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On the epidemic of financial crises

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  • Nikolaos Demiris
  • Theodore Kypraios
  • L. Vanessa Smith

Abstract

type="main" xml:id="rssa12044-abs-0001"> The paper proposes a framework for modelling financial contagion that is based on susceptible–infected–recovered transmission models from epidemic theory. This class of models addresses two important features of contagion modelling, which are a common shortcoming of most existing empirical approaches, namely the direct modelling of the inherent dependences that are involved in the transmission mechanism, and an associated canonical measure of crisis severity. The methodology proposed naturally implies a control mechanism, which is required when evaluating prospective immunization policies that intend to mitigate the effect of a crisis. It can be implemented not only as a way of learning from past experiences, but also at the onset of a contagious financial crisis. The approach is illustrated on a number of currency crisis episodes, using both historical final outcome and temporal data. The latter require the introduction of a novel hierarchical model that we call the hidden epidemic model and which embeds the stochastic financial epidemic as a latent process. The empirical results suggest, among others, an increasing trend for global transmission of currency crises over time.

Suggested Citation

  • Nikolaos Demiris & Theodore Kypraios & L. Vanessa Smith, 2014. "On the epidemic of financial crises," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(3), pages 697-723, June.
  • Handle: RePEc:bla:jorssa:v:177:y:2014:i:3:p:697-723
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    File URL: http://hdl.handle.net/10.1111/rssa.2014.177.issue-3
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    Cited by:

    1. Eva F. Janssens & Robin L. Lumsdaine, 2024. "Sectoral slowdowns in the United Kingdom: Evidence from transmission probabilities and economic linkages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 22-40, January.
    2. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    3. Dávid Csercsik & Hubert János Kiss, 2018. "Optimal Payments to Connected Depositors in Turbulent Times: A Markov Chain Approach," Complexity, Hindawi, vol. 2018, pages 1-14, April.
    4. X. Zhang & L. D. Valdez & H. E. Stanley & L. A. Braunstein, 2019. "Modeling Risk Contagion in the Venture Capital Market: A Multilayer Network Approach," Complexity, Hindawi, vol. 2019, pages 1-11, December.
    5. Eva (E.F.) Janssens & Robin (R.) Lumsdaine & Sebastiaan (S.H.L.C.G.) Vermeulen, 2018. "An Epidemiological Model of Crisis Spread Across Sectors in The United States," Tinbergen Institute Discussion Papers 18-008/III, Tinbergen Institute.
    6. Grinis, Inna, 2015. "Credit risk spillovers, systemic importance and vulnerability in financial networks," LSE Research Online Documents on Economics 60954, London School of Economics and Political Science, LSE Library.
    7. Eva F. Janssens & Robin L. Lumsdaine & Sebastiaan H.L.C.G. Vermeulen, 2022. "An Epidemiological Model of Economic Crisis Spread across Sectors in the United States," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(4), pages 885-919, June.
    8. Paolo Bartesaghi & Michele Benzi & Gian Paolo Clemente & Rosanna Grassi & Ernesto Estrada, 2019. "Risk-dependent centrality in economic and financial networks," Papers 1907.07908, arXiv.org, revised Apr 2020.

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