Lottery-type stocks in Brazil Evidence from a survivorship-bias-corrected universe

Main Article Content

Thiago de Sousa Barros
https://orcid.org/0000-0001-7739-9150

Abstract

I examine the pricing implications of lottery-type stock characteristics in Brazil’s equity market (B3) over the period 2002–2024, a setting that differs markedly from the United States in institutional development, retail investor participation, and macroeconomic volatility. Following an established lottery-stock identification framework—classifying stocks as “lottery” if they simultaneously fall below the median in price, above the median in idiosyncratic volatility, and above the median in return skewness (LSCORE = 3)—I document a result consistent with prior U.S. evidence: lottery stocks in Brazil underperform the strict LSCORE = 0 benchmark portfolio by −1.259% per month (−14.11% annually) on a Carhart four-factor risk-adjusted basis (t = −5.75, p < 0.001), with |t| above the 3.0 threshold. The discount remains economically and statistically significant under a Carhart-plus-IML five-factor specification (α = −1.249% per month, t = −5.70), is negative in each of four non-overlapping subperiods (2002–2008, 2009–2015, 2016–2019, 2020–2024), and is concentrated among less liquid stocks where arbitrage is costliest. A key methodological contribution is to quantify the selection induced by a continuously observed-firms filter: restricting the universe to firms that report returns in every calendar year of the sample inflates the lottery alpha by approximately 0.37 percentage points per month, attenuating the estimated discount by roughly 30%. These findings are consistent with cumulative prospect theory and limits-to-arbitrage theory.

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How to Cite
de Sousa Barros, T. (2026). Lottery-type stocks in Brazil: Evidence from a survivorship-bias-corrected universe. Brazilian Review of Finance, 24(1), e202613. https://doi.org/10.12660/rbfin.v24n1.2026.98265
Section
Papers
Author Biography

Thiago de Sousa Barros, Universidade Federal de Ouro Preto

NA

References

Amihud, Y. 2002. Illiquidity and stock returns: Cross-section and time-series effects, Journal of Financial Markets, 5, 31–56. https://doi.org/10.1016/S1386-4181(01)00024-6 DOI: https://doi.org/10.1016/S1386-4181(01)00024-6

Ang, A., Hodrick, R. J., Xing, Y. & Zhang, X. 2006. The cross-section of volatility and expected returns, Journal of Finance, 61, 259–299. https://doi.org/10.1111/j.1540-6261.2006.00836.x DOI: https://doi.org/10.1111/j.1540-6261.2006.00836.x

Ang, A., Hodrick, R. J., Xing, Y. & Zhang, X. 2009. High idiosyncratic volatility and low returns: International and further U.S. evidence, Journal of Financial Economics, 91, 1–23. https://doi.org/10.1016/j.jfineco.2007.12.005 DOI: https://doi.org/10.1016/j.jfineco.2007.12.005

Bali, T. G., Brown, S. J., Murray, S. & Tang, Y. 2017. A lottery-demand-based explanation of the beta anomaly, Journal of Financial and Quantitative Analysis, 52, 2369–2397. https://doi.org/10.1017/s0022109017000928 DOI: https://doi.org/10.1017/S0022109017000928

Bali, T. G., Cakici, N. & Whitelaw, R. F. 2011. Maxing out: Stocks as lotteries and the cross-section of expected returns, Journal of Financial Economics, 99, 427–446. https://doi.org/10.1016/j.jfineco.2010.08.014 DOI: https://doi.org/10.1016/j.jfineco.2010.08.014

Barber, B. M., Huang, X., Odean, T. & Schwarz, C. 2022. Attention-induced trading and returns: Evidence from Robinhood users, Journal of Finance, 77, 3141–3190. https://doi.org/10.1111/jofi.13183 DOI: https://doi.org/10.1111/jofi.13183

Barber, B. M. & Odean, T. 2000. Trading is hazardous to your wealth: The common stock investment performance of individual investors, Journal of Finance, 55, 773–806. https://doi.org/10.1111/0022-1082.00226 DOI: https://doi.org/10.1111/0022-1082.00226

Barber, B. M. & Odean, T. 2001. Boys will be boys: Gender, overconfidence, and common stock investment, Quarterly Journal of Economics, 116, 261–292. https://doi.org/10.1162/003355301556400 DOI: https://doi.org/10.1162/003355301556400

Barberis, N. 2018. Psychology-Based Models of Asset Prices and Trading Volume, in B. D. Bernheim, S. DellaVigna and D. Laibson (eds), Handbook of Behavioral Economics, Elsevier, Amsterdam, pp. 79–175. https://doi.org/10.1016/bs.hesbe.2018.07.001 DOI: https://doi.org/10.1016/bs.hesbe.2018.07.001

Barberis, N. & Huang, M. 2008. Stocks as lotteries: The implications of probability weighting for security prices, American Economic Review, 98, 2066–2100. https://doi.org/10.1257/aer.98.5.2066 DOI: https://doi.org/10.1257/aer.98.5.2066

