Beyond market anomalies: How heuristics and perceived efficiency shape investor behavior in developing markets
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DOIhttp://dx.doi.org/10.21511/imfi.21(3).2024.01
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Article InfoVolume 21 2024, Issue #3, pp. 1-14
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Cognitive biases often influence investor behavior in developing capital markets, leading to market anomalies and affecting overall market efficiency. With the increasing integration of global financial markets and the growing participation of retail investors, understanding these biases is more critical than ever. While market anomalies have been extensively studied in developed markets, their influence in developing economies remains under-explored. This study aims to examine the impact of heuristic biases on investment decisions, focusing on Nepal’s stock market. Structural Equation Modeling is used to assess how perceived market efficiency mediates the relationship between heuristic biases and investor behavior. Data were collected from purposively selected 403 active individual investors in Nepal Stock Exchange (NEPSE). The findings reveal that representative and overconfidence biases significantly and positively influence investment decisions and market efficiency. Specifically, investors exhibiting these biases are more likely to make confident and bold investment choices, believing in their ability to predict market movements accurately. Furthermore, the study finds that perceived market efficiency mediates the relationship between anchoring and adjustment bias and investment decisions, suggesting that investors who rely heavily on initial information (anchors) adjust their decisions based on their perceptions of market efficiency. The results highlight the critical role of heuristic biases in shaping investor behavior and stress the importance of market efficiency in this process. The study emphasizes the need to enhance investor awareness of these biases and implement policies to improve market transparency and efficiency. Such measures are vital for mitigating risks and fostering a more robust and resilient financial market in developing economies like Nepal.
- Keywords
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JEL Classification (Paper profile tab)G41, G14, G11, D81
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References39
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Tables6
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Figures3
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- Figure 1. Conceptual framework
- Figure 2. Structural model of heuristics and investment decision
- Figure 3. Structural model of determinants of heuristics and market efficiency
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- Table 1. Operationalization of the variables
- Table 2. Initial and improved measurement model indices
- Table 3. Construct validity and reliability
- Table 4. Structural path coefficient of determinants of heuristics on investment decision
- Table 5. Structural path coefficient of determinants of heuristics on market efficiency
- Table 6. Mediation analysis results
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- Abdallah, S., & Hilu, K. (2015). Exploring determinants to explain aspects of individual investors’ financial behavior. Australasian Accounting, Business and Finance Journal, 9(2), 4-22.
- Anderson, J., & Gerbing, D. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(1), 411-423.
- Bakar, S., & Yi, A. N. C. (2016). The impact of psychological factors on investors’ decision making in Malaysian stock market: A case of Klang Valley and Pahang. Procedia Economics and Finance, 35(1), 319-328.
- Caparrelli, F. D., Arcangelis, A.M., & Cassuto, A. (2004). Herding in the Italian stock market: A case of behavioral finance. Journal of Behavioral Finance, 5(4), 222-230.
- Gautam, D. K. (2013). Hofstede’s cultural dimensions after 35 years: Business practices and paradoxical proverbs in Nepal: A case study of NABIL bank. The International Journal of Nepalese Academy of Management, 1(1), 109-136.
- Green, S. B. (1991). How many subjects does it take to do a regression analysis. Multivariate Behavioral Research, 26(3), 449-510.
- Gurung, R., Dahal, R. K., Ghimire, B., & Koirala, N. (2024). Unraveling behavioral biases in decision making: A study of Nepalese investors. Investment Management and Financial Innovations, 21(1), 25-37.
- Hadi, F. (2017). Impact of biases on perceived market efficiency: Case of Pakistani financial market. Research Journal of Finance and Accounting, 8(1), 36-70.
- Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.). Upper Saddle River: Prentice-Hall, Inc.
- Hair, J. F., Babin, B., & Krey, N. (2017). Covariance-based structural equation modeling in the journal of advertising: Review and recommendations. Journal of Advertising, 46(1), 163-177.
- Hayes, A. F., & Coutts, J. J. (2020). Use omega rather than Cronbach’s alpha for estimating reliability. Communication Methods and Measures, 14, 1-24.
- Hayes, A. F., & Preacher, K. J. (2008). Asymptotic and re-sampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(1), 879-891.
- Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53-60.
- Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to under parameterized model misspecification. Psychological Methods, 3, 424-453.
- Hulland, J., Baumgartner, H., & Smith, K. M. (2017). Marketing survey research best practices: Evidence and recommendations from a review of JAMS articles. Journal of the Academy of Marketing Science, 1-17.
