DaJagannathan2005d.java

package org.drip.sample.blacklitterman;

import org.drip.measure.statistics.MultivariateMoments;
import org.drip.numerical.common.FormatUtil;
import org.drip.numerical.linearalgebra.Matrix;
import org.drip.portfolioconstruction.allocator.*;
import org.drip.portfolioconstruction.asset.AssetComponent;
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>DaJagannathan2005d</i> reconciles the Outputs of the Black-Litterman Model Process. The References are:
 *  
 * <br><br>
 *  <ul>
 *      <li>
 *          Da, Z., and R. Jagannathan (2005): https://www3.nd.edu/~zda/TeachingNote_Black-Litterman.pdf
 *      </li>
 *      <li>
 *          He. G., and R. Litterman (1999): <i>The Intuition behind the Black-Litterman Model Portfolios</i>
 *              <b>Goldman Sachs Asset Management</b>
 *      </li>
 *  </ul>
 *  
 * <br><br>
 *  <ul>
 *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ProductCore.md">Product Core Module</a></li>
 *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/TransactionCostAnalyticsLibrary.md">Transaction Cost 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/blacklitterman/README.md">Canonical Black Litterman and Extensions</a></li>
 *  </ul>
 * <br><br>
 *
 * @author Lakshmi Krishnamurthy
 */

public class DaJagannathan2005d {

    public static final void main (
        final String[] astArgs)
        throws Exception
    {
        EnvManager.InitEnv (
            "",
            true
        );

        String[] astrID = new String[] {
            "CORPORATE BOND     ",
            "LONG TERM GOVVIE   ",
            "MEDIUM TERM GOVVIE ",
            "STRONG BUY EQUITY  ",
            "BUY EQUITY         ",
            "NEUTRAL EQUITY     ",
            "SELL EQUITY        ",
            "STRONG SELL EQUITY "
        };

        double[][] aadblHistoricalCovariance = new double[][] {
            {0.0050, 0.0047, 0.0024, 0.0036, 0.0023, 0.0031, 0.0032, 0.0030},
            {0.0047, 0.0062, 0.0030, 0.0033, 0.0016, 0.0024, 0.0026, 0.0020},
            {0.0024, 0.0030, 0.0020, 0.0015, 0.0006, 0.0009, 0.0012, 0.0008},
            {0.0036, 0.0033, 0.0015, 0.0468, 0.0354, 0.0371, 0.0379, 0.0414},
            {0.0023, 0.0016, 0.0006, 0.0354, 0.0354, 0.0323, 0.0317, 0.0371},
            {0.0031, 0.0024, 0.0009, 0.0371, 0.0323, 0.0349, 0.0342, 0.0364},
            {0.0032, 0.0026, 0.0012, 0.0379, 0.0317, 0.0342, 0.0432, 0.0384},
            {0.0030, 0.0020, 0.0008, 0.0414, 0.0371, 0.0364, 0.0384, 0.0498}
        };

        double[] adblHistoricalReturn = new double[] {
            0.0595,
            0.0553,
            0.0545,
            0.1302,
            0.1114,
            0.1116,
            0.1217,
            0.1220
        };

        double[] adblHistoricalOptimalWeight = new double[] {
             0.2154,
            -0.5434,
             1.1976,
             0.0624,
             0.0808,
            -0.0450,
             0.0472,
            -0.0149
        };

        double[] adblMarketWeight = new double[] {
            0.1667,
            0.0833,
            0.0833,
            0.2206,
            0.1184,
            0.1065,
            0.0591,
            0.1622
        };

        double[] adblMarketImpliedReturnReconciler = new double[] {
            0.0335,
            0.0332,
            0.0315,
            0.0584,
            0.0539,
            0.0544,
            0.0554,
            0.0585
        };

        double dblRiskFreeRate = 0.03;
        double[] adblAdjustedHistoricalReturn = new double[adblHistoricalReturn.length];

        for (int i = 0; i < adblHistoricalReturn.length; ++i)
            adblAdjustedHistoricalReturn[i] = adblHistoricalReturn[i] - dblRiskFreeRate;

