Smart VWAP FVG SystemSmart VWAP FVG System - Professional Multi-Filter Trading Indicator
📊 OVERVIEW
The Smart VWAP FVG System is an advanced multi-layered trading indicator that combines institutional volume analysis, multi-timeframe VWAP trend confirmation, and Fair Value Gap detection to identify high-probability trade entries. This indicator uses a sophisticated filtering mechanism where signals appear only when multiple independent confirmation criteria align simultaneously.
Recommended Timeframe: 5-minute (M5) or higher. The indicator works best on M5, M15, and M30 charts for intraday trading.
🎯 ORIGINALITY & PURPOSE
This indicator is original because it combines three distinct analytical methods into a unified decision-making system:
Market Profile Volume Analysis - Identifies institutional accumulation/distribution zones
Dual VWAP Filtering - Confirms trend direction using two independent VWAP calculations
Fair Value Gap Detection - Validates institutional interest through price inefficiency zones
The key innovation is the directional filter system: the primary Market Profile generates BUY-ONLY or SELL-ONLY states based on higher timeframe value area reversals, which then controls which signals from the main system are displayed. This creates a multi-timeframe confluence that significantly reduces false signals.
Unlike simple indicator mashups, each component serves a specific purpose:
Market Profile → Direction bias (trend filter)
Primary VWAP (Session) → Short-term trend confirmation
Secondary VWAP (Week) → Medium-term trend confirmation
FVG Detection → Institutional activity validation
🔧 HOW IT WORKS
1. Primary Market Profile Filter (Higher Timeframe)
The indicator calculates Market Profile on a higher timeframe (default: 1 hour) to determine the overall market structure:
Value Area High (VAH): Top 70% of volume distribution
Value Area Low (VAL): Bottom 70% of volume distribution
Point of Control (POC): Price level with highest volume
When price reaches VAH and reverses down → SELL-ONLY mode activated
When price reaches VAL and reverses up → BUY-ONLY mode activated
This higher timeframe filter ensures you're trading in the direction of institutional flow.
2. Dual VWAP System
Two independent VWAP calculations provide multi-timeframe trend confirmation:
Primary VWAP (Session-based): Resets daily, tracks intraday momentum
Secondary VWAP (Week-based): Resets weekly, confirms longer-term trend
Filter Logic:
BUY signals require: Price > Primary VWAP AND Price > Secondary VWAP
SELL signals require: Price < Primary VWAP AND Price < Secondary VWAP
This dual confirmation prevents counter-trend trades during ranging conditions.
3. Fair Value Gap (FVG) Detection
FVG zones identify price inefficiencies where institutional orders were executed rapidly:
Bullish FVG: Gap between candle .high and candle .low (upward imbalance)
Bearish FVG: Gap between candle .high and candle .low (downward imbalance)
The indicator monitors recent FVG formation (lookback: 50 bars) and requires:
Bullish FVG present for BUY signals
Bearish FVG present for SELL signals
FVG zones are displayed as colored boxes and automatically marked as "mitigated" when price fills the gap.
4. Main Trading Signal Logic
The secondary Market Profile (default: 1 hour) generates the actual trading signals:
BUY Signal Conditions:
Price reaches Value Area Low
Reversal pattern confirmed (minimum 1 bar)
Price > Primary VWAP
Price > Secondary VWAP (if filter enabled)
Recent Bullish FVG detected (if filter enabled)
Primary MP Filter = BUY-ONLY or NEUTRAL
SELL Signal Conditions:
Price reaches Value Area High
Reversal pattern confirmed (minimum 1 bar)
Price < Primary VWAP
Price < Secondary VWAP (if filter enabled)
Recent Bearish FVG detected (if filter enabled)
Primary MP Filter = SELL-ONLY or NEUTRAL
All conditions must be TRUE simultaneously for a signal to appear.
📈 VISUAL ELEMENTS
On Chart:
🟢 Green Triangle (▲) = BUY Signal
🔴 Red Triangle (▼) = SELL Signal
🟦 Blue horizontal lines = Value Area zones
🟡 Yellow line = Point of Control (POC)
🟩 Green boxes = Bullish FVG zones
🟥 Red boxes = Bearish FVG zones
🔵 Blue line = Primary VWAP (Session)
⚪ White line = Secondary VWAP (Week)
Info Panel (Top Right):
Real-time status display showing:
Filter Direction (BUY ONLY / SELL ONLY / NEUTRAL)
Active timeframes for both MP filters
FVG filter status and count
VWAP positions (ABOVE/BELOW)
Signal enablement status
Alert status
⚙️ KEY SETTINGS
MP/TPO Filter Settings (Primary Indicator)
MP Filter Time Frame: 60 minutes (controls directional bias)
Filter Value Area %: 70% (standard Market Profile calculation)
Filter Alert Distance: 1 bar
Filter Min Bars for Reversal: 1 bar
Filter Alert Zone Margin: 0.01 (1%)
FVG Filter Settings
Use FVG Filter: Enabled (toggle on/off)
FVG Timeframe: 60 minutes (1 hour)
FVG Filter Mode: Both (require bullish FVG for BUY, bearish for SELL)
FVG Lookback Period: 50 bars (how far back to search)
Show FVG Formation Signals: Optional visual markers
Max FVG on Chart: 50 zones
Show Mitigated FVG: Display filled gaps
Market Profile Settings
Higher Time Frame: 60 minutes (for main signals)
Percent for Value Area: 70%
Show POC Line: Enabled
Keep Old MPs: Enabled (maintain historical profiles)
Primary VWAP Filter
Use Primary VWAP Filter: Enabled
Primary VWAP Anchor Period: Session (resets daily)
Primary VWAP Source: HLC3 (typical price)
Secondary VWAP Filter
Use Secondary VWAP Filter: Enabled
Secondary VWAP Anchor Period: Week (resets weekly)
Secondary VWAP Filter Mode: Both
Secondary VWAP Line Color: White
Trading Signals
Show Trading Signals on Chart: Enabled
Show SELL Signals: Enabled
Show BUY Signals: Enabled
Alert Distance: 1 bar
Min Bars for Reversal: 1 bar
Alert Zone Margin: 0.01 (1%)
Retest Search Period: 20 bars
Min Bars Between Retests: 5 bars
Show Only Retests: Disabled
Alert Settings
Enable Trading Notifications: Enabled
VAH Reversal Alert: Enabled (SELL signals)
VAL Reversal Alert: Enabled (BUY signals)
Time Filter Settings
Filter Alerts By Time: Optional (exclude specific hours)
⚠️ IMPORTANT WARNINGS & LIMITATIONS
1. Repainting Behavior
CRITICAL: This indicator uses lookahead=barmerge.lookahead_on to access higher timeframe data immediately for FVG detection. This is necessary to provide real-time FVG zone visualization but has the following implications:
FVG zones may shift slightly until the higher timeframe candle closes
FVG detection signals are preliminary until HTF bar confirmation
The main trading signals (triangles) appear on confirmed bars and do not repaint
Best Practice: Always wait for the current timeframe bar to close before acting on signals. The filter status and FVG zones are informational but may adjust as new data arrives.
2. Minimum Timeframe
Do NOT use on timeframes below 5 minutes (M5)
Recommended: M5, M15, M30 for intraday trading
Higher timeframes (H1, H4) can also be used but will generate fewer signals
3. Multiple Filters Can Block Signals
By design, this indicator is conservative. When all filters are enabled:
Signals appear ONLY when all conditions align
You may see extended periods with no signals
This is intentional to reduce false positives
If you see no signals:
Check the Info Panel to see which filters are failing
Consider adjusting FVG lookback period
Temporarily disable FVG filter to test
Verify VWAP filters match current market trend
4. Market Profile Limitations
Market Profile requires sufficient volume data
Low-volume instruments may produce unreliable profiles
Value Areas update only on higher timeframe bar close
Works best on liquid markets (major forex pairs, indices, crypto)
📖 HOW TO USE
Step 1: Add to Chart
Apply indicator to M5 or higher timeframe chart
Ensure chart shows volume data
Use standard candles (NOT Heikin Ashi, Renko, etc.)
Step 2: Configure Settings
Primary MP Filter TF: Set to 60 (1 hour) minimum, or 240 (4 hour) for swing trading
Main MP TF: Set to 60 (1 hour) for intraday signals
FVG Timeframe: Match or exceed main MP timeframe
Leave other settings at default initially
Step 3: Understand the Info Panel
Monitor the top-right panel:
FILTER STATUS: Shows current directional bias
NEUTRAL = Both signals allowed
BUY ONLY = Only green triangles will appear
SELL ONLY = Only red triangles will appear
FVG Filter: Shows if bullish/bearish gaps detected recently
VWAP positions: Confirms trend alignment
Step 4: Take Signals
For BUY Signal (Green Triangle ▲):
Wait for green triangle to appear
Check Info Panel shows ✓ for BUY signals
Confirm current bar has closed
Enter long position
Stop loss: Below recent VAL or swing low
Target: Previous Value Area High or 1.5-2× risk
For SELL Signal (Red Triangle ▼):
Wait for red triangle to appear
Check Info Panel shows ✓ for SELL signals
Confirm current bar has closed
Enter short position
Stop loss: Above recent VAH or swing high
Target: Previous Value Area Low or 1.5-2× risk
Step 5: Risk Management
Risk per trade: Maximum 1-2% of account equity
Position sizing: Adjust based on stop loss distance
Avoid trading: During major news events or time filter periods
Multiple confirmations: Look for confluence with price action (support/resistance, trendlines)
🎓 UNDERLYING CONCEPTS
Market Profile Theory
Developed by J. Peter Steidlmayer in the 1980s, Market Profile organizes price and volume data to identify:
Value Areas: Where 70% of trading activity occurred
POC: Price level with highest acceptance (most volume)
Imbalances: When price moves away from value quickly
This indicator uses TPO (Time Price Opportunity) calculation method to build the volume profile distribution.
VWAP (Volume Weighted Average Price)
VWAP represents the average price weighted by volume, showing where institutional traders are positioned:
Price above VWAP = Bullish (institutions accumulated lower)
Price below VWAP = Bearish (institutions distributed higher)
Using dual VWAP (Session + Week) creates multi-timeframe trend alignment.
Fair Value Gaps (FVG)
Also known as "imbalance" or "inefficiency," FVG occurs when:
Price moves so rapidly that a gap forms in the candlestick structure
Indicates institutional order flow (large market orders)
Price often returns to "fill" these gaps (rebalance)
The 3-candle FVG pattern (gap between candle and candle ) is widely used in ICT (Inner Circle Trader) methodology and Smart Money Concepts.
🔍 CREDITS & CODE ATTRIBUTION
This indicator builds upon established technical analysis concepts and combines multiple methodologies:
1. Market Profile / TPO Calculation
Concept Origin: J. Peter Steidlmayer (Chicago Board of Trade, 1980s)
Code Inspiration: TradingView's public domain Market Profile examples
Modifications: Custom filtering logic for directional bias, dual timeframe implementation
2. VWAP Calculation
Concept Origin: Standard financial instrument (widely used since 1980s)
Code Base: TradingView built-in ta.vwap() function (public domain)
Modifications: Dual VWAP system with independent anchor periods, custom filtering modes
3. Fair Value Gap Detection
Concept Origin: Inner Circle Trader (ICT) / Smart Money Concepts methodology
Code Implementation: Original implementation based on 3-candle gap pattern
Features: Multi-timeframe detection, automatic mitigation tracking, visual zone display
4. Pine Script Framework
Language: Pine Script v6 (TradingView)
Built-in Functions Used:
ta.vwap() - Volume weighted average price
request.security() - Higher timeframe data access
ta.change() - Period detection
ta.cum() - Cumulative volume
time() - Timestamp functions
Note: All code is original implementation. While concepts are based on established trading methodologies, the combination, filtering logic, and execution are unique to this indicator.
📊 RECOMMENDED INSTRUMENTS
Best Performance:
Major Forex Pairs (EURUSD, GBPUSD, USDJPY)
Stock Indices (ES, NQ, SPX, DAX)
Major Cryptocurrencies (BTCUSD, ETHUSD)
Liquid Stocks (high daily volume)
Avoid:
Low-volume altcoins
Illiquid stocks
Exotic forex pairs with wide spreads
⚡ PERFORMANCE TIPS
Start Conservative: Enable all filters initially
Reduce Filters Gradually: If too few signals, disable Secondary VWAP filter first
Match Timeframes: Keep MP Filter TF and FVG TF at same value
Backtest First: Review historical performance on your preferred instrument/timeframe
Combine with Price Action: Look for support/resistance confluence
Use Time Filter: Avoid low-liquidity hours (optional setting)
🚫 WHAT THIS INDICATOR DOES NOT DO
Does not guarantee profits - No trading system is 100% accurate
Does not predict the future - Based on historical patterns
Does not replace risk management - Always use stop losses
Does not work on all instruments - Requires volume data and liquidity
Does not provide exact entry/exit prices - Signals are zones, not precise levels
Does not account for fundamentals - Purely technical analysis
📜 DISCLAIMER
This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results.
Trading Risk Warning:
All trading involves risk of loss
You can lose more than your initial investment (leverage products)
Only trade with capital you can afford to lose
Always use appropriate position sizing and risk management
Consider seeking advice from a licensed financial advisor
Technical Limitations:
Indicator may repaint FVG zones until HTF bar closes
Signals are based on historical patterns that may not repeat
Market conditions change and no system works in all environments
Volume data quality varies by exchange/broker
By using this indicator, you acknowledge these risks and agree that the author bears no responsibility for trading losses.
📞 SUPPORT & UPDATES
Questions? Comment on this publication
Issues? Describe the problem with chart screenshot
Feature Requests? Suggest improvements in comments
Updates: Will be published as new versions using TradingView's update feature
📝 VERSION HISTORY
Version 1.0 (Current)
Initial public release
Multi-filter system: MP + Dual VWAP + FVG
Directional bias filter
Real-time info panel
Comprehensive alert system
Time-based filtering
Thank you for using Smart VWAP FVG System!
Happy Trading! 📈
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Analog Flow [KedArc Quant]Overview
AnalogFlow is an advanced analogue based market projection engine that reconstructs future price tendencies by matching current price behavior to historical analogues in the same instrument. Instead of using traditional indicators such as moving averages, RSI, or regression, AnalogFlow applies pattern vector similarity analysis - a data driven technique that identifies historically similar sequences and aggregates their subsequent movements into a smooth, forward looking curve.
Think of it as a market memory system:
If the current pattern looks like one we have seen before, how did price move afterward?
Why AnalogFlow Is Unique
1. Pattern centric - it does not rely on any standard indicator formula; it directly analyzes price movement vectors.
2. Adaptive - it learns from the same instrument's past behavior, making it self calibrating to volatility and regime shifts.
3. Non repainting - the projection is generated on the latest completed bar and remains fixed until new data is available.
4. Noise resistant - the EMA Blend engine smooths the projected trajectory, reducing random variance between analogues.
Inputs and Configuration
Pattern Bars
Number of bars in the reference pattern window: 40
Projection Bars
Number of bars forward to project: 30
Search Depth
Number of bars back to look for matching analogues: 600
Distance Metric
Comparison method: Euclidean, Manhattan, or Cosine (default Euclidean)
Matches
Number of top analogues to blend (1-5): Top 3
Build Mode
Projection type: Cumulative, MeanStep, or EMA Blend (default EMA Blend)
EMA Blend Length
Smoothness of the projected path: 15
Normalize Pattern
Enable Z score normalization for shape matching: true
Dissimilarity Mode
If true, finds inverse analogues for mean reversion analysis: false
Line Color and Width
Style settings for projection curve: Blue, width 2
How It Works with Past Data
1. The system builds a memory bank of patterns from the last N bars based on the scanDepth value.
2. It compares the latest Pattern Bars segment to each historical segment.
3. It selects the Top K most similar or dissimilar analogues.
4. For each analogue, it retrieves what happened after that pattern historically.
5. It averages or smooths those forward moves into a single composite forecast curve.
6. The forecast (blue line) is drawn ahead of the current candle using line.new with no repainting.
Output Explained
Blue Path
The weighted mean future trajectory based on historical analogues.
Smoother when EMA Blend mode is enabled.
Flat Section
Indicates low directional consensus or equilibrium across analogues.
Upward or Downward Slope
Represents historical tendency toward continuation or reversal following similar conditions.
Recommended Timeframes
Scalping / Short Term
1m - 5m : Short winLen (20-30), small ahead (10-15)
Swing Trading
15m - 1h : Balanced settings (winLen 40-60, ahead 20-30)
Positional / Multi Day
4h - 1D : Large windows (winLen 80-120, ahead 30-50)
Instrument Compatibility
Works seamlessly on:
Stocks and ETFs
Indices
Cryptocurrency
Commodities (Gold, Crude, etc.)
Futures and F&O (both intraday and positional)
Forex
No symbol specific calibration needed. It self adapts to volatility.
How Traders Can Use It
Forecast Context
Identify likely short term price path or drift direction.
Reversal Detection
Flip seekOpp to true for mean reversion pattern analysis.
Scenario Comparison
Observe whether the current regime tends to continue or stall.
Momentum Confirmation
Combine with trend tools such as EMA or MACD for directional bias.
Backtesting Support
Compare projected path versus realized price to evaluate reliability.
FAQ
Q1. Does AnalogFlow repaint?
No. It calculates only once per completed bar and projects forward. The future path remains static until a new bar closes.
Q2. Is it a neural network or AI model?
Not in the machine learning sense. It is a deterministic analogue matching engine using statistical distance metrics.
Q3. Why does the projection sometimes flatten?
That means similar historical setups had no clear consensus in direction (neutral expectation).
Q4. Can I use it for live trading signals?
AnalogFlow is not a signal generator. It provides probabilistic context for upcoming movement.
Q5. Does higher scanDepth improve accuracy?
Up to a point. More depth gives more analogues, but too much can dilute recency. Try 400 to 800.
Glossary
Analogue
A past pattern similar to the current price behavior.
Distance Metric
Mathematical formula for pattern similarity.
Step Vector
Difference between consecutive closing prices.
EMA Blend
Exponential smoothing of the projected path.
Cumulative Mode
Adds sequential historical deltas directly.
Z Score Normalization
Rescaling to mean 0 and variance 1 for shape comparison.
Summary
AnalogFlow converts the market's historical echoes into a structured, statistically weighted forward projection. It gives traders a contextual roadmap, not a signal, showing how similar past setups evolved and allowing better informed entries, exits, and scenario planning across all asset classes.
Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and proper risk management when applying this strategy.
BK AK-13⚔️ BK AK-13 — The Mentor’s 13. Revealed on 11. Command the Band. Punish the Extremes. ⚔️
This is my 11th release—and that matters. 11 is a sacred number to me, so for release eleven I’m doing something I never planned to do: I’m putting my mentor’s secret 13 MA into the open.
For years, this 13-based MA framework was part of our private playbook—quietly doing work behind the scenes. Now I’m handing it to you fully armed, because I believe in karma in, karma out: I took years of wisdom from the market. I took years of wisdom from the men who taught me. This is one of the ways I give back—with structure, respect, and intent.
🎖 Full Credit — Respect the Origin
The core architecture of BK AK-13 is not mine. It stands firmly on the work of DZIV.
What comes from DZIV:
The Heikin Ashi MA engine (MA calculated on HA Open/High/Low/Close)
The multi-MA engine on the HA feed (ALMA / HMA / SMA / RMA / VWMA / WMA / ZLEMA / EMA)
The Body / Wick / Band zone classification for price
The dynamic body & wick clouds that give this structure its clean visual form
If this framework changes the way you see trend and price location, remember the name: DZIV.
On top of his backbone, I forged the BK AK-13 enhancement layer: trend-strength regimes, background modes, structured band-reversal arrows, momentum acceleration dots, extreme pivot markers, historical band-touch rails, the info panel, and a complete alert suite.
And as always, the “AK” in the name is not branding—it’s honor. It belongs to my mentor A.K. His secret 13 MA is the spine of this system, and his obsession with clarity, patience, and zero shortcuts sits behind every decision in this tool. Above that, all glory and gratitude to Gd—the real source of any wisdom, edge, or endurance we have in this game.
🧠 Why “BK AK-13”?
BK — my mark, the house I’m building.
AK — my mentor, the standard I’m still chasing.
13 — his secret moving average, the length that quietly shaped how I see trend, location, and pressure.
For years, 13 stayed off the public record—used, not discussed. Now, on indicator number 11, I’m putting that weapon in the open: 11th release. Sacred number. Secret 13 revealed, not for hype—but as karmic give-back. Karma in. Karma out.
🧱 What BK AK-13 Actually Is
BK AK-13 is a Heikin Ashi MA battle band with a brain and a conscience.
It does three big things:
Builds a smoothed HA-MA band using Heikin Ashi OHLC to create a cleaner, truer band around price.
Maps price into zones: Body, Upper Wick, Lower Wick, Above Band, Below Band—so every bar has a role.
Assigns a trend regime by computing a normalized trend-strength %, classifying the environment as Weak / Normal / Strong / Extreme.
You’re never guessing: Is this real trend or just drift? Am I in the spine, the wick, or off the rails? Is this where I press, fade, or stand down? The band, zones, and regimes answer that for you.
🎨 Visual Architecture — Band, Clouds, Regimes
Body & Wick Clouds (DZIV’s craft)
Body cloud between HA-MA Open & Close.
Wick clouds between body and HA-MA High/Low.
Color follows trend: bull, bear, or neutral.
You’re not decoding noisy candles—you’re reading the spine and skin of the move.
Background Regime Modes (BK layer)
Standard – background always on, soft trend-follow color.
Hybrid (Extreme + Breaks) – lights only on extreme trend states or reversal break events.
Hybrid (Strong/Extreme + Breaks) – shows strong & extreme regimes, darker tone on true extremes.
Breaks Only – background flashes only on reversal arrows.
When the background goes quiet, you’re in ordinary flow. When it lights up, something is strategic, not cosmetic.
🎯 Weapons Inside BK AK-13
⭐ Trend Change Stars
Stars appear when the internal band trend crosses zero: bull star when it flips negative → positive, bear star from positive → negative. They’re your pivot flags for swing shifts when aligned with your higher timeframe bias.
🔁 Band Reversal Arrows — Edge Flip Logic
Not every band tap—only structured reversals:
Reversal Down (short idea): first a break of the upper band, then later, for the first time, a break of the lower band.
Reversal Up (long idea): first a break of the lower band, then later, for the first time, a break of the upper band.
You can require a close outside the band and set a minimum break distance (% of band range) so only real punches count. These arrows mark campaign flips, not noise.
💡 Momentum Acceleration Dots
In strong trend regimes only:
Green dot = trend accelerating in its own direction (uptrend steepening, downtrend deepening).
Red dot = trend decelerating, even if direction hasn’t flipped yet.
They protect you from chasing late when the engine is dying and from staying stubborn when momentum is bleeding out.
⚠ Extreme Pivot Markers
Pivot highs/lows are found with a configurable lookback and only marked when trend strength at that pivot bar is above your threshold. You’ll see ⚠ above likely exhaustion tops in strong bulls and ⚠ below likely exhaustion lows in strong bears—perfect for final scale-outs, countertrend scouts, and knowing where campaigns commonly run out of blood.
📏 Historical Band-Touch Rails
Over your lookback window, BK AK-13 tracks the highest upper band touch and lowest lower band touch, drawing them as dashed rails. They’re dynamic SR built from real band extremes—ideal for trend targets, fade zones, and stop/scale-out context.
🧭 Info Panel — On-Chart War Room
The Info Panel compresses everything into a single strip: direction + strength codes (BULL STR, BEAR EXT, NEUT WEAK), four segments that brighten as |trend| climbs from weak → normal → strong → extreme, and a zone + deviation label (BDY/UW/LW/AB/BL × OK/AL/EX).
Hover and you get a full tactical brief: trend, momentum change, acceleration, band levels, distances to upper/lower/nearest band in ticks, outer-band streaks, strategic state, plus “Action” guidance and a “What-if” forward scenario. It doesn’t just tell you where you are—it pushes you toward a structured thought process on each bar.
🕹 How to Use BK AK-13 with Intent
1️⃣ Trend-Rider Mode
In Strong/Extreme bull with price in Body or Lower Wick: buy dips into the band (mid/lower) instead of chasing tops; target the upper band / upper rail while structure holds.
In Strong/Extreme bear with price in Body or Upper Wick: sell rallies into the band; target lower band / lower rail while acceleration stays healthy.
The band defines where you’re allowed to do business.
2️⃣ Extreme Snapback Hunter
Prime conditions: trend tagged Extreme, price pressed into the outer band in trend direction, strategic state lit + Hybrid background active. That’s where pressing fresh risk often flips from reward to punishment. Use it to stop adding, start harvesting, or launch controlled mean-reversion probes back to the midline—if your system and risk rules allow it.
3️⃣ Exhaustion & Turn Zones
Watch for confluence: red momentum dots, extreme pivot ⚠ markers, a reversal arrow, and a nearby historical rail or your own key level (Fibs, VWAP, volume structure, etc.). That’s where campaigns often end, traps are set, and new campaigns begin.
🔔 Alerts — The Chart Calls You
Included alerts: Bullish/Bearish Trend Change, Strategic Extreme at Outer Band, Reversal Up/Down, Extreme Pivot High/Low, and Body Zone Entry during Strong Trend. Use them so you respond to events, not impulses.
🔧 Tuning the Extremes — Help Me Perfect the Advanced Side
The extreme thresholds and advanced features are powerful but sensitive, and there is no single perfect universal setting. I’m still tuning them myself across instruments and timeframes: strong/extreme trend thresholds, extreme background thresholds, momentum acceleration threshold, pivot lookback + pivot trend filter, band-touch lookback, and minimum break distance for reversals.
Different markets and timeframes breathe differently.
