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Goal programming with extended factors for portfolio selection
Author(s) -
Tamiz Mehrdad,
Azmi Rania A.
Publication year - 2019
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12423
Subject(s) - portfolio , decision maker , selection (genetic algorithm) , goal programming , portfolio optimization , computer science , modern portfolio theory , project portfolio management , operations research , econometrics , actuarial science , mathematical optimization , economics , mathematics , machine learning , financial economics , project management , management
This paper proposes and examines the use of several stock‐related factors, called extended factors, for portfolio selection. These factors, including the traditional factors of risk and return, are represented as objectives in weighted goal programming (WGP) models. Several WGP models with passive and active target values and various weights for their unwanted deviational variables in their achievement functions have been developed. The weights and target values of the extended factors represent decision makers’ utility toward their portfolio. The resulting portfolios for the proposed models are compared against each other as well as against the Dow Jones Industrial Average index and portfolios obtained from the well‐established Markowitz and Konno and Yamazaki's models. The experimental results strongly support the use of extended factors for portfolio selection problems and the assumption of meeting decision maker's preferences and utilities better than the portfolios based entirely on risk and return.