This study aims to investigate the behavioural characteristics of lottery-featured stocks (LFS) in BRIC stock markets (Brazil, Russia, India and China) from the perspective of behavioural finance. Employing a top–bottom tercile portfolio approach, the research focuses on lottery feature stocks alongside the index with expected stock returns under varying economic conditions, such as environmental, social and governance (ESG), economic growth and unemployment rate. The data for this investigation were meticulously collected from BRIC country’s stock markets, spanning from January 1993 to December 2021. The findings support the predictions of the prospect theory, suggesting that investors perceive companies with high idiosyncratic skewness as riskier and demand a higher risk premium for holding these stocks in Russia and Brazil. The results indicate a consistent negative relationship between Brazil and Russia’s stock returns and lottery features. The study also highlights the importance of considering idiosyncratic risk in investment decisions and sheds light on why investors demand higher expected returns. The findings suggest that future research should explore the robustness of this relationship across different periods and countries to better understand the economic significance of lottery features stocks and indices with expected stock returns.
AharoniG., GrundyB., & ZengQ. (2013). Stock returns and the Miller Modigliani valuation formula: Revisiting the Fama–French analysis. Journal of Financial Economics, 110(2), 347–357.
2.
AkbariM., Hooshmand ChaijaniM., AletahaS. H., HatamiM., Chathurika GamageT., & TajeddiniK. (2025). Boosting employee citizenship behavior through internal marketing efforts: Exploring the influence of perceived value. Interdisciplinary Journal of Management Studies. https://doi.org/10.22059/ijms.2025.381746.677001”10.22059/ijms.2025.381746.677001
3.
BaliT. G., CakiciN., & WhitelawR. F. (2011). Maxing out: Stocks as lotteries and the cross-section of expected returns. Journal of Financial Economics, 99(2), 427–446. https://doi.org/https://doi.org/10.1016/j.jfineco.2010.08.014
BengitözP., & UmutluM. (2023). Are return predictors of industrial equity indexes common across regions?Journal of Asset Management, 24(5), 396–418. https://doi.org/10.1057/s41260-023-00313-4
6.
ByunS.-J., & KimD.-H. (2016). Gambling preference and individual equity option returns. Journal of Financial Economics, 122(1), 155–174. https://doi.org/10.1016/j.jfineco.2016.06.004
7.
CalvetL. E., & SodiniP. (2014). Twin picks: Disentangling the determinants of risk-taking in household portfolios. The Journal of Finance, 69(2), 867–906. https://doi.org/10.1111/jofi.12125
8.
ChanY.-C., & ChuiA. C. (2016). Gambling in the Hong Kong stock market. International Review of Economics & Finance, 44, 204–218. https://doi.org/10.1016/j.iref.2016.04.012
9.
ChenH., & ZhengM. (2021). IPO underperformance and the idiosyncratic risk puzzle. Journal of Banking & Finance, 131, 106190. https://doi.org/10.1016/j.jbankfin.2021.106190
10.
ChenW., TajeddiniK., RattenV., & TabariS. (2019). Educational immigrants: Evidence from Chinese young entrepreneurs in the UK. Journal of Enterprising Communities: People and Places in the Global Economy, 13(1/2), 196–215. https://doi:10.1108/JEC-11-2018-0093
11.
DelfabbroP., KingD. L., & WilliamsJ. (2021). The psychology of cryptocurrency trading: Risk and protective factors. Journal of Behavioral Addictions, 10(2), 201–207. https://doi.org/https://doi.org/10.1556/2006.2021.00037
12.
ElyasianiE., GambarelliL., & MuzzioliS. (2021). The skewness index: uncovering the relationship with volatility and market returns. Applied Economics, 53(31), 3619–3635. https://doi.org/10.1080/00036846.2021.1884837
13.
FalkenströmL., & OlssonJ. (2023). Does ESG-score matter to investors? An EU taxonomy perspective. https://hdl.handle.net/2077/77625
14.
FamaE. F., & FrenchK. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3–56. https://doi.org/https://doi.org/10.1016/0304-405X(93)90023-5
15.
FamaE. F., & FrenchK. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1–22. https://doi.org/https://doi.org/10.1016/j.jfineco.2014.10.010
16.
FamaE. F., & FrenchK. R. (2018). Choosing factors. Journal of Financial Economics, 128(2), 234–252. https://doi.org/https://doi.org/10.1016/j.jfineco.2018.02.012
17.
