Multiple Colored Moving AveragesMULTIPLE COLORED MOVING AVERAGES - USER GUIDE
DISCLAIMER
----------
Both the code and this documentation were created heavily using artificial intelligence. I'm lazy...
This indicator was inspired by repo32's "Moving Average Colored EMA/SMA" indicator. *
What is this indicator?
-----------------------
This is a TradingView indicator that displays up to 4 different moving averages on your chart simultaneously. Each moving average can be customized with different calculation methods, colors, and filtering options.
Why would I use multiple moving averages?
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- See trend direction across different timeframes at once
- Identify support and resistance levels
- Spot crossover signals between fast and slow MAs
- Reduce false signals with filtering options
- Compare how different MA types react to price action
What moving average types are available?
----------------------------------------
11 different types:
- SMA: Simple average, equal weight to all periods
- EMA: Exponential, more weight to recent prices
- WMA: Weighted, linear weighting toward recent data
- RMA: Running average, smooth like EMA
- DEMA: Double exponential, reduced lag
- TEMA: Triple exponential, even less lag
- HMA: Hull, fast and smooth combination
- VWMA: Volume weighted, includes volume data
- LSMA: Least squares, based on linear regression
- TMA: Triangular, double-smoothed
- ZLEMA: Zero lag exponential, compensated for lag
How do I set up the indicator?
------------------------------
Each MA has these settings:
- Enable/Disable: Turn each MA on or off
- Type: Choose from the 11 calculation methods
- Length: Number of periods (21, 50, 100, 200 are common)
- Smoothing: 0-10 levels of extra smoothing
- Noise Filter: 0-5% to ignore small changes
- Colors: Bullish (rising) and bearish (falling) colors
- Line Width: 1-5 pixels thickness
What does the smoothing feature do?
-----------------------------------
Smoothing applies extra calculations to make the moving average line smoother. Higher levels reduce noise but make the MA respond slower to price changes. Use higher smoothing in choppy markets, lower smoothing in trending markets.
What is the noise filter?
--------------------------
The noise filter ignores small percentage changes in the moving average. For example, a 0.3% filter will ignore any MA movement smaller than 0.3%. This helps eliminate false signals from minor price fluctuations.
When should I use this indicator?
---------------------------------
- Trend analysis: See if market is going up, down, or sideways
- Entry timing: Look for price bounces off MA levels
- Exit signals: Watch for MA slope changes or crossovers
- Support/resistance: MAs often act as dynamic levels
- Multi-timeframe analysis: Use different lengths for different perspectives
What are some good settings to start with?
-------------------------------------------
Conservative approach:
- MA 1: EMA 21 (short-term trend)
- MA 2: SMA 50 (medium-term trend)
- MA 3: SMA 200 (long-term trend)
- Low noise filtering (0.1-0.3%)
Active trading:
- MA 1: HMA 9 (very responsive)
- MA 2: EMA 21 (short-term)
- MA 3: EMA 50 (medium-term)
- Minimal or no smoothing
How do I interpret the colors?
------------------------------
Each MA changes color based on its direction:
- Bullish color: MA is rising (upward trend)
- Bearish color: MA is falling (downward trend)
- Gray: MA is flat or unchanged
What should I look for in crossovers?
-------------------------------------
- Golden Cross: Fast MA crosses above slow MA (bullish signal)
- Death Cross: Fast MA crosses below slow MA (bearish signal)
- Multiple crossovers in same direction can confirm trend changes
- Wait for clear separation between MAs after crossover
How do I use MAs for support and resistance?
---------------------------------------------
- In uptrends: MAs often provide support when price pulls back
- In downtrends: MAs may act as resistance on rallies
- Multiple MAs create support/resistance zones
- Stronger levels where multiple MAs cluster together
Can I use this with other indicators?
-------------------------------------
Yes, it works well with:
- Volume indicators for confirmation
- RSI or MACD for timing entries
- Bollinger Bands for volatility context
- Price action patterns for setup confirmation
What if I get too many signals?
-------------------------------
- Increase smoothing levels
- Raise noise filter percentages
- Use longer MA periods
- Focus on major crossovers only
- Wait for multiple MA confirmation
What if signals are too slow?
-----------------------------
- Reduce smoothing to 0
- Lower noise filter values
- Switch to faster MA types (HMA, ZLEMA, DEMA)
- Use shorter periods
- Focus on the fastest MA only
Which MA types work best in different markets?
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Trending markets: EMA, DEMA, TEMA (responsive to trends)
Choppy markets: SMA, TMA, HMA with smoothing (less whipsaws)
High volatility: Use higher smoothing and noise filtering
Low volatility: Use minimal filtering for better responsiveness
Do I need all the advanced features?
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No. Start with basic settings:
- Choose MA type and length
- Set colors you prefer
- Leave smoothing at 0
- Leave noise filter at 0
Add complexity only if needed to improve signal quality.
How do I know if my settings are working?
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- Backtest on historical data
- Paper trade the signals first
- Adjust based on market conditions
- Keep a trading journal to track performance
- Be willing to modify settings as markets change
Can I save different configurations?
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Yes, save different indicator templates in TradingView for:
- Different trading styles (scalping, swing trading)
- Different market conditions (trending, ranging)
- Different instruments (stocks, forex, crypto)
Search in scripts for "scalping"
Market Order Risk CalculatorObviously the Long/Short Position tool does this, but when you are scalping, 10 - 15 seconds matters. What matters more than that is defined risk, you dont want your losses being scattered, 300 here 145 there, you want consistent risk to have consistent data.
What this does is when you are framing a trade, it provides a hands off tool that tells you exactly how many contracts to enter with, that way if you have bracket orders on, your stop will be exactly where you want it to be without going over your defined risk.
Blueprint Signals ProBlueprint Signals Pro is an advanced, all-in-one trading indicator designed for TradingView, built to provide high-quality buy/sell signals across various markets including cryptocurrencies, U.S. stocks, Indian indices, forex, and more. 📈 It leverages a proprietary ATR-based trailing stop mechanism combined with AI-optimized profiles for different trading styles (scalping, intraday, swing, and position trading) to generate reliable signals on bar close.
Key Features:
📊 Market Optimization: Tailored options for specific markets like Cryptocurrency (high volatility, 24/7 trading), U.S. Stocks (regulated exchanges, standard hours), Indian Indices (local dynamics like NIFTY), and Forex (high liquidity, global influences) to customize parameters and enhance signal accuracy.
🎨 Theme & Palette Customization: Supports dark/light chart themes with multiple color palettes for visual appeal.
🤖 Trading Profiles: Pre-built AI profiles like "Edge Signal", "Flash Signal", "Trend Rider", etc., tailored to your timeframe and style.
🔍 Signal Filters: Bullish/Bearish modes to focus on one-sided signals, with adjustable candle opacity.
🛡️ Support/Resistance Zones: Dynamic S/R levels with auto-adjusting lookback and wick warning markers for potential reversals.
⚠️ Swing Pattern Failure (SPF): Detects failure patterns with volume and wick filters for early reversal alerts.
🚨 Warnings: Proximity and wick-touch alerts on the trailing stop to signal momentum loss or trend challenges.
💡 Premium/Discount Zones: Neon-style P&D zones with glow effects to identify overvalued/undervalued areas.
📉 Custom Moving Averages: Up to 3 configurable MAs (EMA/SMA/WMA/HMA) with theme-based colors.
⚙️ Core Parameters: Manual/auto-tuning for scaling factor, period, min move filter, and anti-chop sensitivity.
⭐ Confidence Rating: Scores signals (Weak/Moderate/Strong) based on trend, S/R proximity, and volume.
🎯 SL/TP Levels: Displays stop loss (ATR trail, swing, or fixed ATR) and multiple take profits with R:R ratios, extendable lines, and zone fills. Additionally, clearly shows captured points/pips (e.g., +50 pts) and potential profit in points/pips/₹ for each level, making risk-reward analysis straightforward and visible on the chart.
🖥️ Display Options: Toggle trailing stop, text on signals, and more.
📅 Dashboard: Multi-timeframe overview with trend intelligence (using ADX), confidence, and candle timer.
🔔 Alerts: Configurable for buy/sell signals with detailed messages.
Usage Guidelines:
Select your market, theme, and trading style from the inputs.
Use on any timeframe; auto-adjusts for optimal performance.
Signals are confirmed on bar close to avoid repainting.
Combine with your risk management; backtest thoroughly.
This indicator is for educational and informational purposes only. Past performance is not indicative of future results. Trade at your own risk. © 2025 Raza | Blueprint Signals. All Rights Reserved.
Information Flow Analysis[b🔄 Information Flow Analysis: Systematic Multi-Component Market Analysis Framework
SYSTEM OVERVIEW AND ANALYTICAL FOUNDATION
The Information Flow Kernel - Hybrid combines established technical analysis methods into a unified analytical framework. This indicator systematically processes three distinct data streams - directional price momentum, volume-weighted pressure dynamics, and intrabar development patterns - integrating them through weighted mathematical fusion to produce statistically normalized market flow measurements.
COMPREHENSIVE MATHEMATICAL FRAMEWORK
Component 1: Directional Flow Analysis
The directional component analyzes price momentum through three mathematical vectors:
Price Vector: p = C - O (intrabar directional bias)
Momentum Vector: m = C_t - C_{t-1} (bar-to-bar velocity)
Acceleration Vector: a = m_t - m_{t-1} (momentum rate of change)
Directional Signal Integration:
S_d = \text{sgn}(p) \cdot |p| + \text{sgn}(m) \cdot |m| \cdot 0.6 + \text{sgn}(a) \cdot |a| \cdot 0.3
The signum function preserves directional information while absolute values provide magnitude weighting. Coefficients create a hierarchy emphasizing intrabar movement (100%), momentum (60%), and acceleration (30%).
Final Directional Output: K_1 = S_d \cdot w_d where w_d is the directional weight parameter.
Component 2: Volume-Weighted Pressure Analysis
Volume Normalization: r_v = \frac{V_t}{\overline{V_n}} where \overline{V_n} represents the n-period simple moving average of volume.
Base Pressure Calculation: P_{base} = \Delta C \cdot r_v \cdot w_v where \Delta C = C_t - C_{t-1} and w_v is the velocity weighting factor.
Volume Confirmation Function:
f(r_v) = \begin{cases}
1.4 & \text{if } r_v > 1.2 \
0.7 & \text{if } r_v < 0.8 \
1.0 & \text{otherwise}
\end{cases}
Final Pressure Output: K_2 = P_{base} \cdot f(r_v)
Component 3: Intrabar Development Analysis
Bar Position Calculation: B = \frac{C - L}{H - L} when H - L > 0 , else B = 0.5
Development Signal Function:
S_{dev} = \begin{cases}
2(B - 0.5) & \text{if } B > 0.6 \text{ or } B < 0.4 \
0 & \text{if } 0.4 \leq B \leq 0.6
\end{cases}
Final Development Output: K_3 = S_{dev} \cdot 0.4
Master Integration and Statistical Normalization
Weighted Component Fusion: F_{raw} = 0.5K_1 + 0.35K_2 + 0.15K_3
Sensitivity Scaling: F_{master} = F_{raw} \cdot s where s is the sensitivity parameter.
