Asymptotics of the QMLE for Non-Linear ARCH Models
Dennis Kristensen and
Anders Rahbek
Journal of Time Series Econometrics, 2009, vol. 1, issue 1, 38
Abstract:
Asymptotic properties of the quasi-maximum likelihood estimator (QMLE) for non-linear ARCH(q) models -- including for example Asymmetric Power ARCH and log-ARCH -- are derived. Strong consistency is established under the assumptions that the ARCH process is geometrically ergodic, the conditional variance function has a finite log-moment, and finite second moment of the rescaled error. Asymptotic normality of the estimator is established under the additional assumption that certain ratios involving the conditional variance function are suitably bounded, and that the rescaled errors have little more than fourth moment. We verify our general conditions, including identification, for a wide range of leading specific ARCH models.
Keywords: ARCH; non-linear; QMLE; asymptotic theory (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
https://doi.org/10.2202/1941-1928.1001 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bpj:jtsmet:v:1:y:2009:i:1:n:2
Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/jtse/html
DOI: 10.2202/1941-1928.1001
Access Statistics for this article
Journal of Time Series Econometrics is currently edited by Javier Hidalgo
More articles in Journal of Time Series Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().