RSI Multi-Timeframe S/R - MehtaMulti-Timeframe Dynamic Support & Resistance Indicator
This tool automatically detects key support and resistance levels across multiple timeframes — including 1-Day, 15-Minute, and 5-Minute charts — using a refined momentum-based algorithm with trend and volume confirmation.
It’s designed to help traders quickly identify confluence zones where intraday and higher-timeframe structures align, improving timing and risk management.
Key Features
Detects dynamic support and resistance zones with a built-in strength filter.
Uses multi-timeframe confirmation to reduce false levels.
Integrates volume-based reliability checks.
Automatically updates only the latest active levels to keep charts clean.
Includes a touch counter panel that tracks how often price interacts with each level (a proxy for zone strength).
Color & Structure Guide
🟩 Support Zones: Indicate potential accumulation areas.
🔴 Resistance Zones: Indicate potential supply or reaction areas.
Solid lines = Higher timeframe (stronger zones)
Dotted lines = Lower timeframe (shorter-term zones)
Best Use
Combine with your price-action or volume analysis to confirm reactions.
Particularly useful in spotting multi-timeframe overlaps — where the strongest reactions tend to occur.
Touch Counter: A handy table on the chart tracks how many times the price has tested each level, helping you gauge its strength.
Combine with Your Strategy: This indicator works best when combined with your existing price action analysis, candlestick patterns, or other confirmation indicators.
STRONG DISCLAIMER & RISK WARNING
PLEASE READ THIS CAREFULLY BEFORE USING THE INDICATOR.
No Financial Advice: This indicator is a technical analysis tool for educational and informational purposes only. It is NOT financial, investment, or trading advice. The creator of this script is not a registered financial advisor.
Not a Guarantee: Past performance is not indicative of future results. The signals and levels generated by this indicator are based on historical data and mathematical formulas and are not a guarantee of future price movement. There is a high risk of loss in trading.
Use at Your Own Risk: You are solely responsible for any trading decisions you make and the resulting profits or losses. Always conduct your own due diligence and consult with a qualified financial professional before engaging in any trade.
Backtest First: It is highly recommended to backtest this indicator and understand its behavior in different market conditions (trending, ranging, volatile) before using it with real capital.
Lagging Nature: Like most technical indicators, this tool is lagging. It reflects past and current market data, which may not accurately predict future price action.
By using this indicator, you acknowledge that you understand and accept these risks entirely.
Feel free to leave feedback, report bugs, or suggest improvements in the comments below!
Happy Trading!
Educational
The DTC Indicator The Day Trading Channel EditionOverview
The DTC Indicator is a precision-built engulfing confirmation system developed by The Day Trading Channel to simplify structured, session-based trading.
It identifies high-probability engulfing setups during user-defined sessions, automatically marks entry levels, and visualizes target/invalidation zones in real time.
The tool provides traders with a clean, rules-driven framework to analyze market structure objectively without relying on subjective interpretation or multi-indicator clutter.
The DTC Indicator is designed for day traders who value logic over luck — offering full control over session windows, confirmation filters, and risk parameters.
Core Concept
At its foundation, the DTC Indicator revolves around a straightforward yet powerful principle:
The first few candles of a session often define the directional intent of the market.
The script scans the initial candles of each active session for bullish or bearish engulfing structures — one of the most reliable candlestick confirmations in price action theory.
Once identified, it automatically logs the entry price, stop-loss, and take-profit levels based on the trader’s configured risk-to-reward ratio.
From there, the indicator takes over visual tracking — plotting live boxes for target and invalidation levels, marking outcome labels (TP/SL), and updating the internal statistics dashboard to keep a running log of all observed setups.
Key Features
🎯 Session Control & Customization
• Define up to four unique trading sessions (e.g., London, New York, Sydney, Asian).
• Each session is independently configurable, allowing traders to isolate setups only during high-activity periods.
• Visually differentiated sessions make it easy to monitor which time windows produce the best consistency.
🧩 Engulfing Confirmation Logic
• Detects bullish engulfing when a candle fully engulfs the body of the previous bearish candle.
• Detects bearish engulfing when a candle fully engulfs the body of the previous bullish candle.
• Signal confirmation is session-aware — only triggers within the specified start-window of each session.
• False positives are filtered out automatically if price fails to close beyond the engulfing range.
📊 Dynamic Entry Snapshot System
• Every valid setup is recorded as a “snapshot,” capturing the entry price, target, and invalidation levels.
• Boxes are drawn live on the chart, extending until price hits either the target or invalidation.
• Once resolved, the outcome is logged into the performance dashboard automatically.
🧮 Performance Dashboard
• Displays key stats directly on-chart:
Total setups
true / false
true-rate percentage
Latest signal direction
Last target & invalidation values
• The dashboard automatically filters by date range, letting traders review historical session performance.
🔔 Smart Alerts
• Optional alerts trigger on confirmed setups.
• Each alert message includes symbol, timeframe, direction, target/invalidation values, and timestamp.
• Compatible with TradingView’s webhook system for automation or third-party integration.
🎨 Visual Customization
• Choose between Modern Blue, Classic Green-Red , and Gold Edition color themes.
• Adjustable label size, box opacity, line thickness, and text color.
• Option to toggle boxes, lines, or only retain labels for a minimal layout.
Why It’s Different
The DTC Indicator isn’t another candlestick detector — it’s a structured visual journal of real-time session behavior.
Instead of cluttering the screen with redundant signals, it focuses on clarity: showing you when a session produces genuine intent, and how price reacts to that intent across multiple timeframes.
Each setup becomes a mini “trade story” — logged, tracked, and concluded.
This gives traders powerful visual feedback on how specific sessions behave and how consistent a setup truly is over time.
Recommended Use Cases
• Intraday Forex and Gold (XAUUSD) trading
• Scalping and short-term swing trading on 1 hour charts
• Session-based backtesting for pattern validation
• Visual trade journaling and post-session analysis
Recommended Defaults:
Timeframe: 1-hour (h1)
Risk-Reward Ratio: 1 : 2.5
Primary Sessions: London, New York
Commission & Margin (recommended table display) : 0.02% commission, 1:100 margin
Limitations & Transparency Notice
• The indicator tracks simulated outcomes only; it does not represent executed trades.
• Historical win-rates are observational, not predictive of future performance.
• Non-standard chart types (Heikin-Ashi, Renko, Range) are not supported for engulfing detection.
• All results are based on visual backtesting and should be interpreted as educational data.
Access & Licensing
This invite-only version of the DTC Indicator is maintained and distributed by The Day Trading Channel .
Access may be granted to selected traders, educational partners, or evaluation firms for research and testing purposes.
Unauthorized redistribution, decompilation, or commercial replication of the script is strictly prohibited.
Disclaimer
This indicator is provided for educational and analytical purposes only.
It does not constitute financial advice, investment recommendations, or trade execution signals.
Trading financial markets carries risk — users are solely responsible for their decisions and results.
© 2025 The Day Trading Channel. All Rights Reserved.
Doctor Scalp (BUY/SELL) [by Adi]A script for fast scalping using. Works best with a 5-minute-to-1-hour interval.
NSE Pairs Screener-20 pair This advanced Pine Script screener is designed for pairs trading on the National Stock Exchange (NSE) of India. It simultaneously monitors up to 20 stock pairs, calculates key statistical metrics, and provides real-time trading signals based on mean reversion strategies.