If you find killer settings for a specific symbol + timeframe, please share:
Instrument & timeframe
Your tuned values for extremes and advanced modules
A few charts showing why they work
Experiment. Dial it in. Then share your best settings for the extremes and advanced features. Let this become a crowd-forged battle manual: I gave you the engine, you tune it to your battleground, and we all benefit from what’s discovered in live fire. Karma in. Karma out.
🤝 Pay It Forward
If BK AK-13 sharpens your read, don’t just flex screenshots—teach structure. Show newer traders body vs wick vs edge. Talk about when you didn’t take a trade because the band said “danger,” not just the wins. Share your settings, charts, and lessons—especially around the extremes and advanced modules. I’m sharing a mentor’s secret on release 11 for a reason. If it blesses you, don’t let it stop with you.
📜 King Solomon’s Lens
King Solomon said: “The prudent sees danger and hides himself, but the simple go on and suffer for it.”
BK AK-13 is built exactly around that dividing line: the simple chase candles at the outer band in extreme regimes and get punished; the prudent see danger in the structure, hide their size, hedge, or reverse with intent.
This indicator won’t make you prudent. It just removes your excuse for being simple.
⚔️ BK AK-13 — The mentor’s secret 13, revealed on 11. Let the band define the field. Let wisdom define your strike.
May Gd bless your eyes, your patience, your settings, and every decision you make at the edge. 🙏
Advanced Psychological Levels with Dynamic Spacing═══════════════════════════════════════
ADVANCED PSYCHOLOGICAL LEVELS WITH DYNAMIC SPACING
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A comprehensive psychological price level indicator that automatically identifies and displays round number levels across multiple timeframes. Features dynamic ATR-based spacing, smart crypto detection, distance tracking, and customizable alert system.
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WHAT THIS INDICATOR DOES
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This indicator automatically draws psychological price levels (round numbers) that often act as support and resistance:
- Dynamic ATR-Based Spacing - Adapts level spacing to market volatility
- Multiple Level Types - Major (250 pip), Standard (100 pip), Mid, and Intraday levels
- Smart Asset Detection - Automatically adjusts for Forex, Crypto, Indices, and CFDs
- Crypto Price Adaptation - Intelligent level spacing based on cryptocurrency price magnitude
- Distance Information Table - Real-time percentage distance to nearest levels
- Combined Level Labels - Clear identification when multiple level types coincide
- Performance Optimized - Configurable visible range and label limits
- Comprehensive Alerts - Notifications when price crosses any level type
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HOW IT WORKS
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PSYCHOLOGICAL LEVELS CONCEPT:
Psychological levels are round numbers where traders tend to place orders, creating natural support and resistance zones. These include:
- Forex: 1.0000, 1.0100, 1.0050 (pips)
- Crypto: $100, $1,000, $10,000 (whole numbers)
- Indices: 10,000, 10,500, 11,000 (points)
Why They Matter:
- Traders naturally gravitate to round numbers
- Stop losses cluster at these levels
- Take profit orders concentrate here
- Institutional algorithmic trading often targets these levels
DYNAMIC ATR-BASED SPACING:
Traditional Method:
- Fixed spacing regardless of volatility
- May be too tight in volatile markets
- May be too wide in quiet markets
Dynamic Method (Recommended):
- Uses ATR (Average True Range) to measure volatility
- Automatically adjusts level spacing
- Tighter levels in low volatility
- Wider levels in high volatility
Calculation:
1. Calculate ATR over specified period (default: 14)
2. Multiply by ATR multiplier (default: 2.0)
3. Round to nearest psychological level
4. Generate levels at dynamic intervals
Benefits:
- Adapts to market conditions
- More relevant levels in all volatility regimes
- Reduces clutter in trending markets
- Provides more detail in ranging markets
LEVEL TYPES:
Major Levels (250 pip/point):
- Highest significance
- Primary support/resistance zones
- Color: Red (default)
- Style: Solid lines
- Spacing: 2.5x standard step
Standard Levels (100 pip/point):
- Secondary importance
- Common psychological barriers
- Color: Blue (default)
- Style: Dashed lines
- Spacing: Standard step
Mid Levels (50% between major):
- Optional intermediate levels
- Halfway between major levels
- Color: Gray (default)
- Style: Dotted lines
- Usage: Additional confluence points
Intraday Levels (sub-100 pip):
- For intraday traders
- Fine-grained precision
- Color: Yellow (default)
- Style: Dotted lines
- Only shown on intraday timeframes
SMART ASSET DETECTION:
Forex Pairs:
- Detects major currency pairs automatically
- Uses pip-based calculations
- Standard: 100 pips (0.0100)
- Major: 250 pips (0.0250)
- Intraday: 20, 50, 80 pip subdivisions
Cryptocurrencies:
- Automatic price magnitude detection
- Adaptive spacing based on price:
* Under $0.10: Levels at $0.01, $0.05
* $0.10-$1: Levels at $0.10, $0.50
* $1-$10: Levels at $1, $5
* $10-$100: Levels at $10, $50
* $100-$1,000: Levels at $100, $500
* $1,000-$10,000: Levels at $1,000, $5,000
* Over $10,000: Levels at $5,000, $10,000
Indices & CFDs:
- Fixed point-based system
- Major: 500 point intervals (with 250 sub-levels)
- Standard: 100 point intervals
- Suitable for stock indices like SPX, NASDAQ
COMBINED LEVEL LABELS:
When multiple level types coincide at the same price:
- Single line drawn (highest priority color)
- Combined label shows all types
- Priority: Major > Standard > Mid > Intraday
Example Label Formats:
- "1.1000 Major" - Major level only
- "1.1000 Std + Major" - Both standard and major
- "50000 Intra + Mid + Std" - Three levels coincide
Benefits:
- Cleaner chart appearance
- Clear identification of confluence
- Reduced visual clutter
- Easy to spot high-importance levels
DISTANCE INFORMATION TABLE:
Real-time tracking of nearest levels:
Table Contents:
- Nearest major level above (price and % distance)
- Nearest standard level above (price and % distance)
- Nearest standard level below (price and % distance)
Display:
- Top right corner (configurable)
- Color-coded by level type
- Real-time percentage calculations
- Helpful for position management
Usage:
- Identify proximity to key levels
- Set realistic profit targets
- Gauge potential move magnitude
- Monitor approaching resistance/support
ALERT SYSTEM:
Comprehensive crossing alerts:
Alert Types:
- Major Level Crosses
- Standard Level Crosses
- Intraday Level Crosses
Alert Modes:
- First Cross Only: Alert once when level is crossed
- All Crosses: Alert every time level is crossed
Alert Information:
- Level type crossed
- Specific price level
- Direction (above/below)
- One alert per bar to prevent spam
Configuration:
- Enable/disable by level type
- Choose alert frequency
- Customize for your trading style
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HOW TO USE
───────────────────────────────────────
INITIAL SETUP:
General Settings:
1. Enable "Use Dynamic ATR-Based Spacing" (recommended)
2. Set ATR Period (14 is standard)
3. Adjust ATR Multiplier (2.0 is balanced)
Visibility Settings:
1. Set Visible Range % (10% recommended for clarity)
2. Adjust Label Offset for readability
3. Configure performance limits if needed
Level Selection:
1. Enable/disable level types based on trading style
2. Adjust line counts for each type
3. Choose line styles and colors for visibility
TRADING STRATEGIES:
Breakout Trading:
1. Wait for price to approach major or standard level
2. Monitor for consolidation near level
3. Enter on confirmed break above/beyond level
4. Stop loss just beyond the broken level
5. Target: Next major or standard level
Rejection Trading:
1. Identify major psychological level
2. Wait for price to test the level
3. Look for rejection signals (wicks, bearish/bullish candles)
4. Enter in direction of rejection
5. Stop beyond the level
6. Target: Previous level or mid-level
Range Trading:
1. Identify range between two major levels
2. Buy at lower psychological level
3. Sell at upper psychological level
4. Use standard and mid-levels for position management
5. Exit if major level breaks with volume
Confluence Trading:
1. Look for combined levels (Std + Major)
2. These represent high-probability zones
3. Use as primary support/resistance
4. Increase position size at confluence
5. Expect stronger reactions at these levels
Session-Based Trading:
1. Note opening level at session start (Asian/London/NY)
2. Trade breakouts of major levels during high-volume sessions
3. London/NY sessions: More likely to break levels
4. Asian session: More likely to respect levels (range trading)
RISK MANAGEMENT WITH PSYCHOLOGICAL LEVELS:
Stop Loss Placement:
- Place stops just beyond psychological levels
- Add buffer (5-10 pips for forex)
- Avoid exact round numbers (stop hunting risk)
- Use previous major level as maximum stop
Take Profit Strategy:
- First target: Next standard level (partial profit)
- Second target: Next major level (remaining position)
- Trail stops to breakeven at first target
- Use distance table to calculate risk/reward
Position Sizing:
- Larger positions at major levels (higher probability)
- Smaller positions at intraday levels (lower probability)
- Scale in at standard levels between major levels
- Reduce size when multiple levels are close together
TIMEFRAME CONSIDERATIONS:
Higher Timeframes (4H, Daily, Weekly):
- Focus on Major and Standard levels only
- Disable Intraday and Mid levels
- Wider level spacing expected
- Use for swing trading and position trading
Lower Timeframes (5m, 15m, 1H):
- Enable all level types
- Use Intraday levels for precision
- Tighter level spacing acceptable
- Good for day trading and scalping
Multi-Timeframe Approach:
- Identify major levels on Daily/4H charts
- Refine entries using 15m/1H intraday levels
- Trade in direction of higher timeframe bias
- Use lower timeframe levels for position management
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CONFIGURATION GUIDE
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GENERAL SETTINGS:
Dynamic ATR-Based Spacing:
- Enabled: Recommended for most markets
- Disabled: Fixed psychological levels
- ATR Period: 14 (standard), 10 (responsive), 20 (smooth)
- ATR Multiplier: 1.0-5.0 (2.0 is balanced)
VISIBILITY SETTINGS:
Visible Range %:
- 5%: Very tight range, minimal clutter
- 10%: Balanced view (recommended)
- 20%: Wide range, more context
- 50%: Maximum range, all levels visible
Label Offset:
- 10-20 bars: Close to current price
- 30-50 bars: Moderate distance
- 50-100 bars: Far from price action
Performance Limits:
- Max Historical Bars: Reduce if indicator loads slowly
- Max Labels: Reduce for cleaner chart (20-30 recommended)
LEVEL CUSTOMIZATION:
Line Count:
- Lower (1-3): Cleaner chart, fewer levels
- Medium (4-6): Balanced view
- Higher (7-10): More context, busier chart
Line Styles:
- Solid: High importance, easy to see
- Dashed: Medium importance, clear but subtle
- Dotted: Low importance, minimal visual weight
Colors:
- Use contrasting colors for different level types
- Red/Blue/Yellow default works well
- Adjust based on chart background and personal preference
DISTANCE TABLE:
Position:
- Top Right: Doesn't interfere with price action
- Top Left: Good for right-side price scale
- Bottom positions: Less common but available
Colors:
- Default (white text, dark background) works for most charts
- Match your chart theme for consistency
- Ensure text is readable against background
ALERT CONFIGURATION:
Alert by Level Type:
- Major: Most important, fewer false signals
- Standard: Balance of frequency and importance
- Intraday: Many signals, best for active traders
Alert Frequency:
- First Cross Only: Cleaner, less noise (recommended for swing trading)
- All Crosses: Every touch, good for scalping
Alert Setup in TradingView:
1. Configure desired alert types in indicator settings
2. Right-click chart → Add Alert
3. Select this indicator
4. Choose "Any alert() function call"
5. Set delivery method (mobile, email, webhook)
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ASSET-SPECIFIC TIPS
───────────────────────────────────────
FOREX (EUR/USD, GBP/USD, etc.):
- Major levels at x.x000, x.x500
- Standard levels at x.xx00
- Intraday levels at 20/50/80 pips
- Most effective during London/NY sessions
- Watch for "figure" levels (1.0000, 1.1000)
CRYPTOCURRENCIES (BTC, ETH, etc.):
- Enable dynamic spacing for volatile markets
- Levels adjust automatically based on price
- Watch major $1,000 increments for BTC
- $100 levels important for ETH
- Smaller caps: Use standard levels
- High volatility: Increase ATR multiplier to 3.0
STOCK INDICES (SPX, NASDAQ, etc.):
- 100-point levels most important
- 500-point levels for major S/R
- 50-point mid-levels for refinement
- Watch end-of-day for level reactions
- Futures often lead spot on level breaks
GOLD/COMMODITIES:
- Major levels at $50 increments ($1,900, $1,950)
- Standard levels at $10 increments
- Very reactive to psychological levels
- Watch for false breaks during low volume
- Best reactions during active trading hours
───────────────────────────────────────
BEST PRACTICES
───────────────────────────────────────
Chart Setup:
- Use clean price action charts
- Avoid too many indicators
- Ensure psychological levels are clearly visible
- Match colors to your chart theme
Level Selection:
- Start with Major and Standard levels only
- Add Mid and Intraday as needed
- Less is more - avoid chart clutter
- Adjust based on timeframe
Combining with Other Tools:
- Volume profile for confluence
- Trendlines intersecting psychological levels
- Moving averages near round numbers
- Fibonacci levels coinciding with psychological levels
Common Mistakes to Avoid:
- Trading every level touch (be selective)
- Ignoring volume confirmation
- Setting stops exactly at levels (stop hunting)
- Forgetting to adjust for different assets
- Over-relying on levels without price action confirmation
Performance Optimization:
- Reduce visible range for faster loading
- Lower max historical bars on lower timeframes
- Limit labels to 30-50 for clarity
- Disable unused level types
───────────────────────────────────────
EDUCATIONAL DISCLAIMER
───────────────────────────────────────
This indicator identifies psychological price levels based on round numbers that tend to act as support and resistance. The methodology includes:
- Round number detection algorithms
- ATR-based dynamic spacing calculations
- Asset-specific level determination
- Distance percentage calculations
Psychological levels are a recognized concept in technical analysis, studied by traders and institutions. However, they do not guarantee price reactions and should be used as part of a comprehensive trading strategy including proper risk management, volume analysis, and price action confirmation.
───────────────────────────────────────
USAGE DISCLAIMER
───────────────────────────────────────
This tool is for educational and analytical purposes. Psychological levels can act as support or resistance but price reactions are not guaranteed. Dynamic spacing may generate different levels in different market conditions. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results.
───────────────────────────────────────
CREDITS & ATTRIBUTION
───────────────────────────────────────
Original Concept: Sonar Lab
Retail vs Banker Net Positions – Symmetry BreakRetail vs Banker Net Positions – Symmetry Break (Institution Focus)
Description:
This advanced indicator is a volume-proxy-based positioning tool that separates institutional vs. retail behavior using bar structure, trend-following logic, and statistical analysis. It identifies net position flows over time, detects institutional aggression spikes, and highlights symmetry breaks—those moments when institutional action diverges sharply from retail behavior. Designed for intraday to swing traders, this is a powerful tool for gauging smart money activity and retail exhaustion.
What It Does:
Separates Volume into Two Groups:
Institutional Proxy: Volume on large bars in trend direction
Retail Proxy: Volume on small or counter-trend bars
Calculates Net Positions (%):
Smooths cumulative buying vs. selling behavior for each group over time.
Highlights Symmetry Breaks:
Alerts when institutions make statistically abnormal moves while retail is quiet or doing the opposite.
Detects Extremes in Institutional Activity:
Flags major tops/bottoms in institutional positioning using swing pivots or rolling windows.
Retail Sentiment Flips:
Marks when the retail line crosses the zero line (e.g., flipping from net short to net long).
How to Use It:
Interpreting the Two Lines:
Aqua/Orange Line (Institutional Proxy):
Rising above zero = Net buying bias
Falling below zero = Net selling bias
Lime/Red Line (Retail Proxy):
Green = Retail buying; Red = Retail selling
Watch for crosses of zero for sentiment shifts
Spotting Symmetry Breaks:
Pink Circle or Background Highlight =
Institutions made a sharp, outsized move while retail was:
Quiet (low ROC), or
Moving in the opposite direction
These often precede explosive directional moves or stop hunts.
Institutional Extremes:
Marked with aqua (top) or orange (bottom) dots
Based on swing pivot logic or rolling highs/lows in institutional positioning
Optional filter: Only show extremes that coincide with a symmetry break
Settings You Can Tune:
Lookback lengths for trend, z-scores, smoothing
Z-Score thresholds to control sensitivity
Retail quiet filters to reduce false positives
Cool-down timer to avoid rapid repeat signals
Toggle visual aids like shading, markers, and threshold lines
Alerts Included:
-Retail flips (green/red)
- Institutional symmetry breaks
- Institutional extreme tops/bottoms
Strategy Tip:
Use this indicator to track institutional accumulation or distribution phases and catch asymmetric inflection points where the "smart money" acts decisively. Confluence with price structure or FVGs (Fair Value Gaps) can further enhance signal quality.
Trend Pullback System```{"variant":"standard","id":"36492","title":"Trend Pullback System Description"}
Trend Pullback System is a price-action trend continuation model that looks to enter on pullbacks, not breakouts. It’s designed to find high-quality long/short entries inside an already established trend, place the stop at meaningful structure, trail that stop as structure evolves, and warn you when the trade thesis is no longer valid.
Developed by: Mohammed Bedaiwi
---------------------------------
HOW IT WORKS
---------------------------------
1. Trend Detection
• The strategy defines overall bias using moving averages.
• Bullish environment (“uptrend”): price above the slower MA, fast MA above slow MA, and the slow MA is sloping up.
• Bearish environment (“downtrend”): price below the slower MA, fast MA below slow MA, and the slow MA is sloping down.
This prevents trading against chop and focuses on continuation moves in the dominant direction.
2. Pullback + Re-entry Logic
• The script waits for price to pull back into structure (support in an uptrend, resistance in a downtrend), and then push back in the direction of the main trend.
• That “push back” is the setup trigger. We don’t chase the first breakout candle — we buy/sell the retest + resume.
3. Structural Levels (“Diamonds”)
• Green diamond (below bar): bullish pivot low formed while the trend is bullish. This marks defended support.
- Use it as a re-entry zone for longs.
- Use it to trail a stop higher when you’re already long.
- Shorts can take profit here because buyers stepped in.
• Red diamond (above bar): bearish pivot high formed while the trend is bearish. This marks defended resistance.
- Use it as a re-entry zone for shorts.
- Use it to trail a stop lower when you’re already short.
- Longs can take profit here because sellers stepped in.
4. Entry Signals
• BUY arrow (green triangle up under the candle, text like “BUY” / “BUY Zone”):
- LongSetup is true.
- Trend is bullish or turning bullish.
- Price just bounced off recent defended support (green diamond) and reclaimed short-term momentum.
Meaning: enter long here or cover/exit shorts.
• SELL arrow (red triangle down above the candle):
- ShortSetup is true.
- Trend is bearish or turning bearish.
- Price just rolled down from defended resistance (red diamond) and lost short-term momentum.
Meaning: enter short here or take profit on longs.
These are the primary trade entries. They are meant to be actionable.
5. Weak Setups (“W” in yellow)
• Yellow triangle with “W”:
- A possible long/short idea is trying to form, BUT the higher-timeframe confirmation is not fully there yet.
- Think of it as early pressure / early caution, not a full signal.
• You usually watch these areas rather than jumping in immediately.
6. Exit Warning (orange “EXIT” label above a bar)
• The strategy will raise an EXIT marker when you’re in a trade and the *opposite* side just produced a confirmed setup.
- You’re short and a valid longSetup appears → EXIT.
- You’re long and a valid shortSetup appears → EXIT.
• This is basically: “Close or reduce — the other side just took control.”
• It’s not just a trailing stop hit; it’s a regime flip warning.
7. Stop, Target, and Trailing
• On every new setup, the script records:
- Initial stop: recent swing beyond the defended level (below support for longs, above resistance for shorts).
- Initial target: recent opposing swing.
• While you’re in position, if new confirming diamonds print in your favor, the stop can trail toward the new defended level.
• This creates structure-based risk management (not just fixed % or ATR).
8. Reference Levels
• The strategy also plots prior higher-timeframe closes (last week’s close, last month’s close, last year’s close). These can behave as magnets or stall points.
• They’re helpful for take-profit timing and for reading “are we trading above or below last month’s close?”
9. Momentum Panel (hidden by default)
• Internally, the script calculates an SMI-style momentum oscillator with overbought/oversold zones.
• This is optional visual confirmation and does not drive the core entry/exit logic.
---------------------------------
WHAT A TRADE LOOKS LIKE IN REAL PRICE ACTION
---------------------------------
Early warning
• Yellow W + red diamonds + red down arrows = “This is getting weak. Short setups are here.”
• You may also see something like “My Short Entry Id.” That’s where the short side actually engages.
Bearish follow-through, then exhaustion
• Price bleeds down.
• Then the orange EXIT appears.
→ Translation: “If you’re still short, close it. Buyers are stepping in hard. Risk of reversal is now high.”
Regime flip
• Right after EXIT, multiple green BUY arrows fire together (“BUY”, “BUYZone”).
• That’s the true long trigger.
→ This is where you either enter long or flip from short to long.
Expansion leg
• After that flip, price rips up for multiple candles / days / weeks.
• While it runs:
- Green diamonds appear under pullbacks → “dip buy zones / trail stop up here.”
- More BUY arrows show on minor pullbacks → continuation long / scale adds.
Distribution / topping
• Later, you start seeing new yellow W triangles again near local highs. That’s your “careful, this might be topping” warning.
• You finally get a hard red candle, and green diamonds stop stacking.
→ That’s where you tighten risk, scale out, or assume the move is mature.
In plain terms, the model is doing the following for you:
• It puts you short during weakness.
• It tells you when to get OUT of the short.
• It flips you long right as control changes.
• It gives you a structure-based trail the whole way up.
• It warns you again when momentum at the top starts cracking.
That is exactly how the logic was designed.
---------------------------------
QUICK INTERPRETATION CHEAT SHEET
---------------------------------
🔻 Red triangle + “Short Entry” near a red diamond
→ Short entry zone (or take profit on a long).
🟥 Red diamond above bar
→ Sellers defended here. Treat it as resistance. Good place to trail short stops just above that level. Avoid chasing longs straight into it.
🟨 Yellow W
→ Attention only. Early pressure / possible turn. Not fully confirmed.
🟧 EXIT (orange label)
→ The opposite side just printed a real setup. Close the old idea (cover shorts if you’re short, exit longs if you’re long). Thesis invalid.
🟩 Burst of green BUY triangles after EXIT
→ Long entry. Also a “cover shorts now” alert. This is the core money entry in bullish reversals.
💎 Green diamond below bar
→ Bulls defended that level. Good for trailing your long stop up, and good “buy the dip in trend” locations.
📈 Blue / teal MAs stacked and rising
→ Confirmed bullish structure. You’re in trend continuation mode, so dips are opportunities, not automatic exits.
---------------------------------
COLOR / SHAPE KEY
---------------------------------
• Green triangle up (“BUY”, “BUY Zone”):
Long entry / cover shorts / continuation long trigger.
• Red triangle down:
Short entry / take profit on longs / continuation short trigger.
• Orange “EXIT” label:
Opposite side just fired a real setup. The previous trade thesis is now invalid.
• Green diamond below price:
Bullish defended support in an uptrend. Use for dip buys, trailing stops on longs, and objective cover zones for shorts.
• Red diamond above price:
Bearish defended resistance in a downtrend. Use for re-entry shorts, trailing stops on shorts, and objective scale-out zones for longs.
• Yellow “W”:
Weak / early potential setup. Watch it, don’t blindly trust it.
• Moving average bands (fast MA, slow MA, Hull MA):
When stacked and rising, bullish control. When stacked and falling, bearish control.
---------------------------------
INTENT
---------------------------------
This system is built to:
• Trade with momentum, not against it.
• Enter on pullbacks into proven structure, not chase stretched breakouts.
• Automate stop/target logic around actual defended swing levels.
• Warn you when the other side takes over so you don’t give back gains.
Typical usage:
1. In an uptrend, wait for price to pull back, print a green diamond (support proved), then take the first BUY arrow that fires.
2. In a downtrend, wait for a bounce into resistance, print a red diamond (sellers proved), then take the first SELL arrow that fires.
3. Respect EXIT when it appears — that’s the model saying “this trade is done.”
---------------------------------
DISCLAIMER
---------------------------------
This script is for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security, cryptoasset, or derivative. Markets carry risk. Past performance does not guarantee future results. You are fully responsible for your own decisions, position sizing, risk management, and compliance with all applicable laws and regulations.
Session Streaks [LuxAlgo]The Session Streaks tool allows traders to identify whether a session is bullish or bearish on the chart. It also shows the current session streak, or the number of consecutive bullish or bearish sessions.
The tool features a dashboard with information about the session streaks of the underlying product on the chart.
🔶 USAGE
Analyzing session streaks is commonly used for market timing by studying the number of consecutive sessions over time and how long they last before the market changes direction.
We identify a bullish session as one in which the closing price is equal to or greater than the opening price, and a bearish session as one in which the closing price is below the opening price.
Each session is labeled according to its bias (bullish or bearish) and the number of consecutive sessions of the same type that conform the current streak.
🔹 Dashboard
The dashboard at the top shows information about the current session.
Under the "Streaks" header, historical information about session streaks is displayed, divided into bullish and bearish categories.
Number: Total number of streaks.
Median: The average duration of those streaks. We chose the median over the mean to avoid misrepresentation due to outliers.
Mode: The most common streak duration.
As the image shows, for this particular market, there are more bullish streaks than bearish ones. Bullish streaks have an average duration that is longer than that of bearish streaks, and both have the same most common streak duration.
If the current session is bullish and the median streak duration for bullish sessions is three, then we could consider scenarios in which the next two sessions are bullish.
🔶 DETAILS
🔹 Streaks On Larger Timeframes
On timeframes lower than or equal to Daily, the tool identifies each consecutive session, but this behavior changes on larger timeframes.
