Nikolaus Hautsch – författare

This book has been written as a doctoral dissertation at the Department of Economics at the University of Konstanz. I am indebted to my supervisor Winfried Pohlmeier for providing a stimulating and pleasant research en- ronment and his continuous support during my doctoral studies. I strongly bene?tted from inspiring discussions with him, his valuable advices and he- ful comments regarding the contents and the exposition of this book. I am grateful to Luc Bauwens for refereeing my work as a second super- sor. Moreover, I wish to thank him for o?ering me the possibility of a research visit at the Center of Operations Research and Econometrics (CORE) at the Universit' e Catholique de Louvain. Important parts of this book have been conceived during this period. Similarly, I am grateful to Tony Hall who invited me for a research visit at the University of Technology, Sydney, and provided me access to an excellent database from the Australian Stock Exchange. I would like to thank him for his valuable support and the permission to use this data for empirical studies in this book.I wish to thank my colleagues at the University of Konstanz Frank G- hard,DieterHess,JoachimInkmann,MarkusJochmann,StefanKlotz,Sandra Lechner and Ingmar Nolte who o?ered me advice, inspiration, friendship and successfulco-operations.Moreover,Iamgratefultothestudentresearchass- tantsat the Chair of Econometrics at the University of Konstanz, particularly Magdalena Ramada Sarasola, Danielle Tucker and Nadine Warmuth who did a lot of editing work.

Recent years have witnessed a growing importance of quantitative methods in both financial research and industry. This linkage between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners comfortable access to new techniques in quantitative finance.

The availability of financial data recorded on high-frequency level has inspired a research area which over the last decade emerged to a major area in econometrics and statistics. The growing popularity of high-frequency econometrics is driven by technological progress in trading systems and an increasing importance of intraday trading, liquidity risk, optimal order placement as well as high-frequency volatility. This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis.

The availability of financial data recorded on high-frequency level has inspired a research area which over the last decade emerged to a major area in econometrics and statistics. The growing popularity of high-frequency econometrics is driven by technological progress in trading systems and an increasing importance of intraday trading, liquidity risk, optimal order placement as well as high-frequency volatility. This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis.