[R-sig-Finance] MC simulation
Jens Wildermuth
Jens.Wildermuth at gmx.de
Thu Jun 22 11:03:56 CEST 2006
Hi,
I am pretty new to R. However, I checked the introduction to R paper and did not find a solution for my problem. I use a mean reversion process to simulate US RMBS spreads for different rating classes. My problem is that for each MC run I would like to generate a vector and attach these vectors with each other to generate a matrix, which contains all the simulation results. Right now I just see the results of every simulation run because I plot them. I tried something using the print(x) (as.matrix() and so forth) command but I didn't work out properly. I would very much appreciate any help on that problem. Thanks in advance.
Cheers
Jens
#Set up variables
AAA<-data$AAA
AA<-data$AA
A<-data$A
BBB<-data$BBB
logAAA<-log(AAA)
logAA<-log(AA)
logA<-log(A)
logBBB<-log(BBB)
diffAAA<-logAAA[1:100]-logAAA[2:101]
diffAA<-logAA[1:100]-logAA[2:101]
diffA<-logA[1:100]-logA[2:101]
diffBBB<-logBBB[1:100]-logBBB[2:101]
#Estimate coefficients by OLS
regAAA<-lm(diffAAA ~ logAAA[2:101])
#Parameters for O-U process
nü<--log(1+regAAA$coefficients[2])
averagex<--(regAAA$coefficients[1]/regAAA$coefficients[2])
resierror<-sqrt(var(regAAA$residuals)) #check this
sigma<-resierror*sqrt((2*log(1+regAAA$coefficients[2]))/((1+regAAA$coefficients[2])^2-1))
lAAA<-length(diffAAA)
x<-logAAA[lAAA]
t<-c(1:60)
delta<-1
mcsim<-40
par(mfrow=c(4,1))
#MC for AAA
for ( k in 1:mcsim ){
rn<-rnorm(length(t), mean=0,sd=1)
for ( i in 1:length(t) ){
x[t+1]<-x[t]*exp(-nü*delta*t)+averagex*(1-exp(-nü*delta*t))+sigma*sqrt((1-exp(-2*nü*delta*t))/(2*nü))*rn[t]
}
vect<-c(logAAA,x[2:length(x)])
plot.ts(exp(vect), plot.type = c("single"),col="red",type="l")
lines(AAA)
}
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