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

Danish Choudhary, Dr. Renuka S · Zenodo (CERN)
Zenodo (CERN) · Papers · License: Open Access
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makingregulation.socialmedia
finfluencers; social media; investment decision-making; behavioral finance; cognitive bias; retail investors; regulation.

Finfluencers and Retail Investment Behaviour: Credibility, Cognitive Bias, and Regulatory Implications | Zenodo Skip to main Communities My dashboard Log in Sign up Published April 17, 2026 | Version v1 Publication Open Finfluencers and Retail Investment Behaviour: Credibility, Cognitive Bias, and Regulatory Implications Authors/Creators Danish Choudhary, Dr. Renuka S 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 Files (897.5 kB) Name Size Download all Finfluencers and Retail Investment Behaviour Credibility, Cognitive Bias, and Regulatory Implications.pdf md5:656232c270c0c3e05f2b9fdbd31b94b0 897.5 kB Preview Download 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 662 Views 190 Downloads Show more details All versions This version Views Total views 662 662 Downloads Total downloads 190 190 Data volume Total data volume 193.0 MB 193.0 MB More info on how stats are collected.... Versions External resources Indexed in OpenAIRE Communities Keywords and subjects Keywords finfluencers; social media; investment decision-making; behavioral finance; cognitive bias; retail investors; regulation. Details DOI DOI Badge DOI 10.5281/zenodo.19635873 Markdown [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.19635873.svg)](https://doi.org/10.5281/zenodo.19635873) reStructuredText .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.19635873.svg :target: https://doi.org/10.5281/zenodo.19635873 HTML <a href="https://doi.org/10.5281/zenodo.19635873"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.19635873.svg" alt="DOI"></a> Image URL https://zenodo.org/badge/DOI/10.5281/zenodo.19635873.svg Target URL https://doi.org/10.5281/zenodo.19635873 Resource type Publication Publisher Zenodo Published in Finfluencers and Retail Investment Behaviour: Credibility, Cognitive Bias, and Regulatory Implications, 04(4), 1-6, ISSN: 3107-6696, 2026. Languages English Rights License Creative Commons Attribution 4.0 International The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. 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