Social media has been playing an increasingly important role for individuals to share their own opinions on many financial issues including credit risk in the investment decision. This paper analyzes whether these opinions transmitted through social media can accurately predict enterprises' future credit risk. We consider financial statements oriented evaluation results based on logit method as the benchmark. And we then conduct textual analysis to retrieve both posts and their corresponding commentaries published on two most popular social media platforms of financial investors in China. The 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.
The determination of the default point is the key to applying the KMV model. In the traditional research, the default point is equal to the sum of short term debt and half of the long term debt empirically based on the credit data of American companies. But whether it is fit for the Chinese companies and whether it is sensitive to industries depend on further research. This paper amends the parameters of default point. Further the paper also analyzes the applicability of amended KMV model in different industries based on the data of Chinese listed companies.
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