Neuroeconomics of Asset-Price Bubbles: Neuroimaging and Digital Technology for the Prediction and Prevention of Major Bubbles
32 Pages Posted: 21 May 2019 Last revised: 2 Oct 2019
Date Written: July 1, 2019
Asset-price bubbles challenge the explanatory and predictive power of standard economic theory, so neuroeconomic measures should be explored as potential tools for improving the predictive power of standard theory. This exploration is begun 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 financial-market 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. Mechanisms are described by which this early-warning signal could be exploited in self-regulatory or government-administered policies for financial-system stabilization. Digital technology may offer an even more readily achievable alternative to neuroimaging (e.g., behavioral precursors to price bubbles may be identified in analyses of investors’ interactions with online asset-trading platforms). In summary, neuroimaging- or digital technology-based financial-system regulation may be useful for distinguishing bubbles from non-bubble periods and preventing major asset-price bubbles.
Keywords: Neuroeconomics, Asset-Price Bubbles, Financial Crises, Financial Regulation, Recessions, Behavioral Finance, Nucleus Accumbens, Anterior Insula
JEL Classification: D03, D87, E03, E32, E37, E63, G01, G02, G18, H12, Z18
Suggested Citation: Suggested Citation