Date of Award

Spring 2021

Document Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

Barberis, Nicholas


This dissertation studies a range of topics in behavioral finance and asset pricing. The three essays presented in this dissertation have the common theme of using economic theory to explain puzzling phenomena in financial markets. Chapters 1 and 2 focus on one of the most well-known theories in behavioral finance, the prospect theory, and its implications on asset returns in the U.S. stock market and options market. Chapter 3 switches the focus to the Chinese warrants market, and explores the pricing efficiency of option pricing models from an econometric perspective. Chapter 1 asks the question "why do investors sometimes require higher expected returns from the stock market in compensation for bearing volatility, but sometimes do not?" We answer this question by referring to two important components of the prospect theory, namely decreasing sensitivity and loss aversion. On one hand, decreasing sensitivity suggests that after investors have experienced a prior loss, they will behave in a locally risk-seeking way, such that the higher the market volatility, the lower the expected return they require from the market. On the other hand, even after a prior loss, investors do not like too much volatility because the pain inflicted by extra losses exceed the joy coming from extra gains. Consistent with the theory, we find the mean-variance relation depends on the relative strength of decreasing sensitivity and loss aversion. In Chapter 2, Jianfei Cao and I ask the question "do investors' preferences over risk change over time in terms of their degrees of loss aversion and probability weighting, and if so, how do these preferences change with other economic variables?" To answer that question, we build a representative agent model based on the prospect theory, and in a dynamic setting, we estimate the structural parameters in the model using data on the U.S. stock market and the options market. Our results show that after the 2007-2008 financial crisis, investors became more loss averse, and had a weaker tendency to overweight right tail events of the market. We also find close relationships between the prospect theory parameters and investor sentiment. Chapter 3 studies the performance of various option pricing models in the Chinese warrants market. To capture the negative skewness and heavy tails in the distribution of Chinese stock returns, we modify the canonical Black-Scholes model from two perspectives. First, we introduce stochastic volatility into stock price dynamics using GARCH (generalized autoregressive conditional heteroscedasticity) models. Second, we add Poisson jumps to reflect big shocks to stock prices. We then conduct Monte Carlo simulations to calculate theoretical warrant prices implied by different models, and compare them with the observed prices. Our results show that the more sophisticated models successfully explain a large part of the discrepancy between theoretical and real prices, but the differences remain non-negligible in some cases, suggesting the existence of bubbles in the Chinese warrants market.