Lux Algo
- インディケータ
- Mahmoud Ahmed Abdou Ali
- バージョン: 10.20
- アップデート済み: 25 2月 2026
- アクティベーション: 5
This system is a Self-Optimizing Algorithmic Framework. Unlike static indicators, it uses a Recursive Feedback Loop to "learn" the current market regime and adjust its sensitivity in real-time.
Because it calculates every step based solely on current and past data, it is a Real-Time Model with no repainting, no bias, and no lookahead.
How the "AI" Operates
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Performance-Based Learning: The system constantly "grades" its own accuracy. If the market is trending cleanly, it increases its sensitivity; if the market becomes noisy or choppy, it automatically dampens its signals to avoid false entries.
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Adaptive Filtering: Instead of a fixed timeframe (like a 20-period average), the internal Moving Average acts as a Variable Learning Rate. It "speeds up" to catch breakouts and "freezes" to ignore market noise.
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Multi-Feature Classification: Before a signal is fired, the system must pass a "Logic Gate" that checks four distinct market features: Trend Strength, Volatility Squeeze, Volume Sentiment, and Momentum Bias.
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Statistical Extremes: It uses mathematical constants (like $\pi$ and the Golden Ratio) to project "Reversal Zones." These act as probabilistic boundaries to identify when a price move has reached a mathematical exhaustion point.
The Bottom Line
This is an Autopilot System that performs continuous Hyperparameter Tuning. It doesn't just follow price; it analyzes the efficiency of the price movement to decide how much to trust the next signal.
