Testing persistence in the context of conditional heteroscedasticity errors

Luis Gil-Alana

Applied Financial Economics, 2010, vol. 20, issue 22, 1709-1723

Abstract: This article examines the power of two well-known procedures of fractional integration in the context of conditional heteroskedasticity in the variance. One of the methods is parametric while the other is semiparametric. Several Monte Carlo experiments conducted in this article show that both methods perform well to detect the order of integration of the series under the assumption that the underlying disturbances follow Generalized Autoregressive Conditional Heteroscedasticity (GARCH)-type errors. The methods are applied to 10 European stock market indices. The results indicate that the orders of integration of the series are close to 1 in all cases, being strictly higher than 1 in four countries. Moreover, taking the d-differenced processes, and estimating Fractionally Integrated GARCH (FI-GARCH) models on the squared residuals, fractional degrees of integration are obtained in the majority of the series.

Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09603107.2010.522516 (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:20:y:2010:i:22:p:1709-1723

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

DOI: 10.1080/09603107.2010.522516

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 ().