Chart-prepFxxDanny Chart-Prep
A practical multi-tool script for clean and structured chart preparation.
✨ Features
Weekly Close Levels
Automatically plots the previous week’s close and the week before that, with clear styling to distinguish current and past levels.
Trading Sessions
Colored session boxes for the three key market sessions:
Asia (20:00–23:00 UTC-4)
Europe (02:00–05:00 UTC-4)
New York (08:00–11:00 UTC-4)
Each session box automatically adapts to the session’s high/low range and only keeps the last 5 visible to avoid clutter.
Previous Day’s High & Low
Plots the prior day’s high and low with lines that extend into the current session. Up to 10 days are kept on the chart.
Daily & Weekly Separators
Vertical lines to visually separate days (dotted) and weeks (solid, colored).
Anchored to a rolling price window so the Y-axis scaling stays clean and unaffected.
✅ Benefits
Stay focused with key price levels and session ranges marked automatically.
No need for manual drawing or constant adjustments.
Optimized performance – old objects are automatically removed.
No axis distortion from “infinite” lines or boxes.
Search in scripts for "session"
Composite Time ProfileComposite Time Profile Overlay (CTPO) - Market Profile Compositing Tool
Automatically composite multiple time periods to identify key areas of balance and market structure
What is the Composite Time Profile Overlay?
The Composite Time Profile Overlay (CTPO) is a Pine Script indicator that automatically composites multiple time periods to identify key areas of balance and market structure. It's designed for traders who use market profile concepts and need to quickly identify where price is likely to find support or resistance.
The indicator analyzes TPO (Time Price Opportunity) data across different timeframes and merges overlapping profiles to create composite levels that represent the most significant areas of balance. This helps you spot where institutional traders are likely to make decisions based on accumulated price action.
Why Use CTPO for Market Profile Trading?
Eliminate Manual Compositing Work
Instead of manually drawing and compositing profiles across different timeframes, CTPO does this automatically. You get instant access to composite levels without spending time analyzing each individual period.
Spot Areas of Balance Quickly
The indicator highlights the most significant areas of balance by compositing overlapping profiles. These areas often act as support and resistance levels because they represent where the most trading activity occurred across multiple time periods.
Focus on What Matters
Rather than getting lost in individual session profiles, CTPO shows you the composite levels that have been validated across multiple timeframes. This helps you focus on the levels that are most likely to hold.
How CTPO Works for Market Profile Traders
Automatic Profile Compositing
CTPO uses a proprietary algorithm that:
- Identifies period boundaries based on your selected timeframe (sessions, daily, weekly, monthly, or auto-detection)
- Calculates TPO profiles for each period using the C2M (Composite 2 Method) row sizing calculation
- Merges overlapping profiles using configurable overlap thresholds (default 50% overlap required)
- Updates composite levels as new price action develops in real-time
Key Levels for Market Profile Analysis
The indicator displays:
- Value Area High (VAH) and Value Area Low (VAL) levels calculated from composite TPO data
- Point of Control (POC) levels where most trading occurred across all composited periods
- Composite zones representing areas of balance with configurable transparency
- 1.618 Fibonacci extensions for breakout targets based on composite range
Multiple Timeframe Support
- Sessions: For intraday market profile analysis
- Daily: For swing trading with daily profiles
- Weekly: For position trading with weekly structure
- Monthly: For long-term market profile analysis
- Auto: Automatically selects timeframe based on your chart
Trading Applications for Market Profile Users
Support and Resistance Trading
Use composite levels as dynamic support and resistance zones. These levels often hold because they represent areas where significant trading decisions were made across multiple timeframes.
Breakout Trading
When composite levels break, they often lead to significant moves. The indicator calculates 1.618 Fibonacci extensions to give you clear targets for breakout trades.
Mean Reversion Strategies
Value Area levels represent the price range where most trading activity occurred. These levels often act as magnets, drawing price back when it moves too far from the mean.
Institutional Level Analysis
Composite levels represent areas where institutional traders have made significant decisions. These levels often hold more weight than traditional technical analysis levels because they're based on actual trading activity.
Key Features for Market Profile Traders
Smart Compositing Logic
- Automatic overlap detection using price range intersection algorithms
- Configurable overlap thresholds (minimum 50% overlap required for merging)
- Dead composite identification (profiles that become engulfed by newer composites)
- Real-time updates as new price action develops using barstate.islast optimization
Visual Customization
- Customizable colors for active, broken, and dead composites
- Adjustable transparency levels for each composite state
- Premium/Discount zone highlighting based on current price vs composite range
- TPO aggression coloring using TPO distribution analysis to identify buying/selling pressure
- Fibonacci level extensions with 1.618 target calculations based on composite range
Clean Chart Presentation
- Only shows the most relevant composite levels (maximum 10 active composites)
- Eliminates clutter from individual session profiles
- Focuses on areas of balance that matter most to current price action
Real-World Trading Examples
Day Trading with Session Composites
Use session-based composites to identify intraday areas of balance. The VAH and VAL levels often act as natural profit targets and stop-loss levels for scalping strategies.
Swing Trading with Daily Composites
Daily composites provide excellent swing trading levels. Look for price reactions at composite zones and use the 1.618 extensions for profit targets.
Position Trading with Weekly Composites
Weekly composites help identify major trend changes and long-term areas of balance. These levels often hold for months or even years.
Risk Management
Composite levels provide natural stop-loss levels. If a composite level breaks, it often signals a significant shift in market sentiment, making it an ideal place to exit losing positions.
Why Composite Levels Work
Composite levels work because they represent areas where significant trading decisions were made across multiple timeframes. When price returns to these levels, traders often remember the previous price action and make similar decisions, creating self-fulfilling prophecies.
The compositing process uses a proprietary algorithm that ensures only levels validated across multiple time periods are displayed. This means you're looking at levels that have proven their significance through actual market behavior, not just random technical levels.
Technical Foundation
The indicator uses TPO (Time Price Opportunity) data combined with price action analysis to identify areas of balance. The C2M row sizing method ensures accurate profile calculations, while the overlap detection algorithm (minimum 50% price range intersection) ensures only truly significant composites are displayed. The algorithm calculates row size based on ATR (Average True Range) divided by 10, then converts to tick size for precise level calculations.
How the Code Actually Works
1. Period Detection and ATR Calculation
The code first determines the appropriate timeframe based on your chart:
- 1m-5m charts: Session-based profiles
- 15m-2h charts: Daily profiles
- 4h charts: Weekly profiles
- 1D charts: Monthly profiles
For each period type, it calculates the number of bars needed for ATR calculation:
- Sessions: 540 minutes divided by chart timeframe
- Daily: 1440 minutes divided by chart timeframe
- Weekly: 7 days worth of minutes divided by chart timeframe
- Monthly: 30 days worth of minutes divided by chart timeframe
2. C2M Row Size Calculation
The code calculates True Range for each bar in the determined period:
- True Range = max(high-low, |high-prevClose|, |low-prevClose|)
- Averages all True Range values to get ATR
- Row Size = (ATR / 10) converted to tick size
- This ensures each TPO row represents a meaningful price movement
3. TPO Profile Generation
For each period, the code:
- Creates price levels from lowest to highest price in the range
- Each level is separated by the calculated row size
- Counts how many bars touch each price level (TPO count)
- Finds the level with highest count = Point of Control (POC)
- Calculates Value Area by expanding from POC until 68.27% of total TPO blocks are included
4. Overlap Detection Algorithm
When a new profile is created, the code checks if it overlaps with existing composites:
- Calculates overlap range = min(currentVAH, prevVAH) - max(currentVAL, prevVAL)
- Calculates current profile range = currentVAH - currentVAL
- Overlap percentage = (overlap range / current profile range) * 100
- If overlap >= 50%, profiles are merged into a composite
5. Composite Merging Logic
When profiles overlap, the code creates a new composite by:
- Taking the earliest start bar and latest end bar
- Using the wider VAH/VAL range (max of both profiles)
- Keeping the POC from the profile with more TPO blocks
- Marking the composite as "active" until price breaks through
6. Real-Time Updates
The code uses barstate.islast to optimize performance:
- Only recalculates on the last bar of each period
- Updates active composite with live price action if enabled
- Cleans up old composites to prevent memory issues
- Redraws all visual elements from scratch each bar
7. Visual Rendering System
The code uses arrays to manage drawing objects:
- Clears all lines/boxes arrays on every bar
- Iterates through composites array to redraw everything
- Uses different colors for active, broken, and dead composites
- Calculates 1.618 Fibonacci extensions for broken composites
Getting Started with CTPO
Step 1: Choose Your Timeframe
Select the period type that matches your trading style:
- Use "Sessions" for day trading
- Use "Daily" for swing trading
- Use "Weekly" for position trading
- Use "Auto" to let the indicator choose based on your chart timeframe
Step 2: Customize the Display
Adjust colors, transparency, and display options to match your charting preferences. The indicator offers extensive customization options to ensure it fits seamlessly into your existing analysis.
Step 3: Identify Key Levels
Look for:
- Composite zones (blue boxes) - major areas of balance
- VAH/VAL lines - value area boundaries
- POC lines - areas of highest trading activity
- 1.618 extension lines - breakout targets
Step 4: Develop Your Strategy
Use these levels to:
- Set entry points near composite zones
- Place stop losses beyond composite levels
- Take profits at 1.618 extension levels
- Identify trend changes when major composites break
Perfect for Market Profile Traders
If you're already using market profile concepts in your trading, CTPO eliminates the manual work of compositing profiles across different timeframes. Instead of spending time analyzing each individual period, you get instant access to the composite levels that matter most.
The indicator's automated compositing process ensures you're always looking at the most relevant areas of balance, while its real-time updates keep you informed of changes as they happen. Whether you're a day trader looking for intraday levels or a position trader analyzing long-term structure, CTPO provides the market profile intelligence you need to succeed.
Streamline Your Market Profile Analysis
Stop wasting time on manual compositing. Let CTPO do the heavy lifting while you focus on executing profitable trades based on areas of balance that actually matter.
Ready to Streamline Your Market Profile Trading?
Add the Composite Time Profile Overlay to your charts today and experience the difference that automated profile compositing can make in your trading performance.
EAOBS by MIGVersion 1
1. Strategy Overview Objective: Capitalize on breakout movements in Ethereum (ETH) price after the Asian open pre-market session (7:00 PM–7:59 PM EST) by identifying high and low prices during the session and trading breakouts above the high or below the low.
Timeframe: Any (script is timeframe-agnostic, but align with session timing).
Session: Pre-market session (7:00 PM–7:59 PM EST, adjustable for other time zones, e.g., 12:00 AM–12:59 AM GMT).
Risk-Reward Ratios (R:R): Targets range from 1.2:1 to 5.2:1, with a fixed stop loss.
Instrument: Ethereum (ETH/USD or ETH-based pairs).
2. Market Setup Session Monitoring: Monitor ETH price action during the pre-market session (7:00 PM–7:59 PM EST), which aligns with the Asian market open (e.g., 9:00 AM–9:59 AM JST).
The script tracks the highest high and lowest low during this session.
Breakout Triggers: Buy Signal: Price breaks above the session’s high after the session ends (7:59 PM EST).
Sell Signal: Price breaks below the session’s low after the session ends.
Visualization: The session is highlighted on the chart with a white background.
Horizontal lines are drawn at the session’s high and low, extended for 30 bars, along with take-profit (TP) and stop-loss (SL) levels.
3. Entry Rules Long (Buy) Entry: Enter a long position when the price breaks above the session’s high price after 7:59 PM EST.
Entry price: Just above the session high (e.g., add a small buffer, like 0.1–0.5%, to avoid false breakouts, depending on volatility).
Short (Sell) Entry: Enter a short position when the price breaks below the session’s low price after 7:59 PM EST.
Entry price: Just below the session low (e.g., subtract a small buffer, like 0.1–0.5%).
Confirmation: Use a candlestick close above/below the breakout level to confirm the entry.
Optionally, add volume confirmation or a momentum indicator (e.g., RSI or MACD) to filter out weak breakouts.
Position Size: Calculate position size based on risk tolerance (e.g., 1–2% of account per trade).
Risk is determined by the stop-loss distance (10 points, as defined in the script).
4. Exit Rules Take-Profit Levels (in points, based on script inputs):TP1: 12 points (1.2:1 R:R).
TP2: 22 points (2.2:1 R:R).
TP3: 32 points (3.2:1 R:R).
TP4: 42 points (4.2:1 R:R).
TP5: 52 points (5.2:1 R:R).
Example for Long: If session high is 3000, TP levels are 3012, 3022, 3032, 3042, 3052.
Example for Short: If session low is 2950, TP levels are 2938, 2928, 2918, 2908, 2898.
Strategy: Scale out of the position (e.g., close 20% at TP1, 20% at TP2, etc.) or take full profit at a preferred TP level based on market conditions.
Stop-Loss: Fixed at 10 points from the entry.
Long SL: Session high - 10 points (e.g., entry at 3000, SL at 2990).
Short SL: Session low + 10 points (e.g., entry at 2950, SL at 2960).
Trailing Stop (Optional):After reaching TP2 or TP3, consider trailing the stop to lock in profits (e.g., trail by 10–15 points below the current price).
5. Risk Management per Trade: Limit risk to 1–2% of your trading account per trade.
Calculate position size: Account Size × Risk % ÷ (Stop-Loss Distance × ETH Price per Point).
Example: $10,000 account, 1% risk = $100. If SL = 10 points and 1 point = $1, position size = $100 ÷ 10 = 0.1 ETH.
