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Long-run Models of Oil Stock Prices

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  • Alessandro Lanza

    (Eni S.p.A., Roma, Fondazione Eni Enrico Mattei, Milano and CRENoS, Cagliari, Italy)

  • Matteo Manera

    (Department of Statistics, University of Milano-Bicocca and Fondazione Eni Enrico Mattei, Milano, Italy)

  • Margherita Grasso

    (Fondazione Eni Enrico Mattei, Milano, Italy)

  • Massimo Giovannini

    (Department of Economics, Boston College, USA and Fondazione Eni Enrico Mattei, Milano, Italy)

Abstract

The identification of the forces that drive oil stock prices is extremely important given the size of the Oil&Gas industry and its links with the energy sector and the environment. In the next decade oil companies will have to deal with international policies to contrast climate change. This issue is likely to affect companies’ shareholder values. In this paper we focus on the long-run financial determinants of the stock prices of six major oil companies (Bp, Chevron-Texaco, Eni, Exxon-Mobil, Royal Dutch Shell, Total-Fina-Elf) using multivariate cointegration techniques and vector error correction models. Weekly oil stock prices are analyzed together with the relevant stock market indexes, exchange rates, spot and future oil prices over the period January 1998- April 2003. The empirical results confirm the statistical significance of the major financial variables in explaining the long-run dynamics of oil companies’ stock values.

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Bibliographic Info

Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2003.96.

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Date of creation: Oct 2003
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Handle: RePEc:fem:femwpa:2003.96

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Keywords: Cointegration; Vector error correction models; Oil companies; Oil stock prices; Hydrocarbon fuels; Energy; Non-renewable resources; Environment;

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  1. Sadorsky, Perry, 2001. "Risk factors in stock returns of Canadian oil and gas companies," Energy Economics, Elsevier, vol. 23(1), pages 17-28, January.
  2. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 601-18, Nov.-Dec..
  3. Amano, R. A. & van Norden, S., 1998. "Oil prices and the rise and fall of the US real exchange rate," Journal of International Money and Finance, Elsevier, vol. 17(2), pages 299-316, April.
  4. Søren Johansen & Katarina Juselius, 1989. "The Full Information Maximum Likelihood Procedure for Inference on Cointegration - with Applications," Discussion Papers 89-11, University of Copenhagen. Department of Economics.
  5. Urbain, J-P., 1991. "On Weak Exogeneity in Error Correction Models," Papers 9103, Liege - Centre de Recherches Economiques et Demographiques.
  6. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
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Cited by:
  1. Mohanty, Sunil & Nandha, Mohan & Bota, Gabor, 2010. "Oil shocks and stock returns: The case of the Central and Eastern European (CEE) oil and gas sectors," Emerging Markets Review, Elsevier, vol. 11(4), pages 358-372, December.
  2. Cong, Rong-Gang & Wei, Yi-Ming & Jiao, Jian-Lin & Fan, Ying, 2008. "Relationships between oil price shocks and stock market: An empirical analysis from China," Energy Policy, Elsevier, vol. 36(9), pages 3544-3553, September.
  3. Matteo Manera & Massimo Giovannini & Margherita Grasso & Alessandro Lanza, 2004. "Conditional Correlations in the Returns on Oil Companies Stock Prices and Their Determinants," Working Papers 2004.71, Fondazione Eni Enrico Mattei.

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