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When two banks fall, how do markets react?

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  • Dora Almeida
  • Andreia Dionísio
  • Paulo Ferreira

Abstract

The most recent fall of the Silicon Valley (SVB) and Credit Suisse (CS) banks increased the fear of a worldwide banking crisis. We analyse the impacts of their fall on five financial indices. We apply detrended fluctuation analysis, static and with sliding windows. We find a higher impact of the SVB fall on the efficiency dynamic of the studied indices, which revealed fluctuating efficiency and a loss of efficiency during the period of the falls. The fall of both banks contributed to some persistence in stock indices returns. The Nasdaq and STOXX Europe 600 Banks are the most and the least efficient indices, respectively. Despite the apparent evidence of inefficiency, it might not necessarily mean a capacity for abnormal profits.

Suggested Citation

  • Dora Almeida & Andreia Dionísio & Paulo Ferreira, 2023. "When two banks fall, how do markets react?," Economics and Business Letters, Oviedo University Press, vol. 12(4), pages 331-341.
    • Handle: RePEc:ove:journl:aid:19622
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    File URL: https://reunido.uniovi.es/index.php/EBL/article/view/19622
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    References listed on IDEAS

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    1. Paulo Ferreira, 2020. "Dynamic long-range dependences in the Swiss stock market," Empirical Economics, Springer, vol. 58(4), pages 1541-1573, April.
    2. Natália Costa & César Silva & Paulo Ferreira, 2019. "Long-Range Behaviour and Correlation in DFA and DCCA Analysis of Cryptocurrencies," IJFS, MDPI, vol. 7(3), pages 1-12, September.
    3. Paulo Ferreira & Andreia Dion�sio, 2014. "Revisiting serial dependence in the stock markets of the G7 countries, Portugal, Spain and Greece," Applied Financial Economics, Taylor & Francis Journals, vol. 24(5), pages 319-331, March.
    4. Cajueiro, Daniel O. & Tabak, Benjamin M., 2006. "Testing for predictability in equity returns for European transition markets," Economic Systems, Elsevier, vol. 30(1), pages 56-78, March.
    5. Cao, Guangxi & Zhang, Minjia, 2015. "Extreme values in the Chinese and American stock markets based on detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 25-35.
    6. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    7. Cajueiro, Daniel O. & Tabak, Benjamin M., 2008. "Testing for time-varying long-range dependence in real state equity returns," Chaos, Solitons & Fractals, Elsevier, vol. 38(1), pages 293-307.
    8. Cajueiro, Daniel O. & Tabak, Benjamin M., 2004. "Evidence of long range dependence in Asian equity markets: the role of liquidity and market restrictions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(3), pages 656-664.
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