Daily Risk Limit: Cap daily losses at 3–5% of the account to avoid overtrading.
Maximum Exposure: Avoid taking both long and short positions simultaneously unless using separate accounts or strategies.
Volatility Consideration: Adjust position size during high-volatility periods (e.g., major news events like Ethereum upgrades or macroeconomic announcements).
6. Trade Management Monitoring :Watch for breakouts after 7:59 PM EST.
Monitor price action near TP and SL levels using alerts or manual checks.
Trade Duration: Breakout lines extend for 30 bars (script parameter). Close trades if no TP or SL is hit within this period, or reassess based on market conditions.
Adjustments: If the market shows strong momentum, consider holding beyond TP5 with a trailing stop.
If the breakout fails (e.g., price reverses before TP1), exit early to minimize losses.
7. Additional Considerations Market Conditions: The 7:00 PM–7:59 PM EST session aligns with the Asian market open (e.g., Tokyo Stock Exchange open at 9:00 AM JST), which may introduce higher volatility due to Asian trading activity.
Avoid trading during low-liquidity periods or extreme volatility (e.g., major crypto news).
Check for upcoming events (e.g., Ethereum network upgrades, ETF decisions) that could impact price.
Backtesting: Test the strategy on historical ETH data using the session high/low breakouts for the 7:00 PM–7:59 PM EST window to validate performance.
Adjust TP/SL levels based on backtest results if needed.
Broker and Fees: Use a low-fee crypto exchange (e.g., Binance, Kraken, Coinbase Pro) to maximize R:R.
Account for trading fees and slippage in your position sizing.
Time zone Adjustment: Adjust session time input for your time zone (e.g., "0000-0059" for GMT).
Ensure your trading platform’s clock aligns with the script’s time zone (default: America/New_York).
8. Example Trade Scenario: Session (7:00 PM–7:59 PM EST) records a high of 3050 and a low of 3000.
Long Trade: Entry: Price breaks above 3050 (e.g., enter at 3051).
TP Levels: 3063 (TP1), 3073 (TP2), 3083 (TP3), 3093 (TP4), 3103 (TP5).
SL: 3040 (3050 - 10).
Position Size: For a $10,000 account, 1% risk = $100. SL = 11 points ($11). Size = $100 ÷ 11 = ~0.09 ETH.
Short Trade: Entry: Price breaks below 3000 (e.g., enter at 2999).
TP Levels: 2987 (TP1), 2977 (TP2), 2967 (TP3), 2957 (TP4), 2947 (TP5).
SL: 3010 (3000 + 10).
Position Size: Same as above, ~0.09 ETH.
Execution: Set alerts for breakouts, enter with limit orders, and monitor TPs/SL.
9. Tools and Setup Platform: Use TradingView to implement the Pine Script and visualize breakout levels.
Alerts: Set price alerts for breakouts above the session high or below the session low after 7:59 PM EST.
Set alerts for TP and SL levels.
Chart Settings: Use a 1-minute or 5-minute chart for precise session tracking.
Overlay the script to see high/low lines, TP levels, and SL levels.
Optional Indicators: Add RSI (e.g., avoid overbought/oversold breakouts) or volume to confirm breakouts.
10. Risk Warnings Crypto Volatility: ETH is highly volatile; unexpected news can cause rapid price swings.
False Breakouts: Breakouts may fail, especially in low-volume sessions. Use confirmation signals.
Leverage: Avoid high leverage (e.g., >5x) to prevent liquidation during volatile moves.
Session Accuracy: Ensure correct session timing for your time zone to avoid misaligned entries.
11. Performance Tracking Journaling :Record each trade’s entry, exit, R:R, and outcome.
Note market conditions (e.g., trending, ranging, news-driven).
Review: Weekly: Assess win rate, average R:R, and adherence to the plan.
Monthly: Adjust TP/SL or session timing based on performance.
90 Minute Cycles + MTFCredit goes to LuxAlgo for the inspiration from 'Sessions' which allowed users to analyse specific price movements within a user defined period with tools such as trendline, mean and vwap.
Settings
Sessions
Enable Session: Allows to enable or disable all associated elements with a specific user set session.
Session Time: Opening and closing times of the user set session in the hh:mm format.
Range: Highlights the associated session range on the chart.
Ranges Settings
Range Area colour: Set each range to a specific colour.
Range Label: Shows the session label at the mid-point of the session interval.
Usage
By breaking 24hrs in quarters, starting with an Asian range of 18:00 NY time you can visualise the principles of Accumulation, Manipulation, Distribution and Rebalance. Know as AMD or PO3 (Power of Three), the principle is that the Manipulation phase will break above or below the Accumulation, before moving in an apposing direction and then rebalancing. This only works when there is a higher timeframe PD array or liquidity to support an apposing move.
Further to the daily quarters, each one can then be broken down again into 90min cycles. Again, each represents AMD, allowing the user an opportunity to watch for reversals during the 90min manipulation phase.
Note: Ensure the Asian Cycle always begins at 18:00 NY time.
The example shows that the 90min cycle occurs, followed by an apposing move away in price action
Here is the Daily cycle, highlighting the Manipulation phase.
Enjoy!
MultiSessions traderglobal.topEste indicador de sesiones está diseñado para traders intradía que desean visualizar con precisión la actividad y la volatilidad característica de cada mercado. Basado en Pine Script v5 y optimizado para la zona horaria “America/New_York”, divide el día en sub-sesiones configurables y resalta sus rangos de precio en tiempo real. En particular, incorpora tres bloques para New York (NY1, NY2, NY3), dos para Londres (LON1, LON2), dos para Tokio (TKO1, TKO2) y mantiene Sídney como sesión opcional. Cada bloque puede activarse o desactivarse de forma independiente y cuenta con su propio color ajustable, lo que permite construir mapas visuales claros para estrategias basadas en horario, solapamientos y micro-estructuras de mercado.
El panel de inputs incluye la opción “Activate High/Low View”. Cuando está activada, el indicador calcula de manera incremental el mínimo y máximo de cada sub-sesión y sombrea el área entre ambos con fill, proporcionando una referencia inmediata del rango intrasesión (útil para medir compresión/expansión y posibles rompimientos). Cuando está desactivada, emplea un simple bgcolor por bloque, ideal para traders que prefieren un gráfico más limpio y solo desean distinguir visualmente los tramos horarios.
La lógica central utiliza dos funciones auxiliares: is_session(sess), que detecta si la vela actual pertenece a un tramo horario concreto, e is_newbar(sess), que determina el inicio de una nueva barra de referencia según la resolución elegida (D, W o M). Gracias a esta combinación, en cada sub-sesión el indicador reinicia sus contadores de alto y bajo al comenzar el período y los actualiza vela a vela mientras el bloque siga activo. Este enfoque evita mezclas de datos entre sesiones y asegura que el rango que se muestra corresponda estrictamente al segmento horario configurado.
Los horarios por defecto están pensados para Forex y contemplan casos que cruzan medianoche (por ejemplo, Tokio 2 y Sídney). Pine Script admite rangos como 2200-0200; no obstante, si tu bróker o la zona horaria del gráfico generan un sombreado parcial, basta con dividir el tramo en dos: 2200-2359 y 0000-0200. Asimismo, cada input.session incluye el patrón :1234567 para habilitar los siete días; puedes restringir días según tu operativa.
En cuanto al uso práctico, el indicador facilita identificar: (1) la estructura del rango por sub-sesión (útil para estrategias de breakout/mean-reversion), (2) los solapamientos entre Londres y New York, donde suele concentrarse la liquidez, y (3) períodos de menor volatilidad (tramos tardíos de Asia o previos a noticias). El color independiente por bloque te permite codificar visualmente la importancia o tu plan de trading (por ejemplo, tonos más intensos en ventanas de alta probabilidad).
Finalmente, su diseño modular hace sencilla la personalización: puedes ajustar colores, activar/desactivar bloques, cambiar horarios y modificar la resolución de reseteo del rango. Como posible mejora, se pueden añadir alertas de ruptura de máximos/mínimos de sub-sesión o etiquetas con la altura del rango (pips) al cierre. Este indicador no sustituye el juicio del trader ni constituye recomendación financiera, pero ofrece una base visual robusta para integrar el factor tiempo en la toma de decisiones.
This sessions indicator is built for intraday traders who want a precise, time-aware view of market activity and typical volatility patterns across the day. Written in Pine Script v5 and optimized for the “America/New_York” timezone, it divides the trading day into configurable sub-sessions and highlights their price ranges in real time. Specifically, it provides three blocks for New York (NY1, NY2, NY3), two for London (LON1, LON2), two for Tokyo (TKO1, TKO2), and keeps Sydney as an optional session. Each block can be enabled or disabled independently and comes with its own adjustable color, letting you build clear visual maps for time-based strategies, overlaps, and microstructure nuances.
In the inputs panel you’ll find the “Activate High/Low View” option. When enabled, the indicator incrementally computes each sub-session’s low and high and shades the area between them with fill, giving you an immediate reference to the intra-session range (useful for gauging compression/expansion and potential breakouts). When disabled, it switches to a clean bgcolor background by block—ideal if you prefer a minimal chart and simply want to distinguish time windows at a glance.
The core logic relies on two helper functions: is_session(sess), which detects whether the current bar falls within a given time window, and is_newbar(sess), which identifies the start of a new reference bar according to your chosen reset resolution (D, W, or M). With this combination, each sub-session resets its high/low at the beginning of the period and updates them bar by bar while the block remains active. This prevents cross-contamination between sessions and ensures the range you see belongs strictly to the configured segment.
Default hours are suited to Forex and include segments that cross midnight (e.g., Tokyo 2 and Sydney). Pine Script supports ranges like 2200-0200; however, if your broker or chart timezone causes partial shading, simply split the segment into two: 2200-2359 and 0000-0200. Each input.session uses the :1234567 suffix to enable all seven days; you can easily restrict days to match your plan.
Practically speaking, the indicator helps you identify: (1) range structure by sub-session (great for breakout or mean-reversion frameworks), (2) overlaps between London and New York, where liquidity and directional moves often concentrate, and (3) lower-volatility windows (late Asia or pre-news lulls). Independent colors per block let you visually encode priority or your trading plan (for example, richer tones in high-probability windows).
Thanks to its modular design, customization is straightforward: adjust colors, toggle blocks, change hours, and tweak the range-reset resolution to suit your routine. As a natural extension, you can add alerts for sub-session high/low breakouts or labels that display the range height (in pips) at session close. While no indicator replaces trader judgment or constitutes financial advice, this tool offers a robust visual foundation for incorporating the time factor directly into your decision-making, helping you contextualize price action within the rhythm of global trading sessions.
Intraday vs Overnight OBV🔍 Purpose
This indicator provides a volume-weighted cumulative flow model that mimics On-Balance Volume (OBV) logic but splits the volume impact into intraday vs. overnight sessions. It allows traders to track how volume contributes to price movement in each session and identify whether buying/selling pressure is stronger during or outside of regular trading hours.
This indicator attempts to alleviate some of the downfalls of the standard OBV indicator, which only looks at total volume and total direction. The price of stocks generally behaves extremely differently during market hours and outside market hours, and many of the large moves happen outside of regular market hours on low volume.
⚙️ Core Features
1) OBV-style calculation:
If price increases → volume is added to the OBV stream.
If price decreases → volume is subtracted.
If price is flat → OBV remains unchanged.
2) Session splitting:
Intraday session: movement from today's open to close.
Overnight session: movement from yesterday’s close to today’s open.
Volume is split proportionally between these two periods based on user input.
3) Four visualization modes:
"Intraday" — plots only OBV from intraday price movement.
"Overnight" — plots only OBV from overnight price movement.
"Aggregate" — plots the sum of intraday and overnight OBV for a holistic view.
"Both Intraday and Overnight" — plots intraday and overnight OBV separately on the same chart.
📐 Inputs
1) Synthetic OBV Type:
"Intraday" — Show OBV from open to close only.
"Overnight" — Show OBV from prior close to today's open only.
"Aggregate" — Show a single line combining both.
"Both Intraday and Overnight" — Show both lines on the same chart.
2) Estimated Overnight Volume %:
Percentage of total daily volume assumed to occur during extended hours.
The rest is allocated to regular session (intraday).
Default: 20% overnight, 80% intraday.
🧮 How It Works
Volume Splitting:
Total bar volume is split into overnight Volume and intraday Volume:
Intraday change is the difference between today’s close and open.
Overnight change is the difference between today’s open and yesterday’s close.
Session OBV Calculations:
OBV is incremented/decremented by the session's allocated volume, depending on whether the session’s price change was positive or negative.
Aggregate OBV:
Combines both session deltas for a holistic volume flow view.
📊 Interpretation
Rising OBV (any stream) suggests accumulation; falling OBV suggests distribution.
Divergences between price and OBV lines (especially overnight vs. intraday) can reveal where hidden buying/selling is occurring.
Comparing intraday vs overnight OBV can help:
Spot whether institutional demand is building off-hours.
Detect retail vs. institutional behavior (retail trades often dominate intraday; institutional may prefer after-hours).
💡 Use Cases
Identify whether overnight gaps are supported by overnight volume momentum.
Detect accumulation in low-volume overnight sessions.
Compare intraday and overnight strength during earnings season or news events.
Complement traditional OBV by seeing session-based breakdowns.
OpeningRange (Trading_Tix)Purpose:
The indicator highlights the high, low, and middle (50%) price levels of a specified session's opening range. These levels can serve as key support and resistance zones for trading strategies. The indicator also offers options to extend these levels beyond the session into later timeframes, making it useful for tracking breakout or trend continuation setups.
