Ultimate Market Structure + MTF Dashboard [FIXED]Ultimate Market Structure + MTF Dashboard — Indicator Description
🔶 Overview
Ultimate Market Structure + MTF Dashboard is a fully-automated Smart Money Concepts (SMC) market-structure indicator designed to give traders extremely clean and accurate structural mapping on any timeframe.
It intelligently detects:
External (Swing) Structure
Internal Structure
BOS / CHoCH (Break of Structure / Change of Character)
HH/HL/LH/LL swing labels
Strong/Weak Highs & Lows
Equal Highs (EQH) & Equal Lows (EQL)
Internal BOS/CHoCH (micro-structure)
Multi-Timeframe Structure Dashboard (D, H4, H1, M15, M5)
This indicator eliminates clutter, repaints nothing, and provides crystal-clear visual understanding of market direction.
🎯 What This Indicator Solves
Most structure indicators fail because they:
✔ spam BOS/CHoCH everywhere
✔ repaint pivots
✔ mix internal and external structure
✔ draw messy lines
✔ ignore confluence
✔ don’t show higher timeframe structure
This script solves all of that by using:
Gap-proof pivot detection
Strict internal/external structure separation
Proper BOS/CHoCH logic using previous break
“LastBreak memory” system (no double BOS on same leg)
ATR-filtered internal pivots
Candle-context confluence filter
User-controlled filters for BOS/CHoCH only
Everything is designed for clean, reliable structure.
🧠 How It Works (Logic Explained Clearly)
1️⃣ Swing Structure – External
Based on user-defined swing length (default: 50).
Detects major turning points and evaluates:
HH / HL → Bullish structure
LH / LL → Bearish structure
Once a swing high/low is confirmed, the indicator tracks:
Has price crossed that pivot?
If yes → BOS or CHoCH depending on previous break direction.
2️⃣ Internal Structure – Micro Trend
A second layer using small length pivots (default: 5).
Useful for:
Entries
Scalp-level reversals
Early CHoCH detection
Internal structure uses ATR distance from swing pivots to avoid overlap.
3️⃣ BOS / CHoCH Logic
The script uses a very strict rule:
If previous break direction was opposite → CHoCH
If previous break direction was same → BOS
This eliminates false CHoCH spam and improves trend clarity.
4️⃣ Strong & Weak High/Low Detection
Each time a BOS occurs:
In bearish trend → last swing high = Strong High
In bullish trend → last swing low = Strong Low
Opposite becomes Weak High/Weak Low
These are important Smart Money Concepts levels for:
Premium/discount zones
Liquidity targets
Stop hunts
5️⃣ Equal Highs & Equal Lows (EQH/EQL)
The script automatically identifies EQH/EQL using:
Percentage threshold
Confirmation bar count
Useful for:
Liquidity sweep setups
Inducement
Stop runs
6️⃣ Multi-Timeframe Dashboard
Displays Internal & External structure for:
D (Daily)
H4
H1
M15
M5
Each cell is color-coded:
🟢 Bullish
🔴 Bearish
⚪ Neutral
This gives you instant top-down analysis without switching charts.
📌 What You Can Use This Indicator For
✔ Trend Trading
Keep trades aligned with:
Higher timeframe external trend
Lower timeframe internal entries
For example:
Daily → Bullish
H1 → Bullish
M5 → CHoCH bullish
Entry → Pullback to strong low
✔ Scalping
Internal structure (i-BOS, i-CHoCH) gives:
Fast reversals
Micro CHoCH entries
High-frequency trend shifts
Works extremely well on 1M–5M.
✔ Smart Money Concepts Trading
This indicator gives every SMC component you need:
Liquidity (EQH/EQL)
Swing structure
Internal structure
BOS/CHoCH
Strong/Weak High/Low
Multi-TF context
Perfect for ICT/SMC trading style.
✔ Institutional Order Flow Mapping
Using strong/weak highs/lows and BOS, you can easily determine:
Where smart money targets your stops
Where displacement started
Where structure shifted
Where mitigation may occur
✔ High-Timeframe Confirmation
The dashboard prevents you from trading against:
Daily trend
H4 liquidity levels
H1 structure direction
📈 Who Is This Indicator For?
Beginners
Learn structure visually instead of guessing.
Advanced Traders
Combine structure with:
Liquidity sweeps
FVG
OB
Breaker blocks
Momentum shifts
Scalpers
Use internal BOS/CHoCH for sniper entries.
Swing Traders
Use swing BOS to hold trades for large R:R moves.
ICT / SMC Traders
Perfect for order-block & FVG models.
📌 Recommended Settings
Swing Structure
Length: 50–100
Best for BTC, FX, XAU
Internal Structure
Length: 3–7
Best for scalping
EQ Threshold
FX: 0.10% – 0.25%
Crypto: 0.35% – 0.5%
Confirm Method
Close = safer
Wick = aggressive (scalping)
🧩 Unique Features (Compared to Other Indicators)
✔ Advanced gap-proof pivot engine
✔ Proper historical vs. present structure mode
✔ ATR-filtered internal pivots
✔ Smart confluence filter (detect candle context)
✔ Chart remains clean & minimal
✔ Works on all timeframes including 1-second
✔ No repaint structure
✔ Optimised for high-volatility assets like XAUUSD
🔚 Final Notes
This indicator was engineered to give traders a complete structure toolkit with professional-grade accuracy normally found only in premium paid tools.
With:
Clean BOS/CHoCH
Perfect swing tracking
Full multi-TF dashboard
Smart liquidity detection
Strong/weak level mapping
You can analyse any market with clarity and confidence.
Tìm kiếm tập lệnh với "high low"
Fractals by KaraTradeFractals by KaraTrade
OVERVIEW
This indicator identifies fractal patterns on the chart, which are key reversal points in price action. Fractals help traders identify potential support and resistance levels, as well as trend reversal zones.
WHAT IS A FRACTAL?
A fractal is a pattern where a central candle's high or low is surrounded by lower highs or higher lows on both sides. Fractals indicate where the market has made a local extreme and potentially reversed direction.
FEATURES
5-Candle Fractals (Dark Gray X marks)
Stronger signals with strict pattern validation
Requires a clear sequence where each candle progressively moves toward the center and then away
Bearish fractal: high < high < high > high > high
Bullish fractal: low > low > low < low < low
The central candle must be the highest high (bearish) or lowest low (bullish)
Displayed with offset=-2 on the central candle
3-Candle Fractals (Light Gray Triangles)
Weaker signals for more frequent patterns
Simpler pattern: central candle must be higher or lower than both neighbors
Bearish fractal: high < high > high
Bullish fractal: low > low < low
Displayed with offset=-1 on the central candle
SETTINGS
Show 5-Candle Fractals: Toggle 5-candle fractal display
Show 3-Candle Fractals: Toggle 3-candle fractal display
HOW TO USE
Bearish Fractals (top): Potential resistance levels or sell zones
Bullish Fractals (bottom): Potential support levels or buy zones
Use in combination with other indicators for confirmation
5-candle fractals are more reliable but less frequent
3-candle fractals provide more signals but require additional confirmation
TECHNICAL DETAILS
Uses strict sequential logic (no equal values allowed)
Based on high/low prices (including wicks/shadows)
Displays with a delay for pattern confirmation
Compatible with all timeframes
Created by KaraTrade
BORSA 321 - Care PackageOverview
Care Package is a complete higher-timeframe and intraday context tool designed to map out every important environmental factor on your chart: sessions, opening levels, gaps, market structure, order blocks, fair value gaps, volume imbalance and more.
It automatically plots:
Sessions / killzones (Asia, London, New York AM/Lunch/PM)
Key opening levels (00:00, 08:30, 09:30, 13:30)
Previous day AM/PM high–low ranges
New Day and New Week Opening Gaps (NDOG / NWOG)
RTH gap and RTH zone levels
Multi-timeframe Fair Value Gaps (up to 4)
Fractals and Order Blocks (with optional FVG confirmation)
Market structure (HH/HL/LL/LH, CHoCH, BOS)
Volume Imbalance zones with mitigation logic
All session logic runs on IANA time zones (like America/New_York), giving accurate sessions and market opens regardless of DST or broker feed.
Care Package serves as the full “context layer” for intraday execution charts.
What It Shows
1. Sessions / Killzones
The indicator automatically highlights:
Asia Session
London Session
New York AM
New York Lunch
New York PM
Each session displays:
A high–low range box
Labels for session high and session low
A midline showing the mean price
Optional forward extensions of session levels to the current bar
This cleanly outlines intraday phases for ICT/SMC execution.
2. Opening Price Levels
Key market open levels tracked:
00:00
08:30
09:30
13:30
For each open, the script draws:
A horizontal line at the opening price
A label showing time and price
An optional vertical line marking the opening bar
These opens often act as liquidity or reversal areas.
3. Previous Day AM/PM Levels
The script splits the prior day into:
Previous Day AM (first half)
Previous Day PM (second half)
Both provide:
PD AM High, PD AM Low
PD PM High, PD PM Low
Forward-projected levels
Labels for easy identification
Useful for navigating intraday targets and reaction zones.
4. Last N Days High/Low
Tracks a rolling daily range:
Each day’s High and Low
Labels containing the date
Forward extension into today’s price action
This shows where price sits relative to recent daily extremes.
5. New Day & New Week Opening Gaps (NDOG / NWOG)
The script automatically identifies:
NDOG (New Day Open Gap)
NWOG (New Week Open Gap)
Each gap includes:
A shaded zone between the two opens
Labels showing the gap type and date/week
Forward extension (optional)
Limiting the number of historical gaps (optional)
Critical for identifying unfilled imbalance zones across sessions and weeks.
6. RTH Gap & RTH Zone
You define RTH open/close times, and the indicator:
Detects RTH gaps
Draws a full zone based on direction
Plots subdivision lines (top, 75%, mid, 25%, bottom)
Extends the RTH Close reference line forward
Can extend old RTH zones automatically
Ideal for futures traders and equities.
7. Higher-Timeframe Fair Value Gaps (up to 4 TFs)
Supports up to four selectable FVG timeframes such as:
Chart timeframe
5m, 15m, 1H, 4H, 1D, 1W, 1M
Each FVG includes:
Top and bottom boundary
A midline (mean threshold)
Colored bullish or bearish fill
A label showing FVG + timeframe
Automatic cleanup when mitigated (close/wick based)
You get a clean and accurate HTF FVG map without clutter.
8. Fractals & Order Blocks
Fractals:
Standard or 5-bar fractals
Plotted as swing highs and lows
Order Blocks:
Bullish OB → down candle before up displacement
Bearish OB → up candle before down displacement
Optionally require OB to be near an FVG
Wick-based or body-based OB size
Forward-projected OB boxes
Auto-delete after mitigation
This keeps your OBs clean and execution-focused.
9. Market Structure (HH/HL/LL/LH, CHoCH, BOS)
The indicator automatically detects:
HH (Higher High)
HL (Higher Low)
LH (Lower High)
LL (Lower Low)
And also identifies:
CHoCH (Change of Character)
BOS (Break of Structure)
Each break includes:
A horizontal level at the break point
A color-coded label
Bullish (green) or bearish (red) styling
A complete market structure map is built automatically.
10. Volume Imbalances (VI)
Detects and displays:
Bullish VI (VI+)
Bearish VI (VI-)
Features:
Configurable colors
Custom label size
Max visible boxes
Extension until mitigation
Automatic mitigation detection (close or wick)
Highlight when price enters an active VI
Perfect for tracking aggressive buying/selling footprints.
11. Timezone & Date/Time Widget
Uses IANA timezones for:
Accurate session boundaries
Proper DST handling
Multi-market consistency
Also includes a small on-chart table showing:
Your timezone date/time
Exchange timezone date/time
Great for globally active traders.
12. Max Display Timeframe
To prevent clutter, the script disables visuals above a chosen timeframe.
If you exceed it:
A clean on-chart message appears
Tells you to lower your chart TF or adjust the Max Display TF
Keeps charts fast and clean
Key Inputs & Customization
Timezone (IANA format)
Max Display Timeframe
Session/Killzone toggles, colors, naming
Opening levels (00:00 / 08:30 / 09:30 / 13:30)
Previous Day AM/PM highs/lows
NDOG / NWOG gap settings
RTH gap settings
FVG batching (4 independent timeframes)
Fractal type
Order Block settings (range type, deletion, FVG filter)
Market structure settings
Volume Imbalance settings
Date/time widget settings
Everything is modular — turn features on/off individually.
How It Helps Traders
For Intraday Traders / Scalpers:
Session mapping for timing setups
Exact key opening prices
RTH gaps and internals
Precise daily AM/PM high–low context
HTF FVGs, OBs, VI zones for higher-timeframe bias
Real-time CHoCH/BOS for entry timing
For Swing Traders:
Daily/weekly context plotted automatically
NDOG, NWOG, RTH gap awareness
Macro structure levels
HTF FVGs and OBs for HTF targets
Scout Regiment - OBV# Scout Regiment - OBV Indicator
## English Documentation
### Overview
Scout Regiment - OBV (On-Balance Volume) is an advanced momentum indicator that combines volume and price movement to identify the strength of buying and selling pressure. This indicator features an oscillator-based approach with divergence detection to help traders spot potential trend reversals and confirm price movements.
### What is OBV?
On-Balance Volume (OBV) is a cumulative volume indicator that adds volume on up days and subtracts volume on down days:
- **Rising OBV**: Accumulation (buying pressure)
- **Falling OBV**: Distribution (selling pressure)
- **OBV Oscillator**: The difference between OBV and its smoothed moving average, making divergences easier to spot
### Key Features
#### 1. **OBV Oscillator Display**
Instead of displaying raw OBV values, this indicator shows the oscillator (difference between OBV and its smoothed line):
**Benefits:**
- Easier to identify divergences
- Clearer trend changes
- More sensitive to momentum shifts
- Zero line as reference point
**Visual Elements:**
- **Step Line**: Main OBV oscillator line
- Green: Positive oscillator (accumulation)
- Red: Negative oscillator (distribution)
- **Histogram**: Visual representation of oscillator strength
- Green bars: Above zero line
- Red bars: Below zero line
- **Zero Line**: White dotted horizontal line as reference
#### 2. **Smoothing Options**
Choose from multiple moving average types to smooth the OBV:
- **None**: Raw OBV (most sensitive)
- **SMA**: Simple Moving Average (equal weight)
- **EMA**: Exponential Moving Average (recent price emphasis) - Default
- **SMMA (RMA)**: Smoothed Moving Average (very smooth)
- **WMA**: Weighted Moving Average (linear weight)
- **VWMA**: Volume Weighted Moving Average (volume emphasis)
**Default Settings:**
- Type: EMA
- Length: 21 periods
- Best for: Most market conditions
#### 3. **Multi-Timeframe Analysis**
- Calculate OBV on any timeframe
- View higher timeframe momentum on lower timeframe charts
- Align trades with larger timeframe volume trends
- Empty field = Current chart timeframe
#### 4. **Visual Enhancements**
**Background Color**
- Light green: Positive oscillator (bullish volume pressure)
- Light red: Negative oscillator (bearish volume pressure)
- Optional display for cleaner charts
**Crossover Labels**
- "突破" (Breakout): When oscillator crosses above zero
- "跌破" (Breakdown): When oscillator crosses below zero
- Indicates potential trend changes
- Can be toggled on/off
#### 5. **Comprehensive Divergence Detection**
The indicator automatically detects four types of divergences:
**Regular Bullish Divergence (Yellow)**
- **Price**: Makes lower lows
- **OBV**: Makes higher lows
- **Signal**: Potential upward reversal
- **Label**: "看涨" (Bullish)
- **Use**: Enter long positions
**Regular Bearish Divergence (Blue)**
- **Price**: Makes higher highs
- **OBV**: Makes lower highs
- **Signal**: Potential downward reversal
- **Label**: "看跌" (Bearish)
- **Use**: Enter short positions or exit longs
**Hidden Bullish Divergence (Light Yellow)**
- **Price**: Makes higher lows
- **OBV**: Makes lower lows
- **Signal**: Trend continuation (uptrend)
- **Label**: "隐藏看涨" (Hidden Bullish)
- **Use**: Add to long positions
**Hidden Bearish Divergence (Light Blue)**
- **Price**: Makes lower highs
- **OBV**: Makes higher highs
- **Signal**: Trend continuation (downtrend)
- **Label**: "隐藏看跌" (Hidden Bearish)
- **Use**: Add to short positions
#### 6. **Customizable Divergence Detection**
**Pivot Lookback Settings:**
- **Left Lookback**: Bars to the left of pivot (default: 5)
- **Right Lookback**: Bars to the right of pivot (default: 5)
- Determines how "extreme" a point must be to qualify as a pivot
**Range Settings:**
- **Maximum Range**: Maximum bars between pivots (default: 60)
- **Minimum Range**: Minimum bars between pivots (default: 5)
- Filters out too-close or too-distant divergences
**Display Options:**
- Toggle regular divergences on/off
- Toggle hidden divergences on/off
- Toggle divergence labels on/off
- Show only the divergences you need
### Configuration Settings
#### Smoothing Settings
- **Smoothing Type**: Choose MA type (None/SMA/EMA/SMMA/WMA/VWMA)
- **Smoothing Length**: Number of periods for smoothing (default: 21)
#### Calculation Settings
- **Timeframe**: Select calculation timeframe (empty = current chart)
#### Display Settings
- **Show OBV Line**: Toggle step line display
- **Show OBV Histogram**: Toggle histogram display
- **Show Background Color**: Toggle background coloring
- **Show Crossover Labels**: Toggle breakout/breakdown labels
#### Divergence Settings
- **Pivot Right Lookback**: Right bars for pivot detection (default: 5)
- **Pivot Left Lookback**: Left bars for pivot detection (default: 5)
- **Range Maximum**: Max bars between divergences (default: 60)
- **Range Minimum**: Min bars between divergences (default: 5)
- **Show Regular Divergences**: Enable/disable regular divergences
- **Show Regular Labels**: Enable/disable regular divergence labels
- **Show Hidden Divergences**: Enable/disable hidden divergences
- **Show Hidden Labels**: Enable/disable hidden divergence labels
### How to Use
#### For Trend Confirmation
1. **Identify Trend with Price**
- Uptrend: Higher highs and higher lows
- Downtrend: Lower highs and lower lows
2. **Confirm with OBV Oscillator**
- Strong uptrend: OBV oscillator staying positive
- Strong downtrend: OBV oscillator staying negative
- Weak trend: OBV oscillator frequently crossing zero
3. **Volume Confirmation**
- Trend with increasing OBV = Strong trend
- Trend with decreasing OBV = Weak trend (watch for reversal)
#### For Divergence Trading
1. **Enable Divergence Detection**
- Start with regular divergences only
- Add hidden divergences for trend continuation
2. **Wait for Divergence Signal**
- Yellow label = Potential bullish reversal
- Blue label = Potential bearish reversal
3. **Confirm with Price Action**
- Wait for support/resistance break
- Look for candlestick confirmation
- Check higher timeframe alignment
4. **Enter Trade**
- Enter after confirmation
- Set stop loss beyond recent swing
- Target based on previous swing or support/resistance
#### For Breakout Trading
1. **Enable Crossover Labels**
- Identify when oscillator crosses zero line
2. **Confirm Volume Strength**
- Strong breakouts have large oscillator moves
- Weak breakouts barely cross zero
3. **Trade Direction**
- "突破" label = Enter long
- "跌破" label = Enter short
4. **Manage Position**
- Exit when oscillator crosses back
- Use price structure for stops
#### For Multi-Timeframe Analysis
1. **Set Higher Timeframe**
- Example: On 15min chart, set timeframe to 1H or 4H
2. **Identify Higher Timeframe Trend**
- Positive oscillator = Uptrend bias
- Negative oscillator = Downtrend bias
3. **Trade with the Trend**
- Only take long signals in uptrend
- Only take short signals in downtrend
4. **Time Entries**
- Use current timeframe for precise entry
- Confirm with higher timeframe direction
### Trading Strategies
#### Strategy 1: Regular Divergence Reversal
**Setup:**
1. Price in strong trend (up or down)
2. Regular divergence appears
3. Price reaches support/resistance level
**Entry:**
- Bullish: After "看涨" label, when price breaks above recent high
- Bearish: After "看跌" label, when price breaks below recent low
**Stop Loss:**
- Bullish: Below divergence low
- Bearish: Above divergence high
**Exit:**
- Take profit at next major support/resistance
- Or when opposite divergence appears
**Best For:** Swing trading, reversal trading
#### Strategy 2: Hidden Divergence Continuation
**Setup:**
1. Clear trend established
2. Price pulls back (retracement)
3. Hidden divergence appears
**Entry:**
- Bullish: After "隐藏看涨" label, when price resumes uptrend
- Bearish: After "隐藏看跌" label, when price resumes downtrend
**Stop Loss:**
- Behind the pullback swing point
**Exit:**
- Trail stop as trend continues
- Exit on regular divergence (reversal signal)
**Best For:** Trend following, adding to positions
#### Strategy 3: Zero Line Crossover
**Setup:**
1. Enable crossover labels
2. Oscillator crosses zero line
3. Confirm with price structure break
**Entry:**
- "突破" label = Buy signal
- "跌破" label = Sell signal
**Stop Loss:**
- Below/above recent swing
**Exit:**
- When oscillator crosses back over zero
- Or at predetermined target
**Best For:** Momentum trading, quick trades
#### Strategy 4: Multi-Timeframe Confluence
**Setup:**
1. Set indicator to higher timeframe (e.g., 4H on 1H chart)
2. Wait for higher TF oscillator to be positive (uptrend) or negative (downtrend)
3. Look for entries on current timeframe aligned with higher TF
**Entry:**
- Long: When both timeframes show positive oscillator or bullish divergence
- Short: When both timeframes show negative oscillator or bearish divergence
**Stop Loss:**
- Based on current timeframe structure
**Exit:**
- When higher timeframe oscillator turns negative (for longs) or positive (for shorts)
**Best For:** Swing trading, high-probability setups
### Best Practices
#### Volume Analysis
1. **Strong Moves Need Volume**
- Price increase + Rising OBV = Healthy uptrend
- Price increase + Falling OBV = Weak uptrend (warning)
2. **Watch for Confirmation**
- New highs with new OBV highs = Confirmed
- New highs without new OBV highs = Potential divergence
3. **Consider Context**
- Low volume periods (Asian session, holidays) = Less reliable
- High volume periods (News, London/NY overlap) = More reliable
#### Divergence Trading Tips
1. **Not All Divergences Work**
- Wait for price confirmation
- Stronger in oversold/overbought areas
- Better at support/resistance levels
2. **Multiple Divergences**
- Multiple divergences on same trend = Stronger signal
- Quick divergence failures = Ignore and wait for next
3. **Timeframe Matters**
- Higher timeframe divergences = More reliable
- Lower timeframe divergences = More frequent, less reliable
#### Smoothing Selection
1. **No Smoothing (None)**
- Most sensitive, more signals
- More noise, more false signals
- Best for: Scalping, very active trading
2. **EMA (Default)**
- Balanced approach
- Good for most strategies
- Best for: Swing trading, day trading
3. **SMMA (RMA)**
- Very smooth, fewer signals
- Less responsive to sudden changes
- Best for: Position trading, longer timeframes
### Indicator Combinations
**With Moving Averages:**
- Use EMAs for trend direction
- OBV for volume confirmation
- Enter when both align
**With RSI:**
- RSI for overbought/oversold
- OBV for volume confirmation
- Divergences on both = Stronger signal
**With Price Action:**
- Support/resistance for levels
- OBV for strength confirmation
