Can news predict firm bankruptcy? 

44 Pages Posted:

See all articles by Siyu Bie

Siyu Bie

City University of Hong Kong (CityU)

Guanhao Feng

City University of Hong Kong (CityU)

Naixin GUO

City University of Hong Kong (CityU)

Jingyu He

City University of Hong Kong (CityU)

Date Written: November 15, 2024

Abstract

This paper investigates whether rapidly changing business news can predict firm bankruptcy. Using the Dow Jones Newswire database (Wall Street Journal), we create U.S. firm bankruptcy-related news-based variables using ChatGPT and compare their predictive performance with FinBERT and dictionary-based models from 1998 to 2023. ChatGPT-generated variables consistently outperform alternatives, with sentiment scores showing strong predictive power for short-and long-term bankruptcy. Leveraging the full text of news articles significantly improves prediction accuracy compared to using headlines alone. Even after controlling for traditional financial predictors, news data provides incremental value, highlighting the superior capabilities of large language models in bankruptcy prediction.

Keywords: Bankruptcy, ChatGPT, Generative AI, News Data, Sentiment JEL Classification: C53, G11, G17, G33

Suggested Citation

Bie, Siyu and Feng, Guanhao and GUO, Naixin and He, Jingyu, Can news predict firm bankruptcy?  (November 15, 2024). Available at SSRN: https://ssrn.com/abstract=

Siyu Bie

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Kowloon
Hong Kong

Guanhao Feng

City University of Hong Kong (CityU) ( email )

Hong Kong

Naixin GUO

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Kowloon
Hong Kong

Jingyu He (Contact Author)

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Hong Kong
Hong Kong

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
17
Abstract Views
82
PlumX Metrics