Abstract: We study so–called augmented GARCH sequences, which include many submodels of considerable interest, such as polynomial and exponential GARCH. To model the returns of speculative assets, it… (More)

ALEXANDER AUE0, LAJOS HORVÁTH1, MARIE HUŠKOVÁ2 AND PIOTR KOKOSZKA3 0Department of Mathematical Sciences, Clemson University, O-324 Martin Hall, Clemson, SC 29634, USA E-mail: alexaue@clemson.edu… (More)

This paper addresses the prediction of stationary functional time series. Existing contributions to this problem have largely focused on the special case of first-order functional autoregressive… (More)

The paper develops a comprehensive asymptotic theory for the estimation of a change– point in the mean function of functional observations. We consider both the case of a constant change size, and… (More)

We propose a unified quasi-likelihood procedure for the estimation of the unknown parameters of a first-order random coefficient autoregressive, RCA, model that works both for stationary and… (More)

We consider a nonlinear polynomial regression model in which we wish to test the null hypothesis of structural stability in the regression parameters against the alternative of a break at an unknown… (More)

We propose the quasi-maximum likelihood method to estimate the parameters of an RCA(1) process, i.e. a random coefficient autoregressive time series of order 1. The strong consistency and the… (More)

We discuss the limiting behavior of the serial correlation coefficient in mildly explosive autoregression, where the error sequence is in the domain of attraction of an α–stable law, α ∈ (0, 2].… (More)

We consider a multiple regression model in which the explanatory variables are specified by time series. To sequentially test for the stability of the regression parameters in time, we introduce a… (More)

Consider a linear model setting in which the explanatory variables are specified by time series. To sequentially test for the stability of the regression parameters in time, we introduce a detector… (More)