- Breakouts with positive OBV = More likely to succeed
**With Bias Indicator:**
- Bias for price deviation
- OBV for volume confirmation
- Both showing divergence = High probability reversal
### Common Patterns
1. **Accumulation**: OBV rising while price consolidates (breakout likely)
2. **Distribution**: OBV falling while price consolidates (breakdown likely)
3. **Confirmation**: OBV and price both making new highs/lows (trend strong)
4. **Divergence**: OBV and price moving opposite directions (reversal warning)
5. **False Breakout**: Price breaks but OBV doesn't confirm (likely to fail)
### Performance Tips
- Disable unused display features for faster loading
- Start with regular divergences only, add hidden later
- Use histogram for quick visual reference
- Enable crossover labels for clear entry signals
- Test different smoothing lengths for your market
### Alert Conditions
The indicator includes alerts for:
- Regular bullish divergence detected
- Regular bearish divergence detected
- Hidden bullish divergence detected
- Hidden bearish divergence detected
**How to Set Alerts:**
1. Click on the indicator name
2. Select "Add Alert"
3. Choose condition
4. Configure notification method
---
## 中文说明文档
### 概述
Scout Regiment - OBV（能量潮）是一个高级动量指标，结合成交量和价格变动来识别买卖压力的强度。该指标采用振荡器方法并具有背离检测功能，帮助交易者发现潜在的趋势反转并确认价格走势。
### 什么是OBV？
能量潮（OBV）是一个累积成交量指标，在上涨日累加成交量，在下跌日减去成交量：
- **上升的OBV**：积累（买入压力）
- **下降的OBV**：派发（卖出压力）
- **OBV振荡器**：OBV与其平滑移动平均线之间的差值，使背离更容易识别
### 核心功能
#### 1. **OBV振荡器显示**
该指标不显示原始OBV值，而是显示振荡器（OBV与其平滑线之间的差值）：
**优势：**
- 更容易识别背离
- 趋势变化更清晰
- 对动量变化更敏感
- 零线作为参考点
**视觉元素：**
- **阶梯线**：主OBV振荡器线
- 绿色：正振荡器（积累）
- 红色：负振荡器（派发）
- **柱状图**：振荡器强度的可视化表示
- 绿色柱：零线以上
- 红色柱：零线以下
- **零线**：白色虚线作为参考
#### 2. **平滑选项**
选择多种移动平均类型来平滑OBV：
- **None**：原始OBV（最敏感）
- **SMA**：简单移动平均（等权重）
- **EMA**：指数移动平均（强调近期价格）- 默认
- **SMMA (RMA)**：平滑移动平均（非常平滑）
- **WMA**：加权移动平均（线性权重）
- **VWMA**：成交量加权移动平均（强调成交量）
**默认设置：**
- 类型：EMA
- 长度：21周期
- 适合：大多数市场状况
#### 3. **多时间框架分析**
- 在任何时间框架上计算OBV
- 在低时间框架图表上查看高时间框架动量
- 使交易与更大时间框架的成交量趋势保持一致
- 空字段 = 当前图表时间框架
#### 4. **视觉增强**
**背景颜色**
- 浅绿色：正振荡器（看涨成交量压力）
- 浅红色：负振荡器（看跌成交量压力）
- 可选显示，图表更清爽
**穿越标签**
- "突破"：振荡器向上穿越零线
- "跌破"：振荡器向下穿越零线
- 指示潜在趋势变化
- 可开关
#### 5. **全面的背离检测**
指标自动检测四种类型的背离：
**常规看涨背离（黄色）**
- **价格**：创新低
- **OBV**：创更高的低点
- **信号**：潜在向上反转
- **标签**："看涨"
- **用途**：进入多头仓位
**常规看跌背离（蓝色）**
- **价格**：创新高
- **OBV**：创更低的高点
- **信号**：潜在向下反转
- **标签**："看跌"
- **用途**：进入空头仓位或退出多头
**隐藏看涨背离（浅黄色）**
- **价格**：创更高的低点
- **OBV**：创更低的低点
- **信号**：趋势延续（上升趋势）
- **标签**："隐藏看涨"
- **用途**：加仓多头
**隐藏看跌背离（浅蓝色）**
- **价格**：创更低的高点
- **OBV**：创更高的高点
- **信号**：趋势延续（下降趋势）
- **标签**："隐藏看跌"
- **用途**：加仓空头
#### 6. **可自定义的背离检测**
**枢轴回溯设置：**
- **左侧回溯**：枢轴点左侧K线数（默认：5）
- **右侧回溯**：枢轴点右侧K线数（默认：5）
- 决定一个点要多"极端"才能成为枢轴点
**范围设置：**
- **最大范围**：枢轴点之间最大K线数（默认：60）
- **最小范围**：枢轴点之间最小K线数（默认：5）
- 过滤太近或太远的背离
**显示选项：**
- 开关常规背离
- 开关隐藏背离
- 开关背离标签
- 只显示需要的背离
### 配置设置
#### 平滑设置
- **平滑类型**：选择MA类型（None/SMA/EMA/SMMA/WMA/VWMA）
- **平滑长度**：平滑周期数（默认：21）
#### 计算设置
- **时间周期**：选择计算时间框架（空 = 当前图表）
#### 显示设置
- **显示OBV点线**：切换阶梯线显示
- **显示OBV柱状图**：切换柱状图显示
- **显示背景颜色**：切换背景着色
- **显示突破标签**：切换突破/跌破标签
#### 背离设置
- **枢轴右侧回溯**：枢轴检测右侧K线数（默认：5）
- **枢轴左侧回溯**：枢轴检测左侧K线数（默认：5）
- **回看范围最大值**：背离之间最大K线数（默认：60）
- **回看范围最小值**：背离之间最小K线数（默认：5）
- **显示常规背离**：启用/禁用常规背离
- **显示常规背离标签**：启用/禁用常规背离标签
- **显示隐藏背离**：启用/禁用隐藏背离
- **显示隐藏背离标签**：启用/禁用隐藏背离标签
### 使用方法
#### 趋势确认
1. **用价格识别趋势**
- 上升趋势：更高的高点和更高的低点
- 下降趋势：更低的高点和更低的低点
2. **用OBV振荡器确认**
- 强劲上升趋势：OBV振荡器保持正值
- 强劲下降趋势：OBV振荡器保持负值
- 弱势趋势：OBV振荡器频繁穿越零线
3. **成交量确认**
- 趋势伴随上升的OBV = 强趋势
- 趋势伴随下降的OBV = 弱趋势（注意反转）
#### 背离交易
1. **启用背离检测**
- 先从常规背离开始
- 添加隐藏背离用于趋势延续
2. **等待背离信号**
- 黄色标签 = 潜在看涨反转
- 蓝色标签 = 潜在看跌反转
3. **用价格行为确认**
- 等待支撑/阻力突破
- 寻找K线确认
- 检查更高时间框架对齐
4. **进入交易**
- 确认后进入
- 在近期波动之外设置止损
- 基于前一波动或支撑/阻力设定目标
#### 突破交易
1. **启用穿越标签**
- 识别振荡器何时穿越零线
2. **确认成交量强度**
- 强突破有大振荡器移动
- 弱突破勉强穿越零线
3. **交易方向**
- "突破"标签 = 进入多头
- "跌破"标签 = 进入空头
4. **管理仓位**
- 振荡器反向穿越时退出
- 使用价格结构设置止损
#### 多时间框架分析
1. **设置更高时间框架**
- 例如：在15分钟图上，设置时间框架为1H或4H
2. **识别更高时间框架趋势**
- 正振荡器 = 上升趋势偏向
- 负振荡器 = 下降趋势偏向
3. **顺趋势交易**
- 仅在上升趋势中接受多头信号
- 仅在下降趋势中接受空头信号
4. **把握入场时机**
- 使用当前时间框架进行精确进入
- 用更高时间框架方向确认
### 交易策略
#### 策略1：常规背离反转
**设置：**
1. 价格处于强趋势（上涨或下跌）
2. 出现常规背离
3. 价格到达支撑/阻力水平
**入场：**
- 看涨：在"看涨"标签后，价格突破近期高点时
- 看跌：在"看跌"标签后，价格跌破近期低点时
**止损：**
- 看涨：背离低点之下
- 看跌：背离高点之上
**退出：**
- 在下一个主要支撑/阻力获利
- 或出现相反背离时
**适合：**波段交易、反转交易
#### 策略2：隐藏背离延续
**设置：**
1. 建立明确趋势
2. 价格回调（回撤）
3. 出现隐藏背离
**入场：**
- 看涨：在"隐藏看涨"标签后，价格恢复上升趋势时
- 看跌：在"隐藏看跌"标签后，价格恢复下降趋势时
**止损：**
- 在回调波动点之后
**退出：**
- 随着趋势延续移动止损
- 出现常规背离（反转信号）时退出
**适合：**趋势跟随、加仓
#### 策略3：零线穿越
**设置：**
1. 启用穿越标签
2. 振荡器穿越零线
3. 用价格结构突破确认
**入场：**
- "突破"标签 = 买入信号
- "跌破"标签 = 卖出信号
**止损：**
- 近期波动之下/之上
**退出：**
- 振荡器反向穿越零线时
- 或在预定目标
**适合：**动量交易、快速交易
#### 策略4：多时间框架汇合
**设置：**
1. 设置指标到更高时间框架（例如，在1H图上设置4H）
2. 等待更高TF振荡器为正（上升趋势）或负（下降趋势）
3. 在当前时间框架上寻找与更高TF一致的入场机会
**入场：**
- 多头：两个时间框架都显示正振荡器或看涨背离时
- 空头：两个时间框架都显示负振荡器或看跌背离时
**止损：**
- 基于当前时间框架结构
**退出：**
- 更高时间框架振荡器变为负（多头）或正（空头）时
**适合：**波段交易、高概率设置
### 最佳实践
#### 成交量分析
1. **强势波动需要成交量**
- 价格上涨 + 上升的OBV = 健康上升趋势
- 价格上涨 + 下降的OBV = 弱上升趋势（警告）
2. **注意确认**
- 新高伴随新OBV高点 = 已确认
- 新高没有新OBV高点 = 潜在背离
3. **考虑背景**
- 低成交量期（亚洲时段、假期）= 可靠性较低
- 高成交量期（新闻、伦敦/纽约重叠）= 更可靠
#### 背离交易技巧
1. **不是所有背离都有效**
- 等待价格确认
- 在超卖/超买区域更强
- 在支撑/阻力水平更好
2. **多重背离**
- 同一趋势上多个背离 = 更强信号
- 背离快速失败 = 忽略并等待下一个
3. **时间框架重要**
- 更高时间框架背离 = 更可靠
- 更低时间框架背离 = 更频繁，可靠性较低
#### 平滑选择
1. **无平滑（None）**
- 最敏感，更多信号
- 更多噪音，更多假信号
- 适合：剥头皮、非常活跃的交易
2. **EMA（默认）**
- 平衡方法
- 适合大多数策略
- 适合：波段交易、日内交易
3. **SMMA (RMA)**
- 非常平滑，更少信号
- 对突然变化响应较慢
- 适合：仓位交易、更长时间框架
### 指标组合
**与移动平均线配合：**
- 使用EMA确定趋势方向
- OBV确认成交量
- 两者一致时进入
**与RSI配合：**
- RSI用于超买超卖
- OBV用于成交量确认
- 两者都背离 = 更强信号
**与价格行为配合：**
- 支撑/阻力确定水平
- OBV确认强度
- 正OBV的突破 = 更可能成功
**与Bias指标配合：**
- Bias用于价格偏离
- OBV用于成交量确认
- 两者都显示背离 = 高概率反转
### 常见形态
1. **积累**：OBV上升而价格盘整（突破可能）
2. **派发**：OBV下降而价格盘整（跌破可能）
3. **确认**：OBV和价格都创新高/新低（趋势强劲）
4. **背离**：OBV和价格反向移动（反转警告）
5. **假突破**：价格突破但OBV不确认（可能失败）
### 性能提示
- 禁用未使用的显示功能以加快加载
- 先从常规背离开始，稍后添加隐藏背离
- 使用柱状图快速视觉参考
- 启用穿越标签以获得清晰的入场信号
- 为您的市场测试不同的平滑长度
### 警报条件
指标包含以下警报：
- 检测到常规看涨背离
- 检测到常规看跌背离
- 检测到隐藏看涨背离
- 检测到隐藏看跌背离
**如何设置警报：**
1. 点击指标名称
2. 选择"添加警报"
3. 选择条件
4. 配置通知方法
---
## Technical Support
For questions or issues, please refer to the TradingView community or contact the indicator creator.
## 技术支持
如有问题，请参考TradingView社区或联系指标创建者。
Curvature Tensor Pivots - HIVECurvature Tensor Pivots - HIVE
I. CORE CONCEPT & ORIGINALITY
Curvature Tensor Pivots - HIVE is an advanced, multi-dimensional pivot detection system that combines differential geometry, reinforcement learning, and statistical physics to identify high-probability reversal zones before they fully form. Unlike traditional pivot indicators that rely on simple price comparisons or lagging moving averages, this system models price action as a smooth curve in geometric space and calculates its mathematical curvature (how sharply the price trajectory is "bending") to detect pivots with scientific precision.
What Makes This Original:
Differential Geometry Engine: The script calculates first and second derivatives of price using Kalman-filtered trajectory analysis, then computes true mathematical curvature (κ) using the classical formula: κ = |y''| / (1 + y'²)^(3/2). This approach treats price as a physical phenomenon rather than discrete data points.
Ghost Vertex Prediction: A proprietary algorithm that detects pivots 1-3 bars BEFORE they complete by identifying when velocity approaches zero while acceleration is high—this is the mathematical definition of a turning point.
Multi-Armed Bandit AI: Four distinct pivot detection strategies (Fast, Balanced, Strict, Tensor) run simultaneously in shadow portfolios. A Thompson Sampling reinforcement learning algorithm continuously evaluates which strategy performs best in current market conditions and automatically selects it.
Hive Consensus System: When 3 or 4 of the parallel strategies agree on the same price zone, the system generates "confluence zones"—areas of institutional-grade probability.
Dynamic Volatility Scaling (DVS): All parameters auto-adjust based on current ATR relative to historical average, making the indicator adaptive across all timeframes and instruments without manual re-optimization.
II. HOW THE COMPONENTS WORK TOGETHER
This is NOT a simple mashup —each subsystem feeds data into the others in a closed-loop learning architecture:
The Processing Pipeline:
Step 1: Geometric Foundation
Raw price is normalized against a 50-period SMA to create a trajectory baseline
A Zero-Lag EMA smooths the trajectory while preserving edge response
Kalman filter removes noise while maintaining signal integrity
Step 2: Calculus Layer
First derivative (y') measures velocity of price movement
Second derivative (y'') measures acceleration (rate of velocity change)
Curvature (κ) is calculated from these derivatives, representing how sharply price is turning
Step 3: Statistical Validation
Z-Score measures how many standard deviations current price deviates from the Kalman-filtered "true price"
Only pivots with Z-Score > threshold (default 1.2) are considered statistically significant
This filters out noise and micro-fluctuations
Step 4: Tensor Construction
Curvature is combined with volatility (ATR-based) and momentum (ROC-based) to create a multidimensional "tensor score"
This tensor represents the geometric stress in the price field
High tensor magnitude = high probability of structural failure (reversal)
Step 5: AI Decision Layer
All 4 bandit strategies evaluate current conditions using different sensitivity thresholds
Each strategy maintains a virtual portfolio that trades its signals in real-time
Thompson Sampling algorithm updates Bayesian priors (alpha/beta distributions) based on each strategy's Sharpe ratio, win rate, and drawdown
The highest-performing strategy's signals are displayed to the user
Step 6: Confluence Aggregation
When multiple strategies agree on the same price zone, that zone is highlighted as a confluence area. These represent "hive mind" consensus—the strongest setups
Why This Integration Matters:
Traditional indicators either detect pivots too late (lagging) or generate too many false signals (noisy). By requiring geometric confirmation (curvature), statistical significance (Z-Score), multi-strategy agreement (hive voting), and performance validation (RL feedback) , this system achieves institutional-grade precision. The reinforcement learning layer ensures the system adapts as market regimes change, rather than degrading over time like static algorithms.
III. DETAILED METHODOLOGY
A. Curvature Calculation (Differential Geometry)
The system models price as a parametric curve where:
x-axis = time (bar index)
y-axis = normalized price
The curvature at any point represents how quickly the direction of the tangent line is changing. High curvature = sharp turn = potential pivot.
Implementation:
Lookback window (default 8 bars) defines the local curve segment
Smoothing (default 5 bars) applies adaptive EMA to reduce tick noise
Curvature is normalized to 0-1 scale using local statistical bounds (mean ± 2 standard deviations)
B. Ghost Vertex (Predictive Pivot Detection)
Classical pivot detection waits for price to form a swing high/low and confirm. Ghost Vertex uses calculus to predict the turning point:
Conditions for Ghost Pivot:
Velocity (y') ≈ 0 (price rate of change approaching zero)
Acceleration (y'') ≠ 0 (change is decelerating/accelerating)
Z-Score > threshold (statistically abnormal position)
This allows detection 1-3 bars before the actual high/low prints, providing an early entry edge.
C. Multi-Armed Bandit Reinforcement Learning
The system runs 4 parallel "bandits" (agents), each with different detection sensitivity:
Bandit Strategies:
Fast: Low curvature threshold (0.1), low Z-Score requirement (1.0) → High frequency, more signals
Balanced: Standard thresholds (0.2 curvature, 1.5 Z-Score) → Moderate frequency
Strict: High thresholds (0.4 curvature, 2.0 Z-Score) → Low frequency, high conviction
Tensor: Requires tensor magnitude > 0.5 → Geometric-weighted detection
Learning Algorithm (Thompson Sampling):
Each bandit maintains a Beta distribution with parameters (α, β)
After each trade outcome, α is incremented for wins, β for losses
Selection probability is proportional to sampled success rate from the distribution
This naturally balances exploration (trying underperformed strategies) vs exploitation (using best strategy)
Performance Metrics Tracked:
Equity curve for each shadow portfolio
Win rate percentage
Sharpe ratio (risk-adjusted returns)
Maximum drawdown
Total trades executed
The system displays all metrics in real-time on the dashboard so users can see which strategy is currently "winning."
D. Dynamic Volatility Scaling (DVS)
Markets cycle between high volatility (trending, news-driven) and low volatility (ranging, quiet). Static parameters fail when regime changes.
DVS Solution:
Measures current ATR(30) / close as normalized volatility
Compares to 100-bar SMA of normalized volatility
Ratio > 1 = high volatility → lengthen lookbacks, raise thresholds (prevent noise)
Ratio < 1 = low volatility → shorten lookbacks, lower thresholds (maintain sensitivity)
This single feature is why the indicator works on 1-minute crypto charts AND daily stock charts without parameter changes.
E. Confluence Zone Detection
The script divides the recent price range (200 bars) into 200 discrete zones. On each bar:
Each of the 4 bandits votes on potential pivot zones
Votes accumulate in a histogram array
Zones with ≥ 3 votes (75% agreement) are drawn as colored boxes
Red boxes = resistance confluence, Green boxes = support confluence
These zones act as magnet levels where price often returns multiple times.
IV. HOW TO USE THIS INDICATOR
For Scalpers (1m - 5m timeframes):
Settings: Use "Aggressive" or "Adaptive" pivot mode, Curvature Window 5-8, Min Pivot Strength 50-60
Entry Signal: Triangle marker appears (🔺 for longs, 🔻 for shorts)
Confirmation: Check that Hive Sentiment on dashboard agrees (3+ votes)
Stop Loss: Use the dotted volatility-adjusted target line in reverse (if pivot is at 100 with target at 110, stop is ~95)
Take Profit: Use the projected target line (default 3× ATR)
Advanced: Wait for confluence zone formation, then enter on retest of the zone
For Day Traders (15m - 1H timeframes):
Settings: Use "Adaptive" mode (default settings work well)
Entry Signal: Pivot marker + Hive Consensus alert
Confirmation: Check dashboard—ensure selected bandit has Sharpe > 1.5 and Win% > 55%
Filter: Only take pivots with Pivot Strength > 70 (shown in dashboard)
Risk Management: Monitor the Live Position Tracker—if your selected bandit is holding a position, consider that as market structure context
Exit: Either use target lines OR exit when opposite pivot appears
For Swing Traders (4H - Daily timeframes):
Settings: Use "Conservative" mode, Curvature Window 12-20, Min Bars Between Pivots 15-30
Focus on Confluence: Only trade when 4/4 bandits agree (unanimous hive consensus)
Entry: Set limit orders at confluence zones rather than market orders at pivot signals
Confirmation: Look for breakout diamonds (◆) after pivot—these signal momentum continuation
Risk Management: Use wider stops (base stop loss % = 3-5%)
Dashboard Interpretation:
Top Section (Real-Time Metrics):
κ (Curv): Current curvature. >0.6 = active pivot forming
Tensor: Geometric stress. Positive = bullish bias, Negative = bearish bias
Z-Score: Statistical deviation. >2.0 or <-2.0 = extreme outlier (strong signal)
Bandit Performance Table:
α/β: Bayesian parameters. Higher α = more wins in history
Win%: Self-explanatory. >60% is excellent
Sharpe: Risk-adjusted returns. >2.0 is institutional-grade
Status: Shows which strategy is currently selected
Live Position Tracker:
Shows if the selected bandit's shadow portfolio is currently holding a position
Displays entry price and real-time P&L
Use this as "what the AI would do" confirmation
Hive Sentiment:
Shows vote distribution across all 4 bandits
"BULLISH" with 3+ green votes = high-conviction long setup
"BEARISH" with 3+ red votes = high-conviction short setup
Alert Setup:
The script includes 6 alert conditions:
"AI High Pivot" = Selected bandit signals short
"AI Low Pivot" = Selected bandit signals long
"Hive Consensus BUY" = 3+ bandits agree on long
"Hive Consensus SELL" = 3+ bandits agree on short
"Breakout Up" = Resistance breakout (continuation long)
"Breakdown Down" = Support breakdown (continuation short)
Recommended Alert Strategy:
Set "Hive Consensus" alerts for high-conviction setups
Use "AI Pivot" alerts for active monitoring during your trading session
Use breakout alerts for momentum/trend-following entries
V. PARAMETER OPTIMIZATION GUIDE
Core Geometry Parameters:
Curvature Window (default 8):
Lower (3-5): Detects micro-structure, best for scalping volatile pairs (crypto, forex majors)
Higher (12-20): Detects macro-structure, best for swing trading stocks/indices
Rule of thumb: Set to ~0.5% of your typical trade duration in bars
Curvature Smoothing (default 5):
Increase if you see too many false pivots (noisy instrument)
Decrease if pivots lag (missing entries by 2-3 bars)
Inflection Threshold (default 0.20):
This is advanced. Lower = more inflection zones highlighted
Useful for identifying order blocks and liquidity voids
Most users can leave default
Pivot Detection Parameters:
Pivot Sensitivity Mode:
Aggressive: Use in low-volatility range-bound markets
Normal: General purpose
Adaptive: Recommended—auto-adjusts via DVS
Conservative: Use in choppy, whipsaw conditions or for swing trading
Min Bars Between Pivots (default 8):
THIS IS CRITICAL for visual clarity
If chart looks cluttered, increase to 12-15
If missing pivots, decrease to 5-6
Match to your timeframe: 1m charts use 3-5, Daily charts use 20+
Min Z-Score (default 1.2):
Statistical filter. Higher = fewer but stronger signals
During news events (NFP, FOMC), increase to 2.0+
In calm markets, 1.0 works well
Min Pivot Strength (default 60):
Composite quality score (0-100)
80+ = institutional-grade pivots only
50-70 = balanced
Below 50 = will show weak setups (not recommended)
RL & DVS Parameters:
Enable DVS (default ON):
Leave enabled unless you want to manually tune for a specific market condition
This is the "secret sauce" for cross-timeframe performance
DVS Sensitivity (default 1.0):
Increase to 1.5-2.0 for extremely volatile instruments (meme stocks, altcoins)
Decrease to 0.5-0.7 for stable instruments (utilities, bonds)
RL Algorithm (default Thompson Sampling):
Thompson Sampling: Best for non-stationary markets (recommended)
UCB1: Best for stable, mean-reverting markets
Epsilon-Greedy: For testing only
Contextual: Advanced—uses market regime as context
Risk Parameters:
Base Stop Loss % (default 2.0):
Set to 1.5-2× your instrument's average ATR as a percentage
Example: If SPY ATR = $3 and price = $450, ATR% = 0.67%, so use 1.5-2.0%
Base Take Profit % (default 4.0):
Aim for 2:1 reward/risk ratio minimum
For mean-reversion strategies, use 1.5-2.0%
For trend-following, use 3-5%
VI. UNDERSTANDING THE UNDERLYING CONCEPTS
Why Differential Geometry?
Traditional technical analysis treats price as discrete data points. Differential geometry models price as a continuous manifold —a smooth surface that can be analyzed using calculus. This allows us to ask: "At what rate is the trend changing?" rather than just "Is price going up or down?"
The curvature metric captures something fundamental: inflection points in market psychology . When buyers exhaust and sellers take over (or vice versa), the price trajectory must curve. By measuring this curvature mathematically, we detect these psychological shifts with precision.
Why Reinforcement Learning?
Markets are non-stationary —statistical properties change over time. A strategy that works in Q1 may fail in Q3. Traditional indicators have fixed parameters and degrade over time.
The multi-armed bandit framework solves this by:
Running multiple strategies in parallel (diversification)
Continuously measuring performance (feedback loop)
Automatically shifting capital to what's working (adaptation)
This is how professional hedge funds operate—they don't use one strategy, they use ensembles with dynamic allocation.
Why Kalman Filtering?
Raw price contains two components: signal (true movement) and noise (random fluctuations). Kalman filters are the gold standard in aerospace and robotics for extracting signal from noisy sensors.
By applying this to price data, we get a "clean" trajectory to measure curvature against. This prevents false pivots from bid-ask bounce or single-print anomalies.
Why Z-Score Validation?
Not all high-curvature points are tradeable. A sharp turn in a ranging market might just be noise. Z-Score ensures that pivots occur at statistically abnormal price levels —places where price has deviated significantly from its Kalman-filtered "fair value."
This filters out 70-80% of false signals while preserving true reversal points.
VII. COMMON USE CASES & STRATEGIES
Strategy 1: Confluence Zone Reversal Trading
Wait for confluence zone to form (red or green box)
Wait for price to approach zone
Enter when pivot marker appears WITHIN the confluence zone
Stop: Beyond the zone
Target: Opposite confluence zone or 3× ATR
Strategy 2: Hive Consensus Scalping
Set alert for "Hive Consensus BUY/SELL"
When alert fires, check dashboard—ensure 3-4 votes
Enter immediately (market order or 1-tick limit)
Stop: Tight, 1-1.5× ATR
Target: 2× ATR or opposite pivot signal
Strategy 3: Bandit-Following Swing Trading
On Daily timeframe, monitor which bandit has best Sharpe ratio over 30+ days
Take ONLY that bandit's signals (ignore others)
Enter on pivot, hold until opposite pivot or target line
Position size based on bandit's current win rate (higher win% = larger position)
Strategy 4: Breakout Confirmation
Identify key support/resistance level manually
Wait for pivot to form AT that level
If price breaks level and diamond breakout marker appears, enter in breakout direction
This combines support/resistance with geometric confirmation
Strategy 5: Inflection Zone Limit Orders
Enable "Show Inflection Zones"
Place limit buy orders at bottom of purple zones
Place limit sell orders at top of purple zones
These zones represent structural change points where price often pauses
VIII. WHAT THIS INDICATOR DOES NOT DO
To set proper expectations:
This is NOT:
A "holy grail" with 100% win rate
A strategy that works without risk management
A replacement for understanding market fundamentals
A signal copier (you must interpret context)
This DOES NOT:
Predict black swan events
Account for fundamental news (you must avoid trading during major news if not experienced)
Work well in extremely low liquidity conditions (penny stocks, microcap crypto)
Generate signals during consolidation (by design—prevents whipsaw)
Best Performance:
Liquid instruments (SPY, ES, NQ, EUR/USD, BTC/USD, etc.)
Clear trend or range conditions (struggles in choppy transition periods)
Timeframes 5m and above (1m can work but requires experience)
IX. PERFORMANCE EXPECTATIONS
Based on shadow portfolio backtesting across multiple instruments:
Conservative Mode:
Signal frequency: 2-5 per week (Daily charts)
Expected win rate: 60-70%
Average RRR: 2.5:1
Adaptive Mode:
Signal frequency: 5-15 per day (15m charts)
Expected win rate: 55-65%
Average RRR: 2:1
Aggressive Mode:
Signal frequency: 20-40 per day (5m charts)
Expected win rate: 50-60%
Average RRR: 1.5:1
Note: These are statistical expectations. Individual results depend on execution, risk management, and market conditions.
