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An equation of the form
 
An equation of the form
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s1101801.png" /></td> <td valign="top" style="width:5%;text-align:right;">(a1)</td></tr></table>
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$$ \tag{a1 }
 +
X _ {t} = X _ {0} + \int\limits _ { 0 } ^ { t }  {\sigma ( s,X _ {s} ) }  {dW _ {s} } + \int\limits _ { 0 } ^ { t }  {b ( s,X _ {s} ) }  {ds } ,
 +
$$
  
where the initial condition <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s1101802.png" /> and/or the coefficients <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s1101803.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s1101804.png" /> are random, the solution <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s1101805.png" /> is not adapted (cf. also [[Optional random process|Optional random process]]) to the [[Brownian motion|Brownian motion]] <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s1101806.png" />, and the stochastic integral is interpreted in the sense of Skorokhod (see [[Skorokhod integral|Skorokhod integral]]; [[Stochastic integral|Stochastic integral]]; [[#References|[a5]]]). One cannot use a fixed-point argument to show the existence and uniqueness of the solution, as it is done for the adapted Itô stochastic equations, because the Skorokhod integral is not continuous in the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s1101807.png" />-norm.
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where the initial condition $  X _ {0} $
 +
and/or the coefficients $  \sigma $
 +
and $  b $
 +
are random, the solution $  X _ {t} $
 +
is not adapted (cf. also [[Optional random process|Optional random process]]) to the [[Brownian motion|Brownian motion]] $  W _ {t} $,  
 +
and the stochastic integral is interpreted in the sense of Skorokhod (see [[Skorokhod integral|Skorokhod integral]]; [[Stochastic integral|Stochastic integral]]; [[#References|[a5]]]). One cannot use a fixed-point argument to show the existence and uniqueness of the solution, as it is done for the adapted Itô stochastic equations, because the Skorokhod integral is not continuous in the $  L  ^ {2} $-
 +
norm.
  
If <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s1101808.png" />, and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s1101809.png" />, where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s11018010.png" /> is a deterministic function, (a1) has an explicit solution given by (see [[#References|[a1]]])
+
If $  b \equiv 0 $,
 +
and  $  \sigma ( s,x ) = \sigma _ {s} x $,  
 +
where $  \sigma _ {s} $
 +
is a deterministic function, (a1) has an explicit solution given by (see [[#References|[a1]]])
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s11018011.png" /></td> <td valign="top" style="width:5%;text-align:right;">(a2)</td></tr></table>
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$$ \tag{a2 }
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X _ {t} = X _ {0} \left ( \omega _  \cdot  - \int\limits _ { 0 } ^  \cdot  {\sigma _ {s} }  {ds } \right ) \times
 +
$$
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s11018012.png" /></td> </tr></table>
+
$$
 +
\times
 +
{ \mathop{\rm exp} } \left ( \int\limits _ { 0 } ^ { t }  {\sigma _ {s} }  {dW _ {s} } - {
 +
\frac{1}{2}
 +
} \int\limits _ { 0 } ^ { t }  {\sigma _ {s}  ^ {2} }  {ds } \right ) .
 +
$$
  
When <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s11018013.png" /> is random, a similar formula holds but the martingale exponential should be replaced by the Girsanov density associated with the anticipating shift <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s11018014.png" /> (see [[#References|[a3]]]).
+
When $  \sigma _ {s} $
 +
is random, a similar formula holds but the martingale exponential should be replaced by the Girsanov density associated with the anticipating shift $  \omega _ {t} \mapsto \omega _ {t} - \int _ {0}  ^ {t} {\sigma _ {s} }  {ds } $(
 +
see [[#References|[a3]]]).
  
 
Using the notion of [[Wick product|Wick product]], introduced in the context of [[Quantum field theory|quantum field theory]], the process (a2) can be rewritten as
 
Using the notion of [[Wick product|Wick product]], introduced in the context of [[Quantum field theory|quantum field theory]], the process (a2) can be rewritten as
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s110/s110180/s11018015.png" /></td> <td valign="top" style="width:5%;text-align:right;">(a3)</td></tr></table>
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$$ \tag{a3 }
 +
X _ {t} = X _ {0} \dia e ^ {\int\limits _ { 0 } ^ { t }  {\sigma _ {s} }  {dW _ {s} } - {
 +
\frac{1}{2}
 +
} \int\limits _ { 0 } ^ { t }  {\sigma  ^ {2} _ {s} }  {ds } } .
 +
$$
  
 
Formula (a3) can be used to solve linear multi-dimensional Skorokhod equations (see [[#References|[a4]]]). One-dimensional non-linear Skorokhod stochastic differential equations are studied in [[#References|[a2]]], and a local existence and uniqueness result is obtained by means of the pathwise representation of one-dimensional diffusions.
 
