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0 (
Then , the process M t :=
A
f(X t )
f )(X s ) d s is a martingale with respect to the
filtration of W .
Proof We apply the Itô formula (1.7)to f(X t ) and obtain, in integral form,
t
t
1
2
xx f(X s 2 (X s ) d s.
f(X t )
=
f(X 0 )
+
x f(X s ) d X s +
0
0
Using d X t =
b(X t ) d t
+
σ(X t ) d W t , and the definition of
A
,wehave
t
t
σ(X s )f (X s ) d W s .
f(X t )
=
f(X 0 )
+
(
A
f )(X s ) d s
+
0
0
The result follows if we can show that the stochastic integral 0 σ(X s )∂ x f(X s ) d W s
is a martingale (with respect to the filtration of W ). According to Proposition 1.2.7,
it is sufficient to show that
0 |
2 d s
E[
σ(X s )∂ x f(X s )
|
]
<
. Since f has bounded
derivatives and σ satisfies (1.4), we obtain
t
0 |
2 d s
2 ) d s
t
2
C 2 sup
x ∈R
2
E
σ(X s )
|
|
x f(X s )
|
|
x f(x)
|
E
( 1
+|
X s |
0
2 1
+ E sup
0
2 ( 1.5 )
TC 2 sup
x
| x f(x) |
T | X s |
<
.
∈R
s
Remark 4.1.2 For t> 0 denote by X t
the solution of the SDE (1.2) starting from
0 (
x at time 0. Then, since M t =
f(X t )
A
f )(X s ) d s is a martingale by Proposi-
tion 4.1.1 , we know that
E[
M 0 ]=
f(x)
= E[
M t ]
. Therefore,
f )(X s ) d s .
t
f(X t )
E[
]=
f(x)
+ E
(
A
0
Since by assumption f has bounded derivatives and b, σ satisfy the global Lipschitz
and linear growth condition (1.3)-(1.4)
E sup
0
|
E sup
0
|
f )(X s )
σ 2 (X s )
b(X s )
s T |
(
A
C
s T |
|+|
C 1
+ E sup
0
2 <
X s |
T |
.
s
f and X t
Thus, since
A
are continuous, the dominated convergence theorem gives
1
t
f )(X s ) d s
t
d
d t E[
f(X t )
]| t = 0 =
lim
t
0 E
(
A
=
(
A
f )(x).
0
is called the infinitesimal generator of the process X t .
Therefore,
A
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