I encountered the following problem.
$\{x_t\}$: Markov chain in discrete time;
$\Omega$: a finite state space s.t. $|\Omega|=n<\infty$;
$\tau_w\equiv\min\{t\ge 0\,|\,x_t=w\}$, $w\in\Omega$ (first hitting time).
Prove: For each $T\ge 1$ and every $x,y\in \Omega$ $$\Pr(\tau_y=T|x_0=x)\le\frac nT.$$
Effort: This is a surprising result as the setup is terribly general. I proceeded by induction. Using recursive characterization, we have $$\Pr(\tau_y=T+1|x_0=x)=\sum_{z\ne y}\Pr(\tau_y=T|x_0=z)p(x,z),$$ where $p(x,z)=\Pr(x_{t+1}=x|x_t=z)$ is the transition probability. For each Markov chain, using the inductive hypothesis, we can easily confirm that this holds for $T$ sufficiently large. So far I cannot see how to show this for a general $T\ge n+1$.
Any hints or comments will be highly appreciated!
Edit: this is wrong.
This seems incorrect. Multiplying both sides by T and summing over T we get $ E( \tau _y | x_0 =x) \leq n $. I don't see why this should be true in general.