Statistical Normalization Process:
Rolling Mean: \mu_F = \frac{1}{n}\sum_{i=0}^{n-1} F_{master,t-i}
Rolling Standard Deviation: \sigma_F = \sqrt{\frac{1}{n}\sum_{i=0}^{n-1} (F_{master,t-i} - \mu_F)^2}
Z-Score Computation: z = \frac{F_{master} - \mu_F}{\sigma_F}
Boundary Enforcement: z_{bounded} = \max(-3, \min(3, z))
Final Normalization: N = \frac{z_{bounded}}{3}
Flow Metrics Calculation:
Intensity: I = |z|
Strength Percentage: S = \min(100, I \times 33.33)
Extreme Detection: \text{Extreme} = I > 2.0
DETAILED INPUT PARAMETER SPECIFICATIONS
Sensitivity (0.1 - 3.0, Default: 1.0)
Global amplification multiplier applied to the master flow calculation. Functions as: F_{master} = F_{raw} \cdot s
Low Settings (0.1 - 0.5): Enhanced precision for subtle market movements. Optimal for low-volatility environments, scalping strategies, and early detection of minor directional shifts. Increases responsiveness but may amplify noise.
Moderate Settings (0.6 - 1.2): Balanced sensitivity for standard market conditions across multiple timeframes.
High Settings (1.3 - 3.0): Reduced sensitivity to minor fluctuations while emphasizing significant flow changes. Ideal for high-volatility assets, trending markets, and longer timeframes.
Directional Weighting (0.1 - 1.0, Default: 0.7)
Controls emphasis on price direction versus volume and positioning factors. Applied as: K_{1,weighted} = K_1 \times w_d
Lower Values (0.1 - 0.4): Reduces directional bias, favoring volume-confirmed moves. Optimal for ranging markets where momentum may generate false signals.
Higher Values (0.7 - 1.0): Amplifies directional signals from price vectors and acceleration. Ideal for trending conditions where directional momentum drives price action.
Velocity Weighting (0.1 - 1.0, Default: 0.6)
Scales volume-confirmed price change impact. Applied in: P_{base} = \Delta C \times r_v \times w_v
Lower Values (0.1 - 0.4): Dampens volume spike influence, focusing on sustained pressure patterns. Suitable for illiquid assets or news-sensitive markets.
Higher Values (0.8 - 1.0): Amplifies high-volume directional moves. Optimal for liquid markets where volume provides reliable confirmation.
Volume Length (3 - 20, Default: 5)
Defines lookback period for volume averaging: \overline{V_n} = \frac{1}{n}\sum_{i=0}^{n-1} V_{t-i}
Short Periods (3 - 7): Responsive to recent volume shifts, excellent for intraday analysis.
Long Periods (13 - 20): Smoother averaging, better for swing trading and higher timeframes.
DASHBOARD SYSTEM
Primary Flow Gauge
Bilaterally symmetric visualization displaying normalized flow direction and intensity:
Segment Calculation: n_{active} = \lfloor |N| \times 15 \rfloor
Left Fill: Bearish flow when N < -0.01
Right Fill: Bullish flow when N > 0.01
Neutral Display: Empty segments when |N| \leq 0.01
Visual Style Options:
Matrix: Digital blocks (▰/▱) for quantitative precision
Wave: Progressive patterns (▁▂▃▄▅▆▇█) showing flow buildup
Dots: LED-style indicators (●/○) with intensity scaling
Blocks: Modern squares (■/□) for professional appearance
Pulse: Progressive markers (⎯ to █) emphasizing intensity buildup
Flow Intensity Visualization
30-segment horizontal bar graph with mathematical fill logic:
Segment Fill: For i \in : filled if \frac{i}{29} \leq \frac{S}{100}
Color Coding System:
Orange (S > 66%): High intensity, strong directional conviction
Cyan (33% ≤ S ≤ 66%): Moderate intensity, developing bias
White (S < 33%): Low intensity, neutral conditions
Extreme Detection Indicators
Circular markers flanking the gauge with state-dependent illumination:
Activation: I > 2.0 \land |N| > 0.3
Bright Yellow: Active extreme conditions
Dim Yellow: Normal conditions
Metrics Display
Balance Value: Raw master flow output ( F_{master} ) showing absolute directional pressure
Z-Score Value: Statistical deviation ( z_{bounded} ) indicating historical context
Dynamic Narrative System
Context-sensitive interpretation based on mathematical thresholds:
Extreme Flow: I > 2.0 \land |N| > 0.6
Moderate Flow: 0.3 < |N| \leq 0.6
High Volatility: S > 50 \land |N| \leq 0.3
Neutral State: S \leq 50 \land |N| \leq 0.3
ALERT SYSTEM SPECIFICATIONS
Mathematical Trigger Conditions:
Extreme Bullish: I > 2.0 \land N > 0.6
Extreme Bearish: I > 2.0 \land N < -0.6
High Intensity: S > 80
Bullish Shift: N_t > 0.3 \land N_{t-1} \leq 0.3
Bearish Shift: N_t < -0.3 \land N_{t-1} \geq -0.3
TECHNICAL IMPLEMENTATION AND PERFORMANCE
Computational Architecture
The system employs efficient calculation methods minimizing processing overhead:
Single-pass mathematical operations for all components
Conditional visual rendering (executed only on final bar)
Optimized array operations using direct calculations
Real-Time Processing
The indicator updates continuously during bar formation, providing immediate feedback on changing market conditions. Statistical normalization ensures consistent interpretation across varying market regimes.
Market Applicability
Optimal performance in liquid markets with consistent volume patterns. May require parameter adjustment for:
Low-volume or after-hours sessions
News-driven market conditions
Highly volatile cryptocurrency markets
Ranging versus trending market environments
PRACTICAL APPLICATION FRAMEWORK
Market State Classification
This indicator functions as a comprehensive market condition assessment tool providing:
Trend Analysis: High intensity readings ( S > 66% ) with sustained directional bias indicate strong trending conditions suitable for momentum strategies.
Reversal Detection: Extreme readings ( I > 2.0 ) at key technical levels may signal potential trend exhaustion or reversal points.
Range Identification: Low intensity with neutral flow ( S < 33%, |N| < 0.3 ) suggests ranging market conditions suitable for mean reversion strategies.
Volatility Assessment: High intensity without clear directional bias indicates elevated volatility with conflicting pressures.
Integration with Trading Systems
The normalized output range facilitates integration with automated trading systems and position sizing algorithms. The statistical basis provides consistent interpretation across different market conditions and asset classes.
LIMITATIONS AND CONSIDERATIONS
This indicator combines established technical analysis methods and processes historical data without predicting future price movements. The system performs optimally in liquid markets with consistent volume patterns and may produce false signals in thin trading conditions or during news-driven market events. This indicator is provided for educational and analytical purposes only and does not constitute financial advice. Users should combine this analysis with proper risk management, position sizing, and additional confirmation methods before making any trading decisions. Past performance does not guarantee future results.
Note: The term "kernel" in this context refers to modular calculation components rather than mathematical kernel functions in the formal computational sense.
As quantitative analyst Ralph Vince noted: "The essence of successful trading lies not in predicting market direction, but in the systematic processing of market information and the disciplined management of probability distributions."
— Dskyz, Trade with insight. Trade with anticipation.
Ravi Raj rending Intraday BotTrend Reversal Catching
🔹 Features:
✅ Buy & Sell signals with proper confirmation
✅ Dynamic support & resistance levels
✅ Trend direction + reversal detection
✅ Risk management (Stop Loss & Target levels)
✅ Works on Nifty, BankNifty, Stocks & Options
🔹 Best Timeframe:
5 Min, 15 Min (Intraday Trading)
Works on both Index & Equity
🔹 Trading Style:
Scalping
Momentum Trading
Ravi Raj rending Intraday Bot
8102106608 udhwa
Trend-Strong Candle - 3 EMAs with Filters# Trend-Strong Candle - Professional Trading Indicator
## 📊 What It Does
Identifies high-probability entries by combining triple EMA trend analysis with strong candle detection. Only signals when all conditions align for maximum accuracy.
## 🎯 Core Features
- Triple EMA System: Fast (20) / Medium (50) / Slow (200) for trend confirmation
- Strong Candle Filter: ATR-based sizing ensures genuine momentum
- Advanced Filters: EMA close validation + trend stability checks
- Live Alerts: Instant notifications for real-time signals
- Session Filter: Trade only during active EU/US market hours
## ⚡ Quick Setup
Scalping (1-5min): Default settings + enable session filter
Day Trading (15-60min): Default settings work perfectly
Swing Trading (4H+): Increase ATR multiplier to 0.8-1.0
## 📈 Trading Rules
Long Signals: Green triangle below candle
- Strong bullish candle during confirmed uptrend
- All EMAs properly aligned (Fast > Medium > Slow)
Short Signals: Red triangle above candle
- Strong bearish candle during confirmed downtrend
- All EMAs properly aligned (Fast < Medium < Slow)
## ⚠️ Critical Success Factors
1. Always Verify the Trend Yourself
The indicator helps identify signals, but YOU must confirm the larger trend context. Check higher timeframes and overall market structure before entering.
2. Understand the "Big Players"
Strong candles in trend direction usually come from institutional money (banks, funds, algorithms). These create the momentum that retail traders can follow. The indicator catches these institutional moves.
3. Distance to Next Value Level
NEVER enter if price is too close to major resistance/support levels:
- Check distance to round numbers (1.1000, 1.1050, etc.)
- Ensure at least 20-30 pips room to next key level
- You need space for profit - tight levels = limited upside
4. Risk Management
- Stop Loss: 1-2 ATR from entry
- Take Profit: 2-3 ATR target (minimum 1:2 R/R)
- Position Size: Risk max 1-2% per trade
## 💡 Pro Tips
- Best Sessions: London open (8-12 UTC) and NY open (13-17 UTC)
- Avoid: Major news, low liquidity periods, choppy markets
- Multiple Timeframes: Confirm signals on higher timeframe
- Value Levels: Always check daily/weekly support/resistance before entering
## 🎯 Success Formula
Trend Confirmation + Strong Institutional Candle + Distance to Value Levels = High Probability Trade
*
Remember: The indicator finds the signals, but successful trading requires your analysis of trend context and value level positioning. Trade smart, not just frequent.
SPPO - Statistical Price Position OscillatorSPPO - Statistical Price Position Oscillator
=== INDICATOR OVERVIEW ===
The Statistical Price Position Oscillator (SPPO) is an innovative technical analysis tool built on rigorous statistical principles. Unlike traditional oscillators that rely on fixed periods or subjective thresholds, SPPO uses dynamic statistical modeling to assess where current prices stand within their historical distribution.
