Set , the stochastic logarithm of . On each finite horizon, a strictly positive continuous path has its reciprocal bounded; stopping at levels of , and rigorously localizes this stochastic integral. Thus is a zero-start continuous local martingale, with
The Itô formula for the ordinary logarithm gives
Accordingly, with the exponential convention printed in this question,
The initial constant in contributes no quadratic variation. Under the standard normalized Doléans-Dade exponential convention, which subtracts the driver's initial value in the exponent, the same formula is written .
For uniqueness, suppose another continuous driver gives the printed exponential. Evaluating at zero forces . Applying the Itô formula to its exponential gives . Since , associativity of stochastic integration yields . Thus , up to indistinguishability of stochastic processes.
There is an initial-integrability qualification if “local martingale” is used with the usual integrable-initial-value definition. The displayed is a continuous local martingale when , in particular when is a positive deterministic number. An arbitrary positive integrable does not ensure this. For example, take an -measurable positive integer with and put for all . This is a bounded strictly positive martingale, but any representing driver must have , which is not integrable. Thus the unqualified claim is false under that definition. For general , the always-valid local-martingale statement is the zero-start representation ; the printed representation additionally requires the stated integrability or the convention that allows arbitrary finite initial constants.
Let on . The Radon-Nikodym derivative is nonnegative and . For ,
Uniqueness of the restricted Radon-Nikodym derivative therefore identifies
For , the tower property of conditional expectation gives , and . Thus is a nonnegative true martingale, indeed a uniformly integrable martingale, since it consists of conditional expectations of one integrable random variable. This is the Radon-Nikodym density martingale. Under the usual conditions for a filtration, it has the standard càdlàg version; continuity is the additional assumption in part (c), not a consequence of absolute continuity alone.
On the finite horizon , strict positivity gives equivalence of the restricted probability measures: for , vanishes if and only if vanishes. The standard change-of-measure theorem gives semimartingale invariance under equivalent measures: a process is a semimartingale under on this horizon if and only if it is one under . The sample-path quadratic variation is unchanged, but the local-martingale and finite-variation parts generally change.
More explicitly, set , the zero-start stochastic logarithm of the density. For every continuous -local martingale , the Girsanov theorem states that
is a continuous -local martingale. Consequently, if the continuous semimartingale decomposition under is , its decomposition under is
The covariation correction is a continuous finite-variation process, locally well-defined because stays strictly positive. In the Brownian case, if , then
is a Brownian motion under . The inverse finite-horizon density is , giving the reverse change of measure. These assertions apply on each horizon on which the density is strictly positive; they do not assert equivalence on a larger terminal sigma-algebra where the full density may vanish.

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