ATR Overlay with Trailing Flip [ask2maniish]📘 ATR Overlay with Trailing Flip
🔍 Overview
The ATR Overlay with Trailing Flip is a dynamic, visually-enhanced overlay indicator designed to assist traders in trend detection, trailing stop management, and volatility-based decision making. It leverages the Average True Range (ATR) with optional dynamic multipliers, filters, and alerts to enhance trade execution precision.
⚙️ Features Summary
✅ Static & dynamic ATR multiplier
✅ Customizable trailing stop logic
✅ Volume & Bollinger Band filters
✅ Buy/Sell label signals with alerts
✅ ATR bands with color fill
✅ Optional candle coloring based on trend
✅ Table showing current ATR multiplier
✅ Fully customizable visual controls
🔧 User Inputs
📘 Info Panel
ATR Usage Guide
Tooltip with trading-style recommendations:
Scalping: ATR 5–10, Intraday: ATR 10–14 , Swing: ATR 14–21 , Position: ATR 21–50
📊 Visual Elements
📈 Plots
Upper/Lower ATR Bands
ATR Fill Zone
Dynamic Trailing Stop Line
🕯 Candle Coloring
Candles colored green (uptrend) or red (downtrend)
Wick coloring matches body
🏷 Signal Labels
"BUY" below candle when trend flips up
"SELL" above candle when trend flips down
📊 Table (Top Right)
Displays current multiplier value:
If static: Static: x.x
If dynamic: percentage format based on ATR ratio
🔔 Alerts
Two alert conditions:
Flip to Long → "📈 ATR flip to LONG"
Flip to Short → "📉 ATR flip to SHORT"
Sound can be enabled for real-time feedback.
🧠 Best Practices
Combine this tool with support/resistance or order flow indicators
Use dynamic ATR during volatile periods for better adaptability
Filter signals in ranging markets with BBand Width Filter
For scalping, reduce ATR period and multiplier for tighter risk
🛠️ Customization Tips
Adjust trailingPeriod for tighter/looser stops
Use color inputs to match your charting theme
Disable features (labels/fill) to declutter chart
"scalp" için komut dosyalarını ara
Multi-timeframe Moving Average Overlay w/ Sentiment Table🔍 Overview
This indicator overlays selected moving averages (MA) from multiple timeframes directly onto the chart and provides a dynamic sentiment table that summarizes the relative bullish or bearish alignment of short-, mid-, and long-term moving averages.
It supports seven moving average types — including traditional and advanced options like DEMA, TEMA, and HMA — and provides visual feedback via table highlights and alerts when strong momentum alignment is detected.
This tool is designed to support traders who rely on multi-timeframe analysis for trend confirmation, momentum filtering, and high-probability entry timing.
⚙️ Core Features
Multi-Timeframe MA Overlay:
Plot moving averages from 1-minute, 5-minute, 1-hour, 1-day, 1-week, and 1-month timeframes on the same chart for visual trend alignment.
Customizable MA Type:
Choose from:
EMA (Exponential Moving Average)
SMA (Simple Moving Average)
DEMA (Double EMA)
TEMA (Triple EMA)
WMA (Weighted MA)
VWMA (Volume-Weighted MA)
HMA (Hull MA)
Adjustable MA Length:
Change the length of all moving averages globally to suit your strategy (e.g. 9, 21, 50, etc.).
Sentiment Table:
Visually track trend sentiment across four key zones (Hourly, Daily, Weekly, Monthly). Each is based on the relative positioning of short-term and long-term MAs.
Sentiment Symbols Explained:
↑↑↑: Strong bullish momentum (short-term MAs stacked above longer-term MAs)
↑↑ / ↑: Moderate bullish bias
↓↓↓: Strong bearish momentum
↓↓ / ↓: Moderate bearish bias
Table Customization:
Choose the table’s position on the chart (bottom right, top right, bottom left, top left).
Style Customization:
Display MA lines as standard Line or Stepline format.
Color Customization:
Individual colors for each timeframe MA line for visual clarity.
Built-in Alerts:
Receive alerts when strong bullish (↑↑↑) or bearish (↓↓↓) sentiment is detected on any timeframe block.
📈 Use Cases
1. Trend Confirmation:
Use sentiment alignment across multiple timeframes to confirm the overall trend direction before entering a trade.
2. Entry Timing:
Wait for a shift from neutral to strong bullish or bearish sentiment to time entries during pullbacks or breakouts.
3. Momentum Filtering:
Only trade in the direction of the dominant multi-timeframe trend. For example, ignore long setups when all sentiment blocks show bearish alignment.
4. Swing & Intraday Scalping:
Use hourly and daily sentiment zones for swing trades, or rely on 1m/5m MAs for precise scalping decisions in fast-moving markets.
5. Strategy Layering:
Combine this overlay with support/resistance, RSI, or volume-based signals to enhance decision-making with multi-timeframe context.
⚠️ Important Notes
Lower-timeframe values (1m, 5m) may appear static on higher-timeframe charts due to resolution limits in TradingView. This is expected behavior.
The indicator uses MA stacking, not crossover events, to determine sentiment.
Pullback SARPullback SAR - Parabolic SAR with Pullback Detection
Description: The "Pullback SAR" is an advanced indicator built on the classic Parabolic SAR but with additional functionality for detecting pullbacks. It helps identify moments when the price pulls back from the main trend, offering potential entry signals. Perfect for traders looking to enter the market after a correction.
Key Features:
SAR (Parabolic SAR): The Parabolic SAR indicator is used to determine potential trend reversal points. It marks levels where the price could reverse its direction.
Pullback Detection: The indicator catches periods when the price moves away from the main trend and then returns, which may suggest a re-entry opportunity.
Long and Short Signals: Once a pullback in the direction of the main trend is identified, the indicator generates signals that could be used to open positions.
Simple and Clear Construction: The indicator is based on the classic SAR, with added pullback detection logic to enhance the accuracy of the signals.
Parameters:
Start (SAR Step): Determines the initial step for the SAR calculation, which controls the rate of change in the indicator at the beginning.
Increment (SAR Increment): Defines the maximum step size for SAR, allowing traders to adjust the indicator’s sensitivity to market volatility.
Max Value (SAR Max): Sets the upper limit for the SAR value, controlling its volatility.
Usage:
Swing Trading: Ideal for swing strategies, aiming to capture larger price moves while maintaining a safe margin.
Scalping: Due to its precise pullback detection, it can also be used in scalping, especially when the price quickly returns to the main trend.
Risk Management: The combination of SAR and pullback detection allows traders to adjust their positions according to changing market conditions.
Special Notes:
Adjusting Parameters: Depending on the market and trading style, users can adjust the SAR parameters (Start, Increment, Max Value) to fit their needs.
Combination with Other Indicators: It's recommended to use the indicator alongside other technical analysis tools (e.g., EMA, RSI) to enhance the accuracy of the signals.
Link to the script: This open-source version of the indicator is available on TradingView, enabling full customization and adjustments to meet your personal trading strategy. Share your experiences and suggestions!
[TehThomas] - ICT Inversion Fair value Gap (IFVG) The Inversion Fair Value Gap (IFVG) indicator is a powerful tool designed for traders who utilize ICT (Inner Circle Trader) strategies. It focuses on identifying and displaying Inversion Fair Value Gaps, which are critical zones that emerge when traditional Fair Value Gaps (FVGs) are invalidated by price action. These gaps represent key areas where price often reacts, making them essential for identifying potential reversals, trend continuations, and liquidity zones.
What Are Inversion Fair Value Gaps?
Inversion Fair Value Gaps occur when price revisits a traditional FVG and breaks through it, effectively flipping its role in the market. For example:
A bullish FVG that is invalidated becomes a bearish zone, often acting as resistance.
A bearish FVG that is invalidated transforms into a bullish zone, serving as support.
These gaps are significant because they often align with institutional trading activity. They highlight areas where large orders have been executed or where liquidity has been targeted. Understanding these gaps provides traders with a deeper insight into market structure and helps them anticipate future price movements with greater accuracy.
Why This Strategy Works
The IFVG concept is rooted in ICT principles, which emphasize liquidity dynamics, market inefficiencies, and institutional order flow. Traditional FVGs represent imbalances in price action caused by gaps between candles. When these gaps are invalidated, they become inversion zones that can act as magnets for price. These zones frequently serve as high-probability areas for price reversals or trend continuations.
This strategy works because it aligns with how institutional traders operate. Inversion gaps often mark areas of interest for "smart money," making them reliable indicators of potential market turning points. By focusing on these zones, traders can align their strategies with institutional behavior and improve their overall trading edge.
How the Indicator Works
This indicator simplifies the process of identifying and tracking IFVGs by automating their detection and visualization on the chart. It scans the chart in real-time to identify bullish and bearish FVGs that meet user-defined thresholds for inversion. Once identified, these gaps are dynamically displayed on the chart with distinct colors for bullish and bearish zones.
The indicator also tracks whether these gaps are mitigated or broken by price action. When an IFVG is broken, it extends the zone for a user-defined number of bars to visualize its potential role as a new support or resistance level. Additionally, alerts can be enabled to notify traders when new IFVGs form or when existing ones are broken, ensuring timely decision-making in fast-moving markets.
Key Features
Automatic Detection: The indicator automatically identifies bullish and bearish IFVGs based on user-defined thresholds.
Dynamic Visualization: It displays IFVGs directly on the chart with customizable colors for easy differentiation.
Real-Time Updates: The status of each IFVG is updated dynamically based on price action.
Zone Extensions: Broken IFVGs are extended to visualize their potential as support or resistance levels.
Alerts: Notifications can be set up to alert traders when key events occur, such as the formation or breaking of an IFVG.
These features make the tool highly efficient and reduce the need for manual analysis, allowing traders to focus on execution rather than tedious chart work.
Benefits of Using This Indicator
The IFVG indicator offers several advantages that make it an indispensable tool for ICT traders. By automating the detection of inversion gaps, it saves time and reduces errors in analysis. The clearly defined zones improve risk management by providing precise entry points, stop-loss levels, and profit targets based on market structure.
This tool is also highly versatile and adapts seamlessly across different timeframes. Whether you’re scalping lower timeframes or swing trading higher ones, it provides actionable insights tailored to your trading style. Furthermore, by aligning your strategy with institutional logic, you gain a significant edge in anticipating market movements.
Practical Applications
This indicator can be used across various trading styles:
Scalping: Identify quick reversal points on lower timeframes using real-time alerts.
Day Trading: Use inversion gaps as key levels for intraday support/resistance or trend continuation setups.
Swing Trading: Analyse higher timeframes to identify major inversion zones that could act as critical turning points in larger trends.
By integrating this tool into your trading routine, you can streamline your analysis process and focus on executing high-probability setups.
Conclusion
The Inversion Fair Value Gap (IFVG) indicator is more than just a technical analysis tool—it’s a strategic ally for traders looking to refine their edge in the markets. By automating the detection and tracking of inversion gaps based on ICT principles, it simplifies complex market analysis while maintaining accuracy and depth. Whether you’re new to ICT strategies or an experienced trader seeking greater precision, this indicator will elevate your trading game by aligning your approach with institutional behavior.
If you’re serious about improving your trading results while saving time and effort, this tool is an essential addition to your toolkit. It provides clarity in chaotic markets, enhances precision in trade execution, and ensures you never miss critical opportunities in your trading journey.
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Multi-Timeframe Confluence IndicatorThe Multi-Timeframe Confluence Indicator strategically combines multiple timeframes with technical tools like EMA and RSI to provide robust, high-probability trading signals. This combination is grounded in the principles of technical analysis and market behavior, tailored for traders across all styles—whether intraday, swing, or positional.
1. The Power of Multi-Timeframe Confluence
Markets are influenced by participants operating on different time horizons:
• Intraday traders act on short-term price fluctuations.
• Swing traders focus on intermediate trends lasting days or weeks.
• Position traders aim to capture multi-month or long-term trends.
By aligning signals from a higher timeframe (macro trend) with a lower timeframe (micro trend), the indicator ensures that short-term entries are in harmony with the broader market direction. This multi-timeframe approach significantly reduces false signals caused by temporary market noise or counter-trend moves.
Example: A bullish trend on the daily chart (higher timeframe) combined with a bullish RSI and EMA alignment on the 15-minute chart (lower timeframe) provides a stronger confirmation than relying on the 15-minute chart alone.
2. Why EMA and RSI Are Essential
Each element of the indicator serves a unique role in ensuring accuracy and reliability:
• EMA (Exponential Moving Average):
• A dynamic trend filter that adjusts quickly to price changes.
• On the higher timeframe, it establishes the overall trend direction (e.g., bullish or bearish).
• On the lower timeframe, it identifies precise entry/exit zones within the trend.
• RSI (Relative Strength Index):
• Adds a momentum-based perspective, confirming whether a trend is backed by strong buying or selling pressure.
• Ensures that signals occur in areas of strength (RSI > 55 for bullish signals, RSI < 45 for bearish signals), filtering out weak or uncertain price movements.
By combining EMA (trend) and RSI (momentum), the indicator delivers confluence-based validation, where both trend and momentum align, making signals more reliable.
3. Cooldown Period for Signal Optimization
Trading in choppy or sideways markets often leads to overtrading and false signals. The cooldown period ensures that once a signal is generated, subsequent signals are suppressed for a defined number of bars. This prevents traders from entering low-probability trades during indecisive market phases, improving overall signal quality.
Example: After a bullish confluence signal, the cooldown period prevents a bearish signal from being triggered prematurely if the market enters a temporary retracement.
4. Use Cases Across Trading Styles
This indicator caters to various trading styles, each benefiting from the confluence of timeframes and technical elements:
• Intraday Trading:
• Use a 1-hour chart as the higher timeframe and a 5-minute chart as the lower timeframe.
• Benefit: Align intraday entries with the hourly trend for higher win rates.
• Swing Trading:
• Use a daily chart as the higher timeframe and a 1-hour chart as the lower timeframe.
• Benefit: Capture multi-day moves while avoiding counter-trend entries.
• Scalping:
• Use a 30-minute chart as the higher timeframe and a 1-minute chart as the lower timeframe.
• Benefit: Enhance scalping efficiency by ensuring short-term trades align with broader intraday trends.
• Position Trading:
• Use a weekly chart as the higher timeframe and a daily chart as the lower timeframe.
• Benefit: Time long-term entries more precisely, maximizing profit potential.
5. Robustness Through Customization
The indicator allows traders to customize:
• Timeframes for higher and lower analysis.
• EMA lengths for trend filtering.
• RSI settings for momentum confirmation.
• Cooldown periods to adapt to market volatility.
This flexibility ensures that the indicator can be tailored to suit individual trading preferences, market conditions, and asset classes, making it a comprehensive tool for any trading strategy.
Why This Mashup Stands Out
The Multi-Timeframe Confluence Indicator is more than a sum of its parts. It leverages:
• EMA’s ability to identify trends, combined with RSI’s insight into momentum, ensuring each signal is well-supported.
• A multi-timeframe perspective that incorporates both macro and micro trends, filtering out noise and improving reliability.
• A cooldown mechanism that prevents overtrading, a common pitfall for traders in volatile markets.
This integration results in a powerful, adaptable indicator that provides actionable, high-confidence signals, reducing uncertainty and enhancing trading performance across all styles.
Multi-Timeframe Stochastic Alert [tradeviZion]# Multi-Timeframe Stochastic Alert : Complete User Guide
## 1. Introduction
### What is the Multi-Timeframe Stochastic Alert?
The Multi-Timeframe Stochastic Alert is an advanced technical analysis tool that helps traders identify potential trading opportunities by analyzing momentum across multiple timeframes. It combines the power of the stochastic oscillator with multi-timeframe analysis to provide more reliable trading signals.
### Key Features and Benefits
- Simultaneous analysis of 6 different timeframes
- Advanced alert system with customizable conditions
- Real-time visual feedback with color-coded signals
- Comprehensive data table with instant market insights
- Motivational trading messages for psychological support
- Flexible theme support for comfortable viewing
### How it Can Help Your Trading
- Identify stronger trends by confirming momentum across multiple timeframes
- Reduce false signals through multi-timeframe confirmation
- Stay informed of market changes with customizable alerts
- Make more informed decisions with comprehensive market data
- Maintain trading discipline with clear visual signals
## 2. Understanding the Display
### The Stochastic Chart
The main chart displays three key components:
1. ** K-Line (Fast) **: The primary stochastic line (default color: green)
2. ** D-Line (Slow) **: The signal line (default color: red)
3. ** Reference Lines **:
- Overbought Level (80): Upper dashed line
- Middle Line (50): Center dashed line
- Oversold Level (20): Lower dashed line
### The Information Table
The table provides a comprehensive view of stochastic readings across all timeframes. Here's what each column means:
#### Column Explanations:
1. ** Timeframe **
- Shows the time period for each row
- Example: "5" = 5 minutes, "15" = 15 minutes, etc.
2. ** K Value **
- The fast stochastic line value (0-100)
- Higher values indicate stronger upward momentum
- Lower values indicate stronger downward momentum
3. ** D Value **
- The slow stochastic line value (0-100)
- Helps confirm momentum direction
- Crossovers with K-line can signal potential trades
4. ** Status **
- Shows current momentum with symbols:
- ▲ = Increasing (bullish)
- ▼ = Decreasing (bearish)
- Color matches the trend direction
5. ** Trend **
- Shows the current market condition:
- "Overbought" (above 80)
- "Bullish" (above 50)
- "Bearish" (below 50)
- "Oversold" (below 20)
#### Row Explanations:
1. ** Title Row **
- Shows "🎯 Multi-Timeframe Stochastic"
- Indicates the indicator is active
2. ** Header Row **
- Contains column titles
- Dark blue background for easy reading
3. ** Timeframe Rows **
- Six rows showing different timeframe analyses
- Each row updates independently
- Color-coded for easy trend identification
4. **Message Row**
- Shows rotating motivational messages
- Updates every 5 bars
- Helps maintain trading discipline
### Visual Indicators and Colors
- ** Green Background **: Indicates bullish conditions
- ** Red Background **: Indicates bearish conditions
- ** Color Intensity **: Shows strength of the signal
- ** Background Highlights **: Appear when alert conditions are met
## 3. Core Settings Groups
### Stochastic Settings
These settings control the core calculation of the stochastic oscillator.
1. ** Length (Default: 14) **
- What it does: Determines the lookback period for calculations
- Higher values (e.g., 21): More stable, fewer signals
- Lower values (e.g., 8): More sensitive, more signals
- Recommended:
* Day Trading: 8-14
* Swing Trading: 14-21
* Position Trading: 21-30
2. ** Smooth K (Default: 3) **
- What it does: Smooths the main stochastic line
- Higher values: Smoother line, fewer false signals
- Lower values: More responsive, but more noise
- Recommended:
* Day Trading: 2-3
* Swing Trading: 3-5
* Position Trading: 5-7
3. ** Smooth D (Default: 3) **
- What it does: Smooths the signal line
- Works in conjunction with Smooth K
- Usually kept equal to or slightly higher than Smooth K
- Recommended: Keep same as Smooth K for consistency
4. ** Source (Default: Close) **
- What it does: Determines price data for calculations
- Options: Close, Open, High, Low, HL2, HLC3, OHLC4
- Recommended: Stick with Close for most reliable signals
### Timeframe Settings
Controls the multiple timeframes analyzed by the indicator.