Key Features
1. Multi-Pair Analysis
Monitor up to 20 stock pairs simultaneously
Customizable number of pairs to display (1-20)
Pre-configured with popular NSE stock pairs across various sectors
2. Statistical Calculations
Correlation Analysis: Measures the strength of relationship between paired stocks
Z-Score Calculation: Identifies extreme deviations from the mean spread
Cointegration Score: Validates long-term equilibrium relationships
Dynamic Hedge Ratio: Calculates optimal position sizing between pairs
3. Trading Signals
Long Signal: When spread is oversold (Z-score ≤ -2.0)
Short Signal: When spread is overbought (Z-score ≥ 2.0)
Exit Signal: When spread returns to mean (Z-score ≤ 0.5)
Watch Status: Pairs requiring monitoring
4. Automated Alert System
Single comprehensive alert for all qualifying pairs
Customizable alert thresholds for correlation, Z-score, and cointegration
On-chart visual alerts with detailed information
Notification support via TradingView's alert system
5. Visual Display
Clean, color-coded table interface
Adjustable table position (9 positions available)
Highlighted trading opportunities
Real-time metric updates
Configuration Parameters
Screener Settings
Number of Pairs to Display: 1-20 pairs (default: 20)
Calculation Parameters
Parameter Default Range Description Correlation Lookback Period25220-500Historical period for correlation calculation Z-Score SMA Length205-100Moving average length for spread calculation Hedge Ratio Length205-100Period for hedge ratio smoothing Minimum Correlation0.70.5-1.0Threshold for pair validation
Alert Settings
Parameter Default Range Description Alert Correlation Threshold0.70.5-1.0Minimum correlation for alerts Alert Z-Score Threshold2.01.0-3.0Z-score trigger level Alert Cointegration Threshold90%80-99%Minimum cointegration percentage
Display Settings
Table Position: 9 position options (default: middle_center)
Table Background Color: Customizable
Highlight Opportunities: Toggle visual highlighting of trading signals
Pre-Configured Stock Pairs
The script includes 20 carefully selected NSE pairs across various sectors:
Financial Services
RELIANCE / ONGC
HDFCBANK / ICICIBANK
SBIN / PNB
KOTAKBANK / AXISBANK
BAJFINANCE / BAJAJFINSV
Information Technology
TCS / INFY
WIPRO / HCLTECH
TECHM / LTIM
Consumer Goods
ITC / HINDUNILVR
TITAN / TANLA
ASIANPAINT / BERGEPAINT
Telecommunications
BHARTIARTL / IDEA
Automotive
MARUTI / TATAMOTORS
Infrastructure & Industrials
LT / UBL
POWERGRID / NTPC
Pharmaceuticals
SUNPHARMA / CIPLA
DIVISLAB / DRREDDY
Materials
ULTRACEMCO / ACC
UPL / JSWSTEEL
Energy
ADANIENT / ADANIPOWER
🎨 Color-Coded Metrics
Correlation
🟢 Green: ≥ Minimum threshold (strong relationship)
🔴 Red: < Minimum threshold (weak relationship)
Z-Score
🔴 Red: |Z| ≥ 2.0 (extreme deviation - trading opportunity)
🟡 Yellow: 0.5 < |Z| < 2.0 (normal range - watch)
🟢 Green: |Z| ≤ 0.5 (mean reversion - exit signal)
Cointegration
🟢 Green: ≥ 70% (strong cointegration)
🟡 Yellow: 50-70% (moderate cointegration)
🔴 Red: < 50% (weak cointegration)
Status
🟢 Green: Long (buy spread)
🔴 Red: Short (sell spread)
🔵 Blue: Exit (close positions)
⚪ Gray: Watch (monitor)
Validation
🟢 Green: Pass (meets all criteria)
🔴 Red: Fail (doesn't meet criteria)
How It Works
1. Data Collection
The script fetches real-time closing prices for all 20 stock pairs from NSE.
2. Statistical Analysis
For each pair, the script calculates:
Log Returns: Natural logarithm of price changes
Correlation: Pearson correlation coefficient between returns
Hedge Ratio: Price ratio smoothed over specified period
Spread: Price difference adjusted by hedge ratio
Z-Score: Standardized spread deviation
3. Signal Generation
Based on Z-score thresholds:
Z ≥ 2.0: Short spread (short overvalued, long undervalued)
Z ≤ -2.0: Long spread (long overvalued, short undervalued)
|Z| ≤ 0.5: Exit positions (spread reverted to mean)
4. Validation
Pairs must meet criteria:
Correlation ≥ minimum threshold
Valid trading signal (entry or exit)
5. Alert Triggering
Alerts fire when pairs simultaneously meet:
Correlation ≥ alert threshold
|Z-score| ≥ alert threshold
Cointegration ≥ alert threshold
Alert System
The script features a single comprehensive alert that monitors all pairs:
Consolidated Notifications: One alert for all qualifying pairs
Detailed Information: Includes pair names, signal type, and key metrics
Visual Indicators: Red label on chart with complete details
Customizable Thresholds: Adjust sensitivity based on trading style
Alert Message Format
PAIR TRADING OPPORTUNITIES
Pair X: STOCK1/STOCK2
Signal: LONG/SHORT Spread
Z-Score: X.XX
Correlation: X.XXX
Cointegration: XX.X%
Trading Strategy Guide
Entry Rules
Long Spread (Z-score ≤ -2.0):
Buy Stock Y
Sell Stock X (in ratio of hedge ratio)
Short Spread (Z-score ≥ 2.0):
Sell Stock Y
Buy Stock X (in ratio of hedge ratio)
Exit Rules
Close positions when Z-score returns to ±0.5
Set stop-loss at Z-score ±3.0 (extreme deviations)
Risk Management
Only trade pairs with correlation ≥ 0.7
Prefer cointegration scores ≥ 90%
Monitor hedge ratio changes
Diversify across multiple pairs
Customization Options
Adding New Pairs
Simply modify the stock symbol inputs in the respective pair groups (Pair 1 through Pair 20).
Adjusting Sensitivity
Conservative: Increase Z-score threshold to 2.5-3.0
Aggressive: Decrease Z-score threshold to 1.5-2.0
Long-term: Increase lookback period to 500
Short-term: Decrease lookback period to 50-100
Visual Preferences
Change table position to suit your layout
Adjust background colors for better contrast
Toggle opportunity highlighting on/off
Technical Notes
Calculation Method
Uses logarithmic returns for correlation (better statistical properties)
Z-score normalized by standard deviation
Cointegration approximated using correlation strength
Hedge ratio smoothed using simple moving average
Performance Considerations
Calculations update on every bar close
Table displays only on the last bar
Alert checks occur at bar close
Maximum 500 labels supported (more than sufficient)
Limitations
Does not account for transaction costs
Assumes linear relationships between pairs
Historical correlation doesn't guarantee future behaviour
Requires sufficient liquidity in both stocks
Best Practices
Back test Thoroughly: Test parameters on historical data before live trading
Monitor Regularly: Check pairs daily for validation changes
Diversify: Trade multiple pairs to reduce risk
Stay Informed: Be aware of corporate actions, news affecting pairs
Adjust Parameters: Optimize for current market conditions
Use Stop-Losses: Protect against extreme divergences
Track Performance: Maintain trading journal for continuous improvement
Indicator Information
Version: Pine Script v5
Overlay: False (separate pane)
Max Labels: 500
Update Frequency: Every bar close
Compatible Timeframes: All (works best on daily or higher)
Getting Started
Add to Chart: Apply indicator to any NSE stock
Configure Pairs: Adjust stock symbols as needed
Set Parameters: Customize calculation and alert settings
Create Alert: Set up Trading View alert for notifications
Monitor: Watch the table for trading opportunities
Execute: Trade based on validated signals
📞Support & Updates
This script is designed for educational and research purposes. Always:
Conduct thorough back testing
Use proper risk management
Consider transaction costs
Consult with financial advisors
Trade responsibly
Disclaimer: This indicator is for educational purposes only. Past performance does not guarantee future results. Always conduct your own research and risk assessment before trading.
