Titan VSA + SMC Prime (Professional Institutional System)Titan VSA + SMC Prime is a comprehensive, hybrid trading system designed to bridge the gap between Volume Spread Analysis (VSA) and Smart Money Concepts (SMC) By Sultan of Multan. This script is built for traders who want to identify institutional activity, spot liquidity traps, and trade in harmony with the "Smart Money."
Unlike standard indicators that repaint or lag, Titan Prime focuses on price action, structural shifts, and volume anomalies to generate high-probability setups.
🔥 Key Features
1. Smart Money Concepts (SMC) Suite
Market Structure: Automatically maps BOS (Break of Structure) and CHoCH (Change of Character) with real-time trend identification (Bullish/Bearish).
Institutional Zones: clearly plots Order Blocks (OB), Breaker Blocks (BB), Fair Value Gaps (FVG), and Supply/Demand Zones.
Mitigation Tracking: Zones are automatically marked as "Mitigated" or removed once price has tested them, keeping your chart clean.
Premium & Discount Zones: Automatically draws the Equilibrium (EQ) to help you sell in Premium and buy in Discount areas.
2. Advanced Liquidity & Traps
Liquidity Sweeps (⚔): Identifies when key Highs or Lows are swept to grab liquidity.
Inducement (IDM 🪤): Highlights short-term highs/lows that act as "traps" for retail traders before the real move occurs. This helps you avoid false breakouts.
3. Volume Spread Analysis (VSA) Engine
Volume Bar Coloring: Candles are color-coded based on volume intensity:
🟨 Yellow: Ultra High Volume (Institutional Activity).
⬜ Gray: Low Volume (Lack of interest).
VSA Signals: Automatically detects powerful VSA patterns including:
No Demand (ND) / No Supply (NS)
Stopping Volume & Climaxes (SC/BC)
UpThrusts (UT) & Springs
Effort to Rise / Fall
Absorption
4. The "Smart Entry" System
This is the core of the indicator. It does not spam signals. It waits for a specific institutional sequence:
Liquidity Sweep: Price grabs liquidity.
Displacement: Price reverses aggressively.
Retest: The system waits for a pullback to the Order Block or FVG.
Confirmation: Only then does it display a "RETEST COMPLETE ✅ - SMART ENTRY" label with suggested TP/SL levels.
5. Professional Dashboards
Trade Status Panel (Top-Right): Monitors active signals, Entry, Stop Loss, Take Profit, and VSA Trend Score.
SMC Status Panel (Bottom-Right): A live scanner showing the status of Supply/Demand, FVGs, Structure, and overall Market Bias at a glance.
How to Use
Identify Trend: Use the dashboard to check if the market structure is Bullish or Bearish.
Wait for Traps: Look for IDM or Liquidity Sweep (⚔) labels. Smart moves usually happen after these traps.
Entry Confirmation: Do not enter blindly. Wait for the "RETEST COMPLETE" label which confirms that price has respected a Smart Money Zone.
Confluence: The best trades occur when an SMC Zone aligns with a VSA Signal (e.g., A Buying Climax inside a Demand Zone).
Customization
Visual Control: Fully adjustable text sizes, colors, and box lengths to fit your charting style.
Zoom Stability: Labels and text are pinned to ensure they remain readable when zooming in or out.
Disclaimer
This tool is for educational and analytical purposes. Always manage your risk and do not rely solely on any single indicator for financial decisions.
Accumulation / Distribution Line (ADL)
FestX VSTFestX NY Session Volume Framework is a session-based momentum and liquidity indicator designed specifically for the New York market open.
The script focuses on time-based market behaviour, filtering signals to only occur at precise session transitions where institutional volume is statistically higher.
Core Concepts Used:
• Session Transition Logic
Signals are only evaluated when the New York trading session opens, eliminating noise from low-liquidity periods.
• Relative Volume Expansion
Instead of raw volume, the script compares current volume against a rolling average to detect abnormal participation at the session open.
• Directional Candle Validation
Entry bias is derived from the relationship between candle open and close at the session trigger, aligning trades with immediate momentum.
• Optional Session Range Context
The tool can be used alongside Asian session highs and lows to identify continuation or reversal behaviour after range compression.
What Makes This Script Different:
This indicator does not attempt to predict direction throughout the day.
It deliberately restricts signals to one specific institutional window, using volume expansion + price acceptance to confirm direction.
This design reduces overtrading and focuses traders on high-quality, time-based opportunities rather than constant signals.
Intended Use:
• NY session open traders
• Index and futures traders
• Traders seeking confirmation at session transitions
This script is not a traditional trend indicator or oscillator and is best used as a contextual decision tool, not a standalone signal generator.
Liquidity Heatmap [Eˣ]💧 Liquidity Heatmap - Free Indicator
Overview
The Liquidity Heatmap reveals where stop losses are clustered in the market - the hidden liquidity zones that smart money targets. This indicator automatically identifies Buy-Side Liquidity (BSL) above price and Sell-Side Liquidity (SSL) below price, showing you exactly where institutional traders are likely to hunt for stops before major moves.
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🎯 What This Indicator Does
Identifies Liquidity Zones:
• Buy-Side Liquidity (BSL) - Stop losses from SHORT positions clustered above price
• Sell-Side Liquidity (SSL) - Stop losses from LONG positions clustered below price
• Automatically clusters nearby levels into high-probability zones
• Shows liquidity strength (1-5+) - higher numbers = more stops = bigger target
• Removes swept liquidity in real-time as price takes out stops
Visual Display:
• 🔴 Red Zones Above Price = Buy-Side Liquidity (shorts' stops)
• 🟢 Green Zones Below Price = Sell-Side Liquidity (longs' stops)
• Thicker/Darker Zones = Higher liquidity concentration
• BSL/SSL Labels = Show exact strength count
• Triangle Markers = Liquidity sweep alerts (when price takes stops)
Smart Features:
• Auto-removes old liquidity (customizable lookback period)
• Clusters nearby levels to reduce noise
• Tracks liquidity strength and age
• Updates in real-time as new swing points form
• Alerts when major liquidity zones are swept
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📊 How To Use This Indicator
Understanding Liquidity Concepts
What is Liquidity?
Liquidity refers to clusters of stop loss orders sitting in the market. These stops represent:
• Long traders' stop losses (below support) = Sell-Side Liquidity
• Short traders' stop losses (above resistance) = Buy-Side Liquidity
Why Does This Matter?
• Institutions NEED liquidity to fill large orders
• Price often "sweeps" liquidity zones before reversing
• Major liquidity = major target for smart money
• Understanding liquidity = understanding market maker behavior
The Liquidity Cycle:
1. Retail traders place stops at obvious levels (swing highs/lows)
2. Smart money identifies these clusters
3. Price is pushed to sweep the stops (liquidity grab)
4. Institutions fill their orders with this liquidity
5. Price reverses in the opposite direction
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💡 Trading Strategies
Strategy 1: Liquidity Sweep Reversals
Best For: Swing trading, catching reversals
Timeframes: 15min, 1H, 4H, Daily
Entry Setup:
1. Identify strong Sell-Side Liquidity (SSL) zone below price
2. Wait for price to sweep down into the SSL zone
3. Look for rejection/reversal candle pattern (pin bar, engulfing)
4. Enter LONG after sweep and reversal confirmation
5. Stop loss: Below the swept liquidity zone
6. Target: Opposite liquidity zone or key resistance
Why It Works: Smart money sweeps stops to fill buy orders, then pushes price higher
Example:
• SSL zone at $45,000 with strength 3
• Price drops to $44,950, sweeps the SSL
• Strong bullish reversal candle forms
• Enter long at $45,100
• Target: BSL zone at $47,000
Strategy 2: Liquidity-to-Liquidity Runs
Best For: Day trading, scalping
Timeframes: 5min, 15min, 1H
Entry Setup:
1. Price sweeps Sell-Side Liquidity below and reverses up
2. Identify Buy-Side Liquidity zone above
3. Enter LONG targeting the BSL zone above
4. Exit near/at the BSL zone (don't wait for sweep)
5. Stop loss: Below recent swing low
Why It Works: Price moves from liquidity pool to liquidity pool
Variation - Reverse for Shorts:
• BSL sweep above → Look for SSL zone below
• Enter short targeting lower liquidity
Strategy 3: Liquidity Avoidance (Stop Placement)
Best For: Improving win rate on existing strategies
Timeframes: All
Rules:
1. NEVER place stops exactly at obvious liquidity zones
2. Place stops beyond the liquidity zone with buffer
3. Or place stops before the liquidity zone (tighter, riskier)
4. Monitor liquidity strength - avoid zones with strength 3+
Why It Works: Market makers hunt obvious stop clusters
Example:
• Trading long, swing low at $100 (SSL zone, strength 4)
• Bad: Stop at $99.50 (will get swept)
• Better: Stop at $98.50 (beyond the liquidity)
• Alternative: Stop at $100.50 (tighter, before sweep zone)
Strategy 4: Confluence Trading
Best For: High probability setups
Timeframes: 1H, 4H, Daily
Entry Setup:
1. Find liquidity zone that aligns with:
• Major support/resistance level
• Fibonacci retracement (0.618, 0.786)
• Trendline
• Round psychological number ($50,000, $2,000, etc)
2. Wait for sweep of this high-confluence zone
3. Enter on reversal with multiple confirmations
4. Larger position size justified by confluence
Why It Works: Multiple factors = institutional interest = higher probability
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⚙️ Settings Explained
Core Settings
Swing Detection Length (Default: 10)
• Number of bars left/right to identify swing highs and lows
• Lower values (5-8): More sensitive, more liquidity zones, more noise
• Higher values (12-20): Less sensitive, only major swings, cleaner chart
• Recommended: 8-10 for intraday, 10-15 for swing trading
Liquidity Lookback Bars (Default: 100)
• How many historical bars to track liquidity zones
• Lower values (50-75): Shows only recent liquidity
• Higher values (100-200): Shows longer-term liquidity clusters
• Zones older than this are automatically removed
• Recommended: 100-150 for most timeframes
Zone Proximity % (Default: 0.5)
• Percentage threshold to group nearby levels into single zone
• Lower values (0.2-0.4): Keeps levels separate, more zones
• Higher values (0.6-1.0): Aggressive clustering, fewer zones
• Recommended: 0.4-0.6 for crypto, 0.3-0.5 for forex, 0.5-0.8 for stocks
Visualization Settings
Show Buy-Side Liquidity
• Toggle ON/OFF red zones above price
• Turn OFF if only interested in downside liquidity
Show Sell-Side Liquidity
• Toggle ON/OFF green zones below price
• Turn OFF if only interested in upside liquidity
Show Liquidity Labels
• Toggle BSL/SSL labels with strength numbers
• Turn OFF for cleaner chart appearance
• Keep ON to see exact liquidity strength
Display Style
• Boxes: Filled rectangular zones (best for visualizing strength)
• Lines: Horizontal dashed lines (minimal, clean look)
• Both: Boxes + Lines (maximum visibility)
Color Intensity
• Low: 85% transparency (subtle, less distracting)
• Medium: 75% transparency (balanced visibility)
• High: 65% transparency (bold, maximum visibility)
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📱 Info Panel Guide
Located in the top-right corner, the info panel provides real-time liquidity statistics:
Buy-Side Zones
• Count of active BSL zones above current price
• Higher number = More upside targets for price
Sell-Side Zones
• Count of active SSL zones below current price
• Higher number = More downside targets for price
Total Zones
• Combined count of all active liquidity
• Useful for gauging overall market structure
Nearest BSL
• Distance in % to closest Buy-Side Liquidity above
• Example: +2.5% means BSL is 2.5% above current price
• Quick reference for next upside target
Nearest SSL
• Distance in % to closest Sell-Side Liquidity below
• Example: -1.8% means SSL is 1.8% below current price
• Quick reference for next downside target
Liquidity Bias
• ⬆️ Bullish : More BSL than SSL (upside targets dominate)
• ⬇️ Bearish : More SSL than BSL (downside targets dominate)
• ↔️ Balanced: Equal liquidity on both sides (range-bound)
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🎓 Understanding Liquidity Strength
What Do The Numbers Mean?
