A reactive greedy randomized adaptive search procedure for a mixed integer portfolio optimization problem

Purpose - The purpose of this paper is to present a procedure for finding the efficient frontier, i.e. a non-decreasing curve representing the set of Pareto-optimal or non-dominated portfolios, when the standard Markowitz' classical mean-variance model is enriched with additional constraints.De...

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Bibliographic Details
Published in:Managerial finance 2010-10, Vol.36 (12), p.1057-1065
Main Authors: Anagnostopoulos, K.P, Chatzoglou, P.D, Katsavounis, S
Format: Article
Language:English
Subjects:
Algorithms
Genetic algorithms
Heuristic
Integer programming
Modelling
Optimization techniques
Pareto optimum
Portfolio investment
Portfolio investments
Studies
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Summary:Purpose - The purpose of this paper is to present a procedure for finding the efficient frontier, i.e. a non-decreasing curve representing the set of Pareto-optimal or non-dominated portfolios, when the standard Markowitz' classical mean-variance model is enriched with additional constraints.Design methodology approach - The mean-variance portfolio optimization model is extended to include integer constraints that limit a portfolio to have a specified number of assets, and to impose limits on the proportion of the portfolio held in a given asset. Optimization-based procedures run into difficulties in this framework and this motivates the investigation of heuristic algorithms to find acceptable solutions.Findings - The problem is solved by a greedy randomized adaptive search procedure (GRASP), enhanced by a learning mechanism and a bias function for determining the next element to be introduced in the solution.Originality value - This is believed to be the first time, a GRASP for finding the efficient frontier for this class of portfolio selection problems is used.
ISSN:0307-4358
1758-7743
DOI:10.1108/03074351011088450