HOW TO ESTIMATE A SPLINE-GARCH MODEL?

[ebondo75]

Hi all,

Does anybody know how to implement the spline-garch model introduced by Engle in 2005 with eviews?

The model is define as:
y = mu + res res~N(0,h_t)
h_t=g_t * f_t
where
g_t= (1-beta_1-beta_2) + beta_1*(res_{t-1}^2)/f_{t-1} + beta_2*g_{t-1}
f_t=gamma_0*exp [gamma_1*t + gamma_2*t^2 + Sum (i=1,k) w_i*max(0,t-t_i) ]

f_t is a deterministic function which represent here a quadratic spline specified as the sum of k truncated quadratic basis functions.

A full definition of the model is available here: http://economics.ucr.edu/seminars/fall0 ... 2-9-05.pdf (page 4)

I want to implement this model by using the log-likehood object of eviews but i don't know how to do that.

Does anyone have an idea on how to estimate the parameters for spline garch please?

Thanks in advance,

Regards,