CreditMetrics (version 0.0-2)

cm.gain: Computation of simulated profits and losses

Description

cm.gain computes profits or losses, this is done by building the difference from the reference value and the simulated portfolio values of the credit positions.

Usage

cm.gain(M, lgd, ead, N, n, r, rho, rating)

Arguments

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

n

number of simulated random numbers

r

riskless interest rate

rho

correlation matrix

rating

rating of companies

Value

This functions returns simulated profits or losses.

Details

This function uses cm.portfolio and cm.ref. By building the difference of these functions, one gets the profits, if the difference is positive, or the losses, if the difference is negative.

References

Glasserman, Paul, Monte Carlo Methods in Financial Engineering, Springer 2004

See Also

cm.matrix, cm.ref, cm.portfolio

Examples

  N <- 3
  n <- 50000
  r <- 0.03
  ead <- c(4000000, 1000000, 10000000)
  lgd <- 0.45
  rating <- c("BBB", "AA", "B")
  firmnames <- c("firm 1", "firm 2", "firm 3")
  
  # correlation matrix
  rho <- matrix(c(  1, 0.4, 0.6,
                  0.4,   1, 0.5,
                  0.6, 0.5,   1), 3, 3, dimnames = list(firmnames, firmnames),
                  byrow = TRUE)

  # one year empirical migration matrix from 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.gain(M, lgd, ead, N, n, r, rho, rating)