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Fuzzy portfolio selection using genetic algorithm (Abiyev, Rahib H.,)

Bibliographical information (record 264049)

Fuzzy portfolio selection using genetic algorithm
Author:	Abiyev, Rahib H., Search Author in Amazon Books

Edition:	2007.
Classification:	TJ213

Detailed notes

- This paper presents the development of fuzzy portfolio selection model in investment. Fuzzy logic is utilized in the estimation of expected return and risk. Using fuzzy logic, managers can extract useful information and estimate expected return by using not only statistical data, but also economical and financial behaviors of the companies and their business strategies. In the formulated fuzzy portfolio model, fuzzy set theory provides the possibility of trade-off between risk and return. This is obtained by assigning a satisfaction degree between criteria and constraints. Using the formulated fuzzy portfolio model, a Genetic Algorithm (GA) is applied to find optimal values of risky securities. Numerical examples are given to demonstrate the effectiveness of proposed method. [ABSTRACT FROM AUTHOR] $b Copyright of Soft Computing - A Fusion of Foundations, Methodologies & Applications is the property of Springer Science & Business Media B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)