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Unit Root Behavior in Energy Futures Prices

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  • Apostolos Serletis

Abstract

This paper re-examines the empirical evidence for random walk type behavior in energy futures prices. In doing so, tests for unit roots in the univariate time-series representation of the daily crude oil, heating oil, and unleaded gasoline series are performed using recent state-of-the-art methodology. The results show that the unit root hypothesis can be rejected if allowance is made for the possibility of a one-time break in the intercept and the slope of the trend function at an unknown point in time.

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Bibliographic Info

Article provided by International Association for Energy Economics in its journal The Energy Journal.

Volume (Year): Volume 13 (1992)
Issue (Month): Number 2 ()
Pages: 119-128

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Handle: RePEc:aen:journl:1992v13-02-a06

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References

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  1. Summers, Lawrence H, 1986. " Does the Stock Market Rationally Reflect Fundamental Values?," Journal of Finance, American Finance Association, vol. 41(3), pages 591-601, July.
  2. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
  3. Zivot, Eric & Andrews, Donald W K, 1992. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 251-70, July.
  4. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
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Cited by:
  1. Noguera, José, 2013. "Oil prices: Breaks and trends," Energy Economics, Elsevier, vol. 37(C), pages 60-67.
  2. Maslyuk, Svetlana & Smyth, Russell, 2008. "Unit root properties of crude oil spot and futures prices," Energy Policy, Elsevier, vol. 36(7), pages 2591-2600, July.
  3. Yudong Wang & Chongfeng Wu, 2013. "Efficiency of Crude Oil Futures Markets: New Evidence from Multifractal Detrending Moving Average Analysis," Computational Economics, Society for Computational Economics, vol. 42(4), pages 393-414, December.
  4. Wang, Yudong & Wu, Chongfeng, 2012. "Long memory in energy futures markets: Further evidence," Resources Policy, Elsevier, vol. 37(3), pages 261-272.
  5. Herbert, John H, 1995. "Trading volume, maturity and natural gas futures price volatility," Energy Economics, Elsevier, vol. 17(4), pages 293-299, October.
  6. Elder, John & Serletis, Apostolos, 2008. "Long memory in energy futures prices," Review of Financial Economics, Elsevier, vol. 17(2), pages 146-155.
  7. Ghoshray, Atanu & Johnson, Ben, 2010. "Trends in world energy prices," Energy Economics, Elsevier, vol. 32(5), pages 1147-1156, September.
  8. Carlos Pestana Barros & Luis A. Gil-Alana, 2011. "Oil Prices: Persistence and Breaks," Faculty Working Papers 09/11, School of Economics and Business Administration, University of Navarra.
  9. Lean, Hooi Hooi & Smyth, Russell, 2009. "Long memory in US disaggregated petroleum consumption: Evidence from univariate and multivariate LM tests for fractional integration," Energy Policy, Elsevier, vol. 37(8), pages 3205-3211, August.
  10. Belbute, José, 2013. "Does final demand for energy in Portugal exhibit long memory?," MPRA Paper 45717, University Library of Munich, Germany.
  11. Vinod Mishra & Russell Smyth, 2014. "Unit root properties of natural gas spot and futures prices: The relevance of heteroskedasticity in high frequency data," Development Research Unit Working Paper Series 20-14, Monash University, Department of Economics.

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