Comparative studies of stochastic portfolio construction models with geometric average rate of return

Sejoon Park, Shiwoo Lee, Tao Yao

Research output: Contribution to conferencePaperpeer-review

Abstract

Every investment has the return and the risk. The portfolio needs to be determined to maximize the return and to minimize the risk. This paper compares two stochastic linear programming models to construct investment portfolio; mean-lower semiabsolute deviation (LSAD) model and Conditional Value-at-Risk (CVaR) constraint model. As a performance measure for investment decision when scenarios for only a single period are known, geometric average rate of return (GARR) is proposed. The comparative studies show that GARR is a good risk-adjusted rate of return for single-period investment problems.

Original languageEnglish (US)
Pages1504-1509
Number of pages6
StatePublished - Dec 1 2008
EventIIE Annual Conference and Expo 2008 - Vancouver, BC, Canada
Duration: May 17 2008May 21 2008

Other

OtherIIE Annual Conference and Expo 2008
CountryCanada
CityVancouver, BC
Period5/17/085/21/08

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software
  • Industrial and Manufacturing Engineering

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