CVaR Deviation for Gain Normal Independent. Special 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
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 for Discrete Distribution as Function of Atom Probabilities, CVaR for Mixture of Normal Distributions as Function of Mixture Weights