cd_HTF_bias_CxOverview:
No matter our trading style or model, to increase our success rate, we must move in the direction of the trend and align with the Higher Time Frame (HTF). Trading "gurus" call this the HTF bias. While we small fish tend to swim in all directions, the smart way is to flow with the big wave and the current. This indicator is designed to help us anticipate that major wave.
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Details and Usage:
This indicator observes HTF price action across preferably seven different pairs, following specific rules. It confirms potential directional moves using CISD levels on a Medium Time Frame (MTF). In short, it forecasts the likely direction (HTF bias). The user can then search for trade opportunities aligned with this bias on a Lower Time Frame (LTF), using their preferred pair, entry model, and style.
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Timeframe Alignment:
The commonly accepted LTF/MTF/HTF combinations include:
• 1m – 15m – H4
• 3m – H1 – Daily / 3m – 30m – Daily
• 5m – H1 – Daily
• 15m – H4 – Weekly
• H1 – Daily – Monthly
• H4 – Weekly – Quarterly
Example: If you're trading with a 3m model on a 30m/3m setup, you should seek trades in the direction of the H1/Daily bias.
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How It Works:
The indicator first looks for sweeps on the selected HTF — when any of the last four candles are swept, the first condition is met.
The second step is confirmation with a CISD close on the MTF — once a candle closes above/below the CISD level, the second condition is fulfilled. This suggests the price has made its directional decision.
Example: If a previous HTF candle is swept and we receive a bearish CISD confirmation on H1, the HTF bias becomes bearish.
After this, you may switch to a more granular setup like HTF: 30m and MTF: 3m to look for trade entries aligned with the bias (e.g., 30m sweep + 3m CISD).
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How Is Bias Determined?
• HTF Sweep + MTF CISD = SC (Sweep & CISD)
• Latest Bullish SC → Bias: Bullish
• Latest Bearish SC → Bias: Bearish
• Price closes above the last Bearish SC → Bias: Strong Bullish
• Price closes below the last Bullish SC → Bias: Strong Bearish
• Strong Bullish bias + Bearish CISD (without HTF sweep) → Bias: Bullish
• Strong Bearish bias + Bullish CISD (without HTF sweep) → Bias: Bearish
• Bearish price violates SC high, but Bullish SC is untouched → Bias: Bullish
• Bullish price violates SC low, but Bearish SC is untouched → Bias: Bearish
• If neither side generates SC → Bias: No Bias
The logic is built on the idea that a price overcoming resistance is stronger, and encountering resistance is weaker. This model is based on the well-known “Daily Bias” structure, but with personal refinements.
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What’s on the Screen?
• Classic HTF zones (boxes)
• Potential MTF CISD levels
• Confirmed MTF lines
• Sweep zones when HTF sweeps occur
• Result table showing current bias status
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Usage:
• Select HTF and MTF timeframes aligned with your trading timeframe.
• Adjust color and position settings as needed.
• Enter up to seven pairs to track via the menu.
• Use the checkbox next to each pair to enable/disable them.
• If “Ignore these assets” is checked, all pairs will be disabled, and only the currently open chart pair will be tracked.
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Alerts:
You can choose alerts for Bullish, Bearish, Strong Bullish, or Strong Bearish conditions.
There are two types of alert sources:
1. From the indicator’s internal list
2. From TradingView’s watchlist
Visual example:
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How I Use It:
• For spot trades, I use HTF: Weekly and MTF: H4 and look for Bullish or Strong Bullish pairs.
• For scalping, I follow bias from HTF: Daily and MTF: H1.
Example: If the indicator shows a Bearish HTF Bias, I switch to HTF: 30m and MTF: 3m and enter trades once bearish conditions are met (timeframe alignment).
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Important Notes:
• The indicator defines CISD levels only at HTF high and low levels.
• If your chart is on a higher timeframe than your selected HTF/MTF, no data will appear.
Example: If HTF = H1 and MTF = 5m, opening a chart on H4 will result in a blank screen.
• The drawn CISD level on screen is the MTF CISD level.
• Not every alert should be traded. Always confirm with personal experience and visual validation.
• Receiving multiple Strong Bullish/Bearish alerts is intentional. (Trick 😊)
• Please share your feedback and suggestions!
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And Most Importantly:
Don't leave street animals without water and food!
Happy trading!
Cerca negli script per "track"
Discord Levels (Label Toggle)This indicator is designed to streamline your multi-asset level tracking by displaying custom price levels directly on your chart for up to eight different stocks. It allows you to define key support, resistance, and moving average levels, enhancing your analysis across various instruments.
Key Features:
Multi-Stock Level Display: Track important levels for up to 8 distinct stock symbols simultaneously.
Customizable Level Inputs: Define all your desired price levels using a simple space-separated string for each stock.
Intelligent Color-Coding: Levels are automatically color-coded for quick identification based on the associated notes in your input string:
White Line: Standard price levels (e.g., 123.45).
Yellow Line: Levels designated as 200 Daily EMA (e.g., 18.70=daily 200 ema).
Blue Line: Levels designated as 50 Daily EMA (e.g., 18.70=daily 50 ema).
Gray Line: Levels designated as 34 Daily EMA (e.g., 18.70=daily 34 ema).
Green Line: Levels designated as 9 Daily EMA (e.g., 18.70=daily 9 ema).
Red Line: Critical or Cautionary levels (e.g., 9.00=cautionary).
Dynamic Label Positioning: Price labels are displayed next to the lines, dynamically positioned to the right of the current bar (30 bars offset) for optimal visibility across different timeframes.
Global Label Toggle: Easily enable or disable all price labels from the indicator's settings.
How to Use:
Input Stock Symbol: For each slot (Stock 1 to Stock 8) you wish to use, enter the exact TradingView symbol (e.g., AAPL, MSFT, TSLA).
Input Levels String: In the corresponding "Levels" input field, enter your desired price levels separated by spaces.
Basic Level: Just enter the number (e.g., 12.34).
Levels with Notes: Use the format PRICE=NOTE for specific annotations (e.g., 18.70=daily 200 ema, 9.00=cautionary).
Supported Notes for Automatic Coloring: daily 200 ema, daily 50 ema, daily 34 ema, daily 9 ema, cautionary, critical. (Case-insensitive)
Manage Slots: If you need to track more than 8 stocks, simply clear the symbol and levels for an old stock and use that slot for your new entry.
This indicator is a powerful tool for traders who rely on fixed price levels and moving averages across multiple securities, providing clear visual cues without cluttering your main chart analysis.
Perfect MA Touch – Full Setup 1,3,5,7,8,9This indicator helps you track a precise candle countdown from a moving average touch, labeling key bars (1, 3, 5, 7, 8, 9) for timing entries and momentum setups — with optional coloring, alerts, and full customization.
What It Detects
1. MA Touch Trigger
The sequence starts when any selected moving average (up to 6 MAs, customizable) is touched by the candle's high/low range.
This "perfect touch" initiates the count and labels that candle as "1".
2. Candle Number Labels
After a perfect MA touch:
Candle 1 = the bar that touches the MA
Candle 3 = two bars after Candle 1
Candle 5 = the fifth bar after the touch
Candle 7 = third bar after Candle 5
Candle 8 = fourth bar after Candle 5
Candle 9 = fifth bar after Candle 5
It creates a time-based sequence you can use to anticipate reactions or momentum shifts.
3. Customization
You can:
Choose between EMA or SMA for each MA (6 total)
Set custom lengths for each MA (9, 20, 50, 100, 150, 200)
Choose which candle numbers (1, 3, 5, 7, 8, 9) to highlight
Pick font size and label color
4. Highlighting and Alerts
Highlight candles (with color) when certain bars (like 3, 5, 7) print
Alerts are available for all tracked bars (1, 3, 5, 7, 8, 9)
Use Case Example
Let’s say you want to enter trades on the 3rd candle after a perfect MA touch:
You set the script to highlight candle 3.
When a candle hits your chosen MA (say EMA 9), it’s labeled “1”.
Two bars later, bar 3 appears — giving you a timed signal to enter if price behavior aligns.
This method is especially useful when paired with:
Volume confirmation
Breakout or reversal patterns
Support/resistance or order block zones
Multi-Position DashMulti-Position Dash — Risk Dashboard for Forex, Stocks & Indices
Overview:
The Multi-Position Dash is a highly customizable trading dashboard designed to help active traders manage up to 8 simultaneous positions across Forex, Stocks, and Indices. Whether you're trading single entries, layering positions, using DCA (Dollar Cost Averaging), or running complex hedging setups, this tool provides essential, real-time risk and P&L insights—directly on your chart.
