Given that $X$ is a non-negative random variable, satisfies $P(X = x) = 0$ and
$P(X > x + y\mid X > x) = P(X > y)$ $ \forall x, y \in \mathbb{R^{+}}$. Prove that $P(X > x) = e^{-\lambda x} $ $\forall x > 0$ and some $\lambda > 0$
By applying the definition of conditional probability, for now I have $P(X > x) = \frac{P(X > x + y)}{P(X > y)}$. I guess we are trying to prove something like $P(X > x) > 0$, but I dont know how to proceed.
If $f(x)=P(X>x)$ then $f(x+y)=f(x)f(y)$ and $f$ is right-continuous. It is well know that the only measurable solutions of this functional equation are of the type $f(x)=e^{cx}$.
Note that $f(x) \leq 1$ which forces $c$ to be $\leq 0$. Since $f(x) \to 0$ as $x \to \infty$, $c$ cannot be $0$. Hence $c <0$. Take $\lambda =-c$.
Sketch of proof of the fact that the solutions of the functional equation are of the type $e^{cx}$: Let $g(x)=\log (f(x))$. Then $g(nx)=ng(x)$. This implies $g(rx)=rg(x)$ for all positive rational numbers $r$. Using right continuity it follows that $g(rx)=rg(x)$ for al $r,x>)$. Put $r=\frac 1 x$ to get $g(1)=\frac {g{(x)}} x$ or $g(x)=cx$ where $c=g(1)$. Hence $f(x)=e^{cx}$.