This dissertation contains two essays that study the implications of information arrival on asset prices. In the first essay, I study an important aspect of the firm-level information structure - the quantity of information - and its effect on the cross-section of stock returns. The main contribution of this essay is to propose a new proxy for information intensity (monthly information quantity) and establish a link between information intensity and stock returns. I find that higher information intensity reduces expected uncertainty and leads to a lower expected return, after controlling for a variety of traditional risk factors and asset pricing anomalies. An information-intensity-based long-short portfolio generates an abnormal return of 4.44% per year. My findings suggest that, as a key component of information structure, information quantity is of first order importance in determining stock returns, and more generally, that investor learning plays an important role in financial markets with incomplete information.
The second essay, based on a joint work with John Maheu and Tom McCurdy, studies the asset-pricing implication of market-level information arrival, which can lead to large movements (jumps) in the market index. Deviating from the literature that studies the impact of jumps through option pricing and motivated by a nonlinear pricing kernel associated with general preferences, we focus on the pricing impact of jumps through the pricing of higher-order moments. We find that three components of a modeling device, including: a 2-component GARCH model for diffusive volatility, an autoregressive model for jump intensity, and a higher order moment specification of the equity premium, are particularly important for asset pricing with jumps. This modeling device enables us to be the first to uncover significant pricing of both diffusive risk and jump risk, using only a time series of equity return data. We find that the risk premium due to jumps is a significant part of the overall equity premium. Our results also suggest the existence of a significant skewness premium and offer a potential resolution to sometimes conflicting results on the intertemporal risk-return relationship. Furthermore, taking jumps into account improves the out-of-sample performance of a portfolio allocation application.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/43770 |
| Date | 14 January 2014 |
| Creators | Zhao, Xiaofei |
| Contributors | Kan, Raymond, McCurdy, Tom |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.0021 seconds