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Doléans-Dade exponential : ウィキペディア英語版
Doléans-Dade exponential
In stochastic calculus, the Doléans-Dade exponential, Doléans exponential, or stochastic exponential, of a semimartingale ''X'' is defined to be the solution to the stochastic differential equation with initial condition . The concept is named after Catherine Doléans-Dade. It is sometimes denoted by ''(unicode:Ɛ)''(''X'').
In the case where ''X'' is differentiable, then ''Y'' is given by the differential equation to which the solution is .
Alternatively, if for a Brownian motion ''B'', then the Doléans-Dade exponential is a geometric Brownian motion. For any continuous semimartingale ''X'', applying Itō's lemma with gives
:
\begin
d\log(Y) &= \frac\,dY -\frac\,d() \\
&= dX - \frac\,d().
\end

Exponentiating gives the solution
:Y_t = \exp\Bigl(X_t-X_0-\frac12()_t\Bigr),\qquad t\ge0.
This differs from what might be expected by comparison with the case where ''X'' is differentiable due to the existence of the quadratic variation term () in the solution.
The Doléans-Dade exponential is useful in the case when ''X'' is a local martingale. Then, ''(unicode:Ɛ)''(''X'') will also be a local martingale whereas the normal exponential exp(''X'') is not. This is used in the Girsanov theorem. Criteria for a continuous local martingale ''X'' to ensure that its stochastic exponential ''(unicode:Ɛ)''(''X'') is actually a martingale are given by Kazamaki's condition, Novikov's condition, and Beneš' condition.
It is possible to apply Itō's lemma for non-continuous semimartingales in a similar way to show that the Doléans-Dade exponential of any semimartingale ''X'' is
:Y_t = \exp\Bigl(X_t-X_0-\frac12()_t\Bigr)\prod_(1+\Delta X_s) \exp \Bigl(-\Delta X_s+\frac12\Delta X_s^2\Bigr),\qquad t\ge0,
where the product extents over the (countable many) jumps of ''X'' up to time ''t''.
== See also ==

* Stochastic logarithm

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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