlgorithm();
}
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void RebalanceFunctionPeriodDue(Language language)
{
TestPortfolioConstructionModel constructionModel;
if (language == Language.Python)
{
constructionModel = new TestPortfolioConstructionModel();
using (Py.GIL())
{
var func = PyModule.FromString("RebalanceFunc",
@"
from datetime import timedelta
def RebalanceFunc(time):
return time + timedelta(days=1)").GetAttr("RebalanceFunc");
constructionModel.SetRebalancingFunc(func);
}
}
else
{
constructionModel = new TestPortfolioConstructionModel(time => time.AddDays(1));
}
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChanges.None);
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 1), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(
new DateTime(2020, 1, 1, 23, 0, 0), new Insight[0]));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 2), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(
new DateTime(2020, 1, 2, 1, 0, 0), new Insight[0]));
}
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void RebalanceFunctionSecurityChanges(Language language)
{
TestPortfolioConstructionModel constructionModel;
if (language == Language.Python)
{
constructionModel = new TestPortfolioConstructionModel();
using (Py.GIL())
{
var func = PyModule.FromString("RebalanceFunc",
@"
from datetime import timedelta
def RebalanceFunc(time):
return time + timedelta(days=1)").GetAttr("RebalanceFunc");
constructionModel.SetRebalancingFunc(func);
}
}
else
{
constructionModel = new TestPortfolioConstructionModel(time => time.AddDays(1));
}
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChanges.None);
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(
new DateTime(2020, 1, 2, 1, 0, 0), new Insight[0]));
var security = new Security(Symbols.SPY,
SecurityExchangeHours.AlwaysOpen(DateTimeZone.Utc),
new Cash(Currencies.USD, 1, 1),
SymbolProperties.GetDefault(Currencies.USD),
new IdentityCurrencyConverter(Currencies.USD),
new RegisteredSecurityDataTypesProvider(),
new SecurityCache());
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(security));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 2), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 2), new Insight[0]));
}
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void RebalanceFunctionNewInsights(Language language)
{
TestPortfolioConstructionModel constructionModel;
if (language == Language.Python)
{
constructionModel = new TestPortfolioConstructionModel();
using (Py.GIL())
{
var func = PyModule.FromString("RebalanceFunc",
@"
from datetime import timedelta
def RebalanceFunc(time):
return time + timedelta(days=1)").GetAttr("RebalanceFunc");
constructionModel.SetRebalancingFunc(func);
}
}
else
{
constructionModel = new TestPortfolioConstructionModel(time => time.AddDays(1));
}
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChanges.None);
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 1), new Insight[0]));
var insights = new[] { Insight.Price(Symbols.SPY, Resolution.Daily, 1, InsightDirection.Down) };
constructionModel.RebalanceOnInsightChanges = false;
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 1), insights));
constructionModel.RebalanceOnInsightChanges = true;
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 1), insights));
}
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void RebalanceFunctionInsightExpiration(Language language)
{
TestPortfolioConstructionModel constructionModel;
if (language == Language.Python)
{
constructionModel = new TestPortfolioConstructionModel();
using (Py.GIL())
{
var func = PyModule.FromString("RebalanceFunc",
@"
from datetime import timedelta
def RebalanceFunc(time):
return time + timedelta(days=10)").GetAttr("RebalanceFunc");
constructionModel.SetRebalancingFunc(func);
}
}
else
{
constructionModel = new TestPortfolioConstructionModel(time => time.AddDays(10));
}
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChanges.None);
constructionModel.SetNextExpiration(new DateTime(2020, 1, 2));
constructionModel.RebalanceOnInsightChanges = false;
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 3), new Insight[0]));
constructionModel.RebalanceOnInsightChanges = true;
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 3), new Insight[0]));
}
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void NoRebalanceFunction(Language language)
{
TestPortfolioConstructionModel constructionModel;
if (language == Language.Python)
{
constructionModel = new TestPortfolioConstructionModel();
using (Py.GIL())
{
var func = PyModule.FromString(
"RebalanceFunc",
@"
from datetime import timedelta
def RebalanceFunc():
return None"
).GetAttr("RebalanceFunc");
constructionModel.SetRebalancingFunc(func.Invoke());
}
}
else
{
constructionModel = new TestPortfolioConstructionModel();
}
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChanges.None);
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 1), new Insight[0]));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 2), new Insight[0]));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 3), new Insight[0]));
var security = new Security(Symbols.SPY,
SecurityExchangeHours.AlwaysOpen(DateTimeZone.Utc),
new Cash(Currencies.USD, 1, 1),
SymbolProperties.GetDefault(Currencies.USD),
new IdentityCurrencyConverter(Currencies.USD),
new RegisteredSecurityDataTypesProvider(),
new SecurityCache());
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(security));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 1), new Insight[0]));
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChanges.None);
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 1), new Insight[0]));
}
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void RebalanceFunctionNull(Language language)
{
TestPortfolioConstructionModel constructionModel;
if (language == Language.Python)
{
constructionModel = new TestPortfolioConstructionModel();
using (Py.GIL())
{
var func = PyModule.FromString(
"RebalanceFunc",
@"
from datetime import timedelta
def RebalanceFunc(time):
if time.day == 17:
return time + timedelta(hours=1)
if time.day == 18:
return time
return None"
).GetAttr("RebalanceFunc");
constructionModel.SetRebalancingFunc(func);
}
}
else
{
constructionModel = new TestPortfolioConstructionModel(
time =>
{
if (time.Day == 18)
{
return time;
}
if (time.Day == 17)
{
return time.AddHours(1);
}
return null;
});
}
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChanges.None);
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 1), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(
new DateTime(2020, 1, 1, 23, 0, 0), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 2), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(
new DateTime(2020, 1, 2, 0, 0, 1), new Insight[0]));
// day number '17' should trigger rebalance in the next hour
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 17), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(
new DateTime(2020, 1, 17, 0, 59, 59), new Insight[0]));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(
new DateTime(2020, 1, 17, 1, 0, 0), new Insight[0]));
constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 20), new Insight[0]);
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 21), new Insight[0]));
// day number '18' should trigger rebalance immediately
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 18), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 1, 21), new Insight[0]));
}
[TestCase(Language.Python)]
[TestCase(Language.CSharp)]
public void RebalanceFunctionDateRules(Language language)
{
var mhdb = MarketHoursDatabase.FromDataFolder();
var dateRules = new DateRules(null, new SecurityManager(
new TimeKeeper(new DateTime(2015, 1, 1), DateTimeZone.Utc)), DateTimeZone.Utc, mhdb);
TestPortfolioConstructionModel constructionModel;
if (language == Language.Python)
{
constructionModel = new TestPortfolioConstructionModel();
using (Py.GIL())
{
dynamic func = PyModule.FromString("RebalanceFunc",
@"
import datetime
def RebalanceFunc(dateRules):
return dateRules.On(datetime.datetime(2015, 1, 10), datetime.datetime(2015, 1, 30))").GetAttr("RebalanceFunc");
constructionModel.SetRebalancingFunc(func(dateRules));
}
}
else
{
var dateRule = dateRules.On(new DateTime(2015, 1, 10), new DateTime(2015, 1, 30));
constructionModel = new TestPortfolioConstructionModel(dateRule);
}
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChanges.None);
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2015, 1, 1), new Insight[0]));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2015, 1, 10), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2015, 1, 20), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2015, 1, 29), new Insight[0]));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 2, 1), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 2, 2), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2020, 10, 2), new Insight[0]));
}
[TestCase(Language.Python, 2)]
[TestCase(Language.Python, 1)]
[TestCase(Language.Python, 0)]
[TestCase(Language.CSharp, 0)]
public void RebalanceFunctionTimeSpan(Language language, int version)
{
TestPortfolioConstructionModel constructionModel;
if (language == Language.Python)
{
constructionModel = new TestPortfolioConstructionModel();
using (Py.GIL())
{
if (version == 1)
{
dynamic func = PyModule.FromString("RebalanceFunc",
@"
from System import *
def RebalanceFunc(timeSpan):
return timeSpan").GetAttr("RebalanceFunc");
constructionModel.SetRebalancingFunc(func(TimeSpan.FromMinutes(20)));
}
else if(version == 2)
{
dynamic func = PyModule.FromString("RebalanceFunc",
@"
from datetime import timedelta
def RebalanceFunc(constructionModel):
return constructionModel.SetRebalancingFunc(timedelta(minutes = 20))").GetAttr("RebalanceFunc");
func(constructionModel);
}
else
{
dynamic func = PyModule.FromString("RebalanceFunc",
@"
from datetime import timedelta
def RebalanceFunc():
return timedelta(minutes = 20)").GetAttr("RebalanceFunc");
constructionModel.SetRebalancingFunc(func());
}
}
}
else
{
constructionModel = new TestPortfolioConstructionModel(time => time.AddMinutes(20));
}
constructionModel.OnSecuritiesChanged(_algorithm, SecurityChanges.None);
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2015, 1, 1), new Insight[0]));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2015, 1, 1, 0, 20, 0), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2015, 1, 1, 0, 22, 0), new Insight[0]));
Assert.IsFalse(constructionModel.IsRebalanceDueWrapper(new DateTime(2015, 1, 1, 0, 21, 0), new Insight[0]));
Assert.IsTrue(constructionModel.IsRebalanceDueWrapper(new DateTime(2015, 1, 1, 0, 40, 0), new Insight[0]));
}
class TestPortfolioConstructionModel : PortfolioConstructionModel
{
public TestPortfolioConstructionModel(IDateRule dateRule)
: this(dateRule.ToFunc())
{
}
public TestPortfolioConstructionModel(Func<DateTime, DateTime> func = null)
: base(func)
{
}
public TestPortfolioConstructionModel(Func<DateTime, DateTime?> func)
: base(func)
{
}
public new void SetRebalancingFunc(PyObject rebalancingFunc)
{
base.SetRebalancingFunc(rebalancingFunc);
}
public bool IsRebalanceDueWrapper(DateTime now, Insight[] insights)
{
