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Multiscaled cross-correlation dynamics in financial time series

Conlon, Thomas and Ruskin, Heather J. and Crane, Martin (2009) Multiscaled cross-correlation dynamics in financial time series. Advances in Complex Systems, 12 (4-5). pp. 439-454. ISSN 0219-5259

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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 (MODWT) to calculate correlation matrices over different time scales and then explore the eigenvalue spectrum over sliding time windows. The dynamics of the eigenvalue spectrum at different scales provides insight into the interactions between the numerous constituents involved. A study of the eigenvalue spectrum in its entirety provides further insight. On partitioning the eigenvalue time series, we show that negative index returns, (drawdowns), are associated with periods where the largest eigenvalue is greatest, while positive index returns, (drawups), are associated with periods where the largest eigenvalue is smallest. Furthermore, through the study of the small eigenvalues of the correlation matrix, we show that information about the correlation dynamics is visible at both ends of the eigenspectrum across all scales.

Item Type:Article (Published)
Uncontrolled Keywords:random matrix theory (RMT); wavelets; eigenvalues; eigenanalysis; financial time series; equity returns;
Subjects:Mathematics > Numerical analysis
Mathematics > Statistics
Physical Sciences > Statistical physics
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:World Scientific Publishing
Official URL:
Copyright Information:Copyright © 2009 World Scientific Publishing Co.
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:14915
Deposited On:01 Oct 2009 10:44 by Martin Crane. Last Modified 01 Oct 2009 11:23

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