PnL Bubble [%] | Fractalyst1. What's the indicator purpose?
The PnL Bubble indicator transforms your strategy's trade PnL percentages into an interactive bubble chart with professional-grade statistics and performance analytics. It helps traders quickly assess system profitability, understand win/loss distribution patterns, identify outliers, and make data-driven strategy improvements.
How does it work?
Think of this indicator as a visual report card for your trading performance. Here's what it does:
What You See
Colorful Bubbles: Each bubble represents one of your trades
Blue/Cyan bubbles = Winning trades (you made money)
Red bubbles = Losing trades (you lost money)
Bigger bubbles = Bigger wins or losses
Smaller bubbles = Smaller wins or losses
How It Organizes Your Trades:
Like a Photo Album: Instead of showing all your trades at once (which would be messy), it shows them in "pages" of 500 trades each:
Page 1: Your first 500 trades
Page 2: Trades 501-1000
Page 3: Trades 1001-1500, etc.
What the Numbers Tell You:
Average Win: How much money you typically make on winning trades
Average Loss: How much money you typically lose on losing trades
Expected Value (EV): Whether your trading system makes money over time
Positive EV = Your system is profitable long-term
Negative EV = Your system loses money long-term
Payoff Ratio (R): How your average win compares to your average loss
R > 1 = Your wins are bigger than your losses
R < 1 = Your losses are bigger than your wins
Why This Matters:
At a Glance: You can instantly see if you're a profitable trader or not
Pattern Recognition: Spot if you have more big wins than big losses
Performance Tracking: Watch how your trading improves over time
Realistic Expectations: Understand what "average" performance looks like for your system
The Cool Visual Effects:
Animation: The bubbles glow and shimmer to make the chart more engaging
Highlighting: Your biggest wins and losses get extra attention with special effects
Tooltips: hover any bubble to see details about that specific trade.
What are the underlying calculations?
The indicator processes trade PnL data using a dual-matrix architecture for optimal performance:
Dual-Matrix System:
• Display Matrix (display_matrix): Bounded to 500 trades for rendering performance
• Statistics Matrix (stats_matrix): Unbounded storage for complete statistical accuracy
Trade Classification & Aggregation:
// Separate wins, losses, and break-even trades
if val > 0.0
pos_sum += val // Sum winning trades
pos_count += 1 // Count winning trades
else if val < 0.0
neg_sum += val // Sum losing trades
neg_count += 1 // Count losing trades
else
zero_count += 1 // Count break-even trades
Statistical Averages:
avg_win = pos_count > 0 ? pos_sum / pos_count : na
avg_loss = neg_count > 0 ? math.abs(neg_sum) / neg_count : na
Win/Loss Rates:
total_obs = pos_count + neg_count + zero_count
win_rate = pos_count / total_obs
loss_rate = neg_count / total_obs
Expected Value (EV):
ev_value = (avg_win × win_rate) - (avg_loss × loss_rate)
Payoff Ratio (R):
R = avg_win ÷ |avg_loss|
Contribution Analysis:
ev_pos_contrib = avg_win × win_rate // Positive EV contribution
ev_neg_contrib = avg_loss × loss_rate // Negative EV contribution
How to integrate with any trading strategy?
Equity Change Tracking Method:
//@version=6
strategy("Your Strategy with Equity Change Export", overlay=true)
float prev_trade_equity = na
float equity_change_pct = na
if barstate.isconfirmed and na(prev_trade_equity)
prev_trade_equity := strategy.equity
trade_just_closed = strategy.closedtrades != strategy.closedtrades
if trade_just_closed and not na(prev_trade_equity)
current_equity = strategy.equity
equity_change_pct := ((current_equity - prev_trade_equity) / prev_trade_equity) * 100
prev_trade_equity := current_equity
else
equity_change_pct := na
plot(equity_change_pct, "Equity Change %", display=display.data_window)
Integration Steps:
1. Add equity tracking code to your strategy
2. Load both strategy and PnL Bubble indicator on the same chart
3. In bubble indicator settings, select your strategy's equity tracking output as data source
4. Configure visualization preferences (colors, effects, page navigation)
How does the pagination system work?
The indicator uses an intelligent pagination system to handle large trade datasets efficiently:
Page Organization:
• Page 1: Trades 1-500 (most recent)
• Page 2: Trades 501-1000
• Page 3: Trades 1001-1500
• Page N: Trades to
Example: With 1,500 trades total (3 pages available):
• User selects Page 1: Shows trades 1-500
• User selects Page 4: Automatically falls back to Page 3 (trades 1001-1500)
5. Understanding the Visual Elements
Bubble Visualization:
• Color Coding: Cyan/blue gradients for wins, red gradients for losses
• Size Mapping: Bubble size proportional to trade magnitude (larger = bigger P&L)
• Priority Rendering: Largest trades displayed first to ensure visibility
• Gradient Effects: Color intensity increases with trade magnitude within each category
Interactive Tooltips:
Each bubble displays quantitative trade information:
tooltip_text = outcome + " | PnL: " + pnl_str +
"\nDate: " + date_str + " " + time_str +
"\nTrade #" + str.tostring(trade_number) + " (Page " + str.tostring(active_page) + ")" +
"\nRank: " + str.tostring(rank) + " of " + str.tostring(n_display_rows) +
"\nPercentile: " + str.tostring(percentile, "#.#") + "%" +
"\nMagnitude: " + str.tostring(magnitude_pct, "#.#") + "%"
Example Tooltip:
Win | PnL: +2.45%
Date: 2024.03.15 14:30
Trade #1,247 (Page 3)
Rank: 5 of 347
Percentile: 98.6%
Magnitude: 85.2%
Reference Lines & Statistics:
• Average Win Line: Horizontal reference showing typical winning trade size
• Average Loss Line: Horizontal reference showing typical losing trade size
• Zero Line: Threshold separating wins from losses
• Statistical Labels: EV, R-Ratio, and contribution analysis displayed on chart
What do the statistical metrics mean?
Expected Value (EV):
Represents the mathematical expectation per trade in percentage terms
EV = (Average Win × Win Rate) - (Average Loss × Loss Rate)
Interpretation:
• EV > 0: Profitable system with positive mathematical expectation
• EV = 0: Break-even system, profitability depends on execution
• EV < 0: Unprofitable system with negative mathematical expectation
Example: EV = +0.34% means you expect +0.34% profit per trade on average
Payoff Ratio (R):
Quantifies the risk-reward relationship of your trading system
R = Average Win ÷ |Average Loss|
Interpretation:
• R > 1.0: Wins are larger than losses on average (favorable risk-reward)
• R = 1.0: Wins and losses are equal in magnitude
• R < 1.0: Losses are larger than wins on average (unfavorable risk-reward)
Example: R = 1.5 means your average win is 50% larger than your average loss
Contribution Analysis (Σ):
Breaks down the components of expected value
Positive Contribution (Σ+) = Average Win × Win Rate
Negative Contribution (Σ-) = Average Loss × Loss Rate
Purpose:
• Shows how much wins contribute to overall expectancy
• Shows how much losses detract from overall expectancy
• Net EV = Σ+ - Σ- (Expected Value per trade)
Example: Σ+: 1.23% means wins contribute +1.23% to expectancy
Example: Σ-: -0.89% means losses drag expectancy by -0.89%
Win/Loss Rates:
Win Rate = Count(Wins) ÷ Total Trades
Loss Rate = Count(Losses) ÷ Total Trades
Shows the probability of winning vs losing trades
Higher win rates don't guarantee profitability if average losses exceed average wins
7. Demo Mode & Synthetic Data Generation
When using built-in sources (close, open, etc.), the indicator generates realistic demo trades for testing:
if isBuiltInSource(source_data)
// Generate random trade outcomes with realistic distribution
u_sign = prand(float(time), float(bar_index))
if u_sign < 0.5
v_push := -1.0 // Loss trade
else
// Skewed distribution favoring smaller wins (realistic)
u_mag = prand(float(time) + 9876.543, float(bar_index) + 321.0)
k = 8.0 // Skewness factor
t = math.pow(u_mag, k)
v_push := 2.5 + t * 8.0 // Win trade
Demo Characteristics:
• Realistic win/loss distribution mimicking actual trading patterns
• Skewed distribution favoring smaller wins over large wins
• Deterministic randomness for consistent demo results
• Includes jitter effects to prevent visual overlap
8. Performance Limitations & Optimizations
Display Constraints:
points_count = 500 // Maximum 500 dots per page for optimal performance
Pine Script v6 Limits:
• Label Count: Maximum 500 labels per indicator
• Line Count: Maximum 100 lines per indicator
• Box Count: Maximum 50 boxes per indicator
• Matrix Size: Efficient memory management with dual-matrix system
Optimization Strategies:
• Pagination System: Handle unlimited trades through 500-trade pages
• Priority Rendering: Largest trades displayed first for maximum visibility
• Dual-Matrix Architecture: Separate display (bounded) from statistics (unbounded)
• Smart Fallback: Automatic page clamping prevents empty displays
Impact & Workarounds:
• Visual Limitation: Only 500 trades visible per page
• Statistical Accuracy: Complete dataset used for all calculations
• Navigation: Use page input to browse through entire trade history
• Performance: Smooth operation even with thousands of trades
9. Statistical Accuracy Guarantees
Data Integrity:
• Complete Dataset: Statistics matrix stores ALL trades without limit
• Proper Aggregation: Separate tracking of wins, losses, and break-even trades
• Mathematical Precision: Pine Script v6's enhanced floating-point calculations
• Dual-Matrix System: Display limitations don't affect statistical accuracy
Calculation Validation:
// Verified formulas match standard trading mathematics
avg_win = pos_sum / pos_count // Standard average calculation
win_rate = pos_count / total_obs // Standard probability calculation
ev_value = (avg_win * win_rate) - (avg_loss * loss_rate) // Standard EV formula
Accuracy Features:
• Mathematical Correctness: Formulas follow established trading statistics
• Data Preservation: Complete dataset maintained for all calculations
• Precision Handling: Proper rounding and boundary condition management
• Real-Time Updates: Statistics recalculated on every new trade
10. Advanced Technical Features
Real-Time Animation Engine:
// Shimmer effects with sine wave modulation
offset = math.sin(shimmer_t + phase) * amp
// Dynamic transparency with organic flicker
new_transp = math.min(flicker_limit, math.max(-flicker_limit, cur_transp + dir * flicker_step))
• Sine Wave Shimmer: Dynamic glowing effects on bubbles
• Organic Flicker: Random transparency variations for natural feel
• Extreme Value Highlighting: Special visual treatment for outliers
• Smooth Animations: Tick-based updates for fluid motion
Magnitude-Based Priority Rendering:
// Sort trades by magnitude for optimal visual hierarchy
sort_indices_by_magnitude(values_mat)
• Largest First: Most important trades always visible
• Intelligent Sorting: Custom bubble sort algorithm for trade prioritization
• Performance Optimized: Efficient sorting for real-time updates
• Visual Hierarchy: Ensures critical trades never get hidden
Professional Tooltip System:
• Quantitative Data: Pure numerical information without interpretative language
• Contextual Ranking: Shows trade position within page dataset
• Percentile Analysis: Performance ranking as percentage
• Magnitude Scaling: Relative size compared to page maximum
• Professional Format: Clean, data-focused presentation
11. Quick Start Guide
Step 1: Add Indicator
• Search for "PnL Bubble | Fractalyst" in TradingView indicators
• Add to your chart (works on any timeframe)
Step 2: Configure Data Source
• Demo Mode: Leave source as "close" to see synthetic trading data
• Strategy Mode: Select your strategy's PnL% output as data source
Step 3: Customize Visualization
• Colors: Set positive (cyan), negative (red), and neutral colors
• Page Navigation: Use "Trade Page" input to browse trade history
• Visual Effects: Built-in shimmer and animation effects are enabled by default
Step 4: Analyze Performance
• Study bubble patterns for win/loss distribution
• Review statistical metrics: EV, R-Ratio, Win Rate
• Use tooltips for detailed trade analysis
• Navigate pages to explore full trade history
Step 5: Optimize Strategy
• Identify outlier trades (largest bubbles)
• Analyze risk-reward profile through R-Ratio
• Monitor Expected Value for system profitability
• Use contribution analysis to understand win/loss impact
12. Why Choose PnL Bubble Indicator?
Unique Advantages:
• Advanced Pagination: Handle unlimited trades with smart fallback system
• Dual-Matrix Architecture: Perfect balance of performance and accuracy
• Professional Statistics: Institution-grade metrics with complete data integrity
• Real-Time Animation: Dynamic visual effects for engaging analysis
• Quantitative Tooltips: Pure numerical data without subjective interpretations
• Priority Rendering: Intelligent magnitude-based display ensures critical trades are always visible
Technical Excellence:
• Built with Pine Script v6 for maximum performance and modern features
• Optimized algorithms for smooth operation with large datasets
• Complete statistical accuracy despite display optimizations
• Professional-grade calculations matching institutional trading analytics
Practical Benefits:
• Instantly identify system profitability through visual patterns
• Spot outlier trades and risk management issues
• Understand true risk-reward profile of your strategies
• Make data-driven decisions for strategy optimization
• Professional presentation suitable for performance reporting
Disclaimer & Risk Considerations:
Important: Historical performance metrics, including positive Expected Value (EV), do not guarantee future trading success. Statistical measures are derived from finite sample data and subject to inherent limitations:
• Sample Bias: Historical data may not represent future market conditions or regime changes
• Ergodicity Assumption: Markets are non-stationary; past statistical relationships may break down
• Survivorship Bias: Strategies showing positive historical EV may fail during different market cycles
• Parameter Instability: Optimal parameters identified in backtesting often degrade in forward testing
• Transaction Cost Evolution: Slippage, spreads, and commission structures change over time
• Behavioral Factors: Live trading introduces psychological elements absent in backtesting
• Black Swan Events: Extreme market events can invalidate statistical assumptions instantaneously
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Kitty PMO [theUltimator5]Kitty PMO is a momentum analysis tool designed to visually track and interpret the Price Momentum Oscillator (PMO) — with stylistic influence inspired by the charting approach made popular by “theRoaringKitty.” It aims to offer clear, actionable momentum signals directly overlaid on the chart without clutter or ambiguity, making it ideal for traders who prioritize simplicity and signal clarity.