1. ** Main Timeframes (TF1-TF6) **
- TF1 (Default: 10): Shortest timeframe for quick signals
- TF2 (Default: 15): Short-term trend confirmation
- TF3 (Default: 30): Medium-term trend analysis
- TF4 (Default: 30): Additional medium-term confirmation
- TF5 (Default: 60): Longer-term trend analysis
- TF6 (Default: 240): Major trend confirmation
Recommended Combinations:
* Scalping: 1, 3, 5, 15, 30, 60
* Day Trading: 5, 15, 30, 60, 240, D
* Swing Trading: 15, 60, 240, D, W, M
2. ** Wait for Bar Close (Default: true) **
- What it does: Controls when calculations update
- True: More reliable but slightly delayed signals
- False: Faster signals but may change before bar closes
- Recommended: Keep True for more reliable signals
### Alert Settings
#### Main Alert Settings
1. ** Enable Alerts (Default: true) **
- Master switch for all alert notifications
- Toggle this off when you don't want any alerts
- Useful during testing or when you want to focus on visual signals only
2. ** Alert Condition (Options) **
- "Above Middle": Bullish momentum alerts only
- "Below Middle": Bearish momentum alerts only
- "Both": Alerts for both directions
- Recommended:
* Trending Markets: Choose direction matching the trend
* Ranging Markets: Use "Both" to catch reversals
* New Traders: Start with "Both" until you develop a specific strategy
3. ** Alert Frequency **
- "Once Per Bar": Immediate alerts during the bar
- "Once Per Bar Close": Alerts only after bar closes
- Recommended:
* Day Trading: "Once Per Bar" for quick reactions
* Swing Trading: "Once Per Bar Close" for confirmed signals
* Beginners: "Once Per Bar Close" to reduce false signals
#### Timeframe Check Settings
1. ** First Check (TF1) **
- Purpose: Confirms basic trend direction
- Alert Triggers When:
* For Bullish: Stochastic is above middle line (50)
* For Bearish: Stochastic is below middle line (50)
* For Both: Triggers in either direction based on position relative to middle line
- Settings:
* Enable/Disable: Turn first check on/off
* Timeframe: Default 5 minutes
- Best Used For:
* Quick trend confirmation
* Entry timing
* Scalping setups
2. ** Second Check (TF2) **
- Purpose: Confirms both position and momentum
- Alert Triggers When:
* For Bullish: Stochastic is above middle line AND both K&D lines are increasing
* For Bearish: Stochastic is below middle line AND both K&D lines are decreasing
* For Both: Triggers based on position and direction matching current condition
- Settings:
* Enable/Disable: Turn second check on/off
* Timeframe: Default 15 minutes
- Best Used For:
* Trend strength confirmation
* Avoiding false breakouts
* Day trading setups
3. ** Third Check (TF3) **
- Purpose: Confirms overall momentum direction
- Alert Triggers When:
* For Bullish: Both K&D lines are increasing (momentum confirmation)
* For Bearish: Both K&D lines are decreasing (momentum confirmation)
* For Both: Triggers based on matching momentum direction
- Settings:
* Enable/Disable: Turn third check on/off
* Timeframe: Default 30 minutes
- Best Used For:
* Major trend confirmation
* Swing trading setups
* Avoiding trades against the main trend
Note: All three conditions must be met simultaneously for the alert to trigger. This multi-timeframe confirmation helps reduce false signals and provides stronger trade setups.
#### Alert Combinations Examples
1. ** Conservative Setup **
- Enable all three checks
- Use "Once Per Bar Close"
- Timeframe Selection Example:
* First Check: 15 minutes
* Second Check: 1 hour (60 minutes)
* Third Check: 4 hours (240 minutes)
- Wider gaps between timeframes reduce noise and false signals
- Best for: Swing trading, beginners
2. ** Aggressive Setup **
- Enable first two checks only
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
- Closer timeframes for quicker signals
- Best for: Day trading, experienced traders
3. ** Balanced Setup **
- Enable all checks
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
* Third Check: 1 hour (60 minutes)
- Balanced spacing between timeframes
- Best for: All-around trading
### Visual Settings
#### Alert Visual Settings
1. ** Show Background Color (Default: true) **
- What it does: Highlights chart background when alerts trigger
- Benefits:
* Makes signals more visible
* Helps spot opportunities quickly
* Provides visual confirmation of alerts
- When to disable:
* If using multiple indicators
* When preferring a cleaner chart
* During manual backtesting
2. ** Background Transparency (Default: 90) **
- Range: 0 (solid) to 100 (invisible)
- Recommended Settings:
* Clean Charts: 90-95
* Multiple Indicators: 85-90
* Single Indicator: 80-85
- Tip: Adjust based on your chart's overall visibility
3. ** Background Colors **
- Bullish Background:
* Default: Green
* Indicates upward momentum
* Customizable to match your theme
- Bearish Background:
* Default: Red
* Indicates downward momentum
* Customizable to match your theme
#### Level Settings
1. ** Oversold Level (Default: 20) **
- Traditional Setting: 20
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 10): More conservative
* Higher values (e.g., 30): More aggressive
- Trading Applications:
* Potential bullish reversal zone
* Support level in uptrends
* Entry point for long positions
2. ** Overbought Level (Default: 80) **
- Traditional Setting: 80
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 70): More aggressive
* Higher values (e.g., 90): More conservative
- Trading Applications:
* Potential bearish reversal zone
* Resistance level in downtrends
* Exit point for long positions
3. ** Middle Line (Default: 50) **
- Purpose: Trend direction separator
- Applications:
* Above 50: Bullish territory
* Below 50: Bearish territory
* Crossing 50: Potential trend change
- Trading Uses:
* Trend confirmation
* Entry/exit trigger
* Risk management level
#### Color Settings
1. ** Bullish Color (Default: Green) **
- Used for:
* K-Line (Main stochastic line)
* Status symbols when trending up
* Trend labels for bullish conditions
- Customization:
* Choose colors that stand out
* Match your trading platform theme
* Consider color blindness accessibility
2. ** Bearish Color (Default: Red) **
- Used for:
* D-Line (Signal line)
* Status symbols when trending down
* Trend labels for bearish conditions
- Customization:
* Choose contrasting colors
* Ensure visibility on your chart
* Consider monitor settings
3. ** Neutral Color (Default: Gray) **
- Used for:
* Middle line (50 level)
- Customization:
* Should be less prominent
* Easy on the eyes
* Good background contrast
### Theme Settings
1. **Color Theme Options**
- Dark Theme (Default):
* Dark background with white text
* Optimized for dark chart backgrounds
* Reduces eye strain in low light
- Light Theme:
* Light background with black text
* Better visibility in bright conditions
- Custom Theme:
* Use your own color preferences
2. ** Available Theme Colors **
- Table Background
- Table Text
- Table Headers
Note: The theme affects only the table display colors. The stochastic lines and alert backgrounds use their own color settings.
### Table Settings
#### Position and Size
1. ** Table Position **
- Options:
* Top Right (Default)
* Middle Right
* Bottom Right
* Top Left
* Middle Left
* Bottom Left
- Considerations:
* Chart space utilization
* Personal preference
* Multiple monitor setups
2. ** Text Sizes **
- Title Size Options:
* Tiny: Minimal space usage
* Small: Compact but readable
* Normal (Default): Standard visibility
* Large: Enhanced readability
* Huge: Maximum visibility
- Data Size Options:
* Recommended: One size smaller than title
* Adjust based on screen resolution
* Consider viewing distance
3. ** Empowering Messages **
- Purpose:
* Maintain trading discipline
* Provide psychological support
* Remind of best practices
- Rotation:
* Changes every 5 bars
* Categories include:
- Market Wisdom
- Strategy & Discipline
- Mindset & Growth
- Technical Mastery
- Market Philosophy
## 4. Setting Up for Different Trading Styles
### Day Trading Setup
1. **Timeframes**
- Primary: 5, 15, 30 minutes
- Secondary: 1H, 4H
- Alert Settings: "Once Per Bar"
2. ** Stochastic Settings **
- Length: 8-14
- Smooth K/D: 2-3
- Alert Condition: Match market trend
3. ** Visual Settings **
- Background: Enabled
- Transparency: 85-90
- Theme: Based on trading hours
### Swing Trading Setup
1. ** Timeframes **
- Primary: 1H, 4H, Daily
- Secondary: Weekly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 14-21
- Smooth K/D: 3-5
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Optional
- Transparency: 90-95
- Theme: Personal preference
### Position Trading Setup
1. ** Timeframes **
- Primary: Daily, Weekly
- Secondary: Monthly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 21-30
- Smooth K/D: 5-7
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Disabled
- Focus on table data
- Theme: High contrast
## 5. Troubleshooting Guide
### Common Issues and Solutions
1. ** Too Many Alerts **
- Cause: Settings too sensitive
- Solutions:
* Increase timeframe intervals
* Use "Once Per Bar Close"
* Enable fewer timeframe checks
* Adjust stochastic length higher
2. ** Missed Signals **
- Cause: Settings too conservative
- Solutions:
* Decrease timeframe intervals
* Use "Once Per Bar"
* Enable more timeframe checks
* Adjust stochastic length lower
3. ** False Signals **
- Cause: Insufficient confirmation
- Solutions:
* Enable all three timeframe checks
* Use larger timeframe gaps
* Wait for bar close
* Confirm with price action
4. ** Visual Clarity Issues **
- Cause: Poor contrast or overlap
- Solutions:
* Adjust transparency
* Change theme settings
* Reposition table
* Modify color scheme
### Best Practices
1. ** Getting Started **
- Start with default settings
- Use "Both" alert condition
- Enable all timeframe checks
- Wait for bar close
- Monitor for a few days
2. ** Fine-Tuning **
- Adjust one setting at a time
- Document changes and results
- Test in different market conditions
- Find your optimal timeframe combination
- Balance sensitivity with reliability
3. ** Risk Management **
- Don't trade against major trends
- Confirm signals with price action
- Use appropriate position sizing
- Set clear stop losses
- Follow your trading plan
4. ** Regular Maintenance **
- Review settings weekly
- Adjust for market conditions
- Update color scheme for visibility
- Clean up chart regularly
- Maintain trading journal
## 6. Tips for Success
1. ** Entry Strategies **
- Wait for all timeframes to align
- Confirm with price action
- Use proper position sizing
- Consider market conditions
2. ** Exit Strategies **
- Trail stops using indicator levels
- Take partial profits at targets
- Honor your stop losses
- Don't fight the trend
3. ** Psychology **
- Stay disciplined with settings
- Don't override system signals
- Keep emotions in check
- Learn from each trade
4. ** Continuous Improvement **
- Record your trades
- Review performance regularly
- Adjust settings gradually
- Stay educated on markets
[ETH] Optimized Trend Strategy - Lorenzo SuperScalpStrategy Title: Optimized Trend Strategy - Lorenzo SuperScalp
Description:
The Optimized Trend Strategy is a comprehensive trading system tailored for Ethereum (ETH) and optimized for the 15-minute timeframe but adaptable to various timeframes. This strategy utilizes a combination of technical indicators—RSI, Bollinger Bands, and MACD—to identify and act on price trends efficiently, providing traders with actionable buy and sell signals based on market conditions.
Key Features:
Multi-Indicator Approach:
RSI (Relative Strength Index): Identifies overbought and oversold conditions to time market entries and exits.
Bollinger Bands: Acts as a dynamic support and resistance level, helping to pinpoint precise entry and exit zones.
MACD (Moving Average Convergence Divergence): Detects momentum changes through bullish and bearish crossovers.
Signal Conditions:
Buy Signal:
RSI is below 45 (indicating an oversold condition).
Price is near or below the lower Bollinger Band.
MACD bullish crossover occurs.
Sell Signal:
RSI is above 55 (indicating an overbought condition).
Price is near or above the upper Bollinger Band.
MACD bearish crossunder occurs.
Trade Execution Logic:
Long Trades: Opened when a buy signal flashes. If there’s an open short position, it is closed before opening a long.
Short Trades: Opened when a sell signal flashes. If there’s an open long position, it is closed before opening a short.
The strategy also ensures a minimum number of bars between consecutive trades to avoid rapid trading in choppy conditions.
Pyramiding Support:
Up to 3 consecutive trades in the same direction are allowed, enabling traders to scale into positions based on strong signals.
Visual Indicators:
RSI Levels: Dotted lines at 45 and 55 for quick reference to oversold and overbought levels.
Buy and Sell Signals: Visual markers on the chart indicate where trades are executed, ensuring clarity on entry and exit points.
Best Used For:
Swing Trading & Scalping: While optimized for the 15-minute timeframe, this strategy works across various timeframes, making it suitable for both short-term scalping and swing trading.
Crypto Trading: Tailored for Ethereum but effective for other cryptocurrencies due to its dynamic indicator setup.
HMA Fibonacci Rainbow Waves[FibonacciFlux]HMA Fibonacci Rainbow Waves
Overview
The HMA Fibonacci Rainbow Waves script is designed for traders who strive for simplicity in their trading strategies while navigating the complexities of chart analysis. By utilizing the Hull Moving Average (HMA) for smoothing, this indicator provides a refined view of price action. However, over-smoothing can sometimes filter out essential market noise. To address this, the indicator incorporates a unique approach by applying Fibonacci weighting to seven HMA200 calculations. This enables traders to capture noise while effectively following market trends.
BTCUSDT 4hour
Key Features
1. Hull Moving Average (HMA)
- The HMA is known for its responsiveness and ability to filter out noise, providing a clear view of the underlying trend.
- The indicator balances smoothness with responsiveness, making it suitable for various trading styles, from day trading to swing trading and scalping.
2. Fibonacci Weighting
- By applying Fibonacci numbers to the HMA calculations, the indicator enhances its ability to adapt to market dynamics.
- This unique approach allows traders to maintain clarity while accommodating fluctuations in price action, ensuring they do not miss critical entry points.
3. Multi-Timeframe Functionality
- The HMA Fibonacci Rainbow Waves indicator operates effectively across multiple timeframes, including daily, 4-hour, 5-minute, and 1-minute charts.
- This adaptability makes it a valuable tool for traders, regardless of their preferred trading style, facilitating seamless transitions between different market conditions.
4. Noise Capture and Trend Following
- The indicator is designed to capture essential market movements while filtering out excessive noise.
- It helps traders follow trends without being overwhelmed by market fluctuations, allowing them to act on advantageous entry conditions that might otherwise be obscured.
Signal Generation and Alerts
- The indicator generates buy and sell signals based on the relationship between the HMAs, providing clear entry and exit points.
- Customizable alerts keep traders informed of significant changes in market conditions, enabling timely decisions that reflect the nuances of market behavior.
BTCUSDT 15min
Benefits
1. Simplified Trading Approach
- Traders can focus on core market movements without being distracted by excessive noise, enhancing decision-making efficiency and minimizing emotional trading.
2. Flexibility Across Timeframes
- The ability to function across different timeframes allows traders to apply the same principles in various trading scenarios, from quick scalps to strategic swing trades.
3. Enhanced Market Insights
- The combination of HMA smoothing and Fibonacci weighting offers a comprehensive view of market trends, aiding traders in identifying potential opportunities, including those that institutional investors might exploit.
4. Resolving Complexity with Simplicity
- This indicator elegantly bridges the gap between simplicity and complexity, providing a single tool that addresses the inherent contradictions in trading psychology. It allows traders to simplify their strategies while still capturing the dynamic nature of the market.
BTCUSDT 1min
Conclusion
The HMA Fibonacci Rainbow Waves script is a powerful tool for traders seeking to streamline their analysis while effectively capturing market dynamics. By integrating advanced smoothing techniques with Fibonacci weighting, this indicator empowers traders to follow market trends confidently across various timeframes. Its design makes it an essential asset for both novice and experienced traders alike, offering insights that can reveal entry points often missed by traditional indicators.
Open Source Collaboration
This script is released as an open-source project on TradingView, inviting the global trading community to contribute and enhance its functionality. By collaborating on this project, traders can help improve its capabilities, ensuring it remains a valuable resource for market participants around the world.
Important Note
As with any trading tool, it is crucial to conduct thorough analysis and risk management when using this indicator. Past performance does not guarantee future results, and traders should always be prepared for potential market fluctuations.
ADX with Donchian Channels
The "ADX with Donchian Channels" indicator combines the Average Directional Index (ADX) with Donchian Channels to provide traders with a powerful tool for identifying trends and potential breakouts.
Features:
Average Directional Index (ADX):
The ADX is used to quantify the strength of a trend. It helps traders determine whether a market is trending or ranging.
Adjustable parameters for ADX smoothing and DI length allow traders to fine-tune the sensitivity of the trend strength measurement.
Donchian Channels on ADX:
Donchian Channels are applied directly to the ADX values to highlight the highest high and lowest low of the ADX over a specified period.
The upper and lower Donchian Channels can signal potential trend breakouts when the ADX value moves outside these bounds.
The middle Donchian Channel provides a reference for the average trend strength.
Visualization:
The indicator plots the ADX line in red to clearly display the trend strength.
The upper and lower Donchian Channels are plotted in blue, with a green middle line to represent the average.
The area between the upper and lower Donchian Channels is filled with a blue shade to visually emphasize the range of ADX values.
Default Settings for Scalping:
Donchian Channel Length: 10
Standard Deviation Multiplier: 1.58
ADX Length: 2
ADX Smoothing Length: 2
These default settings are optimized for scalping, offering a quick response to changes in trend strength and potential breakout signals. However, traders can adjust these settings to suit different trading styles and market conditions.
How to Use:
Trend Strength Identification: Use the ADX line to identify the strength of the current trend. Higher ADX values indicate stronger trends.
Breakout Signals: Monitor the ADX value in relation to the Donchian Channels. A breakout above the upper channel or below the lower channel can signal a potential trend continuation or reversal.
Range Identification: The filled area between the Donchian Channels provides a visual representation of the ADX range, helping traders identify when the market is ranging or trending.
This indicator is designed to enhance your trading strategy by combining trend strength measurement with breakout signals, making it a versatile tool for various market conditions.
The Reaper WhistleThe Reaper Whistle is a high-precision RSI momentum system engineered for scalpers and intraday traders.
It combines a customizable RSI with a dynamic moving average signal line to detect micro-shifts in momentum, early reversals, and continuation setups with extreme speed.
