A MAXIMAL PREDICTABILITY PORTFOLIO MODEL: ALGORITHM AND PERFORMANCE EVALUATION

Rei Yamamoto (), Daisuke Ishii and Hiroshi Konno
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Rei Yamamoto: Department of Industrial and Systems Engineering, Chuo University and Mitsubishi UFJ Trust Investment Technology Institute Co., Ltd., Japan
Daisuke Ishii: Department of Industrial and Systems Engineering, Chuo University, Japan
Hiroshi Konno: Department of Industrial and Systems Engineering, Chuo University, Japan

International Journal of Theoretical and Applied Finance (IJTAF), 2007, vol. 10, issue 06, 1095-1109

Abstract: The purpose of this paper is to show that an algorithm recently proposed by authors can in fact solve a maximal predictability portfolio (MPP) optimization problem, which is a hard nonconvex fractional programming optimization. Also, we will compare MPP with standard mean-variance portfolio (MVP) and show that MPP outperforms MVP and index. We believe that this paper is of interest to researchers and practitioners in the field of portfolio optimization.

Keywords: Portfolio optimization; maximal predictability portfolio; mean-variance portfolio; global optimization; fractional programming; 0-1 integer programming (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (4)

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DOI: 10.1142/S0219024907004561

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