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US Oil Price Exposure: The Industry Effects

Author

Listed:
  • Don Bredin

    (University College Dublin)

  • John Elder

    (Colorado State University)

Abstract

This paper investigates the exposure of industry level portfolios to oil price shocks. Our paper utilizes the Campbell (1991) decomposition of stock returns based on a log-linear approximation to the discounted present value relation while allowing for time varying expected returns. The results from our baseline regressions indicate that there is little sensitivity in industry level portfolios to unexpected movements in oil prices, with the gold, oil & gas and retail industries being the only exception. In contrast, based in the Campbell (1991) decomposition, we identify extensive exposure to oil prices in industry level returns in particular channels. The extent of the exposure is particularly significant for a number of the industries, with positive (negative) permanent implications for gold, and the oil and gas industries (retail and meals, restaurants and hotels).

Suggested Citation

  • Don Bredin & John Elder, 2011. "US Oil Price Exposure: The Industry Effects," Working Papers 201107, Geary Institute, University College Dublin.
  • Handle: RePEc:ucd:wpaper:201107
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    File URL: http://www.ucd.ie/geary/static/publications/workingpapers/gearywp201107.pdf
    File Function: First version, 2011
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    Cited by:

    1. Shaeri, Komeil & Adaoglu, Cahit & Katircioglu, Salih T., 2016. "Oil price risk exposure: A comparison of financial and non-financial subsectors," Energy, Elsevier, vol. 109(C), pages 712-723.

    More about this item

    Keywords

    Oil; Industry Stock Returns; Vector autoregression;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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