MULTIFRACTIONAL PROPERTIES OF STOCK INDICES DECOMPOSED BY FILTERING THEIR POINTWISE HÖLDER REGULARITY

Sergio Bianchi () and A. Pianese ()
Additional contact information
A. Pianese: Faculty of Economics, University of Cassino, Italy

International Journal of Theoretical and Applied Finance (IJTAF), 2008, vol. 11, issue 06, pages 567-595

Abstract: We propose a decomposition of financial time series into Gaussian subsequences characterized by a constant Hölder exponent. In (multi)fractal models this condition is equivalent to the subsequences themselves being stationarity. For the different subsequences, we study the scaling of the variance and the bias that is generated when the Hölder exponent is re-estimated using traditional estimators. The results achieved by both analyses are shown to be strongly consistent with the assumption that the price process can be modeled by the multifractional Brownian motion, a nonstationary process whose Hölder regularity changes from point to point.

Keywords: Multifractional Brownian motion; pointwise Hölder exponent estimation; stock price process (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://www.worldscinet.com/cgi-bin/details.cgi?type=pdf&id=pii:S0219024908004932 (application/pdf)
http://www.worldscinet.com/cgi-bin/details.cgi?typ ... ii:S0219024908004932 (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: http://EconPapers.repec.org/RePEc:wsi:ijtafx:v:11:y:2008:i:06:p:567-595

Ordering information: This journal article can be ordered from

Access Statistics for this article

International Journal of Theoretical and Applied Finance (IJTAF) is edited by L P Hughston

More articles in International Journal of Theoretical and Applied Finance (IJTAF) from World Scientific Publishing Co. Pte. Ltd.
Series data maintained by Tai Tone Lim ().