A Bayesian methodology for systemic risk assessment in financial networks

Date

Oct 14, 2015

Time

5:00 PM - 6:00 PM

Speaker

Prof. Dr. Luitgard Veraart

Affiliation

London School of Economics and Political Science, Department of Mathematics

Series

TUD Dresdner Mathematisches Seminar

Language

en

Main Topic

Mathematik

Other Topics

Mathematik

Host

Prof. Dr. M. Keller-Ressel

Description

We develop a Bayesian methodology for systemic risk assessment in financial networks such as the interbank market. Nodes represent participants in the network and weighted directed edges represent liabilities. Often, for every participant, only the total liabilities and total assets within this network are observable. However, systemic risk assessment needs the individual liabilities. We propose a model for the individual liabilities, which, fol-lowing a Bayesian approach, we then condition on the observed total liabilities and as-sets. We construct a Gibbs sampler to generate samples from this conditional distribu-tion. These samples can be used in stress testing, giving probabilities for the outcomes of interest. As one application we derive default probabilities of individual banks and dis-cuss their sensitivity with respect to prior information included to model the network. An R-package implementing the methodology is provided. This is joint work with Axel Gandy (Imperial College London).

Links

• Dresdner Mathematisches Seminar

Last modified: Oct 7, 2015, 5:04:30 PM