Statistical properties of volatility in fractal dimensions and probability distribution among six stock markets
Hai-Chin Yu and
Ming-Chang Huang
Applied Financial Economics, 2004, vol. 14, issue 15, 1087-1095
Abstract:
This study examines the statistical properties of volatility among New York, Tokyo, Taiwan, South Korea, Singapore and Hong Kong stock markets. Fractal dimensions, probability distribution and two-point volatility correlation are used to measure and compare volatility among the six over the 12-year period from 1 January 1990 to 31 December 2001. New York market is found to be the strongest among all in terms of market efficiency. Moreover, the Tokyo and Singapore markets are found to be very similar in fractal dimension and probability distribution, but different in their resistance to volatility: Tokyo has a higher ability to dissipate volatility. This phenomenon implies that the Tokyo market is more efficient than the Singapore market. Hong Kong market is similar to the Singapore market in its ability to dissipate volatility. Meanwhile, Taiwanese and Korean markets are the most two volatile markets among the six, but Taiwanese market is weaker than the Korean market in dissipating volatility.
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09603100412331297694 (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:14:y:2004:i:15:p:1087-1095
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20
DOI: 10.1080/09603100412331297694
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 ().