FeraTrading Compression Indicator v1.2

A directional compression breakout filter that visualizes high-probability breakout potential through minimalistic arrow signals based on range contraction, volatility bursts, and momentum alignment.

🧠 Overview:
The FeraTrading Compression Indicator v1.2 identifies moments where price action has compressed and a directional breakout is likely to occur. It focuses on early-stage moves by waiting for volatility to drop, then confirming momentum through strong candle bodies and EMA alignment.

Compared to full-band compression tools, this version delivers simple, clean arrow signals. Optional session filtering ensures alerts only trigger during high-volume market windows. It uses relative volatility, burst confirmation, and momentum filters to cut through noise and highlight meaningful breakout opportunities.

⚙️ How It Works:
The indicator detects compression by comparing short-term vs. long-term candle ranges. It then waits for a range expansion, which signals breakout pressure.

Once compression and burst are confirmed, it filters the signal using:

EMA alignment (fast vs. slow)

Strong-bodied candle (real momentum)

Optional time filter (NY session only)

If all conditions align:

A green arrow appears for bullish breakout bias

A red arrow appears for bearish breakout bias

🎨 Visual Behavior:
Green Arrows: Bullish breakout detected

Red Arrows: Bearish breakout detected

Session Filter: Limits signals to 08:30–11:30 EST if enabled

⚙️ Inputs:
Input Multiplier: Controls how strict the compression detection is (lower = tighter conditions)

Morning Toggle: Limits signals to NY morning session for added selectivity

📷 Visual Examples:
Bullish Compression Breakout (Green Arrow)


Bearish Compression Breakout (Red Arrow)


Session-Filter On


Session-Filter Off


🔎 Use Case Summary:
This indicator is ideal for traders who want clean directional signals following compression, without the complexity of bands or overlays. It's best suited for breakout entries and directional trades, especially during high-volume hours on lower timeframes like 1–15 min.