Abstract
This paper is devoted to the presentation of methods of economic time series analysis and modelling using the Box-Jenkins methodology, the signal processing approach and the feedforward neural network technique. Some results of our research on time series modelling with emphasis on potential improving forecast accuracy are presented here. The assessment of the particular models has been made using the root mean square error.
Highlights
Artificial neural network (ANN) is being applied to many problems far removed from their first beginnings
There is much controversy about the application of traditional statistical or econometric models and the ANN approaches within the field of economic time series modelling and forecasting. These controversies are based on the assumptions that there is no consensus at all on whether there is chaos in economic time series or not
Many of modelling techniques of autoregressive processes are based on recent developments in time series analysis recently consolidated and presented by Box and Jenkins [4]
Summary
Artificial neural network (ANN) is being applied to many problems far removed from their first beginnings. Application to management problems have included predicting bankruptcy [3], predicting ratings of corporate bonds [11], forecasting financial markets [6] and time series forecasting [7]. Their main strengths lie in pattern recognition and have been a hot topic of research for many years now. There is much controversy about the application of traditional statistical or econometric models and the ANN approaches within the field of economic time series modelling and forecasting. Many of modelling techniques of autoregressive processes are based on recent developments in time series analysis recently consolidated and presented by Box and Jenkins [4]. By using only the actual and forecast values within the ex post forecasting period only, the accuracy of the model can be calculated
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Communications - Scientific letters of the University of Zilina
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
