DYNAMIC TRADING DASHBOARDStudy Material for the "Dynamic Trading Dashboard"
This Dynamic Trading Dashboard is designed as an educational tool within the TradingView environment. It compiles commonly used market indicators and analytical methods into one visual interface so that traders and learners can see relationships between indicators and price action. Understanding these indicators, step by step, can help traders develop discipline, improve technical analysis skills, and build strategies. Below is a detailed explanation of each module.
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1. Price and Daily Reference Points
The dashboard displays the current price, along with percentage change compared to the day’s opening price. It also highlights whether the price is moving upward or downward using directional symbols. Alongside, it tracks daily high, low, open, and daily range.
For traders, daily levels provide valuable reference points. The daily high and low are considered intraday support and resistance, while the median price of the day often acts as a pivot level for mean reversion traders. Monitoring these helps learners see how price oscillates within daily ranges.
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2. VWAP (Volume Weighted Average Price)
VWAP is calculated as a cumulative average price weighted by volume. The dashboard compares the current price with VWAP, showing whether the market is trading above or below it.
For traders, VWAP is often a guide for institutional order flow. Price trading above VWAP suggests bullish sentiment, while trading below VWAP indicates bearish sentiment. Learners can use VWAP as a training tool to recognize trend-following vs. mean reversion setups.
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3. Volume Analysis
The system distinguishes between buy volume (when the closing price is higher than the open) and sell volume (when the closing price is lower than the open). A progress bar highlights the ratio of buying vs. selling activity in percentage.
This is useful because volume confirms price action. For instance, if prices rise but sell volume dominates, it can signal weakness. New traders learning with this tool should focus on how volume often precedes price reversals and trends.
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4. RSI (Relative Strength Index)
RSI is a momentum oscillator that measures price strength on a scale from 0 to 100. The dashboard classifies RSI readings into overbought (>70), oversold (<30), or neutral zones and adds visual progress bars.
RSI helps learners understand momentum shifts. During training, one should notice how trending markets can keep RSI extended for longer periods (not immediate reversal signals), while range-bound markets react more sharply to RSI extremes. It is an excellent tool for practicing trend vs. range identification.
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5. MACD (Moving Average Convergence Divergence)
The MACD indicator involves a fast EMA, slow EMA, and signal line, with focus on crossovers. The dashboard shows whether a “bullish cross” (MACD above signal line) or “bearish cross” (MACD below signal line) has occurred.
MACD teaches traders to identify trend momentum shifts and divergence. During practice, traders can explore how MACD signals align with VWAP trends or RSI levels, which helps in building a structured multi-indicator analysis.
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6. Stochastic Oscillator
This indicator compares the current close relative to a range of highs and lows over a period. Displayed values oscillate between 0 and 100, marking zones of overbought (>80) and oversold (<20).
Stochastics are useful for students of trading to recognize short-term momentum changes. Unlike RSI, it reacts faster to price volatility, so false signals are common. Part of the training exercise can be to observe how stochastic “flips” can align with volume surges or daily range endpoints.
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7. Trend & Momentum Classification
The dashboard adds simple labels for trend (uptrend, downtrend, neutral) based on RSI thresholds. Additionally, it provides quick momentum classification (“bullish hold”, “bearish hold”, or neutral).
This is beneficial for beginners as it introduces structured thinking: differentiating long-term market bias (trend) from short-term directional momentum. By combining both, traders can practice filtering signals instead of trading randomly.
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8. Accumulation / Distribution Bias
Based on RSI levels, the script generates simplified tags such as “Accumulate Long”, “Accumulate Short”, or “Wait”.
This is purely an interpretive guide, helping learners think in terms of accumulation phases (when markets are low) and distribution phases (when markets are high). It reinforces the concept that trading is not only directional but also involves timing.
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9. Overall Market Status and Score
Finally, the dashboard compiles multiple indicators (VWAP position, RSI, MACD, Stochastics, and price vs. median levels) into a Market Score expressed as a percentage. It also labels the market as Overbought, Oversold, or Normal.
This scoring system isn’t a recommendation but a learning framework. Students can analyze how combining different indicators improves decision-making. The key training focus here is confluence: not depending on one indicator but observing when several conditions align.
Extended Study Material with Formulas
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1. Daily Reference Levels (High, Low, Open, Median, Range)
• Day High (H): Maximum price of the session.
DayHigh=max(Hightoday)DayHigh=max(Hightoday)
• Day Low (L): Minimum price of the session.
DayLow=min(Lowtoday)DayLow=min(Lowtoday)
• Day Open (O): Opening price of the session.
DayOpen=OpentodayDayOpen=Opentoday
• Day Range:
Range=DayHigh−DayLowRange=DayHigh−DayLow
• Median: Mid-point between high and low.
Median=DayHigh+DayLow2Median=2DayHigh+DayLow
These act as intraday guideposts for seeing how far the price has stretched from its key reference levels.
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2. VWAP (Volume Weighted Average Price)
VWAP considers both price and volume for a weighted average:
VWAPt=∑i=1t(Pricei×Volumei)∑i=1tVolumeiVWAPt=∑i=1tVolumei∑i=1t(Pricei×Volumei)
Here, Price_i can be the average price (High + Low + Close) ÷ 3, also known as hlc3.
• Interpretation: Price above VWAP = bullish bias; Price below = bearish bias.
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3. Volume Buy/Sell Analysis
The dashboard splits total volume into buy volume and sell volume based on candle type.
• Buy Volume:
BuyVol=Volumeif Close > Open, else 0BuyVol=Volumeif Close > Open, else 0
• Sell Volume:
SellVol=Volumeif Close < Open, else 0SellVol=Volumeif Close < Open, else 0
• Buy Ratio (%):
VolumeRatio=BuyVolBuyVol+SellVol×100VolumeRatio=BuyVol+SellVolBuyVol×100
This helps traders gauge who is in control during a session—buyers or sellers.
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4. RSI (Relative Strength Index)
RSI measures strength of momentum by comparing gains vs. losses.
Step 1: Compute average gains (AG) and losses (AL).
AG=Average of Upward Closes over N periodsAG=Average of Upward Closes over N periodsAL=Average of Downward Closes over N periodsAL=Average of Downward Closes over N periods
Step 2: Calculate relative strength (RS).
RS=AGALRS=ALAG
Step 3: RSI formula.
RSI=100−1001+RSRSI=100−1+RS100
• Used to detect overbought (>70), oversold (<30), or neutral momentum zones.
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5. MACD (Moving Average Convergence Divergence)
• Fast EMA:
EMAfast=EMA(Close,length=fast)EMAfast=EMA(Close,length=fast)
• Slow EMA:
EMAslow=EMA(Close,length=slow)EMAslow=EMA(Close,length=slow)
• MACD Line:
MACD=EMAfast−EMAslowMACD=EMAfast−EMAslow
• Signal Line:
Signal=EMA(MACD,length=signal)Signal=EMA(MACD,length=signal)
• Histogram:
Histogram=MACD−SignalHistogram=MACD−Signal
Crossovers between MACD and Signal are used in studying bullish/bearish phases.
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6. Stochastic Oscillator
Stochastic compares the current close against a range of highs and lows.
%K=Close−LowestLowHighestHigh−LowestLow×100%K=HighestHigh−LowestLowClose−LowestLow×100
Where LowestLow and HighestHigh are the lowest and highest values over N periods.
The %D line is a smooth version of %K (using a moving average).
%D=SMA(%K,smooth)%D=SMA(%K,smooth)
• Values above 80 = overbought; below 20 = oversold.
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7. Trend and Momentum Classification
This dashboard generates simplified trend/momentum logic using RSI.
• Trend:
• RSI < 40 → Downtrend
• RSI > 60 → Uptrend
• In Between → Neutral
• Momentum Bias:
• RSI > 70 → Bullish Hold
• RSI < 30 → Bearish Hold
• Otherwise Neutral
This is not predictive, only a classification framework for educational use.
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8. Accumulation/Distribution Bias
Based on extreme RSI values:
• RSI < 25 → Accumulate Long Bias
• RSI > 80 → Accumulate Short Bias
• Else → Wait/No Action
This helps learners understand the idea of accumulation at lows (strength building) and distribution at highs (profit booking).
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9. Overall Market Status and Score
The tool adds up 5 bullish conditions:
1. Price above VWAP
2. RSI > 50
3. MACD > Signal
4. Stochastic > 50
5. Price above Daily Median
BullishScore=ConditionsMet5×100BullishScore=5ConditionsMet×100
Then it categorizes the market:
• RSI > 70 or Stoch > 80 → Overbought
• RSI < 30 or Stoch < 20 → Oversold
• Else → Normal
This encourages learners to think in terms of probabilistic conditions instead of single-indicator signals.
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⚠️ Warning:
• Trading financial markets involves substantial risk.
• You can lose more money than you invest.
• Past performance of indicators does not guarantee future results.
• This script must not be copied, resold, or republished without authorization from aiTrendview.
By using this material or the code, you agree to take full responsibility for your trading decisions and acknowledge that this is not financial advice.
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⚠️ Disclaimer and Warning (From aiTrendview)
This Dynamic Trading Dashboard is created strictly for educational and research purposes on the TradingView platform. It does not provide financial advice, buy/sell recommendations, or guaranteed returns. Any use of this tool in live trading is completely at the user’s own risk. Markets are inherently risky; losses can exceed initial investment.
The intellectual property of this script and its methodology belongs to aiTrendview. Unauthorized reproduction, modification, or redistribution of this code is strictly prohibited. By using this study material or the script, you acknowledge personal responsibility for any trading outcomes. Always consult professional financial advisors before making investment decisions.
Search in scripts for "accumulation"
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels.
**The Solution:** This script implements an integrated approach that:
- Maps volume distribution across price levels using configurable row density
- Estimates delta (buying vs selling pressure) using three different methodologies
- Identifies Point of Control (highest volume price level) for key support/resistance
- Calculates Value Area boundaries where 70% of volume traded
- Provides real-time alerts for key level interactions and volume imbalances
**Unique Features:**
1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete
2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions
3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance
4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes
5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds
6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Volume Profile Methodology:
**1. Price Level Distribution:**
- Divides price range into user-defined rows (10-50 configurable)
- Calculates row height: `(Highest Price - Lowest Price) / Number of Rows`
- Distributes each bar's volume across price levels it touched proportionally
**2. Delta Volume Calculation Methods:**
**Price Action Method:**
```
Price Range = High - Low
Buy Pressure = (Close - Low) / Price Range
Sell Pressure = (High - Close) / Price Range
Buy Volume = Total Volume × Buy Pressure
Sell Volume = Total Volume × Sell Pressure
Delta = Buy Volume - Sell Volume
```
**Bid/Ask Estimation Method:**
```
Average Price = (High + Low + Close) / 3
Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4
Sell Volume = Total Volume - Buy Volume
```
**Cumulative Method:**
```
Buy Volume = Close > Open ? Volume : Volume × 0.3
Sell Volume = Close ≤ Open ? Volume : Volume × 0.3
```
**3. Point of Control (POC) Identification:**
- Scans all price levels to find maximum volume concentration
- POC represents the price level with highest trading activity
- Acts as significant support/resistance level
- **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation.
**4. Value Area Calculation:**
- Starts from POC and expands up/down to encompass 70% of total volume
- VAH (Value Area High): Upper boundary of value area
- VAL (Value Area Low): Lower boundary of value area
- Expansion algorithm prioritizes direction with higher volume
**5. Adaptive Range Selection:**
Based on profile type and timeframe optimization:
- **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars)
- **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days)
- **Session**: Current trading session or custom session times
### Performance Optimization Features:
- **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy
- **Memory Management**: Clears previous drawings to prevent performance degradation
- **Safety Constraints**: Prevents excessive memory usage with configurable limits
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Profile Configuration**: Select profile type based on trading style:
- N Bars Back: Precise control over data range
- Days Back: Intuitive calendar-based analysis
- Session: Real-time session development
2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance
3. **Delta Method**: Choose calculation method based on market type:
- Price Action: Best for trending markets
- Bid/Ask Estimate: Good for ranging markets
- Cumulative: Smoothed approach for volatile markets
4. **Visual Settings**: Configure colors, position (left/right), and display options
### Reading the Profile:
**Volume Bars:**
- **Length**: Represents relative volume at that price level
- **Color**: Green = net buying pressure, Red = net selling pressure
- **Intensity**: Darker colors indicate volume imbalances above threshold
**Key Levels:**
- **POC (Blue Line)**: Highest volume price - major support/resistance
- **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value
- **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value
- **Value Area Fill**: Shaded region showing main trading range
**Developing POC Trail:**
- **Blue Dotted Lines**: Show real-time POC evolution throughout the session
- **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution
- **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity
- **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment
### Trading Applications:
**Support/Resistance Analysis:**
- POC acts as magnetic price level - expect reactions
- VAH/VAL provide intermediate support/resistance levels
- Profile edges show areas of low volume acceptance
**Developing POC Analysis:**
- **Upward Migration**: POC moving higher = institutional accumulation, bullish bias
- **Downward Migration**: POC moving lower = institutional distribution, bearish bias
- **Stable POC**: Tight clustering = balanced market, range-bound conditions
- **Early Trend Detection**: POC direction change often precedes price breakouts
**Entry Strategies:**
- Buy at VAL with POC as target (in uptrends)
- Sell at VAH with POC as target (in downtrends)
- Breakout plays above/below profile extremes
**Volume Imbalance Trading:**
- Strong buying imbalance (>60% threshold) suggests continued upward pressure
- Strong selling imbalance suggests continued downward pressure
- Imbalances near key levels provide high-probability setups
**Multi-Timeframe Context:**
- Use higher timeframe profiles for major levels
- Lower timeframe profiles for precise entries
- Session profiles for intraday trading structure
## SCRIPT SETTINGS EXPLANATION
### Volume Profile Settings:
- **Profile Type**: Determines data range for calculation
- N Bars Back: Exact number of bars (20-500 range)
- Days Back: Calendar days with timeframe adaptation (1-365 days)
- Session: Trading session-based (intraday focus)
- **Number of Rows**: Profile resolution (10-50 range)
- **Profile Width**: Visual width as chart percentage (10-50%)
- **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard)
- **Auto-Adjust**: Automatically optimizes for different timeframes
### Delta Volume Settings:
- **Show Delta Volume**: Enable/disable delta calculations
- **Delta Calculation Method**: Choose methodology based on market conditions
- **Highlight Imbalances**: Visual emphasis for significant volume imbalances
- **Imbalance Threshold**: Percentage for imbalance detection (50-90%)
### Session Settings:
- **Session Type**: Daily, Weekly, Monthly, or Custom periods
- **Custom Session Time**: Define specific trading hours
- **Previous Sessions**: Number of historical sessions to display
### Days Back Settings:
- **Lookback Days**: Number of calendar days to analyze (1-365)
- **Automatic Calculation**: Script automatically converts days to bars based on timeframe:
- Intraday: Accounts for 6.5 trading hours per day
- Daily: 1 bar per day
- Weekly/Monthly: Proportional adjustment
### N Bars Back Settings:
- **Lookback Bars**: Exact number of bars to analyze (20-500)
- **Precise Control**: Best for systematic analysis and backtesting
### Visual Customization:
- **Colors**: Bullish (green), Bearish (red), and level colors
- **Profile Position**: Left or Right side of chart
- **Profile Offset**: Distance from current price action
- **Labels**: Show/hide level labels and values
- **Smooth Profile Bars**: Enhanced visual appearance
### Alert Configuration:
- **POC Touch**: Alerts when price interacts with Point of Control
- **VA Entry/Exit**: Alerts for Value Area boundary interactions
- **Major Imbalance**: Alerts for significant volume imbalances
## VISUAL FEATURES
### Profile Display:
- **Horizontal Bars**: Volume distribution across price levels
- **Color Coding**: Delta-based coloring for directional bias
- **Smooth Rendering**: Optional smoothing for cleaner appearance
- **Transparency**: Configurable opacity for chart readability
### Level Lines:
- **POC**: Solid blue line with optional label
- **VAH/VAL**: Dashed colored lines with value displays
- **Extension**: Lines extend across relevant time periods
- **Value Area Fill**: Optional shaded region between VAH/VAL
### Information Table:
- **Current Values**: Real-time POC, VAH, VAL prices
- **VA Range**: Value Area width calculation
- **Positioning**: Multiple table positions available
- **Text Sizing**: Adjustable for different screen sizes
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- Volume profile analysis provides structural context, not trading signals
- Delta calculations are estimations based on price action, not actual order flow
- Past volume distribution does not guarantee future price behavior
- Combine with other analysis methods for comprehensive market view
**Best Practices:**
- Use appropriate profile types for your trading style:
- Day Trading: Session or Days Back (1-5 days)
- Swing Trading: Days Back (10-30 days) or N Bars Back
- Position Trading: Days Back (60-180 days)
- Consider market context (trending vs ranging conditions)
- Verify key levels with additional technical analysis
- Monitor profile development for changing market structure
**Performance Considerations:**
- Higher row counts increase calculation complexity
- Large lookback periods may affect chart performance
- Auto-adjust feature optimizes for most use cases
- Consider using session profiles for intraday efficiency
**Limitations:**
- Delta calculations are estimations, not actual transaction data
- Profile accuracy depends on available price/volume history
- Effectiveness varies across different instruments and market conditions
- Requires understanding of volume profile concepts for optimal use
**Data Requirements:**
- Requires volume data for accurate calculations
- Works best on liquid instruments with consistent volume
- May be less effective on very low volume or exotic instruments
This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
Dark Pool Block Trades - Institutional Volume📊 Dark Pool Block Trades - Institutional Volume
Visualize where institutional money positions before major price moves occur. This indicator reveals hidden dark pool block trades that often precede significant price movements - because when smart money deploys millions and billions in strategic accumulation or distribution, retail traders need to see where it's happening.
