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Property crime and lottery-related anomalies

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  • Gao, Ya
  • Bradrania, Reza

Abstract

In this paper, we explore the association between property crime rate and lottery demand anomalies. Motivated by criminology literature that suggests a positive relation between crime and risk-taking, we conjecture that gambling propensity in the stock market is stronger (weaker) in regions with higher (lower) property crime rate. Consistent with our conjecture, we show that underperformance of lottery stocks, proxied by MAX, is more pronounced in the US regions with higher property crime rates compared to regions with lower property crime rates. Our results are robust to alternative proxies for lottery demand, such as alternative constructions of MAX and skewness measures, and various empirical tests. Our findings suggest variation in crime-induced gambling propensity affects financial market outcomes.

Suggested Citation

  • Gao, Ya & Bradrania, Reza, 2024. "Property crime and lottery-related anomalies," Global Finance Journal, Elsevier, vol. 59(C).
    • Handle: RePEc:eee:glofin:v:59:y:2024:i:c:s1044028323001229
    DOI: 10.1016/j.gfj.2023.100927
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    as
    1. 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.
    2. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    3. 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.
    4. Moya, Andrés, 2018. "Violence, psychological trauma, and risk attitudes: Evidence from victims of violence in Colombia," Journal of Development Economics, Elsevier, vol. 131(C), pages 15-27.
    5. Pamela Jakiela & Owen Ozier, 2019. "The Impact of Violence on Individual Risk Preferences: Evidence from a Natural Experiment," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 547-559, July.
    6. Scholes, Myron & Williams, Joseph, 1977. "Estimating betas from nonsynchronous data," Journal of Financial Economics, Elsevier, vol. 5(3), pages 309-327, December.
    7. Jonathan M. Karpoff & D. Scott Lee & Gerald S. Martin, 2014. "The Consequences to Managers for Financial Misrepresentation," Springer Books, in: Roberto Pietra & Stuart McLeay & Joshua Ronen (ed.), Accounting and Regulation, edition 127, chapter 0, pages 339-375, Springer.
    8. Simon Davies & Tim Hinks, 2010. "Crime and Happiness Amongst Heads of Households in Malawi," Journal of Happiness Studies, Springer, vol. 11(4), pages 457-476, August.
    9. John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2008. "In Search of Distress Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2899-2939, December.
    10. Chew, Soo Hong & Ho, Joanna L, 1994. "Hope: An Empirical Study of Attitude toward the Timing of Uncertainty Resolution," Journal of Risk and Uncertainty, Springer, vol. 8(3), pages 267-288, May.
    11. 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.
    12. 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.
    13. Gilbert V. Nartea & Ji Wu & Hong Tao Liu, 2014. "Extreme returns in emerging stock markets: evidence of a MAX effect in South Korea," Applied Financial Economics, Taylor & Francis Journals, vol. 24(6), pages 425-435, March.
    14. Byun, Suk-Joon & Goh, Jihoon & Kim, Da-Hea, 2020. "The role of psychological barriers in lottery-related anomalies," Journal of Banking & Finance, Elsevier, vol. 114(C).
    15. 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.
    16. 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.
    17. Loughran, Tim & Schultz, Paul, 2004. "Weather, Stock Returns, and the Impact of Localized Trading Behavior," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(2), pages 343-364, June.
    18. Yong-Ho Cheon & Kuan-Hui Lee, 2018. "Maxing Out Globally: Individualism, Investor Attention, and the Cross Section of Expected Stock Returns," Management Science, INFORMS, vol. 64(12), pages 5807-5831, December.
    19. Mirko Draca & Stephen Machin, 2015. "Crime and Economic Incentives," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 389-408, August.
    20. 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.
    21. 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.
    22. Brushwood, James & Dhaliwal, Dan & Fairhurst, Douglas & Serfling, Matthew, 2016. "Property crime, earnings variability, and the cost of capital," Journal of Corporate Finance, Elsevier, vol. 40(C), pages 142-173.
    23. Bradrania, Reza & Veron, Jose Francisco, 2023. "The beta anomaly in the Australian stock market and the lottery demand," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    24. Mikesell, John L., 1994. "State Lottery Sales and Economic Activity," National Tax Journal, National Tax Association;National Tax Journal, vol. 47(1), pages 165-171, March.
    25. Dimson, Elroy, 1979. "Risk measurement when shares are subject to infrequent trading," Journal of Financial Economics, Elsevier, vol. 7(2), pages 197-226, June.
    26. 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.
    27. Berggrun, Luis & Cardona, Emilio & Lizarzaburu, Edmundo, 2019. "Extreme daily returns and the cross-section of expected returns: Evidence from Brazil," Journal of Business Research, Elsevier, vol. 102(C), pages 201-211.
    28. Dai, Bochuan & Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2023. "Lottery stocks and stop-loss rules," Global Finance Journal, Elsevier, vol. 56(C).