=== KEY FEATURES ===
• Statistical Foundation: Based on normal distribution theory and Z-Score standardization
• Dynamic Parameter Adjustment: Automatically adapts to market volatility conditions
• Probability Quantification: Provides objective probability assessments for price levels
• Multi-Layer Visual System: Six layers of information encoding (line position, color intensity, line width, background, histogram, data panel)
• Professional Color Schemes: Multiple themes optimized for different trading environments
• Real-time Risk Assessment: Quantifies the statistical significance of current price positions
=== CORE COMPONENTS ===
1. SPPO Main Line
- Represents the standardized price position (Z-Score × Sensitivity)
- Dynamic line width: Normal (2px) for |Z| ≤ 1.0, Bold (6px) for extreme deviations
- Color coding: Neutral (gray) for normal range, Orange/Yellow for moderate deviation, Blue/Purple for extreme deviation
2. SPPO Histogram (Momentum Bars)
- Measures the momentum of statistical deviation, not price momentum
- Calculated as: (Current Z-Score - EMA of Z-Score) × Sensitivity
- Helps identify momentum divergences and trend continuation/reversal signals
3. Intelligent Data Panel
- Real-time display of key statistical metrics
- Shows: Price Position, Z-Score, Probability, Momentum, Deviation Classification, Market Regime
- Dynamic parameter display for transparency
4. Adaptive Background System
- Visual representation of market regimes
- Color intensity based on statistical significance
- Helps quickly identify extreme market conditions
=== PARAMETER SETTINGS ===
Core Parameters:
• Distribution Period (30-120, default 50): Statistical calculation window based on Central Limit Theorem
• Range Evaluation Period (10-100, default 14): Price range assessment window
• Position Sensitivity (0.5-4.0, default 2.5): Indicator responsiveness factor
• Probability Threshold (0.01-0.2, default 0.03): Signal trigger threshold
Confidence Intervals:
• 1σ Confidence (60%-75%, default 68%): Normal range boundary
• 2σ Confidence (90%-98%, default 95%): Significant deviation boundary
• 3σ Confidence (99.5%-99.9%, default 99.7%): Extreme deviation boundary
Dynamic Adjustment:
• Enable Dynamic Adjustment: Automatically optimizes parameters based on market volatility
• Volatility Lookback (10-50, default 10): Period for volatility assessment
• Dynamic Sensitivity Multiplier (0.5-3.0, default 1.5): Volatility-based sensitivity adjustment
=== MATHEMATICAL FOUNDATION ===
SPPO is built on several key mathematical concepts:
1. Z-Score Standardization: Z = (X - μ) / σ
Where X = current price, μ = mean, σ = standard deviation
2. Normal Distribution Theory: Assumes prices follow normal distribution within rolling windows
3. Probability Density Function: PDF(z) = e^(-z²/2) / √(2π)
4. Cumulative Distribution Function: Approximates tail probabilities for extreme events
5. Dynamic Parameter Optimization: Adjusts calculation parameters based on market volatility percentiles
=== TRADING APPLICATIONS ===
1. Mean Reversion Strategy
- Entry: SPPO > +8 or < -8 with probability < 5%
- Confirmation: Momentum histogram showing divergence
- Exit: SPPO returns to ±3 range
2. Trend Confirmation
- Trend continuation: SPPO and histogram aligned
- Trend exhaustion: Extreme SPPO with weakening histogram
- Breakout validation: SPPO breaking confidence intervals with volume
3. Risk Management
- Position sizing based on probability inverse
- Stop-loss when SPPO extends beyond ±12
- Take-profit at statistical mean reversion levels
=== MARKET REGIME CLASSIFICATION ===
• Normal Range (|SPPO| < 3): Trend-following strategies preferred
• Moderate Deviation (3 < |SPPO| < 8): Cautious mean reversion with partial positions
• Extreme Deviation (|SPPO| > 8): Aggressive mean reversion with strict risk management
=== TIMEFRAME RECOMMENDATIONS ===
• Short-term Trading (30-50 period): Intraday scalping, high sensitivity
• Medium-term Analysis (50-80 period): Swing trading, balanced sensitivity
• Long-term Trends (80-120 period): Position trading, statistical stability focus
=== UNIQUE ADVANTAGES ===
1. Objective Signal Generation: Every signal backed by statistical probability
2. Self-Adaptive System: Automatically adjusts to changing market conditions
3. Multi-Dimensional Information: Six layers of visual information in single indicator
4. Universal Application: Works across all markets and timeframes
5. Risk Quantification: Provides probability-based risk assessment
6. Professional Visualization: Institutional-grade color schemes and data presentation
=== TECHNICAL SPECIFICATIONS ===
• Pine Script Version: v6 compatible
• Maximum Bars Back: 500 (optimized for performance)
• Calculation Efficiency: Incremental updates with caching
• Memory Management: Dynamic array sizing with intelligent cleanup
• Rendering Optimization: Conditional rendering to reduce resource consumption
=== ALERT CONDITIONS ===
• Extreme Probability Alert: Triggered when probability < extreme threshold
• Buy Signal Alert: Statistical mean reversion buy conditions met
• Sell Signal Alert: Statistical mean reversion sell conditions met
• High Volatility Alert: Market enters high volatility regime (>90th percentile)
=== COMPATIBILITY ===
• Asset Classes: Stocks, Forex, Commodities, Cryptocurrencies, Indices
• Timeframes: All standard timeframes (1m to 1M)
• Market Sessions: 24/7 markets and traditional market hours
• Data Requirements: Minimum 120 bars for optimal statistical accuracy
=== PERFORMANCE OPTIMIZATION ===
• Efficient Algorithms: Uses Pine Script built-in functions for optimal speed
• Memory Management: Limited historical data caching to prevent overflow
• Rendering Optimization: Layered rendering system reduces redraw overhead
• Precision Balance: Optimized balance between calculation accuracy and performance
=== RISK DISCLAIMER ===
SPPO is a statistical analysis tool designed to assist in market analysis. While based on rigorous mathematical principles, it should not be used as the sole basis for trading decisions. Always combine SPPO analysis with:
• Fundamental analysis
• Risk management practices
• Market context awareness
• Position sizing discipline
Past performance does not guarantee future results. Trading involves substantial risk of loss.
=== SUPPORT AND DOCUMENTATION ===
For detailed technical documentation, implementation examples, and advanced strategies, please refer to the comprehensive SPPO Technical Documentation included with this indicator.
=== VERSION INFORMATION ===
Current Version: 2.0
Last Updated: 2024
Compatibility: Pine Script v6
Author:
=== CONCLUSION ===
SPPO represents a significant advancement in technical analysis, bringing institutional-grade statistical modeling to retail traders. Its combination of mathematical rigor, adaptive intelligence, and professional visualization makes it an invaluable tool for traders seeking objective, probability-based market analysis.
The indicator's unique approach to quantifying price position within statistical distributions provides traders with unprecedented insight into market extremes and mean reversion opportunities, while its self-adaptive nature ensures consistent performance across varying market conditions.
SPPO - Statistical Price Position OscillatorSPPO - Statistical Price Position Oscillator
=== INDICATOR OVERVIEW ===
The Statistical Price Position Oscillator (SPPO) is an innovative technical analysis tool built on rigorous statistical principles. Unlike traditional oscillators that rely on fixed periods or subjective thresholds, SPPO uses dynamic statistical modeling to assess where current prices stand within their historical distribution.
=== KEY FEATURES ===
• Statistical Foundation: Based on normal distribution theory and Z-Score standardization
• Dynamic Parameter Adjustment: Automatically adapts to market volatility conditions
• Probability Quantification: Provides objective probability assessments for price levels
• Multi-Layer Visual System: Six layers of information encoding (line position, color intensity, line width, background, histogram, data panel)
• Professional Color Schemes: Multiple themes optimized for different trading environments
• Real-time Risk Assessment: Quantifies the statistical significance of current price positions
=== CORE COMPONENTS ===
1. SPPO Main Line
- Represents the standardized price position (Z-Score × Sensitivity)
- Dynamic line width: Normal (2px) for |Z| ≤ 1.0, Bold (6px) for extreme deviations
- Color coding: Neutral (gray) for normal range, Orange/Yellow for moderate deviation, Blue/Purple for extreme deviation
2. SPPO Histogram (Momentum Bars)
- Measures the momentum of statistical deviation, not price momentum
- Calculated as: (Current Z-Score - EMA of Z-Score) × Sensitivity
- Helps identify momentum divergences and trend continuation/reversal signals
3. Intelligent Data Panel
- Real-time display of key statistical metrics
- Shows: Price Position, Z-Score, Probability, Momentum, Deviation Classification, Market Regime
- Dynamic parameter display for transparency
4. Adaptive Background System
- Visual representation of market regimes
- Color intensity based on statistical significance
- Helps quickly identify extreme market conditions
=== PARAMETER SETTINGS ===
Core Parameters:
• Distribution Period (30-120, default 50): Statistical calculation window based on Central Limit Theorem
• Range Evaluation Period (10-100, default 14): Price range assessment window
• Position Sensitivity (0.5-4.0, default 2.5): Indicator responsiveness factor
• Probability Threshold (0.01-0.2, default 0.03): Signal trigger threshold
Confidence Intervals:
• 1σ Confidence (60%-75%, default 68%): Normal range boundary
• 2σ Confidence (90%-98%, default 95%): Significant deviation boundary
• 3σ Confidence (99.5%-99.9%, default 99.7%): Extreme deviation boundary
Dynamic Adjustment:
• Enable Dynamic Adjustment: Automatically optimizes parameters based on market volatility
• Volatility Lookback (10-50, default 10): Period for volatility assessment
• Dynamic Sensitivity Multiplier (0.5-3.0, default 1.5): Volatility-based sensitivity adjustment
=== MATHEMATICAL FOUNDATION ===
SPPO is built on several key mathematical concepts:
1. Z-Score Standardization: Z = (X - μ) / σ
Where X = current price, μ = mean, σ = standard deviation
2. Normal Distribution Theory: Assumes prices follow normal distribution within rolling windows
3. Probability Density Function: PDF(z) = e^(-z²/2) / √(2π)
4. Cumulative Distribution Function: Approximates tail probabilities for extreme events
5. Dynamic Parameter Optimization: Adjusts calculation parameters based on market volatility percentiles
=== TRADING APPLICATIONS ===
1. Mean Reversion Strategy
- Entry: SPPO > +8 or < -8 with probability < 5%
- Confirmation: Momentum histogram showing divergence
- Exit: SPPO returns to ±3 range
2. Trend Confirmation
- Trend continuation: SPPO and histogram aligned
- Trend exhaustion: Extreme SPPO with weakening histogram
- Breakout validation: SPPO breaking confidence intervals with volume
3. Risk Management
- Position sizing based on probability inverse
- Stop-loss when SPPO extends beyond ±12
- Take-profit at statistical mean reversion levels
=== MARKET REGIME CLASSIFICATION ===
• Normal Range (|SPPO| < 3): Trend-following strategies preferred
• Moderate Deviation (3 < |SPPO| < 8): Cautious mean reversion with partial positions
• Extreme Deviation (|SPPO| > 8): Aggressive mean reversion with strict risk management
=== TIMEFRAME RECOMMENDATIONS ===
• Short-term Trading (30-50 period): Intraday scalping, high sensitivity
• Medium-term Analysis (50-80 period): Swing trading, balanced sensitivity
• Long-term Trends (80-120 period): Position trading, statistical stability focus
=== UNIQUE ADVANTAGES ===
1. Objective Signal Generation: Every signal backed by statistical probability
2. Self-Adaptive System: Automatically adjusts to changing market conditions
3. Multi-Dimensional Information: Six layers of visual information in single indicator
4. Universal Application: Works across all markets and timeframes
5. Risk Quantification: Provides probability-based risk assessment
6. Professional Visualization: Institutional-grade color schemes and data presentation
=== TECHNICAL SPECIFICATIONS ===
• Pine Script Version: v6 compatible
• Maximum Bars Back: 500 (optimized for performance)
• Calculation Efficiency: Incremental updates with caching
• Memory Management: Dynamic array sizing with intelligent cleanup
• Rendering Optimization: Conditional rendering to reduce resource consumption
=== ALERT CONDITIONS ===
• Extreme Probability Alert: Triggered when probability < extreme threshold
• Buy Signal Alert: Statistical mean reversion buy conditions met
• Sell Signal Alert: Statistical mean reversion sell conditions met
• High Volatility Alert: Market enters high volatility regime (>90th percentile)
=== COMPATIBILITY ===
• Asset Classes: Stocks, Forex, Commodities, Cryptocurrencies, Indices
• Timeframes: All standard timeframes (1m to 1M)
• Market Sessions: 24/7 markets and traditional market hours
• Data Requirements: Minimum 120 bars for optimal statistical accuracy
=== PERFORMANCE OPTIMIZATION ===
• Efficient Algorithms: Uses Pine Script built-in functions for optimal speed
• Memory Management: Limited historical data caching to prevent overflow
• Rendering Optimization: Layered rendering system reduces redraw overhead
• Precision Balance: Optimized balance between calculation accuracy and performance
=== RISK DISCLAIMER ===
SPPO is a statistical analysis tool designed to assist in market analysis. While based on rigorous mathematical principles, it should not be used as the sole basis for trading decisions. Always combine SPPO analysis with:
• Fundamental analysis
• Risk management practices
• Market context awareness
• Position sizing discipline
Past performance does not guarantee future results. Trading involves substantial risk of loss.
