11-MA Institutional System (ATR+HTF Filters)11-MA Institutional Trading System Analysis.
This is a comprehensive Trading View Pine Script indicator that implements a sophisticated multi-timeframe moving average system with institutional-grade filters. Let me break down its key components and functionality:
🎯 Core Features
1. 11 Moving Average System. The indicator plots 11 customizable moving averages with different roles:
MA1-MA4 (5, 8, 10, 12): Fast-moving averages for short-term trends
MA5 (21 EMA): Short-term anchor - critical pivot point
MA6 (34 EMA): Intermediate support/resistance
MA7 (50 EMA): Medium-term bridge between short and long trends
MA8-MA9 (89, 100): Transition zone indicators
MA10-MA11 (150, 200): Long-term anchors for major trend identification
Each MA is fully customizable:
Type: SMA, EMA, WMA, TMA, RMA
Color, width, and enable/disable toggle
📊 Signal Generation System
Three Signal Tiers: Short-Term Signals (ST)
Trigger: MA8 (EMA 8) crossing MA21 (EMA 21)
Filters Applied:
✅ ATR-based post-cross confirmation (optional)
✅ Momentum confirmation (RSI > 50, MACD positive)
✅ Volume spike requirement
✅ HTF (Higher Timeframe) alignment
✅ Strong candle body ratio (>50%)
✅ Multi-MA confirmation (3+ MAs supporting direction)
✅ Price beyond MA21 with conviction
✅ Minimum bar spacing (prevents signal clustering)
✅ Consolidation filter
✅ Whipsaw protection (ATR-based price threshold)
Medium-Term Signals (MT)
Trigger: MA21 crossing MA50
Less strict filtering for swing trades
Major Signals
Golden Cross: MA50 crossing above MA200 (major bullish)
Death Cross: MA50 crossing below MA200 (major bearish)
🔍 Advanced Filtering System1. ATR-Based ConfirmationPrice must move > (ATR × 0.25) beyond the MA after crossover
This prevents false signals during low-volatility consolidation.2. Momentum Filters
RSI (14)
MACD Histogram
Rate of Change (ROC)
Composite momentum score (-3 to +3)
3. Volume Analysis
Volume spike detection (2x MA)
Volume classification: LOW, MED, HIGH, EXPL
Directional volume confirmation
4. Higher Timeframe Alignment
HTF1: 60-minute (default)
HTF2: 4-hour (optional)
HTF3: Daily (optional)
Signals only trigger when current TF aligns with HTF trend
5. Market Structure Detection
Break of Structure (BOS): Price breaking recent swing highs/lows
Order Blocks (OB): Institutional demand/supply zones
Fair Value Gaps (FVG): Imbalance areas for potential fills
📈 Comprehensive DashboardReal-Time Metrics Display: {scrollbar-width:none;-ms-overflow-style:none;-webkit-overflow-scrolling:touch;} ::-webkit-scrollbar{display:none}MetricDescriptionPriceCurrent close priceTimeframeCurrent chart timeframeSHORT/MEDIUM/MAJORTrend classification (🟢BULL/🔴BEAR/⚪NEUT)HTF TrendsHigher timeframe alignment indicatorsMomentumSTR↑/MOD↑/WK↑/WK↓/MOD↓/STR↓VolatilityLOW/MOD/HIGH/EXTR (based on ATR%)RSI(14)Color-coded: >70 red, <30 greenATR%Volatility as % of priceAdvanced Dashboard Features (Optional):
Price Distance from Key MAs
vs MA21, MA50, MA200 (percentage)
Color-coded: green (above), red (below)
MA Alignment Score
Calculates % of MAs in proper order
🟢 for bullish alignment, 🔴 for bearish
Trend Strength
Based on separation between MA21 and MA200
NONE/WEAK/MODERATE/STRONG/EXTREME
Consolidation Detection
Identifies low-volatility ranges
Prevents signals during sideways markets
⚙️ Customization OptionsFilter Toggles:
☑️ Require Momentum
☑️ Require Volume
☑️ Require HTF Alignment
☑️ Use ATR post-cross confirmation
☑️ Whipsaw filter
Min bars between signals (default: 5)
Dashboard Styling:
9 position options
6 text sizes
Custom colors for header, rows, and text
Toggle individual metrics on/off
🎨 Visual Elements
Signal Labels:
ST▲/ST▼ (green/red) - Short-term
MT▲/MT▼ (blue/orange) - Medium-term
GOLDEN CROSS / DEATH CROSS - Major signals
Volume Spikes:
Small labels showing volume class + direction
Example: "HIGH🟢" or "EXPL🔴"
Market Structure:
Dashed lines for Break of Structure levels
Automatic detection of swing highs/lows
🔔 Alert Conditions
Pre-configured alerts for:
Short-term bullish/bearish crosses
Medium-term bullish/bearish crosses
Golden Cross / Death Cross
Volume spikes
💡 Key Strengths
Institutional-Grade Filtering: Multiple confirmation layers reduce false signals
Multi-Timeframe Analysis: Ensures alignment across timeframes
Adaptive to Market Conditions: ATR-based thresholds adjust to volatility
Comprehensive Dashboard: All critical metrics in one view
Highly Customizable: 100+ input parameters
Signal Quality Over Quantity: Strict filters prioritize high-probability setups
⚠️ Usage Recommendations
Best for: Swing trading and position trading
Timeframes: Works on all TFs, optimized for 15m-Daily
Markets: Stocks, Forex, Crypto, Indices
Signal Frequency: Conservative (quality over quantity)
Combine with: Support/resistance, price action, risk management
🔧 Technical Implementation Notes
Uses Pine Script v6 syntax
Efficient calculation with minimal repainting
Maximum 500 labels for performance
Security function for HTF data (no lookahead bias)
Array-based MA alignment calculation
State variables to track signal spacing
This is a professional-grade trading system that combines classical technical analysis (moving averages) with modern institutional concepts (market structure, order blocks, multi-timeframe alignment).
The extensive filtering system is designed to eliminate noise and focus on high-probability trade setups.
Search in scripts for "美股标普500"
Kalkulator pozycji XAUUSD PLN, 1:500, 1100 to 100 kontaPosition calculator based on the number of pips that you quickly enter from the tool, this device will select the appropriate lot for you and you can quickly take a position
ICT Breaker Blocks [Exponential-X]🔄 Breaker Blocks
Overview
Breaker Blocks automatically identifies failed order blocks that have reversed their polarity. When an order block gets broken, it often becomes a powerful support or resistance zone in the opposite direction. This indicator tracks these institutional "flips" based on ICT (Inner Circle Trader) concepts, helping identify where price is likely to find strong support or resistance after a structural break.
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🎯 What This Indicator Does
Detects Breaker Blocks:
• 🔵 Bullish Breaker Blocks (BB+) - Failed bearish order blocks that became support
• 🟣 Bearish Breaker Blocks (BB-) - Failed bullish order blocks that became resistance
• Tracks order blocks first, then monitors when they break
• Converts broken order blocks into breaker blocks automatically
• Shows when breakers get tested by price
How Breakers Form:
1. Order block forms (last opposite candle before strong move)
2. Price returns and breaks through the order block
3. Broken order block becomes a breaker block with flipped polarity
4. Old resistance becomes new support (or vice versa)
Visual Display: Smart Features:
• Auto-timeframe adjustment for optimal detection
• ATR-based strength filtering
• Active block highlighting
• Test tracking
• Distance calculator
• Duplicate prevention
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📚 Understanding Breaker Blocks
What Are Breaker Blocks?
Breaker blocks are failed order blocks that price has broken through. In ICT methodology:
• When institutions place orders creating an order block
• If that level fails and price breaks through
• The zone often becomes strong support/resistance in the opposite direction
• This represents institutional position flipping
Why Breakers Form:
• Failed Defense: Institutions couldn't defend the original level
• Position Flip: Institutions reversed their position
• Stop Hunt Complete: After sweeping stops, new levels form
• Polarity Change: Old resistance becomes new support (or vice versa)
Key Difference From Order Blocks: [/b>
• Order Block: Original institutional level (unbroken)
• Breaker Block: Failed order block that flipped polarity
• Breakers often provide STRONGER reactions than original OBs
• Represents where institutions changed their strategy
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🔵 Bullish Breaker Blocks Explained
Formation Process:
1. Step 1: Bearish order block forms (last bullish candle before drop)
2. Step 2: Price breaks ABOVE this bearish OB
3. Step 3: The broken bearish OB becomes a bullish breaker
4. Step 4: Now acts as SUPPORT when price returns
What It Means:
• Old resistance level failed
• Institutions flipped from selling to buying
• When price returns, zone acts as strong support
• Higher probability long setup than regular support
Trading Bullish Breakers:
Entry Setup:
• Wait for price to retrace back to bullish breaker
• Look for rejection/bounce from the breaker zone
• Enter long when price respects the breaker as support
• Stop loss: Below the breaker block
• Target: Recent high or opposite breaker
Why It Works:
Failed resistance becoming support is a strong technical signal indicating structural change in market sentiment.
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🟣 Bearish Breaker Blocks Explained
Formation Process:
1. Step 1: Bullish order block forms (last bearish candle before rally)
2. Step 2: Price breaks BELOW this bullish OB
3. Step 3: The broken bullish OB becomes a bearish breaker
4. Step 4: Now acts as RESISTANCE when price returns
What It Means:
• Old support level failed
• Institutions flipped from buying to selling
• When price returns, zone acts as strong resistance
• Higher probability short setup than regular resistance
Trading Bearish Breakers:
Entry Setup:
• Wait for price to retrace back to bearish breaker
• Look for rejection/reversal from the breaker zone
• Enter short when price respects the breaker as resistance
• Stop loss: Above the breaker block
• Target: Recent low or opposite breaker
Why It Works:
Failed support becoming resistance indicates structural change and often leads to continuation moves.
