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Possibilistic data analysis and its application to portfolio selection problems

Peijun Guo, Hideo Tanaka. Osaka Prefecture University

Abstract

In this paper, possibility distributions are identified from the given data and associated possibility grades for reflecting some specific knowledge. This method is used to obtain upper and lower possibility distributions from the given security data to reflect two extreme opinions in portfolio selection problems. Portfolio selection problems based on upper and lower possibility distributions are formalized as quadratic programming problems. Portfolios for compromising two extreme opinions from upper and lower possibility distributions and balancing the opinions of a group of experts can be obtained by quadratic optimization problems, respectively.

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