Interval Price AlertsInterval Price Alerts
A versatile indicator that creates horizontal price levels with customizable alerts. Perfect for tracking multiple price levels simultaneously without having to create individual horizontal lines manually.
Features:
• Create evenly spaced price levels between a start and end price
• Customizable price interval spacing
• Optional price labels with flexible positioning
• Alert capabilities for both price crossovers and crossunders
• Highly customizable visual settings
Settings Groups:
1. Price Settings
• Start Price: The lower boundary for price levels
• End Price: The upper boundary for price levels
• Price Interval: The spacing between price levels
2. Line Style
• Line Color: Choose any color for the price level lines
• Line Style: Choose between Solid, Dashed, or Dotted lines
• Line Width: Adjustable from 2-4 pixels (optimized for opacity)
• Line Opacity: Control the transparency of lines (0-100%)
3. Label Style
• Show Price Labels: Toggle price labels on/off
• Label Color: Customize label text color
• Label Size: Choose from Tiny, Small, Normal, or Large
• Label Position: Place labels on Left or Right side
• Label Background: Set the background color
• Background Opacity: Control label background transparency
• Text Opacity: Adjust label text transparency
4. Alert Settings
• Alert on Crossover: Enable/disable upward price cross alerts
• Alert on Crossunder: Enable/disable downward price cross alerts
Usage Tips:
• Great for marking key price levels, support/resistance zones
• Useful for tracking multiple entry/exit points
• Perfect for scalping when you need to monitor multiple price levels
• Ideal for pre-market planning and level setting
Notes:
• Line width starts at 2 for optimal opacity rendering
• Labels can be fully customized or hidden completely
• Alert messages include the symbol and price level crossed
Multitimeframe
ICT NY Opens (Midnight, 7:30 & 8:30) True📌 ICT NY Opens Fixed (Midnight, 7:30 & 8:30) TRUE
This indicator is designed for traders following ICT (Inner Circle Trader) concepts and provides precise reference levels for the most relevant New York session opens. It automatically captures and plots the opening price for Midnight (00:00 NY), 7:30 AM, and 8:30 AM (configurable), letting you use them as liquidity anchors, manipulation zones, or institutional reference points.
🔑 Key Features
Fixed New York Opens (configurable)
Midnight (00:00 NY), 7:30 AM (NY), 8:30 AM (NY) — each open is captured from the first bar of the configured session.
Sessions are editable: the indicator exposes input.session fields for each open, so you can change the exact hour/minute (e.g., set 00:00 → 23:30 or 08:30 → 08:00). The lines and levels will follow the chosen session times.
Extension & Custom Hours (explicit)
Preset extensions: 1 Day or 2 Days (the horizontal line spans that period).
Directional extension: Right (extend to the right) or Both (left & right).
Custom Hours option: enable a custom-hours toggle and enter a specific number of hours (1–23). When enabled, horizontal lines extend for the exact number of hours you enter instead of the preset day lengths.
Labels are positioned relative to the extension setting (anchored at the open or after the extension depending on the selected mode).
Customizable visuals
Show/hide each open individually.
Independent color and line-style (solid / dotted / dashed) for each open.
Separate text color for labels.
Automatic Labels & Vertical Line
Each drawn level includes an automatic label with the open name and the exact opening price.
A dedicated vertical line option exists for the Midnight open (visual daily separator).
⚙️ How it behaves (precision & workflow)
The script detects the first bar inside the session you configure and records that bar's open as the session Open price.
If you change the session string/time in settings, the indicator will use the new time going forward and draw the corresponding level at that session's opening bar.
Extensions respect either the preset days or the custom hours you specify, so you can make lines last a precise number of hours (useful for intraday setups).
🧭 Use Cases
Pinpoint liquidity clusters and anticipate stop hunts near session opens.
Use as range anchors to measure intraday deviations.
Monitor reactions around economic releases and futures opens (7:30 / 8:30).
Integrate into ICT-based scalping or swing setups where precise session timing matters.
ICT First FVG - 9:30am & Custom (v4)ICT First FVG - 9:30am & Custom Time Ranges (v4)
📖 DESCRIPTION
This comprehensive Pine Script indicator identifies and displays Fair Value Gaps (FVGs), Volume Imbalances (VIs), and Liquidity Voids (LVs) based on Inner Circle Trading (ICT) concepts. The indicator offers dual functionality: traditional 9:30am New York session FVG detection and customizable time range analysis for maximum flexibility.
🚀 KEY FEATURES
Dual Detection System
9:30am NY Open FVG: Classic ICT first presentation detection after market open
Custom Time Range FVG: User-configurable time periods for specialized analysis
Independent Operations: Both systems work simultaneously without interference
Separate Controls: Each system has its own settings and previous days configuration
Advanced Gap Detection
Fair Value Gaps (FVG): Three-candle patterns showing price inefficiencies
Volume Imbalances (VI): Single candle volume-related gaps
Liquidity Voids (LV): Areas where price moved too fast, creating liquidity gaps
Consequent Encroachment (CE): Midpoint lines of detected inefficiencies
Precision Sizing System
Multi-Asset Support: Automatic point/pip calculation for Forex, Futures, and Indices
Forex Handling: Specialized pip calculation for major pairs and JPY crosses
Size Filtering: Minimum gap size filter to eliminate noise
Real-Time Display: Shows exact gap sizes in labels (e.g., "15.3 pips" or "12.7 pts")
Professional Visualization
Dual Display Modes: Choose between solid blocks or line representations
Color Coding: Different colors for current vs. previous day imbalances
Smart Labels: Configurable date, time, type, and size information
Extension Options: Extend gaps to session end or current bar
M1 Data Integration
High Accuracy: Uses 1-minute data regardless of chart timeframe
Better Detection: More precise gap identification on higher timeframes
Flexible Usage: Works on any timeframe ≤15 minutes
⚙️ CONFIGURATION GUIDE
General Settings
Visualization Type: Choose "Blocks" for filled areas or "Lines" for boundaries
Previous Days: Number of historical days to display (0 = today only)
Extend Imbalances: Project gaps to session end or current bar
Use M1 Data: Recommended ON for better accuracy
FVG Size Filter
Minimum FVG Size: Filter out gaps smaller than specified points
Enable Filter: Toggle size filtering on/off
🎯 RECOMMENDED MINIMUM SIZES:
USD/JPY: 0.01 points (1 pip)
Gold (XAUUSD): 1.6 points
NQ (Nasdaq-100): 0.2 points
Nasdaq CFD: 2.0 points
Other instruments: Experiment and discover optimal values
Custom FVG System
Enable Custom FVG: Activate secondary time range detection
Custom Time Range: Use session format (e.g., "1430-1600" for 2:30-4:00 PM)
Custom Previous Days: Independent historical period for custom ranges
Custom Label Color: Distinct color for custom time range gaps
Delete Default FVG 9:30: Use when running multiple instances with different timeframes
Imbalance Types
Fair Value Gaps: Main three-candle inefficiency patterns
Include Open/Close Gap: Additional gap calculation method
Volume Imbalances: Single-candle volume-based gaps
Liquidity Voids: Fast price movement gaps
C.E. (Consequent Encroachment): Midpoint reference lines
Label Customization
Show Labels: Toggle date/time information display
Include Time: Add timestamp to labels
Include Type: Display gap type (FVG, VI, LV)
Include Size: Show calculated gap size in points/pips
Position: Configure label placement (left/center/right, top/center/bottom)
Size & Color: Customize label appearance
Visual Styling
Colors: Separate colors for FVG, VI, LV types
Previous Day Colors: Distinct styling for historical gaps
Border Styles: Solid, dashed, or dotted borders
Line Widths: Configurable border thickness
📊 TECHNICAL SPECIFICATIONS
Supported Markets
Forex: All major and minor pairs with proper pip calculation
Futures: ES, NQ, YM, RTY, GC, SI, CL, etc.
Indices: SPX, NDX, DJI, and CFD versions
Stocks: Individual equities (adjust size filter accordingly)
Time Frame Compatibility
Recommended: 1m, 3m, 5m, 15m charts
Maximum: 15-minute timeframe
Optimal: 1m or 5m for best precision
Session Handling
Timezone: America/New_York (Eastern Time)
Default 9:30am: Standard NY market open detection
Custom Sessions: Any time range using HHMM-HHMM format
Weekend Filtering: Automatic exclusion of non-trading days
🔧 USAGE INSTRUCTIONS
Basic Setup
Add indicator to chart (≤15m timeframe recommended)
Enable "Use M1 Data" for accuracy
Set "Minimum FVG Size" based on instrument (see recommendations above)
Configure "Previous Days Imbalances" (5 is good default)
Custom Time Range Setup
Enable "Enable Custom FVG"
Set "Custom Time Range" (e.g., "1430-1600" for 2:30-4:00 PM ET)
Adjust "Custom Previous Days" as needed
Choose distinct "Custom Label Color" for easy identification
Multiple Instance Usage
Add indicator multiple times for different time ranges
Enable "Delete Default FVG 9:30" on additional instances
Use different custom time ranges for each instance
Assign unique colors to distinguish between instances
Label Optimization
Enable size display to see gap magnitude
Position labels to avoid chart clutter
Use appropriate label size for your screen resolution
Consider disabling time display on crowded charts
🎯 PRACTICAL APPLICATIONS
ICT Trading Concepts
First Presentation: Initial FVG after 9:30am NY open
Return to Gap: Price revisiting inefficiency areas
Mitigation Levels: Using FVG boundaries as support/resistance
Liquidity Hunting: Understanding where price seeks efficiency
Multi-Session Analysis
London Close: Set custom range for 1600-1601 London close gaps
Asian Session: Configure overnight inefficiencies
Power Hour: Analyze 1500-1600 ET gaps
Lunch Hour: Study 1200-1300 ET price behavior
Risk Management
Size-Based Filtering: Focus on significant gaps only
Historical Context: Compare current gaps to previous days
Confluence Trading: Combine with other ICT concepts
Session-Specific: Target gaps from specific market sessions
⚠️ IMPORTANT NOTES
Performance Considerations
Maximum Objects: Indicator creates multiple visual elements
Historical Limit: Adjust "Previous Days" to balance history vs. performance
Chart Refresh: Allow time for initial loading on historical data
Data Quality
Broker Dependency: Gap detection accuracy depends on data feed quality
Weekend Gaps: Sunday gaps may appear due to data provider differences
Fast Markets: Extremely volatile periods may create false gaps
Best Practices
Timeframe Consistency: Use same timeframe for analysis and execution
Size Calibration: Adjust minimum sizes based on instrument volatility
Session Awareness: Understand which sessions produce most relevant gaps
Confirmation: Use additional ICT concepts to confirm gap validity
LÜMI_INDICATOR_v1.279_Smart_Money_All_in_One_Tools!!!Русский перевод внизу!!!!
Before using it, go to the settings and uncheck all the boxes!!!
And only then after that deal with this indicator, what you need from there, then add.
In the future, I will release a COMPLETE guide to this indicator with screenshots, so throw it to your favorites, don't waste it.
This version is still raw, but WORKING. There will be improvements in the structure of the indicator so that you can intuitively understand what each of the 100+(!) indicator settings is responsible for.
What's inside:
1. Session indicator. 15 Fully customizable time boxes, for any needs, and sessions. Enter your time zone, the time of your session, and that's it. There are also a couple of unexpected bonuses in this part of the indicator))
2. A set of horizontal lines of lines that come out at the right time for you. It is convenient to designate NYM, NYSE OPEN RANge, and other events on the chart that occur strictly on time. It can be widely used if you know what to look for.
3. Like the 2nd item, only vertical.
4. Fractal indicator.
5. OHL levels for
5.1. Current day
5.2. Current week
5.3. Current month.
6. Vertical chart dividers by opening levels
6.1 Days
6.2. Weeks
6.3. Months.
This feature is ideal for those who trade forex price delivery profiles or indices.
!!! Перед использованием зайдите в настройки и поснимайте все галочки!!!
И только потом после этого разбирайтесь с этим индюком, что вам оттуда нужно, то и добавляйте.
В дальнейшем выпущу ПОЛНЕЙШИЙ гайд на этот индюк со скриншотами, так что кидайте в избранное, не теряйте
Версия пока сырая, но РАБОЧАЯ. Будут доработки в структуре индикатора, чтобы можно было интуитивно понять, за что отвечает каждая из 100+(!) настроек индикатора
Что внутри:
1. Индикатор сессий. 15полностью настраиваемых боксов по времени, под любые нужды, и сессии. Вводите свой часовой пояс, время вашей сессии и всё. В этой части индикатора также есть пара неожиданных бонусов))
2. Набор горизонтальных линий линий, выходят в нужное для вас время. Удобно обозначать NYM, NYSE OPEN RANge, и другие события на графике, которые происходят строго по времени. Применение можно найти широкое, если знать, что искать
3. Как 2 пункт, только вертикальные.
4. Индикатор фракталов.
5. Уровни OHL для
5.1. Текущего дня
5.2. Текущей недели
5.3. Текущего месяца.
6. Вертикальные разделители графика по уровням открытия
6.1 Дня
6.2. Недели
6.3. Месяца.
Эта функция идеальна для тех, кто торгует профили доставки цены форекс или индексов.
MTFA MACD Boss (DBE/SBE on H4) — Crossover + Table + AlertsThis Indicator Showing SBE/DBE Signal when and only if M+W+D+4h Aligning together for the Same Environment.
