Throughout, the stopping-time toolkit is cited by claim number, Dn={kT2−n:k∈{0,…,2n}} is the n-th dyadic grid, and σn,τn are the dyadic approximations from above of σ,τ (toolkit, claim 3). A real-valued function on Ω is called G-measurable, for a σ-algebra G⊆F, when it is measurable with respect to G and the Borel σ-algebra of the real line. Every random variable U with ∣U∣≤C everywhere is square-integrable (E[U2]≤C2 by monotonicity of the integral), hence integrable; this is used without further comment for all the bounded random variables below.
Step 0: two forms of right-continuity. Let ω∈Ω be a point at which the path t↦Mt(ω) is right-continuous at every t∈[0,T) in the sense of the hypothesis (in particular, any ω∈Ω0). The path is then right-continuous in the sequential sense of the toolkit: let t∈[0,T] and let (sj) be a sequence in [t,T] converging to t. If t=T then sj=T for all j and there is nothing to prove. If t<T, given ε>0 choose η>0 from the hypothesis; for all large j we have t≤sj≤min(t+η,T), hence ∣Msj(ω)−Mt(ω)∣≤ε. Conversely, if a path is right-continuous in the sequential sense at every point of [0,T], it is right-continuous at every t∈[0,T) in the sense of the hypothesis: otherwise there would be t∈[0,T), ε>0 and, for each j∈N, a point sj∈[t,min(t+1/j,T)] with ∣Msj(ω)−Mt(ω)∣>ε, contradicting the sequential form along (sj).
Step 1: measurability and convergence of the dyadic samples (claim (a)). Since the pair σ≤τ in the statement is arbitrary, whatever is proved below for τ (respectively for the pair σ≤τ) holds for every stopping time ρ (respectively every pair ρ≤ρ′) of (Ft)t∈[0,T]; claims (a) and (b) are used in that generality in Step 4. Fix n. At every ω exactly one of the sets {τn=d}, d∈Dn, contains ω, so pointwise
Mτn=d∈Dn∑Md1{τn=d}.
Each {τn=d} lies in Fd⊆FT (toolkit, claim 1) and each Md is Fd-measurable, so Mτn is an FT-measurable random variable by claims 1--3 of the arithmetic lemma for measurable functions, with ∣Mτn∣≤K. For ω∈Ω0, (τn(ω))n is a sequence in [τ(ω),T] converging to τ(ω) (toolkit, claim 3), so Step 0 gives Mτn(ω)→Mτ(ω). Hence Mτn1Ω0→Mτ1Ω0 at every point of Ω (both sides vanish off Ω0), and the limit is a random variable on (Ω,F,P) by claim 5 of the arithmetic lemma (1Ω0 being F-measurable as Ω0∈F), bounded by K. The same applies to σ. If every path of M is right-continuous at every t∈[0,T), then by Step 0 every path is right-continuous in the sequential sense, M is adapted, so M is progressively measurable by claim 2 of the progressive measurability toolkit, and Mτ is Fτ-measurable by claim 4(ii) of the stopping-time toolkit. This proves (a).
Step 2: optional stopping on the dyadic grid. Fix n and list Dn as t0<t1<⋯<t2n. By toolkit claim 3, σn≤τn pointwise. For every ω, with σn(ω)=ti and τn(ω)=ti′, i≤i′, the indicator of {σn≤tk}∩{τn>tk} at ω equals 1 exactly for i≤k≤i′−1, so the telescoping identity
Mτn−Mσn=k=0∑2n−1(Mtk+1−Mtk)1{σn≤tk}1{τn>tk}
holds pointwise (an empty sum when i=i′). Let D∈Fσ. Since σ≤σn, toolkit claim 3 gives D∈Fσn, so D∩{σn≤tk}∈Ftk by the definition of the prior σ-algebra; and {τn>tk}∈Ftk by toolkit claim 1. Hence Ak=D∩{σn≤tk}∩{τn>tk}∈Ftk, and the martingale property in averaged form of the martingale definition, for the times tk≤tk+1, gives E[Mtk+11Ak]=E[Mtk1Ak]. Multiplying the telescoping identity by 1D, taking expectations (all terms are bounded random variables) and using linearity of the integral,
E[(Mτn−Mσn)1D]=k=0∑2n−1(E[Mtk+11Ak]−E[Mtk1Ak])=0.