The indicator includes five key zones used by liquidity and SMC-style traders:
• Strong Sell (90) – Extreme momentum exhaustion
• Sell (80) – Overextension area
• TP Zone (50) – Momentum balance / decision point
• Buy (20) – Discount area
• Strong Buy (10) – Extreme sell-side exhaustion
By tracking how RSI interacts with its MA inside these zones, traders can identify high-probability sniper entries on the 1m, 3m, and 5m charts.
⸻
⭐ HOW IT WORKS (Quick Breakdown)
• RSI Period: defines momentum sensitivity
• MA Period: smooths RSI noise and clarifies direction shifts
• MA Type: SMA, EMA, or WMA for different reaction speeds
• Crossovers: show momentum flips or trend continuation
• Zones: filter out weak signals and highlight only premium setups
⸻
⚡ STRATEGY EXAMPLES
1️⃣ Liquidity Sweep Reversal (Most Powerful Setup)
Use case: Gold, NAS100, NQ, US30
1. Price sweeps a previous high/low
2. RSI spikes into Strong Sell (90) or Strong Buy (10)
3. RSI crosses its MA back inside the zone
4. Enter on candle confirmation
5. TP at the next imbalance, VWAP, or volume cluster
This setup catches V-shaped reversals and trap plays.
⸻
2️⃣ Trend Continuation Pullback
Use case: Trending markets
1. Identify trend direction (EMA 200, structure, etc.)
2. Wait for RSI to pull back to the TP (50) zone
3. Watch for RSI crossing its MA in trend direction
4. Enter with trend
5. TP at previous swing high/low
This setup filters out weak pullbacks and catches clean momentum continuation.
⸻
3️⃣ Breakout Confirmation
Use case: Range breakouts, opening range breaks
1. Price breaks a consolidation high/low
2. RSI holds above Sell (80) in uptrend or below Buy (20) in downtrend
3. RSI crosses its MA with momentum
4. Enter breakout
5. TP at HTF zone or liquidity target
Perfect for fast markets like NAS100 and Bitcoin.
⸻
4️⃣ Divergence + Whistle Flip
Use case: Slow markets or pre-session moves
1. Look for bullish or bearish RSI divergence
2. Wait for RSI to cross the MA in direction of divergence
3. Enter once momentum confirms
4. TP at imbalance, FVG, or mid-range
This increases divergence accuracy dramatically.
⸻
🔥 RECOMMENDED SETTINGS
• Scalping (1m–3m):
• RSI: 5
• MA: 3
• Type: EMA
• Intraday 5m–15m:
• RSI: 7–14
• MA: 5
• Type: SMA
⸻
⭐ WHO IT’S BUILT FOR
• Liquidity + SMC traders
• Scalpers who need fast confirmation
• Traders who want clean, simple entries
• Beginners who want visual guidance
• Professionals who want momentum precision
The Reaper Whistle is intentionally designed for speed, clarity, and reliability — no clutter, no lag, just pure momentum read.
— Created by TheTrendSniper (ChartReaper)
“When the market whispers… the Reaper whistles.”
ROC Bot AlertsA rules-based momentum scalping framework for short-term index futures
This indicator is designed for traders who focus on fast-moving, intraday momentum opportunities—particularly on lower timeframes such as the 1-minute chart. It uses a structured combination of trend filters and short-term momentum tools to help identify potential continuation entries during active market conditions.
Core Concept
The tool evaluates price behavior relative to a dynamic trend line while measuring short-term rate-of-change and directional strength. When all components align, the indicator highlights moments where the market may be transitioning into or sustaining momentum in one direction. Conversely, when conditions deteriorate or momentum weakens, the indicator suppresses signals to reduce noise and avoid choppy environments.
This approach aims to provide buy/sell signals for scalping in trending or expanding-volatility conditions.
What the Indicator Uses
The system assesses several factors before confirming a potential momentum signal:
A dynamic trend filter to determine directional bias
A rate-of-change threshold to confirm short-term acceleration
A trend-strength component to avoid signals during low-energy or ranging conditions
A cooldown mechanism to prevent rapid, back-to-back signals in unsettled areas
Only when all conditions align does the indicator paint a long or short trigger on the chart.
Intended Use
This tool is best suited for:
- Active scalpers
- Intraday index futures traders (NQ, ES, GC, etc.)
- Short-duration momentum traders
- Traders who prefer clean, rules-based decision making
It is not designed for swing trading, long-term trend following, or counter-trend strategies.
How to Read the Signals
- Buy markers appear when trend, momentum, and strength all support upward continuation.
- Sell markers appear when these same factors align in the opposite direction.
- The 90-period trend line can be shown or hidden based on user preference, but it remains part of the decision framework internally.
- The user may optionally adjust the momentum threshold (ROC%) to suit different volatility environments.
Important Notes
Signals are generated only on completed bars.
As with all technical tools, this should be used alongside proper risk and trade management practices.
Hybrid Flow Master📊 Hybrid Flow Master - Professional Trading Indicator
Overview
Hybrid Flow Master is an advanced all-in-one trading indicator that combines Smart Money Concepts, institutional order flow analysis, and multi-timeframe confluence scoring to identify high-probability trade setups. Designed for both scalpers and swing traders across all markets (Forex, Crypto, Stocks, Indices).
🎯 Key Features
1. Intelligent Confluence System (0-100% Scoring) Proprietary scoring algorithm that weighs multiple factors Only signals when minimum confidence threshold is met
Real-time probability calculations for each setup Signal quality grading: A+, A, B, C ratings
2. Smart Money Concepts (SMC)
Automatic Order Block detection (bullish/bearish) Fair Value Gap (FVG) identification
Market structure analysis (Higher Highs, Lower Lows) Swing high/low tracking with visual markers
3. Multi-Timeframe Analysis
Higher timeframe trend filter for confluence Customizable HTF periods (1H, 4H, Daily, etc.)
Prevents counter-trend trades Aligns entries with major trends
4. Volume Flow Analysis
Volume spike detection with customizable thresholds Volume delta calculations (buying vs selling pressure) Institutional footprint identification Background highlighting for high-volume bars
5. Advanced Risk Management
ATR-based stop loss calculation Automatic take profit levels Customizable risk/reward ratios (1:1, 1:2, 1:3+) Visual SL/TP lines on chart Position sizing guidance
6. Professional Dashboard
Real-time HUD displaying:
Market bias (Bullish/Bearish/Neutral)
Higher timeframe trend status
Current confluence percentage
Volume status (Normal/High)
RSI reading with color coding
ATR volatility measure
Signal quality grade
7. Smart Alert System
Bullish confluence signals
Bearish confluence signals
Volume spike notifications
Customizable alert messages
Works with mobile app notifications
📈 What Makes It Unique?
✅ No Repainting - All signals are confirmed and final
✅ Probability-Based - Shows confidence level, not just binary signals
✅ Multi-Factor Confluence - Combines structure, volume, momentum, and HTF analysis
✅ Clean Interface - Toggle individual components on/off
✅ Works on All Timeframes - From 1-minute scalping to daily swing trading
✅ Universal Markets - Forex, Crypto, Stocks, Indices, Commodities
🎨 Customization Options
Adjustable swing detection length
Volume threshold settings
Minimum confluence score filter
Custom color schemes
Dashboard position (4 corners)
Show/hide individual components
Risk/reward ratio adjustment
ATR multiplier for stops
📊 Best Used For:
✔️ Scalping (1m - 15m charts)
✔️ Day Trading (15m - 1H charts)
✔️ Swing Trading (4H - Daily charts)
✔️ Trend Following
✔️ Reversal Trading
✔️ Breakout Trading
💡 How to Use:
Add indicator to chart - Works immediately with default settings Set your timeframe - Choose your trading style Wait for signals - Green BUY or Red SELL labels with confidence %
Check confluence score - Higher % = better quality setup Review dashboard - Confirm market bias and HTF trend Manage risk - Use provided SL/TP levels or adjust to your preference
Set alerts - Get notified of high-probability setups
⚙️ Recommended Settings:
For Scalping (1m-5m):
Swing Length: 5-7
Min Confluence: 70%
HTF: 15m or 1H
For Day Trading (15m-1H):
Swing Length: 10-15
Min Confluence: 60%
HTF: 4H or Daily
For Swing Trading (4H-Daily):
Swing Length: 15-20
Min Confluence: 50-60%
HTF: Weekly
📚 Indicator Components:
✦ Market Structure Detection
✦ Order Block Identification
✦ Fair Value Gaps (FVG)
✦ Volume Analysis
✦ RSI (14)
✦ MACD (12, 26, 9)
✦ ATR (14)
✦ Multi-Timeframe Trend
✦ Confluence Scoring Algorithm
🚀 Performance Notes:
Optimized for speed and efficiency Minimal CPU usage Clean chart presentation
Limited drawing objects (no chart clutter) Works on all TradingView plans
⚠️ Important Notes:
This indicator is a tool to assist trading decisions, not financial advice Always use proper risk management (1-2% per trade recommended) Backtest on your preferred market and timeframe
Combine with your own analysis and strategy Past performance does not guarantee future results
🔔 Alert Setup:
Right-click indicator name → "Add Alert" → Choose:
"Bullish Confluence Signal" for buy setups
"Bearish Confluence Signal" for sell setups
"Volume Spike Alert" for unusual activity
💬 Support:
For questions, suggestions, or custom modifications, feel free to message me directly through TradingView.
Gann Levels (Auto) by RRR📌 Gann Levels (Auto) — Intraday, Swing & Elliott Wave Precision Tool
Gann Levels (Auto) is a high-accuracy price-reaction indicator designed for intraday scalpers, swing traders, and Elliott Wave traders who want clean, auto-updating support and resistance levels without manually drawing anything.
The indicator automatically detects the latest swing high & swing low and plots the 8 Gann Octave Levels between them. These levels act as a complete price map—showing equilibrium, structure, trend continuation zones, and reversal points with extreme precision.
🔥 Why This Indicator Stands Out
✔ Fully automatic swing detection
Levels update as structure evolves — no manual adjustments.
✔ All Gann Octave levels
Plots 1/8 through 8/8 including the critical 4/8 midpoint.
✔ Intraday-optimized
Exceptional on 1m, 3m, 5m, and 15m charts.
✔ Ultra-clean support & resistance
Levels act as reliable barriers and breakout zones.
⭐ MOST IMPORTANT LEVELS FOR INTRADAY
4/8 – Midpoint (Major Decision Pivot)
Strongest Gann level.
Controls trend or reversal for the session.
Breakout → Trend Day
Rejection → Reversal Day
8/8 & 0/8 – Extreme Structure Edges
Most likely zones for intraday reversals.
Perfect for scalp entries when combined with volume exhaustion.
🎯 How to Trade ELLIOTT WAVE Using Gann Levels
This indicator is exceptionally powerful when combined with Elliott Wave Theory.
Here is how to use it wave-by-wave:
🔵 Wave 2 → Identify Bottom Using 0/8 or 1/8 Levels
Wave 2 typically retraces deep but remains above key structure.
Gann confirmation:
Price stops at 0/8 or 1/8 zone
Rejection wick + low volume breakdown attempt
Bullish intent starts forming
This gives a perfect Wave 3 entry zone.
🔴 Wave 3 → Breakout Above 4/8 Midpoint
Wave 3 is the strongest impulsive wave.
The 4/8 level works like a force-field.
Wave 3 confirmation:
Price breaks and retests 4/8
Strong volume
No deep pullbacks after break
This is one of the most reliable Elliott + Gann trades.
🟡 Wave 4 → Uses 3/8 or 5/8 as Support/Resistance
Wave 4 is corrective and shallow compared to Wave 2.
Gann alignment:
Wave 4 often consolidates between 3/8 and 5/8
Levels act like range boundaries
Avoid trading inside chop; wait for breakout
This gives perfect continuation entries for Wave 5.
🟣 Wave 5 → Ends Near 7/8 or 8/8 Extreme Zone
Wave 5 usually ends in overbought territory.
Gann confirmation:
Price hits 7/8 or 8/8
Momentum weakens
Divergence builds (RSI/MACD optional)
Last push = exhaustion
This is where reversals or major pullbacks begin.
💥 BONUS: Corrective Waves (A-B-C)
Wave A:
Often rejects from 4/8 or 5/8.
Wave B:
Typically trapped between 3/8–5/8.
Wave C:
Usually ends around 0/8 (for bullish trend)
or 8/8 (for bearish trend).
These zones give ultra-high confidence entries.
⚙️ Who This Indicator Is Perfect For
Elliott Wave traders
Intraday scalpers
Swing traders
Price action & structure traders
Traders who want automatic support-resistance levels
Traders who want clean, non-cluttered levels
⚠️ Disclaimer
This indicator is for educational purposes only.
Trading involves risk. Always use proper risk management.
HTF Candles Pro by MurshidFx# HTF Candles Pro by MurshidFx
## Professional Trading Indicator for Multi-Timeframe Market Structure Analysis
**HTF Candles Pro** is an advanced, open-source trading indicator that synthesizes Higher Timeframe (HTF) candle visualization with CISD (Change in State of Delivery) detection, providing comprehensive market structure analysis across multiple timeframes. Designed for traders at all experience levels—from scalpers to swing traders—this tool enables precise alignment of trades with higher timeframe momentum while identifying critical market structure transitions.
---
## Core Functionality
This indicator integrates three essential analytical frameworks:
- **HTF Candle Visualization** – Inspired by the innovative work of Fadi x MMT's MTF Candles indicator
- **CISD Detection System** – Algorithmic identification of significant market structure reversals
- **Intelligent Session Level Management** – Automated consolidation of overlapping session markers for enhanced chart clarity
The result is a sophisticated yet streamlined analytical tool that delivers actionable market insights with minimal visual complexity.
---
## Feature Set
### Higher Timeframe Candle Analysis
Monitor higher timeframe price action seamlessly without chart switching. The indicator employs automatic HTF selection based on current timeframe, with manual override capability.
**Components:**
- **Primary HTF Display**: Automatically positioned adjacent to current price action
- **Secondary HTF Display**: Optional dual-timeframe analysis capability
- **Adaptive Time Labeling**: Context-aware formatting (intraday times, day names, week numbers)
- **Real-Time Countdown**: Optional timer displaying remaining time until HTF candle close
- **Customizable Color Schemes**: Full color customization for bullish and bearish candles
### CISD Detection (Change in State of Delivery)
The CISD system identifies critical inflection points where market structure undergoes directional change, signaling potential trend reversals or continuations.
**Mechanism:**
- **Market Structure Monitoring**: Continuous tracking of swing highs and lows
- **Liquidity Sweep Detection**: Identification of stop-hunt patterns preceding reversals
- **Reversal Confirmation**: Validation-based CISD level plotting upon structure break confirmation
- **Clear Visual Signals**: Bullish CISD (blue) and bearish CISD (red) demarcation
- **Optimized Display**: Default 5-bar line length (adjustable) minimizes chart clutter
**Technical Definition:**
CISD occurs when price breaches structure in one direction—typically sweeping liquidity and triggering stops—then reverses to break structure in the opposite direction, indicating a fundamental shift in market delivery bias.
### Intelligent Session Level Management
Eliminates visual clutter caused by overlapping session opens at identical price levels through automated consolidation.
**Functionality:**
- **Automatic Consolidation**: Merges multiple concurrent session opens into single reference lines
- **Combined Labeling**: Creates unified labels (e.g., "Week-Day Open," "4H-Day-Week Open")
- **Enhanced Clarity**: Maintains professional chart aesthetics while preserving all relevant information
**Supported Session Intervals:**
- 30-Minute Opens
- 4-Hour Opens
- Daily Opens
- Weekly Opens
- Monthly Opens
### Advanced Market Structure Tools
**Liquidity Sweep Identification:**
Highlights price wicks extending beyond previous HTF extremes that close within range—characteristic liquidity grab patterns.
**HTF Midpoint Reference:**
Displays the 50% retracement level of the most recent completed HTF candle, serving as a key reference for entries and profit targets.
**HTF Opening Price:**
Tracks current HTF candle open price, frequently functioning as dynamic support or resistance.
**Interval Demarcation:**
Visual separators defining HTF period boundaries for enhanced temporal clarity.
### Information Dashboard
Compact, customizable dashboard displaying:
- Current symbol and active timeframe
- HTF candle countdown timer
- Active trading session (Asia/London/New York)
- Current date and time
Flexible positioning: configurable for any chart corner.
---
## Default Configuration
Optimized settings for immediate professional-grade chart presentation:
- **Secondary HTF**: Disabled (enable for multi-timeframe comparative analysis)
- **CISD Bullish Color**: Blue (#0080ff) – optimal visibility with reduced eye strain
- **CISD Line Width**: 1 pixel – subtle yet discernible
- **CISD Line Length**: 5 bars – balanced visibility without excessive clutter
- **Session Opens**: Smart consolidation enabled – eliminates overlapping labels
---
## Application Strategies
### Trend Following
1. Monitor CISD confirmations aligned with HTF trend direction
2. Utilize HTF candle color for directional bias confirmation
3. Execute entries on pullbacks to HTF midpoint or open price levels
### Reversal Trading
1. Identify counter-trend CISD formations
2. Await HTF candle close confirming new directional bias
3. Use session opens as secondary confirmation levels
### Scalping
1. Trade exclusively in HTF candle direction
2. Employ lower timeframe CISD signals for precise entry timing
3. Target HTF midpoint or subsequent session open levels
### Structure-Based Trading
1. Mark liquidity sweep levels as potential reversal zones
2. Monitor CISD formations at key session opens
3. Confirm trend changes via HTF candle closes
---
## Customization Parameters
Comprehensive customization options:
- **Color Schemes**: Independent control of bull/bear candles, borders, CISD signals, session levels
- **Dimensional Settings**: Candle width, line thickness, label sizing
- **Display Quantities**: HTF candle count (1-10 range)
- **Positioning**: Candle offset, dashboard placement, label positioning
- **Line Styles**: Solid, dashed, or dotted rendering
- **Timeframe Selection**: Manual secondary HTF specification
---
## Attribution
**HTF Candle Visualization:**
The HTF candle rendering methodology draws inspiration from Fadi x MMT's "MTF Candles" indicator. Their elegant implementation of multi-timeframe candle visualization provided valuable reference for this development. Recognition and appreciation to their contribution to the TradingView community.
**CISD Detection:**
Proprietary CISD detection algorithm engineered to identify market structure transitions with high signal clarity and reduced false positive rate.
**Session Level Consolidation:**
Custom-developed intelligent grouping system addressing the common challenge of overlapping session labels at coincident price levels.
---
## Open Source License
This indicator is released as open source for the TradingView community. Permitted uses include:
- Implementation in live trading
- Educational study for Pine Script learning
- Personal modification and customization
- Distribution among trading communities
Community contributions, improvements, and derivative works are welcomed and encouraged.
