Cumulative Volume Delta Z Score [BackQuant]Cumulative Volume Delta Z Score
The Cumulative Volume Delta Z Score indicator is a sophisticated tool that combines the cumulative volume delta (CVD) with Z-Score normalization to provide traders with a clearer view of market dynamics. By analyzing volume imbalances and standardizing them through a Z-Score, this tool helps identify significant price movements and market trends while filtering out noise.
Core Concept of Cumulative Volume Delta (CVD)
Cumulative Volume Delta (CVD) is a popular indicator that tracks the net difference between buying and selling volume over time. CVD helps traders understand whether buying or selling pressure is dominating the market. Positive CVD signals buying pressure, while negative CVD indicates selling pressure.
The addition of Z-Score normalization to CVD makes it easier to evaluate whether current volume imbalances are unusual compared to past behavior. Z-Score helps in detecting extreme conditions by showing how far the current CVD is from its historical mean in terms of standard deviations.
Key Features
Cumulative Volume Delta (CVD): Tracks the net buying vs. selling volume, allowing traders to gauge the overall market sentiment.
Z-Score Normalization: Converts CVD into a standardized value to highlight extreme movements in volume that are statistically significant.
Divergence Detection: The indicator can spot bullish and bearish divergences between price and CVD, which can signal potential trend reversals.
Pivot-Based Divergence: Identifies price and CVD pivots, highlighting divergence patterns that are crucial for predicting price changes.
Trend Analysis: Colors bars according to trend direction, providing a visual indication of bullish or bearish conditions based on Z-Score.
How It Works
Cumulative Volume Delta (CVD): The CVD is calculated by summing the difference between buying and selling volume for each bar. It represents the net buying or selling pressure, giving insights into market sentiment.
Z-Score Normalization: The Z-Score is applied to the CVD to normalize its values, making it easier to compare current conditions with historical averages. A Z-Score greater than 0 indicates a bullish market, while a Z-Score less than 0 signals a bearish market.
Divergence Detection: The indicator detects regular and hidden bullish and bearish divergences between price and CVD. These divergences often precede trend reversals, offering traders a potential entry point.
Pivot-Based Analysis: The indicator uses pivot highs and lows in both price and CVD to identify divergence patterns. A bullish divergence occurs when price makes a lower low, but CVD fails to follow, suggesting weakening selling pressure. Conversely, a bearish divergence happens when price makes a higher high, but CVD doesn't confirm the move, indicating potential selling pressure.
Trend Coloring: The bars are colored based on the trend direction. Green bars indicate an uptrend (CVD is positive), and red bars indicate a downtrend (CVD is negative). This provides an easy-to-read visualization of market conditions.
Standard Deviation Levels: The indicator plots ±1σ, ±2σ, and ±3σ levels to indicate the degree of deviation from the average CVD. These levels act as thresholds for identifying extreme buying or selling pressure.
Customization Options
Anchor Timeframe: The user can define an anchor timeframe to aggregate the CVD, which can be customized based on the trader’s needs (e.g., daily, weekly, custom lower timeframes).
Z-Score Period: The period for calculating the Z-Score can be adjusted, allowing traders to fine-tune the indicator's sensitivity.
Divergence Detection: The tool offers controls to enable or disable divergence detection, with the ability to adjust the lookback periods for pivot detection.
Trend Coloring and Visuals: Traders can choose whether to color bars based on trend direction, display standard deviation levels, or visualize the data as a histogram or line plot.
Display Options: The indicator also allows for various display options, including showing the Z-Score values and divergence signals, with customizable colors and line widths.
Alerts and Signals
The Cumulative Volume Delta Z Score comes with pre-configured alert conditions for:
Z-Score Crossovers: Alerts are triggered when the Z-Score crosses the 0 line, indicating a potential trend reversal.
Shifting Trend: Alerts for when the Z-Score shifts direction, signaling a change in market sentiment.
Divergence Detection: Alerts for both regular and hidden bullish and bearish divergences, offering potential reversal signals.
Extreme Imbalances: Alerts when the Z-Score reaches extreme positive or negative levels, indicating overbought or oversold market conditions.
Applications in Trading
Trend Identification: Use the Z-Score to confirm bullish or bearish trends based on cumulative volume data, filtering out noise and false signals.
Reversal Signals: Divergences between price and CVD can help identify potential trend reversals, making it a powerful tool for swing traders.
Volume-Based Confirmation: The Z-Score allows traders to confirm price movements with volume data, providing more reliable signals compared to price action alone.
Divergence Strategy: Use the divergence signals to identify potential points of entry, particularly when regular or hidden divergences appear.
Volatility and Market Sentiment: The Z-Score provides insights into market volatility by measuring the deviation of CVD from its historical mean, helping to predict price movement strength.
The Cumulative Volume Delta Z Score is a powerful tool that combines volume analysis with statistical normalization. By focusing on volume imbalances and applying Z-Score normalization, this indicator provides clear, reliable signals for trend identification and potential reversals. It is especially useful for filtering out market noise and ensuring that trades are based on significant price movements driven by substantial volume changes.
This indicator is perfect for traders looking to add volume-based analysis to their strategy, offering a more robust and accurate way to gauge market sentiment and trend strength.
Statistics
Volume v4 (Dollar Value) by Koenigsegg📊 Volume v3 (Dollar Value) by Koenigsegg
🎯 Purpose:
Volume v3 (Dollar Value) by Koenigsegg transforms traditional raw-unit volume into dollar-denominated volume, revealing how much money actually flows through each candle.
Instead of measuring how many coins or contracts were traded, this version calculates the total traded value = volume × average price (hlc3), allowing traders to visually assess capital intensity and market participation within each move.
⚙️ Core Features
- Converts raw volume into USD-based traded value for each candle.
- Color-coded bars show bullish (green/teal) vs. bearish (red) activity.
- Built-in SMA and SMMA overlays highlight sustained shifts in value flow.
- Designed for visual clarity to support momentum, exhaustion, and divergence studies.
📖 How to Read It
Rising Dollar Volume — indicates growing market participation and strong capital flow, often aligning with impulsive waves in trend direction.
Falling Dollar Volume — signals waning interest or reduced participation, potentially hinting at correction or exhaustion phases.
Comparing Legs — when price makes new highs/lows but dollar volume weakens, it can reveal divergences between price movement and actual capital commitment.
SMA / SMMA Lines — use them to identify longer-term accumulation or depletion of market activity, separating short bursts from sustained inflows or outflows.
The goal is to visualize the strength of market moves in terms of capital energy, not just tick activity. This distinction helps traders interpret whether a trend is being driven by genuine money flow or low-liquidity drift.
⚠️ Disclaimer
This script is provided for research and educational purposes only.
It does not constitute financial advice, investment recommendations, or trading signals.
Always conduct your own analysis and manage your own risk when trading live markets.
The author accepts no liability for financial losses incurred from use of this tool.
🧠 Credits
Developed and published by Koenigsegg.
Written in Pine Script® v6, fully compliant with TradingView’s House Rules for Pine Scripts.
Licensed under the Mozilla Public License 2.0.
IB range + Breakout fibsThe IB High / Low + Auto-Fib indicator automatically plots the Initial Balance range and a Fibonacci projection for each trading day.
Define your IB start and end times (e.g., 09:30–10:30).
The indicator marks the IB High and IB Low from that session and extends them to the session close.
It keeps the last N days visible for context.
When price breaks outside the IB range, it automatically plots a Fibonacci retracement/extension from the opposite IB side to the breakout, using levels 0, 0.236, 0.382, 0.5, 0.618, 0.88, 1.
The Fib updates dynamically as the breakout extends, and labels are neatly aligned on the right side of the chart for clarity.
Ideal for traders who monitor Initial Balance breaks, range expansions, and Fibonacci reaction levels throughout the trading session.
Triple SuperTrend + RSI + Fib BBTriple SuperTrend + RSI + Fibonacci Bollinger Bands Strategy
📊 Overview
This advanced trading strategy combines the power of three SuperTrend indicators with RSI confirmation and Fibonacci Bollinger Bands to generate high-probability trade signals. The strategy is designed to capture strong trending moves while filtering out false signals through multi-indicator confluence.
🔧 Core Components
Three SuperTrend Indicators
The strategy uses three SuperTrend indicators with progressively longer periods and multipliers:
SuperTrend 1: 10-period ATR, 1.0 multiplier (fastest, most sensitive)
SuperTrend 2: 11-period ATR, 2.0 multiplier (medium sensitivity)
SuperTrend 3: 12-period ATR, 3.0 multiplier (slowest, most stable)
This layered approach ensures that all three timeframe perspectives align before generating a signal, significantly reducing false entries.
RSI Confirmation (7-period)
The Relative Strength Index acts as a momentum filter:
Long signals require RSI > 50 (bullish momentum)
Short signals require RSI < 50 (bearish momentum)
This prevents entries during weak or divergent price action.
Fibonacci Bollinger Bands (200, 2.618)
Uses a 200-period Simple Moving Average with 2.618 standard deviation bands (Fibonacci ratio). These bands serve dual purposes:
Visual representation of price extremes
Automatic exit trigger when price reaches overextended levels
📈 Entry Logic
LONG Entry (BUY Signal)
A LONG position is opened when ALL of the following conditions are met simultaneously:
All three SuperTrend indicators turn green (bullish)
RSI(7) is above 50
This is the first bar where all conditions align (no repainting)
SHORT Entry (SELL Signal)
A SHORT position is opened when ALL of the following conditions are met simultaneously:
All three SuperTrend indicators turn red (bearish)
RSI(7) is below 50
This is the first bar where all conditions align (no repainting)
🚪 Exit Logic
Positions are automatically closed when ANY of these conditions occur:
SuperTrend Color Change: Any one of the three SuperTrend indicators changes direction
Fibonacci BB Touch: Price reaches or exceeds the upper or lower Fibonacci Bollinger Band (2.618 standard deviations)
This dual-exit approach protects profits by:
Exiting quickly when trend momentum shifts (SuperTrend change)
Taking profits at statistical price extremes (Fib BB touch)
🎨 Visual Features
Signal Arrows
Green Up Arrow (BUY): Appears below the bar when long entry conditions are met
Red Down Arrow (SELL): Appears above the bar when short entry conditions are met
Yellow Down Arrow (EXIT): Appears above the bar when exit conditions are met
Background Coloring
Light Green Tint: All three SuperTrends are bullish (uptrend environment)
Light Red Tint: All three SuperTrends are bearish (downtrend environment)
SuperTrend Lines
Three colored lines plotted with varying opacity:
Solid line (ST1): Most responsive to price changes
Semi-transparent (ST2): Medium-term trend
Most transparent (ST3): Long-term trend structure
Dashboard
Real-time information panel showing:
Individual SuperTrend status (UP/DOWN)
Current RSI value and color-coded status
Current position (LONG/SHORT/FLAT)
Net Profit/Loss
⚙️ Customizable Parameters
SuperTrend Settings
ATR periods for each SuperTrend (default: 10, 11, 12)
Multipliers for each SuperTrend (default: 1.0, 2.0, 3.0)
RSI Settings
RSI length (default: 7)
RSI source (default: close)
Fibonacci Bollinger Bands
BB length (default: 200)
BB multiplier (default: 2.618)
Strategy Options
Enable/disable long trades
Enable/disable short trades
Initial capital
Position sizing
Commission settings
💡 Strategy Philosophy
This strategy is built on the principle of confluence trading - waiting for multiple independent indicators to align before taking a position. By requiring three SuperTrend indicators AND RSI confirmation, the strategy filters out the majority of low-probability setups.
The multi-timeframe SuperTrend approach ensures that short-term, medium-term, and longer-term trends are all in agreement, which typically occurs during strong, sustainable price moves.
The exit strategy is equally important, using both trend-following logic (SuperTrend changes) and mean-reversion logic (Fibonacci BB touches) to adapt to different market conditions.
