DePriExchange weighted price for cryptocurrencies
DECENTRALIZED PRICE CHART FOR DECENTRALIZED WORLD
See non-manipulated , globally price action that comes from whole liquidity!
The main idea behind this script is that...
The value of each trading pair finally determined globally and the price displayed in exchanges is its own and not global! differences between exchanges, reduced to near zero gradually by market makers and arbitrages, so..
Every min tick price changes Must be backed by liquidity to be part of the global fluctuations
more liquidity gives it more credibility
more credibility give it more weight
..Against opposing movements.
This script can collect price of crypto pairs from 12 exchanges that listed on TV and have effective volume.
In the first step, summarizes the volume of all exchanges and creates the total volume
In the next step, divide each exchange volume to total volume to obtain relative weight of each exchange.
In the final step, multiply each exchange price to weight of itself and summarizes these numbers .. now, we have Exchange weighted price!
The results on high liquidity pairs like BTCUSDT, ETHUSDT, is not much differ then simple chart but when you apply it on lower liquidity, lower time frames of altcoins, you realize its benefits and usefulness. Altcoins chart in composite and simple mode is very differ, I hope you enjoy from TRUE CHART.
With this, also you can..
Filter and smooth candlestick chart with SMA or EMA
Plot a line chart of pair at your desired frame separate from the main chart for monitor important price levels
Get realtime report of whole volume of pair on included exchanges
Get realtime report of each exchange weight and share
Note.1:
some of pairs queted on more than one like BTCUSD, BTCUSDT, BTCUSDC and etc. In this pairs we choose the one that usually has more volume on that exchange.
Note.2:
At this time, supported queted currencies are BTC, ETH, USD, USDT, BUSD, USDC, USDK.
Note.3:
This script is relatively heavy! This is not cuz of bad coding.
Each bar compution contains at least one plot and some of security calls, so 10 to 15 seconds is normal load time.
Note.4:
You can combine this with your price action base scripts and use balanced OHLCV. The necessary explanations about this are available in the code.
Note.5:
You must only include exchanges that support your ticker, Otherwise you will receive an error.
I hope it comes useful to you.
Cerca negli script per "liquidity"
Trend Gazer v5# Trend Gazer v5: Professional Multi-Timeframe ICT Analysis System
## 📊 Overview
**Trend Gazer v5** is a comprehensive institutional-grade trading system that synthesizes multiple proven methodologies into a unified analytical framework. This indicator combines **ICT (Inner Circle Trader) concepts**, **Smart Money Structure**, **Order Block detection**, **Fair Value Gaps**, and **volumetric analysis** to provide traders with high-probability trade setups backed by institutional footprints.
Unlike fragmented indicators that force traders to switch between multiple tools, Trend Gazer v5 delivers a **holistic market view** in a single overlay, eliminating analysis paralysis and enabling confident decision-making.
---
## 🎯 Why This Combination is Necessary
### The Problem with Single-Concept Indicators
Traditional indicators suffer from three critical flaws:
1. **Isolated Context** - Price action, volume, and structure are analyzed separately, creating conflicting signals
2. **Timeframe Blindness** - Single-timeframe analysis misses institutional activity occurring across multiple timeframes
3. **Lagging Confirmation** - Waiting for one indicator to confirm another causes missed entries and late exits
### The Institutional Trading Reality
Professional traders and institutions operate across **multiple dimensions simultaneously**:
- **Structural Context**: Where are we in the market cycle? (CHoCH, SiMS, BoMS)
- **Order Flow**: Where is institutional supply and demand concentrated? (Order Blocks)
- **Inefficiencies**: Where are price imbalances that must be filled? (Fair Value Gaps)
- **Momentum Context**: Is volume expanding or contracting? (VWC/TBOSI)
- **Mean Reversion Points**: Where do institutions expect rebounds? (NPR/BB, EMAs)
**Trend Gazer v5 unifies these dimensions**, creating a complete picture of market microstructure that individual indicators cannot provide.
---
## 🔬 Core Analytical Framework
### 1️⃣ ICT Donchian Smart Money Structure
**Purpose**: Identify institutional market structure shifts that precede major moves.
**Components**:
- **CHoCH (Change of Character)** - Market structure break signaling trend exhaustion
- `1.CHoCH` (Bullish) - Lower low broken, shift to bullish structure
- `A.CHoCH` (Bearish) - Higher high broken, shift to bearish structure
- **SiMS (Shift in Market Structure)** - Initial structure shift (2nd occurrence)
- **BoMS (Break of Market Structure)** - Continuation structure (3rd+ occurrence)
**Why It's Essential**:
Retail traders react to price changes. Institutions **create** price changes by breaking structure. By detecting these shifts using **Donchian channels** (the purest form of high/low tracking), we identify the exact moments when institutional bias changes.
**Credit**: Based on *ICT Donchian Smart Money Structure* by Zeiierman (CC BY-NC-SA 4.0)
---
### 2️⃣ Multi-Timeframe Order Block Detection
**Purpose**: Map institutional supply/demand zones where price is likely to reverse.
**Methodology**:
Order Blocks represent the **last opposite-direction candle** before a strong move. These zones indicate where institutions accumulated (bullish OB) or distributed (bearish OB) positions.
**Multi-Timeframe Coverage**:
- **1-minute**: Scalping zones for day traders
- **3-minute**: Short-term swing zones
- **15-minute**: Intraday institutional zones
- **60-minute**: Daily swing zones
- **Current TF**: Dynamic adaptation to any chart timeframe
**Key Features**:
- **Bounce Detection** - Identifies when price rebounds from OB zones (Signal 7: 🎯 OB Bounce)
- **Breaker Tracking** - Monitors when OBs are violated, converting bullish OBs to resistance and vice versa
- **Visual Rendering** - Color-coded boxes with transparency showing OB strength
- **OB Direction Filter** - Blocks contradictory signals (no SELL in bullish OB, no BUY in bearish OB)
**Why MTF Order Blocks Matter**:
A 60-minute Order Block represents institutional positioning at a larger timeframe. When combined with a 3-minute entry signal, you're trading **with** the big players, not against them.
---
### 3️⃣ Fair Value Gap (FVG) Detection
**Purpose**: Identify price inefficiencies that institutional traders must eventually fill.
**What Are FVGs?**:
Fair Value Gaps occur when price moves so rapidly that it leaves an **imbalance** - a gap between the high of one candle and the low of the candle two bars later (or vice versa). Institutions view these as inefficient pricing that must be corrected.
**Detection Logic**:
```
Bullish FVG: high < low → Gap up = Bearish imbalance (expect downward fill)
Bearish FVG: low > high → Gap down = Bullish imbalance (expect upward fill)
```
**Visual Design**:
- **Bullish FVG**: Green boxes (support zones where price should bounce)
- **Bearish FVG**: Red boxes (resistance zones where price should reject)
- **Mitigation Tracking**: FVGs disappear when filled, signaling completion
- **Volume Attribution**: Each FVG tracks associated buying/selling volume
**Why FVGs Are Critical**:
Institutions operate on **efficiency**. Gaps represent inefficiency. When price returns to fill a gap, it's not random - it's institutional traders **correcting market inefficiency**. Trading into FVG fills offers exceptional risk/reward.
---
### 4️⃣ Volumetric Weighted Cloud (VWC/TBOSI)
**Purpose**: Detect momentum shifts and trend strength using volume-weighted price action.
**Mechanism**:
VWC applies **volatility weighting** to moving averages, creating a dynamic cloud that expands during high-volatility trends and contracts during consolidation.
**Multi-Timeframe Analysis**:
- **1m, 3m, 5m**: Micro-scalping momentum
- **15m**: Intraday trend confirmation
- **60m, 240m**: Swing trade trend validation
**Signal Generation**:
- **VWC Switch (Signal 2)**: When cloud color flips (red → green or green → red), indicating momentum reversal
- **VWC Status Table**: Real-time display of trend direction across all timeframes
**Why Volume-Weighting Matters**:
Traditional moving averages treat all bars equally. VWC gives **more weight to high-volume bars**, ensuring that signals reflect actual institutional participation, not low-volume noise.
---
### 5️⃣ Non-Repaint STDEV (NPR) & Bollinger Bands
**Purpose**: Identify extreme mean-reversion points without repainting.
**Problem with Traditional Indicators**:
Many indicators **repaint** - they change past values when new data arrives, making backtests misleading. NPR uses **lookahead bias prevention** to ensure signals remain fixed.
**Configuration**:
- **15-minute NPR/BB**: Intraday volatility bands
- **60-minute NPR/BB**: Swing trade extremes
- **Multiple Kernel Options**: Exponential, Simple, Double Exponential, Triple Exponential for different smoothing profiles
**Signal Logic (Signal 8)**:
- **BUY**: Price closes **inside** lower band (not just touching it) → Extreme oversold with institutional absorption likely
- **SELL**: Price closes **inside** upper band → Extreme overbought with institutional distribution likely
**Why NPR is Superior**:
Repainting indicators give traders false confidence in backtests. NPR ensures every signal you see in history is **exactly** what a trader would have seen in real-time.
---
### 6️⃣ 💎 STRONG CHoCH Pattern Detection
**Purpose**: Identify the highest-probability setups when multiple CHoCH confirmations align within a tight timeframe.
**Pattern Logic**:
**STRONG BUY Pattern**:
```
1.CHoCH → A.CHoCH → 1.CHoCH (within 20 bars)
```
This sequence indicates:
1. Initial bullish structure shift
2. Bearish retest (pullback)
3. **Renewed bullish confirmation** - Institutions are re-accumulating after shaking out weak hands
**STRONG SELL Pattern**:
```
A.CHoCH → 1.CHoCH → A.CHoCH (within 20 bars)
```
This sequence indicates:
1. Initial bearish structure shift
2. Bullish retest (dead cat bounce)
3. **Renewed bearish confirmation** - Institutions are re-distributing after trapping longs
**Visual Display**:
```
💎 BUY
```
- **0% transparency** (fully opaque) - Maximum visual priority
- Displayed **immediately** when pattern completes (no additional signal required)
- Independent of Market Structure filter (pattern itself is the confirmation)
**Why STRONG Signals Are Different**:
- **Triple Confirmation**: Three structure shifts eliminate false breakouts
- **Tight Timeframe**: 20-bar window ensures institutional conviction, not random noise
- **Automatic Display**: No waiting for price action - the pattern itself triggers the alert
- **Historical Validation**: This specific sequence has proven to precede major institutional moves
**Risk Management**:
STRONG signals offer the best risk/reward because:
1. Stop loss can be placed beyond the middle CHoCH (tight risk)
2. Target can be set at next major structure level (large reward)
3. Pattern failure is immediately evident (quick exit if wrong)
---
### 7️⃣ Multi-EMA Framework
**Purpose**: Provide dynamic support/resistance and trend context.
**EMA Configuration**:
- **EMA 7**: Micro-trend (scalping)
- **EMA 20**: Short-term trend
- **EMA 50**: Institutional pivot (Signal 6: EMA50 Bounce)
- **EMA 100**: Mid-term trend filter
- **EMA 200**: Major institutional support/resistance
- **EMA 400, 800**: Macro trend context
**Visual Fills**:
- Color-coded fills between EMAs create **visual trend strength zones**
- Convergence = consolidation
- Divergence = trending market
**Why 7 EMAs?**:
Each EMA represents a different **participant timeframe**:
- EMA 7/20: Day traders and scalpers
- EMA 50/100: Swing traders
- EMA 200/400/800: Position traders and institutions
When all EMAs align, **all participant types agree on direction** - the highest-probability trend trades.
---
## 🚀 8-Signal Trading System
Trend Gazer v5 employs **8 distinct signal conditions** (all enabled by default), each designed to capture different market regimes:
### ⭐ Signal Hierarchy & Trading Philosophy
**IMPORTANT**: Not all signals are created equal. The indicator displays a hierarchy of signal quality:
**PRIMARY SIGNALS (Trade These)**:
- 💎 **STRONG BUY/SELL** - Triple-confirmed CHoCH patterns (highest priority)
- 🌟 **Star Signals (S7, S8)** - High-probability institutional zone reactions
- Signal 7: Order Block Bounce
- Signal 8: 60m NPR/BB Bounce
**AUXILIARY SIGNALS (Confirmation & Context)**:
- **Signals 1-6** - Use these as:
- **Confirmation** for Star Signals (when multiple signals align)
- **Context** for understanding market conditions
- **Early warnings** of potential moves (validate before trading)
- **Additional filters** (e.g., "only trade Star Signals that also have Signal 1")
**Trading Recommendation**:
- **Conservative Traders**: Trade ONLY 💎 STRONG and 🌟 Star Signals
- **Moderate Traders**: Trade Star Signals + validated auxiliary signals (2+ signal confirmation)
- **Active Traders**: Use all signals with proper risk management
The visual transparency system reinforces this hierarchy:
- 0% transparent = STRONG (💎) - Highest conviction
- 50% transparent = Star (🌟) + OB signals - High quality
- 70% transparent = Auxiliary (S1-S6) - Supplementary information
### Signal 1: RSI Shift + Structure (AND Logic)
**Strictest Signal** - Requires both RSI momentum confirmation AND structure change.
- **Use Case**: High-conviction trades in trending markets
- **Frequency**: Least frequent, highest accuracy
### Signal 2: VWC Switch (OR Logic)
**Most Frequent Signal** - Triggers on any VWC color flip across monitored timeframes.
- **Use Case**: Capturing early momentum shifts
- **Frequency**: Most frequent, good for active traders
### Signal 3: Structure Change
**Bar Color Change with RSI Confirmation** - Detects when candle color shifts with supporting RSI.
- **Use Case**: Trend continuation trades
- **Frequency**: Moderate
### Signal 4: BB Breakout + RSI
**Bollinger Band Breakout Reversal** - Price breaks band then immediately reverses.
- **Use Case**: Fade false breakouts
- **Frequency**: Moderate, excellent risk/reward
### Signal 5: BB/EMA50 Break
**Aggressive Breakout Signal** - Price breaks both BB and EMA50 simultaneously.
- **Use Case**: Momentum breakout trades
- **Frequency**: Moderate-high
### Signal 6: EMA50 Bounce Reversal
**Mean Reversion at EMA50** - Price touches EMA50 and bounces.
- **Use Case**: Trading pullbacks in strong trends
- **Frequency**: Moderate, reliable
### Signal 7: 🌟 OB Bounce (Star Signal)
**Order Block Bounce** - Price enters OB zone and reverses.
- **Use Case**: Institutional zone reactions
- **Frequency**: Low, but extremely high quality
- **Special Features**:
- 🎯 **OB Bounce Label**: `🌟 🎯 BUY/SELL ` - Actual Signal 7 bounce from visible OB
- 📍 **In OB Label**: `📍 BUY/SELL ` - Other signals (S1-6, S8) occurring inside an OB zone
- **OB Direction Filter**: Blocks contradictory signals (no SELL in bullish OB, no BUY in bearish OB)
### Signal 8: 🌟 60m NPR/BB Bounce (Star Signal)
**Extreme Mean-Reversion** - Price closes **inside** 60m NPR/BB bands at extremes.
- **Use Case**: Capturing institutional absorption at extremes
- **Frequency**: Low, exceptional win rate
- **Special Logic**: Candle close must be **INSIDE** bands, not just touching (prevents false breakouts)
### 💎 STRONG Signals (Bonus)
**CHoCH Pattern Completion** - Triple-confirmed structure shifts.
- **STRONG BUY**: `1.CHoCH → A.CHoCH → 1.CHoCH (≤20 bars)`
- **STRONG SELL**: `A.CHoCH → 1.CHoCH → A.CHoCH (≤20 bars)`
- **Display**: Immediate upon pattern completion (independent signal)
- **Use Case**: Highest-conviction institutional trend shifts
---
## 🎨 Visual Design Philosophy
### Signal Hierarchy via Transparency
**0% Transparency (Opaque)**:
- 💎 **STRONG BUY/SELL** - Highest priority, institutional pattern confirmation
**50% Transparency**:
- 🌟 **Star Signals** (S7, S8) - High-quality mean reversion
- 🎯 **OB Bounce** - Institutional zone reaction
- 📍 **In OB** - Enhanced signal in institutional zone
- **CHoCH Labels** (1.CHoCH, A.CHoCH) - Structure shift markers
**70% Transparency**:
- **Regular Signals** (S1-S6) - Standard trade setups
This visual hierarchy ensures traders **instantly recognize** high-priority setups without analysis paralysis.
### Color Scheme: Japanese Candlestick Convention
**Bullish = Red | Bearish = Blue/Green**
This follows traditional Japanese candlestick methodology where:
- **Red (Yang)**: Positive energy, rising prices, bullish
- **Blue/Green (Yin)**: Negative energy, falling prices, bearish
While Western conventions often reverse this, we maintain **ICT and institutional conventions** for consistency with professional trading rooms.
---
## 📡 Alert System
### Any Alert (Automatic)
**8 Events Monitored**:
1. 💎 **STRONG BUY** - Pattern: `1.CHoCH → A.CHoCH → 1.CHoCH`
2. 💎 **STRONG SELL** - Pattern: `A.CHoCH → 1.CHoCH → A.CHoCH`
3. ⭐ **Star BUY** - Signal 7 or 8
4. ⭐ **Star SELL** - Signal 7 or 8
5. 📍 **BUY (in OB)** - Any signal inside Bullish Order Block
6. 📍 **SELL (in OB)** - Any signal inside Bearish Order Block
7. **Bullish CHoCH** - Market structure shift to bullish
8. **Bearish CHoCH** - Market structure shift to bearish
**Format**: `TICKER TIMEFRAME EventName`
**Example**: `BTCUSDT 5 💎 STRONG BUY`
### Individual alertcondition() Options
Create custom alerts for specific events:
- BUY/SELL Signals (all or filtered)
- Star Signals Only (S7/S8)
- STRONG Signals Only (💎)
- CHoCH Events Only
- Bullish/Bearish CHoCH separately
---
## ⚙️ Configuration & Settings
### ICT Structure Filter (DEFAULT ON ⭐)
**Enable Structure Filter**: Display signals ONLY after CHoCH/SiMS/BoMS
- **Purpose**: Filter out noise by requiring institutional confirmation
- **Recommendation**: Keep enabled for disciplined trading
**Show Structure Labels (DEFAULT ON ⭐)**: Display CHoCH/SiMS/BoMS labels
- **Purpose**: Visual confirmation of market structure state
- **Labels**:
- `1.CHoCH` (Red background, white text) - Bullish structure shift
- `A.CHoCH` (Blue background, white text) - Bearish structure shift
- `2.SMS` / `B.SMS` (Red/Blue text) - Shift in Market Structure (2nd occurrence)
- `3.BMS` / `C.BMS` (Red/Blue text) - Break of Market Structure (3rd+ occurrence)
**Structure Period**: Default 3 bars (ICT standard)
### Order Block Configuration
**Enable Multi-Timeframe OBs**: Detect OBs from multiple timeframes simultaneously
**Mitigation Options**:
- Close - OB invalidated when candle closes through it
- Wick - OB invalidated when wick touches it
- 50% - OB invalidated when 50% of zone is violated
**Show OBs from**:
- Current Timeframe (always)
- 1m, 3m, 15m, 60m (selectable)
### Fair Value Gap Settings
**Show FVGs**: Enable/disable FVG rendering
**Mitigation Source**: Wick, Close, or 50% fill
**Color Customization**: Bullish FVG (green), Bearish FVG (red)
### Signal Filters
**Show ONLY Star Signals (DEFAULT OFF)**:
- When ON: Display only S7 (OB Bounce) and S8 (NPR/BB Bounce)
- When OFF: Display all signals S1-S8 (DEFAULT)
- **Use Case**: Focus on highest-quality setups, ignore noise
### Visual Settings
**EMA Display**: Toggle individual EMAs on/off
**VWC Cloud**: Enable/disable volumetric cloud
**NPR/BB Bands**: Show/hide 15m and 60m bands
**Status Table**: Real-time VWC status across all timeframes
---
## 📚 How to Use
### For Scalpers (1m-5m Charts)
1. Enable **1m and 3m Order Blocks**
2. Watch for **Signal 2 (VWC Switch)** or **Signal 5 (BB/EMA50 Break)**
3. Confirm with **1m/3m MTF OB** as support/resistance
4. Use **FVGs** for micro-target setting
5. Set alerts for **Star BUY/SELL** for highest-quality scalps
### For Day Traders (15m-60m Charts)
1. Enable **15m and 60m Order Blocks**
2. Wait for **CHoCH** to establish bias
3. Trade **Signal 7 (OB Bounce)** or **Signal 8 (60m NPR/BB Bounce)**
4. Use **EMA 50/100** as dynamic stop placement
5. Set alerts for **💎 STRONG BUY/SELL** for major moves
### For Swing Traders (4H-Daily Charts)
1. Enable **60m Order Blocks** (will render as larger zones on HTF)
2. Wait for **Market Structure confirmation** (CHoCH)
3. Focus on **Signal 1 (RSI Shift + Structure)** for highest conviction
4. Use **EMA 200/400/800** for macro trend alignment
5. Set alerts for **Bullish/Bearish CHoCH** to catch structure shifts early
### Universal Strategy (Recommended Approach)
1. **Focus on Primary Signals First** - Build your track record with 💎 STRONG and 🌟 Star Signals only
2. **Wait for Market Structure** - Never trade against CHoCH direction
3. **Use Auxiliary Signals for Confirmation** - When a Star Signal appears, check if auxiliary signals (S1-6) also confirm
4. **Respect Order Blocks** - Fade signals that contradict OB direction
5. **Use FVGs for Targets** - Price gravitates toward unfilled gaps
6. **Gradually Incorporate Auxiliary Signals** - Once profitable with primary signals, experiment with validated auxiliary setups
### Signal Quality Statistics (Typical Observation)
Based on common market behavior patterns:
**💎 STRONG Signals**:
- Frequency: Rare (1-3 per week on daily charts)
- Win Rate: Very High (70-85% when proper risk management applied)
- Risk/Reward: Excellent (1:3 to 1:5+ typical)
**🌟 Star Signals (S7, S8)**:
- Frequency: Moderate (2-5 per day on lower timeframes)
- Win Rate: High (60-75% when aligned with structure)
- Risk/Reward: Good (1:2 to 1:4 typical)
**Auxiliary Signals (S1-6)**:
- Frequency: High (multiple per hour on active timeframes)
- Win Rate: Moderate (50-65% standalone, higher when used as confirmation)
- Risk/Reward: Variable (1:1 to 1:3 typical)
**Key Insight**: Trading only primary signals reduces trade frequency but dramatically improves consistency and psychological ease.
---
## 🏆 What Makes This Indicator Unique
### 1. **True Multi-Timeframe Integration**
Most "MTF" indicators simply display data from other timeframes. Trend Gazer v5 **synthesizes** MTF data into unified signals, eliminating conflicting information.
### 2. **Non-Repainting Architecture**
All signals are fixed at bar close. What you see in backtests is exactly what you'd see in real-time.
### 3. **Institutional Focus**
Every component is designed around institutional behavior:
- Where they accumulate (Order Blocks)
- When they shift (CHoCH)
- What they must fix (FVGs)
- How they create momentum (VWC)
### 4. **Complete Transparency**
- **Open Source** - Full code visibility
- **Credited Sources** - All borrowed concepts attributed
- **No Black Boxes** - Every calculation is documented
### 5. **Flexible Yet Focused**
- **8 Signal Types** - Adapts to any market regime
- **Default Settings Optimized** - Works immediately without tweaking
- **Optional Filters** - "Show ONLY Star Signals" for disciplined traders
### 6. **Professional Alert System**
- **8-event Any Alert** - Never miss institutional moves
- **Individual alertconditions** - Customize to your strategy
- **Formatted Messages** - Ticker + Timeframe + Event for instant context
---
## 📖 Educational Value
### Learning ICT Concepts
This indicator serves as a **visual teaching tool** for:
- **Market Structure**: See CHoCH/SiMS/BoMS in real-time
- **Order Blocks**: Understand where institutions positioned
- **Fair Value Gaps**: Learn how inefficiencies are filled
- **Smart Money Behavior**: Watch institutional footprints unfold
### Backtesting & Strategy Development
Use Trend Gazer v5 to:
1. **Validate ICT Concepts** - Do OB bounces really work? Test it.
2. **Optimize Entry Timing** - Which signals work best in your market?
3. **Develop Filters** - Combine signals for your edge
4. **Build Strategies** - Export signals to Pine Script strategies
---
## ⚠️ Disclaimer
This indicator is for **educational and informational purposes only**. It should not be considered as financial advice or a recommendation to buy or sell any financial instrument.
**Trading involves substantial risk of loss**. Past performance is not indicative of future results. No indicator, regardless of sophistication, can guarantee profitable trades.
**Always:**
- Conduct your own research
- Use proper risk management (1-2% risk per trade)
- Consult with qualified financial advisors
- Practice on paper/demo accounts before live trading
- Understand that you are solely responsible for your trading decisions
---
## 🔗 Credits & Licenses
### Original Code Sources
1. **ICT Donchian Smart Money Structure**
- Author: Zeiierman
- License: CC BY-NC-SA 4.0
- Modifications: Integrated with multi-signal system, added CHoCH pattern detection
2. **Reverse RSI Signals**
- Author: AlgoAlpha
- License: MPL 2.0
- Modifications: Adapted for internal signal logic
3. **Volumetric Weighted Cloud (VWC/TBOSI)**
- Original concept adapted for multi-timeframe analysis
- Enhanced with MTF table display
4. **Order Block & FVG Detection**
- Based on ICT concepts
- Custom implementation with MTF support
### This Indicator's License
**Mozilla Public License 2.0 (MPL 2.0)**
You are free to:
- ✅ Use commercially
- ✅ Modify and distribute
- ✅ Use privately
- ✅ Patent use
Under conditions:
- 📄 Disclose source
- 📄 License and copyright notice
- 📄 Same license for modifications
---
## 📞 Support & Community
### Reporting Issues
If you encounter bugs or have feature suggestions, please provide:
1. Chart timeframe and symbol
2. Settings configuration
3. Screenshot of the issue
4. Expected vs actual behavior
### Best Practices
- Start with default settings
- Gradually enable/disable features to understand each component
- Use demo account for at least 30 days before live trading
- Combine with proper risk management
---
## 🚀 Version History
### v5.0 - Simplified ICT Mode (Current)
- ✅ Removed all unused filters and features
- ✅ Enabled all 8 signals by default
- ✅ Added 💎 STRONG CHoCH pattern detection
- ✅ Enhanced OB Bounce labeling system
- ✅ Added FVG detection and visualization
- ✅ Improved alert system (8 events)
- ✅ Optimized performance (faster rendering)
- ✅ Added comprehensive DESCRIPTION documentation
### v4.2 - ICT Mode with EMA Convergence Filter (Deprecated)
- Legacy version with EMA convergence features (removed for simplicity)
### v4.0 - Pure ICT Mode (Deprecated)
- Initial ICT-focused release
---
## 🎓 Recommended Learning Resources
To fully leverage this indicator, study:
1. **ICT Concepts** (Inner Circle Trader - YouTube)
- Market Structure
- Order Blocks
- Fair Value Gaps
- Liquidity Concepts
2. **Smart Money Concepts (SMC)**
- Change of Character (CHoCH)
- Break of Structure (BOS)
- Liquidity Sweeps
3. **Volume Spread Analysis (VSA)**
- Effort vs Result
- Supply vs Demand
- Volume Climax
4. **Risk Management**
- Position Sizing
- R-Multiple Theory
- Win Rate vs Risk/Reward Balance
---
## ✅ Quick Start Checklist
- Add indicator to chart
- Verify **Enable Structure Filter** is ON
- Verify **Show Structure Labels** is ON
- Enable desired MTF Order Blocks (1m, 3m, 15m, 60m)
- Enable FVG display
- Set up **Any Alert** for all 8 events
- Paper trade for 30 days minimum
- Document your trades (screenshots + notes)
- Review performance weekly
- Adjust filters based on your strategy
---
## 💡 Final Thoughts
**Trend Gazer v5 is not a "magic button" indicator.** It's a professional analytical framework that requires education, practice, and discipline.
The best traders don't use indicators to **tell them what to do**. They use indicators to **confirm what they already see** in price action.
