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On the non-stationarity of financial time series: impact on optimal portfolio selection

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  • Giacomo Livan
  • Jun-ichi Inoue
  • Enrico Scalas

Abstract

We investigate the possible drawbacks of employing the standard Pearson estimator to measure correlation coefficients between financial stocks in the presence of non-stationary behavior, and we provide empirical evidence against the well-established common knowledge that using longer price time series provides better, more accurate, correlation estimates. Then, we investigate the possible consequences of instabilities in empirical correlation coefficient measurements on optimal portfolio selection. We rely on previously published works which provide a framework allowing to take into account possible risk underestimations due to the non-optimality of the portfolio weights being used in order to distinguish such non-optimality effects from risk underestimations genuinely due to non-stationarities. We interpret such results in terms of instabilities in some spectral properties of portfolio correlation matrices.

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File URL: http://arxiv.org/pdf/1205.0877
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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number 1205.0877.

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Date of creation: May 2012
Date of revision: Jul 2012
Publication status: Published in J. Stat. Mech. (2012) P07025
Handle: RePEc:arx:papers:1205.0877

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  1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, 03.
  2. Michael C. M\"unnix & Takashi Shimada & Rudi Sch\"afer & Francois Leyvraz Thomas H. Seligman & Thomas Guhr & H. E. Stanley, 2012. "Identifying States of a Financial Market," Papers 1202.1623, arXiv.org.
  3. Kondor, Imre & Pafka, Szilard & Nagy, Gabor, 2007. "Noise sensitivity of portfolio selection under various risk measures," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1545-1573, May.
  4. Stefano Galluccio & Jean-Philippe Bouchaud & Marc Potters, 1998. "Rational Decisions, Random Matrices and Spin Glasses," Papers cond-mat/9801209, arXiv.org.
  5. Livan, Giacomo & Alfarano, Simone & Scalas, Enrico, 2011. "The fine structure of spectral properties for random correlation matrices: an application to financial markets," MPRA Paper 28964, University Library of Munich, Germany.
  6. Marsili, Matteo & Raffaelli, Giacomo & Ponsot, Benedicte, 2009. "Dynamic instability in generic model of multi-assets markets," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1170-1181, May.
  7. Giacomo Raffaelli & Matteo Marsili, 2005. "Dynamic instability in a phenomenological model of correlated assets," Papers physics/0508159, arXiv.org, revised Apr 2006.
  8. Galluccio, Stefano & Bouchaud, Jean-Philippe & Potters, Marc, 1998. "Rational decisions, random matrices and spin glasses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 259(3), pages 449-456.
  9. Z. Burda & A. Görlich & J. Jurkiewicz & B. Wacław, 2006. "Correlated Wishart matrices and critical horizons," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 49(3), pages 319-323, 02.
  10. Pafka, Szilárd & Kondor, Imre, 2003. "Noisy covariance matrices and portfolio optimization II," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 319(C), pages 487-494.
  11. Burda, Z. & Görlich, A. & Jarosz, A. & Jurkiewicz, J., 2004. "Signal and noise in correlation matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 295-310.
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Cited by:
  1. A. E. Biondo & A. Pluchino & A. Rapisarda & D. Helbing, 2013. "Are random trading strategies more successful than technical ones?," Papers 1303.4351, arXiv.org, revised Jul 2013.

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