Modelling the dynamic dependent data by the linear approach is the most popular among
the researchers because of its simplicity in calculation and approximation, however, in real …

In economies that are open to foreign markets the numerical value of the currencies as a
macroeconomic variable is of great importance especially when the mutual dependency …

We introduce a short-term time series prediction model by means of evolutionary algorithms
and Bernstein polynomials. This adapts Bernstein-type algebraic skeletons to extrapolate …

This study explores the multi-step ahead forecasting performance of a so-called hybrid
conditional quantile method, which combines relevant conditional quantile forecasts from …

One of the major importance of modeling in time series is to forecast future values of that
series which requires the use of appropriate method to fit the time series data that are …

This study is on Self-Exciting Threshold Auto regressive (SETAR) modeling of the NSE 20
Share Index using the Bayesian approach. The objectives of the study are toana-lyze the …