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Aggiornato ERAK Quantitative Gaussian Edge [Pro Math Model]

Overview
The ERAK Quantitative Gaussian Edge is not a traditional trading indicator; it is a probabilistic mathematical model designed to identify statistical anomalies in asset prices. Unlike classical indicators (RSI, MACD) that rely on lagging price derivatives, this algorithm utilizes Linear Regression Analysis and Gaussian Distribution (Normal Distribution) theory to determine the probability of a Mean Reversion event.
Core Philosophy
Markets are stochastic, but they exhibit "Fat Tail" behavior. This strategy operates on the principle that while prices wander, they are mathematically tethered to a "Center of Gravity" (Mean). When the price deviates significantly (Z-Score > 2.5 Sigma) from this mean without fundamental justification, it presents a high-probability arbitrage opportunity to trade back toward equilibrium.
Key Features & Mathematical Logic:
1. Dynamic Linear Regression Channel: Instead of simple Moving Averages (which lag significantly), we use a Linear Regression Curve to establish the "Fair Value" of the asset in real-time.
2. Statistical Z-Score Trigger: Entries are not based on arbitrary levels but on Standard Deviation (Sigma).
• Entry: Occurs when price hits ±2.5 Sigma (Statistically, this represents the outer ~1% of price occurrences).
• Exit: Occurs when price reverts to the mean (Expected Value).
3. R-Squared (R^2) Trend Filter: To avoid "catching a falling knife," the algorithm calculates the Coefficient of Determination (R^2).
• If R^2 > 0.80, it implies a strong deterministic trend. The system blocks counter-trend trades to prevent fighting strong momentum.
4. Volatility Regime Detection: Uses ATR analysis to detect "Fat Tail" events (Black Swans). If volatility expands beyond 2.5x the norm, the system pauses to protect capital from chaotic market conditions.
5. Advanced Money Management (Kelly Criterion): Includes a live dashboard that calculates the Half-Kelly Criterion, offering a mathematically optimal position size suggestion based on the strategy's real-time Win Rate and Payoff Ratio.
How to Use the Dashboard:
• Live Z-Score: Shows how many deviations the current price is from the mean. (Red values indicate extreme anomalies).
• Trend Strength (R^2): If this is Red (>0.80), do NOT open counter-trend positions manually.
• Kelly Rec %: Suggests the optimal % of equity to risk for the next trade to maximize geometric growth while minimizing the risk of ruin.
Disclaimer: This is a quantitative tool for statistical analysis. Past performance in backtests does not guarantee future results. Always manage your risk.
The ERAK Quantitative Gaussian Edge is not a traditional trading indicator; it is a probabilistic mathematical model designed to identify statistical anomalies in asset prices. Unlike classical indicators (RSI, MACD) that rely on lagging price derivatives, this algorithm utilizes Linear Regression Analysis and Gaussian Distribution (Normal Distribution) theory to determine the probability of a Mean Reversion event.
Core Philosophy
Markets are stochastic, but they exhibit "Fat Tail" behavior. This strategy operates on the principle that while prices wander, they are mathematically tethered to a "Center of Gravity" (Mean). When the price deviates significantly (Z-Score > 2.5 Sigma) from this mean without fundamental justification, it presents a high-probability arbitrage opportunity to trade back toward equilibrium.
Key Features & Mathematical Logic:
1. Dynamic Linear Regression Channel: Instead of simple Moving Averages (which lag significantly), we use a Linear Regression Curve to establish the "Fair Value" of the asset in real-time.
2. Statistical Z-Score Trigger: Entries are not based on arbitrary levels but on Standard Deviation (Sigma).
• Entry: Occurs when price hits ±2.5 Sigma (Statistically, this represents the outer ~1% of price occurrences).
• Exit: Occurs when price reverts to the mean (Expected Value).
3. R-Squared (R^2) Trend Filter: To avoid "catching a falling knife," the algorithm calculates the Coefficient of Determination (R^2).
