Enhanced MTF Bias Table by Odegos# Enhanced MTF Bias Table - Publication Description
## Short Description (for TradingView listing)
Multi-timeframe bias indicator combining Market Structure Shifts (MSS) with EMA analysis. Displays real-time bias across 7 timeframes (5m-Weekly) with distance metrics and volatility measurements. Perfect for identifying trend alignment and potential reversal points.
---
## Full Description
### Overview
The **Enhanced MTF Bias Table** is a comprehensive multi-timeframe analysis tool designed to help traders quickly identify market bias across different time horizons. By combining Market Structure Shift (MSS) detection with Exponential Moving Average (EMA) analysis, this indicator provides a clear, color-coded view of market sentiment from short-term (5-minute) to long-term (weekly) timeframes.
### What This Indicator Does
**Core Functionality:**
- **Multi-Timeframe Analysis**: Simultaneously monitors 7 different timeframes (5m, 15m, 30m, 1h, 4h, Daily, Weekly)
- **Market Structure Detection**: Identifies when price breaks previous swing highs/lows, indicating potential trend changes
- **EMA-Based Bias**: Combines market structure with price distance from a customizable EMA to determine bias strength
- **Visual Market Structure Shifts**: Draws horizontal lines on the chart when significant market structure shifts occur
- **Real-Time Metrics**: Displays distance from EMA and ATR (volatility) for each timeframe
### How It Works
**Bias Calculation Logic:**
The indicator uses a sophisticated two-factor approach to determine market bias:
1. **Market Structure Analysis**:
- Tracks swing highs and lows using pivot points
- Identifies when price breaks above previous highs (bullish structure) or below previous lows (bearish structure)
- Uses a customizable lookback period to filter noise
2. **EMA Distance Analysis**:
- Measures how far price is from the selected EMA
- Strong bias requires BOTH structure break AND significant distance from EMA
- Neutral zone prevents false signals when price consolidates near the EMA
**Bias Categories:**
- **Strong ↑** (Dark Green): Bullish market structure + price above EMA threshold
- **Weak ↑** (Light Green): Bullish structure OR price moderately above EMA
- **Neutral** (Orange): Price within neutral zone around EMA
- **Weak ↓** (Light Red): Bearish structure OR price moderately below EMA
- **Strong ↓** (Dark Red): Bearish market structure + price below EMA threshold
### Key Features
**📊 Customizable Table Display:**
- Two table styles: Compact (minimal) or Full (detailed with labels)
- 9 position options to fit any chart layout
- Toggle distance from EMA and ATR displays
- Shows current symbol, timeframe, and date
**📈 Flexible Indicator Settings:**
- Adjustable EMA length (default: 50)
- Customizable MSS lookback period (5-50 bars)
- Breakout threshold adjustment for different instruments
- Neutral zone configuration to reduce noise
**📍 Visual Market Structure Shifts:**
- Draws horizontal lines at significant structure breaks
- Customizable colors for bullish/bearish MSS
- Optional text labels ("MSS") for easy identification
- Adjustable line width and style (solid, dashed, dotted)
**📉 EMA Overlay:**
- Optional EMA display on chart
- Full customization: color, width, line style
- Helps visualize the reference point for bias calculations
**🎨 Full Color Customization:**
- Independent color controls for all bias levels
- Customize header and table appearance
- Matches any chart theme or preference
### Best Use Cases
**1. Trend Alignment:**
Use the MTF table to identify when multiple timeframes align in the same direction. When 5-6 or more timeframes show the same bias, it indicates strong directional momentum.
**2. Divergence Detection:**
Look for disagreements between timeframes. For example, if higher timeframes (Daily/Weekly) show bearish bias while lower timeframes (5m/15m) show bullish bias, it may indicate a counter-trend bounce or potential reversal setup.
**3. Entry Timing:**
Use higher timeframe bias for direction and lower timeframe bias for entry timing. Enter trades when your trading timeframe aligns with higher timeframe bias.
**4. Risk Management:**
When lower timeframes show opposite bias to higher timeframes, it suggests trading against the major trend—requiring tighter stops and smaller positions.
**5. Market Structure Confirmation:**
The MSS lines help identify key levels where market structure changed, useful for:
- Stop loss placement (below/above MSS levels)
- Target setting (previous structure points)
- Breakout confirmation
### Recommended Settings by Instrument
**Index Futures:**
- **ES (S&P 500)**: Breakout Threshold: 0.15%, Neutral Zone: 0.15%
- **NQ (Nasdaq)**: Breakout Threshold: 0.25%, Neutral Zone: 0.20%
- **YM (Dow Jones)**: Breakout Threshold: 0.20%, Neutral Zone: 0.20%
**Forex Pairs:**
- **Major Pairs**: Breakout Threshold: 0.10%, Neutral Zone: 0.10%
- **Volatile Pairs**: Breakout Threshold: 0.20%, Neutral Zone: 0.15%
**Cryptocurrencies:**
- Breakout Threshold: 0.30-0.50%, Neutral Zone: 0.25-0.40%
- Higher volatility requires larger thresholds
### Understanding the Metrics
**Distance from EMA (%):**
- Positive values = Price above EMA (bullish territory)
- Negative values = Price below EMA (bearish territory)
- Larger absolute values = Stronger deviation from mean
- Useful for identifying overextended moves
**ATR (%):**
- Measures current volatility as percentage of price
- Higher values = More volatile conditions
- Helps adjust position sizing and stop distances
- Compare across timeframes to see where volatility concentrates
### Tips for Optimal Use
1. **Start with higher timeframes**: Check Daily and Weekly bias first to understand the bigger picture
2. **Use the 50 EMA default**: It's widely used and provides reliable support/resistance
3. **Adjust MSS lookback for your style**: Lower values (5-7) for day trading, higher values (15-25) for swing trading
4. **Watch for neutral zones**: Orange/neutral readings often precede significant moves
5. **Combine with price action**: Use MSS lines as reference points for entries and exits
6. **Don't ignore weak signals**: "Weak" bias often precedes strong moves as structure builds
### What Makes This Different
Unlike simple moving average indicators, this script:
- Combines TWO confirmation factors (structure + distance) for more reliable signals
- Provides context across multiple timeframes simultaneously
- Visually marks important market structure changes on your chart
- Offers both compact and detailed display modes
- Includes volatility measurement to gauge market conditions
### Technical Notes
- Uses `request.security()` to fetch data from multiple timeframes
- Implements `pivothigh()` and `pivotlow()` for swing detection
- All calculations use `lookahead=barmerge.lookahead_off` to prevent repainting
- MSS lines drawn in real-time as structure breaks occur
- Optimized for performance with minimal script resources
### Disclaimer
This indicator is a tool for analysis and does not provide trading signals or financial advice. Always:
- Use proper risk management
- Combine with other forms of analysis
- Test thoroughly in a demo environment
- Understand that past performance doesn't guarantee future results
- Consider market conditions and fundamental factors
---
## Tags (for TradingView)
multi-timeframe, market-structure, bias, trend, EMA, momentum, support-resistance, price-action, volatility, ATR, swing-trading, day-trading
## Category
Trend Analysis / Multi-Timeframe Analysis
---
## Quick Start Guide
**For Day Traders:**
1. Add indicator to your chart
2. Focus on 5m, 15m, 30m, and 1h timeframes
3. Look for alignment across these timeframes
4. Use MSS lines as entry/exit reference points
**For Swing Traders:**
1. Add indicator to your chart
2. Focus on 4h, Daily, and Weekly timeframes
3. Wait for 2-3 timeframe alignment
4. Use lower timeframes only for entry timing
**For Position Traders:**
1. Add indicator to your chart
2. Focus on Daily and Weekly timeframes
3. Ignore short-term noise
4. Enter when both show same strong bias
ابحث في النصوص البرمجية عن "weekly"
Bull Engulf @ Rolling Support + HTF Confluence (2-8w) This indicator is designed to identify high-probability bullish reversal setups that occur at proven support levels, with confirmation from higher timeframes.
It is built for swing traders targeting 2–8 week moves, prioritizing win rate and trade quality over frequency.
The script focuses on institutional-style price behavior: pullbacks into support, seller exhaustion, and clear buyer confirmation before entry.
Core Logic
A signal is generated only when all of the following align:
Bullish Engulfing Candle
Current candle fully engulfs the prior candle’s body
Optional filters ensure strong momentum (close above prior high, meaningful candle size)
Rolling-Low Support
Price must be near a rolling support level based on recent swing lows
Support adapts dynamically to market structure
Higher Timeframe (HTF) Confluence
Daily setups can require alignment with weekly and monthly support
Weekly setups can require monthly support
This dramatically reduces low-quality signals
Strongest-Only Scoring System
Each setup is scored based on:
Proximity to support
HTF confluence
Candle strength
Volume and volatility filters
Only setups meeting a minimum score threshold are shown
Signals & Labels
SETUP / TOP label
Appears when a valid bullish engulfing forms at support with HTF confirmation.
ENTRY label
Appears when price breaks above the high of the engulfing candle (confirmation entry).
Support Lines
Local (rolling) support
Weekly and Monthly support (when applicable)
Each label includes:
Timeframe
Score
Support distance
Suggested risk level
A standardized options structure for 2–8 week trades
Intended Trading Style
Timeframe: Daily and Weekly charts
Trade Duration: ~2–8 weeks
Market Type: Stocks (best on liquid, mid/large-cap names)
Approach:
Wait for price to come to support
Wait for buyers to prove control
Enter only after confirmation
This indicator is not designed for:
Day trading
Chasing breakouts
High-frequency signals
Fewer signals is intentional.
How to Use
Apply the indicator to Daily or Weekly charts
Wait for a SETUP/TOP label at support
Enter only after the ENTRY confirmation (break above engulfing high)
Use the displayed risk level to define invalidation
Let the trade develop over multiple weeks
Alerts can be enabled for:
Pre-market watchlist signals (yesterday’s setups)
Confirmed signals at the close
Entry confirmation
Why This Works
Markets often reverse at support, not randomly.
By combining:
Structural support
Price-action confirmation
Higher timeframe alignment
this indicator filters out most noise and focuses on areas where larger participants are likely active.
Disclaimer
This indicator is for educational and analytical purposes only.
It does not constitute financial advice. Always manage risk appropriately.
Fifty Two Week Highs and Lows Displays 52-week highs and lows with percentage distance context, optional dashboard, and visual connections between successive new highs for long-term range awareness.
Fifty Two Week Highs and Lows
This indicator provides clear, objective context around price location within its 52-week range. It is designed to help users quickly assess how extended or compressed price is relative to its long-term highs and lows, without generating trade signals or placing orders.
What the indicator does
Calculates 52-week highs and lows using one of two reference definitions:
Daily (252 bars): Rolling high and low over a configurable number of daily bars, best suited for Daily charts.
Weekly (52 weeks): True weekly 52-week high and low values projected onto the active chart timeframe.
Displays a compact dashboard showing:
Percent below the 52-week high
Percent above the 52-week low
Both values are color-coded to provide immediate visual context.
Optionally draws lines connecting successive new 52-week highs, making sequences of higher highs easier to observe.
Alerts
Optional indicator alerts are included for:
New 52-week highs (Daily or Weekly mode)
Price entering defined distance zones relative to the 52-week high or low
All alerts are evaluated on confirmed bar close.
How to use
Add the indicator to any chart and select the preferred 52-week reference mode.
Use the dashboard values as context, not signals, to understand where price sits within its long-term range.
Enable alerts if you want notifications when price reaches specific distance thresholds.
Notes
In Weekly mode, values are derived from higher-timeframe weekly data and projected onto the active chart.
This script is an indicator only and does not place trades.
Educational and informational use only.
Bloomberg Mega Board [v2.5 Fixed]Transform your TradingView chart into a professional-grade command center. Designed for traders who need high-level market awareness without switching tabs, this dashboard provides deep, multi-timeframe analysis across US Sectors, Commodities, Currencies, and Crypto.
Key Features
1. Multi-Asset Paging System Pine Script has a limit of 40 security calls, which usually limits how much data you can see. This script bypasses that limitation using a smart Paging System:
Sectors Page: Tracks the top 10 US Sectors (SPY, XLK, XLF, etc.) & Indices.
Commodities Page: Gold, Silver, Oil, Gas, Copper, Corn, etc.
Currencies Page: Major Forex pairs including DXY, EURUSD, USDJPY.
Crypto Page: Top 10 Cryptocurrencies by volume.
Switch pages instantly via the Settings menu.
2. Smart "News" Headlines Since Pine Script cannot access the live internet for news, this script uses an Algorithmic Headline Generator. It analyzes price action and trend alignment to generate a "Market Status" summary:
Full Bull Trend: Intraday + Daily + Weekly trends are all positive.
Strong Rally: Asset is up significantly (>1.25%) on the day.
Heavy Sell-off: Asset is down significantly (<-1.25%) on the day.
Pullback (Buy?): Daily trend is UP, but Intraday is DOWN (potential entry).
Consolidating: Market is chopping sideways.
3. Timeframe Trend Matrix Monitor momentum across the curve with a single glance. The "Trend" columns are powered by the 5 EMA (Exponential Moving Average):
Intraday: Adapts to your current chart timeframe (e.g., switch your chart to 15m to see the 15m trend).
Daily / Weekly / Monthly: These are hard coded to always show the higher timeframe trend, regardless of what chart you are looking at. Trend is determined by price in relation to it's 5 EMA.
4. "Terminal" Aesthetic
Styled with a dark, high-contrast Bloomberg Terminal look.
Uses Amber tickers and Neon status blocks for rapid visual scanning.
Optimized for Full Screen Mode: Hide your main chart candles to turn your monitor into a dedicated data dashboard.
How to Use
Add the indicator to your chart and move it to "New Lower Indicator" Then repeat 4 times for each dashboard.
Open Settings (the gear icon) and find "Select Page".
Choose your desired market view (e.g., Sectors, Crypto, Currencies, Commodities)
Optional: To replicate the full dashboard look, go to your Chart Settings -> Symbol -> Uncheck "Body" and "Borders" to hide the candles behind the table.
2 hours ago
Release Notes
Transform your TradingView chart into a professional-grade command center. Designed for traders who need high-level market awareness without switching tabs, this dashboard provides deep, multi-timeframe analysis across US Sectors, Commodities, Currencies, and Crypto.
Key Features
1. Multi-Asset Paging System Pine Script has a limit of 40 security calls, which usually limits how much data you can see. This script bypasses that limitation using a smart Paging System:
Sectors Page: Tracks the top 10 US Sectors (SPY, XLK, XLF, etc.) & Indices.
Commodities Page: Gold, Silver, Oil, Gas, Copper, Corn, etc.
Currencies Page: Major Forex pairs including DXY, EURUSD, USDJPY.
Crypto Page: Top 10 Cryptocurrencies by volume.
Switch pages instantly via the Settings menu.
2. Smart "News" Headlines Since Pine Script cannot access the live internet for news, this script uses an Algorithmic Headline Generator. It analyzes price action and trend alignment to generate a "Market Status" summary:
Full Bull Trend: Intraday + Daily + Weekly trends are all positive.
