Economics at your fingertips  

Multiscaled Cross-Correlation Dynamics in Financial Time-Series

Thomas Conlon (), Heather J. Ruskin and Martin Crane

Papers from

Abstract: The cross correlation matrix between equities comprises multiple interactions between traders with varying strategies and time horizons. In this paper, we use the Maximum Overlap Discrete Wavelet Transform to calculate correlation matrices over different timescales and then explore the eigenvalue spectrum over sliding time windows. The dynamics of the eigenvalue spectrum at different times and scales provides insight into the interactions between the numerous constituents involved. Eigenvalue dynamics are examined for both medium and high-frequency equity returns, with the associated correlation structure shown to be dependent on both time and scale. Additionally, the Epps effect is established using this multivariate method and analyzed at longer scales than previously studied. A partition of the eigenvalue time-series demonstrates, at very short scales, the emergence of negative returns when the largest eigenvalue is greatest. Finally, a portfolio optimization shows the importance of timescale information in the context of risk management.

Date: 2010-01
New Economics Papers: this item is included in nep-rmg
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Published in Advances in Complex Systems, 12 (4-5) (2009), 439-454

Downloads: (external link) 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:

Access Statistics for this paper

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

Page updated 2021-09-23
Handle: RePEc:arx:papers:1001.0497