For standard Brownian motion and deterministic , the process , , is standard Brownian motion on that interval in its own natural filtration. Disjoint reversed time intervals give independent centered normal increments with the correct variances. This is different from an arbitrary random-time shift, which can depend on future data. It is also different from the time inversion of Brownian motion transformation .
For every finite collection of positive times, is a linear transformation of the corresponding values of , so is a centered Gaussian process. If , then
Thus has the covariance of Brownian motion.
Its paths are continuous for . As , put . The given almost-sure limit gives
The Gaussian-process characterization of Brownian motion now proves the time inversion of Brownian motion:
Use the time-inverted Brownian motion . For , set . Then
As corresponds exactly to , and the inequality at is automatic because , this is the pathwise identity
Since and have the same law by time inversion of Brownian motion,
For positive times the transformed process is centered and jointly Gaussian, and
Its paths are continuous away from zero. To verify continuity at zero, we need almost surely as . The strong law of large numbers applied to the independent increments gives . On the unit interval after , the Doob L2 maximal inequality gives
The Borel-Cantelli first lemma, first for each positive rational , shows that these between-integer fluctuations divided by tend to zero. Hence for all real , and as .
The Gaussian-process characterization of Brownian motion now proves is standard Brownian motion, with respect to its natural filtration. This is time inversion of Brownian motion; the transformed process need not be adapted to the original forward filtration.