CKLSParameters.java
package org.drip.dynamics.meanreverting;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2020 Lakshmi Krishnamurthy
* Copyright (C) 2019 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>CKLSParameters</i> contains the Parameters for the R<sup>1</sup> Chan-Karolyi-Longstaff-Sanders 1992
* Stochastic Evolver. The References are:
*
* <br><br>
* <ul>
* <li>
* Doob, J. L. (1942): The Brownian Movement and Stochastic Equations <i>Annals of Mathematics</i>
* <b>43 (2)</b> 351-369
* </li>
* <li>
* Gardiner, C. W. (2009): <i>Stochastic Methods: A Handbook for the Natural and Social Sciences
* 4<sup>th</sup> Edition</i> <b>Springer-Verlag</b>
* </li>
* <li>
* Kadanoff, L. P. (2000): <i>Statistical Physics: Statics, Dynamics, and Re-normalization</i>
* <b>World Scientific</b>
* </li>
* <li>
* Karatzas, I., and S. E. Shreve (1991): <i>Brownian Motion and Stochastic Calculus 2<sup>nd</sup>
* Edition</i> <b>Springer-Verlag</b>
* </li>
* <li>
* Risken, H., and F. Till (1996): <i>The Fokker-Planck Equation – Methods of Solution and
* Applications</i> <b>Springer</b>
* </li>
* </ul>
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ProductCore.md">Product Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/FixedIncomeAnalyticsLibrary.md">Fixed Income Analytics</a></li>
* <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>
* <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>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class CKLSParameters
{
private double _meanReversionLevel = java.lang.Double.NaN;
private double _meanReversionSpeed = java.lang.Double.NaN;
private double _volatilityExponent = java.lang.Double.NaN;
private double _volatilityCoefficient = java.lang.Double.NaN;
/**
* Construct the Vasicek Instance of the CKLS Parameters
*
* @param meanReversionSpeed The Mean Reversion Speed
* @param meanReversionLevel The Mean Reversion Level
* @param volatility The Volatility
*
* @return The Vasicek Instance of the CKLS Parameters
*/
public static final CKLSParameters Vasicek (
final double meanReversionSpeed,
final double meanReversionLevel,
final double volatility)
{
try
{
return new CKLSParameters (
meanReversionSpeed,
meanReversionLevel,
volatility,
0.
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* Construct the Ornstein-Uhlenbeck Instance of the CKLS Parameters
*
* @param meanReversionSpeed The Mean Reversion Speed
* @param volatility The Volatility
*
* @return The Ornstein-Uhlenbeck Instance of the CKLS Parameters
*/
public static final CKLSParameters OrnsteinUhlenbeck (
final double meanReversionSpeed,
final double volatility)
{
try
{
return new CKLSParameters (
meanReversionSpeed,
0.,
volatility,
0.
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* Construct the Cox-Ingersoll-Ross Instance of the CKLS Parameters
*
* @param meanReversionSpeed The Mean Reversion Speed
* @param meanReversionLevel The Mean Reversion Level
* @param volatilityCoefficient The Volatility Coefficient
*
* @return The Cox-Ingersoll-Ross Instance of the CKLS Parameters
*/
public static final CKLSParameters CoxIngersollRoss (
final double meanReversionSpeed,
final double meanReversionLevel,
final double volatilityCoefficient)
{
try
{
return new CKLSParameters (
meanReversionSpeed,
meanReversionLevel,
volatilityCoefficient,
0.5
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* CKLSParameters Constructor
*
* @param meanReversionSpeed The Mean Reversion Speed
* @param meanReversionLevel The Mean Reversion Level
* @param volatilityCoefficient The Volatility Coefficient
* @param volatilityExponent The Volatility Exponent
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public CKLSParameters (
final double meanReversionSpeed,
final double meanReversionLevel,
final double volatilityCoefficient,
final double volatilityExponent)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (
_meanReversionSpeed = meanReversionSpeed
) || 0. > _meanReversionSpeed || !org.drip.numerical.common.NumberUtil.IsValid (
_meanReversionLevel = meanReversionLevel
) || 0. > _meanReversionLevel || !org.drip.numerical.common.NumberUtil.IsValid (
_volatilityCoefficient = volatilityCoefficient
) || 0. > _volatilityCoefficient || !org.drip.numerical.common.NumberUtil.IsValid (
_volatilityExponent = volatilityExponent
) || 0. > _volatilityExponent
)
{
throw new java.lang.Exception (
"CKLSParameters Constructor => Invalid Inputs"
);
}
}
/**
* Retrieve the Mean Reversion Speed
*
* @return The Mean Reversion Speed
*/
public double meanReversionSpeed()
{
return _meanReversionSpeed;
}
/**
* Retrieve the Mean Reversion Level
*
* @return The Mean Reversion Level
*/
public double meanReversionLevel()
{
return _meanReversionLevel;
}
/**
* Retrieve the Volatility Coefficient
*
* @return The Volatility Coefficient
*/
public double volatilityCoefficient()
{
return _volatilityCoefficient;
}
/**
* Retrieve the CKLS Volatility Exponent
*
* @return The CKLS Volatility Exponent
*/
public double volatilityExponent()
{
return _volatilityExponent;
}
}