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The trilogy of China cotton markets: The lead–lag relationship among spot, forward, and futures markets

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  • Mert Demir
  • Terrence F. Martell
  • Jun Wang

Abstract

China is a leading participant in the world cotton market. China’s distinctive regulatory structure and procedures and business environment provide an opportunity to explore some unique market dynamics. This study investigates the interrelationship among the spot, futures, and forward cotton markets in China over a period of a major policy change: A temporary State reserve program for cotton that was established in 2011 and ended in 2014. This government intervention significantly distorted the way farmers, manufacturers, and speculators interacted and was not sustainable. Overall, our results support futures market’s dominant role in the price discovery process.

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  • Mert Demir & Terrence F. Martell & Jun Wang, 2019. "The trilogy of China cotton markets: The lead–lag relationship among spot, forward, and futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(4), pages 522-534, April.
  • Handle: RePEc:wly:jfutmk:v:39:y:2019:i:4:p:522-534
    DOI: 10.1002/fut.21981
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    1. Sokbae Lee & Myung Hwan Seo & Youngki Shin, 2017. "Correction," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 883-883, April.
    2. Yongmin Zhang & Shusheng Ding & Eric Scheffel, 2018. "Policy impact on volatility dynamics in commodity futures markets: Evidence from China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(10), pages 1227-1245, October.
    3. Hammoudeh, Shawkat & Li, Huimin, 2004. "The impact of the Asian crisis on the behavior of US and international petroleum prices," Energy Economics, Elsevier, vol. 26(1), pages 135-160, January.
    4. Bohl, Martin T. & Siklos, Pierre L. & Wellenreuther, Claudia, 2018. "Speculative activity and returns volatility of Chinese agricultural commodity futures," Journal of Asian Economics, Elsevier, vol. 54(C), pages 69-91.
    5. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    6. Cheung, Yin-Wong & Ng, Lilian K., 1996. "A causality-in-variance test and its application to financial market prices," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 33-48.
    7. Chen, Pei-Fen & Lee, Chien-Chiang & Zeng, Jhih-Hong, 2014. "The relationship between spot and futures oil prices: Do structural breaks matter?," Energy Economics, Elsevier, vol. 43(C), pages 206-217.
    8. MacDonald, Stephen & Gale, Fred & Hansen, James, 2015. "Cotton Policy in China," MPRA Paper 70863, University Library of Munich, Germany.
    9. Hernandez, Manuel & Torero, Maximo, 2010. "Examining the dynamic relationship between spot and future prices of agricultural commodities," IFPRI discussion papers 988, International Food Policy Research Institute (IFPRI).
    10. 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.
    11. 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.
    12. Brorsen, B. Wade & Bailey, DeeVon & Richardson, James W., 1984. "Investigation Of Price Discovery And Efficiency For Cash And Futures Cotton Prices," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 9(1), pages 1-7, July.
    13. Gordon C. Rausser & James A. Chalfant & H. Alan Love & Kostas G. Stamoulis, 1986. "Macroeconomic Linkages, Taxes, and Subsidies in the U.S. Agricultural Sector," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(2), pages 399-412.
    14. Martin T. Bohl & Pierre L. Siklos & Claudia Wellenreuther, 2018. "Speculative activity and returns volatility of Chinese major agricultural commodity futures," CAMA Working Papers 2018-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Gordon C. Rausser & James A. Chalfant & H. Alan Love & Kostas G. Stamoulis, 1986. "Macroeconomic Linkages, Taxes, and Subsidies in the U.S. Agricultural Sector," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(2), pages 399-412.
    16. Yuanlong Ge & Holly H. Wang & Sung K. Ahn, 2010. "Cotton market integration and the impact of China's new exchange rate regime," Agricultural Economics, International Association of Agricultural Economists, vol. 41(5), pages 443-451, September.
    17. 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.
    18. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, Decembrie.
    19. Param Silvapulle & Imad A. Moosa, 1999. "The relationship between spot and futures prices: Evidence from the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(2), pages 175-193, April.
    20. Lee, Chien-Chiang & Chiu, Yi-Bin, 2013. "Modeling OECD energy demand: An international panel smooth transition error-correction model," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 372-383.
    21. Kapetanios, George & Shin, Yongcheol & Snell, Andy, 2006. "Testing For Cointegration In Nonlinear Smooth Transition Error Correction Models," Econometric Theory, Cambridge University Press, vol. 22(2), pages 279-303, April.
    22. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    23. Foster, Andrew J., 1996. "Price discovery in oil markets: a time varying analysis of the 1990-1991 Gulf conflict," Energy Economics, Elsevier, vol. 18(3), pages 231-246, July.
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    Cited by:

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    3. Pradhan, Rudra P. & Hall, John H. & du Toit, Elda, 2021. "The lead–lag relationship between spot and futures prices: Empirical evidence from the Indian commodity market," Resources Policy, Elsevier, vol. 70(C).

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