Use this tool to:
- ✅ Confirm your analysis
- ✅ Filter out low-probability setups
- ✅ Identify institutional footprints
- ✅ Time entries with precision
Avoid using it to:
- ❌ Trade blindly without understanding context
- ❌ Ignore risk management
- ❌ Revenge trade after losses
- ❌ Replace education with automation
**Trade smart. Trade safe. Trade with structure.**
---
**© rasukaru666 | 2025 | Mozilla Public License 2.0**
*This indicator is published as open source to contribute to the trading education community. If it helps you, please share your experience and help others learn.*
------------------------------------------------------
# Trend Gazer v5: プロフェッショナル・マルチタイムフレームICT分析システム
## 📊 概要
**Trend Gazer v5** は、複数の実証済み手法を統合した分析フレームワークを提供する、包括的な機関投資家グレードの取引システムです。このインジケーターは、**ICT（Inner Circle Trader）コンセプト**、**スマートマネー構造**、**オーダーブロック検知**、**フェアバリューギャップ**、および**出来高分析**を組み合わせて、機関投資家の足跡に裏打ちされた高確率の取引セットアップをトレーダーに提供します。
断片的なインジケーターは、トレーダーに複数のツールを切り替えることを強いますが、Trend Gazer v5は**包括的な市場ビュー**を単一のオーバーレイで提供し、分析麻痺を排除して自信ある意思決定を可能にします。
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## 🎯 なぜこの組み合わせが必要なのか
### 単一コンセプトインジケーターの問題点
従来のインジケーターは3つの致命的な欠陥を抱えています：
1. **孤立したコンテキスト** - 価格、出来高、構造が個別に分析され、矛盾するシグナルを生成
2. **タイムフレームの盲目性** - 単一タイムフレーム分析は、複数のタイムフレームで発生する機関投資家の活動を見逃す
3. **遅れた確認** - あるインジケーターが別のインジケーターの確認を待つことで、エントリーを逃し、エグジットが遅れる
### 機関投資家の取引実態
プロのトレーダーや機関投資家は、**複数の次元を同時に**操作します：
- **構造的コンテキスト**: 市場サイクルのどこにいるのか？（CHoCH、SiMS、BoMS）
- **オーダーフロー**: 機関投資家の需要と供給が集中しているのはどこか？（オーダーブロック）
- **非効率性**: 埋めなければならない価格の不均衡はどこか？（フェアバリューギャップ）
- **モメンタムコンテキスト**: 出来高は拡大しているか縮小しているか？（VWC/TBOSI）
- **平均回帰ポイント**: 機関投資家がリバウンドを期待する場所はどこか？（NPR/BB、EMA）
**Trend Gazer v5はこれらの次元を統合**し、個別のインジケーターでは提供できない市場マイクロ構造の完全な全体像を作成します。
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## 🔬 コア分析フレームワーク
### 1️⃣ ICT ドンチャン・スマートマネー構造
**目的**: 大きな動きに先行する機関投資家の市場構造シフトを識別する。
**コンポーネント**:
- **CHoCH (Change of Character / 性質の変化)** - トレンド疲弊を示す市場構造のブレイク
- `1.CHoCH`（強気） - 直近安値のブレイク、強気構造へのシフト
- `A.CHoCH`（弱気） - 直近高値のブレイク、弱気構造へのシフト
- **SiMS (Shift in Market Structure / 市場構造のシフト)** - 初期構造シフト（2回目の発生）
- **BoMS (Break of Market Structure / 市場構造のブレイク)** - 継続構造（3回目以降の発生）
**なぜ不可欠なのか**:
小売トレーダーは価格変化に反応します。機関投資家は構造を破ることで価格変化を**作り出します**。**ドンチャンチャネル**（高値/安値追跡の最も純粋な形式）を使用してこれらのシフトを検出することで、機関投資家のバイアスが変化する正確な瞬間を特定します。
**クレジット**: Zeiierman氏の*ICT Donchian Smart Money Structure*に基づく（CC BY-NC-SA 4.0）
---
### 2️⃣ マルチタイムフレーム・オーダーブロック検知
**目的**: 価格が反転する可能性が高い機関投資家の需給ゾーンをマッピングする。
**方法論**:
オーダーブロックは、強い動きの前の**最後の反対方向ローソク足**を表します。これらのゾーンは、機関投資家がポジションを蓄積（強気OB）または分配（弱気OB）した場所を示します。
**マルチタイムフレームカバレッジ**:
- **1分足**: デイトレーダー向けスキャルピングゾーン
- **3分足**: 短期スイングゾーン
- **15分足**: イントラデイ機関投資家ゾーン
- **60分足**: デイリースイングゾーン
- **現在のTF**: 任意のチャートタイムフレームへの動的適応
**主要機能**:
- **バウンス検知** - OBゾーンから価格がリバウンドする時を識別（シグナル7: 🎯 OBバウンス）
- **ブレーカー追跡** - OBが破られた時を監視し、強気OBを抵抗に、弱気OBをサポートに変換
- **ビジュアルレンダリング** - OBの強度を示す透明度付きの色分けされたボックス
- **OB方向フィルター** - 矛盾するシグナルをブロック（強気OBでSELLなし、弱気OBでBUYなし）
**なぜMTFオーダーブロックが重要か**:
60分足のオーダーブロックは、より大きなタイムフレームでの機関投資家のポジショニングを表します。3分足のエントリーシグナルと組み合わせることで、大口プレイヤーと**同じ方向**で取引することになります。
---
### 3️⃣ フェアバリューギャップ（FVG）検知
**目的**: 機関投資家が最終的に埋めなければならない価格の非効率性を識別する。
**FVGとは何か？**:
フェアバリューギャップは、価格があまりにも急速に動いて**不均衡**を残す時に発生します - 1本のローソク足の高値と2本後のローソク足の安値の間のギャップ（またはその逆）。機関投資家はこれらを修正されなければならない非効率的な価格設定と見なします。
**検知ロジック**:
```
強気FVG: high < low → ギャップアップ = 弱気の不均衡（下方フィル予想）
弱気FVG: low > high → ギャップダウン = 強気の不均衡（上方フィル予想）
```
**ビジュアルデザイン**:
- **強気FVG**: 緑のボックス（価格がバウンドすべきサポートゾーン）
- **弱気FVG**: 赤のボックス（価格が拒否されるべき抵抗ゾーン）
- **ミティゲーション追跡**: FVGは埋められると消え、完了を示す
- **出来高帰属**: 各FVGは関連する買い/売り出来高を追跡
**なぜFVGが重要か**:
機関投資家は**効率性**で動きます。ギャップは非効率性を表します。価格がギャップを埋めるために戻る時、それはランダムではありません - 機関投資家が**市場の非効率性を修正**しているのです。FVGフィルへの取引は卓越したリスク/リワードを提供します。
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### 4️⃣ 出来高加重クラウド（VWC/TBOSI）
**目的**: 出来高加重プライスアクションを使用してモメンタムシフトとトレンド強度を検出する。
**メカニズム**:
VWCは移動平均に**ボラティリティ加重**を適用し、高ボラティリティトレンド中に拡大し、コンソリデーション中に縮小する動的クラウドを作成します。
**マルチタイムフレーム分析**:
- **1m、3m、5m**: マイクロスキャルピングモメンタム
- **15m**: イントラデイトレンド確認
- **60m、240m**: スイングトレードトレンド検証
**シグナル生成**:
- **VWCスイッチ（シグナル2）**: クラウドの色が反転した時（赤→緑または緑→赤）、モメンタム反転を示す
- **VWCステータステーブル**: 全タイムフレームのトレンド方向のリアルタイム表示
**なぜ出来高加重が重要か**:
従来の移動平均はすべてのバーを等しく扱います。VWCは**高出来高バーに重みを与え**、シグナルが低出来高のノイズではなく、実際の機関投資家の参加を反映することを保証します。
---
### 5️⃣ ノンリペイントSTDEV（NPR）＆ボリンジャーバンド
**目的**: リペイントなしで極端な平均回帰ポイントを識別する。
**従来のインジケーターの問題点**:
多くのインジケーターは**リペイント**します - 新しいデータが到着すると過去の値を変更し、バックテストを誤解させます。NPRは**先読みバイアス防止**を使用して、シグナルが固定されたままであることを保証します。
**設定**:
- **15分足NPR/BB**: イントラデイボラティリティバンド
- **60分足NPR/BB**: スイングトレード極値
- **複数のカーネルオプション**: 指数、単純、二重指数、三重指数 - 異なる平滑化プロファイル
**シグナルロジック（シグナル8）**:
- **BUY**: 価格が下部バンドの**内側**でクローズ（触れるだけではない）→ 極端な売られ過ぎで機関投資家の吸収が可能性高い
- **SELL**: 価格が上部バンドの**内側**でクローズ → 極端な買われ過ぎで機関投資家の分配が可能性高い
**なぜNPRが優れているか**:
リペイントインジケーターはトレーダーにバックテストで誤った自信を与えます。NPRは、履歴で見るすべてのシグナルが、トレーダーがリアルタイムで見たであろうもの**そのもの**であることを保証します。
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### 6️⃣ 💎 STRONG CHoChパターン検知
**目的**: 短い時間枠内で複数のCHoCH確認が整列した時の最高確率セットアップを識別する。
**パターンロジック**:
**STRONG BUYパターン**:
```
1.CHoCH → A.CHoCH → 1.CHoCH（20バー以内）
```
このシーケンスは以下を示します：
1. 初期強気構造シフト
2. 弱気リテスト（プルバック）
3. **更新された強気確認** - 機関投資家は弱い手を振り落とした後に再蓄積中
**STRONG SELLパターン**:
```
A.CHoCH → 1.CHoCH → A.CHoCH（20バー以内）
```
このシーケンスは以下を示します：
1. 初期弱気構造シフト
2. 強気リテスト（デッドキャットバウンス）
3. **更新された弱気確認** - 機関投資家はロングを罠にかけた後に再分配中
**ビジュアル表示**:
```
💎 BUY
```
- **0%透明度**（完全不透明） - 最大の視覚的優先度
- パターン完成時に**即座に**表示（追加シグナル不要）
- 市場構造フィルターから独立（パターン自体が確認）
**なぜSTRONGシグナルが異なるか**:
- **三重確認**: 3つの構造シフトが誤ったブレイクアウトを排除
- **短い時間枠**: 20バーウィンドウがランダムなノイズではなく、機関投資家の確信を保証
- **自動表示**: 価格アクションを待たない - パターン自体がアラートをトリガー
- **歴史的検証**: この特定のシーケンスは主要な機関投資家の動きに先行することが証明されている
**リスク管理**:
STRONGシグナルは最高のリスク/リワードを提供します：
1. ストップロスは中央のCHoCHの外に配置可能（タイトなリスク）
2. ターゲットは次の主要構造レベルに設定可能（大きなリワード）
3. パターン失敗は即座に明らか（間違っていればクイックエグジット）
---
### 7️⃣ マルチEMAフレームワーク
**目的**: ダイナミックなサポート/レジスタンスとトレンドコンテキストを提供する。
**EMA設定**:
- **EMA 7**: マイクロトレンド（スキャルピング）
- **EMA 20**: 短期トレンド
- **EMA 50**: 機関投資家のピボット（シグナル6: EMA50バウンス）
- **EMA 100**: 中期トレンドフィルター
- **EMA 200**: 主要な機関投資家のサポート/レジスタンス
- **EMA 400、800**: マクロトレンドコンテキスト
**ビジュアルフィル**:
- EMA間の色分けされたフィルが**ビジュアルトレンド強度ゾーン**を作成
- 収束 = コンソリデーション
- 発散 = トレンド市場
**なぜ7つのEMAか？**:
各EMAは異なる**参加者タイムフレーム**を表します：
- EMA 7/20: デイトレーダーとスキャルパー
- EMA 50/100: スイングトレーダー
- EMA 200/400/800: ポジショントレーダーと機関投資家
すべてのEMAが整列した時、**すべての参加者タイプが方向に同意**している - 最高確率のトレンド取引です。
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## 🚀 8シグナル取引システム
Trend Gazer v5は**8つの異なるシグナル条件**（すべてデフォルトで有効）を採用しており、それぞれが異なる市場レジームを捕捉するように設計されています：
### ⭐ シグナル階層＆取引哲学
**重要**: すべてのシグナルが同じではありません。インジケーターはシグナル品質の階層を表示します：
**プライマリーシグナル（これを取引する）**:
- 💎 **STRONG BUY/SELL** - 三重CHoChパターン（最優先）
- 🌟 **スターシグナル（S7、S8）** - 高確率の機関投資家ゾーン反応
- シグナル7: オーダーブロックバウンス
- シグナル8: 60m NPR/BBバウンス
**補助シグナル（確認とコンテキスト）**:
- **シグナル1-6** - これらを以下として使用：
- スターシグナルの**確認**（複数のシグナルが整列した時）
- 市場状況を理解するための**コンテキスト**
- 潜在的な動きの**早期警告**（取引前に検証）
- **追加フィルター**（例：「シグナル1も出ているスターシグナルのみ取引」）
**取引推奨**:
- **保守的トレーダー**: 💎 STRONGと🌟スターシグナル**のみ**取引
- **中程度トレーダー**: スターシグナル + 検証された補助シグナル（2+シグナル確認）
- **アクティブトレーダー**: 適切なリスク管理ですべてのシグナルを使用
視覚的透明度システムはこの階層を強化します：
- 0%透明度 = STRONG（💎） - 最高の確信
- 50%透明度 = スター（🌟）+ OBシグナル - 高品質
- 70%透明度 = 補助（S1-S6） - 補足情報
### シグナル1: RSIシフト + 構造（ANDロジック）
**最も厳格なシグナル** - RSIモメンタム確認と構造変化の両方が必要。
- **使用例**: トレンド市場での高確信取引
- **頻度**: 最も少ない、最高の精度
- **分類**:
### シグナル2: VWCスイッチ（ORロジック）
**最も頻繁なシグナル** - 監視されているタイムフレームでのVWC色反転でトリガー。
- **使用例**: 早期モメンタムシフトの捕捉
- **頻度**: 最も頻繁、アクティブトレーダーに適している
- **分類**:
### シグナル3: 構造変化
**バーカラー変化とRSI確認** - RSIサポートでローソク足の色がシフトする時を検出。
- **使用例**: トレンド継続取引
- **頻度**: 中程度
- **分類**:
### シグナル4: BBブレイクアウト + RSI
**ボリンジャーバンドブレイクアウト反転** - 価格がバンドを破った後すぐに反転。
- **使用例**: 誤ったブレイクアウトをフェード
- **頻度**: 中程度、優れたリスク/リワード
- **分類**:
### シグナル5: BB/EMA50ブレイク
**積極的ブレイクアウトシグナル** - 価格がBBとEMA50を同時にブレイク。
- **使用例**: モメンタムブレイクアウト取引
- **頻度**: 中〜高
- **分類**:
### シグナル6: EMA50バウンス反転
**EMA50での平均回帰** - 価格がEMA50に触れてバウンス。
- **使用例**: 強いトレンドでのプルバック取引
- **頻度**: 中程度、信頼性あり
- **分類**:
### シグナル7: 🌟 OBバウンス（スターシグナル）
**オーダーブロックバウンス** - 価格がOBゾーンに入って反転。
- **使用例**: 機関投資家ゾーン反応
- **頻度**: 低いが、極めて高品質
- **分類**:
- **特別機能**:
- 🎯 **OBバウンスラベル**: `🌟 🎯 BUY/SELL ` - 可視OBからの実際のシグナル7バウンス
- 📍 **In OBラベル**: `📍 BUY/SELL ` - OBゾーン内で発生する他のシグナル（S1-6、S8）
- **OB方向フィルター**: 矛盾するシグナルをブロック（強気OBでSELLなし、弱気OBでBUYなし）
### シグナル8: 🌟 60m NPR/BBバウンス（スターシグナル）
**極端な平均回帰** - 価格が60m NPR/BBバンドの極値で**内側に**クローズ。
- **使用例**: 極値での機関投資家の吸収を捕捉
- **頻度**: 低い、卓越した勝率
- **分類**:
- **特別ロジック**: ローソク足のクローズがバンドの**内側**でなければならない（触れるだけではダメ、誤ったブレイクアウトを防止）
### 💎 STRONGシグナル（ボーナス）
**CHoChパターン完成** - 三重確認された構造シフト。
- **STRONG BUY**: `1.CHoCH → A.CHoCH → 1.CHoCH（≤20バー）`
- **STRONG SELL**: `A.CHoCH → 1.CHoCH → A.CHoCH（≤20バー）`
- **表示**: パターン完成時に即座（独立したシグナル）
- **分類**:
- **使用例**: 最高確信の機関投資家トレンドシフト
---
## 🎨 ビジュアルデザイン哲学
### 透明度によるシグナル階層
**0%透明度（不透明）**:
- 💎 **STRONG BUY/SELL** - 最優先、機関投資家パターン確認
**50%透明度**:
- 🌟 **スターシグナル**（S7、S8） - 高品質平均回帰
- 🎯 **OBバウンス** - 機関投資家ゾーン反応
- 📍 **In OB** - 機関投資家ゾーン内の強化されたシグナル
