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On diagnostic checking of vector ARMA-GARCH models with Gaussian and Student-t innovations

Wang, Yongning; Tsay, Ruey S. - In: Econometrics : open access journal 1 (2013) 1, pp. 1-31

model checking. A residual-based bootstrap method is provided and demonstrated as an effective way to approximate the …

Persistent link: https://www.econbiz.de/10009754537

A residual-based test for multivariate GARCH models using transformed quadratic residuals

Ke, Rui; Jia, Jing; Tan, Changchun - In: Economics letters 206 (2021), pp. 1-5

Persistent link: https://www.econbiz.de/10012886565

Automatic specification testing for vector autoregressions and multivariate nonlinear time series models

Escanciano, Juan Carlos; Lobato, Ignacio N.; Zhu, Lin - In: Journal of business & economic statistics : JBES ; a … 31 (2013) 4, pp. 426-437

Persistent link: https://www.econbiz.de/10010337859

Testing for uncorrelated residuals in dynamic count models with an application to corporate bankruptcy

Sant'Anna, Pedro H. C. - In: Journal of business & economic statistics : JBES ; a … 35 (2017) 3, pp. 349-358

Persistent link: https://www.econbiz.de/10011705946

Linear double autoregression

Zhu, Qianqian; Zheng, Yao; Li, Guodong - In: Journal of econometrics 207 (2018) 1, pp. 162-174

Persistent link: https://www.econbiz.de/10012116135

Regular variation of popular GARCH processes allowing for distributional asymmetry

Prono, Todd - 2017 - First version: August 2017

Linear GARCH(1,1) and threshold GARCH(1,1) processes are established as regularly varying, meaning their heavy tails are Pareto like, under conditions that allow the innovations from the, respective, processes to be skewed. Skewness is considered a stylized fact for many financial returns...

Persistent link: https://www.econbiz.de/10011803123