return base.IsRebalanceDue(insights, now);
}
public void SetNextExpiration(DateTime nextExpiration)
{
Algorithm.Insights.Add(
new Insight(Symbols.SPY, time => nextExpiration, InsightType.Price, InsightDirection.Down));
}
}
}
}
Tests/Algorithm/Framework/Portfolio/PortfolioOptimizerPythonWrapperTests.cs
+76
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/*
* 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 aaplicable 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 NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm.Framework.Portfolio;
using System;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio;
[TestFixture]
public class PortfolioOptimizerPythonWrapperTests
{
[Test]
public void OptimizeIsCalled()
{
using (Py.GIL())
{
var module = PyModule.FromString(Guid.NewGuid().ToString(),
@$"
from AlgorithmImports import *
class CustomPortfolioOptimizer:
def __init__(self):
self.OptimizeWasCalled = False
def Optimize(self, historicalReturns, expectedReturns = None, covariance = None):
self.OptimizeWasCalled= True");
var pyCustomOptimizer = module.GetAttr("CustomPortfolioOptimizer").Invoke();
var wrapper = new PortfolioOptimizerPythonWrapper(pyCustomOptimizer);
var historicalReturns = new double[,] { { -0.50, -0.13 }, { 0.81, 0.31 }, { -0.02, 0.01 } };
wrapper.Optimize(historicalReturns);
pyCustomOptimizer
.GetAttr("OptimizeWasCalled")
.TryConvert(out bool optimizerWasCalled);
Assert.IsTrue(optimizerWasCalled);
}
}
[Test]
public void WrapperThrowsIfOptimizerDoesNotImplementInterface()
{
using (Py.GIL())
{
var module = PyModule.FromString(Guid.NewGuid().ToString(),
@$"
from AlgorithmImports import *
class CustomPortfolioOptimizer:
def __init__(self):
self.OptimizeWasCalled = False
def Calculate(self, historicalReturns, expectedReturns = None, covariance = None):
pass");
var pyCustomOptimizer = module.GetAttr("CustomPortfolioOptimizer").Invoke();
Assert.Throws<NotImplementedException>(() => new PortfolioOptimizerPythonWrapper(pyCustomOptimizer));
}
}
}
Tests/Algorithm/Framework/Portfolio/PortfolioOptimizerTestsBase.cs
+59
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/*
* 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 aaplicable 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 NUnit.Framework;
using QuantConnect.Algorithm.Framework.Portfolio;
using System;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio;
public abstract class PortfolioOptimizerTestsBase
{
protected IList<double[,]> HistoricalReturns { get; set; }
protected IList<double[]> ExpectedReturns { get; set; }
protected IList<double[,]> Covariances { get; set; }
protected IList<double[]> ExpectedResults { get; set; }
protected abstract IPortfolioOptimizer CreateOptimizer();
public virtual void OptimizeWeightings(int testCaseNumber)
{
var testOptimizer = CreateOptimizer();
var result = testOptimizer.Optimize(
HistoricalReturns[testCaseNumber],
ExpectedReturns[testCaseNumber],
Covariances[testCaseNumber]);
Assert.AreEqual(ExpectedResults[testCaseNumber], result.Select(x => Math.Round(x, 6)));
}
[Test]
public virtual void EmptyPortfolioReturnsEmptyArrayOfDouble()
{
var testOptimizer = CreateOptimizer();
var historicalReturns = new double[,] { { } };
var expectedResult = Array.Empty<double>();
var result = testOptimizer.Optimize(historicalReturns);
Assert.AreEqual(result, expectedResult);
}
}
Tests/Algorithm/Framework/Portfolio/PortfolioTargetCollectionTests.cs
+345
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/*
* 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.Linq;
using NUnit.Framework;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data.Market;
using QuantConnect.Orders;
using QuantConnect.Securities;
using QuantConnect.Tests.Common.Securities;
using QuantConnect.Tests.Engine.DataFeeds;
using QuantConnect.Util;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class PortfolioTargetCollectionTests
{
private string _symbol = "SPY";
[Test]
public void TryGetValue()
{
var collection = new PortfolioTargetCollection();
Assert.IsFalse(collection.TryGetValue(Symbols.SPY, out var target));
collection[Symbols.SPY] = new PortfolioTarget(Symbols.SPY, 1);
Assert.IsTrue(collection.TryGetValue(Symbols.SPY, out target));
Assert.AreEqual(target, collection[Symbols.SPY]);
}
[Test]
public void IndexAccess()
{
var collection = new PortfolioTargetCollection();
collection[Symbols.SPY] = new PortfolioTarget(Symbols.SPY, 1);
Assert.AreEqual(1, collection.Count);
Assert.AreEqual(1, collection.Values.Count);
Assert.AreEqual(1, collection.Keys.Count);
collection[Symbols.IBM] = new PortfolioTarget(Symbols.IBM, 1);
Assert.AreEqual(2, collection.Count);
Assert.AreEqual(2, collection.Values.Count);
Assert.AreEqual(2, collection.Keys.Count);
collection[Symbols.IBM] = null;
Assert.AreEqual(2, collection.Count);
Assert.AreEqual(2, collection.Values.Count);
Assert.AreEqual(2, collection.Keys.Count);
}
[Test]
public void Count()
{
var collection = new PortfolioTargetCollection();
var targets = new[] { new PortfolioTarget(Symbols.SPY, 1) };
collection.AddRange(targets);
Assert.AreEqual(1, collection.Count);
collection.AddRange(new[] { new PortfolioTarget(Symbols.IBM, 1), new PortfolioTarget(Symbols.AAPL, 1) });
Assert.AreEqual(3, collection.Count);
collection.Clear();
}
[Test]
public void IsEmpty()
{
var collection = new PortfolioTargetCollection();
Assert.IsTrue(collection.IsEmpty);
Assert.IsFalse(collection.ContainsKey(Symbols.SPY));
collection.Add(new PortfolioTarget(Symbols.SPY, 1));
Assert.AreEqual(1, collection.Count);
Assert.IsFalse(collection.IsEmpty);
Assert.IsTrue(collection.ContainsKey(Symbols.SPY));
}
[Test]
public void AddRange()
{
var collection = new PortfolioTargetCollection();
var targets = new[] { new PortfolioTarget(Symbols.SPY, 1), new PortfolioTarget(Symbols.AAPL, 1) };
collection.AddRange(targets);
Assert.AreEqual(2, collection.Count);
Assert.IsTrue(collection.ContainsKey(Symbols.SPY));
Assert.IsTrue(collection.ContainsKey(Symbols.AAPL));
Assert.AreEqual(targets[0], collection[Symbols.SPY]);
Assert.AreEqual(targets[1], collection[Symbols.AAPL]);
Assert.AreEqual(1, collection.Values.Count(target => target == targets[0]));
Assert.AreEqual(1, collection.Values.Count(target => target == targets[1]));
Assert.AreEqual(1, collection.Keys.Count(symbol => symbol == Symbols.SPY));
Assert.AreEqual(1, collection.Keys.Count(symbol => symbol == Symbols.AAPL));
}
[Test]
public void RemoveTargetRespectsReference()
{
var symbol = new Symbol(SecurityIdentifier.GenerateBase(null, _symbol, Market.USA), _symbol);
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, 1);
collection.Add(target);
Assert.AreEqual(collection.Count, 1);
Assert.IsTrue(collection.Contains(target));
// removes by reference even if same symbol
Assert.IsFalse(collection.Remove(new PortfolioTarget(symbol, 1)));
Assert.AreEqual(collection.Count, 1);
}
[Test]
public void AddContainsAndRemoveWork()
{
var symbol = new Symbol(SecurityIdentifier.GenerateBase(null, _symbol, Market.USA), _symbol);
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, 1);
collection.Add(target);
Assert.AreEqual(collection.Count, 1);
Assert.IsTrue(collection.Contains(target));
Assert.IsTrue(collection.Remove(target));
Assert.AreEqual(collection.Count, 0);
}
[Test]
public void ClearFulfilledDoesNotRemoveUnreachedTarget()
{
var algorithm = new FakeAlgorithm();
algorithm.SetFinishedWarmingUp();
var symbol = new Symbol(SecurityIdentifier.GenerateEquity(_symbol, Market.USA), _symbol);
#pragma warning disable CS0618
var equity = algorithm.AddEquity(symbol);
var dummySecurityHolding = new FakeSecurityHolding(equity);
equity.Holdings = dummySecurityHolding;
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, -1);
collection.Add(target);
collection.ClearFulfilled(algorithm);
Assert.AreEqual(collection.Count, 1);
}
[Test]
public void ClearRemovesUnreachedTarget()
{
var algorithm = new FakeAlgorithm();
algorithm.SetFinishedWarmingUp();
var symbol = new Symbol(SecurityIdentifier.GenerateEquity(_symbol, Market.USA), _symbol);
var equity = algorithm.AddEquity(symbol);
var dummySecurityHolding = new FakeSecurityHolding(equity);
equity.Holdings = dummySecurityHolding;
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, -1);
collection.Add(target);
collection.Clear();
Assert.AreEqual(collection.Count, 0);
}
[Test]
public void ClearFulfilledRemovesPositiveTarget()
{
var algorithm = new FakeAlgorithm();
algorithm.SetFinishedWarmingUp();
var symbol = new Symbol(SecurityIdentifier.GenerateEquity(_symbol, Market.USA), _symbol);
var equity = algorithm.AddEquity(symbol);
var dummySecurityHolding = new FakeSecurityHolding(equity);
equity.Holdings = dummySecurityHolding;
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, 1);
collection.Add(target);
dummySecurityHolding.SetQuantity(1);
collection.ClearFulfilled(algorithm);
Assert.AreEqual(collection.Count, 0);
}
[Test]
public void ClearFulfilledRemovesNegativeTarget()
{
var algorithm = new FakeAlgorithm();
algorithm.SetFinishedWarmingUp();
var symbol = new Symbol(SecurityIdentifier.GenerateEquity(_symbol, Market.USA), _symbol);
var equity = algorithm.AddEquity(symbol);
var dummySecurityHolding = new FakeSecurityHolding(equity);
equity.Holdings = dummySecurityHolding;
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, -1);
collection.Add(target);
dummySecurityHolding.SetQuantity(-1);
collection.ClearFulfilled(algorithm);
Assert.AreEqual(collection.Count, 0);
}
[Test]
public void OrderByMarginImpactDoesNotReturnTargetsWithNoData()
{
var algorithm = new FakeAlgorithm();
algorithm.SetFinishedWarmingUp();
algorithm.Transactions.SetOrderProcessor(new FakeOrderProcessor());
var symbol = new Symbol(SecurityIdentifier.GenerateEquity(_symbol, Market.USA), _symbol);
algorithm.AddEquity(symbol);
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, -1);
collection.Add(target);
var targets = collection.OrderByMarginImpact(algorithm);
Assert.AreEqual(collection.Count, 1);
Assert.IsTrue(targets.IsNullOrEmpty());
}
[Test]
public void OrderByMarginImpactReturnsExpectedTargets()
{
var algorithm = new FakeAlgorithm();
algorithm.SetFinishedWarmingUp();
algorithm.Transactions.SetOrderProcessor(new FakeOrderProcessor());
var symbol = new Symbol(SecurityIdentifier.GenerateEquity(_symbol, Market.USA), _symbol);
var equity = algorithm.AddEquity(symbol);
equity.Cache.AddData(new TradeBar(DateTime.UtcNow, symbol, 1, 1, 1, 1, 1));
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, -1);
collection.Add(target);
var targets = collection.OrderByMarginImpact(algorithm);
Assert.AreEqual(collection.Count, 1);
Assert.AreEqual(targets.Count(), 1);
Assert.AreEqual(targets.First(), target);
}
[Test]
public void OrderByMarginImpactDoesNotReturnTargetsForWhichUnorderedQuantityIsZeroBecauseTargetIsZero()
{
var algorithm = new FakeAlgorithm();
algorithm.SetFinishedWarmingUp();
algorithm.Transactions.SetOrderProcessor(new FakeOrderProcessor());
var symbol = new Symbol(SecurityIdentifier.GenerateEquity(_symbol, Market.USA), _symbol);
var equity = algorithm.AddEquity(symbol);
equity.Cache.AddData(new TradeBar(DateTime.UtcNow, symbol, 1, 1, 1, 1, 1));
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, 0);
collection.Add(target);
