50/100/200 Moving Averages (Pine Script For Copy)by fresca
SCRIPT LANGUAGE
Copy script below and adjust based on your preferences.
-function (change function from "sma" to "ema", "wma" and more)
-length (25 Day, 150 Day or add more averages to the three in this script.)
-color, (red, yellow, etc. or use color hex codes i.e. #FEDA15, #FFAD8F, etc.)
-transparency (set to desired level 1-100)
Or add more options.
RESOURCES
Color hex codes site: www.canva.com
Trading View Pine Script Editor Reference Guide: www.tradingview.com
在脚本中搜索"北证50+股票+新浪财经"
Taint's Multi Time Frame MA50-100-200 SMA with two 200 EMA's all with the ability choose a time frame for each.
Algoticks.in: Bollinger Bands Strategy (Sample)Bollinger Bands Strategy - User Guide
Overview
This is a Mean Reversion strategy using Bollinger Bands. It generates trading signals when price moves outside the bands and then crosses back, or simply crosses the bands depending on the logic. It integrates with Algoticks.in API for automated trading on Delta Exchange.
Strategy Logic
Long Signal: When Price crosses below the Lower Band (Oversold / Dip Buy)
Short Signal: When Price crosses above the Upper Band (Overbought / Top Sell)
Automatically closes opposite positions before entering new ones
Quick Setup
1. Add to TradingView
Open TradingView and go to the chart
Click "Pine Editor" at the bottom
Paste the script code
Click "Add to Chart"
2. Configure Strategy Parameters
Strategy Settings
Length (default: 20): The lookback period for the SMA basis
StdDev (default: 2.0): The number of standard deviations for the bands
General API Settings
Paper Trading : Enable for testing without real money
Signal Type : Choose "Trading Signal" (default) for tracking
Exchange : DELTA (Delta Exchange)
Segment :
futures - Perpetual contracts
options - Call/Put options
spot - Spot trading
Order Settings: Basic
Quantity : Number of contracts (e.g., 1, 0.5, 2)
Validity :
GTC - Good Till Cancelled
IOC - Immediate or Cancel
FOK - Fill or Kill
DAY - Day order
Product : cross_margin or isolated_margin
Order Settings: Entry Type
Choose how orders are executed:
Market Order : Immediate fill at best price
Limit Order : Fill at specified price or better
Stop Market : Triggers at stop price, then market order
Stop Limit : Triggers at stop price, then limit order
Entry Prices (for Limit/Stop orders)
Limit Price:
Price : The value to use
Type : Last Price / Mark Price / Index Price
Mode :
Absolute - Exact price (e.g., 65000)
Relative - Offset from entry price
% Checkbox : If checked, relative uses percentage; if unchecked, uses points
Example:
Absolute: 65000 → Order at exactly 65000
Relative 1% (checked): Entry ± 1% of entry price
Relative 100 (unchecked): Entry ± 100 points
Trigger Price: Same logic as Limit Price, used for Stop orders
Exit / Bracket Prices (SL/TP)
Stop Loss (SL):
Type : Price type to monitor (Mark Price recommended)
Mode : Absolute or Relative
% : Percentage or points
SL : Stop loss value (e.g., 2 for 2%)
Trig : Optional trigger price (creates Stop-Limit SL)
Take Profit (TP): Same structure as SL
Example:
Long entry at 65000, SL = 2% → Exit at 63700 (65000 - 2%)
Short entry at 65000, TP = 3% → Exit at 63050 (65000 - 3%)
3. Options Trading Setup (Only if Segment = Options)
Strike Selection Method
User Defined Mode:
Manually specify exact strike and option type
Best for: Trading specific levels
Required fields:
Strike Price : e.g., "65000"
Option Type : Call or Put
Dynamic Mode:
System calculates strike based on ATM price
Best for: Automated strategies
Required fields:
Algo Type : Options Buying or Selling
Strike Offset : 0 (ATM), +1 (above ATM), -1 (below ATM)
Strike Interval : Gap between strikes (e.g., BTC: 500, ETH: 50)
Expiry Date Formats:
T+0 - Today
T+1 - Tomorrow
current week - This Friday
next week - Next Friday
current month - Last Friday of month
131125 - Specific date (13 Nov 2025)
4. Create Alert for Automation
Right-click on chart → "Add Alert"
Condition : Select your strategy name
Alert Actions : Webhook URL
Webhook URL : Your Algoticks.in API endpoint
Message : Leave as {{strategy.order.alert_message}} (contains JSON)
Click "Create"
The alert will automatically send JSON payloads to your API when signals occur.
Example Configurations
Standard Mean Reversion
Strategy: Length = 20, StdDev = 2.0
Segment: futures
Order Type: market_order
Quantity: 1
SL: 1% (Relative)
TP: 2% (Relative)
Wide Band Reversal
Strategy: Length = 20, StdDev = 2.5
Segment: futures
Order Type: market_order
Quantity: 1
SL: 1.5% (Relative)
TP: 3% (Relative)
Important Notes
Paper Trading First : Always test with paper trading enabled before live trading
Order Tags : Automatically generated for tracking (max 18 chars)
Position Management : Strategy closes opposite positions automatically
Signal Confirmation : Uses barstate.isconfirmed to prevent repainting
JSON Payload : All settings are converted to JSON and sent via webhook
Troubleshooting
No signals : Check if price is actually touching the bands
Orders not executing : Verify webhook URL and API credentials
Wrong strikes : Double-check Strike Interval for your asset
SL Bollinger Bands Strategy - User Guide
Overview
This is a Mean Reversion strategy using Bollinger Bands. It generates trading signals when price moves outside the bands and then crosses back, or simply crosses the bands depending on the logic. It integrates with Algoticks.in API for automated trading on Delta Exchange.
Strategy Logic
Long Signal: When Price crosses below the Lower Band (Oversold / Dip Buy)
Short Signal: When Price crosses above the Upper Band (Overbought / Top Sell)
Automatically closes opposite positions before entering new ones
Quick Setup
1. Add to TradingView
Open TradingView and go to the chart
Click "Pine Editor" at the bottom
Paste the script code
Click "Add to Chart"
2. Configure Strategy Parameters
Strategy Settings
Length (default: 20): The lookback period for the SMA basis
StdDev (default: 2.0): The number of standard deviations for the bands
General API Settings
Paper Trading : Enable for testing without real money
Signal Type : Choose "Trading Signal" (default) for tracking
Exchange : DELTA (Delta Exchange)
Segment :
futures - Perpetual contracts
options - Call/Put options
spot - Spot trading
Order Settings: Basic
Quantity : Number of contracts (e.g., 1, 0.5, 2)
Validity :
GTC - Good Till Cancelled
IOC - Immediate or Cancel
FOK - Fill or Kill
DAY - Day order
Product : cross_margin or isolated_margin
Order Settings: Entry Type
Choose how orders are executed:
Market Order : Immediate fill at best price
Limit Order : Fill at specified price or better
Stop Market : Triggers at stop price, then market order
Stop Limit : Triggers at stop price, then limit order
Entry Prices (for Limit/Stop orders)
Limit Price:
Price : The value to use
Type : Last Price / Mark Price / Index Price
Mode :
Absolute - Exact price (e.g., 65000)
Relative - Offset from entry price
% Checkbox : If checked, relative uses percentage; if unchecked, uses points
Example:
Absolute: 65000 → Order at exactly 65000
Relative 1% (checked): Entry ± 1% of entry price
Relative 100 (unchecked): Entry ± 100 points
Trigger Price: Same logic as Limit Price, used for Stop orders
Exit / Bracket Prices (SL/TP)
Stop Loss (SL):
Type : Price type to monitor (Mark Price recommended)
Mode : Absolute or Relative
% : Percentage or points
SL : Stop loss value (e.g., 2 for 2%)
Trig : Optional trigger price (creates Stop-Limit SL)
Take Profit (TP): Same structure as SL
Example:
Long entry at 65000, SL = 2% → Exit at 63700 (65000 - 2%)
Short entry at 65000, TP = 3% → Exit at 63050 (65000 - 3%)
3. Options Trading Setup (Only if Segment = Options)
Strike Selection Method
User Defined Mode:
Manually specify exact strike and option type
Best for: Trading specific levels
Required fields:
Strike Price : e.g., "65000"
Option Type : Call or Put
Dynamic Mode:
System calculates strike based on ATM price
Best for: Automated strategies
Required fields:
Algo Type : Options Buying or Selling
Strike Offset : 0 (ATM), +1 (above ATM), -1 (below ATM)
Strike Interval : Gap between strikes (e.g., BTC: 500, ETH: 50)
Expiry Date Formats:
T+0 - Today
T+1 - Tomorrow
current week - This Friday
next week - Next Friday
current month - Last Friday of month
131125 - Specific date (13 Nov 2025)
4. Create Alert for Automation
Right-click on chart → "Add Alert"
Condition : Select your strategy name
Alert Actions : Webhook URL
Webhook URL : Your Algoticks.in API endpoint
Message : Leave as {{strategy.order.alert_message}} (contains JSON)
Click "Create"
The alert will automatically send JSON payloads to your API when signals occur.
Example Configurations
Standard Mean Reversion
Strategy: Length = 20, StdDev = 2.0
Segment: futures
Order Type: market_order
Quantity: 1
SL: 1% (Relative)
TP: 2% (Relative)
Wide Band Reversal
Strategy: Length = 20, StdDev = 2.5
Segment: futures
Order Type: market_order
Quantity: 1
SL: 1.5% (Relative)
TP: 3% (Relative)
Important Notes
Paper Trading First : Always test with paper trading enabled before live trading
Order Tags : Automatically generated for tracking (max 18 chars)
Position Management : Strategy closes opposite positions automatically
Signal Confirmation : Uses barstate.isconfirmed to prevent repainting
JSON Payload : All settings are converted to JSON and sent via webhook
Troubleshooting
No signals : Check if price is actually touching the bands
Orders not executing : Verify webhook URL and API credentials
Wrong strikes : Double-check Strike Interval for your asset
SL
Scout Regiment - KSI# Scout Regiment - KSI Indicator
## English Documentation
### Overview
Scout Regiment - KSI (Key Stochastic Indicators) is a comprehensive momentum oscillator that combines three powerful technical indicators - RSI, CCI, and Williams %R - into a single, unified display. This multi-indicator approach provides traders with diverse perspectives on market momentum, overbought/oversold conditions, and potential reversal points through advanced divergence detection.
### What is KSI?
KSI stands for "Key Stochastic Indicators" - a composite momentum indicator that:
- Displays multiple oscillators normalized to a 0-100 scale
- Uses standardized bands (20/50/80) for consistent interpretation
- Combines RSI for trend, CCI for cycle, and Williams %R for reversal detection
- Provides enhanced divergence detection specifically for RSI
### Key Features
#### 1. **Triple Oscillator System**
**① RSI (Relative Strength Index)** - Primary Indicator
- **Purpose**: Measures momentum and identifies overbought/oversold conditions
- **Default Length**: 22 periods
- **Display**: Blue line (2px)
- **Key Levels**:
- Above 50: Bullish momentum
- Below 50: Bearish momentum
- Above 80: Overbought
- Below 20: Oversold
- **Special Features**:
- Background color indication (green/red)
- Crossover labels at 50 level
- Full divergence detection (4 types)
**② CCI (Commodity Channel Index)** - Dual Period
- **Purpose**: Identifies cyclical trends and extreme conditions
- **Dual Display**:
- CCI(33): Short-term cycle - Green line (1px)
- CCI(77): Medium-term cycle - Orange line (1px)
- **Default Source**: HLC3 (typical price)
- **Normalized Scale**: Mapped from ±100 to 0-100 for consistency
- **Interpretation**:
- Above 80: Strong upward momentum
- Below 20: Strong downward momentum
- 50 level: Neutral
- Divergence between periods: Trend change warning
**③ Williams %R** - Optional
- **Purpose**: Identifies overbought/oversold extremes
- **Default Length**: 28 periods
- **Display**: Magenta line (2px)
- **Scale**: Inverted and normalized to 0-100
- **Best For**: Short-term reversal signals
- **Default**: Disabled (enable when needed for extra confirmation)
#### 2. **Standardized Band System**
**Three-Level Structure:**
- **Upper Band (80)**: Overbought zone
- Strong momentum area
- Watch for reversal signals
- Divergences here are most reliable
- **Middle Line (50)**: Equilibrium
- Separates bullish/bearish zones
- Crossovers indicate momentum shifts
- Key decision level
- **Lower Band (20)**: Oversold zone
- Weak momentum area
- Look for bounce signals
- Divergences here signal potential reversals
**Band Fill**: Dark background between 20-80 for visual clarity
#### 3. **RSI Visual Enhancements**
**Background Color Indication**
- Green background: RSI above 50 (bullish bias)
- Red background: RSI below 50 (bearish bias)
- Optional display for cleaner charts
- Helps identify overall momentum direction
**Crossover Labels**
- "突破" (Breakout): RSI crosses above 50
- "跌破" (Breakdown): RSI crosses below 50
- Marks momentum shift points
- Can be toggled on/off
#### 4. **Advanced RSI Divergence Detection**
The indicator includes comprehensive divergence detection for RSI only (most reliable oscillator):
**Regular Bullish Divergence (Yellow)**
- **Price**: Lower lows
- **RSI**: Higher lows
- **Signal**: Potential upward reversal
- **Label**: "涨" (Up)
- **Most Common**: Near oversold levels (below 30)
**Regular Bearish Divergence (Blue)**
- **Price**: Higher highs
- **RSI**: Lower highs
- **Signal**: Potential downward reversal
- **Label**: "跌" (Down)
- **Most Common**: Near overbought levels (above 70)
**Hidden Bullish Divergence (Light Yellow)**
- **Price**: Higher lows
- **RSI**: Lower lows
- **Signal**: Uptrend continuation
- **Label**: "隐涨" (Hidden Up)
- **Use**: Add to existing longs
**Hidden Bearish Divergence (Light Blue)**
- **Price**: Lower highs
- **RSI**: Higher highs
- **Signal**: Downtrend continuation
- **Label**: "隐跌" (Hidden Down)
- **Use**: Add to existing shorts
**Divergence Parameters** (Fully Customizable):
- **Right Lookback**: Bars to right of pivot (default: 5)
- **Left Lookback**: Bars to left of pivot (default: 5)
- **Max Range**: Maximum bars between pivots (default: 60)
- **Min Range**: Minimum bars between pivots (default: 5)
### Configuration Settings
#### KSI Display Settings
- **Show RSI**: Toggle RSI indicator
- **Show CCI**: Toggle both CCI lines
- **Show Williams %R**: Toggle Williams %R (optional)
#### RSI Settings
- **RSI Length**: Period for calculation (default: 22)
- **Data Source**: Price source (default: close)
- **Show Background**: Toggle green/red background
- **Show Cross Labels**: Toggle 50-level crossover labels
#### RSI Divergence Settings
- **Right Lookback**: Pivot detection right side
- **Left Lookback**: Pivot detection left side
- **Max Range**: Maximum lookback distance
- **Min Range**: Minimum lookback distance
- **Show Regular Divergence**: Enable regular divergence lines
- **Show Regular Labels**: Enable regular divergence labels
- **Show Hidden Divergence**: Enable hidden divergence lines
- **Show Hidden Labels**: Enable hidden divergence labels
#### CCI Settings
- **CCI Length**: Short-term period (default: 33)
- **CCI Mid Length**: Medium-term period (default: 77)
- **Data Source**: Price calculation (default: HLC3)
- **Show CCI(33)**: Toggle short-term CCI
- **Show CCI(77)**: Toggle medium-term CCI
#### Williams %R Settings
- **Length**: Calculation period (default: 28)
- **Data Source**: Price source (default: close)
### How to Use
#### For Basic Momentum Trading
1. **Enable RSI Only** (primary indicator)
- Focus on 50-level crossovers
- Enable crossover labels for signals
2. **Identify Momentum Direction**
- RSI > 50 = Bullish momentum
- RSI < 50 = Bearish momentum
- Background color confirms direction
3. **Look for Extremes**
- RSI > 80 = Overbought (consider selling)
- RSI < 20 = Oversold (consider buying)
4. **Trade Setup**
- Enter long when RSI crosses above 50 from oversold
- Enter short when RSI crosses below 50 from overbought
#### For Divergence Trading
1. **Enable RSI with Divergence Detection**
- Turn on regular divergence
- Optionally add hidden divergence
2. **Wait for Divergence Signal**
- Yellow label = Bullish divergence
- Blue label = Bearish divergence
3. **Confirm with Price Structure**
- Wait for support/resistance break
- Look for candlestick patterns
- Check volume confirmation
4. **Enter Position**
- Enter after confirmation
- Stop beyond divergence pivot
- Target next key level
#### For Multi-Oscillator Confirmation
1. **Enable All Three Indicators**
- RSI (momentum)
- CCI dual (cycle analysis)
- Williams %R (extremes)
2. **Look for Alignment**
- All above 50 = Strong bullish
- All below 50 = Strong bearish
- Mixed signals = Consolidation
3. **Identify Extremes**
- All indicators > 80 = Extreme overbought
- All indicators < 20 = Extreme oversold
4. **Trade Reversals**
- Enter counter-trend when all aligned at extremes
- Confirm with divergence if available
- Use tight stops
#### For CCI Dual-Period Analysis
1. **Enable Both CCI Lines**
- CCI(33) = Short-term
- CCI(77) = Medium-term
2. **Watch for Crossovers**
- Green crosses above orange = Bullish acceleration
- Green crosses below orange = Bearish acceleration
3. **Analyze Divergence Between Periods**
- Short-term rising, medium falling = Potential reversal
- Both rising together = Strong trend
4. **Trade Accordingly**
- Follow crossover direction
- Exit when lines converge
### Trading Strategies
#### Strategy 1: RSI 50-Level Crossover
**Setup:**
- Enable RSI with background and labels
- Wait for clear trend
- Look for retracement to 50 level
**Entry:**
- Long: "突破" label appears after pullback
- Short: "跌破" label appears after bounce
**Stop Loss:**
- Long: Below recent swing low
- Short: Above recent swing high
**Exit:**
- Opposite crossover label
- Or predetermined target (2:1 risk-reward)
**Best For:** Trend following, clear markets
#### Strategy 2: RSI Divergence Reversal
**Setup:**
- Enable RSI with regular divergence
- Wait for extreme levels (>70 or <30)
- Look for divergence signal
**Entry:**
- Long: Yellow "涨" label at oversold level
- Short: Blue "跌" label at overbought level
**Confirmation:**
- Wait for price to break structure
- Check for volume increase
- Look for candlestick reversal pattern
**Stop Loss:**
- Beyond divergence pivot point
**Exit:**
- Take partial profit at 50 level
- Exit remainder at opposite extreme or divergence
**Best For:** Swing trading, range-bound markets
#### Strategy 3: Triple Oscillator Confluence
**Setup:**
- Enable all three indicators
- Wait for all to reach extreme (>80 or <20)
- Look for alignment
**Entry:**
- Long: All three below 20, first one crosses above 20
- Short: All three above 80, first one crosses below 80
**Confirmation:**
- All indicators must align
- Price at support/resistance
- Volume spike helps
**Stop Loss:**
- Fixed percentage or ATR-based
**Exit:**
- When any indicator crosses 50 level
- Or at predetermined target
**Best For:** High-probability reversals, volatile markets
#### Strategy 4: CCI Dual-Period System
**Setup:**
- Enable both CCI lines only
- Disable RSI and Williams %R for clarity
- Watch for crossovers
**Entry:**
- Long: CCI(33) crosses above CCI(77) below 50 line
- Short: CCI(33) crosses below CCI(77) above 50 line
**Confirmation:**
- Both should be moving in entry direction
- Price breaking key level helps
**Stop Loss:**
- When CCIs cross back in opposite direction
**Exit:**
- Both CCIs enter opposite extreme zone
- Or trailing stop
**Best For:** Catching trend continuations, momentum trading
#### Strategy 5: Hidden Divergence Continuation
**Setup:**
- Enable RSI with hidden divergence
- Confirm existing trend
- Wait for pullback
**Entry:**
- Uptrend: "隐涨" label during pullback
- Downtrend: "隐跌" label during bounce
**Confirmation:**
- Price holds key moving average
- Trend structure intact
**Stop Loss:**
- Beyond pullback extreme
**Exit:**
- Regular divergence appears (reversal warning)
- Or trend structure breaks
**Best For:** Adding to positions, trend trading
### Best Practices
#### Choosing Which Indicators to Display
**For Beginners:**
- Use RSI only
- Enable background color and labels
- Focus on 50-level crossovers
- Simple and effective
**For Intermediate Traders:**
- RSI + Regular Divergence
- Add CCI for confirmation
- Use dual perspectives
- Better accuracy
**For Advanced Traders:**
- All three indicators
- Full divergence detection
- Multi-timeframe analysis
- Maximum information
#### Oscillator Priority
**Primary**: RSI (22)
- Most reliable
- Best divergence detection
- Good for all timeframes
- Use this as your main decision maker
**Secondary**: CCI (33/77)
- Adds cycle analysis
- Great for confirmation
- Dual-period crossovers valuable
- Use to confirm RSI signals
**Tertiary**: Williams %R (28)
- Extreme readings useful
- More volatile
- Best for short-term
- Use sparingly for extra confirmation
#### Timeframe Considerations
**Lower Timeframes (1m-15m):**
- More signals, less reliable
- Use tight divergence parameters
- Focus on RSI crossovers
- Quick entries and exits
**Medium Timeframes (30m-4H):**
- Balanced signal frequency
- Default settings work well
- Best for divergence trading
- Swing trading optimal
**Higher Timeframes (Daily+):**
- Fewer but stronger signals
- Widen divergence ranges
- All indicators more reliable
- Position trading best
#### Divergence Trading Tips
1. **Wait for Confirmation**
- Divergence alone isn't enough
- Need price structure break
- Volume helps validate
2. **Best at Extremes**
- Divergences near 80/20 levels most reliable
- Mid-level divergences often fail
- Combine with support/resistance
3. **Multiple Divergences**
- Second divergence stronger than first
- Third divergence extremely powerful
- Watch for "triple divergence"
4. **Timeframe Alignment**
- Check higher timeframe for direction
- Trade divergences in direction of larger trend
- Counter-trend divergences riskier
### Indicator Combinations
**With Moving Averages:**
- Use EMAs (21/55/144) for trend
- KSI for entry timing
- Enter when both align
**With Volume:**
- Volume confirms breakouts
- Divergence + volume divergence = Stronger
- Low volume at extremes = Reversal likely
**With Support/Resistance:**
- Price levels for targets
- KSI for entry timing
- Divergences at levels = Highest probability
**With Bias Indicator:**
- Bias shows price deviation
- KSI shows momentum
- Both diverging = Strong reversal signal
**With OBV Indicator:**
- OBV shows volume trend
- KSI shows price momentum
- Volume/momentum divergence powerful
### Common Patterns
1. **Bullish Reversal**: All oscillators oversold + RSI bullish divergence
2. **Bearish Reversal**: All oscillators overbought + RSI bearish divergence
3. **Trend Acceleration**: RSI > 50, both CCIs rising, Williams %R not extreme
4. **Weakening Trend**: RSI declining while price rising (pre-divergence warning)
5. **Strong Trend**: All oscillators stay above/below 50 for extended period
6. **Consolidation**: Oscillators crossing 50 frequently without extremes
7. **Exhaustion**: Multiple oscillators at extreme + hidden divergence failure
### Performance Tips
- Start simple: RSI only
- Add indicators gradually as you learn
- Disable unused features for cleaner charts
- Use labels strategically (not always on)
- Test different RSI lengths for your market
- Adjust divergence parameters based on volatility
### Alert Conditions
The indicator includes alerts for:
- RSI crossing above 50
- RSI crossing below 50
- RSI regular bullish divergence
- RSI regular bearish divergence
- RSI hidden bullish divergence
- RSI hidden bearish divergence
---
## 中文说明文档
### 概述
Scout Regiment - KSI（关键随机指标）是一个综合性动量振荡器，将三个强大的技术指标 - RSI、CCI和威廉指标 - 组合到一个统一的显示中。这种多指标方法为交易者提供了市场动量、超买超卖状况和通过高级背离检测发现潜在反转点的多元视角。
### 什么是KSI？
KSI代表"关键随机指标" - 一个综合动量指标：
- 显示多个振荡器，标准化到0-100刻度
- 使用标准化波段（20/50/80）便于一致解读
- 结合RSI用于趋势、CCI用于周期、威廉指标用于反转检测
- 专门为RSI提供增强的背离检测
### 核心功能
#### 1. **三重振荡器系统**
**① RSI（相对强弱指数）** - 主要指标
- **用途**：测量动量并识别超买超卖状况
- **默认长度**：22周期
- **显示**：蓝色线（2像素）
- **关键水平**：
- 50以上：看涨动量
- 50以下：看跌动量
- 80以上：超买
- 20以下：超卖
- **特殊功能**：
- 背景颜色指示（绿色/红色）
- 50水平穿越标签
- 完整背离检测（4种类型）
**② CCI（顺势指标）** - 双周期
- **用途**：识别周期性趋势和极端状况
- **双重显示**：
- CCI(33)：短期周期 - 绿色线（1像素）
- CCI(77)：中期周期 - 橙色线（1像素）
- **默认数据源**：HLC3（典型价格）
- **标准化刻度**：从±100映射到0-100以保持一致性
- **解读**：
- 80以上：强劲上升动量
- 20以下：强劲下降动量
- 50水平：中性
- 周期间背离：趋势变化警告
**③ 威廉指标 %R** - 可选
- **用途**：识别超买超卖极值
- **默认长度**：28周期
- **显示**：洋红色线（2像素）
- **刻度**：反转并标准化到0-100
- **最适合**：短期反转信号
- **默认**：禁用（需要额外确认时启用）
#### 2. **标准化波段系统**
**三层结构：**
- **上轨（80）**：超买区域
- 强动量区域
- 注意反转信号
- 此处的背离最可靠
- **中线（50）**：均衡线
- 分隔看涨/看跌区域
- 穿越表示动量转变
- 关键决策水平
- **下轨（20）**：超卖区域
- 弱动量区域
- 寻找反弹信号
- 此处的背离预示潜在反转
**波段填充**：20-80之间的深色背景，增强视觉清晰度
#### 3. **RSI视觉增强**
**背景颜色指示**
- 绿色背景：RSI在50以上（看涨偏向）
- 红色背景：RSI在50以下（看跌偏向）
- 可选显示，图表更清爽
- 帮助识别整体动量方向
**穿越标签**
- "突破"：RSI向上穿越50
- "跌破"：RSI向下穿越50
- 标记动量转变点
- 可开关
#### 4. **高级RSI背离检测**
指标仅为RSI（最可靠的振荡器）提供全面背离检测：
**常规看涨背离（黄色）**
- **价格**：更低的低点
- **RSI**：更高的低点
- **信号**：潜在向上反转
- **标签**："涨"
- **最常见**：在超卖水平附近（30以下）
**常规看跌背离（蓝色）**
- **价格**：更高的高点
- **RSI**：更低的高点
- **信号**：潜在向下反转
- **标签**："跌"
- **最常见**：在超买水平附近（70以上）
**隐藏看涨背离（浅黄色）**
- **价格**：更高的低点
- **RSI**：更低的低点
- **信号**：上升趋势延续
- **标签**："隐涨"
- **用途**：加仓现有多头
**隐藏看跌背离（浅蓝色）**
- **价格**：更低的高点
- **RSI**：更高的高点
- **信号**：下降趋势延续
- **标签**："隐跌"
- **用途**：加仓现有空头
**背离参数**（完全可自定义）：
- **右侧回溯**：枢轴点右侧K线数（默认：5）
- **左侧回溯**：枢轴点左侧K线数（默认：5）
- **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）
### 配置设置
#### KSI显示设置
- **显示RSI**：切换RSI指标
- **显示CCI**：切换两条CCI线
- **显示威廉指标 %R**：切换威廉指标（可选）
#### RSI设置
- **RSI长度**：计算周期（默认：22）
- **数据源**：价格源（默认：收盘价）
- **显示背景**：切换绿色/红色背景
- **显示穿越标签**：切换50水平穿越标签
#### RSI背离设置
- **右侧回溯**：枢轴检测右侧
- **左侧回溯**：枢轴检测左侧
- **回溯范围最大值**：最大回溯距离
- **回溯范围最小值**：最小回溯距离
- **显示常规背离**：启用常规背离线
- **显示常规背离标签**：启用常规背离标签
- **显示隐藏背离**：启用隐藏背离线
- **显示隐藏背离标签**：启用隐藏背离标签
#### CCI设置
- **CCI长度**：短期周期（默认：33）
- **CCI中期长度**：中期周期（默认：77）
- **数据源**：价格计算（默认：HLC3）
- **显示CCI(33)**：切换短期CCI
- **显示CCI(77)**：切换中期CCI
#### 威廉指标 %R 设置
- **长度**：计算周期（默认：28）
- **数据源**：价格源（默认：收盘价）
### 使用方法
#### 基础动量交易
1. **仅启用RSI**（主要指标）
- 关注50水平穿越
- 启用穿越标签获取信号
2. **识别动量方向**
- RSI > 50 = 看涨动量
- RSI < 50 = 看跌动量
- 背景颜色确认方向
3. **寻找极值**
- RSI > 80 = 超买（考虑卖出）
- RSI < 20 = 超卖（考虑买入）
4. **交易设置**
- RSI从超卖区向上穿越50时做多
- RSI从超买区向下穿越50时做空
#### 背离交易
1. **启用RSI和背离检测**
- 打开常规背离
- 可选添加隐藏背离
2. **等待背离信号**
- 黄色标签 = 看涨背离
- 蓝色标签 = 看跌背离
3. **用价格结构确认**
- 等待支撑/阻力突破
- 寻找K线形态
- 检查成交量确认
4. **进入仓位**
- 确认后进入
- 止损设在背离枢轴点之外
- 目标下一个关键水平
#### 多振荡器确认
1. **启用全部三个指标**
- RSI（动量）
- CCI双周期（周期分析）
- 威廉指标 %R（极值）
2. **寻找一致性**
- 全部在50以上 = 强劲看涨
- 全部在50以下 = 强劲看跌
- 信号混合 = 盘整
3. **识别极值**
- 所有指标 > 80 = 极度超买
- 所有指标 < 20 = 极度超卖
4. **交易反转**
- 所有指标在极值一致时逆势进入
- 可能的话用背离确认
- 使用紧密止损
#### CCI双周期分析
1. **启用两条CCI线**
- CCI(33) = 短期
- CCI(77) = 中期
2. **观察穿越**
- 绿色线穿越橙色线向上 = 看涨加速
- 绿色线穿越橙色线向下 = 看跌加速
3. **分析周期间背离**
- 短期上升，中期下降 = 潜在反转
- 两者同时上升 = 强趋势
4. **相应交易**
- 跟随穿越方向
- 线条汇合时退出
### 交易策略
#### 策略1：RSI 50水平穿越
**设置：**
- 启用RSI及背景和标签
- 等待明确趋势
- 寻找回调至50水平
**入场：**
- 多头：回调后出现"突破"标签
- 空头：反弹后出现"跌破"标签
**止损：**
- 多头：近期波动低点之下
- 空头：近期波动高点之上
**离场：**
- 出现相反穿越标签
- 或预定目标（2:1风险收益比）
**适合：**趋势跟随、明确市场
#### 策略2：RSI背离反转
**设置：**
- 启用RSI和常规背离
- 等待极端水平（>70或<30）
- 寻找背离信号
**入场：**
- 多头：超卖水平出现黄色"涨"标签
- 空头：超买水平出现蓝色"跌"标签
**确认：**
- 等待价格突破结构
- 检查成交量增加
- 寻找K线反转形态
**止损：**
- 背离枢轴点之外
**离场：**
- 在50水平部分获利
- 其余在相反极值或背离处离场
**适合：**波段交易、震荡市场
#### 策略3：三重振荡器汇合
**设置：**
- 启用全部三个指标
- 等待全部达到极值（>80或<20）
- 寻找一致性
**入场：**
- 多头：三个全部低于20，第一个向上穿越20
- 空头：三个全部高于80，第一个向下穿越80
**确认：**
- 所有指标必须一致
- 价格在支撑/阻力位
- 成交量激增有帮助
**止损：**
- 固定百分比或基于ATR
**离场：**
- 任一指标穿越50水平时
- 或在预定目标
**适合：**高概率反转、波动市场
#### 策略4：CCI双周期系统
**设置：**
- 仅启用两条CCI线
- 禁用RSI和威廉指标以保持清晰
- 观察穿越
**入场：**
- 多头：CCI(33)在50线下方向上穿越CCI(77)
- 空头：CCI(33)在50线上方向下穿越CCI(77)
**确认：**
- 两者都应朝入场方向移动
- 价格突破关键水平有帮助
**止损：**
- CCI反向穿越时
**离场：**
- 两条CCI进入相反极值区域
- 或移动止损
**适合：**捕捉趋势延续、动量交易
#### 策略5：隐藏背离延续
**设置：**
- 启用RSI和隐藏背离
- 确认现有趋势
- 等待回调
**入场：**
- 上升趋势：回调期间出现"隐涨"标签
- 下降趋势：反弹期间出现"隐跌"标签
**确认：**
- 价格守住关键移动平均线
- 趋势结构完整
**止损：**
- 回调极值之外
**离场：**
- 出现常规背离（反转警告）
- 或趋势结构破坏
**适合：**加仓、趋势交易
### 最佳实践
#### 选择显示哪些指标
**新手：**
- 仅使用RSI
- 启用背景颜色和标签
- 关注50水平穿越
- 简单有效
**中级交易者：**
- RSI + 常规背离
- 添加CCI确认
- 使用双重视角
- 更高准确度
**高级交易者：**
- 全部三个指标
- 完整背离检测
- 多时间框架分析
- 信息最大化
#### 振荡器优先级
**主要**：RSI (22)
- 最可靠
- 最佳背离检测
- 适用所有时间框架
- 用作主要决策依据
**次要**：CCI (33/77)
- 添加周期分析
- 确认效果好
- 双周期穿越有价值
- 用于确认RSI信号
**第三**：威廉指标 %R (28)
- 极值读数有用
- 更波动
- 最适合短期
- 谨慎使用以获额外确认
#### 时间框架考虑
**低时间框架（1分钟-15分钟）：**
- 更多信号，可靠性较低
