PTMultiPeriodPD: Multi-period Pluto and Tasche Model

In LDPD: Probability of Default Calibration

Description

Estimates probability of default (PD) according to Multi-period Pluto & Tasche model.

Usage

PTMultiPeriodPD(portf.uncond, portf.def, rho, cor.St, kT, kNS = 1000, conf.interval = 0.9)

Arguments

portf.uncond	Unconditional portfolio distribution (e.g. number of counterparts by rating classes).
portf.def	Number of defaults by rating classes.
rho	Correlation with systematic factor.
cor.St	Correlation matrix of systematic factor realization through the time. In case constant is given - power matrix is used: Correlation matrix (i, j) = cor.St ^ |s - t|, s = 1..kT, t = 1..kT.
kT	Number of periods used in the PD estimation.
kNS	Number of simulations for integral estimation (using Monte-Carlo approach).
conf.interval	Confidence interval for PD estimation.

Details

Estimates probabilities of default according to multi-period Pluto and Tasche model (additionally captures the inter-temporal correlation effects).

Value

Conditional PDs according to Multi-period Pluto and Tasche model

Note

Portfolio and default data should be sorted by rating classes from lowest credit quality to higher one.

Author(s)

Denis Surzhko <[e-mail]>

References

Pluto, K. and Tasche, D., 2005. Thinking Positively. Risk, August, 72-78.

See Also

PTOnePeriodPD

Examples

portfolio <- c(10,20,30,40,10)
defaults <- c(1,2,0,0,0)
PTMultiPeriodPD(portfolio, defaults, 0.3, cor.St = 0.3, kT = 5, kNS = 1000, conf.interval = 0.5)

Example output

[1] 0.04284042 0.03299894 0.01780414 0.01146315 0.01053244

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