var targets = collection.OrderByMarginImpact(algorithm);
Assert.AreEqual(collection.Count, 1);
Assert.IsTrue(targets.IsNullOrEmpty());
}
[Test]
public void OrderByMarginImpactDoesNotReturnTargetsForWhichUnorderedQuantityIsZeroBecauseTargetReached()
{
var algorithm = new FakeAlgorithm();
algorithm.SetFinishedWarmingUp();
algorithm.Transactions.SetOrderProcessor(new FakeOrderProcessor());
var symbol = new Symbol(SecurityIdentifier.GenerateEquity(_symbol, Market.USA), _symbol);
var equity = algorithm.AddEquity(symbol);
var dummySecurityHolding = new FakeSecurityHolding(equity);
equity.Holdings = dummySecurityHolding;
equity.Cache.AddData(new TradeBar(DateTime.UtcNow, symbol, 1, 1, 1, 1, 1));
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, 1);
collection.Add(target);
dummySecurityHolding.SetQuantity(1);
var targets = collection.OrderByMarginImpact(algorithm);
Assert.AreEqual(collection.Count, 1);
Assert.IsTrue(targets.IsNullOrEmpty());
}
[Test]
public void OrderByMarginImpactDoesNotReturnTargetsForWhichUnorderedQuantityIsZeroBecauseOpenOrder()
{
var orderProcessor = new FakeOrderProcessor();
var algorithm = GetAlgorithm(orderProcessor);
var symbol = new Symbol(SecurityIdentifier.GenerateEquity(_symbol, Market.USA), _symbol);
var equity = algorithm.AddEquity(symbol);
#pragma warning restore CS0618
equity.Cache.AddData(new TradeBar(DateTime.UtcNow, symbol, 1, 1, 1, 1, 1));
var collection = new PortfolioTargetCollection();
var target = new PortfolioTarget(symbol, 1);
collection.Add(target);
var openOrderRequest = new SubmitOrderRequest(OrderType.Market, symbol.SecurityType, symbol, 1, 0, 0, DateTime.UtcNow, "");
openOrderRequest.SetOrderId(1);
var openOrderTicket = new OrderTicket(algorithm.Transactions, openOrderRequest);
orderProcessor.AddOrder(new MarketOrder(symbol, 1, DateTime.UtcNow));
orderProcessor.AddTicket(openOrderTicket);
var targets = collection.OrderByMarginImpact(algorithm);
Assert.AreEqual(collection.Count, 1);
Assert.IsTrue(targets.IsNullOrEmpty());
}
private QCAlgorithm GetAlgorithm(IOrderProcessor orderProcessor)
{
var algorithm = new FakeAlgorithm();
algorithm.SetFinishedWarmingUp();
algorithm.Transactions.SetOrderProcessor(orderProcessor);
return algorithm;
}
private class FakeSecurityHolding : SecurityHolding
{
public FakeSecurityHolding(Security security) :
base(security, new IdentityCurrencyConverter(security.QuoteCurrency.Symbol))
{
}
public void SetQuantity(int quantity)
{
Quantity = quantity;
}
}
private class FakeAlgorithm : QCAlgorithm
{
public FakeAlgorithm()
{
SubscriptionManager.SetDataManager(new DataManagerStub(this));
}
}
}
}
Tests/Algorithm/Framework/Portfolio/PortfolioTargetTests.cs
+134
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/*
* 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.Linq;
using Moq;
using NUnit.Framework;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data.Market;
using QuantConnect.Securities;
using QuantConnect.Tests.Engine;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class PortfolioTargetTests
{
[Test]
public void PercentInvokesBuyingPowerModelAndAddsInExistingHoldings()
{
const decimal bpmQuantity = 100;
const decimal holdings = 50;
const decimal targetPercent = 0.5m;
var algorithm = PerformanceBenchmarkAlgorithms.SingleSecurity_Second;
algorithm.Initialize();
algorithm.PostInitialize();
var security = algorithm.Securities.Single().Value;
security.SetMarketPrice(new Tick{Value = 1m});
security.Holdings.SetHoldings(1m, holdings);
var buyingPowerMock = new Mock<IBuyingPowerModel>();
buyingPowerMock.Setup(bpm => bpm.GetMaximumOrderQuantityForTargetBuyingPower(It.IsAny<GetMaximumOrderQuantityForTargetBuyingPowerParameters>()))
.Returns(new GetMaximumOrderQuantityResult(bpmQuantity, null, false));
security.BuyingPowerModel = buyingPowerMock.Object;
buyingPowerMock.Setup(bpm => bpm.GetLeverage(It.IsAny<Security>())).Returns(1);
var target = PortfolioTarget.Percent(algorithm, security.Symbol, targetPercent);
Assert.AreEqual(security.Symbol, target.Symbol);
Assert.AreEqual(bpmQuantity + holdings, target.Quantity);
}
[Test]
public void PercentReturnsNullIfPriceIsZero()
{
const decimal holdings = 50;
const decimal targetPercent = 1m;
var algorithm = PerformanceBenchmarkAlgorithms.SingleSecurity_Second;
algorithm.Initialize();
algorithm.PostInitialize();
var security = algorithm.Securities.Single().Value;
security.SetMarketPrice(new Tick { Value = 0m });
security.Holdings.SetHoldings(1m, holdings);
var target = PortfolioTarget.Percent(algorithm, security.Symbol, targetPercent);
Assert.IsNull(target);
}
[Test]
public void PercentReturnsNullIfBuyingPowerModelError()
{
const decimal holdings = 50;
const decimal targetPercent = 1m;
var algorithm = PerformanceBenchmarkAlgorithms.SingleSecurity_Second;
algorithm.Initialize();
algorithm.PostInitialize();
var security = algorithm.Securities.Single().Value;
security.SetMarketPrice(new Tick { Value = 1m });
security.Holdings.SetHoldings(1m, holdings);
var buyingPowerMock = new Mock<IBuyingPowerModel>();
buyingPowerMock.Setup(bpm => bpm.GetMaximumOrderQuantityForTargetBuyingPower(It.IsAny<GetMaximumOrderQuantityForTargetBuyingPowerParameters>()))
.Returns(new GetMaximumOrderQuantityResult(0, "The portfolio does not have enough margin available."));
security.BuyingPowerModel = buyingPowerMock.Object;
buyingPowerMock.Setup(bpm => bpm.GetLeverage(It.IsAny<Security>())).Returns(1);
var target = PortfolioTarget.Percent(algorithm, security.Symbol, targetPercent);
Assert.IsNull(target);
}
[TestCase(-3, true)]
[TestCase(3, true)]
[TestCase(2, false)]
[TestCase(-2, false)]
[TestCase(0.01, true)]
[TestCase(-0.01, true)]
[TestCase(0.1, false)]
[TestCase(-0.1, false)]
[TestCase(0, false)]
public void PercentIgnoresExtremeValuesBasedOnSettings(double value, bool shouldBeNull)
{
var algorithm = PerformanceBenchmarkAlgorithms.SingleSecurity_Second;
algorithm.Settings.MaxAbsolutePortfolioTargetPercentage = 2;
algorithm.Settings.MinAbsolutePortfolioTargetPercentage = 0.1m;
algorithm.Initialize();
algorithm.PostInitialize();
var security = algorithm.Securities.Single().Value;
security.SetMarketPrice(new Tick { Value = 1m });
var buyingPowerMock = new Mock<IBuyingPowerModel>();
buyingPowerMock.Setup(bpm => bpm.GetMaximumOrderQuantityForTargetBuyingPower(It.IsAny<GetMaximumOrderQuantityForTargetBuyingPowerParameters>()))
.Returns(new GetMaximumOrderQuantityResult(1, null, false));
buyingPowerMock.Setup(bpm => bpm.GetLeverage(It.IsAny<Security>())).Returns(1);
security.BuyingPowerModel = buyingPowerMock.Object;
var target = PortfolioTarget.Percent(algorithm, security.Symbol, value);
if (shouldBeNull)
{
Assert.IsNull(target);
}
else
{
Assert.IsNotNull(target);
}
}
}
}
Tests/Algorithm/Framework/Portfolio/ReturnsSymbolDataTests.cs
+252
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/*
* 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 Accord.Math;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Python;
using QuantConnect.Securities;
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Tests.Common.Data.UniverseSelection;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class ReturnsSymbolDataTests
{
[Test]
public void ReturnsDoesNotThrowIndexOutOfRangeException()
{
var dateTime = new DateTime(2020, 02, 01);
var returnsSymbolData = new ReturnsSymbolData(Symbols.EURGBP, 1, 5);
returnsSymbolData.Add(dateTime, 10);
returnsSymbolData.Add(dateTime.AddDays(1), 100);
returnsSymbolData.Add(dateTime.AddDays(2), 5);
var returnsSymbolData2 = new ReturnsSymbolData(Symbols.BTCUSD, 1, 5);
returnsSymbolData2.Add(dateTime.AddDays(1), 33);
returnsSymbolData2.Add(dateTime.AddDays(2), 2);
var returnsSymbolDatas = new Dictionary<Symbol, ReturnsSymbolData>
{
{Symbols.EURGBP, returnsSymbolData},
{Symbols.BTCUSD, returnsSymbolData2},
};
var result = returnsSymbolDatas.FormReturnsMatrix(new List<Symbol> {Symbols.EURGBP, Symbols.BTCUSD });
Assert.AreEqual(4, result.Length);
Assert.AreEqual(5m, result[0, 0]);
Assert.AreEqual(2m, result[0, 1]);
Assert.AreEqual(100m, result[1, 0]);
Assert.AreEqual(33m, result[1, 1]);
}
[Test]
public void ReturnsDoesNotThrowKeyAlreadyExistsException()
{
var returnsSymbolData = new ReturnsSymbolData(Symbols.EURGBP, 1, 5);
var dateTime = new DateTime(2020, 02, 01);
returnsSymbolData.Add(dateTime, 10);
returnsSymbolData.Add(dateTime, 100);
Assert.AreEqual(1, returnsSymbolData.Returns.Count);
Assert.AreEqual(returnsSymbolData.Returns[dateTime], 10);
}
[Test]
[TestCase(false)]
[TestCase(true)]
public void ReturnsSymbolDataMatrixIsSimilarToPandasDataFrame(bool odd)
{
var symbols = new[] { "A", "B", "C", "D", "E" }
.Select(x => Symbol.Create(x, SecurityType.Equity, Market.USA, x));
var slices = GetHistory(symbols, odd);
var expected = GetExpectedValue(slices);
var symbolDataDict = new Dictionary<Symbol, ReturnsSymbolData>();
slices.PushThrough(bar =>
{
ReturnsSymbolData symbolData;
if (!symbolDataDict.TryGetValue(bar.Symbol, out symbolData))
{
symbolData = new ReturnsSymbolData(bar.Symbol, 1, 5);
symbolDataDict.Add(bar.Symbol, symbolData);
}
symbolData.Update(bar.EndTime, bar.Value);
});
var matrix = symbolDataDict.FormReturnsMatrix(symbols);
var actual = matrix.Determinant();
Assert.AreEqual(expected, actual, 0.000001);
}
[Test]
public void DuplicateKeyPortfolioConstructionModelDoesNotThrow()
{
var algorithm = new QCAlgorithm();
var timezone = algorithm.TimeZone;
algorithm.SetDateTime(new DateTime(2018, 8, 7).ConvertToUtc(timezone));
algorithm.SetPortfolioConstruction(new DuplicateKeyPortfolioConstructionModel());
var symbol = Symbols.SPY;
var security = new Security(
SecurityExchangeHours.AlwaysOpen(timezone),
new SubscriptionDataConfig(
typeof(TradeBar),
symbol,
Resolution.Daily,
timezone,
timezone,
true,
false,
false
),
new Cash(Currencies.USD, 0, 1),
SymbolProperties.GetDefault(Currencies.USD),
ErrorCurrencyConverter.Instance,
RegisteredSecurityDataTypesProvider.Null,
new SecurityCache()
);
security.SetMarketPrice(new Tick(algorithm.Time, symbol, 1m, 1m));
algorithm.Securities.Add(symbol, security);
algorithm.PortfolioConstruction.OnSecuritiesChanged(algorithm, SecurityChangesTests.AddedNonInternal(security));
var insights = new[] {Insight.Price(symbol, Time.OneMinute, InsightDirection.Up, .1)};
Assert.DoesNotThrow(() => algorithm.PortfolioConstruction.CreateTargets(algorithm, insights));
}
private List<Slice> GetHistory(IEnumerable<Symbol> symbols, bool odd)
{
var reference = DateTime.Now;
var rnd = new Random(reference.Second);
var symbolsArray = symbols.ToArray();
return Enumerable.Range(0, 10).Select(t =>
{
var time = reference.AddDays(t);
var data = Enumerable.Range(0, symbolsArray.Length).Select(i =>
{
// Odd data means that one of the symbols have a different timestamp
if (odd && i == symbolsArray.Length - 1)
{
time = time.AddMinutes(10);
}
return new Tick(time, symbolsArray[i], (decimal)rnd.NextDouble(), 0, 0) {TickType = TickType.Trade};
});
return new Slice(time, data, time);
}).ToList();
}
private double GetExpectedValue(List<Slice> history)
{
var code = @"
import numpy as np
import pandas as pd
import math
from BlackLittermanOptimizationPortfolioConstructionModel import BlackLittermanOptimizationPortfolioConstructionModel as blopcm
