# Variance of convolution between filter $A$ and Ornstein-Uhlenbeck process $x_t$

If we consider $x_t$ an Ornstein-Uhlenbeck process (with $W_t$ the Wiener process), does anyone know what would be the variance of the convolution of $x_t$ with a given filter $A$ i.e. $V(x_t \star A)$ ?

I've been trying to derive the solution starting from the analytical solution such as

$x_t = \mu_x \int_0^{\infty} A(p-t) (1-e^{-p/T}) dp + (\frac{2\sigma}{T})^{1/2} \int_0^{\infty} \left(A(p-t) \int_0^p e^{-(p-s)/T} dW_s \right) dp$

and using properties of stochastic integrals and Itô isometry but I can't get the end of it...

So far, my "most successful" unsuccessful developments are the following. Since the integration of a stochastic process is a stochastic process such that

$\int_0^p e^{-(p-s)/T} dW_s = X_p = \mathcal{N}\left(0,\int_0^p e^{-2(p-s)/T} ds \right) = \mathcal{N}\left(0,\frac{T}{2}(1-e^{-2p/T})\right)$

and that one can consider (with $W_p$ a Wiener process)

$X_p = \left(\frac{\frac{T}{2}(1-e^{-2p/T})}{p}\right)^{1/2} W_p$

then

$x_t = \mu_x \int_0^{\infty} A(p-t) (1-e^{-p/T}) dp + (\frac{2\sigma}{T})^{1/2} \int_0^{\infty} A(p-t) \left(\frac{\frac{T}{2}(1-e^{-2p/T})}{p}\right)^{1/2} W_p dp$

and given that

$\int_0^{a} g'(p) W_p dp \sim \mathcal{N}\left(0, \int_0^{a} \left(g(s)-g(p)\right)^2 ds\right)$

one therefore gets with $a=\infty$

$\sigma_x^2 = \sigma^2 \int_0^{\infty} \left( \int_p^{\infty} A(u-t) \left(\frac{1-e^{-2u/T}}{u}\right)^{1/2} du \right)^2 dp$

But I can't go anywhere from the last equation. Even taking $A$ as a dirac, it's not easy...any help would be greatly appreciated !

Thanks!

Represent the Orenstein-Uhlenbeck process as white noise passing through a low-pass (this is really the representation in the equation for $x_t$ you wrote). Call the transfer function of the low-pass $H$. Then your process is white noise passing through the filter $AH$. Now the variance you ask about is simply the square of the $L^2$ norm of $AH$, i.e. $\int |AH(\omega)|^2 d\omega$.
• So H can be calculated using the link between the autocorrelation of $x_t$ and the spectral density. Here an even more general derivation math.stackexchange.com/questions/1647793/… – Romain May 8 '18 at 13:54