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Simple VIDYA Smooth | QuantEdgeB

Simple VIDYA Smooth (SVS) | QuantEdgeB
🔍 What Is Simple VIDYA Smooth?
SVS is a smoothed, volatility-adaptive trend filter that blends a Gaussian-pre-filtered, low-lag moving average with dynamic standard-deviation bands. It identifies trends by measuring when price moves decisively above or below a normalized VIDYA (Variable Index Dynamic Average) baseline—filtering out noise and adapting to changing market turbulence.
⚙️ Core Components
1. DEMA Pre-Filter
o A double-EMA smoothing to reduce initial noise before further processing.
2. Gaussian Smoothing
o Applies a small-kernel Gaussian filter to produce a cleaner input series that suppresses rapid spikes.
3. VIDYA Adaptive Average
o Computes a dynamic EMA whose smoothing constant adjusts according to the ratio of short- and long-term standard deviations—making it inherently responsive in volatile times and smooth in calmer periods.
4. Volatility Bands
o Surrounds the VIDYA line with ±N×SD bands (separate multipliers for upper and lower) to capture current market volatility, yielding dynamic thresholds for trend detection.
5. Trend Signal
o Generates a “long” when price closes above the upper band, a “short” when it closes below the lower band, otherwise stays neutral.
💡 Why It’s Special
• Adaptive Responsiveness: VIDYA’s volatility-weighted smoothing constant speeds up trend recognition in choppy markets and slows in quiet ones, avoiding whipsaws.
• Multi-Stage Filtering: The DEMA→Gaussian→VIDYA sequence ensures both rapid noise suppression and flexible trend adaptation.
• Asymmetric Bands: Separate multipliers for the upper and lower volatility bands let you fine-tune sensitivity to bullish versus bearish impulses.
• Visual Clarity: Color-coded candles and filled bands highlight trending phases at a glance, while backtest tables quantify performance.
📊 Backtest Mode
AVBO includes an optional backtest table, enabling traders to assess its historical effectiveness before applying it in live trading conditions.
🔹 Backtest Metrics Displayed:
• Equity Max Drawdown → Largest historical loss from peak equity.
• Profit Factor → Ratio of total profits to total losses, measuring system efficiency.
• Sharpe Ratio → Assesses risk-adjusted return performance.
• Sortino Ratio → Focuses on downside risk-adjusted returns.
• Omega Ratio → Evaluates return consistency & performance asymmetry.
• Half Kelly → Optimal position sizing based on risk/reward analysis.
• Total Trades & Win Rate → Assess historical success rate.
BTC

