Naslov
Cardinality Constrained Portfolio Optimization by Means of Genetic Algorithms

Autori
Martinjak, Ivica

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of 20th International Central European Conference on Information and Intelligent Systems / Aurer, Boris ; Bača, Miroslav ; Rabuzin, Kornelije - Varaždin : Fakultet organizacije i informatike Sveučilišta u Zagrebu, 2009, 225-231

Skup
Central European Conference on Information and Intelligent Systems

Mjesto i datum
Varaždin, Hrvatska, 23.09.2009. - 25.09.2009

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
portfolio optimization; rational investor; efficient frontier; heuristic algorithm; genetic algorithm

Sažetak
When applying the standard Markowitz mean-variance model on a real portfolio selection problem, we are faced with certain limitations like cardinality of chosen assets, discrete nature of trading variables etc. While the classical mean-variance model can be successfully solved by standard algorithms (quadratic programming), modelling an actual investment leads to NP-hard optimization problem. In such circumstances heuristic methods appear as the only way out. This paper aims at finding efficient evolutionary inspired algorithm for cardinality constrained portfolio optimization. Among developed algorithms which were able to solve problems with very many possible assets, the algorithm with hybrid crossover presents itself as the most effective. In order to make obtained results comparable, test sample was chosen from databases that serve as a benchmark for this problem class.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo, Ekonomija

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