Hybrid -WinCAlgo/// 🇬🇧
Hybrid - WinCAlgo is a weighted composite oscillator designed to provide a more robust and reliable signal than the standard Relative Strength Index (RSI). It integrates four different momentum and volume metrics—RSI, Money Flow Index (MFI), Scaled CCI, and VWAP-RSI—into a single 0-100 oscillator.
This powerful tool aims to filter market noise and enhance the detection of trend reversals by confirming momentum with trading volume and volume-weighted average price action.
⚪ What is this Indicator?
The Hybrid Oscillator combines:
* RSI (40% Weight): Measures fundamental price momentum.
* VWAP-RSI (40% Weight): Measures the momentum of the Volume Weighted Average Price (VWAP), providing strong volume confirmation for trend strength.
* MFI (10% Weight): Measures money flow volume, confirming momentum with liquidity.
* Scaled CCI (10% Weight): Tracks market extremes and potential trend shifts, scaled to fit the 0-100 range.
⚪ Key Features
* Composite Strength: Blends four different market factors for a multi-dimensional view of momentum.
* Volume Integration: High weights on VWAP-RSI and MFI ensure that momentum signals are backed by trading volume.
* Advanced Divergence: The robust formula significantly enhances the detection of Bullish and Bearish Divergences, often providing an earlier signal than traditional oscillators.
* Customizable: Adjustable Lookback Length (N) and Individual Component Weights allow users to fine-tune the oscillator for specific assets or timeframes.
* Visual Clarity: Uses 40/60 bands for earlier Overbought/Oversold indications, with a gradient-styled background for intuitive visual interpretation.
⚪ Usage
Use Hybrid – WinCAlgo as your primary momentum confirmation tool:
* Divergence Signals: Trust the indicator when it fails to confirm new price highs/lows; this signals imminent trend exhaustion and reversal.
* Accumulation/Distribution: Look for the oscillator to rise/fall while the price is ranging at a bottom/top; this confirms hidden buying or selling (accumulation).
* Overbought/Oversold: Use the 60 band as the trigger for potential selling/shorting signals, and the 40 band for potential buying/longing signals.
* Noise Filter: Combine with a higher timeframe chart (e.g., 4H or Daily) to filter out gürültü (noise) and focus only on significant momentum shifts.
---
Tìm kiếm tập lệnh với "CCI"
Delta Zones Smart Money Concept (SMC) UT Trend Reversal Mul.Sig.🚀 What's New in This Version (V5 Update)
This version is a major overhaul focused on improving trade entry timing and risk management through enhanced UT Bot functionality:
Integrated UT Trailing Stop (ATR-based): The primary trend filter and moving stop-loss mechanism is now fully integrated.
Pre-Warning Line: A revolutionary feature that alerts traders when the price penetrates a specific percentage distance (customizable) from the UT Trailing Stop before the main reversal signal fires.
"Ready" Signal: Plots a "Ready" warning label on the chart and triggers an alert condition (UT Ready Long/Short) for pre-emptive trade preparation.
V5 Compatibility: All code has been optimized for Pine Script version 5, utilizing the modern array and type structures for efficient Order Block and Breaker Block detection.
💡 How to Use This Indicator
This indicator works best when confirming signals across different components:
1. Identify the Trend Bias (UT Trailing Stop)
Uptrend: UT Trailing Stop line is Green (Focus only on Buy/Long opportunities).
Downtrend: UT Trailing Stop line is Red (Focus only on Sell/Short opportunities).
2. Prepare for Entry (Warning Line)
Action: When you see the "Ready" label or the price hits the Pre-Warning Line (Dotted Orange Line), this is your alert to prepare for a trend flip, or to tighten the stop on your current trade.
3. Confirm the Entry (Multi-Signals)
Look for a primary entry signal that aligns with the desired trend:
High-Conviction Entry: Wait for the UT Buy/Sell label (confirmed trend flip) AND a Combined Buy/Sell arrow (confirmed by your selected Oscillator settings).
High-Liquidity Entry: Look for a Delta Zone Box forming near an active Order Block or Breaker Block (SMC zones), and then confirm with a UT or Combined Signal.
4. Manage Risk (Trailing Stop)
Always set your initial Stop Loss (SL) either just outside the opposite Order Block or at the UT Trailing Stop level itself.
If the price closes back across the UT Trailing Stop, exit your position immediately, as the trend bias has officially shifted.
Features & Components
1. Delta Zones (Liquidity/Wick Pressure)
Identifies periods of extreme buying or selling pressure based on wick-to-body ratios and standard deviation analysis.
Plots colored pressure boxes (Buy/Sell) to highlight potential exhaustion points or institutional activity.
2. Smart Money Concepts (SMC)
Automatically detects and plots Order Blocks (OBs) and Breaker Blocks (BBs) based on confirmed Market Structure Breaks (MSBs).
Includes Chop Control logic to remove less reliable Breaker Blocks.
3. UT Bot Trailing Stop & Warning Line
UT Trailing Stop (ATR-based): Plots a dynamic trend line (Green/Red) that acts as a moving stop-loss and primary trend filter.
Ready/Warning Signals: Alerts traders (via the "Ready" label and orange lines) when the price enters a "Pre-Reversal Zone" near the Trailing Stop.
4. Multi-Indicator Confirmation (Filters)
Includes customizable signals based on the crossover/crossunder of RSI, CCI, and Stochastic indicators against configurable Overbought/Oversold levels.
Allows selection of combination signals (e.g., RSI & CCI, All Combined, etc.) for high-conviction entries.
Scout Regiment - MACD# Scout Regiment - MACD Indicator
## English Documentation
### Overview
Scout Regiment - MACD is an advanced implementation of the Moving Average Convergence Divergence indicator with enhanced features including dual divergence detection (histogram and MACD line), customizable moving average types, multi-timeframe analysis, and sophisticated visual elements. This indicator provides traders with comprehensive momentum analysis and high-probability reversal signals.
### What is MACD?
MACD (Moving Average Convergence Divergence) is a trend-following momentum indicator that shows the relationship between two moving averages:
- **MACD Line**: Difference between fast and slow EMAs
- **Signal Line**: Moving average of the MACD line
- **Histogram**: Difference between MACD line and signal line
- **Purpose**: Identifies trend direction, momentum strength, and potential reversals
### Key Features
#### 1. **Enhanced MACD Display**
**Three Core Components:**
**MACD Line** (Default: Blue/Orange, 2px)
- Fast EMA (13) minus Slow EMA (34)
- Shows momentum direction
- Color changes based on position relative to signal line:
- Blue: Above signal line (bullish)
- Orange: Below signal line (bearish)
- Can be toggled on/off
**Signal Line** (Default: White/Blue with transparency, 2px)
- EMA (9) of the MACD line
- Serves as trigger line for crossover signals
- Color varies based on settings
- Essential for identifying entry/exit points
**Histogram** (Default: 4-color gradient, 4px columns)
- Difference between MACD and signal line
- Visual representation of momentum strength
- Advanced 4-color scheme:
- **Dark Green (#26A69A)**: Positive and increasing (strong bullish)
- **Light Green (#B2DFDB)**: Positive but decreasing (weakening bullish)
- **Dark Red (#FF5252)**: Negative and decreasing (strong bearish)
- **Light Red (#FFCDD2)**: Negative but increasing (weakening bearish)
- Histogram tells the "story" of momentum changes