Key Features:
1. Session Detection:
The indicator identifies a specific session period using the user-defined Session Time. It calculates the start time, high, and low prices during this period:
rangeTime: Defines the session time range (default: 5:00 PM to 2:59 AM).
extendTime: Defines the extended time range where lines/backgrounds can be prolonged.
2. Opening Range Calculation:
High (high_val) and Low (low_val)**:
Tracks the highest and lowest prices during the session.
Middle Line:
A midpoint is calculated by averaging high_val and low_val.
3. Visual Elements:
Horizontal Lines:
Drawn at the high, low, and middle levels.
Customizable in width and color.
Shaded Background Box:
Covers the range between high and low prices.
The box’s color and transparency can be adjusted.
Line and Box Extension:
Optionally extends these elements into the extended time range.
4. Customization:
Users have the flexibility to:
Toggle visibility of lines, middle line, and background box.
Adjust colors, line thickness, and style.
Enable or disable the extension of lines and backgrounds into the extended period.
How It Works:
Initialization:
The script initializes variables to store range data (startTime, high_val, low_val) and drawing objects (lines, boxes).
It detects whether the current bar falls within the session (inSession) or extended timeframe (inExtend).
Plotting:
During the session:
Deletes previous lines and boxes from prior sessions.
Draws new lines at the high, low, and middle levels.
Creates a background box covering the range, if enabled.
During the extended period:
Extends the session lines and box, if the user has opted for extensions.
Updates:
Continuously adjusts the high/low values and updates the lines as new price data arrives.
Use Cases:
This indicator can be valuable for traders who:
Use the opening range to identify potential breakout zones.
Trade based on price consolidation within the range.
Want a visual representation of key price levels to plan entries and exits.
Would you like help refining this script further or adjusting its settings to match your trading style?
chrono_utilsLibrary "chrono_utils"
Collection of objects and common functions that are related to datetime windows session days and time
ranges. The main purpose of this library is to handle time-related functionality and make it easy to reason about a
future bar and see if it is part of a predefined user session and/or inside a datetime window. All existing session
functions I found in the documentation e.g. "not na(time(timeframe, session, timezone))" are not suitable for
strategies, since the execution of the orders is delayed by one bar due to the execution happening at the bar close.
So a prediction for the next bar is necessary. Moreover, a history operator with a negative value is not allowed e.g.
`not na(time(timeframe, session, timezone) )` expression is not valid. Thus, I created this library to overcome
this small but very important limitation. In the meantime, I added useful functionality to handle session-based
behavior. An interesting utility that emerged from this development is data anomaly detection where a comparison
between the prediction and the actual value is happening. If those two values are different then a data inconsistency
happens between the prediction bar and the actual bar (probably due to a holiday or half session day etc..)
exTimezone(timezone)
exTimezone - Convert extended timezone to timezone string
Parameters:
timezone (simple string) : - The timezone or a special string
Returns: string representing the timezone
nameOfDay(day)
nameOfDay - Convert the day id into a short nameOfDay
Parameters:
day (int) : - The day id to convert
Returns: - The short name of the day
today()
today - Get the day id of this day
Returns: - The day id
nthDayAfter(day, n)
nthDayAfter - Get the day id of n days after the given day
Parameters:
day (int) : - The day id of the reference day
n (int) : - The number of days to go forward
Returns: - The day id of the day that is n days after the reference day
nextDayAfter(day)
nextDayAfter - Get the day id of next day after the given day
Parameters:
day (int) : - The day id of the reference day
Returns: - The day id of the next day after the reference day
nthDayBefore(day, n)
nthDayBefore - Get the day id of n days before the given day
Parameters:
day (int) : - The day id of the reference day
n (int) : - The number of days to go forward
Returns: - The day id of the day that is n days before the reference day
prevDayBefore(day)
prevDayBefore - Get the day id of previous day before the given day
Parameters:
day (int) : - The day id of the reference day
Returns: - The day id of the previous day before the reference day
tomorrow()
tomorrow - Get the day id of the next day
Returns: - The next day day id
normalize(num, min, max)
normalizeHour - Check if number is inthe range of
Parameters:
num (int)
min (int)
max (int)
Returns: - The normalized number
normalizeHour(hourInDay)
normalizeHour - Check if hour is valid and return a noralized hour range from
Parameters:
hourInDay (int)
Returns: - The normalized hour
normalizeMinute(minuteInHour)
normalizeMinute - Check if minute is valid and return a noralized minute from
Parameters:
minuteInHour (int)
Returns: - The normalized minute
monthInMilliseconds(mon)
monthInMilliseconds - Calculate the miliseconds in one bar of the timeframe
Parameters:
mon (int) : - The month of reference to get the miliseconds
Returns: - The number of milliseconds of the month
barInMilliseconds()
barInMilliseconds - Calculate the miliseconds in one bar of the timeframe
Returns: - The number of milliseconds in one bar
method init(this, fromDateTime, toDateTime)
init - Initialize the time window object from boolean values of each session day
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object that will hold the from and to datetimes
fromDateTime (int) : - The starting datetime of the time window
toDateTime (int) : - The ending datetime of the time window
Returns: - The time window object
method init(this, refTimezone, chTimezone, fromDateTime, toDateTime)
init - Initialize the time window object from boolean values of each session day
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object that will hold the from and to datetimes
refTimezone (simple string) : - The timezone of reference of the 'from' and 'to' dates
chTimezone (simple string) : - The target timezone to convert the 'from' and 'to' dates
fromDateTime (int) : - The starting datetime of the time window
toDateTime (int) : - The ending datetime of the time window
Returns: - The time window object
method init(this, sun, mon, tue, wed, thu, fri, sat)
init - Initialize the session days object from boolean values of each session day
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object that will hold the day selection
sun (bool) : - Is Sunday a trading day?
mon (bool) : - Is Monday a trading day?
tue (bool) : - Is Tuesday a trading day?
wed (bool) : - Is Wednesday a trading day?
thu (bool) : - Is Thursday a trading day?
fri (bool) : - Is Friday a trading day?
sat (bool) : - Is Saturday a trading day?
Returns: - The session days objectfrom_chart
method init(this, unixTime)
init - Initialize the object from the hour and minute of the session time in exchange timezone (syminfo.timezone)
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
unixTime (int) : - The unix time
Returns: - The session time object
method init(this, hourInDay, minuteInHour)
init - Initialize the object from the hour and minute of the session time in exchange timezone (syminfo.timezone)
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
hourInDay (int) : - The hour of the time
minuteInHour (int) : - The minute of the time
Returns: - The session time object
method init(this, hourInDay, minuteInHour, refTimezone)
init - Initialize the object from the hour and minute of the session time
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
hourInDay (int) : - The hour of the time
minuteInHour (int) : - The minute of the time
refTimezone (string) : - The timezone of reference of the 'hour' and 'minute'
Returns: - The session time object
method init(this, startTime, endTime)
init - Initialize the object from the start and end session time in exchange timezone (syminfo.timezone)
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
startTime (SessionTime) : - The time the session begins
endTime (SessionTime) : - The time the session ends
Returns: - The session time range object
method init(this, startTimeHour, startTimeMinute, endTimeHour, endTimeMinute, refTimezone)
init - Initialize the object from the start and end session time
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
startTimeHour (int) : - The time hour the session begins
startTimeMinute (int) : - The time minute the session begins
endTimeHour (int) : - The time hour the session ends
endTimeMinute (int) : - The time minute the session ends
refTimezone (string)
Returns: - The session time range object
method init(this, days, timeRanges)
init - Initialize the user session object from session days and time range
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object that will hold the day and the time range selection
days (SessionDays) : - The session days object that defines the days the session is happening
timeRanges (SessionTimeRange ) : - The array of all the session time ranges during a session day
Returns: - The user session object
method to_string(this)
to_string - Formats the time window into a human-readable string
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - The string of the time window
method to_string(this)
to_string - Formats the session days into a human-readable string with short day names
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
Returns: - The string of the session day short names
method to_string(this)
to_string - Formats the session time into a human-readable string
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The string of the session time
method to_string(this)
to_string - Formats the session time into a human-readable string
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The string of the session time
method to_string(this)
to_string - Formats the user session into a human-readable string
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object with the day and the time range selection
Returns: - The string of the user session
method to_string(this)
to_string - Formats the bar into a human-readable string
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
Returns: - The string of the bar times
method to_string(this)
to_string - Formats the chart session into a human-readable string
Namespace types: ChartSession
Parameters:
this (ChartSession) : - The chart session object that contains the days and the time range shown in the chart
Returns: - The string of the chart session
method get_size_in_secs(this)
get_size_in_secs - Count the seconds from start to end in the given timeframe
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - The number of seconds inside the time widow for the given timeframe
method get_size_in_secs(this)
get_size_in_secs - Calculate the seconds inside the session
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The number of seconds inside the session
method get_size_in_bars(this)
get_size_in_bars - Count the bars from start to end in the given timeframe
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - The number of bars inside the time widow for the given timeframe
method get_size_in_bars(this)
get_size_in_bars - Calculate the bars inside the session
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The number of bars inside the session for the given timeframe
method from_chart(this)
from_chart - Initialize the session days object from the chart
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object that will hold the day selection
Returns: - The user session object
method from_chart(this)
from_chart - Initialize the session time range object from the chart
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
Returns: - The session time range object
method from_chart(this)
from_chart - Initialize the session object from the chart
Namespace types: ChartSession
Parameters:
this (ChartSession) : - The chart session object that will hold the days and the time range shown in the chart
Returns: - The chart session object
method to_sess_string(this)
to_sess_string - Formats the session days into a session string with day ids
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object
Returns: - The string of the session day ids
method to_sess_string(this)
to_sess_string - Formats the session time into a session string
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The string of the session time
method to_sess_string(this)
to_sess_string - Formats the session time into a session string
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The string of the session time
method to_sess_string(this)
to_sess_string - Formats the user session into a session string
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object with the day and the time range selection
Returns: - The string of the user session
method to_sess_string(this)
to_sess_string - Formats the chart session into a session string
Namespace types: ChartSession
Parameters:
this (ChartSession) : - The chart session object that contains the days and the time range shown in the chart
Returns: - The string of the chart session
method from_sess_string(this, sess)
from_sess_string - Initialize the session days object from the session string
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object that will hold the day selection
sess (string) : - The session string part that represents the days
Returns: - The session days object
method from_sess_string(this, sess)
from_sess_string - Initialize the session time object from the session string in exchange timezone (syminfo.timezone)
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object that will hold the hour and minute of the time
sess (string) : - The session string part that represents the time HHmm
Returns: - The session time object
method from_sess_string(this, sess, refTimezone)
from_sess_string - Initialize the session time object from the session string
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object that will hold the hour and minute of the time
sess (string) : - The session string part that represents the time HHmm
refTimezone (simple string) : - The timezone of reference of the 'hour' and 'minute'
Returns: - The session time object
method from_sess_string(this, sess)
from_sess_string - Initialize the session time range object from the session string in exchange timezone (syminfo.timezone)
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
sess (string) : - The session string part that represents the time range HHmm-HHmm
Returns: - The session time range object
method from_sess_string(this, sess, refTimezone)
from_sess_string - Initialize the session time range object from the session string
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
sess (string) : - The session string part that represents the time range HHmm-HHmm
refTimezone (simple string) : - The timezone of reference of the time ranges
Returns: - The session time range object
method from_sess_string(this, sess)
from_sess_string - Initialize the user session object from the session string in exchange timezone (syminfo.timezone)
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object that will hold the day and the time range selection
sess (string) : - The session string that represents the user session HHmm-HHmm,HHmm-HHmm:ddddddd
Returns: - The session time range object
method from_sess_string(this, sess, refTimezone)
from_sess_string - Initialize the user session object from the session string
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object that will hold the day and the time range selection
sess (string) : - The session string that represents the user session HHmm-HHmm,HHmm-HHmm:ddddddd
refTimezone (simple string) : - The timezone of reference of the time ranges
Returns: - The session time range object
method nth_day_after(this, day, n)
nth_day_after - The nth day after the given day that is a session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
day (int) : - The day id of the reference day
n (int) : - The number of days after
Returns: - The day id of the nth session day of the week after the given day
method nth_day_before(this, day, n)
nth_day_before - The nth day before the given day that is a session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
day (int) : - The day id of the reference day
n (int) : - The number of days after
Returns: - The day id of the nth session day of the week before the given day
method next_day(this)
next_day - The next day that is a session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
Returns: - The day id of the next session day of the week
method previous_day(this)
previous_day - The previous day that is session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
Returns: - The day id of the previous session day of the week
method get_sec_in_day(this)
get_sec_in_day - Count the seconds since the start of the day this session time represents
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The number of seconds passed from the start of the day until that session time
method get_ms_in_day(this)
get_ms_in_day - Count the milliseconds since the start of the day this session time represents
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The number of milliseconds passed from the start of the day until that session time
method eq(this, other)
eq - Compare two bars
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
other (Bar) : - The bar object to compare with
Returns: - Whether this bar is equal to the other one
method get_open_time(this)
get_open_time - The open time object
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
Returns: - The open time object
method get_close_time(this)
get_close_time - The close time object
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
Returns: - The close time object
method get_time_range(this)
get_time_range - Get the time range of the bar
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
Returns: - The time range that the bar is in
getBarNow()
getBarNow - Get the current bar object with time and time_close timestamps
Returns: - The current bar
getFixedBarNow()
getFixedBarNow - Get the current bar with fixed width defined by the timeframe. Note: There are case like SPX 15min timeframe where the last session bar is only 10min. This will return a bar of 15 minutes
Returns: - The current bar
method is_in_window(this, win)
is_in_window - Check if the given bar is between the start and end dates of the window
Namespace types: Bar
Parameters:
this (Bar) : - The bar to check if it is between the from and to datetimes of the window
win (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - Whether the current bar is inside the datetime window
method is_in_timerange(this, rng)
is_in_timerange - Check if the given bar is inside the session time range
Namespace types: Bar
Parameters:
this (Bar) : - The bar to check if it is between the from and to datetimes
rng (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - Whether the bar is inside the session time range and if this part of the next trading day
method is_in_days(this, days)
is_in_days - Check if the given bar is inside the session days
Namespace types: Bar
Parameters:
this (Bar) : - The bar to check if its day is a trading day
days (SessionDays) : - The session days object with the day selection
Returns: - Whether the current bar day is inside the session
method is_in_session(this, sess)
is_in_session - Check if the given bar is inside the session as defined by the input params (what "not na(time(timeframe.period, this.to_sess_string()) )" should return if you could write it
Namespace types: Bar
Parameters:
this (Bar) : - The bar to check if it is between the from and to datetimes
sess (UserSession) : - The user-defined session object with the day and the time range selection
Returns: - Whether the current time is inside the session
method next_bar(this, offsetBars)
next_bar - Predicts the next bars open and close time based on the charts session
Namespace types: ChartSession
Parameters:
this (ChartSession) : - The chart session object that contains the days and the time range shown in the chart
offsetBars (simple int) : - The number of bars forward
Returns: - Whether the current time is inside the session
DateTimeWindow
DateTimeWindow - Object that represents a datetime window with a beginning and an end
Fields:
fromDateTime (series int) : - The beginning of the datetime window
toDateTime (series int) : - The end of the datetime window
SessionDays
SessionDays - Object that represent the trading days of the week
Fields:
days (map) : - The map that contains all days of the week and their session flag
SessionTime
SessionTime - Object that represents the time (hour and minutes)
Fields:
hourInDay (series int) : - The hour of the day that ranges from 0 to 24
minuteInHour (series int) : - The minute of the hour that ranges from 0 to 59
minuteInDay (series int) : - The minute of the day that ranges from 0 to 1440. They will be calculated based on hourInDay and minuteInHour when method is called
SessionTimeRange
SessionTimeRange - Object that represents a range that extends from the start to the end time
Fields:
startTime (SessionTime) : - The beginning of the time range
endTime (SessionTime) : - The end of the time range
isOvernight (series bool) : - Whether or not this is an overnight time range
UserSession
UserSession - Object that represents a user-defined session
Fields:
days (SessionDays) : - The map of the user-defined trading days
timeRanges (SessionTimeRange ) : - The array with all time ranges of the user-defined session during the trading days
Bar
Bar - Object that represents the bars' open and close times
Fields:
openUnixTime (series int) : - The open time of the bar
closeUnixTime (series int) : - The close time of the bar
chartDayOfWeek (series int)
ChartSession
ChartSession - Object that represents the default session that is shown in the chart
Fields:
days (SessionDays) : - A map with the trading days shown in the chart
timeRange (SessionTimeRange) : - The time range of the session during a trading day
isFinalized (series bool)
time_filtersLibrary "time_filters"
Collection of filters that related with time like sessions and datetime ranges.
