This thesis consists of three essays in empirical finance covering various aspects of asset prices and their relation to the behavior of investors.
Chapter 2 looks at the cross-section of stock returns and the size and value premium in the context of technology risk. We find that the risk of creative destruction plays an important role in the stock market and is priced. The growth of patent issues, patent activity growth (PAG), serves as a measure for technology shocks and creative destruction risk. While small value firms have a negative exposure to patent activity growth, large growth firms have a positive exposure to this factor. This results in an economically meaningful risk premium which can account for the size and the value premium.
The effects of technological change on asset prices have received growing attention in recent years (e.g. Nicholas 2008, Comin et al. 2009, Hsu 2009, P´astor and Veronesi 2009).
A detailed analysis of how technological uncertainty affects the financial market provides an interesting agenda for future research.
Chapter 3 investigates the time-varying equity premium in the context of investor be-havior. The focus of this chapter lies on one specific investor group, mutual fund investors.
The key result is that mutual fund investors buy stocks when predictive variables signal high expected returns and sell stocks when predictive variables signal low expected re-turns. This portfolio adjustment suggests that mutual fund investors are less willing to
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hold equity in bad times than the average investor. Possible explanations for this behavior are that mutual fund investors have a higher risk aversion or a higher exposure to income shocks.
Understanding the risk attitudes and portfolio choices of different investor groups is of importance for portfolio theory as pointed out by John H. Cochrane in his presidential ad-dress to the American Finance Association (AFA) in 2011: “We cannot all time the market [...]. No portfolio advice other than ‘hold the market’ can apply to everyone. A useful and durable portfolio theory must be consistent with this theorem. Our discount-rate facts and theories suggest one, built on differences between people” (Cochrane 2011, p. 1081, emphasis in original). By investigating the portfolio adjustment of mutual fund investors, Chapter 3 is a first step in understanding the differences between market participants. If mutual fund investors sell stocks in bad times, a question that naturally arises is, who buys these stocks and bears this risk in bad times. Answering this question is a promising avenue for further research and will help us to better understand how risk is shared in the financial market.
Chapter 4 analyzes the behavior of retail investors in the context of stock market volatility. The interest of retail investors in the stock market is measured by their search queries for index names such as Dow, FTSE, CAC, or DAX. Searches of index names and the volatility of the index show a strong co-movement over time. Furthermore, we find that searches help to predict volatility in addition to the time-series dynamics of volatility.
These results can be interpreted in the context of agent-based models of volatility, where noise traders induce additional volatility. We utilize the fact that searches Granger cause volatility and include search query data into models of realized volatility. The inclusion of searches improves in-sample as well as out-of-sample forecasts.
The use of internet search queries as a measure of peoples’ attention and interest is only in its infancy, but has already found various interesting applications in economics and finance (e.g. Choi and Varian 2009a,b, Da et al. 2010a,b, 2011, Drake et al. 2011). While autoregressive time series models do very well in extrapolating trends, Choi and Varian
(2009b) argue that search query data might help to predict turning points in the data.
Chapter 4 supports this by showing that times series models of realized volatility do very well in calm times, but search queries improve forecasts considerably in turbulent times.
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