ECONOPHYSICS: WHAT CAN PHYSICISTS CONTRIBUTE TO ECONOMICS?

H. Eugene Stanley, Luís A. Nunes Amaral, Parameswaran Gopikrishnan, Yanhui Liu, Vasiliki Plerou and Bernd Rosenow
Additional contact information
H. Eugene Stanley: Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA
Luís A. Nunes Amaral: Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA
Parameswaran Gopikrishnan: Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA
Yanhui Liu: Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA
Vasiliki Plerou: Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA;
Bernd Rosenow: Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA;

International Journal of Theoretical and Applied Finance (IJTAF), 2000, vol. 03, issue 03, 335-346

Abstract: In recent years, a considerable number of physicists have started applying physics concepts and methods to understand economic phenomena. The term "Econophysics" is sometimes used to describe this work. Economic fluctuations can have many repercussions, and understanding fluctuations is a topic that many physicists have contributed to in recent years. Further, economic systems are examples of complex interacting systems for which a huge amount of data exist and it is possible that the experience gained by physicists in studying fluctuations in physical systems might yield new results in economics. Much recent work in econophysics is focused on understanding the peculiar statistical properties of price fluctuations in financial time series. In this talk, we discuss three recent results. The first result concerns the probability distribution of stock price fluctuations. This distribution decreases with increasing fluctuations with a power-law tail well outside the Lévy stable regime and describes fluctuations that differ by as much as 8 orders of magnitude. Further, this nonstable distribution preserves its functional form for fluctuations on time scales that differ by 3 orders of magnitude, from 1 min up to approximately 10 days. The second result concerns the accurate quantification of volatility correlations in financial time series. While price fluctuations themselves have rapidly decaying correlations, the volatility estimated by using either the absolute value or the square of the price fluctuations has correlations that decay as a power-law and persist for several months. The third result bears on the application of random matrix theory to understand the correlations among price fluctuations of any two different stocks. We compare the statistics of the cross-correlation matrix constructed from price fluctuations of the leading 1000 stocks and a matrix with independent random elements, i.e., a random matrix. Contrary to first expectations, we find little or no deviation from the universal predictions of random matrix theory for all but a few of the largest eigenvalues of the cross-correlation matrix.

Keywords: Scaling; distributions; power-laws; returns; Lévy (search for similar items in EconPapers)
Date: 2000
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219024900000796
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:wsi:ijtafx:v:03:y:2000:i:03:n:s0219024900000796

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219024900000796

Access Statistics for this article

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

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