Smart Bar Counter with Alerts🚀 Smart Bar Counter with Alerts 🚀
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Overview
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Ever wanted to count a specific number of bars from a key point on your chart—such as after a Break of Structure (BOS), the start of a new trading session, or from any point of interest— without having to stare at the screen?
This "Smart Bar Counter" indicator was created to solve this exact problem. It's a simple yet powerful tool that allows you to define a custom "Start Point" and a "Target Bar Count." Once the target count is reached, it can trigger an Alert to notify you immediately.
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Key Features
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• Manual Start Point: Precisely select the date and time from which you want the count to begin, offering maximum flexibility in your analysis.
• Custom Bar Target: Define exactly how many bars you want to count, whether it's 50, 100, or 200 bars.
• On-Chart Display: A running count is displayed on each bar after the start time, allowing you to visually track the progress.
• Automatic Alerts: Set up alerts to be notified via TradingView's various channels (pop-up, mobile app, email) once the target count is reached.
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How to Use
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1. Add this indicator to your chart.
2. Go to the indicator's Settings (Gear Icon ⚙️).
- Select Start Time: Set the date and time you wish to begin counting.
- Number of Bars to Count: Input your target number.
3. Set up the Alert ( Very Important! ).
- Right-click on the chart > Select " Add alert ."
- In the " Condition " dropdown, select this indicator: Smart Bar Counter with Alerts .
- In the next dropdown, choose the available alert condition.
- Set " Options " to Once Per Bar Close .
- Choose your desired notification methods under " Alert Actions ."
- Click " Create ."
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Use Cases
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• Post-Event Analysis: Count bars after a key event like a Break of Structure (BOS) or Change of Character (CHoCH) to observe subsequent price action.
• Time-based Analysis: Use it to count bars after a market open for a specific session (e.g., London, New York).
• Strategy Backtesting: Useful for testing trading rules that are based on time or a specific number of bars.
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Final Words
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Hope you find this indicator useful for your analysis and trading strategies! Feel free to leave comments or suggestions below.
Indikator dan strategi
Volume Dominancean indicator to display volume dominance.
the green line is the average volume of the past n bars, except the bars with lower closes than the last bar have their volumes replaced with zero. the red line is the opposite, where higher closes than the last bar have their volumes replaced with zero.
this is a prototype i plan on turning in to an oscillator.
Renko New Brick AlertA simple indicator that triggers an alert when a new brick is formed on a Renko chart.
Bands Vision-XBands Vision-X (BB-Vision-X) – Full Description
Description:
Bands Vision-X is an indicator based on dynamic bands constructed from customizable moving averages and standard deviation, allowing you to visualize potential support and resistance zones, volatility, and market conditions. It uses an adjustable moving average (with multiple options such as SMA, EMA, WMA, JMA, LSMA, DEMA, and TEMA) to define the central line, and upper and lower bands calculated by standard deviation multiplied by an adjustable factor. The bands are smoothed by a Hull Moving Average (HMA) to reduce noise and improve clarity.
How to Use
The bands indicate potential support and resistance levels.
The central line serves as a dynamic price reference.
The distance between bands reflects market volatility.
Touches or breakouts of the bands may signal entry or exit opportunities.
Parameters
Parameter Description Default
Standard Error Band Period Period for moving average and standard deviation 20
Moving Average Type Type of moving average (SMA, EMA, etc.) SMA
Standard Deviation Multiplier Multiplier for standard deviation 2.0
Band Lines Smoothing Period Period for smoothing the bands (HMA) 5
Technical Notes
The JMA function used is not the original Jurik version but an approximate and open implementation based on publicly available TradingView community code.
Developed in Pine Script v6 with optimized and clean code.
Recommendations
Ideal for traders seeking a clear view of volatility and dynamic support/resistance levels.
Should not be used in isolation; it is recommended to combine with volume analysis, price action, or other technical indicators.
Adjust the period and multiplier according to the asset and timeframe for better effectiveness.
Candle Body Strength CounterThis indicator measures the total bullish and bearish candle body strength over a user-defined lookback period. For each bar, it sums the absolute body sizes of bullish candles (where close > open) and bearish candles (where close < open) within the lookback window. The result is two lines: one for bullish body strength and one for bearish body strength, making it easy to spot shifts in market momentum and bias.
Adjustable lookback period (default: 20 bars)
Green line: cumulative bullish body strength
Red line: cumulative bearish body strength
Use this tool to quickly assess which side (bulls or bears) has been stronger over your chosen timeframe.
ICT Directional FVG Indicator (Buffered SL)This is the first indicator I have ever made, and I am very new to Pine Script. I’ve tried my best to create this as a strategy, but I’m still learning, so please be kind and constructive with your feedback!
ICT Directional FVG Indicator (Buffered SL)
This indicator is designed for traders who follow ICT (Inner Circle Trader) concepts, focusing on Fair Value Gaps (FVGs), liquidity sweeps, and session-based trading. It automatically detects bullish and bearish FVGs, highlights them on the chart, and identifies liquidity sweep events. The indicator features three customizable Kill Zones (London, New York, and Asia sessions), each with independent toggles and color-coded backgrounds for clear visual separation.
Key features:
Fair Value Gap Detection: Highlights bullish and bearish FVGs in real time.
Liquidity Sweep Alerts: Marks potential liquidity sweep events for both highs and lows.
Session Kill Zones: Toggle each Kill Zone (London, New York, Asia) independently; background color changes only in enabled zones.
Trade Signal Visualization: Plots entry, stop loss, and take profit levels based on FVG and sweep logic, with a user-defined stop loss buffer.
Customizable Display: Easily enable or disable FVGs, sweeps, trade levels, and each Kill Zone to suit your strategy.
This tool is ideal for ICT-based traders who want a clear, automated view of FVGs, sweeps, and session activity, with full control over which sessions and signals are displayed.
Langlands-Operadic Möbius Vortex (LOMV)Langlands-Operadic Möbius Vortex (LOMV)
Where Pure Mathematics Meets Market Reality
A Revolutionary Synthesis of Number Theory, Category Theory, and Market Dynamics
🎓 THEORETICAL FOUNDATION
The Langlands-Operadic Möbius Vortex represents a groundbreaking fusion of three profound mathematical frameworks that have never before been combined for market analysis:
The Langlands Program: Harmonic Analysis in Markets
Developed by Robert Langlands (Fields Medal recipient), the Langlands Program creates bridges between number theory, algebraic geometry, and harmonic analysis. In our indicator:
L-Function Implementation:
- Utilizes the Möbius function μ(n) for weighted price analysis
- Applies Riemann zeta function convergence principles
- Calculates quantum harmonic resonance between -2 and +2
- Measures deep mathematical patterns invisible to traditional analysis
The L-Function core calculation employs:
L_sum = Σ(return_val × μ(n) × n^(-s))
Where s is the critical strip parameter (0.5-2.5), controlling mathematical precision and signal smoothness.
