Groundnut price forecasting using Auto Regressive Integrated Moving Average (ARIMA) model: GROUNDNUT PRICE FORECASTING USING AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE MODEL - R VIJAYA KUMARI; VENKATESH PANASA; G RAMAKRISHNA; A SREENIVAS (Journal of Oilseeds Research, 2025)
This paper analyzes the monthly modal prices of groundnut in Telangana using Autoregressive Integrated Moving Average (ARIMA) models to determine the most efficient and suitable model for forecasting these prices. The results show that the ARIMA (2,1,2) model was the most appropriate and effective for forecasting, based on comparison of model selection criteria and diagnostic tests, the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Mean Absolute Percentage Error (MAPE), along with the significance of the (p,d,q) parameters. Time series analysis was conducted using SAS 9.3 software. The forecast indicated that during the rabi (yasangi) season, groundnut prices in the Gadwal market ranged from ` 6600-7000 per quintal (January to March 2025). The Minimum Support Price (MSP) for groundnut was ` 6783 per quintal for the 2024-25 marketing season. A comprehensive understanding of groundnut price trends and future projections will assist farmers and other stake holders in making informed decisions regarding buying and selling patterns. Therefore, the government should implement suitable policies to support the sector. This highlights the need for the government to adopt appropriate measures to ensure that both farmers and end users benefit from price stability