Journal
SWARM AND EVOLUTIONARY COMPUTATION
Volume 39, Issue -, Pages 36-52Publisher
ELSEVIER
DOI: 10.1016/j.swevo.2018.01.009
Keywords
Artificial bee colony; Metaheuristics; Particle swarm optimization; Portfolio optimization; Swann intelligence
Funding
- Scientific and Technological Research Council of Turkey (TUBITAK) [214M224]
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In portfolio optimization (PO), often, a risk measure is an objective to be minimized or an efficient frontier representing the best tradeoff between return and risk is sought. In order to overcome computational difficulties of this NP-hard problem, a growing number of researchers have adopted swarm intelligence (SI) methodologies to deal with PO. The main PO models are summarized, and the suggested SI methodologies are analyzed in depth by conducting a survey from the recent published literature. Hence, this study provides a review of the SI contributions to PO literature and identifies areas of opportunity for future research.
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