Browsing by Subject "Systemic Risk"

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Open Access
Computation of systemic risk measures: a mixed-integer linear programming approach
(2018-12) Meimanjanov, Nurtai
In the scope of nance, systemic risk is concerned with the instability of a nancial system, where the members of the system are interdependent in the sense that the failure of some institutions may trigger defaults throughout the system. National and global economic crises are important examples of such system collapses. One of the factors that contribute to systemic risk is the existence of mutual liabilities that are met through a clearing procedure. In this study, two network models of systemic risk involving a clearing procedure, the Eisenberg-Noe network model and the Rogers-Veraart network model, are investigated and extended from the optimization point of view. The former one is extended to the case where operating cash ows in the system are unrestricted in sign. Two mixed integer linear programming (MILP) problems are introduced, which provide programming characterizations of clearing vectors in both the signed Eisenberg-Noe and Rogers-Veraart network models. The modi cations made to these network models are nancially interpretable. Based on these modi cations, two MILP aggregation functions are introduced and used to de ne systemic risk measures. These systemic risk measures, which are not necessarily convex set-valued functions, are then approximated by a Benson type algorithm with respect to a user-de ned error level and a user-de ned upper-bound vector. This algorithm involves approximating the upper images of some associated non-convex vector optimization problems. A computational study is conducted on two-group and three-group systemic risk measures. In addition, sensitivity analyses are performed on twogroup systemic risk measures.
Open Access
Network formation with systemic risk and default insurance
(2016-07) İdem, Mehmet Hamdi Berk
In this paper, we study the networks that arise in the equilibrium when risk averse investors play a network formation game for making joint investments with each other. The outcomes of these projects are stochastic and hence, depending on the shock realizations, investors may choose to default. However, counterparty defaults are damaging and investors have the option to buy default insurances against this damage. We show that in this model, equilibrium networks consist of complete components of a certain size, which maximize the expected utility of investors in that component. For a wide variety of parameters, it turns out that investors choose not to buy any insurance at the equilibrium.