Technological innovations are altering the traditional value chain in securities trading. Hitherto the order handling, i.e. the appropriate implementation of a general trading decision into particular orders, has been a core competence of brokers. Labeled as Algorithmic Trading, the automation of this task recently found its way both into the brokers' portfolio of service offerings as well as to their customers' trading desks. The software performing the order handling thereby constantly monitors the market(s) in real-time and further evaluates historical data to dynamically determine appropriate points in time for trading. Within only a few years, this technology propagated itself among market participants along the entire value chain and has nowadays gained a significant market share on securities markets worldwide. Surprisingly, there has been only little research analyzing the impact of this special type of trading on markets. Markus Gsell's book aims at closing this gap by analyzing the drivers for adoption of this technology, the impact the application of this technology has on markets on a macro level, i.e. how the market outcome is affected, as well as on a micro level, i.e. how the exhibited trading behavior of these automated traders differs from normal traders' behavior.

This dissertation consists of three essays that examine various problems in financial economics. Chapter 1 fills in a gap in the IPO literature by documenting a close connection between IPO underpricing and the long-term underperformance of IPOs. Firms going public in periods of low underpricing do not underperform in the long run, while firms going public in high underpricing periods do. Furthermore, IPOs in later stages of high underpricing periods underperform even relative to their offer prices, which suggests that many of the most "underpriced" IPOs are in fact priced above fundamental value. This result is unlikely to be explained by differences in risk, or to be driven by a peso problem. I also find that firms going public in later stages of high underpricing periods display worse operating performance and profitability, lower asset growth, lower investment rates and higher cash holdings. Finally, I provide evidence that investor sentiment is stronger in high-underpricing periods. These results are consistent with a setting in which low quality firms, in periods in which the average underpricing in the market is high, try to exploit investors' sentiment by going public. Chapter 2 looks at the return predictability information in Single Country Closed-End Fund (SCCEF) discounts. It is long argued that discounts in closed-end funds are caused by differences in sentiment between investors that trade the fund and investors that trade the underlying assets. SCCEFs provide an interesting setting given the clear market segmentation. American SCCEFs are priced by American investors, while underlying assets are mainly traded by investors in the respective country. I argue that if cross-sectional and time-series variation in SCCEFs are linked to differences in sentiment, then the SCCEF discount can be used to predict future performance of SCCEFs, international stock markets, or both. The evidence on international stock markets' return predictability using SCCEF discounts is mixed. A trading strategy designed to exploit potential differences in sentiment by buying and selling international stock indices delivers alphas of around 90bps per month in an International CAPM. Adding three extra factors: value, size and momentum in U.S. equity does not change the result. However, once we control for international value and momentum in stock markets, we no longer observe positive alphas for short-horizon investments. The evidence on SCCEF return predictability from SCCEF discounts is very strong. For all three asset pricing models considered, a strategy that exploits differences in sentiment yields positive alphas, with magnitudes ranging from 2% to 4% per month. In Chapter 3, I investigate how the stock market reacts to earnings surprises announced during major sport events in the U.S. In a rational and frictionless market, investors should not react differently to announcements released during sport events. However, major sport events combine two known psychological biases. First, sports can be distracting, impairing investors' judgment. Second, sports can change people's mood. Hence, through these biases, market prices could be affected. Considering the Super Bowl, World Series of Baseball and NBA finals I find that investors, immediately after sport events, underreact to positive surprises, and overreact to negative surprises in earnings. After this initial reaction, I find that, investors undo their 'mistakes' in the following weeks to the announcement. However, for the most negative and positive surprises, they over-compensate. In this study, I show that non relevant financial events have an impact on market prices. Moreover, I show that the observed impact cannot be explained only by limited attention, as investor mood seems to be crucial to explain investors' reactions.

Anna Mathieu clarifies if real estate decisions are affected by investor and consumer sentiment and how severely the sentiment should be considered. With regard to international capital markets Mathieu conducts an analysis of the impact of investor sentiment on the return of the real estate-specific investment vehicle “Real Estate Investment Trust (REIT)” by applying a GARCH-Model. She investigates the effects of investor sentiment on the return and the underlying volatilities of REITs and Non-REITs during the financial crisis. The hypotheses are tested for validity in a GARCH-Model. Parallel to capital markets and thereby in changing from an indirect Real Estate investment perspective to a direct perspective the author conducts an analysis if consumer sentiment impacts the household decision to buy a new home in the US. Therefore a dataset with 385 monthly observations from 1978 to 2010 is tested by a component model.

The efficient markets hypothesis has been the central proposition in finance for nearly thirty years. It states that securities prices in financial markets must equal fundamental values, either because all investors are rational or because arbitrage eliminates pricing anomalies. This book describes an alternative approach to the study of financial markets: behavioral finance. This approach starts with an observation that the assumptions of investor rationality and perfect arbitrage are overwhelmingly contradicted by both psychological and institutional evidence. In actual financial markets, less than fully rational investors trade against arbitrageurs whose resources are limited by risk aversion, short horizons, and agency problems. The book presents and empirically evaluates models of such inefficient markets. Behavioral finance models both explain the available financial data better than does the efficient markets hypothesis and generate new empirical predictions. These models can account for such anomalies as the superior performance of value stocks, the closed end fund puzzle, the high returns on stocks included in market indices, the persistence of stock price bubbles, and even the collapse of several well-known hedge funds in 1998. By summarizing and expanding the research in behavioral finance, the book builds a new theoretical and empirical foundation for the economic analysis of real-world markets.

Arbitrage, State Prices and Portfolio Theory / Philip h. Dybvig and Stephen a. Ross / - Intertemporal Asset Pricing Theory / Darrell Duffle / - Tests of Multifactor Pricing Models, Volatility Bounds and Portfolio Performance / Wayne E. Ferson / - Consumption-Based Asset Pricing / John y Campbell / - The Equity Premium in Retrospect / Rainish Mehra and Edward c. Prescott / - Anomalies and Market Efficiency / William Schwert / - Are Financial Assets Priced Locally or Globally? / G. Andrew Karolyi and Rene M. Stuli / - Microstructure and Asset Pricing / David Easley and Maureen O'hara / - A Survey of Behavioral Finance / Nicholas Barberis and Richard Thaler / - Derivatives / Robert E. Whaley / - Fixed-Income Pricing / Qiang Dai and Kenneth J. Singleton.