Sharp moment estimates for martingales with uniformly bounded square functions

TL;DR

This paper derives precise bounds for exponential and p-moments of martingales with bounded square functions, using Bellman functions and supersolutions to achieve sharp tail estimates.

Contribution

It introduces a novel Bellman function approach for extremal problems related to martingale moments and tail bounds, connecting to BMO space techniques.

Findings

Established sharp exponential and p-moment bounds for martingales

Developed a Bellman function method for extremal problems

Provided sharp tail estimates using supersolutions

Abstract

We provide sharp bounds for the exponential moments and $p$-moments, $1\leqslant p \leqslant 2$, of the terminate distribution of a martingale whose square function is uniformly bounded by one. We introduce a Bellman function for the corresponding extremal problem and reduce it to the already known Bellman function on $\mathrm{BMO}([0,1])$. In the case of tail estimates, a similar reduction does not work exactly, so we come up with a fine supersolution that leads to sharp tail estimates.