X. PRIVACY & INVITE-ONLY NATURE
This script is invite-only to:
Maintain signal quality (prevent market impact from mass adoption)
Provide dedicated support to users
Continuously improve the algorithm based on user feedback
Ensure users understand the complexity before deploying real capital
The script is closed-source to protect proprietary research in:
Ghost Vertex prediction mathematics
Tensor construction methodology
Bandit reward function design
DVS scaling algorithms
XI. FINAL RECOMMENDATIONS
Before Trading Live:
Paper trade for minimum 2 weeks to understand signal timing
Start with ONE timeframe and master it before adding others
Monitor the dashboard —if selected bandit Sharpe drops below 1.0, reduce size
Use confluence and hive consensus for highest-quality setups
Respect the Min Bars Between Pivots setting —this prevents overtrading
Risk Management Rules:
Never risk more than 1-2% of account per trade
If 3 consecutive losses occur, stop trading and review (possible regime change)
Use the shadow portfolio as a guide—if ALL bandits are losing, market is in transition
Combine with other analysis (order flow, volume profile) for best results
Continuous Learning:
The RL system improves over time, but only if you:
Keep the indicator running (it learns from bar data)
Don't constantly change parameters (confuses the learning)
Let it accumulate at least 50 samples before judging performance
Review the dashboard weekly to see which bandits are adapting
CONCLUSION
Curvature Tensor Pivots - HIVE represents a fusion of advanced mathematics, machine learning, and practical trading experience. It is designed for serious traders who want institutional-grade tools and understand that edge comes from superior methodology, not magic formulas.
The system's strength lies in its adaptive intelligence —it doesn't just detect pivots, it learns which detection method works best right now, in this market, under these conditions. The hive consensus mechanism provides confidence, the geometric foundation provides precision, and the reinforcement learning provides evolution.
Use it wisely, manage risk properly, and let the mathematics work for you.
Disclaimer: This indicator is a tool for analysis and does not constitute financial advice. Past performance of shadow portfolios does not guarantee future results. Trading involves substantial risk of loss. Always perform your own due diligence and never trade with capital you cannot afford to lose.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Liquidity Void Zone Detector [PhenLabs]📊 Liquidity Void Zone Detector
Version: PineScript™v6
📌 Description
The Liquidity Void Zone Detector is a sophisticated technical indicator designed to identify and visualize areas where price moved with abnormally low volume or rapid momentum, creating "voids" in market liquidity. These zones represent areas where insufficient trading activity occurred during price movement, often acting as magnets for future price action as the market seeks to fill these gaps.
Built on PineScript v6, this indicator employs a dual-detection methodology that analyzes both volume depletion patterns and price movement intensity relative to ATR. The revolutionary 3D visualization system uses three-layer polyline rendering with adaptive transparency and vertical offsets, creating genuine depth perception where low liquidity zones visually recede and high liquidity zones protrude forward. This makes critical market structure immediately apparent without cluttering your chart.
🚀 Points of Innovation
Dual detection algorithm combining volume threshold analysis and ATR-normalized price movement sensitivity for comprehensive void identification
Three-layer 3D visualization system with progressive transparency gradients (85%, 78%, 70%) and calculated vertical offsets for authentic depth perception
Intelligent state machine logic that tracks consecutive void bars and only renders zones meeting minimum qualification requirements
Dynamic strength scoring system (0-100 scale) that combines inverted volume ratios with movement intensity for accurate void characterization
Adaptive ATR-based spacing calculation that automatically adjusts 3D layering depth to match instrument volatility
Efficient memory management system supporting up to 100 simultaneous void visualizations with automatic array-based cleanup
🔧 Core Components
Volume Analysis Engine: Calculates rolling volume averages and compares current bar volume against dynamic thresholds to detect abnormally thin trading conditions
Price Movement Analyzer: Normalizes bar range against ATR to identify rapid price movements that indicate liquidity exhaustion regardless of instrument or timeframe
Void Tracking State Machine: Maintains persistent tracking of void start bars, price boundaries, consecutive bar counts, and cumulative strength across multiple bars
3D Polyline Renderer: Generates three-layer rectangular polylines with precise timestamp-to-bar index conversion and progressive offset calculations
Strength Calculation System: Combines volume component (inverted ratio capped at 100) with movement component (ATR intensity × 30) for comprehensive void scoring
🔥 Key Features
Automatic Void Detection: Continuously scans price action for low volume conditions or rapid movements, triggering void tracking when thresholds are exceeded
Real-Time Visualization: Creates 3D rectangular zones spanning from void initiation to termination, with color-coded depth indicating liquidity type
Adjustable Sensitivity: Configure volume threshold multiplier (0.1-2.0x), price movement sensitivity (0.5-5.0x), and minimum qualifying bars (1-10) for customized detection
Dual Color Coding: Separate visual treatment for low liquidity voids (receding red) and high liquidity zones (protruding green) based on 50-point strength threshold
Optional Compact Labels: Toggle LV (Low Volume) or HV (High Volume) circular labels at void centers for quick identification without visual clutter
Lookback Period Control: Adjust analysis window from 5 to 100 bars to match your trading timeframe and market volatility characteristics
Memory-Efficient Design: Automatically manages polyline and label arrays, deleting oldest elements when user-defined maximum is reached
Data Window Integration: Plots void detection binary, current strength score, and average volume for detailed analysis in TradingView's data window
🎨 Visualization
Three-Layer Depth System: Each void is rendered as three stacked polylines with progressive transparency (85%, 78%, 70%) and calculated vertical offsets creating authentic 3D appearance
Directional Depth Perception: Low liquidity zones recede with back layer most transparent; high liquidity zones protrude with front layer most transparent for instant visual differentiation
Adaptive Offset Spacing: Vertical separation between layers calculated as ATR(14) × 0.001, ensuring consistent 3D effect across different instruments and volatility regimes
Color Customization: Fully configurable base colors for both low liquidity zones (default: red with 80 transparency) and high liquidity zones (default: green with 80 transparency)
Minimal Chart Clutter: Closed polylines with matching line and fill colors create clean rectangular zones without unnecessary borders or visual noise
Background Highlight: Subtle yellow background (96% transparency) marks bars where void conditions are actively detected in real-time
Compact Labeling: Optional tiny circular labels with 60% transparent backgrounds positioned at void center points for quick reference
📖 Usage Guidelines
Detection Settings
Lookback Period: Default: 10 | Range: 5-100 | Number of bars analyzed for volume averaging and void detection. Lower values increase sensitivity to recent changes; higher values smooth detection across longer timeframes. Adjust based on your trading timeframe: short-term traders use 5-15, swing traders use 20-50, position traders use 50-100.
Volume Threshold: Default: 1.0 | Range: 0.1-2.0 (step 0.1) | Multiplier applied to average volume. Bars with volume below (average × threshold) trigger void conditions. Lower values detect only extreme volume depletion; higher values capture more moderate low-volume situations. Start with 1.0 and decrease to 0.5-0.7 for stricter detection.
Price Movement Sensitivity: Default: 1.5 | Range: 0.5-5.0 (step 0.1) | Multiplier for ATR-normalized price movement detection. Values above this threshold indicate rapid price changes suggesting liquidity voids. Increase to 2.0-3.0 for volatile instruments; decrease to 0.8-1.2 for ranging or low-volatility conditions.
Minimum Void Bars: Default: 10 | Range: 1-10 | Minimum consecutive bars exhibiting void conditions required before visualization is created. Filters out brief anomalies and ensures only sustained voids are displayed. Use 1-3 for scalping, 5-10 for intraday trading, 10+ for swing trading to match your time horizon.
Visual Settings
Low Liquidity Color: Default: Red (80% transparent) | Base color for zones where volume depletion or rapid movement indicates thin liquidity. These zones recede visually (back layer most transparent). Choose colors that contrast with your chart theme for optimal visibility.
High Liquidity Color: Default: Green (80% transparent) | Base color for zones with relatively higher liquidity compared to void threshold. These zones protrude visually (front layer most transparent). Ensure clear differentiation from low liquidity color.
Show Void Labels: Default: True | Toggle display of compact LV/HV labels at void centers. Disable for cleaner charts when trading; enable for analysis and review to quickly identify void types across your chart.
Max Visible Voids: Default: 50 | Range: 10-100 | Maximum number of void visualizations kept on chart. Each void uses 3 polylines, so setting of 50 maintains 150 total polylines. Higher values preserve more history but may impact performance on lower-end systems.
✅ Best Use Cases
Gap Fill Trading: Identify unfilled liquidity voids that price frequently returns to, providing high-probability retest and reversal opportunities when price approaches these zones
Breakout Validation: Distinguish genuine breakouts through established liquidity from false breaks into void zones that lack sustainable volume support
Support/Resistance Confluence: Layer void detection over key horizontal levels to validate structural integrity—levels within high liquidity zones are stronger than those in voids
Trend Continuation: Monitor for new void formation in trend direction as potential continuation zones where price may accelerate due to reduced resistance
Range Trading: Identify void zones within consolidation ranges that price tends to traverse quickly, helping to avoid getting caught in rapid moves through thin areas
Entry Timing: Wait for price to reach void boundaries rather than entering mid-void, as voids tend to be traversed quickly with limited profit-taking opportunities
⚠️ Limitations
Historical Pattern Indicator: Identifies past liquidity voids but cannot predict whether price will return to fill them or when filling might occur
No Volume on Forex: Indicator uses tick volume for forex pairs, which approximates but doesn't represent true trading volume, potentially affecting detection accuracy
Lagging Confirmation: Requires minimum consecutive bars (default 10) before void is visualized, meaning detection occurs after void formation begins
Trending Market Behavior: Strong trends driven by fundamental catalysts may create voids that remain unfilled for extended periods or permanently
Timeframe Dependency: Detection sensitivity varies significantly across timeframes; settings optimized for one timeframe may not perform well on others
No Directional Bias: Indicator identifies liquidity characteristics but provides no predictive signal for price direction after void detection
Performance Considerations: Higher max visible void settings combined with small minimum void bars can generate numerous visualizations impacting chart rendering speed
💡 What Makes This Unique
Industry-First 3D Visualization: Unlike flat volume or liquidity indicators, the three-layer rendering with directional depth perception provides instant visual hierarchy of liquidity quality
Dual-Mode Detection: Combines both volume-based and movement-based detection methodologies, capturing voids that single-approach indicators miss
Intelligent Qualification System: State machine logic prevents premature visualization by requiring sustained void conditions, reducing false signals and chart clutter
ATR-Normalized Analysis: All detection thresholds adapt to instrument volatility, ensuring consistent performance across stocks, forex, crypto, and futures without constant recalibration
Transparency-Based Depth: Uses progressive transparency gradients rather than colors or patterns to create depth, maintaining visual clarity while conveying information hierarchy
Comprehensive Strength Metrics: 0-100 void strength calculation considers both the degree of volume depletion and the magnitude of price movement for nuanced zone characterization
🔬 How It Works
Phase 1: Real-Time Detection
On each bar close, the indicator calculates average volume over the lookback period and compares current bar volume against the volume threshold multiplier
Simultaneously measures current bar's high-low range and normalizes it against ATR, comparing the result to price movement sensitivity parameter
If either volume falls below threshold OR movement exceeds sensitivity threshold, the bar is flagged as exhibiting void characteristics
Phase 2: Void Tracking & Qualification
When void conditions first appear, state machine initializes tracking variables: start bar index, initial top/bottom prices, consecutive bar counter, and cumulative strength accumulator
Each subsequent bar with void conditions extends the tracking, updating price boundaries to envelope all bars and accumulating strength scores
When void conditions cease, system checks if consecutive bar count meets minimum threshold; if yes, proceeds to visualization; if no, discards the tracking and resets
Phase 3: 3D Visualization Construction
Calculates average void strength by dividing cumulative strength by number of bars, then determines if void is low liquidity (>50 strength) or high liquidity (≤50 strength)
Generates three polyline layers spanning from start bar to end bar and from top price to bottom price, each with calculated vertical offset based on ATR
Applies progressive transparency (85%, 78%, 70%) with layer ordering creating recession effect for low liquidity zones and protrusion effect for high liquidity zones
Creates optional center label and pushes all visual elements into arrays for memory management
Phase 4: Memory Management & Display
Continuously monitors polyline array size (each void creates 3 polylines); when total exceeds max visible voids × 3, deletes oldest polylines via array.shift()
Similarly manages label array, removing oldest labels when count exceeds maximum to prevent memory accumulation over extended chart history
Plots diagnostic data to TradingView’s data window (void detection binary, current strength, average volume) for detailed analysis without cluttering main chart
💡 Note:
This indicator is designed to enhance your market structure analysis by revealing liquidity characteristics that aren’t visible through standard price and volume displays. For best results, combine void detection with your existing support/resistance analysis, trend identification, and risk management framework. Liquidity voids are descriptive of past market behavior and should inform positioning decisions rather than serve as standalone entry/exit signals. Experiment with detection parameters across different timeframes to find settings that align with your trading style and instrument characteristics.
Pinbar MTF - No Repaint# Pinbar MTF - No Repaint Indicator
## Complete Technical Documentation
---
## 📊 Overview
**Pinbar MTF (Multi-Timeframe) - No Repaint** is a professional-grade TradingView Pine Script indicator designed to detect high-probability pinbar reversal patterns with advanced filtering systems. The indicator is specifically engineered to be **100% non-repainting**, making it reliable for both live trading and backtesting.
### Key Features
✅ **Non-Repainting** - Signals only appear AFTER bar closes, never disappear
✅ **Three-Layer Filter System** - ATR, SWING, and RSI filters
✅ **Automatic SL/TP Calculation** - Based on risk:reward ratios
✅ **Real-time Alerts** - TradingView notifications for all signals
✅ **Visual Trade Management** - Lines, labels, and areas for entries, stops, and targets
✅ **Backtesting Ready** - Reliable historical data for strategy testing
---
## 🎯 What is a Pinbar?
A **Pinbar (Pin Bar/Pinocchio Bar)** is a single candlestick pattern that indicates a potential price reversal:
### Bullish Pinbar (BUY Signal)
- **Long lower wick** (rejection of lower prices)
- **Small body at the top** of the candle
- Shows buyers rejected sellers' attempt to push price down
- Forms at support levels or swing lows
- Entry signal for LONG positions
### Bearish Pinbar (SELL Signal)
- **Long upper wick** (rejection of higher prices)
- **Small body at the bottom** of the candle
- Shows sellers rejected buyers' attempt to push price up
- Forms at resistance levels or swing highs
- Entry signal for SHORT positions
---
## 🔧 How the Indicator Works
### 1. **Pinbar Detection Logic**
The indicator analyzes the **previous closed bar ** to identify pinbar patterns:
```
Bullish Pinbar Requirements:
- Lower wick > 72% of total candle range (adjustable)
- Upper wick < 28% of total candle range
- Close > Open (bullish candle body)
Bearish Pinbar Requirements:
- Upper wick > 72% of total candle range (adjustable)
- Lower wick < 28% of total candle range
- Close < Open (bearish candle body)
```
**Why check ?** By analyzing the previous completed bar, we ensure the pattern is fully formed and won't change, preventing repainting.
---
### 2. **Three-Layer Filter System**
#### 🔍 **Filter #1: ATR (Average True Range) Filter**
- **Purpose**: Ensures the pinbar has significant size
- **Function**: Only signals if pinbar range ≥ ATR value
- **Benefit**: Filters out small, insignificant pinbars
- **Settings**:
- Enable/Disable toggle
- ATR Period (default: 7)
**Example**: If ATR = 50 pips, only pinbars with 50+ pip range will signal.
---
#### 🔍 **Filter #2: SWING Filter** (Always Active)
- **Purpose**: Confirms pinbar forms at swing highs/lows
- **Function**: Validates the pinbar is an absolute high/low
- **Benefit**: Identifies true reversal points
- **Settings**:
- Swing Candles (default: 3)
**How it works**:
- For bullish pinbar: Checks if low is lowest of past 3 bars
- For bearish pinbar: Checks if high is highest of past 3 bars
**Example**: With 3 swing candles, a bullish pinbar must have the lowest low among the last 3 bars.
---
#### 🔍 **Filter #3: RSI (Relative Strength Index) Filter**
- **Purpose**: Confirms momentum conditions
- **Function**: Prevents signals in extreme momentum zones
- **Benefit**: Avoids counter-trend trades
- **Settings**:
- Enable/Disable toggle
- RSI Period (default: 7)
- RSI Source (Close, Open, High, Low, HL2, HLC3, OHLC4)
- Overbought Level (default: 70)
- Oversold Level (default: 30)
**Logic**:
- Bullish Pinbar: Only signals if RSI < 70 (not overbought)
- Bearish Pinbar: Only signals if RSI > 30 (not oversold)
---
### 3. **Stop Loss Calculation**
Two methods available:
#### Method A: ATR-Based Stop Loss (Recommended)
```
Bullish Pinbar:
SL = Pinbar Low - (1 × ATR)
Bearish Pinbar:
SL = Pinbar High + (1 × ATR)
```
**Benefit**: Dynamic stops that adapt to market volatility
#### Method B: Fixed Pips Stop Loss
```
Bullish Pinbar:
SL = Pinbar Low - (Fixed Pips)
Bearish Pinbar:
SL = Pinbar High + (Fixed Pips)
```
**Settings**:
- Calculate Stop with ATR (toggle)
- Stop Pips without ATR (default: 5)
---
### 4. **Take Profit Calculation**
Take Profit is calculated based on Risk:Reward ratio:
```
Bullish Trade:
TP = Entry + (Entry - SL) × Risk:Reward Ratio
Bearish Trade:
TP = Entry - (SL - Entry) × Risk:Reward Ratio
```
**Example**:
- Entry: 1.2000
- SL: 1.1950 (50 pip risk)
- RR: 2:1
- TP: 1.2100 (100 pip reward = 50 × 2)
**Settings**:
- Risk:Reward Ratio (default: 1.0, range: 0.1 to 10.0)
---
## 📈 Visual Elements
### On-Chart Displays
1. **Signal Markers**
- 🟢 **Green Triangle Up** = Bullish Pinbar (BUY)
- 🔴 **Red Triangle Down** = Bearish Pinbar (SELL)
- Placed directly on the pinbar candle
2. **Entry Labels**
- Green "BUY" label with entry price
- Red "SELL" label with entry price
- Shows exact entry level
3. **Stop Loss Lines**
- 🔴 Red horizontal line
- "SL" label
- Extends 20 bars forward
4. **Take Profit Lines**
- 🟢 Green horizontal line
- "TP" label
- Extends 20 bars forward
5. **Risk/Reward Areas** (Optional)
- Red shaded box = Risk zone (Entry to SL)
- Green shaded box = Reward zone (Entry to TP)
- Visual risk:reward visualization
6. **Info Table** (Top Right)
- Displays current settings
- Shows filter status (ON/OFF)
- Real-time RSI value
- Quick reference panel
---
## 🔔 Alert System
Three alert types available:
### 1. Combined Alert: "Pinbar Signal (Any Direction)"
- Fires for BOTH bullish and bearish pinbars
- **Best for**: General monitoring
- **Message**: "Pinbar Signal Detected on {TICKER} at {PRICE}"
### 2. Bullish Alert: "Bullish Pinbar Alert"
- Fires ONLY for BUY signals
- **Best for**: Long-only strategies
- **Message**: "BUY Signal on {TICKER} at {PRICE}"
### 3. Bearish Alert: "Bearish Pinbar Alert"
- Fires ONLY for SELL signals
- **Best for**: Short-only strategies
- **Message**: "SELL Signal on {TICKER} at {PRICE}"
---
## ⚙️ Input Parameters Reference
### **Filters Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| ATR Filter on Pinbar Range? | ✅ ON | Boolean | Enable/disable ATR filter |
| ATR Period | 7 | 1+ | Lookback period for ATR calculation |
| Swing Candles | 3 | 1+ | Bars to check for swing high/low |
| RSI Filter on Pinbar? | ❌ OFF | Boolean | Enable/disable RSI filter |
| RSI Period | 7 | 2+ | Lookback period for RSI calculation |
| RSI Source | Close | Multiple | Price data for RSI (Close/Open/High/Low/etc) |
| RSI Overbought Level | 70 | 50-100 | Upper threshold for RSI filter |
| RSI Oversold Level | 30 | 0-50 | Lower threshold for RSI filter |
### **Pinbar Detection Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Shadow % vs Body | 72 | 50-95 | Minimum wick size as % of total range |
### **Visualization Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Show SL and TP Lines? | ✅ ON | Boolean | Display stop loss and take profit lines |
| Show SL and TP Area? | ❌ OFF | Boolean | Show shaded risk/reward boxes |
### **Risk Management Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Risk:Reward Ratio | 1.0 | 0.1-10.0 | Target profit vs risk (1.0 = 1:1, 2.0 = 1:2) |
| Calculate Stop with ATR? | ✅ ON | Boolean | Use ATR for stop calculation |
| Stop Pips without ATR | 5 | 1+ | Fixed pip stop when ATR disabled |
---
## 🚫 Non-Repainting Architecture
### What is Repainting?
**Repainting** occurs when an indicator's historical signals differ from what appeared in real-time. This makes backtesting unreliable and can lead to false confidence in a strategy.
### How This Indicator Prevents Repainting
1. **Closed Bar Analysis**
- All calculations use ` ` offset (previous bar)
- Only analyzes COMPLETED candles
- Signals appear on the bar AFTER the pinbar closes
2. **Confirmed Swing Points**
- Waits for sufficient bar history before signaling
- Only checks historical bars that cannot change
- Prevents premature swing detection
3. **Static Alert Timing**
- Alerts fire only after bar completion
- No conditional logic that changes historically
- Same results in replay mode and live trading
### Verification Method
To verify non-repainting behavior:
1. Apply indicator to chart
2. Note signal locations and prices
3. Refresh browser / reload chart
4. **Signals remain in exact same locations**
---
## 💼 Trading Strategy Guidelines
### Entry Rules
**For Bullish Pinbar (LONG):**
1. Wait for green triangle to appear
2. Enter at close of pinbar (shown in label)
3. Alternative: Enter on break of pinbar high
4. Place stop loss at red SL line
5. Set target at green TP line
**For Bearish Pinbar (SHORT):**
1. Wait for red triangle to appear
2. Enter at close of pinbar (shown in label)
3. Alternative: Enter on break of pinbar low
4. Place stop loss at red SL line
5. Set target at green TP line
### Risk Management
- **Position Sizing**: Risk only 1-2% of account per trade
- **Stop Loss**: Always use the calculated SL (never move it wider)
- **Take Profit**: Use calculated TP or trail stop after 1:1 RR
- **Multiple Timeframes**: Confirm signals on higher timeframe
### Best Practices
✅ **DO:**
- Wait for bar to close before entering
- Trade in direction of higher timeframe trend
- Use on liquid markets with clear support/resistance
- Combine with price action analysis
- Keep a trading journal
❌ **DON'T:**
- Enter before bar closes (prevents seeing full pattern)
- Trade against strong trends
- Ignore the filters (they improve win rate)
- Risk more than 2% per trade
- Trade every signal (be selective)
---
## 📊 Backtesting & Data Export
### Available Data Points
The indicator exports these values for strategy development:
| Output | Description |
|--------|-------------|
| Bullish Signal | 1 = BUY signal, 0 = No signal |
| Bearish Signal | 1 = SELL signal, 0 = No signal |
| Bull SL | Stop loss level for long trades |
| Bull TP | Take profit level for long trades |
| Bull Entry | Entry price for long trades |
| Bear SL | Stop loss level for short trades |
| Bear TP | Take profit level for short trades |
| Bear Entry | Entry price for short trades |
### How to Use in Strategy
These values can be accessed by Pine Script strategies using:
```pine
indicator_values = request.security(syminfo.tickerid, timeframe.period,
)
```
---
## 🎓 Understanding the Filters
### Why Use Multiple Filters?
Single-indicator systems often generate too many false signals. This indicator uses a **confluence approach**:
1. **Pinbar Pattern** = Price rejection detected
2. **+ SWING Filter** = Rejection at key level
3. **+ ATR Filter** = Significant move
4. **+ RSI Filter** = Favorable momentum
**Result**: Higher probability setups with better risk:reward
### Filter Optimization
**Conservative Settings** (Fewer, Higher Quality Signals):
- ATR Filter: ON
- Swing Candles: 5
- RSI Filter: ON
- Shadow %: 75%
**Aggressive Settings** (More Signals, More Noise):
- ATR Filter: OFF
- Swing Candles: 2
- RSI Filter: OFF
- Shadow %: 65%
**Balanced Settings** (Recommended):
- ATR Filter: ON
- Swing Candles: 3
- RSI Filter: OFF (or ON for trending markets)
- Shadow %: 72%
---
## 🔍 Troubleshooting
### "No Signals Appearing"
**Possible Causes:**
1. Filters are too strict
2. No pinbars forming on chart
3. Insufficient bar history
**Solutions:**
- Reduce Shadow % to 65%
- Reduce Swing Candles to 2
- Disable ATR or RSI filters temporarily
- Check that chart has enough data loaded
### "Too Many Signals"
**Solutions:**
- Enable ATR filter
- Increase Swing Candles to 4-5
- Enable RSI filter
- Increase Shadow % to 75-80%
### "Signals Appearing Late"
**This is normal behavior!** The indicator:
- Analyzes previous closed bar
- Signals appear on the bar AFTER the pinbar
- This is what prevents repainting
- Signal latency is 1 bar (by design)
---
## 📝 Technical Specifications
**Indicator Type:** Overlay (displays on price chart)
**Pine Script Version:** 5
**Max Labels:** 500
**Max Lines:** 500
**Repainting:** None (100% non-repainting)
**Data Window Values:** 8 exported values
**Alert Types:** 3 (Combined, Bullish, Bearish)
**Performance:**
- Lightweight script (fast execution)
- Works on all timeframes
- Compatible with all markets (Forex, Crypto, Stocks, Futures)
- No data snooping bias
---
## 🎯 Use Cases
### 1. **Swing Trading**
- Timeframe: Daily, 4H
- Filter Settings: All enabled
- Best for: Catching major reversals
### 2. **Day Trading**
- Timeframe: 15m, 1H
- Filter Settings: ATR + SWING only
- Best for: Intraday reversals
### 3. **Scalping**
- Timeframe: 5m, 15m
- Filter Settings: SWING only (aggressive)
- Best for: Quick reversals (requires experience)
### 4. **Position Trading**
- Timeframe: Weekly, Daily
- Filter Settings: All enabled + high RR (2:1 or 3:1)
- Best for: Long-term trend reversal catches
---
## 🏆 Advantages Over Other Pinbar Indicators
✅ **Guaranteed Non-Repainting** - Many pinbar indicators repaint; this one never does
✅ **Automatic SL/TP** - No manual calculation needed
✅ **Multi-Layer Filtering** - Reduces false signals significantly
✅ **Visual Trade Management** - Clear entry, stop, and target levels
✅ **Flexible Configuration** - Adaptable to any trading style
✅ **Alert System** - Never miss a setup
✅ **Backtesting Ready** - Reliable historical data
✅ **Professional Grade** - Suitable for live trading
---
## 📚 Educational Resources
### Recommended Reading on Pinbars
- "The Pin Bar Trading Strategy" by Nial Fuller
- "Price Action Trading" by Al Brooks
- TradingView Education: Price Action Patterns
### Practice Recommendations
1. Paper trade signals for 20+ trades before live trading
2. Backtest on different timeframes and markets
3. Keep detailed records of all trades
4. Analyze winning vs losing setups
5. Refine filter settings based on results
---
## ⚖️ Disclaimer
This indicator is a tool for technical analysis and does not guarantee profits. Trading involves substantial risk of loss. Past performance is not indicative of future results.
