IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03793866.html
   My bibliography  Save this paper

What drives most jumps in global crude oil prices? Fundamental shortage conditions, Cartel, geopolitics or the behavior of market financial participants

Author

Listed:
  • Refk Selmi

    (ESC PAU - Ecole Supérieure de Commerce, Pau Business School)

  • Shawkat Hammoudeh

    (Drexel University)

  • Mark Wohar

    (University of Nebraska Omaha - University of Nebraska System)

Abstract

Several studies have emphasized the potential role of oil price volatility as a leading macroeconomic indicator, since it provides prominent information to energy traders, market participants and policymakers. In an effort to shed fresh insights on the underlying factors of wide oil price changes, the objective of this paper is twofold. First to capture large oil price changes caused by the arrival of surprising news (i.e., jumps); second to distinguish between short-, medium-and long-term determinants of jumps in oil prices due to changes in oil supply and demand fundamentals, factors associated with the market power of oil producers, speculation, geopolitical risks and OPEC's spare capacity. Using an Empirical Mode Decomposition (EMD), we find that oil supply and demand forces are the most prevalent in determining oil price changes in the long run, which is quite predictable. OPEC gains increasing importance in the medium-and long-terms. Our method also allows us to show that OPEC's use of spare capacity moderately reduces oil price volatility in the short-term, thus suggesting a limited stabilizing influence on the oil market. We consider broader policy implications for our results.

Suggested Citation

  • Refk Selmi & Shawkat Hammoudeh & Mark Wohar, 2022. "What drives most jumps in global crude oil prices? Fundamental shortage conditions, Cartel, geopolitics or the behavior of market financial participants," Post-Print hal-03793866, HAL.
    • Handle: RePEc:hal:journl:hal-03793866
    Note: View the original document on HAL open archive server: https://hal.science/hal-03793866
    as

    Download full text from publisher

    File URL: https://hal.science/hal-03793866/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. So, Mike K.P. & Yu, Philip L.H., 2006. "Empirical analysis of GARCH models in value at risk estimation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(2), pages 180-197, April.
    2. Mr. Noureddine Krichene, 2006. "World Crude Oil Markets: Monetary Policy and the Recent Oil Shock," IMF Working Papers 2006/062, International Monetary Fund.
    3. Brémond, Vincent & Hache, Emmanuel & Mignon, Valérie, 2012. "Does OPEC still exist as a cartel? An empirical investigation," Energy Economics, Elsevier, vol. 34(1), pages 125-131.
    4. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    5. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    6. John M. Maheu & Thomas H. McCurdy, 2004. "News Arrival, Jump Dynamics, and Volatility Components for Individual Stock Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 755-793, April.
    7. Selmi, Refk & Bouoiyour, Jamal & Miftah, Amal, 2020. "Oil price jumps and the uncertainty of oil supplies in a geopolitical perspective: The role of OPEC’s spare capacity," International Economics, Elsevier, vol. 164(C), pages 18-35.
    8. Lutz Kilian & Bruce Hicks, 2013. "Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003–2008?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 385-394, August.
    9. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    10. Petter Vegard Hansen & Lars Lindholt, 2008. "The market power of OPEC 1973-2001," Applied Economics, Taylor & Francis Journals, vol. 40(22), pages 2939-2959.
    11. Andreas Breitenfellner & Jesús Crespo Cuaresma & Catherine Keppel, 2009. "Determinants of Crude Oil Prices: Supply, Demand, Cartel or Speculation?," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 111-136.
    12. Sun, Edward W. & Meinl, Thomas, 2012. "A new wavelet-based denoising algorithm for high-frequency financial data mining," European Journal of Operational Research, Elsevier, vol. 217(3), pages 589-599.
    13. Hnyilicza, Esteban & Pindyck, Robert S., 1976. "Pricing policies for a two-part exhaustible resource cartel : The case of OPEC," European Economic Review, Elsevier, vol. 8(2), pages 139-154, August.
    14. Noguera-Santaella, José, 2016. "Geopolitics and the oil price," Economic Modelling, Elsevier, vol. 52(PB), pages 301-309.
    Full references (including those not matched with items on IDEAS)