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📊 How To Use This Indicator
Strategy 1: Breaker Block Retest
Timeframes: 15min, 1H, 4H
Style: [/b> Swing trading, reversal entries
Rules:
1. Identify active breaker block (bright color, not gray)
2. Wait for price to return to the breaker zone
3. Look for reversal confirmation (pin bar, engulfing, rejection)
4. Enter in the direction the breaker suggests
5. Stop: Beyond opposite side of breaker
6. Target: 2-3R or previous structure
Example - Bullish Breaker:
• Bullish breaker at $48,000-$48,500
• Price drops to $48,200 (enters breaker)
• Bullish pin bar forms
• Enter long at $48,600, stop at $47,800
• Target: $50,000+
Strategy 2: Multi-Timeframe Breakers
Timeframes: Combine 1H + 4H or 15min + 1H
Style: [/b> High-probability setups
Rules:
1. Identify breaker on higher timeframe (4H or Daily)
2. Switch to lower timeframe (1H or 15min)
3. Look for lower TF breaker WITHIN higher TF breaker
4. Trade the lower TF breaker in same direction as HTF
5. Stop: Below lower TF breaker
6. Target: Edge of higher TF breaker or beyond
Why It Works: Alignment across timeframes increases probability
Strategy 3: Breaker + Order Block Confluence
Timeframes: 1H, 4H
Style: High-conviction trades
Rules:
1. Find breaker block that overlaps with fresh order block
2. This creates double institutional zone
3. Wait for price to reach confluence area
4. Enter on first touch with confirmation
5. Stop: Beyond confluence zone
6. Target: 3-5R
Why It Works: Two ICT concepts aligned = maximum probability
Strategy 4: Breaker Breakout
Timeframes: [/b> 5min, 15min, 1H
Style: Trend continuation
Rules:
1. Price approaches breaker block
2. Instead of respecting it, price breaks THROUGH
3. This indicates very strong momentum
4. Enter breakout in direction of break
5. Stop: Back inside the breaker
6. Target: 2-3R
Why It Works: When breakers fail, momentum is extremely strong
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⚙️ Settings Explained
Core Settings
Auto-Adjust for Timeframe (Default: ON)
• Automatically optimizes detection for current chart
• 1min: 3 bars lookback
• 5min: 4 bars lookback
• 15min: 5 bars lookback
• 1H: 6 bars lookback
• 4H+: 8-12 bars lookback
• Recommended: Keep ON
Manual Detection Length (Default: 5)
• Only used when Auto-Adjust is OFF
• Lookback period for finding order blocks
• Lower = more sensitive
• Higher = more selective
Display Settings
Show Bullish/Bearish Breaker Blocks
• Toggle each type independently
• Customize colors (default: cyan and fuchsia)
• Tip: Use colors that stand out from order blocks
Max Breaker Blocks to Display (Default: 10) [/b>
• Limits visible breakers
• Lower (5-8): Cleaner chart
• Higher (15-30): More context
• Recommended: 10-15
Show Breaker Block Labels [/b>
• Displays BB+ and BB- text
• Shows 🎯 on active (nearest) breaker
• Turn OFF for minimal appearance
Extend Blocks (bars) (Default: 50)
• How far to extend boxes to the right
• Recommended: 40-60 bars
Filters
Block Strength Filter (Default: Medium)
• Low: 0.5x ATR - More breakers, more noise
• Medium: 1x ATR - Balanced
• High: 1.5x ATR - Only strongest breakers
• Note: Breakers are naturally less common than OBs
• For learning: Use Low to see more examples
• For trading: Use Medium or High
Min Block Size % (Default: 0.1)
• Minimum breaker size as % of price
• Filters tiny insignificant blocks
• Adjust based on instrument volatility
Advanced
Show Tested Blocks (Default: OFF) [/b>
• When ON: Shows gray boxes for tested breakers
• When OFF: Breakers disappear after test
• Use ON: For learning and analysis
• Use OFF: For clean active trading
Highlight Active Block (Default: ON)
• Highlights nearest breaker to current price
• Active block shown with brighter color and 🎯
• Recommended: Keep ON
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📱 Info Panel Guide
Bullish BB Count Bearish BB Count
• Number of active (untested) bearish breaker blocks
• More bearish breakers = More resistance zones above
Bias Indicator [/b>
• ⬆ Bullish: More bullish breakers (support > resistance)
• ⬇ Bearish: More bearish breakers (resistance > support)
• ↔ Neutral: Equal breakers on both sides
Near Indicator
• Shows nearest active breaker and distance
• Example: "Bull BB -1.5%" = Bullish breaker 1.5% below price
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📱 Alert Setup
This indicator includes 2 alert types:
1. Price Entering Bullish Breaker [/b>
• Fires when price touches bullish breaker block
• Action: Watch for bounce/support
2. Price Entering Bearish Breaker
• Fires when price touches bearish breaker block
• Action: Watch for rejection/resistance
To Set Up Alerts:
1. Click "Alert" button (clock icon)
2. Select "Breaker Blocks"
3. Choose alert type
4. Configure notifications
5. Click "Create"
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💎 Pro Tips & Best Practices
✅ DO:
• Wait for confirmation before entering at breakers
• First touch of breaker has highest reliability
• Use breakers with trend direction for best results
• Combine with order blocks and FVGs for confluence
• Check multiple timeframes for breaker alignment
• Respect breakers - they're stronger than regular S/R
• Use proper stop placement beyond the breaker
⚠️ DON'T:
• Don't trade every breaker - quality over quantity
• Don't ignore breaker breaks - very strong momentum signal
• Don't use tight stops - allow room for wicks
• Don't expect all breakers to hold
• Don't trade against strong momentum through breakers
• Don't confuse breakers with regular order blocks
🎯 Best Timeframes:
• Scalping: 5min, 15min (quick breaker tests)
• Day Trading: 15min, 1H (balanced)
• Swing Trading: 1H, 4H, Daily (major breakers)
🔥 Best Markets:
• Excellent: BTC, ETH, Forex majors, ES, NQ
• Good: Gold, Oil, Major indices
• Note: Breakers need volatility to form
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🎓 Advanced Concepts
Breaker Strength Hierarchy
From weakest to strongest:
1. Support/Resistance lines
2. Order Blocks (unbroken)
3. Breaker Blocks (broken OBs) ← Often strongest
4. Multiple breakers stacked together
Breaker vs Order Block Priority
If breaker and order block overlap:
• Breaker takes precedence
• Failed levels are more significant
• Price respects breakers more reliably
Nested Breakers [/b>
When lower timeframe breaker exists within higher timeframe breaker:
• Trade lower TF breaker first
• Use higher TF breaker as final target
• Highest probability setups
Multiple Breaker Tests [/b>
• First test: Highest probability
• Second test: Still valid but weaker
• Third test: Likely to break through
Breaker Breakouts [/b>
When price breaks through breaker:
• Extremely strong momentum signal
• Old level completely invalidated
• Trade the breakout aggressively
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📈 Common Patterns [/b>
Pattern 1: The Perfect Flip
• Bearish OB forms
• Price breaks above it cleanly
• Becomes bullish breaker
• First retest bounces perfectly
• High-probability setup
Pattern 2: The Double Break
• Bullish OB breaks down (becomes bearish breaker)
• Price tests it and rejects
• Later breaks back up through breaker
• Very strong momentum signal
Pattern 3: The Breaker Ladder [/b>
• Multiple breakers stacked like stairs
• Price bounces from one to next
• Each breaker provides support/resistance
Pattern 4: The Failed Breaker
• Breaker forms but gets broken immediately
• Shows extreme momentum
• Don't fight it - trade the breakout
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🙏 If You Find This Helpful
• ⭐ Leave your feedback
• 💬 Share your experience in the comments
• 🔔 Follow for updates and new tools
Questions about breaker blocks? Feel free to ask in the comments.
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Version History [/b>
• v1.0 - Initial release with auto-timeframe detection and polarity flip tracking
ALT Risk Metric StrategyHere's a professional write-up for your ALT Risk Strategy script:
ALT/BTC Risk Strategy - Multi-Crypto DCA with Bitcoin Correlation Analysis
Overview
This strategy uses Bitcoin correlation as a risk indicator to time entries and exits for altcoins. By analyzing how your chosen altcoin performs relative to Bitcoin, the strategy identifies optimal accumulation periods (when alt/BTC is oversold) and profit-taking opportunities (when alt/BTC is overbought). Perfect for traders who want to outperform Bitcoin by strategically timing altcoin positions.
Key Innovation: Why Alt/BTC Matters
Most traders focus solely on USD price, but Alt/BTC ratios reveal true altcoin strength:
When Alt/BTC is low → Altcoin is undervalued relative to Bitcoin (buy opportunity)
When Alt/BTC is high → Altcoin has outperformed Bitcoin (take profits)
This approach captures the rotation between BTC and alts that drives crypto cycles
Key Features
📊 Advanced Technical Analysis
RSI (60% weight): Primary momentum indicator on weekly timeframe
Long-term MA Deviation (35% weight): Measures distance from 150-period baseline
MACD (5% weight): Minor confirmation signal
EMA Smoothing: Filters noise while maintaining responsiveness
All calculations performed on Alt/BTC pairs for superior market timing
💰 3-Tier DCA System
Level 1 (Risk ≤ 70): Conservative entry, base allocation
Level 2 (Risk ≤ 50): Increased allocation, strong opportunity
Level 3 (Risk ≤ 30): Maximum allocation, extreme undervaluation
Continuous buying: Executes every bar while below threshold for true DCA behavior
Cumulative sizing: L3 triggers = L1 + L2 + L3 amounts combined
📈 Smart Profit Management
Sequential selling: Must complete L1 before L2, L2 before L3
Percentage-based exits: Sell portions of position, not fixed amounts
Auto-reset on re-entry: New buy signals reset sell progression
Prevents premature full exits during volatile conditions
🤖 3Commas Automation
Pre-configured JSON webhooks for Custom Signal Bots
Multi-exchange support: Binance, Coinbase, Kraken, Bitfinex, Bybit
Flexible quote currency: USD, USDT, or BUSD
Dynamic order sizing: Automatically adjusts to your tier thresholds
Full webhook documentation compliance
🎨 Multi-Asset Support
Pre-configured for popular altcoins:
ETH (Ethereum)
SOL (Solana)
ADA (Cardano)
LINK (Chainlink)
UNI (Uniswap)
XRP (Ripple)
DOGE
RENDER
Custom option for any other crypto
How It Works
Risk Metric Calculation (0-100 scale):
Fetches weekly Alt/BTC price data for stability
Calculates RSI, MACD, and deviation from 150-period MA
Normalizes MACD to 0-100 range using 500-bar lookback
Combines weighted components: (MACD × 0.05) + (RSI × 0.60) + (Deviation × 0.35)
Applies 5-period EMA smoothing for cleaner signals
Color-Coded Risk Zones:
Green (0-30): Extreme buying opportunity - Alt heavily oversold vs BTC
Lime/Yellow (30-70): Accumulation range - favorable risk/reward
Orange (70-85): Caution zone - consider taking initial profits
Red/Maroon (85-100+): Euphoria zone - aggressive profit-taking
Entry Logic:
Buys execute every candle when risk is below threshold
As risk decreases, position sizing automatically scales up
Example: If risk drops from 60→25, you'll be buying at L1 rate until it hits 50, then L2 rate, then L3 rate
Exit Logic:
Sells only trigger when in profit AND risk exceeds thresholds
Sequential execution ensures partial profit-taking
If new buy signal occurs before all sells complete, sell levels reset to L1
Configuration Guide
Choosing Your Altcoin:
Select crypto from dropdown (or use CUSTOM for unlisted coins)
Pick your exchange
Choose quote currency (USD, USDT, BUSD)
Risk Metric Tuning:
Long Term MA (default 150): Higher = more extreme signals, Lower = more frequent
RSI Length (default 10): Lower = more volatile, Higher = smoother
Smoothing (default 5): Increase for less noise, decrease for faster reaction
Buy Settings (Aggressive DCA Example):
L1 Threshold: 70 | Amount: $5
L2 Threshold: 50 | Amount: $6
L3 Threshold: 30 | Amount: $7
Total L3 buy = $18 per candle when deeply oversold
Sell Settings (Balanced Exit Example):
L1: 70 threshold, 25% position
L2: 85 threshold, 35% position
L3: 100 threshold, 40% position (final exit)
3Commas Setup
Bot Configuration:
Create Custom Signal Bot in 3Commas
Set trading pair to your altcoin/USD (e.g., ETH/USD, SOL/USDT)
Order size: Select "Send in webhook, quote" to use strategy's dollar amounts
Copy Bot UUID and Secret Token
Script Configuration:
Paste credentials into 3Commas section inputs
Check "Enable 3Commas Alerts"
Save and apply to chart
TradingView Alert:
Create Alert → Condition: "alert() function calls only"
Webhook URL: api.3commas.io
Enable "Webhook URL" checkbox
Expiration: Open-ended
Strategy Advantages
✅ Outperform Bitcoin: Designed specifically to beat BTC by timing alt rotations
✅ Capture Alt Seasons: Automatically accumulates when alts lag, sells when they pump
✅ Risk-Adjusted Sizing: Buys more when cheaper (better risk/reward)
✅ Emotional Discipline: Systematic approach removes fear and FOMO
✅ Multi-Asset: Run same strategy across multiple altcoins simultaneously
✅ Proven Indicators: Combines RSI, MACD, and MA deviation - battle-tested tools
Backtesting Insights
Optimal Timeframes:
Daily chart: Best for backtesting and signal generation
Weekly data is fetched internally regardless of display timeframe
Historical Performance Characteristics:
Accumulates heavily during bear markets and BTC dominance periods
Captures explosive altcoin rallies when BTC stagnates
Sequential selling preserves capital during extended downtrends
Works best on established altcoins with multi-year history
Risk Considerations:
Requires capital reserves for extended accumulation periods
Some altcoins may never recover if fundamentals deteriorate
Past correlation patterns may not predict future performance
Always size positions according to personal risk tolerance
Visual Interface
Indicator Panel Displays:
Dynamic color line: Green→Lime→Yellow→Orange→Red as risk increases
Horizontal threshold lines: Dashed lines mark your buy/sell levels
Entry/Exit labels: Green labels for buys, Orange/Red/Maroon for sells
Real-time risk value: Numerical display on price scale
Customization:
All threshold lines are adjustable via inputs
Color scheme clearly differentiates buy zones (green spectrum) from sell zones (red spectrum)
Line weights emphasize most extreme thresholds (L3 buy and L3 sell)
Strategy Philosophy
This strategy is built on the principle that altcoins move in cycles relative to Bitcoin. During Bitcoin rallies, alts often bleed against BTC (high sell, accumulate). When Bitcoin consolidates, alts pump (take profits). By measuring risk on the Alt/BTC chart instead of USD price, we time these rotations with precision.
