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Cranes among chickens: The general-attention‐grabbing effect of daily price limits in China's stock market

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  • LIN, Fengjiao
  • QIU, Zhigang
  • ZHENG, Weinan

Abstract

This paper examines the general-attention-grabbing effect of daily price limits in China's stock market. We show that stocks with large exposure to daily price limits attract more investor attention and have lower future returns. The exposure is measured empirically through the absolute beta with respect to the daily proportion of stocks that hit price limits. The general-attention-grabbing effect is not solely caused by stocks that recently hit price limits, is not subsumed by market volatility exposure, and does not reflect other stock market characteristics. Moreover, the effect is stronger among stocks that are heavily invested in by retail investors.

Suggested Citation

  • LIN, Fengjiao & QIU, Zhigang & ZHENG, Weinan, 2023. "Cranes among chickens: The general-attention‐grabbing effect of daily price limits in China's stock market," Journal of Banking & Finance, Elsevier, vol. 150(C).
  • Handle: RePEc:eee:jbfina:v:150:y:2023:i:c:s0378426623000432
    DOI: 10.1016/j.jbankfin.2023.106818
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    as
    1. Kai Li & Tan Wang & Yan-Leung Cheung & Ping Jiang, 2011. "Privatization and Risk Sharing: Evidence from the Split Share Structure Reform in China," Review of Financial Studies, Society for Financial Studies, vol. 24(7), pages 2499-2525.
    2. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    3. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    4. Kim, Kenneth A., 2001. "Price limits and stock market volatility," Economics Letters, Elsevier, vol. 71(1), pages 131-136, April.
    5. Thomas J. Chemmanur & An Yan, 2019. "Advertising, Attention, and Stock Returns," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-51, September.
    6. Huang, Yuqin & Qiu, Huiyan & Wu, Zhiguo, 2016. "Local bias in investor attention: Evidence from China's Internet stock message boards," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 338-354.
    7. Brian Boyer & Todd Mitton & Keith Vorkink, 2010. "Expected Idiosyncratic Skewness," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 169-202, January.
    8. Liu, Baixiao & McConnell, John J., 2013. "The role of the media in corporate governance: Do the media influence managers' capital allocation decisions?," Journal of Financial Economics, Elsevier, vol. 110(1), pages 1-17.
    9. Nicholas Barberis & Abhiroop Mukherjee & Baolian Wang, 2016. "Prospect Theory and Stock Returns: An Empirical Test," Review of Financial Studies, Society for Financial Studies, vol. 29(11), pages 3068-3107.
    10. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    11. Liu, Jianan & Stambaugh, Robert F. & Yuan, Yu, 2019. "Size and value in China," Journal of Financial Economics, Elsevier, vol. 134(1), pages 48-69.
    12. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    13. Cai, Haidong & Jiang, Ying & Liu, Xiaoquan, 2022. "Investor attention, aggregate limit-hits, and stock returns," International Review of Financial Analysis, Elsevier, vol. 83(C).
    14. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    15. Gu, Ming & Kang, Wenjin & Xu, Bu, 2018. "Limits of arbitrage and idiosyncratic volatility: Evidence from China stock market," Journal of Banking & Finance, Elsevier, vol. 86(C), pages 240-258.
    16. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    17. Nartea, Gilbert V. & Kong, Dongmin & Wu, Ji, 2017. "Do extreme returns matter in emerging markets? Evidence from the Chinese stock market," Journal of Banking & Finance, Elsevier, vol. 76(C), pages 189-197.
    18. Chen, Ting & Gao, Zhenyu & He, Jibao & Jiang, Wenxi & Xiong, Wei, 2019. "Daily price limits and destructive market behavior," Journal of Econometrics, Elsevier, vol. 208(1), pages 249-264.
    19. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    20. Kim, Kenneth & Rhee, S Ghon, 1997. "Price Limit Performance: Evidence from the Tokyo Stock Exchange," Journal of Finance, American Finance Association, vol. 52(2), pages 885-899, June.
    21. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    22. Huang, Shiyang & Huang, Yulin & Lin, Tse-Chun, 2019. "Attention allocation and return co-movement: Evidence from repeated natural experiments," Journal of Financial Economics, Elsevier, vol. 132(2), pages 369-383.
    23. Hsieh, Ping-Hung & Kim, Yong H. & Yang, J. Jimmy, 2009. "The magnet effect of price limits: A logit approach," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 830-837, December.
    24. Seasholes, Mark S. & Wu, Guojun, 2007. "Predictable behavior, profits, and attention," Journal of Empirical Finance, Elsevier, vol. 14(5), pages 590-610, December.
    25. Ma, C.K. & Rao, R.P. & Sears, R.S., 1989. "Volatility, Price Resolution, And The Effectiveness Of Price Limits," Papers t7, Columbia - Center for Futures Markets.
    26. Firth, Michael & Lin, Chen & Zou, Hong, 2010. "Friend or Foe? The Role of State and Mutual Fund Ownership in the Split Share Structure Reform in China," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(3), pages 685-706, June.
    27. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    28. Chan, Soon Huat & Kim, Kenneth A. & Rhee, S. Ghon, 2005. "Price limit performance: evidence from transactions data and the limit order book," Journal of Empirical Finance, Elsevier, vol. 12(2), pages 269-290, March.
    29. Deb, Saikat Sovan & Kalev, Petko S. & Marisetty, Vijaya B., 2010. "Are price limits really bad for equity markets?," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2462-2471, October.
    30. Li An & Huijun Wang & Jian Wang & Jianfeng Yu, 2020. "Lottery-Related Anomalies: The Role of Reference-Dependent Preferences," Management Science, INFORMS, vol. 66(1), pages 473-501, January.
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    More about this item

    Keywords

    Chinese stock market; Daily price limits; General-Attention-Grabbing Effect;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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