cm.gain {CreditMetrics}R Documentation

Computation of simulated profits and losses

Description

cm.gain computes the 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

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.

Value

This functions returns the simulated profits or losses.

Author(s)

Andreas Wittmann andreas_wittmann@gmx.de

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

[Package CreditMetrics version 0.0-1 Index]