---
## Implementation Guide
1. **Installation**: Click "Add to Chart"
2. **Configuration Access**: Open indicator settings panel
3. **Initial Use**: Default settings provide optimal starting configuration
4. **Optional Features**: Enable secondary HTF for multi-timeframe analysis
5. **Theme Integration**: Adjust color schemes to match chart aesthetics
---
## Best Practices
**Timeframe Optimization:**
- 1-5 minute charts: Optimal with 15m or 1H HTF
- 15-30 minute charts: Effective with 4H HTF
- 1-4 hour charts: Suitable for Daily HTF
- Daily charts: Best utilized with Weekly/Monthly HTF
**CISD Trading Guidelines:**
- Require CISD confirmation before position entry
- Prioritize CISD signals at significant levels (session opens, HTF midpoints)
- Confirm CISD direction aligns with HTF candle bias
- Apply contextual filtering—not all CISD signals warrant trades
**Session Open Strategy:**
- Weekly opens typically provide robust support/resistance
- Daily opens offer reliable intraday reference points
- 4-Hour opens effective for short-term scalping
- Consolidated labels (e.g., "Week-Day Open") indicate confluence zones with elevated significance
---
## Technical Specifications
**Performance Optimization:**
- Intelligent object management prevents TradingView rendering limits
- Efficient array processing for session consolidation
- Proper memory management through systematic object deletion
- Consistent performance across all timeframe ranges
**Compatibility:**
- Universal timeframe support
- Optimized for all market types (forex, stocks, crypto, futures)
- Minimal computational overhead
---
## Support & Development
**Feedback Channels:**
- Comment section for user feedback and suggestions
- Bug reports and feature requests welcomed
- Community-driven enhancement consideration
**Documentation:**
- Well-commented source code for learning purposes
- Clear section organization for easy navigation
- Comprehensive type definitions for structural clarity
- Educational value for market structure concept understanding
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## Version Information
**Version:** 1.0 (Initial Release)
**License:** Open Source
**Category:** Multi-Timeframe Analysis | Market Structure
**Compatibility:** All Timeframes
**Language:** Pine Script v5
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**For optimal results:**
- Provide feedback through comments
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**Professional Support:**
Available through comment section for technical inquiries, implementation questions, and feature requests.
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*Developed for the TradingView trading community | Professional-grade market structure analysis | Open source contribution*
Multi EMA + Indicators + Mini-Dashboard + Reversals v6📘 Multi EMA + Indicators + Mini-Dashboard + Reversals v6
🧩 Overview
This indicator is a multi-EMA setup that combines trend, momentum, and reversal analysis in a single visual framework.
It integrates four exponential moving averages (EMAs), key oscillators (RSI, MACD, Stochastic, CCI), volatility filtering (ATR), and a dynamic mini-dashboard that summarizes all signals in real time.
Its purpose is to help traders visually confirm trend alignment, filter valid entries, and identify possible trend continuation or reversal points.
It can display buy/sell arrows, detect reversal candles, and issue alerts when trading conditions are met.
⚙️ Core Components
1. Moving Averages (EMA Setup)
EMA1 (fast) and EMA2 (medium) define the short-term trend and trigger bias.
When the price is above both EMAs → bullish bias.
When below → bearish bias.
EMA3 and EMA4 act as trend filters. Their slopes (up or down) confirm overall momentum and help validate signals.
Each EMA has customizable lengths, sources, and colors for up/down trends.
This “EMA stack” is the foundation of the setup — a structured trend-following framework that adapts to market speed and volatility.
2. Momentum and Confirmation Filters
Each indicator can be individually enabled or disabled for flexibility.
RSI: confirms direction (above/below 50).
MACD: detects momentum crossover (MACD > Signal for bullish confirmation).
Stochastic: identifies trend continuation (K > D for longs, K < D for shorts).
CCI: adds trend bias above/below a threshold.
ATR Filter: filters out small, low-volatility candles to reduce noise.
You can activate only the filters that fit your trading plan — for instance, trend traders often use RSI and MACD, while scalpers may rely on Stochastic and ATR.
3. Reversal Detection
The indicator includes an optional Reversal Section that independently detects potential turning points.
It combines multiple configurable criteria:
Candlestick patterns (Bullish Hammer, Shooting Star).
Large Candle filter — detects unusually large bars (relative to close).
Price-to-EMA distance — identifies overextended moves that might revert.
RSI Divergence — detects potential momentum shifts.
RSI Overbought/Oversold zones (70/30 by default).
Doji Candles — sign of indecision.
A bullish or bearish reversal signal appears when enough selected criteria are met.
All sub-modules can be toggled on/off individually, giving you full control over sensitivity.
4. Signal Logic
Buy and sell signals are triggered when EMA alignment and the chosen confirmations agree:
Buy Signal
→ Price above EMA1 & EMA2
→ Confirmations (RSI/MACD/Stoch/CCI/ATR) pass
→ Trend filters (EMA3/EMA4) point upward
Sell Signal
→ Price below EMA1 & EMA2
→ Confirmations align bearishly
→ Trend filters (EMA3/EMA4) slope downward
Reversal signals can appear independently, even against the current EMA trend, depending on your settings.
5. Visual Dashboard
A mini-dashboard appears near the chart showing:
Current trade bias (LONG / SHORT / NEUTRAL)
EMA3 and EMA4 trend directions (↑ / ↓)
Quick visual bars (🟩 / 🟥) for each filter: RSI, MACD, Stoch, ATR, CCI, EMA filters
Reversal criteria status (Doji, RSI divergence, candle size, etc.)
This panel gives you a compact overview of all indicator states at a glance.
The color of the panel changes dynamically — green for bullish, red for bearish, gray for neutral.
6. Alerts
Built-in alerts allow automation or notifications:
Buy Alert
Sell Alert
Reversal Buy
Reversal Sell
You can connect these alerts to TradingView notifications or external bots for semi-automated execution.
💡 How to Use
✅ Trend-Following Setup
Focus on trades in the direction of EMA1 & EMA2.
Confirm with EMA3 & EMA4 trending in the same direction.
Use RSI/MACD/Stoch filters to ensure momentum supports the trade.
Avoid entries when ATR filter indicates low volatility.
🔄 Reversal Setup
Enable the Reversal section for potential tops/bottoms.
Look for reversal buy signals near support zones or after strong downtrends.
Use RSI divergence or Doji + Hammer signals as confirmation.
Combine with key chart areas (supply/demand or previous swing levels).
⚖️ Combination Approach
Trade continuation signals when all EMAs are aligned and filters are green.
Trade reversals only when at a key area (support/resistance) and confirmed by reversal conditions.
Always check higher-timeframe bias before entering a trade.
🧭 Practical Tips
Use different EMA sets for different timeframes:
9/21/50/100 for swing or trend trades.
5/13/34/89 for intraday scalping.
Turn off filters you don’t use to reduce lag.
Always validate signals with price structure, not just indicator alignment.
Practice in replay mode before live trading.
🗺️ Key Chart Confluence (Highly Recommended)
Although the indicator provides structured signals, its best use is in confluence with:
Support and resistance levels
Supply/demand zones
Trendlines and channels
Liquidity pools
Volume clusters
Signals aligned with strong key areas on the chart tend to have greater reliability than isolated indicator triggers.
I use EMA 1 - 20 Open ; EMA 2 - 20 Close ; EMA 3 - 50 ; EMA 4 - 200 or 100 , but that's me...
⚠️ Important Disclaimer
This indicator is a technical tool, not a guarantee of results.
Trading involves risk, and no signal is ever 100% accurate.
Every trader should develop a personal strategy, use proper risk management, and adapt settings to their instrument and timeframe.
Always combine indicator signals with key chart areas, higher-timeframe context, and your own analysis before taking a trade.
Daily MA — Higher-Timeframe Daily Moving Average OverlayThis indicator plots a clean, higher-timeframe daily moving average directly on any chart, so you can always see where price sits relative to the daily trend — even while trading on lower timeframes (1m, 5m, etc.).
It’s designed to be:
Simple – a single, configurable daily MA line
Consistent – always anchored to the 1D timeframe
Flexible – choose EMA or SMA and customize line width/color
⸻
What This Indicator Does
Pulls the 1-Day (1D) moving average of the current symbol, regardless of your chart timeframe.
Lets you choose between EMA (Exponential Moving Average) or SMA (Simple Moving Average).
Plots that daily MA as a smooth overlay on your current chart.
Keeps the line visually clean and continuous, making it easy to see daily trend and dynamic support/resistance.
This is not a signals/strategy script. It doesn’t generate buy/sell arrows or backtest logic. It’s a context tool for visualizing the daily trend while you execute your own strategy.
⸻
Why a Daily MA Overlay Is Useful
Traders commonly use a daily moving average to:
Anchor intraday trades to the higher-timeframe trend
Longs when price is holding above the Daily MA
Shorts or caution when price is rejecting from the Daily MA
Identify dynamic support/resistance
Price often reacts around well-watched daily MAs (e.g., 50, 100, 200)
Filter setups
Only take long setups when price is above the daily trend line
Avoid counter-trend trades when price is extended far from the Daily MA
Because this script forces the MA to always be computed on 1D, you don’t have to switch back and forth between intraday and daily charts to keep track of the bigger picture.
⸻
Inputs & Settings
MA Length
Default: 200
Any positive integer (min 1)
Common examples: 50, 100, 200 for trend structure
MA Type
EMA – reacts faster to recent price (default)
SMA – smoother, slower, more “classic” feel
Line Width
Default: 2
Range: 1 to 10
Increase if you want the Daily MA to stand out clearly against other indicators
Color
Default: Purple tone
Fully customizable – pick any color that works with your chart theme
⸻
How to Use It in Your Workflow
Intraday traders (scalpers/day-traders):
Apply the indicator to your 1m/5m/15m charts.
Use the Daily MA as a trend filter :
Only look for long scalps when price is above the Daily MA.
Be more cautious with longs or consider shorts when price is below it.
Swing traders :
Use it on 1H/4H charts to see where price sits relative to a longer-term daily trend.
Watch for:
Pullbacks to the Daily MA in an uptrend as potential demand zones.
Rejections at the Daily MA in a downtrend as potential supply zones.
Risk management & context :
Avoid chasing extended moves far from the Daily MA.
Mark confluence with other tools (support/resistance, volume profile, etc.) around the Daily MA.
⸻
Notes & Limitations
The moving average itself is calculated from daily candles , then displayed on your current timeframe.
This is a visual aid only . It does not guarantee future performance or provide financial advice.
Always combine this indicator with your own analysis, risk management, and trading plan.
⸻
Disclaimer :
This script is provided for educational and informational purposes only. It is not financial advice and does not constitute a recommendation to buy or sell any financial instrument. Always do your own research and trade at your own risk.
Victoria Overlay - HTF 200 + VWAP + ATR Stop + MA TrioConsolidated road to minions
Buy Setup:
EMA1 crosses above SMA3.
RSI confirms above 50.
Volume increasing (confirming momentum).
Candle closes above SMA1 base.
Sell Setup:
EMA1 crosses below SMA3.
RSI drops below 50 or exits overbought.
Volume confirms (declining or reversing).
Candle closes below SMA1 base.
Tips:
Think of EMA1 as the scalper’s trigger.
SMA3 is your momentum check.
SMA1 (base) = short-term bias.
Avoid entries during low-volume chop.
Use for day trades or tight scalps; exits happen fast.
Overlay (Smoothed Heikin Ashi + Swing + VWAP + ATR Stop + 200-SMA)
Purpose: Multi-layer trend confirmation + clean structure.
Type: Swing alignment tool.
🟩 BUY / CALL Conditions
Green “Buy (Gated)” arrow appears.
Price is above VWAP, above 200-SMA, and above ATR stop.
ATR stop (green line) sits under price → support confirmed.
Heikin-Ashi candles are green/lime.
Bias label says “Above VWAP | Above 200 | Swing Up”.
🟥 SELL / PUT Conditions
Red “Sell (Gated)” arrow appears.
Price is below VWAP, below 200-SMA, and below ATR stop.
ATR stop (red line) sits above price → resistance confirmed.
Heikin-Ashi candles are red.
Bias label says “Below VWAP | Below 200 | Swing Down”.
Exit / Risk Control:
Close position when price crosses ATR stop.
If Heikin candles flip color, momentum is reversing.
Best Use Cases:
For next-day or multi-hour swing entries.
Use ATR Stop for dynamic stop loss.
Stay out when the bias label is mixed (e.g. “Above VWAP | Below 200 | Swing Down”).
Pro Tip:
On big news days, let VWAP reset post-open before acting on arrows — filters fake signals.
RSI Panel Pro (v6)
Purpose: Strength + exhaustion confirmation.
Type: Momentum filter.
Key Levels:
Overbought: 80+ → take profits soon.
Oversold: 20– → watch for bounce setups.
Bull regime: RSI above 60 = momentum strong.
Bear regime: RSI below 40 = weakness.
Buy / Entry Signals:
RSI crosses up from below 40 or 20.
RSI line is above RSI-EMA (gray line).
Higher timeframe RSI (if used) is also rising.
Trim / Exit:
RSI drops under 60 after being strong.
RSI crosses below its EMA.
Sell / Put Setup:
RSI fails at 60 or drops below 40.
RSI crosses under EMA after a bounce.
Tips:
Pair RSI panel with Victoria Overlay — only take gated buys when RSI confirms.
RSI < 40 but above 20 = “loading zone” for reversals.
RSI > 70 = overextended → wait for confirmation before entering.
Combined Execution Rules
Goal What to Watch Action
Entry (CALL) EMA1 > SMA3, Buy (Gated) arrow, RSI rising > 50 Buy call / open long
Entry (PUT) EMA1 < SMA3, Sell (Gated) arrow, RSI < 50 Buy put / open short
Exit Early Price crosses ATR stop or RSI flips under EMA Exit trade / protect gains
Trend Filter VWAP + 200-SMA alignment Only trade in that direction
Avoid Trades Conflicting bias label or low volume Stay flat
Pro Tips
VWAP → Intraday mean: above = bullish control, below = bearish control.
ATR Stop → Dynamic trailing stop: never widen it manually.
Smoothed Heikin-Ashi → filters noise: trend stays until color flips twice.
RSI Panel → confirms whether to hold through pullbacks.
If RSI and Overlay disagree — wait, not trade.
COT IndexTHE HIDDEN INTELLIGENCE IN FUTURES MARKETS
What if you could see what the smartest players in the futures markets are doing before the crowd catches on? While retail traders chase momentum indicators and moving averages, obsess over Japanese candlestick patterns, and debate whether the RSI should be set to fourteen or twenty-one periods, institutional players leave footprints in the sand through their mandatory reporting to the Commodity Futures Trading Commission. These footprints, published weekly in the Commitment of Traders reports, have been hiding in plain sight for decades, available to anyone with an internet connection, yet remarkably few traders understand how to interpret them correctly. The COT Index indicator transforms this raw institutional positioning data into actionable trading signals, bringing Wall Street intelligence to your trading screen without requiring expensive Bloomberg terminals or insider connections.
The uncomfortable truth is this: Most retail traders operate in a binary world. Long or short. Buy or sell. They apply technical analysis to individual positions, constrained by limited capital that forces them to concentrate risk in single directional bets. Meanwhile, institutional traders operate in an entirely different dimension. They manage portfolios dynamically weighted across multiple markets, adjusting exposure based on evolving market conditions, correlation shifts, and risk assessments that retail traders never see. A hedge fund might be simultaneously long gold, short oil, neutral on copper, and overweight agricultural commodities, with position sizes calibrated to volatility and portfolio Greeks. When they increase gold exposure from five percent to eight percent of portfolio allocation, this rebalancing decision reflects sophisticated analysis of opportunity cost, risk parity, and cross-market dynamics that no individual chart pattern can capture.
This portfolio reweighting activity, multiplied across hundreds of institutional participants, manifests in the aggregate positioning data published weekly by the CFTC. The Commitment of Traders report does not show individual trades or strategies. It shows the collective footprint of how actual commercial hedgers and large speculators have allocated their capital across different markets. When mining companies collectively increase forward gold sales to hedge thirty percent more production than last quarter, they are not reacting to a moving average crossover. They are making strategic allocation decisions based on production forecasts, cost structures, and price expectations derived from operational realities invisible to outside observers. This is portfolio management in action, revealed through positioning data rather than price charts.
If you want to understand how institutional capital actually flows, how sophisticated traders genuinely position themselves across market cycles, the COT report provides a rare window into that hidden world. But understand what you are getting into. This is not a tool for scalpers seeking confirmation of the next five-minute move. This is not an oscillator that flashes oversold at market bottoms with convenient precision. COT analysis operates on a timescale measured in weeks and months, revealing positioning shifts that precede major market turns but offer no precision timing. The data arrives three days stale, published only once per week, capturing strategic positioning rather than tactical entries.
If you need instant gratification, if you trade intraday moves, if you demand mechanical signals with ninety percent accuracy, close this document now. COT analysis rewards patience, position sizing discipline, and tolerance for being early. It punishes impatience, overleveraging, and the expectation that any single indicator can substitute for market understanding.
The premise is deceptively simple. Every Tuesday, large traders in futures markets must report their positions to the CFTC. By Friday afternoon, this data becomes public. Academic research spanning three decades has consistently shown that not all market participants are created equal. Some traders consistently profit while others consistently lose. Some anticipate major turning points while others chase trends into exhaustion. Bessembinder and Chan (1992) demonstrated in their seminal study that commercial hedgers, those with actual exposure to the underlying commodity or financial instrument, possess superior forecasting ability compared to speculators. Their research, published in the Journal of Finance, found statistically significant predictive power in commercial positioning, particularly at extreme levels. This finding challenged the efficient market hypothesis and opened the door to a new approach to market analysis based on positioning rather than price alone.
Think about what this means. Every week, the government publishes a report showing you exactly how the most informed market participants are positioned. Not their opinions. Not their predictions. Their actual money at risk. When agricultural producers collectively hold their largest short hedge in five years, they are not making idle speculation. They are locking in prices for crops they will harvest, informed by private knowledge of weather conditions, soil quality, inventory levels, and demand expectations invisible to outside observers. When energy companies aggressively hedge forward production at current prices, they reveal information about expected supply that no analyst report can capture. This is not technical analysis based on past prices. This is not fundamental analysis based on publicly available data. This is behavioral analysis based on how the smartest money is actually positioned, how institutions allocate capital across portfolios, and how those allocation decisions shift as market conditions evolve.
WHY SOME TRADERS KNOW MORE THAN OTHERS
Building on this foundation, Sanders, Boris and Manfredo (2004) conducted extensive research examining the behaviour patterns of different trader categories. Their work, which analyzed over a decade of COT data across multiple commodity markets, revealed a fascinating dynamic that challenges much of what retail traders are taught. Commercial hedgers consistently positioned themselves against market extremes, buying when speculators were most bearish and selling when speculators reached peak bullishness. The contrarian positioning of commercials was not random noise but rather reflected their superior information about supply and demand fundamentals. Meanwhile, large speculators, primarily hedge funds and commodity trading advisors, exhibited strong trend-following behaviour that often amplified market moves beyond fundamental values. Small traders, the retail participants, consistently entered positions late in trends, frequently near turning points, making them reliable contrary indicators.
