Author(s): CK Nihala Asees and AD Kalola

Abstract: Agricultural commodities such as groundnut and groundnut oil hold significant importance in India’s economy and food system. However, their prices are subject to high volatility due to a range of factors including seasonal variations, weather uncertainties, policy changes and global market dynamics. In such a scenario, accurate price forecasting becomes crucial for farmers, traders and policy makers to make informed decisions regarding production, marketing and inventory management. In light of these, the present study was undertaken with the primary objective of developing the linear Autoregressive Integrated Moving Average (ARIMA) model for predicting the monthly prices of groundnut oil for Rajkot market of Gujarat using the time series data from January 2006 to December 2025. The model was selected based on the AIC and BIC statistics. The accuracy of the forecasts was also evaluated using the error metrics like RMSE, MAE and MAPE. The ACF residual plot as well as Ljung-Box test were employed to check the residuals autocorrelation. The analysis resulted in selection of ARIMA (0, 1, 1) model with a drift parameter as the best fitting model for forecasting the monthly groundnut oil prices of Rajkot market. The model was found to have a lower RMSE of 568.38, MAE of 420.11 and an MAPE of 4.6 percent. The forecast of groundnut oil price for Rajkot market was found to have an upward trend indicating an increasing price in 2025-2026 period.

Pages: 15-20 | Views: 785 | Downloads: 3

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