Noise dressing of financial correlation matrices

Laurent Laloux, Pierre Cizeau, Jean-Philippe Bouchaud and Marc Potters ()
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Laurent Laloux: Science & Finance, Capital Fund Management
Pierre Cizeau: Science & Finance, Capital Fund Management
Jean-Philippe Bouchaud: Science & Finance, Capital Fund Management

No 500051, Science & Finance (CFM) working paper archive from Science & Finance, Capital Fund Management

Abstract: We show that results from the theory of random matrices are potentially of great interest to understand the statistical structure of the empirical correlation matrices appearing in the study of price fluctuations. The central result of the present study is the 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). In particular the present study raises serious doubts on the blind use of empirical correlation matrices for risk management.

JEL-codes: G10 (search for similar items in EconPapers)
Date: 1998-10
New Economics Papers: this item is included in nep-cfn, nep-ecm, nep-fin and nep-rmg
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Citations: View citations in EconPapers (27)

Published in Physical Review Letters 83(7), 1467 (1999)

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Persistent link: https://EconPapers.repec.org/RePEc:sfi:sfiwpa:500051

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