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Signal and Noise in Financial Correlation Matrices

Listed author(s):
  • Zdzislaw Burda
  • Jerzy Jurkiewicz
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    Using Random Matrix Theory one can derive exact relations between the eigenvalue spectrum of the covariance matrix and the eigenvalue spectrum of its estimator (experimentally measured correlation matrix). These relations will be used to analyze a particular case of the correlations in financial series and to show that contrary to earlier claims, correlations can be measured also in the ``random'' part of the spectrum. Implications for the portfolio optimization are briefly discussed.

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    Paper provided by in its series Papers with number cond-mat/0312496.

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    Date of creation: Dec 2003
    Date of revision: Feb 2004
    Publication status: Published in Physica A 344, 67 (2004)
    Handle: RePEc:arx:papers:cond-mat/0312496
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