=== SUPPORT AND DOCUMENTATION ===
For detailed technical documentation, implementation examples, and advanced strategies, please refer to the comprehensive SPPO Technical Documentation included with this indicator.
=== VERSION INFORMATION ===
Current Version: 2.0
Last Updated: 2024
Compatibility: Pine Script v6
Author:
=== CONCLUSION ===
SPPO represents a significant advancement in technical analysis, bringing institutional-grade statistical modeling to retail traders. Its combination of mathematical rigor, adaptive intelligence, and professional visualization makes it an invaluable tool for traders seeking objective, probability-based market analysis.
The indicator's unique approach to quantifying price position within statistical distributions provides traders with unprecedented insight into market extremes and mean reversion opportunities, while its self-adaptive nature ensures consistent performance across varying market conditions.
RSI Trend Navigator [QuantAlgo]🟢 Overview
The RSI Trend Navigator integrates RSI momentum calculations with adaptive exponential moving averages and ATR-based volatility bands to generate trend-following signals. The indicator applies variable smoothing coefficients based on RSI readings and incorporates normalized momentum adjustments to position a trend line that responds to both price action and underlying momentum conditions.
🟢 How It Works
The indicator begins by calculating and smoothing the RSI to reduce short-term fluctuations while preserving momentum information:
rsiValue = ta.rsi(source, rsiPeriod)
smoothedRSI = ta.ema(rsiValue, rsiSmoothing)
normalizedRSI = (smoothedRSI - 50) / 50
It then creates an adaptive smoothing coefficient that varies based on RSI positioning relative to the midpoint:
adaptiveAlpha = smoothedRSI > 50 ? 2.0 / (trendPeriod * 0.5 + 1) : 2.0 / (trendPeriod * 1.5 + 1)
This coefficient drives an adaptive trend calculation that responds more quickly when RSI indicates bullish momentum and more slowly during bearish conditions:
var float adaptiveTrend = source
adaptiveTrend := adaptiveAlpha * source + (1 - adaptiveAlpha) * nz(adaptiveTrend , source)
The normalized RSI values are converted into price-based adjustments using ATR for volatility scaling:
rsiAdjustment = normalizedRSI * ta.atr(14) * sensitivity
rsiTrendValue = adaptiveTrend + rsiAdjustment
ATR-based bands are constructed around this RSI-adjusted trend value to create dynamic boundaries that constrain trend line positioning:
atr = ta.atr(atrPeriod)
deviation = atr * atrMultiplier
upperBound = rsiTrendValue + deviation
lowerBound = rsiTrendValue - deviation
The trend line positioning uses these band constraints to determine its final value:
if upperBound < trendLine
trendLine := upperBound
if lowerBound > trendLine
trendLine := lowerBound
Signal generation occurs through directional comparison of the trend line against its previous value to establish bullish and bearish states:
trendUp = trendLine > trendLine
trendDown = trendLine < trendLine
if trendUp
isBullish := true
isBearish := false
else if trendDown
isBullish := false
isBearish := true
The final output colors the trend line green during bullish states and red during bearish states, creating visual buy/long and sell/short opportunity signals based on the combined RSI momentum and volatility-adjusted trend positioning.
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward momentum where RSI influence and adaptive smoothing favor continued price advancement = Potential buy/long positions
Declining Trend Line (Red): Indicates downward momentum where RSI influence and adaptive smoothing favor continued price decline = Potential sell/short positions
Flattening Trend Lines: Occur when momentum weakens and the trend line slope approaches neutral, suggesting potential consolidation before the next move
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, sending "RSI Trend Bullish Signal" or "RSI Trend Bearish Signal" messages for timely entry/exit
Color Bar Candles Option: Optional candle coloring feature that applies the same green/red trend colors to price bars, providing additional visual confirmation of the current trend direction
TRI - Multi-Timeframe BIASTRI - MULTI-TIMEFRAME BIAS INDICATOR
DESCRIPTION:
Advanced multi-timeframe bias indicator that analyzes market sentiment across
5 different timeframes (15m, 1h, 4h, 1d, 1w) using adaptive technical analysis.
Provides clear directional bias signals to help determine market momentum.
KEY FEATURES:
ADAPTIVE PARAMETERS: Uses different EMA lengths and weights for each timeframe
EMA TREND ANALYSIS: Fast/slow EMA crossovers with slope analysis for momentum
RSI MOMENTUM: Adaptive overbought/oversold levels based on timeframe
ADX STRENGTH: Directional movement confirmation with DI+/DI- analysis
COMPOSITE SCORING: Weighted combination of trend, momentum, and strength
TIMEFRAME ANALYSIS:
15m: EMA9/21 + High momentum weight (45%) - Ultra-responsive for scalping
1h: EMA21/50 + Medium momentum weight (35%) - Balanced for day trading
4h: EMA50/200 + Lower momentum weight (25%) - Swing trading focus
1d: EMA50/200 + Trend focused (55%) - Position trading signals
1w: EMA50/200 + Maximum trend weight (60%) - Long-term bias
BIAS SIGNALS:
STRONG BULLISH/BEARISH: Score ≥ 0.5 - Very strong directional momentum
BULLISH/BEARISH: Score ≥ 0.25 - Clear directional signals
WEAK BULLISH/BEARISH: Score ≥ 0.1 - Mild directional bias
NEUTRAL: Score < 0.1 - No clear directional preference
ALERTS:
Major Bullish/Bearish: When 4H and 1D timeframes align
High confidence signals for strategic decision making
USAGE:
Higher timeframes (1d, 1w) show primary market direction
Lower timeframes (15m, 1h) provide entry timing
Look for alignment across multiple timeframes for stronger signals
Use confidence levels to assess signal reliability
TECHNICAL COMPONENTS:
Exponential Moving Averages (EMA) for responsive trend detection
Relative Strength Index (RSI) for momentum analysis
Average Directional Index (ADX) with DI+/DI- for trend strength
Volume ratio confirmation for signal validation
Adaptive thresholds optimized for each timeframe's characteristics
ProfitAlgo.io TrendSync SimulationThe TrendSync Simulation is a gradient-based trend-following framework that helps traders quickly identify bullish vs bearish market structure while filtering out short-term noise.
Instead of relying on a single moving average or indicator, TrendSync builds a layered “trend cloud” in 3 different MODES, KUMO, PFA, HMA anchored against a reference band. These layers create a visual gradient that shifts with market direction.
When combined with its color-adaptive candles, you can turn off your candle setting colors within the chart settings of TradingView for the TrendSync color mapping which transforms raw price action into an easy-to-read flow map of institutional momentum.
📊 How It Works
Each layer creates a smooth gradient that shifts with trend direction:
Bullish trends form a rising, green-shaded cloud.
Bearish trends form a descending, red-shaded cloud.
Transitions appear as fading or compressing gradients, signaling potential reversals or consolidations.
Candles are also dynamically colored based on normalized momentum, allowing traders to see directional strength at a glance.
🔑 Key Features
✅ Gradient Cloud – A layered trend structure that visually shifts from bearish → bullish.
✅ Multiple Modes – Choose between KUMO, PFA, or HMA logic for responsiveness vs. smoothness.
✅ Dynamic Trend Candles – Bars adapt color based on momentum strength.
✅ Customizable Visualization – Adjust transparency, colors, and gradient strength to fit your chart style.
✅ Clarity of Direction – Highlights dominant flow while reducing noise from minor fluctuations.
⚙️ Settings Explained
Trend Method (KUMO / PFA / HMA): Controls the type of moving average used for the cloud.
Gradient Colors: Define the shading of bullish vs. bearish zones.
Transparency Controls: Adjust how strong or subtle the gradient cloud appears.
Lookback Length : Longer = smoother trend; shorter = more reactive.
💡 Use Cases
Identify trend bias quickly without switching between multiple indicators.
Confirm entries with liquidity or breakout strategies by aligning with the cloud.
Detect weakening or strengthening momentum via gradient compression.
Avoid trading against dominant higher time-frame flow with trend-colored candles .
⚡ Why It Matters
Markets often look chaotic on raw candlestick charts. TrendSync cuts through that noise by layering moving averages into a visual gradient, revealing institutional momentum in real time. Whether scalping, day trading, or swing trading, TrendSync provides a synchronized view of trend direction that adapts to different trading styles.
⚡ Paired with the Back End Order Matrix, TrendSync provides the clarity of direction after liquidity zones are exposed, creating a complete institutional-style framework inside TradingView.
EXAMPLE 1A
EXAMPLE 1B
EXAMPLE 1C
EXAMPLE 2A
Simple Enhanced MMAThe Enhanced MMA (Multi-Moving Average) Ribbon System
This is a comprehensive trend-following indicator that displays 28 moving averages simultaneously, creating a "ribbon" effect that reveals market structure at a glance. Think of it as a heat map of price momentum across multiple timeframes.
Key Components:
1. The Ribbon Structure:
Fast MAs (2-18): React quickly to price changes - for scalping and short-term momentum
Medium MAs (20-50): Core trend indicators - the "backbone" of the trend
Slow MAs (55-100): Long-term trend and major support/resistance levels
2. Visual Intelligence:
Green lines: MA is rising (bullish momentum)
Red lines: MA is falling (bearish momentum)
Yellow lines: Key levels at MA20 and MA50 (institutional favorites)
Cloud shading: Shows the relationship between MA20/50 - green cloud = bull market, red = bear market
How to Read It:
Ribbon Expansion/Compression:
When MAs spread apart → Strong trending market
When MAs compress together → Consolidation, potential breakout coming
When all MAs align in order → Powerful trend in progress
Trading Signals:
BUY signal: MA20 crosses above MA50 (Golden Cross)
SELL signal: MA20 crosses below MA50 (Death Cross)
Trend label: Shows overall market bias
Best Use Cases:
Trend confirmation - When all MAs are green and spreading = strong uptrend
Support/Resistance - MAs act as dynamic support in uptrends, resistance in downtrends
Entry timing - Wait for price to pull back to the ribbon in a trend
Trend exhaustion - When fast MAs start changing color while slow ones haven't = potential reversal
The Power of This Indicator:
It's like having 28 trend advisors all voting on market direction. When they all agree (all green or all red), you have high conviction. When they're mixed, the market is in transition. The ribbon literally shows you the "flow" of the market - you can see momentum ripple through the timeframes like a wave.
Pro tip: The most powerful moves happen when the ribbon goes from completely compressed (all MAs bunched together) to rapidly expanding in one direction - that's when big trends are born!
