Calculating Value-at-Risk Using the Granularity Adjustment Method in the Portfolio Credit Risk Model with Random Loss Given Default

Abstract

According to the Basel Committee on Banking Supervision (BCBS), the internal ratings-based approach of Basel II and Basel III allows a bank to calculate the Valueat-Risk (VaR) for portfolio credit risk by using its own credit risk model. In this paper we use the Granularity Adjustment (GA) method proposed by Martin and Wilde (2002) to calculate VaR in the portfolio credit risk model with random loss given default. Moreover, we utilize a Monte Carlo simulation to study the impact of concentration risk on VaR.