Econometric Analysis of Financial and Economic Time Series : Part A

by Terrell; Fomby; Carter Hill; Fomby

• ISBN13: 9780762312740
• ISBN10: 0762312742
• Format: Hardcover
• Copyright: 2006-03-29
• Publisher: Elsevier Science & Technology

Summary

This is a two-part volume honouring the Nobel prizes in Economics received by Robert Engle and Clive Granger in 2003. Part A of the volume contains remarks by Engle and Granger on the field of time series econometrics given at the Third Annual Advances in Econometrics Conference held at Louisiana State University in November of 2004 as well as 13 papers on the subject of the measurement and forecasting of volatility in financial and economic time series. These 13 volatility papers are broken into three groups: Multivariate Volatility Models, High Frequency Models, and Univariate Volatility Models. Part B of the volume likewise contains the conference remarks of Engle and Granger and, in addition, contains 13 papers on a broader range of subjects including cointegration, modelling long-memory, nonlinear models of stock market behaviour unbalanced regression models, seasonal time series models, mixture-of-expert models, and tail-dependent time series models, among other topics. Also Granger provides comments on a paper that reviews his first professional journal publication. Book jacket.

Table of Contents

DEDICATION	ix
LIST OF CONTRIBUTORS	xi
INTRODUCTION
Dek Terrell and Thomas B. Fomby	xiii
REMARKS BY ROBERT F. ENGLE III AND SIR CLIVE W.J. GRANGER, KB
Given During Third Annual Advances in Econometrics Conference at Louisiana State University, Baton Rouge, November 5-7, 2004
GOOD IDEAS
Robert F. Engle III	xix
THE CREATIVITY PROCESS
Sir Clive W.J. Granger, KB	xxiii
PART I: MULTIVARIATE VOLATILITY MODELS
A FLEXIBLE DYNAMIC CORRELATION MODEL
Dirk Baur	3	(30)
A MULTIVARIATE SKEW-GARCH MODEL
Giovanni De Luca, Marc G. Genton and Nicola Loperfido	33	(26)
SEMI-PARAMETRIC MODELING OF CORRELATION DYNAMICS
Christian M. Hafner, Dick van Dijk and Philip Hans Franses	59	(46)
A MULTIVARIATE HEAVY-TAILED DISTRIBUTION FOR ARCH/GARCH RESIDUALS
Dimitris N. Politis	105	(20)
A PORTMANTEAU TEST FOR MULTIVARIATE GARCH WHEN THE CONDITIONAL MEAN IS AN ECM: THEORY AND EMPIRICAL APPLICATIONS
Chor-yiu Sin	125	(30)
PART II: HIGH FREQUENCY VOLATILITY MODELS
SAMPLING FREQUENCY AND WINDOW LENGTH TRADE-OFFS IN DATA-DRIVEN VOLATILITY ESTIMATION: APPRAISING THE ACCURACY OF ASYMPTOTIC APPROXIMATIONS
Elena Andreou and Eric Ghysels	155	(28)
MODEL-BASED MEASUREMENT OF ACTUAL VOLATILITY IN HIGH-FREQUENCY DATA
Borus Jungbacker and Siem Jan Koopman	183	(28)
NOISE REDUCED REALIZED VOLATILITY: A KALMAN FILTER APPROACH
John P. Owens and Douglas G. Steigerwald	211	(20)
PART III: UNIVARIATE VOLATILITY MODELS
MODELING THE ASYMMETRY OF STOCK MOVEMENTS USING PRICE RANGES
Ray Y Chou	231	(28)
ON A SIMPLE TWO-STAGE CLOSED-FORM ESTIMATOR FOR A STOCHASTIC VOLATILITY IN A GENERAL LINEAR REGRESSION
Jean-Marie Dufour and Pascale Valéry	259	(30)
THE STUDENT'S T DYNAMIC LINEAR REGRESSION: RE-EXAMINING VOLATILITY MODELING
Maria S. Heracleous and Aris Spanos	289	(32)
ARCH MODELS FOR MULTI-PERIOD FORECAST UNCERTAINTY: A REALITY CHECK USING A PANEL OF DENSITY FORECASTS
Kajal Lahiri and Fushang Liu	321	(44)
NECESSARY AND SUFFICIENT RESTRICTIONS FOR EXISTENCE OF A UNIQUE FOURTH MOMENT OF A UNIVARIATE GARCH (P,Q) PROCESS
Peter A. Zadrozny	365