Econometrics of Financial High-Frequency Data

• Κύριος συγγραφέας: Hautsch, Nikolaus (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
• Θέματα: Economics, Mathematical.; Econometrics.; Macroeconomics.; Economics.; Macroeconomics/Monetary Economics//Financial Economics.; 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. 

 1 Introduction -- 2 Microstructure Foundations -- 3 Empirical Properties of High-Frequency Data -- 4 Financial Point Processes -- 5 Univariate Multiplicative Error Models -- 6 Generalized Multiplicative Error Models -- 7 Vector Multiplicative Error Models -- 8 Modelling High-Frequency Volatility -- 9 Estimating Market Liquidity -- 10 Semiparametric Dynamic Proportional Hazard Models -- 11 Univariate Dynamic Intensity Models -- 12 Multivariate Dynamic Intensity Models -- 13 Autoregressive Discrete Processes and Quote Dynamics -- Appendix: Important Distributions for Positive-Value Data -- Index.