| Issue |
SHS Web Conf.
Volume 225, 2025
2025 3rd International Conference on Financial Management and the Digital Economy (ICFMDE 2025)
|
|
|---|---|---|
| Article Number | 01038 | |
| Number of page(s) | 8 | |
| Section | Digital Economics & Behavior | |
| DOI | https://doi.org/10.1051/shsconf/202522501038 | |
| Published online | 13 November 2025 | |
Behavioral finance studies of irrational investor behavior: Theoretical evolution and future directions
College of Letters and Science, University of California Davis, 95616 One Shields Ave, Davis, CA Unitied State
* Corresponding author: 18666025962@163.com
Behavioral finance is an interdisciplinary field that integrates psychology, economics, and neuroscience to better understand irrational investor behavior and its impact on financial markets. This paper reviews foundational theories such as prospect theory, mental accounting, overconfidence, and herding, while also highlighting the explanatory value of dual systems theory and social identity theory. It explores advancements in methodologies, including experimental economics, neuroeconomics, computational models, and natural experiments, to assess how behavioral biases influence asset pricing, volatility, and liquidity. Empirical evidence points to phenomena like overtrading, information neglect, and emotion-driven decision-making, which challenge market efficiency and stability. The paper also critiques current limitations in cross-cultural relevance, theoretical coherence, policy application, and methodological flexibility. It calls for the development of integrated bias models, expanded use of AI, and enhanced cross-market and interdisciplinary research to advance the theoretical and practical contributions of behavioral finance. This research deeply explore the shortcomings of existing theories and methods, and clearly propose the development direction of future research.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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