Imposing stationarity constraints on the parameters of ARCH and GARCH models

Christopher J. O’Donnell and Vanessa Rayner

A chapter in Bayesian Econometrics, 2008, pp 545-566 from Emerald Group Publishing Limited

Abstract: In their seminal papers on ARCH and GARCH models, Engle (1982) and Bollerslev (1986) specified parametric inequality constraints that were sufficient for non-negativity and weak stationarity of the estimated conditional variance function. This paper uses Bayesian methodology to impose these constraints on the parameters of an ARCH(3) and a GARCH(1,1) model. The two models are used to explain volatility in the London Metals Exchange Index. Model uncertainty is resolved using Bayesian model averaging. Results include estimated posterior pdfs for one-step-ahead conditional variance forecasts.

Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-9053(08)23017-3

DOI: 10.1016/S0731-9053(08)23017-3

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