Vectorizing nested ifelse

I'm trying to fasten my function in R. It contains of three ifelse statements where one of it is nested. For the single one I conducted vectorization which reduced my computation time. Unfortunately I don't see how I can vectorize the nested one. Every way I apply it returns an error. Furthemore if there is any another quirk I can use to speed it up?

cont.run <- function(reps=10000, n=10000, d=0.005, l=10 ,s=0.1) {
  r <- rep(0, reps)
  theta <- rep(0, n)
  for (t in 1:reps) {
    epsilon <- rnorm(1, 0, d)
    Zt = sum(ifelse(epsilon > theta, 1, 
                ifelse(epsilon < -theta, -1, 0)))
    r[t] <- Zt / (l * n)
    theta <- ifelse(runif(n) < s, abs(r[t]), theta)
  }
  return(mean(r))
}

system.time(cont.run())

I got:

cont.run <- function(reps=10000, n=10000, d=0.005, l=10 ,s=0.1) {
  r <- rep(0, reps)
  theta <- rep(0, n)
  for (t in 1:reps) {
    epsilon <- rnorm(1, 0, d)
    Zt = rep(NA, length(theta))
    Zt = sum(Zt[epsilon > theta, 1])
    Zt = sum(Zt[epsilon < -theta, -1])
    r[t] <- Zt / (l * n)
    theta = rep(theta, length(s))
    theta[runif(n)  < s] = abs(r[t])  
  }
  return(mean(r))
}

system.time(cont.run())