Our paper "Solution Space Size in Credit Risk Simulation" on credit risk analysis has been presented at the 15th International Conference on Computer Modelling and Simulation UKSim 2013, held in Cambridge on April 9-12, 2013. You can download the presentation hereFollowing our previous paper at UKSim 2012, we tackle the issue of analysing credit risk, i.e., the chance that a lending institution does not get its money back. Rather than focusing on the evaluation of the loss probability as in the past, we now address the problem of identifying the obligors involved in the most critical default situations.
Abstract: In a portfolio of securities, lenders may incur sub- stantial losses if the obligors do not return the money borrowed by them. In credit risk evaluation through simulation, the states of the portfolio associated to large losses are sampled rather than identified exhaustively. Enumeration of all such critical states is however relevant for the early warning of heavy losses. We provide a general enumerative algorithm, and evaluate its computational complexity, which results to be equal to the number of critical states, for three cases of the distribution of losses associated to individual obligors: uniform, linear, and exponential. In the presence of a possibly huge number of critical states, the evaluation of the computational complexity allows us to assess beforehand if the enumeration task is feasible.