#### 2. **Customizable Moving Average Types**
**Oscillator MA Type** (MACD Line calculation):
- **EMA** (Exponential) - Default, more responsive
- **SMA** (Simple) - Smoother, less responsive
**Signal Line MA Type**:
- **EMA** (Exponential) - Default, faster signals
- **SMA** (Simple) - Slower, fewer false signals
**Flexibility**: Mix and match for different trading styles
- EMA/EMA: Most responsive (day trading)
- SMA/SMA: Smoothest (swing trading)
- EMA/SMA or SMA/EMA: Balanced approaches
#### 3. **Multi-Timeframe Capability**
**Current Chart Period** (Default: Enabled)
- Uses current timeframe automatically
- Simplest option for most traders
**Custom Timeframe Selection**
- Calculate MACD on any timeframe
- Display higher timeframe MACD on lower timeframe charts
- Example: View 1H MACD on 15min chart
- **Use Case**: Align lower timeframe trades with higher timeframe momentum
#### 4. **Visual Enhancement Features**
**Golden Cross / Death Cross Markers**
- Circles mark crossover points
- Color matches MACD line color
- Clearly identifies entry/exit signals
- Can be toggled on/off
**Zero Line** (White, 2px solid)
- Reference for positive/negative momentum
- Critical level for trend identification
- MACD above zero = Bullish bias
- MACD below zero = Bearish bias
**Color Transitions**
- MACD line changes color at signal line crosses
- Histogram shows momentum acceleration/deceleration
- Provides early warning of trend changes
#### 5. **Dual Divergence Detection System**
This indicator features TWO separate divergence detection systems:
**A. Histogram Divergence Detection**
- **Purpose**: Earlier divergence signals (most sensitive)
- **Detects**: Regular bullish and bearish divergences
- **Label**: "H涨" (Histogram Up), "H跌" (Histogram Down)
- **Special Feature**: Same-sign requirement option
- Top divergence: Both histogram points must be positive
- Bottom divergence: Both histogram points must be negative
- Filters out less reliable divergences
**B. MACD Line Divergence Detection**
- **Purpose**: Stronger, more reliable divergences
- **Detects**: Regular bullish and bearish divergences
- **Label**: "M涨" (MACD Up), "M跌" (MACD Down)
- **Use**: Confirmation of histogram divergences or standalone
**Divergence Types Explained:**
**Regular Bullish Divergence (Yellow)**
- **Price**: Lower lows
- **Indicator**: Higher lows (histogram OR MACD line)
- **Signal**: Potential upward reversal
- **Best**: Near support levels, oversold conditions
- **Entry**: After price breaks above recent resistance
**Regular Bearish Divergence (Blue)**
- **Price**: Higher highs
- **Indicator**: Lower highs (histogram OR MACD line)
- **Signal**: Potential downward reversal
- **Best**: Near resistance levels, overbought conditions
- **Entry**: After price breaks below recent support
#### 6. **Advanced Divergence Parameters**
**Histogram Divergence Settings:**
- **Price Reference**: Wicks (default) or Bodies
- **Right Lookback**: Bars to right of pivot (default: 2)
- **Left Lookback**: Bars to left of pivot (default: 5)
- **Max Range**: Maximum bars between divergences (default: 60)
- **Min Range**: Minimum bars between divergences (default: 5)
- **Same Sign Requirement**: Ensures both histogram points have same sign
- **Show Regular Divergence**: Toggle display
- **Show Labels**: Toggle divergence labels
**MACD Line Divergence Settings:**
- **Price Reference**: Wicks (default) or Bodies
- **Right Lookback**: Bars to right of pivot (default: 1)
- **Left Lookback**: Bars to left of pivot (default: 5)
- **Max Range**: Maximum bars between divergences (default: 60)
- **Min Range**: Minimum bars between divergences (default: 5)
- **Show Regular Divergence**: Toggle display
- **Show Labels**: Toggle divergence labels
**Independent Control**: Adjust histogram and MACD line divergences separately
### Configuration Settings
#### MACD Basic Settings
- **Fast EMA Period**: Fast moving average length (default: 13)
- **Slow EMA Period**: Slow moving average length (default: 34)
- **Signal Line Period**: Signal line length (default: 9)
- **Use Current Chart Period**: Auto-adjust to current timeframe
- **Select Period**: Choose custom timeframe
- **Show MACD & Signal Lines**: Toggle lines display
- **Show Cross Markers**: Toggle golden/death cross dots
- **Show Histogram**: Toggle histogram display
- **Show Crossover Color Change**: Enable MACD line color change
- **Show Histogram Colors**: Enable 4-color histogram scheme
- **Oscillator MA Type**: Choose SMA or EMA for MACD
- **Signal Line MA Type**: Choose SMA or EMA for signal
#### Histogram Divergence Settings
- **Show Histogram Divergence**: Enable histogram divergence detection
- **Price Reference**: Wicks or Bodies for price comparison
- **Right/Left Lookback**: Pivot detection parameters
- **Max/Min Range**: Distance constraints between pivots
- **Show Regular Divergence**: Display histogram divergence lines
- **Show Labels**: Display histogram divergence labels
- **Require Same Sign**: Enforce histogram sign consistency
#### MACD Line Divergence Settings
- **Show MACD Line Divergence**: Enable MACD line divergence detection
- **Price Reference**: Wicks or Bodies for price comparison
- **Right/Left Lookback**: Pivot detection parameters
- **Max/Min Range**: Distance constraints between pivots
- **Show Regular Divergence**: Display MACD line divergence lines
- **Show Labels**: Display MACD line divergence labels
### How to Use
#### For Basic Trend Following
1. **Enable Core Components**
- MACD line, signal line, and histogram
- Enable cross markers
2. **Identify Trend**
- MACD above zero = Uptrend
- MACD below zero = Downtrend
3. **Watch for Crossovers**
- Golden cross (MACD crosses above signal) = Buy signal
- Death cross (MACD crosses below signal) = Sell signal
4. **Confirm with Histogram**
- Increasing histogram = Strengthening trend
- Decreasing histogram = Weakening trend
#### For Divergence Trading
1. **Enable Both Divergence Systems**
- Histogram divergence (early signals)
- MACD line divergence (confirmation)
2. **Wait for Divergence Signals**
- "H涨" or "H跌" = Early warning
- "M涨" or "M跌" = Confirmation
3. **Best Divergences**
- Both histogram AND MACD line showing divergence
- Divergence at key support/resistance levels
- Multiple divergences on same trend
4. **Entry Timing**
- Wait for price structure break
- Enter on pullback after confirmation
- Use MACD crossover as trigger
#### For Multi-Timeframe Analysis
1. **Set Higher Timeframe**
- Example: 4H MACD on 1H chart
- Uncheck "Use Current Chart Period"
- Select desired timeframe
2. **Identify Higher TF Trend**
- MACD position relative to zero
- MACD vs signal line relationship
3. **Trade with HTF Direction**
- Only take long signals if HTF MACD bullish
- Only take short signals if HTF MACD bearish
4. **Use Current TF for Entries**
- Higher TF for bias
- Current TF for precise timing
#### For Histogram Analysis
1. **Enable 4-Color Histogram**
- Watch color transitions
- Dark colors = Strong momentum
- Light colors = Weakening momentum
2. **Momentum Stages**
- Dark green → Light green = Bullish losing steam
- Light red → Dark red = Bearish gaining strength
3. **Trade Transitions**
- Light green to light red = Momentum shift (potential reversal)
- Entry on confirmation crossover
### Trading Strategies
#### Strategy 1: Classic MACD Crossover
**Setup:**
- Standard settings (13/34/9)
- Enable MACD, signal line, and cross markers
- Clear trend on higher timeframe
**Entry:**
- **Long**: Golden cross (circle marker) above zero line
- **Short**: Death cross (circle marker) below zero line
**Confirmation:**
- Histogram color supporting direction
- Volume increase helps
