2019-02-23T04:55:08Zhttp://repositori.uji.es/oai/requestoai:repositori.uji.es:10234/1666132018-11-08T08:52:03Zcom_10234_8643com_10234_9col_10234_8644
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Montagna, Mattia
author
Lux, Thomas
author
2016
One lesson of the financial crisis erupting in 2008 has been that domino effects constitute a serious
threat to the stability of the financial sector, i.e. the failure of one node in the interbank network
might entail the danger of contagion to large parts of the entire system. How important this effect
is, depends on the exact topology of the network on which the supervisory authorities have typically
very incomplete knowledge. In order to explore the extent of contagion effects and to analyse the
effectiveness of macroprudential measures to contain such effects, a reconstruction of the quantitative
features of the empirical network would be needed. We propose a probabilistic approach to such a
reconstruction: we propose to combine some important known quantities (like the size of the banks)
with a realistic stochastic representation of the remaining structural elements. Our approach allows
us to evaluate relevant measures for the contagion risk after default of one unit (i.e. the number of
expected subsequent defaults, or their probabilities). For some quantities we are able to derive closed
form solutions, others can be obtained via computational mean-field approximations.
Mattia Montagna & Thomas Lux (2017) Contagion risk in the interbank market: a probabilistic approach to cope with incomplete structural information, Quantitative Finance, 17:1, 101-120
1469-7688
1469-7696
http://hdl.handle.net/10234/166613
http://dx.doi.org/10.1080/14697688.2016.1178855
Contagion
Interbank market
Network models
Contagion risk in the interbank market: a probabilistic approach to cope with incomplete structural information