Strength 1 : Single swing point
• Light liquidity, minor target
• Can be ignored in trending markets
• Useful in ranging/choppy conditions
Strength 2-3 : Moderate liquidity cluster
• Multiple nearby swing points merged
• Decent target for intraday moves
• Watch for potential sweeps
Strength 4-5 : Strong liquidity cluster
• Major cluster of stops
• High-probability target for institutions
• Expect reactions when swept
Strength 6+ : Extreme liquidity pool
• Massive stop cluster (rare)
• Critical zone - high probability of sweep
• Often marks major support/resistance
• Ideal for confluence setups
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📱 Alert Setup
This indicator includes 2 powerful alert types:
1. Buy-Side Liquidity Sweep
• Triggers when price sweeps BSL zone above
• Shows potential bullish reversal opportunity
• Often precedes upward continuation after sweep
2. Sell-Side Liquidity Sweep
• Triggers when price sweeps SSL zone below
• Shows potential bearish reversal opportunity
• Often precedes downward continuation after sweep
To Set Up Alerts:
1. Click the "Alert" button (clock icon) in TradingView
2. Condition: Select "Liquidity Heatmap"
3. Choose alert type: BSL Sweep or SSL Sweep
4. Configure notification method (push, email, webhook)
5. Click "Create"
Pro Tip: Set alerts for both BSL and SSL sweeps to catch opportunities in both directions
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💎 Pro Tips & Best Practices
✅ DO:
• Wait for confirmation - Don't enter immediately on sweep, wait for reversal pattern
• Combine with trend - SSL sweeps in uptrends = higher probability longs
• Check multiple timeframes - 1H liquidity + 4H liquidity = strongest zones
• Monitor strength - Focus on zones with strength 3+
• Use proper risk management - Liquidity sweeps can go further than expected
• Watch for re-sweeps - Sometimes liquidity zones get swept multiple times
• Consider volume - High volume sweeps = stronger reversal potential
⚠️ DON'T:
• Don't fade strong trends - In strong trends, sweeps often continue rather than reverse
• Don't overtrade - Not every sweep is a tradeable setup
• Don't ignore context - Check broader market conditions and news
• Don't use alone - Combine with price action, support/resistance, and other analysis
• Don't place stops at liquidity - Your stops will be hunted
• Don't expect perfection - Some sweeps fail, some zones never get hit
🎯 Best Timeframes:
• Scalping: 5min, 15min (fast moves, frequent sweeps)
• Day Trading: 15min, 1H (balanced view)
• Swing Trading: 1H, 4H, Daily (major liquidity zones)
• Position Trading: 4H, Daily, Weekly (institutional liquidity)
🔥 Best Markets:
• Crypto (high volatility, frequent liquidity grabs)
• Forex (EUR/USD, GBP/USD - liquid pairs)
• Futures (ES, NQ, CL - high liquidity contracts)
• Stocks (large caps with high volume)
⏰ Best Times:
• Market opens (high volatility = liquidity hunting)
• Before/after major news events
• Session overlaps (London/NY for forex)
• First hour and last hour of trading
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🚀 What Makes This Different?
Unlike basic pivot indicators, the Liquidity Heatmap:
• Institutional Perspective - Shows where smart money hunts stops
• Dynamic Clustering - Automatically groups nearby levels for clarity
• Strength Tracking - Not just where, but HOW MUCH liquidity exists
• Auto-Cleanup - Removes swept and old liquidity automatically
• Visual Clarity - Instant understanding of market structure
• Actionable - Clear targets and reversal zones for trading
• Real-Time Updates - Adapts as market structure evolves
Based On Professional Concepts:
• Order flow analysis
• Market maker behavior
• Institutional trading techniques
• Liquidity engineering principles
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📈 Common Liquidity Patterns
Pattern 1: The Double Sweep
• Price sweeps SSL below, reverses up
• Price sweeps BSL above, reverses down
• Back to original range
• Trading: Fade the second sweep for mean reversion
Pattern 2: The Cascade
• Multiple SSL zones stacked below
• Price sweeps first zone, continues to next
• Chain reaction of stop losses triggering
• Trading: Ride the momentum to lowest zone
Pattern 3: The Fake-Out
• Price approaches liquidity but doesn't quite sweep
• Reverses before hitting the zone
• "Scared money" didn't wait for full sweep
• Trading: Wait for actual sweep, don't anticipate
Pattern 4: The Absorption
• Price sweeps major liquidity zone (strength 5+)
• No reversal, just consolidation
• Institutions absorbed all liquidity
• Trading: Wait for breakout direction, likely continuation
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📈 Upgrade Your Trading Arsenal
This free indicator gives you institutional-level liquidity analysis. Want more?
🔥 Check out my premium scripts for:
• Automated entry signals with liquidity confirmation
• Multi-timeframe liquidity analysis
• Advanced stop loss management that avoids liquidity zones
• Backtested strategies with performance tracking
• Custom alerts for high-probability setups
• And much more...
👉 Visit my profile to see all available tools!
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📝 Important Notes
• Liquidity analysis is one piece of the puzzle - use with other analysis methods
• Not all liquidity zones get swept - some remain untouched
• Market conditions change - adapt your strategy accordingly
• Always use proper position sizing and risk management
• Liquidity sweeps can be violent - use appropriate stop losses
• Practice on demo accounts before trading with real capital
• Past liquidity patterns don't guarantee future price action
Disclaimer: This indicator is for educational purposes. Trading involves risk. Always do your own research and never risk more than you can afford to lose.
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🙏 Support This Work
If you find this indicator valuable:
• ⭐ Give it a thumbs up
• 💬 Share your best liquidity sweep trades in the comments
• 🔔 Follow for more free professional-grade tools
• 🚀 Share with traders who need to understand liquidity
Got questions? Drop a comment and I'll help you master liquidity trading!
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Developed with ❤️ for traders who want to think like institutions
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Version History
• v1.0 - Initial release with dynamic liquidity detection and clustering
Dynamic Support and Resistance with Trend LinesDynamic Support and Resistance with Trend Lines (DSRTL)
1. Introduction & Methodology
The DSRTL indicator is designed to provide a multidimensional analysis of market structure. Unlike traditional tools that rely solely on price pivots, this script combines Static Volume-based Zones with Dynamic Trend Lines to evaluate the price's position relative to critical market components.
The S/R Identification Technique
Instead of standard pivot points, DSRTL utilizes Volume Analysis to highlight areas of significant trader participation:
- Strategy A:
Matrix Climax: Identifies candles within the lookback period that are near price extremes (Highs/Lows) and coincide with significant buying or selling volume.
- Strategy B:
Volume Extremes: Detects candles with the absolute highest buy/sell volumes within the selected lookback window, creating extreme volume-based S/R zones.
- Result:
This creates Support/Resistance (S/R) zones that are validated by actual market activity, not just price geometry.
Dynamic Trend Lines
To complement the static zones, the indicator employs two adaptive channel methods:
- Pivot Span: Connects recent significant pivots for a fast, reactive trend corridor.
- 5-Point Channel: Segments the lookback period into 5 parts to perform a linear regression analysis, creating a stable and statistically significant channel.
2. Volume Calculation Methodology
Accurate S/R detection requires distinguishing Buy Volume from Sell Volume. DSRTL offers two calculation modes:
- Geometry (Source File): Estimates buy/sell volume based on the Close price's position relative to the High/Low of the candle.
Note: This is an approximation that works on all plan types as it does not require intrabar data.
- Intrabar (Precise): Analyzes historical lower-timeframe data (e.g., 15S) to calculate intrabar-based volume deltas with higher precision compared to the geometric method.
Note: This offers superior accuracy. It requires access to historical intrabar data (depending on your plan limits). For the best analytical results, use this mode if available.
3. The Smart Matrix Engine (3D Analysis)
The core of DSRTL is its dashboard, powered by the "Smart Matrix Engine." This engine evaluates the current price in a multi-layer market structure context (Static Volume Zones + Dynamic Channels + Volume Metrics).:
A. S-State (Static): Where is the price relative to the Volume S/R zones?
B. D-State (Dynamic): Where is the price relative to the Trend Channels?
How to read the Matrix Map:
The dashboard displays a 5x5 grid representing 25 possible market scenarios.
- Rows (S1-S5): Represent the Static State (S1=Breakout, S3=Mid-Range, S5=Breakdown).
- Columns (D1-D5): Represent the Dynamic State (D1=Overextended Up, D3=Neutral, D5=Overextended Down).
- Active Cell: Marked with a dot, indicating the specific intersection of price action and market structure.
4. Matrix Interpretations (The 25 Scenarios)
Below is the detailed logic for every possible state displayed on the dashboard, explaining the Title, Bias, and actionable Signal.
Section I: S1 - Static Breakout (Price > Static Resistance)
The price has cleared the static volume resistance zone.
- S1 / D1: HYPER EXTENSION
Bias: Extreme Bullish
Signal: Caution: Exhaustion Risk. Trail stops tight.
- S1 / D2: RESISTANCE CLASH
Bias: Bullish
Signal: Breakout confirmed but facing immediate dynamic resistance.
- S1 / D3: CHANNEL BREAKOUT
Bias: Strong Bullish
Signal: Ideal Trend Continuation. Look to buy dips.
