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Herding behaviour in asymmetric and extreme situations: the case of China

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  • Ziyao Luo
  • Christophe Schinckus

Abstract

This paper will investigate herding behaviour in asymmetric (bearish versus bullish context) and extreme market conditions (characterized by significant changes in stock prices) through daily data from the Shanghai and Shenzhen stock exchange markets. Results show that a bullish context generates a herding behaviour for B-shares while a bearish situation rather favours a crowd movement for A-shares. Given that sophisticated investors are known to trade on B-shares, these results suggest that this category of actors is more likely to follow the trend when they face with a bullish context while they can reduce their herding behaviour in a bearish context by using technical/analytical tools allowing them not to follow the crowd behaviour.

Suggested Citation

  • Ziyao Luo & Christophe Schinckus, 2015. "Herding behaviour in asymmetric and extreme situations: the case of China," Applied Economics Letters, Taylor & Francis Journals, vol. 22(11), pages 869-873, July.
    • Handle: RePEc:taf:apeclt:v:22:y:2015:i:11:p:869-873
    DOI: 10.1080/13504851.2014.985363
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    Citations

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    Cited by:

    1. Omokolade Akinsomi & Yener Coskun & Rangan Gupta & Chi Keung Marco Lau, 2016. "Impact of Volatility and Equity Market Uncertainty on Herd Behavior: Evidence from UK REITs," Working Papers 201688, University of Pretoria, Department of Economics.
    2. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    3. Yi-Chang Chen & Hung-Che Wu & Jen-Jsung Huang, 2017. "Herd Behavior and Rational Expectations: A Test of China's Market Using Quantile Regression," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 649-663.
    4. Ormos, Mihály & Timotity, Dusán, 2016. "Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading," Finance Research Letters, Elsevier, vol. 19(C), pages 60-66.
    5. Lee, Kyuseok, 2017. "Herd behavior of the overall market: Evidence based on the cross-sectional comovement of returns," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 266-284.
    6. Canh P. Nguyen & Christophe Schinckus & Dinh Su Thanh, 2020. "Economic Fluctuations And The Shadow Economy: A Global Study," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-24, September.
    7. Canh P. Nguyen & Christophe Schinckus & Thanh D. Su & Felicia H. L. Chong, 2022. "Determinants of stock market returns in emerging markets: The linkage between institutional quality and macro liquidity," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4472-4486, October.
    8. Mouna Youssef & Khaled Mokni, 2023. "Herding behavior in stock markets of oil-importing and oil-exporting countries: the role of oil price," Journal of Asset Management, Palgrave Macmillan, vol. 24(1), pages 44-58, February.
    9. Oi-Ping Chong & A.N. Bany-Ariffin & Annuar Md Nassir & Junaina Muhammad, 2019. "An Empirical Study of Herding Behaviour in China’s A-Share and B-Share Markets: Evidence of Bidirectional Herding Activities," Capital Markets Review, Malaysian Finance Association, vol. 27(2), pages 37-57.
    10. Hui HONG & Shulin XU & Chien-Chiang LEE, 2020. "Investor Herding in the China Stock Market: An Examination of ChiNext," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 47-61, December.

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