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Scalar Brownian bridge barrier-crossing probability
Statement
Assume AC. Let , barrier , and endpoints . For a scalar Brownian bridge from to over , defined in Scalar Brownian bridge from x to y, If either endpoint equals , the event has probability one and the formula gives one. For strict endpoints , the event is a genuine interior bridge crossing.
Facts & Assumptions
Given: AC, , a level , endpoints , and the canonical bridge law.
For standard Brownian motion and , for every . Brownian reflection principle
The bridge law conditioned at any fixed endpoint is explicitly defined by , and its restriction to , , has density relative to Brownian motion from . Scalar Brownian bridge from x to y Endpoint law and restriction density of a scalar Brownian bridge
The endpoint density is , continuous and strictly positive for . The Brownian kernels form a semigroup
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
First assume , put , , and let denote the canonical bridge from to over duration . The bridge event in the Statement has the law of : subtracting the bridge path from negates its centered Gaussian residual and has terminal value . Since , the restriction and endpoint-disintegration statement [F2] applies to this endpoint.
Write . From [F1], for , Indeed, subtract the reflection identities at and and change variables in the Gaussian endpoint integral [F3]. The full endpoint disintegration [F2] then identifies for Lebesgue-almost every .
The function is continuous on . Under the explicit bridge representation, changing endpoint from to changes the path uniformly by at most . Thus the crossing indicators converge almost surely as unless the bridge maximum equals . For fixed , if that maximum equals , it is attained before ; hence for some the bridge maximum on equals . By the restriction density in [F2], this event has probability zero because the Brownian maximum on has a continuous distribution by the reflection identity [F1] and the continuous Gaussian density [F3]. The countable union over is null. Dominated convergence (Dominated convergence) applies with the integrable constant majorant and proves continuity of .
Both and are continuous on . 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 for the specified endpoint . Since and , the Gaussian density ratio is
If or , the bridge begins or ends at the barrier, so the event in the Statement is certain and the right side is . These boundary cases complete the claim for . The strict case used , which follows exactly from ; no formula is asserted when an endpoint lies below the barrier. AC is used only through [A1].
Depends on
Used by
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Sources
- Gregory F. Lawler, Stochastic Calculus: An Introduction with Applications, Proposition 2.7.2, pp. 60–61 (standard reference, not scraped)
- Mike Giles, Monte Carlo Methods, Module 4: Monte Carlo path simulation, Brownian bridge barrier crossing, pp. 31–32 (standard reference, not scraped)