RiskFactorTenorSensitivity.java

  1. package org.drip.simm.product;

  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.  * Copyright (C) 2018 Lakshmi Krishnamurthy
  9.  *
  10.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  11.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  12.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  13.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  14.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  15.  *      and computational support.
  16.  *  
  17.  *      https://lakshmidrip.github.io/DROP/
  18.  *  
  19.  *  DROP is composed of three modules:
  20.  *  
  21.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  22.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  23.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  24.  *
  25.  *  DROP Product Core implements libraries for the following:
  26.  *  - Fixed Income Analytics
  27.  *  - Loan Analytics
  28.  *  - Transaction Cost Analytics
  29.  *
  30.  *  DROP Portfolio Core implements libraries for the following:
  31.  *  - Asset Allocation Analytics
  32.  *  - Asset Liability Management Analytics
  33.  *  - Capital Estimation Analytics
  34.  *  - Exposure Analytics
  35.  *  - Margin Analytics
  36.  *  - XVA Analytics
  37.  *
  38.  *  DROP Computational Core implements libraries for the following:
  39.  *  - Algorithm Support
  40.  *  - Computation Support
  41.  *  - Function Analysis
  42.  *  - Model Validation
  43.  *  - Numerical Analysis
  44.  *  - Numerical Optimizer
  45.  *  - Spline Builder
  46.  *  - Statistical Learning
  47.  *
  48.  *  Documentation for DROP is Spread Over:
  49.  *
  50.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  51.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  52.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  53.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  54.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  55.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  56.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  57.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  58.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  59.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  60.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  61.  *
  62.  *  Licensed under the Apache License, Version 2.0 (the "License");
  63.  *      you may not use this file except in compliance with the License.
  64.  *  
  65.  *  You may obtain a copy of the License at
  66.  *      http://www.apache.org/licenses/LICENSE-2.0
  67.  *  
  68.  *  Unless required by applicable law or agreed to in writing, software
  69.  *      distributed under the License is distributed on an "AS IS" BASIS,
  70.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  71.  *  
  72.  *  See the License for the specific language governing permissions and
  73.  *      limitations under the License.
  74.  */

  75. /**
  76.  * <i>RiskFactorTenorSensitivity</i> holds the ISDA SIMM 2.0 Risk Factor Tenor Bucket Sensitivities. The
  77.  * References are:
  78.  *
  79.  * <br><br>
  80.  *  <ul>
  81.  *      <li>
  82.  *          Andersen, L. B. G., M. Pykhtin, and A. Sokol (2017): Credit Exposure in the Presence of Initial
  83.  *              Margin https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2806156 <b>eSSRN</b>
  84.  *      </li>
  85.  *      <li>
  86.  *          Albanese, C., S. Caenazzo, and O. Frankel (2017): Regression Sensitivities for Initial Margin
  87.  *              Calculations https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2763488 <b>eSSRN</b>
  88.  *      </li>
  89.  *      <li>
  90.  *          Anfuso, F., D. Aziz, P. Giltinan, and K. Loukopoulus (2017): A Sound Modeling and Back-testing
  91.  *              Framework for Forecasting Initial Margin Requirements
  92.  *                  https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2716279 <b>eSSRN</b>
  93.  *      </li>
  94.  *      <li>
  95.  *          Caspers, P., P. Giltinan, R. Lichters, and N. Nowaczyk (2017): Forecasting Initial Margin
  96.  *              Requirements - A Model Evaluation https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2911167
  97.  *                  <b>eSSRN</b>
  98.  *      </li>
  99.  *      <li>
  100.  *          International Swaps and Derivatives Association (2017): SIMM v2.0 Methodology
  101.  *              https://www.isda.org/a/oFiDE/isda-simm-v2.pdf
  102.  *      </li>
  103.  *  </ul>
  104.  *
  105.  * <br><br>
  106.  *  <ul>
  107.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/PortfolioCore.md">Portfolio Core Module</a></li>
  108.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/MarginAnalyticsLibrary.md">Initial and Variation Margin Analytics</a></li>
  109.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/simm/README.md">Initial Margin Analytics based on ISDA SIMM and its Variants</a></li>
  110.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/simm/product/README.md">ISDA SIMM Risk Factor Sensitivities</a></li>
  111.  *  </ul>
  112.  * <br><br>
  113.  *
  114.  * @author Lakshmi Krishnamurthy
  115.  */

  116. public class RiskFactorTenorSensitivity
  117. {
  118.     private java.util.Map<java.lang.String, java.lang.Double> _sensitivityMap = null;

  119.     /**
  120.      * RiskFactorTenorSensitivity Constructor
  121.      *
  122.      * @param sensitivityMap The Tenor Sensitivity Map
  123.      *
  124.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  125.      */