- 使用紧密背离参数
- 关注RSI穿越
- 快速进出
**中等时间框架（30分钟-4小时）：**
- 信号频率平衡
- 默认设置效果好
- 最适合背离交易
- 波段交易最优
**高时间框架（日线+）：**
- 信号较少但更强
- 扩大背离范围
- 所有指标更可靠
- 最适合仓位交易
#### 背离交易技巧
1. **等待确认**
- 仅背离不够
- 需要价格结构突破
- 成交量帮助验证
2. **极值处最佳**
- 80/20水平附近的背离最可靠
- 中间水平背离常失败
- 结合支撑/阻力
3. **多重背离**
- 第二次背离强于第一次
- 第三次背离极其强大
- 注意"三重背离"
4. **时间框架对齐**
- 检查更高时间框架方向
- 顺大趋势方向交易背离
- 逆势背离风险更大
### 指标组合
**与移动平均线配合：**
- 使用EMA（21/55/144）确定趋势
- KSI用于入场时机
- 两者一致时进入
**与成交量配合：**
- 成交量确认突破
- 背离 + 成交量背离 = 更强
- 极值处低成交量 = 可能反转
**与支撑/阻力配合：**
- 价格水平作为目标
- KSI用于入场时机
- 水平处的背离 = 最高概率
**与Bias指标配合：**
- Bias显示价格偏离
- KSI显示动量
- 两者都背离 = 强反转信号
**与OBV指标配合：**
- OBV显示成交量趋势
- KSI显示价格动量
- 成交量/动量背离强大
### 常见形态
1. **看涨反转**：所有振荡器超卖 + RSI看涨背离
2. **看跌反转**：所有振荡器超买 + RSI看跌背离
3. **趋势加速**：RSI > 50，两条CCI上升，威廉指标不极端
4. **趋势减弱**：价格上升时RSI下降（背离前警告）
5. **强趋势**：所有振荡器长时间保持在50上方/下方
6. **盘整**：振荡器频繁穿越50无极值
7. **衰竭**：多个振荡器在极值 + 隐藏背离失败
### 性能提示
- 从简单开始：仅RSI
- 学习时逐渐添加指标
- 禁用未使用功能以保持图表清晰
- 策略性使用标签（不总是开启）
- 为您的市场测试不同RSI长度
- 根据波动性调整背离参数
### 警报条件
指标包含以下警报：
- RSI向上穿越50
- RSI向下穿越50
- RSI常规看涨背离
- RSI常规看跌背离
- RSI隐藏看涨背离
- RSI隐藏看跌背离
---
## 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。
EMA Dynamic Crossover Detector with Real-Time Signal TableDescriptionWhat This Indicator Does:This indicator monitors all possible crossovers between four key exponential moving averages (20, 50, 100, and 200 periods) and displays them both visually on the chart and in an organized data table. Unlike standard EMA indicators that only plot the lines, this tool actively detects every crossover event, marks the exact crossover point with a circle, records the precise price level, and maintains a running log of all crossovers during the trading session. It's designed for traders who want comprehensive EMA crossover analysis without manually watching multiple moving average pairs.Key Features:
Four Essential EMAs: Plots 20, 50, 100, and 200-period exponential moving averages with color-coded thin lines for clean chart presentation
Complete Crossover Detection: Monitors all 6 possible EMA pair combinations (20×50, 20×100, 20×200, 50×100, 50×200, 100×200) in both directions
Precise Price Marking: Places colored circles at the exact average price where crossovers occur (not just at candle close)
Real-Time Signal Table: Displays up to 10 most recent crossovers with timestamp, direction, exact price, and signal type
Session Filtering: Only records crossovers during active trading hours (10:00-18:00 Istanbul time) to avoid noise from low-liquidity periods
Automatic Daily Reset: Clears the signal table at the start of each new trading day for fresh analysis
Built-In Alerts: Two alert conditions (bullish and bearish crossovers) that can be configured to send notifications
How It Works:The indicator calculates four exponential moving averages using the standard EMA formula, then continuously monitors for crossover events using Pine Script's ta.crossover() and ta.crossunder() functions:Bullish Crossovers (Green ▲):
When a faster EMA crosses above a slower EMA, indicating potential upward momentum:
20 crosses above 50, 100, or 200
50 crosses above 100 or 200
100 crosses above 200 (Golden Cross when it's the 50×200)
Bearish Crossovers (Red ▼):
When a faster EMA crosses below a slower EMA, indicating potential downward momentum:
20 crosses below 50, 100, or 200
50 crosses below 100 or 200
100 crosses below 200 (Death Cross when it's the 50×200)
Price Calculation:
Instead of marking crossovers at the candle's close price (which might not be where the actual cross occurred), the indicator calculates the average price between the two crossing EMAs, providing a more accurate representation of the crossover point.Signal Table Structure:The table in the top-right corner displays four columns:
Saat (Time): Exact time of crossover in HH:MM format
Yön (Direction): Arrow indicator (▲ green for bullish, ▼ red for bearish)
Fiyat (Price): Calculated average price at the crossover point
Durum (Status): Signal classification ("ALIŞ" for buy signals, "SATIŞ" for sell signals) with color-coded background
The table shows up to 10 most recent crossovers, automatically updating as new signals appear. If no crossovers have occurred during the session within the time filter, it displays "Henüz kesişim yok" (No crossovers yet).EMA Color Coding:
EMA 20 (Aqua/Turquoise): Fastest-reacting, most sensitive to recent price changes
EMA 50 (Green): Short-term trend indicator
EMA 100 (Yellow): Medium-term trend indicator
EMA 200 (Red): Long-term trend baseline, key support/resistance level
How to Use:For Day Traders:
Monitor 20×50 crossovers for quick entry/exit signals within the day
Use the time filter (10:00-18:00) to focus on high-volume trading hours
Check the signal table throughout the session to track momentum shifts
Look for confirmation: if 20 crosses above 50 and price is above EMA 200, bullish bias is stronger
For Swing Traders:
Focus on 50×200 crossovers (Golden Cross/Death Cross) for major trend changes
Use higher timeframes (4H, Daily) for more reliable signals
Wait for price to close above/below the crossover point before entering
Combine with support/resistance levels for better entry timing
For Position Traders:
Monitor 100×200 crossovers on daily/weekly charts for long-term trend changes
Use as confirmation of major market shifts
Don't react to every crossover—wait for sustained movement after the cross
Consider multiple timeframe analysis (if crossovers align on weekly and daily, signal is stronger)
Understanding EMA Hierarchies:The indicator becomes most powerful when you understand EMA relationships:Bullish Hierarchy (Strongest to Weakest):
All EMAs ascending (20 > 50 > 100 > 200): Strong uptrend
20 crosses above 50 while both are above 200: Pullback ending in uptrend
50 crosses above 200 while 20/50 below: Early trend reversal signal
Bearish Hierarchy (Strongest to Weakest):
All EMAs descending (20 < 50 < 100 < 200): Strong downtrend
20 crosses below 50 while both are below 200: Rally ending in downtrend
50 crosses below 200 while 20/50 above: Early trend reversal signal
Trading Strategy Examples:Pullback Entry Strategy:
Identify major trend using EMA 200 (price above = uptrend, below = downtrend)
Wait for pullback (20 crosses below 50 in uptrend, or above 50 in downtrend)
Enter when 20 re-crosses 50 in the trend direction
Place stop below/above the recent swing point
Exit when 20 crosses 50 against the trend again
Golden Cross/Death Cross Strategy:
Wait for 50×200 crossover (appears in the signal table)
Verify: Check if crossover occurs with increasing volume
Entry: Enter in the direction of the cross after a pullback
Stop: Place stop below/above the 200 EMA
Target: Swing high/low or when opposite crossover occurs
Multi-Crossover Confirmation:
Watch for multiple crossovers in the same direction within a short period
Example: 20×50 crossover followed by 20×100 = strengthening momentum
Enter after the second confirmation crossover
More crossovers = stronger signal but also means you're entering later
Time Filter Benefits:The 10:00-18:00 Istanbul time filter prevents recording crossovers during:
Pre-market volatility and gaps
Low-volume overnight sessions (for 24-hour markets)
After-hours erratic movements
Multi SMA + Golden/Death + Heatmap + BB**Multi SMA (50/100/200) + Golden/Death + Candle Heatmap + BB**
A practical trend toolkit that blends classic 50/100/200 SMAs with clear crossover labels, special 🚀 Golden / 💀 Death Cross markers, and a readable candle heatmap based on a dynamic regression midline and volatility bands. Optional Bollinger Bands are included for context.
* See trend direction at a glance with SMAs.
* Get minimal, de-cluttered labels on important crosses (50↔100, 50↔200, 100↔200).
* Highlight big regime shifts with special Golden/Death tags.
* Read momentum and volatility with the candle heatmap.
* Add Bollinger Bands if you want classic mean-reversion context.
Designed to be lightweight, non-repainting on confirmed bars, and flexible across timeframes.
# What This Indicator Does (plain English)
* **Tracks trend** using **SMA 50/100/200** and lets you optionally compute each SMA on a higher or different timeframe (HTF-safe, no lookahead).
* **Prints labels** when SMAs cross each other (up or down). You can force signals only after bar close to avoid repaint.
* **Marks Golden/Death Crosses** (50 over/under 200) with special labels so major regime changes stand out.
* **Colors candles** with a **heatmap** built from a regression midline and volatility bands—greenish above, reddish below, with a smooth gradient.
* **Optionally shows Bollinger Bands** (basis SMA + stdev bands) and fills the area between them.
* **Includes alert conditions** for Golden and Death Cross so you can automate notifications.
---
# Settings — Simple Explanations
## Source
* **Source**: Price source used to calculate SMAs and Bollinger basis. Default: `close`.
## SMA 50
* **Show 50**: Turn the SMA(50) line on/off.
* **Length 50**: How many bars to average. Lower = faster but noisier.
* **Color 50** / **Width 50**: Visual style.
* **Timeframe 50**: Optional alternate timeframe for SMA(50). Leave empty to use the chart timeframe.
## SMA 100
* **Show 100**: Turn the SMA(100) line on/off.
* **Length 100**: Bars used for the mid-term trend.
* **Color 100** / **Width 100**: Visual style.
* **Timeframe 100**: Optional alternate timeframe for SMA(100).
## SMA 200
* **Show 200**: Turn the SMA(200) line on/off.
* **Length 200**: Bars used for the long-term trend.
* **Color 200** / **Width 200**: Visual style.
* **Timeframe 200**: Optional alternate timeframe for SMA(200).
## Signals (crossover labels)
* **Show crossover signals**: Prints triangle labels on SMA crosses (50↔100, 50↔200, 100↔200).
* **Wait for bar close (confirmed)**: If ON, signals only appear after the candle closes (reduces repaint).
* **Min bars between same-pair signals**: Minimum spacing to avoid duplicate labels from the same SMA pair too often.
* **Trend filter (buy: 50>100>200, sell: 50<100<200)**: Only show bullish labels when SMAs are stacked bullish (50 above 100 above 200), and only show bearish labels when stacked bearish.
### Label Offset
* **Offset mode**: Choose how to push labels away from price:
* **Percent**: Offset is a % of price.
* **ATR x**: Offset is ATR(14) × multiplier.
* **Percent of price (%)**: Used when mode = Percent.
* **ATR multiplier (for ‘ATR x’)**: Used when mode = ATR x.
### Label Colors
* **Bull color** / **Bear color**: Background of triangle labels.
* **Bull label text color** / **Bear label text color**: Text color inside the triangles.
## Golden / Death Cross
* **Show 🚀 Golden Cross (50↑200)**: Show a special “Golden” label when SMA50 crosses above SMA200.
* **Golden label color** / **Golden text color**: Styling for Golden label.
* **Show 💀 Death Cross (50↓200)**: Show a special “Death” label when SMA50 crosses below SMA200.
* **Death label color** / **Death text color**: Styling for Death label.
## Candle Heatmap
* **Enable heatmap candle colors**: Turns the heatmap on/off.
* **Length**: Lookback for the regression midline and volatility measure.
* **Deviation Multiplier**: Band width around the midline (bigger = wider).
* **Volatility basis**:
* **RMA Range** (smoothed high-low range)
* **Stdev** (standard deviation of close)
* **Upper/Middle/Lower color**: Gradient colors for the heatmap.
* **Heatmap transparency (0..100)**: 0 = solid, 100 = invisible.
* **Force override base candles**: Repaint base candles so heatmap stays visible even if your chart has custom coloring.
## Bollinger Bands (optional)
* **Show Bollinger Bands**: Toggle the overlay on/off.
* **Length**: Basis SMA length.
* **StdDev Multiplier**: Distance of bands from the basis in standard deviations.
* **Basis color** / **Band color**: Line colors for basis and bands.
* **Bands fill transparency**: Opacity of the fill between upper/lower bands.
---
# Features & How It Works
## 1) HTF-Safe SMAs
Each SMA can be calculated on the chart timeframe or a higher/different timeframe you choose. The script pulls HTF values **without lookahead** (non-repainting on confirmed bars).
## 2) Crossover Labels (Three Pairs)
* **50↔100**, **50↔200**, **100↔200**:
* **Triangle Up** label when the first SMA crosses **above** the second.
* **Triangle Down** label when it crosses **below**.
* Optional **Trend Filter** ensures only signals aligned with the overall stack (50>100>200 for bullish, 50<100<200 for bearish).
* **Debounce** spacing avoids repeated labels for the same pair too close together.
## 3) Golden / Death Cross Highlights
* **🚀 Golden Cross**: SMA50 crosses **above** SMA200 (often a longer-term bullish regime shift).
* **💀 Death Cross**: SMA50 crosses **below** SMA200 (often a longer-term bearish regime shift).
* Separate styling so they stand out from regular cross labels.
## 4) Candle Heatmap
* Builds a **regression midline** with **volatility bands**; colors candles by their position inside that channel.
* Smooth gradient: lower side → reddish, mid → yellowish, upper side → greenish.
* Helps you see momentum and “where price sits” relative to a dynamic channel.
## 5) Bollinger Bands (Optional)
* Classic **basis SMA** ± **StdDev** bands.
* Light visual context for mean-reversion and volatility expansion.
## 6) Alerts
* **Golden Cross**: `🚀 GOLDEN CROSS: SMA 50 crossed ABOVE SMA 200`
* **Death Cross**: `💀 DEATH CROSS: SMA 50 crossed BELOW SMA 200`
Add these to your alerts to get notified automatically.
---
# Tips & Notes
* For fewer false positives, keep **“Wait for bar close”** ON, especially on lower timeframes.
* Use the **Trend Filter** to align signals with the broader stack and cut noise.
* For HTF context, set **Timeframe 50/100/200** to higher frames (e.g., H1/H4/D) while you trade on a lower frame.
* Heatmap “Length” and “Deviation Multiplier” control smoothness and channel width—tune for your asset’s volatility.
RSI Overbought/Oversold + Divergence Indicator (new)//@version=5
indicator('CryptoSignalScanner - RSI Overbought/Oversold + Divergence Indicator (new)',
//---------------------------------------------------------------------------------------------------------------------------------
//--- Define Colors ---------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------
vWhite = #FFFFFF
vViolet = #C77DF3
vIndigo = #8A2BE2
vBlue = #009CDF
vGreen = #5EBD3E
vYellow = #FFB900
vRed = #E23838
longColor = color.green
shortColor = color.red
textColor = color.white
bullishColor = color.rgb(38,166,154,0) //Used in the display table
bearishColor = color.rgb(239,83,79,0) //Used in the display table
nomatchColor = color.silver //Used in the display table
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Functions--------------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
TF2txt(TF) =>
switch TF
"S" => "RSI 1s:"
"5S" => "RSI 5s:"
"10S" => "RSI 10s:"
"15S" => "RSI 15s:"
"30S" => "RSI 30s"
"1" => "RSI 1m:"
"3" => "RSI 3m:"
"5" => "RSI 5m:"
"15" => "RSI 15m:"
"30" => "RSI 30m"
"45" => "RSI 45m"
"60" => "RSI 1h:"
"120" => "RSI 2h:"
"180" => "RSI 3h:"
"240" => "RSI 4h:"
"480" => "RSI 8h:"
"D" => "RSI 1D:"
"1D" => "RSI 1D:"
"2D" => "RSI 2D:"
"3D" => "RSI 2D:"
"3D" => "RSI 3W:"
"W" => "RSI 1W:"
"1W" => "RSI 1W:"
"M" => "RSI 1M:"
"1M" => "RSI 1M:"
"3M" => "RSI 3M:"
"6M" => "RSI 6M:"
"12M" => "RSI 12M:"
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Show/Hide Settings ----------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsiShowInput = input(true, title='Show RSI', group='Show/Hide Settings')
maShowInput = input(false, title='Show MA', group='Show/Hide Settings')
showRSIMAInput = input(true, title='Show RSIMA Cloud', group='Show/Hide Settings')
rsiBandShowInput = input(true, title='Show Oversold/Overbought Lines', group='Show/Hide Settings')
rsiBandExtShowInput = input(true, title='Show Oversold/Overbought Extended Lines', group='Show/Hide Settings')
rsiHighlightShowInput = input(true, title='Show Oversold/Overbought Highlight Lines', group='Show/Hide Settings')
DivergenceShowInput = input(true, title='Show RSI Divergence Labels', group='Show/Hide Settings')
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Table Settings --------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsiShowTable = input(true, title='Show RSI Table Information box', group="RSI Table Settings")
rsiTablePosition = input.string(title='Location', defval='middle_right', options= , group="RSI Table Settings", inline='1')
rsiTextSize = input.string(title=' Size', defval='small', options= , group="RSI Table Settings", inline='1')
rsiShowTF1 = input(true, title='Show TimeFrame1', group="RSI Table Settings", inline='tf1')
rsiTF1 = input.timeframe("15", title=" Time", group="RSI Table Settings", inline='tf1')
rsiShowTF2 = input(true, title='Show TimeFrame2', group="RSI Table Settings", inline='tf2')
rsiTF2 = input.timeframe("60", title=" Time", group="RSI Table Settings", inline='tf2')
rsiShowTF3 = input(true, title='Show TimeFrame3', group="RSI Table Settings", inline='tf3')
rsiTF3 = input.timeframe("240", title=" Time", group="RSI Table Settings", inline='tf3')
rsiShowTF4 = input(true, title='Show TimeFrame4', group="RSI Table Settings", inline='tf4')
rsiTF4 = input.timeframe("D", title=" Time", group="RSI Table Settings", inline='tf4')
rsiShowHist = input(true, title='Show RSI Historical Columns', group="RSI Table Settings", tooltip='Show the information of the 2 previous closed candles')
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- RSI Input Settings ----------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsiSourceInput = input.source(close, 'Source', group='RSI Settings')
rsiLengthInput = input.int(14, minval=1, title='RSI Length', group='RSI Settings', tooltip='Here we set the RSI lenght')
rsiColorInput = input.color(#26a69a, title="RSI Color", group='RSI Settings')
rsimaColorInput = input.color(#ef534f, title="RSIMA Color", group='RSI Settings')
rsiBandColorInput = input.color(#787B86, title="RSI Band Color", group='RSI Settings')
rsiUpperBandExtInput = input.int(title='RSI Overbought Extended Line', defval=80, minval=50, maxval=100, group='RSI Settings')
rsiUpperBandInput = input.int(title='RSI Overbought Line', defval=70, minval=50, maxval=100, group='RSI Settings')
rsiLowerBandInput = input.int(title='RSI Oversold Line', defval=30, minval=0, maxval=50, group='RSI Settings')
rsiLowerBandExtInput = input.int(title='RSI Oversold Extended Line', defval=20, minval=0, maxval=50, group='RSI Settings')
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- MA Input Settings -----------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
maTypeInput = input.string("EMA", title="MA Type", options= , group="MA Settings")
maLengthInput = input.int(14, title="MA Length", group="MA Settings")
maColorInput = input.color(color.yellow, title="MA Color", group='MA Settings') //#7E57C2
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Divergence Input Settings ---------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
lbrInput = input(title="Pivot Lookback Right", defval=2, group='RSI Divergence Settings')
lblInput = input(title="Pivot Lookback Left", defval=2, group='RSI Divergence Settings')
lbRangeMaxInput = input(title="Max of Lookback Range", defval=10, group='RSI Divergence Settings')
lbRangeMinInput = input(title="Min of Lookback Range", defval=2, group='RSI Divergence Settings')
plotBullInput = input(title="Plot Bullish", defval=true, group='RSI Divergence Settings')
plotHiddenBullInput = input(title="Plot Hidden Bullish", defval=true, group='RSI Divergence Settings')
plotBearInput = input(title="Plot Bearish", defval=true, group='RSI Divergence Settings')
plotHiddenBearInput = input(title="Plot Hidden Bearish", defval=true, group='RSI Divergence Settings')
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- RSI Calculation -------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsi = ta.rsi(rsiSourceInput, rsiLengthInput)
rsiprevious = rsi
= request.security(syminfo.tickerid, rsiTF1, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on)
= request.security(syminfo.tickerid, rsiTF2, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on)
= request.security(syminfo.tickerid, rsiTF3, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on)
= request.security(syminfo.tickerid, rsiTF4, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on)
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- MA Calculation -------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
ma(source, length, type) =>
switch type
"SMA" => ta.sma(source, length)
"Bollinger Bands" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
rsiMA = ma(rsi, maLengthInput, maTypeInput)
rsiMAPrevious = rsiMA
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Stoch RSI Settings + Calculation --------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
showStochRSI = input(false, title="Show Stochastic RSI", group='Stochastic RSI Settings')
smoothK = input.int(title="Stochastic K", defval=3, minval=1, maxval=10, group='Stochastic RSI Settings')
smoothD = input.int(title="Stochastic D", defval=4, minval=1, maxval=10, group='Stochastic RSI Settings')
lengthRSI = input.int(title="Stochastic RSI Lenght", defval=14, minval=1, group='Stochastic RSI Settings')
lengthStoch = input.int(title="Stochastic Lenght", defval=14, minval=1, group='Stochastic RSI Settings')
colorK = input.color(color.rgb(41,98,255,0), title="K Color", group='Stochastic RSI Settings', inline="1")
colorD = input.color(color.rgb(205,109,0,0), title="D Color", group='Stochastic RSI Settings', inline="1")
StochRSI = ta.rsi(rsiSourceInput, lengthRSI)
k = ta.sma(ta.stoch(StochRSI, StochRSI, StochRSI, lengthStoch), smoothK) //Blue Line
d = ta.sma(k, smoothD) //Red Line
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Divergence Settings ------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
bearColor = color.red
bullColor = color.green
hiddenBullColor = color.new(color.green, 50)
hiddenBearColor = color.new(color.red, 50)
//textColor = color.white
noneColor = color.new(color.white, 100)
osc = rsi
plFound = na(ta.pivotlow(osc, lblInput, lbrInput)) ? false : true
phFound = na(ta.pivothigh(osc, lblInput, lbrInput)) ? false : true
_inRange(cond) =>
bars = ta.barssince(cond == true)
lbRangeMinInput <= bars and bars <= lbRangeMaxInput
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Define Plot & Line Colors ---------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsiColor = rsi >= rsiMA ? rsiColorInput : rsimaColorInput
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Plot Lines ------------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
// Create a horizontal line at a specific price level
myLine = line.new(bar_index , 75, bar_index, 75, color = color.rgb(187, 14, 14), width = 2)
bottom = line.new(bar_index , 50, bar_index, 50, color = color.rgb(223, 226, 28), width = 2)
mymainLine = line.new(bar_index , 60, bar_index, 60, color = color.rgb(13, 154, 10), width = 3)
hline(50, title='RSI Baseline', color=color.new(rsiBandColorInput, 50), linestyle=hline.style_solid, editable=false)
hline(rsiBandExtShowInput ? rsiUpperBandExtInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false)
hline(rsiBandShowInput ? rsiUpperBandInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false)
hline(rsiBandShowInput ? rsiLowerBandInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false)
hline(rsiBandExtShowInput ? rsiLowerBandExtInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false)
bgcolor(rsiHighlightShowInput ? rsi >= rsiUpperBandExtInput ? color.new(rsiColorInput, 70) : na : na, title="Show Extended Oversold Highlight", editable=false)
bgcolor(rsiHighlightShowInput ? rsi >= rsiUpperBandInput ? rsi < rsiUpperBandExtInput ? color.new(#64ffda, 90) : na : na: na, title="Show Overbought Highlight", editable=false)
bgcolor(rsiHighlightShowInput ? rsi <= rsiLowerBandInput ? rsi > rsiLowerBandExtInput ? color.new(#F43E32, 90) : na : na : na, title="Show Extended Oversold Highlight", editable=false)
bgcolor(rsiHighlightShowInput ? rsi <= rsiLowerBandInput ? color.new(rsimaColorInput, 70) : na : na, title="Show Oversold Highlight", editable=false)
maPlot = plot(maShowInput ? rsiMA : na, title='MA', color=color.new(maColorInput,0), linewidth=1)
rsiMAPlot = plot(showRSIMAInput ? rsiMA : na, title="RSI EMA", color=color.new(rsimaColorInput,0), editable=false, display=display.none)
rsiPlot = plot(rsiShowInput ? rsi : na, title='RSI', color=color.new(rsiColor,0), linewidth=1)
fill(rsiPlot, rsiMAPlot, color=color.new(rsiColor, 60), title="RSIMA Cloud")
plot(showStochRSI ? k : na, title='Stochastic K', color=colorK, linewidth=1)
plot(showStochRSI ? d : na, title='Stochastic D', color=colorD, linewidth=1)
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Plot Divergence -------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
// Regular Bullish
// Osc: Higher Low
oscHL = osc > ta.valuewhen(plFound, osc , 1) and _inRange(plFound )
// Price: Lower Low
priceLL = low < ta.valuewhen(plFound, low , 1)
bullCond = plotBullInput and priceLL and oscHL and plFound
plot(
plFound ? osc : na,
offset=-lbrInput,
title="Regular Bullish",
linewidth=2,
color=(bullCond ? bullColor : noneColor)
)
plotshape(
DivergenceShowInput ? bullCond ? osc : na : na,
offset=-lbrInput,
title="Regular Bullish Label",
text=" Bull ",
style=shape.labelup,
location=location.absolute,
color=bullColor,
textcolor=textColor
)
//------------------------------------------------------------------------------
// Hidden Bullish
// Osc: Lower Low
oscLL = osc < ta.valuewhen(plFound, osc , 1) and _inRange(plFound )
// Price: Higher Low
priceHL = low > ta.valuewhen(plFound, low , 1)
hiddenBullCond = plotHiddenBullInput and priceHL and oscLL and plFound
plot(
plFound ? osc : na,
offset=-lbrInput,
title="Hidden Bullish",
linewidth=2,
color=(hiddenBullCond ? hiddenBullColor : noneColor)
)
plotshape(
DivergenceShowInput ? hiddenBullCond ? osc : na : na,
offset=-lbrInput,
title="Hidden Bullish Label",
text=" H Bull ",
style=shape.labelup,
location=location.absolute,
color=bullColor,
textcolor=textColor
)
//------------------------------------------------------------------------------
// Regular Bearish
// Osc: Lower High
oscLH = osc < ta.valuewhen(phFound, osc , 1) and _inRange(phFound )
// Price: Higher High
priceHH = high > ta.valuewhen(phFound, high , 1)
bearCond = plotBearInput and priceHH and oscLH and phFound
plot(
phFound ? osc : na,
offset=-lbrInput,
title="Regular Bearish",
linewidth=2,
color=(bearCond ? bearColor : noneColor)
)
plotshape(
DivergenceShowInput ? bearCond ? osc : na : na,
offset=-lbrInput,
title="Regular Bearish Label",
text=" Bear ",
style=shape.labeldown,
location=location.absolute,
color=bearColor,
textcolor=textColor
)
//------------------------------------------------------------------------------
// Hidden Bearish
// Osc: Higher High
oscHH = osc > ta.valuewhen(phFound, osc , 1) and _inRange(phFound )
// Price: Lower High
priceLH = high < ta.valuewhen(phFound, high , 1)
hiddenBearCond = plotHiddenBearInput and priceLH and oscHH and phFound
plot(
phFound ? osc : na,
offset=-lbrInput,
title="Hidden Bearish",
linewidth=2,
color=(hiddenBearCond ? hiddenBearColor : noneColor)
)
plotshape(
DivergenceShowInput ? hiddenBearCond ? osc : na : na,
offset=-lbrInput,
title="Hidden Bearish Label",
text=" H Bear ",
style=shape.labeldown,
location=location.absolute,
color=bearColor,
textcolor=textColor
)
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Check RSI Lineup ------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
bullTF = rsi > rsi and rsi > rsi
bearTF = rsi < rsi and rsi < rsi
bullTF1 = rsi1 > rsi1_1 and rsi1_1 > rsi1_2
bearTF1 = rsi1 < rsi1_1 and rsi1_1 < rsi1_2
bullTF2 = rsi2 > rsi2_1 and rsi2_1 > rsi2_2
bearTF2 = rsi2 < rsi2_1 and rsi2_1 < rsi2_2
bullTF3 = rsi3 > rsi3_1 and rsi3_1 > rsi3_2
bearTF3 = rsi3 < rsi3_1 and rsi3_1 < rsi3_2
