Autorregresive conditional volatility, skewness and kurtosis

Angel León, Gonzalo Rubio Irigoyen and Gregorio Serna

No 1988-088X, DFAEII Working Papers from University of the Basque Country - Department of Foundations of Economic Analysis II

Abstract: This paper proposes a GARCH-type model allowing for time-varying volatility, skewness and kurtosis. The model is estimated assuming a Gram-Charlier series expansion of the normal density function for the error term, which is easier to estimate than the non-central t distribution proposed by Harvey and Siddique (1999). Moreover, this approach accounts for time-varying skewness and kurtosis while the approach by Harvey and Siddique (1999) only accounts for nonnormal skewness. We apply this method to daily returns of a variety of stock indices and exchange rates. Our results indicate a significant presence of conditional skewness and kurtosis. It is also found that specifications allowing for time-varying skewness and kurtosis outperform specifications with constant third and fourth moments.

Keywords: conditional volatility; skewness and kurtosis; Gram-Charlier series expansion; stock indices (search for similar items in EconPapers)
Date: 2002
References: Add references at CitEc
Citations:

Downloads: (external link)
https://addi.ehu.eus/handle/10810/6759 (application/pdf)

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:ehu:dfaeii:6759

Ordering information: This working paper can be ordered from
Dpto. de Fundamentos del Análisis Económico II, = Facultad de CC. Económicas y Empresariales, Universidad del País Vasco, Avda. Lehendakari Aguirre 83, 48015 Bilbao, Spain

Access Statistics for this paper

More papers in DFAEII Working Papers from University of the Basque Country - Department of Foundations of Economic Analysis II Contact information at EDIRC.
Bibliographic data for series maintained by Alcira Macías Redondo ().