Econometrics of Financial High-Frequency Data

Nikolaus Hautsch

ISBN 10: 3642427723 / ISBN 13: 9783642427725

Edité par Springer Berlin Heidelberg, 2013

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - 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.

N° de réf. du vendeur 9783642427725

Détails bibliographiques

• Titre: Econometrics of Financial High-Frequency Data
• Éditeur: Springer Berlin Heidelberg
• Date de parution: 2013
• Langue: anglais
• ISBN à 10 chiffres: 3642427723
• ISBN à 13 chiffres: 9783642427725
• Reliure: Taschenbuch
• État de l'article: Neu

A propos de ce titre

Synopsis

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.

À propos de l?auteur

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.