BoundedMarkovitzBullet.java
package org.drip.sample.efficientfrontier;
import java.util.*;
import org.drip.function.rdtor1descent.LineStepEvolutionControl;
import org.drip.function.rdtor1solver.InteriorPointBarrierControl;
import org.drip.measure.statistics.MultivariateMoments;
import org.drip.numerical.common.FormatUtil;
import org.drip.portfolioconstruction.allocator.*;
import org.drip.portfolioconstruction.asset.*;
import org.drip.portfolioconstruction.mpt.MarkovitzBullet;
import org.drip.portfolioconstruction.params.AssetUniverseStatisticalProperties;
import org.drip.service.env.EnvManager;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2020 Lakshmi Krishnamurthy
* Copyright (C) 2019 Lakshmi Krishnamurthy
* Copyright (C) 2018 Lakshmi Krishnamurthy
* Copyright (C) 2017 Lakshmi Krishnamurthy
* Copyright (C) 2016 Lakshmi Krishnamurthy
*
* This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
* asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
* analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
* equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
* numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
* and computational support.
*
* https://lakshmidrip.github.io/DROP/
*
* DROP is composed of three modules:
*
* - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
* - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
* - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
*
* DROP Product Core implements libraries for the following:
* - Fixed Income Analytics
* - Loan Analytics
* - Transaction Cost Analytics
*
* DROP Portfolio Core implements libraries for the following:
* - Asset Allocation Analytics
* - Asset Liability Management Analytics
* - Capital Estimation Analytics
* - Exposure Analytics
* - Margin Analytics
* - XVA Analytics
*
* DROP Computational Core implements libraries for the following:
* - Algorithm Support
* - Computation Support
* - Function Analysis
* - Model Validation
* - Numerical Analysis
* - Numerical Optimizer
* - Spline Builder
* - Statistical Learning
*
* Documentation for DROP is Spread Over:
*
* - Main => https://lakshmidrip.github.io/DROP/
* - Wiki => https://github.com/lakshmiDRIP/DROP/wiki
* - GitHub => https://github.com/lakshmiDRIP/DROP
* - Repo Layout Taxonomy => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
* - Javadoc => https://lakshmidrip.github.io/DROP/Javadoc/index.html
* - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
* - Release Versions => https://lakshmidrip.github.io/DROP/version.html
* - Community Credits => https://lakshmidrip.github.io/DROP/credits.html
* - Issues Catalog => https://github.com/lakshmiDRIP/DROP/issues
* - JUnit => https://lakshmidrip.github.io/DROP/junit/index.html
* - Jacoco => https://lakshmidrip.github.io/DROP/jacoco/index.html
*
* 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.
*/
/**
* <i>BoundedMarkovitzBullet</i> demonstrates the Construction of the Efficient Frontier using the
* Constrained Mean Variance Optimizer for a Bounded Portfolio.
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/PortfolioCore.md">Portfolio Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/AssetAllocationAnalyticsLibrary.md">Asset Allocation Analytics</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sample/README.md">DROP API Construction and Usage</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sample/efficientfrontier/README.md">Efficient Frontier Markovitz Bullet Variants</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class BoundedMarkovitzBullet
{
private static void DisplayPortfolioMetrics (
final HoldingsAllocation optimalOutput)
throws Exception
{
AssetComponent[] globalMinimumAssetComponentArray =
optimalOutput.optimalPortfolio().assetComponentArray();
String dump = "\t|" +
FormatUtil.FormatDouble (optimalOutput.optimalMetrics().excessReturnsMean(), 1, 4, 100.) + "% |" +
FormatUtil.FormatDouble (optimalOutput.optimalMetrics().excessReturnsStandardDeviation(), 1, 4, 100.) + " |";
for (AssetComponent assetComponent : globalMinimumAssetComponentArray)
{
dump += " " + FormatUtil.FormatDouble (
assetComponent.amount(), 3, 2, 100.
) + "% |";
}
System.out.println (dump + "|");
}
public static final void main (
final String[] argumentArray)
throws Exception
{
EnvManager.InitEnv ("");
String[] assetNameArray = new String[]
{
"TOK",
"EWJ",
"HYG",
"LQD",
"EMD",
"GSG",
"BWX"
};
double[] assetHoldingsLowerBoundArray = new double[]
{
0.05,
0.05,
0.05,
0.10,
0.05,
0.05,
0.03
};
double[] assetHoldingsUpperBoundArray = new double[]
{
0.40,
0.40,
0.30,
0.60,
0.35,
0.15,
0.50
};
double[] expectedAssetReturnsArray = new double[]
{
0.008430,
0.007230,
0.006450,
0.002560,
0.004480,
0.006840,
0.001670
};
double[][] assetReturnsCovarianceMatrix = new double[][]
{
{0.002733, 0.002083, 0.001593, 0.000488, 0.001172, 0.002312, 0.000710},
{0.002083, 0.002768, 0.001302, 0.000457, 0.001105, 0.001647, 0.000563},
{0.001593, 0.001302, 0.001463, 0.000639, 0.001050, 0.001110, 0.000519},
{0.000488, 0.000457, 0.000639, 0.000608, 0.000663, 0.000042, 0.000370},
{0.001172, 0.001105, 0.001050, 0.000663, 0.001389, 0.000825, 0.000661},
{0.002312, 0.001647, 0.001110, 0.000042, 0.000825, 0.005211, 0.000749},
{0.000710, 0.000563, 0.000519, 0.000370, 0.000661, 0.000749, 0.000703}
};
int frontierSampleUnits = 20;
AssetUniverseStatisticalProperties assetUniverseStatisticalProperties =
AssetUniverseStatisticalProperties.FromMultivariateMetrics (
MultivariateMoments.Standard (
assetNameArray,
expectedAssetReturnsArray,
assetReturnsCovarianceMatrix
)
);
double[][] covarianceMatrix = assetUniverseStatisticalProperties.covariance (
assetNameArray
);
System.out.println ("\n\n\t|------------------------------------------------------------------------------------------------||");
System.out.println ("\t| CROSS ASSET COVARIANCE MATRIX ||");
System.out.println ("\t|------------------------------------------------------------------------------------------------||");
String header = "\t| |";
for (int assetIndex = 0;
assetIndex < assetNameArray.length;
++assetIndex)
{
header += " " + assetNameArray[assetIndex] + " |";
}
System.out.println (header + "|");
System.out.println ("\t|------------------------------------------------------------------------------------------------||");
for (int assetIndexI = 0;
assetIndexI < assetNameArray.length;
++assetIndexI)
{
String dump = "\t| " + assetNameArray[assetIndexI] + " ";
for (int assetIndexJ = 0;
assetIndexJ < assetNameArray.length;
++assetIndexJ)
{
dump += "|" + FormatUtil.FormatDouble (
covarianceMatrix[assetIndexI][assetIndexJ], 1, 8, 1.