Strong Rally: Asset is up significantly (>1.25%) on the day.
Heavy Sell-off: Asset is down significantly (<-1.25%) on the day.
Pullback (Buy?): Daily trend is UP, but Intraday is DOWN (potential entry).
Consolidating: Market is chopping sideways.
3. Timeframe Trend Matrix Monitor momentum across the curve with a single glance. The "Trend" columns are powered by the 5 EMA (Exponential Moving Average):
Intraday: Adapts to your current chart timeframe (e.g., switch your chart to 15m to see the 15m trend).
Daily / Weekly / Monthly: These are hard coded to always show the higher timeframe trend, regardless of what chart you are looking at. Trend is determined by price in relation to it's 5 EMA.
4. "Terminal" Aesthetic
Styled with a dark, high-contrast Bloomberg Terminal look.
Uses Amber tickers and Neon status blocks for rapid visual scanning.
Optimized for Full Screen Mode: Hide your main chart candles to turn your monitor into a dedicated data dashboard.
How to Use
Add the indicator to your chart and move it to "New Lower Indicator" Then repeat 4 times for each dashboard.
Open Settings (the gear icon) and find "Select Page".
Choose your desired market view (e.g., Sectors, Crypto, Currencies, Commodities)
Optional: To replicate the full dashboard look, go to your Chart Settings -> Symbol -> Uncheck "Body" and "Borders" to hide the candles behind the table.
2 hours ago
Release Notes
Transform your TradingView chart into a professional-grade command center. Designed for traders who need high-level market awareness without switching tabs, this dashboard provides deep, multi-timeframe analysis across US Sectors, Commodities, Currencies, and Crypto.
Key Features
1. Multi-Asset Paging System Pine Script has a limit of 40 security calls, which usually limits how much data you can see. This script bypasses that limitation using a smart Paging System:
Sectors Page: Tracks the top 10 US Sectors (SPY, XLK, XLF, etc.) & Indices.
Commodities Page: Gold, Silver, Oil, Gas, Copper, Corn, etc.
Currencies Page: Major Forex pairs including DXY, EURUSD, USDJPY.
Crypto Page: Top 10 Cryptocurrencies by volume.
Switch pages instantly via the Settings menu.
2. Smart "News" Headlines Since Pine Script cannot access the live internet for news, this script uses an Algorithmic Headline Generator. It analyzes price action and trend alignment to generate a "Market Status" summary:
Full Bull Trend: Intraday + Daily + Weekly trends are all positive.
Strong Rally: Asset is up significantly (>1.25%) on the day.
Heavy Sell-off: Asset is down significantly (<-1.25%) on the day.
Pullback (Buy?): Daily trend is UP, but Intraday is DOWN (potential entry).
Consolidating: Market is chopping sideways.
3. Timeframe Trend Matrix Monitor momentum across the curve with a single glance. The "Trend" columns are powered by the 5 EMA (Exponential Moving Average):
Intraday: Adapts to your current chart timeframe (e.g., switch your chart to 15m to see the 15m trend).
Daily / Weekly / Monthly: These are hard coded to always show the higher timeframe trend, regardless of what chart you are looking at. Trend is determined by price in relation to it's 5 EMA.
4. "Terminal" Aesthetic
Styled with a dark, high-contrast Bloomberg Terminal look.
Uses Amber tickers and Neon status blocks for rapid visual scanning.
Optimized for Full Screen Mode: Hide your main chart candles to turn your monitor into a dedicated data dashboard.
How to Use
Add the indicator to your chart and move it to "New Lower Indicator" Then repeat 4 times for each dashboard.
Open Settings (the gear icon) and find "Select Page".
Choose your desired market view (e.g., Sectors, Crypto, Currencies, Commodities)
Optional: To replicate the full dashboard look, go to your Chart Settings -> Symbol -> Uncheck "Body" and "Borders" to hide the candles behind the table.
2 hours ago
Release Notes
Transform your TradingView chart into a professional-grade command center. Designed for traders who need high-level market awareness without switching tabs, this dashboard provides deep, multi-timeframe analysis across US Sectors, Commodities, Currencies, and Crypto.
Key Features
1. Multi-Asset Paging System Pine Script has a limit of 40 security calls, which usually limits how much data you can see. This script bypasses that limitation using a smart Paging System:
Sectors Page: Tracks the top 10 US Sectors (SPY, XLK, XLF, etc.) & Indices.
Commodities Page: Gold, Silver, Oil, Gas, Copper, Corn, etc.
Currencies Page: Major Forex pairs including DXY, EURUSD, USDJPY.
Crypto Page: Top 10 Cryptocurrencies by volume.
Switch pages instantly via the Settings menu.
2. Smart "News" Headlines Since Pine Script cannot access the live internet for news, this script uses an Algorithmic Headline Generator. It analyzes price action and trend alignment to generate a "Market Status" summary:
Full Bull Trend: Intraday + Daily + Weekly trends are all positive.
Strong Rally: Asset is up significantly (>1.25%) on the day.
Heavy Sell-off: Asset is down significantly (<-1.25%) on the day.
Pullback (Buy?): Daily trend is UP, but Intraday is DOWN (potential entry).
Consolidating: Market is chopping sideways.
3. Timeframe Trend Matrix Monitor momentum across the curve with a single glance. The "Trend" columns are powered by the 5 EMA (Exponential Moving Average):
Intraday: Adapts to your current chart timeframe (e.g., switch your chart to 15m to see the 15m trend).
Daily / Weekly / Monthly: These are hard coded to always show the higher timeframe trend, regardless of what chart you are looking at. Trend is determined by price in relation to it's 5 EMA.
4. "Terminal" Aesthetic
Styled with a dark, high-contrast Bloomberg Terminal look.
Uses Amber tickers and Neon status blocks for rapid visual scanning.
Optimized for Full Screen Mode: Hide your main chart candles to turn your monitor into a dedicated data dashboard.
How to Use
Add the indicator to your chart and move it to "New Lower Indicator" Then repeat 4 times for each dashboard.
Open Settings (the gear icon) and find "Select Page".
Choose your desired market view (e.g., Sectors, Crypto, Currencies, Commodities)
Optional: To replicate the full dashboard look, go to your Chart Settings -> Symbol -> Uncheck "Body" and "Borders" to hide the candles behind the table.
Master Strategy: BTC W1 Mean Reversion [Institutional SOP]Overview This is an institutional-grade Mean Reversion and Range Rotation strategy designed specifically for Bitcoin (BTC/USDT) Perpetual Futures. It operates on the philosophy that liquidity resides at the extremes of the previous week's range (Previous Week High/Low). The strategy looks for false breakouts (Sweeps) followed by a confirmed return to the range (Reclaim), targeting the weekly equilibrium (EQ).
Core Logic: The Deviation Play Unlike standard breakout strategies, this indicator hunts for trapped liquidity.
Weekly Levels (Fixed): It calculates PWH (Previous Week High) and PWL (Previous Week Low) based on confirmed, closed weekly data. These levels act as the "Box" for the current week.
The Sweep: We wait for price to pierce the PWH or PWL (taking liquidity/stops). The script uses a dynamic ATR-based threshold to filter out noise (micro-pokes).
The Reclaim (4H Close): A signal is generated ONLY if a 4H candle closes back inside the weekly range shortly after the sweep. This confirms rejection of higher/lower prices.
The Entry: The script suggests a Limit Order at the retested level (PWH/PWL) to maximize R:R.
Institutional Quality Filters ("Kill Switches") To prevent trading in unfavorable conditions, the script includes strict SOP (Standard Operating Procedure) filters:
Trend Filter (ADX): Blocks mean reversion signals if the daily trend is too strong (ADX > 25).
Expansion Filter: Blocks signals if price accepted levels outside the range for too long (prevents fighting a true breakout).
Weekly Range Filter: Filters out weeks that are statistically too tight (chop) or too wide (expansion).
Time Filter: A reclaim must happen within a set number of 4H bars after the sweep (default: 3).
Key Features
Zero Repainting: Logic is based strictly on closed candles ( , , ).
State Machine Logic: Uses internal memory to track sweeps regardless of chart timeframe glitches.
Operational Dashboard: Displays current status, countdown to next decision candle (4H close), and exact parameters for the last valid signal (Entry, SL, TP).
Unified Alerting: A single "Any function call" alert handles both Long and Short scenarios dynamically.
Clean Visuals: Levels are plotted with line breaks to avoid visual clutter between weeks.
How to Use
Timeframe: Set your chart to 4H. This is crucial as the logic relies on 4H closes.
Signals: Wait for the "4H RECLAIM" label.
Execution: Place a Limit Order at the suggested Level (PWH/PWL).
Stop Loss: Use the calculated SL provided by the indicator (Swing extreme + ATR buffer).
Target: TP1 is always the EQ (Equilibrium/Mid-range).
Liquidity Maxing [JOAT]Liquidity Maxing - Institutional Liquidity Matrix
Introduction
Liquidity Maxing is an open-source strategy for TradingView built around institutional market structure concepts. It identifies structural shifts, evaluates trades through multi-factor confluence, and implements layered risk controls.
The strategy is designed for swing trading on 4-hour timeframes, focusing on how institutional order flow manifests in price action through structure breaks, inducements, and liquidity sweeps.
Core Functionality
Liquidity Maxing performs three primary functions:
Tracks market structure to identify when control shifts between buyers and sellers
Scores potential trades using an eight-factor confluence system
Manages position sizing and risk exposure dynamically based on volatility and user-defined limits
The goal is selective trading when multiple conditions align, rather than frequent entries.
Market Structure Engine
The structure engine tracks three key events:
Break of Structure (BOS): Price pushes beyond a prior pivot in the direction of trend
Change of Character (CHoCH): Control flips from bullish to bearish or vice versa
Inducement Sweeps (IDM): Market briefly runs stops against trend before moving in the real direction
The structure module continuously updates strong highs and lows, labeling structural shifts visually. IDM markers are optional and disabled by default to maintain chart clarity.
The trade engine requires valid structure alignment before considering entries. No structure, no trade.
Eight-Factor Confluence System
Instead of relying on a single indicator, Liquidity Maxing uses an eight-factor scoring system:
Structure alignment with current trend
RSI within healthy bands (different ranges for up and down trends)
MACD momentum agreement with direction
Volume above adaptive baseline
Price relative to main trend EMA
Session and weekend filter (configurable)
Volatility expansion/contraction via ATR shifts
Higher-timeframe EMA confirmation
Each factor contributes one point to the confluence score. The default minimum confluence threshold is 6 out of 8, but you can adjust this from 1-8 based on your preference for trade frequency versus selectivity.
Only when structure and confluence agree does the strategy proceed to risk evaluation.
Dynamic Risk Management
Risk controls are implemented in multiple layers:
ATR-based stops and targets with configurable risk-to-reward ratio (default 2:1)
Volatility-adjusted position sizing to maintain consistent risk per trade as ranges expand or compress
Daily and weekly risk budgets that halt new entries once thresholds are reached
Correlation cooldown to prevent clustered trades in the same direction
Global circuit breaker with maximum drawdown limit and emergency kill switch
If any guardrail is breached, the strategy will not open new positions. The dashboard clearly displays risk state for transparency.
Market Presets
The strategy includes configuration presets optimized for different market types:
Crypto (BTC/ETH): RSI bands 70/30, volume multiplier 1.2, enhanced ATR scaling
Forex Majors: RSI bands 75/25, volume multiplier 1.5
Indices (SPY/QQQ): RSI bands 70/30, volume multiplier 1.3
Custom: Default values for user customization
For crypto assets, the strategy automatically applies ATR volatility scaling to account for higher volatility characteristics.
Monitoring and Dashboards
The strategy includes optional monitoring layers:
Risk Operations Dashboard (top-right):
Trend state
Confluence score
ATR value
Current position size percentage
Global drawdown
Daily and weekly risk consumption
Correlation guard state
Alert mode status
Performance Console (top-left):
Net profit
Current equity
Win rate percentage
Average trade value
Sharpe-style ratio (rolling 50-bar window)
Profit factor
Open trade count
Optional risk tint on chart background provides visual indication of "safe to trade" versus "halted" state.
All visualization elements can be toggled on/off from the inputs for clean chart viewing or full telemetry during parameter tuning.
Alerts and Automation
The strategy supports alert integration with two formats:
Standard alerts: Human-readable messages for long, short, and risk-halt conditions
Webhook format: JSON-formatted payloads ready for external execution systems (optional)
Alert messages are predictable and unambiguous, suitable for manual review or automated forwarding to execution engines.
Built-in Validation Suite
The strategy includes an optional validation layer that can be enabled from inputs. It checks:
Internal consistency of structure and confluence metrics
Sanity and ordering of risk parameters
Position sizing compliance with user-defined floors and caps
This validation is optional and not required for trading, but provides transparency into system operation during development or troubleshooting.
Strategy Parameters
Market Presets:
Configuration Preset: Choose between Crypto (BTC/ETH), Forex Majors, Indices (SPY/QQQ), or Custom
Market Structure Architecture:
Pivot Length: Default 5 bars
Filter by Inducement (IDM): Default enabled
Visualize Structure: Default enabled
Structure Lookback: Default 50 bars
Risk & Capital Preservation:
Risk:Reward Ratio: Default 2.0
ATR Period: Default 14
ATR Multiplier (Stop): Default 2.0
Max Drawdown Circuit Breaker: Default 10%
Risk per Trade (% Equity): Default 1.5%
Daily Risk Limit: Default 6%
Weekly Risk Limit: Default 12%
Min Position Size (% Equity): Default 0.25%
Max Position Size (% Equity): Default 5%
Correlation Cooldown (bars): Default 3
Emergency Kill Switch: Default disabled
Signal Confluence:
RSI Length: Default 14
Trend EMA: Default 200
HTF Confirmation TF: Default Daily
Allow Weekend Trading: Default enabled
Minimum Confluence Score (0-8): Default 6
Backtesting Considerations
When backtesting this strategy, consider the following:
Commission: Default 0.05% (adjustable in strategy settings)
Initial Capital: Default $100,000 (adjustable)
Position Sizing: Uses percentage of equity (default 2% per trade)
Timeframe: Optimized for 4-hour charts, though can be tested on other timeframes
Results will vary significantly based on:
Market conditions and volatility regimes
Parameter settings, especially confluence threshold
Risk limit configuration
Symbol characteristics (crypto vs forex vs equities)
Past performance does not guarantee future results. Win rate, profit factor, and other metrics should be evaluated in context of drawdown periods, trade frequency, and market conditions.
How to Use This Strategy
This is a framework that requires understanding and parameter tuning, not a one-size-fits-all solution.
Recommended workflow:
Start on 4-hour timeframe with default parameters and appropriate market preset
Run backtests and study performance console metrics: focus on drawdown behavior, win rate, profit factor, and trade frequency
Adjust confluence threshold to match your risk appetite—higher thresholds mean fewer but more selective trades
Set realistic daily and weekly risk budgets appropriate for your account size and risk tolerance
Consider ATR multiplier adjustments based on market volatility characteristics
Only connect alerts or automation after thorough testing and parameter validation
Treat this as a risk framework with an integrated entry engine, not merely an entry signal generator. The risk controls are as important as the trade signals.