On timeframes larger than daily, the tool identifies the last session of each bar. Let's use the chart in the image as a reference.
At the top of the image, there is a daily chart where each session corresponds to each candle. One candle equals one day.
In the middle, we have a weekly chart where each session is the last session of each week, which is usually Friday for the Nasdaq 100 futures contract. The levels and labels displayed correspond to the last session within each candle, which is the last day of each week.
The levels and labels on the monthly chart correspond to the last session of each month, which is the last day of each month.
🔹 Gradient Style
Traders can choose between two different color gradients for the session background. Each gradient provides different information about price behavior within each session.
Horizontal: Green indicates prices at the top of the session range and red indicates prices at the bottom.
Vertical: Green indicates prices that are equal to or greater than the open price and red indicates prices that are below the open price of the session.
🔶 SETTINGS
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Position: Select the location of the dashboard.
Size: Select the dashboard size.
🔹 Style
Bullish: Select a color for bullish sessions.
Bearish: Select a color for bearish sessions.
Transparency: Select a transparency level from 100 to 0.
Gradient: Select a horizontal or vertical gradient.
Auto Fibonacci LevelsAuto Fibonacci Momentum Zones with Visible Range Table
Overview and Originality
The Auto Fibonacci Momentum Zones indicator offers a streamlined, static overlay of Fibonacci retracement levels inspired by extreme RSI momentum thresholds, enhanced with a dynamic table displaying the high and low of the currently visible chart range. This isn't a repackaged RSI oscillator or basic Fib drawer—common in TradingView's library—but a purposeful fusion of geometric harmony (Fibonacci ratios) with momentum psychology (RSI extremes at 35/85), projected as fixed horizontal reference lines on the price chart. The addition of the visible range table, powered by PineCoders' VisibleChart library, provides real-time context for the chart's current view, enabling traders to quickly assess range compression or expansion relative to these zones.
This script's originality stems from its "static momentum mapping": by hardcoding Fib levels on a dynamic chart, it creates universal psychological support/resistance lines that transcend specific assets or timeframes.
Unlike dynamic Fib tools that auto-adjust to price swings (risking noise in ranging markets) or standalone RSI plots (confined to panes), this delivers clean, bias-adjustable overlays for confluence analysis. The visible range table justifies the library integration—it's not a gratuitous add-on but a complementary tool that quantifies the "screen real estate" of price action, helping users correlate Fib touches with actual volatility. Drawn from original code (no auto-generation or public templates), it builds TradingView's body of knowledge by simplifying multi-tool workflows into one indicator, ideal for discretionary traders who value visual efficiency over algorithmic complexity.
How It Works: Underlying Concepts
Fibonacci retracements, derived from the Fibonacci sequence and the golden ratio (≈0.618), identify potential reversal points based on the idea that markets retrace prior moves in predictable proportions: shallow (23.6%, 38.2%), mid (50%), and deep (61.8%, 78.6%).
Adjustable Outputs
1. The "Invert Fibs" toggle (default: true) for bearish/topping bias, can be flipped aligning with trend context.
2. Fibonacci Levels: Seven semi-transparent horizontal lines are drawn using `hline()`:
- 0.0 at high (gray).
- 0.236: high - (range × 0.236) (light cyan, shallow pullback).
- 0.382: high - (range × 0.382) (teal, common retracement).
- 0.5: midpoint average (green, equilibrium).
- 0.618: high - (range × 0.618) (amber, golden pocket for reversals).
- 0.786: high - (range × 0.786) (orange, deep support).
- 1.0 at low (gray).
Colors progress from cool (shallow) to warm (deep) for intuitive scanning.
3. Optional Fib Labels: Right-edge text labels (e.g., "0.618") appear only if enabled, positioned at the last bar + offset for non-cluttering visibility.
4. Visible Range Table: Leveraging the VisibleChart library's `visible.high()` and `visible.low()` functions, a compact 2x2 table (top-right corner) updates on the last bar to show the extrema of bars currently in view. This mashup enhances utility: Fib zones provide fixed anchors, while the table's dynamic values reveal if price is "pinned" to a zone (e.g., visible high hugging 0.382 signals resistance). The library is invoked sparingly for performance, adding value by bridging static geometry with viewport-aware data—unavailable in built-ins without custom code.
How to Use It
1. Setup:
Add to any chart (e.g., 15M for scalps, Daily for swings). As an overlay, lines appear directly on price candles—adjust chart scaling if needed.
2. Input Tweaks:
Invert Fibs: Enable for downtrends (85 top), disable for uptrends (35 bottom).
Show Fibs: Toggle labels for ratio callouts (off for clean charts).
Show Table: Display/hide the visible high/low summary (red for high, green for low, formatted to 2 decimals).
3. Trading Application:
Zone Confluence: Seek price reactions at each fibonacci level—e.g., a doji at 0.618 + rising volume suggests entry; use 0.0/1.0 as invalidation.
Range Context: Check the table: If visible high/low spans <20% of the Fib arc (e.g., both near 0.5), anticipate breakout; wider spans signal consolidation.
Multi-Timeframe: Overlay on higher TF for bias, lower for precision—e.g., Daily Fibs guide 1H entries.
Enhancements: Pair with volume or candlesticks; set alerts on line crosses via TradingView's built-in tools. Backtest on your symbols to validate (e.g., equities favor 0.382, forex the 0.786).
This indicator automates advanced Fibonacci synthesis dynamically, eliminating manual measurement and calculations.
published by ozzy_livin
Candle Size MonitorCandle Size Monitor – Description
Update 27.10.25
Objective Volatility Assessment
The Candle Size Monitor helps traders assess actual market movement—regardless of whether candles appear visually large or small on the chart. It supports evaluating whether your planned trade structure (e.g., stop-loss, take-profit) aligns with current volatility.
Key Features
Volatility Analysis:
Calculates the average candle size (difference between high and low) over a user-defined number of candles.
Identifies the largest candle in the selected period.
Displays results in a compact table on the chart.
Exchange Rate Integration (optional):
Shows the current USD-EUR exchange rate (formatted with German-style comma and four decimal places).
Useful for traders in USD-denominated markets who apply EUR-based risk management rules.
Customizable Display:
Text Size: Small, medium, or large.
Colors: Customizable text and background colors.
Table Position: Top/bottom left/right.
Number of Candles: User-defined (default: 20).
Dynamic Updates:
The table updates with each new bar.
The exchange rate is fetched in real-time from OANDA:EURUSD.
Settings and Translations
Settings
Anzahl Kerzen → Number of Candles (Number of candles for calculation, default: 20).
Textgröße → Text Size (Text size in the table: small, medium, large).
Textfarbe → Text Color (Text color, default: white).
Hintergrundfarbe → Background Color (Background color of the table, default: black).
Position → Position (Table position: Top Left, Top Right, Bottom Left, Bottom Right).
Wechselkurs anzeigen (USD → EUR) → Show Exchange Rate (USD → EUR) (Option to display the exchange rate).
Table Contents and Translations
The table displays the following information (with German formatting):
Ø Größe (N):
English: "Avg Size (N): " (Average candle size over the last N candles).
Example: "Ø Größe (20): 15,3" → "Avg Size (20): 15.3".
Größte Kerze:
English: "Largest Candle: " (Largest candle size in the selected period).
Example: "Größte Kerze: 42,7" → "Largest Candle: 42.7".
1 USD = € (only if enabled)
English: "1 USD = EUR" (Current USD-EUR exchange rate, formatted with a comma).
Example: "1 USD = 0,9234 €" → "1 USD = 0.9234 EUR".
COT IndexTHE HIDDEN INTELLIGENCE IN FUTURES MARKETS
What if you could see what the smartest players in the futures markets are doing before the crowd catches on? While retail traders chase momentum indicators and moving averages, obsess over Japanese candlestick patterns, and debate whether the RSI should be set to fourteen or twenty-one periods, institutional players leave footprints in the sand through their mandatory reporting to the Commodity Futures Trading Commission. These footprints, published weekly in the Commitment of Traders reports, have been hiding in plain sight for decades, available to anyone with an internet connection, yet remarkably few traders understand how to interpret them correctly. The COT Index indicator transforms this raw institutional positioning data into actionable trading signals, bringing Wall Street intelligence to your trading screen without requiring expensive Bloomberg terminals or insider connections.
The uncomfortable truth is this: Most retail traders operate in a binary world. Long or short. Buy or sell. They apply technical analysis to individual positions, constrained by limited capital that forces them to concentrate risk in single directional bets. Meanwhile, institutional traders operate in an entirely different dimension. They manage portfolios dynamically weighted across multiple markets, adjusting exposure based on evolving market conditions, correlation shifts, and risk assessments that retail traders never see. A hedge fund might be simultaneously long gold, short oil, neutral on copper, and overweight agricultural commodities, with position sizes calibrated to volatility and portfolio Greeks. When they increase gold exposure from five percent to eight percent of portfolio allocation, this rebalancing decision reflects sophisticated analysis of opportunity cost, risk parity, and cross-market dynamics that no individual chart pattern can capture.
This portfolio reweighting activity, multiplied across hundreds of institutional participants, manifests in the aggregate positioning data published weekly by the CFTC. The Commitment of Traders report does not show individual trades or strategies. It shows the collective footprint of how actual commercial hedgers and large speculators have allocated their capital across different markets. When mining companies collectively increase forward gold sales to hedge thirty percent more production than last quarter, they are not reacting to a moving average crossover. They are making strategic allocation decisions based on production forecasts, cost structures, and price expectations derived from operational realities invisible to outside observers. This is portfolio management in action, revealed through positioning data rather than price charts.
If you want to understand how institutional capital actually flows, how sophisticated traders genuinely position themselves across market cycles, the COT report provides a rare window into that hidden world. But understand what you are getting into. This is not a tool for scalpers seeking confirmation of the next five-minute move. This is not an oscillator that flashes oversold at market bottoms with convenient precision. COT analysis operates on a timescale measured in weeks and months, revealing positioning shifts that precede major market turns but offer no precision timing. The data arrives three days stale, published only once per week, capturing strategic positioning rather than tactical entries.
If you need instant gratification, if you trade intraday moves, if you demand mechanical signals with ninety percent accuracy, close this document now. COT analysis rewards patience, position sizing discipline, and tolerance for being early. It punishes impatience, overleveraging, and the expectation that any single indicator can substitute for market understanding.
The premise is deceptively simple. Every Tuesday, large traders in futures markets must report their positions to the CFTC. By Friday afternoon, this data becomes public. Academic research spanning three decades has consistently shown that not all market participants are created equal. Some traders consistently profit while others consistently lose. Some anticipate major turning points while others chase trends into exhaustion. Bessembinder and Chan (1992) demonstrated in their seminal study that commercial hedgers, those with actual exposure to the underlying commodity or financial instrument, possess superior forecasting ability compared to speculators. Their research, published in the Journal of Finance, found statistically significant predictive power in commercial positioning, particularly at extreme levels. This finding challenged the efficient market hypothesis and opened the door to a new approach to market analysis based on positioning rather than price alone.
Think about what this means. Every week, the government publishes a report showing you exactly how the most informed market participants are positioned. Not their opinions. Not their predictions. Their actual money at risk. When agricultural producers collectively hold their largest short hedge in five years, they are not making idle speculation. They are locking in prices for crops they will harvest, informed by private knowledge of weather conditions, soil quality, inventory levels, and demand expectations invisible to outside observers. When energy companies aggressively hedge forward production at current prices, they reveal information about expected supply that no analyst report can capture. This is not technical analysis based on past prices. This is not fundamental analysis based on publicly available data. This is behavioral analysis based on how the smartest money is actually positioned, how institutions allocate capital across portfolios, and how those allocation decisions shift as market conditions evolve.
WHY SOME TRADERS KNOW MORE THAN OTHERS
Building on this foundation, Sanders, Boris and Manfredo (2004) conducted extensive research examining the behaviour patterns of different trader categories. Their work, which analyzed over a decade of COT data across multiple commodity markets, revealed a fascinating dynamic that challenges much of what retail traders are taught. Commercial hedgers consistently positioned themselves against market extremes, buying when speculators were most bearish and selling when speculators reached peak bullishness. The contrarian positioning of commercials was not random noise but rather reflected their superior information about supply and demand fundamentals. Meanwhile, large speculators, primarily hedge funds and commodity trading advisors, exhibited strong trend-following behaviour that often amplified market moves beyond fundamental values. Small traders, the retail participants, consistently entered positions late in trends, frequently near turning points, making them reliable contrary indicators.
Wang (2003) extended this research by demonstrating that the predictive power of commercial positioning varies significantly across different commodity sectors. His analysis of agricultural commodities showed particularly strong forecasting ability, with commercial net positions explaining up to fifteen percent of return variance in subsequent weeks. This finding suggests that the informational advantages of hedgers are most pronounced in markets where physical supply and demand fundamentals dominate, as opposed to purely financial markets where information asymmetries are smaller. When a corn farmer hedges six months of expected harvest, that decision incorporates private observations about rainfall patterns, crop health, pest pressure, and local storage capacity that no distant analyst can match. When an oil refinery hedges crude oil purchases and gasoline sales simultaneously, the spread relationships reveal expectations about refining margins that reflect operational realities invisible in public data.
The theoretical mechanism underlying these empirical patterns relates to information asymmetry and different participant motivations. Commercial hedgers engage in futures markets not for speculative profit but to manage business risks. An agricultural producer selling forward six months of expected harvest is not making a bet on price direction but rather locking in revenue to facilitate financial planning and ensure business viability. However, this hedging activity necessarily incorporates private information about expected supply, inventory levels, weather conditions, and demand trends that the hedger observes through their commercial operations (Irwin and Sanders, 2012). When aggregated across many participants, this private information manifests in collective positioning.
Consider a gold mining company deciding how much forward production to hedge. Management must estimate ore grades, recovery rates, production costs, equipment reliability, labor availability, and dozens of other operational variables that determine whether locking in prices at current levels makes business sense. If the industry collectively hedges more aggressively than usual, it suggests either exceptional production expectations or concern about sustaining current price levels or combination of both. Either way, this positioning reveals information unavailable to speculators analyzing price charts and economic data. The hedger sees the physical reality behind the financial abstraction.
Large speculators operate under entirely different incentives and constraints. Commodity Trading Advisors managing billions in assets typically employ systematic, trend-following strategies that respond to price momentum rather than fundamental supply and demand. When crude oil rallies from sixty dollars to seventy dollars per barrel, these systems generate buy signals. As the rally continues to eighty dollars, position sizes increase. The strategy works brilliantly during sustained trends but becomes a liability at reversals. By the time oil reaches ninety dollars, trend-following funds are maximally long, having accumulated positions progressively throughout the rally. At this point, they represent not smart money anticipating further gains but rather crowded money vulnerable to reversal. Sanders, Boris and Manfredo (2004) documented this pattern across multiple energy markets, showing that extreme speculator positioning typically marked late-stage trend exhaustion rather than early-stage trend development.
Small traders, the retail participants who fall below reporting thresholds, display the weakest forecasting ability. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns, meaning their aggregate positioning served as a reliable contrary indicator. The explanation combines several factors. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, entering trends after mainstream media coverage when institutional participants are preparing to exit. Perhaps most importantly, they trade with emotion, buying into euphoria and selling into panic at precisely the wrong times.
At major turning points, the three groups often position opposite each other with commercials extremely bearish, large speculators extremely bullish, and small traders piling into longs at the last moment. These high-divergence environments frequently precede increased volatility and trend reversals. The insiders with business exposure quietly exit as the momentum traders hit maximum capacity and retail enthusiasm peaks. Within weeks, the reversal begins, and positions unwind in the opposite sequence.
FROM RAW DATA TO ACTIONABLE SIGNALS
The COT Index indicator operationalizes these academic findings into a practical trading tool accessible through TradingView. At its core, the indicator normalizes net positioning data onto a zero to one hundred scale, creating what we call the COT Index. This normalization is critical because absolute position sizes vary dramatically across different futures contracts and over time. A commercial trader holding fifty thousand contracts net long in crude oil might be extremely bullish by historical standards, or it might be quite neutral depending on the context of total market size and historical ranges. Raw position numbers mean nothing without context. The COT Index solves this problem by calculating where current positioning stands relative to its range over a specified lookback period, typically two hundred fifty-two weeks or approximately five years of weekly data.
The mathematical transformation follows the methodology originally popularized by legendary trader Larry Williams, though the underlying concept appears in statistical normalization techniques across many fields. For any given trader category, we calculate the highest and lowest net position values over the lookback period, establishing the historical range for that specific market and trader group. Current positioning is then expressed as a percentage of this range, where zero represents the most bearish positioning ever seen in the lookback window and one hundred represents the most bullish extreme. A reading of fifty indicates positioning exactly in the middle of the historical range, suggesting neither extreme optimism nor pessimism relative to recent history (Williams and Noseworthy, 2009).
This index-based approach allows for meaningful comparison across different markets and time periods, overcoming the scaling problems inherent in analyzing raw position data. A commercial index reading of eighty-five in gold carries the same interpretive meaning as an eighty-five reading in wheat or crude oil, even though the absolute position sizes differ by orders of magnitude. This standardization enables systematic analysis across entire futures portfolios rather than requiring market-specific expertise for each contract.
The lookback period selection involves a fundamental tradeoff between responsiveness and stability. Shorter lookback periods, perhaps one hundred twenty-six weeks or approximately two and a half years, make the index more sensitive to recent positioning changes. However, it also increases noise and produces more false signals. Longer lookback periods, perhaps five hundred weeks or approximately ten years, create smoother readings that filter short-term noise but become slower to recognize regime changes. The indicator settings allow users to adjust this parameter based on their trading timeframe, risk tolerance, and market characteristics.
UNDERSTANDING CFTC DATA STRUCTURES
The indicator supports both Legacy and Disaggregated COT report formats, reflecting the evolution of CFTC reporting standards over decades of market development. Legacy reports categorize market participants into three broad groups: commercial traders (hedgers with underlying business exposure), non-commercial traders (large speculators seeking profit without commercial interest), and non-reportable traders (small speculators below reporting thresholds). Each category brings distinct motivations and information advantages to the market (CFTC, 2020).
The Disaggregated reports, introduced in September 2009 for physical commodity markets, provide finer granularity by splitting participants into five categories (CFTC, 2009). Producer and merchant positions capture those actually producing, processing, or merchandising the physical commodity. Swap dealers represent financial intermediaries facilitating derivative transactions for clients. Managed money includes commodity trading advisors and hedge funds executing systematic or discretionary strategies. Other reportables encompasses diverse participants not fitting the main categories. Small traders remain as the fifth group, representing retail participation.
This enhanced categorization reveals nuances invisible in Legacy reports, particularly distinguishing between different types of institutional capital and their distinct behavioural patterns. The indicator automatically detects which report type is appropriate for each futures contract and adjusts the display accordingly.
Importantly, Disaggregated reports exist only for physical commodity futures. Agricultural commodities like corn, wheat, and soybeans have Disaggregated reports because clear producer, merchant, and swap dealer categories exist. Energy commodities like crude oil and natural gas similarly have well-defined commercial hedger categories. Metals including gold, silver, and copper also receive Disaggregated treatment (CFTC, 2009). However, financial futures such as equity index futures, Treasury bond futures, and currency futures remain available only in Legacy format. The CFTC has indicated no plans to extend Disaggregated reporting to financial futures due to different market structures and participant categories in these instruments (CFTC, 2020).
THE BEHAVIORAL FOUNDATION
Understanding which trader perspective to follow requires appreciation of their distinct trading styles, success rates, and psychological profiles. Commercial hedgers exhibit anticyclical behaviour rooted in their fundamental knowledge and business imperatives. When agricultural producers hedge forward sales during harvest season, they are not speculating on price direction but rather locking in revenue for crops they will harvest. Their business requires converting volatile commodity exposure into predictable cash flows to facilitate planning and ensure survival through difficult periods. Yet their aggregate positioning reveals valuable information because these hedging decisions incorporate private information about supply conditions, inventory levels, weather observations, and demand expectations that hedgers observe through their commercial operations (Bessembinder and Chan, 1992).
Consider a practical example from energy markets. Major oil companies continuously hedge portions of forward production based on price levels, operational costs, and financial planning needs. When crude oil trades at ninety dollars per barrel, they might aggressively hedge the next twelve months of production, locking in prices that provide comfortable profit margins above their extraction costs. This hedging appears as short positioning in COT reports. If oil rallies further to one hundred dollars, they hedge even more aggressively, viewing these prices as exceptional opportunities to secure revenue. Their short positioning grows increasingly extreme. To an outside observer watching only price charts, the rally suggests bullishness. But the commercial positioning reveals that the actual producers of oil find these prices attractive enough to lock in years of sales, suggesting skepticism about sustaining even higher levels. When the eventual reversal occurs and oil declines back to eighty dollars, the commercials who hedged at ninety and one hundred dollars profit while speculators who chased the rally suffer losses.
Large speculators or managed money traders operate under entirely different incentives and constraints. Their systematic, momentum-driven strategies mean they amplify existing trends rather than anticipate reversals. Trend-following systems, the most common approach among large speculators, by definition require confirmation of trend through price momentum before entering positions (Sanders, Boris and Manfredo, 2004). When crude oil rallies from sixty dollars to eighty dollars per barrel over several months, trend-following algorithms generate buy signals based on moving average crossovers, breakouts, and other momentum indicators. As the rally continues, position sizes increase according to the systematic rules.
However, this approach becomes a liability at turning points. By the time oil reaches ninety dollars after a sustained rally, trend-following funds are maximally long, having accumulated positions progressively throughout the move. At this point, their positioning does not predict continued strength. Rather, it often marks late-stage trend exhaustion. The psychological and mechanical explanation is straightforward. Trend followers by definition chase price momentum, entering positions after trends establish rather than anticipating them. Eventually, they become fully invested just as the trend nears completion, leaving no incremental buying power to sustain the rally. When the first signs of reversal appear, systematic stops trigger, creating a cascade of selling that accelerates the downturn.
Small traders consistently display the weakest track record across academic studies. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns in his analysis across multiple commodity markets. This result means that whatever small traders collectively do, the opposite typically proves profitable. The explanation for small trader underperformance combines several factors documented in behavioral finance literature. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, learning about commodity trends through mainstream media coverage that arrives after institutional participants have already positioned. Perhaps most importantly, retail traders are more susceptible to emotional decision-making, buying into euphoria and selling into panic at precisely the wrong times (Tharp, 2008).
SETTINGS, THRESHOLDS, AND SIGNAL GENERATION
The practical implementation of the COT Index requires understanding several key features and settings that users can adjust to match their trading style, timeframe, and risk tolerance. The lookback period determines the time window for calculating historical ranges. The default setting of two hundred fifty-two bars represents approximately one year on daily charts or five years on weekly charts, balancing responsiveness with stability. Conservative traders seeking only the most extreme, highest-probability signals might extend the lookback to five hundred bars or more. Aggressive traders seeking earlier entry and willing to accept more false positives might reduce it to one hundred twenty-six bars or even less for shorter-term applications.
The bullish and bearish thresholds define signal generation levels. Default settings of eighty and twenty respectively reflect academic research suggesting meaningful information content at these extremes. Readings above eighty indicate positioning in the top quintile of the historical range, representing genuine extremes rather than temporary fluctuations. Conversely, readings below twenty occupy the bottom quintile, indicating unusually bearish positioning (Briese, 2008).
However, traders must recognize that appropriate thresholds vary by market, trader category, and personal risk tolerance. Some futures markets exhibit wider positioning swings than others due to seasonal patterns, volatility characteristics, or participant behavior. Conservative traders seeking high-probability setups with fewer signals might raise thresholds to eighty-five and fifteen. Aggressive traders willing to accept more false positives for earlier entry could lower them to seventy-five and twenty-five.
The key is maintaining meaningful differentiation between bullish, neutral, and bearish zones. The default settings of eighty and twenty create a clear three-zone structure. Readings from zero to twenty represent bearish territory where the selected trader group holds unusually bearish positions. Readings from twenty to eighty represent neutral territory where positioning falls within normal historical ranges. Readings from eighty to one hundred represent bullish territory where the selected trader group holds unusually bullish positions.
The trading perspective selection determines which participant group the indicator follows, fundamentally shaping interpretation and signal meaning. For counter-trend traders seeking reversal opportunities, monitoring commercial positioning makes intuitive sense based on the academic research discussed earlier. When commercials reach extreme bearish readings below twenty, indicating unprecedented short positioning relative to recent history, they are effectively betting against the crowd. Given their informational advantages demonstrated by Bessembinder and Chan (1992), this contrarian stance often precedes major bottoms.
Trend followers might instead monitor large speculator positioning, but with inverted logic compared to commercials. When managed money reaches extreme bullish readings above eighty, the trend may be exhausting rather than accelerating. This seeming paradox reflects their late-cycle participation documented by Sanders, Boris and Manfredo (2004). Sophisticated traders thus use speculator extremes as fade signals, entering positions opposite to speculator consensus.
Small trader monitoring serves primarily as a contrary indicator for all trading styles. Extreme small trader bullishness above seventy-five or eighty typically warns of retail FOMO at market tops. Extreme small trader bearishness below twenty or twenty-five often marks capitulation bottoms where the last weak hands have sold.
VISUALIZATION AND USER INTERFACE
The visual design incorporates multiple elements working together to facilitate decision-making and maintain situational awareness during active trading. The primary COT Index line plots in bold with adjustable line width, defaulting to two pixels for clear visibility against busy price charts. An optional glow effect, controlled by a simple toggle, adds additional visual prominence through multiple plot layers with progressively increasing transparency and width.
A twenty-one period exponential moving average overlays the index line, providing trend context for positioning changes. When the index crosses above its moving average, it signals accelerating bullish sentiment among the selected trader group regardless of whether absolute positioning is extreme. Conversely, when the index crosses below its moving average, it signals deteriorating sentiment and potentially the beginning of a reversal in positioning trends.
