This paper surveys recent developments related to the smooth transition autoregressive
(STAR) time series model and several of its variants. We put emphasis on new methods for …

This paper describes some recent advances and contributions to our understanding of
economic forecasting. The framework we develop helps explain the findings of forecasting …

Recently, support vector machine (SVM), a novel artificial neural network (ANN), has been
successfully used for financial forecasting. This paper deals with the application of SVM in …

We examine the unemployment hysteresis hypothesis for 31 European countries, the USA
and Japan, using alternative linear and nonlinear unit root tests, taking into account possible …

The debate on the forecasting ability of non-linear models has a long history, and the Great
Recession episode provides an interesting opportunity for a re-assessment of the …

In recent years there has been a considerable development in modelling non‐linearities and
asymmetries in economic and financial variables. The aim of the current paper is to compare …

Traditional autocorrelation and variance ratio tests are based on serial uncorrelatedness
rather than martingale difference. As such, they do not capture potential nonlinearity-in …

Nonlinear time series models have become fashionable tools to describe and forecast a
variety of economic time series. A closer look at reported empirical studies, however, reveals …

Exchange rate movements can significantly impact not only foreign trade, capital flows, and
asset portfolio management, but also real economic activity. Therefore, the forecast of …

Stock price prediction is a popular research domain for its complex data structure and
confounding factors. The use of Data science tools enormously increased along with the …