At its core, the indicator calculates the PMO by applying a custom recursive smoothing function to the rate of change (ROC) of price. This smoothed momentum measure is then:
Amplified by a scaling factor (×10),
Further smoothed using user-defined parameters,
Compared against a signal line (EMA of PMO),
And tracked with a secondary moving average (PMO MA) to capture medium-term trend inflections.
While the PMO and its associated signal lines can optionally be plotted, the indicator primarily emphasizes crossovers between the PMO MA and the other two components. When the PMO MA crosses above both the PMO and signal line, a green upward arrow (↑) is plotted below the price. When it crosses below both, a red downward arrow (↓) appears above the price — making it easy to spot potential turning points in momentum.
Additionally, a floating info table can be toggled on to display all current user-defined parameters in a clean, resizable format. This makes the script ideal not just for technical execution but also for real-time strategy tuning and tracking across multiple timeframes.
The script includes optional alerts so you can be notified the moment a key crossover signal is triggered, without needing to keep your eyes glued to the screen.
Rev & Line - CoffeeKillerRev & Line - CoffeeKiller Indicator Guide
🔔 Warning: This Indicator Repaints 🔔 This indicator uses real-time calculations that may change based on future price action. As a result, signals (such as arrows, lines, or color changes) **can and will repaint** — meaning they may appear, disappear, or shift after a candle closes.
**Do not rely on this tool alone for live trading decisions.** Use with caution and always confirm with non-repainting tools or additional analysis.(This indicator is designed to show me the full length of the trend and because of this there can be a smaller movement inside of the trend movement)
Welcome traders! This guide will walk you through the Rev & Line indicator, a sophisticated technical analysis tool developed by CoffeeKiller that combines multiple methodologies to identify market pivots, trends, and potential reversal points.
Core Components
1. ZigZag Analysis
- Dynamic pivot detection using ATR (Average True Range)
- Customizable sensitivity through ATR Reversal Factor
- Color-coded trend lines (green for upward, red for downward)
- Optional vertical lines at pivot points
- Real-time pivot point analysis
2. Donchian Channel Integration
- Traditional upper, lower, and middle bands
- Customizable length and displacement
- Channel-based entry signals
- Dynamic market structure visualization
3. Marker Lines System
- Dynamic support/resistance level tracking
- Pivot-based reset mechanism
- Optional fill zones between markers
- Percentage position tracking within range
4. Signal Generation System
- Confluence between ZigZag pivots and Donchian channels
- Up/down arrow visualization
- Alert system
Main Features
ZigZag Settings
- ATR Reversal Factor: Controls pivot sensitivity (default 3.2)
- Customizable line appearance:
Width control (default: 3)
Color selection (green for uptrend, red for downtrend)
Vertical line options at pivot points
Maximum vertical lines display limit
- Hide repainted option for more reliable signals
Donchian Channel Configuration
- Optional channel visibility toggle
- Length parameter for lookback period (default: 20)
- Displace option for time offset
- Bubble offset for visual placement
Marker Lines System
- High/low/middle marker lines with step-line visualization
- Dotted line projections for future reference
- Pivot-based reset mechanism
- Color-coded percentage position display
Signal Generation
- Triangle markers for signals
- Combined ZigZag and Donchian confluence
- Alert system for notifications
Visual Elements
1. Pivot Lines
- Green: Upward price movements
- Red: Downward price movements
- Customizable line width
- Optional vertical pivot markers with style options:
Solid lines for confirmed pivots
Dashed lines for older pivots
Dotted lines for most recent pivots
2. Donchian Channels
- Upper band (red): Resistance level
- Lower band (green): Support level
- Middle band (yellow): Median price line
- Customizable display options
3. Marker Lines
- High marker line (magenta): Tracks highest open price
- Low marker line (cyan): Tracks lowest open price
- Middle marker line (blue): 50% level between high/low
- Dotted line extensions for future price projections
4. Position Tracking
- Percentage position display within marker range
- Real-time calculations from 0% to 100%
- Label system for visual reference
Trading Applications
1. Trend Following
- Enter on confirmed ZigZag pivot points
- Use Donchian channel boundaries as targets
- Trail stops using marker lines
- Monitor for confluence between systems
2. Counter-Trend Trading
- Trade bounces from marker lines
- Use pivot confirmation for entry timing
- Set stops based on recent pivot points
- Target the opposite marker line
3. Range Trading
- Use high/low marker lines to define range
- Trade bounces between upper and lower markers
- Consider middle marker for range midpoint
- Monitor percentage position within range
4. Breakout Trading
- Enter on breaks above/below marker lines
- Confirm with Donchian channel breakouts
- Use ZigZag pivot confirmations
- Wait for arrow signals for additional confirmation
Optimization Guide
1. ZigZag Parameters
- Higher ATR Factor: Less sensitive, major moves only
- Lower ATR Factor: More sensitive, catches minor moves
- Adjust line width for chart visibility
- Balance vertical line count for clarity
2. Donchian Channel Settings
- Longer length: Smoother channels, fewer false signals
- Shorter length: More responsive, but potentially noisier
- Displacement: Offset for historical reference
- Consider timeframe when setting parameters
3. Marker Line Configuration
- Enable/disable based on trading style
- Toggle middle line for additional reference
- Adjust colors for visual clarity
- Enable/disable labels as needed
4. Signal Generation
- Use "Hide repainted" option for more reliable signals
- Combine ZigZag and Donchian signals for confirmation
- Set alerts based on confirmed pivot points
- Balance sensitivity with reliability
Best Practices
1. Signal Confirmation
- Wait for confirmed pivot points
- Check for Donchian channel interactions
- Confirm with price action
- Look for arrow signals at pivot points
2. Risk Management
- Use recent pivot points for stop placement
- Consider marker line boundaries for targets
- Don't trade against strong trends
- Wait for clear confluence between systems
3. Setup Optimization
- Start with default settings
- Adjust based on timeframe
- Fine-tune ATR sensitivity
- Match settings to trading style
Advanced Features
1. Alert System
- Customizable arrow alerts
- Pivot point notifications
- Text message alerts with ticker information
- Once-per-bar frequency option
2. Pivot Detection Logic
The indicator uses a sophisticated state-based approach to detect pivots:
- State transitions between "uptrend," "downtrend," and "undefined"
- ATR-based reversal detection
- Minimum movement threshold for pivot confirmation
- Historical pivot tracking and labeling
3. Marker Line Reset Mechanism
- Marker lines reset based on pivot detection
- Dynamic support/resistance level adjustment
- Percentage position calculation within range
- Automatic updates as market structure changes
Remember:
- Combine multiple confirmation signals
- Use appropriate timeframe settings
- Monitor both ZigZag and Marker signals
- Pay attention to Donchian channel interactions
- Consider market volatility when trading
This indicator works best when:
- Used with proper risk management
- Combined with other technical tools
- Applied to appropriate timeframes
- Signals are confirmed by price action
**DISCLAIMER**: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
Key Levels by MoneyTribe21This custom script provides real-time tracking of key market price levels, helping traders identify critical support and resistance zones. It dynamically updates throughout the trading session, making it ideal for intraday trading, breakout strategies, and market structure analysis.
Features:
Real-Time Tracking of Key Price Levels:
ATH (All-Time High): Tracks the highest price ever reached for the asset.
PDH (Previous Day High): Marks the high of the last trading day,
PDL (Previous Day Low): Marks the low of the last trading day, serving as dynamic support.
Resistance Level: Based on the current day’s high, signaling potential price rejection points.
Support Level: Based on the current day’s low, indicating potential price bounces.
Daily Open Price: Tracks the exact market open price at the start of the trading session.
Works Across All Timeframes:
Designed for intraday, swing, and long-term trading.
Automatically adjusts levels for Forex, Stocks, Crypto, and Indices.
Fully Customizable Settings:
Modify line colors, thickness, and styles for better chart readability.
Enable/disable specific levels based on trading preference.
Works on all TradingView-compatible brokers and platforms.
How to Use This Indicator:
Breakout & Reversal Trading:
If price breaks above PDH, it may indicate bullish momentum.
If price breaks below PDL, it may signal a bearish continuation.
ATH levels can act as strong resistance zones—watch for breakouts or rejection.
Dynamic Support & Resistance:
Resistance Level (Current Day High): If price fails to break, it may signal a reversal.
Support Level (Current Day Low): If price bounces off, it may confirm a strong uptrend.
Daily Open for Trend Confirmation:
Above Daily Open: Market sentiment is bullish.
Below Daily Open: Market sentiment is bearish.
Customization Options:
Toggle individual price levels ON/OFF for a clutter-free chart.
Customize colors, line styles, and alerts for better visualization.
Set alerts for breakouts & retests of key levels.
Ideal for Traders Who:
Want high-probability support & resistance zones in real-time.
Trade breakouts, reversals, or trend continuations.
Use market structure analysis for informed decision-making.
Need automatic price tracking instead of drawing levels manually.
Compatible with all TradingView timeframes & assets (Forex, Stocks, Crypto, Indices).
Designed for both beginner and advanced traders.
Add this indicator to your chart and start tracking key levels instantly.
lib_mathLibrary "lib_math"
a collection of functions calculating without history operator to avoid max_bars_back errors
mean(value, reset)
Parameters:
value (float) : series to track
reset (bool) : flag to reset tracking
@return returns average/mean of value since last reset
vwap(value, reset)
Parameters:
value (float) : series to track
reset (bool) : flag to reset tracking
@return returns vwap of value and volume since last reset
variance(value, reset)
Parameters:
value (float) : series to track
reset (bool) : flag to reset tracking
@return returns variance of value since last reset
trend(value, reset)
Parameters:
value (float) : series to track
reset (bool) : flag to reset tracking
@return where slope is the trend direction, correlation is a measurement for how well the values fit to the trendline (positive means ), stddev is how far the values deviate from the trend, x1 would be the time where reset is true and x2 would be the current time
VWAP Kalman FilterOverview
This indicator applies Kalman filtering techniques to Volume Weighted Average Price (VWAP) calculations, providing a statistically optimized approach to VWAP analysis. The Kalman filter reduces noise while maintaining responsiveness to genuine price movements, addressing common VWAP limitations in volatile or low-volume conditions.
Technical Implementation
Kalman Filter Mathematics
The indicator implements a state-space model for VWAP estimation:
- Prediction Step: x̂(k|k-1) = x̂(k-1|k-1) + v(k-1)
- Update Step: x̂(k|k) = x̂(k|k-1) + K(k)
- Kalman Gain: K(k) = P(k|k-1) / (P(k|k-1) + R)
Where:
- x̂ = estimated VWAP state
- K = Kalman gain (adaptive weighting factor)
- P = error covariance
- R = measurement noise
- Q = process noise
- v = optional velocity component
Core Components
Dual VWAP System
- Standard VWAP: Traditional volume-weighted calculation
- Kalman-filtered VWAP: Noise-reduced estimation with optional velocity tracking
- Real-time divergence measurement between filtered and unfiltered values
Adaptive Filtering
- Process Noise (Q): Controls adaptation to price changes (0.001-1.0)
- Measurement Noise (R): Determines smoothing intensity (0.01-5.0)
- Optional velocity tracking for momentum-based filtering
Multi-Timeframe Anchoring
- Session, Weekly, Monthly, Quarterly, and Yearly anchor periods
- Automatic Kalman state reset on anchor changes
- Maintains VWAP integrity across timeframes
Features
Visual Components
- Dual VWAP Lines: Compare filtered vs. unfiltered in real-time
- Dynamic Bands: Three-level deviation bands (1σ, 2σ, 3σ)
- Trend Coloring: Automatic color adaptation based on price position
- Cloud Visualization: Highlights divergence between standard and Kalman VWAP
- Signal Markers: Crossover and band-touch indicators
Trading Signals
- VWAP crossover detection with Kalman filtering
- Band touch alerts at multiple standard deviation levels
- Velocity-based momentum confirmation (optional)
- Divergence warnings when filtered/unfiltered values separate
Information Display
- Real-time VWAP values (both standard and filtered)
- Trend direction indicator
- Velocity/momentum reading (when enabled)
- Divergence percentage calculation
- Anchor period display
Input Parameters
VWAP Settings
- Anchor Period: Choose calculation reset period
- Band Multipliers: Customize deviation band distances
- Display Options: Toggle standard VWAP and bands
Kalman Parameters
- Length: Base period for calculations (5-200)
- Process Noise (Q: Higher values increase responsiveness
- Measurement Noise (R): Higher values increase smoothing
- Velocity Tracking: Enable momentum-based filtering
Visual Controls
- Toggle filtered/unfiltered VWAP display
- Band visibility options
- Signal markers on/off
- Cloud fill between VWAPs
- Bar coloring by trend
Use Cases
Noise Reduction
Particularly effective during:
- Low volume periods (pre-market, lunch hours)
- Volatile market conditions
- Fast-moving markets where standard VWAP whipsaws
Trend Identification
- Cleaner trend signals with reduced false crosses
- Earlier trend detection through velocity component
- Confirmation through divergence analysis
Support/Resistance
- Filtered VWAP provides more stable S/R levels
- Bands adapt to filtered values for better zone identification
- Reduced false breakout signals
Technical Advantages
1. Optimal Estimation: Mathematically optimal under Gaussian noise assumptions
2. Adaptive Response: Self-adjusting to market conditions
3. Predictive Element: Velocity component provides forward-looking insight
4. Noise Immunity: Superior noise rejection vs. simple moving average smoothing
Limitations
- Assumes linear price dynamics
- Requires parameter optimization for different instruments
- May lag during sudden volatility regime changes
- Not suitable as standalone trading system
Mathematical Background
Based on control systems theory, the Kalman filter provides recursive Bayesian estimation originally developed for aerospace applications. This implementation adapts the algorithm specifically for financial time series, maintaining VWAP's volume-weighted properties while adding statistical filtering.
