This paper shows that oil price changes, measured as short-term futures returns, are a strong predictor of excess stock returns at short horizons. Ours is a leading variable for the business cycle and exhibits low persistence which avoids the fictitious long-horizon predictability associated with other predictors used in the literature. We compare our variable with the most popular predictors in a sample period that includes the recent financial crisis. Our results suggest that oil price changes are the only variable with forecasting power for stock returns. This significant predictive ability is robust against the inclusion of other variables and out-of-sample tests. We also study the cross-section of expected stock returns in a conditional CAPM framework based on oil price shocks. Our model displays high statistical significance and a better fit than all the conditional and unconditional models considered, including the Fama-French three-factor model. From a practical perspective, ours is a high-frequency, observable variable that has the advantage of being readily available to market-timing investors.View full textDownload full textKeywordsCommodity markets, Commodity prices, Financial econometrics, Forecasting applications, Empirical asset pricing JEL Classification E3, E4, E32, E44, G1, G12, Q4, Q43Related var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/14697688.2012.751122
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