- Autor
- Singh Abhishek (Banaras Hindu University, India), Mishra G.C. (Banaras Hindu University, India)
- Tytuł
- Application of Box-Jenkins Method and Artificial Neural Network Procedure for Time Series Forecasting of Prices
- Źródło
- Statistics in Transition, 2015, vol. 16, nr 1, s. 83-96, rys., tab., bibliogr. s. 95-96
- Słowa kluczowe
- Prognozowanie cen, Modele ARIMA, Sztuczne sieci neuronowe (SSN)
Prediction of prices, Autoregressive integrated moving average (ARIMA) models, Artificial neural networks (ANN) - Uwagi
- summ.
- Abstrakt
- 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)
- Dostępne w
- Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach - Pełny tekst
- Pokaż
- Bibliografia
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- Cytowane przez
- ISSN
- 1234-7655
- Język
- eng