IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v84y2023ics0301420723004403.html
   My bibliography  Save this article

Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach

Author

Listed:
  • Chatziantoniou, Ioannis
  • Gabauer, David
  • Gupta, Rangan

Abstract

In this study, we introduce a novel time-varying parameter vector autoregressive frequency connectedness approach to obtain refined measures of the frequency transmission mechanism and dynamic integration among six well-established crude oil benchmarks. The period of investigation ranges from May 14th, 1996 to December 3rd, 2020 and focuses on the differences between short-term (1–5 days) and long-term (6–100 days) crude oil volatility connectedness. Findings are suggestive of relatively strong co-movements among crude oil volatility over time. For most part of the sample period, connectedness occurs in the short-run; nonetheless, starting approximately in 2010, long-run connectedness gains much prominence until at least the end of 2015. Long-run connectedness is also prevalent at the beginning of 2020 caused by the COVID-19 pandemic. We opine that periods of increased long-run connectedness relate to deeper changes in the market for crude oil that bring about new dynamics and associations within the specific network.

Suggested Citation

  • Chatziantoniou, Ioannis & Gabauer, David & Gupta, Rangan, 2023. "Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach," Resources Policy, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:jrpoli:v:84:y:2023:i:c:s0301420723004403
    DOI: 10.1016/j.resourpol.2023.103729
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420723004403
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2023.103729?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. Chatziantoniou, Ioannis & Gabauer, David, 2021. "EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 1-14.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Stiassny, Alfred, 1996. "A Spectral Decomposition for Structural VAR Models," Empirical Economics, Springer, vol. 21(4), pages 535-555.
    4. Gabauer, David, 2021. "Dynamic measures of asymmetric & pairwise connectedness within an optimal currency area: Evidence from the ERM I system," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    5. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    6. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    7. Severin Borenstein and Ryan Kellogg, 2014. "The Incidence of an Oil Glut: Who Benefits from Cheap Crude Oil in the Midwest?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    8. Koop, Gary & Korobilis, Dimitris, 2014. "A new index of financial conditions," European Economic Review, Elsevier, vol. 71(C), pages 101-116.
    9. Kim, Myung Suk, 2018. "Impacts of supply and demand factors on declining oil prices," Energy, Elsevier, vol. 155(C), pages 1059-1065.
    10. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    11. Wiesen, Thomas F.P. & Beaumont, Paul M. & Norrbin, Stefan C. & Srivastava, Anuj, 2018. "Are generalized spillover indices overstating connectedness?," Economics Letters, Elsevier, vol. 173(C), pages 131-134.
    12. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    13. Scheitrum, Daniel P. & Carter, Colin A. & Revoredo-Giha, Cesar, 2018. "WTI and Brent futures pricing structure," Energy Economics, Elsevier, vol. 72(C), pages 462-469.
    14. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    15. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    16. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    17. Caporin, Massimiliano & Fontini, Fulvio & Talebbeydokhti, Elham, 2019. "Testing persistence of WTI and Brent long-run relationship after the shale oil supply shock," Energy Economics, Elsevier, vol. 79(C), pages 21-31.
    18. Xia, Yan & Kong, Yishu & Ji, Qiang & Zhang, Dayong, 2019. "Impacts of China-US trade conflicts on the energy sector," China Economic Review, Elsevier, vol. 58(C).
    19. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    20. Bahattin Buyuksahin, Thomas K. Lee, James T. Moser, and Michel A. Robe, 2013. "Physical Markets, Paper Markets and the WTI-Brent Spread," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    21. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan & Plakandaras, Vasilios, 2018. "Dynamic connectedness of uncertainty across developed economies: A time-varying approach," Economics Letters, Elsevier, vol. 166(C), pages 63-75.
    22. Fattouh, Bassam, 2010. "The dynamics of crude oil price differentials," Energy Economics, Elsevier, vol. 32(2), pages 334-342, March.
    23. van Moerkerk, Mike & Crijns-Graus, Wina, 2016. "A comparison of oil supply risks in EU, US, Japan, China and India under different climate scenarios," Energy Policy, Elsevier, vol. 88(C), pages 148-158.
    24. Niyati Bhanja & Arif Billah Dar & Aviral Kumar Tiwari, 2018. "Do Global Crude Oil Markets Behave as One Great Pool? A Cyclical Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 219-241, November.
    25. Mark Agerton and Gregory B. Upton Jr., 2019. "Decomposing Crude Price Differentials: Domestic Shipping Constraints or the Crude Oil Export Ban?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    26. Zhang, Wenting & Hamori, Shigeyuki, 2021. "Crude oil market and stock markets during the COVID-19 pandemic: Evidence from the US, Japan, and Germany," International Review of Financial Analysis, Elsevier, vol. 74(C).
    27. Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2021. "Geopolitical risk and forecastability of tail risk in the oil market: Evidence from over a century of monthly data," Energy, Elsevier, vol. 235(C).
    28. Mastroeni, Loretta & Mazzoccoli, Alessandro & Quaresima, Greta & Vellucci, Pierluigi, 2021. "Decoupling and recoupling in the crude oil price benchmarks: An investigation of similarity patterns," Energy Economics, Elsevier, vol. 94(C).
    29. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    30. M. A. Adelman, 1984. "International Oil Agreements," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-10.
    31. Zhang, Dayong & Ji, Qiang & Kutan, Ali M., 2019. "Dynamic transmission mechanisms in global crude oil prices: Estimation and implications," Energy, Elsevier, vol. 175(C), pages 1181-1193.
    32. Ajmi, Ahdi Noomen & Hammoudeh, Shawkat & Mokni, Khaled, 2021. "Detection of bubbles in WTI, brent, and Dubai oil prices: A novel double recursive algorithm," Resources Policy, Elsevier, vol. 70(C).
    33. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    34. Gabauer, David & Gupta, Rangan, 2018. "On the transmission mechanism of country-specific and international economic uncertainty spillovers: Evidence from a TVP-VAR connectedness decomposition approach," Economics Letters, Elsevier, vol. 171(C), pages 63-71.
    35. Robert J. Weiner, 1991. "Is the World Oil Market "One Great Pool"?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 95-108.
    36. Michael Plante and Grant Strickler, 2021. "Closer to One Great Pool? Evidence from Structural Breaks in Oil Price Differentials," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-30.
    37. Nusair, Salah A. & Olson, Dennis, 2019. "The effects of oil price shocks on Asian exchange rates: Evidence from quantile regression analysis," Energy Economics, Elsevier, vol. 78(C), pages 44-63.
    38. Thomas J. Fisher & Colin M. Gallagher, 2012. "New Weighted Portmanteau Statistics for Time Series Goodness of Fit Testing," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 777-787, June.
    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. Zhu, Zongyuan & Luo, Qingtian, 2023. "Inter-industry risk spillover, role reversal, and economic stability," Finance Research Letters, Elsevier, vol. 57(C).
    2. Zheng, Jinlin & Wen, Baoyu & Jiang, Yaohui & Wang, Xiaohan & Shen, Yue, 2023. "Risk spillovers across geopolitical risk and global financial markets," Energy Economics, Elsevier, vol. 127(PA).

    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. Ioannis Chatziantoniou & David Gabauer & Rangan Gupta, 2021. "Integration and Risk Transmission in the Market for Crude Oil: A Time-Varying Parameter Frequency Connectedness Approach," Working Papers 202147, University of Pretoria, Department of Economics.
    2. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    3. Chatziantoniou, Ioannis & Gabauer, David & Perez de Gracia, Fernando, 2022. "Tail risk connectedness in the refined petroleum market: A first look at the impact of the COVID-19 pandemic," Energy Economics, Elsevier, vol. 111(C).
    4. Stenfors, Alexis & Chatziantoniou, Ioannis & Gabauer, David, 2022. "Independent policy, dependent outcomes: A game of cross-country dominoes across European yield curves," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    5. Chatziantoniou, Ioannis & Gabauer, David & Stenfors, Alexis, 2020. "From CIP-deviations to a market for risk premia: A dynamic investigation of cross-currency basis swaps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 69(C).
    6. Ioannis Chatziantoniou & David Gabauer & Hardik A. Marfatia, 2022. "Dynamic connectedness and spillovers across sectors: Evidence from the Indian stock market," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(3), pages 283-300, July.
    7. Chatziantoniou, Ioannis & Elsayed, Ahmed H. & Gabauer, David & Gozgor, Giray, 2023. "Oil price shocks and exchange rate dynamics: Evidence from decomposed and partial connectedness measures for oil importing and exporting economies," Energy Economics, Elsevier, vol. 120(C).
    8. Tiantian Liu & Shigeyuki Hamori, 2021. "Does Investor Sentiment Affect Clean Energy Stock? Evidence from TVP-VAR-Based Connectedness Approach," Energies, MDPI, vol. 14(12), pages 1-21, June.
    9. Lee, Chien-Chiang & Zhou, Hegang & Xu, Chao & Zhang, Xiaoming, 2023. "Dynamic spillover effects among international crude oil markets from the time-frequency perspective," Resources Policy, Elsevier, vol. 80(C).
    10. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    11. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    12. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Gabauer, David & Dwumfour, Richard Adjei, 2022. "Dynamic spillover effects among green bond, renewable energy stocks and carbon markets during COVID-19 pandemic: Implications for hedging and investments strategies," Global Finance Journal, Elsevier, vol. 51(C).
    13. Keagile Lesame & Elie Bouri & David Gabauer & Rangan Gupta, 2021. "On the Dynamics of International Real Estate Investment Trust Propagation Mechanisms: Evidence from Time-Varying Return and Volatility Connectedness Measures," Working Papers 202152, University of Pretoria, Department of Economics.
    14. Cui, Jinxin & Maghyereh, Aktham, 2023. "Time-frequency dependence and connectedness among global oil markets: Fresh evidence from higher-order moment perspective," Journal of Commodity Markets, Elsevier, vol. 30(C).
    15. Gabauer, David, 2021. "Dynamic measures of asymmetric & pairwise connectedness within an optimal currency area: Evidence from the ERM I system," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    16. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan, 2019. "Greek economic policy uncertainty: Does it matter for Europe? Evidence from a dynamic connectedness decomposition approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    17. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan, 2019. "International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression," International Review of Financial Analysis, Elsevier, vol. 65(C).
    18. David Gabauer, 2020. "Volatility impulse response analysis for DCC‐GARCH models: The role of volatility transmission mechanisms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 788-796, August.
    19. Juncal Cunado & David Gabauer & Rangan Gupta & Chien-Chiang Lee, 2022. "On the Propagation Mechanism of International Real Interest Rate Spillovers: Evidence from More than 200 Years of Data," Working Papers 202212, University of Pretoria, Department of Economics.
    20. Christophe Andre & David Gabauer & Rangan Gupta, 2020. "Time-Varying Spillovers between Housing Sentiment and Housing Market in the United States," Working Papers 202091, University of Pretoria, Department of Economics.

    More about this item

    Keywords

    World crude oil market; TVP-VAR; Volatility spillovers; Frequency connectedness;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F30 - International Economics - - International Finance - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    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:jrpoli:v:84:y:2023:i:c:s0301420723004403. 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.