Beta for Alpha: Neural Engagement in Financial Trading -- by Liang Chen, Tse-Chun Lin, Fei Wu, Xingjian Zheng, Eric Zou

The emergence of wearable electroencephalography (EEG) technologies presents new opportunities to identify and quantify neural correlates of decision-making in real-time, financially consequential settings. We report a field study in which we use wearable EEG devices to record brainwave activity from professional day traders during real-world, high-stakes trading. Using these signals, we construct an established psychophysiological Engagement Index (EI), which is defined as beta wave power divided by the sum of alpha and theta wave power, and document clear spike-and-decay patterns around trade execution. Linking EI dynamics to trading performance, we find that more successful trades are preceded by larger EI spikes in the 30 seconds before execution, while baseline or background EI levels have no predictive power and, if anything, are negatively associated with performance. We further show that higher EI is associated with attenuated behavioral biases in trading, including the round number heuristic and the disposition effect.