A Bibliometric Analysis of Possibilistic Portfolio Selection Models

Abstract

Possibility theory is one of the most used uncertainty theories in decision-making. This study aims to examine possibilistic portfolio selection models. In this context, we perform their bibliometric analysis with the Web of Science (WOS) data, using the Bibliometrix, without limiting the timespan. We get many results by analyzing the data of 303 documents, of which timespan is from 1995 to 2023. We see that W. G. Zhang is the most influential author in this field. The paper introducing the possibilistic mean-variance (MV) model is the most influential document in this field. The paper introducing Markowitz’s MV model is the most influential reference. China is the most productive country in this field, whereas The South China University of Technology is the most productive institution in this field. Fuzzy Sets and Systems is the most influential journal in this field. Variance originated from Markowitz’s MV model is the most critical keyword plus in this field. It has also maintained its trend topic position for a long time. To the best of our knowledge, this is the first paper making a bibliometric analysis of possibilistic portfolio selection models.