All existing session functions I found in the documentation e.g. not na(time(timeframe.period, sessionTimes))
are not suitable for strategies, since the execution of the entries and the exits are delayed by one bar.
Thus I created this library to overcome this small but very important limitation.
is_in_date_range(fromDate, toDate, srcTimezone, dstTimezone, t)
is_in_date_range - Check if the given time is between the start and end dates
Parameters:
fromDate : - The start date in UNIX time of the valid range
toDate : - The end date in UNIX time of the valid range
srcTimezone : - The timezone of reference for the 'from' and 'to' dates
dstTimezone : - The target timezone to convert the 'from' and 'to' dates
t : - The time to compare in UNIX format
Returns: series of bool whether or not the time is inside the valid range
is_in_session(startTime, endTime, days, srcTimezone, dstTimezone, t)
is_in_session - Check if the given time is inside the session as defined by the input params
Parameters:
startTime : - The sessionTime object with the use flag and the start time
endTime : - The sessionTime object with the use flag and the end time
days : - The sessionDays object with the use flag and marks for each day of the session
srcTimezone : - The timezone of reference for the time ranges
dstTimezone : - The target timezone to convert the time ranges
t : - The current time to compare in UNIX format.
Returns: series of bool whether or not the time is inside the session
sessionTime
Fields:
hourInDay
minuteInHour
sessionDays
Fields:
mon
tue
wed
thu
fri
sat
sun
Institutional Confluence Mapper [JOAT]Institutional Confluence Mapper (ICM)
Introduction
The Institutional Confluence Mapper is an open-source multi-factor analysis tool that combines five analytical modules into a unified confluence scoring system. It synthesizes institutional trading concepts including Relative Rotation analysis, Smart Money flow detection, Liquidity zone mapping, Session-based timing, and Volatility regime classification.
Rather than relying on a single indicator, ICM evaluates market conditions through multiple lenses simultaneously, presenting a clear confluence score (0-100%) that reflects the alignment of various market factors.
This script is fully open-source under the Mozilla Public License 2.0.
Originality and Purpose
This indicator is NOT a random mashup of existing indicators. It is an original implementation that creates a unified institutional analysis framework:
Why Multiple Modules? Most retail traders struggle because they rely on single indicators that provide conflicting signals. Institutional traders evaluate markets through multiple frameworks simultaneously. ICM bridges this gap by providing a unified view of complementary analysis methods.
The Confluence Scoring System: Each module contributes to a weighted confluence score (0-100%). Scores above 65% indicate bullish confluence; below 35% indicates bearish confluence.
How Components Work Together:
RRG (Relative Rotation) determines macro bias - is this asset outperforming or underperforming its benchmark?
Institutional Flow confirms smart money activity - are institutions accumulating or distributing?
Volatility Regime determines strategy selection - trend-follow or mean-revert?
Liquidity Detection identifies key levels - where are the stop hunts happening?
Session Analysis optimizes timing - when should you trade?
The Five Core Modules
1. Relative Rotation Momentum Matrix (RRG)
Compares the current symbol against a benchmark (default: SPY) using the JdK RS-Ratio methodology with double-smoothed EMA. Assets rotate through four quadrants:
LEADING: Outperforming with positive momentum (strongest bullish)
WEAKENING: Outperforming but losing momentum
LAGGING: Underperforming with negative momentum (strongest bearish)
IMPROVING: Underperforming but gaining momentum
2. Institutional Flow Analysis
Analyzes volume patterns to detect smart money activity:
Volume Z-Score measures how unusual current volume is
Buy/Sell pressure estimation based on candle structure
Unusual volume detection highlights institutional activity
3. Volatility Regime System
Uses ATR percentile ranking to classify market conditions:
COMPRESSION: Low volatility (ATR < 20th percentile) - potential breakout
EXPANSION: High volatility (ATR > 80th percentile) - trending
TRENDING_BULL/BEAR: Directional trends based on EMA alignment
RANGING: Sideways consolidation
4. Liquidity Detection
Identifies institutional liquidity targets using swing point analysis:
Swing highs/lows are tracked and displayed as dashed lines
Purple dashed lines mark resistance/sell-side liquidity
Teal dashed lines mark support/buy-side liquidity
Gold diamonds appear when liquidity sweeps are detected (potential reversals)
5. Session Momentum Profiler
Tracks trading sessions based on your selected timezone:
Asian Session: 7PM - 4AM EST
London Session: 3AM - 12PM EST
New York Session: 9:30AM - 4PM EST
London/NY Overlap: 8AM - 12PM EST (peak liquidity)
Visual Elements
Main Dashboard (Top-Right):
BIAS: Overall direction with confluence percentage
RRG: Current quadrant and momentum
FLOW: Smart money bias and volume status
REGIME: Market condition and volatility percentile
SESSION: Active trading session and current time
LIQUIDITY: Active zones and grab signals
SIGNAL: Actionable recommendation
Chart Elements:
Gold Diamond: Liquidity grab (potential reversal point)
Teal Dashed Line: Support / Buy-side liquidity zone
Purple Dashed Line: Resistance / Sell-side liquidity zone
EMA 21/55/200: Trend structure with cloud fill
Volatility Bands: ATR-based channels
How to Use
Step 1: Check the BIAS row for overall market direction
Step 2: Check REGIME to understand market conditions
Step 3: Identify key levels using liquidity zones and EMAs
Step 4: Wait for confluence above 65% (bullish) or below 35% (bearish)
Step 5: Look for gold diamond signals at key levels
Best Setups
Bullish: Confluence >65%, RRG in LEADING/IMPROVING, bullish flow, price near teal support zone.
Bearish: Confluence <35%, RRG in LAGGING/WEAKENING, bearish flow, price near purple resistance zone.
Reversal: Gold diamond appears after price sweeps a liquidity zone.
Key Input Parameters
Benchmark Symbol: Compare against (default: SPY)
RS-Ratio/Momentum Lookback: RRG calculation periods
Volume Analysis Period: Flow detection lookback
Swing Length: Liquidity zone detection
ATR Period/Rank Period: Regime classification
Timezone: Session detection timezone
Alerts
Liquidity Grab Bull: Bullish sweep detected
Liquidity Grab Bear: Bearish sweep detected
High Confluence Bull: Confluence above 70%
High Confluence Bear: Confluence below 30%
Best Practices
Use on 1H, 4H, or Daily timeframes for reliable signals
Combine with price action for confirmation
Respect the regime - don't fight strong trends
Trade during London/NY overlap for best liquidity
Wait for high confluence scores before entering
Always use proper risk management
Limitations
Works best on liquid markets with sufficient volume
Session features optimized for forex/crypto markets
RRG requires a valid benchmark symbol
No indicator predicts the future - use proper risk management
Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results.
-Made with passion by officialjackofalltrades
[ST] Killzones - Minimal Killzones — Minimal
User Manual
1. Purpose of the Indicator
Killzones — Minimal is a session-based market structure tool designed to highlight the highest-liquidity time windows of the trading day.
Instead of generating signals, this indicator provides context by visually marking the ICT Killzones, allowing the trader to:
Identify where liquidity is built
See which session created the range
Anticipate where liquidity is likely to be taken
Align SMC / Wyckoff / Order Flow analysis with time-based institutional behavior
This tool is especially effective for Crypto, Forex, and Indices, where markets run continuously and liquidity cycles matter more than exchange open times.
2. Killzones Covered (São Paulo Time – UTC-3)
The indicator draws one minimal, dotted box per session:
Session Time (SP) Role in Market Structure
ASIA 21:00 – 03:00 Range formation & liquidity buildup
LONDON 04:00 – 07:00 First liquidity raid & manipulation
NEW YORK (Killzone) 10:00 – 13:00 True displacement & delivery
These are ICT Killzones, not official stock exchange open times.
3. Visual Design Philosophy
The indicator is intentionally minimalist:
Dotted borders → no visual clutter
Optional fill → focus on structure, not noise
No signals or arrows → forces contextual reading
One box per session → clean session boundaries
The goal is to let price action and liquidity tell the story, not indicators.
4. How the Boxes Behave
Each session box:
Starts on the first candle of the session
Expands dynamically to include the session High and Low
Stops updating once the session ends
Remains fixed on the chart as historical context
This allows you to instantly see:
Which session created the current range
Where stop-loss clusters are likely resting
Which session was manipulated or delivered price
5. How to Use the Indicator (Practical Workflow)
Step 1 — Identify the Current Session
Ask:
Are we inside Asia, London, or New York?
Your expectations should change depending on the session.
Step 2 — Read Session Intent
ASIA
Expect compression and balance
Focus on identifying Asia High / Asia Low
Avoid aggressive trades inside the range
LONDON
Look for liquidity raids on Asia High/Low
Many London moves are manipulative
A failed raid is often a setup for NY
NEW YORK
Look for true displacement
High probability of:
Continuation
Reversal after a sweep
Best session to execute trades
Step 3 — Trade Liquidity, Not Candles
Use the boxes as liquidity maps, not entries.
High-probability ideas come from:
Asia range being swept during London
London manipulation being reversed during NY
NY taking remaining liquidity and delivering direction
6. Example Use Cases
Setup 1 — Asia Range Sweep
Asia forms a tight range
London sweeps Asia High or Low
Price fails to continue
Market shifts structure
Entry on OB / FVG toward the opposite side
Setup 2 — London Manipulation → NY Delivery
London sweeps liquidity but stalls
New York opens
NY takes the opposite side liquidity
Strong displacement occurs
Entry on NY pullback
Setup 3 — Session Breakout
No sweep
Immediate strong displacement
Clean continuation
Trade only after confirmation
7. What NOT to Do
Do not trade inside the middle of session boxes
Do not assume every sweep means reversal
Do not force trades without structure shift
Do not treat sessions as signals
The indicator shows where to pay attention, not when to click Buy or Sell.
8. Best Confluence Tools
This indicator works best when combined with:
Market Structure (BOS / CHoCH)
Order Blocks
Fair Value Gaps
Liquidity pools
Volume-based candle analysis (e.g. CandleFlow)
9. Final Notes
Killzones — Minimal is a contextual framework, not a strategy.
If you wait for:
Liquidity to be taken
Structure to shift
Price to confirm intent
You will trade with the market narrative, not against it.
Time reveals intent. Liquidity confirms it.
