Visualize the dependence between 2 gaussian shocks

This function helps you in visualizing the dependence between 2 gaussian shocks.

esgplotshocks(x, y = NULL)

Arguments

x

an output from simshocks, a list with 2 components.

y

an output from simshocks, a list with 2 components (Optional).

References

H. Wickham (2009), ggplot2: elegant graphics for data analysis. Springer New York.

See also

simshocks

Author

T. Moudiki + some nice blogs :)

Examples

# Number of risk factors
d <- 2

# Number of possible combinations of the risk factors
dd <- d*(d-1)/2

# Family : Gaussian copula 
fam1 <- rep(1,dd)
# Correlation coefficients between the risk factors (d*(d-1)/2)
par0.1 <- 0.1
par0.2 <- -0.9

# Family : Rotated Clayton (180 degrees)
fam2 <- 13
par0.3 <- 2

# Family : Rotated Clayton (90 degrees)
fam3 <- 23
par0.4 <- -2

# number of simulations
nb <- 500

# Simulation of shocks for the d risk factors
s0.par1 <- simshocks(n = nb, horizon = 4, 
family = fam1, par = par0.1)

s0.par2 <- simshocks(n = nb, horizon = 4, 
family = fam1, par = par0.2)

s0.par3 <- simshocks(n = nb, horizon = 4, 
family = fam2, par = par0.3)

s0.par4 <- simshocks(n = nb, horizon = 4, 
family = fam3, par = par0.4)


esgplotshocks(s0.par1, s0.par2)

esgplotshocks(s0.par2, s0.par3)

esgplotshocks(s0.par2, s0.par4)

esgplotshocks(s0.par1, s0.par4)