Operadic Composition Theory: Multi-Strategy Democracy
Category theory and operads provide the mathematical framework for composing multiple trading strategies into a unified signal. This isn't simple averaging - it's mathematical composition using:
Strategy Composition Arity (2-5 strategies):
- Momentum analysis via RSI transformation
- Mean reversion through Bollinger Band mathematics
- Order Flow Polarity Index (revolutionary T3-smoothed volume analysis)
- Trend detection using Directional Movement
- Higher timeframe momentum confirmation
Agreement Threshold System: Democratic voting where strategies must reach consensus before signal generation. This prevents false signals during market uncertainty.
Möbius Function: Number Theory in Action
The Möbius function μ(n) forms the mathematical backbone:
- μ(n) = 1 if n is a square-free positive integer with even number of prime factors
- μ(n) = -1 if n is a square-free positive integer with odd number of prime factors
- μ(n) = 0 if n has a squared prime factor
This creates oscillating weights that reveal hidden market periodicities and harmonic structures.
🔧 COMPREHENSIVE INPUT SYSTEM
Langlands Program Parameters
Modular Level N (5-50, default 30):
Primary lookback for quantum harmonic analysis. Optimized by timeframe:
- Scalping (1-5min): 15-25
- Day Trading (15min-1H): 25-35
- Swing Trading (4H-1D): 35-50
- Asset-specific: Crypto 15-25, Stocks 30-40, Forex 35-45
L-Function Critical Strip (0.5-2.5, default 1.5):
Controls Riemann zeta convergence precision:
- Higher values: More stable, smoother signals
- Lower values: More reactive, catches quick moves
- High frequency: 0.8-1.2, Medium: 1.3-1.7, Low: 1.8-2.3
Frobenius Trace Period (5-50, default 21):
Galois representation lookback for price-volume correlation:
- Measures harmonic relationships in market flows
- Scalping: 8-15, Day Trading: 18-25, Swing: 25-40
HTF Multi-Scale Analysis:
Higher timeframe context prevents trading against major trends:
- Provides market bias and filters signals
- Improves win rates by 15-25% through trend alignment
Operadic Composition Parameters
Strategy Composition Arity (2-5, default 4):
Number of algorithms composed for final signal:
- Conservative: 4-5 strategies (higher confidence)
- Moderate: 3-4 strategies (balanced approach)
- Aggressive: 2-3 strategies (more frequent signals)
Category Agreement Threshold (2-5, default 3):
Democratic voting minimum for signal generation:
- Higher agreement: Fewer but higher quality signals
- Lower agreement: More signals, potential false positives
Swiss-Cheese Mixing (0.1-0.5, default 0.382):
Golden ratio φ⁻¹ based blending of trend factors:
- 0.382 is φ⁻¹, optimal for natural market fractals
- Higher values: Stronger trend following
- Lower values: More contrarian signals
OFPI Configuration:
- OFPI Length (5-30, default 14): Order Flow calculation period
- T3 Smoothing (3-10, default 5): Advanced exponential smoothing
- T3 Volume Factor (0.5-1.0, default 0.7): Smoothing aggressiveness control
Unified Scoring System
Component Weights (sum ≈ 1.0):
- L-Function Weight (0.1-0.5, default 0.3): Mathematical harmony emphasis
- Galois Rank Weight (0.1-0.5, default 0.2): Market structure complexity
- Operadic Weight (0.1-0.5, default 0.3): Multi-strategy consensus
- Correspondence Weight (0.1-0.5, default 0.2): Theory-practice alignment
Signal Threshold (0.5-10.0, default 5.0):
Quality filter producing:
- 8.0+: EXCEPTIONAL signals only
- 6.0-7.9: STRONG signals
- 4.0-5.9: MODERATE signals
- 2.0-3.9: WEAK signals
🎨 ADVANCED VISUAL SYSTEM
Multi-Dimensional Quantum Aura Bands
Five-layer resonance field showing market energy:
- Colors: Theme-matched gradients (Quantum purple, Holographic cyan, etc.)
- Expansion: Dynamic based on score intensity and volatility
- Function: Multi-timeframe support/resistance zones
Morphism Flow Portals
Category theory visualization showing market topology:
- Green/Cyan Portals: Bullish mathematical flow
- Red/Orange Portals: Bearish mathematical flow
- Size/Intensity: Proportional to signal strength
- Recursion Depth (1-8): Nested patterns for flow evolution
Fractal Grid System
Dynamic support/resistance with projected L-Scores:
- Multiple Timeframes: 10, 20, 30, 40, 50-period highs/lows
- Smart Spacing: Prevents level overlap using ATR-based minimum distance
- Projections: Estimated signal scores when price reaches levels
- Usage: Precise entry/exit timing with mathematical confirmation
Wick Pressure Analysis
Rejection level prediction using candle mathematics:
- Upper Wicks: Selling pressure zones (purple/red lines)
- Lower Wicks: Buying pressure zones (purple/green lines)
- Glow Intensity (1-8): Visual emphasis and line reach
- Application: Confluence with fractal grid creates high-probability zones
Regime Intensity Heatmap
Background coloring showing market energy:
- Black/Dark: Low activity, range-bound markets
- Purple Glow: Building momentum and trend development
- Bright Purple: High activity, strong directional moves
- Calculation: Combines trend, momentum, volatility, and score intensity
Six Professional Themes
- Quantum: Purple/violet for general trading and mathematical focus
- Holographic: Cyan/magenta optimized for cryptocurrency markets
- Crystalline: Blue/turquoise for conservative, stability-focused trading
- Plasma: Gold/magenta for high-energy volatility trading
- Cosmic Neon: Bright neon colors for maximum visibility and aggressive trading
📊 INSTITUTIONAL-GRADE DASHBOARD
Unified AI Score Section
- Total Score (-10 to +10): Primary decision metric
- >5: Strong bullish signals
- <-5: Strong bearish signals
- Quality ratings: EXCEPTIONAL > STRONG > MODERATE > WEAK
- Component Analysis: Individual L-Function, Galois, Operadic, and Correspondence contributions
Order Flow Analysis
Revolutionary OFPI integration:
- OFPI Value (-100% to +100%): Real buying vs selling pressure