- Always use proper risk management
- Never risk more than you can afford to lose
- Consider your trading experience and objectives
- Seek independent financial advice if needed
---
## 📧 Version Information
**Current Version:** 1.0
**Last Updated:** 2024
**Compatibility:** TradingView Pine Script v5
**Status:** Production Ready
---
## 🔄 Future Enhancements (Potential)
Possible future additions:
- Multi-timeframe confirmation option
- Volume filter integration
- Customizable color schemes
- Win rate statistics display
- Partial profit taking levels
- Trailing stop functionality
---
## 📖 Quick Start Guide
### 5-Minute Setup
1. **Add to Chart**
- Open TradingView
- Go to Pine Editor
- Paste the code
- Click "Add to Chart"
2. **Configure Settings**
- Open indicator settings (gear icon)
- Start with default settings
- Enable "Show SL and TP Lines"
3. **Set Alert**
- Right-click indicator name
- Click "Add Alert"
- Select "Pinbar Signal (Any Direction)"
- Configure notification method
4. **Test**
- Scroll back on chart
- Verify signals make sense
- Check that signals don't repaint
5. **Trade** (After Practice!)
- Wait for alert
- Verify signal quality
- Enter, place SL/TP
- Manage trade
---
## 🎯 Final Thoughts
The **Pinbar MTF - No Repaint** indicator is designed for serious traders who value:
- **Reliability** over flashy signals
- **Quality** over quantity
- **Honesty** over false promises
This indicator will NOT:
- Make you rich overnight
- Win every trade
- Replace proper trading education
This indicator WILL:
- Identify high-probability reversal setups
- Save you analysis time
- Provide consistent, non-repainting signals
- Help you develop a systematic trading approach
**Success in trading comes from:**
1. Proper education (60%)
2. Risk management (30%)
3. Technical tools like this indicator (10%)
Use this tool as part of a complete trading plan, not as a standalone solution.
cd_correlation_analys_Cxcd_correlation_analys_Cx
General:
This indicator is designed for correlation analysis by classifying stocks (487 in total) and indices (14 in total) traded on Borsa İstanbul (BIST) on a sectoral basis.
Tradingview's sector classifications (20) have been strictly adhered to for sector grouping.
Depending on user preference, the analysis can be performed within sectors, between sectors, or manually (single asset).
Let me express my gratitude to the code author, @fikira, beforehand; you will find the reason for my thanks in the context.
Details:
First, let's briefly mention how this indicator could have been prepared using the classic method before going into details.
Classically, assets could be divided into groups of forty (40), and the analysis could be performed using the built-in function:
ta.correlation(source1, source2, length) → series float.
I chose sectoral classification because I believe there would be a higher probability of assets moving together, rather than using fixed-number classes.
In this case, 21 arrays were formed with the following number of elements:
(3, 11, 21, 60, 29, 20, 12, 3, 31, 5, 10, 11, 6, 48, 73, 62, 16, 19, 13, 34 and indices (14)).
However, you might have noticed that some arrays have more than 40 elements. This is exactly where @Fikira's indicator came to the rescue. When I examined their excellent indicator, I saw that it could process 120 assets in a single operation. (I believe this was the first limit overrun; thanks again.)
It was amazing to see that data for 3 pairs could be called in a single request using a special method.
You can find the details here:
When I adapted it for BIST, I found it sufficient to call data for 2 pairs instead of 3 in a single go. Since asset prices are regular and have 2 decimal places, I used a fixed multiplier of $10^8$ and a fixed decimal count of 2 in Fikira's formulas.
With this method, the (high, low, open, close) values became accessible for each asset.
The summary up to this point is that instead of the ready-made formula + groups of 40, I used variable-sized groups and the method I will detail now.
Correlation/harmony/co-movement between assets provides advantages to market participants. Coherent assets are expected to rise or fall simultaneously.
Therefore, to convert co-movement into a mathematical value, I defined the possible movements of the current candle relative to the previous candle bar over a certain period (user-defined). These are:
Up := high > high and low > low
Down := high < high and low < low
Inside := high <= high and low >= low
Outside := high >= high and low <= low and NOT Inside.
Ignore := high = low = open = close
If both assets performed the same movement, 1 was added to the tracking counter.
If (Up-Up), (Down-Down), (Inside-Inside), or (Outside-Outside), then counter := counter + 1.
If the period length is 100 and the counter is 75, it means there is 75% co-movement.
Corr = counter / period ($75/100$)
Average = ta.sma(Corr, 100) is obtained.
The highest coefficients recorded in the array are presented to the user in a table.
From the user menu options, the user can choose to compare:
• With assets in its own sector
• With assets in the selected sector
• By activating the confirmation box and manually entering a single asset for comparison.
Table display options can be adjusted from the Settings tab.
In the attached examples:
Results for AKBNK stock from the Finance sector compared with GARAN stock from the same sector:
Timeframe: Daily, Period: 50 => Harmony 76% (They performed the same movement in 38 out of 50 bars)
Comment: Opposite movements at swing high and low levels may indicate a change in the direction of the price flow (SMT).
Looking at ASELS from the Electronic Technology sector over the last 30 daily candles, they performed the same movements by 40% with XU100, 73.3% (22/30) with XUTEK (Technology Index), and 86.9% according to the averages.
Comment: It is more appropriate to follow ASELS stock with XUTEK (Technology index) instead of the general index (XU100). Opposite movements at swing high and low levels may indicate a change in the direction of the price flow (SMT).
Again, when ASELS stock is taken on H1 instead of daily, and the length is 100 instead of 30, the harmony rate is seen to be 87%.
Please share your thoughts and criticisms regarding the indicator, which I prepared with a bit of an educational purpose specifically for BIST.
Happy trading.
Chronos Reversal Labs🧬 Chronos Reversal Lab - Machine Learning Market Structure Analysis
OVERVIEW
Chronos Reversal Lab (CRL) is an advanced market structure analyzer that combines computational intelligence kernels with classical technical analysis to identify high-probability reversal opportunities. The system integrates Shannon Entropy analysis, Detrended Fluctuation Analysis (DFA), Kalman adaptive filtering, and harmonic pattern recognition into a unified confluence-based signal engine.
WHAT MAKES IT ORIGINAL
Unlike traditional reversal indicators that rely solely on oscillators or pattern recognition, CRL employs a multi-kernel machine learning approach that analyzes market behavior through information theory, statistical physics, and adaptive state-space estimation. The system combines these computational methods with geometric pattern analysis and market microstructure to create a comprehensive reversal detection framework.
HOW IT WORKS (Technical Methodology)
1. COMPUTATIONAL KERNELS
Shannon Entropy Analysis
Measures market uncertainty using information theory:
• Discretizes price returns into bins (user-configurable 5-20 bins)
• Calculates probability distribution entropy over lookback window
• Normalizes entropy to 0-1 scale (0 = perfectly predictable, 1 = random)
• Low entropy states (< 0.3 default) indicate algorithmic clarity phases
• When entropy drops, directional moves become statistically more probable
Detrended Fluctuation Analysis (DFA)
Statistical technique measuring long-range correlations:
• Analyzes price series across multiple box sizes (4 to user-set maximum)
• Calculates fluctuation scaling exponent (Alpha)
• Alpha > 0.5: Trend persistence (momentum regime)
• Alpha < 0.5: Mean reversion tendency (reversal regime)
• Alpha range 0.3-1.5 mapped to trading strategies
Kalman Adaptive Filter
State-space estimation for lag-free trend tracking:
• Maintains separate fast and slow Kalman filters
• Process noise and measurement noise are user-configurable
• Tracks price state with adaptive gain adjustments
• Calculates acceleration (second derivative) for momentum detection
• Provides cleaner trend signals than traditional moving averages
2. HARMONIC PATTERN DETECTION
Identifies geometric reversal patterns:
• Gartley: 0.618 AB/XA, 0.786 AD/XA retracement
• Bat: 0.382-0.5 AB/XA, 0.886 AD/XA retracement
• Butterfly: 0.786 AB/XA, 1.272-1.618 AD/XA extension
• Cypher: 0.382-0.618 AB/XA, 0.786 AD/XA retracement
Pattern Validation Process:
• Requires alternating swing structure (XABCD points)
• Fibonacci ratio tolerance: 0.02-0.20 (user-adjustable precision)
• Minimum 50% ratio accuracy score required
• PRZ (Potential Reversal Zone) calculated around D point
• Zone size: ATR-based with pattern-specific multipliers
• Active pattern tracking with 100-bar invalidation window
3. MARKET STRUCTURE ANALYSIS
Swing Point Detection:
• Pivot-based swing identification (3-21 bars configurable)
• Minimum swing size: ATR multiples (0.5-5.0x)
• Adaptive filtering: volatility regime adjustment (0.7-1.3x)
• Swing confirmation tracking with RSI and volume context
• Maintains structural history (up to 500 swings)
Break of Structure (BOS):
• Detects price crossing previous swing highs/lows
• Used for trend continuation vs reversal classification
• Optional requirement for signal validation
Support/Resistance Detection:
• Identifies horizontal levels from swing clusters
• Touch counting algorithm (price within ATR×0.3 tolerance)
• Weighted by recency and number of tests
• Dynamic updating as structure evolves
4. CONFLUENCE SCORING SYSTEM
Multi-factor analysis with regime-aware weighting:
Hierarchical Kernel Logic:
• Entropy gates advanced kernel activation
• Only when entropy < threshold do DFA and Kalman accelerate scoring
• Prevents false signals during chaotic (high entropy) conditions
Scoring Components:
ML Kernels (when entropy low):
• Low entropy + trend alignment: +3.0 points × trend weight
• DFA super-trend (α>1.5): +4.0 points × trend weight
• DFA persistence (α>0.65): +2.5 points × trend weight
• DFA mean-reversion (α<0.35): +2.0 points × mean-reversion weight
• Kalman acceleration: up to +3.0 points (scaled by magnitude)
Classical Technical Analysis:
• RSI oversold (<30) / overbought (>70): +1.5 points
• RSI divergence (bullish/bearish): +2.5 points
• High relative volume (>1.5x): +0-2.0 points (scaled)
• Volume impulse (>2.0x): +1.5 points
• VWAP extremes: +1.0 point
• Trend alignment (Kalman fast vs slow): +1.5 points
• MACD crossover/momentum: +1.0 point
Structural Factors:
• Near support (within 0.5 ATR): +0-2.0 points (inverse distance)
• Near resistance (within 0.5 ATR): +0-2.0 points (inverse distance)
• Harmonic PRZ zone: +3.0 to +6.0 points (pattern score dependent)
• Break of structure: +1.5 points
Regime Adjustments:
• Trend weight: 1.5× in trend regime, 0.5× in mean-reversion
• Mean-reversion weight: 1.5× in MR regime, 0.5× in trend
• Volatility multiplier: 0.7-1.3× based on ATR regime
• Theory mode multiplier: 0.8× (Conservative) to 1.2× (APEX)
Final Threshold:
Base threshold (default 3.5) adjusted by:
• Theory mode: -0.3 (APEX) to +0.8 (Conservative)
• Regime: +0.5 (high vol) to -0.3 (low vol or strong trend)
• Filter: +0.2 if regime filter enabled
5. SIGNAL GENERATION ARCHITECTURE
Five-stage validation process:
Stage 1 - ML Kernel Analysis:
• Entropy threshold check
• DFA regime classification
• Kalman acceleration confirmation
Stage 2 - Structural Confirmation:
• Market structure supports directional bias
• BOS alignment (if required)
• Swing point validation
Stage 3 - Trigger Validation:
• Engulfing candle (if required)
• HTF bias confirmation (if strict HTF enabled)
• Harmonic PRZ alignment (if confirmation enabled)
Stage 4 - Consistency Check:
• Anticipation depth: checks N bars back (1-13 configurable)
• Ensures Kalman acceleration direction persists
• Filters whipsaw conditions
Stage 5 - Structural Soundness (Critical Filter):
• Verifies adequate room before next major swing level
• Long signals: must have >0.25 ATR clearance to last swing high
• Short signals: must have >0.25 ATR clearance to last swing low
• Prevents trades directly into obvious structural barriers
Dynamic Risk Management:
• Stop-loss: Placed beyond last structural swing ± 2 ticks
• Take-profit 1: Risk × configurable R1 multiplier (default 1.5R)
• Take-profit 2: Risk × configurable R2 multiplier (default 3.0R)
• Confidence score: Calibrated 0-99% based on confluence + kernel boost
6. ADAPTIVE REGIME SYSTEM
Continuous market state monitoring:
Trend Regime:
• Kalman fast vs slow positioning
• Multi-timeframe alignment (optional HTF)
• Strength: ATR-normalized fast/slow spread
Volatility Regime:
• Current ATR vs 100-bar average
• Regime ratio: 0.7-1.3 typical range
• Affects swing size filtering and cooldown periods
Signal Cooldown:
• Base: User-set bars (1-300)
• High volatility (>1.5): cooldown × 1.5
• Low volatility (<0.5): cooldown × 0.7
• Post-BOS: minimum 20-bar cooldown enforced
FOUR OPERATIONAL MODES
CONSERVATIVE MODE:
• Threshold adjustment: +0.8
• Mode multiplier: 0.8×
• Strictest filtering for highest quality
• Recommended for: Beginners, large accounts, swing trading
• Expected signals: 3-5 per week (typical volatile instrument)
BALANCED MODE:
• Threshold adjustment: +0.3
• Mode multiplier: 1.0×
• Standard operational parameters
• Recommended for: General trading, learning phase
• Expected signals: 5-10 per week
APEX MODE:
• Threshold adjustment: -0.3
• Mode multiplier: 1.2×
• Maximum sensitivity, reduced cooldowns
• Recommended for: Scalping, high volatility, experienced traders
• Expected signals: 10-20 per week
INSTITUTIONAL MODE:
• Threshold adjustment: +0.5
• Mode multiplier: 1.1×
• Enhanced structural weighting, HTF emphasis
• Recommended for: Professional traders, swing positions
• Expected signals: 4-8 per week
VISUAL COMPONENTS
1. Fibonacci Retracement Levels
• Auto-calculated from most recent swing structure
• Standard levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%, 127.2%, 161.8%, 200%, 261.8%
• Key levels emphasized (50%, 61.8%, 100%, 161.8%)
• Color gradient from bullish to bearish based on level
• Automatic cleanup when levels are crossed
• Label intensity control (None/Fib only/All)
2. Support and Resistance Lines
• Dynamic horizontal levels from swing clusters
• Width: 2px solid lines
• Colors: Green (support), Red (resistance)
• Labels show price and level type
• Touch-based validation (minimum 2 touches)
• Real-time updates and invalidation
3. Harmonic PRZ Boxes
• Displayed around pattern completion (D point)
• Pattern-specific colors (Gartley: purple, Bat: orange, etc.)
• Box height: ATR-based zone sizing
• Score-dependent transparency
• 100-bar active window before removal
4. Confluence Boxes
• Appear when confluence ≥ threshold
• Yellow/orange gradient based on score strength
• Height: High to low of bar
• Width: 1 bar on each side
• Real-time score-based transparency
5. Kalman Filter Lines
• Fast filter: Bullish color (green default)
• Slow filter: Bearish color (red default)
• Width: 2px
• Transparency adjustable (0-90%)
• Optional display toggle
6. Signal Markers
• Long: Green triangle below bar (tiny size)
• Short: Red triangle above bar (tiny size)
• Appear only on confirmed signals
• Includes alert generation
7. Premium Dashboard
Features real-time metrics with visual gauges:
Layout Options:
• Position: 4 corners selectable
• Size: Small (9 rows) / Normal (12 rows) / Large (14 rows)
• Themes: Supreme, Cosmic, Vortex, Heritage
Metrics Displayed:
• Gamma (DFA - 0.5): Shows trend persistence vs mean-reversion
• TCI (Trend Strength): ATR-normalized Kalman spread with gauge
• v/c (Relative Volume): Current vs average with color coding
• Entropy: Market predictability state with gauge
• HFL (High-Frequency Line): Kalman fast/slow difference / ATR
• HFL_acc (Acceleration): Second derivative momentum
• Mem Bias: Net bullish-bearish confluence (-1 to +1)
• Assurance: Confidence × (1-entropy) metric
• Squeeze: Bollinger Band / Keltner Channel squeeze detection
• Breakout P: Probability estimate from DFA + trend + acceleration
• Score: Final confluence vs threshold (normalized)
• Neighbors: Active harmonic patterns count
• Signal Strength: Strong/Moderate/Weak classification
• Signal Banner: Current directional bias with emoji indicators
Gauge Visualization:
• 10-bar horizontal gauges (█ filled, ░ empty)
• Color-coded: Green (strong) / Gold (moderate) / Red (weak)
• Real-time updates every bar
HOW TO USE
Step 1: Configure Mode and Resolution
• Select Theory Mode based on trading style (Conservative/Balanced/APEX/Institutional)
• Set Structural Resolution (Standard for fast markets, High for balanced, Ultra/Institutional for swing)
• Enable Adaptive Filtering (recommended for all volatile assets)
Step 2: Enable Desired Kernels
• Shannon Entropy: Essential for predictability detection (recommended ON)
• DFA Analysis: Critical for regime classification (recommended ON)
• Kalman Filter: Provides lag-free trend tracking (recommended ON)
• All three work synergistically; disabling reduces effectiveness
Step 3: Configure Confluence Factors
• Enable desired technical factors (RSI, MACD, Volume, Divergence)
• Enable Liquidity Mapping for support/resistance proximity scoring
• Enable Harmonic Detection if trading pattern-based setups
• Adjust base confluence threshold (3.5 default; higher = fewer, cleaner signals)
Step 4: Set Trigger Requirements
• Require Engulfing: Adds precision, reduces frequency (recommended for Conservative)
• Require BOS: Ensures structural alignment (recommended for trend-following)
• Require Structural Soundness: Critical filter preventing traps (highly recommended)
• Strict HTF Bias: For multi-timeframe traders only
Step 5: Adjust Visual Preferences
• Enable/disable Fibonacci levels, S/R lines, PRZ boxes, confluence boxes
• Set label intensity (None/Fib/All)
• Adjust transparency (0-90%) for overlay clarity
• Configure dashboard position, size, and theme
Step 6: Configure Alerts
• Enable master alerts toggle
• Select alert types: Anticipation, Confirmation, High Confluence, Low Entropy
• Enable JSON details for automated trading integration
Step 7: Interpret Signals
• Wait for triangle markers (green up = long, red down = short)
• Check dashboard for confluence score, entropy, DFA regime
• Verify signal aligns with higher timeframe bias (if using HTF setting)
• Confirm adequate space to take-profit levels (no nearby structural barriers)
Step 8: Execute and Manage
• Enter at close of signal candle (or next bar open)
• Set stop-loss at calculated level (visible in alert if JSON enabled)
• Scale out at TP1 (1.5R default), trail remaining to TP2 (3.0R default)
• Exit early if entropy spikes >0.7 or DFA regime flips against position
CUSTOMIZATION GUIDE
Timeframe Optimization:
Scalping (1-5 minutes):
• Theory Mode: APEX
• Anticipation Depth: 3-5
• Structural Resolution: STANDARD
• Signal Cooldown: 8-12 bars
• Enable fast kernels, disable HTF bias
Day Trading (15m-1H):
• Theory Mode: BALANCED
• Anticipation Depth: 5-8
• Structural Resolution: HIGH
• Signal Cooldown: 12-20 bars
• Standard configuration
Swing Trading (4H-Daily):
• Theory Mode: INSTITUTIONAL
• Anticipation Depth: 8-13
• Structural Resolution: ULTRA or INSTITUTIONAL
• Signal Cooldown: 20-50 bars
• Enable HTF bias, strict confirmations
Market Type Optimization:
Forex Majors:
• All kernels enabled
• Harmonic patterns effective
• Balanced or Institutional mode
• Standard settings work well
Stock Indices:
• Emphasis on volume analysis
• DFA critical for regime detection
• Conservative or Balanced mode
• Enable liquidity mapping
Cryptocurrencies:
• Adaptive filtering essential
• Higher volatility regime expected
• APEX mode for active trading
• Wider ATR multiples for swing sizing
IMPORTANT DISCLAIMERS
• This indicator does not predict future price movements
• Computational kernels calculate probabilities, not certainties
• Past confluence scores do not guarantee future signal performance
• Always backtest on YOUR specific instruments and timeframes before live trading
• Machine learning kernels require calibration period (minimum 100 bars of data)
• Performance varies significantly across market conditions and regimes
• Signals are suggestions for analysis, not automated trading instructions
• Proper risk management (stops, position sizing) is mandatory
• Complex calculations may impact performance on lower-end devices
• Designed for liquid markets; avoid illiquid or gap-prone instruments
PERFORMANCE CONSIDERATIONS
Computational Intensity:
• DFA analysis: Moderate (scales with length and box size parameters)
• Entropy calculation: Moderate (scales with lookback and bins)
• Kalman filtering: Low (efficient state-space updates)
• Harmonic detection: Moderate to High (pattern matching across swing history)
• Overall: Medium computational load
Optimization Tips:
• Reduce Structural Analysis Depth (144 default → 50-100 for faster performance)
• Increase Calc Step (2 default → 3-4 for lighter load)
• Reduce Pattern Analysis Depth (8 default → 3-5 if harmonics not primary focus)
• Limit Draw Window (150 bars default prevents visual clutter on long charts)
• Disable unused confluence factors to reduce calculations
Best Suited For:
• Liquid instruments: Major forex, stock indices, large-cap crypto
• Active timeframes: 5-minute through daily (avoid tick/second charts)
• Trending or ranging markets: Adapts to both via regime detection
• Pattern traders: Harmonic integration adds geometric confluence
• Multi-timeframe analysts: HTF bias and regime detection support this approach
Not Recommended For:
• Illiquid penny stocks or micro-cap altcoins
• Markets with frequent gaps (stocks outside regular hours without gap adjustment)
• Extremely fast timeframes (tick, second charts) due to calculation overhead
• Pure mean-reversion systems (unless using CONSERVATIVE mode with DFA filters)
METHODOLOGY NOTE
The computational kernels (Shannon Entropy, DFA, Kalman Filter) are established statistical and signal processing techniques adapted for financial time series analysis. These are deterministic mathematical algorithms, not predictive AI models. The term "machine learning" refers to the adaptive, data-driven nature of the calculations, not neural networks or training processes.
Confluence scoring is rule-based with regime-dependent weighting. The system does not "learn" from historical trades but adapts its sensitivity to current volatility and trend conditions through mathematical regime classification.
SUPPORT & UPDATES
• Questions about configuration or usage? Send me a message on TradingView
• Feature requests are welcome for consideration in future updates
• Bug reports appreciated and addressed promptly
• I respond to messages within 24 hours
• Regular updates included (improvements, optimizations, new features)
FINAL REMINDERS
• This is an analytical tool for confluence analysis, not a standalone trading system
• Combine with your existing strategy, risk management, and market analysis
• Start with paper trading to learn the system's behavior on your markets
• Allow 50-100 signals minimum for performance evaluation
• Adjust parameters based on YOUR timeframe, instrument, and trading style
• No indicator guarantees profitable trades - proper risk management is essential
— Dskyz, Trade with insight. Trade with anticipation.
Forecast PriceTime Oracle [CHE] Forecast PriceTime Oracle — Prioritizes quality over quantity by using Power Pivots via RSI %B metric to forecast future pivot highs/lows in price and time
Summary
This indicator identifies potential pivot highs and lows based on out-of-bounds conditions in a modified RSI %B metric, then projects future occurrences by estimating time intervals and price changes from historical medians. It provides visual forecasts via diagonal and horizontal lines, tracks achievement with color changes and symbols, and displays a dashboard for statistical overview including hit rates. Signals are robust due to median-based aggregation, which reduces outlier influence, and optional tolerance settings for near-misses, making it suitable for anticipating reversals in ranging or trending markets.
Motivation: Why this design?
Standard pivot detection often lags or generates false signals in volatile conditions, missing the timing of true extrema. This design leverages out-of-bounds excursions in RSI %B to capture "Power Pivots" early—focusing on quality over quantity by prioritizing significant extrema rather than every minor swing—then uses historical deltas in time and price to forecast the next ones, addressing the need for proactive rather than reactive analysis. It assumes that pivot spacing follows statistical patterns, allowing users to prepare entries or exits ahead of confirmation.
What’s different vs. standard approaches?
- Reference baseline: Diverges from traditional ta.pivothigh/low, which require fixed left/right lengths and confirm only after bars close, often too late for dynamic markets.
- Architecture differences:
- Detects extrema during OOB runs rather than post-bar symmetry.
- Aggregates deltas via medians (or alternatives) over a user-defined history, capping arrays to manage resources.
- Applies tolerance thresholds for hit detection, with options for percentage, absolute, or volatility-adjusted (ATR) flexibility.
- Freezes achieved forecasts with visual states to avoid clutter.
