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Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks

Listed author(s):
  • Chen, Shiu-Sheng

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 (one-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 one-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 the AMEX oil index is ignificantly 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.

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File URL: https://mpra.ub.uni-muenchen.de/49240/1/MPRA_paper_49240.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 49240.

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Date of creation: 22 Aug 2013
Handle: RePEc:pra:mprapa:49240
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