Portfolio optimization with an envelope-based multi-objective evolutionary algorithm

Branke, J. ; Scheckenbach, B. ; Stein, M. ; Deb, K. ; Schmeck, H. (2009) Portfolio optimization with an envelope-based multi-objective evolutionary algorithm European Journal of Operational Research, 199 (3). pp. 684-693. ISSN 0377-2217

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Official URL: http://linkinghub.elsevier.com/retrieve/pii/S03772...

Related URL: http://dx.doi.org/10.1016/j.ejor.2008.01.054


The problem of portfolio selection is a standard problem in financial engineering and has received a lot of attention in recent decades. Classical mean-variance portfolio selection aims at simultaneously maximizing the expected return of the portfolio and minimizing portfolio variance. In the case of linear constraints, the problem can be solved efficiently by parametric quadratic programming (i.e., variants of Markowitz' critical line algorithm). However, there are many real-world constraints that lead to a non-convex search space, e.g., cardinality constraints which limit the number of different assets in a portfolio, or minimum buy-in thresholds. As a consequence, the efficient approaches for the convex problem can no longer be applied, and new solutions are needed. In this paper, we propose to integrate an active set algorithm optimized for portfolio selection into a multi-objective evolutionary algorithm (MOEA). The idea is to let the MOEA come up with some convex subsets of the set of all feasible portfolios, solve a critical line algorithm for each subset, and then merge the partial solutions to form the solution of the original non-convex problem. We show that the resulting envelope-based MOEA significantly outperforms existing MOEAs.

Item Type:Article
Source:Copyright of this article belongs to Association of European Operational Research Societies.
Keywords:Portfolio Optimization; Evolutionary Algorithm; Multi-objective
ID Code:9444
Deposited On:02 Nov 2010 12:12
Last Modified:16 May 2016 19:14

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