Regensburg 2016 – wissenschaftliches Programm

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AGjDPG: Arbeitsgruppe junge DPG

AGjDPG 1: Tutorial: Evolutionary Dynamics and Applications to Biology, Social and Economic Systems

AGjDPG 1.3: Tutorium

Sonntag, 6. März 2016, 17:40–18:30, H16

Maximum-entropy methods for network reconstruction, systemic risk estimation, and early-warning signals — •Diego Garlaschelli — Lorentz Institute for Theoretical Physics, University of Leiden, The Netherlands

The global financial crisis shifted the interest from traditional measures of ``risk'' of individual banks to new measures of ``systemic risk'', defined as the risk of collapse of an entire interbank system. In principle, estimating systemic risk requires the knowledge of the whole network of exposures among banks. However, due to confidentiality issues, banks only disclose their total exposure towards the aggregate of all other banks, rather than their individual exposures towards each bank. Is it possible to statistically reconstruct the hidden structure of a network in such a way that privacy is protected, but at the same time higher-order properties are correctly predicted? In this talk, I will present a general maximum-entropy approach to the problem of network reconstruction and systemic risk estimation. I will illustrate the power of the method when applied to various economic, social, and biological systems. Then, as a counter-example, I will show how the Dutch interbank network started to depart from its reconstructed counterpart in the three years preceding the 2008 crisis. Over this period, many topological properties of the network showed a gradual transition to the crisis, suggesting their usefulness as early-warning signals of the upcoming crisis. By definition, these early warnings are undetectable if the network is reconstructed from partial bank-specific information.