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Robust drawdown-based performance measures

Author

Listed:
  • Noureddine Kouaissah

    (Excelia Business School, CERIIM, La Rochelle, France)

  • Amin Hocine

    (International University of Rabat, RBS College of Management, BEARLab)

Abstract

In this paper, we propose a robust optimization framework for drawdown-based performance measures that substantially improves upon conventional portfolio choices. In particular, we motivate and develop a robust optimization method that is typically used with conventional robust statistical estimation techniques, directly and explicitly addressing the estimation errors in the portfolio optimization process of the drawdown-based performance measures. Empirical analyses validate the proposed methodologies and confirm that robust drawdown-based performance measures yield better out-of-sample performance than their classic versions.

Suggested Citation

  • Noureddine Kouaissah & Amin Hocine, 2022. "Robust drawdown-based performance measures," Economics Bulletin, AccessEcon, vol. 42(2), pages 513-522.
  • Handle: RePEc:ebl:ecbull:eb-21-00212
    as

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    References listed on IDEAS

    as
    1. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    2. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Portfolio selection; robust portfolio optimization; drawdown-based performance measures;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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