I am a beginner in R and my econometrics background is not very sound either. I want to build a constant conditional correlation GARCH (1,1) model in R and I found the function, the description of which I have copy-pasted below. This functions requires that you calculate the individual matrices and vectors individually and then you plug them into the function. The problem is that I do not know how to do it individually. Is there any package that calculates the GARCH coefficients automatically?
Thanks a lot!
Simulating an (E)CCC-GARCH(1,1) process
Description
This function simulates data either from the original CCC-GARCH by Bollerslev (1990) or from the Extended CCC-GARCH that has non-zero off-diagonal entries in the parameter matrices in the GARCH equation. The innovations (the standardised residuals) can be either a normal or student's $t$ distribution.
The dimension (N) is determined by the number of elements in the \mathbf{a} vector.
Usage
eccc.sim(nobs, a, A, B, R, d.f=Inf, cut=1000, model) Arguments
nobs
a number of observations to be simulated (T)
a
a vector of constants in the GARCH equation (N \times 1)
A
an ARCH parameter matrix in the GARCH equation. \mathbf{A} can be a diagonal matrix for the original CCC-GARCH model or a full matrix for the extended model (N \times N)
B
a GARCH parameter matrix in the GARCH equation. \mathbf{B} can be a diagonal matrix for the original CCC-GARCH model or a full matrix for the extended model (N \times N)
R
a constant conditional correlation matrix (N \times N)
d.f the degrees of freedom parameter for the t-distribution
cut the number of observations to be thrown away for removing initial effects of simulation
model
a character string describing the model. "diagonal" for the diagonal model and "extended" for the extended (full ARCH and GARCH parameter matrices) model