CKLSParameters.java

  1. package org.drip.dynamics.meanreverting;

  3. /*
  4.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  5.  */

  7. /*!
  8.  * Copyright (C) 2020 Lakshmi Krishnamurthy
  9.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  10.  * 
  11.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  12.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  13.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  14.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  15.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  16.  *      and computational support.
  17.  *  
  18.  *      https://lakshmidrip.github.io/DROP/
  19.  *  
  20.  *  DROP is composed of three modules:
  21.  *  
  22.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  23.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  24.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  25.  * 
  26.  *  DROP Product Core implements libraries for the following:
  27.  *  - Fixed Income Analytics
  28.  *  - Loan Analytics
  29.  *  - Transaction Cost Analytics
  30.  * 
  31.  *  DROP Portfolio Core implements libraries for the following:
  32.  *  - Asset Allocation Analytics
  33.  *  - Asset Liability Management Analytics
  34.  *  - Capital Estimation Analytics
  35.  *  - Exposure Analytics
  36.  *  - Margin Analytics
  37.  *  - XVA Analytics
  38.  * 
  39.  *  DROP Computational Core implements libraries for the following:
  40.  *  - Algorithm Support
  41.  *  - Computation Support
  42.  *  - Function Analysis
  43.  *  - Model Validation
  44.  *  - Numerical Analysis
  45.  *  - Numerical Optimizer
  46.  *  - Spline Builder
  47.  *  - Statistical Learning
  48.  * 
  49.  *  Documentation for DROP is Spread Over:
  50.  * 
  51.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  52.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  53.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  54.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  55.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  56.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  57.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  58.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  59.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  60.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  61.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  62.  * 
  63.  *  Licensed under the Apache License, Version 2.0 (the "License");
  64.  *      you may not use this file except in compliance with the License.
  65.  *   
  66.  *  You may obtain a copy of the License at
  67.  *      http://www.apache.org/licenses/LICENSE-2.0
  68.  *  
  69.  *  Unless required by applicable law or agreed to in writing, software
  70.  *      distributed under the License is distributed on an "AS IS" BASIS,
  71.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  72.  *  
  73.  *  See the License for the specific language governing permissions and
  74.  *      limitations under the License.
  75.  */

  77. /**
  78.  * <i>CKLSParameters</i> contains the Parameters for the R<sup>1</sup> Chan-Karolyi-Longstaff-Sanders 1992
  79.  *  Stochastic Evolver. The References are:
  80.  *  
  81.  *  <br><br>
  82.  *  <ul>
  83.  *      <li>
  84.  *          Doob, J. L. (1942): The Brownian Movement and Stochastic Equations <i>Annals of Mathematics</i>
  85.  *              <b>43 (2)</b> 351-369
  86.  *      </li>
  87.  *      <li>
  88.  *          Gardiner, C. W. (2009): <i>Stochastic Methods: A Handbook for the Natural and Social Sciences
  89.  *              4<sup>th</sup> Edition</i> <b>Springer-Verlag</b>
  90.  *      </li>
  91.  *      <li>
  92.  *          Kadanoff, L. P. (2000): <i>Statistical Physics: Statics, Dynamics, and Re-normalization</i>
  93.  *              <b>World Scientific</b>
  94.  *      </li>
  95.  *      <li>
  96.  *          Karatzas, I., and S. E. Shreve (1991): <i>Brownian Motion and Stochastic Calculus 2<sup>nd</sup>
  97.  *              Edition</i> <b>Springer-Verlag</b>
  98.  *      </li>
  99.  *      <li>
  100.  *          Risken, H., and F. Till (1996): <i>The Fokker-Planck Equation – Methods of Solution and
  101.  *              Applications</i> <b>Springer</b>
  102.  *      </li>
  103.  *  </ul>
  104.  *
  105.  *  <br><br>
  106.  *  <ul>
  107.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ProductCore.md">Product Core Module</a></li>
  108.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/FixedIncomeAnalyticsLibrary.md">Fixed Income Analytics</a></li>
  109.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/dynamics/README.md">HJM, Hull White, LMM, and SABR Dynamic Evolution Models</a></li>
  110.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/dynamics/meanreverting/README.md">Mean Reverting Stochastic Process Dynamics</a></li>
  111.  *  </ul>
  112.  *
  113.  * @author Lakshmi Krishnamurthy
  114.  */

  116. public class CKLSParameters
  117. {
  118.     private double _meanReversionLevel = java.lang.Double.NaN;
  119.     private double _meanReversionSpeed = java.lang.Double.NaN;
  120.     private double _volatilityExponent = java.lang.Double.NaN;
  121.     private double _volatilityCoefficient = java.lang.Double.NaN;

  123.     /**
  124.      * Construct the Vasicek Instance of the CKLS Parameters
  125.      * 
  126.      * @param meanReversionSpeed The Mean Reversion Speed
  127.      * @param meanReversionLevel The Mean Reversion Level
  128.      * @param volatility The Volatility
  129.      * 
  130.      * @return The Vasicek Instance of the CKLS Parameters
  131.      */

