BERT人工智能模型能识别管理层语调中的机会主义吗?OA北大核心CHSSCDCSSCICSTPCD

Previous studies find that the management of listed companies has the phenomenon of"opportunism"by manipulating the positive tone of the annual report to cover up adverse information and mislead investors into making investment decisions.Based on the sample of the"Management Discussion and Analysis"(MD&A)section from annual reports of China's A-share listed companies from 2007 to 2022,this paper explores the effectiveness of the BERT artificial intelligence model in identifying the opportunistic tendency in management tone.The study finds that the positive degree of management intonation measured by the BERT model can identify the management opportunistic tendency and predict management opportunistic behavior in the following year,and its identification effectiveness outperforms the traditional bag-of-words method.The difference in identification effectiveness becomes more pronounced as the degree to which the tone of annual report texts can be manipulated increases.Further research shows that the BERT model can more accurately predict companies'future performance and stock price crash risk.This paper introduces the BERT model into the field of financial text sentiment analysis,which provides a new approach to measure the tone of the MD&A section.The conclusion of this paper further improves the signaling theory,which not only helps report users to conduct sentiment analysis on complex texts such as annual reports of listed companies,reducing the mispricing caused by management text manipulation,but also provides evidence for regulatory authorities to identify the management opportunistic tendency through the tone of annual reports and to use large artificial intelligence models to support digital and intelligent regulation.