📊 Best Use Cases
Trending Markets: Works best in markets with clear directional bias
Higher Timeframes: Designed for 15-minute to daily charts
Volatile Assets: SuperTrend indicators excel in assets with clear trends
Swing Trading: Hold times typically range from hours to days
⚠️ Important Notes
No Repainting: All signals are confirmed and will not change on historical bars
One Signal Per Setup: The strategy prevents duplicate signals on consecutive bars
Exit Protection: Always exits before potentially taking an opposite position
Visual Clarity: All three SuperTrend lines are visible simultaneously for transparency
🎯 Recommended Settings
While default parameters are optimized for general use, consider:
Crypto/Volatile Markets: May benefit from slightly higher multipliers
Forex: Default settings work well for major pairs
Stocks: Consider longer BB periods (250-300) for daily charts
Lower Timeframes: Reduce all periods proportionally for scalping
📝 Alerts
Built-in alert conditions for:
BUY signal triggered
SELL signal triggered
EXIT signal triggered
Set up notifications to never miss a trade opportunity!
Disclaimer: This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Always backtest thoroughly and practice proper risk management before live trading.
Risk sizing toolHelps you manage risk per trade accurately.
Automatically adjusts position size if the stop-loss or account constraints are exceeded.
Gives a clear visual summary directly on your stock chart.
Prevents taking trades that are too large relative to your account.
Regular Trading Hours Opening Range Gap (RTH ORG)### Regular Trading Hours (RTH) Gap Indicator with Quartile Levels
**Overview**
Discover overnight gaps in index futures like ES, YM, and NQ, or stocks like SPY, with this enhanced Pine Script v6 indicator. It visualizes the critical gap between the previous RTH close (4:15 PM ET for futures, 4:00 PM for SPY) and the next RTH open (9:30 AM ET), helping traders spot potential price sensitivity formed during after-hours trading.
**Key Features**
- **Standard Gap Boxes**: Semi-transparent boxes highlight the gap range, with optional text labels showing day-of-week and "RTH" identifier.
- **Midpoint Line**: A customizable dashed line at the 50% level, with price labels for quick reference.
- **New: Quartile Lines (25% & 75%)**: Dotted lines (default width 1) mark the quarter and three-quarter points within the gap, ideal for finer intraday analysis. Toggle on/off, adjust style/color/width, and add labels.
- **High-Low Gap Variant**: Optional boxes and midlines for gaps between the prior close's high/low and the open's high/low—perfect for wick-based overlaps on lower timeframes (5-min or below recommended).
- **RTH Close Lines**: Extend previous close levels with dotted lines and price tags.
- **Customization Galore**: Extend elements right, limit historical displays (default: 3 gaps), no-plot sessions (e.g., avoid weekends), and time offsets for non-US indices.
**How to Use**
Apply to 15-min or lower charts for best results. Toggle "extend right" for ongoing levels. SPY auto-adjusts for its 4 PM close.
Tested on major indices—enhance your gap trading strategy today! Questions? Drop a comment.
Thanks to twingall for supplying the original code.
Thanks to The Inner Circle Trader (ICT) for the logical and systematic application.
6 minutes ago
Release Notes
### Regular Trading Hours (RTH) Gap Indicator with Quartile Levels
**Overview**
Discover overnight gaps in index futures like ES, YM, and NQ, or stocks like SPY, with this enhanced Pine Script v6 indicator. It visualizes the critical gap between the previous RTH close (4:15 PM ET for futures, 4:00 PM for SPY) and the next RTH open (9:30 AM ET), helping traders spot potential price sensitivity formed during after-hours trading.
**Key Features**
- **Standard Gap Boxes**: Semi-transparent boxes highlight the gap range, with optional text labels showing day-of-week and "RTH" identifier.
- **Midpoint Line**: A customizable dashed line at the 50% level, with price labels for quick reference.
- **New: Quartile Lines (25% & 75%)**: Dotted lines (default width 1) mark the quarter and three-quarter points within the gap, ideal for finer intraday analysis. Toggle on/off, adjust style/color/width, and add labels.
- **High-Low Gap Variant**: Optional boxes and midlines for gaps between the prior close's high/low and the open's high/low—perfect for wick-based overlaps on lower timeframes (5-min or below recommended).
- **RTH Close Lines**: Extend previous close levels with dotted lines and price tags.
- **Customization Galore**: Extend elements right, limit historical displays (default: 3 gaps), no-plot sessions (e.g., avoid weekends), and time offsets for non-US indices.
**How to Use**
Apply to 15-min or lower charts for best results. Toggle "extend right" for ongoing levels. SPY auto-adjusts for its 4 PM close.
Tested on major indices—enhance your gap trading strategy today! Questions? Drop a comment.
Thanks to twingall for supplying the original code.
Thanks to The Inner Circle Trader (ICT) for the logical and systematic application.
+++ 2025.10.13 added new labels / fixed bugs
Z-Score Momentum | MisinkoMasterThe Z-Score Momentum is a new trend analysis indicator designed to catch reversals, and shifts in trends by comparing the "positive" and "negative" momentum by using the Z-Score.
This approach helps traders and investors get unique insight into the market of not just Crypto, but any market.
A deeper dive into the indicator
First, I want to cover the "Why?", as I believe it will ease of the part of the calculation to make it easier to understand, as by then you will understand how it fits the puzzle.
I had an attempt to create a momentum oscillator that would catch reversals and provide high tier accuracy while maintaining the main part => the speed.
I thought back to many concepts, divergences between averages?
- Did not work
Maybe a MACD rework?
- Did not work with what I tried :(
So I thought about statistics, Standard Deviation, Z-Score, Sharpe/Sortino/Omega ratio...
Wait, was that the Z-Score? I only tried the For Loop version of it :O
So on my way back from school I formulated a concept (originaly not like this but to that later) that would attempt to use the Z-Score as an accurate momentum oscillator.
Many ideas were falling out of the blue, but not many worked.
After almost giving up on this, and going to go back to developing my strategies, I tried one last thing:
What if we use divergences in the average, formulated like a Z-score?
Surprise-surprise, it worked!
Now to explain what I have been so passionately yapping about, and to connect the pieces of the puzzle once and for all:
The indicator compares the "strength" of the bullish/bearish factors (could be said differently, but this is my "speach bubble", and I think this describes it the best)
What could we use for the "bullish/bearish" factors?
How about high & low?
I mean, these are by definitions the highest and lowest points in price, which I decided to interpret as: The highest the bull & bear "factors" achieved that bar.
The problem here is comparison, I mean high will ALWAYS > low, unless the asset decided to unplug itself and stop moving, but otherwise that would be unfair.
Now if I use my Z-score, it will get higher while low is going up, which is the opposite of what I want, the bearish "factor" is weaker while we go up!
So I sat on my ret*rded a*s for 25 minutes, completly ignoring the fact the number "-1" exists.
Surprise surprise, multiplying the Z-Score of the low by -1 did what I wanted!
Now it reversed itself (magically). Now while the low keeps going down, the bear factor increases, and while it goes up the bear factor lowers.
This was btw still too noisy, so instead of the classic formula:
a = current value
b = average value
c = standard deviation of a
Z = (a-b)/c
I used:
a = average value over n/2 period
b = average value over n period
c = standard deviation of a
Z = (a-b)/c
And then compared the Z-Score of High to the Z-Score of Low by basic subtraction, which gives us final result and shows us the strength of trend, the direction of the trend, and possibly more, which I may have not found.
As always, this script is open source, so make sure to play around with it, you may uncover the treasure that I did not :)
Enjoy Gs!
Advanced Memecoin Tracker -> PROFABIGHI_CAPITAL (Backtest)🌟 Overview
The Advanced Memecoin Tracker → PROFABIGHI_CAPITAL (Backtest) indicator screens a diverse portfolio of memecoins across major blockchains, scoring them based on momentum, volatility-adjusted performance, and relative strength to chain basecoins for dynamic eligibility ranking. It simulates rotational long-only exposure to top performers while comparing against equal-weight holds and benchmarks, delivering tables for conditions, rankings, and metrics to identify high-potential memecoin rotations.
⚙️ Backtest Configuration
- Leverage Multiplier : Adjustable amplification for simulated position returns to model leveraged trading scenarios
- Start Date Selection : Defines the beginning of the backtest period for all equity and hold calculations
- Slippage Percentage : Deducts execution costs from trades to reflect real-market friction
- Commission Percentage : Applies brokerage fees on position changes for net performance accuracy
- Metrics Tables Toggle : Enables or disables detailed performance summaries for chart focus
- Basecoin Symbols : Configurable references (ETH, SOL, SUI, VIRTUAL) for relative strength comparisons
📅 Date Range Settings
- Backtest Inception Point : Restricts simulations to bars after the selected timestamp for targeted analysis
- Equity Initialization : Sets starting value to unity on the inception date
- Historical Gating : Ignores pre-start data to focus on defined performance windows
- Forward Cost Application : Applies slippage and commissions only within the active period
📊 PROFABIGHI_CAPITAL Metrics Display
Equity Curve Options:
- Dynamic Portfolio Path : Traces cumulative returns from rotational allocations
- Benchmark Overlay : Compares against hold strategies for relative outperformance
- Inception Reference : Marks the start with a vertical line and label
- Return Percentage Label : Shows total gain/loss dynamically
- Shaded Growth Area : Fills under the curve for visual volume emphasis
- Suppression Choice : Hides the curve to prioritize table views
Metrics Table Setup:
- Split-Panel Distribution : Organizes asset stats across bottom-center and bottom-right
- Essential Metrics Suite : Covers drawdown, Sharpe, Sortino, Omega, and returns per asset
- Portfolio Summary : Highlights aggregated system performance
- Benchmark Hold View : Dedicated panel for passive index metrics with thresholds
- Toggle-Based Rendering : Switches to compact summary when full tables off
- Dark Theme Consistency : Black backgrounds with white text for readability
⚙️ Evaluation and Portfolio Settings
- Signal Mode Selection : Aggressive for threshold-based averaging or conservative for unanimous passes
- Asset Evaluation Count : Limits the total memecoins analyzed for efficiency
- Top Ranking Limit : Restricts the display table to elite performers
- Eligibility Threshold : Minimum score cutoff for aggressive mode inclusion
- Indicator Activation Toggles : Enables RSI variants, ROC scales, Sharpe, momentum, delta, and relative strength
- Chain Grouping Bonus : Awards extra points to memecoins outperforming their basecoin
📊 Indicator Selection
Oscillator Suite:
- Short RSI Toggle : Activates quick momentum readings for early signals
- Long RSI Toggle : Includes trend-aligned overbought/oversold checks
- ROC Multi-Scale Toggles : Engages short, medium, long change rates for layered acceleration
Efficiency and Strength Measures:
- Sharpe Ratio Toggle : Factors in risk-adjusted returns for quality filtering
- Momentum RSI Toggle : Applies bounded oscillator to velocity for persistence
- Price Delta Toggle : Evaluates directional changes or smoothed variants
- Relative Strength Toggle : Compares to basecoins for chain-specific outperformance
📊 RSI Configuration
Input and Period Controls:
- RSI Price Source : Chooses the data feed for oscillator computation
- Short Period Adjustment : Tunes responsiveness for fast memecoin swings
- Long Period Adjustment : Sets broader horizon for sustained momentum
Noise Reduction Layers:
- Primary Average Type and Span : Selects and sizes first smoothing for clarity
- Secondary Layer Toggle : Adds comparator average for crossover refinement
- Secondary Average Type and Span : Customizes the backup smoother
- Adaptive Volatility Window : VIDYA lookback for dynamic response
Signal Generation Rules:
- Mid-Range Favoring : Credits building strength without extremes
- Crossover Preference : Rewards favorable MA alignments in dual setups
- Mode-Adaptive Scoring : Partial in aggressive, strict in conservative
📊 ROC Configuration
Change Rate Horizons:
- Short-Term Period : Captures immediate price velocity bursts
- Medium-Term Period : Balances recent acceleration trends
- Long-Term Period : Smooths over extended momentum phases
Directional Bias Logic:
- Positive Thresholding : Full credit for upward changes across scales
- Unified Multi-Period View : Aggregates for comprehensive rate alignment
- Binary Momentum Check : Pass/fail on positivity for simplicity
📊 Sharpe Ratio Configuration
Efficiency Windowing:
- Return/Volatility Lookback : Defines historical scope for ratio base
- Value Smoothing Span : Applies EMA to steady raw computations
- Buy Signal Bound : Upper threshold for positive efficiency
- Sell Signal Bound : Lower cutoff for underperformance flags
Scaling and Normalization:
- Annual Factor Application : Converts daily to yearly for standardization
- Zero-Division Guard : Defaults to neutral on flat volatility
- Threshold-Based Credit : Full pass above buy, penalties below sell in aggressive mode
📊 Momentum RSI Configuration
Velocity Oscillation Setup:
- Momentum Horizon : Sets change detection period for input to RSI
