How News and Its Context Drive Risk and Returns around the World

83 Pages Posted: 20 Jan 2020 Last revised: 4 Sep 2018

See all articles by Charles W. Calomiris

Charles W. Calomiris

Columbia University - Columbia Business School; National Bureau of Economic Research (NBER)

Harry Mamaysky

Columbia University - Columbia Business School

Multiple version iconThere are 2 versions of this paper

Date Written: March 1, 2018

Abstract

We develop a classification methodology for the context and content of news articles to predict risk and return in stock markets in 51 developed and emerging economies. A parsimonious summary of news, including topic-specific sentiment, frequency, and unusualness (entropy) of word flow, predicts future country-level returns, volatilities, and drawdowns. Economic and statistical significance are high and larger for year-ahead than monthly predictions. The effect of news measures on market outcomes differs by country type and over time. News stories about emerging markets contain more incremental information. Out-of-sample testing confirms the economic value of our approach for forecasting country-level market outcomes.

Keywords: Empirical Asset Pricing, International Markets, Financial News Media, Natural Language Processing

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JEL Classification: G12, G15, G17

Suggested Citation

Calomiris, Charles W. and Mamaysky, Harry, How News and Its Context Drive Risk and Returns around the World (March 1, 2018). Columbia Business School Research Paper No. 17-40, Available at SSRN: https://ssrn.com/abstract=2944826 or http://dx.doi.org/10.2139/ssrn.2944826

Charles W. Calomiris

Columbia University - Columbia Business School ( email )

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National Bureau of Economic Research (NBER)

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Harry Mamaysky (Contact Author)

Columbia University - Columbia Business School ( email )

3022 Broadway
New York, NY 10027
United States

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