The 3-tier system ensures you're always averaging in at better prices and scaling out at better prices, maximizing your Bitcoin-denominated returns.
Advanced Tips
Multi-Bot Strategy:
Run this on 5-10 different altcoins simultaneously to:
Diversify correlation risk
Capture whichever alt is pumping
Smooth equity curve through rotation
Pairing with BTC Strategy:
Use alongside the BTC DCA Risk Strategy for complete portfolio coverage:
BTC strategy for core holdings
ALT strategies for alpha generation
Rebalance between them based on BTC dominance
Threshold Calibration:
Check 2-3 years of historical data for your chosen alt
Note where risk metric sat during major bottoms (set buy thresholds)
Note where it peaked during euphoria (set sell thresholds)
Adjust for your risk tolerance and holding period
Credits
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Technical Analysis Framework: RSI, MACD, Moving Average theory
Implementation: pommesUNDwurst
Disclaimer
This strategy is for educational purposes only. Cryptocurrency trading involves substantial risk of loss. Altcoins are especially volatile and many fail completely. The strategy assumes liquid markets and reliable Alt/BTC price data. Always do your own research, understand the fundamentals of any asset you trade, and never risk more than you can afford to lose. Past performance does not guarantee future results. The authors are not financial advisors and assume no liability for trading decisions.
Additional Warning: Using leverage or trading illiquid altcoins amplifies risk significantly. This strategy is designed for spot trading of established cryptocurrencies with deep liquidity.
Tags: Altcoin, Alt/BTC, DCA, Risk Metric, Dollar Cost Averaging, 3Commas, ETH, SOL, Crypto Rotation, Bitcoin Correlation, Automated Trading, Alt Season
Feel free to modify any sections to better match your style or add specific backtesting results you've observed! 🚀Claude is AI and can make mistakes. Please double-check responses. Sonnet 4.5
Volume Profile VisionVolume Profile Vision - Complete Description
Overview
Volume Profile Vision (VPV) is an advanced volume profile indicator that visualizes where trading activity has occurred at different price levels over a specified time period. Unlike traditional volume indicators that show volume over time, this indicator displays volume distribution across price levels, helping traders identify key support/resistance zones, fair value areas, and potential reversal points.
What Makes This Indicator Original
Volume Profile Vision introduces several unique features not found in standard volume profile tools:
Dual-Direction Histogram Display:
Unlike conventional volume profiles that only show bars extending in one direction, VPV displays volume bars extending both left (into historical candles) and right (as a traditional histogram). This bi-directional approach allows traders to see exactly where historical price action intersected with high-volume nodes.
Real-Time Candle Highlighting: The indicator dynamically highlights volume bars that intersect with the current candle's price range, making it immediately obvious which volume levels are currently in play.
Four Professional Color Schemes: Each color scheme uses distinct gradient algorithms and visual encoding systems:
Traffic Light: Uses red (POC), green (VA boundaries), yellow (HVN), with grayscale gradients outside the value area
Aurora Glass: Modern cyan-to-magenta gradient with hot magenta POC highlighting
Obsidian Precision: Professional dark theme with white POC and electric cyan accents
Black Ice: Monochromatic cyan family with graduated intensity
Adaptive Transparency System: Automatically adjusts bar transparency based on position relative to value area, with special handling for each color scheme to maintain visual clarity.
Core Concepts & Calculations
Volume Distribution Analysis
The indicator divides the visible price range into user-defined price levels (default: 80 levels) and calculates the total volume traded at each level by:
Scanning back through the specified lookback period (customizable or visible range)
For each historical bar, determining which price levels the bar's high/low range intersects
Accumulating volume for each intersected price level
Optionally filtering by bullish/bearish volume only
Point of Control (POC)
The POC is the price level with the highest traded volume during the analyzed period. This represents the "fairest" price where most traders agreed on value. The indicator marks this with distinct coloring (red in Traffic Light, magenta in Aurora Glass, white in Obsidian Precision, cyan in Black Ice).
Trading Significance: POC acts as a strong magnet for price - markets tend to return to fair value. When price is away from POC, traders watch for:
Mean reversion opportunities when price is far from POC
Rejection signals when price tests POC from above/below
Breakout confirmation when price breaks through and holds beyond POC
Value Area (VA)
The Value Area encompasses the price range where a specified percentage (default: 68%) of all volume traded. This represents the range of "accepted value" by market participants.
Calculation Method:
Start at the POC (highest volume level)
Expand upward and downward, adding adjacent price levels
Always add the level with higher volume next
Continue until accumulated volume reaches the VA percentage threshold
Value Area High (VAH): Upper boundary of accepted value - acts as resistance
Value Area Low (VAL): Lower boundary of accepted value - acts as support
Trading Significance:
Price spending time inside VA indicates market equilibrium
Breakouts above VAH suggest bullish momentum shift
Breakdowns below VAL suggest bearish momentum shift
Returns to VA boundaries often provide high-probability entry zones
High Volume Nodes (HVN)
Price levels with volume exceeding a threshold percentage (default: 80%) of POC volume. These represent areas of strong agreement and consolidation.
Trading Significance:
HVNs act as strong support/resistance zones
Price tends to consolidate at HVNs before making directional moves
Breaking through an HVN often signals strong momentum
Low Volume Nodes (LVN)
Price levels within the Value Area with volume ≤30% of POC volume. These are zones price moved through quickly with minimal consolidation.
Trading Significance:
LVNs represent areas of rejection - price finds little acceptance
Price tends to move rapidly through LVN zones
Useful for setting stop-losses (below LVN for longs, above for shorts)
Can identify potential gaps or "air pockets" in the market structure
Grayscale POC Detection
A secondary POC detection system identifies the highest volume level outside the Value Area (with a 2-level buffer to avoid confusion). This helps identify significant volume accumulation zones that exist beyond the main value area.
How to Use This Indicator
Setup
Choose Lookback Period:
Enable "Use Visible Range" to analyze only what's on your chart
Or set "Fixed Range Lookback Depth" (default: 200 bars) for consistent analysis
Adjust Profile Resolution:
"Number of Price Levels" (default: 80) - higher = more granular analysis, lower = broader zones
Select Color Scheme:
Traffic Light: Best for clear POC/VA/HVN identification
Aurora Glass: Modern aesthetic for dark charts
Obsidian Precision: Professional trader preference
Black Ice: Minimalist single-color family
Visual Customization
Left Extension: How far back the left-side histogram extends into historical candles (default: 490 bars)
Right Extension: Width of the traditional histogram bars on the right (default: 50 bars)
Right Margin: Space between current price bar and histogram (default: 0 for flush alignment)
Left Profile Gap: Space between left-side histogram and candles (default: 0)
Trading Strategies
Strategy 1: Value Area Mean Reversion
Wait for price to move outside the Value Area (above VAH or below VAL)
Look for rejection signals (wicks, bearish/bullish candles)
Enter trades toward the POC
Take profits as price returns to POC or opposite VA boundary
Strategy 2: Breakout Confirmation
Identify when price is consolidating within the Value Area
Wait for a strong close above VAH (bullish) or below VAL (bearish)
Enter on the breakout or on first pullback to the VA boundary
Target previous HVNs or swing highs/lows outside the VA
Strategy 3: POC Support/Resistance
Watch for price approaching the POC level
If approaching from below, look for bullish reversal patterns at POC (support)
If approaching from above, look for bearish reversal patterns at POC (resistance)
Trade in the direction of the bounce with stops beyond the POC
Strategy 4: LVN Fast Movement Zones
Identify LVN zones within the Value Area (marked with "LVN" label)
When price enters an LVN, expect rapid movement through the zone
Avoid entering trades within LVNs
Use LVNs as confirmation of directional momentum
Alert System
The indicator includes 7 customizable alert conditions:
POC Touch: Alerts when price comes within 0.5 ATR of POC
VAH/VAL Touch: Alerts at Value Area boundaries
VA Breakout: Alerts on breakouts above VAH or below VAL
HVN Touch: Alerts when price contacts High Volume Nodes
LVN Entry: Alerts when entering Low Volume zones
POC Shift: Alerts when POC moves to a new price level
Reading the Profile
Price Labels (shown on the right side):
POC: Point of Control - highest volume price level
VAH: Value Area High - upper boundary of accepted value
VAL: Value Area Low - lower boundary of accepted value
LVN: Low Volume Node - expect fast movement through this zone
Color Intensity Interpretation:
Brighter colors = higher volume concentration
Dimmer colors = lower volume
Abrupt color changes = transition between volume zones
Gaps in the histogram = price levels with no trading activity
Technical Details
Volume Accumulation Logic:
For each bar in lookback period:
For each price level:
If bar's high/low range intersects price level:
Add bar's volume to that price level's total
Gradient Algorithm:
Traffic Light: Dual-range piecewise gradient (0-50% and 50-100% volume intensity)
Aurora Glass: Linear cyan-to-magenta interpolation
Obsidian Precision: Dark blue gradient with cyan highlights
Black Ice: Three-stage cyan intensity progression
Real-Time Updates:
The profile recalculates on every bar, including real-time tick data, ensuring the volume distribution always reflects current market structure.
Best Practices
Timeframe Selection: Use higher timeframes (4H, Daily) for swing trading, lower timeframes (5min, 15min) for day trading
Combine with Price Action: Volume profile shows WHERE, price action shows WHEN
Multiple Timeframe Analysis: Check daily VP for major levels, then drill down to intraday for entries
Volume Type Selection: Use "Bullish" volume in uptrends, "Bearish" in downtrends, or "Both" for complete picture
Adjust VA Percentage: 68% (default) captures one standard deviation; try 70% for tighter or 60% for broader value areas
Performance Notes
Maximum bars back: 5000 (handles deep historical analysis)
Maximum boxes: 500 (handles complex profiles)
Optimized calculation: Only recalculates on last bar for efficiency
Real-time capable: Updates as new ticks arrive
Swing Trading IndicatorThis script is a swing‑trading dashboard designed for BTC, ETH, S&P 500 (for now). It combines weekly RSI, USDT.D, VIX, moving averages and Fisher Transform into a single visual tool, with background highlights, an on‑chart info table and ready‑made alerts to help you time high‑probability swing entries and manage risk.
1. Overview
The indicator is intended to work on daily timeframe.
Signals are context‑aware: BTC and ETH get USDT.D conditions, SPX gets VIX and EMA‑100 logic, and all non‑ETH symbols can also use Fisher Transform as a mean‑reversion filter.
2. Conditions and background highlights
Each component sets a boolean condition and, when active, paints a background layer:
Weekly RSI condition
True when weekly RSI is below its symbol‑specific threshold.
USDT.D conditions
BTC: triggered when USDT.D is above the user threshold and the chart symbol is BTC.
ETH: same logic for ETH, but tracked separately..
VIX condition (SPX only)
True when VIX high is at or above the VIX threshold while the chart is SPX.
EMA condition (BTC & SPX)
BTC: daily close below EMA‑200.
SPX: daily close below EMA‑100.
Fisher Transform condition (non‑ETH)
Fisher Transform on the chart timeframe, using the configured period.
True when Fisher value is below the Fisher threshold.
3. Intended use and notes
This indicator is designed as a confluence tool for swing traders, not a standalone buy/sell system. It works best on assets that are in a clear uptrend, where the main idea is to accumulate during corrections within that broader bullish structure.
During larger market shocks, deep corrections, or black‑swan events, trend‑based and mean‑reversion filters can produce false signals, because volatility and correlations often behave abnormally in those periods. For that reason, this script should always be combined with independent risk management, higher‑timeframe trend analysis, and your own discretion.
SMC N-Gram Probability Matrix [PhenLabs]📊 SMC N-Gram Probability Matrix
Version: PineScript™ v6
📌 Description
The SMC N-Gram Probability Matrix applies computational linguistics methodology to Smart Money Concepts trading. By treating SMC patterns as a discrete “alphabet” and analyzing their sequential relationships through N-gram modeling, this indicator calculates the statistical probability of which pattern will appear next based on historical transitions.
