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

• Authors: Singh Abhishek , Mishra G. C.
• Languages of publication: EN

Abstracts

EN

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

EN

forecasting; feed forward network; ARIMA; ANN

• Publisher: Główny Urząd Statystyczny
• Journal: Statistics in Transition new series
• Year: 2015
• Volume: 16
• Issue: 1
• Pages: 83–96

Contributors

author

Singh Abhishek

• Department of Farm Engineering; Institute of Agricultural Sciences; Banaras Hindu University, Varanasi, India

author

Mishra G. C.

• Department of Farm Engineering; Institute of Agricultural Sciences; Banaras Hindu University, Varanasi, India

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