UC Santa Cruz

This dissertation contains three essays broadly related to financial markets, with an emphasis on decision-makers’ belief-updating and decision-making.

Chapter 1 studies subjects’ belief-updating when they face an uncertain event accompanied by two independent signals in the laboratory. The “Average model” is introduced and compared with other important models for the goodness off fit. At theindividual level, the results are mixed. Some subjects behave close to one of the model’s predictions, while some behave close to another model’s predictions. The average model outperforms the Bayesian model at the aggregate level in predicting subjects’ posterior beliefs. No clear evidence indicates that subjects’ posterior beliefs converge to the Average or Bayesian model’s predictions over time.

Chapter 2 studies the impact of motivated beliefs, the phenomenon that people believe what they want to believe, on market performance in a laboratory market for a state-contingent common value asset. Motivated beliefs are induced so that traders have polarized preferences over the states. The main findings are that (i) these induced motivated beliefs do not have a significant impact on overall market efficiency, but (ii) they do impact traders’ final asset holdings and belief updating processes, and (iii) the induced polarization persists after receiving private signals and trading in the market. Other findings suggest that a more intense financial stake might improve market efficiency. The induced ego-relevant motivation is significantly stronger than the homegrown motivation to believe in higher payoffs.

In Chapter 3, joint work with Daniel Friedman and Thomas Bowen, we study the impact of traders’ overconfidence on market performance. How does trader overconfidence (judgemental or self-enhancement) affect their performance in asset markets, and overall market quality? Conversely, how does market participation affect traders’ overconfidence? To address such questions, we build a laboratory asset market in which human participants receive private information of varying precision and then trade an asset that pays a single state-contingent dividend. Among other results, we find that greater trader overconfidence can improve price efficiency in some environments, but not in the most realistic environment with experienced traders and ambiguous mixed information precision. In that environment, overconfidence reduces trader profits. We detect no substantial impact of market exposure on trader overconfidence.