- Visual Gauge: Horizontal bar chart showing flow intensity
- Momentum Status: SHIFTING, ACCELERATING, STRONG, MODERATE, or WEAK
- Trading Application: Flow shifts often precede major moves
Signal Performance Tracking
- Win Rate Monitoring: Real-time success percentage with emoji indicators
- Signal Count: Total signals generated for frequency analysis
- Current Position: LONG, SHORT, or NONE with P&L tracking
- Volatility Regime: HIGH, MEDIUM, or LOW classification
Market Structure Analysis
- Möbius Field Strength: Mathematical field oscillation intensity
- CHAOTIC: High complexity, use wider stops
- STRONG: Active field, normal position sizing
- MODERATE: Balanced conditions
- WEAK: Low activity, consider smaller positions
- HTF Trend: Higher timeframe bias (BULL/BEAR/NEUTRAL)
- Strategy Agreement: Multi-algorithm consensus level
Position Management
When in trades, displays:
- Entry Price: Original signal price
- Current P&L: Real-time percentage with risk level assessment
- Duration: Bars in trade for timing analysis
- Risk Level: HIGH/MEDIUM/LOW based on current exposure
🚀 SIGNAL GENERATION LOGIC
Balanced Long/Short Architecture
The indicator generates signals through multiple convergent pathways:
Long Entry Conditions:
- Score threshold breach with algorithmic agreement
- Strong bullish order flow (OFPI > 0.15) with positive composite signal
- Bullish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bullish OFPI (>0.3) with any positive score
Short Entry Conditions:
- Score threshold breach with bearish agreement
- Strong bearish order flow (OFPI < -0.15) with negative composite signal
- Bearish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bearish OFPI (<-0.3) with any negative score
Exit Logic:
- Score deterioration below continuation threshold
- Signal quality degradation
- Opposing order flow acceleration
- 10-bar minimum between signals prevents overtrading
⚙️ OPTIMIZATION GUIDELINES
Asset-Specific Settings
Cryptocurrency Trading:
- Modular Level: 15-25 (capture volatility)
- L-Function Precision: 0.8-1.3 (reactive to price swings)
- OFPI Length: 10-20 (fast correlation shifts)
- Cascade Levels: 5-7, Theme: Holographic
Stock Index Trading:
- Modular Level: 25-35 (balanced trending)
- L-Function Precision: 1.5-1.8 (stable patterns)
- OFPI Length: 14-20 (standard correlation)
- Cascade Levels: 4-5, Theme: Quantum
Forex Trading:
- Modular Level: 35-45 (smooth trends)
- L-Function Precision: 1.6-2.1 (high smoothing)
- OFPI Length: 18-25 (disable volume amplification)
- Cascade Levels: 3-4, Theme: Crystalline
Timeframe Optimization
Scalping (1-5 minute charts):
- Reduce all lookback parameters by 30-40%
- Increase L-Function precision for noise reduction
- Enable all visual elements for maximum information
- Use Small dashboard to save screen space
Day Trading (15 minute - 1 hour):
- Use default parameters as starting point
- Adjust based on market volatility
- Normal dashboard provides optimal information density
- Focus on OFPI momentum shifts for entries
Swing Trading (4 hour - Daily):
- Increase lookback parameters by 30-50%
- Higher L-Function precision for stability
- Large dashboard for comprehensive analysis
- Emphasize HTF trend alignment
🏆 ADVANCED TRADING STRATEGIES
The Mathematical Confluence Method
1. Wait for Fractal Grid level approach
2. Confirm with projected L-Score > threshold
3. Verify OFPI alignment with direction
4. Enter on portal signal with quality ≥ STRONG
5. Exit on score deterioration or opposing flow
The Regime Trading System
1. Monitor Aether Flow background intensity
2. Trade aggressively during bright purple periods
3. Reduce position size during dark periods
4. Use Möbius Field strength for stop placement
5. Align with HTF trend for maximum probability
The OFPI Momentum Strategy
1. Watch for momentum shifting detection
2. Confirm with accelerating flow in direction
3. Enter on immediate portal signal
4. Scale out at Fibonacci levels
5. Exit on flow deceleration or reversal
⚠️ RISK MANAGEMENT INTEGRATION
Mathematical Position Sizing
- Use Galois Rank for volatility-adjusted sizing
- Möbius Field strength determines stop width
- Fractal Dimension guides maximum exposure
- OFPI momentum affects entry timing
Signal Quality Filtering
- Trade only STRONG or EXCEPTIONAL quality signals
- Increase position size with higher agreement levels
- Reduce risk during CHAOTIC Möbius field periods
- Respect HTF trend alignment for directional bias
🔬 DEVELOPMENT JOURNEY
Creating the LOMV was an extraordinary mathematical undertaking that pushed the boundaries of what's possible in technical analysis. This indicator almost didn't happen. The theoretical complexity nearly proved insurmountable.
The Mathematical Challenge
Implementing the Langlands Program required deep research into:
- Number theory and the Möbius function
- Riemann zeta function convergence properties
- L-function analytical continuation
- Galois representations in finite fields
The mathematical literature spans decades of pure mathematics research, requiring translation from abstract theory to practical market application.
The Computational Complexity
Operadic composition theory demanded:
- Category theory implementation in Pine Script
- Multi-dimensional array management for strategy composition
- Real-time democratic voting algorithms
- Performance optimization for complex calculations
The Integration Breakthrough
Bringing together three disparate mathematical frameworks required:
- Novel approaches to signal weighting and combination
- Revolutionary Order Flow Polarity Index development
- Advanced T3 smoothing implementation
- Balanced signal generation preventing directional bias
Months of intensive research culminated in breakthrough moments when the mathematics finally aligned with market reality. The result is an indicator that reveals market structure invisible to conventional analysis while maintaining practical trading utility.
