An MCDM approach to portfolio optimization
European Journal of Operational ResearchPublished 25 March 2003
Matthias Ehrgott, Kathrin Klamroth, Christian Schwehm
Citations315
SJR quartileQ1
SJR score2.24
SNIP2.62
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TL;DR
Numerical results using customized local search, simulated annealing, tabu search and genetic algorithm heuristics show that problems of practically relevant size can be solved quickly.
Abstract
We propose a model for portfolio optimization extending the Markowitz mean–variance model. Based on cooperation with Standard and Poor's we use five specific objectives related to risk and return and allow consideration of individual preferences through the construction of decision-maker specific utility functions and an additive global utility function. Numerical results using customized local search, simulated annealing, tabu search and genetic algorithm heuristics show that problems of practically relevant size can be solved quickly.
Keywords
Decision SciencesEngineering
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