Signal latency is one of those problems that sounds technical but bites you in the wallet. Every millisecond between when your system generates a signal and when your order hits the exchange is an opportunity for the market to move against you. In mid-cap ASX equities, where spreads are wider and order books thinner, that bite can be savage.

The tricky part is attribution. Most traders see slippage on their trade reports and shrug — "market was moving." But slippage has components, and latency-driven slippage is both the most preventable and the most frequently misidentified. You can't fix what you can't isolate, and that's exactly why this question matters more than most traders realise.

CONCEPTLatency slippage is the gap between signal price and fill price caused purely by system delay — entirely separate from market impact.
WARNINGAttributing all slippage to "market volatility" masks latency costs and leaves preventable edge destruction invisible in your P&L.
KEY IDEAIn ASX mid-caps, a 200ms latency increase can translate to 2–4 basis points of additional slippage per trade on average.

Think of it like ordering coffee at a busy café. The moment you decide you want a flat white is your signal. The moment the barista starts making it is your fill. If you spend three minutes finding your wallet, someone else orders ahead of you, the milk steamer queue grows, and your coffee costs extra time. Markets work identically — delay invites queue position deterioration and adverse price movement, both of which show up as slippage.

Avg Slippage (bps) by Latency Band — ASX Mid-Caps<50ms50–150ms150–300ms>300ms1.22.13.85.6bpsIllustrative estimates based on market microstructure research

Slippage attribution frameworks used by systematic traders typically decompose fill costs into three buckets: signal-to-order latency, order-to-fill latency, and residual market impact. The first bucket is pure system overhead — network, computation, order management system processing. The second covers exchange queue mechanics and matching engine timing. Separating these analytically requires timestamping at every stage, which many retail-grade platforms simply don't offer. Academic market microstructure literature, particularly work drawing on market microstructure theory, confirms that mid-cap securities suffer disproportionately because their thinner books mean even small queue position changes produce measurable price impact. Traders who want to go deeper on the mechanics of how fill costs accumulate should review the concept of slippage as defined in execution analysis, and for the infrastructure side of the problem, the principles behind trading latency and its sources provide a solid foundation for diagnosing where delay actually lives in a system.

The practical takeaway is simple: timestamp everything, then regress your slippage against your latency measurements by stock liquidity tier. If the relationship is strong, your infrastructure is costing you more than your strategy is earning.

Your edge lives in the signal. Don't let the plumbing eat it.

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