Skin conductance predicts earnings in a market bubble-and-crash scenario
Szymon Wichary,
Monika Allenbach,
Bettina von Helversen,
Dániel Kaszás,
Radosław Sterna,
Christoph Hoelscher and
Sandra Andraszewicz
Additional contact information
Szymon Wichary: Jagiellonian University in Krakow
Bettina von Helversen: University of Bremen
Sandra Andraszewicz: ETH Zurich
No ybu8z, OSF Preprints from Center for Open Science
Abstract:
In financial markets, profit is usually associated with risk-taking, as those who take risks, use the opportunities that markets present. However, during market bubbles, risk-taking might lead to losses, whereas risk aversion can lead to more profit. Emotion-based warning signals might play a role here by helping to recognize when risk aversion is preferable. To study this, we used a trading simulator, where 27 male participants traded on a historical stock price trend during a market bubble-and-crash scenario, and we continuously monitored their skin conductance level. We found that participants earning the most were characterized by an adaptive pattern of risk-taking —they invested much in the asset in the initial phase of the bubble but sold their stocks before the crash. Their skin conductance level was closely associated with the price trend, peaking before the crash started. This suggests that skin conductance provided a bodily warning signal in this group. Moreover, in high earners, skin conductance level correlated negatively with the proportion of stocks, indicating that the high earners used this warning signal to sell stocks. These results underscore the adaptive role of bodily signals in decision-making and elucidate the neural basis of success in uncertain financial markets.
Date: 2023-12-07
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://osf.io/download/65720ee2666e10000f1a7c0a/
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:ybu8z
DOI: 10.31219/osf.io/ybu8z
Access Statistics for this paper
More papers in OSF Preprints from Center for Open Science
Bibliographic data for series maintained by OSF ().