High Frequency Financial Econometrics: Recent Developments by Luc BauwensHigh Frequency Financial Econometrics: Recent Developments by Luc Bauwens

High Frequency Financial Econometrics: Recent Developments

byLuc BauwensEditorWinfried Pohlmeier, David Veredas

Paperback | October 19, 2010

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Shedding light on some of the most pressing open questions in the analysis of high frequency data, this volume presents cutting-edge developments in high frequency financial econometrics. Coverage spans a diverse range of topics, including market microstructure, tick-by-tick data, bond and foreign exchange markets, and large dimensional volatility modeling. The volume is of interest to graduate students, researchers, and industry professionals.
Title:High Frequency Financial Econometrics: Recent DevelopmentsFormat:PaperbackDimensions:312 pages, 23.5 × 15.5 × 0.02 inPublished:October 19, 2010Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3790825409

ISBN - 13:9783790825404


Table of Contents

Editor's introduction: Recent developments in high frequency financial econometrics.- Exchange rate volatility and the mixture of distribution hypothesis.- A multivariate integer count hurdle model: Theory and application to exchange rate dynamics.- Asymmetries in bid and ask responses to innovation in the trading process.- Liquidity supply and adverse selection in a pure limit oder book market.- How large is liquidity risk in an automated auction market.- Order aggressiveness and order book dynamics.- Modelling financial transaction price movements: a dynamic integer count data model.- The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market.- Semiparametric estimation for financial durations.- Intraday stock prices, volume, and duration: a nonparametric conditional density approach.- Macroeconomic surprises and short-term behaviour in bond futures.- Dynamic modelling of large dimensional covariance matrices.