Abstract
This paper addresses the drawbacks of the macroeconomic approach to estimate downturn loss given defaults (LGD) that is currently used in the EU banking regulation. Using a large dataset of more than 186.000 defaulted credit exposures covering a time span of 18 years we demonstrate by Monte Carlo simulations that the macroeconomic approach proposed by the European Banking Authority (EBA) does not reach a confidence level of 99.9%. As an alternative we develop a downturn LGD estimation based on a latent variable approach. Our simulations demonstrate that this approach outperforms the macroeconomic approach in two dimensions: It induces capital requirements that are sufficient to cover potential losses at a 99.9% confidence level and compared to all regulatory eligible macroeconomic approaches that provide sufficient loss coverage, our approach requires the least amount of capital. The latent variable approach, developed in this paper is applicable for market based LGDs as well as for workout LGDs, i.e., for defaulted exposures with a long workout period. We argue that banking regulation as well as banks’ risk management can be improved if the latent variable approach is used in addition to the traditional macroeconomic approach for estimating downturn LGDs.
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