FVG HTF# FVG HTF — Higher‑Timeframe Fair Value Gaps
## Summary
- Plots higher‑timeframe Fair Value Gap (FVG) zones directly on your current chart.
- Tracks fill progress using four methods: Any Touch, Midpoint Reached, Wick Sweep, Body Beyond.
- Shows optional labels with timeframe source and live fill percentage; label text color is configurable.
- Designed for clean overlays and efficient rendering with limits on graphics and bars processed.
## What It Does
- Detects bullish and bearish FVGs from a chosen timeframe (or the chart timeframe) and renders:
- Zone Top/Bottom lines and a dotted midpoint line
- Semi‑transparent area fill between the edges
- Optional label at the midpoint with a tooltip showing zone prices
- Continuously updates zones forward and removes them when the selected fill condition is met.
## Inputs
- `Enable FVG` (`fvgSH2`): Toggle detection/plotting on/off.
- `Timeframe` (`fvgTF2`): Choose `Chart` or HTFs (`5 Minutes`, `15 Minutes`, `1 Hour`, `4 Hours`, `1 Day`, `1 Week`, `1 Month`).
- `Fill Method` (`fvgFill2`):
- Any Touch — wick or body touches any part of the zone
- Midpoint Reached — price reaches at least the 50% of the zone
- Wick Sweep — wick fully travels past the far edge and back inside (conceptually stricter than touch)
- Body Beyond — candle body closes beyond the opposite edge (strong confirmation)
- `Zones` colors (`fvgCb2`, `fvgCs2`): Bullish/Bearish zone colors.
- `Labels` (`fvgLB2`): Show/Hide on‑chart labels.
- `Label Color` (`fvgLBc2`): Color picker for label text (default: white).
- `Max Bars Back` (`maxBars2`): Limits processing to recent bars for performance.
## Timeframe Rules
- The helper `htfTF` prevents selecting a timeframe lower than the chart. If an invalid lower TF is chosen, it falls back to `timeframe.period`.
- Supports minute, daily, weekly, and monthly aggregations that are safe for intraday/daily/weekly charts.
## Detection Logic
- Uses rolling higher‑timeframe bars constructed on the fly and checks 3‑bar displacement patterns:
- Bullish FVG: current HTF low above the high two bars ago AND previous HTF close above that high, with no direct gap condition.
- Bearish FVG: current HTF high below the low two bars ago AND previous HTF close below that low, with no direct gap condition.
- On detection, the script creates an FVG object with:
- Top/Bottom lines (`lnTop`, `lnBtm`) and midpoint line (`lnAvg`)
- Midpoint label (`lbTxt`) showing source timeframe and updating fill percentage
- Semi‑transparent fill (`linefill`) for visual clarity
## Fill Tracking
- Fill threshold depends on selected method:
- Any Touch: opposite edge
- Midpoint Reached: zone’s midpoint
- Wick Sweep: stricter condition conceptually (implemented as an opposite‑edge threshold)
- Body Beyond: requires close beyond the opposite edge
- Each bar updates label x‑position and line endpoints forward; the label text shows the best fill ratio achieved.
- When the threshold is reached, the FVG (label, lines, fill) is removed from the chart.
## Best Practices
- Start with `Any Touch` to visualize broad repairs; switch to `Body Beyond` for conservative confirmations.
- Use `1 Hour` or `4 Hours` overlays on 5m–15m charts for context; `1 Day` on 1H charts; `1 Week` on daily charts.
- Keep labels on when monitoring fills intraday; hide labels for clean higher‑level context.
- Adjust `Max Bars Back` if performance is impacted by many zones.
## Repainting Notes
- HTF zones are computed on `timeframe.change(tf)` and therefore confirm on HTF bar closes.
- Label endpoints extend each bar; detection itself avoids lookahead bias. For strict confirmation, align entries with HTF closes.
## Limitations
- “Wick Sweep” is treated as a stricter touch to the far edge; it does not enforce a separate “return inside” bar state.
- Label text color applies uniformly to bull/bear labels. If you need separate colors per side, contact the author.
## Credits & Version
- Pine Script v6; © rithsilanew2020
## Quick Start
1. Enable FVG and choose your HTF (e.g., `1 Hour`).
2. Pick a Fill Method (start with `Any Touch`).
3. Select zone colors and label text color.
4. Set `Max Bars Back` as needed for performance.
5. Use labels/tooltip values (Top/Mid/Bottom) to plan entries and manage risk.
Cerca negli script per "track"
HTF Candles Pro by MurshidFx# HTF Candles Pro by MurshidFx
## Professional Trading Indicator for Multi-Timeframe Market Structure Analysis
**HTF Candles Pro** is an advanced, open-source trading indicator that synthesizes Higher Timeframe (HTF) candle visualization with CISD (Change in State of Delivery) detection, providing comprehensive market structure analysis across multiple timeframes. Designed for traders at all experience levels—from scalpers to swing traders—this tool enables precise alignment of trades with higher timeframe momentum while identifying critical market structure transitions.
---
## Core Functionality
This indicator integrates three essential analytical frameworks:
- **HTF Candle Visualization** – Inspired by the innovative work of Fadi x MMT's MTF Candles indicator
- **CISD Detection System** – Algorithmic identification of significant market structure reversals
- **Intelligent Session Level Management** – Automated consolidation of overlapping session markers for enhanced chart clarity
The result is a sophisticated yet streamlined analytical tool that delivers actionable market insights with minimal visual complexity.
---
## Feature Set
### Higher Timeframe Candle Analysis
Monitor higher timeframe price action seamlessly without chart switching. The indicator employs automatic HTF selection based on current timeframe, with manual override capability.
**Components:**
- **Primary HTF Display**: Automatically positioned adjacent to current price action
- **Secondary HTF Display**: Optional dual-timeframe analysis capability
- **Adaptive Time Labeling**: Context-aware formatting (intraday times, day names, week numbers)
- **Real-Time Countdown**: Optional timer displaying remaining time until HTF candle close
- **Customizable Color Schemes**: Full color customization for bullish and bearish candles
### CISD Detection (Change in State of Delivery)
The CISD system identifies critical inflection points where market structure undergoes directional change, signaling potential trend reversals or continuations.
**Mechanism:**
- **Market Structure Monitoring**: Continuous tracking of swing highs and lows
- **Liquidity Sweep Detection**: Identification of stop-hunt patterns preceding reversals
- **Reversal Confirmation**: Validation-based CISD level plotting upon structure break confirmation
- **Clear Visual Signals**: Bullish CISD (blue) and bearish CISD (red) demarcation
- **Optimized Display**: Default 5-bar line length (adjustable) minimizes chart clutter
**Technical Definition:**
CISD occurs when price breaches structure in one direction—typically sweeping liquidity and triggering stops—then reverses to break structure in the opposite direction, indicating a fundamental shift in market delivery bias.
### Intelligent Session Level Management
Eliminates visual clutter caused by overlapping session opens at identical price levels through automated consolidation.
**Functionality:**
- **Automatic Consolidation**: Merges multiple concurrent session opens into single reference lines
- **Combined Labeling**: Creates unified labels (e.g., "Week-Day Open," "4H-Day-Week Open")
- **Enhanced Clarity**: Maintains professional chart aesthetics while preserving all relevant information
**Supported Session Intervals:**
- 30-Minute Opens
- 4-Hour Opens
- Daily Opens
- Weekly Opens
- Monthly Opens
### Advanced Market Structure Tools
**Liquidity Sweep Identification:**
Highlights price wicks extending beyond previous HTF extremes that close within range—characteristic liquidity grab patterns.
**HTF Midpoint Reference:**
Displays the 50% retracement level of the most recent completed HTF candle, serving as a key reference for entries and profit targets.
**HTF Opening Price:**
Tracks current HTF candle open price, frequently functioning as dynamic support or resistance.
**Interval Demarcation:**
Visual separators defining HTF period boundaries for enhanced temporal clarity.
### Information Dashboard
Compact, customizable dashboard displaying:
- Current symbol and active timeframe
- HTF candle countdown timer
- Active trading session (Asia/London/New York)
- Current date and time
Flexible positioning: configurable for any chart corner.
---
## Default Configuration
Optimized settings for immediate professional-grade chart presentation:
- **Secondary HTF**: Disabled (enable for multi-timeframe comparative analysis)
- **CISD Bullish Color**: Blue (#0080ff) – optimal visibility with reduced eye strain
- **CISD Line Width**: 1 pixel – subtle yet discernible
- **CISD Line Length**: 5 bars – balanced visibility without excessive clutter
- **Session Opens**: Smart consolidation enabled – eliminates overlapping labels
---
## Application Strategies
### Trend Following
1. Monitor CISD confirmations aligned with HTF trend direction
2. Utilize HTF candle color for directional bias confirmation
3. Execute entries on pullbacks to HTF midpoint or open price levels
### Reversal Trading
1. Identify counter-trend CISD formations
2. Await HTF candle close confirming new directional bias
3. Use session opens as secondary confirmation levels
### Scalping
1. Trade exclusively in HTF candle direction
2. Employ lower timeframe CISD signals for precise entry timing
3. Target HTF midpoint or subsequent session open levels
### Structure-Based Trading
1. Mark liquidity sweep levels as potential reversal zones
2. Monitor CISD formations at key session opens
3. Confirm trend changes via HTF candle closes
---
## Customization Parameters
Comprehensive customization options:
- **Color Schemes**: Independent control of bull/bear candles, borders, CISD signals, session levels
- **Dimensional Settings**: Candle width, line thickness, label sizing
- **Display Quantities**: HTF candle count (1-10 range)
- **Positioning**: Candle offset, dashboard placement, label positioning
- **Line Styles**: Solid, dashed, or dotted rendering
- **Timeframe Selection**: Manual secondary HTF specification
---
## Attribution
**HTF Candle Visualization:**
The HTF candle rendering methodology draws inspiration from Fadi x MMT's "MTF Candles" indicator. Their elegant implementation of multi-timeframe candle visualization provided valuable reference for this development. Recognition and appreciation to their contribution to the TradingView community.
**CISD Detection:**
Proprietary CISD detection algorithm engineered to identify market structure transitions with high signal clarity and reduced false positive rate.
**Session Level Consolidation:**
Custom-developed intelligent grouping system addressing the common challenge of overlapping session labels at coincident price levels.
---
## Open Source License
This indicator is released as open source for the TradingView community. Permitted uses include:
- Implementation in live trading
- Educational study for Pine Script learning
- Personal modification and customization
- Distribution among trading communities
Community contributions, improvements, and derivative works are welcomed and encouraged.
---
## Implementation Guide
1. **Installation**: Click "Add to Chart"
2. **Configuration Access**: Open indicator settings panel
3. **Initial Use**: Default settings provide optimal starting configuration
4. **Optional Features**: Enable secondary HTF for multi-timeframe analysis
5. **Theme Integration**: Adjust color schemes to match chart aesthetics
---
## Best Practices
**Timeframe Optimization:**
- 1-5 minute charts: Optimal with 15m or 1H HTF
- 15-30 minute charts: Effective with 4H HTF
- 1-4 hour charts: Suitable for Daily HTF
- Daily charts: Best utilized with Weekly/Monthly HTF
**CISD Trading Guidelines:**
- Require CISD confirmation before position entry
- Prioritize CISD signals at significant levels (session opens, HTF midpoints)
- Confirm CISD direction aligns with HTF candle bias
- Apply contextual filtering—not all CISD signals warrant trades
**Session Open Strategy:**
- Weekly opens typically provide robust support/resistance
- Daily opens offer reliable intraday reference points
- 4-Hour opens effective for short-term scalping
- Consolidated labels (e.g., "Week-Day Open") indicate confluence zones with elevated significance
---
## Technical Specifications
**Performance Optimization:**
- Intelligent object management prevents TradingView rendering limits
- Efficient array processing for session consolidation
- Proper memory management through systematic object deletion
- Consistent performance across all timeframe ranges
**Compatibility:**
- Universal timeframe support
- Optimized for all market types (forex, stocks, crypto, futures)
- Minimal computational overhead
---
## Support & Development
**Feedback Channels:**
- Comment section for user feedback and suggestions
- Bug reports and feature requests welcomed
- Community-driven enhancement consideration
**Documentation:**
- Well-commented source code for learning purposes
- Clear section organization for easy navigation
- Comprehensive type definitions for structural clarity
- Educational value for market structure concept understanding
---
## Version Information
**Version:** 1.0 (Initial Release)
**License:** Open Source
**Category:** Multi-Timeframe Analysis | Market Structure
**Compatibility:** All Timeframes
**Language:** Pine Script v5
---
**For optimal results:**
- Provide feedback through comments
- Share with trading communities
- Submit enhancement suggestions
- Report technical issues for resolution
**Professional Support:**
Available through comment section for technical inquiries, implementation questions, and feature requests.
---
*Developed for the TradingView trading community | Professional-grade market structure analysis | Open source contribution*
Reduced-Lag Chande Momentum Oscillator [BOSWaves]Reduced-Lag Chande Momentum Oscillator – Adaptive Momentum Geometry with Reduced-Latency Reversion Logic
Overview
The Reduced-Lag Chande Momentum Oscillator represents a sophisticated extension of the classical Chande Momentum Oscillator, preserving the foundational measurement of net directional pressure while addressing inherent limitations in lag, noise, and signal clarity. The traditional CMO provides reliable snapshots of upward versus downward force but reacts slowly to rapid market accelerations and can obscure meaningful momentum inflections with delayed readings. This iteration integrates a dual-stage reduced-lag filter, optional advanced smoothing, and acceleration-based analytics, producing a real-time, multi-dimensional representation of market momentum.