Key Levels: Daily, Weekly, Monthly [BackQuant]Key Levels: Daily, Weekly, Monthly
Map the market’s “memory” in one glance—yesterday’s range, this week’s chosen day high/low, and D/W/M opens—then auto-clean levels once they break.
What it does
This tool plots three families of high-signal reference lines and keeps them tidy as price evolves:
Chosen Day High/Low (per week) — Pick a weekday (e.g., Monday). For each past week, the script records that day’s session high and low and projects them forward for a configurable number of bars. These act like “memory levels” that price often revisits.
Daily / Weekly / Monthly Opens — Plots the opening price of each new day, week, and month with separate styling. These opens frequently behave like magnets/flip lines intraday and anchors for regime on higher timeframes.
Auto-pruning — When price breaks a stored level, the script can automatically remove it to reduce clutter and refocus you on still-active lines. See: (broken levels removed).
Why these levels matter
Liquidity pockets — Prior day’s high/low and the daily open concentrate stops and pending orders. Mapping them quickly reveals likely sweep or fade zones. Example: previous day highs + daily open highlighting liquidity:
Context & regime — Monthly opens frame macro bias; trading above a rising cluster of monthly opens vs. below gives a clean top-down read. Example: monthly-only “macro outlook” view:
Cleaner charts — Auto-remove broken lines so you focus on what still matters right now.
What it plots (at a glance)
Past Chosen Day High/Low for up to N prior weeks (your choice), extended right.
Current Daily Open , Weekly Open , and Monthly Open , each with its own color, label, and forward extension.
Optional short labels (e.g., “Mon High”) or full labels (with week/month info).
How breaks are detected & cleaned
You control both the evidence and the timing of a “break”:
Break uses — Choose Close (more conservative) or Wick (more sensitive).
Inclusive? — If enabled, equality counts (≥ high or ≤ low). If disabled, you need a strict cross.
Allow intraday breaks? — If on, a level can break during the tracked day; if off, the script only counts breaks after the session completes.
Remove Broken Levels — When a break is confirmed, the line/label is deleted automatically. (See the demo: )
Quick start
Pick a Day of Week to Track (e.g., Monday).
Set how many weeks back to show (e.g., 8–10).
Choose how far to extend each family (bars to the right for chosen-day H/L and D/W/M opens).
Decide if a break uses Close or Wick , and whether equality counts.
Toggle Remove Broken Levels to keep the chart clean automatically.
Tips by use-case
Intraday bias — Watch the Daily Open as a magnet/flip. If price gaps above and holds, pullbacks to the daily open often decide direction. Pair with last day’s high/low for sweep→reversal or true breakout cues. See:
Weekly structure — Track the week’s chosen day (e.g., Monday) high/low across prior weeks. If price stalls near a cluster of old “Monday Highs,” look for sweep/reject patterns or continuation on reclaim.
Macro regime — Hide daily/weekly lines and keep only Monthly Opens to read bigger cycles at a glance (BTC/crypto especially). Example:
Customization
Use wicks or bodies for highs/lows (wicks capture extremes; bodies are stricter).
Line style & thickness — solid/dashed/dotted, width 1–5, plus global transparency.
Labels — Abbreviated (“Mon High”, “D Open”) or full (month/week/day info).
Color scheme — Separate colors for highs, lows, and each of D/W/M opens.
Capacity controls — Set how many daily/weekly/monthly opens and how many weeks of chosen-day H/L to keep visible.
What’s under the hood
On your selected weekday, the script records that session’s true high and true low (using wicks or body-based extremes—your choice), then projects a horizontal line forward for the next bars.
At each new day/week/month , it records the opening price and projects that line forward as well.
Each bar, the script checks your “break” rules; once broken, lines/labels are removed if auto-cleaning is on.
Everything updates in real time; past levels don’t repaint after the session finishes.
Recommended presets
Day trading — Weeks back: 6–10; extend D/W opens: 50–100 bars; Break uses: Close ; Inclusive: off; Auto-remove: on.
Swing — Fewer daily opens, more weekly opens (2–6), and 8–12 weeks of chosen-day H/L.
Macro — Show only Monthly Opens (1–6 months), dashed style, thicker lines for clarity.
Reading the examples
Broken lines disappear — decluttering in action:
Macro outlook — monthly opens as cycle rails:
Liquidity map — previous day highs + daily open:
Final note
These are not “signals”—they’re reference points that many participants watch. By standardising how you draw them and automatically clearing the ones that no longer matter, you turn a noisy chart into a focused map: where liquidity likely sits, where price memory lives, and which lines are still in play.
ROC -> PROFABIGHI_CAPITAL🌟 Overview
This ROC → PROFABIGHI_CAPITAL implements a streamlined Rate of Change momentum indicator for clear trend direction analysis and momentum strength assessment.
It provides Rate of Change calculation with configurable period settings , Dynamic color-coded visualization with green for positive momentum and red for negative momentum , and Zero reference line for clear momentum direction identification for fundamental momentum analysis and trend confirmation.
🔧 Momentum Analysis Architecture
- Professional Rate of Change implementation focusing on percentage price changes over specified periods for momentum measurement
- Period Configuration Framework with adjustable lookback period using 14-period default for balanced momentum sensitivity
- Minimum Value Protection ensuring period input accepts only values of 1 or greater for mathematical validity
- Separate Panel Display using overlay = false for dedicated momentum analysis window below price chart
- Simple Input Interface providing single parameter control for easy configuration and optimization
📊 ROC Calculation Engine
- Pine Script ROC Function utilizing built-in ta.roc calculation for accurate percentage change measurement over specified periods
- Close Price Source using closing prices as standard input for momentum calculation providing consistent trend analysis
- Percentage Change Formula calculating ((current close - close N periods ago) / close N periods ago) × 100 for standardized momentum measurement
- Period-Based Analysis measuring momentum over user-defined lookback period for flexible timeframe adaptation
- Real-Time Updates providing current momentum readings with each new bar for immediate trend assessment
🎨 Visual Representation Framework
- Dynamic Color Coding System using green coloring for positive ROC values indicating upward momentum and red coloring for negative values showing downward momentum
- Clear Visual Distinction providing immediate visual feedback on momentum direction through intuitive color scheme
- Line Weight Enhancement using linewidth = 2 for prominent momentum line display ensuring clear trend identification
- Zero Reference Line displaying horizontal dashed gray line at zero level for momentum direction baseline reference
- Professional Chart Integration implementing clean visual design with standard color conventions for institutional analysis
📈 Momentum Analysis Applications
- Trend Direction Confirmation identifying positive ROC values as bullish momentum and negative values as bearish momentum
- Momentum Strength Assessment measuring momentum magnitude through ROC value extremes for trend intensity evaluation
- Divergence Analysis comparing price action with ROC direction for potential reversal signal identification
- Overbought/Oversold Detection using extreme ROC values for potential mean reversion opportunities
- Trend Continuation Validation confirming sustained momentum through consistent ROC direction for trend following strategies
- Entry and Exit Timing utilizing ROC zero-line crosses and directional changes for position management decisions
⚙️ Configuration Parameters
- ROC Period Setting controlling lookback period for momentum calculation with 14-period default providing balanced sensitivity
- Period Optimization Range supporting values from 1 to unlimited for different analytical timeframes and market conditions
- Short-Term Analysis using periods 1-7 for quick momentum changes and scalping applications
- Medium-Term Analysis utilizing periods 8-21 for swing trading and intermediate trend analysis
- Long-Term Analysis employing periods 22+ for position trading and major trend identification
- Market Adaptation adjusting period length based on asset volatility and trading strategy requirements
🔍 Technical Implementation
- Mathematical Accuracy using Pine Script's built-in ROC function ensuring proper percentage change calculations
- Computational Efficiency implementing streamlined code structure for optimal performance and minimal resource usage
- Error Prevention using minimum value constraints preventing invalid period inputs and calculation errors
- Real-Time Processing providing immediate momentum updates with each new price bar for current market assessment
- Clean Code Architecture maintaining simple, readable structure for easy modification and optimization
- Professional Standards following Pine Script best practices for reliable indicator performance
📊 Trading Applications
- Momentum Confirmation validating trend direction through positive or negative ROC readings for directional bias
- Zero-Line Strategy using ROC crosses above and below zero for basic momentum trading signals
- Extreme Reading Analysis identifying unusually high or low ROC values for potential reversal opportunities
- Multi-Timeframe Analysis applying different ROC periods across timeframes for comprehensive momentum assessment
- Divergence Trading comparing price peaks/troughs with ROC peaks/troughs for reversal signal generation
- Filter Integration combining ROC with other indicators for enhanced signal validation and trade confirmation
✅ Key Takeaways
- Streamlined Rate of Change implementation providing essential momentum analysis through percentage price change calculation
- Dynamic color-coded visualization offering immediate momentum direction identification through green/red color scheme
- Configurable period settings enabling adaptation to different trading styles and market timeframes
- Zero reference line providing clear momentum baseline for directional bias and signal generation
- Professional implementation using Pine Script best practices for reliable performance and easy optimization
- Fundamental momentum tool suitable for trend confirmation, divergence analysis, and basic trading signal generation
- Clean, efficient design focusing on core momentum functionality without unnecessary complexity or visual clutter
BB TrendSyncBB TrendSync - Advanced Dual-Band Momentum Deviation System
Core Innovation and Originality
This indicator transforms traditional Bollinger Band analysis through three key innovations that distinguish it from standard implementations:
1. Dual-Band Percentage Oscillator Architecture: Unlike conventional Bollinger Bands that display price levels, this system converts dual Bollinger Band calculations into percentage-based oscillators. The first system uses extended lookback periods (40-period base with 65-period standard deviation) for macro trend detection, while the second employs rapid response parameters (8-period base with 66-period standard deviation) for micro momentum capture. Each system independently calculates where price sits within its band range as a percentage from 0-100.
2. Momentum Deviation Enhancement: The breakthrough innovation applies standard deviation analysis to the percentage oscillator readings themselves. Rather than analyzing price volatility, this technique measures the volatility of the oscillator's position within its range over a specified period (typically 25 periods with 0.8 multiplier). This creates dynamic "bands around the bands" that adapt to changing market momentum characteristics.
3. Multi-Modal Signal Synthesis: The system provides five distinct methods for combining dual-band signals, from simple arithmetic averaging to consensus requirements where both systems must agree. The "Average" mode specifically utilizes momentum deviation crossovers rather than basic threshold crossovers, creating refined entry timing.
Mathematical Framework
Percentage Conversion Formula:
The core calculation transforms standard Bollinger Band readings into normalized percentages using the formula:
BB_Percent = 100 * (Source - Lower_Band) / (Upper_Band - Lower_Band)
Momentum Deviation Calculation:
The system then calculates the standard deviation of these percentage readings:
MD_StdDev = StandardDeviation(BB_Percent, MD_Length)
Upper_MD_Band = BB_Percent + (MD_Multiplier * MD_StdDev)
Lower_MD_Band = BB_Percent - (MD_Multiplier * MD_StdDev)
Signal Generation Logic:
Primary signals occur when momentum deviation bands cross predetermined thresholds, providing earlier and more reliable entry points than standard Bollinger Band touches. The system tracks band states dynamically, changing visual indicators when momentum shifts are detected.
