This book directly focuses on finding optimal trading strategies in the real world and supports that with a well-defined theoretical foundation that allows trading strategy problems to be solved. Critically, it also delivers a menu of actual solutions that can be applied by traders with various risk profiles and objectives in markets that exhibit substantial tail risk. It shows how the Markowitz approach leads to excessive risk taking, and trader underperformance, in the real world. It summarizes the key features of Utility Theory, the deficiencies of the Sharpe Ratio as a statistic, and develops an optimal decision theory with fully developed examples for both 'Normal' and leptokurtotic distributions.

Do financial derivatives enhance or impede innovation? We aim to answer this question by examining the relationship between equity options markets and standard measures of firm innovation. Our baseline results show that firms with more options trading activity generate more patents and patent citations per dollar of R&D invested. We then investigate how more active options markets affect firms' innovation strategy. Our results suggest that firms with greater trading activity pursue a more creative, diverse and risky innovation strategy. We discuss potential underlying mechanisms and show that options appear to mitigate managerial career concerns that would induce managers to take actions that boost short-term performance measures. Finally, using several econometric specifications that try to account for the potential endogeneity of options trading, we argue that the positive effect of options trading on firm innovation is causal.

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.