BlackLittermanCustomConfidenceOutput.java

package org.drip.portfolioconstruction.bayesian;

/*
 * -*- 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>BlackLittermanCustomConfidenceOutput</i> holds the Outputs generated from a Custom Confidence Black
 * Litterman Bayesian Combination Run. The References are:
 *  
 *  <br><br>
 *      <ul>
 *          <li>
 *              He. G., and R. Litterman (1999): <i>The Intuition behind the Black-Litterman Model
 *                  Portfolios</i> <b>Goldman Sachs Asset Management</b>
 *          </li>
 *          <li>
 *              Idzorek, T. (2005): <i>A Step-by-Step Guide to the Black-Litterman Model: Incorporating
 *                  User-Specified Confidence Levels</i> <b>Ibbotson Associates</b> Chicago, IL
 *          </li>
 *      </ul>
 *
 *  <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/portfolioconstruction/README.md">Portfolio Construction under Allocation Constraints</a></li>
 *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/portfolioconstruction/bayesian/README.md">Black Litterman Bayesian Portfolio Construction</a></li>
 *  </ul>
 *
 * @author Lakshmi Krishnamurthy
 */

public class BlackLittermanCustomConfidenceOutput
    extends org.drip.portfolioconstruction.bayesian.BlackLittermanOutput
{
    private org.drip.measure.bayesian.R1MultivariateConvolutionMetrics _jointPosteriorMetrics = null;

    /**
     * BlackLittermanCustomConfidenceOutput Constructor
     * 
     * @param forwardReverseOptimizationOutput The Adjusted Forward Reverse Equilibrium Optimization Output
     * @param allocationAdjustmentTiltArray Array of the Allocation Adjustment Tilts
     * @param jointPosteriorMetrics The Bayesian Joint/Posterior Metrics Instance
     * 
     * @throws java.lang.Exception Thrown if the Inputs are Invalid
     */

    public BlackLittermanCustomConfidenceOutput (
        final org.drip.portfolioconstruction.allocator.ForwardReverseHoldingsAllocation
            forwardReverseOptimizationOutput,
        final double[] allocationAdjustmentTiltArray,
        final org.drip.measure.bayesian.R1MultivariateConvolutionMetrics jointPosteriorMetrics)
        throws java.lang.Exception
    {
        super (
            forwardReverseOptimizationOutput,
            allocationAdjustmentTiltArray
        );

        if (null == (_jointPosteriorMetrics = jointPosteriorMetrics))
        {
            throw new java.lang.Exception
                ("BlackLittermanCustomConfidenceOutput Constructor => Invalid Inputs");
        }
    }

    /**
     * Retrieve the Bayesian Joint/Posterior Metrics
     * 
     * @return The Bayesian Joint/Posterior Metrics
     */

    public org.drip.measure.bayesian.R1MultivariateConvolutionMetrics jointPosteriorMetrics()
    {
        return _jointPosteriorMetrics;
    }
}