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Contemporaneous and Asymmetric Properties in the Price-Volume Relationships in China's Agricultural Futures Markets

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  • Ling-Yun He
  • Sheng Yang
  • Wen-Si Xie
  • Zhi-Hong Han

Abstract

In this paper, we choose six representative futures contracts—soybean, soy meal, corn, hard wheat, strong gluten wheat, and sugar—from China's futures markets to examine predictability and market efficiency from the perspective of the price-volume relationships. Our empirical results show that there is a positive unidirectional causality relationship between volume and return (absolute return). We also find that the trading volumes behave asymmetrically in bull and bear markets, which supports the "heterogeneity of traders" hypothesis but contradicts the "short-selling constraint" hypothesis. Finally, we find that China's futures markets are predictable using historical information and thus are not informationally efficient.

Suggested Citation

  • Ling-Yun He & Sheng Yang & Wen-Si Xie & Zhi-Hong Han, 2014. "Contemporaneous and Asymmetric Properties in the Price-Volume Relationships in China's Agricultural Futures Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(S1), pages 148-166.
  • Handle: RePEc:mes:emfitr:v:50:y:2014:i:s1:p:148-166
    DOI: 10.2753/REE1540-496X5001S110
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    Cited by:

    1. Li, Jianxuan & Shi, Yingying & Cao, Guangxi, 2018. "Topology structure based on detrended cross-correlation coefficient of exchange rate network of the belt and road countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1140-1151.
    2. Wei Zhang & Pengfei Wang & Xiao Li & Dehua Shen, 2018. "Some stylized facts of the cryptocurrency market," Applied Economics, Taylor & Francis Journals, vol. 50(55), pages 5950-5965, November.
    3. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    4. Go, You-How & Lau, Wee-Yeap, 2020. "The impact of global financial crisis on informational efficiency: Evidence from price-volume relation in crude palm oil futures market," Journal of Commodity Markets, Elsevier, vol. 17(C).
    5. Zhang, Xin & Zhu, Yingming & Yang, Liansheng, 2018. "Multifractal detrended cross-correlations between Chinese stock market and three stock markets in The Belt and Road Initiative," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 105-115.
    6. Yan, Kai & Zhang, Wei & Shen, Dehua, 2020. "Stylized facts of the carbon emission market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    7. Atilgan, Yigit & Demirtas, K. Ozgur & Simsek, Koray D., 2016. "Derivative markets in emerging economies: A survey," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 88-102.
    8. You‐How Go & Wee‐Yeap Lau, 2023. "What do we know about informational efficiency? Three puzzles and the new direction forward," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1489-1525, September.
    9. Muzhao Jin & Fearghal Kearney & Youwei Li & Yung Chiang Yang, 2023. "Order book price impact in the Chinese soybean futures market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 606-625, January.
    10. Zhou, Liyun & Zhang, Rixin & Huang, Jialiang, 2019. "Investor trading behavior on agricultural future prices," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 365-379.
    11. Fousekis, Panos & Tzaferi, Dimitra, 2021. "Returns and volume: Frequency connectedness in cryptocurrency markets," Economic Modelling, Elsevier, vol. 95(C), pages 13-20.
    12. Cao, Guangxi & Xu, Wei, 2016. "Nonlinear structure analysis of carbon and energy markets with MFDCCA based on maximum overlap wavelet transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 505-523.
    13. Zhi-Hong Han & Sheng Yang & Mu-Ling Chen & Ling-Yun He, 2015. "Mean spillover effect between crude oil and gasoline markets: an empirical result," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(1/2/3), pages 49-68.

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