Overheat Oscillator with DivergenceIndicator Description
The Overheat Oscillator with Divergence is an advanced technical indicator designed for the TradingView platform, assisting traders in identifying potential market reversal points by analyzing price momentum and volume, as well as detecting divergences. The indicator combines trend strength assessment with signal smoothing to provide clear indications of market overheat or oversold conditions. An optional divergence detection feature allows for the identification of discrepancies between price movement and the oscillator's value, which may signal upcoming trend changes.
The indicator is displayed in a separate panel below the price chart and offers visual cues through a color gradient, horizontal reference lines, and a dynamic market sentiment table. Users can customize numerous parameters, such as calculation periods, sentiment thresholds, line colors, and visualization styles, making the indicator a versatile tool for various trading strategies.
How the Indicator Works
The indicator is based on the following key components:
Oscillator Calculations
The indicator analyzes price candles, assigning a score based on their nature. A bullish candle (when the closing price is higher than the opening price) receives a score of +1.0, while a bearish candle (when the closing price is lower than the opening price) receives a score of -1.0. This scoring reflects the strength of price movement over a given period.
The score is modified by a volume multiplier (default: 2.0) if the candle's volume exceeds the volume's simple moving average (SMA, default: calculated over 20 candles). This ensures that candles with higher volume have a greater impact on the oscillator's value, better capturing significant market movements driven by increased trading activity. For example, a bullish candle with high volume may receive a score of +2.0 instead of +1.0, amplifying the bullish signal.
The scores are summed over a specified number of candles (default: 20), normalized to a 0–100 range, and then smoothed using a simple moving average (SMA, default: 5 periods) to reduce noise and improve signal clarity.
Color Gradient
The oscillator's values are visualized using a color gradient that changes based on the oscillator's level:
Green: Market cooldown (values below the Gradient Min threshold).
Yellow: Neutral sentiment (values between Gradient Min and Gradient Yellow).
Orange: Elevated activity (values between Gradient Yellow and Gradient Orange).
Red: Market overheat (values above Gradient Orange).
The color gradient is applied as the background in the oscillator panel, facilitating quick assessment of market sentiment.
Reference Levels
The indicator displays customizable horizontal lines for key thresholds (e.g., Overheat Threshold, Oversold Threshold, Gradient Min, Yellow, Orange, Max). These lines are visible only at the height of the last few oscillator candles, preventing chart clutter and helping users focus on current values.
Users can also define three custom horizontal lines with selectable styles (solid, dotted, dashed) and colors. These lines serve as auxiliary tools, e.g., for marking personal support/resistance levels, but do not affect the oscillator's signals or background colors.
Market Sentiment
The indicator displays sentiment labels in a table located in the top-right corner of the panel, dynamically updating based on the oscillator's value:
Cooled: Values below Gradient Yellow (default: 35).
Neutral: Values between Gradient Yellow and Gradient Orange (default: 60).
Excited: Values between Gradient Orange and Overheat Threshold (default: 70).
Overheated: Values above Overheat Threshold (default: 70).
The Overheat Threshold and Oversold Threshold are critical for displaying the "Overheated" and "Cooled" labels in the sentiment table, enabling users to quickly identify extreme market conditions. The labels update when key thresholds are crossed, and their colors match the oscillator's gradient.
Divergence Detection
The indicator offers optional detection of regular bullish and bearish divergences:
Bullish Divergence: Occurs when the price forms a lower low, but the oscillator forms a higher low, suggesting a weakening downtrend.
Bearish Divergence: Occurs when the price forms a higher high, but the oscillator forms a lower high, suggesting a weakening uptrend.
Divergences are marked on the chart with labels ("Bull" for bullish, "Bear" for bearish) and lines indicating pivot points. They are calculated with a delay equal to the Lookback Right setting (default: 5 candles), meaning signals appear after pivot confirmation in the specified lookback period. The indicator also generates alerts for users when a divergence is detected.
Indicator Settings
Main Settings (SETTINGS)
Period Length: Specifies the number of candles used for oscillator calculations (default: 20).
Volume SMA Period: The period for the volume's simple moving average (default: 20).
Volume Multiplier: Multiplier applied to candle scores when volume exceeds the average (default: 2.0).
SMA Length: The period for smoothing the oscillator with a simple moving average (default: 5).
Thresholds (THRESHOLDS)
Overheat Threshold: Level indicating market overheat (default: 70). This value determines when the sentiment table displays the "Overheated" label, signaling a potential peak in an uptrend.
Oversold Threshold: Level indicating market cooldown (default: 30). This value determines when the sentiment table displays the "Cooled" label, signaling a potential bottom in a downtrend.
Gradient Min (Green): Lower threshold for the green gradient (default: 20).
Gradient Yellow Threshold: Threshold for the yellow gradient (default: 35).
Gradient Orange Threshold: Threshold for the orange gradient (default: 60).
Gradient Max (Red): Upper threshold for the red gradient (default: 70).
Visualization (VISUALIZATION)
Signal Line Color: Color of the oscillator line (default: dark red, RGB(5, 0, 0)).
Show Reference Lines: Enables/disables the display of threshold lines (default: enabled).
Divergence Settings (DIVERGENCE SETTINGS)
Calculate Divergence: Enables/disables divergence detection (default: disabled).
Lookback Right: Number of candles back for pivot analysis (default: 5).
Lookback Left: Number of candles to the left for pivot analysis (default: 5).
Line Style (STYLE)
Custom Line 1, 2, 3 Value: Levels for custom horizontal lines (default: 70, 50, 30).
Custom Line 1, 2, 3 Color: Colors for custom lines (default: black, RGB(0, 0, 0)).
Custom Line 1, 2, 3 Style: Line styles (solid, dotted, dashed; default: dashed, dotted, dashed).
How to Use the Indicator
Adding to the Chart
Add the indicator to your TradingView chart by searching for "Overheat Oscillator with Divergence."
Configure the settings according to your trading strategy.
Signal Interpretation
Overheated: Values above the Overheat Threshold (default: 70) in the sentiment table may indicate a potential uptrend peak.
Cooled: Values below the Oversold Threshold (default: 30) in the sentiment table may suggest a potential downtrend bottom.
Divergences:
Bullish: Look for "Bull" labels on the chart, indicating potential upward reversals (calculated with a Lookback Right delay).
Bearish: Look for "Bear" labels, indicating potential downward reversals (calculated with a Lookback Right delay).
Customization
Experiment with settings such as period length, volume multiplier, or gradient thresholds to tailor the indicator to your trading style (e.g., scalping, medium-term trading).
Usage Examples
Scalping: Set a shorter period (e.g., Period Length = 10, SMA Length = 3) and monitor rapid sentiment changes and divergences on lower timeframes (e.g., 5-minute charts).
Medium-Term Trading: Use default settings or increase Period Length (e.g., 30) and SMA Length (e.g., 7) for more stable signals on hourly or daily charts.
Reversal Detection: Enable divergence detection and observe "Bull" or "Bear" labels in conjunction with overheat/cooled levels in the sentiment table.
Notes
The indicator performs best when used in conjunction with other technical analysis tools, such as support/resistance lines, moving averages, or Fibonacci levels.
Divergences may serve as early signals but do not always guarantee immediate trend reversals—confirmation with other indicators is recommended.
Test different settings on historical data to find the optimal configuration for your chosen market and timeframe.
Sentiment
Advanced Correlation Monitor📊 Advanced Correlation Monitor - Pine Script v6
🎯 What does this indicator do?
Monitors real-time correlations between 13 different asset pairs and alerts you when historically strong correlations break, indicating potential trading opportunities or changes in market dynamics.
🚀 Key Features
✨ Multi-Market Monitoring
7 Forex Pairs (GBPUSD/DXY, EURUSD/GBPUSD, etc.)
6 Index/Stock Pairs (SPY/S&P500, DAX/NASDAQ, TSLA/NVDA, etc.)
Fully configurable - change any pair from inputs
📈 Dual Correlation Analysis
Long Period (90 bars): Identifies historically strong correlations
Short Period (6 bars): Detects recent breakdowns
Pearson Correlation using Pine Script v6 native functions
🎨 Intuitive Visualization
Real-time table with 6 information columns
Color coding: Green (correlated), Red (broken), Gray (normal)
Visual states: 🟢 OK, 🔴 BROKEN, ⚫ NORMAL
🚨 Smart Alert System
Only alerts previously correlated pairs (>80% historical)
Detects breakdowns when short correlation <80%
Consolidated alert with all affected pairs
🛠️ Flexible Configuration
Adjustable Parameters:
📅 Periods: Long (30-500), Short (2-50)
🎯 Threshold: 50%-99% (default 80%)
🎨 Table: Configurable position and size
📊 Symbols: All pairs are configurable
Default Pairs:
FOREX: INDICES/STOCKS:
- GBPUSD vs DXY • SPY vs S&P500
- EURUSD vs GBPUSD • DAX vs S&P500
- EURUSD vs DXY • DAX vs NASDAQ
- USDCHF vs DXY • TSLA vs NVDA
- GBPUSD vs USDCHF • MSFT vs NVDA
- EURUSD vs USDCHF • AAPL vs NVDA
- EURUSD vs EURCAD
💡 Practical Use Cases
🔄 Pairs Trading
Detects when strong correlations break for:
Statistical arbitrage
Mean reversion trading
Divergence opportunities
🛡️ Risk Management
Identifies when "safe" assets start moving independently:
Portfolio diversification
Smart hedging
Regime change detection
📊 Market Analysis
Understand underlying market structure:
Forex/DXY correlations
Tech sector rotation
Regional market disconnection
🎓 Results Interpretation
Reading Example:
EURUSD vs DXY: -98.57% → -98.27% | 🟢 OK
└─ Perfect negative correlation maintained (EUR rises when DXY falls)
TSLA vs NVDA: 78.12% → 0% | ⚫ NORMAL
└─ Lost tech correlation (divergence opportunity)
Trading Signals:
🟢 → 🔴: Broken correlation = Possible opportunity
Large difference: Indicates correlation tension
Multiple breaks: Market regime change
Midnight Open Line (Auto)This script plots the Midnight Open Line on the chart automatically based on GMT 00:00 Open.
Helps in setting daily bias according to ICT concepts.
Works on Forex, Indices & Crypto.
RSI CONPECTThis is an indicator measuring relative strength. I added the price on the RSI at the HT and KC zones, where RSI 60 is Resistance and 40 is Support. You should watch those price zones for buying and selling signals with a reversal. I also added a warning function when the RSI and EMA9 WMA45 cross each other, creating a buy or sell pattern.
Clarix Trend Filter Purpose
This indicator helps traders quickly identify strong bullish or bearish market conditions by combining a moving average and directional strength.
How It Works
SMMA (200): Smooths price to detect overall trend direction.
ADX (14): Measures trend strength, filtering out weak/noisy moves.
+DI / -DI: Directional movement indicators help confirm the dominant side.
Trend Logic
Bullish Trend: Price is above SMMA, ADX > threshold, and +DI > -DI
Bearish Trend: Price is below SMMA, ADX > threshold, and -DI > +DI
Otherwise, the trend is considered weak or unclear.
Features
Background shading for trend clarity
Optional buy/sell arrows based on trend confirmation
Configurable SMMA length and ADX threshold
Designed for 1-minute timeframes, but can be adjusted
Tips
Best used as a trend filter with your existing entry/exit strategy
Avoid trading signals when ADX is low (flat or ranging conditions)
Works well when combined with volume or momentum indicators
Fibonacci Optimal Entry Zone By Jazzman# Fibonacci Optimal Entry Zone - Multi-Timeframe Trading System
## Overview
This comprehensive trading indicator combines market structure analysis, Fibonacci retracements, multi-timeframe trend confirmation, and visual enhancements to provide traders with optimal entry and exit zones. The script intelligently adapts to both bullish and bearish market conditions, automatically drawing Fibonacci levels based on confirmed market structure breaks.