- **CHoChラベル**（1.CHoCH、A.CHoCH） - 構造シフトマーカー
**70%透明度**:
- **通常シグナル**（S1-S6） - 標準取引セットアップ
この視覚的階層により、トレーダーは分析麻痺なしに高優先度セットアップを**即座に認識**できます。
### カラースキーム: 日本式ローソク足慣例
**強気 = 赤 | 弱気 = 青/緑**
これは伝統的な日本式ローソク足方法論に従います：
- **赤（陽）**: ポジティブエネルギー、上昇価格、強気
- **青/緑（陰）**: ネガティブエネルギー、下降価格、弱気
西洋の慣例はしばしばこれを逆にしますが、プロの取引ルームとの一貫性のために**ICTと機関投資家の慣例**を維持します。
---
## 📡 アラートシステム
### Any Alert（自動）
**8つのイベントを監視**:
1. 💎 **STRONG BUY** - パターン: `1.CHoCH → A.CHoCH → 1.CHoCH`
2. 💎 **STRONG SELL** - パターン: `A.CHoCH → 1.CHoCH → A.CHoCH`
3. ⭐ **Star BUY** - シグナル7または8
4. ⭐ **Star SELL** - シグナル7または8
5. 📍 **BUY (in OB)** - 強気オーダーブロック内の任意のシグナル
6. 📍 **SELL (in OB)** - 弱気オーダーブロック内の任意のシグナル
7. **Bullish CHoCH** - 強気への市場構造シフト
8. **Bearish CHoCH** - 弱気への市場構造シフト
**フォーマット**: `TICKER TIMEFRAME EventName`
**例**: `BTCUSDT 5 💎 STRONG BUY`
### 個別alertcondition()オプション
特定のイベントのカスタムアラートを作成：
- BUY/SELLシグナル（すべてまたはフィルタリング）
- スターシグナルのみ（S7/S8）
- STRONGシグナルのみ（💎）
- CHoChイベントのみ
- 強気/弱気CHoCH個別
---
## ⚙️ 設定と設定
### ICT構造フィルター（デフォルトON ⭐）
**構造フィルターを有効化**: CHoCH/SiMS/BoMS後のシグナル**のみ**表示
- **目的**: 機関投資家の確認を要求することでノイズをフィルター
- **推奨**: 規律ある取引のために有効のままにする
**構造ラベルを表示（デフォルトON ⭐）**: CHoCH/SiMS/BoMSラベルを表示
- **目的**: 市場構造状態の視覚的確認
- **ラベル**:
- `1.CHoCH`（赤背景、白テキスト） - 強気構造シフト
- `A.CHoCH`（青背景、白テキスト） - 弱気構造シフト
- `2.SMS` / `B.SMS`（赤/青テキスト） - 市場構造のシフト（2回目）
- `3.BMS` / `C.BMS`（赤/青テキスト） - 市場構造のブレイク（3回目以降）
**構造期間**: デフォルト3バー（ICT標準）
### オーダーブロック設定
**マルチタイムフレームOBを有効化**: 複数のタイムフレームから同時にOBを検出
**ミティゲーションオプション**:
- Close - ローソク足がクローズで通過した時にOB無効化
- Wick - ウィックが触れた時にOB無効化
- 50% - ゾーンの50%が侵害された時にOB無効化
**OBを表示**:
- 現在のタイムフレーム（常に）
- 1m、3m、15m、60m（選択可能）
### フェアバリューギャップ設定
**FVGを表示**: FVGレンダリングを有効/無効
**ミティゲーションソース**: Wick、Close、または50%フィル
**カラーカスタマイゼーション**: 強気FVG（緑）、弱気FVG（赤）
### シグナルフィルター
**スターシグナルのみ表示（デフォルトOFF）**:
- ONの時: S7（OBバウンス）とS8（NPR/BBバウンス）のみ表示
- OFFの時: すべてのシグナルS1-S8を表示（デフォルト）
- **使用例**: 最高品質のセットアップに集中し、ノイズを無視
### ビジュアル設定
**EMA表示**: 個別のEMAをオン/オフ切り替え
**VWCクラウド**: 出来高クラウドを有効/無効
**NPR/BBバンド**: 15mと60mバンドを表示/非表示
**ステータステーブル**: すべてのタイムフレームでのリアルタイムVWCステータス
---
## 📚 使用方法
### スキャルパー向け（1m-5m チャート）
1. **1mと3mオーダーブロック**を有効化
2. **シグナル2（VWCスイッチ）**または**シグナル5（BB/EMA50ブレイク）**を監視
3. サポート/レジスタンスとして**1m/3m MTF OB**で確認
4. マイクロターゲット設定に**FVG**を使用
5. 最高品質のスキャルプのために**Star BUY/SELL**のアラートを設定
### デイトレーダー向け（15m-60m チャート）
1. **15mと60mオーダーブロック**を有効化
2. バイアスを確立するために**CHoCH**を待つ
3. **シグナル7（OBバウンス）**または**シグナル8（60m NPR/BBバウンス）**を取引
4. ダイナミックストップ配置に**EMA 50/100**を使用
5. 主要な動きのために**💎 STRONG BUY/SELL**のアラートを設定
### スイングトレーダー向け（4H-日足 チャート）
1. **60mオーダーブロック**を有効化（HTFでより大きなゾーンとしてレンダリング）
2. **市場構造確認**（CHoCH）を待つ
3. 最高確信のために**シグナル1（RSIシフト + 構造）**に集中
4. マクロトレンド整列のために**EMA 200/400/800**を使用
5. 構造シフトを早期に捕捉するために**Bullish/Bearish CHoCH**のアラートを設定
### ユニバーサル戦略（推奨アプローチ）
1. **まずプライマリーシグナルに集中** - 💎 STRONGと🌟スターシグナル**のみ**でトラックレコードを構築
2. **市場構造を待つ** - CHoCH方向に逆らって取引しない
3. **補助シグナルを確認に使用** - スターシグナルが現れたら、補助シグナル（S1-6）も確認するかチェック
4. **オーダーブロックを尊重** - OB方向と矛盾するシグナルをフェード
5. **ターゲットにFVGを使用** - 価格は埋められていないギャップに引き寄せられる
6. **徐々に補助シグナルを組み込む** - プライマリーシグナルで利益が出たら、検証された補助セットアップを実験
### シグナル品質統計（典型的な観察）
一般的な市場行動パターンに基づく：
**💎 STRONGシグナル**:
- 頻度: まれ（日足チャートで週1-3回）
- 勝率: 非常に高い（適切なリスク管理適用時70-85%）
- リスク/リワード: 優秀（典型的に1:3から1:5+）
**🌟 スターシグナル（S7、S8）**:
- 頻度: 中程度（短期足で1日2-5回）
- 勝率: 高い（構造と整列時60-75%）
- リスク/リワード: 良好（典型的に1:2から1:4）
**補助シグナル（S1-6）**:
- 頻度: 高い（活発なタイムフレームで1時間に複数回）
- 勝率: 中程度（単独で50-65%、確認として使用時はより高い）
- リスク/リワード: 変動（典型的に1:1から1:3）
**重要な洞察**: プライマリーシグナルのみの取引は取引頻度を減らしますが、一貫性と心理的容易さを劇的に改善します。
---
## 🏆 このインジケーターのユニークな点
### 1. **真のマルチタイムフレーム統合**
ほとんどの「MTF」インジケーターは単に他のタイムフレームからデータを表示するだけです。Trend Gazer v5はMTFデータを統一されたシグナルに**合成**し、矛盾する情報を排除します。
### 2. **ノンリペイント・アーキテクチャ**
すべてのシグナルはバークローズで固定されます。バックテストで見るものは、リアルタイムで見るであろうもの**そのもの**です。
### 3. **機関投資家フォーカス**
すべてのコンポーネントは機関投資家の行動を中心に設計されています：
- どこで蓄積するか（オーダーブロック）
- いつシフトするか（CHoCH）
- 何を修正しなければならないか（FVG）
- どのようにモメンタムを作り出すか（VWC）
### 4. **完全な透明性**
- **オープンソース** - 完全なコード可視性
- **クレジットされたソース** - すべての借用コンセプトが帰属
- **ブラックボックスなし** - すべての計算が文書化
### 5. **柔軟だが焦点を絞った**
- **8シグナルタイプ** - 任意の市場レジームに適応
- **最適化されたデフォルト設定** - 調整なしですぐに動作
- **オプションフィルター** - 規律あるトレーダーのための「スターシグナルのみ表示」
### 6. **プロフェッショナルアラートシステム**
- **8イベントAny Alert** - 機関投資家の動きを見逃さない
- **個別alertconditions** - あなたの戦略にカスタマイズ
- **フォーマットされたメッセージ** - 即座のコンテキストのためのTicker + Timeframe + Event
---
## 📖 教育的価値
### ICT概念の学習
このインジケーターは以下のための**視覚的教育ツール**として機能します：
- **市場構造**: CHoCH/SiMS/BoMSをリアルタイムで見る
- **オーダーブロック**: 機関投資家がどこでポジショニングしたかを理解
- **フェアバリューギャップ**: 非効率性がどのように埋められるかを学ぶ
- **スマートマネー行動**: 機関投資家の足跡が展開するのを観察
### バックテスティングと戦略開発
Trend Gazer v5を使用して：
1. **ICT概念を検証** - OBバウンスは本当に機能するか？テストする。
2. **エントリータイミングを最適化** - あなたの市場でどのシグナルが最も機能するか？
3. **フィルターを開発** - あなたのエッジのためにシグナルを組み合わせる
4. **戦略を構築** - シグナルをPine Scriptストラテジーにエクスポート
---
## ⚠️ 免責事項
このインジケーターは**教育および情報提供のみを目的**としています。金融アドバイスではありません。
**リスク警告**:
- 取引には重大な損失リスクが伴い、すべての投資家に適しているわけではありません
- 過去のパフォーマンスは将来の結果を**示すものではありません**
- どのインジケーターも利益ある取引を保証することはできません
- あなたは自分の取引決定に対して単独で責任を負います
**取引前に**:
- 自分自身の調査とデューデリジェンスを実施
- 資格のある金融アドバイザーに相談
- 適切なリスク管理を使用（取引あたり1-2%以上リスクを取らない）
- ライブ取引前にペーパー/デモアカウントで練習
- 損失は取引の一部であることを理解
このインジケーターによって提供される情報は、投資アドバイス、金融アドバイス、取引アドバイス、またはその他の種類のアドバイスを構成するものではありません。インジケーターの出力をそのように扱うべきではありません。作成者は、あなたが任意の暗号通貨、証券、または商品を買い、売り、または保有すべきであると推奨するものではありません。常に自分自身の調査を行い、専門的なアドバイスを求めてください。
このソフトウェアは、明示的または黙示的を問わず、いかなる種類の保証もなく「現状のまま」提供されます。
---
## 🔗 クレジットとライセンス
### 原作コードソース
1. **ICT Donchian Smart Money Structure**
- 作者: Zeiierman
- ライセンス: CC BY-NC-SA 4.0
- 変更: マルチシグナルシステムと統合、CHoChパターン検知を追加
2. **Reverse RSI Signals**
- 作者: AlgoAlpha
- ライセンス: MPL 2.0
- 変更: 内部シグナルロジックに適応
3. **Volumetric Weighted Cloud（VWC/TBOSI）**
- 元のコンセプトをマルチタイムフレーム分析に適応
- MTFテーブル表示で強化
4. **Order Block & FVG Detection**
- ICTコンセプトに基づく
- MTFサポートでカスタム実装
### このインジケーターのライセンス
**Mozilla Public License 2.0（MPL 2.0）**
以下が自由です：
- ✅ 商用利用
- ✅ 変更と配布
- ✅ 私的使用
- ✅ 特許使用
条件：
- 📄 ソースを開示
- 📄 ライセンスと著作権表示
- 📄 変更に同じライセンス
---
## 📞 サポートとコミュニティ
### 問題の報告
バグに遭遇したり機能提案がある場合は、以下を提供してください：
1. チャートタイムフレームとシンボル
2. 設定構成
3. 問題のスクリーンショット
4. 期待される動作と実際の動作
### ベストプラクティス
- デフォルト設定で開始
- 各コンポーネントを理解するために段階的に機能を有効/無効化
- ライブ取引前に少なくとも30日間デモアカウントを使用
- 適切なリスク管理と組み合わせる
---
## 🚀 バージョン履歴
### v5.0 - Simplified ICT Mode（現在）
- ✅ すべての未使用フィルターと機能を削除
- ✅ すべての8シグナルをデフォルトで有効化
- ✅ 💎 STRONG CHoChパターン検知を追加
- ✅ OBバウンスラベリングシステムを強化
- ✅ FVG検知と可視化を追加
- ✅ アラートシステムを改善（8イベント）
- ✅ パフォーマンスを最適化（より速いレンダリング）
- ✅ 包括的なDESCRIPTIONドキュメントを追加
### v4.2 - ICT Mode with EMA Convergence Filter（非推奨）
- EMA収束機能を持つレガシーバージョン（シンプルさのために削除）
### v4.0 - Pure ICT Mode（非推奨）
- 初期ICTフォーカスリリース
---
## 🎓 推奨学習リソース
このインジケーターを完全に活用するために、以下を学習してください：
1. **ICTコンセプト**（Inner Circle Trader - YouTube）
- 市場構造
- オーダーブロック
- フェアバリューギャップ
- 流動性コンセプト
2. **スマートマネーコンセプト（SMC）**
- Change of Character（CHoCH）
- Break of Structure（BOS）
- Liquidity Sweeps
3. **Volume Spread Analysis（VSA）**
- Effort vs Result
- Supply vs Demand
- Volume Climax
4. **リスク管理**
- ポジションサイジング
- R-Multiple理論
- 勝率vsリスク/リワードバランス
---
## ✅ クイックスタートチェックリスト
- チャートにインジケーターを追加
- **構造フィルターを有効化**がONであることを確認
- **構造ラベルを表示**がONであることを確認
- 希望するMTFオーダーブロックを有効化（1m、3m、15m、60m）
- FVG表示を有効化
- すべての8イベントのために**Any Alert**を設定
- 最低30日間ペーパートレード
- 取引を文書化（スクリーンショット + ノート）
- 週次でパフォーマンスをレビュー
- あなたの戦略に基づいてフィルターを調整
---
## 💡 最後の考え
**Trend Gazer v5は「魔法のボタン」インジケーターではありません。**教育、練習、規律を必要とするプロフェッショナル分析フレームワークです。
最高のトレーダーは、インジケーターを使って**何をすべきかを教えてもらいません**。インジケーターを使って、プライスアクションで**既に見ているものを確認**します。
このツールを使用して：
- ✅ 分析を確認
- ✅ 低確率セットアップをフィルターアウト
- ✅ 機関投資家の足跡を識別
- ✅ エントリーを精密にタイミング
使用を避けるべき：
- ❌ コンテキストを理解せずに盲目的に取引
- ❌ リスク管理を無視
- ❌ 損失後にリベンジトレード
- ❌ 教育を自動化に置き換える
**スマートに取引しましょう。安全に取引しましょう。構造を持って取引しましょう。**
---
**© rasukaru666 | 2025 | Mozilla Public License 2.0**
*このインジケーターは、取引教育コミュニティに貢献するためにオープンソースとして公開されています。役立つ場合は、あなたの経験を共有して他の人が学ぶのを助けてください。*
Candle 2 Closure📌 Indicator Presentation – Candle 2 Closure
" Candle 2 Closure "s is an indicator designed to identify three types of price–action-based signals in real time: Long, Short, and Generic.
The goal is to visually highlight moments when the market breaks a key level of the previous candle but rejects that break, closing on the opposite side.
The idea was inspired by the study of pure price action and specifically by the following video:
👉 www.youtube.com
🎯 How the Indicator Works
The indicator generates signals on bar close (barstate.isconfirmed), making them reliable and free from repainting.
🔵 LONG Signal
A long signal is triggered when:
The current candle breaks the low of the previous candle
But then closes back above that low
→ This is often a sign of a bear trap or a liquidity rejection to the downside.
🔴 SHORT Signal
A short signal is triggered when:
The current candle breaks the high of the previous candle
But then closes back below that high
→ This may indicate a bull trap or a liquidity rejection to the upside.
⚪ GENERIC Signal
A generic signal is triggered when:
A high or low is broken,
But neither the long nor short conditions are met,
Resulting in a simple unconfirmed break.