  133.     public static final CKLSParameters Vasicek (
  134.         final double meanReversionSpeed,
  135.         final double meanReversionLevel,
  136.         final double volatility)
  137.     {
  138.         try
  139.         {
  140.             return new CKLSParameters (
  141.                 meanReversionSpeed,
  142.                 meanReversionLevel,
  143.                 volatility,
  144.                 0.
  145.             );
  146.         }
  147.         catch (java.lang.Exception e)
  148.         {
  149.             e.printStackTrace();
  150.         }

  152.         return null;
  153.     }

  155.     /**
  156.      * Construct the Ornstein-Uhlenbeck Instance of the CKLS Parameters
  157.      * 
  158.      * @param meanReversionSpeed The Mean Reversion Speed
  159.      * @param volatility The Volatility
  160.      * 
  161.      * @return The Ornstein-Uhlenbeck Instance of the CKLS Parameters
  162.      */

  164.     public static final CKLSParameters OrnsteinUhlenbeck (
  165.         final double meanReversionSpeed,
  166.         final double volatility)
  167.     {
  168.         try
  169.         {
  170.             return new CKLSParameters (
  171.                 meanReversionSpeed,
  172.                 0.,
  173.                 volatility,
  174.                 0.
  175.             );
  176.         }
  177.         catch (java.lang.Exception e)
  178.         {
  179.             e.printStackTrace();
  180.         }

  182.         return null;
  183.     }

  185.     /**
  186.      * Construct the Cox-Ingersoll-Ross Instance of the CKLS Parameters
  187.      * 
  188.      * @param meanReversionSpeed The Mean Reversion Speed
  189.      * @param meanReversionLevel The Mean Reversion Level
  190.      * @param volatilityCoefficient The Volatility Coefficient
  191.      * 
  192.      * @return The Cox-Ingersoll-Ross Instance of the CKLS Parameters
  193.      */

  195.     public static final CKLSParameters CoxIngersollRoss (
  196.         final double meanReversionSpeed,
  197.         final double meanReversionLevel,
  198.         final double volatilityCoefficient)
  199.     {
  200.         try
  201.         {
  202.             return new CKLSParameters (
  203.                 meanReversionSpeed,
  204.                 meanReversionLevel,
  205.                 volatilityCoefficient,
  206.                 0.5
  207.             );
  208.         }
  209.         catch (java.lang.Exception e)
  210.         {
  211.             e.printStackTrace();
  212.         }

  214.         return null;
  215.     }

  217.     /**
  218.      * CKLSParameters Constructor
  219.      * 
  220.      * @param meanReversionSpeed The Mean Reversion Speed
  221.      * @param meanReversionLevel The Mean Reversion Level
  222.      * @param volatilityCoefficient The Volatility Coefficient
  223.      * @param volatilityExponent The Volatility Exponent
  224.      * 
  225.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  226.      */

  228.     public CKLSParameters (
  229.         final double meanReversionSpeed,
  230.         final double meanReversionLevel,
  231.         final double volatilityCoefficient,
  232.         final double volatilityExponent)
  233.         throws java.lang.Exception
  234.     {
  235.         if (!org.drip.numerical.common.NumberUtil.IsValid (
  236.                 _meanReversionSpeed = meanReversionSpeed
  237.             ) || 0. > _meanReversionSpeed || !org.drip.numerical.common.NumberUtil.IsValid (
  238.                 _meanReversionLevel = meanReversionLevel
  239.             ) || 0. > _meanReversionLevel || !org.drip.numerical.common.NumberUtil.IsValid (
  240.                 _volatilityCoefficient = volatilityCoefficient
  241.             ) || 0. > _volatilityCoefficient || !org.drip.numerical.common.NumberUtil.IsValid (
  242.                 _volatilityExponent = volatilityExponent
  243.             ) || 0. > _volatilityExponent
  244.         )
  245.         {
  246.             throw new java.lang.Exception (
  247.                 "CKLSParameters Constructor => Invalid Inputs"
  248.             );
  249.         }
  250.     }

  252.     /**
  253.      * Retrieve the Mean Reversion Speed
  254.      * 
  255.      * @return The Mean Reversion Speed
  256.      */

  258.     public double meanReversionSpeed()
  259.     {
  260.         return _meanReversionSpeed;
  261.     }

  263.     /**
  264.      * Retrieve the Mean Reversion Level
  265.      * 
  266.      * @return The Mean Reversion Level
  267.      */

  269.     public double meanReversionLevel()
  270.     {
  271.         return _meanReversionLevel;
  272.     }

  274.     /**
  275.      * Retrieve the Volatility Coefficient
  276.      * 
  277.      * @return The Volatility Coefficient
  278.      */

  280.     public double volatilityCoefficient()
  281.     {
  282.         return _volatilityCoefficient;
  283.     }

  285.     /**
  286.      * Retrieve the CKLS Volatility Exponent
  287.      * 
  288.      * @return The CKLS Volatility Exponent
  289.      */

  291.     public double volatilityExponent()
  292.     {
  293.         return _volatilityExponent;
  294.     }
  295. }
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