Understanding Behavioural Finance: Investor Psychology and Market Anomalies
DOI:
https://doi.org/10.56741/IISTR.jmsd.001998
Keywords:
Behavioral Finance, Cognitive Biases, Financial Decision-Making, Investor Psychology, Market Anomalies
Abstract
This study explores the evolving field of behavioral finance, focusing on how psychological factors influence investor decision-making and contribute to persistent market anomalies. Unlike traditional financial theories that assume rational behavior and efficient markets, behavioral finance integrates cognitive biases, emotional influences, and social dynamics to explain deviations from expected market outcomes. The research examines key behavioral concepts such as overconfidence, loss aversion, herding, and framing effects, and their implications for asset pricing, risk perception, and investor behavior. Drawing upon recent empirical and theoretical work from both global and Indian contexts (2020–2025), the study highlights how these psychological elements lead to mispricing and volatility in financial markets. The findings suggest that incorporating behavioral insights can improve investment strategies, regulatory frameworks, and financial literacy programs. By advancing a multidisciplinary approach, this paper contributes to a deeper understanding of real-world financial behavior and calls for more adaptive and inclusive financial systems.
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References
H. Shefrin and M. Statman, “Behavioral portfolio theory,” Journal of Financial and Quantitative Analysis, vol. 35, no. 2, pp. 127–151, 2000. DOI: https://doi.org/10.2307/2676187
M. Statman, “Behavioral finance: Finance with normal people,” Borsa Istanbul Review, vol. 14, no. 2, pp. 65–73, 2014. DOI: https://doi.org/10.1016/j.bir.2014.03.001
O. S. Mitchell and A. Lusardi, “Financial literacy and financial behavior at older ages,” in The Routledge Handbook of the Economics of Ageing. London, U.K.: Routledge, 2023, pp. 553–565. DOI: https://doi.org/10.4324/9781003150398-37
S. Benartzi and R. H. Thaler, “Behavioral economics and the retirement savings crisis,” Science, vol. 339, no. 6124, pp. 1152–1153, 2013. DOI: https://doi.org/10.1126/science.1231320
S. R. Baker, N. Bloom, S. J. Davis, and S. J. Terry, “Covid-induced economic uncertainty,” National Bureau of Economic Research, Cambridge, MA, USA, Working Paper w26983, 2020. DOI: https://doi.org/10.3386/w26983
S. Zheng, Y. Zhang, and Y. Chen, “Leveraging financial sentiment analysis for detecting abnormal stock market volatility: An evidence-based approach from social media data,” Academia Nexus Journal, vol. 3, no. 3, 2024.
S. Gupta, S. Kadyan, and N. K. Bhasin, “Analytical study of behavioral finance in bank merger: Impact of digitalization,” Academy of Accounting and Financial Studies Journal, vol. 25, pp. 1–17, 2021.
R. Saxena, A. Chaturvedi, A. Bhatia, A. Mehta, A. Chaudhari, and A. Jain, “Studying the influence of cognitive biases on the investment decision-making of retail investors in India,” Advances in Consumer Research, vol. 2, pp. 4156–4164, 2025.
N. Kumar, M. Janani, R. Pavithra, and T. M. Kumar, “Beyond the hype: A tech-driven analysis of Gen Z’s cryptocurrency investment behavior amid regulatory uncertainty and risk-return perceptions in India,” NMIMS Management Review, vol. 33, no. 3, pp. 186–198, 2025. DOI: https://doi.org/10.1177/09711023251351511
S. Patil, “The impact of AI-powered influencer marketing on consumer engagement and purchase intent: An Indian perspective,” Perspective, vol. 2, no. 4, pp. 4131–4148, 2025.
