A MAXIMAL PREDICTABILITY PORTFOLIO USING DYNAMIC FACTOR SELECTION STRATEGY

Hiroshi Konno, Yoshihiro Takaya and Rei Yamamoto ()
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Hiroshi Konno: Department of Industrial and Systems Engineering, Chuo University, Japan
Yoshihiro Takaya: Department of Industrial and Systems Engineering, Chuo University, Japan
Rei Yamamoto: Department of Industrial and Systems Engineering, Chuo University, Japan;

International Journal of Theoretical and Applied Finance (IJTAF), 2010, vol. 13, issue 03, 355-366

Abstract: In this paper, we will propose a practical method for improving the performance of a maximal predictability portfolio (MPP) model proposed by Lo and MacKinlay and later extended by the authors. We will employ an alternative version of MPP using absolute deviation instead of variance as a measure of fitting and apply a dynamic strategy for choosing the set of factors which fits best to the market data. It will be shown that this approach leads to a significantly better performance than the standard MPP and the index.

Keywords: Maximal predictability portfolio; factor model; nonconvex minimization problem; fractional programming; absolute deviation; 0–1 integer programming (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (3)

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DOI: 10.1142/S0219024910005802

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