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Modelling and Forecasting Crude Oil Prices during COVID-19 Pandemic

Author

Listed:
  • Ernie Hendrawaty

    (Department of Management, Faculty of Economics and Business, Universitas Lampung, Lampung, Indonesia)

  • Rialdi Azhar

    (Department of Accounting, Faculty of Economics and Business, Universitas Lampung, Lampung, Indonesia.)

  • Fajrin Satria Dwi Kesumah

    (Department of Management, Faculty of Economics and Business, Universitas Lampung, Lampung, Indonesia)

  • Sari Indah Oktanti Sembiring

    (Department of Accounting, Faculty of Economics and Business, Universitas Lampung, Lampung, Indonesia.)

  • Mega Metalia

    (Department of Accounting, Faculty of Economics and Business, Universitas Lampung, Lampung, Indonesia.)

Abstract

Currently, the world suffers from the COVID-19 pandemic, which affects almost every aspect of daily life, giving rise to recession and affecting the world prices of crude oil. The study aims to model the high uncertainty of volatility as well as to forecast the daily prices of crude oil during the pandemic. One econometric model applied in this study is the Generalised Autoregressive Conditional Heteroscedasticity (GARCH) that allows more accurate and appropriate statistical analyses. Particularly, this study also discusses solving economic issues on the condition of any disturbances in the stability of daily crude oil prices. The findings suggest that the AR(1)-GARCH(1,1) model is a well-fitted model to predict relatively small errors. This model can act as a foundation for determining strategies in the future while facing such uncertain circumstances.

Suggested Citation

  • Ernie Hendrawaty & Rialdi Azhar & Fajrin Satria Dwi Kesumah & Sari Indah Oktanti Sembiring & Mega Metalia, 2021. "Modelling and Forecasting Crude Oil Prices during COVID-19 Pandemic," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 149-154.
    • Handle: RePEc:eco:journ2:2021-02-20
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    References listed on IDEAS

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    Cited by:

    1. Rialdi Azhar & Febryan Kusuma Wisnu & Fajrin Satria Dwi Kesuma & Widya Rizki Eka Putri & Rian Andri Prasetya, 2022. "State-space Implementation in Forecasting Carbon and Gas Prices in Commodity Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 280-286, May.
    2. Andr s Oviedo-G mez & Sandra Milena Londo o-Hern ndez & Diego Fernando Manotas-Duque, 2023. "Directional Spillover of Fossil Fuels Prices on a Hydrothermal Power Generation Market," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 85-90, January.
    3. Saring Suhendro & Mega Matalia & Sari Indah Oktanti Sembiring, 2021. "Public Sector Policy of Estimating Model for Renewable Energy," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 609-613.

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    More about this item

    Keywords

    Forecasting; COVID-19 pandemic; Crude oil prices; Pandemic; Generalised Autoregressive Conditional Heteroscedasticity model;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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