## Key Features & Originality
### 1. Intelligent Market Structure Detection
- **Adaptive Pivot Detection**: Uses configurable pivot periods to identify significant swing highs and lows
- **Break of Structure (BoS) Identification**: Automatically detects and marks Change of Character (CHoCH) points
- **Direction-Aware Analysis**: Distinguishes between bullish (Higher Highs/Higher Lows) and bearish (Lower Highs/Lower Lows) structures
- **Customizable Structure Visualization**: Multiple line styles (solid, dotted, dashed) with adjustable width and colors
### 2. Dynamic Fibonacci Retracement System
- **Comprehensive Level Set**: Includes 15 Fibonacci levels from -2.0 to 1.618, covering both retracement and extension zones
- **Real-Time Updates**: Fibonacci levels automatically adjust as new market structure forms
- **Swing Tracker Mode**: Option to follow the most recent swing or maintain levels from initial structure break
- **Smart Direction Calculation**: Correctly calculates retracements whether moving from high-to-low or low-to-high
### 3. Multi-Timeframe Trend Confirmation (MTF)
**This is a significant original addition that combines four technical indicators across four timeframes:**
#### Technical Indicators Used:
- **Supertrend**: Trend-following indicator using ATR-based volatility bands
- **SMA20 & SMA8**: Moving average alignment for trend confirmation
- **RSI**: Momentum oscillator with overbought/oversold filtering (50-80 range)
#### Timeframe Analysis:
- **Daily (D)**: Primary trend direction
- **Weekly (W)**: Long-term trend context
- **4-Hour (4H)**: Intermediate trend
- **65-Minute (65M)**: Short-term trend alignment
#### Scoring Methodology:
- **Strict Mode**: All four conditions must align for bullish/bearish signal
- **Weighted Mode**: Assigns configurable weights to each timeframe and indicator
- **Threshold-Based Classification**: Configurable bullish/bearish thresholds with neutral zone
- **Visual Dashboard**: Color-coded table showing trend status across all timeframes
### 4. Advanced Visual Features
- **Golden Zone Highlighting**: Automatically fills optimal entry zones (typically 0.382-0.618 for bearish, 0.5-0.618 for bullish)
- **Swing Connection Lines**: Dotted lines connecting swing points with customizable thickness
- **Price Labels**: Display exact price values at swing highs/lows
- **Fibonacci Labels**: Show both percentage levels and corresponding price values
- **Historical Levels**: Option to maintain previous Fibonacci levels or clear them
### 5. Professional Watermark System
- **Market Information Display**: Symbol, timeframe, company name, sector/industry
- **Market Capitalization**: Automatically calculates and formats market cap (B/M/T notation)
- **ATR Volatility Indicator**: 14-period ATR with percentage and color-coded risk assessment
- **Flexible Positioning**: 9 position options with custom offset controls
## How the Components Work Together
### The Strategic Integration:
1. **Market Structure First**: The system begins by identifying confirmed breaks of structure using pivot analysis
2. **Fibonacci Overlay**: Once structure is confirmed, Fibonacci levels are automatically drawn from the relevant swing points
3. **MTF Confirmation**: Before taking trades at Fibonacci levels, the MTF system confirms trend alignment across multiple timeframes
4. **Risk Assessment**: The watermark's ATR display helps gauge current volatility for position sizing
### Trading Logic Flow:
```
Market Structure Break Detected → Fibonacci Levels Drawn → MTF Trend Check → Entry Decision
```
## Unique Algorithmic Approach
### Direction-Aware Fibonacci Calculation:
Unlike standard Fibonacci tools, this script intelligently determines whether to calculate from high-to-low or low-to-high based on the detected market structure direction:
```pine
fibb(v, h, l, ih, il) =>
if il < ih // Bearish: High to Low
diff = h - l
level = h - (diff * v)
else // Bullish: Low to High
diff = h - l
level = l + (diff * v)
```
### Multi-Timeframe Weighted Scoring:
The MTF system uses a sophisticated weighted average approach:
- Each timeframe receives a configurable weight (default: Daily 30%, Weekly 30%, 4H 20%, 65M 20%)
- Each technical indicator within a timeframe receives its own weight
- Final score determines trend classification (Bullish/Neutral/Bearish)
## Practical Applications
### For Swing Traders:
- Use Weekly/Daily MTF confirmation with 0.618-0.786 Fibonacci levels
- Focus on structure breaks on higher timeframes
- Utilize Golden Zone fills for optimal entry areas
### For Day Traders:
- Emphasize 4H/65M timeframes in MTF analysis
- Watch for 0.382-0.5 retracements in trending markets
- Use ATR indicator for stop-loss placement
### For Position Traders:
- Prioritize Weekly trend alignment
- Focus on major structure breaks with extended Fibonacci levels (1.272, 1.618)
- Monitor market cap and sector information for fundamental context
## Configuration Options
### Structure Settings:
- Pivot period (default: 10 bars)
- Color customization for bullish/bearish structures
- Line style and width options
### Fibonacci Settings:
- Enable/disable individual levels
- Custom level values and colors
- Fill options between adjacent levels
- Label positioning and formatting
### MTF Settings:
- Scoring mode selection (Strict vs Weighted)
- Individual timeframe and indicator weights
- Threshold adjustments for trend classification
- Visual customization options
### Display Options:
- Watermark positioning and styling
- Information display toggles
- ATR risk thresholds and color coding
## Technical Requirements
- **Pine Script Version**: v6
- **Chart Overlay**: Yes
- **Resource Usage**: Moderate (max 500 lines/labels)
- **Optimal Timeframe**: Works on all timeframes, MTF table visible on Daily
- **Market Compatibility**: All markets (stocks, forex, crypto, futures)
## Credits and Acknowledgments
This indicator builds upon fundamental technical analysis concepts:
- Fibonacci retracements (Leonardo Fibonacci)
- Market structure analysis (SMC methodology)
- Supertrend indicator (Olivier Seban)
- Multi-timeframe analysis principles
The implementation, algorithmic logic, MTF integration, and visual enhancements are original contributions that significantly extend beyond basic indicator combinations.
---
*Built by Jazzman - A comprehensive trading system designed for serious market analysis and optimal entry identification.*
Trend Sentiment with IntervalThis indicator filteres out the trend on the basis of statistical derivation of average price over the specified timeframe. On the settings page of this indicator, you will see drop down of Sentiment Timeframe. You can use this as per your own risk reward. For more confirmation, I recommend to use multiple instances of this indicator in multi time frames.
52SIGNAL RECIPE CME Gap Support & Resistance Detector═══ 52SIGNAL RECIPE CME Gap Support & Resistance Detector ═══
◆ Overview
The 52SIGNAL RECIPE CME Gap Support & Resistance Detector is an advanced technical indicator that automatically detects and visualizes all types of price gaps occurring in the CME Bitcoin futures market on trading charts. It captures not only gaps formed during weekend and holiday closures, but also those created during the daily 1-hour maintenance period on weekdays, and sudden price gaps resulting from economic indicator releases or news events.
The core value of this indicator lies beyond simply displaying gaps; it visualizes how these price discontinuities act as powerful support and resistance zones that influence future price movements. In real markets, these CME gaps have a high probability of either being "filled" or functioning as important reaction zones, providing traders with valuable entry and exit signals.
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◆ Key Features
• Comprehensive Gap Detection: Detects gaps in all market conditions
- Weekend/holiday closure gaps
- Weekday 1-hour maintenance period gaps
- Gaps from economic indicators/news events causing rapid price changes
• Intuitive Color Coding:
- Blue: When gaps act as support (price is above the gap)
- Red: When gaps act as resistance (price is below the gap)
- Gray: Filled gaps (price has completely passed through the gap area)
• Real-time Role Switching: Automatically changes colors as price moves above/below gaps, visualizing support↔resistance role transitions
• Status Tracking System: Automatically tracks whether gaps are "Filled" or "Unfilled"
• Dynamic Boxes: Clearly marks gap areas with boxes and dynamically changes colors based on price movement
• Precise Labeling: Accurately displays the price range of each gap to support trader decision-making
• Smart Filtering: Improved algorithm that solves consecutive gap detection issues for complete gap tracking
• Key Usage Points:
- Pay special attention when price approaches gap areas
- Color changes in gaps signal important market sentiment shifts
- Areas with multiple clustered gaps are particularly strong reaction zones
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◆ User Guide: Understanding Gap Roles Through Colors
■ Color System Interpretation
• Blue Gaps (Support Role):
▶ Meaning: Current price is above the gap, making the gap act as support
▶ Trading Application: Consider buying opportunities when price approaches blue gap areas
▶ Psychological Meaning: Buying pressure likely to increase at this price level
• Red Gaps (Resistance Role):
▶ Meaning: Current price is below the gap, making the gap act as resistance
▶ Trading Application: Consider selling opportunities when price approaches red gap areas
▶ Psychological Meaning: Selling pressure likely to increase at this price level
• Gray Gaps (Filled Gaps):
▶ Meaning: Price has completely passed through the gap area, filling the gap
▶ Reference Value: Still valuable as reference for past important reaction zones
▶ Trading Application: Used to confirm trend strength and identify key psychological levels
■ Understanding Color Transitions
• Blue → Red Transition:
▶ Meaning: Price has fallen below the gap, changing its role from support to resistance
▶ Market Interpretation: Breakdown of previous support strengthens bearish signals
▶ Trading Application: Consider potential further decline; check gap bottom as resistance during bounces
• Red → Blue Transition:
▶ Meaning: Price has risen above the gap, changing its role from resistance to support
▶ Market Interpretation: Breakout above previous resistance strengthens bullish signals
▶ Trading Application: Consider potential further rise; check gap top as support during pullbacks
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◆ Practical Application Guide
■ Basic Trading Scenarios
• Blue Gap Support Strategy:
▶ Entry Point: When price approaches the top of a blue gap and forms a bounce candle
▶ Stop Loss: Below the gap bottom (if price completely breaks down through the gap)
▶ Take Profit: Previous swing high or next resistance level above
▶ Probability Enhancers: Gap aligned with major moving averages, oversold RSI, strong bounce candle pattern
• Red Gap Resistance Strategy:
▶ Entry Point: When price approaches the bottom of a red gap and forms a rejection candle
▶ Stop Loss: Above the gap top (if price completely breaks up through the gap)
▶ Take Profit: Previous swing low or next support level below
▶ Probability Enhancers: Gap aligned with major moving averages, overbought RSI, strong rejection candle pattern
■ Advanced Pattern Applications
• Multiple Gap Cluster Identification:
▶ Several gaps in close price proximity form extremely powerful support/resistance zones
▶ Same-color gap clusters: Very strong single-direction reaction zones
▶ Mixed-color gap clusters: High volatility zones with bidirectional reactions expected
• Gap Sequence Analysis:
▶ Consecutive same-direction gaps: Strong trend confirmation signal
▶ Increasing gap size pattern: Trend acceleration signal
▶ Decreasing gap size pattern: Trend weakening signal
• News/Indicator Release Gap Utilization:
▶ Gaps formed immediately after economic indicators: Measure market shock intensity
▶ Gap color change observation: Track market reinterpretation of news
▶ Gap filling speed analysis: Evaluate news impact duration
• Key Attention Points:
▶ Pay special attention to the chart whenever price approaches gap areas
▶ Gap color changes signal important market sentiment shifts
▶ Areas with multiple concentrated gaps are likely to show strong price reactions
─────────────────────────────────────
◆ Technical Foundation
■ CME Gap Formation Principles
• Key Gap Formation Scenarios:
▶ Weekend Closures (Friday close → Monday open): Most common CME gap formation point
▶ Holiday Closures: Gaps occurring due to CME closures on US holidays
▶ Weekday 1-hour Maintenance: Gaps during daily CME maintenance period (16:00-17:00 CT)
▶ Major Economic Indicator Releases: Gaps from rapid price changes during US employment reports, FOMC decisions, CPI releases, etc.
▶ Significant News Events: Gaps from regulatory announcements, geopolitical events, market shocks, etc.
