The ARCH(2) model: Pseudo-maximum estimation and asymptotic results under dependent innovations

Eugene Kouassi, Patrice Takam Soh, Morvan N. Donfack and Jean Marcelin B. Bosson

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 9, 2146-2171

Abstract: This paper investigates the pseudo-maximum likelihood (PML) estimation of an ARCH(2) model when the innovations' law belongs to the quadratic exponential family. In addition, the error terms are conditionally independent, but not necessarily dependent. The consistency and asymptotic normality of the PML estimator are obtained by means of martingale techniques.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2017.1337142 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:47:y:2018:i:9:p:2146-2171

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2017.1337142

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().