Step 3: passage to the limit (claim (b)). Put gn=(Mτn−Mσn)1D and fn=gn1Ω0. Both are random variables bounded by 2K everywhere and agree on Ω0, so E[fn]=E[gn]=0 by claim 2 of the lemma on almost sure equality of bounded random variables and Step 2. By Step 1, fn→f=(Mτ−Mσ)1Ω01D at every point of Ω, and ∣fn∣≤2K with the constant 2K integrable on the probability space. The dominated convergence theorem yields E[f]=limnE[fn]=0, which by linearity is the identity of (b). For the particular case take σ to be the constant 0 (a stopping time with σ≤τ, toolkit claim 1) and D=Ω, which lies in Fσ=F0 by toolkit claim 2: then E[Mτ1Ω0]=E[M01Ω0]=E[M0], the last equality again by claim 2 of the almost-sure-equality lemma. Finally, suppose every path of M is right-continuous at every t∈[0,T). By Step 1, Mσ is Fσ-measurable and Mτ is a random variable, both bounded by K, hence square-integrable; and for D∈Fσ,
E[Mτ1D]=E[Mτ1Ω01D]=E[Mσ1Ω01D]=E[Mσ1D],
the outer equalities by the almost-sure-equality lemma and the middle one by (b). These are conditions (i)--(iii) of the definition of conditional expectation, so Mσ is a conditional expectation of Mτ given Fσ.
Step 4: the stopped process (claim (c)). Claims (a) and (b) are used here for arbitrary stopping times, as justified at the start of Step 1. Fix 0≤s≤t≤T and D∈Fs. Put σ′=min(s,τ) and τ′=min(t,τ), stopping times by toolkit claim 1 with σ′≤τ′ pointwise, so that Msτ=Mσ′ and Mtτ=Mτ′. By Step 1 applied to σ′ and τ′, both Mσ′1Ω0 and Mτ′1Ω0 are random variables bounded by K. Split D into E1=D∩{τ≤s} and E2=D∩{τ>s}; both lie in Fs ({τ≤s} by the definition of a stopping time, {τ>s} by toolkit claim 1), so 1E1 and 1E2 are random variables and 1D=1E1+1E2. On E1 we have min(t,τ)=τ=min(s,τ), so Mτ′1Ω01E1=Mσ′1Ω01E1 pointwise. By the splitting assertion of toolkit claim 2, E2∈Fσ′, so claim (b) applied to the stopping times σ′≤τ′ and the event E2 gives E[Mτ′1Ω01E2]=E[Mσ′1Ω01E2]. Adding the two contributions by linearity of the integral yields the identity of (c).
Suppose finally that every path of M is right-continuous at every t∈[0,T). As in Step 1, M is progressively measurable, so Mτ is adapted by toolkit claim 4(i); ∣Mtτ(ω)∣=∣Mmin(t,τ(ω))(ω)∣≤K for all t,ω, so each Mtτ is square-integrable; and for s≤t and D∈Fs the identity of (c) together with claim 2 of the almost-sure-equality lemma (applied on each side to remove the factor 1Ω0) gives E[Mtτ1D]=E[Msτ1D], the martingale property in averaged form. Thus Mτ is a square-integrable martingale with respect to (Ft)t∈[0,T], with time index restricted to [0,T]. By Step 0 every path of M is right-continuous in the sequential sense, so by toolkit claim 4(iii) every path of Mτ is right-continuous in the sequential sense, hence, by the converse direction of Step 0, right-continuous at every t∈[0,T) in the sense of the hypothesis. ■