🎯 PRACTICAL IMPLEMENTATION
Getting Started
1. Apply indicator with default settings
2. Select appropriate theme for your markets
3. Observe dashboard metrics during different market conditions
4. Practice signal identification without trading
5. Gradually adjust parameters based on observations
Signal Confirmation Process
- Never trade on score alone - verify quality rating
- Confirm OFPI alignment with intended direction
- Check fractal grid level proximity for timing
- Ensure Möbius field strength supports position size
- Validate against HTF trend for bias confirmation
Performance Monitoring
- Track win rate in dashboard for strategy assessment
- Monitor component contributions for optimization
- Adjust threshold based on desired signal frequency
- Document performance across different market regimes
🌟 UNIQUE INNOVATIONS
1. First Integration of Langlands Program mathematics with practical trading
2. Revolutionary OFPI with T3 smoothing and momentum detection
3. Operadic Composition using category theory for signal democracy
4. Dynamic Fractal Grid with projected L-Score calculations
5. Multi-Dimensional Visualization through morphism flow portals
6. Regime-Adaptive Background showing market energy intensity
7. Balanced Signal Generation preventing directional bias
8. Professional Dashboard with institutional-grade metrics
📚 EDUCATIONAL VALUE
The LOMV serves as both a practical trading tool and an educational gateway to advanced mathematics. Traders gain exposure to:
- Pure mathematics applications in markets
- Category theory and operadic composition
- Number theory through Möbius function implementation
- Harmonic analysis via L-function calculations
- Advanced signal processing through T3 smoothing
⚖️ RESPONSIBLE USAGE
This indicator represents advanced mathematical research applied to market analysis. While the underlying mathematics are rigorously implemented, markets remain inherently unpredictable.
Key Principles:
- Use as part of comprehensive trading strategy
- Implement proper risk management at all times
- Backtest thoroughly before live implementation
- Understand that past performance does not guarantee future results
- Never risk more than you can afford to lose
The mathematics reveal deep market structure, but successful trading requires discipline, patience, and sound risk management beyond any indicator.
🔮 CONCLUSION
The Langlands-Operadic Möbius Vortex represents a quantum leap forward in technical analysis, bringing PhD-level pure mathematics to practical trading while maintaining visual elegance and usability.
From the harmonic analysis of the Langlands Program to the democratic composition of operadic theory, from the number-theoretic precision of the Möbius function to the revolutionary Order Flow Polarity Index, every component works in mathematical harmony to reveal the hidden order within market chaos.
This is more than an indicator - it's a mathematical lens that transforms how you see and understand market structure.
Trade with mathematical precision. Trade with the LOMV.
*"Mathematics is the language with which God has written the universe." - Galileo Galilei*
*In markets, as in nature, profound mathematical beauty underlies apparent chaos. The LOMV reveals this hidden order.*
— Dskyz, Trade with insight. Trade with anticipation.
Fractals 1hFractals 1h, visible on 5m TF.
This indicator allows me to backtest my strategy "from zone to zone"...
Fear-Greed ThermometerFear-Greed Thermometer
This indicator measures market sentiment between fear and greed by combining three key factors: volatility, average volume, and percentage price change. Each factor is normalized and averaged to produce an index ranging from 0 to 100 that reflects the overall level of market fear or greed.
How to use:
Index above 50: Indicates greed dominance. The market tends to be more optimistic, signaling potential bullish conditions or overbought levels.
Index below 50: Indicates fear dominance. The market is more cautious or pessimistic, pointing to potential bearish conditions or oversold levels.
Neutral line (50): Acts as a reference for transitions between fear and greed phases.
Features:
Dynamic background: The chart background changes color according to sentiment — green for greed, red for fear — making it easy to visually gauge the index.
Customizable: Adjust the calculation periods for volatility, volume, and price change to fit your analysis style.
Tips:
Use alongside other technical tools to confirm entry and exit points.
Watch for divergences between the index and price to anticipate possible reversals.
Monitoring extreme levels can help identify market turning points.
This indicator is not a buy or sell recommendation but an additional tool to help understand the overall market sentiment.
MACD Full [Titans_Invest]MACD Full — A Smarter, More Flexible MACD.
Looking for a MACD with real customization power?
We present one of the most complete public MACD indicators available on TradingView.
It maintains the classic MACD structure but is enhanced with 20 fully customizable long entry conditions and 20 short entry conditions , giving you precise control over your strategy.
Plus, it’s fully automation-ready, making it ideal for quantitative systems and algorithmic trading.
Whether you're a discretionary trader or a bot developer, this tool is built to seamlessly adapt to your style.
⯁ WHAT IS THE MACD❓
The Moving Average Convergence Divergence (MACD) is a technical analysis indicator developed by Gerald Appel. It measures the relationship between two moving averages of a security’s price to identify changes in momentum, direction, and strength of a trend. The MACD is composed of three components: the MACD line, the signal line, and the histogram.
⯁ HOW TO USE THE MACD❓
The MACD is calculated by subtracting the 26-period Exponential Moving Average (EMA) from the 12-period EMA. A 9-period EMA of the MACD line, called the signal line, is then plotted on top of the MACD line. The MACD histogram represents the difference between the MACD line and the signal line.
Here are the primary signals generated by the MACD:
Bullish Crossover: When the MACD line crosses above the signal line, indicating a potential buy signal.
Bearish Crossover: When the MACD line crosses below the signal line, indicating a potential sell signal.
Divergence: When the price of the security diverges from the MACD, suggesting a potential reversal.
Overbought/Oversold Conditions: Indicated by the MACD line moving far away from the signal line, though this is less common than in oscillators like the RSI.
⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
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🔹 CONDITIONS TO BUY 📈
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 MACD > Signal Smoothing
🔹 MACD < Signal Smoothing
🔹 Histogram > 0
🔹 Histogram < 0
🔹 Histogram Positive
🔹 Histogram Negative
🔹 MACD > 0
🔹 MACD < 0
🔹 Signal > 0
🔹 Signal < 0
🔹 MACD > Histogram
🔹 MACD < Histogram
🔹 Signal > Histogram
🔹 Signal < Histogram
🔹 MACD (Crossover) Signal
🔹 MACD (Crossunder) Signal
🔹 MACD (Crossover) 0
🔹 MACD (Crossunder) 0
🔹 Signal (Crossover) 0
🔹 Signal (Crossunder) 0
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🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 MACD > Signal Smoothing
🔸 MACD < Signal Smoothing
🔸 Histogram > 0
🔸 Histogram < 0
🔸 Histogram Positive
🔸 Histogram Negative
🔸 MACD > 0
🔸 MACD < 0
🔸 Signal > 0
🔸 Signal < 0
🔸 MACD > Histogram
🔸 MACD < Histogram
🔸 Signal > Histogram
🔸 Signal < Histogram
🔸 MACD (Crossover) Signal
🔸 MACD (Crossunder) Signal
🔸 MACD (Crossover) 0
🔸 MACD (Crossunder) 0
🔸 Signal (Crossover) 0
🔸 Signal (Crossunder) 0
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
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Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
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📜 SCRIPT : MACD Full
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
P&L Entry Zone Marker (clean)This indicator is a simple visual calculator for futures traders.
It helps you track your long and short entry zones based on position size and average price.
🔹 Green line – recalculated long entry after averaging down.
🔹 Red line – short entry point.