• If R^2 > 0.80, it implies a strong deterministic trend. The system blocks counter-trend trades to prevent fighting strong momentum.
4. Volatility Regime Detection: Uses ATR analysis to detect "Fat Tail" events (Black Swans). If volatility expands beyond 2.5x the norm, the system pauses to protect capital from chaotic market conditions.
5. Advanced Money Management (Kelly Criterion): Includes a live dashboard that calculates the Half-Kelly Criterion, offering a mathematically optimal position size suggestion based on the strategy's real-time Win Rate and Payoff Ratio.
How to Use the Dashboard:
• Live Z-Score: Shows how many deviations the current price is from the mean. (Red values indicate extreme anomalies).
• Trend Strength (R^2): If this is Red (>0.80), do NOT open counter-trend positions manually.
• Kelly Rec %: Suggests the optimal % of equity to risk for the next trade to maximize geometric growth while minimizing the risk of ruin.
Disclaimer: This is a quantitative tool for statistical analysis. Past performance in backtests does not guarantee future results. Always manage your risk.
Note di rilascio
OverviewThe ERAK Quantitative Gaussian Edge is not a traditional trading indicator; it is a probabilistic mathematical model designed to identify statistical anomalies in asset prices. Unlike classical indicators (RSI, MACD) that rely on lagging price derivatives, this algorithm utilizes Linear Regression Analysis and Gaussian Distribution (Normal Distribution) theory to determine the probability of a Mean Reversion event.
Core Philosophy
Markets are stochastic, but they exhibit "Fat Tail" behavior. This strategy operates on the principle that while prices wander, they are mathematically tethered to a "Center of Gravity" (Mean). When the price deviates significantly (Z-Score > 2.5 Sigma) from this mean without fundamental justification, it presents a high-probability arbitrage opportunity to trade back toward equilibrium.
Key Features & Mathematical Logic:
1. Dynamic Linear Regression Channel: Instead of simple Moving Averages (which lag significantly), we use a Linear Regression Curve to establish the "Fair Value" of the asset in real-time.
2. Statistical Z-Score Trigger: Entries are not based on arbitrary levels but on Standard Deviation (Sigma).
• Entry: Occurs when price hits ±2.5 Sigma (Statistically, this represents the outer ~1% of price occurrences).
• Exit: Occurs when price reverts to the mean (Expected Value).
3. R-Squared (R^2) Trend Filter: To avoid "catching a falling knife," the algorithm calculates the Coefficient of Determination (R^2).
• If R^2 > 0.80, it implies a strong deterministic trend. The system blocks counter-trend trades to prevent fighting strong momentum.
4. Volatility Regime Detection: Uses ATR analysis to detect "Fat Tail" events (Black Swans). If volatility expands beyond 2.5x the norm, the system pauses to protect capital from chaotic market conditions.
5. Advanced Money Management (Kelly Criterion): Includes a live dashboard that calculates the Half-Kelly Criterion, offering a mathematically optimal position size suggestion based on the strategy's real-time Win Rate and Payoff Ratio.
How to Use the Dashboard:
• Live Z-Score: Shows how many deviations the current price is from the mean. (Red values indicate extreme anomalies).
• Trend Strength (R^2): If this is Red (>0.80), do NOT open counter-trend positions manually.
• Kelly Rec %: Suggests the optimal % of equity to risk for the next trade to maximize geometric growth while minimizing the risk of ruin.
Disclaimer: This is a quantitative tool for statistical analysis. Past performance in backtests does not guarantee future results. Always manage your risk.
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Script protetto
Questo script è pubblicato come codice protetto. Tuttavia, è possibile utilizzarle liberamente e senza alcuna limitazione – ulteriori informazioni qui.
Declinazione di responsabilità
Le informazioni e le pubblicazioni non sono intese come, e non costituiscono, consulenza o raccomandazioni finanziarie, di investimento, di trading o di altro tipo fornite o approvate da TradingView. Per ulteriori informazioni, consultare i Termini di utilizzo.