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Cointegration and detectable linear and nonlinear causality: analysis using the London Metal Exchange lead contract

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  • An-Sing Chen
  • James Wuh Lin

Abstract

This study applies linear and nonlinear Granger causality tests to examine the dynamic relation between London Metal Exchange (LME) cash prices and three possible predictors. The analysis uses matched quarterly inventory, UK Treasury bill interest rates, futures prices and cash prices for the commodity lead traded on the LME. The effects of cointegration on both linear and nonlinear Granger causality tests is also examined. When cointegration is not modelled, evidence is found of both linear and nonlinear causality between cash prices and analysed predictor variables. However, after controlling for cointegration, evidence of significant nonlinear causality is no longer found. These results contribute to the empirical literature on commodity price forecasting by highlighting the relationship between cointegration and detectable linear and nonlinear causality. The importance of interest rate and inventory as well as futures price in forecasting cash prices is also illustrated. Failure to detect significant nonlinearity after controlling for cointegration may also go some way to explaining the reason for the disappointing forecasting performances of many nonlinear models in the general finance literature. It may be that the variables are correct, but the functional form is overly complex and a standard VAR or VECM may often apply.

Suggested Citation

  • 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.
  • Handle: RePEc:taf:applec:v:36:y:2004:i:11:p:1157-1167
    DOI: 10.1080/0003684042000247352
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    Cited by:

    1. Sebastian Nick, 2016. "The Informational Efficiency of European Natural Gas Hubs: Price Formation and Intertemporal Arbitrage," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    2. Gurgul, Henryk & Lach, Łukasz, 2012. "The association between stock market and exchange rates for advanced and emerging markets – A case study of the Swiss and Polish economies," MPRA Paper 52238, University Library of Munich, Germany.
    3. Kyrtsou, Catherine & Mikropoulou, Christina & Papana, Angeliki, 2016. "Does the S&P500 index lead the crude oil dynamics? A complexity-based approach," Energy Economics, Elsevier, vol. 56(C), pages 239-246.
    4. Liu, Li & Wan, Jieqiu, 2011. "A study of correlations between crude oil spot and futures markets: A rolling sample test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3754-3766.
    5. Alzahrani, Mohammed & Masih, Mansur & Al-Titi, Omar, 2014. "Linear and non-linear Granger causality between oil spot and futures prices: A wavelet based test," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 175-201.
    6. 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).
    7. Hammami Algia & Bouri Abdelfatteh, 2016. "The Volatility of Oil Prices: What Factors?," Bulletin of Energy Economics (BEE), The Economics and Social Development Organization (TESDO), vol. 4(1), pages 98-110, March.
    8. Syed Hassan & Sarosh Shabi & Taufiq Choudhry, 2018. "US Economic Uncertainty, EU Business Cycles and the Global Financial Crisis," Working Papers 2018-05, Swansea University, School of Management.
    9. Gurgul, Henryk & Lach, lukasz, 2011. "The role of coal consumption in the economic growth of the Polish economy in transition," Energy Policy, Elsevier, vol. 39(4), pages 2088-2099, April.
    10. 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.
    11. Henryk Gurgul & Łukasz Lach & Roland Mestel, 2012. "The relationship between budgetary expenditure and economic growth in Poland," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(1), pages 161-182, March.
    12. Gurgul, Henryk & Lach, Łukasz, 2011. "Causality analysis between public expenditure and economic growth of Polish economy in last decade," MPRA Paper 52281, University Library of Munich, Germany.
    13. Lukasz Lach & Henryk Gurgul, 2010. "International trade and economic growth in the Polish economy," Operations Research and Decisions, Wroclaw University of Technology, Institute of Organization and Management, vol. 3, pages 5-29.
    14. 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.
    15. Beckmann, Joscha & Czudaj, Robert, 2014. "Volatility transmission in agricultural futures markets," Economic Modelling, Elsevier, vol. 36(C), pages 541-546.
    16. Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.

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