Overview
Trade Count Ratio applies the same normalization as Volume Ratio but uses the number of trades instead of volume:
Trade Count Ratio = (buyTrades - sellTrades) / (buyTrades + sellTrades)
The result ranges from -1 (all trades are sells) to +1 (all trades are buys). This reveals whether directional activity is driven by many participants or a few large players.
How It Works
While Volume Ratio tells you the magnitude of buying vs selling, Trade Count Ratio tells you the breadth. A high Volume Ratio with a low Trade Count Ratio means a small number of large orders are driving the imbalance — likely institutional activity.
This distinction is critical for understanding the nature of market moves:
- High trade count + high volume — Broad-based move with strong conviction
- Low trade count + high volume — Few large players driving the move
- High trade count + low volume — Many small participants, retail-dominated
Interpretation
| Scenario | Volume Ratio | Trade Count Ratio | Meaning |
|---|
| Institutional buying | High positive | Near zero or low | Few large buy orders |
| Retail panic selling | Near zero | High negative | Many small sell orders |
| Broad-based rally | High positive | High positive | Everyone buying |
| Institutional distribution | Near zero or negative | Near zero | Large sells absorbed by retail buys |
Compare Trade Count Ratio with Volume Ratio side by side. When trade count shows buying but volume shows selling, large sellers are disguising their activity among many small retail buys.
Settings
| Parameter | Description | Default |
|---|
positiveColor | Color for positive (buy-dominant) bars | #22c55e |
negativeColor | Color for negative (sell-dominant) bars | #ef4444 |
displayMode | Visualization style: line, columns, or candles | columns |
highlightAnomalies | Highlight statistically unusual readings | true |
anomalyThreshold | Standard deviations for anomaly detection | 2.5 |
anomalyPeriod | Lookback period for anomaly calculation | 30 |
gradientIntensity | Scale bar opacity by value magnitude | true |
Display Modes
- Columns — Default histogram view. Best for quick visual scanning.
- Line — Continuous line connecting ratio values. Good for identifying trends.
- Candles — OHLC representation of ratio values per bar.
Anomaly Detection
When highlightAnomalies is enabled, bars that deviate more than anomalyThreshold standard deviations from the rolling mean are visually highlighted. Anomalies in trade count ratio often indicate:
- Flash crash or flash rally events
- Coordinated bot activity
- Sudden shift in market participant composition
Gradient Intensity
With gradientIntensity enabled, bar opacity scales proportionally to the absolute ratio value. Near-zero readings fade out, keeping your focus on meaningful imbalances.
Trade Count Ratio is most informative on lower timeframes (1m–15m) where individual trade granularity is preserved. On higher timeframes, aggregation dilutes the signal.
Practical Examples
Detecting Iceberg Orders: Price drops sharply, Trade Count Ratio is near zero (few trades), but Volume Ratio is very negative — a single large seller using iceberg orders.
Retail FOMO Detection: After a breakout, Trade Count Ratio spikes to extreme positive while Volume Ratio is moderate — many small buyers chasing the move.
Smart Money Accumulation: Trade Count Ratio oscillates near zero while price slowly grinds up and Volume Ratio trends positive — large players accumulating quietly.