 Forecasting the Equity Premium: Mind the News!*Philipp Adämmer and Rainer A Schüssler Review of Finance, 2020, vol. 24, issue 6, 1313-1355 Abstract: We introduce a novel strategy to predict monthly equity premia that is based on extracted news from more than 700,000 newspaper articles, which were published in The New York Times and Washington Post between 1980 and 2018. We propose a flexible data-adaptive switching approach to map a large set of different news-topics into forecasts of aggregate stock returns. The information that is embedded in our extracted news is not captured by established economic predictors. Compared with the prevailing historical mean between 1999 and 2018, we find large out-of-sample (OOS) gains with an ROOS2 of 6.52% and sizeable utility gains for a mean–variance investor. The empirical results indicate that geopolitical news are at times more valuable than economic news to predict the equity premium and we also find that forecasting gains arise in down markets. Keywords: Topic modeling; Big data; Return predictability; Text as data (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:oup:revfin:v:24:y:2020:i:6:p:1313-1355. Ordering information: This journal article can be ordered from Access Statistics for this article Review of Finance is currently edited by Marcin Kacperczyk More articles in Review of Finance from European Finance Association Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC. |
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