A Study on Forecasting Prices of Groundnut Oil in Delhi by Arima Methodology and Artificial Neural Networks

Forecasting of prices of commodities specially those of agricultural commodities is very difficult because they are not only governed by demand and supply but by so many other factors which are beyond control like weather vagaries, storage capacity, transportation etc. In this paper times series namely ARIMA (Autoregressive Integrated Moving Average) methodology given by Box and Jenkins has been used for forecasting prices of edible oils and this approach has been compared with ANN (Artificial Neural Network) methodology.


Issue Date:
Sep 30 2013
Publication Type:
Journal Article
DOI and Other Identifiers:
1804-1930 (Other)
PURL Identifier:
http://purl.umn.edu/157527
Published in:
Volume 05, Number 3
AGRIS on-line Papers in Economics and Informatics
Page range:
25-34
Total Pages:
10
JEL Codes:
GA; IN
Series Statement:
5
3




 Record created 2017-04-01, last modified 2017-08-27

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