АВТОМАТИЗИРАНА АНАЛИТИКА: ПРОГНОЗИРАНЕ НА ВРЕМЕВИ РЕДОВЕ В ИКОНОМИКАТА И БИЗНЕСА

Abstract

This paper demonstrates a feasible approach to fit an automated forecasting algorithm on four crucial economic time series from the Bulgarian economy. We use data on GDP growth, inflation, unemployment, and interest rates and estimate a large number of possible models. The best ones are selected by taking recourse to the Akaike Information Criterion. The optimal ARIMA models are studied and commented. Forecast accuracy metrics are presented and a few major conclusions and possible model applications are outlined. The paper concludes with directions for further research.