When Markets Move, so Does the Body: Emotions, Physiology, and Decisions in Crypto Trading

Abstract

The rise of cryptocurrency has created a volatile environment, ideal for studying decision-making under risk. While psychophysiological responses to risk are well-studied in gambling and traditional finance (investing), little is known about these responses in the context of cryptocurrency trading. This thesis addresses the gap by exploring how physiological responses – electrodermal activity (EDA) and heart rate (HR), commonly used indicators of emotional arousal and stress – relate to decision-making in cryptocurrency trading. The study aims to investigate: 1) What physiological and emotional responses do crypto traders exhibit in scenarios of varying risk levels? 2) Are these responses linked to trading decisions? 3) What other factors influence their decision-making?

Thirty participants with at least one year of crypto trading experience will take part in a simulation of key market events (e.g., price surges, crashes, or regulatory changes), during which they will be asked to decide whether to buy, sell, or hold a cryptocurrency asset. EDA and HR responses will be measured, and eye-tracking data will capture participants’ visual attention. After each scenario, participants will complete a questionnaire on their emotional state and decision rationale. A final questionnaire will gather data on their trading habits and attitudes towards risk.

We expect heightened physiological arousal in high-uncertainty or loss scenarios - patterns observed in prior studies of financial risk processing [1]. Anxiety-related arousal has been linked with risk-averse choices under uncertainty [2], a pattern we anticipate as well. Additionally, factors such as trading experience, cognitive biases – like overconfidence and herding, which have been shown to influence investor decisions [3] – and the salience of visual interface elements (e.g., price charts, asset values, and news panels) are expected to shape participants’ attention and decision-making process.

The study's limitations include the use of a mock-up-based environment, which may not fully capture the psychological intensity of real-world trading, and a relatively small sample size. Nonetheless, this thesis contributes to the understanding of decision-making in digital finance by linking psychophysiological data with behavioral economics. It also opens the door for future studies exploring how crypto traders experience decision-making in real time. Insights from this study could guide the development of user interfaces to help traders manage stress and make clearer decisions, as well as educational tools that foster better risk perception and strategic thinking.

References

[1] A. W. Lo and D. V. Repin, “The Psychophysiology of Real-Time Financial Risk Processing,” Journal of Cognitive Neuroscience, vol. 14, no. 3, pp. 323–339, Apr. 2002. doi: 10.1162/089892902317361877.

[2] C. M. Kuhnen and B. Knutson, “The Influence of Affect on Beliefs, Preferences, and Financial Decisions,” Journal of Financial & Quantitative Analysis, vol. 46, no. 3, pp. 605–626, Jun. 2011, doi: 10.1017/S0022109011000123.

[3] B. L. Handoko, M. Hamsal, A. M. Sundjaja, and W. Gunadi, “Heuristic Bias and Herding Behavior for Predicting Investor Decision in Cryptocurrency Trading,” International Journal of Safety and Security Engineering, vol. 14, no. 4, pp. 1269–1277, Aug. 2024, doi: 10.18280/ijsse.140424.