Add to ORKGIn the paper a non-stationary ARCH model is defined and its relation with a heteroscedastic RCA model is presented. Further, estimation of unknown parameters in a non-stationary ARCH(l) is described under a special seasonal behaviour of time varying parameters. This procedure is compared with two different approaches of parameters estimation in a heteroscedastic RCA(l) model. Asymptotic properties of these estimators are shortly summarized. Finally, numerical simulations are presented.ARCH models, random coefficients, autoregression, heteroscedasticity
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatil...
We investigate the estimation of parameters in the random coefficient autoregressive (RCA) model X ...
The autoregressive conditional heteroscedastic (ARCH) model and its extensions have been widely used...
In this paper the class of ARCH(∞) models is generalized to the nonsta-tionary class of ARCH(∞) mode...
While theory of autoregressive conditional heteroskedasticity (ARCH) models is well understood for s...
in pressInternational audienceWe develop a complete methodology for detecting time varying or non-ti...
In this paper it is shown that the popular Autoregressive Conditional Heteroscedasticity (ARCH) mode...
In this paper, we develop a complete methodology for semiparametric inference in the time-varying AR...
The purpose of this selective review is to present recent theoretical findings on the modelling of A...
ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper s...
In this paper consistency and asymptotic normality of the quasi maximum like-lihood estimator in the...
There exists very few results on mixing for nonstationary processes. However, mixing is often requir...
This paper finds conditions under which the generalized hyperbolic ARCH-type model is strictly stati...
summary:The paper concerns with a heteroscedastic random coefficient autoregressive model (RCA) of t...
Over the last fifteen years, the interest in nonlinear time series models has been steadily increasi...
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatil...
We investigate the estimation of parameters in the random coefficient autoregressive (RCA) model X ...
The autoregressive conditional heteroscedastic (ARCH) model and its extensions have been widely used...
In this paper the class of ARCH(∞) models is generalized to the nonsta-tionary class of ARCH(∞) mode...
While theory of autoregressive conditional heteroskedasticity (ARCH) models is well understood for s...
in pressInternational audienceWe develop a complete methodology for detecting time varying or non-ti...
In this paper it is shown that the popular Autoregressive Conditional Heteroscedasticity (ARCH) mode...
In this paper, we develop a complete methodology for semiparametric inference in the time-varying AR...
The purpose of this selective review is to present recent theoretical findings on the modelling of A...
ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper s...
In this paper consistency and asymptotic normality of the quasi maximum like-lihood estimator in the...
There exists very few results on mixing for nonstationary processes. However, mixing is often requir...
This paper finds conditions under which the generalized hyperbolic ARCH-type model is strictly stati...
summary:The paper concerns with a heteroscedastic random coefficient autoregressive model (RCA) of t...
Over the last fifteen years, the interest in nonlinear time series models has been steadily increasi...
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatil...
We investigate the estimation of parameters in the random coefficient autoregressive (RCA) model X ...
The autoregressive conditional heteroscedastic (ARCH) model and its extensions have been widely used...