IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v86y2023ipas0301420723009054.html
   My bibliography  Save this article

Asymmetric efficiency in petroleum markets before and during COVID-19

Author

Listed:
  • Naeem, Muhammad Abubakr
  • Farid, Saqib
  • Yousaf, Imran
  • Kang, Sang Hoon

Abstract

Petroleum markets encountered exceptional challenges during the outbreak period. In this backdrop, the price dynamics in petroleum markets were also significantly influenced by fearsome environment and unprecedented risk experienced during the pandemic. In this direction, the study attempts to investigate the efficiency dynamics of the petroleum markets before and during the COVID-19 pandemic. The study utilizes high frequency data of four major petroleum markets namely, crude oil, Brent oil, diesel and natural gas. In order to unveil asymmetric multifractal scaling behavior of petroleum markets we employ a widely recognized approach known as asymmetric multifractal detrended fluctuation analysis (A-MF-DFA). The results confirm the presence of prevailing market inefficiencies in petroleum markets. In fact, the findings suggest that asymmetric multifractality is more pronounced during the downward trends. Also, the findings stress that market efficiency dynamics in the petroleum sector are dependent upon investment horizon, market conditions and investor behavior. More importantly, the sub-period analysis of COVID-19 era uncovers deteriorating market efficiencies in petroleum markets. Furthermore, the natural gas market emerges as the most efficient market before and during the COVID-19 time period.

Suggested Citation

  • Naeem, Muhammad Abubakr & Farid, Saqib & Yousaf, Imran & Kang, Sang Hoon, 2023. "Asymmetric efficiency in petroleum markets before and during COVID-19," Resources Policy, Elsevier, vol. 86(PA).
  • Handle: RePEc:eee:jrpoli:v:86:y:2023:i:pa:s0301420723009054
    DOI: 10.1016/j.resourpol.2023.104194
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420723009054
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.resourpol.2023.104194?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.

