An Analysis of the Influence of Crisis Memory on Investment Decisions from the Perspective of Behavioral Finance
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An Analysis of the Influence of Crisis Memory on Investment Decisions from the Perspective of Behavioral Finance

Zilin Yin 1*
1 Guangzhou College of Commercial
*Corresponding author: rkerysxthomas@gmail.com
Published on 26 November 2025
Volume Cover
AEMPS Vol.243
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-80590-557-8
ISBN (Online): 978-1-80590-558-5
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Abstract

You know, the global financial markets have really taken some hard hits over the years — from the 2008 financial crisis to the wild swings caused by COVID-19 in 2020, it’s just been one shock after another. Every time something big like that happens, asset prices go crazy, and investors end up with some pretty deep psychological scars. Those “crisis memories,” as we call them, have actually become a super important concept in behavioral finance lately — people in both academia and the financial world are paying more and more attention to them.So, in this study, we take a behavioral finance perspective and try to figure out how these crisis memories mess with people’s investment decisions. Basically, we look back at past financial crises, pull in theories like risk preference, loss aversion, and herd behavior, and analyze how crisis memories create psychological biases. Those biases then lead people to do things like panic selling, being overly cautious, or just blindly following the crowd — all of which make market volatility worse.Our results show that the impact of crisis memories is long-term and pretty complicated. The way they play out depends on stuff like how transparent the market is and what kind of investors you’re talking about. In the end, we also throw out some practical suggestions to help investors make better decisions, help financial institutions manage risk more effectively, and give regulators a few ideas for keeping markets more stable.

Keywords:

Behavioral finance, crisis memory, investment decision-making

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Yin,Z. (2025). An Analysis of the Influence of Crisis Memory on Investment Decisions from the Perspective of Behavioral Finance. Advances in Economics, Management and Political Sciences,243,23-30.

References

[1]. Maganioti, A.E., Chrissanthi, H.D., Charalabos, P.C., Andreas, R.D., George, P.N. and Christos, C.N. (2010) Cointegration of Event-Related Potential (ERP) Signals in Experiments with Different Electromagnetic Field (EMF) Conditions. Health, 2, 400-406.

[2]. Liu, J. C. & Mao, L. E. (2025) A Study on the Influence Mechanism of Investor Sentiment on Stock Market Volatility From the Perspective of Behavioral Finance. China Collective Economy, 23, 105-108.

[3]. Ruan, J. Q. (2023) An Analysis of Individual Investor Behavior in the Stock Market From the Perspective of Behavioral Finance. Market Weekly, 36, 144-147.

[4]. Wang, N. (2022) A Study on the Impact of Investor Sentiment on Stock Prices (Master's thesis, University of International Business and Economics), 16, 32-55.

[5]. Ma, H. (2022) The Impact of Institutional Investor Behavior on Stock Market Volatility (Master's thesis, Lanzhou University of Finance and Economics), 22, 44-48.

[6]. Application of Behavioral Finance Analysis of Individual and Institutional Investors in Investor Education (2022) Proceedings of the High-Quality Development of China's Securities Industry, 66, 446-454.

[7]. Lin, Z. Y., Zhu, H. Q. & Xie, Z. H. (2025) Investor Risk Perception and Cross-Sectional Stock Returns: An Analysis Based on China's Securities Market. Systems Science and Mathematics, 10, 1-23.

[8]. Sun, P. D. (2023) Analyst Ratings, Investor Sentiment, and the Herding Effect of Mutual Funds (Doctoral dissertation, Shanghai Academy of Social Sciences), 16, 22-26.

[9]. Li, H., Jin, X. & Hou, Y. T. (2024) A Study on the Fuzzy Multi-Objective Portfolio Problem Based on Investors' Dynamic Loss Aversion. Operations Research and Management Science, 33, 200-207.

[10]. Ying, X. (2023) An Empirical Study on Investor Overconfidence and Excessive Trading (Master's thesis, University of International Business and Economics), 32, 66-70.

[11]. Li, J. S. & Xiong, X. L. (2024) Major Public Health Emergencies, Investor Behavior, and the Price Discovery Function of Corn Futures: A Case Study of the COVID-19 Pandemic. Jiangsu Business Review 7, 12-17.

