ICT Sigma Hybrid FVG

This indicator combines three analytical components—statistical volatility modeling, ICT imbalance logic, and higher-timeframe bias filtering—to help traders interpret displacement-driven price inefficiencies. The goal is to reduce noise and highlight only meaningful FVGs that occur with sufficient volatility and directional context.

Sigma Volatility Zones

The script calculates statistically normalized deviation levels using a multi-regime standard deviation blended with ATR.
This produces adaptive volatility zones that:

Expand during trending or high-volatility periods
Contract during consolidation
Highlight extremes more accurately than fixed standard deviations

These zones help users identify where price is operating in premium/discount relative to recent volatility.

Fair Value Gaps With Displacement Scoring

Every potential FVG is evaluated using a displacement score based on candle body expansion, wick displacement, and relative move efficiency. FVGs that do not exceed the minimum score are filtered out. This ensures the script only displays gaps associated with meaningful movement, not minor pricing noise.

Optional Higher-Timeframe Bias Filter

The HTF bias engine evaluates structure using selected higher-timeframe EMAs.
When enabled, the indicator:

Shows bullish FVGs only in bullish higher-timeframe conditions
Shows bearish FVGs only in bearish conditions
Hides counter-trend FVGs that may have lower reliability
Users may disable this to see all qualifying gaps regardless of bias.

ATR-Adaptive Volatility Conditioning

ATR is blended into the model so the displacement score and sigma zones adjust automatically to sudden volatility changes such as:

Major economic releases
Earnings
High-impact market events
Overnight volatility shifts

This helps maintain consistent FVG quality during rapidly changing conditions.

How to Use the Indicator:

Use sigma levels to understand whether price is extended or discounted relative to recent volatility.

Monitor FVGs that appear within or near sigma extremes to identify potential exhaustion or continuation zones.

Combine HTF bias with LTF displacement gaps to align intraday entries with broader directional flow.

ATR-adjusted scoring helps distinguish between meaningful inefficiencies and low-quality gaps.

Example 1 — Intraday Sigma Expansion & Displacement FVG Reaction


Figure 1. Price collapses from a 4.5σ extreme during a volatility expansion event.
Only high-impact FVGs are shown due to the displacement filter, removing low-quality gaps.
Sigma bands expand dynamically as volatility increases, illustrating how the model adapts automatically.

Example 2 — Higher-Timeframe Sigma Compression After a Major Trend Leg


Figure 2. After a large macro move, sigma levels compress tightly, forming a volatility cluster.
These HTF sigma zones later act as reaction levels during continuation.
This demonstrates why the model blends HTF sigma structure with LTF displacement gaps for alignment.

Recommended Settings

Standard deviation lookback: 100

ATR length: 50

ATR blend weight: 0.5

Minimum Z-score: 1.8

Sigma levels: 1.5 / 3 / 4.5

HTF bias: Daily (optional)

FVG displacement filter: On