Econometrics of Financial High-Frequency Data

Häftad, Engelska, 2013

AvNikolaus Hautsch

2 509 kr

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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.

Produktinformation

Utgivningsdatum2013-11-29
Mått155 x 235 x 21 mm
Vikt587 g
FormatHäftad
SpråkEngelska
Antal sidor374
Upplaga2012
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783642427725

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Nikolaus Hautsch, born 1972, is director of the Institute for Econometrics at the Department of Economics and Business Administration at the Humboldt-Universität zu Berlin since 2007. His research interests are financial econometrics, empirical finance and multivariate time series analysis. Particular focus is on the econometric modelling of financial high-frequency data, market microstructure analysis as well as volatility and liquidity estimation.

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.

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