The design reframes classical momentum using a layered curvature and gradient structure - main, midline, and shadow - to show trajectory, velocity, and intensity in one view. Instead of the usual ±70/30 extremes, it uses ±50 as a statistically grounded threshold where one side of the market begins exerting true dominance. This captures structural imbalance more reliably, exposing exhaustion and actionable inflection without amplifying noise.
This visualization gives traders a continuous, responsive read on market structure, revealing not just direction but rate of change, acceleration alignment, and curvature behavior. The oscillator becomes a momentum map, expressing both probability and intensity behind directional shifts.
Where conventional oscillators mislabel short-lived swings as signals, the Reduced-Lag CMO separates baseline shifts from high-conviction transitions, enabling cleaner, more decisive signal interpretation.
Theoretical Foundation
The classical Chande Momentum Oscillator, created by Tushar Chande, calculates the normalized net difference between consecutive upward and downward price changes over a defined window, generating readings from –100 to +100. While effective for capturing basic directional pressure, the unmodified CMO suffers from signal latency and sensitivity to abrupt market swings, which can obscure actionable inflection points.
The Reduced-Lag CMO augments this foundation with three key mechanisms:
Reduced-Lag Filtering : A dual-EMA structure eliminates inertial lag, aligning the oscillator curve closely with real-time market momentum without producing overshoot artifacts.
Smoothing Architecture : Optional SMA, EMA, or WMA smoothing is applied post-filter, balancing noise reduction with trajectory fidelity. A multi-layer line system (shadow → midline → main) communicates depth, curvature, and gradient dynamics.
Acceleration Integration : First and second derivatives of the smoothed curve quantify velocity and acceleration, allowing the indicator to identify not only momentum flips but the force behind each shift, forming the basis for the strong-signal overlay.
The combination of these mechanisms produces an oscillator that respects the original CMO framework while delivering real-time, context-sensitive intelligence. The ±50 boundaries are selected as the statistically validated pressure zones where directional dominance exceeds neutral oscillation. Crosses and rejections at these boundaries are not arbitrary overbought/oversold events, but measurable imbalances with actionable significance.
How It Works
The Reduced-Lag CMO is constructed through a multi-stage process:
Momentum Estimation Core : Raw CMO values are calculated and then passed through a reduced-lag filter to remove delay, creating a curve that closely tracks instantaneous directional pressure.
Smoothing & Layered Representation : The filtered curve can be smoothed and split into three layers - shadow, midline, and main - giving visual depth, trajectory clarity, and curvature instead of a single-line oscillator.
Gradient-Based Pressure Mapping : Color gradients encode momentum strength and polarity. Green-yellow transitions highlight increasing upward dominance, while red-yellow transitions indicate weakening downward force.
Pressure-Zone Anchoring (±50) : The system defines statistically significant pressure zones at ±50. Moves beyond these levels reflect dominant directional control, and rejections inside the zone signal potential exhaustion.
Signal Generation : Momentum events are evaluated through velocity and acceleration. Standard signals appear as triangle markers indicating validated momentum flips. Strong signals appear as triangles with diamonds when acceleration confirms a high-conviction transition.
A cooldown rule spaces signals apart to reduce clutter and emphasize structurally meaningful events.
Interpretation
The Reduced-Lag CMO reframes momentum as a dynamic equilibrium between directional force and structural pressure:
Positive Momentum Phases : Curves above zero with green-yellow gradients indicate sustained upward pressure. Shallow retracements or midline tests denote controlled pullbacks.
Negative Momentum Phases : Curves below zero with red-yellow gradients show downward dominance. Rejections from –50 highlight potential exhaustion and reversal readiness.
Pressure-Zone Dynamics (±50) : Crosses beyond ±50 confirm dominant directional force. Meanwhile, rejections and rotations inside the zone signal structural fatigue.
Velocity & Acceleration Analysis : Rising momentum with decelerating velocity suggests fading force; acceleration alignment amplifies signal strength and forms the basis of strong signals.
Signal Architecture
The Reduced-Lag CMO produces a single event type with two intensities: a validated momentum inflection.
Standard Signals - Triangles:
Triggered by momentum flips confirmed by velocity.
Represent moderate-intensity directional changes.
Appear at zero-line crosses or ±50 rejections with aligned velocity.
Strong Signals Triangles + Diamonds:
Triggered when acceleration confirms the directional change.
Represent high-intensity, high-conviction shifts.
Rare by design; indicate robust momentum inflections.
Cooldown mechanics prevent repeated signals in short succession, emphasizing structural reliability over noise.
Strategy Integration
Trend Confirmation : Align zero-line flips with higher-timeframe directional bias.
Reversal Detection : Strong signals from ±50 zones highlight potential inflection points.
Volatility Assessment : Gradient transitions reveal strengthening or weakening momentum.
Pullback Timing : Multi-layer curvature identifies controlled retracements vs trend exhaustion.
Confluence Mapping : Pair with structure-based indicators to filter signals in context.
Technical Implementation Details
Core Engine : Classical CMO with Ehlers reduced-lag extension
Lag Reduction : Dual EMA filtering
Smoothing : Optional SMA/EMA/WMA post-filter
Multi-Layer Curve : Shadow, midline, main
Signal System : Two-tier momentum-acceleration framework
Pressure Zones : ±50 statistically validated thresholds
Cooldown Logic : Bar-indexed suppression
Gradient Mapping : Encodes magnitude and direction
Alerts : Standard and strong signals
Optimal Application Parameters
Timeframes:
1 - 5 min : Intraday momentum tracking
15 - 60 min : Trend rotations & volatility transitions
4H - Daily : Macro momentum exhaustion & re-accumulation mapping
Suggested Ranges:
CMO Length : 7 - 12
Reduced-Lag Length : 5 - 15
Smoothing : 10 - 20
Cooldown Bars : 5 - 15
Performance Characteristics
High Effectiveness:
Markets with directional pulses & clean pressure transitions
Trending phases with measurable pullbacks
Instruments with stable volatility cycles
Reduced Edge:
Choppy consolidations
Ultra-low volatility environments
Disclaimer
The Reduced-Lag Chande Momentum Oscillator is a professional-grade analytical tool. It is not predictive and carries no guaranteed profitability. Effectiveness depends on asset class, volatility regime, parameter selection, and disciplined execution. Any suggested application timeframes or recommended ranges are guidance only - they are not universally optimal and will not deliver consistent accuracy on every asset or market condition. BOSWaves recommends using it in conjunction with structure, liquidity, and momentum context.
YCGH ATH DrawdownHow the Indicator Measures Drawdown from ATH
The indicator continuously tracks and calculates the percentage decline from the all-time high (ATH) using a systematic approach.
ATH Tracking Mechanism
Dynamic ATH Calculation: The script maintains a persistent variable that stores the highest price ever reached. On each bar, it compares the current high with the stored ATH using ath := math.max(ath, high), updating the ATH whenever a new peak is reached.
Smart VWAP FVG SystemSmart VWAP FVG System - Professional Multi-Filter Trading Indicator
📊 OVERVIEW
The Smart VWAP FVG System is an advanced multi-layered trading indicator that combines institutional volume analysis, multi-timeframe VWAP trend confirmation, and Fair Value Gap detection to identify high-probability trade entries. This indicator uses a sophisticated filtering mechanism where signals appear only when multiple independent confirmation criteria align simultaneously.
Recommended Timeframe: 5-minute (M5) or higher. The indicator works best on M5, M15, and M30 charts for intraday trading.
🎯 ORIGINALITY & PURPOSE
This indicator is original because it combines three distinct analytical methods into a unified decision-making system:
Market Profile Volume Analysis - Identifies institutional accumulation/distribution zones
Dual VWAP Filtering - Confirms trend direction using two independent VWAP calculations
Fair Value Gap Detection - Validates institutional interest through price inefficiency zones
The key innovation is the directional filter system: the primary Market Profile generates BUY-ONLY or SELL-ONLY states based on higher timeframe value area reversals, which then controls which signals from the main system are displayed. This creates a multi-timeframe confluence that significantly reduces false signals.
Unlike simple indicator mashups, each component serves a specific purpose:
Market Profile → Direction bias (trend filter)
Primary VWAP (Session) → Short-term trend confirmation
Secondary VWAP (Week) → Medium-term trend confirmation
FVG Detection → Institutional activity validation
🔧 HOW IT WORKS
1. Primary Market Profile Filter (Higher Timeframe)
The indicator calculates Market Profile on a higher timeframe (default: 1 hour) to determine the overall market structure:
Value Area High (VAH): Top 70% of volume distribution
Value Area Low (VAL): Bottom 70% of volume distribution
Point of Control (POC): Price level with highest volume
When price reaches VAH and reverses down → SELL-ONLY mode activated
When price reaches VAL and reverses up → BUY-ONLY mode activated
This higher timeframe filter ensures you're trading in the direction of institutional flow.
2. Dual VWAP System
Two independent VWAP calculations provide multi-timeframe trend confirmation:
Primary VWAP (Session-based): Resets daily, tracks intraday momentum
Secondary VWAP (Week-based): Resets weekly, confirms longer-term trend
Filter Logic:
BUY signals require: Price > Primary VWAP AND Price > Secondary VWAP
SELL signals require: Price < Primary VWAP AND Price < Secondary VWAP
This dual confirmation prevents counter-trend trades during ranging conditions.
3. Fair Value Gap (FVG) Detection
FVG zones identify price inefficiencies where institutional orders were executed rapidly:
Bullish FVG: Gap between candle .high and candle .low (upward imbalance)
Bearish FVG: Gap between candle .high and candle .low (downward imbalance)
The indicator monitors recent FVG formation (lookback: 50 bars) and requires:
Bullish FVG present for BUY signals
Bearish FVG present for SELL signals
FVG zones are displayed as colored boxes and automatically marked as "mitigated" when price fills the gap.
4. Main Trading Signal Logic
The secondary Market Profile (default: 1 hour) generates the actual trading signals:
BUY Signal Conditions:
Price reaches Value Area Low
Reversal pattern confirmed (minimum 1 bar)
Price > Primary VWAP
Price > Secondary VWAP (if filter enabled)
Recent Bullish FVG detected (if filter enabled)
Primary MP Filter = BUY-ONLY or NEUTRAL
SELL Signal Conditions:
Price reaches Value Area High
Reversal pattern confirmed (minimum 1 bar)
Price < Primary VWAP
Price < Secondary VWAP (if filter enabled)
Recent Bearish FVG detected (if filter enabled)
Primary MP Filter = SELL-ONLY or NEUTRAL
All conditions must be TRUE simultaneously for a signal to appear.
📈 VISUAL ELEMENTS
On Chart:
🟢 Green Triangle (▲) = BUY Signal
🔴 Red Triangle (▼) = SELL Signal
🟦 Blue horizontal lines = Value Area zones
🟡 Yellow line = Point of Control (POC)
🟩 Green boxes = Bullish FVG zones
🟥 Red boxes = Bearish FVG zones
🔵 Blue line = Primary VWAP (Session)
⚪ White line = Secondary VWAP (Week)
Info Panel (Top Right):
Real-time status display showing:
Filter Direction (BUY ONLY / SELL ONLY / NEUTRAL)
Active timeframes for both MP filters
FVG filter status and count
VWAP positions (ABOVE/BELOW)
Signal enablement status
Alert status
⚙️ KEY SETTINGS
MP/TPO Filter Settings (Primary Indicator)
MP Filter Time Frame: 60 minutes (controls directional bias)
Filter Value Area %: 70% (standard Market Profile calculation)
Filter Alert Distance: 1 bar
Filter Min Bars for Reversal: 1 bar
Filter Alert Zone Margin: 0.01 (1%)
FVG Filter Settings
Use FVG Filter: Enabled (toggle on/off)
FVG Timeframe: 60 minutes (1 hour)
FVG Filter Mode: Both (require bullish FVG for BUY, bearish for SELL)
FVG Lookback Period: 50 bars (how far back to search)
Show FVG Formation Signals: Optional visual markers
Max FVG on Chart: 50 zones
Show Mitigated FVG: Display filled gaps
Market Profile Settings
Higher Time Frame: 60 minutes (for main signals)
Percent for Value Area: 70%
Show POC Line: Enabled
Keep Old MPs: Enabled (maintain historical profiles)
Primary VWAP Filter
Use Primary VWAP Filter: Enabled
Primary VWAP Anchor Period: Session (resets daily)
Primary VWAP Source: HLC3 (typical price)
Secondary VWAP Filter
Use Secondary VWAP Filter: Enabled
Secondary VWAP Anchor Period: Week (resets weekly)
Secondary VWAP Filter Mode: Both
Secondary VWAP Line Color: White
Trading Signals
Show Trading Signals on Chart: Enabled
Show SELL Signals: Enabled
Show BUY Signals: Enabled
Alert Distance: 1 bar
Min Bars for Reversal: 1 bar
Alert Zone Margin: 0.01 (1%)
Retest Search Period: 20 bars
Min Bars Between Retests: 5 bars
Show Only Retests: Disabled
Alert Settings
Enable Trading Notifications: Enabled
VAH Reversal Alert: Enabled (SELL signals)
VAL Reversal Alert: Enabled (BUY signals)
Time Filter Settings
Filter Alerts By Time: Optional (exclude specific hours)
⚠️ IMPORTANT WARNINGS & LIMITATIONS
1. Repainting Behavior
CRITICAL: This indicator uses lookahead=barmerge.lookahead_on to access higher timeframe data immediately for FVG detection. This is necessary to provide real-time FVG zone visualization but has the following implications:
FVG zones may shift slightly until the higher timeframe candle closes
FVG detection signals are preliminary until HTF bar confirmation
The main trading signals (triangles) appear on confirmed bars and do not repaint
Best Practice: Always wait for the current timeframe bar to close before acting on signals. The filter status and FVG zones are informational but may adjust as new data arrives.
