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On asymptotic theory for ARCH(∞) models

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Hafner, Christian [UCL] Preminger, Arie [UCL]

ARCH(∞) models nest a wide range of ARCH and GARCH models in- cluding models with long memory in volatility. Existing work assumes the existence of second moments. However, the FIGARCH model, one version of a long memory in volatility model, does not have finite second moments and rarely satisfies the moment conditions of the existing literature. This pa- per weakens the moment assumptions of a general ARCH(∞) class of models, and develops the theory for consistency and asymptotic normality of the quasi maximum likelihood estimator.

Document type Document de travail (Working Paper)
Access type Accès libre
Publication date 2017
Language Anglais
Number of pages 22 pages
Collection ISBA Discussion Paper - 2017/09
Affiliations UCL - SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles
UCL - SSH/LIDAM/CORE - Center for operations research and econometrics
Keywords volatility ; long memory ; fractional integration ; quasi maximum likelihood
Links
Bibliographic reference Hafner, Christian ; Preminger, Arie. On asymptotic theory for ARCH(∞) models. ISBA Discussion Paper ; 2017/09 (2017) 22 pages
Permanent URL http://hdl.handle.net/2078.1/185255