| Popis: |
The intangible nature of Corporate Social Responsible (CSR) issues has typically hindered financial analysts' abilities to integrate such information into investment models. To address this limitation, we employ a probabilistic topic model known as Latent Dirichlet Allocation (LDA) to infer contextual information and semantic meaning in text. Using a sample of 105,983 CSR articles from newswires, newspapers, blogs and magazines over the period 1980-2014, the model detects CSR allegations based on ethical grounds versus those that attribute corporate difficulties and litigation risk. Our findings indicate a statistically significant and negative correlation between material CSR concerns and firms’ future earnings surprises, and a statistically insignificant correlation for more ethical concerns. |