Strategy Limitations
Designed for swing trading timeframes; may not perform optimally on very short timeframes
Requires sufficient market structure to identify pivots; may struggle in choppy or low-volatility environments
Crypto markets require different parameter tuning than traditional markets
Risk limits may prevent entries during favorable setups if daily/weekly budgets are exhausted
Correlation cooldown may delay entries that would otherwise be valid
Backtesting results depend on data quality and may not reflect live trading with slippage
Design Philosophy
Many indicators tell you when price crossed a moving average or RSI left oversold. This strategy addresses questions institutional traders ask:
Who is in control of the market right now?
Is this move structurally significant or just noise?
Do I want to add more risk given what I've already done today/week?
If I'm wrong, exactly how painful can this be?
The strategy provides disciplined, repeatable answers to these questions through systematic structure analysis, confluence filtering, and multi-layer risk management.
Technical Implementation
The strategy uses Pine Script v6 with:
Custom types for structure, confluence, and risk state management
Functional programming approach for reusable calculations
State management through persistent variables
Optional visual elements that can be toggled independently
The code is open-source and can be modified to suit individual needs. All important logic is visible in the source code.
Disclaimer
This script is provided for educational and informational purposes only. It is not intended as financial, investment, trading, or any other type of advice or recommendation. Trading involves substantial risk of loss and is not suitable for all investors. Past performance, whether real or indicated by historical tests of strategies, is not indicative of future results.
No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between backtested results and actual results subsequently achieved by any particular trading strategy.
The user should be aware of the risks involved in trading and should trade only with risk capital. The authors and publishers of this script are not responsible for any losses or damages, including without limitation, any loss of profit, which may arise directly or indirectly from use of or reliance on this script.
This strategy uses technical analysis methods and indicators that are not guaranteed to be accurate or profitable. Market conditions change, and strategies that worked in the past may not work in the future. Users should thoroughly test any strategy in a paper trading environment before risking real capital.
Commission and slippage settings in backtests may not accurately reflect live trading conditions. Real trading results will vary based on execution quality, market liquidity, and other factors not captured in backtesting.
The user assumes full responsibility for all trading decisions made using this script. Always consult with a qualified financial advisor before making investment decisions.
Enjoy - officialjackofalltrades
Elite Monday Range V3- ProfessionalElite Monday Range V3 - Advanced Institutional Bias & Analysis
Overview
The Elite Monday Range V3 is a high-performance decision-support tool designed for traders who utilize the "Weekly Open" and "Monday's Range" as their primary benchmark for the trading week. Unlike standard range indicators, this script employs an advanced Multi-Asset Analysis Engine to determine the weekly bias with institutional-grade precision.
It doesn't just draw lines; it analyzes Previous Week's Close (PWC), Monday's Candle Structures (Price Action), and Internal Liquidity to provide a definitive "Directional Bias" and "Confidence Score."
Key Features
Smart Multi-Asset Detection: Automatically detects if you are trading Forex, Crypto, or Indices and adjusts its internal logic and strategy suggestions accordingly.
Institutional Bias Engine: Calculates a Confidence Score (from -4 to +4) based on 4 critical criteria:
Price vs. Previous Week Close: Checks if the bulls or bears are maintaining momentum from the prior week.
Monday Candle Analysis: Automatically identifies Pin Bars (Liquidity Grabs) or Strong Engulfing movements.
Price vs. Monday Midpoint (Equilibrium): The ultimate pivot point for weekly trend direction.
Price vs. Weekly Open: Tracks the "true" opening sentiment.
Liquidity Hunt Signals (Judas Swing): Visual alerts for LIQ BUY and LIQ SELL when price sweeps Monday's extremes and returns inside the range—a classic sign of institutional manipulation before a trend.
Symmetric Expansion Levels: Projects +50%, +100%, -50%, and -100% extensions of the Monday range to identify high-probability Take Profit (TP) and reversal zones.
Dynamic Professional Dashboard: A sleek, real-time table on your chart that summarizes Asset Type, Weekly Bias, Candle Info, and the Confidence Score.
Force Overlay Technology: Ensures all lines and labels remain visible and crisp on the top layer, above candles and other indicators.
How to Trade with the Elite Dashboard
Check the "Net Weekly Bias": Look for STRONG BULL or STRONG BEAR.
Verify Confidence Score: A score of 3 or 4 (or -3/-4 for shorts) indicates high-probability conditions.
Identify Entry: If the Bias is "STRONG BULL," wait for a retest of the Monday Mid (MID) or Monday High (MON H).
Confirm with Liquidity: Look for a LIQ BUY signal near the Monday Low for the highest-quality "A+ Setup."
Target: Use the Expansion Levels (+50% / +100%) as your primary targets for the week.
Technical Settings
Lookback Weeks: Choose exactly how many historical weeks to display to keep your chart clean.
Customizable Colors: Fully adjustable colors for Monday ranges and expansion projections.
Line Width: User-defined thickness for professional visual clarity.
Short-Term Bubble Risk [Phantom] Short-Term Bubble Risk
Concept
This indicator visualizes short-term market risk by measuring how far price is stretched relative to its recent weekly trend.
Instead of focusing on absolute price levels, it looks at price behavior.
A similar reading means similar market conditions, whether price is high or low.
The goal is to help identify areas of potential accumulation and potential distribution in a clear, visual way.
How It Works
The indicator compares the weekly closing price to a weekly moving average and displays the deviation as a histogram.
When price is far below its average, risk is considered lower
When price is far above its average, risk is considered higher
The zero line represents fair value, where price equals its weekly average.
Features
Color-coded histogram showing short-term risk levels
Designed to work across different assets and price ranges
Optional bar coloring on the main chart using weekly risk data
Safe to use on any timeframe (risk is calculated on weekly data)
Settings
# Moving Average Length (Weeks):
Adjusts how sensitive the indicator is to price changes
# Color Visibility Toggles:
Allows hiding or showing specific risk zones
# Bar Coloring:
Option to color chart candles based on weekly risk levels
Usage
This indicator is best used as a risk lens, not a timing tool.
Common uses include:
Identifying potential accumulation zones during weakness
Spotting overextended conditions during strong moves
Comparing short-term risk across different assets
Adding context to trend-following or DCA strategies
Trade Ideas
# Lower-risk zones (cool colors):
Can support accumulation or patience during downtrends
# Higher-risk zones (warm colors):
Can signal caution, reduced exposure, or profit-taking
Always combine with:
Trend direction
Market structure
Higher-timeframe context
Limitations
This indicator does not predict tops or bottoms
High risk can remain high during strong trends
Low risk does not guarantee immediate reversals
It should not be used as a standalone trading system.
Disclaimer
This indicator is for educational and informational purposes only.
It is not financial advice.
Always do your own research and manage risk appropriately.
Previous Day Week Month Highs & Lows [MHA Finverse]Previous Day Week Month Highs & Lows is a comprehensive multi-timeframe indicator that automatically plots previous period highs and lows across Daily, Weekly, Monthly, 4-Hour, and 8-Hour timeframes. Perfect for identifying key support and resistance levels that often act as magnets for price action.
How It Works
The indicator retrieves the highest high and lowest low from the previous completed period for each selected timeframe. Lines extend forward into current price action, allowing you to see when price approaches or breaks these critical levels in real-time. The indicator tracks the exact bar where each high and low occurred, ensuring accurate historical placement.
---
Key Features
Multi-Timeframe Levels:
• Current Daily, Previous Daily, 4H, 8H, Weekly, and Monthly highs/lows
• Fully customizable colors and line styles (Solid, Dashed, Dotted)
• Adjustable line width and extension length
Visual Enhancements:
• Price labels showing exact level values
• Range position percentage (distance from high/low)
• Optional period boxes highlighting timeframe ranges
• Day and date labels for reference
Trading Tools:
• Breakout markers when price crosses key levels
• Touch count tracking (how many times price tested each level)
• Time at level display (consolidation detection)
• Customizable thresholds for touch and time analysis
Alert System:
• Individual alerts for each timeframe: Daily High/Low Break, 4H High/Low Break, 8H High/Low Break, Weekly High/Low Break, Monthly High/Low Break
• Toggle switches to enable/disable alerts per timeframe
• Clear messages showing which level was broken and at what price
---
How to Use
Setup:
1. Enable your preferred timeframes in "Highs & Lows MTF" settings
2. Customize colors and styles to match your chart
3. Turn on visual features like price labels and range percentages
4. Set up alerts by creating specific alert conditions or using toggle switches
Trading Applications:
Breakout Trading: Watch for strong momentum when price breaks above previous highs or below previous lows
Support/Resistance: Use these levels as potential reversal points for entry/exit signals
Range Trading: Trade between previous highs and lows using the range position indicator
Stop Loss Placement: Place stops just beyond previous highs (shorts) or lows (longs)
Multiple Timeframe Confirmation: Combine timeframes for stronger signals (e.g., Daily near Weekly support)
---
Best Practices
• Use Weekly/Monthly for swing trading, Daily/4H/8H for day trading
• Combine with volume or momentum indicators for confirmation
• Multiple timeframe levels clustering together create high-probability zones
• The more touches a level has, the more significant it becomes
---
Disclaimer
This indicator is a technical analysis tool for identifying price levels based on historical data. It does not guarantee profits or predict future movements. Trading involves substantial risk. Always use proper risk management and never risk more than you can afford to lose.
ShooterViz Lazy Trader EMA SystemShooterViz Lazy Trader EMA System - Complete User Guide
What This Script Does
This is a position scaling indicator that tells you exactly when to enter, add to, and exit trades using a simplified 5-EMA system. It removes the guesswork and decision fatigue from trading by giving you clear visual signals.
The Core Concept
3 entry signals that build your position from 20% → 50% → 100%
2 exit signals that scale you out at 50% → 50% (complete exit)
1 higher timeframe filter that keeps you on the right side of the trend
No Fibonacci calculations, no RSI divergence, no multi-indicator confusion. Just EMAs and price action.
What You'll See On Your Chart
1. Colored EMA Lines
Blue Lines (Entry Zone):
3 EMA (lightest blue) - Early reversal detector
5 EMA (darker blue) - Confirmation line
Green Lines (Add Zone):
21 EMA (bright green) - First add location
34 EMA (lighter green) - Final add location
Red Lines (Exit Zone):
89 EMA (lighter red) - First exit trigger
144 EMA (darker red) - Final exit trigger
Orange Lines (Hyper Frame - optional):
Hyper 21 EMA (from higher timeframe) - Trend direction
Hyper 34 EMA (from higher timeframe) - Bias confirmation
2. Triangle Signals
Green Triangles (Below Price) = BUY/ADD:
Lime triangle with "20%" = Entry 1: Price reclaimed 3→5 EMA (starter position)
Green triangle with "30%" = Entry 2: Price bounced off 21 EMA (first add)
Teal triangle with "50%" = Entry 3: Price broke out from 34 EMA compression (final add)
Red Triangles (Above Price) = SELL:
Orange triangle with "50% OFF" = Exit 1: Price broke below 89 EMA (take half off)
Red triangle with "EXIT ALL" = Exit 2: Price broke below 144 EMA (close remaining position)
3. Background Color (Trend Bias)
Light green background = Hyper frame EMAs trending up (bias LONG)
Light red background = Hyper frame EMAs trending down (bias SHORT)
Gray background = Neutral/choppy (be cautious)
4. Info Table (Top Right Corner)
A live status dashboard showing:
Which entry signals are currently active (✓ or —)
Which exit signals are currently active (⚠ or ⛔)
Current hyper frame bias (🟢 LONG / 🔴 SHORT / ⚪ NEUTRAL)
Which timeframe you're using for hyper frame filtering
How to Install and Set Up
Step 1: Add the Script to TradingView
Open TradingView
Click "Pine Editor" at the bottom of the screen
Copy the entire script code
Paste it into the Pine Editor
Click "Add to Chart"
Step 2: Configure Your Settings
Click the gear icon ⚙️ next to "LazyEMA" in your indicators list.
Critical Settings to Configure:
Hyper Frame Selection (Most Important!)
Location: "Hyper Frame (Pick ONE)" section
Setting: "Timeframe"
What to choose:
Trading 15min or 1H charts? → Use "240" (4-hour)
Trading 4H or Daily charts? → Use "D" (Daily)
Trading Daily or Weekly charts? → Use "W" (Weekly)
Why this matters: This filter keeps you aligned with the bigger trend. Only take longs when this timeframe is green, shorts when it's red.
MA Type (Optional, default is fine)
Location: "MA Config" section
Default: EMA (recommended)
Options: EMA, SMA, WMA, HMA, RMA, VWMA
Most traders should stick with EMA
Visual Toggles (Customize your view)
Entry Zone: Turn individual EMAs on/off (3, 5, 21, 34)
Exit Zone: Turn individual EMAs on/off (89, 144)
Hyper Frame: Toggle the higher timeframe EMAs on/off
Step 3: Clean Up Your Chart
Turn OFF these if visible:
Volume bars (they clutter the view)
Any other indicators you have loaded
Grid lines (optional, but cleaner)
Keep ONLY:
Price candles
Your ShooterViz Lazy Trader EMA System
Maybe support/resistance levels if you manually draw them
How to Trade With This Script
The Basic Workflow
Before the Market Opens:
Check the background color and info table bias
Green background? Look for LONG setups only
Red background? Look for SHORT setups only
Gray background? Stay flat or trade small
During the Trading Session:
LONGS (When hyper frame is bullish):
Wait for Entry 1 signal:
Lime triangle appears with "20%"
Price has reclaimed the 5 EMA after dipping to 3 EMA
Action: Enter 20% of your intended position
Stop loss: Place below the 5 EMA or recent swing low
Wait for Entry 2 signal:
Green triangle appears with "30%"
Price pulled back to 21 EMA and bounced
Action: Add 30% more (you're now at 50% total)
Move stop: Trail it up to below 21 EMA
Wait for Entry 3 signal:
Teal triangle appears with "50%"
Price compressed at 34 EMA and broke out
Action: Add final 50% (you're now 100% loaded)
Move stop: Trail it up to below 34 EMA
Wait for Exit 1 signal:
Orange triangle appears with "50% OFF"
Price broke below 89 EMA
Action: Exit 50% of your position immediately
Move stop on rest: Trail to 89 EMA or lock in profits
Wait for Exit 2 signal:
Red triangle appears with "EXIT ALL"
Price broke below 144 EMA
Action: Exit remaining 50% (you're now flat)
Or: Stop gets hit at 89 EMA (same result)
SHORTS (When hyper frame is bearish):
Same process, but inverted
Triangles appear above price instead of below
Look for breakdowns below EMAs instead of bounces off them
Exit when price reclaims 89 and 144 EMAs
Real-World Example Walkthrough
Setup: Trading ES (S&P 500 Futures) on 1H Chart
Chart Configuration:
Timeframe: 1 Hour
Hyper Frame: 240 (4-hour)
Ticker: ES
Pre-Market Check:
Background is light green
Info table shows "🟢 LONG" for Hyper Bias
Decision: Only look for long entries today
9:30 AM - Market Opens
Price dips and touches 3 EMA
Watch for: Reclaim of 5 EMA
9:45 AM - Entry 1 Triggers
Lime triangle appears below bar
Price closed above 5 EMA at $4,550
Action taken:
Enter long 20% position (2 contracts if targeting 10 total)
Stop loss at $4,545 (below 5 EMA)
Risk: $10 per contract × 2 = $20 risk
10:30 AM - Entry 2 Triggers
Price rallied to $4,565, pulls back
Green triangle appears at 21 EMA ($4,555)
Action taken:
Add 30% (3 more contracts, now have 5 total)
Move stop to $4,550 (below 21 EMA)
Current P/L: +$25 ($5 gain on original 2 contracts, break-even on new 3)
11:15 AM - Entry 3 Triggers
Price consolidates at 34 EMA around $4,560
Teal triangle appears as price breaks to $4,568
Action taken:
Add final 50% (5 more contracts, now have 10 total)
Move stop to $4,555 (below 34 EMA)
Current P/L: +$70
1:00 PM - Price Extends
Price rallies to $4,595 (on track)
89 EMA is at $4,575
No action yet, let it run
2:15 PM - Exit 1 Triggers
Price pulls back from $4,600
Orange triangle appears as price breaks below 89 EMA at $4,580
Action taken:
Exit 50% (5 contracts closed at $4,580)
Keep 5 contracts with stop at 89 EMA ($4,575)
Banked: +$150 average gain on closed 5 contracts
2:45 PM - Exit 2 Triggers
Price continues down
Red triangle appears as price breaks 144 EMA at $4,570
Action taken:
Exit remaining 5 contracts at $4,570
Banked: +$100 on remaining 5 contracts
Final Results:
Total gain: $250 on the trade
Initial risk: $50 (if stopped out at Entry 1)
Risk/Reward: 5:1
Time in trade: ~5 hours
Common Questions
"What if I miss Entry 1? Can I still take Entry 2?"
