Latency arbitrage on the desk: a practical playbook for props

Latency arbitrage shows up as microstructure advantage: systematically better fills around news, rollovers, or thin books. It is often legal by the letter of naive rules while toxic to your economics.

Desks that only react after Twitter threads have already paid for the lesson. Desks that measure slippage distributions and hold time early catch drift while it is still an internal ops problem.

Define what “fair” execution means for your programme

Write it in trader-facing language: how you expect slippage to behave in volatile conditions, what constitutes abuse of liquidity, and how you will investigate edge cases. Ambiguity becomes ammunition later.

Pair the policy with baselines: cohort-level distributions by session, symbol, and account tier. Outliers are not automatically guilty—but they should be automatically visible.

Investigation discipline

Good investigations combine execution charts, server timestamps, and session context. Great investigations also document what you ruled out and why—so appeals do not reopen closed loops.

Automation should pre-cluster similar cases so analysts recognise repeat MOs instead of treating every ticket as novel.

When to say no—and mean it

If your policy is real, enforcement must be real. Partial enforcement trains adversaries on your exact tolerance band.

The upside of crisp enforcement is faster payouts for clean traders: when risk queues shrink, everyone benefits—especially marketing, which finally has a story backed by data.