Abstract
The main propose of this study is to build a more powerful earning prediction model by incorporating risk information disclosed in the textual portion of financial reports. We adopt the single-index model developed by Weiss, Naik and Tsai as a foundation. However, other than the traditionally used numeric financial information, our model adds textual information about risk sentiment contained in financial reports. We believe such a model can reduce specification errors resulting from pre-assuming linear relationship, thus can predict future earnings more accurately. The empirical results show that the modified model does significantly improve the accuracy of earning prediction.
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Chen, KT., Chen, TJ., Yen, JC. (2009). Predicting Future Earnings Change Using Numeric and Textual Information in Financial Reports. In: Chen, H., Yang, C.C., Chau, M., Li, SH. (eds) Intelligence and Security Informatics. PAISI 2009. Lecture Notes in Computer Science, vol 5477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01393-5_7
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DOI: https://doi.org/10.1007/978-3-642-01393-5_7
Publisher Name: Springer, Berlin, Heidelberg
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