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U.S. industry-level returns and oil prices

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  • Fan, Qinbin
  • Jahan-Parvar, Mohammad R.

Abstract

This paper empirically investigates and provides further support for the oil price effect documented in Driesprong et al. (2008) in the U.S. industry-level returns. We find that oil price predictability is concentrated in a relatively small number of industry-level returns, the relevant measure for a study of the oil effect is percentage change in oil spot prices, and changes in oil futures prices have virtually no prediction power for industry-level returns. With percentage changes in oil spot prices as the predictor, approximately one fifth of industry returns are oil-predictable. We detect a two trading weeks delay in reaction to oil price changes which is consistent with the Hong and Stein (1996) underreaction hypothesis. These results are robust to various alternative specifications, and are shown to be unrelated to time-varying risk premia. Moreover, we demonstrate that trading strategies based on the oil effect generate superior gains in comparison with buy-and-hold strategy in the presence of reasonable trading costs.

Suggested Citation

  • Fan, Qinbin & Jahan-Parvar, Mohammad R., 2012. "U.S. industry-level returns and oil prices," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 112-128.
  • Handle: RePEc:eee:reveco:v:22:y:2012:i:1:p:112-128 DOI: 10.1016/j.iref.2011.09.004
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    Cited by:

    1. Magnus Abeng, 2016. "Analysis of the Effect of Oil Price Shock on Industry Stock Returns in Nigeria," EcoMod2016 9285, EcoMod.
    2. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Links Between Commodity Futures And Stock Market: Diversification Benefits, Financialization And Financial Crises," MPRA Paper 59727, University Library of Munich, Germany.
    3. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Oil price and stock returns of consumers and producers of crude oil," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 245-262.
    4. Zhang, Chuanguo & Chen, Xiaoqing, 2014. "The impact of global oil price shocks on China’s bulk commodity markets and fundamental industries," Energy Policy, Elsevier, vol. 66(C), pages 32-41.
    5. Berna Aydogan & Istemi Berk, 2015. "Crude Oil Price Shocks and Stock Returns: Evidences from Turkish Stock Market under Global Liquidity Conditions," International Journal of Energy Economics and Policy, Econjournals, pages 54-68.
    6. Saleh Mothana Obadi & Matej Korcek, 2015. "Investigation of Driving Forces of Energy Consumption in European Union 28 Countries," International Journal of Energy Economics and Policy, Econjournals, pages 422-432.
    7. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2016. "Can commodity returns forecast Canadian sector stock returns?," International Review of Economics & Finance, Elsevier, pages 172-188.
    8. Chortareas, Georgios & Noikokyris, Emmanouil, 2014. "Oil shocks, stock market prices, and the U.S. dividend yield decomposition," International Review of Economics & Finance, Elsevier, pages 639-649.
    9. Salisu, Afees A. & Oloko, Tirimisiyu F., 2015. "Modeling oil price–US stock nexus: A VARMA–BEKK–AGARCH approach," Energy Economics, Elsevier, pages 1-12.
    10. Tsai, Chun-Li, 2015. "How do U.S. stock returns respond differently to oil price shocks pre-crisis, within the financial crisis, and post-crisis?," Energy Economics, Elsevier, pages 47-62.
    11. repec:eee:jbfina:v:79:y:2017:i:c:p:129-141 is not listed on IDEAS

    More about this item

    Keywords

    Industry-level returns; Market efficiency; Oil prices; Return predictability; Underreaction;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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