**Stop Loss:**
- Below recent swing low (long)
- Above recent swing high (short)
**Exit:**
- Opposite crossover
- MACD crosses zero line against position
**Best For:** Trend following, clear trending markets
#### Strategy 2: Zero Line Bounce
**Setup:**
- Enable all components
- Established trend (MACD staying one side of zero)
- Wait for pullback to zero line
**Entry:**
- **Long**: MACD touches zero from above, bounces up with golden cross
- **Short**: MACD touches zero from below, bounces down with death cross
**Confirmation:**
- Histogram color change
- Price at support/resistance
**Stop Loss:**
- Just beyond zero line (opposite side)
**Exit:**
- Target previous extreme
- Or opposite crossover
**Best For:** Trend continuation, strong markets
#### Strategy 3: Dual Divergence Confirmation
**Setup:**
- Enable both histogram and MACD line divergences
- Price at extreme (high/low)
- Wait for divergence signals
**Entry:**
- **Long**: Both "H涨" AND "M涨" labels appear
- **Short**: Both "H跌" AND "M跌" labels appear
**Confirmation:**
- Price breaks structure
- Volume increase
- Golden/death cross confirms
**Stop Loss:**
- Beyond divergence pivot point
**Exit:**
- MACD crosses zero line
- Or opposite divergence appears
**Best For:** Reversal trading, swing trading
#### Strategy 4: Histogram Color Transition
**Setup:**
- Enable 4-color histogram
- Focus on color changes
- Price in trend
**Entry:**
- **Long**: Light red → Light green transition + golden cross
- **Short**: Light green → Light red transition + death cross
**Rationale:**
- Light colors show momentum exhaustion
- Color flip = momentum shift
- Early entry before full trend reversal
**Stop Loss:**
- Recent swing point
**Exit:**
- Histogram color turns light against position
- Or at predetermined target
**Best For:** Scalping, day trading, early entries
#### Strategy 5: Multi-Timeframe Momentum
**Setup:**
- Display higher timeframe MACD (e.g., 4H on 1H chart)
- Current chart shows current momentum
- Higher TF shows overall bias
**Entry:**
- **Long**: HTF MACD above zero + current TF golden cross
- **Short**: HTF MACD below zero + current TF death cross
**Confirmation:**
- HTF histogram supporting direction
- Both timeframes aligned
**Stop Loss:**
- Based on current timeframe structure
**Exit:**
- Current TF opposite crossover
- Or HTF MACD momentum weakens
**Best For:** Swing trading, high-probability setups
#### Strategy 6: Histogram-Only Divergence Scout
**Setup:**
- Enable only histogram divergence
- Use "same sign requirement"
- Focus on early signals
**Entry:**
- **Long**: "H涨" label + price at support
- **Short**: "H跌" label + price at resistance
**Confirmation:**
- Wait for MACD/signal crossover
- Or price structure break
**Advantage:**
- Earliest divergence signals
- Get in before crowd
**Risk:**
- More false signals than MACD line divergence
- Requires strict confirmation
**Stop Loss:**
- Tight stop beyond entry bar
**Exit:**
- Quick targets (30-50% of expected move)
- Or trail stop
**Best For:** Active traders, scalpers seeking early entries
### Best Practices
#### MACD Period Selection
**Standard (13/34/9)** - Default
- Balanced for most markets
- Good for day trading and swing trading
- Widely used, works with general market psychology
**Faster (8/21/5 or 12/26/9)**
- More responsive
- More signals, more noise
- Best for: Scalping, volatile markets
- Risk: More false signals
**Slower (21/55/13)**
- Smoother signals
- Fewer but stronger signals
- Best for: Swing trading, position trading
- Benefit: Higher reliability
#### Histogram vs MACD Line Divergences
**Histogram Divergence:**
- ✅ Earlier signals
- ✅ Catch moves before others
- ❌ More false signals
- ❌ Requires confirmation
- **Best for**: Active traders, scalpers
**MACD Line Divergence:**
- ✅ More reliable
- ✅ Stronger divergences
- ❌ Later signals
- ❌ May miss early moves
- **Best for**: Swing traders, conservative traders
**Both Together:**
- ✅ Maximum confidence
- ✅ Histogram for alert, MACD for confirmation
- ✅ Highest probability setups
- **Best for**: All traders seeking quality over quantity
#### Same Sign Requirement Feature
**Enabled (Recommended):**
- Filters low-quality divergences
- Top divergence: Both histogram points positive
- Bottom divergence: Both histogram points negative
- Results in fewer but more reliable signals
**Disabled:**
- More divergence signals
- Includes zero-line crossing divergences
- Higher false signal rate
- Only for experienced traders
#### Price Reference: Wicks vs Bodies
**Wicks (Default):**
- Uses high/low prices
- Catches all extremes
- More divergences detected
- Best for: Most trading styles
**Bodies:**
- Uses open/close prices
- Filters out spike movements
- Fewer but cleaner divergences
- Best for: Noisy markets, crypto
#### Visual Settings Recommendations
**For Beginners:**
- Enable: MACD line, signal line, histogram
- Enable: Cross markers
- Enable: Histogram colors
- Disable: Both divergence systems initially
- Focus: Learn basic crossovers first
**For Intermediate:**
- All basic components
- Add: Histogram divergence only
- Use: Same sign requirement
- Focus: Early reversal signals
**For Advanced:**
- All components
- Both divergence systems
- Custom parameters per market
- Multi-timeframe analysis
- Focus: High-probability confluence setups
### Indicator Combinations
**With Moving Averages (EMAs):**
- EMAs (21/55/144) show trend
- MACD shows momentum
- Enter when both align
- Exit when MACD turns first
**With RSI:**
- RSI for overbought/oversold
- MACD for momentum confirmation
- Divergence on both = Extremely strong signal
- RSI + MACD divergence = High probability trade
**With Volume:**
- Volume confirms MACD signals
- Crossover + volume spike = Valid breakout
- Divergence + volume divergence = Strong reversal
**With Support/Resistance:**
- S/R levels for entry/exit targets
- MACD divergence at levels = Highest probability
- MACD crossover at level = Strong confirmation
**With Bias Indicator:**
- Bias shows price deviation from EMA
- MACD shows momentum
- Both diverging = Powerful reversal signal
- Bias extreme + MACD divergence = High conviction trade
**With OBV:**
- OBV shows volume trend
- MACD shows price momentum
- OBV + MACD divergence = Volume not supporting price
- Strong reversal indication
**With KSI (RSI/CCI):**
- KSI for oscillator extremes
- MACD for momentum direction
- KSI extreme + MACD divergence = Reversal likely
- All aligned = Maximum confidence
### Common MACD Patterns
1. **Bullish Cross Above Zero**: Strong uptrend continuation signal
2. **Bearish Cross Below Zero**: Strong downtrend continuation signal
3. **Zero Line Rejection**: Price respects zero as support/resistance
4. **Histogram Peak**: Momentum climax, watch for reversal
5. **Double Divergence**: Two divergences without reversal = Very strong signal when it finally reverses
6. **Histogram Convergence**: Histogram narrowing = Trend losing steam
7. **Signal Line Hug**: MACD stays close to signal = Consolidation, expect breakout
### Performance Tips
- Start with default settings (13/34/9 EMA/EMA)
- Test one divergence system at a time
- Use same sign requirement initially
- Enable cross markers for clear signals
- Adjust lookback parameters per market volatility
- Higher timeframe MACD more reliable than lower
- Combine histogram early signal with MACD line confirmation
- Don't trade every divergence - wait for best setups
### Alert Conditions
While not explicitly coded, you can set custom alerts on:
- MACD crossing above/below signal line
- MACD crossing above/below zero line
- Histogram crossing zero
- When divergence labels appear (using visual alerts)
