Package org.drip.function.rdtor1

Class RiskObjectiveUtilityMultivariate

java.lang.Object

org.drip.function.definition.RdToR1

org.drip.function.rdtor1.RiskObjectiveUtilityMultivariate

public class RiskObjectiveUtilityMultivariate
extends RdToR1

RiskObjectiveUtilityMultivariate implements the Risk Objective R^d To R¹ Multivariate Function used in Portfolio Allocation. It accommodates both the Risk Tolerance and Risk Aversion Variants.

• Module = Computational Core Module
• Library = Numerical Analysis Library
• Project = R^d To R^d Function Analysis
• Package = Built-in R^d To R¹ Functions

Author:

Lakshmi Krishnamurthy

Constructor Summary

Constructors

Constructor	Description
RiskObjectiveUtilityMultivariate(double[][] aadblCovarianceMatrix, double[] adblExpectedReturns, double dblRiskAversion, double dblRiskTolerance, double dblRiskFreeRate)	RiskObjectiveUtilityMultivariate Constructor

Method Summary

Modifier and Type	Method	Description
double[][]	covariance()	Retrieve the Co-variance Matrix
int	dimension()	Retrieve the Input Variate Dimension
double	evaluate(double[] adblVariate)	Evaluate for the given Input Variates
double[]	expectedReturns()	Retrieve the Array of Expected Returns
double[][]	hessian(double[] adblVariate)	Evaluate The Hessian for the given Input Variates
double[]	jacobian(double[] adblVariate)	Evaluate the Jacobian for the given Input Variates
double	riskAversion()	Retrieve the Risk Aversion Factor
double	riskFreeRate()	Retrieve the Risk Free Rate
double	riskTolerance()	Retrieve the Risk Tolerance Factor

Methods inherited from class org.drip.function.definition.RdToR1

conditionNumber, conditionNumberL2, conditionNumberLInfinity, conditionNumberLp, derivative, differential, gradient, gradientModulus, gradientModulusFunction, integrate, maxima, minima, ValidateInput

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

RiskObjectiveUtilityMultivariate

public RiskObjectiveUtilityMultivariate(double[][] aadblCovarianceMatrix,
double[] adblExpectedReturns,
double dblRiskAversion,
double dblRiskTolerance,
double dblRiskFreeRate)
                                 throws java.lang.Exception

RiskObjectiveUtilityMultivariate Constructor

Parameters:

aadblCovarianceMatrix - The Co-variance Matrix Double Array

adblExpectedReturns - Array of Expected Returns

dblRiskAversion - The Risk Aversion Parameter

dblRiskTolerance - The Risk Tolerance Parameter

dblRiskFreeRate - The Risk Free Rate

Throws:

java.lang.Exception - Thrown if the Inputs are Invalid

Method Details

dimension

public int dimension()

Retrieve the Input Variate Dimension

Specified by:

dimension in class RdToR1

Returns:

The Input Variate Dimension

covariance

public double[][] covariance()

Retrieve the Co-variance Matrix

Returns:

The Co-variance Matrix

expectedReturns

public double[] expectedReturns()

Retrieve the Array of Expected Returns

Returns:

The Array of Expected Returns

riskAversion

public double riskAversion()

Retrieve the Risk Aversion Factor

Returns:

The Risk Aversion Factor

riskTolerance

public double riskTolerance()

Retrieve the Risk Tolerance Factor

Returns:

The Risk Tolerance Factor

riskFreeRate

public double riskFreeRate()

Retrieve the Risk Free Rate

Returns:

The Risk Free Rate

evaluate

public double evaluate(double[] adblVariate)
                throws java.lang.Exception

Description copied from class: RdToR1

Evaluate for the given Input Variates

Specified by:

evaluate in class RdToR1

Parameters:

adblVariate - Array of Input Variates

Returns:

The Calculated Value

Throws:

java.lang.Exception - Thrown if the Evaluation cannot be done

jacobian

public double[] jacobian(double[] adblVariate)

Description copied from class: RdToR1

Evaluate the Jacobian for the given Input Variates

Overrides:

jacobian in class RdToR1

Parameters:

adblVariate - Array of Input Variates

Returns:

The Jacobian Array

hessian

public double[][] hessian(double[] adblVariate)

Description copied from class: RdToR1

Evaluate The Hessian for the given Input Variates

Overrides:

hessian in class RdToR1

Parameters:

adblVariate - Array of Input Variates

Returns:

The Hessian Matrix