Range Trading StrategyOVERVIEW
The Range Trading Strategy is a systematic trading approach that identifies price ranges
from higher timeframe candles or trading sessions, tracks pivot points, and generates
trading signals when range extremes are mitigated and confirmed by pivot levels.
CORE CONCEPT
The strategy is based on the principle that when a candle (or session) closes within the
range of the previous candle (or session), that previous candle becomes a "range" with
identifiable high and low extremes. When price breaks through these extremes, it creates
trading opportunities that are confirmed by pivot levels.
RANGE DETECTION MODES
1. HTF (Higher Timeframe) Mode:
Automatically selects a higher timeframe based on the current chart timeframe
Uses request.security() to fetch HTF candle data
Range is created when an HTF candle closes within the previous HTF candle's range
The previous HTF candle's high and low become the range extremes
2. Sessions Mode:
- Divides the trading day into 4 sessions (UTC):
* Session 1: 00:00 - 06:00 (6 hours)
* Session 2: 06:00 - 12:00 (6 hours)
* Session 3: 12:00 - 20:00 (8 hours)
* Session 4: 20:00 - 00:00 (4 hours, spans midnight)
- Tracks high, low, and close for each session
- Range is created when a session closes within the previous session's range
- The previous session's high and low become the range extremes
PIVOT DETECTION
Pivots are detected based on candle color changes (bullish/bearish transitions):
1. Pivot Low:
Created when a bullish candle appears after a bearish candle
Pivot low = minimum of the current candle's low and previous candle's low
The pivot bar is the actual bar where the low was formed (current or previous bar)
2. Pivot High:
Created when a bearish candle appears after a bullish candle
Pivot high = maximum of the current candle's high and previous candle's high
The pivot bar is the actual bar where the high was formed (current or previous bar)
IMPORTANT: There is always only ONE active pivot high and ONE active pivot low at any
given time. When a new pivot is created, it replaces the previous one.
RANGE CREATION
A range is created when:
(HTF Mode) An HTF candle closes within the previous HTF candle's range AND a new HTF
candle has just started
(Sessions Mode) A session closes within the previous session's range AND a new session
has just started
Or Range Can Be Created when the Extreme of Another Range Gets Mitigated and We Have a Pivot low Just Above the Range Low or Pivot High just Below the Range High
Range Properties:
rangeHigh: The high extreme of the range
rangeLow: The low extreme of the range
highStartTime: The timestamp when the range high was actually formed (found by looping
backwards through bars)
lowStartTime: The timestamp when the range low was actually formed (found by looping
backwards through bars)
highMitigated / lowMitigated: Flags tracking whether each extreme has been broken
isSpecial: Flag indicating if this is a "special range" (see Special Ranges section)
RANGE MITIGATION
A range extreme is considered "mitigated" when price interacts with it:
High is mitigated when: high >= rangeHigh (any interaction at or above the level)
Low is mitigated when: low <= rangeLow (any interaction at or below the level)
Mitigation can happen:
At the moment of range creation (if price is already beyond the extreme)
At any point after range creation when price touches the extreme
SIGNAL GENERATION
1. Pending Signals:
When a range extreme is mitigated, a pending signal is created:
a) BEARISH Pending Signal:
- Triggered when: rangeHigh is mitigated
- Confirmation Level: Current pivotLow
- Signal is confirmed when: close < pivotLow
- Stop Loss: Current pivotHigh (at time of confirmation)
- Entry: Short position
Signal Confirmation
b) BULLISH Pending Signal:
- Triggered when: rangeLow is mitigated
- Confirmation Level: Current pivotHigh
- Signal is confirmed when: close > pivotHigh
- Stop Loss: Current pivotLow (at time of confirmation)
- Entry: Long position
IMPORTANT: There is only ever ONE pending bearish signal and ONE pending bullish signal
at any given time. When a new pending signal is created, it replaces the previous one
of the same type.
2. Signal Confirmation:
- Bearish: Confirmed when price closes below the pivot low (confirmation level)
- Bullish: Confirmed when price closes above the pivot high (confirmation level)
- Upon confirmation, a trade is entered immediately
- The confirmation line is drawn from the pivot bar to the confirmation bar
TRADE EXECUTION
When a signal is confirmed:
1. Position Management:
- Any existing position in the opposite direction is closed first
- Then the new position is entered
2. Stop Loss:
- Bearish (Short): Stop at pivotHigh
- Bullish (Long): Stop at pivotLow
3. Take Profit:
- Calculated using Risk:Reward Ratio (default 2:1)
- Risk = Distance from entry to stop loss
- Target = Entry ± (Risk × R:R Ratio)
- Can be disabled with "Stop Loss Only" toggle
4. Trade Comments:
- "Range Bear" for short trades
- "Range Bull" for long trades
SPECIAL RANGES
Special ranges are created when:
- A range high is mitigated AND the current pivotHigh is below the range high
- A range low is mitigated AND the current pivotLow is above the range low
In these cases:
- The pivot value is stored in an array (storedPivotHighs or storedPivotLows)
- A "special range" is created with only ONE extreme:
* If pivotHigh < rangeHigh: Creates a range with rangeHigh = pivotLow, rangeLow = na
* If pivotLow > rangeLow: Creates a range with rangeLow = pivotHigh, rangeHigh = na
- Special ranges can generate signals just like normal ranges
- If a special range is mitigated on the creation bar or the next bar, it is removed
entirely without generating signals (prevents false signals)
Special Ranges
REVERSE ON STOP LOSS
When enabled, if a stop loss is hit, the strategy automatically opens a trade in the
opposite direction:
1. Long Stop Loss Hit:
- Detects when: position_size > 0 AND position_size <= 0 AND low <= longStopLoss
- Action: Opens a SHORT position
- Stop Loss: Current pivotHigh
- Trade Comment: "Reverse on Stop"
2. Short Stop Loss Hit:
- Detects when: position_size < 0 AND position_size >= 0 AND high >= shortStopLoss
- Action: Opens a LONG position
- Stop Loss: Current pivotLow
- Trade Comment: "Reverse on Stop"
The reverse trade uses the same R:R ratio and respects the "Stop Loss Only" setting.
VISUAL ELEMENTS
1. Range Lines:
- Drawn from the time when the extreme was formed to the mitigation point (or current
time if not mitigated)
- High lines: Blue (or mitigated color if mitigated)
- Low lines: Red (or mitigated color if mitigated)
- Style: SOLID
- Width: 1
2. Confirmation Lines:
- Drawn when a signal is confirmed
- Extends from the pivot bar to the confirmation bar
- Bearish: Red, solid line
- Bullish: Green, solid line
- Width: 1
- Can be toggled on/off
STRATEGY SETTINGS
1. Range Detection Mode:
- HTF: Uses higher timeframe candles
- Sessions: Uses trading session boundaries
2. Auto HTF:
- Automatically selects HTF based on current chart timeframe
- Can be disabled to use manual HTF selection
3. Risk:Reward Ratio:
- Default: 2.0 (2:1)
- Minimum: 0.5
- Step: 0.5
4. Stop Loss Only:
- When enabled: Trades only have stop loss (no take profit)
- Trades close on stop loss or when opposite signal confirms
5. Reverse on Stop Loss:
- When enabled: Hitting a stop loss opens opposite trade with stop at opposing pivot
6. Max Ranges to Display:
- Limits the number of ranges kept in memory
- Oldest ranges are purged when limit is exceeded
KEY FEATURES
1. Dynamic Pivot Tracking:
- Pivots update on every candle color change
- Always maintains one high and one low pivot
2. Range Lifecycle:
- Ranges are created when price closes within previous range
- Ranges are tracked until mitigated
- Mitigation creates pending signals
- Signals are confirmed by pivot levels
3. Signal Priority:
- Only one pending signal of each type at a time
- New signals replace old ones
- Confirmation happens on close of bar
4. Position Management:
- Closes opposite positions before entering new trades
- Tracks stop loss levels for reverse functionality
- Respects pyramiding = 1 (only one position per direction)
5. Time-Based Drawing:
- Uses time coordinates instead of bar indices for line drawing
- Prevents "too far from current bar" errors
- Lines can extend to any historical point
USAGE NOTES
- Best suited for trending and ranging markets
- Works on any timeframe, but HTF mode adapts automatically
- Sessions mode is ideal for intraday trading
- Pivot detection requires clear candle color changes
- Range detection requires price to close within previous range
- Signals are generated on bar close, not intra-bar
The strategy combines range identification, pivot tracking, and signal confirmation to
create a systematic approach to trading breakouts and reversals based on price structure, past performance does not in any way predict future performance
EMA20 Cross Strategy with countertrades and signalsEMA20 Cross Strategy Documentation
Overview
The EMA20 Cross Strategy with Counter-Trades and Instant Signals is a Pine Script (version 6) trading strategy designed for the TradingView platform. It implements an Exponential Moving Average (EMA) crossover system to generate buy and sell signals, with optional trend filtering, session-based trading, instant signal processing, and visual/statistical feedback. The strategy supports counter-trades (closing opposing positions before entering new ones) and operates with a fixed trade size in EUR.
Features
EMA Crossover Mechanism:
Uses a short-term EMA (configurable length, default: 1) and a long-term EMA (default: 20) to detect crossovers.
A buy signal is generated when the short EMA crosses above the long EMA.
A sell signal is generated when the short EMA crosses below the long EMA.
Instant Signals:
If enabled (useInstantSignals), signals are based on the current price crossing the short EMA, rather than waiting for the candle close.
This allows faster trade execution but may increase sensitivity to price fluctuations.
Trend Filter:
Optionally filters trades based on the trend direction (useTrendFilter).
Long trades are allowed only when the short EMA (or price, for instant signals) is above the long EMA.
Short trades are allowed only when the short EMA (or price) is below the long EMA.
Session Filter:
Restricts trading to specific market hours (sessionStart, default: 09:00–17:00) if enabled (useSessionFilter).
Ensures trades occur only during active market sessions, reducing exposure to low-liquidity periods.
Customizable Timeframe:
The EMA calculations can use a higher timeframe (e.g., 5m, 15m, 1H, 4H, 1D, default: 1H) via request.security.
This allows the strategy to base signals on longer-term trends while operating on a shorter-term chart.
Trade Management:
Fixed trade size of €100,000 per trade (tradeAmount), with a maximum quantity cap (maxQty = 10,000) to prevent oversized trades.
Counter-trades: Closes short positions before entering a long position and vice versa.
Trades are executed with a minimum quantity of 1 to ensure valid orders.
Visualization:
EMA Lines: The short EMA is colored based on the last signal (green for buy, red for sell, gray for neutral), and the long EMA is orange.
Signal Markers: Displays buy/sell signals as arrows (triangles) above/below candles if enabled (showSignalShapes).
Background/Candle Coloring: Optionally colors the chart background or candles green (bullish) or red (bearish) based on the trend (useColoredBars).
Statistics Display:
If enabled (useStats), a label on the chart shows:
Total closed trades
Open trades
Win rate (%)
Number of winning/losing trades
Profit factor (gross profit / gross loss)
Net profit
Maximum drawdown
Configuration Inputs
EMA Short Length (emaLength): Length of the short-term EMA (default: 1).
Trend EMA Length (trendLength): Length of the long-term EMA (default: 20).
Enable Trend Filter (useTrendFilter): Toggles trend-based filtering (default: true).
Color Candles (useColoredBars): Colors candles instead of the background (default: true).
Enable Session Filter (useSessionFilter): Restricts trading to specified hours (default: false).
Trading Session (sessionStart): Defines trading hours (default: 09:00–17:00).
Show Statistics (useStats): Displays performance stats on the chart (default: true).
Show Signal Arrows (showSignalShapes): Displays buy/sell signals as arrows (default: true).
Use Instant Signals (useInstantSignals): Generates signals based on live price action (default: false).
EMA Timeframe (emaTimeframe): Timeframe for EMA calculations (options: 5m, 15m, 1H, 4H, 1D; default: 1H).
Strategy Logic
Signal Generation:
Standard Mode: Signals are based on EMA crossovers (short EMA crossing long EMA) at candle close.
Instant Mode: Signals are based on the current price crossing the short EMA, enabling faster reactions.
Trade Execution:
On a buy signal, closes any short position and opens a long position.
On a sell signal, closes any long position and opens a short position.
Position size is calculated as the minimum of €100,000 or available equity, divided by the current price, capped at 10,000 units.
Filters:
Trend Filter: Ensures trades align with the trend direction (if enabled).
Session Filter: Restricts trades to user-defined market hours (if enabled).
Visual Feedback
EMA Lines: Provide a clear view of the short and long EMAs, with the short EMA’s color reflecting the latest signal.
Signal Arrows: Large green triangles (buy) below candles or red triangles (sell) above candles for easy signal identification.
Chart Coloring: Highlights bullish (green) or bearish (red) trends via background or candle colors.
Statistics Label: Displays key performance metrics in a label above the chart for quick reference.
Usage Notes
Initial Capital: €100,000 (configurable via initial_capital).
Currency: EUR (set via currency).
Order Processing: Orders are processed at candle close (process_orders_on_close=true) unless instant signals are enabled.
Dynamic Requests: Allows dynamic timeframe adjustments for EMA calculations (dynamic_requests=true).
Platform: Designed for TradingView, compatible with any market supported by the platform (e.g., stocks, forex, crypto).
Example Use Case
Scenario: Trading on a 5-minute chart with a 1-hour EMA timeframe, trend filter enabled, and session filter set to 09:00–17:00.
Behavior: The strategy will:
Calculate EMAs on the 1-hour timeframe.
Generate buy signals when the short EMA crosses above the long EMA (and price is above the long EMA).