Custom Checklist# Custom Checklist - Trading Preparation & Reminders
A fully customizable checklist overlay indicator for TradingView that helps traders maintain discipline and follow their trading routine systematically.
## 🎯 Purpose
This indicator serves as a visual reminder system on your charts to ensure you complete all necessary analysis steps before entering a trade. Perfect for traders who want to maintain consistency and avoid emotional or rushed trading decisions.
## ✨ Key Features
- **20 Customizable Lines**: Create your own checklist items with any text you need
- **Flexible Display Options**:
- Show/hide title header
- Toggle entire checklist on/off
- Position anywhere on chart (9 positions available)
- Adjustable text size (tiny to huge)
- **Symbol Filtering**: Option to show checklist only on specific symbols (BTC/USD, GOLD, SPX500, USOIL)
- **Customizable Appearance**:
- Background color
- Text color
- Border color
- Transparency controls
- **Clean Interface**: Empty by default - add only the items you need
## 📋 Use Cases
- **Morning Routine**: Daily market preparation checklist
- **Trade Entry Rules**: Verify all setup conditions are met
- **Risk Management**: Confirm stop-loss, position size, and exit strategy
- **Multi-Timeframe Analysis**: Ensure you checked all required timeframes
- **Technical Analysis**: Track which indicators and patterns you've reviewed
- **News & Events**: Remember to check economic calendar and news
- **Personal Rules**: Your custom trading rules and reminders
## 🎨 Customization
Every aspect is customizable:
- All 20 lines can be edited to your needs
- Only non-empty lines are displayed
- Table position adjustable to any corner or middle position
- Color scheme fully customizable to match your chart theme
- Text size scalable for different screen sizes
## 💡 How to Use
1. Add indicator to your chart
2. Open Settings > Checklist Items
3. Fill in your checklist items (Line 1, Line 2, etc.)
4. Customize colors and position in Display Settings
5. Optional: Enable "Show Only on Specific Symbols" to show on select instruments
## 🔧 Display Settings
- **Checklist Title**: Custom header for your checklist
- **Show Title Header**: Toggle title display
- **Show Checklist**: Master on/off switch
- **Symbol Filter**: Restrict display to specific trading instruments
- **Position**: 9 placement options (corners and middle positions)
- **Text Size**: 5 size options (tiny, small, normal, large, huge)
- **Colors**: Background, text, and border fully customizable
## 📝 Example Checklist Ideas
**Swing Trading:**
- Support/Resistance levels identified
- Trend direction confirmed
- Volume analysis completed
- RSI/MACD signals checked
- Risk/Reward ratio calculated
**Day Trading:**
- Pre-market review done
- Key levels marked
- Economic calendar checked
- Trading plan written
- Position size calculated
**Technical Analysis:**
- Multiple timeframe alignment
- Chart patterns identified
- Moving averages reviewed
- Fibonacci levels drawn
- Volume profile analyzed
## ⚙️ Technical Details
- Pine Script v6
- Overlay indicator (displays on main chart)
- Lightweight - no complex calculations
- No repainting
- Works on all timeframes and instruments
## 🎓 Perfect For
- Beginner traders learning systematic analysis
- Experienced traders maintaining discipline
- Anyone who wants visual trading reminders
- Traders following multi-step strategies
- Those prone to FOMO or emotional trading
---
**Note**: This is a visual tool only. It does not generate trading signals or perform analysis. It serves as a reminder checklist to help you follow your own trading process consistently.
Fibonacci Auto Retracement & HTF candles ReferenceAdvanced Higher Timeframe (HTF) Candle & Fibonacci Viewer
Overview:
The Advanced HTF Candle & Fibonacci Viewer is a professional Trading View indicator designed to help traders overlay higher timeframe price structures onto lower timeframe charts. By combining daily candle analysis with precise Fibonacci retracement levels, this tool allows traders to identify critical support and resistance zones, potential breakouts, and retracement opportunities without switching charts.
Special Thanks:
This script includes a small part of coding inspired by Zeiierman, whose work on HTF analysis provided the foundation for visualizing higher timeframe structures. Full credit to Zeiierman for their invaluable contribution to the Trading View community.
Key Features:
1. Multi-Day HTF Range Display
Automatically displays high and low of 1–7 previous days.
Highlights candle bodies and wicks for clear structure visualization.
Ideal for spotting daily ranges and breakout levels.
2. Dynamic Fibonacci Levels
Standard levels: 0%, 11.8%, 23.6%, 38.2%, 50%, 61.8%, 76.4%, 88.2%, 100%.
Optional mid-level lines for intraday support/resistance identification.
Levels adjust automatically to reflect price action direction.
3. Customizable Labels & Colors
Adjustable text size, color, transparency, and offset.
Fully customizable candle and Fibonacci colors.
Mid-level lines can be shown or hidden for a cleaner look.
4. Persistent Levels
Levels remain until the next trading session or breakout, helping track trends and retracements consistently.
5. Multi-Timeframe Optimization
Works on any chart timeframe, from 1-minute to weekly charts.
Provides higher timeframe insight while trading on lower timeframes.
Why Traders Love This Indicator:
View higher timeframe action without switching charts.
Identify high-probability entry and exit zones.
Combine with other indicators for complete market analysis.
Useful for swing traders, day traders, and scalpers alike.
Customization Options:
Number of previous days (1–7)
Show/hide mid-level lines
Show/hide labels
Customize label size, color, and offset
Customize Fibonacci and candle colors
Ideal Use Cases:
Swing Trading: Identify daily key levels for entry, exit, and stop-loss.
Day Trading: Use HTF ranges on intraday charts to spot breakouts and reversals.
Fibonacci Analysis: Locate retracement zones efficiently.
Trend Confirmation: Validate trades with higher timeframe structure.
Summary:
The Advanced HTF Candle & Fibonacci Viewer is a powerful tool for traders seeking clarity, structure, and precision. With higher timeframe insight overlaid on active charts and proper credit to Zeiierman for their HTF coding contribution, this indicator helps traders make informed, confident decisions in any market.
Demand and supplyshows basic Demand and Supply.
whenever the price Retest Demand zone -Buy
whenever the price Retest Supply zone -Sell
ATR + EMA + Sessions ProATR + EMA + Sessions Pro By Saeed Fadi to save indicator space, it,s for atr, emas, sessions etc.
580TL — NovaSenseNovaSense by 580TradingLab combines multi-EMA structure, price actions, momentum confirmation, and volatility logic to detect trend strength and early reversals with high accuracy. It filters out market noise, identifies "location zones" for optional entries, and sends timely Buy/Sell alerts when institutional momentum shifts. Designed for traders who value clarity, discipline, and precision.
