Impact of mobile applications on participation of retail investors in Indian stock market
Keywords:
FinTech, mobile apps, retail investors, Robo advisorsAbstract
Over the last few years, Stock markets around the world has witnessed major changes in terms of participation of retail investors. One of the key factors behind these changes is the availability of investing opportunities via online and mobile trading. With reduced transaction cost and ease of access, stock markets have become almost within a reach of hand, especially for retail investors. We find that financial technology has enabled more small investors to enter into the stock market than the large investors because of low cost and ease of access.
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References
Adrian Mitroi, I. S. (2014, Jaunuary). BIASES, ANOMALIES, PSYCHOLOGY OF A LOSS AND INDIVIDUAL
INVESTMENT DECISION MAKING.
Balapour, A., Nikkhah, H. R., & Sabherwal, R. (2020). Mobile application security: Role of perceived privacy as the predictor of security perceptions. International Journal of Information Management, 52(102063), 1-13.
Bergeron, B. (2001). The wireless Web: How to develop and execute a winning wireless strategy. New York, NY: McGraw-Hill.
Brown, M. (2017, September 19). Robo advisors vs. financial advisors-Millennials still prefer real-life. LendEDU. Retrieved from https://lendedu.com/blog/roboadvisors-vs-financial-advisors/
Chaudhry, S. Kulkarni, C.(2021) Design patterns of trading apps and their effects on investing behaviors
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Deloitte, 2019. Robots are here: The rise of robo-advisers in Asia Pacific. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/sg/Documents/financialservices/sea-fsi-robo-advisers- asia-pacific.pdf
https://doi.org/10.1016/j.ijinfomgt.2019.102063
Dr. Syed Tabassum Sultana, D. S. (2012). An Empirical Analysis of Factors Influencing Indian Individual Equity Investors’ Decision Making and Behavior. European Journal of Business and Management, Vol 4, No.18, 2012, 50-61.
Fama, E. F. (1970, May). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 35.
Hamory, J. (2018, January 17). Robo-advisors encouraging millennials to invest, but do they understand how it works? LendEDU. Retrieved from
https://lendedu.com/blog/robo-advisors-attractingmillennials/
InvestorAcademy. (2020, November 20). Best Share Trading Apps in India for 2020:- Online Mobile Trading Android Apps. https://investoracademy.in/best-share-trading-apps/
Kindberg T., Sellen A., Geelhoed E. (2004) Security and Trust in Mobile Interactions: A Study of Users’ Perceptions and Reasoning. In: Davies N., Mynatt E.D., Siio I. (eds) UbiComp 2004: Ubiquitous Computing. UbiComp 2004. Lecture Notes in Computer Science, vol 3205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30119-
Levenson, H. (2016, August 2). 7 Common Reasons Users are Abandoning your App. https://www.webanalyticsworld.net/2016/08/why-usersare-abandoning-your-mobile-app.html/
Lin, M. (2015). Why Investors Are Irrational, According to Behavioral Finance. Liu, J. W. (2015).
Malhotra, S. ( November 2020). Study of features of mobile trading apps: a silver lining of pandemic
Mookerjee, I., Mazumdar, R., & Acharya, N. (2020, May 17). India’s lockdown mints more than a million new stock traders. The Economic Times. https://economictimes.indiatimes.com/markets/stocks/news/i ndias-lockdown-mints-more-than-a-million- new-stocktraders/articleshow/75772315.cms?from=mdr
Rukhaiyar, A. (2020, June 3). Mobile trading surges during lockdown. The Hindu. https://www.thehindu.com/business/mobile-trading-surgesduring-lockdown/article31742088.ece
Singh, G. M. (2019, June 26). An Analysis of Behavioral Biases in Investment Decision-Making. International Journal of Financial Research, Vol. 10, No. 4; 2019, 13. doi:10.5430/ijfr.v10n4p55 Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research, 11(4), 342-365. https://doi.org/10.1287/isre.11.4.342.11872
Welch, I. (2020). Retail raw: Wisdom of the Robinhood crowd and the COVID crisis (NBER Working Paper No. w27866). National Bureau of Economic Research. Http s://www.nber.org/papers/w27866
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