bullTF4 = rsi4 > rsi4_1 and rsi4_1 > rsi4_2
bearTF4 = rsi4 < rsi4_1 and rsi4_1 < rsi4_2
bbTxt(bull,bear) =>
bull ? "BULLISH" : bear ? "BEARISCH" : 'NO LINEUP'
bbColor(bull,bear) =>
bull ? bullishColor : bear ? bearishColor : nomatchColor
newTC(tBox, col, row, txt, width, txtColor, bgColor, txtHA, txtSize) =>
table.cell(table_id=tBox,column=col, row=row, text=txt, width=width,text_color=txtColor,bgcolor=bgColor, text_halign=txtHA, text_size=txtSize)
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Define RSI Table Setting ----------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
width_c0 = 0
width_c1 = 0
if rsiShowTable
var tBox = table.new(position=rsiTablePosition, columns=5, rows=6, bgcolor=color.rgb(18,22,33,50), frame_color=color.black, frame_width=1, border_color=color.black, border_width=1)
newTC(tBox, 0,1,"RSI Current",width_c0,color.orange,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,1,str.format(" {0,number,#.##} ", rsi),width_c0,vWhite,rsi < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,1,bbTxt(bullTF, bearTF),width_c0,vWhite,bbColor(bullTF, bearTF),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,1,str.format(" {0,number,#.##} ", rsi ),width_c0,vWhite,rsi < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,1,str.format(" {0,number,#.##} ", rsi ),width_c0,vWhite,rsi < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
if rsiShowTF1
newTC(tBox, 0,2,TF2txt(rsiTF1),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,2,str.format(" {0,number,#.##} ", rsi1),width_c0,vWhite,rsi1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,2,bbTxt(bullTF1, bearTF1),width_c0,vWhite,bbColor(bullTF1,bearTF1),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,2,str.format(" {0,number,#.##} ", rsi1_1),width_c0,vWhite,rsi1_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,2,str.format(" {0,number,#.##} ", rsi1_2),width_c0,vWhite,rsi1_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
if rsiShowTF2
newTC(tBox, 0,3,TF2txt(rsiTF2),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,3,str.format(" {0,number,#.##} ", rsi2),width_c0,vWhite,rsi2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,3,bbTxt(bullTF2, bearTF2),width_c0,vWhite,bbColor(bullTF2,bearTF2),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,3,str.format(" {0,number,#.##} ", rsi2_1),width_c0,vWhite,rsi2_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,3,str.format(" {0,number,#.##} ", rsi2_2),width_c0,vWhite,rsi2_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
if rsiShowTF3
newTC(tBox, 0,4,TF2txt(rsiTF3),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,4,str.format(" {0,number,#.##} ", rsi3),width_c0,vWhite,rsi3 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,4,bbTxt(bullTF3, bearTF3),width_c0,vWhite,bbColor(bullTF3,bearTF3),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,4,str.format(" {0,number,#.##} ", rsi3_1),width_c0,vWhite,rsi3_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,4,str.format(" {0,number,#.##} ", rsi3_2),width_c0,vWhite,rsi3_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
if rsiShowTF4
newTC(tBox, 0,5,TF2txt(rsiTF4),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,5,str.format(" {0,number,#.##} ", rsi4),width_c0,vWhite,rsi4 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,5,bbTxt(bullTF4, bearTF4),width_c0,vWhite,bbColor(bullTF4,bearTF4),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,5,str.format(" {0,number,#.##} ", rsi4_1),width_c0,vWhite,rsi4_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,5,str.format(" {0,number,#.##} ", rsi4_2),width_c0,vWhite,rsi4_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
//------------------------------------------------------
//--- Alerts -------------------------------------------
//------------------------------------------------------
Price Action Concepts [RUDYINDICATOR]/// This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) creativecommons.org
// © RUDYBANK INDICATOR - formerly know as RUDY INDICATOR
//@version=5
indicator("Price Action Concepts ", shorttitle = "RUDYINDICATOR-V1
- Price Action RUDYINDICATOR ", overlay = true, max_lines_count = 500, max_labels_count = 500, max_boxes_count = 500, max_bars_back = 500, max_polylines_count = 100)
//-----------------------------------------------------------------------------{
//Boolean set
//-----------------------------------------------------------------------------{
s_BOS = 0
s_CHoCH = 1
i_BOS = 2
i_CHoCH = 3
i_pp_CHoCH = 4
green_candle = 5
red_candle = 6
s_CHoCHP = 7
i_CHoCHP = 8
boolean =
array.from(
false
, false
, false
, false
, false
, false
, false
, false
, false
)
//-----------------------------------------------------------------------------{
// User inputs
//-----------------------------------------------------------------------------{
show_swing_ms = input.string ("All" , "Swing        " , inline = "1", group = "MARKET STRUCTURE" , options = )
show_internal_ms = input.string ("All" , "Internal     " , inline = "2", group = "MARKET STRUCTURE" , options = )
internal_r_lookback = input.int (5 , "" , inline = "2", group = "MARKET STRUCTURE" , minval = 2)
swing_r_lookback = input.int (50 , "" , inline = "1", group = "MARKET STRUCTURE" , minval = 2)
ms_mode = input.string ("Manual" , "Market Structure Mode" , inline = "a", group = "MARKET STRUCTURE" , tooltip = " Use selected lenght\n Use automatic lenght" ,options = )
show_mtf_str = input.bool (true , "MTF Scanner" , inline = "9", group = "MARKET STRUCTURE" , tooltip = "Display Multi-Timeframe Market Structure Trend Directions. Green = Bullish. Red = Bearish")
show_eql = input.bool (false , "Show EQH/EQL" , inline = "6", group = "MARKET STRUCTURE")
plotcandle_bool = input.bool (false , "Plotcandle" , inline = "3", group = "MARKET STRUCTURE" , tooltip = "Displays a cleaner colored candlestick chart in place of the default candles. (requires hiding the current ticker candles)")
barcolor_bool = input.bool (false , "Bar Color" , inline = "4", group = "MARKET STRUCTURE" , tooltip = "Color the candle bodies according to market strucutre trend")
i_ms_up_BOS = input.color (#089981 , "" , inline = "2", group = "MARKET STRUCTURE")
i_ms_dn_BOS = input.color (#f23645 , "" , inline = "2", group = "MARKET STRUCTURE")
s_ms_up_BOS = input.color (#089981 , "" , inline = "1", group = "MARKET STRUCTURE")
s_ms_dn_BOS = input.color (#f23645 , "" , inline = "1", group = "MARKET STRUCTURE")
lvl_daily = input.bool (false , "Day   " , inline = "1", group = "HIGHS & LOWS MTF")
lvl_weekly = input.bool (false , "Week " , inline = "2", group = "HIGHS & LOWS MTF")
lvl_monthly = input.bool (false , "Month" , inline = "3", group = "HIGHS & LOWS MTF")
lvl_yearly = input.bool (false , "Year  " , inline = "4", group = "HIGHS & LOWS MTF")
css_d = input.color (color.blue , "" , inline = "1", group = "HIGHS & LOWS MTF")
css_w = input.color (color.blue , "" , inline = "2", group = "HIGHS & LOWS MTF")
css_m = input.color (color.blue , "" , inline = "3", group = "HIGHS & LOWS MTF")
css_y = input.color (color.blue , "" , inline = "4", group = "HIGHS & LOWS MTF")
s_d = input.string ('⎯⎯⎯' , '' , inline = '1', group = 'HIGHS & LOWS MTF' , options = )
s_w = input.string ('⎯⎯⎯' , '' , inline = '2', group = 'HIGHS & LOWS MTF' , options = )
s_m = input.string ('⎯⎯⎯' , '' , inline = '3', group = 'HIGHS & LOWS MTF' , options = )
s_y = input.string ('⎯⎯⎯' , '' , inline = '4', group = 'HIGHS & LOWS MTF' , options = )
ob_show = input.bool (true , "Show Last    " , inline = "1", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Display volumetric order blocks on the chart \n\n Ammount of volumetric order blocks to show")
ob_num = input.int (5 , "" , inline = "1", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Orderblocks number", minval = 1, maxval = 10)
ob_metrics_show = input.bool (true , "Internal Buy/Sell Activity" , inline = "2", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Display volume metrics that have formed the orderblock")
css_metric_up = input.color (color.new(#089981, 50) , "         " , inline = "2", group = "VOLUMETRIC ORDER BLOCKS")
css_metric_dn = input.color (color.new(#f23645 , 50) , "" , inline = "2", group = "VOLUMETRIC ORDER BLOCKS")
ob_swings = input.bool (false , "Swing Order Blocks" , inline = "a", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Display swing volumetric order blocks")
css_swing_up = input.color (color.new(color.gray , 90) , "                 " , inline = "a", group = "VOLUMETRIC ORDER BLOCKS")
css_swing_dn = input.color (color.new(color.silver, 90) , "" , inline = "a", group = "VOLUMETRIC ORDER BLOCKS")
ob_filter = input.string ("None" , "Filtering             " , inline = "d", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Filter out volumetric order blocks by BOS/CHoCH/CHoCH+", options = )
ob_mitigation = input.string ("Absolute" , "Mitigation           " , inline = "4", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Trigger to remove volumetric order blocks", options = )
ob_pos = input.string ("Precise" , "Positioning          " , inline = "k", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Position of the Order Block\n Cover the whole candle\n Cover half candle\n Adjust to volatility\n Same as Accurate but more precise", options = )
use_grayscale = input.bool (false , "Grayscale" , inline = "6", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Use gray as basic order blocks color")
use_show_metric = input.bool (true , "Show Metrics" , inline = "7", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Show volume associated with the orderblock and his relevance")
use_middle_line = input.bool (true , "Show Middle-Line" , inline = "8", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Show mid-line order blocks")
use_overlap = input.bool (true , "Hide Overlap" , inline = "9", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Hide overlapping order blocks")
use_overlap_method = input.string ("Previous" , "Overlap Method    " , inline = "Z", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = " Preserve the most recent volumetric order blocks\n\n Preserve the previous volumetric order blocks", options = )
ob_bull_css = input.color (color.new(#089981 , 90) , "" , inline = "1", group = "VOLUMETRIC ORDER BLOCKS")
ob_bear_css = input.color (color.new(#f23645 , 90) , "" , inline = "1", group = "VOLUMETRIC ORDER BLOCKS")
show_acc_dist_zone = input.bool (false , "" , inline = "1", group = "Accumulation And Distribution")
zone_mode = input.string ("Fast" , "" , inline = "1", group = "Accumulation And Distribution" , tooltip = " Find small zone pattern formation\n Find bigger zone pattern formation" ,options = )
acc_css = input.color (color.new(#089981 , 60) , "" , inline = "1", group = "Accumulation And Distribution")
dist_css = input.color (color.new(#f23645 , 60) , "" , inline = "1", group = "Accumulation And Distribution")
show_lbl = input.bool (false , "Show swing point" , inline = "1", group = "High and Low" , tooltip = "Display swing point")
show_mtb = input.bool (false , "Show High/Low/Equilibrium" , inline = "2", group = "High and Low" , tooltip = "Display Strong/Weak High And Low and Equilibrium")
toplvl = input.color (color.red , "Premium Zone   " , inline = "3", group = "High and Low")
midlvl = input.color (color.gray , "Equilibrium Zone" , inline = "4", group = "High and Low")
btmlvl = input.color (#089981 , "Discount Zone    " , inline = "5", group = "High and Low")
fvg_enable = input.bool (false , "        " , inline = "1", group = "FAIR VALUE GAP" , tooltip = "Display fair value gap")
what_fvg = input.string ("FVG" , "" , inline = "1", group = "FAIR VALUE GAP" , tooltip = "Display fair value gap", options = )
fvg_num = input.int (5 , "Show Last  " , inline = "1a", group = "FAIR VALUE GAP" , tooltip = "Number of fvg to show")
fvg_upcss = input.color (color.new(#089981, 80) , "" , inline = "1", group = "FAIR VALUE GAP")
fvg_dncss = input.color (color.new(color.red , 80) , "" , inline = "1", group = "FAIR VALUE GAP")
fvg_extend = input.int (10 , "Extend FVG" , inline = "2", group = "FAIR VALUE GAP" , tooltip = "Extend the display of the FVG.")
fvg_src = input.string ("Close" , "Mitigation  " , inline = "3", group = "FAIR VALUE GAP" , tooltip = " Use the close of the body as trigger\n\n Use the extreme point of the body as trigger", options = )
fvg_tf = input.timeframe ("" , "Timeframe " , inline = "4", group = "FAIR VALUE GAP" , tooltip = "Timeframe of the fair value gap")
t = color.t (ob_bull_css)
invcol = color.new (color.white , 100)
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - UDT }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
type bar
float o = open
float c = close
float h = high
float l = low
float v = volume
int n = bar_index
int t = time
type Zphl
line top
line bottom
label top_label
label bottom_label
bool stopcross
bool sbottomcross
bool itopcross
bool ibottomcross
string txtup
string txtdn
float topy
float bottomy
float topx
float bottomx
float tup
float tdn
int tupx
int tdnx
float itopy
float itopx
float ibottomy
float ibottomx
float uV
float dV
type FVG
box box
line ln
bool bull
float top
float btm
int left
int right
type ms
float p
int n
float l
type msDraw
int n
float p
color css
string txt
bool bull
type obC
float top
float btm
int left
float avg
float dV
float cV
int wM
int blVP
int brVP
int dir
float h
float l
int n
type obD
box ob
box eOB
box blB
box brB
line mL
type zone
chart.point points
float p
int c
int t
type hqlzone
box pbx
box ebx
box lbx
label plb
label elb
label lbl
type ehl
float pt
int t
float pb
int b
type pattern
string found = "None"
bool isfound = false
int period = 0
bool bull = false
type alerts
bool chochswing = false
bool chochplusswing = false
bool swingbos = false
bool chochplus = false
bool choch = false
bool bos = false
bool equal = false
bool ob = false
bool swingob = false
bool zone = false
bool fvg = false
bool obtouch = false
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - General Setup }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
bar b = bar.new()
var pattern p = pattern.new()
alerts blalert = alerts.new()
alerts bralert = alerts.new()
if p.isfound
p.period += 1
if p.period == 50
p.period := 0
p.found := "None"
p.isfound := false
p.bull := na
switch
b.c > b.o => boolean.set(green_candle, true)
b.c < b.o => boolean.set(red_candle , true)
f_zscore(src, lookback) =>
(src - ta.sma(src, lookback)) / ta.stdev(src, lookback)
var int iLen = internal_r_lookback
var int sLen = swing_r_lookback
vv = f_zscore(((close - close ) / close ) * 100,iLen)
if ms_mode == "Dynamic"
switch
vv >= 1.5 or vv <= -1.5 => iLen := 10
vv >= 1.6 or vv <= -1.6 => iLen := 9
vv >= 1.7 or vv <= -1.7 => iLen := 8
vv >= 1.8 or vv <= -1.8 => iLen := 7
vv >= 1.9 or vv <= -1.9 => iLen := 6
vv >= 2.0 or vv <= -2.0 => iLen := 5
=> iLen
var msline = array.new(0)
iH = ta.pivothigh(high, iLen, iLen)
sH = ta.pivothigh(high, sLen, sLen)
iL = ta.pivotlow (low , iLen, iLen)
sL = ta.pivotlow (low , sLen, sLen)
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - ARRAYS }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
hl () =>
= request.security(syminfo.tickerid , 'D' , hl() , lookahead = barmerge.lookahead_on)
= request.security(syminfo.tickerid , 'W' , hl() , lookahead = barmerge.lookahead_on)
= request.security(syminfo.tickerid , 'M' , hl() , lookahead = barmerge.lookahead_on)
= request.security(syminfo.tickerid , '12M', hl() , lookahead = barmerge.lookahead_on)
lstyle(style) =>
out = switch style
'⎯⎯⎯' => line.style_solid
'----' => line.style_dashed
'····' => line.style_dotted
mtfphl(h, l ,tf ,css, pdhl_style) =>
var line hl = line.new(
na
, na
, na
, na
, xloc = xloc.bar_time
, color = css
, style = lstyle(pdhl_style)
)
var line ll = line.new(
na
, na
, na
, na
, xloc = xloc.bar_time
, color = css
, style = lstyle(pdhl_style)
)
var label lbl = label.new(
na
, na
, xloc = xloc.bar_time
, text = str.format('P{0}L', tf)
, color = invcol
, textcolor = css
, size = size.small
, style = label.style_label_left
)
var label hlb = label.new(
na
, na
, xloc = xloc.bar_time
, text = str.format('P{0}H', tf)
, color = invcol
, textcolor = css
, size = size.small
, style = label.style_label_left
)
hy = ta.valuewhen(h != h , h , 1)
hx = ta.valuewhen(h == high , time , 1)
ly = ta.valuewhen(l != l , l , 1)
lx = ta.valuewhen(l == low , time , 1)
if barstate.islast
extension = time + (time - time ) * 50
line.set_xy1(hl , hx , hy)
line.set_xy2(hl , extension , hy)
label.set_xy(hlb, extension , hy)
line.set_xy1(ll , lx , ly)
line.set_xy2(ll , extension , ly)
label.set_xy(lbl, extension , ly)
if lvl_daily
mtfphl(pdh , pdl , 'D' , css_d, s_d)
if lvl_weekly
mtfphl(pwh , pwl , 'W' , css_w, s_w)
if lvl_monthly
mtfphl(pmh , pml, 'M' , css_m, s_m)
if lvl_yearly
mtfphl(pyh , pyl , '12M', css_y, s_y)
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - Market Structure }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
method darkcss(color css, float factor, bool bull) =>
blue = color.b(css) * (1 - factor)
red = color.r(css) * (1 - factor)
green = color.g(css) * (1 - factor)
color.rgb(red, green, blue, 0)
method f_line(msDraw d, size, style) =>
var line id = na
var label lbl = na
id := line.new(
d.n
, d.p
, b.n
, d.p
, color = d.css
, width = 1
, style = style
)
if msline.size() >= 250
line.delete(msline.shift())
msline.push(id)
lbl := label.new(
int(math.avg(d.n, b.n))
, d.p
, d.txt
, color = invcol
, textcolor = d.css
, style = d.bull ? label.style_label_down : label.style_label_up
, size = size
, text_font_family = font.family_monospace
)
structure(bool mtf) =>
msDraw drw = na
bool isdrw = false
bool isdrwS = false
var color css = na
var color icss = na
var int itrend = 0
var int trend = 0
bool bull_ob = false
bool bear_ob = false
bool s_bull_ob = false
bool s_bear_ob = false
n = bar_index
var ms up = ms.new(
array.new()
, array.new< int >()
, array.new()
)
var ms dn = ms.new(
array.new()
, array.new< int >()
, array.new()
)
var ms sup = ms.new(
array.new()
, array.new< int >()
, array.new()
)
var ms sdn = ms.new(
array.new()
, array.new< int >()
, array.new()
)
switch show_swing_ms
"All" => boolean.set(s_BOS , true ), boolean.set(s_CHoCH, true ) , boolean.set(s_CHoCHP, true )
"CHoCH" => boolean.set(s_BOS , false), boolean.set(s_CHoCH, true ) , boolean.set(s_CHoCHP, false )
"CHoCH+" => boolean.set(s_BOS , false), boolean.set(s_CHoCH, false) , boolean.set(s_CHoCHP, true )
"BOS" => boolean.set(s_BOS , true ), boolean.set(s_CHoCH, false) , boolean.set(s_CHoCHP, false )
"None" => boolean.set(s_BOS , false), boolean.set(s_CHoCH, false) , boolean.set(s_CHoCHP, false )
=> na
switch show_internal_ms
"All" => boolean.set(i_BOS, true ), boolean.set(i_CHoCH, true ), boolean.set(i_CHoCHP, true )
"CHoCH" => boolean.set(i_BOS, false), boolean.set(i_CHoCH, true ), boolean.set(i_CHoCHP, false)
"CHoCH+" => boolean.set(i_BOS, false), boolean.set(i_CHoCH, false ), boolean.set(i_CHoCHP, true )
"BOS" => boolean.set(i_BOS, true ), boolean.set(i_CHoCH, false ), boolean.set(i_CHoCHP, false)
"None" => boolean.set(i_BOS, false), boolean.set(i_CHoCH, false ), boolean.set(i_CHoCHP, false)
=> na
switch
iH =>
up.p.unshift(b.h )
up.l.unshift(b.h )
up.n.unshift(n )
iL =>
dn.p.unshift(b.l )
dn.l.unshift(b.l )
dn.n.unshift(n )
sL =>
sdn.p.unshift(b.l )
sdn.l.unshift(b.l )
sdn.n.unshift(n )
sH =>
sup.p.unshift(b.h )
sup.l.unshift(b.h )
sup.n.unshift(n )
// INTERNAL BULLISH STRUCTURE
if up.p.size() > 0 and dn.l.size() > 1
if ta.crossover(b.c, up.p.first())
bool CHoCH = na
string txt = na
if itrend < 0
CHoCH := true
switch
not CHoCH =>
txt := "BOS"
css := i_ms_up_BOS
blalert.bos := true
if boolean.get(i_BOS) and mtf == false and na(drw)
isdrw := true
drw := msDraw.new(
up.n.first()
, up.p.first()
, i_ms_up_BOS
, txt
, true
)
CHoCH =>
dn.l.first() > dn.l.get(1) ? blalert.chochplus : blalert.choch
txt := dn.l.first() > dn.l.get(1) ? "CHoCH+" : "CHoCH"
css := i_ms_up_BOS.darkcss(0.25, true)
if (dn.l.first() > dn.l.get(1) ? boolean.get(i_CHoCHP) : boolean.get(i_CHoCH)) and mtf == false and na(drw)
isdrw := true
drw := msDraw.new(
up.n.first()
, up.p.first()
, i_ms_up_BOS.darkcss(0.25, true)
, txt
, true
)
if mtf == false
switch
ob_filter == "None" => bull_ob := true
ob_filter == "BOS" and txt == "BOS" => bull_ob := true
ob_filter == "CHoCH" and txt == "CHoCH" => bull_ob := true
ob_filter == "CHoCH+" and txt == "CHoCH+" => bull_ob := true
itrend := 1
up.n.clear()
up.p.clear()
// INTERNAL BEARISH STRUCTURE
if dn.p.size() > 0 and up.l.size() > 1
if ta.crossunder(b.c, dn.p.first())
bool CHoCH = na
string txt = na
if itrend > 0
CHoCH := true
switch
not CHoCH =>
bralert.bos := true
txt := "BOS"
css := i_ms_dn_BOS
if boolean.get(i_BOS) and mtf == false and na(drw)
isdrw := true
drw := msDraw.new(
dn.n.first()
, dn.p.first()
, i_ms_dn_BOS
, txt
, false
)
CHoCH =>
if up.l.first() < up.l.get(1)
bralert.chochplus := true
else
bralert.choch := true
txt := up.l.first() < up.l.get(1) ? "CHoCH+" : "CHoCH"
css := i_ms_dn_BOS.darkcss(0.25, false)
if (up.l.first() < up.l.get(1) ? boolean.get(i_CHoCHP) : boolean.get(i_CHoCH)) and mtf == false and na(drw)
isdrw := true
drw := msDraw.new(
dn.n.first()
, dn.p.first()
, i_ms_dn_BOS.darkcss(0.25, false)
, txt
, false
)
if mtf == false
switch
ob_filter == "None" => bear_ob := true
ob_filter == "BOS" and txt == "BOS" => bear_ob := true
ob_filter == "CHoCH" and txt == "CHoCH" => bear_ob := true
ob_filter == "CHoCH+" and txt == "CHoCH+" => bear_ob := true
itrend := -1
dn.n.clear()
dn.p.clear()
// SWING BULLISH STRUCTURE
if sup.p.size() > 0 and sdn.l.size() > 1
if ta.crossover(b.c, sup.p.first())
bool CHoCH = na
string txt = na
if trend < 0
CHoCH := true
switch
not CHoCH =>
blalert.swingbos := true
txt := "BOS"
icss := s_ms_up_BOS
if boolean.get(s_BOS) and mtf == false and na(drw)
isdrwS := true
drw := msDraw.new(
sup.n.first()
, sup.p.first()
, s_ms_up_BOS
, txt
, true
)
CHoCH =>
if sdn.l.first() > sdn.l.get(1)
blalert.chochplusswing := true
else
blalert.chochswing := true
txt := sdn.l.first() > sdn.l.get(1) ? "CHoCH+" : "CHoCH"
icss := s_ms_up_BOS.darkcss(0.25, true)
if (sdn.l.first() > sdn.l.get(1) ? boolean.get(s_CHoCHP) : boolean.get(s_CHoCH)) and mtf == false and na(drw)
isdrwS := true
drw := msDraw.new(
sup.n.first()
, sup.p.first()
, s_ms_up_BOS.darkcss(0.25, true)
, txt
, true
)
if mtf == false
switch
ob_filter == "None" => s_bull_ob := true
ob_filter == "BOS" and txt == "BOS" => s_bull_ob := true
ob_filter == "CHoCH" and txt == "CHoCH" => s_bull_ob := true
ob_filter == "CHoCH+" and txt == "CHoCH+" => s_bull_ob := true
trend := 1
sup.n.clear()
sup.p.clear()
// SWING BEARISH STRUCTURE
if sdn.p.size() > 0 and sup.l.size() > 1
if ta.crossunder(b.c, sdn.p.first())
bool CHoCH = na
string txt = na
if trend > 0
CHoCH := true
switch
not CHoCH =>
bralert.swingbos := true
txt := "BOS"
icss := s_ms_dn_BOS
if boolean.get(s_BOS) and mtf == false and na(drw)
isdrwS := true
drw := msDraw.new(
sdn.n.first()
, sdn.p.first()
, s_ms_dn_BOS
, txt
, false
)
CHoCH =>
if sup.l.first() < sup.l.get(1)
bralert.chochplusswing := true
else
bralert.chochswing := true
txt := sup.l.first() < sup.l.get(1) ? "CHoCH+" : "CHoCH"
icss := s_ms_dn_BOS.darkcss(0.25, false)
if (sup.l.first() < sup.l.get(1) ? boolean.get(s_CHoCHP) : boolean.get(s_CHoCH)) and mtf == false and na(drw)
isdrwS := true
drw := msDraw.new(
sdn.n.first()
, sdn.p.first()
, s_ms_dn_BOS.darkcss(0.25, false)
, txt
, false
)
if mtf == false
switch
ob_filter == "None" => s_bear_ob := true
ob_filter == "BOS" and txt == "BOS" => s_bear_ob := true
ob_filter == "CHoCH" and txt == "CHoCH" => s_bear_ob := true
ob_filter == "CHoCH+" and txt == "CHoCH+" => s_bear_ob := true
trend := -1
sdn.n.clear()
sdn.p.clear()
= structure(false)
if isdrw
f_line(drw, size.small, line.style_dashed)
if isdrwS
f_line(drw, size.small, line.style_solid)
= request.security("", "15" , structure(true))
= request.security("", "60" , structure(true))
= request.security("", "240" , structure(true))
= request.security("", "1440" , structure(true))
if show_mtf_str
var tab = table.new(position = position.top_right, columns = 10, rows = 10, bgcolor = na, frame_color = color.rgb(54, 58, 69, 0), frame_width = 1, border_color = color.rgb(54, 58, 69, 100), border_width = 1)
table.cell(tab, 0, 1, text = "15" , text_color = color.silver, text_halign = text.align_center, text_size = size.normal, bgcolor = chart.bg_color, text_font_family = font.family_monospace, width = 2)
table.cell(tab, 0, 2, text = "1H" , text_color = color.silver, text_halign = text.align_center, text_size = size.normal, bgcolor = chart.bg_color, text_font_family = font.family_monospace, width = 2)
table.cell(tab, 0, 3, text = "4H" , text_color = color.silver, text_halign = text.align_center, text_size = size.normal, bgcolor = chart.bg_color, text_font_family = font.family_monospace, width = 2)
table.cell(tab, 0, 4, text = "1D" , text_color = color.silver, text_halign = text.align_center, text_size = size.normal, bgcolor = chart.bg_color, text_font_family = font.family_monospace, width = 2)
table.cell(tab, 1, 1, text = itrend15 == 1 ? "BULLISH" : itrend15 == -1 ? "BEARISH" : na , text_halign = text.align_center, text_size = size.normal, text_color = itrend15 == 1 ? i_ms_up_BOS.darkcss(-0.25, true) : itrend15 == -1 ? i_ms_dn_BOS.darkcss(0.25, false) : color.gray, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 1, 2, text = itrend1H == 1 ? "BULLISH" : itrend1H == -1 ? "BEARISH" : na , text_halign = text.align_center, text_size = size.normal, text_color = itrend1H == 1 ? i_ms_up_BOS.darkcss(-0.25, true) : itrend1H == -1 ? i_ms_dn_BOS.darkcss(0.25, false) : color.gray, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 1, 3, text = itrend4H == 1 ? "BULLISH" : itrend4H == -1 ? "BEARISH" : na , text_halign = text.align_center, text_size = size.normal, text_color = itrend4H == 1 ? i_ms_up_BOS.darkcss(-0.25, true) : itrend4H == -1 ? i_ms_dn_BOS.darkcss(0.25, false) : color.gray, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 1, 4, text = itrend1D == 1 ? "BULLISH" : itrend1D == -1 ? "BEARISH" : na , text_halign = text.align_center, text_size = size.normal, text_color = itrend1D == 1 ? i_ms_up_BOS.darkcss(-0.25, true) : itrend1D == -1 ? i_ms_dn_BOS.darkcss(0.25, false) : color.gray, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 0, 5, text = "Detected Pattern", text_halign = text.align_center, text_size = size.normal, text_color = color.silver, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 0, 6, text = p.found, text_halign = text.align_center, text_size = size.normal, text_color = na(p.bull) ? color.white : p.bull ? i_ms_up_BOS.darkcss(-0.25, true) : p.bull == false ? i_ms_dn_BOS.darkcss(0.25, false) : na, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.merge_cells(tab, 0, 5, 1, 5)
table.merge_cells(tab, 0, 6, 1, 6)
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - Strong/Weak High/Low And Equilibrium }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
var phl = Zphl.new(
na
, na
, label.new(na , na , color = invcol , textcolor = i_ms_dn_BOS , style = label.style_label_down , size = size.tiny , text = "")
, label.new(na , na , color = invcol , textcolor = i_ms_up_BOS , style = label.style_label_up , size = size.tiny , text = "")
, true
, true
, true
, true
, ""
, ""
, 0
, 0
, 0
, 0
, high
, low
, 0
, 0
, 0
, 0
, 0
, 0
, na
, na
)
zhl(len)=>
upper = ta.highest(len)
lower = ta.lowest(len)
var float out = 0
out := b.h > upper ? 0 : b.l < lower ? 1 : out
top = out == 0 and out != 0 ? b.h : 0
btm = out == 1 and out != 1 ? b.l : 0
= zhl(sLen)
= zhl(iLen)
upphl(trend) =>
var label lbl = label.new(
na
, na
, color = invcol
, textcolor = toplvl
, style = label.style_label_down
, size = size.small
)
if top
phl.stopcross := true
phl.txtup := top > phl.topy ? "HH" : "HL"
if show_lbl
topl = label.new(
b.n - swing_r_lookback
, top
, phl.txtup
, color = invcol
, textcolor = toplvl
, style = label.style_label_down
, size = size.small
)
