Are risk disclosures in financial reports informative? A text mining-based perspective

Xiaoqian Zhu, Jianping Li and Yinghui Wang ()
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Xiaoqian Zhu: University of Chinese Academy of Sciences
Jianping Li: University of Chinese Academy of Sciences
Yinghui Wang: University of Chinese Academy of Sciences

Palgrave Communications, 2024, vol. 11, issue 1, 1-18

Abstract: Abstract This paper studies whether the risk factors disclosed in financial reports are as informative as SEC requires. The subprime crisis is used as a typical real-risk event to test their informativeness by text mining methods. By analyzing the textual attributes and specific contents of the risk disclosures in 14089 Form 10-K statements of 1,685 financial firms from 2006 to 2022, the results show that firms tend to disclose risks in more specific and negative language and significantly reduce stickiness and boilerplate during the subprime crisis. This paper also finds that the changes of risk factors are consistent with the actual risk profile before, during and after the subprime crisis. The failed institutions during the crisis have disclosed more risks related to the subprime crisis using a more negative tone than the survived institutions. These findings all provide evidence that the risk factors in Form 10-K are informative and not invariable boilerplate.

Date: 2024
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DOI: 10.1057/s41599-024-04169-w

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