The EMA provides a dynamic reference line for assessing positioning momentum. When the index trades far above its EMA, positioning is not only extreme in absolute terms but also building with momentum. When the index trades far below its EMA, positioning is contracting or reversing, which may indicate weakening conviction even if absolute levels remain elevated.
The data table positioned at the top right of the chart displays eleven metrics for each trader category, transforming the indicator from a simple index calculation into an analytical dashboard providing multidimensional market intelligence. Beyond the COT Index itself, users can monitor positioning extremity, which measures how unusual current levels are compared to historical norms using statistical techniques. The extremity metric clarifies whether a reading represents the ninety-fifth or ninety-ninth percentile, with values above two standard deviations indicating genuinely exceptional positioning.
Market power quantifies each group's influence on total open interest. This metric expresses each trader category's net position as a percentage of total market open interest. A commercial entity holding forty percent of total open interest commands significantly more influence than one holding five percent, making their positioning signals more meaningful.
Momentum and rate of change metrics reveal whether positions are building or contracting, providing early warning of potential regime shifts. Position velocity measures the rate of change in positioning changes, effectively a second derivative providing even earlier insight into inflection points.
Sentiment divergence highlights disagreements between commercial and speculative positioning. This metric calculates the absolute difference between normalized commercial and large speculator index values. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals.
The table also displays concentration metrics when available, showing how positioning is distributed among the largest handful of traders in each category. High concentration indicates a few dominant players controlling most of the positioning, while low concentration suggests broad-based participation across many traders.
THE ALERT SYSTEM AND MONITORING
The alert system, comprising five distinct alert conditions, enables systematic monitoring of dozens of futures markets without constant screen watching. The bullish and bearish COT signal alerts trigger when the index crosses user-defined thresholds, indicating the selected trader group has reached extreme positioning worthy of attention. These alerts fire in real-time as new weekly COT data publishes, typically Friday afternoon following the Tuesday measurement date.
Extreme positioning alerts fire at ninety and ten index levels, representing the top and bottom ten percent of the historical range, warning of particularly stretched readings that historically precede reversals with high probability. When commercials reach a COT Index reading below ten, they are expressing their most bearish stance in the entire lookback period.
The data staleness alert notifies users when COT reports have not updated for more than ten days, preventing reliance on outdated information for trading decisions. Government shutdowns or federal holidays can interrupt the normal Friday publication schedule. Using stale signals while believing them current creates dangerous false confidence.
The indicator's watermark information display positioned in the bottom right corner provides essential context at a glance. This persistent display shows the symbol and timeframe, the COT report date timestamp, days since last update, and the current signal state. A trader analyzing a potential short entry in crude oil can glance at the watermark to instantly confirm positioning context without interrupting analysis flow.
LIMITATIONS AND REALISTIC EXPECTATIONS
Practical application requires understanding both the indicator's considerable strengths and inherent limitations. COT data inherently lags price action by three days, as Tuesday positions are not published until Friday afternoon. This delay means the indicator cannot catch rapid intraday reversals or respond to surprise news events. Traders using the COT Index for timing entries must accept this latency and focus on swing trading and position trading timeframes where three-day lags matter less than in day trading or scalping.
The weekly publication schedule similarly makes the indicator unsuitable for short-term trading strategies requiring immediate feedback. The COT Index works best for traders operating on weekly or longer timeframes, where positioning shifts measured in weeks and months align with trading horizon.
Extreme COT readings can persist far longer than typical technical indicators suggest, testing the patience and capital reserves of traders attempting to fade them. When crude oil enters a sustained bull market driven by genuine supply disruptions, commercial hedgers may maintain bearish positioning for many months as prices grind higher. A commercial COT Index reading of fifteen indicating extreme bearishness might persist for three months while prices continue rallying before finally reversing. Traders without sufficient capital and risk tolerance to weather such drawdowns will exit prematurely, precisely when the signal is about to work (Irwin and Sanders, 2012).
Position sizing discipline becomes paramount when implementing COT-based strategies. Rather than risking large percentages of capital on individual signals, successful COT traders typically allocate modest position sizes across multiple signals, allowing some to take time to mature while others work more quickly.
The indicator also cannot overcome fundamental regime changes that alter the structural drivers of markets. If gold enters a true secular bull market driven by monetary debasement, commercial hedgers may remain persistently bearish as mining companies sell forward years of production at what they perceive as favorable prices. Their positioning indicates valuation concerns from a production cost perspective, but cannot stop prices from rising if investment demand overwhelms physical supply-demand balance.
Similarly, structural changes in market participation can alter the meaning of positioning extremes. The growth of commodity index investing in the two thousands brought massive passive long-only capital into futures markets, fundamentally changing typical positioning ranges. Traders relying on COT signals without recognizing this regime change would have generated numerous false bearish signals during the commodity supercycle from 2003 to 2008.
The research foundation supporting COT analysis derives primarily from commodity markets where the commercial hedger information advantage is most pronounced. Studies specifically examining financial futures like equity indices and bonds show weaker but still present effects. Traders should calibrate expectations accordingly, recognizing that COT analysis likely works better for crude oil, natural gas, corn, and wheat than for the S&P 500, Treasury bonds, or currency futures.
Another important limitation involves the reporting threshold structure. Not all market participants appear in COT data, only those holding positions above specified minimums. In markets dominated by a few large players, concentration metrics become critical for proper interpretation. A single large trader accounting for thirty percent of commercial positioning might skew the entire category if their individual circumstances are idiosyncratic rather than representative.
GOLD FUTURES DURING A HYPOTHETICAL MARKET CYCLE
Consider a practical example using gold futures during a hypothetical but realistic market scenario that illustrates how the COT Index indicator guides trading decisions through a complete market cycle. Suppose gold has rallied from fifteen hundred to nineteen hundred dollars per ounce over six months, driven by inflation concerns following aggressive monetary expansion, geopolitical uncertainty, and sustained buying by Asian central banks for reserve diversification.
Large speculators, operating primarily trend-following strategies, have accumulated increasingly bullish positions throughout this rally. Their COT Index has climbed progressively from forty-five to eighty-five. The table display shows that large speculators now hold net long positions representing thirty-two percent of total open interest, their highest in four years. Momentum indicators show positive readings, indicating positions are still building though at a decelerating rate. Position velocity has turned negative, suggesting the pace of position building is slowing.
Meanwhile, commercial hedgers have responded to the rally by aggressively selling forward production and inventory. Their COT Index has moved inversely to price, declining from fifty-five to twenty. This bearish commercial positioning represents mining companies locking in forward sales at prices they view as attractive relative to production costs. The table shows commercials now hold net short positions representing twenty-nine percent of total open interest, their most bearish stance in five years. Concentration metrics indicate this positioning is broadly distributed across many commercial entities, suggesting the bearish stance reflects collective industry view rather than idiosyncratic positioning by a single firm.
Small traders, attracted by mainstream financial media coverage of gold's impressive rally, have recently piled into long positions. Their COT Index has jumped from forty-five to seventy-eight as retail investors chase the trend. Television financial networks feature frequent segments on gold with bullish guests. Internet forums and social media show surging retail interest. This retail enthusiasm historically marks late-stage trend development rather than early opportunity.
The COT Index indicator, configured to monitor commercial positioning from a contrarian perspective, displays a clear bearish signal given the extreme commercial short positioning. The table displays multiple confirming metrics: positioning extremity shows commercials at the ninety-sixth percentile of bearishness, market power indicates they control twenty-nine percent of open interest, and sentiment divergence registers sixty-five, indicating massive disagreement between commercial hedgers and large speculators. This divergence, the highest in three years, places the market in the historically high-risk category for reversals.
The interpretation requires nuance and consideration of context beyond just COT data. Commercials are not necessarily predicting an imminent crash. Rather, they are hedging business operations at what they collectively view as favorable price levels. However, the data reveals they have sold unusually large quantities of forward production, suggesting either exceptional production expectations for the year ahead or concern about sustaining current price levels or combination of both. Combined with extreme speculator positioning indicating a crowded long trade, and small trader enthusiasm confirming retail FOMO, the confluence suggests elevated reversal risk even if the precise timing remains uncertain.
A prudent trader analyzing this situation might take several actions based on COT Index signals. Existing long positions could be tightened with closer stop losses. Profit-taking on a portion of long exposure could lock in gains while maintaining some participation. Some traders might initiate modest short positions as portfolio hedges, sizing them appropriately for the inherent uncertainty in timing reversals. Others might simply move to the sidelines, avoiding new long entries until positioning normalizes.
The key lesson from case study analysis is that COT signals provide probabilistic edges rather than deterministic predictions. They work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five percent win rate with proper risk management produces substantial profits over time, yet still means forty-five percent of signals will be premature or wrong. Traders must embrace this probabilistic reality rather than seeking the impossible goal of perfect accuracy.
INTEGRATION WITH TRADING SYSTEMS
Integration with existing trading systems represents a natural and powerful use case for COT analysis, adding a positioning dimension to price-based technical approaches or fundamental analytical frameworks. Few traders rely exclusively on a single indicator or methodology. Rather, they build systems that synthesize multiple information sources, with each component addressing different aspects of market behavior.
Trend followers might use COT extremes as regime filters, modifying position sizing or avoiding new trend entries when positioning reaches levels historically associated with reversals. Consider a classic trend-following system based on moving average crossovers and momentum breakouts. Integration of COT analysis adds nuance. When large speculator positioning exceeds ninety or commercial positioning falls below ten, the regime filter recognizes elevated reversal risk. The system might reduce position sizing by fifty percent for new signals during these high-risk periods (Kaufman, 2013).
Mean reversion traders might require COT signal confluence before fading extended moves. When crude oil becomes technically overbought and large speculators show extreme long positioning above eighty-five, both signals confirm. If only technical indicators show extremes while positioning remains neutral, the potential short signal is rejected, avoiding fades of trends with underlying institutional support (Kaufman, 2013).
Discretionary traders can monitor the indicator as a continuous awareness tool, informing bias and position sizing without dictating mechanical entries and exits. A discretionary trader might notice commercial positioning shifting from neutral to progressively more bullish over several months. This trend informs growing positive bias even without triggering mechanical signals.
Multi-timeframe analysis represents another powerful integration approach. A trader might use daily charts for trade execution and timing while monitoring weekly COT positioning for strategic context. When both timeframes align, highest-probability opportunities emerge.
Portfolio construction for futures traders can incorporate COT signals as an additional selection criterion. Markets showing strong technical setups AND favorable COT positioning receive highest allocations. Markets with strong technicals but neutral or unfavorable positioning receive reduced allocations.
ADVANCED METRICS AND INTERPRETATION
The metrics table transforms simple positioning data into multidimensional market intelligence. Position extremity, calculated as the absolute deviation from the historical mean normalized by standard deviation, helps identify truly unusual readings versus routine fluctuations. A reading above two standard deviations indicates ninety-fifth percentile or higher extremity. Above three standard deviations indicates ninety-ninth percentile or higher, genuinely rare positioning that historically precedes major events with high probability.
Market power, expressed as a percentage of total open interest, reveals whose positioning matters most from a mechanical market impact perspective. Consider two scenarios in gold futures. In scenario one, commercials show a COT Index reading of fifteen while their market power metric shows they hold net shorts representing thirty-five percent of open interest. This is a high-confidence bearish signal. In scenario two, commercials also show a reading of fifteen, but market power shows only eight percent. While positioning is extreme relative to this category's normal range, their limited market share means less mechanical influence on price.
The rate of change and momentum metrics highlight whether positions are accelerating or decelerating, often providing earlier warnings than absolute levels alone. A COT Index reading of seventy-five with rapidly building momentum suggests continued movement toward extremes. Conversely, a reading of eighty-five with decelerating or negative momentum indicates the positioning trend is exhausting.
Position velocity measures the rate of change in positioning changes, effectively a second derivative. When velocity shifts from positive to negative, it indicates that while positioning may still be growing, the pace of growth is slowing. This deceleration often precedes actual reversal in positioning direction by several weeks.
Sentiment divergence calculates the absolute difference between normalized commercial and large speculator index values. When commercials show extreme bearish positioning at twenty while large speculators show extreme bullish positioning at eighty, the divergence reaches sixty, representing near-maximum disagreement. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals. The mechanism is intuitive. Extreme divergence indicates the informed hedgers and momentum-following speculators have positioned opposite each other with conviction. One group will prove correct and profit while the other proves incorrect and suffers losses. The resolution of this disagreement through price movement often involves volatility.
The table also displays concentration metrics when available. High concentration indicates a few dominant players controlling most of the positioning within a category, while low concentration suggests broad-based participation. Broad-based positioning more reliably reflects collective market intelligence and industry consensus. If mining companies globally all independently decide to hedge aggressively at similar price levels, it suggests genuine industry-wide view about price valuations rather than circumstances specific to one firm.
DATA QUALITY AND RELIABILITY
The CFTC has maintained COT reporting in various forms since the nineteen twenties, providing nearly a century of positioning data across multiple market cycles. However, data quality and reporting standards have evolved substantially over this long period. Modern electronic reporting implemented in the late nineteen nineties and early two thousands significantly improved accuracy and timeliness compared to earlier paper-based systems.
Traders should understand that COT reports capture positions as of Tuesday's close each week. Markets remain open three additional days before publication on Friday afternoon, meaning the reported data is three days stale when received. During periods of rapid market movement or major news events, this lag can be significant. The indicator addresses this limitation by including timestamp information and staleness warnings.
The three-day lag creates particular challenges during extreme volatility episodes. Flash crashes, surprise central bank interventions, geopolitical shocks, and other high-impact events can completely transform market positioning within hours. Traders must exercise judgment about whether reported positioning remains relevant given intervening events.
Reporting thresholds also mean that not all market participants appear in disaggregated COT data. Traders holding positions below specified minimums aggregate into the non-reportable or small trader category. This aggregation affects different markets differently. In highly liquid contracts like crude oil with thousands of participants, reportable traders might represent seventy to eighty percent of open interest. In thinly traded contracts with only dozens of active participants, a few large reportable positions might represent ninety-five percent of open interest.
Another data quality consideration involves trader classification into categories. The CFTC assigns traders to commercial or non-commercial categories based on reported business purpose and activities. However, this process is not perfect. Some entities engage in both commercial and speculative activities, creating ambiguity about proper classification. The transition to Disaggregated reports attempted to address some of these ambiguities by creating more granular categories.
COMPARISON WITH ALTERNATIVE APPROACHES
Several alternative approaches to COT analysis exist in the trading community beyond the normalization methodology employed by this indicator. Some analysts focus on absolute position changes week-over-week rather than index-based normalization. This approach calculates the change in net positioning from one week to the next. The emphasis falls on momentum in positioning changes rather than absolute levels relative to history. This method potentially identifies regime shifts earlier but sacrifices cross-market comparability (Briese, 2008).
Other practitioners employ more complex statistical transformations including percentile rankings, z-score standardization, and machine learning classification algorithms. Ruan and Zhang (2018) demonstrated that machine learning models applied to COT data could achieve modest improvements in forecasting accuracy compared to simple threshold-based approaches. However, these gains came at the cost of interpretability and implementation complexity.
The COT Index indicator intentionally employs a relatively straightforward normalization methodology for several important reasons. First, transparency enhances user understanding and trust. Traders can verify calculations manually and develop intuitive feel for what different readings mean. Second, academic research suggests that most of the predictive power in COT data comes from extreme positioning levels rather than subtle patterns requiring complex statistical methods to detect. Third, robust methods that work consistently across many markets and time periods tend to be simpler rather than more complex, reducing the risk of overfitting to historical data. Fourth, the complexity costs of implementation matter for retail traders without programming teams or computational infrastructure.
PSYCHOLOGICAL ASPECTS OF COT TRADING
Trading based on COT data requires psychological fortitude that differs from momentum-based approaches. Contrarian positioning signals inherently mean betting against prevailing market sentiment and recent price action. When commercials reach extreme bearish positioning, prices have typically been rising, sometimes for extended periods. The price chart looks bullish, momentum indicators confirm strength, moving averages align positively. The COT signal says bet against all of this. This psychological difficulty explains why COT analysis remains underutilized relative to trend-following methods.
Human psychology strongly predisposes us toward extrapolation and recency bias. When prices rally for months, our pattern-matching brains naturally expect continued rally. The recent price action dominates our perception, overwhelming rational analysis about positioning extremes and historical probabilities. The COT signal asking us to sell requires overriding these powerful psychological impulses.
The indicator design attempts to support the required psychological discipline through several features. Clear threshold markers and signal states reduce ambiguity about when signals trigger. When the commercial index crosses below twenty, the signal is explicit and unambiguous. The background shifts to red, the signal label displays bearish, and alerts fire. This explicitness helps traders act on signals rather than waiting for additional confirmation that may never arrive.
The metrics table provides analytical justification for contrarian positions, helping traders maintain conviction during inevitable periods of adverse price movement. When a trader enters short positions based on extreme commercial bearish positioning but prices continue rallying for several weeks, doubt naturally emerges. The table display provides reassurance. Commercial positioning remains extremely bearish. Divergence remains high. The positioning thesis remains intact even though price action has not yet confirmed.
Alert functionality ensures traders do not miss signals due to inattention while also not requiring constant monitoring that can lead to emotional decision-making. Setting alerts for COT extremes enables a healthier relationship with markets. When meaningful signals occur, alerts notify them. They can then calmly assess the situation and execute planned responses.
However, no indicator design can completely overcome the psychological difficulty of contrarian trading. Some traders simply cannot maintain short positions while prices rally. For these traders, COT analysis might be better employed as an exit signal for long positions rather than an entry signal for shorts.
Ultimately, successful COT trading requires developing comfort with probabilistic thinking rather than certainty-seeking. The signals work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five or sixty percent win rate with proper risk management produces substantial profits over years, yet still means forty to forty-five percent of signals will be premature or wrong. COT analysis provides genuine edge, but edge means probability advantage, not elimination of losing trades.
EDUCATIONAL RESOURCES AND CONTINUOUS LEARNING
The indicator provides extensive built-in educational resources through its documentation, detailed tooltips, and transparent calculations. However, mastering COT analysis requires study beyond any single tool or resource. Several excellent resources provide valuable extensions of the concepts covered in this guide.
Books and practitioner-focused monographs offer accessible entry points. Stephen Briese published The Commitments of Traders Bible in two thousand eight, offering detailed breakdowns of how different markets and trader categories behave (Briese, 2008). Briese's work stands out for its empirical focus and market-specific insights. Jack Schwager includes discussion of COT analysis within the broader context of market behavior in his book Market Sense and Nonsense (Schwager, 2012). Perry Kaufman's Trading Systems and Methods represents perhaps the most rigorous practitioner-focused text on systematic trading approaches including COT analysis (Kaufman, 2013).
Academic journal articles provide the rigorous statistical foundation underlying COT analysis. The Journal of Futures Markets regularly publishes research on positioning data and its predictive properties. Bessembinder and Chan's earlier work on systematic risk, hedging pressure, and risk premiums in futures markets provides theoretical foundation (Bessembinder, 1992). Chang's examination of speculator returns provides historical context (Chang, 1985). Irwin and Sanders provide essential skeptical perspective in their two thousand twelve article (Irwin and Sanders, 2012). Wang's two thousand three article provides one of the most empirical analyses of COT data across multiple commodity markets (Wang, 2003).
Online resources extend beyond academic and book-length treatments. The CFTC website provides free access to current and historical COT reports in multiple formats. The explanatory materials section offers detailed documentation of report construction, category definitions, and historical methodology changes. Traders serious about COT analysis should read these official CFTC documents to understand exactly what they are analyzing.
Commercial COT data services such as Barchart provide enhanced visualization and analysis tools beyond raw CFTC data. TradingView's educational materials, published scripts library, and user community provide additional resources for exploring different approaches to COT analysis.
The key to mastering COT analysis lies not in finding a single definitive source but rather in building understanding through multiple perspectives and information sources. Academic research provides rigorous empirical foundation. Practitioner-focused books offer practical implementation insights. Direct engagement with data through systematic backtesting develops intuition about how positioning dynamics manifest across different market conditions.
SYNTHESIZING KNOWLEDGE INTO PRACTICE
The COT Index indicator represents the synthesis of academic research, trading experience, and software engineering into a practical tool accessible to retail traders equipped with nothing more than a TradingView account and willingness to learn. What once required expensive data subscriptions, custom programming capabilities, statistical software, and institutional resources now appears as a straightforward indicator requiring only basic parameter selection and modest study to understand. This democratization of institutional-grade analysis tools represents a broader trend in financial markets over recent decades.
Yet technology and data access alone provide no edge without understanding and discipline. Markets remain relentlessly efficient at eliminating edges that become too widely known and mechanically exploited. The COT Index indicator succeeds only when users invest time learning the underlying concepts, understand the limitations and probability distributions involved, and integrate signals thoughtfully into trading plans rather than applying them mechanically.
The academic research demonstrates conclusively that institutional positioning contains genuine information about future price movements, particularly at extremes where commercial hedgers are maximally bearish or bullish relative to historical norms. This informational content is neither perfect nor deterministic but rather probabilistic, providing edge over many observations through identification of higher-probability configurations. Bessembinder and Chan's finding that commercial positioning explained modest but significant variance in future returns illustrates this probabilistic nature perfectly (Bessembinder and Chan, 1992). The effect is real and statistically significant, yet it explains perhaps ten to fifteen percent of return variance rather than most variance. Much of price movement remains unpredictable even with positioning intelligence.
The practical implication is that COT analysis works best as one component of a trading system rather than a standalone oracle. It provides the positioning dimension, revealing where the smart money has positioned and where the crowd has followed, but price action analysis provides the timing dimension. Fundamental analysis provides the catalyst dimension. Risk management provides the survival dimension. These components work together synergistically.
The indicator's design philosophy prioritizes transparency and education over black-box complexity, empowering traders to understand exactly what they are analyzing and why. Every calculation is documented and user-adjustable. The threshold markers, background coloring, tables, and clear signal states provide multiple reinforcing channels for conveying the same information.
This educational approach reflects a conviction that sustainable trading success comes from genuine understanding rather than mechanical system-following. Traders who understand why commercial positioning matters, how different trader categories behave, what positioning extremes signify, and where signals fit within probability distributions can adapt when market conditions change. Traders mechanically following black-box signals without comprehension abandon systems after normal losing streaks.
The research foundation supporting COT analysis comes primarily from commodity markets where commercial hedger informational advantages are most pronounced. Agricultural producers hedging crops know more about supply conditions than distant speculators. Energy companies hedging production know more about operating costs than financial traders. Metals miners hedging output know more about ore grades than index funds. Financial futures markets show weaker but still present effects.
The journey from reading this documentation to profitable trading based on COT analysis involves several stages that cannot be rushed. Initial reading and basic understanding represents the first stage. Historical study represents the second stage, reviewing past market cycles to observe how positioning extremes preceded major turning points. Paper trading or small-size real trading represents the third stage to experience the psychological challenges. Refinement based on results and personal psychology represents the fourth stage.
Markets will continue evolving. New participant categories will emerge. Regulatory structures will change. Technology will advance. Yet the fundamental dynamics driving COT analysis, that different market participants have different information, different motivations, and different forecasting abilities that manifest in their positioning, will persist as long as futures markets exist. While specific thresholds or optimal parameters may shift over time, the core logic remains sound and adaptable.
The trader equipped with this indicator, understanding of the theory and evidence behind COT analysis, realistic expectations about probability rather than certainty, discipline to maintain positions through adverse volatility, and patience to allow signals time to develop possesses genuine edge in markets. The edge is not enormous, markets cannot allow large persistent inefficiencies without arbitraging them away, but it is real, measurable, and exploitable by those willing to invest in learning and disciplined application.
REFERENCES
Bessembinder, H. (1992) Systematic risk, hedging pressure, and risk premiums in futures markets, Review of Financial Studies, 5(4), pp. 637-667.
Bessembinder, H. and Chan, K. (1992) The profitability of technical trading rules in the Asian stock markets, Pacific-Basin Finance Journal, 3(2-3), pp. 257-284.
Briese, S. (2008) The Commitments of Traders Bible: How to Profit from Insider Market Intelligence. Hoboken: John Wiley & Sons.
Chang, E.C. (1985) Returns to speculators and the theory of normal backwardation, Journal of Finance, 40(1), pp. 193-208.
Commodity Futures Trading Commission (CFTC) (2009) Explanatory Notes: Disaggregated Commitments of Traders Report. Available at: www.cftc.gov (Accessed: 15 January 2025).
Commodity Futures Trading Commission (CFTC) (2020) Commitments of Traders: About the Report. Available at: www.cftc.gov (Accessed: 15 January 2025).
Irwin, S.H. and Sanders, D.R. (2012) Testing the Masters Hypothesis in commodity futures markets, Energy Economics, 34(1), pp. 256-269.
Kaufman, P.J. (2013) Trading Systems and Methods. 5th edn. Hoboken: John Wiley & Sons.
Ruan, Y. and Zhang, Y. (2018) Forecasting commodity futures prices using machine learning: Evidence from the Chinese commodity futures market, Applied Economics Letters, 25(12), pp. 845-849.
Sanders, D.R., Boris, K. and Manfredo, M. (2004) Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports, Energy Economics, 26(3), pp. 425-445.
Schwager, J.D. (2012) Market Sense and Nonsense: How the Markets Really Work and How They Don't. Hoboken: John Wiley & Sons.
Tharp, V.K. (2008) Super Trader: Make Consistent Profits in Good and Bad Markets. New York: McGraw-Hill.
Wang, C. (2003) The behavior and performance of major types of futures traders, Journal of Futures Markets, 23(1), pp. 1-31.
Williams, L.R. and Noseworthy, M. (2009) The Right Stock at the Right Time: Prospering in the Coming Good Years. Hoboken: John Wiley & Sons.