Grand Master's Candlestick Dominance (ATR Enhanced)### Grand Master's Candlestick Dominance (ATR Enhanced)
**Overview**
Unleash the ancient wisdom of Japanese candlestick charting with a modern twist! This comprehensive Pine Script v5 strategy and indicator scans for over 75 classic and advanced candlestick patterns (bullish, bearish, and neutral), assigning dynamic strength scores (1-10) to each for precise signal filtering. Enhanced with Average True Range (ATR) for volatility-aware body size validation, it dominates the markets by combining timeless pattern recognition with robust confirmation layers. Whether used as a backtestable strategy or visual indicator, it empowers traders to spot high-probability reversals, continuations, and indecision setups with surgical accuracy.
Inspired by Steve Nison's *Japanese Candlestick Charting Techniques*, this tool elevates pattern analysis beyond basics—think Hammers, Engulfing patterns, Morning Stars, and rare gems like Abandoned Baby or Concealing Baby Swallow—all consolidated into intelligent arrays for real-time averaging and prioritization.
**Key Features**
- **Extensive Pattern Library**:
- **Bullish (25+ patterns)**: Hammer (8.0), Bullish Engulfing (10.0), Morning Star (7.0), Three White Soldiers (9.0), Dragonfly Doji (8.0), and more (e.g., Rising Three, Unique Three River Bottom).
- **Bearish (25+ patterns)**: Hanging Man (8.0), Bearish Engulfing (10.0), Evening Star (7.0), Three Black Crows (9.0), Gravestone Doji (8.0), and exotics like Upside Gap Two Crows or Stalled Pattern.
- **Neutral/Indecision (34+ patterns)**: Doji variants (Long-Legged, Four Price), Spinning Tops, Harami Crosses, and multi-bar setups like Upside Tasuki Gap or Advancing Block.
Each pattern includes duration tracking (1-5 bars) and ATR-adjusted body/shadow criteria for relevance in volatile conditions.
- **Smart Confirmation Filters** (All Toggleable):
- **Trend Alignment**: 20-period SMA (customizable) ensures entries align with the prevailing trend; optional higher timeframe (e.g., Daily) MA crossover for multi-timeframe confluence.
- **Support/Resistance (S/R)**: Pivot-based levels with 0.01% tolerance to confirm bounces or breaks.
- **Volume Surge**: 20-period volume MA with 1.5x spike multiplier to validate momentum.
- **ATR Body Sizing**: Filters small bodies (<0.3x ATR) and long bodies (>0.8x ATR) for context-aware pattern reliability.
- **Follow-Through**: Ensures post-pattern confirmation via bullish/bearish closes or closes beyond prior bars.
Minimum average strength (default 7.0) and individual pattern thresholds (5.0) prevent weak signals.
- **Entry & Exit Logic**:
- **Long Entry**: Bullish average strength ≥7.0 (outweighing bearish), uptrend, volume spike, near support, follow-through, and HTF alignment.
- **Short Entry**: Mirror for bearish dominance in downtrends near resistance.
- **Exits**: Bearish/neutral shift, or fixed TP (5%) / SL (2%)—pyramiding disabled, 10% equity sizing.
- Backtest range: Jan 1, 2020 – Dec 31, 2025 (editable). Initial capital: $10,000.
- **Interactive Dashboard** (Top-Right Panel):
Real-time insights including:
- Market phase (e.g., "Bullish Phase (Avg Str: 8.2)"), active pattern (e.g., "BULLISH: Bullish Engulfing (Str: 10.0, Bars: 2)"), and trend status.
- Strength breakdowns (Bull/Bear/Neutral counts & averages).
- Filter status (e.g., "Volume: ✔ Spike", "ATR: Enabled (L:0.8, S:0.3)").
- Backtest stats: Total trades, win rate, streak, and last entry/exit details (price & timestamp).
Toggle mode: Strategy (live trades) or Indicator (signals only).
- **Advanced Alerts** (15+ Toggleable Types):
Set up via TradingView's "Any alert() function call" for bar-close triggers:
- Entry/Exit signals with strength & pattern details.
- Strong patterns (≥2 bullish/bearish), neutral indecision, volume spikes.
- S/R breakouts, HTF reversals, high-confidence singles (≥8.0 strength).
- Conflicting signals, MA crossovers, ATR volatility bursts, multi-bar completions.
Example: "STRONG BULLISH PATTERN detected! Strength: 9.5 | Top Pattern: Three White Soldiers | Trend: Up".
**Customization & Usage Tips**
- **Inputs Groups**: Strategy toggles, confirmations, exits, backtest dates, and 15+ alert switches—all intuitively grouped.
- **Optimization**: Tune min strengths for aggressive (lower) or conservative (higher) trading; enable/disable filters to suit your style (e.g., disable S/R for scalping).
- **Best For**: Forex, stocks, crypto on 1H–Daily charts. Test on historical data to refine TP/SL.
- **Limitations**: No external data installs; relies on built-in TA functions. Patterns are probabilistic—combine with your risk management.
Master the candles like a grandmaster. Deploy on TradingView, backtest relentlessly, and let dominance begin! Questions? Drop a comment.
*Version: 1.0 | Updated: September 2025 | Credits: Built on Pine Script v5 with nods to Nison's timeless techniques.*
EMA 50 & 200 (TF-specific)This script plots EMA 50 and EMA 200 only on the timeframes where they matter most:
EMA 50 (gray): visible on 1H, 4H, and 12H charts – often used by intraday traders.
EMA 200 (black): visible on Daily and Weekly charts – a classic long-term trend indicator.
🔹 Why use it?
Avoids clutter by showing each EMA only on the relevant timeframe.
Helps align intraday trading with higher timeframe trends.
Simple, clean, and effective for both swing and day trading.
MTF Stochastic Range FinderThis indicator compares Stochastic RSI from 2 timeframes to signal possible reversals. Default 5 minute and 2 minute. Both Stochastic RSIs are customizable.
Allows for 6 support/resistance lines and allows a tolerance to filter proximity to levels for entry.
Can filter price level by manual support/resistance levels and/or VWAP
cd_indiCATor_CxGeneral:
This indicator is the redesigned, simplified, and feature-enhanced version of the previously shared indicators:
cd_cisd_market_Cx, cd_HTF_Bias_Cx, cd_sweep&cisd_Cx, cd_SMT_Sweep_CISD_Cx, and cd_RSI_divergence_Cx.
Within the holistic setup, the indicator tracks:
• HTF bias
• Market structure (trend) in the current timeframe
• Divergence between selected pairs (SMT)
• Divergence between price and RSI values
• Whether the price is in an important area (FVG, iFVG, and Volume Imbalance)
• Whether the price is at a key level
• Whether the price is within a user-defined special timeframe
The main condition and trigger of the setup is an HTF sweep with CISD confirmation on the aligned timeframe.
When the main condition occurs, the indicator provides the user with a real-time market status summary, enriched with other data.
________________________________________
What’s new?
-In the SMT module:
• Triad SMT analysis (e.g.: NQ1!, ES1!, and YM1!)
• Dyad SMT analysis (e.g.: EURUSD, GBPUSD)
• Alternative pair definition and divergence analysis for non-correlated assets
o For crypto assets (xxxUSDT <--> xxxUSDT.P) (e.g.: SOLUSDT.P, SOLUSDT)
o For stocks, divergence analysis by comparing the asset with its value in another currency
(BIST:xxx <--> BIST:xxx / EURTRY), (BAT:xxx <--> BAT:xxx / EURUSD)
-Special timeframe definition
-Configurable multi-option alarm center
-Alternative summary presentation (check list / status table / stickers)
________________________________________
Details and usage:
The user needs to configure four main sections:
• Pair and correlated pairs
• Timeframes (Auto / Manual)
• Alarm center
• Visual arrangement and selections
Pair Selections:
The user should adjust trading pairs according to their trade preferences.
Examples:
• Triad: NQ1!-ES1!-YM1!, BTC-ETH-Total3
• Dyad: NAS100-US500, XAUUSD-XAGUSD, XRPUSDT-XLMUSDT
Single pairs:
-Crypto Assets:
If crypto assets are not in the triad or dyad list, they are automatically matched as:
Perpetual <--> Spot (e.g.: DOGEUSDT.P <--> DOGEUSDT)
If the asset is already defined in a dyad list (e.g., DOGE – SHIB), the dyad definition takes priority.
________________________________________
-Stocks:
If stocks are defined in the dyad list (e.g.: BIST:THYAO <--> BIST:PGSUS), the dyad definition takes priority.
If not defined, the stock is compared with its value in the selected currency.
For example, in the Turkish Stock Exchange:
BIST:FENER stock, if EUR is chosen from the menu, is compared as BIST:FENER / OANDA:EURTRY.
Here, “OANDA” and the stock market currency (TRY) are automatically applied for the exchange rate.
For NYSE:XOM, its pair will be NYSE:XOM / EURUSD.
________________________________________
Timeframes:
By default, the menu is set to “Auto.” In this mode, aligned timeframes are automatically selected.
Aligned timeframes (LTF-HTF):
1m-15m, 3m-30m, 5m-1h, 15m-4h, 1h-D, 4h-W, D-M
Example: if monitoring the chart on 5m:
• 1h sweep + 5m CISD confirmation
• D sweep + 1h CISD confirmation (bias)
• 5m market structure
• 1h SMT and 1h RSI divergence analysis
For manual selections, the user must define the timeframes for Sweep and HTF bias.
FVG, iFVG, and Volume Imbalance timeframes must be manually set in both modes.
________________________________________
Alarm Center:
The user can choose according to preferred criteria.
Each row has options.
“Yes” → included in alarm condition.
“No” → not included in alarm condition.
If special timeframe criteria are added to the alarm, the hour range must also be entered in the same row, and the “Special Zone” tab (default: -4) should be checked.
Key level timeframes and plot options must be set manually.
Example alarm setup:
Alongside the main Sweep + CISD condition, if we also want HTF bias + Trend alignment + key level (W, D) and special timeframe (09:00–11:00), we should set up the menu as follows:
________________________________________
Visual Arrangement and Selections:
Users can control visibility with checkboxes according to their preferences.
In the Table & Sticker tab, table options and labels can be controlled.
• Summary Table has two options: Check list and Status Table
• From the HTF bias section, real-time bias and HTF sweep zone (optional) are displayed
• The RSI divergence section only shows divergence analysis results
• The SMT 2 sub-section only functions when triad is selected
Labels are shown on the bar where the sweep + CISD condition occurs, displaying the current situation.
With the Check box option, all criteria’s real-time status is shown (True/False).
Status Table provides a real-time summary table.
Although the menu may look crowded, most settings only need to be adjusted once during initial use.
________________________________________
What’s next?
• Suggestions from users
• Standard deviation projection
• Mitigation/order blocks (cd special mtg)
• PSP /TPD
________________________________________
Final note:
Every additional criterion in the alarm settings will affect alarm frequency.
Multiple conditions occurring at the same time is not, by itself, sufficient to enter a trade—you should always apply your own judgment.
Looking forward to your feedback and suggestions.
Happy trading! 🎉
Alert: 10m FU at Top of HourWhen an FU happens on the hour, it will typically give a good indication of direction
Pair this with negation and HCS
HTF Big Candle ProjectionsWhat it does
This indicator overlays higher-timeframe (HTF) “big candles” at the right edge of any chart and keeps them perfectly parallel with price while you zoom or pan. In End-of-Chart (EOC) mode, all objects are anchored by bar index (not time) and clamped to TradingView’s ≤500 bars into the future rule, so they move 1:1 with the chart—no drift, no lag. A fallback mode preserves time-anchored labels if you prefer them.
Why it’s different / useful
Most MTF overlays drift when you scale or pan because they anchor by time or mix coordinate systems. This script anchors every end-of-chart object (bodies, wicks, OHLC guide lines, labels, range readout) in bar-index space, so the overlay scales identically to real bars. It also includes a safe-clamp to the 500-bar forward limit, automatic TF mapping for D/W/M charts, and optional projections from the previous HTF candle.
How it works (technical overview)
HTF data: The indicator fetches HTF OHLC using request.security() (no lookahead) and updates the current HTF candle live on each chart bar.
EOC placement (ON): Big candles are rendered with index-anchored boxes + wicks (box.new + line.new). X-positions are computed from bar_index + offset, then clamped to stay within the forward limit.
Fallback placement (OFF): Label coordinates switch to time-anchored for familiarity; candle bodies remain parallel via index logic.
OHLC helpers: Optional high/low/close guide lines extend right from the active HTF candle; OHLC labels and a range label can be placed to the side; a remaining-time widget shows how long until the HTF bar closes.
No lookahead / repaint caveat: The current HTF candle naturally evolves until it closes; that’s expected behavior for real-time HTF overlays.
Inputs & features
Place at end of chart (EOC mode toggle): index-anchored layout with ≤500-bar clamp.
Right Candle Timeframe: auto-map for D/W/M (D→W, W→M, M→3M) or set manually.
Offsets & width: right-edge offset (bars), left-candle offset, body width (bars), minimum gap between candles.
Wicks: show/hide (fallback mode draws wicks; index mode draws them via lines).
OHLC guide lines: toggle H/L/C, choose style/width/color, with right-side projection distance.
OHLC labels: side selection, text size, background/text colors, side offset.
Range label: toggle, side offset, size; option to show pip units (1/mintick).
Prev candle projections: optional HTF high/low lines from the left candle.
Remaining-time panel: live countdown to the HTF bar close.
Colors: bullish/bearish bodies and wicks.
How to use
Add to any chart (works best on intraday charts when viewing D/W/M candles).
Keep “Place at end of chart” ON for perfect parallel tracking while zooming/panning.
Choose Right Candle Timeframe (or use auto for D/W/M).
Adjust Body Width and Label/Line Offsets to taste. If you push offsets too far, the script auto-clamps objects to respect the 500-bar forward limit.
Optionally enable Prev Candle HL projections, OHLC labels, and the Range readout.
Publish with a clean chart so the overlay is easy to understand at a glance.
Notes & limitations
Forward plotting limit: TradingView only allows drawing ≤500 bars into the future. The script clamps all end-of-chart objects automatically; if you request more, it will shorten projections to remain compliant.
Sessions & symbols: Exotic sessions or illiquid symbols may produce uneven HTF boundaries. If needed, set the Right Candle Timeframe manually.
No signals, no promises: This is a visualization tool—it does not generate trade signals or promise performance. Use it alongside your own analysis and risk management.
Settings quick reference
EOC mode: ON (index-anchored) / OFF (time-anchored labels).
Right Candle TF: Auto D→W→M→3M or manual TF.
Offsets: Right edge, left candle, label/range/line projections.
Body Width: Candle thickness in bars.
Lines/Labels: OHLC guides, OHLC labels, Range label.
Prev HL: Previous HTF high/low projections.
Timer: Remaining time in the current HTF bar.
Colors: Bull/Bear bodies, wicks.
Disclaimer
For educational purposes only. Not financial advice. Past performance does not guarantee future results. Always test on your own and trade responsibly.
Author’s note on originality
This script focuses on bar-index anchored EOC rendering with comprehensive forward-clamping and dual label modes, aiming to solve the common drift/desync issues seen in MTF overlays during chart scaling.
Session AnchorsDescription
This indicator highlights the four main global trading sessions — London, New York AM, New York PM, and Asia — as color-coded boxes on the chart. Each session is defined by fixed start/end times (New York time) and dynamically updates with the evolving high and low during that interval. This provides a clear view of how volatility and structure shift as trading activity passes from one region to another.
How to use
• Works on any timeframe.
• Toggle sessions on/off based on your trading hours.
• Observe price behavior as one session closes and another opens.
• Use session boxes as context for liquidity, volatility, and structure analysis.
Originality
This script delivers a clean, customizable visualization of global market hours and session ranges, avoiding extra overlays so traders can isolate session-based behavior without distraction.
⚠️ Disclaimer
This indicator does not generate signals. It provides a structural mapping of global sessions for contextual analysis only.
Supertrend Ravi Shinde📌 Multi-Timeframe Supertrend (MFT Supertrend)
This indicator is a refined version of the classic Supertrend, designed with multi-timeframe flexibility for traders who rely on higher-timeframe confirmation while trading lower charts.
🔑 Key Features:
Multi-Timeframe Analysis: Apply Supertrend from any higher timeframe (e.g., use 15m, 1h, or 1d Supertrend on a 5m chart).
Clear Trend Identification:
🔴 Price below Supertrend → Bearish trend.
🟢 Price above Supertrend → Bullish trend.
Customizable Parameters: Input ATR length, ATR multiplier, and timeframe of your choice.
Visual Simplicity: Clean chart display with no clutter – just the essential Supertrend line.
Risk Calculator You can enter your account size and your stop-loss level, and the calculator will display the risk you are taking both as an actual monetary value and as a percentage of your account. If your account currency differs from the instrument’s currency, you can also input a conversion factor to see the risk in your account currency.
Copeland Dynamic Dominance Matrix System | GForgeCopeland Dynamic Dominance Matrix System | GForge - v1
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📊 COMPREHENSIVE SYSTEM OVERVIEW
The GForge Dynamic BB% TrendSync System represents a revolutionary approach to algorithmic portfolio management, combining cutting-edge statistical analysis, momentum detection, and regime identification into a unified framework. This system processes up to 39 different cryptocurrency assets simultaneously, using advanced mathematical models to determine optimal capital allocation across dynamic market conditions.
Core Innovation: Multi-Dimensional Analysis
Unlike traditional single-asset indicators, this system operates on multiple analytical dimensions:
Momentum Analysis: Dual Bollinger Band Modified Deviation (DBBMD) calculations
Relative Strength: Comprehensive dominance matrix with head-to-head comparisons
Fundamental Screening: Alpha and Beta statistical filtering
Market Regime Detection: Five-component statistical testing framework
Portfolio Optimization: Dynamic weighting and allocation algorithms
Risk Management: Multi-layered protection and regime-based positioning
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🔧 DETAILED COMPONENT BREAKDOWN
1. Dynamic Bollinger Band % Modified Deviation Engine (DBBMD)
The foundation of this system is an advanced oscillator that combines two independent Bollinger Band systems with asymmetric parameters to create unique momentum readings.
Technical Implementation:
[
// BB System 1: Fast-reacting with extended standard deviation
primary_bb1_ma_len = 40 // Shorter MA for responsiveness
primary_bb1_sd_len = 65 // Longer SD for stability
primary_bb1_mult = 1.0 // Standard deviation multiplier
// BB System 2: Complementary asymmetric design
primary_bb2_ma_len = 8 // Longer MA for trend following
primary_bb2_sd_len = 66 // Shorter SD for volatility sensitivity
primary_bb2_mult = 1.7 // Wider bands for reduced noise
Key Features:
Asymmetric Design: The intentional mismatch between MA and Standard Deviation periods creates unique oscillation characteristics that traditional Bollinger Bands cannot achieve
Percentage Scale: All readings are normalized to 0-100% scale for consistent interpretation across assets
Multiple Combination Modes:
BB1 Only: Fast/reactive system
BB2 Only: Smooth/stable system
Average: Balanced blend (recommended)
Both Required: Conservative (both must agree)
Either One: Aggressive (either can trigger)
Mean Deviation Filter: Additional volatility-based layer that measures the standard deviation of the DBBMD% itself, creating dynamic trigger bands
Signal Generation Logic:
// Primary thresholds
primary_long_threshold = 71 // DBBMD% level for bullish signals
primary_short_threshold = 33 // DBBMD% level for bearish signals
// Mean Deviation creates dynamic bands around these thresholds
upper_md_band = combined_bb + (md_mult * bb_std)
lower_md_band = combined_bb - (md_mult * bb_std)
// Signal triggers when DBBMD crosses these dynamic bands
long_signal = lower_md_band > long_threshold
short_signal = upper_md_band < short_threshold
For more information on this BB% indicator, find it here:
2. Revolutionary Dominance Matrix System
This is the system's most sophisticated innovation - a comprehensive framework that compares every asset against every other asset to determine relative strength hierarchies.
Mathematical Foundation:
The system constructs a mathematical matrix where each cell represents whether asset i dominates asset j:
// Core dominance matrix (39x39 for maximum assets)
var matrix dominance_matrix = matrix.new(39, 39, 0)
// For each qualifying asset pair (i,j):
for i = 0 to active_count - 1
for j = 0 to active_count - 1
if i != j
// Calculate price ratio BB% TrendSync for asset_i/asset_j
ratio_array = calculate_price_ratios(asset_i, asset_j)
ratio_dbbmd = calculate_dbbmd(ratio_array)
// Asset i dominates j if ratio is in uptrend
if ratio_dbbmd_state == 1
matrix.set(dominance_matrix, i, j, 1)
Copeland Scoring Algorithm:
Each asset receives a dominance score calculated as:
Dominance Score = Total Wins - Total Losses
// Calculate net dominance for each asset
for i = 0 to active_count - 1
wins = 0
losses = 0
for j = 0 to active_count - 1
if i != j
if matrix.get(dominance_matrix, i, j) == 1
wins += 1
else
losses += 1
copeland_score = wins - losses
array.set(dominance_scores, i, copeland_score)
Head-to-Head Analysis Process:
Ratio Construction: For each asset pair, calculate price_asset_A / price_asset_B
DBBMD Application: Apply the same DBBMD analysis to these ratios
Trend Determination: If ratio DBBMD shows uptrend, Asset A dominates Asset B
Matrix Population: Store dominance relationships in mathematical matrix
Score Calculation: Sum wins minus losses for final ranking
This creates a tournament-style ranking where each asset's strength is measured against all others, not just against a benchmark.
3. Advanced Alpha & Beta Filtering System
The system incorporates fundamental analysis through Capital Asset Pricing Model (CAPM) calculations to filter assets based on risk-adjusted performance.
Alpha Calculation (Excess Return Analysis):
// CAPM Alpha calculation
f_calc_alpha(asset_prices, benchmark_prices, alpha_length, beta_length, risk_free_rate) =>
// Calculate asset and benchmark returns
asset_returns = calculate_returns(asset_prices, alpha_length)
benchmark_returns = calculate_returns(benchmark_prices, alpha_length)
// Get beta for expected return calculation
beta = f_calc_beta(asset_prices, benchmark_prices, beta_length)
// Average returns over period
avg_asset_return = array_average(asset_returns) * 100
avg_benchmark_return = array_average(benchmark_returns) * 100
// Expected return using CAPM: E(R) = Beta * Market_Return + Risk_Free_Rate
expected_return = beta * avg_benchmark_return + risk_free_rate
// Alpha = Actual Return - Expected Return
alpha = avg_asset_return - expected_return
Beta Calculation (Volatility Relationship):
// Beta measures how much an asset moves relative to benchmark
f_calc_beta(asset_prices, benchmark_prices, length) =>
// Calculate return series for both assets
asset_returns =
benchmark_returns =
// Populate return arrays
for i = 0 to length - 1
asset_return = (current_price - previous_price) / previous_price
benchmark_return = (current_bench - previous_bench) / previous_bench
// Calculate covariance and variance
covariance = calculate_covariance(asset_returns, benchmark_returns)
benchmark_variance = calculate_variance(benchmark_returns)
// Beta = Covariance(Asset, Market) / Variance(Market)
beta = covariance / benchmark_variance
Filtering Applications:
Alpha Filter: Only includes assets with alpha above specified threshold (e.g., >0.5% monthly excess return)
Beta Filter: Screens for desired volatility characteristics (e.g., beta >1.0 for aggressive assets)
Combined Screening: Both filters must pass for asset qualification
Dynamic Thresholds: User-configurable parameters for different market conditions
4. Intelligent Tie-Breaking Resolution System
When multiple assets have identical dominance scores, the system employs sophisticated methods to determine final rankings.
Standard Tie-Breaking Hierarchy:
// Primary tie-breaking logic
if score_i == score_j // Tied dominance scores
// Level 1: Compare Beta values (higher beta wins)
beta_i = array.get(beta_values, i)
beta_j = array.get(beta_values, j)
if beta_j > beta_i
swap_positions(i, j)
else if beta_j == beta_i
// Level 2: Compare Alpha values (higher alpha wins)
alpha_i = array.get(alpha_values, i)
alpha_j = array.get(alpha_values, j)
if alpha_j > alpha_i
swap_positions(i, j)
Advanced Tie-Breaking (Head-to-Head Analysis):
For the top 3 performers, an enhanced tie-breaking mechanism analyzes direct head-to-head price ratio performance:
// Advanced tie-breaker for top performers
f_advanced_tiebreaker(asset1_idx, asset2_idx, lookback_period) =>
// Calculate price ratio over lookback period
ratio_history =
for k = 0 to lookback_period - 1
price_ratio = price_asset1 / price_asset2
array.push(ratio_history, price_ratio)
// Apply simplified trend analysis to ratio
current_ratio = array.get(ratio_history, 0)
average_ratio = calculate_average(ratio_history)
// Asset 1 wins if current ratio > average (trending up)
if current_ratio > average_ratio
return 1 // Asset 1 dominates
else
return -1 // Asset 2 dominates
5. Five-Component Aggregate Market Regime Filter
This sophisticated framework combines multiple statistical tests to determine whether market conditions favor trending strategies or require defensive positioning.
Component 1: Augmented Dickey-Fuller (ADF) Test
Tests for unit root presence to distinguish between trending and mean-reverting price series.
// Simplified ADF implementation
calculate_adf_statistic(price_series, lookback) =>
// Calculate first differences
differences =
for i = 0 to lookback - 2
diff = price_series - price_series
array.push(differences, diff)
// Statistical analysis of differences
mean_diff = calculate_mean(differences)
std_diff = calculate_standard_deviation(differences)
// ADF statistic approximation
adf_stat = mean_diff / std_diff
// Compare against threshold for trend determination
is_trending = adf_stat <= adf_threshold
Component 2: Directional Movement Index (DMI)
Classic Wilder indicator measuring trend strength through directional movement analysis.
// DMI calculation for trend strength
calculate_dmi_signal(high_data, low_data, close_data, period) =>
// Calculate directional movements
plus_dm_sum = 0.0
minus_dm_sum = 0.0
true_range_sum = 0.0
for i = 1 to period
// Directional movements
up_move = high_data - high_data
down_move = low_data - low_data
// Accumulate positive/negative movements
if up_move > down_move and up_move > 0
plus_dm_sum += up_move
if down_move > up_move and down_move > 0
minus_dm_sum += down_move
// True range calculation
true_range_sum += calculate_true_range(i)
// Calculate directional indicators
di_plus = 100 * plus_dm_sum / true_range_sum
di_minus = 100 * minus_dm_sum / true_range_sum
// ADX calculation
dx = 100 * math.abs(di_plus - di_minus) / (di_plus + di_minus)
adx = dx // Simplified for demonstration
// Trending if ADX above threshold
is_trending = adx > dmi_threshold
Component 3: KPSS Stationarity Test
Complementary test to ADF that examines stationarity around trend components.