Formula (a3) can be used to solve linear multi-dimensional Skorokhod equations (see [[#References|[a4]]]). One-dimensional non-linear Skorokhod stochastic differential equations are studied in [[#References|[a2]]], and a local existence and uniqueness result is obtained by means of the pathwise representation of one-dimensional diffusions.

Latest revision as of 08:14, 6 June 2020


An equation of the form

$$ \tag{a1 } X _ {t} = X _ {0} + \int\limits _ { 0 } ^ { t } {\sigma ( s,X _ {s} ) } {dW _ {s} } + \int\limits _ { 0 } ^ { t } {b ( s,X _ {s} ) } {ds } , $$

where the initial condition $ X _ {0} $ and/or the coefficients $ \sigma $ and $ b $ are random, the solution $ X _ {t} $ is not adapted (cf. also Optional random process) to the Brownian motion $ W _ {t} $, and the stochastic integral is interpreted in the sense of Skorokhod (see Skorokhod integral; Stochastic integral; [a5]). One cannot use a fixed-point argument to show the existence and uniqueness of the solution, as it is done for the adapted Itô stochastic equations, because the Skorokhod integral is not continuous in the $ L ^ {2} $- norm.

If $ b \equiv 0 $, and $ \sigma ( s,x ) = \sigma _ {s} x $, where $ \sigma _ {s} $ is a deterministic function, (a1) has an explicit solution given by (see [a1])

$$ \tag{a2 } X _ {t} = X _ {0} \left ( \omega _ \cdot - \int\limits _ { 0 } ^ \cdot {\sigma _ {s} } {ds } \right ) \times $$

$$ \times { \mathop{\rm exp} } \left ( \int\limits _ { 0 } ^ { t } {\sigma _ {s} } {dW _ {s} } - { \frac{1}{2} } \int\limits _ { 0 } ^ { t } {\sigma _ {s} ^ {2} } {ds } \right ) . $$

When $ \sigma _ {s} $ is random, a similar formula holds but the martingale exponential should be replaced by the Girsanov density associated with the anticipating shift $ \omega _ {t} \mapsto \omega _ {t} - \int _ {0} ^ {t} {\sigma _ {s} } {ds } $( see [a3]).

Using the notion of Wick product, introduced in the context of quantum field theory, the process (a2) can be rewritten as

$$ \tag{a3 } X _ {t} = X _ {0} \dia e ^ {\int\limits _ { 0 } ^ { t } {\sigma _ {s} } {dW _ {s} } - { \frac{1}{2} } \int\limits _ { 0 } ^ { t } {\sigma ^ {2} _ {s} } {ds } } . $$

Formula (a3) can be used to solve linear multi-dimensional Skorokhod equations (see [a4]). One-dimensional non-linear Skorokhod stochastic differential equations are studied in [a2], and a local existence and uniqueness result is obtained by means of the pathwise representation of one-dimensional diffusions.

References

[a1] R. Buckdahn, "Linear Skorohod stochastic differential equations" Probab. Th. Rel. Fields , 90 (1991) pp. 223–240
[a2] R. Buckdahn, "Skorohod stochastic differential equations of diffusion type" Probab. Th. Rel. Fields , 92 (1993) pp. 297–324
[a3] R. Buckdahn, "Anticipative Girsanov transformations and Skorohod stochastic differential equations" , Memoirs , 533 , Amer. Math. Soc. (1994)
[a4] R. Buckdahn, D. Nualart, "Linear stochastic differential equations and Wick products" Probab. Th. Rel. Fields , 99 (1994) pp. 501–526
[a5] A.V. Skorokhod, "On a generalization of a stochastic integral" Th. Probab. Appl. , 20 (1975) pp. 219–233
How to Cite This Entry:
Skorokhod stochastic differential equation. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Skorokhod_stochastic_differential_equation&oldid=17111
This article was adapted from an original article by D. Nualart (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article