- Bounded Strength Period : RSI length on momentum for normalized power
- First Smoothing Choice and Size : Average type and length for initial filter
- Second Layer Activation : Optional dual for advanced crossover
Dynamic Adaptation:
- Volatility Response Window : VIDYA period for market-sensitive smoothing
- Midline Dominance Reward : Credits above-center persistence
- Alignment Scoring : Full in conservative, flexible in aggressive
📊 Price Delta RSI Configuration
Change Assessment Mode:
- Raw vs. Smoothed Delta : Direct differences or RSI-applied for refinement
- Delta Computation Span : Lookback for price shift evaluation
- Oscillation on Delta : RSI period when using bounded variant
Filter Enhancements:
- Initial Average Type and Span : Smoother for delta signal clarity
- Comparator Layer Toggle : Dual-MA for directional confirmation
- Adaptive Volatility Span : VIDYA window for responsive adjustment
Bias Determination:
- Upward Shift Credit : Full for positive raw deltas
- Center or Cross Favor : Above 50 or aligned MA for smoothed
- Integrated Versatility : Supports both basic and layered delta views
📊 Relative Strength Configuration
Chain Comparison Framework:
- RSI Ratio Period : Oscillator length on asset-to-basecoin ratio
- Smoothing Average Type and Span : Filter for RS signal stability
- Dual Layer Toggle : Second average for crossover enhancement
- Volatility-Adjusted Window : VIDYA lookback for dynamic RS smoothing
Outperformance Logic:
- Midline Superiority : Credits RS above 50 for basecoin dominance
- Crossover Alignment : Rewards favorable dual-MA setups
- Group Bonus Integration : Extra points for top chain performers
📊 Beta Assessment
Market Sensitivity Measure:
- Benchmark Reference : Index symbol for relative volatility baseline
- Covariance Horizon : Period for return pairing and normalization
Correlation Derivation:
- Daily Shift Alignment : Matches asset and benchmark changes
- Variance Safeguard : Handles edge cases in division
- Contextual Layer : Adds relative risk without direct score impact
🪙 Memecoin Portfolio Setup
Chain-Segmented Inputs:
- Ethereum Group : Up to 9 symbols for ETH-based memecoins
- Solana Group : Up to 9 symbols for SOL-based memecoins
- SUI Group : Up to 9 symbols for SUI-based memecoins
- BASE/VIRTUAL Group : Up to 9 symbols for alternative chain memecoins
Basecoin References:
- ETH, SOL, SUI, VIRTUAL Symbols : Configurable anchors for RS calculations
- Security Price Fetching : Pulls closes for all enabled memecoins
- Group-Aware Arrays : Stores names, metrics, and conditions by index
📊 Scoring and Rotation Engine
Chain Strength Ranking:
- Basecoin RSI Computation : Applies oscillator to each reference
- Top Chain Identification : Selects strongest base for bonus allocation
- Group Bonus Assignment : Boosts scores for memecoins on leading chains
Per-Asset Evaluation:
- Enabled Indicator Tally : Counts active metrics for normalized averaging
- Binary Alignment Check : 1 for bullish conditions, 0 otherwise
- RS Multi-Chain Max : Takes highest relative strength across bases
Final Eligibility Rules:
- Aggressive Averaging : Full score if normalized meets threshold
- Conservative Consensus : Requires all toggled indicators to pass
- Bonus-Enhanced RS : Adds chain leadership points for competitive edge
🏆 Ranking and Allocation
Score-Based Sorting:
- Descending Order : Ranks assets by final eligibility rating
- Threshold Pruning : Filters to qualifying entries up to limit
- Eligible Pool Formation : Builds set for dynamic position weighting
Long Signal Generation:
- Top-Asset Activation : Flags longs for ranked memecoins
- Array Mapping : Assigns booleans to each instrument index
- Real-Time Rebalance : Updates on bar close for responsive rotation
📋 Tables and Visuals
Ranking Display Panel:
- Bottom-Left Compact Grid : Lists top assets with rank, name, and score
- Clean Name Stripping : Removes exchange prefixes for brevity
- Last-Bar Refresh [/b>: Updates only on final bar for efficiency
Basiscoin Strength Table:
- Top-Left Summary : Ranks basecoins by RSI for chain context
- Numerical Ordering : 1-4 positions with symbol labels
- Performance Insight : Highlights leading ecosystem for bonus awareness
📈 Backtest Simulation
State Tracking Arrays:
- Current/Prior Long Flags : Monitors position changes per asset
- Weight Persistence : Stores previous allocations for cost calc
- Transition Detection : Identifies flips to apply fees
Equity Path Building:
- Weighted Daily Shifts : Sums changes by lagged allocations
- Cost Subtraction : Deducts slippage/commissions on transitions
- Compounded Growth : Chains net returns from unity start
- Hold Baseline : Equal-weight across all for passive comparison
📊 Metrics Derivation
Risk-Return Analytics:
- Maximum Drawdown : Peak-to-trough drops for each path
- Sharpe Efficiency : Annualized return per volatility unit
- Sortino Downside Focus : Penalizes only negative deviations
- Omega Probability Weight : Gains vs. losses beyond threshold
Comprehensive Breakdown:
- Per-Asset Isolation : Individual stats for memecoin performance
- System Composite : Aggregated from rotational equity
- Benchmark Parallels : Hold metrics for validation
- Formatted Presentation [/b>: Percentages and rounded values in tables
🔔 Alert Integration
- Eligible Asset List : Comma-separated top-ranked memecoins on close
- No-Qualify Notice : Alerts when criteria unmet
- Bar-Close Dispatch [/b>: Single trigger per confirmed bar
- Name Simplification [/b>: Clean symbols without prefixes
✅ Key Takeaways
- Chain-Focused Screening : Scores memecoins with relative strength to basecoins for ecosystem edge
- Rotational Exposure : Dynamically weights top eligible for momentum capture
- Realistic Simulation : Factors leverage, costs, and holds for practical insights
- Visual Prioritization : Tables spotlight rankings, conditions, and basecoin leaders
- Flexible Calibration : Toggles and modes tune sensitivity to volatility
- Bonus-Driven Groups : Rewards outperformance within leading chains
- Alert Efficiency : Delivers actionable picks without overload
- Scalable Multi-Asset : Handles dozens of memecoins with array optimization
M Carlo Pro -> PROFABIGHI_CAPITAL🌟 Overview
The M Carlo Pro is a sophisticated Monte Carlo simulation engine that generates probabilistic price projections and scenario analysis frameworks . It offers dual-mode operation combining forward-looking price path modeling with return-based scenario testing , featuring confidence interval calculations , histogram distribution analysis , and customizable random sampling from historical data or user-defined return distributions.
⚙️ Main Mode Selector
- Analysis Mode Choice : Select between Scenario Analysis or Price Projection
- Scenario Analysis : Return-based simulations displayed in separate indicator pane with distribution analysis
- Price Projection : Forward price paths rendered directly on main price chart
- Mode-Specific Visualization : Each mode optimizes display for its analytical purpose
📊 Common Simulation Settings
- Random Seed : Fixed seed value for reproducible simulation results across multiple runs
- Distribution Type Selection : Choose between Normal (Gaussian) distribution or Bootstrap resampling
- Number of Paths : Total simulation iterations to generate for statistical validity
- Projection Length : Forward-looking bars or steps for each simulation path
- Boundaries Only Toggle : Display only confidence bounds instead of full path ensemble
- Historical Lookback : Number of past bars to collect for return distribution calculation
- Path Style Selector : Visual line style (solid, dotted, or dashed) for rendered paths
📈 Scenario Analysis Settings
Simulation Source Options:
- Price Mode : Calculates returns from historical price data automatically
- Custom Returns Mode : Uses user-defined return values for scenario testing
Return Input Framework:
- Primary Returns : Main scenario return values entered as text (one per line)
- Secondary Returns : Additional scenario layer for multi-dimensional analysis
- Tertiary Returns : Third scenario dimension for complex modeling
- Quaternary Returns : Fourth scenario layer for maximum flexibility
- Multi-Layer Support : Combine multiple return sets for comprehensive scenario coverage
Confidence and Display:
- Confidence Level Percentage : Statistical confidence interval for boundary calculations
- Path Lines Only : Show simulation paths without additional visual elements
- Scatter Plot Mode : Render final outcomes as scatter points instead of connected paths
- Distribution View Only : Display exclusively the histogram distribution without paths
Histogram Configuration:
- Binning Method Selection : Choose between Sturges, Rice, Square Root, or custom bin calculation
- Automatic Bin Sizing : Statistical formulas determine optimal histogram granularity
- Custom Bin Option : Manual specification of histogram bar count when custom method selected
📈 Price Projection Settings
- Display Scale Toggle : Show or hide price axis and scale labels on projection chart
- Force Render Option : Override path limit for full rendering (may truncate long projections)
- Show Mean Path : Display the average projection path across all simulations for central tendency visualization
- Performance Table : Summary statistics showing number of paths generated and projection length
🔧 Distribution Methods
Normal Distribution (Gaussian):
- Calculates mean and standard deviation from historical returns
- Generates random values using Box-Muller transform
- Produces symmetric probability distribution around mean
- Two independent uniform random numbers transformed into normally distributed values
Bootstrap Resampling:
- Randomly samples from actual historical return observations
- Preserves empirical distribution characteristics without parametric assumptions
- Each simulation step selects one historical return with replacement
- Captures real market behavior including fat tails and skewness
Return Calculation Logic:
- Price Mode : Logarithmic returns calculated from consecutive price ratios
- Custom Mode : User-provided returns applied directly to simulation
- Exponential Application : Price mode uses exponential of return for price updates
- Additive Application : Custom return mode adds returns directly
📊 Scenario Analysis Execution
Simulation Loop Process:
- Initialize starting value (price or sum of returns)
- Generate random return using selected distribution method
- Apply return to current value using appropriate calculation method
- Store intermediate results in matrix structure
- Track final outcomes in endpoint array
- Repeat for specified number of paths
Confidence Interval Calculation:
- Bins final outcomes into histogram with chosen binning method
- Identifies bin with maximum frequency (mode)
- Expands range symmetrically around mode
- Calculates cumulative probability of range
- Highlights bins within specified confidence level
- Displays confidence percentage and visual fill
Visualization Components:
- Path Rendering : Colored lines showing individual simulation trajectories
- Scatter Plot Option : Final outcomes plotted as individual points with labels or boxes
- Boundary Lines : Orange and teal lines marking confidence envelope when boundaries-only enabled
- Current Sum Line : Yellow reference line showing starting return sum in custom mode
- Step Labels : Bar numbers or step counts along horizontal axis
- Scale Axes : Vertical scale with value labels and horizontal baseline
📈 Price Projection Execution
Path Generation Framework:
- Divides total paths into twenty batches for performance optimization
- Each batch processes assigned number of simulations
- Generates forward price points using distribution sampling
- Accumulates sum of all prices at each projection step for average calculation
- Stores endpoints for statistical analysis
- Renders paths as polylines with random color assignment
Mean Path Calculation:
- Sums all simulated prices at each forward bar
- Divides by total number of simulations for average
- Plots thicker aqua-colored line representing expected value path
- Provides central tendency reference across all scenarios
Performance Optimization:
- Batch Processing : Splits simulations into manageable chunks
- Point Aggregation : Collects points before polyline rendering
- Conditional Rendering : Force option overrides automatic path limits
- Dynamic Coloring : Random RGB generation for path differentiation
Scale and Annotation:
- Vertical Scale : Price axis with evenly spaced labels showing projection range
- Horizontal Scale : Bar count labels showing forward projection timeline
- Grid Lines : Teal-colored axes forming scale framework
- Performance Table : Bottom-right display of simulation parameters
🎨 Visualization Features
Scenario Analysis Display (Separate Pane):
- Simulation Paths : Multi-colored trajectories from starting point to projection horizon
- Baseline Plot : Aqua line showing starting value (price or return sum)
- Confidence Boundaries : Orange (lower) and teal (upper) envelope lines
- Histogram Distribution : Orange bars showing frequency of final outcomes
- Bin Labels : Outcome values and frequencies displayed on each histogram bar
- Confidence Highlight : Darker orange shading on bins within confidence interval
- Confidence Label : Percentage display showing statistical coverage
- Axis Scaling : Adaptive vertical scale based on outcome range
Price Projection Display (Main Chart):
- Price Candles : Teal (bullish) or orange (bearish) candles on underlying price chart
- Projection Paths : Rainbow-colored polylines extending forward from current bar
- Mean Path Line : Thick aqua line showing average projection across all simulations
- Scale Display : Optional price axis and bar count labels
- Performance Table : Summary box showing simulation statistics
Common Visual Elements:
- Random Coloring : Each path assigned unique RGB values for differentiation
- Line Style Options : Solid, dotted, or dashed rendering for all paths