---
## 中文说明文档
### 概述
Scout Regiment - MACD 是移动平均线收敛发散指标的高级实现版本，具有增强功能，包括双重背离检测（直方图和MACD线）、可自定义的移动平均类型、多时间框架分析和复杂的视觉元素。该指标为交易者提供全面的动量分析和高概率反转信号。
### 什么是MACD？
MACD（移动平均线收敛发散）是一个趋势跟随动量指标，显示两条移动平均线之间的关系：
- **MACD线**：快速和慢速EMA之间的差值
- **信号线**：MACD线的移动平均
- **直方图**：MACD线和信号线之间的差值
- **用途**：识别趋势方向、动量强度和潜在反转
### 核心功能
#### 1. **增强的MACD显示**
**三个核心组件：**
**MACD线**（默认：蓝色/橙色，2像素）
- 快速EMA（13）减去慢速EMA（34）
- 显示动量方向
- 根据相对于信号线的位置改变颜色：
- 蓝色：信号线上方（看涨）
- 橙色：信号线下方（看跌）
- 可开关显示
**信号线**（默认：白色/蓝色带透明度，2像素）
- MACD线的EMA（9）
- 作为交叉信号的触发线
- 颜色根据设置变化
- 识别进出场点的关键
**直方图**（默认：4色渐变，4像素柱）
- MACD和信号线之间的差值
- 动量强度的视觉表示
- 高级4色方案：
- **深绿色（#26A69A）**：正值且增加（强劲看涨）
- **浅绿色（#B2DFDB）**：正值但减少（看涨减弱）
- **深红色（#FF5252）**：负值且减少（强劲看跌）
- **浅红色（#FFCDD2）**：负值但增加（看跌减弱）
- 直方图讲述动量变化的"故事"
#### 2. **可自定义的移动平均类型**
**振荡器MA类型**（MACD线计算）：
- **EMA**（指数）- 默认，反应更快
- **SMA**（简单）- 更平滑，反应较慢
**信号线MA类型**：
- **EMA**（指数）- 默认，更快信号
- **SMA**（简单）- 更慢，假信号更少
**灵活性**：混合搭配以适应不同交易风格
- EMA/EMA：最灵敏（日内交易）
- SMA/SMA：最平滑（波段交易）
- EMA/SMA或SMA/EMA：平衡方法
#### 3. **多时间框架功能**
**当前图表周期**（默认：启用）
- 自动使用当前时间框架
- 大多数交易者的最简单选项
**自定义时间框架选择**
- 在任何时间框架上计算MACD
- 在低时间框架图表上显示高时间框架MACD
- 示例：在15分钟图上查看1小时MACD
- **使用场景**：使低时间框架交易与高时间框架动量保持一致
#### 4. **视觉增强功能**
**金叉/死叉标记**
- 圆点标记交叉点
- 颜色与MACD线颜色匹配
- 清晰识别进出场信号
- 可开关
**零线**（白色，2像素实线）
- 正负动量的参考
- 趋势识别的关键水平
- MACD在零线上方 = 看涨偏向
- MACD在零线下方 = 看跌偏向
**颜色转换**
- MACD线在信号线交叉处改变颜色
- 直方图显示动量加速/减速
- 提供趋势变化的早期警告
#### 5. **双重背离检测系统**
该指标具有两个独立的背离检测系统：
**A. 直方图背离检测**
- **用途**：更早的背离信号（最敏感）
- **检测**：常规看涨和看跌背离
- **标签**："H涨"（直方图上涨）、"H跌"（直方图下跌）
- **特殊功能**：同符号要求选项
- 顶背离：两个直方图点都必须为正
- 底背离：两个直方图点都必须为负
- 过滤不太可靠的背离
**B. MACD线背离检测**
- **用途**：更强、更可靠的背离
- **检测**：常规看涨和看跌背离
- **标签**："M涨"（MACD上涨）、"M跌"（MACD下跌）
- **用途**：确认直方图背离或独立使用
**背离类型说明：**
**常规看涨背离（黄色）**
- **价格**：更低的低点
- **指标**：更高的低点（直方图或MACD线）
- **信号**：潜在向上反转
- **最佳**：在支撑水平附近、超卖状况
- **入场**：价格突破近期阻力后
**常规看跌背离（蓝色）**
- **价格**：更高的高点
- **指标**：更低的高点（直方图或MACD线）
- **信号**：潜在向下反转
- **最佳**：在阻力水平附近、超买状况
- **入场**：价格跌破近期支撑后
#### 6. **高级背离参数**
**直方图背离设置：**
- **价格参考**：影线（默认）或实体
- **右侧回溯**：枢轴点右侧K线数（默认：2）
- **左侧回溯**：枢轴点左侧K线数（默认：5）
- **最大范围**：背离之间最大K线数（默认：60）
- **最小范围**：背离之间最小K线数（默认：5）
- **同符号要求**：确保两个直方图点符号相同
- **显示常规背离**：切换显示
- **显示标签**：切换背离标签
**MACD线背离设置：**
- **价格参考**：影线（默认）或实体
- **右侧回溯**：枢轴点右侧K线数（默认：1）
- **左侧回溯**：枢轴点左侧K线数（默认：5）
- **最大范围**：背离之间最大K线数（默认：60）
- **最小范围**：背离之间最小K线数（默认：5）
- **显示常规背离**：切换显示
- **显示标签**：切换背离标签
**独立控制**：分别调整直方图和MACD线背离
### 配置设置
#### MACD基础设置
- **快速EMA周期**：快速移动平均长度（默认：13）
- **慢速EMA周期**：慢速移动平均长度（默认：34）
- **信号线周期**：信号线长度（默认：9）
- **使用当前图表周期**：自动调整到当前时间框架
- **选择周期**：选择自定义时间框架
- **显示MACD线和信号线**：切换线条显示
- **显示金叉死叉圆点标记**：切换金叉/死叉圆点
- **显示直方图**：切换直方图显示
- **显示穿越变化MACD线**：启用MACD线颜色变化
- **显示直方图颜色**：启用4色直方图方案
- **振荡器MA类型**：为MACD选择SMA或EMA
- **信号线MA类型**：为信号线选择SMA或EMA
#### 直方图背离设置
- **显示直方图背离信号**：启用直方图背离检测
- **价格参考**：影线或实体用于价格比较
- **右侧/左侧回溯**：枢轴检测参数
- **最大/最小范围**：枢轴之间的距离约束
- **显示直方图常规背离**：显示直方图背离线
- **显示直方图常规背离标签**：显示直方图背离标签
- **要求背离点柱状图同符号**：强制直方图符号一致性
#### MACD线背离设置
- **显示MACD线背离信号**：启用MACD线背离检测
- **价格参考**：影线或实体用于价格比较
- **右侧/左侧回溯**：枢轴检测参数
- **最大/最小范围**：枢轴之间的距离约束
- **显示线常规背离**：显示MACD线背离线
- **显示线常规背离标签**：显示MACD线背离标签
### 使用方法
#### 基础趋势跟随
1. **启用核心组件**
- MACD线、信号线和直方图
- 启用交叉标记
2. **识别趋势**
- MACD在零线上方 = 上升趋势
- MACD在零线下方 = 下降趋势
3. **观察交叉**
- 金叉（MACD向上穿越信号线）= 买入信号
- 死叉（MACD向下穿越信号线）= 卖出信号
4. **用直方图确认**
- 直方图增加 = 趋势加强
- 直方图减少 = 趋势减弱
#### 背离交易
1. **启用两个背离系统**
- 直方图背离（早期信号）
- MACD线背离（确认）
2. **等待背离信号**
- "H涨"或"H跌" = 早期警告
- "M涨"或"M跌" = 确认
3. **最佳背离**
- 直方图和MACD线都显示背离
- 在关键支撑/阻力水平的背离
- 同一趋势上多个背离
4. **入场时机**
- 等待价格结构突破
- 确认后回调时进入
- 使用MACD交叉作为触发
#### 多时间框架分析
1. **设置更高时间框架**
- 示例：在1小时图上显示4小时MACD
- 取消勾选"使用当前图表周期"
- 选择所需时间框架
2. **识别更高TF趋势**
- MACD相对于零线的位置
- MACD与信号线的关系
3. **顺HTF方向交易**
- 仅在HTF MACD看涨时接受多头信号
- 仅在HTF MACD看跌时接受空头信号
4. **使用当前TF入场**
- 更高TF确定偏向
- 当前TF精确定时
#### 直方图分析
1. **启用4色直方图**
- 观察颜色转换
- 深色 = 强动量
- 浅色 = 动量减弱
2. **动量阶段**
- 深绿色→浅绿色 = 看涨失去动力
- 浅红色→深红色 = 看跌获得力量
3. **交易转换**
- 浅绿色到浅红色 = 动量转变（潜在反转）
- 确认交叉时入场
### 交易策略
#### 策略1：经典MACD交叉
**设置：**
- 标准设置（13/34/9）
- 启用MACD、信号线和交叉标记
- 更高时间框架明确趋势
**入场：**
- **多头**：零线上方金叉（圆点标记）
- **空头**：零线下方死叉（圆点标记）
**确认：**
- 直方图颜色支持方向
- 成交量增加有帮助
**止损：**
- 近期波动低点之下（多头）
- 近期波动高点之上（空头）
**离场：**
- 相反交叉
- MACD反向穿越零线
**适合：**趋势跟随、明确趋势市场
#### 策略2：零线反弹
**设置：**
- 启用所有组件
- 已建立趋势（MACD保持在零线一侧）
- 等待回调至零线
**入场：**
- **多头**：MACD从上方触及零线，向上反弹并金叉
- **空头**：MACD从下方触及零线，向下反弹并死叉
**确认：**
- 直方图颜色变化
- 价格在支撑/阻力位
**止损：**
- 零线对面一侧
**离场：**
- 目标前一极值
- 或相反交叉
**适合：**趋势延续、强势市场
#### 策略3：双重背离确认
**设置：**
- 启用直方图和MACD线背离
- 价格在极值（高点/低点）
- 等待背离信号
**入场：**
- **多头**："H涨"和"M涨"标签都出现
- **空头**："H跌"和"M跌"标签都出现
**确认：**
- 价格突破结构
- 成交量增加
- 金叉/死叉确认
**止损：**
- 背离枢轴点之外
**离场：**
- MACD穿越零线
- 或出现相反背离
**适合：**反转交易、波段交易
#### 策略4：直方图颜色转换
**设置：**
- 启用4色直方图
- 关注颜色变化
- 价格处于趋势
**入场：**
- **多头**：浅红色→浅绿色转换 + 金叉
- **空头**：浅绿色→浅红色转换 + 死叉
**原理：**
- 浅色显示动量衰竭
- 颜色翻转 = 动量转变
- 完全趋势反转前的早期入场
**止损：**
- 近期波动点
**离场：**
- 直方图颜色变为反向浅色
- 或预定目标
**适合：**剥头皮、日内交易、早期入场
#### 策略5：多时间框架动量
**设置：**
- 显示更高时间框架MACD（例如，在1小时图上显示4小时）
- 当前图表显示当前动量
- 更高TF显示整体偏向
**入场：**
- **多头**：HTF MACD在零线上方 + 当前TF金叉
- **空头**：HTF MACD在零线下方 + 当前TF死叉
**确认：**
- HTF直方图支持方向
- 两个时间框架对齐
**止损：**
- 基于当前时间框架结构
**离场：**
- 当前TF相反交叉
- 或HTF MACD动量减弱
**适合：**波段交易、高概率设置
#### 策略6：仅直方图背离侦察
**设置：**
- 仅启用直方图背离
- 使用"同符号要求"
- 关注早期信号
**入场：**
- **多头**："H涨"标签 + 价格在支撑位
- **空头**："H跌"标签 + 价格在阻力位
**确认：**
- 等待MACD/信号线交叉
- 或价格结构突破
**优势：**
- 最早的背离信号
- 在大众之前进入
**风险：**
- 比MACD线背离假信号更多
- 需要严格确认
**止损：**
- 入场K线之外紧密止损
**离场：**
- 快速目标（预期波动的30-50%）
- 或移动止损
**适合：**活跃交易者、寻求早期入场的剥头皮交易者
### 最佳实践
#### MACD周期选择
**标准（13/34/9）** - 默认
- 大多数市场的平衡
- 适合日内交易和波段交易
- 广泛使用，符合一般市场心理
**更快（8/21/5或12/26/9）**
- 更灵敏
- 更多信号，更多噪音
- 最适合：剥头皮、波动市场
- 风险：更多假信号
**更慢（21/55/13）**
- 更平滑的信号
- 信号较少但更强
- 最适合：波段交易、仓位交易
- 优势：更高可靠性
#### 直方图vs MACD线背离
**直方图背离：**
- ✅ 更早信号
- ✅ 在其他人之前捕捉波动
- ❌ 更多假信号
- ❌ 需要确认
- **最适合**：活跃交易者、剥头皮交易者
**MACD线背离：**
- ✅ 更可靠
- ✅ 更强的背离
- ❌ 信号较晚
- ❌ 可能错过早期波动
- **最适合**：波段交易者、保守交易者
**两者结合：**
- ✅ 最大信心
- ✅ 直方图警报，MACD确认
- ✅ 最高概率设置
- **最适合**：所有寻求质量而非数量的交易者
#### 同符号要求功能
**启用（推荐）：**
- 过滤低质量背离
- 顶背离：两个直方图点都为正
- 底背离：两个直方图点都为负
- 产生更少但更可靠的信号
**禁用：**
- 更多背离信号
- 包括零线穿越背离
- 假信号率更高
- 仅适合有经验的交易者
#### 价格参考：影线vs实体
**影线（默认）：**
- 使用最高/最低价
- 捕捉所有极值
- 检测到更多背离
- 最适合：大多数交易风格
**实体：**
- 使用开盘/收盘价
- 过滤突刺波动
- 背离更少但更干净
- 最适合：噪音市场、加密货币
#### 视觉设置建议
**新手：**
- 启用：MACD线、信号线、直方图
- 启用：交叉标记
- 启用：直方图颜色
- 禁用：初始禁用两个背离系统
- 重点：先学习基本交叉
**中级：**
- 所有基本组件
- 添加：仅直方图背离
- 使用：同符号要求
- 重点：早期反转信号
**高级：**
- 所有组件
- 两个背离系统
- 每个市场自定义参数
- 多时间框架分析
- 重点：高概率汇合设置
### 指标组合
**与移动平均线（EMA）配合：**
- EMA（21/55/144）显示趋势
- MACD显示动量
- 两者一致时进入
- MACD先转向时退出
**与RSI配合：**
- RSI用于超买超卖
- MACD用于动量确认
- 两者都背离 = 极强信号
- RSI + MACD背离 = 高概率交易
**与成交量配合：**
- 成交量确认MACD信号
- 交叉 + 成交量激增 = 有效突破
- 背离 + 成交量背离 = 强反转
**与支撑/阻力配合：**
- 支撑阻力水平用于进出目标
- 水平处的MACD背离 = 最高概率
- 水平处的MACD交叉 = 强确认
**与Bias指标配合：**
- Bias显示价格相对EMA的偏离
- MACD显示动量
- 两者都背离 = 强大反转信号
- Bias极值 + MACD背离 = 高信念交易
**与OBV配合：**
- OBV显示成交量趋势
- MACD显示价格动量
- OBV + MACD背离 = 成交量不支持价格
- 强反转迹象
**与KSI（RSI/CCI）配合：**
- KSI用于振荡器极值
- MACD用于动量方向
- KSI极值 + MACD背离 = 可能反转
- 全部对齐 = 最大信心
### 常见MACD形态
1. **零线上方看涨交叉**：强上升趋势延续信号
2. **零线下方看跌交叉**：强下降趋势延续信号
3. **零线拒绝**：价格将零线作为支撑/阻力
4. **直方图峰值**：动量高潮，注意反转
5. **双重背离**：两次背离未反转 = 最终反转时非常强
6. **直方图收敛**：直方图变窄 = 趋势失去动力
7. **信号线紧贴**：MACD紧贴信号线 = 盘整，预期突破
### 性能提示
- 从默认设置开始（13/34/9 EMA/EMA）
- 一次测试一个背离系统
- 初始使用同符号要求
- 启用交叉标记以获得清晰信号
- 根据市场波动性调整回溯参数
- 更高时间框架MACD比更低的更可靠
- 结合直方图早期信号与MACD线确认
- 不要交易每个背离 - 等待最佳设置
### 警报条件
虽然没有明确编码，但您可以设置自定义警报：
- MACD向上/向下穿越信号线
- MACD向上/向下穿越零线
- 直方图穿越零线
- 背离标签出现时（使用视觉警报）
---
## 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。
Scout Regiment - D17# Scout Regiment - D17 Indicator
## English Documentation
### Overview
Scout Regiment - D17 is a comprehensive TradingView indicator that combines multiple technical analysis tools into one powerful overlay indicator. It provides traders with market structure analysis, divergence detection, volume profiling, smart money concepts, and session analysis.
