
This paper uses monthly data from 1984:M10 to 2012:M8 to show that oil‐sensitive stock price indices, particularly those in the energy sector, have strong power in predicting nominal and real crude oil prices at short horizons (1‐month‐ahead predictions), using both in‐ and out‐of‐sample tests. In particular, the forecasts based on oil‐sensitive stock price indices are able to outperform significantly the no‐change forecasts. For example, using the NYSE Arca (AMEX) oil index as a predictor, the 1‐month‐ahead forecasts for nominal crude oil prices reduce the mean squared prediction error by between 22% (for the West Texas Intermediate oil price) and 28% (for the Dubai oil price). Moreover, we find that the directional forecast based on the AMEX oil index is significantly better than a 50:50 coin toss. The novelty of this analysis is that it proposes a new and valuable predictor that both reflects timely market information and is readily available for forecasting the spot oil price.(JEL G17, Q43, Q47, C53)
oil-sensitive stock prices; oil prices; out-of-sample prediction, jel: jel:G17, jel: jel:C53, jel: jel:Q43, jel: jel:Q47
oil-sensitive stock prices; oil prices; out-of-sample prediction, jel: jel:G17, jel: jel:C53, jel: jel:Q43, jel: jel:Q47
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 46 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
