Volatility of Stock-Market Indexes--An Analysis Based on SEMIFAR Models
Jan Beran and
Dirk Ocker
Journal of Business & Economic Statistics, 2001, vol. 19, issue 1, 103-16
Abstract:
By applying SEMIFAR models, we examine "long memory" in the volatility of worldwide stock-market indexes. Our analysis yields strong evidence of "long memory" in stock-market volatility, either in terms of stochastic long-range dependence or in the form of deterministic trends. In some cases, both components are detected in the data. Thus, at least partially, there appears to be even stronger and more systematic long memory than suggested by a stationary model with long-range dependence.
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (14)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
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:bes:jnlbes:v:19:y:2001:i:1:p:103-16
Ordering information: This journal article can be ordered from
http://www.amstat.org/publications/index.html
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano
More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().