• Psychological Importance of Gaps:
▶ Zones where price formation did not occur, representing imbalance between buying/selling forces
▶ Gap areas have no actual trading, resulting in accumulated potential orders
▶ Reflect institutional investor positions and liquidity distribution in the CME futures market
■ Support/Resistance Mechanism
• Psychological Level Formation Mechanism:
▶ Unexecuted order accumulation in gap areas: Loss of ordering opportunity at those price levels
▶ Liquidity imbalance: No trading occurred in gap areas, creating liquidity voids
▶ Institutional activity: Institutional participants in CME futures markets pay attention to these gap areas
• Evidence of Support/Resistance Function:
▶ Statistical gap fill phenomenon: Most gaps eventually "fill" (price returns to gap area)
▶ Gap-based reactions: Increased frequency of price reactions (bounces/rejections) when reaching gap areas
▶ Market psychology impact: Influences traders' perceived value and fair price assessment
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◆ Advanced Configuration Options
■ Visualization Settings
• Show Gap Labels (Default: On)
▶ On: Displays price ranges of each gap numerically for precise support/resistance level identification
▶ Off: Hides labels for visual cleanliness
• Color Settings
▶ Filled Gap Color: Gray tones, shows gaps already traversed by price
▶ Unfilled Gap Color - Support: Blue, shows gaps currently acting as support
▶ Unfilled Gap Color - Resistance: Red, shows gaps currently acting as resistance
■ Data Management Settings
• Filled Gap Storage Limit (Default: 10)
▶ Sets maximum number of filled gaps to retain on chart
▶ Recommended settings: Short-term traders (5-8), Swing traders (8-12), Position traders (10-15)
• Maximum Gap Retention Period (Default: 12 months)
▶ Sets period after which old unfilled gaps are automatically removed
▶ Recommended settings: Short-term analysis (3-6 months), Medium-term analysis (6-12 months), Long-term analysis (12-24 months)
─────────────────────────────────────
◆ Synergy with Other Indicators
• Volume Profile: Greatly increased reaction probability when CME gaps align with Volume Profile value areas
• Fibonacci Retracements: Formation of powerful reaction zones when major Fibonacci levels coincide with gap areas
• Moving Averages: Areas where major moving averages overlap with CME gaps act as "composite support/resistance"
• Horizontal Support/Resistance: Very strong price reactions expected when historical key price levels align with CME gaps
• Market Sentiment Indicators (RSI/MACD): Assess reaction probability by checking oversold/overbought conditions when price approaches gap areas
─────────────────────────────────────
◆ Conclusion
The 52SIGNAL RECIPE CME Gap Support & Resistance Detector is not merely a gap display tool, but an advanced analytical tool that visualizes important support/resistance areas where price may strongly react, using intuitive color codes (blue=support, red=resistance). It detects all types of gaps without omission, whether from weekend and holiday closures, weekday 1-hour maintenance periods, important economic indicator releases, or market shock situations.
The core value of this indicator lies in clearly expressing through intuitive color coding that gaps are not simple price discontinuities, but psychological support/resistance areas that significantly influence future price action. Traders can instantly identify areas where blue gaps act as support and red gaps act as resistance, enabling quick and effective decision-making.
By referencing the color codes when price approaches gap areas to predict possible price reactions, and especially interpreting color transition moments (blue→red or red→blue) as signals of important market sentiment changes and integrating them into trading strategies, traders can capture higher-probability trading opportunities.
─────────────────────────────────────
※ Disclaimer: Like all trading tools, the CME Gap Detector should be used as a supplementary indicator and not relied upon alone for trading decisions. Past gap reaction patterns cannot guarantee the same behavior in the future. Always use appropriate risk management strategies.
═══ 52SIGNAL RECIPE CME Gap Support & Resistance Detector ═══
◆ 개요
52SIGNAL RECIPE CME Gap Support & Resistance Detector는 CME 비트코인 선물 시장에서 발생하는 모든 유형의 가격 갭(Gap)을 자동으로 감지하여 트레이딩 차트에 시각화하는 고급 기술적 지표입니다. 주말과 공휴일 휴장은 물론, 평일 1시간 휴장 시간, 그리고 중요 경제지표 발표나 뉴스 이벤트 시 발생하는 급격한 가격 갭까지 누락 없이 포착합니다.
이 인디케이터의 핵심 가치는 단순히 갭을 표시하는 것을 넘어, 이러한 가격 불연속성이 미래 가격 움직임에 영향을 미치는 강력한 지지(Support)와 저항(Resistance) 영역으로 작용한다는 원리를 시각화하는 데 있습니다. 실제 시장에서 이러한 CME 갭은 높은 확률로 미래에 "매꿔지거나" 중요한 반응 구간으로 기능하여 트레이더에게 귀중한 진입/퇴출 신호를 제공합니다.
─────────────────────────────────────
◆ 주요 특징
• 전방위 갭 감지: 모든 시장 조건에서 발생하는 갭을 감지
- 주말/공휴일 휴장 갭
- 평일 1시간 휴장 시간 갭
- 경제지표/뉴스 이벤트 시 급격한 가격 변동 갭
• 직관적 색상 구분:
- 파란색: 갭이 지지 역할을 할 때(가격이 갭 위에 있을 때)
- 빨간색: 갭이 저항 역할을 할 때(가격이 갭 아래에 있을 때)
- 회색: 이미 매꿔진 갭(가격이 갭 영역을 완전히 통과)
• 실시간 역할 전환: 가격이 갭 위/아래로 이동함에 따라 지지↔저항 역할 전환을 자동으로 색상 변경으로 시각화
• 상태 추적 시스템: 갭이 "매꿔짐(Filled)" 또는 "매꿔지지 않음(Unfilled)" 상태를 자동 추적
• 다이나믹 박스: 갭 영역을 명확한 박스로 표시하고 가격 움직임에 따라 동적으로 색상 변경
• 정밀 레이블링: 각 갭의 가격 범위를 정확히 표시하여 트레이더의 의사결정 지원
• 스마트 필터링: 연속적 갭 감지 문제를 해결하는 개선된 알고리즘으로 누락 없는 갭 추적
• 핵심 활용 포인트:
- 가격이 갭 영역에 접근할 때 특별히 주목하세요
- 갭 색상 변경 시점은 중요한 시장 심리 변화 신호입니다
- 여러 갭이 밀집된 영역은 특히 강한 반응이 예상되는 구간입니다
─────────────────────────────────────
◆ 사용 가이드: 색상으로 이해하는 갭 역할
■ 색상 시스템 해석법
• 파란색 갭 (지지 역할):
▶ 의미: 현재 가격이 갭 위에 있어 갭이 지지선으로 작용
▶ 트레이딩 응용: 가격이 파란색 갭 영역으로 하락 접근 시 매수 기회 고려
▶ 심리적 의미: 매수세력이 이 가격대에서 수요 증가 가능성
• 빨간색 갭 (저항 역할):
▶ 의미: 현재 가격이 갭 아래에 있어 갭이 저항선으로 작용
▶ 트레이딩 응용: 가격이 빨간색 갭 영역으로 상승 접근 시 매도 기회 고려
▶ 심리적 의미: 매도세력이 이 가격대에서 공급 증가 가능성
• 회색 갭 (매꿔진 갭):
▶ 의미: 가격이 갭 영역을 완전히 통과하여 갭이 매꿔진 상태
▶ 참조 가치: 과거 중요 반응 구간으로 여전히 참고 가치 있음
▶ 트레이딩 응용: 추세 강도 확인 및 주요 심리적 레벨 식별에 활용
■ 색상 전환 이해하기
• 파란색 → 빨간색 전환:
▶ 의미: 가격이 갭 아래로 하락하여 갭이 지지에서 저항으로 역할 변경
▶ 시장 해석: 이전 지지선 붕괴로 약세 신호 강화
▶ 트레이딩 응용: 추가 하락 가능성 고려, 반등 시 갭 하단 저항 확인
• 빨간색 → 파란색 전환:
▶ 의미: 가격이 갭 위로 상승하여 갭이 저항에서 지지로 역할 변경
▶ 시장 해석: 이전 저항선 돌파로 강세 신호 강화
▶ 트레이딩 응용: 추가 상승 가능성 고려, 조정 시 갭 상단 지지 확인
─────────────────────────────────────
◆ 실전 활용 가이드
■ 기본 트레이딩 시나리오
• 파란색 갭 지지 전략:
▶ 진입 시점: 가격이 파란색 갭 상단에 접근하여 반등 캔들 형성 시
▶ 손절 위치: 갭 하단 아래(갭 완전히 하향 돌파 시)
▶ 이익실현: 이전 스윙 고점 또는 상방 다음 저항선
▶ 확률 증가 조건: 갭과 주요 이동평균선 일치, 과매도 RSI, 강한 반등 캔들
• 빨간색 갭 저항 전략:
▶ 진입 시점: 가격이 빨간색 갭 하단에 접근하여 거부 캔들 형성 시
▶ 손절 위치: 갭 상단 위(갭 완전히 상향 돌파 시)
▶ 이익실현: 이전 스윙 저점 또는 하방 다음 지지선
▶ 확률 증가 조건: 갭과 주요 이동평균선 일치, 과매수 RSI, 강한 거부 캔들
■ 고급 패턴 활용법
• 다중 갭 클러스터 식별:
▶ 여러 갭이 근접한 가격대에 있다면 더욱 강력한 지지/저항 존
▶ 동일 색상 갭 클러스터: 매우 강력한 단일 방향 반응 구간
▶ 색상 혼합 갭 클러스터: 심한 변동성과 양방향 반응 예상 구간
• 갭 시퀀스 분석:
▶ 연속적인 동일 방향 갭: 강한 추세 확인 신호
▶ 갭 크기 증가 패턴: 추세 가속화 신호
▶ 갭 크기 감소 패턴: 추세 약화 신호
• 뉴스/지표 발표 후 갭 활용:
▶ 경제지표 발표 직후 형성된 갭: 시장 충격 강도 측정
▶ 갭 색상 변화 관찰: 시장의 뉴스 재해석 과정 파악
▶ 갭 매꿈 속도 분석: 뉴스 임팩트의 지속성 평가
• 핵심 주목 포인트:
▶ 가격이 갭 영역에 접근할 때마다 차트를 특별히 주목하세요
▶ 갭 색상이 변경되는 시점은 중요한 시장 심리 변화를 의미합니다
▶ 여러 갭이 밀집된 영역은 가격이 강하게 반응할 가능성이 높습니다
─────────────────────────────────────
◆ 기술적 기반
■ CME 갭의 발생 원리
• 주요 갭 발생 상황:
▶ 주말 휴장 (금요일 종가 → 월요일 시가): 가장 일반적인 CME 갭 형성 시점
▶ 공휴일 휴장: 미국 공휴일에 따른 CME 휴장 시 발생
▶ 평일 1시간 휴장: CME 시장의 일일 정비 시간(16:00~17:00 CT) 동안 발생
▶ 주요 경제지표 발표: 미 고용지표, FOMC 결정, CPI 등 발표 시 급격한 가격 변동으로 인한 갭
▶ 중요 뉴스 이벤트: 규제 발표, 지정학적 이벤트, 시장 충격 등으로 인한 급격한 가격 변화
• 갭의 심리적 중요성:
▶ 가격 형성이 이루어지지 않은 구간으로, 매수/매도 세력의 불균형 영역
▶ 갭 구간에는 실제 거래가 없었기 때문에 잠재적 주문이 누적되는 영역
▶ 기관 투자자들의 선물 포지션과 유동성 분포가 반영된 중요한 가격 레벨
■ 지지/저항으로 작용하는 원리
• 심리적 레벨 형성 메커니즘:
▶ 갭 구간의 미실행 주문 축적: 갭 발생 시 해당 가격대에 대한 주문 기회 상실
▶ 유동성 불균형: 갭 구간에는 거래가 없었으므로 유동성 공백 발생
▶ 기관 투자자 활동: CME 선물 시장의 기관 참여자들은 이러한 갭 영역에 관심
• 지지/저항 작용 증거:
▶ 통계적 갭 필 현상: 대부분의 갭은 미래에 "매꿔짐"(가격이 갭 구간으로 회귀)
▶ 갭 기반 반응: 갭 영역에 도달 시 가격 반응(반등/거부) 발생 빈도 증가
▶ 시장 심리 영향: 트레이더들의 인지된 가치와 공정가격 평가에 영향
─────────────────────────────────────
◆ 고급 설정 옵션
■ 시각화 설정
• 라벨 표시 설정 (Show Gap Labels) (기본값: 켜짐)
▶ 켜짐: 각 갭의 가격 범위를 숫자로 표시하여 정확한 지지/저항 레벨 확인
▶ 꺼짐: 시각적 깔끔함을 위해 라벨 숨김
• 색상 설정
▶ 매꿔진 갭 색상(Filled Gap Color): 회색 계열, 이미 가격이 통과한 갭 표시
▶ 미매꿔진 갭 색상 - 지지(Support): 파란색, 현재 지지 역할을 하는 갭
▶ 미매꿔진 갭 색상 - 저항(Resistance): 빨간색, 현재 저항 역할을 하는 갭
■ 데이터 관리 설정
• 매꿔진 갭 저장 한도 (Filled Gap Storage Limit) (기본값: 10)
▶ 이미 매꿔진 갭을 최대 몇 개까지 차트에 유지할지 설정
▶ 권장 설정: 단기 트레이더(5-8), 스윙 트레이더(8-12), 포지션 트레이더(10-15)
• 최대 갭 보관 기간 (Maximum Gap Retention Period) (기본값: 12개월)
▶ 오래된 미매꿔진 갭을 자동으로 제거하는 기간 설정
▶ 권장 설정: 단기 분석(3-6개월), 중기 분석(6-12개월), 장기 분석(12-24개월)
─────────────────────────────────────
◆ 다른 지표와의 시너지
• 볼륨 프로파일: CME 갭과 볼륨 프로파일의 밸류 영역 일치 시 반응 확률 크게 증가
• 피보나치 리트레이스먼트: 주요 피보나치 레벨과 갭 영역 일치 시 강력한 반응 존 형성
• 이동평균선: 주요 이동평균선과 CME 갭이 겹치는 영역은 "복합 지지/저항"으로 작용
• 수평 지지/저항: 과거 중요 가격대와 CME 갭 일치 시 매우 강력한 가격 반응 예상 가능
• 시장 심리 지표(RSI/MACD): 갭 영역 접근 시 과매수/과매도 확인으로 반응 가능성 판단
─────────────────────────────────────
◆ 결론
52SIGNAL RECIPE CME Gap Support & Resistance Detector는 단순한 갭 표시 도구가 아닌, 가격이 강하게 반응할 수 있는 중요한 지지/저항 영역을 직관적인 색상 코드(파란색=지지, 빨간색=저항)로 시각화하는 고급 분석 도구입니다. 주말과 공휴일 휴장 시간뿐만 아니라, 평일 1시간 휴장 시간, 중요 경제지표 발표, 그리고 시장 충격 상황에서 발생하는 모든 유형의 갭을 누락 없이 감지합니다.
