Learning in speculative bubbles: Theory and experiment

Jieying Hong, Sophie Moinas and Sébastien Pouget

Journal of Economic Behavior & Organization, 2021, vol. 185, issue C, 1-26

Abstract: Does learning reduce or fuel speculative bubbles? We study this issue in the context of the Bubble Game proposed by Moinas and Pouget (2013). Our theoretical analysis based on adaptive learning shows that i) in the long run, learning induces convergence to the unique no-bubble equilibrium, ii) in the short run, more experienced traders create more bubbles, and iii) learning is more difficult when more steps of reasoning are necessary to reach equilibrium. These predictions are consistent with our experimental observations. We find that reinforcement learning rather than belief-based learning is driving behavior in our experiment.

Keywords: Financial markets; Adaptive learning; Speculation; Bubbles (search for similar items in EconPapers)
JEL-codes: C91 G12 G40 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:185:y:2021:i:c:p:1-26

DOI: 10.1016/j.jebo.2021.01.009

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