Ito process: Difference between revisions

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imported>Valentin Clément
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Let <math>(\Omega, F, \mathbb{F}, \mathbb{P})</math> be a probability space with a filtration <math>\mathbb{F}=(F_t)_{t\geq 0}</math> that we consider as complete (that is to say, all sets which measure is null are contained in <math>F_0</math>
Let <math>(\Omega, F, \mathbb{F}, \mathbb{P})</math> be a probability space with a filtration <math>\mathbb{F}=(F_t)_{t\geq 0}</math> that we consider as complete (that is to say, all sets which measure is null are contained in <math>F_0</math>


Let also be <math>B=(B^1_t,\dots,B^d_t)_{t\geq 0}</math> a ''d''-dimensional <math>\mathbb{F}</math>- Standard Brownian Motion.
Let also be <math>B=(B^1_t,\dots,B^d_t)_{t\geq 0}</math> a ''d''-dimensional <math>\mathbb{F}</math>- Standard Brownian Motion.


Then we call Ito Process all process <math>(X_t)_{t\geq 0}</math> that can be written like :
Then we call Ito Process all process <math>(X_t)_{t\geq 0}</math> that can be written like :


<math>X_t = X_0 + \int_0^t K_s\mathrm{ds} + \sum_{j=1}^d\int_0^t H_s*\mathrm{dB}_s^j</math>
 
<math>X_t = X_0 + \int_0^t K_s\mathrm{ds} + \sum_{j=1}^d\int_0^t H^j_s*\mathrm{dB}_s^j</math>
 


Where :
Where :
* <math>X_0</math> is <math>F_0</math> measurable
* <math>X_0</math> is <math>F_0</math> measurable
* <math>(K_t)_{t\geq 0}</math> is a progressively measurable process such as <math>\forall t\geq 0,\ \int_0^t|K_s|\textrm{ds}<+\infty</math> almost surely.
* <math>(K_t)_{t\geq 0}</math> is a progressively measurable process such as <math>\forall t\geq 0,\ \int_0^t|K_s|\textrm{ds}<+\infty</math> almost surely.
* <math>(H^i_t)_{t\geq 0,\ i\in[1\dots d]}</math> is progressively measurable and such as <math>\forall i\in [1\dots d],\ \forall t\geq 0,\ \int_0^t(H_s^i)^2\mathrm(ds)<+\infty</math> almost surely.







Revision as of 14:16, 28 December 2008

An Ito Process is a type of stochastic process described by Japanese mathematician Kiyoshi Ito, which can be written as the sum of the integral of a process over time and of another process over a Brownian Motion.

Those processes are the base of Stochastic Integration, and are therefore widely used in Financial Mathematics and Stochastic Calculus.


Description of the Ito Processes

Let be a probability space with a filtration that we consider as complete (that is to say, all sets which measure is null are contained in


Let also be a d-dimensional - Standard Brownian Motion.


Then we call Ito Process all process that can be written like :



Where :

  • is measurable
  • is a progressively measurable process such as almost surely.
  • is progressively measurable and such as almost surely.