Retail Investors in DeFi-Based Stock Markets: Fairness, Transparency, and Manipulation Risks
DOI:
https://doi.org/10.48165/tjmitm.2026.16.01.09Abstract
DeFi-based stock markets extend decentralized finance infrastructures to tokenized and synthetic equity exposures, raising fresh questions about fairness, transparency, and protection for small investors in emerging markets. This study investigates how Indian retail investors perceive governance features of DeFi platforms offering India- linked tokenized stocks and how these perceptions relate to trust and intention to continue investing. Using a quantitative, cross sectional online survey of 250 retail investors with DeFi experience, the research measures perceived fairness, transparency, manipulation risk, trust and participation intention through multi-item Likert scales and analyses relationships using descriptive statistics, correlations and multiple regression. Findings indicate moderate levels of perceived fairness, transparency and trust, alongside non-trivial concerns about manipulation risk. However, perceived fairness and transparency show only weak, statistically insignificant effects on trust, manipulation risk has a marginal negative association, and trust does not significantly predict intention to continue investing. These results suggest that other drivers such as returns, liquidity, user experience and regulatory developments may dominate governance perceptions in shaping behaviour. Limitations include non-probability sampling, self-reported measures, and a single country, cross-sectional design within a rapidly evolving DeFi environment. This study offers tentative empirical evidence about retail involvement in equity markets that are built on DeFi, and outlines governance, regulatory, and investor education mechanisms to enhance enforcement of market integrity and investor protection.
References
Aitken, M. J., Aspris, A., Foley, S., & Harris, F. H. de B. (2018). Market fairness: The poor country cousin of market efficiency. Journal of Business Ethics, 147(1), 5–23. https://doi.org/10.1007/s10551-015-2964-y
Ballis, A., & Verousis, T. (2022). Behavioural finance and cryptocurrencies. Review of Behavioral Finance, 14(4), 545–562. https://doi.org/10.1108/RBF-11-2021-0256
Baeckström, Y., Jalan, A., & Matkovskyy, R. (2025). Individual investor trust and cryptocurrency participation: Evidence from three Nordic countries. The Journal of Technology Transfer. Advance online publication. https://doi.org/10.1007/s10961-025-10276-w
Boone, H. N., Jr., & Boone, D. A. (2012). Analyzing Likert data. Journal of Extension, 50(2), Article 2TOT2.
Caldarelli, G., & Ellul, J. (2021). The blockchain oracle problem in decentralized finance—A multivocal approach. Applied Sciences, 11(16), 7572. https://doi.org/10.3390/app11167572
Chen, Y., & Bellavitis, C. (2020). Blockchain disruption and decentralized finance: The rise of decentralized business models. Journal of Business Venturing Insights, 13, e00151. https://doi.org/10.1016/j.jbvi.2019.e00151
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.
Cong, L. W., Li, Y., & Wang, N. (2023). Crypto wash trading. Management Science, 69(2), 574–604. https://doi.org/10.1287/mnsc.2021.02709
Field, A. P. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). Sage.
Gliem, J. A., & Gliem, R. R. (2003). Calculating, interpreting, and reporting Cronbach’s alpha reliability coefficient for Likert-type scales. In Proceedings of the 2003 Midwest Research-to-Practice Conference in Adult, Continuing, and Community Education (pp. 82–88). The Ohio State University.
Gramlich, V., Guggenberger, T., Principato, M., Schellinger, B., & Urbach, N. (2023). A multivocal literature review of decentralized finance: Current knowledge and future research avenues. Electronic Markets, 33(1), Article 11. https://doi.org/10.1007/s12525-023-00637-4
Hägele, S. (2024). Centralized exchanges vs decentralized exchanges in cryptocurrency markets: A systematic literature review. Electronic Markets, 34, Article 33. https://doi.org/10.1007/s12525-024-00714-2
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433. https://doi.org/10.1007/s11747-011-0261-6
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Kaur, M., Jain, J., & Sood, K. (2023). “All are investing in crypto, I fear of being missed out”: Examining the influence of herding, loss aversion, and overconfidence in the cryptocurrency market with the mediating effect of FOMO. Quality & Quantity, 58, 2237–2263. https://doi.org/10.1007/s11135-023-01739-z
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
Lambert, T., Liebau, D., & Roosenboom, P. (2022). Security token offerings. Small Business Economics, 59, 299–325. https://doi.org/10.1007/s11187-021-00539-9
Le Pennec, G., Fiedler, I., & Ante, L. (2021). Wash trading at cryptocurrency exchanges. Finance Research Letters, 43, 101982. https://doi.org/10.1016/j.frl.2021.101982
Makarov, I., & Schoar, A. (2022). Cryptocurrencies and decentralized finance (DeFi). Brookings Papers on Economic Activity, 2022(1), 141–215. https://doi.org/10.1353/eca.2022.0014
Nguyen, L., & Nguyen, P. (2024). Determinants of cryptocurrency and decentralized finance adoption: A configurational exploration. Technological Forecasting and Social Change, 201, 123244. https://doi.org/10.1016/j.techfore.2024.123244
Sá da Costa, P. R., & Farkas, W. (2023). Deciphering DeFi: A comprehensive analysis and visualization of risks in decentralized finance. Journal of Risk and Financial Management, 16(10), 454. https://doi.org/10.3390/jrfm16100454
Salami, I. (2021). Challenges and approaches to regulating decentralized finance. American Journal of International Law Unbound, 115, 425–429. https://doi.org/10.1017/aju.2021.66
Schär, F. (2021). Decentralized finance: On blockchain- and smart contract-based financial markets. Federal Reserve Bank of St. Louis Review, 103(2), 153–174. https://doi.org/10.20955/r.103.153-74
Sood, K., Pathak, P., Jain, J., & Gupta, S. (2023). Gauging investors’ investment decisions in the crypto market through the PRISM of behavioral biases: A fuzzy AHP approach. International Journal of Emerging Markets, 20(4), 1465–1486. https://doi.org/10.1108/IJOEM-02-2022-0263
Sood, K., Sharma, V., & Kumar, R. (2024). Unveiling risks in decentralized finance: A systematic literature review. In ICETSBP 2024: Advances in Business Information Systems and Analytics (Conference proceedings). https://doi.org/10.2991/978-94-6463-544-7_21
Steinmetz, F., von Meduna, M., Ante, L., & Fiedler, I. (2021). Ownership, uses and perceptions of cryptocurrency: Results from a population survey. Technological Forecasting and Social Change, 173, 121073. https://doi.org/10.1016/j.techfore.2021.121073
Victor, F., & Weintraud, A. M. (2021). Detecting and quantifying wash trading on decentralized cryptocurrency exchanges. In Proceedings of the Web Conference 2021 (WWW ’21) (pp. 23–32). ACM. https://doi.org/10.1145/3442381.3449824
Zetzsche, D. A., Arner, D. W., & Buckley, R. P. (2020). Decentralized finance. Journal of Financial Regulation, 6(2), 172–203. https://doi.org/10.1093/jfr/fjaa010
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