You can manually input your initial entry, volume, averaging volume, and averaging price.
The script calculates your new average entry for long positions and plots both lines as full horizontal levels across the chart.
✳️ Useful for:
Visualizing break-even zones
Planning P&L zones for hedged positions
Quickly aligning your trades with market structure
✅ Clean version — no labels, just lines.
📉 Works on all symbols and timeframes.
DWMY Opens (for aggr. charts) by Koenigsegg🟣 DWMY Opens (for Aggregated Charts) by Koenigsegg
Revolutionary compatibility with aggregated charts – This indicator represents a significant breakthrough in displaying Daily, Weekly, Monthly, and Yearly opening levels on aggregated chart types where traditional DWMY indicators have historically failed to function properly.
Complete aggregated chart support – Unlike previous Daily Weekly Monthly Yearly Opens indicators that experienced severe limitations when pulling data from non-standard chart types, this version is specifically engineered to work flawlessly with aggregated charts, range bars, Renko charts, Point & Figure charts, and all other non-time-based chart constructions.
Persistent horizontal reference lines – The indicator draws four distinct horizontal lines representing the opening prices of the current Daily, Weekly, Monthly, and Yearly periods, extending these levels forward into future bars to provide clear reference points for key support and resistance analysis.
Advanced customization capabilities – Features comprehensive user controls including custom label naming for each timeframe, adjustable line colors with independent color selection for Daily, Weekly, Monthly, and Yearly levels, configurable line width settings, and variable label font sizes ranging from tiny to huge.
Dynamic label positioning system – Implements a sophisticated label placement mechanism with configurable tick offset positioning and fixed end-bars-ahead projection, ensuring labels remain visible and properly positioned regardless of chart zoom level or timeframe.
Intelligent period detection logic – Utilizes advanced Pine Script time change detection algorithms specifically optimized for aggregated charts, accurately identifying new Daily, Weekly, Monthly, and Yearly periods even when traditional time-based functions fail on non-standard chart types.
Performance-optimized architecture – Built with efficient persistent variable storage using the var keyword, minimizing computational overhead while maintaining real-time updates across all timeframe levels simultaneously.
Professional visual presentation – Delivers clean, uncluttered chart visualization with strategically positioned labels that clearly identify each timeframe level without interfering with price action analysis.
Universal market compatibility – Functions seamlessly across all asset classes including stocks, forex, cryptocurrencies, commodities, and indices, adapting automatically to different tick sizes and price scales through syminfo.mintick integration.
Pine Script v6 foundation – Leverages the latest Pine Script version 6 capabilities, ensuring optimal performance, stability, and compatibility with current and future TradingView platform updates.
This indicator solves a critical limitation that has long plagued traders using aggregated chart types, finally enabling reliable access to essential Daily, Weekly, Monthly, and Yearly opening levels that serve as fundamental support and resistance zones in technical analysis. The breakthrough lies in its ability to maintain accurate period detection and level plotting regardless of the underlying chart construction methodology.
🟣 How It Works
Automatic period detection – The indicator continuously monitors for time changes across four distinct timeframes using ta.change(time()) functions for Daily and Weekly periods, month transitions for Monthly levels, and year changes for Yearly opens, ensuring precise identification of new period beginnings.
Real-time level updates – When a new period is detected, the indicator captures the opening price at that exact moment and immediately establishes a horizontal line from that bar extending forward to a configurable number of bars ahead, creating persistent reference levels.
Dynamic line management – Each timeframe maintains its own dedicated line object and label, with the indicator continuously updating the endpoint coordinates and label positions as new bars form, ensuring the levels always project the specified distance into the future.
Intelligent label placement – Labels are positioned at the end of each line with automatic vertical offset based on the symbol’s minimum tick size, preventing overlap with price action while maintaining clear identification of each timeframe level.
🟣 Pro Tips for Optimal Usage
Multi-timeframe confluence – Look for areas where multiple DWMY levels converge within close proximity, as these zones typically act as stronger support or resistance levels due to increased market participant attention at these psychological price points.
Breakout confirmation strategy – When price breaks above or below a significant DWMY level with strong volume, the broken level often transforms into support (if broken upward) or resistance (if broken downward), providing excellent entry and exit reference points.
Range trading opportunities – On ranging markets, use Daily and Weekly opens as potential reversal zones, especially when price approaches these levels during low-volume periods or near session opens when institutional activity increases.
Timeframe alignment technique – For swing trading, prioritize trades that align with the direction of the break from Weekly or Monthly opens, while using Daily opens for precise entry timing and position management.
Chart type optimization – This indicator excels on Renko, Range, and Point & Figure charts where traditional time-based DWMY indicators fail, making it invaluable for traders who prefer these aggregated chart types for cleaner price action analysis.
Important Disclaimer:
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All trading involves risk, and past performance does not guarantee future results. Please conduct your own research and consult with a qualified financial advisor before making any trading decisions. The author is not responsible for any losses incurred from using this indicator.
