how to simulate a time series

Dear useRs,

I want to simulate a time series (stationary; the distribution of
values is skewed to the right; quite a few ARMA absolute standardized
residuals above 2 - about 8% of them). Is this the right way to do it?
#--------------------------------
load("rdtb")	#the time series

summary(rdtb)

   Min.  1st Qu.   Median     Mean  3rd Qu.     Max.
-1.11800 -0.65010 -0.09091  0.30390  1.12500  2.67600

farma <- arima(rdtb,order=c(1,0,1),include.mean=T)

farma[["coef"]]

      ar1        ma1  intercept
0.58091575 0.02313803 0.30417062

sim <- list(NULL)	#simulated
for (i in 1:5) {
	sim[[i]] <- as.vector(arima.sim(list(ar=c(farma[["coef"]][1]),
		ma=c(farma[["coef"]][2])),n=length(rdtb),innov=rdtb))
	}
allsim <- as.data.frame(sim)
colnames(allsim) <- paste("sim",1:5,sep="")
all <- cbind(rdtb,allsim)
#--------------------------------

I don't understand why the simulation runs generate virtually identical
values:

all[100:105,]

         rdtb     sim1     sim2     sim3     sim4     sim5
100  2.3863636 1.065661 1.065661 1.065661 1.065661 1.065661
101  1.9318182 2.606093 2.606093 2.606093 2.606093 2.606093
102  2.2954545 3.854074 3.854074 3.854074 3.854074 3.854074
103  2.5882353 4.880240 4.880240 4.880240 4.880240 4.880240
104  2.0227273 4.917622 4.917622 4.917622 4.917622 4.917622
105 -0.1521739 2.751352 2.751352 2.751352 2.751352 2.751352

It appears I may be missing something (very) basic, but don't know
what.