        HoldingsAllocation op = new QuadraticMeanVarianceOptimizer().allocate (
            new HoldingsAllocationControl (
                astrID,
                CustomRiskUtilitySettings.RiskTolerant (0.078),
                EqualityConstraintSettings.FullyInvested()
            ),
            AssetUniverseStatisticalProperties.FromMultivariateMetrics (
                MultivariateMoments.Standard (
                    astrID,
                    adblAdjustedHistoricalReturn,
                    aadblHistoricalCovariance
                )
            )
        );

        AssetComponent[] aAC = op.optimalPortfolio().assetComponentArray();

        double[] adblMarketImpliedReturn = Matrix.Product (
            aadblHistoricalCovariance,
            adblMarketWeight
        );

        System.out.println ("\n\t|---------------------------------------------------------------------------------------------||");

        System.out.println ("\t|                                HISTORICAL COVARIANCE MATRIX                                 ||");

        System.out.println ("\t|---------------------------------------------------------------------------------------------||");

        for (int i = 0; i < astrID.length; ++i) {
            String strDump = "\t| " + astrID[i] + " ";

            for (int j = 0; j < astrID.length; ++j)
                strDump += "|" + FormatUtil.FormatDouble (aadblHistoricalCovariance[i][j], 1, 4, 1.) + " ";

            System.out.println (strDump + "||");
        }

        System.out.println ("\t|---------------------------------------------------------------------------------------------||\n");

        System.out.println ("\t||---------------------------------||");

        System.out.println ("\t||         MARKET WEIGHT           ||");

        System.out.println ("\t||---------------------------------||");

        for (int i = 0; i < adblMarketWeight.length; ++i)
            System.out.println (
                "\t||  " + astrID[i] + " => " +
                FormatUtil.FormatDouble (adblMarketWeight[i], 2, 2, 100.) + "% ||"
            );

        System.out.println ("\t||---------------------------------||\n");

        System.out.println ("\t||---------------------------------||");

        System.out.println ("\t||       HISTORICAL RETURNS        ||");

        System.out.println ("\t||---------------------------------||");

        for (int i = 0; i < adblHistoricalReturn.length; ++i)
            System.out.println (
                "\t||  " + astrID[i] + " => " +
                FormatUtil.FormatDouble (adblHistoricalReturn[i], 2, 2, 100.) + "% ||"
            );

        System.out.println ("\t||---------------------------------||");

        System.out.println ("\n\t||---------------------------------------------||");

        System.out.println ("\t||      HISTORICAL PARAM OPTIMAL WEIGHTS       ||");

        System.out.println ("\t||---------------------------------------------||");

        System.out.println ("\t||         ASSET        =>   CALC   |   PAPER  ||");

        System.out.println ("\t||---------------------------------------------||");

        for (int i = 0; i < aAC.length; ++i)
            System.out.println (
                "\t||  " + astrID[i] + " => " +
                FormatUtil.FormatDouble (adblHistoricalOptimalWeight[i], 3, 2, 100.) + "% | " +
                FormatUtil.FormatDouble (aAC[i].amount(), 3, 2, 100.) + "% ||"
            );

        System.out.println ("\t||---------------------------------------------||");

        System.out.println ("\n\t||----------------------------------------||");

        System.out.println ("\t||         MARKET IMPLIED RETURNS         ||");

        System.out.println ("\t||----------------------------------------||");

        System.out.println ("\t||         ASSET        =>  CALC  | PAPER ||");

        System.out.println ("\t||----------------------------------------||");

        for (int i = 0; i < aAC.length; ++i)
            System.out.println (
                "\t||  " + astrID[i] + " => " +
                FormatUtil.FormatDouble (adblMarketImpliedReturn[i] + dblRiskFreeRate, 1, 2, 100.) + "% |" +
                FormatUtil.FormatDouble (adblMarketImpliedReturnReconciler[i], 1, 2, 100.) + "% ||"
            );

        System.out.println ("\t||----------------------------------------||\n");

        EnvManager.TerminateEnv();
    }
}