Agricultural Product Price Forecasting Methods: A Review

Feihu Sun, Xianyong Meng, Yan Zhang, Yan Wang, Hongtao Jiang and Pingzeng Liu ()
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Feihu Sun: School of Information Science and Engineering, Shandong Agricultural University, Taian 271018, China
Xianyong Meng: School of Information Science and Engineering, Shandong Agricultural University, Taian 271018, China
Yan Zhang: School of Information Science and Engineering, Shandong Agricultural University, Taian 271018, China
Yan Wang: School of Information Science and Engineering, Shandong Agricultural University, Taian 271018, China
Hongtao Jiang: School of Information Science and Engineering, Shandong Agricultural University, Taian 271018, China
Pingzeng Liu: School of Information Science and Engineering, Shandong Agricultural University, Taian 271018, China

Agriculture, 2023, vol. 13, issue 9, 1-20

Abstract: Agricultural price prediction is a hot research topic in the field of agriculture, and accurate prediction of agricultural prices is crucial to realize the sustainable and healthy development of agriculture. It explores traditional forecasting methods, intelligent forecasting methods, and combination model forecasting methods, and discusses the challenges faced in the current research landscape of agricultural commodity price prediction. The results of the study show that: (1) The use of combined models for agricultural product price forecasting is a future development trend, and exploring the combination principle of the models is a key to realize accurate forecasting; (2) the integration of the combination of structured data and unstructured variable data into the models for price forecasting is a future development trend; and (3) in the prediction of agricultural product prices, both the accuracy of the values and the precision of the trends should be ensured. This paper reviews and analyzes the methods of agricultural product price prediction and expects to provide some help for the development of research in this field.

Keywords: price forecasting; combined models; intelligent prediction methods; agricultural product price (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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