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I want to solve the stochastic differential equation $$\mathrm dX(t)=B(t)X(t)\mathrm dt+B(t)X(t)\mathrm dB(t)$$ with condition $X(0)=1$.

saz
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peter
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    Sometimes this helps: Apply the Ito formula to compute the SDE satisfied by $Y(t)=e^{-B(t)}X(t)$, intended to (mostly) remove the $dt$ term, and modify this approach to further reduce the number of resulting terms. – Lutz Lehmann Jan 01 '14 at 10:18
  • @LutzL.ok thanks for help. – peter Jan 01 '14 at 10:32

1 Answers1

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Solution I Dividing the SDE (formally) by $X_t$ yields

$$\frac{dX_t}{X_t} = B(t) \, dt+ B(t) \, dB_t.$$

This equation suggests using an approach similar to the separation-by-parts-approach for ordinary differential equations: We set $Z_t := \log X_t$ and apply Itô's formula

$$\begin{align*} Z_t - Z_0 &= \int_0^t \frac{1}{X_s} \, dX_s - \frac{1}{2} \int_0^t \frac{1}{X_s^2} \, d\langle X \rangle_s \tag{1} \end{align*}$$

where

$$dX_s = B(s) X(s) \, ds + B(s) X(s) \, dB(s) \qquad d\langle X \rangle_s = B(s)^2 X(s)^2 \, ds. \tag{2}$$

Combining $(1)$ and $(2)$, we obtain

$$Z_t - Z_0 = \int_0^t B(s) \, dB_s + \int_0^t \left( B(s) - \frac{1}{2} B_s^2 \right) \, ds.$$

By definition, $Z_t = \log X_t$, and therefore we find an explicit expression for $X_t$. Itô's formula shows that $(X_t)_t$ defines indeed a solution of the given SDE.

Solution II Consider the corresponding ordinary differential equation

$$dx(t) = B(t) \, x(t) \, dt \qquad x(0)=1.$$

Its unique solution is given by

$$x(t) = \exp \left( \int_0^t B(s) \, ds \right)$$

or, equivalently,

$$x_t \cdot \exp \left( - \int_0^t B(s) \, ds \right)=1$$

This indicates that we may try the following Ansatz:

$$Y_t := X_t \cdot \exp \left( -\int_0^t B(s) \, ds \right).$$

Applying Itô's formula to $f(x,y) := x \cdot e^{-y}$ and the (two-dimensional) Itô process $(X_t, \int_0^t B(s) \, ds)$ gives

$$\begin{align*} Y_t - Y_0 &= \int_0^t \exp \left(- \int_0^s B(r) \, dr \right) \, dX_s - \int_0^t Y_s B(s) \, ds = \int_0^t B(s) Y_s \, dB_s. \end{align*}$$

This SDE can be solved easily and therefore we obtain an expression for $X_t$. This approach looks more complicated and lengthy, but actually it works out in a much more general setting.

saz
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  • Hi Saz, noticed you are an expert in stochastic stuff. Can i please ask how you got the ansatz? What is the thing to do in general? Is it trying to solve the bit without BM, then divide that part? – Lost1 Jan 02 '14 at 13:58
  • I prefer your method. Seems more systematic. Don't think it is more complicated. – Lost1 Jan 02 '14 at 13:59
  • @Lost1 Well, actually, the idea is simply that in the determinstic case $$x_t \cdot \exp \left( - \int_0^t B(s) , ds \right)=1 =: y_t,$$ in particular the right-hand side is constant. Since we want to add a stochastic term (kind of a "perturbation" of the ODE), it seems natural to allow a dependence on $\omega$, i.e. $y_t = Y_t(\omega)$. Applying Itô's formula yields a SDE for $(Y_t)_{t \geq 0}$ - and hopefully we are able to solve this SDE in order to solve the original SDE. Here is another example. – saz Jan 02 '14 at 15:17
  • And yes, $(x_t)_t$ is the solution of the corresponding ODE, i.e. if we consider a SDE of the form $$dX_t = \sigma(X_t) , dB_t+ b(X_t) , dt$$ then the corresponding ODE is given by $$dx_t = b(x_t) , dt.$$ – saz Jan 02 '14 at 15:24