Article (Scientific journals)
A robust heuristic for the optimal selection of a portfolio of stocks
Schyns, Michael
2010In International Journal of Operational Research, 9 (3), p. 258-271
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Keywords :
combinatorial optimization; robustness; Markowitz; MCD
Abstract :
[en] This paper introduces a new optimization heuristic for the robustification of critical inputs under consideration in many problems. It is shown that it allows to improve significantly the quality and the stability of the results for two classical financial problems, i.e. the Markowitz' portfolio selection problem and the computation of the financial beta. Focus here is on the robust Minimum Covariance Determinant (MCD) estimator which can easily be substituted to the classical estimators of location and scatter. By definition, the computation of this estimator gives rise to a combinatorial optimization problem. We present a new heuristic, called 'RelaxMCD', which is based on a relaxation of the problem to the continuous space. The utility of this approach and the performance of our heuristic, with respect to other competitors, are illustrated through extensive simulations.
Research center :
QuantOM
Disciplines :
Quantitative methods in economics & management
Author, co-author :
Schyns, Michael ;  Université de Liège - ULiège > HEC - École de gestion de l'ULiège > Informatique de gestion
Language :
English
Title :
A robust heuristic for the optimal selection of a portfolio of stocks
Publication date :
2010
Journal title :
International Journal of Operational Research
ISSN :
1745-7645
eISSN :
1745-7653
Publisher :
InderScience
Volume :
9
Issue :
3
Pages :
258-271
Peer reviewed :
Peer Reviewed verified by ORBi
Commentary :
The original publication is available at www.inderscience.com
Available on ORBi :
since 05 June 2009

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