Comparison with Standard VWAP
Standard VWAP Issues Addressed:
- Choppy behavior in low volume
- Whipsaws around VWAP line
- Lag in trend identification
- Noise in deviation bands
Kalman VWAP Benefits:
- Smooth yet responsive line
- Fewer false signals
- Optional momentum tracking
- Statistically optimized filtering
Alert Conditions
The indicator includes several pre-configured alert conditions:
- Bullish/Bearish VWAP crosses
- Upper/Lower band touches
- High divergence warnings
- Velocity shifts (if enabled)
---
This open-source indicator is provided as-is for educational and trading purposes. No guarantees are made regarding trading performance. Users should conduct their own testing and validation before using in live trading.
Volume Profile & Smart Money Explorer🔍 Volume Profile & Smart Money Explorer: Decode Institutional Footprints
Master the art of institutional trading with this sophisticated volume analysis tool. Track smart money movements, identify peak liquidity windows, and align your trades with major market participants.
🌟 Key Features:
📊 Triple-Layer Volume Analysis
• Total Volume Patterns
• Directional Volume Split (Up/Down)
• Institutional Flow Detection
• Real-time Smart Money Tracking
• Historical Pattern Recognition
⚡ Smart Money Detection
• Institutional Trade Identification
• Large Block Order Tracking
• Smart Money Concentration Periods
• Whale Activity Alerts
• Volume Threshold Analysis
📈 Advanced Profiling
• Hourly Volume Distribution
• Directional Bias Analysis
• Liquidity Heat Maps
• Volume Pattern Recognition
• Custom Threshold Settings
🎯 Strategic Applications:
Institutional Trading:
• Track Big Player Movements
• Identify Accumulation/Distribution
• Follow Smart Money Flow
• Detect Institutional Trading Windows
• Monitor Block Orders
Risk Management:
• Identify High Liquidity Windows
• Avoid Thin Market Periods
• Optimize Position Sizing
• Track Market Participation
• Monitor Volume Quality
Market Analysis:
• Volume Pattern Recognition
• Smart Money Flow Analysis
• Liquidity Window Identification
• Institutional Activity Cycles
• Market Depth Analysis
💡 Perfect For:
• Professional Traders
• Volume Profile Traders
• Institutional Traders
• Risk Managers
• Algorithmic Traders
• Smart Money Followers
• Day Traders
• Swing Traders
📊 Key Metrics:
• Normalized Volume Profiles
• Institutional Thresholds
• Directional Volume Split
• Smart Money Concentration
• Historical Patterns
• Real-time Analysis
⚡ Trading Edge:
• Trade with Institution Flow
• Identify Optimal Entry Points
• Recognize Distribution Patterns
• Follow Smart Money Positioning
• Avoid Thin Markets
• Capitalize on Peak Liquidity
🎓 Educational Value:
• Understand Market Structure
• Learn Volume Analysis
• Master Institutional Patterns
• Develop Market Intuition
• Track Smart Money Flow
🛠️ Customization:
• Adjustable Time Windows
• Flexible Volume Thresholds
• Multiple Timeframe Analysis
• Custom Alert Settings
• Visual Preference Options
Whether you're tracking institutional flows in crypto markets or following smart money in traditional markets, the Volume Profile & Smart Money Explorer provides the deep insights needed to trade alongside the biggest players.
Transform your trading from retail guesswork to institutional precision. Know exactly when and where smart money moves, and position yourself ahead of major market shifts.
#VolumeProfile #SmartMoney #InstitutionalTrading #MarketAnalysis #TradingView #VolumeAnalysis #CryptoTrading #ForexTrading #TechnicalAnalysis #Trading #PriceAction #MarketStructure #OrderFlow #Liquidity #RiskManagement #TradingStrategy #DayTrading #SwingTrading #AlgoTrading #QuantitativeTrading
AMD Session Structure Levels# Market Structure & Manipulation Probability Indicator
## Overview
This advanced indicator is designed for traders who want a systematic approach to analyzing market structure, identifying manipulation, and assessing probability-based trade setups. It incorporates four core components:
### 1. Session Price Action Analysis
- Tracks **OHLC (Open, High, Low, Close)** within defined sessions.
- Implements a **dual tracking system**:
- **Official session levels** (fixed from the session open to close).
- **Real-time max/min tracking** to differentiate between temporary spikes and real price acceptance.
### 2. Market Manipulation Detection
- Identifies **manipulative price action** using the relationship between the open and close:
- If **price closes below open** → assumes **upward manipulation**, followed by **downward distribution**.
- If **price closes above open** → assumes **downward manipulation**, followed by **upward distribution**.
- Normalized using **ATR**, ensuring adaptability across different volatility conditions.
### 3. Probability Engine
- Tracks **historical wick ratios** to assess trend vs. reversal conditions.
- Calculates **conditional probabilities** for price moves.
- Uses a **special threshold system (0.45 and 0.03)** for reversal signals.
- Provides **real-time probability updates** to enhance trade decision-making.
### 4. Market Condition Classification
- Classifies market conditions using a **wick-to-body ratio**:
```pine
wick_to_body_ratio = open > close ? upper_wick / (high - low) : lower_wick / (high - low)
```
- **Low ratio (<0.25)** → Likely a **trend day**.
- **High ratio (>0.25)** → Likely a **range day**.
---
## Why This Indicator Stands Out
### ✅ Smarter Level Detection
- Uses **ATR-based dynamic levels** instead of static support/resistance.
- Differentiates **manipulation from distribution** for better decision-making.
- Updates probabilities **in real-time**.
### ✅ Memory-Efficient Design
- Implements **circular buffers** to maintain efficiency:
```pine
var float manipUp = array.new_float(lookbackPeriod, 0.0)
var float manipDown = array.new_float(lookbackPeriod, 0.0)
```
- Ensures **constant memory usage**, even over extended trading sessions.
### ✅ Advanced Probability Calculation
- Utilizes **conditional probabilities** instead of simple averages.
- Incorporates **market context** through wick analysis.
- Provides **actionable signals** via a probability table.
---
## Trading Strategy Guide
### **Best Entry Setups**
✅ Wait for **price to approach manipulation levels**.
✅ Confirm using the **probability table**.
✅ Check the **wick ratio for context**.
✅ Enter when **conditional probability aligns**.
### **Smart Exit Management**
✅ Use **distribution levels** as **profit targets**.
✅ Scale out **when probabilities shift**.
✅ Monitor **wick percentiles** for confirmation.
### **Risk Management**
✅ Size positions based on **probability readings**.
✅ Place stops at **manipulation levels**.
✅ Adjust position size based on **trend vs. range classification**.
---
## Configuration Tips
### **Session Settings**
```pine
sessionTime = input.session("0830-1500", "Session Hours")
weekDays = input.string("23456", "Active Days")
```
- Match these to your **primary trading session**.
- Adjust for different **market opens** if needed.
### **Analysis Parameters**
```pine
lookbackPeriod = input.int(50, "Lookback Period")
low_threshold = input.float(0.25, "Trend/Range Threshold")
```
- **50 periods** is a good starting point but can be optimized per instrument.
- The **0.25 threshold** is ideal for most markets but may need adjustments.
---
## Market Structure Breakdown
### **Trend/Continuation Days**
- **Characteristics:**
✅ Small **opposing wicks** (minimal counter-pressure).
✅ Clean, **directional price movement**.
- **Bullish Trend Day Example:**
✅ Small **lower wicks** (minimal downward pressure).
✅ Strong **closes near the highs** → **Buyers in control**.
- **Bearish Trend Day Example:**
✅ Small **upper wicks** (minimal upward pressure).
✅ Strong **closes near the lows** → **Sellers in control**.
### **Reversal Days**
- **Characteristics:**
✅ **Large opposing wicks** → Failed momentum in the initial direction.
- **Bullish Reversal Example:**
✅ **Large upper wick early**.
✅ **Strong close from the lows** → **Sellers failed to maintain control**.
- **Bearish Reversal Example:**
✅ **Large lower wick early**.
✅ **Weak close from the highs** → **Buyers failed to maintain control**.
---
## Summary
This indicator systematically quantifies market structure by measuring **manipulation, distribution, and probability-driven trade setups**. Unlike traditional indicators, it adapts dynamically using **ATR, historical probabilities, and real-time tracking** to offer a structured, data-driven approach to trading.
🚀 **Use this tool to enhance your decision-making and gain an objective edge in the market!**
Liquidations Zones [ChartPrime]The Liquidation Zones indicator is designed to detect potential liquidation zones based on common leverage levels such as 10x, 25x, 50x, and 100x. By calculating percentage distances from recent pivot points, the indicator shows where leveraged positions are most likely to get liquidated. It also tracks buy and sell volumes in these zones, helping traders assess market pressure and predict liquidation scenarios. Additionally, the indicator features a heat map mode to highlight areas where orders and stop-losses might be clustered.
⯁ KEY FEATURES AND HOW TO USE
⯌ Leverage Zones Detection :
The indicator identifies zones where positions with leverage ratios of 100x, 50x, 25x, and 10x are at risk of liquidation. These zones are based on percentage moves from recent pivots: a 1% move can liquidate 100x positions, a 4% move affects 25x positions, and so on.
⯌ Liquidated Zones and Volume Tracking :
The indicator displays liquidated zones by plotting gray areas where the price potentually liquidate positons. It calculates the volume needed to liquidate positions in these zones, showing volume from bullish candles if short positions were liquidated and volume from bearish candles for long positions. This feature helps traders assess the risk of liquidation as the price approaches these zones.
⯌ Buy/Sell Volume Calculation :
Buy and sell volumes are calculated from the most recent pivot high or low. For buy volume, only bullish candles are considered, while for sell volume, only bearish candles are summed. This data helps traders gauge the strength of potential liquidation in different zones.
Example of buy and sell volume tracking in active zones:
⯌ Liquidity Heat Map :
In heat map mode, the indicator visualizes potential liquidity areas where orders and stop-losses may be clustered. This map highlights zones that are likely to experience liquidations based on leverage ratios. Additionally, it tracks the highest and lowest price levels for the past 100 bars, while also displaying buy and sell volumes. This feature is useful for predicting market moves driven by liquidation events.
⯁ USER INPUTS
Length : Determines the number of bars used to calculate pivots for liquidation zones.
Extend : Controls how far the liquidation zones are extended on the chart.
Leverage Options : Toggle options to display zones for different leverage levels: 10x, 25x, 50x, and 100x.
Display Heat Map : Enables or disables the liquidity heat map feature.
⯁ CONCLUSION
The Liquidation Zones indicator provides a powerful tool for identifying potential liquidation zones, tracking volume pressure, and visualizing liquidity areas on the chart. With its real-time updates and multiple features, this indicator offers valuable insights for managing risk and anticipating market moves driven by leveraged positions.
Multi-Step FlexiMA - Strategy [presentTrading]It's time to come back! hope I can not to be busy for a while.
█ Introduction and How It Is Different
The FlexiMA Variance Tracker is a unique trading strategy that calculates a series of deviations between the price (or another indicator source) and a variable-length moving average (MA). Unlike traditional strategies that use fixed-length moving averages, the length of the MA in this system varies within a defined range. The length changes dynamically based on a starting factor and an increment factor, creating a more adaptive approach to market conditions.
This strategy integrates Multi-Step Take Profit (TP) levels, allowing for partial exits at predefined price increments. It enables traders to secure profits at different stages of a trend, making it ideal for volatile markets where taking full profits at once might lead to missed opportunities if the trend continues.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
🔶 FlexiMA Concept
The FlexiMA (Flexible Moving Average) is at the heart of this strategy. Unlike traditional MA-based strategies where the MA length is fixed (e.g., a 50-period SMA), the FlexiMA varies its length with each iteration. This is done using a **starting factor** and an **increment factor**.
The formula for the moving average length at each iteration \(i\) is:
`MA_length_i = indicator_length * (starting_factor + i * increment_factor)`
Where:
- `indicator_length` is the user-defined base length.
- `starting_factor` is the initial multiplier of the base length.
- `increment_factor` increases the multiplier in each iteration.
Each iteration applies a **simple moving average** (SMA) to the chosen **indicator source** (e.g., HLC3) with a different length based on the above formula. The deviation between the current price and the moving average is then calculated as follows:
`deviation_i = price_current - MA_i`
These deviations are normalized using one of the following methods:
- **Max-Min normalization**:
`normalized_i = (deviation_i - min(deviations)) / range(deviations)`
- **Absolute Sum normalization**:
`normalized_i = deviation_i / sum(|deviation_i|)`
The **median** and **standard deviation (stdev)** of the normalized deviations are then calculated as follows:
`median = median(normalized deviations)`
For the standard deviation:
`stdev = sqrt((1/(N-1)) * sum((normalized_i - mean)^2))`
These values are plotted to provide a clear indication of how the price is deviating from its variable-length moving averages.
For more detail:
🔶 Multi-Step Take Profit
This strategy uses a multi-step take profit system, allowing for exits at different stages of a trade based on the percentage of price movement. Three take-profit levels are defined:
- Take Profit Level 1 (TP1): A small, quick profit level (e.g., 2%).
