Title: Analysis of Systemic Risk in Financial Networks with Credit Default Swaps via Monte Carlo Simulations (MSc thesis defense)
Abstract: We examine what effect the presence of CDSs has on systemic risks, mainly default ambiguity by conducting Monte Carlo simulations. Default ambiguity is a situation where it is impossible to decide which banks are in default. This phenomenon is observed when we strive to solve the clearing problem. It is known that, in financial networks with CDSs, the clearing problem is computationally hard and the desired properties proposed by Eisenberg and Noe (2001) are not guaranteed to hold anymore. Our first contribution is development of a stress testing algorithm that is both efficient and is able to provide certificates for instances in which these desiderata are not satisfied. Furthermore, we define an analysis framework which enables us to present the quantitative effects of the network structure on default ambiguity. Finally, we observe that this type of systemic risk arises in realistic networks and thus we will discuss policy implications to prevent the occurrence of this systemic risk in CDS market.
Note: This is going to be a short talk (approx. 20 minutes) followed by a round of questions (approx. 10 minutes).