A Behavioral Accounting Framework for Retail Investor Interpretation of Financial Disclosures: Evidence from Mutual Fund Allocation Patterns
Article Sidebar
Main Article Content
Abstract
Understanding how retail investors interpret accounting disclosures is central to advancing accounting theory, particularly in contexts characterized by heightened market uncertainty. The study develops a behavioral accounting framework that explains how financial performance and risk disclosures shape retail investors’ cognitive processing, risk framing, and subsequent investment allocation decisions. Drawing on behavioral theories such as loss aversion, recency bias, and herding, the framework proposes a set of theoretical propositions linking disclosure attributes to observable shifts in asset allocation across risk categories. Market-level mutual fund allocation patterns are used illustratively to examine the behavioral consistency of the proposed framework across different market conditions. The study contributes to theoretical accounting research by integrating behavioral insights into disclosure interpretation, offering implications for accounting standard setters, regulators, and practitioners concerned with improving the design and communication of financial information.
Article Details
Section
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
References
1. Adil, M., Singh, Y., & Ansari, M. S. (2022). How financial literacy moderate the association between behaviour biases and investment decision?. Asian Journal of Accounting Research, 7(1), 17-30. https://doi.org/10.1108/AJAR-09-2020-0086
2. American Accounting Association, & Accounting, B. (Eds.). (1989). Behavioral Research in Accounting. American Accounting Association.
3. Arora, R., & Purohit, S. (2024). Determinants of investment behaviour of investors: a review and research agenda. International Journal of Behavioural Accounting and Finance, 7(2), 153-176. https://doi.org/10.1504/IJBAF.2024.139359
4. Association of Mutual Funds in India (AMFI). (2023). AUM/AAUM report for the quarter ended 31-Dec-2023 (Q3 2023–24): Asset class-wise disclosure
5. Bihari, A., Dash, M., Kar, S. K., Muduli, K., Kumar, A., & Luthra, S. (2022). Exploring behavioural bias affecting investment decision-making: a network cluster based conceptual analysis for future research. International Journal of Industrial Engineering and Operations Management, 4(1-2), 19-43. https://doi.org/10.1108/IJIEOM-08-2022-0033
6. Chauhan, Y., Mishra, A. K., & Parikh, B. (2023). Fund family versus mutual fund performance: evidence from the Indian investors’ perspective. Journal of Asset Management, 24(4), 268-283. https://doi.org/10.1057/s41260-022-00301-0
7. De Franco, G., Kothari, S. P., & Verdi, R. S. (2011). The benefits of financial statement comparability. Journal of Accounting research, 49(4), 895-931. https://doi.org/10.1111/j.1475-679X.2011.00415.xDigital Object Identifier (DOI)
8. Dey, K., & Singh, A. (2022). Recency bias: Impact of market news on stocks. Indian Journal of Research in Capital Markets, 9(2-3), 19-41. DOI: https://doi.org/10.17010/ijrcm/2022/v9i2-3/172550
9. Ding, W., Mazouz, K., Ap Gwilym, O., & Wang, Q. (2023). Technical analysis as a sentiment barometer and the cross-section of stock returns. Quantitative Finance, 23(11), 1617-1636. https://doi.org/10.1080/14697688.2023.2244991
10. Gupta, P., & Kohli, B. (2021). Herding behavior in the Indian stock market: An empirical study. Indian Journal of Finance, 15(5-7), 86-99. DOI: https://doi.org/10.17010/ijf/2021/v15i5-7/164495
11. Hamurcu, Ç., Hazar, A., & Babuşcu, Ş. (2025). A Portfolio-Focused Behavioral Model Linking Financial Literacy and Risk Tolerance: Evidence from Mutual Fund Investors in Türkiye. Borsa Istanbul Review. https://doi.org/10.1016/j.bir.2025.09.001
12. Hans, A., Choudhary, F. S., & Sudan, T. (2024). Behavioral determinants of investment decisions: evidence from Indian retail equity investors in the wake of COVID-19 induced financial risks. International Journal of Accounting & Information Management. https://doi.org/10.1108/IJAIM-03-2024-0091
13. Hirshleifer, D., Lim, S. S., & Teoh, S. H. (2009). Driven to distraction: Extraneous events and underreaction to earnings news. The journal of finance, 64(5), 2289-2325. https://doi.org/10.1111/j.1540-6261.2009.01501.x
14. Jain, J., Walia, N., Kaur, M., & Singh, S. (2022). Behavioural biases affecting investors’ decision-making process: a scale development approach. Management Research Review, 45(8), 1079-1098. https://doi.org/10.1108/MRR-02-2021-0139
15. Kanojia, S., Singh, D., & Goswami, A. (2022). Impact of herding on the returns in the Indian stock market: an empirical study. Review of Behavioral Finance, 14(1), 115-129.