Key Features:
✔️ Supports Forex, Stocks, Indices — with automatic pip and contract conversions
✔️ Track up to 8 manual positions, each with customizable direction, lot size or contracts, entry price, Take Profit, and Stop Loss
✔️ Full GBP-based P&L and risk calculation, including automatic USD-to-GBP conversion for non-FX assets
✔️ Real-time display of:
Total potential Take Profit (GBP)
Total potential Stop Loss (GBP)
Risk % relative to account balance
Live P&L (GBP) based on current price
✔️ Breakeven price calculation, even across mixed-direction positions (DCA & hedging aware)
✔️ Visual breakeven line, live P&L arrows, and entry price markers
✔️ Shared Stop Loss option for all positions — perfect for DCA traders
✔️ Easy export strings for logging trades to external tools like spreadsheets
Ideal For:
✅ Forex traders using lot-based risk models
✅ Stock & Index traders wanting simplified contract-based position tracking
✅ Traders managing multiple active positions, with or without hedging
✅ Anyone needing at-a-glance P&L and risk monitoring, independent of broker platforms
Notes & Usage:
This is a manual tracking tool—you enter your positions, TP, SL levels, etc., and the dashboard calculates the rest. It does not place or manage live orders.
Supports both Long and Short positions.
All calculations are based on your inputs and market price—accuracy depends on maintaining your inputs properly.
Shared Stop Loss feature applies a single, unified stop across all active positions for simplified risk control in DCA setups.
GBP is used as the account currency—USD-to-GBP conversion is applied to stocks and indices as needed.
Disclaimer:
This tool is for educational and planning purposes only. It does not place or manage live trades, and is not a substitute for broker risk management tools. Always double-check your own position sizing and risk before placing live orders.
Liquidity Hunter HeatmapLiquidity Hunter (GPS Companion Tool)
Liquidity Hunter is a specialized script designed to help traders visualize and track potential liquidation zones, clusters, and imbalance traps in real-time. It is particularly useful for scalpers and short-term traders who rely on liquidity sweeps, stop hunts, and reversion plays.
This tool does not replicate open-source liquidation trackers. Instead, it uses a proprietary combination of volume surges, candle displacement, VWAP deviation, and high-timeframe wicks to infer areas of trapped traders and display them with clear, color-coded markers.
Key Features:
• Real-Time Liquidation Estimates: Detects where major stop losses (and potential liquidations) may have occurred, based on proprietary volume + price action logic.
• Cluster Strength Bubbles: Visual bubbles (scaled by cluster size) show where liquidations are stacking. Purple for bearish, white for bullish — intensity reflects strength.
• Pre-Liquidation Warning Zones: Highlights areas where price is likely to sweep liquidity before reversing, helping traders avoid chasing moves.
• Dollar-Based Labels (Optional): Displays the estimated value liquidated, helping traders size the significance of a move (e.g., $8.4M).
• Minimal Clutter Mode: Designed for intraday clarity — hides excess lines and uses bubbles, not shapes, for cleaner visualization.
Trend Flow Trail [AlgoAlpha]OVERVIEW
This script overlays a custom hybrid indicator called the Money Flow Trail which combines a volatility-based trend-following trail with a volume-weighted momentum oscillator. It’s built around two core components: the AlphaTrail—a dynamic band system influenced by Hull MA and volatility—and a smoothed Money Flow Index (MFI) that provides insights into buying or selling pressure. Together, these tools are used to color bars, generate potential reversal markers, and assist traders in identifying trend continuation or exhaustion phases in any market or timeframe.
CONCEPTS
The AlphaTrail calculates a volatility-adjusted channel around price using the Hull Moving Average as the base and an EMA of range as the spread. It adaptively shifts based on price interaction to capture trend reversals while avoiding whipsaws. The direction (bullish or bearish) determines both the band being tracked and how the trail locks in. The Money Flow Index (MFI) is derived from hlc3 and volume, measuring buying vs selling pressure, and is further smoothed with a short Hull MA to reduce noise while preserving structure. These two systems work in tandem: AlphaTrail governs directional context, while MFI refines the timing.
FEATURES
Dynamic AlphaTrail line with regime switching logic that controls directional bias and bar coloring.
Smoothed MFI with gradient coloring to visually communicate pressure and exhaustion levels.
Overbought/oversold thresholds (80/20), mid-level (50), and custom extreme zones (90/10) for deeper signal granularity.
Built-in take-profit signal logic: crossover of MFI into overbought with bullish AlphaTrail, or into oversold with bearish AlphaTrail.
Visual fills between price and AlphaTrail for clearer confirmation during trend phases.
Alerts for regime shifts, MFI crossovers, trail interactions, and bar color regime changes.
USAGE
Add the indicator to any chart. Use the AlphaTrail plot to define trend context: bullish (trailing below price) or bearish (trailing above). MFI values give supporting confirmation—favor long setups when MFI is rising and above 50 in a bullish regime, and shorts when MFI is falling and below 50 in a bearish regime. The colored fills help visually track strength; sharp changes in MFI crossing 80/20 or 90/10 zones often precede pullbacks or reversals. Use the plotted circles as optional take-profit signals when MFI and trend are extended. Adjust AlphaTrail length/multiplier and MFI smoothing to better match the asset’s volatility profile.
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.
VWAP Supply & Demand Zones PRO**Overview:**
This script represents a major evolution of the original "VWAP Supply and Demand Zones" indicator. Initially created to explore price interaction with VWAP, it has now matured into a robust and feature-rich tool for identifying high-probability zones of institutional buying and selling pressure. The update introduces volume and momentum validation, dynamic zone management, alert logic, and a visual dashboard (HUD) — all designed for improved precision and clarity. The structural improvements, anti-repainting logic, and significant added utility warranted releasing this as a new script rather than a minor update.
---
### What It Does:
This indicator dynamically detects **supply and demand zones** using VWAP-based logic combined with **volume** and **momentum confirmation**. When price crosses VWAP with strength, it identifies the potential zone of excess demand (below VWAP) or supply (above VWAP), marking it visually with colored regions on the chart.
Each zone is extended for a user-defined duration, monitored for touch interactions (tests), and tracked for possible breaks. The script helps traders interpret price behavior around these institutional zones as either **reversal** opportunities or **continuation** confirmation depending on context and strategy preference.
---
### How It Works:
* **VWAP Basis**: Zones are anchored at VWAP at the time of a significant cross.
* **Volume & Momentum Filters**: Crosses are only considered valid if backed by above-average volume and notable price momentum.
* **Zone Drawing**: Validated supply and demand zones are drawn as boxes on the chart. Each is extended forward for a customizable number of bars.
* **Touch Counting**: Zones track the number of price touches. Alerts are issued after a user-defined number of tests.
* **Break Detection**: If price closes significantly beyond a zone boundary, the zone is marked as broken and visually dimmed.
* **Visual Dashboard (HUD)**: A compact real-time HUD displays VWAP value, active zone counts, and current market bias.
---
### How to Use It:
**Reversal Trading:**
* Look for price **rejecting** a zone after touching it.
* Use rejection candles or secondary indicators (e.g., RSI divergence) to confirm.
* These setups may offer low-risk entries when price respects the zone.
**Continuation Trading:**
* A **break of a zone** suggests strong directional bias.
* Use confirmed zone breaks to enter in the direction of momentum.
* Ideal in trending environments, especially with high volume and ATR movement.
---
### Key Inputs:
* **VWAP Length**: Moving VWAP period (default: 20)
* **Zone Width %**: Percentage size of zone buffer (default: 0.5%)
* **Min Touches**: How many times price must test a zone before alerts trigger
* **Zone Extension**: How far into the future zones are projected
* **Volume & ATR Filters**: Ensure only strong, valid crossovers create zones
---
### Alerts:
You can enable alerts for:
* **New zone creation**
* **Zone tests (after minimum touch count)**
* **Zone breaks**
* **VWAP crosses**
* **Active presence inside a zone (entry conditions)**
These alerts help automate market monitoring, making it suitable for discretionary or systematic workflows.
---
### Why It's a New Script:
This is not a cosmetic update. The internal logic, signal generation, filtering methodology, visual engine, and UX framework have been entirely rebuilt from the ground up. The result is a highly adaptive, precision-oriented tool — appropriate for intraday scalpers and swing traders alike. It goes far beyond the original in terms of functionality and reliability, justifying a fresh release.
---
### Suitable Markets and Timeframes:
* Works across all liquid markets (crypto, equities, futures, forex)
* Best used on timeframes where volume data is stable (5m and above recommended)
* Recalibrate inputs for optimal detection across instruments
Trend Matrix Multi-Timeframe Dashboard(TechnoBlooms)Trend Matrix Multi-Timeframe Dashboard is a Minimalist Multi-Timeframe Trend Analyzer with Smart Indicator Integration. Trend Matrix MTF Dashboard is a clean, efficient, and visually intuitive trend analyzer built for traders who value simplicity without compromising on technical depth.
This dashboard empowers you to track trend direction across multiple timeframes using a curated set of powerful technical indicators—all from one compact visual panel. The design philosophy is simple: eliminate clutter, highlight trend clarity, and accelerate your decision-making process.