Traditional SMC analysis is reactive—traders identify patterns after they form and then anticipate the next move. This indicator inverts that approach by building a transition probability matrix from up to 5,000 bars of pattern history, enabling traders to see which SMC formations most frequently follow their current market sequence.
The indicator detects and classifies 11 distinct SMC patterns including Fair Value Gaps, Order Blocks, Liquidity Sweeps, Break of Structure, and Change of Character in both bullish and bearish variants, then tracks how these patterns transition from one to another over time.
🚀 Points of Innovation
First indicator to apply N-gram sequence modeling from computational linguistics to SMC pattern analysis
Dynamic transition matrix rebuilds every 50 bars for adaptive probability calculations
Supports bigram (2), trigram (3), and quadgram (4) sequence lengths for varying analysis depth
Priority-based pattern classification ensures higher-significance patterns (CHoCH, BOS) take precedence
Configurable minimum occurrence threshold filters out statistically insignificant predictions
Real-time probability visualization with graphical confidence bars
🔧 Core Components
Pattern Alphabet System: 11 discrete SMC patterns encoded as integers for efficient matrix indexing and transition tracking
Swing Point Detection: Uses ta.pivothigh/pivotlow with configurable sensitivity for non-repainting structure identification
Transition Count Matrix: Flattened array storing occurrence counts for all possible pattern sequence transitions
Context Encoder: Converts N-gram pattern sequences into unique integer IDs for matrix lookup
Probability Calculator: Transforms raw transition counts into percentage probabilities for each possible next pattern
🔥 Key Features
Multi-Pattern SMC Detection: Simultaneously identifies FVGs, Order Blocks, Liquidity Sweeps, BOS, and CHoCH formations
Adjustable N-Gram Length: Choose between 2-4 pattern sequences to balance specificity against sample size
Flexible Lookback Range: Analyze anywhere from 100 to 5,000 historical bars for matrix construction
Pattern Toggle Controls: Enable or disable individual SMC pattern types to customize analysis focus
Probability Threshold Filtering: Set minimum occurrence requirements to ensure prediction reliability
Alert Integration: Built-in alert conditions trigger when high-probability predictions emerge
🎨 Visualization
Probability Table: Displays current pattern, recent sequence, sample count, and top N predicted patterns with percentage probabilities
Graphical Probability Bars: Visual bar representation (█░) showing relative probability strength at a glance
Chart Pattern Markers: Color-coded labels placed directly on price bars identifying detected SMC formations
Pattern Short Codes: Compact notation (F+, F-, O+, O-, L↑, L↓, B+, B-, C+, C-) for quick pattern identification
Customizable Table Position: Place probability display in any corner of your chart
📖 Usage Guidelines
N-Gram Configuration
N-Gram Length: Default 2, Range 2-4. Lower values provide more samples but less specificity. Higher values capture complex sequences but require more historical data.
Matrix Lookback Bars: Default 500, Range 100-5000. More bars increase statistical significance but may include outdated market behavior.
Min Occurrences for Prediction: Default 2, Range 1-10. Higher values filter noise but may reduce prediction availability.
SMC Detection Settings
Swing Detection Length: Default 5, Range 2-20. Controls pivot sensitivity for structure analysis.
FVG Minimum Size: Default 0.1%, Range 0.01-2.0%. Filters insignificant gaps.
Order Block Lookback: Default 10, Range 3-30. Bars to search for OB formations.
Liquidity Sweep Threshold: Default 0.3%, Range 0.05-1.0%. Minimum wick extension beyond swing points.
Display Settings
Show Probability Table: Toggle the probability matrix display on/off.
Show Top N Probabilities: Default 5, Range 3-10. Number of predicted patterns to display.
Show SMC Markers: Toggle on-chart pattern labels.
✅ Best Use Cases
Anticipating continuation or reversal patterns after liquidity sweeps
Identifying high-probability BOS/CHoCH sequences for trend trading
Filtering FVG and Order Block signals based on historical follow-through rates
Building confluence by comparing predicted patterns with other technical analysis
Studying how SMC patterns typically sequence on specific instruments or timeframes
⚠️ Limitations
Predictions are based solely on historical pattern frequency and do not account for fundamental factors
Low sample counts produce unreliable probabilities—always check the Samples display
Market regime changes can invalidate historical transition patterns
The indicator requires sufficient historical data to build meaningful probability matrices
Pattern detection uses standardized parameters that may not capture all institutional activity
💡 What Makes This Unique
Linguistic Modeling Applied to Markets: Treats SMC patterns like words in a language, analyzing how they “flow” together
Quantified Pattern Relationships: Transforms subjective SMC analysis into objective probability percentages
Adaptive Learning: Matrix rebuilds periodically to incorporate recent pattern behavior
Comprehensive SMC Coverage: Tracks all major Smart Money Concepts in a unified probability framework
🔬 How It Works
1. Pattern Detection Phase
Each bar is analyzed for SMC formations using configurable detection parameters
A priority hierarchy assigns the most significant pattern when multiple detections occur
2. Sequence Encoding Phase
Detected patterns are stored in a rolling history buffer of recent classifications
The current N-gram context is encoded into a unique integer identifier
3. Matrix Construction Phase
Historical pattern sequences are iterated to count transition occurrences
Each context-to-next-pattern transition increments the appropriate matrix cell
4. Probability Calculation Phase
Current context ID retrieves corresponding transition counts from the matrix
Raw counts are converted to percentages based on total context occurrences
5. Visualization Phase
Probabilities are sorted and the top N predictions are displayed in the table
Chart markers identify the current detected pattern for visual reference
💡 Note:
This indicator performs best when used as a confluence tool alongside traditional SMC analysis. The probability predictions highlight statistically common pattern sequences but should not be used as standalone trading signals. Always verify predictions against price action context, higher timeframe structure, and your overall trading plan. Monitor the sample count to ensure predictions are based on adequate historical data.
VWAP-Anchored MACD [BOSWaves]VWAP-Anchored MACD - Volume-Weighted Momentum Mapping With Zero-Line Filtering
Overview
The VWAP-Anchored MACD delivers a refined momentum model built on volume-weighted price rather than raw closes, giving you a more grounded view of trend strength during sessions, weeks, or months.
Instead of tracking two EMAs of price like a standard MACD, this tool reconstructs the MACD engine using anchored VWAP as the core input. The result is a momentum structure that reacts to real liquidity flow, filters out weak crossovers near the zero line, and visualizes acceleration shifts with clear, high-contrast gradients.
This indicator acts as a precise momentum map that adapts in real time. You see how weighted price is accelerating, where valid crossovers form, and when trend conviction is strong enough to justify execution.
It uses gradient line coloring to show bullish or bearish momentum, histogram shading to highlight energy shifts, cross dots to mark valid crossovers, optional buy/sell diamonds for execution cues, and candle coloring to display trend strength at a glance.
Theoretical Foundation
Traditional MACD compares the difference between two exponential moving averages of price.
This variant replaces price with anchored VWAP, making the calculation sensitive to actual traded volume across your chosen period (Session, Week, or Month).
Three principles drive the logic:
Anchored VWAP Momentum : Price is weighted by volume and aggregated across the selected anchor. The fast and slow VWAP-EMAs then expose how liquidity-corrected momentum is expanding or contracting.
Zero-Line Distance Filtering : Crossover signals that occur too close to the zero line are removed. This eliminates the common MACD problem of generating weak, directionless signals in choppy phases.
Directional Visualization : MACD line, signal line, histogram, candle colors, and optional diamond markers all react to shifts in VWAP-momentum, giving you a clean structural read on market pressure.
Anchoring VWAP to session, weekly, or monthly resets creates a systematic framework for tracking how capital flow is driving momentum throughout each trading cycle.
How It Works
The core engine processes momentum through several mapped layers:
VWAP Aggregation : Price × volume is accumulated until the anchor resets. This creates a continuous, liquidity-corrected VWAP curve.
MACD Construction : Fast and slow VWAP-EMAs define the MACD line, while a smoothed signal line identifies edges where momentum shifts.
Zero-Line Distance Filter : MACD and signal must both exceed a threshold distance from zero for a crossover to count as valid. This prevents fake crossovers during compression.
Visual Momentum Layers : It uses gradient line coloring to show bullish or bearish momentum, histogram shading to highlight energy shifts, cross dots to mark valid crossovers, optional buy/sell diamonds for execution cues, and candle coloring to display trend strength at a glance.
This layered structure ensures you always know whether momentum is strengthening, fading, or transitioning.
Interpretation
You get a clean, structural understanding of VWAP-based momentum:
Bullish Phases : MACD > Signal, histogram expands, candles turn bullish, and crossovers occur above the threshold.
Bearish Phases : MACD < Signal, histogram drives lower, candles shift bearish, and downward crossovers trigger below the threshold.
Neutral/Compression : Both lines remain near the zero boundary, histogram flattens, and signals are suppressed to avoid noise.
This creates a more disciplined version of MACD momentum reading - less noise, more conviction, and better alignment with liquidity.
Strategy Integration
Trend Continuation : Use VWAP-MACD crossovers that occur far from the zero line as higher-conviction entries.
Zero-Line Rejection : Watch for histogram contractions near zero to anticipate flattening momentum and potential reversal setups.
Session/Week/Month Anchors : Session anchor works best for intraday flows. Weekly or monthly anchor structures create cleaner macro momentum reads for swing trading.
Signal-Only Execution : Optional buy/sell diamonds give you direct points to trigger trades without overanalyzing the chart.
This indicator slots cleanly into any momentum-following system and offers higher signal quality than classic MACD variants due to the volume-weighted core.
Technical Implementation Details
VWAP Reset Logic : Session (D), Week (W), or Month (M)
Dynamic Fast/Slow VWAP EMAs : Fully configurable lengths, smoothing and anchor settings
MACD/Signal Line Framework : Traditional structure with volume-anchored input
Zero-Line Filtering : Adjustable threshold for structural confirmation
Dual Visualization Layers : MACD body + histogram + crosses + candle coloring
Optimized Performance : Lightweight, fast rendering across all timeframes
Optimal Application Parameters
Timeframes:
1- 15 min : Short-term momentum scalping and rapid trend shifts
30- 240 min : Balanced momentum mapping with clear structural filtering
Daily : Macro VWAP regime identification
Suggested Configuration:
Fast Length : 12
Slow Length : 26
Signal Length : 9
Zero Threshold : 200 - 500 depending on asset range
These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance.
Performance Characteristics
High Effectiveness:
Assets with strong intraday or session-based volume cycles
Markets where volume-weighted momentum leads price swings
Trend environments with strong acceleration
Reduced Effectiveness:
Ultra-choppy markets hugging the VWAP axis
Sessions with abnormally low volume
Ranges where MACD naturally compresses
Disclaimer
The VWAP-Anchored MACD is a structural momentum tool designed to enhance directional clarity - not a guaranteed predictor. Performance depends on market regime, volatility, and disciplined execution. Use it alongside broader trend, volume, and structural analysis for optimal results.
ShooterViz Lazy Trader EMA SystemShooterViz Lazy Trader EMA System - Complete User Guide
What This Script Does
This is a position scaling indicator that tells you exactly when to enter, add to, and exit trades using a simplified 5-EMA system. It removes the guesswork and decision fatigue from trading by giving you clear visual signals.
The Core Concept
3 entry signals that build your position from 20% → 50% → 100%
2 exit signals that scale you out at 50% → 50% (complete exit)
1 higher timeframe filter that keeps you on the right side of the trend
No Fibonacci calculations, no RSI divergence, no multi-indicator confusion. Just EMAs and price action.