Trade with clarity. Sense the trend before it flips.
ForexDada Trade LogicIdentifies Boring, Quiet, No Supply / No Demand candles. "
+ "Highlights potential 5★ setups for trading confirmation when price breaks candle highs/lows. "
+ "Helps traders spot low-volume turning points and breakout opportunities.
580TL • ApexFlip (Trend + Reversal Pro)Use EMA to find trends. Look for EMA cross, or EMA break with trends. Combine price action to find entry and set stop loss behind EMA.
3D Institutional Battlefield [SurgeGuru]Professional Presentation: 3D Institutional Flow Terrain Indicator
Overview
The 3D Institutional Flow Terrain is an advanced trading visualization tool that transforms complex market structure into an intuitive 3D landscape. This indicator synthesizes multiple institutional data points—volume profiles, order blocks, liquidity zones, and voids—into a single comprehensive view, helping you identify high-probability trading opportunities.
Key Features
🎥 Camera & Projection Controls
Yaw & Pitch: Adjust viewing angles (0-90°) for optimal perspective
Scale Controls: Fine-tune X (width), Y (depth), and Z (height) dimensions
Pro Tip: Increase Z-scale to amplify terrain features for better visibility
🌐 Grid & Surface Configuration
Resolution: Adjust X (16-64) and Y (12-48) grid density
Visual Elements: Toggle surface fill, wireframe, and node markers
Optimization: Higher resolution provides more detail but requires more processing power
📊 Data Integration
Lookback Period: 50-500 bars of historical analysis
Multi-Source Data: Combine volume profile, order blocks, liquidity zones, and voids
Weighted Analysis: Each data source contributes proportionally to the terrain height
How to Use the Frontend
💛 Price Line Tracking (Your Primary Focus)
The yellow price line is your most important guide:
Monitor Price Movement: Track how the yellow line interacts with the 3D terrain
Identify Key Levels: Watch for these critical interactions:
Order Blocks (Green/Red Zones):
When yellow price line enters green zones = Bullish order block
When yellow price line enters red zones = Bearish order block
These represent institutional accumulation/distribution areas
Liquidity Voids (Yellow Zones):
When yellow price line enters yellow void areas = Potential acceleration zones
Voids indicate price gaps where minimal trading occurred
Price often moves rapidly through voids toward next liquidity pool
Terrain Reading:
High Terrain Peaks: High volume/interest areas (support/resistance)
Low Terrain Valleys: Low volume areas (potential breakout zones)
Color Coding:
Green terrain = Bullish volume dominance
Red terrain = Bearish volume dominance
Purple = Neutral/transition areas
📈 Volume Profile Integration
POC (Point of Control): Automatically marks highest volume level
Volume Bins: Adjust granularity (10-50 bins)
Height Weight: Control how much volume affects terrain elevation
🏛️ Order Block Detection
Detection Length: 5-50 bar lookback for block identification
Strength Weighting: Recent blocks have greater impact on terrain
Candle Body Option: Use full candles or body-only for block definition
💧 Liquidity Zone Tracking
Multiple Levels: Track 3-10 key liquidity zones
Buy/Sell Side: Different colors for bid/ask liquidity
Strength Decay: Older zones have diminishing terrain impact
🌊 Liquidity Void Identification
Threshold Multiplier: Adjust sensitivity (0.5-2.0)
Height Amplification: Voids create significant terrain depressions
Acceleration Zones: Price typically moves quickly through void areas
Practical Trading Application
Bullish Scenario:
Yellow price line approaches green order block terrain
Price finds support in elevated bullish volume areas
Terrain shows consistent elevation through key levels
Bearish Scenario:
Yellow price line struggles at red order block resistance
Price falls through liquidity voids toward lower terrain
Bearish volume peaks dominate the landscape
Breakout Setup:
Yellow price line consolidates in flat terrain
Minimal resistance (low terrain) in projected direction
Clear path toward distant liquidity zones
Pro Tips
Start Simple: Begin with default settings, then gradually customize
Focus on Yellow Line: Your primary indicator of current price position
Combine Timeframes: Use the same terrain across multiple timeframes for confluence
Volume Confirmation: Ensure terrain peaks align with actual volume spikes
Void Anticipation: When price enters voids, prepare for potential rapid movement
Order Blocks & Voids Architecture
Order Blocks Calculation
Trigger: Price breaks fractal swing points
Bullish OB: When close > swing high → find lowest low in lookback period
Bearish OB: When close < swing low → find highest high in lookback period
Strength: Based on price distance from block extremes
Storage: Global array maintains last 50 blocks with FIFO management
Liquidity Voids Detection
Trigger: Price gaps exceeding ATR threshold
Bull Void: Low - high > (ATR200 × multiplier)
Bear Void: Low - high > (ATR200 × multiplier)
Validation: Close confirms gap direction
Storage: Global array maintains last 30 voids
Key Design Features
Real-time Updates: Calculated every bar, not just on last bar
Global Persistence: Arrays maintain state across executions
FIFO Management: Automatic cleanup of oldest entries
Configurable Sensitivity: Adjustable lookback periods and thresholds
Scientific Testing Framework
Hypothesis Testing
Primary Hypothesis: 3D terrain visualization improves detection of institutional order flow vs traditional 2D charts
Testable Metrics:
Prediction Accuracy: Does terrain structure predict future support/resistance?
Reaction Time: Faster identification of key levels vs conventional methods
False Positive Reduction: Lower rate of failed breakouts/breakdowns
Control Variables
Market Regime: Trending vs ranging conditions
Asset Classes: Forex, equities, cryptocurrencies
Timeframes: M5 to H4 for intraday, D1 for swing
Volume Conditions: High vs low volume environments
Data Collection Protocol
Terrain Features to Quantify:
Slope gradient changes at price inflection points
Volume peak clustering density
Order block terrain elevation vs subsequent price action
Void depth correlation with momentum acceleration
Control Group: Traditional support/resistance + volume profile
Experimental Group: 3D Institutional Flow Terrain
Statistical Measures
Signal-to-Noise Ratio: Terrain features vs random price movements
Lead Time: Terrain formation ahead of price confirmation
Effect Size: Performance difference between groups (Cohen's d)
Statistical Power: Sample size requirements for significance
Validation Methodology
Blind Testing:
Remove price labels from terrain screenshots
Have traders identify key levels from terrain alone
Measure accuracy vs actual price action
Backtesting Framework:
Automated terrain feature extraction
Correlation with future price reversals/breakouts
Monte Carlo simulation for significance testing
Expected Outcomes
If hypothesis valid:
Significant improvement in level prediction accuracy (p < 0.05)
Reduced latency in institutional level identification
Higher risk-reward ratios on terrain-confirmed trades
Research Questions:
Does terrain elevation reliably indicate institutional interest zones?
Are liquidity voids statistically significant momentum predictors?
Does multi-timeframe terrain analysis improve signal quality?
How does terrain persistence correlate with level strength?
