The Application of Behavioral Finance in Personal Investment Decision-Making: Cognitive Biases and Market Anomalies
DOI:
https://doi.org/10.54097/w0n7nt15Keywords:
Behavioral finance, cognitive biases, market anomalies, personal investment decision-making.Abstract
Traditional financial theories like the Efficient Market Hypothesis assume investor rationality. However, market anomalies, such as the size, value, and momentum effects, constantly challenge this assumption. This study is centered on exploring the impact of cognitive biases and market anomalies on personal investment decisions. It reviews the theoretical framework of behavioral finance, classifies cognitive biases into those in information-processing and decision-execution as well as individual and group biases, and conducts four case analyses of overconfidence, herd behavior, loss aversion, and other biases. By linking cognitive bias mitigation to market anomaly exploitation, the study demonstrates how behavioral tools can systematically address irrationality while uncovering profit opportunities. The results indicate that cognitive biases cause investors to make irrational decisions. Market anomalies, on the other hand, present chances for obtaining excess returns. Behavioral finance offers a more practical decision-making framework. It enables investors to identify biases, take advantage of anomalies, and optimize their portfolios. This, in turn, helps them recognize biases, utilize anomalies, and optimize portfolios, thus enhancing investment decision-making and improving financial outcomes.
Downloads
References
[1] Fama E F. Efficient capital markets. Journal of finance, 1970, 25(2): 383-417.
[2] Fabozzi F J, Markowitz H M, Gupta F. Portfolio selection. Handbook of finance, 2008, 2: 3-13.
[3] Banz R W. The relationship between return and market value of common stocks. Journal of financial economics, 1981, 9(1): 3-18.
[4] Rosenberg B, Reid K, Lanstein R. Persuasive evidence of market inefficiency. Journal of portfolio management, 1985, 11(3): 9-16.
[5] Efficiency S M. Returns to Buying Winners and Selling Losers: Implications for. The Journal of Finance, 1993, 48(1): 65-91.
[6] Kahneman D, Tversky A. Prospect theory: An analysis of decision under risk. Handbook of the fundamentals of financial decision making. Part I. 2013: 99-127.
[7] Shiller R J. From efficient markets theory to behavioral finance. Journal of economic perspectives, 2003, 17(1): 83-104.
[8] Tversky A, Kahneman D. Judgment under Uncertainty: Heuristics and Biases: Biases in judgments reveal some heuristics of thinking under uncertainty. science, 1974, 185(4157): 1124-1131.
[9] Fama E F, French K R. The cross‐section of expected stock returns. the Journal of Finance, 1992, 47(2): 427-465.
[10] Fama E F, French K R. The value premium and the CAPM. The Journal of Finance, 2006, 61(5): 2163-2185.
[11] Thaler R H. Advances in Behavioral Finance Russell Sage Foundation. New York, 1993.
[12] De Bondt W F M, Thaler R. Does the stock market overreact? The Journal of finance, 1985, 40(3): 793-805.
[13] Lakonishok J, Shleifer A, Vishny R W. Contrarian investment, extrapolation, and ris. The journal of finance, 1994, 49(5): 1541-1578.
[14] Hirshleifer D. Investor psychology and asset pricing. The journal of Finance, 2001, 56(4): 1533-1597.
[15] Nickerson R S. Confirmation bias: A ubiquitous phenomenon in many guise. Review of general psychology, 1998, 2(2): 175-220.
[16] Odean T. Are investors reluctant to realize their losses? The Journal of finance, 1998, 53(5): 1775-1798.
[17] Barber B M, Odean T. Boys will be boys: Gender, overconfidence, and common stock investmen. The quarterly journal of economics, 2001, 116(1): 261-292.
[18] Shefrin H, Statman M. The disposition to sell winners too early and ride losers too long: Theory and evidence. The Journal of finance, 1985, 40(3): 777-790.
[19] Devenow A, Welch I. Rational herding in financial economics. European economic review, 1996, 40(3-5): 603-615.
[20] Scharfstein D S, Stein J C. Herd behavior and investment. The American economic review, 1990: 465-479.
[21] Shiller R J. Narrative economics: How stories go viral and drive major economic events. 2020.
[22] Kuranchie-Pong R, Forson J A. Overconfidence bias and stock market volatility in Ghana: testing the rationality of investors in the Covid-19 era. African Journal of Economic and Management Studies, 2022, 13(1): 147-161.
[23] Youssef M, Waked S S. Herding behavior in the cryptocurrency market during COVID-19 pandemic: The role of media coverage. The North American Journal of Economics and Finance, 2022, 62: 101752.
[24] Saltık Ö. Navigating the Stock Market: Modeling Wealth Exchange and Network Interaction with Loss Aversion, Disposition Effect and Anchoring and Adjustment Bias. Ekonomi Politika ve Finans Araştırmaları Dergisi, 2024, 9(1): 88-122.
[25] Barber B M, Huang X, Odean T, et al. Attention‐induced trading and returns: Evidence from Robinhood users. The Journal of Finance, 2022, 77(6): 3141-3190.
[26] Barberis N, Thaler R. A survey of behavioral finance. Handbook of the Economics of Finance, 2003, 1: 1053-1128.
[27] Fama E F. Market efficiency, long-term returns, and behavioral finance. Journal of financial economics, 1998, 49(3): 283-306.
[28] Lo A W. The adaptive markets hypothesis: Market efficiency from an evolutionary perspective. Journal of Portfolio Management, Forthcoming, 2004.
[29] Malkiel B G. The efficient market hypothesis and its critics. Journal of economic perspectives, 2003, 17(1): 59-82.
[30] Camerer C, Loewenstein G, Prelec D. Neuroeconomics: How neuroscience can inform economics. Journal of economic Literature, 2005, 43(1): 9-64.
[31] Antweiler W, Frank M Z. Is all that talk just noise? The information content of internet stock message boards. The Journal of finance, 2004, 59(3): 1259-1294.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Highlights in Business, Economics and Management

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.