What You'll See On Your Chart
1. Colored EMA Lines
Blue Lines (Entry Zone):
3 EMA (lightest blue) - Early reversal detector
5 EMA (darker blue) - Confirmation line
Green Lines (Add Zone):
21 EMA (bright green) - First add location
34 EMA (lighter green) - Final add location
Red Lines (Exit Zone):
89 EMA (lighter red) - First exit trigger
144 EMA (darker red) - Final exit trigger
Orange Lines (Hyper Frame - optional):
Hyper 21 EMA (from higher timeframe) - Trend direction
Hyper 34 EMA (from higher timeframe) - Bias confirmation
2. Triangle Signals
Green Triangles (Below Price) = BUY/ADD:
Lime triangle with "20%" = Entry 1: Price reclaimed 3→5 EMA (starter position)
Green triangle with "30%" = Entry 2: Price bounced off 21 EMA (first add)
Teal triangle with "50%" = Entry 3: Price broke out from 34 EMA compression (final add)
Red Triangles (Above Price) = SELL:
Orange triangle with "50% OFF" = Exit 1: Price broke below 89 EMA (take half off)
Red triangle with "EXIT ALL" = Exit 2: Price broke below 144 EMA (close remaining position)
3. Background Color (Trend Bias)
Light green background = Hyper frame EMAs trending up (bias LONG)
Light red background = Hyper frame EMAs trending down (bias SHORT)
Gray background = Neutral/choppy (be cautious)
4. Info Table (Top Right Corner)
A live status dashboard showing:
Which entry signals are currently active (✓ or —)
Which exit signals are currently active (⚠ or ⛔)
Current hyper frame bias (🟢 LONG / 🔴 SHORT / ⚪ NEUTRAL)
Which timeframe you're using for hyper frame filtering
How to Install and Set Up
Step 1: Add the Script to TradingView
Open TradingView
Click "Pine Editor" at the bottom of the screen
Copy the entire script code
Paste it into the Pine Editor
Click "Add to Chart"
Step 2: Configure Your Settings
Click the gear icon ⚙️ next to "LazyEMA" in your indicators list.
Critical Settings to Configure:
Hyper Frame Selection (Most Important!)
Location: "Hyper Frame (Pick ONE)" section
Setting: "Timeframe"
What to choose:
Trading 15min or 1H charts? → Use "240" (4-hour)
Trading 4H or Daily charts? → Use "D" (Daily)
Trading Daily or Weekly charts? → Use "W" (Weekly)
Why this matters: This filter keeps you aligned with the bigger trend. Only take longs when this timeframe is green, shorts when it's red.
MA Type (Optional, default is fine)
Location: "MA Config" section
Default: EMA (recommended)
Options: EMA, SMA, WMA, HMA, RMA, VWMA
Most traders should stick with EMA
Visual Toggles (Customize your view)
Entry Zone: Turn individual EMAs on/off (3, 5, 21, 34)
Exit Zone: Turn individual EMAs on/off (89, 144)
Hyper Frame: Toggle the higher timeframe EMAs on/off
Step 3: Clean Up Your Chart
Turn OFF these if visible:
Volume bars (they clutter the view)
Any other indicators you have loaded
Grid lines (optional, but cleaner)
Keep ONLY:
Price candles
Your ShooterViz Lazy Trader EMA System
Maybe support/resistance levels if you manually draw them
How to Trade With This Script
The Basic Workflow
Before the Market Opens:
Check the background color and info table bias
Green background? Look for LONG setups only
Red background? Look for SHORT setups only
Gray background? Stay flat or trade small
During the Trading Session:
LONGS (When hyper frame is bullish):
Wait for Entry 1 signal:
Lime triangle appears with "20%"
Price has reclaimed the 5 EMA after dipping to 3 EMA
Action: Enter 20% of your intended position
Stop loss: Place below the 5 EMA or recent swing low
Wait for Entry 2 signal:
Green triangle appears with "30%"
Price pulled back to 21 EMA and bounced
Action: Add 30% more (you're now at 50% total)
Move stop: Trail it up to below 21 EMA
Wait for Entry 3 signal:
Teal triangle appears with "50%"
Price compressed at 34 EMA and broke out
Action: Add final 50% (you're now 100% loaded)
Move stop: Trail it up to below 34 EMA
Wait for Exit 1 signal:
Orange triangle appears with "50% OFF"
Price broke below 89 EMA
Action: Exit 50% of your position immediately
Move stop on rest: Trail to 89 EMA or lock in profits
Wait for Exit 2 signal:
Red triangle appears with "EXIT ALL"
Price broke below 144 EMA
Action: Exit remaining 50% (you're now flat)
Or: Stop gets hit at 89 EMA (same result)
SHORTS (When hyper frame is bearish):
Same process, but inverted
Triangles appear above price instead of below
Look for breakdowns below EMAs instead of bounces off them
Exit when price reclaims 89 and 144 EMAs
Real-World Example Walkthrough
Setup: Trading ES (S&P 500 Futures) on 1H Chart
Chart Configuration:
Timeframe: 1 Hour
Hyper Frame: 240 (4-hour)
Ticker: ES
Pre-Market Check:
Background is light green
Info table shows "🟢 LONG" for Hyper Bias
Decision: Only look for long entries today
9:30 AM - Market Opens
Price dips and touches 3 EMA
Watch for: Reclaim of 5 EMA
9:45 AM - Entry 1 Triggers
Lime triangle appears below bar
Price closed above 5 EMA at $4,550
Action taken:
Enter long 20% position (2 contracts if targeting 10 total)
Stop loss at $4,545 (below 5 EMA)
Risk: $10 per contract × 2 = $20 risk
10:30 AM - Entry 2 Triggers
Price rallied to $4,565, pulls back
Green triangle appears at 21 EMA ($4,555)
Action taken:
Add 30% (3 more contracts, now have 5 total)
Move stop to $4,550 (below 21 EMA)
Current P/L: +$25 ($5 gain on original 2 contracts, break-even on new 3)
11:15 AM - Entry 3 Triggers
Price consolidates at 34 EMA around $4,560
Teal triangle appears as price breaks to $4,568
Action taken:
Add final 50% (5 more contracts, now have 10 total)
Move stop to $4,555 (below 34 EMA)
Current P/L: +$70
1:00 PM - Price Extends
Price rallies to $4,595 (on track)
89 EMA is at $4,575
No action yet, let it run
2:15 PM - Exit 1 Triggers
Price pulls back from $4,600
Orange triangle appears as price breaks below 89 EMA at $4,580
Action taken:
Exit 50% (5 contracts closed at $4,580)
Keep 5 contracts with stop at 89 EMA ($4,575)
Banked: +$150 average gain on closed 5 contracts
2:45 PM - Exit 2 Triggers
Price continues down
Red triangle appears as price breaks 144 EMA at $4,570
Action taken:
Exit remaining 5 contracts at $4,570
Banked: +$100 on remaining 5 contracts
Final Results:
Total gain: $250 on the trade
Initial risk: $50 (if stopped out at Entry 1)
Risk/Reward: 5:1
Time in trade: ~5 hours
Common Questions
"What if I miss Entry 1? Can I still take Entry 2?"
Yes! Each entry is independent. If you miss the 3→5 reclaim, wait for the 21 EMA bounce. You'll start with a 30% position instead of 20%, but that's fine.
Rule: Never chase. Wait for the next EMA setup.
"What if multiple entry signals trigger at the same bar?"
Rare, but possible. If you see both Entry 1 and Entry 2 trigger together:
Take Entry 1 first (20%)
If the next bar confirms Entry 2 is still valid, add 30%
When in doubt, scale in gradually
"The hyper frame is green but I'm seeing short signals?"
Don't take them. The hyper frame is your bias filter. If it says "go long," ignore short setups. They're usually lower probability and will get stopped out.
"Can I use this for swing trading overnight?"
Absolutely. Just switch your hyper frame:
If you're on Daily charts, use Weekly hyper frame
If you're on 4H charts, use Daily hyper frame
Adjust position sizes for overnight risk
"What if the signal appears right at market close?"
Don't chase it. Wait for the next bar (next day) to confirm. Signals that appear in the last 5 minutes are often noise.
"How do I set up alerts?"
Right-click on the chart
Select "Add Alert"
Choose "LazyEMA" from the condition dropdown
Select which signal you want alerts for:
Entry 1: 3→5 Reclaim
Entry 2: 21 EMA Add
Entry 3: 34 EMA Breakout
Exit 1: 89 EMA Break
Exit 2: 144 EMA Break
Click "Create"
Pro tip: Set up all 5 alerts so you never miss a signal.
Position Sizing Guide see
swingtradenotes.substack.com
Critical Rule: Know your total risk BEFORE you take Entry 1. Don't wing it.
Customization Tips
For Day Traders (Scalpers)
Use 5min or 15min charts
Hyper frame: 1H or 4H
Expect 2-4 setups per day
Tighter stops (0.5% risk per entry)
For Swing Traders
Use 4H or Daily charts
Hyper frame: Daily or Weekly
Expect 1-2 setups per week
Wider stops (1-2% risk per entry)
For Position Traders
Use Daily or Weekly charts
Hyper frame: Weekly or Monthly
Expect 1-2 setups per month
Widest stops (2-3% risk per entry)
The "Don't Be Stupid" Checklist
Before taking ANY signal from this script, ask:
✅ Is the hyper frame bias pointing in my direction?
✅ Is the signal clean (not at a weird time or during news)?
✅ Do I know my stop loss level?
✅ Do I know my position size?
✅ Can I afford to lose if this trade fails?
If you answered "no" to ANY of these, skip the trade.
Troubleshooting
"I'm not seeing any signals"
Possible causes:
The "Show Lazy Trader System" toggle is off (turn it on)
Your chart timeframe is too high (try 1H or 4H)
Market is in a tight range (EMAs are compressed)
You need to refresh the chart
"Too many signals, getting whipsawed"
Fixes:
Increase your chart timeframe (go from 15m to 1H)
Switch to a less volatile ticker
Only trade when hyper frame bias is STRONG (not neutral)
Add a minimum bar count between signals
"The info table is covering my price action"
Fix:
Edit the script
Find the line: table.new(position.top_right, ...
Change position.top_right to position.bottom_right or position.top_left
"Signals appear then disappear"
This is normal (repainting). Some signals (especially compression breakouts) can disappear if the next bar reverses. This is why you:
Wait for bar close before acting
Use alerts that only fire on confirmed bars
Don't chase signals mid-bar
Final Thoughts
This script is a decision-making tool, not a crystal ball. It shows you high-probability setups based on EMA dynamics and trend structure. You still need to:
Manage your risk
Choose your position size
Stick to the rules
Accept losses when they happen
The system works when YOU work the system.
Print this guide, tape it next to your monitor, and follow it religiously for 20 trades before making ANY changes.
Good luck, and stay lazy (the smart way).
RV − IV Spread Alert (SPY vs VIX)Realized vs Implied Volatility Spread (RV − IV) for the S&P 500 / SPY.
Plots the daily difference between 30-day realized volatility (SPY) and implied volatility (VIX) in basis points.
Key insight from the research: when the spread turns and stays above ≈ +50 bps, forward returns historically degrade and volatility of returns rises sharply — a useful early-warning regime flag.
Features:
- Clean daily plot of RV − IV in bps
- Horizontal lines at 0, −50 bps and +50 bps
- Red background when spread > +50 bps
- Built-in alert condition that fires once per bar close when spread closes above +50 bps
- Optional “all-clear” alert when it drops back below
Use on SPY or ES1! daily chart. Perfect for anyone wanting a simple notification when the market enters the “risk-on” volatility regime highlighted by Machina Quanta and the original Bali & Hovakimian (2007) paper.
Reversal WaveThis is the type of quantitative system that can get you hated on investment forums, now that the Random Walk Theory is back in fashion. The strategy has simple price action rules, zero over-optimization, and is validated by a historical record of nearly a century on both Gold and the S&P 500 index.
Recommended Markets
SPX (Weekly, Monthly)
SPY (Monthly)
Tesla (Weekly)
XAUUSD (Weekly, Monthly)
NVDA (Weekly, Monthly)
Meta (Weekly, Monthly)
GOOG (Weekly, Monthly)
MSFT (Weekly, Monthly)
AAPL (Weekly, Monthly)
System Rules and Parameters
Total capital: $10,000
We will use 10% of the total capital per trade
Commissions will be 0.1% per trade
Condition 1: Previous Bearish Candle (isPrevBearish) (the closing price was lower than the opening price).
Condition 2: Midpoint of the Body The script calculates the exact midpoint of the body of that previous bearish candle.
• Formula: (Previous Open + Previous Close) / 2.
