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Price Formation and Intertemporal Arbitrage within a Low-Liquidity Framework: Empirical Evidence from European Natural Gas Markets

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  • Nick, Sebastian

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

Abstract

In this study, the informational efficiency of the European natural gas market is analyzed by empirically investigating price formation and arbitrage efficiency between spot and futures markets. Econometric approaches are specified that explicitly account for nonlinearities and the low liquidity-framework of the considered gas hubs. The empirical results reveal that price discovery takes place on the futures market, while the spot price subsequently follows the futures market price. Furthermore, there is empirical evidence of significant market frictions hampering intertemporal arbitrage. UK’s NBP seems to be the hub at which arbitrage opportunities are exhausted most efficiently, although there is convergence in the degree of intertemporal arbitrage efficiency over time at the hubs investigated.

Suggested Citation

  • Nick, Sebastian, 2013. "Price Formation and Intertemporal Arbitrage within a Low-Liquidity Framework: Empirical Evidence from European Natural Gas Markets," EWI Working Papers 2013-14, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
  • Handle: RePEc:ris:ewikln:2013_014
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    as
    1. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2013. "On the short- and long-run efficiency of energy and precious metal markets," Energy Economics, Elsevier, vol. 40(C), pages 832-844.
    2. Helmut Lütkepohl, 2005. "New Introduction to Multiple Time Series Analysis," Springer Books, Springer, number 978-3-540-27752-1, December.
    3. Growitsch Christian & Nepal Rabindra & Stronzik Marcus, 2015. "Price Convergence and Information Efficiency in German Natural Gas Markets," German Economic Review, De Gruyter, vol. 16(1), pages 87-103, February.
    4. Granger, C W J & Lee, T H, 1989. "Investigation of Production, Sales and Inventory Relationships Using Multicointegration and Non-symmetric Error Correction Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages 145-159, Supplemen.
    5. Dergiades, Theologos & Madlener, Reinhard & Christofidou, Georgia, 2018. "The nexus between natural gas spot and futures prices at NYMEX: Do weather shocks and non-linear causality in low frequencies matter?," The Journal of Economic Asymmetries, Elsevier, vol. 18(C), pages 1-1.
    6. Stronzik, Marcus & Rammerstorfer, Margarethe & Neumann, Anne, 2009. "Does the European natural gas market pass the competitive benchmark of the theory of storage? Indirect tests for three major trading points," Energy Policy, Elsevier, vol. 37(12), pages 5432-5439, December.
    7. Timothy J. Considine & Donald F. Larson, 2001. "Risk premiums on inventory assets: the case of crude oil and natural gas," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(2), pages 109-126, February.
    8. An-Sing Chen & James Wuh Lin, 2004. "Cointegration and detectable linear and nonlinear causality: analysis using the London Metal Exchange lead contract," Applied Economics, Taylor & Francis Journals, vol. 36(11), pages 1157-1167.
    9. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    10. Eugene F. Fama & Kenneth R. French, 2015. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 4, pages 79-102, World Scientific Publishing Co. Pte. Ltd..
    11. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    12. Bénédicte Vidaillet & V. d'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    13. Root, Thomas H. & Lien, Donald, 2003. "Can modeling the natural gas futures market as a threshold cointegrated system improve hedging and forecasting performance?," International Review of Financial Analysis, Elsevier, vol. 12(2), pages 117-133.
    14. Jinghong Shu & Jin E. Zhang, 2012. "Causality in the VIX futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(1), pages 24-46, January.
    15. Diks Cees & Panchenko Valentyn, 2005. "A Note on the Hiemstra-Jones Test for Granger Non-causality," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-9, June.
    16. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    17. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    18. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    19. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    20. Huang, Bwo-Nung & Yang, C.W. & Hwang, M.J., 2009. "The dynamics of a nonlinear relationship between crude oil spot and futures prices: A multivariate threshold regression approach," Energy Economics, Elsevier, vol. 31(1), pages 91-98, January.
    21. Nick, Sebastian & Thoenes, Stefan, 2014. "What drives natural gas prices? — A structural VAR approach," Energy Economics, Elsevier, vol. 45(C), pages 517-527.
    22. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    23. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    24. Ming-Yuan Leon Li, 2010. "Dynamic hedge ratio for stock index futures: application of threshold VECM," Applied Economics, Taylor & Francis Journals, vol. 42(11), pages 1403-1417.
    25. Gebre-Mariam, Yohannes Kebede, 2011. "Testing for unit roots, causality, cointegration, and efficiency: The case of the northwest US natural gas market," Energy, Elsevier, vol. 36(5), pages 3489-3500.
    26. Enders, Walter & Siklos, Pierre L, 2001. "Cointegration and Threshold Adjustment," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 166-176, April.
    27. Anne Neumann & Boriss Siliverstovs & Christian von Hirschhausen, 2006. "Convergence of European spot market prices for natural gas? A real-time analysis of market integration using the Kalman Filter," Applied Economics Letters, Taylor & Francis Journals, vol. 13(11), pages 727-732.
    28. Stelios Bekiros, 2011. "Nonlinear causality testing with stepwise multivariate filtering," Economics Working Papers ECO2011/22, European University Institute.
    29. Urbain, Jean-Pierre, 1992. "On Weak Exogeneity in Error Correction Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(2), pages 187-207, May.
    30. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality," Energy Economics, Elsevier, vol. 30(5), pages 2673-2685, September.
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    More about this item

    Keywords

    natural gas market; informational efficiency; liquidity; nonlinear causality; threshold error correction; Kalman filter;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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