CCO_LibraryLibrary "CCO_Library"
Contrarian Crowd Oscillator (CCO) Library - Multi-oscillator consensus indicator for contrarian trading signals
@author B3AR_Trades
calculate_oscillators(rsi_length, stoch_length, cci_length, williams_length, roc_length, mfi_length, percentile_lookback, use_rsi, use_stochastic, use_williams, use_cci, use_roc, use_mfi)
Calculate normalized oscillator values
Parameters:
rsi_length (simple int) : (int) RSI calculation period
stoch_length (int) : (int) Stochastic calculation period
cci_length (int) : (int) CCI calculation period
williams_length (int) : (int) Williams %R calculation period
roc_length (int) : (int) ROC calculation period
mfi_length (int) : (int) MFI calculation period
percentile_lookback (int) : (int) Lookback period for CCI/ROC percentile ranking
use_rsi (bool) : (bool) Include RSI in calculations
use_stochastic (bool) : (bool) Include Stochastic in calculations
use_williams (bool) : (bool) Include Williams %R in calculations
use_cci (bool) : (bool) Include CCI in calculations
use_roc (bool) : (bool) Include ROC in calculations
use_mfi (bool) : (bool) Include MFI in calculations
Returns: (OscillatorValues) Normalized oscillator values
calculate_consensus_score(oscillators, use_rsi, use_stochastic, use_williams, use_cci, use_roc, use_mfi, weight_by_reliability, consensus_smoothing)
Calculate weighted consensus score
Parameters:
oscillators (OscillatorValues) : (OscillatorValues) Individual oscillator values
use_rsi (bool) : (bool) Include RSI in consensus
use_stochastic (bool) : (bool) Include Stochastic in consensus
use_williams (bool) : (bool) Include Williams %R in consensus
use_cci (bool) : (bool) Include CCI in consensus
use_roc (bool) : (bool) Include ROC in consensus
use_mfi (bool) : (bool) Include MFI in consensus
weight_by_reliability (bool) : (bool) Apply reliability-based weights
consensus_smoothing (int) : (int) Smoothing period for consensus
Returns: (float) Weighted consensus score (0-100)
calculate_consensus_strength(oscillators, consensus_score, use_rsi, use_stochastic, use_williams, use_cci, use_roc, use_mfi)
Calculate consensus strength (agreement between oscillators)
Parameters:
oscillators (OscillatorValues) : (OscillatorValues) Individual oscillator values
consensus_score (float) : (float) Current consensus score
use_rsi (bool) : (bool) Include RSI in strength calculation
use_stochastic (bool) : (bool) Include Stochastic in strength calculation
use_williams (bool) : (bool) Include Williams %R in strength calculation
use_cci (bool) : (bool) Include CCI in strength calculation
use_roc (bool) : (bool) Include ROC in strength calculation
use_mfi (bool) : (bool) Include MFI in strength calculation
Returns: (float) Consensus strength (0-100)
classify_regime(consensus_score)
Classify consensus regime
Parameters:
consensus_score (float) : (float) Current consensus score
Returns: (ConsensusRegime) Regime classification
detect_signals(consensus_score, consensus_strength, consensus_momentum, regime)
Detect trading signals
Parameters:
consensus_score (float) : (float) Current consensus score
consensus_strength (float) : (float) Current consensus strength
consensus_momentum (float) : (float) Consensus momentum
regime (ConsensusRegime) : (ConsensusRegime) Current regime classification
Returns: (TradingSignals) Trading signal conditions
calculate_cco(rsi_length, stoch_length, cci_length, williams_length, roc_length, mfi_length, consensus_smoothing, percentile_lookback, use_rsi, use_stochastic, use_williams, use_cci, use_roc, use_mfi, weight_by_reliability, detect_momentum)
Calculate complete CCO analysis
Parameters:
rsi_length (simple int) : (int) RSI calculation period
stoch_length (int) : (int) Stochastic calculation period
cci_length (int) : (int) CCI calculation period
williams_length (int) : (int) Williams %R calculation period
roc_length (int) : (int) ROC calculation period
mfi_length (int) : (int) MFI calculation period
consensus_smoothing (int) : (int) Consensus smoothing period
percentile_lookback (int) : (int) Percentile ranking lookback
use_rsi (bool) : (bool) Include RSI
use_stochastic (bool) : (bool) Include Stochastic
use_williams (bool) : (bool) Include Williams %R
use_cci (bool) : (bool) Include CCI
use_roc (bool) : (bool) Include ROC
use_mfi (bool) : (bool) Include MFI
weight_by_reliability (bool) : (bool) Apply reliability weights
detect_momentum (bool) : (bool) Calculate momentum and acceleration
Returns: (CCOResult) Complete CCO analysis results
calculate_cco_default()
Calculate CCO with default parameters
Returns: (CCOResult) CCO result with standard settings
cco_consensus_score()
Get just the consensus score with default parameters
Returns: (float) Consensus score (0-100)
cco_consensus_strength()
Get just the consensus strength with default parameters
Returns: (float) Consensus strength (0-100)
is_panic_bottom()
Check if in panic bottom condition
Returns: (bool) True if panic bottom signal active
is_euphoric_top()
Check if in euphoric top condition
Returns: (bool) True if euphoric top signal active
bullish_consensus_reversal()
Check for bullish consensus reversal
Returns: (bool) True if bullish reversal detected
bearish_consensus_reversal()
Check for bearish consensus reversal
Returns: (bool) True if bearish reversal detected
bearish_divergence()
Check for bearish divergence
Returns: (bool) True if bearish divergence detected
bullish_divergence()
Check for bullish divergence
Returns: (bool) True if bullish divergence detected
get_regime_name()
Get current regime name
Returns: (string) Current consensus regime name
get_contrarian_signal()
Get contrarian signal
Returns: (string) Current contrarian trading signal
get_position_multiplier()
Get position size multiplier
Returns: (float) Recommended position sizing multiplier
OscillatorValues
Individual oscillator values
Fields:
rsi (series float) : RSI value (0-100)
stochastic (series float) : Stochastic value (0-100)
williams (series float) : Williams %R value (0-100, normalized)
cci (series float) : CCI percentile value (0-100)
roc (series float) : ROC percentile value (0-100)
mfi (series float) : Money Flow Index value (0-100)
ConsensusRegime
Consensus regime classification
Fields:
extreme_bearish (series bool) : Extreme bearish consensus (<= 20)
moderate_bearish (series bool) : Moderate bearish consensus (20-40)
mixed (series bool) : Mixed consensus (40-60)
moderate_bullish (series bool) : Moderate bullish consensus (60-80)
extreme_bullish (series bool) : Extreme bullish consensus (>= 80)
regime_name (series string) : Text description of current regime
contrarian_signal (series string) : Contrarian trading signal
TradingSignals
Trading signals
Fields:
panic_bottom_signal (series bool) : Extreme bearish consensus with high strength
euphoric_top_signal (series bool) : Extreme bullish consensus with high strength
consensus_reversal_bullish (series bool) : Bullish consensus reversal
consensus_reversal_bearish (series bool) : Bearish consensus reversal
bearish_divergence (series bool) : Bearish price-consensus divergence
bullish_divergence (series bool) : Bullish price-consensus divergence
strong_consensus (series bool) : High consensus strength signal
CCOResult
Complete CCO calculation results
Fields:
consensus_score (series float) : Main consensus score (0-100)
consensus_strength (series float) : Consensus strength (0-100)
consensus_momentum (series float) : Rate of consensus change
consensus_acceleration (series float) : Rate of momentum change
oscillators (OscillatorValues) : Individual oscillator values
regime (ConsensusRegime) : Regime classification
signals (TradingSignals) : Trading signals
position_multiplier (series float) : Recommended position sizing multiplier
Math by Thomas Liquidity PoolDescription
Math by Thomas Liquidity Pool is a TradingView indicator designed to visually identify potential liquidity pools on the chart by detecting areas where price forms clusters of equal highs or equal lows.
Bullish Liquidity Pools (Green Boxes): Marked below price where two adjacent candles have similar lows within a specified difference, indicating potential demand zones or stop loss clusters below support.
