A model for portfolio selection with order of expected returns
This paper proposes a new model for portfolio selection in which the expected returns of securities are considered as variables rather than as the arithmetic means of securities. A genetic algorithm is designed to solve the optimization problem which is difficult to solve with the existing traditional algorithms due to its nonconcavity and special structure. We illustrate the new model by a numerical example and compare the results with those derived from the traditional model of Markowitz. Scope and purpose Portfolio selection, originally articulated by Markowitz, has been one of the most important research fields in modern finance. Several new models and extensions such as the inclusion of transaction costs and taxes have been proposed to improve the performance of portfolio investment. All those models and extensions have advantages and disadvantages in both theory and practical applications. The purpose of this paper is to describe the return and risk of a portfolio more accurately. On the basis of an order of expected returns of securities, we propose a new model for portfolio selection. (C) 2000 Elsevier Science Ltd. All rights reserved.
genetic algorithm portfolio optimization bi-objective programming