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Tracking investor gambling intensity

Author

Listed:
  • Zhu, Hongbing
  • Yang, Lihua
  • Xu, Changxin
Abstract
We provide a simple method to track firm-specific investor gambling intensity based on the publicly available transaction data. This identification approach effectively incorporates information on what and how much to buy in the trading decision of an investor with a gambling preference. With empirical analysis based on data of the Chinese stock market from January 2003 to May 2021, we document that investor gambling intensity is strongly persistent and significantly predicts future stock returns, which is not a rediscovery of the well-known lottery effect. Stocks with high aggregate gambling intensity underperform stocks with low aggregate gambling intensity by approximately 117 basis points over the following month. Several potential explanations for such empirical findings are examined, and we document support for the explanation based on information diffusion.

Suggested Citation

  • Zhu, Hongbing & Yang, Lihua & Xu, Changxin, 2023. "Tracking investor gambling intensity," International Review of Financial Analysis, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:finana:v:86:y:2023:i:c:s1057521922004185
    DOI: 10.1016/j.irfa.2022.102468
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    as
    1. Zhou, Xuemei & Liu, Qiang & Guo, Shuxin, 2021. "Do overnight returns explain firm-specific investor sentiment in China?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 451-477.
    2. Paul A. Gompers & Andrew Metrick, 2001. "Institutional Investors and Equity Prices," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 229-259.
    3. Xuemin (Sterling) Yan & Zhe Zhang, 2009. "Institutional Investors and Equity Returns: Are Short-term Institutions Better Informed?," The Review of Financial Studies, Society for Financial Studies, vol. 22(2), pages 893-924, February.
    4. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    5. 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.
    6. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 18, pages 1053-1128, Elsevier.
    7. Ng, Lilian & Wu, Fei, 2006. "Revealed stock preferences of individual investors: Evidence from Chinese equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 14(2), pages 175-192, April.
    8. 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.
    9. Lee, Charles M.C. & Sun, Stephen Teng & Wang, Rongfei & Zhang, Ran, 2019. "Technological links and predictable returns," Journal of Financial Economics, Elsevier, vol. 132(3), pages 76-96.
    10. David Hirshleifer & Siew Hong Teoh & Jeff Jiewei Yu, 2011. "Short Arbitrage, Return Asymmetry, and the Accrual Anomaly," The Review of Financial Studies, Society for Financial Studies, vol. 24(7), pages 2429-2461.
    11. Hirshleifer, David & Teoh, Siew Hong, 2003. "Limited attention, information disclosure, and financial reporting," Journal of Accounting and Economics, Elsevier, vol. 36(1-3), pages 337-386, December.
    12. Brian Boyer & Todd Mitton & Keith Vorkink, 2010. "Expected Idiosyncratic Skewness," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 169-202, January.
    13. Karen Schnatterly & Kenneth W. Shaw & William W. Jennings, 2008. "Information advantages of large institutional owners," Strategic Management Journal, Wiley Blackwell, vol. 29(2), pages 219-227, February.
    14. Aboody, David & Even-Tov, Omri & Lehavy, Reuven & Trueman, Brett, 2018. "Overnight Returns and Firm-Specific Investor Sentiment," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(2), pages 485-505, April.
    15. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    16. Conrad, Jennifer & Kapadia, Nishad & Xing, Yuhang, 2014. "Death and jackpot: Why do individual investors hold overpriced stocks?," Journal of Financial Economics, Elsevier, vol. 113(3), pages 455-475.
    17. Markus K. Brunnermeier & Jonathan A. Parker & Christian Gollier, 2007. "Optimal Beliefs, Asset Prices, and the Preference for Skewed Returns," American Economic Review, American Economic Association, vol. 97(2), pages 159-165, May.
    18. Peng, Lin & Xiong, Wei, 2006. "Investor attention, overconfidence and category learning," Journal of Financial Economics, Elsevier, vol. 80(3), pages 563-602, June.
    19. 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.
    20. 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.
