AdjustedVariationMarginDynamics.java

package org.drip.exposure.regressiontrade;

/*
 * -*- 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
 * 
 *  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>AdjustedVariationMarginDynamics</i> builds the Dynamics of the Sparse Path Adjusted Variation Margin.
 * The References are:
 *  
 * <br><br>
 *      <ul>
 *          <li>
 *              Andersen, L. B. G., M. Pykhtin, and A. Sokol (2017): Re-thinking Margin Period of Risk
 *                  https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2902737 <b>eSSRN</b>
 *          </li>
 *          <li>
 *              Andersen, L. B. G., M. Pykhtin, and A. Sokol (2017): Credit Exposure in the Presence of
 *                  Initial Margin https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2806156 <b>eSSRN</b>
 *          </li>
 *          <li>
 *              Albanese, C., and L. Andersen (2014): Accounting for OTC Derivatives: Funding Adjustments and
 *                  the Re-Hypothecation Option https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2482955
 *                  <b>eSSRN</b>
 *          </li>
 *          <li>
 *              Burgard, C., and M. Kjaer (2017): Derivatives Funding, Netting, and Accounting
 *                  https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2534011 <b>eSSRN</b>
 *          </li>
 *          <li>
 *              Pykhtin, M. (2009): Modeling Counter-party Credit Exposure in the Presence of Margin
 *                  Agreements http://www.risk-europe.com/protected/michael-pykhtin.pdf
 *          </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/ExposureAnalyticsLibrary.md">Exposure Analytics</a></li>
 *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/exposure/README.md">Exposure Group Level Collateralized/Uncollateralized Exposure</a></li>
 *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/exposure/regressiontrade/README.md">Exposure Regression under Margin and Trade Payments</a></li>
 *  </ul>
 * 
 * @author Lakshmi Krishnamurthy
 */

public class AdjustedVariationMarginDynamics
{
    private org.drip.exposure.regressiontrade.AdjustedVariationMarginEstimate[]
        _pathAdjustedVariationMarginEstimate = null;

    /**
     * AdjustedVariationMarginDynamics Constructor
     * 
     * @param pathAdjustedVariationMarginEstimate The Path-wise Adjusted Variation Margin Estimate Array
     * 
     * @throws java.lang.Exception Thrown if the Inputs are Invalid
     */

    public AdjustedVariationMarginDynamics (
        final org.drip.exposure.regressiontrade.AdjustedVariationMarginEstimate[]
            pathAdjustedVariationMarginEstimate)
        throws java.lang.Exception
    {
        if (null == (_pathAdjustedVariationMarginEstimate = pathAdjustedVariationMarginEstimate))
        {
            throw new java.lang.Exception ("AdjustedVariationMarginDynamics Constructor");
        }

        int pathCount = _pathAdjustedVariationMarginEstimate.length;

        if (0 == pathCount)
        {
            throw new java.lang.Exception ("AdjustedVariationMarginDynamics Constructor");
        }

        for (int pathIndex = 0; pathIndex < pathCount; ++pathIndex)
        {
            if (null == _pathAdjustedVariationMarginEstimate[pathIndex])
            {
                throw new java.lang.Exception ("AdjustedVariationMarginDynamics Constructor");
            }
        }
    }

    /**
     * Retrieve the Adjusted Variation Margin Estimate Array
     * 
     * @return The Adjusted Variation Margin Estimate Array
     */

    public org.drip.exposure.regressiontrade.AdjustedVariationMarginEstimate[]
        adjustedVariationMarginEstimateArray()
    {
        return _pathAdjustedVariationMarginEstimate;
    }

    /**
     * Generate the Dynamics of the Sparse Pillar a.k.a Pykhtin (2009)
     * 
     * @return The Pykhtin Pillar Dynamics Array
     */

    public org.drip.exposure.regression.PykhtinPillarDynamics[] pillarDynamics()
    {
        int exposureDateCount =
            _pathAdjustedVariationMarginEstimate[0].adjustedVariationMarginEstimateArray().length;

        int pathCount = _pathAdjustedVariationMarginEstimate.length;
        double[][] pathAdjustedVariationMargin = new double[exposureDateCount][pathCount];
        org.drip.exposure.regression.PykhtinPillarDynamics[] pykhtinPillarDynamicsArray = new
            org.drip.exposure.regression.PykhtinPillarDynamics[exposureDateCount];

        for (int pathIndex = 0; pathIndex < pathCount; ++pathIndex)
        {
            double[] pathAdjustedVariationMarginEstimateArray =
                _pathAdjustedVariationMarginEstimate[pathIndex].adjustedVariationMarginEstimateArray();

            for (int exposureDateIndex = 0; exposureDateIndex < exposureDateCount; ++exposureDateIndex)
            {
                pathAdjustedVariationMargin[exposureDateIndex][pathIndex] =
                    pathAdjustedVariationMarginEstimateArray[exposureDateIndex];
            }
        }

        for (int exposureDateIndex = 0; exposureDateIndex < exposureDateCount; ++exposureDateIndex)
        {
            if (null == (pykhtinPillarDynamicsArray[exposureDateIndex] =
                org.drip.exposure.regression.PykhtinPillarDynamics.Standard
                    (pathAdjustedVariationMargin[exposureDateIndex])))
            {
                return null;
            }
        }

        return pykhtinPillarDynamicsArray;
    }
}