A. W. Lo and D. V. Repin, “The psychophysiology of real-time financial risk processing,” Journal of Cognitive Neuroscience, vol. 14, no. 3, pp. 323–339, 2002. DOI: https://doi.org/10.1162/089892902317361877
J. Kim and B. Han, “A case analysis of artificial intelligence-based financial systems aimed at mitigating investor behavioral biases,” Korea Business Review, vol. 29, no. 3, pp. 185–202, 2025. DOI: https://doi.org/10.17287/kbr.2025.29.3.185
M. Srivastava, G. D. Sharma, A. K. Srivastava, and S. S. Kumaran, “What’s in the brain for us: A systematic literature review of neuroeconomics and neurofinance,” Qualitative Research in Financial Markets, vol. 12, no. 4, pp. 413–435, 2020. DOI: https://doi.org/10.1108/QRFM-10-2019-0127
B. M. Barber and T. Odean, “Boys will be boys: Gender, overconfidence, and common stock investment,” The Quarterly Journal of Economics, vol. 116, no. 1, pp. 261–292, 2001. DOI: https://doi.org/10.1162/003355301556400
R. Dasgupta and R. Singh, “Investor sentiment antecedents: A structural equation modeling approach in an emerging market context,” Review of Behavioral Finance, vol. 11, no. 1, pp. 37–55, 2019. DOI: https://doi.org/10.1108/RBF-07-2017-0068
P. C. Sinha, “Stocks’ pricing dynamics and behavioral finance: A review,” Management Science Letters, vol. 5, no. 9, pp. 797–820, 2015. DOI: https://doi.org/10.5267/j.msl.2015.7.003
E. De Giorgi and T. Hens, “Making prospect theory fit for finance,” Financial Markets and Portfolio Management, vol. 20, no. 3, pp. 339–360, 2006. DOI: https://doi.org/10.1007/s11408-006-0019-1
G. Loewenstein, “Emotions in economic theory and economic behavior,” American Economic Review, vol. 90, no. 2, pp. 426–432, 2000. DOI: https://doi.org/10.1257/aer.90.2.426
H. A. Khan and R. J. K. Chahal, “Asymmetric impact of social media sentiments and stock market uncertainty on Indian sectoral returns: A quantile-on-quantile approach,” The North American Journal of Economics and Finance, vol. 79, p. 102456, 2025. DOI: https://doi.org/10.1016/j.najef.2025.102456
L. H. Singh, K. Kumar, and G. Tanty, “Modeling investor herding behavior through social media sentiment: A machine learning approach using YouTube Shorts,” Journal of Behavioral Finance, pp. 1–13, 2025. DOI: https://doi.org/10.1080/15427560.2025.2597231
R. H. Thaler, “The end of behavioral finance,” Financial Analysts Journal, vol. 55, no. 6, pp. 12–17, 1999. DOI: https://doi.org/10.2469/faj.v55.n6.2310
R. P. Buckley, D. W. Arner, D. A. Zetzsche, and E. Selga, “The dark side of digital financial transformation: The new risks of fintech and the rise of techrisk,” UNSW Law Research Paper, no. 19-89, 2019. DOI: https://doi.org/10.2139/ssrn.3478640
J. M. Prosad, S. Kapoor, and J. Sengupta, “Behavioral biases of Indian investors: A survey of Delhi-NCR region,” Qualitative Research in Financial Markets, vol. 7, no. 3, pp. 230–263, 2015. DOI: https://doi.org/10.1108/QRFM-04-2014-0012
C. Camerer, G. Loewenstein, and D. Prelec, “Neuroeconomics: How neuroscience can inform economics,” Journal of Economic Literature, vol. 43, no. 1, pp. 9–64, 2005. DOI: https://doi.org/10.1257/0022051053737843
B. Knutson and S. M. Greer, “Anticipatory affect: Neural correlates and consequences for choice,” Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 363, no. 1511, pp. 3771–3786, 2008. DOI: https://doi.org/10.1098/rstb.2008.0155
M. Cull, S. Burton, and R. Lam, “Ethics in financial products marketing,” in The SAGE Handbook of Marketing Ethics. Thousand Oaks, CA, USA: SAGE Publications, 2020, pp. 301–325. DOI: https://doi.org/10.4135/9781529739725.n22
G. A. Mumbi Mugo, K. Athanasiadis, and D. Koufopoulos, “Gender differences in financial literacy: An empirical study of professionals in Nairobi, Kenya, using the Organisation for Economic Co-operation and Development (OECD) toolkit,” Cureus Journal of Business and Economics, pp. 1–38, 2026.
P. V. Bhandare, S. Guha, R. H. Chaudhury, and C. Ghosh, “Impact of financial literacy models on the financial behavior of individuals: An empirical study on the Indian context,” Strategic Change, vol. 30, no. 4, pp. 377–387, 2021. DOI: https://doi.org/10.1002/jsc.2431
J. S. Dote-Pardo, M. C. Cordero-Díaz, M. T. Espinosa Jaramillo, and J. Parra-Domínguez, “Leveraging artificial intelligence for enhanced decision-making in finance: Trends and future directions,” Journal of Accounting Literature, 2025. DOI: https://doi.org/10.1108/JAL-02-2025-0100
H. Canton, “Organisation for Economic Co-operation and Development—OECD,” in The Europa Directory of International Organizations 2021. London, U.K.: Routledge, 2021, pp. 677–687. DOI: https://doi.org/10.4324/9781003179900-102
S. Banerjee, M. Murshidabad, and P. Ray, “Factors affecting investors’ inclination towards sustainable investment: A comparative study based on gender,” Academy of Marketing Studies Journal, vol. 29, Special Issue 3, pp. 1–9, 2025.
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