Application of Box-Jenkins Method and Artificial Neural Network Procedure for Time Series Forecasting of Prices

Singh, Abhishek; Mishra, G.C.

Author

Singh Abhishek (Banaras Hindu University, India), Mishra G.C. (Banaras Hindu University, India)

Title

Application of Box-Jenkins Method and Artificial Neural Network Procedure for Time Series Forecasting of Prices

Source

Statistics in Transition, 2015, vol. 16, nr 1, s. 83-96, rys., tab., bibliogr. s. 95-96

Keyword

Prognozowanie cen, Modele ARIMA, Sztuczne sieci neuronowe (SSN)
Prediction of prices, Autoregressive integrated moving average (ARIMA) models, Artificial neural networks (ANN)

Note

summ.

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. (original abstract)

Accessibility

The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice

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ISSN

1234-7655

Language

eng

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