- Transparent Colors : Semi-transparent fills and lines prevent visual clutter
- Dynamic Scaling : Automatic axis adjustment based on outcome distribution
🔍 Advanced Features
Matrix Data Management:
- Row-Column Structure : Simulation results stored in two-dimensional matrix
- Color Matrix : Parallel matrix storing path colors for rendering
- Min-Max Tracking : Boundary matrix records extremes at each projection step
- Endpoint Array : Final outcome values collected for histogram analysis
Histogram Construction:
- Automatic Binning : Statistical formulas calculate optimal bin count based on sample size
- Sturges Formula : Logarithmic approach for bin determination
- Rice Rule : Cube-root-based calculation for granularity
- Square Root Method : Simple square root of sample size
- Frequency Counting : Each outcome assigned to appropriate bin
- Value Tracking : Minimum value in each bin recorded for labeling
Scatter Plot Implementation:
- Label Creation : First 500 outcomes rendered as styled labels with circular markers
- Box Fallback : Additional outcomes beyond label limit rendered as boxes
- Random Positioning : X-coordinate randomization prevents perfect vertical alignment
- Color Preservation : Each point retains its assigned simulation color
Adaptive Visualization:
- Mode Detection : Different rendering logic for price versus return simulations
- Toggle Interactions : Boundary-only and histogram-only modes override default displays
- Dynamic Limits : Path rendering adjusts based on performance constraints
- Conditional Elements : Scale, mean, and table displays controlled by user toggles
🎯 Use Cases and Applications
Risk Assessment:
- Generate probability distribution of future outcomes
- Identify worst-case and best-case scenarios with confidence intervals
- Quantify likelihood of specific price targets
- Visualize range of plausible futures based on historical volatility
Scenario Planning:
- Test specific return sequences using custom input mode
- Model multiple market environments with layered return sets
- Compare outcomes across different volatility assumptions
- Evaluate strategy performance under various conditions
Portfolio Projections:
- Forecast future portfolio values with probabilistic bounds
- Estimate expected returns across multiple timeframes
- Assess probability of reaching financial goals
- Understand distribution of potential outcomes
Education and Research:
- Demonstrate Monte Carlo methodology visually
- Explore effects of different distribution assumptions
- Compare normal versus empirical (bootstrap) distributions
- Illustrate concepts of confidence intervals and central limit theorem
✅ Key Takeaways
- Dual-Mode Flexibility : Scenario Analysis for distribution study or Price Projection for forward visualization
- Statistical Rigor : Confidence interval calculation with automatic histogram binning methods
- Distribution Choices : Normal (Gaussian) assumption or Bootstrap for empirical distribution preservation
- Custom Scenario Testing : Four-layer return input system for complex multi-dimensional analysis
- Reproducible Results : Fixed random seed ensures consistent output across multiple runs
- Batch Processing Optimization : Twenty-batch execution for handling large simulation counts
- Visual Clarity : Separate pane for scenario analysis, main chart overlay for price projections
- Mean Path Reference : Average trajectory across all simulations provides expected value guidance
- Adaptive Scaling : Automatic axis adjustment and range detection for optimal display
- Performance Management : Conditional rendering limits and force options balance detail with execution speed
- Histogram Intelligence : Multiple binning algorithms with confidence highlighting for outcome distribution
- Comprehensive Visualization : Paths, boundaries, scatter plots, histograms, scales, and tables for complete analytical picture
🚀🚀 PROFABIGHI_CAPITAL Correlation Heatmap System 🚀🚀🌟 Overview
The PROFABIGHI_CAPITAL Correlation Heatmap System is an institutional-grade multi-asset correlation visualization tool engineered for cryptocurrency traders seeking to dissect inter-asset dependencies and portfolio risk clustering through dynamic, rolling correlation matrices or benchmark-focused comparisons. By computing Pearson correlation coefficients over adjustable lookback periods across up to 20 symbols, it generates color-coded heatmaps highlighting positive (green) or negative (red) relationships, while the single-asset mode benchmarks against a primary symbol (e.g., BTC) to reveal relative strength hierarchies [/b>, top/bottom extremes, and diversification insights—empowering users to optimize allocations, detect co-movement risks , or uncover decoupling opportunities in volatile markets with real-time table updates and symmetric visualizations.
This sophisticated system transcends basic scatter plots by offering dual-mode flexibility —comprehensive pairwise matrices for broad ecosystem scanning or targeted single-asset scans for focused relative analysis—complete with invalid symbol tolerance [/b>, dynamic table sizing [/b>, and performance-optimized fetching [/b>, ensuring seamless scalability from watchlists of 5 assets to full 20-symbol universes while maintaining computational efficiency and visual clarity for professional-grade decision-making.
🚀 Main Settings
- Display Mode : Core selector between 'X -> Y Matrix' for exhaustive pairwise correlation grids that reveal the full network of asset interdependencies, ideal for identifying clusters of high-beta alts or low-correlation hedges, and 'Single Asset R Comparison' for streamlined benchmarking against a chosen primary symbol, perfect for evaluating how individual tokens align or diverge from market leaders like BTC during regime shifts
- Correlation Length : Adjustable rolling window (default 30 bars) that defines the historical scope for coefficient calculations, where shorter periods emphasize recent volatility correlations for tactical adjustments and longer horizons capture structural relationships for strategic portfolio construction, balancing noise reduction with regime sensitivity
- Number of Assets in Matrix : Scalable limit (up to 20) controlling the heatmap dimensions, enabling focused 5x5 grids for core holdings or expansive 20x20 matrices for ecosystem-wide scanning, with automatic diagonal suppression (em-dashes) to avoid self-correlation artifacts and optimize visual density
📊 Single Asset R Comparison Settings
- The PROFABIGHI_CAPITAL Asset : Primary symbol designation (default BTCUSD) serving as the correlation anchor, allowing traders to assess how alts co-move with this reference during pumps, dumps, or sideways action, facilitating relative strength rankings and beta-like exposure profiling without full regressions
- Number of Assets in Main Table : Configurable count (up to 20) for the unsorted correlation list, providing a comprehensive yet manageable view of dependencies in original input order, useful for sequential portfolio reviews or quick scans of predefined watchlists
- Number of Top/Bottom Assets : Highlight limit (default 5) for dedicated tables showcasing strongest positive (top) and weakest/negative (bottom) correlations, spotlighting diversification candidates (low R) or momentum followers (high R) to guide rebalancing decisions amid market rotations
📈 Assets List (20x)
- Asset 1 through Asset 20 : Sequential symbol inputs for building the correlation universe, starting with majors like BTC, ETH, SOL for baseline stability and extending to alts like XRP, ADA for diversification insights, with tooltip guidance for format (e.g., CRYPTO:BTCUSD) and flexibility for custom tokens across exchanges
- Grouped Configuration : Organized list for streamlined portfolio assembly, allowing quick swaps of underperformers or additions of emerging narratives, ensuring the heatmap reflects current market themes from blue-chips to speculative plays
- Exchange Prefix Support : Native handling of prefixed symbols (e.g., CRYPTO:, BINANCE:), enabling cross-platform comparisons without manual adjustments, while the short name extractor cleans displays for readability in dense tables
📡 Data Fetching (20x)
- Parallel Security Requests : Simultaneous close price pulls for all 20 assets using timeframe-aligned fetches, ensuring synchronized data across symbols to maintain correlation accuracy even in asynchronous market hours
- System Asset Isolation : Dedicated retrieval for the primary benchmark symbol, preventing contamination in single-mode comparisons and allowing independent updates without affecting matrix computations
- Invalid Symbol Resilience : Built-in ignore_invalid_symbol parameter with na defaults, gracefully handling malformed inputs or delisted tokens to avoid script crashes and enable partial universe analysis
- Chart Timeframe Alignment : Automatic adaptation to the active chart resolution, supporting from 1-minute intraday correlations for scalping to daily for swing trading, with consistent bar indexing for reliable rolling windows
🔧 Helper Functions
- Short Name Extractor : Utility to strip exchange prefixes and suffixes (e.g., CRYPTO:BTCUSD → BTC), generating compact labels for table headers and cells, enhancing scannability in large matrices without losing symbol identity
- Correlation Column Generator : Core function computing Pearson coefficients between two series over the specified length, returning both the value and a binary color (green for positive >0, red for negative) to streamline heatmap cell population with visual intuition
- Cell Filler Routine : Standardized table.cell wrapper applying consistent black-transparent backgrounds, small text sizing, and dynamic text colors, ensuring uniform aesthetics across all visualization modes while supporting conditional formatting for emphasis
📊 Correlation Calculations
- Pairwise Rolling Coefficients : Exhaustive computation of ta.correlation for every unique asset pair (up to 190 in 20x20 mode), generating symmetric matrices that illuminate co-movement patterns, from tight BTC-ETH linkages to decoupled niche alts, with na-safe handling for data gaps
- Single-Asset Benchmark Series : Dedicated correlations against the primary symbol for all others, producing a vector of R values that quantify relative dependencies, enabling quick identification of 'BTC clones' (high positive) or inverse hedges (negative)
- Length-Parameterized Rolling : Each coefficient uses the user-defined lookback to filter transient noise, where 20-bar windows highlight short-term spillovers and 100-bar captures enduring regime correlations for long-term allocation
- Color Mapping Logic : Binary green/red assignment based on sign (positive/negative), providing immediate visual cues for diversification (seek reds) or momentum trading (cluster greens), with potential for gradient extensions in future iterations
- Diagonal Suppression : Automatic em-dash placement on self-correlations (always 1.0), avoiding redundant cells and centering focus on inter-asset insights in the heatmap grid
🎨 Visualization Logic
- Last-Bar Dynamic Refresh : Table recreation on barstate.islast with prior deletions to prevent accumulation, ensuring crisp updates without historical artifacts or memory bloat in extended sessions
- Branding Banner Table : Bottom-center single-cell overlay with bold, yellow-texted indicator title on black background, serving as persistent identifier and visual anchor amid multi-table layouts
- Matrix Heatmap Construction : Centered (num_assets+1)x(num_assets+1) table with gray borders, populating headers vertically/horizontally with short names, filling off-diagonals with formatted R values and sign-based colors for symmetric, at-a-glance dependency mapping
- Single-Mode Multi-Table Suite : Top-center primary asset highlight (yellow-bordered), middle-center unsorted main list for sequential review, left/right top/bottom sorted subsets for extreme correlation spotlights, all with gray headers and color-coded R cells
- Progressive Cell Population : Nested conditionals scaling fills to active asset count, ensuring partial matrices render cleanly while full 20x20 grids showcase exhaustive pairwise analysis without overflow
- Error Handling Label : Fallback red downward label when no valid correlations available, prompting data checks and preventing blank displays in edge cases like all-invalid symbols
✅ Key Takeaways
- Dual-Mode Versatility : Seamlessly toggles between exhaustive pairwise heatmaps for ecosystem mapping and single-asset benchmarks for relative strength profiling, adapting to tactical or strategic analysis needs
- Rolling Correlation Insights : Adjustable windows reveal dynamic dependencies, crucial for spotting co-crash risks (high positive R) or counter-trend hedges (negative R) in crypto's correlated environments
- Visual Heatmap Efficiency : Color gradients and symmetric layouts enable instant pattern recognition, from BTC-beta clusters to low-R diversification gems, accelerating portfolio optimization
- Scalable Asset Handling : Up to 20 symbols with invalid tolerance and dynamic sizing, supporting watchlist scans without performance hits or manual exclusions
- Top/Bottom Extremes : Dedicated tables flag strongest/weakest links, guiding quick rebalances toward uncorrelated assets for reduced drawdowns or amplified momentum plays
- Benchmark-Centric Flexibility : Custom primary symbol centers analysis on user priorities like ETH for DeFi focus, transforming raw R values into actionable relative performance hierarchies
TRADE ORBIT :Support & Resistance Level🧩 Features
✅ Automatically updates at the start of each new trading day
✅ Draws horizontal pivot lines that extend across the current day
✅ Red lines = Resistance levels
✅ Green lines = Support levels
✅ Labels (R1–R5, S1–S5) displayed at the right edge for clarity
✅ Lightweight and compatible with all timeframes
💡 How to Use
These levels can act as potential intraday or swing reversal zones.
