Analytical Framework for Credit Portfolios

TL;DR

This paper introduces an analytical framework for calculating credit portfolio risk metrics such as VaR and Expected Shortfall, eliminating the need for computationally intensive simulations.

Contribution

It presents a novel analytical method for credit risk measurement based on a multi-factor Merton-type model, enabling efficient and accurate risk assessment.

Findings

High accuracy demonstrated through benchmarking against Monte Carlo simulations

Framework allows risk allocation to individual transactions

Eliminates the need for time-consuming simulations

Abstract

Analytical, free of time consuming Monte Carlo simulations, framework for credit portfolio systematic risk metrics calculations is presented. Techniques are described that allow calculation of portfolio-level systematic risk measures (standard deviation, VaR and Expected Shortfall) as well as allocation of risk down to individual transactions. The underlying model is the industry standard multi-factor Merton-type model with arbitrary valuation function at horizon (in contrast to the simplistic default-only case). High accuracy of the proposed analytical technique is demonstrated by benchmarking against Monte Carlo simulations.