Generate sell signals when the short EMA crosses below the long EMA (and price is below the long EMA).
Execute trades only during 09:00–17:00.
Display green/red candles and performance stats on the chart.
Limitations
Instant Signals: May lead to more frequent signals, increasing the risk of false positives in volatile markets.
Fixed Trade Size: Does not adjust dynamically based on market conditions beyond equity and max quantity limits.
Session Filter: Simplified and may not account for complex session rules or holidays.
Statistics: Displayed on-chart, which may clutter the view in smaller charts.
Customization
Adjust emaLength and trendLength to suit different market conditions (e.g., shorter for scalping, longer for swing trading).
Toggle useInstantSignals for faster or more stable signal generation.
Modify sessionStart to align with specific market hours.
Disable useStats or showSignalShapes for a cleaner chart.
This strategy is versatile for both manual and automated trading, offering flexibility for various markets and trading styles while providing clear visual and statistical feedback.
True Open CalculationsIndicator Description: True Open Calculations
This custom Pine Script indicator calculates and plots key "True Open" levels based on specific time intervals and trading sessions. The True Open levels represent significant price points on the chart, helping traders identify key reference points tied to various market opening times. These levels are important for understanding price action in relation to market sessions and trading cycles. The indicator is designed to plot lines corresponding to different "True Opens" on the chart and display labels with the associated information.
Key Features:
True Year Open:
This represents the opening price on the first Monday of April each year. It serves as a reference point for the yearly price level.
Plot Color: Green.
True Month Open:
This represents the opening price on the second Monday of each month. It helps in identifying monthly trends and provides a key reference for monthly price movements.
Plot Color: Blue.
True Week Open:
This represents the opening price every Monday at 6:00 PM. It gives traders a level to track weekly opening movements and can be useful for weekly trend analysis.
Plot Color: Orange.
True Day Open:
This represents the opening price at 12:00 AM (midnight) each day. It serves as a daily benchmark for price action at the start of the trading day.
Plot Color: Red.
True New York Session Open:
This represents the opening price at 7:30 AM (New York session start time). This level is crucial for traders focused on the New York trading session.
Plot Color: Purple.
Additional Features:
Labels: The indicator displays labels to the right of each plotted line to describe which "True Open" it represents (e.g., "True Year Open," "True Month Open," etc.).
Dynamic Plotting: The lines are only plotted on the current candle, and the lines are dynamically updated for each time period based on the corresponding "True Open."
Visual Cues: The colors of the plotted lines (green, blue, orange, red, purple) help quickly distinguish between different "True Open" levels, making it easy for traders to track price action and make informed decisions.
Use Cases:
Yearly, Monthly, Weekly, Daily, and Session Benchmarking: This indicator provides traders with important price levels to use as benchmarks for the current year, month, week, and day, helping to identify trends and potential reversals.
Session Awareness: It is particularly useful for traders who want to track key market sessions, such as the New York session, and their impact on price movement.
Long-term Analysis: By including the yearly open, this indicator helps traders gain a broader perspective on market trends and provides context for analyzing shorter-term price movements.
Benefits:
Helps identify important reference points for longer-term trends (yearly, monthly) as well as shorter-term moves (daily, weekly, and session).
Visually intuitive with color-coded lines and labels, allowing quick and easy identification of key market open levels.
Dynamic and real-time: The indicator plots and updates the True Open levels dynamically as the market progresses.
Number of Bars CheatSheetA regular trading day on the New York Stock Exchange (NYSE) consists of two main sessions: the Opening Auction and the Closing Auction, separated by a continuous trading session. Here's a breakdown of the trading day:
1. **Pre-Opening Session**: This session starts at 4:00 AM Eastern Time (ET) and lasts until 9:30 AM ET. During this time, there is limited trading activity, and orders can be entered and canceled. However, most of the trading activity doesn't occur until the regular trading session begins.
2. **Regular Trading Session**: The regular trading session on the NYSE starts at 9:30 AM ET and lasts until 4:00 PM ET. This is the primary trading session where the majority of price bars are formed.
3. **Closing Auction**: After the regular trading session ends at 4:00 PM ET, there is a closing auction period that typically lasts until 4:10 PM ET. During this time, there is a final price discovery process where orders are matched to determine the closing price for each security.
So, during the regular trading session, which is the main focus for most traders and investors, there are a total of 6.5 hours of trading. Trading occurs continuously during this time, with price bars being formed based on the time frame you're looking at. The most common time frames for price bars are one minute, five minutes, 15 minutes, 30 minutes, and one hour, among others. Therefore, the number of price bars in a regular trading day on the NYSE will depend on the time frame you are using for your analysis. For example, if you are using one-minute bars, there will be 6.5 x 60 = 390 price bars in a regular trading day.
NYCSessionLibrary "NYCSession"
Library for New York trading session time functions
@author abneralvarado
@version 1.0
isInNYSession(sessionStart, sessionEnd)
Determines if the current bar is within New York trading session
Parameters:
sessionStart (simple int) : Starting time of NY session in 24hr format (HHMM) like 0930 for 9:30 AM ET
sessionEnd (simple int) : Ending time of NY session in 24hr format (HHMM) like 1600 for 4:00 PM ET
Returns: True if current bar is within the NY session time, false otherwise
getNYSessionStartTime(lookback, sessionStart)
Gets the start time of NY session for a given bar
Parameters:
lookback (simple int) : Bar index to check (0 is current bar)
sessionStart (simple int) : Starting time of NY session in 24hr format (HHMM)
Returns: Unix timestamp for the start of NY session on the given bar's date
getNYSessionEndTime(lookback, sessionEnd)
Gets the end time of NY session for a given bar
Parameters:
lookback (simple int) : Bar index to check (0 is current bar)
sessionEnd (simple int) : Ending time of NY session in 24hr format (HHMM)
Returns: Unix timestamp for the end of NY session on the given bar's date
isNYSessionOpen(sessionStart)
Checks if current bar opens the NY session
Parameters:
sessionStart (simple int) : Starting time of NY session in 24hr format (HHMM)
Returns: True if current bar marks the session opening, false otherwise
isNYSessionClose(sessionEnd)
Checks if current bar closes the NY session
Parameters:
sessionEnd (simple int) : Ending time of NY session in 24hr format (HHMM)
Returns: True if current bar marks the session closing, false otherwise
isWeekday()
Determines if the current day is a weekday (Mon-Fri)
Returns: True if current bar is on a weekday, false otherwise
getSessionBackgroundColor(sessionStart, sessionEnd, bgColor)
Gets session background color with transparency
Parameters:
sessionStart (simple int) : Starting time of NY session in 24hr format (HHMM)
sessionEnd (simple int) : Ending time of NY session in 24hr format (HHMM)
bgColor (color) : Background color for session highlighting
Returns: Color value for background or na if not in session
DCSessionStatsOHLC_v1.0DCSessionStatsOHLC_v1.0
© dc_77 | Pine Script™ v6 | Licensed under Mozilla Public License 2.0
This indicator overlays customizable session-based OHLC (Open, High, Low, Close) statistics on your TradingView chart. It tracks price action within user-defined sessions, calculates average manipulation and distribution levels based on historical data, and visually projects these levels with lines and labels. Additionally, it provides a session count table to monitor bullish and bearish sessions.
Key Features:
Session Customization: Define session time (e.g., "0000-1600") and time zone (e.g., UTC, America/New_York). Analyze up to 20 historical sessions.
Anchor Line: Displays a vertical line at session start with customizable style, color, and optional label.
Session Open Line: Plots a horizontal line at the session’s opening price with adjustable appearance and label.
Manipulation Levels: Calculates and projects average price extensions (high/low relative to open) for manipulative moves, shown as horizontal lines with labels.
Distribution Levels: Displays average price ranges (high/low beyond open) for distribution phases, with customizable lines and labels.
Visual Flexibility: Adjust line styles (solid, dashed, dotted), colors, widths, label sizes, and projection offsets (bars beyond session start).
Session Stats Table: Optional table showing counts of bullish (close > open) and bearish (close < open) sessions, with configurable position and size.
How It Works:
Tracks OHLC data within each session and identifies session start/end based on the specified time range.
Computes averages for manipulation (e.g., low below open in bullish sessions) and distribution (e.g., high above open) levels from past sessions.
Projects these levels forward as horizontal lines, extending them by a user-defined offset for easy reference.
Updates a table with real-time bullish/bearish session counts.
Use Case:
Ideal for traders analyzing intraday or custom session behavior, identifying key price levels, and gauging market sentiment over time.
Toggle individual elements on/off and fine-tune visuals to suit your trading style.
Historical VolatilityHistorical Volatility Indicator with Custom Trading Sessions
Overview
This indicator calculates **annualized Historical Volatility (HV)** using logarithmic returns and standard deviation. Unlike standard HV indicators, this version allows you to **customize trading sessions and holidays** for different markets, ensuring accurate volatility calculations for options pricing and risk management.
Key Features
✅ Custom Trading Sessions - Define multiple trading sessions per day with precise start/end times
✅ Multiple Markets Support - Pre-configured for US, Russian, European, and crypto markets
✅ Clearing Periods Handling - Account for intraday clearing breaks
✅ Flexible Calendar - Set trading days per year for different countries
✅ All Timeframes - Works correctly on intraday, daily, weekly, and monthly charts
✅ Info Table - Optional display showing calculation parameters
How It Works
The indicator uses the classical volatility formula:
σ_annual = σ_period × √(periods per year)
Where:
- σ_period = Standard deviation of logarithmic returns over the specified period
- Periods per year = Calculated based on actual trading time (not calendar time)
Calculation Method
1. Computes log returns: ln(close / close )
2. Calculates standard deviation over the lookback period
3. Annualizes using the square root rule with accurate period count
4. Displays as percentage
Settings
Calculation
- Period (default: 10) - Lookback period for volatility calculation
Trading Schedule
- Trading Days Per Year (default: 252) - Number of actual trading days
- USA: 252
- Russia: 247-250
- Europe: 250-253
- Crypto (24/7): 365
- Trading Sessions - Define trading hours in format: `hh:mm:ss-hh:mm:ss, hh:mm:ss-hh:mm:ss`
Display
- Show Info Table - Shows calculation parameters in real-time
Market Presets
United States (NYSE/NASDAQ)
Trading Sessions: 09:30:00-16:00:00
Trading Days Per Year: 252
Trading Minutes Per Day: 390
Russia (MOEX)
Trading Sessions: 10:00:00-14:00:00, 14:05:00-18:40:00
Trading Days Per Year: 248
Trading Minutes Per Day: 515
Europe (LSE)
Trading Sessions: 08:00:00-16:30:00
Trading Days Per Year: 252
Trading Minutes Per Day: 510
Germany (XETRA)
Trading Sessions: 09:00:00-17:30:00
Trading Days Per Year: 252
Trading Minutes Per Day: 510
Cryptocurrency (24/7)
Trading Sessions: 00:00:00-23:59:59
Trading Days Per Year: 365
Trading Minutes Per Day: 1440
Use Cases
Options Trading
- Compare HV vs IV - Historical volatility compared to implied volatility helps identify mispriced options
- Volatility mean reversion - Identify when volatility is unusually high or low
- Straddle/strangle selection - Choose optimal strikes based on historical movement
Risk Management
- Position sizing - Adjust position size based on current volatility
- Stop-loss placement - Set stops based on expected price movement
- Portfolio volatility - Monitor individual asset volatility contribution
Market Analysis
- Regime identification - Detect transitions between low and high volatility environments
- Cross-market comparison - Compare volatility across different assets and markets
Why Accurate Trading Hours Matter
Standard HV indicators assume 24-hour trading or use simplified day counts, leading to significant errors in annualized volatility:
- 5-minute chart error : Can be off by 50%+ if using wrong period count
- Options pricing impact : Even 2-3% HV error affects option values substantially
- Intraday vs overnight : Correctly excludes non-trading periods
This indicator ensures your HV calculations match the methodology used in professional options pricing models.
Technical Notes
- Uses actual trading minutes, not calendar days
- Handles multiple clearing periods within a single trading day
- Properly scales volatility across all timeframes
- Logarithmic returns for more accurate volatility measurement
- Compatible with Pine Script v6
Author Notes: This indicator was designed specifically for options traders who need precise volatility measurements across different global markets. The customizable trading sessions ensure your HV calculations align with actual market hours and industry-standard options pricing models.
Opening Range BoxThis indicator, called the "Opening Range Box," is a visual tool that helps you track the start of key trading sessions like London and New York (or whatever session you set).
It does three main things:
Finds the Daily 'First Move': It automatically calculates the High and Low reached during the first 30 minutes (or whatever time you set) of each defined session.
Draws a Box: It immediately draws a colored, transparent box on your chart from the moment the session starts. The top of the box is the OR High, and the bottom is the OR Low. This box acts as a clear reference for the session's initial boundaries.
Extends the Levels: After the initial 30 minutes are over, the box stops growing vertically (it locks in the OR High/Low) but continues to stretch out horizontally for the rest of the trading session. This allows you to easily see how the price reacts to the opening levels throughout the day.
In short: It visually highlights the most important price levels established at the very beginning of the major market sessions.
Intraday Volume Pulse GSK-VIZAG-AP-INDIAIntraday Volume Pulse Indicator
Overview
This indicator is designed to track and visualize intraday volume dynamics during a user-defined trading session. It calculates and displays key volume metrics such as buy volume, sell volume, cumulative delta (difference between buy and sell volumes), and total volume. The data is presented in a customizable table overlay on the chart, making it easy to monitor volume pulses throughout the session. This can help traders identify buying or selling pressure in real-time, particularly useful for intraday strategies.