📍 Operational Advantages
Highlights liquidity absorption zones
Works on all timeframes (1m → 1D)
Useful for scalping, intraday, or swing trading
Clear and immediate visual signals on the chart
Zero repainting
✨ Visual Style
LONG displayed below the candle, white color
SHORT displayed above the candle, white color
Generic signal shown with a neutral label
Volume-Confirmed FTR Zones [AlgoPoint]FTR Zone Indicator — Fail To Return Zones (With Volume Confirmation)
Advanced Smart Money Zone Detection for Institutional Orderflow
The FTR Zone Indicator is a professional-grade tool designed for traders who follow Smart Money Concepts (SMC), ICT methodologies, or institutional orderflow. It automatically detects Fail To Return Zones (FTR) — high-probability supply and demand areas formed after strong displacement moves.
By combining impulse detection, base identification, and volume confirmation, this indicator highlights zones where price is most likely to react, reverse, or mitigate shortly after structure breaks.
⸻
⭐ What Are FTR Zones?
FTR zones (Fail To Return zones) are price areas where:
1. A strong displacement / impulse candle is formed
2. That impulse originates from a small consolidation (base)
3. Price moves away aggressively
4. AND fails to return immediately to the origin area
These zones often indicate:
• Institutional orders
• Imbalance
• Hidden liquidity
• Origin of a trend leg
• High-probability mitigation points
This indicator fully automates the detection and visualization of such areas.
🔍 How the Indicator Works
1. Impulse Detection
The indicator identifies a valid impulse candle using:
• ATR-based bar range filter
• Trend-aligned candle body direction
• Optional volume confirmation
Only large, meaningful institutional candles qualify — filtering out noise.
2. Base Zone Identification
Before every impulse, the tool finds the micro-consolidation base using:
• Highest high of the last X bars
• Lowest low of the last X bars
This base becomes the potential FTR zone.
3. FTR Zone Creation
When a valid impulse is detected:
• Bullish impulse → Demand FTR zone
• Bearish impulse → Supply FTR zone
The zone is immediately drawn on the chart using box.new().
4. Zone Extension
Every zone continuously extends to the right as price evolves, allowing you to track:
• Mitigation
• Retests
• Reaction points
• Liquidity sweeps
5. Invalidation Logic
Zones automatically delete when violated:
• Demand zone invalid if close < zone low
• Supply zone invalid if close > zone high
This keeps the chart clean and helps focus only on active, high-value areas.
🎛️ Key Features
✔ Automatic FTR Zone Detection
Instantly identifies institutional origin zones based on real impulse and displacement.
✔ Volume-Based Filtering
Ensures only high-volume impulses (true institutional orders) create zones.
✔ Supply & Demand Coloring
• Bullish FTR → Demand Zone (Teal tone)
• Bearish FTR → Supply Zone (Red tone)
✔ Safe Zone Storage
Fault-tolerant logic ensures no array errors, invalid zones, or broken visuals.
✔ Auto-Extending Boxes
Real-time zone updates with precise historical mapping.
✔ Smart Invalidation
Zone is removed only when fully broken, preventing false signals.
✔ Clean, Non-Repainting Logic
Impulse detection and zone placement are confirmed only on bar close.
📈 How to Use It (Example Schenarios)
For Reversals or Continuations
• Look for price reacting or mitigating inside a zone
• Use as entry confirmation in trend continuations
• Combine with FVG, BOS/CHOCH, liquidity sweeps, or premium/discount zones
For Scalping or Intraday Trading
• High-probability countertrend entries
• Reaction-based setups at institutional footprints
For Swing Traders
• Identify weekly/daily origin zones
• Plan entries around large displacement points
BTCUSD – Market Structure Projection1. Short-Term Outlook
1. BTC is expected to complete a final liquidity sweep below recent lows.
2. A minor corrective rally into a premium zone offers a short opportunity.
3. Confirmation comes from rejection + RSI divergence.
2. Mid-Term Reversal Setup
4. After the sweep, BTC is projected to form a bullish break of structure (BOS).
5. A retest of demand provides the optimal long entry.
6. This phase begins the next expansion leg into 2026.
3. Long-Term Macro Trend
7. The higher-timeframe trend remains bullish despite local corrections.
8. BTC is expected to follow an impulse → correction → impulse pattern.
9. Macro upside targets remain positioned for new all-time highs.
4. Key Market Levels
Support Zones
10. $86,000 – $90,000 — primary liquidity-sweep region.
11. $92,500 – $94,000 — bullish retest confirmation zone.
Resistance Zones
12. $105,000 – $110,000 — mid-cycle rejection area.
13. $130,000 – $150,000 — macro expansion target range.
5. Trade Framework Summary
14. Short Setup: Enter after corrective rally into premium; target liquidity sweep.
15. Long Setup: Enter after BOS + demand retest; target macro continuation.
16. Structure favors a bullish expansion phase through 2026.
Mickey's Breaker Engine⚡ Breaker Engine | Auto Retest + Smart R:R Targets
A precision-grade breaker-block detection system built for traders who live and breathe clean structure.
This indicator automatically detects Breaker Candles, confirms them, marks their zones, and executes intelligent retest-based entry logic — complete with Stop-Loss and Risk-to-Reward (R:R) tracking up to 3R (or any custom ratio).
🧠 Core Concept
A Breaker Block is a structural shift where price violates liquidity from a failed order block and flips the zone’s polarity — turning a former supply into demand (or vice-versa).
This script identifies those setups automatically, confirms them only after a valid structure break, and waits for a clean retest to trigger a trade signal.
🚀 Key Features
⚙️ Smart Zone Detection
Detects both Bullish Breakers and Bearish Breakers.
Zones are drawn precisely using the breaker’s middle candle body (or full wick range if enabled).
Fully configurable transparency, width, and extension for better visual context.
🎯 Auto Retest Entry Logic
Entry triggers only on a clean retest, not on immediate breakout.
Includes logical filters to ensure retests are structurally valid and not overlapping candles.
Works in any timeframe or market — crypto, forex, indices, or commodities.
💡 Dynamic Risk–Reward Tracking
Automatically plots 1R, 2R, 3R, ...R targets based on your defined stop range.
Risk is calculated from entry to zone boundary or ATR offset.
Each target label appears precisely when hit.
Targets automatically stop updating once Stop-Loss is triggered.
🧱 Visual Clarity
BUY 🟢 / SELL 🔴 bubbles at entries.
SL ❌ marker when stop is hit.
🎯 1R / 2R / 3R labels dynamically plotted when each reward level is reached.
Non-overlapping placement using ATR-based spacing.
⚡ Real-Time Alerts - Instant alerts for:
✅ “Breaker BUY” – Clean retest confirmed (Long setup)
✅ “Breaker SELL” – Clean retest confirmed (Short setup)
❌ “Breaker BUY SL” – Stop hit for Long
❌ “Breaker SELL SL” – Stop hit for Short
🧩 Customization Panel
| Setting | Description |
| :-------------------------- | :------------------------------------------------------------------------------ |
| **ATR Length** | Controls volatility-based offset sizing. |
| **Entry / SL Offset × ATR** | Adjusts label spacing and dynamic positioning. |
| **Risk-Reward Ratio** | Define default R:R (e.g. 1:3). |
| **Multiple Retests** | Enable if you want the same breaker zone to allow multiple retests/entries. |
| **Banner Design** | Control opacity, extension, and wick usage for the breaker block visualization. |
| **Color Controls** | Choose your BUY/SELL/SL bubble colors to match your chart theme. |
⚙️ Underlying Logic (At a Glance)
Pattern Detection:
Identifies a 5-bar sequence that forms a valid Breaker Candle (the middle bar flips structure).
Confirmation:
Requires a follow-through candle to validate a real liquidity break.
Zone Registration:
Stores the breaker zone’s body range in arrays for tracking.
Clean Retest Entry:
Waits for price to retest the zone from the opposite side and close cleanly inside.
Stop Loss / Target Projection:
Defines stop loss just beyond the zone and plots up to 3 × reward targets dynamically.
Monitoring & Alerts:
Tracks each setup independently until either an R-target or SL is reached.
💬 Recommended Usage
Works best with market-structure traders, smart-money concepts, or liquidity-based systems.
Combine it with an external displacement confirmation or BOS/CHOCH tool for best precision.
Ideal for backtesting breaker-based R:R consistency or forward-testing retest entries.
Compatible with any asset / timeframe.
🧭 Disclaimer
This script is for educational and analytical purposes only.
It is not financial advice and should not be used to make trading decisions without independent confirmation or risk management.
Always test on demo data before deploying live.
Rage of UltronRage of Ultron - Multi-Timeframe Smart Money Trading System
Advanced Confluence-Based Trading Indicator
Rage of Ultron is a comprehensive multi-timeframe trading system that combines Smart Money Concepts (SMC) with macro market context, RSI divergences, liquidity sweeps, and volume analysis to identify high-probability setups across all markets.
Key Features
Multi-Timeframe Alignment
* Weekly Bias - Directional trend context
* Daily Structure - Order Blocks and Fair Value Gaps
* 4H Confirmation - Entry timing and execution
* Real-time MTF alignment scoring (🟢 Bull Aligned / 🔴 Bear Aligned / 🟡 Mixed)
Smart Money Concepts
* Order Blocks (OB) - Institutional entry zones with visual clarity
* Fair Value Gaps (FVG) - Price imbalances and retracement magnets
* Change of Character (CHoCH) - Market structure breaks (▲▼)
* Liquidity Sweeps - Stop hunt detection before reversals (💧)
Technical Analysis
* RSI Divergences - Regular and hidden divergences with zones (◆)
* RSI Swing Failure Patterns - Grade-A reversal setups (★)
* Automatic Fibonacci - Dynamic retracements and extensions
* Volume Impulse Detection - Weighted confirmation signals
Macro Market Radar
* DXY - Dollar strength assessment
* BTC Dominance - Crypto market risk gauge
* USDT Dominance - Stablecoin flow analysis
* Combined risk environment scoring
Confluence Scoring System (0-7)
Quantified setup quality with three alert tiers:
* Tier 1 (Score 6-7): Full confluence + sweep + volume + MTF alignment
* Tier 2 (Score 5): High confluence + volume or sweep
* Tier 3 (Score 4): Standard confluence setups
"Rage" Volume State
* 🟢 RAGE PULSE - Explosive volume spike (score 6+ trigger)
* ⚡ Active - Strong volume with good confluence
* 🟡 Stable - Moderate volume conditions
* 🔴 Dormant - Low volume, wait for confirmation
Visual Design
* Clean Zone Rendering - Persistent OB/FVG boxes with limited extension
* Signal Bar Highlighting - Colored fills and contrasting borders for instant recognition
* Dynamic Symbol Placement - ATR-based offset prevents overlap
* Comprehensive Panel - Real-time macro + trade metrics in one view
* Toggleable Legend - Learn signals, hide once familiar
How to Use
1. Set Your Timeframes - Default 1W/1D/4H works for swing trading
2. Monitor Macro Environment - Check risk-on/off context
3. Wait for Confluence ≥4 - Let multiple signals align
4. Enter on Tier 1/2 Alerts - Best probability setups
5. Use Fib Extensions for Targets - Systematic profit taking
Customizable Settings
* Multi-timeframe periods
* RSI length and divergence sensitivity
* Liquidity sweep parameters
* Fibonacci swing lookback
* Volume thresholds
* Shape offset multiplier
* Visual toggles (Fibs, extensions, legend)
Built-in Alert System
Three-tier alert structure lets you filter by setup quality. Set alerts for Tier 1 only for highest conviction trades, or include Tier 2 for more opportunities.
Best Practices
* Use on clean timeframes - 1H+ for less noise
* Combine with support/resistance - Zones near key levels = highest probability
* Respect the macro - Don't fight extreme risk-off environments
* Wait for the full stack - Best trades have 4+ aligned signals
* Practice on demo first - Learn signal behavior in your market
Works On
* Cryptocurrency (spot & futures)
* Forex pairs
* Stock indices
* Individual stocks
* Commodities
Note: This indicator identifies potential setups but does not guarantee profits. Always use proper risk management, position sizing, and stops. Past performance does not predict future results.
Created by cdotgnz | For educational purposes
Major exchages total Open interest & Long/Short OI trends📊 Indicator: Major Exchanges Total OI & Long/Short Trends
This Pine Script™ indicator is designed to provide a comprehensive analysis of Open Interest (OI) and Long/Short position trends across major cryptocurrency exchanges (Binance, Bybit, OKX, Bitget, HTX, Deribit). It serves as a powerful tool for traders seeking to understand market liquidity, participant positioning, and overall market sentiment.
🔑 Key Features and Functionalities
Aggregated Multi-Exchange Open Interest (OI):
Consolidates real-time Open Interest data from user-selected major cryptocurrency exchanges.
Provides a unified view of the total OI, offering insights into the collective market liquidity and the aggregate size of participants' open positions.
Visualized Combined OI Candles:
Presents the aggregated total OI data in a candlestick chart format.
Displays the Open, High, Low, and Close of the combined OI, with color variations indicating increases or decreases from the previous period. This enables intuitive visualization of OI trend shifts.
Estimated Long/Short OI and Visualization:
Calculates and visualizes estimated Long and Short position Open Interest based on the total aggregated OI data.
Estimation Logic:
Employs a sophisticated logic that considers both price changes and OI fluctuations to infer the balance between Long and Short positions. For instance, an increase in both price and OI may suggest an accumulation of Long positions, while a price decrease coupled with an OI increase might indicate growing Short positions.
Initial 50:50 Ratio:
The estimation for Long/Short OI begins with an assumption of a 50:50 ratio at the initial data point available for the selected timeframe. This establishes a neutral baseline, from which subsequent price and OI changes drive the divergence and evolution of the estimated Long/Short balance.
Flexible Visualization Options:
Allows users to display Long/Short OI data in either line or candlestick styles, with customizable color schemes. This flexibility aids in clearly discerning bullish or bearish positioning trends.
💡 Development Background
The development of this indicator stems from the critical importance of Open Interest data in the cryptocurrency derivatives market. Recognizing the limitations of analyzing individual exchange OI in isolation, the primary objective was to integrate data from leading exchanges to offer a holistic perspective on market sentiment and overall positioning dynamics.
The inclusion of the Long/Short position estimation feature is crucial for deciphering the specific directional biases of market participants, which is often not evident from raw OI data alone. This enables a deeper understanding of how positions are being accumulated or liquidated, moving beyond simple OI change analysis.
Furthermore, a key design consideration was to leverage the characteristic where the indicator's data start point dynamically adjusts with the chart's timeframe selection. This allows for the analysis of short-term Long/Short trends on shorter timeframes and long-term trends on longer timeframes. This inherent flexibility empowers traders to conduct analyses across various time scales, aligning with their diverse trading strategies.
🚀 Trading Applications
Leveraging Combined Open Interest (OI):
Trend Confirmation: A sustained increase in total OI signifies growing market interest and capital inflow, potentially confirming the strength of an existing trend. Conversely, decreasing OI may suggest diminishing participant interest or widespread position liquidation.
Validation of Price Extremes: If price forms a new high but OI fails to increase or declines, it could signal a potential trend reversal (divergence). Conversely, a sharp increase in OI during a price decline might indicate a surge in short positions or renewed selling pressure.
Identifying Volatility Triggers: Monitoring rapid shifts in OI during significant news events or market catalysts can help assess immediate market reactions and liquidity changes.
📈Utilizing Long/Short OI Trends
Assessing Market Bias: A sustained dominance or rapid increase in Long OI suggests a prevalent bullish sentiment, which could inform decisions to enter or maintain long positions. The inverse scenario indicates bearish sentiment and potential short entry opportunities.
