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Stress Testing and Systemic Risk Measures Using Elliptical Conditional Multivariate Probabilities

Aste, T; (2021) Stress Testing and Systemic Risk Measures Using Elliptical Conditional Multivariate Probabilities. Journal of Risk and Financial Management , 14 (5) , Article 213. 10.3390/jrfm14050213. Green open access

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Abstract

Systemic risk, in a complex system with several interrelated variables, such as a financial market, is quantifiable from the multivariate probability distribution describing the reciprocal influence between the system’s variables. The effect of stress on the system is reflected by the change in such a multivariate probability distribution, conditioned to some of the variables being at a given stress’ amplitude. Therefore, the knowledge of the conditional probability distribution function can provide a full quantification of risk and stress propagation in the system. However, multivariate probabilities are hard to estimate from observations. In this paper, I investigate the vast family of multivariate elliptical distributions, discussing their estimation from data and proposing novel measures for stress impact and systemic risk in systems with many interrelated variables. Specific examples are described for the multivariate Student-t and the multivariate normal distributions applied to financial stress testing. An example of the US equity market illustrates the practical potentials of this approach.

Type: Article
Title: Stress Testing and Systemic Risk Measures Using Elliptical Conditional Multivariate Probabilities
Open access status: An open access version is available from UCL Discovery
DOI: 10.3390/jrfm14050213
Publisher version: http://dx.doi.org/10.3390/jrfm14050213
Language: English
Additional information: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: stress testing; systemic risk; elliptical conditional probability
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10128098
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