A compact mean-variance-skewness model for large-scale portfolio optimization and its application to the NYSE market

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6 Citations (Scopus)

Abstract

This paper develops a portfolio optimization model that uses the first three moments of the distribution of the rate of return on investment in selecting portfolios. An alternative measure of skewness is designed for the purpose, and, in the grand scheme of compact factorization, the proposed model is transformed to an equivalent quadratic program with a quadratic constraint with 2 T nonlinear variables and terms, where usually T≤50. Extensive computational results are obtained on a real-world dataset of the returns of about 3500 stocks that were traded in the NYSE from 3 January to 17 September 2002. In summary, the portfolios built by the proposed model gave the average return on investment of 66.85% over the course of 150 trading days, a period in time when US economy and stock markets suffered tremendously after the tragic events of September 2001.

Original languageEnglish
Pages (from-to)505-515
Number of pages11
JournalJournal of the Operational Research Society
Volume58
Issue number4
DOIs
Publication statusPublished - 2007 Apr 1

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Factorization
New York Stock Exchange
Skewness
Return on investment
Portfolio optimization
Mean-variance
US economy
Stock market
Optimization model
Rate of return
Financial markets

Keywords

  • Compact factorization
  • Fractional programming
  • Multiobjective
  • NYSE
  • Portfolio optimization
  • Skewness

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Strategy and Management
  • Management Science and Operations Research

Cite this

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abstract = "This paper develops a portfolio optimization model that uses the first three moments of the distribution of the rate of return on investment in selecting portfolios. An alternative measure of skewness is designed for the purpose, and, in the grand scheme of compact factorization, the proposed model is transformed to an equivalent quadratic program with a quadratic constraint with 2 T nonlinear variables and terms, where usually T≤50. Extensive computational results are obtained on a real-world dataset of the returns of about 3500 stocks that were traded in the NYSE from 3 January to 17 September 2002. In summary, the portfolios built by the proposed model gave the average return on investment of 66.85{\%} over the course of 150 trading days, a period in time when US economy and stock markets suffered tremendously after the tragic events of September 2001.",
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AB - This paper develops a portfolio optimization model that uses the first three moments of the distribution of the rate of return on investment in selecting portfolios. An alternative measure of skewness is designed for the purpose, and, in the grand scheme of compact factorization, the proposed model is transformed to an equivalent quadratic program with a quadratic constraint with 2 T nonlinear variables and terms, where usually T≤50. Extensive computational results are obtained on a real-world dataset of the returns of about 3500 stocks that were traded in the NYSE from 3 January to 17 September 2002. In summary, the portfolios built by the proposed model gave the average return on investment of 66.85% over the course of 150 trading days, a period in time when US economy and stock markets suffered tremendously after the tragic events of September 2001.

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