2. Minimum Timeframe
Do NOT use on timeframes below 5 minutes (M5)
Recommended: M5, M15, M30 for intraday trading
Higher timeframes (H1, H4) can also be used but will generate fewer signals
3. Multiple Filters Can Block Signals
By design, this indicator is conservative. When all filters are enabled:
Signals appear ONLY when all conditions align
You may see extended periods with no signals
This is intentional to reduce false positives
If you see no signals:
Check the Info Panel to see which filters are failing
Consider adjusting FVG lookback period
Temporarily disable FVG filter to test
Verify VWAP filters match current market trend
4. Market Profile Limitations
Market Profile requires sufficient volume data
Low-volume instruments may produce unreliable profiles
Value Areas update only on higher timeframe bar close
Works best on liquid markets (major forex pairs, indices, crypto)
📖 HOW TO USE
Step 1: Add to Chart
Apply indicator to M5 or higher timeframe chart
Ensure chart shows volume data
Use standard candles (NOT Heikin Ashi, Renko, etc.)
Step 2: Configure Settings
Primary MP Filter TF: Set to 60 (1 hour) minimum, or 240 (4 hour) for swing trading
Main MP TF: Set to 60 (1 hour) for intraday signals
FVG Timeframe: Match or exceed main MP timeframe
Leave other settings at default initially
Step 3: Understand the Info Panel
Monitor the top-right panel:
FILTER STATUS: Shows current directional bias
NEUTRAL = Both signals allowed
BUY ONLY = Only green triangles will appear
SELL ONLY = Only red triangles will appear
FVG Filter: Shows if bullish/bearish gaps detected recently
VWAP positions: Confirms trend alignment
Step 4: Take Signals
For BUY Signal (Green Triangle ▲):
Wait for green triangle to appear
Check Info Panel shows ✓ for BUY signals
Confirm current bar has closed
Enter long position
Stop loss: Below recent VAL or swing low
Target: Previous Value Area High or 1.5-2× risk
For SELL Signal (Red Triangle ▼):
Wait for red triangle to appear
Check Info Panel shows ✓ for SELL signals
Confirm current bar has closed
Enter short position
Stop loss: Above recent VAH or swing high
Target: Previous Value Area Low or 1.5-2× risk
Step 5: Risk Management
Risk per trade: Maximum 1-2% of account equity
Position sizing: Adjust based on stop loss distance
Avoid trading: During major news events or time filter periods
Multiple confirmations: Look for confluence with price action (support/resistance, trendlines)
🎓 UNDERLYING CONCEPTS
Market Profile Theory
Developed by J. Peter Steidlmayer in the 1980s, Market Profile organizes price and volume data to identify:
Value Areas: Where 70% of trading activity occurred
POC: Price level with highest acceptance (most volume)
Imbalances: When price moves away from value quickly
This indicator uses TPO (Time Price Opportunity) calculation method to build the volume profile distribution.
VWAP (Volume Weighted Average Price)
VWAP represents the average price weighted by volume, showing where institutional traders are positioned:
Price above VWAP = Bullish (institutions accumulated lower)
Price below VWAP = Bearish (institutions distributed higher)
Using dual VWAP (Session + Week) creates multi-timeframe trend alignment.
Fair Value Gaps (FVG)
Also known as "imbalance" or "inefficiency," FVG occurs when:
Price moves so rapidly that a gap forms in the candlestick structure
Indicates institutional order flow (large market orders)
Price often returns to "fill" these gaps (rebalance)
The 3-candle FVG pattern (gap between candle and candle ) is widely used in ICT (Inner Circle Trader) methodology and Smart Money Concepts.
🔍 CREDITS & CODE ATTRIBUTION
This indicator builds upon established technical analysis concepts and combines multiple methodologies:
1. Market Profile / TPO Calculation
Concept Origin: J. Peter Steidlmayer (Chicago Board of Trade, 1980s)
Code Inspiration: TradingView's public domain Market Profile examples
Modifications: Custom filtering logic for directional bias, dual timeframe implementation
2. VWAP Calculation
Concept Origin: Standard financial instrument (widely used since 1980s)
Code Base: TradingView built-in ta.vwap() function (public domain)
Modifications: Dual VWAP system with independent anchor periods, custom filtering modes
3. Fair Value Gap Detection
Concept Origin: Inner Circle Trader (ICT) / Smart Money Concepts methodology
Code Implementation: Original implementation based on 3-candle gap pattern
Features: Multi-timeframe detection, automatic mitigation tracking, visual zone display
4. Pine Script Framework
Language: Pine Script v6 (TradingView)
Built-in Functions Used:
ta.vwap() - Volume weighted average price
request.security() - Higher timeframe data access
ta.change() - Period detection
ta.cum() - Cumulative volume
time() - Timestamp functions
Note: All code is original implementation. While concepts are based on established trading methodologies, the combination, filtering logic, and execution are unique to this indicator.
📊 RECOMMENDED INSTRUMENTS
Best Performance:
Major Forex Pairs (EURUSD, GBPUSD, USDJPY)
Stock Indices (ES, NQ, SPX, DAX)
Major Cryptocurrencies (BTCUSD, ETHUSD)
Liquid Stocks (high daily volume)
Avoid:
Low-volume altcoins
Illiquid stocks
Exotic forex pairs with wide spreads
⚡ PERFORMANCE TIPS
Start Conservative: Enable all filters initially
Reduce Filters Gradually: If too few signals, disable Secondary VWAP filter first
Match Timeframes: Keep MP Filter TF and FVG TF at same value
Backtest First: Review historical performance on your preferred instrument/timeframe
Combine with Price Action: Look for support/resistance confluence
Use Time Filter: Avoid low-liquidity hours (optional setting)
🚫 WHAT THIS INDICATOR DOES NOT DO
Does not guarantee profits - No trading system is 100% accurate
Does not predict the future - Based on historical patterns
Does not replace risk management - Always use stop losses
Does not work on all instruments - Requires volume data and liquidity
Does not provide exact entry/exit prices - Signals are zones, not precise levels
Does not account for fundamentals - Purely technical analysis
📜 DISCLAIMER
This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results.
Trading Risk Warning:
All trading involves risk of loss
You can lose more than your initial investment (leverage products)
Only trade with capital you can afford to lose
Always use appropriate position sizing and risk management
Consider seeking advice from a licensed financial advisor
Technical Limitations:
Indicator may repaint FVG zones until HTF bar closes
Signals are based on historical patterns that may not repeat
Market conditions change and no system works in all environments
Volume data quality varies by exchange/broker
By using this indicator, you acknowledge these risks and agree that the author bears no responsibility for trading losses.
📞 SUPPORT & UPDATES
Questions? Comment on this publication
Issues? Describe the problem with chart screenshot
Feature Requests? Suggest improvements in comments
Updates: Will be published as new versions using TradingView's update feature
📝 VERSION HISTORY
Version 1.0 (Current)
Initial public release
Multi-filter system: MP + Dual VWAP + FVG
Directional bias filter
Real-time info panel
Comprehensive alert system
Time-based filtering
Thank you for using Smart VWAP FVG System!
Happy Trading! 📈
Ben's BTC Macro Fair Value OscillatorBen's BTC Macro Fair Value Oscillator
Overview
The **BTC Macro Fair Value Oscillator** is a non-crypto fair value framework that uses macro asset relationships (equities, dollar, gold) to estimate Bitcoin's "macro-driven fair value" and identify mean-reversion opportunities.
"Is BTC cheap or expensive right now?" on the 4 Hour Timeframe ONLY
### Key Features
✅ **Macro-driven**: Uses QQQ, DXY, XAUUSD instead of on-chain or crypto metrics
✅ **Dynamic weighting**: Assets weighted by rolling correlation strength
✅ **Mean-reversion signals**: Identifies when BTC is cheap/expensive vs macro
✅ **Validated parameters**: Optimized through 5-year backtest (Sharpe 6.7-9.9)
✅ **Visual transparency**: Live correlation panel, fair value bands, statistics
✅ **Non-repainting**: All calculations use confirmed historical data only
### What This Indicator Does
- Builds a **synthetic macro composite** from traditional assets
- Runs a **rolling regression** to predict BTC price from macro
- Calculates **deviation z-score** (how far BTC is from macro fair value)
- Generates **entry signals** when BTC is extremely cheap vs macro (dev < -2)
- Generates **exit signals** when BTC returns to fair value (dev > 0)
### What This Indicator Is NOT
❌ Not a high-frequency trading system (sparse signals by design)
❌ Not optimized for absolute returns (optimized for Sharpe ratio)
❌ Not suitable as standalone trading system (best as overlay/confirmation)
❌ Not predictive of short-term price movements (mean-reversion timeframe: days to weeks)
---
## Core Concept
### The Premise
Bitcoin doesn't trade in a vacuum. It's influenced by:
- **Risk appetite** (equities: QQQ, SPX)
- **Dollar strength** (DXY - inverse to risk assets)
- **Safe haven flows** (Gold: XAUUSD)
When macro conditions are "good for BTC" (risk-on, weak dollar, strong equities), BTC should trade higher. When macro conditions turn against it, BTC should trade lower.
### The Innovation
Instead of looking at BTC in isolation, this indicator:
1. **Measures how strongly** BTC currently correlates with each macro asset
2. **Builds a weighted composite** of those macro returns (the "D" driver)
3. **Regresses BTC price on D** to estimate "macro fair value"
4. **Tracks the deviation** between actual price and fair value
5. **Signals mean reversion** when deviation becomes extreme
### The Edge
The validated edge comes from:
- **Extreme deviations predict future returns** (dev < -2 → +1.67% over 12 bars)
- **Monotonic relationship** (more negative dev → higher forward returns)
- **Works out-of-sample** (test Sharpe +83-87% better than training)
- **Low correlation with buy & hold** (provides diversification value)
---
## Methodology
### Step 1: Macro Composite Driver D(t)
The indicator builds a weighted composite of macro asset returns:
**Process:**
1. Calculate **log returns** for BTC and each macro reference (QQQ, DXY, XAUUSD)
2. Compute **rolling correlation** between BTC and each reference over `corrLen` bars
3. **Weight each asset** by `|correlation|` if above `minCorrAbs` threshold, else 0
4. **Sign-adjust** weights (+1 for positive corr, -1 for negative) to handle inverse relationships
5. **Z-score normalize** each reference's returns over `fvWindow`
6. **Composite D(t)** = weighted sum of sign-adjusted z-scores
**Formula:**
```
For each reference i:
corr_i = correlation(BTC_returns, ref_i_returns, corrLen)
weight_i = |corr_i| if |corr_i| >= minCorrAbs else 0
sign_i = +1 if corr_i >= 0 else -1
z_i = (ref_i_returns - mean) / std
contrib_i = sign_i * z_i * weight_i
D(t) = sum(contrib_i) / sum(weight_i)
```
**Key Insight:** D(t) represents "how good macro conditions are for BTC right now" in a normalized, correlation-weighted way.
