Previous day high lowThis script Identifies and draw Previous day High low on 15 min Intra day chart
תבניות גרפים
Major Trading Sessions IndicatorsThis indicator displays vertical lines on your chart to mark the opening times of the major global trading sessions (Tokyo, Shanghai/HK, London, and New York). As a crypto trader I want to find price action patterns after sessions open.
It's fully customizable and extendable (you could add closing time for sessions as well)
Works best on short timeframes.
Features:
6 configurable vertical lines (4 preset for major sessions + 2 custom)
Each line shows a customizable label (e.g., "Tokyo", "London")
Individual time and color settings for each line
UTC offset for each line to handle Daylight Saving Time
Option to fix all labels at a specific price level for cleaner appearance (need to set and save it for each chart, it becomes a mess if you don't). Default behavior and limit of Pine Script is that it will be attached to the price wick.
Default Sessions:
Tokyo: 00:00 UTC (midnight)
Shanghai/HK: 01:30 UTC
London: 08:00 UTC (winter) - adjust offset to +1 for summer
New York: 13:00 UTC (winter) - adjust offset to -4 for summer
DST Adjustments:
Simply change the UTC offset when daylight saving time begins/ends:
London: 0 (winter) or +1 (summer)
New York: -5 (winter) or -4 (summer)
Lines extend from top to bottom of the chart and appear precisely when each session opens.
My preferred configuration: shorten names and reduce opacity of colors to 20-30%.
Match on Selectable Percentage Change + RangeIndicator Overview:
Match on Selectable Percentage Change + Range is a powerful analytical tool designed for traders and analysts who want to identify historical price bars that match a specific percentage variation, and then evaluate how price evolved in the following days. It combines precision filtering with visual tabular feedback, making it ideal for pattern recognition, backtesting, and scenario analysis.
What It Does
This indicator scans historical bars to find instances where the percentage change between two consecutive closes matches a user-defined target (± a customizable tolerance). Once matches are found, it displays:
The date of each match (most recent first)
The actual variation searched
The percentage change after 2, 10, 20, and 30 bars
The min-max range (in %) over those same periods
All results are shown in a dynamic table directly on the chart.
Inputs & Controls
Input Description
Which variation do you want to analyze? (%)
Set the target percentage change to look for (e.g. 2.5%)
% deviation from the variation to be considered (%) Define the tolerance range around the target (e.g. ±0.5%)
Bars to analyze (max 9999) Set how many past bars to scan
Show match table Toggle to enable/disable the entire table
Show percentage variations (2d, 10d, 20d, 30d) Toggle to show/hide post-match percentage changes
Show min-max ranges (2d, 10d, 20d, 30d) Toggle to show/hide post-match high/low ranges
Table Structure
Each row in the table represents a historical match. Columns include:
Date: When the match occurred
Variation in: The actual % change that triggered the match
2d / 10d / 20d / 30d: % change after those days
Min-Max 2d / 10d / 20d / 30d: Range of price movement after those days
Color coding helps quickly identify bullish (green) vs bearish (red) outcomes.
Use Cases
Backtesting: See how similar past moves evolved over time
Scenario modeling: Estimate potential outcomes after a known variation
Pattern recognition: Spot recurring setups or volatility clusters
Risk analysis: Understand post-variation drawdowns and upside potential
Tips for Use
Use tighter deviation (e.g. 0.3%) for precision, or wider (e.g. 1%) for broader pattern capture.
Combine with other indicators to validate setups (e.g. volume, RSI, trend filters).
Toggle off variation or range columns to focus only on the metrics you need.
Trend Telescope v4 Basic Configuration
pine
// Enable only the components you need
Order Flow: ON
Delta Volume: ON
Volume Profile: ON
Cumulative Delta: ON
Volatility Indicator: ON
Momentum Direction: ON
Volatility Compression: ON
📊 Component Breakdown
1. Order Flow Analysis
Purpose: Identifies buying vs selling pressure
Visual: Histogram (Green=Buying, Red=Selling)
Calculation: Volume weighted by price position
Usage: Spot institutional order blocks
2. Delta Volume Values
Purpose: Shows volume imbalance
Bull Volume (Green): Volume on up bars
Bear Volume (Red): Volume on down bars
Usage: Identify volume divergences
3. Anchored Volume Profile
Purpose: Finds high-volume price levels
POC (Point of Control): Price with highest volume
Profile Length: Adjustable (default: 50 bars)
Usage: Identify support/resistance zones
4. Cumulative Volume Delta
Purpose: Tracks net buying/selling pressure over time
Trend Analysis: Rising=Buying pressure, Falling=Selling pressure
Divergence Detection: Price vs Delta divergences
Usage: Confirm trend strength
5. Volatility Indicator
Purpose: Measures market volatility with cycle detection
Volatility Ratio: ATR as percentage of price
Volatility Cycle: SMA of volatility (identifies periods)
Histogram: Difference between current and average volatility
Usage: Adjust position sizing, identify breakout setups
6. Real-time Momentum Direction
Purpose: Multi-factor momentum assessment
Components: Price momentum (50%), RSI momentum (30%), Volume momentum (20%)
Visual: Line plot with color coding
Labels: Clear BULLISH/BEARISH/NEUTRAL signals
Usage: Trend confirmation, reversal detection
7. Volatility Compression Analysis
Purpose: Identifies low-volatility consolidation periods
Compression Detection: True Range below threshold
Strength Meter: How compressed the market is
Histogram: Red when compressed, Gray when normal
Usage: Predict explosive moves, prepare for breakouts
⚙️ Advanced Configuration
Optimal Settings for Different Timeframes
pine
// Scalping (1-15 min)
Profile Length: 20
ATR Period: 10
Momentum Length: 8
Compression Threshold: 0.3
// Day Trading (1H-4H)
Profile Length: 50
ATR Period: 14
Momentum Length: 14
Compression Threshold: 0.5
// Swing Trading (Daily)
Profile Length: 100
ATR Period: 20
Momentum Length: 21
Compression Threshold: 0.7
Alert Setup Guide
Enable "Enable Alerts" in settings
Choose alert types:
Momentum Alerts: When momentum changes direction
Compression Alerts: When volatility compression begins
Set alert frequency to "Once Per Bar"
Configure notification preferences
🎯 Trading Strategies
Strategy 1: Compression Breakout
pine
Entry Conditions:
