IDEAS home Printed from https://ideas.repec.org/a/sae/globus/v18y2017i6p1465-1477.html
   My bibliography  Save this article

A Study of Risk Spillover in the Crude Oil and the Natural Gas Markets

Author

Listed:
  • Dilip Kumar

Abstract

This article examines the upside and downside risk spillover effects among crude oil (WTI and Brent) and Henry Hub natural gas markets. We consider value-at-risk (VaR) as a measure of risk and model both upside and downside 95 per cent, 99 per cent and 99.5 per cent VaR using various VaR approaches. The VaR models are evaluated using Christoffersen’s (1998) conditional coverage test and Lopez’s loss function approach to select the best-performing VaR model. Finally, we apply Hong, Liu and Wang’s (2009) approach to examine the upside and the downside risk spillover among crude oil and Henry Hub natural gas markets. We find significant two-way as well as one-way upside and downside risk spillover between WTI and Brent crude oil. Our results provide weak evidence of upside risk spillover from natural gas market to crude oil markets for 99.5 per cent VaR.

Suggested Citation

  • Dilip Kumar, 2017. "A Study of Risk Spillover in the Crude Oil and the Natural Gas Markets," Global Business Review, International Management Institute, vol. 18(6), pages 1465-1477, December.
    • Handle: RePEc:sae:globus:v:18:y:2017:i:6:p:1465-1477
    DOI: 10.1177/0972150917713046
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0972150917713046
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0972150917713046?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
    ---><---

    References listed on IDEAS

    as
    1. Fan, Ying & Zhang, Yue-Jun & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach," Energy Economics, Elsevier, vol. 30(6), pages 3156-3171, November.
    2. Marimoutou, Velayoudoum & Raggad, Bechir & Trabelsi, Abdelwahed, 2009. "Extreme Value Theory and Value at Risk: Application to oil market," Energy Economics, Elsevier, vol. 31(4), pages 519-530, July.
    3. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    4. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    5. Hong, Yongmiao, 2001. "A test for volatility spillover with application to exchange rates," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 183-224, July.
    6. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    7. Dilip Kumar, 2014. "Correlations, Return and Volatility Spillovers in Indian Exchange Rates," Global Business Review, International Management Institute, vol. 15(1), pages 77-91, March.
    8. Michelle Michot Foss, 2005. "Global Natural Gas Issues and Challenges: A Commentary," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 111-128.
    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. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.
    2. de Araújo, André da Silva & Garcia, Maria Teresa Medeiros, 2013. "Risk contagion in the north-western and southern European stock markets," Journal of Economics and Business, Elsevier, vol. 69(C), pages 1-34.
    3. Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
    4. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    5. Med Imen Gallali & Raggad Zahraa, 2012. "Evaluation of VaR models' forecasting performance: the case of oil markets," International Journal of Financial Services Management, Inderscience Enterprises Ltd, vol. 5(3), pages 197-215.
    6. Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018. "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, vol. 74(C), pages 628-643.
    7. Zhi-Fu Mi & Yi-Ming Wei & Bao-Jun Tang & Rong-Gang Cong & Hao Yu & Hong Cao & Dabo Guan, 2017. "Risk assessment of oil price from static and dynamic modelling approaches," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 929-939, February.
    8. Karmakar, Madhusudan & Paul, Samit, 2016. "Intraday risk management in International stock markets: A conditional EVT approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 34-55.
    9. Szymon Lis & Marcin Chlebus, 2021. "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers 2021-11, Faculty of Economic Sciences, University of Warsaw.
    10. Jian Zhou, 2013. "Extreme risk spillover among international REIT markets," Applied Financial Economics, Taylor & Francis Journals, vol. 23(2), pages 91-103, January.
    11. Karmakar, Madhusudan & Shukla, Girja K., 2015. "Managing extreme risk in some major stock markets: An extreme value approach," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 1-25.
    12. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    13. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
    14. Krzysztof Echaust & Małgorzata Just, 2021. "Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic," Energies, MDPI, vol. 14(14), pages 1-21, July.
    15. Yue-Jun Zhang & Ting Yao & Ling-Yun He, 2015. "Forecasting crude oil market volatility: can the Regime Switching GARCH model beat the single-regime GARCH models?," Papers 1512.01676, arXiv.org.
    16. Chebbi, Ali & Hedhli, Amel, 2022. "Revisiting the accuracy of standard VaR methods for risk assessment: Using the Copula–EVT multidimensional approach for stock markets in the MENA region," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 430-445.
    17. Chang, Ting-Huan & Su, Hsin-Mei & Chiu, Chien-Liang, 2011. "Value-at-risk estimation with the optimal dynamic biofuel portfolio," Energy Economics, Elsevier, vol. 33(2), pages 264-272, March.
    18. Chen, Liyuan & Zerilli, Paola & Baum, Christopher F., 2019. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Energy Economics, Elsevier, vol. 79(C), pages 111-129.
    19. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    20. Emrah Ismail Cevik & Sel Dibooglu & Atif Awad Abdallah & Eisa Abdulrahman Al-Eisa, 2021. "Oil prices, stock market returns, and volatility spillovers: evidence from Saudi Arabia," International Economics and Economic Policy, Springer, vol. 18(1), pages 157-175, February.

    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:sae:globus:v:18:y:2017:i:6:p:1465-1477. 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: SAGE Publications (email available below). General contact details of provider: http://www.imi.edu/ .

    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.