🎯 WHY DARK POOL DATA MATTERS:
Institutions don't move large capital randomly. Dark pool block trades represent strategic positioning by sophisticated money managers with superior research and conviction. These trades create hidden support/resistance levels that often predict future price action.
The key principle: Follow institutional flow, don't fight it. When institutions get involved, they create high-probability trading opportunities.
💰 HOW INSTITUTIONS INFLUENCE PRICE:
- Large block trades establish hidden accumulation/distribution zones
- Smart money builds positions BEFORE retail awareness increases
- Institutional activity creates "footprints" at key technical levels
- These trades often signal conviction plays ahead of major moves
- Institutions typically add to winning positions throughout trends
🔍 WHAT THIS INDICATOR SHOWS:
- Visual overlay of dark pool block trades directly on price charts
- Track institutional positioning across major stocks and ETFs
- Identify accumulation/distribution zones before they become obvious to retail
- Spot high-conviction institutional trades in real-time visualization
- Customizable block trade size filters and timeframe selection
- Historical institutional activity up to 5 years or custom ranges
💡 THE TRADING ADVANTAGE:
Instead of guessing price direction, see where institutions are already positioning. When large block trades appear in dark pools, you're witnessing strategic institutional commitment that frequently leads to significant price movements.
⚡ HOW IT WORKS:
This Pine Script displays institutional dark pool transactions as visual markers on your charts. The script comes with sample data for immediate use. For expanded ticker coverage and real-time updates, external data services are available.
🎯 IDEAL FOR:
- Swing traders following institutional footprints
- Traders seeking setups backed by smart money conviction
- Position traders looking for accumulation zones
- Anyone wanting to align with institutional flow rather than fight it
🔄 SAMPLE DATA INCLUDED:
Pre-loaded with institutional activity data across popular tickers, updated daily to demonstrate how dark pool activity correlates with future price movements.
The script initially covers these tickers going back 6 months showing the top 10 trades by volume over 400,000 shares: AAPL, AMD, AMZN, ARKK, ARKW, BAC, BITO, COIN, COST, DIA, ETHA, GLD, GOOGL, HD, HYG, IBB, IWM, JNJ, JPM, LQD, MA, META, MSFT, NVDA, PG, QQQ, RIOT, SLV, SMCI, SMH, SOXX, SPY, TLT, TSLA, UNH, USO, V, VEA, VNQ, VOO, VTI, VWO, WMT, XLE, XLF, XLK, XLU, XLV, XLY
Volume Range Profile with Fair Value (Zeiierman)█ Overview
The Volume Range Profile with Fair Value (Zeiierman) is a precision-built volume-mapping tool designed to help traders visualize where institutional-level activity is occurring within the price range — and how that volume behavior shifts over time.
Unlike traditional volume profiles that rely on fixed session boundaries or static anchors, this tool dynamically calculates and displays volume zones across both the upper and lower ends of a price range, revealing point-of-control (POC) levels, directional volume flow, and a fair value drift line that updates live with each candle.
You’re not just looking at volume anymore. You’re dissecting who’s in control — and at what price.
⚪ In simple terms:
Upper Zone = The upper portion of the price range, showing concentrated volume activity — typically where selling or distribution may occur
Lower Zone = The lower portion of the price range, highlighting areas of high volume — often associated with buying or accumulation
POC Bin = The bin (price level) with the highest traded volume in the zone — considered the most accepted price by the market
Fair Value Trend = A dynamic trend line tracking the average POC price over time — visualizing the evolving fair value
Zone Labels = Display real-time breakdown of buy/sell volume within each zone and inside the POC — revealing who’s in control
█ How It Works
⚪ Volume Zones
Upper Zone: Anchored at the highest high in the lookback period
Lower Zone: Anchored at the lowest low in the lookback period
Width is user-defined via % of range
Each zone is divided into a series of volume bins
⚪ Volume Bins (Histograms)
Each zone is split into N bins that show how much volume occurred at each level:
Taller = More volume
The POC bin (Point of Control) is highlighted
Labels show % of volume in the POC relative to the whole zone
⚪ Buy vs Sell Breakdown
Each volume bin is split by:
Buy Volume = Close ≥ Open
Sell Volume = Close < Open
The script accumulates these and displays total Buy/Sell volume per zone.
⚪ Fair Value Drift Line
A POC trend is plotted over time:
Represents where volume was most active across each range
Color changes dynamically — green for rising, red for falling
Serves as a real-time fair value anchor across changing market structure
█ How to Use
⚪ Identify Key Control Zones
Use Upper/Lower Zone structures to understand where supply and demand is building.
Zones automatically adapt to recent highs/lows and re-center volume accordingly.
⚪ Follow Institutional Activity
Watch for POC clustering near price tops or bottoms.
Large volumes near extremes may indicate accumulation or distribution.
⚪ Spot Fair Value Drift
The fair value trend line (average POC price) gives insight into market equilibrium.
One strategy can be to trade a re-test of the fair value trend, trades are taken in the direction of the current trend.
█ Understanding Buy & Sell Volume Labels (Zone Totals)
These labels show the total buy and sell volume accumulated within each zone over the selected lookback period:
Buy Vol (green label) → Total volume where candles closed bullish
Sell Vol (red label) → Total volume where candles closed bearish
Together, they tell you which side dominated:
Higher Buy Vol → Bullish accumulation zone
Higher Sell Vol → Bearish distribution zone
This gives a quick visual insight into who controlled the zone, helping you spot areas of demand or supply imbalance.
█ Understanding POC Volume Labels
The POC (Point of Control) represents the price level where the most volume occurred within the zone. These labels break down that volume into:
Buy % – How much of the volume was buying (price closed up)
Sell % – How much was selling (price closed down)
Total % – How much of the entire zone’s volume happened at the POC
Use it to spot strong demand or supply zones:
High Buy % + High Total % → Strong buying interest = likely support
High Sell % + High Total % → Strong selling pressure = likely resistance
It gives a deeper look into who was in control at the most important price level.
█ Why It’s Useful
Track where fair value is truly forming
Detect aggressive volume accumulation or dumping
Visually split buyer/seller control at the most relevant price levels
Adapt volume structures to current trend direction
█ Settings Explained
Lookback Period: Number of bars to scan for highs/lows. Higher = smoother zones, Lower = reactive.
Zone Width (% of Range): Controls how much of the range is used to define each zone. Higher = broader zones.
Bins per Zone: Number of volume slices per zone. Higher = more detail, but heavier on resources.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Grid TraderGrid Trader Indicator ( GTx ):
Overview
The Grid Trader Indicator is a tool that helps traders visualize key levels within a specified trading range. The indicator plots accumulation and distribution levels, an entry level, an exit level, and a midpoint. This guide will help you understand how to use the indicator and its features for effective grid trading.
Basics of Trading Range, Grid Buy, and Grid Sell
Trading Range
A trading range is the horizontal price movement between a defined upper ( resistance ) and lower ( support ) level over a period of time. When a security trades within a range, it repeatedly moves between these two levels without trending upwards or downwards significantly. Traders often use the trading range to identify potential buy and sell points:
Upper Level (Resistance): This is the price level at which selling pressure overcomes buying pressure, preventing the price from rising further.
Lower Level (Support): This is the price level at which buying pressure overcomes selling pressure, preventing the price from falling further.
Grid Trading Strategy
Grid trading is a type of trading strategy that involves placing buy and sell orders at predefined intervals around a set price. It aims to profit from the natural market volatility by buying low and selling high in a range-bound market. The strategy divides the trading range into several grid levels where orders are placed.
Grid Buy
Grid buy orders are placed at intervals below the current price . When the price drops to these levels, buy orders are triggered . This strategy ensures that the trader buys more as the price falls, potentially lowering the average purchase price .
Grid Sell
Grid sell orders are placed at intervals above the current price . When the price rises to these levels, sell orders are triggered . This ensures that the trader sells portions of their holdings as the price increases, potentially securing profits at higher levels .
Key Points of Grid Trading
Grid Size : The interval between each buy and sell order. This can be constant (e.g., $2 intervals) or variable based on certain conditions.
Accumulation Range : The lower part of the trading range where buy orders are placed.
Distribution Range : The upper part of the trading range where sell orders are placed.
Midpoint : The average price of the entry and exit levels, often used as a reference point for balance.
As the price moves up and down within this range, your buy orders will be triggered as the price drops and your sell orders will be triggered as the price rises. This allows you to accumulate more of the asset at lower prices and sell portions at higher prices, profiting from the price oscillations within the defined range. Grid trading can be particularly effective in a sideways market where there is no clear long-term trend. However, it requires careful monitoring and adjustment of grid levels based on market conditions to minimize risks and maximize returns .
Configuring the Indicator :
Once the indicator is added, you will see a settings icon next to it. Click on it to open the settings menu.
Adjust the Upper Level , Lower Level , Entry Level , and Exit Level to match your trading strategy and market conditions.
Set the Levels Visibility to control how many bars back the levels will be plotted.
Interpreting the Levels :
Accumulation Levels : These are plotted below the entry level and are potential buy zones. They are labeled as Accumulation Level 1, 2, and 3.
Distribution Levels : These are plotted above the exit level and are potential sell zones. They are labeled as Distribution Level 1, 2, and 3.
Upper Level : Marked in fuchsia, indicating the top boundary of the trading range.
Exit Level : Marked in yellow, indicating the level at which you plan to exit trades.
Midpoint : Marked in white, indicating the average of the entry and exit levels.
Entry Level : Marked in yellow, indicating the level at which you plan to enter trades.
Lower Level : Marked in aqua, indicating the bottom boundary of the trading range.
By visualizing key levels, you can make informed decisions on where to place buy and sell orders, potentially maximizing your trading profits through systematic grid trading.
Sadgir Patterns with SL/TPThe "Sadgir Patterns with SL/TP" is a cutting-edge trading indicator designed for traders seeking to leverage the power of Hull Moving Averages in conjunction with phase accumulation analysis. This unique indicator, developed on the Pine Script platform, is ideal for various markets, including stocks, forex, cryptocurrencies, and commodities.
Key Features:
Adaptive Hull Moving Average: Utilizes an adaptive Hull Moving Average, which provides a smooth and responsive moving average line, aiding in identifying trend directions and potential market reversals.
Phase Accumulation Analysis: Integrates phase accumulation calculations to dynamically adjust the length of the Hull Moving Average, ensuring that the indicator stays in sync with market conditions.
Signal Generation: Generates clear "Long" and "Short" signals, which are visually represented on the chart, assisting traders in making informed decisions.
Dynamic Stop Loss and Take Profit Levels: Automatically calculates and plots dynamic stop loss (SL) and take profit (TP) levels as horizontal lines on the chart, based on user-defined percentage settings. These levels adjust in real-time with the price action, offering a systematic approach to risk management.
Customizable Settings: Provides users with the flexibility to adjust the source of the moving average, power settings for the Hull Moving Average, cycles, and powers for phase accumulation, as well as the percentage values for SL and TP levels.
Visual and Alert Features: Includes options for coloring the bars based on the trend direction and displays trade signals with distinct shapes. Additionally, alert conditions are set for both Long and Short signals, enabling traders to stay informed of potential trade opportunities.
Usage:
This indicator is designed for traders of all levels, from beginners to advanced. It can be used for trend following, catching reversals, or as part of a larger trading strategy. The dynamic SL and TP levels aid in managing trades effectively, providing both entry and exit points. However, traders are advised to use this indicator in conjunction with other analysis tools and consider the overall market context for the best results.
Disclaimer:
Trading involves risk, and it's important to do your own research and consider your risk tolerance before using this indicator. This tool is not intended as financial advice.
NSE:BANKNIFTY
NSE:NIFTY
MCX:CRUDEOIL1!