Wang (2003) extended this research by demonstrating that the predictive power of commercial positioning varies significantly across different commodity sectors. His analysis of agricultural commodities showed particularly strong forecasting ability, with commercial net positions explaining up to fifteen percent of return variance in subsequent weeks. This finding suggests that the informational advantages of hedgers are most pronounced in markets where physical supply and demand fundamentals dominate, as opposed to purely financial markets where information asymmetries are smaller. When a corn farmer hedges six months of expected harvest, that decision incorporates private observations about rainfall patterns, crop health, pest pressure, and local storage capacity that no distant analyst can match. When an oil refinery hedges crude oil purchases and gasoline sales simultaneously, the spread relationships reveal expectations about refining margins that reflect operational realities invisible in public data.
The theoretical mechanism underlying these empirical patterns relates to information asymmetry and different participant motivations. Commercial hedgers engage in futures markets not for speculative profit but to manage business risks. An agricultural producer selling forward six months of expected harvest is not making a bet on price direction but rather locking in revenue to facilitate financial planning and ensure business viability. However, this hedging activity necessarily incorporates private information about expected supply, inventory levels, weather conditions, and demand trends that the hedger observes through their commercial operations (Irwin and Sanders, 2012). When aggregated across many participants, this private information manifests in collective positioning.
Consider a gold mining company deciding how much forward production to hedge. Management must estimate ore grades, recovery rates, production costs, equipment reliability, labor availability, and dozens of other operational variables that determine whether locking in prices at current levels makes business sense. If the industry collectively hedges more aggressively than usual, it suggests either exceptional production expectations or concern about sustaining current price levels or combination of both. Either way, this positioning reveals information unavailable to speculators analyzing price charts and economic data. The hedger sees the physical reality behind the financial abstraction.
Large speculators operate under entirely different incentives and constraints. Commodity Trading Advisors managing billions in assets typically employ systematic, trend-following strategies that respond to price momentum rather than fundamental supply and demand. When crude oil rallies from sixty dollars to seventy dollars per barrel, these systems generate buy signals. As the rally continues to eighty dollars, position sizes increase. The strategy works brilliantly during sustained trends but becomes a liability at reversals. By the time oil reaches ninety dollars, trend-following funds are maximally long, having accumulated positions progressively throughout the rally. At this point, they represent not smart money anticipating further gains but rather crowded money vulnerable to reversal. Sanders, Boris and Manfredo (2004) documented this pattern across multiple energy markets, showing that extreme speculator positioning typically marked late-stage trend exhaustion rather than early-stage trend development.
Small traders, the retail participants who fall below reporting thresholds, display the weakest forecasting ability. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns, meaning their aggregate positioning served as a reliable contrary indicator. The explanation combines several factors. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, entering trends after mainstream media coverage when institutional participants are preparing to exit. Perhaps most importantly, they trade with emotion, buying into euphoria and selling into panic at precisely the wrong times.
At major turning points, the three groups often position opposite each other with commercials extremely bearish, large speculators extremely bullish, and small traders piling into longs at the last moment. These high-divergence environments frequently precede increased volatility and trend reversals. The insiders with business exposure quietly exit as the momentum traders hit maximum capacity and retail enthusiasm peaks. Within weeks, the reversal begins, and positions unwind in the opposite sequence.
FROM RAW DATA TO ACTIONABLE SIGNALS
The COT Index indicator operationalizes these academic findings into a practical trading tool accessible through TradingView. At its core, the indicator normalizes net positioning data onto a zero to one hundred scale, creating what we call the COT Index. This normalization is critical because absolute position sizes vary dramatically across different futures contracts and over time. A commercial trader holding fifty thousand contracts net long in crude oil might be extremely bullish by historical standards, or it might be quite neutral depending on the context of total market size and historical ranges. Raw position numbers mean nothing without context. The COT Index solves this problem by calculating where current positioning stands relative to its range over a specified lookback period, typically two hundred fifty-two weeks or approximately five years of weekly data.
The mathematical transformation follows the methodology originally popularized by legendary trader Larry Williams, though the underlying concept appears in statistical normalization techniques across many fields. For any given trader category, we calculate the highest and lowest net position values over the lookback period, establishing the historical range for that specific market and trader group. Current positioning is then expressed as a percentage of this range, where zero represents the most bearish positioning ever seen in the lookback window and one hundred represents the most bullish extreme. A reading of fifty indicates positioning exactly in the middle of the historical range, suggesting neither extreme optimism nor pessimism relative to recent history (Williams and Noseworthy, 2009).
This index-based approach allows for meaningful comparison across different markets and time periods, overcoming the scaling problems inherent in analyzing raw position data. A commercial index reading of eighty-five in gold carries the same interpretive meaning as an eighty-five reading in wheat or crude oil, even though the absolute position sizes differ by orders of magnitude. This standardization enables systematic analysis across entire futures portfolios rather than requiring market-specific expertise for each contract.
The lookback period selection involves a fundamental tradeoff between responsiveness and stability. Shorter lookback periods, perhaps one hundred twenty-six weeks or approximately two and a half years, make the index more sensitive to recent positioning changes. However, it also increases noise and produces more false signals. Longer lookback periods, perhaps five hundred weeks or approximately ten years, create smoother readings that filter short-term noise but become slower to recognize regime changes. The indicator settings allow users to adjust this parameter based on their trading timeframe, risk tolerance, and market characteristics.
UNDERSTANDING CFTC DATA STRUCTURES
The indicator supports both Legacy and Disaggregated COT report formats, reflecting the evolution of CFTC reporting standards over decades of market development. Legacy reports categorize market participants into three broad groups: commercial traders (hedgers with underlying business exposure), non-commercial traders (large speculators seeking profit without commercial interest), and non-reportable traders (small speculators below reporting thresholds). Each category brings distinct motivations and information advantages to the market (CFTC, 2020).
The Disaggregated reports, introduced in September 2009 for physical commodity markets, provide finer granularity by splitting participants into five categories (CFTC, 2009). Producer and merchant positions capture those actually producing, processing, or merchandising the physical commodity. Swap dealers represent financial intermediaries facilitating derivative transactions for clients. Managed money includes commodity trading advisors and hedge funds executing systematic or discretionary strategies. Other reportables encompasses diverse participants not fitting the main categories. Small traders remain as the fifth group, representing retail participation.
This enhanced categorization reveals nuances invisible in Legacy reports, particularly distinguishing between different types of institutional capital and their distinct behavioural patterns. The indicator automatically detects which report type is appropriate for each futures contract and adjusts the display accordingly.
Importantly, Disaggregated reports exist only for physical commodity futures. Agricultural commodities like corn, wheat, and soybeans have Disaggregated reports because clear producer, merchant, and swap dealer categories exist. Energy commodities like crude oil and natural gas similarly have well-defined commercial hedger categories. Metals including gold, silver, and copper also receive Disaggregated treatment (CFTC, 2009). However, financial futures such as equity index futures, Treasury bond futures, and currency futures remain available only in Legacy format. The CFTC has indicated no plans to extend Disaggregated reporting to financial futures due to different market structures and participant categories in these instruments (CFTC, 2020).
THE BEHAVIORAL FOUNDATION
Understanding which trader perspective to follow requires appreciation of their distinct trading styles, success rates, and psychological profiles. Commercial hedgers exhibit anticyclical behaviour rooted in their fundamental knowledge and business imperatives. When agricultural producers hedge forward sales during harvest season, they are not speculating on price direction but rather locking in revenue for crops they will harvest. Their business requires converting volatile commodity exposure into predictable cash flows to facilitate planning and ensure survival through difficult periods. Yet their aggregate positioning reveals valuable information because these hedging decisions incorporate private information about supply conditions, inventory levels, weather observations, and demand expectations that hedgers observe through their commercial operations (Bessembinder and Chan, 1992).
Consider a practical example from energy markets. Major oil companies continuously hedge portions of forward production based on price levels, operational costs, and financial planning needs. When crude oil trades at ninety dollars per barrel, they might aggressively hedge the next twelve months of production, locking in prices that provide comfortable profit margins above their extraction costs. This hedging appears as short positioning in COT reports. If oil rallies further to one hundred dollars, they hedge even more aggressively, viewing these prices as exceptional opportunities to secure revenue. Their short positioning grows increasingly extreme. To an outside observer watching only price charts, the rally suggests bullishness. But the commercial positioning reveals that the actual producers of oil find these prices attractive enough to lock in years of sales, suggesting skepticism about sustaining even higher levels. When the eventual reversal occurs and oil declines back to eighty dollars, the commercials who hedged at ninety and one hundred dollars profit while speculators who chased the rally suffer losses.
Large speculators or managed money traders operate under entirely different incentives and constraints. Their systematic, momentum-driven strategies mean they amplify existing trends rather than anticipate reversals. Trend-following systems, the most common approach among large speculators, by definition require confirmation of trend through price momentum before entering positions (Sanders, Boris and Manfredo, 2004). When crude oil rallies from sixty dollars to eighty dollars per barrel over several months, trend-following algorithms generate buy signals based on moving average crossovers, breakouts, and other momentum indicators. As the rally continues, position sizes increase according to the systematic rules.
However, this approach becomes a liability at turning points. By the time oil reaches ninety dollars after a sustained rally, trend-following funds are maximally long, having accumulated positions progressively throughout the move. At this point, their positioning does not predict continued strength. Rather, it often marks late-stage trend exhaustion. The psychological and mechanical explanation is straightforward. Trend followers by definition chase price momentum, entering positions after trends establish rather than anticipating them. Eventually, they become fully invested just as the trend nears completion, leaving no incremental buying power to sustain the rally. When the first signs of reversal appear, systematic stops trigger, creating a cascade of selling that accelerates the downturn.
Small traders consistently display the weakest track record across academic studies. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns in his analysis across multiple commodity markets. This result means that whatever small traders collectively do, the opposite typically proves profitable. The explanation for small trader underperformance combines several factors documented in behavioral finance literature. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, learning about commodity trends through mainstream media coverage that arrives after institutional participants have already positioned. Perhaps most importantly, retail traders are more susceptible to emotional decision-making, buying into euphoria and selling into panic at precisely the wrong times (Tharp, 2008).
SETTINGS, THRESHOLDS, AND SIGNAL GENERATION
The practical implementation of the COT Index requires understanding several key features and settings that users can adjust to match their trading style, timeframe, and risk tolerance. The lookback period determines the time window for calculating historical ranges. The default setting of two hundred fifty-two bars represents approximately one year on daily charts or five years on weekly charts, balancing responsiveness with stability. Conservative traders seeking only the most extreme, highest-probability signals might extend the lookback to five hundred bars or more. Aggressive traders seeking earlier entry and willing to accept more false positives might reduce it to one hundred twenty-six bars or even less for shorter-term applications.
The bullish and bearish thresholds define signal generation levels. Default settings of eighty and twenty respectively reflect academic research suggesting meaningful information content at these extremes. Readings above eighty indicate positioning in the top quintile of the historical range, representing genuine extremes rather than temporary fluctuations. Conversely, readings below twenty occupy the bottom quintile, indicating unusually bearish positioning (Briese, 2008).
However, traders must recognize that appropriate thresholds vary by market, trader category, and personal risk tolerance. Some futures markets exhibit wider positioning swings than others due to seasonal patterns, volatility characteristics, or participant behavior. Conservative traders seeking high-probability setups with fewer signals might raise thresholds to eighty-five and fifteen. Aggressive traders willing to accept more false positives for earlier entry could lower them to seventy-five and twenty-five.
The key is maintaining meaningful differentiation between bullish, neutral, and bearish zones. The default settings of eighty and twenty create a clear three-zone structure. Readings from zero to twenty represent bearish territory where the selected trader group holds unusually bearish positions. Readings from twenty to eighty represent neutral territory where positioning falls within normal historical ranges. Readings from eighty to one hundred represent bullish territory where the selected trader group holds unusually bullish positions.
The trading perspective selection determines which participant group the indicator follows, fundamentally shaping interpretation and signal meaning. For counter-trend traders seeking reversal opportunities, monitoring commercial positioning makes intuitive sense based on the academic research discussed earlier. When commercials reach extreme bearish readings below twenty, indicating unprecedented short positioning relative to recent history, they are effectively betting against the crowd. Given their informational advantages demonstrated by Bessembinder and Chan (1992), this contrarian stance often precedes major bottoms.
Trend followers might instead monitor large speculator positioning, but with inverted logic compared to commercials. When managed money reaches extreme bullish readings above eighty, the trend may be exhausting rather than accelerating. This seeming paradox reflects their late-cycle participation documented by Sanders, Boris and Manfredo (2004). Sophisticated traders thus use speculator extremes as fade signals, entering positions opposite to speculator consensus.
Small trader monitoring serves primarily as a contrary indicator for all trading styles. Extreme small trader bullishness above seventy-five or eighty typically warns of retail FOMO at market tops. Extreme small trader bearishness below twenty or twenty-five often marks capitulation bottoms where the last weak hands have sold.
VISUALIZATION AND USER INTERFACE
The visual design incorporates multiple elements working together to facilitate decision-making and maintain situational awareness during active trading. The primary COT Index line plots in bold with adjustable line width, defaulting to two pixels for clear visibility against busy price charts. An optional glow effect, controlled by a simple toggle, adds additional visual prominence through multiple plot layers with progressively increasing transparency and width.
A twenty-one period exponential moving average overlays the index line, providing trend context for positioning changes. When the index crosses above its moving average, it signals accelerating bullish sentiment among the selected trader group regardless of whether absolute positioning is extreme. Conversely, when the index crosses below its moving average, it signals deteriorating sentiment and potentially the beginning of a reversal in positioning trends.
The EMA provides a dynamic reference line for assessing positioning momentum. When the index trades far above its EMA, positioning is not only extreme in absolute terms but also building with momentum. When the index trades far below its EMA, positioning is contracting or reversing, which may indicate weakening conviction even if absolute levels remain elevated.
The data table positioned at the top right of the chart displays eleven metrics for each trader category, transforming the indicator from a simple index calculation into an analytical dashboard providing multidimensional market intelligence. Beyond the COT Index itself, users can monitor positioning extremity, which measures how unusual current levels are compared to historical norms using statistical techniques. The extremity metric clarifies whether a reading represents the ninety-fifth or ninety-ninth percentile, with values above two standard deviations indicating genuinely exceptional positioning.
Market power quantifies each group's influence on total open interest. This metric expresses each trader category's net position as a percentage of total market open interest. A commercial entity holding forty percent of total open interest commands significantly more influence than one holding five percent, making their positioning signals more meaningful.
Momentum and rate of change metrics reveal whether positions are building or contracting, providing early warning of potential regime shifts. Position velocity measures the rate of change in positioning changes, effectively a second derivative providing even earlier insight into inflection points.
Sentiment divergence highlights disagreements between commercial and speculative positioning. This metric calculates the absolute difference between normalized commercial and large speculator index values. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals.
The table also displays concentration metrics when available, showing how positioning is distributed among the largest handful of traders in each category. High concentration indicates a few dominant players controlling most of the positioning, while low concentration suggests broad-based participation across many traders.
THE ALERT SYSTEM AND MONITORING
The alert system, comprising five distinct alert conditions, enables systematic monitoring of dozens of futures markets without constant screen watching. The bullish and bearish COT signal alerts trigger when the index crosses user-defined thresholds, indicating the selected trader group has reached extreme positioning worthy of attention. These alerts fire in real-time as new weekly COT data publishes, typically Friday afternoon following the Tuesday measurement date.
Extreme positioning alerts fire at ninety and ten index levels, representing the top and bottom ten percent of the historical range, warning of particularly stretched readings that historically precede reversals with high probability. When commercials reach a COT Index reading below ten, they are expressing their most bearish stance in the entire lookback period.
The data staleness alert notifies users when COT reports have not updated for more than ten days, preventing reliance on outdated information for trading decisions. Government shutdowns or federal holidays can interrupt the normal Friday publication schedule. Using stale signals while believing them current creates dangerous false confidence.
The indicator's watermark information display positioned in the bottom right corner provides essential context at a glance. This persistent display shows the symbol and timeframe, the COT report date timestamp, days since last update, and the current signal state. A trader analyzing a potential short entry in crude oil can glance at the watermark to instantly confirm positioning context without interrupting analysis flow.
LIMITATIONS AND REALISTIC EXPECTATIONS
Practical application requires understanding both the indicator's considerable strengths and inherent limitations. COT data inherently lags price action by three days, as Tuesday positions are not published until Friday afternoon. This delay means the indicator cannot catch rapid intraday reversals or respond to surprise news events. Traders using the COT Index for timing entries must accept this latency and focus on swing trading and position trading timeframes where three-day lags matter less than in day trading or scalping.
The weekly publication schedule similarly makes the indicator unsuitable for short-term trading strategies requiring immediate feedback. The COT Index works best for traders operating on weekly or longer timeframes, where positioning shifts measured in weeks and months align with trading horizon.
Extreme COT readings can persist far longer than typical technical indicators suggest, testing the patience and capital reserves of traders attempting to fade them. When crude oil enters a sustained bull market driven by genuine supply disruptions, commercial hedgers may maintain bearish positioning for many months as prices grind higher. A commercial COT Index reading of fifteen indicating extreme bearishness might persist for three months while prices continue rallying before finally reversing. Traders without sufficient capital and risk tolerance to weather such drawdowns will exit prematurely, precisely when the signal is about to work (Irwin and Sanders, 2012).
Position sizing discipline becomes paramount when implementing COT-based strategies. Rather than risking large percentages of capital on individual signals, successful COT traders typically allocate modest position sizes across multiple signals, allowing some to take time to mature while others work more quickly.
The indicator also cannot overcome fundamental regime changes that alter the structural drivers of markets. If gold enters a true secular bull market driven by monetary debasement, commercial hedgers may remain persistently bearish as mining companies sell forward years of production at what they perceive as favorable prices. Their positioning indicates valuation concerns from a production cost perspective, but cannot stop prices from rising if investment demand overwhelms physical supply-demand balance.
Similarly, structural changes in market participation can alter the meaning of positioning extremes. The growth of commodity index investing in the two thousands brought massive passive long-only capital into futures markets, fundamentally changing typical positioning ranges. Traders relying on COT signals without recognizing this regime change would have generated numerous false bearish signals during the commodity supercycle from 2003 to 2008.
The research foundation supporting COT analysis derives primarily from commodity markets where the commercial hedger information advantage is most pronounced. Studies specifically examining financial futures like equity indices and bonds show weaker but still present effects. Traders should calibrate expectations accordingly, recognizing that COT analysis likely works better for crude oil, natural gas, corn, and wheat than for the S&P 500, Treasury bonds, or currency futures.
