Garch model indentification using neural network

Abstract

GARCH models are being largely used to estimate the volatility offinancial assets, and GARCH(1,1) is the one most used. However, identificationof GARCH models is not fully explored. Some specialist systems technology havebeen used in some applications of time series models such as time seriesclassification problems, ARMA models identification, as well as SARIMA. The aim of this paper is to develop an intelligent system that can accurately identifythe specification of GARCH models providing the right choice of the model to beused, thus avoiding the indiscriminate usage of GARCH(1,1) model.