> The second you use pandas with a custom data type
That's a pandas (and maybe numpy) issue, not a dynamic language issue. (If you want to generalize from the specific libraries more accurately than “dynamic language”, it's “using a low-level library whose type system doesn't match the host language type system” issue.
> Quants tend to use fixed precision types. It is like a float in every way, except base 10 instead of base 2 so there is no floating point error.
No, a type that is like binary floating point in every way except base 10 instead of base 2 would be decimal floating point, not fixed point. Decimal fixed point is different from binary floating point in more ways than base.