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AlphaZ-Score - Bitcoin Market Cycle Indicator
Overview
AlphaZ-Score is a comprehensive Bitcoin market cycle indicator that combines multiple on-chain, technical, and fundamental metrics into a single normalized oscillator. By aggregating Z-scores from various proven Bitcoin indicators, it provides clear overbought and oversold signals that align with Bitcoin's cyclical nature.
Key Features:
Multi-dimensional market analysis combining 7 different methodologies
Normalized Z-score output ranging from extreme oversold (-3+) to extreme overbought (+3+)
Modular design - enable/disable individual components
Real-time market condition assessment with visual feedback
Optimized for Bitcoin's unique market dynamics
How It Works
AlphaZ-Score calculates individual Z-scores for each enabled indicator, then combines them using a weighted average approach. A Z-score measures how many standard deviations a value is from its historical mean, making it perfect for identifying extreme market conditions.
Interpretation:
+3 or higher: Extreme Overbought (Strong Sell Signal)
+2 to +3: Overbought (Sell Signal)
-2 to +2: Neutral Zone
-2 to -3: Oversold (Buy Signal)
-3 or lower: Extreme Oversold (Strong Buy Signal)
Component Indicators
1. Days Higher Streak Valuation (DHSV)
Purpose: Measures how many days in historical data had higher prices than current price, accounting for price streaks and momentum decay.
How it works:
Counts historical days with prices above current level
Tracks consecutive "streak" days when no historical prices are higher
Applies dynamic threshold decay to account for sustained moves
Higher streak values indicate potential oversold conditions
Key Parameters:
Historical Bars (1000): Number of past bars to analyze for comparison
Lower Streak Threshold (5%): Percentage threshold for price comparison
Threshold Decay (0.05): Rate at which threshold decays over time
Z-Score Lookback (1000): Period for calculating the Z-score normalization
2. High Probability Overbought/Oversold (HPOB)
Purpose: Advanced momentum indicator using volume-weighted Hull moving averages to identify high-probability reversal zones.
How it works:
Calculates Volume-Weighted Hull Moving Average (SVWHMA)
Compares with standard Hull Moving Average
Normalizes the difference using 100-period SMA
Extreme readings indicate momentum exhaustion
Key Parameters:
SVWHMA Length (50): Period for volume-weighted Hull MA calculation
HMA Length (50): Period for standard Hull MA
Smooth Length (50): EMA smoothing period for final output
3. Stablecoin Supply Ratio Oscillator (SSRO)
Purpose: Analyzes the relationship between Bitcoin's market cap and major stablecoin supply (USDT + USDC) to gauge buying power available.
How it works:
Calculates ratio: BTC Market Cap / (USDT Supply + USDC Supply)
Higher ratios indicate Bitcoin is expensive relative to available stablecoin liquidity
Z-score normalization identifies extreme ratios historically
Key Parameters:
SSRO Length (200): Lookback period for Z-score calculation
Market Logic: When stablecoin supply is high relative to BTC market cap, it suggests significant buying power exists (bearish for current price). When ratio is high, it suggests Bitcoin is overvalued relative to available liquidity.
4. MVRV Z-Score
Purpose: Classic Bitcoin cycle indicator comparing Market Value to Realized Value, identifying macro cycle tops and bottoms.
How it works:
Uses MVRV ratio data (Market Cap / Realized Cap)
Realized Cap values coins at the price they last moved, not current price
High MVRV indicates coins are trading well above their "fair value"
Z-score normalization identifies historical extremes
Key Parameters:
MVRV Length (520): Period for Z-score calculation (~2 years of daily data)
Market Logic: MVRV > 3.7 historically marks cycle tops, while MVRV < 1.0 marks cycle bottoms. The Z-score version normalizes these levels across different market cycles.
5. Risk Index Z-Score
Purpose: Proprietary risk calculation based on the relationship between realized cap and market cap over time.
How it works:
Calculates delta between current realized cap and historical realized cap
Normalizes by current market cap to create risk percentage
Applies time-based scaling and Z-score normalization
Key Parameters:
Risk Multiplier (0.625): Scaling factor for realized cap comparison
Risk Z Length (1500): Period for Z-score calculation
6. SOPR Z-Score (Spent Output Profit Ratio)
Purpose: Measures the profit ratio of coins being moved on-chain, indicating holder behavior and market sentiment.
