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Lottery preference, short-sale constraint, and the salience effect: Evidence from China

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  • Liu, Chang
  • Sun, Peng
  • Zhu, Dongming

Abstract

This paper documents the significant and robust salience theory (ST) effect in China, which differs from the findings in the literature. First, the upside-ST effect from stocks with salient upsides is stronger than the downside-ST effect from stocks with salient downsides; the opposite pattern is documented in the US market. We demonstrate that this pattern is due to strong lottery preference and short-sale constraint in China, where investors are prone to engage in salient thinking when they bet on lottery stocks; meanwhile, short-sale constraint prevents rational investors from correcting salience-induced mispricing. Second, the salience effect remains strong in big stocks and high institutional ownership stocks. Our findings are consistent with the existing evidence that fund managers cater to fund investors' lottery preferences to hold lottery stocks. Our study provides new insights into the sources of the salience effect in China, especially salience's interaction with investor behaviors and the market's institutional characteristics.

Suggested Citation

  • Liu, Chang & Sun, Peng & Zhu, Dongming, 2023. "Lottery preference, short-sale constraint, and the salience effect: Evidence from China," Economic Modelling, Elsevier, vol. 125(C).
  • Handle: RePEc:eee:ecmode:v:125:y:2023:i:c:s0264999323001530
    DOI: 10.1016/j.econmod.2023.106341
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    as
    1. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    2. Liu, Jianan & Stambaugh, Robert F. & Yuan, Yu, 2019. "Size and value in China," Journal of Financial Economics, Elsevier, vol. 134(1), pages 48-69.
    3. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    4. Diefeng Peng & Yulei Rao & Mei Wang, 2016. "Do Top 10 Lists of Daily Stock Returns Attract Investor Attention? Evidence from a Natural Experiment," International Review of Finance, International Review of Finance Ltd., vol. 16(4), pages 565-593, December.
    5. Leippold, Markus & Wang, Qian & Zhou, Wenyu, 2022. "Machine learning in the Chinese stock market," Journal of Financial Economics, Elsevier, vol. 145(2), pages 64-82.
    6. 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.
    7. Alon Brav & J.B. Heaton & Si Li, 2010. "The Limits of the Limits of Arbitrage," Review of Finance, European Finance Association, vol. 14(1), pages 157-187.
    8. Muhammad A. Cheema & Gilbert V. Nartea & Yimei Man, 2020. "Maxing Out in China: Optimism or Attention?," International Review of Finance, International Review of Finance Ltd., vol. 20(4), pages 961-971, December.
    9. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    10. Li, Hao & Li, Zhisheng & Lin, Bingxuan & Xu, Xiaowei, 2019. "The effect of short sale constraints on analyst forecast quality: Evidence from a natural experiment in China," Economic Modelling, Elsevier, vol. 81(C), pages 338-347.
    11. 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.
    12. Gu, Ming & Jiang, George J. & Xu, Bu, 2019. "The role of analysts: An examination of the idiosyncratic volatility anomaly in the Chinese stock market," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 237-254.
    13. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    14. Eugene F. Fama & Kenneth R. French, 2008. "Dissecting Anomalies," Journal of Finance, American Finance Association, vol. 63(4), pages 1653-1678, August.
    15. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2012. "Salience Theory of Choice Under Risk," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1243-1285.
    16. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Asset Prices," American Economic Review, American Economic Association, vol. 103(3), pages 623-628, May.
    17. Feng, Xunan & Chan, Kam C., 2016. "Information advantage, short sales, and stock returns: Evidence from short selling reform in China," Economic Modelling, Elsevier, vol. 59(C), pages 131-142.
    18. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    19. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    20. Baars, Maren & Mohrschladt, Hannes, 2021. "An alternative behavioral explanation for the MAX effect," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 868-886.