// KPSS test implementation
calculate_kpss_statistic(price_series, lookback, significance_level) =>
// Calculate mean and variance
series_mean = calculate_mean(price_series, lookback)
series_variance = calculate_variance(price_series, lookback)
// Cumulative sum of deviations
cumulative_sum = 0.0
cumsum_squared_sum = 0.0
for i = 0 to lookback - 1
deviation = price_series - series_mean
cumulative_sum += deviation
cumsum_squared_sum += math.pow(cumulative_sum, 2)
// KPSS statistic
kpss_stat = cumsum_squared_sum / (lookback * lookback * series_variance)
// Compare against critical values
critical_value = significance_level == 0.01 ? 0.739 :
significance_level == 0.05 ? 0.463 : 0.347
is_trending = kpss_stat >= critical_value
Component 4: Choppiness Index
Measures market directionality using fractal dimension analysis of price movement.
// Choppiness Index calculation
calculate_choppiness(price_data, period) =>
// Find highest and lowest over period
highest = price_data
lowest = price_data
true_range_sum = 0.0
for i = 0 to period - 1
if price_data > highest
highest := price_data
if price_data < lowest
lowest := price_data
// Accumulate true range
if i > 0
true_range = calculate_true_range(price_data, i)
true_range_sum += true_range
// Choppiness calculation
range_high_low = highest - lowest
choppiness = 100 * math.log10(true_range_sum / range_high_low) / math.log10(period)
// Trending if choppiness below threshold (typically 61.8)
is_trending = choppiness < 61.8
Component 5: Hilbert Transform Analysis
Phase-based cycle detection and trend identification using mathematical signal processing.
// Hilbert Transform trend detection
calculate_hilbert_signal(price_data, smoothing_period, filter_period) =>
// Smooth the price data
smoothed_price = calculate_moving_average(price_data, smoothing_period)
// Calculate instantaneous phase components
// Simplified implementation for demonstration
instant_phase = smoothed_price
delayed_phase = calculate_moving_average(price_data, filter_period)
// Compare instantaneous vs delayed signals
phase_difference = instant_phase - delayed_phase
// Trending if instantaneous leads delayed
is_trending = phase_difference > 0
Aggregate Regime Determination:
// Combine all five components
regime_calculation() =>
trending_count = 0
total_components = 0
// Test each enabled component
if enable_adf and adf_signal == 1
trending_count += 1
if enable_adf
total_components += 1
// Repeat for all five components...
// Calculate trending proportion
trending_proportion = trending_count / total_components
// Market is trending if proportion above threshold
regime_allows_trading = trending_proportion >= regime_threshold
The system only allows asset positions when the specified percentage of components indicate trending conditions. During choppy or mean-reverting periods, the system automatically positions in USD to preserve capital.
6. Dynamic Portfolio Weighting Framework
Six sophisticated allocation methodologies provide flexibility for different market conditions and risk preferences.
Weighting Method Implementations:
1. Equal Weight Distribution:
// Simple equal allocation
if weighting_mode == "Equal Weight"
weight_per_asset = 1.0 / selection_count
for i = 0 to selection_count - 1
array.push(weights, weight_per_asset)
2. Linear Dominance Scaling:
// Linear scaling based on dominance scores
if weighting_mode == "Linear Dominance"
// Normalize scores to 0-1 range
min_score = array.min(dominance_scores)
max_score = array.max(dominance_scores)
score_range = max_score - min_score
total_weight = 0.0
for i = 0 to selection_count - 1
score = array.get(dominance_scores, i)
normalized = (score - min_score) / score_range
weight = 1.0 + normalized * concentration_factor
array.push(weights, weight)
total_weight += weight
// Normalize to sum to 1.0
for i = 0 to selection_count - 1
current_weight = array.get(weights, i)
array.set(weights, i, current_weight / total_weight)
3. Conviction Score (Exponential):
// Exponential scaling for high conviction
if weighting_mode == "Conviction Score"
// Combine dominance score with DBBMD strength
conviction_scores =
for i = 0 to selection_count - 1
dominance = array.get(dominance_scores, i)
dbbmd_strength = array.get(dbbmd_values, i)
conviction = dominance + (dbbmd_strength - 50) / 25
array.push(conviction_scores, conviction)
// Exponential weighting
total_weight = 0.0
for i = 0 to selection_count - 1
conviction = array.get(conviction_scores, i)
normalized = normalize_score(conviction)
weight = math.pow(1 + normalized, concentration_factor)
array.push(weights, weight)
total_weight += weight
// Final normalization
normalize_weights(weights, total_weight)
Advanced Features:
Minimum Position Constraint: Prevents dust allocations below specified threshold
Concentration Factor: Adjustable parameter controlling weight distribution aggressiveness
Dominance Boost: Extra weight for assets exceeding specified dominance thresholds
Dynamic Rebalancing: Automatic weight recalculation on portfolio changes
7. Intelligent USD Management System
The system treats USD as a competing asset with its own dominance score, enabling sophisticated cash management.
USD Scoring Methodologies:
Smart Competition Mode (Recommended):
f_calculate_smart_usd_dominance() =>
usd_wins = 0
// USD beats assets in downtrends or weak uptrends
for i = 0 to active_count - 1
asset_state = get_asset_state(i)
asset_dbbmd = get_asset_dbbmd(i)
// USD dominates shorts and weak longs
if asset_state == -1 or (asset_state == 1 and asset_dbbmd < long_threshold)
usd_wins += 1
// Calculate Copeland-style score
base_score = usd_wins - (active_count - usd_wins)
// Boost during weak market conditions
qualified_assets = count_qualified_long_assets()
if qualified_assets <= active_count * 0.2
base_score := math.round(base_score * usd_boost_factor)
base_score
Auto Short Count Mode:
// USD dominance based on number of bearish assets
usd_dominance = count_assets_in_short_state()
// Apply boost during low activity
if qualified_long_count <= active_count * 0.2
usd_dominance := usd_dominance * usd_boost_factor
Regime-Based USD Positioning:
When the five-component regime filter indicates unfavorable conditions, the system automatically overrides all asset signals and positions 100% in USD, protecting capital during choppy markets.
8. Multi-Asset Infrastructure & Data Management
The system maintains comprehensive data structures for up to 39 assets simultaneously.
Data Collection Framework:
// Full OHLC data matrices (200 bars depth for performance)
var matrix open_data = matrix.new(39, 200, na)
var matrix high_data = matrix.new(39, 200, na)
var matrix low_data = matrix.new(39, 200, na)
var matrix close_data = matrix.new(39, 200, na)
// Real-time data collection
if barstate.isconfirmed
for i = 0 to active_count - 1
ticker = array.get(assets, i)
= request.security(ticker, timeframe.period,
[open , high , low , close ],
lookahead=barmerge.lookahead_off)
// Store in matrices with proper shifting
matrix.set(open_data, i, 0, nz(o, 0))
matrix.set(high_data, i, 0, nz(h, 0))
matrix.set(low_data, i, 0, nz(l, 0))
matrix.set(close_data, i, 0, nz(c, 0))
Asset Configuration:
The system comes pre-configured with 39 major cryptocurrency pairs across multiple exchanges:
Major Pairs: BTC, ETH, XRP, SOL, DOGE, ADA, etc.
Exchange Coverage: Binance, KuCoin, MEXC for optimal liquidity
Configurable Count: Users can activate 2-39 assets based on preferences
Custom Tickers: All asset selections are user-modifiable
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⚙️ COMPREHENSIVE CONFIGURATION GUIDE
Portfolio Management Settings
Maximum Portfolio Size (1-10):
Conservative (1-2): High concentration, captures strong trends
Balanced (3-5): Moderate diversification with trend focus
Diversified (6-10): Lower concentration, broader market exposure
Dominance Clarity Threshold (0.1-1.0):
Low (0.1-0.4): Prefers diversification, holds multiple assets frequently
Medium (0.5-0.7): Balanced approach, context-dependent allocation
High (0.8-1.0): Concentration-focused, single asset preference
Signal Generation Parameters
DBBMD Thresholds:
// Standard configuration
primary_long_threshold = 71 // Conservative: 75+, Aggressive: 65-70
primary_short_threshold = 33 // Conservative: 25-30, Aggressive: 35-40
// BB System parameters
bb1_ma_len = 40 // Fast system: 20-50
bb1_sd_len = 65 // Stability: 50-80
bb2_ma_len = 8 // Trend: 60-100
bb2_sd_len = 66 // Sensitivity: 10-20
Risk Management Configuration
Alpha/Beta Filters:
Alpha Threshold: 0.0-2.0% (higher = more selective)
Beta Threshold: 0.5-2.0 (1.0+ for aggressive assets)
Calculation Periods: 20-50 bars (longer = more stable)
Regime Filter Settings:
Trending Threshold: 0.3-0.8 (higher = stricter trend requirements)
Component Lookbacks: 30-100 bars (balance responsiveness vs stability)
Enable/Disable: Individual component control for customization
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📊 PERFORMANCE TRACKING & VISUALIZATION
Real-Time Dashboard Features
The compact dashboard provides essential information:
Current Holdings: Asset names and allocation percentages
Dominance Score: Current position's relative strength ranking
Active Assets: Qualified long signals vs total asset count
Returns: Total portfolio performance percentage
Maximum Drawdown: Peak-to-trough decline measurement
Trade Count: Total portfolio transitions executed
Regime Status: Current market condition assessment
Comprehensive Ranking Table
The left-side table displays detailed asset analysis:
Ranking Position: Numerical order by dominance score
Asset Symbol: Clean ticker identification with color coding
Dominance Score: Net wins minus losses in head-to-head comparisons
Win-Loss Record: Detailed breakdown of dominance relationships
DBBMD Reading: Current momentum percentage with threshold highlighting
Alpha/Beta Values: Fundamental analysis metrics when filters enabled
Portfolio Weight: Current allocation percentage in signal portfolio
Execution Status: Visual indicator of actual holdings vs signals
Visual Enhancement Features
Color-Coded Assets: 39 distinct colors for easy identification
Regime Background: Red tinting during unfavorable market conditions
Dynamic Equity Curve: Portfolio value plotted with position-based coloring
Status Indicators: Symbols showing execution vs signal states
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🔍 ADVANCED TECHNICAL FEATURES
State Persistence System
The system maintains asset states across bars to prevent excessive switching:
// State tracking for each asset and ratio combination
var array asset_states = array.new(1560, 0) // 39 * 40 ratios
// State changes only occur on confirmed threshold breaks
if long_crossover and current_state != 1
current_state := 1
array.set(asset_states, asset_index, 1)
else if short_crossover and current_state != -1
current_state := -1
array.set(asset_states, asset_index, -1)
Transaction Cost Integration
Realistic modeling of trading expenses:
// Transaction cost calculation
transaction_fee = 0.4 // Default 0.4% (fees + slippage)
// Applied on portfolio transitions
if should_execute_transition
was_holding_assets = check_current_holdings()
will_hold_assets = check_new_signals()
// Charge fees for meaningful transitions
if transaction_fee > 0 and (was_holding_assets or will_hold_assets)
fee_amount = equity * (transaction_fee / 100)
equity -= fee_amount
total_fees += fee_amount
Dynamic Memory Management
Optimized data structures for performance:
200-Bar History: Sufficient for calculations while maintaining speed
Matrix Operations: Efficient storage and retrieval of multi-asset data
Array Recycling: Memory-conscious data handling for long-running backtests
Conditional Calculations: Skip unnecessary computations during initialization
12H 30 assets portfolio
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🚨 SYSTEM LIMITATIONS & TESTING STATUS
CURRENT DEVELOPMENT PHASE: ACTIVE TESTING & OPTIMIZATION
This system represents cutting-edge algorithmic trading technology but remains in continuous development. Key considerations:
Known Limitations:
Requires significant computational resources for 39-asset analysis
Performance varies significantly across different market conditions
Complex parameter interactions may require extensive optimization
Slippage and liquidity constraints not fully modeled for all assets
No consideration for market impact in large position sizes
Areas Under Active Development:
Enhanced regime detection algorithms
Improved transaction cost modeling
Additional portfolio weighting methodologies
Machine learning integration for parameter optimization
Cross-timeframe analysis capabilities
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🔒 ANTI-REPAINTING ARCHITECTURE & LIVE TRADING READINESS
One of the most critical aspects of any trading system is ensuring that signals and calculations are based on confirmed, historical data rather than current bar information that can change throughout the trading session. This system implements comprehensive anti-repainting measures to ensure 100% reliability for live trading .
The Repainting Problem in Trading Systems
Repainting occurs when an indicator uses current, unconfirmed bar data in its calculations, causing:
False Historical Signals: Backtests appear better than reality because calculations change as bars develop
Live Trading Failures: Signals that looked profitable in testing fail when deployed in real markets
Inconsistent Results: Different results when running the same indicator at different times during a trading session
Misleading Performance: Inflated win rates and returns that cannot be replicated in practice
GForge Anti-Repainting Implementation
This system eliminates repainting through multiple technical safeguards:
1. Historical Data Usage for All Calculations
// CRITICAL: All calculations use PREVIOUS bar data (note the offset)
= request.security(ticker, timeframe.period,
[open , high , low , close , close],
lookahead=barmerge.lookahead_off)
// Store confirmed previous bar OHLC for calculations
matrix.set(open_data, i, 0, nz(o1, 0)) // Previous bar open
matrix.set(high_data, i, 0, nz(h1, 0)) // Previous bar high
matrix.set(low_data, i, 0, nz(l1, 0)) // Previous bar low
matrix.set(close_data, i, 0, nz(c1, 0)) // Previous bar close
// Current bar close only for visualization
matrix.set(current_prices, i, 0, nz(c0, 0)) // Live price display
2. Confirmed Bar State Processing
// Only process data when bars are confirmed and closed
if barstate.isconfirmed
// All signal generation and portfolio decisions occur here
// using only historical, unchanging data
// Shift historical data arrays
for i = 0 to active_count - 1
for bar = math.min(data_bars, 199) to 1
// Move confirmed data through historical matrices
old_data = matrix.get(close_data, i, bar - 1)
matrix.set(close_data, i, bar, old_data)
// Process new confirmed bar data
calculate_all_signals_and_dominance()
3. Lookahead Prevention
// Explicit lookahead prevention in all security calls
request.security(ticker, timeframe.period, expression,
lookahead=barmerge.lookahead_off)
// This ensures no future data can influence current calculations
// Essential for maintaining signal integrity across all timeframes
4. State Persistence with Historical Validation
// Asset states only change based on confirmed threshold breaks
// using historical data that cannot change
var array asset_states = array.new(1560, 0)
// State changes use only confirmed, previous bar calculations
if barstate.isconfirmed
=
f_calculate_enhanced_dbbmd(confirmed_price_array, ...)