Watch for price rejections or breakouts near these calculated pivots.
Combine with other tools such as RSI, volume, or moving averages for confirmation.
Portfolio Command Center📊 Portfolio Command Center — Real-Time Trading Portfolio Dashboard
Overview:
The Portfolio Command Center is an advanced management and tracking system designed for discretionary traders who manually plan their trades and want to monitor performance, exposure, and risk in real time — all directly on the chart.
Core Concept:
This tool transforms your TradingView chart into a live trading dashboard, allowing you to log your active trades, monitor their progress, calculate real-time P/L, and visualize your portfolio-wide risk exposure.
Analytical Framework:
The indicator uses a dynamic calculation engine that continuously analyzes the relationship between the current market price and your predefined trade parameters (entry, stop, and targets).
It measures Active Risk Exposure for each trade based on volatility and position size.
It aggregates results across all active trades to display real-time portfolio health metrics (balance, total profit/loss, and risk utilization).
A visual alert system highlights trades exceeding risk limits or reaching targets using color-coded cells.
Practical Purpose:
To help traders make objective decisions based on structured risk metrics rather than emotions. It serves as your personal trading command center, ensuring that every trade aligns with your predefined plan.
How to Use:
In settings, define your total portfolio balance and acceptable risk per trade.
Enter your trades manually (symbol, entry price, stop-loss, take-profit).
Monitor your performance instantly as the dashboard updates in real time.
Watch for color alerts indicating risk breaches or achieved targets.
Why is it closed-source?
The script is protected because it implements a proprietary algorithm for dynamic risk distribution and real-time performance calculation.
While the source code is private to safeguard the original methodology, the description provides a clear explanation of its purpose, concept, and use, allowing traders and moderators to understand its functionality effectively.
HPAS – Historical Price Action StatisticsHPAS – Historical Price Action Statistics (v7)
A data-driven overview of weekday behavior: price, volatility, and volume.
1) OVERVIEW
HPAS analyzes how each weekday behaves across your selected history. It aggregates daily returns, intraday ranges, and volumes into a compact heatmap table and optionally plots daily range bands (historical & today) on the chart.
Note: All weekday statistics are calculated using UTC-based daily candles for consistent results across markets (especially 24/7 assets like crypto).
The goal is context and probabilities — not signals.
2) HOW IT WORKS
Collects daily bar stats: % gain/loss (close vs open), intraday range ((High−Low) ÷ Open × 100), and contracts (volume).
Groups data by weekday (Sun–Sat) and computes: win/loss frequencies, average and max moves, average intraday ranges, and average volume.
Note: “Weekday” refers to the calendar day in UTC time . This ensures consistency across all assets and exchanges, particularly for 24/7 markets like crypto.
Compares average weekday volume to the current 20-day average (% of 20D).
Displays results in a color-shaded table; optionally draws historical daily range bands plus today’s projection with optional smoothing.
3) INCLUDED FEATURES
Core metrics
Total → Gain / Loss (% of Days): How often the day closes above/below open.
Closing → Avg / Max: Average and largest daily % moves up/down.
Intrabar (optional) → Avg / Max: Typical and extreme intraday % ranges.
Contracts → Avg (K): Average daily volume (shown in thousands).
Contracts → %20D: Weekday’s average volume as % of the current 20-day average.
Visualization & UX
Heatmap coloring: lower values appear darker; higher values lighter.
Current weekday highlight with a left-side triangle.
Tooltips on headers explain what/why/how.
Dark/Light theme support; Colorblind-safe palette toggle (Okabe–Ito).
Projection Bands
Plots historical daily range bands and today’s projected band.
Optional smoothing (SMA) for cleaner band movement.
Band Smoothing Explained: Applies a simple moving average over recent projection values to reduce sudden jumps in the upper/lower bands.
Higher values make the range lines steadier but slower to react; lower values show more real-time variability.
4) USAGE TIPS
Context, not prediction: Use stats to frame expectations, not to force trades.
Cycle awareness: Compare long vs short date windows; behavior can shift across regimes.
Volume tells a story: Elevated %20D can hint at increased participation or attention on certain weekdays.
Targets & risk: Range bands provide realistic context for sizing stops/targets.
Accessibility: Enable Colorblind-safe mode if red/green contrast is hard to read.
5) INTERPRETATION GUIDE
% Gain / % Loss — Frequency of up/down closes. Higher % Gain suggests a bullish weekday bias.
Avg Gain / Avg Loss — Mean daily % move on green/red days. Gauges typical magnitude.
Max Gain / Max Loss — Largest observed daily % change. Sets an upper bound of past extremes.
Hi-Lo Avg / Max — Typical and extreme intraday % ranges. Context for expected volatility.
Contracts Avg (K) — Average daily volume in thousands. Participation proxy.
%20D — Volume vs current 20-day average. 100% = typical, >100% = above-normal, <100% = lighter-than-normal.
6) CREDITS
Inspired by the HPAS concept popularized by Krown Trading and The Caretaker.
Rebuilt and extended for clarity, accessibility, and practical context.
Version: v7 (October 2025)
License: Educational, non-commercial use
Key Inputs (snippet)
// Projection Bands
grpBands = “Projection Bands”
showBands = input.bool(true, “Show daily range bands (historical & today)”, group=grpBands)
smoothLen = input.int(1, “Band smoothing (days)”, minval=1, maxval=20, group=grpBands)
SEIZ - Statistical External & Internal Zones [Pro]Overview
SEIZ (Statistical External & Internal Zones) visualizes how far price typically travels beyond a prior candle’s range (external to previous candles high/low) or within it (internal to previous candles high/low).
It displays percentile thresholds that highlight when movement is statistically common vs. stretched relative to recent structure.
Key Features
• External zones: mark areas where price historically tends to extend beyond the previous range.
Example: a 50th external high percentile is a historically common extension above the prior candle range’s high; a 50th external low percentile is a historically common extension below the prior candle range’s low.
• Internal zones: mark areas where price historically tends to retrace while remaining inside the previous range.
Example: a 50th internal high percentile represents a historically common move that remained within the prior candle range on the high side; similarly for internal low.
• Auto-switching: When "enabled" the indicator will automatically switch to the correct internal or external zones. For example if the indicator is on the daily timeframe it will automatically show external high zones and levels if it has gone above the previous days high. It will then hide/filter out the internal high zones because price is no longer within the previous daily range.
• Multi-time-frame table: summarizes the most significant percentile reached on each enabled timeframe (e.g., 15m → 12h, 1D) with an interval-progress readout. For example if indicator is set to "Daily" it will show the highest level reached within the day under the "High" column, and the lowest level reached in the day under the "Low" column. The "Progress" column shows how much of the timeframe of that row has completed its candle/interval.
• Highly customizable settings:
- "Show Historic": When on will show current interval zones and as many previous intervals as possible
- "Show Intervals 2 Only": When on will show only the current and previous interval zones and levels.
- Choose between drawing lines for levels or zones or both. Customize colors and transparency of zones.
Methodology (transparency)
• SEIZ uses pre-computed, timeframe-specific percentile datasets that quantify typical extensions and retracements observed in historical data.
• The datasets are embedded in the script for deterministic plotting across timeframes; no external connections are used.
• Percentile values reflect empirical frequencies (not assumptions of a normal distribution).
• These levels do not have any prediction power over future price. They are a visual to compare historically where highs and lows most commonly formed for a time period with current price.
How to use
Choose the Timeframe to reference for zones.
Leave Auto external/internal zones filtering ON for regime-aware plotting.
Optional: enable percentile lines (25 / 50 / 75 / 85 / 95) and/or filled zones; adjust opacity and labels to taste.
Set alerts on percentile crosses to be notified when price reaches statistically rare areas.
Treat SEIZ as context; it does not generate entries or exits.
Notes
• Descriptive tool — no prediction or performance claims.
• Percentiles summarize historical behavior and can vary with market conditions.
• Source is protected to safeguard the proprietary construction of percentile datasets.
• Non-standard chart types (e.g., Heikin Ashi, Renko) are for display only.
Credits
Developed by LevelLogic Indicators to help interpret market structure through empirical percentile context.
AlphaTrend - Medium Term Trend Probability Indicator on TOTALESWHAT IS ALPHATREND?
AlphaTrend is a consensus-based trend identification system that combines 7 independent trend detection methodologies into a single probability score. Designed for medium-term trading (days to weeks), it aggregates diverse analytical approaches—from volatility-adjusted moving averages to statistical oscillators—to determine directional bias with quantifiable confidence.
Unlike single-indicator systems prone to false signals during consolidation, AlphaTrend requires majority agreement across multiple uncorrelated methods before generating directional signals, significantly reducing whipsaws in choppy markets.
METHODOLOGY - THE 7-INDICATOR VOTING SYSTEM
Each indicator analyzes trend from a mathematically distinct perspective and casts a vote: +1 (bullish), -1 (bearish), or 0 (neutral). The average of all 7 votes creates the final probability score ranging from -1 (strong bearish) to +1 (strong bullish).
1. FLXWRT RMA (VOLATILITY-ADJUSTED BASELINE)
Method: RMA (Running Moving Average) with ATR-based dynamic bands
Calculation:
RMA = Running MA of price over 12 periods
ATR = Average True Range over 20 periods
Long Signal: Price > RMA + ATR
Short Signal: Price < RMA - ATR
Logic: Trend confirmed only when price breaks beyond volatility-adjusted boundaries, not just the moving average itself. This filters noise by requiring momentum sufficient to overcome recent volatility.
Why it works: Standard MA crossovers generate excessive false signals in ranging markets. Adding ATR bands ensures price has genuine directional momentum, not just minor fluctuations.
Settings:
RMA Length (12): Base trend smoothing
ATR Length (20): Volatility measurement period
2. BOOSTED MOVING AVERAGE (MOMENTUM-ENHANCED TREND)
Method: Double EMA with acceleration boost factor
Calculation:
EMA1 = EMA(close, length)
EMA2 = EMA(close, length/2) // Faster EMA
Boosted Value = EMA2 + sensitivity × (EMA2 - EMA1)
Final = EMA smoothing of Boosted Value
Logic: Amplifies the difference between fast and slow EMAs to emphasize trend momentum. The boost factor (1.3) accelerates response to directional moves while subsequent smoothing prevents over-reaction.
Why it works: Traditional MAs lag price action. The boost mechanism projects trend direction forward by amplifying the momentum differential between two EMAs, providing earlier signals without sacrificing reliability.
Settings:
Length (36): Base EMA period
Boost Factor (1.3): Momentum amplification multiplier
Originality: This is a proprietary enhancement to standard double EMA systems. Most indicators simply cross fast/slow EMAs; this one mathematically projects momentum trajectory.
3. HEIKIN ASHI TREND (T3-SMOOTHED CANDLES)
Method: Heikin Ashi candles with T3 exponential smoothing
Calculation:
Heikin Ashi candles = Smoothed OHLC transformation
T3 Smoothing = Triple-exponential smoothing (Tillson T3)
Signal: T3(HA_Open) crosses T3(HA_Close)
Logic: Heikin Ashi candles filter intrabar noise by averaging consecutive bars. T3 smoothing adds additional filtering using Tillson's generalized DEMA algorithm with custom volume factor.
Why it works: Regular candlesticks contain high-frequency noise. Heikin Ashi transformation creates smoother trends, and T3 smoothing eliminates remaining whipsaws while maintaining responsiveness. The T3 algorithm specifically addresses the lag-vs-smoothness tradeoff.
