A mean-variance-skewness model: Algorithm and applications

Hiroshi Konno, Rei Yamamoto

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

We will show that a mean-variance-skewness portfolio optimization model, a direct extension of the classical mean-variance model can be solved exactly and fast by using the state-of-the-art integer programming approach. This implies that we can now calculate a portfolio with maximal expected utility for any decreasing risk averse utility function. Also, we will show that this model can be used as a practical tool for constructing a portfolio when the asset returns follow skewed distribution. As an example, we apply this model to construct an index plus alpha portfolio.

Original languageEnglish
Pages (from-to)409-423
Number of pages15
JournalInternational Journal of Theoretical and Applied Finance
Volume8
Issue number4
DOIs
Publication statusPublished - 2005 Jun 1
Externally publishedYes

Fingerprint

Skewness
Mean-variance
Optimization model
Mean-variance model
Asset returns
Skewed distribution
Risk-averse
Portfolio optimization
Expected utility
Utility function
Integer programming

Keywords

  • Efficient frontier
  • Integer programming
  • Mean-variance-skewness
  • Nonconvex minimization
  • Portfolio optimization
  • Third order moment

ASJC Scopus subject areas

  • Finance
  • Economics, Econometrics and Finance(all)

Cite this

A mean-variance-skewness model : Algorithm and applications. / Konno, Hiroshi; Yamamoto, Rei.

In: International Journal of Theoretical and Applied Finance, Vol. 8, No. 4, 01.06.2005, p. 409-423.

Research output: Contribution to journalArticle

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