OPEN-SOURCE SCRIPT
Laplace Momentum Percentile ║ BullVision

🔬 Overview
Laplace Momentum Percentile ║ BullVision is a custom-built trend analysis tool that applies Laplace-inspired smoothing to price action and maps the result to a historical percentile scale. This provides a contextual view of trend intensity, with optional signal refinement using a Kalman filter.
This indicator is designed for traders and analysts seeking a normalized, scale-independent perspective on market behavior. It does not attempt to predict price but instead helps interpret the relative strength or weakness of recent movements.
⚙️ Key Concepts
📉 Laplace-Based Smoothing
🎯 Percentile Mapping
🧠 Optional Kalman Filter
🔧 User Settings
🔁 Transform Parameters
📊 Percentile Settings
🧠 Kalman Filter Controls
🎨 Visual Settings
📈 Visual Output
🧩 Trend Classification Logic
The indicator segments percentile values into five zones:
🔍 Use Cases
This tool is intended as a visual and contextual aid for identifying trend regimes, assessing historical momentum strength, or supporting broader confluence-based analysis. It can be used in combination with other tools or frameworks at the discretion of the trader.
⚠️ Important Notes
Laplace Momentum Percentile ║ BullVision is a custom-built trend analysis tool that applies Laplace-inspired smoothing to price action and maps the result to a historical percentile scale. This provides a contextual view of trend intensity, with optional signal refinement using a Kalman filter.
This indicator is designed for traders and analysts seeking a normalized, scale-independent perspective on market behavior. It does not attempt to predict price but instead helps interpret the relative strength or weakness of recent movements.
⚙️ Key Concepts
📉 Laplace-Based Smoothing
- The core signal is built using a Laplace-style weighted average, applying an exponential decay to price values over a specified length. This emphasizes recent movements while still accounting for historical context.
🎯 Percentile Mapping
- Rather than displaying the raw output, the filtered signal is converted into a percentile rank based on its position within a historical lookback window. This helps normalize interpretation across different assets and timeframes.
🧠 Optional Kalman Filter
- For users seeking additional smoothing, a Kalman filter is included. This statistical method updates signal estimates dynamically, helping reduce short-term fluctuations without introducing significant lag.
🔧 User Settings
🔁 Transform Parameters
- Transform Parameter (s): Controls the decay rate for Laplace weighting.
- Calculation Length: Sets how many candles are used for smoothing.
📊 Percentile Settings
- Lookback Period: Defines how far back to calculate the historical percentile ranking.
🧠 Kalman Filter Controls
- Enable Kalman Filter: Optional toggle.
- Process Noise / Measurement Noise: Adjust the filter’s responsiveness and tolerance to volatility.
🎨 Visual Settings
- Show Raw Signal: Optionally display the pre-smoothed percentile value.
- Thresholds: Customize upper and lower trend zone boundaries.
📈 Visual Output
- Main Line: Smoothed percentile rank, color-coded based on strength.
- Raw Line (Optional): The unsmoothed percentile value for comparison.
- Trend Zones: Background shading highlights strong upward or downward regimes.
- Live Label: Displays current percentile value and trend classification.
🧩 Trend Classification Logic
The indicator segments percentile values into five zones:
- Above 80: Strong upward trend
- 50–80: Mild upward trend
- 20–50: Neutral zone
- 0–20: Mild downward trend
- Below 0: Strong downward trend
🔍 Use Cases
This tool is intended as a visual and contextual aid for identifying trend regimes, assessing historical momentum strength, or supporting broader confluence-based analysis. It can be used in combination with other tools or frameworks at the discretion of the trader.
⚠️ Important Notes
- This script does not provide buy or sell signals.
- It is intended for educational and analytical purposes only.
- It should be used as part of a broader decision-making process.
- Past signal behavior should not be interpreted as indicative of future results.
開源腳本
本著TradingView的真正精神,此腳本的創建者將其開源,以便交易者可以查看和驗證其功能。向作者致敬!雖然您可以免費使用它,但請記住,重新發佈程式碼必須遵守我們的網站規則。
Join my free discord server for weekly maket summary, free trend signals and more : discord.gg/srN3VzRxFE
免責聲明
這些資訊和出版物並不意味著也不構成TradingView提供或認可的金融、投資、交易或其他類型的意見或建議。請在使用條款閱讀更多資訊。
開源腳本
本著TradingView的真正精神,此腳本的創建者將其開源,以便交易者可以查看和驗證其功能。向作者致敬!雖然您可以免費使用它,但請記住,重新發佈程式碼必須遵守我們的網站規則。
Join my free discord server for weekly maket summary, free trend signals and more : discord.gg/srN3VzRxFE
免責聲明
這些資訊和出版物並不意味著也不構成TradingView提供或認可的金融、投資、交易或其他類型的意見或建議。請在使用條款閱讀更多資訊。