### Key Features
#### 1. **EMA (Exponential Moving Averages)**
- **Purpose**: Trend identification and dynamic support/resistance levels
- **Configuration**: 13 customizable EMAs with adjustable periods
- **Default Active EMAs**: EMA 3 (21), EMA 5 (55), EMA 7 (144), EMA 8 (233)
- **Uses**: Identify trend direction, entry/exit points, and trend strength
- **Color Coding**: Different colors for easy visual distinction
#### 2. **TFMA (Timeframe Moving Averages)**
- **Purpose**: Multi-timeframe trend analysis
- **Features**:
- 3 EMAs on higher timeframes
- Dynamic labels showing trend direction
- Price difference percentage display
- Customizable timeframe settings
- **Default Settings**: 21-period timeframe with lengths 55, 144, and 233
- **Benefits**: Align trades with higher timeframe trends
#### 3. **DFMA (Daily Frame Moving Averages)**
- **Purpose**: Daily timeframe perspective on any chart
- **Features**: Similar to TFMA but specifically for daily analysis
- **Default Timeframe**: 1D (Daily)
- **Use Case**: Long-term trend confirmation and positioning
#### 4. **PMA (Price Moving Averages)**
- **Purpose**: Price channel analysis with filled areas
- **Configuration**: 7 customizable moving averages with fill zones
- **Default Lengths**: 12, 144, 169, 288, 338, 576, 676
- **Visual**: Color-filled zones between selected MAs for channel trading
#### 5. **VWAP (Volume Weighted Average Price)**
- **Purpose**: Institutional trading levels and fair value
- **Features**:
- Multiple anchor periods (Session, Week, Month, Quarter, Year, etc.)
- Standard deviation bands
- Corporate event anchoring (Earnings, Dividends, Splits)
- **Use Case**: Identify institutional support/resistance and mean reversion opportunities
#### 6. **Divergence Detector**
- **Purpose**: Identify potential trend reversals
- **Supported Indicators**: MACD, MACD Histogram, RSI, Stochastic, CCI, Williams %R, Bias, Momentum, OBV, SOBV, VWmacd, CMF, MFI, and external indicators
- **Divergence Types**:
- Regular Bullish/Bearish
- Hidden Bullish/Bearish
- **Features**:
- Automatic divergence line drawing
- Customizable detection parameters
- Color-coded alerts
#### 7. **Volume Profile & Node Detection**
- **Purpose**: Identify key price levels based on volume distribution
- **Features**:
- Volume Profile with POC (Point of Control)
- Value Area High (VAH) and Value Area Low (VAL)
- Peak and trough volume node detection
- Highest/lowest volume node highlighting
- **Lookback**: Configurable (default 377 bars)
- **Use Case**: Identify support/resistance zones and liquidity areas
#### 8. **Smart Money Concepts**
- **Purpose**: Track institutional trading patterns
- **Features**:
- Market Structure (BOS - Break of Structure, CHoCH - Change of Character)
- Internal and Swing structures
- Strong/Weak Highs and Lows
- Equal Highs/Lows detection
- Fair Value Gaps (FVG)
- **Modes**: Historical or Present (latest only)
- **Use Case**: Trade with institutional flow
#### 9. **Trading Sessions**
- **Purpose**: Analyze market behavior during different global sessions
- **Available Sessions**:
- Asian Session
- Sydney, Tokyo, Shanghai, Hong Kong
- European Session
- London, New York, NYSE
- **Features**:
- Session boxes with high/low visualization
- Real-time countdown timers
- Volume and price change tracking
- Information table with session statistics
- **Customization**: Choose which sessions to display, colors, and box styles
### How to Use
#### For Trend Following:
1. Enable EMAs 3, 5, 7, and 8
2. Use TFMA for higher timeframe confirmation
3. Look for price above/below key EMAs for trend direction
4. Use VWAP as additional confirmation
#### For Reversal Trading:
1. Enable Divergence Detector with MACD Histogram and Bias
2. Look for divergences at key support/resistance levels
3. Confirm with Smart Money CHoCH signals
4. Use Volume Profile nodes as entry/exit targets
#### For Intraday Trading:
1. Enable Trading Sessions
2. Focus on high-volume sessions (London, New York overlap)
3. Use session highs/lows as support/resistance
4. Trade Fair Value Gaps during active sessions
#### For Swing Trading:
1. Use DFMA for daily trend
2. Enable PMA for channel identification
3. Look for price reactions at volume profile value areas
4. Confirm with swing structure breaks
### Best Practices
1. **Don't Overcrowd**: Enable only the components you need for your strategy
2. **Multi-Timeframe Analysis**: Always check higher timeframe TFMA/DFMA
3. **Confluence**: Look for multiple signals confirming the same direction
4. **Volume Confirmation**: Use Volume Profile to validate price action
5. **Session Awareness**: Be aware of which session is active for volatility expectations
### Performance Optimization
- Disable unused features to improve chart loading speed
- Use "Present Mode" for Smart Money Concepts if historical data isn't needed
- Reduce Volume Profile lookback period on slower devices
### Alerts
The indicator includes alert conditions for:
- All divergence types (8 conditions)
- Smart Money structure breaks (8 conditions)
- Equal highs/lows detection
- Fair Value Gaps formation
---
## 中文说明文档
### 概述
Scout Regiment - D17 是一款综合性TradingView指标，将多个技术分析工具整合到一个强大的叠加指标中。它为交易者提供市场结构分析、背离检测、成交量分析、聪明钱概念和时区分析。
### 核心功能
#### 1. **EMA（指数移动平均线）**
- **用途**：趋势识别和动态支撑阻力位
- **配置**：13条可自定义周期的EMA
- **默认启用**：EMA 3（21）、EMA 5（55）、EMA 7（144）、EMA 8（233）
- **应用**：识别趋势方向、进出场点位和趋势强度
- **颜色编码**：不同颜色便于视觉区分
#### 2. **TFMA（时间框架移动平均线）**
- **用途**：多时间框架趋势分析
- **特点**：
- 3条更高时间框架的EMA
- 显示趋势方向的动态标签
- 价格差异百分比显示
- 可自定义时间框架设置
- **默认设置**：21周期时间框架，长度为55、144和233
- **优势**：使交易与更高时间框架趋势保持一致
#### 3. **DFMA（日线框架移动平均线）**
- **用途**：在任何图表上提供日线时间框架视角
- **特点**：与TFMA类似，但专门用于日线分析
- **默认时间框架**：1D（日线）
- **使用场景**：长期趋势确认和定位
#### 4. **PMA（价格移动平均线）**
- **用途**：价格通道分析与填充区域
- **配置**：7条可自定义的移动平均线，带填充区域
- **默认长度**：12、144、169、288、338、576、676
- **视觉效果**：选定MA之间的彩色填充区域，用于通道交易
#### 5. **VWAP（成交量加权平均价格）**
- **用途**：机构交易水平和公允价值
- **特点**：
- 多个锚定周期（交易日、周、月、季度、年等）
- 标准差波段
- 企业事件锚定（财报、分红、拆股）
- **使用场景**：识别机构支撑阻力和均值回归机会
#### 6. **背离检测器**
- **用途**：识别潜在趋势反转
- **支持指标**：MACD、MACD柱状图、RSI、随机指标、CCI、威廉指标、乖离率、动量、OBV、SOBV、VWmacd、CMF、MFI及外部指标
- **背离类型**：
- 常规看涨/看跌背离
- 隐藏看涨/看跌背离
- **特点**：
- 自动绘制背离连线
- 可自定义检测参数
- 颜色编码警报
#### 7. **成交量分布与节点检测**
- **用途**：基于成交量分布识别关键价格水平
- **特点**：
- 成交量分布图与POC（控制点）
- 价值区域高点（VAH）和低点（VAL）
- 峰值和低谷成交量节点检测
- 最高/最低成交量节点突出显示
- **回溯期**：可配置（默认377根K线）
- **使用场景**：识别支撑阻力区域和流动性区域
#### 8. **聪明钱概念**
- **用途**：追踪机构交易模式
- **特点**：
- 市场结构（BOS-突破结构、CHoCH-结构转变）
- 内部和摆动结构
- 强/弱高低点
- 等高/等低检测
- 公允价值缺口（FVG）
- **模式**：历史模式或当前模式（仅最新）
- **使用场景**：跟随机构资金流动交易
#### 9. **交易时区**
- **用途**：分析不同全球时段的市场行为
- **可用时段**：
- 亚洲时段
- 悉尼、东京、上海、香港
- 欧洲时段
- 伦敦、纽约、纽交所
- **特点**：
- 时段方框显示高低点
- 实时倒计时
- 成交量和价格变化追踪
- 时段统计信息表格
- **自定义**：选择显示哪些时段、颜色和方框样式
### 使用方法
#### 趋势跟随策略：
1. 启用EMA 3、5、7和8
2. 使用TFMA进行更高时间框架确认
3. 观察价格在关键EMA上方/下方确定趋势方向
4. 使用VWAP作为额外确认
#### 反转交易策略：
1. 启用背离检测器（MACD柱状图和乖离率）
2. 在关键支撑阻力位寻找背离
3. 用聪明钱CHoCH信号确认
4. 使用成交量分布节点作为进出场目标
#### 日内交易策略：
1. 启用交易时区
2. 关注高成交量时段（伦敦、纽约重叠时段）
3. 使用时段高低点作为支撑阻力
4. 在活跃时段交易公允价值缺口
#### 波段交易策略：
1. 使用DFMA确定日线趋势
2. 启用PMA识别通道
3. 观察价格在成交量分布价值区域的反应
4. 用摆动结构突破确认
### 最佳实践
1. **避免过度拥挤**：仅启用策略所需的组件
2. **多时间框架分析**：始终检查更高时间框架的TFMA/DFMA
3. **汇合点**：寻找多个信号确认同一方向
4. **成交量确认**：使用成交量分布验证价格行为
5. **时段意识**：了解当前活跃时段以预期波动性
### 性能优化
- 禁用未使用的功能以提高图表加载速度
- 如果不需要历史数据，对聪明钱概念使用"当前模式"
- 在较慢设备上减少成交量分布回溯期
### 警报
指标包含以下警报条件：
- 所有背离类型（8个条件）
- 聪明钱结构突破（8个条件）
- 等高/等低检测
- 公允价值缺口形成
---
## 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。
Ultimate Prime Hyper Oscillator Pro [TraderCloud]추세, 변동성, 모멘텀, 평균회귀 모든 분석과 원리를 분석할 수 있는 최고의 오실레이터.
맨 상단에는 고래의 매수와 매도 시그널을 보여준다.
중간에는 rsi, mfi, rci, cci 등의 과열/과냉 지표를 로지스틱 회귀 평활화로 복합 운영하는 종합 모멘텀 오실레이터이다. 단기, 중기, 장기 이렇게 3가지의 기간별 다이버전스와 히든 다이버전스를 시각화한다.