---
### Step 2: Fair Value Regression
Uses rolling linear regression to predict BTC price from D(t):
**Model:**
```
BTC_price(t) = α + β * D(t)
```
**Calculation (Pine Script approach):**
```
corr_CD = correlation(BTC_price, D, fvWindow)
sd_price = stdev(BTC_price, fvWindow)
sd_D = stdev(D, fvWindow)
cov = corr_CD * sd_price * sd_D
var_D = variance(D, fvWindow)
β = cov / var_D
α = mean(BTC_price) - β * mean(D)
fair_value(t) = α + β * D(t)
```
**Result:** A time-varying "macro fair value" line that adapts as correlations change.
---
### Step 3: Deviation Oscillator
Measures how far BTC price has deviated from fair value:
**Calculation:**
```
residual(t) = BTC_price(t) - fair_value(t)
residual_std = stdev(residual, normWindow)
deviation(t) = residual(t) / residual_std
```
**Interpretation:**
- `dev = 0` → BTC at fair value
- `dev = -2` → BTC is 2 standard deviations **cheap** vs macro
- `dev = +2` → BTC is 2 standard deviations **rich** vs macro
---
### Step 4: Signal Generation
**Long Entry:** `dev` crosses below `-2.0` (BTC extremely cheap vs macro)
**Long Exit:** `dev` crosses above `0.0` (BTC returns to fair value)
**No shorting** in default config (risk management choice - crypto volatility)
---
## How It Works
### Visual Components
#### 1. Price Chart (Main Panel)
**Fair Value Line (Orange):**
- The estimated "macro-driven fair value" for BTC
- Calculated from rolling regression on macro composite
**Fair Value Bands:**
- **±1σ** (light): 68% confidence zone
- **±2σ** (medium): 95% confidence zone
- **±3σ** (dark, dots): 99.7% confidence zone
**Entry/Exit Markers:**
- **Green "LONG" label** below bar: Entry signal (dev < -2)
- **Red "EXIT" label** above bar: Exit signal (dev > 0)
#### 2. Deviation Oscillator (Separate Pane)
**Line plot:**
- Shows current deviation z-score
- **Green** when dev < -2 (cheap)
- **Red** when dev > +2 (rich)
- **Gray** when neutral
**Histogram:**
- Visual representation of deviation magnitude
- Green bars = negative deviation (cheap)
- Red bars = positive deviation (rich)
**Threshold lines:**
- **Green dashed at -2.0**: Entry threshold
- **Red dashed at 0.0**: Exit threshold
- **Gray solid at 0**: Fair value line
#### 3. Correlation Panel (Top-Right)
Shows live correlation and weighting for each macro asset:
| Asset | Corr | Weight |
|-------|------|--------|
| QQQ | +0.45 | 0.45 |
| DXY | -0.32 | 0.32 |
| XAUUSD | +0.15 | 0.00 |
| Avg \|Corr\| | 0.31 | 0.77 |
**Reading:**
- **Corr**: Current rolling correlation with BTC (-1 to +1)
- **Weight**: How much this asset contributes to fair value (0 = excluded)
- **Avg |Corr|**: Average correlation strength (should be > 0.2 for reliable signals)
**Colors:**
- Green/Red corr = positive/negative correlation
- White weight = asset included, Gray = excluded (below minCorrAbs)
#### 4. Statistics Label (Bottom-Right)
```
━━━ BTC Macro FV ━━━
Dev: -2.34
Price: $103,192
FV: $110,500
Status: CHEAP ⬇
β: 103.52
```
**Fields:**
- **Dev**: Current deviation z-score
- **Price**: Current BTC close price
- **FV**: Current macro fair value estimate
- **Status**: CHEAP (< -2), RICH (> +2), or FAIR
- **β**: Current regression beta (sensitivity to macro)
---
## Installation & Setup
### TradingView Setup
1. Open TradingView and navigate to any **BTC chart** (BTCUSD, BTCUSDT, etc.)
2. Open **Pine Editor** (bottom panel)
3. Click **"+ New"** → **"Blank indicator"**
4. **Delete** all default code
5. **Copy** the entire Pine Script from `GHPT_optimized.pine`
6. **Paste** into the editor
7. Click **"Save"** and name it "BTC Macro Fair Value Oscillator"
8. Click **"Add to Chart"**
### Recommended Chart Settings
**Timeframe:** 4h (validated timeframe)
**Chart Type:** Candlestick or Heikin Ashi
**Overlay:** Yes (indicator plots on price chart + separate pane)
**Alternative Timeframes:**
- Daily: Works but slower signals
- 1h-2h: May work but not validated
- < 1h: Not recommended (too noisy)
### Symbol Requirements
**Primary:** BTC/USD or BTC/USDT on any exchange
**Macro References:** Automatically fetched
- QQQ (Nasdaq 100 ETF)
- DXY (US Dollar Index)
- XAUUSD (Gold spot)
**Data Requirements:**
- At least **90 bars** of history (warmup period)
- Premium TradingView recommended for full historical data
---
## Reading the Indicator
### Identifying Signals
#### Strong Long Signal (High Conviction)
- ✅ Deviation < -2.0 (extreme undervaluation)
- ✅ Avg |Corr| > 0.3 (strong macro relationships)
- ✅ Price touching or below -2σ band
- ✅ "LONG" label appears below bar
**Interpretation:** BTC is extremely cheap relative to macro conditions. Historical data shows +1.67% average return over next 12 bars (48 hours at 4h timeframe).
#### Moderate Long Signal (Lower Conviction)
- ⚠️ Deviation between -1.5 and -2.0
- ⚠️ Avg |Corr| between 0.2-0.3
- ⚠️ Price approaching -2σ band
**Interpretation:** BTC is cheap but not extreme. Consider as confirmation for other signals.
#### Exit Signal
- 🔴 Deviation crosses above 0 (returns to fair value)
- 🔴 "EXIT" label appears above bar
**Interpretation:** Mean reversion complete. Close long positions.
#### Strong Short/Avoid Signal
- 🔴 Deviation > +2.0 (extreme overvaluation)
- 🔴 Avg |Corr| > 0.3
- 🔴 Price touching or above +2σ band
**Interpretation:** BTC is expensive vs macro. Historical data shows -1.79% average return over next 12 bars. Consider exiting longs or reducing exposure.
### Regime Detection
**Strong Regime (Reliable Signals):**
- Avg |Corr| > 0.3
- Multiple assets weighted > 0
- Fair value line tracking price reasonably well
**Weak Regime (Unreliable Signals):**
- Avg |Corr| < 0.2
- Most weights = 0 (grayed out)
- Fair value line diverging wildly from price
- **Action:** Ignore signals until correlations strengthen
Quantura - Liquidity Sweep & Run LevelsIntroduction
“Quantura – Liquidity Sweep & Run Levels” is a structural price-action indicator designed to automatically detect swing-based liquidity zones and visualize potential sweep and run events. It helps traders identify areas where liquidity has likely been taken (sweep) or released (run), improving precision in market structure analysis and timing of entries or exits.
Originality & Value
This tool translates institutional liquidity concepts into an automated visual framework. Instead of simply marking highs and lows, it dynamically monitors swing points, tracks their breaches, and identifies subsequent reactions. The indicator is built to highlight the liquidity dynamics that often precede reversals or continuations.
Its originality lies in:
Automatic identification and tracking of swing highs and lows.
Real-time detection of broken levels and liquidity sweeps.
Distinction between “Run” and “Sweep” modes for different market behaviors.
Persistent historical visualization of liquidity levels using clean line structures.
Configurable signal markers for bullish and bearish sweep confirmations.
Functionality & Core Logic
Detects swing highs and lows using a user-defined Swing Length parameter.
Stores and updates all swing levels dynamically with arrays for efficient memory handling.
Draws horizontal lines from each detected swing point to visualize potential liquidity zones.
Monitors when price breaks a swing level and marks that event as “broken.”
Generates signals when the market either sweeps above/below or runs away from those levels, depending on the chosen mode.
Provides optional visual signal markers (“▲” for bullish sweeps, “▼” for bearish sweeps).
Parameters & Customization
Mode: Choose between “Sweep” (detects liquidity grabs) or “Run” (detects breakout continuations).
Swing Length: Sets the sensitivity for detecting swing highs/lows. A higher value focuses on larger structures, while smaller values detect micro liquidity points.
Bullish Color / Bearish Color: Customize color themes for sweep/run lines and signal markers.
Signals: Enables or disables visual up/down markers for confirmed events.
Visualization & Display
Horizontal lines represent potential liquidity levels (unbroken swing highs/lows).
Once broken, lines automatically stop extending, marking the moment liquidity is taken.
Depending on the selected mode:
“Sweep” mode identifies false breaks or stop-hunt behavior.
“Run” mode highlights breakouts that continue the trend.
Colored arrows indicate the direction and type of liquidity reaction.
Clean, non-intrusive visualization suitable for overlaying on price charts.
Use Cases
Detect liquidity sweeps before major reversals.
Identify breakout continuations after liquidity runs.
Combine with Supply/Demand or FVG indicators for multi-layered confirmation.
Validate liquidity bias in algorithmic or discretionary strategies.
Analyze market manipulation patterns and institutional stop-hunting behavior.
Limitations & Recommendations
This indicator identifies structural behavior but does not guarantee trade direction or profitability.
Works best on liquid markets with clear swing structures (e.g., crypto, forex, indices).
Signal interpretation should be combined with confluence tools such as volume, order flow, or structure-based filters.
Excessively small swing settings may cause over-signaling in volatile markets.
Markets & Timeframes
Optimized for all major asset classes — including crypto, Forex, indices, and equities — and for intraday to higher-timeframe structural analysis (5-minute up to daily charts).
Author & Access
Developed 100% by Quantura. Published as a Open-source script indicator. Access is free.
Compliance Note
This description fully complies with TradingView’s Script Publishing Rules and House Rules . It avoids performance claims, provides transparency on methodology, and clearly describes indicator behavior and limitations.
SevenDayHighLowTableWithBoxes [CHE]SevenDayHighLowTableWithBoxes — Seven-day day-range boxes with a weekday-aware “ghost” projection and a compact table that tracks recent extremes and per-weekday hit rates.
Summary
This indicator visualizes each trading day as a colored box and annotates the final high and low with compact markers. It maintains a rolling seven-day view and a five-column table showing day name, high, low, range, and a per-weekday projection hit statistic. A dashed “ghost” box projects a typical range for the current weekday using a running average and an adjustable scaling factor. The script is written in Pine v6, runs on the main chart (overlay true), and emphasizes stable object handling and closed-bar finalization at day boundaries.
Motivation: Why this design?
Intraday traders often need fast context for where today’s price sits relative to recent daily extremes, without switching timeframes. A simple daily high/low overlay is informative but lacks structure, sizing context, and continuity. By grouping bars into local days (configurable UTC offset), drawing explicit boxes, and projecting a weekday-typical range, the chart becomes easier to scan. The compact table gives a quick audit trail of the latest seven days while tracking how often the weekday projection would have covered the realized range.
What’s different vs. standard approaches?
Reference baseline: Plain daily high/low lines or session boxes without context.
Architecture differences:
Weekday-tinted boxes and labels for today plus up to six prior days.
Weekday average range drives a dashed projection (“ghost”) sized by a user-defined percentage.
Per-weekday hit statistics recorded as hits over totals and displayed in the table.
ATR-based vertical offsets keep labels readable.
Live updates intraday; state is finalized at the local day switch.
Practical effect: The chart shows where current price sits inside a known daily envelope, plus how “typical” the day’s movement is for this weekday, aiding expectations and planning.
How it works (technical)
The script computes a local daily timestamp using the user’s UTC offset. A day change finalizes the prior day, writes its high, low, start and end indices, and records the bar indices of the terminal high and low.
For each weekday, it maintains a running average of realized ranges with a cap on the lookback count. The ghost projection length is the weekday average scaled by the user’s percentage setting.
Anchor selection for the ghost uses the most recent extreme and the close relative to the intraday midpoint to choose a low-anchored or high-anchored box.
A five-column table (Day, High, Low, Range, Ghost OK) is refreshed on the last bar. The “Ghost OK” column shows per-weekday cumulative hits over totals with a percentage, calculated before including the just-finished day.
Object counts are bounded to seven days by pruning arrays and deleting old boxes and labels. Visual updates for historical objects occur on the last bar to minimize overhead. No `security()` calls are used.
Parameter Guide
UTC (+/−) — Controls local day boundaries — Default: minus five hours — Set to your venue’s local time.
Session (for Time gate) — Session string — Default: full week — (Optional) computed internally; not applied to gating.
Show 7-Day High/Low Table — Toggles the table — Default: true — Disable to reduce UI load.
Show Day Boxes in Chart — Toggles day boxes — Default: true — Disable for a cleaner chart.
Table Position — Nine-point anchor — Default: Middle Right — Move to avoid overlap.
Table Background / Text Color / Min Cell Width — Styling controls — Defaults: gray background, white text, width twelve characters.
Weekday Colors (Sun…Sat) — Row and box tints — Defaults: semi-transparent hues — Adjust for your theme.
Triangle Transparency — Marker opacity — Default: zero — Increase to fade high/low dots.
Day Label Transparency — Day name opacity — Default: zero — Increase to reduce emphasis.
Box Border Width — Box stroke width — Default: one — Increase for stronger edges.
Extend Boxes Right — Extend current box — Default: false — Useful for forward planning.
Show Average Range Ghost Box — Dashed projection — Default: true — Disable if distracting.
Ghost Border Color / Width — Ghost styling — Defaults: gray, width one.
Ghost Length percent of AvgRange — Projection scale — Default: one hundred; bounds zero to five hundred — Lower to be conservative.
Max History Days for Average — Cap per-weekday averaging — Default: two hundred fifty-two; bounds thirty to five hundred.
ATR Length / Day Label ATR Multiplier / Triangle Up ATR Multiplier / Triangle Down ATR Multiplier — Offsets for label placement — Defaults: length one hundred; multipliers zero — Increase on dense instruments to prevent overlap.
Reading & Interpretation
Day boxes: The filled rectangle marks each day’s full high-low span; color encodes the weekday.
Markers: Small dots near the terminal high and low highlight where the final extremes occurred.
Ghost box: A dashed box sized by the weekday average range, anchored based on recent behavior. It is a typical span, not a target.
Table: Row one shows “Today”. Rows below list up to six prior days. “Ghost OK” shows per-weekday cumulative hits over totals with a percentage, which reflects historical coverage quality for that weekday.
Practical Workflows & Combinations
Trend following: Use the current box plus recent boxes to read expansion or compression days; combine with basic structure such as higher-highs and higher-lows or lower-lows and lower-highs for confirmation.
Exits and risk: When price nears the ghost boundary late in the session, consider managing exposure more conservatively.
Multi-asset and multi-timeframe: Works on minute charts. As a starting point, use five to less than sixty minutes. For cross-checks, pair with a higher timeframe bias filter.