Barberis, N., Mukherjee, A. & Wang, B. 2016. Prospect theory and stock returns: An empirical test, Review of Financial Studies, 29, 3068–3107. https://doi.org/10.1093/rfs/hhw049 DOI: https://doi.org/10.1093/rfs/hhw049

Bekaert, G., Harvey, C. R. & Lundblad, C. 2007. Liquidity and expected returns: Lessons from emerging markets, Review of Financial Studies, 20, 1783–1831. https://doi.org/10.1093/rfs/hhm030 DOI: https://doi.org/10.1093/rfs/hhm030

Boyer, B., Mitton, T. & Vorkink, K. 2010. Expected idiosyncratic skewness, Review of Financial Studies, 23, 169–202. https://doi.org/10.1093/rfs/hhp041 DOI: https://doi.org/10.1093/rfs/hhp041

Brunnermeier, M. K., Gollier, C. & Parker, J. A. 2007. Optimal beliefs, asset prices, and the preference for skewed returns, American Economic Review, 97, 159–165. https://doi.org/10.1257/aer.97.2.159 DOI: https://doi.org/10.1257/aer.97.2.159

Cakici, N., Fabozzi, F. J. & Tan, S. 2013. Size, value, and momentum in emerging market stock returns, Emerging Markets Review, 16, 46–65. https://doi.org/10.1016/j.ememar.2013.03.001 DOI: https://doi.org/10.1016/j.ememar.2013.03.001

Carhart, M. M. 1997. On persistence in mutual fund performance, Journal of Finance, 52, 57–82. https://doi.org/10.1111/j.1540-6261.1997.tb03808.x DOI: https://doi.org/10.1111/j.1540-6261.1997.tb03808.x

Conrad, J., Dittmar, R. F. & Ghysels, E. 2013. Ex ante skewness and expected stock returns, Journal of Finance, 68, 85–124. https://doi.org/10.1111/j.1540-6261.2012.01795.x DOI: https://doi.org/10.1111/j.1540-6261.2012.01795.x

Da, Z., Engelberg, J. & Gao, P. 2011. In search of attention, Journal of Finance, 66, 1461–1499. https://doi.org/10.1111/j.1540-6261.2011.01679.x DOI: https://doi.org/10.1111/j.1540-6261.2011.01679.x

Eraker, B. & Ready, M. 2015. Do investors overpay for stocks with lottery-like payoffs? An examination of the returns of OTC stocks, Journal of Financial Economics, 115, 486–504. https://doi.org/10.1016/j.jfineco.2014.11.002 DOI: https://doi.org/10.1016/j.jfineco.2014.11.002

Fama, E. F. & French, K. R. 1993. Common risk factors in the returns on stocks and bonds, Journal of Financial Economics, 33, 3–56. https://doi.org/10.1016/0304-405X(93)90023-5 DOI: https://doi.org/10.1016/0304-405X(93)90023-5

Fama, E. F. & French, K. R. 2015. A five-factor asset pricing model, Journal of Financial Economics, 116, 1–22. https://doi.org/10.1016/j.jfineco.2014.10.010 DOI: https://doi.org/10.1016/j.jfineco.2014.10.010

Fama, E. F. & MacBeth, J. D. 1973. Risk, return, and equilibrium: Empirical tests, Journal of Political Economy, 81, 607–636. https://doi.org/10.1086/260061 DOI: https://doi.org/10.1086/260061

Fehr-Duda, H. & Epper, T. 2012. Probability and risk: Foundations and economic implications of probability-dependent risk preferences, Annual Review of Economics, 4, 567–593. https://doi.org/10.1146/annurev-economics-080511-110950 DOI: https://doi.org/10.1146/annurev-economics-080511-110950

Friedman, M. & Savage, L. J. 1948. The utility analysis of choices involving risk, Journal of Political Economy, 56, 279–304. https://doi.org/10.1086/256692 DOI: https://doi.org/10.1086/256692

Green, T. C. & Hwang, B. H. 2012. Initial public offerings as lotteries: Skewness preference and first-day returns, Management Science, 58, 432–444. https://doi.org/10.1287/mnsc.1110.1431 DOI: https://doi.org/10.1287/mnsc.1110.1431

Han, B. & Kumar, A. 2013. Speculative retail trading and asset prices, Journal of Financial and Quantitative Analysis, 48, 377–404. https://doi.org/10.1017/s0022109013000100 DOI: https://doi.org/10.1017/S0022109013000100

Harvey, C. R., Liu, Y. & Zhu, H. 2016. …and the cross-section of expected returns, Review of Financial Studies, 29, 5–68. https://doi.org/10.1093/rfs/hhv059 DOI: https://doi.org/10.1093/rfs/hhv059