- S1 / D4: SMART PULLBACK
Bias: Bullish (Pullback)
Signal: A pullback occurring after a breakout. Strong buy opportunity.
- S1 / D5: CONFLICT (DIV)
Bias: Conflict/Reversal
Signal: Major Divergence. Static breakout is failing against dynamic structure. High Risk.
Section II: S2 - Inside Static Resistance
The price is currently testing the overhead resistance zone.
- S2 / D1: WEAK SPIKE
Bias: Neutral/Bullish
Signal: Testing resistance, but short-term overextended.
- S2 / D2: IRON FORTRESS (R)
Bias: Rejection Risk
Signal: Double Resistance (Static + Dynamic). High probability of rejection.
- S2 / D3: TESTING RES
Bias: Neutral
Signal: Consolidating at resistance. Wait for a clear break or rejection.
- S2 / D4: COMPRESSION (UP)
Bias: Conflict (Squeeze)
Signal: Squeezed between Static Resistance and Dynamic Support. Volatility imminent.
- S2 / D5: RES vs DOWN-TREND
Bias: Bearish
Signal: Strong downtrend meeting static resistance. Potential Short entry.
Section III: S3 - Mid-Range
The price is floating between significant Static Support and Resistance.
- S3 / D1: OVERBOUGHT RANGE
Bias: Rejection Risk (OB)
Signal: Overextended within the range. Potential fade (short).
- S3 / D2: RANGE HIGH LIMIT
Bias: Neutral/Bearish
Signal: At the top of the dynamic channel. Look for rejection signs.
- S3 / D3: NEUTRAL / CHOPPY
Bias: Neutral
Signal: Dead Center. Low probability environment. Avoid trading.
- S3 / D4: RANGE DIP BUY
Bias: Neutral/Bullish
Signal: At the bottom of the dynamic channel. Look for bounce signs.
- S3 / D5: WEAK RANGE (OS)
Bias: Bounce Risk (OS)
Signal: Oversold within the range. Potential fade (long).
Section IV: S4 - Inside Static Support
The price is currently testing the floor support zone.
- S4 / D1: SUP vs UP-TREND
Bias: Bullish
Signal: Strong uptrend meeting static support. Potential Long entry.
- S4 / D2: COMPRESSION (DN)
Bias: Conflict (Squeeze)
Signal: Squeezed between Static Support and Dynamic Resistance. Volatility imminent.
- S4 / D3: TESTING SUPPORT
Bias: Neutral
Signal: Consolidating at support. Wait for a bounce or breakdown.
- S4 / D4: IRON FLOOR (S)
Bias: Bounce Risk
Signal: Double Support (Static + Dynamic). High probability of a bounce.
- S4 / D5: WEAK DIP
Bias: Neutral/Bearish
Signal: Testing support, but short-term oversold.
Section V: S5 - Static Breakdown (Price < Static Support)
The price has dropped below the static volume support zone.
- S5 / D1: CONFLICT (DIV)
Bias: Conflict/Reversal
Signal: Major Divergence. Static breakdown is failing. High Risk.
- S5 / D2: BEAR PULLBACK
Bias: Bearish (Pullback)
Signal: A pullback occurring after a breakdown. Strong selling opportunity.
- S5 / D3: CHANNEL BREAKDOWN
Bias: Strong Bearish
Signal: Ideal Trend Continuation (Down). Sell rallies.
- S5 / D4: SUPPORT CLASH
Bias: Bearish
Signal: Breakdown confirmed but facing immediate dynamic support.
- S5 / D5: HYPER DROP (VOID)
Bias: Extreme Bearish
Signal: Caution: Climax risk. Trail stops for shorts.
DISCLAIMER & EDUCATIONAL PURPOSE
This indicator is strictly an educational tool designed to visualize complex market structure concepts. Its primary purpose is to help traders "bridge the gap" between academic theory and real-time market behavior by providing a visual representation of support, resistance, and volume dynamics.
Please Note:
1. Not a Trading Strategy: This script is an analytical assistant, not a standalone "Black Box" trading system. It does not generate buy or sell signals that should be followed blindly.
2. No Financial Advice: The data provided by this tool is for informational purposes only. It is not a recommendation to buy or sell any asset.
3. Risk Warning: Trading involves significant risk. Always use your own judgment, perform your own technical analysis, and use proper risk management. Do not use this tool as the sole basis for your trading decisions.
4. Data Precision & Platform Limits: The "Intrabar (Precise)" calculation mode relies on high-resolution historical data to provide exact results. Access to this specific data depth depends entirely on your platform's subscription capabilities. If your plan does not support this level of historical intrabar data, the Precise mode may have limited coverage. In that case, you should switch to "Geometry" mode for a fully populated view.
Accumulation And Distribution Zones (Zeiierman)█ Overview
Accumulation And Distribution Zones (Zeiierman) is a structural zone indicator that highlights where the market has recently been absorbing sell pressure (Accumulation) or releasing buy pressure (Distribution).
The indicator tracks a refined sequence of swing highs and lows and measures how these swings tighten, expand, or step directionally. When they form staircase-style structures such as higher lows with compressing highs for Accumulation or lower highs with compressing lows for Distribution, the script marks these areas as shifts in market control.
Once the full pattern completes, the indicator converts it into an Accumulation or Distribution zone. Each zone is based on a confirmed structural sequence rather than a single point, making it more reliable and reflective of actual market behavior.
The indicator can also display a mini-volume profile within each zone and extend POC levels forward, showing where trading activity clustered most. Combined, these features reveal areas where price has recently shown acceptance, absorption, or rejection, helping you understand whether current price action is reacting to, breaking from, or retesting these important structural regions.
█ How It Works
⚪ Swing Structure
The indicator builds its foundation by detecting swing highs and lows using a configurable Swing Detection Window. Each confirmed swing is stored with its price, time, bar index, and direction. If two consecutive swings share the same direction, only the more extreme one is kept. This produces a clean structural sequence that removes noise and keeps only meaningful turning points.
⚪ Accumulation vs Distribution Pattern Logic
Using the refined swing sequence, the script looks for staircase-style formations that signal shifts in control:
Accumulation (bottoming): higher lows combined with compressing highs.
Distribution (topping): lower highs combined with compressing lows.
Two detection modes are available:
Quick for compact 4-swing formations
Slow for broader 6-swing structures
When a full structural pattern completes, the indicator marks the zone and resets the swing buffer for the next formation.
⚪ Volume Profile Construction
The price range between the zone’s upper and lower boundary is divided into several Rows. For every bar within the zone’s swing range, the bar’s volume is added to the appropriate price row.
Volume is classified as:
Bullish volume when close > open
Bearish volume when close < open
Each row is drawn as two horizontal segments (bull and bear), colored with smooth gradients based on your bull/bear color settings. This creates a compact profile that reveals where trading activity is concentrated inside the zone and whether buyers or sellers dominate those price levels.
█ How to Use
The indicator is designed to provide context and confluence, not raw buy/sell signals.
⚪ Spot Fresh Accumulation & Distribution
Use newly printed zones as a map of where the market has recently:
Absorbed selling and formed a floor (Accumulation below price).
Absorbed buying and formed a cap (Distribution above price).
In a trending environment, fresh accumulation zones below price are often areas to watch for pullbacks, while distribution zones above price can act as sell zones or targets.
⚪ Volume Profile
Longer horizontal bars show where the market traded the most volume inside the zone.
Bull-leaning rows inside an accumulation zone often signal strong buying interest during the formation.
Bear-leaning rows inside a distribution zone highlight concentrated selling pressure.
By combining this volume distribution with the zone label and the broader trend context, you can judge whether the structure is more likely to hold, break, or retest as the price approaches it again.
⚪ POC (Point of Control) Trading
Extended POC zones (Regular or Faded) can be treated as dynamic support/resistance rails:
When price revisits a prior accumulation POC and rejects it from above, the level may act as support. When price retests a distribution POC from below and fails to break through, it can act as resistance.
⚪ Combine with Your Own Strategy
The script does not decide direction for you. You get the most value by combining it with:
Your own trend filters (moving averages, higher timeframe structure, volatility measures).
Your preferred entry models (reversal candles, momentum breaks, liquidity grabs, etc.).
Higher-timeframe mapping.
Think of this tool as a map of where the market did meaningful business. You decide how to trade around those areas.
█ Settings
Acc/Dist Ranges – Master switch for drawing all Accumulation and Distribution zones. Turn this off to temporarily hide boxes while leaving supporting logic active.
Pattern – Shows or hides the swing-based pattern outline that formed each zone. Good for structural debugging and education.
Pattern Sensitivity
Quick – more responsive, detects smaller compact structures.
Slow – stricter, focuses on wider and more established zones.
Swing Detection Window – Pivot width used to confirm swing highs and lows. Larger values filter noise and produce bigger zones; smaller values pick up more minor structures.
Volume Profile – Enables the embedded volume profile inside each zone.
Rows – Number of price slices used to aggregate volume in the zone. Higher values give more detail but increase visual density.
Switch Order – Flips the horizontal order of bull vs bear volume segments within each row.
Extend Zones – Behaviour of POC and zone extension:
None – No forward extension.
Faded Zones – Store and draw up to four past POC zones as faded horizontal levels.
Regular Zones – Extend POC boxes forward until price breaks out.
-----------------
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.
TradeBeard Larry Williams A/D + Classic DivergenceName: TradeBeard – Larry Williams A/D + Classic Divergence
What it does:
This indicator plots a classic Larry Williams Accumulation/Distribution (A/D) line, using:
(Close−Open)/(High−Low)×Volume
It then looks at price swings vs. A/D swings and marks true Larry-style divergences:
Bull Div – Price makes a lower low, but the A/D line makes a higher low → buying pressure/accumulation.
Bear Div – Price makes a higher high, but the A/D line makes a lower high → selling pressure/distribution.
Lines are drawn between the two pivots on the A/D line, with a label at the most recent pivot.
How to use / read it:
Use on any timeframe; the logic is the same.
Look for Bull Div near potential bottoms as confirmation that smart money is quietly buying.
Look for Bear Div near potential tops as confirmation that smart money is unloading.
Settings:
Pivot left bars (price) / Pivot right bars (price)
Controls how “wide” a swing high/low must be.
1 / 1 ≈ very sensitive (ICT/Larry-style 3-bar swings).
Higher values = fewer but cleaner swings and fewer signals.
Show bullish divergences / Show bearish divergences
Turn each signal type on or off.
Bullish color (line + label) / Bearish color (line + label)
Color of the divergence lines and label background.
Bullish label text color / Bearish label text color
Text color inside the Bull Div / Bear Div labels.