FURTHER READING
For traders seeking to deepen their understanding of COT analysis and futures market positioning beyond this documentation, the following resources provide valuable extensions:
Academic Journal Articles:
Fishe, R.P.H. and Smith, A. (2012) Do speculators drive commodity prices away from supply and demand fundamentals?, Journal of Commodity Markets, 1(1), pp. 1-16.
Haigh, M.S., Hranaiova, J. and Overdahl, J.A. (2007) Hedge funds, volatility, and liquidity provision in energy futures markets, Journal of Alternative Investments, 9(4), pp. 10-38.
Kocagil, A.E. (1997) Does futures speculation stabilize spot prices? Evidence from metals markets, Applied Financial Economics, 7(1), pp. 115-125.
Sanders, D.R. and Irwin, S.H. (2011) The impact of index funds in commodity futures markets: A systems approach, Journal of Alternative Investments, 14(1), pp. 40-49.
Books and Practitioner Resources:
Murphy, J.J. (1999) Technical Analysis of the Financial Markets: A Guide to Trading Methods and Applications. New York: New York Institute of Finance.
Pring, M.J. (2002) Technical Analysis Explained: The Investor's Guide to Spotting Investment Trends and Turning Points. 4th edn. New York: McGraw-Hill.
Federal Reserve and Research Institution Publications:
Federal Reserve Banks regularly publish working papers examining commodity markets, futures positioning, and price discovery mechanisms. The Federal Reserve Bank of San Francisco and Federal Reserve Bank of Kansas City maintain active research programs in this area.
Online Resources:
The CFTC website provides free access to current and historical COT reports, explanatory materials, and regulatory documentation.
Barchart offers enhanced COT data visualization and screening tools.
TradingView's community library contains numerous published scripts and educational materials exploring different approaches to positioning analysis.
Smart MACD Volume Trader# Smart MACD Volume Trader
## Overview
Smart MACD Volume Trader is an enhanced momentum indicator that combines the classic MACD (Moving Average Convergence Divergence) oscillator with an intelligent high-volume filter. This combination significantly reduces false signals by ensuring that trading signals are only generated when price momentum is confirmed by substantial volume activity.
The indicator supports over 24 different instruments including major and exotic forex pairs, precious metals (gold and silver), energy commodities (crude oil, natural gas), and industrial metals (copper). For forex and commodity traders, the indicator automatically maps to CME and COMEX futures contracts to provide accurate institutional-grade volume data.
## Originality and Core Concept
Traditional MACD indicators generate signals based solely on price momentum, which can result in numerous false signals during low-activity periods or ranging markets. This indicator addresses this critical weakness by introducing a volume confirmation layer with automatic institutional volume integration.
**What makes this approach original:**
- Signals are triggered only when MACD crossovers coincide with elevated volume activity
- Implements a lookback mechanism to detect volume spikes within recent bars
- Automatically detects and maps 24+ forex pairs and commodities to their corresponding CME and COMEX futures contracts
- Provides real institutional volume data for forex pairs where spot volume is unreliable
- Combines two independent market dimensions (price momentum and volume) into a single, actionable signal
- Includes intelligent asset detection that works across multiple exchanges and ticker formats
**The underlying principle:** Volume validates price movement. When institutional money enters the market, it creates volume signatures. By requiring high volume confirmation and using actual institutional volume data from futures markets, this indicator filters out weak price movements and focuses on trades backed by genuine market participation. The automatic futures mapping ensures that forex and commodity traders always have access to the most accurate volume data available, without manual configuration.
## How It Works
### MACD Component
The indicator calculates MACD using standard methodology:
1. **Fast EMA (default: 12 periods)** - Tracks short-term price momentum
2. **Slow EMA (default: 26 periods)** - Tracks longer-term price momentum
3. **MACD Line** - Difference between Fast EMA and Slow EMA
4. **Signal Line (default: 9-period SMA)** - Smoothed average of MACD line
**Crossover signals:**
- **Bullish:** MACD line crosses above Signal line (momentum turning positive)
- **Bearish:** MACD line crosses below Signal line (momentum turning negative)
### Volume Filter Component
The volume filter adds an essential confirmation layer:
1. **Volume Moving Average** - Calculates exponential MA of volume (default: 20 periods)
2. **High Volume Threshold** - Multiplies MA by ratio (default: 2.0x or 200%)
3. **Volume Detection** - Identifies bars where current volume exceeds threshold
4. **Lookback Period** - Checks if high volume occurred in recent bars (default: 5 bars)
**Signal logic:**
- Buy/Sell signals only trigger when BOTH conditions are met:
- MACD crossover/crossunder occurs
- High volume detected within lookback period
### Automatic CME Futures Integration
For forex traders, spot FX volume data can be unreliable or non-existent. This indicator solves this problem by automatically detecting forex pairs and mapping them to corresponding CME futures contracts with real institutional volume data.
**Supported Major Forex Pairs (7):**
- EURUSD → CME:6E1! (Euro FX Futures)
- GBPUSD → CME:6B1! (British Pound Futures)
- AUDUSD → CME:6A1! (Australian Dollar Futures)
- USDJPY → CME:6J1! (Japanese Yen Futures)
- USDCAD → CME:6C1! (Canadian Dollar Futures)
- USDCHF → CME:6S1! (Swiss Franc Futures)
- NZDUSD → CME:6N1! (New Zealand Dollar Futures)
**Supported Exotic Forex Pairs (4):**
- USDMXN → CME:6M1! (Mexican Peso Futures)
- USDRUB → CME:6R1! (Russian Ruble Futures)
- USDBRL → CME:6L1! (Brazilian Real Futures)
- USDZAR → CME:6Z1! (South African Rand Futures)
**Supported Cross Pairs (6):**
- EURJPY → CME:6E1! (Uses Euro Futures)
- GBPJPY → CME:6B1! (Uses British Pound Futures)
- EURGBP → CME:6E1! (Uses Euro Futures)
- AUDJPY → CME:6A1! (Uses Australian Dollar Futures)
- EURAUD → CME:6E1! (Uses Euro Futures)
- GBPAUD → CME:6B1! (Uses British Pound Futures)
**Supported Precious Metals (2):**
- Gold (XAUUSD, GOLD) → COMEX:GC1! (Gold Futures)
- Silver (XAGUSD, SILVER) → COMEX:SI1! (Silver Futures)
**Supported Energy Commodities (3):**
- WTI Crude Oil (USOIL, WTIUSD) → NYMEX:CL1! (Crude Oil Futures)
- Brent Oil (UKOIL) → NYMEX:BZ1! (Brent Crude Futures)
- Natural Gas (NATGAS) → NYMEX:NG1! (Natural Gas Futures)
**Supported Industrial Metals (1):**
- Copper (COPPER) → COMEX:HG1! (Copper Futures)
**How the automatic detection works:**
The indicator intelligently identifies the asset type by analyzing:
1. Exchange name (FX, OANDA, TVC, COMEX, NYMEX, etc.)
2. Currency pair pattern (6-letter codes like EURUSD, GBPUSD)
3. Commodity identifiers (XAU for gold, XAG for silver, OIL for crude)
When a supported instrument is detected, the indicator automatically switches to the corresponding futures contract for volume analysis. For stocks, cryptocurrencies, and other assets, the indicator uses the native volume data from the current chart.
**Visual feedback:**
An information table appears in the top-right corner of the MACD pane showing:
- Current chart symbol
- Exchange name
- Currency pair or asset name
- Volume source being used (highlighted in orange for futures, yellow for native volume)
- Current high volume status
This provides complete transparency about which data source the indicator is using for its volume analysis.
## How to Use
### Basic Setup
1. Add the indicator to your chart
2. The indicator displays in a separate pane (MACD) and overlay (signals/volume bars)
3. Default settings work well for most assets, but can be customized
### Signal Interpretation
### Visual Signals
**Visual Signals:**
- **Green "BUY" label** - Bullish MACD crossover confirmed by high volume
- **Red "SELL" label** - Bearish MACD crossunder confirmed by high volume
- **Green/Red candles** - Highlight bars with volume exceeding the threshold
- **Light green/red background** - Emphasizes signal bars on the chart
**Information Table:**
A detailed information table appears in the top-right corner of the MACD pane, providing real-time transparency about the indicator's operation:
- **Chart:** Current symbol being analyzed
- **Exchange:** The exchange or data feed being used
- **Pair:** The currency pair or asset name extracted from the ticker
- **Volume From:** The actual symbol used for volume analysis
- Orange color indicates CME or COMEX futures are being used (automatic institutional volume)
- Yellow color indicates native volume from the chart symbol is being used
- Hover tooltip shows whether automatic futures mapping is active
- **High Volume:** Current status showing YES (green) when volume exceeds threshold, NO (gray) otherwise
This table ensures complete transparency and allows you to verify that the correct volume source is being used for your analysis.
**Volume Analysis:**
- Gray histogram bars = Normal volume
- Red histogram bars = High volume (exceeds threshold)
- Green line = Volume moving average baseline
**MACD Analysis:**
- Blue line = MACD line (momentum indicator)
- Orange line = Signal line (trend confirmation)
- Gray dotted line = Zero line (bullish above, bearish below)
### Parameter Customization
**MACD Parameters:**
- Adjust Fast/Slow EMA lengths for different sensitivities
- Shorter periods = More signals, faster response
- Longer periods = Fewer signals, less noise
**Volume Parameters:**
- **Volume MA Period:** Higher values smooth volume analysis
- **High Volume Ratio:** Lower values (1.5x) = More signals; Higher values (3.0x) = Fewer, stronger signals
- **Volume Lookback Bars:** Controls how recent the volume spike must be
**Direction Filters:**
- **Only Buy Signals:** Enables long-only strategy mode
- **Only Sell Signals:** Enables short-only strategy mode
### Alert Configuration
The indicator includes three alert types:
1. **Buy Signal Alert** - Triggers when bullish signal appears
2. **Sell Signal Alert** - Triggers when bearish signal appears
3. **High Volume Alert** - Triggers when volume exceeds threshold
To set up alerts:
1. Click the indicator name → "Add alert on Smart MACD Volume Trader"
2. Select desired alert condition
3. Configure notification method (popup, email, webhook, etc.)
## Trading Strategy Guidelines
### Best Practices
**Recommended markets:**
- Liquid stocks (large-cap, high daily volume)
- Major forex pairs (EURUSD, GBPUSD, USDJPY, AUDUSD, USDCAD, USDCHF, NZDUSD)
- Exotic forex pairs (USDMXN, USDRUB, USDBRL, USDZAR)
- Cross pairs (EURJPY, GBPJPY, EURGBP, AUDJPY, EURAUD, GBPAUD)
- Precious metals (Gold, Silver with automatic COMEX futures mapping)
- Energy commodities (Crude Oil, Natural Gas with automatic NYMEX futures mapping)
- Industrial metals (Copper with automatic COMEX futures mapping)
- Major cryptocurrency pairs
- Index futures and ETFs
**Timeframe recommendations:**
- **Day trading:** 5-minute to 15-minute charts
- **Swing trading:** 1-hour to 4-hour charts
- **Position trading:** Daily charts
**Risk management:**
- Use signals as entry confirmation, not standalone strategy
- Combine with support/resistance levels
- Consider overall market trend direction
- Always use stop-loss orders
### Strategy Examples
**Trend Following Strategy:**
1. Identify overall trend using higher timeframe (e.g., daily chart)
2. Trade only in trend direction
3. Use "Only Buy" filter in uptrends, "Only Sell" in downtrends
4. Enter on signal, exit on opposite signal or at resistance/support
**Volume Breakout Strategy:**
1. Wait for consolidation period (low volume, tight MACD range)
2. Enter when signal appears with high volume (confirms breakout)
3. Target previous swing highs/lows
4. Stop loss below/above recent consolidation
**Forex Scalping Strategy (with automatic CME futures):**
1. The indicator automatically detects forex pairs and uses CME futures volume
2. Trade during active sessions only (use session filter)
3. Focus on quick profits (10-20 pips)
4. Exit at opposite signal or profit target
**Commodities Trading Strategy (Gold, Silver, Oil):**
1. The indicator automatically maps to COMEX and NYMEX futures contracts
2. Trade during high-liquidity sessions (overlap of major markets)
3. Use the high volume confirmation to identify institutional entry points
4. Combine with key support and resistance levels for entries
5. Monitor the information table to confirm futures volume is being used (orange color)
6. Exit on opposite MACD signal or at predefined profit targets
## Why This Combination Works
### The Volume Advantage
Studies consistently show that price movements accompanied by high volume are more likely to continue, while low-volume movements often reverse. This indicator leverages this principle by requiring volume confirmation.
**Key benefits:**
1. **Reduced False Signals:** Eliminates MACD whipsaws during low-volume consolidation
2. **Confirmation Bias:** Two independent indicators (price momentum + volume) agreeing
3. **Institutional Alignment:** High volume often indicates institutional participation
4. **Trend Validation:** Volume confirms that price momentum has "conviction"
### Statistical Edge
By combining two uncorrelated signals (MACD crossovers and volume spikes), the indicator creates a higher-probability setup than either signal alone. The lookback mechanism ensures signals aren't missed if volume spike slightly precedes the MACD cross.
## Supported Exchanges and Automatic Detection
The indicator includes intelligent asset detection that works across multiple exchanges and ticker formats:
**Forex Exchanges (Automatic CME Mapping):**
- FX (TradingView forex feed)
- OANDA
- FXCM
- SAXO
- FOREXCOM
- PEPPERSTONE
- EASYMARKETS
- FX_IDC
**Commodity Exchanges (Automatic COMEX/NYMEX Mapping):**
- TVC (TradingView commodity feed)
- COMEX (directly)
- NYMEX (directly)
- ICEUS
**Other Asset Classes (Native Volume):**
- Stock exchanges (NASDAQ, NYSE, AMEX, etc.)
- Cryptocurrency exchanges (BINANCE, COINBASE, KRAKEN, etc.)
- Index providers (SP, DJ, etc.)
The detection algorithm analyzes three factors:
1. Exchange prefix in the ticker symbol
2. Pattern matching for currency pairs (6-letter codes)
3. Commodity identifiers in the symbol name
This ensures accurate automatic detection regardless of which data feed or exchange you use for charting. The information table in the top-right corner always displays which volume source is being used, providing complete transparency.
## Technical Details
**Calculations:**
- MACD Fast MA: EMA(close, fastLength)
- MACD Slow MA: EMA(close, slowLength)
- MACD Line: Fast MA - Slow MA
- Signal Line: SMA(MACD Line, signalLength)
- Volume MA: Exponential MA of volume
- High Volume: Current volume >= Volume MA × Ratio
**Signal logic:**
```
Buy Signal = (MACD crosses above Signal) AND (High volume in last N bars)
Sell Signal = (MACD crosses below Signal) AND (High volume in last N bars)
```
## Parameters Reference
| Parameter | Default | Description |
|-----------|---------|-------------|
| Volume Symbol | Blank | Manual override for volume source (leave blank for automatic detection) |
| Use CME Futures | False | Legacy option (automatic detection is now built-in) |
| Alert Session | 1530-2200 | Active session time range for alerts |
| Timezone | UTC+1 | Timezone for alert sessions |
| Volume MA Period | 20 | Number of periods for volume moving average |
| High Volume Ratio | 2.0 | Volume threshold multiplier (2.0 = 200% of average) |
| Volume Lookback | 5 | Number of bars to check for high volume confirmation |
| MACD Fast Length | 12 | Fast EMA period for MACD calculation |
| MACD Slow Length | 26 | Slow EMA period for MACD calculation |
| MACD Signal Length | 9 | Signal line SMA period |
| Only Buy | False | Filter to show only bullish signals |
| Only Sell | False | Filter to show only bearish signals |
| Show Signals | True | Display buy and sell labels on chart |
## Optimization Tips
**For volatile markets (crypto, small caps):**
- Increase High Volume Ratio to 2.5-3.0
- Reduce Volume Lookback to 3-4 bars
- Consider faster MACD settings (8, 17, 9)
**For stable markets (large-cap stocks, bonds):**
- Decrease High Volume Ratio to 1.5-1.8
- Increase Volume MA Period to 30-50
- Use standard MACD settings
**For forex (with automatic CME futures):**
- The indicator automatically uses CME futures when forex pairs are detected
- Set appropriate trading session based on your timezone
- Use Volume Lookback of 5-7 bars
- Consider session-based alerts only
- Monitor the information table to verify correct futures mapping
**For commodities (Gold, Silver, Oil, Copper):**
- The indicator automatically maps to COMEX and NYMEX futures
- Increase High Volume Ratio to 2.0-2.5 for metals
- Use slightly higher Volume MA Period (25-30) for smoother analysis
- Trade during active market hours for best volume data
- The information table will show the futures contract being used (orange highlight)
## Limitations and Considerations
**What this indicator does NOT do:**
- Does not predict future price direction
- Does not guarantee profitable trades
- Does not replace proper risk management
- Does not work well in extremely low-volume conditions
**Market conditions to avoid:**
- Pre-market and after-hours sessions (low volume)
- Major news events (volatile, unpredictable volume)
- Holidays and low-liquidity periods
- Extremely low float stocks
## Conclusion
Smart MACD Volume Trader represents a significant evolution of the traditional MACD indicator by combining volume confirmation with automatic institutional volume integration. This dual-confirmation approach significantly improves signal quality by filtering out low-conviction price movements and ensuring traders work with accurate volume data.
The indicator's automatic detection and mapping system supports over 24 instruments across forex, commodities, and metals markets. By intelligently switching to CME and COMEX futures contracts when appropriate, the indicator provides forex and commodity traders with the same quality of volume data that stock traders naturally have access to.
This indicator is particularly valuable for traders who want to:
- Align their entries with institutional money flow
- Avoid getting trapped in false breakouts
- Trade forex pairs with reliable volume data
- Access accurate volume information for gold, silver, and energy commodities
- Combine momentum and volume analysis in a single, streamlined tool
Whether you are day trading stocks, swing trading forex pairs, or positioning in commodities markets, this indicator provides a robust framework for identifying high-probability momentum trades backed by genuine institutional participation. The automatic futures mapping works seamlessly across all supported instruments, requiring no manual configuration or expertise in futures markets.
---
## Support and Updates
This indicator is actively maintained and updated based on user feedback and market conditions. For questions about implementation or custom modifications, please use the comments section below.
**Disclaimer:** This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and risk management before trading.
Advanced Speedometer Gauge [PhenLabs]Advanced Speedometer Gauge
Version: PineScript™v6
📌 Description
The Advanced Speedometer Gauge is a revolutionary multi-metric visualization tool that consolidates 13 distinct trading indicators into a single, intuitive speedometer display. Instead of cluttering your workspace with multiple oscillators and panels, this gauge provides a unified interface where you can switch between different metrics while maintaining consistent visual interpretation.
Built on PineScript™ v6, the indicator transforms complex technical calculations into an easy-to-read semi-circular gauge with color-coded zones and a precision needle indicator. Each of the 13 available metrics has been carefully normalized to a 0-100 scale, ensuring that whether you’re analyzing RSI, volume trends, or volatility extremes, the visual interpretation remains consistent and intuitive.
The gauge is designed for traders who value efficiency and clarity. By consolidating multiple analytical perspectives into one compact display, you can quickly assess market conditions without the visual noise of traditional multi-indicator setups. All metrics are non-overlapping, meaning each provides unique insights into different aspects of market behavior.
🚀 Points of Innovation
13 selectable metrics covering momentum, volume, volatility, trend, and statistical analysis, all accessible through a single dropdown menu
Universal 0-100 normalization system that standardizes different indicator scales for consistent visual interpretation across all metrics
Semi-circular gauge design with 21 arc segments providing smooth precision and clear visual feedback through color-coded zones
Non-redundant metric selection ensuring each indicator provides unique market insights without analytical overlap
Advanced metrics including MFI (volume-weighted momentum), CCI (statistical deviation), Volatility Rank (extended lookback), Trend Strength (ADX-style), Choppiness Index, Volume Trend, and Price Distance from MA
Flexible positioning system with 5 chart locations, 3 size options, and fully customizable color schemes for optimal workspace integration
🔧 Core Components
Metric Selection Engine: Dropdown interface allowing instant switching between 13 different technical indicators, each with independent parameter controls
Normalization System: All metrics converted to 0-100 scale using indicator-specific algorithms that preserve the statistical significance of each measurement
Semi-Circular Gauge: Visual display using 21 arc segments arranged in curved formation with two-row thickness for enhanced visibility
Color Zone System: Three distinct zones (0-40 green, 40-70 yellow, 70-100 red) providing instant visual feedback on metric extremes
Needle Indicator: Dynamic pointer that positions across the gauge arc based on precise current metric value
Table Implementation: Professional table structure ensuring consistent positioning and rendering across different chart configurations
🔥 Key Features
RSI (Relative Strength Index): Classic momentum oscillator measuring overbought/oversold conditions with adjustable period length (default 14)
Stochastic Oscillator: Compares closing price to price range over specified period with smoothing, ideal for identifying momentum shifts
MFI (Money Flow Index): Volume-weighted RSI that combines price movement with volume to measure buying and selling pressure intensity
CCI (Commodity Channel Index): Measures statistical deviation from average price, normalized from typical -200 to +200 range to 0-100 scale
Williams %R: Alternative overbought/oversold indicator using high-low range analysis, inverted to match 0-100 scale conventions
Volume %: Current volume relative to moving average expressed as percentage, capped at 100 for extreme spikes
Volume Trend: Cumulative directional volume flow showing whether volume is flowing into up moves or down moves over specified period
ATR Percentile: Current Average True Range position within historical range using specified lookback period (default 100 bars)
Volatility Rank: Close-to-close volatility measured against extended historical range (default 252 days), differs from ATR in calculation method
Momentum: Rate of change calculation showing price movement speed, centered at 50 and normalized to 0-100 range
Trend Strength: ADX-style calculation using directional movement to quantify trend intensity regardless of direction
Choppiness Index: Measures market choppiness versus trending behavior, where high values indicate ranging markets and low values indicate strong trends
Price Distance from MA: Measures current price over-extension from moving average using standard deviation calculations
🎨 Visualization
Semi-Circular Arc Display: Curved gauge spanning from 0 (left) to 100 (right) with smooth progression and two-row thickness for visibility
Color-Coded Zones: Green zone (0-40) for low/oversold conditions, yellow zone (40-70) for neutral readings, red zone (70-100) for high/overbought conditions
Needle Indicator: Downward-pointing triangle (▼) positioned precisely at current metric value along the gauge arc
Scale Markers: Vertical line markers at 0, 25, 50, 75, and 100 positions with corresponding numerical labels below
Title Display: Merged cell showing “𓄀 PhenLabs” branding plus currently selected metric name in monospace font
Large Value Display: Current metric value shown with two decimal precision in large text directly below title
Table Structure: Professional table with customizable background color, text color, and transparency for minimal chart obstruction
📖 Usage Guidelines
Metric Selection
Select Metric: Default: RSI | Options: RSI, Stochastic, Volume %, ATR Percentile, Momentum, MFI (Money Flow), CCI (Commodity Channel), Williams %R, Volatility Rank, Trend Strength, Choppiness Index, Volume Trend, Price Distance | Choose the technical indicator you want to display on the gauge based on your current analytical needs
RSI Settings
RSI Length: Default: 14 | Range: 1+ | Controls the lookback period for RSI calculation, shorter periods increase sensitivity to recent price changes
Stochastic Settings
Stochastic Length: Default: 14 | Range: 1+ | Lookback period for stochastic calculation comparing close to high-low range
Stochastic Smooth: Default: 3 | Range: 1+ | Smoothing period applied to raw stochastic value to reduce noise and false signals
Volume Settings
Volume MA Length: Default: 20 | Range: 1+ | Moving average period used to calculate average volume for comparison with current volume
Volume Trend Length: Default: 20 | Range: 5+ | Period for calculating cumulative directional volume flow trend
ATR and Volatility Settings
ATR Length: Default: 14 | Range: 1+ | Period for Average True Range calculation used in ATR Percentile metric
ATR Percentile Lookback: Default: 100 | Range: 20+ | Historical range used to determine current ATR position as percentile
Volatility Rank Lookback (Days): Default: 252 | Range: 50+ | Extended lookback period for Volatility Rank metric using close-to-close volatility
Momentum and Trend Settings
Momentum Length: Default: 10 | Range: 1+ | Lookback period for rate of change calculation in Momentum metric
Trend Strength Length: Default: 20 | Range: 5+ | Period for directional movement calculations in ADX-style Trend Strength metric
Advanced Metric Settings
MFI Length: Default: 14 | Range: 1+ | Lookback period for Money Flow Index calculation combining price and volume
CCI Length: Default: 20 | Range: 1+ | Period for Commodity Channel Index statistical deviation calculation
Williams %R Length: Default: 14 | Range: 1+ | Lookback period for Williams %R high-low range analysis
Choppiness Index Length: Default: 14 | Range: 5+ | Period for calculating market choppiness versus trending behavior
Price Distance MA Length: Default: 50 | Range: 10+ | Moving average period used for Price Distance standard deviation calculation
Visual Customization
Position: Default: Top Right | Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Right | Controls gauge placement on chart for optimal workspace organization
Size: Default: Normal | Options: Small, Normal, Large | Adjusts overall gauge dimensions and text size for different monitor resolutions and preferences
Low Zone Color (0-40): Default: Green (#00FF00) | Customize color for low/oversold zone of gauge arc
Medium Zone Color (40-70): Default: Yellow (#FFFF00) | Customize color for neutral/medium zone of gauge arc
High Zone Color (70-100): Default: Red (#FF0000) | Customize color for high/overbought zone of gauge arc
Background Color: Default: Semi-transparent dark gray | Customize gauge background for contrast and chart integration
Text Color: Default: White (#FFFFFF) | Customize all text elements including title, value, and scale labels
✅ Best Use Cases
Quick visual assessment of market conditions when you need instant feedback on whether an asset is in extreme territory across multiple analytical dimensions
Workspace organization for traders who monitor multiple indicators but want to reduce chart clutter and visual complexity
Metric comparison by switching between different indicators while maintaining consistent visual interpretation through the 0-100 normalization
Overbought/oversold identification using RSI, Stochastic, Williams %R, or MFI depending on whether you prefer price-only or volume-weighted analysis
Volume analysis through Volume %, Volume Trend, or MFI to confirm price movements with corresponding volume characteristics
Volatility monitoring using ATR Percentile or Volatility Rank to identify expansion/contraction cycles and adjust position sizing
Trend vs range identification by comparing Trend Strength (high values = trending) against Choppiness Index (high values = ranging)
Statistical over-extension detection using CCI or Price Distance to identify when price has deviated significantly from normal behavior
Multi-timeframe analysis by duplicating the gauge on different timeframe charts to compare metric readings across time horizons
Educational purposes for new traders learning to interpret technical indicators through consistent visual representation
⚠️ Limitations
The gauge displays only one metric at a time, requiring manual switching to compare different indicators rather than simultaneous multi-metric viewing
The 0-100 normalization, while providing consistency, may obscure the raw values and specific nuances of each underlying indicator
Table-based visualization cannot be exported or saved as an image separately from the full chart screenshot
Optimal parameter settings vary by asset type, timeframe, and market conditions, requiring user experimentation for best results
💡 What Makes This Unique
Unified Multi-Metric Interface: The only gauge-style indicator offering 13 distinct metrics through a single interface, eliminating the need for multiple oscillator panels
Non-Overlapping Analytics: Each metric provides genuinely unique insights—MFI combines volume with price, CCI measures statistical deviation, Volatility Rank uses extended lookback, Trend Strength quantifies directional movement, and Choppiness Index measures ranging behavior
Universal Normalization System: All metrics standardized to 0-100 scale using indicator-appropriate algorithms that preserve statistical meaning while enabling consistent visual interpretation
Professional Visual Design: Semi-circular gauge with 21 arc segments, precision needle positioning, color-coded zones, and clean table implementation that maintains clarity across all chart configurations
Extensive Customization: Independent parameter controls for each metric, five position options, three size presets, and full color customization for seamless workspace integration
🔬 How It Works
1. Metric Calculation Phase:
All 13 metrics are calculated simultaneously on every bar using their respective algorithms with user-defined parameters
Each metric applies its own specific calculation method—RSI uses average gains vs losses, Stochastic compares close to high-low range, MFI incorporates typical price and volume, CCI measures deviation from statistical mean, ATR calculates true range, directional indicators measure up/down movement, and statistical metrics analyze price relationships
2. Normalization Process:
Each calculated metric is converted to a standardized 0-100 scale using indicator-appropriate transformations
Some metrics are naturally 0-100 (RSI, Stochastic, MFI, Williams %R), while others require scaling—CCI transforms from ±200 range, Momentum centers around 50, Volume ratio caps at 2x for 100, ATR and Volatility Rank calculate percentile positions, and Price Distance scales by standard deviations
3. Gauge Rendering:
The selected metric’s normalized value determines the needle position across 21 arc segments spanning 0-100
Each arc segment receives its color based on position—segments 0-8 are green zone, segments 9-14 are yellow zone, segments 15-20 are red zone
The needle indicator (▼) appears in row 5 at the column corresponding to the current metric value, providing precise visual feedback
4. Table Construction:
The gauge uses TradingView’s table system with merged cells for title and value display, ensuring consistent positioning regardless of chart configuration
Rows are allocated as follows: Row 0 merged for title, Row 1 merged for large value display, Row 2 for spacing, Rows 3-4 for the semi-circular arc with curved shaping, Row 5 for needle indicator, Row 6 for scale markers, Row 7 for numerical labels at 0/25/50/75/100
All visual elements update on every bar when barstate.islast is true, ensuring real-time accuracy without performance impact
💡 Note:
This indicator is designed for visual analysis and market condition assessment, not as a standalone trading system. For best results, combine gauge readings with price action analysis, support and resistance levels, and broader market context. Parameter optimization is recommended based on your specific trading timeframe and asset class. The gauge works on all timeframes but may require different parameter settings for intraday versus daily/weekly analysis. Consider using multiple instances of the gauge set to different metrics for comprehensive market analysis without switching between settings.