- Practical effect: Charts show proactive dashed projections instead of retrospective dots; the dashboard reveals evolving hit rates, helping users gauge reliability over time without manual calculation.
How it works (technical)
The indicator first computes a smoothed RSI over a specified length, then applies Bollinger Bands to derive %B, flagging out-of-bounds below zero or above one hundred as potential run starts. During these runs, it tracks the extreme high or low price and bar index. Upon exit from the OOB state, it confirms the Power Pivot at that extreme and records the time delta (bars since prior) and price change percentage to rolling arrays.
For forecasts, it calculates the median (or selected statistic) of recent deltas, subtracts the confirmation delay (bars from apex to exit), and projects ahead by that adjusted amount. Price targets use the median change applied to the origin pivot value. Lines are drawn from the apex to the target bar and price, with a short horizontal at the endpoint. Arrays store up to five active forecasts, pruning oldest on overflow.
Tolerance adjusts hit checks: for highs, if the high reaches or exceeds the target (adjusted by tolerance); for lows, if the low drops to or below. Once hit, the forecast freezes, changing colors and symbols, and extends the horizontal to the hit bar. Persistent variables maintain last pivot states across bars; arrays initialize empty and grow until capped at history length.
Parameter Guide
Source: Specifies the data input for the RSI computation, influencing how price action is captured. Default is close. For conservative signals in noisy environments, switch to high; using low boosts responsiveness but may increase false positives.
RSI Length: Sets the smoothing period for the RSI calculation, with longer values helping to filter out whipsaws. Default is 32. Opt for shorter lengths like 14 to 21 on faster timeframes for quicker reactions, or extend to 50 or more in strong trends to enhance stability at the cost of some lag.
BB Length: Defines the period for the Bollinger Bands applied to %B, directly affecting how often out-of-bounds conditions are triggered. Default is 20. Align it with the RSI length: shorter periods detect more potential runs but risk added noise, while longer ones provide better filtering yet might overlook emerging extrema.
BB StdDev: Controls the multiplier for the standard deviation in the bands, where wider settings reduce false out-of-bounds alerts. Default is 2.0. Narrow it to 1.5 for highly volatile assets to catch more signals, or broaden to 2.5 or higher to emphasize only major movements.
Show Price Forecast: Enables or disables the display of diagonal and target lines along with their updates. Default is true. Turn it off for simpler chart views, or keep it on to aid in trade planning.
History Length: Determines the number of recent pivot samples used for median-based statistics, where more history leads to smoother but potentially less current estimates. Default is 50. Start with a minimum of 5 to build data; limit to 100 to 200 to prevent outdated regimes from skewing results.
Max Lookahead: Limits the number of bars projected forward to avoid overly extended lines. Default is 500. Reduce to 100 to 200 for intraday focus, or increase for longer swing horizons.
Stat Method: Selects the aggregation technique for time and price deltas: Median for robustness against outliers, Trimmed Mean (20%) for a balanced trim of extremes, or 75th Percentile for a conservative upward tilt. Default is Median. Use Median for even distributions; switch to Percentile when emphasizing potential upside in trending conditions.
Tolerance Type: Chooses the approach for flexible hit detection: None for exact matches, Percentage for relative adjustments, Absolute for fixed point offsets, or ATR for scaling with volatility. Default is None. Begin with Percentage at 0.5 percent for currency pairs, or ATR for adapting to cryptocurrency swings.
Tolerance %: Provides the relative buffer when using Percentage mode, forgiving small deviations. Default is 0.5. Set between 0.2 and 1.0 percent; higher values accommodate gaps but can overstate hit counts.
Tolerance Points: Establishes a fixed offset in price units for Absolute mode. Default is 0.0010. Tailor to the asset, such as 0.0001 for forex pairs, and validate against past wick behavior.
ATR Length: Specifies the period for the Average True Range in dynamic tolerance calculations. Default is 14. This is the standard setting; shorten to 10 to reflect more recent volatility.
ATR Multiplier: Adjusts the ATR scale for tolerance width in ATR mode. Default is 0.5. Range from 0.3 for tighter precision to 0.8 for greater leniency.
Dashboard Location: Positions the summary table on the chart. Default is Bottom Right. Consider Top Left for better visibility on mobile devices.
Dashboard Size: Controls the text scaling for dashboard readability. Default is Normal. Choose Tiny for dense overlays or Large for detailed review sessions.
Text/Frame Color: Sets the color scheme for dashboard text and borders. Default is gray. Align with your chart theme, opting for lighter shades on dark backgrounds.
Reading & Interpretation
Forecast lines appear as dashed diagonals from confirmed pivots to projected targets, with solid horizontals at endpoints marking price levels. Open targets show a target symbol (🎯); achieved ones switch to a trophy symbol (🏆) in gray, with lines fading to gray. The dashboard summarizes median time/price deltas, sample counts, and hit rates—rising rates indicate improving forecast alignment. Colors differentiate highs (red) from lows (lime); frozen states signal validated projections.
Practical Workflows & Combinations
- Trend following: Enter long on low forecast hits during uptrends (higher highs/lower lows structure); filter with EMA crossovers to ignore counter-trend signals.
- Reversal setups: Short above high projections in overextended rallies; use volume spikes as confirmation to reduce false breaks.
- Exits/Stops: Trail stops to prior pivot lows; conservative on low hit rates (below 50%), aggressive above 70% with tight tolerance.
- Multi-TF: Apply on 1H for entries, 4H for time projections; combine with Ichimoku clouds for confluence on targets.
- Risk management: Position size inversely to delta uncertainty (wider history = smaller bets); avoid low-liquidity sessions.
Behavior, Constraints & Performance
Confirmation occurs on OOB exit, so live-bar pivots may adjust until close, but projections update only on events to minimize repaint. No security or HTF calls, so no external lookahead issues. Arrays cap at history length with shifts; forecasts limited to five active, pruning FIFO. Loops iterate over small fixed sizes (e.g., up to 50 for stats), efficient on most hardware. Max lines/labels at 500 prevent overflow.
Known limits: Sensitive to OOB parameter tuning—too tight misses runs; assumes stationary pivot stats, which may shift in regime changes like low vol. Gaps or holidays distort time deltas.
Sensible Defaults & Quick Tuning
Defaults suit forex/crypto on 1H–4H: RSI 32/BB 20 for balanced detection, Median stats over 50 samples, None tolerance for exactness.
- Too many false runs: Increase BB StdDev to 2.5 or RSI Length to 50 for filtering.
- Lagging forecasts: Shorten History Length to 20; switch to 75th Percentile for forward bias.
- Missed near-hits: Enable Percentage tolerance at 0.3% to capture wicks without overcounting.
- Cluttered charts: Reduce Max Lookahead to 200; disable dashboard on lower TFs.
What this indicator is—and isn’t
This is a forecasting visualization layer for pivot-based analysis, highlighting statistical projections from historical patterns. It is not a standalone system—pair with price action, volume, and risk rules. Not predictive of all turns; focuses on OOB-derived extrema, ignoring volume or news impacts.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Volume Cluster Heatmap [BackQuant]Volume Cluster Heatmap
A visualization tool that maps traded volume across price levels over a chosen lookback period. It highlights where the market builds balance through heavy participation and where it moves efficiently through low-volume zones. By combining a heatmap, volume profile, and high/low volume node detection, this indicator reveals structural areas of support, resistance, and liquidity that drive price behavior.
What Are Volume Clusters?
A volume cluster is a horizontal aggregation of traded volume at specific price levels, showing where market participants concentrated their buying and selling.
High Volume Nodes (HVN) : Price levels with significant trading activity; often act as support or resistance.
Low Volume Nodes (LVN) : Price levels with little trading activity; price moves quickly through these areas, reflecting low liquidity.
Volume clusters help identify key structural zones, reveal potential reversals, and gauge market efficiency by highlighting where the market is balanced versus areas of thin liquidity.
By creating heatmaps, profiles, and highlighting high and low volume nodes (HVNs and LVNs), it allows traders to see where the market builds balance and where it moves efficiently through thin liquidity zones.
Example: Bitcoin breaking away from the high-volume zone near 118k and moving cleanly through the low-volume pocket around 113k–115k, illustrating how markets seek efficiency:
Core Features
Visual Analysis Components:
Heatmap Display : Displays volume intensity as colored boxes, lines, or a combination for a dynamic view of market participation.
Volume Profile Overlay : Shows cumulative volume per price level along the right-hand side of the chart.
HVN & LVN Labels : Marks high and low volume nodes with color-coded lines and labels.
Customizable Colors & Transparency : Adjust high and low volume colors and minimum transparency for clear differentiation.
Session Reset & Timeframe Control : Dynamically resets clusters at the start of new sessions or chosen timeframes (intraday, daily, weekly).
Alerts
HVN / LVN Alerts : Notify when price reaches a significant high or low volume node.
High Volume Zone Alerts : Trigger when price enters the top X% of cumulative volume, signaling key areas of market interest.
How It Works
Each bar’s volume is distributed proportionally across the horizontal price levels it touches. Over the lookback period, this builds a cumulative volume profile, identifying price levels with the most and least trading activity. The highest cumulative volume levels become HVNs, while the lowest are LVNs. A side volume profile shows aggregated volume per level, and a heatmap overlay visually reinforces market structure.
Applications for Traders
Identify strong support and resistance at HVNs.
Detect areas of low liquidity where price may move quickly (LVNs).
Determine market balance zones where price may consolidate.
Filter noise: because volume clusters aggregate activity into levels, minor fluctuations and irrelevant micro-moves are removed, simplifying analysis and improving strategy development.
Combine with other indicators such as VWAP, Supertrend, or CVD for higher-probability entries and exits.
Use volume clusters to anticipate price reactions to breaking points in thin liquidity zones.
Advanced Display Options
Heatmap Styles : Boxes, lines, or both. Boxes provide a traditional heatmap, lines are better for high granularity data.
Line Mode Example : Simplified line visualization for easier reading at high level counts:
Profile Width & Offset : Adjust spacing and placement of the volume profile for clarity alongside price.
Transparency Control : Lower transparency for more opaque visualization of high-volume zones.
Best Practices for Usage
Reduce the number of levels when using line mode to avoid clutter.
Use HVN and LVN markers in conjunction with volume profiles to plan entries and exits.
Apply session resets to monitor intraday vs. multi-day volume accumulation.
Combine with other technical indicators to confirm high-probability trading signals.
Watch price interactions with LVNs for potential rapid movements and with HVNs for possible support/resistance or reversals.
Technical Notes
Each bar contributes volume proportionally to the price levels it spans, creating a dynamic and accurate representation of traded interest.
Volume profiles are scaled and offset for visual clarity alongside live price.
Alerts are fully integrated for HVN/LVN interaction and high-volume zone entries.
Optimized to handle large lookback windows and numerous price levels efficiently without performance degradation.
This indicator is ideal for understanding market structure, detecting key liquidity areas, and filtering out noise to model price more accurately in high-frequency or algorithmic strategies.
Luxy Momentum, Trend, Bias and Breakout Indicators V7
TABLE OF CONTENTS
This is Version 7 (V7) - the latest and most optimized release. If you are using any older versions (V6, V5, V4, V3, etc.), it is highly recommended to replace them with V7.
Why This Indicator is Different
Who Should Use This
Core Components Overview
The UT Bot Trading System
Understanding the Market Bias Table
Candlestick Pattern Recognition
Visual Tools and Features
How to Use the Indicator
Performance and Optimization
FAQ
---
### CREDITS & ATTRIBUTION
This indicator implements proven trading concepts using entirely original code developed specifically for this project.
### CONCEPTUAL FOUNDATIONS
• UT Bot ATR Trailing System
- Original concept by @QuantNomad: (search "UT-Bot-Strategy"
- Our version is a complete reimplementation with significant enhancements:
- Volume-weighted momentum adjustment
- Composite stop loss from multiple S/R layers
- Multi-filter confirmation system (swing, %, 2-bar, ZLSMA)
- Full integration with multi-timeframe bias table
- Visual audit trail with freeze-on-touch
- NOTE: No code was copied - this is a complete reimplementation with enhancements.
• Standard Technical Indicators (Public Domain Formulas):
- Supertrend: ATR-based trend calculation with custom gradient fills
- MACD: Gerald Appel's formula with separation filters
- RSI: J. Welles Wilder's formula with pullback zone logic
- ADX/DMI: Custom trend strength formula inspired by Wilder's directional movement concept, reimplemented with volume weighting and efficiency metrics
- ZLSMA: Zero-lag formula enhanced with Hull MA and momentum prediction
### Custom Implementations
- Trend Strength: Inspired by Wilder's ADX concept but using volume-weighted pressure calculation and efficiency metrics (not traditional +DI/-DI smoothing)
- All code implementations are original
### ORIGINAL FEATURES (70%+ of codebase)
- Multi-Timeframe Bias Table with live updates
- Risk Management System (R-multiple TPs, freeze-on-touch)
- Opening Range Breakout tracker with session management
- Composite Stop Loss calculator using 6+ S/R layers
- Performance optimization system (caching, conditional calcs)
- VIX Fear Index integration
- Previous Day High/Low auto-detection
- Candlestick pattern recognition with interactive tooltips
- Smart label and visual management
- All UI/UX design and table architecture
### DEVELOPMENT PROCESS
**AI Assistance:** This indicator was developed over 2+ months with AI assistance (ChatGPT/Claude) used for:
- Writing Pine Script code based on design specifications
- Optimizing performance and fixing bugs
- Ensuring Pine Script v6 compliance
- Generating documentation
**Author's Role:** All trading concepts, system design, feature selection, integration logic, and strategic decisions are original work by the author. The AI was a coding tool, not the system designer.
**Transparency:** We believe in full disclosure - this project demonstrates how AI can be used as a powerful development tool while maintaining creative and strategic ownership.
---
1. WHY THIS INDICATOR IS DIFFERENT
Most traders use multiple separate indicators on their charts, leading to cluttered screens, conflicting signals, and analysis paralysis. The Suite solves this by integrating proven technical tools into a single, cohesive system.
Key Advantages:
All-in-One Design: Instead of loading 5-10 separate indicators, you get everything in one optimized script. This reduces chart clutter and improves TradingView performance.
Multi-Timeframe Bias Table: Unlike standard indicators that only show the current timeframe, the Bias Table aggregates trend signals across multiple timeframes simultaneously. See at a glance whether 1m, 5m, 15m, 1h are aligned bullish or bearish - no more switching between charts.
Smart Confirmations: The indicator doesn't just give signals - it shows you WHY. Every entry has multiple layers of confirmation (MA cross, MACD momentum, ADX strength, RSI pullback, volume, etc.) that you can toggle on/off.
Dynamic Stop Loss System: Instead of static ATR stops, the SL is calculated from multiple support/resistance layers: UT trailing line, Supertrend, VWAP, swing structure, and MA levels. This creates more intelligent, price-action-aware stops.
R-Multiple Take Profits: Built-in TP system calculates targets based on your initial risk (1R, 1.5R, 2R, 3R). Lines freeze when touched with visual checkmarks, giving you a clean audit trail of partial exits.
Educational Tooltips Everywhere: Every single input has detailed tooltips explaining what it does, typical values, and how it impacts trading. You're not guessing - you're learning as you configure.
Performance Optimized: Smart caching, conditional calculations, and modular design mean the indicator runs fast despite having 15+ features. Turn off what you don't use for even better performance.
No Repainting: All signals respect bar close. Alerts fire correctly. What you see in history is what you would have gotten in real-time.
What Makes It Unique:
Integrated UT Bot + Bias Table: No other indicator combines UT Bot's ATR trailing system with a live multi-timeframe dashboard. You get precision entries with macro trend context.
Candlestick Pattern Recognition with Interactive Tooltips: Patterns aren't just marked - hover over any emoji for a full explanation of what the pattern means and how to trade it.
Opening Range Breakout Tracker: Built-in ORB system for intraday traders with customizable session times and real-time status updates in the Bias Table.
Previous Day High/Low Auto-Detection: Automatically plots PDH/PDL on intraday charts with theme-aware colors. Updates daily without manual input.
Dynamic Row Labels in Bias Table: The table shows your actual settings (e.g., "EMA 10 > SMA 20") not generic labels. You know exactly what's being evaluated.
Modular Filter System: Instead of forcing a fixed methodology, the indicator lets you build your own strategy. Start with just UT Bot, add filters one at a time, test what works for your style.
---
2. WHO WHOULD USE THIS
Designed For:
Intermediate to Advanced Traders: You understand basic technical analysis (MAs, RSI, MACD) and want to combine multiple confirmations efficiently. This isn't a "one-click profit" system - it's a professional toolkit.
Multi-Timeframe Traders: If you trade one asset but check multiple timeframes for confirmation (e.g., enter on 5m after checking 15m and 1h alignment), the Bias Table will save you hours every week.
Trend Followers: The indicator excels at identifying and following trends using UT Bot, Supertrend, and MA systems. If you trade breakouts and pullbacks in trending markets, this is built for you.
Intraday and Swing Traders: Works equally well on 5m-1h charts (day trading) and 4h-D charts (swing trading). Scalpers can use it too with appropriate settings adjustments.
Discretionary Traders: This isn't a black-box system. You see all the components, understand the logic, and make final decisions. Perfect for traders who want tools, not automation.
Works Across All Markets:
Stocks (US, international)
Cryptocurrency (24/7 markets supported)
Forex pairs
Indices (SPY, QQQ, etc.)
Commodities
NOT Ideal For :
Complete Beginners: If you don't know what a moving average or RSI is, start with basics first. This indicator assumes foundational knowledge.
Algo Traders Seeking Black Box: This is discretionary. Signals require context and confirmation. Not suitable for blind automated execution.
Mean-Reversion Only Traders: The indicator is trend-following at its core. While VWAP bands support mean-reversion, the primary methodology is trend continuation.
---
3. CORE COMPONENTS OVERVIEW
The indicator combines these proven systems:
Trend Analysis:
Moving Averages: Four customizable MAs (Fast, Medium, Medium-Long, Long) with six types to choose from (EMA, SMA, WMA, VWMA, RMA, HMA). Mix and match for your style.
Supertrend: ATR-based trend indicator with unique gradient fill showing trend strength. One-sided ribbon visualization makes it easier to see momentum building or fading.
ZLSMA : Zero-lag linear-regression smoothed moving average. Reduces lag compared to traditional MAs while maintaining smooth curves.
Momentum & Filters:
MACD: Standard MACD with separation filter to avoid weak crossovers.
RSI: Pullback zone detection - only enter longs when RSI is in your defined "buy zone" and shorts in "sell zone".
ADX/DMI: Trend strength measurement with directional filter. Ensures you only trade when there's actual momentum.
Volume Filter: Relative volume confirmation - require above-average volume for entries.
Donchian Breakout: Optional channel breakout requirement.
Signal Systems:
UT Bot: The primary signal generator. ATR trailing stop that adapts to volatility and gives clear entry/exit points.
Base Signals: MA cross system with all the above filters applied. More conservative than UT Bot alone.
Market Bias Table: Multi-timeframe dashboard showing trend alignment across 7 timeframes plus macro bias (3-day, weekly, monthly, quarterly, VIX).
Candlestick Patterns: Six major reversal patterns auto-detected with interactive tooltips.
ORB Tracker: Opening range high/low with breakout status (intraday only).
PDH/PDL: Previous day levels plotted automatically on intraday charts.
VWAP + Bands : Session-anchored VWAP with up to three standard deviation band pairs.
---
4. THE UT BOT TRADING SYSTEM
The UT Bot is the heart of the indicator's signal generation. It's an advanced ATR trailing stop that adapts to market volatility.
Why UT Bot is Superior to Fixed Stops:
Traditional ATR stops use a fixed multiplier (e.g., "stop = entry - 2×ATR"). UT Bot is smarter:
It TRAILS the stop as price moves in your favor
It WIDENS during high volatility to avoid premature stops
It TIGHTENS during consolidation to lock in profits
It FLIPS when price breaks the trailing line, signaling reversals
Visual Elements You'll See:
Orange Trailing Line: The actual UT stop level that adapts bar-by-bar
Buy/Sell Labels: Aqua triangle (long) or orange triangle (short) when the line flips
ENTRY Line: Horizontal line at your entry price (optional, can be turned off)
Suggested Stop Loss: A composite SL calculated from multiple support/resistance layers:
- UT trailing line
- Supertrend level
- VWAP
- Swing structure (recent lows/highs)
- Long-term MA (200)
- ATR-based floor
Take Profit Lines: TP1, TP1.5, TP2, TP3 based on R-multiples. When price touches a TP, it's marked with a checkmark and the line freezes for audit trail purposes.
Status Messages: "SL Touched ❌" or "SL Frozen" when the trade leg completes.
How UT Bot Differs from Other ATR Systems:
Multiple Filters Available: You can require 2-bar confirmation, minimum % price change, swing structure alignment, or ZLSMA directional filter. Most UT implementations have none of these.
Smart SL Calculation: Instead of just using the UT line as your stop, the indicator suggests a better SL based on actual support/resistance. This prevents getting stopped out by wicks while keeping risk controlled.
Visual Audit Trail: All SL/TP lines freeze when touched with clear markers. You can review your trades weeks later and see exactly where entries, stops, and targets were.
Performance Options: "Draw UT visuals only on bar close" lets you reduce rendering load without affecting logic or alerts - critical for slower machines or 1m charts.
Trading Logic:
UT Bot flips direction (Buy or Sell signal appears)
Check Bias Table for multi-timeframe confirmation
Optional: Wait for Base signal or candlestick pattern
Enter at signal bar close or next bar open
Place stop at "Suggested Stop Loss" line
Scale out at TP levels (TP1, TP2, TP3)
Exit remaining position on opposite UT signal or stop hit
---
5. UNDERSTANDING THE MARKET BIAS TABLE
This is the indicator's unique multi-timeframe intelligence layer. Instead of looking at one chart at a time, the table aggregates signals across seven timeframes plus macro trend bias.
Why Multi-Timeframe Analysis Matters:
Professional traders check higher and lower timeframes for context:
Is the 1h uptrend aligning with my 5m entry?
Are all short-term timeframes bullish or just one?
Is the daily trend supportive or fighting me?
Doing this manually means opening multiple charts, checking each indicator, and making mental notes. The Bias Table does it automatically in one glance.
Table Structure:
Header Row:
On intraday charts: 1m, 5m, 15m, 30m, 1h, 2h, 4h (toggle which ones you want)
On daily+ charts: D, W, M (automatic)
Green dot next to title = live updating
Headline Rows - Macro Bias:
These show broad market direction over longer periods:
3 Day Bias: Trend over last 3 trading sessions (uses 1h data)
Weekly Bias: Trend over last 5 trading sessions (uses 4h data)
Monthly Bias: Trend over last 30 daily bars
Quarterly Bias: Trend over last 13 weekly bars
VIX Fear Index: Market regime based on VIX level - bullish when low, bearish when high
Opening Range Breakout: Status of price vs. session open range (intraday only)
These rows show text: "BULLISH", "BEARISH", or "NEUTRAL"
Indicator Rows - Technical Signals:
These evaluate your configured indicators across all active timeframes:
Fast MA > Medium MA (shows your actual MA settings, e.g., "EMA 10 > SMA 20")
Price > Long MA (e.g., "Price > SMA 200")
Price > VWAP
MACD > Signal
Supertrend (up/down/neutral)
ZLSMA Rising
RSI In Zone
ADX ≥ Minimum
These rows show emojis: GREEB (bullish), RED (bearish), GRAY/YELLOW (neutral/NA)
AVG Column:
Shows percentage of active timeframes that are bullish for that row. This is the KEY metric:
AVG > 70% = strong multi-timeframe bullish alignment
AVG 40-60% = mixed/choppy, no clear trend
AVG < 30% = strong multi-timeframe bearish alignment
How to Use the Table:
For a long trade:
Check AVG column - want to see > 60% ideally
Check headline bias rows - want to see BULLISH, not BEARISH
Check VIX row - bullish market regime preferred
Check ORB row (intraday) - want ABOVE for longs
Scan indicator rows - more green = better confirmation
For a short trade:
Check AVG column - want to see < 40% ideally
Check headline bias rows - want to see BEARISH, not BULLISH
Check VIX row - bearish market regime preferred
Check ORB row (intraday) - want BELOW for shorts
Scan indicator rows - more red = better confirmation
When AVG is 40-60%:
Market is choppy, mixed signals. Either stay out or reduce position size significantly. These are low-probability environments.
Unique Features:
Dynamic Labels: Row names show your actual settings (e.g., "EMA 10 > SMA 20" not generic "Fast > Slow"). You know exactly what's being evaluated.
Customizable Rows: Turn off rows you don't care about. Only show what matters to your strategy.
Customizable Timeframes: On intraday charts, disable 1m or 4h if you don't trade them. Reduces calculation load by 20-40%.
Automatic HTF Handling: On Daily/Weekly/Monthly charts, the table automatically switches to D/W/M columns. No configuration needed.
Performance Smart: "Hide BIAS table on 1D or above" option completely skips all table calculations on higher timeframes if you only trade intraday.
---
6. CANDLESTICK PATTERN RECOGNITION
The indicator automatically detects six major reversal patterns and marks them with emojis at the relevant bars.
Why These Six Patterns:
These are the most statistically significant reversal patterns according to trading literature:
High win rate when appearing at support/resistance
Clear visual structure (not subjective)
Work across all timeframes and assets
Studied extensively by institutions
The Patterns:
Bullish Patterns (appear at bottoms):
Bullish Engulfing: Green candle completely engulfs prior red candle's body. Strong reversal signal.
Hammer: Small body with long lower wick (at least 2× body size). Shows rejection of lower prices by buyers.
Morning Star: Three-candle pattern (large red → small indecision → large green). Very strong bottom reversal.
Bearish Patterns (appear at tops):
Bearish Engulfing: Red candle completely engulfs prior green candle's body. Strong reversal signal.
Shooting Star: Small body with long upper wick (at least 2× body size). Shows rejection of higher prices by sellers.
Evening Star: Three-candle pattern (large green → small indecision → large red). Very strong top reversal.