The indicator resets its calculations at the start of each new day and only accumulates volume data from the specified session start time onward. It uses simple logic to classify volume as buy or sell based on candle direction:
Buy Volume: Assigned to green (up) candles or half of neutral (doji) candles.
Sell Volume: Assigned to red (down) candles or half of neutral (doji) candles.
All calculations are approximate and based on available volume data from the chart. This script does not incorporate external data sources, order flow, or tick-level information—it's purely derived from standard OHLCV (Open, High, Low, Close, Volume) bars.
Key Features
Session Customization: Define the start time of your trading session (e.g., market open) and select from common timezones like Asia/Kolkata, America/New_York, etc.
Volume Metrics:
Buy Volume: Total volume attributed to bullish activity.
Sell Volume: Total volume attributed to bearish activity.
Cumulative Delta: Net difference (Buy - Sell), highlighting overall market bias.
Total Volume: Sum of all volume during the session.
Formatted Display: Volumes are formatted for readability (e.g., in thousands "K", lakhs "L", or crores "Cr" for large numbers).
Color-Coded Table: Uses a patriotic color scheme inspired by general themes (Saffron, White, Green) with dynamic backgrounds based on positive/negative values for quick visual interpretation.
Table Options: Toggle visibility and position (top-right, top-left, etc.) for a clean chart layout.
How to Use
Add to Chart: Apply this indicator to any symbol's chart (works best on intraday timeframes like 1-min, 5-min, or 15-min).
Configure Inputs:
Session Start Hour/Minute: Set to your market's open time (default: 9:15 for Indian markets).
Timezone: Choose the appropriate timezone to align with your trading hours.
Show Table: Enable/disable the metrics table.
Table Position: Place the table where it doesn't obstruct your view.
Interpret the Table:
Monitor for spikes in buy/sell volume or shifts in cumulative delta.
Positive delta (green) suggests buying pressure; negative (red) suggests selling.
Use alongside price action or other indicators for confirmation—e.g., high total volume with positive delta could indicate bullish momentum.
Limitations:
Volume classification is heuristic and not based on actual order flow (e.g., it splits doji volume evenly).
Data accumulation starts from the session time and resets daily; historical backtesting may be limited by the max_bars_back=500 setting.
This is for educational and visualization purposes only—do not use as sole basis for trading decisions.
Calculation Details
Session Filter: Uses timestamp() to define the session start and filters bars with time >= sessionStart.
New Day Detection: Resets volumes on daily changes via ta.change(time("D")).
Volume Assignment:
Buy: Full volume if close > open; half if close == open.
Sell: Full volume if close < open; half if close == open.
Cumulative Metrics: Accumulated only during the session.
Formatting: Custom function f_format() scales large numbers for brevity.
Disclaimer
This script is for educational and informational purposes only. It does not provide financial advice or signals to buy/sell any security. Always perform your own analysis and consult a qualified financial professional before making trading decisions.
© 2025 GSK-VIZAG-AP-INDIA
Momentum Reversal StrategyBEST USE IN 15MIN TIME FRAME EURUSD / XAUSUD
1. Strategy Overview
This strategy hunts short-term momentum reversals at key levels during high-liquidity sessions.
Timeframes: 5-minute for entries; 15-minute for trend context
Sessions: London for EUR/USD & GBP/USD; New York for XAU/USD
Pairs: EUR/USD, GBP/USD, XAU/USD
Indicators (3 max):
EMA(20) and EMA(50) (close)
MACD (12, 26, 9) histogram
Optional: RSI(14) (for divergence filter)
2. Entry Rules
Trend Filter (15 min):
Long only if EMA20 > EMA50; short only if EMA20 < EMA50.
Price-Action Zone (5 min):
Identify recent swing high/low within past 20 bars.
Draw horizontal support (for longs) or resistance (for shorts).
Indicator Alignment (5 min):
MACD histogram crossing from negative to positive for longs, positive to negative for shorts.
Candle close beyond EMA20 in direction of trade.
Candle Confirmation:
Bullish engulfing or hammer at support for longs; bearish engulfing or shooting star at resistance for shorts.
Entry Execution:
Place market order on candle close that meets all above.
3. Exit Rules
Stop-Loss (SL):
Long: 1.5× ATR(14) below entry candle low.
Short: 1.5× ATR(14) above entry candle high.
Take-Profit (TP):
Set at 2× SL distance (RR 1:2).
Trailing SL:
After price moves 1× SL in profit, trail SL to breakeven.
Partial Booking:
Close 50% at 1× SL (50% of TP), move SL to entry.
Close remaining at full TP.
4. Trade Management
False Signal Filter: Skip trades when RSI(14) > 70 for longs or < 30 for shorts (avoids overbought/oversold extremes).
One Trade at a Time: No multiple positions on same pair.
Session Cutoff: Close any open trade 15 minutes before session end.
5. Risk Parameters
Risk per Trade: 1% of account equity.
Reward Target: ≥2% (1:2 RR) per trade.
Win-Rate Expectancy: ≥75% based on indicator confluence and price-action confirmation.
Daily Floor PivotsDaily Floor Pivots with Comprehensive Statistical Analysis
Overview
This indicator combines traditional floor pivot levels with golden zone analysis and comprehensive statistical insights derived from 15 years of historical NQ futures data. While the pivot levels and golden zones can be applied to any instrument, the statistical tables are specifically calibrated for NQ/MNQ futures based on analysis of 2,482 NY Regular Trading Hours (RTH) sessions from 2010-2025.
What Makes This Indicator Original
Unlike standard pivot indicators that merely plot levels, this tool provides:
Enhanced Golden Zone Analysis: Calculates not only the main golden zone (0.5-0.618 retracement of previous day's range) but also golden zones between each pivot pair (PP-R1, R1-R2, R2-R3, PP-S1, S1-S2, S2-S3)
Data-Driven Statistical Tables: Two comprehensive tables displaying real statistics from 2,482 trading days of NQ analysis, including:
Probability-based touch rates and continuation patterns
Context-aware statistics based on opening position
Gap analysis and behavioral patterns
First touch dynamics and time-to-reach averages
Granular Customization: Every visual element and statistical section can be independently toggled, allowing traders to focus on what matters most to their strategy
How It Works
Pivot Calculation Methodology
The indicator uses the standard floor pivot formula based on the previous day's price action:
Pivot Point (PP) = (Previous High + Previous Low + Previous Close) / 3
Resistance Levels: R1, R2, R3 calculated from PP and previous range
Support Levels: S1, S2, S3 calculated from PP and previous range
Golden Zone Calculations
Main Golden Zone: The 0.5 to 0.618 Fibonacci retracement of the previous day's range, representing a key reversal and continuation area.
Inter-Pivot Golden Zones: For each adjacent pivot pair, golden zones are calculated as:
Resistance pairs (PP→R1, R1→R2, R2→R3): 0.5-0.618 range from the lower pivot
Support pairs (PP→S1, S1→S2, S2→S3): 0.382-0.5 range from the upper pivot
These zones represent high-probability areas where price tends to react when moving between pivot levels.
Statistical Analysis Source
All statistics displayed in the tables are derived from external Python analysis of 15 years of 1-minute NQ futures data (2010-2025), specifically analyzing NY RTH sessions (9:30 AM - 4:00 PM EST). The analysis tracked:
2,482 complete trading days
Intraday pivot touches and closes
Opening position context
Gap behavior relative to previous day
Time-of-day patterns
Sequential pivot interactions
IMPORTANT: While the pivot levels and golden zones are universally applicable mathematical calculations that work on any instrument, the statistical percentages shown in the tables are specific to NQ/MNQ behavior only. Do not assume these statistics transfer to other instruments.
Configuration Guide
Basic Settings
Number of Periods Back (1-20, default: 3)
Controls how many historical pivot periods are displayed on the chart
Setting to 1 shows only current day's pivots
Higher values show more historical context
Labels Position (Left/Right)
Choose whether pivot labels appear on the left or right side of each level line
Line Width (1-5, default: 2)
Adjust the thickness of all pivot and golden zone lines
Golden Zone Customization
Show Daily Golden Zone (0.5-0.618)
Toggle the main golden zone on/off
When enabled, displays a shaded box between the 0.5 and 0.618 retracement levels
Line Color / Fill Color
Customize the appearance of the main golden zone
Fill color determines the shaded box transparency
Show Labels / Show Prices
Control whether "0.5" and "0.618" labels appear
Control whether price values are displayed on labels
Inter-Pivot Golden Zones
Six toggle options allow you to show/hide individual golden zones:
PP to R1 / PP to S1: Most frequently touched (60.8% / 50.9%)
R1 to R2 / S1 to S2: Moderately touched (25.2% / 24.0%)
R2 to R3 / S2 to S3: Rarely touched (9.4% / 10.5%)
Line Color / Fill Color: Customize appearance of all inter-pivot zones
Show Labels / Show Prices: Control labeling for inter-pivot zones
Usage Tip: Disable outer zones (R2-R3, S2-S3) on lower volatility days to reduce chart clutter.
Pivot Display
Show Support/Resistance Levels: Master toggle for all pivot lines
Show SR Labels / Show SR Prices: Control labeling on pivot levels
Individual level toggles and colors:
PP (Pivot Point): The central reference point
R1/S1: Primary resistance/support (38.9% / 35.4% touch rate)
R2/S2: Secondary levels (15.6% / 16.1% touch rate)
R3/S3: Extended levels (5.1% / 7.3% touch rate)
Color Customization: Each level's color can be independently set
Overall Statistics Table
Show Overall Statistics Table: Master toggle
Table Size: tiny/small/normal/large/huge/auto
Table Position: Top Left/Top Right/Bottom Left/Bottom Right
Section Toggles (enable/disable individual sections):
Current Session Info
Touch & Close Rates
Continue & Reject Rates
First Touch Statistics
Golden Zone Statistics
Daily Close Distribution
Highest/Lowest Levels Reached
Context Statistics Table
Show Context Statistics Table: Master toggle
Table Size: tiny/small/normal/large/huge/auto
Table Position: Top Left/Top Right/Bottom Left/Bottom Right
Section Toggles:
Current Opening Zone
Opening Zone Statistics
Previous Day Gap Context
Understanding the Statistical Tables
TABLE 1: OVERALL STATISTICS
This table presents universal statistics from 2,482 days of NQ analysis.
Current Session Info
Displays real-time context for the active session:
Open: Where the current RTH session opened relative to pivots (e.g., "GZ_TO_R1" means opened between the PP-R1 golden zone and R1)
Now: Current price position relative to pivots
Direction: Bull (close > open), Bear (close < open), or Flat
How to use: This section helps you quickly understand where price opened and where it currently is, providing immediate context for the day's action.
Touch & Close Rates
Shows probability that each pivot level will be reached during RTH:
Touch %: Percentage of days where price touched this level at any point
Example: R1 touched 38.9% of days, PP touched 57.5% of days
Close %: Percentage of days where price closed beyond this level
Example: R1 close beyond happened 39.8% of days
How to interpret:
Higher touch rates indicate more reliable levels for intraday targeting
The difference between touch and close rates shows rejection frequency
PP has the highest touch rate (57.5%), making it the most magnetic level
Outer levels (R3/S3) have low touch rates (5.1%/7.3%), indicating rare extension days
Continue & Reject Rates
When a level is touched, these statistics show what happens next:
Continue %: Probability price continues through the level
Example: When PP is touched, price continues 88.1% of the time
Reject %: Probability price rejects from the level and reverses
Example: When R1 is touched, price rejects 50.9% of the time
How to interpret:
PP shows highest continuation (88.1%), confirming it's a poor reversal level
Support levels (S1/S2/S3) show strong rejection rates (62.5%/60.7%/56.1%), making them better reversal candidates
Continuation rates above 80% suggest the level is better as a target than an entry
First Touch Statistics
Analyzes which pivot is typically touched first during RTH:
1st Touch %: Probability this level is the first pivot encountered
PP is first touched 37.1% of days (most common)
R1 is first touched 26.0% of days
S1 is first touched 10.9% of days
1st→Continue: If this level is touched first, probability of continuation
S1-S3 show 95.6%-100% continuation when touched first
This means when price reaches support first, it usually continues lower
Avg Time: Minutes after 9:30 AM EST before first touch
PP: 1h 6m average
S3: 19m average (when bearish)
R3: 3h 19m average (when bullish)
How to interpret:
Opening away from PP means higher probability of reaching extremes (R2/R3 or S2/S3)
When support is touched first (within first 2 hours), expect continuation lower
Late-day first touches (after 2 PM) often indicate strong trending days
Multi-Touch: Shows how often levels are tested multiple times (92.8%-95.0% across all levels)
Golden Zone Statistics
Main GZ: 58.5% touch rate for the 0.5-0.618 zone
Inter-Pivot zones:
PP-R1: 60.8% (highest probability)
PP-S1: 50.9%
R1-R2: 25.2%
S1-S2: 24.0%
R2-R3: 9.4%
S2-S3: 10.5%
How to interpret:
Main GZ is touched more often than any individual resistance level
PP-R1 and PP-S1 golden zones are high-probability mean reversion areas
Outer golden zones (R2-R3, S2-S3) are only relevant on high volatility days
Daily Close Distribution
Shows where RTH sessions typically close:
Above/Below PP: 58.5% close above, 41.5% below (slight bullish bias)
Above R1: 24.5% of days
Below S1: 18.7% of days
In GZ: Only 6.3% close in the golden zone (typically transits through it)
How to interpret:
Most days (58.5%) have bullish bias (close above PP)
Less than 25% of days are strong trending days (beyond R1/S1)
Golden zone is an action area, not a resting area
Highest/Lowest Levels Reached
Distribution of the most extreme level reached:
High Resist: R1 (26.0%), R2 (10.8%), R3 (5.1%)
Low Support: S1 (35.4%), S2 (1.9%), S3 (0.6%)
How to interpret:
Most days don't reach beyond R1 or S1
R3/S3 are rare events (5.1%/0.6%), indicating major trending days
S1 is reached as lowest level more often than R1 as highest, suggesting downside is more frequently tested
TABLE 2: CONTEXT STATISTICS
This table provides conditional statistics based on how the session opened.