// Only update states after bar confirmation
if long_crossover_confirmed and current_state != 1
current_state := 1
array.set(asset_states, asset_index, 1)
Live Trading vs. Backtesting Consistency
The system's architecture ensures identical behavior in both environments:
Backtesting Mode:
Uses historical offset data for all calculations
Processes confirmed bars with `barstate.isconfirmed`
Maintains identical signal generation logic
No access to future information
Live Trading Mode:
Uses same historical offset data structure
Waits for bar confirmation before signal updates
Identical mathematical calculations and thresholds
Real-time price display without affecting signals
Technical Implementation Details
Data Collection Timing
// Example of proper data collection timing
if barstate.isconfirmed // Wait for bar to close
// Collect PREVIOUS bar's confirmed OHLC data
for i = 0 to active_count - 1
ticker = array.get(assets, i)
// Get confirmed previous bar data (note offset)
=
request.security(ticker, timeframe.period,
[open , high , low , close , close],
lookahead=barmerge.lookahead_off)
// ALL calculations use prev_* values
// current_close only for real-time display
portfolio_calculations_use_previous_bar_data()
Signal Generation Process
// Signal generation workflow (simplified)
if barstate.isconfirmed and data_bars >= minimum_required_bars
// Step 1: Calculate DBBMD using historical price arrays
for i = 0 to active_count - 1
historical_prices = get_confirmed_price_history(i) // Uses offset data
= calculate_dbbmd(historical_prices)
update_asset_state(i, state)
// Step 2: Build dominance matrix using confirmed data
calculate_dominance_relationships() // All historical data
// Step 3: Generate portfolio signals
new_portfolio = generate_target_portfolio() // Based on confirmed calculations
// Step 4: Compare with previous signals for changes
if portfolio_signals_changed()
execute_portfolio_transition()
Verification Methods for Users
Users can verify the anti-repainting behavior through several methods:
1. Historical Replay Test
Run the indicator on historical data
Note signal timing and portfolio changes
Replay the same period - signals should be identical
No retroactive changes in historical signals
2. Intraday Consistency Check
Load indicator during active trading session
Observe that previous day's signals remain unchanged
Only current day's final bar should show potential signal changes
Refresh indicator - historical signals should be identical
Live Trading Deployment Considerations
Data Quality Assurance
Exchange Connectivity: Ensure reliable data feeds for all 39 assets
Missing Data Handling: System includes safeguards for data gaps
Price Validation: Automatic filtering of obvious price errors
Timeframe Synchronization: All assets synchronized to same bar timing
Performance Impact of Anti-Repainting Measures
The robust anti-repainting implementation requires additional computational resources:
Memory Usage: 200-bar historical data storage for 39 assets
Processing Delay: Signals update only after bar confirmation
Calculation Overhead: Multiple historical data validations
Alert Timing: Slight delay compared to current-bar indicators
However, these trade-offs are essential for reliable live trading performance and accurate backtesting results.
Critical: Equity Curve Anti-Repainting Architecture
The most sophisticated aspect of this system's anti-repainting design is the temporal separation between signal generation and performance calculation . This creates a realistic trading simulation that perfectly matches live trading execution.
The Timing Sequence
// STEP 1: Store what we HELD during the current bar (for performance calc)
if barstate.isconfirmed
// Record positions that were active during this bar
array.clear(held_portfolio)
array.clear(held_weights)
for i = 0 to array.size(execution_portfolio) - 1
array.push(held_portfolio, array.get(execution_portfolio, i))
array.push(held_weights, array.get(execution_weights, i))
// STEP 2: Calculate performance based on what we HELD
portfolio_return = 0.0
for i = 0 to array.size(held_portfolio) - 1
held_asset = array.get(held_portfolio, i)
held_weight = array.get(held_weights, i)
// Performance from current_price vs reference_price
// This is what we ACTUALLY earned during this bar
if held_asset != "USD"
current_price = get_current_price(held_asset) // End of bar
reference_price = get_reference_price(held_asset) // Start of bar
asset_return = (current_price - reference_price) / reference_price
portfolio_return += asset_return * held_weight
// STEP 3: Apply return to equity (realistic timing)
equity := equity * (1 + portfolio_return)
// STEP 4: Generate NEW signals for NEXT period (using confirmed data)
= f_generate_target_portfolio()
// STEP 5: Execute transitions if signals changed
if signal_changed
// Update execution_portfolio for NEXT bar
array.clear(execution_portfolio)
array.clear(execution_weights)
for i = 0 to array.size(new_signal_portfolio) - 1
array.push(execution_portfolio, array.get(new_signal_portfolio, i))
array.push(execution_weights, array.get(new_signal_weights, i))
Why This Prevents Equity Curve Repainting
Performance Attribution: Returns are calculated based on positions that were **actually held** during each bar, not future signals
Signal Timing: New signals are generated **after** performance calculation, affecting only **future** bars
Realistic Execution: Mimics real trading where you earn returns on current positions while planning future moves
No Retroactive Changes: Once a bar closes, its performance contribution to equity is permanent and unchangeable
The One-Bar Offset Mechanism
This system implements a critical one-bar timing offset:
// Bar N: Performance Calculation
// ================================
// 1. Calculate returns on positions held during Bar N
// 2. Update equity based on actual holdings during Bar N
// 3. Plot equity point for Bar N (based on what we HELD)
// Bar N: Signal Generation
// ========================
// 4. Generate signals for Bar N+1 (using confirmed Bar N data)
// 5. Send alerts for what will be held during Bar N+1
// 6. Update execution_portfolio for Bar N+1
// Bar N+1: The Cycle Continues
// =============================
// 1. Performance calculated on positions from Bar N signals
// 2. New signals generated for Bar N+2
Alert System Timing
The alert system reflects this sophisticated timing:
Transaction Cost Realism
Even transaction costs follow realistic timing:
// Fees applied when transitioning between different portfolios
if should_execute_transition
// Charge fees BEFORE taking new positions (realistic timing)
if transaction_fee > 0
fee_amount = equity * (transaction_fee / 100)
equity -= fee_amount // Immediate cost impact
total_fees += fee_amount
// THEN update to new portfolio
update_execution_portfolio(new_signals)
transitions += 1
// Fees reduce equity immediately, affecting all future calculations
// This matches real trading where fees are deducted upon execution
LIVE TRADING CERTIFICATION:
This system has been specifically designed and tested for live trading deployment. The comprehensive anti-repainting measures ensure that:
Backtesting results accurately represent real trading potential
Signals are generated using only confirmed, historical data
No retroactive changes can occur to previously generated signals
Portfolio transitions are based on reliable, unchanging calculations
Performance metrics reflect realistic trading outcomes including proper timing
Users can deploy this system with confidence that live trading results will closely match backtesting performance, subject to normal market execution factors such as slippage and liquidity.
---
⚡ ALERT SYSTEM & AUTOMATION
The system provides comprehensive alerting for automation and monitoring:
Available Alert Conditions
Portfolio Signal Change: Triggered when new portfolio composition is generated
Regime Override Active: Alerts when market regime forces USD positioning
Individual Asset Signals: Can be configured for specific asset transitions
Performance Thresholds: Drawdown or return-based notifications
---
📈 BACKTESTING & PERFORMANCE ANALYSIS
8 Comprehensive Metrics Tracking
The system maintains detailed performance statistics:
Equity Curve: Real-time portfolio value progression
Returns Calculation: Total and annualized performance metrics
Drawdown Analysis: Peak-to-trough decline measurements
Transaction Counting: Portfolio transition frequency
Fee Tracking: Cumulative transaction cost impact
Win Rate Analysis: Success rate of position changes
Backtesting Configuration
// Backtesting parameters
initial_capital = 10000.0 // Starting capital
use_custom_start = true // Enable specific start date
custom_start = timestamp("2023-09-01") // Backtest beginning
transaction_fee = 0.4 // Combined fees and slippage %
// Performance calculation
total_return = (equity - initial_capital) / initial_capital * 100
current_drawdown = (peak_equity - equity) / peak_equity * 100
---
🔧 TROUBLESHOOTING & OPTIMIZATION
Common Configuration Issues
Insufficient Data: Ensure 100+ bars available before start date
[*} Not Compiling: Go on an asset's price chart with 2 or 3 years of data to
make the system compile or just simply reapply the indicator again
Too Many Assets: Reduce active count if experiencing timeouts
Regime Filter Too Strict: Lower trending threshold if always in USD
Excessive Switching: Increase MD multiplier or adjust thresholds
---
💡 USER FEEDBACK & ENHANCEMENT REQUESTS
The continuous evolution of this system depends heavily on user experience and community feedback. Your insights will help motivate me for new improvements and new feature developments.
---
⚖️ FINAL COMPREHENSIVE RISK DISCLAIMER
TRADING INVOLVES SUBSTANTIAL RISK OF LOSS
This indicator is a sophisticated analytical tool designed for educational and research purposes. Important warnings and considerations:
System Limitations:
No algorithmic system can guarantee profitable outcomes
Complex systems may fail in unexpected ways during extreme market events
Historical backtesting does not account for all real-world trading challenges
Slippage, liquidity constraints, and market impact can significantly affect results
System parameters require careful optimization and ongoing monitoring
The creator and distributor of this indicator assume no liability for any financial losses, system failures, or adverse outcomes resulting from its use. This tool is provided "as is" without any warranties, express or implied.
By using this indicator, you acknowledge that you have read, understood, and agreed to assume all risks associated with algorithmic trading and cryptocurrency investments.
ElectronixTrader - Multi-Timeframe S/RThis script is a powerful multi-timeframe tool designed to help traders identify key support and resistance levels for both intraday and swing trading. It's a custom-built indicator that projects Bollinger Band levels from a higher timeframe onto your current chart, providing a unique perspective to filter out market noise and focus on high-probability trading zones.
The core principle is that significant price levels established on a daily or weekly chart can act as powerful support and resistance points on a lower, intraday timeframe. This helps traders align their entries and exits with the broader market context.
Key Features:
Dynamic Levels: The support and resistance lines are not static. They are automatically calculated and updated at the start of each new higher-timeframe candle, providing fresh and relevant levels.
Multi-Timeframe Capability: Easily switch the input timeframe (e.g., Daily to Weekly) to adapt the indicator for your trading style, from intraday to swing trading.
Disclaimer:
Trading involves significant risk, and past performance is not a guarantee of future results. This tool is for informational and educational purposes only and should be used in conjunction with your own risk management and trading plan.
A Note on Originality:
This indicator uses a unique application of built-in functions to project dynamic, higher-timeframe levels. While it is based on classic concepts, the specific methodology of projecting and consistently plotting these zones across different timeframes provides a unique and actionable tool for traders.
Simple Technicals Table📊 Simple Technicals Table
🎯 A comprehensive technical analysis dashboard displaying key pivot points and moving averages across multiple timeframes
📋 OVERVIEW
The Simple Technicals Table is a powerful indicator that organizes essential trading data into a clean, customizable table format. It combines Fibonacci-based pivot points with critical moving averages for both daily and weekly timeframes, giving traders instant access to key support/resistance levels and trend information.
Perfect for:
Technical analysts studying multi-timeframe data
Chart readers needing quick reference levels
Market researchers analyzing price patterns
Educational purposes and data visualization
🚀 KEY FEATURES
📊 Dual Timeframe Analysis
Daily (D1) and Weekly (W1) data side-by-side
Real-time updates as market conditions change
Seamless comparison between timeframes
🎯 Fibonacci Pivot Points
R3, R2, R1 : Resistance levels using Fibonacci ratios (38.2%, 61.8%, 100%)
PP : Central pivot point from previous period's data
S1, S2, S3 : Support levels with same methodology
📈 Complete EMA Suite
EMA 10 : Short-term trend identification
EMA 20 : Popular swing trading reference
EMA 50 : Medium-term trend confirmation
EMA 100 : Institutional support/resistance
EMA 200 : Long-term trend determination
📊 Essential Indicators
RSI 14 : Momentum for overbought/oversold conditions
ATR 14 : Volatility measurement for risk management
🎨 Full Customization
9 table positions : Place anywhere on your chart
5 text sizes : Tiny to huge for optimal visibility
Custom colors : Background, headers, and text
Optional pivot lines : Visual weekly levels on chart
⚙️ HOW IT WORKS
Fibonacci Pivot Calculation:
Pivot Point (PP) = (High + Low + Close) / 3
Range = High - Low
Resistance Levels:
R1 = PP + (Range × 0.382)
R2 = PP + (Range × 0.618)
R3 = PP + (Range × 1.000)
Support Levels:
S1 = PP - (Range × 0.382)
S2 = PP - (Range × 0.618)
S3 = PP - (Range × 1.000)
Smart Price Formatting:
< $1: 5 decimal places (crypto-friendly)
$1-$10: 4 decimal places
$10-$100: 3 decimal places
> $100: 2 decimal places
📊 TECHNICAL ANALYSIS APPLICATIONS
⚠️ EDUCATIONAL PURPOSE ONLY
This indicator is designed solely for technical analysis and educational purposes . It provides data visualization to help understand market structure and price relationships.
