Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/244260 
Erscheinungsjahr: 
2020
Schriftenreihe/Nr.: 
ESRB Working Paper Series No. 108
Verlag: 
European Systemic Risk Board (ESRB), European System of Financial Supervision, Frankfurt a. M.
Zusammenfassung: 
We show that the news is a rich source of data on distressed firm links that drive firm- level and aggregate risks. The news tends to report about links in which a less popular firm is distressed and may contaminate a more popular firm. This constitutes a contagion channel that yields predictable returns and downgrades. Shocks to the degree of news-implied firm connectivity predict increases in aggregate volatilities, credit spreads, and default rates, and declines in output. To obtain our results, we propose a machine learning methodology that takes text data as input and outputs a data-implied firm network.
Schlagwörter: 
Networks
contagion
predictability
risk measurement
machine learning
natural language processing
JEL: 
E32
E44
L11
G10
C82
Persistent Identifier der Erstveröffentlichung: 
ISBN: 
978-92-9472-129-7
Dokumentart: 
Working Paper

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