Luxy Momentum, Trend, Bias and Breakout Indicators V7
TABLE OF CONTENTS
This is Version 7 (V7) - the latest and most optimized release. If you are using any older versions (V6, V5, V4, V3, etc.), it is highly recommended to replace them with V7.
Why This Indicator is Different
Who Should Use This
Core Components Overview
The UT Bot Trading System
Understanding the Market Bias Table
Candlestick Pattern Recognition
Visual Tools and Features
How to Use the Indicator
Performance and Optimization
FAQ
---
### CREDITS & ATTRIBUTION
This indicator implements proven trading concepts using entirely original code developed specifically for this project.
### CONCEPTUAL FOUNDATIONS
• UT Bot ATR Trailing System
- Original concept by @QuantNomad: (search "UT-Bot-Strategy"
- Our version is a complete reimplementation with significant enhancements:
- Volume-weighted momentum adjustment
- Composite stop loss from multiple S/R layers
- Multi-filter confirmation system (swing, %, 2-bar, ZLSMA)
- Full integration with multi-timeframe bias table
- Visual audit trail with freeze-on-touch
- NOTE: No code was copied - this is a complete reimplementation with enhancements.
• Standard Technical Indicators (Public Domain Formulas):
- Supertrend: ATR-based trend calculation with custom gradient fills
- MACD: Gerald Appel's formula with separation filters
- RSI: J. Welles Wilder's formula with pullback zone logic
- ADX/DMI: Custom trend strength formula inspired by Wilder's directional movement concept, reimplemented with volume weighting and efficiency metrics
- ZLSMA: Zero-lag formula enhanced with Hull MA and momentum prediction
### Custom Implementations
- Trend Strength: Inspired by Wilder's ADX concept but using volume-weighted pressure calculation and efficiency metrics (not traditional +DI/-DI smoothing)
- All code implementations are original
### ORIGINAL FEATURES (70%+ of codebase)
- Multi-Timeframe Bias Table with live updates
- Risk Management System (R-multiple TPs, freeze-on-touch)
- Opening Range Breakout tracker with session management
- Composite Stop Loss calculator using 6+ S/R layers
- Performance optimization system (caching, conditional calcs)
- VIX Fear Index integration
- Previous Day High/Low auto-detection
- Candlestick pattern recognition with interactive tooltips
- Smart label and visual management
- All UI/UX design and table architecture
### DEVELOPMENT PROCESS
**AI Assistance:** This indicator was developed over 2+ months with AI assistance (ChatGPT/Claude) used for:
- Writing Pine Script code based on design specifications
- Optimizing performance and fixing bugs
- Ensuring Pine Script v6 compliance
- Generating documentation
**Author's Role:** All trading concepts, system design, feature selection, integration logic, and strategic decisions are original work by the author. The AI was a coding tool, not the system designer.
**Transparency:** We believe in full disclosure - this project demonstrates how AI can be used as a powerful development tool while maintaining creative and strategic ownership.
---
1. WHY THIS INDICATOR IS DIFFERENT
Most traders use multiple separate indicators on their charts, leading to cluttered screens, conflicting signals, and analysis paralysis. The Suite solves this by integrating proven technical tools into a single, cohesive system.
Key Advantages:
All-in-One Design: Instead of loading 5-10 separate indicators, you get everything in one optimized script. This reduces chart clutter and improves TradingView performance.
Multi-Timeframe Bias Table: Unlike standard indicators that only show the current timeframe, the Bias Table aggregates trend signals across multiple timeframes simultaneously. See at a glance whether 1m, 5m, 15m, 1h are aligned bullish or bearish - no more switching between charts.
Smart Confirmations: The indicator doesn't just give signals - it shows you WHY. Every entry has multiple layers of confirmation (MA cross, MACD momentum, ADX strength, RSI pullback, volume, etc.) that you can toggle on/off.
Dynamic Stop Loss System: Instead of static ATR stops, the SL is calculated from multiple support/resistance layers: UT trailing line, Supertrend, VWAP, swing structure, and MA levels. This creates more intelligent, price-action-aware stops.
R-Multiple Take Profits: Built-in TP system calculates targets based on your initial risk (1R, 1.5R, 2R, 3R). Lines freeze when touched with visual checkmarks, giving you a clean audit trail of partial exits.
Educational Tooltips Everywhere: Every single input has detailed tooltips explaining what it does, typical values, and how it impacts trading. You're not guessing - you're learning as you configure.
Performance Optimized: Smart caching, conditional calculations, and modular design mean the indicator runs fast despite having 15+ features. Turn off what you don't use for even better performance.
No Repainting: All signals respect bar close. Alerts fire correctly. What you see in history is what you would have gotten in real-time.
What Makes It Unique:
Integrated UT Bot + Bias Table: No other indicator combines UT Bot's ATR trailing system with a live multi-timeframe dashboard. You get precision entries with macro trend context.
Candlestick Pattern Recognition with Interactive Tooltips: Patterns aren't just marked - hover over any emoji for a full explanation of what the pattern means and how to trade it.
Opening Range Breakout Tracker: Built-in ORB system for intraday traders with customizable session times and real-time status updates in the Bias Table.
Previous Day High/Low Auto-Detection: Automatically plots PDH/PDL on intraday charts with theme-aware colors. Updates daily without manual input.
Dynamic Row Labels in Bias Table: The table shows your actual settings (e.g., "EMA 10 > SMA 20") not generic labels. You know exactly what's being evaluated.
Modular Filter System: Instead of forcing a fixed methodology, the indicator lets you build your own strategy. Start with just UT Bot, add filters one at a time, test what works for your style.
---
2. WHO WHOULD USE THIS
Designed For:
Intermediate to Advanced Traders: You understand basic technical analysis (MAs, RSI, MACD) and want to combine multiple confirmations efficiently. This isn't a "one-click profit" system - it's a professional toolkit.
Multi-Timeframe Traders: If you trade one asset but check multiple timeframes for confirmation (e.g., enter on 5m after checking 15m and 1h alignment), the Bias Table will save you hours every week.
Trend Followers: The indicator excels at identifying and following trends using UT Bot, Supertrend, and MA systems. If you trade breakouts and pullbacks in trending markets, this is built for you.
Intraday and Swing Traders: Works equally well on 5m-1h charts (day trading) and 4h-D charts (swing trading). Scalpers can use it too with appropriate settings adjustments.
Discretionary Traders: This isn't a black-box system. You see all the components, understand the logic, and make final decisions. Perfect for traders who want tools, not automation.
Works Across All Markets:
Stocks (US, international)
Cryptocurrency (24/7 markets supported)
Forex pairs
Indices (SPY, QQQ, etc.)
Commodities
NOT Ideal For :
Complete Beginners: If you don't know what a moving average or RSI is, start with basics first. This indicator assumes foundational knowledge.
Algo Traders Seeking Black Box: This is discretionary. Signals require context and confirmation. Not suitable for blind automated execution.
Mean-Reversion Only Traders: The indicator is trend-following at its core. While VWAP bands support mean-reversion, the primary methodology is trend continuation.
---
3. CORE COMPONENTS OVERVIEW
The indicator combines these proven systems:
Trend Analysis:
Moving Averages: Four customizable MAs (Fast, Medium, Medium-Long, Long) with six types to choose from (EMA, SMA, WMA, VWMA, RMA, HMA). Mix and match for your style.
Supertrend: ATR-based trend indicator with unique gradient fill showing trend strength. One-sided ribbon visualization makes it easier to see momentum building or fading.
ZLSMA : Zero-lag linear-regression smoothed moving average. Reduces lag compared to traditional MAs while maintaining smooth curves.
Momentum & Filters:
MACD: Standard MACD with separation filter to avoid weak crossovers.
RSI: Pullback zone detection - only enter longs when RSI is in your defined "buy zone" and shorts in "sell zone".
ADX/DMI: Trend strength measurement with directional filter. Ensures you only trade when there's actual momentum.
Volume Filter: Relative volume confirmation - require above-average volume for entries.
Donchian Breakout: Optional channel breakout requirement.
Signal Systems:
UT Bot: The primary signal generator. ATR trailing stop that adapts to volatility and gives clear entry/exit points.
Base Signals: MA cross system with all the above filters applied. More conservative than UT Bot alone.
Market Bias Table: Multi-timeframe dashboard showing trend alignment across 7 timeframes plus macro bias (3-day, weekly, monthly, quarterly, VIX).
Candlestick Patterns: Six major reversal patterns auto-detected with interactive tooltips.
ORB Tracker: Opening range high/low with breakout status (intraday only).
PDH/PDL: Previous day levels plotted automatically on intraday charts.
VWAP + Bands : Session-anchored VWAP with up to three standard deviation band pairs.
---
4. THE UT BOT TRADING SYSTEM
The UT Bot is the heart of the indicator's signal generation. It's an advanced ATR trailing stop that adapts to market volatility.
Why UT Bot is Superior to Fixed Stops:
Traditional ATR stops use a fixed multiplier (e.g., "stop = entry - 2×ATR"). UT Bot is smarter:
It TRAILS the stop as price moves in your favor
It WIDENS during high volatility to avoid premature stops
It TIGHTENS during consolidation to lock in profits
It FLIPS when price breaks the trailing line, signaling reversals
Visual Elements You'll See:
Orange Trailing Line: The actual UT stop level that adapts bar-by-bar
Buy/Sell Labels: Aqua triangle (long) or orange triangle (short) when the line flips
ENTRY Line: Horizontal line at your entry price (optional, can be turned off)
Suggested Stop Loss: A composite SL calculated from multiple support/resistance layers:
- UT trailing line
- Supertrend level
- VWAP
- Swing structure (recent lows/highs)
- Long-term MA (200)
- ATR-based floor
Take Profit Lines: TP1, TP1.5, TP2, TP3 based on R-multiples. When price touches a TP, it's marked with a checkmark and the line freezes for audit trail purposes.
Status Messages: "SL Touched ❌" or "SL Frozen" when the trade leg completes.
How UT Bot Differs from Other ATR Systems:
Multiple Filters Available: You can require 2-bar confirmation, minimum % price change, swing structure alignment, or ZLSMA directional filter. Most UT implementations have none of these.
Smart SL Calculation: Instead of just using the UT line as your stop, the indicator suggests a better SL based on actual support/resistance. This prevents getting stopped out by wicks while keeping risk controlled.
Visual Audit Trail: All SL/TP lines freeze when touched with clear markers. You can review your trades weeks later and see exactly where entries, stops, and targets were.
Performance Options: "Draw UT visuals only on bar close" lets you reduce rendering load without affecting logic or alerts - critical for slower machines or 1m charts.
Trading Logic:
UT Bot flips direction (Buy or Sell signal appears)
Check Bias Table for multi-timeframe confirmation
Optional: Wait for Base signal or candlestick pattern
Enter at signal bar close or next bar open
Place stop at "Suggested Stop Loss" line
Scale out at TP levels (TP1, TP2, TP3)
Exit remaining position on opposite UT signal or stop hit
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5. UNDERSTANDING THE MARKET BIAS TABLE
This is the indicator's unique multi-timeframe intelligence layer. Instead of looking at one chart at a time, the table aggregates signals across seven timeframes plus macro trend bias.
Why Multi-Timeframe Analysis Matters:
Professional traders check higher and lower timeframes for context:
Is the 1h uptrend aligning with my 5m entry?
Are all short-term timeframes bullish or just one?
Is the daily trend supportive or fighting me?
Doing this manually means opening multiple charts, checking each indicator, and making mental notes. The Bias Table does it automatically in one glance.
Table Structure:
Header Row:
On intraday charts: 1m, 5m, 15m, 30m, 1h, 2h, 4h (toggle which ones you want)
On daily+ charts: D, W, M (automatic)
Green dot next to title = live updating
Headline Rows - Macro Bias:
These show broad market direction over longer periods:
3 Day Bias: Trend over last 3 trading sessions (uses 1h data)
Weekly Bias: Trend over last 5 trading sessions (uses 4h data)
Monthly Bias: Trend over last 30 daily bars
Quarterly Bias: Trend over last 13 weekly bars
VIX Fear Index: Market regime based on VIX level - bullish when low, bearish when high
Opening Range Breakout: Status of price vs. session open range (intraday only)
These rows show text: "BULLISH", "BEARISH", or "NEUTRAL"
Indicator Rows - Technical Signals:
These evaluate your configured indicators across all active timeframes:
Fast MA > Medium MA (shows your actual MA settings, e.g., "EMA 10 > SMA 20")
Price > Long MA (e.g., "Price > SMA 200")
Price > VWAP
MACD > Signal
Supertrend (up/down/neutral)
ZLSMA Rising
RSI In Zone
ADX ≥ Minimum
These rows show emojis: GREEB (bullish), RED (bearish), GRAY/YELLOW (neutral/NA)
AVG Column:
Shows percentage of active timeframes that are bullish for that row. This is the KEY metric:
AVG > 70% = strong multi-timeframe bullish alignment
AVG 40-60% = mixed/choppy, no clear trend
AVG < 30% = strong multi-timeframe bearish alignment
How to Use the Table:
For a long trade:
Check AVG column - want to see > 60% ideally
Check headline bias rows - want to see BULLISH, not BEARISH
Check VIX row - bullish market regime preferred
Check ORB row (intraday) - want ABOVE for longs
Scan indicator rows - more green = better confirmation
For a short trade:
Check AVG column - want to see < 40% ideally
Check headline bias rows - want to see BEARISH, not BULLISH
Check VIX row - bearish market regime preferred
Check ORB row (intraday) - want BELOW for shorts
Scan indicator rows - more red = better confirmation
When AVG is 40-60%:
Market is choppy, mixed signals. Either stay out or reduce position size significantly. These are low-probability environments.
Unique Features:
Dynamic Labels: Row names show your actual settings (e.g., "EMA 10 > SMA 20" not generic "Fast > Slow"). You know exactly what's being evaluated.
Customizable Rows: Turn off rows you don't care about. Only show what matters to your strategy.
Customizable Timeframes: On intraday charts, disable 1m or 4h if you don't trade them. Reduces calculation load by 20-40%.
Automatic HTF Handling: On Daily/Weekly/Monthly charts, the table automatically switches to D/W/M columns. No configuration needed.
Performance Smart: "Hide BIAS table on 1D or above" option completely skips all table calculations on higher timeframes if you only trade intraday.
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6. CANDLESTICK PATTERN RECOGNITION
The indicator automatically detects six major reversal patterns and marks them with emojis at the relevant bars.
Why These Six Patterns:
These are the most statistically significant reversal patterns according to trading literature:
High win rate when appearing at support/resistance
Clear visual structure (not subjective)
Work across all timeframes and assets
Studied extensively by institutions
The Patterns:
Bullish Patterns (appear at bottoms):
Bullish Engulfing: Green candle completely engulfs prior red candle's body. Strong reversal signal.
Hammer: Small body with long lower wick (at least 2× body size). Shows rejection of lower prices by buyers.
Morning Star: Three-candle pattern (large red → small indecision → large green). Very strong bottom reversal.
Bearish Patterns (appear at tops):
Bearish Engulfing: Red candle completely engulfs prior green candle's body. Strong reversal signal.
Shooting Star: Small body with long upper wick (at least 2× body size). Shows rejection of higher prices by sellers.
Evening Star: Three-candle pattern (large green → small indecision → large red). Very strong top reversal.
Interactive Tooltips:
Unlike most pattern indicators that just draw shapes, this one is educational:
Hover your mouse over any pattern emoji
A tooltip appears explaining: what the pattern is, what it means, when it's most reliable, and how to trade it
No need to memorize - learn as you trade
Noise Filter:
"Min candle body % to filter noise" setting prevents false signals:
Patterns require minimum body size relative to price
Filters out tiny candles that don't represent real buying/selling pressure
Adjust based on asset volatility (higher % for crypto, lower for low-volatility stocks)
How to Trade Patterns:
Patterns are NOT standalone entry signals. Use them as:
Confirmation: UT Bot gives signal + pattern appears = stronger entry
Reversal Warning: In a trade, opposite pattern appears = consider tightening stop or taking profit
Support/Resistance Validation: Pattern at key level (PDH, VWAP, MA 200) = level is being respected
Best combined with:
UT Bot or Base signal in same direction
Bias Table alignment (AVG > 60% or < 40%)
Appearance at obvious support/resistance
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7. VISUAL TOOLS AND FEATURES
VWAP (Volume Weighted Average Price):
Session-anchored VWAP with standard deviation bands. Shows institutional "fair value" for the trading session.
Anchor Options: Session, Day, Week, Month, Quarter, Year. Choose based on your trading timeframe.
Bands: Up to three pairs (X1, X2, X3) showing statistical deviation. Price at outer bands often reverses.
Auto-Hide on HTF: VWAP hides on Daily/Weekly/Monthly charts automatically unless you enable anchored mode.
Use VWAP as:
Directional bias (above = bullish, below = bearish)
Mean reversion levels (outer bands)
Support/resistance (the VWAP line itself)
Previous Day High/Low:
Automatically plots yesterday's high and low on intraday charts:
Updates at start of each new trading day
Theme-aware colors (dark text for light charts, light text for dark charts)
Hidden automatically on Daily/Weekly/Monthly charts
These levels are critical for intraday traders - institutions watch them closely as support/resistance.
Opening Range Breakout (ORB):
Tracks the high/low of the first 5, 15, 30, or 60 minutes of the trading session:
Customizable session times (preset for NYSE, LSE, TSE, or custom)
Shows current breakout status in Bias Table row (ABOVE, BELOW, INSIDE, BUILDING)
Intraday only - auto-disabled on Daily+ charts
ORB is a classic day trading strategy - breakout above opening range often leads to continuation.
Extra Labels:
Change from Open %: Shows how far price has moved from session open (intraday) or daily open (HTF). Green if positive, red if negative.
ADX Badge: Small label at bottom of last bar showing current ADX value. Green when above your minimum threshold, red when below.
RSI Badge: Small label at top of last bar showing current RSI value with zone status (buy zone, sell zone, or neutral).
These labels provide quick at-a-glance confirmation without needing separate indicator windows.
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8. HOW TO USE THE INDICATOR
Step 1: Add to Chart
Load the indicator on your chosen asset and timeframe
First time: Everything is enabled by default - the chart will look busy
Don't panic - you'll turn off what you don't need
Step 2: Start Simple
Turn OFF everything except:
UT Bot labels (keep these ON)
Bias Table (keep this ON)
Moving Averages (Fast and Medium only)
Suggested Stop Loss and Take Profits
Hide everything else initially. Get comfortable with the basic UT Bot + Bias Table workflow first.
Step 3: Learn the Core Workflow
UT Bot gives a Buy or Sell signal
Check Bias Table AVG column - do you have multi-timeframe alignment?
If yes, enter the trade
Place stop at Suggested Stop Loss line
Scale out at TP levels
Exit on opposite UT signal
Trade this simple system for a week. Get a feel for signal frequency and win rate with your settings.
Step 4: Add Filters Gradually
If you're getting too many losing signals (whipsaws in choppy markets), add filters one at a time:
Try: "Require 2-Bar Trend Confirmation" - wait for 2 bars to confirm direction
Try: ADX filter with minimum threshold - only trade when trend strength is sufficient
Try: RSI pullback filter - only enter on pullbacks, not chasing
Try: Volume filter - require above-average volume
Add one filter, test for a week, evaluate. Repeat.
Step 5: Enable Advanced Features (Optional)
Once you're profitable with the core system, add:
Supertrend for additional trend confirmation
Candlestick patterns for reversal warnings
VWAP for institutional anchor reference
ORB for intraday breakout context
ZLSMA for low-lag trend following
Step 6: Optimize Settings
Every setting has a detailed tooltip explaining what it does and typical values. Hover over any input to read:
What the parameter controls
How it impacts trading
Suggested ranges for scalping, day trading, and swing trading
Start with defaults, then adjust based on your results and style.
Step 7: Set Up Alerts
Right-click chart → Add Alert → Condition: "Luxy Momentum v6" → Choose:
"UT Bot — Buy" for long entries
"UT Bot — Sell" for short entries
"Base Long/Short" for filtered MA cross signals
Optionally enable "Send real-time alert() on UT flip" in settings for immediate notifications.
Common Workflow Variations:
Conservative Trader:
UT signal + Base signal + Candlestick pattern + Bias AVG > 70%
Enter only at major support/resistance
Wider UT sensitivity, multiple filters
Aggressive Trader:
UT signal + Bias AVG > 60%
Enter immediately, no waiting
Tighter UT sensitivity, minimal filters
Swing Trader:
Focus on Daily/Weekly Bias alignment
Ignore intraday noise
Use ORB and PDH/PDL less (or not at all)
Wider stops, patient approach
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9. PERFORMANCE AND OPTIMIZATION
The indicator is optimized for speed, but with 15+ features running simultaneously, chart load time can add up. Here's how to keep it fast:
Biggest Performance Gains:
Disable Unused Timeframes: In "Time Frames" settings, turn OFF any timeframe you don't actively trade. Each disabled TF saves 10-15% calculation time. If you only day trade 5m, 15m, 1h, disable 1m, 2h, 4h.
Hide Bias Table on Daily+: If you only trade intraday, enable "Hide BIAS table on 1D or above". This skips ALL table calculations on higher timeframes.
Draw UT Visuals Only on Bar Close: Reduces intrabar rendering of SL/TP/Entry lines. Has ZERO impact on logic or alerts - purely visual optimization.
Additional Optimizations:
Turn off VWAP bands if you don't use them
Disable candlestick patterns if you don't trade them
Turn off Supertrend fill if you find it distracting (keep the line)
Reduce "Limit to 10 bars" for SL/TP lines to minimize line objects
Performance Features Built-In:
Smart Caching: Higher timeframe data (3-day bias, weekly bias, etc.) updates once per day, not every bar
Conditional Calculations: Volume filter only calculates when enabled. Swing filter only runs when enabled. Nothing computes if turned off.