    21. Simon Gervais & Ron Kaniel & Dan H. Mingelgrin, 2001. "The High‐Volume Return Premium," Journal of Finance, American Finance Association, vol. 56(3), pages 877-919, June.
    22. Constantinos Antoniou & John A. Doukas & Avanidhar Subrahmanyam, 2016. "Investor Sentiment, Beta, and the Cost of Equity Capital," Management Science, INFORMS, vol. 62(2), pages 347-367, February.
    23. Yao, Shouyu & Wang, Chunfeng & Cui, Xin & Fang, Zhenming, 2019. "Idiosyncratic skewness, gambling preference, and cross-section of stock returns: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 464-483.
    24. 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.
    25. Cosemans, Mathijs & Frehen, Rik, 2021. "Salience theory and stock prices: Empirical evidence," Journal of Financial Economics, Elsevier, vol. 140(2), pages 460-483.
    26. 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.
    27. Nagel, Stefan, 2005. "Short sales, institutional investors and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 78(2), pages 277-309, November.
    28. Carpenter, Jennifer N. & Lu, Fangzhou & Whitelaw, Robert F., 2021. "The real value of China’s stock market," Journal of Financial Economics, Elsevier, vol. 139(3), pages 679-696.
    29. Wan, Xiaoyuan, 2018. "Is the idiosyncratic volatility anomaly driven by the MAX or MIN effect? Evidence from the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 1-15.
    30. Shleifer, Andrei & Vishny, Robert W, 1997. "The Limits of Arbitrage," Journal of Finance, American Finance Association, vol. 52(1), pages 35-55, March.
    31. Liu, Hongqi & Peng, Cameron & Wei, Xiong & Wei, Xiong, 2022. "Taming the bias zoo," LSE Research Online Documents on Economics 109301, London School of Economics and Political Science, LSE Library.
    32. Kumar, Alok & Page, Jeremy K. & Spalt, Oliver G., 2016. "Gambling and Comovement," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(1), pages 85-111, February.
    33. Jiang, George J. & Lu, Liangliang & Zhu, Dongming, 2014. "The information content of analyst recommendation revisions — Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 29(C), pages 1-17.
    34. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    35. Kewei Hou & Chen Xue & Lu Zhang, 2020. "Replicating Anomalies," Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2019-2133.
    36. Zhao, Zhongkuang & Li, Shuqi & Xiong, Heping, 2014. "Short sale constraints, disperse pessimistic beliefs and market efficiency — Evidence from the Chinese stock market," Economic Modelling, Elsevier, vol. 42(C), pages 333-342.
    37. 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.
    38. Liu, Hongqi & Peng, Cameron & Xiong, Wei A. & Xiong, Wei, 2022. "Taming the bias zoo," Journal of Financial Economics, Elsevier, vol. 143(2), pages 716-741.
    39. Robert F. Stambaugh & Jianfeng Yu & Yu Yuan, 2015. "Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle," Journal of Finance, American Finance Association, vol. 70(5), pages 1903-1948, October.
    40. Gang, Jianhua & Qian, Zongxin & Xu, Tiange, 2019. "Investment horizons, cash flow news, and the profitability of momentum and reversal strategies in the Chinese stock market," Economic Modelling, Elsevier, vol. 83(C), pages 364-371.
    41. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    42. Stephen Brown & Yan Lu & Sugata Ray & Melvyn Teo, 2018. "Sensation Seeking and Hedge Funds," Journal of Finance, American Finance Association, vol. 73(6), pages 2871-2914, December.
    43. 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.
    44. Königsheim, C. & Lukas, M. & Nöth, M., 2019. "Salience theory: Calibration and heterogeneity in probability distortion," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 477-495.
    45. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    46. Zhu, Hong-bing & Zhang, Bing & Yang, Li-hua, 2021. "The gambling preference and stock price: Evidence from China's stock market," Emerging Markets Review, Elsevier, vol. 49(C).
    47. Elena Asparouhova & Hendrik Bessembinder & Ivalina Kalcheva, 2013. "Noisy Prices and Inference Regarding Returns," Journal of Finance, American Finance Association, vol. 68(2), pages 665-714, April.
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    More about this item

    Keywords

    Salience effect; Lottery preference; Short-sale constraint; Chinese stock market;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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