For deterministic square-integrable and a Poisson random measure of intensity , first define the integral for simple functions on disjoint finite-intensity sets. Independence and the equality of Poisson distribution mean and variance prove the displayed isometry. Completion defines the integral for all , even when . A small-jump compensated martingale is thereby defined through convergence in Lp, not by subtracting two divergent ordinary integrals.
Lp martingale convergence theorem Created 2026-10-05 Updated 2026-10-14
A martingale satisfying , for , has almost sure convergence and convergence in Lp to a limit . Also . The Doob Lp maximal inequality makes integrable to the power ; the martingale convergence theorem gives the almost-sure limit, and the dominated convergence theorem gives convergence in the Lp norm. Boundedness in alone does not imply convergence in L1.
The uniformly integrable martingale convergence theorem states that a uniformly integrable martingale has an integrable terminal random variable such that almost surely and in the L1 norm, and
The last identity follows by passing to the limit of a sequence in for and , using convergence in L1.
Part (b)(iii) verifies uniform integrability for , so
Moreover almost surely. In this particular problem the common bound also yields convergence in Lp for every finite , including convergence in L2: the dominated convergence theorem applies to . General uniform integrability alone does not assert these higher-power conclusions.