Bayesian Analysis of FIAPARCH Model: An Application to Sao Paulo Stock Market

Abstract

In this paper, we develop a Bayesian analysis of a FIAPARCH(p,d,q) model for parameter estimation and conditional variance prediction. In order to study the inference problem we use the Metropolis-Hastings algorithm.This methodology is illustrated in a simulation study and it is applied to a set of observations concerning the returns of IBOVESPA values.