1. Volatility Compression shows RED histogram
2. Cumulative Delta trending upward
3. Momentum turns BULLISH
4. Price breaks above POC level
Exit: When Momentum turns BEARISH or Compression ends
Strategy 2: Momentum Reversal
pine
Entry Conditions:
1. Strong Order Flow in opposite direction
2. Momentum divergence (price makes new high/low but momentum doesn't)
3. Volume confirms the reversal
Exit: When Order Flow returns to trend direction
Strategy 3: Institutional Accumulation
pine
Identification:
1. High Cumulative Delta but flat/sideways price
2. Consistent Order Flow in one direction
3. Volume Profile shows accumulation at specific levels
Trade: Enter in direction of Order Flow when price breaks level
📈 Interpretation Guide
Bullish Signals
✅ Order Flow consistently green
✅ Cumulative Delta making higher highs
✅ Momentum above zero and rising
✅ Bull Volume > Bear Volume
✅ Price above POC level
Bearish Signals
✅ Order Flow consistently red
✅ Cumulative Delta making lower lows
✅ Momentum below zero and falling
✅ Bear Volume > Bull Volume
✅ Price below POC level
Caution Signals
⚠️ Momentum divergence (price vs indicator)
⚠️ Volatility compression (potential big move coming)
⚠️ Mixed signals across components
🔧 Troubleshooting
Common Issues & Solutions
Problem: Indicators not showing
Solution: Check "Show on Chart" is enabled
Problem: Alerts not triggering
Solution: Verify alert is enabled in both script and TradingView alert panel
Problem: Performance issues
Solution: Reduce number of enabled components or increase timeframe
Problem: Volume Profile not updating
Solution: Adjust Profile Length setting, ensure sufficient historical data
Performance Optimization
Disable unused components
Increase chart timeframe
Reduce historical bar count
Use on lower timeframes with fewer indicators enabled
💡 Pro Tips
Risk Management
Use Volatility Indicator for position sizing
Monitor Cumulative Delta for trend confirmation
Use POC levels for stop-loss placement
Multi-Timeframe Analysis
Use higher timeframe for trend direction
Use current timeframe for entry timing
Correlate signals across timeframes
Market Condition Adaptation
Trending Markets: Focus on Momentum + Order Flow
Ranging Markets: Focus on Volume Profile + Compression
High Volatility: Use smaller position sizes
Low Volatility: Prepare for compression breakouts
📚 Educational Resources
Key Concepts to Master
Volume-price relationships
Market microstructure
Institutional order flow
Volatility regimes
Momentum vs mean reversion
Recommended Learning Path
Start with Order Flow + Momentum only
Add Volume Profile once comfortable
Incorporate Volatility analysis
Master multi-component correlation
🆘 Support
Getting Help
Check component toggles are enabled
Verify sufficient historical data is loaded
Test on major pairs/indices first
Adjust settings for your trading style
Continuous Improvement
Backtest strategies thoroughly
Keep a trading journal
Adjust parameters based on market conditions
Combine with price action analysis
Remember: No indicator is perfect. Use this tool as part of a comprehensive trading plan with proper risk management. Always test strategies in demo accounts before live trading.
Happy Trading! 📈
Adaptive Pulse Frequency & Amplitude TrendAdaptive Pulse Frequency & Amplitude Trend Indicator
This Pine Script indicator is designed to identify strong bullish or bearish trends by analyzing volume dynamics on a lower timeframe than the one currently displayed on the chart. It operates on the principle of detecting significant spikes in buying or selling pressure, referred to as "pulses," and then evaluating their frequency, strength, and dominance over the opposing market forces.
Core Concepts
Lower Timeframe Volume Analysis: The script requests up-volume and down-volume data from a more granular, lower timeframe (e.g., 1-minute data when on a 15-minute chart). This provides a higher-resolution view of the flow of buy and sell orders.
Adaptive Pulse Detection: A "pulse" is defined as a bar with an unusually high net volume (up volume minus down volume). Instead of using a fixed value, the indicator calculates an adaptive threshold based on the 90th percentile of net volume over a 100-bar lookback period. Any bar with a net volume exceeding this dynamic threshold is flagged as a pulse, categorized as either bullish (positive net volume) or bearish (negative net volume).
Frequency and Amplitude: The indicator measures two key aspects of these pulses over user-defined lookback periods:
Net Frequency: The number of bullish pulses minus the number of bearish pulses. A positive value indicates more buying pulses, while a negative value indicates more selling pulses.
Net Amplitude : The cumulative volume of bullish pulses minus the cumulative volume of bearish pulses. This measures the overall strength and conviction behind the pulses.
Primary Trend Signal
The indicator's primary signal comes from a strict dominance condition. It doesn't just look for more buying or selling pulses; it checks if these pulses are powerful enough to overwhelm the total opposite pressure in the market.
Bullish Dominance (Green Background): A strong bullish signal is generated when the total volume of all bullish pulses within a lookback period is greater than the total down-volume from all bars (not just pulses) in that same period.
Bearish Dominance (Red Background): A strong bearish signal is generated when the total volume of all bearish pulses is greater than the total up-volume from all bars in that period.
The chart background is colored green for bullish dominance and red for bearish dominance, providing a clear visual cue for when one side has taken decisive control.
Plotted Data
In addition to the background coloring, the indicator plots several lines in its own pane for more detailed analysis:
Net Frequency: Shows the trend in the number of bull vs. bear pulses.
Net Amplitude: Shows the trend in the strength of bull vs. bear pulses.
Bullish/Bearish Amplitude: The individual cumulative volumes for bull and bear pulses.
Dynamic Threshold: The adaptive value used to identify pulses.
By combining an adaptive detection method with a strict dominance condition, this tool aims to filter out market noise and highlight periods of genuinely strong, volume-backed trends.
Constant Auto Trendlines (Extended Right)📈 Constant Auto Trendlines (Extended Right)
This indicator automatically detects market structure by connecting swing highs and lows with permanent, forward-projecting trendlines.
