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

• Autorzy: Abhishek Singh , G.C. Mishra
• Języki publikacji: EN

Abstrakty

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. (original abstract)

Słowa kluczowe

EN

Prediction of prices; Autoregressive integrated moving average (ARIMA) models; Artificial neural networks (ANN)

PL

Prognozowanie cen; Modele ARIMA; Sztuczne sieci neuronowe (SSN)

• Czasopismo: Statistics in Transition
• Rocznik: 2015
• Tom: 16
• Numer: nr 1
• Strony: 83--96

Twórcy

autor

Abhishek Singh

• Banaras Hindu University, India

autor

G.C. Mishra

• Banaras Hindu University, India

Bibliografia

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