Abstract
Article history: Received 31 January 2010 Received in revised form 28 March 2010 Accepted 1 May 2010 Available online 7 May 2010 Portfolio selection is one of the important problems encountered by any investor. The purpose of this paper is to solve a real stock portfolio selection problem in Iran. According to the uncertain environments in which financial decisions are made, most of the recent works in this field use fuzzy sets theory in order to incorporate these uncertainties into their analysis. The problem is to determine how to allocate a limited fund among the stocks of some pharmaceutical companies in Tehran stock exchange. For this purpose we apply two fuzzy analytic hierarchy process (FAHP) methods to this problem. Finally, the results obtained from the two methods are compared in terms of the solution quality. © 2011 Growing Science Ltd. All rights reserved.
Highlights
In multiple criteria decision making (MCDM) problems, a decision maker (DM) often needs to select or rank alternatives associated with some usually conflicting attributes or objectives
Fuzzy set theory is a powerful tool used to describe an uncertain environment with ambiguity, vagueness or some other type of fuzziness, which appears in many aspects of financial markets, such as the unpredictable behavior of financial managers (Wang & Zhu, 2002)
To evaluate a crisp weight for each stock, one can use the defuzzification method to replace the fuzzy numbers by crisp numbers
Summary
In multiple criteria decision making (MCDM) problems, a decision maker (DM) often needs to select or rank alternatives associated with some usually conflicting attributes or objectives. Based on the worst regret to the portfolio selection, Inuiguchi and Tanino (2000) proposed a new possibilistic programming approach for portfolio optimization, considering how a model yields a distributive investment solution. Tiryaki and Ahlatcioglu (2009) used the two constrained fuzzy AHP methods, developed by Enea and Piazza (2004), to the problem of portfolio selection in Istanbul stock exchange. They addressed some fallacies in the first model of Enea and Piazza and corrected it. The idea behind their method 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 consolidate the
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