    References listed on IDEAS

    as
    1. Naeem, Muhammad Abubakr & Yousaf, Imran & Karim, Sitara & Yarovaya, Larisa & Ali, Shoaib, 2023. "Tail-event driven NETwork dependence in emerging markets," Emerging Markets Review, Elsevier, vol. 55(C).
    2. Zheng, Shiyuan & Lan, Xiangang, 2016. "Multifractal analysis of spot rates in tanker markets and their comparisons with crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 547-559.
    3. Michael Halling & Jin Yu & Josef Zechner, 2020. "How Did COVID-19 Affect Firms’ Access to Public Capital Markets?," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 9(3), pages 501-533.
    4. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    5. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Upside-Downside Multifractality and Efficiency of Green Bonds: The Roles of Global Factors and COVID-19," Finance Research Letters, Elsevier, vol. 43(C).
    6. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Pricing efficiency and asymmetric multifractality of major asset classes before and during COVID-19 crisis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    7. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices," Resources Policy, Elsevier, vol. 69(C).
    8. Liu, Min & Lee, Chien-Chiang, 2021. "Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting," Energy Economics, Elsevier, vol. 103(C).
    9. Shrestha, Keshab & Naysary, Babak & Philip, Sheena Sara Suresh, 2023. "Fintech market efficiency: A multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 54(C).
    10. Yuan, Ying & Zhuang, Xin-tian & Jin, Xiu & Huang, Wei-qiang, 2014. "Stable distribution and long-range correlation of Brent crude oil market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 173-179.
    11. Cao, Guangxi & Han, Yan & Cui, Weijun & Guo, Yu, 2014. "Multifractal detrended cross-correlations between the CSI 300 index futures and the spot markets based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 308-320.
    12. Gu, Rongbao & Chen, Hongtao & Wang, Yudong, 2010. "Multifractal analysis on international crude oil markets based on the multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2805-2815.
    13. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    14. Naeem, Muhammad Abubakr & Karim, Sitara & Farid, Saqib & Tiwari, Aviral Kumar, 2022. "Comparing the asymmetric efficiency of dirty and clean energy markets pre and during COVID-19," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 548-562.
    15. Arshad, Shaista & Rizvi, Syed Aun R. & Haroon, Omair & Mehmood, Fahad & Gong, Qiang, 2021. "Are oil prices efficient?," Economic Modelling, Elsevier, vol. 96(C), pages 362-370.
    16. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    17. Alvarez-Ramirez, Jose & Cisneros, Myriam & Ibarra-Valdez, Carlos & Soriano, Angel, 2002. "Multifractal Hurst analysis of crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 313(3), pages 651-670.
    18. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2010. "Auto-correlated behavior of WTI crude oil volatilities: A multiscale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5759-5768.
    19. Apostolos Serletis & Ioannis Andreadis, 2007. "Random Fractal Structures in North American Energy Markets," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 18, pages 245-255, World Scientific Publishing Co. Pte. Ltd..
    20. Lee, Minhyuk & Song, Jae Wook & Park, Ji Hwan & Chang, Woojin, 2017. "Asymmetric multi-fractality in the U.S. stock indices using index-based model of A-MFDFA," Chaos, Solitons & Fractals, Elsevier, vol. 97(C), pages 28-38.
    21. Nguyen, Thi Thu Ha & Naeem, Muhammad Abubakr & Balli, Faruk & Balli, Hatice Ozer & Vo, Xuan Vinh, 2021. "Time-frequency comovement among green bonds, stocks, commodities, clean energy, and conventional bonds," Finance Research Letters, Elsevier, vol. 40(C).
    22. Naeem, Muhammad Abubakr & Farid, Saqib & Ferrer, Román & Shahzad, Syed Jawad Hussain, 2021. "Comparative efficiency of green and conventional bonds pre- and during COVID-19: An asymmetric multifractal detrended fluctuation analysis," Energy Policy, Elsevier, vol. 153(C).
    23. Jiang, Zhi-Qiang & Xie, Wen-Jie & Zhou, Wei-Xing, 2014. "Testing the weak-form efficiency of the WTI crude oil futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 235-244.
    24. Huang, Menghao & Shao, Wei & Wang, Jian, 2023. "Correlations between the crude oil market and capital markets under the Russia–Ukraine conflict: A perspective of crude oil importing and exporting countries," Resources Policy, Elsevier, vol. 80(C).
    25. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    26. Muhammad Abubakr Naeem & Zaheer Anwer & Sitara Karim & Aviral Kumar Tiwari, 2023. "Are Exchange Rate Contagions Asymmetric? Evidence from Emerging Market Economies," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 59(15), pages 4107-4124, December.
    27. Ali, Shoaib & Moussa, Faten & Youssef, Manel, 2023. "Connectedness between cryptocurrencies using high-frequency data: A novel insight from the Silicon Valley Banks collapse," Finance Research Letters, Elsevier, vol. 58(PB).
    28. Zhuang, Xiaoyang & Wei, Yu & Zhang, Bangzheng, 2014. "Multifractal detrended cross-correlation analysis of carbon and crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 113-125.
    29. Baur, Dirk G. & Dimpfl, Thomas, 2018. "Asymmetric volatility in cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 148-151.
    30. Arfaoui, Nadia & Naeem, Muhammad Abubakr & Boubaker, Sabri & Mirza, Nawazish & Karim, Sitara, 2023. "Interdependence of clean energy and green markets with cryptocurrencies," Energy Economics, Elsevier, vol. 120(C).
