AnomIQ

Documentation

Rolling Window Metrics (5m / 15m / 60m)

These filters appear under three separate scanner groups: 5m, 15m, and 60m. The names are the same; the group determines the window length.

Buy/Sell variants are based on trade aggressor side: “Buy” = aggressive taker buying, “Sell” = aggressive taker selling.

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Timeframe metrics

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Trade Size Ratio (Total / Buy / Sell)

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Compares the average trade size in this window to the historical norm. Available as Total (all executions), Buy (taker buying), and Sell (taker selling).

UI field: Total / Buy / Sell Size Ratio

Calculation
(Current Avg Trade Size / Historical Avg Trade Size) × 100
Range / Units
%. Values hover around 100%.
Interpretation
High values indicate larger capital is moving the asset compared to normal conditions.
Trading Application
A Buy Size Ratio > 150% suggests buyers are using significantly larger capital than usual, hinting at institutional accumulation.
Common mistakes
  • Looking at Total Size Ratio without checking if Buys or Sells are driving the increase.

Trade Count Ratio (Total / Buy / Sell)

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Compares the total number of individual trade executions (count) in this window to the historical average.

UI field: Total / Buy / Sell (count) Trades Ratio

Calculation
(Current Trade Count / Historical Avg Trade Count) × 100
Range / Units
%.
Interpretation
High values indicate a surge in crowd participation or high-frequency algorithmic activity.
Trading Application
A Buy Trades Ratio > 200% means twice as many individual buy orders are executing compared to normal, indicating retail FOMO.
Common mistakes
  • Assuming high trade count means smart money is entering (it usually means retail is entering).

Volume Ratio (Total / Buy / Sell)

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The ratio of volume in this timeframe versus the historical average. This is the primary measure of unusual activity.

UI field: Total / Buy / Sell Volume Ratio

Suggested floor: > 150%

Calculation
(Current Window Volume / Historical Avg Window Volume) × 100
Range / Units
%. 200% = 2x normal volume.
Interpretation
If Buy Volume Ratio is significantly higher than Sell Volume Ratio, taker-buyers are aggressively lifting the offer.
Trading Application
Use Total Volume Ratio > 200% as a baseline filter to only view coins experiencing highly abnormal liquidity events.
Common mistakes
  • Trading a breakout when the Volume Ratio is only ~100% (indicating no new capital is supporting the move).

Current Volume Ratio (Buy / Sell)

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Measures the percentage of total volume within the current rolling window that is driven by aggressive taker buying or selling. For example, a 5-minute Buy Volume Ratio of 70% means that over the last 4 completely finished 1-minute bars plus the current active minute, 70% of all capital flow was aggressive taker buying.

UI field: Current (TimeFrame) Buy / Sell Volume Ratio

Suggested floor: > 65%

Calculation
(Buy or Sell Volume / Total Window Volume) × 100
Range / Units
% (0 to 100%).
Interpretation
Values > 50% mean that side is dominating the immediate flow. Values > 65% indicate overwhelming, one-sided pressure.
Trading Application
This is your primary directional filter. If a coin is breaking out but the Current Buy Volume Ratio is only 45%, the breakout is being heavily absorbed by limit sellers. Wait for > 65% to confirm buyers are in total control.
Common mistakes
  • Confusing this with 'Historical Volume Ratio'. This metric only looks at the internal Buy vs Sell battle happening right now, not how today compares to yesterday.

Current Trades Ratio (Buy / Sell)

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Measures the percentage of the total number of trade executions (trade count) within the current rolling window that were buys or sells.

UI field: Current (TimeFrame) Buy / Sell Trades Ratio

Suggested floor: > 65%

Calculation
(Buy or Sell Trade Count / Total Trade Count) × 100
Range / Units
% (0 to 100%).
Interpretation
Indicates which side of the market is making more frequent, individual transactions. > 50% means that side is executing more frequently.
Trading Application
Compare this to the Volume Ratio. If Buy Trades Ratio is 80% but Buy Volume Ratio is 40%, it means thousands of retail traders are buying tiny amounts, but a few massive whales are absorbing it all with massive sell orders.
Common mistakes
  • Assuming a high Buy Trades Ratio is bullish on its own (it often just represents retail FOMO if not backed by volume).

