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Forecasting Models Based on Fuzzy Logic: An Application on International Coffee Prices

Author

Listed:
  • Fatih Chellai

    (Department of Basic Education, Ferhat Abbas University, Setif, Algeria)

Abstract

In recent decades, Fuzzy Time Series (FTS) has become a competitive, sometimes complementary, approach to classical time series methods such as that of Box-Jenkins. This study has two different purposes: a theoretical purpose, presenting an overview of the fuzzy logic and fuzzy time series models, and a practical purpose, which is to estimate and forecast monthly international coffee prices during the period 2000-2022. Analysing and forecasting the dynamics of coffee prices is of great interest to producers, consumers, and other market actors in managing and making rational decisions. The findings showed that international coffee prices exhibited significant fluctuations, with large increases and decreases influenced mainly by the level of top-ranked producers. The forecasted results revealed that a decrease in prices during the next six months (Jan 2023 to June 2023) is expected. Based on the results, it is also clear that the FTS models are more flexible and can be applied in forecasting time-series variables. At the same time, volatility and, sometimes, the unexpected swingsin coffee prices continue to draw more criticism and raise different issues regarding the roles of the markets and countries in ensuring food security.

Suggested Citation

  • Fatih Chellai, 2022. "Forecasting Models Based on Fuzzy Logic: An Application on International Coffee Prices," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 26(4), pages 1-16, December.
    • Handle: RePEc:vrs:eaiada:v:26:y:2022:i:4:p:1-16:n:1
    DOI: 10.15611/eada.2022.4.01
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    References listed on IDEAS

    as
    1. Singh, S.R., 2008. "A computational method of forecasting based on fuzzy time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 539-554.
    2. Yen Pham & Kathryn Reardon-Smith & Shahbaz Mushtaq & Geoff Cockfield, 2019. "The impact of climate change and variability on coffee production: a systematic review," Climatic Change, Springer, vol. 156(4), pages 609-630, October.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    fuzzy logic; time series; forecasting; coffee prices; FTS models;
    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
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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