Foreseeing bankruptcy: A novel perspective based on the uncertainty of text-based communicative value of annual reports

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters Pub Date : 2025-06-15 DOI:10.1016/j.frl.2025.107771

Tsung-Kang Chen , Yun Hao , Ting-Ru Chang , Yu-Chun Lin

引用次数: 0

Abstract

We examine whether incorporating the uncertainty of text-based communicative value (U_TCV) in annual reports enhances bankruptcy prediction models under machine learning settings using U.S. firm data from 1996 to 2018. Our findings show that U_TCV variables significantly improve prediction effectiveness beyond Barboza et al.’s (2017) financial variables and Chen et al.’s (2023) text-based communicative value (TCV) variables. Notably, U_TCV variables have greater enhancement on medium- to long-term predictions, contribute to explaining bankruptcy risk term structure, significantly reducing Type I error (misjudging bankrupt firms as non-bankrupt) while maintaining a low Type II error, and complementing the predictive power of TCV variables.

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预见破产：基于年报文本传播价值不确定性的新视角

我们使用1996年至2018年的美国公司数据，研究了在年度报告中纳入基于文本的沟通价值（U_TCV）的不确定性是否增强了机器学习设置下的破产预测模型。我们的研究结果表明，U_TCV变量比Barboza等人（2017）的金融变量和Chen等人（2023）的基于文本的交际价值（TCV）变量显著提高了预测有效性。值得注意的是，U_TCV变量对中长期预测有更大的增强作用，有助于解释破产风险期限结构，显著减少I型误差（将破产企业误认为非破产企业），同时保持较低的II型误差，并补充了TCV变量的预测能力。

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

Finance Research Letters BUSINESS, FINANCE-

CiteScore

11.10

自引率

14.40%

发文量

863

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