Current Opening Zone
Displays which of 13 possible zones the RTH session opened in:
ABOVE_R3, R2_TO_R3, R1_TO_R2, GZ_TO_R1, IN_GZ, PP_TO_GZ, AT_PP, GZ_TO_PP, S1_TO_GZ, S2_TO_S1, S3_TO_S2, BELOW_S3
How to use: This immediately tells you the market structure and what type of day to expect.
Opening Zone Statistics
Detailed statistics for the current opening zone (only shows for 6 major zones):
For each zone, you see:
Occurs: How often this opening scenario happens
GZ_TO_R1: 38.4% (most common)
AT_PP: 12.8%
S1_TO_GZ: 24.2%
R1_TO_R2: 9.4%
S2_TO_S1: 6.3%
IN_GZ: 3.8%
Bull/Bear %: Close direction probability
Example: GZ_TO_R1 is perfectly balanced (50.0% bull / 49.6% bear)
R1_TO_R2 is bullish (58.1% bull / 41.0% bear)
Levels Hit: Probability of reaching each pivot level from this opening
Helps identify high-probability targets
Example: From GZ_TO_R1, PP is hit 52.9%, R1 is hit 49.0%, S1 is hit 21.6%
How to interpret:
GZ_TO_R1 (most common): Balanced day, watch PP and GZ for direction clues
AT_PP: Slight bullish bias (56.9%), high chance of touching both PP (92.8%) and GZ (90.3%)
R1_TO_R2: Bullish bias (58.1%), expect continuation to R2 (58.1% chance)
S2_TO_S1: Bullish reversal setup (59.9%), very high chance of S1 touch (82.8%)
IN_GZ: Rare opening (3.8%), bullish bias, virtually guaranteed GZ touch (100%)
Previous Day Gap Context
Shows current gap scenario and typical behavior:
Three scenarios:
GAP UP: Opened Above Yesterday's High (20.5% of days)
R1 Touch: 65.9% (high probability)
R2 Touch: 42.1%
S1 Touch: 15.0% (low probability)
Bias: Bullish continuation
GAP DOWN: Opened Below Yesterday's Low (11.3% of days)
S1 Touch: 71.5% (high probability)
S2 Touch: 55.2%
R1 Touch: 12.1% (low probability)
Bias: Bearish continuation
NO GAP: Opened Within Yesterday's Range (68.2% of days)
PP Touch: 69.5%
GZ Touch: 71.7%
R1 Touch: 35.2%
Bias: Balanced (watch for direction at PP/GZ)
How to interpret:
Gap days (up or down) tend to continue in the gap direction
When gapping, fade trades are low probability (15.0% and 12.1%)
Most days (68.2%) open within previous range, making PP and GZ critical decision zones
The "bias" line provides clear directional guidance for trade selection
Practical Application Examples
Example 1: Standard Day Setup
Scenario: RTH opens at 20,450
PP: 20,400
GZ: 20,390-20,395
R1: 20,425
Previous day high: 20,460
What the tables tell you:
Opening Zone: "GZ_TO_R1" (38.4% occurrence)
Gap Context: "NO GAP" (68.2% occurrence)
Expected behavior: Balanced (50/50 bull/bear)
High probability: PP touch (52.9%), GZ touch (56.8%)
Moderate probability: R1 touch (49.0%), S1 touch (21.6%)
Trade plan:
Wait for price to reach PP (52.9% chance) or GZ (56.8% chance)
Look for directional confirmation at these levels
First target R1 if bullish, S1 if bearish
Avoid assuming direction without confirmation (perfectly balanced opening)
Example 2: Gap Up Day
Scenario: RTH opens at 20,510
Previous day high: 20,460
R1: 20,425
R2: 20,475
What the tables tell you:
Gap Context: "GAP UP" (20.5% occurrence)
R1 touch: 65.9% probability
R2 touch: 42.1% probability
S1 touch: Only 15.0% probability
Bias: Bullish continuation
Trade plan:
Favor long setups
Target R1 first (65.9% chance), then R2 (42.1%)
If R1 breaks, R2 becomes likely target
Shorting is low probability (only 15.0% reach S1)
Example 3: Opening in Golden Zone
Scenario: RTH opens at 20,393
PP: 20,400
GZ: 20,390-20,395
What the tables tell you:
Opening Zone: "IN_GZ" (rare, only 3.8% occurrence)
Bullish bias: 58.1%
GZ touch: 100% (guaranteed - already there)
PP touch: 75.3%
R1 touch: 41.9%
Trade plan:
Expect price to test PP (75.3% chance)
Slight bullish bias suggests long setups better than shorts
Watch how price reacts at PP - likely to continue to R1 (41.9%)
This is an uncommon opening, suggesting potential for larger moves
Best Practices
Match Your Instrument: Remember, statistics are NQ-specific. If trading other instruments, use the levels but disregard the statistical percentages.
Combine with Price Action: Use the statistics for probability context, not as standalone signals. Always confirm with price action, volume, and your trading methodology.
Adapt Table Display: Don't display all sections all the time. Toggle based on your trading phase:
Pre-market: Focus on "Gap Context" to understand the setup
Market open: Watch "Opening Zone Statistics" for directional bias
Intraday: Monitor "Current Session Info" for position tracking
Understand Context: A 60% touch rate doesn't mean guaranteed—it means 40% of days don't touch. Use these probabilities to size positions and manage expectations.
Inter-Pivot Golden Zones: These are most useful when price is already in motion toward a level. For example, if price breaks above PP heading to R1, the PP-R1 golden zone (60.8% touch rate) becomes a high-probability pullback area.
Time Awareness: The "Avg Time" statistics help you understand urgency. If it's 10:30 AM and S1 hasn't been touched (average is 55 minutes), the window for bearish moves is closing.
Technical Notes
Time Zone: All times referenced are NY/EST
Session Definition: RTH is 9:30 AM - 4:00 PM EST
Calculation Period: Pivots update daily based on previous 24-hour period (18:00 previous day to 17:00 current day)
Data Source: Statistics derived from 12 years of NQ 1-minute futures data (2013-2025)
Sample Size: 2,482 complete RTH trading sessions
Disclaimer
This indicator provides statistical probabilities based on historical NQ futures data. Past performance does not guarantee future results. The statistical tables are educational tools and should not be the sole basis for trading decisions. Always:
Use proper risk management
Combine with your own analysis
Understand that probabilities are not certainties
Remember that statistics are instrument-specific (NQ/MNQ only)
Credits
Statistical analysis performed using Python analysis of 12 years of historical NQ futures data. All pivot and golden zone calculations use standard mathematical formulas applicable to any instrument.
Unmitigated MTF High Low - Cave Diving Plot
IntroductionThe Unmitigated MTF High Low -
Cave Diving Plot is a multi-timeframe (MTF) indicator designed for NQ and ES futures traders who want to identify high-probability entry and exit zones based on unmitigated price levels. The "Cave Diving" visualization helps you navigate between support (floor) and resistance (ceiling) zones, while the integrated Strat analysis provides directional context.
Who Is This For?
Futures traders (NQ, ES) trading during ETH and RTH sessions
Scalpers and day traders looking for precise entry/exit levels
Traders using The Strat methodology for directional analysis
Anyone seeking confluence between price action and key levels
Core Concepts
1. Unmitigated Level:
An unmitigated level is a price high or low that has been created but not yet tested (touched) by price. These levels act as magnets - price often returns to test them.Key Properties:
Resistance (Highs): Price has created a high but hasn't revisited it
Support (Lows): Price has created a low but hasn't revisited it
Mitigation: When price touches a level, it becomes "mitigated" and loses strength
2. The Cave Diving MetaphorThink of trading as cave diving between two zones:
┌─────────────────────────────────┐
│ CEILING (Upper Band) │ ← 1st & 2nd Unmitigated Highs
│ 🟥 Resistance Zone │
├─────────────────────────────────┤
│ │
│ THE TUNNEL │ ← Price navigates here
│ (Trading Channel) │
│ │
├─────────────────────────────────┤
│ 🟢 Support Zone │
│ FLOOR (Lower Band) │ ← 1st & 2nd Unmitigated Lows
└─────────────────────────────────┘
Trading Concept:
Ceiling: Formed by the 1st and 2nd most recent unmitigated highs
Floor: Formed by the 1st and 2nd most recent unmitigated lows
Tunnel: The space between ceiling and floor where price operates
Cave Diving: Navigating between these zones for entries and exits
3. Session-Based Age TrackingLevels are tracked by session age:
Session: 6:00 PM to 5:00 PM NY time (23-hour window)
Age 0: Created in the current session (today)
Age 1: Created 1 session ago (yesterday)
Age 2+: Older levels (more significant)
Why Age Matters:
Older unmitigated levels are typically stronger magnets
Fresh levels (Age 0) may be weaker and easier to break
Age 2+ levels often provide high-probability reversal zones
Indicator Components
Visual Elements
1. Colored Bands (Cave Zones)Upper Band (Pink/Maroon - 95% transparency)
Space between 1st and 2nd unmitigated highs
Acts as resistance zone
Price often hesitates or reverses here
Lower Band (Teal - 95% transparency)
Space between 1st and 2nd unmitigated lows
Acts as support zone
Price often finds buyers here
2. Information Table Located in your chosen corner (default: Bottom Right), the table displays:
5 most recent unmitigated highs (top section)
Tunnel row (middle separator)
5 most recent unmitigated lows (bottom section)
Reading the TableTable Structure
┌────────┬──────────┬────────┬───────┐
│ Level │ $ │ Points │ Age │
├────────┼──────────┼────────┼───────┤
│ ↑↑↑↑↑ │ 21,450.25│ +45.30 │ 3 │ ← 5th High (oldest)
│ ↑↑↑↑ │ 21,425.50│ +32.75 │ 2 │ ← 4th High
│ ↑↑↑ │ 21,410.00│ +25.00 │ 1 │ ← 3rd High
│ ↑↑ │ 21,400.75│ +18.50 │ 1 │ ← 2nd High
│ ↑ │ 21,395.25│ +12.00 │ 0 │ ← 1st High (newest)
├────────┼──────────┼────────┼───────┤
│ Tunnel │ 🟢 │ Δ 85.50│ 2U │ ← Current State
├────────┼──────────┼────────┼───────┤
│ ↓ │ 21,310.00│ -15.25 │ 0 │ ← 1st Low (newest)
│ ↓↓ │ 21,295.50│ -22.75 │ 1 │ ← 2nd Low
│ ↓↓↓ │ 21,280.25│ -30.00 │ 1 │ ← 3rd Low
│ ↓↓↓↓ │ 21,265.75│ -38.50 │ 2 │ ← 4th Low
│ ↓↓↓↓↓ │ 21,250.00│ -45.00 │ 3 │ ← 5th Low (oldest)
└────────┴──────────┴────────┴───────┘Column
Breakdown
Column 1: Level (Arrows)
Green arrows (↑): Resistance levels above current price
Red arrows (↓): Support levels below current price
Arrow count: Indicates recency (1 arrow = newest, 5 arrows = oldest)
Why This Matters:
More arrows = older level = stronger magnet for price
Column 2: $ (Price)
Exact price of the unmitigated level
Use this for limit orders and stop placement
Column 3: Points (Distance)
Positive (+) for highs: Points above current price
Negative (-) for lows: Points below current price
Helps gauge proximity to key levels
Trading Application:
If you're +2.50 points from resistance, a reversal may be imminent
If you're -45.00 points from support, you're far from the floor
Column 4: Age (Sessions)
Number of full 6pm-5pm sessions the level has survived
Age 0: Created today (current session)
Age 1+: Created in previous sessions
Significance Ladder:
Age 0: Weak, may break easily
Age 1-2: Medium strength
Age 3+: Strong, high-probability reaction zone
Tunnel Row (Critical Information)│ Tunnel │ 🟢 │ Δ 85.50│ 2U │
└─┬─┘ └─┬─┘ └──┬──┘ └─┬─┘
│ │ │ │
Label Direction Range Strat
1. Tunnel Label: Identifies the separator row
2. Direction Indicator (🟢/🔴)
🟢 Green Circle: Current 15m bar closed bullish (above previous close)
🔴 Red Circle: Current 15m bar closed bearish (below previous close)
3. Δ (Delta/Range)
Distance in points between 1st High and 1st Low
Shows the tunnel width (trading range)
Example: Δ 85.50 = 85.50 points between ceiling and floor
Trading Use:
Wide tunnel (>100 points): More room to trade, consider range strategies
Narrow tunnel (<50 points): Tight range, expect breakout
4. Strat Pattern
1: Inside bar (consolidation)
2U: 2 Up (bullish directional bar)
2D: 2 Down (bearish directional bar)
3: Outside bar (expansion/volatility)
Color Coding:
Green: 2U (bullish)
Red: 2D (bearish)
Yellow: 3 (expansion)
Gray: 1 (inside/neutral)
