Let $(X^n_t)_{t \geq 0}$ be a sequence of cadlag stochastic processes, that is $X^n$ is a random element in the Skorokhod space $D([0, \infty), \mathbb{R}$) for each $n \in \mathbb{N}$. Also for each $n$ let $T^n_t$ be a cadlag stochastic process in $D([0, \infty), [0, \infty))$ which is non-decreasing.
Assume that
- $X^n$ converges in finite-dimensional distributions to a cadlag process $X$ (but not necessarily in distribution) and
- $T^n$ converges in distribution to the identity $\text{id}$.
Is it true that the composition $X^n \circ T^n$ (i.e. the process $(X^n_{T^n_t})_{t \geq 0}$) also converges in finite-dimensional distributions to $X$?
I know that this result is true when $X^n$ converges in distribution since
- the composition has some nice continuity properties (see Ward Whitt, "Stochastic Process Limits") ... the limit $\text{id}$ of $T^n$ is continuous and strictly increasing
- $T^n$ converges to a non-random process and thus we have joint convergence in distribution $(X^n, T^n)$ and
- we can apply the Continuous Mapping Theorem.
But when I weaken the convergence of $X^n$ to only convergence in finite-dimensional distributions and on the other hand seek also only for convergence in finite-dimensional distributions of the composed process, then I don't know whether this type of convergence still holds.