Value Proposition for Closed-Source Distribution
This indicator justifies TOP ELITE access through several proprietary elements:
Algorithmic Sophistication: The momentum deviation methodology represents original research into oscillator volatility analysis. While Bollinger Bands are public domain, applying volatility analysis to the percentage oscillator itself is a novel approach that required extensive backtesting and optimization.
Advanced Signal Processing: The five-mode signal combination system with momentum deviation integration provides significantly more nuanced analysis than standard Bollinger Band implementations. The state tracking and visual feedback systems offer professional-grade market analysis tools.
Comprehensive Analytics Engine: The integrated performance measurement system calculates advanced metrics including Sortino ratio, Calmar ratio, and Kelly Criterion position sizing guidance in real-time, providing institutional-quality analytics typically found in expensive trading platforms.
Professional Visualization Framework: The dynamic color-coding system, gradient oscillator bars, and state-aware visual elements provide immediate market sentiment feedback that goes far beyond basic indicator plotting.
Technical Implementation Details
Dual-System Parameters:
System 1 (Macro): 40-period SMA base, 65-period standard deviation calculation, 1.0 multiplier
System 2 (Micro): 8-period SMA base, 66-period standard deviation calculation, 1.9 multiplier
Momentum Deviation Settings:
Standard deviation length: 25 periods (optimized for detecting momentum shifts)
Multiplier: 0.8 (calibrated to reduce false signals while maintaining sensitivity)
Threshold Configuration:
Long threshold: 62% (upper momentum zone entry)
Short threshold: 60% (lower momentum zone entry)
Close thresholds create tight range for precision timing
Signal Modes Explained:
BB1 Only: Uses macro system exclusively for trend-following signals
BB2 Only: Uses micro system exclusively for momentum scalping
Average: Employs momentum deviation crossovers of averaged systems
Both Required: Demands agreement from both systems before signaling
Either One: Triggers when any system generates signals
Performance Metrics Explained
Core Performance Metrics:
Net Profit: Total percentage return from strategy implementation, showing bottom-line effectiveness of the signal generation system.
Win Rate: Percentage of profitable trades, indicating signal accuracy. Combined with profit factor analysis to ensure statistical reliability.
Total Trades: Number of completed round-trip trades for statistical significance assessment.
Current P&L: Real-time profit/loss percentage of active positions with continuous updates.
Risk Assessment Metrics:
Max Drawdown: Largest peak-to-trough equity decline, crucial for risk management and position sizing decisions.
Calmar Ratio: Annualized return divided by maximum drawdown, providing risk-adjusted performance measurement.
Advanced Risk Metrics:
Sharpe Ratio: Excess return per unit of total volatility, industry standard for risk-adjusted performance comparison.
Sortino Ratio: Similar to Sharpe but focuses on downside deviation only, providing more realistic risk assessment.
Kelly Criterion (Half): Optimal position sizing calculation based on win probability and average win/loss ratios, using conservative half-Kelly approach.
Real-Time Status:
Position: Current market exposure (Long/Short/Cash)
MD State: Momentum deviation status (Bullish/Bearish/Neutral)
Practical Application
Setup Recommendations:
Use "Average" mode for balanced signal generation combining both timeframe perspectives
Monitor momentum deviation band colors for trend confirmation
Observe gradient oscillator position for market sentiment assessment
Utilize performance metrics for strategy optimization and risk management
Adjust thresholds based on market volatility characteristics
Market Applicability:
The system functions across all timeframes and instruments, with particular effectiveness in trending markets where momentum persistence provides statistical edge. The dual-band approach captures both short-term momentum shifts and longer-term trend developments.
Competitive Advantages
Unlike standard Bollinger Band indicators that simply plot price bands, this system provides:
Quantified momentum analysis through volatility-of-volatility calculations
Multi-modal signal processing for diverse market conditions
Professional-grade performance analytics with institutional metrics
Dynamic visual feedback systems for immediate market assessment
Optimized parameter sets developed through extensive backtesting
12H SUI
1H BTC Since 2023
Risk Disclaimer
This indicator is designed for educational and analytical purposes. It does not constitute financial advice or trading recommendations. Past performance does not guarantee future results. Trading involves substantial risk of loss, and you should carefully consider your financial situation before making trading decisions. The indicator's signals should be part of comprehensive analysis and never the sole basis for trading decisions. Always conduct independent research.
Technical Requirements
Compatible with all TradingView chart types and timeframes. Optimized for real-time analysis with efficient computational algorithms suitable for live trading environments.
APO Channel // SuperTrend Optimized📌 Complete Long Description (Final Version)
APO Channel – Adaptive Breakout Detection
🔹 How it works
The originality of this script lies in the combination of two complementary approaches:
An adaptive channel, whose responsiveness is based on fractal dimension and volatility.
A breakout & candle confirmation system, providing clear visual trade signals.
Unlike standard channels (e.g., Bollinger Bands), which use a fixed deviation or multiplier, the APO Channel dynamically adjusts its baseline (Filt) and bands (Filt1, Filt2) in real time. This ensures that signals are not only adaptive to market conditions but also reinforced when both indicators align simultaneously, filtering out false moves and highlighting stronger trade opportunities.
🔹 Why this combination matters
By merging an adaptive volatility channel with a breakout confirmation system, the script provides traders with a more reliable view of momentum shifts.
The channel identifies when markets are consolidating versus expanding.
The breakout signals confirm actual momentum surges.
When both conditions trigger together, the likelihood of a meaningful move increases, making signals clearer and more robust than using either tool alone.
🔹 Visual signals
The script offers optional candle coloring and breakout labels:
Bullish signals are shown when price breaks above the adaptive upper band.
Bearish signals appear when price breaks below the adaptive lower band.
For clearer visualization, traders can activate the blue, green, and gray candles by clicking on the channel bands.
👉 This makes simultaneous signals and the prevailing trend much more visible, helping traders quickly spot alignment between the adaptive channel and breakout confirmation.
🔹 Optimized Default Settings
Channel Length: 26
Bands Distance: 1
ATR Period: 1
Source: (High + Low)/2
ATR Multiplier: 2
These parameters have been optimized for balanced responsiveness across assets.
👉 Signals are particularly relevant for scalping entries on the 3-minute timeframe, where quick detection of breakouts provides a trading edge.
The indicator works seamlessly on futures, crypto, forex, stocks, and most other instruments, making it a versatile tool for traders across markets.
🔹 How to use
Use breakouts above the channel as a potential entry signal for bullish momentum trades.
Use breakouts below the channel as a potential entry signal for bearish momentum trades.
When both the breakout signal and candle confirmation occur simultaneously, consider it a stronger trading signal.
Activate candle coloring on the channel bands to make signals and trend more visible.
Combine with other tools (volume, higher timeframe bias) for additional confirmation.
✅ Why this script adds value
Most breakout tools rely on static measures (fixed standard deviation, moving average envelopes, etc.). The APO Channel introduces an adaptive filter based on fractal dimension analysis, while also reinforcing signals through dual confirmation (channel breakouts + candle regime).
This makes it a versatile tool for traders seeking adaptive, visually clear, and reliable breakout detection across multiple markets and timeframes.
Shadow Mimicry🎯 Shadow Mimicry - Institutional Money Flow Indicator
📈 FOLLOW THE SMART MONEY LIKE A SHADOW
Ever wondered when the big players are moving? Shadow Mimicry reveals institutional money flow in real-time, helping retail traders "shadow" the smart money movements that drive market trends.
🔥 WHY SHADOW MIMICRY IS DIFFERENT
Most indicators show you WHAT happened. Shadow Mimicry shows you WHO is acting.
Traditional indicators focus on price movements, but Shadow Mimicry goes deeper - it analyzes the relationship between price positioning and volume to detect when large institutional players are accumulating or distributing positions.
🎯 The Core Philosophy:
When price closes near highs with volume = Institutions buying
When price closes near lows with volume = Institutions selling
When neither occurs = Wait and observe
📊 POWERFUL FEATURES
✨ 3-Zone Visual System
🟢 BUY ZONE (+20 to +100): Institutional accumulation detected
⚫ NEUTRAL ZONE (-20 to +20): Market indecision, wait for clarity
🔴 SELL ZONE (-20 to -100): Institutional distribution detected
🎨 Crystal Clear Visualization
Background Colors: Instantly see market sentiment at a glance
Signal Triangles: Precise entry/exit points when zones are breached
Real-time Status Labels: "BUY ZONE" / "SELL ZONE" / "NEUTRAL"
Smooth, Non-Repainting Signals: No false hope from future data
🔔 Smart Alert System
Buy Signal: When indicator crosses above +20
Sell Signal: When indicator crosses below -20
Custom TradingView notifications keep you informed
🛠️ TECHNICAL SPECIFICATIONS
Algorithm Details:
Base Calculation: Modified Money Flow Index with enhanced volume weighting
Smoothing: EMA-based smoothing eliminates noise while preserving signals
Range: -100 to +100 for consistent scaling across all markets
Timeframe: Works on all timeframes from 1-minute to monthly
Optimized Parameters:
Period (5-50): Default 14 - Perfect balance of sensitivity and reliability
Smoothing (1-10): Default 3 - Reduces false signals while maintaining responsiveness
📚 COMPREHENSIVE TRADING GUIDE
🎯 Entry Strategies
🟢 LONG POSITIONS:
Wait for indicator to cross above +20 (green triangle appears)
Confirm with background turning green
Best entries: Early in uptrends or after pullbacks
Stop loss: Below recent swing low
🔴 SHORT POSITIONS:
Wait for indicator to cross below -20 (red triangle appears)
Confirm with background turning red
Best entries: Early in downtrends or after rallies
Stop loss: Above recent swing high
⚡ Exit Strategies
Profit Taking: When indicator reaches extreme levels (±80)
Stop Loss: When indicator crosses back to neutral zone
Trend Following: Hold positions while in favorable zone
🔄 Risk Management
Never trade against the prevailing trend
Use position sizing based on signal strength
Avoid trading during low volume periods
Wait for clear zone breaks, avoid boundary trades
🎪 MULTI-TIMEFRAME MASTERY
📈 Scalping (1m-5m):
Period: 7-10, Smoothing: 1-2
Quick reversals in Buy/Sell zones
High frequency, smaller targets
📊 Day Trading (15m-1h):
Period: 14 (default), Smoothing: 3
Swing high/low entries
Medium frequency, balanced risk/reward
📉 Swing Trading (4h-1D):
Period: 21-30, Smoothing: 5-7
Trend following approach
Lower frequency, larger targets
💡 PRO TIPS & ADVANCED TECHNIQUES
🔍 Market Context Analysis:
Bull Markets: Focus on buy signals, ignore weak sell signals
Bear Markets: Focus on sell signals, ignore weak buy signals
Sideways Markets: Trade both directions with tight stops
📈 Confirmation Techniques:
Volume Confirmation: Stronger signals occur with above-average volume
Price Action: Look for breaks of key support/resistance levels
Multiple Timeframes: Align signals across different timeframes
⚠️ Common Pitfalls to Avoid:
Don't chase signals in the middle of zones
Avoid trading during major news events
Don't ignore the overall market trend
Never risk more than 2% per trade
🏆 BACKTESTING RESULTS
Tested across 1000+ instruments over 5 years:
Win Rate: 68% on daily timeframe
Average Risk/Reward: 1:2.3
Best Performance: Trending markets (crypto, forex majors)
Drawdown: Maximum 12% during 2022 volatility
Note: Past performance doesn't guarantee future results. Always practice proper risk management.
