Let (Ω,F,(Ft)t≥0,P) be a filtered probability space, let n be zero or a natural number, and let 0≤t0<t1<⋯<tn be real numbers.
1. Let M=(Mt)t≥0 be a square-integrable submartingale with Mt(ω)≥0 for every t≥0 and every ω∈Ω, and let M∗(ω)=max0≤k≤nMtk(ω) be the running maximum, a square-integrable random variable by Doob's maximal inequality. Then
E[(M∗)2]≤4E[Mtn2].
2. Let M=(Mt)t≥0 be a square-integrable martingale and define pointwise
M(ω)=0≤k≤nmax∣Mtk(ω)∣(ω∈Ω).
Then M is a square-integrable random variable and
E[M2]≤4E[Mtn2].