Volatility and autocorrelation in major European stock markets

G. Geoffrey Booth and Gregory Koutmos

The European Journal of Finance, 1998, vol. 4, issue 1, 61-74

Abstract: This paper models index stock returns for four major European stock markets as conditionally heteroskedastic processes with time dependent serial correlation. The evidence suggests that current returns in these markets are nonlinearly dependent on their past history. The dependence is strong during calm periods and weak during volatile periods and manifests itself as an inverse relationship between first order autocorrelations and volatility. While this relationship is statistically significant in daily returns, it is absent from weekly returns. Additional tests reveal that the nonlinear specification used by LeBaron (1992) is not necessarily the most adequate representation of the short-term dynamics of stock index returns.

Keywords: EAR-EGARCH model; volatility; autocorrelation; European stock markets (search for similar items in EconPapers)
Date: 1998
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/13518479800000003 (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:eurjfi:v:4:y:1998:i:1:p:61-74

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/REJF20

DOI: 10.1080/13518479800000003

Access Statistics for this article

The European Journal of Finance is currently edited by Chris Adcock

More articles in The European Journal of Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().