Published April 17, 2026 | Version v1

Finfluencers and Retail Investment Behaviour: Credibility, Cognitive Bias, and Regulatory Implications

Description

The proliferation of financial influencers—commonly termed finfluencers—on social media platforms has created a new paradigm in how retail investors access, evaluate, and act upon financial information. Drawing on a structured survey of 51 active retail investors in an emerging-market context, this study examines the mechanisms through which finfluencer content shapes individual investment decisions, with particular attention to perceived credibility, parasocial trust, cognitive-bias activation (fear of missing out, herding, overconfidence, and anchoring), and the moderating role of financial literacy. Anchored in Behavioral Finance Theory (Kahneman & Tversky, 1979) and Kelman's (1958) Social Influence framework, the findings reveal that finfluencer exposure significantly amplifies cognitive biases and increases trading frequency, even among respondents with advanced academic qualifications. Notably, 64.2% of participants favor mandatory professional certification for financial influencers, signaling public readiness for tighter oversight. The study contributes empirical evidence to an underexplored intersection of digital communication and retail finance in developing economies, and offers actionable implications for regulators, financial institutions, and platform designers.

Files

Finfluencers and Retail Investment Behaviour Credibility, Cognitive Bias, and Regulatory Implications.pdf

Additional details

Dates

Submitted
2026-04-17
The democratization of financial information through social media represents one of the most consequential shifts in retail finance over the past decade. Where institutional brokers and licensed analysts once controlled the flow of investment guidance, a new class of digital opinion leaders—financial influencers, or finfluencers—now commands vast audiences on Instagram, YouTube, X (formerly Twitter), and TikTok. These individuals, often lacking formal credentials yet possessing substantial followings, translate complex market dynamics into accessible narratives that resonate with younger, mobile-first investors.

References

  • 1. Banerjee, A. V. (1992). A simple model of herd behavior. The Quarterly Journal of Economics, 107(3), 797–817. https://doi.org/10.2307/2118364 2. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261–292. https://doi.org/10.1162/003355301556400 3. Cao, J., & Liu, B. (2022). Social media and stock market anomalies: Evidence from GameStop. Journal of Financial Markets, 58, 100–123. https://doi.org/10.1016/j.finmar.2022.100123 4. Casalo, L. V., Flavian, C., & Ibanez-Sanchez, S. (2018). Influencers on Instagram: Antecedents and consequences of opinion leadership. Journal of Business Research, 117, 510–519. https://doi.org/10.1016/j.jbusres.2018.07.005 5. CFA Institute. (2024). Finfluencers: Understanding retail investor engagement with social media financial content. CFA Institute Research Foundation. 6. Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155 7. Dixon, C. (2022). The finfluencer problem: Regulatory gaps in social media financial promotion. Journal of Financial Regulation, 8(2), 177–204. https://doi.org/10.1093/jfr/fjac007 8. European Securities and Markets Authority. (2024). Social media and retail investors: Finfluencers, price movements, and investor protection. ESMA Technical Report. 9. Freberg, K., Graham, K., McGaughey, K., & Freberg, L. A. (2011). Who are the social media influencers? A study of public perceptions of personality. Public Relations Review, 37(1), 90–92. https://doi.org/10.1016/j.pubrev.2010.11.001 10. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185 11. Kelman, H. C. (1958). Compliance, identification, and internalization: Three processes of attitude change. Journal of Conflict Resolution, 2(1), 51–60. https://doi.org/10.1177/002200275800200106 12. Lee, J., & Kim, S. (2022). Algorithmic amplification of financial content on social media: Engagement-based ranking and the rise of speculative narratives. New Media and Society, 24(8), 1876–1894. https://doi.org/10.1177/14614448211052145 13. Lim, X. J., Radzol, A. R. M., Cheah, J., & Wong, M. W. (2017). The impact of social media influencers on purchase intention and the mediation effect of customer attitude. Asian Journal of Business Research, 7(2), 19–36. https://doi.org/10.14707/ajbr.170035 14. Martinez, L. (2021). Finfluencers and the post-crisis trust deficit. Media, Culture and Society, 43(6), 1102–1119. https://doi.org/10.1177/01634437211002345 15. Pandey, A., Mishra, D., & Sharma, N. (2025). YouTube finfluencers and equity investment attitudes: Credibility, relatability, and content clarity as determinants of influence. Journal of Retailing and Consumer Services, 82, 103–117. https://doi.org/10.1016/j.jretconser.2024.103117 16. Warkulat, S., Meier, F., & Schmitt, J. (2024). Social media attention and retail investor trading: Matched evidence from individual trading accounts. Review of Financial Studies, 37(4), 1234–1268. https://doi.org/10.1093/rfs/hhad079