How to Talk When a Machine Is Listening: Corporate Disclosure in the Age of AI

IF 6.8 1区 经济学 Q1 BUSINESS, FINANCE
Sean Cao, Wei Jiang, Baozhong Yang, Alan L Zhang
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引用次数: 2

Abstract

Abstract Growing AI readership (proxied for by machine downloads and ownership by AI-equipped investors) motivates firms to prepare filings friendlier to machine processing and to mitigate linguistic tones that are unfavorably perceived by algorithms. Loughran and McDonald (2011) and BERT available since 2018 serve as event studies supporting attribution of the decrease in the measured negative sentiment to increased machine readership. This relationship is stronger among firms with higher benefits to (e.g., external financing needs) or lower cost (e.g., litigation risk) of sentiment management. This is the first study exploring the feedback effect on corporate disclosure in response to technology. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
机器在倾听时如何说话:人工智能时代的企业信息披露
不断增长的人工智能读者(以机器下载和人工智能投资者的所有权为代表)促使公司准备对机器处理更友好的文件,并减轻算法所感知的不利语言语调。Loughran和McDonald(2011)以及自2018年以来可用的BERT作为事件研究,支持将测量的负面情绪减少归因于机器读者人数的增加。在情绪管理收益较高(如外部融资需求)或成本较低(如诉讼风险)的公司中,这种关系更强。本研究首次探讨科技对企业信息披露的反馈效应。作者们提供了一份互联网附录,可以在牛津大学出版社的网站上找到,就在最终发表论文的链接旁边。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
16.00
自引率
2.40%
发文量
83
期刊介绍: The Review of Financial Studies is a prominent platform that aims to foster and widely distribute noteworthy research in financial economics. With an expansive editorial board, the Review strives to maintain a balance between theoretical and empirical contributions. The primary focus of paper selection is based on the quality and significance of the research to the field of finance, rather than its level of technical complexity. The scope of finance within the Review encompasses its intersection with economics. Sponsoring The Society for Financial Studies, the Review and the Society appoint editors and officers through limited terms.
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