LuxAlgo BigBeluga hapharmonic
Dual FUT/Spot price with next monthly expiryThis Pine Script dashboard indicator is specifically designed for pair trading strategies in Indian futures markets (NSE). Let me break down how it facilitates pair trading:
Core Pair Trading Concept
The script monitors two correlated stocks simultaneously (Symbol A and Symbol B), comparing their:
Spot prices vs Futures prices
Current month futures vs Next month futures
Premium/discount relationships
Key Pair Trading Features
1. Dual Symbol Monitoring
symbolA = "NSE:TCS" (Default)
symbolB = "NSE:INFY" (Default)
Allows traders to watch two stocks in the same sector (like TCS and Infosys in IT) to identify relative value opportunities.
2. Basis Analysis for Each Stock
The indicator calculates the basis (difference between futures and spot):
Price Difference: FUT - SPOT
Premium/Discount %: ((FUT - SPOT) / SPOT) × 100
This helps identify when one stock's futures are relatively more expensive than the other's.
3. Multi-Expiry View
Near Month Futures (1!): Current active contract
Next Month Futures (2!): Upcoming contract
This enables calendar spread analysis within each stock and helps anticipate rollover effects.
4. Comparative Table
The detailed table displays side-by-side:
Symbol Spot Price Near Future Near Diff (%)Next Monthly Next Diff (%)Lot SizeTCS₹3,500₹3,520+20 (+0.57%)₹3,535+35 (+1.00%)125INFY₹1,450₹1,455+5 (+0.34%)₹1,460+10 (+0.69%)600
5. Lot Size Integration
Critical for position sizing in pair trades - the indicator fetches actual contract lot sizes, enabling proper hedge ratio calculations.
Pair Trading Strategies Enabled
Strategy 1: Basis Divergence Trading
When TCS futures trade at +0.8% premium and INFY at +0.2%
Trade: Short TCS futures, Long INFY futures (betting on convergence)
The indicator highlights these differences with color-coded cells
Strategy 2: Calendar Spread Arbitrage
Compare near month vs next month premium for each stock
If TCS shows wider calendar spread than INFY, potential arbitrage exists
Trade the relative calendar spread difference
Strategy 3: Premium/Discount Reversal
Monitor which stock moves from premium to discount (or vice versa)
Color indicators (green/red) make this immediately visible
Enter pairs when relative premium relationships normalize
Strategy 4: Lot-Adjusted Pair Trading
Use lot size data to create market-neutral positions
Example: If TCS lot = 125 and INFY lot = 600
Ratio = 600/125 = 4.8:1 for rupee-neutral positioning
Visual Trading Cues
Green cells: Futures at premium (contango)
Red cells: Futures at discount (backwardation)
Purple values: Next month contracts
Yellow highlights: Spot prices
Practical Pair Trading Example
Scenario: Both stocks in same sector, historically correlated
Normal state: Both show +0.5% premium
Divergence: TCS jumps to +1.2%, INFY stays at +0.5%
Trade Signal:
Short TCS futures (expensive)
Long INFY futures (relatively cheap)
Exit: When premiums converge back to similar levels
Hedge ratio: Use lot sizes to maintain proper exposure balance
Advantages for Pair Traders
✓ Single-screen monitoring of both legs
✓ Real-time basis calculations eliminate manual math
✓ Multi-timeframe view (near + next month)
✓ Automatic lot size fetching for position sizing
✓ Visual alerts through color coding
✓ Percentage normalization for easy comparison
This indicator essentially transforms raw price data into actionable pair trading intelligence by highlighting relative value discrepancies between correlated assets in the futures market.
Enjoy!!
Connors Double Seven (with options)Rules (original, long-only)
Trade only when Close > 200-day SMA.
Entry: Buy when Close makes a 7-day low.
Exit: Sell when Close makes a 7-day high.
Scientific Correlation Testing FrameworkScientific Correlation Testing Framework - Comprehensive Guide
Introduction to Correlation Analysis
What is Correlation?
Correlation is a statistical measure that describes the degree to which two assets move in relation to each other. Think of it like measuring how closely two dancers move together on a dance floor.
Perfect Positive Correlation (+1.0): Both dancers move in perfect sync, same direction, same speed
Perfect Negative Correlation (-1.0): Both dancers move in perfect sync but in opposite directions
Zero Correlation (0): The dancers move completely independently of each other
In financial markets, correlation helps us understand relationships between different assets, which is crucial for:
Portfolio diversification
Risk management
Pairs trading strategies
Hedging positions
Market analysis
Why This Script is Special
This script goes beyond simple correlation calculations by providing:
Two different correlation methods (Pearson and Spearman)
Statistical significance testing to ensure results are meaningful
Rolling correlation analysis to track how relationships change over time
Visual representation for easy interpretation
Comprehensive statistics table with detailed metrics
Deep Dive into the Script's Components
1. Input Parameters Explained-
Symbol Selection:
This allows you to select the second asset to compare with the chart's primary asset
Default is Apple (NASDAQ:AAPL), but you can change this to any symbol
Example: If you're viewing a Bitcoin chart, you might set this to "NASDAQ:TSLA" to see if Bitcoin and Tesla are correlated
Correlation Window (60): This is the number of periods used to calculate the main correlation
Larger values (e.g., 100-500) provide more stable, long-term correlation measures
Smaller values (e.g., 10-50) are more responsive to recent price movements
60 is a good balance for most daily charts (about 3 months of trading days)
Rolling Correlation Window (20): A shorter window to detect recent changes in correlation
This helps identify when the relationship between assets is strengthening or weakening
Default of 20 is roughly one month of trading days
Return Type: This determines how price changes are calculated
Simple Returns: (Today's Price - Yesterday's Price) / Yesterday's Price
Easy to understand: "The asset went up 2% today"
Log Returns: Natural logarithm of (Today's Price / Yesterday's Price)
More mathematically elegant for statistical analysis
Better for time-additive properties (returns over multiple periods)
Less sensitive to extreme values.
Confidence Level (95%): This determines how certain we want to be about our results
95% confidence means we accept a 5% chance of being wrong (false positive)
Higher confidence (e.g., 99%) makes the test more strict
Lower confidence (e.g., 90%) makes the test more lenient
95% is the standard in most scientific research
Show Statistical Significance: When enabled, the script will test if the correlation is statistically significant or just due to random chance.
Display options control what you see on the chart:
Show Pearson/Spearman/Rolling Correlation: Toggle each correlation type on/off
Show Scatter Plot: Displays a scatter plot of returns (limited to recent points to avoid performance issues)
Show Statistical Tests: Enables the detailed statistics table
Table Text Size: Adjusts the size of text in the statistics table
2.Functions explained-
calcReturns():
This function calculates price returns based on your selected method:
Log Returns:
Formula: ln(Price_t / Price_t-1)
Example: If a stock goes from $100 to $101, the log return is ln(101/100) = ln(1.01) ≈ 0.00995 or 0.995%
Benefits: More symmetric, time-additive, and better for statistical modeling
Simple Returns:
Formula: (Price_t - Price_t-1) / Price_t-1
Example: If a stock goes from $100 to $101, the simple return is (101-100)/100 = 0.01 or 1%
Benefits: More intuitive and easier to understand
rankArray():
This function calculates the rank of each value in an array, which is used for Spearman correlation:
How ranking works:
The smallest value gets rank 1
The second smallest gets rank 2, and so on
For ties (equal values), they get the average of their ranks
Example: For values
Sorted:
Ranks: (the two 2s tie for ranks 1 and 2, so they both get 1.5)
Why this matters: Spearman correlation uses ranks instead of actual values, making it less sensitive to outliers and non-linear relationships.