def GetDeterminantFromHistory(history):
returns = dict()
history = history.lastprice.unstack(0)
for symbol, df in history.items():
symbolData = blopcm.BlackLittermanSymbolData(symbol, 1, 5)
for time, close in df.dropna().items():
symbolData.update(time, close)
returns[symbol] = symbolData.return_
df = pd.DataFrame(returns)
if df.isna().sum().sum() > 0:
df[df.columns[-1]] = df[df.columns[-1]].bfill()
df = df.dropna()
return np.linalg.det(df)";
using (Py.GIL())
{
dynamic GetDeterminantFromHistory = PyModule.FromString("GetDeterminantFromHistory", code)
.GetAttr("GetDeterminantFromHistory");
dynamic df = new PandasConverter().GetDataFrame(history);
return GetDeterminantFromHistory(df);
}
}
private class DuplicateKeyPortfolioConstructionModel : IPortfolioConstructionModel
{
private readonly Dictionary<Symbol, ReturnsSymbolData> _symbolDataDict = new Dictionary<Symbol, ReturnsSymbolData>();
public IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
{
// Updates the ReturnsSymbolData with insights
foreach (var insight in insights)
{
ReturnsSymbolData symbolData;
if (_symbolDataDict.TryGetValue(insight.Symbol, out symbolData))
{
symbolData.Add(algorithm.Time, .1m);
}
}
Assert.DoesNotThrow(() => _symbolDataDict.FormReturnsMatrix(insights.Select(x => x.Symbol)));
return Enumerable.Empty<PortfolioTarget>();
}
public void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
{
const int period = 2;
var reference = algorithm.Time.AddDays(-period);
foreach (var security in changes.AddedSecurities)
{
var symbol = security.Symbol;
var symbolData = new ReturnsSymbolData(symbol, 1, period);
for (var i = 0; i <= period; i++)
{
symbolData.Update(reference.AddDays(i), 1);
}
_symbolDataDict[symbol] = symbolData;
}
}
}
}
}
Tests/Algorithm/Framework/Portfolio/RiskParityPortfolioConstructionModelTests.cs
+188
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/*
* 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 aaplicable 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.Linq;
using Accord.Math;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Lean.Engine.DataFeeds;
using QuantConnect.Lean.Engine.HistoricalData;
using QuantConnect.Packets;
using QuantConnect.Tests.Common.Data.UniverseSelection;
using QuantConnect.Tests.Engine.DataFeeds;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class RiskParityPortfolioConstructionModelTests
{
private DateTime _nowUtc;
private QCAlgorithm _algorithm;
[SetUp]
public virtual void SetUp()
{
_nowUtc = new DateTime(2021, 1, 10);
_algorithm = new AlgorithmStub();
_algorithm.SetFinishedWarmingUp();
_algorithm.Settings.MinimumOrderMarginPortfolioPercentage = 0;
_algorithm.Settings.FreePortfolioValue = 250;
_algorithm.SetDateTime(_nowUtc.ConvertToUtc(_algorithm.TimeZone));
_algorithm.SetCash(1200);
var historyProvider = new SubscriptionDataReaderHistoryProvider();
_algorithm.SetHistoryProvider(historyProvider);
historyProvider.Initialize(new HistoryProviderInitializeParameters(
new BacktestNodePacket(),
null,
TestGlobals.DataProvider,
TestGlobals.DataCacheProvider,
TestGlobals.MapFileProvider,
TestGlobals.FactorFileProvider,
i => { },
true,
new DataPermissionManager(),
_algorithm.ObjectStore,
_algorithm.Settings));
}
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void DoesNotReturnTargetsIfSecurityPriceIsZero(Language language)
{
var algorithm = new QCAlgorithm();
algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(algorithm));
algorithm.AddEquity(Symbols.SPY.Value);
algorithm.SetDateTime(DateTime.MinValue.ConvertToUtc(algorithm.TimeZone));
SetPortfolioConstruction(language, PortfolioBias.Long);
var insights = new[] { new Insight(_nowUtc, Symbols.SPY, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null) };
var actualTargets = algorithm.PortfolioConstruction.CreateTargets(algorithm, insights);
Assert.AreEqual(0, actualTargets.Count());
}
[TestCase(Language.CSharp, PortfolioBias.Long)]
[TestCase(Language.Python, PortfolioBias.Long)]
[TestCase(Language.CSharp, PortfolioBias.Short)]
[TestCase(Language.Python, PortfolioBias.Short)]
public void PortfolioBiasIsRespected(Language language, PortfolioBias bias)
{
if (bias == PortfolioBias.Short)
{
var throwsConstraint = language == Language.CSharp
? Throws.InstanceOf<ArgumentException>()
: Throws.InstanceOf<ClrBubbledException>().With.InnerException.InstanceOf<ArgumentException>();
Assert.That(() => GetPortfolioConstructionModel(language, bias, Resolution.Daily),
throwsConstraint.And.Message.EqualTo("Long position must be allowed in RiskParityPortfolioConstructionModel."));
return;
}
SetPortfolioConstruction(language, bias);
var aapl = _algorithm.AddEquity("AAPL");
var spy = _algorithm.AddEquity("SPY");
foreach (var equity in new[] { aapl, spy })
{
equity.SetMarketPrice(new Tick(_nowUtc, equity.Symbol, 10, 10));
}
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(aapl, spy));
var insights = new[]
{
new Insight(_nowUtc, aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
new Insight(_nowUtc, spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Down, null, null)
};
foreach (var target in _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights))
{
if (target.Quantity == 0)
{
continue;
}
Assert.AreEqual(Math.Sign((int)bias), Math.Sign(target.Quantity));
}
}
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void CorrectWeightings(Language language)
{
SetPortfolioConstruction(language, PortfolioBias.Long);
var aapl = _algorithm.AddEquity("AAPL");
var spy = _algorithm.AddEquity("SPY");
aapl.SetMarketPrice(new Tick(_nowUtc, aapl.Symbol, 10, 10));
spy.SetMarketPrice(new Tick(_nowUtc, spy.Symbol, 10, 10));
aapl.SetMarketPrice(new Tick(_nowUtc.AddDays(1), aapl.Symbol, 12, 12));
spy.SetMarketPrice(new Tick(_nowUtc.AddDays(1), spy.Symbol, 20, 20));
aapl.SetMarketPrice(new Tick(_nowUtc.AddDays(2), aapl.Symbol, 13, 13));
spy.SetMarketPrice(new Tick(_nowUtc.AddDays(2), spy.Symbol, 30, 30));
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, SecurityChangesTests.AddedNonInternal(aapl, spy));
var insights = new[]
{
new Insight(_nowUtc.AddDays(2), aapl.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null),
new Insight(_nowUtc.AddDays(2), spy.Symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, null, null)
};
_algorithm.Insights.AddRange(insights);
var targets = _algorithm.PortfolioConstruction.CreateTargets(_algorithm, insights).ToArray();
Assert.AreEqual(targets[0].Quantity, 30m); // AAPL
Assert.AreEqual(targets[1].Quantity, 18m); // SPY
}
protected void SetPortfolioConstruction(Language language, PortfolioBias bias, IPortfolioConstructionModel defaultModel = null)
{
var model = defaultModel ?? GetPortfolioConstructionModel(language, bias, Resolution.Daily);
_algorithm.SetPortfolioConstruction(model);
foreach (var kvp in _algorithm.Portfolio)
{
kvp.Value.SetHoldings(kvp.Value.Price, 0);
}
var changes = SecurityChangesTests.AddedNonInternal(_algorithm.Securities.Values.ToArray());
_algorithm.PortfolioConstruction.OnSecuritiesChanged(_algorithm, changes);
}
public IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, PortfolioBias bias, Resolution resolution)
{
if (language == Language.CSharp)
{
return new RiskParityPortfolioConstructionModel(resolution, bias, 1, 252, resolution);
}
using (Py.GIL())
{
const string name = nameof(RiskParityPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name)
.Invoke(((int)resolution).ToPython(), ((int)bias).ToPython(), 1.ToPython(), 252.ToPython(), ((int)resolution).ToPython());
return new PortfolioConstructionModelPythonWrapper(instance);
}
}
}
}
Tests/Algorithm/Framework/Portfolio/RiskParityPortfolioOptimizerTests.cs
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/*
* 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 aaplicable 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 System.Linq;
using Accord.Math;
using NUnit.Framework;
using QuantConnect.Algorithm.Framework.Portfolio;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class RiskParityPortfolioOptimizerTests
{
private Dictionary<int, double[][]> _covariances = new();
private Dictionary<int, double[]> _riskBudgets = new();
private Dictionary<int, double[]> _expectedResults = new();
[SetUp]
public virtual void SetUp()
{
var riskBudget1 = new double[] {0.5d, 0.5d}; // equal risk distribution
var riskBudget2 = new double[] {0.25d, 0.75d}; // 25% risk assigned to A, 75% risk assigned to B
var covariance1 = new double[][] {new[]{0.25, -0.2}, new[]{-0.2, 0.25}}; // both 50% variance, -80% correlation
var covariance2 = new double[][] {new[]{0.01, 0}, new[]{0, 0.04}}; // sigma(A) 10%, sigma(B) 20%, 0% correlation
var covariance3 = new double[][] {new[]{1, 0.45}, new[]{0.45, 0.25}}; // sigma(A) 100%, sigma(B) 50%, 90% correlation
var covariance4 = new double[][] {new[]{0.25, 0.05}, new[]{0.05, 0.04}}; // sigma(A) 50%, sigma(B) 10%, 25% correlation
var expectedResult1 = new double[] {3.162278d, 3.162278d};
var expectedResult2 = new double[] {7.071068d, 3.535534d};
var expectedResult3 = new double[] {0.512989d, 1.025978d};
var expectedResult4 = new double[] {1.154701d, 2.886751d};
var expectedResult5 = new double[] {2.965685d, 3.285618d};
var expectedResult6 = new double[] {5d, 4.330127d};
var expectedResult7 = new double[] {0.264749d, 1.510089d};
var expectedResult8 = new double[] {0.681774d, 3.924933d};
_covariances.TryAdd(1, covariance1);
_covariances.TryAdd(2, covariance2);
_covariances.TryAdd(3, covariance3);
_covariances.TryAdd(4, covariance4);
_covariances.TryAdd(5, covariance1);
_covariances.TryAdd(6, covariance2);
_covariances.TryAdd(7, covariance3);
_covariances.TryAdd(8, covariance4);
_riskBudgets.TryAdd(1, riskBudget1);
_riskBudgets.TryAdd(2, riskBudget1);
_riskBudgets.TryAdd(3, riskBudget1);
_riskBudgets.TryAdd(4, riskBudget1);
_riskBudgets.TryAdd(5, riskBudget2);
_riskBudgets.TryAdd(6, riskBudget2);
_riskBudgets.TryAdd(7, riskBudget2);
_riskBudgets.TryAdd(8, riskBudget2);
_expectedResults.TryAdd(1, expectedResult1);
_expectedResults.TryAdd(2, expectedResult2);
_expectedResults.TryAdd(3, expectedResult3);
_expectedResults.TryAdd(4, expectedResult4);
_expectedResults.TryAdd(5, expectedResult5);
_expectedResults.TryAdd(6, expectedResult6);
_expectedResults.TryAdd(7, expectedResult7);
_expectedResults.TryAdd(8, expectedResult8);
}
[TestCase(1)]
[TestCase(0)]
[TestCase(1001)]
public void TestForExtremeNumberOfVariablesRiskParityNewtonMethodOptimization(int numberOfVariables)
{
var testOptimizer = new TestRiskParityPortfolioOptimizer();
if (numberOfVariables < 1 || numberOfVariables > 1000)
{
var exception = Assert.Throws<ArgumentException>(() => testOptimizer.TestOptimization(numberOfVariables, new double[,]{}, new double[]{}));
Assert.That(exception.Message, Is.EqualTo("Argument \"numberOfVariables\" must be a positive integer between 1 and 1000"));
return;
}
var result = testOptimizer.TestOptimization(numberOfVariables, new double[,]{}, new double[]{});
Assert.AreEqual(new double[] {1d}, result);
}
[TestCase(1)]
[TestCase(2)]
[TestCase(3)]
[TestCase(4)]
[TestCase(5)]
[TestCase(6)]
[TestCase(7)]
[TestCase(8)]
public void TestRiskParityNewtonMethodOptimizationWeightings(int testCaseNumber)
{
var testOptimizer = new TestRiskParityPortfolioOptimizer();
