CVaR Deviation for Gain Normal Independent (cvar_ni_dev_g)

CVaR Deviation for Gain Normal IndependentSpecial case of the CVaR Deviation for Gain when all coefficients in -(Linear Loss ) function are independent normally distributed random values.

 

Syntax

cvar_ni_dev_g(α, matrix_mn,matrix_vr)

short call

cvar_ni_dev_g_name(α, matrix_mn,matrix_vr)

call with optional name

 

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_vr        is a PSG matrix of variance values:

 

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

 

       is a confidence level.

 

Mathematical Definition

CVaR Deviation for Gain Normal Independent function is calculated as follows:

,

where

is CVaR Risk for Loss Normal Independent function,

,

,

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

,

,

 is a probability density function of the standard normal distribution,

,

is the standard normal distribution,

is an argument of function.

 

Remarks

matrix_mn do not used in the calculation of CVaR Deviation for Gain Normal Independent function

 

Example

Calculation in Run-File Environment
Calculation in MATLAB Environment

 

See also

CVaR Deviation Normal Independent,

CVaR,

CVaR Normal Independent, CVaR Normal Dependent,

CVaR Deviation, CVaR Deviation Normal Dependent,

CVaR for Mixture of Normal Independent, CVaR Deviation for Mixture of Normal Independent

CVaR Max, CVaR Max Deviation,

CVaR for Discrete Distribution as Function of Atom Probabilities, CVaR for Mixture of Normal Distributions as Function of Mixture Weights