Ifelse leading to inconsistent result

I have used ifelse in count variables to count the number of times in a simulation the values of a vector of logprice fall within mutually exclusive ranges. However, there is a double count in the result i.e. i am getting output indicating values falling in mutually exclusive ranges. Here is the code and result
R script

niter = 1e5 # number of iterations is 10^5
CountLoss = rep(0,niter)
CountProf = rep (0,niter)
set.seed(2009) # enables reproducibility of result if script run again"
for (i in 1:niter)
{
 r = rnorm(100,mean=.05/253,
           sd=.23/sqrt(253)) # generate 100 random normal numbers
 logPrice = log(1e6) + cumsum(r) #vector of 100 days log prices
 maxlogP = max(logPrice) # max price over next 100 days
 minlogP = min(logPrice)
 CountLoss[i] <- ifelse (minlogP < log(950000), 1, ifelse (maxlogP > log (1000000), 0, 1))
 CountProf[i] <- ifelse (maxlogP < log (1100000),0,1)
}
sum(CountLoss)
mean(CountLoss) # fraction of times out of niter that stock is sold for a loss in a 100 day period
sum(CountProf)
mean(CountProf) # fraction of times out of niter that stock is sold for a profit in a 100 day period

Output
sum(CountLoss)
[1] 64246

mean(CountLoss) # fraction of times out of niter that stock is sold for a loss in a 100 day period

[1] 0.64246

sum(CountProf)

[1] 51857

mean(CountProf) # fraction of times out of niter that stock is sold for a profit in a 100 day period

[1] 0.51857

CountLoss and CountProf should sum to less than the number of interations. When I troubleshoot by reducing the number of iterations and that size of the logprice, I can't reproduce the contradicion.