EconPapers    
Economics at your fingertips  
 

Application of Box-Jenkins method and Artificial Neural Network procedure for time series forecasting of prices

Abhishek Singh () and G. C. Mishra ()

Statistics in Transition new series, 2015, vol. 16, issue 1, 83-96

Abstract: Forecasting of prices of commodities, especially those of agricultural commodities, is very difficult because they are not only governed by demand and supply but also by so many other factors which are beyond control, such as weather vagaries, storage capacity, transportation, etc. In this paper time series models namely ARIMA (Autoregressive Integrated Moving Average) methodology given by Box and Jenkins has been used for forecasting prices of Groundnut oil in Mumbai. This approach has been compared with ANN (Artificial Neural Network) methodology. The results showed that ANN performed better than the ARIMA models in forecasting the prices.

Keywords: forecasting; feed forward network; ARIMA; ANN. (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v16_2016_i1_n6.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:csb:stintr:v:16:y:2015:i:1:p:83-96

Access Statistics for this article

Statistics in Transition new series is currently edited by Włodzimierz Okrasa

More articles in Statistics in Transition new series from Główny Urząd Statystyczny (Polska) Contact information at EDIRC.
Bibliographic data for series maintained by Beata Witek ( this e-mail address is bad, please contact ).

 
Page updated 2021-03-28
Handle: RePEc:csb:stintr:v:16:y:2015:i:1:p:83-96