The generalized autoregressive conditional heteroskedasticity (GARCH) process is an econometric term used to describe an approach to estimate volatility in financial markets.

We propose a multiplicative component conditional autoregressive range (MCCARR) model to capture the "long-memory" effect in volatility. We show both theoretically and empirically that the MCCARR ...

This paper extends the classical two-regime threshold autoregressive model by introducing hysteresis to its regime-switching structure, which leads to a new model: the hysteretic autoregressive model.

Trend models are suitable for capturing long-term behavior, whereas autoregressive models are more appropriate for capturing short-term fluctuations. One approach to forecasting is to combine a ...

The model assumed is first-order autoregressive with contemporaneous correlation between cross sections. In this model, the covariance matrix for the vector of random errors u can be expressed as A ...

We generalize the Gaussian mixture transition distribution (GMTD) model introduced by Le and co-workers to the mixture autoregressive (MAR) model for the modelling of non-linear time series. The ...