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Modelling tail dependence between energy market and stock markets in the BRIC countries

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  • Zhiyuan Pan

Abstract

This article investigates the tail dependence structure between energy market and stock markets returns in the BRIC (Brazil, Russia, India and China) countries over the period from 12 January 2000 to 28 December 2012. Using the regime switching dynamic symmetrized Joe--Clayton (SJC) copula model, we find that the tail dependence increased rather substantially in the financial crisis of 2008/12; moreover, the lower tail dependence for all the paired returns is almost larger than the upper one. Finally, the tail dependence is found to be the strongest for Russia and the weakest for China. The empirical results documented in this study have important implications for portfolio and risk management.

Suggested Citation

  • Zhiyuan Pan, 2014. "Modelling tail dependence between energy market and stock markets in the BRIC countries," Applied Economics Letters, Taylor & Francis Journals, vol. 21(11), pages 789-794, July.
    • Handle: RePEc:taf:apeclt:v:21:y:2014:i:11:p:789-794
    DOI: 10.1080/13504851.2014.892188
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    Cited by:

    1. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Imhotep Paul Alagidede & Shawkat Hammoudeh, 2023. "Nonlinearity in the causality and systemic risk spillover between the OPEC oil and GCC equity markets: a pre- and post-financial crisis analysis," Empirical Economics, Springer, vol. 65(3), pages 1027-1103, September.
    2. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    3. Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad & Balli, Faruk & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency domain quantile coherence of emerging stock markets with gold and oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    4. BenSaïda, Ahmed, 2018. "The contagion effect in European sovereign debt markets: A regime-switching vine copula approach," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 153-165.
    5. Wang, Lu & Ma, Feng & Niu, Tianjiao & He, Chengting, 2020. "Crude oil and BRICS stock markets under extreme shocks: New evidence," Economic Modelling, Elsevier, vol. 86(C), pages 54-68.
    6. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    7. Tiwari, Aviral Kumar & Trabelsi, Nader & Alqahtani, Faisal & Hammoudeh, Shawkat, 2019. "Analysing systemic risk and time-frequency quantile dependence between crude oil prices and BRICS equity markets indices: A new look," Energy Economics, Elsevier, vol. 83(C), pages 445-466.
    8. Wang, Ze & Gao, Xiangyun & An, Haizhong & Tang, Renwu & Sun, Qingru, 2020. "Identifying influential energy stocks based on spillover network," International Review of Financial Analysis, Elsevier, vol. 68(C).
    9. Yonghong Jiang & Jinqi Mu & He Nie & Lanxin Wu, 2022. "Time‐frequency analysis of risk spillovers from oil to BRICS stock markets: A long‐memory Copula‐CoVaR‐MODWT method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3386-3404, July.

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