Condition 3: 50% Recovery (longCondition) The current candle must be bullish (green) and, most importantly, its closing price must be above the midpoint calculated in the previous step.
Once these parameters are met, the system executes a long entry and calculates the exit parameters:
Stop Loss (SL): Placed at the low of the candle that generated the entry signal.
Take Profit (TP): Calculated by projecting the risk distance upward.
• Calculation: Entry Price + (Risk * 1).
Risk:Reward Ratio of 1:1.
About the Profit Factor
In my experience, TradingView calculates profits and losses based on the percentage of movement, which can cause returns to not match expectations. This doesn’t significantly affect trending systems, but it can impact systems with a high win rate and a well-defined risk-reward ratio. It only takes one large entry candle that triggers the SL to translate into a major drop in performance.
For example, you might see a system with a 60% win rate and a 1:1 risk-reward ratio generating losses, even though commissions are under control relative to the number of trades.
My recommendation is to manually calculate the performance of systems with a well-defined risk-reward ratio, assuming you will trade using a fixed amount per trade and limit losses to a fixed percentage.
Remember that, even if candles are larger or smaller in size, we can maintain a fixed loss percentage by using leverage (in cases of low volatility) or reducing the capital at risk (when volatility is high).
Implementing leverage or capital reduction based on volatility is something I haven’t been able to incorporate into the code, but it would undoubtedly improve the system’s performance dramatically, as it would fix a consistent loss percentage per trade, preventing losses from fluctuating with volatility swings.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to exit or SL
And if volatility is high and exceeds the fixed percentage we want to expose per trade (if SL is hit), we could reduce the position size.
For example, imagine we only want to risk 15% per SL on Tesla, where volatility is high and would cause a 23.57% loss. In this case, we subtract 23.57% from 15% (the loss percentage we’re willing to accept per trade), then subtract the result from our usual position size.
23.57% - 15% = 8.57%
Suppose I use $200 per trade.
To calculate 8.57% of $200, simply multiply 200 by 8.57/100. This simple calculation shows that 8.57% equals about $17.14 of the $200. Then subtract that value from $200:
$200 - $17.14 = $182.86
In summary, if we reduced the position size to $182.86 (from the usual $200, where we’re willing to lose 15%), no matter whether Tesla moves up or down 23.57%, we would still only gain or lose 15% of the $200, thus respecting our risk management.
Final Notes
The code is extremely simple, and every step of its development is detailed within it.
If you liked this strategy, which complements very well with others I’ve already published, stay tuned. Best regards.
MeanReversion_tradeALERTOverview The Apex Reversal Predictor v2.5 is a specialized mean reversion strategy designed for scalping high-volatility assets like NQ (Nasdaq), ES (S&P 500), and Crypto. While most indicators chase breakouts, this system hunts for "Liquidity Sweeps"—moments where the market briefly breaks a key level to trap retail traders before snapping back to the true value (VWAP).
This is not just a signal indicator; it is a full Trade Manager that calculates your Entry, Stop Loss, and Take Profit levels automatically based on volatility (ATR).
The Logic: Why This Works Markets act like a rubber band. They can only stretch so far from their average price before snapping back. This script combines three layers of logic to identify these snap-back points:
The Stretch (Sigma Score): Measures how far price is from the VWAP relative to ATR. If the score > 2.0, the "rubber band" is overextended.
The Trap (Liquidity Sweep): Identifies Pivot Highs/Lows. It waits for price to break a pivot (luring in breakout traders) and then immediately reverse (trapping them).
The Exhaustion (RSI): Confirms that momentum is Overbought/Oversold to prevent trading against a strong trend.
Key Features
Dynamic Lines: Automatically draws Blue (Entry), Red (SL), and Green (TP) lines on the chart for active trades.
Smart Targets: Two modes for taking profit:
Mean Reversion: Targets the VWAP line (High Win Rate).
Fixed Ratio: Targets a specific Risk:Reward (e.g., 1:2).
Live Dashboard: Tracks Win Rate, Net Points, and the live "Stretch Score" in the bottom right corner.
Alert Ready: Formatted JSON alerts for easy integration with Discord or trading bots.
How & When to Use (User Guide)
1. Best Timeframes
5-Minute (5m): Best for NQ and volatile stocks (TSLA, NVDA). Filters out 1-minute noise but catches the intraday reversals.
15-Minute (15m): Best for Forex or slower-moving indices (ES).
2. The Setup Checklist Before taking a trade, look at the Dashboard in the bottom right:
Step 1: Check the "Stretch (Sigma)". Is it Orange or Red? This means price is extended and ripe for a reversal. If it's Green, the market is calm—be careful.
Step 2: Wait for the Signal.
"Apex BUY" (Green Label): Price swept a low and closed green.
"Apex SELL" (Red Label): Price swept a high and closed red.
Step 3: Execute. Enter at the close of the signal candle. Set your stop loss at the Red Line provided by the script.
3. Warning / When NOT to Use
Strong Trending Days: If the market is trending heavily (e.g., creating higher highs all day without looking back), do not fight the trend.
News Events: Avoid using this during CPI, FOMC, or NFP releases. The "rubber band" logic breaks during news because volatility expands indefinitely.
Volatility Risk PremiumTHE INSURANCE PREMIUM OF THE STOCK MARKET
Every day, millions of investors face a fundamental question that has puzzled economists for decades: how much should protection against market crashes cost? The answer lies in a phenomenon called the Volatility Risk Premium, and understanding it may fundamentally change how you interpret market conditions.
Think of the stock market like a neighborhood where homeowners buy insurance against fire. The insurance company charges premiums based on their estimates of fire risk. But here is the interesting part: insurance companies systematically charge more than the actual expected losses. This difference between what people pay and what actually happens is the insurance premium. The same principle operates in financial markets, but instead of fire insurance, investors buy protection against market volatility through options contracts.
The Volatility Risk Premium, or VRP, measures exactly this difference. It represents the gap between what the market expects volatility to be (implied volatility, as reflected in options prices) and what volatility actually turns out to be (realized volatility, calculated from actual price movements). This indicator quantifies that gap and transforms it into actionable intelligence.
THE FOUNDATION
The academic study of volatility risk premiums began gaining serious traction in the early 2000s, though the phenomenon itself had been observed by practitioners for much longer. Three research papers form the backbone of this indicator's methodology.
Peter Carr and Liuren Wu published their seminal work "Variance Risk Premiums" in the Review of Financial Studies in 2009. Their research established that variance risk premiums exist across virtually all asset classes and persist over time. They documented that on average, implied volatility exceeds realized volatility by approximately three to four percentage points annualized. This is not a small number. It means that sellers of volatility insurance have historically collected a substantial premium for bearing this risk.
Tim Bollerslev, George Tauchen, and Hao Zhou extended this research in their 2009 paper "Expected Stock Returns and Variance Risk Premia," also published in the Review of Financial Studies. Their critical contribution was demonstrating that the VRP is a statistically significant predictor of future equity returns. When the VRP is high, meaning investors are paying substantial premiums for protection, future stock returns tend to be positive. When the VRP collapses or turns negative, it often signals that realized volatility has spiked above expectations, typically during market stress periods.
Gurdip Bakshi and Nikunj Kapadia provided additional theoretical grounding in their 2003 paper "Delta-Hedged Gains and the Negative Market Volatility Risk Premium." They demonstrated through careful empirical analysis why volatility sellers are compensated: the risk is not diversifiable and tends to materialize precisely when investors can least afford losses.
HOW THE INDICATOR CALCULATES VOLATILITY
The calculation begins with two separate measurements that must be compared: implied volatility and realized volatility.
For implied volatility, the indicator uses the CBOE Volatility Index, commonly known as the VIX. The VIX represents the market's expectation of 30-day forward volatility on the S&P 500, calculated from a weighted average of out-of-the-money put and call options. It is often called the "fear gauge" because it rises when investors rush to buy protective options.
Realized volatility requires more careful consideration. The indicator offers three distinct calculation methods, each with specific advantages rooted in academic literature.
The Close-to-Close method is the most straightforward approach. It calculates the standard deviation of logarithmic daily returns over a specified lookback period, then annualizes this figure by multiplying by the square root of 252, the approximate number of trading days in a year. This method is intuitive and widely used, but it only captures information from closing prices and ignores intraday price movements.
The Parkinson estimator, developed by Michael Parkinson in 1980, improves efficiency by incorporating high and low prices. The mathematical formula calculates variance as the sum of squared log ratios of daily highs to lows, divided by four times the natural logarithm of two, times the number of observations. This estimator is theoretically about five times more efficient than the close-to-close method because high and low prices contain additional information about the volatility process.
The Garman-Klass estimator, published by Mark Garman and Michael Klass in 1980, goes further by incorporating opening, high, low, and closing prices. The formula combines half the squared log ratio of high to low prices minus a factor involving the log ratio of close to open. This method achieves the minimum variance among estimators using only these four price points, making it particularly valuable for markets where intraday information is meaningful.
THE CORE VRP CALCULATION
Once both volatility measures are obtained, the VRP calculation is straightforward: subtract realized volatility from implied volatility. A positive result means the market is paying a premium for volatility insurance. A negative result means realized volatility has exceeded expectations, typically indicating market stress.
The raw VRP signal receives slight smoothing through an exponential moving average to reduce noise while preserving responsiveness. The default smoothing period of five days balances signal clarity against lag.
INTERPRETING THE REGIMES
The indicator classifies market conditions into five distinct regimes based on VRP levels.
The EXTREME regime occurs when VRP exceeds ten percentage points. This represents an unusual situation where the gap between implied and realized volatility is historically wide. Markets are pricing in significantly more fear than is materializing. Research suggests this often precedes positive equity returns as the premium normalizes.
The HIGH regime, between five and ten percentage points, indicates elevated risk aversion. Investors are paying above-average premiums for protection. This often occurs after market corrections when fear remains elevated but realized volatility has begun subsiding.
The NORMAL regime covers VRP between zero and five percentage points. This represents the long-term average state of markets where implied volatility modestly exceeds realized volatility. The insurance premium is being collected at typical rates.
The LOW regime, between negative two and zero percentage points, suggests either unusual complacency or that realized volatility is catching up to implied volatility. The premium is shrinking, which can precede either calm continuation or increased stress.
The NEGATIVE regime occurs when realized volatility exceeds implied volatility. This is relatively rare and typically indicates active market stress. Options were priced for less volatility than actually occurred, meaning volatility sellers are experiencing losses. Historically, deeply negative VRP readings have often coincided with market bottoms, though timing the reversal remains challenging.
TERM STRUCTURE ANALYSIS
Beyond the basic VRP calculation, sophisticated market participants analyze how volatility behaves across different time horizons. The indicator calculates VRP using both short-term (default ten days) and long-term (default sixty days) realized volatility windows.
Under normal market conditions, short-term realized volatility tends to be lower than long-term realized volatility. This produces what traders call contango in the term structure, analogous to futures markets where later delivery dates trade at premiums. The RV Slope metric quantifies this relationship.
When markets enter stress periods, the term structure often inverts. Short-term realized volatility spikes above long-term realized volatility as markets experience immediate turmoil. This backwardation condition serves as an early warning signal that current volatility is elevated relative to historical norms.
The academic foundation for term structure analysis comes from Scott Mixon's 2007 paper "The Implied Volatility Term Structure" in the Journal of Derivatives, which documented the predictive power of term structure dynamics.
MEAN REVERSION CHARACTERISTICS
One of the most practically useful properties of the VRP is its tendency to mean-revert. Extreme readings, whether high or low, tend to normalize over time. This creates opportunities for systematic trading strategies.
The indicator tracks VRP in statistical terms by calculating its Z-score relative to the trailing one-year distribution. A Z-score above two indicates that current VRP is more than two standard deviations above its mean, a statistically unusual condition. Similarly, a Z-score below negative two indicates VRP is unusually low.
Mean reversion signals trigger when VRP reaches extreme Z-score levels and then shows initial signs of reversal. A buy signal occurs when VRP recovers from oversold conditions (Z-score below negative two and rising), suggesting that the period of elevated realized volatility may be ending. A sell signal occurs when VRP contracts from overbought conditions (Z-score above two and falling), suggesting the fear premium may be excessive and due for normalization.
