Temporal evolution into a more efficient stock market

Jae-Suk Yang, Taisei Kaizoji () and Wooseop Kwak

Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, issue 11, 2002-2008

Abstract: Using the price change and the log return of 10 stock market indices, we examine the temporal evolution of the time scale. The 10 stock markets had similar properties. Their log-return time series had patterns and long-range correlations until the mid-1990s. In the 2000s, however, the long-range correlations for most markets shortened, and the patterns weakened. These phenomena were due to advances in communication infrastructure such as the Internet and internet-based trading systems, which increased the speed of information dissemination. We examined the temporal evolution of the time scale in the markets by comparing the probability density function of log returns for the 2000s with that in the 1990s and by using the minimum entropy density method.

Keywords: Econophysics; Stock market; Time scale; Minimum entropy density (search for similar items in EconPapers)
Date: 2011
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437111000720
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

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:eee:phsmap:v:390:y:2011:i:11:p:2002-2008

DOI: 10.1016/j.physa.2011.01.009

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().