Bounding the variance of a stopping time

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Please refer to the exact same setting of this question:

Durret problem 4.8.3 - Random walk and optional sampling theorem application

I repeat the setting here in any case:

Let $S_n = \xi_1+\ldots+\xi_n$, $(\xi_i)_i$ independent with $0$ mean and $Var(\xi_i)=\sigma^2$. Then $S^2_n−n\sigma^2$ is a martingale. Let consider the stopping time $T=\inf \{n:|S_n|>a\}$.

Show $\mathbb{E}[T]>\frac{a^2}{\sigma^2}$.

Is there an expression that corresponds to $Var(T)$? Or at least an upper bound for $Var(T)$?

For example, if we are dealing with a symmetric simple random walk, then we can get an expression for $Var(T)$. See for example:

Stopping time computations via martingales

What about the more general case stated in the first link? I have tried to follow a similar approach, trying to come up with some clever martingale and apply the optional stopping theorem, but so far to no avail.

Thanks!