# Is the topology generated by the convergence of finite-dimensional distributions metrizable?

Let $$\mathbf{D} := D([0,1]; \mathbb{R}^d)$$ be the Skorokhod space (equipped with the Skorokhod metric) of càdlàg functions, and let $$X = (X_t)_{t \geq 0}$$ be its canonical process. The space of probability measures on $$\mathbf{D}$$ is denoted $$\mathcal{P}(\mathbf{D})$$. It is well known that weak convergence/topology on $$\mathcal{P}(\mathbf{D})$$ is metrizable. I'm now wondering the following:

If we equip $$\mathcal{P}(D)$$ with the topology $$\mathcal{T}_w$$ of convergence of finite-dimensional distributions, that is, the coarsest topology making the maps of the form

$$\mathcal{P}(\mathbf{D}) \ni \mathbb{P} \mapsto E_{\mathbb{P}}[f(X_{t_1},\ldots,X_{t_n})] \in \mathbb{R}$$

continuous for all $$n \in \mathbb{N}$$, all $$0 \leq t_1 < \ldots < t_n \leq 1$$ and each bounded, continuous $$f : \mathbb{R}^n \rightarrow \mathbb{R}$$, is then $$\mathcal{T}_w$$ metrizable?

• Is there a countable basis of neighborhoods at each point? Mar 25 at 16:21
• Do you mean for $\mathbf{D}$? If so, then yes as $\mathbf{D}$ is polish.
– vaoy
Mar 25 at 16:46
• I mean in the topology $\mathcal T_w$, does each measure have a countable basis of neighborhoods containing it? Mar 25 at 17:21
• It seems like the question boils down to being able to define $\mathcal{T}_w$ with only say rational or dyadic values for the $t_i$'s. Mar 25 at 21:38