line.delete(phl.top )
phl.top := line.new(
b.n - sLen
, top
, b.n
, top
, color = toplvl)
phl.topy := top
phl.topx := b.n - sLen
phl.tup := top
phl.tupx := b.n - sLen
if itop
phl.itopcross := true
phl.itopy := itop
phl.itopx := b.n - iLen
phl.tup := math.max(high, phl.tup)
phl.tupx := phl.tup == high ? b.n : phl.tupx
phl.uV := phl.tup != phl.tup ? b.v : phl.uV
if barstate.islast
line.set_xy1(
phl.top
, phl.tupx
, phl.tup
)
line.set_xy2(
phl.top
, b.n + 50
, phl.tup
)
label.set_x(
lbl
, b.n + 50
)
label.set_y(
lbl
, phl.tup
)
dist = math.abs(phl.uV / (phl.uV + phl.dV)) * 100
label.set_text (lbl, trend < 0
? "Strong High | " + str.tostring(phl.uV, format.volume) + " (" + str.tostring(math.round(dist,0)) + "%)"
: "Weak High | " + str.tostring(phl.uV, format.volume) + " (" + str.tostring(math.round(dist,0)) + "%)")
dnphl(trend) =>
var label lbl = label.new(
na
, na
, color = invcol
, textcolor = btmlvl
, style = label.style_label_up
, size = size.small
)
if btm
phl.sbottomcross := true
phl.txtdn := btm > phl.bottomy ? "LH" : "LL"
if show_lbl
btml = label.new(
b.n - swing_r_lookback
, btm, phl.txtdn
, color = invcol
, textcolor = btmlvl
, style = label.style_label_up
, size = size.small
)
line.delete(phl.bottom )
phl.bottom := line.new(
b.n - sLen
, btm
, b.n
, btm
, color = btmlvl
)
phl.bottomy := btm
phl.bottomx := b.n - sLen
phl.tdn := btm
phl.tdnx := b.n - sLen
if ibtm
phl.ibottomcross := true
phl.ibottomy := ibtm
phl.ibottomx := b.n - iLen
phl.tdn := math.min(low, phl.tdn)
phl.tdnx := phl.tdn == low ? b.n : phl.tdnx
phl.dV := phl.tdn != phl.tdn ? b.v : phl.dV
if barstate.islast
line.set_xy1(
phl.bottom
, phl.tdnx
, phl.tdn
)
line.set_xy2(
phl.bottom
, b.n + 50
, phl.tdn
)
label.set_x(
lbl
, b.n + 50
)
label.set_y(
lbl
, phl.tdn
)
dist = math.abs(phl.dV / (phl.uV + phl.dV)) * 100
label.set_text (lbl, trend > 0
? "Strong Low | " + str.tostring(phl.dV, format.volume) + " (" + str.tostring(math.round(dist,0)) + "%)"
: "Weak Low | " + str.tostring(phl.uV, format.volume) + " (" + str.tostring(math.round(dist,0)) + "%)")
midphl() =>
avg = math.avg(phl.bottom.get_y2(), phl.top.get_y2())
var line l = line.new(
y1 = avg
, y2 = avg
, x1 = b.n - sLen
, x2 = b.n + 50
, color = midlvl
, style = line.style_solid
)
var label lbl = label.new(
x = b.n + 50
, y = avg
, text = "Equilibrium"
, style = label.style_label_left
, color = invcol
, textcolor = midlvl
, size = size.small
)
if barstate.islast
more = (phl.bottom.get_x1() + phl.bottom.get_x2()) > (phl.top.get_x1() + phl.top.get_x2()) ? phl.top.get_x1() : phl.bottom.get_x1()
line.set_xy1(l , more , avg)
line.set_xy2(l , b.n + 50, avg)
label.set_x (lbl , b.n + 50 )
label.set_y (lbl , avg )
dist = math.abs((l.get_y2() - close) / close) * 100
label.set_text (lbl, "Equilibrium (" + str.tostring(math.round(dist,0)) + "%)")
hqlzone() =>
if barstate.islast
var hqlzone dZone = hqlzone.new(
box.new(
na
, na
, na
, na
, bgcolor = color.new(toplvl, 70)
, border_color = na
)
, box.new(
na
, na
, na
, na
, bgcolor = color.new(midlvl, 70)
, border_color = na
)
, box.new(
na
, na
, na
, na
, bgcolor = color.new(btmlvl, 70)
, border_color = na
)
, label.new(na, na, text = "Premium" , color = invcol, textcolor = toplvl, style = label.style_label_down, size = size.small)
, label.new(na, na, text = "Equilibrium", color = invcol, textcolor = midlvl, style = label.style_label_left, size = size.small)
, label.new(na, na, text = "Discount" , color = invcol, textcolor = btmlvl, style = label.style_label_up , size = size.small)
)
dZone.pbx.set_lefttop(int(math.max(phl.topx, phl.bottomx)) , phl.tup)
dZone.pbx.set_rightbottom(b.n + 50 , 0.95 * phl.tup + 0.05 * phl.tdn)
dZone.ebx.set_lefttop(int(math.max(phl.topx, phl.bottomx)), 0.525 * phl.tup + 0.475 * phl.tdn)
dZone.ebx.set_rightbottom(b.n + 50 , 0.525 * phl.tdn + 0.475 * phl.tup)
dZone.lbx.set_lefttop(int(math.max(phl.topx, phl.bottomx)), 0.95 * phl.tdn + 0.05 * phl.tup)
dZone.lbx.set_rightbottom(b.n + 50 , phl.tdn)
dZone.plb.set_xy( int(math.avg(math.max(phl.topx, phl.bottomx), int(b.n + 50))) , phl.tup)
dZone.elb.set_xy( int(b.n + 50) , math.avg(phl.tup, phl.tdn))
dZone.lbl.set_xy( int(math.avg(math.max(phl.topx, phl.bottomx), int(b.n + 50))) , phl.tdn)
if show_mtb
upphl (trend)
dnphl (trend)
hqlzone()
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - Volumetric Order Block }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
method eB(box b, bool ext, color css, bool swing) =>
b.unshift(
box.new(
na
, na
, na
, na
, xloc = xloc.bar_time
, text_font_family = font.family_monospace
, extend = ext ? extend.right : extend.none
, border_color = swing ? color.new(css, 0) : color.new(color.white,100)
, bgcolor = css
, border_width = 1
)
)
method eL(line l, bool ext, bool solid, color css) =>
l.unshift(
line.new(
na
, na
, na
, na
, width = 1
, color = css
, xloc = xloc.bar_time
, extend = ext ? extend.right : extend.none
, style = solid ? line.style_solid : line.style_dashed
)
)
method drawVOB(bool cdn, bool bull, color css, int loc, bool swing) =>
= request.security(
syminfo.tickerid
, ""
,
, lookahead = barmerge.lookahead_off
)
var obC obj = obC.new(
array.new()
, array.new()
, array.new< int >()
, array.new()
, array.new()
, array.new()
, array.new< int >()
, array.new< int >()
, array.new< int >()
, array.new< int >()
, array.new()
, array.new()
, array.new< int >()
)
var obD draw = obD.new(
array.new()
, array.new()
, array.new()
, array.new()
, array.new()
)
if barstate.isfirst
for i = 0 to ob_num - 1
draw.mL .eL(false, false, use_grayscale ? color.new(color.gray, 0) : color.new(css,0))
draw.ob .eB(false, use_grayscale ? color.new(color.gray, 90) : css, swing)
draw.blB.eB(false, css_metric_up , swing)
draw.brB.eB(false, css_metric_dn , swing)
draw.eOB.eB(true , use_grayscale ? color.new(color.gray, 90) : css, swing)
float pos = ob_pos == "Full"
? (bull ? high : low)
: ob_pos == "Middle"
? ohlc4
: ob_pos == "Accurate"
? hl2
: hl2
if cdn
obj.h.clear()
obj.l.clear()
obj.n.clear()
for i = 0 to math.abs((loc - b.n)) - 1
obj.h.push(hH )
obj.l.push(lL )
obj.n.push(b.t )
// obj.h.reverse()
// obj.l.reverse()
int iU = obj.l.indexof(obj.l.min()) + 1
int iD = obj.h.indexof(obj.h.max()) + 1
obj.dir.unshift(
bull
? (b.c > b.o ? 1 : -1)
: (b.c > b.o ? 1 : -1)
)
obj.top.unshift(
bull
? pos
: obj.h.max()
)
obj.btm.unshift(
bull
? obj.l.min()
: pos
)
obj.left.unshift(
bull
? obj.n.get(obj.l.indexof(obj.l.min()))
: obj.n.get(obj.h.indexof(obj.h.max()))
)
obj.avg.unshift(
math.avg(obj.top.first(), obj.btm.first())
)
obj.cV.unshift(
bull
? b.v
: b.v
)
if ob_pos == "Precise"
switch bull
true =>
if obj.avg.get(0) < (b.c < b.o ? b.c : b.o ) and obj.top.get(0) > hlcc4
obj.top.set(0, obj.avg.get(0))
obj.avg.set(0, math.avg(obj.top.first(), obj.btm.first()))
false =>
if obj.avg.get(0) > (b.c < b.o ? b.o : b.c ) and obj.btm.get(0) < hlcc4
obj.btm.set(0, obj.avg.get(0))
obj.avg.set(0, math.avg(obj.top.first(), obj.btm.first()))
obj.blVP.unshift ( 0 )
obj.brVP.unshift ( 0 )
obj.wM .unshift ( 1 )
if use_overlap
int rmP = use_overlap_method == "Recent" ? 1 : 0
if obj.avg.size() > 1
if bull
? obj.btm.first() < obj.top.get(1)
: obj.top.first() > obj.btm.get(1)
obj.wM .remove(rmP)
obj.cV .remove(rmP)
obj.dir .remove(rmP)
obj.top .remove(rmP)
obj.avg .remove(rmP)
obj.btm .remove(rmP)
obj.left .remove(rmP)
obj.blVP .remove(rmP)
obj.brVP .remove(rmP)
if barstate.isconfirmed
for x = 0 to ob_num - 1
tg = switch ob_mitigation
"Middle" => obj.avg
"Absolute" => bull ? obj.btm : obj.top
for in tg
if (bull ? cC < pt : cC > pt)
obj.wM .remove(idx)
obj.cV .remove(idx)
obj.dir .remove(idx)
obj.top .remove(idx)
obj.avg .remove(idx)
obj.btm .remove(idx)
obj.left .remove(idx)
obj.blVP .remove(idx)
obj.brVP .remove(idx)
if barstate.islast
if obj.avg.size() > 0
// Alert
if bull
? ta.crossunder(low , obj.top.get(0))
: ta.crossover (high, obj.btm.get(0))
switch bull
true => blalert.obtouch := true
false => bralert.obtouch := true
float tV = 0
obj.dV.clear()
seq = math.min(ob_num - 1, obj.avg.size() - 1)
for j = 0 to seq
tV += obj.cV.get(j)
if j == seq
for y = 0 to seq
obj.dV.unshift(
math.floor(
(obj.cV.get(y) / tV) * 100)
)
obj.dV.reverse()
for i = 0 to math.min(ob_num - 1, obj.avg.size() - 1)
dmL = draw.mL .get(i)
dOB = draw.ob .get(i)
dblB = draw.blB.get(i)
dbrB = draw.brB.get(i)
deOB = draw.eOB.get(i)
dOB.set_lefttop (obj.left .get(i) , obj.top.get(i))
deOB.set_lefttop (b.t , obj.top.get(i))
dOB.set_rightbottom (b.t , obj.btm.get(i))
deOB.set_rightbottom(b.t + (b.t - b.t ) * 100 , obj.btm.get(i))
if use_middle_line
dmL.set_xy1(obj.left.get(i), obj.avg.get(i))
dmL.set_xy2(b.t , obj.avg.get(i))
if ob_metrics_show
dblB.set_lefttop (obj.left.get(i), obj.top.get(i))
dbrB.set_lefttop (obj.left.get(i), obj.avg.get(i))
dblB.set_rightbottom(obj.left.get(i), obj.avg.get(i))
dbrB.set_rightbottom(obj.left.get(i), obj.btm.get(i))
rpBL = dblB.get_right()
rpBR = dbrB.get_right()
dbrB.set_right(rpBR + (b.t - b.t ) * obj.brVP.get(i))
dblB.set_right(rpBL + (b.t - b.t ) * obj.blVP.get(i))
if use_show_metric
txt = switch
obj.cV.get(i) >= 1000000000 => str.tostring(math.round(obj.cV.get(i) / 1000000000,3)) + "B"
obj.cV.get(i) >= 1000000 => str.tostring(math.round(obj.cV.get(i) / 1000000,3)) + "M"
obj.cV.get(i) >= 1000 => str.tostring(math.round(obj.cV.get(i) / 1000,3)) + "K"
obj.cV.get(i) < 1000 => str.tostring(math.round(obj.cV.get(i)))
deOB.set_text(
str.tostring(
txt + " (" + str.tostring(obj.dV.get(i)) + "%)")
)
deOB.set_text_size (size.auto)
deOB.set_text_halign(text.align_left)
deOB.set_text_color (use_grayscale ? color.silver : color.new(css, 0))
if ob_metrics_show and barstate.isconfirmed
if obj.wM.size() > 0
for i = 0 to obj.avg.size() - 1
switch obj.dir.get(i)
1 =>
switch obj.wM.get(i)
1 => obj.blVP.set(i, obj.blVP.get(i) + 1), obj.wM.set(i, 2)
2 => obj.blVP.set(i, obj.blVP.get(i) + 1), obj.wM.set(i, 3)
3 => obj.brVP.set(i, obj.brVP.get(i) + 1), obj.wM.set(i, 1)
-1 =>
switch obj.wM.get(i)
1 => obj.brVP.set(i, obj.brVP.get(i) + 1), obj.wM.set(i, 2)
2 => obj.brVP.set(i, obj.brVP.get(i) + 1), obj.wM.set(i, 3)
3 => obj.blVP.set(i, obj.blVP.get(i) + 1), obj.wM.set(i, 1)
var hN = array.new(1, b.n)
var lN = array.new(1, b.n)
var hS = array.new(1, b.n)
var lS = array.new(1, b.n)
if iH
hN.pop()
hN.unshift(int(b.n ))
if iL
lN.pop()
lN.unshift(int(b.n ))
if sH
hS.pop()
hS.unshift(int(b.n ))
if sL
lS.pop()
lS.unshift(int(b.n ))
if ob_show
bull_ob.drawVOB(true , ob_bull_css, hN.first(), false)
bear_ob.drawVOB(false, ob_bear_css, lN.first(), false)
if ob_swings
s_bull_ob.drawVOB(true , css_swing_up, hS.first(), true)
s_bear_ob.drawVOB(false, css_swing_dn, lS.first(), true)
if bull_ob
blalert.ob := true
if bear_ob
bralert.ob := true
if s_bull_ob
blalert.swingob := true
if s_bear_ob
blalert.swingob := true
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - FVG | VI | OG }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
ghl() => request.security(syminfo.tickerid, fvg_tf, [high , low , close , open ])
tfG() => request.security(syminfo.tickerid, fvg_tf, )
cG(bool bull) =>
= ghl()
= tfG()
var FVG draw = FVG.new(
array.new()
, array.new()
)
var FVG cords = array.new()
float pup = na
float pdn = na
bool cdn = na
int pos = 2
cc = timeframe.change(fvg_tf)
if barstate.isfirst
for i = 0 to fvg_num - 1
draw.box.unshift(box.new (na, na, na, na, border_color = color.new(color.white, 100), xloc = xloc.bar_time))
draw.ln.unshift (line.new(na, na, na, na, xloc = xloc.bar_time, width = 1, style = line.style_solid))
switch what_fvg
"FVG" =>
pup := bull ? gl : l
pdn := bull ? h : gh
cdn := bull ? gl > h and cc : gh < l and cc
pos := 2
"VI" =>
pup := bull
? (gc > go
? go
: gc)
: (gc > go
? go
: gc )
pdn := bull
? (gc > go
? gc
: go )
: (gc > go
? gc
: go)
cdn := bull
? go > gc and gh >
Parameter Free RSI [InvestorUnknown]The Parameter Free RSI (PF-RSI) is an innovative adaptation of the traditional Relative Strength Index (RSI), a widely used momentum oscillator that measures the speed and change of price movements. Unlike the standard RSI, which relies on a fixed lookback period (typically 14), the PF-RSI dynamically adjusts its calculation length based on real-time market conditions. By incorporating volatility and the RSI's deviation from its midpoint (50), this indicator aims to provide a more responsive and adaptable tool for identifying overbought/oversold conditions, trend shifts, and momentum changes. This adaptability makes it particularly valuable for traders navigating diverse market environments, from trending to ranging conditions.
PF-RSI offers a suite of customizable features, including dynamic length variants, smoothing options, visualization tools, and alert conditions.
Key Features
1. Dynamic RSI Length Calculation
The cornerstone of the PF-RSI is its ability to adjust the RSI calculation period dynamically, eliminating the need for a static parameter. The length is computed using two primary factors:
Volatility: Measured via the standard deviation of past RSI values.
Distance from Midpoint: The absolute deviation of the RSI from 50, reflecting the strength of bullish or bearish momentum.
The indicator offers three variants for calculating this dynamic length, allowing users to tailor its responsiveness:
Variant I (Aggressive): Increases the length dramatically based on volatility and a nonlinear scaling of the distance from 50. Ideal for traders seeking highly sensitive signals in fast-moving markets.
Variant II (Moderate): Combines volatility with a scaled distance from 50, using a less aggressive adjustment. Strikes a balance between responsiveness and stability, suitable for most trading scenarios.
Variant III (Conservative): Applies a linear combination of volatility and raw distance from 50. Offers a stable, less reactive length adjustment for traders prioritizing consistency.
// Function that returns a dynamic RSI length based on past RSI values
// The idea is to make the RSI length adaptive using volatility (stdev) and distance from the RSI midpoint (50)
// Different "variant" options control how aggressively the length changes
parameter_free_length(free_rsi, variant) =>
len = switch variant
// Variant I: Most aggressive adaptation
// Uses standard deviation scaled by a nonlinear factor of distance from 50
// Also adds another distance-based term to increase length more dramatically
"I" => math.ceil(
ta.stdev(free_rsi, math.ceil(free_rsi)) *
math.pow(1 + (math.ceil(math.abs(50 - (free_rsi - 50))) / 100), 2)
) +
(
math.ceil(math.abs(free_rsi - 50)) *
(1 + (math.ceil(math.abs(50 - (free_rsi - 50))) / 100))
)
// Variant II: Moderate adaptation
// Adds the standard deviation and a distance-based scaling term (less nonlinear)
"II" => math.ceil(
ta.stdev(free_rsi, math.ceil(free_rsi)) +
(
math.ceil(math.abs(free_rsi - 50)) *
(1 + (math.ceil(math.abs(50 - (free_rsi - 50))) / 100))
)
)
// Variant III: Least aggressive adaptation
// Simply adds standard deviation and raw distance from 50 (linear scaling)
"III" => math.ceil(
ta.stdev(free_rsi, math.ceil(free_rsi)) +
math.ceil(math.abs(free_rsi - 50))
)
2. Smoothing Options
To refine the dynamic RSI and reduce noise, the PF-RSI provides smoothing capabilities:
Smoothing Toggle: Enable or disable smoothing of the dynamic length used for RSI.
Smoothing MA Type for RSI MA: Choose between SMA and EMA
Smoothing Length Options for RSI MA:
Full: Uses the entire calculated dynamic length.
Half: Applies half of the dynamic length for smoother output.
SQRT: Uses the square root of the dynamic length, offering a compromise between responsiveness and smoothness.
The smoothed RSI is complemented by a separate moving average (MA) of the RSI itself, further enhancing signal clarity.
3. Visualization Tools
The PF-RSI includes visualization options to help traders interpret market conditions at a glance.
Plots:
Dynamic RSI: Displayed as a white line, showing the adaptive RSI value.
RSI Moving Average: Plotted in yellow, providing a smoothed reference for trend and momentum analysis.
Dynamic Length: A secondary plot (in faint white) showing how the calculation period evolves over time.
Histogram: Represents the RSI’s position relative to 50, with color gradients.
Fill Area: The space between the RSI and its MA is filled with a gradient (green for RSI > MA, red for RSI < MA), highlighting momentum shifts.
Customizable bar colors on the price chart reflect trend and momentum:
Trend (Raw RSI): Green (RSI > 50), Red (RSI < 50).
Trend (RSI MA): Green (MA > 50), Red (MA < 50).
Trend (Raw RSI) + Momentum: Adds momentum shading (lighter green/red when RSI and MA diverge).
Trend (RSI MA) + Momentum: Similar, but based on the MA’s trend.
Momentum: Green (RSI > MA), Red (RSI < MA).
Off: Disables bar coloring.
Intrabar Updating: Optional real-time updates within each bar for enhanced responsiveness.
4. Alerts
The PF-RSI supports customizable alerts to keep traders informed of key events.
Trend Alerts:
Raw RSI: Triggers when the RSI crosses above (uptrend) or below (downtrend) 50.
RSI MA: Triggers when the moving average crosses 50.
Off: Disables trend alerts.
Momentum Alerts:
Triggers when the RSI crosses its moving average, indicating rising (RSI > MA) or declining (RSI < MA) momentum.
Alerts are fired once per bar close, with descriptive messages including the ticker symbol (e.g., " Uptrend on: AAPL").
How It Works
The PF-RSI operates in a multi-step process:
Initialization
On the first run, it calculates a standard RSI with a 14-period length to seed the dynamic calculation.
Dynamic Length Computation
Once seeded, the indicator switches to a dynamic length based on the selected variant, factoring in volatility and distance from 50.
If smoothing is enabled, the length is further refined using an SMA.
RSI Calculation
The adaptive RSI is computed using the dynamic length, ensuring it reflects current market conditions.
Moving Average
A separate MA (SMA or EMA) is applied to the RSI, with a length derived from the dynamic length (Full, Half, or SQRT).
Visualization and Alerts
The results are plotted, and alerts are triggered based on user settings.
This adaptive approach minimizes lag in fast markets and reduces false signals in choppy conditions, offering a significant edge over fixed-period RSI implementations.
Why Use PF-RSI?
The Parameter Free RSI stands out by eliminating the guesswork of selecting an RSI period. Its dynamic length adjusts to market volatility and momentum, providing timely signals without manual tweaking.
Breadth Indicators NYSE Percent Above Moving AverageBreadth Indicators NYSE - transmits the processed data from the Barchart provider
NYSE - Breadth Indicators
S&P 500 - Breadth Indicators
DOW - Breadth Indicators
RUSSEL 1000 - Breadth Indicators
RUSSEL 2000 - Breadth Indicators
RUSSEL 3000 - Breadth Indicators
Moving Average - 5, 20, 50, 100, 150, 200
The "Percentage above 50-day SMA" indicator measures the percentage of stocks in the index trading above their 50-day moving average. It is a useful tool for assessing the general state of the market and identifying overbought and oversold conditions.
One way to use the "Percentage above 50-day SMA" indicator in a trading strategy is to combine it with a long-term moving average to determine whether the trend is bullish or bearish. Another way to use it is to combine it with a short-term moving average to identify pullbacks and rebounds within the overall trend.
The purpose of using the "Percentage above 50-day SMA" indicator is to participate in a larger trend with a better risk-reward ratio. By using this indicator to identify pullbacks and bounces, you can reduce the risk of entering trades at the wrong time.
Bull Signal Recap:
150-day EMA of $SPXA50R crosses above 52.5 and remains above 47.50 to set the bullish tone.
5-day EMA of $SPXA50R moves below 40 to signal a pullback
5-day EMA of $SPXA50R moves above 50 to signal an upturn
Bear Signal Recap:
150-day EMA of $SPXA50R crosses below 47.50 and remains below 52.50 to set the bearish tone.
5-day EMA of $SPXA50R moves above 60 to signal a bounce
5-day EMA of $SPXA50R moves below 50 to signal a downturn
Tweaking
There are numerous ways to tweak a trading system, but chartists should avoid over-optimizing the indicator settings. In other words, don't attempt to find the perfect moving average period or crossover level. Perfection is unattainable when developing a system or trading the markets. It is important to keep the system logical and focus tweaks on other aspects, such as the actual price chart of the underlying security.
What do levels above and below 50% signify in the long-term moving average?
A move above 52.5% is deemed bullish, and below 47.5% is deemed bearish. These levels help to reduce whipsaws by using buffers for bullish and bearish thresholds.
How does the short-term moving average work to identify pullbacks or bounces?
When using a 5-day EMA, a move below 40 signals a pullback, and a move above 60 signals a bounce.
How is the reversal of pullback or bounce identified?
A move back above 50 after a pullback or below 50 after a bounce signals that the respective trend may be resuming.
How can you ensure that the uptrend has resumed?
It’s important to wait for the surge above 50 to ensure the uptrend has resumed, signaling improved breadth.
Can the system be tweaked to optimize indicator settings?
While there are various ways to tweak the system, seeking perfection through over-optimizing settings is advised against. It's crucial to keep the system logical and focus tweaks on the price chart of the underlying security.
RUSSIAN \ Русская версия.
Индикатор "Процент выше 50-дневной скользящей средней" измеряет процент акций, торгующихся в индексе выше их 50-дневной скользящей средней. Это полезный инструмент для оценки общего состояния рынка и выявления условий перекупленности и перепроданности.
Один из способов использования индикатора "Процент выше 50-дневной скользящей средней" в торговой стратегии - это объединить его с долгосрочной скользящей средней, чтобы определить, является ли тренд бычьим или медвежьим. Другой способ использовать его - объединить с краткосрочной скользящей средней, чтобы выявить откаты и отскоки в рамках общего тренда.
Цель использования индикатора "Процент выше 50-дневной скользящей средней" - участвовать в более широком тренде с лучшим соотношением риска и прибыли. Используя этот индикатор для выявления откатов и отскоков, вы можете снизить риск входа в сделки в неподходящее время.
Краткое описание бычьего сигнала:
150-дневная ЕМА на уровне $SPXA50R пересекает отметку 52,5 и остается выше 47,50, что задает бычий настрой.
5-дневная ЕМА на уровне $SPXA50R опускается ниже 40, сигнализируя об откате
5-дневная ЕМА на уровне $SPXA50R поднимается выше 50, сигнализируя о росте
Обзор медвежьих сигналов:
150-дневная ЕМА на уровне $SPXA50R пересекает уровень ниже 47,50 и остается ниже 52,50, что указывает на медвежий настрой.
5-дневная ЕМА на уровне $SPXA50R поднимается выше 60, сигнализируя о отскоке
5-дневная ЕМА на уровне $SPXA50 опускается ниже 50, что сигнализирует о спаде
Корректировка
Существует множество способов настроить торговую систему, но графологам следует избегать чрезмерной оптимизации настроек индикатора. Другими словами, не пытайтесь найти идеальный период скользящей средней или уровень пересечения. Совершенство недостижимо при разработке системы или торговле на рынках. Важно поддерживать логику системы и уделять особое внимание другим аспектам, таким как график фактической цены базовой ценной бумаги.
Что означают уровни выше и ниже 50% в долгосрочной скользящей средней?
Движение выше 52,5% считается бычьим, а ниже 47,5% - медвежьим. Эти уровни помогают снизить риски, используя буферы для бычьих и медвежьих порогов.
Как краткосрочная скользящая средняя помогает идентифицировать откаты или отскоки?
При использовании 5-дневной ЕМА движение ниже 40 указывает на откат, а движение выше 60 указывает на отскок.
Как определяется разворот отката или отскока?
Движение выше 50 после отката или ниже 50 после отскока сигнализирует о возможном возобновлении соответствующего тренда.
Как вы можете гарантировать, что восходящий тренд возобновился?
Важно дождаться скачка выше 50, чтобы убедиться в возобновлении восходящего тренда, сигнализирующего о расширении диапазона.
Можно ли настроить систему для оптимизации настроек индикатора?
Хотя существуют различные способы настройки системы, не рекомендуется стремиться к совершенству с помощью чрезмерной оптимизации настроек. Крайне важно сохранить логичность системы и сфокусировать изменения на ценовом графике базовой ценной бумаги.
Pinescript - Common Label & Line Array Functions Library by RRBPinescript - Common Label & Line Array Functions Library by RagingRocketBull 2021
Version 1.0
This script provides a library of common array functions for arrays of label and line objects with live testing of all functions.
Using this library you can easily create, update, delete, join label/line object arrays, and get/set properties of individual label/line object array items.
You can find the full list of supported label/line array functions below.
There are several libraries:
- Common String Functions Library
- Standard Array Functions Library
- Common Fixed Type Array Functions Library
- Common Label & Line Array Functions Library
- Common Variable Type Array Functions Library
Features:
- 30 array functions in categories create/update/delete/join/get/set with support for both label/line objects (45+ including all implementations)
- Create, Update label/line object arrays from list/array params
- GET/SET properties of individual label/line array items by index
- Join label/line objects/arrays into a single string for output
- Supports User Input of x,y coords of 5 different types: abs/rel/rel%/inc/inc% list/array, auto transforms x,y input into list/array based on type, base and xloc, translates rel into abs bar indexes
- Supports User Input of lists with shortened names of string properties, auto expands all standard string properties to their full names for use in functions
- Live Output for all/selected functions based on User Input. Test any function for possible errors you may encounter before using in script.
- Output filters: hide all excluded and show only allowed functions using a list of function names
- Output Panel customization options: set custom style, color, text size, and line spacing
Usage:
- select create function - create label/line arrays from lists or arrays (optional). Doesn't affect the update functions. The only change in output should be function name regardless of the selected implementation.
- specify num_objects for both label/line arrays (default is 7)
- specify common anchor point settings x,y base/type for both label/line arrays and GET/SET items in Common Settings
- fill lists with items to use as inputs for create label/line array functions in Create Label/Line Arrays section
- specify label/line array item index and properties to SET in corresponding sections
- select label/line SET function to see the changes applied live
Code Structure:
- translate x,y depending on x,y type, base and xloc as specified in UI (required for all functions)
- expand all shortened standard property names to full names (required for create/update* from arrays and set* functions, not needed for create/update* from lists) to prevent errors in label.new and line.new
- create param arrays from string lists (required for create/update* from arrays and set* functions, not needed for create/update* from lists)
- create label/line array from string lists (property names are auto expanded) or param arrays (requires already expanded properties)
- update entire label/line array or
- get/set label/line array item properties by index
Transforming/Expanding Input values:
- for this script to work on any chart regardless of price/scale, all x*,y* are specified as % increase relative to x0,y0 base levels by default, but user can enter abs x,price values specific for that chart if necessary.