FanM., TangZ., QalatiS. A., TajeddiniK., MaoQ., & BuxA. (2022). Cross-border e-commerce brand internationalization: An online review evaluation based on Kano model. Sustainability, 14(20), 13127. https://doi.org/10.3390/su142013127
18.
FeoG. (2021). Does good ESG guarantee better financial performance? Sustainable finance evolution, challenges and investment perspectives: A quantitative analysis of the electric mobility sector [Master’s thesis]. LUISS Guido Carli University and Paris Dauphine University. https://tesi.luiss.it/32418/1/721501_FEO_GIOVANNI.pdf
19.
FongW., & TohB. (2014). Investor sentiment and the MAX effect. Journal of Banking & Finance, 46, 190–201. https://doi.org/https://doi.org/10.1016/j.jbankfin.2014.05.006
20.
GarciaA. S., Mendes-Da-SilvaW., & OrsatoR. J. (2019). Corporate sustainability, capital markets, and esg performance. In Mendes-Da-SilvaW. (Ed.), Individual behaviors and technologies for financial innovations (pp. 287–309). Springer International Publishing. https://doi.org/10.1007/978-3-319-91911-9_13
21.
GavrilakisN., & FlorosC. (2023). ESG performance, herding behavior and stock market returns: Evidence from Europe. Operational Research, 23(1), 3. https://doi.org/10.1007/s12351-023-00745-1
22.
GianfrateG., KievidT., & van DijkM. (2021). On the resilience of ESG stocks during COVID-19: Global evidence. COVID Economics, 25, 83.
23.
Gibson BrandonR., KruegerP., & SchmidtP. S. (2021). ESG rating disagreement and stock returns. Financial Analysts Journal, 77(4), 104–127.
24.
GuoX., McAleerM., WongW.-K., & ZhuL. (2017). A Bayesian approach to excess volatility, short-term underreaction and long-term overreaction during financial crises. The North American Journal of Economics and Finance, 42, 346–358. https://doi.org/10.1016/j.najef.2017.08.001
25.
HaiH. V., ParkJ. W., TsaiP.-C., & EomC. (2020). Lottery mindset, mispricing and idiosyncratic volatility puzzle: Evidence from the Chinese stock market. The North American Journal of Economics and Finance, 54, 101266. https://doi.org/https://doi.org/10.1016/j.najef.2020.101266
26.
HarveyC. R., & SiddiqueA. (2000). Conditional skewness in asset pricing tests. The Journal of Finance, 55(3), 1263–1295.
27.
HialM. I. M., & TajeddiniK. (2019). Destination functional attributes and tourists’ revisit intention to Sri Lanka’s Pasikuda: A critical role of destination brand equity. In TajeddiniK., RattenV., & MerkelT. (Eds.), Tourism, hospitality and digital transformation. Routledge.
28.
HongL., & ZhouT. (2023). Idiosyncratic volatility in commodity futures markets: measurement and puzzle. Managerial Finance. https://doi.org/10.1108/MF-12-2022-0589
29.
HuangW., LiuQ., RheeS. G., & ZhangL. (2010). Return reversals, idiosyncratic risk, and expected returns. The Review of Financial Studies, 23(1), 147–168. https://doi.org/10.1093/rfs/hhp015
30.
KhemirS., BaccoucheC., & AyadiS. D. (2019). The influence of ESG information on investment allocation decisions. Journal of Applied Accounting Research, 20(4), 458–480. https://doi.org/10.1108/JAAR-12-2017-0141
31.
KölbelJ. F., HeebF., PaetzoldF., & BuschT. (2018). Beyond returns: Investigating the social and environmental impact of sustainable investing. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.328954
32.
La TorreM., MangoF., CafaroA., & LeoS. (2020). Does the ESG index affect stock return? Evidence from the Eurostoxx50. Sustainability, 12(16), 6387.
33.
Lopez-de-SilanesF., McCaheryJ. A., & PudschedlP. C. (2020). ESG performance and disclosure: A cross-country analysis. Singapore Journal of Legal Studies, 217–241. https://search.informit.org/doi/10.3316/agispt.20200715033349
34.
LuoD., ShanX., YanJ., & YanQ. (2023). Sustainable investment under ESG volatility and ambiguity. Economic Modelling, 128, 106471.
35.
MalkielB. G., & XuY. (2002). Idiosyncratic risk and security returns. University of Texas at Dallas. https://personal.utdallas.edu/~yexiaoxu/IVOT_H.PDF
36.
