VaR for Gain Normal Dependent. Special case of the VaR for Gain when all coefficients in Linear Loss function are mutually dependent  normally distributed random values.

 

Syntax

 

Parameters

matrix_mn        is a PSG matrix of mean values:

 

where the header row contains names of variables. The second row contains numerical data.

 

matrix_cov        is a PSG matrix of covariance values:

 

where the header row contains names of variables. Other rows contain numerical data.

       is a confidence level.

 

Mathematical Definition

VaR for Gain Normal Dependent function is calculated as follows:

,

where

is a VaR Normal Dependent function,

is Gain function (See section Loss and Gain Functions),

,

,

,

is the standard normal distribution,

 is probability density function of the standard normal distribution,

is an argument of VaR for Gain Normal Dependent function.

 

Example

 

See also

VaR  Normal Dependent,

VaR,

VaR Normal Independent,

VaR Deviation, VaR Deviation Normal Independent, VaR Deviation Normal Dependent,

VaR for Mixture of Normal Independent, VaR Deviation for Mixture of Normal Independent