Market Phases NJRMarket Phases Indicator
Overview:
The Market Phases Indicator is a versatile tool designed for traders to identify key market phases, including accumulation, distribution, markup, and markdown. By analyzing the relationship between price and volume, this indicator aims to assist traders in recognizing potential shifts in market sentiment and trend direction.
Features:
1. **Moving Average Analysis:**
- Utilizes a customizable moving average length to assess the overall trend direction.
2. **Volume Confirmation:**
- Incorporates volume analysis to confirm the strength of identified market phases.
3. **Visualization:**
- Clearly visualizes accumulation, distribution, markup, and markdown phases on the price chart using intuitive shapes.
Input Parameters:
- **Moving Average Length (default: 20):**
- Adjusts the length of the moving average for trend analysis.
- **Volume Multiplier (default: 1.5):**
- Sets the multiplier to customize the volume threshold for identifying significant market phases.
How to Use:
1. **Accumulation and Distribution:**
- Green triangles indicate potential accumulation phases when the closing price is above the moving average, and volume is higher than the specified threshold. Red triangles indicate potential distribution phases.
2. **Markup and Markdown:**
- Blue triangles suggest potential markup phases when the closing price is above the moving average, and volume is below the specified threshold. Orange triangles indicate potential markdown phases.
Important Notes:
- This indicator is a tool for analysis and should be used in conjunction with other technical analysis methods.
- Parameters can be adjusted based on the specific characteristics of the asset being analyzed.
Disclaimer:
Trading involves risk, and no indicator can guarantee profits. Users should exercise caution, conduct thorough research, and consider risk management principles when making trading decisions.
PA-Adaptive T3 Loxxer [Loxx]PA-Adaptive T3 Loxxer is a Loxxer indicator that is Phase Accumulation Cycle adaptive and uses T3 moving average for smoothing instead of the typical SMA or EMA . this allows for smoother signals by reducing noise.
What is Loxxer?
The Loxxer indicator is a technical analysis tool that compares the most recent maximum and minimum prices to the previous period's equivalent price to measure the demand of the underlying asset.
What is the Phase Accumulation Cycle?
The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio.
Included
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Divergences
[blackcat] L3 Banker Fund AttackLevel 3
Background
This indicator is used to capture the movement of the banker fund. The buying and selling point is determined according to whether the momentum of the banker fund and the price momentum resonate.
How to use the indicator:
The red column line indicates that the banker fund accumulation signal appears, and the following 2 conditions are all satisfied to buy; (both above the green line of the banker fund attack threshold)
1. The yellow line and the purple line all cross the red accumulation histogram signal;
2. The yellow and purple trend lines are up
Key point: If the yellow line crosses the green line of the banker fund attack threshold, it will be pulled up or the big market will open! The main thing is to see the red accumulation histogram signal, or the green line that crosses the banker fund attack threshold. If there is a red accumulation histogram signal, it means that there are main low-acquisition chips, and start trading on the left to open a position. The area above the green line of the banker fund attack threshold belongs to the main force pulling stage. When the green line of the banker fund attack threshold is not broken upwards, there is still a lot of profit space, but if it can be effectively broken through, it is highly profitable!
Remarks
This indicator only effective for instruments that contains banker fund. If there is no obvious large fund inside, the indicator is not as meaningful as it is called.
I verified it worked well for > 4H or 1D timeframe. For the other time frames, you may need to check and verify by yourself.
Feedbacks are appreciated.
PA-Adaptive Polynomial Regression Fitted Moving Average [Loxx]PA-Adaptive Polynomial Regression Fitted Moving Average is a moving average that is calculated using Polynomial Regression Analysis. The purpose of this indicator is to introduce polynomial fitting that is to be used in future indicators. This indicator also has Phase Accumulation adaptive period inputs. Even though this first indicator is for demonstration purposes only, its still one of the only viable implementations of Polynomial Regression Analysis on TradingView is suitable for trading, and while this same method can be used to project prices forward, I won't be doing that since forecasting is generally worthless and causes unavoidable repainting. This indicator only repaints on the current bar. Once the bar closes, any signal on that bar won't change.
For other similar Polynomial Regression Fitted methodologies, see here
Poly Cycle
What is the Phase Accumulation Cycle?
The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio.
What is Polynomial Regression?
In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modelled as an nth degree polynomial in x. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean of y, denoted E(y |x). Although polynomial regression fits a nonlinear model to the data, as a statistical estimation problem it is linear, in the sense that the regression function E(y | x) is linear in the unknown parameters that are estimated from the data. For this reason, polynomial regression is considered to be a special case of multiple linear regression.
Things to know
You can select from 33 source types
The source is smoothed before being injected into the Polynomial fitting algorithm, there are 35+ moving averages to choose from for smoothing
The output of the Polynomial fitting algorithm is then smoothed to create the signal, there are 35+ moving averages to choose from for smoothing
Included
Alerts
Signals
Bar coloring
PA-Adaptive TRIX Log [Loxx]PA-Adaptive TRIX Log is a Phase Accumulation Adaptive TRIX Log indicator. This adaptation smooths the signal to catch larger trends.
What is TRIX?
TRIX is a momentum oscillator that displays the percent rate of change of a TEMA . It was developed in the early 1980's by Jack Hutson, an editor for "Technical Analysis of Stocks and Commodities" magazine. With its triple smoothing, TRIX is designed to filter insignificant price movements. In his article he uses a logarithm of a price (which is in many versions, left out).
What is the Phase Accumulation Cycle?
The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio.
Included
Bar coloring
2 signal options
Alerts
Volume Indicators PackageCONTAINS 3 OF MY BEST VOLUME INDICATORS ALL FOR THE PRICE OF ONE!
CONTAINS:
Average Dollar Volume in RED
Up/Down Volume Ratio in Green
Volume Buzz/Volume Run Rate in BLUE
If you would like to get these individually, I also have scripts for that too.
Below is information about all three of these indicators, what they do, and why they are important.
---------------------------------------------------------------------------------------------AVERAGE DOLLAR VOLUME----------------------------------------------------------------------------------------
Dollar volume is simply the volume traded multiplied times the cost of the stock.
Dollar volume is an extremely important metric for finding stocks with enough liquidity for market makers to position themselves in. Market Liquidity is defined as market's feature whereby an individual or firm can quickly purchase or sell an asset without causing a drastic change in the asset's price. The key concept you want to understand is that these big instructions with billions of dollars need liquidity in a stock in order to even think about buying it, and therefore these institutions will demand a large dollar volume . A good dollar volume amount, that represents a pretty liquid name, is typically above 100 million $ average. Why are institutions important? Simple because they are the ones who make stocks move, and I mean really move. If you want to see large growth from a stock in a short amount of time, you need institutions wielding billions of dollars to be fighting one another to buy more shares. Institutions are the ones who make or break a stock, this is why we call them market makers.
My script calculates average dollar volume using four averages: the 50, the 30, the 20, and the 10 period. I use multiple averages in order to provide the accurate and up to date information to you. It then selects the minimum of these averages and divides this value by 1 million and displays this number to you.
TL;DR? If you want monster moves from your stocks, you need to pick names with average high liquidity(dollar volume >= $100 million). The number presented to you is in millions of whatever currency the name is traded in.
---------------------------------------------------------------------------------------------UP/DOWN VOLUME RATIO-----------------------------------------------------------------------------------------
Up/Down Volume Ratio is calculated by summing volume on days when it closes up and divide that total by the volume on days when the stock closed down.
High volume up days are typically a sign of accumulation(buying) by big players, while down days are signs of distribution(selling) by big market players. The Up Down volume ratio takes this assumption and turns it into a tangible number that's easier for the trader to understand. My formula is calculated using the past 50 periods, be warned it will not display a value for stocks with under 50 periods of trading history. This indicator is great for identify accumulation of growth stocks early on in their moves, most of the time you would like a growth stocks U/D value to be above 2, showing institutional sponsorship of a stock.
Up/Down Volume value interpretation:
U/D < 1 -> Bearish outlook, as sellers are in control
U/D = 1 -> Sellers and Buyers are equal
U/D > 1 -> Bullish outlook, as buyers are in control
U/D > 2 -> Bullish outlook, significant accumulation underway by market makers
U/D >= 3 -> MONSTER STOCK ALERT, market makers can not get enough of this stock and are ravenous to buy more
U/D values greater than 2 are rare and typically do not last very long, and U/D >= 3 are extremely rare one example I kind find of a stock's U/D peaking above 3 was Google back in 2005.
-----------------------------------------------------------------------------------------------------VOLUME BUZZ-----------------------------------------------------------------------------------------------
Volume Buzz/ Volume Run Rate as seen on TC2000 and MarketSmith respectively.
Basically, the volume buzz tells you what percentage over average(100 time period moving average) the volume traded was. You can use this indicator to more readily identify above-average trading volume and accumulation days on charts. The percentage will show up in the top left corner, make sure to click the settings button and uncheck the second box(left of plot) in order to get rid of the chart line.
Dynamic Money FlowDynamic Money Flow is a volume indicator based on Marc Chaikin's Money Flow with a few improvements.
It can be used to confirm break-outs and trends.
Zero line crosses and divergences can provide useful signals while considering chart analysis as well.
Two weaknesses of CMF have been already fixed by Colin Twiggs (IncredibleCharts)...
1.CMF uses Chaikin's accumulation/distribution line to calculate the flow of money.
Accumulation/distribution line does not take the gaps into account. This can be solved using true range.
I call it true accumulation/distribution.
2.Oscillators have a tendency to center because of averaging calculations.
DMF is average of flowing volume divided by average of total volume. This means indicator plots the change of first factor compared to the other one. In Simple Averaging method every data is given an equal weight thus when the last data drops it will have heavy impact on the averages and the change of them.
It is much easier to identity these impacts after the drop of very high or very low data... So reducing the weight exponentially is a better option.
3.There is something else with CMF... changes of close price is ignored, because the formula only compares close price to its range.
To include the movements of close beside the close to range comparison, the distance between two last close prices should be compared to true range as well.
So volume can be distributed between close to range comparison (True Accumulation/Distribution) and close to close comparison automatically. And then results are summed to have a single multiplier.
An example for how close to close comparison affects DMF...
Or here you can see how lower wicks keep TMF (same as CMF in this case) from crossing zero line while price is trending down.
Fractal Market Geometry [JOAT]
Fractal Market Geometry
Overview
Fractal Market Geometry is an open-source overlay indicator that combines fractal analysis with harmonic pattern detection, Fibonacci retracements and extensions, Elliott Wave concepts, and Wyckoff phase identification. It provides traders with a geometric framework for understanding market structure and identifying potential reversal patterns with multi-factor signal confirmation.
What This Indicator Does
The indicator calculates and displays:
Fractal Detection - Identifies fractal highs and lows using Williams-style pivot analysis with configurable period
Fractal Dimension - Calculates market complexity using range-based dimension estimation
Harmonic Patterns - Detects Gartley, Butterfly, Bat, Crab, Shark, Cypher, and ABCD patterns using Fibonacci ratios
Fibonacci Retracements - Key levels at 38.2%, 50%, and 61.8%
Fibonacci Extensions - Projection level at 161.8%
Elliott Wave Count - Simplified wave counting based on pivot detection (1-5)
Wyckoff Phase - Volume-based phase identification (Accumulation, Markup, Distribution, Neutral)
Golden Spiral Levels - ATR-based support and resistance levels using phi (1.618) ratio
Trend Detection - EMA crossover trend identification (20/50 EMA)
How It Works
Fractal detection uses a configurable period to identify swing points:
detectFractalHigh(simple int period) =>
bool result = true
float centerVal = high
for i = 0 to period - 1
if high >= centerVal or high >= centerVal
result := false
break
Harmonic pattern detection uses Fibonacci ratio analysis between swing points. Each pattern has specific ratio requirements:
Gartley: AB 0.382-0.618, BC 0.382-0.886, CD 1.27-1.618
Butterfly: AB 0.382-0.5, BC 0.382-0.886, CD 1.618-2.24
Bat: AB 0.5-0.618, BC 1.13-1.618, CD 1.618-2.24
Crab: AB 0.382-0.618, BC 0.382-0.886, CD 2.24-3.618
Shark: AB 0.382-0.618, BC 1.13-1.618, CD 1.618-2.24
Cypher: AB 0.382-0.618, BC 1.13-1.414, CD 0.786-0.886
Wyckoff phase detection analyzes volume relative to price movement:
wyckoffPhase(simple int period) =>
float avgVol = ta.sma(volume, period)
float priceChg = ta.change(close, period)
string phase = "NEUTRAL"
if volume > avgVol * 1.5 and math.abs(priceChg) < close * 0.02
phase := "ACCUMULATION"
else if volume > avgVol * 1.5 and math.abs(priceChg) > close * 0.05
phase := "MARKUP"
else if volume < avgVol * 0.7
phase := "DISTRIBUTION"
phase
Signal Generation
Signals use multi-factor confirmation for accuracy:
BUY Signal: Fractal low + Uptrend (EMA20 > EMA50) + RSI 30-55 + Bullish candle + Volume confirmation
SELL Signal: Fractal high + Downtrend (EMA20 < EMA50) + RSI 45-70 + Bearish candle + Volume confirmation
Pattern Detection: Label appears when harmonic pattern completes at current bar
Dashboard Panel (Top-Right)
Dimension - Fractal dimension value (market complexity measure)
Last High - Most recent fractal high price
Last Low - Most recent fractal low price
Pattern - Current harmonic pattern name or NONE
Elliott Wave - Current wave count (Wave 1-5) or OFF
Wyckoff - Current market phase or OFF
Trend - BULLISH, BEARISH, or NEUTRAL based on EMA crossover
Signal - BUY, SELL, or WAIT status
Visual Elements
Fractal Markers - Small triangles at fractal highs (down arrow) and lows (up arrow)
Geometry Lines - Dashed lines connecting the most recent fractal high and low
Fibonacci Levels - Clean horizontal lines at 38.2%, 50%, and 61.8% retracement levels
Fibonacci Extension - Horizontal line at 161.8% extension level
Golden Spiral Levels - Support and resistance lines based on ATR x 1.618
3D Fractal Field - Optional depth layers around swing levels (OFF by default)
Harmonic Pattern Markers - Small diamond shapes when Crab, Shark, or Cypher patterns detected
Pattern Labels - Text label showing pattern name when detected
Signal Labels - BUY/SELL labels on confirmed multi-factor signals
Input Parameters
Fractal Period (default: 5) - Bars on each side for fractal detection
Geometry Depth (default: 3) - Complexity of geometric calculations
Pattern Sensitivity (default: 0.8) - Tolerance for pattern ratio matching
Show Fibonacci Levels (default: true) - Display retracement levels
Show Fibonacci Extensions (default: true) - Display extension level
Elliott Wave Detection (default: true) - Enable wave counting
Wyckoff Analysis (default: true) - Enable phase detection
Golden Spiral Levels (default: true) - Display spiral support/resistance
Show Fractal Points (default: true) - Display fractal markers
Show Geometry Lines (default: true) - Display connecting lines
Show Pattern Labels (default: true) - Display pattern name labels
Show 3D Fractal Field (default: false) - Display depth layers
Show Harmonic Patterns (default: true) - Display pattern markers
Show Buy/Sell Signals (default: true) - Display signal labels
Suggested Use Cases
Identify potential reversal zones using harmonic pattern completion
Use Fibonacci levels for entry, stop-loss, and target planning
Monitor Wyckoff phases for accumulation/distribution awareness
Track Elliott Wave counts for trend structure analysis
Use fractal dimension to gauge market complexity
Wait for multi-factor signal confirmation before entering trades
Timeframe Recommendations
Best on 1H to Daily charts. Lower timeframes produce more fractals but with less significance. Higher timeframes provide stronger levels and more reliable signals.