📈 Data Analysis Uses
Support & Resistance Identification : Visualize Fibonacci-based pivot levels
Trend Analysis : Study EMA relationships and price positioning
Multi-Timeframe Study : Compare daily and weekly technical data
Market Structure : Understand key technical levels and indicators
📚 Educational Benefits
Learn about Fibonacci pivot point calculations
Understand moving average relationships
Study RSI and ATR indicator values
Practice multi-timeframe technical analysis
🔍 Data Visualization Features
Organized table format for easy data reading
Color-coded levels for quick identification
Real-time technical indicator values
Historical data integrity maintained
🛠️ SETUP GUIDE
1. Installation
Search "Simple Technicals Table" in indicators
Add to chart (appears in middle-left by default)
Table displays automatically on any timeframe
2. Customization
Table Position : Choose from 9 locations
Text Size : Adjust for screen resolution
Colors : Match your chart theme
Pivot Lines : Toggle weekly level visualization
3. Optimization Tips
Use larger text on mobile devices
Dark backgrounds work well with light text
Enable pivot lines for visual reference
✅ BEST PRACTICES
Recommended Usage:
Use for technical analysis and educational study only
Combine with other analytical methods for comprehensive analysis
Study multi-timeframe data relationships
Practice understanding technical indicator values
Important Notes:
Levels based on previous period's data
Most effective in trending markets
No repainting - uses confirmed data only
Works on all instruments and timeframes
🔧 TECHNICAL SPECS
Performance:
Pine Script v5 optimized code
Minimal CPU/memory usage
Real-time data updates
No lookahead bias
Compatibility:
All chart types (Candlestick, Bar, Line)
Any instrument (Stocks, Forex, Crypto, etc.)
All timeframes supported
Mobile and desktop friendly
Data Accuracy:
Precise floating-point calculations
Historical data integrity maintained
No future data leakage
📱 DEVICE SUPPORT
✅ Desktop browsers (Chrome, Firefox, Safari, Edge)
✅ TradingView mobile app (iOS/Android)
✅ TradingView desktop application
✅ Light and dark themes
✅ All screen resolutions
📋 VERSION INFO
Version 1.0 - Initial Release
Fibonacci-based pivot calculations
Dual timeframe support (Daily/Weekly)
Complete EMA suite (10, 20, 50, 100, 200)
RSI and ATR indicators
Fully customizable interface
Optional pivot line visualization
Smart price formatting
Mobile-optimized display
⚠️ DISCLAIMER
This indicator is designed for technical analysis, educational and informational purposes ONLY . It provides data visualization and technical calculations to help users understand market structure and price relationships.
⚠️ NOT FOR TRADING DECISIONS
This tool does NOT provide trading signals or investment advice
All data is for analytical and educational purposes only
Users should not base trading decisions solely on this indicator
Always conduct thorough research and analysis before making any financial decisions
📚 Educational Use Only
Use for learning technical analysis concepts
Study market data and indicator relationships
Practice chart reading and data interpretation
Understand mathematical calculations behind technical indicators
The Simple Technicals Table provides technical data visualization to assist in market analysis education. It does not constitute financial advice, trading recommendations, or investment guidance. Users are solely responsible for their own research and decisions.
Author: ToTrieu
Version: 1.0
Category: Technical Analysis / Support & Resistance
License: Open source for educational use
💬 Questions? Comments? Feel free to reach out!
ADRIXAUUSD - BUY/SELL (MultiTF Strategy + Labels + Alerts)This strategy is designed for XAU/USD (Gold) and can be tested on multiple timeframes (15m, 1H, 4H).
It combines several confluences for high-probability trades:
🔹 EMA Cross (Fast/Slow) to capture trend direction
🔹 Fibonacci Golden Zone retracements
🔹 Fair Value Gaps (FVG) for imbalance confirmation
🔹 ATR-based Stop Loss and Take Profit for adaptive risk management
The script works as both a backtesting strategy and a live indicator:
✅ Strategy Tester shows profit factor, win rate, and performance
✅ On-chart labels with "BUY" and "SELL"
✅ Built-in alerts for real-time notifications
Presets included:
- 15m Scalping (short-term, more trades)
- 1H Intraday (balanced)
- 4H Swing (longer-term, fewer but stronger setups)
Dual EMA (EMA Average)Simple EMA visual with 2 EMAs + Average
Includes:
2 EMAs with timeframe settings
EMA Midline - an average of EMAs
shaded space between EMA lines
FX % Change TableFX % Change Table
This tool provides currency strength analysis at a glance, allowing traders to instantly identify which currencies are outperforming or underperforming without the need to manually check each pair. It offers decision support for entries and exits by helping traders align their positions with broader strength and weakness trends, such as buying the strongest currency against the weakest. Its versatility makes it suitable for any timeframe, whether used by scalpers or swing traders. Best of all, it delivers these insights in a clean and simple format, presenting complex multi-pair calculations in an easy-to-read visual display.
This tool is especially helpful for traders who incorporate currency strength analysis, correlation checks, or basket trading into their strategy. It reduces time spent flipping through charts and provides a structured overview for smarter trade decisions.
Unlike traditional single-pair indicators, this tool calculates the percentage change between the current and previous higher timeframe closes for a group of forex pairs. You can choose between two curated groups:
• Majors – EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, NZDUSD, USDCAD
• Cross Pairs – A wide basket of EUR, GBP, AUD, NZD, CAD, and CHF crosses
For each symbol, the script requests the selected timeframe’s price data, calculates the percentage change from the previous bar’s close, and then displays it in a neatly formatted table. Green highlights strength, red highlights weakness, and gray shows neutrality — making shifts in momentum instantly recognizable.
How to Use
1. Select your timeframe – For example, "60" (1H) to view hourly change, "240" (4H) for broader moves, or "D" for daily strength/weakness.
2. Choose your group – Focus on the Majors for a macro USD view, or switch to Cross Pairs for secondary flows.
3. Position the table – Place it in any corner of your chart (top-left, top-right, bottom-left, bottom-right) to match your workspace.
The table updates dynamically at the close of each bar, ensuring the displayed data always reflects the most recent market movements.
Rapeez's BOS IndicatorIt will highlight all the BOS (Break of Structure) points on the chart with blue and red lines, making it easier to spot them without having to analyze the chart deeply. This tool is also great for identifying the overall market trend and works across all timeframes. Updates will be provided every month.
Happy charting—hope you find it helpful!
Rapid bp-meter(2Y) MTF V2.0US 2Y Yield — Basis-Point Meter (30s Fast + 1m Confirm)
What it does (one-liner):
A simple, fast basis-point (bp) meter for the US 2-Year Treasury yield that shows a 30-second “pre-trigger” and a 1-minute confirmation so you can quickly gauge risk-on / risk-off during news and FOMC events.
Overview
This tool tracks the change in the US 2-Year yield in basis points (1 bp = 0.01%). It displays two readings:
Fast: 30-second bp change (early signal).
Confirm: 1-minute bp change (confirmation).
Color logic is intentionally simple:
Green = yields down beyond your threshold (typical risk-on bias).
Red = yields up beyond your threshold (typical risk-off bias).
Gray = within thresholds (no signal).
Typical interpretation (not a signal service):
Yields ↓ (green) often align with USD weakness / risk-on (e.g., EURUSD↑, XAUUSD↑, NQ100↑, USDJPY↓).
Yields ↑ (red) often align with USD strength / risk-off (e.g., EURUSD↓, XAUUSD↓, NQ100↓, USDJPY↑).
Works on any chart. The yield is fetched from your chosen symbol/timeframes via request.security, independent of the chart timeframe.
Inputs
Yield symbol: default TVC:US02Y.
(Alternative proxy if seconds TF not available: 2-yr futures CBOT:ZT1!—note futures price ↑ = yield ↓.)
Fast timeframe: default 30S. (Use 1m if your plan/symbol doesn’t support seconds.)
Confirm timeframe: default 1 (1-minute).
Fast trigger (bp): default 2.0 bp.
Confirm trigger (bp): default 5.0 bp.
No-repaint mode: uses completed bars only. Turn off if you want intrabar responsiveness (may repaint).
Panel position: choose where the table appears on your chart.
What the table shows
2Y Δ fast (30S): e.g., −2.4 bp (green)
2Y Δ conf (1): e.g., −6.1 bp (green)
Rule of thumb
Both GREEN → risk-on bias likely (consider EURUSD/XAU/NQ long, USDJPY short).
Both RED → risk-off bias likely (consider the inverse).
Mixed → wait for alignment or price structure confirmation.
How to use (step-by-step)
Add to any chart.
Set Yield symbol to TVC:US02Y. If seconds aren’t available, keep Fast=1m and Confirm=3m (or use ZT1! as a fast proxy + US02Y confirm).
Choose Fast/Confirm thresholds. Defaults (2 bp / 5 bp) are conservative for major news (CPI/NFP/FOMC).
During events, wait for the first 1–3 minutes to pass; then act only if both readings agree and price gives a clean impulse → pullback → continuation.
Risk: size down on news; use a fixed $ risk per trade; place stops beyond the impulse origin.
Optional: enable the built-in alerts (const messages) for Fast up/down and Confirm up/down.
Alerts (included)
Fast down (pre-trigger) – “US 2Y down ≥ fast threshold → risk-on (pre-trigger)”
Fast up (pre-trigger) – “US 2Y up ≥ fast threshold → risk-off (pre-trigger)”
Confirm down (confirmed) – “US 2Y down ≥ confirm threshold → risk-on (confirmed)”
Confirm up (confirmed) – “US 2Y up ≥ confirm threshold → risk-off (confirmed)”
Tip: You can customize alert text in TradingView’s alert dialog if you want to include thresholds or tickers.
Best practices & notes
Seconds data requires the appropriate plan and symbol support. If seconds aren’t supported for US02Y, use 1m/3m or combine ZT1! (futures) for “fast” with US02Y for confirm.
No-repaint mode is recommended; turning it off will read intrabar values that can change by bar close.
The meter is directional context, not an entry by itself—combine with levels (NY H/L, VWAP, H1 S/R).
On some sessions, headline vs. core news or Powell Q&A may cause second-leg reversals; confirm with price action.
Limitations (transparent)
This tool does not predict future yields; it only reads the recent bp change on your selected timeframes.
Correlations vary; yield moves don’t always translate into the same magnitude on FX/indices/commodities.
If your broker or symbol has delays or limited intraday history, readings may differ.
Futures proxy (ZT1!) is inversely related to yield; interpretation must be inverted if you use it for the fast leg.
What “inverse to yield” means
When yields fall, bond prices rise.
TVC:US02Y = the yield itself.
CBOT:ZT1! = the price of the 2-yr note futures.
So:
US02Y ↓ (−bp) ⇢ ZT1! ↑ (price up)
US02Y ↑ (+bp) ⇢ ZT1! ↓ (price down)
That’s the “inverse” part: yield and futures price move in opposite directions.
Disclaimer
This script is for informational and educational purposes only. It does not constitute financial, investment, or trading advice, and it does not guarantee outcomes or profits. Trading involves risk, including the loss of principal. Always do your own research and use proper risk management.
Gabriel's Squeeze Momentum📊 Gabriel’s Squeeze Momentum — Deluxe Volatility + Momentum Suite
An advanced, all-in-one squeeze & momentum framework that times volatility compression/expansion and trend shifts, with optional CVD (cumulative volume delta) momentum, ATR zone context, Discontinued Signal Lines (DSL) scalps, Colored DMI trend label, Williams VIX Fix (WVF) low-volatility exhaustion pings, Buff’s VTTI/VPCI volume confirmation, and real-time divergence detection.
What it does:
Discover Squeezes. They occur when volatility contracts, often preceding significant price moves.
Measures momentum with a fast, ATR-normalized linear regression—optionally on Price or CVD—so you see direction and “how hard it’s pushing.”
🧭 Signal Legend ~ Colors the squeeze so you instantly know regime:
🟡 / 🟣 (Tight/Very Tight): Coiled spring; prepare a plan.
🔴 / ⚫ = (Regular/Wide): Watch for Divergences between Price and Momentum.
🟢 (Fired): Expansion started; trade with momentum cross and bias.
Adds context bands at ±1/±2/±3 ATR (“trend / expansion / OB-OS”) to filter late or weak signals.
DSL (Discontinued Signal Lines) give early scalp flips on momentum vs. adaptive bands.
DMI label & triangles communicate trend strength and whether +DI / −DI is in control.
Williams VIX Fix flags capitulation/exhaustion style spikes (with optional VIX proxy).
VTTI/VPCI modules confirm when volume aligns with price trend or contradicts it.
Divergences (regular & hidden) auto-draw with optional live (may repaint) or on-close.
🎢 Squeeze Momentum — How the Logic Works 🎢
The Squeeze Momentum model is built on the principle of volatility compression and expansion. In markets, periods of low volatility are often followed by explosive moves, while high volatility eventually contracts. The “squeeze” seeks to identify these compression phases and prepare traders for the likely expansion that follows.
This indicator achieves that by comparing Bollinger Bands (BB) to Keltner Channels (KC).
Bands: Bollinger vs. Keltner
Bollinger Bands (BB): Calculated using a Simple Moving Average (SMA) of price and standard deviations (σ) of the closing price. The bands expand and contract depending on volatility.
Keltner Channels (KC): Built from an SMA plus/minus multiples of the Average True Range (ATR). Unlike some simplified squeeze indicators that approximate ATR, this implementation uses a true ATR-based KC, ensuring accuracy across different assets and timeframes.