- Take Profit Level 2 (TP2): A medium-level profit target (e.g., 8%).
- Take Profit Level 3 (TP3): A larger, more ambitious target (e.g., 18%).
At each level, a corresponding percentage of the trade is exited:
- TP Percent 1: E.g., 30% of the position.
- TP Percent 2: E.g., 20% of the position.
- TP Percent 3: E.g., 15% of the position.
This approach ensures that profits are locked in progressively, reducing the risk of market reversals wiping out potential gains.
Local
🔶 Trade Entry and Exit Conditions
The entry and exit signals are determined by the interaction between the **SuperTrend Polyfactor Oscillator** and the **median** value of the normalized deviations:
- Long entry: The SuperTrend turns bearish, and the median value of the deviations is positive.
- Short entry: The SuperTrend turns bullish, and the median value is negative.
Similarly, trades are exited when the SuperTrend flips direction.
* The SuperTrend Toolkit is made by @EliCobra
█ Trade Direction
The strategy allows users to specify the desired trade direction:
- Long: Only long positions will be taken.
- Short: Only short positions will be taken.
- Both: Both long and short positions are allowed based on the conditions.
This flexibility allows the strategy to adapt to different market conditions and trading styles, whether you're looking to buy low and sell high, or sell high and buy low.
█ Usage
This strategy can be applied across various asset classes, including stocks, cryptocurrencies, and forex. The primary use case is to take advantage of market volatility by using a flexible moving average and multiple take-profit levels to capture profits incrementally as the market moves in your favor.
How to Use:
1. Configure the Inputs: Start by adjusting the **Indicator Length**, **Starting Factor**, and **Increment Factor** to suit your chosen asset. The defaults work well for most markets, but fine-tuning them can improve performance.
2. Set the Take Profit Levels: Adjust the three **TP levels** and their corresponding **percentages** based on your risk tolerance and the expected volatility of the market.
3. Monitor the Strategy: The SuperTrend and the FlexiMA variance tracker will provide entry and exit signals, automatically managing the positions and taking profits at the pre-set levels.
█ Default Settings
The default settings for the strategy are configured to provide a balanced approach that works across different market conditions:
Indicator Length (10):
This controls the base length for the moving average. A lower length makes the moving average more responsive to price changes, while a higher length smooths out fluctuations, making the strategy less sensitive to short-term price movements.
Starting Factor (1.0):
This determines the initial multiplier applied to the moving average length. A higher starting factor will increase the average length, making it slower to react to price changes.
Increment Factor (1.0):
This increases the moving average length in each iteration. A larger increment factor creates a wider range of moving average lengths, allowing the strategy to track both short-term and long-term trends simultaneously.
Normalization Method ('None'):
Three methods of normalization can be applied to the deviations:
- None: No normalization applied, using raw deviations.
- Max-Min: Normalizes based on the range between the maximum and minimum deviations.
- Absolute Sum: Normalizes based on the total sum of absolute deviations.
Take Profit Levels:
- TP1 (2%): A quick exit to capture small price movements.
- TP2 (8%): A medium-term profit target for stronger trends.
- TP3 (18%): A long-term target for strong price moves.
Take Profit Percentages:
- TP Percent 1 (30%): Exits 30% of the position at TP1.
- TP Percent 2 (20%): Exits 20% of the position at TP2.
- TP Percent 3 (15%): Exits 15% of the position at TP3.
Effect of Variables on Performance:
- Short Indicator Lengths: More responsive to price changes but prone to false signals.
- Higher Starting Factor: Slows down the response, useful for longer-term trend following.
- Higher Increment Factor: Widens the variability in moving average lengths, making the strategy adapt to both short-term and long-term price trends.
- Aggressive Take Profit Levels: Allows for quick profit-taking in volatile markets but may exit positions prematurely in strong trends.
The default configuration offers a moderate balance between short-term responsiveness and long-term trend capturing, suitable for most traders. However, users can adjust these variables to optimize performance based on market conditions and personal preferences.
ICT Killzones and Sessions W/ Silver Bullet + MacrosForex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times
This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours.
Features:
Session and Killzone Lines:
Green: London Open (LO)
White: New York (NY)
Orange: Australian (AU)
Purple: Asian (AS)
Includes AM and PM session markers.
Dotted/Striped Lines indicate overlapping kill zones within the session timeline.
Customization Options:
Display sessions and killzones in collapsed or full view.
Hide specific sessions or killzones based on your preferences.
Customize colors, texts, and sizes.
Option to hide drawings older than the current day.
Automatic Updates:
The indicator draws all lines and boxes at the start of a new day.
Automatically adjusts time-based boxes according to the New York timezone.
Killzone Time Windows (for indices):
London KZ: 02:00 - 05:00
New York AM KZ: 07:00 - 10:00
New York PM KZ: 13:30 - 16:00
Silver Bullet Times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro Times:
02:33 - 03:00
04:03 - 04:30
08:50 - 09:10
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
Latest Update:
January 15:
Added option to automatically change text coloring based on the chart.
Included additional optional macro times per user request:
12:50 - 13:10
13:50 - 14:15
14:50 - 15:10
15:50 - 16:15
Usage:
To maximize your experience, minimize the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts.
Originality and Justification:
This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making.
Credits:
This script incorporates open-source elements with significant improvements to enhance functionality and user experience.
Forex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times
This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours.
Features:
Session and Killzone Lines:
Green: London Open (LO)
White: New York (NY)
Orange: Australian (AU)
Purple: Asian (AS)
Includes AM and PM session markers.
Dotted/Striped Lines indicate overlapping kill zones within the session timeline.
Customization Options:
Display sessions and killzones in collapsed or full view.
Hide specific sessions or killzones based on your preferences.
Customize colors, texts, and sizes.
Option to hide drawings older than the current day.
Automatic Updates:
The indicator draws all lines and boxes at the start of a new day.
Automatically adjusts time-based boxes according to the New York timezone.
Killzone Time Windows (for indices):
London KZ: 02:00 - 05:00
New York AM KZ: 07:00 - 10:00
New York PM KZ: 13:30 - 16:00
Silver Bullet Times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro Times:
02:33 - 03:00
04:03 - 04:30
08:50 - 09:10
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
Latest Update:
January 15:
Added option to automatically change text coloring based on the chart.
Included additional optional macro times per user request:
12:50 - 13:10
13:50 - 14:15
14:50 - 15:10
15:50 - 16:15
ICT Sessions and Kill Zones
What They Are:
ICT Sessions: These are specific times during the trading day when market activity is expected to be higher, such as the London Open, New York Open, and the Asian session.
Kill Zones: These are specific time windows within these sessions where the probability of significant price movements is higher. For example, the New York AM Kill Zone is typically from 8:30 AM to 11:00 AM EST.
How to Use Them:
Identify the Session: Determine which trading session you are in (London, New York, or Asian).
Focus on Kill Zones: Within that session, focus on the kill zones for potential trade setups. For instance, during the New York session, look for setups between 8:30 AM and 11:00 AM EST.
Silver Bullets
What They Are:
Silver Bullets: These are specific, high-probability trade setups that occur within the kill zones. They are designed to be "one shot, one kill" trades, meaning they aim for precise and effective entries and exits.
How to Use Them:
Time-Based Setup: Look for these setups within the designated kill zones. For example, between 10:00 AM and 11:00 AM for the New York AM session .
Chart Analysis: Start with higher time frames like the 15-minute chart and then refine down to 5-minute and 1-minute charts to identify imbalances or specific patterns .
Macros
What They Are:
Macros: These are broader market conditions and trends that influence your trading decisions. They include understanding the overall market direction, seasonal tendencies, and the Commitment of Traders (COT) reports.
How to Use Them:
Understand Market Conditions: Be aware of the macroeconomic factors and market conditions that could affect price movements.
Seasonal Tendencies: Know the seasonal patterns that might influence the market direction.
COT Reports: Use the Commitment of Traders reports to understand the positioning of large traders and commercial hedgers .
Putting It All Together
Preparation: Understand the macro conditions and review the COT reports.
Session and Kill Zone: Identify the trading session and focus on the kill zones.
Silver Bullet Setup: Look for high-probability setups within the kill zones using refined chart analysis.
Execution: Execute the trade with precision, aiming for a "one shot, one kill" outcome.
By following these steps, you can effectively use ICT sessions, kill zones, silver bullets, and macros to enhance your trading strategy.
Usage:
To maximize your experience, shrink the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts.
Originality and Justification:
This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making.
Credits:
This script incorporates open-source elements with significant improvements to enhance functionality and user experience. All credit goes to itradesize for the SB + Macro boxes
Heikin Ashi RSI + OTT [Erebor]Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a popular momentum oscillator used in technical analysis to measure the speed and change of price movements. Developed by J. Welles Wilder, the RSI is calculated using the average gains and losses over a specified period, typically 14 days. Here's how it works:
Description and Calculation:
1. Average Gain and Average Loss Calculation:
- Calculate the average gain and average loss over the chosen period (e.g., 14 days).
- The average gain is the sum of gains divided by the period, and the average loss is the sum of losses divided by the period.
2. Relative Strength (RS) Calculation:
- The relative strength is the ratio of average gain to average loss.
The RSI oscillates between 0 and 100. Traditionally, an RSI above 70 indicates overbought conditions, suggesting a potential sell signal, while an RSI below 30 suggests oversold conditions, indicating a potential buy signal.
Pros of RSI:
- Identifying Overbought and Oversold Conditions: RSI helps traders identify potential reversal points in the market due to overbought or oversold conditions.
- Confirmation Tool: RSI can be used in conjunction with other technical indicators or chart patterns to confirm signals, enhancing the reliability of trading decisions.
- Versatility: RSI can be applied to various timeframes, from intraday to long-term charts, making it adaptable to different trading styles.
Cons of RSI:
- Whipsaws: In ranging markets, RSI can generate false signals, leading to whipsaws (rapid price movements followed by a reversal).
- Not Always Accurate: RSI may give false signals, especially in strongly trending markets where overbought or oversold conditions persist for extended periods.
- Subjectivity: Interpretation of RSI levels (e.g., 70 for overbought, 30 for oversold) is somewhat subjective and can vary depending on market conditions and individual preferences.
Checking RSIs in Different Periods:
Traders often use multiple timeframes to analyze RSI for a more comprehensive view:
- Fast RSI (e.g., 8-period): Provides more sensitive signals, suitable for short-term trading and quick decision-making.
- Slow RSI (e.g., 32-period): Offers a smoother representation of price movements, useful for identifying longer-term trends and reducing noise.
By comparing RSI readings across different periods, traders can gain insights into the momentum and strength of price movements over various timeframes, helping them make more informed trading decisions. Additionally, divergence between fast and slow RSI readings may signal potential trend reversals or continuation patterns.
Heikin Ashi Candles
Let's consider a modification to the traditional “Heikin Ashi Candles” where we introduce a new parameter: the period of calculation. The traditional HA candles are derived from the open 01, high 00 low 00, and close 00 prices of the underlying asset.
Now, let's introduce a new parameter, period, which will determine how many periods are considered in the calculation of the HA candles. This period parameter will affect the smoothing and responsiveness of the resulting candles.
In this modification, instead of considering just the current period, we're averaging or aggregating the prices over a specified number of periods . This will result in candles that reflect a longer-term trend or sentiment, depending on the chosen period value.
For example, if period is set to 1, it would essentially be the same as traditional Heikin Ashi candles. However, if period is set to a higher value, say 5, each candle will represent the average price movement over the last 5 periods, providing a smoother representation of the trend but potentially with delayed signals compared to lower period values.
Traders can adjust the period parameter based on their trading style, the timeframe they're analyzing, and the level of smoothing or responsiveness they prefer in their candlestick patterns.
Optimized Trend Tracker
The "Optimized Trend Tracker" is a proprietary trading indicator developed by TradingView user ANIL ÖZEKŞİ. It is designed to identify and track trends in financial markets efficiently. The indicator attempts to smooth out price fluctuations and provide clear signals for trend direction.
The Optimized Trend Tracker uses a combination of moving averages and adaptive filters to detect trends. It aims to reduce lag and noise typically associated with traditional moving averages, thereby providing more timely and accurate signals.
Some of the key features and applications of the OTT include:
• Trend Identification: The indicator helps traders identify the direction of the prevailing trend in a market. It distinguishes between uptrends, downtrends, and sideways consolidations.
• Entry and Exit Signals: The OTT generates buy and sell signals based on crossovers and direction changes of the trend. Traders can use these signals to time their entries and exits in the market.
• Trend Strength: It also provides insights into the strength of the trend by analyzing the slope and momentum of price movements. This information can help traders assess the conviction behind the trend and adjust their trading strategies accordingly.
• Filter Noise: By employing adaptive filters, the indicator aims to filter out market noise and false signals, thereby enhancing the reliability of trend identification.
• Customization: Traders can customize the parameters of the OTT to suit their specific trading preferences and market conditions. This flexibility allows for adaptation to different timeframes and asset classes.
Overall, the OTT can be a valuable tool for traders seeking to capitalize on trending market conditions while minimizing false signals and noise. However, like any trading indicator, it is essential to combine its signals with other forms of analysis and risk management strategies for optimal results. Additionally, traders should thoroughly back-test the indicator and practice using it in a demo environment before applying it to live trading.
The following types of moving average have been included: "SMA", "EMA", "SMMA (RMA)", "WMA", "VWMA", "HMA", "KAMA", "LSMA", "TRAMA", "VAR", "DEMA", "ZLEMA", "TSF", "WWMA". Thanks to the authors.
Thank you for your indicator “Optimized Trend Tracker”. © kivancozbilgic
Thank you for your programming language, indicators and strategies. © TradingView
Kind regards.
