The Strong Markov property says that for every almost surely finite stopping time , the process is a standard Brownian motion independent of .
The process is centered Gaussian and continuous. Its covariance is
as follows by expanding Brownian covariances, or by reading its increments backwards. The Gaussian-process characterization of Brownian motion therefore shows that has the same law as .
The event is the event that for every . By part (ii), its probability equals the probability that Brownian motion started at zero remains nonnegative throughout . The Brownian reflection principle implies . Hence .
Continuity gives existence of a minimizer. If there were two, choose a rational strictly between them. Then the minima on and would coincide. Conditional on , the latter equals plus the minimum of an independent Brownian motion on , whose distribution is continuous by the Brownian reflection principle. Thus equality has conditional probability zero. Taking the countable union over rational proves almost-sure uniqueness.
Almost surely, Brownian motion has a unique minimizer on every interval with rational endpoints, by rescaling part (iv). Every local minimum is the minimum on some rational interval contained in a witnessing neighbourhood. Each rational interval contributes at most one point, and there are countably many such intervals. The set of local minima is therefore countable.
The function is harmonic on the annulus . Hence is a bounded martingale by Itô formula. Optional stopping gives
Solving yields
For fixed , part (i), translated by , and then show that planar Brownian motion has probability zero of ever hitting before leaving any fixed large disk. Letting the disk radius tend to infinity shows . By Tonelli theorem,
The nonnegative random area is therefore zero almost surely.

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