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Econometrics of Financial High-Frequency Data [electronic resource] /by Nikolaus Hautsch.

by Hautsch, Nikolaus [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : 2012.Description: XIV, 374 p. online resource.ISBN: 9783642219252.Subject(s): Economics | Finance | Econometrics | Economics/Management Science | Econometrics | Financial Economics | Quantitative FinanceDDC classification: 330.015195 Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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.
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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.

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.

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