Abstract
In this work a sequence of procedures are described to estimate parameters, to select order and to forecast the Autoregressive Conditional Heteroskedasticity ARCH(p) and the generalized ARCH, GARCH(p,q) models. The estimates are obtained by using both classical maximum likelihood method and Bayesian inference approach jointly with simulation of Monte Carlo Markov Chain (MCMC). In the Baye…