Key Features
✅ Minimalist Design with Maximum Insight
A compact dashboard view designed for clean charts and focused trading
Optimized layout shows everything you need—nothing you don’t
✅ Multi-Timeframe Access at a Glance
Instantly read the trend direction of selected indicators on multiple timeframes (e.g., 15m, 1h, 4h, 1D)
Customize the timeframe stack to fit scalping, intraday, swing, or positional strategies
✅ Robust Technical Indicators Built In
Each one is hand-picked for trend reliability:
MACD – Momentum and crossover confirmation
RSI – Overbought/oversold and directional shift
EMA – Dynamic support/resistance and trend bias
Bollinger Bands – Volatility structure and trend containment
PVT – Volume-Weighted Trend Confirmation
Supertrend – Price-following trend tracker
✅ Live Updates & Lightweight Performance
Built to update efficiently on every bar close
Minimal performance impact even with multiple timeframes active
By offering multi-timeframe (MTF) access to proven trend-following indicators, Trend Matrix helps you confidently align with the market’s dominant direction—without jumping between charts or analyzing indicators one by one.
This indicator offers customizable settings. The trader can choose the input parameters timeframes as per the choice.
Trend Matrix Multi-Timeframe Dashboard helps traders to identify trend based on technical indications. Trader can refer this while taking trading decisions.
🧠 Ideal For
Scalpers who need higher timeframe confirmation
Swing traders identifying clean entries aligned with the macro trend
Trend followers seeking clarity before committing capital
Price action & SMC traders validating market structure setups
Beginners who want a high-level trend guide without messy indicators
VNIndex Over 6.5% Downside Drop Indicator with TableOverview: The VNIndex 6.5% Downside Drop Indicator is a powerful tool designed to help traders and investors identify significant market drops on the VNIndex (or any other asset) based on a 6.5% downside threshold. This Pine Script® indicator automatically detects when the price of an asset drops by more than 6.5% within a single day, and visually marks those events on the chart.
Key Features:
6.5% Downside Drop Detection: Automatically calculates the daily percentage drop and identifies when the price falls by more than 6.5%.
Table Display: Displays the dates and corresponding percentage drops of all identified instances in a convenient table at the bottom right of the chart.
Markers: Red down-pointing markers are plotted above bars where the price drop exceeds the 6.5% threshold, making it easy to spot critical drop events at a glance.
Easy-to-Read Table: The table lists the date and drop percentage, updating dynamically as new drops are detected. This allows for easy tracking of significant downside moves over time.
How to Use:
Install the Script: Add this indicator to your TradingView chart.
Monitor Price Drops: The indicator will automatically detect when the price drops by over 6.5% from the previous close and display a marker on the chart and the table in the bottom right corner.
View the Table: The table displays the date and the percentage drop of each detected event, making it easy to track past significant moves.
Alerts: You can set an alert for 6.5% drops to receive notifications in real-time.
Customization Options:
The drop percentage threshold (6.5%) can be adjusted in the script to fit other market conditions or assets.
The table can be resized or styled based on user preference for better visibility.
Why Use This Indicator? This indicator is perfect for traders looking to spot large, significant price movements quickly. Large downside drops can signal potential market reversals or trading opportunities, and this tool helps you track such events effortlessly. Whether you're monitoring the VNIndex or any other asset, this indicator provides crucial insights into volatile price action, helping you make more informed decisions.
Open Source License: This indicator is open source and free to use under the Mozilla Public License 2.0. You are welcome to modify, distribute, and contribute to the project.
Contributions: Feel free to contribute improvements, fixes, or new features by creating a pull request. Let’s collaborate to make this indicator even better for the community!
real_time_candlesIntroduction
The Real-Time Candles Library provides comprehensive tools for creating, manipulating, and visualizing custom timeframe candles in Pine Script. Unlike standard indicators that only update at bar close, this library enables real-time visualization of price action and indicators within the current bar, offering traders unprecedented insight into market dynamics as they unfold.
This library addresses a fundamental limitation in traditional technical analysis: the inability to see how indicators evolve between bar closes. By implementing sophisticated real-time data processing techniques, traders can now observe indicator movements, divergences, and trend changes as they develop, potentially identifying trading opportunities much earlier than with conventional approaches.
Key Features
The library supports two primary candle generation approaches:
Chart-Time Candles: Generate real-time OHLC data for any variable (like RSI, MACD, etc.) while maintaining synchronization with chart bars.
Custom Timeframe (CTF) Candles: Create candles with custom time intervals or tick counts completely independent of the chart's native timeframe.
Both approaches support traditional candlestick and Heikin-Ashi visualization styles, with options for moving average overlays to smooth the data.
Configuration Requirements
For optimal performance with this library:
Set max_bars_back = 5000 in your script settings
When using CTF drawing functions, set max_lines_count = 500, max_boxes_count = 500, and max_labels_count = 500
These settings ensure that you will be able to draw correctly and will avoid any runtime errors.
Usage Examples
Basic Chart-Time Candle Visualization
// Create real-time candles for RSI
float rsi = ta.rsi(close, 14)
Candle rsi_candle = candle_series(rsi, CandleType.candlestick)
// Plot the candles using Pine's built-in function
plotcandle(rsi_candle.Open, rsi_candle.High, rsi_candle.Low, rsi_candle.Close,
"RSI Candles", rsi_candle.candle_color, rsi_candle.candle_color)
Multiple Access Patterns
The library provides three ways to access candle data, accommodating different programming styles:
// 1. Array-based access for collection operations
Candle candles = candle_array(source)
// 2. Object-oriented access for single entity manipulation
Candle candle = candle_series(source)
float value = candle.source(Source.HLC3)
// 3. Tuple-based access for functional programming styles
= candle_tuple(source)
Custom Timeframe Examples
// Create 20-second candles with EMA overlay
plot_ctf_candles(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 20,
timezone = -5,
tied_open = true,
ema_period = 9,
enable_ema = true
)
// Create tick-based candles (new candle every 15 ticks)
plot_ctf_tick_candles(
source = close,
candle_type = CandleType.heikin_ashi,
number_of_ticks = 15,
timezone = -5,
tied_open = true
)
Advanced Usage with Custom Visualization
// Get custom timeframe candles without automatic plotting
CandleCTF my_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 30
)
// Apply custom logic to the candles
float ema_values = my_candles.ctf_ema(14)
// Draw candles and EMA using time-based coordinates
my_candles.draw_ctf_candles_time()
ema_values.draw_ctf_line_time(line_color = #FF6D00)
Library Components
Data Types
Candle: Structure representing chart-time candles with OHLC, polarity, and visualization properties
CandleCTF: Extended candle structure with additional time metadata for custom timeframes
TickData: Structure for individual price updates with time deltas
Enumerations
CandleType: Specifies visualization style (candlestick or Heikin-Ashi)
Source: Defines price components for calculations (Open, High, Low, Close, HL2, etc.)
SampleType: Sets sampling method (Time-based or Tick-based)
Core Functions
get_tick(): Captures current price as a tick data point
candle_array(): Creates an array of candles from price updates
candle_series(): Provides a single candle based on latest data
candle_tuple(): Returns OHLC values as a tuple
ctf_candles_array(): Creates custom timeframe candles without rendering
Visualization Functions
source(): Extracts specific price components from candles
candle_ctf_to_float(): Converts candle data to float arrays
ctf_ema(): Calculates exponential moving averages for candle arrays
draw_ctf_candles_time(): Renders candles using time coordinates
draw_ctf_candles_index(): Renders candles using bar index coordinates
draw_ctf_line_time(): Renders lines using time coordinates
draw_ctf_line_index(): Renders lines using bar index coordinates
Technical Implementation Notes
This library leverages Pine Script's varip variables for state management, creating a sophisticated real-time data processing system. The implementation includes:
Efficient tick capturing: Samples price at every execution, maintaining temporal tracking with time deltas
Smart state management: Uses a hybrid approach with mutable updates at index 0 and historical preservation at index 1+
Temporal synchronization: Manages two time domains (chart time and custom timeframe)
The tooltip implementation provides crucial temporal context for custom timeframe visualizations, allowing users to understand exactly when each candle formed regardless of chart timeframe.
Limitations
Custom timeframe candles cannot be backtested due to Pine Script's limitations with historical tick data
Real-time visualization is only available during live chart updates
Maximum history is constrained by Pine Script's array size limits
Applications
Indicator visualization: See how RSI, MACD, or other indicators evolve in real-time
Volume analysis: Create custom volume profiles independent of chart timeframe
Scalping strategies: Identify short-term patterns with precisely defined time windows
Volatility measurement: Track price movement characteristics within bars
Custom signal generation: Create entry/exit signals based on custom timeframe patterns
Conclusion
The Real-Time Candles Library bridges the gap between traditional technical analysis (based on discrete OHLC bars) and the continuous nature of market movement. By making indicators more responsive to real-time price action, it gives traders a significant edge in timing and decision-making, particularly in fast-moving markets where waiting for bar close could mean missing important opportunities.
Whether you're building custom indicators, researching price patterns, or developing trading strategies, this library provides the foundation for sophisticated real-time analysis in Pine Script.
Implementation Details & Advanced Guide
Core Implementation Concepts
The Real-Time Candles Library implements a sophisticated event-driven architecture within Pine Script's constraints. At its heart, the library creates what's essentially a reactive programming framework handling continuous data streams.