- Ikram, Z. (2016). An empirical investigation on behavioral determinants and impact on investment decision making, moderating role of locus of control. Journal of Poverty, Investment and Development, 26(1), 15-37.
- Javed, H. Bagh, T., & Razzaq, S. (2017). Herding effects, over confidence, availability bias and representativeness as behavioral determinants of perceived investment performance: Empirical evidence from Pakistan Stock Exchange (PSX).’ Journal of Global Economics, 6(1).
- Kahneman, D., & Tversky, A. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
- Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-292.
- Kengathara, L., & Kengathara, N. (2014). The influence of behavioral factors in making investment decisions and performance: Study on investors of Colombo stock exchange, Sri Lanka. Asian Journal of Finance and Accounting, 6(1), 1-23.
- Keswani, S., Dhingra, V., & Wadhwa, B. (2019). Impact of behavioral factors in making investment decisions and performance: Study on investors of National stock exchange. International Journal of Economics and Finance, 11(1), 80-103.
- Khan, H., Naz, I., Qureshi, F., & Ghafoor, A. (2017). Heuristics and stock buying decision: Evidence from Malaysian and Pakistani stock markets. Borsa Istanbul Review, 17(2), 97-110.
- Luong, L. P., & Ha, D. T. T. (2011). Behavioral factors influencing individual investor’s decision making and performance: A survey at the Ho Chi Minh stock exchange (pp. 1-103).
- Nofsinger, J. R., & Varma, A. (2013). Availability, recency, and sophistication in the repurchasing behavior of retail investors. Journal of Banking and Finance, 37(7).
- Nyamute, W. I. (2016). Investor behaviour, investor demographic characteristics, investment style and individual investor portfolio performance at the Nairobi Securities exchange (Doctoral dissertation). JKUAT, Juja.
- Park, J., Konana, P., Gu, B., Kumar, A., & Raghunathan, R. (2010). Confirmation bias, overconfidence, and investment performance: Evidence from stock message boards.
- Prosad, J. M., Kapoor, S., & Sengupta, J. (2015). Behavioral biases of Indian investors: A survey of Delhi-NCR region. Qualitative Research in Financial Markets, 7(3), 230-263.
- Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research, 99(6), 323-338.
- Sebastian, M., Waldemar, T., & Malgorzata, T. L. (2020). Measuring investors’ emotions using econometric models of trading volume of stock exchange indexes. Investment Management and Financial Innovations, 17(3), 281-291.
- Shagufta, P. Zoya, W. S., Qazi, A. S., & Sana. J. (2020). Exploring market overreaction, investors’ sentiments and investment decisions in an emerging stock market. Borsa Istanbul Review, 20(3), 224-235.
- Shah, S., Ahmad, M., & Mahmood, F. (2018). Heuristic biases in investment decision-making and perceived market efficiency: A survey at the Pakistan stock exchange. Qualitative Research in Financial Markets, 10(1), 85-110.
- Shah, S. F., Raza, M. W., & Khurshid, M. R. (2012). Overconfidence and perceived market efficiency. Interdisciplinary Journal of Contemporary Research in Business, 3(10), 984-997.
- Shantha, K. V. A., Chen, X., Gamini, L. P. S., & McMillan, D. (2018). A conceptual framework on individual investors’ learning behavior in the context of stock trading: An integrated perspective. Cogent Economics & Finance.
- Shefrin, H. (2007). Beyond greed and fear: Understanding behavioral finance and the psychology of investing. OUP Catalogue. Oxford University Press.
- Shefrin, H., & Statman, M. (1994). Behavioral capital asset pricing theory. Journal of Financial and Quantitative Analysis, 29, 323-349.
- Statman, M. (2017). Finance for Normal People: How Investors and Managers Behave. New York: Oxford University Press.
- Sureshб G. (2024). Impact of financial literacy and behavioural biases on investment decision-making. FIIB Business Review, 13(1), 72-86.
- Waweru, N. M., Munyoki, E., & Uliana, E. (2008). The effects of behavioural factors in investment decision-making: A survey of institutional investors operating at the Nairobi stock exchange. International Journal of Business and Emerging Markets, 1(1), 24-41.
- Waweru, N., Mwangi, G., & Parkinson, J. (2014). Behavioural factors influencing investment decisions in the Kenyan property market. Afro-Asian Journal of Finance and Accounting, 4(1), 26-49.