Abstract:

Numerical optimization is pervasive in applied finance. Here we present a nontypical use in which we are trying to measure the risk for a set of portfolios instead of an individual portfolio. Key here is the interplay between model selection and computational tractability. Specifically, the problem is modeled to produce a specific type of convex optimization problem (second order cone program) which may be solved efficiently using interior point methods.