Yes! Each entry is independent. If you miss the 3→5 reclaim, wait for the 21 EMA bounce. You'll start with a 30% position instead of 20%, but that's fine.
Rule: Never chase. Wait for the next EMA setup.
"What if multiple entry signals trigger at the same bar?"
Rare, but possible. If you see both Entry 1 and Entry 2 trigger together:
Take Entry 1 first (20%)
If the next bar confirms Entry 2 is still valid, add 30%
When in doubt, scale in gradually
"The hyper frame is green but I'm seeing short signals?"
Don't take them. The hyper frame is your bias filter. If it says "go long," ignore short setups. They're usually lower probability and will get stopped out.
"Can I use this for swing trading overnight?"
Absolutely. Just switch your hyper frame:
If you're on Daily charts, use Weekly hyper frame
If you're on 4H charts, use Daily hyper frame
Adjust position sizes for overnight risk
"What if the signal appears right at market close?"
Don't chase it. Wait for the next bar (next day) to confirm. Signals that appear in the last 5 minutes are often noise.
"How do I set up alerts?"
Right-click on the chart
Select "Add Alert"
Choose "LazyEMA" from the condition dropdown
Select which signal you want alerts for:
Entry 1: 3→5 Reclaim
Entry 2: 21 EMA Add
Entry 3: 34 EMA Breakout
Exit 1: 89 EMA Break
Exit 2: 144 EMA Break
Click "Create"
Pro tip: Set up all 5 alerts so you never miss a signal.
Position Sizing Guide see
swingtradenotes.substack.com
Critical Rule: Know your total risk BEFORE you take Entry 1. Don't wing it.
Customization Tips
For Day Traders (Scalpers)
Use 5min or 15min charts
Hyper frame: 1H or 4H
Expect 2-4 setups per day
Tighter stops (0.5% risk per entry)
For Swing Traders
Use 4H or Daily charts
Hyper frame: Daily or Weekly
Expect 1-2 setups per week
Wider stops (1-2% risk per entry)
For Position Traders
Use Daily or Weekly charts
Hyper frame: Weekly or Monthly
Expect 1-2 setups per month
Widest stops (2-3% risk per entry)
The "Don't Be Stupid" Checklist
Before taking ANY signal from this script, ask:
✅ Is the hyper frame bias pointing in my direction?
✅ Is the signal clean (not at a weird time or during news)?
✅ Do I know my stop loss level?
✅ Do I know my position size?
✅ Can I afford to lose if this trade fails?
If you answered "no" to ANY of these, skip the trade.
Troubleshooting
"I'm not seeing any signals"
Possible causes:
The "Show Lazy Trader System" toggle is off (turn it on)
Your chart timeframe is too high (try 1H or 4H)
Market is in a tight range (EMAs are compressed)
You need to refresh the chart
"Too many signals, getting whipsawed"
Fixes:
Increase your chart timeframe (go from 15m to 1H)
Switch to a less volatile ticker
Only trade when hyper frame bias is STRONG (not neutral)
Add a minimum bar count between signals
"The info table is covering my price action"
Fix:
Edit the script
Find the line: table.new(position.top_right, ...
Change position.top_right to position.bottom_right or position.top_left
"Signals appear then disappear"
This is normal (repainting). Some signals (especially compression breakouts) can disappear if the next bar reverses. This is why you:
Wait for bar close before acting
Use alerts that only fire on confirmed bars
Don't chase signals mid-bar
Final Thoughts
This script is a decision-making tool, not a crystal ball. It shows you high-probability setups based on EMA dynamics and trend structure. You still need to:
Manage your risk
Choose your position size
Stick to the rules
Accept losses when they happen
The system works when YOU work the system.
Print this guide, tape it next to your monitor, and follow it religiously for 20 trades before making ANY changes.
Good luck, and stay lazy (the smart way).
Reversal WaveThis is the type of quantitative system that can get you hated on investment forums, now that the Random Walk Theory is back in fashion. The strategy has simple price action rules, zero over-optimization, and is validated by a historical record of nearly a century on both Gold and the S&P 500 index.
Recommended Markets
SPX (Weekly, Monthly)
SPY (Monthly)
Tesla (Weekly)
XAUUSD (Weekly, Monthly)
NVDA (Weekly, Monthly)
Meta (Weekly, Monthly)
GOOG (Weekly, Monthly)
MSFT (Weekly, Monthly)
AAPL (Weekly, Monthly)
System Rules and Parameters
Total capital: $10,000
We will use 10% of the total capital per trade
Commissions will be 0.1% per trade
Condition 1: Previous Bearish Candle (isPrevBearish) (the closing price was lower than the opening price).
Condition 2: Midpoint of the Body The script calculates the exact midpoint of the body of that previous bearish candle.
• Formula: (Previous Open + Previous Close) / 2.
Condition 3: 50% Recovery (longCondition) The current candle must be bullish (green) and, most importantly, its closing price must be above the midpoint calculated in the previous step.
Once these parameters are met, the system executes a long entry and calculates the exit parameters:
Stop Loss (SL): Placed at the low of the candle that generated the entry signal.
Take Profit (TP): Calculated by projecting the risk distance upward.
• Calculation: Entry Price + (Risk * 1).
Risk:Reward Ratio of 1:1.
About the Profit Factor
In my experience, TradingView calculates profits and losses based on the percentage of movement, which can cause returns to not match expectations. This doesn’t significantly affect trending systems, but it can impact systems with a high win rate and a well-defined risk-reward ratio. It only takes one large entry candle that triggers the SL to translate into a major drop in performance.
For example, you might see a system with a 60% win rate and a 1:1 risk-reward ratio generating losses, even though commissions are under control relative to the number of trades.
My recommendation is to manually calculate the performance of systems with a well-defined risk-reward ratio, assuming you will trade using a fixed amount per trade and limit losses to a fixed percentage.
Remember that, even if candles are larger or smaller in size, we can maintain a fixed loss percentage by using leverage (in cases of low volatility) or reducing the capital at risk (when volatility is high).
Implementing leverage or capital reduction based on volatility is something I haven’t been able to incorporate into the code, but it would undoubtedly improve the system’s performance dramatically, as it would fix a consistent loss percentage per trade, preventing losses from fluctuating with volatility swings.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to exit or SL
And if volatility is high and exceeds the fixed percentage we want to expose per trade (if SL is hit), we could reduce the position size.
For example, imagine we only want to risk 15% per SL on Tesla, where volatility is high and would cause a 23.57% loss. In this case, we subtract 23.57% from 15% (the loss percentage we’re willing to accept per trade), then subtract the result from our usual position size.
23.57% - 15% = 8.57%
Suppose I use $200 per trade.
To calculate 8.57% of $200, simply multiply 200 by 8.57/100. This simple calculation shows that 8.57% equals about $17.14 of the $200. Then subtract that value from $200:
$200 - $17.14 = $182.86
In summary, if we reduced the position size to $182.86 (from the usual $200, where we’re willing to lose 15%), no matter whether Tesla moves up or down 23.57%, we would still only gain or lose 15% of the $200, thus respecting our risk management.
Final Notes
The code is extremely simple, and every step of its development is detailed within it.
If you liked this strategy, which complements very well with others I’ve already published, stay tuned. Best regards.
Luxy VWAP Magic - MTF Projection EngineThis indicator transforms the classic VWAP into a comprehensive trading system. Instead of switching between multiple indicators, you get everything in one place: multi-timeframe analysis, statistical bands, momentum detection, volume profiling, session tracking, and divergence signals.
What Makes This Different
Traditional VWAP indicators show a single line. This tool treats VWAP as a foundation for complete market analysis. The indicator automatically detects your asset type (stocks, crypto, forex, futures) and adjusts its behavior accordingly. Crypto traders get 24/7 session tracking. Stock traders get proper market hours handling. Everyone gets institutional-grade analytics.
Anchor Period Options
The anchor period determines when VWAP resets and recalculates. You have three categories of options:
Time-Based Anchors:
Session - Resets at market open. Best for intraday stock trading where you want fresh VWAP each day.
Day - Resets at midnight UTC. Standard option for most traders.
Week / Month / Quarter / Year - Longer reset periods for swing traders and position traders who want broader context.
Rolling Window Anchors:
Rolling 5D - A sliding 5-day window that never resets. Solves the Monday problem where weekly VWAP equals daily VWAP on first day of week.
Rolling 21D - Approximately one month of trading data in continuous calculation. Excellent for crypto and forex markets that trade 24/7 without clear session breaks.
Event-Based Anchors:
Dividends - Resets on ex-dividend dates. Track institutional cost basis from dividend events.
Splits - Resets on stock split dates. Useful for analyzing post-split trading behavior.
Earnings - Resets on earnings report dates. See where volume-weighted trading occurred since last quarterly report.
Standard Deviation Bands
Three sets of bands surround the main VWAP line:
Band 1 (Aqua) - Plus and minus one standard deviation. Approximately 68% of price action occurs within this range under normal distribution. Touches suggest minor extension.
Band 2 (Fuchsia) - Plus and minus two standard deviations. Only 5% of trading should occur outside this range statistically. Touches here indicate significant overextension and high probability of mean reversion.
Band 3 (Purple) - Plus and minus three standard deviations. Touches are rare (0.3% probability) and represent extreme conditions. Often marks climax moves or panic selling/buying.
Each band can be toggled independently. Most traders show Band 1 by default and add Band 2 and 3 for specific setups or volatile instruments.
Multi-Timeframe VWAP System
The MTF section plots previous period VWAPs as horizontal support and resistance levels:
Daily VWAP - Previous day's final VWAP value. Key intraday reference level.
Weekly VWAP - Previous week's final VWAP. Important for swing traders.
Monthly VWAP - Previous month's final VWAP. Institutional benchmark level.
Quarterly VWAP - Previous quarter's final VWAP. Major support/resistance for position traders.
Previous Day VWAP - Yesterday's closing VWAP specifically, separate from current daily calculation.
The Confluence Zone percentage setting determines how close multiple VWAPs must be to trigger a confluence alert. When two or more timeframe VWAPs converge within this threshold, you get a high-probability support/resistance zone.
Session VWAPs for Global Markets
For forex, crypto, and futures traders who operate in 24/7 markets, the indicator tracks three major global sessions:
Asia Session - UTC 21:00 to 08:00. Gold colored line. Typically lower volatility, range-bound action that sets overnight levels.
London Session - UTC 08:00 to 17:00. Orange colored line. Often determines daily direction with high volume European participation.
New York Session - UTC 13:00 to 22:00. Blue colored line. Highest volume session globally. Sharp directional moves common.
Previous session VWAP values display as horizontal lines when each session closes, acting as intraday support and resistance. The table shows which sessions are currently active with checkmarks.
On-Chart Labels and Signals
The indicator plots several types of labels directly on price action when significant events occur:
Volume Spike Labels
Fire when current bar volume exceeds configurable thresholds relative to both the previous bar and the 20-bar average. Default settings require 300% of previous bar AND 200% of average volume. Green labels indicate bullish candles. Red labels indicate bearish candles. These spikes often mark institutional entry points.
Momentum Shift Labels
Appear when VWAP acceleration changes direction. The Slowing label warns when an active trend loses steam, often preceding reversal. The Accelerating label confirms trend continuation or potential bottom during downtrends. Filters available to show only reversal signals in existing trends.
VWAP Squeeze Labels
Detect when standard deviation bands contract relative to ATR (Average True Range). Low volatility compression often precedes explosive breakout moves. When the squeeze fires (releases), a label appears with directional prediction based on VWAP slope.
Divergence Labels
Mark price/volume divergences using CVD (Cumulative Volume Delta) analysis:
Bullish divergence: Price makes lower low, but CVD makes higher low. Hidden accumulation despite price weakness.
Bearish divergence: Price makes higher high, but CVD makes lower high. Hidden distribution despite price strength.
Dynamic VWAP Coloring
The main VWAP line changes color based on its slope direction:
Green - VWAP is rising. Institutional buying pressure. Volume-weighted price increasing.
Red - VWAP is falling. Institutional selling pressure. Volume-weighted price decreasing.
Gray - VWAP is flat. Consolidation or balance between buyers and sellers.
This coloring can be disabled for a static blue line if you prefer cleaner visuals. The VWAP label next to the line shows the current trend direction and delta percentage.
Calculated Projection Cone
One of the most powerful features is the Calculated Projection Cone. Unlike traditional extrapolation methods that simply extend a trend line forward, this system analyzes what actually happened in similar market conditions throughout the chart's history.
