In this paper, we conduct semi-parametric estimation for autoregressive conditional heteroscedasticity (ARCH) model with Quasi likelihood (QL) and Asymptotic Quasi-likelihood (AQL) estimation methods. The QL approach relaxes the distributional assumptions of ARCH processes. The AQL technique is obtained from the QL method when the process conditional variance is unknown. We present an application of the methods to a daily exchange rate series. Keywords: ARCH model, Quasi likelihood (QL), Asymptotic Quasi-likelihood (AQL), Martingale difference, Kernel estimato
The author presents asymptotic results for the class of pseudo-likelihood estimators in the autoregr...
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatil...
We investigate a class of semiparametric ARCH(∞) models that includes as a special case the partiall...
AbstractIn this paper, we conduct semi-parametric estimation for autoregressive conditional heterosc...
Abstract: This paper studies asymptotic properties of the quasi-maximum likelihood estimator (QMLE) ...
This article studies asymptotic properties of the quasi-maximum likelihood estimator (QMLE) for the ...
The autoregressive conditional heteroscedastic (ARCH) model and its extensions have been widely used...
In this paper, estimation for the generalized autoregressive conditional heteroscedasticity (GARCH) ...
We provide simulation and theoretical results concerning the finite-sample theory of quasi-maximum-l...
In this paper, we develop a complete methodology for semiparametric inference in the time-varying AR...
We establish consistency and asymptotic normality of the quasi-maximum likelihood estimator in the l...
We provide three new results concerning quasi-maximum likelihood (QML) estimators in generalized aut...
ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper s...
in pressInternational audienceWe develop a complete methodology for detecting time varying or non-ti...
We provide simulation and theoretical results concerning the finite-sample theory of quasi-maximum-l...
The author presents asymptotic results for the class of pseudo-likelihood estimators in the autoregr...
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatil...
We investigate a class of semiparametric ARCH(∞) models that includes as a special case the partiall...
AbstractIn this paper, we conduct semi-parametric estimation for autoregressive conditional heterosc...
Abstract: This paper studies asymptotic properties of the quasi-maximum likelihood estimator (QMLE) ...
This article studies asymptotic properties of the quasi-maximum likelihood estimator (QMLE) for the ...
The autoregressive conditional heteroscedastic (ARCH) model and its extensions have been widely used...
In this paper, estimation for the generalized autoregressive conditional heteroscedasticity (GARCH) ...
We provide simulation and theoretical results concerning the finite-sample theory of quasi-maximum-l...
In this paper, we develop a complete methodology for semiparametric inference in the time-varying AR...
We establish consistency and asymptotic normality of the quasi-maximum likelihood estimator in the l...
We provide three new results concerning quasi-maximum likelihood (QML) estimators in generalized aut...
ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper s...
in pressInternational audienceWe develop a complete methodology for detecting time varying or non-ti...
We provide simulation and theoretical results concerning the finite-sample theory of quasi-maximum-l...
The author presents asymptotic results for the class of pseudo-likelihood estimators in the autoregr...
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatil...
We investigate a class of semiparametric ARCH(∞) models that includes as a special case the partiall...