Nadaraya-Watson Envelope & ATR & CE & EMA - Step 1

📈 Multi-Layered Trend and Reversal Toolkit

🧠 Why These Components Are Combined
This closed-source script integrates four distinct yet complementary logic modules for a complete trend and reversal assessment:

Nadaraya-Watson Envelope: Applies kernel smoothing to model dynamic price envelopes.

ATR-based Zones: Provide adaptive buffer zones for reversal or take-profit planning.

Chandelier Exit (CE): Tracks trend direction changes based on recent price extremes and volatility.

Multi-EMA Channels: Help identify macro trend bias and potential entry zones.

Each module contributes a unique market context layer: trend bias, price expansion, breakout timing, and adaptive risk control.

🔍 Key Modules Overview
📐 1. Nadaraya-Watson Envelope (NWE)
Estimates high/low zones with Gaussian regression.

Supports both repaint and non-repaint modes.

Arrows (▲▼) appear when price crosses envelope boundaries.

📊 2. ATR Stop Zones
Uses smoothed volatility to display dynamic high/low thresholds.

Displays a data table for traders to reference stop zone values.

Smoothing methods selectable via menu.

🎯 3. Chandelier Exit
Highlights trend reversals using a volatility-based trailing mechanism.

Displays Buy/Sell labels when state changes occur.

Filled areas change color depending on regime (bull/bear).

📶 4. EMA Trend Channels
Four adaptive EMAs help filter trend directions.

Serves as a higher-timeframe guide or squeeze detector.

⚙️ Suggested Use Cases
Confirm NWE breakouts with EMA slope alignment.

Combine CE labels with ATR zones for risk-aware entries/exits.

Use alerts for direction change to build semi-automated systems.

✅ Originality Statement
This script is not a superficial mashup. It offers a unified framework integrating statistical, trend, and volatility analysis into a practical, modular tool. Each module can be enabled/disabled independently for strategy adaptation.

⚠️ Disclaimer
For educational and research purposes only. Not financial advice. Use at your own risk.