인디케이터의 핵심 가치는 갭이 단순한 가격 불연속성이 아닌, 미래 가격 행동에 중요한 영향을 미치는 심리적 지지/저항 영역임을 직관적인 색상 코드로 명확히 표현하는 데 있습니다. 파란색 갭은 지지 역할을, 빨간색 갭은 저항 역할을 하는 영역을 즉각적으로 식별할 수 있어 트레이더가 빠르고 효과적인 의사결정을 내릴 수 있도록 도와줍니다.
갭 영역에 접근할 때마다 색상 코드를 참고하여 가능한 가격 반응을 예측하고, 특히 색상 전환이 일어나는 순간(파란색→빨간색 또는 빨간색→파란색)은 중요한 시장 심리 변화 신호로 해석하여 트레이딩 전략에 통합한다면, 더 높은 확률의 거래 기회를 포착할 수 있을 것입니다.
─────────────────────────────────────
※ 면책 조항: 모든 트레이딩 도구와 마찬가지로, CME Gap Detector는 보조 지표로 사용되어야 하며 단독으로 거래 결정을 내리는 데 사용해서는 안 됩니다. 과거의 갭 반응 패턴이 미래에도 동일하게 작용한다고 보장할 수 없습니다. 항상 적절한 리스크 관리 전략을 사용하세요.
🚀 QuantSignals AI Trend Pro 15M🚀 QuantSignals AI Trend Pro 15M
Welcome to QuantSignals AI Trend Pro, the ultimate AI-powered trend and signal system designed for serious day traders and scalpers.
🔒 This is a closed-source invite-only script. Only approved users may access this strategy.
🔍 What is it?
QuantSignals AI Trend Pro uses proprietary machine learning logic and smart signal filters to detect high-probability entries and exits on the 15-minute timeframe.
Designed by real traders, backed by data science, and battle-tested across crypto, forex, and equities.
💡 Key Features
🎯 AI-Powered Signal Engine
Smart buy/sell logic filtered by momentum, volatility, and multi-timeframe confluence.
📈 Smart Trend Strength System
Auto-classifies market into 🚀 Strong Bull, ⚖️ Neutral, or 🔥 Strong Bear zones.
🧠 Visual Dashboard Overlay
Real-time scoreboards for trend status, signal quality, momentum, and volatility.
🎯 Smart Support & Resistance Zones
Auto-calculated pivot levels based on dynamic market structure.
🔔 Built-In Alerts
Get real-time signals directly to your device — ready for TradingView alert automation.
✅ Optimized For:
🕒 15-minute timeframe
🔁 Scalping & Day Trading
💹 Crypto / Stocks / Forex / Futures
💎 How to Get Access?
This is a limited free version of our full QuantSignals system.
To unlock:
🔓 Full algorithm (multi-timeframe + sentiment + volume)
🔔 Real-time signals + smart alerts
📘 Educational content & live strategy sessions
➕ Join our community and request access:
🌐 Website: quantsignals.xyz
💬 Discord: discord.gg
🧠 Who is this for?
Active day traders and scalpers
Traders seeking institutional-grade tools
Anyone tired of fake signal groups and repainting indicators
📉 Disclaimer
This script is for educational and informational purposes only.
Trading carries risk. Use with proper risk management.
📊 52-Week Price % Distance (Advanced Table)This TradingView Pine Script displays a compact, informative table showing how far the current price is from the 52-week high and low, expressed as percentages.
Session Volatility Dashboard█ Session Volatility Dashboard: HOW IT WORKS
This tool is built on transparent, statistically-grounded principles to ensure reliability and build user trust.
Session Logic: The script accurately identifies session periods based on user-defined start and end times in conjunction with the selected UTC offset. This ensures the session boxes and data are correctly aligned regardless of your local timezone or daylight saving changes.
Volatility Calculation: The core of the volatility engine is a comparison of current and historical price action. The script calculates a rolling Average True Range (ATR) over a user-defined lookback period (e.g., the last 20 sessions). It then compares the current session's ATR to this historical baseline to generate a simple percentage. For example, a reading of "135%" indicates the current session is 35% more volatile than the recent average, while "80%" indicates a contraction in volatility.
Dashboard Population : The script leverages TradingView's table object to construct the dashboard. This powerful feature allows the data to be displayed in a fixed position on the screen (e.g., top-right corner). Unlike plotted text, this table does not scroll with the chart's price history, ensuring that the most critical, up-to-date information is always available at a glance.
█ ACTIONABLE INTELLIGENCE: TRADING STRATEGIES & USE CASES
Translate data into action with these practical trading concepts.
Strategy 1: The Breakout Trade: Identify a session with low, coiling volatility (e.g., a Volatility reading below 75%)—often the Asian session. Mark the session high and low plotted by the indicator. These levels become prime targets for a potential breakout trade during the high-volume, high-volatility open of the subsequent London session.
Strategy 2 : The Mean Reversion (Fade) Trade: In a session with extremely high volatility (e.g., >150% of average), watch for price to rapidly extend to a new session high or low and then print a clear reversal candlestick pattern (like a pin bar or engulfing candle). This can signal momentum exhaustion and a high-probability opportunity to "fade" the move back toward the session midpoint.
Strategy 3 : The Trend Continuation: During a clear trending day, use the session midpoint as a dynamic area of value. Look for price to pull back to the midpoint during the London or New York session. If the session's Bias in the dashboard remains aligned with the higher-timeframe trend, this can present a quality entry to rejoin the established momentum.
█ COMPLETE CUSTOMIZATION: SETTINGS
Session Times: Independently set the start and end times for Asia, London, and New York sessions.
Timezone: Select your preferred UTC offset to align all sessions correctly.
Volatility Lookback: Define the number of past sessions to use for calculating the average volatility baseline (default is 20).
Dashboard Settings: Choose the on-screen position of the table, text size, and colors.
Visual Elements: Toggle on/off session background colors, high/low lines, and midpoint lines. Customize all colors.
Alerts: Enable/disable and customize alerts for session high/low breaks and volatility threshold crossings.
Top Crypto Above 28-Day AverageDescription
The “Top Crypto Above 28-Day Average” (CRYPTOTW) script scans a selectable universe of up to 120 top-capitalization cryptocurrencies (divided into customizable 40-symbol batches), then plots the count of those trading above their own 28-period simple moving average. It helps you gauge broad market strength and identify which tokens are showing momentum relative to their recent trend.
Key Features
• Batch Selection: Choose among “Top40,” “Mid40,” or “Low40” market-cap groups, or set a custom batch size (up to 40 symbols) to keep within the API limit.
• Dynamic Plot: Displays a live line chart of how many cryptos are above their 28-day MA on each bar.
• Reference Lines: Automatic horizontal lines at 25%, 50%, and 75% of your batch to provide quick visual thresholds.
• Background Coloration: The chart background shifts green/yellow/red based on whether more than 70%, 50–70%, or under 50% of the batch is above the MA.
• Optional Table: On the final bar, show a sortable table of up to 28 tickers currently above their 28-day MA, including current price, percent above MA, and “Above” status color-coding.
• Alerts:
• Strong Batch Performance: Fires when >70% of the batch is above the MA.
• Weak Batch Performance: Fires when <10 cryptos (i.e. <25%) are above the MA.
Inputs
• Show Results Table (show_table): Toggle the detailed table on/off.
• Table Position (table_position): Select one of the four corners for your table overlay.
• Max Cryptos to Display (max_display): Limit the number of rows in the results table.
• Current Batch (current_batch): Pick “Top40,” “Mid40,” or “Low40.”
• Batch Size (batch_size): Define the number of symbols (1–40) you want to include from the chosen batch.
How to Use
1. Add the CRYPTOTW indicator to any chart.
2. Select your batch and size to focus on the segment of the crypto market you follow.
3. Watch the plotted line to see the proportion of tokens with bullish momentum.
4. (Optional) Enable the results table to see exactly which tokens are outperforming their 28-day average.
5. Set alerts to be notified when the batch either overheats (strong performance) or cools off significantly.
Why It Matters
By tracking the share of assets riding their 28-day trend, you gain a macro-level view of market breadth—crucial for spotting emerging rallies or early signs of broad weakness. Whether you’re swing-trading individual altcoins or assessing overall market mood, this tool distills complex data into an intuitive, actionable signal.
SNIPERKILLS NQ JULY 18 2025, GAMEPLANNQ GAME PLAN JULY 18, 2025!
✅ Bullish Scenario
Condition: Price breaks and holds above 23,279.75
Targets:
🎯 Target 1: 23,320 — minor imbalance / reaction zone
🎯 Target 2: 23,375 — potential liquidity sweep
🎯 Target 3: 23,420 — psychological level / extended move
Stop Loss: Below 23,234.25 (Short Trigger / invalidation)
❌ Bearish Scenario
Condition: Price breaks and holds below 23,234.25
Targets:
🎯 Target 1: 23,200 — FVG or intraday demand
🎯 Target 2: 23,150 — mid-range flush target
🎯 Target 3: 23,017 — prior day’s low & major liquidity zone
Stop Loss: Above 23,279.75 (Long Trigger / invalidation)
Diamond Peaks [EdgeTerminal]The Diamond Peaks indicator is a comprehensive technical analysis tool that uses a few mathematical models to identify high-probability trading opportunities. This indicator goes beyond traditional support and resistance identification by incorporating volume analysis, momentum divergences, advanced price action patterns, and market sentiment indicators to generate premium-quality buy and sell signals.
