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Noureddine Kouaissah and Amin Hocine
''Robust drawdown-based performance measures''
( 2022, Vol. 42 No.2 )
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.
Keywords: Portfolio selection; robust portfolio optimization; drawdown-based performance measures
JEL: G1 - General Financial Markets
C1 - Econometric and Statistical Methods: General
Manuscript Received : Mar 04 2021 Manuscript Accepted : Jun 30 2022

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