By Dek Terrell, Thomas B. B Fomby
The editors are happy to provide the next papers to the reader in acceptance and appreciation of the contributions to our literature made through Robert Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics. the elemental subject matters 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 diversified time scales in GARCH modelling, out-of-sample assessment of the 'Fed version' in inventory fee valuation, structural switch instead to lengthy reminiscence, using tender transition auto-regressions in stochastic volatility modelling, the research of the "balanced-ness" of regressions reading Taylor-Type principles of the Fed cash cost, a mixture-of-experts technique for the estimation of stochastic volatility, a latest review of Clive's first released paper on Sunspot job, and a brand new classification of versions of tail-dependence in time sequence topic to jumps. *This sequence: Aids within the diffusion of latest econometric innovations * Emphasis is put on expositional readability and straightforwardness of assimilation for readers who're unusual with a given subject of a quantity *Illustrates new recommendations
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Additional info for Econometric analysis of financial and economic time series
Engle, R. , & Kroner, K. F. (1991). Multivariate simultaneous generalized ARCH. MS. Thesis University of California, Department of Economics, San Diego. , & Rombouts, J. V. K. (2005). Multivariate Garch models: A survey. Journal of Applied Econometrics, forthcoming. , & Wu, G. (2000). Asymmetric volatility and risk in equity markets. The Review of Financial Studies, 13, 1–42. , & Hausman, J. (1974). Estimation and inference in nonlinear structural models. Annals of Economic and Social Measurement, 3/4, 653–665.
Volatility is higher in presence of bad news. Skewness is negative (positive) and more remarkable in presence of bad (good) news. In both cases, a high degree of leptokurtosis is observed. Finally, bad news involves a stronger correlation between present European returns and the one-day lagged US return. Allowing for a GARCH structure for taking into account the heteroskedastic nature of financial time series, under standard assumptions, the distribution of the European returns conditionally on news (that is, on the sign of the one-day lagged US return) and past information turns out to be skew-normal (Azzalini, 1985).
1991). Multivariate simultaneous generalized ARCH. MS. Thesis University of California, Department of Economics, San Diego. , & Rombouts, J. V. K. (2005). Multivariate Garch models: A survey. Journal of Applied Econometrics, forthcoming. , & Wu, G. (2000). Asymmetric volatility and risk in equity markets. The Review of Financial Studies, 13, 1–42. , & Hausman, J. (1974). Estimation and inference in nonlinear structural models. Annals of Economic and Social Measurement, 3/4, 653–665. Black, F. (1976).