How News and Its Context Drive Risk and Returns around the World
83 Pages Posted: 20 Jan 2020
Date Written: March 1, 2018
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
JEL Classification: G12, G15, G17
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