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High†Frequency Positive Feedback Trading and Market Quality: Evidence from China's Stock Market

Author

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  • Die Wan
  • Xiaoguang Yang

Abstract

This paper managed to measure the positive feedback trading intensity and its asymmetry with high†frequency transaction data of China's individual stocks. The intraday positive feedback trading is found to be heterogeneous, and buying†winners effect is significantly stronger than selling†losers effect. In general, the high†frequency asymmetric positive feedback trading's impact on market quality is mixed: The intraday positive feedback trades contribute to a liquid and active†trading market but at the same time slow down the price discovery process and reduce the price efficiency.

Suggested Citation

  • Die Wan & Xiaoguang Yang, 2017. "High†Frequency Positive Feedback Trading and Market Quality: Evidence from China's Stock Market," International Review of Finance, International Review of Finance Ltd., vol. 17(4), pages 493-523, December.
    • Handle: RePEc:bla:irvfin:v:17:y:2017:i:4:p:493-523
    DOI: 10.1111/irfi.12116
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    Cited by:

    1. Prachi Deuskar & Deng Pan & Fei Wu & Hongfeng Zhou, 2021. "How does regret affect investor behaviour? Evidence from Chinese stock markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(S1), pages 1851-1896, April.
    2. Wang, Chen & Xiong, Xiong & Shen, Dehua, 2022. "Tail risks, firm characteristics, and stock returns," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    3. Liu, Xufeng & Wan, Die, 2023. "Retail investor trading and ESG pricing in China," Research in International Business and Finance, Elsevier, vol. 65(C).
    4. SENARATHNE W Chamil & JIANGUO Wei, 2018. "Do Investors Mimic Trading Strategies Of Foreign Investors Or The Market: Implications For Capital Asset Pricing," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 13(3), pages 171-205, December.
    5. Liu, Xufeng & Wan, Die, 2022. "Asymmetric positive feedback trading and stock pricing in China," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    6. Dimitrios Koutmos & James E. Payne, 2021. "Intertemporal asset pricing with bitcoin," Review of Quantitative Finance and Accounting, Springer, vol. 56(2), pages 619-645, February.
    7. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2021. "Stock Market’s responses to intraday investor sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    8. Shi, Leilei & Wang, Binghong & Guo, Xinshuai & Li, Honggang, 2021. "A price dynamic equilibrium model with trading volume weights based on a price-volume probability wave differential equation," International Review of Financial Analysis, Elsevier, vol. 74(C).
    9. Yingli Wang & Chang Lu & Xiaoguang Yang & Qingpeng Zhang, 2023. "Asymmetric responses to Purchasing Managers' Index announcements in China's stock returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2937-2955, July.

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