How it works:
Uses Glassnode SOPR data (ratio of sold price to purchase price)
Applies EMA smoothing to reduce noise
Z-score normalization identifies extreme profit-taking or capitulation
Key Parameters:
SOPR EMA Length (7): Smoothing period for SOPR data
SOPR Z Length (180): Period for Z-score calculation
Market Logic: SOPR > 1 means coins are being sold at profit, SOPR < 1 indicates selling at a loss. Extreme Z-scores identify unsustainable profit-taking (tops) or capitulation (bottoms).
7. On-chain Z-Score Composite
Purpose: Multi-metric on-chain analysis combining NUPL, SOPR, and MVRV for comprehensive network state assessment.
Components:
NUPL (Net Unrealized Profit/Loss): (Market Cap - Realized Cap) / Market Cap
SOPR Z-Score: Standardized SOPR with custom smoothing
MVRV Z-Score: Market-to-realized value ratio normalized
Key Parameters:
NUPL Z Length (126): Period for NUPL Z-score calculation
SOPR Z Length (111): Period for on-chain SOPR Z-score
MVRV Z Length (111): Period for on-chain MVRV Z-score
SOPR EMA Length (14): Smoothing for SOPR Z-score component
How it works:
Averages the three Z-scores to provide a comprehensive on-chain market state assessment.
Input Parameters Guide
General Settings
Use [Indicator]: Toggle switches for each component indicator. Disabling indicators removes them from the aggregated calculation, potentially creating more extreme readings.
Optimization Tips
For more extreme signals: Disable complex indicators (DHSV, HPOB, Risk Index, On-chain) and focus on core cycle indicators (MVRV, SOPR, SSRO)
For more sensitivity: Reduce lookback periods on Z-score calculations
For smoother signals: Increase smoothing periods and Z-score lookback periods
For different timeframes: Adjust the lengths proportionally (e.g., halve all periods for 12H charts)
Default Configuration
The default settings are optimized for Bitcoin daily charts and focus on the three most reliable cycle indicators:
Enabled: SSRO, MVRV, SOPR
Disabled: DHSV, HPOB, Risk Index, On-chain (to achieve more extreme readings)
Visual Elements
Plot Colors
Bright Red: Extreme Overbought (Z-score ≥ 3)
Light Red: Overbought (Z-score ≥ 2)
Gradient: Neutral zone (-2 to +2)
Light Green: Oversold (Z-score ≤ -2)
Bright Green: Extreme Oversold (Z-score ≤ -3)
Reference Lines
Solid White: Zero line
Dashed Lines: ±2 levels (primary overbought/oversold)
Dotted Lines: ±3 levels (extreme conditions)
Background & Bar Coloring
Background highlighting during extreme conditions
Bar coloring changes when overbought/oversold thresholds are reached
Summary Table
Real-time market condition assessment displayed in the top-right corner showing current state and exact Z-score value.
Usage Strategy
For Long-term Investors
Buy: Z-score < -2 (especially < -3)
Sell: Z-score > +2 (especially > +3)
Hold: -2 to +2 range
For Traders
Reversal Signals: Look for divergences at extreme levels
Trend Confirmation: Use with price action and volume analysis
Risk Management: Reduce position sizes at extreme overbought levels
Best Practices
Combine with Price Action: Don't use in isolation
Consider Multiple Timeframes: Check higher timeframes for context
Wait for Confirmation: Extreme readings can persist during strong trends
Backtest Settings: Optimize parameters for your specific trading style
Technical Notes
Data Sources: Combines TradingView native data with external feeds from Glassnode, CoinMetrics, and IntoTheBlock
Update Frequency: Real-time on supported exchanges, daily updates for on-chain components
Computational Intensity: Moderate - uses multiple external data requests
Best Timeframe: Optimized for daily charts, but adaptable to other timeframes
The Aggregated Z-Score Market Oscillator represents a sophisticated approach to Bitcoin market analysis, combining the wisdom of multiple proven methodologies into a single, actionable signal. By understanding each component and how they interact, traders and investors can make more informed decisions about Bitcoin's cyclical nature.
