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In that sense, David Williams’ book doesn’t give you answers. It gives you a pair of glasses through which random processes reveal their fair-game essence. And once you see that, every problem’s solution becomes a small act of discovery — not a computation, but a proof that the world, properly conditioned, plays fair.
The best solution here is not the slickest formula, but the one that explicitly verifies the conditions. Williams trains you to treat optional stopping as a precision instrument: check bounded stopping time, or bounded increments + finite expectation, or uniform integrability. Otherwise, you get nonsense (e.g., predicting ( \mathbbE[X_T] = 0 ) when ( T ) is the time to hit ±1 starting from 0 — which is false because ( T=1 ) almost surely? Wait, that’s a trap — actually for symmetric RW starting at 0, ( T ) to hit ±1 has ( \mathbbE[X_T]=0 ) because ( X_T ) is symmetric. Williams loves these subtle checks.)