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Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks

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  • Chen, Shiu-Sheng

Abstract

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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Bibliographic Info

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
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Handle: RePEc:pra:mprapa:49240

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Keywords: oil-sensitive stock prices; oil prices; out-of-sample prediction;

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