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I am wondering if anyone can provide me links or idea about how i can calculate stochastic npv after monte carlo simulation and how i can calculate probability of npv>0? We first calculated deterministic npv with all the assumptions and then I took some important parameters where I can assign uncertainty and then assigned them uniform distribution (runif). But the probability of positive npv seems to be 0/1, nowhere in between, Is there something wrong with how i am calculating probability of positive npv?or how i am calculating npv_vec[i]?

...

a<- runif(100,10,20)
b<- runif(100,20,30)
npv_vec <- rep(NA,ndraw)
profit_vec <- rep(NA,ndraw)


for(i in 1:ndraw) {
  npv_vec[i] <- NPV_fun(a_vec[i],b_vec[i])
  profit_vec[i] <- ifelse(npv_vec[i]>0,1,0)
}


# calculate the probability of positive npv
pb_profit <- mean(profit_vec)
pb_profit

...

Muhammad Ibrahim Shah
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1 Answers1

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On a single flip of a coin, it comes up either heads or tails. This does not mean that the probability of heads is either 0 or 1. To estimate that probability you have to perform multiple trials of the coin flip, and determine the proportion of flips which are heads.

Similarly, the probability of NPV>0 is 0 or 1 with no chance of anything in between. As with coin flips, you determine the probability based on multiple trials and calculating the proportion of trials which had NPV>0.

pjs
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