NewallP. W. S., & Weiss-CohenL. (2022). The gamblification of investing: How a new generation of investors is being born to lose. International Journal of Environmental Research and Public Health, 19(9), 5391.
37.
PiraD., AghajaniH., Alizadeh SaniM., & TajeddiniK. (2025). Appropriability model for open innovation in value chain of food and pharmaceutical firms. Journal of Management Accounting and Auditing Knowledge, 15, 217–240. https://doi.org/10.22034/jmaak.2025.23866
38.
PlastunA., BouriE., GuptaR., & JiQ. (2022). Price effects after one-day abnormal returns in developed and emerging markets: ESG versus traditional indices. The North American Journal of Economics and Finance, 59, 101572. https://doi.org/https://doi.org/10.1016/j.najef.2021.101572
39.
SeifM., DochertyP., & ShamsuddinA. (2018). Limits to arbitrage and the MAX anomaly in advanced emerging markets. Emerging Markets Review, 36, 95–109. https://doi.org/https://doi.org/10.1016/j.ememar.2018.03.004
40.
SrikantaP. S., PallottaV., & TajeddiniK. (2023). Global trends in technology startup project development and management: From innovation to startup creation. Springer Nature.
41.
SrikantaP. S., TajeddiniK., & JainV. (2021). Computational management: Applications of computational intelligence in business management. Springer.
42.
StotzO. (2022). Expected and realized returns on stocks with high- and low-ESG exposure. In de JongM. & diBartolomeoD. (Eds.), Risks related to environmental, social and governmental, issues (ESG) (pp. 59–76). Springer. https://doi.org/10.1007/978-3-031-18227-3_6
43.
SultanA. G. (2017). The effect of earnings announcement distraction on individual trading behaviour: An attention-based hypothesis (Master’s thesis). College of Business and Economics, The Australian National University, pp. 6–7.
44.
TajeddiniK. (2014). The effect of organisational structure and hoteliers’ risk proclivity on innovativeness. Asia-Pacific Journal of Management Research and Innovation, 10(1), 1–12. https://doi.org/10.1177/2319510X14529487
45.
TajeddiniK. (2015). Using the integration of disparate antecedents to drive world-class innovation performance: An empirical investigation of Swiss watch manufacturing firms. Tékhne: Review of Applied Management Studies, 13, 34–50.
46.
ThirumalaiN. K. (2022). A study on the awareness level of investors in ESG investing and the impact of non-financial factors in long-term performance of organisations in Indian market. National College of Ireland, Dublin.
47.
TsaiC.-F., ChangJ.-H., & TsaiF.-T. (2021). Lottery preferences and retail short selling. Pacific-Basin Finance Journal, 68, 101611. https://doi.org/https://doi.org/10.1016/j.pacfin.2021.101611
48.
UmutluM. (2019). Does idiosyncratic volatility matter at the global level?The North American Journal of Economics and Finance, 47, 252–268. https://doi.org/10.1016/j.najef.2018.12.015
49.
WalkshäuslC. (2014). The MAX effect: European evidence. Journal of Banking & Finance, 42, 1–10.
50.
YaoS., WangC., CuiX., & FangZ. (2019). Idiosyncratic skewness, gambling preference, and cross-section of stock returns: Evidence from China. Pacific-Basin Finance Journal, 53, 464–483. https://doi.org/10.1016/j.pacfin.2019.01.002
51.
YeC., SongX., & LiangY. (2022). Corporate sustainability performance, stock returns, and ESG indicators: fresh insights from EU member states. Environmental Science and Pollution Research, 29(58), 87680–87691. https://doi.org/10.1007/s11356-022-20789-8
52.
YinX.-N., LiJ.-P., & SuC.-W. (2023). How does ESG performance affect stock returns? Empirical evidence from listed companies in China. Heliyon, 9(5), e16320. https://doi.org/https://doi.org/10.1016/j.heliyon.2023.e16320
53.
YuanJ., ShahS. K., TajeddiniK., GamageT. C., & Acevedo-DuqueÁ. (2025). Unveiling psychosocial factors influencing metaverse-associated app adoption: Acumens from fsQCA Approach. International Journal of Human–Computer Interaction, 1–15. https://doi.org/10.1080/10447318.2025.2482744
54.
ZhangT., SongM., LiK., & LiuZ. (2021). Lottery preference and stock market return: Chinese evidence using daily and provincial data. Applied Economics Letters, 28(18), 1582–1588. https://doi.org/10.1080/13504851.2020.1834496