또한 오실레이터 중간에 있는 히스토그램은 lazybear의 squeeze momentum oscillator를 기반으로 제작한 히스토그램 지표이다.
주요 변동성 오실레이터 바로 상/하단에는 히스토그램과 UPO 오실레이터의 추세가 동일하거나, 잠재성을 가질 때를 시각화해서 보여준다.
아래에는 중단기 추세를 Chop Zone 형식으로 시각화해서 보여준다.
아래 얇은 막대의 자잘 자잘한 신호들은 중단기적 평균회귀 구간을 보여준다.
마지막으로 테이블은 타임별 오실레이터의 추세를 간략화해서 정리해준다.
“The ultimate oscillator capable of analyzing all aspects of trend, volatility, momentum, and mean reversion.”
At the very top, it displays whale buy and sell signals.
In the middle, it functions as a comprehensive momentum oscillator that combines and smooths overbought/oversold indicators such as RSI, MFI, RCI, and CCI through logistic regression. It visualizes three types of divergences — short-term, mid-term, and long-term — as well as hidden divergences.
The histogram located in the center of the oscillator is based on LazyBear’s Squeeze Momentum Oscillator.
Right above and below the main volatility oscillator, it visualizes when the histogram and UPO oscillator share the same trend or show potential correlation.
At the bottom, mid- to short-term trends are visualized in a Chop Zone style.
The small thin bars below indicate short- to mid-term mean reversion zones.
Finally, the table provides a simplified summary of each oscillator’s trend by timeframe.
Super Frog Power - Cluster Flip %Super Frog Power - Cluster Flip %
🔄 Trade Smarter, Not Harder: Let the Cluster Decide
Welcome to the "Super Frog Power - Cluster Flip %" strategy, a sophisticated multi-system confluence engine designed to filter out market noise and pinpoint high-probability trade setups. This isn't just another indicator; it's a comprehensive trading system that aggregates signals from eight distinct technical methodologies, waiting for them to align into a powerful "cluster" before you enter a trade.
🎯 Core Philosophy: The Power of Confluence
A single indicator can give false signals. A cluster of indicators from uncorrelated systems agreeing on a direction is a much stronger signal. This strategy continuously monitors multiple independent systems and only executes a trade when a significant number of them flip to a consensus, dramatically increasing the likelihood of a successful move.
✨ The 8 Systems of Super Frog Power
This strategy synthesizes signals from the following powerful components:
Bollinger Bands®: Identifies overbought and oversold conditions relative to recent volatility.
CMI (Cluster Momentum Index) System: A unique multi-period momentum oscillator that identifies convergence and breakout moments with custom "Lion" (SELL) and "Car" (BUY) signals.
SMI (Stochastic Momentum Index) System: A refined momentum indicator that generates "Mouse" (BUY) signals and combines with CMI for "Green Angel" and "Red Devil" super signals.
Lucky Balls (NVI/PVI): Utilizes Negative and Positive Volume Index to gauge smart money flow and identify accumulation/distribution zones.
Momentum System: A triple-threat combo of RSI, CCI, and PPO, scaled and combined to generate robust momentum-based entries and exits.
Lucky Table (Oscillator Overload): Counts the number of key oscillators (SMI, RSI, CCI) in overbought or oversold territory, triggering a signal when a threshold is met.
Apples & Pairs System: A complex system analyzing price swings, accumulation, mass index, and doji patterns with fun, emoji-based signals like "Apple Cross Up" 🍎 and "Pig Cross Down" 🐖.
ZBT (Zonal Breakout Trend) System: A multi-timeframe trend-following system using dynamic EMA channels and an ATR-based trailing stop to identify the primary trend and robust breakout points.
⚙️ How It Works: The Cluster Flip Logic
The magic happens in the signal aggregation. The strategy counts every single BUY and SELL signal from all active systems.
A "Strong Buy" is triggered when 6 or more independent BUY signals occur simultaneously.
A "Strong Sell" is triggered when 5 or more independent SELL signals occur simultaneously.
This "cluster flip" mechanism ensures you are only trading when there is broad-based technical agreement, keeping you out of choppy and uncertain market conditions.
🛡️ Integrated Risk Management
We believe a strategy is nothing without proper risk management. This system comes with built-in, percentage-based order management:
User-Defined Profit Target (%): Lock in profits automatically at your specified percentage gain.
User-Defined Stop Loss (%): Protect your capital with a hard stop loss.
Position Sizing: Control your risk per trade with a customizable position size.
Trades are also managed logically: a new strong signal in the opposite direction will automatically close any existing position, ensuring you're always on the right side of the cluster's consensus.
🎨 Visual Features & Customization
Fully Customizable: Don't like one system? Turn it off! Every system can be toggled on/off from the inputs.
Clear Visuals: Each system is plotted in a distinct color, making the chart a rich source of information without being cluttered.
Signal Markers: Strong Buy and Strong Sell clusters are clearly marked with large circles below and above the bars.
Alert Ready: Built-in alerts for Strong Buy and Strong Sell signals so you never miss a cluster setup.
🚀 How to Use
Add the script to your chart (1H, 4H, or Daily timeframes are recommended for swing trading).
Adjust the inputs to your liking, especially the Profit Target %, Stop Loss %, and Position Size under the "Strategy Parameters" section.
Observe the clusters. Wait for the "Strong Buy" or "Strong Sell" circle to appear.
Enter the trade. The strategy will automatically plot the profit target and stop loss levels on the chart for your reference.
Manage your trade. Let the logic handle the exits, or use your own discretion.
💡 Ideal For
Swing Traders looking for high-confidence set-and-forget setups.
Technical Analysts who appreciate the depth of multi-system confluence.
Traders who want to avoid the paralysis of analyzing too many indicators separately.
Unleash the power of cluster trading. Add the "Super Frog Power - Cluster Flip %" to your chart today!
Perpetual Swing [HCR]The Perpetual Swing is a fully automated swing-direction indicator designed to help traders visualize long-term trend regimes and smooth out noise in volatile markets.
It combines:
• Hash Adaptive CCI – a dynamically tuned Commodity Channel Index that adapts to volatility conditions.
• Regime-based SMMA – a Smoothed Moving Average model used to define bullish and bearish environments.
The indicator continuously monitors both momentum and structural trend, switching bias automatically between long and short conditions.
It can be used on any asset or timeframe to identify directional bias, trend transitions, and potential swing entries.
How it works:
– When the adaptive CCI confirms bullish strength above the SMMA regime, the indicator signals a long bias.
– When momentum and regime flip bearish, it switches to short bias.
– The system remains continuously engaged to capture multi-cycle swings.
Stochastic Enhanced [DCAUT]█ Stochastic Enhanced
📊 ORIGINALITY & INNOVATION
The Stochastic Enhanced indicator builds upon George Lane's classic momentum oscillator (developed in the late 1950s) by providing comprehensive smoothing algorithm flexibility. While traditional implementations limit users to Simple Moving Average (SMA) smoothing, this enhanced version offers 21 advanced smoothing algorithms, allowing traders to optimize the indicator's characteristics for different market conditions and trading styles.
Key Improvements:
Extended from single SMA smoothing to 21 professional-grade algorithms including adaptive filters (KAMA, FRAMA), zero-lag methods (ZLEMA, T3), and advanced digital filters (Kalman, Laguerre)
Maintains backward compatibility with traditional Stochastic calculations through SMA default setting
Unified smoothing algorithm applies to both %K and %D lines for consistent signal processing characteristics
Enhanced visual feedback with clear color distinction and background fill highlighting for intuitive signal recognition
Comprehensive alert system covering crossovers and zone entries for systematic trade management
Differentiation from Traditional Stochastic:
Traditional Stochastic indicators use fixed SMA smoothing, which introduces consistent lag regardless of market volatility. This enhanced version addresses the limitation by offering adaptive algorithms that adjust to market conditions (KAMA, FRAMA), reduce lag without sacrificing smoothness (ZLEMA, T3, HMA), or provide superior noise filtering (Kalman Filter, Laguerre filters). The flexibility helps traders balance responsiveness and stability according to their specific needs.
📐 MATHEMATICAL FOUNDATION
Core Stochastic Calculation:
The Stochastic Oscillator measures the position of the current close relative to the high-low range over a specified period:
Step 1: Raw %K Calculation
%K_raw = 100 × (Close - Lowest Low) / (Highest High - Lowest Low)
Where:
Close = Current closing price
Lowest Low = Lowest low over the %K Length period
Highest High = Highest high over the %K Length period
Result ranges from 0 (close at period low) to 100 (close at period high)
Step 2: Smoothed %K Calculation
%K = MA(%K_raw, K Smoothing Period, MA Type)
Where:
MA = Selected moving average algorithm (SMA, EMA, etc.)