© Erebor_GIT
Heikin Ashi TSI and OTT [Erebor]TSI (True Strength Index)
The TSI (True Strength Index) is a momentum-based trading indicator used to identify trend direction, overbought/oversold conditions, and potential trend reversals in financial markets. It was developed by William Blau and first introduced in 1991.
Here's how the TSI indicator is calculated:
• Double Smoothed Momentum (DM): This is calculated by applying double smoothing to the price momentum. First, the single smoothed momentum is calculated by subtracting the smoothed closing price from the current closing price. Then, this single smoothed momentum is smoothed again using an additional smoothing period.
• Absolute Smoothed Momentum (ASM): This is calculated by applying smoothing to the absolute value of the price momentum. Similar to DM, ASM applies a smoothing period to the absolute value of the difference between the current closing price and the smoothed closing price.
• TSI Calculation: The TSI is calculated as the ratio of DM to ASM, multiplied by 100 to express it as a percentage. Mathematically, TSI = (DM / ASM) * 100.
The TSI indicator oscillates around a centerline (typically at zero), with positive values indicating bullish momentum and negative values indicating bearish momentum. Traders often look for crossovers of the TSI above or below the centerline to identify shifts in momentum and potential trend reversals. Additionally, divergences between price and the TSI can signal weakening trends and potential reversal points.
Pros of the TSI indicator:
• Smoothed Momentum: The TSI uses double smoothing techniques, which helps to reduce noise and generate smoother signals compared to other momentum indicators.
• Versatility: The TSI can be applied to various financial instruments and timeframes, making it suitable for both short-term and long-term trading strategies.
• Trend Identification: The TSI is effective in identifying the direction and strength of market trends, helping traders to align their positions with the prevailing market sentiment.
Cons of the TSI indicator:
• Lagging Indicator: Like many momentum indicators, the TSI is a lagging indicator, meaning it may not provide timely signals for entering or exiting trades during rapidly changing market conditions.
• False Signals: Despite its smoothing techniques, the TSI can still produce false signals, especially during periods of low volatility or ranging markets.
• Subjectivity: Interpretation of the TSI signals may vary among traders, leading to subjective analysis and potential inconsistencies in trading decisions.
Overall, the TSI indicator can be a valuable tool for traders when used in conjunction with other technical analysis tools and risk management strategies. It can help traders identify potential trading opportunities and confirm trends, but it's essential to consider its limitations and incorporate additional analysis for more robust trading decisions.
Heikin Ashi Candles
Let's consider a modification to the traditional “Heikin Ashi Candles” where we introduce a new parameter: the period of calculation. The traditional HA candles are derived from the open , high low , and close prices of the underlying asset.
Now, let's introduce a new parameter, period, which will determine how many periods are considered in the calculation of the HA candles. This period parameter will affect the smoothing and responsiveness of the resulting candles.
In this modification, instead of considering just the current period, we're averaging or aggregating the prices over a specified number of periods . This will result in candles that reflect a longer-term trend or sentiment, depending on the chosen period value.
For example, if period is set to 1, it would essentially be the same as traditional Heikin Ashi candles. However, if period is set to a higher value, say 5, each candle will represent the average price movement over the last 5 periods, providing a smoother representation of the trend but potentially with delayed signals compared to lower period values.
Traders can adjust the period parameter based on their trading style, the timeframe they're analyzing, and the level of smoothing or responsiveness they prefer in their candlestick patterns.
Optimized Trend Tracker
The "Optimized Trend Tracker" is a proprietary trading indicator developed by TradingView user ANIL ÖZEKŞİ. It is designed to identify and track trends in financial markets efficiently. The indicator attempts to smooth out price fluctuations and provide clear signals for trend direction.
The Optimized Trend Tracker uses a combination of moving averages and adaptive filters to detect trends. It aims to reduce lag and noise typically associated with traditional moving averages, thereby providing more timely and accurate signals.
Some of the key features and applications of the OTT include:
• Trend Identification: The indicator helps traders identify the direction of the prevailing trend in a market. It distinguishes between uptrends, downtrends, and sideways consolidations.
• Entry and Exit Signals: The OTT generates buy and sell signals based on crossovers and direction changes of the trend. Traders can use these signals to time their entries and exits in the market.
• Trend Strength: It also provides insights into the strength of the trend by analyzing the slope and momentum of price movements. This information can help traders assess the conviction behind the trend and adjust their trading strategies accordingly.
• Filter Noise: By employing adaptive filters, the indicator aims to filter out market noise and false signals, thereby enhancing the reliability of trend identification.
• Customization: Traders can customize the parameters of the OTT to suit their specific trading preferences and market conditions. This flexibility allows for adaptation to different timeframes and asset classes.
Overall, the OTT can be a valuable tool for traders seeking to capitalize on trending market conditions while minimizing false signals and noise. However, like any trading indicator, it is essential to combine its signals with other forms of analysis and risk management strategies for optimal results. Additionally, traders should thoroughly back-test the indicator and practice using it in a demo environment before applying it to live trading.
The following types of moving average have been included: "SMA", "EMA", "SMMA (RMA)", "WMA", "VWMA", "HMA", "KAMA", "LSMA", "TRAMA", "VAR", "DEMA", "ZLEMA", "TSF", "WWMA". Thanks to the authors.
Thank you for your indicator “Optimized Trend Tracker”. © kivancozbilgic
Thank you for your programming language, indicators and strategies. © TradingView
Kind regards.
© Erebor_GIT
Portfolio_Tracking_TRThis is a portfolio tracker that will track individual, overall and daily profit/loss for up. You can set the size of your buys and price of your buys for accurate, up to date profit and loss data right on your chart. It works on all markets and timeframes.
Next we get into setting up your , order size and price. Each ticker lets you set which stock you bought, then set how much you purchased and then what price you purchased them at.
FEATURES
Top Section
The portfolio tracker has 2 sections. The top section shows each ticker in your portfolio individually with the following data:
- Ticker Name
- Weight of that asset compared to your total portfolio in %
- Current value of that position in TL
- Profit or loss value from purchase price in %
- Todays change in value from yesterday’s close in %
Bottom Section
The bottom section of the tracker will give you info for your portfolio as a whole. It has the following data:
- Total cost of your entire portfolio in TL
- Current value of your entire portfolio in TL
- Current profit or loss of your entire portfolio in TL
- Current profit or loss of your entire portfolio in %
- Todays change of your entire portfolio value compared to yesterday’s close in %
This indicator was compiled from FriendOfTheTrend's indicator named Portfolio Tracker For Stocks & Crypto.
ORB FX REPLAY - FINAL SAFEHere is the description in English, written to sound professional and meet all the requirements for publishing on TradingView:
Script Description:
Title: ORB Strategy Backtest Pro - Ultra Compatibility
Description: This is an Opening Range Breakout (ORB) strategy specifically designed for professional backtesting. It is optimized to run smoothly on external platforms like FX Replay and TradingView's replay mode.
Key Features:
Custom Session: Automatically calculates the High and Low of a specific time window (default: 10:00 - 10:15 Bucharest/GMT+2).
Impulse Confirmation: Features a "Min Impulse" filter to ensure entries happen on strong momentum, avoiding "fake-outs" near the range boundaries.
Hard Target Management: Designed for "Set & Forget" backtesting. Once a trade is triggered, the script tracks it until it hits either the Stop Loss (SL) or the final Take Profit 3 (TP3).
Visual Projections: Draws clear, real-time lines for Entry, SL, and TP3 on the chart for easy visual tracking.
Automated Statistics: Includes a dynamic label system that tracks Total Trades, Win Count, and Loss Count based on the TP3/SL logic.
Optimized Code: Built using Pine Script v5 with a focus on stability and compatibility, avoiding complex tables that often cause errors on external engines.
Liquidity Void Zone Detector [PhenLabs]📊 Liquidity Void Zone Detector
Version: PineScript™v6
📌 Description
The Liquidity Void Zone Detector is a sophisticated technical indicator designed to identify and visualize areas where price moved with abnormally low volume or rapid momentum, creating "voids" in market liquidity. These zones represent areas where insufficient trading activity occurred during price movement, often acting as magnets for future price action as the market seeks to fill these gaps.
Built on PineScript v6, this indicator employs a dual-detection methodology that analyzes both volume depletion patterns and price movement intensity relative to ATR. The revolutionary 3D visualization system uses three-layer polyline rendering with adaptive transparency and vertical offsets, creating genuine depth perception where low liquidity zones visually recede and high liquidity zones protrude forward. This makes critical market structure immediately apparent without cluttering your chart.
🚀 Points of Innovation
Dual detection algorithm combining volume threshold analysis and ATR-normalized price movement sensitivity for comprehensive void identification
Three-layer 3D visualization system with progressive transparency gradients (85%, 78%, 70%) and calculated vertical offsets for authentic depth perception
Intelligent state machine logic that tracks consecutive void bars and only renders zones meeting minimum qualification requirements
Dynamic strength scoring system (0-100 scale) that combines inverted volume ratios with movement intensity for accurate void characterization
Adaptive ATR-based spacing calculation that automatically adjusts 3D layering depth to match instrument volatility
Efficient memory management system supporting up to 100 simultaneous void visualizations with automatic array-based cleanup
🔧 Core Components
Volume Analysis Engine: Calculates rolling volume averages and compares current bar volume against dynamic thresholds to detect abnormally thin trading conditions
Price Movement Analyzer: Normalizes bar range against ATR to identify rapid price movements that indicate liquidity exhaustion regardless of instrument or timeframe
Void Tracking State Machine: Maintains persistent tracking of void start bars, price boundaries, consecutive bar counts, and cumulative strength across multiple bars
3D Polyline Renderer: Generates three-layer rectangular polylines with precise timestamp-to-bar index conversion and progressive offset calculations
Strength Calculation System: Combines volume component (inverted ratio capped at 100) with movement component (ATR intensity × 30) for comprehensive void scoring
🔥 Key Features
Automatic Void Detection: Continuously scans price action for low volume conditions or rapid movements, triggering void tracking when thresholds are exceeded
Real-Time Visualization: Creates 3D rectangular zones spanning from void initiation to termination, with color-coded depth indicating liquidity type
Adjustable Sensitivity: Configure volume threshold multiplier (0.1-2.0x), price movement sensitivity (0.5-5.0x), and minimum qualifying bars (1-10) for customized detection
Dual Color Coding: Separate visual treatment for low liquidity voids (receding red) and high liquidity zones (protruding green) based on 50-point strength threshold
Optional Compact Labels: Toggle LV (Low Volume) or HV (High Volume) circular labels at void centers for quick identification without visual clutter
Lookback Period Control: Adjust analysis window from 5 to 100 bars to match your trading timeframe and market volatility characteristics
Memory-Efficient Design: Automatically manages polyline and label arrays, deleting oldest elements when user-defined maximum is reached
Data Window Integration: Plots void detection binary, current strength score, and average volume for detailed analysis in TradingView's data window
🎨 Visualization
Three-Layer Depth System: Each void is rendered as three stacked polylines with progressive transparency (85%, 78%, 70%) and calculated vertical offsets creating authentic 3D appearance
Directional Depth Perception: Low liquidity zones recede with back layer most transparent; high liquidity zones protrude with front layer most transparent for instant visual differentiation
Adaptive Offset Spacing: Vertical separation between layers calculated as ATR(14) × 0.001, ensuring consistent 3D effect across different instruments and volatility regimes
Color Customization: Fully configurable base colors for both low liquidity zones (default: red with 80 transparency) and high liquidity zones (default: green with 80 transparency)
Minimal Chart Clutter: Closed polylines with matching line and fill colors create clean rectangular zones without unnecessary borders or visual noise
Background Highlight: Subtle yellow background (96% transparency) marks bars where void conditions are actively detected in real-time
Compact Labeling: Optional tiny circular labels with 60% transparent backgrounds positioned at void center points for quick reference
📖 Usage Guidelines
Detection Settings
Lookback Period: Default: 10 | Range: 5-100 | Number of bars analyzed for volume averaging and void detection. Lower values increase sensitivity to recent changes; higher values smooth detection across longer timeframes. Adjust based on your trading timeframe: short-term traders use 5-15, swing traders use 20-50, position traders use 50-100.
Volume Threshold: Default: 1.0 | Range: 0.1-2.0 (step 0.1) | Multiplier applied to average volume. Bars with volume below (average × threshold) trigger void conditions. Lower values detect only extreme volume depletion; higher values capture more moderate low-volume situations. Start with 1.0 and decrease to 0.5-0.7 for stricter detection.
Price Movement Sensitivity: Default: 1.5 | Range: 0.5-5.0 (step 0.1) | Multiplier for ATR-normalized price movement detection. Values above this threshold indicate rapid price changes suggesting liquidity voids. Increase to 2.0-3.0 for volatile instruments; decrease to 0.8-1.2 for ranging or low-volatility conditions.
Minimum Void Bars: Default: 10 | Range: 1-10 | Minimum consecutive bars exhibiting void conditions required before visualization is created. Filters out brief anomalies and ensures only sustained voids are displayed. Use 1-3 for scalping, 5-10 for intraday trading, 10+ for swing trading to match your time horizon.
Visual Settings
Low Liquidity Color: Default: Red (80% transparent) | Base color for zones where volume depletion or rapid movement indicates thin liquidity. These zones recede visually (back layer most transparent). Choose colors that contrast with your chart theme for optimal visibility.
High Liquidity Color: Default: Green (80% transparent) | Base color for zones with relatively higher liquidity compared to void threshold. These zones protrude visually (front layer most transparent). Ensure clear differentiation from low liquidity color.
Show Void Labels: Default: True | Toggle display of compact LV/HV labels at void centers. Disable for cleaner charts when trading; enable for analysis and review to quickly identify void types across your chart.
