Advanced Time Series Data Analysis: Forecasting Using EViews

Advanced Time Series Data Analysis presents advanced univariate multiple regressions, which can directly be used to forecast their dependent variables, evaluate their in-sample forecast values, and  compute forecast values beyond the sample period. 

Various alternative multiple regressions models are presented based on a single time series, bivariate, and triple time-series, which are developed by taking into account specific growth patterns of each dependent variables, starting with the simplest model up to the most advanced model. Graphs of the observed scores and the forecast evaluation of each of the models are presented, to show the worst and the best forecast models among each set of the models of a  specific independent variable. Most of these models, the interaction models in particular, are recorded here for the first time.

This book will appeal to researchers and practitioners in forecasting models, as well as those studying quantitative data analysis. It is suitable for those wishing to obtain a better knowledge and understanding on forecasting, specifically the uncertainty of  forecast values.