Add to ORKGThis paper investigates several empirical issues regarding quasi-maximum likelihood estimation of Smooth Transition Autoregressive (STAR) models with GARCH errors, specifically STAR-GARCH and STAR-STGARCH. Convergence, the choice of different algorithms for maximising the likelihood function, and the sensitivity of the estimates to outliers and extreme observations, are examined using daily data for S&P 500, Heng Seng and Nikkei 225 for the period January 1986 to April 2000
AbstractNonlinear time series models, especially those with regime-switching and/or conditionally he...
In this paper we study the behavior of GARCH(1,1) parameter estimates when data is generated by cert...
This thesis is mainly concerned with the estimation of parameters of a first-order Smooth Threshold ...
Non-linear time series models, especially regime-switching models, have become increasingly popular ...
Non-linear time series models, especially regime-switching models, have become increasingly popular ...
It is well known in the literature that obtaining the parameter estimates for the Smooth Transition ...
Abstract: One of the most important family of nonlinear time-series models, capable of exhibiting li...
Finding a precise estimate for the smoothness parameter of LSTAR models is notoriously difficult. Th...
Outliers and nonlinearity may easily be mistaken. This paper uses Monte Carlo methods to examine and...
textabstractThis paper surveys recent developments related to the smooth transition autoregressive [...
Consider a class of power transformed and threshold GARCH(p,q) (PTTGRACH(p,q)) model, which is a nat...
The GARCH (p, q) model is a very interesting stochastic process with widespread applications and a c...
textabstractOutliers and nonlinearity may easily be mistaken. This paper uses Monte Carlo methods to...
Nonlinear time series models, especially those with regime-switching and conditionally heteroskedast...
The GARCH (p, q) model is a very interesting stochastic process with widespread applications and a c...
AbstractNonlinear time series models, especially those with regime-switching and/or conditionally he...
In this paper we study the behavior of GARCH(1,1) parameter estimates when data is generated by cert...
This thesis is mainly concerned with the estimation of parameters of a first-order Smooth Threshold ...
Non-linear time series models, especially regime-switching models, have become increasingly popular ...
Non-linear time series models, especially regime-switching models, have become increasingly popular ...
It is well known in the literature that obtaining the parameter estimates for the Smooth Transition ...
Abstract: One of the most important family of nonlinear time-series models, capable of exhibiting li...
Finding a precise estimate for the smoothness parameter of LSTAR models is notoriously difficult. Th...
Outliers and nonlinearity may easily be mistaken. This paper uses Monte Carlo methods to examine and...
textabstractThis paper surveys recent developments related to the smooth transition autoregressive [...
Consider a class of power transformed and threshold GARCH(p,q) (PTTGRACH(p,q)) model, which is a nat...
The GARCH (p, q) model is a very interesting stochastic process with widespread applications and a c...
textabstractOutliers and nonlinearity may easily be mistaken. This paper uses Monte Carlo methods to...
Nonlinear time series models, especially those with regime-switching and conditionally heteroskedast...
The GARCH (p, q) model is a very interesting stochastic process with widespread applications and a c...
AbstractNonlinear time series models, especially those with regime-switching and/or conditionally he...
In this paper we study the behavior of GARCH(1,1) parameter estimates when data is generated by cert...
This thesis is mainly concerned with the estimation of parameters of a first-order Smooth Threshold ...