We discuss estimation of so-called long vector autoregressions for multivariate series exhibiting possibly time-varying mean and (co)variances. In applied work, such changes often escape undetected, and we ask how standard tools (least squares estimation, point forecasts, and estimated impulse...

This paper addresses the fundamental topic of time dependence for time series when data points are given as functions. We construct a notion of time dependence through the scores of the principal components, which allows us to adapt various scalar time series techniques to the functional data...

This paper develops a Lagrange multiplier test statistic and its variants to test for the null hypothesis of no asymmetric effects of shocks on time series. In asymmetric time series models that allow for different responses to positive and negative past shocks the likelihood functions are, in...

Over recent years several methods to deal with high-frequency data (economic, financial and other) have been proposed in the literature. An interesting example is for instance interval valued time series described by the temporal evolution of high and low prices of an asset. In this paper a new...