Fluctuation Analysis for the Loss From Default

TL;DR

This paper studies the variability of losses from default in large portfolios, providing a Gaussian approximation for the loss distribution that is both accurate and computationally efficient.

Contribution

It introduces a weak convergence framework for the fluctuation process and develops a Gaussian approximation method for the loss distribution in correlated default models.

Findings

Gaussian approximation closely matches empirical loss distributions

The method improves computational efficiency for large portfolios

Numerical results validate the accuracy of the approximation

Abstract

We analyze the fluctuation of the loss from default around its large portfolio limit in a class of reduced-form models of correlated firm-by-firm default timing. We prove a weak convergence result for the fluctuation process and use it for developing a conditionally Gaussian approximation to the loss distribution. Numerical results illustrate the accuracy and computational efficiency of the approximation.