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Brownian reflection principle

Statement

Assume the Axiom of Choice, let B be a standard Brownian motion Brownian motion. All path operations below use a fixed everywhere-continuous, zero-start representative: choose a measurable probability-one event on which the paths are continuous and B0=0, and replace B by the zero path off this event, as in Wiener measure on continuous path space. Retain the notation B for this representative and use its own raw natural filtration and usual augmentation. This preserves every finite-dimensional law; all maxima and hitting times below refer to this representative, without transferring stopping times between the raw filtrations of different versions. Let a>0 and T>0, and put MT:=sup⁡0≤s≤TBs,τa:=inf⁡{s≥0:Bs=a}. Then:

  1. The path reflected at τa has Wiener law: for each T>0 the process (Bu)0≤u≤T and its reflection B~u:=Bu for u≤τa∧T, B~u:=2a−Bu for τa∧T<u≤T, have the same law on the cylinder sigma-algebra σ(πu:u∈[0,T]) of R[0,T].
  2. For every b≤a, P(MT≥a, BT≤b)=P(BT≥2a−b), and in particular P(MT≥a)=2P(BT≥a).

Facts & Assumptions

Given: AC, a standard Brownian motion B with every path continuous and B0=0 everywhere, real a>0, T>0 and b≤a.

[F1]

τa is a stopping time for the raw natural filtration and hence for the usual augmentation, which is right-continuous; and MT≥a if and only if τa≤T. The combination S:=τa∧T is a stopping time bounded by T. Brownian closed-set hitting times are stopping times Continuous-time stopping times and stopped sigma-algebras Natural and usual augmented Brownian filtrations

[F2]

Strong Markov: for an a.s. finite stopping time τ of the usual augmentation, the shifted increment process (Bτ+t−Bτ)t≥0 is independent of Fτ with the finite-dimensional marginals of Wiener measure; moreover E[Φ((Bτ+t))∣Fτ]=ΨΦ(Bτ) for bounded Borel path functionals Φ. Strong Markov property of Brownian motion

[F3]

Wiener measure is the unique Borel probability on continuous path space whose coordinates are centered Gaussian with covariance min⁡(s,t); hence the map w↦−w preserves Wiener measure, because it preserves every finite-dimensional centered Gaussian law with that covariance. Uniqueness of Wiener measure Wiener measure on continuous path space

[F4]

For each t>0 the law of Bt has the strictly positive density pt(0,⋅), so P(Bt=c)=0 for every c. The Brownian kernels form a semigroup

[F5]

By definition, the cylinder sigma-algebra σ(πu:u∈[0,T]) is generated by finite-coordinate cylinder sets, which form a pi-system; a lambda-system containing that pi-system contains the generated sigma-algebra, and conditional laws agree almost surely when their defining conditional expectations agree. Dynkin's pi-lambda theorem Conditional expectation as an ae class

[F7]

If R is FS-measurable and W is an independent random element with law μ, then for bounded product-measurable h, E[h(R,W)∣FS]=∫h(R,w)μ(dw). The Borel sigma-algebra of continuous path space is generated by coordinates; thus coordinate measurability and cylinder independence imply path-space measurability and independence for an everywhere-continuous random path. Conditioning a known state and independent noise Borel sigma-algebra of continuous path space is generated by coordinates

[F6]

AC supplies the conditional-expectation and strong-Markov interfaces. The Axiom of Choice Strong Markov property of Brownian motion

Proof

technique · direct
1.1F1given

By [F1] the time τa is a stopping time of the usual augmentation and S=τa∧T is a stopping time bounded by the deterministic time T, hence a.s. finite; on the event {τa≤T} one has S=τa and BS=a by continuity, while on {τa>T} one has S=T. Also MT≥a  ⟺  τa≤T by continuity of the path.

1.2F3F5

The law of any finite-dimensional marginal of B is unchanged by the substitution B↦−B, and the cylinder pi-system determines a law on R[0,T]; hence the law of (Bu)u≤T is invariant under negation, and the same holds for every process whose finite-dimensional marginals are those of Brownian motion, by [F5] and [F3].

2.1F1F2F5F7step 1.1step 1.2

Define B~u:=Bu for u≤S and B~u:=2a−Bu for S<u≤T. Every coordinate is measurable by the stopping-time tests. The path is continuous: if S<T, then BS=a, and if S=T it is unchanged. For finitely many ui∈[0,T], put R=(S,Bu1∧S,…,Buk∧S). This is FS-measurable: S is measurable there by its test events, and [F2]'s stopped-value measurability at ui∧S, followed by the stopped-sigma-algebra inclusion for ui∧S≤S, gives the other coordinates. Since paths are everywhere continuous and these times finite, the version convention in [F2] gives the literal values. The path W(r)=BS+r−BS is everywhere continuous, has Wiener law and is independent of FS by [F2], [F7] and coordinate generation. Random evaluation (s,w)↦w((ui−s)+) is measurable: replace its time by the ceiling on the dyadic mesh, use the countable coordinate formula, then pass to the pointwise limit by continuity. Hence the vectors Bui=Bui∧S+W((ui−S)+) and B~ui=Bui∧S−W((ui−S)+) are product-measurable functions of (R,W). These formulas also hold when S=T because W(0)=0. For every bounded Borel test of this vector, [F7] and invariance of Wiener measure under w↦−w from step 1.2 give equal conditional expectations. Thus the finite-dimensional laws agree, and [F5] gives equality on the entire cylinder sigma-algebra.

3.1F1step 1.1step 2.1

On the event {τa≤T}, the reflected path coincides with B on [0,τa], so τa(B~)=τa; moreover B~T=2a−BT there. Hence {τa≤T, BT≤b}={τa(B~)≤T, B~T≥2a−b} as events. These are cylinder-measurable events on the continuous-path representatives: use the rational-distance formula of [F1] for the hit event and the terminal coordinate for the inequality. Thus by step 2.1 the probability equals P(τa≤T, BT≥2a−b). Since b≤a implies 2a−b≥a, the event {BT≥2a−b} is contained in {BT≥a}⊆{τa≤T}, so the last probability is P(BT≥2a−b). Together with MT≥a  ⟺  τa≤T from step 1.1, this is the first identity of assertion 2.

4.1F4step 3.1

Taking b=a in step 3.1 gives P(MT≥a, BT≤a)=P(BT≥a). Since {BT>a}⊆{MT≥a} and {BT>a} differs from {BT≥a} by the null event {BT=a} by [F4], adding P(BT>a)=P(BT≥a) to both sides gives P(MT≥a)=2P(BT≥a), the second identity of assertion 2. Assertion 1 is step 2.1.

5.1F1F4F6givenstep 3.1∎

The endpoint and degenerate cases are covered: the statement requires a>0 and T>0; the value b=a is used in step 4.1 and is the boundary case of the constraint b≤a; the case b<a is step 3.1 unchanged; the case τa>T contributes to neither event in the first probability identity, by the containment in step 3.1; the case τa≤T with equality BT=a is the null event excluded by [F4]. AC is used through [F6] for the strong Markov and conditional-expectation interfaces.

Source notes

Lawler, Proposition 2.7.2, derives the maximum formula from post-hit symmetry and absence of a terminal atom. Here the full reflected-path law is proved by conditioning on the bounded time tau_a wedge T, so the proof needs no prior almost-sure finiteness of tau_a. The measurable continuous-path representative is fixed before forming its filtration and hitting times.

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