Unlike standard trendline tools that stop at the last pivot, this version extends each trendline infinitely into the future — helping traders visualize where price may react next.
🔍 How It Works
The script identifies pivot highs and lows using user-defined left/right bar counts.
When a new lower high or higher low appears, the indicator draws a line between the two pivots and extends it forward using extend.right.
Each new confirmed trendline stays fixed, creating a historical map of structure that evolves naturally with market action.
Optional filters:
Min Slope – ignore nearly flat trendlines
Show Latest Only – focus on the most relevant trendline
Alerts – get notified when price crosses the most recent uptrend or downtrend line
🧩 Why It’s Useful
This tool helps traders:
Spot emerging trends early
Identify dynamic support/resistance diagonals
Avoid redrawing trendlines manually
Backtest structure breaks historically
⚙️ Inputs
Pivot Left / Right bars
Min slope threshold
Line color, width, and style
Show only latest line toggle
Alert options
NWOG/NDOG + EHPDA🌐 ENGLISH DESCRIPTION
Hybrid NWOG/NDOG + EHPDA – Advanced Gaps & Event Horizon Indicator
(Enhanced with Real-Time Alerts and Info Table)
📊 Overview
This advanced indicator combines automatic detection of weekly gaps (NWOG) and daily gaps (NDOG) with the Event Horizon (EHPDA) concept, now featuring customizable alerts and a real-time info table for a more efficient trading experience. Designed for traders who operate based on institutional price structures, liquidity zones, and SMC/ICT confluences.
✨ Key Features
1. Gap Detection & Visualization
NWOG (New Week Opening Gap): Identifies and visualizes the gap between Friday’s close and Monday’s open.
NDOG (New Day Opening Gap): Detects daily gaps on intraday timeframes.
Enhanced visualization: Semi-transparent boxes, price levels (top, middle, bottom), and lines extended to the current bar.
Customizable labels: Display gap formation date and price levels (optional).
2. Event Horizon (EHPDA)
Automatically calculates the Event Horizon level between two non-overlapping gaps.
Dashed line marking the equilibrium zone between bullish and bearish gaps.
3. Advanced 5pm-6pm Mode
Special option to detect the Sunday-Monday gap using 4H bars.
4. Real-Time Alerts
New gaps (NWOG/NDOG): Immediate notification when a new gap forms.
Gap fill: Alert when price completely fills a gap.
Event Horizon active: Notification when the Event Horizon level is triggered.
5. Info Table
Real-time display: number of active gaps, Event Horizon status, time remaining until weekly/daily close.
Customizable: position, size, and style.
🎨 Customization
Configurable colors for bullish gaps, bearish gaps, and Event Horizon line.
Customizable price labels and date format.
📈 Use Cases
Reversal trading, price targets, liquidity zones, SMC/ICT confluences.
⚙️ Recommended Settings
Timeframes: Daily and intraday (15m, 1H, 4H, etc.).
NWOG: Enable on all timeframes.
NDOG: Enable only on intraday.
Max Gaps: 3-5 for clean charts, 10-15 for historical analysis.
📝 Important Notes
Works best on 24/5 markets (Forex, Crypto).
Gaps automatically close when filled.
Event Horizon only appears with at least 2 non-overlapping gaps.
CVD Divergence + Volume MarkerHere is a Pine Script concept to mark candlestick chart candles when cumulative delta is divergent to price action and volume is above average. Cumulative delta divergence typically occurs when the price forms new highs/lows while cumulative delta forms lower highs/lows (or vice versa). The script should include a marker only when this divergence occurs alongside above-average volume, increasing signal strength and filtering out weak setups.
Coding Concept
Calculate cumulative delta (approximation using price and volume if true bid/ask volume is unavailable, e.g., on spot).
Calculate moving average of volume.
Detect bullish divergence (price makes lower low, cumulative delta makes higher low) and bearish divergence (price makes higher high, cumulative delta makes lower high).
Mark candle with above-average volume when divergence is present.
Flip to GreenPurpose:
This indicator applies a Lorentzian-distance–based machine-learning model to classify market conditions and highlight probable momentum shifts.
Where traditional indicators react to price movement, this one uses statistical pattern recognition to predict when momentum is likely to flip direction — the classic “flip to green” signal.
Concept:
Financial markets don’t move linearly; they bend and distort around major catalysts (news, FOMC meetings, earnings, etc.) in a way similar to how gravity warps space-time.
This indicator accounts for that distortion by measuring distance in Lorentzian space instead of the usual Euclidean space.
In simple terms: it adapts to volatility “warping,” allowing the model to detect structural momentum changes that normal math misses.
Core logic:
Imports two custom libraries:
MLExtensions for machine-learning utilities
KernelFunctions for advanced distance calculations
Computes relationships among multiple features (e.g., RSI, ADX, or other inputs).
Uses Lorentzian geometry to weight how recent price-time behavior influences current classification.
Outputs a visual “flip” cue when the probability of trend reversal exceeds threshold confidence.
Why it matters:
Most indicators measure what has already happened.
Lorentzian Classification attempts to capture what’s about to happen by comparing the present market state to a trained historical distribution under warped “price-time” geometry.
It’s particularly useful for spotting early accumulation or exhaustion zones before they become obvious on standard momentum tools.
Recommended use:
Run it as a background trend classifier or color overlay.
Combine it with volume-based confirmation tools (e.g., Dollar Volume Ownership Gauge) and structural analysis.
A “flip to green” suggests buyers are regaining control; a fade or flip to red implies control returning to sellers.
Dollar Volume Ownership GaugePurpose:
DVOG tracks the real money moving through a ticker by converting share volume into dollar volume (price × volume). It helps identify when institutional-sized players enter, defend, or unload positions — information that plain volume bars often hide.
How it works:
Each bar represents 4-minute aggregated dollar volume.
Green bars = moderate sponsorship ($400 K–$1 M per 4 min).
Red bars = heavy sponsorship ($1 M+ per 4 min).
Black bars = normal retail flow (under $400 K).
Optional horizontal guides mark both thresholds for quick reference.
Alerts:
Green Bar Alert: fires every time a bar exceeds $400 K, signaling fresh institutional activity.
