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Frequency volatility connectedness across different industries in China

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  • Jiang, Junhua
  • Piljak, Vanja
  • Tiwari, Aviral Kumar
  • Äijö, Janne

Abstract

Utilizing the advantageous method of Barunik and Krehlik (2018), we examine the frequency connectedness of equity volatilities across 12 industries in China from October 2003 to April 2018. The results indicate that the main targets of risks in China are Banking and Real Estate, while the main sources of risks are Construction and Materials, Industrial Transportation, and Chemicals. The study also highlights the importance of the use of frequency connectedness method such that the main targets and sources of risks at different frequencies over different time periods can be detected, providing essential information for the monitoring of the financial market.

Suggested Citation

  • Jiang, Junhua & Piljak, Vanja & Tiwari, Aviral Kumar & Äijö, Janne, 2020. "Frequency volatility connectedness across different industries in China," Finance Research Letters, Elsevier, vol. 37(C).
    • Handle: RePEc:eee:finlet:v:37:y:2020:i:c:s1544612319302910
    DOI: 10.1016/j.frl.2019.101376
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    as
    1. 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.
    2. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    3. 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.
    4. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    5. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    6. Fernández-Rodríguez, Fernando & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2016. "Using connectedness analysis to assess financial stress transmission in EMU sovereign bond market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 126-145.
    7. Baum, Christopher F. & Kurov, Alexander & Wolfe, Marketa Halova, 2015. "What do Chinese macro announcements tell us about the world economy?," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 100-122.
    8. Francis X. Diebold & Kamil Yilmaz, 2016. "Trans-Atlantic Equity Volatility Connectedness: U.S. and European Financial Institutions, 2004–2014," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 81-127.
    9. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan & Plakandaras, Vasilios, 2018. "Dynamic connectedness of uncertainty across developed economies: A time-varying approach," Economics Letters, Elsevier, vol. 166(C), pages 63-75.
    10. Dayong Zhang & Gang-Zhi Fan, 2019. "Regional spillover and rising connectedness in China’s urban housing prices," Regional Studies, Taylor & Francis Journals, vol. 53(6), pages 861-873, June.
    11. Chan, Steven & Han, Gaofeng & Zhang, Wenlang, 2016. "How strong are the linkages between real estate and other sectors in China?," Research in International Business and Finance, Elsevier, vol. 36(C), pages 52-72.
    12. Gabauer, David & Gupta, Rangan, 2018. "On the transmission mechanism of country-specific and international economic uncertainty spillovers: Evidence from a TVP-VAR connectedness decomposition approach," Economics Letters, Elsevier, vol. 171(C), pages 63-71.
    13. Tiwari, Aviral Kumar & Cunado, Juncal & Gupta, Rangan & Wohar, Mark E., 2018. "Volatility spillovers across global asset classes: Evidence from time and frequency domains," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 194-202.
    14. Koutmos, Dimitrios, 2018. "Return and volatility spillovers among cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 122-127.
    15. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    16. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    17. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    18. Wang, Xunxiao & Wang, Yudong, 2019. "Volatility spillovers between crude oil and Chinese sectoral equity markets: Evidence from a frequency dynamics perspective," Energy Economics, Elsevier, vol. 80(C), pages 995-1009.
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    Cited by:

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    2. Naeem, Muhammad Abubakr & Karim, Sitara & Tiwari, Aviral Kumar, 2022. "Quantifying systemic risk in US industries using neural network quantile regression," Research in International Business and Finance, Elsevier, vol. 61(C).
    3. Liow, Kim Hiang & Song, Jeong Seop, 2022. "Frequency volatility connectedness and market integration in international real estate investment trusts," Finance Research Letters, Elsevier, vol. 45(C).
    4. Cao, Li & Jiang, Junhua & Piljak, Vanja, 2023. "Did mega-regional trade agreements reshuffle the financial influence of the US, China, and Japan in ASEAN? Evidence from the volatility-spillover effects," Research in International Business and Finance, Elsevier, vol. 65(C).
    5. Ahmad, Wasim & Hernandez, Jose Arreola & Saini, Seema & Mishra, Ritesh Kumar, 2021. "The US equity sectors, implied volatilities, and COVID-19: What does the spillover analysis reveal?," Resources Policy, Elsevier, vol. 72(C).
    6. Qiao, Xingzhi & Zhu, Huiming & Zhang, Zhongqingyang & Mao, Weifang, 2022. "Time-frequency transmission mechanism of EPU, investor sentiment and financial assets: A multiscale TVP-VAR connectedness analysis," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).

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    More about this item

    Keywords

    Frequency volatility connectedness; Volatility spillovers; Chinese industries;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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