By comparing whether the Bollinger Bands are inside or outside the Keltner Channels, the indicator identifies different squeeze regimes, each representing a distinct volatility environment.
📦 Regime Colors
The squeeze states are color-coded for quick interpretation:
🔹Wide Squeeze (⚫): BB inside KC with a high ATR multiplier. Extremely low volatility, often before major expansion.
🔹Normal Squeeze (🔴): BB inside KC with a moderate ATR multiplier (about 25% more sensitive than Wide). Typical compression setting.
🔹Narrow Squeeze (🟡): BB inside KC with a lower ATR multiplier (about 50% more sensitive than Wide). Signals tighter compression.
🔹Very Narrow Squeeze (🟣): BB inside KC with the lowest ATR multiplier (100% more sensitive than Wide). Indicates extreme coiling.
🔹Fired Squeeze (🟢): BB break outside KC. Marks the release of volatility and potential trend acceleration.
This multi-layered system improves upon classical SQZPRO by using precisely calculated Keltner Channels and multiple sensitivity levels, giving traders more granular information about volatility states.
🔒 Multi-Timeframe Support
The indicator automatically adjusts squeeze thresholds for different timeframes — hourly, 4-hour, daily, weekly, and monthly charts. Each regime has been manually tuned for its timeframe, allowing traders to use the same tool whether scalping, swing trading, or holding longer-term positions.
🎯 Momentum Core
Detecting a squeeze is only half the equation — the indicator also includes a momentum engine to determine direction and strength.
Price momentum is measured as the distance of Close from its Highest High and Lowest Low range, smoothed with a Simple Moving Average, and refined with Linear Regression.
This value is then divided by ATR, normalizing momentum relative to volatility.
Optionally, CVD Mode (Cumulative Volume Delta ÷ Volume) can replace price momentum for assets where order-flow and volume dynamics dominate (e.g., crypto).
🦆 Signal Line
Momentum is paired with a Simple Moving Average signal line:
🔹Bullish: Momentum > Signal.
🔹Bearish: Momentum < Signal.
This crossover logic provides directional bias and filters for false squeezes.
🚀 When to Use Price vs. CVD
CVD Mode (Crypto, FX with tick volume): Best for assets with strong volume/order-flow signals.
Price Mode (Equities, Commodities, Higher TFs): Best for assets with irregular or thin volume data.
🛢️ATR Zones (context filter) 🛢️
Its design is straightforward yet effective: it measures the difference between the current price from its highest highs, lowest lows, and a moving average over a chosen period, then expresses that difference in terms of the Average True Range (ATR) over the same period. By normalizing price deviations against volatility, ATR provides a clear sense of how far and how fast price is moving relative to its “normal” range.
Interpreting the Zone
Positive Values: When it is above zero, price is trading above its HH, LL, and moving average, suggesting bullish momentum. The higher the value, the stronger the momentum relative to volatility.
Negative Values: When the Momentum is below zero, price is trading below its HH, LL, and moving average, signaling bearish momentum. The deeper the reading, the stronger the downside pressure.
Magnitude Matters: Because the Momentum is expressed in ATR units, traders can immediately gauge whether the move is small (less than 1 ATR), moderate (1–2 ATRs), or extreme (3+ ATRs). This makes it especially useful for assessing overbought or oversold conditions in a normalized way.
Strengths:
🔹Volatility-Normalized: Unlike simple squeeze momentum oscillators that have different OB/OS levels, this Momentum adjusts for volatility. This makes signals more consistent across assets with different volatility profiles.
🔹Simplicity:
±1 ATR: trending zone (bulls above +1, bears below −1)
±2 ATR: expansion (keep, add, or trail). Stretch/risk of mean reversion.
±3 ATR: potential exhaustion/mean-revert zone.
🔹Momentum Clarity: By framing momentum in ATR terms, it is easier to distinguish between a small deviation from trend and a genuinely significant move. Sometimes it is a good sign that it trend to ±3/2 ATR, looks for similar directional moves.
Color: The script shades +2/+3 (OB) and −2/−3 (OS) areas and provides swing alerts at ±1 ATR.
💚 What Are Discontinued Signal Lines (DSL)? 💚
In technical analysis, one of the most common tools for smoothing out noisy data is the signal line. This concept appears in many indicators, such as the MACD or stochastic oscillator, where the raw value of an indicator is compared to a smoothed version of itself. The signal line acts as a lagging filter, making it easier to identify shifts in momentum, crossovers, and directional changes.
While useful, the classic signal line approach has limitations. By design, a single smoothed line introduces lag, which means traders may receive signals later than ideal. Additionally, a one-size-fits-all smoothing process often struggles to adapt to different levels of volatility or rapidly changing market conditions.
This is where Discontinued Signal Lines (DSL) come in. DSL is an advanced extension of the traditional signal line concept. Instead of relying on just one smoothed comparison, DSL employs multiple adaptive lines that adjust dynamically to the current state of the indicator. These adaptive lines effectively “discontinue” the dependence on a single, fixed smoothing method, producing a more flexible and nuanced representation of market conditions.
How DSL Works?
Traditional Signal Line: Compares an the Momentum against its own moving average. Provides crossover signals when the raw indicator value moves above or below the smoothed line.
Strength: reduces noise. Weakness: delayed signals and limited adaptability.
DSL Extension: Uses multiple adaptive lines that respond differently to the indicator’s current behavior. Instead of one static moving average, the DSL approach creates faster and slower “reaction lines.” These lines adapt dynamically, capturing acceleration or deceleration in the indicator’s state.
Result: Traders see how momentum is evolving across multiple adaptive thresholds. This reduces false signals and improves responsiveness in volatile conditions.
Benefits of Discontinued Signal Lines
🔹Nuanced Trend Detection
DSL doesn’t just flag when momentum changes direction—it shows the quality of that shift, highlighting whether it is gaining strength, losing steam, or consolidating.
🔹Adaptability Across Markets
Because DSL adjusts to the Momentum’s own dynamics, it works well across different asset classes and timeframes, from equities and futures to forex and crypto.
🔹Earlier Signal Recognition
Multiple adaptive lines allow traders to spot developing trends earlier than with a single smoothed signal line, without being overwhelmed by raw indicator noise.
🔹Better Confirmation
DSL is particularly useful for confirmation. If both adaptive lines agree then a fill is applied in the direction, confidence in the trend is higher as the color turns bull/bear.
🔹Practical Uses
Momentum Trading: Spot acceleration or deceleration in trend strength.
Trend Confirmation: Verify whether a breakout has momentum behind it.
Noise Filtering: Smooth out erratic moves while retaining adaptability.
⚖️ Colored Directional Movement Index (CDMI) ⚖️
The Directional Movement Index (DMI), created by J. Welles Wilder, is one of the most respected trend-following indicators in technical analysis. It is actually a family of three separate indicators combined into one: the +DI (Positive Directional Indicator), the –DI (Negative Directional Indicator), and the ADX (Average Directional Index). Together, they measure not only whether the market is trending but also the strength of that trend. Traders have used the DMI for decades to identify trend direction, gauge momentum, and filter out periods of market noise.
However, despite its reliability, the traditional DMI can be challenging to interpret. Reading three separate lines at once and extracting meaningful signals requires both experience and careful observation. This complexity often discourages newer traders from fully utilizing its power.
The Colored Directional Movement Index (CDMI) is a modern reinterpretation of Wilder’s classic tool. It condenses the same information into a single visual line while using color, shape, and density to communicate what’s happening beneath the surface. The goal is simple: make the DMI’s insights faster to read, easier to act upon, and more intuitive to integrate into trading decisions.
Key Features of CDMI
🔹Color Scale for Trend Strength
The main triangle changes its base color depending on the strength of the DI reading. Dark Red or Green, colors correspond to stronger trends, while faded Gray or lighter yellow tones signal weaker or fading trends. This makes it visually clear when the market is consolidating versus trending strongly.
🔹Color Density for Momentum
Beyond strength, the CDMI uses color density to represent momentum in the trend’s strength. If the ADX is rising (trend gaining momentum), the triangles grows more darker. If the ADX is falling (trend losing momentum), the triangle becomes paler. This provides an instant sense of whether a trend is accelerating or decelerating.
🔹Directional Triangles for Trend Direction
To replace the separate +DI and –DI lines, the CDMI plots small triangle shapes along the bottom axis. An upward-facing triangle indicates that +DI is dominant, confirming bullish direction. A downward-facing triangle signals –DI dominance, confirming bearish direction. This way, both strength and direction are shown without the clutter of multiple overlapping lines.
🔹Label Display for Detailed Values
For traders who want precise data alongside the visuals, CDMI includes a label that shows:
Current trend strength (ADX value).
Current +DI and –DI values.
Momentum status of the ADX (rising or falling).
Historical values of DMI readings, so traders can track how the indicator has evolved over time.
Tooltips are also available to explain “How to read the colored DMI line”, making this version more beginner-friendly.
Why CDMI Matters
The CDMI retains the proven reliability of Wilder’s DMI while solving its biggest drawback—interpretation difficulty. Instead of juggling three separate plots, traders get a single, information-rich line supplemented with intuitive shapes and labels. This streamlined format makes trend verification, momentum analysis, and signal confirmation much faster.
For trading applications, the CDMI can help:
Confirm Entries by showing whether the market is trending strongly enough to justify a position.
Avoid False Signals by filtering out periods of low ADX (weak trend).
Enhance Timing by tracking momentum shifts in trend strength.
By simplifying the complexity of the original DMI into an elegant, color-coded tool, the CDMI makes one of technical analysis’ most advanced indicators practical for everyday use.
😅 The VIX, the Williams Vix Fix, and Market Bottoms 😎
The VIX, formally known as the CBOE Volatility Index, has long been considered one of the most reliable indicators for spotting major market bottoms. Often referred to as the “fear gauge,” it measures the market’s expectation of volatility in the S&P 500 over the next 30 days. When fear grips investors and volatility spikes, the VIX rises sharply. Historically, these moments of extreme fear often coincide with powerful buying opportunities, as markets have a tendency to rebound once panic selling exhausts itself.
Larry Williams, a well-known trader and author, developed the Williams Vix Fix as a way to replicate the insights of the VIX across any tradable asset. While the VIX itself is tied specifically to S&P 500 options, Williams wanted a tool that could capture similar panic-driven dynamics in stocks, futures, forex, and other markets where the VIX is not directly applicable. His “fix” uses price action and volatility formulas to approximate the same emotional extremes reflected in the official VIX, creating almost identical results in practice. This makes the Williams Vix Fix a powerful addition to the trader’s toolbox, allowing the same principle that works on U.S. equities to be applied universally.
One of the most important characteristics of both the VIX and the Williams Vix Fix is that they are far more reliable at signaling market bottoms than market tops. The reason is psychological as much as it is mathematical. At market bottoms, fear and panic are widespread. Retail investors often capitulate, selling in a frenzy as prices drop. This panic drives volatility higher, producing the spikes we see in the VIX. At the same time, professional traders and institutions—those with larger capital and more disciplined strategies—tend to step in when volatility is stretched. They buy when others are fearful, using the panic of retail investors as an opportunity to acquire assets at discounted prices. This confluence of retail panic and institutional buying power is what makes the VIX such a strong bottom-finding tool.
In contrast, at market tops, the dynamic is very different. Tops tend not to be marked by panic or fear. Instead, they form quietly as enthusiasm fades, liquidity dries up, and buying interest wanes. Investors are often complacent, assuming prices will continue to rise, while professional money begins distributing their positions. Because there is no surge in fear, volatility remains muted, and the VIX does not offer a clear warning. This is why traders who rely on the VIX or the Williams Vix Fix must understand its limitations: it is exceptional for detecting bottoms but less useful for anticipating tops.
For traders, the lesson is straightforward. When you see the VIX or Williams Vix Fix spiking to extreme levels, it often indicates a high-probability environment for a rebound. These tools should not be used in isolation, but when combined with support levels, sentiment indicators, and market breadth, they can provide some of the most reliable bottom-fishing signals available. While no indicator is perfect, few have stood the test of time as consistently as the VIX—and thanks to Williams’ adaptation, its power can now be applied to nearly every market.
Indicator Signals (Great in risk-off charts):
🔹Flags spike events (tops/bottoms) with both original and filtered (AE/FE) criteria.
🔹Great as a risk overlay: tighten stops into AE/FE, or require “no spike” to enter.
🤯 Volume Comfirmation: VTTI & VPCI (Buff Dormeier) 🤯
Volume Trend Technical Indicator (VTTI)
The Volume Trend Technical Indicator (VTTI) is a momentum-style tool that analyzes how volume trends interact with price movement. Unlike basic volume measures that simply report how many shares or contracts were traded, the VTTI evaluates whether volume is expanding or contracting in the same direction as the prevailing price trend. The underlying logic is that healthy trends are supported by rising volume, while weakening trends often occur on shrinking volume.
At its core, VTTI looks at the rate of change in volume compared to price movements. By smoothing and normalizing these relationships, the indicator helps traders determine whether momentum is accelerating, decelerating, or diverging.
Rising VTTI: Suggests that volume is confirming the current price trend, strengthening the case for continuation. Flips BG Green after crossing it's signal.
Falling VTTI: Indicates that the trend may be losing participation, often a sign of possible consolidation or reversal. Flips BG Red after crossing it's signal.
Traders often use VTTI to filter entries and exits. For example, if price breaks out but VTTI does not rise above zero, the breakout may lack conviction. On the other hand, when both price and VTTI are aligned, probability of continuation improves.
