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

• 成果类型: Article
• 署名作者: Calomiris, Charles W.; Mamaysky, Harry
• 署名单位: Columbia University; National Bureau of Economic Research; Columbia University
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2018.11.009
• 发表日期: 2019
• 页码: 299-336
• 关键词: Empirical asset pricing; International markets; Financial news media; Natural Language Processing

摘要

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. (C) 2019 Elsevier B.V. All rights reserved.