var covariance = JaggedArrayTo2DArray(_covariances[testCaseNumber]);
var result = testOptimizer.TestOptimization(2, covariance, _riskBudgets[testCaseNumber]);
result = result.Select(x => Math.Round(x, 6)).ToArray();
Assert.AreEqual(_expectedResults[testCaseNumber], result);
}
[TestCase(1)]
[TestCase(2)]
[TestCase(3)]
[TestCase(4)]
[TestCase(5)]
[TestCase(6)]
[TestCase(7)]
[TestCase(8)]
public void TestOptimizeWeightings(int testCaseNumber)
{
var testOptimizer = new TestRiskParityPortfolioOptimizer();
var covariance = JaggedArrayTo2DArray(_covariances[testCaseNumber]);
var result = testOptimizer.Optimize(new double[,]{}, _riskBudgets[testCaseNumber], covariance);
result = result.Select(x => Math.Round(x, 6)).ToArray();
var expected = _expectedResults[testCaseNumber];
expected = Elementwise.Divide(expected, expected.Sum()).Select(x => Math.Clamp(x, 1e-05, double.MaxValue)).ToArray();
expected = expected.Select(x => Math.Round(x, 6)).ToArray();
Assert.AreEqual(expected, result);
}
private T[,] JaggedArrayTo2DArray<T>(T[][] source)
{
int FirstDim = source.Length;
int SecondDim = source.GroupBy(row => row.Length).Single().Key;
var result = new T[FirstDim, SecondDim];
for (int i = 0; i < FirstDim; ++i)
for (int j = 0; j < SecondDim; ++j)
result[i, j] = source[i][j];
return result;
}
private class TestRiskParityPortfolioOptimizer : RiskParityPortfolioOptimizer
{
public TestRiskParityPortfolioOptimizer()
: base()
{
}
public double[] TestOptimization(int numOfVar, double[,] covariance, double[] budget)
{
return base.RiskParityNewtonMethodOptimization(numOfVar, covariance, budget);
}
}
}
}
Tests/Algorithm/Framework/Portfolio/SectorWeightingPortfolioConstructionModelTests.cs
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/*
* 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 NodaTime;
using NUnit.Framework;
using Python.Runtime;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Data.Fundamental;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Securities;
using QuantConnect.Securities.Equity;
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Tests.Common.Data.UniverseSelection;
using QuantConnect.Interfaces;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class SectorWeightingPortfolioConstructionModelTests : BaseWeightingPortfolioConstructionModelTests
{
private const double _weight = 0.01;
public override double? Weight => Algorithm.Securities.Count == 0 ? default(double) : 1d / Algorithm.Securities.Count;
[OneTimeSetUp]
public override void SetUp()
{
base.SetUp();
var prices = new Dictionary<Symbol, Tuple<decimal, string>>
{
{ Symbol.Create("XXX", SecurityType.Equity, Market.USA), Tuple.Create(55.22m, "") },
{ Symbol.Create("B01", SecurityType.Equity, Market.USA), Tuple.Create(55.22m, "B") },
{ Symbol.Create("B02", SecurityType.Equity, Market.USA), Tuple.Create(55.22m, "B") },
{ Symbol.Create("B03", SecurityType.Equity, Market.USA), Tuple.Create(55.22m, "B") },
{ Symbol.Create("T01", SecurityType.Equity, Market.USA), Tuple.Create(145.17m, "T") },
{ Symbol.Create("T02", SecurityType.Equity, Market.USA), Tuple.Create(145.17m, "T") },
{ Symbol.Create("SPY", SecurityType.Equity, Market.USA), Tuple.Create(281.79m, "X") },
};
Func<Symbol, Security> GetSecurity = symbol =>
new Equity(
symbol,
SecurityExchangeHours.AlwaysOpen(DateTimeZone.Utc),
new Cash(Currencies.USD, 0, 1),
SymbolProperties.GetDefault(Currencies.USD),
ErrorCurrencyConverter.Instance,
RegisteredSecurityDataTypesProvider.Null,
new SecurityCache()
);
var industryTemplateCodeDict = new Dictionary<SecurityIdentifier, string>();
foreach (var kvp in prices)
{
var symbol = kvp.Key;
var security = GetSecurity(symbol);
var price = kvp.Value.Item1;
var sectorCode = kvp.Value.Item2;
// The first item does not have a valid sector code,
// This procedure shows that the model ignores the securities without it
if (!string.IsNullOrEmpty(sectorCode))
{
security.SetMarketPrice(new Fundamental(Algorithm.Time, symbol)
{
Value = price
});
industryTemplateCodeDict[symbol.ID] = kvp.Value.Item2;
}
security.SetMarketPrice(new Tick(Algorithm.Time, symbol, price, price));
Algorithm.Securities.Add(symbol, security);
}
FundamentalService.Initialize(TestGlobals.DataProvider, new TestFundamentalDataProvider(industryTemplateCodeDict), false);
}
[Test]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public override void AutomaticallyRemoveInvestedWithNewInsights(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language);
// Let's create a position for SPY
var insights = new[] { GetInsight(Symbols.SPY, direction, Algorithm.UtcTime) };
foreach (var target in Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights))
{
var holding = Algorithm.Portfolio[target.Symbol];
holding.SetHoldings(holding.Price, target.Quantity);
Algorithm.Portfolio.SetCash(StartingCash - holding.HoldingsValue);
}
SetUtcTime(Algorithm.UtcTime.AddDays(2));
// Since we have 3 B, 2 T and 1 X, each security in each sector will get
// B => .166%, T => .25, X => 0% (removed)
var sectorCount = 2;
var groupedBySector = Algorithm.Securities
.Where(pair => pair.Value.Fundamentals?.CompanyReference.IndustryTemplateCode != null)
.GroupBy(pair => pair.Value.Fundamentals.CompanyReference.IndustryTemplateCode);
var expectedTargets = new List<PortfolioTarget>();
foreach (var securities in groupedBySector)
{
var list = securities.ToList();
var amount = Algorithm.Portfolio.TotalPortfolioValue / list.Count / sectorCount *
(1 - Algorithm.Settings.FreePortfolioValuePercentage);
expectedTargets.AddRange(list
.Select(x => new PortfolioTarget(x.Key, x.Key.Value == "SPY" ? 0
: (int)direction * Math.Floor(amount / x.Value.Price))));
}
// Do no include SPY in the insights
insights = Algorithm.Securities.Keys.Where(x => x.Value != "SPY")
.Select(x => GetInsight(x, direction, Algorithm.UtcTime)).ToArray();
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights);
Assert.Greater(Algorithm.Securities.Count, expectedTargets.Count);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public override void DelistedSecurityEmitsFlatTargetWithNewInsights(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language);
var insights = new[] { GetInsight(Symbols.SPY, InsightDirection.Down, Algorithm.UtcTime) };
var targets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights).ToList();
Assert.AreEqual(1, targets.Count);
// Removing SPY should clear the key in the insight collection
var changes = SecurityChangesTests.RemovedNonInternal(Algorithm.Securities[Symbols.SPY]);
Algorithm.PortfolioConstruction.OnSecuritiesChanged(Algorithm, changes);
// Since we have 3 B, 2 T and 1 X, each security in each sector will get
// B => .166%, T => .25, X => 0% (removed)
var sectorCount = 2;
var groupedBySector = Algorithm.Securities
.Where(pair => pair.Value.Fundamentals?.CompanyReference.IndustryTemplateCode != null)
.GroupBy(pair => pair.Value.Fundamentals.CompanyReference.IndustryTemplateCode);
var expectedTargets = new List<PortfolioTarget>();
foreach (var securities in groupedBySector)
{
var list = securities.ToList();
var amount = Algorithm.Portfolio.TotalPortfolioValue / list.Count / sectorCount *
(1 - Algorithm.Settings.FreePortfolioValuePercentage);
expectedTargets.AddRange(list
.Select(x => new PortfolioTarget(x.Key, x.Key.Value == "SPY" ? 0
: (int)direction * Math.Floor(amount / x.Value.Price))));
}
// Do no include SPY in the insights
insights = Algorithm.Securities.Keys.Where(x => x.Value != "SPY")
.Select(x => GetInsight(x, direction, Algorithm.UtcTime)).ToArray();
// Create target from an empty insights array
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights);
Assert.Greater(Algorithm.Securities.Count, expectedTargets.Count);
AssertTargets(expectedTargets, actualTargets);
}
[TestCase(Language.CSharp, InsightDirection.Up)]
[TestCase(Language.CSharp, InsightDirection.Down)]
[TestCase(Language.CSharp, InsightDirection.Flat)]
[TestCase(Language.Python, InsightDirection.Up)]
[TestCase(Language.Python, InsightDirection.Down)]
[TestCase(Language.Python, InsightDirection.Flat)]
public override void FlatDirectionNotAccountedToAllocation(Language language, InsightDirection direction)
{
SetPortfolioConstruction(language);
// Since we have 3 B, 2 T and 1 X, each security in each sector will get
// B => .166%, T => .25, X => 0% (removed)
var sectorCount = 2;
var groupedBySector = Algorithm.Securities
.Where(pair => pair.Value.Fundamentals?.CompanyReference.IndustryTemplateCode != null)
.GroupBy(pair => pair.Value.Fundamentals.CompanyReference.IndustryTemplateCode);
var expectedTargets = new List<PortfolioTarget>();
foreach (var securities in groupedBySector)
{
var list = securities.ToList();
var amount = Algorithm.Portfolio.TotalPortfolioValue / list.Count / sectorCount *
(1 - Algorithm.Settings.FreePortfolioValuePercentage);
expectedTargets.AddRange(list
.Select(x => new PortfolioTarget(x.Key, x.Key.Value == "SPY" ? 0
: (int)direction * Math.Floor(amount / x.Value.Price))));
}
var insights = Algorithm.Securities.Keys.Select(x =>
{
// SPY insight direction is flat
var actualDirection = x.Value == "SPY" ? InsightDirection.Flat : direction;
return GetInsight(x, actualDirection, Algorithm.UtcTime);
});
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights.ToArray());
Assert.Greater(Algorithm.Securities.Count, expectedTargets.Count);
AssertTargets(expectedTargets, actualTargets);
}
[Test]
[TestCase(Language.CSharp)]
[TestCase(Language.Python)]
public void WeightsBySectorProportionally(Language language)
{
SetPortfolioConstruction(language);
// create two insights whose weights sums up to 2
var insights = Algorithm.Securities
.Select(x => GetInsight(x.Key, InsightDirection.Up, Algorithm.UtcTime))
.ToArray();
// Since we have 3 B, 2 T and 1 X, each security in each secotr will get B => .11%, T => .165, X => .33%
var sectorCount = 3;
var groupedBySector = Algorithm.Securities
.Where(pair => pair.Value.Fundamentals?.CompanyReference.IndustryTemplateCode != null)
.Where(pair => insights.Any(insight => pair.Key == insight.Symbol))
.GroupBy(pair => pair.Value.Fundamentals.CompanyReference.IndustryTemplateCode);
var expectedTargets = new List<PortfolioTarget>();
foreach (var securities in groupedBySector)
{
var list = securities.ToList();
var amount = Algorithm.Portfolio.TotalPortfolioValue / list.Count / sectorCount *
(1 - Algorithm.Settings.FreePortfolioValuePercentage);
expectedTargets.AddRange(list
.Select(x => new PortfolioTarget(x.Key, (int)InsightDirection.Up * Math.Floor(amount / x.Value.Price))));
}
var actualTargets = Algorithm.PortfolioConstruction.CreateTargets(Algorithm, insights).ToList();
Assert.AreEqual(6, actualTargets.Count);
Assert.Greater(Algorithm.Securities.Count, expectedTargets.Count);
AssertTargets(expectedTargets, actualTargets);
}
public override Insight GetInsight(Symbol symbol, InsightDirection direction, DateTime generatedTimeUtc, TimeSpan? period = null, double? weight = _weight)
{
period ??= TimeSpan.FromDays(1);
var insight = Insight.Price(symbol, period.Value, direction, weight: weight);
insight.GeneratedTimeUtc = generatedTimeUtc;
insight.CloseTimeUtc = generatedTimeUtc.Add(period.Value);
Algorithm.Insights.Add(insight);
