Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/334137 
Year of Publication: 
2025
Citation: 
[Journal:] Asian Journal of Economics and Banking (AJEB) [ISSN:] 2633-7991 [Volume:] 9 [Issue:] 1 [Year:] 2025 [Pages:] 64-82
Publisher: 
Emerald, Leeds
Abstract: 
Purpose - Developing price forecasts for various agricultural commodities has long been a significant undertaking for a variety of agricultural market players. The weekly wholesale price of edible oil in the Chinese market over a ten-year period, from January 1, 2010 to January 3, 2020, is the forecasting issue we explore. Design/methodology/approach - Using Bayesian optimisations and cross-validation, we study Gaussian process (GP) regressions for our forecasting needs. Findings - The produced models delivered precise price predictions for the one-year period between January 4, 2019 and January 3, 2020, with an out-of-sample relative root mean square error of 5.0812%, a root mean square error (RMSEA) of 4.7324 and a mean absolute error (MAE) of 2.9382. Originality/value - The projection's output may be utilised as stand-alone technical predictions or in combination with other projections for policy research that involves making assessment.
Subjects: 
Bayesian optimization
Chinese market
Cross-validation
Gaussian process regression
Price forecasting
Wholesale edible oil
JEL: 
C22
C53
C63
Q11
Q13
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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