Bearish Liquidity Pools (Red Boxes): Marked above price where two adjacent candles have similar highs within the difference threshold, indicating potential supply zones or stop loss clusters above resistance.
This tool helps traders spot areas where smart money might hunt stop losses or where price is likely to react, providing valuable insight for trade entries, exits, and risk management.
Features:
Adjustable box height (vertical range) in points.
Adjustable maximum difference threshold between candle highs/lows to consider them equal.
Boxes automatically extend forward for visibility and delete when price sweeps through or after a defined lifetime.
Separate visual zones for bullish and bearish liquidity with customizable colors.
How to Use
Add the Indicator to your chart (preferably on instruments like Nifty where point-based thresholds are meaningful).
Adjust Inputs:
Box Height: Set the vertical size of the liquidity zones (default 15 points).
Max Difference Between Highs/Lows: Set the max price difference to consider two candle highs or lows as “equal” (default 10 points).
Box Lifetime: How many bars the box stays visible if not swept (default 120 bars).
Interpret Boxes:
Green Boxes (Bullish Liquidity Pools): Areas of potential demand and stop loss clusters below price. Watch for price bounces or accumulation near these zones.
Red Boxes (Bearish Liquidity Pools): Areas of potential supply and stop loss clusters above price. Watch for price rejections or distribution near these zones.
Trading Strategy Tips:
Use these zones to anticipate where stop loss hunting or liquidity sweeps may occur.
Combine with your Order Block, Fair Value Gap, and Market Structure tools for higher probability setups.
Manage risk by avoiding entries into price regions just before large liquidity pools get swept.
Automatic Cleanup:
Boxes delete automatically once price breaks above (for bearish zones) or below (for bullish zones) the zone or after the set lifetime.
AMF_LibraryLibrary "AMF_Library"
Adaptive Momentum Flow (AMF) Library - A comprehensive momentum oscillator that adapts to market volatility
@author B3AR_Trades
f_ema(source, length)
Custom EMA calculation that accepts a series length
Parameters:
source (float) : (float) Source data for calculation
length (float) : (float) EMA length (can be series)
Returns: (float) EMA value
f_dema(source, length)
Custom DEMA calculation that accepts a series length
Parameters:
source (float) : (float) Source data for calculation
length (float) : (float) DEMA length (can be series)
Returns: (float) DEMA value
f_sum(source, length)
Custom sum function for rolling sum calculation
Parameters:
source (float) : (float) Source data for summation
length (int) : (int) Number of periods to sum
Returns: (float) Sum value
get_average(data, length, ma_type)
Get various moving average types for fixed lengths
Parameters:
data (float) : (float) Source data
length (simple int) : (int) MA length
ma_type (string) : (string) MA type: "SMA", "EMA", "WMA", "DEMA"
Returns: (float) Moving average value
calculate_adaptive_lookback(base_length, min_lookback, max_lookback, volatility_sensitivity)
Calculate adaptive lookback length based on volatility
Parameters:
base_length (int) : (int) Base lookback length
min_lookback (int) : (int) Minimum allowed lookback
max_lookback (int) : (int) Maximum allowed lookback
volatility_sensitivity (float) : (float) Sensitivity to volatility changes
Returns: (int) Adaptive lookback length
get_volatility_ratio()
Get current volatility ratio
Returns: (float) Current volatility ratio vs 50-period average
calculate_volume_analysis(vzo_length, smooth_length, smooth_type)
Calculate volume-based buying/selling pressure
Parameters:
vzo_length (int) : (int) Lookback length for volume analysis
smooth_length (simple int) : (int) Smoothing length
smooth_type (string) : (string) Smoothing MA type
Returns: (float) Volume analysis value (-100 to 100)
calculate_amf(base_length, smooth_length, smooth_type, signal_length, signal_type, min_lookback, max_lookback, volatility_sensitivity, medium_multiplier, slow_multiplier, vzo_length, vzo_smooth_length, vzo_smooth_type, price_vs_fast_weight, fast_vs_medium_weight, medium_vs_slow_weight, vzo_weight)
Calculate complete AMF oscillator
Parameters:
base_length (int) : (int) Base lookback length
smooth_length (simple int) : (int) Final smoothing length
smooth_type (string) : (string) Final smoothing MA type
signal_length (simple int) : (int) Signal line length
signal_type (string) : (string) Signal line MA type
min_lookback (int) : (int) Minimum adaptive lookback
max_lookback (int) : (int) Maximum adaptive lookback
volatility_sensitivity (float) : (float) Volatility adaptation sensitivity
medium_multiplier (float) : (float) Medium DEMA length multiplier
slow_multiplier (float) : (float) Slow DEMA length multiplier
vzo_length (int) : (int) Volume analysis lookback
vzo_smooth_length (simple int) : (int) Volume analysis smoothing
vzo_smooth_type (string) : (string) Volume analysis smoothing type
price_vs_fast_weight (float) : (float) Weight for price vs fast DEMA
fast_vs_medium_weight (float) : (float) Weight for fast vs medium DEMA
medium_vs_slow_weight (float) : (float) Weight for medium vs slow DEMA
vzo_weight (float) : (float) Weight for volume analysis component
Returns: (AMFResult) Complete AMF calculation results
calculate_amf_default()
Calculate AMF with default parameters
Returns: (AMFResult) AMF result with standard settings
amf_oscillator()
Get just the main AMF oscillator value with default parameters
Returns: (float) Main AMF oscillator value
amf_signal()
Get just the AMF signal line with default parameters
Returns: (float) AMF signal line value
is_overbought(overbought_level)
Check if AMF is in overbought condition
Parameters:
overbought_level (float) : (float) Overbought threshold (default 70)
Returns: (bool) True if overbought
is_oversold(oversold_level)
Check if AMF is in oversold condition
Parameters:
oversold_level (float) : (float) Oversold threshold (default -70)
Returns: (bool) True if oversold
bullish_crossover()
Detect bullish crossover (main line crosses above signal)
Returns: (bool) True on bullish crossover
bearish_crossover()
Detect bearish crossover (main line crosses below signal)
Returns: (bool) True on bearish crossover
AMFResult
AMF calculation results
Fields:
main_oscillator (series float) : The main AMF oscillator value (-100 to 100)
signal_line (series float) : The signal line for crossover signals
dema_fast (series float) : Fast adaptive DEMA value
dema_medium (series float) : Medium adaptive DEMA value
dema_slow (series float) : Slow adaptive DEMA value
volume_analysis (series float) : Volume-based buying/selling pressure (-100 to 100)
adaptive_lookback (series int) : Current adaptive lookback length
volatility_ratio (series float) : Current volatility ratio vs average
Market Structure TableJust learning pinescript...