That’s it: pure Larry Williams A/D flow, price-based pivots, and clean visual divergence signals, wrapped in a TradeBeard skin.
I hope this will help you in your trading.
// Disclaimer:
// This script is for educational and informational purposes only.
// Trading and investing involve risk. You are fully responsible for your own decisions,
RED-E Gamma Range DetectorRED-E Gamma Range Detector
Overview
The RED-E Gamma Range Detector identifies key support and resistance zones based on recent price action and volume distribution, combined with a simple momentum ribbon to help traders visualize trend direction. It's designed to highlight potential areas where price may react, inspired by the concept of gamma exposure levels in options trading.
How It Works
1. Support & Resistance Zones (Green & Red Boxes)
RED-E analyzes the recent price range over a customizable lookback period
It identifies high-probability support levels (green boxes) below current price
It identifies high-probability resistance levels (red boxes) above current price
These zones represent areas where price has historically shown increased activity
2. Gamma Flip Level (Yellow Dashed Line)
The yellow line represents the approximate "gamma flip" - the midpoint of the recent range
Above this line: Price tends to be more stable with range-bound behavior
Below this line: Price tends to be more volatile with trending behavior
This level acts as a key pivot point for market structure
3. Momentum Ribbon (Green/Red Fill)
A simple visual indicator using 9 and 21 period EMAs
Green ribbon: 9 EMA is above 21 EMA (bullish momentum)
Red ribbon: 9 EMA is below 21 EMA (bearish momentum)
Ribbon width shows strength of trend (wider = stronger trend)
How to Use
For Range Trading:
Look for buy signals near green support zones when above gamma flip
Look for sell signals near red resistance zones when above gamma flip
Price tends to bounce between zones in stable conditions
For Trend Trading:
Watch for breakouts above resistance or below support zones
Use the momentum ribbon to confirm trend direction
Wider ribbon gaps indicate stronger directional moves
For Risk Management:
Use support/resistance zones for stop-loss placement
Recognize increased volatility potential below the gamma flip
Adjust position sizing based on your proximity to key zones
Settings
Lookback Period: Number of bars to analyze (default: 20)
Lower values = more responsive to recent price action
Higher values = more stable, longer-term levels
Best Practices
Works best on liquid instruments (major stocks, indices, forex pairs)
Combine with other technical analysis tools for confirmation
Most effective on 1H, 4H, and daily timeframes
Always use proper risk management and stop losses
Why "RED-E"?
RED-E stands for being Ready to identify critical gamma levels, support/resistance zones, and momentum shifts - keeping you prepared for market moves before they happen.
Educational Note
This indicator approximates gamma exposure concepts using price and volume analysis. It does not use actual options data. The term "gamma" refers to the rate of change in options delta and how market makers hedge their positions, which can create support/resistance at certain price levels.
Disclaimer
This indicator is for educational and informational purposes only. It does not guarantee profitable trades. Past performance is not indicative of future results. Always conduct your own analysis and manage risk appropriately. Trading involves substantial risk of loss.
Recommended Categories
Primary Category:
✅ Support and Resistance
Secondary Categories:
✅ Momentum
✅ Trend Analysis
✅ Volatility
God of Scalping BTCUnleash divine precision in the chaotic realm of BTC scalping with the God of Scalping BTC—a bespoke, price-action powerhouse crafted for lightning-fast entries and exits on 1-5 minute charts. Forged from raw momentum velocity (no recycled RSI or MACD here), this indicator detects micro-trend accelerations to pinpoint surge moments where BTC's volatility bends to your will.Core Mechanics:Velocity Engine: Calculates fast (default: 3-bar) and slow (default: 8-bar) price speeds, then derives normalized acceleration using ATR (14-bar) to filter noise in BTC's wild swings.
Surge Detection: Smoothed signal line confirms crossovers—bullish when acceleration surges above signal with positive bias; bearish on the downside.
Volume Guardian: Triggers only on 20%+ volume spikes above its EMA (10-bar), ensuring conviction behind the chaos.
Visual Oracle:Blue/Red Lines: Fast (EMA close, 3-bar) and slow (EMA close, 8-bar) velocity trends for trend context.
Background Glow: Subtle green/red tint for real-time momentum bias.
Divine Arrows: Green triangles below bars for BUY surges; red above for SELL—your scalp signals from the heavens.
Scalping Ritual:Optimal Altar: Load on BTCUSD/USDT (1m-5m). Tune lengths for your broker's feed.
Invocation: Enter long on green arrow (target 0.1-0.3% gains), short on red. Tight stops at recent swings; exit on opposite signal or threshold breach (1.5x mult).
Alerts: Built-in notifications—"God Surge Buy: BTC Scalp Entry!"—to summon you mid-prayer (er, trade).
Backtested for BTC's fury, this isn't a holy grail, but a scalper's Excalibur: pure, adaptive, and unyielding. Trade wisely—markets are mortal, your edge is eternal.
Accumulation Distribution LineThis indicator provides an implementation of the classic Accumulation/Distribution Line (ADL). It enhances the standard indicator with a built-in divergence detection engine.
Key Features:
Full Divergence Suite (Class A, B, C): The primary feature is the integrated divergence engine. It automatically detects and plots all three major types of divergences:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise, leading to more robust signals.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the ADL level of the confirming pivot.
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF ADL Line: The ADL line itself can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 12 comprehensive alerts that trigger on the start and end of all 6 divergence types (e.g., "Regular Bullish Started", "Regular Bullish Ended").
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
MTF K-Means Price Regimes [matteovesperi] ⚠️ The preview uses a custom example to identify support/resistance zones. due to the fact that this identifier clusterizes, this is possible. this example was set up "in a hurry", therefore it has a possible inaccuracy. When setting up the indicator, it is extremely important to select the correct parameters and double-check them on the selected history.
📊 OVERVIEW
Purpose
MTF K-Means Price Regimes is a TradingView indicator that automatically identifies and classifies the current market regime based on the K-Means machine learning algorithm. The indicator uses data from a higher timeframe (Multi-TimeFrame, MTF) to build stable classification and applies it to the working timeframe in real-time.
Key Features
✅ Automatic market regime detection — the algorithm finds clusters of similar market conditions
✅ Multi-timeframe (MTF) — clustering on higher TF, application on lower TF
✅ Adaptive — model recalculates when a new HTF bar appears with a rolling window
✅ Non-Repainting — classification is performed only on closed bars
✅ Visualization — bar coloring + information panel with cluster characteristics
✅ Flexible settings — from 2 to 10 clusters, customizable feature periods, HTF selection
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🔬 TECHNICAL DETAILS
K-Means Clustering Algorithm
What is K-Means?
K-Means is one of the most popular clustering algorithms (unsupervised machine learning). It divides a dataset into K groups (clusters) so that similar elements are within each cluster, and different elements are between clusters.
Algorithm objective:
Minimize within-cluster variance (sum of squared distances from points to their cluster center).
How Does K-Means Work in Our Indicator?
Step 1: Data Collection
The indicator accumulates history from the higher timeframe (HTF):
RSI (Relative Strength Index) — overbought/oversold indicator
ATR% (Average True Range as % of price) — volatility indicator
ΔP% (Price Change in %) — trend strength and direction indicator
By default, 200 HTF bars are accumulated (clusterLookback parameter).
Step 2: Creating Feature Vectors
Each HTF bar is described by a three-dimensional vector:
Vector =
Step 3: Normalization (Z-Score)
All features are normalized to bring them to a common scale:
Normalized_Value = (Value - Mean) / StdDev
This is critically important, as RSI is in the range 0-100, while ATR% and ΔP% have different scales. Without normalization, one feature would dominate over others.
Step 4: K-Means++ Centroid Initialization
Instead of random selection of K initial centers, an improved K-Means++ method is used:
First centroid is randomly selected from the data
Each subsequent centroid is selected with probability proportional to the square of the distance to the nearest already selected centroid
This ensures better initial centroid distribution and faster convergence
Step 5: Iterative Optimization (Lloyd's Algorithm)
Repeat until convergence (or maxIterations):
1. Assignment step:
For each point find the nearest centroid and assign it to this cluster
2. Update step:
Recalculate centroids as the average of all points in each cluster
3. Convergence check:
If centroids shifted less than 0.001 → STOP
Euclidean distance in 3D space is used:
Distance = sqrt((RSI1 - RSI2)² + (ATR1 - ATR2)² + (ΔP1 - ΔP2)²)
Step 6: Adaptive Update
With each new HTF bar:
The oldest bar is removed from history (rolling window method)
New bar is added to history
K-Means algorithm is executed again on updated data
Model remains relevant for current market conditions
Real-Time Classification
After building the model (clusters + centroids), the indicator works in classification mode:
On each closed bar of the current timeframe, RSI, ATR%, ΔP% are calculated
Feature vector is normalized using HTF statistics (Mean/StdDev)
Distance to all K centroids is calculated
Bar is assigned to the cluster with minimum distance
Bar is colored with the corresponding cluster color
Important: Classification occurs only on a closed bar (barstate.isconfirmed), which guarantees no repainting .
Data Architecture
Persistent variables (var):
├── featureVectors - Normalized HTF feature vectors
├── centroids - Cluster center coordinates (K * 3 values)
├── assignments - Assignment of each HTF bar to a cluster
├── htfRsiHistory - History of RSI values from HTF
├── htfAtrHistory - History of ATR values from HTF
├── htfPcHistory - History of price changes from HTF
├── htfCloseHistory - History of close prices from HTF
├── htfRsiMean, htfRsiStd - Statistics for RSI normalization
├── htfAtrMean, htfAtrStd - Statistics for ATR normalization
├── htfPcMean, htfPcStd - Statistics for Price Change normalization
├── isCalculated - Model readiness flag
└── currentCluster - Current active cluster
All arrays are synchronized and updated atomically when a new HTF bar appears.
Computational Complexity
Data collection: O(1) per bar
K-Means (one pass):
- Assignment: O(N * K) where N = number of points, K = number of clusters
- Update: O(N * K)
- Total: O(N * K * I) where I = number of iterations (usually 5-20)
Example: With N=200 HTF bars, K=5 clusters, I=20 iterations:
200 * 5 * 20 = 20,000 operations (executes quickly)
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📖 USER GUIDE
Quick Start
1. Adding the Indicator
TradingView → Indicators → Favorites → MTF K-Means Price Regimes
Or copy the code from mtf_kmeans_price_regimes.pine into Pine Editor.
2. First Launch
When adding the indicator to the chart, you'll see a table in the upper right corner:
┌─────────────────────────┐
│ Status │ Collecting HTF │
├─────────────────────────┤
│ Collected│ 15 / 50 │
└─────────────────────────┘
This means the indicator is accumulating history from the higher timeframe. Wait until the counter reaches the minimum (default 50 bars for K=5).