Cross Alerts: trigger once when dollar volume crosses the $400 K or $1 M levels, perfect for automation or notifications.
Why it’s useful:
DVOG visually confirms when a breakout, knife-and-reclaim, or coil is being driven by real capital rather than low-liquidity noise.
It turns abstract volume into a direct measure of who’s actually in control.
Recommended use:
Run it in a separate pane below price. Combine with your normal structure analysis — higher lows, double bottoms, coils, etc. — and act only when structure and sponsorship line up.
Signal vs. Noise Have been working on this to get a better feel for market conditions. Am generally a pretty shit trader so just wanted to give this a go. Any feedback is appreciated.
Inside SwingsOverview
The Inside Swings indicator identifies and visualizes "inside swing" patterns in price action. These patterns occur when price creates a series of pivots that form overlapping ranges, indicating potential consolidation or reversal zones.
What are Inside Swings?
Inside swings are specific pivot patterns where:
- HLHL Pattern: High-Low-High-Low sequence where the first high is higher than the second high, and the first low is lower than the second low
- LHLH Pattern: Low-High-Low-High sequence where the first low is lower than the second low, and the first high is higher than the second high
Here an Example
These patterns create overlapping price ranges that often act as:
- Support/Resistance zones
- Consolidation areas
- Potential reversal points
- Breakout levels
Levels From the Created Range
Input Parameters
Core Settings
- Pivot Lookback Length (default: 5): Number of bars on each side to confirm a pivot high/low
- Max Boxes (default: 100): Maximum number of patterns to display on chart
Extension Settings
- Extend Lines: Enable/disable line extensions - this extends the Extremes of the Swings to where a new Swing Started or Extended Right for the Latest Inside Swings
- Show High 1 Line: Display first high/low extension line
- Show High 2 Line: Display second high/low extension line
- Show Low 1 Line: Display first low/high extension line
- Show Low 2 Line: Display second low/high extension line
Visual Customization
Box Colors
- HLHL Box Color: Color for HLHL pattern boxes (default: green)
- HLHL Border Color: Border color for HLHL boxes
- LHLH Box Color: Color for LHLH pattern boxes (default: red)
- LHLH Border Color: Border color for LHLH boxes
Line Colors
- HLHL Line Color: Extension line color for HLHL patterns
- LHLH Line Color: Extension line color for LHLH patterns
- Line Width: Thickness of extension lines (1-5)
Pattern Detection Logic
HLHL Pattern (Bullish Inside Swing)
Condition: High1 > High2 AND Low1 < Low2
Sequence: High → Low → High → Low
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form High-Low-High-Low sequence
2. Fourth pivot (first high) > Second pivot (second high)
3. Third pivot (first low) < Last pivot (second low)
LHLH Pattern (Bearish Inside Swing)
Condition: Low1 < Low2 AND High1 > High2
Sequence: Low → High → Low → High
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form Low-High-Low-High sequence
2. Fourth pivot (first low) < Second pivot (second low)
3. Third pivot (first high) > Last pivot (second high)
Visual Elements
Boxes
- Box 1: Spans from first pivot to last pivot (larger range)
- Box 2: Spans from third pivot to last pivot (smaller range)
- Overlap: The intersection of both boxes represents the inside swing zone
Extension Lines
- High 1 Line: Horizontal line at first high/low level
- High 2 Line: Horizontal line at second high/low level
- Low 1 Line: Horizontal line at first low/high level
- Low 2 Line: Horizontal line at second low/high level
Line Extension Behavior
- Historical Patterns: Lines extend until the next pattern starts
- Latest Pattern: Lines extend to the right edge of chart
- Dynamic Updates: All lines are redrawn on each bar for accuracy
Trading Applications
Support/Resistance Levels
Inside swing levels often act as:
- Dynamic support/resistance
- Breakout confirmation levels
- Reversal entry points
Pattern Interpretation
- HLHL Patterns: Potential bullish continuation or reversal
- LHLH Patterns: Potential bearish continuation or reversal
- Overlap Zone: Key area for price interaction
Entry Strategies
1. Breakout Strategy: Enter on break above/below inside swing levels
2. Reversal Strategy: Enter on bounce from inside swing levels
3. Range Trading: Trade between inside swing levels
Technical Implementation
Data Structures
type InsideSwing
int startBar // First pivot bar
int endBar // Last pivot bar
string patternType // "HLHL" or "LHLH"
float high1 // First high/low
float low1 // First low/high
float high2 // Second high/low
float low2 // Second low/high
box box1 // First box
box box2 // Second box
line high1Line // High 1 extension line
line high2Line // High 2 extension line
line low1Line // Low 1 extension line
line low2Line // Low 2 extension line
bool isLatest // Latest pattern flag
Memory Management
- Pattern Storage: Array-based storage with automatic cleanup
- Pivot Tracking: Maintains last 4 pivots for pattern detection
- Resource Cleanup: Automatically removes oldest patterns when limit exceeded
Performance Optimization
- Duplicate Prevention: Checks for existing patterns before creation
- Efficient Redraw: Only redraws lines when necessary
- Memory Limits: Configurable maximum pattern count
Usage Tips
Best Practices
1. Combine with Volume: Use volume confirmation for breakouts
2. Multiple Timeframes: Check higher timeframes for context
3. Risk Management: Set stops beyond inside swing levels
4. Pattern Validation: Wait for confirmation before entering
Common Scenarios
- Consolidation Breakouts: Inside swings often precede significant moves
- Reversal Zones: Failed breakouts at inside swing levels
- Trend Continuation: Inside swings in trending markets
Limitations
- Lagging Indicator: Patterns form after completion
- False Signals: Not all inside swings lead to significant moves
- Market Dependent: Effectiveness varies by market conditions
Customization Options
Visual Adjustments
- Modify colors for different market conditions
- Adjust line widths for visibility
- Enable/disable specific elements
Detection Sensitivity
- Increase pivot length for smoother patterns
- Decrease for more sensitive detection
- Balance between noise and signal
Display Management
- Control maximum pattern count
- Adjust cleanup frequency
- Manage memory usage
Conclusion
The Inside Swings indicator provides a systematic approach to identifying consolidation and potential reversal zones in price action. By visualizing overlapping pivot ranges
The indicator's strength lies in its ability to:
- Identify key price levels automatically
- Provide visual context for market structure
- Offer flexible customization options
- Maintain performance through efficient memory management
Torus Trend Bands — Windowed HammingTorus Trend Bands — Windowed Hamming
This TradingView indicator creates dynamic support and resistance bands on your chart. It uses the mathematical model of a torus (a donut shape) to generate cyclical and responsive channel boundaries. The bands are further refined with an advanced smoothing method called a Hamming window to reduce noise and provide a clearer signal.
