Given limited network information, we consider robust risk quantification under the Eisenberg-Noe model for financial networks. To be more specific, motivated by the fact that the structure of the interbank network is not completely known in practice, we propose a robust optimization approach to...

Stress testing of financial systems has been increasingly important after several financial crises in recent years, thereby drawing keen attention to the choice of appropriate stress scenarios to effectively test the robustness of the systems. To this end, we consider the problem of identifying...

We consider an ordinal optimization problem, where a decision maker learns the statistical characteristics of a number of systems using sequential sampling in order to ultimately determine the "best" one (with high probability). In so doing, the decision maker postulates a parametric model which...

We consider the problem of estimating the expectation over a convex polyhedron specified by a set of linear inequalities. This problem encompasses a multitude of financial applications including systemic risk quantification, exotic option pricing, and portfolio management. We particularly focus...