By Terrell D. (ed.), Fomby T. (ed.)

ISBN-10: 0762312742

ISBN-13: 9780762312740

The editors are happy to provide the subsequent papers to the reader in reputation and appreciation of the contributions to our literature made by means of Robert Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics. the fundamental issues of this a part of quantity 20 of Advances in Econometrics are time various betas of the capital asset pricing version, research of predictive densities of nonlinear types of inventory returns, modelling multivariate dynamic correlations, versatile seasonal time sequence types, estimation of long-memory time sequence versions, the appliance of the means of boosting in volatility forecasting, using various time scales in GARCH modelling, out-of-sample review of the 'Fed version' in inventory expense valuation, structural switch in its place to lengthy reminiscence, using gentle transition auto-regressions in stochastic volatility modelling, the research of the ''balanced-ness'' of regressions examining Taylor-Type ideas of the Fed money expense, a mixture-of-experts strategy for the estimation of stochastic volatility, a latest evaluation of Clive's first released paper on Sunspot task, and a brand new category of types of tail-dependence in time sequence topic to jumps.

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Extra resources for Econometric Analysis of Financial and Economic Time Series Part A, Volume 20 (Advances in Econometrics)

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This can be attributed to the greater flexibility of the FDC model. The results for the variances show that the CCM, the ZCM and the FDCz model perform best. 15 Estimating time-varying correlations (instead of assuming a zero or constant correlation) does even seem to influence variance estimates negatively. For the asymmetric models, results do not change considerably. Consequently, I do not report these results. However, I further analyze the behavior of the asymmetric FDCz model when a two-step procedure is used (see Engle, 2002).

Significant at 1% level. although mentioned, further research is necessary to answer the question as to how correlation estimates change with the specification of the volatility equations and vice versa. NOTES 1. Restricting the BEKK model to be diagonal reduces the number of parameters that must be estimated. The factor GARCH model (Engle, Ng, & Rothschild, 1990) reduces the number of parameters and can be transformed to a BEKK model. 2. Note that the nested ADC model requires further restrictions to guarantee a positive-definite covariance matrix.

1976). Studies of stock market volatility changes. Proceeding of the American Statistical Association, Business and Economic Statistics Section, 177–181. Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH approach. Review of Economics and Statistics, 72, 1155–1180. , Engle, R. , & Wooldridge, J. M. (1988). A capital asset pricing model with time-varying covariances. Journal of Political Economy, 96, 116–131. , & Wooldridge, J. M.

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