pearsonCorr():
This function calculates the Pearson correlation coefficient:
Mathematical Formula:
r = (nΣxy - ΣxΣy) / √
Where x and y are the two variables, and n is the sample size
What it measures:
The strength and direction of the linear relationship between two variables
Values range from -1 (perfect negative linear relationship) to +1 (perfect positive linear relationship)
0 indicates no linear relationship
Example:
If two stocks have a Pearson correlation of 0.8, they have a strong positive linear relationship
When one stock goes up, the other tends to go up in a fairly consistent proportion
spearmanCorr():
This function calculates the Spearman rank correlation:
How it works:
Convert each value in both datasets to its rank
Calculate the Pearson correlation on the ranks instead of the original values
What it measures:
The strength and direction of the monotonic relationship between two variables
A monotonic relationship is one where as one variable increases, the other either consistently increases or decreases
It doesn't require the relationship to be linear
When to use it instead of Pearson:
When the relationship is monotonic but not linear
When there are significant outliers in the data
When the data is ordinal (ranked) rather than interval/ratio
Example:
If two stocks have a Spearman correlation of 0.7, they have a strong positive monotonic relationship
When one stock goes up, the other tends to go up, but not necessarily in a straight-line relationship
tStatistic():
This function calculates the t-statistic for correlation:
Mathematical Formula: t = r × √((n-2)/(1-r²))
Where r is the correlation coefficient and n is the sample size
What it measures:
How many standard errors the correlation is away from zero
Used to test the null hypothesis that the true correlation is zero
Interpretation:
Larger absolute t-values indicate stronger evidence against the null hypothesis
Generally, a t-value greater than 2 (in absolute terms) is considered statistically significant at the 95% confidence level
criticalT() and pValue():
These functions provide approximations for statistical significance testing:
criticalT():
Returns the critical t-value for a given degrees of freedom (df) and significance level
The critical value is the threshold that the t-statistic must exceed to be considered statistically significant
Uses approximations since Pine Script doesn't have built-in statistical distribution functions
pValue():
Estimates the p-value for a given t-statistic and degrees of freedom
The p-value is the probability of observing a correlation as strong as the one calculated, assuming the true correlation is zero
Smaller p-values indicate stronger evidence against the null hypothesis
Standard interpretation:
p < 0.01: Very strong evidence (marked with **)
p < 0.05: Strong evidence (marked with *)
p ≥ 0.05: Weak evidence, not statistically significant
stdev():
This function calculates the standard deviation of a dataset:
Mathematical Formula: σ = √(Σ(x-μ)²/(n-1))
Where x is each value, μ is the mean, and n is the sample size
What it measures:
The amount of variation or dispersion in a set of values
A low standard deviation indicates that the values tend to be close to the mean
A high standard deviation indicates that the values are spread out over a wider range
Why it matters for correlation:
Standard deviation is used in calculating the correlation coefficient
It also provides information about the volatility of each asset's returns
Comparing standard deviations helps understand the relative riskiness of the two assets.
3.Getting Price Data-
price1: The closing price of the primary asset (the chart you're viewing)
price2: The closing price of the secondary asset (the one you selected in the input parameters)
Returns are used instead of raw prices because:
Returns are typically stationary (mean and variance stay constant over time)
Returns normalize for price levels, allowing comparison between assets of different values
Returns represent what investors actually care about: percentage changes in value
4.Information Table-
Creates a table to display statistics
Only shows on the last bar to avoid performance issues
Positioned in the top right of the chart
Has 2 columns and 15 rows
Populating the Table
The script then populates the table with various statistics:
Header Row: "Metric" and "Value"
Sample Information: Sample size and return type
Pearson Correlation: Value, t-statistic, p-value, and significance
Spearman Correlation: Value, t-statistic, p-value, and significance
Rolling Correlation: Current value
Standard Deviations: For both assets
Interpretation: Text description of the correlation strength
The table uses color coding to highlight important information:
Green for significant positive results
Red for significant negative results
Yellow for borderline significance
Color-coded headers for each section
=> Practical Applications and Interpretation
How to Interpret the Results
Correlation Strength
0.0 to 0.3 (or 0.0 to -0.3): Weak or no correlation
The assets move mostly independently of each other
Good for diversification purposes
0.3 to 0.7 (or -0.3 to -0.7): Moderate correlation
The assets show some tendency to move together (or in opposite directions)
May be useful for certain trading strategies but not extremely reliable
0.7 to 1.0 (or -0.7 to -1.0): Strong correlation
The assets show a strong tendency to move together (or in opposite directions)
Can be useful for pairs trading, hedging, or as a market indicator
Statistical Significance
p < 0.01: Very strong evidence that the correlation is real
Marked with ** in the table
Very unlikely to be due to random chance
p < 0.05: Strong evidence that the correlation is real
Marked with * in the table
Unlikely to be due to random chance
p ≥ 0.05: Weak evidence that the correlation is real
Not marked in the table
Could easily be due to random chance
Rolling Correlation
The rolling correlation shows how the relationship between assets changes over time
If the rolling correlation is much different from the long-term correlation, it suggests the relationship is changing
This can indicate:
A shift in market regime
Changing fundamentals of one or both assets
Temporary market dislocations that might present trading opportunities
Trading Applications
1. Portfolio Diversification
Goal: Reduce overall portfolio risk by combining assets that don't move together
Strategy: Look for assets with low or negative correlations
Example: If you hold tech stocks, you might add some utilities or bonds that have low correlation with tech
2. Pairs Trading
Goal: Profit from the relative price movements of two correlated assets
Strategy:
Find two assets with strong historical correlation
When their prices diverge (one goes up while the other goes down)
Buy the underperforming asset and short the outperforming asset
Close the positions when they converge back to their normal relationship
Example: If Coca-Cola and Pepsi are highly correlated but Coca-Cola drops while Pepsi rises, you might buy Coca-Cola and short Pepsi
3. Hedging
Goal: Reduce risk by taking an offsetting position in a negatively correlated asset
Strategy: Find assets that tend to move in opposite directions
Example: If you hold a portfolio of stocks, you might buy some gold or government bonds that tend to rise when stocks fall
4. Market Analysis
Goal: Understand market dynamics and interrelationships
Strategy: Analyze correlations between different sectors or asset classes
Example:
If tech stocks and semiconductor stocks are highly correlated, movements in one might predict movements in the other
If the correlation between stocks and bonds changes, it might signal a shift in market expectations
5. Risk Management
Goal: Understand and manage portfolio risk
Strategy: Monitor correlations to identify when diversification benefits might be breaking down
Example: During market crises, many assets that normally have low correlations can become highly correlated (correlation convergence), reducing diversification benefits
Advanced Interpretation and Caveats
Correlation vs. Causation
Important Note: Correlation does not imply causation
Example: Ice cream sales and drowning incidents are correlated (both increase in summer), but one doesn't cause the other
Implication: Just because two assets move together doesn't mean one causes the other to move
Solution: Look for fundamental economic reasons why assets might be correlated
Non-Stationary Correlations
Problem: Correlations between assets can change over time
Causes:
Changing market conditions
Shifts in monetary policy
Structural changes in the economy
Changes in the underlying businesses
Solution: Use rolling correlations to monitor how relationships change over time