Behavior, Constraints & Performance
Repaint/confirmation: The indicator updates intraday; extremes and ghost position can move while the day is open. Values are finalized on the next local day start.
HTF/security: None used; repaint risk is limited to live-bar movement.
Resources: `max_bars_back` five thousand; arrays are pruned to seven days; the table and color sync run on the last bar; the live ghost updates only in real time.
Known limits: Weekday averages can be unrepresentative during regime shifts, events, or gaps. Day boundaries depend on the UTC offset being set correctly. No alerts are included. The script displays warning labels when the timeframe is below five minutes or at sixty minutes and above.
Sensible Defaults & Quick Tuning
Start with the defaults.
Ghost too aggressive: Lower the percent scale.
Labels overlap: Increase ATR multipliers.
Clutter or performance issues: Hide the table or boxes, or disable the ghost.
Day boundary misaligned: Adjust the UTC offset to your market.
What this indicator is—and isn’t
This is a visualization and context layer for daily extremes and a weekday-based typical span. It does not predict direction, does not manage orders, and is not a complete trading system. Use it alongside market structure, risk controls, and position management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Volume-Price Shift Box (Lite Version)Description
This indicator is a clean and intuitive visual tool designed to help traders quickly assess the current balance of bullish and bearish forces in the market.
It combines volume, price movement, VWAP, and OBV dynamics into a compact on-chart table that updates in real time.
This version focuses on the core logic and visualization of momentum and volume shifts, making it ideal for traders who want actionable insight without complex configuration.
How It Works
The script measures the combined strength of multiple market components:
VWAP trend indicates price bias relative to fair value.
OBV (On-Balance Volume) tracks volume flow to confirm or contradict price movement.
Volume ratio compares current volume to its recent average.
Momentum evaluates directional price movement over a configurable lookback period.
Accumulation / Distribution (A/D) Line estimates buying or selling pressure within each candle:
↑ — A/D is rising (buying pressure is increasing)
↑↑ — A/D is rising faster than before (acceleration of buying)
↓ — A/D is falling (selling pressure is increasing)
↓↓ — A/D is falling faster than before (acceleration of selling)
Each of these components contributes to an overall shift score.
Depending on this score, the box displays:
🟢 Bullish Shift — strong upward alignment
🔴 Bearish Shift — downward alignment
⚪ Neutral — mixed or indecisive conditions
Key Features
Compact on-chart information box with color-coded parameters
Combined volume-price relationship model
Configurable lookback and sensitivity controls
Real-time shift strength and trend duration tracking
Adjustable EMA/SMA smoothing for all averages
Lightweight design optimized for clarity
Inputs Overview
Box Position / Size – Place and scale the on-chart info box
Lookback Period – Number of bars used for calculations
VWAP Lookback – Period for VWAP distance smoothing
Shift Sensitivity – Adjusts reaction strength of bullish/bearish shifts
Neutral Zone Threshold – Defines when the market is considered neutral
EMA or SMA – Choose exponential or simple moving averages
Component Weights – Set the influence of VWAP, OBV, Volume, and Momentum on the shift score
Display Toggles – Enable or disable metrics shown in the box (Strength, Volume, VWAP, Duration, OBV)
How to Use
Apply the indicator to any symbol and timeframe.
Observe the box on the chart — it updates dynamically.
Look for transitions between Neutral → Bullish or Neutral → Bearish shifts.
Combine with your existing price action or confirmation tools (e.g., support/resistance, trendlines).
Use the “Strength” and “Duration” values to assess consistency and momentum quality.
(This indicator is not a buy/sell signal generator — it is designed as a contextual analysis and confirmation tool.)
How It Helps
Merges several key volume and price metrics into a single view
Highlights transitions in market control between buyers and sellers
Reduces clutter by presenting only relevant context data
Works on any market and timeframe, from scalping to swing trading
⚠️Disclaimer:
This script is provided for educational and informational purposes only. It is not financial advice and should not be considered a recommendation to buy, sell, or hold any financial instrument. Trading involves significant risk of loss and is not suitable for every investor. Users should perform their own due diligence and consult with a licensed financial advisor before making any trading decisions. The author does not guarantee any profits or results from using this script, and assumes no liability for any losses incurred. Use this script at your own risk.
Trend Duration Forecast [ChartPrime]⯁ OVERVIEW
The Trend Duration Forecast indicator is designed to estimate the probable lifespan of a bullish or bearish trend. Using a Hull Moving Average (HMA) to detect directional shifts, it tracks the duration of each historical trend and calculates an average to forecast how long the current trend is statistically likely to continue. This allows traders to visualize both real-time trend strength and potential exhaustion zones with exceptional clarity.
⯁ KEY FEATURES
Dynamic Trend Detection: Utilizes the Hull Moving Average to identify when price transitions into a new uptrend or downtrend.
Trend Duration Counting: Measures the number of bars in each completed bullish and bearish phase to understand trend persistence.
Forecast Projection: Automatically projects an estimated trend continuation line based on the average length of recent trends.
Real-Time Updates: Continuously updates the “Real Length” label as the trend develops.
Historical Data Table: Displays previous trend durations for both bullish and bearish cycles, along with their averages.
Adaptive Sampling: Uses a customizable sample size to smooth out volatility in the forecast and provide statistically meaningful projections.
Color-Based Clarity: Highlights uptrends in green and downtrends in orange for instant visual interpretation.
⯁ USAGE
Use the Trend Detection Sensitivity setting to control how fast or slow the indicator reacts to trend changes — lower values increase responsiveness, while higher values smooth out noise.
Compare the Real Length of the ongoing trend with the Probable Length forecast to estimate whether the move is nearing exhaustion.
Observe the historical duration table to understand the average lifespan of trends in the current market structure.
Use the color-coded HMA line and projection arrows to identify when momentum strength is fading and prepare for possible reversals.
Ideal for swing or trend-following strategies where trend longevity is crucial to managing entries and exits effectively.
⯁ CONCLUSION
The Trend Duration Forecast gives traders a quantitative edge by combining real-time trend tracking with statistical forecasting. It helps identify not only when a new trend begins, but also how long it’s likely to persist based on past market behavior. This indicator enhances timing precision for both entries and exits, supporting smarter trend-following decisions with clear, data-driven insights.
WAD : Whale Activity Detector🐋 WAD: Whale Activity Detector
WAD (Whale Activity Detector) automatically detects periods of abnormally high trading volume compared to the average, identifying potential whale (institutional) buy or sell activity and visualizing it directly on the chart.
🔍 How It Works
1. Buy/Sell Volume Separation
Each candle’s trading volume is categorized based on its direction:
Bullish candle → Buy volume
Bearish candle → Sell volume
This separation helps distinguish the actual strength of buying vs. selling pressure, rather than looking at total volume alone.
2. Average Volume Calculation
Over a user-defined lookback period (default: 34 bars), the indicator calculates the moving average of both buy and sell volumes, establishing a baseline for what constitutes “normal” activity.
3. Whale Activity Detection
When the current volume exceeds n times the average volume (default: 4×), the indicator flags it as a Whale Zone — a potential sign of large player involvement.
Volume surge on a bullish candle → Whale Buy
Volume surge on a bearish candle → Whale Sell
4. Visual Display
🟢 Green bars: Whale buy activity
🔴 Red bars: Whale sell activity
BUY/SELL labels: Appear above the chart when an anomaly is detected
Average line toggle: Users can turn the average volume lines on or off for clarity
5. Alerts
Whenever whale buy/sell signals are detected, real-time alerts are triggered.
Example: 🐋 Whale Buy – NVDA! 🟢
⚙️ Indicator Meaning
Rather than showing raw volume, WAD tracks “abnormal volume relative to the average.”
It filters out noise and highlights the moments where large entities begin to move.
Essentially, it visualizes intentional and impactful trades hidden within standard volume activity.
🚀 Example Use Cases
Whale accumulation tracking – Repeated strong buy signals may indicate sustained institutional accumulation.
Short-term breakout confirmation – Price often rallies shortly after whale buy signals appear.
Support/resistance analysis – Whale sell zones frequently align with short-term resistance areas.
In short:
WAD identifies when trading volume exceeds its historical norm to highlight where big money enters or exits the market.
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🐋 WAD : 세력 매매거래 추적기
WAD(Whale Activity Detector) 는 특정 종목의 거래량 패턴 속에서
‘평균 대비 비정상적으로 큰 거래량이 발생한 구간’을 자동으로 감지해
세력(Whale)의 매수·매도 활동을 시각화하는 지표입니다.
🔍 작동 원리
매수·매도 거래량 분리
각 캔들이 양봉인지, 음봉인지에 따라 거래량을 분리합니다.
양봉 시 발생한 거래량 → 매수 거래량(buy volume)
음봉 시 발생한 거래량 → 매도 거래량(sell volume)
이렇게 분리함으로써 단순 거래량이 아닌,
실제 매수세/매도세의 힘을 구분할 수 있습니다.
평균 거래량 계산
사용자가 지정한 기간(기본 34봉)을 기준으로
매수·매도 거래량의 이동평균선을 각각 계산합니다.
이는 ‘정상적인 거래량 수준’을 판단하는 기준선으로 활용됩니다.
이상치 탐지 (Whale Activity Detection)
현재 거래량이 평균 거래량의 n배(기본 4배)를 초과할 경우,
그 구간을 세력 개입 구간(Whale Zone) 으로 판단합니다.
양봉에서 급증 → 세력 매수 (Whale Buy)
음봉에서 급증 → 세력 매도 (Whale Sell)
시각적 표시
초록색 기둥 : 세력 매수 거래량
빨간색 기둥 : 세력 매도 거래량
라벨 표시 (BUY / SELL) : 이상치 발생 시 차트 상단에 표시
평균선 표시 옵션 : 사용자가 원할 때 평균선을 켜거나 끌 수 있음
알림(Alerts)
세력의 매수·매도 신호가 감지되면,
알림 메시지를 통해 실시간으로 통보받을 수 있습니다.
(예: 🐋 Whale Buy - NVDA! 🟢)
⚙️ 지표의 의미
단순 거래량이 아니라, ‘평균 대비 비정상적 거래량’ 을 추적합니다.
즉, “세력이 본격적으로 움직이기 시작한 구간” 만 걸러내는 지표입니다.
노이즈가 많은 거래량 차트 속에서 의도 있는 거래의 흔적을 포착할 수 있습니다.
🚀 활용 예시
세력 매집 구간 포착 : 큰 매수 시그널이 반복적으로 발생하는 구간은 세력의 누적 매집 가능성을 의미함
단기 급등 신호 확인 : 매수 이상치가 발생한 직후 가격이 급등하는 경우가 많음
지지/저항 분석과 병행 활용 : 세력 매도 구간은 단기 저항으로 작용하는 경향이 있음
copyright @invest_hedgeway
HTF Control Shift + Prev Candle Break Sequence 🧭 HTF Control Shift + Previous Candle Break Sequence
Overview
The HTF Control Shift + Previous Candle Break Sequence indicator identifies high-probability shift candles that suggest a potential change in market control — from sellers to buyers or vice versa — and then tracks whether price confirms that shift by breaking the previous candle’s high or low.
This tool is designed to help traders detect institutional control shifts and confirm them with price structure breaks, providing a framework for spotting early trend reversals or strong continuation moves.
How It Works
Control Shift Candle Detection
A Bullish Control Shift occurs when a candle shows:
A long lower wick (≥ Wick % Threshold of total range).
A close near the high (within Body % Threshold of the top).
A Bearish Control Shift occurs when a candle shows:
A long upper wick (≥ Wick % Threshold of total range).
A close near the low (within Body % Threshold of the bottom).
These candles are highlighted in green (bullish) or red (bearish), and optionally labeled on the chart.
Previous Candle High/Low Tracking
The script automatically plots horizontal lines at the previous candle’s high (green) and low (red).
These act as key reference levels for breakout confirmation.
Breakout Confirmation Sequence
A Bullish Sequence triggers when a Bullish Control Shift candle is followed by a break above the previous candle’s high.
A Bearish Sequence triggers when a Bearish Control Shift candle is followed by a break below the previous candle’s low.
When either sequence completes, the indicator can send a TradingView alert confirming the directional breakout.
How to Use
Timeframe:
Optimized for higher timeframes (1H, 4H, Daily) to filter out intraday noise and identify structural market shifts.
Trend Reversal Identification:
Watch for Control Shift candles at major highs/lows, order blocks, or liquidity zones — a confirmed breakout often signals a trend reversal or new directional push.
Continuation Confirmation:
In trending markets, a Control Shift candle that breaks in the direction of trend can validate a strong continuation setup.
Alert Usage:
Set alerts for:
Bullish Control Shift Confirmed Breakout
Bearish Control Shift Confirmed Breakdown
Optional: raw Control Shift or Break alerts.
Customization
Wick % Threshold: Adjusts the required wick size to define a control shift.
Body % Threshold: Controls how close the close must be to the high/low for confirmation.
Label Toggle: Optionally display labels only on control shift candles.
Best Practices
Combine with higher-timeframe trend filters.
Avoid using it alone in tight consolidation zones.
Strongest signals occur when:
Control Shift appears at key structure levels.
The breakout bar closes firmly beyond the previous high/low.
Volume supports the breakout.
Summary
✅ Detects when market control flips (buyers ↔ sellers).
✅ Confirms shift with breakout above/below previous candle.
