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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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    Cited by:

    1. 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).
    2. 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).
    3. 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).
    4. Zhang, Yingying & Xu, Shaojun, 2023. "Spillover connectedness between oil and China's industry stock markets: A perspective of carbon emissions," Finance Research Letters, Elsevier, vol. 54(C).
    5. 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).
    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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