Current Size Ratio (Buy / Sell)

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Measures the percentage of the total average trade size in the current window attributed to buys versus sells.

UI field: Current (TimeFrame) Buy / Sell Size Ratio

Suggested floor: > 65%

Calculation
(Avg Buy Trade Size / Avg Total Trade Size) × 100
Range / Units
% (0 to 100%).
Interpretation
Values > 50% indicate that buyers (or sellers) are utilizing larger capital per order than their counter-parties.
Trading Application
A powerful institutional footprint. If the Current Buy Size Ratio is > 70%, it means the average buy order is significantly larger than the average sell order, hinting at institutional accumulation.
Common mistakes
  • Using this on highly illiquid pairs where a single random $1,000 trade can skew the ratio to 99%.

Current Window Return (%)

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The percentage price change strictly within this specific rolling timeframe. It shows the immediate direction and magnitude of the move happening right now.

UI field: Current (TimeFrame) Return

Suggested floor: > 0.5%

Calculation
((Current Price - Price at Start of Window) / Price at Start of Window) × 100
Range / Units
%. Can be positive or negative.
Interpretation
A positive value confirms the asset is moving up within the scanned window. The higher the value, the more aggressive the price action.
Trading Application
Use this as a directional filter. If you are scanning for bullish breakouts using Volume Z-Scores, you must set Current Return > 0.5% to ensure the volume spike is actually pushing the price upward, not downward.
Common mistakes
  • Assuming high volume guarantees a positive return. Massive volume can happen on flat or negative price action (absorption or distribution).

Volume Z-Score (Total / Buy / Sell)

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Measures the statistical rarity of the volume within this specific timeframe. By tracking Total, Buy, and Sell variants independently, you can pinpoint exactly which side of the market is behaving abnormally.

UI field: Total / Buy / Sell volume Z-score

Suggested floor: > 2.5

Calculation
1. Get Live Mean: (Accumulated Volume + Live Tick Volume) / Window Size
2. Standard Math: (Live Mean - Historical Mean) / Historical StdDev
3. Flatline Breakout: If StdDev is 0 and Live > Mean, the system forces a 10.0 score.
Range / Units
Z (Standard Deviations).
Interpretation
Values > 2.0 are statistically significant. Values > 3.0 are extreme anomalies (the top 0.3% of all historical activity). A forced `10.0` means the coin just woke up from absolute zero volume.
Trading Application
A Buy Volume Z-score > 3.0 indicates unusual, aggressive taker-buying compared to the norm. This is the ultimate mathematical confirmation of a breakout.
Common mistakes
  • Looking at Total Volume Z-Score without verifying if the Buy or Sell side is driving the anomaly.

Trade Count Z-Score (Total / Buy / Sell)

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Measures the statistical rarity of the number of individual executions (trade count) within this timeframe. High values indicate abnormal crowd participation or high-frequency bot activity.

UI field: Total / Buy / Sell count trades Z-score

Suggested floor: > 2.5

Calculation
1. Get Live Mean: (Accumulated Trades + Live Tick Trades) / Window Size
2. Standard Math: (Live Mean - Historical Mean) / Historical StdDev
Range / Units
Z (Standard Deviations).
Interpretation
A high Z-score means significantly more separate transactions are happening than usual. An influx of individual buyers or sellers.
Trading Application
If the Buy Trade Z-Score is > 3.0 but the Buy Size Z-score is low, the breakout is being driven by retail FOMO (many small trades), which is highly prone to reversal.
Common mistakes
  • Assuming a high Trade Count Z-Score means large capital is entering. It usually implies the exact opposite (fragmented, retail capital).

Trade Size Z-Score (Total / Buy / Sell)

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Measures the statistical rarity of the average trade size within this timeframe. This is a direct indicator of institutional activity.