Limitations
Harmonic pattern detection uses simplified ratio ranges and may not match all textbook definitions
Elliott Wave counting is basic and does not include all wave rules
Wyckoff phase detection is volume-based approximation
Fractal dimension calculation is simplified
Signals require fractal confirmation which has inherent lag equal to the fractal period
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Harmonic Liquidity Waves [JOAT]Harmonic Liquidity Waves
Overview
Harmonic Liquidity Waves is an open-source oscillator indicator that combines multiple volume-based analysis techniques into a unified liquidity flow framework. It integrates VWAP calculations, Chaikin Money Flow (CMF), Money Flow Index (MFI), and Klinger Volume Oscillator (KVO) with custom harmonic wave calculations to provide a comprehensive view of volume dynamics and money flow.
What This Indicator Does
The indicator calculates and displays:
Liquidity Flow - Volume-weighted price movement accumulated over a lookback period
Harmonic Wave - Multi-depth smoothed oscillator derived from liquidity flow
Chaikin Money Flow (CMF) - Classic accumulation/distribution indicator
Money Flow Index (MFI) - Volume-weighted RSI showing buying/selling pressure
Klinger Volume Oscillator (KVO) - Trend-volume relationship indicator
Wave Interference - Combined constructive/destructive wave patterns
Volume Profile POC - Point of Control from simplified volume distribution
How It Works
The core liquidity flow calculation tracks volume-weighted price changes:
calculateLiquidityFlow(series float vol, series float price, simple int period) =>
float priceChange = ta.change(price)
float volumeFlow = vol * math.sign(priceChange)
// Accumulated over period using buffer array
float avgFlow = flowSum / period
avgFlow
The harmonic oscillator applies multi-depth smoothing:
harmonicOscillator(series float flow, simple int depth, simple int period) =>
float harmonic = 0.0
for i = 1 to depth
float wave = ta.ema(flow, period * i) / i
harmonic += wave
harmonic / depth
CMF measures accumulation/distribution using the Money Flow Multiplier:
float mfm = ((close - low) - (high - close)) / (high - low)
float mfv = mfm * vol
float cmf = ta.sum(mfv, period) / ta.sum(vol, period) * 100
Signal Generation
Liquidity shift signals occur when:
Bullish Shift: Smoothed wave crosses above signal line
Bearish Shift: Smoothed wave crosses below signal line
Strong signals require volume indicator confirmation:
Strong Bull: Bullish shift + CMF > 0 + MFI > 50 + KVO > 0
Strong Bear: Bearish shift + CMF < 0 + MFI < 50 + KVO < 0
Divergence detection compares price pivots with liquidity wave pivots to identify potential reversals.
Dashboard Panel (Bottom-Right)
Wave Strength - Normalized wave magnitude
Volume Pressure - Current volume vs average percentage
Flow Direction - BUYING or SELLING based on wave sign
Histogram - Wave minus signal line value
CMF - Chaikin Money Flow reading
MFI - Money Flow Index value (0-100)
KVO - Klinger oscillator value
Vol Confluence - Combined volume indicator score
Signal - Current actionable status
Visual Elements
Liquidity Wave - Main oscillator line
Wave Signal - Smoothed signal line for crossover detection
Wave Histogram - Difference between wave and signal
Wave Interference - Area plot showing combined wave patterns
CMF/KVO/MFI Lines - Individual volume indicator plots
Divergence Labels - BULL DIV / BEAR DIV markers
Shift Markers - Triangles for basic shifts, labels for strong shifts
Input Parameters
Wave Period (default: 21) - Base period for liquidity calculations
Volume Weight (default: 1.5) - Multiplier for volume emphasis
Harmonic Depth (default: 3) - Number of smoothing layers
Smoothing (default: 3) - Final wave smoothing period
Suggested Use Cases
Identify accumulation/distribution phases using CMF and wave direction
Confirm momentum with MFI overbought/oversold readings
Watch for divergences between price and liquidity flow
Use strong signals when multiple volume indicators align
Timeframe Recommendations
Best on 15m to Daily charts. Volume-based indicators require sufficient trading activity for meaningful readings.
Limitations
Volume data quality varies by exchange and instrument
Divergence detection uses pivot-based lookback and may lag
Volume Profile POC is simplified and not a full profile analysis
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Ultimate MACD [captainua]Ultimate MACD - Comprehensive MACD Trading System
Overview
This indicator combines traditional MACD calculations with advanced features including divergence detection, volume analysis, histogram analysis tools, regression forecasting, strong top/bottom detection, and multi-timeframe confirmation to provide a comprehensive MACD-based trading system. The script calculates MACD using configurable moving average types (EMA, SMA, RMA, WMA) and applies various smoothing methods to reduce noise while maintaining responsiveness. The combination of these features creates a multi-layered confirmation system that reduces false signals by requiring alignment across multiple indicators and timeframes.
Core Calculations
MACD Calculation:
The script calculates MACD using the standard formula: MACD Line = Fast MA - Slow MA, Signal Line = Moving Average of MACD Line, Histogram = MACD Line - Signal Line. The default parameters are Fast=12, Slow=26, Signal=9, matching the traditional MACD settings. The script supports four moving average types:
- EMA (Exponential Moving Average): Standard and most responsive, default choice
- SMA (Simple Moving Average): Equal weight to all periods
- RMA (Wilder's Moving Average): Smoother, less responsive
- WMA (Weighted Moving Average): Recent prices weighted more heavily
The price source can be configured as Close (standard), Open, High, Low, HL2, HLC3, or OHLC4. Alternative sources provide different sensitivity characteristics for various trading strategies.
Configuration Presets:
The script includes trading style presets that automatically configure MACD parameters:
- Scalping: Fast/Responsive settings (8,18,6 with minimal smoothing)
- Day Trading: Balanced settings (10,22,7 with minimal smoothing)
- Swing Trading: Standard settings (12,26,9 with moderate smoothing)
- Position Trading: Smooth/Conservative settings (15,35,12 with higher smoothing)
- Custom: Full manual control over all parameters
Histogram Smoothing:
The histogram can be smoothed using EMA to reduce noise and filter minor fluctuations. Smoothing length of 1 = raw histogram (no smoothing), higher values (3-5) = smoother histogram. Increased smoothing reduces noise but may delay signals slightly.
Percentage Mode:
MACD values can be converted to percentage of price (MACD/Close*100) for cross-instrument comparison. This is useful when comparing MACD signals across instruments with different price levels (e.g., BTC vs ETH). The percentage mode normalizes MACD values, making them comparable regardless of instrument price.
MACD Scale Factor:
A scale factor multiplier (default 1.0) allows adjusting MACD display size for better visibility. Use 0.3-0.5 if MACD appears too compressed, or 2.0-3.0 if too small.
Dynamic Overbought/Oversold Levels:
Overbought and oversold levels are calculated dynamically based on MACD's mean and standard deviation over a lookback period. The formula: OB = MACD Mean + (StdDev × OB Multiplier), OS = MACD Mean - (StdDev × OS Multiplier). This adapts to current market conditions, widening in volatile markets and narrowing in calm markets. The lookback period (default 20) controls how quickly the levels adapt: longer periods (30-50) = more stable levels, shorter (10-15) = more responsive.
OB/OS Background Coloring:
Optional background coloring can highlight the entire panel when MACD enters overbought or oversold territory, providing prominent visual indication of extreme conditions. The background colors are drawn on top of the main background to ensure visibility.
Divergence Detection
Regular Divergence:
The script uses the MACD line (not histogram) for divergence detection, which provides more reliable signals. Bullish divergence: Price makes a lower low while MACD line makes a higher low. Bearish divergence: Price makes a higher high while MACD line makes a lower high. Divergences often precede reversals and are powerful reversal signals.
Pivot-Based Divergence:
The divergence detection uses actual pivot points (pivotlow/pivothigh) instead of simple lowest/highest comparisons. This provides more accurate divergence detection by identifying significant pivot lows/highs in both price and MACD line. The pivot-based method compares two recent pivot points: for bullish divergence, price makes a lower low while MACD makes a higher low at the pivot points. This method reduces false divergences by requiring actual pivot points rather than just any low/high within a period.
The pivot lookback parameters (left and right) control how many bars on each side of a pivot are required for confirmation. Higher values = more conservative pivot detection.
Hidden Divergence:
Continuation patterns that signal trend continuation rather than reversal. Bullish hidden divergence: Price makes a higher low but MACD makes a lower low. Bearish hidden divergence: Price makes a lower high but MACD makes a higher high. These patterns indicate the trend is likely to continue in the current direction.
Zero-Line Filter:
The "Don't Touch Zero Line" option ensures divergences occur in proper context: for bullish divergence, MACD must stay below zero; for bearish divergence, MACD must stay above zero. This filters out divergences that occur in neutral zones.
Range Filtering:
Minimum and maximum lookback ranges control the time window between pivots to consider for divergence. This helps filter out divergences that are too close together (noise) or too far apart (less relevant).
Volume Confirmation System
Volume threshold filtering requires current volume to exceed the volume SMA multiplied by the threshold factor. The formula: Volume Confirmed = Volume > (Volume SMA × Threshold). If the threshold is set to 1.0 or lower, volume confirmation is effectively disabled (always returns true). This allows you to use the indicator without volume filtering if desired. Volume confirmation significantly increases divergence and signal reliability.
Volume Climax and Dry-Up Detection:
The script can mark bars with extremely high volume (volume climax) or extremely low volume (volume dry-up). Volume climax indicates potential reversal points or strong momentum continuation. Volume dry-up indicates low participation and may produce unreliable signals. These markers use standard deviation multipliers to identify extreme volume conditions.
Zero-Line Cross Detection
MACD zero-line crosses indicate momentum shifts: above zero = bullish momentum, below zero = bearish momentum. The script includes alert conditions for zero-line crosses with cooldown protection to prevent alert spam. Zero-line crosses can provide early warning signals before MACD crosses the signal line.
Histogram Analysis Tools
Histogram Moving Average:
A moving average applied to the histogram itself helps identify histogram trend direction and acts as a signal line for histogram movements. Supports EMA, SMA, RMA, and WMA types. Useful for identifying when histogram momentum is strengthening or weakening.
Histogram Bollinger Bands:
Bollinger Bands are applied to the MACD histogram instead of price. The calculation: Basis = SMA(Histogram, Period), StdDev = stdev(Histogram, Period), Upper = Basis + (StdDev × Deviation Multiplier), Lower = Basis - (StdDev × Deviation Multiplier). This creates dynamic zones around the histogram that adapt to histogram volatility. When the histogram touches or exceeds the bands, it indicates extreme conditions relative to recent histogram behavior.
Stochastic MACD (StochMACD):
Stochastic MACD applies the Stochastic oscillator formula to the MACD histogram instead of price. This normalizes the histogram to a 0-100 scale, making it easier to identify overbought/oversold conditions on the histogram itself. The calculation: %K = ((Histogram - Lowest Histogram) / (Highest Histogram - Lowest Histogram)) × 100. %K is smoothed, and %D is calculated as the moving average of smoothed %K. Standard thresholds are 80 (overbought) and 20 (oversold).
Regression Forecasting
The script includes advanced regression forecasting that predicts future MACD values using mathematical models. This helps anticipate potential MACD movements and provides forward-looking context for trading decisions.
Regression Types:
- Linear: Simple trend line (y = mx + b) - fastest, works well for steady trends
- Polynomial: Quadratic curve (y = ax² + bx + c) - captures curvature in MACD movement
- Exponential Smoothing: Weighted average with more weight on recent values - responsive to recent changes
- Moving Average: Uses difference between short and long MA to estimate trend - stable and smooth
Forecast Horizon:
Number of bars to forecast ahead (default 5, max 50 for linear/MA, max 20 for polynomial due to performance). Longer horizons predict further ahead but may be less accurate.
Confidence Bands:
Optional upper/lower bands around forecast show prediction uncertainty based on forecast error (standard deviation of prediction vs actual). Wider bands = higher uncertainty. The confidence level multiplier (default 1.5) controls band width.
Forecast Display:
Forecast appears as dotted lines extending forward from current bar, with optional confidence bands. All forecast values respect percentage mode and scale factor settings.
Strong Top/Bottom Signals
The script detects strong recovery from extreme MACD levels, generating "sBottom" and "sTop" signals. These identify significant reversal potential when MACD recovers substantially from overbought/oversold extremes.
Strong Bottom (sBottom):
Triggered when:
1. MACD was at or near its lowest point in the bottom period (default 10 bars)
2. MACD was in or near the oversold zone
3. MACD has recovered by at least the threshold amount (default 0.5) from the lowest point
4. Recovery persists for confirmation bars (default 2 consecutive bars)
5. MACD has moved out of the oversold zone
6. Volume is above average
7. All enabled filters pass
8. Minimum bars have passed since last signal (reset period, default 5 bars)
Strong Top (sTop):
Triggered when:
1. MACD was at or near its highest point in the top period (default 7 bars)
2. MACD was in or near the overbought zone
3. MACD has declined by at least the threshold amount (default 0.5) from the highest point
4. Decline persists for confirmation bars (default 2 consecutive bars)
5. MACD has moved out of the overbought zone
6. Volume is above average
7. All enabled filters pass
8. Minimum bars have passed since last signal (reset period, default 5 bars)
Label Placement:
sTop/sBottom labels appear on the historical bar where the actual extreme occurred (not on current bar), showing the exact MACD value at that extreme. Labels respect the unified distance checking system to prevent overlaps with Buy/Sell Strength labels.
Signal Strength Calculation
The script calculates a composite signal strength score (0-100) based on multiple factors:
- MACD distance from signal line (0-50 points): Larger separation indicates stronger signal
- Volume confirmation (0-15 points): Volume above average adds points
- Secondary timeframe alignment (0-15 points): Higher timeframe agreement adds points
- Distance from zero line (0-20 points): Closer to zero can indicate stronger reversal potential
Higher scores (70+) indicate stronger, more reliable signals. The signal strength is displayed in the statistics table and can be used as a filter to only accept signals above a threshold.
