Modelling and forecasting symbolic data, especially interval-valued time series (ITS) data, has received considerable attention in statistics and related fields. The core of available methods on ITS analysis is based on various applications of conventional linear modelling. However, few works...

Modelling and forecasting symbolic data, especially interval-valued time series (ITS) data, has received considerable attention in statistics and related fields. The core of available methods on ITS analysis is based on various applications of conventional linear modelling. However, few works...

We propose two parsimonious autoregressive conditional interval-valued (ACI) models to forecast crude oil prices. The ACI models are a new class of time series models proposed by Han et al. (2009). They can characterize the dynamics of economic variables in both level and range of variation in a...

Modelling and forecasting interval-valued time series (ITS) have received increasing attention in statistics and econometrics. An interval-valued observation contains more information than a point-valued observation in the same time period. The previous literature has mainly considered modelling...