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Portfolio Management With Higher Moments: The Cardinality Impact

Author

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  • Rui Pedro Brito

    (Faculty of Economics, University of Coimbra, and GEMF, Portugal)

  • Hélder Sebastião

    (Faculty of Economics, University of Coimbra, and GEMF, Portugal)

  • Pedro Godinho

    (Faculty of Economics, University of Coimbra, and GEMF, Portugal)

Abstract

In this paper we extend the study of the cardinality impact from the standard mean-variance scenario to higher moments, considering a utility maximization framework. For each scenario, we propose a bi-objective model that allows the investor to directly analyse the efficient trade-off between expected utility and cardinality. We study not only the effect of cardinality in each scenario but also the real gain of considering higher moments in portfolio management. This analysis is performed assuming that the investor has constant relative risk aversion (CRRA) preferences. For the data collected on the PSI20 index, the empirical results showed that there are no performance gains, in-sample, from the efficient mean-variance expected utility/cardinality portfolios to the efficient expected utility/cardinality portfolios when higher moments are considered. However, the out-of-sample performance of the efficient mean-variance-skewness expected utility/cardinality portfolios and of the efficient mean-variance-skewness-kurtosis expected utility/cardinality portfolios suggest the existence of real gains, especially when transaction costs are considered.

Suggested Citation

  • Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2015. "Portfolio Management With Higher Moments: The Cardinality Impact," GEMF Working Papers 2015-15, GEMF, Faculty of Economics, University of Coimbra.
  • Handle: RePEc:gmf:wpaper:2015-15
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    References listed on IDEAS

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    More about this item

    Keywords

    Portfolio management; cardinality; expected utility maximization; CRRA preferences; derivative-free optimization; PSI20 index.;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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