These signals should not be interpreted as standalone trading recommendations. They indicate probabilistic conditions based on historical patterns. Market context and other factors always matter.
MOMENTUM ANALYSIS
The rate of change in VRP carries its own information content. Rapidly rising VRP suggests fear is building faster than volatility is materializing, often seen in the early stages of corrections before realized volatility catches up. Rapidly falling VRP indicates either calming conditions or rising realized volatility eating into the premium.
The indicator tracks VRP momentum as the difference between current VRP and VRP from a specified number of bars ago. Positive momentum with positive acceleration suggests strengthening risk aversion. Negative momentum with negative acceleration suggests intensifying stress or rapid normalization from elevated levels.
PRACTICAL APPLICATION
For equity investors, the VRP provides context for risk management decisions. High VRP environments historically favor equity exposure because the market is pricing in more pessimism than typically materializes. Low or negative VRP environments suggest either reducing exposure or hedging, as markets may be underpricing risk.
For options traders, understanding VRP is fundamental to strategy selection. Strategies that sell volatility, such as covered calls, cash-secured puts, or iron condors, tend to profit when VRP is elevated and compress toward its mean. Strategies that buy volatility tend to profit when VRP is low and risk materializes.
For systematic traders, VRP provides a regime filter for other strategies. Momentum strategies may benefit from different parameters in high versus low VRP environments. Mean reversion strategies in VRP itself can form the basis of a complete trading system.
LIMITATIONS AND CONSIDERATIONS
No indicator provides perfect foresight, and the VRP is no exception. Several limitations deserve attention.
The VRP measures a relationship between two estimates, each subject to measurement error. The VIX represents expectations that may prove incorrect. Realized volatility calculations depend on the chosen method and lookback period.
Mean reversion tendencies hold over longer time horizons but provide limited guidance for short-term timing. VRP can remain extreme for extended periods, and mean reversion signals can generate losses if the extremity persists or intensifies.
The indicator is calibrated for equity markets, specifically the S&P 500. Application to other asset classes requires recalibration of thresholds and potentially different data sources.
Historical relationships between VRP and subsequent returns, while statistically robust, do not guarantee future performance. Structural changes in markets, options pricing, or investor behavior could alter these dynamics.
STATISTICAL OUTPUTS
The indicator presents comprehensive statistics including current VRP level, implied volatility from VIX, realized volatility from the selected method, current regime classification, number of bars in the current regime, percentile ranking over the lookback period, Z-score relative to recent history, mean VRP over the lookback period, realized volatility term structure slope, VRP momentum, mean reversion signal status, and overall market bias interpretation.
Color coding throughout the indicator provides immediate visual interpretation. Green tones indicate elevated VRP associated with fear and potential opportunity. Red tones indicate compressed or negative VRP associated with complacency or active stress. Neutral tones indicate normal market conditions.
ALERT CONDITIONS
The indicator provides alerts for regime transitions, extreme statistical readings, term structure inversions, mean reversion signals, and momentum shifts. These can be configured through the TradingView alert system for real-time monitoring across multiple timeframes.
REFERENCES
Bakshi, G., and Kapadia, N. (2003). Delta-Hedged Gains and the Negative Market Volatility Risk Premium. Review of Financial Studies, 16(2), 527-566.
Bollerslev, T., Tauchen, G., and Zhou, H. (2009). Expected Stock Returns and Variance Risk Premia. Review of Financial Studies, 22(11), 4463-4492.
Carr, P., and Wu, L. (2009). Variance Risk Premiums. Review of Financial Studies, 22(3), 1311-1341.
Garman, M. B., and Klass, M. J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53(1), 67-78.
Mixon, S. (2007). The Implied Volatility Term Structure of Stock Index Options. Journal of Empirical Finance, 14(3), 333-354.
Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53(1), 61-65.
Relative Strength Line by QuantxThe Relative Strength Line compares the price performance of a stock against a benchmark index (e.g., NIFTY, S&P 500, Bank Nifty, etc.).
It does not indicate momentum of the stock itself — it indicates whether the stock is outperforming or underperforming the market.
🔍 How To Read It
RSL Behavior Meaning
RSL moving up Stock is outperforming the benchmark (strong leadership)
RSL moving down Stock is underperforming the benchmark (weakness vs market)
RSL breaking above previous highs Strong institutional demand, leadership candidate
RSL trending sideways Stock is performing similar to the index (no leadership)
📈 Why It Matters
Institutional traders and top-performing strategies focus on stocks showing relative strength BEFORE price breakout.
A stock making new RSL highs even before a price breakout often becomes a top performer in the coming trend.
🧠 Core Trading Edge
You don’t need to predict the market.
Just identify which stocks are being accumulated and leading the market right now — that’s what the Relative Strength Line reveals.
Liquidation Heatmap [Alpha Extract]A sophisticated liquidity zone visualization system that identifies and maps potential liquidation levels based on swing point analysis with volume-weighted intensity measurement and gradient heatmap coloring. Utilizing pivot-based pocket detection and ATR-scaled zone heights, this indicator delivers institutional-grade liquidity mapping with dynamic color intensity reflecting relative liquidity concentration. The system's dual-swing detection architecture combined with configurable weight metrics creates comprehensive liquidation level identification suitable for strategic position planning and market structure analysis.
🔶 Advanced Pivot-Based Pocket Detection
Implements dual swing width analysis to identify potential liquidation zones at pivot highs and lows with configurable lookback periods for comprehensive level coverage. The system detects primary swing points using main pivot width and optional secondary swing detection for increased pocket density, creating layered liquidity maps that capture both major and minor liquidation levels across extended price history.
🔶 Multi-Metric Weight Calculation Engine
Features flexible weight source selection including Volume, Range (high-low spread), and Volume × Range composite metrics for liquidity intensity measurement. The system calculates pocket weights based on market activity at pivot formation, enabling traders to identify which liquidation levels represent higher concentration of potential stops and liquidations with configurable minimum weight thresholds for noise filtering.
🔶 ATR-Based Zone Height Framework
Utilizes Average True Range calculations with percentage-based multipliers to determine pocket vertical dimensions that adapt to market volatility conditions. The system creates ATR-scaled bands above swing highs for short liquidation zones and below swing lows for long liquidation zones, ensuring zone heights remain proportional to current market volatility for accurate level representation.
🔶 Dynamic Gradient Heatmap Visualization
Implements sophisticated color gradient system that maps pocket weights to intensity scales, creating intuitive visual representation of relative liquidity concentration. The system applies power-law transformation with configurable contrast adjustment to enhance differentiation between weak and strong liquidity pockets, using cyan-to-blue gradients for long liquidations and yellow-to-orange for short liquidations.
🔶 Intelligent Pocket State Management
Features advanced pocket tracking system that monitors price interaction with liquidation zones and updates pocket states dynamically. The system detects when price trades through pocket midpoints, marking them as "hit" with optional preservation or removal, and manages pocket extension for untouched levels with configurable forward projection to maintain visibility of approaching liquidity zones.
🔶 Real-Time Liquidity Scale Display
Provides gradient legend showing min-max range of pocket weights with 24-segment color bar for instant liquidity intensity reference. The system positions the scale at chart edge with volume-formatted labels, enabling traders to quickly assess relative strength of visible liquidation pockets without numerical clutter on the main chart area.
🔶 Touched Pocket Border System
Implements visual confirmation of executed liquidations through border highlighting when price trades through pocket zones. The system applies configurable transparency to touched pocket borders with inverted slider logic (lower values fade borders, higher values emphasize them), providing clear historical record of liquidated levels while maintaining focus on active untouched pockets.
🔶 Dual-Swing Density Enhancement
Features optional secondary swing width parameter that creates additional pocket layer with tighter pivot detection for increased liquidation level density. The system runs parallel pivot detection at both primary and secondary swing widths, populating chart with comprehensive liquidity mapping that captures both major swing liquidations and intermediate level clusters.
🔶 Adaptive Pocket Extension Framework
Utilizes intelligent time-based extension that projects untouched pockets forward by configurable bar count, maintaining visibility as price approaches potential liquidation zones. The system freezes touched pocket right edges at hit timestamps while extending active pockets dynamically, creating clear distinction between historical liquidations and forward-projected active levels.
🔶 Weight-Based Label Integration
Provides floating labels on untouched pockets displaying volume-formatted weight values with dynamic positioning that follows pocket extension. The system automatically manages label lifecycle, creating labels for new pockets, updating positions as pockets extend, and removing labels when pockets are touched, ensuring clean chart presentation with relevant liquidity information.
🔶 Performance Optimization Framework
Implements efficient array management with automatic clean-up of old pockets beyond lookback period and optimized box/label deletion to maintain smooth performance. The system includes configurable maximum object counts (500 boxes, 50 labels, 100 lines) with intelligent removal of oldest elements when limits are approached, ensuring consistent operation across extended timeframes.
This indicator delivers sophisticated liquidity zone analysis through pivot-based detection and volume-weighted intensity measurement with intuitive heatmap visualization. Unlike simple support/resistance indicators, the Liquidation Heatmap combines swing point identification with market activity metrics to identify where concentrated liquidations are likely to occur, while the gradient color system instantly communicates relative liquidity strength. The system's dual-swing architecture, configurable weight metrics, ATR-adaptive zone heights, and intelligent state management make it essential for traders seeking strategic position planning around institutional liquidity levels across cryptocurrency, forex, and futures markets. The visual heatmap approach enables instant identification of high-probability reversal zones where cascading liquidations may trigger significant price reactions.
P_NQ Futures Daily Bias & Structure ProOverview The Master Sniper is a professional-grade execution system designed for high-volatility assets like NQ (Nasdaq 100) and ES (S&P 500). Unlike standard indicators that generate blind signals, this script uses a Multi-Timeframe Logic Engine to first establish a daily bias and then hunt for specific intraday triggers.
It features a Hybrid Strategy that can automatically switch between Trend Following (Smart Money Concepts) and Mean Reversion (Gap Fades), giving you a complete toolkit for any market condition.
Key Features
1. Macro Bias Engine (The Filter) Before generating any signal, the script analyzes the Daily Chart in the background:
Structure: Checks for Higher Highs/Lows vs. Lower Highs/Lows.
Momentum: Uses RSI and the 200 EMA to ensure you aren't buying the top or selling the bottom.
Result: It generates a directional bias (Bullish/Bearish) that filters out low-probability trades.
2. Hybrid Entry Logic
Trend Mode (SMC): Identifies Fair Value Gaps (FVG) within "Discount" or "Premium" zones. It only triggers if the price pulls back into a value area aligned with the Daily Bias.
Reversal Mode (Elasticity): Detects when price is over-extended (2.0 Standard Deviations from VWAP) or when a "Liquidity Sweep" occurs, signaling a snap-back trade.
Gap Rejection (Morning Fade): A dedicated engine that monitors the Opening Gap. If the market gaps significantly but fails to hold, it triggers a "Fade" trade to target the gap fill.
3. Professional Trade Management Visualizes your trade plan instantly on the chart:
Split Targets: Draws targets for Contract 1 (Scalp) and Contract 2 (Runner).
Auto-Break Even: The moment TP1 is hit, the Stop Loss line visually moves to your Entry Price, signaling a "Risk-Free" trade.
Infinite Target Lines: Extends target lines to the right until the trade concludes, keeping your chart clean.
4. Risk Filters
Range Filter: Prevents buying in the Top 1/3 or selling in the Bottom 1/3 of the daily range.
Proximity Filter: Blocks trades that are squeezing too tight against the 100-candle High/Low.
How to Use
Timeframe: Optimized for the 5-Minute (5m) chart on Futures (NQ/ES) or Tech Stocks.
Dashboard: Check the bottom-right panel. Ensure "Status" says "SCANNING" and Filters show "Active."
Execution: Wait for the alert (e.g., "🟢 ENTER LONG"). Place your orders at the Blue Line with SL at the Red Line.
One Point Global Net Liquidity The "Fuel" Behind the MarketMost traders look at price action, but price is often just a reflection of the money supply available in the system. This indicator tracks Global Net Liquidity—the actual amount of fiat currency available to flow into risk assets like Crypto and Equities.
