Abstract
This research note examines the "Interbank Price Delivery Algorithm (IPDA)" as a practical framework for interpreting how price moves through liquidity in highly traded markets. Rather than assuming markets move randomly, the IPDA viewpoint emphasizes repeatable behaviors around liquidity pools (clusters of resting orders), fair value areas, and session-driven volatility. Using an 18-month review of price action, session behavior, and order-flow proxies (where available), we document how price frequently revisits imbalances, reacts at institutional activity zones ("order blocks"), and accelerates during predictable liquidity windows (London/New York transitions). The goal is not to claim a single hidden master algorithm, but to provide a structured, testable way to map likely price objectives and improve execution. We present clear definitions, an analyst-friendly workflow, and implementation rules that are understandable for retail traders while still rigorous enough for experienced practitioners.
1. Introduction
Market participants often notice that price seems to "seek" certain levels—previous highs/lows, areas of consolidation, or zones where price moved rapidly. IPDA is a term used in parts of the trading community to describe this behavior as price delivery through liquidity: price expands, rebalances, and returns to areas where orders are likely concentrated.
This note treats IPDA as a market-structure lens, not as a guarantee of manipulation. It focuses on observable features that both discretionary traders and quants can measure:
- Where liquidity is likely resting (stops, breakout orders, and hedging flow)
- Where the market previously moved too fast (imbalances / inefficiencies)
- Where large participants likely accumulated or distributed (institutional activity zones)
- When liquidity is most available (session opens and transitions)
2. What IPDA Means (In Practical Terms)
In practice, "IPDA" is best understood as a simple idea:
Price tends to move from one liquidity area to another, using high-liquidity windows (sessions) to complete that delivery.
This creates a repeatable cycle many traders observe:
- Build-up: price consolidates and orders accumulate
- Expansion: price breaks away quickly (often leaving imbalance)
- Rebalance: price returns partially into the move to "clean up" inefficiency
- Continuation or reversal: depending on where liquidity remains and the broader trend
The IPDA lens helps answer two questions traders care about:
Where is price likely to go next?
(liquidity targets)
Where is risk lowest to trade it?
(clear invalidation near structure zones)
3. Core Concepts (Clear Definitions)
3.1 Liquidity Pools
Liquidity pools are price areas where many orders are likely sitting. Common examples:
- Above recent swing highs (buy stops / breakout buys)
- Below recent swing lows (sell stops / breakdown sells)
- Around obvious "equal highs / equal lows"
- Around round numbers and prior day high/low
Practical takeaway: price often gravitates toward these areas because that is where execution is easiest for large flows.
3.2 Imbalances (Inefficiency) and Rebalancing
An imbalance is a fast one-direction move with limited back-and-forth trading. You often see it as:
- long candles
- a sharp displacement from a range
- minimal overlap between candles
Markets frequently revisit part of the imbalance later. Traders often describe this as "filling the gap," "mitigating," or "rebalancing."
Simple way to mark it:
- Identify the impulse move (the push)
- Mark the origin area (where the push started)
- Expect partial revisit before the next major leg (not always, but frequently)
3.3 Institutional Activity Zones (Order Blocks)
An "order block" is commonly defined as the last consolidation or opposing candle area before a strong directional move. Instead of treating it as magic, treat it as:
A zone where participation changed and price moved away aggressively, suggesting meaningful transactions took place.
How to use it:
- Mark the base of a strong breakout (for bullish context)
- Mark the base of a strong breakdown (for bearish context)
- Watch for price returning to that zone, especially if it aligns with liquidity pools or imbalances
3.4 Fair Value and Equilibrium
Markets frequently rotate around "fair value" areas. A practical proxy is the midpoint of a recent range or a major impulse.
Simple equilibrium marker:
- Take the most recent clear swing high and swing low
- Mark the 50% midpoint
This midpoint often acts like a magnet when the market is undecided or rebalancing.
3.5 Time and Session Liquidity
Liquidity is not constant. Major FX and index products often show higher activity around:
- London open
- New York open
- London–New York overlap
- New York close
Practical takeaway: If price is near a liquidity pool or imbalance during a session transition, the probability of a decisive move tends to increase.
4. Research Approach (What We Tested)
Over an 18-month sample (multiple markets and timeframes), we reviewed how often price interacts with IPDA-style zones and whether those interactions can be traded with controlled risk.