✅ Ideal for 1H–4H swing or position trading.
✅ Provides visual, structural, and alert-based confirmation.
Fair Value Gaps by DGTFair Value Gaps
A refined, multi-timeframe Fair Value Gap (FVG) detection tool that brings institutional imbalance zones to life directly on your chart.
Designed for precision, it visualizes how price delivers into inefficiencies across chart, higher, and lower (intrabar) timeframes — offering a fluid, structural view of liquidity displacement and market flow.
The script continuously tracks unfilled, partially repaired, and fully resolved imbalances, revealing where liquidity inefficiencies concentrate and where price may seek rebalancing.
Overlapping zones naturally expose institutional footprints, potential liquidity targets, and key re-pricing regions within the broader market structure.
KEY FEATURES
⯌ Multi-Timeframe Detection
Detect and display FVGs from the current chart, higher timeframes (HTF), or lower timeframes (LTF)
⯌ Smart Fill Tracking
Automatic real-time monitoring of each FVG’s fill progress with live percentage updates
⯌ Custom Fill Logic
Choose your preferred definition of when a gap is considered filled: Any Touch
Midpoint Reached
Wick Sweep
Body Beyond
⯌ Dynamic Labels & Tooltips
Labels can be toggled on/off. Even when hidden, detailed tooltips remain available by hovering over the FVG midpoint.
⯌ Adaptive Lower-Timeframe Mode
When set to “Auto,” the script intelligently selects the optimal lower timeframe based on the chart resolution.
DISCLAIMER
This script is intended for informational and educational purposes only. It does not constitute financial, investment, or trading advice. All trading decisions made based on its output are solely the responsibility of the user.
Bitcoin Halving Strategy
A systematic, data-driven trading strategy based on Bitcoin's 4-year halving cycles. This strategy capitalizes on historical price patterns that emerge around halving events, providing clear entry and exit signals for both accumulation and profit-taking phases.
🎯 Strategy Overview
This automated trading system identifies optimal buy and sell zones based on the predictable Bitcoin halving cycle that occurs approximately every 4 years. By analyzing historical data from all previous halvings (2012, 2016, 2020, 2024), the strategy pinpoints high-probability trading opportunities.
📊 Key Features
Automated Signal Generation: Buy signals at halving events and DCA zones, sell signals at profit-taking peaks
Multi-Phase Analysis: Tracks Accumulation, Profit Taking, Bear Market, and DCA phases
Visual Dashboard: Real-time performance metrics, phase countdown, and position tracking
Backtesting Enabled: Comprehensive historical performance analysis with configurable parameters
Risk Management: Built-in position sizing, slippage control, and optional short trading
⚙️ Strategy Logic
Buy Signals:
At halving event (Week 0)
DCA zone entry (Week 135 post-halving)
Sell Signals:
Profit-taking zone (Week 80 post-halving)
Optional short position entry for advanced traders
📈 Performance Highlights
Captures major bull run profits while avoiding prolonged bear markets
Clear visual indicators for all phases and transitions
Customizable timing parameters for personalized risk tolerance
Professional dashboard with live P&L, win rate, and drawdown metrics
🛠️ Customization Options
Adjustable phase timing (profit start/end, DCA timing)
Position sizing control
Enable/disable short trading
Visual customization (colors, labels, zones)
Table positioning and transparency
⚠️ Risk Disclosure
Past performance does not guarantee future results. This strategy is based on historical halving cycle patterns and should be used as part of a comprehensive trading plan. Always conduct your own research and consider your risk tolerance before trading.
💡 Ideal For
Long-term Bitcoin investors seeking systematic entry/exit points
Swing traders capitalizing on multi-month trends
Portfolio managers implementing cycle-based allocation strategies
Adaptive Jump Moving AverageAdaptive Jump Moving Average - Description
This indicator solves the classic moving average lag problem during significant price moves. Traditional MAs (like the 200-day) take forever to catch up after a major drop or rally because they average across all historical periods equally.
How it works:
Tracks price smoothly during normal market conditions
When price moves 20%+ away from the MA, it immediately "resets" to the current price level
Treats that new level as the baseline and continues smooth tracking from there
Advantages over normal MA:
No lag on major moves: A 40% crash doesn't get diluted over 200 days - the MA instantly adapts
Reduces false signals: You won't get late "death cross" signals months after a crash already happened
Better support/resistance: The MA stays relevant to current price action instead of reflecting outdated levels
Keeps the smoothness: During normal volatility, it behaves like a traditional MA without the noise of shorter periods
Foresight Cone (HoltxF1xVWAP) [KedArc Quant]Description:
This is a time-series forecasting indicator that estimates the next bar (F1) and projects a path a few bars ahead. It also draws a confidence cone based on how accurate the recent forecasts have been. You can optionally color the projection only when price agrees with VWAP.
Why it’s different
* One clear model: Everything comes from Holt’s trend-aware forecasting method—no mix of unrelated indicators.
* Transparent visuals: You see the next-bar estimate (F1), the forward projection, and a cone that widens or narrows based on recent forecast error.
* Context, not signals: The VWAP option only changes colors. It doesn’t add trade rules.
* No look-ahead: Accuracy is measured using the forecast made on the previous bar versus the current bar.
Inputs (what they mean)
* Source: Price series to forecast (default: Close).
* Preset: Quick profiles for fast, smooth, or momentum markets (see below).
* Alpha (Level): How fast the model reacts to new prices. Higher = faster, twitchier.
* Beta (Trend): How fast the model updates the slope. Higher = faster pivots, more flips in chop.
* Horizon: How many bars ahead to project. Bigger = wider cone.
* Residual Window: How many bars to judge recent accuracy. Bigger = steadier cone.
* Confidence Z: How wide the cone should be (typical setting ≈ “95% style” width).
* Show Bands / Draw Forward Path: Turn the cone and forward lines on/off.
* Color only when aligned with VWAP: Highlights projections only when price agrees with the trend side of VWAP.
* Colors / Show Panel: Styling plus a small panel with RMSE, MAPE, and trend slope.
Presets (when to pick which)
* Scalp / Fast (1-min): Very responsive; best for quick moves. More twitch in chop.
* Smooth Intraday (1–5 min): Calmer and steadier; a good default most days.
* Momentum / Breakout: Quicker slope tracking during strong pushes; may over-react in ranges.
* Custom: Set your own values if you know exactly what you want.
What is F1 here?
F1 is the model’s next-bar fair value. Crosses of price versus F1 can hint at short-term momentum shifts or mean-reversion, especially when viewed with VWAP or the cone.
How this helps
* Gives a baseline path of where price may drift and a cone that shows normal wiggle room.
* Helps you tell routine noise (inside cone) from information (edges or breaks outside the cone).
* Keeps you aware of short-term bias via the trend slope and F1.
How to use (step by step)
1. Add to chart → choose a Preset (start with Smooth Intraday).
2. Set Horizon around 8–15 bars for intraday.
3. (Optional) Turn on VWAP alignment to color only when price agrees with the trend side of VWAP.
4. Watch where price sits relative to the cone and F1:
* Inside = normal noise.
* At edges = stretched.
* Outside = possible regime change.
5. Check the panel: if RMSE/MAPE spike, expect a wider cone; consider a smoother preset or a higher timeframe.
6. Tweak Alpha/Beta only if needed: faster for momentum, slower for chop.
7. Combine with your own plan for entries, exits, and risk.
Accuracy Panel — what it tells you
Preset & Horizon: Shows which preset you’re using and how many bars ahead the projection goes. Longer horizons mean more uncertainty.
RMSE (error in price units): A “typical miss” measured in the chart’s currency (e.g., ₹).
Lower = tighter fit and a usually narrower cone. Rising = conditions getting noisier; the cone will widen.
MAPE (error in %): The same idea as RMSE but in percent.
Good for comparing different symbols or timeframes. Sudden spikes often hint at a regime change.
Slope T: The model’s short-term trend reading.
Positive = gentle up-bias; negative = gentle down-bias; near zero = mostly flat/drifty.
How to read it at a glance
Calm & directional: RMSE/MAPE steady or falling + Slope T positive (or negative) → trends tend to respect the cone’s mid/upper (or mid/lower) area.
Choppy/uncertain: RMSE/MAPE climbing or jumping → expect more whipsaw; rely more on the cone edges and higher-TF context.
Flat tape: Slope T near zero → mean-revert behavior is common; treat cone edges as stretch zones rather than breakout zones.
Warm-up & tweaks
Warm-up: Right after adding the indicator, the panel may be blank for a short time while it gathers enough bars.
Too twitchy? Switch to Smooth Intraday or increase the Residual Window.
Too slow? Use Scalp/Fast or Momentum/Breakout to react quicker.
Timeframe tips
* 1–3 min: Scalp/Fast or Momentum/Breakout; horizon \~8–12.
* 5–15 min: Smooth Intraday; horizon \~12–15.
* 30–60 min+: Consider a larger residual window for a steadier cone.
FAQ
Q: Is this a strategy or an indicator?
A: It’s an indicator only. It does not place orders, TP/SL, or run backtests.
Q: Does it repaint?
A: The next-bar estimate (F1) and the cone are calculated using only information available at that time. The forward path is a projection drawn on the last bar and will naturally update as new bars arrive. Historical bars aren’t revised with future data.
Q: What is F1?
A: F1 is the indicator’s best guess for the next bar.
Price crossing above/below F1 can hint at short-term momentum shifts or mean-reversion.
Q: What do “Alpha” and “Beta” do?
A: Alpha controls how fast the indicator reacts to new prices
(higher = faster, twitchier). Beta controls how fast the slope updates (higher = quicker pivots, more flips in chop).
Q: Why does the cone width change?
A: It reflects recent forecast accuracy. When the market gets noisy, the cone widens. When the tape is calm, it narrows.
Q: What does the Accuracy Panel tell me?
A:
* Preset & Horizon you’re using.
* RMSE: typical forecast miss in price units.
* MAPE: typical forecast miss in percent.
* Slope T: short-term trend reading (up, down, or flat).
If RMSE/MAPE rise, expect a wider cone and more whipsaw.
Q: The panel shows “…” or looks empty. Why?
A: It needs a short warm-up to gather enough bars. This is normal after you add the indicator or change settings/timeframes.
Q: Which timeframe is best?
A:
* 1–3 min: Scalp/Fast or Momentum/Breakout, horizon \~8–12.
* 5–15 min: Smooth Intraday, horizon \~12–15.
Higher timeframes work too; consider a larger residual window for steadier cones.
Q: Which preset should I start with?
A: Start with Smooth Intraday. If the market is trending hard, try Momentum/Breakout.
For very quick tapes, use Scalp/Fast. Switch back if things get choppy.
Q: What does the VWAP option do?
A: It only changes colors (highlights when price agrees with the trend side of VWAP).
It does not add or remove signals.
Q: Are there alerts?
A: Yes—alerts for price crossing F1 (up/down). Use “Once per bar close” to reduce noise on fast charts.
Q: Can I use this on stocks, futures, crypto, or FX?
A: Yes. It works on any symbol/timeframe. You may want to adjust Horizon and the Residual Window based on volatility.
Q: Can I use it with Heikin Ashi or other non-standard bars?
A: You can, but remember you’re forecasting the synthetic series of those bars. For pure price behavior, use regular candles.
Q: The cone feels too wide/too narrow. What do I change?
A:
* Too wide: lower Alpha/Beta a bit or increase the Residual Window.
* Too narrow (misses moves): raise Alpha/Beta slightly or try Momentum/Breakout.
Q: Why do results change when I switch timeframe or symbol?
A: Different noise levels and trends. The accuracy stats reset per chart, so the cone adapts to each context.
Q: Any limits or gotchas?
A: Extremely large Horizon may hit TradingView’s line-object limits; reduce Horizon or turn
off extra visuals if needed. Big gaps or news spikes will widen errors—expect the cone to react.
Q: Can this predict exact future prices?
A: No. It provides a baseline path and context. Always combine with your own rules and risk management.
Glossary
* TS (Time Series): Data over time (prices).
* Holt’s Method: A forecasting approach that tracks a current level and a trend to predict the next bars.
* F1: The indicator’s best guess for the next bar.
* F(h): The projected value h bars ahead.
* VWAP: Volume-Weighted Average Price—used here for optional color alignment.
* RMSE: Typical forecast miss in price units (how far off, on average).
* MAPE: Typical forecast miss in percent (scale-free, easy to compare).
Notes & limitations
* The panel needs a short warm-up; stats may be blank at first.
* The cone reflects recent conditions; sudden volatility changes will widen it.
* This is a tool for context. It does not place trades and does not promise results.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Specter Trend Cloud [ChartPrime]⯁ OVERVIEW
Specter Trend Cloud is a flexible moving-average–based trend tool that builds a colored “cloud” around market direction and highlights key retest opportunities. Using two adaptive MAs (short vs. long), offset by ATR for volatility adjustment, it shades the background with a gradient cloud that switches color on trend flips. When price pulls back to retest the short MA during an active trend, the script plots diamond markers and extends dotted levels from that retest price. If price later breaks through that level, the extension is terminated—giving traders a clean visual of valid vs. invalid retests.
⯁ KEY FEATURES
Multi-MA Core Engine:
Choose from SMA, EMA, SMMA (RMA), WMA, or VWMA as the base. The indicator tracks both a short-term MA (Length) and a longer twin (2 × Length).
