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: 25 Mar 2020

See all articles by John Haracz

John Haracz

Indiana University Bloomington - Department of Psychological and Brain Sciences

Date Written: January 26, 2020

Abstract

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 asset-trading platforms). In summary, neuroimaging- or digital technology-based financial-system regulation may be useful for distinguishing bubble from non-bubble periods and preventing major asset-price bubbles. To clarify the role of cognitive distortions in these cyclical periods, price is classified as a heuristic that yields bubble or crash biases.

Keywords: neuroeconomics, asset-price bubbles, financial crises, financial regulation, recessions, behavioral finance, price heuristic, bubble bias, crash bias, nucleus accumbens, anterior insula

JEL Classification: D03, D87, E03, E32, E37, E63, G01, G02, G18, H12, Z18

Suggested Citation

Haracz, John, Neuroeconomics of Asset-Price Bubbles: Neuroimaging and Digital Technology for the Prediction and Prevention of Major Bubbles (January 26, 2020). Available at SSRN: https://ssrn.com/abstract=3366527 or http://dx.doi.org/10.2139/ssrn.3366527

John Haracz (Contact Author)

Indiana University Bloomington - Department of Psychological and Brain Sciences ( email )

1101 E. 10th St.
Bloomington, IN 47405
United States
(510) 910-2025 (Phone)

HOME PAGE: https://www.researchgate.net/profile/John_Haracz

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
107
Abstract Views
1,350
rank
298,447
PlumX Metrics