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Scalar Brownian bridge barrier-crossing probability

Statement

Assume AC. Let h>0, barrier c∈R, and endpoints x,y≥c. For a scalar Brownian bridge Bx,y,h from x to y over [0,h], defined in Scalar Brownian bridge from x to y, P{inf⁡0≤s≤hBsx,y,h≤c}=exp⁡(−2(x−c)(y−c)h). If either endpoint equals c, the event has probability one and the formula gives one. For strict endpoints x,y>c, the event is a genuine interior bridge crossing.

Facts & Assumptions

Given: AC, h>0, a level c, endpoints x,y≥c, and the canonical bridge law.

[F1]

For standard Brownian motion W and a>0, P{sup⁡s≤hWs≥a, Wh≤b}=P{Wh≥2a−b} for every b≤a. Brownian reflection principle

[F2]

The bridge law conditioned at any fixed endpoint is explicitly defined by x+(s/h)(y−x)+Ws−(s/h)Wh, and its restriction to [0,t], t<h, has density ph−t(y−Xt)/ph(y−x) relative to Brownian motion from x. Scalar Brownian bridge from x to y Endpoint law and restriction density of a scalar Brownian bridge

[F3]

The endpoint density is ph(z)=(2πh)−1/2exp⁡(−z2/(2h)), continuous and strictly positive for h>0. The Brownian kernels form a semigroup

[A1]

AC is inherited from the Brownian reflection and conditional-law interfaces [F1]–[F2]; no selection is made in the density argument. The Axiom of Choice

Proof

1.1F2givenalgebra

First assume x,y>c, put a=x−c>0, z=x−y, and let Wz denote the canonical bridge from 0 to z over duration h. The bridge event in the Statement has the law of {sup⁡s≤hWsz≥a}: subtracting the bridge path from x negates its centered Gaussian residual and has terminal value z. Since z=a−(y−c)<a, the restriction and endpoint-disintegration statement [F2] applies to this endpoint.

1.2F1F2F3algebra

Write q(z)=P{sup⁡s≤hWsz≥a}. From [F1], for u<v<a, P{sup⁡s≤hWs≥a, u<Wh≤v}=∫uvph(2a−r)dr. Indeed, subtract the reflection identities at v and u and change variables in the Gaussian endpoint integral [F3]. The full endpoint disintegration [F2] then identifies q(r)ph(r)=ph(2a−r) for Lebesgue-almost every r<a.

2.1F1F2F3step 1.1given

The function q is continuous on (−∞,a). Under the explicit bridge representation, changing endpoint from r to r′ changes the path uniformly by at most ∣r−r′∣. Thus the crossing indicators converge almost surely as r′→r unless the bridge maximum equals a. For fixed r<a, if that maximum equals a, it is attained before h; hence for some tk=h(1−1/k)<h the bridge maximum on [0,tk] equals a. By the restriction density in [F2], this event has probability zero because the Brownian maximum on [0,tk] has a continuous distribution by the reflection identity [F1] and the continuous Gaussian density [F3]. The countable union over k≥2 is null. Dominated convergence (Dominated convergence) applies with the integrable constant majorant 1 and proves continuity of q.

3.1F3step 1.2step 2.1algebra

Both q(r)ph(r) and ph(2a−r) are continuous on r<a. Step 1.2 shows they agree almost everywhere there; if their difference were nonzero at one point, continuity would make it nonzero on an interval of positive Lebesgue measure, a contradiction. Hence q(z)=ph(2a−z)ph(z) for the specified endpoint z<a. Since 2a−z=(x−c)+(y−c) and z=(x−c)−(y−c), the Gaussian density ratio is exp⁡(−((x−c)+(y−c))2−((x−c)−(y−c))22h)=exp⁡(−2(x−c)(y−c)h).

4.1A1step 3.1given∎

If x=c or y=c, the bridge begins or ends at the barrier, so the event in the Statement is certain and the right side is e0=1. These boundary cases complete the claim for x,y≥c. The strict case used z<a, which follows exactly from y>c; no formula is asserted when an endpoint lies below the barrier. AC is used only through [A1].

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