Forecasting of mango prices by simple linear arima model

Abstract

This study examines the trends in the prices of Mango in the Rajnandgaon district of Chhattisgarh of daily from 2017-18 to 2023-24. Data were sourced from Agmarknet the official government price site. The ARIMA (Autoregressive Integrated Moving Average) model was used to forecast future trends. For Mango prices, the ARIMA model alone can fully capture the nonlinear trends in the data. The forecasts became more accurate, with lower error rates. This model effectively captured both simple and complex patterns, making it more reliable for predicting mango prices. These findings underscore the importance of selecting appropriate models based on data characteristics to enhance forecasting accuracy in agriculture market prices.