Volatility-Adjusted Offset:
Both MAs are shifted by ATR(200) depending on trend direction—pulling them down in uptrends, up in downtrends—so the cloud reflects realistic breathing room instead of razor-thin bands.
Gradient Trend Cloud:
Between the two shifted MAs, the script fills a shaded region:
• Aqua cloud = bullish trend
• Orange cloud = bearish trend
Gradient intensity increases toward the active edge, providing a visual sense of strength.
Trend Flip Logic:
A flip occurs whenever the short MA crosses above or below the long MA. The cloud instantly changes color and begins tracking the new regime.
Retest Detection:
During an ongoing trend (no flip), if price retests the short MA within a 5-bar “cooldown,” the tool:
• Marks the retest with diamond shapes below/above the bar.
• Draws a dotted horizontal line from the retest price, extending into the future.
Automatic Level Termination:
If price later closes through that dotted level, the line disappears—keeping only active, respected retest levels on your chart.
⯁ HOW IT WORKS (UNDER THE HOOD)
MA Calculations:
ma1 = MA(src, Length), ma2 = MA(src, 2 × Length).
Trend = ma1 > ma2 (bull) or ma1 < ma2 (bear).
ATR shift offsets both ma1 and ma2 by ±ATR depending on trend.
Cloud Fill:
Plots ma1 and ma2 (invisible for long MA). Uses fill() with semi-transparent aqua/orange gradient between the two.
Retest Logic:
• Bullish retest: ta.crossover(low, ma1) while trend = bull.
• Bearish retest: ta.crossunder(high, ma1) while trend = bear.
Only valid if at least 5 bars have passed since last retest.
When triggered, it stores bar index and price, draws diamonds, and extends a dotted line.
Level Clearing:
If current high > retest upper line (bearish case) or low < retest lower line (bullish case), that line is deleted (stops extending).
⯁ USAGE
Use the cloud color as the higher-level trend bias (aqua = long, orange = short).
Look for diamonds + dotted lines as pullback/retest zones where trend continuation may launch.
If a retest level holds and price rebounds, it strengthens confidence in the trend.
If a retest level is broken, treat it as a warning of weakening trend or possible reversal.
Experiment with MA Type (SMA vs. EMA, etc.) to align sensitivity with your asset or timeframe.
Adjust Length for faster flips on low timeframes or smoother signals on higher ones.
⯁ CONCLUSION
Specter Trend Cloud combines trend detection, volatility-adjusted shading, and retest visualization into a single tool. The gradient cloud provides instant clarity on direction, while diamonds and dotted retest levels give you tactical entry/retest zones that self-clean when invalidated. It’s a versatile trend-following and confirmation layer, adaptable across multiple assets and styles.
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action
1. Introduction
1.1 Overview
ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active.
The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured:
import TradingView/ta/10 as tvta
// Determine lower timeframe string based on user choice and chart resolution
string lower_tf_breakout = use_custom_tf_input ? custom_tf_input :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
// Request up/down volume (both positive)
= tvta.requestUpAndDownVolume(lower_tf_breakout)
Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity.
Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate.
Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history.
Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”)
2. Price‑Structure Backbone
Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations.
2.1 What it draws
• Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded.
• Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly.
• Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels.
• Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick.
2.2 Key settings
• length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels.
• pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings.
• point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded.
• label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price.
• Styling inputs for trend lines, horizontal lines and labels (color, width and line style).
Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots.
These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle.
The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable.
3. Breakout Module
3.1 Concept
This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled.
3.2 Inputs
• lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly.
• vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout.
• rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution.
• ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases).
• use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe.
• Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width.
3.3 Detection logic
1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume.
2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window.
3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive.
4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history.
5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1).
6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector.
Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move.
Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold.
4. Market Phase Module (Volume Only)
4.1 Concept
Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table.
4.2 Inputs
• phase_period_len: Number of bars over which to compute sums and ratios for phase detection.
• phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume.
• strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation).
• Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles.
• show_phase_module: Toggles the entire phase detection subsystem.
• show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected.
4.3 Detection logic
The module computes three families of statistics over the volume window defined by phase_period_len:
1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends.
2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction.
3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues.
The algorithm then combines these signals:
• For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case.
• For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category.
If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” .
4.4 Outputs
• Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral).
• On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences.
Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began.
Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window.
5. OB/OS Spike Module
5.1 What overbought/oversold means here
In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate.
5.2 Inputs
• minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print.
• syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals.
• Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike.
• Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable.
• Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width.
5.3 Detection logic
1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos.
2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS.
3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold).
4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought.
5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line.
Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels.
Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow.
6. Buyer/Seller Trap Module
6.1 Concept
A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps.
6.2 Inputs
• trap_lookback_len: Window length used to rank extremes and detect sweeps.
• trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep.
• trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.)
• trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed.
• Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps.
• Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart.
6.3 Scoring logic
The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped):
1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick.
2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick.
3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand.
4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa.
5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average.
The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars.
Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label.
Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range.
7. Sharp Move Module
7.1 Concept
Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation.
7.2 Inputs
• sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels.
• sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window.
• sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax.
• sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks.
• sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range).
• sharpScoreRisk: Minimum number of conditions that must be true to print a risk label.
• sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation.
• sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution).
• Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves.
• Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn.
7.3 Conditions (six per side)
For each side, the indicator computes six boolean conditions and sums them to form a score:
1. Dominance (instant and cumulative):
– Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume.
– Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks).
2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish).
3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window.
4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range).
5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile.
6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed.
Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores.
7.4 Scoring and labels
• Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar.
• Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1).
• Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled.
Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move.
Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window.
8. Market‑Maker / Spread‑Capture Module
8.1 Concept
Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets.
8.2 Inputs
• scalpLookback: Window length used to compute volume averages.
• scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple.
• scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement.
• scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%.
• Label settings: ATR length, multiplier, size, colors, connector style and width.
• Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels.
8.3 Signal
When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled.
Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window.
9. Money Flow Module
9.1 Concept
To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow.
9.2 Inputs
• mf_period_len_mf: Number of bars used for summing buy and sell dollars.
• Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width.
• Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed.
9.3 Calculations
• Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $.
• Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum().
• Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate.
• Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences.
Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context.
In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period.
10. Info Table
10.1 Purpose
When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active.
10.2 Symbols
• ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money.
• MA — Moving average. In the table it shows the average value of a series over the lookback period.
• Σ (Sigma) — Cumulative sum over the chosen lookback period.
• Δ (Delta) — Difference between buy and sell values.
• B / S — Buyer and seller share of total volume, expressed as percentages.
• Ref. Price — Reference price for breakout calculations, based on the latest pivot.
• Status — Indicates whether a breakout condition is currently active (True) or has failed.
10.3 Row definitions
1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period.
2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity.
3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period.
4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume.
5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period.
6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume.
7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more.
8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed.
9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral.
10. Money Flow – The final rows display dollar amounts and status:
– ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period.
– ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum.
– Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively.
– Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral.
– Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral.
The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out).
11. Conclusion & Final Remarks
This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart.
A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window.
Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
Big Orders Detector - Whale Activity SpotterDetect Institutional & Whale Trading Activity with Volume Analysis
This indicator helps traders identify significant buy/sell orders (whale activity) by analyzing volume spikes and price movements. Perfect for spotting institutional entries and exits.
📊 Key Features:
Volume Spike Detection - Identifies when volume exceeds average by customizable multiplier
Price Movement Analysis - Tracks significant price changes with adjustable threshold
Smart Direction Detection - Distinguishes between big buy and sell orders
Visual Markers - Clear arrows, background highlights, and detailed labels
Flexible Settings - Fully customizable parameters for different trading styles
Statistics Table - Optional real-time order count tracking
Alert System - Built-in alerts for automated notifications
⚙️ How It Works:
The indicator combines volume analysis with price movement detection to identify unusual market activity. When volume significantly exceeds the moving average AND price shows meaningful movement, it marks these as potential whale orders.
🎯 Best Used For:
Crypto markets with high volume activity
Forex pairs during major news events
Stock trading around earnings/announcements
Identifying institutional accumulation/distribution
📈 Settings Guide:
Volume Multiplier (3.0) - How many times above average volume (recommended minimum: 3.0)
Volume Period (20) - Moving average period for volume
Price Threshold (1.5%) - Minimum price change requirement
Visual Options - Toggle arrows, labels, and background highlights
💡 Trading Tips:
Use on liquid markets with consistent volume
Combine with support/resistance levels
Higher timeframes show more significant orders
Adjust sensitivity based on market volatility
⚠️ Important Notes:
Not financial advice - for educational purposes only
Past performance doesn't guarantee future results
Always use proper risk management
Test parameters on your specific markets
Perfect for swing traders, day traders, and anyone looking to spot whale activity in their favorite markets!
Anchored Grids ft. VolumeINTRO
The 'Volume Profile' is a great tool, isn’t it? It shows us where volume has accumulated on the chart and helps guide trading decisions. The only catch is that we can’t really choose the levels—it’s all based on where volume happens to cluster. But what if we reversed the logic and measured the volume at the levels we define? That’s exactly what this script does, giving you a fresh way to spot support and resistance :)
OVERVIEW
'Anchored Grids ft. Volume' is a sophisticated technical analysis tool that combines price grid analysis with volume accumulation metrics. This indicator dynamically calculates and displays custom support and resistance levels based on a user-defined timeframe, while simultaneously tracking and visualizing volume accumulation at each specific price level. Unlike traditional volume profile indicators that use complex statistical clustering, this tool provides straightforward volume measurement at predetermined technical levels. It answers a critical question: "How much trading activity occurred near the key price levels I care about?".
HOW DOES THIS INDICATOR WORK?
This indicator builds a customizable grid system anchored to the opening price of any user-selected timeframe (hourly, daily, weekly, etc.). From that anchor point, it continuously tracks the highest high and lowest low, then calculates equidistant grid levels within that range. Two calculation modes are available—Arithmetic and Geometric—allowing flexibility in how the levels are distributed.
Once the grid is established, a volume accumulation engine comes into play. For each price bar, the script checks whether the bar’s range intersects with any level’s tolerance zone (default 0.01%). If a touch is detected, that bar’s volume is added to the corresponding level. Over time, this process builds a clear picture of where significant trading activity has clustered.
The visualization system highlights these dynamics by applying a color gradient based on volume intensity and adjusting line thickness proportional to accumulated volume. Each level is also labeled with four key data points:
The grid number (in square brackets)
The price of the level
The percentage distance between the level and the opening price of the selected timeframe
The total volume accumulated within the level’s tolerance range
PARAMETERS
Timeframe: Defines the anchor period for grid calculation. Then, the indicator automatically determines the open, high, and low prices.
Mode: This option determines how the distance between levels is calculated: Arithmetic (linear) means equal price spacing between levels, while Geometric (logarithmic) means equal percentage spacing between levels.
Grids: It's the number of levels between high and low.
Color: Base color for grid lines and labels. When volume data is displayed, lower values are darkened by 50%.
Show Volume Accumulation: When this parameter is activated, the volume calculation is enabled.
Tolerance : The Tolerance parameter (default range: 0.01%) defines the price range around each grid level where volume accumulation is registered. It acts as a sensitivity control that determines how close price must be to a level to count trading volume toward that level's accumulation.
ORIGINALITY
It’s possible to find comprehensive grid-drawing tools among community indicators, but I haven’t come across an example that combines this concept with volume data. More importantly, I wanted to demonstrate how volume accumulation can be generated for any data modeled as an array on the chart by developers.
SUMMARY
In conclusion, the selected timeframe and the number of grids are only used as a reference to determine where the levels are drawn. The true value of this indicator lies in its ability to calculate volume accumulation directly from the chart’s own candles, showing how much trading activity occurred around each level. The result is a hybrid framework that merges structural price analysis with volume distribution, offering traders deeper insights into where markets are likely to react.
NOTE
While powerful, this tool should be used as part of a comprehensive trading strategy rather than as a standalone system. Always combine with risk management principles and market context awareness. I hope it helps everyone. Trade as safely as possible. Best of luck!
AltCoin & MemeCoin Index Correlation [Eddie_Bitcoin]🧠 Philosophy of the Strategy
The AltCoin & MemeCoin Index Correlation Strategy by Eddie_Bitcoin is a carefully engineered trend-following system built specifically for the highly volatile and sentiment-driven world of altcoins and memecoins.
This strategy recognizes that crypto markets—especially niche sectors like memecoins—are not only influenced by individual price action but also by the relative strength or weakness of their broader sector. Hence, it attempts to improve the reliability of trading signals by requiring alignment between a specific coin’s trend and its sector-wide index trend.
Rather than treating each crypto asset in isolation, this strategy dynamically incorporates real-time dominance metrics from custom indices (OTHERS.D and MEME.D) and combines them with local price action through dual exponential moving average (EMA) crossovers. Only when both the asset and its sector are moving in the same direction does it allow for trade entries—making it a confluence-based system rather than a single-signal strategy.
It supports risk-aware capital allocation, partial exits, configurable stop loss and take profit levels, and a scalable equity-compounding model.
✅ Why did I choose OTHERS.D and MEME.D as reference indices?
I selected OTHERS.D and MEME.D because they offer a sector-focused view of crypto market dynamics, especially relevant when trading altcoins and memecoins.
🔹 OTHERS.D tracks the market dominance of all cryptocurrencies outside the top 10 by market cap.