How It Works
The Torus Model: The indicator maps price action onto a geometric torus shape. This is defined by two key parameters:
Major Radius (a): The distance from the center of the torus to the center of the tube. This controls the overall size and primary cycle.
Minor Radius (b): The radius of the tube itself. This controls the secondary, faster "breathing" motion of the bands.
Dual-Phase Engine: The behavior of the bands is driven by two different cyclical inputs, or "phases":
Major Rotation (φ): A slow, time-based cycle (φ period) that governs the long-term oscillation of the bands.
Minor Rotation (q): A fast, momentum-based cycle derived from the Relative Strength Index (RSI). This makes the bands react quickly to price momentum, expanding and contracting as the market becomes overbought or oversold.
Standard Technical Core : The torus model is anchored to the price chart using standard indicators:
Midline : A central moving average that acts as the baseline for the channel. You can choose from EMA, SMA, HMA, or VWAP.
Width Source: A volatility measure that determines the fundamental width of the bands. You can choose between the Average True Range (ATR) or Standard Deviation.
Hamming Window Smoothing: This is a sophisticated weighted averaging technique (a Finite Impulse Response filter) used in digital signal processing. It provides exceptionally smooth results with less lag than traditional moving averages. You can apply this smoothing to the RSI, the midline, and the width source independently to filter out market noise.
How to Interpret and Use the Indicator
Dynamic Support & Resistance: The primary use is to identify potential reversal or continuation points. The upper band acts as dynamic resistance, and the lower band acts as dynamic support.
Trend Identification: The color of the bands helps you quickly see the current trend. Teal bands indicate an uptrend (the midline is rising), while red bands indicate a downtrend (the midline is falling).
Volatility Gauge: When the bands widen, it signals an increase in market volatility. When they contract, it suggests volatility is decreasing.
Alerts: The indicator includes built-in alerts that can notify you when the price touches or breaks through the upper or lower bands, helping you stay on top of key price action.
Key Settings
Torus Parameters : Adjust Major radius a and Minor radius b to change the shape and cyclical behavior of the bands.
Phase Controls:
φ period: Controls the length of the main, slow cycle in bars.
RSI length → q: Sets the lookback for the RSI that drives the momentum-based cycle.
Midline & Width: Choose the type and length for the central moving average and the volatility source (ATR/StDev) that best fits your trading style.
Width & Bias Shaping:
Min/Max width ×: Control how much the bands expand and contract.
Bias ×: Shifts the entire channel up or down based on RSI momentum, helping the bands better capture strong trends.
Hamming Controls: Enable or disable the advanced smoothing on different parts of the indicator and set the Hamming length (a longer length results in more smoothing).
This indicator provides a unique and highly customizable way to visualize market cycles, volatility, and trend, combining geometry with proven technical analysis tools.
Divergence for Many Indicators v5 - No RepaintUses confirmed bar processing to prevent repainting, ensuring
signals never change after they appear. Automatically draws
divergence lines on the chart and labels show which indicators
are diverging. Customizable settings include pivot period,
minimum divergence threshold, line styles, and colors for
different divergence types.
Ideal for identifying potential trend reversals (regular
divergence) and trend continuations (hidden divergence) with
high-confidence multi-indicator confirmation.
Smart Money Dynamics Blocks — Pearson MatrixSmart Money Dynamics Blocks — Pearson Matrix
A structural fusion of Prime Number Theory, Pearson Correlation, and Cumulative Delta Geometry.
1. Mathematical Foundation
This indicator is built on the intersection of Prime Number Theory and the Pearson correlation coefficient, creating a structural framework that quantifies how price and time evolve together.
Prime numbers — unique, indivisible, and irregular — are used here as nonlinear time intervals. Each prime length (2, 3, 5, 7, 11…97) represents a regression horizon where correlation is measured between price and time. The result is a multi-scale correlation lattice — a geometric matrix that captures hidden directional strength and temporal bias beyond traditional moving averages.
2. The Pearson Matrix Logic
For every prime interval p, the indicator calculates the linear correlation:
r_p = corr(price, bar_index, p)
Each r_p reflects how closely price and time move together across a prime-defined window. All r_p values are then averaged to create avgR, a single adaptive coefficient summarizing overall structural coherence.
- When avgR > 0.8 → strong positive correlation (labeled R+).
- When avgR < -0.8 → strong negative correlation (labeled R−).
This approach gives a mathematically grounded definition of trend — one that isn’t based on pattern recognition, but on measurable correlation strength.
3. Sequential Prime Slope and Median Pivot
Using the ordered sequence of 25 prime intervals, the model computes sequential slopes between adjacent primes. These slopes represent the rate of change of structure between two prime scales. A robust median aggregator smooths the slopes, producing a clean, stable directional vector.
The system anchors this slope to the 41-bar pivot — the median of the first 25 primes — serving as the geometric midpoint of the prime lattice. The resulting yellow line on the chart is not an ordinary regression line; it’s a dynamic prime-slope function, adapting continuously with correlation feedback.
4. Regression-Style Parallel Bands
Around this prime-slope line, the indicator constructs parallel bands using standard deviation envelopes — conceptually similar to a regression channel but recalculated through the prime–Pearson matrix.
These bands adjust dynamically to:
- Volatility, via standard deviation of residuals.
- Correlation strength, via avgR sign weighting.
Together, they visualize statistical deviation geometry, making it easier to observe symmetry, expansion, and contraction phases of price structure.
5. Volume and Cumulative Delta Peaks
Below the geometric layer, the indicator incorporates a custom lower-timeframe volume feed — by default using 15-second data (custom_tf_input_volume = “15S”). This allows precise delta computation between up-volume and down-volume even on higher timeframe charts.
