Toward the Prediction and Prevention of Major Bubbles

Asset-price bubbles challenge the explanatory and predictive power of standard economic theory, suggesting that neuroeconomic measures should be explored as potential tools for improving the predictive power of standard theory. We begin this exploration by reviewing results from functional magnetic resonance imaging (fMRI) studies of lab asset-price bubbles and herding behavior (i.e., following others' decisions). These results are consistent with a neuroeconomics-based hypothesis of asset-price bubbles. In this view, decision making during bubble or non-bubble periods of financialmarket activity is driven by, respectively, evolutionarily ancient or new neurocircuitry. Neuroimaging studies that test this or other neuroeconomics-based hypotheses of asset-price bubbles may yield a bubble-related biomarker (e.g., low trade-related lateral neocortical activity associated with traders’ herding-based decisions). Wearable functional near-infrared spectroscopy (fNIRS) technology could determine the prevalence of such a biomarker among financial-market participants, thereby enabling the real-time detection of an emerging bubble. We describe mechanisms by which this early-warning signal could be exploited in self-regulatory or government-administered policies for financial-system stabilization. In summary, neuroimaging-based financial-system regulation may be useful for distinguishing bubbles from non-bubble periods and preventing major asset-price bubbles. *Corresponding author: John L. Haracz, Goldman School of Public Policy, UC Berkeley, 2607 Hearst Ave., Berkeley, CA 94720; phone: (510) 910-2025; email: [email protected]