Revealing Traders’ Stress Levels Through Physiological Signals

It is known that investing mistakes are caused by fear and greed of traders. Based on the general adaptation syndrome theory (a human-stress cycle theory), fear and greed could assumably be represented by a state of fight or flight occurring in the alarm state of a stress cycle. Such stress state can be psycho-physiologically quantified through analyzing physiological signals such as photoplethysmography (PPG) or galvanic skin response (GSR). In this study, we developed a prototype device for measuring PPG and GSR based on the ESP32 microcontroller. The trier social stress test was selected as a protocol to collect such bio-signals. The experiments were conducted by performing a simulated trading platform based on the movement of the Bitcoin price. From the analysis results, it was found that when investors perceived fluctuations in price, an increase in stress levels was pronounced. This was statistically revealed by physiological parameters calculated from the recorded PPG during the relax (a period of low stress) and performance (a period of high stress) periods. Heart rate was found to be promising a biomarker which shows statistically significant difference (p-value < 0.05) between both periods. Heart rate could be used to track and monitor stress levels of traders while trading.