Non-linear time series models, especially regime-switching models, have become increasingly popular in the economics, finance and financial econometrics literature. However, much of the research has concentrated on the empirical applications of various models, with little theoretical or statistical analysis associated with the structure of the models or asymptotic theory. Some structural and statistical properties have recently been established for the Smooth Transition Autoregressive (STAR) - Generalised Autoregresssive Conditional Heteroscedasticity (GARCH), or STAR-GARCH, model, including the necessary and sufficient conditions for the existence of moments, and the sufficient condition for consistency and asymptotic normality of the (Qua...
This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditi...
This paper investigates several empirical issues regarding quasi-maximum likelihood estimation of Sm...
This paper studies the stability of nonlinear autoregressive models with conditionally heteroskedast...
Non-linear time series models, especially regime-switching models, have become increasingly popular ...
Nonlinear time series models, especially those with regime-switching and conditionally heteroskedast...
textabstractNonlinear time series models, especially those with regime-switching and conditionally h...
Nonlinear time series models, especially those with regime-switching and conditionally heteroskedast...
AbstractNonlinear time series models, especially those with regime-switching and/or conditionally he...
Nonlinear time series models, especially those with regime-switching and/or conditionally heterosked...
Nonlinear time series models, especially those with regime-switching and/or conditionally heterosked...
Economic and finance time series are typically asymmetric and are expected to be modeled using asymm...
This paper investigates the asymptotic theory for a vector autoregressive moving average-generalized...
This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditi...
AbstractGeneralized autoregressive conditional heteroskedasticity (GARCH) models having normal or St...
Properties of three well-known and frequently applied first-order models for modelling and forecasti...
This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditi...
This paper investigates several empirical issues regarding quasi-maximum likelihood estimation of Sm...
This paper studies the stability of nonlinear autoregressive models with conditionally heteroskedast...
Non-linear time series models, especially regime-switching models, have become increasingly popular ...
Nonlinear time series models, especially those with regime-switching and conditionally heteroskedast...
textabstractNonlinear time series models, especially those with regime-switching and conditionally h...
Nonlinear time series models, especially those with regime-switching and conditionally heteroskedast...
AbstractNonlinear time series models, especially those with regime-switching and/or conditionally he...
Nonlinear time series models, especially those with regime-switching and/or conditionally heterosked...
Nonlinear time series models, especially those with regime-switching and/or conditionally heterosked...
Economic and finance time series are typically asymmetric and are expected to be modeled using asymm...
This paper investigates the asymptotic theory for a vector autoregressive moving average-generalized...
This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditi...
AbstractGeneralized autoregressive conditional heteroskedasticity (GARCH) models having normal or St...
Properties of three well-known and frequently applied first-order models for modelling and forecasti...
This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditi...
This paper investigates several empirical issues regarding quasi-maximum likelihood estimation of Sm...
This paper studies the stability of nonlinear autoregressive models with conditionally heteroskedast...