16. Kaur, I., & Vagrecha, K. (2023). Causality between equity mutual fund flows, stock market return and volatility: Indian evidence. International Journal of Business and Globalisation, 35(1-2), 88-106. https://doi.org/10.1057/s41260-022-00301-0
17. Koonce, L., McAnally, M. L., & Mercer, M. (2005). How do investors judge the risk of financial items?. The accounting review, 80(1), 221-241. https://doi.org/10.2308/accr.2005.80.1.221
18. Kumar, J., & Prince, N. (2022). Overconfidence bias in the Indian stock market in diverse market situations: an empirical study. International Journal of System Assurance Engineering and Management, 13(6), 3031-3047. https://doi.org/10.1007/s13198-022-01792-1
19. Ladrón de Guevara Cortés, R., Tolosa, L. E., & Rojo, M. P. (2023). Prospect theory in the financial decision-making process: an empirical study of two Argentine universities. Journal of Economics, Finance and Administrative Science, 28(55), 116-133. https://doi.org/10.1108/JEFAS-12-2021-0272
20. Libby, R., Bloomfield, R., & Nelson, M. W. (2002). Experimental research in financial accounting. Accounting, organizations and society, 27(8), 775-810.https://doi.org/10.1016/S0361-3682(01)00011-3
21. Lusardi, A., & Messy, F. A. (2023). The importance of financial literacy and its impact on financial wellbeing. Journal of Financial Literacy and Wellbeing, 1(1), 1-11. DOI: https://doi.org/10.1017/flw.2023.8
22. Maheen, M. S. (2021). Impact of COVID-19 on the performance of emerging market mutual funds: evidence from India. Future Business Journal, 7(1), 37. https://doi.org/10.1186/s43093-021-00081-w
23. Maines, L. A., & McDaniel, L. S. (2000). Effects of comprehensive‐income characteristics on nonprofessional investors' judgments: The role of financial‐statement presentation format. The accounting review, 75(2), 179-207. https://doi.org/10.2308/accr.2000.75.2.179
24. Mathew, R. L., & Kumar, S. R. (2022). Factors influencing investment decisions: a study of individual investors in the Indian stock market.
25. Messaoud, D., Ben Amar, A., & Boujelbene, Y. (2023). Investor sentiment and liquidity in emerging stock markets. Journal of Economic and Administrative Sciences, 39(4), 867-891. https://doi.org/10.1108/JEAS-11-2020-0198
26. Ministry of Finance, Government of India. (2024). Economic Survey 2024–25.
27. Mydhili, V., Kumar, M. N. V., Jetti, V. K., Kalyani, P., & Baji, G. (2025). An Empirical Study Of Behavioral Biases Affecting Mutual Fund Investments: With Special Reference To The Twin Cities Of Guntur And Vijayawada, Andhra Pradesh. International Soil and Water Conservation Research, 13(3), 1-10.
28. National Stock Exchange of India. (2024). Annual report 2023–24.
29. Nurmelia, N., Fadilla, F. N., AR, N. W., & Leon, F. M. (2022). Past behaviour, financial literacy, and investment decision-making process of individual investors. SIMAK, 20(01), 55-79.
30. Potharla, S. (2025). Unlocking Value Through IPOs: A Two-Decade Review of India's Corporate Listings and Capital Market Dynamics. SSRN: https://ssrn.com/abstract=5392297
31. Securities and Exchange Board of India. (2024, August). Annual report 2022–23.
32. Sharma, D. P. C. (2022). Mutual Fund Flow Scale: A Multi-Item Scale For Measuring Perception of Mutual Fund Investors. Journal of Commerce & Accounting Research, 11(2).
33. Singh, D., Malik, G., & Jha, A. (2024). Overconfidence bias among retail investors: A systematic review and future research directions. Investment Management & Financial Innovations, 21(1), 302. http://dx.doi.org/10.21511/imfi.21(1).2024.23
34. Thanki, H., Tripathy, N., & Shah, S. (2025). Investors’ behavioral intention in mutual fund investments in India: applicability of theory of planned behavior. Asia-Pacific Financial Markets, 32(3), 975-996. https://doi.org/10.1007/s10690-024-09477-4
35. Yadav, A. P., & Yadav, R. K. (2024). Impact of COVID-19 Pandemic on Mutual Fund Flows: Evidence from the Indian Mutual Fund Industry. Indian Journal of Research in Capital Markets, 11(4), https://doi.org/10.17010/ijrcm/2024/v11i4/174724