4 Conclusions
As the two noise reduction methods are conceptually different, they also produce different results. Our preliminary studies cannot serve as a basis to make schematic suggestions as to which method ought to be preferred in which situation. This will always be difficult. But further and systematic studies extending the ones presented here might yield some guidelines.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Laloux L, Cizeau P, Bouchaud JP, Potters M (1999), Noise Dressing of Financial Correlation Matrices, Phys. Rev. Lett. 83:1467–1470
Plerou V, Gopikrishnan P, Rosenow B, Amaral LAN, Stanley HE (1999), Universal and Nonuniversal Properties of Cross-Correlations in Financial Time Series, Phys. Rev. Lett. 83:1471–1474
Gopikrishnan P, Rosenow B, Plerou V, Stanley HE (2001), Quantifying and Interpreting Collective Behavior in Financial Markets, Phys. Rev. E64:035106(R)
Plerou V, Gopikrishnan P, Rosenow B, Amaral LAN, Guhr T, Stanley HE (2002), A Random Matrix Approach to Cross-Correlations in Financial Data, Phys. Rev. E65:066126
Guhr T, Kälber B (2003), A New Method to Estimate the Noise in Financial Correlation Matrices, J. Phys. A36:3009–3032
www.stockholmsborsen.se (2003), web download
Fama E, French K (2003), web download
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Tokyo
About this paper
Cite this paper
Andersson, PJ., Öberg, A., Guhr, T. (2006). Testing Methods to Reduce Noise in Financial Correlation Matrices. In: Takayasu, H. (eds) Practical Fruits of Econophysics. Springer, Tokyo. https://doi.org/10.1007/4-431-28915-1_42
Download citation
DOI: https://doi.org/10.1007/4-431-28915-1_42
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-28914-2
Online ISBN: 978-4-431-28915-9
eBook Packages: Business and EconomicsEconomics and Finance (R0)