Econometric Analysis of Financial and Economic Time Series Part B

by Fomby; Terrell; Carter Hill; Fomby

• ISBN13: 9780762312733
• ISBN10: 0762312734
• Format: Hardcover
• Copyright: 2006-03-24
• 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	p. ix
List of Contributors	p. xi
Introduction	p. 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	p. xix
The Creativity Process	p. xxiii
Realized Beta: Persistence and Predictability	p. 1
Asymmetric Predictive Abilities of Nonlinear Models for Stock Returns: Evidence From Density Forecast Comparison	p. 41
Flexible Seasonal Time Series Models	p. 63
Estimation of Long-Memory Time Series Models: A Survey of Different Likelihood-Based Methods	p. 89
Boosting-Based Frameworks in Financial Modeling: Application to Symbolic Volatility Forecasting	p. 123
Overlaying Time Scales in Financial Volatility Data	p. 153
Evaluating the 'Fed Model' of Stock Price Valuation: An Out-of-Sample Forecasting Perspective	p. 179
Structural Change as an Alternative to Long Memory in Financial Time Series	p. 205
Time Series Mean Level and Stochastic Volatility Modeling by Smooth Transition Autoregressions: A Bayesian Approach	p. 225
Estimating Taylor-Type Rules: An Unbalanced Regression?	p. 239
Bayesian Inference on Mixture-of-Experts for Estimation of Stochastic Volatility	p. 277
A Modern Time Series Assessment of "A Statistical Model for Sunspot Activity" By C. W. J. Granger (1957)	p. 297
Personal Comments on Yoon's Discussion of My 1957 Paper	p. 315
A New Class of Tail-Dependent Time-Series Models and its Applications in Financial Time Series	p. 317
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