Abstract
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.
Original language | English |
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Pages (from-to) | 430-444 |
Number of pages | 15 |
Journal | Energy Economics |
Volume | 83 |
DOIs | |
Publication status | Published - Sept 2019 |
Externally published | Yes |
Keywords
- Oil price news
- Predictive regression
- Stock returns
- Time-series