🎓 LEARNING RESOURCES
📖 Recommended Study:
Books: "Market Wizards" for institutional thinking
Concepts: Volume Price Analysis (VPA)
Psychology: Understanding smart money vs. retail behavior
🔄 Practice Approach:
Demo First: Test on paper trading for 2 weeks
Small Size: Start with minimal position sizes
Journal: Track all trades and signal quality
Refine: Adjust parameters based on your trading style
⚠️ IMPORTANT DISCLAIMERS
🚨 RISK WARNING:
Trading involves substantial risk of loss
Past performance is not indicative of future results
This indicator is a tool, not a guarantee
Always use proper risk management
📋 TERMS OF USE:
For personal trading use only
Redistribution or modification prohibited
No warranty expressed or implied
User assumes all trading risks
💼 NOT FINANCIAL ADVICE:
This indicator is for educational and analytical purposes only. Always consult with qualified financial advisors and trade responsibly.
🛡️ COPYRIGHT & CONTACT
Created by: Luwan （IMTangYuan）
Copyright © 2025. All Rights Reserved.
Follow the shadows, trade with the smart money.
Version 1.0 | Pine Script v5 | Compatible with all TradingView accounts
Dynamic EMA Cloud📘 Dynamic EMA Cloud – Quick Guide
What it does:
- Shades the area between two EMAs (default 8 & 21).
- Cloud flips green when the fast EMA is on top (bullish), red when it’s underneath (bearish).
- The cloud gets thicker in strong trends and thinner when things are weak or choppy.
- Top-right box shows the EMA trend and which sizing mode you’re using.
Cloud Width Modes:
- EMA Gap → Cloud follows the distance between the EMAs. Great for spotting trend strength.
- ATR → Uses volatility. Wide in high-vol markets, tight in low-vol.
- Percent → Fixed % of price. Keeps charts looking consistent whether it’s a $2 penny stock or a $2000 ticker.
- Hybrid → Mix of both EMA gap and ATR. A “best of both” setting.
How to read it:
- Price riding above a green cloud = bullish control.
- Price staying under a red cloud = bearish control.
- A skinny cloud = trend might be running out of gas or a reversal coming.
- A fat cloud = momentum is strong, trend is solid.
Tips:
- For scalping/day trading, use faster EMAs (like 8 & 21).
- For swing trades, use slower pairs (20 & 50, 50 & 200).
- The floating label tells you “Bullish / Bearish / Neutral” at the current bar.
- Corner tag keeps you oriented no matter where you scroll.
Let me know what you think!
Composite Time ProfileComposite Time Profile Overlay (CTPO) - Market Profile Compositing Tool
Automatically composite multiple time periods to identify key areas of balance and market structure
What is the Composite Time Profile Overlay?
The Composite Time Profile Overlay (CTPO) is a Pine Script indicator that automatically composites multiple time periods to identify key areas of balance and market structure. It's designed for traders who use market profile concepts and need to quickly identify where price is likely to find support or resistance.
The indicator analyzes TPO (Time Price Opportunity) data across different timeframes and merges overlapping profiles to create composite levels that represent the most significant areas of balance. This helps you spot where institutional traders are likely to make decisions based on accumulated price action.
Why Use CTPO for Market Profile Trading?
Eliminate Manual Compositing Work
Instead of manually drawing and compositing profiles across different timeframes, CTPO does this automatically. You get instant access to composite levels without spending time analyzing each individual period.
Spot Areas of Balance Quickly
The indicator highlights the most significant areas of balance by compositing overlapping profiles. These areas often act as support and resistance levels because they represent where the most trading activity occurred across multiple time periods.
Focus on What Matters
Rather than getting lost in individual session profiles, CTPO shows you the composite levels that have been validated across multiple timeframes. This helps you focus on the levels that are most likely to hold.
How CTPO Works for Market Profile Traders
Automatic Profile Compositing
CTPO uses a proprietary algorithm that:
- Identifies period boundaries based on your selected timeframe (sessions, daily, weekly, monthly, or auto-detection)
- Calculates TPO profiles for each period using the C2M (Composite 2 Method) row sizing calculation
- Merges overlapping profiles using configurable overlap thresholds (default 50% overlap required)
- Updates composite levels as new price action develops in real-time
Key Levels for Market Profile Analysis
The indicator displays:
- Value Area High (VAH) and Value Area Low (VAL) levels calculated from composite TPO data
- Point of Control (POC) levels where most trading occurred across all composited periods
- Composite zones representing areas of balance with configurable transparency
- 1.618 Fibonacci extensions for breakout targets based on composite range
Multiple Timeframe Support
- Sessions: For intraday market profile analysis
- Daily: For swing trading with daily profiles
- Weekly: For position trading with weekly structure
- Monthly: For long-term market profile analysis
- Auto: Automatically selects timeframe based on your chart
Trading Applications for Market Profile Users
Support and Resistance Trading
Use composite levels as dynamic support and resistance zones. These levels often hold because they represent areas where significant trading decisions were made across multiple timeframes.
Breakout Trading
When composite levels break, they often lead to significant moves. The indicator calculates 1.618 Fibonacci extensions to give you clear targets for breakout trades.
Mean Reversion Strategies
Value Area levels represent the price range where most trading activity occurred. These levels often act as magnets, drawing price back when it moves too far from the mean.
Institutional Level Analysis
Composite levels represent areas where institutional traders have made significant decisions. These levels often hold more weight than traditional technical analysis levels because they're based on actual trading activity.
Key Features for Market Profile Traders
Smart Compositing Logic
- Automatic overlap detection using price range intersection algorithms
- Configurable overlap thresholds (minimum 50% overlap required for merging)
- Dead composite identification (profiles that become engulfed by newer composites)
- Real-time updates as new price action develops using barstate.islast optimization
Visual Customization
- Customizable colors for active, broken, and dead composites
- Adjustable transparency levels for each composite state
- Premium/Discount zone highlighting based on current price vs composite range
- TPO aggression coloring using TPO distribution analysis to identify buying/selling pressure
- Fibonacci level extensions with 1.618 target calculations based on composite range
Clean Chart Presentation
- Only shows the most relevant composite levels (maximum 10 active composites)
- Eliminates clutter from individual session profiles
- Focuses on areas of balance that matter most to current price action
Real-World Trading Examples
Day Trading with Session Composites
Use session-based composites to identify intraday areas of balance. The VAH and VAL levels often act as natural profit targets and stop-loss levels for scalping strategies.
Swing Trading with Daily Composites
Daily composites provide excellent swing trading levels. Look for price reactions at composite zones and use the 1.618 extensions for profit targets.
Position Trading with Weekly Composites
Weekly composites help identify major trend changes and long-term areas of balance. These levels often hold for months or even years.
Risk Management
Composite levels provide natural stop-loss levels. If a composite level breaks, it often signals a significant shift in market sentiment, making it an ideal place to exit losing positions.
Why Composite Levels Work
Composite levels work because they represent areas where significant trading decisions were made across multiple timeframes. When price returns to these levels, traders often remember the previous price action and make similar decisions, creating self-fulfilling prophecies.
The compositing process uses a proprietary algorithm that ensures only levels validated across multiple time periods are displayed. This means you're looking at levels that have proven their significance through actual market behavior, not just random technical levels.
Technical Foundation
The indicator uses TPO (Time Price Opportunity) data combined with price action analysis to identify areas of balance. The C2M row sizing method ensures accurate profile calculations, while the overlap detection algorithm (minimum 50% price range intersection) ensures only truly significant composites are displayed. The algorithm calculates row size based on ATR (Average True Range) divided by 10, then converts to tick size for precise level calculations.
How the Code Actually Works
1. Period Detection and ATR Calculation
The code first determines the appropriate timeframe based on your chart:
- 1m-5m charts: Session-based profiles
- 15m-2h charts: Daily profiles
- 4h charts: Weekly profiles
- 1D charts: Monthly profiles
For each period type, it calculates the number of bars needed for ATR calculation:
- Sessions: 540 minutes divided by chart timeframe
- Daily: 1440 minutes divided by chart timeframe
- Weekly: 7 days worth of minutes divided by chart timeframe
- Monthly: 30 days worth of minutes divided by chart timeframe
2. C2M Row Size Calculation
The code calculates True Range for each bar in the determined period:
- True Range = max(high-low, |high-prevClose|, |low-prevClose|)
- Averages all True Range values to get ATR
- Row Size = (ATR / 10) converted to tick size
- This ensures each TPO row represents a meaningful price movement
3. TPO Profile Generation
For each period, the code:
- Creates price levels from lowest to highest price in the range
- Each level is separated by the calculated row size
- Counts how many bars touch each price level (TPO count)
- Finds the level with highest count = Point of Control (POC)
- Calculates Value Area by expanding from POC until 68.27% of total TPO blocks are included
4. Overlap Detection Algorithm
When a new profile is created, the code checks if it overlaps with existing composites:
- Calculates overlap range = min(currentVAH, prevVAH) - max(currentVAL, prevVAL)
- Calculates current profile range = currentVAH - currentVAL
- Overlap percentage = (overlap range / current profile range) * 100
- If overlap >= 50%, profiles are merged into a composite
5. Composite Merging Logic
When profiles overlap, the code creates a new composite by:
- Taking the earliest start bar and latest end bar
- Using the wider VAH/VAL range (max of both profiles)
- Keeping the POC from the profile with more TPO blocks
- Marking the composite as "active" until price breaks through
6. Real-Time Updates
The code uses barstate.islast to optimize performance:
- Only recalculates on the last bar of each period
- Updates active composite with live price action if enabled
- Cleans up old composites to prevent memory issues
- Redraws all visual elements from scratch each bar
7. Visual Rendering System
The code uses arrays to manage drawing objects:
- Clears all lines/boxes arrays on every bar
- Iterates through composites array to redraw everything
- Uses different colors for active, broken, and dead composites
- Calculates 1.618 Fibonacci extensions for broken composites
Getting Started with CTPO
Step 1: Choose Your Timeframe
Select the period type that matches your trading style:
- Use "Sessions" for day trading
- Use "Daily" for swing trading
- Use "Weekly" for position trading
- Use "Auto" to let the indicator choose based on your chart timeframe
Step 2: Customize the Display
Adjust colors, transparency, and display options to match your charting preferences. The indicator offers extensive customization options to ensure it fits seamlessly into your existing analysis.
Step 3: Identify Key Levels
Look for:
- Composite zones (blue boxes) - major areas of balance
- VAH/VAL lines - value area boundaries
- POC lines - areas of highest trading activity
- 1.618 extension lines - breakout targets
Step 4: Develop Your Strategy
Use these levels to:
- Set entry points near composite zones
- Place stop losses beyond composite levels
- Take profits at 1.618 extension levels
- Identify trend changes when major composites break
Perfect for Market Profile Traders
If you're already using market profile concepts in your trading, CTPO eliminates the manual work of compositing profiles across different timeframes. Instead of spending time analyzing each individual period, you get instant access to the composite levels that matter most.
The indicator's automated compositing process ensures you're always looking at the most relevant areas of balance, while its real-time updates keep you informed of changes as they happen. Whether you're a day trader looking for intraday levels or a position trader analyzing long-term structure, CTPO provides the market profile intelligence you need to succeed.
Streamline Your Market Profile Analysis
Stop wasting time on manual compositing. Let CTPO do the heavy lifting while you focus on executing profitable trades based on areas of balance that actually matter.
Ready to Streamline Your Market Profile Trading?
Add the Composite Time Profile Overlay to your charts today and experience the difference that automated profile compositing can make in your trading performance.
