期刊
ENERGY ECONOMICS
卷 83, 期 -, 页码 430-444出版社
ELSEVIER
DOI: 10.1016/j.eneco.2019.07.022
关键词
Oil price news; Stock returns; Predictive regression; Time-series
类别
We hand-collect time-series data on positive and negative oil price news from 100 news sources from around the world, covering 59,129 news articles on oil prices. Using time-series predictive regression models estimated for 45 countries, we show that: (a) positive and negative news predict stock returns for at most 12 countries for which the oil price does not predict returns; and (b) together the three oil price measures predict returns for at most 23/45 countries. Therefore, oil price news turns out to be more powerful in predicting returns in a horserace with oil price. We show that the ability of oil to predict returns is through the discount rate and cash flow channels. Our results survive a battery of robustness tests. (C) 2019 Elsevier B.V. All rights reserved.
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