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Measuring the connectedness of global health sector stock markets

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  • Ye, Liping
  • Geng, Jiang-Bo

Abstract

This paper uses the minimum spanning tree model to investigate the dependency structure and integration degree of the global health sector stock markets. It examines the direction, intensity, time-varying characteristics, and asymmetric effects of return connectedness among these stock markets using the directional connectedness network model. It also explores the hedging and diversification analyses of global health sector stock markets. The empirical results suggest that health sector stock markets of the developing and developed countries show obvious group clustering characteristics, forming a low level of integration between the two groups and a high degree of integration within each group. For the return connectedness network, France, the UK, the US, and Germany are net return transmitters. India, Canada, China, Japan, and South Africa are net return recipients. Meanwhile, return spillovers among health sector stocks in these nine countries have obvious time-varying characteristics. In particular, the 2008 global financial crisis increased the integration level among global health sector stock markets. Moreover, there exists a significant asymmetric effect of return spillover among the global health sector stock markets, and the return spillover intensity in a declining market is significantly higher than it is in favourable market conditions. Finally, diversification evidence shows the optimal hedge ratios and portfolio weights across all nine countries changes over time.

Suggested Citation

  • Ye, Liping & Geng, Jiang-Bo, 2021. "Measuring the connectedness of global health sector stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
  • Handle: RePEc:eee:pacfin:v:68:y:2021:i:c:s0927538x21001220
    DOI: 10.1016/j.pacfin.2021.101615
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    as
    1. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    2. Hannes Schwandt, 2018. "Wealth Shocks and Health Outcomes: Evidence from Stock Market Fluctuations," American Economic Journal: Applied Economics, American Economic Association, vol. 10(4), pages 349-377, October.
    3. Shan Huang & Martin Salm, 2020. "The effect of a ban on gender‐based pricing on risk selection in the German health insurance market," Health Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 3-17, January.
    4. Chad Cotti & Richard A. Dunn & Nathan Tefft, 2015. "The Dow is Killing Me: Risky Health Behaviors and the Stock Market," Health Economics, John Wiley & Sons, Ltd., vol. 24(7), pages 803-821, July.
    5. Kang, Sang Hoon & Maitra, Debasish & Dash, Saumya Ranjan & Brooks, Robert, 2019. "Dynamic spillovers and connectedness between stock, commodities, bonds, and VIX markets," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    6. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    7. Chen, Mei-Ping & Lin, Yu-Hui & Tseng, Chun-Yao & Chen, Wen-Yi, 2015. "Bubbles in health care: Evidence from the U.S., U.K., and German stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 193-205.
    8. Chen, Mei-Ping & Chen, Wen-Yi & Tseng, Tseng-Chan, 2017. "Co-movements of returns in the health care sectors from the US, UK, and Germany stock markets: Evidence from the continuous wavelet analyses," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 484-498.
    9. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    10. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    11. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    12. Schell, Daniel & Wang, Mei & Huynh, Toan Luu Duc, 2020. "This time is indeed different: A study on global market reactions to public health crisis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    13. Jozef Barunik & Mattia Bevilacqua & Radu Tunaru, 2022. "Asymmetric Network Connectedness of Fears," The Review of Economics and Statistics, MIT Press, vol. 104(6), pages 1304-1316, November.
    14. John A. Vernon & Joseph H. Golec & Joseph A. Dimasi, 2010. "Drug development costs when financial risk is measured using the Fama–French three‐factor model," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 1002-1005, August.
    15. Tsai, Chun-Li, 2015. "How do U.S. stock returns respond differently to oil price shocks pre-crisis, within the financial crisis, and post-crisis?," Energy Economics, Elsevier, vol. 50(C), pages 47-62.
    16. Mollick, André Varella & Assefa, Tibebe Abebe, 2013. "U.S. stock returns and oil prices: The tale from daily data and the 2008–2009 financial crisis," Energy Economics, Elsevier, vol. 36(C), pages 1-18.
    17. Yujing Shen & Randall P. Ellis, 2002. "How profitable is risk selection? A comparison of four risk adjustment models," Health Economics, John Wiley & Sons, Ltd., vol. 11(2), pages 165-174, March.
    18. Huyghebaert, Nancy & Wang, Lihong, 2010. "The co-movement of stock markets in East Asia: Did the 1997-1998 Asian financial crisis really strengthen stock market integration?," China Economic Review, Elsevier, vol. 21(1), pages 98-112, March.
    19. Huang, Shan & Salm, Martin, 2020. "The effect of a ban on gender-based pricing on risk selection in the German health insurance market," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 29(1), pages 3-17.
    20. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    21. M. Ruth Lavergne & Lindsay Hedden & Michael R. Law & Kim McGrail & Megan Ahuja & Morris Barer, 2018. "The impact of the 2008/2009 financial crisis on specialist physician activity in Canada," Health Economics, John Wiley & Sons, Ltd., vol. 27(11), pages 1859-1867, November.
    22. Elsayed, Ahmed H. & Nasreen, Samia & Tiwari, Aviral Kumar, 2020. "Time-varying co-movements between energy market and global financial markets: Implication for portfolio diversification and hedging strategies," Energy Economics, Elsevier, vol. 90(C).
    23. Robyn Swift, 2011. "The relationship between health and GDP in OECD countries in the very long run," Health Economics, John Wiley & Sons, Ltd., vol. 20(3), pages 306-322, March.
    24. Bidisha Mandal & Raymond G. Batina & Wen Chen, 2018. "Do gender gaps in education and health affect economic growth? A cross‐country study from 1975 to 2010," Health Economics, John Wiley & Sons, Ltd., vol. 27(5), pages 877-886, May.
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