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Risk spillovers between large banks and the financial sector: Asymmetric evidence from Europe

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  • Shahzad, Syed Jawad Hussain
  • Hoang, Thi Hong Van
  • Arreola-Hernandez, Jose

Abstract

We investigate the interaction between large banks and the financial sector in Europe using the cross-quantilogram approach of Han et al. (2016). We find evidence of asymmetry in the character of the spillovers between the largest European banks and the European financial sector that are dependent on the market state. Specifically, in bearish markets, the financial sector spillovers on large banks, whereas the reverse occurs during bullish markets. The time-varying analysis confirms the asymmetric character of the network structure.

Suggested Citation

  • Shahzad, Syed Jawad Hussain & Hoang, Thi Hong Van & Arreola-Hernandez, Jose, 2019. "Risk spillovers between large banks and the financial sector: Asymmetric evidence from Europe," Finance Research Letters, Elsevier, vol. 28(C), pages 153-159.
    • Handle: RePEc:eee:finlet:v:28:y:2019:i:c:p:153-159
    DOI: 10.1016/j.frl.2018.04.008
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    Cited by:

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    3. Huang, Wei-Qiang & Wang, Dan, 2020. "Financial network linkages to predict economic output," Finance Research Letters, Elsevier, vol. 33(C).
    4. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Hussain Shahzad, Syed Jawad & Výrost, Tomáš, 2022. "Measuring systemic risk in the global banking sector: A cross-quantilogram network approach," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
    5. Foglia, Matteo & Di Tommaso, Caterina & Wang, Gang-Jin & Pacelli, Vincenzo, 2024. "Interconnectedness between stock and credit markets: The role of European G-SIBs in a multilayer perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    6. Liu, Wei & Ma, Qianting & Liu, Xiaoxing, 2022. "Research on the dynamic evolution and its influencing factors of stock correlation network in the Chinese new energy market," Finance Research Letters, Elsevier, vol. 45(C).
    7. Apostolakis, George N. & Floros, Christos & Giannellis, Nikolaos, 2022. "On bank return and volatility spillovers: Identifying transmitters and receivers during crisis periods," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 156-176.
    8. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    9. Huynh, Toan Luu Duc & Foglia, Matteo & Doukas, John A., 2022. "COVID-19 and Tail-event Driven Network Risk in the Eurozone," Finance Research Letters, Elsevier, vol. 44(C).
    10. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
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    12. Qian, Biyu & Wang, Gang-Jin & Feng, Yusen & Xie, Chi, 2022. "Partial cross-quantilogram networks: Measuring quantile connectedness of financial institutions," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).

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    More about this item

    Keywords

    Cross-quantilogram; Large banks; Financial sector; Risk spillovers; Asymmetry; Europe;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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