The empirical relevance of long memory conditional heteroscedasticity has emerged in a variety of studies of long time series of high frequency financial measurements. A reassessment of the applicability of existing semiparametric frequency domain tools for the analysis of time dependence and long run behaviour of time series is therefore warranted. To that end, this paper analyses the averaged periodogram statistic in the framework of a generalized linear process with long memory conditional heteroscedastic innovations according to a model specification first proposed by Robinson (1991). It is shown that the averaged periodogram estimate of the spectral density of a short memory process remains asymptotically normal with unchanged asymptot...
This paper reinterprets results of Ohanissian et al (2003) to show the asymptotic equivalence of tem...
Robust parameter estimation and pivotal inference is crucial for credible statistical conclusions. T...
This paper proposes an extension of the log periodogram regression in perturbed long memory series t...
Semiparametric spectral methods seem particularly appropriate for the analysis of long financial tim...
This dissertation considers semiparametric spectral estimates of temporal dependence in time series....
Semiparametric estimates of long memory seem useful in the analysis of long financial time series be...
Semiparametric estimates of long memory seem useful in the analysis of long financial time series be...
The estimation of the memory parameter in perturbed long memory series has recently attracted attent...
Abstract. The paper is concerned with the estimation of the long memory parameter in a condi-tionall...
We study problems of semiparametric statistical inference connected with long-memory covariance stat...
We show the consistency of the log-periodogram regression estimate of the long memory parameter for ...
We consider a general long memory time series, assumed stationary and linear, but not necessarily Ga...
This article revises semiparametric methods of inference on different aspects of long mem-ory time s...
This thesis examines some statistical procedures in the frequency domain to analyze long-memory seri...
We analyse the properties of nonparametric spectral estimates when applied to long memory and trendi...
This paper reinterprets results of Ohanissian et al (2003) to show the asymptotic equivalence of tem...
Robust parameter estimation and pivotal inference is crucial for credible statistical conclusions. T...
This paper proposes an extension of the log periodogram regression in perturbed long memory series t...
Semiparametric spectral methods seem particularly appropriate for the analysis of long financial tim...
This dissertation considers semiparametric spectral estimates of temporal dependence in time series....
Semiparametric estimates of long memory seem useful in the analysis of long financial time series be...
Semiparametric estimates of long memory seem useful in the analysis of long financial time series be...
The estimation of the memory parameter in perturbed long memory series has recently attracted attent...
Abstract. The paper is concerned with the estimation of the long memory parameter in a condi-tionall...
We study problems of semiparametric statistical inference connected with long-memory covariance stat...
We show the consistency of the log-periodogram regression estimate of the long memory parameter for ...
We consider a general long memory time series, assumed stationary and linear, but not necessarily Ga...
This article revises semiparametric methods of inference on different aspects of long mem-ory time s...
This thesis examines some statistical procedures in the frequency domain to analyze long-memory seri...
We analyse the properties of nonparametric spectral estimates when applied to long memory and trendi...
This paper reinterprets results of Ohanissian et al (2003) to show the asymptotic equivalence of tem...
Robust parameter estimation and pivotal inference is crucial for credible statistical conclusions. T...
This paper proposes an extension of the log periodogram regression in perturbed long memory series t...