Smart Label Placement System
The script includes an advanced label placement system that tracks MACD extremes and places Buy/Sell Strength labels at optimal locations:
Label Placement Algorithm:
- Labels appear on the current bar at confirmation (not on historical extreme bars), ensuring they're visible when the signal is confirmed
- The system tracks pending signals when MACD enters OB/OS zones or crosses the signal line
- During tracking, the system continuously searches for the true extreme (lowest MACD for buys, highest MACD for sells) within a configurable historical lookback period
- Labels are only finalized when: (1) MACD exits the OB/OS zone, (2) sufficient bars have passed (2x minimum distance), (3) MACD has recovered/declined by a configurable percentage from the extreme (default 15%), and (4) tracking has stopped (no better extreme found)
Label Spacing and Overlap Prevention:
- Minimum Bars Between Labels: Base distance requirement (default 5 bars)
- Label Spacing Multiplier: Scales the base distance (default 1.5x) for better distribution. Higher values = more spacing between labels
- Effective distance = Base Distance × Spacing Multiplier (e.g., 5 × 1.5 = 7.5 bars minimum)
- Unified distance checking prevents overlaps between all label types (Buy Strength, Sell Strength, sTop, sBottom)
Strength-Based Filtering:
- Label Strength Minimum (%): Only labels with strength at or above this threshold are displayed (default 75%)
- When multiple potential labels are close together, the system automatically compares strengths and keeps only the strongest one
- This ensures only the most significant signals are displayed, reducing chart clutter
Zero Line Polarity Enforcement:
- Enforce Zero Line Polarity (default enabled): Ensures labels follow traditional MACD interpretation
- Buy Strength labels only appear when the tracked extreme MACD value was below zero (negative territory)
- Sell Strength labels only appear when the tracked extreme MACD value was above zero (positive territory)
- This prevents counter-intuitive labels (e.g., Buy labels above zero line) and aligns with standard MACD trading principles
Recovery/Decline Confirmation:
- Recovery/Decline Confirm (%): Percent move away from the extreme required before finalizing (default 15%)
- For Buy labels: MACD must recover by at least this percentage from the tracked bottom
- For Sell labels: MACD must decline by at least this percentage from the tracked top
- Higher values = more confirmation required, fewer but more reliable labels
Historical Lookback:
- Historical Lookback for Label Placement: Number of bars to search for true extremes (default 20)
- The system searches within this period to find the actual lowest/highest MACD value
- Higher values analyze more history but may be slower; lower values are faster but may miss some extremes
Cross Quality Score
The script calculates a MACD cross quality score (0-100) that rates crossover quality based on:
- Cross angle (0-50 points): Steeper crosses = stronger signals
- Volume confirmation (0-25 points): Volume above average adds points
- Distance from zero line (0-25 points): Crosses near zero line are stronger
This score helps identify high-quality crossovers and can be used as a filter to only accept signals meeting minimum quality threshold.
Filtering System
Histogram Filter:
Requires histogram to be above zero for buy signals, below zero for sell signals. Ensures momentum alignment before generating signals.
Signal Strength Filter:
Requires minimum signal strength score for signals. Higher threshold = only strongest signals pass. This combines multiple confirmation factors into a single filter.
Cross Quality Filter:
Requires minimum cross quality score for signals. Rates crossover quality based on angle, volume, momentum, and distance from zero. Only signals meeting minimum quality threshold will be generated.
All filters use the pattern: filterResult = not filterEnabled OR conditionMet. This means if a filter is disabled, it always passes (returns true). Filters can be combined, and all must pass for a signal to fire.
Multi-Timeframe Analysis
The script can display MACD from a secondary (higher) timeframe and use it for confirmation. When secondary timeframe confirmation is enabled, signals require the higher timeframe MACD to align (bullish/bearish) with the signal direction. This ensures signals align with the larger trend context, reducing counter-trend trades.
Secondary Timeframe MACD:
The secondary timeframe MACD uses the same calculation parameters (fast, slow, signal, MA type) as the main MACD but from a higher timeframe. This provides context for the current timeframe's MACD position relative to the larger trend. The secondary MACD lines are displayed on the chart when enabled.
Noise Filtering
Noise filtering hides small histogram movements below a threshold. This helps focus on significant moves and reduces chart clutter. When enabled, only histogram movements above the threshold are displayed. Typical threshold values are 0.1-0.5 for most instruments, depending on the instrument's price range and volatility.
Signal Debounce
Signal debounce prevents duplicate MACD cross signals within a short time period. Useful when MACD crosses back and forth quickly, creating multiple signals. Debounce ensures only one signal per period, reducing signal spam during choppy markets. This is separate from alert cooldown, which applies to all alert types.
Background Color Modes
The script offers three background color modes:
- Dynamic: Full MACD heatmap based on OB/OS conditions, confidence, and momentum. Provides rich visual feedback.
- Monotone: Soft neutral background but still allows overlays (OB/OS zones). Keeps the chart clean without overpowering candles.
- Off: No MACD background (only overlays and plots). Maximum chart cleanliness.
When OB/OS background colors are enabled, they are drawn on top of the main background to ensure visibility.
Statistics Table
A real-time statistics table displays current MACD values, signal strength, distance from zero line, secondary timeframe alignment, volume confirmation status, and all active filter statuses. The table dynamically adjusts to show only enabled features, keeping it clean and relevant. The table position can be configured (Top Left, Top Right, Bottom Left, Bottom Right).
Performance Statistics Table
An optional performance statistics table shows comprehensive filter diagnostics:
- Total buy/sell signals (raw crossover count before filters)
- Filtered buy/sell signals (signals that passed all filters)
- Overall pass rates (percentage of signals that passed filters)
- Rejected signals count
- Filter-by-filter rejection diagnostics showing which filters rejected how many signals
This table helps optimize filter settings by showing which filters are most restrictive and how they impact signal frequency. The diagnostics format shows rejections as "X B / Y S" (X buy signals rejected, Y sell signals rejected) or "Disabled" if the filter is not active.
Alert System
The script includes separate alert conditions for each signal type:
- MACD Cross: MACD line crosses above/below Signal line (with or without secondary confirmation)
- Zero-Line Cross: MACD crosses above/below zero
- Divergence: Regular and hidden divergence detections
- Secondary Timeframe: Higher timeframe MACD crosses
- Histogram MA Cross: Histogram crosses above/below its moving average
- Histogram Zero Cross: Histogram crosses above/below zero
- StochMACD: StochMACD overbought/oversold entries and %K/%D crosses
- Histogram BB: Histogram touches/breaks Bollinger Bands
- Volume Events: Volume climax and dry-up detections
- OB/OS: MACD entry/exit from overbought/oversold zones
- Strong Top/Bottom: sTop and sBottom signal detections
Each alert type has its own cooldown system to prevent alert spam. The cooldown requires a minimum number of bars between alerts of the same type, reducing duplicate alerts during volatile periods. Alert types can be filtered to only evaluate specific alert types (All, MACD Cross, Zero Line, Divergence, Secondary Timeframe, Histogram MA, Histogram Zero, StochMACD, Histogram BB, Volume Events, OB/OS, Strong Top/Bottom).
How Components Work Together
MACD crossovers provide the primary signal when the MACD line crosses the Signal line. Zero-line crosses indicate momentum shifts and can provide early warning signals. Divergences identify potential reversals before they occur.
Volume confirmation ensures signals occur with sufficient market participation, filtering out low-volume false breakouts. Histogram analysis tools (MA, Bollinger Bands, StochMACD) provide additional context for signal reliability and identify significant histogram zones.
Signal strength combines multiple confirmation factors into a single score, making it easy to filter for only the strongest signals. Cross quality score rates crossover quality to identify high-quality setups. Multi-timeframe confirmation ensures signals align with higher timeframe trends, reducing counter-trend trades.
Usage Instructions
Getting Started:
The default configuration shows MACD(12,26,9) with standard EMA calculations. Start with default settings and observe behavior, then customize settings to match your trading style. You can use configuration presets for quick setup based on your trading style.
Customizing MACD Parameters:
Adjust Fast Length (default 12), Slow Length (default 26), and Signal Length (default 9) based on your trading timeframe. Shorter periods (8,17,7) for faster signals, longer (15,30,12) for smoother signals. You can change the moving average type: EMA for responsiveness, RMA for smoothness, WMA for recent price emphasis.
Price Source Selection:
Choose Close (standard), or alternative sources (HL2, HLC3, OHLC4) for different sensitivity. HL2 uses the midpoint of the high-low range, HLC3 and OHLC4 incorporate more price information.
Histogram Smoothing:
Set smoothing to 1 for raw histogram (no smoothing), or increase (3-5) for smoother histogram that reduces noise. Higher smoothing reduces false signals but may delay signals slightly.
Percentage Mode:
Enable percentage mode when comparing MACD across instruments with different price levels. This normalizes MACD values, making them directly comparable.
Dynamic OB/OS Levels:
The dynamic thresholds automatically adapt to volatility. Adjust the multipliers (default 1.5) to fine-tune sensitivity: higher values (2.0-3.0) = more extreme thresholds (fewer signals), lower (1.0-1.5) = more frequent signals. Adjust the lookback period to control how quickly levels adapt. Enable OB/OS background colors for visual indication of extreme conditions.
Volume Confirmation:
Set volume threshold to 1.0 (default, effectively disabled) or higher (1.2-1.5) for standard confirmation. Higher values require more volume for confirmation. Set to 0.1 to completely disable volume filtering.
Filters:
Enable filters gradually to find your preferred balance. Start with histogram filter for basic momentum alignment, then add signal strength filter (threshold 50+) for moderate signals, then cross quality filter (threshold 50+) for high-quality crossovers. Combine filters for highest-quality signals but expect fewer signals.
Divergence:
Enable divergence detection and adjust pivot lookback parameters. Pivot-based divergence provides more accurate detection using actual pivot points. Hidden divergence is useful for trend-following strategies. Adjust range parameters to filter divergences by time window.
Zero-Line Crosses:
Zero-line cross alerts are automatically available when alerts are enabled. These provide early warning signals for momentum shifts.
Histogram Analysis Tools:
Enable Histogram Moving Average to see histogram trend direction. Enable Histogram Bollinger Bands to identify extreme histogram zones. Enable Stochastic MACD to normalize histogram to 0-100 scale for overbought/oversold identification.
Multi-Timeframe:
Enable secondary timeframe MACD to see higher timeframe context. Enable secondary confirmation to require higher timeframe alignment for signals.
Signal Strength:
Signal strength is automatically calculated and displayed in the statistics table. Use signal strength filter to only accept signals above a threshold (e.g., 50 for moderate, 70+ for strong signals only).
Smart Label Placement:
Configure label placement settings to control label appearance and quality:
- Label Strength Minimum (%): Set threshold (default 75%) to show only strong signals. Higher = fewer, stronger labels
- Label Spacing Multiplier: Adjust spacing (default 1.5x) for better distribution. Higher = more spacing between labels
- Recovery/Decline Confirm (%): Set confirmation requirement (default 15%). Higher = more confirmation, fewer labels
- Enforce Zero Line Polarity: Enable (default) to ensure Buy labels only appear when tracked extreme was below zero, Sell labels only when above zero
- Historical Lookback: Adjust search period (default 20 bars) for finding true extremes. Higher = more history analyzed
Cross Quality:
Cross quality score is automatically calculated for crossovers. Use cross quality filter to only accept high-quality crossovers (threshold 50+ for moderate, 70+ for high quality).
Alerts:
Set up alerts for your preferred signal types. Enable alert cooldown (default enabled, 5 bars) to prevent alert spam. Use alert type filter to only evaluate specific alert types (All, MACD Cross, Zero Line, Divergence, Secondary Timeframe, Histogram MA, Histogram Zero, StochMACD, Histogram BB, Volume Events, OB/OS, Strong Top/Bottom). Each signal type has its own alert condition, so you can be selective about which signals trigger alerts.
Visual Elements and Signal Markers
The script uses various visual markers to indicate signals and conditions:
- MACD Line: Green when above signal (bullish), red when below (bearish) if dynamic colors enabled. Optional black outline for enhanced visibility
- Signal Line: Orange line with optional black outline for enhanced visibility
- Histogram: Color-coded based on direction and momentum (green for bullish rising, lime for bullish falling, red for bearish falling, orange for bearish rising)
- Zero Line: Horizontal reference line at MACD = 0
- Fill to Zero: Green/red semi-transparent fill between MACD line and zero line showing bullish/bearish territory
- Fill Between OB/OS: Blue semi-transparent fill between overbought/oversold thresholds highlighting neutral zone
- OB/OS Background Colors: Background coloring when MACD enters overbought/oversold zones
- Background Colors: Dynamic or monotone backgrounds indicating MACD state, or custom chart background
- Divergence Labels: "🐂" for bullish, "🐻" for bearish, "H Bull" for hidden bullish, "H Bear" for hidden bearish
- Divergence Lines: Colored lines connecting pivot points when divergences are detected
- Volume Climax Markers: ⚡ symbol for extremely high volume
- Volume Dry-Up Markers: 💧 symbol for extremely low volume
- Buy/Sell Strength Labels: Show signal strength percentage (e.g., "Buy Strength: 75%")
- Strong Top/Bottom Labels: "sTop" and "sBottom" for extreme level recoveries
- Secondary MACD Lines: Purple lines showing higher timeframe MACD
- Histogram MA: Orange line showing histogram moving average
- Histogram BB: Blue bands around histogram showing extreme zones
- StochMACD Lines: %K and %D lines with overbought/oversold thresholds
- Regression Forecast: Dotted blue lines extending forward with optional confidence bands
Signal Priority and Interpretation
Signals are generated independently and can occur simultaneously. Higher-priority signals generally indicate stronger setups:
1. MACD Cross with Multiple Filters - Highest priority: Requires MACD crossover plus all enabled filters (histogram, signal strength, cross quality) and secondary timeframe confirmation if enabled. These are the most reliable signals.
2. Zero-Line Cross - High priority: Indicates momentum shift. Can provide early warning signals before MACD crosses the signal line.
3. Divergence Signals - Medium-High priority: Pivot-based divergence is more reliable than simple divergence. Hidden divergence indicates continuation rather than reversal.
4. MACD Cross with Basic Filters - Medium priority: MACD crosses signal line with basic histogram filter. Less reliable alone but useful when combined with other confirmations.
Best practice: Wait for multiple confirmations. For example, a MACD crossover combined with divergence, volume confirmation, and secondary timeframe alignment provides the strongest setup.
Chart Requirements
For proper script functionality and compliance with TradingView requirements, ensure your chart displays:
- Symbol name: The trading pair or instrument name should be visible
- Timeframe: The chart timeframe should be clearly displayed
- Script name: "Ultimate MACD " should be visible in the indicator title
These elements help traders understand what they're viewing and ensure proper script identification. The script automatically includes this information in the indicator title and chart labels.