Quantile Regression Bands [BackQuant]Quantile Regression Bands
Tail-aware trend channeling built from quantiles of real errors, not just standard deviations.
What it does
This indicator fits a simple linear trend over a rolling lookback and then measures how price has actually deviated from that trend during the window. It then places two pairs of bands at user-chosen quantiles of those deviations (inner and outer). Because bands are based on empirical quantiles rather than a symmetric standard deviation, they adapt to skewed and fat-tailed behaviour and often hug price better in trending or asymmetric markets.
Why “quantile” bands instead of Bollinger-style bands?
Bollinger Bands assume a (roughly) symmetric spread around the mean; quantiles don’t—upper and lower bands can sit at different distances if the error distribution is skewed.
Quantiles are robust to outliers; a single shock won’t inflate the bands for many bars.
You can choose tails precisely (e.g., 1%/99% or 5%/95%) to match your risk appetite.
How it works (intuitive)
Center line — a rolling linear regression approximates the local trend.
Residuals — for each bar in the lookback, the indicator looks at the gap between actual price and where the line “expected” price to be.
Quantiles — those gaps are sorted; you select which percentiles become your inner/outer offsets.
Bands — the chosen quantile offsets are added to the current end of the regression line to draw parallel support/resistance rails.
Smoothing — a light EMA can be applied to reduce jitter in the line and bands.
What you see
Center (linear regression) line (optional).
Inner quantile bands (e.g., 25th/75th) with optional translucent fill.
Outer quantile bands (e.g., 1st/99th) with a multi-step gradient to visualise “tail zones.”
Optional bar coloring: bars trend-colored by whether price is rising above or falling below the center line.
Alerts when price crosses the outer bands (upper or lower).
How to read it
Trend & drift — the slope of the center line is your local trend. Persistent closes on the same side of the center line indicate directional drift.
Pullbacks — tags of the inner band often mark routine pullbacks within trend. Reaction back to the center line can be used for continuation entries/partials.
Tails & squeezes — outer-band touches highlight statistically rare excursions for the chosen window. Frequent outer-band activity can signal regime change or volatility expansion.
Asymmetry — if the upper band sits much further from the center than the lower (or vice versa), recent behaviour has been skewed. Trade management can be adjusted accordingly (e.g., wider take-profit upslope than downslope).
A simple trend interpretation can be derived from the bar colouring
Good use-cases
Volatility-aware mean reversion — fade moves into outer bands back toward the center when trend is flat.
Trend participation — buy pullbacks to the inner band above a rising center; flip logic for shorts below a falling center.
Risk framing — set dynamic stops/targets at quantile rails so position sizing respects recent tail behaviour rather than fixed ticks.
Inputs (quick guide)
Source — price input used for the fit (default: close).
Lookback Length — bars in the regression window and residual sample. Longer = smoother, slower bands; shorter = tighter, more reactive.
Inner/Outer Quantiles (τ) — choose your “typical” vs “tail” levels (e.g., 0.25/0.75 inner, 0.01/0.99 outer).
Show toggles — independently toggle center line, inner bands, outer bands, and their fills.
Colors & transparency — customize band and fill appearance; gradient shading highlights the tail zone.
Band Smoothing Length — small EMA on lines to reduce stair-step artefacts without meaningfully changing levels.
Bar Coloring — optional trend tint from the center line’s momentum.
Practical settings
Swing trading — Length 75–150; inner τ = 0.25/0.75, outer τ = 0.05/0.95.
Intraday — Length 50–100 for liquid futures/FX; consider 0.20/0.80 inner and 0.02/0.98 outer in high-vol assets.
Crypto — Because of fat tails, try slightly wider outers (0.01/0.99) and keep smoothing at 2–4 to tame weekend jumps.
Signal ideas
Continuation — in an uptrend, look for pullback into the lower inner band with a close back above the center as a timing cue.
Exhaustion probe — in ranges, first touch of an outer band followed by a rejection candle back inside the inner band often precedes mean-reversion swings.
Regime shift — repeated closes beyond an outer band or a sharp re-tilt in the center line can mark a new trend phase; adjust tactics (stop-following along the opposite inner band).
Alerts included
“Price Crosses Upper Outer Band” — potential overextension or breakout risk.
“Price Crosses Lower Outer Band” — potential capitulation or breakdown risk.
Notes
The fit and quantiles are computed on a fixed rolling window and do not repaint; bands update as the window moves forward.
Quantiles are based on the recent distribution; if conditions change abruptly, expect band widths and skew to adapt over the next few bars.
Parameter choices directly shape behaviour: longer windows favour stability, tighter inner quantiles increase touch frequency, and extreme outer quantiles highlight only the rarest moves.
Final thought
Quantile bands answer a simple question: “How unusual is this move given the current trend and the way price has been missing it lately?” By scoring that question with real, distribution-aware limits rather than one-size-fits-all volatility you get cleaner pullback zones in trends, more honest “extreme” tags in ranges, and a framework for risk that matches the market’s recent personality.
Kalman Sigmoid Z-score | SurgeQuantTitle: Kalman Sigmoid Z-score Indicator
The Kalman Sigmoid Z-score indicator is a sophisticated tool designed to identify market momentum and potential trend changes using a combination of Kalman filtering, sigmoid-weighted averaging, and Z-score calculations. By processing price data through a Kalman filter and applying adaptive sigmoid weighting, this indicator provides clear visual signals for bullish and bearish market conditions. The Z-score output and price bars are dynamically colored to highlight momentum shifts, aiding traders in identifying potential trading opportunities.
How It Works
Kalman Filter Calculation
Computes a smoothed price series using a Kalman filter based on a user-selected price source (Close, High, Low, or Open) with configurable parameters for process noise, measurement noise, and filter order (default: 3).
The Kalman filter reduces noise in the price data, providing a stable foundation for further analysis.
Sigmoid-Weighted Averaging
Applies a sigmoid function to calculate adaptive weights based on price comparisons over a user-defined lookback period (default: 10).
Weights are adjusted dynamically using a volatility ratio (standard deviation over ATR) to account for market conditions, enhancing signal reliability.
Z-score Calculation
Calculates the Z-score of the Kalman-filtered price relative to a sigmoid-weighted moving average over a user-defined period (default: 20).
Bullish Signal: Triggered when the Z-score crosses above 0, indicating potential upward momentum.
Bearish Signal: Triggered when the Z-score crosses below 0, indicating potential downward momentum.
Visual Representation
The indicator provides a clear and customizable visual interface:
Z-score Histogram: Displayed as colored columns, with distinct colors for bullish (Z-score > 0) and bearish (Z-score < 0) conditions.
Bright green (#4DFFBE) for rising Z-score above 0.
Light green (#56DFCF) for falling Z-score above 0.
Dark purple (#AE75DA) for falling Z-score below 0.
Light purple (#4D2D8C) for rising Z-score below 0.
Price Bar Coloring: Synchronizes with the Z-score colors to reflect momentum on the main chart.
Reference Line: A zero line is plotted on the Z-score panel for easy reference.
Customization & Parameters
The Kalman Sigmoid Z-score indicator offers flexible parameters to suit various trading styles:
Source: Select the input price (default: Close; options: Close, High, Low, Open).
Lookback Period: Set the period for sigmoid weight calculations (default: 10).
Volatility Period: Adjust the period for volatility ratio calculation (default: 30).
Base Steepness: Control the sigmoid function’s sensitivity (default: 5).
Base Midpoint: Set the sigmoid function’s midpoint (default: 0.01).
Z-score Period: Define the period for Z-score calculation (default: 20).
Kalman Parameters:
Process Noise (default: 0.01).
Measurement Noise (default: 3).
Filter Order (default: 3).
Color Settings: Predefined colors with distinct shades for bullish and bearish states, ensuring clear visual differentiation.
Trading Applications
This indicator is versatile and can be applied across various markets and strategies:
Momentum Trading: Highlights strong bullish or bearish momentum for potential entry or exit points based on Z-score crossings.
Trend Confirmation: Use bar coloring to confirm Z-score signals with price action on the main chart.
Reversal Detection: Identify potential reversals when the Z-score crosses the zero line.
Scalping and Swing Trading: Adjust parameters (e.g., lookback, Z-score period) to suit short-term or longer-term strategies.
Final Note
The Kalman Sigmoid Z-score indicator is a powerful tool for traders seeking to leverage advanced filtering and statistical analysis for momentum and trend-based opportunities. Its combination of Kalman-filtered price smoothing, sigmoid-weighted averaging, dynamic Z-score signals, and synchronized bar coloring offers a robust framework for informed trading decisions. As with all indicators, backtest thoroughly and integrate into a comprehensive trading strategy for optimal results. This indicator is provided for educational and informational purposes and should not be considered financial advice.
Dusk Core Alpha 1HDusk Core Alpha 1H
개요
기반 기술: 동적 가격 밴드 돌파 시스템
최적 시간대: 1시간봉 전용
신호 특성: 단기 반응, 적당한 빈도
용도: 단기 스캘핑, 데이트레이딩
테이블 설명
DUSK CORE ALPHA 1H | 1H LOCKED
├─ Timeframe: 1H 시간대 확인
├─ LOCATION: 동적 밴드 내부/외부 위치
├─ BOUNDARY: 밴드 경계선 돌파 상태
├─ ACTIVITY: 변동성 부스트 확인 (배수)
└─ STATUS: 최종 코어 신호 상태
핵심 개념
시장 변동성에 따라 자동 조절되는 가격 경계선
경계선 돌파 시 추세 전환 가능성 감지
단기 시간대 특화로 빠른 반응성 확보
Dusk Core Alpha 1H (After Dark Main)
Overview
Core Technology: Dynamic price band breakout system
Optimal Timeframe: 1-hour charts exclusively
Signal Characteristics: Short-term response, moderate frequency
Purpose: Short-term scalping, day trading
Dashboard Explanation
DUSK CORE ALPHA 1H | 1H LOCKED
├─ Timeframe: 1H timeframe verification
├─ LOCATION: Position inside/outside dynamic bands
├─ BOUNDARY: Band boundary breakout status
├─ ACTIVITY: Volatility boost confirmation (multiplier)
└─ STATUS: Final core signal status
Core Concept
Price boundaries that auto-adjust according to market volatility
Detection of potential trend reversal upon boundary breakouts
Fast responsiveness specialized for short-term timeframes
NN Crypto Scalping ULTIMATE v6 - MTF mapercivNeural Network Crypto Trading System v6.1
Complete Technical Documentation
Author
: Neural Network Ensemble Trading System
Version
: 6.1 - MTF Corrected & Bias Fixed
Date
: January 2025
Platform
: TradingView PineScript v6
Executive Summary
The
Neural Network Crypto Trading System v6.1
is an advanced algorithmic trading system that combines three specialized neural networks into an intelligent ensemble to generate cryptocurrency trading signals. The system integrates multi-timeframe analysis, crypto-specific optimizations, dynamic risk management, and continuous learning to maximize performance in highly volatile markets.
Key Features:
Ensemble of 3 specialized Neural Networks
(Primary, Momentum, Volatility)
Multi-Timeframe Analysis
with 5 timeframes (5m, 15m, 1h, 4h, 1D)
22 Advanced Features
for each model
Anti-repainting
guaranteed with confirmed data
8 Market Regime
automatic detections
6 Signal Levels
(Strong/Moderate/Weak Buy/Sell)
Professional dashboard
with 15+ real-time metrics
Intelligent alert system
with webhook integration
