New credit risk modelling approach touted to reduce CCAR bias
Academic aims to address gaps in existing LGD forecast method with two-equation fix
A new way of modelling likely losses on loan portfolios claims to offer banks more accurate results by correcting what an academic describes as “bias” in lenders’ loss forecasts. The method also promises sounder macroeconomic sensitivity analysis in estimating required capital for regulatory stress tests.
In a recent paper in the Journal of Credit Risk, Northwestern University professor Heng Chen proposes an improvement to traditional loss given default (LGD) models where time to recovery is
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