On the epidemic of financial crises

Demiris, Nikolaos, Kypraios, Theodore and Smith, Lynette Vanessa (2014) On the epidemic of financial crises. Journal of the Royal Statistical Society: Series A (Statistics in Society), 177 (3). pp. 697-723. ISSN 1467-985X

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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.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/728350
Additional Information: This is the peer reviewed version of the following article: Demiris, N., Kypraios, T. and Vanessa Smith, L. (2014), On the epidemic of financial crises. J. R. Stat. Soc. A, 177: 697–723., which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/rssa.12044/full. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Keywords: Contagion; Financial crisis; Markov chain Monte Carlo methods; Random graph;Stochastic epidemic model
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
Identification Number: https://doi.org/10.1111/rssa.12044
Depositing User: Eprints, Support
Date Deposited: 10 Oct 2017 09:48
Last Modified: 04 May 2020 16:47
URI: https://eprints.nottingham.ac.uk/id/eprint/47113

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