Bollinger Momentum Deviation | QuantEdgeB

6 mar

Introducing Bollinger Momentum Deviation (BMD) by QuantEdgeB

🛠️ Overview
Bollinger Momentum Deviation (BMD) is a trend-following momentum indicator designed to identify strong price movements while also detecting overbought and oversold conditions in ranging markets.

By normalizing a simple moving average (SMA) with standard deviation, BMD captures momentum shifts, helping traders make data-driven entries and exits. In trending conditions, it acts as a momentum confirmation tool, while in ranging markets, it highlights mean-reversion opportunities for profit-taking or re-accumulation.

BMD combines the best of both worlds—a robust trend-following framework with an integrated volatility-based overbought/oversold detection system.

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✨ Key Features

🔹 Momentum & Trend-Following Core
Built upon a normalized SMA with standard deviation filtering, BMD efficiently tracks price movements while reducing lag.

🔹 Overbought/Oversold Market Detection
By dynamically adjusting its thresholds based on standard deviation, it identifies high-probability reversion zones in sideways markets.

🔹 Adaptive Normalization Mechanism
Ensures consistent signal reliability across different assets and timeframes by standardizing momentum fluctuations.

🔹 Customizable Visual & Signal Settings
Includes multiple color modes, extra plots, and trend labels, making it easy to align with different trading styles.

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📊 How It Works

1️⃣ Normalized Momentum Calculation
BMD computes a normalized momentum score using a simple moving average (SMA) combined with a standard deviation (SD) filter to create dynamic upper and lower bands. The final momentum score is derived by normalizing the price within this volatility-adjusted range. This normalization makes momentum readings comparable across different price levels and timeframes.

2️⃣ Standard Deviation Filtering
Unlike traditional approaches where standard deviation is derived from price as is the first SD, BMDs second SD is driven from the normalized momentum oscillator itself. This allows for a volatility-adjusted smoothing mechanism that adapts to momentum shifts rather than raw price fluctuations. This ensures that the trend signals remain dynamic and responsive, filtering out short-term noise while keeping the core momentum structure intact. By applying standard deviation directly to the oscillator, BMD achieves a self-regulating feedback loop, improving accuracy in both trending and range-bound conditions.

3️⃣ Signal Generation

✅ Long Signal → Upper BMD SD > Long Threshold (83)
❌ Short Signal → Lower BMD SD < Short Threshold (60)

📌 Additional Features:
- Overbought Zone → Values above 130 indicate price extension.
- Oversold Zone → Values below -10 suggest potential accumulation.
- Momentum Labels → Optional "Long" and "Short" markers for clear trade identification.

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👥 Who Should Use It?

✅ Trend Traders & Momentum Followers → Use BMD as a confirmation tool for strong directional trends.
✅ Range & Mean Reversion Traders → Identify reversal opportunities at extreme BMD levels.
✅ Swing & Position Traders → Utilize normalized momentum shifts for data-driven entries & exits.
✅ Systematic & Quant Traders → Implement BMD within algorithmic frameworks for adaptive market detection.

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⚙️ Customization & Default Settings

🔧 Key Custom Inputs:
- Base Length (Default: 40) → Defines the SMA calculation period.
- Standard Deviation Length (Default: 50) → Controls the volatility filter strength.
- SD Multiplier (Default: 0-7) → Adjusts the sensitivity of the momentum filter.
- Long Threshold (Default: 83) → Above this level, momentum is bullish.
- Short Threshold (Default: 60) → Below this level, momentum weakens.
- Visual Customizations → Multiple color themes, extra plots, and trend labels available.

🚀 By default, BMD is optimized for trend-following and momentum filtering while remaining adaptable to various trading strategies.

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📌 How to Use Bollinger Momentum Deviation (BMD) in Trading

1️⃣ Trend-Following Strategy (Momentum Confirmation)
✔ Enter long positions when BMD crosses above the long threshold (83), confirming upward momentum.
✔ Enter short positions when BMD crosses below the short threshold (60), confirming downward momentum.
✔ Stay in trades as long as BMD remains in trend direction, filtering out noise.

2️⃣ Mean Reversion Strategy (Overbought/Oversold Conditions)
✔ Take profits or hedge when BMD crosses above 130 (overbought).
✔ Re-accumulate positions when BMD drops below -10 (oversold).

📌 Why?
- In trending markets, follow BMD’s momentum confirmation.
- In ranging markets, use BMD’s normalized bands to buy at deep discounts and sell into strength.

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📌 Conclusion

Bollinger Momentum Deviation (BMD) is a versatile momentum indicator that combines trend-following mechanics with volatility-adjusted mean reversion zones. By normalizing SMA-based momentum shifts, BMD ensures robust signal reliability across different assets and timeframes.

🔹 Key Takeaways:
1️⃣ Momentum Confirmation & Trend Detection – Captures directional strength with dynamic filtering.
2️⃣ Overbought/Oversold Conditions – Identifies reversal opportunities in sideways markets.
3️⃣ Adaptive & Customizable – Works across different timeframes and trading styles.

🔹 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.

6 mar

Note di rilascio

Added 📊 Backtest Mode

4️⃣ Evaluating Historical Performance
BMD now includes an optional backtest table, allowing traders to assess its past performance before integrating it into their trading strategy. This feature provides key quantitative metrics to measure the indicator's effectiveness over historical price data.

🔹 Backtest Metrics Displayed:
- Equity Max Drawdown → Largest historical loss from peak equity.
- Intra-Trade Max Drawdown → The worst loss experienced within a single trade.
- Profit Factor → Ratio of total profits to total losses, indicating system efficiency.
- Profitable % → Win rate of the strategy over the backtest period.
- Sharpe Ratio → Risk-adjusted return measurement.
- Sortino Ratio → Focuses on downside risk-adjusted returns.
- Omega Ratio → Measures return consistency and performance asymmetry.
- Half Kelly → Position sizing guidance based on risk/reward optimization.
- Total Trades → Number of executed trades.
- Net Profit % → Cumulative percentage return over the backtest period.

📌 Disclaimer:
The backtest results are based on past performance and are not indicative of future outcomes. Market conditions evolve, and while historical metrics provide insight into potential effectiveness, traders should always apply proper risk management and real-time validation before live execution.

🚀 **Why This Matters?**
✅ **Strategy Validation** → Gain **insight into profitability, risk, and efficiency** over historical price action.
✅ **Optimization Tool** → Adjust BMD parameters and **observe how different settings impact past performance**.
✅ **Risk Awareness** → Understand potential **drawdowns** and **performance consistency** before trading live.

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This new section **fully integrates the backtest table**, ensuring that traders can **evaluate BMD’s past performance with transparency** while reinforcing **risk management awareness**. 🚀 Let me know if you need any refinements! 📊

10 mar

Note di rilascio

Fixed Backtest Parameters Calculation.

10 mar

Note di rilascio

Added HalfKelly to the backtest metrics

12 mar

Note di rilascio

Fixed plot colors.

13 mar

Note di rilascio

Fixed Alerts name

6 apr

Note di rilascio

Added option to chose different Moving Average as base