cm.state {CreditMetrics} | R Documentation |
cm.state
computes a state space, this is at time t = 1 the credit positions
of all companies for all migrations is calculated. This state space is needed for
the later valuation for the credit positions of each scenario.
cm.state(M, lgd, ead, N, r)
M |
one year empirical migration matrix, where the last row gives the default class. |
lgd |
loss given default |
ead |
exposure at default |
N |
number of companies |
r |
riskless interest rate |
This function computes the value of the credits of each firm in one year, this is
V_t = EAD_t e^{-(r_t + CS_t) t}
where t = 1. Also the value for the default class is calculated, that is
V_t = EAD (1 - LGD)
Return value is the matrix V
for time t = 1 of each rating in the migration
matrix including the credit values for all companies. The last column in the matrix
V
is the value for the default event of each company.
Andreas Wittmann andreas_wittmann@gmx.de
Glasserman, Paul, Monte Carlo Methods in Financial Engineering, Springer 2004
N <- 3 r <- 0.03 ead <- c(4000000, 1000000, 10000000) 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.state(M, lgd, ead, N, r)