Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/298449 
Year of Publication: 
2022
Series/Report no.: 
Discussion paper No. 156
Publisher: 
Aboa Centre for Economics (ACE), Turku
Abstract: 
Economic research has shown that debt markets have an information sensitivity property that allows these markets to work properly when price discovery is absent and opaqueness is maintained. Dang, Gorton and Holmström (2015) argue that sufficiently 'bad news' can switch debt to become information sensitive and start a financial crisis. We identify narrative triggers in the news by utilizing machine learning methods and daily information about firm default probability, the public's information acquisition and newspaper articles. We find state-specific generalizable triggers whose effect is determined by the language used by journalists. This language is associated with different psychological thinking processes.
Subjects: 
information sensitivity
debt markets
financial crisis
machine learning
news data
primordial thinking process
JEL: 
G01
G14
G41
Document Type: 
Working Paper

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