    21. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    22. Zeng, Yeqin, 2016. "Institutional investors: Arbitrageurs or rational trend chasers," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 240-262.
    23. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    24. Liu, Jianan & Stambaugh, Robert F. & Yuan, Yu, 2019. "Size and value in China," Journal of Financial Economics, Elsevier, vol. 134(1), pages 48-69.
    25. 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.
    26. Lee, Charles M. C., 1992. "Earnings news and small traders : An intraday analysis," Journal of Accounting and Economics, Elsevier, vol. 15(2-3), pages 265-302, August.
    27. T. Clifton Green & Byoung-Hyoun Hwang, 2012. "Initial Public Offerings as Lotteries: Skewness Preference and First-Day Returns," Management Science, INFORMS, vol. 58(2), pages 432-444, February.
    28. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    29. 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.
    30. Xiaohui Gao & Tse-Chun Lin, 2015. "Do Individual Investors Treat Trading as a Fun and Exciting Gambling Activity? Evidence from Repeated Natural Experiments," The Review of Financial Studies, Society for Financial Studies, vol. 28(7), pages 2128-2166.
    31. Chan, Louis K C & Jegadeesh, Narasimhan & Lakonishok, Josef, 1996. "Momentum Strategies," Journal of Finance, American Finance Association, vol. 51(5), pages 1681-1713, December.
    32. 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.
    33. 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).
    34. Ng, Lilian & Wu, Fei, 2007. "The trading behavior of institutions and individuals in Chinese equity markets," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2695-2710, September.
    35. Li, Xindan & Geng, Ziyang & Subrahmanyam, Avanidhar & Yu, Honghai, 2017. "Do wealthy investors have an informational advantage? Evidence based on account classifications of individual investors," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 1-18.
    36. Han, Bing & Kumar, Alok, 2013. "Speculative Retail Trading and Asset Prices," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(2), pages 377-404, April.
    37. Jang, Jeewon & Kang, Jangkoo, 2019. "Probability of price crashes, rational speculative bubbles, and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 222-247.
    38. Cai, Fang & Han, Song & Li, Dan & Li, Yi, 2019. "Institutional herding and its price impact: Evidence from the corporate bond market," Journal of Financial Economics, Elsevier, vol. 131(1), pages 139-167.
    39. Ekkehart Boehmer & Charles M. Jones & Xiaoyan Zhang & Xinran Zhang, 2021. "Tracking Retail Investor Activity," Journal of Finance, American Finance Association, vol. 76(5), pages 2249-2305, October.
    40. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    41. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    42. Ke, Bin & Ramalingegowda, Santhosh, 2005. "Do institutional investors exploit the post-earnings announcement drift?," Journal of Accounting and Economics, Elsevier, vol. 39(1), pages 25-53, February.
    43. Hendershott, Terrence & Livdan, Dmitry & Rösch, Dominik, 2020. "Asset pricing: A tale of night and day," Journal of Financial Economics, Elsevier, vol. 138(3), pages 635-662.
    44. Chordia, Tarun & Subrahmanyam, Avanidhar, 2004. "Order imbalance and individual stock returns: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 72(3), pages 485-518, June.
    45. Florian Weißofner & Ulrich Wessels, 2020. "Overnight Returns: An International Sentiment Measure," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 21(2), pages 205-217, April.
    46. Liu, Bibo & Wang, Huijun & Yu, Jianfeng & Zhao, Shen, 2020. "Time-varying demand for lottery: Speculation ahead of earnings announcements," Journal of Financial Economics, Elsevier, vol. 138(3), pages 789-817.
    47. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    48. Byun, Suk-Joon & Kim, Da-Hea, 2016. "Gambling preference and individual equity option returns," Journal of Financial Economics, Elsevier, vol. 122(1), pages 155-174.
    49. 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.
    50. Anne Jones Dorn & Daniel Dorn & Paul Sengmueller, 2015. "Trading as Gambling," Management Science, INFORMS, vol. 61(10), pages 2376-2393, October.
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    More about this item

    Keywords

    Investor gambling preference; Gambling intensity; Return predictability; Information diffusion;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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