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Measuring systemic risk of the US banking sector in time-frequency domain

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  • Teply, Petr
  • Kvapilikova, Ivana

Abstract

To estimate short-term, medium-term, and long-term financial connectedness, we propose a frequency-based approach and measure the contribution of individual financial institutions to overall systemic risk. We derive Wavelet Conditional Value at Risk (WCoVaR) – a robust market-based measure of systemic risk across financial cycles of differing length. We evaluate the systemic importance of financial institutions based on their stock returns and use wavelet framework to analyze returns in a time-frequency domain. Empirical analysis on US banking sector data between 2004 and 2013 demonstrates that wavelet decomposition can improve the forecast power of the CoVaR measure. We use panel regression to explain systemic importance of individual banks, using their objectively measurable characteristics and conclude that size, volatility and value-at-risk are the most robust determinants of systemic risk.

Suggested Citation

  • Teply, Petr & Kvapilikova, Ivana, 2017. "Measuring systemic risk of the US banking sector in time-frequency domain," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 461-472.
  • Handle: RePEc:eee:ecofin:v:42:y:2017:i:c:p:461-472
    DOI: 10.1016/j.najef.2017.08.007
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    5. Mensi, Walid & Rehman, Mobeen Ur & Maitra, Debasish & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh, 2021. "Oil, natural gas and BRICS stock markets: Evidence of systemic risks and co-movements in the time-frequency domain," Resources Policy, Elsevier, vol. 72(C).
    6. Tian, Maoxi & Guo, Fei & Niu, Rong, 2022. "Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    7. Meng, Xiangcai & Huang, Chia-Hsing, 2019. "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 131-148.
    8. Axel Per Hedström & Gazi Salah Uddin & Md Lutfur Rahman & Bo Sjö, 2024. "Systemic risk in the Scandinavian banking sector," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 581-608, January.
    9. Petr Teply & Tomas Klinger, 2019. "Agent-based modeling of systemic risk in the European banking sector," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 811-833, December.
    10. 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.
    11. Bhuiyan, Rubaiyat Ahsan & Rahman, Maya Puspa & Saiti, Buerhan & Ghani, Gairuzazmi Bin Mat, 2019. "Does the Malaysian Sovereign sukuk market offer portfolio diversification opportunities for global fixed-income investors? Evidence from wavelet coherence and multivariate-GARCH analyses," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 675-687.
    12. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    13. Zulu, Thulani & Manguzvane, Mathias Mandla & Bonga-Bonga, Lumengo, 2023. "Assessing the contribution of South African Insurance Firms to Systemic Risk," MPRA Paper 116815, University Library of Munich, Germany.
    14. Xu, Qifa & Jin, Bei & Jiang, Cuixia, 2021. "Measuring systemic risk of the Chinese banking industry: A wavelet-based quantile regression approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    15. Tarek Eldomiaty & Amr Youssef & Heba Mahrous, 2022. "The Robustness of the Determinants of Overall Bank Risks in the MENA Region," JRFM, MDPI, vol. 15(10), pages 1-17, September.

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