@Agrasar. I think I got the solution. Going with the definition of expectation,
if s={x_{1},x_{2}.........,x_{n}} is the sample space then,
E(X^{2}) = $\sum_{r\epsilon s}^{}$ X(r=s)^{2}.P(r) ..................(1)
E(X) = $\sum_{r\epsilon s}^{}$ X(r=s).P(r) ..................(2)
Now, (1) and (2) are both equal which implies X(r=s)^{2}=X(r=s) ..................(3)
Now, lets consider what value we get for E(X^{3}).
E(X^{3})
= $\sum_{r\epsilon s}^{}$ X(r=s)^{3}.P(r)
= $\sum_{r\epsilon s}^{}$ X(r=s)^{2}. X(r=s)^{ }.P(r)
= $\sum_{r\epsilon s}^{}$ X(r=s). X(r=s)^{ }.P(r) .................from (3)
= E(X^{2})
=1
Similarly, we can go on computing for E(X^{100}).
Thus, I think, E(X^{100}) = 1