4- Engine Operation
Structure Tags
This page provides a brief overview of the available structure tags and their significance in market structure analysis.
Purpose
Structure tags are essential for categorizing market structure phases and identifying key behavioral traits like Breaks of Structure (BoS) and Liquidity Interactions (LQ). These tags provide consistent, data-driven insights into market behavior, making them a core component of Structure Lab’s statistical analysis.
Why Structure Tags Matter
Identify Market Phases: Tags segment the market into repeatable phases (A, B, C, D), allowing traders to anticipate shifts in price behavior.
Highlight Behavioral Traits: BoS tags reveal trend shifts, while LQ tags indicate liquidity events, providing context for price action.
Ensure Consistency in Data Mining: The accuracy of your analytics depends on structured, mechanical tagging.
Garbage In, Garbage Out: If tags are applied inconsistently, the statistical insights become less reliable, reducing the effectiveness of data-driven decision-making.
Types of Structure Tags & Their Significance
1. Phase Tags (A, B, C, D)
Recall from the previous Phases section, market movements unfold in a structured sequence of phases, each representing a distinct behavioral characteristic (refer to the Phase Map):
Phase A → Direction is aligned with both swing and internal structure.
Phase B → Direction is aligned with swing structure but against internal structure.
Phase C → Direction is counter (against) swing structure but aligned with internal structure.
Phase D → Direction is against both swing and internal structure.
✅ Proper phase tagging helps traders quantify market behavior and anticipate future movements with higher probability.
2. Break of Structure (BoS & iBoS) Tags
A Break of Structure (BoS) occurs when price breaks a previously established swing high or low, signaling either continuation or reversal in market direction.
BoS (Swing Break of Structure): Identifies breaks of swing structure, marking significant directional shifts.
iBoS (Internal Break of Structure): Identifies breaks of internal structure, revealing smaller price shifts within the larger swing structure.
Market Profiling with BoS & iBoS
BoS and iBoS tags help profile market phases by identifying how often structure breaks within each phase.
Some phases (e.g., A, C) may tend to break structure frequently, suggesting strong momentum.
Other phases (e.g., B, D) may rarely break structure, indicating a pullback before the next price run.
By tagging BoS and iBoS consistently, traders can quantify the probability of structure breaks within each phase, refining entry and exit decisions.
3. Liquidity Interaction (LQ)
Liquidity Interaction (LQ) tags help traders profile how different market phases behave by identifying whether liquidity interactions tend to initiate or terminate specific phases of market structure.
Some phases may frequently begin with liquidity grabs, signaling the start of a new market cycle.
Other phases may end with liquidity sweeps, indicating exhaustion before a reversal or continuation.
LQ tags allow traders to quantify these behaviors over time, uncovering repeatable liquidity patterns that can refine trade timing.
Why This Matters
✅ Phase Profiling – Does a particular phase (A, B, C, or D) tend to start or end with liquidity sweeps? LQ tags help answer this.
✅ Improved Trade Filtering – If a high-probability phase consistently begins with a liquidity event, traders can fine-tune their entries.
✅ Enhanced Statistical Insights – Structure Lab’s analytics become more powerful when liquidity interactions are tagged with precision, revealing market tendencies beyond standard price action patterns.
🚀 Using LQ tags mechanically, traders shift from subjective guessing to data-driven market behavior profiling, reinforcing a true statistical edge.
Key Principles for Using Structure Tags Effectively
✅ Consistency is Key – Always apply tags based on objective, mechanical rules to ensure accurate and reliable analytics.
✅ Stick to the Framework – Structure tags are most effective when mapped using repeatable, systematic methods.
✅ Data Accuracy Matters – "Garbage in, garbage out." If tags are applied inconsistently, the predictive analytics lose accuracy, making the insights unreliable.
📊 By properly tagging market structure, Slab users gain a powerful statistical edge, allowing them to identify high-probability trade setups with confidence.
