When you generate random data, you will NEVER be able to know the EXACT correlation coefficient. The data was composed of random numbers. Perhaps a related example will help.
What is the mean of a uniform random variable, sampled from the interval [0,1]? We know this of course to be 0.5. But try it?
n = 1e6;
x = rand(1,n);
mean(x)
ans =
0.50032
x = rand(1,n);
mean(x)
ans =
0.50006
x = rand(1,n);
mean(x)
ans =
0.4997
Hmm. I got a different number each time, and none of them were the expected value of 0.5. Close, but not exactly so.
In fact, statistics 101 will teach us that as the sample size increases, the mean will in fact approach the known expected value, but we will never expect an exact result. The sample correlation coefficient taken from data has the same property. It will be an estimate of that parameter, but it will generally never be the true value, that one could compute using theory. As well, the value we get will vary, due to the randomness of the sample. This is all exactly as we expect.
