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Volatility transmission and volatility impulse response functions in crude oil markets

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  • Jin, Xiaoye
  • Xiaowen Lin, Sharon
  • Tamvakis, Michael

Abstract

Using daily data from July 2005 to February 2011 for WTI, Dubai and Brent futures contracts, we employ a VAR-BEKK model to investigate crude oil markets integration on the second moment. We also quantify the size and persistence of these connections through the analysis of Volatility Impulse Response Functions (VIRF) for two historical shocks, namely the 2008 Financial Crisis and the BP Deepwater Horizon oil spill. We observe that Brent and Dubai crude are highly responsive to market shocks, whereas WTI crude shows the least responsiveness of the three benchmarks, which creates questions about its predominance as a benchmark crude oil. Furthermore, we fit the density of the VIRF at different forecast horizons. These fitted distributions are asymmetric, showing that the probability of observing a large impact of a shock is lower while the probability of a relatively smaller impact is much higher. Finally, we simulate the VIRF for a given probability of a random shock. The VIRF shows that only a “large” shock (derived from a smaller probability) will result in an increase in expected conditional volatilities. These results provide useful insights into the volatility transmission mechanism in crude oil markets and their associated risk estimation, and may have significant implications for various market participants and regulators.

Suggested Citation

  • Jin, Xiaoye & Xiaowen Lin, Sharon & Tamvakis, Michael, 2012. "Volatility transmission and volatility impulse response functions in crude oil markets," Energy Economics, Elsevier, vol. 34(6), pages 2125-2134.
  • Handle: RePEc:eee:eneeco:v:34:y:2012:i:6:p:2125-2134
    DOI: 10.1016/j.eneco.2012.03.003
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    Cited by:

    1. Yen-Hsien Lee & Ting-Huei Liao & Ya-Ling Huang & Tzu-Ling Huang, 2015. "Dynamic Spillovers between Oil and Stock Markets: New Approaches at Spillover Index," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 6(2), pages 178-189, April.
    2. repec:spr:ssefpa:v:9:y:2017:i:4:d:10.1007_s12571-017-0702-2 is not listed on IDEAS
    3. PIERRET, Diane, 2013. "The systemic risk of energy markets," CORE Discussion Papers 2013018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Awartani, Basel & Maghyereh, Aktham Issa, 2013. "Dynamic spillovers between oil and stock markets in the Gulf Cooperation Council Countries," Energy Economics, Elsevier, vol. 36(C), pages 28-42.
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    6. Peri, Massimo, 2015. "Cliamte Variability and Agricultural Price volatility: the case of corn and soybeans," 2015 Conference, August 9-14, 2015, Milan, Italy 212623, International Association of Agricultural Economists.
    7. Assefa, Tsion & Meuwissen, Miranda & Lansink, Alfons G.J.M., 2015. "Food scares and price volatility: the case of German and Spanish pig chains," 2015 Conference, August 9-14, 2015, Milan, Italy 210966, International Association of Agricultural Economists.
    8. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
    9. Dowling, Michael & Cummins, Mark & Lucey, Brian M., 2016. "Psychological barriers in oil futures markets," Energy Economics, Elsevier, vol. 53(C), pages 293-304.
    10. Jin, Xiaoye, 2015. "Volatility transmission and volatility impulse response functions among the Greater China stock markets," Journal of Asian Economics, Elsevier, vol. 39(C), pages 43-58.
    11. David E. Allen & Michael McAleer & Robert Powell & Abhay K. Singh, 2017. "Volatility spillover and multivariate volatility impulse response analysis of GFC news events," Applied Economics, Taylor & Francis Journals, vol. 49(33), pages 3246-3262, July.
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    15. Baldi, Lucia & Peri, Massimo & Vandone, Daniela, 2016. "Financial Markets and Agricultural Commodities: Volatility Impulse Response Analysis," 2016 International European Forum, February 15-19, 2016, Innsbruck-Igls, Austria 244461, International European Forum on System Dynamics and Innovation in Food Networks.
    16. Jin, Xiaoye & An, Ximeng, 2016. "Global financial crisis and emerging stock market contagion: A volatility impulse response function approach," Research in International Business and Finance, Elsevier, vol. 36(C), pages 179-195.
    17. Antonio Rubia Serrano & Lidia Sanchis-Marco, 2015. "Measuring Tail-Risk Cross-Country Exposures in the Banking Industry," Working Papers. Serie AD 2015-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
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    More about this item

    Keywords

    Energy futures; Volatility; VIRF; Shocks;

    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
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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