At time $t$, there are a measure of particle whose distribution is described by the p.d.f. $g(x,t)$. Each particle follows a geometric Brownian motion with zero drift, $\frac{dx^{i}}{x^{i}}=\sigma dB^{i}$, where $dB^i$ is independent across $i$. By the law of large number, the diffusion terms cancel each other out in the distribution. Their distribution then follows the Kolmogorov Forward Equation (KFE): $$\frac{d}{dt}g(x,t)=\frac{d^{2}}{dx^{2}}\left(g(x,t)\frac{1}{2}σ^{2}x^{2}\right)$$
Denote $X_t=\mathbb \int x^i_t di = \int g(x,t)xdx$ to be the mean of the particles. How does $X_t$ evolve?
An intuitive but probably not really rigorous derivation would be:
$$\begin{aligned}dX_{t} &=d\int x_{t}^{i}di\\ &=\int dx_{t}^{i}di\\ &=\int\left(\sigma x_{i}dB^{i}\right)di\\ &=0\\ \end{aligned} $$
The last step uses the argument that "the diffusion terms cancel each other out", but it doesn't seem very rigorous to me. What's the $di$ measure and can we interchange its integral with the derivative?
Another approach is to use the Kolmogorov forward equation: $$\begin{aligned}\frac{dX_{t}}{dt} =\frac{1}{2}\sigma^{2}\int_{0}^{\infty}x\frac{d^{2}}{dx^{2}}\left(g(x,t)x^{2}\right)dx\\ =\frac{1}{2}\sigma^{2}\int_{0}^{\infty}2g(x,t)x+4g_{x}(x,t)x^{2}+x^{3}g_{xx}(x,t)dx\\ =\frac{1}{2}\sigma^{2}\left(x^{2}g(x,t)+x^{3}g_{x}(x,t)\right)|_{0}^{\infty}\end{aligned}$$
Now we are left with a bunch of higher-order terms and limits. Assume the first moment exists for $g(x,t)$, is the integral always zero, or will it eventually be distribution-dependent?
P.S. the derivation using the $di$ measure proves a stronger property than the KFE approach above. It essentially says for any diffusion processes, not only the geometric brownian motion, they will cancel each other out for the first moment. Is there any way to establish that as well using KFE? i.e.
$$\int\frac{d^{2}}{dx^{2}}\left(g(x,t)σ^{2}(x)\right)dx=0$$