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Heterogeneous dependence and dynamic hedging between sectors of BRIC and global markets

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  • Ahmad, Wasim
  • Mishra, Anil V.
  • Daly, Kevin

Abstract

This study examines the dynamic dependence structure via return and volatility spillovers between BRIC (Brazil, Russia, India, and China) and global markets (USA, Europe, and World) at sectoral level. Using directional spillover and dynamic conditional correlation models, we find that there is substantial evidence of heterogeneity across sample sectors within BRIC and between BRIC and global indices. The sectors that exhibit high inter-country spillovers are industrial metal & mining, banking, industrial transportation and oil & gas. The regional and global indices represented by Europe and World show better spillover mechanism than any other indices, implying that these global sectoral indices impact the sectoral indices returns of BRIC markets. The dynamic hedge ratios and portfolio weights suggest that among BRIC, the sectoral indices of China and India provide better opportunities for risk management than Brazil and Russia. We thus conclude that the heterogeneous dependence structure makes BRIC as a diverse asset class from strategic asset allocation perspective.

Suggested Citation

  • Ahmad, Wasim & Mishra, Anil V. & Daly, Kevin, 2018. "Heterogeneous dependence and dynamic hedging between sectors of BRIC and global markets," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 117-133.
  • Handle: RePEc:eee:finana:v:59:y:2018:i:c:p:117-133
    DOI: 10.1016/j.irfa.2018.07.005
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    Cited by:

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    3. Panda, Ajaya Kumar & Panda, Pradiptarathi & Nanda, Swagatika & Parad, Atul, 2021. "Information bias and its spillover effect on return volatility: A study on stock markets in the Asia-Pacific region," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    4. Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2021. "Dynamic return and volatility spillovers among S&P 500, crude oil, and gold," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 153-170, January.
    5. Hendriks, Johannes Jurgens & Bonga-Bonga, Lumengo, 2020. "Sectoral dependence and contagion in the BRICS grouping: an application of the R-Vine copulas," MPRA Paper 102473, University Library of Munich, Germany.
    6. Rehman, Mobeen Ur & Vo, Xuan Vinh & McIver, Ron & Kang, Sang Hoon, 2022. "Sensitivity of US sectoral returns to energy commodities under different investment horizons and market conditions," Energy Economics, Elsevier, vol. 108(C).
    7. Hassan, Kamrul & Hoque, Ariful & Gasbarro, Dominic, 2019. "Separating BRIC using Islamic stocks and crude oil: dynamic conditional correlation and volatility spillover analysis," Energy Economics, Elsevier, vol. 80(C), pages 950-969.
    8. Ying-Ying Shen & Zhi-Qiang Jiang & Jun-Chao Ma & Gang-Jin Wang & Wei-Xing Zhou, 2022. "Sector connectedness in the Chinese stock markets," Empirical Economics, Springer, vol. 62(2), pages 825-852, February.
    9. Jian, Zhihong & Lu, Haisong & Zhu, Zhican & Xu, Huiling, 2023. "Frequency heterogeneity of tail connectedness: Evidence from global stock markets," Economic Modelling, Elsevier, vol. 125(C).
    10. Al-Nassar, Nassar S. & Boubaker, Sabri & Chaibi, Anis & Makram, Beljid, 2023. "In search of hedges and safe havens during the COVID─19 pandemic: Gold versus Bitcoin, oil, and oil uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 318-332.
    11. Kang, Sanghoon & Hernandez, Jose Arreola & Sadorsky, Perry & McIver, Ronald, 2021. "Frequency spillovers, connectedness, and the hedging effectiveness of oil and gold for US sector ETFs," Energy Economics, Elsevier, vol. 99(C).
    12. Ozdemir, Huseyin & Ozdemir, Zeynel Abidin, 2021. "A Survey of Hedge and Safe Havens Assets against G-7 Stock Markets before and during the COVID-19 Pandemic," IZA Discussion Papers 14888, Institute of Labor Economics (IZA).
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    15. N.S. Al-Nassar & Sabri Boubaker & A. Chaibi & B. Makram, 2023. "In Search of Hedges and Safe Havens during the COVID-19 Pandemic: Gold versus Bitcoin, Oil, and Oil Uncertainty," Post-Print hal-04435437, HAL.
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    • 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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G1 - Financial Economics - - General Financial Markets

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