IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v45y2022ics1544612321002634.html
   My bibliography  Save this article

Time varying market efficiency in the Brent and WTI crude market

Author

Listed:
  • Okoroafor, Ugochi Chibuzor
  • Leirvik, Thomas

Abstract

This paper examines time-varying market efficiency in the crude oil spot market using a recently derived measure of market efficiency: the Adjusted Market Inefficiency Model (AMIM). Analysing efficiency in the crude oil market, and its response to significant events within the global financial and commodity market, we identify that the Brent market is on average more efficient than the West Texas Intermediate (WTI). We also find that the WTI market is persistently inefficient during financial crises, with high volatility of the efficiency in such periods. In addition to confirming the adaptive market hypothesis, this study offers a new perspective by highlighting the non-uniform response of efficiency in similar markets to global events.

Suggested Citation

  • Okoroafor, Ugochi Chibuzor & Leirvik, Thomas, 2022. "Time varying market efficiency in the Brent and WTI crude market," Finance Research Letters, Elsevier, vol. 45(C).
    • Handle: RePEc:eee:finlet:v:45:y:2022:i:c:s1544612321002634
    DOI: 10.1016/j.frl.2021.102191
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612321002634
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2021.102191?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. 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.
    2. Bassam Fattouh, Lutz Kilian, and Lavan Mahadeva, 2013. "The Role of Speculation in Oil Markets: What Have We Learned So Far?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    3. Creti, Anna & Joëts, Marc & Mignon, Valérie, 2013. "On the links between stock and commodity markets' volatility," Energy Economics, Elsevier, vol. 37(C), pages 16-28.
    4. repec:dau:papers:123456789/14980 is not listed on IDEAS
    5. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2012. "Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1607-1626.
    6. Kuruppuarachchi, Duminda & Lin, Hai & Premachandra, I.M., 2019. "Testing commodity futures market efficiency under time-varying risk premiums and heteroscedastic prices," Economic Modelling, Elsevier, vol. 77(C), pages 92-112.
    7. Zhang, Bing, 2013. "Are the crude oil markets becoming more efficient over time? New evidence from a generalized spectral test," Energy Economics, Elsevier, vol. 40(C), pages 875-881.
    8. Alizadeh, Amir H. & Muradoglu, Gulnur, 2014. "Stock market efficiency and international shipping-market information," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 445-461.
    9. Brad M. Barber & Terrance Odean, 2001. "Boys will be Boys: Gender, Overconfidence, and Common Stock Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 261-292.
    10. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    11. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    12. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    13. Noda, Akihiko, 2016. "A test of the adaptive market hypothesis using a time-varying AR model in Japan," Finance Research Letters, Elsevier, vol. 17(C), pages 66-71.
    14. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    15. 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.
    16. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2014. "International stock market efficiency: a non-Bayesian time-varying model approach," Applied Economics, Taylor & Francis Journals, vol. 46(23), pages 2744-2754, August.
    17. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    18. Shane A. Corwin & Paul Schultz, 2012. "A Simple Way to Estimate Bid‐Ask Spreads from Daily High and Low Prices," Journal of Finance, American Finance Association, vol. 67(2), pages 719-760, April.
    19. repec:pri:cepsud:91malkiel is not listed on IDEAS
    20. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    21. 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.
    22. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    23. Lim, Kian-Ping & Brooks, Robert D. & Kim, Jae H., 2008. "Financial crisis and stock market efficiency: Empirical evidence from Asian countries," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 571-591, June.
    24. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    25. Ghazani, Majid Mirzaee & Ebrahimi, Seyed Babak, 2019. "Testing the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the crude oil prices," Finance Research Letters, Elsevier, vol. 30(C), pages 60-68.
    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. Yuan, Ying & Du, Xinyu, 2023. "Dynamic spillovers across global stock markets during the COVID-19 pandemic: Evidence from jumps and higher moments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    2. Clement Moyo & Izunna Anyikwa & Andrew Phiri, 2023. "The Impact of Covid-19 on Oil Market Returns: Has Market Efficiency Being Violated?," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 118-127, January.
    3. Okoroafor, Ugochi C. & Leirvik, Thomas, 2023. "Time-varying market efficiency of safe-haven assets," Finance Research Letters, Elsevier, vol. 56(C).
    4. Roy, Archi & Soni, Anchal & Deb, Soudeep, 2023. "A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets," Energy Economics, Elsevier, vol. 124(C).
    5. Espinosa-Paredes, G. & Rodriguez, E. & Alvarez-Ramirez, J., 2022. "A singular value decomposition entropy approach to assess the impact of Covid-19 on the informational efficiency of the WTI crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 160(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. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    2. 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).
    3. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    4. Majid Mirzaee Ghazani & Mohammad Ali Jafari, 2021. "Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    5. 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).
    6. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    7. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    8. Leirvik, Thomas, 2022. "Cryptocurrency returns and the volatility of liquidity," Finance Research Letters, Elsevier, vol. 44(C).
    9. Dionysia Dionysiou, 2015. "Choosing Among Alternative Long-Run Event-Study Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 158-198, February.
    10. Aloosh, Arash & Choi, Hyung-Eun & Ouzan, Samuel, 2023. "The tail wagging the dog: How do meme stocks affect market efficiency?," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 68-78.
    11. Cristi Spulbar & Ramona Birau & Lucian Florin Spulbar, 2021. "A Critical Survey on Efficient Market Hypothesis (EMH), Adaptive Market Hypothesis (AMH) and Fractal Markets Hypothesis (FMH) Considering Their Implication on Stock Markets Behavior," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 1161-1165, December.
    12. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    13. Kristoufek, Ladislav & Vosvrda, Miloslav, 2016. "Gold, currencies and market efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 27-34.
    14. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
    15. Bernard Njindan Iyke, 2019. "A Test Of The Efficiency Of The Foreign Exchange Market In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 0(12th BMEB), pages 1-26, January.
    16. Kristoufek, Ladislav & Vosvrda, Miloslav, 2013. "Measuring capital market efficiency: Global and local correlations structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 184-193.
    17. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    18. Roscoe, Philip & Howorth, Carole, 2009. "Identification through technical analysis: A study of charting and UK non-professional investors," Accounting, Organizations and Society, Elsevier, vol. 34(2), pages 206-221, February.
    19. Marcus F. da Silva & Eder Johnson de Area Leão Pereira & Idaraí Santos de Santana & José Garcia Vivas Miranda, 2013. "Pattern of fluctuations in the exchange rate change from fixed to floating, in Brazil, Argentina and Mexico," Economics Bulletin, AccessEcon, vol. 33(2), pages 1547-1555.
    20. Al Janabi, Mazin A.M. & Hatemi-J, Abdulnasser & Irandoust, Manuchehr, 2010. "An empirical investigation of the informational efficiency of the GCC equity markets: Evidence from bootstrap simulation," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 47-54, January.

    More about this item

    Keywords

    Adaptive Market Hypothesis; Crude oil prices; Market efficiency;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:eee:finlet:v:45:y:2022:i:c:s1544612321002634. 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/frl .

    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.