AlphaZ-Score is a comprehensive Bitcoin market cycle indicator that combines multiple on-chain, technical, and fundamental metrics into a single normalized oscillator. By aggregating Z-scores from various proven Bitcoin indicators, it provides clear overbought and oversold signals that align with Bitcoin's cyclical nature.
Key Features:
Multi-dimensional market analysis combining 7 different methodologies
Normalized Z-score output ranging from extreme oversold (-3+) to extreme overbought (+3+)
Modular design - enable/disable individual components
Real-time market condition assessment with visual feedback
Optimized for Bitcoin's unique market dynamics
How It Works
AlphaZ-Score calculates individual Z-scores for each enabled indicator, then combines them using a weighted average approach. A Z-score measures how many standard deviations a value is from its historical mean, making it perfect for identifying extreme market conditions.
Interpretation:
+3 or higher: Extreme Overbought (Strong Sell Signal)
+2 to +3: Overbought (Sell Signal)
-2 to +2: Neutral Zone
-2 to -3: Oversold (Buy Signal)
-3 or lower: Extreme Oversold (Strong Buy Signal)
Component Indicators
1. Days Higher Streak Valuation (DHSV)
Purpose: Measures how many days in historical data had higher prices than current price, accounting for price streaks and momentum decay.
How it works:
Counts historical days with prices above current level
Tracks consecutive "streak" days when no historical prices are higher
Applies dynamic threshold decay to account for sustained moves
Higher streak values indicate potential oversold conditions
Key Parameters:
Historical Bars (1000): Number of past bars to analyze for comparison
Lower Streak Threshold (5%): Percentage threshold for price comparison
Threshold Decay (0.05): Rate at which threshold decays over time
Z-Score Lookback (1000): Period for calculating the Z-score normalization
2. High Probability Overbought/Oversold (HPOB)
Purpose: Advanced momentum indicator using volume-weighted Hull moving averages to identify high-probability reversal zones.
How it works:
Calculates Volume-Weighted Hull Moving Average (SVWHMA)
Compares with standard Hull Moving Average
Normalizes the difference using 100-period SMA
Extreme readings indicate momentum exhaustion
Key Parameters:
SVWHMA Length (50): Period for volume-weighted Hull MA calculation
HMA Length (50): Period for standard Hull MA
Smooth Length (50): EMA smoothing period for final output
3. Stablecoin Supply Ratio Oscillator (SSRO)
Purpose: Analyzes the relationship between Bitcoin's market cap and major stablecoin supply (USDT + USDC) to gauge buying power available.
How it works:
Calculates ratio: BTC Market Cap / (USDT Supply + USDC Supply)
Higher ratios indicate Bitcoin is expensive relative to available stablecoin liquidity
Z-score normalization identifies extreme ratios historically
Key Parameters:
SSRO Length (200): Lookback period for Z-score calculation
Market Logic: When stablecoin supply is high relative to BTC market cap, it suggests significant buying power exists (bearish for current price). When ratio is high, it suggests Bitcoin is overvalued relative to available liquidity.
4. MVRV Z-Score
Purpose: Classic Bitcoin cycle indicator comparing Market Value to Realized Value, identifying macro cycle tops and bottoms.
How it works:
Uses MVRV ratio data (Market Cap / Realized Cap)
Realized Cap values coins at the price they last moved, not current price
High MVRV indicates coins are trading well above their "fair value"
Z-score normalization identifies historical extremes
Key Parameters:
MVRV Length (520): Period for Z-score calculation (~2 years of daily data)
Market Logic: MVRV > 3.7 historically marks cycle tops, while MVRV < 1.0 marks cycle bottoms. The Z-score version normalizes these levels across different market cycles.
5. Risk Index Z-Score
Purpose: Proprietary risk calculation based on the relationship between realized cap and market cap over time.
How it works:
Calculates delta between current realized cap and historical realized cap
Normalizes by current market cap to create risk percentage
Applies time-based scaling and Z-score normalization
Key Parameters:
Risk Multiplier (0.625): Scaling factor for realized cap comparison
Risk Z Length (1500): Period for Z-score calculation
6. SOPR Z-Score (Spent Output Profit Ratio)
Purpose: Measures the profit ratio of coins being moved on-chain, indicating holder behavior and market sentiment.
