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The present study has been accepted as a doctoral thesis by the Depart ment of Economics of the Johann Wolfgang Goethe-University in Frankfurt am Main. It grew out from my five year long participation in two research projects, "Econometric analysis of transaction intensity and volatility on fi nancial markets", and "Microstructure on financial markets", that were both conducted by the chair of Statistics and Econometrics (Empirical Economic Research) at the Department of Economics and Business Administration, Jo hann Wolfgang Goethe-University in Frankfurt am Main and financed by the state of Hessen. During this time I have benefitted from many people. First and foremost I would like to thank my thesis supervisor, Prof. Dr. Reinhard Hujer, for initiating and supporting my studies with great encouragement. I am also very grateful to Prof. Dr. Christian Schlag for acting as the second thesis supervisor. Furthermore, I wish to thank Prof. Dr. Joachim Grammig who introduced me to the topics covered in this study in the first place and helped me to sharpen my views on econometrics and financial market microstructure theory through many discussions and also through his willingness to work with me on several related studies.
This clearly structured and well-written reference work examines the consequences of speculative trading based on private information about financial asset markets. It presents an extensive and thorough discussion of theoretical and empirical methods used in previous studies on sequential trade models. The text also introduces a new framework for estimation and hypothesis testing that substantially advances earlier work in the field. The results that are necessary for understanding the introduced empirical framework are derived step-by-step. The text is ideally suited as a reference work on old and new results as well as a textbook for graduate courses on market microstructure theory, empirical methods in finance or econometrics.
A Course in Monetary Economics is an insightful introduction to advanced topics in monetary economics. Accessible to students who have mastered the diagrammatic tools of economics, it discusses real issues with a variety of modeling alternatives, allowing for a direct comparison of the implications of the different models. The exposition is clear and logical, providing a solid foundation in monetary theory and the techniques of economic modeling. The inventive analysis explores an extensive range of topics including the optimum quantity of money, optimal monetary and fiscal policy, and uncertain and sequential trade models. Additionally, the text contains a simple general equilibrium version of Lucas (1972) confusion hypothesis, and presents and synthesizes the results of recent empirical work. The text is rooted in the author's years of teaching and research, and will be highly suitable for monetary economics courses at both the upper-level undergraduate and graduate levels.
The interactions that occur in securities markets are among the fastest, most information intensive, and most highly strategic of all economic phenomena. This book is about the institutions that have evolved to handle our trading needs, the economic forces that guide our strategies, and statistical methods of using and interpreting the vast amount of information that these markets produce. The book includes numerous exercises.
The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.
A comprehensive introduction to the statistical and econometric methods for analyzing high-frequency financial data High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis. Yacine Aït-Sahalia and Jean Jacod cover the mathematical foundations of stochastic processes, describe the primary characteristics of high-frequency financial data, and present the asymptotic concepts that their analysis relies on. Aït-Sahalia and Jacod also deal with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As they demonstrate, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes. Aït-Sahalia and Jacod approach high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike.
Over the past 25 years, applied econometrics has undergone tremen dous changes, with active developments in fields of research such as time series, labor econometrics, financial econometrics and simulation based methods. Time series analysis has been an active field of research since the seminal work by Box and Jenkins (1976), who introduced a gen eral framework in which time series can be analyzed. In the world of financial econometrics and the application of time series techniques, the ARCH model of Engle (1982) has shifted the focus from the modelling of the process in itself to the modelling of the volatility of the process. In less than 15 years, it has become one of the most successful fields of 1 applied econometric research with hundreds of published papers. As an alternative to the ARCH modelling of the volatility, Taylor (1986) intro duced the stochastic volatility model, whose features are quite similar to the ARCH specification but which involves an unobserved or latent component for the volatility. While being more difficult to estimate than usual GARCH models, stochastic volatility models have found numerous applications in the modelling of volatility and more particularly in the econometric part of option pricing formulas. Although modelling volatil ity is one of the best known examples of applied financial econometrics, other topics (factor models, present value relationships, term structure 2 models) were also successfully tackled.
Dieses etwas andere Lehrbuch bietet keine vorgefertigten Rezepte und Problemlösungen, sondern eine kritische Diskussion ökonometrischer Modelle und Methoden: voller überraschender Fragen, skeptisch, humorvoll und anwendungsorientiert. Sein Erfolg gibt ihm Recht.
This book criticizes the fact that profitability measures derived from capital market models such as the Sharpe ratio and the reward-to-VaR ratio are proposed for loan portfolios, although it is not proven whether their risk-return trade-offs are optimal for banks. The authors demonstrate that even the reward-to-VaR ratio, which is developed for valuating loan portfolios, can be highly misleading. They also show how market discipline, capital requirements, and insured deposits affect decision-making.