Systems with Correlations in the Variance: Generating Power-Law Tails in Probability Distributions

Boris Podobnik, Plamen Ch. Ivanov, Youngki Lee, Alessandro Chessa and H. Eugene Stanley

Papers from arXiv.org

Abstract: We study how the presence of correlations in physical variables contributes to the form of probability distributions. We investigate a process with correlations in the variance generated by (i) a Gaussian or (ii) a truncated L\'{e}vy distribution. For both (i) and (ii), we find that due to the correlations in the variance, the process ``dynamically'' generates power-law tails in the distributions, whose exponents can be controlled through the way the correlations in the variance are introduced. For (ii), we find that the process can extend a truncated distribution {\it beyond the truncation cutoff}, which leads to a crossover between a L\'{e}vy stable power law and the present ``dynamically-generated'' power law. We show that the process can explain the crossover behavior recently observed in the $S&P500$ stock index.

Date: 1999-10, Revised 2000-05
References: View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://arxiv.org/pdf/cond-mat/9910433 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:cond-mat/9910433

Access Statistics for this paper

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