OPEN-SOURCE SCRIPT
Laguerre Timeframe Oscillator
Laguerre Timeframe Breadth Oscillator
Multi-timeframe × multi-gamma Laguerre breadth model
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Usage Notes
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• This is a regime & consensus indicator, not a trigger
• Best used for trend validation and risk filtering
• Extreme values tend to persist during strong regimes
This indicator answers a single question:
“Out of 198 independent Laguerre filters, how many are currently rising?”
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Concept
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Using Laguerre polynomials, we aggregate price behavior across:
• 11 explicit timeframes (1-minute → 1-day)
• 18 gamma responsiveness levels (0.10 → 0.95)
This produces 198 independent Laguerre curves.
The final oscillator is NOT price.
It represents a directional consensus across timescales and smoothing sensitivities.
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Laguerre Filter Mathematics
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For each Laguerre line i:
L0ᵢ(t) = (1 − γᵢ) · x(t) + γᵢ · L0ᵢ(t−1)
L1ᵢ(t) = −γᵢ · L0ᵢ(t) + L0ᵢ(t−1) + γᵢ · L1ᵢ(t−1)
L2ᵢ(t) = −γᵢ · L1ᵢ(t) + L1ᵢ(t−1) + γᵢ · L2ᵢ(t−1)
L3ᵢ(t) = −γᵢ · L2ᵢ(t) + L2ᵢ(t−1) + γᵢ · L3ᵢ(t−1)
Smoothed output:
Yᵢ(t) = ( L0ᵢ + 2·L1ᵢ + 2·L2ᵢ + L3ᵢ ) / 6
This weighted sum smooths noise while preserving phase better than a traditional EMA.
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Gamma Responsiveness
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Gamma controls responsiveness vs stability:
0.10 — Very fast, noisy
0.40 — Momentum-sensitive
0.70 — Trend-stable
0.95 — Very slow, structural
Each timeframe is evaluated across all gamma levels.
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Timeframes Used (11)
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Minutes: 1, 3, 5, 10, 15, 30, 45
Hours: 1, 2, 4
Days: 1
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Direction Test
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Each Laguerre line votes “up” or “down”:
Iᵢ(t) = 1 if Yᵢ(t) > Yᵢ(t−1)
Iᵢ(t) = 0 otherwise
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Breadth Calculation
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greenCount(t) =
I₁(t) + I₂(t) + I₃(t) + … + I₁₉₈(t)
Total number of rising Laguerre filters.
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Centered Breadth Oscillator
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oscRaw(t) = greenCount(t) − 99
(99 = half of 198; zero represents balanced breadth)
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Smoothing & Amplification
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EMA smoothing:
oscSmooth(t) = EMA₁₀₀(oscRaw)
Extreme emphasis:
oscExtreme(t) = 2 · oscSmooth(t)
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Clamped Final Output
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osc(t) = max( −99 , min( 99 , oscExtreme(t) ) )
Range:
• −99 → all filters falling
• 0 → mixed / neutral
• +99 → all filters rising
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Optional Probabilistic Interpretation
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p(t) = greenCount(t) / 198
Interpretable as the probability of upward directional alignment.
Reach out on Discord if you need further guidance. - Coño Vista
Multi-timeframe × multi-gamma Laguerre breadth model
────────────────────────
Usage Notes
────────────────────────
• This is a regime & consensus indicator, not a trigger
• Best used for trend validation and risk filtering
• Extreme values tend to persist during strong regimes
This indicator answers a single question:
“Out of 198 independent Laguerre filters, how many are currently rising?”
────────────────────────
Concept
────────────────────────
Using Laguerre polynomials, we aggregate price behavior across:
• 11 explicit timeframes (1-minute → 1-day)
• 18 gamma responsiveness levels (0.10 → 0.95)
This produces 198 independent Laguerre curves.
The final oscillator is NOT price.
It represents a directional consensus across timescales and smoothing sensitivities.
────────────────────────
Laguerre Filter Mathematics
────────────────────────
For each Laguerre line i:
L0ᵢ(t) = (1 − γᵢ) · x(t) + γᵢ · L0ᵢ(t−1)
L1ᵢ(t) = −γᵢ · L0ᵢ(t) + L0ᵢ(t−1) + γᵢ · L1ᵢ(t−1)
L2ᵢ(t) = −γᵢ · L1ᵢ(t) + L1ᵢ(t−1) + γᵢ · L2ᵢ(t−1)
L3ᵢ(t) = −γᵢ · L2ᵢ(t) + L2ᵢ(t−1) + γᵢ · L3ᵢ(t−1)
Smoothed output:
Yᵢ(t) = ( L0ᵢ + 2·L1ᵢ + 2·L2ᵢ + L3ᵢ ) / 6
This weighted sum smooths noise while preserving phase better than a traditional EMA.
────────────────────────
Gamma Responsiveness
────────────────────────
Gamma controls responsiveness vs stability:
0.10 — Very fast, noisy
0.40 — Momentum-sensitive
0.70 — Trend-stable
0.95 — Very slow, structural
Each timeframe is evaluated across all gamma levels.
────────────────────────
Timeframes Used (11)
────────────────────────
Minutes: 1, 3, 5, 10, 15, 30, 45
Hours: 1, 2, 4
Days: 1
────────────────────────
Direction Test
────────────────────────
Each Laguerre line votes “up” or “down”:
Iᵢ(t) = 1 if Yᵢ(t) > Yᵢ(t−1)
Iᵢ(t) = 0 otherwise
────────────────────────
Breadth Calculation
────────────────────────
greenCount(t) =
I₁(t) + I₂(t) + I₃(t) + … + I₁₉₈(t)
Total number of rising Laguerre filters.
────────────────────────
Centered Breadth Oscillator
────────────────────────
oscRaw(t) = greenCount(t) − 99
(99 = half of 198; zero represents balanced breadth)
────────────────────────
Smoothing & Amplification
────────────────────────
EMA smoothing:
oscSmooth(t) = EMA₁₀₀(oscRaw)
Extreme emphasis:
oscExtreme(t) = 2 · oscSmooth(t)
────────────────────────
Clamped Final Output
────────────────────────
osc(t) = max( −99 , min( 99 , oscExtreme(t) ) )
Range:
• −99 → all filters falling
• 0 → mixed / neutral
• +99 → all filters rising
────────────────────────
Optional Probabilistic Interpretation
────────────────────────
p(t) = greenCount(t) / 198
Interpretable as the probability of upward directional alignment.
Reach out on Discord if you need further guidance. - Coño Vista
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Skrip sumber terbuka
Dalam semangat TradingView sebenar, pencipta skrip ini telah menjadikannya sumber terbuka, jadi pedagang boleh menilai dan mengesahkan kefungsiannya. Terima kasih kepada penulis! Walaupuan anda boleh menggunakan secara percuma, ingat bahawa penerbitan semula kod ini tertakluk kepada Peraturan Dalaman.
Penafian
Maklumat dan penerbitan adalah tidak bertujuan, dan tidak membentuk, nasihat atau cadangan kewangan, pelaburan, dagangan atau jenis lain yang diberikan atau disahkan oleh TradingView. Baca lebih dalam Terma Penggunaan.