From this feed, the indicator accumulates delta over a configurable period (default: 100 bars). When cumulative delta reaches a local maximum or minimum, peak and trough markers appear, showing the precise bar where buying or selling pressure statistically peaked.
This combination of geometry and order flow reveals the intersection of market structure and energy — where liquidity pressure expresses itself through mathematical form.
6. Chart Interpretation
The primary chart view represents the live execution of the indicator. It displays the relationship between structural correlation and volume behavior in real time.
Orange “R+” and blue “R−” labels indicate regions of strong positive or negative Pearson correlation across the prime matrix. The yellow median prime-slope line serves as the structural backbone of the indicator, while green and red parallel bands act as dynamic regression boundaries derived from the underlying correlation strength. Peaks and troughs in cumulative delta — displayed as numerical annotations — mark statistically significant shifts in buying and selling pressure.
The secondary visualization (Prime Regression Concept) expands on this by illustrating how regression behavior evolves across prime intervals. Each colored regression fan corresponds to a prime number window (2, 3, 5, 7, …, 97), demonstrating how multiple regression lines would appear if drawn independently. The indicator integrates these into one unified geometric model — eliminating the need to plot tens of regression lines manually. It’s a conceptual tool to help visualize the internal logic: the synthesis of many small-scale regressions into a single coherent structure.
7. Interpretive Insight
This model is not a prediction tool; it’s an instrument of mathematical observation. By translating price dynamics into a prime-structured correlation space, it reveals how coherence unfolds through time — not as a forecast, but as a measurable evolution of structure.
It unifies three analytical domains:
- Prime distribution — defines a nonlinear temporal architecture.
- Pearson correlation — quantifies statistical cohesion.
- Cumulative delta — expresses behavioral imbalance in order flow.
The synthesis creates a geometric analysis of liquidity and time — where structure meets energy, and where the invisible rhythm of market flow becomes measurable.
8. Contribution & Feedback
Share your observations in the comments:
- The time gap and alternation between R+ and R− clusters.
- How different timeframes change delta sensitivity or reveal compression/expansion.
- Prime intervals/clusters that tend to sit near turning points or liquidity shifts.
- How avgR behaves across assets or regimes (trending, ranging, high-vol).
- Notable interactions with the parallel bands (touches, breaks, mean-revert).
Your field notes help others read the model more effectively and compare contexts.
Summary
- Primes define the structure.
- Pearson quantifies coherence.
- Slope median stabilizes geometry.
- Regression bands visualize deviation.
- Cumulative delta locates imbalance.
Together, they construct a framework where mathematics meets market behavior.
Tradytics Levels with EMA CloudThis indicator has tradytics price chart levels where you can put in the input code seen below.
The code has positive gamma (green lines), negative gamma (Red lines) and white dotted line are the darkpool levels.
This is Amazon's 5 minute from Sep30th to October 20th Gammas and weekly Darkpool levels. Just copy and paste code below in the input code and the chart would show the levels.
212.8*1*neutral 220.07*1*neutral 216.038*1*neutral 215.57*1*neutral 219.988*1*neutral 217.401*1*neutral 217.351*1*neutral 212.815*1*neutral 212.75*1*neutral 212.4*1*neutral 215*0*negative 222.5*0*positive 217.5*0*positive 220*0*positive
4h 相对超跌筛选器 · Webhook v2.0## 指标用途
用于你的「框架第2步」：在**美股 RTH**里，按**4h 收盘**（06:30–10:30 PT 为首根）筛出相对大盘/行业**显著超跌**且结构健康的候选标的，并可**通过 Webhook 自动推送**`symbol + ts`给下游 AI 执行新闻甄别（第3步）与进出场评估（第4步）。
## 工作原理（核心逻辑）
* **结构健康**：最近 80 根 4h 中，收盘 > 4h_SMA50 的占比 ≥ 阈值（默认 55%）。
* **跌深条件**：4h 跌幅 ≤ −4%，且近两根累计（≈8h）≤ −6%。
* **相对劣化**：相对大盘（SPY/QQQ）与相对行业（XLK/XLF/… 或 KWEB/CQQQ）各 ≤ −3%。
* **流动性与价格**：ADV20_USD ≥ 2000 万；价格 ≥ 3 美元。
* **只在 4h 收盘刻评估与触发**，历史点位全部保留，便于回放核验。
* **冷却**：同一标的信号间隔 ≥ N 天（默认 10）。
## 主要输入参数
* **bench / sector**：大盘与行业基准（例：SPY/QQQ，XLK/XLF/XLY；中概用 KWEB/CQQQ）。
* **advMinUSD / priceMin**：20 日美元成交额下限、最小价格。
* **pctAboveTh**：结构健康阈值（%）。
* **drop4hTh / drop8hTh**：4h/8h 跌幅阈值（%）。
* **relMktTh / relSecTh**：相对大盘/行业阈值（%）。
* **coolDays**：冷却天数。
* **fromDate**：仅显示此日期后的历史信号（图表拥挤时可用）。
* **showTable / tableRows**：是否显示右上角“最近信号表”及行数。
## 图表信号
* **S2 绿点**：当根 4h 收盘满足全部筛选条件。
* **右上角表格**：滚动列出最近 N 条命中（`SYMBOL @ yyyy-MM-dd HH:mm`，按图表本地时区）。
## Webhook 联动（生产用）
1. 添加指标 → 🔔 新建警报（Alert）：
* **Condition**：`Any alert() function call`
* **Options**：`Once per bar close`
* **Webhook URL**：填你的接收地址（可带 `?token=...`）
* **Message**：留空（脚本内部 `alert(payload)` 会发送 JSON）。
2. 典型 JSON 载荷（举例）：
```json
{
"event": "step2_signal",
"symbol": "LULU",
"symbol_id": "NASDAQ:LULU",
"venue": "NASDAQ",
"bench": "SPY",
"sector": "XLY",
"ts_bar_close_ms": 1754524200000,
"ts_bar_close_local": "2025-06-06 10:30",
"price_close": 318.42,
"ret_4h_pct": -5.30,
"ret_8h_pct": -7.45,
"rel_mkt_pct": -4.90,
"rel_sec_pct": -3.80
}
```
> 建议以 `symbol + ts_bar_close_ms` 做去重键；接收端先快速 `200 OK`，后续异步处理并交给第3步 AI。
## 使用建议
* **时间框架**：任意周期可用，指标内部统一拉取 240 分钟数据并仅在 4h 收盘刻触发。
* **行业映射**：尽量选与个股业务最贴近的 ETF；中国 ADR 可用 `PGJ/KWEB/CQQQ` 叠加细分行业对照。
* **回放验证**：Bar Replay **不发送真实 Webhook**；仅用于查看历史命中与表格。测试接收端请用 Alert 面板的 **Test**。
## 适配说明
* Pine Script **v5**。
* 不含成分筛查逻辑（请在你的 500–600 只候选池内使用）。
* 数字常量不使用下划线分隔；如需大数可用 `20000000` 或 `2e7`。
## 常见问题
* ⛔️ 报错 `tostring(...)`：Pine 无时间格式化重载，脚本已内置 `timeToStr()`。
* ⛔️ `syminfo.exchange` 不存在：已改用 `syminfo.prefix`（交易所前缀）。
* ⛔️ 多行字符串拼接报 `line continuation`：本脚本已用括号包裹或 `str.format` 规避。
## 免责声明
该指标仅供筛选与研究使用，不构成投资建议。请结合你的第3步新闻/基本面甄别与第4步执行规则共同决策。
Trend Strength Detector TSDTrend Strength Detector (TSD)
*Objective Trend Quality Measurement for Educational Market Analysis*
Note: This mathematical framework is a proprietary quantitative model developed by Ario Pinelab, inspired by classical EMA, ADX, RSI and MACD principles, yet not documented in any public technical or academic publication.