Interactive Tooltips:
Unlike most pattern indicators that just draw shapes, this one is educational:
Hover your mouse over any pattern emoji
A tooltip appears explaining: what the pattern is, what it means, when it's most reliable, and how to trade it
No need to memorize - learn as you trade
Noise Filter:
"Min candle body % to filter noise" setting prevents false signals:
Patterns require minimum body size relative to price
Filters out tiny candles that don't represent real buying/selling pressure
Adjust based on asset volatility (higher % for crypto, lower for low-volatility stocks)
How to Trade Patterns:
Patterns are NOT standalone entry signals. Use them as:
Confirmation: UT Bot gives signal + pattern appears = stronger entry
Reversal Warning: In a trade, opposite pattern appears = consider tightening stop or taking profit
Support/Resistance Validation: Pattern at key level (PDH, VWAP, MA 200) = level is being respected
Best combined with:
UT Bot or Base signal in same direction
Bias Table alignment (AVG > 60% or < 40%)
Appearance at obvious support/resistance
---
7. VISUAL TOOLS AND FEATURES
VWAP (Volume Weighted Average Price):
Session-anchored VWAP with standard deviation bands. Shows institutional "fair value" for the trading session.
Anchor Options: Session, Day, Week, Month, Quarter, Year. Choose based on your trading timeframe.
Bands: Up to three pairs (X1, X2, X3) showing statistical deviation. Price at outer bands often reverses.
Auto-Hide on HTF: VWAP hides on Daily/Weekly/Monthly charts automatically unless you enable anchored mode.
Use VWAP as:
Directional bias (above = bullish, below = bearish)
Mean reversion levels (outer bands)
Support/resistance (the VWAP line itself)
Previous Day High/Low:
Automatically plots yesterday's high and low on intraday charts:
Updates at start of each new trading day
Theme-aware colors (dark text for light charts, light text for dark charts)
Hidden automatically on Daily/Weekly/Monthly charts
These levels are critical for intraday traders - institutions watch them closely as support/resistance.
Opening Range Breakout (ORB):
Tracks the high/low of the first 5, 15, 30, or 60 minutes of the trading session:
Customizable session times (preset for NYSE, LSE, TSE, or custom)
Shows current breakout status in Bias Table row (ABOVE, BELOW, INSIDE, BUILDING)
Intraday only - auto-disabled on Daily+ charts
ORB is a classic day trading strategy - breakout above opening range often leads to continuation.
Extra Labels:
Change from Open %: Shows how far price has moved from session open (intraday) or daily open (HTF). Green if positive, red if negative.
ADX Badge: Small label at bottom of last bar showing current ADX value. Green when above your minimum threshold, red when below.
RSI Badge: Small label at top of last bar showing current RSI value with zone status (buy zone, sell zone, or neutral).
These labels provide quick at-a-glance confirmation without needing separate indicator windows.
---
8. HOW TO USE THE INDICATOR
Step 1: Add to Chart
Load the indicator on your chosen asset and timeframe
First time: Everything is enabled by default - the chart will look busy
Don't panic - you'll turn off what you don't need
Step 2: Start Simple
Turn OFF everything except:
UT Bot labels (keep these ON)
Bias Table (keep this ON)
Moving Averages (Fast and Medium only)
Suggested Stop Loss and Take Profits
Hide everything else initially. Get comfortable with the basic UT Bot + Bias Table workflow first.
Step 3: Learn the Core Workflow
UT Bot gives a Buy or Sell signal
Check Bias Table AVG column - do you have multi-timeframe alignment?
If yes, enter the trade
Place stop at Suggested Stop Loss line
Scale out at TP levels
Exit on opposite UT signal
Trade this simple system for a week. Get a feel for signal frequency and win rate with your settings.
Step 4: Add Filters Gradually
If you're getting too many losing signals (whipsaws in choppy markets), add filters one at a time:
Try: "Require 2-Bar Trend Confirmation" - wait for 2 bars to confirm direction
Try: ADX filter with minimum threshold - only trade when trend strength is sufficient
Try: RSI pullback filter - only enter on pullbacks, not chasing
Try: Volume filter - require above-average volume
Add one filter, test for a week, evaluate. Repeat.
Step 5: Enable Advanced Features (Optional)
Once you're profitable with the core system, add:
Supertrend for additional trend confirmation
Candlestick patterns for reversal warnings
VWAP for institutional anchor reference
ORB for intraday breakout context
ZLSMA for low-lag trend following
Step 6: Optimize Settings
Every setting has a detailed tooltip explaining what it does and typical values. Hover over any input to read:
What the parameter controls
How it impacts trading
Suggested ranges for scalping, day trading, and swing trading
Start with defaults, then adjust based on your results and style.
Step 7: Set Up Alerts
Right-click chart → Add Alert → Condition: "Luxy Momentum v6" → Choose:
"UT Bot — Buy" for long entries
"UT Bot — Sell" for short entries
"Base Long/Short" for filtered MA cross signals
Optionally enable "Send real-time alert() on UT flip" in settings for immediate notifications.
Common Workflow Variations:
Conservative Trader:
UT signal + Base signal + Candlestick pattern + Bias AVG > 70%
Enter only at major support/resistance
Wider UT sensitivity, multiple filters
Aggressive Trader:
UT signal + Bias AVG > 60%
Enter immediately, no waiting
Tighter UT sensitivity, minimal filters
Swing Trader:
Focus on Daily/Weekly Bias alignment
Ignore intraday noise
Use ORB and PDH/PDL less (or not at all)
Wider stops, patient approach
---
9. PERFORMANCE AND OPTIMIZATION
The indicator is optimized for speed, but with 15+ features running simultaneously, chart load time can add up. Here's how to keep it fast:
Biggest Performance Gains:
Disable Unused Timeframes: In "Time Frames" settings, turn OFF any timeframe you don't actively trade. Each disabled TF saves 10-15% calculation time. If you only day trade 5m, 15m, 1h, disable 1m, 2h, 4h.
Hide Bias Table on Daily+: If you only trade intraday, enable "Hide BIAS table on 1D or above". This skips ALL table calculations on higher timeframes.
Draw UT Visuals Only on Bar Close: Reduces intrabar rendering of SL/TP/Entry lines. Has ZERO impact on logic or alerts - purely visual optimization.
Additional Optimizations:
Turn off VWAP bands if you don't use them
Disable candlestick patterns if you don't trade them
Turn off Supertrend fill if you find it distracting (keep the line)
Reduce "Limit to 10 bars" for SL/TP lines to minimize line objects
Performance Features Built-In:
Smart Caching: Higher timeframe data (3-day bias, weekly bias, etc.) updates once per day, not every bar
Conditional Calculations: Volume filter only calculates when enabled. Swing filter only runs when enabled. Nothing computes if turned off.
Modular Design: Every component is independent. Turn off what you don't need without breaking other features.
Typical Load Times:
5m chart, all features ON, 7 timeframes: ~2-3 seconds
5m chart, core features only, 3 timeframes: ~1 second
1m chart, all features: ~4-5 seconds (many bars to calculate)
If loading takes longer, you likely have too many indicators on the chart total (not just this one).
---
10. FAQ
Q: How is this different from standard UT Bot indicators?
A: Standard UT Bot (originally by @QuantNomad) is just the ATR trailing line and flip signals. This implementation adds:
- Volume weighting and momentum adjustment to the trailing calculation
- Multiple confirmation filters (swing, %, 2-bar, ZLSMA)
- Smart composite stop loss system from multiple S/R layers
- R-multiple take profit system with freeze-on-touch
- Integration with multi-timeframe Bias Table
- Visual audit trail with checkmarks
Q: Can I use this for automated trading?
A: The indicator is designed for discretionary trading. While it has clear signals and alerts, it's not a mechanical system. Context and judgment are required.
Q: Does it repaint?
A: No. All signals respect bar close. UT Bot logic runs intrabar but signals only trigger on confirmed bars. Alerts fire correctly with no lookahead.
Q: Do I need to use all the features?
A: Absolutely not. The indicator is modular. Many profitable traders use just UT Bot + Bias Table + Moving Averages. Start simple, add complexity only if needed.
Q: How do I know which settings to use?
A: Every single input has a detailed tooltip. Hover over any setting to see:
What it does
How it affects trading
Typical values for scalping, day trading, swing trading
Start with defaults, adjust gradually based on results.
Q: Can I use this on crypto 24/7 markets?
A: Yes. ORB will not work (no defined session), but everything else functions normally. Use "Day" anchor for VWAP instead of "Session".
Q: The Bias Table is blank or not showing.
A: Check:
"Show Table" is ON
Table position isn't overlapping another indicator's table (change position)
At least one row is enabled
"Hide BIAS table on 1D or above" is OFF (if on Daily+ chart)
Q: Why are candlestick patterns not appearing?
A: Patterns are relatively rare by design - they only appear at genuine reversal points. Check:
Pattern toggles are ON
"Min candle body %" isn't too high (try 0.05-0.10)
You're looking at a chart with actual reversals (not strong trending market)
Q: UT Bot is too sensitive/not sensitive enough.
A: Adjust "Sensitivity (Key×ATR)". Lower number = tighter stop, more signals. Higher number = wider stop, fewer signals. Read the tooltip for guidance.
Q: Can I get alerts for the Bias Table?
A: The Bias Table is a dashboard for visual analysis, not a signal generator. Set alerts on UT Bot or Base signals, then manually check Bias Table for confirmation.
Q: Does this work on stocks with low volume?
A: Yes, but turn OFF the volume filter. Low volume stocks will never meet relative volume requirements.
Q: How often should I check the Bias Table?
A: Before every entry. It takes 2 seconds to glance at the AVG column and headline rows. This one check can save you from fighting the trend.
Q: What if UT signal and Base signal disagree?
A: UT Bot is more aggressive (ATR trailing). Base signals are more conservative (MA cross + filters). If they disagree, either:
Wait for both to align (safest)
Take the UT signal but with smaller size (aggressive)
Skip the trade (conservative)
There's no "right" answer - depends on your risk tolerance.
---
FINAL NOTES
The indicator gives you an edge. How you use that edge determines results.
For questions, feedback, or support, comment on the indicator page or message the author.
Happy Trading!
RSI Donchian Channel [DCAUT]█ RSI Donchian Channel
📊 ORIGINALITY & INNOVATION
The RSI Donchian Channel represents an important synthesis of two complementary analytical frameworks: momentum oscillators and breakout detection systems. This indicator addresses a common limitation in traditional RSI analysis by replacing fixed overbought/oversold thresholds with adaptive zones derived from historical RSI extremes.
Key Enhancement:
Traditional RSI analysis relies on static threshold levels (typically 30/70), which may not adequately reflect changing market volatility regimes. This indicator adapts the reference zones dynamically based on the actual RSI behavior over the lookback period, helping traders identify meaningful momentum extremes relative to recent price action rather than arbitrary fixed levels.
The implementation combines the proven momentum measurement capabilities of RSI with Donchian Channel's breakout detection methodology, creating a framework that identifies both momentum exhaustion points and potential continuation signals through the same analytical lens.
📐 MATHEMATICAL FOUNDATION
Core Calculation Process:
Step 1: RSI Calculation
The Relative Strength Index measures momentum by comparing the magnitude of recent gains to recent losses:
Calculate price changes between consecutive periods
Separate positive changes (gains) from negative changes (losses)
Apply selected smoothing method (RMA standard, also supports SMA, EMA, WMA) to both gain and loss series
Compute Relative Strength (RS) as the ratio of smoothed gains to smoothed losses
Transform RS into bounded 0-100 scale using the formula: RSI = 100 - (100 / (1 + RS))
Step 2: Donchian Channel Application
The Donchian Channel identifies the highest and lowest RSI values within the specified lookback period:
Upper Channel: Highest RSI value over the lookback period, represents the recent momentum peak
Lower Channel: Lowest RSI value over the lookback period, represents the recent momentum trough
Middle Channel (Basis): Average of upper and lower channels, serves as equilibrium reference
Channel Width Dynamics:
The distance between upper and lower channels reflects RSI volatility. Wide channels indicate high momentum variability, while narrow channels suggest momentum consolidation and potential breakout preparation. The indicator monitors channel width over a 100-period window to identify squeeze conditions that often precede significant momentum shifts.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Primary Signal Categories:
Breakout Signals:
Upper Breakout: RSI crosses above the upper channel, indicates momentum reaching new relative highs and potential trend continuation, particularly significant when accompanied by price confirmation
Lower Breakout: RSI crosses below the lower channel, suggests momentum reaching new relative lows and potential trend exhaustion or reversal setup
Breakout strength is enhanced when the channel is narrow prior to the breakout, indicating a transition from consolidation to directional movement
Mean Reversion Signals:
Upper Touch Without Breakout: RSI reaches the upper channel but fails to break through, may indicate momentum exhaustion and potential reversal opportunity
Lower Touch Without Breakout: RSI reaches the lower channel without breakdown, suggests potential bounce as momentum reaches oversold extremes
Return to Basis: RSI moving back toward the middle channel after touching extremes signals momentum normalization
Trend Strength Assessment:
Sustained Upper Channel Riding: RSI consistently remains near or above the upper channel during strong uptrends, indicates persistent bullish momentum
Sustained Lower Channel Riding: RSI stays near or below the lower channel during strong downtrends, reflects persistent bearish pressure
Basis Line Position: RSI position relative to the middle channel helps identify the prevailing momentum bias
Channel Compression Patterns:
Squeeze Detection: Channel width narrowing to 100-period lows indicates momentum consolidation, often precedes significant directional moves
Expansion Phase: Channel widening after a squeeze confirms the initiation of a new momentum regime
Persistent Narrow Channels: Extended periods of tight channels suggest market indecision and accumulation/distribution phases
🎯 STRATEGIC APPLICATIONS
Trend Continuation Strategy:
This approach focuses on identifying and trading momentum breakouts that confirm established trends:
Identify the prevailing price trend using higher timeframe analysis or trend-following indicators
Wait for RSI to break above the upper channel in uptrends (or below the lower channel in downtrends)
Enter positions in the direction of the breakout when price action confirms the momentum shift
Place protective stops below the recent swing low (long positions) or above swing high (short positions)
Target profit levels based on prior swing extremes or use trailing stops to capture extended moves
Exit when RSI crosses back through the basis line in the opposite direction
Mean Reversion Strategy:
This method capitalizes on momentum extremes and subsequent corrections toward equilibrium:
Monitor for RSI reaching the upper or lower channel boundaries
Look for rejection signals (price reversal patterns, volume divergence) when RSI touches the channels
Enter counter-trend positions when RSI begins moving back toward the basis line
Use the basis line as the initial profit target for mean reversion trades
Implement tight stops beyond the channel extremes to limit risk on failed reversals
Scale out of positions as RSI approaches the basis line and closes the position when RSI crosses the basis
Breakout Preparation Strategy:
This approach positions traders ahead of potential volatility expansion from consolidation phases:
Identify squeeze conditions when channel width reaches 100-period lows
Monitor price action for consolidation patterns (triangles, rectangles, flags) during the squeeze
Prepare conditional orders for breakouts in both directions from the consolidation
Enter positions when RSI breaks out of the narrow channel with expanding width
Use the channel width expansion as a confirmation signal for the breakout's validity
Manage risk with stops just inside the opposite channel boundary
Multi-Timeframe Confluence Strategy:
Combining RSI Donchian Channel analysis across multiple timeframes can improve signal reliability:
Identify the primary trend direction using a higher timeframe RSI Donchian Channel (e.g., daily or weekly)
Use a lower timeframe (e.g., 4-hour or hourly) to time precise entry points
Enter long positions when both timeframes show RSI above their respective basis lines
Enter short positions when both timeframes show RSI below their respective basis lines
Avoid trades when timeframes provide conflicting signals (e.g., higher timeframe below basis, lower timeframe above)
Exit when the higher timeframe RSI crosses its basis line in the opposite direction
Risk Management Guidelines:
Effective risk management is essential for all RSI Donchian Channel strategies:
Position Sizing: Calculate position sizes based on the distance between entry point and stop loss, limiting risk to 1-2% of capital per trade
Stop Loss Placement: For breakout trades, place stops just inside the opposite channel boundary; for mean reversion trades, use stops beyond the channel extremes
Profit Targets: Use the basis line as a minimum target for mean reversion trades; for trend trades, target prior swing extremes or use trailing stops
Channel Width Context: Increase position sizes during narrow channels (lower volatility) and reduce sizes during wide channels (higher volatility)
Correlation Awareness: Monitor correlations between traded instruments to avoid over-concentration in similar setups
📋 DETAILED PARAMETER CONFIGURATION
RSI Source:
Defines the price data series used for RSI calculation:
Close (Default): Standard choice providing end-of-period momentum assessment, suitable for most trading styles and timeframes
High-Low Average (HL2): Reduces the impact of closing auction dynamics, useful for markets with significant end-of-day volatility
High-Low-Close Average (HLC3): Provides a more balanced view incorporating the entire period's range
Open-High-Low-Close Average (OHLC4): Offers the most comprehensive price representation, helpful for identifying overall period sentiment
Strategy Consideration: Use Close for end-of-period signals, HL2 or HLC3 for intraday volatility reduction, OHLC4 for capturing full period dynamics
RSI Length:
Controls the number of periods used for RSI calculation:
Short Periods (5-9): Highly responsive to recent price changes, produces more frequent signals with increased false signal risk, suitable for short-term trading and volatile markets
Standard Period (14): Widely accepted default balancing responsiveness with stability, appropriate for swing trading and intermediate-term analysis
Long Periods (21-28): Produces smoother RSI with fewer signals but more reliable trend identification, better for position trading and reducing noise in choppy markets
Optimization Approach: Test different lengths against historical data for your specific market and timeframe, consider using longer periods in ranging markets and shorter periods in trending markets
RSI MA Type:
Determines the smoothing method applied to price changes in RSI calculation:
RMA (Relative Moving Average - Default): Wilder's original smoothing method providing stable momentum measurement with gradual response to changes, maintains consistency with classical RSI interpretation
SMA (Simple Moving Average): Treats all periods equally, responds more quickly to changes than RMA but may produce more whipsaws in volatile conditions
EMA (Exponential Moving Average): Weights recent periods more heavily, increases responsiveness at the cost of potential noise, suitable for traders prioritizing early signal generation
WMA (Weighted Moving Average): Applies linear weighting favoring recent data, offers a middle ground between SMA and EMA responsiveness
Selection Guidance: Maintain RMA for consistency with traditional RSI analysis, use EMA or WMA for more responsive signals in fast-moving markets, apply SMA for maximum simplicity and transparency
DC Length:
Specifies the lookback period for Donchian Channel calculation on RSI values:
Short Periods (10-14): Creates tight channels that adapt quickly to changing momentum conditions, generates more frequent trading signals but increases sensitivity to short-term RSI fluctuations
Standard Period (20): Balances channel responsiveness with stability, aligns with traditional Bollinger Bands and moving average periods, suitable for most trading styles
Long Periods (30-50): Produces wider, more stable channels that better represent sustained momentum extremes, reduces signal frequency while improving reliability, appropriate for position traders and higher timeframes
Calibration Strategy: Match DC length to your trading timeframe (shorter for day trading, longer for swing trading), test channel width behavior during different market regimes, consider using adaptive periods that adjust to volatility conditions
Market Adaptation: Use shorter DC lengths in trending markets to capture momentum shifts earlier, apply longer periods in ranging markets to filter noise and focus on significant extremes
Parameter Combination Recommendations:
Scalping/Day Trading: RSI Length 5-9, DC Length 10-14, EMA or WMA smoothing for maximum responsiveness
Swing Trading: RSI Length 14, DC Length 20, RMA smoothing for balanced analysis (default configuration)
Position Trading: RSI Length 21-28, DC Length 30-50, RMA or SMA smoothing for stable signals
High Volatility Markets: Longer RSI periods (21+) with standard DC length (20) to reduce noise
Low Volatility Markets: Standard RSI length (14) with shorter DC length (10-14) to capture subtle momentum shifts
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Adaptive Threshold Mechanism:
Unlike traditional RSI analysis with fixed 30/70 thresholds, this indicator's Donchian Channel approach provides several improvements:
Context-Aware Extremes: Overbought/oversold levels adjust automatically based on recent momentum behavior rather than arbitrary fixed values
Volatility Adaptation: In low volatility periods, channels narrow to reflect tighter momentum ranges; in high volatility, channels widen appropriately
Market Regime Recognition: The indicator implicitly adapts to different market conditions without manual threshold adjustments
False Signal Reduction: Adaptive channels help reduce premature reversal signals that often occur with fixed thresholds during strong trends
Signal Quality Characteristics:
The indicator's dual-purpose design provides distinct advantages for different trading objectives:
Breakout Trading: Channel boundaries offer clear, objective breakout levels that update dynamically, eliminating the ambiguity of when momentum becomes "too high" or "too low"
Mean Reversion: The basis line provides a natural profit target for reversion trades, representing the midpoint of recent momentum extremes
Trend Strength: Persistent channel boundary riding offers an objective measure of trend strength without additional indicators
Consolidation Detection: Channel width analysis provides early warning of potential volatility expansion from compression phases
Comparative Analysis:
When compared to traditional RSI implementations and other momentum frameworks:
vs. Fixed Threshold RSI: Provides market-adaptive reference levels rather than static values, helping to reduce false signals during trending markets where RSI can remain "overbought" or "oversold" for extended periods
vs. RSI Bollinger Bands: Offers clearer breakout signals and more intuitive extreme identification through actual high/low boundaries rather than statistical standard deviations
vs. Stochastic Oscillator: Maintains RSI's momentum measurement advantages (unbounded calculation avoiding scale compression) while adding the breakout detection capabilities of Donchian Channels
vs. Standard Donchian Channels: Applies breakout methodology to momentum space rather than price, providing earlier signals of potential trend changes before price breakouts occur
Performance Characteristics:
The indicator exhibits specific behavioral patterns across different market conditions:
Trending Markets: Excels at identifying momentum continuation through channel breakouts, RSI tends to ride one channel boundary during strong trends, providing trend confirmation
Ranging Markets: Channel width narrows during consolidation, offering early preparation signals for potential breakout trading opportunities
High Volatility: Channels widen to reflect increased momentum variability, automatically adjusting signal sensitivity to match market conditions
Low Volatility: Channels contract, making the indicator more sensitive to subtle momentum shifts that may be significant in calm market environments
Transition Periods: Channel squeezes often precede major trend changes, offering advance warning of potential regime shifts
Limitations and Considerations:
Users should be aware of certain operational characteristics:
Lookback Dependency: Channel boundaries depend entirely on the lookback period, meaning the indicator has no predictive element beyond identifying current momentum relative to recent history
Lag Characteristics: As with all moving average-based indicators, RSI calculation introduces lag, and channel boundaries update only as new extremes occur within the lookback window
Range-Bound Sensitivity: In extremely tight ranges, channels may become very narrow, potentially generating excessive signals from minor momentum fluctuations
Trending Persistence: During very strong trends, RSI may remain at channel extremes for extended periods, requiring patience for mean reversion setups or commitment to trend-following approaches
No Absolute Levels: Unlike traditional RSI, this indicator provides no fixed reference points (like 50), making it less suitable for strategies that depend on absolute momentum readings
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to help traders understand momentum dynamics and identify potential trading opportunities. The RSI Donchian Channel has limitations and should not be used as the sole basis for trading decisions.
Important considerations:
Performance varies significantly across different market conditions, timeframes, and instruments
Historical signal patterns do not guarantee future results, as market behavior continuously evolves
Effective use requires understanding of both RSI momentum principles and Donchian Channel breakout concepts
Risk management practices (stop losses, position sizing, diversification) are essential for any trading application
Consider combining with additional analytical tools such as volume analysis, price action patterns, or trend indicators for confirmation
Backtest thoroughly on your specific instruments and timeframes before live trading implementation
Be aware that optimization on historical data may lead to curve-fitting and poor forward performance
The indicator performs best when used as part of a comprehensive trading methodology that incorporates multiple forms of market analysis, sound risk management, and realistic expectations about win rates and drawdowns.
MACD Enhanced [DCAUT]█ MACD Enhanced
📊 ORIGINALITY & INNOVATION
The MACD Enhanced represents a significant improvement over traditional MACD implementations. While Gerald Appel's original MACD from the 1970s was limited to exponential moving averages (EMA), this enhanced version expands algorithmic options by supporting 21 different moving average calculations for both the main MACD line and signal line independently.
This improvement addresses an important limitation of traditional MACD: the inability to adapt the indicator's mathematical foundation to different market conditions. By allowing traders to select from algorithms ranging from simple moving averages (SMA) for stability to advanced adaptive filters like Kalman Filter for noise reduction, this implementation changes MACD from a fixed-algorithm tool into a flexible instrument that can be adjusted for specific market environments and trading strategies.
The enhanced histogram visualization system uses a four-color gradient that helps communicate momentum strength and direction more clearly than traditional single-color histograms.
📐 MATHEMATICAL FOUNDATION
The core calculation maintains the proven MACD formula: Fast MA(source, fastLength) - Slow MA(source, slowLength), but extends it with algorithmic flexibility. The signal line applies the selected smoothing algorithm to the MACD line over the specified signal period, while the histogram represents the difference between MACD and signal lines.
