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Awesome Oscillator (AO) with Signals [AIBitcoinTrend]

👽 Multi-Scale Awesome Oscillator (AO) with Signals (AIBitcoinTrend)
The Multi-Scale Awesome Oscillator transforms the traditional Awesome Oscillator (AO) by integrating multi-scale wavelet filtering, enhancing its ability to detect momentum shifts while maintaining responsiveness across different market conditions.
Additionally, it features real-time divergence detection and an ATR-based dynamic trailing stop, making it a powerful tool for momentum analysis, reversals, and breakout strategies.

👽 What Makes the Multi-Scale AO – Wavelet-Enhanced Momentum Unique?
Unlike traditional AO indicators, this enhanced version leverages wavelet-based decomposition and volatility-adjusted normalization, ensuring improved signal consistency across various timeframes and assets.

👽 The Math Behind the Indicator
👾 Wavelet-Based AO Smoothing
The indicator applies multi-scale wavelet decomposition to extract high-frequency, medium-frequency, and low-frequency trend components, ensuring an optimal balance between reactivity and smoothness.
Pine Script®
Why It Works:
👾 Z-Score Normalization
To ensure consistency across different markets, the Awesome Oscillator is normalized using a Z-score transformation, making overbought and oversold levels stable across all assets.
Pine Script®
Why It Works:
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy

👾 Buy & Sell Signals with Trailing Stop
Bullish Setup:
Bearish Setup:

👽 Why It’s Useful for Traders
👽 Indicator Settings
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
The Multi-Scale Awesome Oscillator transforms the traditional Awesome Oscillator (AO) by integrating multi-scale wavelet filtering, enhancing its ability to detect momentum shifts while maintaining responsiveness across different market conditions.
Unlike conventional AO calculations, this advanced version refines trend structures using high-frequency, medium-frequency, and low-frequency wavelet components, providing traders with superior clarity and adaptability.
Additionally, it features real-time divergence detection and an ATR-based dynamic trailing stop, making it a powerful tool for momentum analysis, reversals, and breakout strategies.
👽 What Makes the Multi-Scale AO – Wavelet-Enhanced Momentum Unique?
Unlike traditional AO indicators, this enhanced version leverages wavelet-based decomposition and volatility-adjusted normalization, ensuring improved signal consistency across various timeframes and assets.
✅ Wavelet Smoothing – Multi-Scale Extraction – Captures short-term fluctuations while preserving broader trend structures.
✅ Frequency-Based Detail Weights – Separates high, medium, and low-frequency components to reduce noise and improve trend clarity.
✅ Real-Time Divergence Detection – Identifies bullish and bearish divergences for early trend reversals.
✅ Crossovers & ATR-Based Trailing Stops – Implements intelligent trade management with adaptive stop-loss levels.
👽 The Math Behind the Indicator
👾 Wavelet-Based AO Smoothing
The indicator applies multi-scale wavelet decomposition to extract high-frequency, medium-frequency, and low-frequency trend components, ensuring an optimal balance between reactivity and smoothness.
sma1 = ta.sma(signal, waveletPeriod1)
sma2 = ta.sma(signal, waveletPeriod2)
sma3 = ta.sma(signal, waveletPeriod3)
detail1 = signal - sma1 // High-frequency detail
detail2 = sma1 - sma2 // Intermediate detail
detail3 = sma2 - sma3 // Low-frequency detail
advancedAO = weightDetail1 * detail1 + weightDetail2 * detail2 + weightDetail3 * detail3
Why It Works:
- Short-Term Smoothing: Captures rapid fluctuations while minimizing noise.
- Medium-Term Smoothing: Balances short-term and long-term trends.
- Long-Term Smoothing: Enhances trend stability and reduces false signals.
👾 Z-Score Normalization
To ensure consistency across different markets, the Awesome Oscillator is normalized using a Z-score transformation, making overbought and oversold levels stable across all assets.
normFactor = ta.stdev(advancedAO, normPeriod)
normalizedAO = advancedAO / nz(normFactor, 1)
Why It Works:
- Standardizes AO values for comparison across assets.
- Enhances signal reliability, preventing misleading spikes.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence
- Price makes a lower low, while AO forms a higher low.
- A buy signal is confirmed when AO starts rising.
Bearish Divergence
- Price makes a higher high, while AO forms a lower high.
- A sell signal is confirmed when AO starts declining.
👾 Buy & Sell Signals with Trailing Stop
Bullish Setup:
✅AO crosses above the bullish trigger level → Buy Signal.
✅Trailing stop placed at Low - (ATR × Multiplier).
✅Exit if price crosses below the stop.
Bearish Setup:
✅AO crosses below the bearish trigger level → Sell Signal.
✅Trailing stop placed at High + (ATR × Multiplier).
✅Exit if price crosses above the stop.
👽 Why It’s Useful for Traders
- Wavelet-Enhanced Filtering – Retains essential trend details while eliminating excessive noise.
- Multi-Scale Momentum Analysis – Separates different trend frequencies for enhanced clarity.
- Real-Time Divergence Alerts – Identifies early reversal signals for better entries and exits.
- ATR-Based Risk Management – Ensures stops dynamically adapt to market conditions.
- Works Across Markets & Timeframes – Suitable for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
- AO Short Period – Defines the short-term moving average for AO calculation.
- AO Long Period – Defines the long-term moving average for AO smoothing.
- Wavelet Smoothing – Adjusts multi-scale decomposition for different market conditions.
- Divergence Detection – Enables or disables real-time divergence analysis. Normalization Period – Sets the lookback period for standard deviation-based AO normalization.
- Cross Signals Sensitivity – Controls crossover signal strength for buy/sell signals.
- ATR Trailing Stop Multiplier – Adjusts the sensitivity of the trailing stop.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
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。
👾 Adam at AI Bitcoin Trend
👽 We are the Quants!
👇 Be part of the fastest-growing quant trading community! 👇
discord.gg/7weCgzN5a7
🌕 Famous on Threads!
🪐 simpleaitrading.com/
👽 We are the Quants!
👇 Be part of the fastest-growing quant trading community! 👇
discord.gg/7weCgzN5a7
🌕 Famous on Threads!
🪐 simpleaitrading.com/
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。
👾 Adam at AI Bitcoin Trend
👽 We are the Quants!
👇 Be part of the fastest-growing quant trading community! 👇
discord.gg/7weCgzN5a7
🌕 Famous on Threads!
🪐 simpleaitrading.com/
👽 We are the Quants!
👇 Be part of the fastest-growing quant trading community! 👇
discord.gg/7weCgzN5a7
🌕 Famous on Threads!
🪐 simpleaitrading.com/
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。