Pseudo-maximum likelihood estimation of ARCH$(\infty )$ models

Abstract

Strong consistency and asymptotic normality of the Gaussian pseudo-maximum likelihood estimate of the parameters in a wide class of ARCH$(\infty )$ processes are established. The conditions are shown to hold in case of exponential and hyperbolic decay in the ARCH weights, though in the latter case a faster decay rate is required for the central limit theorem than for the law of large numbers. Particular parameterizations are discussed.

Published at http://dx.doi.org/10.1214/009053606000000245 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

References in corpus (1)

• Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: A stochastic recurrence equations approach