Another important limitation involves the reporting threshold structure. Not all market participants appear in COT data, only those holding positions above specified minimums. In markets dominated by a few large players, concentration metrics become critical for proper interpretation. A single large trader accounting for thirty percent of commercial positioning might skew the entire category if their individual circumstances are idiosyncratic rather than representative.
GOLD FUTURES DURING A HYPOTHETICAL MARKET CYCLE
Consider a practical example using gold futures during a hypothetical but realistic market scenario that illustrates how the COT Index indicator guides trading decisions through a complete market cycle. Suppose gold has rallied from fifteen hundred to nineteen hundred dollars per ounce over six months, driven by inflation concerns following aggressive monetary expansion, geopolitical uncertainty, and sustained buying by Asian central banks for reserve diversification.
Large speculators, operating primarily trend-following strategies, have accumulated increasingly bullish positions throughout this rally. Their COT Index has climbed progressively from forty-five to eighty-five. The table display shows that large speculators now hold net long positions representing thirty-two percent of total open interest, their highest in four years. Momentum indicators show positive readings, indicating positions are still building though at a decelerating rate. Position velocity has turned negative, suggesting the pace of position building is slowing.
Meanwhile, commercial hedgers have responded to the rally by aggressively selling forward production and inventory. Their COT Index has moved inversely to price, declining from fifty-five to twenty. This bearish commercial positioning represents mining companies locking in forward sales at prices they view as attractive relative to production costs. The table shows commercials now hold net short positions representing twenty-nine percent of total open interest, their most bearish stance in five years. Concentration metrics indicate this positioning is broadly distributed across many commercial entities, suggesting the bearish stance reflects collective industry view rather than idiosyncratic positioning by a single firm.
Small traders, attracted by mainstream financial media coverage of gold's impressive rally, have recently piled into long positions. Their COT Index has jumped from forty-five to seventy-eight as retail investors chase the trend. Television financial networks feature frequent segments on gold with bullish guests. Internet forums and social media show surging retail interest. This retail enthusiasm historically marks late-stage trend development rather than early opportunity.
The COT Index indicator, configured to monitor commercial positioning from a contrarian perspective, displays a clear bearish signal given the extreme commercial short positioning. The table displays multiple confirming metrics: positioning extremity shows commercials at the ninety-sixth percentile of bearishness, market power indicates they control twenty-nine percent of open interest, and sentiment divergence registers sixty-five, indicating massive disagreement between commercial hedgers and large speculators. This divergence, the highest in three years, places the market in the historically high-risk category for reversals.
The interpretation requires nuance and consideration of context beyond just COT data. Commercials are not necessarily predicting an imminent crash. Rather, they are hedging business operations at what they collectively view as favorable price levels. However, the data reveals they have sold unusually large quantities of forward production, suggesting either exceptional production expectations for the year ahead or concern about sustaining current price levels or combination of both. Combined with extreme speculator positioning indicating a crowded long trade, and small trader enthusiasm confirming retail FOMO, the confluence suggests elevated reversal risk even if the precise timing remains uncertain.
A prudent trader analyzing this situation might take several actions based on COT Index signals. Existing long positions could be tightened with closer stop losses. Profit-taking on a portion of long exposure could lock in gains while maintaining some participation. Some traders might initiate modest short positions as portfolio hedges, sizing them appropriately for the inherent uncertainty in timing reversals. Others might simply move to the sidelines, avoiding new long entries until positioning normalizes.
The key lesson from case study analysis is that COT signals provide probabilistic edges rather than deterministic predictions. They work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five percent win rate with proper risk management produces substantial profits over time, yet still means forty-five percent of signals will be premature or wrong. Traders must embrace this probabilistic reality rather than seeking the impossible goal of perfect accuracy.
INTEGRATION WITH TRADING SYSTEMS
Integration with existing trading systems represents a natural and powerful use case for COT analysis, adding a positioning dimension to price-based technical approaches or fundamental analytical frameworks. Few traders rely exclusively on a single indicator or methodology. Rather, they build systems that synthesize multiple information sources, with each component addressing different aspects of market behavior.
Trend followers might use COT extremes as regime filters, modifying position sizing or avoiding new trend entries when positioning reaches levels historically associated with reversals. Consider a classic trend-following system based on moving average crossovers and momentum breakouts. Integration of COT analysis adds nuance. When large speculator positioning exceeds ninety or commercial positioning falls below ten, the regime filter recognizes elevated reversal risk. The system might reduce position sizing by fifty percent for new signals during these high-risk periods (Kaufman, 2013).
Mean reversion traders might require COT signal confluence before fading extended moves. When crude oil becomes technically overbought and large speculators show extreme long positioning above eighty-five, both signals confirm. If only technical indicators show extremes while positioning remains neutral, the potential short signal is rejected, avoiding fades of trends with underlying institutional support (Kaufman, 2013).
Discretionary traders can monitor the indicator as a continuous awareness tool, informing bias and position sizing without dictating mechanical entries and exits. A discretionary trader might notice commercial positioning shifting from neutral to progressively more bullish over several months. This trend informs growing positive bias even without triggering mechanical signals.
Multi-timeframe analysis represents another powerful integration approach. A trader might use daily charts for trade execution and timing while monitoring weekly COT positioning for strategic context. When both timeframes align, highest-probability opportunities emerge.
Portfolio construction for futures traders can incorporate COT signals as an additional selection criterion. Markets showing strong technical setups AND favorable COT positioning receive highest allocations. Markets with strong technicals but neutral or unfavorable positioning receive reduced allocations.
ADVANCED METRICS AND INTERPRETATION
The metrics table transforms simple positioning data into multidimensional market intelligence. Position extremity, calculated as the absolute deviation from the historical mean normalized by standard deviation, helps identify truly unusual readings versus routine fluctuations. A reading above two standard deviations indicates ninety-fifth percentile or higher extremity. Above three standard deviations indicates ninety-ninth percentile or higher, genuinely rare positioning that historically precedes major events with high probability.
Market power, expressed as a percentage of total open interest, reveals whose positioning matters most from a mechanical market impact perspective. Consider two scenarios in gold futures. In scenario one, commercials show a COT Index reading of fifteen while their market power metric shows they hold net shorts representing thirty-five percent of open interest. This is a high-confidence bearish signal. In scenario two, commercials also show a reading of fifteen, but market power shows only eight percent. While positioning is extreme relative to this category's normal range, their limited market share means less mechanical influence on price.
The rate of change and momentum metrics highlight whether positions are accelerating or decelerating, often providing earlier warnings than absolute levels alone. A COT Index reading of seventy-five with rapidly building momentum suggests continued movement toward extremes. Conversely, a reading of eighty-five with decelerating or negative momentum indicates the positioning trend is exhausting.
Position velocity measures the rate of change in positioning changes, effectively a second derivative. When velocity shifts from positive to negative, it indicates that while positioning may still be growing, the pace of growth is slowing. This deceleration often precedes actual reversal in positioning direction by several weeks.
Sentiment divergence calculates the absolute difference between normalized commercial and large speculator index values. When commercials show extreme bearish positioning at twenty while large speculators show extreme bullish positioning at eighty, the divergence reaches sixty, representing near-maximum disagreement. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals. The mechanism is intuitive. Extreme divergence indicates the informed hedgers and momentum-following speculators have positioned opposite each other with conviction. One group will prove correct and profit while the other proves incorrect and suffers losses. The resolution of this disagreement through price movement often involves volatility.
The table also displays concentration metrics when available. High concentration indicates a few dominant players controlling most of the positioning within a category, while low concentration suggests broad-based participation. Broad-based positioning more reliably reflects collective market intelligence and industry consensus. If mining companies globally all independently decide to hedge aggressively at similar price levels, it suggests genuine industry-wide view about price valuations rather than circumstances specific to one firm.
DATA QUALITY AND RELIABILITY
The CFTC has maintained COT reporting in various forms since the nineteen twenties, providing nearly a century of positioning data across multiple market cycles. However, data quality and reporting standards have evolved substantially over this long period. Modern electronic reporting implemented in the late nineteen nineties and early two thousands significantly improved accuracy and timeliness compared to earlier paper-based systems.
Traders should understand that COT reports capture positions as of Tuesday's close each week. Markets remain open three additional days before publication on Friday afternoon, meaning the reported data is three days stale when received. During periods of rapid market movement or major news events, this lag can be significant. The indicator addresses this limitation by including timestamp information and staleness warnings.
The three-day lag creates particular challenges during extreme volatility episodes. Flash crashes, surprise central bank interventions, geopolitical shocks, and other high-impact events can completely transform market positioning within hours. Traders must exercise judgment about whether reported positioning remains relevant given intervening events.
Reporting thresholds also mean that not all market participants appear in disaggregated COT data. Traders holding positions below specified minimums aggregate into the non-reportable or small trader category. This aggregation affects different markets differently. In highly liquid contracts like crude oil with thousands of participants, reportable traders might represent seventy to eighty percent of open interest. In thinly traded contracts with only dozens of active participants, a few large reportable positions might represent ninety-five percent of open interest.
Another data quality consideration involves trader classification into categories. The CFTC assigns traders to commercial or non-commercial categories based on reported business purpose and activities. However, this process is not perfect. Some entities engage in both commercial and speculative activities, creating ambiguity about proper classification. The transition to Disaggregated reports attempted to address some of these ambiguities by creating more granular categories.
COMPARISON WITH ALTERNATIVE APPROACHES
Several alternative approaches to COT analysis exist in the trading community beyond the normalization methodology employed by this indicator. Some analysts focus on absolute position changes week-over-week rather than index-based normalization. This approach calculates the change in net positioning from one week to the next. The emphasis falls on momentum in positioning changes rather than absolute levels relative to history. This method potentially identifies regime shifts earlier but sacrifices cross-market comparability (Briese, 2008).
Other practitioners employ more complex statistical transformations including percentile rankings, z-score standardization, and machine learning classification algorithms. Ruan and Zhang (2018) demonstrated that machine learning models applied to COT data could achieve modest improvements in forecasting accuracy compared to simple threshold-based approaches. However, these gains came at the cost of interpretability and implementation complexity.
The COT Index indicator intentionally employs a relatively straightforward normalization methodology for several important reasons. First, transparency enhances user understanding and trust. Traders can verify calculations manually and develop intuitive feel for what different readings mean. Second, academic research suggests that most of the predictive power in COT data comes from extreme positioning levels rather than subtle patterns requiring complex statistical methods to detect. Third, robust methods that work consistently across many markets and time periods tend to be simpler rather than more complex, reducing the risk of overfitting to historical data. Fourth, the complexity costs of implementation matter for retail traders without programming teams or computational infrastructure.
PSYCHOLOGICAL ASPECTS OF COT TRADING
Trading based on COT data requires psychological fortitude that differs from momentum-based approaches. Contrarian positioning signals inherently mean betting against prevailing market sentiment and recent price action. When commercials reach extreme bearish positioning, prices have typically been rising, sometimes for extended periods. The price chart looks bullish, momentum indicators confirm strength, moving averages align positively. The COT signal says bet against all of this. This psychological difficulty explains why COT analysis remains underutilized relative to trend-following methods.
Human psychology strongly predisposes us toward extrapolation and recency bias. When prices rally for months, our pattern-matching brains naturally expect continued rally. The recent price action dominates our perception, overwhelming rational analysis about positioning extremes and historical probabilities. The COT signal asking us to sell requires overriding these powerful psychological impulses.
The indicator design attempts to support the required psychological discipline through several features. Clear threshold markers and signal states reduce ambiguity about when signals trigger. When the commercial index crosses below twenty, the signal is explicit and unambiguous. The background shifts to red, the signal label displays bearish, and alerts fire. This explicitness helps traders act on signals rather than waiting for additional confirmation that may never arrive.
The metrics table provides analytical justification for contrarian positions, helping traders maintain conviction during inevitable periods of adverse price movement. When a trader enters short positions based on extreme commercial bearish positioning but prices continue rallying for several weeks, doubt naturally emerges. The table display provides reassurance. Commercial positioning remains extremely bearish. Divergence remains high. The positioning thesis remains intact even though price action has not yet confirmed.
Alert functionality ensures traders do not miss signals due to inattention while also not requiring constant monitoring that can lead to emotional decision-making. Setting alerts for COT extremes enables a healthier relationship with markets. When meaningful signals occur, alerts notify them. They can then calmly assess the situation and execute planned responses.
However, no indicator design can completely overcome the psychological difficulty of contrarian trading. Some traders simply cannot maintain short positions while prices rally. For these traders, COT analysis might be better employed as an exit signal for long positions rather than an entry signal for shorts.
Ultimately, successful COT trading requires developing comfort with probabilistic thinking rather than certainty-seeking. The signals work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five or sixty percent win rate with proper risk management produces substantial profits over years, yet still means forty to forty-five percent of signals will be premature or wrong. COT analysis provides genuine edge, but edge means probability advantage, not elimination of losing trades.
EDUCATIONAL RESOURCES AND CONTINUOUS LEARNING
The indicator provides extensive built-in educational resources through its documentation, detailed tooltips, and transparent calculations. However, mastering COT analysis requires study beyond any single tool or resource. Several excellent resources provide valuable extensions of the concepts covered in this guide.
Books and practitioner-focused monographs offer accessible entry points. Stephen Briese published The Commitments of Traders Bible in two thousand eight, offering detailed breakdowns of how different markets and trader categories behave (Briese, 2008). Briese's work stands out for its empirical focus and market-specific insights. Jack Schwager includes discussion of COT analysis within the broader context of market behavior in his book Market Sense and Nonsense (Schwager, 2012). Perry Kaufman's Trading Systems and Methods represents perhaps the most rigorous practitioner-focused text on systematic trading approaches including COT analysis (Kaufman, 2013).
Academic journal articles provide the rigorous statistical foundation underlying COT analysis. The Journal of Futures Markets regularly publishes research on positioning data and its predictive properties. Bessembinder and Chan's earlier work on systematic risk, hedging pressure, and risk premiums in futures markets provides theoretical foundation (Bessembinder, 1992). Chang's examination of speculator returns provides historical context (Chang, 1985). Irwin and Sanders provide essential skeptical perspective in their two thousand twelve article (Irwin and Sanders, 2012). Wang's two thousand three article provides one of the most empirical analyses of COT data across multiple commodity markets (Wang, 2003).
Online resources extend beyond academic and book-length treatments. The CFTC website provides free access to current and historical COT reports in multiple formats. The explanatory materials section offers detailed documentation of report construction, category definitions, and historical methodology changes. Traders serious about COT analysis should read these official CFTC documents to understand exactly what they are analyzing.
Commercial COT data services such as Barchart provide enhanced visualization and analysis tools beyond raw CFTC data. TradingView's educational materials, published scripts library, and user community provide additional resources for exploring different approaches to COT analysis.
The key to mastering COT analysis lies not in finding a single definitive source but rather in building understanding through multiple perspectives and information sources. Academic research provides rigorous empirical foundation. Practitioner-focused books offer practical implementation insights. Direct engagement with data through systematic backtesting develops intuition about how positioning dynamics manifest across different market conditions.
SYNTHESIZING KNOWLEDGE INTO PRACTICE
The COT Index indicator represents the synthesis of academic research, trading experience, and software engineering into a practical tool accessible to retail traders equipped with nothing more than a TradingView account and willingness to learn. What once required expensive data subscriptions, custom programming capabilities, statistical software, and institutional resources now appears as a straightforward indicator requiring only basic parameter selection and modest study to understand. This democratization of institutional-grade analysis tools represents a broader trend in financial markets over recent decades.
Yet technology and data access alone provide no edge without understanding and discipline. Markets remain relentlessly efficient at eliminating edges that become too widely known and mechanically exploited. The COT Index indicator succeeds only when users invest time learning the underlying concepts, understand the limitations and probability distributions involved, and integrate signals thoughtfully into trading plans rather than applying them mechanically.
The academic research demonstrates conclusively that institutional positioning contains genuine information about future price movements, particularly at extremes where commercial hedgers are maximally bearish or bullish relative to historical norms. This informational content is neither perfect nor deterministic but rather probabilistic, providing edge over many observations through identification of higher-probability configurations. Bessembinder and Chan's finding that commercial positioning explained modest but significant variance in future returns illustrates this probabilistic nature perfectly (Bessembinder and Chan, 1992). The effect is real and statistically significant, yet it explains perhaps ten to fifteen percent of return variance rather than most variance. Much of price movement remains unpredictable even with positioning intelligence.
The practical implication is that COT analysis works best as one component of a trading system rather than a standalone oracle. It provides the positioning dimension, revealing where the smart money has positioned and where the crowd has followed, but price action analysis provides the timing dimension. Fundamental analysis provides the catalyst dimension. Risk management provides the survival dimension. These components work together synergistically.
The indicator's design philosophy prioritizes transparency and education over black-box complexity, empowering traders to understand exactly what they are analyzing and why. Every calculation is documented and user-adjustable. The threshold markers, background coloring, tables, and clear signal states provide multiple reinforcing channels for conveying the same information.
This educational approach reflects a conviction that sustainable trading success comes from genuine understanding rather than mechanical system-following. Traders who understand why commercial positioning matters, how different trader categories behave, what positioning extremes signify, and where signals fit within probability distributions can adapt when market conditions change. Traders mechanically following black-box signals without comprehension abandon systems after normal losing streaks.
The research foundation supporting COT analysis comes primarily from commodity markets where commercial hedger informational advantages are most pronounced. Agricultural producers hedging crops know more about supply conditions than distant speculators. Energy companies hedging production know more about operating costs than financial traders. Metals miners hedging output know more about ore grades than index funds. Financial futures markets show weaker but still present effects.
The journey from reading this documentation to profitable trading based on COT analysis involves several stages that cannot be rushed. Initial reading and basic understanding represents the first stage. Historical study represents the second stage, reviewing past market cycles to observe how positioning extremes preceded major turning points. Paper trading or small-size real trading represents the third stage to experience the psychological challenges. Refinement based on results and personal psychology represents the fourth stage.
Markets will continue evolving. New participant categories will emerge. Regulatory structures will change. Technology will advance. Yet the fundamental dynamics driving COT analysis, that different market participants have different information, different motivations, and different forecasting abilities that manifest in their positioning, will persist as long as futures markets exist. While specific thresholds or optimal parameters may shift over time, the core logic remains sound and adaptable.
The trader equipped with this indicator, understanding of the theory and evidence behind COT analysis, realistic expectations about probability rather than certainty, discipline to maintain positions through adverse volatility, and patience to allow signals time to develop possesses genuine edge in markets. The edge is not enormous, markets cannot allow large persistent inefficiencies without arbitraging them away, but it is real, measurable, and exploitable by those willing to invest in learning and disciplined application.
