Econometrics of financial high-frequency data
- Nikolaus Hautsch.
- Berlin : Springer, c2012.
- Physical description
- xiii, 371 : ill ; 24 cm.
Math & Statistics Library
|HG106 .H378 2012||Unknown|
- Hautsch, Nikolaus.
- Includes bibliographical references and index.
- 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.
- (source: Nielsen Book Data)9783642219245 20160608
- Publisher's Summary
- 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.
(source: Nielsen Book Data)9783642219245 20160608
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