Data-Driven Approach for Systemic Risk

A Macroprudential Perspective

Book Chapter (2022)
Author(s)

F.B. Barsotti (Universiteit van Amsterdam, TU Delft - Applied Probability, ING Analytics)

Research Group
Applied Probability
Copyright
© 2022 F.B. Barsotti
DOI related publication
https://doi.org/10.1007/978-3-031-11818-0_68
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 F.B. Barsotti
Research Group
Applied Probability
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
527-534
ISBN (print)
978-3-031-11817-3
ISBN (electronic)
978-3-031-11818-0
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

This paper proposes a sovereign CDS analysis for systemic risk, assuming a macroprudential perspective and building on the modelling framework proposed by Baglioni and Cherubini (J. Econ. Dynam. Control 37:1581–1597, 2013). A data-driven approach applied to CDS quotes is considered to estimate a reduced form model for the marginal intensity of defaults at country level and investigate the presence of common factors. Results show a systematic effect on default intensities, rank correlation and common factors for countries in the sample with specific geographic differences. This is an important empirical evidence to further investigate how to model, measure and assess the drivers explaining heterogeneity in impacts across countries and build early warning indicators to support strategic decision making.

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