    29. Aboulamer, Anas & Kryzanowski, Lawrence, 2016. "Are idiosyncratic volatility and MAX priced in the Canadian market?," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 20-36.
    30. Piccotti, Louis R. & Wang, Heng, 2023. "Informed trading in the options market surrounding data breaches," Global Finance Journal, Elsevier, vol. 56(C).
    31. 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.
    32. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    33. Maarten J. Voors & Eleonora E. M. Nillesen & Philip Verwimp & Erwin H. Bulte & Robert Lensink & Daan P. Van Soest, 2012. "Violent Conflict and Behavior: A Field Experiment in Burundi," American Economic Review, American Economic Association, vol. 102(2), pages 941-964, April.
    34. Zhong, Angel & Gray, Philip, 2016. "The MAX effect: An exploration of risk and mispricing explanations," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 76-90.
    35. Jegadeesh, Narasimhan, 1990. "Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    36. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    37. 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.
    38. Michael Callen & Mohammad Isaqzadeh & James D. Long & Charles Sprenger, 2014. "Violence and Risk Preference: Experimental Evidence from Afghanistan," American Economic Review, American Economic Association, vol. 104(1), pages 123-148, January.
    39. Annaert, Jan & De Ceuster, Marc & Verstegen, Kurt, 2013. "Are extreme returns priced in the stock market? European evidence," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3401-3411.
    40. Kumar, Alok & Page, Jeremy K. & Spalt, Oliver G., 2011. "Religious beliefs, gambling attitudes, and financial market outcomes," Journal of Financial Economics, Elsevier, vol. 102(3), pages 671-708.
    41. Tse-Chun Lin & Xin Liu, 2018. "Skewness, Individual Investor Preference, and the Cross-section of Stock Returns [Illiquidity and stock returns: cross-section and time-series effects]," Review of Finance, European Finance Association, vol. 22(5), pages 1841-1876.
    42. Bradrania, Reza & Veron, Jose Francisco & Wu, Winston, 2023. "The beta anomaly and the quality effect in international stock markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    43. 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.
    44. Eric D. Gould & Bruce A. Weinberg & David B. Mustard, 2002. "Crime Rates And Local Labor Market Opportunities In The United States: 1979-1997," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 45-61, February.
    45. Ryan Brown & Verónica Montalva & Duncan Thomas & Andrea Velásquez, 2019. "Impact of Violent Crime on Risk Aversion: Evidence from the Mexican Drug War," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 892-904, December.
    46. Stefan Zeume, 2017. "Bribes and Firm Value," The Review of Financial Studies, Society for Financial Studies, vol. 30(5), pages 1457-1489.
    47. Nguyen, Hung T. & Truong, Cameron, 2018. "When are extreme daily returns not lottery? At earnings announcements!," Journal of Financial Markets, Elsevier, vol. 41(C), pages 92-116.
    48. Ehrlich, Isaac, 1973. "Participation in Illegitimate Activities: A Theoretical and Empirical Investigation," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 521-565, May-June.
    49. Alharbi, Samar & Atawnah, Nader & Al Mamun, Md & Ali, Muhammad Jahangir, 2022. "Local culture and tax avoidance: Evidence from gambling preference behavior," Global Finance Journal, Elsevier, vol. 52(C).
    50. Mishra, Sandeep & Lalumière, Martin, 2009. "Is the crime drop of the 1990s in Canada and the USA associated with a general decline in risky and health-related behavior?," Social Science & Medicine, Elsevier, vol. 68(1), pages 39-48, January.
    51. Anand, Amber & Gatchev, Vladimir A. & Madureira, Leonardo & Pirinsky, Christo A. & Underwood, Shane, 2011. "Geographic proximity and price discovery: Evidence from NASDAQ," Journal of Financial Markets, Elsevier, vol. 14(2), pages 193-226, May.
    52. Bali, Turan G. & Brown, Stephen J. & Murray, Scott & Tang, Yi, 2017. "A Lottery-Demand-Based Explanation of the Beta Anomaly," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(6), pages 2369-2397, December.
    53. Wim Bernasco & Richard Block & Stijn Ruiter, 2013. "Go where the money is: modeling street robbers' location choices," Journal of Economic Geography, Oxford University Press, vol. 13(1), pages 119-143, January.
    54. Fong, Wai Mun & Toh, Benjamin, 2014. "Investor sentiment and the MAX effect," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 190-201.
    55. Soo Hong Chew & Haoming Liu & Alberto Salvo, 2021. "Adversity-hope hypothesis: Air pollution raises lottery demand in China," Journal of Risk and Uncertainty, Springer, vol. 62(3), pages 247-280, June.
    56. 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.
    57. 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.
    58. Seif, Mostafa & Docherty, Paul & Shamsuddin, Abul, 2018. "Limits to arbitrage and the MAX anomaly in advanced emerging markets," Emerging Markets Review, Elsevier, vol. 36(C), pages 95-109.
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    More about this item

    Keywords

    MAX; Lottery-related anomalies; Crime; Property crime; Skewness; Expected returns;
    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
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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