## 🎯 Purpose & Design Philosophy
The ** Trend Strength Detector- TSD ** is an educational research tool that provides **quantitative measurement of trend quality** through two independent scoring systems (0-100 scale). It answers the analytical question: *"How strong and aligned is the current market trend environment?"*
This indicator is designed with a **modular, complementary approach** to work alongside various analysis methodologies, particularly pattern-based recognition systems.
## 🔗 Complementary Research Framework
### Designed to Work With Pattern Detection Systems
This indicator provides **environmental context measurement** that complements qualitative pattern recognition tools. It works particularly well alongside systems like:
- **RMBS Smart Detector - Multi-Factor Momentum System**
- Traditional chart pattern analyzers
- Any momentum-based pattern identification tools
🔍 **To find RMBS Smart Detector:**
- Search in TradingView Indicators Library: `" RMBS Smart Detector - Multi-Factor Momentum System"`
- Look for: *Multi-Factor Momentum System*
- By author: ` `
### Why This Complementary Approach?
**Trend Quality Measurement** (TSD - this tool) provides:
- ✅ Structural trend alignment (0-100 score)
- ✅ Momentum intensity levels (0-100 score)
- ✅ Environment classification (Strong/Moderate/Weak)
- 📌 **Answers:** *"HOW STRONG is the underlying trend environment?"*
### Educational Research Value
When used together in a research context, these tools enable systematic study of questions like:
- How do reversal patterns behave when Strength Score is above 70 vs below 30?
- Do continuation patterns in weakening environments (declining scores) show different characteristics?
- What is the correlation between high Alignment Scores and pattern "success rates"?
- Can environment classification help identify genuine trend initiation vs false starts?
⚠️ **Important Note:** Both tools are **independent and work standalone**. TSD provides value whether used alone or with other analysis methods. The relationship with RMBS (or any pattern tool) is **complementary for research purposes**, not dependent.
---
###Mathematical Foundation
##TSA Formula: scoring method developed by Ario
-Trend Model (0 – 100)
TAS = EMA Alignment (0–40) + Price Position (0–30) + Trend Consistency (0–30)
EMA Alignment checks EMA_fast vs EMA_slow vs EMA_trend structure.
Price Position evaluates if Close is above/below all EMAs.
Consistency = 3 × max(bullish,bearish bars within 10 candles).
-Strength Model (0 – 100)
Strength = ADX (0–50) + EMA Slope (0–25) + RSI (0–15) + MACD (0–10)
ADX measures trend energy; Slope shows EMA momentum %;
RSI assesses zone positioning; MACD confirms directional agreement.
Note: This formula represents a proprietary quantitative model by Ario_Pinelab, inspired by classical technical concepts but not published in any external reference.________________________________________
📊 Environment Classification
Based on Total Strength Score:
🟢 Strong Environment: Score ≥ 60
→ Well-defined momentum, clear directional bias
🟡 Moderate Environment: 40 ≤ Score < 60
→ Mixed signals, transitional conditions
🔴 Weak Environment: Score < 40
→ Ranging, choppy, low conviction movement
Color Coding:
• Green background: Strong (≥60)
• Yellow background: Moderate (40-59)
• Red background: Weak (<40)
________________________________________
📈 Visual Components
Main Chart Display
Score Labels (Top-Right Corner):
┌─────────────────────────────────┐
│ 📊 Alignment: 75 | Strength: 82 │
│ Environment: Strong 🟢 │
└─────────────────────────────────┘
Color-Coded Background:
• Environment strength visually indicated via background color
• Helps quick identification of market regime
• Customizable transparency (default: 90%)
Reference Lines:
• Dotted line at 60: Strong/Moderate threshold
• Dotted line at 40: Moderate/Weak threshold
• Mid-line at 50: Neutral reference
________________________________________
🔧 Customization Settings
Input Parameters
The best setting is the default mode.
