Volume Intelligence

Volume-flow analysis across supported pair-timeframe combinations, using the Institutional Intent Score (IIS) from 0–100 as model context. High-IIS readings indicate notable volume conditions for review; they do not reveal intent, forecast direction, or establish a recommendation.

What this page covers

• What the Institutional Intent Score (IIS) measures and how it's calculated
• How to read Multi-TF Volume Confluence as analytical context
• The 5 Smart Volume Patterns and what each means
• How to build and use your AI Watchlist for 24/7 monitoring

Institutional Intent Score (IIS)

The IIS is the core metric of the Volume Intelligence system. It is a 0–100 composite score summarizing volume, price response, timing, and related model inputs; it does not identify participant intent or distinguish institutions from other activity.

An IIS score is a model output for comparison. It does not forecast a direction, establish a threshold for action, or prove that a large participant acted. Review phase, pattern, session, and source-data context separately.

How IIS Is Calculated

The IIS is built from 6 sub-scores, each weighted differently:

IIS Score Interpretation

Multi-TF Volume Confluence Detector

The MTF Confluence Detector identifies volume anomalies that appear simultaneously on two or more timeframes for the same pair.

When a volume event is visible on the 15m, the 1H, AND the 4H simultaneously, it means institutions are executing large enough orders to leave a footprint across multiple chart resolutions. This is the signature of major positioning — not a minor allocation.

Smart Volume Patterns

• Absorption

  High volume with limited price movement. This label describes a volume/price relationship for comparison; it does not establish who acted or forecast a reversal.

• Volume Climax

  A large volume reading near a structural level. Review subsequent candles as retrospective context rather than treating the label as proof of exhaustion.

• Breakout Volume

  Volume above a recent average during a structural break. Compare the reading with later price behavior; it does not confirm participation or persistence.

• Delta Divergence

  The difference between buy-initiated and sell-initiated volume. Positive delta (more buying) on a bearish candle = hidden demand. Negative delta (more selling) on a bullish candle = hidden supply. These divergences often precede reversals.

• Volume Velocity

  The rate of volume change over the last 3–5 candles. A rising velocity label marks an observation for review and does not forecast action at a level.

AI Watchlist

Your AI Watchlist is a personalized monitoring list of up to 12 pairs. When a pair generates a configured volume or MTF reading, the system can display or deliver the selected notification; thresholds are user-defined filters, not recommendations.

1. Open Volume Intelligence

   Navigate to Volume Intelligence from the Market Intelligence section of the sidebar.

2. Browse the pair matrix

   The main view shows all 31 supported pairs as a matrix with IIS scores per timeframe. Red cells = high IIS. Click any cell for details.

3. Add to watchlist

   Click the star icon next to any pair to add it to your AI Watchlist. Choose a display or notification filter that suits your study process.

4. Configure delivery

   In Watchlist Settings, choose which alert types trigger Telegram notifications and which stay in-app only.

Volume-First Study Checklist

Use this checklist to document volume observations before comparing them with other model readings. It is a paper-study framework, not a trade filter or threshold.

1. Record the model score

   Open Volume Intelligence for the selected pair and timeframe and record the IIS alongside its component readings. Do not treat a numerical score as an approval threshold.

2. Compare direction labels

   Compare any displayed bullish or bearish volume label with price and timeframe context. The label is a classification, not an entry or position instruction.

3. Identify the pattern label

   Record whether the engine displayed Absorption, Breakout, Climax, or another pattern, then compare the label with surrounding candles and alternative explanations.

4. Compare timeframes

   Note whether the anomaly appears on multiple timeframes and whether the readings agree. Multi-timeframe agreement is an observation, not proof or a reliability ranking.

5. Record session context

   Note whether the volume reading occurred during a configured session window, then compare historical examples without inferring that timing improves outcomes.

IIS Score Reference

The IIS is a 0–100 model output. These ranges describe how the interface groups readings for display; they are not action thresholds, institutional classifications, or forecasts:

📊 VOLUME ANOMALY DETECTED
⏰ 09:43 UTC | Kill Zone: ACTIVE

📍 XAUUSD — 1H Timeframe
   IIS Score: 87/100 ████████░░  ← VERY HIGH
   Pattern: Absorption (Buy-initiated)
   Delta: +68% buy pressure dominant
   Volume: 3.4× 20-period average

 🔬 MODEL CONTEXT:
    ✓ Spread: Tight (6 pips — displayed observation)
    ✓ Session: London-NY overlap (configured study window)
    ✓ MTF: Anomaly displayed on 1H + 4H simultaneously
   ✓ Level: Near Volume Profile VAL ($2,291)
   ✗ Historical precedent: Moderate (not a recurrent level)

 🤖 AI CONTEXT:
    "The model labels a volume/price relationship near
     the $2,291 VAL. Compare the high buy-initiated volume
     and tight spread with later candles; this label does
     not identify participants or forecast a move."

🔗 View full analysis → Volume Intelligence