    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. Refk Selmi & Shawkat Hammoudeh & Mark E. Wohar, 2023. "What drives most jumps in global crude oil prices? Fundamental shortage conditions, cartel, geopolitics or the behaviour of financial market participants," The World Economy, Wiley Blackwell, vol. 46(3), pages 598-618, March.
    2. Golombek, Rolf & Irarrazabal, Alfonso A. & Ma, Lin, 2018. "OPEC's market power: An empirical dominant firm model for the oil market," Energy Economics, Elsevier, vol. 70(C), pages 98-115.
    3. Gatfaoui, Hayette, 2016. "Linking the gas and oil markets with the stock market: Investigating the U.S. relationship," Energy Economics, Elsevier, vol. 53(C), pages 5-16.
    4. repec:ipg:wpaper:19 is not listed on IDEAS
    5. Dong, Minyi & Chang, Chun-Ping & Gong, Qiang & Chu, Yin, 2019. "Revisiting global economic activity and crude oil prices: A wavelet analysis," Economic Modelling, Elsevier, vol. 78(C), pages 134-149.
    6. Yannick Le Pen & Benoît Sévi, 2013. "Futures Trading and the Excess Comovement of Commodity Prices," Working Papers halshs-00793724, HAL.
    7. repec:ipg:wpaper:2013-019 is not listed on IDEAS
    8. Vincent Brémond & Emmanuel Hache & Tovonony Razafindrabe, 2016. "The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 97-131, June.
    9. Karakotsios, Achillefs & Katrakilidis, Constantinos & Kroupis, Nikolaos, 2021. "The dynamic linkages between food prices and oil prices. Does asymmetry matter?," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    10. Selmi, Refk & Bouoiyour, Jamal & Miftah, Amal, 2020. "Oil price jumps and the uncertainty of oil supplies in a geopolitical perspective: The role of OPEC’s spare capacity," International Economics, Elsevier, vol. 164(C), pages 18-35.
    11. Umar, Muhammad & Su, Chi-Wei & Rizvi, Syed Kumail Abbas & Lobonţ, Oana-Ramona, 2021. "Driven by fundamentals or exploded by emotions: Detecting bubbles in oil prices," Energy, Elsevier, vol. 231(C).
    12. Jose de Gregorio & Oscar Landerretche & Christopher Neilson, 2007. "Another Pass-Through Bites the Dust? Oil Prices and Inflation," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 155-208, January.
    13. Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017. "Influential factors in crude oil price forecasting," Energy Economics, Elsevier, vol. 68(C), pages 77-88.
    14. Fan, Ying & Xu, Jin-Hua, 2011. "What has driven oil prices since 2000? A structural change perspective," Energy Economics, Elsevier, vol. 33(6), pages 1082-1094.
    15. Xiao, Jihong & Wen, Fenghua & He, Zhifang, 2023. "Impact of geopolitical risks on investor attention and speculation in the oil market: Evidence from nonlinear and time-varying analysis," Energy, Elsevier, vol. 267(C).
    16. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    17. James Nolan & Zoe Laulederkind, 2022. "Plane to See? Empirical Analysis of the 1999–2006 Air Cargo Cartel," Advances in Airline Economics, in: The International Air Cargo Industry, volume 9, pages 241-262, Emerald Group Publishing Limited.
    18. Baumann, Ursel & Darracq Pariès, Matthieu & Westermann, Thomas & Riggi, Marianna & Bobeica, Elena & Meyler, Aidan & Böninghausen, Benjamin & Fritzer, Friedrich & Trezzi, Riccardo & Jonckheere, Jana & , 2021. "Inflation expectations and their role in Eurosystem forecasting," Occasional Paper Series 264, European Central Bank.
    19. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    20. Sandra Eickmeier & Katharina Pijnenburg, 2013. "The Global Dimension of Inflation – Evidence from Factor-Augmented Phillips Curves," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 103-122, February.
    21. Apergis, Nicholas & Hayat, Tasawar & Saeed, Tareq, 2021. "US partisan conflict uncertainty and oil prices," Energy Policy, Elsevier, vol. 150(C).
    22. Angela Abbate & Sandra Eickmeier & Wolfgang Lemke & Massimiliano Marcellino, 2016. "The Changing International Transmission of Financial Shocks: Evidence from a Classical Time‐Varying FAVAR," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(4), pages 573-601, June.

    More about this item

    Keywords

    Oil price jumps; oil price determinants; Empirical Mode Decomposition; Empirical Mode Decomposition JEL classification: G15; C11; C58; Q30; Q31;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hal:journl:hal-03793866. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.