PRC-VIDYA | QuantEdgeB

Introducing PRC-VIDYA by QuantEdgeB

Overview
The PRC-VIDYA(Volatility–Indexed Dynamic Average) is a sophisticated trading indicator developed for traders looking to capitalize on trend shifts with enhanced filtering mechanisms. It blends an Endpoint VIDYA filter—an adaptive, volatility-scaled moving average with percentile-based thresholds and a median-absolute-deviation buffer to craft a dynamic entry/exit envelope. Price thrusts beyond the upper or lower band generate crisp long/short signals, complete with colored fills, candle tinting, alerts and optional backtest stats

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Key Features
🔹VIDYA(Volatility–Indexed Dynamic Average):
- Adaptive Moving Average that adjusts its responsiveness based on market volatility.
- Uses a dynamic smoothing constant based on standard deviations.
- Allows for better trend detection compared to static moving averages.

🔹2. Percentile Rank-Based Dynamic Levels:
- Identifies overbought (75th percentile) and oversold (25th percentile) zones.
- Dynamically adjusts based on historical data, making it robust across different market conditions.

🔹3. Median Absolute Deviation (MAD) Filtering:
- An advanced volatility filter that refines entry and exit points.
- Reduces noise by filtering out weak signals, focusing only on meaningful trend shifts.
- Uses two multipliers (long and short) to fine-tune sensitivity.

🔹4. Signal Generation:
- 📈Long Signal: Triggered when price closes above the upper dynamic threshold.
- 📉Short Signal: Triggered when price closes below the lower dynamic threshold.
- Uses color-coded candles to visually indicate trend shifts.
- Optional signal labels can be enabled for clear entry/exit indications.

🔹5. Customizable Visualization:
- Multiple color themes to match user preferences.
- Ability to overlay signals on price charts.
- Alerts available for long & short crossovers.

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How It Works
1. The script calculates VIDYA based on a user-defined period.
2. It computes the 75th and 25th percentile ranks of the moving average.
3. Median Absolute Deviation (MAD) Filtering is applied to reduce false breakouts.
4. A buy (long) or sell (short) signal is triggered when price crosses the respective filtered percentile levels.
5. Alerts and labels can be used to notify traders of new signals.

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Behavior across Crypto Majors

BTC


ETH


SOL



Note: Past behaviour is not indicative of future results. Always conduct thorough testing and risk management before making trading decisions.

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Best Use Cases
📌 Trend Confirmation – Use VIDYA to confirm if a trend is strengthening or weakening.
📌 Noise Reduction – MAD filtering prevents reacting to minor fluctuations, focusing on stronger trend shifts.
📌 Multi-Timeframe Scalability – Works across multiple timeframes (1H, 4H, Daily, etc.), depending on the trader’s strategy.

🧬 Default Settings
• Endpoint VIDYA Mode: “Mid” (9 bar, 24 bar hist)
• Percentile Length: 21 bars
• Upper/Lower Percentiles: 75% / 25%
• MAD Window: 21 bars
• Upper/Lower MAD Multipliers: 1.8 / 0.9
• Visuals: Candle coloring on, labels off, “Strategy” palette
• Backtest Table: off by default

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📌 Conclusion
PRC-VIDYA fuses a volatility-aware adaptive average with percentile boundaries and a robust deviation buffer, yielding a self-adjusting channel that captures genuine breakouts and breakdowns. Its clear regime coloring, alerts and optional backtest table make it a turnkey solution for traders who want signals that breathe with the market.

🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.