return insight;
}
public override IPortfolioConstructionModel GetPortfolioConstructionModel(Language language, dynamic paramenter = null)
{
if (language == Language.CSharp)
{
return new SectorWeightingPortfolioConstructionModel(paramenter);
}
using (Py.GIL())
{
const string name = nameof(SectorWeightingPortfolioConstructionModel);
var instance = Py.Import(name).GetAttr(name).Invoke(((object)paramenter).ToPython());
return new PortfolioConstructionModelPythonWrapper(instance);
}
}
private class TestFundamentalDataProvider : IFundamentalDataProvider
{
private readonly Dictionary<SecurityIdentifier, string> _industryTemplateCodeDict;
public TestFundamentalDataProvider(Dictionary<SecurityIdentifier, string> industryTemplateCodeDict)
{
_industryTemplateCodeDict = industryTemplateCodeDict;
}
public T Get<T>(DateTime time, SecurityIdentifier securityIdentifier, FundamentalProperty name)
{
if (securityIdentifier == SecurityIdentifier.Empty)
{
return default;
}
return Get(time, securityIdentifier, name);
}
private dynamic Get(DateTime time, SecurityIdentifier securityIdentifier, FundamentalProperty enumName)
{
var name = Enum.GetName(enumName);
switch (name)
{
case "CompanyReference_IndustryTemplateCode":
if(_industryTemplateCodeDict.TryGetValue(securityIdentifier, out var result))
{
return result;
}
return null;
}
return null;
}
public void Initialize(IDataProvider dataProvider, bool liveMode)
{
}
}
}
}
Tests/Algorithm/Framework/Portfolio/SignalExportTargetTests.cs
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/*
* 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 NUnit.Framework;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Algorithm.Framework.Portfolio.SignalExports;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Interfaces;
using QuantConnect.Orders;
using QuantConnect.Orders.Fees;
using QuantConnect.Securities;
using QuantConnect.Tests.Engine.DataFeeds;
using System;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class SignalExportTargetTests
{
[TestCaseSource(nameof(SendsTargetsToCollective2AppropriatelyTestCases))]
public void SendsTargetsToCollective2Appropriately(string currency, Symbol symbol, decimal quantity, string expectedMessage)
{
var targetList = new List<PortfolioTarget>() { new(symbol, quantity) };
var algorithm = new AlgorithmStub();
algorithm.SetDateTime(new DateTime(2016, 02, 16, 11, 53, 30));
algorithm.Portfolio.SetAccountCurrency(currency);
var security = algorithm.AddSecurity(symbol);
security.QuoteCurrency.ConversionRate = 1;
security.FeeModel = new ConstantFeeModel(0);
security.SetMarketPrice(new Tick { Value = 100 });
var initialMarginRequirement = security.BuyingPowerModel.GetInitialMarginRequirement(new(security, 1));
if (initialMarginRequirement.Value == 0)
{
security.SetBuyingPowerModel(BuyingPowerModel.Null);
}
algorithm.Portfolio.SetCash(1500000);
using var manager = new Collective2SignalExportHandler("", 0);
var message = manager.GetMessageSent(new SignalExportTargetParameters { Targets = targetList, Algorithm = algorithm });
Assert.AreEqual(expectedMessage, message);
}
[Test]
public void Collective2SignalExportManagerDoesNotLogMoreThanOnceWhenUnknownMarket()
{
var targetList = new List<PortfolioTarget>() { new(Symbols.EURUSD, 1), new PortfolioTarget(Symbols.GBPUSD, 1) };
var algorithm = new AlgorithmStub();
algorithm.SetDateTime(new DateTime(2016, 02, 16, 11, 53, 30));
algorithm.Portfolio.SetAccountCurrency("USD");
var security = algorithm.AddSecurity(Symbols.EURUSD);
var security2 = algorithm.AddSecurity(Symbols.GBPUSD);
security.SetMarketPrice(new Tick { Value = 100 });
security2.SetMarketPrice(new Tick { Value = 100 });
algorithm.Portfolio.SetCash(50000);
using var manager = new Collective2SignalExportHandler("", 0);
for (int count = 0; count < 100; count++)
{
manager.GetMessageSent(new SignalExportTargetParameters { Targets = targetList, Algorithm = algorithm });
}
Assert.AreEqual(3, algorithm.DebugMessages.Count);
var debugMessages = algorithm.DebugMessages.ToList();
Assert.IsTrue(debugMessages[0].Contains($"The market of the symbol {Symbols.EURUSD.Value} was unexpected: {Symbols.EURUSD.ID.Market}. Using 'DEFAULT' as market", StringComparison.InvariantCultureIgnoreCase));
Assert.IsTrue(debugMessages[1].Contains($"Warning: Collective2 failed to calculate target quantity for {targetList[0]}. The smallest quantity C2 trades is \"1\" which is a mini-lot (10,000 currency units), and the target quantity is 498. Will return 0 for all similar cases.", StringComparison.InvariantCultureIgnoreCase));
Assert.IsTrue(debugMessages[2].Contains($"The market of the symbol {Symbols.GBPUSD.Value} was unexpected: {Symbols.GBPUSD.ID.Market}. Using 'DEFAULT' as market", StringComparison.InvariantCultureIgnoreCase));
}
[Test]
public void Collective2SignalExportManagerDoesNotLogMoreThanOnceWhenUnknownSecurityType()
{
var targetList = new List<PortfolioTarget>() { new(Symbols.BTCUSD, 1), new PortfolioTarget(Symbols.XAUJPY, 1) };
var algorithm = new AlgorithmStub();
algorithm.SetDateTime(new DateTime(2016, 02, 16, 11, 53, 30));
algorithm.Portfolio.SetAccountCurrency("USD");
var security = algorithm.AddSecurity(Symbols.BTCUSD);
var security2 = algorithm.AddSecurity(Symbols.XAUJPY);
security.SetMarketPrice(new Tick { Value = 100 });
security2.SetMarketPrice(new Tick { Value = 100 });
algorithm.Portfolio.SetCash(50000);
using var manager = new Collective2SignalExportHandler("", 0);
for (int count = 0; count < 100; count++)
{
manager.GetMessageSent(new SignalExportTargetParameters { Targets = targetList, Algorithm = algorithm });
}
Assert.AreEqual(2, algorithm.DebugMessages.Count);
var debugMessages = algorithm.DebugMessages.ToList();
Assert.IsTrue(debugMessages[0].Contains($"Unexpected security type found: {security.Symbol.SecurityType}. Collective2 just accepts: Equity, Future, Option, Index Option and Stock", StringComparison.InvariantCultureIgnoreCase));
Assert.IsTrue(debugMessages[1].Contains($"Unexpected security type found: {security2.Symbol.SecurityType}. Collective2 just accepts: Equity, Future, Option, Index Option and Stock", StringComparison.InvariantCultureIgnoreCase));
}
[Test]
public void Collective2ConvertsPercentageToQuantityAppropriately()
{
var symbols = new List<Symbol>()
{
Symbols.SPY,
Symbols.EURUSD,
Symbols.AAPL,
Symbols.IBM,
Symbols.GOOG,
Symbols.MSFT,
Symbols.CAT
};
var targetList = new List<PortfolioTarget>()
{
new PortfolioTarget(Symbols.SPY, (decimal)0.01),
new PortfolioTarget(Symbols.EURUSD, (decimal)0.99),
new PortfolioTarget(Symbols.AAPL, (decimal)(-0.01)),
new PortfolioTarget(Symbols.IBM, (decimal)(-0.99)),
new PortfolioTarget(Symbols.GOOG, (decimal)0.0),
new PortfolioTarget(Symbols.MSFT, (decimal)1.0),
new PortfolioTarget(Symbols.CAT, (decimal)(-1.0))
};
var algorithm = new AlgorithmStub();
AddSymbols(symbols, algorithm);
algorithm.Portfolio.SetCash(50000);
algorithm.Settings.MinimumOrderMarginPortfolioPercentage = 0;
algorithm.Settings.FreePortfolioValue = 250;
using var manager = new Collective2SignalExportHandler("", 0);
var expectedQuantities = new Dictionary<string, int>()
{
{ "SPY", 4 },
// 492 was rounded down to zero because 1 is a minilot of 10,000 USD
// https://support.collective2.com/hc/en-us/articles/360038042774-Forex-minilots
{ "EURUSD", 0},
{ "AAPL", -4 },
{ "IBM", -492 },
{ "GOOG", 0 },
{ "MSFT", 497 },
{ "CAT", -497 }
};
foreach (var target in targetList)
{
var quantity = manager.ConvertPercentageToQuantity(algorithm, target);
Assert.AreEqual(expectedQuantities[target.Symbol.Value], quantity);
}
}
[Test]
public void SendsTargetsToCrunchDAOAppropriately()
{
var symbols = new List<Symbol>()
{
Symbols.SPY,
Symbols.AAPL,
Symbols.CAT
};
var targetList = new List<PortfolioTarget>()
{
new PortfolioTarget(Symbols.SPY, (decimal)0.2),
new PortfolioTarget(Symbols.AAPL, (decimal)0.2),
new PortfolioTarget(Symbols.CAT, (decimal)0.2),
};
var algorithm = new AlgorithmStub();
AddSymbols(symbols, algorithm);
using var manager = new CrunchDAOSignalExportHandler("", "");
var message = manager.GetMessageSent(new SignalExportTargetParameters { Targets = targetList, Algorithm = algorithm });
var expectedMessage = "ticker,date,signal\nSPY,2016-02-16,0.2\nAAPL,2016-02-16,0.2\nCAT,2016-02-16,0.2\n";
Assert.AreEqual(expectedMessage, message);
}
[Test]
public void CrunchDAOSignalExportReturnsFalseWhenSymbolIsNotAllowed()
{
var symbols = new List<Symbol>()
{
Symbols.ES_Future_Chain,
Symbols.SPY_Option_Chain,
Symbols.EURUSD,
Symbols.BTCUSD,
};
var targetList = new List<PortfolioTarget>();
foreach (var symbol in symbols)
{
targetList.Add(new PortfolioTarget(symbol, (decimal)0.1));
}
var algorithm = new AlgorithmStub();
AddSymbols(symbols, algorithm);
algorithm.Portfolio.SetCash(50000);
using var manager = new CrunchDAOSignalExport("", "");
var result = manager.Send(new SignalExportTargetParameters { Targets = targetList, Algorithm = algorithm });
Assert.IsFalse(result);
}
[Test]
public void CrunchDAOSignalExportReturnsFalseWhenPortfolioTargetListIsEmpty()
{
var targetList = new List<PortfolioTarget>();
using var manager = new CrunchDAOSignalExport("", "");
var algorithm = new QCAlgorithm();
var result = manager.Send(new SignalExportTargetParameters { Targets = targetList, Algorithm = algorithm });
Assert.IsFalse(result);
}
[Test]
public void SendsTargetsToNumeraiAppropriately()
{
var targets = new List<PortfolioTarget>()
{
new PortfolioTarget(Symbols.SGX, (decimal)0.05),
new PortfolioTarget(Symbols.AAPL, (decimal)0.1),
new PortfolioTarget(Symbols.MSFT, (decimal)0.1),
new PortfolioTarget(Symbols.ZNGA, (decimal)0.05),
new PortfolioTarget(Symbols.FXE, (decimal)0.05),
new PortfolioTarget(Symbols.LODE, (decimal)0.05),
new PortfolioTarget(Symbols.IBM, (decimal)0.05),
new PortfolioTarget(Symbols.GOOG, (decimal)0.1),
new PortfolioTarget(Symbols.NFLX, (decimal)0.1),
new PortfolioTarget(Symbols.CAT, (decimal)0.1)
};
using var manager = new NumeraiSignalExportHandler("", "", "");
var algorithm = new QCAlgorithm();
algorithm.SetDateTime(new DateTime(2023, 03, 03));
var message = manager.GetMessageSent(new SignalExportTargetParameters { Targets = targets, Algorithm = algorithm });
var expectedMessage = "numerai_ticker,signal\nSGX SP,0.05\nAAPL US,0.1\nMSFT US,0.1\nZNGA US,0.05\nFXE US,0.05\nLODE US,0.05\nIBM US,0.05\nGOOG US,0.1\nNFLX US,0.1\nCAT US,0.1\n";
Assert.AreEqual(expectedMessage, message);
}
[Test]
public void NumeraiReturnsFalseWhenSymbolIsNotAllowed()
{
var targets = new List<PortfolioTarget>()
{
new PortfolioTarget(Symbols.SGX, (decimal)0.05),
new PortfolioTarget(Symbols.AAPL, (decimal)0.1),
new PortfolioTarget(Symbols.MSFT, (decimal)0.1),
new PortfolioTarget(Symbols.ZNGA, (decimal)0.05),
new PortfolioTarget(Symbols.FXE, (decimal)0.05),
new PortfolioTarget(Symbols.LODE, (decimal)0.05),
new PortfolioTarget(Symbols.IBM, (decimal)0.05),
new PortfolioTarget(Symbols.GOOG, (decimal)0.1),
new PortfolioTarget(Symbols.NFLX, (decimal)0.1),
new PortfolioTarget(Symbols.EURUSD, (decimal)0.1)
};
using var manager = new NumeraiSignalExport("", "", "");
var algorithm = new QCAlgorithm();
var result = manager.Send(new SignalExportTargetParameters { Targets = targets, Algorithm = algorithm });
Assert.IsFalse(result);
}
[Test]