- all lists can be empty, contain 1 or several items, have the same/different lengths. Array Length = min(min(len(list*)), mum_objects) is used to create label/line objects. Missing list items are replaced with default property values.
- when a list contains only 1 item it is duplicated (label name/tooltip is also auto incremented) to match the calculated Array Length
- since this script processes user input, all x,y values must be translated to abs bar indexes before passing them to functions. Your script may provide all data internally and doesn't require this step.
- at first int x, float y arrays are created from user string lists, transformed as described below and returned as x,y arrays.
- translated x,y arrays can then be passed to create from arrays function or can be converted back to x,y string lists for the create from lists function if necessary.
- all translation logic is separated from create/update/set functions for the following reasons:
- to avoid redundant code/dependency on ext functions/reduce local scopes and to be able to translate everything only once in one place - should be faster
- to simplify internal logic of all functions
- because your script may provide all data internally without user input and won't need the translation step
- there are 5 types available for both x,y: abs, rel, rel%, inc, inc%. In addition to that, x can be: bar index or time, y is always price.
- abs - absolute bar index/time from start bar0 (x) or price (y) from 0, is >= 0
- rel - relative bar index/time from cur bar n (x) or price from y0 base level, is >= 0
- rel% - relative % increase of bar index/time (x) or price (y) from corresponding base level (x0 or y0), can be <=> 0
- inc - relative increment (step) for each new level of bar index/time (x) or price (y) from corresponding base level (x0 or y0), can be <=> 0
- inc% - relative % increment (% step) for each new level of bar index/time (x) or price (y) from corresponding base level (x0 or y0), can be <=> 0
- x base level >= 0
- y base level can be 0 (empty) or open, close, high, low of cur bar
- single item x1_list = "50" translates into:
- for x type abs: "50, 50, 50 ..." num_objects times regardless of xloc => x = 50
- for x type rel: "50, 50, 50 ... " num_objects times => x = x_base + 50
- for x type rel%: "50%, 50%, 50% ... " num_objects times => x_base * (1 + 0.5)
- for x type inc: "0, 50, 100 ... " num_objects times => x_base + 50 * i
- for x type inc%: "0%, 50%, 100% ... " num_objects times => x_base * (1 + 0.5 * i)
- when xloc = xloc.bar_index each rel*/inc* value in the above list is then subtracted from n: n - x to convert rel to abs bar index, values of abs type are not affected
- x1_list = "0, 50, 100, ..." of type rel is the same as "50" of type inc
- x1_list = "50, 50, 50, ..." of type abs/rel/rel% produces a sequence of the same values and can be shortened to just "50"
- single item y1_list = "2" translates into (ragardless of yloc):
- for y type abs: "2, 2, 2 ..." num_objects times => y = 2
- for y type rel: "2, 2, 2 ... " num_objects times => y = y_base + 2
- for y type rel%: "2%, 2%, 2% ... " num_objects times => y = y_base * (1 + 0.02)
- for y type inc: "0, 2, 4 ... " num_objects times => y = y_base + 2 * i
- for y type inc%: "0%, 2%, 4% ... " num_objects times => y = y_base * (1 + 0.02 * i)
- when yloc != yloc.price all calculated values above are simply ignored
- y1_list = "0, 2, 4" of type rel% is the same as "2" with type inc%
- y1_list = "2, 2, 2" of type abs/rel/rel% produces a sequence of the same values and can be shortened to just "2"
- you can enter shortened property names in lists. To lookup supported shortened names use corresponding dropdowns in Set Label/Line Array Item Properties sections
- all shortened standard property names must be expanded to full names (required for create/update* from arrays and set* functions, not needed for create/update* from lists) to prevent errors in label.new and line.new
- examples of shortened property names that can be used in lists: bar_index, large, solid, label_right, white, left, left, price
- expanded to their corresponding full names: xloc.bar_index, size.large, line.style_solid, label.style_label_right, color.white, text.align_left, extend.left, yloc.price
- all expanding logic is separated from create/update* from arrays and set* functions for the same reasons as above, and because param arrays already have different types, implying the use of final values.
- all expanding logic is included in the create/update* from lists functions because it seemed more natural to process string lists from user input directly inside the function, since they are already strings.
Creating Label/Line Objects:
- use study max_lines_count and max_labels_count params to increase the max number of label/line objects to 500 (+3) if necessary. Default number of label/line objects is 50 (+3)
- all functions use standard param sequence from methods in reference, except style always comes before colors.
- standard label/line.get* functions only return a few properties, you can't read style, color, width etc.
- label.new(na, na, "") will still create a label with x = n-301, y = NaN, text = "" because max default scope for a var is 300 bars back.
- there are 2 types of color na, label color requires color(na) instead of color_na to prevent error. text_color and line_color can be color_na
- for line to be visible both x1, x2 ends must be visible on screen, also when y1 == y2 => abs(x1 - x2) >= 2 bars => line is visible
- xloc.bar_index line uses abs x1, x2 indexes and can only be within 0 and n ends, where n <= 5000 bars (free accounts) or 10000 bars (paid accounts) limit, can't be plotted into the future
- xloc.bar_time line uses abs x1, x2 times, can't go past bar0 time but can continue past cur bar time into the future, doesn't have a length limit in bars.
- xloc.bar_time line with length = exact number of bars can be plotted only within bar0 and cur bar, can't be plotted into the future reliably because of future gaps due to sessions on some charts
- xloc.bar_index line can't be created on bar 0 with fixed length value because there's only 1 bar of horiz length
- it can be created on cur bar using fixed length x < n <= 5000 or
- created on bar0 using na and then assigned final x* values on cur bar using set_x*
- created on bar0 using n - fixed_length x and then updated on cur bar using set_x*, where n <= 5000
- default orientation of lines (for style_arrow* and extend) is from left to right (from bar 50 to bar 0), it reverses when x1 and x2 are swapped
- price is a function, not a line object property
Variable Type Arrays:
- you can't create an if/function that returns var type value/array - compiler uses strict types and doesn't allow that
- however you can assign array of any type to another array of any type creating an arr pointer of invalid type that must be reassigned to a matching array type before used in any expression to prevent error
- create_any_array2 uses this loophole to return an int_arr pointer of a var type array
- this works for all array types defined with/without var keyword and doesn't work for string arrays defined with var keyword for some reason
- you can't do this with var type vars, only var type arrays because arrays are pointers passed by reference, while vars are actual values passed by value.
- you can only pass a var type value/array param to a function if all functions inside support every type - otherwise error
- alternatively values of every type must be passed simultaneously and processed separately by corresponding if branches/functions supporting these particular types returning a common single type result
- get_var_types solves this problem by generating a list of dummy values of every possible type including the source type, tricking the compiler into allowing a single valid branch to execute without error, while ignoring all dummy results
Notes:
- uses Pinescript v3 Compatibility Framework
- uses Common String Functions Library, Common Fixed Type Array Functions Library, Common Variable Type Array Functions Library
- has to be a separate script to reduce the number of local scopes/compiled file size, can't be merged with another library.
- lets you live test all label/line array functions for errors. If you see an error - change params in UI
- if you see "Loop too long" error - hide/unhide or reattach the script
- if you see "Chart references too many candles" error - change x type or value between abs/rel*. This can happen on charts with 5000+ bars when a rel bar index x is passed to label.new or line.new instead of abs bar index n - x
- create/update_label/line_array* use string lists, while create/update_label/line_array_from_arrays* use array params to create label/line arrays. "from_lists" is dropped to shorten the names of the most commonly used functions.
- create_label/line_array2,4 are preferable, 5,6 are listed for pure demonstration purposes only - don't use them, they don't improve anything but dramatically increase local scopes/compiled file size
- for this reason you would mainly be using create/update_label/line_array2,4 for list params or create/update_label/line_array_from_arrays2 for array params
- all update functions are executed after each create as proof of work and can be disabled. Only create functions are required. Use update functions when necessary - when list/array params are changed by your script.
- both lists and array item properties use the same x,y_type, x,y_base from common settings
- doesn't use pagination, a single str contains all output
- why is this so complicated? What are all these functions for?
- this script merges standard label/line object methods with standard array functions to create a powerful set of label/line object array functions to simplify manipulation of these arrays.
- this library also extends the functionality of Common Variable Type Array Functions Library providing support for label/line types in var type array functions (any_to_str6, join_any_array5)
- creating arrays from either lists or arrays adds a level of flexibility that comes with complexity. It's very likely that in your script you'd have to deal with both string lists as input, and arrays internally, once everything is converted.
- processing user input, allowing customization and targeting for any chart adds a whole new layer of complexity, all inputs must be translated and expanded before used in functions.
- different function implementations can increase/reduce local scopes and compiled file size. Select a version that best suits your needs. Creating complex scripts often requires rewriting your code multiple times to fit the limits, every line matters.
P.S. Don't rely too much on labels, for too often they are fables.
List of functions*:
* - functions from other libraries are not listed
1. Join Functions
Labels
- join_label_object(label_, d1, d2)
- join_label_array(arr, d1, d2)
- join_label_array2(arr, d1, d2, d3)
Lines
- join_line_object(line_, d1, d2)
- join_line_array(arr, d1, d2)
- join_line_array2(arr, d1, d2, d3)
Any Type
- any_to_str6(arr, index, type)
- join_any_array4(arr, d1, d2, type)
- join_any_array5(arr, d, type)
2. GET/SET Functions
Labels
- label_array_get_text(arr, index)
- label_array_get_xy(arr, index)
- label_array_get_fields(arr, index)
- label_array_set_text(arr, index, str)
- label_array_set_xy(arr, index, x, y)
- label_array_set_fields(arr, index, x, y, str)
- label_array_set_all_fields(arr, index, x, y, str, xloc, yloc, label_style, label_color, text_color, text_size, text_align, tooltip)
- label_array_set_all_fields2(arr, index, x, y, str, xloc, yloc, label_style, label_color, text_color, text_size, text_align, tooltip)
Lines
- line_array_get_price(arr, index, bar)
- line_array_get_xy(arr, index)
- line_array_get_fields(arr, index)
- line_array_set_text(arr, index, width)
- line_array_set_xy(arr, index, x1, y1, x2, y2)
- line_array_set_fields(arr, index, x1, y1, x2, y2, width)
- line_array_set_all_fields(arr, index, x1, y1, x2, y2, xloc, extend, line_style, line_color, width)
- line_array_set_all_fields2(arr, index, x1, y1, x2, y2, xloc, extend, line_style, line_color, width)
3. Create/Update/Delete Functions
Labels
- delete_label_array(label_arr)
- create_label_array(list1, list2, list3, list4, list5, d)
- create_label_array2(x_list, y_list, str_list, xloc_list, yloc_list, style_list, color1_list, color2_list, size_list, align_list, tooltip_list, d)
- create_label_array3(x_list, y_list, str_list, xloc_list, yloc_list, style_list, color1_list, color2_list, size_list, align_list, tooltip_list, d)
- create_label_array4(x_list, y_list, str_list, xloc_list, yloc_list, style_list, color1_list, color2_list, size_list, align_list, tooltip_list, d)
- create_label_array5(x_list, y_list, str_list, xloc_list, yloc_list, style_list, color1_list, color2_list, size_list, align_list, tooltip_list, d)
- create_label_array6(x_list, y_list, str_list, xloc_list, yloc_list, style_list, color1_list, color2_list, size_list, align_list, tooltip_list, d)
- update_label_array2(label_arr, x_list, y_list, str_list, xloc_list, yloc_list, style_list, color1_list, color2_list, size_list, align_list, tooltip_list, d)
- update_label_array4(label_arr, x_list, y_list, str_list, xloc_list, yloc_list, style_list, color1_list, color2_list, size_list, align_list, tooltip_list, d)
- create_label_array_from_arrays2(x_arr, y_arr, str_arr, xloc_arr, yloc_arr, style_arr, color1_arr, color2_arr, size_arr, align_arr, tooltip_arr, d)
- create_label_array_from_arrays4(x_arr, y_arr, str_arr, xloc_arr, yloc_arr, style_arr, color1_arr, color2_arr, size_arr, align_arr, tooltip_arr, d)
- update_label_array_from_arrays2(label_arr, x_arr, y_arr, str_arr, xloc_arr, yloc_arr, style_arr, color1_arr, color2_arr, size_arr, align_arr, tooltip_arr, d)
Lines
- delete_line_array(line_arr)
- create_line_array(list1, list2, list3, list4, list5, list6, d)
- create_line_array2(x1_list, y1_list, x2_list, y2_list, xloc_list, extend_list, style_list, color_list, width_list, d)
- create_line_array3(x1_list, y1_list, x2_list, y2_list, xloc_list, extend_list, style_list, color_list, width_list, d)
- create_line_array4(x1_list, y1_list, x2_list, y2_list, xloc_list, extend_list, style_list, color_list, width_list, d)
- create_line_array5(x1_list, y1_list, x2_list, y2_list, xloc_list, extend_list, style_list, color_list, width_list, d)
- create_line_array6(x1_list, y1_list, x2_list, y2_list, xloc_list, extend_list, style_list, color_list, width_list, d)
- update_line_array2(line_arr, x1_list, y1_list, x2_list, y2_list, xloc_list, extend_list, style_list, color_list, width_list, d)
- update_line_array4(line_arr, x1_list, y1_list, x2_list, y2_list, xloc_list, extend_list, style_list, color_list, width_list, d)
- create_line_array_from_arrays2(x1_arr, y1_arr, x2_arr, y2_arr, xloc_arr, extend_arr, style_arr, color_arr, width_arr, d)
- update_line_array_from_arrays2(line_arr, x1_arr, y1_arr, x2_arr, y2_arr, xloc_arr, extend_arr, style_arr, color_arr, width_arr, d)
Support and resistance levels (Day, Week, Month) + EMAs + SMAs(ENG): This Pine 5 script provides various tools for configuring and displaying different support and resistance levels, as well as moving averages (EMA and SMA) on charts. Using these tools is an essential strategy for determining entry and exit points in trades.
Support and Resistance Levels
Daily, weekly, and monthly support and resistance levels play a key role in analyzing price movements:
Daily levels: Represent prices where a cryptocurrency has tended to bounce within the current trading day.
Weekly levels: Reflect strong prices that hold throughout the week.
Monthly levels: Indicate the most significant levels that can influence price movement over the month.
When trading cryptocurrencies, traders use these levels to make decisions about entering or exiting positions. For example, if a cryptocurrency approaches a weekly resistance level and fails to break through it, this may signal a sell opportunity. If the price reaches a daily support level and starts to bounce up, it may indicate a potential long position.
Market context and trading volumes are also important when analyzing support and resistance levels. High volume near a level can confirm its significance and the likelihood of subsequent price movement. Traders often combine analysis across different time frames to get a more complete picture and improve the accuracy of their trading decisions.
Moving Averages
Moving averages (EMA and SMA) are another important tool in the technical analysis of cryptocurrencies:
EMA (Exponential Moving Average): Gives more weight to recent prices, allowing it to respond more quickly to price changes.
SMA (Simple Moving Average): Equally considers all prices over a given period.
Key types of moving averages used by traders:
EMA 50 and 200: Often used to identify trends. The crossing of the 50-day EMA with the 200-day EMA is called a "golden cross" (buy signal) or a "death cross" (sell signal).
SMA 50, 100, 150, and 200: These periods are often used to determine long-term trends and support/resistance levels. Similar to the EMA, the crossings of these averages can signal potential trend changes.
Settings Groups:
EMA Golden Cross & Death Cross: A setting to display the "golden cross" and "death cross" for the EMA.
EMA 50 & 200: A setting to display the 50-day and 200-day EMA.
Support and Resistance Levels: Includes settings for daily, weekly, and monthly levels.
SMA 50, 100, 150, 200: A setting to display the 50, 100, 150, and 200-day SMA.
SMA Golden Cross & Death Cross: A setting to display the "golden cross" and "death cross" for the SMA.
Components:
Enable/disable the display of support and resistance levels.
Show level labels.
Parameters for adjusting offset, display of EMA and SMA, and their time intervals.
Parameters for configuring EMA and SMA Golden Cross & Death Cross.
EMA Parameters:
Enable/disable the display of 50 and 200-day EMA.
Color and style settings for EMA.
Options to use bar gaps and the "LookAhead" function.
SMA Parameters:
Enable/disable the display of 50, 100, 150, and 200-day SMA.
Color and style settings for SMA.
Options to use bar gaps and the "LookAhead" function.
Effective use of support and resistance levels, as well as moving averages, requires an understanding of technical analysis, discipline, and the ability to adapt the strategy according to changing market conditions.
(RUS) Данный Pine 5 скрипт предоставляет разнообразные инструменты для настройки и отображения различных уровней поддержки и сопротивления, а также скользящих средних (EMA и SMA) на графиках. Использование этих инструментов является важной стратегией для определения точек входа и выхода из сделок.
Уровни поддержки и сопротивления
Дневные, недельные и месячные уровни поддержки и сопротивления играют ключевую роль в анализе движения цен:
Дневные уровни: Представляют собой цены, на которых криптовалюта имела тенденцию отскакивать в течение текущего торгового дня.
Недельные уровни: Отражают сильные цены, которые сохраняются в течение недели.
Месячные уровни: Указывают на наиболее значимые уровни, которые могут влиять на движение цены в течение месяца.
При торговле криптовалютами трейдеры используют эти уровни для принятия решений о входе в позицию или закрытии сделки. Например, если криптовалюта приближается к недельному уровню сопротивления и не удается его преодолеть, это может стать сигналом для продажи. Если цена достигает дневного уровня поддержки и начинает отскакивать вверх, это может указывать на возможность открытия длинной позиции.
Контекст рынка и объемы торговли также важны при анализе уровней поддержки и сопротивления. Высокий объем при приближении к уровню может подтвердить его значимость и вероятность последующего движения цены. Трейдеры часто комбинируют анализ различных временных рамок для получения более полной картины и улучшения точности своих торговых решений.
Скользящие средние
Скользящие средние (EMA и SMA) являются еще одним важным инструментом в техническом анализе криптовалют:
EMA (Exponential Moving Average): Экспоненциальная скользящая средняя, которая придает большее значение последним ценам. Это позволяет более быстро реагировать на изменения в ценах.
SMA (Simple Moving Average): Простая скользящая средняя, которая равномерно учитывает все цены в заданном периоде.
Основные виды скользящих средних, которые используются трейдерами:
EMA 50 и 200: Часто используются для выявления трендов. Пересечение 50-дневной EMA с 200-дневной EMA называется "золотым крестом" (сигнал на покупку) или "крестом смерти" (сигнал на продажу).
SMA 50, 100, 150 и 200: Эти периоды часто используются для определения долгосрочных трендов и уровней поддержки/сопротивления. Аналогично EMA, пересечения этих средних могут сигнализировать о возможных изменениях тренда.
Группы настроек:
EMA Golden Cross & Death Cross: Настройка для отображения "золотого креста" и "креста смерти" для EMA.
EMA 50 & 200: Настройка для отображения 50-дневной и 200-дневной EMA.
Уровни поддержки и сопротивления: Включает настройки для дневных, недельных и месячных уровней.
SMA 50, 100, 150, 200: Настройка для отображения 50, 100, 150 и 200-дневных SMA.
SMA Golden Cross & Death Cross: Настройка для отображения "золотого креста" и "креста смерти" для SMA.
Компоненты:
Включение/отключение отображения уровней поддержки и сопротивления.
Показ ярлыков уровней.
Параметры для настройки смещения, отображения EMA и SMA, а также их временных интервалов.
Параметры для настройки EMA и SMA Golden Cross & Death Cross.
Параметры EMA:
Включение/отключение отображения 50 и 200-дневных EMA.
Настройки цвета и стиля для EMA.
Опции для использования разрыва баров и функции "LookAhead".
Параметры SMA:
Включение/отключение отображения 50, 100, 150 и 200-дневных SMA.
Настройки цвета и стиля для SMA.
Опции для использования разрыва баров и функции "LookAhead".
Эффективное использование уровней поддержки и сопротивления, а также скользящих средних, требует понимания технического анализа, дисциплины и умения адаптировать стратегию в зависимости от изменяющихся условий рынка.
ICT Killzones and Sessions W/ Silver Bullet + MacrosForex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times
This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours.
Features:
Session and Killzone Lines:
Green: London Open (LO)
White: New York (NY)
Orange: Australian (AU)
Purple: Asian (AS)
Includes AM and PM session markers.
Dotted/Striped Lines indicate overlapping kill zones within the session timeline.
Customization Options:
Display sessions and killzones in collapsed or full view.
Hide specific sessions or killzones based on your preferences.
Customize colors, texts, and sizes.
Option to hide drawings older than the current day.
Automatic Updates:
The indicator draws all lines and boxes at the start of a new day.
Automatically adjusts time-based boxes according to the New York timezone.
Killzone Time Windows (for indices):
London KZ: 02:00 - 05:00
New York AM KZ: 07:00 - 10:00
New York PM KZ: 13:30 - 16:00
Silver Bullet Times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro Times:
02:33 - 03:00
04:03 - 04:30
08:50 - 09:10
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
Latest Update:
January 15:
Added option to automatically change text coloring based on the chart.
Included additional optional macro times per user request:
12:50 - 13:10
13:50 - 14:15
14:50 - 15:10
15:50 - 16:15
Usage:
To maximize your experience, minimize the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts.
Originality and Justification:
This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making.
Credits:
This script incorporates open-source elements with significant improvements to enhance functionality and user experience.
Forex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times
This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours.
Features:
Session and Killzone Lines:
Green: London Open (LO)
White: New York (NY)
Orange: Australian (AU)
Purple: Asian (AS)
Includes AM and PM session markers.
Dotted/Striped Lines indicate overlapping kill zones within the session timeline.
Customization Options:
Display sessions and killzones in collapsed or full view.
Hide specific sessions or killzones based on your preferences.
Customize colors, texts, and sizes.
Option to hide drawings older than the current day.
Automatic Updates:
The indicator draws all lines and boxes at the start of a new day.
Automatically adjusts time-based boxes according to the New York timezone.
Killzone Time Windows (for indices):
London KZ: 02:00 - 05:00
New York AM KZ: 07:00 - 10:00
New York PM KZ: 13:30 - 16:00
Silver Bullet Times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro Times:
02:33 - 03:00
04:03 - 04:30
08:50 - 09:10
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
Latest Update:
January 15:
Added option to automatically change text coloring based on the chart.
Included additional optional macro times per user request:
12:50 - 13:10
13:50 - 14:15
14:50 - 15:10
15:50 - 16:15
ICT Sessions and Kill Zones
What They Are:
ICT Sessions: These are specific times during the trading day when market activity is expected to be higher, such as the London Open, New York Open, and the Asian session.
Kill Zones: These are specific time windows within these sessions where the probability of significant price movements is higher. For example, the New York AM Kill Zone is typically from 8:30 AM to 11:00 AM EST.
How to Use Them:
Identify the Session: Determine which trading session you are in (London, New York, or Asian).
Focus on Kill Zones: Within that session, focus on the kill zones for potential trade setups. For instance, during the New York session, look for setups between 8:30 AM and 11:00 AM EST.
Silver Bullets
What They Are:
Silver Bullets: These are specific, high-probability trade setups that occur within the kill zones. They are designed to be "one shot, one kill" trades, meaning they aim for precise and effective entries and exits.
How to Use Them:
Time-Based Setup: Look for these setups within the designated kill zones. For example, between 10:00 AM and 11:00 AM for the New York AM session .
Chart Analysis: Start with higher time frames like the 15-minute chart and then refine down to 5-minute and 1-minute charts to identify imbalances or specific patterns .
Macros
What They Are:
Macros: These are broader market conditions and trends that influence your trading decisions. They include understanding the overall market direction, seasonal tendencies, and the Commitment of Traders (COT) reports.
How to Use Them:
Understand Market Conditions: Be aware of the macroeconomic factors and market conditions that could affect price movements.
Seasonal Tendencies: Know the seasonal patterns that might influence the market direction.
COT Reports: Use the Commitment of Traders reports to understand the positioning of large traders and commercial hedgers .
Putting It All Together
Preparation: Understand the macro conditions and review the COT reports.
Session and Kill Zone: Identify the trading session and focus on the kill zones.
Silver Bullet Setup: Look for high-probability setups within the kill zones using refined chart analysis.
Execution: Execute the trade with precision, aiming for a "one shot, one kill" outcome.
By following these steps, you can effectively use ICT sessions, kill zones, silver bullets, and macros to enhance your trading strategy.
Usage:
To maximize your experience, shrink the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts.
Originality and Justification:
This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making.
Credits:
This script incorporates open-source elements with significant improvements to enhance functionality and user experience. All credit goes to itradesize for the SB + Macro boxes
Minervini VCP Pattern -Indian ContextThis script implements Mark Minervini's Trend Template and VCP (Volatility Contraction Pattern) pattern, specifically adapted for Indian stock markets (NSE). It helps identify stocks that are in strong uptrends and ready to break out.
Core Concepts Explained
1. What is the Minervini Trend Template?
Mark Minervini's method identifies stocks in Stage 2 uptrends - the sweet spot where institutional money is accumulating and stocks show the strongest momentum. Think of it as finding stocks that are "leaders" rather than "laggards."
2. What is VCP (Volatility Contraction Pattern)?
A VCP occurs when:
Stock price consolidates (moves sideways) after an uptrend
Price swings get tighter and tighter (like a coiled spring)
Volume dries up (fewer people trading)
Then it breaks out with force.
You can customize the strategy settings without editing code.
Key Settings:
Minimum Price (₹50): Filters out penny stocks that are too volatile
Min Distance from 52W Low (30%): Stock should be at least 30% above its yearly low
Max Distance from 52W High (25%): Stock should be within 25% of its yearly high (showing strength)
Moving Average Periods: 10, 50, 150, 200 days (industry standard)
Minimum Volume (100,000 shares): Ensures the stock is liquid enough to trade
Indian Market Adaptation: The default values (₹50 minimum, volume thresholds) are adjusted for NSE stocks, which behave differently than US markets.
The script pulls weekly chart data even when you're viewing daily charts.
Why it matters: Weekly trends are more reliable than daily noise. Professional traders use weekly charts to confirm the bigger picture.
What are Moving Averages (MAs)?
Simple averages of closing prices over X days
They smooth out price action to show trends
Think of them as the "average cost" of buyers over different time periods
The 4 Key MAs:
10 MA (Fast): Very short-term trend
50 MA: Short to medium-term trend
150 MA: Medium to long-term trend
200 MA: Long-term trend (the "grandfather" of all MAs)
Why Weekly MAs?
The script also calculates 10 and 50 MAs on weekly data for additional confirmation of the bigger trend.
The script Finds the highest and lowest prices over the past 52 weeks (1 year).
Why it matters:
Stocks near 52-week highs are showing strength (institutions buying)
Stocks far from 52-week lows have "room to run" upward
This is a psychological level that influences trader behaviour.
What is Volume here ?
The number of shares traded each day
High volume = many traders interested (conviction)
Low volume = lack of interest (weakness or consolidation)
Volume in VCP:
During consolidation (sideways movement), volume should dry up - this shows sellers are exhausted and buyers are holding. When volume spikes on a breakout, it confirms the move.
NSE Context: Indian stocks often have different volume patterns than US stocks, so the 50-day average is used as a baseline.
Relative Strength vs Nifty:
Example:
If your stock is up 20% and Nifty is up 10%, your stock has strong RS
If your stock is up 5% and Nifty is up 15%, your stock has weak RS (avoid it!)
Why it matters: The best performing stocks almost always have strong relative strength before major moves.
The 13 Minervini Conditions:-
Condition 1: Price > 50/150/200 MA
Meaning: Current price must be above ALL three major moving averages.
Why: This confirms the stock is in a clear uptrend. If price is below these MAs, the stock is weak or in a downtrend.
Condition 2: MA 50 > 150 > 200
Meaning: The moving averages themselves must be in proper order.
Analogy: Think of this like layers in a cake - short-term on top, long-term at bottom. If they're tangled, the trend is unclear.
Condition 3: 200 MA Rising (1 Month)
Meaning: The 200 MA today must be higher than it was 20 days ago.
Why: This confirms the long-term trend is UP, not flat or down. The means "20 bars ago."
Condition 4: 50 MA Rising
Meaning: The 50 MA today must be higher than 5 days ago.
Why: Confirms short-term momentum is accelerating upward.
Condition 5: Within 25% of 52-Week High
Meaning: Current price should be within 25% of its 1-year high.
Example:
52-week high = ₹1000
Current price must be above ₹750 (within 25%)
Why: Strong stocks stay near their highs. Weak stocks fall far from highs.
Condition 6: 30%+ Above 52-Week Low (OPTIONAL)
Meaning: Stock should be at least 30% above its yearly low.
Note: The script marks this as "SECONDARY - Optional" because the other conditions are more important. However, it's still a good confirmation.
Condition 7: Price > 10 MA
Meaning: Very short-term strength - price above the 10-day moving average.
Why: Ensures the stock hasn't just rolled over in the immediate term.
Condition 8: Price >= ₹50
Meaning: Filters out stocks below ₹50.
Why: In Indian markets, stocks below ₹50 tend to be penny stocks with poor liquidity and higher manipulation risk.
Condition 9: Weekly Uptrend
Meaning: On the weekly chart, price must be above both weekly MAs, and they must be properly aligned.
Why: Confirms the bigger picture trend, not just daily fluctuations.
Condition 10: 150 MA Rising
Meaning: The 150 MA is trending upward over the past 10 days.
Why: Another confirmation of medium-term trend health.
Condition 11: Sufficient Volume
Meaning: Average volume must exceed 100,000 shares (or your custom setting).
Why: Ensures you can actually buy/sell the stock without moving the price too much (liquidity).
Condition 12: RS vs Nifty Strong
Meaning: The stock's relative strength vs Nifty must be improving.
Why: You want stocks that are outperforming the market, not underperforming.
Condition 13: Nifty in Uptrend
Meaning: The Nifty 50 index itself must be above its 50 MA.
Why: "A rising tide lifts all boats." It's easier to make money in individual stocks when the overall market is bullish.
VCP Requirements:
Volatility Contracting: Price swings getting tighter (coiling spring)
Volume Drying Up: Fewer shares trading + trending lower
The Setup: When volatility contracts and volume dries up WHILE all 13 trend conditions are met, you have a VCP setup ready to explode.
What You See on Chart:
Colored Lines: 10 MA (green), 50 MA (blue), 150 MA (orange), 200 MA (red)
Blue Background: Trend template conditions met (watch zone)
Green Background: Full VCP setup detected (buy zone)
↟ Symbol Below Price: New VCP buy signal just triggered
Information Table:
What it does: Creates a checklist table on your chart showing the status of all conditions.
Table Structure:
Column 1: Condition name
Column 2: Status (✓ green = met, ✗ red = not met)
Final Row: Shows "BUY" (green) or "WAIT" (red) based on full VCP setup status.
Dos:
Example:
Account size: ₹5,00,000
Risk per trade: 1% = ₹5,000
Entry: ₹1000
Stop loss: ₹920 (8% below)
Distance to stop: ₹80
Shares to buy: ₹5,000 / ₹80 = 62 shares
Exit Strategy:
Sell 1/3 at +20% profit
Sell another 1/3 at +40% profit
Let the final 1/3 run with a trailing stop
Always exit if price closes below 10 MA on heavy volume
What This Script Does NOT Do:
Guarantee profits - No strategy works 100% of the time
Account for news events - Earnings, regulatory changes, etc.