Dynamic Support/Resistance Calculation
The indicator employs an adaptive algorithm that calculates support and resistance levels using a volatility-adjusted lookback period. The base calculation uses ta.highest(length) and ta.lowest(length) functions, where the length parameter is dynamically adjusted using the formula: adjusted_length = base_length * (1 + (volatility_ratio - 1) * volatility_factor). The volatility ratio is computed as current_ATR / average_ATR over a 50-period window, ensuring the lookback period expands during volatile conditions and contracts during calm periods. This mathematical approach prevents the indicator from using fixed periods that may become irrelevant during different market regimes.
Momentum Divergence Detection Algorithm
The divergence detection system uses a mathematical comparison between price series and oscillator values over a specified lookback period. For bullish divergences, the algorithm identifies when recent_low < previous_low while simultaneously indicator_at_recent_low > indicator_at_previous_low. The inverse logic applies to bearish divergences. The system tracks both RSI (calculated using Pine Script's standard ta.rsi() function with Wilder's smoothing) and MACD (using ta.macd() with exponential moving averages). The mathematical rigor ensures that divergences are only flagged when there's a clear mathematical relationship between price momentum and the underlying oscillator momentum, eliminating false signals from minor price fluctuations.
Volume Analysis Mathematical Framework
The volume analysis component uses multiple mathematical transformations to assess market participation. The Cumulative Volume Delta (CVD) is calculated as ∑(buying_volume - selling_volume) where buying_volume occurs when close > open and selling_volume when close < open. The relative volume calculation uses current_volume / ta.sma(volume, period) to normalize current activity against historical averages. Volume Rate of Change employs ta.roc(volume, period) = (current_volume - volume ) / volume * 100 to measure volume acceleration. Large trade detection uses a threshold multiplier against the volume moving average, mathematically identifying institutional activity when relative_volume > threshold_multiplier.
Advanced Price Action Mathematics
The Wyckoff analysis component uses mathematical volume climax detection by comparing current volume against ta.highest(volume, 50) * 0.8, while price compression is measured using (high - low) < ta.atr(20) * 0.5. Liquidity sweep detection employs percentage-based calculations: bullish sweeps occur when low < recent_low * (1 - threshold_percentage/100) followed by close > recent_low. Supply and demand zones are mathematically validated by tracking subsequent price action over a defined period, with zone strength calculated as the count of bars where price respects the zone boundaries. Fair value gaps are identified using ATR-based thresholds: gap_size > ta.atr(14) * 0.5.
Sentiment and Market Regime Mathematics
The sentiment analysis employs a multi-factor mathematical model. The fear/greed index uses volatility normalization: 100 - min(100, stdev(price_changes, period) * scaling_factor). Market regime classification uses EMA crossover mathematics with additional ADX-based trend strength validation. The trend strength calculation implements a modified ADX algorithm: DX = |+DI - -DI| / (+DI + -DI) * 100, then ADX = RMA(DX, period). Bull regime requires short_EMA > long_EMA AND ADX > 25 AND +DI > -DI. The mathematical framework ensures objective regime classification without subjective interpretation.
Confluence Scoring Mathematical Model
The confluence scoring system uses a weighted linear combination: Score = (divergence_component * 0.25) + (volume_component * 0.25) + (price_action_component * 0.25) + (sentiment_component * 0.25) + contextual_bonuses. Each component is normalized to a 0-100 scale using percentile rankings and threshold comparisons. The mathematical model ensures that no single component can dominate the score, while contextual bonuses (regime alignment, volume confirmation, etc.) provide additional mathematical weight when multiple factors align. The final score is bounded using math.min(100, math.max(0, calculated_score)) to maintain mathematical consistency.
Vitality Field Mathematical Implementation
The vitality field uses a multi-factor scoring algorithm that combines trend direction (EMA crossover: trend_score = fast_EMA > slow_EMA ? 1 : -1), momentum (RSI-based: momentum_score = RSI > 50 ? 1 : -1), MACD position (macd_score = MACD_line > 0 ? 1 : -1), and volume confirmation. The final vitality score uses weighted mathematics: vitality_score = (trend * 0.4) + (momentum * 0.3) + (macd * 0.2) + (volume * 0.1). The field boundaries are calculated using ATR-based dynamic ranges: upper_boundary = price_center + (ATR * user_defined_multiplier), with EMA smoothing applied to prevent erratic boundary movements. The gradient effect uses mathematical transparency interpolation across multiple zones.
Signal Generation Mathematical Logic
The signal generation employs boolean algebra with multiple mathematical conditions that must simultaneously evaluate to true. Buy signals require: (confluence_score ≥ threshold) AND (divergence_detected = true) AND (relative_volume > 1.5) AND (volume_ROC > 25%) AND (RSI < 35) AND (trend_strength > minimum_ADX) AND (regime = bullish) AND (cooldown_expired = true) AND (last_signal ≠ buy). The mathematical precision ensures that signals only generate when all quantitative conditions are met, eliminating subjective interpretation. The cooldown mechanism uses bar counting mathematics: bars_since_last_signal = current_bar_index - last_signal_bar_index ≥ cooldown_period. This mathematical framework provides objective, repeatable signal generation that can be backtested and validated statistically.
This mathematical foundation ensures the indicator operates on objective, quantifiable principles rather than subjective interpretation, making it suitable for algorithmic trading and systematic analysis while maintaining transparency in its computational methodology.
* for now, we're planning to keep the source code private as we try to improve the models used here and allow a small group to test them. My goal is to eventually use the multiple models in this indicator as their own free and open source indicators. If you'd like to use this indicator, please send me a message to get access.
Advanced Confluence Scoring System
Each support and resistance level receives a comprehensive confluence score (0-100) based on four weighted components:
Momentum Divergences (25% weight)
RSI and MACD divergence detection
Identifies momentum shifts before price reversals
Bullish/bearish divergence confirmation
Volume Analysis (25% weight)
Cumulative Volume Delta (CVD) analysis
Volume Rate of Change monitoring
Large trade detection (institutional activity)
Volume profile strength assessment
Advanced Price Action (25% weight)
Supply and demand zone identification
Liquidity sweep detection (stop hunts)
Wyckoff accumulation/distribution patterns
Fair value gap analysis
Market Sentiment (25% weight)
Fear/Greed index calculation
Market regime classification (Bull/Bear/Sideways)
Trend strength measurement (ADX-like)
Momentum regime alignment
Dynamic Support and Resistance Detection
The indicator uses an adaptive algorithm to identify significant support and resistance levels based on recent market highs and lows. Unlike static levels, these zones adjust dynamically to market volatility using the Average True Range (ATR), ensuring the levels remain relevant across different market conditions.
Vitality Field Background
The indicator features a unique vitality field that provides instant visual feedback about market sentiment:
Green zones: Bullish market conditions with strong momentum
Red zones: Bearish market conditions with weak momentum
Gray zones: Neutral/sideways market conditions
The vitality field uses a sophisticated gradient system that fades from the center outward, creating a clean, professional appearance that doesn't overwhelm the chart while providing valuable context.
Buy Signals (🚀 BUY)
Buy signals are generated when ALL of the following conditions are met:
Valid support level with confluence score ≥ 80
Bullish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bull market regime environment
RSI below 35 (oversold conditions)
Price action confirmation (Wyckoff accumulation, liquidity sweep, or large buying volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive buy signals)
Cooldown period expired (default 10 bars)
Sell Signals (🔻 SELL)
Sell signals are generated when ALL of the following conditions are met:
Valid resistance level with confluence score ≥ 80
Bearish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bear market regime environment
RSI above 65 (overbought conditions)
Price action confirmation (Wyckoff distribution, liquidity sweep, or large selling volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive sell signals)
Cooldown period expired (default 10 bars)
How to Use the Indicator
1. Signal Quality Assessment
Monitor the confluence scores in the information table:
Score 90-100: Exceptional quality levels (A+ grade)
Score 80-89: High quality levels (A grade)
Score 70-79: Good quality levels (B grade)
Score below 70: Weak levels (filtered out by default)
2. Market Context Analysis
Use the vitality field and market regime information to understand the broader market context:
Trade buy signals in green vitality zones during bull regimes
Trade sell signals in red vitality zones during bear regimes
Exercise caution in gray zones (sideways markets)
3. Entry and Exit Strategy
For Buy Signals:
Enter long positions when premium buy signals appear
Place stop loss below the support confluence zone
Target the next resistance level or use a risk/reward ratio of 2:1 or higher
For Sell Signals:
Enter short positions when premium sell signals appear
Place stop loss above the resistance confluence zone
Target the next support level or use a risk/reward ratio of 2:1 or higher
4. Risk Management
Only trade signals with confluence scores above 80
Respect the signal alternation system (no overtrading)
Use appropriate position sizing based on signal quality
Consider the overall market regime before taking trades
Customizable Settings
Signal Generation Controls
Signal Filtering: Enable/disable advanced filtering
Confluence Threshold: Adjust minimum score requirement (70-95)
Cooldown Period: Set bars between signals (5-50)
Volume/Momentum Requirements: Toggle confirmation requirements
Trend Strength: Minimum ADX requirement (15-40)
Vitality Field Options
Enable/Disable: Control background field display
Transparency Settings: Adjust opacity for center and edges
Field Size: Control the field boundaries (3.0-20.0)
Color Customization: Set custom colors for bullish/bearish/neutral states
Weight Adjustments
Divergence Weight: Adjust momentum component influence (10-40%)
Volume Weight: Adjust volume component influence (10-40%)
Price Action Weight: Adjust price action component influence (10-40%)
Sentiment Weight: Adjust sentiment component influence (10-40%)
Best Practices
Always wait for complete signal confirmation before entering trades
Use higher timeframes for signal validation and context
Combine with proper risk management and position sizing
Monitor the information table for real-time market analysis
Pay attention to volume confirmation for higher probability trades
Respect market regime alignment for optimal results
Basic Settings
Base Length (Default: 25)
Controls the lookback period for identifying support and resistance levels
Range: 5-100 bars
Lower values = More responsive, shorter-term levels
Higher values = More stable, longer-term levels
Recommendation: 25 for intraday, 50 for swing trading
Enable Adaptive Length (Default: True)
Automatically adjusts the base length based on market volatility
When enabled, length increases in volatile markets and decreases in calm markets
Helps maintain relevant levels across different market conditions
Volatility Factor (Default: 1.5)
Controls how much the adaptive length responds to volatility changes
Range: 0.5-3.0
Higher values = More aggressive length adjustments
Lower values = More conservative length adjustments
Volume Profile Settings
VWAP Length (Default: 200)
Sets the calculation period for the Volume Weighted Average Price
