A maximal predictability portfolio using dynamic factor selection strategy

Hiroshi Konno, Yoshihiro Takaya, Rei Yamamoto

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)355-366
Number of pages12
JournalInternational Journal of Theoretical and Applied Finance
Volume13
Issue number3
DOIs
Publication statusPublished - 2010 May 1
Externally publishedYes

Fingerprint

Dynamic factor
Predictability
Factors
Deviation
Dynamic strategy
Portfolio model
Market data

Keywords

  • 01 integer programming
  • absolute deviation
  • factor model
  • fractional programming
  • Maximal predictability portfolio
  • nonconvex minimization problem

ASJC Scopus subject areas

  • Finance
  • Economics, Econometrics and Finance(all)

Cite this

A maximal predictability portfolio using dynamic factor selection strategy. / Konno, Hiroshi; Takaya, Yoshihiro; Yamamoto, Rei.

In: International Journal of Theoretical and Applied Finance, Vol. 13, No. 3, 01.05.2010, p. 355-366.

Research output: Contribution to journalArticle

Konno, Hiroshi ; Takaya, Yoshihiro ; Yamamoto, Rei. / A maximal predictability portfolio using dynamic factor selection strategy. In: International Journal of Theoretical and Applied Finance. 2010 ; Vol. 13, No. 3. pp. 355-366.
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