How It Works:
The system classifies each bar into one of 27 unique market states:
Z-Score Level - LOW (oversold), MID (fair value), or HIGH (overbought) based on configurable thresholds
Trend Direction - DOWN, FLAT, or UP based on VWAP slope
Volume Profile - LOW (below 80%), NORMAL (80-150%), or HIGH (above 150%) relative volume
When you look at the current bar, the indicator:
1. Identifies the current market state (e.g., LOW Z-Score + UP Trend + HIGH Volume)
2. Searches through all historical bars on the chart that had the same state
3. Calculates what happened in those bars X bars later (where X is your projection horizon)
4. Shows you the probability of up/down and the average move size
Visual Elements:
Probability Cone - Colored green (bullish probability above 55%), red (bearish below 45%), or gold (neutral). The cone width represents the historical range of outcomes (roughly the 20th to 80th percentile).
Center Line - Shows the average expected price based on historical outcomes in similar conditions.
Probability Label - Displays direction probability and average move. Example: "67% UP (+0.8%)" means 67% of similar past cases moved up, averaging 0.8% gain.
Fallback System:
When the exact 27-state match has insufficient historical data:
First fallback: Uses Z-Score plus Trend only (9 broader states, ignoring volume)
Second fallback: Uses Z-Score only (3 states)
When fallback is active, confidence automatically adjusts
Settings:
Projection Horizon - How many bars forward to analyze outcomes (5, 10, 15, or 20 bars, default 10)
Lookback Period - Historical data window in days (30-252, default 60)
Minimum Samples - Cases needed before using fallback (5-30, default 10)
Z-Score Threshold - Bucket boundary for LOW/MID/HIGH classification (1.0, 1.5, or 2.0 sigma)
Cloud Transparency - Adjust visibility (50-95%)
Colors - Customize bullish, bearish, and neutral cone colors
Confidence Levels:
HIGH - 30 or more similar historical cases found
MEDIUM - 15-29 similar cases
LOW - Fewer than 15 cases (more uncertainty)
IMPORTANT DISCLAIMER:
The Calculated Projection is based on past patterns only. It is NOT a price prediction or financial advice. Similar market states in the past do not guarantee similar outcomes in the future. The probability shown is historical frequency, not a guarantee. Always combine with other analysis and never rely solely on projections for trading decisions.
Alert Conditions
The indicator includes over 20 pre-built alert conditions:
Price vs VWAP:
Price crosses above VWAP
Price crosses below VWAP
Band Touches:
Price touches plus or minus one sigma band
Price touches plus or minus two sigma band (extreme)
Price touches plus or minus three sigma band (very extreme)
Z-Score Extremes:
Z-Score crosses above plus two (overbought extreme)
Z-Score crosses below minus two (oversold extreme)
Momentum and Trend:
Momentum slowing
Momentum accelerating
Trend turns bullish/bearish/neutral
Volume:
Volume spike detected
CVD Direction:
Buyers take control
Sellers take control
High Probability Signals:
Bullish reversal signal (oversold plus accelerating momentum)
Bearish reversal signal (overbought plus slowing momentum)
MTF and Special:
MTF confluence zone entry
VWAP squeeze fired
Bullish/Bearish divergence detected
Any significant signal (catch-all)
All signals use confirmed bar data to prevent false alerts from incomplete candles.
Settings Overview
Settings are organized into logical groups:
VWAP Settings
Anchor Period selection
Show/Hide VWAP line
Dynamic coloring toggle
VWAP label visibility
Bands Visibility
Toggle each of three bands independently
Info Table
Show/Hide table
Table position (9 options)
Text size
Volume spike label settings with adjustable thresholds
Momentum label settings with filters
Signal labels limited to 5 most recent (auto-managed)
Probability engine lookback period
Multi-Timeframe VWAP
Enable/Disable MTF system
Show MTF in table
Show MTF lines on chart
Individual timeframe toggles
Confluence zone threshold
Squeeze detection toggle
Session VWAPs
Enable/Disable session tracking
Apply to all assets option
Show session labels
Divergence Detection
Enable/Disable divergence
Pivot lookback period
Show divergence labels
Calculated Projection
Enable/Disable projection cone
Projection horizon (5, 10, 15, or 20 bars)
Lookback period in days (30-252)
Minimum samples threshold
Z-Score classification threshold (1.0, 1.5, or 2.0 sigma)
Cloud transparency adjustment
Bullish, bearish, and neutral colors
The Info Table - Your Trading Dashboard
The right side of your chart displays a compact table with up to twelve metrics.
Row-by-Row Breakdown:
Asset and Period - Shows what the indicator detected (US Stock, Crypto, Forex, etc.) and your selected anchor period. The detection happens automatically based on exchange data, so VWAP resets and calculations match your actual trading instrument.
Delta Percentage - How far current price sits from VWAP, expressed as a percentage. Positive means price trades above fair value. Negative means below. Large delta values (beyond 1-2%) often precede mean reversion moves. Day traders watch this for overextension.
Z-Score - Statistical deviation from VWAP measured in standard deviations. Unlike raw delta, Z-Score accounts for volatility. A 2% move in a volatile biotech stock differs from 2% in a stable utility. Z-Score normalizes this. Values beyond plus or minus two sigma occur only 5% of the time statistically.
Trend Direction - Whether VWAP itself is rising, falling, or flat. Rising VWAP means the volume-weighted average price is increasing, which indicates institutional accumulation. Falling VWAP suggests distribution. This differs from price trend since it weights by volume.
Momentum State - Is the trend accelerating or slowing down? This measures the rate of change in VWAP slope. When an uptrend shows slowing momentum, it often precedes reversal. Accelerating momentum in a downtrend can signal capitulation and potential bottom.
Relative Volume - Current bar volume compared to the 20-bar average, shown as percentage. Values above 150% indicate above-average activity. Spikes above 200-300% often mark institutional involvement. Low volume (below 80%) warns of potential fake moves.
MTF Bias - Four checkmarks or X marks showing whether price sits above or below Daily, Weekly, Monthly, and Quarterly VWAP. Four checkmarks means strong bullish alignment across all timeframes. Four X marks indicates bearish alignment. Mixed readings suggest consolidation or transition.
Band Probabilities - Historical statistics showing how often price touched each standard deviation band over your lookback period. This helps you understand if mean reversion or trend following works better for your specific instrument.
Session Status - Which global trading sessions are currently active (Asia, London, New York). Shows checkmarks for active sessions. Important for forex and crypto traders who need to know when major liquidity windows open and close.
Divergence State - Whether the indicator detects bullish or bearish divergence between price and cumulative volume delta. Bullish divergence occurs when price makes lower lows but buying pressure (CVD) makes higher lows, suggesting hidden accumulation.
Confidence Score - A weighted composite of all factors displayed as a progress bar and percentage. Combines MTF alignment, Z-Score, trend direction, volume delta, momentum, and relative volume into a single 0-100 score. Higher scores indicate stronger conviction setups.
Calculated Projection - When the Projection Cone is enabled, shows the historical probability of price direction and expected move. For example: "▲ 67% (+0.8%)" means in similar market states historically, price moved up 67% of the time with an average gain of 0.8%. The system analyzes 27 unique market states based on Z-Score, Trend, and Volume conditions.
Recommended Use Cases
Day Trading Stocks:
Use Session anchor with Band 1 visible. Watch for price returning to VWAP after morning move. Volume spikes near VWAP often mark institutional accumulation zones.
Swing Trading:
Use Weekly or Rolling 21D anchor. Enable MTF lines for Daily and Weekly levels. Trade pullbacks to these levels in direction of MTF bias.
Crypto and Forex:
Enable Session VWAPs. Use Rolling anchors to avoid artificial resets. Monitor session transitions for breakout opportunities.
Mean Reversion:
Focus on Z-Score reaching plus or minus two. Add Band 2 visibility. Combine with slowing momentum for highest probability reversals.
Trend Following:
Watch MTF bias alignment. Four checkmarks plus accelerating momentum plus high volume confirms trend continuation setups.
Projection Planning:
Enable the Calculated Projection to see what happened historically in similar market conditions. Use 5-10 bars for intraday setups, 15-20 bars for swing trade planning. Focus on high probability readings (above 60%) with HIGH confidence (30 or more samples). The cone shows the probable range of outcomes based on actual historical data. Combine with other factors like MTF alignment and volume for higher conviction setups.
Important Notes
The indicator does not repaint. MTF values use previous period's confirmed data.
Rolling VWAP works best on 15-minute timeframes and above due to bar lookback requirements.
Session VWAPs apply to global markets by default (forex, crypto, futures). Enable the all-assets option for stocks if desired.
Volume data for forex represents tick volume, not actual traded volume.
All alert conditions fire only on confirmed (closed) bars to prevent false signals.
The Calculated Projection updates each bar as market state changes. This is expected behavior. The projection shows probabilities based on similar past conditions, not a fixed prediction.
Q AND A
Q: Does this indicator repaint?
A: No. The main VWAP calculation uses standard TradingView VWAP methodology. Multi-timeframe values use previous period's confirmed data with appropriate lookahead settings. All alert signals require bar confirmation.
Q: Why does my Rolling VWAP look different on 1-minute versus 15-minute charts?
A: Rolling VWAP calculates across a fixed number of trading days. On very short timeframes, the bar lookback may hit TradingView limits. For best Rolling VWAP accuracy, use 15-minute or higher timeframes.
Q: Can I use this on any instrument?
A: Yes. The indicator automatically detects asset type and adjusts behavior. Stocks use standard market hours. Crypto uses 24/7 calculations. Forex uses tick volume. Everything adapts automatically.
Q: What does the Confidence Score actually measure?
A: The score combines six weighted factors: MTF alignment (25%), Z-Score position (20%), Trend direction (20%), CVD pressure (15%), Momentum state (10%), and Relative volume (10%). Higher scores indicate more factors aligned in one direction.
Q: Why are Session VWAPs not showing on my stock chart?
A: Session VWAPs apply to 24-hour markets by default (forex, crypto, futures). For stocks, enable the Use for All Assets option in Session VWAP settings.
Q: The Divergence labels appear delayed. Is this a bug?
A: Divergence detection requires pivot confirmation, which needs bars on both sides of the pivot point. The label appears at the actual pivot location (several bars back) once confirmed. This is intentional and prevents false signals.
Q: Can I change the band colors?
A: Yes. Each of the three bands has its own color input setting. You can customize Band 1, Band 2, and Band 3 colors to match your preferences. The defaults are Aqua, Fuchsia, and Purple. The main VWAP line color adapts dynamically based on slope direction or can be set to static blue.
Q: How do I set up alerts?
A: Right-click on the chart, select Add Alert, choose this indicator, and select your desired condition from the dropdown. All conditions include descriptive alert messages with relevant data.
Q: What is the Probability Engine lookback period?
A: This setting determines how many trading days the indicator analyzes to calculate band touch rates and mean reversion statistics. Default is 60 days (approximately 3 months). Longer periods provide more stable statistics but may miss recent behavior changes.
Q: Why do I see fewer labels than expected?
A: Signal labels (Volume, Momentum, Squeeze, Divergence) are limited to 5 most recent labels on the chart to keep it clean. When a new label appears, the oldest one is automatically removed. Additionally, momentum labels have several filters: check the slope multiplier setting (higher values require stronger trends) and the Only Reversal Signals option (when enabled, labels only appear for potential reversals, not trend confirmations).
Q: What is the Calculated Projection and how accurate is it?
A: The Calculated Projection analyzes what happened in past market conditions similar to the current state. It classifies each bar by Z-Score level, Trend direction, and Volume profile (27 unique states), then shows the historical probability of up vs down and the average move size. It is NOT a price prediction or guarantee. The probability shown is how often similar conditions led to up/down moves historically, not a future guarantee. Always use it as one input among many.
Q: Why does the Projection probability change?
A: The projection updates on each bar as market state changes. If Z-Score moves from LOW to MID, or trend shifts from UP to FLAT, the system looks up a different historical category. This is expected behavior. The projection shows what happened in similar past conditions to the current bar's state.
Q: The Projection shows LOW confidence. What does that mean?
A: Confidence levels indicate sample size: HIGH means 30 or more historical cases found, MEDIUM means 15-29 cases, LOW means fewer than 15 cases. When sample size is low, the system uses a fallback: first aggregating by Z-Score plus Trend only (ignoring volume), then by Z-Score only. LOW confidence means less statistical reliability, so weight other factors more heavily in your decision.
Q: Why does the cone sometimes show 50/50 probability?
A: A 50/50 reading means that in similar past market states, price moved up roughly half the time and down half the time. This indicates a neutral or balanced condition where historical patterns provide no directional edge. Consider waiting for a higher probability setup or using other analysis methods.
CREDITS AND ACKNOWLEDGMENTS
Methodology Foundation:
VWAP (Volume Weighted Average Price) - Standard institutional benchmark calculation, widely used since the 1980s for algorithmic execution and fair value assessment
Standard Deviation Bands - Statistical volatility measurement applying normal distribution principles to price deviation from mean
Z-Score Analysis - Classic statistical normalization technique for comparing values across different volatility regimes
Cumulative Volume Delta (CVD) - Order flow analysis concept measuring aggressive buying versus selling pressure
Concept Integration:
Mean reversion probability engine - Custom historical statistics tracking for band touch rates
Momentum acceleration detection - Second derivative analysis of VWAP slope changes
VWAP Squeeze - Volatility compression concept adapted from TTM Squeeze methodology applied to VWAP bands versus ATR
Confidence scoring system - Weighted composite scoring combining multiple technical factors
Calculated Projection Cone - Probability-based projection using 27-state market classification (Z-Score, Trend, Volume) with historical outcome analysis and weighted fallback system
All calculations use standard public domain formulas and TradingView built-in functions. No proprietary third-party code was used.
For questions, feedback, or feature requests, please comment below or send a private message.
Happy Trading!
Week high / Week low (Mo–Fr)The indicator tracks the weekly high and low levels of the market starting from Monday 00:00 and updates them throughout the week until Friday. It draws horizontal lines across the chart representing:
Weekly High
Weekly Low
Each level also displays a label that can be positioned in different ways depending on user settings.
🧠 How it works step-by-step
1. Every Monday a new week starts
When a new week begins:
The script stores the current candle’s high as the initial weekHigh
And the current candle’s low as weekLow
Previous week's lines and labels are deleted
New horizontal lines are created and extended to the right
Labels (for high & low) are placed initially at the start of the week
2. During Monday–Friday
On every candle:
If a new higher price is reached → weekly high updates
If a new lower price is reached → weekly low updates
The horizontal line moves to the new value
A saved index remembers where that high/low was created
3. Label Position Control
The user can choose how labels should be anchored:
Mode Meaning
Update point Label stays where the high/low occurred
Right edge Label always moves to the current bar (right end of week)
Right offset Like Right edge but shifted further right by X bars
You can also customize:
label background color
label text color
label size
whether the label points up/down (above or below the line)
line color, style, and width
4. Weekend behavior
On Saturday, the script stops extending the lines, effectively freezing the weekly high and low for that completed week.
Summary
This indicator is useful for traders who want automatic weekly levels, visually clean chart structure, and customizable label placement. It tracks market structure weekly, keeps levels persistent across the chart, and lets you choose exactly how those levels appear.