Available Algorithms:
The implementation supports a comprehensive spectrum of technical analysis algorithms:
Basic Averages: SMA (arithmetic mean), EMA (exponential weighting), RMA (Wilder's smoothing), WMA (linear weighting)
Advanced Averages: HMA (Hull's low-lag), VWMA (volume-weighted), ALMA (Arnaud Legoux adaptive)
Mathematical Filters: LSMA (least squares regression), DEMA (double exponential), TEMA (triple exponential), ZLEMA (zero-lag exponential)
Adaptive Systems: T3 (Tillson T3), FRAMA (fractal adaptive), KAMA (Kaufman adaptive), MCGINLEY_DYNAMIC (reactive to volatility)
Signal Processing: ULTIMATE_SMOOTHER (low-pass filter), LAGUERRE_FILTER (four-pole IIR), SUPER_SMOOTHER (two-pole Butterworth), KALMAN_FILTER (state-space estimation)
Specialized: TMA (triangular moving average), LAGUERRE_BINOMIAL_FILTER (binomial smoothing)
Each algorithm responds differently to price action, allowing traders to match the indicator's behavior to market characteristics: trending markets benefit from responsive algorithms like EMA or HMA, while ranging markets require stable algorithms like SMA or RMA.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Histogram Interpretation:
Positive Values: Indicate bullish momentum when MACD line exceeds signal line, suggesting upward price pressure and potential buying opportunities
Negative Values: Reflect bearish momentum when MACD line falls below signal line, indicating downward pressure and potential selling opportunities
Zero Line Crosses: MACD crossing above zero suggests transition to bullish bias, while crossing below indicates bearish bias shift
Momentum Changes: Rising histogram (regardless of positive/negative) signals accelerating momentum in the current direction, while declining histogram warns of momentum deceleration
Advanced Signal Recognition:
Divergences: Price making new highs/lows while MACD fails to confirm often precedes trend reversals
Convergence Patterns: MACD line approaching signal line suggests impending crossover and potential trade setup
Histogram Peaks: Extreme histogram values often mark momentum exhaustion points and potential reversal zones
🎯 STRATEGIC APPLICATIONS
Comprehensive Trend Confirmation Strategies:
Primary Trend Validation Protocol:
Identify primary trend direction using higher timeframe (4H or Daily) MACD position relative to zero line
Confirm trend strength by analyzing histogram progression: consistent expansion indicates strong momentum, contraction suggests weakening
Use secondary confirmation from MACD line angle: steep angles (>45°) indicate strong trends, shallow angles suggest consolidation
Validate with price structure: trending markets show consistent higher highs/higher lows (uptrend) or lower highs/lower lows (downtrend)
Entry Timing Techniques:
Pullback Entries in Uptrends: Wait for MACD histogram to decline toward zero line without crossing, then enter on histogram expansion with MACD line still above zero
Breakout Confirmations: Use MACD line crossing above zero as confirmation of upward breakouts from consolidation patterns
Continuation Signals: Look for MACD line re-acceleration (steepening angle) after brief consolidation periods as trend continuation signals
Advanced Divergence Trading Systems:
Regular Divergence Recognition:
Bullish Regular Divergence: Price creates lower lows while MACD line forms higher lows. This pattern is traditionally considered a potential upward reversal signal, but should be combined with other confirmation signals
Bearish Regular Divergence: Price makes higher highs while MACD shows lower highs. This pattern is traditionally considered a potential downward reversal signal, but trading decisions should incorporate proper risk management
Hidden Divergence Strategies:
Bullish Hidden Divergence: Price shows higher lows while MACD displays lower lows, indicating trend continuation potential. Use for adding to existing long positions during pullbacks
Bearish Hidden Divergence: Price creates lower highs while MACD forms higher highs, suggesting downtrend continuation. Optimal for adding to short positions during bear market rallies
Multi-Timeframe Coordination Framework:
Three-Timeframe Analysis Structure:
Primary Timeframe (Daily): Determine overall market bias and major trend direction. Only trade in alignment with daily MACD direction
Secondary Timeframe (4H): Identify intermediate trend changes and major entry opportunities. Use for position sizing decisions
Execution Timeframe (1H): Precise entry and exit timing. Look for MACD line crossovers that align with higher timeframe bias
Timeframe Synchronization Rules:
Daily MACD above zero + 4H MACD rising = Strong uptrend context for long positions
Daily MACD below zero + 4H MACD declining = Strong downtrend context for short positions
Conflicting signals between timeframes = Wait for alignment or use smaller position sizes
1H MACD signals only valid when aligned with both higher timeframes
Algorithm Considerations by Market Type:
Trending Markets: Responsive algorithms like EMA, HMA may be considered, but effectiveness should be tested for specific market conditions
Volatile Markets: Noise-reducing algorithms like KALMAN_FILTER, SUPER_SMOOTHER may help reduce false signals, though results vary by market
Range-Bound Markets: Stability-focused algorithms like SMA, RMA may provide smoother signals, but individual testing is required
Short Timeframes: Low-lag algorithms like ZLEMA, T3 theoretically respond faster but may also increase noise
Important Note: All algorithm choices and parameter settings should be thoroughly backtested and validated based on specific trading strategies, market conditions, and individual risk tolerance. Different market environments and trading styles may require different configuration approaches.
📋 DETAILED PARAMETER CONFIGURATION
Comprehensive Source Selection Strategy:
Price Source Analysis and Optimization:
Close Price (Default): Most commonly used, reflects final market sentiment of each period. Best for end-of-day analysis, swing trading, daily/weekly timeframes. Advantages: widely accepted standard, good for backtesting comparisons. Disadvantages: ignores intraday price action, may miss important highs/lows
HL2 (High+Low)/2: Midpoint of the trading range, reduces impact of opening gaps and closing spikes. Best for volatile markets, gap-prone assets, forex markets. Calculation impact: smoother MACD signals, reduced noise from price spikes. Optimal when asset shows frequent gaps, high volatility during specific sessions
HLC3 (High+Low+Close)/3: Weighted average emphasizing the close while including range information. Best for balanced analysis, most asset classes, medium-term trading. Mathematical effect: 33% weight to high/low, 33% to close, provides compromise between close and HL2. Use when standard close is too noisy but HL2 is too smooth
OHLC4 (Open+High+Low+Close)/4: True average of all price points, most comprehensive view. Best for complete price representation, algorithmic trading, statistical analysis. Considerations: includes opening sentiment, smoothest of all options but potentially less responsive. Optimal for markets with significant opening moves, comprehensive trend analysis
Parameter Configuration Principles:
Important Note: Different moving average algorithms have distinct mathematical characteristics and response patterns. The same parameter settings may produce vastly different results when using different algorithms. When switching algorithms, parameter settings should be re-evaluated and tested for appropriateness.
Length Parameter Considerations:
Fast Length (Default 12): Shorter periods provide faster response but may increase noise and false signals, longer periods offer more stable signals but slower response, different algorithms respond differently to the same parameters and may require adjustment
Slow Length (Default 26): Should maintain a reasonable proportional relationship with fast length, different timeframes may require different parameter configurations, algorithm characteristics influence optimal length settings
Signal Length (Default 9): Shorter lengths produce more frequent crossovers but may increase false signals, longer lengths provide better signal confirmation but slower response, should be adjusted based on trading style and chosen algorithm characteristics
Comprehensive Algorithm Selection Framework:
MACD Line Algorithm Decision Matrix:
EMA (Standard Choice): Mathematical properties: exponential weighting, recent price emphasis. Best for general use, traditional MACD behavior, backtesting compatibility. Performance characteristics: good balance of speed and smoothness, widely understood behavior
SMA (Stability Focus): Equal weighting of all periods, maximum smoothness. Best for ranging markets, noise reduction, conservative trading. Trade-offs: slower signal generation, reduced sensitivity to recent price changes
HMA (Speed Optimized): Hull Moving Average, designed for reduced lag. Best for trending markets, quick reversals, active trading. Technical advantage: square root period weighting, faster trend detection. Caution: can be more sensitive to noise
KAMA (Adaptive): Kaufman Adaptive MA, adjusts smoothing based on market efficiency. Best for varying market conditions, algorithmic trading. Mechanism: fast smoothing in trends, slow smoothing in sideways markets. Complexity: requires understanding of efficiency ratio
Signal Line Algorithm Optimization Strategies:
Matching Strategy: Use same algorithm for both MACD and signal lines. Benefits: consistent mathematical properties, predictable behavior. Best when backtesting historical strategies, maintaining traditional MACD characteristics
Contrast Strategy: Use different algorithms for optimization. Common combinations: MACD=EMA, Signal=SMA for smoother crossovers, MACD=HMA, Signal=RMA for balanced speed/stability, Advanced: MACD=KAMA, Signal=T3 for adaptive behavior with smooth signals
Market Regime Adaptation: Trending markets: both fast algorithms (EMA/HMA), Volatile markets: MACD=KALMAN_FILTER, Signal=SUPER_SMOOTHER, Range-bound: both slow algorithms (SMA/RMA)
Parameter Sensitivity Considerations:
Impact of Parameter Changes:
Length Parameter Sensitivity: Small parameter adjustments can significantly affect signal timing, while larger adjustments may fundamentally change indicator behavior characteristics
Algorithm Sensitivity: Different algorithms produce different signal characteristics. Thoroughly test the impact on your trading strategy before switching algorithms
Combined Effects: Changing multiple parameters simultaneously can create unexpected effects. Recommendation: adjust parameters one at a time and thoroughly test each change
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Response Characteristics by Algorithm:
Fastest Response: ZLEMA, HMA, T3 - minimal lag but higher noise
Balanced Performance: EMA, DEMA, TEMA - good trade-off between speed and stability
Highest Stability: SMA, RMA, TMA - reduced noise but increased lag
Adaptive Behavior: KAMA, FRAMA, MCGINLEY_DYNAMIC - automatically adjust to market conditions
Noise Filtering Capabilities:
Advanced algorithms like KALMAN_FILTER and SUPER_SMOOTHER help reduce false signals compared to traditional EMA-based MACD. Noise-reducing algorithms can provide more stable signals in volatile market conditions, though results will vary based on market conditions and parameter settings.
Market Condition Adaptability:
Unlike fixed-algorithm MACD, this enhanced version allows real-time optimization. Trending markets benefit from responsive algorithms (EMA, HMA), while ranging markets perform better with stable algorithms (SMA, RMA). The ability to switch algorithms without changing indicators provides greater flexibility.
Comparative Performance vs Traditional MACD:
Algorithm Flexibility: 21 algorithms vs 1 fixed EMA
Signal Quality: Reduced false signals through noise filtering algorithms
Market Adaptability: Optimizable for any market condition vs fixed behavior
Customization Options: Independent algorithm selection for MACD and signal lines vs forced matching
Professional Features: Advanced color coding, multiple alert conditions, comprehensive parameter control
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions. Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always combine with proper risk management and thorough strategy testing.
cd_VWAP_mtg_CxCd_VWAP_mtg_Cx
Overview
The most important condition for being successful and profitable in the market is to consistently follow the same rules without compromise, while the price constantly moves in countless different ways.
Regardless of the concept or trading school, those who have rules win.
In this indicator, we will define and use three main sections to set and apply our rules.
The indicator uses the VWAP (Volume Weighted Average Price) — price weighted by volume.
Two VWAPs can be displayed either by manually entering date and time, or by selecting from the menu.
From the menu, you can select the following reference levels:
• HTF Open: Opening candle of the higher timeframe
• ATH / ATL: All-Time High / All-Time Low candles
• PMH / PML, PWH / PWL, PDH / PDL, PH4H / PH4L: Previous Month, Week, Day, or H4 Highs/Lows
• MH / ML, WH / WL, DH / DL, H4H / H4L: Current Month, Week, Day, or H4 Highs/Lows
Additionally, it includes:
• Mitigation / Order Block zones (local buyer-seller balance) across two timeframes.
• Buy/Sell Side Liquidity levels (BSL / SSL) from the aligned higher timeframe (target levels).
________________________________________
Components and Usage
1 – VWAP
Calculated using the classical method:
• High + Volume for the upper value
• Close + Volume for the middle value
• Low + Volume for the lower value
The VWAP is displayed as a colored band, where the coloring represents the bias.
Let’s call this band FVB (Fair Value Band) for ease of explanation.
The FVB represents the final line of defense, the buyer/seller boundary, and in technical terms, it can be viewed as premium/discount zones or support/resistance levels.
Within this critical area, the strong side continues its move, while the weaker side is forced to retreat.
But does the side that breaks beyond the band always keep going?
We all know that’s not always the case — in different pairs and timeframes, price often violates both the upper and lower edges multiple times.
To achieve more consistent analysis, we’ll define a new set of rules.
________________________________________
2 – Mitigation / Order Blocks
In trading literature, there are dozens of different definitions and uses of mitigation or order blocks.
Here, we will interpret the candlesticks to create our own definition, and we’ll use the zones defined by candles that fit this pattern.
For simplicity, let’s abbreviate mitigation as “mtg.”
For a candle to be selected as an mtg, it must clearly show strength from one side (buyers or sellers) — which can also be observed visually on the chart.
________________________________________
Bullish mtg criteria:
1. The first candle must be bullish (close > open) → buyers are strong.
2. The next candle makes a new high (buyers push higher) but fails to close above and pulls back to close inside the previous range → sellers react.
It also must not break the previous low → buyers defend.
3. In the following candle(s), as long as the first candle’s low is protected and the second candle’s high is broken, it indicates buyer strength → a bullish mtg is confirmed.
When price returns to this zone later (gets mitigated), the expectation is that the zone holds and price pushes upward again.
If the low is violated, the mtg becomes invalid.
In technical terms:
If the previous candle’s high is broken but no close occurs above it, the expectation is a reversal move that will retest its low.
Question:
What if the low is protected and in the next candle(s) a new high forms?
Answer: → Bullish mtg.
Bearish mtg (opposite)
3 – Buy/Sell Side Liquidity Levels
With the help of the aligned higher timeframe (swing points), we will define our market structure framework and set our liquidity targets accordingly.
Let’s put the pieces together.
If we continue explaining from a trade-focused perspective, our first priority should be our bias — our projection or expectation of the market’s potential movement.
We will determine this bias using the FVB.
Since we know the band often gets violated on both sides, we want the price action to convince us of its strength.
To do that, we’ll use the first candle that closes beyond the band.
The distance from that candle’s high to low will be our threshold range
Bullish level = high + (candle length × coefficient)
Bearish level = low - (candle length × coefficient)
When the price closes beyond this threshold, it demonstrates strength, and our bias will now align in that direction.
How long will this bias remain valid?
→ Until a closing candle appears on the opposite side of the band.
If a close occurs on the opposite side, then a new bias will only be confirmed once the new threshold level is broken.
During the period in between, we have no bias.
Let’s continue on the chart:
Now that our bias has been established, where and how do we look for trade opportunities?
There are two possible entry approaches:
• Aggressive entry: Enter immediately with the breakout.
• Conservative entry: Wait for a pullback and enter once a suitable structure forms.
(The choice depends on the user’s preference.)
At this stage, the user can apply their own entry model. Let’s give an example:
Let’s assume we’re looking for setups using HTF sweep + LTF CISD confirmation.
Once our bias turns bearish, we look for an HTF sweep forming on or near an FVB or mtg block, and then confirm the entry with a CISD signal.
In summary:
• FVB defines the bias, the entry zone, and the target zone.
• Mtg blocks represent entry zones.
• BSL / SSL levels suggest target zones.
Overlapping FVB and mtg blocks are expected to be more effective.
The indicator also provides an option for a second FVB.
A band attached to a lower timeframe can be used as confirmation.
• Main band: Bias + FVB
• Extra band: Entry trigger confirmed by a close beyond it.
Mtg blocks can provide trade entry opportunities, especially when the price is moving strongly in one direction (flow).
Consecutive or complementary mtg blocks indicate that the price is decisive in one direction, while sometimes also showing areas where we should wait before entering.
Mtg blocks that contain an FVG (Fair Value Gap) within their body are expected to be more effective.
Settings:
The default values are set to 1-3-5m, optimized for scalping trades.
VWAP settings:
Main VWAP (FVB):
• Can be set by selecting a start time, manually entering date and time, or choosing a predefined level.
Extra VWAP (FVB):
• Set from the menu. If not needed, select “none.”
• Visibility, color, and fill settings for VWAP are located here.
• Threshold levels visibility and color options are also in this section.
• The multiplier is used for calculating the threshold level.
Important:
• If the Extra VWAP is selected but not displayed, you need to increase the chart timeframe.
o Example: If the chart is on 3m and you select WH from the extra options, it will not display correctly.
• Upper limits for VWAP:
o 1m and 3m charts: daily High/Low
o 5m chart: weekly High/Low
________________________________________
Mtg Settings:
• Visibility and color settings for blocks are configured here.
• To display on a second timeframe, the box must be checked and the timeframe specified.
• Optional display modes: “only active blocks,” “only last violated mtg,” or “all.”
• For confirmation and removal criteria, choosing high/low or close determines the source used for mtg block formation and deletion conditions.
BSL/SSL Settings:
• Visibility, color, font size, and line style can be configured in this section.
When “Auto” is selected, the aligned timeframe is determined automatically by the indicator, while in manual mode, the user defines the timeframe.
Final Words:
Simply opening trades every time the price touches the VWAP or mtg blocks will not make you a profitable trader. Searching for setups with similar structures while maintaining proper risk management will yield better results in the long run.
I would be happy to hear your feedback and suggestions.
Happy trading!
Trend lines indicator by ForexBeeEnhanced 3-Swing Trendline Zones - Complete Feature Guide
WHAT THIS INDICATOR DOES
This indicator automatically draws trendline zones on your chart using a 3-point validation system. Instead of just connecting any two price points like basic trendline tools, it waits for three swing points to confirm the trendline is valid before drawing it.
FEATURE 1: SWING POINT DETECTION
What it detects:
Swing highs: Price points where the high is higher than surrounding candles
Swing lows: Price points where the low is lower than surrounding candles
These show up as small arrows on your chart labeled "SH" (swing high) and "SL" (swing low)
Settings that control this:
Swing Length : Default is 6, range 1-20
Higher numbers = fewer, more significant swing points
Lower numbers = more swing points, including minor ones
Example: Setting 5 means each swing point must be higher/lower than 5 candles on each side
How to use this setting:
On 1-minute charts: Use 5-10 to filter out noise
On daily charts: Use 2-3 for more sensitivity
Volatile markets: Increase the number
Quiet markets: Decrease the number
Please See the Below Images To See the difference of swing length of 6 and 8
Display control:
Show Swing Points : Turn the arrows on/off
Default: ON (you'll see the arrows)
Turn OFF if arrows clutter your chart
FEATURE 2: RETRACEMENT VALIDATION SYSTEM
What this does:
After finding two swing points, the system checks if the second swing represents a proper market retracement, not just random price movement.
How it works:
Finds the highest point between two swing lows (or lowest point between two swing highs)
Calculates how much the second swing retraced from this extreme point
Only accepts swings that retrace between your set percentages
Settings that control this:
Lower Limit % : Default 50%, range 0-100%
Upper Limit % : Default 90%, range 0-100%
These create a "valid retracement zone"
Why this matters:
Eliminates random trendlines that don't follow market structure
Ensures trendlines represent actual retracement patterns
Based on Elliott Wave and Fibonacci principles
FEATURE 3: ATR-BASED ZONE WIDTH
What ATR means:
Average True Range measures how much price typically moves in a given period. Instead of fixed-width trendlines, this creates zones that adapt to market volatility.
Settings that control this:
Zone Width (ATR Multiple) : Default 0.3, range 0.1-1.0
ATR Length : Default 14, range 1-50 periods
How zone width works:
Multiplier 0.1 = Very narrow zones (tight around trendline)
Multiplier 0.5 = Medium zones
Multiplier 1.0 = Wide zones (accommodates more price movement)
ATR Length explained:
14 periods = Uses last 14 candles to calculate average volatility
Shorter periods (7) = More sensitive to recent volatility changes
Longer periods (21) = Smoother, less sensitive to volatility spikes
Practical impact:
During high volatility: Zones automatically become wider
During low volatility: Zones automatically become narrower
Prevents false breakouts during normal market noise
Creates realistic support/resistance areas instead of precise lines
FEATURE 4: VISUAL ZONE SYSTEM
Active Uptrend Zones:
Green upper boundary line (solid, thick)
Lime green lower boundary line (solid, thick)
Green fill between lines (80% transparency)
These represent dynamic support levels
Active Downtrend Zones:
Blue upper boundary line (solid, thick)
Navy blue lower boundary line (solid, thick)
Red fill between lines (80% transparency)
These represent dynamic resistance levels
Broken/Expired Zones:
Gray/silver boundary lines (dashed, thick)
Original fill color maintained (green for uptrend zones, red for downtrend zones)
Shows historical trendlines that are no longer active
FEATURE 5: BREAK DETECTION SYSTEM
How breaks are detected:
The system monitors when price violates the zone boundaries, indicating the trendline structure has failed.
Settings that control this:
Use Wick Break : True/False toggle
TRUE: Break occurs when candle high/low touches zone boundary
FALSE: Break occurs when candle close price crosses zone boundary
Conservative vs Aggressive approach:
Wick Break = TRUE (Aggressive) :
- More sensitive, earlier signals
- May produce more false breaks during volatile periods
- Good for scalping and short-term trading
Wick Break = FALSE (Conservative) :
- Requires candle to close beyond zone
- Fewer false signals, more reliable breaks
- Better for swing trading and position trading
What happens when zone breaks:
Zone lines change from solid to dashed
Zone lines change color to gray/silver
Fill color remains original (green/red) for identification
Zone stops extending forward
Zone is removed from active monitoring
FEATURE 6: ZONE EXPIRATION SYSTEM
What expiration does:
Allows trendlines to automatically become inactive after a set number of bars, even if they haven't been broken.
Settings that control this:
Use Zone Expiration : True/False toggle
Zone Expiration (Bars) : Default 500, range 1-1000
FALSE: Zones run indefinitely until broken
TRUE: Zones expire after specified number of bars
Visual result:
Expired zones look identical to broken zones
Lines become dashed and gray/silver
Fill colors remain original (green/red)
FEATURE 7: MULTI-TIMEFRAME TREND ANALYSIS TABLE
What the table shows:
A small table on your chart that monitors trend conditions across four different timeframes simultaneously.
Settings that control this:
TF1, TF2, TF3, TF4 : Four customizable timeframes
Default: 4H, 8H, 1D, 1W
Table Position : 9 positions (top/middle/bottom + left/center/right)
Text Size : Tiny, Small, Normal, Large, Huge
How trend detection works:
Uptrend Pattern : Current candle's high AND low are both higher than previous candle's high AND low on specified timeframes
This creates higher highs and higher lows
Shows consistent buying pressure
Table displays green background with upward arrow (▲)
Downtrend Pattern : Current candle's high AND low are both lower than previous candle's high AND low on specified timeframes
This creates lower highs and lower lows
Shows consistent selling pressure
Table displays red background with downward arrow (▼)
Range/Sideways Pattern : Current candle creates either inside bar or outside bar
Inside bar: Current range smaller than previous candle
Outside bar: Current range larger than previous candle
Shows market indecision or consolidation
Table displays orange background with diamond symbol (◆)
No Clear Pattern : None of the above conditions are met
Table displays gray background with horizontal line (⎯)
How to interpret the table:
All timeframes green (uptrend): Strong bullish alignment
All timeframes red (downtrend): Strong bearish alignment
Mixed colors: Conflicting timeframes, exercise caution
Mostly orange: Market in consolidation phase
Tooltip explanations: Hover over each cell for detailed description
FEATURE 8: BACKGROUND COLOR SYSTEM
What background colors show:
Optional feature that colors your chart background based on the current timeframe's trend condition.
Settings that control this:
Show Background Colors : True/False toggle
Background Transparency : 80-98% range
Default: OFF (no background colors)
Color scheme:
Green background: Current timeframe showing uptrend
Red background: Current timeframe showing downtrend
Orange background: Current timeframe showing range/consolidation
No background: No clear trend pattern
Transparency levels:
80%: More visible background color
95%: Subtle background hint
98%: Very subtle background tint
Scalping MasterMarket Structure Analysis:
Swing Structure: Detects higher highs (HH), lower highs (LH), higher lows (HL), aur lower lows (LL) ko identify karta hai using pivot points (based on ta.highest aur ta.lowest).
Internal Structure: Chhote timeframes ke liye internal swing points aur break of structure (BOS)/change of character (CHoCH) ko track karta hai.
BOS/CHoCH Detection: Bullish aur bearish structure breaks (BOS) aur trend reversals (CHoCH) ko label karta hai.
Order Blocks (OB):
Internal Order Blocks: Chhote timeframe ke order blocks ko plot karta hai, jo liquidity zones ko represent karte hain.
Swing Order Blocks: Bade timeframe ke order blocks ko show karta hai.
Filtering: ATR ya Cumulative Mean Range ke basis par volatile order blocks ko filter karta hai.
Fair Value Gaps (FVG):
Price gaps (bullish aur bearish) ko detect aur plot karta hai.
Auto-threshold aur timeframe customization ke saath FVGs ko filter karta hai.
FVGs ko extend karne ka option deta hai (visual representation ke liye).
Equal Highs/Lows (EQH/EQL):
Equal highs aur lows ko identify karta hai, jo support/resistance zones ke liye useful hote hain.
Bars confirmation aur sensitivity threshold ke saath customizable hai.
Previous Highs/Lows (MTF):
Daily, weekly, aur monthly high/low levels ko plot karta hai.
Line style (solid, dashed, dotted) aur colors customizable hain.
Premium/Discount Zones:
Market ke premium, equilibrium, aur discount zones ko highlight karta hai, jo price action ke liye key areas hote hain.
Visual Customization:
Color Themes: Colored ya monochrome themes ke options.
Candle Coloring: Trend ke hisaab se candles ko color karta hai.
Labels aur Lines: Swing points, strong/weak highs/lows, aur structure breaks ke liye labels aur lines plot karta hai.
Modes:
Historical Mode: Past data ke saath complete structure dikhata hai.
Present Mode: Sirf recent structure aur signals dikhata hai, clutter reduce karne ke liye.
Alerts:
Bullish/Bearish BOS, CHoCH, order block breaks, aur EQH/EQL ke liye alerts set karne ka option.
Swing Points aur Trailing:
Strong/weak high aur low points ko track karta hai.
Trailing maximum/minimum ko extend karta hai for real-time analysis.
Kya Kya Mila Kar Bana Hai?
Yeh indicator Smart Money Concepts ke core principles par based hai aur in elements ko combine karta hai:
Pivot Point Analysis:
ta.highest aur ta.lowest functions se swing highs/lows detect karta hai.
Internal aur swing structure ke liye alag-alag lengths (e.g., length aur 5 for internal swings).
Price Action Concepts:
Break of Structure (BOS): Jab price pivot high/low ko break karta hai.
Change of Character (CHoCH): Jab trend reverse hota hai.
Confluence filtering ke saath accuracy improve karta hai.
Order Blocks:
Liquidity zones ko identify karne ke liye high/low ranges aur ATR/cumulative mean range ka use.
Bullish aur bearish order blocks ke liye customizable colors.
Fair Value Gaps:
Gaps in price action ko detect karne ke liye OHLC data ka analysis.
Timeframe aur auto-threshold ke saath flexibility.
MTF (Multi-Timeframe) Analysis:
Daily, weekly, monthly high/low levels ke liye ta.valuewhen aur time-based calculations.
