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Does Trading Behaviour Converge across Commodity Markets? Evidence from the Perspective of Hedgers’ Sentiment

Author

Listed:
  • Qiang Ji

    (Center for Energy and Environmental Policy research, Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China and School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Walid Bahloul

    (Governance, Finance and Accounting Laboratory, Faculty of Business and Economics, University of Sfax, Sfax 3018, Tunisia)

  • Jiang-bo Geng

    (School of Finance, Zhongnan University of Economics and Law, Wuhan 430073, China)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

Abstract

We analyse the connectedness network for commercial traders’ sentiment across different futures markets. Using weekly data over the period of 2 September 2008 to 27 December 2016 on 21 commodity covering agriculture, energy, metals and livestock, we find that: (a) producer/merchant/processor/user (PMPU) in agricultural and energy markets are mainly engaged in cross-hedging in the futures market, and most of them would avoid risks in these markets by operating in the metal markets, which can be considered safe for PMPU traders, and that the cross-hedging strategies may play the role of PMPU sentiment spillover across futures markets; (b) as index traders, the swap dealers operate more in two markets, namely between the agricultural and metal markets, or between the agricultural and energy markets; (c) the influence of geopolitical risks in some countries can affect the stability of energy markets, which in turn can cause PMPU system-wide connectedness.

Suggested Citation

  • Qiang Ji & Walid Bahloul & Jiang-bo Geng & Rangan Gupta, 2019. "Does Trading Behaviour Converge across Commodity Markets? Evidence from the Perspective of Hedgers’ Sentiment," Working Papers 201930, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201930
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    References listed on IDEAS

    as
    1. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    2. Wang, Changyun, 2004. "Futures trading activity and predictable foreign exchange market movements," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1023-1041, May.
    3. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    4. Changyun Wang, 2001. "Investor Sentiment and Return Predictability in Agricultural Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(10), pages 929-952, October.
    5. Changyun Wang, 2002. "The effect of net positions by type of trader on volatility in foreign currency futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(5), pages 427-450, May.
    6. Ing-Haw Cheng & Wei Xiong, 2014. "Why Do Hedgers Trade So Much?," The Journal of Legal Studies, University of Chicago Press, vol. 43(S2), pages 183-207.
    7. Sirimon Treepongkaruna & Stephen Gray, 2009. "Information and volatility links in the foreign exchange market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 49(2), pages 385-405, June.
    8. Frans A. De Roon & Theo E. Nijman & Chris Veld, 2000. "Hedging Pressure Effects in Futures Markets," Journal of Finance, American Finance Association, vol. 55(3), pages 1437-1456, June.
    9. Sakemoto, Ryuta, 2018. "Do precious and industrial metals act as hedges and safe havens for currency portfolios?," Finance Research Letters, Elsevier, vol. 24(C), pages 256-262.
    10. Bahloul, Walid & Bouri, Abdelfettah, 2016. "Profitability of return and sentiment-based investment strategies in US futures markets," Research in International Business and Finance, Elsevier, vol. 36(C), pages 254-270.
    11. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    12. Zhang, Dayong, 2017. "Oil shocks and stock markets revisited: Measuring connectedness from a global perspective," Energy Economics, Elsevier, vol. 62(C), pages 323-333.
    13. Peijie Wang, 2009. "The Economics of Foreign Exchange and Global Finance," Springer Books, Springer, number 978-3-642-00100-0, January.
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