Performance Considerations
The script is optimized for performance:
- Calculations use efficient Pine Script functions (ta.ema, ta.sma, etc.) which are optimized by TradingView
- Conditional execution: Features only calculate when enabled
- Label management: Old labels are automatically deleted to prevent accumulation
- Array management: Divergence label arrays are limited to prevent memory accumulation
The script should perform well on all timeframes. On very long historical data with many enabled features, performance may be slightly slower, but it remains usable.
Known Limitations and Considerations
- Dynamic OB/OS levels can vary significantly based on recent MACD volatility. In very volatile markets, levels may be wider; in calm markets, they may be narrower.
- Volume confirmation requires sufficient historical volume data. On new instruments or very short timeframes, volume calculations may be less reliable.
- Higher timeframe MACD uses request.security() which may have slight delays on some data feeds.
- Stochastic MACD requires the histogram to have sufficient history. Very short periods on new charts may produce less reliable StochMACD values initially.
- Divergence detection requires sufficient historical data to identify pivot points. Very short lookback periods may produce false positives.
Practical Use Cases
The indicator can be configured for different trading styles and timeframes:
Swing Trading:
Use MACD(12,26,9) with secondary timeframe confirmation. Enable divergence detection. Use signal strength filter (threshold 50+) and cross quality filter (threshold 50+) for higher-quality signals. Enable histogram analysis tools for additional context.
Day Trading:
Use MACD(8,17,7) or use "Day Trading" preset with minimal histogram smoothing for faster signals. Enable zero-line cross alerts for early signals. Use volume confirmation with threshold 1.2-1.5. Enable histogram MA for momentum tracking.
Trend Following:
Use MACD(12,26,9) or longer periods (15,30,12) for smoother signals. Enable secondary timeframe confirmation for trend alignment. Hidden divergence signals are useful for trend continuation entries. Use cross quality filter to identify high-quality crossovers.
Reversal Trading:
Focus on divergence detection (pivot-based for accuracy) combined with zero-line crosses. Enable volume confirmation. Use histogram Bollinger Bands to identify extreme histogram zones. Enable StochMACD for overbought/oversold identification.
Multi-Timeframe Analysis:
Enable secondary timeframe MACD to see context from larger timeframes. For example, use daily MACD on hourly charts to understand the larger trend context. Enable secondary confirmation to require higher timeframe alignment for signals.
Practical Tips and Best Practices
Getting Started:
Start with default settings and observe MACD behavior. The default configuration (MACD 12,26,9 with EMA) is balanced and works well across different markets. After observing behavior, customize settings to match your trading style. Consider using configuration presets for quick setup.
Reducing Repainting:
All signals are based on confirmed bars, minimizing repainting. The script uses confirmed bar data for all calculations to ensure backtesting accuracy.
Signal Quality:
MACD crosses with multiple filters provide the highest-quality signals because they require alignment across multiple indicators. These signals have lower frequency but higher reliability. Use signal strength scores to identify the strongest signals (70+). Use cross quality scores to identify high-quality crossovers (70+).
Filter Combinations:
Start with histogram filter for basic momentum alignment, then add signal strength filter for moderate signals, then cross quality filter for high-quality crossovers. Combining all filters significantly reduces false signals but also reduces signal frequency. Find your balance based on your risk tolerance.
Volume Filtering:
Set volume threshold to 1.0 (default, effectively disabled) or lower to effectively disable volume filtering if you trade instruments with unreliable volume data or want to test without volume confirmation. Standard confirmation uses 1.2-1.5 threshold.
MACD Period Selection:
Standard MACD(12,26,9) provides balanced signals suitable for most trading. Shorter periods (8,17,7) for faster signals, longer (15,30,12) for smoother signals. Adjust based on your timeframe and trading style. Consider using configuration presets for optimized settings.
Moving Average Type:
EMA provides balanced responsiveness with smoothness. RMA is smoother and less responsive. WMA gives more weight to recent prices. SMA gives equal weight to all periods. Choose based on your preference for responsiveness vs. smoothness.
Divergence:
Pivot-based divergence is more reliable than simple divergence because it uses actual pivot points. Hidden divergence indicates continuation rather than reversal, useful for trend-following strategies. Adjust pivot lookback parameters to control sensitivity.
Dynamic Thresholds:
Dynamic OB/OS thresholds automatically adapt to volatility. In volatile markets, thresholds widen; in calm markets, they narrow. Adjust the multipliers to fine-tune sensitivity. Enable OB/OS background colors for visual indication.
Zero-Line Crosses:
Zero-line crosses indicate momentum shifts and can provide early warning signals before MACD crosses the signal line. Enable alerts for zero-line crosses to catch these early signals.
Alert Management:
Enable alert cooldown (default enabled, 5 bars) to prevent alert spam. Use alert type filter to only evaluate specific alert types. Signal debounce (default enabled, 3 bars) prevents duplicate MACD cross signals during choppy markets.
Technical Specifications
- Pine Script Version: v6
- Indicator Type: Non-overlay (displays in separate panel below price chart)
- Repainting Behavior: Minimal - all signals are based on confirmed bars, ensuring accurate backtesting results
- Performance: Optimized with conditional execution. Features only calculate when enabled.
- Compatibility: Works on all timeframes (1 minute to 1 month) and all instruments (stocks, forex, crypto, futures, etc.)
- Edge Case Handling: All calculations include safety checks for division by zero, NA values, and boundary conditions. Alert cooldowns and signal debounce handle edge cases where conditions never occurred or values are NA.
Technical Notes
- All MACD values respect percentage mode conversion when enabled
- Volume confirmation uses cached volume SMA for performance
- Label arrays (divergence) are automatically limited to prevent memory accumulation
- Background coloring: OB/OS backgrounds are drawn on top of main background to ensure visibility
- All calculations are optimized with conditional execution - features only calculate when enabled (performance optimization)
- Signal strength calculation combines multiple factors into a single score for easy filtering
- Cross quality calculation rates crossover quality based on angle, volume, and distance from zero
- Secondary timeframe MACD uses request.security() for higher timeframe data access
- Histogram analysis features (Bollinger Bands, MA, StochMACD) provide additional context beyond basic MACD signals
- Statistics table dynamically adjusts to show only enabled features, keeping it clean and relevant
- Divergence detection uses MACD line (not histogram) for more reliable signals
- Configuration presets automatically optimize MACD parameters for different trading styles
- Smart label placement: Labels appear on current bar at confirmation, using strength from tracked extreme point
- Label spacing uses effective distance (base distance × spacing multiplier) for better distribution
- Zero line polarity enforcement ensures Buy labels only appear when tracked extreme MACD < 0, Sell labels only when tracked extreme MACD > 0
- Label finalization requires MACD exit from OB/OS zone, sufficient bars passed, and recovery/decline percentage confirmation
- Strength-based filtering automatically compares and keeps only the strongest label when multiple signals are close together
- Enhanced visualization: Line outlines drawn behind main lines for superior visibility (black default, configurable)
- Enhanced visualization: Fill between MACD and zero line provides instant visual feedback (green above, red below)
- Enhanced visualization: Fill between OB/OS thresholds highlights neutral zone when dynamic levels are active
- Custom chart background overrides background mode when enabled, allowing theme-consistent indicator panels
CandelaCharts - Composite Pressure Index 📝 Overview
The CandelaCharts – Composite Pressure Index (CPI) is a multi-factor oscillator that blends RSI , Money Flow Index (MFI) , and Chaikin Money Flow (CMF) into a single, stretchable “pressure” line. Instead of looking at three separate indicators, CPI compresses price momentum and volume flow into one normalized curve around 0 , then amplifies extremes using a rolling z-score .
The result is a dynamic gauge of buying vs. selling pressure that can travel beyond ±1 during strong regime shifts, helping you spot exhaustion, climaxes, and trend-strength phases more intuitively.
📦 Features
Composite pressure engine – Combines RSI, MFI, and CMF into a single normalized oscillator around 0, giving you a unified view of market pressure.
Custom weighting of components – Independently weight RSI, MFI, and CMF to prioritize pure price momentum or volume-driven signals.
Rolling z-score stretch – Uses a configurable z-score window to “stretch” the composite values, letting the line exceed ±1 during extremes instead of staying capped.
Adaptive amplitude control – An amplitude (gain) factor lets you scale how aggressive or subtle the CPI swings appear.
EMA smoothing – Optional smoothing removes noise while preserving the timing of swings and reversals.
Visual pressure band – Zero, +1, and -1 reference lines with a shaded band make it easy to see when pressure is “normal” vs. extended.
Dynamic color gradients – Warm/orange tones above 0 for bullish pressure and cool/blue tones below 0 for bearish pressure, with saturation increasing as pressure intensifies.
NA-safe statistics – Custom mean and standard deviation routines ensure stable behavior from the start of the chart and during partial history.
⚙️ Settings
RSI Length : Lookback length for RSI . Higher values smooth the RSI component; lower values make it more reactive to short-term price momentum.
MFI Length : Lookback length for the manual Money Flow Index . Adjust this to control how sensitive CPI is to price–volume interaction.
CMF Length : Lookback length for Chaikin Money Flow . This defines the window used to assess accumulation/distribution through volume flow.
RSI Weight : Relative importance of RSI within the composite. Increasing this emphasizes pure price momentum in the CPI.
MFI Weight : Relative importance of MFI. Higher values strengthen the influence of volume-weighted price moves.
CMF Weight : Relative importance of CMF. Raising this highlights accumulation/distribution as a driver of the pressure index.
Smoothing : EMA length applied to the stretched CPI line. A value of 1 effectively disables smoothing, while higher values reduce noise at the cost of a slight lag.
Z-score Window : Rolling window used to compute the mean and standard deviation of the raw composite. This defines the statistical context for what counts as “extreme”. Shorter windows adapt faster; longer windows give a more stable regime.
Amplitude : Gain factor applied to the z-scored composite. Values above 1.0 exaggerate swings and make extremes more visually pronounced; values below 1.0 compress them.
⚡️ Showcase
Composite Pressure Index
Mean Line
Divergences
📒 Usage
1. Identify directional pressure regimes
Use 0 as the key balance line:
CPI > 0 → Net bullish pressure (buyers in control).
CPI < 0 → Net bearish pressure (sellers in control).
You can treat prolonged stays above or below 0 as confirmations of trend direction, especially when price structure agrees.
2. Read statistical extremes instead of fixed levels
Because CPI is stretched via a z-score , values beyond ±1 typically represent statistically meaningful extremes within your chosen window:
CPI > +1 → Overextended bullish pressure / potential euphoria.
CPI < -1 → Overextended bearish pressure / potential capitulation.
These zones are not automatic reversal signals, but they highlight areas where monitoring for exhaustion, blow-offs, or risk-reward shifts can be beneficial.
3. Spot divergences with price
Classic divergence logic applies particularly well when pressure is composite:
Bearish divergence – Price makes higher highs, but CPI makes lower highs or fails to confirm.
Bullish divergence – Price makes lower lows, but CPI makes higher lows or shows less downside extension.
These patterns can be integrated with support/resistance, liquidity levels, and other CandelaCharts tools.
4. Tune the weights to your strategy
Adjust the three weights to match your focus:
Higher RSI weight → More sensitivity to pure price momentum (good for breakout or trend-following systems).
Higher MFI weight → Greater emphasis on price–volume interaction (ideal for spotting volume-confirmed moves).
Higher CMF weight → Stronger focus on accumulation/distribution (helpful for swing and position traders).
5. Integrate with existing setups
The CPI is designed to sit comfortably below price:
Use it as a “context” oscillator underneath your main price-action and liquidity models.
Combine CPI extremes and divergences with key levels, range models, or order flow signals for higher-confluence entries.
🚨 Alerts
The indicator does not provide any alerts!
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Buy / Sell Volume + % (Classic + Pressure)Buy / Sell Volume % (Classic + Pressure)
Overview
Buy / Sell Volume (Classic + Pressure) is a volume decomposition and dominance indicator designed to help traders understand how trading volume is distributed between buying and selling pressure on each candle.
Instead of treating volume as a single number, this indicator splits total volume into estimated Buy Volume and Sell Volume, visualizes them symmetrically, and summarizes dominance using a compact on-chart dashboard.
The indicator is intended as a context and confirmation tool, not a trade signal generator.
Core Concepts
1. Buy / Sell Volume Decomposition
The indicator estimates buying and selling activity based on the position of the close within the candle’s high–low range:
Closes near the high → more buying pressure
Closes near the low → more selling pressure
Middle closes → balanced activity
This provides a clear visual view of demand vs supply on every bar.
2. Dual Calculation Modes
🔹 Classic Mode (Default)
Uses pure candle-range logic
Buy Volume + Sell Volume = Total Volume (exact conservation)
No smoothing or directional bias
Values closely match traditional volume behavior
Best for:
Structural analysis
Accumulation / distribution studies
Comparing against raw volume
🔹 Pressure Mode
Introduces a directional bias:
Bullish candles slightly favor buy volume
Bearish candles slightly favor sell volume
Optional EMA smoothing reduces noise
Still volume-conserving (Buy + Sell = Total Volume)
Best for:
Identifying dominance
Trend continuation confirmation
Absorption vs initiative activity
Visual Elements
Volume Bars
Buy Volume plotted above zero
Sell Volume plotted below zero
Optional Total Volume Envelope for context
Color by Dominance
Bright colors when one side dominates
Faded colors when dominance is weak
Helps instantly identify:
Accumulation
Distribution
Absorption
Dashboard (Optional)
A compact dashboard displays:
Buy %
Sell %
Dominance State
BUY DOM
SELL DOM
BALANCED
The dashboard can be toggled ON/OFF and switched between Normal and Compact size to suit multi-pane layouts.
How to Use This Indicator
This indicator works best as a confirmation layer, not a standalone system.
Common Use Cases
Confirming breakouts or breakdowns
Spotting accumulation or distribution near key levels
Identifying absorption during consolidations
Filtering false price moves
Examples
Price rising + strong Buy % → constructive demand
Price rising + strong Sell % → possible distribution
Flat price + balanced volume → absorption / compression
What This Indicator Is NOT
❌ Not true order-flow or bid/ask data
❌ Not a buy/sell signal generator
❌ Not predictive on its own
All calculations are candle-based estimations, designed for context and insight, not execution timing.
Best Use
Works on all timeframes
Most reliable on liquid instruments
Especially useful when combined with:
Support / resistance
Trend structure
Market regime or breadth indicators
Summary
Buy / Sell Volume (Classic + Pressure) helps traders go beyond raw volume by visualizing who is in control of each candle, how strong that control is, and whether volume behavior supports price action.
Used correctly, it can significantly improve trade selectivity, confidence, and risk awareness.
Short-Term Bubble Risk [Phantom] Short-Term Bubble Risk
Concept
This indicator visualizes short-term market risk by measuring how far price is stretched relative to its recent weekly trend.
Instead of focusing on absolute price levels, it looks at price behavior.
A similar reading means similar market conditions, whether price is high or low.
