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Journal of Pharmacognosy and Phytochemistry

Journal of Pharmacognosy and Phytochemistry

Vol. 8, Issue 3 (2019)

Forecasting coconut oil price using auto regressive integrated moving average (ARIMA) model

Author(s):

Priyanga V, T Paul Lazarus, Shilpa Mathew and Brigit Joseph

Abstract:
The study deals with the analysis of times series data on monthly wholesale prices of coconut oil in Cochin market at Kerala during January 2008 to December 2018. Augmented Dicky Fuller test was used for testing the stationarity of the series. Box- Jenkins Auto Regressive Integrated Moving Average method was used for modelling and forecasting the price of coconut oil in Cochin market. Various model selection criteria such as Akaike Information Criteria (AIC) and Schwarz Information Criteria (SIC) were used for the identification of representative model for forecasting. Analysis was done using Gretl software. The results indicated that ARIMA (1, 2, 1) model was the most adequate and efficient model for forecasting the prices of coconut oil. The results showed that there is an expectation of price of coconut oil to be in the range between ₹ 2200 to 2300 per 15 kg in Cochin market at Kerala for the period January to December 2019.

Pages: 2164-2169  |  1471 Views  758 Downloads


Journal of Pharmacognosy and Phytochemistry Journal of Pharmacognosy and Phytochemistry
How to cite this article:
Priyanga V, T Paul Lazarus, Shilpa Mathew and Brigit Joseph. Forecasting coconut oil price using auto regressive integrated moving average (ARIMA) model. J Pharmacogn Phytochem 2019;8(3):2164-2169.

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