Settings:
T3 Length (13): Smoothing period
T3 Factor (0.3): Volume factor for T3 algorithm
Percent Squeeze (0.2): Sensitivity adjustment
Technical Note: T3 is superior to simple EMA smoothing because it applies the generalized DEMA formula recursively, reducing lag while maintaining smooth output.
4. VIISTOP (ATR-BASED TREND FILTER)
Method: Simple trend detection using price position vs smoothed baseline with ATR confirmation
Calculation:
Baseline = SMA(close, 16)
ATR = ATR(16)
Uptrend: Close > Baseline
Downtrend: Close < Baseline
Logic: The simplest component—pure price position relative to medium-term average. While basic, it provides a "sanity check" against over-optimized indicators.
Why it works: Sometimes the simplest approach is most robust. In strong trends, price consistently stays above/below its moving average. This indicator prevents the system from over-complicating obvious directional moves.
Settings:
Length (16): Baseline period
Multiplier (2.8): ATR scaling (not actively used in vote logic)
Purpose in Ensemble: Provides grounding in basic trend logic. Complex indicators can sometimes generate counterintuitive signals; ViiStop ensures the system stays aligned with fundamental price positioning.
5. NORMALIZED KAMA OSCILLATOR (ADAPTIVE EFFICIENCY-BASED TREND)
Method: Kaufman Adaptive Moving Average normalized to oscillator format
Calculation:
Efficiency Ratio = |Close - Close | / Sum(|Close - Close |, 8)
Smoothing Constant = ER × (Fast SC - Slow SC) + Slow SC
KAMA = Adaptive moving average using dynamic smoothing
Normalized = (KAMA - Lowest) / (Highest - Lowest) - 0.5
Logic: KAMA adjusts its smoothing speed based on market efficiency. In trending markets (high efficiency), it speeds up. In ranging markets (low efficiency), it slows down. Normalization converts absolute values to -0.5/+0.5 oscillator for consistent voting.
Why it works: Fixed-period moving averages perform poorly across varying market conditions. KAMA's adaptive nature makes it effective in both trending and choppy environments by automatically adjusting its responsiveness.
Settings:
Fast Period (9): Maximum responsiveness
Slow Period (21): Minimum responsiveness
ER Period (8): Efficiency calculation window
Normalization Lookback (35): Oscillator scaling period
Mathematical Significance: Kaufman's algorithm is one of the most sophisticated adaptive smoothing methods in technical analysis. The Efficiency Ratio mathematically quantifies trend strength vs noise.
6. LÉVY FLIGHT RSI (HEAVY-TAILED MOMENTUM)
Method: Modified RSI using Lévy distribution weighting for gains/losses
Calculation:
Weighted Gain = (Max(Price Change, 0))^Alpha
Weighted Loss = (-Min(Price Change, 0))^Alpha
RSI = 100 - (100 / (1 + RMA(Gain) / RMA(Loss)))
Centered RSI = RSI - 50
Logic: Standard RSI treats all price changes linearly. Lévy Flight RSI applies power-law weighting (Alpha = 1.5) to emphasize larger moves, modeling heavy-tailed distributions observed in real market data.
Why it works: Market returns exhibit "fat tails"—large moves occur more frequently than normal distribution predicts. Lévy distributions (Alpha between 1-2) better model this behavior. By weighting larger price changes more heavily, this RSI variant becomes more sensitive to genuine momentum shifts while filtering small noise.
Settings:
RSI Length (14): Standard period
Alpha (1.5): Lévy exponent (1=linear, 2=quadratic)
MA Length (12): Final smoothing
Originality: Standard RSI uses unweighted gains/losses. This implementation applies stochastic process theory (Lévy flights) from quantitative finance to create a momentum indicator more aligned with actual market behavior.
Mathematical Background: Lévy flights describe random walks with heavy-tailed step distributions, observed in financial markets, animal foraging patterns, and human mobility. Alpha=1.5 balances between normal distribution (Alpha=2) and Cauchy distribution (Alpha=1).
7. REGULARIZED-MA OSCILLATOR (Z-SCORED TREND DEVIATION)
Method: Moving average converted to z-score oscillator
Calculation:
MA = EMA(close, 19)
Mean = SMA(MA, 30)
Std Dev = Standard Deviation(MA, 30)
Z-Score = (MA - Mean) / Std Dev
Logic: Converts absolute MA values to statistical standard deviations from mean. Positive z-score = MA above its typical range (bullish), negative = below range (bearish).
Why it works: Raw moving averages don't indicate strength—a 50-day MA at $50k vs $60k has no contextual meaning. Z-scoring normalizes this to "how unusual is current MA level?" This makes signals comparable across different price levels and time periods.
Settings:
Length (19): Base MA period
Regularization Length (30): Statistical normalization window
Statistical Significance: Z-scores are standard in quantitative analysis. This indicator asks: "Is the current trend statistically significant or just random noise?"
AGGREGATION METHODOLOGY
Voting System:
Each indicator returns: +1 (bullish), -1 (bearish), or 0 (neutral)
Total Score = Sum of all 7 votes (-7 to +7)
Average Score = Total / 7 (-1.00 to +1.00)
Signal Generation:
Long Signal: Average > 0 (majority bullish)
Short Signal: Average < 0 (majority bearish)
Neutral: Average = 0 (perfect split or all neutral)
Why Equal Weighting:
Each indicator represents a fundamentally different analytical approach:
Volatility-adjusted (RMA, ViiStop)
Momentum-based (Boosted MA, Lévy RSI)
Adaptive smoothing (KAMA)
Statistical (MA Oscillator)
Noise-filtered (Heikin Ashi T3)
Equal weighting ensures no single methodology dominates. This diversification reduces bias and improves robustness across market conditions.
ORIGINALITY - WHY THIS COMBINATION WORKS
Traditional Multi-Indicator Approaches:
Combine similar indicators (multiple MAs, multiple oscillators)
Use arbitrary thresholds for each indicator
Don't normalize signals (hard to compare RSI to MACD)
Often just "if RSI > 70 AND MACD > 0 = buy"
AlphaTrend MTPI Innovations:
Methodological Diversity: Includes volatility-adaptive (RMA), momentum-enhanced (Boosted MA), efficiency-based (KAMA), heavy-tailed statistics (Lévy RSI), and smoothed candles (HA). No redundant indicators.
Binary Voting: Each indicator reduces to simple +1/-1/0 vote, making aggregation transparent and preventing any indicator from overwhelming the consensus.
Medium-Term Optimization: Parameter choices (12-36 period averages) specifically target multi-day to multi-week trends, not scalping or long-term positioning.
Advanced Mathematics: Incorporates Tillson T3, Kaufman Efficiency Ratio, Lévy distributions, and statistical z-scoring—not just basic MAs and RSIs.
No Overfit Risk: With 7 diverse components voting equally, the system can't overfit to any specific market regime. If trending markets favor KAMA, but choppy markets favor Boosted MA, the ensemble stays robust.
Why 7 Indicators, Not 3 or 10:
Fewer than 5: Insufficient diversification, single indicator failures impact results heavily
More than 9: Diminishing returns, redundancy increases, computational load grows
7 provides: Odd number (no ties), sufficient diversity, manageable complexity
VISUAL COMPONENTS
1. Bar Coloring:
Cyan bars: Bullish consensus (average score > 0)
Magenta bars: Bearish consensus (average score < 0)
No color: Neutral (score = 0 or date filter disabled)
2. MTPI Summary Table (Bottom Center):
MTPI Signal: Current directional bias (LONG/SHORT/NEUTRAL)
Average Score: Precise consensus reading (-1.00 to +1.00)
3. Indicator Status Table (Bottom Right):
Shows all 7 individual indicator scores
Score column: +1 (bullish), -1 (bearish), 0 (neutral)
Signal column: Text interpretation of each vote
Color-coded cells: Cyan (long), Magenta (short), Gray (neutral)
HOW TO USE
For Swing Trading (Recommended - Days to Weeks):
Entry Signals:
Strong Long: 5+ indicators bullish (score ≥ 0.71)
Standard Long: 4+ indicators bullish (score ≥ 0.57)
Weak Long: Simple majority (score > 0) — use with caution
Exit Signals:
Hard Stop: Score flips negative (consensus reverses)
Partial Take Profit: Score drops to +0.30 or below (weakening)
Trailing Stop: Use ATR-based stop below entry
Position Sizing:
Strong signals (|score| > 0.7): Full position
Moderate signals (0.4-0.7): 50-75% position
Weak signals (< 0.4): 25-50% or skip
For Trend Confirmation:
Use alongside your primary strategy for confluence
Only take trades when AlphaTrend agrees with your analysis
Avoid counter-trend trades when score is extreme (|score| > 0.7)
Best Timeframes:
4H: Primary timeframe for swing trading
1D: Position trading and major trend identification
1H: Active trading (shorter hold periods)
< 1H: Not recommended (designed for medium-term)
Market Conditions:
Trending markets: System excels (consensus emerges quickly)
Ranging markets: Expect mixed signals (score oscillates near zero)
High volatility: RMA and ViiStop provide stabilization
Low volatility: KAMA and Boosted MA maintain responsiveness
SETTINGS EXPLAINED
General Settings:
Use Date Filter: Enable/disable historical backtesting range
Start Date: When to begin signal generation (default: Jan 1, 2018)
Flxwrt RMA Settings:
RMA Length (12): Base trend smoothing
ATR Length (20): Volatility measurement period
Source: Price input (default: close)
Boosted MA Settings:
Length (36): Base EMA period
Boost Factor (1.3): Momentum amplification
Source: Price input
Heikin Ashi Settings:
Percent Squeeze (0.2): Sensitivity adjustment
T3 Factor (0.3): Tillson volume factor
T3 Length (13): Smoothing period
ViiStop Settings:
Length (16): Baseline period
Multiplier (2.8): ATR scaling
Source: Price input
KAMA Settings:
Fast Period (9): Maximum responsiveness
Slow Period (21): Minimum responsiveness
ER Period (8): Efficiency calculation
Normalization Lookback (35): Oscillator scaling
Levy RSI Settings:
RSI Length (14): Standard period
Alpha (1.5): Lévy exponent (power-law weighting)
MA Length (12): Final smoothing
Source: Price input
MA Oscillator Settings:
Length (19): Base MA period
Regularize Length (30): Z-score normalization window
PERFORMANCE CHARACTERISTICS
Strengths:
✅ Reduced whipsaws vs single indicators
✅ Works across varying market conditions (adaptive components)
✅ Transparent methodology (see every vote)
✅ Customizable to trading style via timeframe selection
✅ No curve-fitting (equal weighting, no optimization)
Limitations:
⚠️ Medium-term focus (not for scalping or very long-term)
⚠️ Lagging by design (consensus requires confirmation)
⚠️ Less effective in violent reversals (momentum carries votes)
⚠️ Requires clean price data (gaps/thin volume can distort)
ALERTS & AUTOMATION
No built-in alerts in current version (visual-only indicator). Users can create custom alerts based on:
Bar color changes (cyan to magenta or vice versa)
Average score crossing above/below thresholds
Specific indicator status changes in the table
BEST PRACTICES
Risk Management:
Never risk more than 1-2% per trade regardless of score
Use stop losses (ATR-based recommended)
Scale positions based on signal strength
Don't average down on losing positions
Combining with Other Analysis:
✅ Support/Resistance levels for entries
✅ Volume confirmation (accumulation/distribution)
✅ Market structure (higher highs/lower lows)
✅ Volatility regimes (adjust position size)
❌ Don't combine with redundant trend indicators (adds no value)
❌ Don't override strong consensus with gut feeling
❌ Don't use on news-driven spikes (wait for stabilization)
Backtesting Notes:
Use "Date Filter" to test specific periods
Forward-test before live deployment
Remember: consensus systems perform best in trending markets, expect reduced edge in ranges
IMPORTANT NOTES
Not a standalone strategy - Use with proper risk management
Requires clean data - Works best on liquid markets with tight spreads
Medium-term by design - Don't expect scalping signals
No magic - No indicator predicts the future; this shows current trend probability
Diversification within - The 7-component ensemble IS the diversification strategy
Not financial advice. This indicator identifies medium-term trend probability based on multi-component consensus. Past performance does not guarantee future results. Always use proper risk management and position sizing.
AlphaBTC - Long Term Trend Probability Indicator on BitcoinWHAT IS ALPHABTC?