Tick Processing System
The foundation of the library is the get_tick() function, which captures price updates as they occur:
export get_tick(series float source = close, series float na_replace = na)=>
varip float price = na
varip int series_index = -1
varip int old_time = 0
varip int new_time = na
varip float time_delta = 0
// ...
This function:
Samples the current price
Calculates time elapsed since last update
Maintains a sequential index to track updates
The resulting TickData structure serves as the fundamental building block for all candle generation.
State Management Architecture
The library employs a sophisticated state management system using varip variables, which persist across executions within the same bar. This creates a hybrid programming paradigm that's different from standard Pine Script's bar-by-bar model.
For chart-time candles, the core state transition logic is:
// Real-time update of current candle
candle_data := Candle.new(Open, High, Low, Close, polarity, series_index, candle_color)
candles.set(0, candle_data)
// When a new bar starts, preserve the previous candle
if clear_state
candles.insert(1, candle_data)
price.clear()
// Reset state for new candle
Open := Close
price.push(Open)
series_index += 1
This pattern of updating index 0 in real-time while inserting completed candles at index 1 creates an elegant solution for maintaining both current state and historical data.
Custom Timeframe Implementation
The custom timeframe system manages its own time boundaries independent of chart bars:
bool clear_state = switch settings.sample_type
SampleType.Ticks => cumulative_series_idx >= settings.number_of_ticks
SampleType.Time => cumulative_time_delta >= settings.number_of_seconds
This dual-clock system synchronizes two time domains:
Pine's execution clock (bar-by-bar processing)
The custom timeframe clock (tick or time-based)
The library carefully handles temporal discontinuities, ensuring candle formation remains accurate despite irregular tick arrival or market gaps.
Advanced Usage Techniques
1. Creating Custom Indicators with Real-Time Candles
To develop indicators that process real-time data within the current bar:
// Get real-time candles for your data
Candle rsi_candles = candle_array(ta.rsi(close, 14))
// Calculate indicator values based on candle properties
float signal = ta.ema(rsi_candles.first().source(Source.Close), 9)
// Detect patterns that occur within the bar
bool divergence = close > close and rsi_candles.first().Close < rsi_candles.get(1).Close
2. Working with Custom Timeframes and Plotting
For maximum flexibility when visualizing custom timeframe data:
// Create custom timeframe candles
CandleCTF volume_candles = ctf_candles_array(
source = volume,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 60
)
// Convert specific candle properties to float arrays
float volume_closes = volume_candles.candle_ctf_to_float(Source.Close)
// Calculate derived values
float volume_ema = volume_candles.ctf_ema(14)
// Create custom visualization
volume_candles.draw_ctf_candles_time()
volume_ema.draw_ctf_line_time(line_color = color.orange)
3. Creating Hybrid Timeframe Analysis
One powerful application is comparing indicators across multiple timeframes:
// Standard chart timeframe RSI
float chart_rsi = ta.rsi(close, 14)
// Custom 5-second timeframe RSI
CandleCTF ctf_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 5
)
float fast_rsi_array = ctf_candles.candle_ctf_to_float(Source.Close)
float fast_rsi = fast_rsi_array.first()
// Generate signals based on divergence between timeframes
bool entry_signal = chart_rsi < 30 and fast_rsi > fast_rsi_array.get(1)
Final Notes
This library represents an advanced implementation of real-time data processing within Pine Script's constraints. By creating a reactive programming framework for handling continuous data streams, it enables sophisticated analysis typically only available in dedicated trading platforms.
The design principles employed—including state management, temporal processing, and object-oriented architecture—can serve as patterns for other advanced Pine Script development beyond this specific application.
------------------------
Library "real_time_candles"
A comprehensive library for creating real-time candles with customizable timeframes and sampling methods.
Supports both chart-time and custom-time candles with options for candlestick and Heikin-Ashi visualization.
Allows for tick-based or time-based sampling with moving average overlay capabilities.
get_tick(source, na_replace)
Captures the current price as a tick data point
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
na_replace (float) : Optional - Value to use when source is na
Returns: TickData structure containing price, time since last update, and sequential index
candle_array(source, candle_type, sync_start, bullish_color, bearish_color)
Creates an array of candles based on price updates
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
sync_start (simple bool) : Optional - Whether to synchronize with the start of a new bar
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of Candle objects ordered with most recent at index 0
candle_series(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides a single candle based on the latest price data
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: A single Candle object representing the current state
candle_tuple(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides candle data as a tuple of OHLC values
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Tuple representing current candle values
method source(self, source, na_replace)
Extracts a specific price component from a Candle
Namespace types: Candle
Parameters:
self (Candle)
source (series Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
na_replace (float) : Optional - Value to use when source value is na
Returns: The requested price value from the candle
method source(self, source)
Extracts a specific price component from a CandleCTF
Namespace types: CandleCTF
Parameters:
self (CandleCTF)
source (simple Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
Returns: The requested price value from the candle as a varip
method candle_ctf_to_float(self, source)
Converts a specific price component from each CandleCTF to a float array
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
Returns: Array of float values extracted from the candles, ordered with most recent at index 0
method ctf_ema(self, ema_period)
Calculates an Exponential Moving Average for a CandleCTF array
Namespace types: array
Parameters:
self (array)
ema_period (simple float) : Period for the EMA calculation
Returns: Array of float values representing the EMA of the candle data, ordered with most recent at index 0
method draw_ctf_candles_time(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar time coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using time-based x-coordinates
method draw_ctf_candles_index(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar index coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using index-based x-coordinates
method draw_ctf_line_time(self, source, line_size, line_color)
Renders a line representing a price component from the candles using time coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_time(self, line_size, line_color)
Renders a line from a varip float array using time coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_index(self, source, line_size, line_color)
Renders a line representing a price component from the candles using index coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
method draw_ctf_line_index(self, line_size, line_color)
Renders a line from a varip float array using index coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots tick-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots tick-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots time-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots time-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_candles(source, candle_type, sample_type, number_of_ticks, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, enable_ema, line_width, ema_color, use_time_indexing)
Unified function for plotting candles with comprehensive options
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Optional - Type of candle chart to display
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
ema_period (simple float) : Optional - Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
enable_ema (bool) : Optional - Whether to display the EMA overlay
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with optional EMA overlay
ctf_candles_array(source, candle_type, sample_type, number_of_ticks, number_of_seconds, tied_open, bullish_color, bearish_color)
Creates an array of custom timeframe candles without rendering them
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to create (candlestick or Heikin-Ashi)
sample_type (simple SampleType) : Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of CandleCTF objects ordered with most recent at index 0
Candle
Structure representing a complete candle with price data and display properties
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
candle_color (series color) : Color to use when rendering the candle
ready (series bool) : Boolean indicating if candle data is valid and ready for use
TickData
Structure for storing individual price updates
Fields:
price (series float) : The price value at this tick
time_delta (series float) : Time elapsed since the previous tick in milliseconds
series_index (series int) : Sequential index identifying this tick
CandleCTF
Structure representing a custom timeframe candle with additional time metadata
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
open_time (series int) : Timestamp marking when the candle was opened (in Unix time)
time_delta (series float) : Duration of the candle in milliseconds
candle_color (series color) : Color to use when rendering the candle
Global M2 Money Supply (USD) GrowthThe Global M2 Growth indicator evaluates the total liquid money supply, including cash, checking deposits, and assets that can be easily converted to cash. It reflects changes in global liquidity by tracking year-on-year (YoY) changes in the Global M2 money supply rather than its absolute value. This approach highlights the velocity of liquidity expansion or contraction, offering a clearer understanding of its correlation with asset performance, such as Bitcoin.
How It Works
When the Global M2 money supply expands, it reflects an increase in available liquidity. This often leads to an influx of capital into higher-yielding and riskier assets like Bitcoin, equities, and commodities. Conversely, when M2 contracts, liquidity tightens, leading to declines in the values of these assets.
An essential insight is that Bitcoin's price is not immediately affected by changes in M2. Research shows a lag of approximately 56-60 days (around two months) between liquidity changes and Bitcoin's price movements. Shifting the liquidity data forward by this period improves the correlation between Global M2 and Bitcoin performance.
How to Use
Track Global M2 YoY Change: Focus on liquidity's yearly change to identify trends. Rapid increases in liquidity often signify favorable conditions for Bitcoin and other risk assets to rise, while contractions often predict price declines or consolidation phases.
Account for the Lag Effect: Incorporate the two-month lag into your analysis to predict Bitcoin's potential moves more accurately. For instance, a recent resurgence in liquidity growth could signal a Bitcoin rally within the next two months.
Use as a Macro Indicator: Monitor liquidity trends alongside other economic indicators and asset performance metrics to build a more comprehensive investment framework.
By tracking these dynamics, traders and investors can better anticipate Bitcoin's trajectory and make informed decisions.
Multi-Timeframe VWAP Master ProThe Multi-Timeframe VWAP Suite is a comprehensive and highly customizable indicator designed for traders who rely on Volume-Weighted Average Price (VWAP) across multiple timeframes and periods. This tool provides a complete suite of VWAP calculations, including daily, weekly, monthly, quarterly, yearly, and custom VWAPs, allowing traders to analyze price action and volume trends with precision. Whether you're a day trader, swing trader, or long-term investor, this indicator offers unparalleled flexibility and depth for your trading strategy.
