ccgarch (version 0.2.2)

grad.dcc.full: Numerical gradient of the full log-likelihood function of the (E)DCC-GARCH model

Description

This function computes numerical gradient of the full log-likelihood function of the (E)DCC-GARCH(1,1) model with respect to its parameters.

Usage

grad.dcc.full(a, A, B, dcc.para, dvar, d=1e-5, model)

Arguments

a

a constant vector in the vector GARCH equation $(N \times 1)$

A

an ARCH parameter matrix in the vector GARCH equation $(N \times N)$

B

a GARCH parameter matrix in the vector GARCH equation $(N \times N)$

dcc.para

a vector of the DCC parameters $(2 \times 1)$

dvar

a matrix of the data used for estimating the (E)DCC-GARCH model $(T \times N)$

d

a step size for computing numerical gradient

model

a character string describing the model. "diagonal" for the diagonal model and "extended" for the extended (full ARCH and GARCH parameter matrices) model

Value

• a matrix of partial derivatives $(T \times npar)$