Nonlinear modeling of adjustments to purchasing power parity has recently gained much attention. However, a huge body of the empirical literature applies ESTAR models and neglects the existence of other competing nonlinear models. Among these, the Markov Switching AR model has a strong...

Long memory has been widely documented for realized financial market volatility. As a novelty, we consider daily realized asset correlations and we investigate whether the observed persistence is (i) due to true long memory (i.e. fractional integration) or (ii) artificially generated by some...

We consider hypothesis testing in a general linear time series regression framework when the possibly fractional order of integration of the error term is unknown. We show that the approach suggested by Vogelsang (1998a) for the case of integer integration does not apply to the case of...

Linearity testing against smooth transition autoregressive (STAR) models when deterministic trends are potentially present in the data is considered in this paper. As opposed to recently reported results in Zhang (2012), we show that linearity tests against STAR models lead to useful results in...

Linearity testing against smooth transition autoregressive (STAR) models when deterministic trends are potentially present in the data is considered in this paper. As opposed to recently reported results in Zhang (2012), we show that linearity tests against STAR models lead to useful results in...

We show that tests for a break in the persistence of a time series in the classical I(0)/I(1) framework have serious size distortions when the actual data-generating process (DGP) exhibits long-range dependencies. We prove that the limiting distribution of a CUSUM of squares-based test depends...

We consider the problem of forecasting time series with long memory when the memory parameter is subject to a structural break. By means of a large-scale Monte Carlo study we show that ignoring such a change in persistence leads to substantially reduced forecasting precision. The strength of...