Indicator should summarise market structure in a table and overplot pivot points on chart
MACD-TITANIndicator Description: MACD-TITAN
MACD-TITAN is an enhanced version of the traditional MACD (Moving Average Convergence Divergence) indicator. It features a modern visual design, vibrant colors, and a clear interpretation of market momentum. The indicator is designed to help traders identify trend strength and potential reversals more effectively.
Configurable Parameters (default values)
Fast Length: 12 – period of the fast moving average
Slow Length: 26 – period of the slow moving average
Signal Smoothing: 9 – smoothing period for the signal line
These settings determine how sensitive the indicator is to price changes and can be adjusted to fit different trading styles.
Visual Interpretation
Strong Green Histogram: bullish momentum increasing
Weak Green Histogram: bullish momentum weakening
Strong Red Histogram: bearish momentum increasing
Weak Red Histogram: bearish momentum weakening
Additional lines:
MACD Line (turquoise): represents current trend momentum
Signal Line (orange): used for crossover confirmations with the MACD line
Built-in Alerts
The indicator includes two native alert conditions:
When the histogram crosses from positive to negative: possible start of a bearish trend
When the histogram crosses from negative to positive: possible start of a bullish trend
These alerts help traders track key momentum shifts.
Usage Tips
This indicator can be used both for spotting potential reversals and for tracking the strength of an ongoing trend. For better reliability, it is recommended to combine it with other tools such as support/resistance levels, RSI, or volume analysis.
BreakoutLibrary "Breakout"
init()
method run(state, opts)
Namespace types: BreakoutState
Parameters:
state (BreakoutState)
opts (BreakoutOpts)
BreakoutState
Fields:
levelUps (array)
levelDowns (array)
levelUpTargets (array)
levelDownTargets (array)
levelUpConfirmed (array)
levelDownConfirmed (array)
levelUpNumLevels (array)
levelDownNumLevels (array)
breakoutSignalUp (series bool)
breakoutSignalDown (series bool)
BreakoutOpts
Fields:
canConfirmUp (series bool)
canConfirmDown (series bool)
numLevelMinToConfirm (series int)
numLevelMaxToConfirm (series int)
zigZagPeriod (series int)
rsi (series float)
rsiMA (series float)
Adaptive MACD Deluxe [AlgoAlpha]OVERVIEW
This script is an advanced rework of the classic MACD indicator, designed to be more adaptive, visually informative, and customizable. It enhances the original MACD formula using a dynamic feedback loop and a correlation-based weighting system that adjusts in real-time based on how deterministic recent price action is. The signal line is flexible, offering several smoothing types including Heiken Ashi, while the histogram is color-coded with gradients to help users visually identify momentum shifts. It also includes optional normalization by volatility, allowing MACD values to be interpreted as relative percentage moves, making the indicator more consistent across different assets and timeframes.
CONCEPTS
This version of MACD introduces a deterministic weight based on R-squared correlation with time, which modulates how fast or slow the MACD adapts to price changes. Higher correlation means smoother, slower MACD responses, and low correlation leads to quicker reaction. The momentum calculation blends traditional EMA math with feedback and damping components to create a smoother, less noisy series. Heiken Ashi is optionally used for signal smoothing to better visualize short-term trend bias. When normalization is enabled, the MACD is scaled by an EMA of the high-low range, converting it into a bounded, volatility-relative indicator. This makes extreme readings more meaningful across markets.
FEATURES
The script offers six distinct options for signal line smoothing: EMA, SMA, SMMA (RMA), WMA, VWMA, and a custom Heiken Ashi mode based on the MACD series. Each option provides a different response speed and smoothing behavior, allowing traders to match the indicator’s behavior to their strategy—whether it's faster reaction or reduced noise.
Normalization is another key feature. When enabled, MACD values are scaled by a volatility proxy, converting the indicator into a relative percentage. This helps standardize the MACD across different assets and timeframes, making overbought and oversold readings more consistent and easier to interpret.
Threshold zones can be customized using upper and lower boundaries, with inner zones for early warnings. These zones are highlighted on the chart with subtle background fills and directional arrows when MACD enters or exits key levels. This makes it easier to spot strong or weak reversals at a glance.
Lastly, the script includes multiple built-in alerts. Users can set alerts for MACD crossovers, histogram flips above or below zero, and MACD entries into strong or weak reversal zones. This allows for hands-free monitoring and quick decision-making without staring at the chart.
USAGE
To use this script, choose your preferred signal smoothing type, enable normalization if you want MACD values relative to volatility, and adjust the threshold zones to fit your asset or timeframe. Use the colored histogram to detect changes in momentum strength—brighter colors indicate rising strength, while faded colors imply weakening. Heiken Ashi mode smooths out noise and provides clearer signals, especially useful in choppy conditions. Use alert conditions for crossover and reversal detection, or monitor the arrow markers for entries into potential exhaustion zones. This setup works well for trend following, momentum trading, and reversal spotting across all market types.
RSI Reversal (instelbare RRR)made by Laila
(Indicator in the making)
How does it work?
Using RSI to decide:
If the RSI drops below 30 (oversold), it opens a buy (long) position.
If the RSI rises above 70 (overbought), it opens a sell (short) position.
Setting risk and reward:
You choose how much of the price you're willing to risk, for example 1%.
You also set how much reward you want, like 2 times the risk (2:1).
So if the entry price is 100:
Stop loss would be at 99 (1% down),
Take profit would be at 102 (2% up).
The strategy handles everything automatically:
When the RSI condition is met, it enters a trade.
It immediately sets both TP and SL levels.
The trade closes automatically when either TP or SL is hit.
Macro Dashboard Multi-TickerThis indicator gives you a compact, high-impact overview of up to 10 custom assets — showing whether each is currently trading above or below a key moving average on a shared timeframe.
🟩 Above MA = colored bar
⬛ Below MA = dimmed bar
Features:
Monitor up to 10 symbols (stocks, crypto, ETFs, etc.)
Customize:
- Symbol
- Color
- Timeframe
- MA type (EMA/SMA)
- MA length
Shared logic keeps the layout clean and consistent.
Use Cases:
- Build a macro trend dashboard for SPY, QQQ, BTC, ETH, ARKK, IWM, DXY, VIX, etc.
- Confirm risk-on alignment
- Identify broad market rotation or weakness
- Pair with individual asset setups to stay in sync with the environment
This tool is ideal for traders who want a one-glance check on market strength without cluttering their main charts. It's fast, flexible, and highly visual.
