Thompson Sampling: Predicting Behavior in Games and Markets

63 Pages Posted: 31 Oct 2017 Last revised: 28 Jul 2020

See all articles by Felix Mauersberger

Felix Mauersberger

University of Texas at Dallas - Naveen Jindal School of Management; University of Bonn

Date Written: July 28, 2020

Abstract

This paper proposes Thompson Sampling as a unifying and tractable theory of expectation formation, which is in line with theories of the brain. Thompson Sampling means that in uncertain environments, agents update their beliefs in a Bayesian way, and subsequently make a random draw from the posterior. Conditional on that random draw, agents optimize. Thompson Sampling helps explain data from experimental games, market experiments, and survey data on inflation expectations in a unified fashion. In comparison to other modeling approaches, Thompson Sampling stands out in terms of statistical fit and predictive accuracy.

Keywords: Learning, bounded rationality, behavioral game theory, expectations, stochastic choice

JEL Classification: C91, C92, D84, E37

Suggested Citation

Mauersberger, Felix, Thompson Sampling: Predicting Behavior in Games and Markets (July 28, 2020). Available at SSRN: https://ssrn.com/abstract=3061481 or http://dx.doi.org/10.2139/ssrn.3061481

Felix Mauersberger (Contact Author)

University of Texas at Dallas - Naveen Jindal School of Management ( email )

P.O. Box 830688
Richardson, TX 75083-0688
United States

University of Bonn ( email )

Bonn
Germany

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