The Estimation Risk in Credit Regulatory Capital

Roberto Baviera ()
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Roberto Baviera: Politecnico di Milano, Department of Mathematics

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2022, pp 76-82 from Springer

Abstract: Abstract In Internal Rating Based approaches, the regulator indicates a model to determine bank’s credit capital requirements. The main concern is on model’s econometric usage and on the estimation of its key parameters: the probability of default and the loss given default. In this study, we point out that taking into account only parameters’ expectation leads to a significant underestimation of bank’s risk and its Regulatory Capital. In particular, we statistically test distributional assumptions on these two parameters and we underline the key role played by parameters’ dependency. We analyse two benchmark datasets: one with all corporations rated by Moody’s and another one that includes only speculative grade firms. Results are striking: we obtain that, considering parameters’ uncertainty, the Regulatory Capital should be increased by an amount in the range between 38% and 66%. A clear policy implication stems from this study: the scaling factor for model risk, removed by Basel III accord, should be reintroduced in the determination of credit Regulatory Capital.

Keywords: Model risk; IRB; LGD-PD dependency; Scaling factor (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-99638-3_13

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DOI: 10.1007/978-3-030-99638-3_13

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