Agricultural Product Price Forecasting using ARIMA Model
Saroj Kanta Biswal1, Anita Sahoo2
1Dr. Saroj Kanta Biswal, MBA, MTA, LLB, PhD (Associate Professor) Research area is Behavioral Finance, Business Analytics,
2Mrs. Anita Sahoo, M.Com, M.Phil, MBA (Assistant Professor) Research areas like Accounting & Costing, Corporate Restructuring, Taxation.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 5203-5207 | Volume-8 Issue-5, January 2020. | Retrieval Number: D7606118419/2020©BEIESP | DOI: 10.35940/ijrte.D7606.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The study consider the comparison of actual market price of green gram and the forecasted price of green gram to identify how close the forecasting tools help to identify the market price of agro product in future. This analysis will help to identify the expected fluctuation from the expected price and actual price of a commodity that will support the farmers and middle to decide the price of a particular commodity. In this study the green gram price of Odisha (India) is taken into consideration for analysis. The study will also explore the best method to identify the future market price. For the analysis weekly price of the product is considered and seasonal ARIMA (1, 1, 1) (1, 0, 1), S=4 model is used as it was found to be the best model for forecasting. It is expected that this analysis will benefit the farmers in deciding the price of the products and support in rescheduling their crop as per the price movement in future.
Keywords: Forecasting price, ARIMA, Indian Agro Products, Green Gram.
Scope of the Article: Agricultural Informatics and Communication.