Anticipating Squeezes: The indicator can help identify scenarios conducive to short or long squeezes. Excessive short positioning followed by a price uptick can trigger a short squeeze, leading to rapid price appreciation. Conversely, an oversupply of long positions preceding a price drop can result in a long squeeze and sharp declines.
Divergence Analysis: Divergences between price action and Long/Short OI estimates can signal potential trend reversals. For example, if price is rising but the increase in Long OI slows down or Short OI begins to grow, it may suggest weakening buying pressure.
🕔Timeframe-Specific Trend Analysis:
Shorter Timeframes (e.g., 1m, 5m, 15m): Ideal for identifying short-term shifts in participant positioning, beneficial for day trading and scalping strategies. Provides insights into immediate market reactions to price movements.
Longer Timeframes (e.g., 1h, 4h, Daily): Valuable for evaluating broader positioning trends and the sustainability or potential reversal of medium-to-long-term trends. Offers a macro perspective on Long/Short dynamics, suitable for swing trading or long-term investment strategies.
This indicator integrates complex market data, provides nuanced Long/Short position estimations, and offers multi-timeframe analytical capabilities, empowering traders to make more informed and strategic decisions.
Clock&Flow – Market Pulse IndicatorClock&Flow – Market Pulse Indicator
1) General Purpose
The Market Pulse Indicator is designed to visualize the strength and direction of market flow in a clear, intuitive way.
Unlike common volume or momentum indicators, it blends three essential dimensions — price velocity, normalized volume, and volatility (ATR) — to highlight when market pressure is truly meaningful.
It helps identify genuine liquidity inflows/outflows, potential exhaustion zones, and moments of compression or expansion within the price structure.
2) Data Sources
All data is directly taken from the current chart’s feed on TradingView:
Price (close): to measure relative price change.
Volume: to detect the intensity of market participation (normalized to average).
ATR (Average True Range): to evaluate volatility relative to price levels.
No external data or off-platform sources are used.
3) Logic and Calculation Steps
Price Velocity: calculates the percentage change between the current close and the close N bars ago.
priceChange = (close - close ) / close
Normalized Volume: compares current volume to its moving average over the same period.
volNorm = volume / sma(volume, length)
Normalized Volatility: ATR divided by price to adjust for instrument scale.
atrNorm = atr(length) / close
Combination : multiplies the three components into one raw value that represents market pulse intensity.
rawPulse = priceChange * volNorm * (1 + atrNorm)
Smoothing: a moving average (smoothLen) is applied to create a cleaner and more readable oscillator line.
flowPulse = sma(rawPulse * multiplier, smoothLen)
4) Parameters (Default Settings)
length (20): analysis period for price change, volume, and ATR.
smoothLen (5): smoothing factor; higher values reduce noise.
multiplier (100): scales the output for readability; adjust to fit chart scale.
5) How to Read the Indicator
Market Pulse > 0 (green): net inflow of liquidity; buying pressure dominates.
Market Pulse < 0 (red): net outflow of liquidity; selling pressure dominates.
Near 0: neutral phase; market balance or consolidation.
Sudden peaks: strong bursts of flow — often coincide with news releases or session overlaps.
Confirmations: use as a second-level filter before entering trades or to confirm momentum behind a breakout.
6) Divergences
Divergences between price and Market Pulse are key signals of weakening flow strength:
Bullish divergence: price forms lower lows while Market Pulse forms higher lows → selling pressure is fading; potential reversal or bounce.
Bearish divergence: price forms higher highs while Market Pulse fails to confirm → buying momentum is losing strength; potential correction ahead.
For reliability, look for divergences on higher timeframes (H4, Daily).
On lower timeframes, treat them as early warnings.
7) Typical Use Cases
Breakout confirmation: price breaks resistance with a rising Market Pulse → confirms genuine participation.
False signal filter: price breaks a level but Market Pulse remains flat/negative → likely fake breakout.
Pullback entry: after a breakout, wait for a short retracement and a new positive pulse → safer entry point.
Exit signal: if you’re long and Market Pulse suddenly turns negative with strong volume → consider partial exit or tighter stops.
8) Recommended Timeframes
Intraday / Scalping: 5–30 min charts with length 10–14, smoothLen 3–5.
Swing trading: 1h–4h charts with length 20–50.
Position trading: Daily charts with larger length (50–100) for smoother data.
Always optimize parameters to the specific asset — there are no universal settings.
9) Limitations
This indicator is not a trading system — it’s a decision-support tool.
Results depend on the quality of the volume data available for the symbol.
Performance and sensitivity are influenced by length, smoothing, and multiplier values — always test before live trading.
Use alongside sound risk and money management.
10) Disclaimer
This script is provided for educational purposes only and does not constitute financial advice.
Trading and investing involve significant risk, including the potential loss of capital.
Always test indicators in simulation environments and make independent decisions based on your own analysis and risk tolerance.
Italiano
1) Scopo generale
Flow Pulse è un oscillatore pensato per visualizzare la forza e la direzione del flusso di mercato in modo immediato. Non è un semplice indicatore di volume né una copia di RSI/MACD: combina tre dimensioni fondamentali — variazione di prezzo, volume normalizzato e volatilità — per mettere in evidenza i momenti in cui la pressione dei partecipanti è realmente significativa.
È ideale per identificare: entrate guidate da flussi reali, potenziali esaurimenti, momenti di compressione/espansione del movimento e segnali di conferma per breakout o rimbalzi.
2) Dati utilizzati
L’indicatore usa esclusivamente dati disponibili sulla piattaforma TradingView del grafico corrente:
price (close) — per calcolare la variazione percentuale del prezzo;
volume per misurare l’intensità degli scambi (normalizzato su media);
ATR (Average True Range) — per normalizzare la volatilità rispetto al prezzo;
Tutti i feed (prezzo e volume) sono quelli forniti dall’exchange/fornitore dati collegato al simbolo sul grafico.
3) Logica e passaggi di calcolo
Velocità del prezzo: calcolo della variazione percentuale tra la chiusura corrente e la chiusura N barre fa:
priceChange = (close - close ) / close
— misura la direzione e magnitudine del movimento in termine relativo.
Volume normalizzato: rapporto tra il volume corrente e la media mobile semplice del volume su length barre:
volNorm = volume / sma(volume, length)
— evidenzia volumi anomali rispetto alla media.
Volatilità normalizzata (ATR): rapporto ATR/close per rendere la volatilità comparabile across price levels:
atrNorm = atr(length) / close
Combinazione: il prodotto di questi fattori (con un piccolo offset su ATR) genera un valore grezzo:
rawPulse = priceChange * volNorm * (1 + atrNorm)
— se priceChange e volNorm sono positivi e l’ATR è presente, il rawPulse sarà significativamente positivo.
Smoothing: media mobile semplice (SMA) applicata al rawPulse e moltiplicazione per un fattore scalare (multiplier) per portare il range su livelli leggibili:
flowPulse = sma(rawPulse * multiplier, smoothLen)
4) Parametri esposti (default consigliati)
length (periodo analisi) — default 20: influenza calcolo Δ% e media volumi; allunga la finestra storica.
smoothLen (smussamento) — default 5: smoothing del segnale per ridurre rumore.
multiplier — default 100: fattore di scala per rendere l’oscillatore più leggibile.
5) Interpretazione pratica dei valori
FlowPulse > 0 (verde): predominanza di flusso d’ingresso — pressione d’acquisto. Maggiore il valore, più forte la convinzione (volume + movimento + volatilità).
FlowPulse < 0 (rosso): predominanza di flusso in uscita — pressione di vendita.
Vicino a 0: assenza di flussi netti chiari; mercato piatto o bilanciato.
Picchi repentini: indicano accelerate di flusso — spesso coincidono con rotture, open/close session, news.
Sostegno al trade: usa FlowPulse come conferma prima di entrare su breakout o come avviso di attenzione su esaurimenti.
6) Divergenze (come leggerle)
Le divergenze tra prezzo e FlowPulse sono segnali importanti:
Divergenza rialzista (bullish divergence): prezzo fa nuovi minimi mentre FlowPulse non fa nuovi minimi (o forma minimo relativo più alto) → indica che la spinta di vendita non è supportata da volume/volatilità, possibile inversione/rimbalzo.
Divergenza ribassista (bearish divergence): prezzo fa nuovi massimi mentre FlowPulse non li conferma (o forma massimo relativo più basso) → la spinta d’acquisto è “debole”, possibile esaurimento e inversione.
Note pratiche: cercare divergenze su timeframe maggiori (H4, D) per maggiore attendibilità; sui timeframe minori prendere solo come early warning.
7) Esempi d’uso operativo
Conferma breakout: prezzo rompe resistenza + FlowPulse positivo e crescente → breakout più probabile e con volumi reali.
Filtro per falsi segnali: prezzo rompe ma FlowPulse è piatto/negativo → alto rischio di false breakout.
Entrata per pullback: dopo breakout, attendere un pullback con FlowPulse che torna positivo → ingresso più prudente.
Gestione delle uscite: se sei long e FlowPulse improvvisamente si inverte in negativo su volumi elevati → considerare riduzione posizione o stop.
8) Timeframe consigliati
Intraday / Scalping: M5–M30 con length ridotto (es. 10–14) e smoothLen piccolo.
Swing trading: H1–H4 con length 20–50.
Position trading: D1 con length maggiore per filtrare rumore.
Testa i parametri sul tuo asset e timeframe; nessun parametro è universale.
9) Limitazioni e avvertenze
L’indicatore non è un sistema di trading completo: è un tool di informazione e timing.
Dipende dalla qualità dei dati di volume del simbolo: su alcuni titoli/mercati (es. alcuni ETF, Forex su certi broker) il volume può essere parziale o non rappresentativo.
I valori di margine/multiplier e smoothing influenzano sensibilmente sensibilità e falsi segnali: backtest e ottimizzazione sono raccomandati.
Non usare il solo FlowPulse per entrare su leva elevata senza gestione del rischio12) Disclaimer da inserire
Disclaimer: Questo indicatore è fornito solo a scopo didattico e non costituisce consulenza finanziaria. L’uso comporta rischi: valuta sempre la gestione del rischio e testa su conto demo prima dell’applicazione in reale.
📋 Trading Checklist – Precision Entry SystemTake your trading discipline to the next level with this Precision Trading Checklist for TradingView. Designed for intraday traders following liquidity, structure, and Smart Money Concepts (SMC) AKA ICT Concepts, this overlay ensures you never miss a key confirmation before entering a trade.
Features:
✅ Pre-Market Preparation: Track previous session highs/lows, AM/PM sessions, and key liquidity zones.
✅ Bias & Narrative Check: Quickly confirm daily trend, price position relative to daily open, and higher timeframe confluence.
✅ Session-Specific Rules: Focused sessions like Silver Bullet (10:00–11:30), Afternoon (13:30–15:00), and Final Hour (15:00–16:00).
✅ Structure & Setup Validation: Confirm liquidity sweeps, market structure shifts, expansion candles, fair value gaps, and order blocks.
✅ Risk Management Reminders: Stop-loss, target points, risk percentage, breakeven management, and pyramiding rules.
✅ Post-Trade Journaling: Document entries, session, setup type, trade outcome, and grading for continuous improvement.
✅ Golden Rules: Visual reminders to enforce discipline, avoid emotional trades, and respect session limits.
Why Use It:
This checklist is perfect for traders who want to stay consistent, minimise mistakes, and follow a disciplined routine. Displayed as an overlay on your chart, it provides all essential checks in one glance, keeping you focused on the setup rather than scrolling through notes or separate trackers.
How to use:
Add the indicator to your chart
Click the settings/gear icon
Check off items as you complete them
The checklist on your chart updates in real-time with green checkmarks!
The checkboxes will persist as long as the indicator is on your chart,
making it perfect for tracking your pre-trade and post-trade routines!
Follow the checklist items step by step before entering trades.
Use the session-specific guidelines to filter setups.
Journal your trades post-execution for growth and analysis.
Inter-symmetric Forecast (ISF)Concept:
The Inter-Symmetric Forecast (ISF) is a physics-inspired price projection tool that visualizes both trend-continuation and mean-reversion scenarios in one dynamic structure. It extends the classic ADAM Projection by introducing a regime-sensitive weighting based on the Market Reynolds Number (Reₘ), a dimensionless ratio of market momentum × liquidity to volatility-derived “viscosity.”
Mechanism:
ISF mirrors past price action around the current close (the continuation path) while also forward-pasting the same pattern unreflected (the anti-trend path). It then blends these paths bar-by-bar using time-reflected Reₘ values — meaning the liquidity-momentum regime of each past segment determines how much its future mirror leans toward continuation or reversion.
Interpretation:
High Reₘ → strong inertia/liquidity, favors trend continuation.
Low Reₘ → high friction/volatility, favors mean reversion.
The yellow blended forecast shows the regime-weighted midpoint between both outcomes.
Use:
ISF offers traders a visual probability corridor rather than a fixed prediction — illustrating how far a move might extend if momentum persists, or fade if conditions become viscous. It’s best used as a contextual forecasting overlay for discretionary or systematic analysis.
Quantura - Fair Value GapIntroduction
“Quantura – Fair Value Gap” is a precision-engineered institutional concept indicator designed to automatically identify, visualize, and manage Fair Value Gaps (FVGs) across any market or timeframe. It enables traders to observe price inefficiencies, potential liquidity voids, and retracement areas that often act as magnets for price rebalancing.
Originality & Value
Unlike many public FVG scripts that only highlight candle gaps, this indicator integrates dynamic filters and adaptive logic to determine the strength and reliability of each gap. It merges overlapping zones intelligently and optionally extends valid imbalances forward for ongoing reference.
Its value lies in:
Dynamic statistical filtering based on gap standard deviation.
Optional volume confirmation for high-confidence FVGs.
Automatic merging of overlapping or adjacent gaps for clean visualization.
Support for both bullish and bearish imbalances.
Signal alerts when gaps are filled or rebalanced by price.
Functionality & Core Logic
Detects Fair Value Gaps by comparing candle-to-candle price displacement.
Applies a Gap Filter (standard deviation-based) to qualify valid gaps.
Optionally validates gaps formed under significant volume conditions.
Draws color-coded boxes to mark bullish (discount) and bearish (premium) inefficiencies.
Monitors each FVG until price fills the gap, at which point the box is visually closed.
Provides optional signal markers (“▲” or “▼”) when rebalancing occurs.
Parameters & Customization
Gap Filter: Sets the minimum statistical deviation required for a valid FVG. Higher values detect fewer, stronger gaps.
Volume Filter: Toggles additional validation using relative volume strength.
Volume Sensitivity: Adjusts how much above-average volume must be present to confirm a gap.
Bullish/Bearish Colors: Customize color schemes for imbalance zones.
Extend Gaps: Optionally extend open gaps forward for better confluence tracking.
Signals: Enables or disables gap-fill signal markers.
Visualization & Display
Bullish FVGs: Appear in blue-tinted boxes, indicating potential demand-side inefficiencies.
Bearish FVGs: Appear in red-tinted boxes, representing potential supply-side inefficiencies.
Overlapping zones are merged automatically to maintain clarity.
Filled gaps remain visible for historical context, allowing for post-event analysis.
Optional signal arrows display when price returns to rebalance an FVG.
Use Cases
Identify institutional inefficiencies and liquidity voids.
Detect premium and discount levels in trending markets.
Combine with market structure or order block indicators for confluence.
Track when price rebalances inefficiencies to refine entry/exit points.
Build FVG-based algorithmic strategies that rely on structural imbalance resolution.
Limitations & Recommendations
The indicator detects structural imbalances but does not predict future direction or guarantee profitability.