Unlike standard "Money Supply" (M2) charts, this indicator focuses on Central Bank Balance Sheets, which is a more direct proxy for "Quantitative Easing" (QE) and "Quantitative Tightening" (QT).
How It Works (The Formula)
This script aggregates the balance sheets of the "Big 4" Central Banks, which represent ~90% of global liquidity. It automatically converts all values to USD Trillions for a standardized view.
{Global Liquidity} = {US Net Liquidity} + {ECB} + {PBoC} + {BoJ}
1. US Net Liquidity (The "Trader's" Formula) We do not just use the Fed's Total Assets. We subtract the money that is "stuck" outside the private economy:
(+) Fed Balance Sheet: Total Assets.
(-) TGA (Treasury General Account): The government's checking account. When this goes up, liquidity is drained from markets.
(-) RRP (Reverse Repo): Money parked by banks at the Fed overnight. When this goes up, liquidity is removed from the system.
2. Global Additions
ECB (Eurozone): Converted to USD.
PBoC (China): Converted to USD.
BoJ (Japan): Converted to USD.
How to Use This Indicator This indicator is designed as an Overlay on the main chart (using the Left Scale).
Correlation: Generally, when the Orange Line (Liquidity) trends up, Bitcoin and the S&P 500 trend up. When Central Banks tighten (line down), risk assets struggle.
The "Divergence" Signal (Alpha):
Bullish: If Price makes a Lower Low but Liquidity makes a Higher Low, it often signals seller exhaustion and a potential bottom.
Bearish: If Price makes a New High but Liquidity fails to follow (or drops), the rally may be unsupported and prone to a reversal.
Settings
Scale: This indicator is pinned to the Scale Left to allow it to overlay price action without distortion.
Data: Uses daily data from ECONOMICS and FRED feeds.
Self-Organized Criticality - Avalanche DistributionHere's all you need to know: This indicator applies Self-Organized Criticality (SOC) theory to financial markets, measuring the power-law exponent (alpha) of price drawdown distributions. It identifies whether markets are in stable Gaussian regimes or critical states where large cascading moves become more probable.
Self-Organized Criticality
SOC theory, introduced by Per Bak, Tang, and Wiesenfeld (1987), describes how complex systems naturally evolve toward critical (fragile) states. An example is a sand pile: adding grains creates avalanches whose sizes follow a power-law distribution rather than a normal distribution.
Financial markets exhibit similar behavior. Price movements aren't purely random walks—they display:
Fat-tailed distributions (more extreme events than Gaussian models predict)
Scale invariance (no characteristic avalanche size)
Intermittent dynamics (periods of calm punctuated by large cascades)
Power-Law Distributions
When a system is in a critical state, the probability of an avalanche of size s follows:
P(s) ∝ s^(-α)
Where:
α (alpha) is the power-law exponent
Higher α → distribution resembles Gaussian (large events rare)
Lower α → heavy tails dominate (large events common)
This indicator estimates α from the empirical distribution of price drawdowns.
Mathematical Method
1. Avalanche Detection
The indicator identifies local price peaks (highest point in a lookback window), then measures the percentage drawdown to the next trough. A dynamic ATR-based threshold filters out noise—small drops in calm markets count, but the bar rises in volatile periods.
2. Logarithmic Binning
Avalanche sizes are sorted into logarithmically-spaced bins (e.g., 1-2%, 2-4%, 4-8%) rather than linear bins. This captures power-law behavior across multiple scales - a 2% drop and 20% crash both matter. The indicator creates 12 adaptive bins spanning from your smallest to largest observed avalanche.
3. Bin-to-Bin Ratio Estimation
For each pair of adjacent bins, we calculate:
α ≈ log(N₁/N₂) / log(s₂/s₁)
Where N₁ and N₂ are avalanche counts, s₁ and s₂ are bin sizes.
Example: If 2% drops happen 4× more often than 4% drops, then α ≈ log(4)/log(2) ≈ 2.0.
We get 8-11 independent estimates and average them. This is more robust than fitting one line through all points—outliers can't dominate.
4. Rolling Window Analysis
Alpha recalculates using only recent avalanches (default: last 500 bars). Old data drops out as new avalanches occur, so the indicator tracks regime shifts in real-time.
Regime Classification
🟢 Gaussian α ≥ 2.8 Normal distribution behavior; large moves are rare outliers
🟡 Transitional 1.8 ≤ α < 2.8 Moderate fat tails; system approaching criticality
🟠 Critical 1.0 ≤ α < 1.8 Heavy tails; large avalanches increasingly common
🔴 Super-Critical α < 1.0 Extreme tail risk; system prone to cascading failures
What Alpha Tells You
Declining alpha → Market moving toward criticality; tail risk increasing
Rising alpha → Market stabilizing; returns to normal distribution
Persistent low alpha → Sustained fragility; heightened crash probability
Supporting Metrics
Heavy Tail %: Concentration of total drawdown in largest 10% of events
Populated Bins: Data coverage quality (11-12 out of 12 is ideal)
Avalanche Count: Sample size for statistical reliability
Limitations
This is a distributional measure, not a timing indicator. Low alpha indicates increased systemic risk but doesn't predict when a cascade will occur. Only that the probability distribution has shifted toward larger events.
How This Differs from the Per Bak Fragility Index
The SOC Avalanche Distribution calculates the power-law exponent (alpha) directly from price drawdown distributions - a pure mathematical analysis requiring only price data. The Per Bak Fragility Index aggregates external stress indicators (VIX, SKEW, credit spreads, put/call ratios) into a weighted composite score.
Technical Notes
Default settings optimized for daily and weekly timeframes on major indices
Requires minimum 200 bars of history for stable estimates
ATR-based dynamic sizing prevents scale-dependent bias
Alerts available for regime transitions and super-critical entry
References
Bak, P., Tang, C., & Wiesenfeld, K. (1987). Self-organized criticality: An explanation of the 1/f noise. Physical Review Letters.
Sornette, D. (2003). Why Stock Markets Crash: Critical Events in Complex Financial Systems. Princeton University Press.
Z-score RegimeThis indicator compares equity behaviour and credit behaviour by converting both into z-scores. It calculates the z-score of SPX and the z-score of a credit proxy based on the HYG divided by LQD ratio.
SPX z-score shows how far the S&P 500 is from its rolling average.
Credit z-score shows how risk-seeking or risk-averse credit markets are by comparing high-yield bonds to investment-grade bonds.
When both z-scores move together, the market is aligned in either risk-on or risk-off conditions.
When SPX z-score is strong but credit z-score is weak, this may signal equity strength that is not supported by credit markets.
When credit z-score is stronger than SPX z-score, credit markets may be leading risk appetite.
The indicator plots the two z-scores as simple lines for clear regime comparison.
50 EMA Rejection Strategy V4 (Correct Signal Logic)//@version=6
indicator("50 EMA Rejection Strategy V4 (Correct Signal Logic)", overlay=true, max_labels_count=500)
//================ INPUTS ================//
group50 = "EMA 50 Trio"
ema50HighLen = input.int(50,"EMA50 High",group=group50)
ema50CloseLen = input.int(50,"EMA50 Close",group=group50)
ema50LowLen = input.int(50,"EMA50 Low",group=group50)
groupBase = "Additional EMAs"
ema10Len = input.int(10,"EMA10")
ema200Len = input.int(200,"EMA200")
ema600Len = input.int(600,"EMA600")
ema2400Len = input.int(2400,"EMA2400")
useTrendFilter = input.bool(false,"Use Higher Time EMA Filter")
groupRR = "Risk Reward Settings"
RR1 = input.float(1.0,"TP1 RR",step=0.5)
RR2 = input.float(2.0,"TP2 RR",step=0.5)
//================ CALCULATIONS ================//
Correlation Scanner📊 CORRELATION SCANNER - Financial Instruments Correlation Analyzer
🎯 ORIGINALITY AND PURPOSE
Correlation Scanner is a professional tool for analyzing correlation relationships between different financial instruments. Unlike standard correlation indicators that show the relationship between only two instruments, this script allows you to simultaneously track the correlation of up to 10 customizable instruments with a selected base asset.
The indicator is designed for traders working with cross-market analysis, portfolio diversification, and searching for related assets for arbitrage strategies.
🔧 HOW IT WORKS
The indicator uses the built-in ta.correlation() function to calculate the Pearson correlation coefficient between instrument closing prices over a specified period. Mathematical foundation:
1. Correlation Calculation: for each instrument, the correlation coefficient with the base asset is calculated over N bars (default 60)
2. Results Sorting: instruments are automatically ranked by absolute correlation value (from strongest to weakest)
3. Visualization: results are displayed in a table with color coding:
- Green: positive correlation (instruments move in the same direction)
- Red: negative correlation (instruments move in opposite directions)
- Color intensity depends on correlation strength
4. Correlation Strength Classification:
- Very Strong (💪💪💪): |r| > 0.8 — very strong relationship
- Strong (💪💪): |r| > 0.6 — strong relationship
- Medium (💪): |r| > 0.4 — medium relationship
- Weak: |r| > 0.2 — weak relationship
- Very Weak: |r| ≤ 0.2 — very weak relationship
📋 SETTINGS AND USAGE
MAIN PARAMETERS:
• Main Instrument — base instrument for comparison (default TVC:DXY - US Dollar Index)
• Correlation Period — calculation period in bars (10-500, default 60)
• Number of Instruments to Display — number of instruments to show (1-10)
• Table Position — table location on the chart
INSTRUMENT CONFIGURATION:
The indicator allows configuring up to 10 instruments for analysis. For each, you can specify:
• Instrument — instrument ticker (e.g., FX_IDC:EURUSD)
• Name — display name (emojis supported)
VISUAL SETTINGS:
• Show Chart Label with Correlation — display current chart's correlation with base instrument
• Table Header Color — table header color
• Table Row Background — table row background color
💡 USAGE EXAMPLES
1. DOLLAR IMPACT ANALYSIS: set DXY as the base instrument and track how dollar index changes affect currency pairs, gold, and cryptocurrencies
2. HEDGING ASSETS SEARCH: find instruments with strong negative correlation for risk diversification
3. PAIRS TRADING: identify assets with high positive correlation to find divergences and arbitrage opportunities
4. CROSS-MARKET ANALYSIS: track relationships between stocks, bonds, commodities, and currencies
5. SYSTEMIC RISK ASSESSMENT: identify periods of increased correlation between assets, which may indicate systemic risks
⚠️ IMPORTANT NOTES
• Correlation does NOT imply causation
• Correlation can change over time — regularly review the analysis period
• High past correlation doesn't guarantee the relationship will persist in the future
• Recommended to use the indicator in combination with fundamental analysis
🔔 ALERTS
The indicator includes a built-in alert condition: triggers when strong correlation (|r| > 0.8) is detected between the current chart and the base instrument.
S&P Options Patterns Detector (6-20 Candles)Pattern detector for S&P options. Detects alerts for bullish or bearish signals for any stock in S&P 500
Global M2(USD) V2This indicator tracks the total Global M2 Money Supply in USD. It aggregates economic data from the world's four largest central banks (Fed, PBOC, ECB, BOJ). The script automatically converts non-USD money supplies (CNY, EUR, JPY) into USD using real-time exchange rates to provide a unified view of global liquidity.
Usage
Macro Analysis: Overlay this on assets like Bitcoin or the S&P 500 to see if price appreciation is driven by fiat currency debasement ("money printing").
Liquidity Trends: A rising orange line indicates expanding global liquidity (generally bullish for risk assets), while a falling line suggests monetary tightening.
Real-time Data: A label at the end of the line displays the exact raw total in USD for precise tracking.
该脚本旨在追踪以美元计价的全球 M2 货币供应总量。它聚合了四大央行（美联储、中国央行、欧洲央行、日本央行）的经济数据，并通过实时汇率将非美货币（人民币、欧元、日元）统一折算为美元，从而构建出一个标准化的全球流动性指标。
用法
宏观对冲： 将其叠加在比特币或股票图表上，用于判断资产价格的上涨是否由全球法币“大放水”推动。
趋势研判： 橙色曲线向上代表全球流动性扩张（通常利好风险资产），向下则代表流动性紧缩。
数据直观： 脚本会在图表末端生成一个标签，实时显示当前全球 M2 的具体美元总额。
