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Signal and noise in financial correlation matrices

Author

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  • Burda, Zdzisław
  • Jurkiewicz, Jerzy

Abstract

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.

Suggested Citation

  • Burda, Zdzisław & Jurkiewicz, Jerzy, 2004. "Signal and noise in financial correlation matrices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 67-72.
  • Handle: RePEc:eee:phsmap:v:344:y:2004:i:1:p:67-72
    DOI: 10.1016/j.physa.2004.06.089
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    Citations

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    Cited by:

    1. Eterovic, Nicolas A. & Eterovic, Dalibor S., 2013. "Separating the wheat from the chaff: Understanding portfolio returns in an emerging market," Emerging Markets Review, Elsevier, vol. 16(C), pages 145-169.
    2. Martins, André C.R., 2007. "Non-stationary correlation matrices and noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(2), pages 552-558.
    3. Conlon, T. & Ruskin, H.J. & Crane, M., 2009. "Cross-correlation dynamics in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 705-714.
    4. Conlon, T. & Ruskin, H.J. & Crane, M., 2007. "Random matrix theory and fund of funds portfolio optimisation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 565-576.
    5. Núñez-Mora, José Antonio & Mata-Mata, Leovardo, 2014. "Una aplicación de la teoría de matrices aleatorias para analizar la variación del rendimiento de diferentes commodities a lo largo del periodo 2000-2012," eseconomía, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 0(41), pages 7-20, segundo s.
    6. Thomas Conlon & Heather J. Ruskin & Martin Crane, 2010. "Cross-Correlation Dynamics in Financial Time Series," Papers 1002.0321, arXiv.org.

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