3. Active Operation
After data collection is complete, the main table with cluster information will appear:
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
The arrow ► indicates the current active regime. Chart bars are colored with the corresponding cluster color.
Customizing for Your Strategy
Choosing Higher Timeframe (HTF)
Rule: HTF should be at least 4 times higher than the working timeframe.
| Working TF | Recommended HTF |
|------------|-----------------|
| 1 min | 15 min - 1H |
| 5 min | 1H - 4H |
| 15 min | 4H - D |
| 1H | D - W |
| 4H | D - W |
| D | W - M |
HTF Selection Effect:
Lower HTF (closer to working TF): More sensitive, frequently changing classification
Higher HTF (much larger than working TF): More stable, long-term regime assessment
Number of Clusters (K)
K = 2-3: Rough division (e.g., "uptrend", "downtrend", "flat")
K = 4-5: Optimal for most cases (DEFAULT: 5)
K = 6-8: Detailed segmentation (requires more data)
K = 9-10: Very fine division (only for long-term analysis with large windows)
Important constraint:
clusterLookback ≥ numClusters * 10
I.e., for K=5 you need at least 50 HTF bars, for K=10 — at least 100 bars.
Clustering Depth (clusterLookback)
This is the rolling window size for building the model.
50-100 HTF bars: Fast adaptation to market changes
200 HTF bars: Optimal balance (DEFAULT)
500-1000 HTF bars: Long-term, stable model
If you get an "Insufficient data" error:
Decrease clusterLookback
Or select a lower HTF (e.g., "4H" instead of "D")
Or decrease numClusters
Color Scheme
Default 10 colors:
Red → Often: strong bearish, high volatility
Orange → Transition, medium volatility
Yellow → Neutral, decreasing activity
Green → Often: strong bullish, high volatility
Blue → Medium bullish, medium volatility
Purple → Oversold, possible reversal
Fuchsia → Overbought, possible reversal
Lime → Strong upward momentum
Aqua → Consolidation, low volatility
White → Undefined regime (rare)
Important: Cluster colors are assigned randomly at each model recalculation! Don't rely on "red = bearish". Instead, look at the description in the table (RSI, ATR%, ΔP%).
You can customize colors in the "Colors" settings section.
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⚙️ INDICATOR PARAMETERS
Main Parameters
Higher Timeframe (htf)
Type: Timeframe selection
Default: "D" (daily)
Description: Timeframe on which the clustering model is built
Recommendation: At least 4 times larger than your working TF
Clustering Depth (clusterLookback)
Type: Integer
Range: 50 - 2000
Default: 200
Description: Number of HTF bars for building the model (rolling window size)
Recommendation:
- Increase for more stable long-term model
- Decrease for fast adaptation or if there's insufficient historical data
Number of Clusters (K) (numClusters)
Type: Integer
Range: 2 - 10
Default: 5
Description: Number of market regimes the algorithm will identify
Recommendation:
- K=3-4 for simple strategies (trending/ranging)
- K=5-6 for universal strategies
- K=7-10 only when clusterLookback ≥ 100*K
Max K-Means Iterations (maxIterations)
Type: Integer
Range: 5 - 50
Default: 20
Description: Maximum number of algorithm iterations
Recommendation:
- 10-20 is sufficient for most cases
- Increase to 30-50 if using K > 7
Feature Parameters
RSI Period (rsiLength)
Type: Integer
Default: 14
Description: Period for RSI calculation (overbought/oversold feature)
Recommendation:
- 14 — standard
- 7-10 — more sensitive
- 20-25 — more smoothed
ATR Period (atrLength)
Type: Integer
Default: 14
Description: Period for ATR calculation (volatility feature)
Recommendation: Usually kept equal to rsiLength
Price Change Period (pcLength)
Type: Integer
Default: 5
Description: Period for percentage price change calculation (trend feature)
Recommendation:
- 3-5 — short-term trend
- 10-20 — medium-term trend
Visualization
Show Info Panel (showDashboard)
Type: Checkbox
Default: true
Description: Enables/disables the information table on the chart
Cluster Color 1-10
Type: Color selection
Description: Customize colors for visual cluster distinction
Recommendation: Use contrasting colors for better readability
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📊 INTERPRETING RESULTS
Reading the Information Table
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
│ 4 │ 45.0 │ 1.20 │ -0.3 │ Low Vol,Bear │ │
│ 5 │ 72.1 │ 3.05 │ 2.8 │ High Vol,Bull│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
"ID" Column
Cluster number (1-K). Order doesn't matter.
"RSI" Column
Average RSI value in the cluster (0-100):
< 30: Oversold zone
30-45: Bearish sentiment
45-55: Neutral zone
55-70: Bullish sentiment
> 70: Overbought zone
"ATR%" Column
Average volatility in the cluster (as % of price):
< 1%: Low volatility (consolidation, narrow range)
1-2%: Normal volatility
2-3%: Elevated volatility
> 3%: High volatility (strong movements, impulses)
Compared to the average volatility across all clusters to determine "High Vol" or "Low Vol".
"ΔP%" Column
Average price change in the cluster (in % over pcLength period):
> +0.05%: Bullish regime
-0.05% ... +0.05%: Flat (sideways movement)
< -0.05%: Bearish regime
"Description" Column
Automatic interpretation:
"High Vol, Bull" → Strong upward momentum, high activity
"Low Vol, Flat" → Consolidation, narrow range, uncertainty
"High Vol, Bear" → Strong decline, panic, high activity
"Low Vol, Bull" → Slow growth, low activity
"Low Vol, Bear" → Slow decline, low activity
"Current" Column
Arrow ► shows which cluster the last closed bar of your working timeframe is in.
Typical Cluster Patterns
Example 1: Trend/Flat Division (K=3)
Cluster 1: RSI=65, ATR%=2.5, ΔP%=+1.5 → Bullish trend
Cluster 2: RSI=50, ATR%=0.8, ΔP%=0.0 → Flat/Consolidation
Cluster 3: RSI=35, ATR%=2.3, ΔP%=-1.4 → Bearish trend
Strategy: Open positions when regime changes Flat → Trend, avoid flat.
Example 2: Volatility Breakdown (K=5)
Cluster 1: RSI=72, ATR%=3.5, ΔP%=+2.5 → Strong bullish impulse (high risk)
Cluster 2: RSI=60, ATR%=1.5, ΔP%=+0.8 → Moderate bullish (optimal entry point)
Cluster 3: RSI=50, ATR%=0.7, ΔP%=0.0 → Flat
Cluster 4: RSI=40, ATR%=1.4, ΔP%=-0.7 → Moderate bearish
Cluster 5: RSI=28, ATR%=3.2, ΔP%=-2.3 → Strong bearish impulse (panic)
Strategy: Enter in Cluster 2 or 4, avoid extremes (1, 5).
Example 3: Mixed Regimes (K=7+)
With large K, clusters can represent condition combinations:
High RSI + Low volatility → "Quiet overbought"
Neutral RSI + High volatility → "Uncertainty with high activity"
Etc.
Requires individual analysis of each cluster.
Regime Changes
Important signal: Transition from one cluster to another!
Trading situation examples:
Flat → Bullish trend → Buy signal
Bullish trend → Flat → Take profit, close longs
Flat → Bearish trend → Sell signal
Bearish trend → Flat → Close shorts, wait
You can build a trading system based on the current active cluster and transitions between them.
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💡 USAGE EXAMPLES
Example 1: Scalping with HTF Filter
Task: Scalping on 5-minute charts, but only enter in the direction of the daily regime.
Settings:
Working TF: 5 min
HTF: D (daily)
K: 3 (simple division)
clusterLookback: 100
Logic:
IF current cluster = "Bullish" (ΔP% > 0.5)
→ Look for long entry points on 5M
IF current cluster = "Bearish" (ΔP% < -0.5)
→ Look for short entry points on 5M
IF current cluster = "Flat"
→ Don't trade / reduce risk
Example 2: Swing Trading with Volatility Filtering
Task: Swing trading on 4H, enter only in regimes with medium volatility.
Settings:
Working TF: 4H
HTF: D (daily)
K: 5
clusterLookback: 200
Logic:
Allowed clusters for entry:
- ATR% from 1.5% to 2.5% (not too quiet, not too chaotic)
- ΔP% with clear direction (|ΔP%| > 0.5)
Prohibited clusters:
- ATR% > 3% → Too risky (possible gaps, sharp reversals)
- ATR% < 1% → Too quiet (small movements, commissions eat profit)
Example 3: Portfolio Rotation
Task: Managing a portfolio of multiple assets, allocate capital depending on regimes.
Settings:
Working TF: D (daily)
HTF: W (weekly)
K: 4
clusterLookback: 100
Logic:
For each asset in portfolio:
IF regime = "Strong trend + Low volatility"
→ Increase asset weight in portfolio (40-50%)
IF regime = "Medium trend + Medium volatility"
→ Standard weight (20-30%)
IF regime = "Flat" or "High volatility without trend"
→ Minimum weight or exclude (0-10%)
Example 4: Combining with Other Indicators
MTF K-Means as a filter:
Main strategy: MA Crossover
Filter: MTF K-Means on higher TF
Rule:
IF MA_fast > MA_slow AND Cluster = "Bullish regime"
→ LONG
IF MA_fast < MA_slow AND Cluster = "Bearish regime"
→ SHORT
ELSE
→ Don't trade (regime doesn't confirm signal)
This dramatically reduces false signals in unsuitable market conditions.
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📈 OPTIMIZATION RECOMMENDATIONS
Optimal Settings for Different Styles
Day Trading
Working TF: 5M - 15M
HTF: 1H - 4H
numClusters: 4-5
clusterLookback: 100-150
Swing Trading
Working TF: 1H - 4H
HTF: D
numClusters: 5-6
clusterLookback: 150-250
Position Trading
Working TF: D
HTF: W - M
numClusters: 4-5
clusterLookback: 100-200
Scalping
Working TF: 1M - 5M
HTF: 15M - 1H
numClusters: 3-4
clusterLookback: 50-100
Backtesting
To evaluate effectiveness:
Load historical data (minimum 2x clusterLookback HTF bars)
Apply the indicator with your settings
Study cluster change history:
- Do changes coincide with actual trend transitions?
- How often do false signals occur?