Outliers and Extreme Events
Problem: Extreme market events can distort correlation measurements
Example: During a market crash, many assets may move in the same direction regardless of their normal relationship
Solution:
Use Spearman correlation, which is less sensitive to outliers
Be cautious when interpreting correlations during extreme market conditions
Sample Size Considerations
Problem: Small sample sizes can produce unreliable correlation estimates
Rule of Thumb: Use at least 30 data points for a rough estimate, 60+ for more reliable results
Solution:
Use the default correlation length of 60 or higher
Be skeptical of correlations calculated with small samples
Timeframe Considerations
Problem: Correlations can vary across different timeframes
Example: Two assets might be positively correlated on a daily basis but negatively correlated on a weekly basis
Solution:
Test correlations on multiple timeframes
Use the timeframe that matches your trading horizon
Look-Ahead Bias
Problem: Using information that wouldn't have been available at the time of trading
Example: Calculating correlation using future data
Solution: This script avoids look-ahead bias by using only historical data
Best Practices for Using This Script
1. Appropriate Parameter Selection
Correlation Window:
For short-term trading: 20-50 periods
For medium-term analysis: 50-100 periods
For long-term analysis: 100-500 periods
Rolling Window:
Should be shorter than the main correlation window
Typically 1/3 to 1/2 of the main window
Return Type:
For most applications: Log Returns (better statistical properties)
For simplicity: Simple Returns (easier to interpret)
2. Validation and Testing
Out-of-Sample Testing:
Calculate correlations on one time period
Test if they hold in a different time period
Multiple Timeframes:
Check if correlations are consistent across different timeframes
Economic Rationale:
Ensure there's a logical reason why assets should be correlated
3. Monitoring and Maintenance
Regular Review:
Correlations can change, so review them regularly
Alerts:
Set up alerts for significant correlation changes
Documentation:
Keep notes on why certain assets are correlated and what might change that relationship
4. Integration with Other Analysis
Fundamental Analysis:
Combine correlation analysis with fundamental factors
Technical Analysis:
Use correlation analysis alongside technical indicators
Market Context:
Consider how market conditions might affect correlations
Conclusion
This Scientific Correlation Testing Framework provides a comprehensive tool for analyzing relationships between financial assets. By offering both Pearson and Spearman correlation methods, statistical significance testing, and rolling correlation analysis, it goes beyond simple correlation measures to provide deeper insights.
For beginners, this script might seem complex, but it's built on fundamental statistical concepts that become clearer with use. Start with the default settings and focus on interpreting the main correlation lines and the statistics table. As you become more comfortable, you can adjust the parameters and explore more advanced applications.
Remember that correlation analysis is just one tool in a trader's toolkit. It should be used in conjunction with other forms of analysis and with a clear understanding of its limitations. When used properly, it can provide valuable insights for portfolio construction, risk management, and pair trading strategy development.
Advanced Time TechniqueAdvanced Time Technique (ATT)
The Advanced Time Technique (ATT) identifies mathematically significant price levels based on candle count sequences within higher timeframes. The indicator tracks specific numerical patterns to project potential reversal zones.
Calculation Methodology:
- Monitors candle cycles in user-selected higher timeframes (1H, 2H, 3H)
- Identifies key candle counts: 3, 11, 17, 29, 41, 47, 53, 59
- Projects these counts as visual markers on the current chart
- Uses pure price action without lagging indicators
Key Features:
- HTF Candle Boxes: Displays higher timeframe candle ranges as colored boxes
- ATT Circles: Places circular markers at specified candle counts
- Multi-timeframe Analysis: References 1-hour, 2-hour, or 3-hour timeframes
- Prediction Labels: Shows upcoming ATT levels within user-defined range
- Historical Display: Optional viewing of past ATT markers
Visual Components:
- Colored boxes representing HTF candle ranges (bullish/bearish)
- Circle markers positioned above/below bars based on candle color
- Optional numerical display on ATT circles
- Customizable colors and transparency settings
Trading Applications:
- Identifies potential reversal zones at mathematically significant intervals
- Highlights liquidity concentration areas
- Useful for intraday and scalp trading strategies
- Complements price action and market structure analysis
The indicator works by counting candles within the selected higher timeframe and marking specific numerical sequences where price reactions commonly occur.
ka66: Symbol InformationThis shows a table of all current (Pine v6) `syminfo.` values.
Please note this is primarily of use to Pine Developers, or the curious trader.
There are a few of these around on TradingView, but many seem to focus on the use case they have. This script just dumps all values, in alphabetical order of properties.
You can use this to inspect the details of the symbol, which in turn, can be fed into various scripts covering tasks such as:
Position Sizing calculation (which requires things like tick, pointvalue, and currency details)
Recommendation engines (which use the recommendation_* properties)
Fundamentals on stocks (which may use share count information, and possibly employee information)
Note that not all table values are populated, as they depend on the instrument being introspected. For example, a share ticker will have some different details to a Forex pair. The `NaN` values (the "Not A Number" special value in programming parlance) are not a bug, they are simply Pine reporting that no value is set for it. I have opted to dump out values as-is as the focus is developers.
My motivation to create it was to write a position sizing tool. Additionally, the output of this script is cleanly formatted, with monospace fonts and conventional alignment for tables/forms with key and values. It also allows customising the table position. Ideally this feature is made part of the default TradingView customisation, but at this time, it is not, and tables don't auto-adjust their positions.
Smart Money Volume Tools | Lyro RSSmart Money Volume Tools | Lyro RS
Overview
The Smart Money Volume Tools (SMVT) is a multi-dimensional volume-based analysis suite designed to visualize the interplay between price action, moving averages, and smart money behavior.
By integrating dynamic moving averages, volume normalization, and multi-timeframe intelligence, SMVT helps traders identify when institutional (smart money) or retail participants are influencing price movements — all in a single, adaptive display.
Unlike traditional oscillators or trend tools, SMVT dynamically adjusts its sensitivity and thresholds based on volume z-scores and normalized momentum, revealing true intent behind price shifts rather than reacting to them.
🔹 Key Features
4 Core Analytical Modes:
Trail Mode – Identifies directional bias using dynamic volume-weighted trails based on adaptive ATR multipliers.
Volume Mode – Displays normalized volume strength vs. price trend, highlighting volume-driven expansions.
Smart Money Volume Mode – Detects institutional buying/selling spikes from lower timeframes using volume z-score outliers.
Retail Money Volume Mode – Contrasts retail-driven impulses to visualize crowd behavior and exhaustion points.
Dynamic Volume Normalization: Converts volume impulses into a 0–100 range using a sigmoid function for smoother interpretation.
Multi-Timeframe Intelligence: Automatically reads lower timeframe volume data to distinguish smart vs. retail activity.
Adaptive Color Systems: Multiple palette modes ( Classic , Mystic , Accented , Royal ) or full custom color control.
Signal Table Overlay: Built-in real-time module summary showing status for Trail , Volume , Smart Money , and Retail Money — right on your chart.
🔹 How It Works
Volume Strength Calculation:
Calculates relative volume strength using a moving average baseline, then normalizes the result via a sigmoid function — mapping activity into a clean 0–100 range.
Smart Money Detection:
Scans lower timeframe data for extreme volume z-scores ( z > 2 ) to pinpoint institutional accumulation or distribution zones.