Max Visible Voids: Default: 50 | Range: 10-100 | Maximum number of void visualizations kept on chart. Each void uses 3 polylines, so setting of 50 maintains 150 total polylines. Higher values preserve more history but may impact performance on lower-end systems.
✅ Best Use Cases
Gap Fill Trading: Identify unfilled liquidity voids that price frequently returns to, providing high-probability retest and reversal opportunities when price approaches these zones
Breakout Validation: Distinguish genuine breakouts through established liquidity from false breaks into void zones that lack sustainable volume support
Support/Resistance Confluence: Layer void detection over key horizontal levels to validate structural integrity—levels within high liquidity zones are stronger than those in voids
Trend Continuation: Monitor for new void formation in trend direction as potential continuation zones where price may accelerate due to reduced resistance
Range Trading: Identify void zones within consolidation ranges that price tends to traverse quickly, helping to avoid getting caught in rapid moves through thin areas
Entry Timing: Wait for price to reach void boundaries rather than entering mid-void, as voids tend to be traversed quickly with limited profit-taking opportunities
⚠️ Limitations
Historical Pattern Indicator: Identifies past liquidity voids but cannot predict whether price will return to fill them or when filling might occur
No Volume on Forex: Indicator uses tick volume for forex pairs, which approximates but doesn't represent true trading volume, potentially affecting detection accuracy
Lagging Confirmation: Requires minimum consecutive bars (default 10) before void is visualized, meaning detection occurs after void formation begins
Trending Market Behavior: Strong trends driven by fundamental catalysts may create voids that remain unfilled for extended periods or permanently
Timeframe Dependency: Detection sensitivity varies significantly across timeframes; settings optimized for one timeframe may not perform well on others
No Directional Bias: Indicator identifies liquidity characteristics but provides no predictive signal for price direction after void detection
Performance Considerations: Higher max visible void settings combined with small minimum void bars can generate numerous visualizations impacting chart rendering speed
💡 What Makes This Unique
Industry-First 3D Visualization: Unlike flat volume or liquidity indicators, the three-layer rendering with directional depth perception provides instant visual hierarchy of liquidity quality
Dual-Mode Detection: Combines both volume-based and movement-based detection methodologies, capturing voids that single-approach indicators miss
Intelligent Qualification System: State machine logic prevents premature visualization by requiring sustained void conditions, reducing false signals and chart clutter
ATR-Normalized Analysis: All detection thresholds adapt to instrument volatility, ensuring consistent performance across stocks, forex, crypto, and futures without constant recalibration
Transparency-Based Depth: Uses progressive transparency gradients rather than colors or patterns to create depth, maintaining visual clarity while conveying information hierarchy
Comprehensive Strength Metrics: 0-100 void strength calculation considers both the degree of volume depletion and the magnitude of price movement for nuanced zone characterization
🔬 How It Works
Phase 1: Real-Time Detection
On each bar close, the indicator calculates average volume over the lookback period and compares current bar volume against the volume threshold multiplier
Simultaneously measures current bar's high-low range and normalizes it against ATR, comparing the result to price movement sensitivity parameter
If either volume falls below threshold OR movement exceeds sensitivity threshold, the bar is flagged as exhibiting void characteristics
Phase 2: Void Tracking & Qualification
When void conditions first appear, state machine initializes tracking variables: start bar index, initial top/bottom prices, consecutive bar counter, and cumulative strength accumulator
Each subsequent bar with void conditions extends the tracking, updating price boundaries to envelope all bars and accumulating strength scores
When void conditions cease, system checks if consecutive bar count meets minimum threshold; if yes, proceeds to visualization; if no, discards the tracking and resets
Phase 3: 3D Visualization Construction
Calculates average void strength by dividing cumulative strength by number of bars, then determines if void is low liquidity (>50 strength) or high liquidity (≤50 strength)
Generates three polyline layers spanning from start bar to end bar and from top price to bottom price, each with calculated vertical offset based on ATR
Applies progressive transparency (85%, 78%, 70%) with layer ordering creating recession effect for low liquidity zones and protrusion effect for high liquidity zones
Creates optional center label and pushes all visual elements into arrays for memory management
Phase 4: Memory Management & Display
Continuously monitors polyline array size (each void creates 3 polylines); when total exceeds max visible voids × 3, deletes oldest polylines via array.shift()
Similarly manages label array, removing oldest labels when count exceeds maximum to prevent memory accumulation over extended chart history
Plots diagnostic data to TradingView’s data window (void detection binary, current strength, average volume) for detailed analysis without cluttering main chart
💡 Note:
This indicator is designed to enhance your market structure analysis by revealing liquidity characteristics that aren’t visible through standard price and volume displays. For best results, combine void detection with your existing support/resistance analysis, trend identification, and risk management framework. Liquidity voids are descriptive of past market behavior and should inform positioning decisions rather than serve as standalone entry/exit signals. Experiment with detection parameters across different timeframes to find settings that align with your trading style and instrument characteristics.
Global M2 Money Supply Growth (GDP-Weighted)📊 Global M2 Money Supply Growth (GDP-Weighted)
This indicator tracks the weighted aggregate M2 money supply growth across the world's four largest economies: United States, China, Eurozone, and Japan. These economies represent approximately 69.3 trillion USD in combined GDP and account for the majority of global liquidity, making this a comprehensive macro indicator for analyzing worldwide monetary conditions.
════════════════════════════════════════════
🔧 KEY FEATURES:
📈 GDP-Weighted Aggregation
Each economy is weighted proportionally by its nominal GDP using 2025 IMF World Economic Outlook data:
• United States: 44.2% (30.62 trillion USD)
• China: 28.0% (19.40 trillion USD)
• Eurozone: 21.6% (15.0 trillion USD)
• Japan: 6.2% (4.28 trillion USD)
The weights are fully adjustable through the indicator settings, allowing you to update them annually as new IMF forecasts are released (typically April and October).
⏱️ Multiple Time Period Options
Choose between three calculation methods to analyze different timeframes:
• YoY (Year-over-Year): 12-month growth rate for identifying long-term liquidity trends and cycles
• MoM (Month-over-Month): 1-month growth rate for detecting short-term monetary policy shifts
• QoQ (Quarter-over-Quarter): 3-month growth rate for medium-term trend analysis
🔄 Advanced Offset Function
Shift the entire indicator forward by 0-365 days to test lead/lag relationships between global liquidity and asset prices. Research suggests a 56-70 day lag between M2 changes and Bitcoin price movements, but you can experiment with different offsets for various assets (equities, gold, commodities, etc.).
🌍 Individual Country Breakdown
Real-time display of each economy's M2 growth rate with:
• Current percentage change (YoY/MoM/QoQ)
• GDP weight contribution
• Color-coded values (green = monetary expansion, red = contraction)
📊 Smart Overlay Capability
Displays directly on your main price chart with an independent left-side scale, allowing you to visually correlate global liquidity trends with any asset's price action without cluttering the chart.
🔧 Customizable GDP Weights
All GDP values can be adjusted through the indicator settings without editing code, making annual updates simple and accessible for all users.
════════════════════════════════════════════
📡 DATA SOURCES:
All M2 money supply data is sourced from ECONOMICS (Trading Economics) for consistency and reliability:
• ECONOMICS:USM2 (United States)
• ECONOMICS:CNM2 (China)
• ECONOMICS:EUM2 (Eurozone)
• ECONOMICS:JPM2 (Japan)
All values are normalized to USD using current daily exchange rates (USDCNY, EURUSD, USDJPY) before GDP-weighted aggregation, ensuring accurate cross-country comparisons.
══════════════════════════════════════════════
💡 USE CASES & APPLICATIONS:
🔹 Liquidity Cycle Analysis
Track global monetary expansion/contraction cycles to identify when central banks are coordinating loose or tight monetary policies.
🔹 Market Timing & Risk Assessment
High M2 growth (>10%) historically correlates with risk-on environments and rising asset prices across crypto, equities, and commodities. Negative M2 growth signals monetary tightening and potential market corrections.
🔹 Bitcoin & Crypto Correlation
Compare with Bitcoin price using the offset feature to identify the optimal lag period. Many traders use 60-70 day offsets to predict crypto market movements based on liquidity changes.
🔹 Macro Portfolio Allocation
Use as a regime filter to adjust portfolio exposure: increase risk assets during liquidity expansion, reduce during contraction.
🔹 Central Bank Policy Divergence
Monitor individual country metrics to identify when major central banks are pursuing divergent policies (e.g., Fed tightening while China eases).
🔹 Inflation & Economic Forecasting
Rapid M2 growth often leads inflation by 12-18 months, making this a leading indicator for future inflation trends.
🔹 Recession Early Warning
Negative M2 growth is extremely rare and has preceded major recessions, making this a valuable risk management tool.
════════════════════════════════════════════
📊 INTERPRETATION GUIDE:
🟢 +10% or Higher
Aggressive monetary expansion, typically during crises (2001, 2008, 2020). The COVID-19 period saw M2 growth reach 20-27%, which preceded significant inflation and asset price surges. Strong bullish signal for risk assets.
🟢 +6% to +10%
Above-average liquidity growth. Central banks are providing stimulus beyond normal levels. Generally favorable for equities, crypto, and commodities.
🟡 +3% to +6%
Normal/healthy growth rate, roughly in line with GDP growth plus 2% inflation targets. Neutral environment with moderate support for risk assets.
🟠 0% to +3%
Slowing liquidity, potential tightening phase beginning. Central banks may be raising rates or reducing balance sheets. Caution warranted for high-beta assets.
🔴 Negative Growth
Monetary contraction - extremely rare. Only occurred during aggressive Fed tightening in 2022-2023. Strong warning signal for risk assets, often precedes recessions or major market corrections.
════════════════════════════════════════════
🎯 OPTIMAL USAGE:
📅 Recommended Timeframes:
• Daily or Weekly charts for macro analysis
• Monthly charts for very long-term trends
💹 Compatible Asset Classes:
• Cryptocurrencies (especially Bitcoin, Ethereum)
• Equity indices (S&P 500, NASDAQ, global markets)
• Commodities (Gold, Silver, Oil)
• Forex majors (DXY correlation analysis)
⚙️ Suggested Settings:
• Default: YoY calculation with 0 offset for current liquidity conditions
• Bitcoin traders: YoY with 60-70 day offset for predictive analysis
• Short-term traders: MoM with 0 offset for recent policy changes
• Quarterly rebalancers: QoQ with 0 offset for medium-term trends
════════════════════════════════════════════
📋 VISUAL DISPLAY:
The indicator plots a blue line showing the selected growth metric (YoY/MoM/QoQ), with a dashed reference line at 0% to clearly identify expansion vs. contraction regimes.
A comprehensive table in the top-right corner displays:
• Current global M2 growth rate (large, prominent display)
• Individual country breakdowns with their GDP weights
• Color-coded growth rates (green for positive, red for negative)
════════════════════════════════════════════
🔄 MAINTENANCE & UPDATES:
GDP weights should be updated annually (ideally in April or October) when the IMF releases new World Economic Outlook forecasts. Simply adjust the four GDP input parameters in the indicator settings - no code editing required.
The relative GDP proportions between the Big 4 economies change very gradually (typically <1-2% per year), so even if you update weights once every 1-2 years, the impact on the indicator's accuracy is minimal.
════════════════════════════════════════════
💭 TRADING PHILOSOPHY:
This indicator embodies the principle that "liquidity drives markets." By tracking the combined M2 money supply of the world's largest economies, weighted by their economic size, you gain insight into the fundamental liquidity conditions that underpin all asset prices.
Unlike single-country M2 indicators, this GDP-weighted approach captures the true global picture, accounting for the fact that US monetary policy has 2x the impact of Japanese policy due to economic size differences.
Perfect for macro-focused traders, long-term investors, and anyone seeking to understand the "tide that lifts all boats" in financial markets.
════════════════════════════════════════════
Created for traders and investors who incorporate global liquidity trends into their decision-making process. Best used alongside other technical and fundamental analysis tools for comprehensive market assessment.
⚠️ Disclaimer: M2 money supply is a lagging macroeconomic indicator. Past correlations do not guarantee future results. Always use proper risk management and combine with other analysis methods.
Price Drop CounterThe Price Drop Counter is a very basic statistical indicator.
See it as an analytical tool that tracks how many times an asset's price has dropped by a specified percentage from its recent peak within a defined date range.
The indicator monitors the highest price reached and counts each occurrence when the price falls by your chosen threshold, then resets its peak tracking point after each drop is registered.
Uses
Volatility Assessment: Measure how frequently significant price corrections occur during specific periods
Market Behavior Analysis: Compare drop frequency across different timeframes or market conditions
Risk Evaluation: Identify assets or periods with higher downside volatility
Historical Pattern Recognition: Study how often major pullbacks happened during bull or bear markets
Backtesting Support: Analyze how your strategy would perform based on the frequency of drawdowns
How to use it
Add the indicator to your TradingView chart
Configure the Percent Drop (%) to define your threshold (default: 10%). The indicator will count each time price falls by this percentage from the most recent high
IMPORTANT Set your Start Date and End Date to analyze a specific period of interest
The blue step-line plot shows the cumulative count of drops within your date range
Adjust the percentage threshold based on your analysis needs - use smaller values (2-5%) for more frequent signals or larger values (15-20%) for major corrections only
The counter resets its high-water mark after each qualifying drop, allowing it to track multiple sequential drops within the same period.
macd sma20
### MACD_sma20 – Multi-Timeframe MACD Pullback & SMA20 Dashboard
This script is a complete trading toolkit built around a **MACD pullback strategy** combined with **multi-timeframe SMA20 filters**, volume analysis, and a compact information panel.