🚫 Important Disclaimers & Limitations
What This Indicator IS:
✅ Educational measurement tool for trend quality research
✅ Quantitative assessment of current market environment
✅ Complementary analysis tool for pattern-based systems
✅ Historical data analyzer for systematic study
✅ Multi-factor scoring system based on technical calculations
What This Indicator IS NOT:
❌ NOT a trading system or signal generator
❌ NOT financial advice or trade recommendations
❌ NOT predictive of future price movements
❌ NOT a guarantee of pattern success/failure
❌ NOT a substitute for comprehensive risk management
________________________________________
Known Limitations
1. Lagging Nature:
⚠️ All components (EMA, ADX, RSI, MACD) are calculated
from historical price data
→ Scores reflect CURRENT and RECENT conditions
→ Cannot predict sudden reversals or black swan events
→ Trend measurements lag actual price turning points
2. Whipsaw Risk:
⚠️ In choppy/ranging markets, scores may fluctuate rapidly
→ Moderate zone (40-60) can see frequent transitions
→ Low timeframes more susceptible to noise
→ Consider higher timeframes for stable measurements
3. Component Conflicts:
⚠️ Individual components may disagree
→ Example: Strong ADX but weak RSI alignment
→ Scores average these conflicts (may hide nuance)
→ Check individual components for deeper insight
4. Not Predictive:
⚠️ High scores do NOT guarantee continuation
⚠️ Low scores do NOT guarantee reversal
→ Measurement ≠ Prediction
→ Use for CONTEXT, not SIGNALS
→ Combine with comprehensive analysis
________________________________________
Risk Acknowledgments
Market Risk:
• All trading involves substantial risk of loss
• Past performance (even systematic studies) does not guarantee future results
• No indicator, system, or methodology can eliminate market risk
Measurement Limitations:
• Scores are mathematical calculations, not market predictions
• Environmental classification is descriptive, not prescriptive
• Strong measurements can deteriorate rapidly without warning
Educational Purpose:
• This tool is designed for LEARNING about market structure
• Not designed, tested, or validated as a standalone trading system
• Any trading decisions are user’s sole responsibility
No Warranty:
• Indicator provided “as-is” for educational purposes
• No guarantee of accuracy, reliability, or profitability
• Users must verify calculations and apply critical thinking
Open Source
Full Pine Script code available for educational study and modification. Feedback and improvement suggestions welcome.
“All logic is presented for research and educational visualization.”
---
**Attribution & Fair Use Notice**
The Trend Strength Detector (TSD) scoring framework (Multi-Factor Momentum System) was originally designed and formulated by *Ahmadrezarahmati( Ario or Ario_ Pine Lab)*.
If you build upon, modify, or republish this logic—please include proper attribution to the original author. This request is made under a spirit of open collaboration and educational fairness.
PDB 4 MA + Candle Strength/Weakness Detector
4MA Strength & Reversal Detector
Unlock the power of momentum with this advanced 4 Moving Average system (20, 50, 100, 200) designed to pinpoint market strength and early reversal zones with precision.
How It Works:
- Bearish Reversal: Triggered when all moving averages align (20 < 50 < 100 < 200) and bearish reversal candles appear — highlighting potential tops.
- Bullish Reversal: Triggered when all moving averages align (200 < 100 < 50 < 20) and bullish reversal candles form — marking potential bottoms
:Best For:
⚡ Scalpers and day traders using 1–5 minute timeframes
📈 Identifying momentum shifts and trend exhaustion early
Tip: Combine this with volume or RSI for stronger confirmation and fewer false signals.
KDJ Max-Distance (K-D vs K-J)This indicator measures the maximum divergence between K and its related lines (D or J) in the KDJ stochastic system.
KEY CONCEPT:
- Calculates two distances: |K-D| and |K-J|
- Outputs whichever distance is larger
- Shows which component (D or J) is most diverged from K at any given time
CALCULATION:
1. Standard KDJ: K (fast), D (K smoothed), J (3K - 2D)
2. Distance K-D: momentum between fast and slow lines
3. Distance K-J: captures extreme divergence
4. Output: max(|K-D|, |K-J|) or signed version
INTERPRETATION:
• High positive values: K strongly above both D and J (strong upward momentum)
• High negative values: K strongly below both D and J (strong downward momentum)
• Near zero: K aligned with D/J (consolidation or reversal zone)
• Background color shows which is dominant: Teal=K-D, Orange=K-J
USE CASES:
- Identify extreme momentum conditions
- Spot divergence exhaustion
- Confirm trend strength
- Filter ranging vs trending markets
SETTINGS:
- Signed mode: preserves direction (positive/negative)
- Absolute mode: shows pure distance magnitude
- Adjustable guide levels for visual reference
CHAN CRYPTO RS🩷 ATR RS (Crypto / High-based 2.1x, Decimal Safe v2)
This indicator is designed for crypto position sizing and stop calculation using ATR-based risk management. It helps traders automatically determine the stop price, per-unit risk, and optimal position size based on a fixed risk amount in USDT.
🔧 Core Logic
ATR Length (Daily RMA) — calculates the daily Average True Range (ATR) using RMA smoothing.
ATR Multiplier (2.1× default) — defines how far the stop is placed from the daily high.
Stop Price (for Longs) = Daily High − ATR × Multiplier
Per-Unit Risk = (Entry − Stop) × Point Value
Position Size = Risk Amount ÷ Per-Unit Risk
Automatically handles decimal precision for micro-priced crypto assets (e.g., PEPE, SHIB).
Includes safeguards for minimum size and maximum position caps.
💡 Features
Uses Daily ATR without lookahead (no repainting).
Dynamically switches between current and previous ATR for stable results when the daily bar isn’t yet confirmed.
“Snap to tick” ensures stop prices align with the symbol’s tick size.
Table display summarizes ATR, stop price, per-unit risk, total risk, size, and bet amount.
Optional stop label on the chart for visual clarity.
🧮 Output Table
Metric Description
ATR(10) Daily RMA-based ATR
ATR used Chosen ATR (current or previous)
Stop Calculated stop price
Per-unit Risk per coin/unit
Risk Total risk in USDT
Size Optimal position size
Bet Total position value (Entry × Size)
🧠 Ideal For
Crypto traders who use fixed-risk ATR strategies and need precise, decimal-safe position sizing even for ultra-low-priced tokens.
Ahi Ultimate Script v6Ultimate Script v6 – a clean and flexible tool for monitoring price action:
Shows key moving lines for tracking market direction, with options to turn each line on or off.
Highlights short-term levels where price may react, using small horizontal lines.
Displays visual signals like “LONG” or “SELL” directly on the chart to help spot opportunities.
Marks important time-based ranges with colored boxes for quick reference.
All elements are clear, adjustable, and designed to keep your chart neat and easy to read