) + " ";
}
System.out.println (dump + "||");
}
System.out.println ("\t|------------------------------------------------------------------------------------------------||\n\n");
System.out.println ("\t|-------------------||");
System.out.println ("\t| ASSET BOUNDS ||");
System.out.println ("\t|-------------------||");
for (int assetIndex = 0;
assetIndex < assetNameArray.length;
++assetIndex)
{
System.out.println (
"\t| " + assetNameArray[assetIndex] + " | " +
FormatUtil.FormatDouble (assetHoldingsLowerBoundArray[assetIndex], 2, 0, 100.) + "% | " +
FormatUtil.FormatDouble (assetHoldingsUpperBoundArray[assetIndex], 2, 0, 100.) + "% ||"
);
}
System.out.println ("\t|-------------------||\n\n");
InteriorPointBarrierControl interiorPointBarrierControl = InteriorPointBarrierControl.Standard();
System.out.println ("\t|--------------------------------------------||");
System.out.println ("\t| INTERIOR POINT METHOD BARRIER PARAMETERS ||");
System.out.println ("\t|--------------------------------------------||");
System.out.println (
"\t| Barrier Decay Velocity : " + 1. / interiorPointBarrierControl.decayVelocity()
);
System.out.println (
"\t| Barrier Decay Steps : " + interiorPointBarrierControl.decayStepCount()
);
System.out.println (
"\t| Initial Barrier Strength : " + interiorPointBarrierControl.initialStrength()
);
System.out.println (
"\t| Barrier Convergence Tolerance : " + interiorPointBarrierControl.relativeTolerance()
);
System.out.println ("\t|--------------------------------------------||\n\n");
BoundedHoldingsAllocationControl boundedPortfolioConstructionParameters =
new BoundedHoldingsAllocationControl (
assetNameArray,
CustomRiskUtilitySettings.VarianceMinimizer(),
new EqualityConstraintSettings (
EqualityConstraintSettings.FULLY_INVESTED_CONSTRAINT,
Double.NaN
)
);
for (int assetIndex = 0;
assetIndex < assetNameArray.length;
++assetIndex)
{
boundedPortfolioConstructionParameters.addBound (
assetNameArray[assetIndex],
assetHoldingsLowerBoundArray[assetIndex],
assetHoldingsUpperBoundArray[assetIndex]
);
}
MarkovitzBullet markovitzBullet = new ConstrainedMeanVarianceOptimizer (
interiorPointBarrierControl,
LineStepEvolutionControl.NocedalWrightStrongWolfe (
false
)
).efficientFrontier (
boundedPortfolioConstructionParameters,
assetUniverseStatisticalProperties,
frontierSampleUnits
);
System.out.println ("\n\n\t|-----------------------------------------------------------------------------------------------||");
System.out.println ("\t| GLOBAL MINIMUM VARIANCE AND MAXIMUM RETURNS PORTFOLIOS ||");
System.out.println ("\t|-----------------------------------------------------------------------------------------------||");
header = "\t| RETURNS | RISK % |";
for (int assetIndex = 0;
assetIndex < assetNameArray.length;
++assetIndex)
{
header += " " + assetNameArray[assetIndex] + " |";
}
System.out.println (header + "|");
System.out.println ("\t|-----------------------------------------------------------------------------------------------||");
DisplayPortfolioMetrics (markovitzBullet.globalMinimumVariance());
DisplayPortfolioMetrics (markovitzBullet.longOnlyMaximumReturns());
System.out.println ("\t|-----------------------------------------------------------------------------------------------||\n\n\n");
TreeMap<Double, HoldingsAllocation> frontierPortfolioMap = markovitzBullet.optimalPortfolioMap();
System.out.println ("\t|-----------------------------------------------------------------------------------------------||");
System.out.println ("\t| EFFICIENT FRONTIER: PORTFOLIO RISK & RETURNS + CORRESPONDING ASSET ALLOCATION ||");
System.out.println ("\t|-----------------------------------------------------------------------------------------------||");
System.out.println (header + "|");
System.out.println ("\t|-----------------------------------------------------------------------------------------------||");
for (Map.Entry<Double, HoldingsAllocation> me : frontierPortfolioMap.entrySet())
{
DisplayPortfolioMetrics (me.getValue());
}
System.out.println ("\t|-----------------------------------------------------------------------------------------------||\n\n");
EnvManager.TerminateEnv();
}
}