If you want, I can also create:
✔ previous week high/low
✔ midline (50% of the range)
✔ alerts when price breaks the weekly high/low
✔ highlight liquidity sweeps
Momentum Structural AnalysisMomentum Structural Analysis (MSA‑style Oscillator)
This indicator implements a simple, MSA‑style momentum oscillator that measures how far price has moved above or below its own long‑term trend on the active timeframe, expressed in percentage terms. Instead of looking at raw price, it "oscillates" price around a timeframe‑appropriate simple moving average (SMA) and plots the percentage distance from that SMA as an orange line around a zero baseline. Zero means price is exactly at its structural trend; positive values mean price is extended above trend; negative values mean it is trading below trend.
The script automatically selects the SMA length based on the chart timeframe:
On daily charts it uses the configurable Daily SMA Length (default 252 trading days, roughly 1 year).
On weekly charts it uses Weekly SMA Length (default 208 weeks).
On monthly charts it uses Monthly SMA Length (default 120 months).
This approach is inspired by the ideas behind Momentum Structural Analysis (MSA), which studies where a market trades relative to long‑term moving averages and then treats the momentum line (the oscillator) as the primary object of analysis. The goal is to highlight structural overbought/oversold conditions and regime changes that are often clearer on momentum than on the raw price chart.
--------------------------------------------------
What the script computes and how it works
For each bar, the indicator:
Chooses an SMA length based on the current timeframe (daily/weekly/monthly).
Calculates the SMA of the close.
Computes the percentage distance:
\text{Diff %} = \frac{\text{Close} - \text{SMA}}{\text{SMA}} \times 100
Plots this Diff % as an orange line, with a dashed horizontal zero line as the base.
This produces a momentum oscillator that oscillates around zero and reflects the "structural" position of price versus its own long‑term mean.
--------------------------------------------------
How to use it on index charts (e.g., NIFTY50)
On indices like NIFTY50, use the indicator to see how stretched the index is versus its structural trend.
Typical uses:
Identify extremes: a). Historically high positive readings can signal euphoric, late‑stage conditions where risk is elevated. b). Deep negative readings can highlight panic/capitulation zones where downside may be exhausted.
Draw structural levels: a). Mark horizontal bands on the oscillator where past turns have occurred (e.g., +15%, −10%, etc. specific to NIFTY50). b). Watch how price behaves when the oscillator revisits these zones: repeated rejections can validate them as structural bounds; clean breaks can indicate a change of regime.
This is not a buy/sell signal generator by itself; it is a framework to understand where the index sits within its long‑term momentum structure and to support risk‑management decisions.
--------------------------------------------------
How to use it on ratio charts
Apply the same indicator to ratio symbols such as NIFTY50/GOLD, BANKNIFTY/NIFTY50, sector vs index, or any spread you plot as a ratio.
On a ratio chart:
The oscillator now measures relative momentum: how far that ratio is above or below its own long‑term mean.
High positive readings = strong outperformance of the numerator vs the denominator (e.g., equities strongly outperforming gold).
Deep negative readings = strong underperformance (e.g., equities structurally lagging gold).
This is very much in the spirit of MSA’s work on spreads between asset classes: it helps visualize major rotations (equities → gold, financials → commodities, etc.) and whether a relative‑performance trend is stretched, reverting, or breaking into a new phase.
--------------------------------------------------
Using multiple timeframes for better decisions
You can stack information across timeframes to get a more robust view:
Monthly : a). Use monthly charts to see secular/structural phases. b). Long multi‑year stretches above or below zero, and large bases or trendline breaks on the monthly oscillator, can mark major bull or bear cycles and big rotations between asset classes.
Weekly : a). Use weekly charts for the primary trend. b). Weekly structures (multi‑month highs/lows, channels, or trendlines on the oscillator) are useful for medium‑term positioning and for confirming or rejecting signals seen on the monthly view.
Daily : a). Use daily charts mainly for timing entries/exits once the higher‑timeframe direction is clear. b). Short‑term extremes on the daily oscillator that align with the larger weekly/monthly structure can offer better‑timed opportunities, while signals that contradict higher‑timeframe momentum are more likely to be noise.
--------------------------------------------------
One for AllOne for All (OFA) - Complete ICT Analysis Suite
Version 3.3.0 by theCodeman
📊 Overview
One for All (OFA) is a comprehensive TradingView indicator designed for traders who follow Inner Circle Trader (ICT) concepts. This all-in-one tool combines essential ICT analysis features—sessions, kill zones, previous period levels, and higher timeframe candles with Fair Value Gaps (FVGs) and Volume Imbalances (VIs)—into a single, highly customizable indicator. Whether you're a beginner learning ICT concepts or an experienced trader refining your edge, OFA provides the visual structure needed for precise market analysis and execution.
✨ Key Features
- 🏷️ Customizable Watermark**: Display your trading identity with customizable titles, subtitles, symbol info, and full style control
- 🌍 Trading Sessions**: Visualize Asian, London, and New York sessions with high/low lines, range boxes, and open/close markers
- 🎯 Kill Zones**: Highlight 5 critical ICT kill zones with precise timing and visual boxes
- 📈 Previous Period H/L**: Track Daily, Weekly, and Monthly highs/lows with customizable styles and lookback periods
- 🕐 Higher Timeframe Candles**: Display up to 5 HTF timeframes with OHLC trace lines, timers, and interval labels
- 🔍 FVG & VI Detection**: Automatically detect and visualize Fair Value Gaps and Volume Imbalances on HTF candles
- ⚙️ Universal Timezone Support**: Works globally with GMT-12 to GMT+14 timezone selection
- 🎨 Full Customization**: Control colors, styles, visibility, and layout for every feature
🚀 How to Use
Watermark Setup
The watermark overlay helps you identify your charts and maintain focus on your trading principles:
1. Enable/disable watermark via "Show Watermark" toggle
2. Customize the title (default: "Name") to display your trading name or account identifier
3. Set up to 3 subtitles (default: "Patience", "Confidence", "Execution") as trading reminders
4. Choose position (9 locations available), size, color, and transparency
5. Toggle symbol and timeframe display as needed
Use Case: Display your trading principles or account name for multi-monitor setups or content creation.
Trading Sessions Analysis
Sessions define market character and liquidity availability:
1. Enable "Show All Sessions" to visualize all three sessions
2. Adjust timezone to match your local market (default: UTC-5 for EST)
3. Customize session times if needed (defaults cover standard hours)
4. Enable session range boxes to see consolidation zones
5. Use session high/low lines to identify key levels for the current session
6. Enable open/close markers to track session transitions
Use Case: Identify which session you're trading in, track session highs/lows for liquidity, and anticipate session transition volatility.
Kill Zones Trading
Kill zones are ICT's high-probability trading windows:
1. Enable individual kill zones or use "Show All Kill Zones"
2. **Asian Kill Zone** (2000-0000 GMT): Early positioning and smart money accumulation
3. **London Kill Zone** (0300-0500 GMT): European market opening volatility
4. **NY AM Kill Zone** (0930-1100 EST): Post-NYSE open expansion
5. **NY Lunch Kill Zone** (1200-1300 EST): Midday consolidation or manipulation
6. **NY PM Kill Zone** (1330-1600 EST): Afternoon positioning and closes
7. Customize colors and times to match your trading style
8. Set max days display to control historical visibility (default: 30 days)
Use Case: Focus entries during high-probability windows. Watch for liquidity sweeps at kill zone openings and institutional positioning.
Previous Period High/Low Levels
Previous period levels act as magnetic price targets and support/resistance:
1. Enable Daily (PDH/PDL), Weekly (PWH/PWL), or Monthly (PMH/PML) levels individually
2. Set lookback period (how many previous periods to display)
3. Choose line style: Solid (current emphasis), Dashed (standard), or Dotted (subtle)
4. Customize colors per timeframe for visual hierarchy
5. Adjust line width (1-5) for visibility preference
6. Enable gradient effect to fade older periods
7. Position labels left or right based on chart layout
8. Customize label text for your preferred notation
Use Case: Identify key levels where price is likely to react. Daily levels work on intraday timeframes, Weekly on daily charts, Monthly for swing trading.
Higher Timeframe (HTF) Candles
HTF candles reveal the larger market context while trading lower timeframes:
1. Enable up to 5 HTF slots simultaneously (default: 5m, 15m, 1H, 4H, Daily)
2. Choose display mode: "Below Chart" (stacked rows) or "Right Side" (compact column)
3. Customize timeframe, colors (bull/bear), and titles for each slot
4. **OHLC Trace Lines**: Visual lines connecting HTF candle levels to chart bars
5. **HTF Timer**: Countdown showing time remaining until HTF candle close
6. **Interval Labels**: Display day of week (Daily+) or time (intraday) on each candle
7. For Daily candles: Choose open time (Midnight, 8:30, 9:30) to match your market structure preference
Use Case: Trade lower timeframes while respecting higher timeframe structure. Watch for HTF candle closes to confirm directional bias.
FVG & VI Detection
Fair Value Gaps and Volume Imbalances highlight inefficiencies that price often revisits:
1. **Fair Value Gaps (FVGs)**: Detected when HTF candle wicks don't overlap between 3 consecutive candles
- Bullish FVG: Gap between candle 1 high and candle 3 low (green box by default)
- Bearish FVG: Gap between candle 1 low and candle 3 high (red box by default)
2. **Volume Imbalances (VIs)**: Similar detection but focuses on body gaps
- Bullish VI: Gap between candle 1 close and candle 3 open
- Bearish VI: Gap between candle 1 open and candle 3 close
3. Enable FVG/VI detection per HTF slot individually
4. Customize colors and transparency for each imbalance type
5. Boxes appear on chart at formation and remain visible as retracement targets
**Use Case**: Identify high-probability retracement zones. Price often returns to fill FVGs and VIs before continuing the trend. Use as entry zones or profit targets.
🎨 Customization
OFA is built for flexibility. Every feature includes extensive customization options:
Visual Customization
- **Colors**: Independent color control for every element (sessions, kill zones, lines, labels, FVGs, VIs)
- **Transparency**: Adjust box and label transparency (0-100%) for clean charts
- **Line Styles**: Choose Solid, Dashed, or Dotted for previous period lines
- **Sizes**: Control text size, line width, and box borders
- **Positions**: Place watermark in 9 positions, labels left/right
Layout Control
- **HTF Display Mode**: "Below Chart" for detailed analysis, "Right Side" for space efficiency
- **Drawing Limits**: Set max days for sessions/kill zones to manage chart clutter
- **Lookback Periods**: Control how many previous periods to display (1-10)
- **Gradient Effects**: Enable fading for older previous period lines
Timing Adjustments
- **Timezone**: Universal GMT offset selector (-12 to +14) for global markets
- **Session Times**: Customize each session's start/end times
- **Kill Zone Times**: Adjust kill zone windows to match your market's characteristics
- **Daily Open**: Choose Midnight, 8:30, or 9:30 for Daily HTF candle open time
💡 Best Practices
1. Start Simple: Enable one feature at a time to learn how each element affects your analysis
2. Match Your Timeframe: Use Daily levels on intraday charts, Weekly on daily charts, HTF candles one or two levels above your trading timeframe
3. Kill Zone Focus: Concentrate your trading activity during kill zones for higher probability setups
4. HTF Confirmation: Wait for HTF candle closes before committing to directional bias
5. FVG/VI Entries: Look for price to return to unfilled FVGs/VIs for entry opportunities with favorable risk/reward
6. Customize Colors: Use a consistent color scheme that matches your chart theme and reduces visual fatigue
7. Reduce Clutter: Disable features you're not actively using in your current trading plan
8. Session Context: Understand which session controls the market—trade with session direction or anticipate reversals at session transitions
⚙️ Settings Guide
OFA organizes settings into logical groups for easy navigation:
- **═══ WATERMARK ═══**: Title, subtitles, position, style, symbol/timeframe display
- **═══ SESSIONS ═══**: Enable/disable sessions, times, colors, high/low lines, boxes, markers
- **═══ KILL ZONES ═══**: Individual kill zone toggles, times, colors, max days display
- **═══ PREVIOUS H/L - DAILY ═══**: Daily high/low lines, style, color, lookback, labels
- **═══ PREVIOUS H/L - WEEKLY ═══**: Weekly high/low lines, style, color, lookback, labels
- **═══ PREVIOUS H/L - MONTHLY ═══**: Monthly high/low lines, style, color, lookback, labels
- **═══ HTF CANDLES ═══**: Global display mode, layout settings
- **═══ HTF SLOT 1-5 ═══**: Individual HTF configuration (timeframe, colors, title, FVG/VI detection, trace lines, timer, interval labels)
Each setting includes tooltips explaining its function. Hover over any input for detailed guidance.
📝 Final Notes
One for All (OFA) represents a complete ICT analysis toolkit in a single indicator. By combining watermark customization, session visualization, kill zone highlighting, previous period levels, and higher timeframe candles with FVG/VI detection, OFA eliminates the need for multiple indicators cluttering your chart.
**Version**: 3.3.0
**Author**: theCodeman
**Pine Script**: v6
**License**: Mozilla Public License 2.0
Start with default settings to learn the indicator's structure, then customize extensively to match your personal trading style. Remember: tools provide information, but your edge comes from disciplined execution of a proven strategy.
Happy Trading! 📈
Minervini VCP Pattern -Indian ContextThis script implements Mark Minervini's Trend Template and VCP (Volatility Contraction Pattern) pattern, specifically adapted for Indian stock markets (NSE). It helps identify stocks that are in strong uptrends and ready to break out.
Core Concepts Explained
1. What is the Minervini Trend Template?
Mark Minervini's method identifies stocks in Stage 2 uptrends - the sweet spot where institutional money is accumulating and stocks show the strongest momentum. Think of it as finding stocks that are "leaders" rather than "laggards."
2. What is VCP (Volatility Contraction Pattern)?
A VCP occurs when:
Stock price consolidates (moves sideways) after an uptrend
Price swings get tighter and tighter (like a coiled spring)
Volume dries up (fewer people trading)
Then it breaks out with force.
You can customize the strategy settings without editing code.
Key Settings:
Minimum Price (₹50): Filters out penny stocks that are too volatile
Min Distance from 52W Low (30%): Stock should be at least 30% above its yearly low
Max Distance from 52W High (25%): Stock should be within 25% of its yearly high (showing strength)
Moving Average Periods: 10, 50, 150, 200 days (industry standard)
Minimum Volume (100,000 shares): Ensures the stock is liquid enough to trade
Indian Market Adaptation: The default values (₹50 minimum, volume thresholds) are adjusted for NSE stocks, which behave differently than US markets.
The script pulls weekly chart data even when you're viewing daily charts.
Why it matters: Weekly trends are more reliable than daily noise. Professional traders use weekly charts to confirm the bigger picture.
What are Moving Averages (MAs)?
Simple averages of closing prices over X days
They smooth out price action to show trends
Think of them as the "average cost" of buyers over different time periods
The 4 Key MAs:
10 MA (Fast): Very short-term trend
50 MA: Short to medium-term trend
150 MA: Medium to long-term trend
200 MA: Long-term trend (the "grandfather" of all MAs)
Why Weekly MAs?
