TITLE:
Low Default Portfolios—A Proposed Rule to Identify Differences between Imprudence, Conservatism, and Exaggeration
AUTHORS:
David J. C. Dinis
KEYWORDS:
Credit Risk, Default Probability, Correlated Distributions, Classical Approach, Bayesian Approach, Conservative Zone
JOURNAL NAME:
Journal of Financial Risk Management,
Vol.11 No.1,
January
24,
2022
ABSTRACT: Internal models may be used by banks to calculate
their regulatory capital for credit risk. There are a variety of methodologies
for estimating default probabilities, which leads to major differences in
credit provisions and capital requirements. Using either a classical or a
Bayesian technique, the computation of default probabilities can be ensured.
Reduced form models are a choice. These models, however, might not be used to
quantify economic capital because they assume independence among default
events. Banks are compelled to employ structural models since defaults in the
real world of banking are not solely due to exogenous causes. Because of the
diversification effects between credit losses for one obligor and credit losses
for other obligors in each bank’s portfolio, total unexpected losses do not
equal the sum of individual unexpected
losses. Those two types of models—reduced form and structural—are
provided in either a theoretical or a numerical format. This paper covers both
the classical and Bayesian techniques, with the latter employing a broader set of
prior functions that offer considerably different probabilities. Distinguishing
between imprudence, conservatism, and exaggeration might be difficult in the
context of low default portfolios with scarce data. A realistic rule is
proposed for finding the minimum and maximum bounds and therefore assessing the
required conservatism margin by comparing classical and Bayesian probabilities.