public void NumeraiReturnsFalseWhenNumberOfTargetsIsLessThanTen()
{
var targets = new List<PortfolioTarget>()
{
new PortfolioTarget(Symbols.SGX, (decimal)0.05),
new PortfolioTarget(Symbols.AAPL, (decimal)0.1),
new PortfolioTarget(Symbols.MSFT, (decimal)0.1),
new PortfolioTarget(Symbols.ZNGA, (decimal)0.05),
new PortfolioTarget(Symbols.FXE, (decimal)0.05),
new PortfolioTarget(Symbols.LODE, (decimal)0.05),
new PortfolioTarget(Symbols.IBM, (decimal)0.05),
new PortfolioTarget(Symbols.GOOG, (decimal)0.1),
new PortfolioTarget(Symbols.NFLX, (decimal)0.1),
};
using var manager = new NumeraiSignalExport("", "", "");
var algorithm = new QCAlgorithm();
var result = manager.Send(new SignalExportTargetParameters { Targets = targets, Algorithm = algorithm });
Assert.IsFalse(result);
}
[TestCase(SecurityType.Equity, "SPY", 68)]
[TestCase(SecurityType.Equity, "AAPL", -68)]
[TestCase(SecurityType.Equity, "GOOG", 345)]
[TestCase(SecurityType.Equity, "IBM", 0)]
[TestCase(SecurityType.Forex, "EURUSD", 90)]
[TestCase(SecurityType.Forex, "EURUSD", -90)]
[TestCase(SecurityType.Future, "ES", 4)]
[TestCase(SecurityType.Future, "ES", -4)]
public void SignalExportManagerGetsCorrectPortfolioTargetArray(SecurityType securityType, string ticker, int quantity)
{
var algorithm = new AlgorithmStub(true);
algorithm.SetFinishedWarmingUp();
algorithm.SetCash(100000);
var security = algorithm.AddSecurity(securityType, ticker);
security.SetMarketPrice(new Tick(new DateTime(2022, 01, 04), security.Symbol, 144.80m, 144.82m));
security.Holdings.SetHoldings(144.81m, quantity);
var signalExportManagerHandler = new SignalExportManagerHandler(algorithm);
var result = signalExportManagerHandler.GetPortfolioTargets(out PortfolioTarget[] portfolioTargets);
Assert.IsTrue(result);
var target = portfolioTargets[0];
var targetQuantity = (int)PortfolioTarget.Percent(algorithm, target.Symbol, target.Quantity).Quantity;
// The quantites can differ by one because of the number of lots for certain securities
Assert.AreEqual(quantity, targetQuantity, 1);
}
[Test]
public void SignalExportManagerDoesNotThrowOnZeroPrice()
{
var algorithm = new AlgorithmStub(true);
algorithm.SetDateTime(new DateTime(2024, 02, 16, 11, 53, 30));
var security = algorithm.AddSecurity(Symbols.SPY);
// Set the market price to 0 to simulate the edge case being tested
security.SetMarketPrice(new Tick { Value = 0 });
using var manager = new Collective2SignalExportHandler("", 0);
// Ensure ConvertPercentageToQuantity does not throw when price is 0
Assert.DoesNotThrow(() =>
{
var result = manager.ConvertPercentageToQuantity(algorithm, new PortfolioTarget(Symbols.SPY, 0));
Assert.AreEqual(0, result);
});
}
[Test]
public void SignalExportManagerHandlesIndexOptions()
{
var algorithm = new AlgorithmStub(true);
algorithm.SetFinishedWarmingUp();
algorithm.SetCash(100000);
int quantity = 123;
var underlying = algorithm.AddIndex("SPX", Resolution.Minute).Symbol;
// Create the option contract (IndexOption) with specific parameters
var option = Symbol.CreateOption(
underlying,
"SPXW",
Market.USA,
OptionStyle.European,
OptionRight.Call,
3800m,
new DateTime(2021, 1, 04));
var security = algorithm.AddIndexOptionContract(option, Resolution.Minute);
security.SetMarketPrice(new Tick(new DateTime(2022, 01, 04), security.Symbol, 144.80m, 144.82m));
security.Holdings.SetHoldings(144.81m, quantity);
// Initialize the SignalExportManagerHandler and get portfolio targets
var signalExportManagerHandler = new SignalExportManagerHandler(algorithm);
var result = signalExportManagerHandler.GetPortfolioTargets(out PortfolioTarget[] portfolioTargets);
// Assert that the result is successful
Assert.IsTrue(result);
// Get the portfolio target and verify the quantity matches
var target = portfolioTargets[0];
var targetQuantity = (int)PortfolioTarget.Percent(algorithm, target.Symbol, target.Quantity).Quantity;
Assert.AreEqual(quantity, targetQuantity);
// Ensure the symbol is of type IndexOption
Assert.IsTrue(target.Symbol.SecurityType == SecurityType.IndexOption);
}
[Test]
public void SignalExportManagerIgnoresIndexSecurities()
{
var algorithm = new AlgorithmStub(true);
algorithm.SetFinishedWarmingUp();
algorithm.SetCash(100000);
var security = algorithm.AddIndexOption("SPX", "SPXW");
security.SetMarketPrice(new Tick(new DateTime(2022, 01, 04), security.Symbol, 144.80m, 144.82m));
security.Holdings.SetHoldings(144.81m, 10);
var signalExportManagerHandler = new SignalExportManagerHandler(algorithm);
var result = signalExportManagerHandler.GetPortfolioTargets(out PortfolioTarget[] portfolioTargets);
Assert.IsTrue(result);
Assert.IsFalse(portfolioTargets.Where(x => x.Symbol.SecurityType == SecurityType.Index).Any());
}
[TestCaseSource(nameof(SignalExportManagerSkipsNonTradeableFuturesTestCase))]
public void SignalExportManagerSkipsNonTradeableFutures(IEnumerable<Symbol> symbols, int expectedNumberOfTargets)
{
var algorithm = new AlgorithmStub(true);
algorithm.SetFinishedWarmingUp();
algorithm.SetCash(100000);
foreach (var symbol in symbols)
{
var security = algorithm.AddSecurity(symbol);
security.SetMarketPrice(new Tick(new DateTime(2022, 01, 04), security.Symbol, 144.80m, 144.82m));
security.Holdings.SetHoldings(144.81m, 100);
}
var signalExportManagerHandler = new SignalExportManagerHandler(algorithm);
var result = signalExportManagerHandler.GetPortfolioTargets(out PortfolioTarget[] portfolioTargets);
Assert.IsTrue(result);
Assert.AreEqual(expectedNumberOfTargets, portfolioTargets.Length);
}
[Test]
public void SignalExportManagerReturnsFalseWhenNegativeTotalPortfolioValue()
{
var algorithm = new AlgorithmStub(true);
algorithm.SetFinishedWarmingUp();
algorithm.SetCash(-100000);
var signalExportManagerHandler = new SignalExportManagerHandler(algorithm);
Assert.IsFalse(signalExportManagerHandler.GetPortfolioTargets(out _));
}
[Test]
public void EmptySignalExportList()
{
var algorithm = new AlgorithmStub(true);
algorithm.SetLiveMode(true);
algorithm.SetFinishedWarmingUp();
algorithm.SetCash(100000);
var security = algorithm.AddSecurity(Symbols.SPY);
security.SetMarketPrice(new Tick(new DateTime(2022, 01, 04), security.Symbol, 144.80m, 144.82m));
security.Holdings.SetHoldings(144.81m, 100);
var utcTime = DateTime.UtcNow;
var signalExportManagerHandler = new SignalExportManagerHandler(algorithm);
signalExportManagerHandler.OnOrderEvent(new OrderEvent(0, security.Symbol, utcTime.AddMinutes(-1), OrderStatus.Filled, OrderDirection.Buy, 100, 100, new Orders.Fees.OrderFee(new Securities.CashAmount(1, "USD"))));
Assert.DoesNotThrow(() => signalExportManagerHandler.SetTargetPortfolioFromPortfolio());
Assert.DoesNotThrow(() => signalExportManagerHandler.Flush(utcTime));
}
private static object[] SendsTargetsToCollective2AppropriatelyTestCases =
{
new object[] { "USD", Symbols.SPY, 0.2m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""SPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""CS""},""quantity"":2992.0}]}" },
new object[] { "USD", Symbols.EURUSD, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""EUR/USD"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "USD", Symbols.EURGBP, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""EUR/GBP"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "USD", Symbols.GBPJPY, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""GBP/JPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "USD", Symbols.GBPUSD, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""GBP/USD"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "USD", Symbols.USDJPY, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""USD/JPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "USD", Symbols.CreateOptionSymbol("SPY", OptionRight.Call, 192m, new DateTime(2016, 02, 15)), 0.2m, @"{""StrategyId"":0,""Positions"":[]}" },
new object[] { "USD", Symbols.CreateOptionSymbol("SPY", OptionRight.Call, 192m, new DateTime(2056, 02, 19)), 0.2m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""SPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""OPT"",""maturityMonthYear"":""20560218"",""putOrCall"":1,""strikePrice"":192.0},""quantity"":29.0}]}" },
new object[] { "USD", Symbols.CreateOptionSymbol("SPY", OptionRight.Put, 192m, new DateTime(2056, 02, 19)), 0.2m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""SPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""OPT"",""maturityMonthYear"":""20560218"",""putOrCall"":0,""strikePrice"":192.0},""quantity"":29.0}]}" },
new object[] { "USD", Symbol.Create("EURUSD", SecurityType.Forex, Market.FXCM), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""EUR/USD"",""currency"":""USD"",""securityExchange"":""FXCM"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "USD", Symbol.Create("NQX", SecurityType.IndexOption, Market.USA), 0.2m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""NQX"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""OPT"",""putOrCall"":1,""strikePrice"":0.0},""quantity"":29.0}]}" },
new object[] { "USD", Symbol.CreateFuture("NIFTY", Market.India, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""NIFTY"",""currency"":""INR"",""securityExchange"":""XNSE"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":299250.0}]}" },
new object[] { "USD", Symbol.CreateFuture("HSI", Market.HKFE, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""HSI"",""currency"":""HKD"",""securityExchange"":""XHKF"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":24.0}]}" },
new object[] { "USD", Symbol.CreateFuture("ZG", Market.NYSELIFFE, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""ZG"",""currency"":""USD"",""securityExchange"":""XNLI"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":73.0}]}" },
new object[] { "USD", Symbol.CreateFuture("FESX", Market.EUREX, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""FESX"",""currency"":""EUR"",""securityExchange"":""XEUR"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":498.0}]}" },
new object[] { "USD", Symbol.CreateFuture("KC", Market.ICE, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""KC"",""currency"":""USD"",""securityExchange"":""IEPA"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":415.0}]}" },
new object[] { "USD", Symbol.CreateFuture("VIX", Market.CFE, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""VIX"",""currency"":""USD"",""securityExchange"":""XCBF"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":14962.0}]}" },
new object[] { "USD", Symbol.CreateFuture("ZC", Market.CBOT, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""ZC"",""currency"":""USD"",""securityExchange"":""XCBT"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":2770.0}]}" },
new object[] { "USD", Symbol.CreateFuture("GC", Market.COMEX, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""GC"",""currency"":""USD"",""securityExchange"":""XCEC"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":316.0}]}" },
new object[] { "USD", Symbol.CreateFuture("CL", Market.NYMEX, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""CL"",""currency"":""USD"",""securityExchange"":""XNYM"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":201.0}]}" },