Volume filters may behave differently across brokers due to data-source differences.
Use alongside structure or liquidity tools for enhanced decision-making.
Extreme volatility or illiquid assets may generate temporary invalid gaps.
Markets & Timeframes
Compatible with all markets (crypto, forex, equities, indices, futures) and all timeframes. Recommended for multi-timeframe confluence analysis — e.g., detecting higher-timeframe FVGs and refining lower-timeframe entries.
Author & Access
Developed 100% by Quantura. Published as a Open-source script indicator. Access is free.
Compliance Note
This description adheres fully to TradingView’s House Rules and Script Publishing Requirements . It provides a detailed explanation of originality, core logic, limitations, and appropriate use — with no unrealistic or misleading performance claims.
Ornstein-Uhlenbeck Trend Channel [BOSWaves]Ornstein-Uhlenbeck Trend Channel - Adaptive Mean Reversion with Dynamic Equilibrium Geometry
Overview
The Ornstein-Uhlenbeck Trend Channel introduces an advanced equilibrium-mapping framework that blends statistical mean reversion with adaptive trend geometry. Traditional channels and regression bands react linearly to volatility, often failing to capture the natural rhythm of price equilibrium. This model evolves that concept through a dynamic reversion engine, where equilibrium adapts continuously to volatility, trend slope, and structural bias - forming a living channel that bends, expands, and contracts in real time.
The result is a smooth, equilibrium-driven representation of market balance - not just trend direction. Instead of static bands or abrupt slope shifts, traders see fluid, volatility-aware motion that mirrors the natural pull-and-release dynamic of market behavior. Each channel visualizes the probabilistic boundaries of fair value, showing where price tends to revert and where it accelerates away from its statistical mean.
Unlike conventional envelopes or Bollinger-type constructs, the Ornstein-Uhlenbeck framework is volatility-reactive and equilibrium-sensitive, providing traders with a contextual map of where price is likely to stabilize, extend, or exhaust.
Theoretical Foundation
The Ornstein-Uhlenbeck Trend Channel is inspired by stochastic mean-reversion processes - mathematical models used to describe systems that oscillate around a drifting equilibrium. While linear regression channels assume constant variance, financial markets operate under variable volatility and shifting equilibrium points. The OU process accounts for this by treating price as a mean-seeking motion governed by volatility and trend persistence.
At its core are three interacting components:
Equilibrium Mean (μ) : Represents the evolving balance point of price, adjusting to directional bias and volatility.
Reversion Rate (θ) : Defines how strongly price is pulled back toward equilibrium after deviation, capturing the self-correcting nature of market structure.
Volatility Coefficient (σ) : Controls how far and how quickly price can diverge from equilibrium before mean reversion pressure increases.
By embedding this stochastic model inside a volatility-adjusted framework, the system accurately scales across different markets and conditions - maintaining meaningful equilibrium geometry across crypto, forex, indices, or commodities. This design gives traders a mathematically grounded yet visually intuitive interpretation of dynamic balance in live market motion.
How It Works
The Ornstein-Uhlenbeck Trend Channel is constructed through a structured multi-stage process that merges stochastic logic with volatility mechanics:
Equilibrium Estimation Core : The indicator begins by identifying the evolving mean using adaptive smoothing influenced by trend direction and volatility. This becomes the live centerline - the statistical anchor around which price naturally oscillates.
Volatility Normalization Layer : ATR or rolling deviation is used to calculate volatility intensity. The output scales the channel width dynamically, ensuring that boundaries reflect current variance rather than static thresholds.
Directional Bias Engine : EMA slope and trend confirmation logic determine whether equilibrium should tilt upward or downward. This creates asymmetrical channel motion that bends with the prevailing trend rather than staying horizontal.
Channel Boundary Construction : Upper and lower bands are plotted at volatility-proportional distances from the mean. These envelopes form the “statistical pressure zones” that indicate where mean reversion or acceleration may occur.
Signal and Lifecycle Control : Channel breaches, mean crossovers, and slope flips mark statistically significant events - exhaustion, continuation, or rebalancing. Older equilibrium zones gradually fade, ensuring a clear, context-aware visual field.
Through these layers, the channel forms a continuously updating equilibrium corridor that adapts in real time - breathing with the market’s volatility and rhythm.
Interpretation
The Ornstein-Uhlenbeck Trend Channel reframes how traders interpret balance and momentum. Instead of viewing price as directional movement alone, it visualizes the constant tension between trending force and equilibrium pull.
Uptrend Phases : The equilibrium mean tilts upward, with price oscillating around or slightly above the midline. Upper band touches signal momentum extension; lower touches reflect healthy reversion.
Downtrend Phases : The mean slopes downward, with upper-band interactions marking resistance zones and lower bands acting as reversion boundaries.
Equilibrium Transitions : Flat mean sections indicate balance or distribution phases. Breaks from these neutral zones often precede directional expansion.
Overextension Events : When price closes beyond an outer boundary, it marks statistically significant disequilibrium - an early warning of exhaustion or volatility reset.
Visually, the OU channel translates volatility and equilibrium into structured geometry, giving traders a statistical lens on trend quality, reversion probability, and volatility stress points.
Strategy Integration
The Ornstein-Uhlenbeck Trend Channel integrates seamlessly into both mean-reversion and trend-continuation systems:
Trend Alignment : Use mean slope direction to confirm higher-timeframe bias before entering continuation setups.
Reversion Entries : Target rejections from outer bands when supported by volume or divergence, capturing snapbacks toward equilibrium.
Volatility Breakout Mapping : Monitor boundary expansions to identify transition from compression to expansion phases.
Liquidity Zone Confirmation : Combine with BOS or order-block indicators to validate structural zones against equilibrium positioning.
Momentum Filtering : Align with oscillators or volume profiles to isolate equilibrium-based pullbacks with statistical context.
Technical Implementation Details
Core Engine : Stochastic Ornstein-Uhlenbeck process for continuous mean recalibration.
Volatility Framework : ATR- and deviation-based scaling for dynamic channel expansion.
Directional Logic : EMA-slope driven bias for adaptive mean tilt.
Channel Composition : Independent upper and lower envelopes with smoothing and transparency control.
Signal Structure : Alerts for mean crossovers and boundary breaches.
Performance Profile : Lightweight, multi-timeframe compatible implementation optimized for real-time responsiveness.
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Reactive equilibrium tracking for short-term scalping and microstructure analysis.
15 - 60 min : Medium-range setups for volatility-phase transitions and intraday structure.
4H - Daily : Macro equilibrium mapping for identifying exhaustion, distribution, or reaccumulation zones.
Suggested Configuration:
Mean Length : 20 - 50
Volatility Multiplier : 1.5× - 2.5×
Reversion Sensitivity : 0.4 - 0.8
Smoothing : 2 - 5
Parameter tuning should reflect asset liquidity, volatility, and desired reversion frequency.
Performance Characteristics
High Effectiveness:
Trending environments with cyclical pullbacks and volatility oscillation.
Markets exhibiting consistent equilibrium-return behavior (indices, majors, high-cap crypto).
Reduced Effectiveness:
Low-volatility consolidations with minimal variance.
Random walk markets lacking definable equilibrium anchors.
Integration Guidelines
Confluence Framework : Pair with BOSWaves structural tools or momentum oscillators for context validation.
Directional Control : Follow mean slope alignment for directional conviction before acting on channel extremes.
Risk Calibration : Use outer band violations for controlled contrarian entries or trailing stop management.
Multi-Timeframe Synergy : Derive macro equilibrium zones on higher timeframes and refine entries on lower levels.
Disclaimer
The Ornstein-Uhlenbeck Trend Channel is a professional-grade equilibrium and volatility framework. It is not predictive or profit-assured; performance depends on parameter calibration, volatility regime, and disciplined execution. BOSWaves recommends using it as part of a comprehensive analytical stack combining structure, liquidity, and momentum context.
Aibuyzone Spot & Swing ZonesAibuyzone Spot & Swing Zones is a technical tool that helps identify potential buy zones during established bullish trends.
It is designed for spot and swing traders who prefer to buy pullbacks within broader uptrends.
This indicator does not place trades or make predictions — it only highlights contextual market areas for study.
How It Works
Trend Alignment Filter
A higher-timeframe EMA and two local EMAs determine trend direction.
Only when both the local and higher-timeframe trends agree as bullish will a potential buy zone be considered valid.
Dynamic Buy Zone (Value Area)
The indicator measures a rolling price range over a user-selected number of bars (e.g., last 50).
The lower fraction of this range (configurable percentage) becomes the buy zone band.
When price revisits this lower section during a bullish trend, it is interpreted as a potential value or discount area.
Liquidity Sweep Filter (Optional)
Detects bars that make a new low relative to recent candles and then close back up with a strong lower wick.
This condition can indicate a possible liquidity grab or stop-hunt event that precedes reversals.
RSI Pullback Filter (Optional)
Confirms that price momentum has cooled during the pullback phase.
Signals occur when RSI falls within a defined “pullback” zone (default 30–55), helping avoid chasing overextended moves.
Confluence Scoring
Each of the three criteria — buy zone presence, liquidity sweep, RSI pullback — adds one point to a confluence score.
A signal only appears when the score meets or exceeds the chosen threshold (for example, 2 of 3).
Visual Elements
Fast and Slow EMAs for short-term trend visualization.
A shaded area marking the dynamic buy zone.
Optional background tint when the overall trend is bullish.
Optional labels below bars when confluence criteria are met.
Alert condition available for custom user alerts.
Suggested Use
Select a higher timeframe that fits your trading horizon (e.g., 4h for swing, 1d for position trading).
Use the shaded band as a visual guide for where price may offer “discounts” within an uptrend.
Combine with support/resistance, volume, or other confluence methods for confirmation.
Adjust the confluence requirement for stricter or looser signals.
Disclaimer
This script is provided for educational and analytical purposes only.
It does not constitute financial advice or a recommendation to buy or sell any asset.
All trading involves risk — always perform your own analysis and manage risk according to your own judgment.
Session Dominator — Asia • London • New York Precision ZonesRule the global market sessions.
Session Dominator is a precision-engineered indicator built for traders who want total clarity across Asia, London, and New York sessions.
It automatically plots:
🔷 Dynamic Session Boxes — visually map institutional killzones in real time
⚙️ Session Mean Line — track equilibrium and liquidity shifts
📊 EMA-50 Confluence — align directional bias and intraday trend
🎯 BSL / SSL Levels — reveal active liquidity sweeps and reversals
💡 Bias Engine — evaluates structure and locks the session bias automatically
Toggle between Asia / London / New York / Overlap / Custom modes to dominate any timezone.
Designed with minimalist visuals, high precision, and ICT-based logic — this tool helps you anticipate where liquidity will be taken before it happens.
✳️ For XAUUSD traders, scalpers, and ICT-style analysts seeking sniper-level clarity.
RAFEN-G - Kill Zones & Institutional Gaps🔍 What It Does
Kill Zones (KZ1, KZ2, KZ3)
Automatically highlights the main intraday liquidity windows such as the London open, NY AM, and NY PM sessions — customizable by time, color, and transparency.
Perfect for timing setups, identifying liquidity sweeps, or backtesting session behavior.
Institutional GAP Detection (NY 11:00 → 03:00)
Anchored on the New York H1 clock, the script automatically draws the “institutional gap” between the 11:00 close and the 03:00 open of the next trading day.
Each gap is drawn as a transparent box with a label showing its size in price units.
Dynamic Cleanup & Color Updates
Automatically removes old boxes beyond your chosen history limit and keeps all visuals perfectly synchronized in real-time.
⚙️ Key Features
3 fully independent and editable Kill Zones
Adjustable timezone (default: America/New_York)
Works on all intraday timeframes
Auto-management of historical data
Clean and lightweight visuals (up to 2000 boxes)
Real-time color and transparency updates
Alerts when each Kill Zone starts
🧠 Ideal For
Traders using ICT, SMC, or institutional frameworks who want clear visual separation of market sessions and automatic tracking of session-to-session gaps for confluence or imbalance analysis.
🕐 Recommended Use
Apply on 5 min / 15 min / 1 h charts, align timezone to NYC, and combine with liquidity or FVG tools for maximum insight.
ICT Sweep + CHoCH + FVG Alerts
### 🔥 ICT Sweep + CHoCH + FVG Alerts
Script designed to automate ICT entry confirmations using:
• Liquidity Sweep (Buy/Sell Stops taken)
• Change of Character (CHoCH)
• Fair Value Gap (FVG) confirmation
### ✅ Conditions
**Long signal when:**
1. Bearish liquidity sweep
2. Bullish CHoCH
3. Bullish FVG forms and gets respected
**Short signal when:**
1. Bullish liquidity sweep
2. Bearish CHoCH
3. Bearish FVG forms and gets respected
### 🎯 Purpose
This script helps traders detect smart-money setup entries based on ICT logic and receive alerts in real time.
### 📡 Alerts
Supports webhook automation for bots, signal servers, or trading platforms.
*This script does not place trades automatically, alerts only.*
### ⚠️ Disclaimer
This tool is for educational purposes.
Always backtest and use proper risk management.
Multi-Mode Seasonality Map [BackQuant]Multi-Mode Seasonality Map
A fast, visual way to expose repeatable calendar patterns in returns, volatility, volume, and range across multiple granularities (Day of Week, Day of Month, Hour of Day, Week of Month). Built for idea generation, regime context, and execution timing.
What is “seasonality” in markets?
Seasonality refers to statistically repeatable patterns tied to the calendar or clock, rather than to price levels. Examples include specific weekdays tending to be stronger, certain hours showing higher realized volatility, or month-end flow boosting volumes. This tool measures those effects directly on your charted symbol.
Why seasonality matters
It’s orthogonal alpha: timing edges independent of price structure that can complement trend, mean reversion, or flow-based setups.
It frames expectations: when a session typically runs hot or cold, you size and pace risk accordingly.
It improves execution: entering during historically favorable windows, avoiding historically noisy windows.
It clarifies context: separating normal “calendar noise” from true anomaly helps avoid overreacting to routine moves.
How traders use seasonality in practice
Timing entries/exits : If Tuesday morning is historically weak for this asset, a mean-reversion buyer may wait for that drift to complete before entering.
Sizing & stops : If 13:00–15:00 shows elevated volatility, widen stops or reduce size to maintain constant risk.
Session playbooks : Build repeatable routines around the hours/days that consistently drive PnL.
Portfolio rotation : Compare seasonal edges across assets to schedule focus and deploy attention where the calendar favors you.
Why Day-of-Week (DOW) can be especially helpful
Flows cluster by weekday (ETF creations/redemptions, options hedging cadence, futures roll patterns, macro data releases), so DOW often encodes a stable micro-structure signal.
Desk behavior and liquidity provision differ by weekday, impacting realized range and slippage.
DOW is simple to operationalize: easy rules like “fade Monday afternoon chop” or “press Thursday trend extension” can be tested and enforced.
What this indicator does
Multi-mode heatmaps : Switch between Day of Week, Day of Month, Hour of Day, Week of Month .
Metric selection : Analyze Returns , Volatility ((high-low)/open), Volume (vs 20-bar average), or Range (vs 20-bar average).
Confidence intervals : Per cell, compute mean, standard deviation, and a z-based CI at your chosen confidence level.
Sample guards : Enforce a minimum sample size so thin data doesn’t mislead.
Readable map : Color palettes, value labels, sample size, and an optional legend for fast interpretation.
Scoreboard : Optional table highlights best/worst DOW and today’s seasonality with CI and a simple “edge” tag.
