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Oil Price Dynamics Forecasting: An Indicator-Pivoted Paradigm

Author

Listed:
  • Mei-Teing Chong

    (Faculty of Economics and Business, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia,)

  • Chin-Hong Puah

    (Faculty of Economics and Business, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia,)

  • Shazali Abu Mansor

    (Faculty of Economics and Business, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia.)

Abstract

Changes in the price of crude oil have significant impacts on a company s production cost. Therefore, research on forecasting the movement of oil prices is imperative to obtain a profound yet forward-looking idea regarding their future direction. Contributing to this effort, this paper endeavours to design and build an oil price indicator that incorporates the ability to determine lead time and has great predictive power and directional accuracy. Applying the indicator construction approach, the present study successfully constructed an OPI with an average leading time of 3.6 months, moving ahead of West Texas Intermediate, a main crude oil benchmark used across the globe. The results revealed that OPI achieves as high as 75.0 percent accuracy. The main goal of this paper is to determine whether the indicator approach can be applied in predicting global oil prices. Upcoming research endeavours can extend the current model to out-of-sample forecasting of oil prices.

Suggested Citation

  • Mei-Teing Chong & Chin-Hong Puah & Shazali Abu Mansor, 2018. "Oil Price Dynamics Forecasting: An Indicator-Pivoted Paradigm," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 307-311.
    • Handle: RePEc:eco:journ2:2018-03-37
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    References listed on IDEAS

    as
    1. Wong, Shirly Siew-Ling & Puah, Chin-Hong & Abu Mansor, Shazali & Liew, Venus Khim-Sen, 2012. "Early warning indicator of economic vulnerability," MPRA Paper 39944, University Library of Munich, Germany.
    2. Baruník, Jozef & Malinská, Barbora, 2016. "Forecasting the term structure of crude oil futures prices with neural networks," Applied Energy, Elsevier, vol. 164(C), pages 366-379.
    3. Greer, Mark, 2003. "Directional accuracy tests of long-term interest rate forecasts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 291-298.
    4. Babecký, Jan & Havránek, Tomáš & Matějů, Jakub & Rusnák, Marek & Šmídková, Kateřina & Vašíček, Bořek, 2013. "Leading indicators of crisis incidence: Evidence from developed countries," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 1-19.
    5. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    6. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    7. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, March.
    8. Marco Gallegati, 2014. "Making leading indicators more leading: A wavelet-based method for the construction of composite leading indexes," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2014(1), pages 1-21.
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    Cited by:

    1. Soh, Ann-Ni, 2020. "A Review on the Leading Indicator Approach towards Economic Forecasting," MPRA Paper 103854, University Library of Munich, Germany.

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    More about this item

    Keywords

    Oil price; forecasting; indicator approach;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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