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Cluster analysis for portfolio optimization

Author

Listed:
  • Vincenzo Tola
  • Fabrizio Lillo
  • Mauro Gallegati
  • Rosario N. Mantegna

Abstract

We consider the problem of the statistical uncertainty of the correlation matrix in the optimization of a financial portfolio. We show that the use of clustering algorithms can improve the reliability of the portfolio in terms of the ratio between predicted and realized risk. Bootstrap analysis indicates that this improvement is obtained in a wide range of the parameters N (number of assets) and T (investment horizon). The predicted and realized risk level and the relative portfolio composition of the selected portfolio for a given value of the portfolio return are also investigated for each considered filtering method.

Suggested Citation

  • Vincenzo Tola & Fabrizio Lillo & Mauro Gallegati & Rosario N. Mantegna, 2005. "Cluster analysis for portfolio optimization," Papers physics/0507006, arXiv.org.
    • Handle: RePEc:arx:papers:physics/0507006
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    References listed on IDEAS

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    1. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169.
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