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Analysis of Precious Metal Price Movements Using Long Memory Model and Fuzzy Time Series Markov Chain

Author

Listed:
  • Erman Arif

    (Department of Information System, Indonesia Universitas Terbuka, Tangerang Selatan 15437, Indonesia,)

  • Dodi Devianto

    (Department of Mathematics and Data Science, Andalas University, Padang 25163, Indonesia.)

  • Mutia Yollanda

    (Department of Mathematics and Data Science, Andalas University, Padang 25163, Indonesia.)

  • Afrimayani Afrimayani

    (Department of Mathematics and Data Science, Andalas University, Padang 25163, Indonesia.)

Abstract

Precious metals occur naturally and have a high resistance to corrosion or oxidation. These natural resources are used as investment instruments to protect wealth values, such as gold, silver, and palladium. Price movements need to be understood when investing, and it is achieved through a time series model that predicts future prices. Also, autoregressive fractional integrated moving average (ARFIMA) is used to model price movements with long memory effects, while fuzzy time series Markov chain (FTSMC) is employed for performing numerical approach. It was observed that gold price movement has a long memory effect; therefore, it is eligible to be formed into the ARFIMA model. However, the silver and palladium prices do not contain a long memory effect, which means their movements are only formed through the FTSMC numerical model. The ARFIMA modeling results show that the gold price long memory model has the best accuracy with the smallest error value and also demonstrates excellent goodness of fit. Furthermore, the gold price long memory model movement has long-term stability compared to other precious metals. This provides an investment advantage because it is a stable asset, easy to liquidate in cash, free of interest, has an emergency fund role, and protects wealth s value.

Suggested Citation

  • Erman Arif & Dodi Devianto & Mutia Yollanda & Afrimayani Afrimayani, 2022. "Analysis of Precious Metal Price Movements Using Long Memory Model and Fuzzy Time Series Markov Chain," International Journal of Energy Economics and Policy, Econjournals, vol. 12(6), pages 202-214, November.
    • Handle: RePEc:eco:journ2:2022-06-27
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Precious metal; Long memory; Fuzzy time series Markov chain; Level of accuracy;
    All these keywords.

    JEL classification:

    • 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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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