Augmented ARCH models for financial time series: stability conditions and empirical evidence

Robert Kunst ()

Applied Financial Economics, 1997, vol. 7, issue 6, 575-586

Abstract: The class of conditionally heteroscedastic models known as 'augmented ARCH' encompasses most liear 'ARCH'-type models found in the literature and, in particular, two basic ARCH variants for autocorrelated series: Engle (1982) explains conditional variance by lagged errors, Weiss (1984) also by lagged observations. The framework permits an evaluation of whether the restrictions evolving from the Engle or the Weiss models are valid in practice. Time series of stock market indexes for some major stock exchanges yield empirical examples. In most cases, the statistical approximation to actual dynamic behaviour is improved substantially by considering augmented ARCH structures

Date: 1997
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/758533849 (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:apfiec:v:7:y:1997:i:6:p:575-586

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20

DOI: 10.1080/758533849

Access Statistics for this article

Applied Financial Economics is currently edited by Anita Phillips

More articles in Applied Financial Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().