IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2018-03-37.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/6394/3755
    Download Restriction: no

    File URL: https://www.econjournals.com/index.php/ijeep/article/view/6394/3755
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Greer, Mark, 2003. "Directional accuracy tests of long-term interest rate forecasts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 291-298.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shirly Siew-Ling WONG & Chin-Hong PUAH & Shazali ABU MANSOR & Venus Khim-Sen LIEW, 2016. "Measuring Business Cycle Fluctuations: An Alternative Precursor To Economic Crises," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 235-248.
    2. Avouyi-Dovi, S. & Matheron, J., 2003. "Interactions between business cycles, stock market cycles and interest rates: the stylised facts," Financial Stability Review, Banque de France, issue 3, pages 80-99, November.
    3. German Forero-Laverde, 2016. "Are All Booms and Busts Created Equal? A New Methodology for Understanding Bull and Bear Stock Markets," UB School of Economics Working Papers 2016/339, University of Barcelona School of Economics.
    4. Mikkel Hermansen & Oliver Röhn, 2017. "Economic resilience: The usefulness of early warning indicators in OECD countries," OECD Journal: Economic Studies, OECD Publishing, vol. 2016(1), pages 9-35.
    5. Dewald, William G. & Haug, Alfred A., 2004. "Longer-term effects of monetary growth on real and nominal variables, major industrial countries, 1880-2001," Working Paper Series 382, European Central Bank.
    6. 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.
    7. Soh, Ann-Ni, 2020. "A Review on the Leading Indicator Approach towards Economic Forecasting," MPRA Paper 103854, University Library of Munich, Germany.
    8. Rossen, Anja, 2015. "What are metal prices like? Co-movement, price cycles and long-run trends," Resources Policy, Elsevier, vol. 45(C), pages 255-276.
    9. Gießler Stefan & Heinisch Katja & Holtemöller Oliver, 2021. "(Since When) Are East and West German Business Cycles Synchronised?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 241(1), pages 1-28, February.
    10. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.
    11. Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini, 2019. "Real and financial cycles: estimates using unobserved component models for the Italian economy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 541-569, September.
    12. Stefano Magrini & Margherita Gerolimetto & Hasan Engin Duran, 2011. "Distortions in Cross-Sectional Convergence Analysis when the Aggregate Business Cycle is Incomplete," Working Papers 2011_07, Department of Economics, University of Venice "Ca' Foscari".
    13. Antonio Bassanetti & Michele Caivano & Alberto Locarno, 2010. "Modelling Italian potential output and the output gap," Temi di discussione (Economic working papers) 771, Bank of Italy, Economic Research and International Relations Area.
    14. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72, October.
    15. Juhro, Solikin M. & Iyke, Bernard Njindan & Narayan, Paresh Kumar, 2024. "Capital flow dynamics and the synchronization of financial cycles and business cycles in emerging market economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    16. Stephen Broadberry & Jagjit S. Chadha & Jason Lennard & Ryland Thomas, 2023. "Dating business cycles in the United Kingdom, 1700–2010," Economic History Review, Economic History Society, vol. 76(4), pages 1141-1162, November.
    17. D. S. G. Pollock, 2016. "Econometric Filters," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 669-691, December.
    18. Hodula, Martin & Janků, Jan & Pfeifer, Lukáš, 2023. "Macro-prudential policies to contain the effect of structural risks on financial downturns," Journal of Policy Modeling, Elsevier, vol. 45(6), pages 1204-1222.
    19. Pamphile MEZUI-MBENG, 2012. "Cycle Du Credit Et Cycle Des Affaires Dans Les Pays De La Cemac," Cahiers du CEREFIGE 1202, CEREFIGE (Centre Europeen de Recherche en Economie Financiere et Gestion des Entreprises), Universite de Lorraine, revised 2012.
    20. Josefine Quast & Maik H. Wolters, 2022. "Reliable Real-Time Output Gap Estimates Based on a Modified Hamilton Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 152-168, January.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eco:journ2:2018-03-37. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.