Under what conditions can a metric vector space be given an equivalent metric that is translation invariant?
I was wondering if the probability measures on real line can be embedded in vector space of bounded measures on real line, so that the Lévy–Prokhorov metric is extended in the natural manner: If $\mu$ and $\nu$ are two measures on real line,
$$d (\mu, \nu) := \inf \left\{ \varepsilon > 0 \mid \mu(A) \leq \nu (A^{\varepsilon}) + \varepsilon \ \text{and} \ \nu (A) \leq \mu (A^{\varepsilon}) + \varepsilon \ \text{for all} \ A \in \mathcal{B}(\mathbb{R}) \right\}.$$
I want to see if this creates topological vector space. I could not prove that the metric is translation invariant.