[12]. Dai, C. Z. (2024) The Impact of Public Health Emergencies on China's Stock Market (Master's thesis, Shandong University of Technology), 12, 45-60.

[13]. Du, R. L. (2025) The Logic Behind Bond Market Ups and Downs From the Perspective of Investor Psychology and Behavior. China Money Market 3, 45-50.

[14]. Zhang, M. Y. (2022) A Review of Overreaction and Underreaction in the Stock Market. Business Economy 11, 182-184.

References

[1]. Maganioti, A.E., Chrissanthi, H.D., Charalabos, P.C., Andreas, R.D., George, P.N. and Christos, C.N. (2010) Cointegration of Event-Related Potential (ERP) Signals in Experiments with Different Electromagnetic Field (EMF) Conditions. Health, 2, 400-406.

[2]. Liu, J. C. & Mao, L. E. (2025) A Study on the Influence Mechanism of Investor Sentiment on Stock Market Volatility From the Perspective of Behavioral Finance. China Collective Economy, 23, 105-108.

[3]. Ruan, J. Q. (2023) An Analysis of Individual Investor Behavior in the Stock Market From the Perspective of Behavioral Finance. Market Weekly, 36, 144-147.

[4]. Wang, N. (2022) A Study on the Impact of Investor Sentiment on Stock Prices (Master's thesis, University of International Business and Economics), 16, 32-55.

[5]. Ma, H. (2022) The Impact of Institutional Investor Behavior on Stock Market Volatility (Master's thesis, Lanzhou University of Finance and Economics), 22, 44-48.

[6]. Application of Behavioral Finance Analysis of Individual and Institutional Investors in Investor Education (2022) Proceedings of the High-Quality Development of China's Securities Industry, 66, 446-454.

[7]. Lin, Z. Y., Zhu, H. Q. & Xie, Z. H. (2025) Investor Risk Perception and Cross-Sectional Stock Returns: An Analysis Based on China's Securities Market. Systems Science and Mathematics, 10, 1-23.

[8]. Sun, P. D. (2023) Analyst Ratings, Investor Sentiment, and the Herding Effect of Mutual Funds (Doctoral dissertation, Shanghai Academy of Social Sciences), 16, 22-26.

[9]. Li, H., Jin, X. & Hou, Y. T. (2024) A Study on the Fuzzy Multi-Objective Portfolio Problem Based on Investors' Dynamic Loss Aversion. Operations Research and Management Science, 33, 200-207.

[10]. Ying, X. (2023) An Empirical Study on Investor Overconfidence and Excessive Trading (Master's thesis, University of International Business and Economics), 32, 66-70.

[11]. Li, J. S. & Xiong, X. L. (2024) Major Public Health Emergencies, Investor Behavior, and the Price Discovery Function of Corn Futures: A Case Study of the COVID-19 Pandemic. Jiangsu Business Review 7, 12-17.

[12]. Dai, C. Z. (2024) The Impact of Public Health Emergencies on China's Stock Market (Master's thesis, Shandong University of Technology), 12, 45-60.

[13]. Du, R. L. (2025) The Logic Behind Bond Market Ups and Downs From the Perspective of Investor Psychology and Behavior. China Money Market 3, 45-50.

[14]. Zhang, M. Y. (2022) A Review of Overreaction and Underreaction in the Stock Market. Business Economy 11, 182-184.

Cite this article

Yin,Z. (2025). An Analysis of the Influence of Crisis Memory on Investment Decisions from the Perspective of Behavioral Finance. Advances in Economics, Management and Political Sciences,243,23-30.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of CONF-BPS 2026 Symposium: Innovation, Finance, and Governance for Sustainable Global Growth

ISBN: 978-1-80590-557-8(Print) / 978-1-80590-558-5(Online)
Editor: Canh Thien Dang, Li Chai
Conference website: https://www.confbps.org/Beijing.html
Conference date: 5 March 2026
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.243
ISSN: 2754-1169(Print) / 2754-1177(Online)

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