Assessing Asset Pricing Anomalies

One of the most important challenges in the field of asset pricing is to understand anomalies: empirical patterns in asset returns that cannot be explained by standard asset pricing models. Currently, there is no consensus in the academic literature on the underlying causes of well-known anomalies, such as the value and momentum anomalies. Anomalies could be the result of data mining, disappear when trading costs are taken into account, be a compensation for a particular form of risk, or have a behavioral explanation. The motivation of this research project is to gain more and better insight into possible explanations for well-known asset pricing anomalies. Understanding asset pricing anomalies is of the utmost importance for investors. It allows them to make better informed investment decisions, and thereby achieve higher return premiums.

The first study in this dissertation shows that the value, momentum and size anomalies are also present in the new emerging equity markets, the so-called frontier emerging markets, which makes data mining as an explanation for these anomalies unlikely. The second study focuses on trading costs as a possible explanation for the short-term reversal anomaly. Focusing on large-cap stocks and applying a more sophisticated portfolio construction algorithm lower trading costs significantly, such that reversal strategies generate profitable results net of trading costs. The third study examines risk as an explanation for the value and size anomalies. Although value and small-cap exposures are typically associated with distress risk, the results indicate that distress risk is not priced and that the small-cap and value premiums are priced beyond distress risk. The fourth and last study examines a behavioral explanation for the low-risk anomaly. Based on a general equilibrium model, tournament behavior causes the returns of low-risk (high-risk) assets to be larger (smaller) than expected according to the Capital Asset Pricing Model. In addition, empirical analyses confirm a positive and significant relation between tournament behavior and the low-risk premium.