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Abstract <p>Hom Thong banana is an economically major climacteric fruit for local and export markets worldwide, a database for planning the Hom Thong banana corresponding to the price variation is very important. This research aims to apply time series analysis techniques to forecast the price of Hom Thong bananas in Thailand. We analyze the time series data of quarterly Hom Thong banana farm gate prices which are collected from Office of Agricultural Economics over consecutive quarters from the first quarter of 2005 to the fourth quarter of 2023. Three forecasting models are considered to be fitted to the data, including the additive winter’s model, the seasonal autoregressive integrated moving average <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12202_2025_8205_Article_IEq1.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="110" /> </InlineMediaObject> <EquationSource Format="TEX">\((1,0,0)(1,0,0)_{4}\)</EquationSource> <!--LobJMat2560026Sannork-m1--> </InlineEquation> model, and combined model. The root-mean-square error and mean absolute percentage error are investigated to compare the accuracy of models. The result shows that the combined model is the most appropriate method. The forecasting values from 2024 to 2033 from the combined model also show that the highest price of Hom Thong banana would be from the third to the fourth quarters and the lowest price would be from the first to the second quarters. Farmers can apply these forecasts for planning Hom Thong banana production according to the period of low and high price.</p>

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Application of Time Series Analysis to Forecast Hom Thong Banana Price in Thailand

  • 期刊论文

  • 发表日期：

    2025年2月1日

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  • Jakkreeporn Sannork,
  • Onuma Thonglor,
  • Sudarat Nidsunkid

摘要

Abstract

Hom Thong banana is an economically major climacteric fruit for local and export markets worldwide, a database for planning the Hom Thong banana corresponding to the price variation is very important. This research aims to apply time series analysis techniques to forecast the price of Hom Thong bananas in Thailand. We analyze the time series data of quarterly Hom Thong banana farm gate prices which are collected from Office of Agricultural Economics over consecutive quarters from the first quarter of 2005 to the fourth quarter of 2023. Three forecasting models are considered to be fitted to the data, including the additive winter’s model, the seasonal autoregressive integrated moving average \((1,0,0)(1,0,0)_{4}\) model, and combined model. The root-mean-square error and mean absolute percentage error are investigated to compare the accuracy of models. The result shows that the combined model is the most appropriate method. The forecasting values from 2024 to 2033 from the combined model also show that the highest price of Hom Thong banana would be from the third to the fourth quarters and the lowest price would be from the first to the second quarters. Farmers can apply these forecasts for planning Hom Thong banana production according to the period of low and high price.