Zones Detection:
Premium, equilibrium, aur discount zones ke liye price range calculations.
Visual Tools:
Lines, labels, aur boxes ke saath market structure ko visually represent karta hai (line.new, label.new, box.new).
Extendable lines aur boxes for better visibility.
User Inputs:
Customizable settings jaise timeframe, colors, lengths, aur filters, jo user ko flexibility dete hain.
Technical Components
PineScript Functions: ta.crossover, ta.crossunder, ta.highest, ta.lowest, ta.atr, ta.cum for calculations.
Arrays: Order blocks ke coordinates store karne ke liye (array.new_float, array.new_int, array.new_box).
Drawing Tools: Lines, labels, aur boxes ke saath dynamic plotting.
Conditional Logic: BOS, CHoCH, aur other signals ke liye complex conditions.
Timeframe Support: Multi-timeframe analysis ke liye input.timeframe.
Key Levels: Daily, Weekly, Monthly [BackQuant]Key Levels: Daily, Weekly, Monthly
Map the market’s “memory” in one glance—yesterday’s range, this week’s chosen day high/low, and D/W/M opens—then auto-clean levels once they break.
What it does
This tool plots three families of high-signal reference lines and keeps them tidy as price evolves:
Chosen Day High/Low (per week) — Pick a weekday (e.g., Monday). For each past week, the script records that day’s session high and low and projects them forward for a configurable number of bars. These act like “memory levels” that price often revisits.
Daily / Weekly / Monthly Opens — Plots the opening price of each new day, week, and month with separate styling. These opens frequently behave like magnets/flip lines intraday and anchors for regime on higher timeframes.
Auto-pruning — When price breaks a stored level, the script can automatically remove it to reduce clutter and refocus you on still-active lines. See: (broken levels removed).
Why these levels matter
Liquidity pockets — Prior day’s high/low and the daily open concentrate stops and pending orders. Mapping them quickly reveals likely sweep or fade zones. Example: previous day highs + daily open highlighting liquidity:
Context & regime — Monthly opens frame macro bias; trading above a rising cluster of monthly opens vs. below gives a clean top-down read. Example: monthly-only “macro outlook” view:
Cleaner charts — Auto-remove broken lines so you focus on what still matters right now.
What it plots (at a glance)
Past Chosen Day High/Low for up to N prior weeks (your choice), extended right.
Current Daily Open , Weekly Open , and Monthly Open , each with its own color, label, and forward extension.
Optional short labels (e.g., “Mon High”) or full labels (with week/month info).
How breaks are detected & cleaned
You control both the evidence and the timing of a “break”:
Break uses — Choose Close (more conservative) or Wick (more sensitive).
Inclusive? — If enabled, equality counts (≥ high or ≤ low). If disabled, you need a strict cross.
Allow intraday breaks? — If on, a level can break during the tracked day; if off, the script only counts breaks after the session completes.
Remove Broken Levels — When a break is confirmed, the line/label is deleted automatically. (See the demo: )
Quick start
Pick a Day of Week to Track (e.g., Monday).
Set how many weeks back to show (e.g., 8–10).
Choose how far to extend each family (bars to the right for chosen-day H/L and D/W/M opens).
Decide if a break uses Close or Wick , and whether equality counts.
Toggle Remove Broken Levels to keep the chart clean automatically.
Tips by use-case
Intraday bias — Watch the Daily Open as a magnet/flip. If price gaps above and holds, pullbacks to the daily open often decide direction. Pair with last day’s high/low for sweep→reversal or true breakout cues. See:
Weekly structure — Track the week’s chosen day (e.g., Monday) high/low across prior weeks. If price stalls near a cluster of old “Monday Highs,” look for sweep/reject patterns or continuation on reclaim.
Macro regime — Hide daily/weekly lines and keep only Monthly Opens to read bigger cycles at a glance (BTC/crypto especially). Example:
Customization
Use wicks or bodies for highs/lows (wicks capture extremes; bodies are stricter).
Line style & thickness — solid/dashed/dotted, width 1–5, plus global transparency.
Labels — Abbreviated (“Mon High”, “D Open”) or full (month/week/day info).
Color scheme — Separate colors for highs, lows, and each of D/W/M opens.
Capacity controls — Set how many daily/weekly/monthly opens and how many weeks of chosen-day H/L to keep visible.
What’s under the hood
On your selected weekday, the script records that session’s true high and true low (using wicks or body-based extremes—your choice), then projects a horizontal line forward for the next bars.
At each new day/week/month , it records the opening price and projects that line forward as well.
Each bar, the script checks your “break” rules; once broken, lines/labels are removed if auto-cleaning is on.
Everything updates in real time; past levels don’t repaint after the session finishes.
Recommended presets
Day trading — Weeks back: 6–10; extend D/W opens: 50–100 bars; Break uses: Close ; Inclusive: off; Auto-remove: on.
Swing — Fewer daily opens, more weekly opens (2–6), and 8–12 weeks of chosen-day H/L.
Macro — Show only Monthly Opens (1–6 months), dashed style, thicker lines for clarity.
Reading the examples
Broken lines disappear — decluttering in action:
Macro outlook — monthly opens as cycle rails:
Liquidity map — previous day highs + daily open:
Final note
These are not “signals”—they’re reference points that many participants watch. By standardising how you draw them and automatically clearing the ones that no longer matter, you turn a noisy chart into a focused map: where liquidity likely sits, where price memory lives, and which lines are still in play.
Multi-Timeframe SMTSummery
The Multi-Timeframe SMT indicator is designed to identify and visualize Higher Timeframe (HTF) data on a Lower Timeframe (LTF) chart, allowing traders to see the broader market context without changing their current chart's resolution. It accurately draws pivots and SMT divergences from higher timeframes on the corresponding candles of your current lower timeframe chart.
Its core features include:
Multi-Timeframe Analysis: Configure and monitor pivots on up to four independent timeframes, from intraday to monthly.
Customizable Pivot Detection: Define the strength of pivots by adjusting the number of bars to the left and right.
SMT Divergence: Automatically identifies bullish and bearish SMT divergences by comparing the price action of the main chart symbol with a chosen correlated asset.
Early SMT Detection: A unique feature that monitors a lower "detection timeframe" to provide early warnings of potential SMT setups before they're confirmed on the main timeframe. Note that this early detection is only shown on timeframes equal to or lower than the "Detection timeframe" you have set.
Visual Cues & Alerts: Clear on-chart labels, lines, and fully customizable alerts notify you of confirmed pivots and SMT divergences, ensuring you don't miss key opportunities.
Important Nuance Regarding Pivot Label Display
Due to a self-imposed limit within this script's drawing management logic, the indicator might quickly reach its drawing capacity if you enable pivot crosses for multiple timeframes simultaneously. When this internal drawing limit is exceeded, the script is designed to automatically remove the oldest drawings to make space for new ones.
Therefore, to ensure optimal performance and visibility of the most recent and relevant pivots, it's highly recommended to only enable the "Show Pivot Crosses" option for one timeframe at a time. If you wish to view pivots for a different timeframe, simply disable the pivot crosses for the currently active timeframe and then enable them for your desired one. This approach prevents the rapid cycling and disappearance of pivot labels, providing a clearer and more stable visual experience.
In-Depth Explanation of the Logic
This script is built on two primary concepts: pivot points and Smart Money Technique (SMT) divergence. It systematically collects historical data on multiple timeframes, identifies pivots, and then compares them between two assets to find divergences.
Pivot Point Identification
A pivot is a turning point in the market. A pivot high is a candle that has a higher high than the candles to its immediate left and right. Conversely, a pivot low is a candle with a lower low than its neighbors.
How it Works in the Script:
The script tracks the highest high and lowest low for each period of the selected timeframe (e.g., for each 4-hour candle). When a new high-timeframe candle closes, it stores that high/low value and its bar index in an array. The checkForPivot() function then checks if a recently stored high or low qualifies as a pivot.
Key Inputs:
Left Strength (leftBars1): The number of candles to the left that must have a lower high (for a pivot high) or higher low (for a pivot low).
Right Strength (rightBars1): The number of candles to the right that must meet the same criteria.
For example, with Left Strength and Right Strength both set to 3, a pivot high is only confirmed when its high is greater than the highs of the 3 previous high-timeframe candles and the 3 subsequent high-timeframe candles. Increasing these values will identify more significant, longer-term pivots.
Smart Money Technique (SMT) Divergence
SMT Divergence is a concept popularized by The Inner Circle Trader (ICT). It occurs when two closely correlated assets fail to move in sync. For instance, if Asset A makes a higher high but Asset B fails to do so and instead makes a lower high, this creates a bearish SMT divergence. It suggests that the "smart money" may not be supporting the move in Asset A, signaling a potential reversal.
Bearish SMT: Main asset makes a higher high, while the correlated asset makes a lower high. This is a potential sell signal.
Bullish SMT: Main asset makes a lower low, while the correlated asset makes a higher low. This is a potential buy signal.
How it Works in the Script:
Data Request: For each timeframe, the script uses the request.security() function to fetch the high and low data for both the main chart symbol (syminfo.tickerid) and the chosen Comparison Asset.
Pivot Comparison: When a new pivot is confirmed on the main asset, the script checks if a corresponding pivot also formed on the comparison asset at the same time.
Divergence Check: It then compares the direction of the pivots. For a bearish SMT, it checks if the main asset's new pivot high is higher than its previous pivot high, while the comparison asset's new pivot high is lower than its previous one. The logic is reversed for bullish SMT.
Visualization: If a divergence is found, the script draws a red (bearish) or green (bullish) line connecting the two pivots on your chart and places an "SMT" label.
Early SMT Detection
This is a proactive feature designed to give you a heads-up. Waiting for a 4-hour or daily pivot to form can take a long time. The early detection system looks for SMT divergences on a much smaller, user-defined Detection timeframe (e.g., 15-minute).
How it Works in the Script:
Awaiting Setup: After a primary pivot (Pivot A) is formed on the main timeframe (e.g., a Daily pivot high), the script begins monitoring.
Intraday Monitoring: It then watches the Detection timeframe (e.g., 15-minute) for smaller intraday pivots.
Potential Divergence: It looks for an intraday pivot that forms a divergence against the primary Pivot A.
Watchline & Alert: When this "potential" divergence occurs, the script draws a dashed white line and triggers a "Potential SMT" alert. This isn't a confirmed SMT on the main timeframe yet, but it's a powerful early warning that one may be forming.
Drawing & Object Management
To keep the chart clean and prevent performance issues, the script manages its drawings (lines and labels) efficiently. It stores them in arrays and uses a drawing limit to automatically delete the oldest drawings as new ones are created, ensuring your TradingView remains responsive.
How to Use the Indicator
Configuration
Enable Timeframes: Use the checkboxes (Enable Timeframe 1, Enable Timeframe 2, etc.) to activate the timeframes you want to monitor. It's often best to start with one or two to keep the chart clean.
Select Timeframes: Choose the higher timeframes you want to analyze (e.g., 240 for 4-hour, D for Daily, W for Weekly).
Set Pivot Strength: The default of 3 for Left/Right strength is a good starting point. Increase it to find more significant market structure points or decrease it for more frequent, shorter-term pivots.
Configure SMT:
Check Enable SMT for the timeframes where you want to detect divergence.
Enter a Comparison Asset . This is crucial. Ensure the assets are correlated.
To use the early warning system, check Enable early SMT detection and select an appropriate Detection timeframe (e.g., 15 or 60 minutes for a Daily analysis).
Premium/Discount with Candle Open stats [Herman]Premium/Discount with Stats
This indicator is designed to help traders identify and analyze premium/discount zones on any timeframe while automatically tracking statistics on price behavior relative to these zones. It is especially valuable for traders looking to structure entries, manage targets, and quantify market reactions to prior session ranges.
What it draws on the chart
✅ Range High and Low Lines
For each selected timeframe period (15min, 30min 1H, 4H, Daily), the indicator plots the high and low of the completed previous period.
These lines are color-coded dynamically based on sweep detection:
If the high was swept (price broke the previous high), the high line is marked as Premium.
If the low was swept, the low line is marked as Discount.
If both were swept or neither, it uses the default color settings.
✅ Midline
An optional midline at the 50% level of the previous period’s high-low range.
Helpful for mean-reversion traders or anyone watching for retests of equilibrium.
✅ Quartile Lines (25%–75%)
Optional additional lines at 25% and 75% of the previous range, helping traders visualize inner range subdivisions.
✅ Open Price Line
Marks the open price of the previous period as a horizontal reference.
✅ Background Fills
The region between low and midline is shaded with the Discount color.
The region between high and midline is shaded with the Premium color.
These optional fills help highlight the premium and discount zones visually.
✅ Current Incomplete Period Lines (optional)
You can choose to display provisional high, low, midline, quartiles, and open for the current forming period.
These update in real-time until the period closes.
Sweep Detection Logic
The indicator automatically tracks if the current period price sweeps above the previous period’s high or below the low.
A "sweep" is simply defined as price exceeding the previous high/low while tracking is active.
The sweep status affects the colors of the premium/discount lines, helping traders see potential liquidity grabs or stop hunts.
What it counts and tracks (Statistics)
The script automatically compiles statistics over time:
✅ Total Touches
Counts how many times the price in a new period touches either the previous period’s high or low.
A “touch” is registered once per side per period.
✅ Midline Returns
Counts how often, after touching the previous high/low, price returns to the previous period’s midline.
Gives you a measure of mean-reversion success.
✅ Open Returns
Similarly, tracks how often price returns to the previous period’s open after touching the previous high/low.
✅ Return Percentages
Displays the percentage of touches that result in a return to midline or open.
These percentages are calculated live on your chart and updated after each period closes.
✅ Stats Table
A customizable on-chart table summarizing all of these stats in real-time.
Helps traders evaluate the effectiveness of range-based trading setups over time.
How it Works (Technical details)
On each new bar, the script checks if a new period (as defined by your timeframe selection) has begun.
When a new period starts, the previous period’s high, low, open, midline, quartiles are recorded and drawn on the chart.
The script then “watches” the current period:
Updates provisional high and low.
Detects sweeps of previous highs/lows.
Tracks if price returns to the previous period’s midline or open after those sweeps.
Increments statistical counters if conditions are met.
Background fills and lines update dynamically based on real-time data.
Intended Use Cases
This indicator is ideal for:
✅ Identifying premium/discount zones for swing or intraday trades.
✅ Spotting liquidity sweeps and possible manipulation zones.
✅ Structuring trades with logical, data-driven target zones (midline, open).
✅ Quantifying the probability of mean-reversion moves after liquidity events.
✅ Developing and backtesting range-based trading models with live stats.
Highly Customizable
Choose any timeframe for defining the premium/discount range.
Toggle visibility of midline, quartiles, open line, current period preview.
Full control over colors, line styles, line widths, and background shading.
Optional real-time statistical table with total counts and return percentages.
Swing High/Low with Liquidity Sweeps🧠 Overview
This indicator identifies swing highs and swing lows based on user-defined candle lengths and checks for liquidity sweeps—situations where the price breaks a previous swing level but then closes back inside, indicating a potential false breakout or stop hunt. It also supports visual labeling and alerts for these events.
⚙️ Inputs
Swing Length (must be odd number ≥ 3):
Determines how many candles are used to identify swing highs/lows. The central candle must be higher or lower than all neighbors within the range.
Example: If swingLength = 5, the central candle must be higher/lower than the 2 candles on both sides.
Sweep Lookback (bars):
Defines how many bars to look back for possible liquidity sweeps.
Show Swing Labels (checkbox):
Optionally display labels on the chart when a swing high or low is detected.
Show Sweep Labels (checkbox):
Optionally display labels on the chart when a liquidity sweep occurs.
🕯️ Swing Detection Logic
A Swing High is detected when the high of the central candle is greater than the highs of all candles around it (as per the defined length).
A Swing Low is detected when the low of the central candle is lower than the lows of surrounding candles.
Swing labels are placed slightly above (for highs) or below (for lows) the candle.
💧 Liquidity Sweep Logic
A Sweep High is triggered if:
The current high breaks above a previously detected swing high,
And then the candle closes below that swing high,
Within the configured lookback window.
A Sweep Low is triggered if:
The current low breaks below a previous swing low,
And then closes above it,
Within the lookback window.
These are often seen as stop hunts or fake breakouts.
🔔 Alerts
Sweep High Alert: Triggered when a sweep above a swing high occurs.
Sweep Low Alert: Triggered when a sweep below a swing low occurs.
You can use these to set up TradingView alerts to notify you of potential liquidity grabs.
📊 Use Cases
Identifying market structure shifts.
Spotting fake breakouts and potential reversals.
Assisting in smart money concepts and liquidity-based trading.
Supporting entry timing in trend continuation or reversal strategies.
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Timeframe Resistance Evaluation And Detection - CoffeeKillerTREAD - Timeframe Resistance Evaluation And Detection Guide
🔔 Important Technical Limitation 🔔
**This indicator does NOT fetch true higher timeframe data.** Instead, it simulates higher timeframe levels by aggregating data from your current chart timeframe. This means:
- Results will vary depending on what chart timeframe you're viewing
- Levels may not match actual higher timeframe candle highs/lows
- You might miss important wicks or gaps that occurred between chart timeframe bars
- **Always verify levels against actual higher timeframe charts before trading**
Welcome traders! This guide will walk you through the TREAD (Timeframe Resistance Evaluation And Detection) indicator, a multi-timeframe analysis tool developed by CoffeeKiller that identifies support and resistance confluence across different time periods.(I am 50+ year old trader and always thought I was bad a teaching and explaining so you get a AI guide. I personally use this on the 5 minute chart with the default settings, but to each there own and if you can improve the trend detection methods please DM me. I would like to see the code. Thanks)
Core Components
1. Dual Timeframe Level Tracking
- Short Timeframe Levels: Tracks opening price extremes within shorter periods
- Long Timeframe Levels: Tracks actual high/low extremes within longer periods
- Dynamic Reset Mechanism: Levels reset at the start of each new timeframe period
- Momentum Detection: Identifies when levels change mid-period, indicating active price movement
2. Visual Zone System
- High Zones: Areas between long timeframe highs and short timeframe highs
- Low Zones: Areas between long timeframe lows and short timeframe lows
- Fill Coloring: Dynamic colors based on whether levels are static or actively changing
- Momentum Highlighting: Special colors when levels break during active periods
3. Customizable Display Options
- Multiple Plot Styles: Line, circles, or cross markers
- Flexible Timeframe Selection: Wide range of short and long timeframe combinations
- Color Customization: Separate colors for each level type and momentum state
- Toggle Controls: Show/hide different elements based on trading preference
Main Features
Timeframe Settings
- Short Timeframe Options: 15m, 30m, 1h, 2h, 4h
- Long Timeframe Options: 1h, 2h, 4h, 8h, 12h, 1D, 1W
- Recommended Combinations:
- Scalping: 15m/1h or 30m/2h
- Day Trading: 30m/4h or 1h/4h
- Swing Trading: 4h/1D or 1D/1W
Display Configuration
- Level Visibility: Toggle short/long timeframe levels independently
- Fill Zone Control: Enable/disable colored zones between levels
- Momentum Fills: Special highlighting for actively changing levels
- Line Customization: Width, style, and color options for all elements
Color System
- Short TF High: Default red for resistance levels
- Short TF Low: Default green for support levels
- Long TF High: Transparent red for broader resistance context
- Long TF Low: Transparent green for broader support context
- Momentum Colors: Brighter colors when levels are actively changing
Technical Implementation Details
How Level Tracking Works
The indicator uses a custom tracking function that:
1. Detects Timeframe Periods: Uses `time()` function to identify when new periods begin
2. Tracks Extremes: Monitors highest/lowest values within each period
3. Resets on New Periods: Clears tracking when timeframe periods change
4. Updates Mid-Period: Continues tracking if new extremes are reached
The Timeframe Limitation Explained
`pinescript
// What the indicator does:
short_tf_start = ta.change(time(short_timeframe)) != 0 // Detects 30m period start
= track_highest(open, short_tf_start) // BUT uses chart TF opens!
// What true multi-timeframe would be:
// short_tf_high = request.security(syminfo.tickerid, short_timeframe, high)
`
This means:
- On a 5m chart with 30m/4h settings: Tracks 5m bar opens during 30m and 4h windows
- On a 1m chart with same settings: Tracks 1m bar opens during 30m and 4h windows
- Results will be different between chart timeframes
- May miss important price action that occurred between your chart's bars
Visual Elements
1. Level Lines
- Short TF High: Upper resistance line from shorter timeframe analysis
- Short TF Low: Lower support line from shorter timeframe analysis
- Long TF High: Broader resistance context from longer timeframe
- Long TF Low: Broader support context from longer timeframe
2. Zone Fills
- High Zone: Area between long TF high and short TF high (potential resistance cluster)
- Low Zone: Area between long TF low and short TF low (potential support cluster)
- Regular Fill: Standard transparency when levels are static
- Momentum Fill: Enhanced visibility when levels are actively changing
3. Dynamic Coloring
- Static Periods: Normal colors when levels haven't changed recently
- Active Periods: Momentum colors when levels are being tested/broken
- Confluence Zones: Different intensities based on timeframe alignment
Trading Applications
1. Support/Resistance Trading
- Entry Points: Trade bounces from zone boundaries
- Confluence Areas: Focus on areas where short and long TF levels cluster
- Zone Breaks: Enter on confirmed breaks through entire zones
- Multiple Timeframe Confirmation: Stronger signals when both timeframes align
2. Range Trading
- Zone Boundaries: Use fill zones as range extremes
- Mean Reversion: Trade back toward opposite zone when price reaches extremes
- Breakout Preparation: Watch for momentum color changes indicating potential breakouts
- Risk Management: Place stops outside the opposite zone
3. Trend Following
- Direction Bias: Trade in direction of zone breaks
- Pullback Entries: Enter on pullbacks to broken zones (now support/resistance)
- Momentum Confirmation: Use momentum coloring to confirm trend strength
- Multiple Timeframe Alignment: Strongest trends when both timeframes agree
4. Scalping Applications
- Quick Bounces: Trade rapid moves between zone boundaries
- Momentum Signals: Enter when momentum colors appear
- Short-Term Targets: Use opposite zone as profit target
- Tight Stops: Place stops just outside current zone
Optimization Guide
1. Timeframe Selection
For Different Trading Styles:
- Scalping: 15m/1h - Quick levels, frequent updates
- Day Trading: 30m/4h - Balanced view, good for intraday moves
- Swing Trading: 4h/1D - Longer-term perspective, fewer false signals
- Position Trading: 1D/1W - Major structural levels
2. Chart Timeframe Considerations
**Important**: Your chart timeframe affects results
- Lower Chart TF: More granular level tracking, but may be noisy
- Higher Chart TF: Smoother levels, but may miss important price action
- Recommended: Use chart timeframe 2-4x smaller than short indicator timeframe
3. Display Settings
- Busy Charts: Disable fills, show only key levels
- Clean Analysis: Enable all fills and momentum coloring
- Multi-Monitor Setup: Use different color schemes for easy identification
- Mobile Trading: Increase line width for visibility
Best Practices
1. Level Verification
- Always Cross-Check: Verify levels against actual higher timeframe charts
- Multiple Timeframes: Check 2-3 different chart timeframes for consistency
- Price Action Confirmation: Wait for candlestick confirmation at levels
- Volume Analysis: Combine with volume for stronger confirmation
2. Risk Management
- Stop Placement: Use zones rather than exact prices for stops
- Position Sizing: Reduce size when zones are narrow (higher risk)
- Multiple Targets: Scale out at different zone boundaries
- False Break Protection: Allow for minor zone penetrations
3. Signal Quality Assessment
- Momentum Colors: Higher probability when momentum coloring appears
- Zone Width: Wider zones often provide stronger support/resistance
- Historical Testing: Backtest on your preferred timeframe combinations
- Market Conditions: Adjust sensitivity based on volatility
Advanced Features
1. Momentum Detection System
The indicator tracks when levels change mid-period:
`pinescript
short_high_changed = short_high != short_high and not short_tf_start
`
This identifies:
- Active level testing
- Potential breakout situations
- Increased market volatility
- Trend acceleration points
2. Dynamic Color System
Complex conditional logic determines fill colors:
- Static Zones: Regular transparency for stable levels
- Active Zones: Enhanced colors for changing levels
- Mixed States: Different combinations based on user preferences
- Custom Overrides: User can prioritize certain color schemes
3. Zone Interaction Analysis
- Convergence: When short and long TF levels approach each other
- Divergence: When timeframes show conflicting levels
- Alignment: When both timeframes agree on direction
- Transition: When one timeframe changes while other remains static
Common Issues and Solutions
1. Inconsistent Levels
Problem: Levels look different on various chart timeframes
Solution: Always verify against actual higher timeframe charts
2. Missing Price Action
Problem: Important wicks or gaps not reflected in levels
Solution: Use chart timeframe closer to indicator's short timeframe setting
3. Too Many Signals
Problem: Excessive level changes and momentum alerts
Solution: Increase timeframe settings or reduce chart timeframe granularity
4. Lagging Signals
Problem: Levels seem to update too slowly
Solution: Decrease chart timeframe or use more sensitive timeframe combinations
Recommended Setups
Conservative Approach
- Timeframes: 4h/1D
- Chart: 1h
- Display: Show fills only, no momentum coloring
- Use: Swing trading, position management
Aggressive Approach
- Timeframes: 15m/1h
- Chart: 5m
- Display: All features enabled, momentum highlighting
- Use: Scalping, quick reversal trades
Balanced Approach
- Timeframes: 30m/4h
- Chart: 15m
- Display: Selective fills, momentum on key levels
- Use: Day trading, multi-session analysis
Final Notes
**Remember**: This indicator provides a synthetic view of multi-timeframe levels, not true higher timeframe data. While useful for identifying potential confluence areas, always verify important levels by checking actual higher timeframe charts.
**Best Results When**:
- Combined with actual multi-timeframe analysis
- Used for confluence confirmation rather than primary signals
- Applied with proper risk management
- Verified against price action and volume
**DISCLAIMER**: This indicator and its signals are intended solely for educational and informational purposes. The timeframe limitation means results may not reflect true higher timeframe levels. Always conduct your own analysis and verify levels independently before making trading decisions. Trading involves significant risk of loss.
