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

Abhishek  Singh; G. C.  Mishra

doi:https://doi.org/10.59170/stattrans-2015-005

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

Abhishek Singh Asstt. Prof., Department of Farm Engineering; Institute of Agricultural Sciences; Banaras Hindu University, Varanasi, India-221005. , G. C. Mishra Prof., Department of Farm Engineering; Institute of Agricultural Sciences; Banaras Hindu University, Varanasi, India-221005. Statistics in Transition new series, vol. 16, 2015, 1, pages: 83-96 Published online: 2 March 2015 https://doi.org/10.59170/stattrans-2015-005

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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.

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