Measuring Volatility Clustering in Stock Markets

Gabjin Oh, Seunghwan Kim, Cheoljun Eom and Taehyuk Kim

Papers from arXiv.org

Abstract: We propose a novel method to quantify the clustering behavior in a complex time series and apply it to a high-frequency data of the financial markets. We find that regardless of used data sets, all data exhibits the volatility clustering properties, whereas those which filtered the volatility clustering effect by using the GARCH model reduce volatility clustering significantly. The result confirms that our method can measure the volatility clustering effect in financial market.

Date: 2007-09
References: Add references at CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/0709.2416 Latest version (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:arx:papers:0709.2416

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().