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RANDOM MATRIX THEORY AND FINANCIAL CORRELATIONS

2000; World Scientific; Volume: 03; Issue: 03 Linguagem: Inglês

10.1142/s0219024900000255

1793-6322

Laurent Laloux, Pierre Cizeau, Marc Potters, Jean‐Philippe Bouchaud,

Theoretical and Computational Physics

We show that results from the theory of random matrices are potentially of great interest when trying to understand the statistical structure of the empirical correlation matrices appearing in the study of multivariate financial time series. We find a remarkable agreement between the theoretical prediction (based on the assumption that the correlation matrix is random) and empirical data concerning the density of eigenvalues associated to the time series of the different stocks of the S&P500 (or other major markets). Finally, we give a specific example to show how this idea can be sucessfully implemented for improving risk management.