Possibly, but if you are processing live market data, you are in the arena of almost hard real-time systems. I.e. you effectively have a time budget to process every single tick/message. Then, even low-level optimization can make a large difference. E.g. if you can make some helper method use less memory, i.e. it uses less of your caches, that can make a big difference on your business logic. Amdahl's law is not at all suited to understand such non-linear non-local inter-dependencies.
Amdahl's law basically says when you speed up part of a task, the overall speedup is limited by the part you didn't speed up. The speedup doesn't have to come from parallelism.
It can be applied more generally. If you're focusing on improving the performance of something that only takes 10% of your time, then the other 90% will still dominate.
Aha, I see. If you’re in a race where every microsecond counts you would still care about there 10% after you’ve made sure that the 90% can’t be further optimized.