Development of Seasonal ARIMA Model to Predict Wholesale Price of Rice in Delhi Market
. Sanjeev, Rohit Kundu, Ajay Sharma, . Preeti
Current Journal of Applied Science and Technology · pp. 155–161 · Published 31 Dec 2022
10.9734/cjast/2022/v41i484050Abstract
Price prediction is more acute with rice crops particularly due to its seasonality. Prediction of rice prices can provide critical and useful information to rice growers making production and marketing decisions. The objectives of this paper were to analyze the wholesale price of rice crop and to develop a Seasonal ARIMA model to predict the monthly rice prices at wholesale level in Delhi, for years 2021. Autocorrelation function (ACF) and partial autocorrelation function (PACF) were estimated, which led to the identification and construction of Seasonal ARIMA models, for explaining the time series and help the future forecasting of rice price. SARIMA (1, 1, 1) (0, 1, 1)12 model was selected as the most suitable model to predict rice price based on RMSE, MAPE and AIC.
Cited by 5
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