IDEAS home Printed from
   My bibliography  Save this paper

The North American Natural Gas Liquids Markets are Chaotic


  • Serletis, A.
  • Gogas, P.


In this paper we test for deterministic chaos(i.e., nonlinear deterministic processes which look random) in seven Mont Belview, Texas hydrocarbon markets, using monthly data from 1985:1 to 1996:12 -- the markets are those of ethane, propane, normal butane, iso-butane, naphta, crude oil, and natural gas. In doing so, we use the Lyapunov exponent estimator of Nychka, Ellner, Gallant and McCaffrey (1992). We conclude that there is evidence consistent with chaotic nonlinear generation process in all five natural gas liquids markets.

Suggested Citation

  • Serletis, A. & Gogas, P., 1998. "The North American Natural Gas Liquids Markets are Chaotic," Papers 98-10, Calgary - Department of Economics.
  • Handle: RePEc:fth:calgar:98-10

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    1. Frederic S. Mishkin, 1984. "The Real Interest Rate: A Multi-Country Empirical Study," Canadian Journal of Economics, Canadian Economics Association, vol. 17(2), pages 283-311, May.
    2. Robert G. King & Mark W. Watson, 1997. "Testing long-run neutrality," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 69-101.
    3. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    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 1057-1072, June.
    5. Christiano, Lawrence J & Eichenbaum, Martin, 1995. "Liquidity Effects, Monetary Policy, and the Business Cycle," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(4), pages 1113-1136, November.
    6. Serletis, Apostolos & Koustas, Zisimos, 1998. "International Evidence on the Neutrality of Money," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 30(1), pages 1-25, February.
    7. Eric M. Leeper & Christopher A. Sims & Tao Zha, 1996. "What Does Monetary Policy Do?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(2), pages 1-78.
    8. Haliassos, Michael & Tobin, James, 1990. "The macroeconomics of government finance," Handbook of Monetary Economics,in: B. M. Friedman & F. H. Hahn (ed.), Handbook of Monetary Economics, edition 1, volume 2, chapter 17, pages 889-959 Elsevier.
    9. Fuerst, Timothy S., 1992. "Liquidity, loanable funds, and real activity," Journal of Monetary Economics, Elsevier, vol. 29(1), pages 3-24, February.
    10. Mankiw, N. Gregory, 1987. "The optimal collection of seigniorage : Theory and evidence," Journal of Monetary Economics, Elsevier, vol. 20(2), pages 327-341, September.
    11. Fisher, Mark E & Seater, John J, 1993. "Long-Run Neutrality and Superneutrality in an ARIMA Framework," American Economic Review, American Economic Association, vol. 83(3), pages 402-415, June.
    12. Lucas, Robert Jr., 1990. "Liquidity and interest rates," Journal of Economic Theory, Elsevier, vol. 50(2), pages 237-264, April.
    13. MacKinnon, James G, 1994. "Approximate Asymptotic Distribution Functions for Unit-Root and Cointegration Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 167-176, April.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    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. 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.
    3. Aghababa, Hajar & Barnett, William A., 2016. "Dynamic structure of the spot price of crude oil: does time aggregation matter?," Energy Economics, Elsevier, vol. 59(C), pages 227-237.
    4. Xu, Weijun & Sun, Qi & Xiao, Weilin, 2012. "A new energy model to capture the behavior of energy price processes," Economic Modelling, Elsevier, vol. 29(5), pages 1585-1591.
    5. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    6. repec:spt:apfiba:v:7:y:2017:i:4:f:7_4_2 is not listed on IDEAS
    7. 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.
    8. Elder, John & Serletis, Apostolos, 2008. "Long memory in energy futures prices," Review of Financial Economics, Elsevier, vol. 17(2), pages 146-155.
    9. 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..
    10. Loretta Mastroeni & Pierluigi Vellucci, 2016. ""Butterfly Effect" vs Chaos in Energy Futures Markets," Papers 1610.05697,
    11. Loretta Mastroeni & Pierluigi Vellucci, 2016. ""Chaos" in energy and commodity markets: a controversial matter," Papers 1611.07432,, revised Mar 2017.
    12. 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.
    13. Wu, Y. & Zhang, D.Z., 2007. "Demand fluctuation and chaotic behaviour by interaction between customers and suppliers," International Journal of Production Economics, Elsevier, vol. 107(1), pages 250-259, May.

    More about this item



    JEL classification:

    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading


    Access and download statistics


    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:fth:calgar:98-10. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.