Multi-Timeframe VWAPs:
Daily, Weekly, Monthly, Quarterly, and Yearly VWAPs: Track VWAP across various timeframes to identify key support and resistance levels.
Customizable Timeframes: Use the SMA timeframe input to adjust the period for moving averages and other calculations.
Previous Period VWAPs:
Previous Daily, Weekly, Monthly, and Quarterly VWAPs: Analyze historical VWAP levels to understand past price behavior and identify potential reversal zones.
Previous Year Quarterly VWAPs: Compare current price action to VWAP levels from specific quarters of the previous year.
Custom VWAPs:
Custom Start Date and Timeframe: Define your own VWAP periods by specifying a start date and timeframe, allowing for tailored analysis.
Dynamic Custom VWAP Calculation: Automatically calculates VWAP based on your custom inputs, ensuring flexibility for unique trading strategies.
Seasonal and Yearly VWAPs:
April, July, and October VWAPs: Analyze seasonal trends by tracking VWAP levels for specific months.
Yearly VWAP: Get a broader perspective on long-term price trends with the yearly VWAP.
SMA Integration:
SMA Overlay: Combine VWAP analysis with a Simple Moving Average (SMA) for additional confirmation of trends and reversals.
Customizable SMA Length and Timeframe: Adjust the SMA settings to match your trading style and preferences.
User-Friendly Customization:
Toggle Visibility and Labels: Easily enable or disable the display of specific VWAPs and their labels to keep your chart clean and focused.
Color Customization: Each VWAP line and label is color-coded for easy identification and can be customized to suit your preferences.
Dynamic Labeling:
Automatic Labels: Labels are dynamically placed on the last bar, providing clear and concise information about each VWAP level.
Customizable Label Text: Labels include detailed information, such as the timeframe or custom period, for quick reference.
Flexible Timeframe Detection:
Automatic Timeframe Detection: The indicator automatically detects new days, weeks, months, and quarters, ensuring accurate VWAP calculations.
Support for Intraday and Higher Timeframes: Works seamlessly on all chart timeframes, from 1-minute to monthly charts.
Previous Year Quarterly VWAPs:
Q1, Q2, Q3, Q4 VWAPs: Compare current price action to VWAP levels from specific quarters of the previous year.
User-Selectable Year: Choose the year for which you want to calculate previous quarterly VWAPs.
Persistent Monthly VWAPs:
Option to Persist Monthly VWAPs Year-Round: Keep monthly VWAP levels visible even after the month ends for ongoing analysis.
Comprehensive Analysis: Combines multiple VWAP timeframes and periods into a single tool, eliminating the need for multiple indicators.
Customizable and Flexible: Tailor the indicator to your specific trading strategy with customizable timeframes, periods, and settings.
Enhanced Decision-Making: Gain deeper insights into price action and volume trends across different timeframes, helping you make more informed trading decisions.
Clean and Organized Charts: Toggle visibility and labels to keep your chart clutter-free while still accessing all the information you need.
Ideal For:
Day Traders: Use daily and intraday VWAPs to identify intraday support and resistance levels.
Swing Traders: Analyze weekly and monthly VWAPs to spot medium-term trends and reversals.
Long-Term Investors: Leverage quarterly and yearly VWAPs to understand long-term price behavior and key levels.
Seasonal Traders: Track April, July, and October VWAPs to capitalize on seasonal trends.
The Multi-Timeframe VWAP Suite is a powerful and versatile tool for traders of all styles and timeframes. With its comprehensive suite of VWAP calculations, customizable settings, and user-friendly design, it provides everything you need to analyze price action and volume trends with precision and confidence. Whether you're looking to fine-tune your intraday strategy or gain a broader perspective on long-term trends, this indicator has you covered.
Kalman Filter Trend BreakersThe Kalman filter is a recursive algorithm developed in 1960 by Rudolf E. Kálmán, a Hungarian-American engineer and mathematician, that provides optimal estimates of a system's state by combining noisy measurements with a predictive model. It is widely used in control systems, signal processing, and finance for tracking and forecasting.
In trading, KF might be a good replacement for a moving average, as it reacts to price changes in a different way. Not only it follows price direction, but can also track the velocity of price change. This specific behaviour of KF is used in this indicator to track changes in trends.
Trend is characterized by price moving directionally, however, any trend comes to pause or complete stop and reversal, as the price changes more slowly (a trend fades into a sideways movement for a while) or the price movement changes direction, thus making a reversal.
This indicator detects the points where such changes occur (trend breaker points), and produces signals, which serve as points of current trend pausing or reversing. By applying different settings for KF calculation, you can produce less or more signals that indicate change in trend character, and either detect only significant trends changes, or less and shorter trends changes as well.
The signals do not differentiate the exact type of a trend change (it can be a brief trend pause followed by a continuation, as well as a complete reversal). However, once you are in a trend, the significant velocity change indicates a change in trend structure. In this sense, trend breaker signals should not be followed blindly, and can be used only as trend (and subsequently, position) exit confirmations, but not the entry contrarian confirmations.
For better visual representation, you can use chart signals attached to bars, and additionally paint a vertical gradient at each signal which shows significant trend deceleration.
Kalman filter calculations used in this indicator are partially based on an open-source code from @loxx which was published in 2022 as Kalman filter overlay .
The Final Countdown//Credit to ©SamRecio for the original indicator that this is based on, which is called, "HTF Bar Close Countdown".
Here are the key differences between the two indicators (That a user would care about):
1.) 10 timeframe slots (double the original number).
2.) Many more timeframe options ('1', '3', '5', '10', '15', '30', '45', '1H', '2H', '4H', '6H', '8H', '12H', 'D', 'W').
3.) Ability to structure timeframes however you want (Higher up top descending, vice versa, or just randomly.).
4.) Support for hour-based timeframes (1H, 2H, etc.).
5.) Displays minutes as numbers, hours with a number followed by H (ex. 1H), and anything above with a letter (D for day, W for week).
6.) Dynamic colors based on remaining time percentage (green->yellow->red) with two user-defined thresholds.
7.) Alerts for when timeframes are close to closing (yellow->red).
8.) More granular timeframe selection options.
9.) Background colors for an additional visual alert.
------Colors background the selected color for each timeframe (Default is all timeframes are blue with 80% transparency).
------This does not repaint, so the color will persist once the red condition is over.
------As soon as you leave the timeframe though, it will be erased and the new timeframe will begin tracking red conditions.
------It always starts from the current bar, so it is not applicable to historical bars unless you leave it running for an extended period of time.
------Do note that since this is not actual paint or colored pencils, the colors do not blend.
------The most recent timeframe to enter a red condition will be the background that you see unless you leave the timeframe and return.
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Now for the description and instructions....
IT'S THE FINAL COUNTDOWN!
This indicator helps shorter-timeframe traders track multiple timeframe closings simultaneously, providing visual, audio and notification alerts when bars are nearing their close. It's particularly useful for traders who want to prepare for potential price action around bar closings across different timeframes. If you're a HODL till you're broke kind of trader, you don't need this.
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Multi-Timeframe Tracking
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- Monitors up to 10 different timeframes simultaneously
- Supports various timeframes from 1 minute to weekly (1m, 3m, 5m, 10m, 15m, 30m, 45m, 1H, 2H, 4H, 6H, 8H, 12H, Daily, Weekly)
- Timeframes can be arranged in any order (ascending, descending, or custom)
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Visual Display
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- Shows a countdown timer for each selected timeframe
- Dynamic color changes based on time remaining:
Green: More than 15% of bar time remaining
Yellow: Between 15% and 5% remaining
Red: Less than 5% remaining
- Customizable background colors appear when timeframes enter their red zone
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Alert System
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- Built-in alerts trigger when any timeframe enters its red zone
- Each timeframe can have its alerts toggled independently
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- Setup Instructions -
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Timeframe Selection
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- Choose up to 10 timeframes to monitor
- Each timeframe has its own toggle switch to turn it on/off
- Default configuration starts from 5m and goes up to 12H
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Visual Customization
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- Adjust the table size, position
- Customize frame and border colors
- Modify the yellow and red threshold percentages
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Background Color Settings
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- Enable/disable background colors for each timeframe
- Choose custom colors for each timeframe's background
- Default setting is blue (with a fixed 80% transparency)
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Usage Tips
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- Use the countdown table to prepare for multiple timeframe closes as big moves (especially reversals) tend to begin come after higher timeframe changes (sometimes to the second).
- Watch for color changes to anticipate important closing periods to avoid getting trapped in bad trade (please always use stop losses if trading, in general).
- Set up alerts for critical timeframes that require immediate attention (2H, 4H, etc.).
- Use background colors as an additional visual cue for timeframe closes.
- Position the table where it won't interfere with your chart analysis.
