AN INTEGRATED DECISION SUPPORT SYSTEM FOR STOCK INVESTMENT BASED ON SPHERICAL FUZZY PT-EDAS METHOD AND MEREC

Author:

Zhang Huiyuan1,Wang Hongjun2,Wei Guiwu3,Chen Xudong4

Affiliation:

1. School of Mathematics and Statistics, Liupanshui Normal University, iupanshui 553004, People’s Republic of China; School of Mathematical Sciences, Sichuan Normal University, Chengdu 610101, People’s Republic of China

2. School of Economics and Management, Chongqing University of Arts and Sciences, Chongqing 402160, People’s Republic of China

3. School of Mathematical Sciences, Sichuan Normal University, Chengdu 610101, People’s Republic of China; School of Business, Sichuan Normal University, Chengdu 610101, People’s Republic of China

4. School of Accounting, Southwestern University of Finance and Economics, Chengdu 610074, People’s Republic of China

Abstract

The stock investment selection could be deemed as a classic multiple attribute group decision making (MAGDM) problem involving multiple conflicts and interleaved qualitative and quantitative attributes. Spherical fuzzy sets (SFSs) can excavate the potential vagueness and intricacy in MAGDM more effectively and deeply. This article we propose an integrated decision support system (IDSS) based on SFSs, prospect theory (PT), distance from average solution (EDAS) method and the MEthod based on the Removal Effects of Criteria (MEREC). The proposed IDSS, called SF-PT-EDAS-MEREC model, uses SFSs to describe the uncertain and obscure assessment information of DMs. The combination of PT and EDAS (PT-EDAS) method adequately captures DMs’ psychological behavior characteristics to execute more reasonable alternative evaluation. The MEREC is utilized to efficaciously obtain unknown attribute weights. In addition, this paper also presents a novel score function to compare spherical fuzzy numbers (SFNs) more directly and efficiently. Eventually, in order to illustrate the practicability of the proposed IDSS, two numerical examples of stock investment selection are employed to achieve this. Meanwhile, the comparative study with existing approach further demonstrates the effectiveness and superiority of SF-PT-EDAS-MEREC model.

Publisher

Vilnius Gediminas Technical University

Subject

Finance

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