Aggregating Credit and Market Risk: The Impact of Model Specification

Abstract

We investigate the effect of model specification on the aggregation of (correlated) market and credit risk. We focus on the functional form linking systematic credit risk drivers to default probabilities. Examples include the normal based probit link function for typical structural models, or the exponential (Poisson) link function for typical reduced form models. We first show analytically how model specification impacts 'diversification benefits' for aggregated market and credit risk. The specification effect can lead to Value-at-Risk (VaR) reductions in the range of 3 percent to 47 percent, particularly at high confidence level VaRs. We also illustrate the effects using a fully calibrated empirical model for US data. The empirical effects corroborate our analytic results.