Optimize parameters:
- If too much noise → increase HTF or clusterLookback
- If reaction too slow → decrease HTF or increase numClusters
Combining with Other Techniques
Regime-Based Approach:
MTF K-Means (regime identification)
↓
+---+---+---+
| | | |
v v v v
Trend Flat High_Vol Low_Vol
↓ ↓ ↓ ↓
Strategy_A Strategy_B Don't_trade
Examples:
Trend: Use trend-following strategies (MA crossover, Breakout)
Flat: Use mean-reversion strategies (RSI, Bollinger Bands)
High volatility: Reduce position sizes, widen stops
Low volatility: Expect breakout, don't open positions inside range
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📞 SUPPORT
Report an Issue
If you found a bug or have a suggestion for improvement:
Describe the problem in as much detail as possible
Specify your indicator settings
Attach a screenshot (if possible)
Specify the asset and timeframe where the problem is observed
Dollar Volume Ownership Gauge Dollar Volume Ownership Gauge (DVOG)
By: Mando4_27
Version: 1.0 — Pine Script® v6
Overview
The Dollar Volume Ownership Gauge (DVOG) is designed to measure the intensity of real money participation behind each price bar.
Instead of tracking raw share volume, this tool converts every bar’s trading activity into dollar volume (price × volume) and highlights the transition points where institutional capital begins to take control of a move.
DVOG’s mission is simple:
Show when the crowd is trading vs. when the institutions are buying control.
Core Concept
Most retail traders focus on share count (volume) — but institutions think in dollar exposure.
A small-cap printing a 1-million-share candle at $1 is very different from a 1-million-share candle at $10.
DVOG normalizes this by displaying total traded dollar value per bar, then color-codes and alerts when the volume of money crosses key thresholds.
This exposes the exact moments when ownership is shifting — often before major breakouts, reclaims, or exhaustion reversals.
How It Works
Dollar Volume Calculation
Each candle’s dollar volume is computed as close × volume.
Data is aggregated from the 5-minute timeframe regardless of your current chart, allowing consistent institutional-flow detection on any resolution.
Threshold Logic
Two customizable levels define interest zones:
$500K Threshold → Early or moderate institutional attention.
$1M Threshold → High-conviction or aggressive accumulation.
Both levels can be edited to fit different market caps or trading styles.
Bar Coloring Scheme
Red = Dollar Volume ≥ $1,000,000 → Significant institutional activity / control bar.
Green = Dollar Volume ≥ $500,000 and < $1,000,000 → Emerging accumulation / transition bar.
Black = Below $500,000 → Retail or low-interest zone.
(Colors are intentionally inverted from standard expectation: when volume intensity spikes, the bar turns hotter in tone.)
Plot Display
Histogram style plot displays 5-minute aggregated dollar volume per bar.
Dotted reference lines mark $500K and $1M levels, with live right-hand labels for quick reading.
Optional debug label shows current bar’s dollar value, closing price, and raw volume for transparency.
Alerts & Conditions
DVOG includes three alert triggers for hands-off monitoring:
Alert Name Trigger Message Purpose
Green Bar Alert – Dollar Volume ≥ $500K When dollar volume first crosses $500K “Institutional interest starting on ” Signals early money entering.
Dollar Volume ≥ $500K Same as above, configurable “Early institutional interest detected…” Broad alert option.
Dollar Volume ≥ $1M When dollar volume first crosses $1M “Significant money flow detected…” Indicates heavy institutional presence or ignition bar.
You can enable or disable alerts via checkbox inputs, allowing you to monitor just the levels that fit your style.
Interpretation & Use Cases
Identify Institutional “Ignition” Points:
Watch for sudden green or red DVOG bars after long low-volume consolidation — these often precede explosive continuation moves.
Confirm Breakouts & Reclaims:
If price reclaims a key level (HOD, neckline, or coil top) and DVOG flashes green/red, odds strongly favor follow-through.
Spot Trap Exhaustion:
After a flush or low-volume fade, the first strong green/red DVOG bar can mark the institutional reclaim — the moment retail control ends.
Filter Noise:
Ignore standard volume spikes. DVOG only reacts when dollar ownership materially changes hands, not when small traders churn shares.
Customization
Setting Default Description
$500K Threshold 500,000 Lower limit for “Green” institutional attention.
$1M Threshold 1,000,000 Upper limit for “Red” heavy institutional control.
Show Alerts ✅ Enable or disable global alerts.
Alert on Green Bars ✅ Toggle only the $500K crossover alerts.
Adjust thresholds to match the liquidity of your preferred tickers — for example, micro-caps may use $100K/$300K, while large-caps might use $5M/$20M.
Reading the Output
Black baseline = Noise / retail chop.
First Green bar = Smart money starts building position.
Red bar(s) = Ownership shift confirmed — institutions active.
Flat-to-rising pattern in DVOG = Sustained accumulation; often aligns with strong trend continuation.
Summary
DVOG transforms raw volume into actionable context — showing you when capital, not hype, is moving.
It’s particularly effective for:
Momentum and breakout traders
Liquidity trap reclaims (Kuiper-style setups)
Identifying early ignition bars before halts
Confirming frontside strength in micro-caps
Use DVOG as your ownership radar — the visual cue for when the market stops being retail and starts being real.
Liquidity Zones - Joe v1This script lets you plot liquidity/order levels (similar to what you see on Bookmap) directly on your TradingView chart.
It is designed to help traders spot support/resistance levels where large limit orders sit and to visualize whether those liquidity pools are still active, already taken, or being replenished.
Key Features
Session-based
Works during a defined trading session.
Resets automatically at the first bar of the session.
Up to 8 Liquidity Zones, each of which includes:
Price level
Size (affects line thickness)
Status (Active, Taken, Re-Stocking, or Automatic).
Zone Statuses
Active → Untouched liquidity (potential support/resistance).
Taken → Liquidity consumed after price trades through it.
Re-Stocking → Level is being reloaded with fresh orders.
Automatic → Updates dynamically (switches to Taken when crossed, otherwise stays Active).
Visual Representation
Zones are drawn as horizontal lines.
Labels show price + size (e.g., 4010 (200k)).
Customizable line styles and colors:
Active = solid red
Taken = gray dashed
Re-Stocking = purple dotted
Dynamic Updates
Levels automatically update during the session.
If price crosses a zone → it’s marked as Taken.
Labels, line styles, and colors adjust live.
Line thickness = zone size ÷ 10 → visually represents liquidity strength.
How this indicator is Used
Upon market open, the order book tends to fill with limit orders. Using Bookmap, you can see where these orders are placed at each relative price point, along with their sizes. The most important ones to focus on are the larger levels, which are typically highlighted in reddish tones (depending on your Bookmap settings).
I then manually enter these levels into this indicator. It only takes a few seconds, and since there’s no direct way to connect TradingView to Bookmap, this method works as an effective workaround. Once entered, the levels will stay visible on your TradingView chart.
This seemingly simple script is very powerful and provides a strong edge. More often than not, price action gravitates toward these larger liquidity levels. Remember, the price of a security is influenced by market makers whose role is to fill orders and earn commissions on transactions. They have little interest in arbitrarily pushing price higher or lower; instead, their primary function is to guide price toward liquidity—where the large orders sit.
Of course, this is a general principle, and many other variables can affect price movement. Still, by keeping this concept in mind, you’ll often find yourself on the right side of the market.
Edge Algo
EDGE ALGO is a trend-following and momentum-based algorithm designed to deliver precise Buy and Sell signals with built-in risk management through dynamic Take Profit and Stop Loss levels.
This invite-only tool was created to assist traders in identifying high-probability trade setups while filtering out market noise and avoiding choppy price action.
🧠 How It Works
Edge Algo combines multiple layers of logic to increase the quality of trade signals:
1. Trend Detection
* A dynamic ATR-based channel determines when the price breaks out in a new direction.
* The trend flips to Bullish or Bearish when price action crosses the adaptive channel, avoiding late entries.
2. Momentum Confirmation
* Custom logic involving RSI (Relative Strength Index) and CMO (Chande Momentum Oscillator) helps filter fake signals.
* Buy conditions require RSI to be under 25 and CMO to confirm upward momentum.
* Sell conditions require RSI to be over 75 and CMO to confirm downward momentum.
3. Support/Resistance Pivot Zones
* Recent highs/lows are used as confirmation points to strengthen entries around key price levels.
4. Entry Logic
* When trend change + momentum filter + pivot confirmation align, the script generates a Buy or Sell signal.
* Each signal is clearly displayed on the chart with custom labels.
🎯 Risk Management (SL/TP Logic)
For every valid entry, the script automatically calculates:
✅ Stop Loss (SL) based on a user-defined percentage
✅Take Profit 1 (TP1) at 1R
✅ Take Profit 2 (TP2) at 2R
✅ Take Profit 3 (TP3) at 3R
This allows traders to follow a consistent risk-to-reward ratio and manage trades using partial exits or full closes at target levels.
📊 Visualization Features
* Optional Cloud Moving Average to visually represent market direction
*Buy/Sell labels on chart with clean styling
* Clearly marked Entry, TP1, TP2, TP3, SL levels
* Real-time alerts for Buy and Sell signals
* Fully customizable styling (colors, cloud, labels, etc.)
⚙️ Best Use Cases
* Timeframes: optimized for 15min to 4H charts
* Pairs: works with Forex, Crypto, Indices, Commodities, and Stocks
* Styles: suitable for scalping, intraday trading, and swing trading
🔒 Why Invite-Only?
Edge Algo PRO contains proprietary logic developed specifically for real-time application with an edge in volatile markets.
To protect the intellectual property and ensure quality use, access is granted only upon request.
Lakshmi - Vajra Energy Signal (VES)Vajra Energy Signal (VES) is an advanced volume analysis indicator that detects energy accumulated inside the market.
When assessing the strength of trading activity, conventional practice looks at the magnitude of volume; VES is designed with the understanding that the same volume can have different meanings depending on the price range.
VES analyzes the complex relationship between price movement and volume with a proprietary algorithm and can detect internal market activities that are invisible from surface‑level price action, visualizing the characteristic whereby the value rises before a breakout.
In other words, VES views the market as an “energy system.” In the energy accumulation phase, relatively high volume occurs relative to the price range, and in the energy release phase, the stored energy is emitted as high volatility in price, that is, a breakout—this is the core concept on which VES is established.
⚡️ Basic Demonstration
i.imgur.com
As you can see in the image above, VES simply displays the highs and lows of energy stored in the market as a thin line in a separate panel.
It is easy for traders to understand its intuitive patterns: it rises when hidden buying accumulation or selling activity continue and sink when a price breakout occurs. It can be applied across symbols and markets (stocks, commodities, cryptocurrencies, spot, and futures). While reducing clutter in price scale labels, it also supports dynamic autoscaling.
⚡️ Practical Usage
VES is expected to be used for the following purposes.
- Entry signal
When the VES value continues to rise—i.e., during energy accumulation—it can be considered on standby for a breakout. After a breakout, a trader can confirm the trend direction and enter.
