Essays in Empirical Asset Pricing

Abstract

What kinds of risk do systematically drive stock returns? This question has prompted vast amounts of research and is still one of the main challenges in finance. It has not only been of interest in the finance literature, but it also concerns investors across the globe. In general, investors aim at avoiding risky stocks but are keen on earning high returns. But which stocks are considered to be risky? Does a premium exist for risky stocks? High returns and low risk –do these two goals conflict with each other? The following dissertation addresses these questions empirically. Studying the German and the US stock market, I investigate the risk-return relation and evaluate which kind of stocks yield a significant risk premium. <br /> This dissertation provides empirical evidence that illiquidty and idiosyncratic risk significantly drive stock returns and earn a significant risk premium while controlling for other potential risk factors. Surprisingly, idiosyncratic risk is negatively priced contradicting the theoretical results from classical finance theory. <br /> The first chapter of this dissertation focuses on the methodology. In contrast to the existent literature, I apply a conditional approach to the Fama-French three-factor model in order to evaluate the risk-return relation. As predicted by theory, my results yield strong support for a positive risk-return relation when risk factor realizations are positive and a negative one when risk factor realizations are negative. As a further contribution to the literature, I derive a test based on the conditional approach to estimate if beta risks are priced. My results show that this test produces very similar results as the standard Fama-MacBeth test. <br /> Chapter two examines the impact of illiquidity on equity returns. Since illiquidity has many facets, I cover the whole spectrum of illiquidity measures: trading speed, trading costs, trading quantity, and price impact. Based on these illiquidity measures I construct factor mimicking portfolios that capture the risk of illiquidity. My findings provide evidence that illiquidity drives stock returns and entails a significant risk premium independent of the measure chosen. Additionally, I investigate the link between size and illiquidity and tackle the question if size proxies for illiquidity.<br /> The third chapter deals with a widely accepted measure of risk, volatility, the standard deviation of returns per time unit. Volatility is often used to identify how risky an investment is. In classical finance theory it is assumed that investors dislike high volatility. Therefore, they require a compensation for holding volatile stocks. Not only most of the empirical and theoretical asset pricing literature predicts a positive relationship between volatility and expected returns, but also many practitioners believe in the trade-off between volatility and expected returns. They share the view that high volatility must be connived in order to earn higher expected returns. Volatility consists of two components: systematic and idiosyncratic risk. The largest component is idiosyncratic risk, which represents over 80% of the total volatility on average for single stocks. The last chapter of this dissertation investigates whether idiosyncratic volatility is a priced risk. My results reflect that low idiosyncratic volatility stocks outperform high idiosyncratic volatility stocks. Further, my empirical findings do not support the positive relation between total volatility and expected returns, but show that the trade-off is negative.