REFERENCES
Bessembinder, H. (1992) Systematic risk, hedging pressure, and risk premiums in futures markets, Review of Financial Studies, 5(4), pp. 637-667.
Bessembinder, H. and Chan, K. (1992) The profitability of technical trading rules in the Asian stock markets, Pacific-Basin Finance Journal, 3(2-3), pp. 257-284.
Briese, S. (2008) The Commitments of Traders Bible: How to Profit from Insider Market Intelligence. Hoboken: John Wiley & Sons.
Chang, E.C. (1985) Returns to speculators and the theory of normal backwardation, Journal of Finance, 40(1), pp. 193-208.
Commodity Futures Trading Commission (CFTC) (2009) Explanatory Notes: Disaggregated Commitments of Traders Report. Available at: www.cftc.gov (Accessed: 15 January 2025).
Commodity Futures Trading Commission (CFTC) (2020) Commitments of Traders: About the Report. Available at: www.cftc.gov (Accessed: 15 January 2025).
Irwin, S.H. and Sanders, D.R. (2012) Testing the Masters Hypothesis in commodity futures markets, Energy Economics, 34(1), pp. 256-269.
Kaufman, P.J. (2013) Trading Systems and Methods. 5th edn. Hoboken: John Wiley & Sons.
Ruan, Y. and Zhang, Y. (2018) Forecasting commodity futures prices using machine learning: Evidence from the Chinese commodity futures market, Applied Economics Letters, 25(12), pp. 845-849.
Sanders, D.R., Boris, K. and Manfredo, M. (2004) Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports, Energy Economics, 26(3), pp. 425-445.
Schwager, J.D. (2012) Market Sense and Nonsense: How the Markets Really Work and How They Don't. Hoboken: John Wiley & Sons.
Tharp, V.K. (2008) Super Trader: Make Consistent Profits in Good and Bad Markets. New York: McGraw-Hill.
Wang, C. (2003) The behavior and performance of major types of futures traders, Journal of Futures Markets, 23(1), pp. 1-31.
Williams, L.R. and Noseworthy, M. (2009) The Right Stock at the Right Time: Prospering in the Coming Good Years. Hoboken: John Wiley & Sons.
FURTHER READING
For traders seeking to deepen their understanding of COT analysis and futures market positioning beyond this documentation, the following resources provide valuable extensions:
Academic Journal Articles:
Fishe, R.P.H. and Smith, A. (2012) Do speculators drive commodity prices away from supply and demand fundamentals?, Journal of Commodity Markets, 1(1), pp. 1-16.
Haigh, M.S., Hranaiova, J. and Overdahl, J.A. (2007) Hedge funds, volatility, and liquidity provision in energy futures markets, Journal of Alternative Investments, 9(4), pp. 10-38.
Kocagil, A.E. (1997) Does futures speculation stabilize spot prices? Evidence from metals markets, Applied Financial Economics, 7(1), pp. 115-125.
Sanders, D.R. and Irwin, S.H. (2011) The impact of index funds in commodity futures markets: A systems approach, Journal of Alternative Investments, 14(1), pp. 40-49.
Books and Practitioner Resources:
Murphy, J.J. (1999) Technical Analysis of the Financial Markets: A Guide to Trading Methods and Applications. New York: New York Institute of Finance.
Pring, M.J. (2002) Technical Analysis Explained: The Investor's Guide to Spotting Investment Trends and Turning Points. 4th edn. New York: McGraw-Hill.
Federal Reserve and Research Institution Publications:
Federal Reserve Banks regularly publish working papers examining commodity markets, futures positioning, and price discovery mechanisms. The Federal Reserve Bank of San Francisco and Federal Reserve Bank of Kansas City maintain active research programs in this area.
Online Resources:
The CFTC website provides free access to current and historical COT reports, explanatory materials, and regulatory documentation.
Barchart offers enhanced COT data visualization and screening tools.
TradingView's community library contains numerous published scripts and educational materials exploring different approaches to positioning analysis.
US30 Quarter Levels (125-point grid) by FxMogul🟦 US30 Quarter Levels — Trade the Index Like the Banks
Discover the Dow’s hidden rhythm.
This indicator reveals the institutional quarter levels that govern US30 — spaced every 125 points, e.g. 45125, 45250, 45375, 45500, 45625, 45750, 45875, 46000, and so on.
These are the liquidity magnets and reaction zones where smart money executes — now visualized directly on your chart.
💼 Why You Need It
See institutional precision: The Dow respects 125-point cycles — this tool exposes them.
Catch reversals before retail sees them: Every impulse and retracement begins at one of these zones.
Build confluence instantly: Perfectly aligns with your FVGs, OBs, and session highs/lows.
Trade like a professional: Turn chaos into structure, and randomness into rhythm.
⚙️ Key Features
Automatically plots US30 quarter levels (…125 / …250 / …375 / …500 / …625 / …750 / …875 / …000).
Color-coded hierarchy:
🟨 xx000 / xx500 → major institutional levels
⚪ xx250 / xx750 → medium-impact levels
⚫ xx125 / xx375 / xx625 / xx875 → intraday liquidity pockets
Customizable window size, label spacing, and line extensions.
Works across all timeframes — from 1-minute scalps to 4-hour macro swings.
Optimized for clean visualization with no clutter.
🎯 How to Use It
Identify liquidity sweeps: Smart money hunts stops at these quarter zones.
Align structure: Combine with session opens, order blocks, or FVGs.
Set precision entries & exits: Trade reaction-to-reaction with tight risk.
Plan daily bias: Watch how New York respects these 125-point increments.
🧭 Designed For
Scalpers, day traders, and swing traders who understand that US30 doesn’t move randomly — it moves rhythmically.
Perfect for traders using ICT, SMC, or liquidity-based frameworks.
⚡ Creator’s Note
“Every 125 points, the Dow breathes. Every 1000, it shifts direction.
Once you see the rhythm, you’ll never unsee it.”
— FxMogul
Luxy Momentum, Trend, Bias and Breakout Indicators V7
TABLE OF CONTENTS
This is Version 7 (V7) - the latest and most optimized release. If you are using any older versions (V6, V5, V4, V3, etc.), it is highly recommended to replace them with V7.
Why This Indicator is Different
Who Should Use This
Core Components Overview
The UT Bot Trading System
Understanding the Market Bias Table
Candlestick Pattern Recognition
Visual Tools and Features
How to Use the Indicator
Performance and Optimization
FAQ
---
### CREDITS & ATTRIBUTION
This indicator implements proven trading concepts using entirely original code developed specifically for this project.
### CONCEPTUAL FOUNDATIONS
• UT Bot ATR Trailing System
- Original concept by @QuantNomad: (search "UT-Bot-Strategy"
- Our version is a complete reimplementation with significant enhancements:
- Volume-weighted momentum adjustment
- Composite stop loss from multiple S/R layers
- Multi-filter confirmation system (swing, %, 2-bar, ZLSMA)
- Full integration with multi-timeframe bias table
- Visual audit trail with freeze-on-touch
- NOTE: No code was copied - this is a complete reimplementation with enhancements.
• Standard Technical Indicators (Public Domain Formulas):
- Supertrend: ATR-based trend calculation with custom gradient fills
- MACD: Gerald Appel's formula with separation filters
- RSI: J. Welles Wilder's formula with pullback zone logic
- ADX/DMI: Custom trend strength formula inspired by Wilder's directional movement concept, reimplemented with volume weighting and efficiency metrics
- ZLSMA: Zero-lag formula enhanced with Hull MA and momentum prediction
### Custom Implementations
- Trend Strength: Inspired by Wilder's ADX concept but using volume-weighted pressure calculation and efficiency metrics (not traditional +DI/-DI smoothing)
- All code implementations are original
### ORIGINAL FEATURES (70%+ of codebase)
- Multi-Timeframe Bias Table with live updates
- Risk Management System (R-multiple TPs, freeze-on-touch)
- Opening Range Breakout tracker with session management
- Composite Stop Loss calculator using 6+ S/R layers
- Performance optimization system (caching, conditional calcs)
- VIX Fear Index integration
- Previous Day High/Low auto-detection
- Candlestick pattern recognition with interactive tooltips
- Smart label and visual management
- All UI/UX design and table architecture
### DEVELOPMENT PROCESS
**AI Assistance:** This indicator was developed over 2+ months with AI assistance (ChatGPT/Claude) used for:
- Writing Pine Script code based on design specifications
- Optimizing performance and fixing bugs
- Ensuring Pine Script v6 compliance
- Generating documentation
**Author's Role:** All trading concepts, system design, feature selection, integration logic, and strategic decisions are original work by the author. The AI was a coding tool, not the system designer.
**Transparency:** We believe in full disclosure - this project demonstrates how AI can be used as a powerful development tool while maintaining creative and strategic ownership.
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1. WHY THIS INDICATOR IS DIFFERENT
Most traders use multiple separate indicators on their charts, leading to cluttered screens, conflicting signals, and analysis paralysis. The Suite solves this by integrating proven technical tools into a single, cohesive system.
Key Advantages:
All-in-One Design: Instead of loading 5-10 separate indicators, you get everything in one optimized script. This reduces chart clutter and improves TradingView performance.
Multi-Timeframe Bias Table: Unlike standard indicators that only show the current timeframe, the Bias Table aggregates trend signals across multiple timeframes simultaneously. See at a glance whether 1m, 5m, 15m, 1h are aligned bullish or bearish - no more switching between charts.
Smart Confirmations: The indicator doesn't just give signals - it shows you WHY. Every entry has multiple layers of confirmation (MA cross, MACD momentum, ADX strength, RSI pullback, volume, etc.) that you can toggle on/off.
Dynamic Stop Loss System: Instead of static ATR stops, the SL is calculated from multiple support/resistance layers: UT trailing line, Supertrend, VWAP, swing structure, and MA levels. This creates more intelligent, price-action-aware stops.
R-Multiple Take Profits: Built-in TP system calculates targets based on your initial risk (1R, 1.5R, 2R, 3R). Lines freeze when touched with visual checkmarks, giving you a clean audit trail of partial exits.
Educational Tooltips Everywhere: Every single input has detailed tooltips explaining what it does, typical values, and how it impacts trading. You're not guessing - you're learning as you configure.
Performance Optimized: Smart caching, conditional calculations, and modular design mean the indicator runs fast despite having 15+ features. Turn off what you don't use for even better performance.
No Repainting: All signals respect bar close. Alerts fire correctly. What you see in history is what you would have gotten in real-time.
What Makes It Unique:
Integrated UT Bot + Bias Table: No other indicator combines UT Bot's ATR trailing system with a live multi-timeframe dashboard. You get precision entries with macro trend context.
Candlestick Pattern Recognition with Interactive Tooltips: Patterns aren't just marked - hover over any emoji for a full explanation of what the pattern means and how to trade it.
Opening Range Breakout Tracker: Built-in ORB system for intraday traders with customizable session times and real-time status updates in the Bias Table.
Previous Day High/Low Auto-Detection: Automatically plots PDH/PDL on intraday charts with theme-aware colors. Updates daily without manual input.
Dynamic Row Labels in Bias Table: The table shows your actual settings (e.g., "EMA 10 > SMA 20") not generic labels. You know exactly what's being evaluated.
Modular Filter System: Instead of forcing a fixed methodology, the indicator lets you build your own strategy. Start with just UT Bot, add filters one at a time, test what works for your style.
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2. WHO WHOULD USE THIS
Designed For:
Intermediate to Advanced Traders: You understand basic technical analysis (MAs, RSI, MACD) and want to combine multiple confirmations efficiently. This isn't a "one-click profit" system - it's a professional toolkit.
Multi-Timeframe Traders: If you trade one asset but check multiple timeframes for confirmation (e.g., enter on 5m after checking 15m and 1h alignment), the Bias Table will save you hours every week.
Trend Followers: The indicator excels at identifying and following trends using UT Bot, Supertrend, and MA systems. If you trade breakouts and pullbacks in trending markets, this is built for you.
Intraday and Swing Traders: Works equally well on 5m-1h charts (day trading) and 4h-D charts (swing trading). Scalpers can use it too with appropriate settings adjustments.
Discretionary Traders: This isn't a black-box system. You see all the components, understand the logic, and make final decisions. Perfect for traders who want tools, not automation.
Works Across All Markets:
Stocks (US, international)
Cryptocurrency (24/7 markets supported)
Forex pairs
Indices (SPY, QQQ, etc.)
Commodities
NOT Ideal For :
Complete Beginners: If you don't know what a moving average or RSI is, start with basics first. This indicator assumes foundational knowledge.
Algo Traders Seeking Black Box: This is discretionary. Signals require context and confirmation. Not suitable for blind automated execution.
Mean-Reversion Only Traders: The indicator is trend-following at its core. While VWAP bands support mean-reversion, the primary methodology is trend continuation.
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3. CORE COMPONENTS OVERVIEW
The indicator combines these proven systems:
Trend Analysis:
Moving Averages: Four customizable MAs (Fast, Medium, Medium-Long, Long) with six types to choose from (EMA, SMA, WMA, VWMA, RMA, HMA). Mix and match for your style.
Supertrend: ATR-based trend indicator with unique gradient fill showing trend strength. One-sided ribbon visualization makes it easier to see momentum building or fading.
ZLSMA : Zero-lag linear-regression smoothed moving average. Reduces lag compared to traditional MAs while maintaining smooth curves.
Momentum & Filters:
MACD: Standard MACD with separation filter to avoid weak crossovers.
RSI: Pullback zone detection - only enter longs when RSI is in your defined "buy zone" and shorts in "sell zone".
ADX/DMI: Trend strength measurement with directional filter. Ensures you only trade when there's actual momentum.
Volume Filter: Relative volume confirmation - require above-average volume for entries.
Donchian Breakout: Optional channel breakout requirement.
Signal Systems:
UT Bot: The primary signal generator. ATR trailing stop that adapts to volatility and gives clear entry/exit points.
Base Signals: MA cross system with all the above filters applied. More conservative than UT Bot alone.
Market Bias Table: Multi-timeframe dashboard showing trend alignment across 7 timeframes plus macro bias (3-day, weekly, monthly, quarterly, VIX).
Candlestick Patterns: Six major reversal patterns auto-detected with interactive tooltips.
ORB Tracker: Opening range high/low with breakout status (intraday only).
PDH/PDL: Previous day levels plotted automatically on intraday charts.
VWAP + Bands : Session-anchored VWAP with up to three standard deviation band pairs.
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4. THE UT BOT TRADING SYSTEM
The UT Bot is the heart of the indicator's signal generation. It's an advanced ATR trailing stop that adapts to market volatility.
Why UT Bot is Superior to Fixed Stops:
Traditional ATR stops use a fixed multiplier (e.g., "stop = entry - 2×ATR"). UT Bot is smarter:
It TRAILS the stop as price moves in your favor
It WIDENS during high volatility to avoid premature stops
It TIGHTENS during consolidation to lock in profits
It FLIPS when price breaks the trailing line, signaling reversals
Visual Elements You'll See:
Orange Trailing Line: The actual UT stop level that adapts bar-by-bar
Buy/Sell Labels: Aqua triangle (long) or orange triangle (short) when the line flips
ENTRY Line: Horizontal line at your entry price (optional, can be turned off)
Suggested Stop Loss: A composite SL calculated from multiple support/resistance layers:
- UT trailing line
- Supertrend level
- VWAP
- Swing structure (recent lows/highs)
- Long-term MA (200)
- ATR-based floor
Take Profit Lines: TP1, TP1.5, TP2, TP3 based on R-multiples. When price touches a TP, it's marked with a checkmark and the line freezes for audit trail purposes.
Status Messages: "SL Touched ❌" or "SL Frozen" when the trade leg completes.
How UT Bot Differs from Other ATR Systems:
Multiple Filters Available: You can require 2-bar confirmation, minimum % price change, swing structure alignment, or ZLSMA directional filter. Most UT implementations have none of these.
Smart SL Calculation: Instead of just using the UT line as your stop, the indicator suggests a better SL based on actual support/resistance. This prevents getting stopped out by wicks while keeping risk controlled.
Visual Audit Trail: All SL/TP lines freeze when touched with clear markers. You can review your trades weeks later and see exactly where entries, stops, and targets were.
Performance Options: "Draw UT visuals only on bar close" lets you reduce rendering load without affecting logic or alerts - critical for slower machines or 1m charts.
Trading Logic:
UT Bot flips direction (Buy or Sell signal appears)
Check Bias Table for multi-timeframe confirmation
Optional: Wait for Base signal or candlestick pattern
Enter at signal bar close or next bar open
Place stop at "Suggested Stop Loss" line
Scale out at TP levels (TP1, TP2, TP3)
Exit remaining position on opposite UT signal or stop hit
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5. UNDERSTANDING THE MARKET BIAS TABLE
This is the indicator's unique multi-timeframe intelligence layer. Instead of looking at one chart at a time, the table aggregates signals across seven timeframes plus macro trend bias.
Why Multi-Timeframe Analysis Matters:
Professional traders check higher and lower timeframes for context:
Is the 1h uptrend aligning with my 5m entry?
Are all short-term timeframes bullish or just one?
Is the daily trend supportive or fighting me?
Doing this manually means opening multiple charts, checking each indicator, and making mental notes. The Bias Table does it automatically in one glance.
Table Structure:
Header Row:
On intraday charts: 1m, 5m, 15m, 30m, 1h, 2h, 4h (toggle which ones you want)
On daily+ charts: D, W, M (automatic)
Green dot next to title = live updating
Headline Rows - Macro Bias:
These show broad market direction over longer periods:
3 Day Bias: Trend over last 3 trading sessions (uses 1h data)
Weekly Bias: Trend over last 5 trading sessions (uses 4h data)
Monthly Bias: Trend over last 30 daily bars
Quarterly Bias: Trend over last 13 weekly bars
VIX Fear Index: Market regime based on VIX level - bullish when low, bearish when high
Opening Range Breakout: Status of price vs. session open range (intraday only)
These rows show text: "BULLISH", "BEARISH", or "NEUTRAL"
Indicator Rows - Technical Signals:
These evaluate your configured indicators across all active timeframes:
Fast MA > Medium MA (shows your actual MA settings, e.g., "EMA 10 > SMA 20")
Price > Long MA (e.g., "Price > SMA 200")
Price > VWAP
MACD > Signal
Supertrend (up/down/neutral)
ZLSMA Rising
RSI In Zone
ADX ≥ Minimum
These rows show emojis: GREEB (bullish), RED (bearish), GRAY/YELLOW (neutral/NA)
AVG Column:
Shows percentage of active timeframes that are bullish for that row. This is the KEY metric:
AVG > 70% = strong multi-timeframe bullish alignment
AVG 40-60% = mixed/choppy, no clear trend
AVG < 30% = strong multi-timeframe bearish alignment
How to Use the Table:
For a long trade:
Check AVG column - want to see > 60% ideally
Check headline bias rows - want to see BULLISH, not BEARISH
Check VIX row - bullish market regime preferred
Check ORB row (intraday) - want ABOVE for longs
Scan indicator rows - more green = better confirmation
For a short trade:
Check AVG column - want to see < 40% ideally
Check headline bias rows - want to see BEARISH, not BULLISH
Check VIX row - bearish market regime preferred
Check ORB row (intraday) - want BELOW for shorts
Scan indicator rows - more red = better confirmation
When AVG is 40-60%:
Market is choppy, mixed signals. Either stay out or reduce position size significantly. These are low-probability environments.