Consider fundamentals - Company financials, debt, management quality
Adapt to market crashes - Works best in bull markets
Best Market Conditions:
✅ Nifty in uptrend (above 50 MA)
✅ Market breadth positive (more stocks advancing)
✅ Sector rotation happening
❌ Avoid in bear markets or high volatility periods
References:
Trade Like a Stock Market Wizard by Mark Minervini
Think & Trade Like a Champion by Mark Minervini
Chart attached: AU Small Finance Bank as on EoD dated 28/11/25
This script is a powerful tool for educational purpose only, remember: It's a tool, not a crystal ball. Use it to find high-probability setups, then apply proper risk management and patience. Good luck!
Macro Range HighlighterThis Pine Script indicator creates visual boxes that highlight specific time-based price ranges throughout the trading day, operating in New York Eastern Time. It offers two distinct modes: a standard hourly range mode and a classic ICT (Inner Circle Trader) Macro mode.
Two Operating Modes
Mode 1: Standard Hourly 50-09 Ranges (Default)
This mode identifies and highlights the price range during the final 10 minutes of each hour (xx:50) through the first 9 minutes of the next hour (xx:09).
Examples of captured ranges:
08:50 - 09:09
09:50 - 10:09
10:50 - 11:09
11:50 - 12:09
12:50 - 13:09
13:50 - 14:09
14:50 - 15:09
And continues for each hour...
Excluded Time Periods:
The indicator excludes certain periods that cross into or occur during market close and the daily reset:
02:50 - 03:09 (excluded to avoid interference with overnight session)
15:50 - 18:09 (excluded to avoid end-of-regular-hours and the 18:00 ET trading day reset)
This means you will NOT see boxes during the 16:00 or 17:00 hours, as these fall within the excluded window.
Mode 2: Classic ICT Macro Times
When enabled, this mode shows ONLY four specific time windows that are significant in ICT methodology:
02:33 - 02:59 (London Midnight Macro)
04:03 - 04:29 (London Open Macro)
13:10 - 13:39 (New York Lunch Macro)
15:15 - 15:44 (New York Close Macro)
When this mode is active, all standard hourly ranges are disabled, including the 02:50-03:09 range.
Green Line - Open Price
Represents the open price of the first candle when the range begins
This line is static once set - it shows where price opened when entering the time window
Extends horizontally across the entire duration of the box
Example: If the range starts at 08:50 and that candle opens at 18,500, the green line will be drawn at 18,500
Blue Line - Evolving Midpoint
Represents the dynamic midpoint between the range high and range low
This line continuously recalculates as new highs or lows are made within the time window
Calculation: Midpoint = (Range High + Range Low) / 2
Evolution example:
At 08:50, range is 18,480 (low) to 18,520 (high), midpoint = 18,500
At 08:55, price makes new high of 18,540, midpoint updates to 18,510
At 09:02, price makes new low of 18,470, midpoint updates to 18,505
The line visually adjusts up and down as the range expands
Extension: The line extends horizontally from the start of the range to the current bar (or end of range)
This gives traders a visual reference for the "fair value" or equilibrium point of the range
Red Line - Close Price
Represents the close price of the most recent candle within the time window
This line updates continuously with each new bar's close price
Extends horizontally across the range
When the range completes (exits the time window), it shows the final close price of the last bar in the range
Example: As price moves from 08:50 to 09:09, the red line will track the close of each candle: 18,505 → 18,510 → 18,508 → 18,515, etc.
This indicator provides a sophisticated visual framework for analyzing specific time-based price behavior. The evolving midpoint (blue line and optional yellow plot) is particularly powerful because it gives you real-time feedback on where the "fair value" of the range is as it develops, allowing you to make informed decisions about whether price is extended or returning to equilibrium. The three-line system (open/mid/close) creates a complete picture of price action within each critical time window, whether you're using standard hourly analysis or focusing on ICT's specific macro times.
Extreme Pressure Zones Indicator (EPZ) [BullByte]Extreme Pressure Zones Indicator(EPZ)
The Extreme Pressure Zones (EPZ) Indicator is a proprietary market analysis tool designed to highlight potential overbought and oversold "pressure zones" in any financial chart. It does this by combining several unique measurements of price action and volume into a single, bounded oscillator (0–100). Unlike simple momentum or volatility indicators, EPZ captures multiple facets of market pressure: price rejection, trend momentum, supply/demand imbalance, and institutional (smart money) flow. This is not a random mashup of generic indicators; each component was chosen and weighted to reveal extreme market conditions that often precede reversals or strong continuations.
What it is?
EPZ estimates buying/selling pressure and highlights potential extreme zones with a single, bounded 0–100 oscillator built from four normalized components. Context-aware weighting adapts to volatility, trendiness, and relative volume. Visual tools include adaptive thresholds, confirmed-on-close extremes, divergence, an MTF dashboard, and optional gradient candles.
Purpose and originality (not a mashup)
Purpose: Identify when pressure is building or reaching potential extremes while filtering noise across regimes and symbols.
Originality: EPZ integrates price rejection, momentum cascade, pressure distribution, and smart money flow into one bounded scale with context-aware weighting. It is not a cosmetic mashup of public indicators.
Why a trader might use EPZ
EPZ provides a multi-dimensional gauge of market extremes that standalone indicators may miss. Traders might use it to:
Spot Reversals: When EPZ enters an "Extreme High" zone (high red), it implies selling pressure might soon dominate. This can hint at a topside reversal or at least a pause in rallies. Conversely, "Extreme Low" (green) can highlight bottom-fish opportunities. The indicator's divergence module (optional) also finds hidden bullish/bearish divergences between price and EPZ, a clue that price momentum is weakening.
Measure Momentum Shifts: Because EPZ blends momentum and volume, it reacts faster than many single metrics. A rising MPO indicates building bullish pressure, while a falling MPO shows increasing bearish pressure. Traders can use this like a refined RSI: above 50 means bullish bias, below 50 means bearish bias, but with context provided by the thresholds.
Filter Trades: In trend-following systems, one could require EPZ to be in the bullish (green) zone before taking longs, or avoid new trades when EPZ is extreme. In mean-reversion systems, one might specifically look to fade extremes flagged by EPZ.
Multi-Timeframe Confirmation: The dashboard can fetch a higher timeframe EPZ value. For example, you might trade a 15-minute chart only when the 60-minute EPZ agrees on pressure direction.
Components and how they're combined
Rejection (PRV) – Captures price rejection based on candle wicks and volume (see Price Rejection Volume).
Momentum Cascade (MCD) – Blends multiple momentum periods (3,5,8,13) into a normalized momentum score.
Pressure Distribution (PDI) – Measures net buy/sell pressure by comparing volume on up vs down candles.
Smart Money Flow (SMF) – An adaptation of money flow index that emphasizes unusual volume spikes.
Each of these components produces a 0–100 value (higher means more bullish pressure). They are then weighted and averaged into the final Market Pressure Oscillator (MPO), which is smoothed and scaled. By combining these four views, EPZ stands out as a comprehensive pressure gauge – the whole is greater than the sum of parts
Context-aware weighting:
Higher volatility → more PRV weight
Trendiness up (RSI of ATR > 25) → more MCD weight
Relative volume > 1.2x → more PDI weight
SMF holds a stable weight
The weighted average is smoothed and scaled into MPO ∈ with 50 as the neutral midline.
What makes EPZ stand out
Four orthogonal inputs (price action, momentum, pressure, flow) unified in a single bounded oscillator with consistent thresholds.
Adaptive thresholds (optional) plus robust extreme detection that also triggers on crossovers, so static thresholds work reliably too.
Confirm Extremes on Bar Close (default ON): dots/arrows/labels/alerts print on closed bars to avoid repaint confusion.
Clean dashboard, divergence tools, pre-alerts, and optional on-price gradients. Visual 3D layering uses offsets for depth only,no lookahead.
Recommended markets and timeframes
Best: liquid symbols (index futures, large-cap equities, major FX, BTC/ETH).
Timeframes: 5–15m (more signals; consider higher thresholds), 1H–4H (balanced), 1D (clear regimes).
Use caution on illiquid or very low TFs where wick/volume geometry is erratic.
Logic and thresholds
MPO ∈ ; 50 = neutral. Above 50 = bullish pressure; below 50 = bearish.
Static thresholds (defaults): thrHigh = 70, thrLow = 30; warning bands 5 pts inside extremes (65/35).
Adaptive thresholds (optional):
thrHigh = min(BaseHigh + 5, mean(MPO,100) + stdev(MPO,100) × ExtremeSensitivity)
thrLow = max(BaseLow − 5, mean(MPO,100) − stdev(MPO,100) × ExtremeSensitivity)
Extreme detection
High: MPO ≥ thrHigh with peak/slope or crossover filter.
Low: MPO ≤ thrLow with trough/slope or crossover filter.
Cooldown: 5 bars (default). A new extreme will not print until the cooldown elapses, even if MPO re-enters the zone.
Confirmation
"Confirm Extremes on Bar Close" (default ON) gates extreme markers, pre-alerts, and alerts to closed bars (non-repainting).
Divergences
Pivot-based bullish/bearish divergence; tags appear only after left/right bars elapse (lookbackPivot).
MTF
HTF MPO retrieved with lookahead_off; values can update intrabar and finalize at HTF close. This is disclosed and expected.
Inputs and defaults (key ones)
Core: Sensitivity=1.0; Analysis Period=14; Smoothing=3; Adaptive Thresholds=OFF.
Extremes: Base High=70, Base Low=30; Extreme Sensitivity=1.5; Confirm Extremes on Bar Close=ON; Cooldown=5; Dot size Small/Tiny.
Visuals: Heatmap ON; 3D depth optional; Strength bars ON; Pre-alerts OFF; Divergences ON with tags ON; Gradient candles OFF; Glow ON.
Dashboard: ON; Position=Top Right; Size=Normal; MTF ON; HTF=60m; compact overlay table on price chart.
Advanced caps: Max Oscillator Labels=80; Max Extreme Guide Lines=80; Divergence objects=60.
Dashboard: what each element means
Header: EPZ ANALYSIS.
Large readout: Current MPO; color reflects state (extreme, approaching, or neutral).
Status badge: "Extreme High/Low", "Approaching High/Low", "Bullish/Neutral/Bearish".
HTF cell (when MTF ON): Higher-timeframe MPO, color-coded vs extremes; updates intrabar, settles at HTF close.
Predicted (when MTF OFF): Simple MPO extrapolation using momentum/acceleration—illustrative only.
Thresholds: Current thrHigh/thrLow (static or adaptive).
Components: ASCII bars + values for PRV, MCD, PDI, SMF.
Market metrics: Volume Ratio (x) and ATR% of price.
Strength: Bar indicator of |MPO − 50| × 2.
Confidence: Heuristic gauge (100 in extremes, 70 in warnings, 50 with divergence, else |MPO − 50|). Convenience only, not probability.
How to read the oscillator
MPO Value (0–100): A reading of 50 is neutral. Values above ~55 are increasingly bullish (green), while below ~45 are increasingly bearish (red). Think of these as "market pressure".
Extreme Zones: When MPO climbs into the bright orange/red area (above the base-high line, default 70), the chart will display a dot and downward arrow marking that extreme. Traders often treat this as a sign to tighten stops or look for shorts. Similarly, a bright green dot/up-arrow appears when MPO falls below the base-low (30), hinting at a bullish setup.
Heatmap/Candles: If "Pressure Heatmap" is enabled, the background of the oscillator pane will fade green or red depending on MPO. Users can optionally color the price candles by MPO value (gradient candles) to see these extremes on the main chart.
Prediction Zone(optional): A dashed projection line extends the MPO forward by a small number of bars (prediction_bars) using current MPO momentum and acceleration. This is a heuristic extrapolation best used for short horizons (1–5 bars) to anticipate whether MPO may touch a warning or extreme zone. It is provisional and becomes less reliable with longer projection lengths — always confirm predicted moves with bar-close MPO and HTF context before acting.
Divergences: When price makes a higher high but EPZ makes a lower high (bearish divergence), the indicator can draw dotted lines and a "Bear Div" tag. The opposite (lower low price, higher EPZ) gives "Bull Div". These signals confirm waning momentum at extremes.
Zones: Warning bands near extremes; Extreme zones beyond thresholds.
Crossovers: MPO rising through 35 suggests easing downside pressure; falling through 65 suggests waning upside pressure.
Dots/arrows: Extreme markers appear on closed bars when confirmation is ON and respect the 5-bar cooldown.
Pre-alert dots (optional): Proximity cues in warning zones; also gated to bar close when confirmation is ON.
Histogram: Distance from neutral (50); highlights strengthening or weakening pressure.
Divergence tags: "Bear Div" = higher price high with lower MPO high; "Bull Div" = lower price low with higher MPO low.
Pressure Heatmap : Layered gradient background that visually highlights pressure strength across the MPO scale; adjustable intensity and optional zone overlays (warning / extreme) for quick visual scanning.
A typical reading: If the oscillator is rising from neutral towards the high zone (green→orange→red), the chart may see strong buying culminating in a stall. If it then turns down from the extreme, that peak EPZ dot signals sell pressure.
Alerts
EPZ: Extreme Context — fires on confirmed extremes (respects cooldown).
EPZ: Approaching Threshold — fires in warning zones if no extreme.
EPZ: Divergence — fires on confirmed pivot divergences.
Tip: Set alerts to "Once per bar close" to align with confirmation and avoid intrabar repaint.
Practical usage ideas
Trend continuation: In positive regimes (MPO > 50 and rising), pullbacks holding above 50 often precede continuation; mirror for bearish regimes.
Exhaustion caution: E High/E Low can mark exhaustion risk; many wait for MPO rollover or divergence to time fades or partial exits.
Adaptive thresholds: Useful on assets with shifting volatility regimes to maintain meaningful "extreme" levels.
MTF alignment: Prefer setups that agree with the HTF MPO to reduce countertrend noise.
Examples
Screenshots captured in TradingView Replay to freeze the bar at close so values don't fluctuate intrabar. These examples use default settings and are reproducible on the same bars; they are for illustration, not cherry-picking or performance claims.
Example 1 — BTCUSDT, 1h — E Low
MPO closed at 26.6 (below the 30 extreme), printing a confirmed E Low. HTF MPO is 26.6, so higher-timeframe pressure remains bearish. Components are subdued (Momentum/Pressure/Smart$ ≈ 29–37), with Vol Ratio ≈ 1.19x and ATR% ≈ 0.37%. A prior Bear Div flagged weakening impulse into the drop. With cooldown set to 5 bars, new extremes are rate-limited. Many traders wait for MPO to curl up and reclaim 35 or for a fresh Bull Div before considering countertrend ideas; if MPO cannot reclaim 35 and HTF stays weak, treat bounces cautiously. Educational illustration only.
Example 2 — ETHUSD, 30m — E High
A strong impulse pushed MPO into the extreme zone (≥ 70), printing a confirmed E High on close. Shortly after, MPO cooled to ~61.5 while a Bear Div appeared, showing momentum lag as price pushed a higher high. Volume and volatility were elevated (≈ 1.79x / 1.25%). With a 5-bar cooldown, additional extremes won't print immediately. Some treat E High as exhaustion risk—either waiting for MPO rollover under 65/50 to fade, or for a pullback that holds above 50 to re-join the trend if higher-timeframe pressure remains constructive. Educational illustration only.
Known limitations and caveats
The MPO line itself can change intrabar; extreme markers/alerts do not repaint when "Confirm Extremes on Bar Close" is ON.
HTF values settle at the close of the HTF bar.
Illiquid symbols or very low TFs can be noisy; consider higher thresholds or longer smoothing.
Prediction line (when enabled) is a visual extrapolation only.
For coders
Pine v6. MTF via request.security with lookahead_off.
Extremes include crossover triggers so static thresholds also yield E High/E Low.
Extreme markers and pre-alerts are gated by barstate.isconfirmed when confirmation is ON.
Arrays prune oldest objects to respect resource limits; defaults (80/80/60) are conservative for low TFs.
3D layering uses negative offsets purely for drawing depth (no lookahead).
Screenshot methodology:
To make labels legible and to demonstrate non-repainting behavior, the examples were captured in TradingView Replay with "Confirm Extremes on Bar Close" enabled. Replay is used only to freeze the bar at close so plots don't change intrabar. The examples use default settings, include both Extreme Low and Extreme High cases, and can be reproduced by scrolling to the same bars outside Replay. This is an educational illustration, not a performance claim.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Markets involve risk; past behavior does not guarantee future results. You are responsible for your own testing, risk management, and decisions.
Volume Weighted RSI (VW RSI)The Volume Weighted RSI (VW RSI) is a momentum oscillator designed for TradingView, implemented in Pine Script v6, that enhances the traditional Relative Strength Index (RSI) by incorporating trading volume into its calculation. Unlike the standard RSI, which measures the speed and change of price movements based solely on price data, the VW RSI weights its analysis by volume, emphasizing price movements backed by significant trading activity. This makes the VW RSI particularly effective for identifying bullish or bearish momentum, overbought/oversold conditions, and potential trend reversals in markets where volume plays a critical role, such as stocks, forex, and cryptocurrencies.
Key Features
Volume-Weighted Momentum Calculation:
The VW RSI calculates momentum by comparing the volume associated with upward price movements (up-volume) to the volume associated with downward price movements (down-volume).
Up-volume is the volume on bars where the closing price is higher than the previous close, while down-volume is the volume on bars where the closing price is lower than the previous close.
These volumes are smoothed over a user-defined period (default: 14 bars) using a Running Moving Average (RMA), and the VW RSI is computed using the formula:
\text{VW RSI} = 100 - \frac{100}{1 + \text{VoRS}}
where
\text{VoRS} = \frac{\text{Average Up-Volume}}{\text{Average Down-Volume}}
.
Oscillator Range and Interpretation:
The VW RSI oscillates between 0 and 100, with a centerline at 50.
Above 50: Indicates bullish volume momentum, suggesting that volume on up bars dominates, which may signal buying pressure and a potential uptrend.
Below 50: Indicates bearish volume momentum, suggesting that volume on down bars dominates, which may signal selling pressure and a potential downtrend.
Overbought/Oversold Levels: User-defined thresholds (default: 70 for overbought, 30 for oversold) help identify potential reversal points:
VW RSI > 70: Overbought, indicating a possible pullback or reversal.
VW RSI < 30: Oversold, indicating a possible bounce or reversal.
Visual Elements:
VW RSI Line: Plotted in a separate pane below the price chart, colored dynamically based on its value:
Green when above 50 (bullish momentum).
Red when below 50 (bearish momentum).
Gray when at 50 (neutral).
Centerline: A dashed line at 50, optionally displayed, serving as the neutral threshold between bullish and bearish momentum.
Overbought/Oversold Lines: Dashed lines at the user-defined overbought (default: 70) and oversold (default: 30) levels, optionally displayed, to highlight extreme conditions.
Background Coloring: The background of the VW RSI pane is shaded red when the indicator is in overbought territory and green when in oversold territory, providing a quick visual cue of potential reversal zones.
Alerts:
Built-in alerts for key events:
Bullish Momentum: Triggered when the VW RSI crosses above 50, indicating a shift to bullish volume momentum.
Bearish Momentum: Triggered when the VW RSI crosses below 50, indicating a shift to bearish volume momentum.
Overbought Condition: Triggered when the VW RSI crosses above the overbought threshold (default: 70), signaling a potential pullback.
Oversold Condition: Triggered when the VW RSI crosses below the oversold threshold (default: 30), signaling a potential bounce.
Input Parameters
VW RSI Length (default: 14): The period over which the up-volume and down-volume are smoothed to calculate the VW RSI. A longer period results in smoother signals, while a shorter period increases sensitivity.
Overbought Level (default: 70): The threshold above which the VW RSI is considered overbought, indicating a potential reversal or pullback.
Oversold Level (default: 30): The threshold below which the VW RSI is considered oversold, indicating a potential reversal or bounce.
Show Centerline (default: true): Toggles the display of the 50 centerline, which separates bullish and bearish momentum zones.
Show Overbought/Oversold Lines (default: true): Toggles the display of the overbought and oversold threshold lines.
How It Works
Volume Classification:
For each bar, the indicator determines whether the price movement is upward or downward:
If the current close is higher than the previous close, the bar’s volume is classified as up-volume.
If the current close is lower than the previous close, the bar’s volume is classified as down-volume.
If the close is unchanged, both up-volume and down-volume are set to 0 for that bar.
Smoothing:
The up-volume and down-volume are smoothed using a Running Moving Average (RMA) over the specified period (default: 14 bars) to reduce noise and provide a more stable measure of volume momentum.
VW RSI Calculation:
The Volume Relative Strength (VoRS) is calculated as the ratio of smoothed up-volume to smoothed down-volume.
The VW RSI is then computed using the standard RSI formula, but with volume data instead of price changes, resulting in a value between 0 and 100.
Visualization and Alerts:
The VW RSI is plotted with dynamic coloring to reflect its momentum direction, and optional lines are drawn for the centerline and overbought/oversold levels.
Background coloring highlights overbought and oversold conditions, and alerts notify the trader of significant crossings.
Usage
Timeframe: The VW RSI can be used on any timeframe, but it is particularly effective on intraday charts (e.g., 1-hour, 4-hour) or daily charts where volume data is reliable. Shorter timeframes may require a shorter length for increased sensitivity, while longer timeframes may benefit from a longer length for smoother signals.
Markets: Best suited for markets with significant and reliable volume data, such as stocks, forex, and cryptocurrencies. It may be less effective in markets with low or inconsistent volume, such as certain futures contracts.
Trading Strategies:
Trend Confirmation:
Use the VW RSI to confirm the direction of a trend. For example, in an uptrend, look for the VW RSI to remain above 50, indicating sustained bullish volume momentum, and consider buying on pullbacks when the VW RSI dips but stays above 50.
In a downtrend, look for the VW RSI to remain below 50, indicating sustained bearish volume momentum, and consider selling on rallies when the VW RSI rises but stays below 50.
Overbought/Oversold Conditions:
When the VW RSI crosses above 70, the market may be overbought, suggesting a potential pullback or reversal. Consider taking profits on long positions or preparing for a short entry, but confirm with price action or other indicators.
When the VW RSI crosses below 30, the market may be oversold, suggesting a potential bounce or reversal. Consider entering long positions or covering shorts, but confirm with additional signals.
Divergences:
Look for divergences between the VW RSI and price to spot potential reversals. For example, if the price makes a higher high but the VW RSI makes a lower high, this bearish divergence may signal an impending downtrend.
Conversely, if the price makes a lower low but the VW RSI makes a higher low, this bullish divergence may signal an impending uptrend.
Momentum Shifts:
A crossover above 50 can signal the start of bullish momentum, making it a potential entry point for long trades.
A crossunder below 50 can signal the start of bearish momentum, making it a potential entry point for short trades or an exit for long positions.
Example
On a 4-hour SOLUSDT chart:
During an uptrend, the VW RSI might rise above 50 and stay there, confirming bullish volume momentum. If it approaches 70, it may indicate overbought conditions, as seen near a price peak of 145.08, suggesting a potential pullback.
During a downtrend, the VW RSI might fall below 50, confirming bearish volume momentum. If it drops below 30 near a price low of 141.82, it may indicate oversold conditions, suggesting a potential bounce, as seen in a slight recovery afterward.
A bullish divergence might occur if the price makes a lower low during the downtrend, but the VW RSI makes a higher low, signaling a potential reversal.
Limitations
Lagging Nature: Like the traditional RSI, the VW RSI is a lagging indicator because it relies on smoothed data (RMA). It may not react quickly to sudden price reversals, potentially missing the start of new trends.
False Signals in Ranging Markets: In choppy or ranging markets, the VW RSI may oscillate around 50, generating frequent crossovers that lead to false signals. Combining it with a trend filter (e.g., ADX) can help mitigate this.
Volume Data Dependency: The VW RSI relies on accurate volume data, which may be inconsistent or unavailable in some markets (e.g., certain forex pairs or futures contracts). In such cases, the indicator’s effectiveness may be reduced.
Overbought/Oversold in Strong Trends: During strong trends, the VW RSI can remain in overbought or oversold territory for extended periods, leading to premature exit signals. Use additional confirmation to avoid exiting too early.
Potential Improvements
Smoothing Options: Add options to use different smoothing methods (e.g., EMA, SMA) instead of RMA for the up/down volume calculations, allowing users to adjust the indicator’s responsiveness.
Divergence Detection: Include logic to detect and plot bullish/bearish divergences between the VW RSI and price, providing visual cues for potential reversals.
Customizable Colors: Allow users to customize the colors of the VW RSI line, centerline, overbought/oversold lines, and background shading.
Trend Filter: Integrate a trend strength filter (e.g., ADX > 25) to ensure signals are generated only during strong trends, reducing false signals in ranging markets.
The Volume Weighted RSI (VW RSI) is a powerful tool for traders seeking to incorporate volume into their momentum analysis, offering a unique perspective on market dynamics by emphasizing price movements backed by significant trading activity. It is best used in conjunction with other indicators and price action analysis to confirm signals and improve trading decisions.
VMDM - Volume, Momentum & Divergence Master [BullByte]VMDM - Volume, Momentum and Divergence Master
Educational Multi-Layer Market Structure Analysis System
Multi-factor divergence engine that scores RSI momentum, volume pressure, and institutional footprints into one non-repainting confluence rating (0-100).
WHAT THIS INDICATOR IS
VMDM is an educational indicator designed to teach traders how to recognize high-probability reversal and continuation patterns by analyzing four independent market dimensions simultaneously. Instead of relying on a single indicator that may produce frequent false signals, VMDM creates a confluence-based scoring system that weights multiple confirmation factors, helping you understand which setups have stronger technical backing and which are lower quality.
This is NOT a trading system or signal generator. It is a learning tool that visualizes complex market structure concepts in an accessible format for both coders and non-coders.
THE PROBLEM IT SOLVES
Most traders face these common challenges:
Challenge 1 - Indicator Overload: Running RSI, volume analysis, and divergence detection separately creates chart clutter and conflicting signals. You waste time cross-referencing multiple windows trying to determine if all factors align.
Challenge 2 - False Divergences: Standard divergence indicators trigger on every minor pivot, creating noise. Many divergences fail because they lack supporting evidence from volume or market structure.
Challenge 3 - Missed Context: A bullish RSI divergence means nothing if it occurs during weak volume or in the middle of strong distribution. Context determines quality.
Challenge 4 - Repainting Confusion: Many divergence scripts repaint, showing perfect historical signals that never actually triggered in real-time, leading to false confidence.
Challenge 5 - Institutional Pattern Recognition: Absorption zones, stop hunts, and exhaustion patterns are taught in trading education but difficult to identify systematically without manual analysis.
VMDM addresses all five challenges by combining complementary analytical layers into one transparent, non-repainting, confluence-weighted system with visual clarity.
WHY THIS SPECIFIC COMBINATION - MASHUP JUSTIFICATION
This indicator is NOT a random mashup of popular indicators. Each of the four layers serves a specific analytical purpose and together they create a complete market structure assessment framework.
THE FOUR ANALYTICAL LAYERS
LAYER 1 - RSI MOMENTUM DIVERGENCE (Trend Exhaustion Detection)
Purpose: Identifies when price momentum is weakening before price itself reverses.
Why RSI: The Relative Strength Index measures momentum on a bounded 0-100 scale, making divergence detection mathematically consistent across all assets and timeframes. Unlike raw price oscillators, RSI normalizes momentum regardless of volatility regime.
How It Contributes: Divergence between price pivots and RSI pivots reveals early momentum exhaustion. A lower price low with a higher RSI low (bullish regular divergence) signals sellers are losing strength even as price makes new lows. This is the PRIMARY signal generator in VMDM.
Limitation If Used Alone: RSI divergence by itself produces many false signals because momentum can remain weak during continued trends. It needs confirmation from volume and structural evidence.
LAYER 2 - VOLUME PRESSURE ANALYSIS (Buying vs Selling Intensity)
Purpose: Quantifies whether the current bar's volume reflects buying pressure or selling pressure based on where price closed within the bar's range.
Methodology: Instead of just measuring volume size, VMDM calculates WHERE in the bar range the close occurred. A close near the high on high volume indicates strong buying absorption. A close near the low indicates selling pressure. The calculation accounts for wick size (wicks reduce pressure quality) and uses percentile ranking over a lookback period to normalize pressure strength on a 0-100 scale.
Formula Concept:
Buy Pressure = Volume × (Close - Low) / (High - Low) × Wick Quality Factor
Sell Pressure = Volume × (High - Close) / (High - Low) × Wick Quality Factor
Net Pressure = Buy Pressure - Sell Pressure
Pressure Strength = Percentile Rank of Net Pressure over lookback period
Why Percentile Ranking: Absolute volume varies by asset and session. Percentile ranking makes 85th percentile pressure on low-volume crypto comparable to 85th percentile pressure on high-volume forex.
How It Contributes: When a bullish divergence occurs at a pivot low AND pressure strength is above 60 (strong buying), this adds 25 confluence points. It confirms that the divergence is occurring during actual accumulation, not just weak selling.
Limitation If Used Alone: Pressure analysis shows current bar intensity but cannot identify trend exhaustion or reversal timing. High buying pressure can exist during a strong uptrend with no reversal imminent.
LAYER 3 - BEHAVIORAL FOOTPRINT PATTERNS (Volume Anomaly Detection)
CRITICAL DISCLAIMER: The terms "institutional footprint," "absorption," "stop hunt," and "exhaustion" used in this indicator are EDUCATIONAL LABELS for specific price and volume behavioral patterns. These patterns are detected through technical analysis of publicly available price, volume, and bar structure data. This indicator does NOT have access to actual institutional order flow, market maker data, broker stop-loss locations, or any non-public data source. These pattern names are used because they are common terminology in trading education to describe these technical behaviors. The analysis is interpretive and based on observable price action, not privileged information.
Purpose: Detect volume anomalies and price patterns that historically correlate with potential reversal zones or trend continuation failure.
Pattern Type 1 - Absorption (Labeled as "ACCUMULATION" or "DISTRIBUTION")
Detection Criteria: Volume is more than 2x the moving average AND bar range is less than 50 percent of the average bar range.
Interpretation: High volume compressed into a tight range suggests large participants are absorbing supply (accumulation) or distribution (distribution) without allowing price to move significantly. This often precedes directional moves once absorption completes.
Visual: Colored box zone highlighting the absorption area.
Pattern Type 2 - Stop Hunt (Labeled as "BULL HUNT" or "BEAR HUNT")
Detection Criteria: Price penetrates a recent 10-bar high or low by a small margin (0.2 percent), then closes back inside the range on above-average volume (1.5x+).
Interpretation: Price briefly spikes beyond recent structure (likely triggering stop losses placed just beyond obvious levels) then reverses. This is a classic false breakout pattern often seen before reversals.
Visual: Label at the wick extreme showing hunt direction.
Pattern Type 3 - Exhaustion (Labeled as "SELL EXHAUST" or "BUY EXHAUST")
Detection Criteria: Lower wick is more than 2.5x the body size with volume above 1.8x average and RSI below 35 (sell exhaustion), OR upper wick more than 2.5x body size with volume above 1.8x average and RSI above 65 (buy exhaustion).