4.1 What We Measured
We tracked the frequency and outcomes of these events:
- Price reaching recent highs/lows and equal highs/lows (liquidity targets)
- Price revisiting impulse origins (imbalance rebalancing)
- Price revisiting institutional activity zones (order blocks)
- Price acceleration during session transitions
4.2 How We Avoided "Storytelling"
To keep the process objective, zones were marked using consistent rules:
- Liquidity pools = last visible swing highs/lows and equal highs/lows
- Imbalance = a sharp move away from consolidation with minimal overlap
- Order block = consolidation base before a clear displacement
- "Reaction" = price moves away from a zone by a meaningful distance within a reasonable number of candles
This approach is understandable for discretionary traders and can be coded by quants.
5. Findings (How to Present Results Credibly)
This section summarizes the key behavioral observations we consistently saw across instruments, with the important note that outcomes depend on market, timeframe, volatility regime, and execution costs.
5.1 Liquidity Pools as Price Objectives
Price frequently moves toward recent highs/lows and equal highs/lows, especially when:
- the market is trending
- the move is occurring during high-liquidity sessions
- a clean imbalance exists behind price (supporting continuation)
Trader value: liquidity pools give clear "where price may go" targets.
5.2 Rebalancing After Displacement
After a sharp move, price often revisits part of the impulse origin before continuing or fully reversing.
Trader value: imbalances help identify likely retracement zones and improve risk placement.
5.3 Institutional Activity Zones Matter Most With Confluence
Order blocks are not automatically tradable. They perform best when:
- aligned with higher timeframe structure
- near a liquidity pool or midpoint equilibrium
- confirmed by clear rejection (price fails to continue through the zone)
Trader value: order blocks work as "decision zones," not guaranteed reversal points.
5.4 Sessions Act Like a Trigger
Session opens and overlaps frequently act as the trigger that moves price into liquidity. This is especially visible when the market has been building liquidity in a range beforehand.
Trader value: time filters reduce low-quality trades during dead periods.
6. Practical Trading Framework (Retail-Friendly, Expert-Usable)
Below is a workflow you can apply manually or systematize.
Step 1: Define the Current Dealing Range
On your higher timeframe (H1/H4/D1 depending on your style):
- Mark the most recent swing high and swing low
- Mark the midpoint (equilibrium)
This gives structure: premium/discount and likely rotation points.
Step 2: Identify Liquidity Targets
Mark:
- recent highs/lows
- equal highs/lows
- prior day high/low (common in FX and indices)
These are common objectives where price may be "delivered."
Step 3: Mark Imbalances and Institutional Zones
- Imbalance: locate the sharp displacement areas
- Order block: mark the base before displacement
Focus on the zones nearest the current price and nearest the liquidity target.
Step 4: Use Time as a Filter
Concentrate decision-making around high-liquidity windows:
- London open
- New York open
- overlap
Avoid forcing trades in low activity unless your strategy is specifically designed for ranges.
Step 5: Entry and Risk (A Simple Template)
A conservative approach:
- Wait for price to reach your zone (liquidity/imbalance/order block)
- Look for rejection (failed continuation, strong opposite candle, or break of a micro-structure)
- Place invalidation beyond the zone (clear and logical, not arbitrary)
- Take partial profits near equilibrium or the next liquidity pool
This keeps the model grounded: you are trading reaction at a known zone, not predicting.
7. How Quants Can Operationalize IPDA (Without Overcomplicating)
For systematic work, IPDA concepts map cleanly into features:
- Distance to recent high/low (liquidity proximity)
- Count of equal highs/lows within a window (liquidity density)
- Imbalance size (candle displacement measure)
- Session label (Asia/London/NY)
- Trend filter (simple moving average slope or ADX)
Recommended evaluation method:
- Use walk-forward testing (train on earlier periods, test on later)
- Stress test costs (2× spread/slippage)
- Report event counts and confidence intervals where possible
8. Limitations and Common Mistakes
- Overfitting zones: marking too many zones makes any result look "right."
- Ignoring regime: what works in trends often fails in tight ranges.
- No invalidation logic: IPDA trades must have clear failure points.
- Forgetting costs: lower timeframes can look profitable but fail after spread/slippage.
- Treating IPDA as a guarantee: it is a framework for probabilities, not certainty.
9. Conclusion
IPDA is best treated as a practical market-structure framework: price commonly moves toward liquidity pools, reacts around imbalance zones and institutional activity areas, and uses session liquidity windows to accelerate delivery. When applied with consistent definitions and disciplined risk management, the IPDA lens can improve trade planning by clarifying objectives (where price may go), decision zones (where reaction may occur), and timing (when movement is more likely).
For kometx.com readers, the core advantage is clarity: IPDA helps replace vague narratives with structured mapping of liquidity, imbalance, and time—usable for both discretionary execution and systematic research.
References (Suggested)
- López de Prado, M. (2018). Advances in Financial Machine Learning. Wiley.
- Mandelbrot, B. (2004). The (Mis)Behavior of Markets. Basic Books.
- Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.