I will give a brief answer, you can find the full solution there (along with additional stuff). In what follows I will use $n$ for the sake of generality (you will see that it does not matter a lot actually), but in the case of a deck of card, you can replace it by 52 everywhere.
If we assume that your shuffling algorithm amounts to selecting one permutation at random, we need to count permutations. There are $n!$ permutations of the deck. The number of derangements (permutations where no card ends up in the same position) is
$$ n!\sum_{i=0}^n\frac{(-1)^i}{i!}.$$
The number of permutations where exactly $k$ cards end up at the same position is the product of the number of derangements of $n-k$ cards and the number of ways of choosing $k$ cards among $n$:
$$ {n \choose k} (n-k)! \sum_{i=0}^{n-k}\frac{(-1)^i}{i!}.$$
Finally, the probability of such a permutation is
$$ \frac{1}{k!} \sum_{i=0}^{n-k}\frac{(-1)^i}{i!} \approx \frac{e^{-1}}{k!}.$$
In the last approximation, we used the first terms of the series development of $e^x$. Interestingly, we recognize the Poisson distribution with parameter $\lambda = 1$, and we see that this approximation does not depend on $n$. So the distribution of the number of fixed cards (not their proportion) rapidly converges to a constant distribution.