K Smoothing = 1 for Fast Stochastic, 3+ for Slow Stochastic
Traditional Fast Stochastic uses %K_raw directly without smoothing
Step 3: Signal Line %D Calculation
%D = MA(%K, D Smoothing Period, MA Type)
Where:
%D acts as a signal line and moving average of %K
D Smoothing typically set to 3 periods in traditional implementations
Both %K and %D use the same MA algorithm for consistent behavior
Available Smoothing Algorithms (21 Options):
Standard Moving Averages:
SMA (Simple): Equal-weighted average, traditional default, consistent lag characteristics
EMA (Exponential): Recent price emphasis, faster response to changes, exponential decay weighting
RMA (Rolling/Wilder's): Smoothed average used in RSI, less reactive than EMA
WMA (Weighted): Linear weighting favoring recent data, moderate responsiveness
VWMA (Volume-Weighted): Incorporates volume data, reflects market participation intensity
Advanced Moving Averages:
HMA (Hull): Reduced lag with smoothness, uses weighted moving averages and square root period
ALMA (Arnaud Legoux): Gaussian distribution weighting, minimal lag with good noise reduction
LSMA (Least Squares): Linear regression based, fits trend line to data points
DEMA (Double Exponential): Reduced lag compared to EMA, uses double smoothing technique
TEMA (Triple Exponential): Further lag reduction, triple smoothing with lag compensation
ZLEMA (Zero-Lag Exponential): Lag elimination attempt using error correction, very responsive
TMA (Triangular): Double-smoothed SMA, very smooth but slower response
Adaptive & Intelligent Filters:
T3 (Tilson T3): Six-pass exponential smoothing with volume factor adjustment, excellent smoothness
FRAMA (Fractal Adaptive): Adapts to market fractal dimension, faster in trends, slower in ranges
KAMA (Kaufman Adaptive): Efficiency ratio based adaptation, responds to volatility changes
McGinley Dynamic: Self-adjusting mechanism following price more accurately, reduced whipsaws
Kalman Filter: Optimal estimation algorithm from aerospace engineering, dynamic noise filtering
Advanced Digital Filters:
Ultimate Smoother: Advanced digital filter design, superior noise rejection with minimal lag
Laguerre Filter: Time-domain filter with N-order implementation, adjustable lag characteristics
Laguerre Binomial Filter: 6-pole Laguerre filter, extremely smooth output for long-term analysis
Super Smoother: Butterworth filter implementation, removes high-frequency noise effectively
📊 COMPREHENSIVE SIGNAL ANALYSIS
Absolute Level Interpretation (%K Line):
%K Above 80: Overbought condition, price near period high, potential reversal or pullback zone, caution for new long entries
%K in 70-80 Range: Strong upward momentum, bullish trend confirmation, uptrend likely continuing
%K in 50-70 Range: Moderate bullish momentum, neutral to positive outlook, consolidation or mild uptrend
%K in 30-50 Range: Moderate bearish momentum, neutral to negative outlook, consolidation or mild downtrend
%K in 20-30 Range: Strong downward momentum, bearish trend confirmation, downtrend likely continuing
%K Below 20: Oversold condition, price near period low, potential bounce or reversal zone, caution for new short entries
Crossover Signal Analysis:
%K Crosses Above %D (Bullish Cross): Momentum shifting bullish, faster line overtakes slower signal, consider long entry especially in oversold zone, strongest when occurring below 20 level
%K Crosses Below %D (Bearish Cross): Momentum shifting bearish, faster line falls below slower signal, consider short entry especially in overbought zone, strongest when occurring above 80 level
Crossover in Midrange (40-60): Less reliable signals, often in choppy sideways markets, require additional confirmation from trend or volume analysis
Multiple Failed Crosses: Indicates ranging market or choppy conditions, reduce position sizes or avoid trading until clear directional move
Advanced Divergence Patterns (%K Line vs Price):
Bullish Divergence: Price makes lower low while %K makes higher low, indicates weakening bearish momentum, potential trend reversal upward, more reliable when %K in oversold zone
Bearish Divergence: Price makes higher high while %K makes lower high, indicates weakening bullish momentum, potential trend reversal downward, more reliable when %K in overbought zone
Hidden Bullish Divergence: Price makes higher low while %K makes lower low, indicates trend continuation in uptrend, bullish trend strength confirmation
Hidden Bearish Divergence: Price makes lower high while %K makes higher high, indicates trend continuation in downtrend, bearish trend strength confirmation
Momentum Strength Analysis (%K Line Slope):
Steep %K Slope: Rapid momentum change, strong directional conviction, potential for extended moves but also increased reversal risk
Gradual %K Slope: Steady momentum development, sustainable trends more likely, lower probability of sharp reversals
Flat or Horizontal %K: Momentum stalling, potential reversal or consolidation ahead, wait for directional break before committing
%K Oscillation Within Range: Indicates ranging market, sideways price action, better suited for range-trading strategies than trend following
🎯 STRATEGIC APPLICATIONS
Mean Reversion Strategy (Range-Bound Markets):
Identify ranging market conditions using price action or Bollinger Bands
Wait for Stochastic to reach extreme zones (above 80 for overbought, below 20 for oversold)
Enter counter-trend position when %K crosses %D in extreme zone (sell on bearish cross above 80, buy on bullish cross below 20)
Set profit targets near opposite extreme or midline (50 level)
Use tight stop-loss above recent swing high/low to protect against breakout scenarios
Exit when Stochastic reaches opposite extreme or %K crosses %D in opposite direction
Trend Following with Momentum Confirmation:
Identify primary trend direction using higher timeframe analysis or moving averages
Wait for Stochastic pullback to oversold zone (<20) in uptrend or overbought zone (>80) in downtrend
Enter in trend direction when %K crosses %D confirming momentum shift (bullish cross in uptrend, bearish cross in downtrend)
Use wider stops to accommodate normal trend volatility
Add to position on subsequent pullbacks showing similar Stochastic pattern
Exit when Stochastic shows opposite extreme with failed cross or bearish/bullish divergence
Divergence-Based Reversal Strategy:
Scan for divergence between price and Stochastic at swing highs/lows
Confirm divergence with at least two price pivots showing divergent Stochastic readings
Wait for %K to cross %D in direction of anticipated reversal as entry trigger
Enter position in divergence direction with stop beyond recent swing extreme
Target profit at key support/resistance levels or Fibonacci retracements
Scale out as Stochastic reaches opposite extreme zone
Multi-Timeframe Momentum Alignment:
Analyze Stochastic on higher timeframe (4H or Daily) for primary trend bias
Switch to lower timeframe (1H or 15M) for precise entry timing
Only take trades where lower timeframe Stochastic signal aligns with higher timeframe momentum direction
Higher timeframe Stochastic in bullish zone (>50) = only take long entries on lower timeframe
Higher timeframe Stochastic in bearish zone (<50) = only take short entries on lower timeframe
Exit when lower timeframe shows counter-signal or higher timeframe momentum reverses
Zone Transition Strategy:
Monitor Stochastic for transitions between zones (oversold to neutral, neutral to overbought, etc.)
Enter long when Stochastic crosses above 20 (exiting oversold), signaling momentum shift from bearish to neutral/bullish
Enter short when Stochastic crosses below 80 (exiting overbought), signaling momentum shift from bullish to neutral/bearish
Use zone midpoint (50) as dynamic support/resistance for position management
Trail stops as Stochastic advances through favorable zones
Exit when Stochastic fails to maintain momentum and reverses back into prior zone
📋 DETAILED PARAMETER CONFIGURATION
%K Length (Default: 14):
Lower Values (5-9): Highly sensitive to price changes, generates more frequent signals, increased false signals in choppy markets, suitable for very short-term trading and scalping
Standard Values (10-14): Balanced sensitivity and reliability, traditional default (14) widely used,适合 swing trading and intraday strategies
Higher Values (15-21): Reduced sensitivity, smoother oscillations, fewer but potentially more reliable signals, better for position trading and lower timeframe noise reduction
Very High Values (21+): Slow response, long-term momentum measurement, fewer trading signals, suitable for weekly or monthly analysis
%K Smoothing (Default: 3):
Value 1: Fast Stochastic, uses raw %K calculation without additional smoothing, most responsive to price changes, generates earliest signals with higher noise
Value 3: Slow Stochastic (default), traditional smoothing level, reduces false signals while maintaining good responsiveness, widely accepted standard
Values 5-7: Very slow response, extremely smooth oscillations, significantly reduced whipsaws but delayed entry/exit timing
Recommendation: Default value 3 suits most trading scenarios, active short-term traders may use 1, conservative long-term positions use 5+
%D Smoothing (Default: 3):
Lower Values (1-2): Signal line closely follows %K, frequent crossover signals, useful for active trading but requires strict filtering
Standard Value (3): Traditional setting providing balanced signal line behavior, optimal for most trading applications
Higher Values (4-7): Smoother signal line, fewer crossover signals, reduced whipsaws but slower confirmation, better for trend trading
Very High Values (8+): Signal line becomes slow-moving reference, crossovers rare and highly significant, suitable for long-term position changes only
Smoothing Type Algorithm Selection:
For Trending Markets:
ZLEMA, DEMA, TEMA: Reduced lag for faster trend entry, quick response to momentum shifts, suitable for strong directional moves
HMA, ALMA: Good balance of smoothness and responsiveness, effective for clean trend following without excessive noise
EMA: Classic choice for trending markets, faster than SMA while maintaining reasonable stability
For Ranging/Choppy Markets:
Kalman Filter, Super Smoother: Superior noise filtering, reduces false signals in sideways action, helps identify genuine reversal points
Laguerre Filters: Smooth oscillations with adjustable lag, excellent for mean reversion strategies in ranges
T3, TMA: Very smooth output, filters out market noise effectively, clearer extreme zone identification
For Adaptive Market Conditions:
KAMA: Automatically adjusts to market efficiency, fast in trends and slow in congestion, reduces whipsaws during transitions
FRAMA: Adapts to fractal market structure, responsive during directional moves, conservative during uncertainty
McGinley Dynamic: Self-adjusting smoothing, follows price naturally, minimizes lag in trending markets while filtering noise in ranges
For Conservative Long-Term Analysis:
SMA: Traditional choice, predictable behavior, widely understood characteristics
RMA (Wilder's): Smooth oscillations, reduced sensitivity to outliers, consistent behavior across market conditions
Laguerre Binomial Filter: Extremely smooth output, ideal for weekly/monthly timeframe analysis, eliminates short-term noise completely
Source Selection:
Close (Default): Standard choice using closing prices, most common and widely tested
HLC3 or OHLC4: Incorporates more price information, reduces impact of sudden spikes or gaps, smoother oscillator behavior
HL2: Midpoint of high-low range, emphasizes intrabar volatility, useful for markets with wide intraday ranges
Custom Source: Can use other indicators as input (e.g., Heikin Ashi close, smoothed price), creates derivative momentum indicators
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Responsiveness Characteristics:
Traditional SMA-Based Stochastic:
Fixed lag regardless of market conditions, consistent delay of approximately (K Smoothing + D Smoothing) / 2 periods
Equal treatment of trending and ranging markets, no adaptation to volatility changes
Predictable behavior but suboptimal in varying market regimes
Enhanced Version with Adaptive Algorithms:
KAMA and FRAMA reduce lag by up to 40-60% in strong trends compared to SMA while maintaining similar smoothness in ranges
ZLEMA and T3 provide near-zero lag characteristics for early entry signals with acceptable noise levels
Kalman Filter and Super Smoother offer superior noise rejection, reducing false signals in choppy conditions by estimations of 30-50% compared to SMA
Performance improvements vary by algorithm selection and market conditions
Signal Quality Improvements:
Adaptive algorithms help reduce whipsaw trades in ranging markets by adjusting sensitivity dynamically
Advanced filters (Kalman, Laguerre, Super Smoother) provide clearer extreme zone readings for mean reversion strategies
Zero-lag methods (ZLEMA, DEMA, TEMA) generate earlier crossover signals in trending markets for improved entry timing
Smoother algorithms (T3, Laguerre Binomial) reduce false extreme zone touches for more reliable overbought/oversold signals
Comparison with Standard Implementations:
Versus Basic Stochastic: Enhanced version offers 21 smoothing options versus single SMA, allowing optimization for specific market characteristics and trading styles
Versus RSI: Stochastic provides range-bound measurement (0-100) with clear extreme zones, RSI measures momentum speed, Stochastic offers clearer visual overbought/oversold identification
Versus MACD: Stochastic bounded oscillator suitable for mean reversion, MACD unbounded indicator better for trend strength, Stochastic excels in range-bound and oscillating markets
Versus CCI: Stochastic has fixed bounds (0-100) for consistent interpretation, CCI unbounded with variable extremes, Stochastic provides more standardized extreme readings across different instruments
Flexibility Advantages:
Single indicator adaptable to multiple strategies through algorithm selection rather than requiring different indicator variants
Ability to optimize smoothing characteristics for specific instruments (e.g., smoother for crypto volatility, faster for forex trends)
Multi-timeframe analysis with consistent algorithm across timeframes for coherent momentum picture
Backtesting capability with algorithm as optimization parameter for strategy development
Limitations and Considerations:
Increased complexity from multiple algorithm choices may lead to over-optimization if parameters are curve-fitted to historical data
Adaptive algorithms (KAMA, FRAMA) have adjustment periods during market regime changes where signals may be less reliable
Zero-lag algorithms sacrifice some smoothness for responsiveness, potentially increasing noise sensitivity in very choppy conditions
Performance characteristics vary significantly across algorithms, requiring understanding and testing before live implementation
Like all oscillators, Stochastic can remain in extreme zones for extended periods during strong trends, generating premature reversal signals
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to provide traders with enhanced flexibility in momentum analysis. The Stochastic Oscillator has limitations and should not be used as the sole basis for trading decisions.