Trail Logic:
Uses adaptive upper and lower trails based on ATR and volume intensity to track volatility-adjusted trend direction.
Color Logic:
Trail, candle, and fill colors change dynamically according to the active signal type and selected palette — making directional bias instantly visible.
🔹 Practical Use
Swing Confirmation (Trail Mode): Confirms sustained bullish or bearish momentum supported by volume, ideal for trailing positions and managing exits.
Volume Expansion (Volume Mode): Highlights key moments when institutional liquidity pushes price before visible breakout confirmation.
Smart vs. Retail Divergence: Identify conflicts between retail activity and smart money to detect exhaustion or reversal points early.
Table Overlay Utility: Instantly see all active signals across modules in one compact, on-chart interface.
🔹 Customization
Custom color palettes or manual bullish/bearish color selection.
Adjustable EMA lengths and Volume SMA period .
Selectable lower timeframe source for Smart Money analysis.
Flexible table position & size controls — choose between Top, Middle, Bottom and Tiny to Huge.
Switch freely between Trail , Volume , Smart Money , and Retail Money modes.
Credits
Thank you to @AlgoAlpha for the smart money and retail activity source code.
⚠️Disclaimer
This indicator is a tool for technical analysis and does not provide guaranteed results. It should be used in conjunction with other analysis methods and proper risk management practices. The creators of this indicator are not responsible for any financial decisions made based on its signals.
Price Above PDH - Complete Multi-Confirmation Alert🎯 COMPLETE FEATURES: $jmoskyhigh cashapp
1. Comprehensive Input Settings
✅ All visual customization options
✅ Color pickers for every element
✅ Toggle for each confirmation requirement
✅ Adjustable thresholds and timeframes
✅ Multiple alert options per day
✅ Customizable panel position
2. Full Confirmation System
✅ Volume: Must exceed customizable multiplier of average
✅ Moving Averages: Fast MA must be above Slow MA
✅ VWAP: Price must be above VWAP
✅ All confirmations must remain valid for ENTIRE hold period
✅ Any confirmation failure = Complete reset
Trade Journal ProTrade Journal Pro
A powerful, visual trading journal that enforces discipline with real-time feedback, reflective prompts, and strict risk limits — all in one clean overlay box.
Jesus is King — trade with wisdom, not emotion.
FEATURES
• AUTO-CALCULATED DAILY TRADES
→ `Trades Today = Wins + Losses + Breakevens` (no manual input needed)
• 4 ENFORCED RISK LIMITS
1. Max Trades Per Day
2. Max Risk Rule Violations
3. Max Consecutive Losses (tilt protection)
4. Max Total Losses Allowed (lifetime/session cap)
• SMART VISUAL FEEDBACK
• GREEN BOX = You hit a limit exactly → “WELL DONE!”
• RED BOX = Breached any limit → “STOP & REFLECT” + ALERT
• Dark = Normal (under all limits)
• REFLECTIVE PROMPTS (Customizable)
1. Why this setup?
2. What was my emotional state?
3. Did I follow my plan?
• LIVE ADVICE ENGINE
→ Win: “Great execution! Log what worked.”
→ Loss: “Loss = tuition. What did you learn?”
→ Breakeven: “Review entry/exit precision.”
• DAILY REMINDER
→ Always visible: “Trade the plan, not the emotion.”
• FULLY CUSTOMIZABLE
• Font size (Tiny → Huge)
• Box position (bars to the right)
• Toggle: Metrics / Prompts / Advice
• Custom colors, messages, limits
• ALERTS
• Breach any limit → Immediate alert
• Hit limit exactly → Discipline win notification
HOW TO USE
1. After each closed trade:
→ Update Wins, Losses, or Breakevens
→ Update Consecutive Losses (reset to 0 on win/BE)
→ Increment Risk Violations if you broke a rule
2. Answer the 3 prompts in your journal
3. Let the box guide your behavior:
• GREEN = Celebrate discipline
• RED = STOP TRADING. Reflect. Reset.
Perfect for day traders, swing traders, or anyone building a professional edge through journaling and risk control.
No strategy entries. No repainting. Pure accountability.
“The market is a mirror. This journal is the polish.”
Developed with integrity. Built to protect your capital — and your peace.
Sunmool's NY Lunch Model BacktestingICT NY Lunch Model Backtesting (12:00–13:00 NY) 🗽🍔
This research indicator tests an ICT narrative using the New York lunch window (12:00–13:00 America/New_York). It records that hour’s high/low and measures, during the post-lunch session (default 13:00–16:00), how often:
⬆️ If the afternoon trends up, the Lunch Low gets swept first.
⬇️ If the afternoon trends down, the Lunch High gets swept first.
It reports these as conditional probabilities, not trade signals. 📈
👀 What it shows
🟦 Lunch Range box (toggle): high/low from 12:00–13:00 NY
🔻🔺 Sweep signals (bar-anchored)
Low sweep: triangle below bar + optional “L”
High sweep: triangle above bar + optional “H”
🧱 Optional small box wrapping the swept candle
📊 Stats table (top-right)
P(L-swept | Up) — % of Up-days where Lunch Low was swept
P(H-swept | Down) — % of Down-days where Lunch High was swept
🔁 Contradictions + sample sizes (Up-days / Down-days)
🎯 Direction logic (Up/Down)
Anchor: 13:00 open (pmOpen) ⏰
Threshold: ATR × multiple or % from 13:00
Close ≥ pmOpen + threshold → Up-day
Close ≤ pmOpen − threshold → Down-day
Tiny moves under the threshold are ignored to reduce noise 🧹
⚙️ Inputs
🌐 Timezone: America/New_York (DST handled)
🍽️ Lunch window: 1200–1300
🕓 Post-lunch window: default 1300–1600 (try 17:00/20:00 for sensitivity)
📐 Trend threshold: ATR / Percent (with length/multiple or % level)
📅 Weekdays-only toggle (FX/Equities style)
👁️ Display toggles: Lunch box / sweep arrows / sweep text / sweep candle box / stats table
🔔 TF hint when chart TF > 15m
🧭 How to use
Use 5–15m charts for accurate lunch range capture.
Scroll ~1 year for meaningful samples.
Run sensitivity checks: vary ATR/% thresholds and the post-lunch end time.
For crypto, compare with vs without weekends. 🚀
🧠 Reading the results
High P(L-swept | Up) with a solid Up-day count ⇒ on up afternoons, lunch low is often swept.
High P(H-swept | Down) ⇒ on down afternoons, lunch high is often swept.
Lower Contradictions = cleaner tendency.
Remember: this is a probabilistic tendency, not a rule. 🎲
📝 Notes & limits
All markers (arrows, text, sweep boxes) are bar-anchored; the lunch range box is a research overlay you can toggle.
Real-time vs historical bar building can differ—interpret on bar close. 🔒
Purchasing Power vs Gold, Stocks, Real Estate, BTC (1971 = 100)Visual comparison of U.S. dollar purchasing power versus major assets since 1971, when the U.S. ended the gold standard. Each asset is normalized to 100 in 1971, showing how real value has shifted across gold, real estate, stocks, and Bitcoin over time.
Source: FRED (CPIAUCSL, SP500, MSPUS) • OANDA (XAUUSD) • TradingView (INDEX:BTCUSD/BLX)
Visualization by 3xplain






