- Exit signal
If the VES value rises during a trend, consider the possibility of a reversal and consider taking profits.
- Risk management
If the VES value remains elevated for a long period, regard it as increased market uncertainty and an approaching breakout; adopt a cautious trading strategy to prepare for higher volatility and adjust position size.
For example, in the BINANCE:SOLUSDT daily chart below, VES clearly shows how it functions in short‑term trading.
i.imgur.com
In September 2023, when the price was moving around 20 USDT, VES formed frequent small spikes. These early spikes suggest that market participants were still in a wait‑and‑see mode and that small‑scale accumulation was being conducted intermittently.
A decisive change came in early October 2023. While the price still stagnated in the 20–25 USDT range, VES suddenly formed a huge spike. The scale of this spike was far larger than those in September 2023, clearly suggesting that hidden substantial trading activities by large investors had begun.
In mid‑October 2023, the price began to rise. It climbed stepwise from 25 USDT to 40 USDT, then to 60 USDT and 75 USDT, and then surged to above 120 USDT within just a few weeks. This suggests that the energy built in the buy accumulation phase in early October 2023 was converted into price appreciation.
Therefore, after such a large VES signal is observed and the price breaks upward, entering a long position could have been profitable.
A large VES reaction is not only a quiet “buy signal” as in the example above; it can also be a “sell signal.” Such a case is explained below using an example on the BTC chart.
i.imgur.com
This BITSTAMP:BTCUSD 4‑hour chart is a valuable example showing how VES detects top formation on a short timeframe. In the first half of February 2024, the price moved in a relatively narrow 96,000–99,000 USD range. During this period, VES remained stable at low levels, and the market continued a calm uptrend.
The first sign appeared on February 16, 2024. While the price still held around 97,000 USD, VES formed a clearly identifiable small spike. This implied that some large investors had begun to take profits, or that new sellers had started to build short positions. However, at that point, the impact on price was limited, and many traders may have overlooked the signal.
The decisive turning point came on February 23, 2024. With the price moving around 98,000 USD, VES suddenly formed a huge spike. The scale of this spike was far larger than previous moves, clearly indicating that significant energy was accumulating.
Importantly, even at this moment the price still remained at the highs. On the surface, price barely moved and the bull trend appeared intact, but VES detected a major internal change underway.
On February 24, 2024, the price collapsed and began to fall. It dropped about 15% from 97,000 USD to 82,000 USD in a few days. The speed and magnitude of this decline corroborated the quiet “sell signal” indicated by the VES spikes.
The key lesson from this chart is that a VES spike does not necessarily mean buy accumulation. A large VES spike formed at high prices may instead indicate a distribution phase—that is, large investors exiting or building short positions. When the price is at elevated levels, a VES spike should be considered not only as a precursor to further upside but also as a warning of potential downside.
From a trading‑strategy perspective, the huge VES spike on February 23, 2024 was a clear signal to exit or to consider entering short positions. At that point, traders should have either closed long positions or to consider building a short position. The moment when price started to decline from its peak was exactly the entry timing for a short.
On the 4‑hour timeframe, changes in VES appear faster and more dramatically. While this allows more agile responses, the risk of false signals is also higher; therefore, confirmation on other timeframes and comprehensive judgment with price action are essential.
VES is a powerful tool for reading internal market activities, and this chart clearly shows that its interpretation requires flexibility that takes into account market conditions and price location.
⚡️ Parameter Settings
Strength 1: The lower the number, the more it emphasizes responses closer to the present timeframe; the higher the number, the more it emphasizes responses farther from the present timeframe. 5 is recommended.
Strength 2: The lower the number, the greater the volatility of the value; the higher the number, the smaller the volatility. 5 is recommended.
Scale: Adjusts the display scale. −30 is recommended.
⚡️ Conclusion
Vajra Energy Signal (VES) visualizes the cycle of energy accumulation in the market from the relative relationship between price range and volume, detecting hidden activities by market participants that conventional volume analysis cannot capture. VES serves as a powerful auxiliary tool for early detection of turning points, enabling deeper market understanding and more accurate timing decisions. As the examples show, there is a possibility of sensing major price movements in advance. When using VES, flexible interpretation according to market environment and price location is required, and it demonstrates its true value when combined with price action and other analysis methods such as support/resistance.
⚡️ Important Notes
- VES is a tool that infers internal market energy; it does not guarantee trades or suggest future results.
- We strongly recommend using it together with price action analysis and support/resistance.
- Confirmation across different timeframes improves reliability.
- Effectiveness may vary depending on market conditions and liquidity.
- Very illiquid instruments or newly listed assets may produce more noise.
⚡️ How to Get Access
This indicator is Public Invite‑Only. If you would like access, please apply by following the Author’s Instructions.
Ighodalo Gold - CRT (Candles are ranges theory)This indicator is designed to automatically identify and display CRT (Candles are Ranges Theory) Candles on your chart. It draws the high and low of the identified range and extends them until price breaks out, providing clear levels of support and resistance.
The Candles are Ranges Theory (CRT) concept was originally developed and shared by a trader named Romeotpt (Raid). All credit for the trading methodology goes to him. This indicator simply makes spotting these specific candles easier.
What is a CRT Candle & How Is It Used?
A CRT candle is a single candle that has both the highest high AND the lowest low over a user-defined period. It is identified by analysing a block of recent candles and finding the one candle that contains the entire price range of that block.
Once a CRT candle is formed, its high and low act as an accumulation range.
A break above or below this range is the manipulation phase.
A reclaim of the range (price closing back inside) signifies a potential distribution phase.
On higher timeframes, this sequence can be interpreted as:
Candle 1: Accumulation
Candle 2: Manipulation
Candle 3: Distribution
Reversal (Turtle Soup):
A sweep of the high or low, followed by a quick reclaim (price closing back inside the range), can signify a reversal. According to the theory’s originator, Romeo, this reversal pattern is called “turtle soup.”
After a bearish reversal at the high, the target becomes the CRT low.
After a bullish reversal at the low, the target becomes the CRT high.
How to Use This Indicator
The indicator is flexible and can be adapted to your trading style. The most important settings are:
Max Lookback Period: Number of past candles ("n") the indicator checks within to find a CRT.
CRT Timeframe:
Select a timeframe (e.g., 1H): The indicator will look at the higher timeframe you selected and plot the most recent CRT range from that timeframe onto your current chart. This is useful for multi-timeframe analysis.
Enable Overlapping CRTs:
False (unchecked): Shows only one active CRT range at a time. The indicator won’t look for a new one until the current range is broken.
True (checked): Constantly searches for and displays all CRT ranges it finds, allowing multiple ranges to appear on the chart simultaneously.
Disclaimer & Notes
-This is a visualisation tool and not a standalone trading signal. Always use it alongside your own analysis and risk management strategy.
-All credit for the "Candles are Ranges Theory" (CRT) concept goes to its creator, Romeotpt (Raid).
"On the journey to the opposite side of the range, price often provides multiple turtle soup entry opportunities. Follow their footprints." — Raid, 2025
Trading Activity Index (Zeiierman)█ Overview
Trading Activity Index (Zeiierman) is a volume-based market activity meter that transforms dollar-volume into a smooth, normalized “activity index.”
It highlights when market participation is unusually low or high with a dynamic color gradient:
Light Blue → Low Activity (thin participation, low liquidity conditions)
Red/Orange → High Activity (active markets, large trades flowing in)
Additional percentile bands (20/40/60/80%) give context, helping you see whether the current activity level is in the bottom quintile, mid-range, or near historical extremes.
█ How It Works
⚪ Dollar Volume Transformation
Each bar, dollar volume is computed:
float dlrVol = close * volume
float dlrVolAvg = ta.sma(dlrVol, len_form)
Dollar volume = price × volume, smoothed by a configurable SMA window.
The result is log-transformed, compressing large outliers for a more stable signal.
⚪ Rolling Percentiles & Ranking
The log-dollar-volume series is compared to its rolling history (len_hist bars):
float p20 = ta.percentile_linear_interpolation(vscale, len_hist, 20)
float p40 = ta.percentile_linear_interpolation(vscale, len_hist, 40)
float p60 = ta.percentile_linear_interpolation(vscale, len_hist, 60)
float p80 = ta.percentile_linear_interpolation(vscale, len_hist, 80)
A normalized rank (0–1) is produced to color the main Trading Activity line.
█ How to Use
⚪ Detect High-Impact Sessions
Quickly see if today’s session is active or quiet relative to its own history — great for filtering setups that need activity.
⚪ Spot Breakouts & Traps
Combine with price action:
High activity near breakouts = strong follow-through likely.
Low activity breakouts = vulnerable to fake-outs.
⚪ Market Regime Context
Percentile bands help you assess whether participation is building up, in the middle of the range, or drying out — valuable for timing mean-reversion trades.
Above 80th percentile (red/orange) → Market is highly active, breakout trades and trend strategies are favored.
Below 20th percentile (light blue) → Market is quiet; fade moves or wait for expansion.
Watch transitions from blue → orange as a signal of growing institutional participation.
█ Settings
Formation Window (bars) – Number of bars used to average dollar volume before log transform.
History Window (bars) – Lookback period for percentile calculations and rank normalization.
-----------------
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.
Continuous Accumulation Strategy [DCA] v9🇬🇧 English: Continuous Accumulation Strategy v9.4
This script is a full-featured strategy designed to backtest the "Buy the Dip" or "Dollar Cost Averaging" (DCA) philosophy. Its core feature is the Dynamic Peak Detection logic, which solves the "lock-in" problem of previous versions. Instead of getting stuck on an old high, the strategy constantly adapts to the market by referencing the most recent peak.
Key Features
* Dynamic Peak Detection: You define the "Peak Lookback Period." For example, on a Daily chart, setting it to `5` references the peak of the last business week.
* Stable Order Management: The strategy consistently uses a fixed cash amount (e.g., $100) for each entry, which prevents any runtime errors related to negative equity.
* Publishing-Ready: To meet TradingView's requirement for a backtest report, this strategy executes a symbolic, one-time "dummy trade" (one buy and one sell) at the very beginning of the test period. This first trade should be ignored when analyzing performance , as its only purpose is to enable publication.
How It Works
The main logic follows an adaptive cycle: Find Dynamic Peak -> Wait for a Drop -> Buy on Crossover -> Repeat.
1. Finds the Dynamic Peak: On every bar, it identifies the highest price within your defined lookback period.
2. Calculates the Drop: It constantly calculates the percentage drop from this moving peak.
3. Executes an Entry: The moment the price crosses below a target drop percentage, it executes a buy order.
4. Continuously Adapts: As the price moves, the dynamic peak is constantly updated, meaning the strategy never gets locked and is always ready for the next opportunity.
