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Measuring contagion between energy market and stock market during financial crisis: A copula approach

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  • Wen, Xiaoqian
  • Wei, Yu
  • Huang, Dengshi
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    Abstract

    In this paper, we apply time-varying copulas to investigate whether a contagion effect existed between energy and stock markets during the recent financial crisis. Using the WTI oil spot price, the S&P500 index, the Shanghai stock market composite index and the Shenzhen stock market component index returns, evidence was found for a significantly increasing dependence between crude oil and stock markets after the failure of Lehman Brothers, thus supporting the existence of contagion in the sense of Forbes and Rigobon's (2002) definition. Moreover, increased tail dependence and symmetry characterize all the paired markets. This indicates that significant increases in tail dependence are an actual dimension of the contagion phenomenon and that crude oil and stock prices are linked to the same degree regardless of whether markets are booming or crashing during the sample period. Finally, the contagion effect is found to be much weaker for China than the US. The empirical results have potentially important implications for risk management.

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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Economics.

    Volume (Year): 34 (2012)
    Issue (Month): 5 ()
    Pages: 1435-1446

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    Handle: RePEc:eee:eneeco:v:34:y:2012:i:5:p:1435-1446

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    Web page: http://www.elsevier.com/locate/eneco

    Related research

    Keywords: Contagion; Energy market; Stock market; Time-varying copula;

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    Cited by:
    1. Heni Boubaker & Nadia Sghaier, 2013. "Instability and time-varying dependence structure between oil prices and stock markets in GCC countries," Working Papers 2013-023, Department of Research, Ipag Business School.
    2. Renée Fry-McKibbin & Cody Hsiao & Chrismin Tang, 2014. "Contagion and Global Financial Crises: Lessons from Nine Crisis Episodes," Open Economies Review, Springer, vol. 25(3), pages 521-570, July.
    3. Jäschke, Stefan, 2014. "Estimation of risk measures in energy portfolios using modern copula techniques," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 359-376.
    4. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    5. repec:wyi:wpaper:002210 is not listed on IDEAS
    6. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 289-300.
    7. Zhu, Hui-Ming & Li, Rong & Li, Sufang, 2014. "Modelling dynamic dependence between crude oil prices and Asia-Pacific stock market returns," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 208-223.
    8. Krenar Avdulaj & Jozef Barunik, 2013. "Are benefits from oil - stocks diversification gone? A new evidence from a dynamic copulas and high frequency data," Papers 1307.5981, arXiv.org.
    9. Wen, Xiaoqian & Guo, Yanfeng & Wei, Yu & Huang, Dengshi, 2014. "How do the stock prices of new energy and fossil fuel companies correlate? Evidence from China," Energy Economics, Elsevier, vol. 41(C), pages 63-75.
    10. Śmiech, Sławomir & Papież, Monika, 2013. "Fossil fuel prices, exchange rate, and stock market: A dynamic causality analysis on the European market," Economics Letters, Elsevier, vol. 118(1), pages 199-202.
    11. Tong, Bin & Wu, Chongfeng & Zhou, Chunyang, 2013. "Modeling the co-movements between crude oil and refined petroleum markets," Energy Economics, Elsevier, vol. 40(C), pages 882-897.

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