| cm.ref {CreditMetrics} | R Documentation |
cm.ref computes the value of a credit in one year for each rating, this is
the return value constVal. Further the portfolio value at time t = 1 is
computed, this is constPV.
cm.ref(M, lgd, ead, r, rating)
M |
one year empirical migration matrix, where the last row gives the default class. |
lgd |
loss given default |
ead |
exposure at default |
r |
riskless interest rate |
rating |
rating of companies |
This function computes the value of the credit in one year, this is
V_t = EAD_t e^{-(r_t + CS_t) t}
where t = 1.
a list containing following components:
constVal |
credit value in one year |
constPV |
portfolio of all credit values in one year |
Andreas Wittmann andreas_wittmann@gmx.de
Glasserman, Paul, Monte Carlo Methods in Financial Engineering, Springer 2004
r <- 0.03
ead <- c(4000000, 1000000, 10000000)
rating <- c("BBB", "AA", "B")
lgd <- 0.45
# one year empirical migration matrix form standard&poors website
rc <- c("AAA", "AA", "A", "BBB", "BB", "B", "CCC", "D")
M <- matrix(c(90.81, 8.33, 0.68, 0.06, 0.08, 0.02, 0.01, 0.01,
0.70, 90.65, 7.79, 0.64, 0.06, 0.13, 0.02, 0.01,
0.09, 2.27, 91.05, 5.52, 0.74, 0.26, 0.01, 0.06,
0.02, 0.33, 5.95, 85.93, 5.30, 1.17, 1.12, 0.18,
0.03, 0.14, 0.67, 7.73, 80.53, 8.84, 1.00, 1.06,
0.01, 0.11, 0.24, 0.43, 6.48, 83.46, 4.07, 5.20,
0.21, 0, 0.22, 1.30, 2.38, 11.24, 64.86, 19.79,
0, 0, 0, 0, 0, 0, 0, 100
)/100, 8, 8, dimnames = list(rc, rc), byrow = TRUE)
cm.ref(M, lgd, ead, r, rating)