WD Gann: Close Price X Bars Ago with Line or Candle PlotThis indicator is inspired by the principles of WD Gann, a legendary trader known for his groundbreaking methods in time and price analysis. It helps traders track the close price of a security from X bars ago, a technique that is often used to identify key price levels in relation to past price movements. This concept is essential for Gann’s market theories, which emphasize the relationship between time and price.
WD Gann’s analysis often revolved around specific numbers that he considered significant, many of which correspond to squared numbers (e.g., 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400, 441, 484, 529, 576, 625, 676, 729, 784, 841, 900, 961, 1024, 1089, 1156, 1225, 1296, 1369, 1444, 1521, 1600, 1681, 1764, 1849, 1936). These numbers are believed to represent natural rhythms and cycles in the market. This indicator can help you explore how past price levels align with these significant numbers, potentially revealing key price zones that could act as support, resistance, or reversal points.
Key Features:
- Historical Close Price Calculation: The indicator calculates and displays the close price of a security from X bars ago (where X is customizable). This method aligns with Gann's focus on price relationships over specific time intervals, providing traders with valuable reference points to assess market conditions.
- Customizable Plot Type: You can choose between two plot types for visualizing the historical close price:
- Line Plot: A simple line that represents the close price from X bars ago, ideal for those who prefer a clean and continuous representation.
- Candle Plot: Displays the close price as a candlestick chart, providing a more detailed view with open, high, low, and close prices from X bars ago.
- Candle Color Coding: For the candle plot type, the script color-codes the candles. Green candles appear when the close price from X bars ago is higher than the open price, indicating bullish sentiment; red candles appear when the close is lower, indicating bearish sentiment. This color coding gives a quick visual cue to market sentiment.
- Customizable Number of Bars: You can adjust the number of bars (X) to look back, providing flexibility for analyzing different timeframes. Whether you're conducting short-term or long-term analysis, this input can be fine-tuned to suit your trading strategy.
- Gann Method Application: WD Gann's methods involved analyzing price action over specific time periods to predict future movements. This indicator offers traders a way to assess how the price of a security has behaved in the past in relation to a chosen time interval, a critical concept in Gann's theories.
How to Use:
1. Input Settings:
- Number of Bars (X): Choose the number of bars to look back (e.g., 100, 200, or any custom period).
- Plot Type: Select whether to display the data as a Line or Candles.
2. Interpretation:
- Using the Line plot, observe how the close price from X bars ago compares to the current market price.
- Using the Candles plot, analyze the full price action of the chosen bar from X bars ago, noting how the close price relates to the open, high, and low of that bar.
3. Gann Analysis: Integrate this indicator into your broader Gann-based analysis. By looking at past price levels and their relationship to significant squared numbers, traders can uncover potential key levels of support and resistance or even potential reversal points. The historical close price can act as a benchmark for predicting future market movements.
Suggestions on WD Gann's Emphasis in Trading:
WD Gann’s trading methods were rooted in several key principles that emphasized the relationship between time and price. These principles are vital to understanding how the "Close Price X Bars Ago" indicator fits into his overall analysis:
1. Time Cycles: Gann believed that markets move in cyclical patterns. By studying price levels from specific time intervals, traders can spot these cycles and predict future market behavior. This indicator allows you to see how the close price from X bars ago relates to current market conditions, helping to spot cyclical highs and lows.
2. Price and Time Squaring: A core concept in Gann’s theory is that certain price levels and time periods align, often marking significant reversal points. The squared numbers (e.g., 1, 4, 9, 16, 25, etc.) serve as potential key levels where price and time might "square" to create support or resistance. This indicator helps traders spot these historical price levels and their potential relevance to future price action.
3. Geometric Angles: Gann used angles (like the 45-degree angle) to predict market movements, with the belief that prices move at specific geometric angles over time. This indicator gives traders a reference for past price levels, which could align with key angles, helping traders predict future price movement based on Gann's geometry.
4. Numerology and Key Intervals: Gann paid particular attention to numbers that held significance, including squared numbers and numbers related to the Fibonacci sequence. This indicator allows traders to analyze price levels based on these key numbers, which can help in identifying potential turning points in the market.
5. Support and Resistance Levels: Gann’s methods often involved identifying levels of support and resistance based on past price action. By tracking the close price from X bars ago, traders can identify past support and resistance levels that may become significant again in future market conditions.
Perfect for:
Traders using WD Gann’s methods, such as Gann angles, time cycles, and price theory.
Analysts who focus on historical price levels to predict future price action.
Those who rely on numerology and geometric principles in their trading strategies.
By integrating this indicator into your trading strategy, you gain a powerful tool for analyzing market cycles and price movements in relation to key time intervals. The ability to track and compare the historical close price to significant numbers—like Gann’s squared numbers—can provide valuable insights into potential support, resistance, and reversal points.
Disclaimer:
This indicator is based on the methods and principles of WD Gann and is for educational purposes only. It is not intended as financial advice. Trading involves significant risk, and you should not trade with money that you cannot afford to lose. Past performance is not indicative of future results. The use of this indicator is at your own discretion and risk. Always do your own research and consider consulting a licensed financial advisor before making any investment decisions.
20/50 SMA Cross 200 SMAThis Pine Script code is designed to identify and visualize crossovers of two shorter-term Simple Moving Averages (SMAs), a 20-period SMA and a 50-period SMA, with a longer-term 200-period SMA on a price chart. It also includes alerts for these crossover events. Here's a breakdown:
**Purpose:**
The core idea behind this script is to detect potential trend changes. Crossovers of shorter-term moving averages over a longer-term moving average are often interpreted as bullish signals, while crossovers below are considered bearish.
**Key Components:**
1. **Moving Average Calculation:**
* `sma20 = ta.sma(close, 20)`: Calculates the 20-period SMA of the closing price.
* `sma50 = ta.sma(close, 50)`: Calculates the 50-period SMA of the closing price.
* `sma200 = ta.sma(close, 200)`: Calculates the 200-period SMA of the closing price.
2. **Crossover Detection:**
* `crossUp20 = ta.crossover(sma20, sma200)`: Returns `true` when the 20-period SMA crosses above the 200-period SMA.
* `crossDown20 = ta.crossunder(sma20, sma200)`: Returns `true` when the 20-period SMA crosses below the 200-period SMA.
* Similar logic applies for `crossUp50` and `crossDown50` with the 50-period SMA.
3. **Recent Crossover Tracking (Crucial Improvement):**
* `lookback = 7`: Defines a lookback period of 7 bars.
* `var bool hasCrossedUp20 = false`, etc.: Declares `var` (persistent) boolean variables to track if a crossover has occurred *within* the last 7 bars. This is the most important correction from previous versions.
* The logic using `ta.barssince()` is the key:
* If a crossover happens (`crossUp20` is true), the corresponding `hasCrossedUp20` is set to `true`.
* If no crossover happens on the current bar, it checks if a crossover happened within the last 7 bars using `ta.barssince(crossUp20) <= lookback`. If so, it keeps `hasCrossedUp20` as `true`. After 7 bars, it becomes `false`.
4. **Plotting Crossovers:**
* `plotshape(...)`: Plots circles on the chart to visually mark the crossovers.
* Green circles below the bars for bullish crossovers (20 and 50).
* Red circles above the bars for bearish crossovers (20 and 50).
* Different shades of green/red (green/lime, red/maroon) distinguish between 20 and 50 SMA crossovers.
5. **Plotting Moving Averages (Optional but Helpful):**
* `plot(sma20, color=color.blue, linewidth=1)`: Plots the 20-period SMA in blue.
* Similar logic for the 50-period SMA (orange) and 200-period SMA (gray).
6. **Alerts:**
* `alertcondition(...)`: Triggers alerts when crossovers occur. This is essential for real-time trading signals.
**How it Works (in Simple Terms):**
The script continuously calculates the 20, 50, and 200 SMAs. It then monitors for instances where the 20 or 50 SMA crosses the 200 SMA. When such a crossover happens, a colored circle is plotted on the chart, and an alert is triggered. The key improvement is that it remembers if a crossover occurred in the last 7 bars and continues to display the circle during that period.
**Use Case:**
Traders use this type of indicator to identify potential entry and exit points in the market. A bullish crossover (shorter SMA crossing above the longer SMA) might be a signal to buy, while a bearish crossover might be a signal to sell.
**Key Improvements over Previous Versions:**
* **Correct Lookback Implementation:** The use of `ta.barssince()` and `var` variables is the correct and efficient way to check for crossovers within a lookback period. This fixes the major flaw in earlier versions.
* **Clear Visualizations:** The use of `plotshape` with distinct colors makes it easy to distinguish between 20 and 50 SMA crossovers.
* **Alerts:** The inclusion of alerts makes the script much more practical for real-time trading.
This improved version provides a robust and useful tool for identifying and tracking SMA crossovers.
Higher Time Frame Support/Resistance [BigBeluga]The Higher Time Frame Support/Resistance indicator is a tool designed to display pivot points derived from higher timeframes on your current chart. These pivot points are calculated based on the highs and lows of price action in different timeframes, and the indicator draws horizontal lines to represent these levels. These lines act as potential support and resistance zones, giving traders key market levels that may influence future price movement.
