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Execution quality report: measuring the milliseconds

How execution quality should be measured: an illustrative six-month dataset of 4.1M orders shows why medians, percentiles and news-window behavior — not averages — tell the real story.

Educational note: figures, benchmarks and scenarios in this article are illustrative examples. They are not IUX production data, execution reporting or a representation of client outcomes.

8 min read

Summary

This explainer uses an illustrative venue dataset — 4.1 million simulated market orders across forex, metals, indices and crypto CFDs over a six-month window — to show how execution quality should be read: the distribution, not just the average. Median, p95 and p99 execution times, slippage direction, and behavior during the six highest-impact news events of the period.

28 ms

Median round-trip in the example dataset

97.1%

Example orders filled at or better than quote

4.1M

Simulated orders in the illustration

Latency distribution

Averages hide tails. A venue quoting “30 ms average” can still deliver 400 ms exactly when volatility spikes — which is when execution matters most. Percentiles tell the truth instead.

Order round-trip latency by percentile

milliseconds — lower is better

p50 (median)28
p9041
p9555
p99 — incl. news spikes112
Illustrative distribution, measured order-receipt to fill-confirmation in the example dataset. Client-observed latency always adds network transit from the trader's location.

The p99 figure includes the release minutes of every NFP, CPI and FOMC event in the window. Even the worst 1% of orders completed in under an eighth of a second.

Slippage direction is the honesty test

Slippage direction is the honesty test for any execution venue. Asymmetric slippage — fills that only ever slip against the client — indicates last-look abuse or quote manipulation. A venue handling slippage symmetrically produces a split like the example below:

Market-order fill outcomes, share of volume

% of 4.1M orders

Filled at quoted price88.3
Positive slippage (price improved)8.8
Negative slippage2.9
Positive vs negative slippage ratio 3.0:1, dominated by fast-market conditions where the touch moved in the client's favor between quote and fill.

If a venue won't publish its negative-slippage share, assume the number answers the question.

— A useful rule of thumb

Behavior under news

The example isolates the 60-second windows around six tier-1 releases. Spreads widen — that is real liquidity thinning, not venue behavior — but execution time and reject rates stayed inside normal bands:

  • Median latency during release minutes in the example dataset: 34 ms (vs 28 ms baseline).
  • Reject rate: 0.4% (vs 0.2% baseline) — rejects re-quote rather than silently fill at a worse price.
  • XAUUSD spread at NFP peak: 3.2× typical, recovering to baseline within 41 seconds on average.
PriceResistance zoneSupport zone
Stylised release-minute price path: liquidity zones re-form within the first minute after the print. · Illustrative data — past performance is not a reliable indicator of future results.

Methodology

  • Population: every market order on live accounts, Jan 1 – Jun 30 2026. No sampling, no exclusions except cancelled-before-fill.
  • Clock: single monotonic clock at the execution gateway; timestamps at receipt, risk-check completion, and fill.
  • Slippage: fill price vs the quote displayed at order submission, signed from the client’s perspective.
  • News windows: ±30 s around the scheduled timestamp of NFP (×2), US CPI (×2), FOMC (×2).

Educational content only. Figures, benchmarks and charts are illustrative examples, not IUX production data or a representation of trading outcomes. Nothing here is investment advice.

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