QMMPlot: Plot Results of Probability of Default Calibration

In LDPD: Probability of Default Calibration

Description

Plot detailed results of probability of default calibration using Quasi Moment Matching algorithm.

Usage

QMMPlot(x)

Arguments

x	Output of QMMRecalibrate function.

Details

Plot contains conditional PD (probability of default) values:

before re-calibration (sample Central Tendency and AR (accuracy ratio));

after re-calibration (target Central Tendency and AR);

upper confidence interval PDs (target Central Tendency and target AR minus one standard deviation of sample AR);

lower confidence interval PDs (target Central Tendency and target AR plus one standard deviation of sample AR).

Value

Plot of conditional PDs.

Note

In case rating.type is 'RATING', PD plot is produced against unconditional cumulative portfolio distribution.
In case rating.type is 'SCORE', PD plot is produced against scores.

Author(s)

Denis Surzhko <[e-mail]>

References

Tasche, D. (2009) Estimating discriminatory power and PD curves when the number of defaults is small. Working paper, Lloyds Banking Group.
Tasche, D. (2013) The art of probability-of-default curve calibration. Journal of Credit Risk, 9:63-103.

See Also

QMMRecalibrate

Examples

pd <- c(0.2, 0.1, 0.005, 0.001, 0.001)
porfolio <- c(100, 200, 200, 200, 100)
qmm <- QMMRecalibrate(0.05, pd, porfolio, rating.type = 'RATING')
QMMPlot(qmm)

Example output

LDPD documentation built on May 1, 2019, 7:56 p.m.