UI field: Total / Buy / Sell trades size Z-score

Suggested floor: > 2.5

Calculation
1. Get Live Mean: (Accumulated Avg Size + Live Tick Avg Size) / Window Size
2. Standard Math: (Live Mean - Historical Mean) / Historical StdDev
Range / Units
Z (Standard Deviations).
Interpretation
A high Z-score suggests 'Whale' activity (large capital per execution) rather than retail noise.
Trading Application
Set Buy Size Z-Score > 2.5 to only receive alerts when massive individual buyers are aggressively hitting the ask, leaving a footprint that retail traders cannot replicate.
Common mistakes
  • Using this on extreme low-liquidity coins where the 'Historical Mean' is so low that a single $500 order triggers a massive Z-score.

Average Trade Size ($)

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The average USD value per single trade execution in this rolling window. Also referred to internally as raw Intensity. High absolute values indicate institutional-sized orders are hitting the book.

UI field: Average Trade Size ($)

Suggested floor: > $500

Calculation
(Accumulated Volume + Live Tick Volume) / (Accumulated Trades + Live Tick Trades)
Range / Units
$ (Quote currency).
Interpretation
If a coin has $1M in volume and 10,000 trades, the average trade size is $100 (retail). If it has $1M in volume and 50 trades, the average size is $20,000 (institutional).
Trading Application
Set a minimum floor (e.g., > $1,000) to filter out bot-driven wash trading or low-tier retail chop, ensuring that the volume you are seeing is backed by meaningful capital.
Common mistakes
  • Using this filter on very cheap meme coins without adjusting expectations (meme coin 'whales' trade smaller absolute sizes than BTC whales).

Intensity Ratio (%)

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Compares the current average trade size to the historical baseline for this asset. It tells you if the current market participants are trading heavier size than usual.

UI field: Intensity Ratio

Suggested floor: > 150%

Calculation
(Current Average Trade Size / Historical Average Trade Size) × 100
Range / Units
%.
Interpretation
A value of 200% means the average trade executing right now is twice as large as the coin's historical norm.
Trading Application
This normalizes trade size across different assets. A $5,000 trade size might be 'normal' (100% ratio) for Bitcoin, but a massive anomaly (500% ratio) for a small-cap altcoin. High values signal sudden institutional interest.
Common mistakes
  • Assuming a high Intensity Ratio means price will go up. Intensity tracks size, not direction. A massive dump also triggers high intensity.

Intensity Z-Score (The Whale Score)

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The crown jewel of the AnomIQ scanner. This is the primary Whale Detector. It mathematically isolates situations where volume is exploding but the actual number of people trading is not.

UI field: Intensity Z-Score (Whale Score)

Suggested floor: > 2.0

Calculation
Volume Z-Score - Trade Count Z-Score
Range / Units
Z (Difference in Standard Deviations).
Interpretation
Positive values (> 2.0) mean volume is rising much faster than the trade count (Whales). Negative values mean trade count is rising much faster than volume (Retail FOMO/Bots).
Trading Application
Combine an Intensity Z-Score > 2.5 with a Current Buy Volume Ratio > 65%. This guarantees you are detecting a massive, one-sided institutional buy wall, filtering out retail noise entirely.
Common mistakes
  • Trading negative Intensity Z-Scores thinking it's a breakout. Negative values mean high retail participation, which often acts as exit liquidity for smart money.

Current Window Volatility (%)

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Measures the high-low price spread relative to the open price for this specific rolling timeframe. It acts as a primary indicator of market 'choppiness' and execution risk.

UI field: Current (TimeFrame) Volatility

Suggested floor: > 0.3%

Calculation
((Maximum High - Minimum Low) / Open Price) × 100
Range / Units
%.
Interpretation
A high volatility percentage means the price is violently whipping up and down within the rolling window, creating massive wicks.
Trading Application
Use this as a safety filter. Setting Volatility < 2.0% on a 5-minute scanner ensures you don't receive alerts for coins that are violently wicking out buyers and sellers, protecting your stop-losses from slippage.
Common mistakes
  • Scanning for high volatility without realizing the spread will destroy your market execution fills.