    31. Ehsan Bagheri & Seyed Babak Ebrahimi & Arman Mohammadi & Mahsa Miri & Stelios Bekiros, 2022. "The Dynamic Volatility Connectedness Structure of Energy Futures and Global Financial Markets: Evidence From a Novel Time–Frequency Domain Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1087-1111, March.
    32. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    33. Syed Aun R. Rizvi & Shaista Arshad, 2016. "How does crisis affect efficiency? An empirical study of East Asian markets," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(1), pages 1-8, March.
    34. Yousaf, Imran, 2021. "Risk transmission from the COVID-19 to metals and energy markets," Resources Policy, Elsevier, vol. 73(C).
    35. Yousaf, Imran & Yarovaya, Larisa, 2022. "Static and dynamic connectedness between NFTs, Defi and other assets: Portfolio implication," Global Finance Journal, Elsevier, vol. 53(C).
    36. Alvarez-Ramirez, J. & Alvarez, J. & Rodríguez, E., 2015. "Asymmetric long-term autocorrelations in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 330-341.
    37. Zhang, Bing & Li, Xiao-Ming & He, Fei, 2014. "Testing the evolution of crude oil market efficiency: Data have the conn," Energy Policy, Elsevier, vol. 68(C), pages 39-52.
    38. Wang, Feng & Ye, Xin & Wu, Congxin, 2019. "Multifractal characteristics analysis of crude oil futures prices fluctuation in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    39. Walid Mensi & Imran Yousaf & Xuan Vinh Vo & Sang Hoon Kang, 2022. "Multifractality during upside/downside trends in the MENA stock markets: the effects of the global financial crisis, oil crash and COVID-19 pandemic," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 18(10), pages 4408-4435, January.
    40. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    41. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo, 2008. "Short-term predictability of crude oil markets: A detrended fluctuation analysis approach," Energy Economics, Elsevier, vol. 30(5), pages 2645-2656, September.
    42. Gao, Xing-Lu & Shao, Ying-Hui & Yang, Yan-Hong & Zhou, Wei-Xing, 2022. "Do the global grain spot markets exhibit multifractal nature?," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    43. Naeem, Muhammad Abubakr & Gul, Raazia & Farid, Saqib & Karim, Sitara & Lucey, Brian M., 2023. "Assessing linkages between alternative energy markets and cryptocurrencies," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 513-529.
    44. Mensi, Walid & Lee, Yun-Jung & Al-Yahyaee, Khamis Hamed & Sensoy, Ahmet & Yoon, Seong-Min, 2019. "Intraday downward/upward multifractality and long memory in Bitcoin and Ethereum markets: An asymmetric multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 31(C), pages 19-25.
    45. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Yoon, Seong-Min, 2018. "Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets," Finance Research Letters, Elsevier, vol. 27(C), pages 228-234.
    46. Yudong Wang & Chongfeng Wu, 2013. "Efficiency of Crude Oil Futures Markets: New Evidence from Multifractal Detrending Moving Average Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 393-414, December.
    47. Wang, Yudong & Wu, Chongfeng & Wei, Yu, 2011. "Can GARCH-class models capture long memory in WTI crude oil markets?," Economic Modelling, Elsevier, vol. 28(3), pages 921-927, May.
    48. Farid, Saqib & Kayani, Ghulam Mujtaba & Naeem, Muhammad Abubakr & Shahzad, Syed Jawad Hussain, 2021. "Intraday volatility transmission among precious metals, energy and stocks during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 72(C).
    49. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    50. He, Ling-Yun & Chen, Shu-Peng, 2010. "Are crude oil markets multifractal? Evidence from MF-DFA and MF-SSA perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3218-3229.
    51. Naeem, Muhammad Abubakr & Yousaf, Imran & Karim, Sitara & Tiwari, Aviral Kumar & Farid, Saqib, 2023. "Comparing asymmetric price efficiency in regional ESG markets before and during COVID-19," Economic Modelling, Elsevier, vol. 118(C).
    52. Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
    53. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Upward/downward multifractality and efficiency in metals futures markets: The impacts of financial and oil crises," Resources Policy, Elsevier, vol. 76(C).
    54. Naeem, Muhammad Abubakr & Karim, Sitara & Yarovaya, Larisa & Lucey, Brian M., 2023. "COVID-induced sentiment and the intraday volatility spillovers between energy and other ETFs," Energy Economics, Elsevier, vol. 122(C).
    55. Khediri, Karim Ben & Charfeddine, Lanouar, 2015. "Evolving efficiency of spot and futures energy markets: A rolling sample approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 6(C), pages 67-79.
    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. Dang, Tam Hoang-Nhat & Balli, Faruk & Balli, Hatice Ozer & Nguyen, Hannah, 2024. "Firm productivity in the Energy-electricity sector over the last two decades with crisis: The role of cross-listing," Energy Economics, Elsevier, vol. 130(C).
    2. Naeem, Muhammad Abubakr & Arfaoui, Nadia, 2023. "Exploring downside risk dependence across energy markets: Electricity, conventional energy, carbon, and clean energy during episodes of market crises," Energy Economics, Elsevier, vol. 127(PB).
    3. Naeem, Muhammad Abubakr & Gul, Raazia & Shafiullah, Muhammad & Karim, Sitara & Lucey, Brian M., 2024. "Tail risk spillovers between Shanghai oil and other markets," Energy Economics, Elsevier, vol. 130(C).