Interpretation: Large wicks with high volume and extreme RSI suggest aggressive buying or selling was met with equally aggressive rejection. This exhaustion often marks short-term extremes.
Visual: Label showing exhaustion type.
How These Contribute: When a divergence forms at a pivot AND one of these behavioral patterns is active, the confluence score increases by 20 points. This confirms the divergence is occurring during structural anomaly activity, not just normal price flow.
Limitation If Used Alone: These patterns can occur mid-trend and do not indicate direction without momentum context. Absorption in a strong uptrend may just be continuation accumulation.
LAYER 4 - CONFLUENCE SCORING MATRIX (Quality Weighting System)
Purpose: Translate all detected conditions into a single 0-100 quality score so you can objectively compare setups.
Scoring Breakdown:
Divergence Present: +30 points (primary signal)
Pressure Confirmation: +25 points (volume supports direction)
Behavioral Footprint Active: +20 points (structural anomaly present)
RSI Extreme: +15 points (RSI below 30 or above 70 at pivot)
Volume Spike: +10 points (current volume above 1.5x average)
Maximum Possible Score: 100 points
Why These Weights: The weights reflect reliability hierarchy based on backtesting observation. Divergence is the core signal (30 points), but without volume confirmation (25 points) many fail. Behavioral patterns add meaningful context (20 points). RSI extremes and volume spikes are secondary confirmations (15 and 10 points).
Quality Tiers:
90-100: TEXTBOOK (all factors aligned)
75-89: HIGH QUALITY (strong confluence)
60-74: VALID (meets minimum threshold)
Below 60: DEVELOPING (not displayed unless threshold lowered)
How It Contributes: The confluence score allows you to filter noise. You can set your minimum quality threshold in settings. Higher thresholds (75+) show fewer but higher-quality patterns. Lower thresholds (50-60) show more patterns but include lower-confidence setups. This teaches you to distinguish strong setups from weak ones.
Limitation: Confluence scoring is historical observation-based, not predictive guarantee. A 95-point setup can still fail. The score represents technical alignment, not future certainty.
WHY THIS COMBINATION WORKS TOGETHER
Each layer addresses a limitation in the others:
RSI Divergence identifies WHEN momentum is exhausting (timing)
Volume Pressure confirms WHETHER the exhaustion is accompanied by opposite-side accumulation (confirmation)
Behavioral Footprint shows IF structural anomalies support the reversal hypothesis (context)
Confluence Scoring weights ALL factors into an objective quality metric (filtering)
Using only RSI divergence gives you timing without confirmation. Using only volume pressure gives you intensity without directional context. Using only pattern detection gives you anomalies without trend exhaustion context. Using all four together creates a complete analytical framework where each layer compensates for the others' weaknesses.
This is not a mashup for the sake of combining indicators. It is a structured analytical system where each component has a defined role in a multi-dimensional market assessment process.
HOW TO READ THE INDICATOR - VISUAL ELEMENTS GUIDE
VMDM displays up to five visual layer types. You can enable or disable each layer independently in settings under "Visual Layers."
VISUAL LAYER 1 - MARKET STRUCTURE (Pivot Points and Lines)
What You See:
Small labels at swing highs and lows marked "PH" (Pivot High) and "PL" (Pivot Low) with horizontal dashed lines extending right from each pivot.
What It Means:
These are CONFIRMED pivots, not real-time. A pivot low appears AFTER the required right-side confirmation bars pass (default 3 bars). This creates a delay but prevents repainting. The pivot only appears once it is mathematically confirmed.
The horizontal lines represent support (from pivot lows) and resistance (from pivot highs) levels where price previously found significant rejection.
Color Coding:
Green label and line: Pivot Low (potential support)
Red label and line: Pivot High (potential resistance)
How To Use:
These pivots are the foundation for divergence detection. Divergence is only calculated between confirmed pivots, ensuring all signals are non-repainting. The lines help you see historical structure levels.
VISUAL LAYER 2 - PRESSURE ZONES (Background Color)
What You See:
Subtle background color shading on bars - light green or light red tint.
What It Means:
This visualizes volume pressure strength in real-time.
Color Coding:
Light Green Background: Pressure Strength above 70 (strong buying pressure - price closing near highs on volume)
Light Red Background: Pressure Strength below 30 (strong selling pressure - price closing near lows on volume)
No Color: Neutral pressure (pressure between 30-70)
How To Use:
When a bullish divergence pattern appears during green pressure zones, it suggests the divergence is forming during accumulation. When a bearish divergence appears during red zones, distribution is occurring. Pressure zones help you filter divergences - those forming in supportive pressure environments have higher probability.
VISUAL LAYER 3 - DIVERGENCE LINES (Dotted Connectors)
What You See:
Dotted lines connecting two pivot points (either two pivot lows or two pivot highs).
What It Means:
A divergence has been detected between those two pivots. The line connects the price pivots where RSI showed opposite behavior.
Color Coding:
Bright Green Line: Bullish divergence (regular or hidden)
Bright Red Line: Bearish divergence (regular or hidden)
How To Use:
The divergence line appears ONLY after the second pivot is confirmed (delayed by right-side confirmation bars). This is intentional to prevent repainting. When you see the line appear, it means:
For Bullish Regular Divergence:
Price made a lower low (second pivot lower than first)
RSI made a higher low (RSI at second pivot higher than first)
Interpretation: Downtrend losing momentum
For Bullish Hidden Divergence:
Price made a higher low (second pivot higher than first)
RSI made a lower low (RSI at second pivot lower than first)
Interpretation: Uptrend continuation likely (pullback within uptrend)
For Bearish Regular Divergence:
Price made a higher high (second pivot higher than first)
RSI made a lower high (RSI at second pivot lower than first)
Interpretation: Uptrend losing momentum
For Bearish Hidden Divergence:
Price made a lower high (second pivot lower than first)
RSI made a higher high (RSI at second pivot higher than first)
Interpretation: Downtrend continuation likely (bounce within downtrend)
If "Show Consolidated Analysis Label" is disabled, a small label will appear on the divergence line showing the divergence type abbreviation.
VISUAL LAYER 4 - BEHAVIORAL FOOTPRINT MARKERS
What You See:
Boxes, labels, and markers at specific bars showing pattern detection.
ABSORPTION ZONES (Boxes):
Colored rectangular boxes spanning one or more bars.
Purple Box: Accumulation absorption zone (high volume, tight range, bullish close)
Red Box: Distribution absorption zone (high volume, tight range, bearish close)
If absorption continues for multiple consecutive bars, the box extends and a counter appears in the label showing how many bars the absorption lasted.
What It Means: Large volume is being absorbed without significant price movement. This often precedes directional breakouts once the absorption phase completes.
STOP HUNT MARKERS (Labels):
Small labels below or above wicks labeled "BULL HUNT" or "BEAR HUNT" (may show bar count if consecutive).
What It Means:
BULL HUNT : Price spiked below recent lows then reversed back up on volume - likely triggered sell stops before reversing
BEAR HUNT : Price spiked above recent highs then reversed back down on volume - likely triggered buy stops before reversing
EXHAUSTION MARKERS (Labels):
Labels showing "SELL EXHAUST" or "BUY EXHAUST."
What It Means:
SELL EXHAUST : Large lower wick with high volume and low RSI - aggressive selling met with strong rejection
BUY EXHAUST : Large upper wick with high volume and high RSI - aggressive buying met with strong rejection
How To Use:
These markers help you identify WHERE structural anomalies occurred. When a divergence signal appears AT THE SAME TIME as one of these patterns, the confluence score increases. You are looking for alignment - divergence + behavioral pattern + pressure confirmation = high-quality setup.
VISUAL LAYER 5 - CONSOLIDATED ANALYSIS LABEL (Main Pattern Signal)
What You See:
A large label appearing at pivot points (or in real-time mode, at current bar) containing full pattern analysis.
Label Appearance:
Depending on your "Use Compact Label Format" setting:
COMPACT MODE (Single Line):
Example: "BULLISH REGULAR | Q:HIGH QUALITY C:82"
Breakdown:
BULLISH REGULAR: Divergence type detected
Q:HIGH QUALITY: Pattern quality tier
C:82: Confluence score (82 out of 100)
FULL MODE (Multi-Line Detailed):
Example:
PATTERN DETECTED
-------------------
BULLISH REGULAR
Quality: HIGH QUALITY
Price: Lower Low
Momentum: Higher Low
Signal: Weakening Downtrend
CONFLUENCE: 82/100
-------------------
Divergence: 30
Pressure: 25
Institutional: 20
RSI Extreme: 0
Volume: 10
Breakdown:
Top section: Pattern type and quality
Middle section: Divergence explanation (what price did vs what RSI did)
Bottom section: Confluence score with itemized breakdown showing which factors contributed
Label Position:
In Confirmed modes: Label appears AT the pivot point (delayed by confirmation bars)
In Real-time mode: Label appears at current bar as conditions develop
Label Color:
Gold: Textbook quality (90+ confluence)
Green: High quality (75-89 confluence)
Blue: Valid quality (60-74 confluence)
How To Use:
This is your primary decision-making label. When it appears:
Check the divergence type (regular divergences are reversal signals, hidden divergences are continuation signals)
Review the quality tier (textbook and high quality have better historical win rates)
Examine the confluence breakdown to see which factors are present and which are missing
Look at the chart context (trend, support/resistance, timeframe)
Use this information to assess whether the setup aligns with your strategy
The label does NOT tell you to buy or sell. It tells you a technical pattern has formed and provides the quality assessment. Your trading decision must incorporate risk management, market context, and your strategy rules.
UNDERSTANDING THE THREE DETECTION MODES
VMDM offers three signal detection modes in settings to accommodate different trading styles and learning objectives.
MODE 1: "Confluence Only (Real-Time)"
How It Works: Displays signals AS THEY DEVELOP on the current bar without waiting for pivot confirmation. The system calculates confluence score from pressure, volume, RSI extremes, and behavioral patterns. Divergence signals are NOT required in this mode.
Delay: ZERO - signals appear immediately.
Use Case: Real-time scanning for high-confluence zones without divergence requirement. Useful for intraday traders who want immediate alerts when multiple factors align.
Tradeoff: More frequent signals but includes setups without confirmed divergence. Higher false signal rate. Signals can change as the bar develops (not repainting in historical bars, but current bar updates).
Visual Behavior: Labels appear at the current bar. No divergence lines unless divergence happens to be present.
MODE 2: "Divergence + Confluence (Confirmed)" - DEFAULT RECOMMENDED
How It Works: Full system engagement. Signals appear ONLY when:
A pivot is confirmed (requires right-side confirmation bars to pass)
Divergence is detected between current pivot and previous pivot
Total confluence score meets or exceeds your minimum threshold
Delay: Equal to your "Pivot Right Bars" setting (default 3 bars). This means signals appear 3 bars AFTER the actual pivot formed.
Use Case: Highest-quality, non-repainting signals for swing traders and learners who want to study confirmed pattern completion.
Tradeoff: Delayed signals. You will not receive the signal until confirmation occurs. In fast-moving markets, price may have already moved significantly by the time the signal appears.
Visual Behavior: Labels appear at the historical pivot location (in the past). Divergence lines connect the two pivots. This is the most educational mode because it shows completed, confirmed patterns.
Non-Repainting Guarantee: Yes. Once a signal appears, it never disappears or changes.
MODE 3: "Divergence + Confluence (Relaxed)"
How It Works: Same as Confirmed mode but with adaptive thresholds. If confluence is very high (10 points above threshold), the signal may appear even if some factors are weak. If divergence is present but confluence is slightly below threshold (within 10 points), it may still appear.
Delay: Same as Confirmed mode (right-side confirmation bars).
Use Case: Slightly more signals than Confirmed mode for traders willing to accept near-threshold setups.
Tradeoff: More signals but lower average quality than Confirmed mode.
Visual Behavior: Same as Confirmed mode.
DASHBOARD GUIDE - READING THE METRICS
The dashboard appears in the corner of your chart (position selectable in settings) and provides real-time market state analysis.
You can choose between four dashboard detail levels in settings: Off, Compact, Optimized (default), Full.
DASHBOARD ROW EXPLANATIONS
ROW 1 - Header Information
Left: Current symbol and timeframe
Center: "VMDM "
Right: Version number
ROW 2 - Mode and Delay
Shows which detection mode you are using and the signal delay.
Example: "CONFIRMED | Delay: 3 bars"
This reminds you that signals in confirmed mode appear 3 bars after the pivot forms.
ROW 3 - Market Regime
Format: "TREND UP HV" or "RANGING NV"
First Part - Trend State:
TREND UP: 20 EMA above 50 EMA with strong separation
TREND DOWN: 20 EMA below 50 EMA with strong separation
RANGING: EMAs close together, low trend strength
TRANSITION: Between trending and ranging states
Second Part - Volatility State:
HV: High Volatility (current ATR more than 1.3x the 50-bar average ATR)
NV: Normal Volatility (current ATR between 0.7x and 1.3x average)
LV: Low Volatility (current ATR less than 0.7x average)
Third Column: Volatility ratio (example: "1.45x" means current ATR is 1.45 times normal)
How To Use: Regime context helps you interpret signals. Reversal divergences are more reliable in ranging or transitional regimes. Continuation divergences (hidden) are more reliable in trending regimes. High volatility means wider stops may be needed.
ROW 4 - Pressure
Shows current volume pressure state.
Format: "BUYING | ██████████░░░░░░░░░"
States:
BUYING : Pressure strength above 60 (closes near highs)
SELLING : Pressure strength below 40 (closes near lows)
NEUTRAL : Pressure strength between 40-60
Bar Visualization: Each block represents 10 percentile points. A full bar (10 filled blocks) = 100th percentile pressure.
Color: Green for buying, red for selling, gray for neutral.
How To Use: When pressure aligns with divergence direction (bullish divergence during buying pressure), confluence is stronger.
ROW 5 - Volume and RSI
Format: "1.8x | RSI 68 | OB"
First Value: Current volume ratio (1.8x = volume is 1.8 times the moving average)
Second Value: Current RSI reading
Third Value: RSI state
OB: Overbought (RSI above 70)
OS: Oversold (RSI below 30)
Blank: Neutral RSI
How To Use: Volume spikes (above 1.5x) during divergence formation add confluence. RSI extremes at pivots add confluence.
ROW 6 - Behavioral Footprint
Format: "BULL HUNT | 2 bars"
Shows the most recent behavioral pattern detected and how long ago.
States:
ACCUMULATION / DISTRIBUTION: Absorption detected
BULL HUNT / BEAR HUNT: Stop hunt detected
SELL EXHAUST / BUY EXHAUST: Exhaustion detected
SCANNING: No recent pattern
NOW: Pattern is active on current bar
How To Use: When footprint activity is recent (within 50 bars) or active now, it adds context to divergence signals forming in that area.
ROW 7 - Current Pattern
Shows the divergence type currently detected (if any).
Examples: "BULLISH REGULAR", "BEARISH HIDDEN", "Scanning..."
Quality: Shows pattern quality (TEXTBOOK, HIGH QUALITY, VALID)
How To Use: This tells you what type of signal is active. Regular divergences are reversal setups. Hidden divergences are continuation setups.
ROW 8 - Session Summary
Format: "14 events | A3 H8 E3"
First Value: Total institutional events this session
Breakdown:
A: Absorption events
H: Stop hunt events
E: Exhaustion events
How To Use: High event counts suggest an active, volatile session with frequent structural anomalies. Low counts suggest quiet, orderly price action.
ROW 9 - Confluence Score (Optimized/Full mode only)
Format: "78/100 | ████████░░"
Shows current real-time confluence score even if no pattern is confirmed yet.
How To Use: Watch this in real-time to see how close you are to pattern formation. When it exceeds your threshold and divergence forms, a signal will appear (after confirmation delay).
ROW 10 - Patterns Studied (Optimized/Full mode only)
Format: "47 patterns | 12 bars ago"
First Value: Total confirmed patterns detected since chart loaded
Second Value: How many bars since the last confirmed pattern appeared
How To Use: Helps you understand pattern frequency on your selected symbol and timeframe. If many bars have passed since last pattern, market may be trending without reversal opportunities.
ROW 11 - Bull/Bear Ratio (Optimized/Full mode only)
Format: "28:19 | BULL"
Shows count of bullish vs bearish patterns detected.
Balance:
BULL: More bullish patterns detected (suggests market has had more bullish reversals/continuations)
BEAR: More bearish patterns detected
BAL: Equal counts
How To Use: Extreme imbalances can indicate directional bias in the studied period. A heavily bullish ratio in a downtrend might suggest frequent failed rallies (bearish continuation). Context matters.
ROW 12 - Volume Ratio Detail (Optimized/Full mode only)
Shows current volume vs average volume in absolute terms.
Example: "1.4x | 45230 / 32300"
How To Use: Confirms whether current activity is above or below normal.
ROW 13 - Last Institutional Event (Full mode only)
Shows the most recent institutional pattern type and how many bars ago it occurred.
Example: "DISTRIBUTION | 23 bars"
How To Use: Tracks recency of last anomaly for context.
SETTINGS GUIDE - EVERY PARAMETER EXPLAINED
PERFORMANCE SECTION
Enable All Visuals (Master Toggle)
Default: ON
What It Does: Master kill switch for ALL visual elements (labels, lines, boxes, background colors, dashboard). When OFF, only plot outputs remain (invisible unless you open data window).
When To Change: Turn OFF on mobile devices, 1-second charts, or slow computers to improve performance. You can still receive alerts even with visuals disabled.
Impact: Dramatic performance improvement when OFF, but you lose all visual feedback.
Maximum Object History
Default: 50 | Range: 10-100
What It Does: Limits how many of each object type (labels, lines, boxes) are kept in memory. Older objects beyond this limit are deleted.
When To Change: Lower to 20-30 on fast timeframes (1-minute charts) to prevent slowdown. Increase to 100 on daily charts if you want more historical pattern visibility.
Impact: Lower values = better performance but less historical visibility. Higher values = more history visible but potential slowdown on fast timeframes.
Alert Cooldown (Bars)
Default: 5 | Range: 1-50
What It Does: Minimum number of bars that must pass before another alert of the same type can fire. Prevents alert spam when multiple patterns form in quick succession.
When To Change: Increase to 20+ on 1-minute charts to reduce noise. Decrease to 1-2 on daily charts if you want every pattern alerted.
Impact: Higher cooldown = fewer alerts. Lower cooldown = more alerts.
USER EXPERIENCE SECTION
Show Enhanced Tooltips
Default: ON
What It Does: Enables detailed hover-over tooltips on labels and visual elements.
When To Change: Turn OFF if you encounter Pine Script compilation errors related to tooltip arguments (rare, platform-specific issue).
Impact: Minimal. Just adds helpful hover text.
MARKET STRUCTURE DETECTION SECTION
Pivot Left Bars
Default: 3 | Range: 2-10
What It Does: Number of bars to the LEFT of the center bar that must be higher (for pivot low) or lower (for pivot high) than the center bar for a pivot to be valid.
Example: With value 3, a pivot low requires the center bar's low to be lower than the 3 bars to its left.
When To Change:
Increase to 5-7 on noisy timeframes (1-minute charts) to filter insignificant pivots
Decrease to 2 on slow timeframes (daily charts) to catch more pivots
Impact: Higher values = fewer, more significant pivots = fewer signals. Lower values = more frequent pivots = more signals but more noise.
Pivot Right Bars
Default: 3 | Range: 2-10
What It Does: Number of bars to the RIGHT of the center bar that must pass for confirmation. This creates the non-repainting delay.
Example: With value 3, a pivot is confirmed 3 bars AFTER it forms.
When To Change:
Increase to 5-7 for slower, more confirmed signals (better for swing trading)
Decrease to 2 for faster signals (better for intraday, but still non-repainting)
Impact: Higher values = longer delay but more reliable confirmation. Lower values = faster signals but less confirmation. This setting directly controls your signal delay in Confirmed and Relaxed modes.
Minimum Confluence Score
Default: 60 | Range: 40-95
What It Does: The threshold score required for a pattern to be displayed. Patterns with confluence scores below this threshold are not shown.
When To Change:
Increase to 75+ if you only want high-quality textbook setups (fewer signals)
Decrease to 50-55 if you want to see more developing patterns (more signals, lower average quality)
Impact: This is your primary signal filter. Higher threshold = fewer, higher-quality signals. Lower threshold = more signals but includes weaker setups. Recommended starting point is 60-65.
TECHNICAL PERIODS SECTION
RSI Period
Default: 14 | Range: 5-50
What It Does: Lookback period for RSI calculation.
When To Change:
Decrease to 9-10 for faster, more sensitive RSI that detects shorter-term momentum changes
Increase to 21-28 for slower, smoother RSI that filters noise
Impact: Lower values make RSI more volatile (more frequent extremes and divergences). Higher values make RSI smoother (fewer but more significant divergences). 14 is industry standard.
Volume Moving Average Period
Default: 20 | Range: 10-200
What It Does: Lookback period for calculating average volume. Current volume is compared to this average to determine volume ratio.
When To Change:
Decrease to 10-14 for shorter-term volume comparison (more sensitive to recent volume changes)
Increase to 50-100 for longer-term volume comparison (smoother, less sensitive)
Impact: Lower values make volume ratio more volatile. Higher values make it more stable. 20 is standard.
ATR Period
Default: 14 | Range: 5-100
What It Does: Lookback period for Average True Range calculation used for volatility measurement and label positioning.
When To Change: Rarely needs adjustment. Use 7-10 for faster volatility response, 21-28 for slower.
Impact: Affects volatility ratio calculation and visual label spacing. Minimal impact on signals.
Pressure Percentile Lookback
Default: 50 | Range: 10-300
What It Does: Lookback period for calculating volume pressure percentile ranking. Your current pressure is ranked against the pressure of the last X bars.
When To Change:
Decrease to 20-30 for shorter-term pressure context (more responsive to recent changes)
Increase to 100-200 for longer-term pressure context (smoother rankings)
Impact: Lower values make pressure strength more sensitive to recent bars. Higher values provide more stable, long-term pressure assessment. Capped at 300 for performance reasons.
SIGNAL DETECTION SECTION
Signal Detection Mode
Default: "Divergence + Confluence (Confirmed)"
Options:
Confluence Only (Real-time)
Divergence + Confluence (Confirmed)
Divergence + Confluence (Relaxed)
What It Does: Selects which detection logic mode to use (see "Understanding The Three Detection Modes" section above).
When To Change: Use Confirmed for learning and non-repainting signals. Use Real-time for live scanning without divergence requirement. Use Relaxed for slightly more signals than Confirmed.
Impact: Fundamentally changes when and how signals appear.
VISUAL LAYERS SECTION
All toggles default to ON. Each controls visibility of one visual layer:
Show Market Structure: Pivot markers and support/resistance lines
Show Pressure Zones: Background color shading
Show Divergence Lines: Dotted lines connecting pivots
Show Institutional Footprint Markers: Absorption boxes, hunt labels, exhaustion labels
Show Consolidated Analysis Label: Main pattern detection label
Use Compact Label Format
Default: OFF
What It Does: Switches consolidated label between single-line compact format and multi-line detailed format.
When To Change: Turn ON if you find full labels too large or distracting.
Impact: Visual clarity vs. information density tradeoff.
DASHBOARD SECTION
Dashboard Mode
Default: "Optimized"
Options: Off, Compact, Optimized, Full
What It Does: Controls how much information the dashboard displays.
Off: No dashboard
Compact: 8 rows (essential metrics only)
Optimized: 12 rows (recommended balance)
Full: 13 rows (every available metric)
Dashboard Position
Default: "Top Right"
Options: Top Right, Top Left, Bottom Right, Bottom Left
What It Does: Screen corner where dashboard appears.
HOW TO USE VMDM - PRACTICAL WORKFLOW
STEP 1 - INITIAL SETUP
Add VMDM to your chart
Select your detection mode (Confirmed recommended for learning)
Set your minimum confluence score (start with 60-65)
Adjust pivot parameters if needed (default 3/3 is good for most timeframes)
Enable the visual layers you want to see
STEP 2 - CHART ANALYSIS
Let the indicator load and analyze historical data
Review the patterns that appear historically
Examine the confluence scores - notice which patterns had higher scores
Observe which patterns occurred during supportive pressure zones
Notice the divergence line connections - understand what price vs RSI did
STEP 3 - PATTERN RECOGNITION LEARNING
When a consolidated analysis label appears:
Read the divergence type (regular or hidden, bullish or bearish)
Check the quality tier (textbook, high quality, or valid)
Review the confluence breakdown - which factors contributed
Look at the chart context - where is price relative to structure, trend, etc.
Observe the behavioral footprint markers nearby - do they support the pattern
STEP 4 - REAL-TIME MONITORING
Watch the dashboard for real-time regime and pressure state
Monitor the current confluence score in the dashboard
When it approaches your threshold, be alert for potential pattern formation
When a new pattern appears (after confirmation delay), evaluate it using the workflow above
Use your trading strategy rules to decide if the setup aligns with your criteria
STEP 5 - POST-PATTERN OBSERVATION
After a pattern appears:
Mark the level on your chart
Observe what price does after the pattern completes
Did price respect the reversal/continuation signal
What was the confluence score of patterns that worked vs. those that failed
Learn which quality tiers and confluence levels produce better results on your specific symbol and timeframe
RECOMMENDED TIMEFRAMES AND ASSET CLASSES
VMDM is timeframe-agnostic and works on any asset with volume data. However, optimal performance varies:
BEST TIMEFRAMES
15-Minute to 1-Hour: Ideal balance of signal frequency and reliability. Pivot confirmation delay is acceptable. Sufficient volume data for pressure analysis.
4-Hour to Daily: Excellent for swing trading. Very high-quality signals. Lower frequency but higher significance. Recommended for learning because patterns are clearer.
1-Minute to 5-Minute: Works but requires adjustment. Increase pivot bars to 5-7 for filtering. Decrease max object history to 30 for performance. Expect more noise.
Weekly/Monthly: Works but very infrequent signals. Increase confluence threshold to 70+ to ensure only major patterns appear.
BEST ASSET CLASSES
Forex Majors: Excellent volume data and clear trends. Pressure analysis works well.
Crypto (Major Pairs): Good volume data. High volatility makes divergences more pronounced. Works very well.
Stock Indices (SPY, QQQ, etc.): Excellent. Clean price action and reliable volume.
Individual Stocks: Works well on high-volume stocks. Low-volume stocks may produce unreliable pressure readings.
Commodities (Gold, Oil, etc.): Works well. Clear trends and reactions.
WHAT THIS INDICATOR CANNOT DO - LIMITATIONS
LIMITATION 1 - It Does Not Predict The Future
VMDM identifies when technical conditions align historically associated with potential reversals or continuations. It does not predict what will happen next. A textbook 95-confluence pattern can still fail if fundamental events, news, or larger timeframe structure override the setup.
LIMITATION 2 - Confirmation Delay Means You Miss Early Entry
In Confirmed and Relaxed modes, the non-repainting design means you receive signals AFTER the pivot is confirmed. Price may have already moved significantly by the time you receive the signal. This is the tradeoff for non-repainting reliability. You can use Real-time mode for faster signals but sacrifice divergence confirmation.
LIMITATION 3 - It Does Not Tell You Position Sizing or Risk Management
VMDM provides technical pattern analysis. It does not calculate stop loss levels, take profit targets, or position sizing. You must apply your own risk management rules. Never risk more than you can afford to lose based on a technical signal.
LIMITATION 4 - Volume Pressure Analysis Requires Reliable Volume Data
On assets with thin volume or unreliable volume reporting, pressure analysis may be inaccurate. Stick to major liquid assets with consistent volume data.
LIMITATION 5 - It Cannot Detect Fundamental Events
VMDM is purely technical. It cannot predict earnings reports, central bank decisions, geopolitical events, or other fundamental catalysts that can override technical patterns.
LIMITATION 6 - Divergence Requires Two Pivots
The indicator cannot detect divergence until at least two pivots of the same type have formed. In strong trends without pullbacks, you may go long periods without signals.
LIMITATION 7 - Institutional Pattern Names Are Interpretive
The behavioral footprint patterns are named using common trading education terminology, but they are detected through technical analysis, not actual institutional data access. The patterns are interpretations based on price and volume behavior.
CONCEPT FOUNDATION - WHY THIS APPROACH WORKS
MARKET PRINCIPLE 1 - Momentum Divergence Precedes Price Reversal
Price is the final output of market forces, but momentum (the rate of change in those forces) shifts first. When price makes a new low but the momentum behind that move is weaker (higher RSI low), it signals that sellers are losing strength even though they temporarily pushed price lower. This precedes reversal. This is a fundamental principle in technical analysis taught by Charles Dow, widely observed in market behavior.
MARKET PRINCIPLE 2 - Volume Reveals Conviction
Price can move on low volume (low conviction) or high volume (high conviction). When price makes a new low on declining volume while RSI shows improving momentum, it suggests the new low is not confirmed by participant conviction. Adding volume pressure analysis to momentum divergence adds a confirmation layer that filters false divergences.
MARKET PRINCIPLE 3 - Anomalies Mark Structural Extremes
When volume spikes significantly but range contracts (absorption), or when price spikes beyond structure then reverses (stop hunt), or when aggressive moves are met with large-wick rejection (exhaustion), these anomalies often mark short-term extremes. Combining these structural observations with momentum analysis creates context.
MARKET PRINCIPLE 4 - Confluence Improves Probability
No single technical factor is reliable in isolation. RSI divergence alone fails frequently. Volume analysis alone cannot time entries. Combining multiple independent factors into a weighted system increases the probability that observed patterns have structural significance rather than random noise.
THE EDUCATIONAL VALUE
By visualizing all four layers simultaneously and breaking down the confluence scoring transparently, VMDM teaches you to think in terms of multi-dimensional analysis rather than single-indicator reliance. Over time, you will learn to recognize these patterns manually and understand which combinations produce better results on your traded assets.
INSTITUTIONAL TERMINOLOGY - IMPORTANT CLARIFICATION
This indicator uses the following terms that are common in trading education:
Institutional Footprint
Absorption (Accumulation / Distribution)
Stop Hunt
Exhaustion
CRITICAL DISCLAIMER:
These terms are EDUCATIONAL LABELS for specific price action and volume behavior patterns detected through technical analysis of publicly available chart data (open, high, low, close, volume). This indicator does NOT have access to:
Actual institutional order flow or order book data
Market maker positions or intentions
Broker stop-loss databases
Non-public trading data
Proprietary institutional information
The patterns labeled as "institutional footprint" are interpretations based on observable price and volume behavior that educational trading literature often associates with potential large-participant activity. The detection is algorithmic pattern recognition, not privileged data access.
When this indicator identifies "absorption," it means it detected high volume within a small range - a condition that MAY indicate large orders being filled but is not confirmation of actual institutional participation.
When it identifies a "stop hunt," it means price briefly penetrated a structural level then reversed - a pattern that MAY have triggered stop losses but is not confirmation that stops were specifically targeted.
When it identifies "exhaustion," it means high volume with large rejection wicks - a pattern that MAY indicate aggressive participation meeting strong opposition but is not confirmation of institutional involvement.
These are technical analysis interpretations, not factual statements about market participant identity or intent.