The script also calculates 10 and 50 MAs on weekly data for additional confirmation of the bigger trend.
The script Finds the highest and lowest prices over the past 52 weeks (1 year).
Why it matters:
Stocks near 52-week highs are showing strength (institutions buying)
Stocks far from 52-week lows have "room to run" upward
This is a psychological level that influences trader behaviour.
What is Volume here ?
The number of shares traded each day
High volume = many traders interested (conviction)
Low volume = lack of interest (weakness or consolidation)
Volume in VCP:
During consolidation (sideways movement), volume should dry up - this shows sellers are exhausted and buyers are holding. When volume spikes on a breakout, it confirms the move.
NSE Context: Indian stocks often have different volume patterns than US stocks, so the 50-day average is used as a baseline.
Relative Strength vs Nifty:
Example:
If your stock is up 20% and Nifty is up 10%, your stock has strong RS
If your stock is up 5% and Nifty is up 15%, your stock has weak RS (avoid it!)
Why it matters: The best performing stocks almost always have strong relative strength before major moves.
The 13 Minervini Conditions:-
Condition 1: Price > 50/150/200 MA
Meaning: Current price must be above ALL three major moving averages.
Why: This confirms the stock is in a clear uptrend. If price is below these MAs, the stock is weak or in a downtrend.
Condition 2: MA 50 > 150 > 200
Meaning: The moving averages themselves must be in proper order.
Analogy: Think of this like layers in a cake - short-term on top, long-term at bottom. If they're tangled, the trend is unclear.
Condition 3: 200 MA Rising (1 Month)
Meaning: The 200 MA today must be higher than it was 20 days ago.
Why: This confirms the long-term trend is UP, not flat or down. The means "20 bars ago."
Condition 4: 50 MA Rising
Meaning: The 50 MA today must be higher than 5 days ago.
Why: Confirms short-term momentum is accelerating upward.
Condition 5: Within 25% of 52-Week High
Meaning: Current price should be within 25% of its 1-year high.
Example:
52-week high = ₹1000
Current price must be above ₹750 (within 25%)
Why: Strong stocks stay near their highs. Weak stocks fall far from highs.
Condition 6: 30%+ Above 52-Week Low (OPTIONAL)
Meaning: Stock should be at least 30% above its yearly low.
Note: The script marks this as "SECONDARY - Optional" because the other conditions are more important. However, it's still a good confirmation.
Condition 7: Price > 10 MA
Meaning: Very short-term strength - price above the 10-day moving average.
Why: Ensures the stock hasn't just rolled over in the immediate term.
Condition 8: Price >= ₹50
Meaning: Filters out stocks below ₹50.
Why: In Indian markets, stocks below ₹50 tend to be penny stocks with poor liquidity and higher manipulation risk.
Condition 9: Weekly Uptrend
Meaning: On the weekly chart, price must be above both weekly MAs, and they must be properly aligned.
Why: Confirms the bigger picture trend, not just daily fluctuations.
Condition 10: 150 MA Rising
Meaning: The 150 MA is trending upward over the past 10 days.
Why: Another confirmation of medium-term trend health.
Condition 11: Sufficient Volume
Meaning: Average volume must exceed 100,000 shares (or your custom setting).
Why: Ensures you can actually buy/sell the stock without moving the price too much (liquidity).
Condition 12: RS vs Nifty Strong
Meaning: The stock's relative strength vs Nifty must be improving.
Why: You want stocks that are outperforming the market, not underperforming.
Condition 13: Nifty in Uptrend
Meaning: The Nifty 50 index itself must be above its 50 MA.
Why: "A rising tide lifts all boats." It's easier to make money in individual stocks when the overall market is bullish.
VCP Requirements:
Volatility Contracting: Price swings getting tighter (coiling spring)
Volume Drying Up: Fewer shares trading + trending lower
The Setup: When volatility contracts and volume dries up WHILE all 13 trend conditions are met, you have a VCP setup ready to explode.
What You See on Chart:
Colored Lines: 10 MA (green), 50 MA (blue), 150 MA (orange), 200 MA (red)
Blue Background: Trend template conditions met (watch zone)
Green Background: Full VCP setup detected (buy zone)
↟ Symbol Below Price: New VCP buy signal just triggered
Information Table:
What it does: Creates a checklist table on your chart showing the status of all conditions.
Table Structure:
Column 1: Condition name
Column 2: Status (✓ green = met, ✗ red = not met)
Final Row: Shows "BUY" (green) or "WAIT" (red) based on full VCP setup status.
Dos:
Example:
Account size: ₹5,00,000
Risk per trade: 1% = ₹5,000
Entry: ₹1000
Stop loss: ₹920 (8% below)
Distance to stop: ₹80
Shares to buy: ₹5,000 / ₹80 = 62 shares
Exit Strategy:
Sell 1/3 at +20% profit
Sell another 1/3 at +40% profit
Let the final 1/3 run with a trailing stop
Always exit if price closes below 10 MA on heavy volume
What This Script Does NOT Do:
Guarantee profits - No strategy works 100% of the time
Account for news events - Earnings, regulatory changes, etc.
Consider fundamentals - Company financials, debt, management quality
Adapt to market crashes - Works best in bull markets
Best Market Conditions:
✅ Nifty in uptrend (above 50 MA)
✅ Market breadth positive (more stocks advancing)
✅ Sector rotation happening
❌ Avoid in bear markets or high volatility periods
References:
Trade Like a Stock Market Wizard by Mark Minervini
Think & Trade Like a Champion by Mark Minervini
Chart attached: AU Small Finance Bank as on EoD dated 28/11/25
This script is a powerful tool for educational purpose only, remember: It's a tool, not a crystal ball. Use it to find high-probability setups, then apply proper risk management and patience. Good luck!
MAHI Indicator v9.5 - Smart Momentum HUD + IntradayMAHI Indicator v9.5 — Smart Momentum HUD (Multi-Framework + Intraday Engine)
A Complete Momentum, Trend, and Setup Framework for Swing, Position & Intraday Traders
MAHI v9.5 is the most advanced version yet — a highly optimized, visual, multi-framework trading system that blends momentum, trend alignment, adaptive setup detection, and now Auto-Intraday Mode for short-term traders.
This indicator acts like a Heads-Up Display (HUD) on your chart: it shows trend strength, squeeze zones, dynamic support/resistance, EMAs, setup validation, and early reversal signals in one clean interface — without clutter.
✔ Core Features
📌 1. Smart Momentum Ribbon
A dynamic EMA-based momentum band that visually shifts as trend strength changes.
Helps identify strong vs. weak momentum zones
Adapts to volatility & trend slope
Works on all timeframes (1m to 1M)
📌 2. EMA 9 → 21 Flip System
A precision trend-switching signal:
EMA 9 → 21 BULL = early bullish momentum
EMA 9 → 21 BEAR = early bearish momentum
More reliable than stand-alone MA crossovers
📌 3. Bullish Setup Engine (Standard + Weak)
Automatically identifies when price is entering a reversal-ready state based on:
Position relative to the ribbon
Candle structure
Momentum compression
Slope + exhaustion conditions
Includes:
Bull Setup (Standard) — Higher probability setup
Bull Setup (Weak) — Early or less developed setup
Setup Invalidated — Confirms that the pattern failed
This prevents false confidence & keeps traders disciplined.
📌 4. Strong Buy / Strong Sell Signals
Only appear when multiple confirmations align:
Ribbon bias
EMA slope
Momentum compression
Trend alignment
Filtered to remove noise — especially in lower timeframes.
📌 5. Multi-Timeframe Trend HUD
Top-right panel summarizing:
Overall Trend (Bullish, Bearish, Neutral)
RSI Condition
Daily vs Weekly Alignment
Trading Mode Suggestions (Buy / Sell / LEAPS / Neutral)
This gives instant context.
📌 6. Auto Intraday Engine (NEW in v9.5)
Automatically switches internal logic when you move into intraday timeframes (1m–30m):
Intraday Enhancements:
Adaptive setup detection
Faster momentum sensitivity
EMAs tuned for scalp/swing precision
Tighter invalidation logic
Reduced false positives
Optional strict filtering
Perfect for scalping, day trading & micro-trends
Works instantly — no settings needed.
Just change the chart timeframe and MAHI adjusts.
📌 7. Dynamic High-Timeframe Support (W & M)
Auto-layers weekly & monthly levels:
Helps identify strong bounce zones
Extremely useful for swing & LEAPS traders
📌 8. Weekly Volume Shelf Projection
Lightweight VWAP-style level based on weekly volume aggregation.
Shows probable bottoming areas during pullbacks.
✔ Who This Indicator Is For
Perfect for:
Day traders
Swing traders
Momentum riders
LEAPS & long-term investors
Beginner traders needing a structured system
MAHI adapts to your timeframe and trading style.
✔ Why MAHI Works
MAHI isn’t a single-signal indicator — it’s a framework.
It combines:
Trend
Momentum
Volatility
Setup pattern detection
Validation & invalidation
Multi-timeframe alignment
Dynamic zones
Intraday optimization
This eliminates guesswork and helps traders avoid the emotional traps that cause most losses.
You don’t just get a signal — you get context.
✔ How to Use It
Follow the ribbon bias
Use EMA 9→21 flips as trend confirmation
Look for Bull Setup tags during pullbacks
Avoid trades when you see Setup Invalidated
Respect weekly/monthly HTF support levels
On intraday charts — rely on auto-optimized mode
For swing entries, combine setups with HTF trend HUD
MAHI gives the map. You choose the path.
✔ Final Notes
This version is heavily optimized for performance, clarity, and high-probability signals.
MAHI does not repaint, and works on all assets including:
Stocks
Crypto
ETFs
Forex
Futures
macd sma20
### MACD_sma20 – Multi-Timeframe MACD Pullback & SMA20 Dashboard
This script is a complete trading toolkit built around a **MACD pullback strategy** combined with **multi-timeframe SMA20 filters**, volume analysis, and a compact information panel.
It is designed for traders who like to:
* Trade **MACD pullbacks above the moving average**
* Track **key SMA20 levels across multiple timeframes** (Daily, 3-Day, Weekly, Monthly)
* Quickly see whether **current price is above or below those reference levels**
* Use **clean visual signals** for entries and exits, instead of staring at raw indicator values
---
### Core Features
#### 1. MACD Pullback Long Signal (Green Triangle Up)
The script detects a **bullish MACD pullback** pattern:
* MACD line is still **above** the signal line
* Both MACD line and histogram **pull back** for several bars
* Then MACD turns back up again, with price trading **above the local SMA20**
When this “pullback and re-acceleration” is confirmed, a **green triangle below the bar** is plotted as a **long entry signal**.
There is also an optional filter:
* **Weekly SMA20 filter**:
If enabled, long signals are only triggered when **current price is above the Weekly SMA20**, helping you stay on the right side of the higher-timeframe trend.
---
#### 2. Bearish Pullback Confirmation Signal (Red Triangle Down)
On the short side, the script detects a **bearish pullback confirmation** based on:
* A recent **high-volume bearish candle** (large down bar with volume above a multiple of the 20-period volume average)
* At least a minimum number of **negative MACD histogram bars**
* MACD line moving closer to the signal line (loss of momentum)
* Price recovering back up near the **top of that high-volume bearish candle**, then starting to fall again while MACD stays positive
When all conditions align, the script prints a **red triangle above the bar**, indicating a **bearish pullback confirmation** – often a good area to take profits on longs or consider short/hedge setups.
---
#### 3. Signal History Tracking
For both long and short signals, the script internally tracks the **most recent three signals**:
* Timestamp of the signal
* Price at the signal
* Short-term percentage change into the signal
This is mainly for internal use and future expansion, but already gives you a structured signal history if you want to extend or connect the logic later.
---
### Multi-Timeframe SMA20 Dashboard (Bottom-Right Panel)
One of the most useful parts of this script is the **compact dashboard table** in the **bottom-right corner** of the chart. It updates in real time and shows:
1. **Current Price**
2. **Daily SMA20** – value + whether price is above/below
3. **3-Day SMA20** – value + whether price is above/below
4. **Weekly SMA20** – value + whether price is above/below
5. **Monthly SMA20** – value + whether price is above/below
6. **RSI** (current timeframe)
For each timeframe’s SMA20:
* If **price ≥ SMA20**, the status cell is **green** with a ✓
* If **price < SMA20**, the status cell is **red** with a ✗
This gives you, at a glance:
* Is the market in a **short-term uptrend or downtrend** (Daily SMA20)?
* Is the **swing / position trend** healthy (3D & Weekly SMA20)?
* Is the broader **macro structure** supportive (Monthly SMA20)?
You don’t need to manually switch timeframes or add multiple moving averages – the script does all of that for you automatically using `request.security`.
---
### Alerts
The script comes with two built-in alert conditions:
* **MACD回踩转多信号 (MACD pullback bullish signal)**
* **空头回抽确认信号 (Bearish pullback confirmation signal)**
You can attach TradingView alerts to these conditions to get notified whenever a new long or bearish-confirmation setup appears, even when you’re not watching the chart.
---
### How to Use It in Your Trading
1. **Choose your main trading timeframe**
* For intraday swing: 15m / 1h / 4h
* For swing / position: 4h / Daily
2. **Watch the bottom-right SMA20 panel**
* If most higher-timeframe SMA20 rows are **green**, you are trading **with the larger trend**.
* If they are **mixed or mostly red**, you’re either counter-trend or in a choppy transition zone.
3. **Use the green MACD pullback signals**
* Prefer long setups when:
* The **Weekly and Monthly SMA20 rows are green**, and
* The signal appears **above the Daily SMA20**
* This stacks multiple edges: trend + pullback + momentum re-acceleration.
4. **Use the red bearish confirmation signals for risk management**
* Take partial profits on longs when a red signal appears near resistance.
* Consider hedge/short opportunities if higher-timeframe SMA20 rows are already red or turning red.
5. **Use RSI as a context indicator**
* Combine with overbought/oversold zones or your own RSI thresholds for additional confirmation.
---
### Why This Script Is Useful
* **Trend awareness across timeframes**:
You always know where current price sits relative to the Daily / 3-Day / Weekly / Monthly SMA20 – without switching charts.
* **Clear, rule-based signals**:
The MACD logic is explicit and systematic, focused on **pullbacks within trends** rather than random crossovers.
* **Volume-aware bearish logic**:
High-volume bearish candles often mark important supply zones. The script builds this idea directly into the short-side confirmation logic.
* **Visual and intuitive**:
Green/Red triangles + Green/Red table cells make it easy to interpret even if you are not a heavy indicator user.
* **Flexible**:
All key parameters (MACD lengths, SMA length, volume threshold, lookback period, RSI length, weekly filter) are customizable, so you can adapt it to different markets (crypto, stocks, FX) and timeframes.
---
In short, this script is a **multi-timeframe MACD pullback system with an integrated SMA20 dashboard**, suitable for swing traders and position traders who want a structured, visually clean way to align entries with trend and momentum while keeping an eye on higher-timeframe levels.
