A maximal predictability portfolio using absolute deviation reformulation

Hiroshi Konno, Yuuhei Morita, Rei Yamamoto

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

This paper shows that a large-scale maximal predictability portfolio (MPP) optimization problem can be solved within a practical amount of computational time using absolute deviation instead of squared deviation in the definition of the coefficient of determination. Also, we will show that MPP portfolio outperforms the mean-absolute deviation portfolio using real asset data in Tokyo Stock Exchange.

Original languageEnglish
Pages (from-to)47-60
Number of pages14
JournalComputational Management Science
Volume7
Issue number1
DOIs
Publication statusPublished - 2010 Jan 1
Externally publishedYes

Fingerprint

Predictability
Deviation
Tokyo Stock Exchange
Portfolio optimization
Optimization problem
Assets
Coefficients

Keywords

  • 0-1 mixed integer programming
  • Absolute deviation
  • Fractional programming
  • Maximal predictability portfolio
  • Portfolio optimization

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems

Cite this

A maximal predictability portfolio using absolute deviation reformulation. / Konno, Hiroshi; Morita, Yuuhei; Yamamoto, Rei.

In: Computational Management Science, Vol. 7, No. 1, 01.01.2010, p. 47-60.

Research output: Contribution to journalArticle

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