IDEAS home Printed from https://ideas.repec.org/a/taf/reroxx/v33y2020i1p1943-1962.html
   My bibliography  Save this article

The inevitable role of El Niño: a fresh insight into the oil market

Author

Listed:
  • Meng Qin
  • Lian-Hong Qiu
  • Ran Tao
  • Muhammad Umar
  • Chi-Wei Su
  • Wen Jiao

Abstract

This paper explores the time-varying interaction between El Niño phenomenon and the oil market by applying the wavelet analysis. Few studies have explored the time-varying interrelationship between El Niño phenomenon and oil price (also the prices of petroleum products) by considering the time and frequency domains, and this paper will fill the above gaps. The empirical results reveal that El Niño index (NINO) which reflects the strength of El Niño phenomenon has a negative influence on oil price (OP) in the long run, but this view does not hold in the short and medium terms. These results are not consistent with the intertemporal capital asset pricing model (ICAPM), which indicates that there is a positive influence from NINO to OP. In turn, OP positively affects NINO in the medium term. Through comparing the five petroleum products, we can conclude that heating oil price (HOP) is the most relevant to NINO, while gasoline price (GOP) and diesel fuel price (DOP) have relatively weak relationships with it. Understanding the interactions between El Niño phenomenon and the oil market can provide insights for the investors, oil enterprises and related authorities.

Suggested Citation

  • Meng Qin & Lian-Hong Qiu & Ran Tao & Muhammad Umar & Chi-Wei Su & Wen Jiao, 2020. "The inevitable role of El Niño: a fresh insight into the oil market," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 33(1), pages 1943-1962, January.
    • Handle: RePEc:taf:reroxx:v:33:y:2020:i:1:p:1943-1962
    DOI: 10.1080/1331677X.2020.1768428
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1331677X.2020.1768428
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/1331677X.2020.1768428?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Qin, Meng & Su, Yun Hsuan & Zhao, Zhengtang & Mirza, Nawazish, 2023. "The politics of climate: Does factionalism impede U.S. carbon neutrality?," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 954-966.
    2. Mohammad Reza Yeganegi & Hossein Hassani & Rangan Gupta, 2023. "The ENSO cycle and forecastability of global inflation and output growth: Evidence from standard and mixed‐frequency multivariate singular spectrum analyses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1690-1707, November.
    3. Su, Chi Wei & Shao, Xuefeng & Jia, Zhijie & Nepal, Rabindra & Umar, Muhammad & Qin, Meng, 2023. "The rise of green energy metal: Could lithium threaten the status of oil?," Energy Economics, Elsevier, vol. 121(C).
    4. Wang, Xinghua & Lee, Zhengzheng & Wu, Shuang & Qin, Meng, 2023. "Exploring the vital role of geopolitics in the oil market: The case of Russia," Resources Policy, Elsevier, vol. 85(PB).
    5. Su, Chi Wei & Qin, Meng & Chang, Hsu-Ling & Țăran, Alexandra-Mădălina, 2023. "Which risks drive European natural gas bubbles? Novel evidence from geopolitics and climate," Resources Policy, Elsevier, vol. 81(C).
    6. Li, Jingwen & Wang, Yue & Song, Yubing & Su, Chi Wei, 2023. "How resistant is gold to stress? New evidence from global supply chain," Resources Policy, Elsevier, vol. 85(PB).
    7. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    8. Gupta, Rangan & Ji, Qiang & Pierdzioch, Christian & Plakandaras, Vasilios, 2023. "Forecasting the conditional distribution of realized volatility of oil price returns: The role of skewness over 1859 to 2023," Finance Research Letters, Elsevier, vol. 58(PC).
    9. Tang, Wenjin & Bu, Hui & Ji, Yuqiong & Li, Zhongfei, 2024. "Market uncertainty and information content in complex seasonality of prices," Pacific-Basin Finance Journal, Elsevier, vol. 86(C).
    10. Mohsin, Muhammad & Jamaani, Fouad, 2023. "A novel deep-learning technique for forecasting oil price volatility using historical prices of five precious metals in context of green financing – A comparison of deep learning, machine learning, an," Resources Policy, Elsevier, vol. 86(PA).
    11. Wei, Yu & Zhang, Jiahao & Bai, Lan & Wang, Yizhi, 2023. "Connectedness among El Niño-Southern Oscillation, carbon emission allowance, crude oil and renewable energy stock markets: Time- and frequency-domain evidence based on TVP-VAR model," Renewable Energy, Elsevier, vol. 202(C), pages 289-309.
    12. Qin, Meng & Su, Chi-Wei & Umar, Muhammad & Lobonţ, Oana-Ramona & Manta, Alina Georgiana, 2023. "Are climate and geopolitics the challenges to sustainable development? Novel evidence from the global supply chain," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 748-763.

    More about this item

    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:taf:reroxx:v:33:y:2020:i:1:p:1943-1962. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/rero .

    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.