Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/210127 
Year of Publication: 
2017
Series/Report no.: 
Working Paper No. 17/2017
Publisher: 
Norges Bank, Oslo
Abstract: 
We decompose the textual data in a daily Norwegian business newspaper into news topics and investigate their predictive and causal role for asset prices. Our three main findings are: (1) a one unit innovation in the news topics predict roughly a 1 percentage point increase in close-to-open returns and signifcant continuation patterns peaking at 4 percentage points after 15 business days, with little sign of reversal; (2) simple zero-cost news-based investment strategies yield signifcant annualized risk-adjusted returns of up to 20 percent; and (3) during a media shortage, due to an exogenous strike, returns for firms particularly exposed to our news measure experience a substantial fall. Our estimates suggest that between 20 to 40 percent of the news topics' predictive power is due to the causal media effect. Together these findings lend strong support for a rational attention view where the media alleviate information frictions and disseminate fundamental information to a large population of investors.
Subjects: 
stock returns
news
machine learning
latent dirichlet allocation
LDA
JEL: 
C5
C8
G4
G12
Persistent Identifier of the first edition: 
ISBN: 
978-82-7553-999-9
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Working Paper
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