new object[] { "USD", Symbol.CreateFuture("NK", Market.SGX, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""NK"",""currency"":""JPY"",""securityExchange"":""XSES"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":425.0}]}" },
new object[] { "EUR", Symbols.SPY, 0.2m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""SPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""CS""},""quantity"":2992.0}]}" },
new object[] { "EUR", Symbols.EURUSD, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""EUR/USD"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "EUR", Symbols.EURGBP, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""EUR/GBP"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "EUR", Symbols.GBPJPY, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""GBP/JPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "EUR", Symbols.GBPUSD, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""GBP/USD"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "EUR", Symbols.USDJPY, 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""USD/JPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "EUR", Symbols.CreateOptionSymbol("SPY", OptionRight.Call, 192m, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""SPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""OPT"",""maturityMonthYear"":""20560218"",""putOrCall"":1,""strikePrice"":192.0},""quantity"":149.0}]}" },
new object[] { "EUR", Symbols.CreateOptionSymbol("SPY", OptionRight.Put, 192m, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""SPY"",""currency"":""USD"",""securityExchange"":""DEFAULT"",""securityType"":""OPT"",""maturityMonthYear"":""20560218"",""putOrCall"":0,""strikePrice"":192.0},""quantity"":149.0}]}" },
new object[] { "EUR", Symbols.CreateOptionSymbol("SPY", OptionRight.Call, 192m, new DateTime(2016, 02, 15)), 0.2m, @"{""StrategyId"":0,""Positions"":[]}" },
new object[] { "EUR", Symbol.Create("EURUSD", SecurityType.Forex, Market.FXCM), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""EUR/USD"",""currency"":""USD"",""securityExchange"":""FXCM"",""securityType"":""FOR""},""quantity"":1.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("NIFTY", Market.India, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""NIFTY"",""currency"":""INR"",""securityExchange"":""XNSE"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":299250.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("HSI", Market.HKFE, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""HSI"",""currency"":""HKD"",""securityExchange"":""XHKF"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":24.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("ZG", Market.NYSELIFFE, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""ZG"",""currency"":""USD"",""securityExchange"":""XNLI"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":73.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("FESX", Market.EUREX, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""FESX"",""currency"":""EUR"",""securityExchange"":""XEUR"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":498.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("KC", Market.ICE, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""KC"",""currency"":""USD"",""securityExchange"":""IEPA"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":415.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("VIX", Market.CFE, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""VIX"",""currency"":""EUR"",""securityExchange"":""XCBF"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":14962.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("ZC", Market.CBOT, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""ZC"",""currency"":""USD"",""securityExchange"":""XCBT"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":2770.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("GC", Market.COMEX, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""GC"",""currency"":""USD"",""securityExchange"":""XCEC"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":316.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("CL", Market.NYMEX, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""CL"",""currency"":""USD"",""securityExchange"":""XNYM"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":201.0}]}" },
new object[] { "EUR", Symbol.CreateFuture("NK", Market.SGX, new DateTime(2056, 02, 19)), 1m, @"{""StrategyId"":0,""Positions"":[{""exchangeSymbol"":{""symbol"":""NK"",""currency"":""JPY"",""securityExchange"":""XSES"",""securityType"":""FUT"",""maturityMonthYear"":""20560219""},""quantity"":425.0}]}" },
};
private static void AddSymbols(List<Symbol> symbols, QCAlgorithm algorithm)
{
algorithm.SetDateTime(new DateTime(2016, 02, 16, 11, 53, 30));
foreach (var symbol in symbols)
{
var security = algorithm.AddSecurity(symbol);
security.SetMarketPrice(new Tick { Value = 100 });
}
}
/// <summary>
/// Creates a TradebarConfiguration for the given symbol
/// </summary>
/// <param name="symbol">Symbol for which we want to create a TradeBarConfiguration</param>
/// <returns>A new TradebarConfiguration for the given symbol</returns>
private static SubscriptionDataConfig CreateTradeBarConfig(Symbol symbol)
{
return new SubscriptionDataConfig(typeof(TradeBar), symbol, Resolution.Minute, TimeZones.NewYork, TimeZones.NewYork, true, true, false);
}
/// <summary>
/// Handler class to test how SignalExportManager obtains the portfolio targets from the algorithm's portfolio
/// </summary>
private class SignalExportManagerHandler : SignalExportManager
{
public SignalExportManagerHandler(IAlgorithm algorithm) : base(algorithm)
{
}
/// <summary>
/// Handler method to obtain portfolio targets from algorithm's portfolio
/// </summary>
/// <param name="targets">An array of portfolio targets from the algorithm's Portfolio</param>
/// <returns>True if TotalPortfolioValue was bigger than zero</returns>
public bool GetPortfolioTargets(out PortfolioTarget[] targets)
{
return base.GetPortfolioTargets(out targets);
}
}
/// <summary>
/// Handler class to test how Collective2SignalExport converts target percentage to number of shares. Additionally,
/// to test the message sent to Collective2 API
/// </summary>
private class Collective2SignalExportHandler : Collective2SignalExport
{
public Collective2SignalExportHandler(string apiKey, int systemId) : base(apiKey, systemId)
{
}
/// <summary>
/// Handler method to test how Collective2SignalExport converts target percentage to number of shares
/// </summary>
/// <param name="algorithm">Algorithm being ran</param>
/// <param name="target">Target with quantity as percentage</param>
/// <returns>Number of shares for the given target percentage</returns>
public int ConvertPercentageToQuantity(IAlgorithm algorithm, PortfolioTarget target)
{
return base.ConvertPercentageToQuantity(algorithm, target);
}
/// <summary>
/// Handler method to test the message sent to Collective2 API
/// </summary>
/// <param name="parameters">A list of holdings from the portfolio
/// expected to be sent to Collective2 API and the algorithm being ran</param>
/// <returns>Message sent to Collective2 API</returns>
public string GetMessageSent(SignalExportTargetParameters parameters)
{
ConvertHoldingsToCollective2(parameters, out List<Collective2Position> positions);
var message = CreateMessage(positions);
return message;
}
}
/// <summary>
/// Handler class to test the message sent to CrunchDAO API
/// </summary>
private class CrunchDAOSignalExportHandler : CrunchDAOSignalExport
{
public CrunchDAOSignalExportHandler(string apiKey, string model, string submissionName = "", string comment = "") : base(apiKey, model, submissionName, comment)
{
}
/// <summary>
/// Handler method to test the message sent to CrunchDAO API
/// </summary>
/// <param name="parameters">A list of holdings from the portfolio
/// expected to be sent to CrunchDAO2 API and the algorithm being ran</param>
/// <returns>Message sent to CrunchDAO API</returns>
public string GetMessageSent(SignalExportTargetParameters parameters)
{
ConvertToCSVFormat(parameters, out string message);
return message;
}
}
/// <summary>
/// Handler class to test message sent to Numerai API
/// </summary>
private class NumeraiSignalExportHandler : NumeraiSignalExport
{
public NumeraiSignalExportHandler(string publicId, string secretId, string modelId, string fileName = "predictions.csv") : base(publicId, secretId, modelId, fileName)
{
}
/// <summary>
/// Handler method to test the message sent to Numerai API
/// </summary>
/// <param name="parameters">A list of holdings from the portfolio
/// expected to be sent to Numerai API and the algorithm being ran</param>
/// <returns>Message sent to Numerai API</returns>
public string GetMessageSent(SignalExportTargetParameters parameters)
{
ConvertTargetsToNumerai(parameters, out string message);
return message;
}
}
private static object[] SignalExportManagerSkipsNonTradeableFuturesTestCase =
{
new object[] { new List<Symbol>() { Symbols.AAPL, Symbols.SPY, Symbols.SPX }, 2 },
new object[] { new List<Symbol>() { Symbols.AAPL, Symbols.SPY, Symbols.NFLX }, 3 },
};
}
}
Tests/Algorithm/Framework/Portfolio/UnconstrainedMeanVariancePortfolioOptimizerTests.cs
+76
View File
@@ -0,0 +1,76 @@
/*
* 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 aaplicable 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 NUnit.Framework;
using QuantConnect.Algorithm.Framework.Portfolio;
using System.Collections.Generic;
namespace QuantConnect.Tests.Algorithm.Framework.Portfolio
{
[TestFixture]
public class UnconstrainedMeanVariancePortfolioOptimizerTests : PortfolioOptimizerTestsBase
{
[OneTimeSetUp]
public void Setup()
{
HistoricalReturns = new List<double[,]>
{
new double[,] { { 0.76, -0.06, 1.22, 0.17 }, { 0.02, 0.28, 1.25, -0.00 }, { -0.50, -0.13, -0.50, -0.03 }, { 0.81, 0.31, 2.39, 0.26 }, { -0.02, 0.02, 0.06, 0.01 } },
new double[,] { { -0.15, 0.67, 0.45 }, { -0.44, -0.10, 0.07 }, { 0.04, -0.41, 0.01 }, { 0.01, 0.03, 0.02 } },
new double[,] { { -0.02, 0.65, 1.25 }, { -0.29, -0.39, -0.50 }, { 0.29, 0.58, 2.39 }, { 0.00, -0.01, 0.06 } },
new double[,] { { 0.76, 0.25, 0.21 }, { 0.02, -0.15, 0.45 }, { -0.50, -0.44, 0.07 }, { 0.81, 0.04, 0.01 }, { -0.02, 0.01, 0.02 } }
};
ExpectedReturns = new List<double[]>
{
new double[] { 0.21, 0.08, 0.88, 0.08 },
new double[] { -0.13, 0.05, 0.14 },
null,
null
};
Covariances = new List<double[,]>
{
new double[,] { { 0.31, 0.05, 0.55, 0.07 }, { 0.05, 0.04, 0.18, 0.01 }, { 0.55, 0.18, 1.28, 0.12 }, { 0.07, 0.01, 0.12, 0.02 } },
new double[,] { { 0.05, -0.02, -0.01 }, { -0.02, 0.21, 0.09 }, { -0.01, 0.09, 0.04 } },
new double[,] { { 0.06, 0.09, 0.28 }, { 0.09, 0.25, 0.58 }, { 0.28, 0.58, 1.66 } },
null
};
ExpectedResults = new List<double[]>
{
new double[] { -13.288136, -23.322034, 8.79661, 9.389831 },
new double[] { -0.142857, -35.285714, 82.857143 },
new double[] { -13.232262, -3.709534, 4.009978 },
new double[] { 4.621852, -9.651736, 5.098332 },
};
}
protected override IPortfolioOptimizer CreateOptimizer()
{
return new UnconstrainedMeanVariancePortfolioOptimizer();
}
[TestCase(0)]
[TestCase(1)]
[TestCase(2)]
[TestCase(3)]
public override void OptimizeWeightings(int testCaseNumber)
{
base.OptimizeWeightings(testCaseNumber);
}
}
}