AlphaBTC is a consensus-based long-term trend probability indicator designed specifically for Bitcoin and cryptocurrency markets. It combines 9 independent trend detection methodologies into a single probabilistic score ranging from -1 (strong bearish) to +1 (strong bullish). Unlike single-indicator systems that can produce frequent false signals, AlphaBTC requires agreement across multiple analytical frameworks before generating directional signals.
METHODOLOGY - THE 9-INDICATOR CONSENSUS MODEL
Each indicator analyzes trend from a different mathematical perspective, providing a binary vote: +1 (bullish), -1 (bearish), or 0 (neutral). The average of all 9 votes creates the final probability score.
1. AADTREND (Average Absolute Deviation Trend)
Method: Calculates average absolute deviation from a moving average using 7 different MA types (SMA, EMA, HMA, DEMA, TEMA, RMA, FRAMA)
Logic: Price crossovers above/below AAD-adjusted bands signal trend changes
Purpose: Adapts to varying market volatility conditions
2. GAUSSIAN SMOOTH TREND (GST)
Method: Multi-stage smoothing using DEMA → Gaussian Filter → SMMA → Standard Deviation bands
Logic: Long when price > (SMMA + SDmultiplier), Short when price < (SMMA - SDmultiplier)
Purpose: Removes high-frequency noise while preserving trend structure
3. RTI (RELATIVE TREND INDEX)
Method: Percentile-based ranking system comparing current price to historical upper/lower trend boundaries
Logic: Generates 0-100 index score; >80 = bullish, <20 = bearish
Purpose: Identifies price position within statistical distribution
4. HIGHEST-LOWEST DEVIATIONS TREND
Method: Dual moving average system (100/50 periods) with dynamic standard deviation bands
Logic: Compares highest and lowest boundaries from both MAs to determine trend extremes
Purpose: Identifies breakouts from multi-timeframe volatility envelopes
5. 25-75 PERCENTILE SUPERTREND
Method: Modified SuperTrend using 25th and 75th percentile bands instead of simple highs/lows
Logic: ATR-based trailing stop system anchored to percentile boundaries
Purpose: More stable trend following by filtering outlier price spikes
6. TS VOLATILITY-ADJUSTED EWMA
Method: Exponentially Weighted Moving Average with dynamic period adjustment based on ATR
Logic: Speeds up during high volatility, slows during low volatility
Purpose: Adaptive responsiveness to changing market conditions
7. NORMALIZED KAMA OSCILLATOR
Method: Kaufman Adaptive Moving Average normalized to 0-centered oscillator
Logic: Uses Efficiency Ratio to adjust smoothing constant; >0 = bullish, <0 = bearish
Purpose: Adapts to both trending and ranging markets automatically
8. EHLERS MESA ADAPTIVE MOVING AVERAGE (EMAMA)
Method: John Ehlers' MAMA/FAMA system using Hilbert Transform for cycle period detection
Logic: MAMA crossover FAMA = bullish, crossunder = bearish
Purpose: Advanced DSP-based trend detection with phase-based adaptation
9. EMA Z-SCORE
Method: Statistical z-score applied to EMA values over lookback period
Logic: >1.0 standard deviation = bullish, <0.0 = bearish
Purpose: Identifies statistically significant trend deviations
AGGREGATION METHODOLOGY
Scoring System:
Each indicator produces: +1 (bullish), -1 (bearish), or 0 (neutral)
Total score = sum of all 9 indicators (-9 to +9)
Average score = total / 9 (displayed as -1.00 to +1.00)
Signal Interpretation:
+0.50 to +1.00: STRONG BULLISH (majority consensus)
+0.30 to +0.50: MODERATE BULLISH
-0.30 to +0.30: WEAK/NEUTRAL (mixed signals)
-0.50 to -0.30: MODERATE BEARISH
-1.00 to -0.50: STRONG BEARISH (majority consensus)
Bar Coloring:
Cyan bars: Bullish consensus (score > 0)
Magenta bars: Bearish consensus (score < 0)
WHY THIS APPROACH WORKS
Traditional Single-Indicator Problems:
Overfitting to specific market conditions
High false signal rates during consolidation
No mechanism for confidence measurement
AlphaBTC Multi-Consensus Solution:
Diversification: 9 uncorrelated methodologies reduce individual indicator bias
Robustness: Requires majority agreement before signaling (prevents whipsaws)
Adaptability: Mix of momentum, volatility, and statistical indicators captures multiple market regimes
Confidence Measurement: Score magnitude indicates signal strength
Why These 9 Specific Indicators:
AADTrend - Volatility adaptation
GST - Noise filtering
RTI - Statistical positioning
HL Deviations - Multi-timeframe breakouts
Percentile ST - Robust trend following
Volatility EWMA - Dynamic responsiveness
KAMA - Efficiency-based adaptation
EMAMA - Cycle-period awareness
EMA Z-Score - Statistical confirmation
This combination covers:
Trend following (ST, EWMA, KAMA, EMAMA)
Volatility adaptation (AAD, GST, HL Dev, EWMA)
Statistical validation (RTI, Z-Score)
Adaptive smoothing (KAMA, EMAMA, Gaussian)
No single indicator covers all these bases. The ensemble approach creates a more reliable system.
VISUAL COMPONENTS
1. Score Table (Bottom Right):
Shows all 9 individual indicator scores
Color-coded: Green (bullish), Red (bearish), Gray (neutral)
Individual signals visible for transparency
2. Main Score Display (Bottom Center):
LTPI SCORE: The averaged consensus (-1.00 to +1.00)
SIGNAL: Current directional bias (LONG/SHORT)
STRENGTH: Signal confidence (STRONG/MODERATE/WEAK)
3. Bar Coloring:
Visual trend indication directly on price bars
Cyan = bullish consensus
Magenta = bearish consensus
HOW TO USE
For Long-Term Position Trading (Recommended):
Wait for average score to cross above 0 for long entries
Exit when score crosses below 0 or reverses to negative territory
Use STRENGTH indicator - only trade STRONG or MODERATE signals
For Trend Confirmation:
Use AlphaBTC as confluence with your existing strategy
Enter trades only when AlphaBTC agrees with your analysis
Avoid counter-trend trades when consensus is strong (|score| > 0.5)
Risk Management:
STRONG signals (|score| > 0.5): Full position size
MODERATE signals (0.3-0.5): Reduced position size
WEAK signals (< 0.3): Avoid trading or use for exits only
Best Timeframes:
1D chart: Primary trend identification for swing/position trading
4H chart: Intermediate trend for multi-day holds
1H chart: Short-term trend for active trading
Not Recommended:
Scalping (too many indicators create lag)
Timeframes < 1H (designed for longer-term trends)
SETTINGS EXPLAINED
Each of the 9 indicators has customizable parameters in its dedicated settings group:
AadTrend Settings:
Average Length (48): Base period for deviation calculation
AAD Multiplier (1.35): Band width adjustment
Average Type: Choose from 7 different MA types
GST Settings:
DEMA Length (9), Gaussian Length (4), SMMA Length (13)
SD Length (66): Standard deviation lookback
Multipliers for upper/lower bands
RTI Settings:
Trend Length (75): Historical data points for boundary calculation
Sensitivity (88%): Percentile threshold
Long/Short Thresholds (80/20): Entry trigger levels
HL Deviations Settings:
Dual MA system (100/50 periods)
Separate deviation coefficients for upper/lower bands
25-75 Percentile ST Settings:
SuperTrend Length (100)
Multiplier (2.35)
Percentile Length (50)
EWMA Settings:
Length (81), ATR Lookback (14)
Volatility Factor (1.0) for dynamic adjustment
KAMA Settings:
Fast/Slow Periods (50/100)
Efficiency Ratio Period (8)
Normalization Lookback (53)
EMAMA Settings:
Fast/Slow Limits (0.08/0.01) for cycle adaptation
EMA Z-Score Settings:
EMA Length (50)
Lookback Period (25)
Threshold levels for long/short signals
ALERTS
Four alert conditions available:
LTPI Long Signal: When average score crosses above 0
LTPI Short Signal: When average score crosses below 0
LTPI Long: Any bar with bullish consensus
LTPI Short: Any bar with bearish consensus
IMPORTANT NOTES
This is a CONSENSUS indicator - it shows probability, not prediction
Designed for Bitcoin
Best for long-term trend identification (days to weeks, not minutes to hours)
Lagging by design - prioritizes accuracy over speed
Not a standalone strategy - use with proper risk management and position sizing
Requires minimum 100+ bars of historical data for proper indicator calculation
Background Trend Follower by exp3rtsThe Background Trend Follower indicator visually highlights the market’s daily directional bias using subtle background colors. It calculates the price change from the daily open and shades the chart background according to the current intraday momentum.
🟢 Green background → Price is significantly above the daily open (strong bullish trend)
🔴 Red background → Price is significantly below the daily open (strong bearish trend)
🟡 Yellow background → Price is trading near the daily open (neutral or consolidating phase)
The script automatically detects each new trading day.
It records the opening price at the start of the day.
As the session progresses, it continuously measures how far the current price has moved from that open.
When the move exceeds ±50 points (custom threshold), the background color adapts to reflect the trend strength.
Perfect for traders who want a quick visual sense of intraday bias — bullish, bearish, or neutral — without cluttering the chart with extra indicators.
HTF Live View - GSK-VIZAG-AP-INDIA📘 HTF Live View — GSK-VIZAG-AP-INDIA
🧩 Overview
The HTF Live View indicator provides a real-time visual representation of higher-timeframe (HTF) candle structures — such as 15min, 30min, 1H, 4H, and Daily — all derived directly from live 1-minute data.
This allows traders to see how higher timeframe candles are forming within the current session — without switching chart timeframes.
⚙️ Core Features
📊 Live Multi-Timeframe OHLC Tracking
Continuously calculates and displays Open, High, Low, and Close values for each key timeframe (15m, 30m, 1H, 4H, and Daily) based on the ongoing session.
⏱ Session-Aware Calculation
Automatically syncs with market hours defined by user-selected start and end times. Works across multiple timezones for global compatibility.
🕹 Visual Candle Representation
Draws mini-candles on the chart for each higher timeframe to represent their current body and wick — updated live.
Green body → bullish development
Red body → bearish development
📅 Informative Table Panel
Displays a summary table showing:
Timeframe label
Period (start–end time)
Live OHLC values
Color-coded close values
🌍 Timezone Support
Fully compatible with common regions such as Asia/Kolkata, New York, London, Tokyo, and Sydney.
🔧 User Inputs
Parameter Description
Market Start Hour/Minute Define session start time (default: 09:15)
Session End Hour/Minute Define market close (default: 15:30)
Timezone Select your preferred timezone for session alignment
💡 How It Works
The indicator uses a rolling OHLC calculation function that dynamically computes candle values based on elapsed session time.
Each timeframe (15m, 30m, 1H, 4H, and Daily) is built from 1-minute data to maintain precision even during intraday updates.
Both a visual representation (candles and wicks) and a data table (numeric summary) are displayed for clarity.
🧠 Use Cases
Monitor how HTF candles are forming live without switching chart intervals.
Understand intraday structure shifts (e.g., when 1H turns from red to green).
Confirm trend alignment across multiple timeframes visually.
Combine with your volume, delta, or liquidity tools for deeper confluence.
🪶 Signature
Developed by GSK-VIZAG-AP-INDIA
© prowelltraders — Educational and analytical use only.
⚠️ Disclaimer
This indicator is for educational and informational purposes only.
It does not provide financial advice or guaranteed trading results.
Always perform your own analysis before making investment decisions.
Volume Sampled Supertrend [BackQuant]Volume Sampled Supertrend
A Supertrend that runs on a volume sampled price series instead of fixed time. New synthetic bars are only created after sufficient traded activity, which filters out low participation noise and makes the trend much easier to read and model.
Original Script Link
This indicator is built on top of my volume sampling engine. See the base implementation here:
Why Volume Sampling
Traditional charts print a bar every N minutes regardless of how active the tape is. During quiet periods you accumulate many small, low information bars that add noise and whipsaws to downstream signals.
Volume sampling replaces the clock with participation. A new synthetic bar is created only when a pre-set amount of volume accumulates (or, in Dollar Bars mode, when pricevolume reaches a dollar threshold). The result is a non-uniform time series that stretches in busy regimes and compresses in quiet regimes. This naturally:
filters dead time by skipping low volume chop;
standardizes the information content per bar, improving comparability across regimes;
stabilizes volatility estimates used inside banded indicators;
gives trend and breakout logic cleaner state transitions with fewer micro flips.
