The Impact of Annual Report Readability on the Risk of Stock Price Collapse of KSE Companies

• 1、Business School, Ningbo University, Ningbo 315211

Abstract：Based on the Python 3.10, the tool jieba is used to slice and dice the annual report text of the 2019-2020 annual reports of KCI listed companies, so as to empirically test the impact of annual report readability (including information size and professional difficulty) on the stock price crash risk. The study finds that: firstly, the longer the length of the annual reports of KCI companies, the higher the risk of stock price collapse; secondly, the higher the density of accounting audit words in the annual reports of KCI companies, the lower the risk of stock price collapse; thirdly, the longer the length of the annual reports of KCI companies audited by non-Big 4 companies, the higher the risk of stock price collapse; fourthly, the longer the length of the annual reports of KCI companies audited by international Big 4 companies, the higher the risk of stock price collapse. Fourthly, the higher the density of audit terms in the annual reports of KCI companies audited by international "Big Four", the lower the risk of stock price collapse.

Keywords： machine learning annual report readability stock price collapse risk KSE