Modular Design: Every component is independent. Turn off what you don't need without breaking other features.
Typical Load Times:
5m chart, all features ON, 7 timeframes: ~2-3 seconds
5m chart, core features only, 3 timeframes: ~1 second
1m chart, all features: ~4-5 seconds (many bars to calculate)
If loading takes longer, you likely have too many indicators on the chart total (not just this one).
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10. FAQ
Q: How is this different from standard UT Bot indicators?
A: Standard UT Bot (originally by @QuantNomad) is just the ATR trailing line and flip signals. This implementation adds:
- Volume weighting and momentum adjustment to the trailing calculation
- Multiple confirmation filters (swing, %, 2-bar, ZLSMA)
- Smart composite stop loss system from multiple S/R layers
- R-multiple take profit system with freeze-on-touch
- Integration with multi-timeframe Bias Table
- Visual audit trail with checkmarks
Q: Can I use this for automated trading?
A: The indicator is designed for discretionary trading. While it has clear signals and alerts, it's not a mechanical system. Context and judgment are required.
Q: Does it repaint?
A: No. All signals respect bar close. UT Bot logic runs intrabar but signals only trigger on confirmed bars. Alerts fire correctly with no lookahead.
Q: Do I need to use all the features?
A: Absolutely not. The indicator is modular. Many profitable traders use just UT Bot + Bias Table + Moving Averages. Start simple, add complexity only if needed.
Q: How do I know which settings to use?
A: Every single input has a detailed tooltip. Hover over any setting to see:
What it does
How it affects trading
Typical values for scalping, day trading, swing trading
Start with defaults, adjust gradually based on results.
Q: Can I use this on crypto 24/7 markets?
A: Yes. ORB will not work (no defined session), but everything else functions normally. Use "Day" anchor for VWAP instead of "Session".
Q: The Bias Table is blank or not showing.
A: Check:
"Show Table" is ON
Table position isn't overlapping another indicator's table (change position)
At least one row is enabled
"Hide BIAS table on 1D or above" is OFF (if on Daily+ chart)
Q: Why are candlestick patterns not appearing?
A: Patterns are relatively rare by design - they only appear at genuine reversal points. Check:
Pattern toggles are ON
"Min candle body %" isn't too high (try 0.05-0.10)
You're looking at a chart with actual reversals (not strong trending market)
Q: UT Bot is too sensitive/not sensitive enough.
A: Adjust "Sensitivity (Key×ATR)". Lower number = tighter stop, more signals. Higher number = wider stop, fewer signals. Read the tooltip for guidance.
Q: Can I get alerts for the Bias Table?
A: The Bias Table is a dashboard for visual analysis, not a signal generator. Set alerts on UT Bot or Base signals, then manually check Bias Table for confirmation.
Q: Does this work on stocks with low volume?
A: Yes, but turn OFF the volume filter. Low volume stocks will never meet relative volume requirements.
Q: How often should I check the Bias Table?
A: Before every entry. It takes 2 seconds to glance at the AVG column and headline rows. This one check can save you from fighting the trend.
Q: What if UT signal and Base signal disagree?
A: UT Bot is more aggressive (ATR trailing). Base signals are more conservative (MA cross + filters). If they disagree, either:
Wait for both to align (safest)
Take the UT signal but with smaller size (aggressive)
Skip the trade (conservative)
There's no "right" answer - depends on your risk tolerance.
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FINAL NOTES
The indicator gives you an edge. How you use that edge determines results.
For questions, feedback, or support, comment on the indicator page or message the author.
Happy Trading!
TwinPulse Q Lead SPY x QQQ Intermarket Pulse 1HTwinPulse Q Lead is a concise one hour indicator for SPY and QQQ that converts three sources of market information into a single pulse line, a mode readout with BUY SELL WAIT, and compact alerts. It blends intermarket leadership between QQQ and SPY, intraday flow from the slope of session VWAP, and where the current price sits inside the regular trading hours range. The three components are normalized, fused, compressed to a stable range, and smoothed for clear thresholds. The aim is a readable intraday regime signal that helps you decide when to participate and when to stand aside.
The script is built with Pine v6, uses request security with lookahead off, and does not repaint. It is an indicator, not a strategy. It does not contain any solicitation, links, or outside references. The description is self contained and explains both logic and use so that any trader can understand the design without reading code.
What makes this original and useful
Intermarket leadership is measured directly from QQQ and SPY on your working timeframe using a Z score of the return spread. When growth is leading value heavy large caps, leadership turns positive. When it lags, leadership turns negative. This gives a real time read of the Nasdaq versus S and P tug of war that most day traders watch informally.
Intraday flow is taken from the slope of the session VWAP. A linear regression of VWAP over a short window captures whether value is rising or falling inside the day. Dividing by ATR normalizes slope by typical movement so that the signal is comparable across weeks.
Session position places price inside the current regular hours high to low. It answers whether the day is trading in the top half, the bottom half, or the middle. This is a simple but powerful context filter for breakouts and fades.
The three components are fused into one pulse, compressed with either hyperbolic tangent or softsign to keep values bounded, and then smoothed by a short EMA. This yields a stable range with a zero line so the eye can read shifts quickly.
The panel shows a human readable mode with reasons and a strength score. Traders who do not want to read lines can rely on a simple state and a compact justification that explains why the state is set.
This is not a mashup that simply overlays unrelated indicators. Each component was chosen to answer a distinct question that is common to SPY and QQQ intraday decision making. Leadership answers who is in charge, flow answers whether value inside the session is building or leaking, and position answers if price is pressing the extremes or circling the middle. The pulse ties the three together and prevents any single component from dominating.
How the calculations work
Leadership. Compute a short rate of change for SPY and QQQ. Subtract SPY from QQQ to get spread returns, then compute a rolling Z score over a longer window. Positive values mean QQQ is leading. Negative values mean SPY is leading.
Flow. Compute session VWAP on the active symbol. Regress VWAP over a short window to obtain a slope estimate. Divide by ATR to scale slope by current volatility so that a small rise on a quiet day is not treated the same as a small rise on a wild day.
Position. Track the highest high and lowest low since the start of regular hours. Place the current close inside that range on a zero to one scale, then recenter to a minus one to plus one scale. Positive means the top half of the day, negative means the bottom half.
Fusion. Multiply each component by a weight so users can emphasize or de emphasize leadership, flow, or position. Sum to a raw pulse.
Compression. Pass the raw pulse through a bounded function. Hyperbolic tangent is smooth and has natural saturation near the extremes. Softsign is faster and behaves like a smoother version of sign near zero. Compression avoids unbounded excursions and makes thresholds meaningful across days.
Smoothing. Apply a short EMA to the compressed pulse to reduce noise. This creates the main line called TwinPulse in the plot.
Thresholds. You can use static symmetric levels or adaptive levels. The adaptive option computes a mean and a standard deviation of the smoothed pulse over a user window, then sets upper and lower thresholds as mean plus or minus sigma times standard deviation. This allows thresholds to adjust across regimes. Static levels are still available for traders who want repeatable levels.
Events and mode. A long event fires when the smoothed pulse crosses the upper threshold with positive flow and any optional filters agree. A short event fires on the symmetric condition. The mode reads the current state rather than fire and forget. It returns BUY when the smoothed pulse is above the upper threshold with positive flow, SELL when the smoothed pulse is below the lower threshold with negative flow, otherwise WAIT. A cooldown controls how often events can fire so alerts do not spam during choppy periods.
Inputs and default values
The script ships with defaults chosen for SPY and QQQ on one hour charts.
Symbols. SPY and QQQ by default. You can switch to any pair. Many users may test IWM versus SPY for small cap reads.
Regular hours selector. On by default. This restricts the position factor to New York regular hours. Turn it off if you prefer full session behavior.
ROC length is three bars. Z score length is fifty bars. VWAP slope window is ten bars. ATR length is fourteen bars. Pulse smoothing length is three bars.
Compression mode. Choose hyperbolic tangent or softsign. Hyperbolic tangent is default.
Weights. Leadership and flow are one by default. Position is set to zero point seven to give a modest influence to where price sits inside the day.
Thresholds. Adaptive thresholds are on by default with a lookback of one hundred bars and a sigma width of zero point eight. Static levels at plus or minus zero point six are ready if you disable adaptive mode.
Filters. ADX filter is off by default. If you enable it, the script requires ADX above a user minimum before it will signal. Higher time frame confirmation is off by default. When enabled it compares the smoothed pulse on the confirm timeframe to zero and requires alignment for longs or shorts.
Cooldown. Three bars by default so that alerts do not trigger too frequently.
UI. Bar coloring is on by default. The panel is on by default and sits at the top right.
All request security calls use lookahead off and will not request future data. All persistent state variables are assigned in a way that prevents repainting. The indicator does not use non standard chart types in its logic.
How to use the indicator
Load a one hour chart of SPY or QQQ. Keep a clean chart so that the script output is easy to read.
Turn on regular hours if you want the session position to reflect the cash session. This is recommended for SPY and QQQ.
Watch the panel. Mode reads BUY or SELL or WAIT. The strength value is a simple vote based score that ranges from zero to one hundred. It counts leadership, flow, ADX if enabled, and higher time frame confirmation if enabled. You can use strength to filter weak states.
Consider action only when mode is BUY or SELL and the signal has not just fired on the last bar. The triangles mark where an event fired. Alerts use the same logic as the events. WAIT means stand aside.
To slow the system, enable ADX and set a higher minimum or enable higher time frame confirmation. To speed it up, disable the filters, disable adaptive thresholds, or tighten the sigma width.
When publishing, use a clean chart with only this indicator. Show the symbol and timeframe clearly and make sure the plot legend is visible. If you add drawings on the chart, only include ones that help readers understand the output.
Publication notes and compliance
This description is written in English. The title uses ASCII and only uses capital letters for common abbreviations. The script is original and explains how and why the components work together. There are no links or promotional material. The script does not claim performance. It does not use lookahead. The panel and alerts exist to help a human read and act with discipline. The indicator can be published as open source or as protected. If you choose protected, the description still allows readers to understand how the logic works without access to the code.
If you later convert the logic into a strategy for publication, use realistic commission and slippage, risk no more than a small share of equity per trade, and choose a dataset that yields a large enough sample. Explain any deviations from these default recommendations in your strategy description. Do not publish results from non standard chart types since they can mislead readers on signal timing.
Limitations and risks
Intermarket leadership is a relative measure. There are hours when both SPY and QQQ fall while leadership remains positive. Treat leadership as a context, not a stand alone trigger.
VWAP slope is a path measure inside the session. It can flip several times on a choppy day. That is why the script uses a short smoothing and an optional cooldown. Use ADX or higher time frame confirmation to avoid the worst chop.
Session position assumes a meaningful regular hours range. On half days or around openings with gaps the position factor can be less informative. If this bothers you, reduce the weight of position or turn it off.
Compression and smoothing introduce lag by design. The goal is stability and clarity. If you want earlier but noisier signals, reduce smoothing and weights, and use static thresholds.
No indicator guarantees future results. TwinPulse Q Lead is a decision aid. It should be combined with your risk rules, position size policy, and a clear exit plan. Past behavior is not a promise for the future.
Frequently asked questions
What symbols are supported. Any symbol can be used as the chart symbol. Leadership uses the two user symbols which default to SPY and QQQ. Many traders may try IWM versus SPY or DIA versus SPY.
Can I change the timeframe. Yes, but the design target is one hour. On very short timeframes the VWAP slope becomes very sensitive and you should consider stronger filters.
Does the script repaint. No. It uses request security with lookahead off and the panel updates on the last bar only. Events are based on bar close conditions unless you attach alerts on any alert function call which will still respect the logic without looking into the future.
How are the strength numbers built. The strength score is the share of aligned votes across leadership, flow, ADX if enabled, and higher time frame confirmation if enabled. A value near one hundred means many filters agree. A value near fifty means partial alignment. It is not a probability or an accuracy number.
Can I use non standard chart types. You can view the indicator on them but do not publish signals from non standard chart types because that can mislead readers about timing. Use classic candles or bars when you publish and when you test.
Why do I sometimes see BUY but the price is not moving. A BUY mode requires pulse above the upper threshold and positive flow. It does not require higher highs immediately. Treat BUY as a permission to look for entries using your own execution rules.
Microgaps (plots-only, 4-channel, same-day only)Purpose:
This indicator visually highlights 3-bar price gaps on your chart, showing clear visual structure for gap zones without lag or diagonal artifacts.
It draws two outer lines (top and bottom of the gap) for every valid 3-bar gap, and optionally a midline when the gap is considered “large.”
⚙️ How it works
A bull gap is detected when the current bar’s low is higher than the high from two bars ago (low > high ).
A bear gap is detected when the current bar’s high is lower than the low from two bars ago (high < low ).
The lines are centered at the middle bar of the 3-bar sequence.
Gaps are only drawn within the same trading day to avoid false overnight gaps.
To prevent overlapping artifacts, up to four concurrent gap channels can be drawn efficiently using GPU-friendly plot() lines.
🔵 Midline logic
The midline (center of the gap) is only displayed when the gap’s vertical size is “large” relative to recent volatility.
“Large” means the gap height is greater than a user-defined fraction of the average bar range over the past N bars.
Example: if the average 8-bar range = 2 points, and the threshold = 0.3, then only gaps larger than 0.6 points will show the midline.
🧩 Parameters
Setting Description
Bull Gap Color / Width Style of bullish gaps (top and bottom lines).
Bear Gap Color / Width Style of bearish gaps (top and bottom lines).
Mid Gap Color / Width Style of the optional midline (shown only when “large”).
Large Gap — Lookback (bars) Number of bars used to calculate the average range (default: 8).
Large Gap — Size vs Avg Range Fraction of the average range that defines a “large” gap (default: 0.5). Set lower (e.g. 0.3) to show more midlines.
💡 Tips
Set threshold lower (0.2–0.4) for more midlines, higher (0.6–1.0) to highlight only extreme gaps.
Works best on intraday timeframes (1-min to 30-min).
Fully GPU-efficient — can scroll back thousands of bars without lag.
Crypto Market Dominance Stacked with LabelsA professional stacked area chart showing the dominance of major crypto market segments: BTC, ETH, Top 100 Altcoins, and #101+ Altcoins. Each layer is color-coded for clarity and includes dynamic labels with the current dominance percentage. Provides a clear visual representation of market share trends for traders, analysts, and crypto enthusiasts.
Features:
Stacked visualization of BTC, ETH, Top 100, and small-cap altcoins (#101+).
Color-coded areas for easy identification.
Dynamic labels showing each category’s current dominance percentage.
Horizontal reference lines for percentage levels.
Approximates top 100 and #101+ altcoins using TOTAL2 and TOTAL3 market cap tickers.
Use Case:
Track how market share shifts between BTC, ETH, large altcoins, and smaller altcoins over time. Ideal for analyzing trends, spotting dominance changes, and visualizing overall crypto market structure.
Flux Power Dashboard (Updated and Renamed)Flux Power Dashboard is a compact market-state heads-up display for TradingView. It blends trend, momentum, and volume-flow into a single on-chart panel with color-coded cues and minimal lag. You get:
Clean visual trend via fast/slow MA with slope/debounce filters
MACD state and most recent cross (with “freshness” tint)
OBV confirmation and gating to reduce noise
Session awareness (Asia/London/New York + pre-sessions + overlap)
Optional HTF Regime row and regime gate to align signals to higher-timeframe bias
Context from VIX/VXN (volatility regime)
A single Flux Score (0–100) as a top-level read
It is deliberately “dashboard-first”: fast to read, consistent between symbols/timeframes, and designed to limit overtrading in chop.
What it can do (capabilities)
Signal gating: You can require multiple pillars to agree (Trend, MACD, OBV) before a “strong” bias is shown.
Debounced trend: Uses slope + confirmation bars to avoid flip-flopping.
Session presets: Auto-adjust the minimum confirmation bars by session (e.g., NY vs London vs Asia) to better match liquidity/volatility.
MACD presets: Quick switch between Scalp / Classic / Slow or roll your own custom speeds.
OBV confirmation: Volume flow must agree for trend/entries to “count” (optional).
HTF Regime awareness: Shows the higher-timeframe backdrop and (optionally) gates signals so you don’t fight the dominant trend.
Volatility context: VIX/VXN auto-colored cells based on your thresholds.
Top-center Session Title: Broadcasts the active session (or Overlap) with a matched background color.
Customizable UI: Column fonts, params font, transparency, dashboard corner, marker styles, colors, widths—tune it to your chart.
Practical use: Start with Flux Score + Summary for a snapshot, confirm with Trend & MACD, check OBV agreement (implicit in signal strength), glance at Regime to avoid counter-trend trades, and use Session + VIX/VXN for timing and risk context.
How it avoids common pitfalls
Repaint-aware: “Confirm on Close” can be enabled to read prior bar states, reducing intrabar noise.
Auto MA sanity: If fast ≥ slow length, it auto-swaps under the hood to keep calculations valid.
Debounce & confirm: Trend flips only after X bars satisfy conditions, cutting false flips in chop.
Freshness tint: New Cross/Signal rows tint slightly brighter for a few bars, so you can spot recency at a glance.
Every line of the dashboard (what it shows, how it’s colored)
Flux Score
What: Composite 0–100 built from three pillars: Trend (40%), MACD (30%), OBV (30%).
Read: ≥70 Bullish, ≤30 Bearish, else Neutral.
Use: Quick “state of play” gauge—stronger alignment pushes the score toward extremes.
Regime (optional row)
What: Higher-timeframe (your Regime TF) backdrop using the same MA pair with HTF slope/ATR buffer.
Values: Bull / Bear / Range.
Gate (optional): If Regime Gate is ON, Trend/Signals only go directional when HTF agrees.
Summary
What: One-line narrative combining the three pillars: MACD (up/down/flat), OBV (up/down/flat), Trend (up/down/flat).
Use: Human-readable cross-check; should rhyme with Flux Score.
Trend
What: Debounced MA relationship on the current chart.
Strict: needs fast > slow and slow rising (mirror for down) + slope debounce + confirmation bars.
Lenient: allows fast > slow or slow rising (mirror for down) with the same debounce/confirm.
Color: Green = UP, Red = DOWN, Gray = FLAT.
Use: Your structural bias on the trading timeframe.
MACD
What: Current MACD line vs signal, using your selected preset (or custom).
Values: Bull (line above), Bear (below), Flat (equal/indeterminate).
Color: Green/Red/Gray.
Cross
What: Most recent MACD cross and how many bars ago it occurred (e.g., “MACD XUP | 3 bars”).
Freshness: If the cross happened within Fresh Signal Tint bars, the cell brightens slightly.
Use: Timing helper for inflection points.
Signal
What: Latest directional shift (from short-bias to long-bias or vice versa) and age in bars.
Strength:
Strong = Trend + MACD + OBV all align
Weak = partial alignment (e.g., Trend + MACD, or Trend + OBV)
Color: Green for long bias, Red for short bias; fresh signals tint brighter.
Use: Action cue—treat Strong as higher quality; Weak as situational.
MA
What: Your slow MA type and length, plus slope direction (“up”/“down”).
Use: Context even when Trend is FLAT; slope often turns before full trend flips.
Session
What: Current market session by Eastern Time: New York / London / Asia, Pre- windows, Overlap, or Off-hours.
Logic: If ≥2 main sessions are active, shows Overlap (and grays the top title background).
Use: Timing and expectations for liquidity/volatility; also drives session-based confirmation presets if enabled.
VIX
What: Real-time CBOE:VIX on your chosen TF.
Auto-color (if on):
Calm (< Calm) → Green
Watch (< Watch) → Yellow
Elevated (< Elevated) → Orange
Very High (≥ Elevated) → Red
Use: Equity market–wide risk mood; higher = bigger moves, lower = quieter.
VXN
What: CBOE:VXN (Nasdaq volatility index) on your chosen TF.
Auto-color thresholds like VIX.
Use: Tech-heavy risk mood; helpful for growth/QQQ/NDX names.
Footer (params row, bottom-right)
What: Key live settings so you always know the context:
P= Trend Confirmation Bars
O= OBV Confirmation Bars
Strict/Lenient (trend mode)
MACD preset (or “Custom”)
swap if MA lengths were auto-swapped for validity
Regime gate if enabled
Candles for clarity
Use: Quick integrity check when comparing charts/screenshots or changing presets.
Recommended workflow
Start at Flux Score & Summary → snapshot of alignment.
Check Trend (color) and MACD (Bull/Bear).
Look at Signal (Strong vs Weak, and age).
Glance at Regime (and use gate if you’re trend-following).
Use Session + VIX/VXN to adjust expectations (breakout vs mean-revert, risk sizing, patience).
Keep Confirm on Close ON when you want stability; turn it OFF for faster (but noisier) reads.
Notes & limitations
Not advice: This is an informational tool; always combine with your own risk rules.
Repaint vs responsiveness: With “Confirm on Close” OFF you’ll see faster state changes but may get more churn intrabar.
Presets matter: Scalp MACD reacts fastest; Slow reduces whipsaw. Choose for your timeframe.
Session windows depend on the strings you set; adjust if your broker’s feed or DST handling needs tweaks.
Grand Master's Candlestick Dominance (ATR Enhanced)### Grand Master's Candlestick Dominance (ATR Enhanced)
**Overview**
Unleash the ancient wisdom of Japanese candlestick charting with a modern twist! This comprehensive Pine Script v5 strategy and indicator scans for over 75 classic and advanced candlestick patterns (bullish, bearish, and neutral), assigning dynamic strength scores (1-10) to each for precise signal filtering. Enhanced with Average True Range (ATR) for volatility-aware body size validation, it dominates the markets by combining timeless pattern recognition with robust confirmation layers. Whether used as a backtestable strategy or visual indicator, it empowers traders to spot high-probability reversals, continuations, and indecision setups with surgical accuracy.
Inspired by Steve Nison's *Japanese Candlestick Charting Techniques*, this tool elevates pattern analysis beyond basics—think Hammers, Engulfing patterns, Morning Stars, and rare gems like Abandoned Baby or Concealing Baby Swallow—all consolidated into intelligent arrays for real-time averaging and prioritization.
**Key Features**
- **Extensive Pattern Library**:
- **Bullish (25+ patterns)**: Hammer (8.0), Bullish Engulfing (10.0), Morning Star (7.0), Three White Soldiers (9.0), Dragonfly Doji (8.0), and more (e.g., Rising Three, Unique Three River Bottom).
- **Bearish (25+ patterns)**: Hanging Man (8.0), Bearish Engulfing (10.0), Evening Star (7.0), Three Black Crows (9.0), Gravestone Doji (8.0), and exotics like Upside Gap Two Crows or Stalled Pattern.
- **Neutral/Indecision (34+ patterns)**: Doji variants (Long-Legged, Four Price), Spinning Tops, Harami Crosses, and multi-bar setups like Upside Tasuki Gap or Advancing Block.
Each pattern includes duration tracking (1-5 bars) and ATR-adjusted body/shadow criteria for relevance in volatile conditions.
- **Smart Confirmation Filters** (All Toggleable):
- **Trend Alignment**: 20-period SMA (customizable) ensures entries align with the prevailing trend; optional higher timeframe (e.g., Daily) MA crossover for multi-timeframe confluence.
- **Support/Resistance (S/R)**: Pivot-based levels with 0.01% tolerance to confirm bounces or breaks.
- **Volume Surge**: 20-period volume MA with 1.5x spike multiplier to validate momentum.
- **ATR Body Sizing**: Filters small bodies (<0.3x ATR) and long bodies (>0.8x ATR) for context-aware pattern reliability.
- **Follow-Through**: Ensures post-pattern confirmation via bullish/bearish closes or closes beyond prior bars.
Minimum average strength (default 7.0) and individual pattern thresholds (5.0) prevent weak signals.
- **Entry & Exit Logic**:
- **Long Entry**: Bullish average strength ≥7.0 (outweighing bearish), uptrend, volume spike, near support, follow-through, and HTF alignment.
- **Short Entry**: Mirror for bearish dominance in downtrends near resistance.
- **Exits**: Bearish/neutral shift, or fixed TP (5%) / SL (2%)—pyramiding disabled, 10% equity sizing.
- Backtest range: Jan 1, 2020 – Dec 31, 2025 (editable). Initial capital: $10,000.
- **Interactive Dashboard** (Top-Right Panel):
Real-time insights including:
- Market phase (e.g., "Bullish Phase (Avg Str: 8.2)"), active pattern (e.g., "BULLISH: Bullish Engulfing (Str: 10.0, Bars: 2)"), and trend status.
- Strength breakdowns (Bull/Bear/Neutral counts & averages).
- Filter status (e.g., "Volume: ✔ Spike", "ATR: Enabled (L:0.8, S:0.3)").
- Backtest stats: Total trades, win rate, streak, and last entry/exit details (price & timestamp).
Toggle mode: Strategy (live trades) or Indicator (signals only).
- **Advanced Alerts** (15+ Toggleable Types):
Set up via TradingView's "Any alert() function call" for bar-close triggers:
- Entry/Exit signals with strength & pattern details.
- Strong patterns (≥2 bullish/bearish), neutral indecision, volume spikes.
- S/R breakouts, HTF reversals, high-confidence singles (≥8.0 strength).
- Conflicting signals, MA crossovers, ATR volatility bursts, multi-bar completions.
Example: "STRONG BULLISH PATTERN detected! Strength: 9.5 | Top Pattern: Three White Soldiers | Trend: Up".
**Customization & Usage Tips**
- **Inputs Groups**: Strategy toggles, confirmations, exits, backtest dates, and 15+ alert switches—all intuitively grouped.
- **Optimization**: Tune min strengths for aggressive (lower) or conservative (higher) trading; enable/disable filters to suit your style (e.g., disable S/R for scalping).
