Do Newspaper Articles Predict Aggregate Stock Returns?
Journal
Journal of Behavioral Finance
ISSN
1542-7560
ISSN-Digital
1542-7579
Type
journal article
Date Issued
2014-09
Author(s)
Abstract
We analyze whether newspaper content can predict aggregate future stock returns. Our study is based on articles published in the Handelsblatt, a leading German Financial newspaper, from July 1989 to March 2011. We summarize newspaper content in a systematic way by constructing word-count indices for a large number of words. Wordcount indices are instantly available and therefore potentially valuable
Financial indicators. Our main Finding is that the predictive power of newspaper content has increased over time, particularly since 2000. We Find that a cluster analysis approach increases the predictive power of newspaper articles substantially. To obtain optimal predictive power, we need at least seven clusters. Our analysis shows that newspaper content is a valuable predictor of future DAX returns in and out of sample.
Financial indicators. Our main Finding is that the predictive power of newspaper content has increased over time, particularly since 2000. We Find that a cluster analysis approach increases the predictive power of newspaper articles substantially. To obtain optimal predictive power, we need at least seven clusters. Our analysis shows that newspaper content is a valuable predictor of future DAX returns in and out of sample.
Language
English
Keywords
Word Count
Text Mining
Expected Returns
Tactical Asset Allocation
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Routledge/Taylor&Francis
Publisher place
New York
Volume
15
Number
3
Start page
195
End page
213
Pages
19
Subject(s)
Eprints ID
216122
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