Each pivot line is color-coded and labeled with its price value and the timeframe it originates from. This allows traders to clearly differentiate between the significance of the levels based on their timeframe. For example, weekly pivot levels may represent stronger, more long-term support and resistance, while hourly pivots offer more immediate, short-term levels to watch.
🔵 IDEA
The Higher Time Frame Support/Resistance indicator is designed to simplify the process of tracking key support and resistance levels across multiple timeframes. Pivot points, which represent turning points in the market, are essential for identifying areas where price might reverse or break out. By displaying these levels from higher timeframes directly on the current chart, traders can quickly identify and react to critical areas in the market without needing to switch between different timeframe charts.
The indicator labels each pivot point with the specific timeframe it comes from (e.g., 4H, 1D, 1W), making it easy for traders to assess the relative strength of each level. Stronger levels from higher timeframes are likely to act as more significant barriers or support zones, while lower timeframe levels can be used for more precise entries and exits.
🔵 KEY FEATURES
Pivot Levels from Multiple Timeframes:
The indicator calculates pivot highs and lows from various higher timeframes (e.g., 4H, 1D, 1W) and plots these levels on the current chart. These pivot points are represented by horizontal lines that extend across the chart, serving as potential support and resistance zones.
Color-Coded Support and Resistance Lines:
Each pivot level is color-coded based on its timeframe, helping traders quickly differentiate between short-term and long-term support and resistance. This visual aid simplifies the analysis and allows for a clearer understanding of key market levels.
Price Labels and Timeframe Information:
In addition to the pivot lines, the indicator displays labels at each level with the corresponding price and timeframe. For example, a label may show "D Pivot High" followed by the exact price. This helps traders understand the origin and significance of each line, allowing for more informed trading decisions.
Labels up and down mark highs and lows from higher timeframes:
Pivot Shadows for Enhanced Clarity:
The indicator can also draw shadow lines that represent the pivot points but with increased transparency. These shadows allow traders to keep track of previous pivots without cluttering the chart with too many solid lines. The width and transparency of these shadows can be customized in the settings.
🔵 HOW TO USE
🔵 CUSTOMIZATION
Timeframes and Pivot Length: Customize which higher timeframes (e.g., 4H, 1D, 1W) you want to display pivot levels from. Adjust the pivot length to control how sensitive the indicator is in detecting market highs and lows.
Line Style and Colors: Adjust the line style (solid, dashed, dotted) and colors for each timeframe to match your personal preference or chart theme. This customization helps in maintaining a clear and visually appealing chart.
Shadow Line Width and Transparency: Control the width and transparency of the shadow pivot lines to reduce chart clutter while still keeping track of key historical levels.
Target Trend [BigBeluga]The Target Trend indicator is a trend-following tool designed to assist traders in capturing directional moves while managing entry, stop loss, and profit targets visually on the chart. Using adaptive SMA bands as the core trend detection method, this indicator dynamically identifies shifts in trend direction and provides structured exit points through customizable target levels.
SP500:
🔵 IDEA
The Target Trend indicator’s concept is to simplify trade management by providing automated visual cues for entries, stops, and targets directly on the chart. When a trend change is detected, the indicator prints an up or down triangle to signal entry direction, plots three customizable target levels for potential exits, and calculates a stop-loss level below or above the entry point. The indicator continuously adapts as price moves, making it easier for traders to follow and manage trades in real time.
When price crosses a target level, the label changes to a check mark, confirming that the target has been achieved. Similarly, if the stop-loss level is hit, the label changes to an "X," and the line becomes dashed, indicating that the stop loss has been activated. This feature provides traders with a clear visual trail of whether their targets or stop loss have been hit, allowing for easier trade tracking and exit strategy management.
🔵 KEY FEATURES & USAGE
SMA Bands for Trend Detection: The indicator uses adaptive SMA bands to identify the trend direction. When price crosses above or below these bands, a new trend is detected, triggering entry signals. The entry point is marked on the chart with a triangle symbol, which updates with each new trend change.
Automated Targets and Stop Loss Management: Upon a new trend signal, the indicator automatically plots three price targets and a stop loss level. These levels provide traders with structured exit points for potential gains and a clear risk limit. The stop loss is placed below or above the entry point, depending on the trend direction, to manage downside risk effectively.
Visual Target and Stop Loss Validation: As price hits each target, the label beside the level updates to a check mark, indicating that the target has been reached. Similarly, if the stop loss is activated, the stop loss label changes to an "X," and the line becomes dashed. This feature visually confirms whether targets or stop losses are hit, simplifying trade management.
The indicator also marks the entry price at each trend change with a label on the chart, allowing traders to quickly see their initial entry point relative to current price and target levels.
🔵 CUSTOMIZATION
Trend Length: Set the lookback period for the trend-detection SMA bands to adjust the sensitivity to trend changes.
Targets Setting: Customize the number and spacing of the targets to fit your trading style and market conditions.
Visual Styles: Adjust the appearance of labels, lines, and symbols on the chart for a clearer view and personalized layout.
🔵 CONCLUSION
The Target Trend indicator offers a streamlined approach to trend trading by integrating entry, target, and stop loss management into a single visual tool. With automatic tracking of target levels and stop loss hits, it helps traders stay focused on the current trend while keeping track of risk and reward with minimal effort.
Dynamic Market Correlation Analyzer (DMCA) v1.0Description
The Dynamic Market Correlation Analyzer (DMCA) is an advanced TradingView indicator designed to provide real-time correlation analysis between multiple assets. It offers a comprehensive view of market relationships through correlation coefficients, technical indicators, and visual representations.
Key Features
- Multi-asset correlation tracking (up to 5 symbols)
- Dynamic correlation strength categorization
- Integrated technical indicators (RSI, MACD, DX)
- Customizable visualization options
- Real-time price change monitoring
- Flexible timeframe selection
## Use Cases
1. **Portfolio Diversification**
- Identify highly correlated assets to avoid concentration risk
- Find negatively correlated assets for hedging strategies
- Monitor correlation changes during market events
2. Pairs Trading
- Detect correlation breakdowns for potential trading opportunities
- Track correlation strength for pair selection
- Monitor technical indicators for trade timing
3. Risk Management
- Assess portfolio correlation risk in real-time
- Monitor correlation shifts during market stress
- Identify potential portfolio vulnerabilities
4. **Market Analysis**
- Study sector relationships and rotations
- Analyze cross-asset correlations (e.g., stocks vs. commodities)
- Track market regime changes through correlation patterns
Components
Input Parameters
- **Timeframe**: Custom timeframe selection for analysis
- **Length**: Correlation calculation period (default: 20)
- **Source**: Price data source selection
- **Symbol Selection**: Up to 5 customizable symbols
- **Display Options**: Table position, text color, and size settings
Technical Indicators
1. **Correlation Coefficient**
- Range: -1 to +1
- Strength categories: Strong/Moderate/Weak (Positive/Negative)
2. **RSI (Relative Strength Index)**
- 14-period default setting
- Momentum comparison across assets
3. **MACD (Moving Average Convergence Divergence)**
- Standard settings (12, 26, 9)
- Trend direction indicator
4. **DX (Directional Index)**
- Trend strength measurement
- Based on DMI calculations
Visual Components
1. **Correlation Table**
- Symbol identifiers
- Correlation coefficients
- Correlation strength descriptions
- Price change percentages
- Technical indicator values
2. **Correlation Plot**
- Real-time correlation visualization
- Multiple correlation lines
- Reference levels at -1, 0, and +1
- Color-coded for easy identification
Installation and Setup
1. Load the indicator on TradingView
2. Configure desired symbols (up to 5)
3. Adjust timeframe and calculation length
4. Customize display settings
5. Enable/disable desired components (table, plot, RSI)
Best Practices
1. **Symbol Selection**
- Choose related but distinct assets
- Include a mix of asset classes
- Consider market cap and liquidity
2. **Timeframe Selection**
- Match timeframe to trading strategy
- Consider longer timeframes for strategic analysis
- Use shorter timeframes for tactical decisions
3. **Interpretation**
- Monitor correlation changes over time
- Consider multiple timeframes
- Combine with other technical analysis tools
- Account for market conditions and volatility
Performance Notes
- Calculations update in real-time
- Resource usage scales with number of active symbols
- Historical data availability may affect initial calculations
Version History
- v1.0: Initial release with core functionality
- Multi-symbol correlation analysis
- Technical indicator integration
- Customizable display options
Future Enhancements (Planned)
- Additional technical indicators
- Advanced correlation algorithms
- Enhanced visualization options
- Custom alert conditions
- Statistical significance testing
Adaptive EMA with ATR and Standard Deviation [QuantAlgo]Adaptive EMA with ATR and Standard Deviation by QuantAlgo 📈✨
Introducing the Adaptive EMA with ATR and Standard Deviation , a comprehensive trend-following indicator designed to combine the smoothness of an Exponential Moving Average (EMA) with the volatility adjustments of Average True Range (ATR) and Standard Deviation. This synergy allows traders and investors to better identify market trends while accounting for volatility, delivering clearer signals in both trending and volatile market conditions. This indicator is suitable for traders and investors seeking to balance trend detection and volatility management, offering a robust and adaptable approach across various asset classes and timeframes.