- **Best For**: Forex, stocks, crypto on 1H–Daily charts. Test on historical data to refine TP/SL.
- **Limitations**: No external data installs; relies on built-in TA functions. Patterns are probabilistic—combine with your risk management.
Master the candles like a grandmaster. Deploy on TradingView, backtest relentlessly, and let dominance begin! Questions? Drop a comment.
*Version: 1.0 | Updated: September 2025 | Credits: Built on Pine Script v5 with nods to Nison's timeless techniques.*
Heikin Ashi Overlay SuiteHeikin Ashi Overlay Suite is designed to give traders more control and clarity when working with Heikin Ashi candles — whether you're analyzing trend strength, reducing chart noise, or simply improving your visual read of market momentum. It works by layering multiple types of HA overlays and color systems on top of your standard candlestick chart — without switching chart types. With dynamic gradient coloring, smoothing options, and a predictive line tool, this script helps you see not just what the current trend is, but how strong it is, and what it would take to reverse it.
Heikin Ashi candles help reduce noise but this script goes further by:
➡️adding color intelligence that shows trend strength using a streak counter
➡️uses smoothing logic to clean up chop and whipsaws
➡️introduces a predictive close line — a subtle but powerful guide for anticipating trend flips before they happen
Everything is configurable: colors, candle sources, overlays, predictive tools, and line styles. It’s built for traders who want visual speed, but don’t want to sacrifice signal quality.
At its core, the script offers two powerful dropdown controls:
💥HA Color Scheme (Colors Regular Candles) — Applies Heikin Ashi-derived coloring to your regular candles based on trend direction or streak strength. This gives you instant visual context without switching to a separate chart type.
💥HA Candle Overlay Mode — Overlays actual Heikin Ashi-style candles directly on top of your chart, using your preferred source:
➡️Custom HA candles using internal formula logic
➡️TradingView’s built-in Heikin Ashi source with your own colors
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
🎨 Custom + Gradient HA Coloring🎨
See trend strength at a glance:
➡️1–4 bar streaks → lighter tone
➡️5–8 bars → medium tone
➡️9+ bars → bold tone, ideal for momentum-based entries, exits, or scaling strategies
→ Choose from:
➡️Your own custom color set
➡️A simple 2-color base mode
➡️Or a 3-level gradient for progressive trend analysis (using the streak counter)
🏛️ TradingView Official Heikin Ashi Overlay
Prefer native HA candles but want your own colors?
This mode plots TradingView's Heikin Ashi source, with your personal bullish/bearish color scheme.
➡️Ensures consistency with built-in charts while still leveraging your visual style.
🌊 Smoothed Heikin Ashi Candles — Clarity in Chaos🌊
These aren’t your standard HA candles. Smoothed Heikin Ashi uses a two-step EMA process to transform chaotic price action into a cleaner, slower-moving trend structure:
🔹 First, it smooths the raw OHLC data using EMA — filtering out minor price fluctuations.
🔹 Then, it applies the Heikin Ashi transformation on top of the smoothed data.
🔹 Finally, it applies a second EMA smoothing pass to the HA values — creating ultra-smooth candles.
📈 What You See:
Trends appear more fluid and consistent.
Choppy ranges and fakeouts are visually suppressed.
Minor pullbacks within a trend are de-emphasized, helping you avoid premature exits.
🎯 Best For:
Swing traders looking to stay in positions longer.
Intraday traders dealing with volatile or noisy instruments.
Anyone who wants a "trend map" overlay without the distractions of raw price action.
✅ Reduces whipsaws
✅ Delivers high-contrast trend zones
✅ Makes reversals more visually apparent (but with a slight lag)
📍 Predictive Close Line📍
Shows where the real close must land to flip the current HA candle's color.
✅ Use it like predictive support/resistance
✅ Know if the trend is actually at risk
✅Visualize potential fakeouts or confirmation
Color-coded based on current HA direction (bullish, bearish, or neutral).
📈 Tick by tick & bar-to-bar Plots📈
Provides 2 plot types:
1)1 plot that tracks a bar tick by tick
2)another plot that tracks the close from bar to bar
For the bar to bar plot, you can choose between 2 options:
✅Full Plot — continuous line colored by HA trend
✅Recent Segments — color just the last few bars (configurable) to reduce chart clutter
✅ Customize width, number of bars, and visibility
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
📘 How to Use this script📘
Imagine you're watching a choppy 15-minute chart on a volatile crypto pair — price action is messy, and it’s hard to tell if a trend is forming or just noise.
Here’s how to cut through the chaos using Heikin Ashi Overlay Suite:
🔹 Step 1: Enable "Smoothed HA Candles"
Start by turning on the smoothed candles. You’ll immediately notice the noise fades, and broader directional moves become easier to follow. It's like switching from static to clean trend zones.
🧠 Why: Smoothed HA uses a double EMA process that filters out small reversals and lets larger moves stand out. Perfect for sideways or jittery charts.
🔹 Step 2: Watch the Color Gradient Build
As the smoothed candles begin to align in one direction, the gradient coloring (1–4, 5–8, 9+ streaks) gives you an at-a-glance visual of how strong the trend is.
✅ If you see 9+ same-colored candles? You’re likely in a mature trend.
✅ If it resets often? You’re in chop — consider staying out.
🔹 Step 3: Use the Predictive Close Line for Anticipation
Now here’s the edge — this line tells you where the candle would have to close to flip colors.
📉 If price is hovering just above it during a bullish run — momentum may be weakening.
📈 If price bounces off it — the trend may be strengthening.
This is excellent for confirming entries, exits, or spotting early warning signs.
🔹 Step 4: Switch Between Candle Modes as Needed
You can flip between:
✅ Custom HA: Gradient candles with your colors
✅ TradingView HA: The official source with your styling
✅ None: Just color regular candles using the HA logic
Use what fits your style — everything is modular.
🔹 Step 5: Tune It to Your Chart
Lastly, tweak streak thresholds (currently only can do this within the source code), smoothing lengths, and line styles to match your timeframe and strategy.
🎯 Tailor The Settings to Fit Your Trading Style🎯
🔹 🧪 Scalper (1–5 min charts)
If you’re trading fast intraday moves, you want quicker responsiveness and less lag.
Try these settings:
🔸Smoothing Lengths: Use lower values (e.g. len = 3, len2 = 5)
🔸Candle Mode: Use Custom HA or TV’s HA for real-time color flips
🔸Predictive Close Line: Great for ultra-fast anticipation of color reversals
🔸Line Mode: Use Recent Segments mode to track short bursts of trend
🔸Colors: Use high-contrast, opaque colors for clarity
✅ These settings help you catch micro-trends and flip signals faster, while still filtering out the worst of the noise.
🔹 🧪 Swing Trader (30m–4h charts and beyond)
If you’re looking for multi-hour or multi-day trend confirmation, prioritize clarity and staying in moves longer.
Recommended setup:
🔸Smoothing Lengths: Medium to high values (e.g. len = 8, len2 = 21)
🔸Candle Mode: Use Smoothed HA Candles to block out intrabar chop
🔸Gradient Colors: Enable to visualize trend maturity and strength
🔸Predictive Close Line: Helps confirm trend continuation or spot early reversals
🔸Line Mode: Use Full Plot Line for clean HA-based trend tracking
✅ These settings give you a calm, clean view of the bigger picture — ideal for holding positions longer and avoiding early exits.
🔧 This script isn’t just a chart overlay — it’s a visual trend engine.🔧
Ideal For:
🔶 Trend-followers who want clean, color-coded confirmation
🔶 Reversal traders spotting exhaustion via predictive flips
🔶 Scalpers filtering noise with lighter smoothing
🔶 Swing traders using smoothed visuals to hold longer
📌 Final Note
Heikin Ashi Overlay Pro is designed to help you see momentum, trend shifts, and market structure with greater clarity — not to predict price on its own. For best results:
✔️ Combine with support/resistance, moving averages, or price action patterns
✔️ Use Predictive Close as a confirmation tool, not a signal generator
✔️ Pair gradient colors with structure to gauge trend maturity
✔️ Always zoom out and check higher timeframes for context
🧠 Use this as part of a layered approach — not a standalone system.
🙏 Credits🙏
⚡HA logic based on SimpleCryptoLife
⚡Smoothed HA concept adapted from a script by Jackvmk
💡💡💡Turn logic into clarity. Structure into trades. And uncertainty into confidence.💡💡💡
Outside the Bollinger Bands Alerting Indicator Overview
The Outside the Bollinger Bands Alerting Indicator is a comprehensive technical analysis tool that combines multiple proven
indicators into a single, powerful system designed to identify high-probability reversal patterns at Bollinger Band extremes. This
indicator goes beyond simple band touches to detect sophisticated pattern formations that often signal strong directional moves.
Key Features & Capabilities
🎯 Advanced Pattern Recognition
Bollinger Band Breakout Patterns
- Detects "pierce-and-reject" formations where price breaks through a Bollinger Band but immediately reverses back inside
- Identifies failed breakouts that often lead to strong moves in the opposite direction
- Combines multiple confirmation signals: engulfing candle patterns, MACD momentum, and ATR volatility filters
- Visual alerts with symbols positioned below (bullish) or above (bearish) candles
Tweezer Top & Bottom Patterns
- Identifies consecutive candles with nearly identical highs (tweezer tops) or lows (tweezer bottoms)
- Requires at least one candle to breach the respective Bollinger Band
- Confirms reversal with directional close requirements
- Customizable tolerance settings for pattern sensitivity
- Visual alerts with ❙❙ symbols for easy identification
📊 Multi-Indicator Integration
Bollinger Bands Indicator
- Dual-band configuration with outer (2.0 std dev) and inner (1.5 std dev) bands that can be adjusted to suit your own parameters
- Configurable MA types: SMA, EMA, SMMA (RMA), WMA, VWMA
- Customizable length, source, and offset parameters
- Color-coded band fills for visual clarity
Moving Average Suite
- EMA 9, 21, 50, and 200 (individually toggleable)
- Special "SMA 3 High" for help visualizing and detecting Bollinger Band break-outs
- Dynamic color coding based on price relationship
Optional Ichimoku Cloud overlay
- Complete Ichimoku implementation with customizable periods
- Dynamic cloud coloring based on trend direction
- Toggleable overlay that doesn't interfere with other indicators
🚨 Comprehensive Alert System
Real-Time JSON Alerts
- Sends structured data on every confirmed bar close
- Includes all indicator values: BB levels, EMAs, MACD, RSI
- Contains signal states and crossover conditions
- Perfect for automated trading systems and webhooks
{"timestamp":1753118700000,"symbol":"ETHUSD","timeframe":"5","price":3773.3,"bollinger_bands":{"upper":3826.95,"basis":3788.32,"lower":3749.68},"emas":{"ema_9":3780.45,"ema_21":3788.92,"ema_50":3800.79,"ema_200":3787.74,"sma_3_high":3789.45},"macd":{"macd":-10.1932,"signal":-11.3266,"histogram":1.1334},"rsi":{"rsi":40.5,"rsi_ma":39.32,"level":"neutral"}}
Specific Alert Conditions
- MACD histogram state changes (rising to falling, falling to rising)
- RSI overbought/oversold crossovers
- All pattern detections (BB Bounce, Tweezer patterns)
- Bollinger Band breakout alerts
🎨 Visual Elements
Pattern Identification
- ♻ symbols for Bollinger Band breakout patterns (green for bullish, red for bearish)
- ❙❙ symbols for tweezer patterns (green below for bottoms, red above for tops)
- Color-coded band fills for trend visualization
Chart Overlay Options
- All moving averages with distinct colors
- Bollinger Bands with inner and outer boundaries
- Optional Ichimoku cloud with trend-based coloring
Trading Applications
Reversal Trading
- Identify high-probability reversal points at extreme price levels
- Use failed breakout patterns for entry signals
- Combine multiple timeframes for enhanced accuracy
Trend Analysis
- Monitor moving average relationships for trend direction
- Use Ichimoku cloud for trend strength assessment
- Track momentum with MACD and RSI integration
Risk Management
- ATR-based volatility filtering reduces false signals
- Multiple confirmation requirements improve signal quality
- Real-time alerts enable prompt decision making
Suggested Use
- Use on multiple timeframes for confluence
- Combine with support/resistance levels for enhanced accuracy
- Set up alerts for hands-free monitoring
- Customize settings based on market volatility and trading style
- Consider volume confirmation for stronger signals
Bollinger Bands (SMA 21, 2.618σ)Indicator Description: Bollinger Bands (2.618σ, 21 SMA) + RSI with Fibonacci
This custom indicator combines Bollinger Bands and Relative Strength Index (RSI), enhanced with Fibonacci-based configurations, to provide confluence signals for rejection candles, reversal setups, and continuation patterns.
Bollinger Bands Settings (Customized)
Middle Band → 21-period Simple Moving Average (SMA)
Upper Band → SMA + 2.618 standard deviations
Lower Band → SMA − 2.618 standard deviations
These parameters expand the bands compared to the traditional (20, 2.0) settings, making them better suited for volatility extremes and higher timeframe swing analysis.
Color Scheme
Middle Band = Orange
Upper Band = Red
Lower Band = Green
This color-coding emphasizes key rejection levels visually.
Candle Rejection Logic
The indicator is designed to highlight potential rejection candles when price interacts with the outer Bollinger Bands:
At the Upper Band, rejection signals suggest overextension and potential downside reaction.
At the Lower Band, rejection signals suggest oversold conditions and potential upside reaction.
Rejection Candle Types Tracked
Hammer (bullish reversal, lower rejection wick at bottom band)
Inverted Hammer (bearish reversal, upper rejection wick at top band)
Doji candles (indecision at band extremes)
Double Top formations near the upper band
Double Bottom formations near the lower band
Relative Strength Index (RSI) Settings
RSI is configured with Fibonacci retracement levels instead of traditional 30/70 thresholds.
Fibonacci sequence levels used include:
23.6% (0.236)
38.2% (0.382)
50% (0.5)
61.8% (0.618)
78.6% (0.786)
This alignment with Fibonacci ratios provides deeper market structure insights into momentum strength and exhaustion points.
Trading Confluence Zones
Upper Band + RSI at 0.618–0.786 zone → High probability bearish rejection.
Lower Band + RSI at 0.236–0.382 zone → High probability bullish reversal.
Band interaction + Doji or Hammer candles → Stronger signal confirmation.
Use Cases
Identifying trend exhaustion when price repeatedly fails to break above the upper band.
Spotting accumulation or distribution phases when price consolidates around Fibonacci-based RSI zones.
Detecting false breakouts when candle patterns (like Doji or Inverted Hammer) occur beyond the bands.
Why 2.618 Deviation & 21 SMA?
Standard Bollinger Bands (20, 2.0) capture ~95% of price action.
By widening to 2.618σ, we target extreme volatility outliers — areas where reversals are statistically more likely.
A 21-period SMA aligns better with common cycle lengths (3 trading weeks on daily charts) and Fibonacci-related time cycles.
Practical Strategy
Step 1: Watch when price touches or pierces the upper/lower band.
Step 2: Check for candle rejection patterns (Hammer, Inverted Hammer, Doji, Double Top/Bottom).
Step 3: Confirm with RSI Fibonacci levels for confluence.
Step 4: Trade with the prevailing trend or look for reversal setups if multiple confluence factors align.
Cautions
Not all touches of the bands signal reversals — strong trends can ride along the bands for extended periods.
Always combine with price action structure, volume, and higher timeframe trend bias.
📌 Summary
This indicator blends volatility-based bands with Fibonacci momentum analysis and classical candle rejection patterns. The combination of Bollinger Bands (21, 2.618σ) and RSI Fibonacci levels helps traders detect high-probability rejection zones, reversal opportunities, and overextended conditions with improved accuracy over traditional default settings.
Measured Move Volume XIndicator Description
The "Measured Move Volume X" indicator, developed for TradingView using Pine Script version 6, projects potential price targets based on the measured move concept, where the magnitude of a prior price leg (Leg A) is used to forecast a subsequent move. It overlays translucent boxes on the chart to visualize bullish (green) or bearish (red) price projections, extending them to the right for a user-specified number of bars. The indicator integrates volume analysis (relative to a simple moving average), RSI for momentum, and VWAP for price-volume weighting, combining these into a confidence score to filter entry signals, displayed as triangles on breakouts. Horizontal key level lines (large, medium, small) are drawn at significant price points derived from the measured moves, with customizable thresholds, colors, and styles. Exhaustion hints, shown as orange labels near box extremes, indicate potential reversal points. Anomalous candles, marked with diamond shapes, are identified based on volume spikes and body-to-range ratios. Optional higher timeframe candle coloring enhances context. The indicator is fully customizable through input groups for lookback periods, transparency, and signal weights, making it adaptable to various assets and timeframes.
Adjustment Tips for Optimization
To optimize the "Measured Move Volume X" indicator for specific assets or timeframes, adjust the following input parameters:
Leg A Lookback (default: 14 bars): Increase to 20-30 for volatile markets (e.g., cryptocurrencies) to capture larger price swings; decrease to 5-10 for intraday charts (e.g., stocks) for faster signals.
Extend Box to the Right (default: 30 bars): Extend to 50+ for daily or weekly charts to project further targets; shorten to 10-20 for lower timeframes to reduce clutter.
Volume SMA Length (default: 20) and Relative Volume Threshold (default: 1.5): Lower the threshold to 1.2-1.3 for low-volume assets (e.g., commodities) to detect subtler spikes; raise to 2.0+ for high-volume equities to filter noise. Match SMA length to RSI length for consistency.
RSI Parameters (default: length 14, overbought 70, oversold 30): Set overbought to 80 and oversold to 20 in trending markets to reduce premature exit signals; shorten length to 7-10 for scalping.
Key Level Thresholds (default: large 10%, medium 5%, small 5%): Increase thresholds (e.g., large to 15%) for volatile assets to focus on significant moves; disable medium or small lines to declutter charts.
Confidence Score Weights (default: volume 0.5, VWAP 0.3, RSI 0.2): Increase volume weight (e.g., 0.7) for volume-driven markets like futures; emphasize RSI (e.g., 0.4) for momentum-focused strategies.
Anomaly Detection (default: volume multiplier 1.5, small body ratio 0.2, large body ratio 0.75): Adjust the volume multiplier higher for stricter anomaly detection in noisy markets; fine-tune body-to-range ratios based on asset-specific candle patterns.
Use TradingView’s replay feature to test adjustments on historical data, ensuring settings suit the chosen market and timeframe.
Tips for Using the Indicator
Interpreting Signals: Green upward triangles indicate bullish breakout entries when price exceeds the prior high with a confidence score ≥40; red downward triangles signal bearish breakouts. Use these to identify potential entry points aligned with the projected box targets.
Box Projections: Bullish boxes project upward targets (top of box) equal to the prior leg’s height added to the breakout price; bearish boxes project downward. Monitor price action near box edges for target completion or reversal.
Exhaustion Hints: Orange labels near box tops (bullish) or bottoms (bearish) suggest potential exhaustion when price deviates within the set percentage (default: 5%) and RSI or volume conditions are met. Use these as cues to watch for reversals.
Key Level Lines: Large, medium, and small lines mark significant price levels from box tops/bottoms. Use these as potential support/resistance zones, especially when drawn with high volume (colored differently).
Anomaly Candles: Orange diamonds highlight candles with unusual volume/body characteristics, indicating potential reversals or pauses. Combine with box levels for context.
Higher Timeframe Coloring: Enable to color bars based on higher timeframe candle closures (e.g., 1, 2, 5, or 15 minutes) for added trend context.
Customization: Toggle "Only Show Bullish Moves" to focus on bullish setups. Adjust transparency and line styles for visual clarity. Test settings to balance signal frequency and chart readability.
Inputs: Organized into groups (e.g., "Measured Move Settings") using input.int, input.float, input.color, and input.bool for user customization, with tooltips for clarity.
Calculations: Computes relative volume (ta.sma(volume, volLookback)), VWAP (ta.vwap(hlc3)), RSI (ta.rsi(close, rsiLength)), and prior leg extremes (ta.highest/lowest) using prior bar data ( ) to prevent repainting.
Boxes and Lines: Creates boxes (box.new) for bullish/bearish projections and lines (line.new) for key levels. The f_addLine function manages line arrays (array.new_line), capping at maxLinesCount to avoid clutter.
Confidence Score: Combines volume, VWAP distance, and RSI into a weighted score (confScore), filtering entries (≥40). Rounded for display.
Exhaustion Hints: Functions like f_plotBullExitHint assess price deviation, RSI, and volume decrease, using label.new for dynamic orange labels.
Entry Signals and Plots: plotshape displays triangles for breakouts; plot and hline show VWAP and RSI levels; request.security handles higher timeframe coloring.
Anomaly Detection: Identifies candles with small-body high-volume or large-body average-volume patterns via ratios, plotted as diamonds.
Transformer Flux DashboardHere’s a practical guide to what your Transformer Flux Dashboard does and how to use it.
What it is
A compact, two-column trading dashboard + signal pack that blends trend, MACD, and OBV into one view (“Flux Score”) and adds session awareness (pre-sessions and main sessions in Eastern time). It’s designed for regular candles by default and avoids repaint by letting you confirm on bar close.
Core pieces it calculates
Moving Averages
Two MAs: Fast (HMA/EMA) and Slow (HMA/EMA).
You choose length, line width, color, and transparency.
Trend engine (Strict/Lenient)
Uses the relation between Fast/Slow MA and a debounced fast-MA slope filter (slope > ATR×buffer).
Strict: requires fast>slow and slow rising (or the inverse for down).
Lenient: fast>slow or slow rising (or the inverse).
A confirmation window (bars) must hold true before trend flips. That window can be auto-tuned by session (Asia/London/NY) or set globally.
OBV confirmation (optional)
OBV smoothed by SMA; needs to be rising/falling for N bars (also session-aware if you enable presets).
MACD
Standard MACD Fast/Slow/Signal; the dashboard shows Bull ▲, Bear ▼ or Flat based on line vs signal.
Flux Score (top row)
A composite, smoothed gauge from 0–100:
40% Trend, 30% MACD, 30% OBV → EMA(3) smoothed.
Labels: Bullish ≥ 70, Bearish ≤ 30, otherwise Neutral.
Summary line explains why (e.g., “MACD↑, OBV↑, Trend up”).
Sessions & zones (Eastern/NY time)
Recognizes Asia / London / New York main sessions and pre-sessions using your chart’s Eastern time.
Session label (top of chart): text is white; background auto-matches the current session color (or your manual color).
Zone backgrounds (optional): off by default; when on, default transparency ≈ 95% (very light), with separate colors for each session and pre-session. A toggle lets you draw pre-session on top or beneath main sessions.
Signals & markers
Two strength tiers: Strong (Trend + OBV + MACD aligned) and Weak (2 of the 3 agree).
To reduce clutter, markers only appear on direction shifts (from last visible direction to a new one), and you can enforce a minimum bar gap.
Marker style:
Default Icons with LabelUp/LabelDown (tiny).
Colors: strong long = bright white by default; others configurable.
Weak markers are slightly offset from price using ATR so they don’t overlap wicks.
Dashboard (2-column)
Left column = label, right column = value:
Flux Score: numeric + Bullish/Neutral/Bearish tag.
Summary: short reason of the score.
Trend: UP / DOWN / FLAT (cell tinted green/red/gray).
MACD: Bull ▲ / Bear ▼ / Flat (tinted).
Signal: last printed signal + bar age (fresh signals get a lighter tint).
MA: slow MA type/length and up/down arrow.
Sess: current session label (e.g., “Pre-London”, “New York”).
VIX / VXN (optional): shows current value.
Auto tint: based on calm/watch/elevated thresholds (you control levels and colors).
Manual tint: fixed BG color if you prefer consistency.
Params: “P”=trend bars, “O”=OBV bars, mode (Strict/Lenient), and “Candles”.
You can set a global Default Transparency for the dashboard cells.
Key settings to know
Confirm On Close: when on (default), trend/OBV/MACD states use the last confirmed bar; this avoids mid-bar flicker and reduces repaint risk.
Session presets: when enabled, the number of bars required for confirmations tightens/loosens per session (e.g., Asia uses more bars than NY).
Colors & Opacity:
MA lines have their own transparency (default 0 = fully opaque).
Dashboard cells use a single global transparency (default 40%).
Session zones default to very light (95%) and are off by default.
VIX/VXN cells can auto-color by regime or use a manual background.
Markers:
“Icons” vs “Ticks.” Default is Icons with tiny labels up/down.
“Shift only” display reduces noise; you can also set min bar spacing.
How to read it (quick workflow)
Flux Score row: a fast “risk-on/off” gauge.
≥70 with green Trend/MACD cells → higher-conviction long context.
≤30 with red Trend/MACD cells → higher-conviction short context.
Summary explains why the score is what it is.
Signal row: tells you the last official signal and how many bars ago it fired. Fresh signals tint lighter.
MA row: aligns your slow baseline; arrow helps spot slow-turns early.
Sess row + label: know which market is active; behavior and your confirmation bars adapt by session if presets are on.
VIX/VXN (if enabled): extra context for risk regime (values and color band).
Good practices & caveats
It’s confirmation-based to reduce false flips; you’ll get signals slightly later, by design.
All signals are informational; there’s no position management or stops in this build (we removed the stop visuals by request).
If you switch to exotic chart types or extreme resolutions, re-tune lengths and confirmation bars (and potentially disable session presets).
For scalping, consider reducing confirmation bars and OBV smoothing; for higher timeframes, increase them.
Quick customization ideas
Want faster flips? Lower confirmBars and obvBars, increase slope buffer a bit to retain quality.
Want fewer weak signals? Show only strong markers (toggle off weak via colors/visibility or increase min bar gap).
Prefer EMA stacking? Set both Fast/Slow to EMA.
Don’t care about OBV? Turn OBV confirm off; Trend + MACD will drive
