Accounting for conditional leptokurtosis and closing days effects in FIGARCH models of daily exchange rates
Michel Beine,
Sébastien Laurent and
Christelle Lecourt
Applied Financial Economics, 2002, vol. 12, issue 8, 589-600
Abstract:
This paper, estimates FIGARCH models introduced by Baillie et al. (1996a) for the four major daily exchange rates against the USD (DEM, FRF, YEN and the GBP). The former contributions are extended by accounting for the observed kurtosis through a Student- t based maximum likelihood estimation and by including variables capturing the effect of closing days. These estimations suggest that the introduction of these features improves the goodness of fit properties of the model on the one hand, and may lead to different interest parameters estimates on the other hand. In particular, it is shown that in the case of the DEM, volatility shocks may display much less persistence than documented by previous studies. Finally, it is shown that an ARFIMA-FIGARCH framework turns out to be relevant for all the currencies (except the GBP), without inducing any significant changes in the inference of the stochastic volatility process.
Date: 2002
References: View complete reference list from CitEc
Citations: View citations in EconPapers (31)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09603100010014041 (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:12:y:2002:i:8:p:589-600
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20
DOI: 10.1080/09603100010014041
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 ().