Range: 50-500 bars
Shorter periods = More responsive to recent price action
Longer periods = More stable reference line
Used for volume profile analysis and confluence scoring
Volume MA Length (Default: 50)
Period for calculating the volume moving average baseline
Range: 10-200 bars
Used to determine relative volume (current volume vs. average)
Shorter periods = More sensitive to volume changes
Longer periods = More stable volume baseline
High Volume Node Threshold (Default: 1.5)
Multiplier for identifying significant volume spikes
Range: 1.0-3.0
Values above this threshold mark high-volume nodes with diamond shapes
Lower values = More frequent high-volume signals
Higher values = Only extreme volume events marked
Momentum Divergence Settings
Enable Divergence Detection (Default: True)
Master switch for momentum divergence analysis
When disabled, removes divergence from confluence scoring
Significantly impacts signal generation quality
RSI Length (Default: 14)
Period for RSI calculation used in divergence detection
Range: 5-50
Standard RSI settings apply (14 is most common)
Shorter periods = More sensitive, more signals
Longer periods = Smoother, fewer but more reliable signals
MACD Settings
Fast (Default: 12): Fast EMA period for MACD calculation (5-50)
Slow (Default: 26): Slow EMA period for MACD calculation (10-100)
Signal (Default: 9): Signal line EMA period (3-20)
Standard MACD settings for divergence detection
Divergence Lookback (Default: 5)
Number of bars to look back when detecting divergences
Range: 3-20
Shorter periods = More frequent divergence signals
Longer periods = More significant divergence signals
Volume Analysis Enhancement Settings
Enable Advanced Volume Analysis (Default: True)
Master control for sophisticated volume calculations
Includes CVD, volume ROC, and large trade detection
Critical for signal accuracy
Cumulative Volume Delta Length (Default: 20)
Period for CVD smoothing calculation
Range: 10-100
Tracks buying vs. selling pressure over time
Shorter periods = More reactive to recent flows
Longer periods = Broader trend perspective
Volume ROC Length (Default: 10)
Period for Volume Rate of Change calculation
Range: 5-50
Measures volume acceleration/deceleration
Key component in volume confirmation requirements
Large Trade Volume Threshold (Default: 2.0)
Multiplier for identifying institutional-size trades
Range: 1.5-5.0
Trades above this threshold marked as large trades
Lower values = More frequent large trade signals
Higher values = Only extreme institutional activity
Advanced Price Action Settings
Enable Wyckoff Analysis (Default: True)
Activates simplified Wyckoff accumulation/distribution detection
Identifies potential smart money positioning
Important for high-quality signal generation
Enable Supply/Demand Zones (Default: True)
Identifies fresh supply and demand zones
Tracks zone strength based on subsequent price action
Enhances confluence scoring accuracy
Enable Liquidity Analysis (Default: True)
Detects liquidity sweeps and stop hunts
Identifies fake breakouts vs. genuine moves
Critical for avoiding false signals
Zone Strength Period (Default: 20)
Bars used to assess supply/demand zone strength
Range: 10-50
Longer periods = More thorough zone validation
Shorter periods = Faster zone assessment
Liquidity Sweep Threshold (Default: 0.5%)
Percentage move required to confirm liquidity sweep
Range: 0.1-2.0%
Lower values = More sensitive sweep detection
Higher values = Only significant sweeps detected
Sentiment and Flow Settings
Enable Sentiment Analysis (Default: True)
Master control for market sentiment calculations
Includes fear/greed index and regime classification
Important for market context assessment
Fear/Greed Period (Default: 20)
Calculation period for market sentiment indicator
Range: 10-50
Based on price volatility and momentum
Shorter periods = More reactive sentiment readings
Momentum Regime Length (Default: 50)
Period for determining overall market regime
Range: 20-100
Classifies market as Bull/Bear/Sideways
Longer periods = More stable regime classification
Trend Strength Length (Default: 30)
Period for ADX-like trend strength calculation
Range: 10-100
Measures directional momentum intensity
Used in signal filtering requirements
Advanced Signal Generation Settings
Enable Signal Filtering (Default: True)
Master control for premium signal generation system
When disabled, uses basic signal conditions
Highly recommended to keep enabled
Minimum Signal Confluence Score (Default: 80)
Required confluence score for signal generation
Range: 70-95
Higher values = Fewer but higher quality signals
Lower values = More frequent but potentially lower quality signals
Signal Cooldown (Default: 10 bars)
Minimum bars between signals of same type
Range: 5-50
Prevents signal spam and overtrading
Higher values = More conservative signal spacing
Require Volume Confirmation (Default: True)
Mandates volume requirements for signal generation
Requires 1.5x average volume + 25% volume ROC
Critical for signal quality
Require Momentum Confirmation (Default: True)
Mandates divergence detection for signals
Ensures momentum backing for directional moves
Essential for high-probability setups
Minimum Trend Strength (Default: 25)
Required ADX level for signal generation
Range: 15-40
Ensures signals occur in trending markets
Higher values = Only strong trending conditions
Confluence Scoring Settings
Minimum Confluence Score (Default: 70)
Threshold for displaying support/resistance levels
Range: 50-90
Levels below this score are filtered out
Higher values = Only strongest levels shown
Component Weights (Default: 25% each)
Divergence Weight: Momentum component influence (10-40%)
Volume Weight: Volume analysis influence (10-40%)
Price Action Weight: Price patterns influence (10-40%)
Sentiment Weight: Market sentiment influence (10-40%)
Must total 100% for balanced scoring
Vitality Field Settings
Enable Vitality Field (Default: True)
Controls the background gradient field display
Provides instant visual market sentiment feedback
Enhances chart readability and context
Vitality Center Transparency (Default: 85%)
Opacity at the center of the vitality field
Range: 70-95%
Lower values = More opaque center
Higher values = More transparent center
Vitality Edge Transparency (Default: 98%)
Opacity at the edges of the vitality field
Range: 95-99%
Creates smooth fade effect from center to edges
Higher values = More subtle edge appearance
Vitality Field Size (Default: 8.0)
Controls the overall size of the vitality field
Range: 3.0-20.0
Based on ATR multiples for dynamic sizing
Lower values = Tighter field around price
Higher values = Broader field coverage
Recommended Settings by Trading Style
Scalping (1-5 minutes)
Base Length: 15
Volume MA Length: 20
Signal Cooldown: 5 bars
Vitality Field Size: 5.0
Higher sensitivity for quick moves
Day Trading (15-60 minutes)
Base Length: 25 (default)
Volume MA Length: 50 (default)
Signal Cooldown: 10 bars (default)
Vitality Field Size: 8.0 (default)
Balanced settings for intraday moves
Swing Trading (4H-Daily)
Base Length: 50
Volume MA Length: 100
Signal Cooldown: 20 bars
Vitality Field Size: 12.0
Longer-term perspective for multi-day moves
Conservative Trading
Minimum Signal Confluence: 85
Minimum Confluence Score: 80
Require all confirmations: True
Higher thresholds for maximum quality
Aggressive Trading
Minimum Signal Confluence: 75
Minimum Confluence Score: 65
Signal Cooldown: 5 bars
Lower thresholds for more opportunities
RSI with 2-Pole FilterA momentum indicator that tells you if a stock is overbought or oversold.
RSI goes between 0 and 100.
70 = overbought (might fall)
<30 = oversold (might rise)
It often looks jagged or choppy on volatile days.
Think of this filter like a momentum smoother:
It still follows RSI closely,
But it doesn’t react to every little jiggle in price,
Which helps avoid false signals.
it keeps track of:
The current RSI,
The last 2 RSI values (inputs), and
The last 2 outputs (filtered RSIs).
It uses feedback to shape the output based on previous values, making it smoother than a simple moving average.
Ultra BUY SELL//@version=5
indicator("Ultra BUY SELL", overlay = false)
// Inputs
src = input(close, "Source", group = "Main settings")
p = input.int(180, "Trend period", group = "Main settings", tooltip = "Changes STRONG signals' sensitivity.", minval = 1)
atr_p = input.int(155, "ATR Period", group = "Main settings", minval = 1)
mult = input.float(2.1, "ATR Multiplier", step = 0.1, group = "Main settings", tooltip = "Changes sensitivity: higher period = higher sensitivty.")
mode = input.string("Type A", "Signal mode", options = , group = "Mode")
use_ema_smoother = input.string("No", "Smooth source with EMA?", options = , group = "Source")
src_ema_period = input(3, "EMA Smoother period", group = "Source")
color_bars = input(true, "Color bars?", group = "Addons")
signals_view = input.string("All", "Signals to show", options = , group = "Signal's Addon")
signals_shape = input.string("Labels", "Signal's shape", options = , group = "Signal's Addon")
buy_col = input(color.rgb(0, 255, 8), "Buy colour", group = "Signal's Addon", inline = "BS")
sell_col = input(color.rgb(255, 0, 0), "Sell colour", group = "Signal's Addon", inline = "BS")
// Calculations
src := use_ema_smoother == "Yes" ? ta.ema(src, src_ema_period) : src
// Source;
h = ta.highest(src, p)
// Highest of src p-bars back;
l = ta.lowest(src, p)
// Lowest of src p-bars back.
d = h - l
ls = ""
// Tracker of last signal
m = (h + l) / 2
// Initial trend line;
m := bar_index > p ? m : m
atr = ta.atr(atr_p)
// ATR;
epsilon = mult * atr
// Epsilon is a mathematical variable used in many different theorems in order to simplify work with mathematical object. Here it used as sensitivity measure.
change_up = (mode == "Type B" ? ta.cross(src, m + epsilon) : ta.crossover(src, m + epsilon)) or src > m + epsilon
// If price breaks trend line + epsilon (so called higher band), then it is time to update the value of a trend line;
change_down = (mode == "Type B" ? ta.cross(src, m - epsilon) : ta.crossunder(src, m - epsilon)) or src < m - epsilon
// If price breaks trend line - epsilon (so called higher band), then it is time to update the value of a trend line.
sb = open < l + d / 8 and open >= l
ss = open > h - d / 8 and open <= h
strong_buy = sb or sb or sb or sb or sb
strong_sell = ss or ss or ss or ss or ss
m := (change_up or change_down) and m != m ? m : change_up ? m + epsilon : change_down ? m - epsilon : nz(m , m)
// Updating the trend line.
ls := change_up ? "B" : change_down ? "S" : ls
// Last signal. Helps avoid multiple labels in a row with the same signal;
colour = ls == "B" ? buy_col : sell_col
// Colour of the trend line.
buy_shape = signals_shape == "Labels" ? shape.labelup : shape.triangleup
sell_shape = signals_shape == "Labels" ? shape.labeldown : shape.triangledown
// Plottings
// Signals with label shape
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Buy/Sell") and change_up and ls != "B" and not strong_buy, "Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.normal, text = "BUY", textcolor = color.white, force_overlay=true)
// Plotting the BUY signal;
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Buy/Sell") and change_down and ls != "S" and not strong_sell, "Sell signal" , color = colour, style = sell_shape, size = size.normal, text = "SELL", textcolor = color.white, force_overlay=true)
// Plotting the SELL signal.
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Strong") and change_up and ls != "B" and strong_buy, "Strong Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.normal, text = "STRONG", textcolor = color.white, force_overlay=true)
// Plotting the STRONG BUY signal;
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Strong") and change_down and ls != "S" and strong_sell, "Strong Sell signal" , color = colour, style = sell_shape, size = size.normal, text = "STRONG", textcolor = color.white, force_overlay=true)
// Plotting the STRONG SELL signal.
// Signal with arrow shape
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Buy/Sell") and change_up and ls != "B" and not strong_buy, "Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.tiny, force_overlay=true)
// Plotting the BUY signal;
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Buy/Sell") and change_down and ls != "S" and not strong_sell, "Sell signal" , color = colour, style = sell_shape, size = size.tiny, force_overlay=true)
// Plotting the SELL signal.