The goal is to help identify areas of potential accumulation and potential distribution in a clear, visual way.
How It Works
The indicator compares the weekly closing price to a weekly moving average and displays the deviation as a histogram.
When price is far below its average, risk is considered lower
When price is far above its average, risk is considered higher
The zero line represents fair value, where price equals its weekly average.
Features
Color-coded histogram showing short-term risk levels
Designed to work across different assets and price ranges
Optional bar coloring on the main chart using weekly risk data
Safe to use on any timeframe (risk is calculated on weekly data)
Settings
# Moving Average Length (Weeks):
Adjusts how sensitive the indicator is to price changes
# Color Visibility Toggles:
Allows hiding or showing specific risk zones
# Bar Coloring:
Option to color chart candles based on weekly risk levels
Usage
This indicator is best used as a risk lens, not a timing tool.
Common uses include:
Identifying potential accumulation zones during weakness
Spotting overextended conditions during strong moves
Comparing short-term risk across different assets
Adding context to trend-following or DCA strategies
Trade Ideas
# Lower-risk zones (cool colors):
Can support accumulation or patience during downtrends
# Higher-risk zones (warm colors):
Can signal caution, reduced exposure, or profit-taking
Always combine with:
Trend direction
Market structure
Higher-timeframe context
Limitations
This indicator does not predict tops or bottoms
High risk can remain high during strong trends
Low risk does not guarantee immediate reversals
It should not be used as a standalone trading system.
Disclaimer
This indicator is for educational and informational purposes only.
It is not financial advice.
Always do your own research and manage risk appropriately.
ALT Risk Metric StrategyHere's a professional write-up for your ALT Risk Strategy script:
ALT/BTC Risk Strategy - Multi-Crypto DCA with Bitcoin Correlation Analysis
Overview
This strategy uses Bitcoin correlation as a risk indicator to time entries and exits for altcoins. By analyzing how your chosen altcoin performs relative to Bitcoin, the strategy identifies optimal accumulation periods (when alt/BTC is oversold) and profit-taking opportunities (when alt/BTC is overbought). Perfect for traders who want to outperform Bitcoin by strategically timing altcoin positions.
Key Innovation: Why Alt/BTC Matters
Most traders focus solely on USD price, but Alt/BTC ratios reveal true altcoin strength:
When Alt/BTC is low → Altcoin is undervalued relative to Bitcoin (buy opportunity)
When Alt/BTC is high → Altcoin has outperformed Bitcoin (take profits)
This approach captures the rotation between BTC and alts that drives crypto cycles
Key Features
📊 Advanced Technical Analysis
RSI (60% weight): Primary momentum indicator on weekly timeframe
Long-term MA Deviation (35% weight): Measures distance from 150-period baseline
MACD (5% weight): Minor confirmation signal
EMA Smoothing: Filters noise while maintaining responsiveness
All calculations performed on Alt/BTC pairs for superior market timing
💰 3-Tier DCA System
Level 1 (Risk ≤ 70): Conservative entry, base allocation
Level 2 (Risk ≤ 50): Increased allocation, strong opportunity
Level 3 (Risk ≤ 30): Maximum allocation, extreme undervaluation
Continuous buying: Executes every bar while below threshold for true DCA behavior
Cumulative sizing: L3 triggers = L1 + L2 + L3 amounts combined
📈 Smart Profit Management
Sequential selling: Must complete L1 before L2, L2 before L3
Percentage-based exits: Sell portions of position, not fixed amounts
Auto-reset on re-entry: New buy signals reset sell progression
Prevents premature full exits during volatile conditions
🤖 3Commas Automation
Pre-configured JSON webhooks for Custom Signal Bots
Multi-exchange support: Binance, Coinbase, Kraken, Bitfinex, Bybit
Flexible quote currency: USD, USDT, or BUSD
Dynamic order sizing: Automatically adjusts to your tier thresholds
Full webhook documentation compliance
🎨 Multi-Asset Support
Pre-configured for popular altcoins:
ETH (Ethereum)
SOL (Solana)
ADA (Cardano)
LINK (Chainlink)
UNI (Uniswap)
XRP (Ripple)
DOGE
RENDER
Custom option for any other crypto
How It Works
Risk Metric Calculation (0-100 scale):
Fetches weekly Alt/BTC price data for stability
Calculates RSI, MACD, and deviation from 150-period MA
Normalizes MACD to 0-100 range using 500-bar lookback
Combines weighted components: (MACD × 0.05) + (RSI × 0.60) + (Deviation × 0.35)
Applies 5-period EMA smoothing for cleaner signals
Color-Coded Risk Zones:
Green (0-30): Extreme buying opportunity - Alt heavily oversold vs BTC
Lime/Yellow (30-70): Accumulation range - favorable risk/reward
Orange (70-85): Caution zone - consider taking initial profits
Red/Maroon (85-100+): Euphoria zone - aggressive profit-taking
Entry Logic:
Buys execute every candle when risk is below threshold
As risk decreases, position sizing automatically scales up
Example: If risk drops from 60→25, you'll be buying at L1 rate until it hits 50, then L2 rate, then L3 rate
Exit Logic:
Sells only trigger when in profit AND risk exceeds thresholds
Sequential execution ensures partial profit-taking
If new buy signal occurs before all sells complete, sell levels reset to L1
Configuration Guide
Choosing Your Altcoin:
Select crypto from dropdown (or use CUSTOM for unlisted coins)
Pick your exchange
Choose quote currency (USD, USDT, BUSD)
Risk Metric Tuning:
Long Term MA (default 150): Higher = more extreme signals, Lower = more frequent
RSI Length (default 10): Lower = more volatile, Higher = smoother
Smoothing (default 5): Increase for less noise, decrease for faster reaction
Buy Settings (Aggressive DCA Example):
L1 Threshold: 70 | Amount: $5
L2 Threshold: 50 | Amount: $6
L3 Threshold: 30 | Amount: $7
Total L3 buy = $18 per candle when deeply oversold
Sell Settings (Balanced Exit Example):
L1: 70 threshold, 25% position
L2: 85 threshold, 35% position
L3: 100 threshold, 40% position (final exit)
3Commas Setup
Bot Configuration:
Create Custom Signal Bot in 3Commas
Set trading pair to your altcoin/USD (e.g., ETH/USD, SOL/USDT)
Order size: Select "Send in webhook, quote" to use strategy's dollar amounts
Copy Bot UUID and Secret Token
Script Configuration:
Paste credentials into 3Commas section inputs
Check "Enable 3Commas Alerts"
Save and apply to chart
TradingView Alert:
Create Alert → Condition: "alert() function calls only"
Webhook URL: api.3commas.io
Enable "Webhook URL" checkbox
Expiration: Open-ended
Strategy Advantages
✅ Outperform Bitcoin: Designed specifically to beat BTC by timing alt rotations
✅ Capture Alt Seasons: Automatically accumulates when alts lag, sells when they pump
✅ Risk-Adjusted Sizing: Buys more when cheaper (better risk/reward)
✅ Emotional Discipline: Systematic approach removes fear and FOMO
✅ Multi-Asset: Run same strategy across multiple altcoins simultaneously
✅ Proven Indicators: Combines RSI, MACD, and MA deviation - battle-tested tools
Backtesting Insights
Optimal Timeframes:
Daily chart: Best for backtesting and signal generation
Weekly data is fetched internally regardless of display timeframe
Historical Performance Characteristics:
Accumulates heavily during bear markets and BTC dominance periods
Captures explosive altcoin rallies when BTC stagnates
Sequential selling preserves capital during extended downtrends
Works best on established altcoins with multi-year history
Risk Considerations:
Requires capital reserves for extended accumulation periods
Some altcoins may never recover if fundamentals deteriorate
Past correlation patterns may not predict future performance
Always size positions according to personal risk tolerance
Visual Interface
Indicator Panel Displays:
Dynamic color line: Green→Lime→Yellow→Orange→Red as risk increases
Horizontal threshold lines: Dashed lines mark your buy/sell levels
Entry/Exit labels: Green labels for buys, Orange/Red/Maroon for sells
Real-time risk value: Numerical display on price scale
Customization:
All threshold lines are adjustable via inputs
Color scheme clearly differentiates buy zones (green spectrum) from sell zones (red spectrum)
Line weights emphasize most extreme thresholds (L3 buy and L3 sell)
Strategy Philosophy
This strategy is built on the principle that altcoins move in cycles relative to Bitcoin. During Bitcoin rallies, alts often bleed against BTC (high sell, accumulate). When Bitcoin consolidates, alts pump (take profits). By measuring risk on the Alt/BTC chart instead of USD price, we time these rotations with precision.
The 3-tier system ensures you're always averaging in at better prices and scaling out at better prices, maximizing your Bitcoin-denominated returns.
Advanced Tips
Multi-Bot Strategy:
Run this on 5-10 different altcoins simultaneously to:
Diversify correlation risk
Capture whichever alt is pumping
Smooth equity curve through rotation
Pairing with BTC Strategy:
Use alongside the BTC DCA Risk Strategy for complete portfolio coverage:
BTC strategy for core holdings
ALT strategies for alpha generation
Rebalance between them based on BTC dominance
Threshold Calibration:
Check 2-3 years of historical data for your chosen alt
Note where risk metric sat during major bottoms (set buy thresholds)
Note where it peaked during euphoria (set sell thresholds)
Adjust for your risk tolerance and holding period
Credits
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Technical Analysis Framework: RSI, MACD, Moving Average theory
Implementation: pommesUNDwurst
Disclaimer
This strategy is for educational purposes only. Cryptocurrency trading involves substantial risk of loss. Altcoins are especially volatile and many fail completely. The strategy assumes liquid markets and reliable Alt/BTC price data. Always do your own research, understand the fundamentals of any asset you trade, and never risk more than you can afford to lose. Past performance does not guarantee future results. The authors are not financial advisors and assume no liability for trading decisions.
Additional Warning: Using leverage or trading illiquid altcoins amplifies risk significantly. This strategy is designed for spot trading of established cryptocurrencies with deep liquidity.
Tags: Altcoin, Alt/BTC, DCA, Risk Metric, Dollar Cost Averaging, 3Commas, ETH, SOL, Crypto Rotation, Bitcoin Correlation, Automated Trading, Alt Season
Feel free to modify any sections to better match your style or add specific backtesting results you've observed! 🚀Claude is AI and can make mistakes. Please double-check responses. Sonnet 4.5
On Balance Volume [BrightSideTrading]
# On Balance Volume - Complete User Guide
## Overview
This enhanced OBV indicator provides clean, actionable volume analysis with intelligent signal filtering. It combines On-Balance Volume (OBV) with a smoothed signal line to identify shifts in buying and selling pressure without chart clutter.
**Key Features:**
- Real-time OBV and signal line visualization
- Smart crossover detection with confirmation filtering
- Z-Score momentum analysis
- Customizable signal alerts with V-shaped markers
- Window-normalized option for detrended analysis
---
## What is On-Balance Volume (OBV)?
OBV is a volume-based momentum indicator that accumulates volume on up days and subtracts volume on down days. It answers a fundamental question: **Is volume flowing in (buying) or out (selling)?**
**Formula:**
- If Close > Previous Close: OBV = Previous OBV + Volume
- If Close < Previous Close: OBV = Previous OBV - Volume
- If Close = Previous Close: OBV = Previous OBV (unchanged)
**What it tells you:**
- **Rising OBV** = Accumulation (smart money buying)
- **Falling OBV** = Distribution (smart money selling)
- **OBV above zero line** = Net positive buying pressure
- **OBV below zero line** = Net negative selling pressure
---
## Interface & Settings
### **MAIN VISUALIZATION**
**OBV Line (Green/Red Ribbon)**
- Green when OBV is above the signal line (bullish trend)
- Red when OBV is below the signal line (bearish trend)
- Toggles between window-normalized (detrended) and raw values
**Signal Line (Orange)**
- Smoothed average of OBV
- Crossovers with OBV generate buy/sell signals
- Default: 21-period SMA
**V-Shaped Markers**
- Green upward V = Bullish crossover (buy signal)
- Red downward V = Bearish crossover (sell signal)
- Appears at the OBV value when signal is triggered
**Zero Line (Yellow)**
- Center equilibrium point for volume balance
- Acts as support/resistance for OBV
- Separates buying pressure (above) from selling pressure (below)
---
### **SOURCE GROUP**
**Source**
- **Default:** Close
- **Options:** Open, High, Low, or any custom value
- Controls which price value triggers OBV direction changes
- Most traders use Close for standard OBV calculation
---
### **SIGNAL SMOOTHING GROUP**
**Show Signal?**
- **Default:** ON
- Toggle visibility of the signal line
- Disable if you prefer to see raw OBV only
**Smoothing Type**
- **SMA (Simple Moving Average)** - Default, standard smoothing
- **EMA (Exponential Moving Average)** - Faster response, weights recent bars more heavily
- **Choose SMA** for consistent, traditional OBV signals
- **Choose EMA** for faster trend identification (more whipsaws possible)
**Smoothing Length**
- **Default:** 21 bars
- **Range:** 1-200 bars
- **Lower values** (5-14): Faster signals, more noise
- **Higher values** (30-50): Slower signals, fewer false alarms
- **Recommendation:** Use 21-25 for most timeframes
---
### **SIGNAL FILTERING GROUP**
This is your primary control for signal quality and frequency.
**Show Signal Markers?**
- **Default:** ON
- Toggle the V-shaped buy/sell markers on/off
- Disable if markers distract from your analysis
**Signal Filter Type**
- **None** - Shows every single crossover (noisy, best for skilled traders)
- **Confirmation Bars** - Waits N bars before confirming signal (recommended)
- **Strength-Based** - Only signals during strong momentum (filters weakest moves)
#### **CONFIRMATION BARS MODE** (Recommended)
Best for reducing false signals while staying responsive to real moves.
**Confirmation Bars**
- **Default:** 2 bars
- **Range:** 1-10 bars
- Waits for the signal to hold for N consecutive bars after crossover
- **Setting 1:** Every crossover (same as "None")
- **Setting 2:** Wait 1 bar confirmation (good balance)
- **Setting 3:** Wait 2 bars confirmation (filters 50% of noise)
- **Setting 4+:** Very selective, misses quick reversals
**How it works:**
1. OBV crosses signal line → Confirmation counter starts
2. If OBV stays on correct side for 2 bars → V-marker appears
3. If OBV crosses back → Counter resets, no signal
#### **STRENGTH-BASED MODE**
Only signals when momentum is statistically significant.
