We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor's 500...

This paper extends the family of smooth transition autoregressive (STAR) models by proposing a speci.cation in which the autoregressive parameters follow random walks. The random walks in the parameters capture permanent structural change within a regime switching framework, but in contrast to...

Smooth-transition autoregressive (STAR) models, competitors of Markov-switching models, are limited by an assumed time-invariant threshold level. We augment the STAR model with a time-varying threshold that can be interpreted as a 'tipping level' where the mean and dynamics of the VAR shift....