Abstract.
One of the main advantages of portfolios over single assets is that risk can be diversified without necessarily reducing the expected return - provided "proper" assets are selected and they are assigned the "proper" weights. Since in practice investors tend to restrict themselves to a rather small number of different assets, the decision which securities to include is a crucial one that turns out to be NP-hard.
In this paper we suggest a hybrid local search algorithm which combines principles of Simulated Annealing and evolutionary strategies and which proved to highly efficiently approach this problem.
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Correspondence to: Dietmar Maringer
The authors would like to thank participants of the 4th Metaheuristics International Conference and the Econometrics Research Seminar at the University of Geneva, U. Derigs, M. Gilli, H.-O. Günther, and two anonymous referees for valuable comments on earlier versions of this paper.
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Maringer, D., Kellerer, H. Optimization of cardinality constrained portfolios with a hybrid local search algorithm. OR Spectrum 25, 481–495 (2003). https://doi.org/10.1007/s00291-003-0139-1
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DOI: https://doi.org/10.1007/s00291-003-0139-1