It is designed for traders who like to:
* Trade **MACD pullbacks above the moving average**
* Track **key SMA20 levels across multiple timeframes** (Daily, 3-Day, Weekly, Monthly)
* Quickly see whether **current price is above or below those reference levels**
* Use **clean visual signals** for entries and exits, instead of staring at raw indicator values
---
### Core Features
#### 1. MACD Pullback Long Signal (Green Triangle Up)
The script detects a **bullish MACD pullback** pattern:
* MACD line is still **above** the signal line
* Both MACD line and histogram **pull back** for several bars
* Then MACD turns back up again, with price trading **above the local SMA20**
When this “pullback and re-acceleration” is confirmed, a **green triangle below the bar** is plotted as a **long entry signal**.
There is also an optional filter:
* **Weekly SMA20 filter**:
If enabled, long signals are only triggered when **current price is above the Weekly SMA20**, helping you stay on the right side of the higher-timeframe trend.
---
#### 2. Bearish Pullback Confirmation Signal (Red Triangle Down)
On the short side, the script detects a **bearish pullback confirmation** based on:
* A recent **high-volume bearish candle** (large down bar with volume above a multiple of the 20-period volume average)
* At least a minimum number of **negative MACD histogram bars**
* MACD line moving closer to the signal line (loss of momentum)
* Price recovering back up near the **top of that high-volume bearish candle**, then starting to fall again while MACD stays positive
When all conditions align, the script prints a **red triangle above the bar**, indicating a **bearish pullback confirmation** – often a good area to take profits on longs or consider short/hedge setups.
---
#### 3. Signal History Tracking
For both long and short signals, the script internally tracks the **most recent three signals**:
* Timestamp of the signal
* Price at the signal
* Short-term percentage change into the signal
This is mainly for internal use and future expansion, but already gives you a structured signal history if you want to extend or connect the logic later.
---
### Multi-Timeframe SMA20 Dashboard (Bottom-Right Panel)
One of the most useful parts of this script is the **compact dashboard table** in the **bottom-right corner** of the chart. It updates in real time and shows:
1. **Current Price**
2. **Daily SMA20** – value + whether price is above/below
3. **3-Day SMA20** – value + whether price is above/below
4. **Weekly SMA20** – value + whether price is above/below
5. **Monthly SMA20** – value + whether price is above/below
6. **RSI** (current timeframe)
For each timeframe’s SMA20:
* If **price ≥ SMA20**, the status cell is **green** with a ✓
* If **price < SMA20**, the status cell is **red** with a ✗
This gives you, at a glance:
* Is the market in a **short-term uptrend or downtrend** (Daily SMA20)?
* Is the **swing / position trend** healthy (3D & Weekly SMA20)?
* Is the broader **macro structure** supportive (Monthly SMA20)?
You don’t need to manually switch timeframes or add multiple moving averages – the script does all of that for you automatically using `request.security`.
---
### Alerts
The script comes with two built-in alert conditions:
* **MACD回踩转多信号 (MACD pullback bullish signal)**
* **空头回抽确认信号 (Bearish pullback confirmation signal)**
You can attach TradingView alerts to these conditions to get notified whenever a new long or bearish-confirmation setup appears, even when you’re not watching the chart.
---
### How to Use It in Your Trading
1. **Choose your main trading timeframe**
* For intraday swing: 15m / 1h / 4h
* For swing / position: 4h / Daily
2. **Watch the bottom-right SMA20 panel**
* If most higher-timeframe SMA20 rows are **green**, you are trading **with the larger trend**.
* If they are **mixed or mostly red**, you’re either counter-trend or in a choppy transition zone.
3. **Use the green MACD pullback signals**
* Prefer long setups when:
* The **Weekly and Monthly SMA20 rows are green**, and
* The signal appears **above the Daily SMA20**
* This stacks multiple edges: trend + pullback + momentum re-acceleration.
4. **Use the red bearish confirmation signals for risk management**
* Take partial profits on longs when a red signal appears near resistance.
* Consider hedge/short opportunities if higher-timeframe SMA20 rows are already red or turning red.
5. **Use RSI as a context indicator**
* Combine with overbought/oversold zones or your own RSI thresholds for additional confirmation.
---
### Why This Script Is Useful
* **Trend awareness across timeframes**:
You always know where current price sits relative to the Daily / 3-Day / Weekly / Monthly SMA20 – without switching charts.
* **Clear, rule-based signals**:
The MACD logic is explicit and systematic, focused on **pullbacks within trends** rather than random crossovers.
* **Volume-aware bearish logic**:
High-volume bearish candles often mark important supply zones. The script builds this idea directly into the short-side confirmation logic.
* **Visual and intuitive**:
Green/Red triangles + Green/Red table cells make it easy to interpret even if you are not a heavy indicator user.
* **Flexible**:
All key parameters (MACD lengths, SMA length, volume threshold, lookback period, RSI length, weekly filter) are customizable, so you can adapt it to different markets (crypto, stocks, FX) and timeframes.
---
In short, this script is a **multi-timeframe MACD pullback system with an integrated SMA20 dashboard**, suitable for swing traders and position traders who want a structured, visually clean way to align entries with trend and momentum while keeping an eye on higher-timeframe levels.
Multi-Symbol EMA Crossover Scanner with Multi-Timeframe AnalysisDescription
What This Indicator Does:
This indicator is a comprehensive market scanner that monitors up to 10 symbols simultaneously across 4 different timeframes (15-minute, 1-hour, 4-hour, and daily) to detect exponential moving average (EMA) crossovers in real-time. Instead of manually checking multiple charts and timeframes for EMA crossover signals, this scanner automatically does the work for you and presents all detected signals in a clean, organized table that updates continuously throughout the trading session.
Key Features:
Multi-Symbol Monitoring: Scan up to 10 different symbols at once (stocks, forex, crypto, or any TradingView symbol)
Multi-Timeframe Analysis: Simultaneously tracks 4 timeframes (15m, 1H, 4H, 1D) with toggle options to enable/disable each
Comprehensive EMA Pairs: Detects crossovers between all major EMA combinations: 20×50, 20×100, 20×200, 50×100, 50×200, and 100×200
Real-Time Signal Feed: Displays the most recent signals in a sorted table (newest first) with timestamp, direction, price, and EMA pair information
Session Filter: Built-in time filter (default 10:00-18:00) to focus on specific trading hours and avoid pre-market/after-hours noise
Pagination System: Navigate through signals using a page selector when you have more signals than fit in one view
Signal Statistics: Footer displays total signals, bullish/bearish breakdown, and page navigation hints
Customizable Display: Choose table position (4 corners), signals per page (5-20), and maximum signal history (10-100)
How It Works:
The scanner uses the request.security() function to fetch EMA data from multiple symbols and timeframes simultaneously. For each symbol-timeframe combination, it calculates four exponential moving averages (20, 50, 100, and 200 periods) and monitors for crossovers:
Bullish Crossovers (▲ Green):
Faster EMA crosses above slower EMA
Indicates potential upward momentum
Common entry signals for long positions
Bearish Crossovers (▼ Red):
Faster EMA crosses below slower EMA
Indicates potential downward momentum
Common entry signals for short positions or exits
The scanner prioritizes crossovers involving faster EMAs (20×50) over slower ones (100×200), as faster crossovers typically generate more frequent signals. Each detected crossover is stored with its timestamp, allowing the scanner to sort signals chronologically and remove duplicates within the same timeframe.
Signal Table Columns:
Sym: Symbol name (abbreviated, e.g., "ASELS" instead of "BIST:ASELS")
TF: Timeframe where the crossover occurred (15m, 1h, 4h, 1D)
⏰: Exact time of the crossover (HH:MM format in Istanbul timezone)
↕: Direction indicator (▲ bullish green / ▼ bearish red)
₺: Price level where the crossover occurred (average of the two EMAs)
MA: Which EMA pair crossed (e.g., "20×50", "50×200")
How to Use:
For Day Traders:
Enable 15m and 1h timeframes
Monitor symbols from your watchlist
Use crossovers as entry timing signals in the direction of the larger trend
Adjust the time filter to match your trading session (e.g., market open to 2 hours before close)
For Swing Traders:
Enable 4h and 1D timeframes
Focus on 50×200 and 100×200 crossovers (golden/death crosses)
Look for multiple timeframe confluence (same symbol showing bullish crossovers on both 4h and 1D)
Use as a pre-market scanner to identify potential setups for the day
For Multi-Market Traders:
Mix symbols from different markets (stocks, forex, crypto)
Use the scanner to identify which markets are showing the most momentum
Track relative strength by comparing crossover frequency across symbols
Identify rotation opportunities when one asset shows bullish signals while another shows bearish
Setup Recommendations:
Default BIST (Turkish Stock Market) Setup:
The code comes pre-configured with 10 popular BIST stocks:
ASELS, EKGYO, THYAO, AKBNK, PGSUS, ASTOR, OTKAR, ALARK, ISCTR, BIMAS
For US Stocks:
Replace with symbols like: NASDAQ:AAPL, NASDAQ:TSLA, NASDAQ:NVDA, NYSE:JPM, etc.
For Forex:
Use pairs like: FX:EURUSD, FX:GBPUSD, FX:USDJPY, OANDA:XAUUSD, etc.
For Crypto:
Use exchanges like: BINANCE:BTCUSDT, COINBASE:ETHUSD, BINANCE:SOLUSDT, etc.
Settings Guide:
Symbol List (10 inputs):
Enter any valid TradingView symbol in "EXCHANGE:TICKER" format
Use symbols you actively trade or monitor
Mix different asset classes if desired
Timeframe Toggles:
15 Minutes: High-frequency signals, best for day trading
1 Hour: Balanced frequency, good for intraday swing trades
4 Hours: Lower frequency, quality swing trade signals
1 Day: Low frequency, major trend changes only
Time Filter:
Start Hour (10): Beginning of your trading session
End Hour (18): End of your trading session
Prevents signals during low-liquidity periods
Adjust to match your market's active hours
Display Settings:
Table Position: Choose corner placement (doesn't interfere with other indicators)
Max Signals (40): Total historical signals to keep in memory
Signals Per Page (10): How many rows to show at once
Page Number: Navigate through signal history (auto-adjusts to available pages)
What Makes This Original:
Multi-symbol scanners exist on TradingView, but this indicator's originality comes from:
Comprehensive EMA Pair Coverage: Most scanners focus on 1-2 EMA pairs, this monitors 6 different combinations simultaneously
Unified Multi-Timeframe View: Presents signals from 4 timeframes in a single, chronologically sorted feed rather than separate panels
Session-Aware Filtering: Built-in time filter prevents signal overload from 24-hour markets
Smart Pagination: Handles large signal volumes gracefully with page navigation instead of scrolling
Signal Deduplication: Prevents the same crossover from appearing multiple times if it persists across several bars
Price-at-Cross Recording: Captures the exact price where the crossover occurred, not just that it happened
Real-Time Statistics: Live tracking of bullish vs bearish signal distribution
Trading Strategy Examples:
Trend Confirmation Strategy:
Find a symbol showing bullish crossover on 1D (major trend change)
Wait for pullback
Enter when 1h shows bullish crossover (confirmation)
Exit when 1h shows bearish crossover
Multi-Timeframe Confluence:
Look for symbols appearing multiple times with same direction
Example: ASELS shows ▲ on both 4h and 1D = strong bullish signal
Avoid symbols showing conflicting signals (▲ on 1h but ▼ on 4h)
Rotation Scanner:
Monitor 10+ symbols from the same sector
Identify which are turning bullish (▲) first
Enter leaders, avoid laggards
Rotate out when crossovers turn bearish (▼)
Important Considerations:
Not a Complete System: EMA crossovers should be confirmed with price action, volume, and support/resistance analysis
Whipsaw Risk: During consolidation, EMAs can cross back and forth frequently (especially on 15m timeframe)
Lag: EMAs are lagging indicators; crossovers occur after the move has already begun
False Signals: More common during sideways markets; work best in trending environments
Symbol Limits: TradingView has limits on request.security() calls; this scanner uses 40 calls (10 symbols × 4 timeframes)
Performance: On lower-end devices, scanning 10 symbols across 4 timeframes may cause slight delays in chart updates
Best Practices:
Start with 5 symbols and 2 timeframes, then expand as you get comfortable
Use in conjunction with a main chart for price context
Don't trade every signal—filter for high-quality setups
Backtest your favorite EMA pairs on your symbols to understand their reliability
Adjust the time filter to exclude lunch hours if your market has low midday volume
Check the footer statistics—if you're getting 50+ signals per day, tighten your time filter or reduce symbols
Technical Notes:
Uses lookahead=barmerge.lookahead_off to prevent future data leakage
Signals are stored in arrays and sorted by timestamp (newest first)
Automatic daily reset clears old signals to prevent memory buildup
Table dynamically resizes based on signal count
All times displayed in Europe/Istanbul timezone (configurable in code)
Trend Bars with Counter Table# TradingView Trend Bar Indicator Explained
## Indicator Overview
This is a TradingView indicator designed to identify and count **Trend Bars**. It not only visually marks strong bullish and bearish bars on the chart but also displays a data table in the upper right corner that tracks the distribution of trend bars across different periods, helping traders quickly assess market bias.
## Core Concept: What is a Trend Bar?
The indicator defines two types of trend bars:
### Bull Trend Bar
- **Condition**: Close > Open (bullish candle)
- **Strength Requirement**: Body size ≥ 75% of total candle range
```
Body Length = |Close - Open|
Total Candle Range = High - Low
Criteria: Body Length ≥ 0.75 × Total Candle Range
```
This means both upper and lower wicks are very short, representing a very strong bullish candle.
### Bear Trend Bar
- **Condition**: Close < Open (bearish candle)
- **Strength Requirement**: Body size ≥ 75% of total candle range
Similarly, this represents a strong bearish candle with minimal wicks and a full body.
