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Speculative Activity and Returns Volatility of Chinese Major Agricultural Commodity Futures

Author

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  • Martin T. Bohl
  • Pierre L. Siklos
  • Claudia Wellenreuther

Abstract

Chinese futures markets for agricultural commodities are among the fastest growing futures markets in the world and trading behaviour in those markets is perceived as highly speculative. Therefore, we empirically investigate whether speculative activity in Chinese futures markets for agricultural commodities destabilizes futures returns. To capture speculative activity a speculation and a hedging ratio are used. Applying GARCH models, we first analyse the influence of both ratios on the conditional volatility of eight heavily traded Chinese futures contracts. Additionally, VAR models in conjunction with Granger causality tests, impulse-response analyses and variance decompositions are used to obtain insight into the lead-lag relationship between speculative activity and returns volatility. For most of the commodities, we find a positive influence of the speculation ratio on conditional volatility. The results relying on the hedging ratio are inconclusive.

Suggested Citation

  • 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.
  • Handle: RePEc:een:camaaa:2018-06
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    Cited by:

    1. Hardik A. Marfatia & Qiang Ji & Jiawen Luo, 2022. "Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 383-404, March.
    2. Li, Jianping & Li, Guowen & Liu, Mingxi & Zhu, Xiaoqian & Wei, Lu, 2022. "A novel text-based framework for forecasting agricultural futures using massive online news headlines," International Journal of Forecasting, Elsevier, vol. 38(1), pages 35-50.
    3. Huilian Huang & Tao Xiong, 2023. "A good hedge or safe haven? The hedging ability of China's commodity futures market under extreme market conditions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(7), pages 968-1035, July.
    4. Yongmei Fang & Bo Guan & Shangjuan Wu & Saeed Heravi, 2020. "Optimal forecast combination based on ensemble empirical mode decomposition for agricultural commodity futures prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 877-886, September.
    5. Junshu Jiang & Jordan Richards & Raphael Huser & David Bolin, 2024. "The Efficient Tail Hypothesis: An Extreme Value Perspective on Market Efficiency," Papers 2408.06661, arXiv.org, revised Jul 2025.
    6. Debopam Rakshit & Ranjit Kumar Paul & Md Yeasin & Walid Emam & Yusra Tashkandy & Christophe Chesneau, 2023. "Modeling Asymmetric Volatility: A News Impact Curve Approach," Mathematics, MDPI, vol. 11(13), pages 1-14, June.
    7. Zhou, Liyun & Huang, Jialiang, 2020. "Contagion of future-level sentiment in Chinese Agricultural Futures Markets," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    8. Donghua Wang & Yang Xin & Xiaohui Chang & Xingze Su, 2021. "Realized volatility forecasting and volatility spillovers: Evidence from Chinese non‐ferrous metals futures," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2713-2731, April.
    9. Fan, John Hua & Mo, Di & Zhang, Tingxi, 2022. "The “necessary evil” in Chinese commodity markets," Journal of Commodity Markets, Elsevier, vol. 25(C).
    10. Wimmer, Thomas & Geyer-Klingeberg, Jerome & Hütter, Marie & Schmid, Florian & Rathgeber, Andreas, 2021. "The impact of speculation on commodity prices: A Meta-Granger analysis," Journal of Commodity Markets, Elsevier, vol. 22(C).
    11. Bernardina Algieri & Matthias Kalkuhl, 2019. "Efficiency and Forecast Performance of Commodity Futures Markets," American Journal of Economics and Business Administration, Science Publications, vol. 11(1), pages 19-34, June.
    12. Chaya Bagrecha & Kuldeep Singh & Geeti Sharma & P. B. Saranya, 2025. "Forecasting silver prices: a univariate ARIMA approach and a proposed model for future direction," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 38(1), pages 131-141, March.
    13. Algirdas Justinas Staugaitis & Bernardas Vaznonis, 2022. "Financial Speculation Impact on Agricultural and Other Commodity Return Volatility: Implications for Sustainable Development and Food Security," Agriculture, MDPI, vol. 12(11), pages 1-27, November.
    14. Algirdas Justinas Staugaitis & Bernardas Vaznonis, 2022. "Short-Term Speculation Effects on Agricultural Commodity Returns and Volatility in the European Market Prior to and during the Pandemic," Agriculture, MDPI, vol. 12(5), pages 1-26, April.
    15. Schmidt, Torsten & Kirsch, Florian & Dirks, Maximilian W., 2021. "Kurzfristige Perspektiven der Rohstoffpreisentwicklung," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 251878.
    16. Ye, Wuyi & Guo, Ranran & Deschamps, Bruno & Jiang, Ying & Liu, Xiaoquan, 2021. "Macroeconomic forecasts and commodity futures volatility," Economic Modelling, Elsevier, vol. 94(C), pages 981-994.
    17. Zeeshan Mustafa & Giuliano Vitali & Ray Huffaker & Maurizio Canavari, 2024. "A systematic review on price volatility in agriculture," Journal of Economic Surveys, Wiley Blackwell, vol. 38(1), pages 268-294, February.
    18. Chang, Chiu-Lan, 2024. "Extreme events, economic uncertainty and speculation on occurrences of price bubbles in crude oil futures," Energy Economics, Elsevier, vol. 130(C).
    19. Luo, Jiawen & Marfatia, Hardik A. & Ji, Qiang & Klein, Tony, 2023. "Co-volatility and asymmetric transmission of risks between the global oil and China's futures markets," Energy Economics, Elsevier, vol. 117(C).
    20. 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.
    21. Ruwei Zhao & Xiong Xiong & Junjun Ma & Yuzhao Zhang & Yongjie Zhang, 2025. "Baidu News and the return volatility of Chinese commodity futures: evidence for the sequential information arrival hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-24, December.
    22. Akinbode, S. O. & Ojo, O. T., . "The Effect of Exchange Rate Volatility on Agricultural Exports in Nigeria: An Autoregressive Distributed Lag (ARDL) Bounds Test Approach," Nigerian Journal of Agricultural Economics, Nigerian Journal of Agricultural Economics, vol. 8(01).
    23. Fang, Ming & Chang, Chiu-Lan & Zhang, Qi, 2023. "Impacts of trading restrictions on price volatilities and speculative activities: Evidence from CSI 300 futures," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 184-204.

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    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F30 - International Economics - - International Finance - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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