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Nonlinear Dynamics in Energy Futures

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  • Mariano Matilla-García

Abstract

This paper studies the possible nonlinear and chaotic nature of three energy futures: natural gas, unleaded gasoline and light crude oil. Nonlinearity is analyzed using the generalized BDS statistic, along with KaplanÕs test. The results show that nonlinearity cannot be rejected. The null hypothesis of chaos is then investigated via the stability of the largest Lyapunov exponent. Evidence of chaos is found in futures returns. Global modelling techniques, like genetic algorithms, have been used in order to estimate potential motion equations. In addition, short term forecasts in futures price movements have been conducted with these estimated equations. The results show that although forecast errors are statistically smaller than those computed with other stochastic approaches, further research on these topics needs to be done.

Suggested Citation

  • Mariano Matilla-García, 2007. "Nonlinear Dynamics in Energy Futures," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 7-30.
  • Handle: RePEc:aen:journl:2007v28-03-a02
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    1. Shintani, Mototsugu & Linton, Oliver, 2004. "Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos," Journal of Econometrics, Elsevier, vol. 120(1), pages 1-33, May.
    2. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-337, July.
    3. Melvin J. Hinich, 1982. "Testing For Gaussianity And Linearity Of A Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(3), pages 169-176, May.
    4. Victor Chwee, 1998. "Chaos in Natural Gas Futures?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 149-164.
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    Cited by:

    1. Loretta Mastroeni & Pierluigi Vellucci, 2016. "“Butterfly Effect" vs Chaos in Energy Futures Markets," Departmental Working Papers of Economics - University 'Roma Tre' 0209, Department of Economics - University Roma Tre.
    2. Baba, Amina & Creti, Anna & Massol, Olivier, 2020. "What can be learned from the free destination option in the LNG imbroglio?," Energy Economics, Elsevier, vol. 89(C).
    3. Amina Baba & Anna Creti & Olivier Massol, 2020. "What can we Learn from the Free Destination Option in the LNG Imbroglio ?," Working Papers hal-03181028, HAL.
    4. Matilla-García, Mariano & Marín, Manuel Ruiz, 2010. "A new test for chaos and determinism based on symbolic dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 600-614, December.
    5. Wang, Tao & Yang, Jian, 2010. "Nonlinearity and intraday efficiency tests on energy futures markets," Energy Economics, Elsevier, vol. 32(2), pages 496-503, March.
    6. Yaya, OlaOluwa Simon & Gil-Alana, Luis Alberiko & Carcel, Hector, 2015. "Testing fractional persistence and non-linearities in the natural gas market: An application of non-linear deterministic terms based on Chebyshev polynomials in time," Energy Economics, Elsevier, vol. 52(PA), pages 240-245.
    7. Mariano Matilla-García & Manuel Ruiz Marín & Mohammed Dore & Rina Ojeda, 2014. "Nonparametric correlation integral–based tests for linear and nonlinear stochastic processes," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(1), pages 181-193, April.
    8. Loretta Mastroeni & Pierluigi Vellucci, 2016. ""Butterfly Effect" vs Chaos in Energy Futures Markets," Papers 1610.05697, arXiv.org.
    9. Barkoulas, John T. & Chakraborty, Atreya & Ouandlous, Arav, 2012. "A metric and topological analysis of determinism in the crude oil spot market," Energy Economics, Elsevier, vol. 34(2), pages 584-591.

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