Analysis of delay correlation matrices

K. B. K. Mayya and R. E. Amritkar

Papers from arXiv.org

Abstract: We construct and analyze symmetrized delay correlation matrices for empirical data sets for atmopheric and financial data to derive information about correlation between different entities of the time series over time. The information about correlations is obtained by comparing the results for the eigenvalue distribution with the analytical results for the independent, identically distributed random data sets. For the atmospheric case we find long term correlations between different entities of the multivariable time series. For the financial time series we find little correlations between different entities over a time delay beyond about two days. Most of the eigenvalues for the symmetrized delay correlation matrices for the financial data are symmetrically distributed about zero. The delay correlation results for the financial data are similar to the analytical results for the random data sets. However there are considerable deviations for the atmospheric data from the random case.

Date: 2006-01
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://arxiv.org/pdf/cond-mat/0601279 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/0601279

Access Statistics for this paper

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