Nadaraya-Watson Envelope [Dynamic Adaptive Working]

24 Okt

LuxAlgo'a kernel channel-based, modified for dynamic stochastic bandwidth adaptation.
Nadaraya-Watson Envelope [Dynamic Adaptive Working], "NWE Adaptive (Working)"

29 Okt

Catatan Rilis

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1 Nov

Catatan Rilis

NWE Adaptive — Modified Nadaraya–Watson Envelope: Squeeze + Gradient Longs
NWE Adaptive (Bool Fix, Relaxed Touch)
Author: © lfu

NWE Adaptive represents a next-generation evolution of the Nadaraya–Watson Envelope, engineered for adaptive volatility intelligence, structural breakout anticipation, and regime-aware long entry detection.
This variant integrates volatility-adjusted kernel regression, relaxed touch logic, and gradient-based trend confirmation within a unified nonparametric smoothing framework.

Core Innovations:

Adaptive Bandwidth (h) dynamically scales using volatility and empirical Hurst feedback loops.

Relaxed Touch Memory System tracks lower-band proximity over multiple bars, allowing delayed breakout detection without signal loss.

Squeeze Analytics quantifies volatility compression through real-time width z-scores, enhancing breakout timing.

Gradient-Weighted Scoring Engine fuses slope, width momentum, and volume confirmation into a normalized signal probability metric.

Boolean-Safe Signal Logic eliminates false positives from Pine’s implicit na coercion issues.

This design prioritizes signal stability, low-latency trend response, and robust performance under volatile or fragmented data environments.
Ideal for volatility breakout, accumulation detection, and adaptive long bias confirmation in discretionary and automated systems.

Strategic Framework Overview

Signal Trigger: Long entries occur when price interacts with the lower band under compression, followed by a bullish engulfing pattern and gradient confirmation.

Adaptive Control: Bandwidths (h) and multipliers evolve via stochastic relaxation under Hurst–volatility coupling.

Scoring Model: Squeeze, slope, width expansion, and volume dynamics form a composite signal probability between 0 and 1.

Use Case: Detects imminent expansions post-volatility compression; ideal for pre-breakout long filtering or composite signal fusion in multi-factor systems.

Not a financial advice. DYOR.