Hou, K., Xue, C. & Zhang, L. 2020. Replicating anomalies, Review of Financial Studies, 33, 2019–2133. https://doi.org/10.1093/rfs/hhy131 DOI: https://doi.org/10.1093/rfs/hhy131

Kimura, H. 2003. Aspectos comportamentais associados às reações do mercado de capitais, RAE-eletrônica, 2(1), 1–14. https://doi.org/10.1590/S1676-56482003000100007 DOI: https://doi.org/10.1590/S1676-56482003000100007

Kumar, A. 2009. Who gambles in the stock market?, Journal of Finance, 64, 1889–1933. https://doi.org/10.1111/j.1540-6261.2009.01483.x DOI: https://doi.org/10.1111/j.1540-6261.2009.01483.x

Kumar, A., Page, J. K. & Spalt, O. G. 2011. Religious beliefs, gambling attitudes, and financial market outcomes, Journal of Financial Economics, 102, 671–708. https://doi.org/10.1016/j.jfineco.2011.07.001 DOI: https://doi.org/10.1016/j.jfineco.2011.07.001

Leippold, M., Wang, Q. & Zhou, W. 2022. Machine learning in the Chinese stock market, Journal of Financial Economics, 145, 64–82. https://doi.org/10.1016/j.jfineco.2021.08.017 DOI: https://doi.org/10.1016/j.jfineco.2021.08.017

Merton, R. C. 1987. A simple model of capital market equilibrium with incomplete information, Journal of Finance, 42, 483–510. https://doi.org/10.1111/j.1540-6261.1987.tb04565.x DOI: https://doi.org/10.1111/j.1540-6261.1987.tb04565.x

Mussa, A., Famá, R. & dos Santos, J. O. 2012. A adição do fator de risco momento ao modelo de precificação de ativos dos três fatores de Fama e French aplicado ao mercado acionário brasileiro, REGE - Revista de Gestão, 19(3), 447–464. https://doi.org/10.5700/rege473 DOI: https://doi.org/10.5700/rege473

Nartea, G. V., Ward, B. D. & Yao, L. J. 2011. Idiosyncratic volatility and cross-sectional stock returns in Southeast Asian stock markets, Accounting & Finance, 51(4), 1031–1054. https://doi.org/10.1111/j.1467-629X.2010.00384.x DOI: https://doi.org/10.1111/j.1467-629X.2010.00384.x

Newey, W. K. & West, K. D. 1987. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix, Econometrica, 55, 703–708. https://doi.org/10.2307/1913610 DOI: https://doi.org/10.2307/1913610

Petersen, M. A. 2009. Estimating standard errors in finance panel data sets: Comparing approaches, Review of Financial Studies, 22, 435–480. https://doi.org/10.1093/rfs/hhn053 DOI: https://doi.org/10.1093/rfs/hhn053

Roll, R. 1984. A simple implicit measure of the effective bid-ask spread in an efficient market, Journal of Finance, 39(4), 1127–1139. https://doi.org/10.1111/j.1540-6261.1984.tb03897.x DOI: https://doi.org/10.1111/j.1540-6261.1984.tb03897.x

Shleifer, A. & Vishny, R. W. 1997. The limits of arbitrage, Journal of Finance, 52, 35–55. https://doi.org/10.1111/j.1540-6261.1997.tb03807.x DOI: https://doi.org/10.1111/j.1540-6261.1997.tb03807.x

Stambaugh, R. F. & Yuan, Y. 2017. Mispricing factors, Review of Financial Studies, 30, 1270–1315. https://doi.org/10.1093/rfs/hhw107 DOI: https://doi.org/10.1093/rfs/hhw107

Stambaugh, R. F., Yu, J. & Yuan, Y. 2015. Arbitrage asymmetry and the idiosyncratic volatility puzzle, Journal of Finance, 70, 1903–1948. https://doi.org/10.1111/jofi.12286 DOI: https://doi.org/10.1111/jofi.12286

Tversky, A. & Kahneman, D. 1992. Advances in prospect theory: Cumulative representation of uncertainty, Journal of Risk and Uncertainty, 5, 297–323. https://doi.org/10.1007/bf00122574 DOI: https://doi.org/10.1007/BF00122574

Varga, G. & Wengert, M. 2011. A indústria de fundos de investimentos no Brasil, Revista de Economia e Administração, 10, 66–109. https://doi.org/10.11132/rea.2010.361 DOI: https://doi.org/10.11132/rea.2010.361

Walkshäusl, C. 2013. The high returns to low volatility stocks are actually a premium on high quality firms, Review of Financial Economics, 22(4), 180–186. https://doi.org/10.1016/j.rfe.2013.06.001 DOI: https://doi.org/10.1016/j.rfe.2013.06.001

Welch, I. 2022. The wisdom of the Robinhood crowd, Journal of Finance, 77(3), 1489–1527. https://doi.org/10.1111/jofi.13128 DOI: https://doi.org/10.1111/jofi.13128