Solving cardinality constrained portfolio optimization problem by binary particle swarm optimization algorithm

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F11%3A86080501" target="_blank" >RIV/61989100:27510/11:86080501 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Solving cardinality constrained portfolio optimization problem by binary particle swarm optimization algorithm
Original language description
Mathematical programming methods dominate in the portfolio optimization problems, but they cannot be used if we introduce a constraint limiting the number of different assets included in the portfolio. To solve this model some of the heuristics methods (such as genetic algorithm, neural networks and particle swarm optimization algorithm) must be used. In this paper we utilize binary particle swarm optimization algorithm and quadratic programming method to find an efficient frontier in portfolio optimization problem. Two datasets are utilized. First dataset consists of the stocks incorporated in the Dow Jones Industrial Average, second dataset contains stocks from the Standard and Poor's 500. The comparison of found efficient frontiers for different limitation on the number of stock held is made at the close of the paper.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AH - Economics
OECD FORD branch
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Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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