Unique Features:
Dynamic Labels: Row names show your actual settings (e.g., "EMA 10 > SMA 20" not generic "Fast > Slow"). You know exactly what's being evaluated.
Customizable Rows: Turn off rows you don't care about. Only show what matters to your strategy.
Customizable Timeframes: On intraday charts, disable 1m or 4h if you don't trade them. Reduces calculation load by 20-40%.
Automatic HTF Handling: On Daily/Weekly/Monthly charts, the table automatically switches to D/W/M columns. No configuration needed.
Performance Smart: "Hide BIAS table on 1D or above" option completely skips all table calculations on higher timeframes if you only trade intraday.
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6. CANDLESTICK PATTERN RECOGNITION
The indicator automatically detects six major reversal patterns and marks them with emojis at the relevant bars.
Why These Six Patterns:
These are the most statistically significant reversal patterns according to trading literature:
High win rate when appearing at support/resistance
Clear visual structure (not subjective)
Work across all timeframes and assets
Studied extensively by institutions
The Patterns:
Bullish Patterns (appear at bottoms):
Bullish Engulfing: Green candle completely engulfs prior red candle's body. Strong reversal signal.
Hammer: Small body with long lower wick (at least 2× body size). Shows rejection of lower prices by buyers.
Morning Star: Three-candle pattern (large red → small indecision → large green). Very strong bottom reversal.
Bearish Patterns (appear at tops):
Bearish Engulfing: Red candle completely engulfs prior green candle's body. Strong reversal signal.
Shooting Star: Small body with long upper wick (at least 2× body size). Shows rejection of higher prices by sellers.
Evening Star: Three-candle pattern (large green → small indecision → large red). Very strong top reversal.
Interactive Tooltips:
Unlike most pattern indicators that just draw shapes, this one is educational:
Hover your mouse over any pattern emoji
A tooltip appears explaining: what the pattern is, what it means, when it's most reliable, and how to trade it
No need to memorize - learn as you trade
Noise Filter:
"Min candle body % to filter noise" setting prevents false signals:
Patterns require minimum body size relative to price
Filters out tiny candles that don't represent real buying/selling pressure
Adjust based on asset volatility (higher % for crypto, lower for low-volatility stocks)
How to Trade Patterns:
Patterns are NOT standalone entry signals. Use them as:
Confirmation: UT Bot gives signal + pattern appears = stronger entry
Reversal Warning: In a trade, opposite pattern appears = consider tightening stop or taking profit
Support/Resistance Validation: Pattern at key level (PDH, VWAP, MA 200) = level is being respected
Best combined with:
UT Bot or Base signal in same direction
Bias Table alignment (AVG > 60% or < 40%)
Appearance at obvious support/resistance
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7. VISUAL TOOLS AND FEATURES
VWAP (Volume Weighted Average Price):
Session-anchored VWAP with standard deviation bands. Shows institutional "fair value" for the trading session.
Anchor Options: Session, Day, Week, Month, Quarter, Year. Choose based on your trading timeframe.
Bands: Up to three pairs (X1, X2, X3) showing statistical deviation. Price at outer bands often reverses.
Auto-Hide on HTF: VWAP hides on Daily/Weekly/Monthly charts automatically unless you enable anchored mode.
Use VWAP as:
Directional bias (above = bullish, below = bearish)
Mean reversion levels (outer bands)
Support/resistance (the VWAP line itself)
Previous Day High/Low:
Automatically plots yesterday's high and low on intraday charts:
Updates at start of each new trading day
Theme-aware colors (dark text for light charts, light text for dark charts)
Hidden automatically on Daily/Weekly/Monthly charts
These levels are critical for intraday traders - institutions watch them closely as support/resistance.
Opening Range Breakout (ORB):
Tracks the high/low of the first 5, 15, 30, or 60 minutes of the trading session:
Customizable session times (preset for NYSE, LSE, TSE, or custom)
Shows current breakout status in Bias Table row (ABOVE, BELOW, INSIDE, BUILDING)
Intraday only - auto-disabled on Daily+ charts
ORB is a classic day trading strategy - breakout above opening range often leads to continuation.
Extra Labels:
Change from Open %: Shows how far price has moved from session open (intraday) or daily open (HTF). Green if positive, red if negative.
ADX Badge: Small label at bottom of last bar showing current ADX value. Green when above your minimum threshold, red when below.
RSI Badge: Small label at top of last bar showing current RSI value with zone status (buy zone, sell zone, or neutral).
These labels provide quick at-a-glance confirmation without needing separate indicator windows.
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8. HOW TO USE THE INDICATOR
Step 1: Add to Chart
Load the indicator on your chosen asset and timeframe
First time: Everything is enabled by default - the chart will look busy
Don't panic - you'll turn off what you don't need
Step 2: Start Simple
Turn OFF everything except:
UT Bot labels (keep these ON)
Bias Table (keep this ON)
Moving Averages (Fast and Medium only)
Suggested Stop Loss and Take Profits
Hide everything else initially. Get comfortable with the basic UT Bot + Bias Table workflow first.
Step 3: Learn the Core Workflow
UT Bot gives a Buy or Sell signal
Check Bias Table AVG column - do you have multi-timeframe alignment?
If yes, enter the trade
Place stop at Suggested Stop Loss line
Scale out at TP levels
Exit on opposite UT signal
Trade this simple system for a week. Get a feel for signal frequency and win rate with your settings.
Step 4: Add Filters Gradually
If you're getting too many losing signals (whipsaws in choppy markets), add filters one at a time:
Try: "Require 2-Bar Trend Confirmation" - wait for 2 bars to confirm direction
Try: ADX filter with minimum threshold - only trade when trend strength is sufficient
Try: RSI pullback filter - only enter on pullbacks, not chasing
Try: Volume filter - require above-average volume
Add one filter, test for a week, evaluate. Repeat.
Step 5: Enable Advanced Features (Optional)
Once you're profitable with the core system, add:
Supertrend for additional trend confirmation
Candlestick patterns for reversal warnings
VWAP for institutional anchor reference
ORB for intraday breakout context
ZLSMA for low-lag trend following
Step 6: Optimize Settings
Every setting has a detailed tooltip explaining what it does and typical values. Hover over any input to read:
What the parameter controls
How it impacts trading
Suggested ranges for scalping, day trading, and swing trading
Start with defaults, then adjust based on your results and style.
Step 7: Set Up Alerts
Right-click chart → Add Alert → Condition: "Luxy Momentum v6" → Choose:
"UT Bot — Buy" for long entries
"UT Bot — Sell" for short entries
"Base Long/Short" for filtered MA cross signals
Optionally enable "Send real-time alert() on UT flip" in settings for immediate notifications.
Common Workflow Variations:
Conservative Trader:
UT signal + Base signal + Candlestick pattern + Bias AVG > 70%
Enter only at major support/resistance
Wider UT sensitivity, multiple filters
Aggressive Trader:
UT signal + Bias AVG > 60%
Enter immediately, no waiting
Tighter UT sensitivity, minimal filters
Swing Trader:
Focus on Daily/Weekly Bias alignment
Ignore intraday noise
Use ORB and PDH/PDL less (or not at all)
Wider stops, patient approach
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9. PERFORMANCE AND OPTIMIZATION
The indicator is optimized for speed, but with 15+ features running simultaneously, chart load time can add up. Here's how to keep it fast:
Biggest Performance Gains:
Disable Unused Timeframes: In "Time Frames" settings, turn OFF any timeframe you don't actively trade. Each disabled TF saves 10-15% calculation time. If you only day trade 5m, 15m, 1h, disable 1m, 2h, 4h.
Hide Bias Table on Daily+: If you only trade intraday, enable "Hide BIAS table on 1D or above". This skips ALL table calculations on higher timeframes.
Draw UT Visuals Only on Bar Close: Reduces intrabar rendering of SL/TP/Entry lines. Has ZERO impact on logic or alerts - purely visual optimization.
Additional Optimizations:
Turn off VWAP bands if you don't use them
Disable candlestick patterns if you don't trade them
Turn off Supertrend fill if you find it distracting (keep the line)
Reduce "Limit to 10 bars" for SL/TP lines to minimize line objects
Performance Features Built-In:
Smart Caching: Higher timeframe data (3-day bias, weekly bias, etc.) updates once per day, not every bar
Conditional Calculations: Volume filter only calculates when enabled. Swing filter only runs when enabled. Nothing computes if turned off.
Modular Design: Every component is independent. Turn off what you don't need without breaking other features.
Typical Load Times:
5m chart, all features ON, 7 timeframes: ~2-3 seconds
5m chart, core features only, 3 timeframes: ~1 second
1m chart, all features: ~4-5 seconds (many bars to calculate)
If loading takes longer, you likely have too many indicators on the chart total (not just this one).
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10. FAQ
Q: How is this different from standard UT Bot indicators?
A: Standard UT Bot (originally by @QuantNomad) is just the ATR trailing line and flip signals. This implementation adds:
- Volume weighting and momentum adjustment to the trailing calculation
- Multiple confirmation filters (swing, %, 2-bar, ZLSMA)
- Smart composite stop loss system from multiple S/R layers
- R-multiple take profit system with freeze-on-touch
- Integration with multi-timeframe Bias Table
- Visual audit trail with checkmarks
Q: Can I use this for automated trading?
A: The indicator is designed for discretionary trading. While it has clear signals and alerts, it's not a mechanical system. Context and judgment are required.
Q: Does it repaint?
A: No. All signals respect bar close. UT Bot logic runs intrabar but signals only trigger on confirmed bars. Alerts fire correctly with no lookahead.
Q: Do I need to use all the features?
A: Absolutely not. The indicator is modular. Many profitable traders use just UT Bot + Bias Table + Moving Averages. Start simple, add complexity only if needed.
Q: How do I know which settings to use?
A: Every single input has a detailed tooltip. Hover over any setting to see:
What it does
How it affects trading
Typical values for scalping, day trading, swing trading
Start with defaults, adjust gradually based on results.
Q: Can I use this on crypto 24/7 markets?
A: Yes. ORB will not work (no defined session), but everything else functions normally. Use "Day" anchor for VWAP instead of "Session".
Q: The Bias Table is blank or not showing.
A: Check:
"Show Table" is ON
Table position isn't overlapping another indicator's table (change position)
At least one row is enabled
"Hide BIAS table on 1D or above" is OFF (if on Daily+ chart)
Q: Why are candlestick patterns not appearing?
A: Patterns are relatively rare by design - they only appear at genuine reversal points. Check:
Pattern toggles are ON
"Min candle body %" isn't too high (try 0.05-0.10)
You're looking at a chart with actual reversals (not strong trending market)
Q: UT Bot is too sensitive/not sensitive enough.
A: Adjust "Sensitivity (Key×ATR)". Lower number = tighter stop, more signals. Higher number = wider stop, fewer signals. Read the tooltip for guidance.
Q: Can I get alerts for the Bias Table?
A: The Bias Table is a dashboard for visual analysis, not a signal generator. Set alerts on UT Bot or Base signals, then manually check Bias Table for confirmation.
Q: Does this work on stocks with low volume?
A: Yes, but turn OFF the volume filter. Low volume stocks will never meet relative volume requirements.
Q: How often should I check the Bias Table?
A: Before every entry. It takes 2 seconds to glance at the AVG column and headline rows. This one check can save you from fighting the trend.
Q: What if UT signal and Base signal disagree?
A: UT Bot is more aggressive (ATR trailing). Base signals are more conservative (MA cross + filters). If they disagree, either:
Wait for both to align (safest)
Take the UT signal but with smaller size (aggressive)
Skip the trade (conservative)
There's no "right" answer - depends on your risk tolerance.
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FINAL NOTES
The indicator gives you an edge. How you use that edge determines results.
For questions, feedback, or support, comment on the indicator page or message the author.
Happy Trading!
Multi-Timeframe Trend Table - EMA Based Trend Analysis📊 Stay Aligned with Higher Timeframe Trends While Scalping
This powerful indicator displays real-time trend direction for 1-hour and 4-hour timeframes in a clean, easy-to-read table format. Perfect for traders who want to align their short-term trades with higher timeframe momentum.
🎯 Key Features
Multi-Timeframe Analysis: Monitor 1H and 4H trends while trading on any timeframe (3min, 5min, 15min, etc.)
EMA-Based Logic: Uses proven EMA 50 and EMA 100 crossover methodology
Visual Clarity: Color-coded table with green (uptrend) and red (downtrend) indicators
Customizable Display: Toggle EMA values and adjust table position
Real-Time Updates: Automatically refreshes with each bar close
Lightweight: Minimal resource usage with efficient data requests
📈 How It Works
The indicator determines trend direction using a simple but effective rule:
UPTREND: Price is above both EMA 50 AND EMA 100
DOWNTREND: Price is below either EMA 50 OR EMA 100
🔧 Settings
Show EMA Values: Display actual EMA 50/100 values in the table
Table Position: Choose from 4 corner positions (Top Right, Top Left, Bottom Right, Bottom Left)
Plot Current EMAs: Optional display of EMA lines on your current chart
💡 Trading Applications
✅ Trend Confirmation: Ensure your trades align with higher timeframe direction
✅ Risk Management: Avoid counter-trend trades in strong directional markets
✅ Entry Timing: Use lower timeframe for entries while respecting higher timeframe bias
✅ Scalping Enhancement: Perfect for 1-5 minute scalping with higher timeframe context
🎨 Visual Design
Clean, professional table design
Intuitive color coding (Green = Up, Red = Down)
Compact size that doesn't obstruct your chart
Clear typography for quick reading
📋 Perfect For
Day traders and scalpers
Swing traders seeking trend confirmation
Multi-timeframe analysis enthusiasts
Traders who want simple, effective trend identification
🚀 Easy Setup
Add to any chart (works on all timeframes)
Customize table position and settings
Start trading with higher timeframe awareness
Watch the table update automatically
No complex configurations needed - just add and trade!
This indicator is designed for educational and informational purposes. Always combine with proper risk management and your own analysis.
Weekend Hunter Ultimate v6.2 Weekend Hunter Ultimate v6.2 - Automated Crypto Weekend Trading System
OVERVIEW:
Specialized trading strategy designed for cryptocurrency weekend markets (Saturday-Sunday) when institutional traders are typically offline and market dynamics differ significantly from weekdays. Optimized for 15-minute timeframe execution with multi-timeframe confluence analysis.
KEY FEATURES:
- Weekend-Only Trading: Automatically activates during configurable weekend hours
- Dynamic Leverage: 5-20x leverage adjusted based on market safety and signal confidence
- Multi-Timeframe Analysis: Combines 4H trend, 1H momentum, and 15M execution
- 10 Pre-configured Crypto Pairs: BTC, ETH, LINK, XRP, DOGE, SOL, AVAX, PEPE, TON, POL
- Position & Risk Management: Max 4 concurrent positions, -30% account protection
- Smart Trailing Stops: Protects profits when approaching targets
RISK MANAGEMENT:
- Maximum daily loss: 5% (configurable)
- Maximum weekend loss: 15% (configurable)
- Per-position risk: Capped at 120-156 USDT
- Emergency stops for flash crashes (8% moves)
- Consecutive loss protection (4 losses = pause)
TECHNICAL INDICATORS:
- CVD (Cumulative Volume Delta) divergence detection
- ATR-based dynamic stop loss and take profit
- RSI, MACD, Bollinger Bands confluence
- Volume surge confirmation (1.5x average)
- Weekend liquidity adjustments
INTEGRATION:
- Designed for Bybit Futures (0.075% taker fee)
- WunderTrading webhook compatibility via JSON alerts
- Minimum position size: 120 USDT (Bybit requirement)
- Initial capital: $500 recommended
TARGET METRICS:
- Win rate target: 65%
- Average win: 5.5%
- Average loss: 1.8%
- Risk-reward ratio: ~3:1
IMPORTANT DISCLAIMERS:
- Past performance does not guarantee future results
- Leveraged trading carries substantial risk of loss
- Weekend crypto markets have 13% of normal liquidity
- Not suitable for traders who cannot afford to lose their entire investment
- Requires continuous monitoring and adjustment
USAGE:
1. Apply to 15-minute charts only
2. Configure weekend hours for your timezone
3. Set up webhook alerts for automation
4. Monitor performance table in top-right corner
5. Adjust parameters based on your risk tolerance
This is an experimental strategy for educational purposes. Always test with small amounts first and never invest more than you can afford to lose completely.
IBS markerIndicator Description
This indicator provides a detailed analysis of the structure and volatility of each candlestick. It is designed to help traders better understand the balance between buying and selling pressure within individual bars, as well as the short-term volatility environment.
📌 Features
Candlestick Structure Analysis
Calculates the relative percentage of the upper wick, lower wick, and real body of each candle.
Helps traders visually and numerically evaluate whether a candle is dominated by bullish, bearish, or indecisive pressure.
IBS (Intraday Bar Strength)
Computes the Intraday Bar Strength value, showing where the close is located relative to the high-low range.
A high IBS indicates strong closing near the high, while a low IBS indicates weakness near the low.
Range Measurements
Displays the candlestick range in both price units and ticks.
Useful for traders who need precise range data for scalping or range-based strategies.
ATR (Average True Range) Volatility Filter
ATR is included with a configurable period setting.
Provides a contextual measure of volatility, helping traders compare current bar size against recent market behavior.
Dynamic Chart Labels
Key values (such as wick percentages, IBS, and range) are displayed directly on the chart through dynamic labels.
This allows for quick interpretation without opening extra panels or indicators.
📈 How to Use
Add the indicator to any chart and configure the settings (ATR period, label visibility, etc.) according to your trading style.
Use wick/body ratios to spot candles with unusual buying/selling pressure.
Combine IBS with ATR to identify potential exhaustion or continuation setups.
The dynamic labels are best used on lower timeframes for scalpers, but they can also provide insights on higher timeframes for swing traders.
🔍 Practical Applications
Identify reversal candles where one wick dominates.
Measure strength of breakouts by comparing candle body % and IBS values.
Detect volatility shifts by monitoring when bar ranges deviate from the ATR baseline.
Support scalping strategies that rely on tick-based range detection.
✅ Notes
This is a standalone indicator and does not require any other script to function.
Works on all markets (stocks, futures, forex, crypto).
For best results, use in conjunction with price action analysis or your preferred trading strategy.
