Investor sentiment index based on intuitionistic fuzzy analytic network process method and empirical analysis¹

Article type: Research Article

Authors: Zhou, Xiaoguang^*; | Cui, Yadi | He, Qin

Affiliations: Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing, China

Correspondence: [*] Corresponding author. Xiaoguang Zhou, E-mail: [email protected].

Note: [1] This work was supported by the National Natural Science Foundation of China (No. 71771023).

Abstract: This paper presents a network index system for assessing investor sentiment. The proposed comprehensive investor sentiment index is based on intuitionistic fuzzy analytic network process (IFANP) and regression model, and is compared with a sentiment index constructed on the basis of principal component analysis (PCA). The long-term relationship and dynamic relationship between the yields of these investor sentiment indexes and the Shanghai Composite Index (SHCI) are explored. Based on autoregressive moving average models and cointegration models, short-term and medium-term forecasts of the yields of investor sentiment index and SHCI are derived. The results of cointegration test, short-term forecasting and medium-term forecasting all show that the investor sentiment index based on IFANP is superior to that based on PCA.

Keywords: Intuitionistic fuzzy set, intuitionistic fuzzy analytic network process, principal component analysis, investor sentiment

DOI: 10.3233/JIFS-190318

Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 19-34, 2020