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Strong") and change_up and ls != "B" and strong_buy, "Strong Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.tiny, force_overlay=true)
// Plotting the STRONG BUY signal;
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Strong") and change_down and ls != "S" and strong_sell, "Strong Sell signal" , color = colour, style = sell_shape, size = size.tiny, force_overlay=true)
// Plotting the STRONG SELL signal.
barcolor(color_bars ? colour : na)
// Bar coloring
// Alerts
matype = input.string(title='MA Type', defval='EMA', options= )
ma_len1 = input(title='Short EMA1 Length', defval=5)
ma_len2 = input(title='Long EMA1 Length', defval=7)
ma_len3 = input(title='Short EMA2 Length', defval=5)
ma_len4 = input(title='Long EMA2 Length', defval=34)
ma_len5 = input(title='Short EMA3 Length', defval=98)
ma_len6 = input(title='Long EMA3 Length', defval=45)
ma_len7 = input(title='Short EMA4 Length', defval=7)
ma_len8 = input(title='Long EMA4 Length', defval=11)
ma_len9 = input(title='Short EMA5 Length', defval=11)
ma_len10 = input(title='Long EMA5 Length', defval=15)
ma_offset = input(title='Offset', defval=0)
//res = input(title="Resolution", type=resolution, defval="240")
f_ma(malen) =>
float result = 0
if matype == 'EMA'
result := ta.ema(src, malen)
result
if matype == 'SMA'
result := ta.sma(src, malen)
result
result
htf_ma1 = f_ma(ma_len1)
htf_ma2 = f_ma(ma_len2)
htf_ma3 = f_ma(ma_len3)
htf_ma4 = f_ma(ma_len4)
htf_ma5 = f_ma(ma_len5)
htf_ma6 = f_ma(ma_len6)
htf_ma7 = f_ma(ma_len7)
htf_ma8 = f_ma(ma_len8)
htf_ma9 = f_ma(ma_len9)
htf_ma10 = f_ma(ma_len10)
//plot(out1, color=green, offset=ma_offset)
//plot(out2, color=red, offset=ma_offset)
//lengthshort = input(8, minval = 1, title = "Short EMA Length")
//lengthlong = input(200, minval = 2, title = "Long EMA Length")
//emacloudleading = input(50, minval = 0, title = "Leading Period For EMA Cloud")
//src = input(hl2, title = "Source")
showlong = input(false, title='Show Long Alerts')
showshort = input(false, title='Show Short Alerts')
showLine = input(false, title='Display EMA Line')
ema1 = input(true, title='Show EMA Cloud-1')
ema2 = input(true, title='Show EMA Cloud-2')
ema3 = input(true, title='Show EMA Cloud-3')
ema4 = input(true, title='Show EMA Cloud-4')
ema5 = input(true, title='Show EMA Cloud-5')
emacloudleading = input.int(0, minval=0, title='Leading Period For EMA Cloud')
mashort1 = htf_ma1
malong1 = htf_ma2
mashort2 = htf_ma3
malong2 = htf_ma4
mashort3 = htf_ma5
malong3 = htf_ma6
mashort4 = htf_ma7
malong4 = htf_ma8
mashort5 = htf_ma9
malong5 = htf_ma10
cloudcolour1 = mashort1 >= malong1 ? color.rgb(0, 255, 0) : color.rgb(255, 0, 0)
cloudcolour2 = mashort2 >= malong2 ? #4caf4f47 : #ff110047
cloudcolour4 = mashort4 >= malong4 ? #4caf4f52 : #f2364652
cloudcolour5 = mashort5 >= malong5 ? #33ff0026 : #ff000026
//03abc1
mashortcolor1 = mashort1 >= mashort1 ? color.olive : color.maroon
mashortcolor2 = mashort2 >= mashort2 ? color.olive : color.maroon
mashortcolor3 = mashort3 >= mashort3 ? color.olive : color.maroon
mashortcolor4 = mashort4 >= mashort4 ? color.olive : color.maroon
mashortcolor5 = mashort5 >= mashort5 ? color.olive : color.maroon
mashortline1 = plot(ema1 ? mashort1 : na, color=showLine ? mashortcolor1 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA1', force_overlay=true)
mashortline2 = plot(ema2 ? mashort2 : na, color=showLine ? mashortcolor2 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA2', force_overlay=true)
mashortline3 = plot(ema3 ? mashort3 : na, color=showLine ? mashortcolor3 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA3', force_overlay=true)
mashortline4 = plot(ema4 ? mashort4 : na, color=showLine ? mashortcolor4 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA4', force_overlay=true)
mashortline5 = plot(ema5 ? mashort5 : na, color=showLine ? mashortcolor5 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA5', force_overlay=true)
malongcolor1 = malong1 >= malong1 ? color.green : color.red
malongcolor2 = malong2 >= malong2 ? color.green : color.red
malongcolor3 = malong3 >= malong3 ? color.green : color.red
malongcolor4 = malong4 >= malong4 ? color.green : color.red
malongcolor5 = malong5 >= malong5 ? color.green : color.red
malongline1 = plot(ema1 ? malong1 : na, color=showLine ? malongcolor1 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA1', force_overlay=true)
malongline2 = plot(ema2 ? malong2 : na, color=showLine ? malongcolor2 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA2', force_overlay=true)
malongline3 = plot(ema3 ? malong3 : na, color=showLine ? malongcolor3 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA3', force_overlay=true)
malongline4 = plot(ema4 ? malong4 : na, color=showLine ? malongcolor4 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA4', force_overlay=true)
malongline5 = plot(ema5 ? malong5 : na, color=showLine ? malongcolor5 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA5', force_overlay=true)
fill(mashortline1, malongline1, color=cloudcolour1, title='MA Cloud1', transp=45)
fill(mashortline2, malongline2, color=cloudcolour2, title='MA Cloud2', transp=65)
fill(mashortline4, malongline4, color=cloudcolour4, title='MA Cloud4', transp=65)
fill(mashortline5, malongline5, color=cloudcolour5, title='MA Cloud5', transp=65)
leftBars = input(15, title='Left Bars ')
rightBars = input(15, title='Right Bars')
volumeThresh = input(20, title='Volume Threshold')
//
highUsePivot = fixnan(ta.pivothigh(leftBars, rightBars) )
lowUsePivot = fixnan(ta.pivotlow(leftBars, rightBars) )
r1 = plot(highUsePivot, color=ta.change(highUsePivot) ? na : #FF0000, linewidth=3, offset=-(rightBars + 1), title='Resistance', force_overlay=true)
s1 = plot(lowUsePivot, color=ta.change(lowUsePivot) ? na : #00ff0d, linewidth=3, offset=-(rightBars + 1), title='Support', force_overlay=true)
//Volume %
short = ta.ema(volume, 5)
long = ta.ema(volume, 10)
osc = 100 * (short - long) / long
//For bull / bear wicks
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © divudivu600
// Developer By ALCON ALGO
//telegram : @harmonicryptosignals
//@version = 5
//indicator(shorttitle='Oscillator Vision', title='Alcon Oscillator Vision', overlay=false)
n1 = input(10, 'Channel length')
n2 = input(21, 'Average length')
reaction_wt = input.int(defval=1, title='Reaction in change of direction', minval=1)
nsc = input.float(53, 'Levels About Buys', minval=0.0)
nsv = input.float(-53, 'Levels About Sells', maxval=-0.0)
Buy_sales = input(true, title='Only Smart Buy Reversal')
Sell_sales = input(true, title='Only Smart Sell Reversal')
Histogram = input(true, title='Show Histogarm')
//Trendx = input(false, title='Show Trendx')
barras = input(true, title='Divergence on chart(Bars)')
divregbull = input(true, title='Regular Divergence Bullish')
divregbear = input(true, title='Regular Divergence Bearish')
divhidbull = input(true, title='Show Divergence Hidden Bullish')
divhidbear = input(true, title='Show Divergence Hidden Bearish')
Tags = input(true, title='Show Divergence Lable')
amme = input(false, title='Activar media movil Extra para WT')
White = #FDFEFE
Black = #000000
Bearish = #e91e62
Bullish = #18e0ff
Strong_Bullish = #2962ff
Bullish2 = #00bedc
Blue1 = #00D4FF
Blue2 = #009BBA
orange = #FF8B00
yellow = #FFFB00
LEZ = #0066FF
purp = #FF33CC
// Colouring
tf(_res, _exp, gaps_on) =>
gaps_on == 0 ? request.security(syminfo.tickerid, _res, _exp) : gaps_on == true ? request.security(syminfo.tickerid, _res, _exp, barmerge.gaps_on, barmerge.lookahead_off) : request.security(syminfo.tickerid, _res, _exp, barmerge.gaps_off, barmerge.lookahead_off)
ha_htf = ''
show_ha = input.bool(true, "Show HA Plot/ Market Bias", group="HA Market Bias")
ha_len = input(7, 'Period', group="HA Market Bias")
ha_len2 = input(10, 'Smoothing', group="HA Market Bias")
// Calculations {
o = ta.ema(open, ha_len)
c = ta.ema(close, ha_len)
h1 = ta.ema(high, ha_len)
l1 = ta.ema(low, ha_len)
haclose = tf(ha_htf, (o + h1 + l1 + c) / 4, 0)
xhaopen = tf(ha_htf, (o + c) / 2, 0)
haopen = na(xhaopen ) ? (o + c) / 2 : (xhaopen + haclose ) / 2
hahigh = math.max(h1, math.max(haopen, haclose))
halow = math.min(l1, math.min(haopen, haclose))
o2 = tf(ha_htf, ta.ema(haopen, ha_len2), 0)
c2 = tf(ha_htf, ta.ema(haclose, ha_len2), 0)
h2 = tf(ha_htf, ta.ema(hahigh, ha_len2), 0)
l2 = tf(ha_htf, ta.ema(halow, ha_len2), 0)
ha_avg = (h2 + l2) / 2
// }
osc_len = 8
osc_bias = 100 *(c2 - o2)
osc_smooth = ta.ema(osc_bias, osc_len)
sigcolor =
(osc_bias > 0) and (osc_bias >= osc_smooth) ? color.new(Bullish, 35) :
(osc_bias > 0) and (osc_bias < osc_smooth) ? color.new(Bullish2, 75) :
(osc_bias < 0) and (osc_bias <= osc_smooth) ? color.new(Bearish, 35) :
(osc_bias < 0) and (osc_bias > osc_smooth) ? color.new(Bearish, 75) :
na
// }
nsc1 = nsc
nsc2 = nsc + 5
nsc3 = nsc + 10
nsc4 = nsc + 15
nsc5 = nsc + 20
nsc6 = nsc + 25
nsc7 = nsc + 30
nsc8 = nsc + 35
nsv1 = nsv - 5
nsv2 = nsv - 10
nsv3 = nsv - 15
nsv4 = nsv - 20
nsv5 = nsv - 25
nsv6 = nsv - 30
nsv7 = nsv - 35
nsv8 = nsv - 40
ap = hlc3
esa = ta.ema(ap, n1)
di = ta.ema(math.abs(ap - esa), n1)
ci = (ap - esa) / (0.015 * di)
tci = ta.ema(ci, n2)
wt1 = tci
wt2 = ta.sma(wt1, 4)
direction = 0
direction := ta.rising(wt1, reaction_wt) ? 1 : ta.falling(wt1, reaction_wt) ? -1 : nz(direction )
Change_of_direction = ta.change(direction, 1)
pcol = direction > 0 ? Strong_Bullish : direction < 0 ? Bearish : na
obLevel1 = input(60, 'Over Bought Level 1')
obLevel2 = input(53, 'Over Bought Level 2')
osLevel1 = input(-60, 'Over Sold Level 1')
osLevel2 = input(-53, 'Over Sold Level 2')
rsi = ta.rsi(close,14)
color greengrad = color.from_gradient(rsi, 10, 90, #00ddff, #007d91)
color redgrad = color.from_gradient(rsi, 10, 90, #8b002e, #e91e62)
ob1 = plot(obLevel1, color=#e91e6301)
os1 = plot(osLevel1, color=#00dbff01)
ob2 = plot(obLevel2, color=#e91e6301)
os2 = plot(osLevel2, color=#00dbff01)
p1 = plot(wt1, color=#00dbff01)
p2 = plot(wt2, color=#e91e6301)
plot(wt1 - wt2, color=wt2 - wt1 > 0 ? redgrad : greengrad, style=plot.style_columns)
// fill(p1,p2,color = wt2 - wt1 > 0 ? redgrad: greengrad) // old
fill(p1,p2,color = sigcolor)
// new
fill(ob1,ob2,color = #e91e6350)
fill(os1,os2,color = #00dbff50)
midpoint = (nsc + nsv) / 2
ploff = (nsc - midpoint) / 8
BullSale = ta.crossunder(wt1, wt2) and wt1 >= nsc and Buy_sales == true
BearSale = ta.crossunder(wt1, wt2) and Buy_sales == false
Bullishh = ta.crossover(wt1, wt2) and wt1 <= nsv and Sell_sales == true
Bearishh = ta.crossover(wt1, wt2) and Sell_sales == false
plot(BullSale ? wt2 + ploff : na, style=plot.style_circles, color=color.new(Bearish, 0), linewidth=6, title='BuysG')
plot(BearSale ? wt2 + ploff : na, style=plot.style_circles, color=color.new(Bearish, 0), linewidth=6, title='SellsG')
plot(Bullishh ? wt2 - ploff : na, style=plot.style_circles, color=color.new(Strong_Bullish, 0), linewidth=6, title='Buys On Sale')
plot(Bearishh ? wt2 - ploff : na, style=plot.style_circles, color=color.new(Strong_Bullish, 0), linewidth=6, title='Sells on Sale')
//plot(Histogram ? wt1 - wt2 : na, style=plot.style_area, color=color.new(Blue2, 80), linewidth=1, title='Histograma')
//barcolor(barras == true and Bullishh == true or barras == true and Bearishh == true ? Bullish2 : na)
//barcolor(barras == true and BullSale == true or barras == true and BearSale == true ? Bearish : na)
