# Portfolio Selection with Possibilistic Kurtosis

Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 125)

## Abstract

This paper proposes a new approach for modeling multiple objective portfolio selection problem by applying weighted possibilistic moments of trapezoidal fuzzy numbers. The proposed model allows the decision-maker to select the suitable portfolio taking into account the impreciseness to the market scenarios. Here, the objectives are to (i) maximize the expected portfolio return, (ii) minimize the portfolio variance, (iii) maximize the portfolio skewness, and (iv) minimize the portfolio kurtosis for the risky investor. The proposed model has been solved by Zimmermann’s fuzzy goal programming technique. The model is illustrated by a numerical example using data extracted from the Bombay Stock Exchange.

## Keywords

Fuzzy portfolio selection Possibilistic measures Mean Variance Skewness Kurtosis Zimmerman’s fuzzy goal programming

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