JumpDiffusionEvolver.java
package org.drip.measure.process;
/*
* -*- 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
*
* 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>JumpDiffusionEvolver</i> implements the Functionality that guides the Single Factor R<sup>1</sup> Jump
* Diffusion Random Process Variable Evolution.
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalAnalysisLibrary.md">Numerical Analysis Library</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/measure/README.md">R<sup>d</sup> Continuous/Discrete Probability Measures</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/measure/process/README.md">Jump Diffusion Evolver Process Variants</a></li>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class JumpDiffusionEvolver extends org.drip.measure.process.DiffusionEvolver {
private org.drip.measure.dynamics.HazardJumpEvaluator _heie = null;
/**
* JumpDiffusionEvolver Constructor
*
* @param de The Diffusion Evaluator Instance
* @param heie The Hazard Point Event Indicator Function Instance
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public JumpDiffusionEvolver (
final org.drip.measure.dynamics.DiffusionEvaluator de,
final org.drip.measure.dynamics.HazardJumpEvaluator heie)
throws java.lang.Exception
{
super (de);
if (null == (_heie = heie))
throw new java.lang.Exception ("JumpDiffusionEvolver Constructor => Invalid Inputs");
}
/**
* Retrieve the Hazard Point Event Indicator Instance
*
* @return The Hazard Point Event Indicator Instance
*/
public org.drip.measure.dynamics.HazardJumpEvaluator eventIndicationEvaluator()
{
return _heie;
}
@Override public org.drip.measure.realization.JumpDiffusionEdge increment (
final org.drip.measure.realization.JumpDiffusionVertex jdv,
final org.drip.measure.realization.JumpDiffusionEdgeUnit ur,
final double dblTimeIncrement)
{
if (null == jdv || null == ur || !org.drip.numerical.common.NumberUtil.IsValid (dblTimeIncrement))
return null;
double dblPreviousValue = jdv.value();
try {
if (jdv.jumpOccurred())
return org.drip.measure.realization.JumpDiffusionEdge.Standard (dblPreviousValue, 0., 0., new
org.drip.measure.realization.StochasticEdgeJump (false, 0., 0., dblPreviousValue), ur);
} catch (java.lang.Exception e) {
e.printStackTrace();
return null;
}
double dblHazardRate = _heie.hazardRate();
org.drip.measure.dynamics.DiffusionEvaluator de = evaluator();
double dblLevelHazardIntegral = dblHazardRate * dblTimeIncrement;
boolean bEventOccurred = java.lang.Math.exp (-1. * (jdv.cumulativeHazardIntegral() +
dblLevelHazardIntegral)) <= ur.jump();
try {
org.drip.measure.realization.StochasticEdgeJump sej = new
org.drip.measure.realization.StochasticEdgeJump (bEventOccurred, dblHazardRate,
dblLevelHazardIntegral, _heie.magnitudeEvaluator().value (jdv));
if (bEventOccurred)
return org.drip.measure.realization.JumpDiffusionEdge.Standard (dblPreviousValue, 0., 0.,
sej, ur);
org.drip.measure.dynamics.LocalEvaluator leVolatility = de.volatility();
return org.drip.measure.realization.JumpDiffusionEdge.Standard (dblPreviousValue,
de.drift().value (jdv) * dblTimeIncrement, null == leVolatility ? 0. : leVolatility.value
(jdv) * ur.diffusion() * java.lang.Math.sqrt (java.lang.Math.abs (dblTimeIncrement)),
sej, ur);
} catch (java.lang.Exception e) {
e.printStackTrace();
}
return null;
}
}