Quantitative Finance Asked by user144410 on February 9, 2021
I would like to clarify a confusion I have.
It is well known that a Wiener process (Brownian motion) is nowhere differentiable. I have no difficulty in understanding that. But I am wondering about the solutions of stochastic differential equations (SDEs). For simplicity, suppose that we have a linear SDE
$$
dX(t) = A, dt + B, dW(t)
$$
with initial value $X(t_0) = X_0$, and where $W(t)$ is a standard Wiener process. Then the solution is given by
$$
X(t) = exp(A(t-t_0)) X_0 + int_{t_0}^t exp(A(t-tau)) B , dW(tau).
$$
I am wondering about the properties of this solution, which is a colored stochastic process. In particular, are the sample paths of $X(t)$ differentiable in $t$?
The source of my confusion is coming from the interpretation of white noise as a formal derivative of Wiener process, and that the nondifferentiability is due to the constant spectrum of white noise. But now $X$ is filtered noise, i.e. it is colored. So I would expect that the irregular behaviour of the noise is smoothened out by the dynamics of the linear system described by the drift part of the equation.
Rather non rigorously,
$frac{W(t)}{t} sim N(0,frac{1}{t}) $
if $t to 0$ , we can see the variance goes to infinity. Hence Ito process is not differentiable.
Answered by Preston Lui on February 9, 2021
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