Regulatory and "economic" solvency standards for internationally active banks
One of the most important policy issues for financial authorities is to decide at what level average capital charges should be set. The decision may alternatively be expressed as the choice of an appropriate survival probability for representative banks over a horizon such as a year, often termed a solvency standard. In this paper, light is shed on the solvency standards implied by current and possible future G10 bank regulation, and on the economic solvency standard that banks choose themselves by their own capital-setting decisions. In particular, a credit risk model is employed to show that the survival probability implied by the 1988 Basel Accord is between 99.0% and 99.9%. It is then demonstrated that if a new Basel Accord were calibrated to such a standard, it would not represent a binding constraint on banks' current operations, since most banks employ a solvency standard significantly higher than 99.9%. To show this, a statistical analysis of bank ratings is employed, adjusted for the impact of official or other support, as well as credit risk model calculations. Lastly, a possible explanation is advanced for the conservative capital choices made by banks, by showing that swap volumes are highly correlated with credit quality for given bank size. This suggests that banks' access to important credit markets like the swap markets may provide a significant discipline in the choice of solvency standard.
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- Ronn, Ehud I. & Verma, Avinash K., 1989. "Risk-based capital adequacy standards for a sample of 43 major banks," Journal of Banking & Finance, Elsevier, vol. 13(1), pages 21-29, March.
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"A comparative anatomy of credit risk models,"
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Elsevier, vol. 24(1-2), pages 119-149, January.
- Simonne Varotto, 2001. "Credit Risk Diversification," ICMA Centre Discussion Papers in Finance icma-dp2001-07, Henley Business School, Reading University.
- Pamela Nickell & William Perraudin & Simone Varotto, 2001. "Ratings versus equity-based credit risk modelling: an empirical analysis," Bank of England working papers 132, Bank of England.
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