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Predicting wholesale edible oil prices through Gaussian process regressions tuned with Bayesian optimization and cross-validation

Author

Listed:
  • Bingzi Jin
  • Xiaojie Xu

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.

Suggested Citation

  • Bingzi Jin & Xiaojie Xu, 2024. "Predicting wholesale edible oil prices through Gaussian process regressions tuned with Bayesian optimization and cross-validation," Asian Journal of Economics and Banking, Emerald Group Publishing Limited, vol. 9(1), pages 64-82, December.
    • Handle: RePEc:eme:ajebpp:ajeb-06-2024-0070
    DOI: 10.1108/AJEB-06-2024-0070
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    More about this item

    Keywords

    Wholesale edible oil; Price forecasting; Gaussian process regression; Bayesian optimization; Cross-validation; Chinese market; C22; C53; C63; Q11; Q13;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

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