ETH

📌 Disclaimer:
Backtest results are based on past performance and do not guarantee future success. Always incorporate real-time validation and risk management in live trading.
💼 Ideal Use Cases
• Trend Identification: Pinpoint reliable trend starts and exits in stocks, FX, or crypto—minimizing lag and false breakouts.
• Volatility Regimes: Automatically adjust to quiet vs. explosive markets—no manual parameter tweaks needed.
• Multitimeframe Alignment: Use SVS on multiple timeframes to confirm trend direction before entering positions.
• System Building Block: Embed SVS as a robust, adaptive filter within larger strategies (e.g., to trigger entries or to validate signals from other indicators).
🎨 Default Configuration
• DEMA Length: 7
• Gaussian Kernel: length = 4, sigma = 2.0
• VIDYA Lengths: fast = 9, slow = 24 (or use presets Set1–Set4)
• Volatility Bands: SD length = 40
📌 In Summary
Simple VIDYA Smooth | QuantEdgeB is an adaptive trend-filtering indicator that layers multiple noise-suppressing and volatility-adjusting techniques to deliver clear, reliable trend signals. By marrying DEMA, Gaussian filtering, VIDYA’s volatility-driven smoothing, and dynamic SD bands, SVS excels at separating genuine directional moves from market noise—across any asset or timeframe.
🔹 Disclaimer: Past performance is not indicative of future results. Always backtest and align AVBO’s settings with your risk tolerance and market objectives before live trading.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
🔍 What Is Simple VIDYA Smooth?
SVS is a smoothed, volatility-adaptive trend filter that blends a Gaussian-pre-filtered, low-lag moving average with dynamic standard-deviation bands. It identifies trends by measuring when price moves decisively above or below a normalized VIDYA (Variable Index Dynamic Average) baseline—filtering out noise and adapting to changing market turbulence.
⚙️ Core Components
1. DEMA Pre-Filter
o A double-EMA smoothing to reduce initial noise before further processing.
2. Gaussian Smoothing
o Applies a small-kernel Gaussian filter to produce a cleaner input series that suppresses rapid spikes.
3. VIDYA Adaptive Average
o Computes a dynamic EMA whose smoothing constant adjusts according to the ratio of short- and long-term standard deviations—making it inherently responsive in volatile times and smooth in calmer periods.
4. Volatility Bands
o Surrounds the VIDYA line with ±N×SD bands (separate multipliers for upper and lower) to capture current market volatility, yielding dynamic thresholds for trend detection.
5. Trend Signal
o Generates a “long” when price closes above the upper band, a “short” when it closes below the lower band, otherwise stays neutral.
💡 Why It’s Special
• Adaptive Responsiveness: VIDYA’s volatility-weighted smoothing constant speeds up trend recognition in choppy markets and slows in quiet ones, avoiding whipsaws.
• Multi-Stage Filtering: The DEMA→Gaussian→VIDYA sequence ensures both rapid noise suppression and flexible trend adaptation.
• Asymmetric Bands: Separate multipliers for the upper and lower volatility bands let you fine-tune sensitivity to bullish versus bearish impulses.
• Visual Clarity: Color-coded candles and filled bands highlight trending phases at a glance, while backtest tables quantify performance.
📊 Backtest Mode
AVBO includes an optional backtest table, enabling traders to assess its historical effectiveness before applying it in live trading conditions.
🔹 Backtest Metrics Displayed:
• Equity Max Drawdown → Largest historical loss from peak equity.
• Profit Factor → Ratio of total profits to total losses, measuring system efficiency.
• Sharpe Ratio → Assesses risk-adjusted return performance.
• Sortino Ratio → Focuses on downside risk-adjusted returns.
• Omega Ratio → Evaluates return consistency & performance asymmetry.
• Half Kelly → Optimal position sizing based on risk/reward analysis.
• Total Trades & Win Rate → Assess historical success rate.
BTC
ETH
📌 Disclaimer:
Backtest results are based on past performance and do not guarantee future success. Always incorporate real-time validation and risk management in live trading.
💼 Ideal Use Cases
• Trend Identification: Pinpoint reliable trend starts and exits in stocks, FX, or crypto—minimizing lag and false breakouts.
• Volatility Regimes: Automatically adjust to quiet vs. explosive markets—no manual parameter tweaks needed.
• Multitimeframe Alignment: Use SVS on multiple timeframes to confirm trend direction before entering positions.
• System Building Block: Embed SVS as a robust, adaptive filter within larger strategies (e.g., to trigger entries or to validate signals from other indicators).
🎨 Default Configuration
• DEMA Length: 7
• Gaussian Kernel: length = 4, sigma = 2.0
• VIDYA Lengths: fast = 9, slow = 24 (or use presets Set1–Set4)
• Volatility Bands: SD length = 40
📌 In Summary
Simple VIDYA Smooth | QuantEdgeB is an adaptive trend-filtering indicator that layers multiple noise-suppressing and volatility-adjusting techniques to deliver clear, reliable trend signals. By marrying DEMA, Gaussian filtering, VIDYA’s volatility-driven smoothing, and dynamic SD bands, SVS excels at separating genuine directional moves from market noise—across any asset or timeframe.
🔹 Disclaimer: Past performance is not indicative of future results. Always backtest and align AVBO’s settings with your risk tolerance and market objectives before live trading.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
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只有經作者批准的使用者才能訪問此腳本。您需要申請並獲得使用權限。該權限通常在付款後授予。如欲了解更多詳情,請依照以下作者的說明操作,或直接聯絡QuantEdgeB。
除非您完全信任其作者並了解腳本的工作原理,否則TradingView不建議您付費或使用腳本。您也可以在我們的社群腳本中找到免費的開源替代方案。
作者的說明
Please check out our Whop page for access!! https://whop.com/quantedgeb/
提醒:在請求訪問權限之前,請閱讀僅限邀請腳本指南。
🔹 Get access to our premium tools:
whop.com/quantedgeb/ 💎
🔹 Unlock our free toolbox:
tradinglibrary.carrd.co/ 🛠️
Disclaimer: All resources and indicators provided are for educational purposes only
whop.com/quantedgeb/ 💎
🔹 Unlock our free toolbox:
tradinglibrary.carrd.co/ 🛠️
Disclaimer: All resources and indicators provided are for educational purposes only
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。
僅限邀請腳本
只有經作者批准的使用者才能訪問此腳本。您需要申請並獲得使用權限。該權限通常在付款後授予。如欲了解更多詳情,請依照以下作者的說明操作,或直接聯絡QuantEdgeB。
除非您完全信任其作者並了解腳本的工作原理,否則TradingView不建議您付費或使用腳本。您也可以在我們的社群腳本中找到免費的開源替代方案。
作者的說明
Please check out our Whop page for access!! https://whop.com/quantedgeb/
提醒:在請求訪問權限之前,請閱讀僅限邀請腳本指南。
🔹 Get access to our premium tools:
whop.com/quantedgeb/ 💎
🔹 Unlock our free toolbox:
tradinglibrary.carrd.co/ 🛠️
Disclaimer: All resources and indicators provided are for educational purposes only
whop.com/quantedgeb/ 💎
🔹 Unlock our free toolbox:
tradinglibrary.carrd.co/ 🛠️
Disclaimer: All resources and indicators provided are for educational purposes only
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。