Bull Bear Indicator# Bull Bear Indicator - TradingView Script Description
## Overview
The Bull Bear Indicator is a powerful visual tool that instantly identifies market sentiment by coloring all candlesticks based on their position relative to a moving average. This indicator helps traders quickly identify bullish and bearish market conditions at a glance.
## Key Features
### 🎨 Visual Bull/Bear Identification
- **Green Candles**: Price is at or above the moving average (Bullish condition)
- **Red Candles**: Price is below the moving average (Bearish condition)
- Complete candle coloring including body, wicks, and borders for maximum clarity
### 📊 Flexible Moving Average Options
- **MA Type**: Choose between Simple Moving Average (MA) or Exponential Moving Average (EMA)
- **Timeframe**: Select Weekly or Daily timeframe for the moving average calculation
- **Customizable Period**: Adjust the MA/EMA period (default: 50)
### 📈 Smooth Moving Average Line
- Displays a smooth blue moving average line on the chart
- Automatically adapts to your selected timeframe and MA type
- Provides clear visual reference for trend identification
## How It Works
The indicator calculates a moving average (MA or EMA) based on your selected timeframe (Weekly or Daily). It then compares the current price to this moving average:
- **Bull Market**: When price ≥ Moving Average → Candles turn **GREEN**
- **Bear Market**: When price < Moving Average → Candles turn **RED**
## Configuration Options
1. **MA Type**: Choose "MA" for Simple Moving Average or "EMA" for Exponential Moving Average
2. **Timeframe**: Select "Weekly" for weekly-based MA or "Daily" for daily-based MA
3. **MA Period**: Set the number of periods for the moving average calculation (default: 50)
## Use Cases
- **Trend Identification**: Quickly identify overall market trend direction
- **Entry/Exit Signals**: Use color changes as potential entry or exit signals
- **Multi-Timeframe Analysis**: Combine with different chart timeframes for comprehensive analysis
- **Visual Clarity**: Reduce chart clutter while maintaining essential trend information
## Best Practices
- Use Weekly MA for longer-term trend identification
- Use Daily MA for shorter-term trend analysis
- Combine with other technical indicators for confirmation
- Adjust the MA period based on your trading style and timeframe
## Technical Details
- Built with Pine Script v6
- Overlay indicator (displays on main chart)
- Optimized for performance
- Compatible with all TradingView chart types
---
**Note**: This indicator is for educational and informational purposes only. Always conduct your own analysis and risk management before making trading decisions.
SRD
SRD v11 - Multi-Timeframe Volume Profile (POC, VAH, VAL)
Key Features
Dual Timeframe Analysis:
📈 Main Analysis (Daily): Calculates and displays the most significant levels based on a user-defined period of daily bars. This is ideal for identifying intraday and short-term trading opportunities.
📊 Strategic Analysis (Weekly): Plots key levels from a weekly perspective, giving you a broader, long-term view of market sentiment and structure. This can be toggled on or off.
Volume Profile Core Levels: The indicator automatically calculates and visualizes the three most important levels derived from volume analysis for both timeframes:
🎯 POC (Point of Control): The price level with the highest traded volume for the specified period. It acts as a powerful magnet for price and a key reference for market equilibrium.
🔴 VAH (Value Area High): The highest price level within the "Value Area" (where ~70% of the volume was traded). It often acts as a significant resistance zone.
🟢 VAL (Value Area Low): The lowest price level within the Value Area. It often serves as a strong support zone.
🟠 24-Hour High: An optional feature that plots the highest price reached in the last 24 hours, providing a crucial reference point for breakout and reversal traders.
Dynamic and Non-Repainting: The levels are calculated based on historical confirmed bars and update automatically as new periods (daily or weekly) close. The lines extend to the right, remaining relevant until a new calculation period begins.
Integrated Alert System: Never miss a key price interaction. The indicator includes a comprehensive alert system for:
Breakouts: Triggers when the price crosses above or below the POC, VAH, or VAL.
Touches: Triggers when the price touches one of these key levels without breaking through it (within a small tolerance).
Unified Alert: A single alert that notifies you of any of the above conditions.
Customization
The SRD v11 is fully customizable to fit your trading style. You can adjust:
Timeframes: Change the base timeframes for both the main (default Daily) and strategic (default Weekly) analysis.
Analysis Periods: Define the number of bars (days or weeks) to include in the Volume Profile calculation.
Visuals: Customize the color, width, and style (solid, dashed, dotted) of every line and label for clear and intuitive visualization.
Toggle Elements: Easily show or hide the strategic (weekly) analysis and the 24-hour high line.
How to Use It >
Identify Key Zones: Use the VAH (resistance) and VAL (support) lines to identify potential entry and exit zones. The area between VAH and VAL is the "Value Area," where the market has found acceptance.
Monitor the POC: The Point of Control is the ultimate level of equilibrium. Watch for price reactions around the POC. A sustained break above or below can signal a new trend.
Combine Timeframes: Use the strategic (weekly) levels as major, long-term points of interest and the main (daily) levels for your day-to-day trading setup. Confluence between levels from different timeframes can indicate extremely strong support or resistance.
Set Alerts: Configure alerts for breakouts or touches to be notified of critical market movements in real-time, even when you are away from the charts.
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.
Ticker Info & Look-Ahead Lines (W/D)This versatile Pine Script indicator for trading views clearly displays current chart information and predicts and plots important future timeframe boundaries (next week, the day after tomorrow, etc.).
Key Features of the Indicator 📈
This indicator is divided into three main sections:
1. Ticker/Timeframe Display
Clearly displays the current ticker and timeframe on the chart.
Customization: You can set the display position (top/middle/bottom, left/center/right), font size, default text color, and background color.
Auto Color by Timeframe: The text color automatically changes depending on the timeframe, allowing you to quickly visually grasp the current timeframe.
2. Weekly Look-Ahead Lines
Predicts the start times of the next week and the week after from the time the current bar is determined, and plots them as vertical lines on the chart.
Display Control: You can toggle the visibility of individual lines.
Style: You can set the line color and style (dotted, dashed, solid).
Maximum Number of Lines Displayed: You can control the number of previously drawn lines to retain (consumes two lines per set).
💡 Daily Chart Specific Filter
When viewing a daily chart, this filter hides all past weekly lines and displays only the most recent two (the lines for the following week and the week after). This significantly reduces the visual noise on the daily chart.
3. Daily Look-Ahead Lines
These lines predict the start times of the next and the day after tomorrow from the time the current bar is determined, and are drawn as vertical lines on the chart.
Display Control/Style: As with weekly lines, you can set the visibility, color, and style of lines.
Maximum Number of Lines Displayed: You can control the number of previously drawn lines to retain (consumes two lines per set).
4. Master Timeframe Filter
This is a master ON/OFF switch that centrally manages the automatic hiding of both weekly and daily lines except for the appropriate timeframe.
Auto-hide Daily Lines: When displaying a chart with a timeframe greater than the line's base timeframe, such as a daily, weekly, or monthly chart, the daily lines will be automatically hidden.
Auto-hide Weekly Lines: When displaying a weekly or monthly chart, the weekly lines will be automatically hidden.
This feature allows you to clearly see the leading lines when analyzing shorter timeframes, while preventing the chart from becoming cluttered with lines when switching to longer timeframes (daily or longer).
このインジケーターは、現在のチャート情報を明確に表示し、さらに将来の重要な時間軸の区切り（翌週、明後日など）を予測して描画する機能を持つ、トレーディングビュー用の多機能な Pine Script インジケーターです。
インジケーターの主要機能 (Key Features) 📈
このインジケーターは、以下の3つの主要なセクションに分かれています。
1. 銘柄・時間足情報表示 (Ticker/Timeframe Display)
チャート上に現在の銘柄名 (Ticker) と時間足 (Timeframe) を分かりやすく表示します。
カスタマイズ: 表示位置（上/中/下、左/中央/右）、文字サイズ、デフォルトの文字色、背景色を設定できます。
時間足別自動カラー: 時間足に応じて文字色が自動的に変わるオプションがあり、現在の時間足を視覚的に素早く把握できます。
2. 週足先行ライン (Weekly Look-Ahead Lines)
現在の足が確定した時点から見た、翌週と再来週の開始時刻を予測し、チャートに垂直線として描画します。
表示制御: ラインの表示/非表示を個別に切り替えられます。
スタイル: ラインの色とスタイル（点線、破線、実線）を設定できます。
最大表示本数: 過去に描画されたラインを何本まで保持するかを制御できます（1組あたり2本消費）。
💡 日足チャート限定フィルター (Daily Chart Specific Filter)
特に日足チャートを表示しているときに、過去の週足ラインをすべて非表示にし、直近の2本（翌週と再来週のライン）のみを表示するフィルター機能があります。これにより、日足チャートの視覚的なノイズを大幅に減らせます。
3. 日足先行ライン (Daily Look-Ahead Lines)
現在の足が確定した時点から見た、翌日と明後日の開始時刻を予測し、チャートに垂直線として描画します。
表示制御・スタイル: 週足ラインと同様に、ラインの表示/非表示、色、スタイルを設定できます。
最大表示本数: 過去のライン保持数を制御できます（1組あたり2本消費）。
4. 時間足フィルター一括制御 (Master Timeframe Filter)
週足ラインと日足ラインの両方に対し、適切な時間足以外での自動非表示を一括で管理するマスターON/OFFスイッチです。
日足ラインの自動非表示: 日足、週足、月足チャートなど、ラインの元となる時間足以上のチャートを表示している場合、日足ラインを自動で非表示にします。
週足ラインの自動非表示: 週足、月足チャートを表示している場合、週足ラインを自動で非表示にします。
この機能は、短期足での分析時には先行ラインを明確に見せつつ、長期足（日足以上）に切り替えた際にチャートが線で cluttered になるのを防ぎます。
Aurum DCX AVE Gold and Silver StrategySummary in one paragraph
Aurum DCX AVE is a volatility break strategy for gold and silver on intraday and swing timeframes. It aligns a new Directional Convexity Index with an Adaptive Volatility Envelope and an optional USD/DXY bias so trades appear only when direction quality and expansion agree. It is original because it fuses three pieces rarely combined in one model for metals: a convexity aware trend strength score, a percentile based envelope that widens with regime heat, and an intermarket DXY filter.
Scope and intent
• Markets. Gold and silver futures or spot, other liquid commodities, major indices
• Timeframes. Five minutes to one day. Defaults to 30min for swing pace
• Default demo used in this publication. TVC:GOLD on 30m
• Purpose. Enter confirmed volatility breaks while muting chop using regime heat and USD bias
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. DCX combines DI strength with path efficiency and curvature. AVE blends ATR with a high TR percentile and widens with DCX heat. DXY adds an intermarket bias
• Failure mode addressed. False starts inside compression and unconfirmed breakouts during USD swings
• Testability. Each component has a named input. Entry names L and S are visible in the list of trades
• Portable yardstick. Weekly ATR for stops and R multiples for targets
• Open source. Method and implementation are disclosed for community review
Method overview in plain language
You score direction quality with DCX, size an adaptive envelope with a blend of ATR and a high TR percentile, and only allow breaks that clear the band while DCX is above a heat threshold in the same direction. An optional DXY filter favors long when USD weakens and short when USD strengthens. Orders are bracketed with a Weekly ATR stop and an R multiple target, with optional trailing to the envelope.
Base measures
• Range basis. True Range and ATR over user windows. A high TR percentile captures expansion tails used by AVE
• Return basis. Not required
Components
• Directional Convexity Index DCX. Measures directional strength with DX, multiplies by path efficiency, blends a curvature term from acceleration, scales to 0 to 100, and uses a rise window
• Adaptive Volatility Envelope AVE. Midline ALMA or HMA or EMA plus bands sized by a blend of ATR and a high TR percentile. The blend weight follows volatility of volatility. Band width widens with DCX heat
• DXY Bias optional. Daily EMA trend of DXY. Long bias when USD weakens. Short bias when USD strengthens
• Risk block. Initial stop equals Weekly ATR times a multiplier. Target equals an R multiple of the initial risk. Optional trailing to AVE band
Fusion rule
• All gates must pass. DCX above threshold and rising. Directional lead agrees. Price breaks the AVE band in the same direction. DXY bias agrees when enabled
Signal rule
• Long. Close above AVE upper and DCX above threshold and DCX rising and plus DI leads and DXY bias is bearish
• Short. Close below AVE lower and DCX above threshold and DCX falling and minus DI leads and DXY bias is bullish
• Exit and flip. Bracket exit at stop or target. Optional trailing to AVE band
Inputs with guidance
Setup
• Symbol. Default TVC:GOLD (Correlation Asset for internal logic)
• Signal timeframe. Blank follows the chart
• Confirm timeframe. Default 1 day used by the bias block
Directional Convexity Index
• DCX window. Typical 10 to 21. Higher filters more. Lower reacts earlier
• DCX rise bars. Typical 3 to 6. Higher demands continuation
• DCX entry threshold. Typical 15 to 35. Higher avoids soft moves
• Efficiency floor. Typical 0.02 to 0.06. Stability in quiet tape
• Convexity weight 0..1. Typical 0.25 to 0.50. Higher gives curvature more influence
Adaptive Volatility Envelope
• AVE window. Typical 24 to 48. Higher smooths more
• Midline type. ALMA or HMA or EMA per preference
• TR percentile 0..100. Typical 75 to 90. Higher favors only strong expansions
• Vol of vol reference. Typical 0.05 to 0.30. Controls how much the percentile term weighs against ATR
• Base envelope mult. Typical 1.4 to 2.2. Width of bands
• Regime adapt 0..1. Typical 0.6 to 0.95. How much DCX heat widens or narrows the bands
Intermarket Bias
• Use DXY bias. Default ON
• DXY timeframe. Default 1 day
• DXY trend window. Typical 10 to 50
Risk
• Risk percent per trade. Reporting field. Keep live risk near one to two percent
• Weekly ATR. Default 14. Basis for stops
• Stop ATR weekly mult. Typical 1.5 to 3.0
• Take profit R multiple. Typical 1.5 to 3.0
• Trail with AVE band. Optional. OFF by default
Properties visible in this publication
• Initial capital. 20000
• Base currency. USD
• request.security lookahead off everywhere
• Commission. 0.03 percent
• Slippage. 5 ticks
• Default order size method percent of equity with value 3% of the total capital available
• Pyramiding 0
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while a bar forms and settle on close
• Strategies use standard candles for signals and orders only
Honest limitations and failure modes
• Economic releases and thin liquidity can break assumptions behind the expansion logic
• Gap heavy symbols may prefer a longer ATR window
• Very quiet regimes can reduce signal contrast. Consider higher DCX thresholds or wider bands
• Session time follows the exchange of the chart and can change symbol to symbol
• Symbol sensitivity is expected. Use the gates and length inputs to find stable settings
Open source reuse and credits
• None
Mode
Public open source. Source is visible and free to reuse within TradingView House Rules
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
