Differential Evolution for Multiobjective Portfolio Optimization
Thiemo Krink () and
Sandra Paterlini
Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) from Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi"
Abstract:
Financial portfolio optimization is a challenging problem. First, the problem is multiobjective (i.e.: minimize risk and maximize profit) and the objective functions are often multimodal and non smooth (e.g.: value at risk). Second, managers have often to face real-world constraints, which are typically non-linear. Hence, conventional optimization techniques, such as quadratic programming, cannot be used. Stochastic search heuristic can be an attractive alternative. In this paper, we propose a new multiobjective algorithm for portfolio optimization: DEMPO - Differential Evolution for Multiobjective Portfolio Optimization. The main advantage of this new algorithm is its generality, i.e., the ability to tackle a portfolio optimization task as it is, without simplifications. Our empirical results show the capability of our approach of obtaining highly accurate results in very reasonable runtime, in comparison with quadratic programming and another state-of-art search heuristic, the so-called NSGA II.
Keywords: Portfolio optimization; multiobjective; real world constraints; value at risk; expected shortfall; differential evolution (search for similar items in EconPapers)
JEL-codes: C61 D81 G11 (search for similar items in EconPapers)
Pages: pages 30
Date: 2008-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
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Working Paper: Differential Evolution for Multiobjective Portfolio Optimization (2008) 
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Persistent link: https://EconPapers.repec.org/RePEc:mod:wcefin:0007
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