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Deca-Oscillator Ultra Suite
Deca-Oscillator Ultra Suite
The Multi-Heuristic Consensus Framework
In modern algorithmic trading, the reliance on a single technical oscillator often leads to "analysis paralysis" or, conversely, frequent false signals due to indicator lag and market noise. The Deca-Oscillator Ultra Suite addresses these inefficiencies by utilizing a Multi-Heuristic Consensus Framework. This model synthesizes ten independent mathematical oscillators into a singular, normalized composite score, providing a high-fidelity view of market momentum.
Mathematical Foundation
1. Linear Feature Normalization
To integrate disparate oscillators (e.g., CCI ranging from -300 to +300 vs. RSI ranging from 0 to 100), the engine applies a Min-Max scaling algorithm to every internal component. This ensures that every indicator contributes to the final score within a standardized 0–100 probability space.
[math]N(x) = 100 * \frac{x - min(x)}{max(x) - min(x)}[/math]*
2. Weighted Composite Calculation
The final composite score (C) is derived from a weighted arithmetic mean of the normalized inputs. The weightings allow the model to prioritize historically reliable metrics like the RSI and Fisher Transform over more volatile indicators.
[math]C = \frac{\sum_{i=1}^{10} (w_i \cdot N(o_i))}{\sum_{i=1}^{10} w_i}[/math]
3. Consensus Logic (k-Agreement)
Beyond simple crossovers, the signal engine employs a k-agreement filter. A signal is only validated if the number of primary components agreeing with the direction meets the required threshold.
[math]Consensus \ge n[/math]
The Ten Core Components
This suite does not just average values; it analyzes market state through ten distinct lenses:
RSI: Standard momentum relative to price change.
MFI: Volume-weighted momentum (Money Flow).
Stochastic: Position of current price relative to the high-low range.
CCI: Statistical deviation from the average.
Williams %R: Inverse momentum for extreme overbought/oversold detection.
ROC: Pure velocity of price change.
Bull/Bear Power: Interaction between high/low and EMA.
Awesome Oscillator: Comparison of short-term and long-term momentum.
Momentum: Simple price-distance velocity.
Fisher Transform: Transforming price distributions into Gaussian normal distributions.
Visual Architecture
High-Contrast Theme: Features Blue (Bullish) and White (Bearish) for optimal visibility on dark-themed charts.
Precision Matrix: A real-time dashboard displaying the consensus of internal components, the HTF trend state, and the total composite score.
Heuristic Divergence: Automates pivot detection to draw momentum-price divergence lines, signaling potential exhaustion before price action confirms the reversal.
Reply below with comments, critiques, or criticisms. All is welcome!
The Multi-Heuristic Consensus Framework
In modern algorithmic trading, the reliance on a single technical oscillator often leads to "analysis paralysis" or, conversely, frequent false signals due to indicator lag and market noise. The Deca-Oscillator Ultra Suite addresses these inefficiencies by utilizing a Multi-Heuristic Consensus Framework. This model synthesizes ten independent mathematical oscillators into a singular, normalized composite score, providing a high-fidelity view of market momentum.
Mathematical Foundation
1. Linear Feature Normalization
To integrate disparate oscillators (e.g., CCI ranging from -300 to +300 vs. RSI ranging from 0 to 100), the engine applies a Min-Max scaling algorithm to every internal component. This ensures that every indicator contributes to the final score within a standardized 0–100 probability space.
[math]N(x) = 100 * \frac{x - min(x)}{max(x) - min(x)}[/math]*
2. Weighted Composite Calculation
The final composite score (C) is derived from a weighted arithmetic mean of the normalized inputs. The weightings allow the model to prioritize historically reliable metrics like the RSI and Fisher Transform over more volatile indicators.
[math]C = \frac{\sum_{i=1}^{10} (w_i \cdot N(o_i))}{\sum_{i=1}^{10} w_i}[/math]
3. Consensus Logic (k-Agreement)
Beyond simple crossovers, the signal engine employs a k-agreement filter. A signal is only validated if the number of primary components agreeing with the direction meets the required threshold.
[math]Consensus \ge n[/math]
The Ten Core Components
This suite does not just average values; it analyzes market state through ten distinct lenses:
RSI: Standard momentum relative to price change.
MFI: Volume-weighted momentum (Money Flow).
Stochastic: Position of current price relative to the high-low range.
CCI: Statistical deviation from the average.
Williams %R: Inverse momentum for extreme overbought/oversold detection.
ROC: Pure velocity of price change.
Bull/Bear Power: Interaction between high/low and EMA.
Awesome Oscillator: Comparison of short-term and long-term momentum.
Momentum: Simple price-distance velocity.
Fisher Transform: Transforming price distributions into Gaussian normal distributions.
Visual Architecture
High-Contrast Theme: Features Blue (Bullish) and White (Bearish) for optimal visibility on dark-themed charts.
Precision Matrix: A real-time dashboard displaying the consensus of internal components, the HTF trend state, and the total composite score.
Heuristic Divergence: Automates pivot detection to draw momentum-price divergence lines, signaling potential exhaustion before price action confirms the reversal.
Reply below with comments, critiques, or criticisms. All is welcome!
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.