Use the standard definition of a local martingale, including an integrable initial value, and let be a localizing sequence. If , the Fatou lemma gives . For , the Conditional Fatou lemma gives
For clarity, the Conditional Fatou lemma itself follows by setting for nonnegative , applying the conditional version of the monotone convergence theorem to , and observing . Hence a nonnegative local martingale is a supermartingale.
If simultaneously for all , with a deterministic , the dominated convergence theorem applied to the stopped martingale identity gives, for each ,
This is exactly the conditional expectation identity, so a bounded local martingale is a true martingale. The same proof works for deterministic bounds on every finite time interval; merely having a finite random pathwise bound supplies no dominating integrable random variable and is a different convention.
Let , with three independent standard Brownian motions, and set and . The radial stochastic process is a three-dimensional Bessel process, which never hits zero by the Hitting-zero classification for a Bessel process. In three dimensions is a harmonic function away from zero: direct differentiation gives .
For the stopping times , , the Itô formula gives
The coefficients are bounded by , so each stopped Itô integral is a true martingale on every finite horizon. The stopping times form a localizing sequence; as permitted, its divergence need not be proved here. Thus is a nonnegative continuous local martingale.
To see that is not a true martingale, integrate the three-dimensional multivariate normal density of in spherical coordinates. The angular integral yields
where is the standard normal distribution function. Therefore the reciprocal of a three-dimensional Bessel process is a strict local martingale.
Put and . The constant-in-time coefficient on is previsible, so the ratio minus is . Since , continuity and the dominated convergence theorem imply
The Itô isometry gives . For , use the Chebyshev inequality and the normal distribution of to obtain
First let , then ; the normal distribution has no atom at zero. This proves
No independence between and the denominator is needed.
The first estimate suggested by the hint is valid: Brownian scaling and the Gamma function give . The second hint requires care about the placement of its expectation: with , the interpretation is correct by the Jensen inequality and the Itô isometry, whereas the interpretation is false with constant . For the latter interpretation, the Burkholder-Davis-Gundy inequality supplies a constant instead. One can see the obstruction with a Brownian motion stopped on exiting : if is that Brownian exit time, then , , and strict Jensen inequality gives .
This obstruction also survives the continuity condition on . On a long finite interval approximate by a continuous adapted process equal to until and decreasing linearly to during the next units of time, and take its initial value to be by inserting a short continuous ramp before starting the exit experiment. The Itô isometry controls these approximations, and letting the interval length tend to infinity recovers the strict inequality above; hence some bounded continuous adapted example also violates the latter interpretation with constant . The direct proof avoids relying on this ambiguous hint.

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