High Frequency Financial Econometrics

Powerful Essays
Luc Bauwens . Winfried Pohlmeier
David Veredas (Eds.)

High Frequency
Financial
Econometrics
Recent Developments

With 57 Figures and 64 Tables

Physica-Verlag
A Springer Company

High Frequency Financial Econometrics
Recent Developments

Prof. Winfried Pohlmeier
Department of Economics
University of Konstanz
78457 Konstanz
Germany
winfried.pohlmeier@uni-konstanz.de

Prof. Luc Bauwens
CORE
Voie du Roman Pays
1348 Louvain-la-Neuve
Belgium
bauwens@ucl.ac.be
Prof. David Veredas
ECARES
´
Universite Libre des Bruxelles
30, Avenue Roosevelt
1050 Brussels
Belgium
dveredas@ulb.ac.be

Parts of the papers have been first published in


“Empirical Economics, Vol. 30, No. 4, 2006

Library of Congress Control Number: 2007933836

ISBN 978-3-7908-1991-5 Physica-Verlag Heidelberg New York
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References: Amilon H (2003) GARCH estimation and discrete stock prices: an application to low-priced Australian stocks Andersen TG, Bollerslev T, Diebold FX, Labys P (1999) (Understanding, optimizing, using and forecasting) realized volatility and correlation, New York University, Leonard N School Finance Department Working Paper, No. 99–061 Antoniou A, Vorlow CE (2005) Price clustering and discreteness: is there chaos behind the noise? Physica A 348:389–403 Ball C (1988) Estimation bias induced by discrete security prices Brock WA, Dechert WD, Scheinkman JA, LeBaron B (1996) A test for independence based on the correlation dimension Cameron C, Li T, Trivedi P, Zimmer D (2004) Modelling the differences in counted outcomes using bivariate copula models with application to mismesured counts Crack TF, Ledoit O (1996) Robust structure without predictability: the “compass rose” pattern of the stock market Denuit M, Lambert P (2005) Constraints on concordance measures in bivariate discrete data. J Multivariate Anal 93:40–57 Diebold FX, Gunther TA, Tay AS (1998) Evaluating density forecasts, with applications to financial risk management Fang Y (2002) The compass rose and random walk tests. Comput Stat Data Anal 39:299–310 Gleason KC, Lee CI, Mathur I (2000) An explanation for the compass rose pattern 68(2):127–133 Hansen PR, Lunde A (2006) Realized variance and market microstructure noise 24:127–218 Heinen A, Rengifo E (2003) Multivariate autoregressive modelling of time series count data Huang RD, Stoll HR (1994) Market microstructure and stock return predictions. Rev Financ Stud 7(1):179–213 Johnson N, Kotz S, Balakrishnan N (1997) Discrete multivariate distributions. Wiley, New York Kocherlakota S, Kocherlakota K (1992) Bivariate discrete distributions Krämer W, Runde R (1997) Chaos and the compass rose. Econ Lett 54(2):113–118 Lee CI, Gleason KC, Mathur I (1999) A comprehensive examination of the compass rose pattern in futures markets. J Futures Mark 19(5):541–564 Liesenfeld R, Nolte I, Pohlmeier W (2006) Modelling financial transaction price movements: a dynamic integer count data model. Empir Econ 30:795–825 Meester S, MacKay J (1994) A parametric model for cluster correlated categorical data. Biometrics 50:954–963 Oomen RCA (2005) Properties of bias-corrected realized variance under alternative sampling schemes. J Financ Econ 3:555–577 Patton A (2001) Modelling time-varying exchange rate dependence using the conditional copula. Discussion Paper, UCSD Department of Economics Russell JR, Engle RF (2002) Econometric analysis of discrete-valued irregularly-spaced financial Shephard N (1995) Generalized linear autoregressions. Working Paper, Nuffield College, Oxford Sklar A (1959) Fonctions de répartition à n dimensions et leurs marges Statistics at the University of Paris 8:229–231 Stevens W (1950) Fiducial limits of the parameter of a discontinuous distribution 37:117–129 Szpiro GG (1998) Tick size, the compass rose and market nanostructure 22(12):1559–1569 Vorlow CE (2004) Stock price clustering and discreteness: the “compass rose” and predictability. model extends the vector autoregressive (VAR) model introduced by Hasbrouck (Hasbrouck J (1991) Measuring the information content of stock trades Departament of Economics, Universidad Carlos III de Madrid, C/Madrid 126, Getafe, 28903 Madrid, Spain

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