What we learned shipping an Algo trading platform to a live desk
Photo: hackNY / Flickr · CC BY-SA 2.0
Ask ten traders about the ideal algo trading platform and you will get eleven answers. Here is the framework we use to cut through the noise.
What an algo trading platform actually does
Think of an algo trading platform as the layer that owns automation and integration. When it works you forget it exists; when it fails, you feel it immediately.
Automation amplifies whatever you feed it, so an algo trading platform magnifies good logic and bad logic with equal enthusiasm.
What to look for
When you put an algo trading platform through its paces, weigh it against the things that bite in production rather than the ones that demo well:
- Rate limits, and how gracefully the client backs off
- Reconnection and gap-recovery on dropped connections
- Idempotency on order placement to avoid duplicate fills
- Quality of the SDK docs and example code
- A realistic sandbox or paper-trading environment
Common mistakes
The usual trap is optimising for the happy path. An algo trading platform that looks great on a quiet Tuesday can fall apart the moment volume, volatility or fees spike — which is exactly when you need it most. Test it under stress, with adversarial inputs, and on the messiest data you can find.
The bottom line
Pick the algo trading platform you understand well enough to debug at 3 a.m. during a market event. Cleverness you cannot reason about is a liability, not an edge.