## Visual Markers
The indicator marks qualifying candles with:
- **Green upward arrow**: Bull trend bar, appears below the candle
- **Red downward arrow**: Bear trend bar, appears above the candle
## Statistical Function
The indicator uses a **rolling array** (storing up to 1000 trend bars) to track historical data, then counts trend bar distribution across 5 different periods:
| Period | Statistical Range |
|--------|------------------|
| Group 1 | Last 7 trend bars |
| Group 2 | Last 15 trend bars |
| Group 3 | Last 21 trend bars |
| Group 4 | Last 29 trend bars |
| Group 5 | Last 35 trend bars |
**Note**: This counts "the last N trend bars," not "the last N candles." Only candles meeting the trend bar criteria are included.
## Data Table Interpretation
The table in the upper right corner contains 5 columns:
1. **Last N**: The set statistical range (7, 15, 21, 29, 35)
2. **Total**: Actual number of trend bars counted (may be less than target initially)
3. **Bull**: Number of bull trend bars (displayed in green)
4. **Bear**: Number of bear trend bars (displayed in red)
5. **Bias**: Market bias
- "bull" (green): More bull trend bars
- "bear" (red): More bear trend bars
## Practical Applications
### 1. Assess Short-term Momentum
Check the distribution of the last 7 trend bars. If bull trend bars dominate (e.g., 5:2), it indicates strong short-term buying pressure.
### 2. Identify Trend Strength
If multiple periods show the same Bias direction, the trend is very clear. For example, all 5 periods showing "bull" is a strong upward signal.
### 3. Spot Trend Reversals
When short-term bias (7 bars) opposes long-term bias (35 bars), it may signal a trend change in progress.
### 4. Combine with Other Indicators
Use this indicator alongside moving averages, support/resistance levels, and other tools to improve trading decision accuracy.
## Technical Highlights
- **Dynamic Array Management**: Uses `array.unshift()` to add new data at the array's beginning, ensuring the latest trend bars are always first
- **Efficient Statistics**: Quickly calculates bull/bear distribution through loop iteration over specified array ranges
- **Adaptive Display**: Shows actual available count when historical data is insufficient
- **Real-time Updates**: Only updates the table on the last bar to avoid unnecessary calculations
## Conclusion
The core value of this indicator lies in **quantifying price action**. By identifying strong candles with full bodies and clear direction, then tracking their distribution, traders can quickly grasp the balance of market forces and make more informed trading decisions. Whether for intraday trading or swing trading, this tool provides valuable reference information.
Structure Pro by MurshidfxInspired by the 'mentfx Structure' indicator created by Anton (mentfx) on TradingView,
## Overview
Structure Pro tracks market structure by maintaining an adaptive dealing range and its midpoint. Swing highs and lows become structural boundaries, and the script responds to confirmed breakouts by recalculating the active range. Labels highlight the latest trend flip so the chart stays readable while the range evolves.
## Core Logic
- Detects swing highs/lows using a configurable pivot strength and promotes confirmed pivots to structural levels.
- Applies a percentage buffer to decide when price truly breaks structure; once triggered, the opposite boundary is recalculated with an anchor search that looks back through historical bars.
- Computes equilibrium as the midpoint between the current structural high and low so you can gauge premium versus discount zones.
- Emits a single BULL or BEAR label when the trend state changes, keeping only the most recent signal on the chart.
## How to Use
1. Open a clean chart and apply only this script.
2. Select a swing strength that matches the scale you want to monitor (lower values for responsive intraday swings, higher values for broader moves).
3. Tune the structure sensitivity percentage if you prefer tighter or looser confirmation before declaring a breakout.
4. Track DRH/DRL for the current dealing range, use the equilibrium line as a mean-reversion guide, and look to the BULL/BEAR label for structure confirmation.
5. Combine the levels with your own execution, risk, and position rules—this script does not manage orders.
## Inputs
- Swing Point Strength: bars required on both sides to confirm a pivot.
- Structure Break Sensitivity: percentage buffer applied to the range before calling a breakout.
- Dealing Range display: toggles for visibility, line width/color, label text, and label size.
- Equilibrium display: line style, width, and color controls.
- Trend Signals: enable/disable labels, adjust text size, and pick label colors.
## Notes
- Designed for live structure tracking; the script relies on confirmed pivots and does not peek into future data.
- Built to be chart-agnostic for standard candles; non-standard chart types can distort the measurements.
- Published open-source so traders can review and verify the implementation details.
Zero Lag Trend Signals (MTF) [Quant Trading] V7Overview
The Zero Lag Trend Signals (MTF) V7 is a comprehensive trend-following strategy that combines Zero Lag Exponential Moving Average (ZLEMA) with volatility-based bands to identify high-probability trade entries and exits. This strategy is designed to reduce lag inherent in traditional moving averages while incorporating dynamic risk management through ATR-based stops and multiple exit mechanisms.
This is a longer term horizon strategy that takes limited trades. It is not a high frequency trading and therefore will also have limited data and not > 100 trades.
How It Works
Core Signal Generation:
The strategy uses a Zero Lag EMA (ZLEMA) calculated by applying an EMA to price data that has been adjusted for lag:
Calculate lag period: floor((length - 1) / 2)
Apply lag correction: src + (src - src )
Calculate ZLEMA: EMA of lag-corrected price
Volatility bands are created using the highest ATR over a lookback period multiplied by a band multiplier. These bands are added to and subtracted from the ZLEMA line to create upper and lower boundaries.
Trend Detection:
The strategy maintains a trend variable that switches between bullish (1) and bearish (-1):
Long Signal: Triggers when price crosses above ZLEMA + volatility band
Short Signal: Triggers when price crosses below ZLEMA - volatility band
Optional ZLEMA Trend Confirmation:
When enabled, this filter requires ZLEMA to show directional momentum before entry:
Bullish Confirmation: ZLEMA must increase for 4 consecutive bars
Bearish Confirmation: ZLEMA must decrease for 4 consecutive bars
This additional filter helps avoid false signals in choppy or ranging markets.
Risk Management Features:
The strategy includes multiple stop-loss and take-profit mechanisms:
Volatility-Based Stops: Default stop-loss is placed at ZLEMA ± volatility band
ATR-Based Stops: Dynamic stop-loss calculated as entry price ± (ATR × multiplier)
ATR Trailing Stop: Ratcheting stop-loss that follows price but never moves against position
Risk-Reward Profit Target: Take-profit level set as a multiple of stop distance
Break-Even Stop: Moves stop to entry price after reaching specified R:R ratio
Trend-Based Exit: Closes position when price crosses EMA in opposite direction
Performance Tracking:
The strategy includes optional features for monitoring and analyzing trades:
Floating Statistics Table: Displays key metrics including win rate, GOA (Gain on Account), net P&L, and max drawdown
Trade Log Labels: Shows entry/exit prices, P&L, bars held, and exit reason for each closed trade
CSV Export Fields: Outputs trade data for external analysis
Default Strategy Settings
Commission & Slippage:
Commission: 0.1% per trade
Slippage: 3 ticks
Initial Capital: $1,000
Position Size: 100% of equity per trade
Main Calculation Parameters:
Length: 70 (range: 70-7000) - Controls ZLEMA calculation period
Band Multiplier: 1.2 - Adjusts width of volatility bands
Entry Conditions (All Disabled by Default):
Use ZLEMA Trend Confirmation: OFF - Requires ZLEMA directional momentum
Re-Enter on Long Trend: OFF - Allows multiple entries during sustained trends
Short Trades:
Allow Short Trades: OFF - Strategy is long-only by default
Performance Settings (All Disabled by Default):
Use Profit Target: OFF
Profit Target Risk-Reward Ratio: 2.0 (when enabled)
Dynamic TP/SL (All Disabled by Default):
Use ATR-Based Stop-Loss & Take-Profit: OFF
ATR Length: 14
Stop-Loss ATR Multiplier: 1.5
Profit Target ATR Multiplier: 2.5
Use ATR Trailing Stop: OFF
Trailing Stop ATR Multiplier: 1.5
Use Break-Even Stop-Loss: OFF
Move SL to Break-Even After RR: 1.5
Use Trend-Based Take Profit: OFF
EMA Exit Length: 9
Trade Data Display (All Disabled by Default):
Show Floating Stats Table: OFF
Show Trade Log Labels: OFF
Enable CSV Export: OFF
Trade Label Vertical Offset: 0.5
Backtesting Date Range:
Start Date: January 1, 2018
End Date: December 31, 2069
Important Usage Notes
Default Configuration: The strategy operates in its most basic form with default settings - using only ZLEMA crossovers with volatility bands and volatility-based stop-losses. All advanced features must be manually enabled.
Stop-Loss Priority: If multiple stop-loss methods are enabled simultaneously, the strategy will use whichever condition is hit first. ATR-based stops override volatility-based stops when enabled.
Long-Only by Default: Short trading is disabled by default. Enable "Allow Short Trades" to trade both directions.
Performance Monitoring: Enable the floating stats table and trade log labels to visualize strategy performance during backtesting.
Exit Mechanisms: The strategy can exit trades through multiple methods: stop-loss hit, take-profit reached, trend reversal, or trailing stop activation. The trade log identifies which exit method was used.
Re-Entry Logic: When "Re-Enter on Long Trend" is enabled with ZLEMA trend confirmation, the strategy can take multiple long positions during extended uptrends as long as all entry conditions remain valid.
Capital Efficiency: Default setting uses 100% of equity per trade. Adjust "default_qty_value" to manage position sizing based on risk tolerance.
Realistic Backtesting: Strategy includes commission (0.1%) and slippage (3 ticks) to provide realistic performance expectations. These values should be adjusted based on your broker and market conditions.
Recommended Use Cases
Trending Markets: Best suited for markets with clear directional moves where trend-following strategies excel
Medium to Long-Term Trading: The default length of 70 makes this strategy more appropriate for swing trading rather than scalping
Risk-Conscious Traders: Multiple stop-loss options allow traders to customize risk management to their comfort level
Backtesting & Optimization: Comprehensive performance tracking features make this strategy ideal for testing different parameter combinations
Limitations & Considerations
Like all trend-following strategies, performance may suffer in choppy or ranging markets
Default 100% position sizing means full capital exposure per trade - consider reducing for conservative risk management
Higher length values (70+) reduce signal frequency but may improve signal quality
Multiple simultaneous risk management features may create conflicting exit signals
Past performance shown in backtests does not guarantee future results
Customization Tips
For more aggressive trading:
Reduce length parameter (minimum 70)
Decrease band multiplier for tighter bands
Enable short trades
Use lower profit target R:R ratios
For more conservative trading:
Increase length parameter
Enable ZLEMA trend confirmation
Use wider ATR stop-loss multipliers
Enable break-even stop-loss
Reduce position size from 100% default
For optimal choppy market performance:
Enable ZLEMA trend confirmation
Increase band multiplier
Use tighter profit targets
Avoid re-entry on trend continuation
Visual Elements
The strategy plots several elements on the chart:
ZLEMA line (color-coded by trend direction)
Upper and lower volatility bands
Long entry markers (green triangles)
Short entry markers (red triangles, when enabled)
Stop-loss levels (when positions are open)
Take-profit levels (when enabled and positions are open)
Trailing stop lines (when enabled and positions are open)
Optional ZLEMA trend markers (triangles at highs/lows)
Optional trade log labels showing complete trade information
Exit Reason Codes (for CSV Export)
When CSV export is enabled, exit reasons are coded as:
0 = Manual/Other
1 = Trailing Stop-Loss
2 = Profit Target
3 = ATR Stop-Loss
4 = Trend Change
Conclusion
Zero Lag Trend Signals V7 provides a robust framework for trend-following with extensive customization options. The strategy balances simplicity in its core logic with sophisticated risk management features, making it suitable for both beginner and advanced traders. By reducing moving average lag while incorporating volatility-based signals, it aims to capture trends earlier while managing risk through multiple configurable exit mechanisms.
The modular design allows traders to start with basic trend-following and progressively add complexity through ZLEMA confirmation, multiple stop-loss methods, and advanced exit strategies. Comprehensive performance tracking and export capabilities make this strategy an excellent tool for systematic testing and optimization.
Note: This strategy is provided for educational and backtesting purposes. All trading involves risk. Past performance does not guarantee future results. Always test thoroughly with paper trading before risking real capital, and adjust position sizing and risk parameters according to your risk tolerance and account size.
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TAGS:
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trend following, ZLEMA, zero lag, volatility bands, ATR stops, risk management, swing trading, momentum, trend confirmation, backtesting
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CATEGORY:
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Strategies
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CHART SETUP RECOMMENDATIONS:
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For optimal visualization when publishing:
Use a clean chart with no other indicators overlaid
Select a timeframe that shows multiple trade signals (4H or Daily recommended)
Choose a trending asset (crypto, forex major pairs, or trending stocks work well)
Show at least 6-12 months of data to demonstrate strategy across different market conditions
Enable the floating stats table to display key performance metrics
Ensure all indicator lines (ZLEMA, bands, stops) are clearly visible
Use the default chart type (candlesticks) - avoid Heikin Ashi, Renko, etc.
Make sure symbol information and timeframe are clearly visible
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COMPLIANCE NOTES:
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✅ Open-source publication with complete code visibility
✅ English-only title and description
✅ Detailed explanation of methodology and calculations
✅ Realistic commission (0.1%) and slippage (3 ticks) included
✅ All default parameters clearly documented
✅ Performance limitations and risks disclosed
✅ No unrealistic claims about performance
✅ No guaranteed results promised
✅ Appropriate for public library (original trend-following implementation with ZLEMA)
✅ Educational disclaimers included
✅ All features explained in detail
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