Modeling Stressed LGDs for Macroeconomic Scenarios

New accounting standards, which place increased emphasis on the ability of banks to calculate current expected credit losses, also make clear the importance of using models that appropriately link probabilities of default (PDs) and losses given default (LGDs) to macroeconomic drivers. At the same time, calculating conditional expected credit losses under Fed-supervised stress tests requires stressed PDs and LGDs as inputs. While validated stressed PD models are already on offer, efforts to properly model LGDs as a function of macroeconomic drivers are still in their infancy.

In this article, we develop and validate a model for stressed LGDs aimed at meeting this need. Empirically, we find that LGDs sometimes lead PDs by several months during crisis periods. At the sector level, our stressed LGDs provide reasonably accurate forecasts out-of-sample for most sectors and exhibit attractive qualities under the Fed’s baseline, adverse, and severely adverse Comprehensive Capital Analysis and Review (CCAR) scenarios for all 13 sectors studied.

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