    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. Naeem, Muhammad Abubakr & Karim, Sitara & Farid, Saqib & Tiwari, Aviral Kumar, 2022. "Comparing the asymmetric efficiency of dirty and clean energy markets pre and during COVID-19," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 548-562.
    2. García-Carranco, Sergio M. & Bory-Reyes, Juan & Balankin, Alexander S., 2016. "The crude oil price bubbling and universal scaling dynamics of price volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 60-68.
    3. Charles, Amélie & Darné, Olivier, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Energy Policy, Elsevier, vol. 37(11), pages 4267-4272, November.
    4. Choi, Sun-Yong, 2021. "Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    5. Wang, Yudong & Wu, Chongfeng, 2012. "What can we learn from the history of gasoline crack spreads?: Long memory, structural breaks and modeling implications," Economic Modelling, Elsevier, vol. 29(2), pages 349-360.
    6. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    7. Cristina Sattarhoff & Marc Gronwald, 2018. "How to Measure Financial Market Efficiency? A Multifractality-Based Quantitative Approach with an Application to the European Carbon Market," CESifo Working Paper Series 7102, CESifo.
    8. Asif, Raheel & Frömmel, Michael, 2022. "Testing Long memory in exchange rates and its implications for the adaptive market hypothesis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    9. Tiwari, Aviral Kumar & Umar, Zaghum & Alqahtani, Faisal, 2021. "Existence of long memory in crude oil and petroleum products: Generalised Hurst exponent approach," Research in International Business and Finance, Elsevier, vol. 57(C).
    10. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Mefteh-Wali, Salma & Owusu, Patrick, 2023. "Measuring price efficiency in petroleum markets: New insights using various long-range dependence techniques," Resources Policy, Elsevier, vol. 82(C).
    11. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    12. Naeem, Muhammad Abubakr & Farid, Saqib & Ferrer, Román & Shahzad, Syed Jawad Hussain, 2021. "Comparative efficiency of green and conventional bonds pre- and during COVID-19: An asymmetric multifractal detrended fluctuation analysis," Energy Policy, Elsevier, vol. 153(C).
    13. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    14. Memon, Bilal Ahmed & Yao, Hongxing & Naveed, Hafiz Muhammad, 2022. "Examining the efficiency and herding behavior of commodity markets using multifractal detrended fluctuation analysis. Empirical evidence from energy, agriculture, and metal markets," Resources Policy, Elsevier, vol. 77(C).
    15. Zhou, Weijie & Dang, Yaoguo & Gu, Rongbao, 2013. "Efficiency and multifractality analysis of CSI 300 based on multifractal detrending moving average algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1429-1438.
    16. Chowdhury, Mohammad Ashraful Ferdous & Abdullah, Mohammad & Alam, Masud & Abedin, Mohammad Zoynul & Shi, Baofeng, 2023. "NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis," International Review of Financial Analysis, Elsevier, vol. 87(C).
    17. Aslam, Faheem & Memon, Bilal Ahmed & Hunjra, Ahmed Imran & Bouri, Elie, 2023. "The dynamics of market efficiency of major cryptocurrencies," Global Finance Journal, Elsevier, vol. 58(C).
    18. Ortiz-Cruz, Alejandro & Rodriguez, Eduardo & Ibarra-Valdez, Carlos & Alvarez-Ramirez, Jose, 2012. "Efficiency of crude oil markets: Evidences from informational entropy analysis," Energy Policy, Elsevier, vol. 41(C), pages 365-373.
    19. Boubaker, Sabri & Karim, Sitara & Naeem, Muhammad Abubakr & Rahman, Molla Ramizur, 2024. "On the prediction of systemic risk tolerance of cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    20. Naeem, Muhammad Abubakr & Gul, Raazia & Shafiullah, Muhammad & Karim, Sitara & Lucey, Brian M., 2024. "Tail risk spillovers between Shanghai oil and other markets," Energy Economics, Elsevier, vol. 130(C).

    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:eee:jrpoli:v:86:y:2023:i:pa:s0301420723009054. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    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.