**Min Z-Score Strength**
- **Default:** 0.3
- **Range:** 0.0-3.0
- Requires OBV deviation from its mean to reach this threshold
- **Setting 0.1-0.3:** More signals, lower quality
- **Setting 0.5-0.8:** Moderate signals, good quality
- **Setting 1.0+:** Only the strongest momentum shifts
**How it works:**
- Calculates how far OBV is from its 50-bar average (Z-score)
- Only shows signals when this distance is meaningful
- Automatically avoids weak, choppy market conditions
---
### **VISUALS & COLORS GROUP**
**Highlight Crossovers?**
- **Default:** ON
- Master toggle for all signal markers
- Turn OFF to see only the OBV/signal lines
**Apply Ribbon Filling?**
- **Default:** ON
- Colors the space between OBV and signal line
- Green fill = OBV above signal (bullish)
- Red fill = OBV below signal (bearish)
- Provides clear visual trend confirmation
- Turn OFF for minimal chart clutter
---
### **STATS & ZONES GROUP**
**Use Window-Normalized OBV (visual only)?**
- **Default:** ON
- Removes long-term trend from OBV for clearer short-term signals
- Detrends the indicator to highlight recent momentum changes
- **ON:** Better for swing trading and identifying reversals
- **OFF:** Better for trend-following strategies
- Note: Z-Score always uses raw OBV for statistical accuracy
**OBV Normalize Window**
- **Default:** 200 bars
- Lookback period for detrending calculation
- Larger values = more aggressive detrending
- Adjust if you want OBV to oscillate more/less around zero
**Show Z-Score (OBV)?**
- **Default:** ON
- Displays statistical momentum indicator below main chart
- Ranges from -3 to +3 (most data within -2 to +2)
- High Z-Score = Strong buying momentum
- Low Z-Score = Strong selling momentum
**Z-Score Lookback**
- **Default:** 50 bars
- Period for calculating Z-Score mean and standard deviation
- Larger = smoother Z-Score, slower response
- Smaller = noisier Z-Score, faster response
**Show ROC (OBV Momentum)?**
- **Default:** OFF
- Rate of Change indicator for OBV velocity
- Useful for identifying momentum turning points
- Enable if you want to see speed of volume changes
**ROC Lookback**
- **Default:** 14 bars
- Period for ROC calculation
**Show Z-Score StdDev Zones?**
- **Default:** ON
- Shaded regions around zero line showing statistical boundaries
- Inner Zone (±1 Z) = Normal variation
- Outer Zone (±2 Z) = Extreme moves, potential reversals
- Helps identify overbought/oversold volume conditions
**Inner Zone (±Z)**
- **Default:** 1.0
- First boundary for standard deviation zones
- Most normal trading occurs within ±1
**Outer Zone (±Z)**
- **Default:** 2.0
- Second boundary for extreme conditions
- Crossing these zones indicates significant momentum shift
---
## Trading Strategy Examples
### **Strategy 1: Signal Line Crossovers (Beginner)**
**Setup:**
- Signal Filter Type: **Confirmation Bars**
- Confirmation Bars: **2-3**
- Show Signal Markers: **ON**
**Rules:**
1. **BUY signal** (green V): When OBV crosses above signal line and holds for 2-3 bars
- Confirms buying pressure is building
- Look for price to follow within 1-3 bars
2. **SELL signal** (red V): When OBV crosses below signal line and holds for 2-3 bars
- Confirms selling pressure is increasing
- Expect price decline
3. **Exit:** Take profits at next signal or use price support/resistance
**Best For:** Swing trading, intraday reversals, timeframes 5m-1h
---
### **Strategy 2: Zero Line Bounce (Intermediate)**
**Setup:**
- Signal Filter Type: **Strength-Based**
- Min Z-Score Strength: **0.5**
- Show Z-Score StdDev Zones: **ON**
**Rules:**
1. **Watch OBV approach zero line** during established trends
- OBV bouncing repeatedly off zero = trend is healthy
- OBV breaking through zero = trend reversal imminent
2. **Enter on bounce:** Buy when OBV bounces from zero line in uptrend
3. **Exit on break:** Close position when OBV breaks below zero line
4. **Confirm with Z-Score:** Only take trades when Z-Score shows momentum (|Z| > 0.5)
**Best For:** Trend traders, identifying trend strength, medium timeframes 15m-4h
---
### **Strategy 3: Momentum Extremes (Advanced)**
**Setup:**
- Signal Filter Type: **None**
- Show Z-Score StdDev Zones: **ON**
- Outer Zone: **2.0**
**Rules:**
1. **Identify extremes:** When Z-Score breaks outer zone (±2.0)
- Indicator is in extreme territory
- Likely overextended
2. **Fade extremes:** Take opposite position when Z-Score hits extreme
- High Z (>2.0) = OBV overbought, expect pullback
- Low Z (<-2.0) = OBV oversold, expect bounce
3. **Confirm:** Wait for crossover signal to enter
4. **Target:** Outer zone of opposite side or zero line
**Best For:** Range trading, mean reversion, experienced traders only
---
## Reading the Indicator in Different Markets
### **Strong Uptrend**
- OBV consistently above signal line (green)
- OBV well above zero line, rising higher lows
- Z-Score positive, trending upward
- **Action:** Buy dips to signal line, sell at resistance
### **Strong Downtrend**
- OBV consistently below signal line (red)
- OBV well below zero line, making lower highs
- Z-Score negative, trending downward
- **Action:** Sell rallies to signal line, cover at support
### **Consolidation/Choppy Market**
- OBV whipsaws around signal line frequently
- Crossovers occur every few bars
- Z-Score oscillating between -1 and +1
- **Action:** Increase confirmation bars to 3-4, or switch to strength-based filter
### **Accumulation (Bottom Formation)**
- OBV rising while price is flat or falling
- Volume flowing in despite downtrend (bullish divergence)
- Z-Score climbing while price lows hold
- **Action:** Expect breakout up; prepare buy near support
### **Distribution (Top Formation)**
- OBV falling while price is flat or rising
- Volume flowing out despite uptrend (bearish divergence)
- Z-Score falling while price continues higher
- **Action:** Expect breakdown down; prepare short near resistance
---
## Parameter Tuning Guide
### **Aggressive Settings (More Signals)**
- Smoothing Length: 14
- Signal Filter: None or Confirmation Bars: 1
- Min Z-Score: 0.1
- Best for: Day trading, high volatility stocks
- Risk: More false signals
### **Balanced Settings (Recommended)**
- Smoothing Length: 21
- Signal Filter: Confirmation Bars: 2
- Min Z-Score: 0.3
- Best for: Swing trading, most market conditions
- Risk/Reward: Moderate
### **Conservative Settings (Fewer Signals)**
- Smoothing Length: 30-40
- Signal Filter: Confirmation Bars: 3-4 or Strength-Based: 0.7+
- Min Z-Score: 0.8
- Best for: Position trading, high-conviction trades only
- Risk: May miss some moves
---
## Common Questions & Troubleshooting
**Q: Why are there more sell signals than buy signals?**
A: This reflects the actual market action. Markets often decline faster than they rise (fear > greed). Confirm signals with price action and support/resistance.
**Q: The indicator keeps whipsawing, should I hide it?**
A: Increase Confirmation Bars to 3-4 or switch to Strength-Based filter. Market conditions matter—choppy markets require stricter filters.
**Q: What's the difference between normalized and raw OBV?**
A: Normalized (detrended) shows shorter-term momentum by removing long-term trends. Raw OBV shows absolute accumulation/distribution over the full period. Use normalized for swing signals, raw for trend confirmation.
**Q: My signals come too late. How do I get faster entry?**
A: Reduce Smoothing Length (try 14 instead of 21), use EMA instead of SMA, or set Confirmation Bars to 1. Trade-off: More false signals.
**Q: Can I use this for day trading?**
A: Yes, on 1m-5m charts with aggressive settings. Use Confirmation Bars: 1 and focus on Z-Score > 0.5 entries only.
**Q: Should I trade every signal?**
A: No. Filter signals using: price near support/resistance, multiple indicators confirming, and Z-Score showing momentum. Best signals occur at key levels.
---
## Best Practices
1. **Always confirm with price action:** OBV signals work best when price is near support, resistance, or moving average. Don't trade signals in a vacuum.
2. **Use volume context:** Check if volume is increasing or decreasing on the signal. Strong signals have volume confirmation (increasing volume on OBV spikes).
3. **Adjust settings per timeframe:**
- 1m-5m: Smoothing 12, Confirmation 1, Z-Score 0.2
- 15m-1h: Smoothing 20, Confirmation 2, Z-Score 0.3
- 4h-1d: Smoothing 25, Confirmation 3, Z-Score 0.5
4. **Watch the zero line:** It's your friend. OBV behavior at the zero line reveals trend strength. Bounces = healthy trend. Breaks = reversal.
5. **Risk management:** No indicator is perfect. Use proper position sizing and stop losses. OBV should confirm your thesis, not be the only reason to trade.
6. **Combine with other indicators:**
- Price moving averages for trend confirmation
- RSI or Stochastic for overbought/oversold levels
- Support/resistance for entry/exit zones
- MACD for momentum divergences
---
## Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Past performance does not guarantee future results. Always conduct your own research and consult with a financial advisor before making trading decisions. Trading carries risk, including potential loss of principal.
---
## Version History
**Version 1.0** - Initial release with enhanced signal filtering, Z-Score analysis, and customizable parameters.
BTC - VERI - Valuation & Entity Ratio IndexVERI: Valuation & Entity Ratio IndexObservation-only.
Data: IntoTheBlock.
Overview & Philosophy
The name VERI is derived from the Latin Veritas (Truth). In a crypto market often driven by deceptive speculative noise, this indicator seeks to establish the "On-Chain Truth" of a price trend.
It operates on the thesis that price action is only sustainable when verified by high-conviction capital flows.VERI is a fundamental composite oscillator that fuses Entity Behavior (Who is holding?) with Network Valuation (Is the price fair?) to identify Bitcoin market cycle extremes.
The "Alpha"
Why this Composite stands out: on-chain metrics often tell only half the story.
MVRV tells you if the price is cheap, but not if anyone is actually buying.
Whale Activity tells you if large players are moving, but not if they are accumulating at a value discount.
VERI fuses these two dimensions into a single Z-Score. It identifies the rare, high-probability moments where Smart Money Conviction intersects with Deep Value.
Methodology
The Mathematics of VERI: The indicator constructs a composite index using three fundamental metrics from IntoTheBlock:
The "Who" (Entity Ratio) : We calculate the flow ratio between Whales (>1% supply holders) and Retail (<0.1% supply holders). A rising ratio indicates supply is transferring from weak hands to strong hands.
The "Why" (Valuation Multiplier) : We utilize the MVRV (Market Value to Realized Value) ratio. To isolate value opportunities, we use the inverse (1 / MVRV).
The Fusion : These factors are multiplied to create the raw VERI index.
Normalization & Inversion
We apply a rolling Z-Score (standard deviation from the mean) and invert the result.
How to Interpret the Indicator
Because the output is inverted, the visual logic matches price action intuitively:
🟥 Distribution Zone (High Values > 1.5):
The Signal: "Low Conviction Overvaluation."
Context: The price is historically expensive relative to the cost basis (High MVRV), and Whales are distributing coins to Retail.Implication: Historically precedes macro tops or deep corrections.
🟩 Accumulation Zone (Low Values < -1.5):
The Signal: "High Conviction Undervaluation."Context: The price is historically cheap (Low MVRV), and Whales are aggressively accumulating relative to Retail.
Implication: Historically precedes macro bottoms and generational entry points.
Zero Line : Represents the historical baseline. A crossover of the zero line often confirms a regime shift (e.g., from Bear to Bull).
Visual Guide & Features
Dynamic Coloring: The line turns Red in the Distribution Zone, Blue in the Accumulation Zone, and Orange during neutral trends.
Zone Labels: Static labels are pinned to the left side of the chart for immediate context.
The "Data Check" Monitor (Status Table): Since this indicator relies on third-party fundamental data, we have included a diagnostic table in the bottom-right corner.
Data Check Monitor Guide
STATUS: LIVE (Green): The indicator is functioning correctly. All data feeds (Whales, Retail, MVRV) are being retrieved successfully.
STATUS: WAIT (Red): The indicator cannot retrieve data. This might happen for some reasons, e.g. your TradingView plan may not support IntoTheBlock integration.
Settings
Lookback Period (Default: 365): The window used for Z-Score normalization. We use a full year to smooth out seasonal volatility.
Smoothing (Default: 7): A 7-day smoothing is applied to the signal to filter out daily noise.
Zone Thresholds: Users can customize the specific Z-Score levels for the Distribution and Accumulation bands.
Disclaimer
This script is for research and educational purposes only. It uses historical on-chain data to visualize market structure and does not constitute financial advice. Past performance of whale entities does not guarantee future results.
Tags
bitcoin, btc, on-chain, mvrv, whales, valuation, fundamentals, cycle, oscillator, veri
Wyckoff + VSA Ultimate - Complete Market Analysis
**Wyckoff + VSA Ultimate** combines three proven methodologies into one powerful indicator:
🔷 **Wyckoff Method** - Identifies market accumulation and distribution phases
🔷 **Volume Spread Analysis** - Confirms moves with volume and price spread
🔷 **Random Walk Index** - Validates trend strength and direction
**MAIN SIGNALS:**
📊 **Wyckoff Signals** (Green = Bullish, Red = Bearish)
• SC (Selling Climax) - Major buying opportunity
• BC (Buying Climax) - Major selling opportunity
• AR (Automatic Rally) - Confirms accumulation
• DAR (Automatic Reaction) - Confirms distribution
• ST (Secondary Test) - Final test before move
📊 **VSA Patterns**
• Upthrust bars (weakness after rally)
• Reverse upthrust (strength after decline)
• No demand/supply bars
• Stopping volume
• Effort failures
**KEY FEATURES:**
✅ Multiple signal confirmation reduces false signals
✅ Real-time info table shows phase, volume, trends
✅ Dynamic stop loss levels calculated automatically
✅ Accumulation/Distribution boxes on chart
✅ Customizable filters for your trading style
✅ 12 alert conditions for all major signals
**HOW TO USE:**
For Swing Trading (4H/Daily):
1. Enable "Require VSA Confirmation"
2. Wait for SC or BC signals
3. Use displayed stop levels
4. Target next opposite phase
For Day Trading (15m/1H):
1. Enable "Require Trend Confirmation"
2. Trade only trend-aligned signals
3. Increase volume threshold to 1.5
4. Use tighter risk management
**BEST FOR:**
✅ Stocks (high volume)
✅ Forex majors
✅ Crypto (BTC, ETH)
✅ Index futures
**SETTINGS:**
Customize everything:
• RSI & Pivot parameters
• Volume & Spread analysis
• Trend periods (RWI)
• Signal filters
• Visual display options
**ALERTS:**
Pre-configured alerts for:
• All Wyckoff signals
• VSA reversals
• Strong buy/sell combinations
**Credits:** Integrates Wyckoff (faytterro) and VSA (theehoganator) methods.
**Disclaimer:** Educational purposes only. Use proper risk management. Past performance doesn't guarantee future results.
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Pine Script™ v6
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