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How news and its context drive risk and returns around the world

Charles W. Calomiris and Harry Mamaysky

Journal of Financial Economics, 2019, vol. 133, issue 2, 299-336

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 (search for similar items in EconPapers)
JEL-codes: G12 G15 G17 (search for similar items in EconPapers)
Date: 2019
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