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Cross-correlation dynamics in financial time series
Conlon, Thomas; Ruskin, Heather J.; Crane, Martin
The dynamics of the equal-time cross-correlation matrix of multivariate financial time series is explored by examination of the eigenvalue spectrum over sliding time windows. Empirical results for the S&P 500 and the Dow Jones Euro Stoxx 50 indices reveal that the dynamics of the small eigenvalues of the cross-correlation matrix, over these time windows, oppose those of the largest eigenvalue. This behaviour is shown to be independent of the size of the time window and the number of stocks examined. A basic one-factor model is proposed, which captures the main dynamical features of the eigenvalue spectrum of the empirical data. Through the addition of perturbations to the one-factor model, (leading to a market plus sectors model), additional sectoral features are added, resulting in an Inverse Participation Ratio comparable to that found for empirical data.
Keyword(s): Numerical analysis; Statistical physics; Computer simulation; Stochastic analysis; correlation matrix; eigenspectrum analysis; econophysics
Publication Date:
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Conlon, Thomas, Ruskin, Heather J. ORCID: 0000-0001-7101-2242 <> and Crane, Martin ORCID: 0000-0001-7598-3126 <> (2009) Cross-correlation dynamics in financial time series. Physica A Statistical Mechanics and its Applications, 388 (5). pp. 705-714. ISSN 0378-4371
Publisher(s): Elsevier
File Format(s): application/pdf
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First Indexed: 2009-11-05 02:01:43 Last Updated: 2019-02-09 06:57:32