Publication: Frontiers in Time Series and Financial Econometrics: An Overview
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2015-02
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Abstract
Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have contributed significantly to time series and financial econometrics, including forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance, prediction of Lévy-driven CARMA processes, functional index coefficient models with variable selection, LASSO estimation of threshold autoregressive models, high dimensional stochastic regression with latent factors, endogeneity and nonlinearity, sign-based portmanteau test for ARCH-type models with heavy-tailed innovations, toward optimal model averaging in regression models with time series errors, high dimensional dynamic stochastic copula models, a misspecification test for multiplicative error models of non-negative time series processes, sample quantile analysis for long-memory stochastic volatility models, testing for independence between functional time series, statistical inference for panel dynamic simultaneous equations models, specification tests of calibrated option pricing models, asymptotic inference in multiple-threshold double autoregressive models, a new hyperbolic GARCH model, intraday value-at-risk: an asymmetric autoregressive conditional duration approach, refinements in maximum likelihood inference on spatial autocorrelation in panel data, statistical inference of conditional quantiles in nonlinear time series models, quasi-likelihood estimation of a threshold diffusion process, threshold models in time series analysis - some reflections, and generalized ARMA models with martingale difference errors.
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The Guest Co-editors wish to thank the Editors of the Journal of Econometrics for their support and encouragement, and the referees for their timely and very helpful comments and suggestions on the papers comprising the special issue. For financial support, the second author wishes to thank the Australian Research Council and the National Science Council, Taiwan.
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Asai, M. and M. McAleer (2015), Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance, to appear in Journal of Econometrics.
Brockwell, P. and A. Lindner (2015), Prediction of Lévy-driven CARMA processes, to appear in Journal of Econometrics.
Cai, Z., T. Juhl and B. Yang (2015), Functional index coefficient models with variable selection, to appear in Journal of Econometrics.
Chan, N.H., C.Y. Yau and R.-M. Zhang (2015), LASSO estimation of threshold autoregressive models, to appear in Journal of Econometrics.
Chang, J., B. Guo and Q. Yao (2015), High dimensional stochastic regression with latent factors, endogeneity and nonlinearity, to appear in Journal of Econometrics.
Chen. M. and K. Zhu (2015), Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations, to appear in Journal of Econometrics.
Cheng, T.-C., C.-K. Ing and S.-H. Yu (2015), Toward optimal model averaging in regression models with time series errors, to appear in Journal of Econometrics.
Creal, D.D. and R.S. Tsay (2015), High dimensional dynamic stochastic copula models, to appear in Journal of Econometrics.
Engle, R.F. (1982), Autoregressive conditional heteroscedasticity, with estimates of the variance of United Kingdom inflation, Econometrica, 50(4), 987-1007.
Franses, P.H. and M. McAleer (2002), Financial volatility: An introduction, Journal of Applied Econometrics, 17, 419-424; in P.H.
Franses and M. McAleer (eds.), Modelling and Forecasting Financial Volatility, special issue of Journal of Applied Econometrics, 17(5), 2002, 419-616.
Gao, J., N.H. Kim and P.W. Saart (2015), A misspecification test for multiplicative error models of non-negative time series processes, to appear in Journal of Econometrics.
Ho, H.-C. (2015), Sample quantile analysis for long-memory stochastic volatility models, to appear in Journal of Econometrics.
Horvath, L. and G. Rice, (2015), Testing for independence between functional time series, to appear in Journal of Econometrics.
Hsiao, C. and Q. Zhou (2015), Statistical inference for panel dynamic simultaneous equations models, to appear in Journal of Econometrics.
Jarrow, R. and S. Kwok (2015), Specification tests of calibrated option pricing models, to appear in Journal of Econometrics.
Li, D., S. Ling and J.-M. Zakoian (2015), Asymptotic inference in multiple-threshold double autoregressive models, to appear in Journal of Econometrics.
Li, M., W.K. Li and G. Li (2015), A new hyperbolic GARCH model, to appear in Journal of Econometrics.
Liu, S. and Y.-K. Tse (2015), Intraday value-at-risk: An asymmetric autoregressive conditional duration approach, to appear in Journal of Econometrics.
Oxley, L. (2002), Earthquakes and volcanoes: The International Conference on Modelling and Forecasting Financial Volatility, Perth, Australia, 7-9 September 2001, Journal of Economic Surveys, 16(2), 227-235.
Robinson, P.M. and F. Rossi (2015), Refinements in maximum likelihood inference on spatial autocorrelation in panel data, to appear in Journal of Econometrics.
So, M.K.P. and R.S.W. Chung (2015), Statistical inference of conditional quantiles in nonlinear time series models, to appear in Journal of Econometrics.
Su, F. and K.-S. Chan (2015), Quasi-likelihood estimation of a threshold diffusion process, to appear in Journal of Econometrics.
Tong, H. (1978). On a threshold model, in C.H. Chen (ed.), Pattern Recognition and Signal Processing, Amsterdam: Sijthoff and Noordhoff.
Tong, H. (2015), Threshold models in time series analysis - some reflections, to appear in Journal of Econometrics.
Zheng, T., H. Xiao and R. Chen (2015), Generalized ARMA models with martingale difference errors, to appear in Journal of Econometrics.