Volume Price Confirmation Indicator (VPCI)
The Volume Price Confirmation Indicator (VPCI), developed by Buff Dormeier, takes the relationship between price and volume a step further. While traditional indicators like On-Balance Volume (OBV) or Chaikin Money Flow look at cumulative patterns, VPCI breaks price and volume into trend and volatility components and then recombines them to measure how well they confirm each other.
In essence, VPCI asks: “Does volume confirm what price is signaling?”
The formula integrates:
Price Trend Component – whether the market is trending upward or downward.
Volume Trend Component – whether trading activity supports that price trend.
Volatility Adjustments – to account for irregular swings.
The resulting oscillator fluctuates around a zero line:
Positive VPCI: Indicates that price and volume trends are in agreement (bullish confirmation).
Negative VPCI: Suggests that price and volume are diverging (bearish warning or false move).
Crossovers of Zero: Can serve as potential buy or sell signals, depending on context.
A key strength of VPCI is its sensitivity to divergence. When prices continue rising but VPCI begins falling, it often foreshadows a weakening rally. Conversely, a rising VPCI during a flat or down market can highlight early accumulation.
VTTI (Entry Signal) vs. VPCI (Exit Signal)
While both indicators study price-volume dynamics, their focus differs:
VTTI is simpler, emphasizing the trend of volume relative to price for momentum confirmation.
VPCI is more advanced, decomposing both price and volume into multiple components to produce a nuanced oscillator.
Used together, they provide complementary insights. VTTI helps quickly spot whether volume is supporting a move, while VPCI offers deeper confirmation and highlights subtle divergences.
Note: The Up/Down Volume Alert works better on the 4 HR, for Daily scalps or 30 minute for HR scalps. Intraday it's 2/10 minute.
🦅 Divergence toolkit 🦅
Divergences in Technical Analysis
Divergence occurs when the price action of an asset moves in one direction while a technical indicator, such as RSI, MACD, or Momentum, moves in the opposite direction. This disagreement between price and indicator often signals a shift in underlying market dynamics. Traders use divergences to anticipate either potential reversals or continuations in trends.
There are two main types of divergences: regular divergences, which typically precede reversals, and hidden divergences, which suggest continuation of the current trend.
Regular Divergence (Reversal Signals)
A regular divergence occurs when price and indicator disagree during a trend extension. These divergences signal that momentum is no longer fully supporting the current trend and that a reversal may be imminent.
🔹Regular Bullish Divergence
Price Action: Forms a lower low.
Indicator: Forms a higher low.
Interpretation: Price is making new lows, but the indicator is gaining strength. This suggests that selling pressure is weakening, and a reversal to the upside may occur.
Example: RSI rising while price dips to fresh lows.
🔹Regular Bearish Divergence
Price Action: Forms a higher high.
Indicator: Forms a lower high.
Interpretation: Price is reaching new highs, but the indicator shows weakening momentum. This implies that buying pressure is fading, warning of a potential downside reversal.
Example: MACD histogram falling while price makes higher highs.
Regular divergences are often spotted near the end of trends and are most powerful when aligned with key support/resistance levels or overbought/oversold conditions.
Hidden Divergence (Continuation Signals)
A hidden divergence occurs during retracements within a trend. Unlike regular divergences, hidden divergences suggest that the prevailing trend still has strength and is likely to continue.
🔹Hidden Bullish Divergence
Price Action: Forms a higher low.
Indicator: Forms a lower low.
Interpretation: Price is retracing within an uptrend, but the indicator is overshooting downward. This shows that momentum remains intact, supporting continuation upward.
🔹Hidden Bearish Divergence
Price Action: Forms a lower high.
Indicator: Forms a higher high.
Interpretation: Price is retracing within a downtrend, while the indicator overshoots upward. This indicates that bearish momentum remains strong, supporting continuation downward.
Hidden divergences often appear during pullbacks, helping traders time entries in the direction of the prevailing trend.
Practical Use of Divergences
🔹Trend Reversal Alerts – Regular divergences are early warnings that a trend may be ending.
🔹Trend Continuation Signals – Hidden divergences help confirm that retracements are simply pauses, not full reversals.
🔹Confluence with Other Tools – Divergences are more reliable when combined with support/resistance, candlestick patterns, or volume analysis.
🔹Multi-Timeframe Analysis – Spotting divergences on higher timeframes often produces stronger signals.
🕭🔔🛎️ Alert 🛎️🔔🕭
🔹Squeeze
🟢 Fired Squeeze
⚫ Low (Wide) Squeeze / 🔴 Normal / 🟡 Tight / 🟣 Very Tight
🔹Momentum
🐂 Bullish Trend Reversal (Crossover of Momentum and Signal from sub −2)
🐻 Bearish Trend Reversal (Crossover of Momentum and Signal from above +2)
📈 Bullish Swing (cross above +1 ATR) / 📉 Bearish Swing (cross below −1 ATR)
🔹DSL
💚 Bullish DSL Scalp / 💔 Bearish DSL Scalp
🔹Volume
🎯 Strong Up Volume (VPCI > 0 and VTTI up)
⏳ Strong Down Volume (VPCI < 0 and VTTI down)
🔹Divergences
🦅 Bullish, 🦆 Bearish, 🦅 Bullish Hidden, 🦆 Bearish Hidden
Management: Search Vanguard ETFs in your browser, look up full list of VOO holdings. Download it, or copy paste all the ticker symbols. Place that with a AI, just ask it to place , in between each ticker. NVDA, TSLA, AVGO, etc. Create a new watchlist, in the + add all tickers separated by commas. Place a watchlist alert ⚠️ only available for premium + subscribers.
Practical playbook
1) Classic Squeeze Break
Setup: 🔴(D)/🟡(2D)/🟣(3D) squeeze → wait for 🟢(1HR) Fired.
Confirm: Momentum > Signal and above +1 ATR (or DMI strong & rising).
Manage: add on pullbacks that hold +1 ATR; scale near +2 ATR or WVF AE/FE.
2) DSL Scalp in Trend
Setup: Clear trend (DMI strong) + DSL bull/bear trigger in the direction of trend.
Filter: avoid tight/very tight yellow/purple unless you want micro-scalps.
Exit: opposite DSL or ATR midline loss.
3) Mean-Reversion Fade
Setup: Momentum extended to ±3 ATR, WVF spike, and a regular divergence.
Entry: Counter signal only when mom crosses back through ±3 ATR toward mid. Exit early if squeeze ⚫/🔴, Momentum may extend to ±3/2 ATR in the same direction.
Risk: reduce size; this is a fade, not trend following.
4) Volume-Confirmed Breakout
Setup: Squeeze → 🟢 Fired + VPCI > 0 and VTTI up → trend continuation.
Manage: trail behind +1 ATR (long) or −1 ATR (short). 9 SMA works good.
Inputs at a glance (key ones)
Mode: Price or CVD momentum; Squeeze Sensitivity (σ); Momentum Length; Signal Length; ATR Smoothing.
🧮 Colors:
SQZMOM: per squeeze regime, momentum, ATR fills.
DSL: On/Off, Fast/Slow, Length.
ATR Zones: Bullish/Bearish levels (±1), ±2/±3 zone lines & fills.
DMI: Lengths, key & weak thresholds, label on/off.
WVF/VIX: Lookbacks, bands, AE/FE toggles, VIX proxy symbol.
VTTI/VPCI: Fast/slow/signal (VTTI), Short/Long (VPCI), and volume source (Tick/CVD/NVI/PVI/OBV/PVT/AccDist/VWAP).
Divergences: Regular/Hidden toggles, Sensitivity %, Lifetime, Live vs On-Close, Lines/Labels.
🔎 Suggested defaults (feel free to tweak)
Calibration: Size Momentum, so that when it's above zero the asset is trending up. For the signal, it can be kept the same or lower.
Intraday (60–240m): σ = 2.0, 18~20, 3~5, DSL Fast, DMI key 23, weak 17.
Daily/Weekly: keep σ = 2.0, consider DSL Slow, DMI key 25, weak 20, widen ATR filters; lean on VPCI/VTTI (4-HR).
CVD mode: use where tick/volume quality is high (index futures, liquid equities, crypto majors).
🪟 Tips & caveats
Swing Screener: Favor liquid underlyings (index futures/ETFs, large caps). Large-Cap, 2 M Vol, Mid-Cap, 500K Vol. Squeeze: BB( 20) upper < KC (20) upper, and BB (20) lower > KC (20) lower. Optional: Price above 9 SMA, 21 SMA, and 50 SMA, they are my SMA of choice. 200 SMA too, unless you are willing to fish in a bear market. Vice-versa for shorts. Optional: ADX 4 HR > 17, or 23 depending on what you are looking for.
Scalp Screener: Same as above, change the D 9 SMA to 5, and the BB/KC from D to 1 HR. Scalps may last 2~3 days.
Position Screener: Change all daily setting to W, aside from Volume. Optional: PEG < 1.5, FCF > 0, ROA > 8% or ROE > 6%.
Good with Moving averages (9/21/50) and low-volume zones.
Position size by IV, ATR, and account risk. Consider stop/hedge rules around ±2/±3 ATR.
Let alerts stage your watchlist; act only on combined squeeze + momentum signals.
Divergences in live mode can repaint (Real-Time); for algo or alerts, use on-close.
Tight/Very tight squeezes are great for scalps but choppy; combine with DMI rising + VPCI>0.
±3 ATR is exhaustion context, not an auto-fade—look for WVF/Div/DSL confirmation.
For alerts, pair “Fired Squeeze + Bullish Swing” (or bearish) to avoid false starts.
🎯 How to Trade Entry ~ Recap:
Tight/very tight squeeze → fires → momentum crosses up (or DSL bull).
Exit/Flip: Momentum crosses down into/after expansion or hits +2/+3 ATR with fade signs. Filter: Avoid fresh longs at +3 ATR; avoid fresh shorts at −3 ATR unless fading with confirmation.
📐 Options Integrations
✅ Risk Reversal/Modified Risk Reversal (Bullish: Short Put + Long Call)
Use when: Squeeze fires up from 🟡/🟣 and momentum crosses above signal (or zero/DSL).
Playbook Entry: On or just after the bullish fire and momentum upcross. DMI or Volume supports trend as well.
Structure: Sell a put at/just below the −2 ATR reference (or recent swing support). Buy a call at/above the breakout zone (prior high/mid-range +1 to +2 ATR).
A classic risk reversal is a long call plus a short put. That’s a very bullish structure—you gain if the price rallies (via the call), and you collect a premium by selling a put. But it has a naked downside risk. The modified risk reversal fixes that by adding a long lower put (making the short put into a defined put credit spread).
Management: If momentum stays above signal, ride toward +2 → +3 ATR. Sell the put near the current price → receive big premium. Buy the lower put → spend part of that premium (risk cap). Buy the call above the current price → spend more, but the short put premium mostly pays for it.
Exits/Adjust: Momentum downcross or squeeze flips back on (new compression) → reduce. If price retests −1/−2 ATR and holds, you can roll the short put down/out.
Breakout = Big Success; No Breakout = you keep the initial credit. Reversal = Max loss is capped by the long lower put.
✅ Iron Condor (Neutral: Short OTM Put Spread + Short OTM Call Spread)
Use when: Squeeze is active (🟡/🟣), momentum is flat near zero, and there is no directional edge. 🟢 lasts for around 5~8 bars typically. I measure the historical duration of it, and wait for a range period to occur.
Playbook Entry: During compression, set wings outside ±2 ATR (or recent range extremes). I prefer identifying boxes where the rectangle pattern occurs on the chart.
Management: Time decay works while price remains trapped in the coil. High-winrate ~80%, but 1 loser can wipe most of the gains.
Exits/Adjust: If a squeeze fires and momentum breaks hard one way, close the losing side, consider converting to a vertical or rotating to a directional spread aligned with momentum.
4HR-Bullish, closing one wing:
Tip: Align daily/weekly context with your intraday entries. 9 > 50 on Weekly, similar on Daily. Sell premium into compression; switch to directional spreads on expansion and momentum confirmation.
✅ Naked Call/Puts (Directional: 10~30 Delta Calls)
Stick to naked calls and puts when the squeezes are fired from either 🔴 or ⚫.
Look for Strikes slightly out of the money with an OI and Volume spread less than <10%.
If Strike Date is >45, manage 21 Days before expiration. Scalp: Expiration Strikes of 1/4 of the Squeeze period. Leap: Expiration Strikes of 1.75x of the Squeeze period.
📐 Futures Integrations
Playbook Entry:
Verify if the squeeze on the hourly is red or green, and enter on the 2- or 5-minute during a similar squeeze state.
Trend-Following: Traditional 2 Renko Block above 21 SMA and Momentum is bullish, or vice versa. (2~ES, 5~NQ)
Structure: Go long at/just below the ATR reference (or recent swing support). Exit below the breakout zone (prior high/mid-range +1 to +2 ATR).
Management: If momentum stays above +1 ATR ride toward +2 → +3 ATR, etc. House-money, should be kept.
Exits/Adjust: Momentum downcross or squeeze flips back on (new compression) → exit. On Renko Charts, lower the sensitivity to 0.7~1. If price retests 0/−1/−2 ATR and holds, you can enter when the 9 SMA flips. The 50 SMA is better for Daily and up; I wouldn't trade against it then.
📌 FOMO Trading Playbook
Credits & License
Credits: @JF10R (Multi-Timeframe Squeeze), @BigBeluga (DSL), @OskarGallard (Colored DMI base), @ChrisMoody (WVF ideas), @PineCodersTASC (VTTI/VPCI), @EliCobra (Divergence toolkit).
License: Mozilla Public License 2.0 (MPL-2.0).
Author: © GabrielAmadeusLau
