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Skin conductance predicts earnings in a market bubble-and-crash scenario

Author

Listed:
  • Wichary, Szymon

    (Jagiellonian University in Krakow)

  • Allenbach, Monika
  • von Helversen, Bettina

    (University of Bremen)

  • Kaszás, Dániel
  • Sterna, Radosław
  • Hoelscher, Christoph
  • Andraszewicz, Sandra

    (ETH Zurich)

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.

Suggested Citation

  • Wichary, Szymon & Allenbach, Monika & von Helversen, Bettina & Kaszás, Dániel & Sterna, Radosław & Hoelscher, Christoph & Andraszewicz, Sandra, 2023. "Skin conductance predicts earnings in a market bubble-and-crash scenario," OSF Preprints ybu8z, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:ybu8z
    DOI: 10.31219/osf.io/ybu8z
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    References listed on IDEAS

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