How to Use This Strategy
* Focus on the Strategy Tester: After adding it to the chart, analyze the Equity Curve, Net Profit, and Max Drawdown to see how this accumulation philosophy would have performed on your favorite asset.
* Optimize Parameters: Adjust the "Peak Lookback Period" and "Drop Percentages" to fit the volatility of the asset you are testing.
This is a tool for testing and analyzing a "buy and accumulate" philosophy. Its main logic does not generate sell signals.
3-Level DCA Buy Strategy🎯 3-Level DCA Buy Strategy - Smart Dollar Cost Averaging
Professional DCA strategy that systematically accumulates positions during market dips. Enhanced with daily trend analysis for intelligent accumulation.
🚀 Key Features
- 3-Level Buying System: Automatic purchases at 5%, 10%, 15% drops from cycle highs
- Daily Trend Analysis: 1-day timeframe trend confirmation
- Smart Peak Detection: 100-period lookback for meaningful peaks
- Volume Filter: Optional volume confirmation system
- USD-Based Positions: Fixed dollar amounts per level
- Never Sells: Pure accumulation philosophy (buy-only)
📊 How It Works
1. Peak Identification: Detects highest price in last 100 periods
2. Daily Trend Check: Confirms price above 50 SMA on 1D timeframe
3. Drop Tracking: Calculates percentage drops from cycle high
4. Systematic Buying: Executes predetermined amounts at each level
5. Cycle Reset: Renews buy permissions when new peaks form
⚙️ Default Settings
- Buy Levels: 5%, 10%, 15% drops
- Position Sizes: $100, $150, $200
- Peak Period: 100 bars
- Higher Timeframe: 1 Day (1D)
- Pyramiding: 500 order capacity
🎨 Visual Elements
- Orange Circles: Mark cycle highs
- Colored Lines: Green/Blue/Red buy levels
- Triangle Signals: Buy point indicators
- Live Panel: Real-time statistics
- Background Colors: Trend and drop level indicators
🔔 Alert System
- Instant notifications for each buy level
- New peak detection alerts
- Major drop warnings (>20%)
- Daily trend change notifications
💡 Ideal Use Cases
- Crypto Accumulation: Bitcoin, Ethereum and major altcoins
- Stock DCA: Long-term portfolio building
- Volatile Markets: Capitalizing on price fluctuations
- Emotional Trading Prevention: Automated and disciplined buying
📈 Strategy Logic
This strategy follows the "buy the dip" philosophy. It waits during market rises and systematically builds positions during declines. Only buys when daily trend is bullish, providing protection during major bear markets.
⚠️ Important Notes
- Buy-only strategy - never sells positions
- Requires sufficient capital for multiple entries
- Most effective in trending and volatile markets
- Always backtest before live trading
- Risk management is your responsibility
🛠️ Customization Options
All parameters are fully customizable: drop percentages, position amounts, timeframes, visual elements and more. Suitable for both beginner and experienced investors.
🎯 Publishing Feature
Note: Strategy includes temporary 1-day sell cycle for TradingView publishing requirements. This feature can be disabled for normal DCA mode operation.
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B A N K $ - HTF Candle Boxes (Power of 3)This indicator allows you to visualise the HTF candles on the LTF's, this is useful for using the Power of 3 / Accumulation, Manipulation & Distribution concepts.
By default, the HTF interval is set to 1h, this means that an outline will be created around the LTF candles that are within that 1h window. (i.e from 13:00-14:00 etc).
Features
HTF Interval Selector - this allows the user to customise which HTF interval to use
Candle Boxes - this outlines the full outer perimeter of the relevant candles
Include Body - this highlights the distance between the candle Open & Close
Show MidLine
Additional Settings
Hide Side Lines - this will only draw the Top & Bottom lines
Extend Lines to Current Candle - most recent Top & Bottom lines will extend to current price
Draw Lines from Exact Candle - this makes the most recent candle lines cleaner
I personally use this indicator to outline the most recent 3 1h candles to make it easier to identify sweeps & reversals however there is additional functionality to allow the user to customise the indicator to their preference.
FluidFlow OscillatorFluidFlow Oscillator: Study Material for Traders
Overview
The FluidFlow Oscillator is a custom technical indicator designed to measure price momentum and market flow dynamics by simulating fluid motion concepts such as velocity, viscosity, and turbulence. It helps traders identify potential buy and sell signals along with trend strength, momentum direction, and volatility conditions.
This study explains the underlying calculation concepts, signal logic, visual cues, and how to interpret the professional dashboard table that summarizes key indicator readings.
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How the FluidFlow Oscillator Works
Core Mechanisms
1. Price Flow Velocity
o Measures the rate of change of price over a specified flow length (default 40 bars).
o Calculated as a percentage change of closing price: roc=close−closelen_flowcloselen_flow×100\text{roc} = \frac{\text{close} - \text{close}_{len\_flow}}{\text{close}_{len\_flow}} \times 100roc=closelen_flowclose−closelen_flow×100
o Smoothed by an EMA (Exponential Moving Average) to reduce noise, generating a "flow velocity" value.
2. Viscosity Factor
o Analogous to fluid viscosity, it adjusts the flow velocity based on recent price volatility.
o Volatility is computed as the standard deviation of close prices over the flow length.
o The viscosity acts as a damping factor to slow down the flow velocity in highly volatile conditions.
o This results in a "flow with viscosity" value, that smooths out the velocity considering market turbulence.
3. Turbulence Burst
o Captures sudden changes or bursts in the flow by measuring changes between successive viscosity-adjusted flows.
o The turbulence value is a smoothed absolute change in flow.
o A burst boost factor is added to the oscillator to incorporate this rapid change component, amplifying signals during sudden shifts.
4. Oscillator Calculation
o The raw oscillator value is the sum of flow with viscosity plus burst boost, scaled by 10.
o Clamped between -100 and +100 to limit extremes.
o Finally, smoothed again by EMA for cleaner visualization.
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Signal Logic
The oscillator works with complementary components to produce actionable signals:
• Signal Line: An EMA-smoothed version of the oscillator for generating crossover-based signals.
• Momentum: The rate of change of the oscillator itself, smoothed by EMA.
• Trend: Uses fast (21-period EMA) and slow (50-period EMA) moving averages of price to identify market trend direction (uptrend, downtrend, or sideways).
Signal Conditions
• Bullish Signal (Buy): Oscillator crosses above the oversold threshold with positive momentum.
• Bearish Signal (Sell): Oscillator crosses below the overbought threshold with negative momentum.
Statuses
The oscillator provides descriptive market states based on level and momentum:
• Overbought
• Oversold
• Buy Signal
• Sell Signal
• Bullish / Bearish (momentum-driven)
• Neutral (no clear trend)
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Color System and Visualization
The oscillator uses a sophisticated HSV color model adapting hues according to:
• Oscillator value magnitude and sign (positive or negative)
• Acceleration of oscillator changes
• Smooth color gradients to facilitate intuitive understanding of trend strength and momentum shifts
Background colors highlight overbought (red tint) and oversold (green tint) zones with transparency.
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How to Understand the Professional Dashboard Table
The FluidFlow Oscillator offers an integrated table at the bottom center of the chart. This dashboard summarizes critical indicator readings in 8 columns across 3 rows:
Column Description
SIGNAL Current signal status (e.g., Buy, Sell, Overbought) with color coding
OSCILLATOR Current oscillator value (-100 to +100) with color reflecting intensity and direction
MOMENTUM Momentum bias indicating strength/direction of oscillator changes (Strong Up, Up, Sideways, Down, Strong Down)
TREND Current trend status based on EMAs (Strong Uptrend, Uptrend, Sideways, Downtrend, Strong Downtrend)
VOLATILITY Volatility percentage relative to average, indicating market activity level
FLOW Flow velocity value describing price momentum magnitude and direction
TURBULENCE Turbulence level indicating sudden bursts or spikes in price movement
PROGRESS Oscillator's position mapped as a percentage (0% to 100%) showing proximity to extreme levels
Rows Explained
• Row 1 (Header): Labels for each metric.
• Row 2 (Values): Current numerical or descriptive values color-coded along a professional scheme:
o Green or lime tones indicate positive or bullish conditions.
o Red or orange tones indicate caution, sell signals, or bearish conditions.
o Blue tones indicate neutral or stable conditions.
• Row 3 (Status Indicators): Emoji-like icons and bars provide a quick visual gauge of each metric's intensity or signal strength:
o For example, "🟢🟢🟢" suggests very strong bullish momentum, while "🔴🔴🔴" suggests strong bearish momentum.
o Progress bar visually demonstrates oscillator movement toward oversold or overbought extremes.
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Practical Interpretation Tips
• A Buy signal with green colors and strong momentum usually precedes upward price moves.
• An Overbought status with red background and red table colors warns of potential price corrections or reversals.
• Watch the Turbulence to gauge market instability; spikes may precede price shocks or volatility bursts.
• Confirm signals with the Trend and Momentum columns to avoid false entries.
• Use the Progress bar to anticipate oscillations approaching key threshold levels for timing trades.
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Alerts
The oscillator supports alerts for:
• Buy and sell signals based on oscillator crossovers.
• Overbought and oversold levels reached.
These help traders automate awareness of important market conditions.
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Disclaimer
The FluidFlow Oscillator and its signals are for educational and informational purposes only. They do not guarantee profits and should not be considered as financial advice. Always conduct your own research and use proper risk management when trading. Past performance is not indicative of future results.
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This detailed explanation should help you understand the workings of the FluidFlow Oscillator, its components, signal logic, and how to analyze its professional dashboard for informed trading decisions.
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MACD EMA 200 Strategy (Roche 5min Scalp)Free to use, stay blessed.
I don't believe charging for something that everyone can use.
Please enjoy it.
CVDD Z-ScoreCumulative Value Days Destroyed (CVDD) - The CVDD was created by Willy Woo and is the ratio of the cumulative value of Coin Days Destroyed in USD and the market age (in days). While this indicator is used to detect bottoms normally, an extension is used to allow detection of BTC tops. When the BTC price goes above the CVDD extension, BTC is generally considered to be overvalued. Because the "strength" of the BTC tops has decreased over the cycles, a logarithmic function for the extension was created by fitting past cycles as log extension = slope * time + intercept. This indicator is triggered for a top when the BTC price is above the CVDD extension. For the bottoms, the CVDD is shifted upwards at a default value of 120%. The slope, intercept, and CVDD bottom shift can all be modified in the script.
Now with the automatic Z-Score calculation for ease of classification of Bitcoin's valuation according to this metric.
Created for TRW.
