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Asymptotic Theory for ARCH Models: Estimation and Testing

Published online by Cambridge University Press:  18 October 2010

Andrew A. Weiss*
Affiliation:
University of Southern California at Los Angeles

Abstract

In the context of a linear dynamic model with moving average errors, we consider a heteroscedastic model which represents an extension of the ARCH model introduced by Engle [4]. We discuss the properties of maximum likelihood and least squares estimates of the parameters of both the regression and ARCH equations, and also the properties of various tests of the model that are available. We do not assume that the errors are normally distributed.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1986 

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