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

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  • Robert Kunst

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

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

Volume (Year): 7 (1997)
Issue (Month): 6 ()
Pages: 575-586

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Handle: RePEc:taf:apfiec:v:7:y:1997:i:6:p:575-586

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Cited by:
  1. Andreas, Brunhart, 2011. "Stock market’s reactions to revelation of tax evasion: an empirical assessment," MPRA Paper 42047, University Library of Munich, Germany, revised Sep 2012.
  2. Kunst, Robert M., 2003. "Testing for Relative Predictive Accuracy: A Critical Viewpoint," Economics Series 130, Institute for Advanced Studies.

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