Jurik Moving Average

🧠 Jurik Moving Average (JMA) — Ultra-Smooth Adaptive Trend Filter
This indicator implements a precise non-repainting recreation of the Jurik Moving Average (JMA) — a high-performance smoothing algorithm known for its ability to reduce lag while preserving rapid response to price changes. It is ideal for traders seeking a responsive yet stable line for trend detection, dynamic support/resistance, or signal generation.

⚙️ Core Functionality
At its heart, this indicator replicates the JMA logic as described in the original Jurik documentation, including:

✅ Adaptive smoothing based on price volatility.

✅ Variable phase shifting for forward/backward displacement.

✅ Power curve smoothing for dynamic control over responsiveness vs. smoothness.

✅ Volatility-aware band generation (optional).

The core algorithm uses a Kalman-style recursive filter with dynamic coefficients, adjusting to market conditions in real-time. Unlike traditional MAs (EMA, WMA, etc.), this implementation uses:

A volatility-normalized momentum engine to track price deviation (Kv factor).

A recursive double-smoothing mechanism for noise suppression without lag.

📈 Inputs
Length: Controls the base smoothing period.

Phase Shift: Moves the curve forward or backward in time (−100 to +100), for signal anticipation or lag removal.

Smoothing Power: Adjusts the sensitivity to price changes. Higher = smoother, lower = faster reaction.

Source: Any input (close, hl2, etc.) to apply the filter on.

Bands (optional): Dynamically generated adaptive envelopes based on real-time volatility.

🎯 How to Use
Use the JMA line as a trend-following tool or dynamic support/resistance.

Apply crossovers with price or other indicators for entries/exits.

Enable the bands to observe overbought/oversold zones or potential breakout areas.

Adjust phase to suit leading (anticipatory) or lagging (confirmation) strategies.

This tool is particularly suitable for:

Scalpers looking for precision in fast markets.

Swing traders filtering noise from signals.

Algorithmic systems needing high-fidelity moving averages.