Name

garch_grad2 — Generates garch gradient

CALLING SEQUENCE

[g,dht,gradt]=garch_grad2(parm,nar,nma,y,x)

PARAMETERS

Input

• parm= vector of parameters (beta, a0, ar and ma in that order)

• nar = # of ar parameters

• nma = # of ma parameters

• y = (n x 1) vector of the endogenous variable

• x = (n x k) vector of the exogenous variables

Output

• g = (k+nar+nma+1 x 1) -gradient at param

• dht = (nobs x nar+nma+1) derivative of sigt w.r.t a0, ar, ma

• scores = (k+nar+nma+1 x 1) sub-gradient at each date

DESCRIPTION

Generates garch likelihood gradient. The maximised parameters are the parameters before the transformation that insures the positivity of the variance, whereas garch_gard applies to the true garch parameters, that is the ones obtained after this transformation.

EXAMPLE

g=garch_grad2(p,nar,nma,grocer_y,grocer_x)
 
Example taken from function garch().  

               

AUTHOR

Eric Dubois 2002