AnomIQ
Rolling UI: Buy volume Z-score Common floor: > 2.5

Buy Volume Z-Score

How statistically rare the current buy-side volume surge is, relative to this instrument's own history. The primary buy-side filter.

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Definition

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Measures the rarity of current buy-side notional volume in the active rolling window relative to the historical buy-volume mean and standard deviation.

Formula & calculation

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(Live Mean Buy Volume - Historical Mean Buy Volume) / Historical StdDev Buy Volume

Units & range

Z (standard deviations). A reading above 2.5 places current buy-side volume in roughly the top 1% of what this instrument has seen over its 24-hour baseline.

Interpretation

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This is the primary buy-side anomaly signal. Because it normalizes against each instrument's own history, the same threshold works on BTCUSDT and a mid-cap altcoin: a 3σ buy surge on a small contract is as meaningful as a 3σ surge on a liquid one. The z-score answers a specific question: how unusual is this buy volume compared to what is normal for this market? It does not tell you whether the price will follow. For that, confirm with net taker imbalance and current window return.

Practical usage

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Start here when building buy-side scanner rules. A floor of 2.5 removes the vast majority of ordinary sessions. Combine with net taker imbalance above 20% and a notional floor to turn a statistical flag into a tradeable setup. Running this without a notional floor will produce alerts on illiquid symbols where large z-scores can appear on minimal absolute volume.

Common mistakes

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Frequent interpretation traps and misuse patterns to avoid when applying this metric.

  • Running it without a notional or liquidity floor. A z-score of 4.0 on a $20k/day symbol is not the same event as a z-score of 4.0 on a $50M/day symbol.
  • Using total volume z-score instead of the buy-side split. The directional information is in the buy/sell separation, not the total.

Timeframe note

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This metric applies to rolling windows such as 5m, 15m, and 60m. The underlying definition stays the same; what changes is the time horizon used to measure it. Shorter windows react faster, while longer windows smooth noise and emphasize broader structure.

5m

Faster response to fresh changes in activity and short-horizon structure.

15m

Balanced view between responsiveness and persistence.

60m

Broader context that is slower but more stable.