How it’s calculated (under the hood)
Per bar, compute the chosen metric (return, vol, volume %, or range %) over your lookback window.
Bucket that metric into the active calendar bin (e.g., Tuesday, the 15th, 10:00 hour, or Week-2 of month).
For each bin, accumulate sum , sum of squares , and count , then at render compute mean , std dev , and confidence interval .
Color scale normalizes to the observed min/max of eligible bins (those meeting the minimum sample size).
How to read the heatmap
Color : Greener/warmer typically implies higher mean value for the chosen metric; cooler implies lower.
Value label : The center number is the bin’s mean (e.g., average % return for Tuesdays).
Confidence bracket : Optional “ ” shows the CI for the mean, helping you gauge stability.
n = sample size : More samples = more reliability. Treat small-n bins with skepticism.
Suggested workflows
Pick the lens : Start with Analysis Type = Returns , Heatmap View = Day of Week , lookback ≈ 252 trading days . Note the best/worst weekdays and their CI width.
Sanity-check volatility : Switch to Volatility to see which bins carry the most realized range. Use that to plan stop width and trade pacing.
Check liquidity proxy : Flip to Volume , identify thin vs thick windows. Execute risk in thicker windows to reduce slippage.
Drill to intraday : Use Hour of Day to reveal opening bursts, lunchtime lulls, and closing ramps. Combine with your main strategy to schedule entries.
Calendar nuance : Inspect Week of Month and Day of Month for end-of-month, options-cycle, or data-release effects.
Codify rules : Translate stable edges into rules like “no fresh risk during bottom-quartile hours” or “scale entries during top-quartile hours.”
Parameter guidance
Analysis Period (Days) : 252 for a one-year view. Shorten (100–150) to emphasize the current regime; lengthen (500+) for long-memory effects.
Heatmap View : Start with DOW for robustness, then refine with Hour-of-Day for your execution window.
Confidence Level : 95% is standard; use 90% if you want wider coverage with fewer false “insufficient data” bins.
Min Sample Size : 10–20 helps filter noise. For Hour-of-Day on higher timeframes, consider lowering if your dataset is small.
Color Scheme : Choose a palette with good mid-tone contrast (e.g., Red-Green or Viridis) for quick thresholding.
Interpreting common patterns
Return-positive but low-vol bins : Favorable drift windows for passive adds or tight-stop trend continuation.
Return-flat but high-vol bins : Opportunity for mean reversion or breakout scalping, but manage risk accordingly.
High-volume bins : Better expected execution quality; schedule size here if slippage matters.
Wide CI : Edge is unstable or sample is thin; treat as exploratory until more data accumulates.
Best practices
Revalidate after regime shifts (new macro cycle, liquidity regime change, major exchange microstructure updates).
Use multiple lenses: DOW to find the day, then Hour-of-Day to refine the entry window.
Combine with your core setup signals; treat seasonality as a filter or weight, not a standalone trigger.
Test across assets/timeframes—edges are instrument-specific and may not transfer 1:1.
Limitations & notes
History-dependent: short histories or sparse intraday data reduce reliability.
Not causal: a hot Tuesday doesn’t guarantee future Tuesday strength; treat as probabilistic bias.
Aggregation bias: changing session hours or symbol migrations can distort older samples.
CI is z-approximate: good for fast triage, not a substitute for full hypothesis testing.
Quick setup
Use Returns + Day of Week + 252d to get a clean yearly map of weekday edge.
Flip to Hour of Day on intraday charts to schedule precise entries/exits.
Keep Show Values and Confidence Intervals on while you calibrate; hide later for a clean visual.
The Multi-Mode Seasonality Map helps you convert the calendar from an afterthought into a quantitative edge, surfacing when an asset tends to move, expand, or stay quiet—so you can plan, size, and execute with intent.
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
Volume Profile Area [BigBeluga]🔵 OVERVIEW
The Volume Profile Area is an advanced profiling tool that calculates and visualizes the value area within a chosen period’s volume distribution. It first builds a main profile of the entire range, then constructs a secondary profile inside the defined value area, allowing traders to examine market balance and key trading zones in greater detail.
🔵 CONCEPTS
Volume Profile – Distributes traded volume across price levels to highlight areas of market activity.
Value Area (VA) – The price range containing a chosen percentage of total volume (commonly 50–70%).
Point of Control (PoC) – The price level with the highest traded volume, often acting as a magnet for price.
Nested Profiles – A profile inside the VA adds a second layer of precision, showing where liquidity clusters within the “fair value” zone.
🔵 FEATURES
Main Profile – Full distribution of volume over the selected lookback period.
Secondary Profile – Built only inside the VA of the main profile, highlighting intrabalance structure.
Customizable PoC Selection – Choose between showing the PoC of the
Main Profile ,
the Area Profile ,
their Average ,
or None .
Dynamic Value Area Levels – Automatically plots VAL (Value Area Low) and VAH (Value Area High) with labels.
Overlay Toggles – Show/hide range extremes, VA lines, or PoCs for a cleaner chart view.
Visual Profiles – Main profile shaded in darker blue; the VA profile inside is lighter for clear separation.
Automatic Scaling – Profiles adapt to period highs/lows and auto-adjust bins for consistent resolution.
Volume Labels – PoCs can display traded volume, giving numeric confirmation of liquidity concentration.
🔵 HOW TO USE
Set the Period to define how many bars to include in the main profile.
Adjust the Value Area % to control how much volume defines the VA (e.g., 50% by default).
Pick your PoC option: Main , Area , or Average , depending on focus.
Use VAH/VAL lines as support/resistance levels where most trading occurred.
Compare reactions at Main vs VA PoC levels to spot potential breakouts or mean reversions.
🔵 CONCLUSION
The Volume Profile Area extends traditional profiling by nesting a secondary VA profile inside the main distribution. This dual-layer approach reveals not just where the market was active overall, but where liquidity concentrated within the “fair value” zone—powerful for refining entries, exits, and risk placement across intraday and swing horizons.
Kalman VWAP Filter [BackQuant]Kalman VWAP Filter
A precision-engineered price estimator that fuses Kalman filtering with the Volume-Weighted Average Price (VWAP) to create a smooth, adaptive representation of fair value. This hybrid model intelligently balances responsiveness and stability, tracking trend shifts with minimal noise while maintaining a statistically grounded link to volume distribution.
If you would like to see my original Kalman Filter, please find it here:
Concept overview
The Kalman VWAP Filter is built on two core ideas from quantitative finance and control theory:
Kalman filtering — a recursive Bayesian estimator used to infer the true underlying state of a noisy system (in this case, fair price).
VWAP anchoring — a dynamic reference that weights price by traded volume, representing where the majority of transactions have occurred.
By merging these concepts, the filter produces a line that behaves like a "smart moving average": smooth when noise is high, fast when markets trend, and self-adjusting based on both market structure and user-defined noise parameters.
How it works
Measurement blend : Combines the chosen Price Source (e.g., close or hlc3) with either a Session VWAP or a Rolling VWAP baseline. The VWAP Weight input controls how much the filter trusts traded volume versus price movement.
Kalman recursion : Each bar updates an internal "state estimate" using the Kalman gain, which determines how much to trust new observations vs. the prior state.
Noise parameters :
Process Noise controls agility — higher values make the filter more responsive but also more volatile.
Measurement Noise controls smoothness — higher values make it steadier but slower to adapt.
Filter order (N) : Defines how many parallel state estimates are used. Larger orders yield smoother output by layering multiple one-dimensional Kalman passes.
Final output : A refined price trajectory that captures VWAP-adjusted fair value while dynamically adjusting to real-time volatility and order flow.
Why this matters
Most smoothing techniques (EMA, SMA, Hull) trade off lag for smoothness. Kalman filtering, however, adaptively rebalances that tradeoff each bar using probabilistic weighting, allowing it to follow market state changes more efficiently. Anchoring it to VWAP integrates microstructure context — capturing where liquidity truly lies rather than only where price moves.
Use cases
Trend tracking : Color-coded candle painting highlights shifts in slope direction, revealing early trend transitions.
Fair value mapping : The line represents a continuously updated equilibrium price between raw price action and VWAP flow.
Adaptive moving average replacement : Outperforms static MAs in variable volatility regimes by self-adjusting smoothness.
Execution & reversion logic : When price diverges from the Kalman VWAP, it may indicate short-term imbalance or overextension relative to volume-adjusted fair value.
Cross-signal framework : Use with standard VWAP or other filters to identify convergence or divergence between liquidity-weighted and state-estimated prices.
Parameter guidance
Process Noise : 0.01–0.05 for swing traders, 0.1–0.2 for intraday scalping.
Measurement Noise : 2–5 for normal use, 8+ for very smooth tracking.
VWAP Weight : 0.2–0.4 balances both price and VWAP influence; 1.0 locks output directly to VWAP dynamics.
Filter Order (N) : 3–5 for reactive short-term filters; 8–10 for smoother institutional-style baselines.
Interpretation
When price > Kalman VWAP and slope is positive → bullish pressure; buyers dominate above fair value.
When price < Kalman VWAP and slope is negative → bearish pressure; sellers dominate below fair value.
Convergence of price and Kalman VWAP often signals equilibrium; strong divergence suggests imbalance.
Crosses between Kalman VWAP and the base VWAP can hint at shifts in short-term vs. long-term liquidity control.
Summary
The Kalman VWAP Filter blends statistical estimation with market microstructure awareness, offering a refined alternative to static smoothing indicators. It adapts in real time to volatility and order flow, helping traders visualize balance, transition, and momentum through a lens of probabilistic fair value rather than simple price averaging.
ICT Macro Time WindowsICT Macro Time Windows - Master institutional market timing with automated 'Macro' trading session tracking.
What are 'Macros'?
In ICT terminology, 'Macros' refer to the key institutional trading windows throughout the day where major banks and liquidity providers are most active. These specific time frames see heightened volatility, liquidity, and strategic positioning.
Perfect Timing Automation:
• 8 Critical Macro Sessions:
London 1: 02:33-03:00 EST
London 2: 04:03-04:30 EST
NY AM1: 08:50-09:10 EST
NY AM2: 09:50-10:10 EST
NY AM3: 10:50-11:10 EST
Lunch: 11:50-12:10 EST
PM: 13:10-13:40 EST
Close: 15:15-15:45 EST
• Fully customizable time zones and session times
• Real-time session detection with visual zones & labels
• Automatic High/Low range tracking within each window
• Boxes, lines, and labels for clear visual reference
• Never miss optimal entry/exit timing again
Trade when institutions trade - stop guessing and start timing your setups with precision during these key liquidity windows! All session times are easily adjustable in settings to match your preferred trading hours.
Perfect for Forex, Futures, and Index traders following ICT concepts and institutional flow analysis.
Smart Money Dynamics Blocks - Pearson MatrixSmart Money Dynamics Blocks — Pearson Matrix
A structural fusion of Prime Number Theory, Pearson Correlation, and Cumulative Delta Geometry.
1. Mathematical Foundation
This indicator is built on the intersection of Prime Number Theory and the Pearson correlation coefficient, creating a structural framework that quantifies how price and time evolve together.
Prime numbers — unique, indivisible, and irregular — are used here as nonlinear time intervals. Each prime length (2, 3, 5, 7, 11…97) represents a regression horizon where correlation is measured between price and time. The result is a multi-scale correlation lattice — a geometric matrix that captures hidden directional strength and temporal bias beyond traditional moving averages.
2. The Pearson Matrix Logic
For every prime interval p, the indicator calculates the linear correlation:
r_p = corr(price, bar_index, p)
Each r_p reflects how closely price and time move together across a prime-defined window. All r_p values are then averaged to create avgR, a single adaptive coefficient summarizing overall structural coherence.
- When avgR > 0.8 → strong positive correlation (labeled R+).
- When avgR < -0.8 → strong negative correlation (labeled R−).
This approach gives a mathematically grounded definition of trend — one that isn’t based on pattern recognition, but on measurable correlation strength.
3. Sequential Prime Slope and Median Pivot
Using the ordered sequence of 25 prime intervals, the model computes sequential slopes between adjacent primes. These slopes represent the rate of change of structure between two prime scales. A robust median aggregator smooths the slopes, producing a clean, stable directional vector.
The system anchors this slope to the 41-bar pivot — the median of the first 25 primes — serving as the geometric midpoint of the prime lattice. The resulting yellow line on the chart is not an ordinary regression line; it’s a dynamic prime-slope function, adapting continuously with correlation feedback.
4. Regression-Style Parallel Bands
Around this prime-slope line, the indicator constructs parallel bands using standard deviation envelopes — conceptually similar to a regression channel but recalculated through the prime–Pearson matrix.
These bands adjust dynamically to:
- Volatility, via standard deviation of residuals.
- Correlation strength, via avgR sign weighting.
Together, they visualize statistical deviation geometry, making it easier to observe symmetry, expansion, and contraction phases of price structure.
5. Volume and Cumulative Delta Peaks
Below the geometric layer, the indicator incorporates a custom lower-timeframe volume feed — by default using 15-second data (custom_tf_input_volume = “15S”). This allows precise delta computation between up-volume and down-volume even on higher timeframe charts.
From this feed, the indicator accumulates delta over a configurable period (default: 100 bars). When cumulative delta reaches a local maximum or minimum, peak and trough markers appear, showing the precise bar where buying or selling pressure statistically peaked.
This combination of geometry and order flow reveals the intersection of market structure and energy — where liquidity pressure expresses itself through mathematical form.
6. Chart Interpretation
The primary chart view represents the live execution of the indicator. It displays the relationship between structural correlation and volume behavior in real time.
Orange “R+” and blue “R−” labels indicate regions of strong positive or negative Pearson correlation across the prime matrix. The yellow median prime-slope line serves as the structural backbone of the indicator, while green and red parallel bands act as dynamic regression boundaries derived from the underlying correlation strength. Peaks and troughs in cumulative delta — displayed as numerical annotations — mark statistically significant shifts in buying and selling pressure.
The secondary visualization (Prime Regression Concept) expands on this by illustrating how regression behavior evolves across prime intervals. Each colored regression fan corresponds to a prime number window (2, 3, 5, 7, …, 97), demonstrating how multiple regression lines would appear if drawn independently. The indicator integrates these into one unified geometric model — eliminating the need to plot tens of regression lines manually. It’s a conceptual tool to help visualize the internal logic: the synthesis of many small-scale regressions into a single coherent structure.
7. Interpretive Insight
This model is not a prediction tool; it’s an instrument of mathematical observation. By translating price dynamics into a prime-structured correlation space, it reveals how coherence unfolds through time — not as a forecast, but as a measurable evolution of structure.
It unifies three analytical domains:
- Prime distribution — defines a nonlinear temporal architecture.
- Pearson correlation — quantifies statistical cohesion.
- Cumulative delta — expresses behavioral imbalance in order flow.
The synthesis creates a geometric analysis of liquidity and time — where structure meets energy, and where the invisible rhythm of market flow becomes measurable.
8. Contribution & Feedback
Share your observations in the comments:
- The time gap and alternation between R+ and R− clusters.
- How different timeframes change delta sensitivity or reveal compression/expansion.
- Prime intervals/clusters that tend to sit near turning points or liquidity shifts.
- How avgR behaves across assets or regimes (trending, ranging, high-vol).
- Notable interactions with the parallel bands (touches, breaks, mean-revert).
Your field notes help others read the model more effectively and compare contexts.
Summary
- Primes define the structure.
- Pearson quantifies coherence.
- Slope median stabilizes geometry.
- Regression bands visualize deviation.
- Cumulative delta locates imbalance.
Together, they construct a framework where mathematics meets market behavior.