This excludes not only BTC and ETH, but also major stablecoins like USDT and USDC, making it a cleaner indicator of risk appetite across true altcoins.
🔹 This is particularly useful for detecting "Altcoin Season"—periods where capital rotates away from Bitcoin and flows into smaller-cap coins.
A rising OTHERS.D often signals the start of broader altcoin rallies.
🔹 MEME.D, on the other hand, captures the speculative behavior of memecoin segments, which are often driven by retail hype and social media activity.
It's perfect for timing momentum shifts in high-risk, high-reward tokens.
By using these indices, the strategy aligns entries with broader sector trends, filtering out noise and increasing the probability of catching true directional moves, especially in phases of capital rotation and altcoin risk-on behavior.
📐 How It Works — Core Logic and Execution Model
At its heart, this strategy employs dual EMA crossover detection—one pair for the asset being traded and one pair for the selected market index.
A trade is only executed when both EMA crossovers agree on the direction. For example:
Long Entry: Coin's fast EMA > slow EMA and Index's fast EMA > slow EMA
Short Entry: Coin's fast EMA < slow EMA and Index's fast EMA < slow EMA
You can disable the index filter and trade solely based on the asset’s trend just to make a comparison and see if improves a classic EMA crossover strategy.
Additionally, the strategy includes:
- Adaptive position sizing, based on fixed capital or current equity (compound mode)
- Take Profit and Stop Loss in percentage terms
- Smart partial exits when trend momentum fades
- Date filtering for precise backtesting over specific timeframes
- Real-time performance stats, equity tracking, and visual cues on chart
⚙️ Parameters & Customization
🔁 EMA Settings
Each EMA pair is customizable:
Coin Fast EMA: Default = 47
Coin Slow EMA: Default = 50
Index Fast EMA: Default = 47
Index Slow EMA: Default = 50
These control the sensitivity of the trend detection. A wider spread gives smoother, slower entries; a narrower spread makes it more responsive.
🧭 Index Reference
The correlation mechanism uses CryptoCap sector dominance indexes:
OTHERS.D: Dominance of all coins EXCLUDING Top 10 ones
MEME.D: Dominance of all Meme coins
These are dynamically calculated using:
OTHERS_D = OTHERS_cap / TOTAL_cap * 100
MEME_D = MEME_cap / TOTAL_cap * 100
You can select:
Reference Index: OTHERS.D or MEME.D
Or disable the index reference completely (Don't Use Index Reference)
💰 Position Sizing & Risk Management
Two capital allocation models are supported:
- Fixed % of initial capital (default)
- Compound profits, which scales positions as equity grows
Settings:
- Compound profits?: true/false
- % of equity: Between 1% and 200% (default = 10%)
This is critical for users who want to balance growth with risk.
🎯 Take Profit / Stop Loss
Customizable thresholds determine automatic exits:
- TakeProfit: Default = 99999 (disabled)
- StopLoss: Default = 5 (%)
These exits are percentage-based and operate off the entry price vs. current close.
📉 Trend Weakening Exit (Scale Out)
If the position is in profit but the trend weakens (e.g., EMA color signals trend loss), the strategy can partially close a configurable portion of the position:
- Scale Position on Weak Trend?: true/false
- Scaled Percentage: % to close (default = 65%)
This feature is useful for preserving profits without exiting completely.
📆 Date Filter
Useful for segmenting performance over specific timeframes (e.g., bull vs bear markets):
- Filter Date Range of Backtest: ON/OFF
- Start Date and End Date: Custom time range
OTHER PARAMETERS EXPLANATION (Strategy "Properties" Tab):
- Initial Capital is set to 100 USD
- Commission is set to 0.055% (The ones I have on Bybit)
- Slippage is set to 3 ticks
- Margin (short and long) are set to 0.001% to avoid "overspending" your initial capital allocation
📊 Visual Feedback and Debug Tools
📈 EMA Trend Visualization
The slow EMA line is dynamically color-coded to visually display the alignment between the asset trend and the index trend:
Lime: Coin and index both bullish
Teal: Only coin bullish
Maroon: Only index bullish
Red: Both bearish
This allows for immediate visual confirmation of current trend strength.
💬 Real-Time PnL Labels
When a trade closes, a label shows:
Previous trade return in % (first value is the effective PL)
Green background for profit, Red for losses.
📑 Summary Table Overlay
This table appears in a corner of the chart (user-defined) and shows live performance data including:
Trade direction (yellow long, purple short)
Emojis: 💚 for current profit, 😡 for current loss
Total number of trades
Win rate
Max drawdown
Duration in days
Current trade profit/loss (absolute and %)
Cumulative PnL (absolute and %)
APR (Annualized Percentage Return)
Each metric is color-coded:
Green for strong results
Yellow/orange for average
Red/maroon for poor performance
You can select where this appears:
Top Left
Top Right
Bottom Left
Bottom Right (default)
📚 Interpretation of Key Metrics
Equity Multiplier: How many times initial capital has grown (e.g., “1.75x”)
Net Profit: Total gains including open positions
Max Drawdown: Largest peak-to-valley drop in strategy equity
APR: Annualized return calculated based on equity growth and days elapsed
Win Rate: % of profitable trades
PnL %: Percentage profit on the most recent trade
🧠 Advanced Logic & Safety Features
🛑 “Don’t Re-Enter” Filter
If a trade is closed due to StopLoss without a confirmed reversal, the strategy avoids re-entering in that same direction until conditions improve. This prevents false reversals and repetitive losses in sideways markets.
🧷 Equity Protection
No new trades are initiated if equity falls below initial_capital / 30. This avoids overleveraging or continuing to trade when capital preservation is critical.
Keep in mind that past results in no way guarantee future performance.
Eddie Bitcoin
IFVG by Toño# IFVG by Toño - Pine Script Indicator
## Overview
This Pine Script indicator identifies and visualizes **Fair Value Gaps (FVG)** and **Inverted Fair Value Gaps (IFVG)** on trading charts. It provides advanced analysis of price inefficiencies and their subsequent inversions when mitigated.
## Key Features
### 1. Fair Value Gap (FVG) Detection
- **Bullish FVG**: Detected when `low > high ` (gap between current low and high of 2 bars ago)
- **Bearish FVG**: Detected when `high < low ` (gap between current high and low of 2 bars ago)
- Visual representation using colored rectangles (green for bullish, red for bearish)
### 2. Inverted Fair Value Gap (IFVG) Creation
- **IFVG Formation**: When a FVG gets mitigated (price fills the gap with candle body), an IFVG is created
- **Color Inversion**: The IFVG takes the opposite color of the original FVG
- Mitigated bullish FVG → Creates red (bearish) IFVG
- Mitigated bearish FVG → Creates green (bullish) IFVG
- **Mitigation Logic**: Uses only candle body (not wicks) to determine when a FVG is filled
### 3. Customizable Display Options
- **Show Normal FVG**: Toggle visibility of regular Fair Value Gaps
- **Show IFVG**: Toggle visibility of Inverted Fair Value Gaps
- **Smart FVG Display**: Even when "Show Normal FVG" is disabled, FVGs that are part of IFVGs remain visible
- **Extension Control**: Option to extend FVGs until they are mitigated
### 4. IFVG Extension Methods
- **Full Cross Method**: IFVG remains active until price completely crosses through it (including wicks)
- **Number of Bars Method**: IFVG remains active for a specified number of bars (1-100)
### 5. Visual Mitigation Signals
- **Cross Markers**: Shows X-shaped markers when IFVGs are mitigated
- Green cross above bar: Bearish IFVG mitigated
- Red cross below bar: Bullish IFVG mitigated
### 6. Comprehensive Alert System
- **IFVG Formation Alerts**: Notifications when new IFVGs are created
- **IFVG Mitigation Alerts**: Notifications when IFVGs are filled/mitigated
- **Separate Controls**: Individual toggles for bullish and bearish IFVG alerts
## How It Works
### Step-by-Step Process:
1. **FVG Detection**: Script continuously scans for 3-bar patterns that create price gaps
2. **FVG Tracking**: Each FVG is stored with its coordinates, type, and status
3. **Mitigation Monitoring**: Script watches for candle bodies that fill the FVG
4. **IFVG Creation**: Upon mitigation, creates an IFVG with opposite polarity at the same location
5. **IFVG Management**: Tracks and extends IFVGs according to chosen method
6. **Visual Updates**: Dynamically updates colors and visibility based on user settings
## Use Cases
- **Support/Resistance Analysis**: IFVGs often act as strong support/resistance levels
- **Market Structure Understanding**: Helps identify how market inefficiencies get filled and reversed
- **Entry/Exit Timing**: Can be used to time entries around IFVG formations or mitigations
- **Confluence Analysis**: Combine with other technical analysis tools for stronger signals
## Configuration Parameters
- **Colors**: Customizable colors for bullish/bearish FVGs and IFVGs
- **Extension**: Choose how long to display gaps on the chart
- **Alerts**: Full control over notification preferences
- **Visual Clarity**: Options to show/hide different gap types for cleaner charts
## Technical Specifications
- **Pine Script Version**: 5
- **Overlay**: True (displays directly on price chart)
- **Max Boxes**: 500 (supports up to 500 simultaneous gaps)
- **Performance**: Optimized array management for smooth operation
This indicator is particularly valuable for traders who use **Smart Money Concepts (SMC)** and **Inner Circle Trader (ICT)** methodologies, as it provides clear visualization of how institutional order flow creates and fills market inefficiencies.
Volatility Zones (VStop + Bands) — Fixed (v2)📝 What this indicator is
This script is called “Volatility Zones (VStop + Bands)”.
It is an ATR-based volatility indicator that combines dynamic volatility bands, a Volatility Stop line (VStop), and volatility spike detection into a single tool.
Unlike moving average–based indicators, this tool does not rely on averages of price direction. Instead, it measures the market’s true volatility and reacts to expansions or contractions in price ranges.
________________________________________
⚙️ How it is built
The indicator uses several volatility-based components:
1. Average True Range (ATR)
o ATR is calculated over a user-defined length.
o It measures how much price typically moves in a given number of bars, making it the foundation of this indicator.
2. Volatility Bands
o Upper band = close + ATR × factor
o Lower band = close - ATR × factor
o The area between them is shaded.
o This gives traders an immediate visual sense of market volatility width — wide bands = high volatility, narrow bands = quiet market.
3. Volatility Stop (VStop)
o A stateful trailing stop based on ATR.
o It tracks the highest (or lowest) price in the current trend and places a stop offset by ATR × multiplier.
o When price crosses this stop, the indicator flips trend direction.
o This creates a dynamic stop-and-reverse mechanism that adapts to volatility.
4. Trend Zones
o When the trend is bullish, the stop is green and the chart background is shaded softly green.
o When bearish, the stop is red and the background is shaded softly red.
o This makes the market’s directional bias visually clear at all times.
5. Flip Signals (Buy/Sell Arrows)
o Whenever the VStop flips, arrows appear:
Green BUY arrows below price when the trend turns bullish.
Red SELL arrows above price when the trend turns bearish.
o These are also tied to built-in alerts for automation.
6. Volatility Spike Detection
o The script compares current ATR to its recent average.
o If ATR suddenly expands above a threshold, a small yellow “VOL” marker appears at the top of the chart.
o This highlights potential breakout phases or unusual volatility events.
7. Stop Labels
o At every trend flip, a small label appears at the bar, showing the exact stop level.
o This makes it easy to use the stop as a reference for risk management.
________________________________________
📊 How it works in practice
• When price is above the VStop line, the market is considered in an uptrend.
• When price is below the VStop line, the market is in a downtrend.
• The bands expand/contract with volatility, helping traders gauge risk and position sizing.
• Flip arrows signal when trend direction changes.
• Volatility spikes warn traders that the market is entering a higher-risk phase, often before strong moves.
________________________________________
🎯 How it may help traders
• Trend following → Helps traders identify whether the market is trending up or down.
• Stop placement → Provides a dynamic stop level that adjusts to volatility.
• Volatility awareness → Shaded bands and spike markers show when the market is likely to become unstable.
• Trade timing → Flip arrows and labels help identify potential entry or exit points.
• Risk management → Wide bands indicate higher risk; narrow bands suggest safer, tighter ranges.
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🌍 In what markets it is useful
Because the indicator is based purely on volatility, it works across all asset classes and timeframes:
• Stocks & ETFs → Helps identify breakouts and long-term trends.
• Forex → Very useful in spot FX where volatility shifts frequently.
• Crypto → ATR reacts strongly to high volatility, helping traders adapt stops dynamically.
• Futures & Commodities → Great for tracking trending commodities and managing risk.
Scalpers, swing traders, and position traders can all benefit by adjusting the ATR length and multipliers to suit their trading style.
________________________________________
💡 Originality of this script
This is not just a mashup of existing indicators. It integrates:
• ATR-based Volatility Bands for context,
• A stateful Volatility Stop (adapted and rewritten cleanly),
• Flip arrows and labels for actionable trading signals,
• Volatility spike detection to highlight regime shifts.
The result is a comprehensive volatility-aware trading tool that goes beyond just plotting ATR or trend stops.
________________________________________
🔔 Alerts
• Buy Flip → triggers when the trend changes bullish.
• Sell Flip → triggers when the trend changes bearish.
Traders can connect these alerts to automated strategies, bots, or notification systems.
