[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1611.07432.html
   My bibliography  Save this paper

"Chaos" in energy and commodity markets: a controversial matter

Author

Listed:
  • Loretta Mastroeni
  • Pierluigi Vellucci
Abstract
We test whether the futures prices of some commodity and energy markets are determined by stochastic rules or exhibit nonlinear deterministic endogenous fluctuations. As for the methodologies, we use the maximal Lyapunov exponents (MLE) and a determinism test, both based on the reconstruction of the phase space. In particular, employing a recent methodology, we estimate a coefficient $\kappa$ that describes the determinism rate of the analyzed time series. We find that the underlying system for futures prices shows a reliability level $\kappa$ near to $1$ while the MLE is positive for all commodity futures series. Thus, the empirical evidence suggests that commodity and energy futures prices are the measured footprint of a nonlinear deterministic, rather than a stochastic, system.

Suggested Citation

  • Loretta Mastroeni & Pierluigi Vellucci, 2016. ""Chaos" in energy and commodity markets: a controversial matter," Papers 1611.07432, arXiv.org, revised Mar 2017.
    • Handle: RePEc:arx:papers:1611.07432
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1611.07432
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Apostolos Serletis & Periklis Gogas, 2007. "The North American Natural Gas Liquids Markets are Chaotic," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 17, pages 225-244, World Scientific Publishing Co. Pte. Ltd..
    2. Gradojevic, Nikola & Gencay, Ramazan, 2008. "Overnight interest rates and aggregate market expectations," Economics Letters, Elsevier, vol. 100(1), pages 27-30, July.
    3. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
    4. Benedetto, F. & Giunta, G. & Mastroeni, L., 2016. "On the predictability of energy commodity markets by an entropy-based computational method," Energy Economics, Elsevier, vol. 54(C), pages 302-312.
    5. Saeed Moshiri & Faezeh Foroutan, 2006. "Forecasting Nonlinear Crude Oil Futures Prices," The Energy Journal, , vol. 27(4), pages 81-96, October.
    6. Victor Chwee, 1998. "Chaos in Natural Gas Futures?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 149-164.
    7. Panas, E., 2001. "Long memory and chaotic models of prices on the London Metal Exchange," Resources Policy, Elsevier, vol. 27(4), pages 235-246, December.
    8. Sarantis, Nicholas, 2001. "Nonlinearities, cyclical behaviour and predictability in stock markets: international evidence," International Journal of Forecasting, Elsevier, vol. 17(3), pages 459-482.
    9. Barnett, William A. & Serletis, Apostolos, 2000. "Martingales, nonlinearity, and chaos," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 703-724, June.
    10. Gençay, Ramazan & Gradojevic, Nikola, 2010. "Crash of '87 -- Was it expected?: Aggregate market fears and long-range dependence," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 270-282, March.
    11. 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.
    12. Adrangi, Bahram & Chatrath, Arjun & Dhanda, Kanwalroop Kathy & Raffiee, Kambiz, 2001. "Chaos in oil prices? Evidence from futures markets," Energy Economics, Elsevier, vol. 23(4), pages 405-425, July.
    13. Zhang, Michael Yuanjie & Russell, Jeffrey R. & Tsay, Ruey S., 2001. "A nonlinear autoregressive conditional duration model with applications to financial transaction data," Journal of Econometrics, Elsevier, vol. 104(1), pages 179-207, August.
    14. Chatrath, Arjun & Adrangi, Bahram & Dhanda, Kanwalroop Kathy, 2002. "Are commodity prices chaotic?," Agricultural Economics, Blackwell, vol. 27(2), pages 123-137, August.
    15. Panas, Epaminondas & Ninni, Vassilia, 2000. "Are oil markets chaotic? A non-linear dynamic analysis," Energy Economics, Elsevier, vol. 22(5), pages 549-568, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Loretta Mastroeni & Pierluigi Vellucci, 2017. "“Chaos” In Energy And Commodity Markets: A Controversial Matter," Departmental Working Papers of Economics - University 'Roma Tre' 0218, Department of Economics - University Roma Tre.
    2. 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.
    3. Loretta Mastroeni & Pierluigi Vellucci, 2016. ""Butterfly Effect" vs Chaos in Energy Futures Markets," Papers 1610.05697, arXiv.org.
    4. Mastroeni, Loretta & Vellucci, Pierluigi & Naldi, Maurizio, 2019. "A reappraisal of the chaotic paradigm for energy commodity prices," Energy Economics, Elsevier, vol. 82(C), pages 167-178.
    5. John Francis Diaz & Jo-Hui Chen, 2017. "Testing for Long-memory and Chaos in the Returns of Currency Exchange-traded Notes (ETNs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-2.
    6. Tao Yin & Yiming Wang, 2019. "Predicting the Price of WTI Crude Oil Using ANN and Chaos," Sustainability, MDPI, vol. 11(21), pages 1-14, October.
    7. 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.
    8. Bildirici, Melike E. & Sonustun, Bahri, 2021. "Chaotic behavior in gold, silver, copper and bitcoin prices," Resources Policy, Elsevier, vol. 74(C).
    9. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    10. Gu, Rongbao & Zhang, Bing, 2016. "Is efficiency of crude oil market affected by multifractality? Evidence from the WTI crude oil market," Energy Economics, Elsevier, vol. 53(C), pages 151-158.
    11. Marcos Álvarez-Díaz, 2020. "Is it possible to accurately forecast the evolution of Brent crude oil prices? An answer based on parametric and nonparametric forecasting methods," Empirical Economics, Springer, vol. 59(3), pages 1285-1305, September.
    12. Gencer, Murat & Unal, Gazanfer, 2016. "Testing Non-Linear Dynamics, Long Memory and Chaotic Behaviour of Energy Commodities," MPRA Paper 74115, University Library of Munich, Germany.
    13. Tapia Cortez, Carlos A. & Hitch, Michael & Sammut, Claude & Coulton, Jeff & Shishko, Robert & Saydam, Serkan, 2018. "Determining the embedding parameters governing long-term dynamics of copper prices," Chaos, Solitons & Fractals, Elsevier, vol. 111(C), pages 186-197.
    14. Lu-Tao Zhao & Guan-Rong Zeng & Ling-Yun He & Ya Meng, 2020. "Forecasting Short-Term Oil Price with a Generalised Pattern Matching Model Based on Empirical Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1151-1169, April.
    15. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo, 2008. "Short-term predictability of crude oil markets: A detrended fluctuation analysis approach," Energy Economics, Elsevier, vol. 30(5), pages 2645-2656, September.
    16. Apostolos Serletis & Ioannis Andreadis, 2007. "Random Fractal Structures in North American Energy Markets," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 18, pages 245-255, World Scientific Publishing Co. Pte. Ltd..
    17. Chen, Shu-Peng & He, Ling-Yun, 2010. "Multifractal spectrum analysis of nonlinear dynamical mechanisms in China’s agricultural futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1434-1444.
    18. Nikola Gradojevic & Marko Caric, 2017. "Predicting Systemic Risk with Entropic Indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(1), pages 16-25, January.
    19. Masih, Rumi & Peters, Sanjay & De Mello, Lurion, 2011. "Oil price volatility and stock price fluctuations in an emerging market: Evidence from South Korea," Energy Economics, Elsevier, vol. 33(5), pages 975-986, September.
    20. Bunyamin Demir & Nesrin Alptekin & Yilmaz Kilicaslan & Mehmet Ergen & Nilgun Caglairmak Uslu, 2015. "Forecasting Agricultural Production: A Chaotic Dynamic Approach," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 1(1), pages 65-80, June.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1611.07432. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.