DISCLAIMER AND RISK WARNING
EDUCATIONAL PURPOSE ONLY
This indicator is designed as an educational tool to help traders learn to recognize technical patterns, understand multi-factor analysis, and practice systematic market observation. It is NOT a trading system, signal service, or financial advice.
NO PERFORMANCE GUARANTEE
Past pattern behavior does not guarantee future results. A pattern that historically preceded price movement in one direction may fail in the future due to changing market conditions, fundamental events, or random variance. Confluence scores reflect historical technical alignment, not future certainty.
TRADING INVOLVES SUBSTANTIAL RISK
Trading financial instruments involves substantial risk of loss. You can lose more than your initial investment. Never trade with money you cannot afford to lose. Always use proper risk management including stop losses, position sizing, and portfolio diversification.
NO PREDICTIVE CLAIMS
This indicator does NOT predict future price movement. It identifies when technical conditions align in patterns that historically have been associated with potential reversals or continuations. Market behavior is probabilistic, not deterministic.
BACKTESTING LIMITATIONS
If you backtest trading strategies using this indicator, ensure you account for:
Realistic commission costs
Realistic slippage (difference between signal price and actual fill price)
Sufficient sample size (minimum 100 trades for statistical relevance)
Reasonable position sizing (risking no more than 1-2 percent of account per trade)
The confirmation delay inherent in the indicator (you cannot enter at the exact pivot in Confirmed mode)
Backtests that do not account for these factors will produce unrealistic results.
AUTHOR LIABILITY
The author (BullByte) is not responsible for any trading losses incurred using this indicator. By using this indicator, you acknowledge that all trading decisions are your sole responsibility and that you understand the risks involved.
NOT FINANCIAL ADVICE
Nothing in this indicator, its code, its description, or its visual outputs constitutes financial, investment, or trading advice. Consult a licensed financial advisor before making investment decisions.
FREQUENTLY ASKED QUESTIONS
Q: Why do signals appear in the past, not at the current bar
A: In Confirmed and Relaxed modes, signals appear at confirmed pivots, which requires waiting for right-side confirmation bars (default 3). This creates a delay but prevents repainting. Use Real-time mode if you want current-bar signals without pivot confirmation.
Q: Can I use this for automated trading
A: You can create alert-based automation, but understand that Confirmed mode signals appear AFTER the pivot with delay, so your entry will not be at the pivot price. Real-time mode signals can change as the current bar develops. Automation requires careful consideration of these factors.
Q: How do I know which confluence score to use
A: Start with 60. Observe which patterns work on your symbol/timeframe. If too many false signals, increase to 70-75. If too few signals, decrease to 55. Quality vs. quantity tradeoff.
Q: Do regular divergences mean I should enter a reversal trade immediately
A: No. Regular divergences indicate momentum exhaustion, which is a WARNING sign that trend may reverse, not a confirmation that it will. Use confluence score, market context, support/resistance, and your strategy rules to make entry decisions. Many divergences fail.
Q: What's the difference between regular and hidden divergence
A: Regular divergence = price and momentum move in opposite directions at extremes = potential reversal signal. Hidden divergence = price and momentum move in opposite directions during pullbacks = potential continuation signal. Hidden divergence suggests the pullback is just a correction within the larger trend.
Q: Why does the pressure zone color sometimes conflict with the divergence direction
A: Pressure is real-time current bar analysis. Divergence is confirmed pivot analysis from the past. They measure different things at different times. A bullish divergence confirmed 3 bars ago might appear during current selling pressure. This is normal.
Q: Can I use this on stocks without volume data
A: No. Volume is required for pressure analysis and behavioral pattern detection. Use only on assets with reliable volume reporting.
Q: How often should I expect signals
A: Depends on timeframe and settings. Daily charts might produce 5-10 signals per month. 1-hour charts might produce 20-30. 15-minute charts might produce 50-100. Adjust confluence threshold to control frequency.
Q: Can I modify the code
A: Yes, this is open source. You can modify for personal use. If you publish a modified version, please credit the original and ensure your publication meets TradingView guidelines.
Q: What if I disagree with a pattern's confluence score
A: The scoring weights are based on general observations and may not suit your specific strategy or asset. You can modify the code to adjust weights if you have data-driven reasons to do so.
Final Notes
VMDM - Volume, Momentum and Divergence Master is an educational multi-layer market analysis system designed to teach systematic pattern recognition through transparent, confluence-weighted signal detection. By combining RSI momentum divergence, volume pressure quantification, behavioral footprint pattern recognition, and quality scoring into a unified framework, it provides a comprehensive learning environment for understanding market structure.
Use this tool to develop your analytical skills, understand how multiple technical factors interact, and learn to distinguish high-quality setups from noise. Remember that technical analysis is probabilistic, not predictive. No indicator replaces proper education, risk management, and trading discipline.
Trade responsibly. Learn continuously. Risk only what you can afford to lose.
-BullByte
Dimensional Resonance ProtocolDimensional Resonance Protocol
🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION
The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states.
The Complexity Hypothesis:
Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics.
Takens' Embedding Theorem (1981):
A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation.
Mathematical Foundation:
From single observable x(t), create embedding vectors:
X(t) =
Where:
• d = Embedding dimension (default 5)
• τ = Time delay (default 3 bars)
• x(t) = Price or return at time t
Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series.
Why This Matters:
Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect:
• Stable regions : Predictable behavior (trade opportunities)
• Chaotic regions : Unpredictable behavior (avoid trading)
• Critical transitions : Phase changes between regimes
Phase Space Magnitude Calculation:
phase_magnitude = sqrt(Σ ² for i = 0 to d-1)
This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation.
📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA)
Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states?
Recurrence Plot Foundation:
A recurrence occurs when two phase space points are closer than threshold ε:
R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0
This creates a binary matrix showing when the system revisits similar states.
Key RQA Metrics:
1. Recurrence Rate (RR):
RR = (Number of recurrent points) / (Total possible pairs)
• RR near 0: System never repeats (highly stochastic)
• RR = 0.1-0.3: Moderate recurrence (tradeable patterns)
• RR > 0.5: System stuck in attractor (ranging market)
• RR near 1: System frozen (no dynamics)
Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck.
2. Determinism (DET):
Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths).
DET = (Recurrence points on diagonals) / (Total recurrence points)
• DET < 0.3: Random dynamics
• DET = 0.3-0.7: Moderate determinism (patterns with noise)
• DET > 0.7: Strong determinism (technical patterns reliable)
Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck).
Threshold Selection (ε):
Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns.
🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT
Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns.
Algorithm (Bandt & Pompe, 2002):
1. Take overlapping windows of length n (default n=4)
2. For each window, record the rank order pattern
Example: → pattern (ranks from lowest to highest)
3. Count frequency of each possible pattern
4. Calculate Shannon entropy of pattern distribution
Mathematical Formula:
H_perm = -Σ p(π) · ln(p(π))
Where π ranges over all n! possible permutations, p(π) is the probability of pattern π.
Normalized to :
H_norm = H_perm / ln(n!)
Interpretation:
• H < 0.3 : Very ordered, crystalline structure (strong trending)
• H = 0.3-0.5 : Ordered regime (tradeable with patterns)
• H = 0.5-0.7 : Moderate complexity (mixed conditions)
• H = 0.7-0.85 : Complex dynamics (challenging to trade)
• H > 0.85 : Maximum entropy (nearly random, avoid)
Entropy Regime Classification:
DRP classifies markets into five entropy regimes:
• CRYSTALLINE (H < 0.3): Maximum order, persistent trends
• ORDERED (H < 0.5): Clear patterns, momentum strategies work
• MODERATE (H < 0.7): Mixed dynamics, adaptive required
• COMPLEX (H < 0.85): High entropy, mean reversion better
• CHAOTIC (H ≥ 0.85): Near-random, minimize trading
Why Permutation Entropy?
Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy:
• Works directly on time series
• Robust to monotonic transformations
• Computationally efficient
• Captures temporal structure, not just distribution
• Immune to outliers (uses ranks, not values)
⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY
The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos.
Physical Meaning:
Two trajectories starting infinitely close will diverge at exponential rate e^(λt):
Distance(t) ≈ Distance(0) × e^(λt)
Interpretation:
• λ > 0 : Positive Lyapunov exponent = CHAOS
- Small errors grow exponentially
- Long-term prediction impossible
- System is sensitive, unpredictable
- AVOID TRADING
• λ ≈ 0 : Near-zero = CRITICAL STATE
- Edge of chaos
- Transition zone between order and disorder
- Moderate predictability
- PROCEED WITH CAUTION
• λ < 0 : Negative Lyapunov exponent = STABLE
- Small errors decay
- Trajectories converge
- System is predictable
- OPTIMAL FOR TRADING
Estimation Method:
DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars):
For each bar i in window:
δ₀ = |x - x | (initial separation)
δ₁ = |x - x | (previous separation)
if δ₁ > 0:
ratio = δ₀ / δ₁
log_ratios += ln(ratio)
λ ≈ average(log_ratios)
Stability Classification:
• STABLE : λ < 0 (negative growth rate)
• CRITICAL : |λ| < 0.1 (near neutral)
• CHAOTIC : λ > 0.2 (strong positive growth)
Signal Filtering:
By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down.
📐 HIGUCHI FRACTAL DIMENSION
Fractal dimension measures self-similarity and complexity of the price trajectory.
Theoretical Background:
A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve):
• D ≈ 1.0 : Smooth, persistent trending
• D ≈ 1.5 : Random walk (Brownian motion)
• D ≈ 2.0 : Highly irregular, space-filling
Higuchi Method (1988):
For a time series of length N, construct k different curves by taking every k-th point:
L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k)
For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k):
D = slope of log(L) vs log(1/k)
Market Interpretation:
• D < 1.35 : Strong trending, persistent (Hurst > 0.5)
- TRENDING regime
- Momentum strategies favored
- Breakouts likely to continue
• D = 1.35-1.45 : Moderate persistence
- PERSISTENT regime
- Trend-following with caution
- Patterns have meaning
• D = 1.45-1.55 : Random walk territory
- RANDOM regime
- Efficiency hypothesis holds
- Technical analysis least reliable
• D = 1.55-1.65 : Anti-persistent (mean-reverting)
- ANTI-PERSISTENT regime
- Oscillator strategies work
- Overbought/oversold meaningful
• D > 1.65 : Highly complex, choppy
- COMPLEX regime
- Avoid directional bets
- Wait for regime change
Signal Filtering:
Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning.
🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW
Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer.
Schreiber's Definition (2000):
Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future:
TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past)
Where H is Shannon entropy.
Key Properties:
1. Directional : TE(X→Y) ≠ TE(Y→X) in general
2. Non-linear : Detects complex causal relationships
3. Model-free : No assumptions about functional form
4. Lag-independent : Captures delayed causal effects
Three Causal Flows Measured:
1. Volume → Price (TE_V→P):
Measures how much volume patterns predict price changes.
• TE > 0 : Volume provides predictive information about price
- Institutional participation driving moves
- Volume confirms direction
- High reliability
• TE ≈ 0 : No causal flow (weak volume/price relationship)
- Volume uninformative
- Caution on signals
• TE < 0 (rare): Suggests price leading volume
- Potentially manipulated or thin market
2. Volatility → Momentum (TE_σ→M):
Does volatility expansion predict momentum changes?
• Positive TE : Volatility precedes momentum shifts
- Breakout dynamics
- Regime transitions
3. Structure → Price (TE_S→P):
Do support/resistance patterns causally influence price?
• Positive TE : Structural levels have causal impact
- Technical levels matter
- Market respects structure
Net Causal Flow:
Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P
• Net > +0.1 : Bullish causal structure
• Net < -0.1 : Bearish causal structure
• |Net| < 0.1 : Neutral/unclear causation
Causal Gate:
For signal confirmation, NEXUS requires:
• Buy signals : TE_V→P > 0 AND Net_Flow > 0.05
• Sell signals : TE_V→P > 0 AND Net_Flow < -0.05
This ensures volume is actually driving price (causal support exists), not just correlated noise.
Implementation Note:
Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner.
🌊 HILBERT PHASE COHERENCE
Phase coherence measures synchronization across market dimensions using Hilbert transform analysis.
Hilbert Transform Theory:
For a signal x(t), the Hilbert transform H (t) creates an analytic signal:
z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t))
Where:
• A(t) = Instantaneous amplitude
• φ(t) = Instantaneous phase
Instantaneous Phase:
φ(t) = arctan(H (t) / x(t))
The phase represents where the signal is in its natural cycle—analogous to position on a unit circle.
Four Dimensions Analyzed:
1. Momentum Phase : Phase of price rate-of-change
2. Volume Phase : Phase of volume intensity
3. Volatility Phase : Phase of ATR cycles
4. Structure Phase : Phase of position within range
Phase Locking Value (PLV):
For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization:
PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩|
Where ⟨·⟩ is time average over window.
Interpretation:
• PLV = 0 : Completely random phase relationship (no synchronization)
• PLV = 0.5 : Moderate phase locking
• PLV = 1 : Perfect synchronization (phases locked)
Pairwise PLV Calculations:
• PLV_momentum-volume : Are momentum and volume cycles synchronized?
• PLV_momentum-structure : Are momentum cycles aligned with structure?
• PLV_volume-structure : Are volume and structural patterns in phase?
Overall Phase Coherence:
Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3
Signal Confirmation:
Emergence signals require coherence ≥ threshold (default 0.70):
• Below 0.70: Dimensions not synchronized, no coherent market state
• Above 0.70: Dimensions in phase, coherent behavior emerging
Coherence Direction:
The summed phase angles indicate whether synchronized dimensions point bullish or bearish:
Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure)
• Direction > 0 : Phases pointing upward (bullish synchronization)
• Direction < 0 : Phases pointing downward (bearish synchronization)
🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT
The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence.
Eight Components with Weights:
1. Phase Coherence (20%):
Direct contribution: coherence × 0.20
Measures dimensional synchronization.
2. Entropy Regime (15%):
Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0
Rewards low entropy (ordered, predictable states).
3. Lyapunov Stability (12%):
• λ < 0 (stable): +0.12
• |λ| < 0.1 (critical): +0.08
• λ > 0.2 (chaotic): +0.0
Requires stable, predictable dynamics.
4. Fractal Dimension Trending (12%):
Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0
Rewards trending fractal structure (D < 1.45).
5. Dimensional Resonance (12%):
Contribution: |dimensional_resonance| × 0.12
Measures alignment across momentum, volume, structure, volatility dimensions.
6. Causal Flow Strength (9%):
Contribution: |net_causal_flow| × 0.09
Rewards strong causal relationships.
7. Phase Space Embedding (10%):
Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0
Rewards strong trajectory in reconstructed phase space.
8. Recurrence Quality (10%):
Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8
Rewards deterministic patterns with moderate recurrence.
Total Emergence Score:
E = Σ(components) ∈
Capped at 1.0 maximum.
Emergence Direction:
Separate calculation determining bullish vs bearish:
• Dimensional resonance sign
• Net causal flow sign
• Phase magnitude correlation with momentum
Signal Threshold:
Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals.
Why Emergence Matters:
Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order.
These are the highest-probability trade opportunities because the entire system is resonating in the same direction.
🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE
DRP generates two tiers of signals with different requirements:
TIER 1: EMERGENCE SIGNALS (Primary)
Requirements:
1. Emergence score ≥ threshold (default 0.75)
2. Phase coherence ≥ threshold (default 0.70)
3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish)
4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction
5. Stability zone (if enabled): λ < 0 or |λ| < 0.1
6. Price confirmation: Close > open (bulls) or close < open (bears)
7. Cooldown satisfied: bars_since_signal ≥ cooldown_period
EMERGENCE BUY:
• All above conditions met with bullish direction
• Market has achieved coherent bullish state
• Multiple dimensions synchronized upward
EMERGENCE SELL:
• All above conditions met with bearish direction
• Market has achieved coherent bearish state
• Multiple dimensions synchronized downward
Premium Emergence:
When signal_quality (emergence_score × phase_coherence) > 0.7:
• Displayed as ★ star symbol
• Highest conviction trades
• Maximum dimensional alignment
Standard Emergence:
When signal_quality 0.5-0.7:
• Displayed as ◆ diamond symbol
• Strong signals but not perfect alignment
TIER 2: RESONANCE SIGNALS (Secondary)
Requirements:
1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish)
2. Fractal dimension < 1.5 (trending/persistent regime)
3. Price confirmation matches direction
4. NOT in chaotic regime (λ < 0.2)
5. Cooldown satisfied
6. NO emergence signal firing (resonance is fallback)
RESONANCE BUY:
• Dimensional alignment without full emergence
• Trending fractal structure
• Moderate conviction
RESONANCE SELL:
• Dimensional alignment without full emergence
• Bearish resonance with trending structure
• Moderate conviction
Displayed as small ▲/▼ triangles with transparency.
Signal Hierarchy:
IF emergence conditions met:
Fire EMERGENCE signal (★ or ◆)
ELSE IF resonance conditions met:
Fire RESONANCE signal (▲ or ▼)
ELSE:
No signal
Cooldown System:
After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions.
Cooldown tracks using bar_index:
bars_since_signal = current_bar_index - last_signal_bar_index
cooldown_ok = bars_since_signal >= cooldown_period
🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY
DRP provides rich visual feedback across four distinct layers:
LAYER 1: COHERENCE FIELD (Background)
Colored background intensity based on phase coherence:
• No background : Coherence < 0.5 (incoherent state)
• Faint glow : Coherence 0.5-0.7 (building coherence)
• Stronger glow : Coherence > 0.7 (coherent state)
Color:
• Cyan/teal: Bullish coherence (direction > 0)
• Red/magenta: Bearish coherence (direction < 0)
• Blue: Neutral coherence (direction ≈ 0)
Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible.
LAYER 2: STABILITY/CHAOS ZONES
Background color indicating Lyapunov regime:
• Green tint (95% transparent): λ < 0, STABLE zone
- Safe to trade
- Patterns meaningful
• Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone
- Edge of chaos
- Moderate risk
• Red tint (85% transparent): λ > 0.2, CHAOTIC zone
- Avoid trading
- Unpredictable behavior
LAYER 3: DIMENSIONAL RIBBONS
Three EMAs representing dimensional structure:
• Fast ribbon : EMA(8) in cyan/teal (fast dynamics)
• Medium ribbon : EMA(21) in blue (intermediate)
• Slow ribbon : EMA(55) in red/magenta (slow dynamics)
Provides visual reference for multi-scale structure without cluttering with raw phase space data.
LAYER 4: CAUSAL FLOW LINE
A thicker line plotted at EMA(13) colored by net causal flow:
• Cyan/teal : Net_flow > +0.1 (bullish causation)
• Red/magenta : Net_flow < -0.1 (bearish causation)
• Gray : |Net_flow| < 0.1 (neutral causation)
Shows real-time direction of information flow.
EMERGENCE FLASH:
Strong background flash when emergence signals fire:
• Cyan flash for emergence buy
• Red flash for emergence sell
• 80% transparency for visibility without obscuring price
📊 COMPREHENSIVE DASHBOARD
Real-time monitoring of all complexity metrics:
HEADER:
• 🌀 DRP branding with gold accent
CORE METRICS:
EMERGENCE:
• Progress bar (█ filled, ░ empty) showing 0-100%
• Percentage value
• Direction arrow (↗ bull, ↘ bear, → neutral)
• Color-coded: Green/gold if active, gray if low
COHERENCE:
• Progress bar showing phase locking value
• Percentage value
• Checkmark ✓ if ≥ threshold, circle ○ if below
• Color-coded: Cyan if coherent, gray if not
COMPLEXITY SECTION:
ENTROPY:
• Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC)
• Numerical value (0.00-1.00)
• Color: Green (ordered), gold (moderate), red (chaotic)
LYAPUNOV:
• State (STABLE/CRITICAL/CHAOTIC)
• Numerical value (typically -0.5 to +0.5)
• Status indicator: ● stable, ◐ critical, ○ chaotic
• Color-coded by state
FRACTAL:
• Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX)
• Dimension value (1.0-2.0)
• Color: Cyan (trending), gold (random), red (complex)
PHASE-SPACE:
• State (STRONG/ACTIVE/QUIET)
• Normalized magnitude value
• Parameters display: d=5 τ=3
CAUSAL SECTION:
CAUSAL:
• Direction (BULL/BEAR/NEUTRAL)
• Net flow value
• Flow indicator: →P (to price), P← (from price), ○ (neutral)
V→P:
• Volume-to-price transfer entropy
• Small display showing specific TE value
DIMENSIONAL SECTION:
RESONANCE:
• Progress bar of absolute resonance
• Signed value (-1 to +1)
• Color-coded by direction
RECURRENCE:
• Recurrence rate percentage
• Determinism percentage display
• Color-coded: Green if high quality
STATE SECTION:
STATE:
• Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING
• Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning)
• Color-coded by state
SIGNALS:
• E: count of emergence signals
• R: count of resonance signals
⚙️ KEY PARAMETERS EXPLAINED
Phase Space Configuration:
• Embedding Dimension (3-10, default 5): Reconstruction dimension
- Low (3-4): Simple dynamics, faster computation
- Medium (5-6): Balanced (recommended)
- High (7-10): Complex dynamics, more data needed
- Rule: d ≥ 2D+1 where D is true dimension
• Time Delay (τ) (1-10, default 3): Embedding lag
- Fast markets: 1-2
- Normal: 3-4
- Slow markets: 5-10
- Optimal: First minimum of mutual information (often 2-4)
• Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity
- Tight (0.01-0.05): Very similar states only
- Medium (0.08-0.15): Balanced
- Loose (0.20-0.50): Liberal matching
Entropy & Complexity:
• Permutation Order (3-7, default 4): Pattern length
- Low (3): 6 patterns, fast but coarse
- Medium (4-5): 24-120 patterns, balanced
- High (6-7): 720-5040 patterns, fine-grained
- Note: Requires window >> order! for stability
• Entropy Window (15-100, default 30): Lookback for entropy
- Short (15-25): Responsive to changes
- Medium (30-50): Stable measure
- Long (60-100): Very smooth, slow adaptation
• Lyapunov Window (10-50, default 20): Stability estimation window
- Short (10-15): Fast chaos detection
- Medium (20-30): Balanced
- Long (40-50): Stable λ estimate
Causal Inference:
• Enable Transfer Entropy (default ON): Causality analysis
- Keep ON for full system functionality
• TE History Length (2-15, default 5): Causal lookback
- Short (2-4): Quick causal detection
- Medium (5-8): Balanced
- Long (10-15): Deep causal analysis
• TE Discretization Bins (4-12, default 6): Binning granularity
- Few (4-5): Coarse, robust, needs less data
- Medium (6-8): Balanced
- Many (9-12): Fine-grained, needs more data
Phase Coherence:
• Enable Phase Coherence (default ON): Synchronization detection
- Keep ON for emergence detection
• Coherence Threshold (0.3-0.95, default 0.70): PLV requirement
- Loose (0.3-0.5): More signals, lower quality
- Balanced (0.6-0.75): Recommended
- Strict (0.8-0.95): Rare, highest quality
• Hilbert Smoothing (3-20, default 8): Phase smoothing
- Low (3-5): Responsive, noisier
- Medium (6-10): Balanced
- High (12-20): Smooth, more lag
Fractal Analysis:
• Enable Fractal Dimension (default ON): Complexity measurement
- Keep ON for full analysis
• Fractal K-max (4-20, default 8): Scaling range
- Low (4-6): Faster, less accurate
- Medium (7-10): Balanced
- High (12-20): Accurate, slower
• Fractal Window (30-200, default 50): FD lookback
- Short (30-50): Responsive FD
- Medium (60-100): Stable FD
- Long (120-200): Very smooth FD
Emergence Detection:
• Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence
- Sensitive (0.5-0.65): More signals
- Balanced (0.7-0.8): Recommended
- Strict (0.85-0.95): Rare signals
• Require Causal Gate (default ON): TE confirmation
- ON: Only signal when causality confirms
- OFF: Allow signals without causal support
• Require Stability Zone (default ON): Lyapunov filter
- ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical)
- OFF: Allow signals in chaotic regimes (risky)
• Signal Cooldown (1-50, default 5): Minimum bars between signals
- Fast (1-3): Rapid signal generation
- Normal (4-8): Balanced
- Slow (10-20): Very selective
- Ultra (25-50): Only major regime changes
Signal Configuration:
• Momentum Period (5-50, default 14): ROC calculation
• Structure Lookback (10-100, default 20): Support/resistance range
• Volatility Period (5-50, default 14): ATR calculation
• Volume MA Period (10-50, default 20): Volume normalization
Visual Settings:
• Customizable color scheme for all elements
• Toggle visibility for each layer independently
• Dashboard position (4 corners) and size (tiny/small/normal)
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: System Familiarization (Week 1)
Goal: Understand complexity metrics and dashboard interpretation
Setup:
• Enable all features with default parameters
• Watch dashboard metrics for 500+ bars
• Do NOT trade yet
Actions:
• Observe emergence score patterns relative to price moves
• Note coherence threshold crossings and subsequent price action
• Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC)
• Correlate Lyapunov state with signal reliability
• Track which signals appear (emergence vs resonance frequency)
Key Learning:
• When does emergence peak? (usually before major moves)
• What entropy regime produces best signals? (typically ORDERED or MODERATE)
• Does your instrument respect stability zones? (stable λ = better signals)
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to instrument characteristics
Requirements:
• Understand basic dashboard metrics from Phase 1
• Have 1000+ bars of history loaded
Embedding Dimension & Time Delay:
• If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2)
• If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5)
• Sweet spot: 4-8 emergence signals per 100 bars
Coherence Threshold:
• Check dashboard: What's typical coherence range?
• If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65
• If coherence often >0.80: Can raise threshold to 0.75-0.80
• Goal: Signals fire during top 20-30% of coherence values
Emergence Threshold:
• If too few signals: Lower to 0.65-0.70
• If too many signals: Raise to 0.80-0.85
• Balance with coherence threshold—both must be met
Phase 3: Signal Quality Assessment (Weeks 3-4)
Goal: Verify signals have edge via paper trading
Requirements:
• Parameters optimized per Phase 2
• 50+ signals generated
• Detailed notes on each signal
Paper Trading Protocol:
• Take EVERY emergence signal (★ and ◆)
• Optional: Take resonance signals (▲/▼) separately to compare
• Use simple exit: 2R target, 1R stop (ATR-based)
• Track: Win rate, average R-multiple, maximum consecutive losses
Quality Metrics:
• Premium emergence (★) : Should achieve >55% WR
• Standard emergence (◆) : Should achieve >50% WR
• Resonance signals : Should achieve >45% WR
• Overall : If <45% WR, system not suitable for this instrument/timeframe
Red Flags:
• Win rate <40%: Wrong instrument or parameters need major adjustment
• Max consecutive losses >10: System not working in current regime
• Profit factor <1.0: No edge despite complexity analysis
Phase 4: Regime Awareness (Week 5)
Goal: Understand which market conditions produce best signals
Analysis:
• Review Phase 3 trades, segment by:
- Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC)
- Lyapunov state (STABLE vs CRITICAL vs CHAOTIC)
- Fractal regime (TRENDING vs RANDOM vs COMPLEX)
Findings (typical patterns):
• Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal
• Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal
• Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these)
Optimization:
• If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70
• If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic
• If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate with minimal capital at risk
Requirements:
• Paper trading shows: WR >48%, PF >1.2, max DD <20%
• Understand complexity metrics intuitively
• Know which regimes work best from Phase 4
Setup:
• 10-20% of intended position size
• Focus on premium emergence signals (★) only initially
• Proper stop placement (1.5-2.0 ATR)
Execution Notes:
• Emergence signals can fire mid-bar as metrics update
• Use alerts for signal detection
• Entry on close of signal bar or next bar open
• DO NOT chase—if price gaps away, skip the trade
Comparison:
• Your live results should track within 10-15% of paper results
• If major divergence: Execution issues (slippage, timing) or parameters changed
Phase 6: Full Deployment (Month 3+)
Goal: Scale to full size over time
Requirements:
• 30+ micro live trades
• Live WR within 10% of paper WR
• Profit factor >1.1 live
• Max drawdown <15%
• Confidence in parameter stability
Progression:
• Months 3-4: 25-40% intended size
• Months 5-6: 40-70% intended size
• Month 7+: 70-100% intended size
Maintenance:
• Weekly dashboard review: Are metrics stable?
• Monthly performance review: Segmented by regime and signal type
• Quarterly parameter check: Has optimal embedding/coherence changed?
Advanced:
• Consider different parameters per session (high vs low volatility)
• Track phase space magnitude patterns before major moves
• Combine with other indicators for confluence
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Phase Space Revelation:
Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D.
The Permutation Entropy Discovery:
Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering.
The Lyapunov Filter Breakthrough:
Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself.
The Transfer Entropy Challenge:
Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters.
The Phase Coherence Insight:
Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason.
The Eight-Component Emergence Formula:
Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it.
The Cooldown Necessity:
Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude.
• NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty.
• NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data.
• NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections.
• NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off.
Core Assumptions:
1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly).
2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong.
3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise).
4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets).
5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive).
6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT).
Performs Best On:
• ES, NQ, RTY (major US index futures - high liquidity, clean volume data)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis)
• Liquid commodities: CL (crude oil), GC (gold), NG (natural gas)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure)
• Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis
• Exotic forex pairs - erratic spreads, thin volume
• Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis
• Pre-market/after-hours - gappy, thin, different dynamics
• Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions
• Highly manipulated instruments - spoofing and layering create false coherence
Known Weaknesses:
• Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed.
• Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument.
• Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable.
• Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive.
• False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through.
• Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this.
• Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless.
Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals.
Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size.
The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it.
Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe.
The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic.
Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations.
Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
📁 DOCUMENTATION
The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research:
Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory.
Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics.
Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data.
Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions.
Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales.
Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory.
The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?).
This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor.
Multiple oscillator-type calculations contribute to dimensional analysis:
Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection.
Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized.
Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed.
Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional.
The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states.
While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space.
Volatility analysis permeates the system:
ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score.
Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility).
Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory.
Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable.
Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions.
The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator.
CLOSING STATEMENT
DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence .
This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity.
When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance .
These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state.
Most indicators see shadows on the wall. DRP reconstructs the cave.
"In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
QTrade Golden, Bronze & Death, Bubonic Cross AlertsThis indicator highlights key EMA regime shifts with simple, color-coded triangles:
- Golden / Death Cross — 50 EMA crossing above/below the 200 EMA.
- Bronze / Bubonic Cross — 50 EMA crossing above/below the 100 EMA.
- Early-Warning Proxy — tiny triangles for the 4 EMA vs. 200 EMA (4↑200 and 4↓200). These often fire before the 50/100 and 50/200 crosses.
No text clutter on the chart—just triangles. Colors: gold (50↑200), red (50↓200), darker-yellow bronze (50↑100), burgundy (50↓100), turquoise (4↑200), purple (4↓200).
What it tells you (in order of warning → confirmation)
- First warning: 4 EMA crosses the 200 EMA (proxy for price shifting around the 200 line).
- Second warning: 50 EMA crosses the 100 EMA (Bronze/Bubonic).
- Confirmation: 50 EMA crosses the 200 EMA (Golden/Death).
Alerts included
- Golden Cross (50↑200) and Death Cross (50↓200)
- Bronze Cross (50↑100) and Bubonic Cross (50↓100)
- 4 EMA vs. 200 EMA crosses (up & down) — early-warning proxy
- Price–100 EMA events (touch/cross, if enabled in settings)
