Add to ORKGThe purpose of this selective review is to present recent theoretical findings on the modelling of ARCH type non-linear times series. We provide an overview of recent the-oretical results on the existence and the structure of stationary solutions to ARCH(∞), LARCH, bilinear ARCH, EGARCH, IARCH and random coefficient ARCH models, and investigate their second order dependence (memory) structure. The topics discussed in the review are: existence of a stationary solution, the presence of the short memory and long memory in ARCH type models, leverage effect, asymptotic behavior of the sums (sample mean), aggregation, parameter estimation and testing for the change-points
Since the introduction of autoregressive conditional heteroscedasticity (ARCH) by Engle, there has b...
The ARCH process (R. F. Engle, 1982) constitutes a paradigmatic generator of stochastic time series ...
In this paper, we develop a complete methodology for semiparametric inference in the time-varying AR...
This dissertation focuses on quadratic ARCH models with long memory. The class of ARCH models was in...
ARCH(∞) models nest a wide range of ARCH and GARCH models in- cluding models with long memory in vol...
In this paper the class of ARCH(∞) models is generalized to the nonsta-tionary class of ARCH(∞) mode...
In the paper a non-stationary ARCH model is defined and its relation with a heteroscedastic RCA mode...
We discuss models that impart a form of long memory in raw time series xt or instantaneous functions...
For a class of parametric ARCH models, Whittle estimation based on squared observations is shown to ...
We discuss the covariance structure and long-memory properties of stationary solutions of the biline...
The ARCH model and its many generalizations are very important in analysing discrete time financial ...
We consider ARCH processes with persistent covariates and provide asymptotic theories that explain h...
We consider a volatility model, named ARCH-NNH model, that is specifically an ARCH process with a no...
We consider ARCH processes with persistent covariates and provide asymptotic theories that explain h...
This paper provides a review of some recent theoretical results for time series models with GARCH er...
Since the introduction of autoregressive conditional heteroscedasticity (ARCH) by Engle, there has b...
The ARCH process (R. F. Engle, 1982) constitutes a paradigmatic generator of stochastic time series ...
In this paper, we develop a complete methodology for semiparametric inference in the time-varying AR...
This dissertation focuses on quadratic ARCH models with long memory. The class of ARCH models was in...
ARCH(∞) models nest a wide range of ARCH and GARCH models in- cluding models with long memory in vol...
In this paper the class of ARCH(∞) models is generalized to the nonsta-tionary class of ARCH(∞) mode...
In the paper a non-stationary ARCH model is defined and its relation with a heteroscedastic RCA mode...
We discuss models that impart a form of long memory in raw time series xt or instantaneous functions...
For a class of parametric ARCH models, Whittle estimation based on squared observations is shown to ...
We discuss the covariance structure and long-memory properties of stationary solutions of the biline...
The ARCH model and its many generalizations are very important in analysing discrete time financial ...
We consider ARCH processes with persistent covariates and provide asymptotic theories that explain h...
We consider a volatility model, named ARCH-NNH model, that is specifically an ARCH process with a no...
We consider ARCH processes with persistent covariates and provide asymptotic theories that explain h...
This paper provides a review of some recent theoretical results for time series models with GARCH er...
Since the introduction of autoregressive conditional heteroscedasticity (ARCH) by Engle, there has b...
The ARCH process (R. F. Engle, 1982) constitutes a paradigmatic generator of stochastic time series ...
In this paper, we develop a complete methodology for semiparametric inference in the time-varying AR...