💫 Core Concept and Innovation
The Adaptive EMA with ATR and Standard Deviation brings together the trend-smoothing properties of the EMA and the volatility sensitivity of ATR and Standard Deviation. By using the EMA to track price movements over time, the indicator smooths out minor fluctuations while still providing valuable insights into overall market direction. However, market volatility can sometimes distort simple moving averages, so the ATR and Standard Deviation components dynamically adjust the trend signals, offering more nuanced insights into trend strength and reversals. This combination equips traders with a powerful tool to navigate unpredictable markets while minimizing false signals.
📊 Technical Breakdown and Calculations
The Adaptive EMA with ATR and Standard Deviation relies on three key technical components:
1. Exponential Moving Average (EMA): The EMA forms the base of the trend detection. Unlike a Simple Moving Average (SMA), the EMA gives more weight to recent price changes, allowing it to react more quickly to new data. Users can adjust the length of the EMA to make it more or less responsive to price movements.
2. Standard Deviation Bands: These bands are calculated from the standard deviation of the EMA and represent dynamic volatility thresholds. The upper and lower bands expand or contract based on recent price volatility, providing more accurate signals in both calm and volatile markets.
3. ATR-Based Volatility Filter: The Average True Range (ATR) is used to measure market volatility over a user-defined period. It helps refine the trend signals by filtering out false positives caused by minor price swings. The ATR filter ensures that the indicator only signals significant market movements.
⚙️ Step-by-Step Calculation:
1. EMA Calculation: First, the indicator calculates the EMA over a specified period based on the chosen price source (e.g., close, high, low).
2. Standard Deviation Bands: Then, it computes the standard deviation of the EMA and applies a multiplier to create upper and lower bands around the EMA. These bands adjust dynamically with the level of market volatility.
3. ATR Filtering: In addition to the standard deviation bands, the ATR is applied as a secondary filter to help refine the trend signals. This step helps eliminate signals generated by short-term price spikes or corrections, ensuring that the signals are more reliable.
4. Trend Detection: When the price crosses above the upper band, a bullish trend is identified, while a move below the lower band signals a bearish trend. The system accounts for both the standard deviation and ATR bands to generate these signals.
✅ Customizable Inputs and Features
The Adaptive EMA with ATR and Standard Deviation provides a range of customizable options to fit various trading/investing styles:
📈 Trend Settings:
1. Price Source: Choose the price type (e.g., close, high, low) to base the EMA calculation on, influencing how the trend is tracked.
2. EMA Length: Adjust the length to control how quickly the EMA reacts to price changes. A shorter length provides a more responsive EMA, while a longer period smooths out short-term fluctuations.
🌊 Volatility Controls:
1. Standard Deviation Multiplier: This parameter controls the sensitivity of the trend detection by adjusting the distance between the upper and lower bands from the EMA.
2. TR Length and Multiplier: Fine-tune the ATR settings to control how volatility is filtered, adjusting the indicator’s responsiveness during high or low volatility phases.
🎨 Visualization and Alerts:
1. Bar Coloring: Select different colors for uptrends and downtrends, providing a clear visual cue when trends change.
2. Alerts: Set up alerts to notify you when the price crosses the upper or lower bands, signaling a potential long or short trend shift. Alerts can help you stay informed without constant chart monitoring.
📈 Practical Applications
The Adaptive EMA with ATR and Standard Deviation is ideal for traders and investors looking to balance trend-following strategies with volatility management. Key uses include:
Detecting Trend Reversals: The dynamic bands help identify when the market shifts direction, providing clear signals when a trend reversal is likely.
Filtering Market Noise: By applying both Standard Deviation and ATR filtering, the indicator helps reduce false signals during periods of heightened volatility.
Volatility-Based Risk Management: The adaptability of the bands ensures that traders can manage risk more effectively by responding to shifts in volatility while keeping focus on long-term trends.
⭐️ Comprehensive Summary
The Adaptive EMA with ATR and Standard Deviation is a highly customizable indicator that provides traders with clearer signals for trend detection and volatility management. By dynamically adjusting its calculations based on market conditions, it offers a powerful tool for navigating both trending and volatile markets. Whether you're looking to detect early trend reversals or avoid false signals during periods of high volatility, this indicator gives you the flexibility and accuracy to improve your trading and investing strategies.
Note: The Adaptive EMA with ATR and Standard Deviation is designed to enhance your market analysis but should not be relied upon as the sole basis for trading or investing decisions. Always combine it with other analytical tools and practices. No statements or signals from this indicator constitute financial advice. Past performance is not indicative of future results.
Price & Volume Breakout Fibonacci Probability [TradeDots]📝 OVERVIEW
The "Price & Volume Breakout Fibonacci Probability" indicator is designed to detect the probability of the maximum run-up and drawdown of each breakout trade on an asset, assisting traders in optimizing their take profit and stop loss strategies.
🧮 CALCULATIONS
The algorithm detects price and volume breakouts to activate the Fibonacci levels displayed on the chart. It calculates these levels using the period pivot high and low, with the close price of the breakout bar as the reference price.
The indicator then forward-tests within an user-selected number of bars, detecting the maximum run-up and drawdown during that period. Consequently, it calculates the probability of the price hitting either side of the Fibonacci levels, showing the likelihood of reaching take profit and stop loss targets for each breakout trade.
📊 EXAMPLE
The above example shows two breakout trades, circled within the yellow rectangle zone.
The first trade has a maximum run-up above the +0.382 Fibonacci level zone and a maximum drawdown below the -0.618 Fibonacci level zone.
When the price reaches the maximum run-up, it only has a ~45% probability of moving further upward into the last two zones (25% + 19.44%). This indicates that setting a take profit at a higher level may have less than a 50% chance of success.
Conversely, when the price reaches its maximum drawdown, there is only an ~8% probability of moving further downward into the last drawdown zone. This could indicate a potential reversal.
⚙️ SETTINGS
Breakout Condition: Determines the type of breakout condition to track: "Price", "Volume", "Price & Volume".
Backtest Period: The maximum run-up and drawdown are detected within this bar period.
Price Breakout Period: Specifies the number of bars the price needs to break out from.
Volume Breakout Period: Specifies the number of bars the volume needs to break out from.
Trendline Confirmation: Confirms that the close price needs to be above the trendline.
📈 HOW TO USE
By understanding the probabilities of price movements to both the upside and downside, traders can set take profit and stop loss targets with greater accuracy.
For instance, placing a stop loss order below the zone with the highest probability minimizes the chances of being stopped out of a profitable trade. Conversely, setting a take profit target at the zone with the highest probability increases the win rate.
Additionally, if the price breaches multiple Fibonacci levels during the breakout period, it may indicate an abnormal state, signaling a potential reversal or pullback. This can help traders exit trades in a timely manner.
Traders can adjust their take profit and stop loss levels based on their individual risk tolerance.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Normalized and Smoothed Cumulative Delta for Top 5 NASDAQ StocksThis script is designed to create a TradingView indicator called **"Normalized and Smoothed Cumulative Delta for Top 5 NASDAQ Stocks."** The purpose of this indicator is to track and visualize the cumulative price delta (the change in price from one period to the next) for the top five NASDAQ stocks: Apple Inc. (AAPL), Microsoft Corporation (MSFT), Alphabet Inc. (GOOGL), Amazon.com Inc. (AMZN), and Meta Platforms Inc. (FB).
### Key Features of the Script:
1. **Ticker Selection**:
- The script focuses on the top five NASDAQ stocks by automatically setting their tickers.
2. **Price Data Retrieval**:
- It fetches the closing prices for each of these stocks using the `request.security` function for the current timeframe.
3. **Delta Calculation**:
- The script calculates the delta for each stock, which is simply the difference between the current closing price and the previous closing price.
4. **Cumulative Delta Calculation**:
- It calculates the cumulative delta for each stock by adding the current delta to the previous cumulative delta. This helps track the total change in price over time.
5. **Summing and Smoothing**:
- The cumulative deltas for all five stocks are summed together.
- The script then applies an Exponential Moving Average (EMA) with a period of 5 to smooth the summed cumulative delta, making the indicator less sensitive to short-term fluctuations.
6. **Normalization**:
- To ensure the cumulative delta is easy to interpret, the script normalizes it to a range of 0 to 1. This is done by tracking the minimum and maximum values of the smoothed cumulative delta and scaling the data accordingly.
7. **Visualization**:
- The normalized cumulative delta is plotted as a smooth line, allowing users to see the overall trend of the cumulative price changes for the top five NASDAQ stocks.
- A horizontal line is added at 0.5, serving as a midline reference, which can help traders quickly assess whether the normalized cumulative delta is above or below its midpoint.
### Usage:
This indicator is particularly useful for traders and investors who want to monitor the aggregated price movements of the top NASDAQ stocks, providing a high-level view of market sentiment and trends. By smoothing and normalizing the data, it offers a clear and concise visualization that can be used to identify potential market turning points or confirm ongoing trends.
