The Binomial Test evaluates
whether the PD of a pool is correctly estimated. It does not take
into account correlated defaults, and it generally yields an overestimate
of the significance of deviations in the realized default rate from
the forecast rate. The Modified Binomial Test now addresses the overestimate.
This test takes into account the correlated defaults
(footnote1)
.
The default correlation coefficient in SAS Model Manager is 0.04.
By using past banking evaluations, you can use these rho values
(footnote2)
:
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The Confidence Interval
indicates the confidence interval band of the PD or LGD for a pool.
The Probability of Default report compares the actual and estimated
PD rates with the CI limit of the estimate. If the estimated PD lies
in the CI limits of the actual PD model, the PD performs better in
estimating actual outcomes.
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The model validation
report for LGD provides a correlation analysis of the estimated LGD
with the actual LGD. This correlation analysis is an important measure
for a model’s usefulness. The Pearson correlation coefficients
are provided at the pool and overall levels for each time period are
examined.
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The Hosmer-Lemeshow
test is a statistical test for goodness-of-fit for classification
models. The test assesses whether the observed event rates match the
expected event rates in pools. Models for which expected and observed
event rates in pools are similar are well calibrated. The p-value
of this test is a measure of the accuracy of the estimated default
probabilities. The closer the p-value is to zero, the poorer the calibration
of the model.
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The Normal Test compares
the normalized difference of predicted and actual default rates per
pool with two limits estimated over multiple observation periods.
This test measures the pool stability over time. If a majority of
the pools lie in the rejection region, to the right of the limits,
then the pooling strategy should be revisited.
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The Traffic Lights Test
evaluates whether the PD of a pool is underestimated, but unlike the
binomial test, it does not assume that cross-pool performance is statistically
independent. If the number of default accounts per pool exceeds either
the low limit (Traffic Lights Test at 0.95 confidence) or high limit
(Traffic Lights Test at 0.99 confidence), the test suggests the model
is poorly calibrated.
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