/////// Divergence ///////
f_top_fractal(_src) =>
_src < _src and _src < _src and _src > _src and _src > _src
f_bot_fractal(_src) =>
_src > _src and _src > _src and _src < _src and _src < _src
f_fractalize(_src) =>
f_top_fractal(_src) ? 1 : f_bot_fractal(_src) ? -1 : 0
fractal_top1 = f_fractalize(wt1) > 0 ? wt1 : na
fractal_bot1 = f_fractalize(wt1) < 0 ? wt1 : na
high_prev1 = ta.valuewhen(fractal_top1, wt1 , 0)
high_price1 = ta.valuewhen(fractal_top1, high , 0)
low_prev1 = ta.valuewhen(fractal_bot1, wt1 , 0)
low_price1 = ta.valuewhen(fractal_bot1, low , 0)
regular_bearish_div1 = fractal_top1 and high > high_price1 and wt1 < high_prev1 and divregbear == true
hidden_bearish_div1 = fractal_top1 and high < high_price1 and wt1 > high_prev1 and divhidbear == true
regular_bullish_div1 = fractal_bot1 and low < low_price1 and wt1 > low_prev1 and divregbull == true
hidden_bullish_div1 = fractal_bot1 and low > low_price1 and wt1 < low_prev1 and divhidbull == true
col1 = regular_bearish_div1 ? Bearish : hidden_bearish_div1 ? Bearish : na
col2 = regular_bullish_div1 ? Strong_Bullish : hidden_bullish_div1 ? Strong_Bullish : na
//plot(title='Divergence Bearish', series=fractal_top1 ? wt1 : na, color=col1, linewidth=2, transp=0)
//plot(title='Divergence Bullish', series=fractal_bot1 ? wt1 : na, color=col2, linewidth=2, transp=0)
plotshape(regular_bearish_div1 and divregbear and Tags ? wt1 + ploff * 1 : na, title='Divergence Regular Bearish', text='Bear', location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(Bearish, 0), textcolor=color.new(White, 0))
plotshape(hidden_bearish_div1 and divhidbear and Tags ? wt1 + ploff * 1 : na, title='Divergence Hidden Bearish', text='H Bear', location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(Bearish, 0), textcolor=color.new(White, 0))
plotshape(regular_bullish_div1 and divregbull and Tags ? wt1 - ploff * 1 : na, title='Divergence Regular Bullish', text='Bull', location=location.absolute, style=shape.labelup, size=size.tiny, color=color.new(Strong_Bullish, 0), textcolor=color.new(White, 0))
plotshape(hidden_bullish_div1 and divhidbull and Tags ? wt1 - ploff * 1 : na, title='Divergence Hidden Bullish', text='H Bull', location=location.absolute, style=shape.labelup, size=size.tiny, color=color.new(Strong_Bullish, 0), textcolor=color.new(White, 0))
/////// Unfazed Alerts //////
////////////////////////////////////////////////-MISTERMOTA MOMENTUM-/////////////////////////////////////
source = input(close)
responsiveness = math.max(0.00001, input.float(0.9, minval=0.0, maxval=1.0))
periodd = input(50)
sd = ta.stdev(source, 50) * responsiveness
var worm = source
diff = source - worm
delta = math.abs(diff) > sd ? math.sign(diff) * sd : diff
worm += delta
ma = ta.sma(source, periodd)
raw_momentum = (worm - ma) / worm
current_med = raw_momentum
min_med = ta.lowest(current_med, periodd)
max_med = ta.highest(current_med, periodd)
temp = (current_med - min_med) / (max_med - min_med)
value = 0.5 * 2
value *= (temp - .5 + .5 * nz(value ))
value := value > .9999 ? .9999 : value
value := value < -0.9999 ? -0.9999 : value
temp2 = (1 + value) / (1 - value)
momentum = .25 * math.log(temp2)
momentum += .5 * nz(momentum )
//momentum := raw_momentum
signal = nz(momentum )
trend = math.abs(momentum) <= math.abs(momentum )
////////////////////////////////////////////////-GROWING/FAILING-//////////////////////////////////////////
length = input.int(title="MOM Period", minval=1, defval=14, group="MOM Settings")
srcc = input(title="MOM Source", defval=hlc3, group="MOM Settings")
txtcol_grow_above = input(#1a7b24, "Above Grow", group="MOM Settings", inline="Above")
txtcol_fall_above = input(#672ec5, "Fall", group="MOM Settings", inline="Above")
txtcol_grow_below = input(#F37121, "Below Grow", group="MOM Settings", inline="Below")
txtcol_fall_below = input(#be0606, "Fall", group="MOM Settings", inline="Below")
ma(source, length, type) =>
switch type
"SMA" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
typeMA = input.string(title = "Method", defval = "SMA", options= , group="MA Settings")
smoothingLength = input.int(title = "Length", defval = 5, minval = 1, maxval = 100, group="MA Settings")
smoothingLine = ma(delta, smoothingLength, typeMA)
deltaText=(delta > 0 ? (delta > delta ? " MOM > 0 and ▲ Growing, MOM = " + str.tostring(delta , "#.##") :" MOM > 0 and ▼ Falling, MOM = " + str.tostring(delta , "#.##") ) : (delta > delta ? "MOM < 0 and ▲ Growing, MOM = " + str.tostring(delta , "#.##"): " MOM < 0 and ▼ Falling, MOM = " + str.tostring(delta , "#.##")))
oneDay = 24 * 60 * 60 * 1000
barsAhead = 3
tmf = if timeframe.ismonthly
barsAhead * oneDay * 30
else if timeframe.isweekly
barsAhead * oneDay * 7
else if timeframe.isdaily
barsAhead * oneDay
else if timeframe.isminutes
barsAhead * oneDay * timeframe.multiplier / 1440
else if timeframe.isseconds
barsAhead * oneDay * timeframe.multiplier / 86400
else
0
angle(_src) =>
rad2degree = 180 / 3.14159265359
//pi
ang = rad2degree * math.atan((_src - _src ) / ta.atr(14))
ang
emae = angle(smoothingLine)
emaanglestat = emae > emae ? "▲ Growing": "▼ Falling"
deltaTextxxx = "MOM MA/ATR angle value is " + str.tostring(emae, "#.##") + "° and is " + emaanglestat
deltacolorxxx = emae >0 and emae >=emae ? txtcol_grow_above : txtcol_fall_below
// Label
label lpt1 = label.new(time, -30, text=deltaTextxxx , color=deltacolorxxx, xloc=xloc.bar_time, style=label.style_label_left, textcolor=color.white, textalign=text.align_left, size=size.normal)
label.set_x(lpt1, label.get_x(lpt1) + tmf)
label.delete(lpt1 )
txtdeltaColors = (delta > 50 ? (delta < delta ? txtcol_grow_above : txtcol_fall_above) : (delta < delta ? txtcol_grow_below : txtcol_fall_below))
label ldelta1 = label.new(time, 30, text=deltaText , color=txtdeltaColors, xloc=xloc.bar_time, style=label.style_label_left, textcolor=color.white, textalign=text.align_left, size=size.normal)
label.set_x(ldelta1, label.get_x(ldelta1) + tmf)
label.delete(ldelta1 )
Trailing Stop by JDTrailing Stop by JD
A dynamic ATR-based trailing stop indicator that automatically adjusts stop levels based on market volatility. Features a clean, single "BUY/SELL" signal system that alerts traders when price breaches the trailing stop line.
Key features:
ATR volatility-based stop calculation
Trend-following logic (stops only move favorably)
Single exit signal display
Real-time trailing stop value in bottom-left table
Customizable ATR period and multiplier settings
Built-in alert system for automated notifications
Perfect for traders looking for a reliable, adaptive stop-loss system that responds to changing market conditions.
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
Time-Rotated Motivational MessagesThis indicator displays rotating messages directly on your chart to help reinforce trading discipline, mindset, or strategy reminders. You can customize the messages using a single input field with | separators, and set how often they rotate (e.g., every 5, 10, or 15 minutes). The table’s position, text size, and colors are fully configurable.
Features:
Pipe-separated message input for easy customization
Configurable rotation interval (in minutes)
Adjustable table position, text size, and colors
Timezone selector for accurate scheduling
Ideal for traders who want visual reminders to stay focused, patient, and disciplined during live trading.
BitDoctor Risk Appetite DashboardBitDoctor Risk Appetite Dashboard
The BitDoctor Risk Appetite Dashboard is a powerful tool for gauging market sentiment and risk appetite across major asset classes. It combines equity, credit, emerging markets, interest rates, and crypto signals into a single dashboard, giving traders a clear view of current market dynamics.
What it does:
- Calculates momentum for each key asset using a 14-day rate of change.
- Normalizes each signal and plots a composite Risk Appetite Strength Index (RASI) on the chart.
- Displays a dashboard table showing the momentum of each component in percentage terms alongside the composite RASI.
How to use it:
The plotted RASI line shows overall risk appetite:
- Positive readings suggest a stronger risk-on environment.
- Negative readings indicate risk-off sentiment.
The dashboard table (top-right corner by default) displays two columns:
- Asset : The tracked asset symbol.
- Momentum : The current 14-day rate of change as a percentage.
Interpreting the table:
Each row represents a component of market risk sentiment:
- SPY : US equities.
- HYG : High yield bonds (credit risk appetite).
- EEM : Emerging markets.
- 1/UST10Y : Inverted 10-year Treasury yield (lower yields support risk appetite).
- ETH : Ethereum (crypto risk proxy).
- RASI : The average of the above signals, indicating overall market risk appetite.
Higher positive values in the table suggest rising momentum in that asset, which contributes positively to the composite RASI. Conversely, negative values signal declining momentum. You can use these individual readings to see which sectors are driving the current risk sentiment and to time entries and exits accordingly.
Customization:
The indicator allows you to adjust the table's background color, text color, text size, cell padding, and position so it remains readable and unobtrusive regardless of your chart theme.
Use the BitDoctor Risk Appetite Dashboard as part of a broader analysis to align your trades with prevailing risk conditions. It is not a standalone trading signal but a context tool to support better decision-making.
Why these assets were chosen:
The dashboard uses a carefully selected mix of widely-followed proxies for global risk sentiment:
- SPY : Represents large-cap US equity market performance, a key barometer of investor confidence.
- HYG : Tracks high-yield corporate bonds, reflecting credit risk appetite in fixed income markets.
- EEM : Captures emerging market equities, which are highly sensitive to global risk-on/off dynamics.
- 1/UST10Y : The inverse of the US 10-year Treasury yield, as falling yields often accompany risk-on moves and vice versa.
- ETH : Ethereum as a representative crypto asset, offering insight into speculative risk appetite in digital assets.
This mix provides a comprehensive view of sentiment across traditional and alternative markets, making the dashboard a robust tool for gauging overall risk appetite.
Glamour ETF Index vs. QQQ mit MA10, MA20 & MA50Stan Weinstein uses the term "Glamour Index" as a sentiment indicator to assess how speculative or overheated the stock market is. The Glamour Index measures the relationship between so-called "glamour stocks" (trendy stocks, hyped stocks with high media attention and sometimes extreme price increases) and solid, more conservative stocks. Weinstein uses this index to: 1) Analyze market sentiment – particularly whether the market is in a speculative euphoria phase.
2) Identify warning signs of a potential top formation or an impending downturn.
My basket compares performance against the QQQ (alternatively, SPY or any other benchmark is also possible).
My basket consists of the ETFs in the ARK universe, as well as other growth ETFs such as IPO, FFTY, and QQQJ.
Multi-TF Z-Score IndicatorIndicator to find the Z score for the daily 4h, 1h, 15m and 5 min time frames with 20 previous samples.
