GapLossWeightFunction.java

  1. package org.drip.validation.distance;

  2. /*
  3.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  4.  */

  5. /*!
  6.  * Copyright (C) 2020 Lakshmi Krishnamurthy
  7.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  8.  *
  9.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  10.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  11.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  12.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  13.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  14.  *      and computational support.
  15.  *  
  16.  *      https://lakshmidrip.github.io/DROP/
  17.  *  
  18.  *  DROP is composed of three modules:
  19.  *  
  20.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  21.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  22.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  23.  *
  24.  *  DROP Product Core implements libraries for the following:
  25.  *  - Fixed Income Analytics
  26.  *  - Loan Analytics
  27.  *  - Transaction Cost Analytics
  28.  *
  29.  *  DROP Portfolio Core implements libraries for the following:
  30.  *  - Asset Allocation Analytics
  31.  *  - Asset Liability Management Analytics
  32.  *  - Capital Estimation Analytics
  33.  *  - Exposure Analytics
  34.  *  - Margin Analytics
  35.  *  - XVA Analytics
  36.  *
  37.  *  DROP Computational Core implements libraries for the following:
  38.  *  - Algorithm Support
  39.  *  - Computation Support
  40.  *  - Function Analysis
  41.  *  - Model Validation
  42.  *  - Numerical Analysis
  43.  *  - Numerical Optimizer
  44.  *  - Spline Builder
  45.  *  - Statistical Learning
  46.  *
  47.  *  Documentation for DROP is Spread Over:
  48.  *
  49.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  50.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  51.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  52.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  53.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  54.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  55.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  56.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  57.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  58.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  59.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  60.  *
  61.  *  Licensed under the Apache License, Version 2.0 (the "License");
  62.  *      you may not use this file except in compliance with the License.
  63.  *  
  64.  *  You may obtain a copy of the License at
  65.  *      http://www.apache.org/licenses/LICENSE-2.0
  66.  *  
  67.  *  Unless required by applicable law or agreed to in writing, software
  68.  *      distributed under the License is distributed on an "AS IS" BASIS,
  69.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  70.  *  
  71.  *  See the License for the specific language governing permissions and
  72.  *      limitations under the License.
  73.  */

  74. /**
  75.  * <i>GapLossWeightFunction</i> weighs the outcome of each Empirical Hypothesis Gap Loss.
  76.  *
  77.  *  <br><br>
  78.  *  <ul>
  79.  *      <li>
  80.  *          Anfuso, F., D. Karyampas, and A. Nawroth (2017): A Sound Basel III Compliant Framework for
  81.  *              Back-testing Credit Exposure Models
  82.  *              https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2264620 <b>eSSRN</b>
  83.  *      </li>
  84.  *      <li>
  85.  *          Diebold, F. X., T. A. Gunther, and A. S. Tay (1998): Evaluating Density Forecasts with
  86.  *              Applications to Financial Risk Management, International Economic Review 39 (4) 863-883
  87.  *      </li>
  88.  *      <li>
  89.  *          Kenyon, C., and R. Stamm (2012): <i>Discounting, LIBOR, CVA, and Funding: Interest Rate and
  90.  *              Credit Pricing</i> <b>Palgrave Macmillan</b>
  91.  *      </li>
  92.  *      <li>
  93.  *          Wikipedia (2018): Probability Integral Transform
  94.  *              https://en.wikipedia.org/wiki/Probability_integral_transform
  95.  *      </li>
  96.  *      <li>
  97.  *          Wikipedia (2019): p-value https://en.wikipedia.org/wiki/P-value
  98.  *      </li>
  99.  *  </ul>
  100.  *
  101.  *  <br><br>
  102.  *  <ul>
  103.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
  104.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ModelValidationAnalyticsLibrary.md">Model Validation Analytics Library</a></li>
  105.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/validation/README.md">Risk Factor and Hypothesis Validation, Evidence Processing, and Model Testing</a></li>
  106.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/validation/distance/README.md">Hypothesis Target Distance Test Builders</a></li>
  107.  *  </ul>
  108.  * <br><br>
  109.  *
  110.  * @author Lakshmi Krishnamurthy
  111.  */

  112. public abstract class GapLossWeightFunction
  113. {

  114.     /**
  115.      * Construct the Cramers-von Mises Version of the Gap Loss Weight Function
  116.      *
  117.      * @return The Cramers-von Mises Version of the Gap Loss Weight Function
  118.      */

  119.     public static final GapLossWeightFunction CramersVonMises()
  120.     {
  121.         return new GapLossWeightFunction()
  122.         {
  123.             @Override public double weight (
  124.                 final double pValueHypothesis)
  125.                 throws java.lang.Exception
  126.             {
  127.                 if (!org.drip.numerical.common.NumberUtil.IsValid (pValueHypothesis))
  128.                 {
  129.                     throw new java.lang.Exception ("GapLossWeightFunction::weight => Invalid Inputs");
  130.                 }

  131.                 return 1.;
  132.             }
  133.         };
  134.     }

  135.     /**
  136.      * Construct the Anderson-Darling Version of the Gap Loss Weight Function
  137.      *
  138.      * @return The Anderson-Darling Version of the Gap Loss Weight Function
  139.      */

  140.     public static final GapLossWeightFunction AndersonDarling()
  141.     {
  142.         return new GapLossWeightFunction()
  143.         {
  144.             @Override public double weight (
  145.                 final double pValueHypothesis)
  146.                 throws java.lang.Exception
  147.             {
  148.                 if (!org.drip.numerical.common.NumberUtil.IsValid (pValueHypothesis))
  149.                 {
  150.                     throw new java.lang.Exception ("GapLossWeightFunction::weight => Invalid Inputs");
  151.                 }

  152.                 return 0. == pValueHypothesis  || 1. == pValueHypothesis ? 0. :
  153.                     1. / (pValueHypothesis * (1. - pValueHypothesis));
  154.             }
  155.         };
  156.     }

  157.     /**
  158.      *
  159.      * Compute the Weight corresponding to the Hypothesis p-Value
  160.      *
  161.      * @param pValueHypothesis The Hypothesis p-Value
  162.      *
  163.      * @return The Weight
  164.      *
  165.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  166.      */

  167.     public abstract double weight (
  168.         final double pValueHypothesis)
  169.         throws java.lang.Exception;
  170. }