What this tool does
It builds a synthetic OHLCV stream from volume based buckets and then applies a Supertrend to that synthetic price. You are effectively running Supertrend on a participation clock rather than a wall clock.
Core Features
Sampling Engine - Choose Volume buckets or Dollar Bars . Thresholds can be dynamic from a rolling mean or median, or fixed by the user.
Synthetic Candles - Plots the volume sampled OHLC candles so you can visually compare against regular time candles.
Supertrend on Synthetic Price - ATR bands and direction are computed on the sampled series, not on time bars.
Adaptive Coloring - Candle colors can reflect side, intensity by volume, or a neutral scheme.
Research Panels - Table shows total samples, current bucket fill, threshold, bars-per-sample, and synthetic return stats.
Alerts - Long and Short triggers on Supertrend direction flips for the synthetic series.
How it works
Sampling
Pick Sampling Method = Volume or Dollar Bars.
Set the dynamic threshold via Rolling Lookback and Filter (Mean or Median), or enable Use Fixed and type a constant.
The script accumulates volume (or pricevolume) each time bar. When the bucket reaches the threshold, it finalizes one or more synthetic candles and resets accumulation.
Each synthetic candle stores its own OHLCV and is appended to the synthetic series used for all downstream logic.
Supertrend on the sampled stream
Choose Supertrend Source (Open, High, Low, Close, HLC3, HL2, OHLC4, HLCC4) derived from the synthetic candle.
Compute ATR over the synthetic series with ATR Period , then form upperBand = src + factorATR and lowerBand = src - factorATR .
Apply classic trailing band and direction rules to produce Supertrend and trend state.
Because bars only come when there is sufficient participation, band touches and flips tend to align with meaningful pushes, not idle prints.
Reading the display
Synthetic Volume Bars - The non-uniform candles that represent equal information buckets. Expect more candles during active sessions and fewer during lulls.
Volume Sampled Supertrend - The main line. Green when Trend is 1, red when Trend is -1.
Markers - Small dots appear when a new synthetic sample is created, useful for aligning activity cycles.
Time Bars Overlay (optional) - Plot regular time candles to compare how the synthetic stream compresses quiet chop.
Settings you will use most
Data Settings
Sampling Method - Volume or Dollar Bars.
Rolling Lookback and Filter - Controls the dynamic threshold. Median is robust to outliers, Mean is smoother.
Use Fixed and Fixed Threshold - Force a constant bucket size for consistent sampling across regimes.
Max Stored Samples - Ring buffer limit for performance.
Indicator Settings
SMA over last N samples - A moving average computed on the synthetic close series. Can be hidden for a cleaner layout.
Supertrend Source - Price field from the synthetic candle.
ATR Period and Factor - Standard Supertrend controls applied on the synthetic series.
Visuals and UI
Show Synthetic Bars - Turn synthetic candles on or off.
Candle Color Mode - Green/Red, Volume Intensity, Neutral, or Adaptive.
Mark new samples - Puts a dot when a bucket closes.
Show Time Bars - Overlay regular candles for comparison.
Paint candles according to Trend - Colors chart candles using current synthetic Supertrend direction.
Line Width , Colors , and Stats Table toggles.
Some workflow notes:
Trend Following
Set Sampling Method = Volume, Filter = Median, and a reasonable Rolling Lookback so busy regimes produce more samples.
Trade in the direction of the Volume Sampled Supertrend. Because flips require real participation, you tend to avoid micro whipsaws seen on time bars.
Use the synthetic SMA as a bias rail and trailing reference for partials or re-entries.
Breakout and Continuation
Watch for rapid clustering of new sample markers and a clean flip of the synthetic Supertrend.
The compression of quiet time and expansion in busy bursts often makes breakouts more legible than on uniform time charts.
Mean Reversion
In instruments that oscillate, faded moves against the synthetic Supertrend are easier to time when the bucket cadence slows and Supertrend flattens.
Combine with the synthetic SMA and return statistics in the table for sizing and expectation setting.
Stats table (top right)
Method and Total Samples - Sampling regime and current synthetic history length.
Current Vol or Dollar and Threshold - Live bucket fill versus the trigger.
Bars in Bucket and Avg Bars per Sample - How much time data each synthetic bar tends to compress.
Avg Return and Return StdDev - Simple research metrics over synthetic close-to-close changes.
Why this reduces noise
Time based bars treat a 5 minute print with 1 percent of average participation the same as one with 300 percent. Volume sampling equalizes bar information content. By advancing the bar only when sufficient activity occurs, you skip low quality intervals that add variance but little signal. For banded systems like Supertrend, this often means fewer false flips and cleaner runs.
Notes and tips
Use Dollar Bars on assets where nominal price varies widely over time or across symbols.
Median filter can resist single burst outliers when setting dynamic thresholds.
If you need a stable research baseline, set Use Fixed and keep the threshold constant across tests.
Enable Show Time Bars occasionally to sanity check what the synthetic stream is compressing or stretching.
Link again for reference
Original Volume Based Sampling engine:
Bottom line
When you let participation set the clock, your Supertrend reacts to meaningful flow instead of idle prints. The result is a cleaner state machine, fewer micro whipsaws, and a trend read that respects when the market is actually trading.
Options Position Size CalculatorOptions Position Size Calculator
Automate your options position sizing directly on the chart.
This indicator calculates the optimal number of options contracts to buy based on your risk management parameters, entry price, stop loss, and expected options decay.
📋 What It Does
Eliminates the need for external calculators by computing your position size directly on TradingView. Simply set your entry and stop loss prices, configure your risk parameters, and the indicator instantly shows you how many contracts to buy.
✨ Key Features
Visual Price Lines: Set entry and stop loss prices with draggable horizontal lines
Custom Loss Table: Input your own options loss percentages for distances from 0.1% to 1.5% (with interpolation between values)
Automatic Calculations: Calculates distance to stop loss, expected options loss, dollar risk, and final contract quantity
Live Display: All calculations shown in a clean info box on your chart
Accounts for Contract Multiplier: Correctly factors in the standard 100x options multiplier
🎯 How to Use
1. Configure Settings First
Add the indicator to your chart (set any initial prices when prompted)
Open indicator Settings (gear icon)
Enter your Portfolio Size (e.g., $10,000)
Set Risk Percentage (e.g., 2%)
Enter the Contract Price (the premium per contract, e.g., $1.50)
2. Fill Your Options Loss Table
This is crucial - you must input your own data
For each distance (0.1%, 0.2%, up to 1.5%), enter the expected % loss your options will suffer
Base this on your strategy (calls/puts), strike selection, and expiration
Use historical data from your trades or an options calculator
Example: If underlying moves 0.5% to your stop, your option might lose 30%
3. Set Entry & Stop Loss on Chart
Go back to indicator settings
Adjust Entry Price and Stop Loss Price to match your trade setup
The indicator calculates your position size instantly
4. Read Results
The indicator displays:
Distance to stop loss (%)
Expected options loss (%)
Dollar risk amount
CONTRACTS TO BUY - your position size
📊 Example
Portfolio: $10,000 | Risk: 2% | Entry: $150 | Stop: $149 (0.67% distance)
Expected loss: 38% | Contract price: $2.00
→ Buy 2 contracts
⚠️ Important
Your loss table values depend on your specific options strategy, strike, DTE, and IV
Different strategies require different loss tables
This is for educational purposes - always verify calculations
Never risk more than you can afford to lose
Made by traders, for traders. Trade safe, size smart.
Extreme Candle Pattern Visualizer🟠 OVERVIEW
This indicator compares the current candle's percentage change against historical data, then highlights past candles with equal or bigger magnitude of movement. Also, for all the highlighted past candles, it tracks how far price extends before recovering to its starting point. It also provides statistical context through percentile rankings.
IN SHORT: Quickly spot similar price movements in the past and understand how unusual the current candle is using percentile rankings.
🟠 CORE CONCEPT
The indicator operates on two fundamental principles:
1. Statistical Rarity Detection
The script calculates the percentage change (open to close) of every candle within a user-defined lookback period and determines where the current candle ranks in this distribution. A candle closing at -9% might fall in the bottom 5th percentile, indicating it's more extreme than 95% of recent candles. This percentile ranking helps traders identify statistically unusual moves that often precede reversals or extended trends.
2. Recovery Path Mapping
Once extreme candles are identified (those matching or exceeding the current candle's magnitude), the indicator tracks their subsequent price action. For bearish candles, it measures how far price dropped before recovering back to the candle's opening price. For bullish candles, it tracks how high price climbed before returning to the open. This reveals whether extreme moves typically extend further or reverse quickly.
🟠 PRACTICAL APPLICATIONS
Mean Reversion Trading:
Candles in extreme percentiles (below 10% or above 90%) often signal oversold/overbought conditions. The recovery lines show typical extension distances, helping traders set profit targets for counter-trend entries.
Momentum Continuation:
When extreme candles show small recovery percentages before price reverses back, it suggests strong directional momentum that may continue.
Stop Loss Placement:
Historical recovery data reveals typical extension ranges after extreme moves, informing more precise stop loss positioning beyond noise but before major reversals.
Pattern Recognition:
By visualizing how similar historical extremes resolved, traders gain context for current price action rather than trading in isolation.
🟠 VISUAL ELEMENTS
Orange Circles: Mark historical candles with similar or greater magnitude to current candle
Red Lines: Track downward extensions after bearish extreme candles
Green Lines: Track upward extensions after bullish extreme candles
Percentage Labels: Show exact extension distance from candle close to extreme point
Percentile Label: Color-coded box displaying current candle's statistical ranking
Hollow Candles: Background rendering for clean chart presentation
🟠 ORIGINALITY
This indicator uniquely combines statistical percentile analysis with forward-looking recovery tracking. While many indicators identify extreme moves, few show what happened next across multiple historical instances simultaneously. The dual approach provides both the "how rare is this?" question (percentile) and "what typically happens after?" answer (recovery paths) in a single visual framework.
MomentumQ Sector MatrixMomentumQ Sector Matrix — Multi-Timeframe & Sector Performance Dashboard
The MomentumQ Sector Matrix is a professional dashboard-style indicator designed to help traders quickly evaluate sector performance and momentum alignment across multiple timeframes.
It provides an instant visual snapshot of how each major U.S. sector is performing, helping traders identify strength, weakness, and rotation trends without switching between charts.
What It Does
MomentumQ Sector Matrix consolidates multi-timeframe return data (1-Month, 1-Week, and 1-Day) into a clean, color-coded table.
Each sector’s cell displays percentage performance, automatically colored green or red based on relative gains or losses.
This tool serves as a sector rotation map , letting traders:
Spot which parts of the market are leading or lagging
Track momentum alignment across monthly, weekly, and daily timeframes
Instantly identify broad market conditions (risk-on vs. risk-off)
Key Features
1. Multi-Timeframe Sector Overview
Displays percentage returns for major SPDR sectors on 1-Month, 1-Week, and 1-Day bases.
Toggle between Today and PrevD (previous day) return modes.
2. Adaptive Table Layout
Fully resizable — choose Small, Medium, or Large table sizes for the best fit on your chart.
Works seamlessly with both light and dark TradingView themes.
3. Light / Dark Mode Support
Switch between modes to automatically match your chart background.
4. Performance-Based Coloring
Green for positive returns, red for negative, gray for neutral.
Provides clear visual contrast even in compact layouts.
5. Instant Market Context
Gain quick insight into overall market strength or weakness.
Ideal for top-down analysis, ETF rotation strategies, and macro confirmation.
How to Use
Add the indicator to any chart (symbol-independent).
Choose your preferred table position and size in the settings panel.
Use 1M / 1W / 1D readings to align your trading bias with higher-timeframe context.
Why It’s Valuable
Consolidates sector analysis into a single, easy-to-read dashboard
Helps identify macro trends and sector leadership quickly
Supports both swing and intraday trading approaches
Complements existing momentum or regime-tracking systems
Disclaimer
This indicator is a technical analysis tool for educational and informational purposes only.
It does not constitute financial advice and does not guarantee profitability.
Always perform your own analysis and use proper risk management.