  126.     public RiskFactorTenorSensitivity (
  127.         java.util.Map<java.lang.String, java.lang.Double> sensitivityMap)
  128.         throws java.lang.Exception
  129.     {
  130.         if (null == (_sensitivityMap = sensitivityMap) || 0 == _sensitivityMap.size())
  131.         {
  132.             throw new java.lang.Exception ("RiskFactorTenorSensitivity Constructor => Invalid Inputs");
  133.         }
  134.     }

  135.     /**
  136.      * Retrieve the Set of Tenors
  137.      *
  138.      * @return The Set of Tenors
  139.      */

  140.     public java.util.Set<java.lang.String> tenorSet()
  141.     {
  142.         return _sensitivityMap.keySet();
  143.     }

  144.     /**
  145.      * Add the Tenor Sensitivity
  146.      *
  147.      * @param tenor The Tenor
  148.      * @param sensitivity Sensitivity for the given Tenor
  149.      *
  150.      * @return TRUE - The Tenor Sensitivity successfully set
  151.      */

  152.     public boolean addTenorDelta (
  153.         final java.lang.String tenor,
  154.         final double sensitivity)
  155.     {
  156.         if (null == tenor || !org.drip.numerical.common.NumberUtil.IsValid (sensitivity))
  157.         {
  158.             return false;
  159.         }

  160.         _sensitivityMap.put (
  161.             tenor,
  162.             sensitivity
  163.         );

  164.         return true;
  165.     }

  166.     /**
  167.      * Indicate of the Sensitivity exists for the specified Tenor
  168.      *
  169.      * @param tenor The Tenor
  170.      *
  171.      * @return TRUE - Sensitivity exists for the specified Tenor
  172.      */

  173.     public boolean tenorExists (
  174.         final java.lang.String tenor)
  175.     {
  176.         return null != tenor && _sensitivityMap.containsKey (tenor);
  177.     }

  178.     /**
  179.      * Retrieve the Sensitivity for the Bucket Tenor
  180.      *
  181.      * @param tenor The Tenor
  182.      *
  183.      * @return The Sensitivity corresponding to the Tenor
  184.      *
  185.      * @throws java.lang.Exception Thrown if the Input is Invalid
  186.      */

  187.     public double sensitivity (
  188.         final java.lang.String tenor)
  189.         throws java.lang.Exception
  190.     {
  191.         if (!tenorExists (tenor))
  192.         {
  193.             throw new java.lang.Exception ("RiskFactorTenorSensitivity::sensitivity => Invalid Inputs");
  194.         }

  195.         return _sensitivityMap.get (tenor);
  196.     }

  197.     /**
  198.      * Retrieve the Map of Tenor Sensitivities
  199.      *
  200.      * @return The Map of Tenor Sensitivities
  201.      */

  202.     public java.util.Map<java.lang.String, java.lang.Double> sensitivityMap()
  203.     {
  204.         return _sensitivityMap;
  205.     }

  206.     /**
  207.      * Generate the Cumulative Tenor Sensitivity
  208.      *
  209.      * @return The Cumulative Tenor Sensitivity
  210.      */

  211.     public double cumulative()
  212.     {
  213.         double cumulative = 0.;

  214.         for (java.util.Map.Entry<java.lang.String, java.lang.Double> sensitivityEntry : _sensitivityMap.entrySet())
  215.         {
  216.             cumulative = cumulative + sensitivityEntry.getValue();
  217.         }

  218.         return cumulative;
  219.     }

  220.     /**
  221.      * Generate the Tenor Sensitivity Margin Map
  222.      *
  223.      * @param sensitivityRiskWeightMap The Tenor Sensitivity Risk Weight Map
  224.      *
  225.      * @return The Tenor Sensitivity Margin Map
  226.      */

  227.     public java.util.Map<java.lang.String, java.lang.Double> sensitivityMargin (
  228.         final java.util.Map<java.lang.String, java.lang.Double> sensitivityRiskWeightMap)
  229.     {
  230.         if (null == sensitivityRiskWeightMap || 0 == sensitivityRiskWeightMap.size())
  231.         {
  232.             return null;
  233.         }

  234.         java.util.Map<java.lang.String, java.lang.Double> sensitivityMargin = new
  235.             java.util.HashMap<java.lang.String, java.lang.Double>();

  236.         for (java.util.Map.Entry<java.lang.String, java.lang.Double> sensitivityEntry :
  237.             _sensitivityMap.entrySet())
  238.         {
  239.             java.lang.String tenor = sensitivityEntry.getKey();

  240.             if (!sensitivityRiskWeightMap.containsKey (tenor))
  241.             {
  242.                 return null;
  243.             }

  244.             sensitivityMargin.put (
  245.                 tenor,
  246.                 sensitivityEntry.getValue() * sensitivityRiskWeightMap.get (tenor)
  247.             );
  248.         }

  249.         return sensitivityMargin;
  250.     }
  251. }