How it works:
Uses Glassnode SOPR data (ratio of sold price to purchase price)
Applies EMA smoothing to reduce noise
Z-score normalization identifies extreme profit-taking or capitulation
Key Parameters:
SOPR EMA Length (7): Smoothing period for SOPR data
SOPR Z Length (180): Period for Z-score calculation
Market Logic: SOPR > 1 means coins are being sold at profit, SOPR < 1 indicates selling at a loss. Extreme Z-scores identify unsustainable profit-taking (tops) or capitulation (bottoms).
7. On-chain Z-Score Composite
Purpose: Multi-metric on-chain analysis combining NUPL, SOPR, and MVRV for comprehensive network state assessment.
Components:
NUPL (Net Unrealized Profit/Loss): (Market Cap - Realized Cap) / Market Cap
SOPR Z-Score: Standardized SOPR with custom smoothing
MVRV Z-Score: Market-to-realized value ratio normalized
Key Parameters:
NUPL Z Length (126): Period for NUPL Z-score calculation
SOPR Z Length (111): Period for on-chain SOPR Z-score
MVRV Z Length (111): Period for on-chain MVRV Z-score
SOPR EMA Length (14): Smoothing for SOPR Z-score component
How it works:
Averages the three Z-scores to provide a comprehensive on-chain market state assessment.
Input Parameters Guide
General Settings
Use [Indicator]: Toggle switches for each component indicator. Disabling indicators removes them from the aggregated calculation, potentially creating more extreme readings.
Optimization Tips
For more extreme signals: Disable complex indicators (DHSV, HPOB, Risk Index, On-chain) and focus on core cycle indicators (MVRV, SOPR, SSRO)
For more sensitivity: Reduce lookback periods on Z-score calculations
For smoother signals: Increase smoothing periods and Z-score lookback periods
For different timeframes: Adjust the lengths proportionally (e.g., halve all periods for 12H charts)
Default Configuration
The default settings are optimized for Bitcoin daily charts and focus on the three most reliable cycle indicators:
Enabled: SSRO, MVRV, SOPR
Disabled: DHSV, HPOB, Risk Index, On-chain (to achieve more extreme readings)
Visual Elements
Plot Colors
Bright Red: Extreme Overbought (Z-score ≥ 3)
Light Red: Overbought (Z-score ≥ 2)
Gradient: Neutral zone (-2 to +2)
Light Green: Oversold (Z-score ≤ -2)
Bright Green: Extreme Oversold (Z-score ≤ -3)
Reference Lines
Solid White: Zero line
Dashed Lines: ±2 levels (primary overbought/oversold)
Dotted Lines: ±3 levels (extreme conditions)
Background & Bar Coloring
Background highlighting during extreme conditions
Bar coloring changes when overbought/oversold thresholds are reached
Summary Table
Real-time market condition assessment displayed in the top-right corner showing current state and exact Z-score value.
Usage Strategy
For Long-term Investors
Buy: Z-score < -2 (especially < -3)
Sell: Z-score > +2 (especially > +3)
Hold: -2 to +2 range
For Traders
Reversal Signals: Look for divergences at extreme levels
Trend Confirmation: Use with price action and volume analysis
Risk Management: Reduce position sizes at extreme overbought levels
Best Practices
Combine with Price Action: Don't use in isolation
Consider Multiple Timeframes: Check higher timeframes for context
Wait for Confirmation: Extreme readings can persist during strong trends
Backtest Settings: Optimize parameters for your specific trading style
Technical Notes
Data Sources: Combines TradingView native data with external feeds from Glassnode, CoinMetrics, and IntoTheBlock
Update Frequency: Real-time on supported exchanges, daily updates for on-chain components
Computational Intensity: Moderate - uses multiple external data requests
Best Timeframe: Optimized for daily charts, but adaptable to other timeframes
The Aggregated Z-Score Market Oscillator represents a sophisticated approach to Bitcoin market analysis, combining the wisdom of multiple proven methodologies into a single, actionable signal. By understanding each component and how they interact, traders and investors can make more informed decisions about Bitcoin's cyclical nature.
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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AlphaEdge_。
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
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。