title: Credit risk evaluation based on social media.
abstract: Social media has been playing an increasingly important role in the sharing of individuals' opinions on many financial issues, including credit risk in investment decisions. This paper analyzes whether these opinions, which are transmitted through social media, can accurately predict enterprises' future credit risk. We consider financial statements oriented evaluation results based on logit and probit approaches as the benchmarks. We then conduct textual analysis to retrieve both posts and their corresponding commentaries published on two of the most popular social media platforms for financial investors in China. Professional advice from financial analysts is also investigated in this paper. We surprisingly find that the opinions extracted from both posts and commentaries surpass opinions of analysts in terms of credit risk prediction.
authors.affiliation: University of Electronic Science and Technology of China, Chengdu, 611731, China; University of Delaware, Newark, DE 19716, USA.
authors.forename: Yang
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Sichuan University, Chengdu 610065, China. Electronic address: gj0901@scu.edu.cn.
authors.forename: Jing
authors.initials: J
authors.lastname: Gu
authors.affiliation: University of Electronic Science and Technology of China, Chengdu, 611731, China.
authors.forename: Zongfang
authors.initials: Z
authors.lastname: Zhou
mesh_terms: D002681:China; D006801:Humans; D007449:Investments; D000067074:Peer Influence; D012306:Risk; D061108:Social Media
keywords: Credit risk; Logit; Probit; Social media; Textual analysis