Important Considerations:
Algorithm performance varies with market conditions - no single smoothing method is optimal for all scenarios
Extreme zone signals (overbought/oversold) indicate potential reversal areas but not guaranteed turning points, especially in strong trends
Crossover signals may generate false entries during sideways choppy markets regardless of smoothing algorithm
Divergence patterns require confirmation from price action or additional indicators before trading
Past indicator characteristics and backtested results do not guarantee future performance
Always combine Stochastic analysis with proper risk management, position sizing, and multi-indicator confirmation
Test selected algorithm on historical data of specific instrument and timeframe before live trading
Market regime changes may require algorithm adjustment for optimal performance
The enhanced smoothing options are intended to provide tools for optimizing the indicator's behavior to match individual trading styles and market characteristics, not to create a perfect predictive tool. Responsible usage includes understanding the mathematical properties of selected algorithms and their appropriate application contexts.
SCTI - D14SCTI - D14 Comprehensive Technical Analysis Suite
English Description
SCTI D14 is an advanced multi-component technical analysis indicator designed for professional traders and analysts. This comprehensive suite combines multiple analytical tools into a single, powerful indicator that provides deep market insights across various timeframes and methodologies.
Core Components:
1. EMA System (Exponential Moving Averages)
13 customizable EMA lines with periods ranging from 8 to 2584
Fibonacci-based periods (8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584)
Color-coded visualization for easy trend identification
Individual toggle controls for each EMA line
2. TFMA (Multi-Timeframe Moving Averages)
Cross-timeframe analysis with 3 independent EMA calculations
Real-time labels showing trend direction and price relationships
Customizable timeframes for each moving average
Percentage deviation display from current price
3. PMA (Precision Moving Average Cloud)
7-layer moving average system with customizable periods
Fill areas between moving averages for trend visualization
Support and resistance zone identification
Dynamic color-coded trend clouds
4. VWAP (Volume Weighted Average Price)
Multiple anchor points (Session, Week, Month, Quarter, Year, Earnings, Dividends, Splits)
Standard deviation bands for volatility analysis
Automatic session detection and anchoring
Statistical price level identification
5. Advanced Divergence Detector
12 technical indicators for divergence analysis (MACD, RSI, Stochastic, CCI, Williams %R, Bias, Momentum, OBV, VW-MACD, CMF, MFI, External)
Regular and hidden divergences detection
Bullish and bearish signals with visual confirmation
Customizable sensitivity and filtering options
Real-time alerts for divergence formations
6. Volume Profile & Node Analysis
Comprehensive volume distribution analysis
Point of Control (POC) identification
Value Area High/Low (VAH/VAL) calculations
Volume peaks and troughs detection
Support and resistance levels based on volume
7. Smart Money Concepts
Market structure analysis with Break of Structure (BOS) and Change of Character (CHoCH)
Internal and swing structure detection
Equal highs and lows identification
Fair Value Gaps (FVG) detection and visualization
Liquidity zones and institutional flow analysis
8. Trading Sessions
9 major trading sessions (Asia, Sydney, Tokyo, Shanghai, Hong Kong, Europe, London, New York, NYSE)
Real-time session status and countdown timers
Session volume and performance tracking
Customizable session boxes and labels
Statistical session analysis table
Key Features:
Modular Design: Enable/disable any component independently
Real-time Analysis: Live updates with market data
Multi-timeframe Support: Works across all chart timeframes
Customizable Alerts: Set alerts for any detected pattern or signal
Professional Visualization: Clean, organized display with customizable colors
Performance Optimized: Efficient code for smooth chart performance
Use Cases:
Trend Analysis: Identify market direction using multiple EMA systems
Entry/Exit Points: Use divergences and structure breaks for timing
Risk Management: Utilize volume profiles and session analysis for better positioning
Multi-timeframe Analysis: Confirm signals across different timeframes
Institutional Analysis: Track smart money flows and market structure
Perfect For:
Day traders seeking comprehensive market analysis
Swing traders needing multi-timeframe confirmation
Professional analysts requiring detailed market structure insights
Algorithmic traders looking for systematic signal generation
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中文描述
SCTI - D14是一个先进的多组件技术分析指标，专为专业交易者和分析师设计。这个综合套件将多种分析工具整合到一个强大的指标中，在各种时间框架和方法论中提供深度市场洞察。
核心组件：
1. EMA系统（指数移动平均线）
13条可定制EMA线，周期从8到2584
基于斐波那契的周期（8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584）
颜色编码可视化，便于趋势识别
每条EMA线的独立切换控制
2. TFMA（多时间框架移动平均线）
跨时间框架分析，包含3个独立的EMA计算
实时标签显示趋势方向和价格关系
每个移动平均线的可定制时间框架
显示与当前价格的百分比偏差
3. PMA（精密移动平均云）
7层移动平均系统，周期可定制
移动平均线间填充区域用于趋势可视化
支撑阻力区域识别
动态颜色编码趋势云
4. VWAP（成交量加权平均价格）
多个锚点（交易时段、周、月、季、年、财报、分红、拆股）
标准差带用于波动性分析
自动时段检测和锚定
统计价格水平识别
5. 高级背离检测器
12个技术指标用于背离分析（MACD、RSI、随机指标、CCI、威廉姆斯%R、Bias、动量、OBV、VW-MACD、CMF、MFI、外部指标）
常规和隐藏背离检测
看涨看跌信号配视觉确认
可定制敏感度和过滤选项
背离形成的实时警报
6. 成交量分布与节点分析
全面的成交量分布分析
控制点（POC）识别
价值区域高/低点（VAH/VAL）计算
成交量峰值和低谷检测
基于成交量的支撑阻力水平
7. 聪明钱概念
市场结构分析，包括结构突破（BOS）和结构转变（CHoCH）
内部和摆动结构检测
等高等低识别
公允价值缺口（FVG）检测和可视化
流动性区域和机构资金流分析
8. 交易时区
9个主要交易时段（亚洲、悉尼、东京、上海、香港、欧洲、伦敦、纽约、纽交所）
实时时段状态和倒计时器
时段成交量和表现跟踪
可定制时段框和标签
统计时段分析表格
主要特性：
模块化设计：可独立启用/禁用任何组件
实时分析：随市场数据实时更新
多时间框架支持：适用于所有图表时间框架
可定制警报：为任何检测到的模式或信号设置警报
专业可视化：清洁、有序的显示界面，颜色可定制
性能优化：高效代码确保图表流畅运行
使用场景：
趋势分析：使用多重EMA系统识别市场方向
入场/出场点：利用背离和结构突破进行时机选择
风险管理：利用成交量分布和时段分析进行更好定位
多时间框架分析：在不同时间框架间确认信号
机构分析：跟踪聪明钱流向和市场结构
适用于：
寻求全面市场分析的日内交易者
需要多时间框架确认的摆动交易者
需要详细市场结构洞察的专业分析师
寻求系统化信号生成的算法交易者
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action
1. Introduction
1.1 Overview
ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active.
The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured:
import TradingView/ta/10 as tvta
// Determine lower timeframe string based on user choice and chart resolution
string lower_tf_breakout = use_custom_tf_input ? custom_tf_input :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
// Request up/down volume (both positive)
= tvta.requestUpAndDownVolume(lower_tf_breakout)
Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity.
Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate.
Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history.
Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”)
2. Price‑Structure Backbone
Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations.
2.1 What it draws
• Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded.
• Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly.
• Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels.
• Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick.
2.2 Key settings
• length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels.
• pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings.
• point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded.
• label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price.
• Styling inputs for trend lines, horizontal lines and labels (color, width and line style).
Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots.
These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle.
The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable.
3. Breakout Module
3.1 Concept
This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled.
3.2 Inputs
• lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly.
• vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout.
• rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution.
• ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases).
• use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe.
• Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width.
3.3 Detection logic
1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume.
2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window.
3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive.
4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history.
5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1).
6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector.
Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move.
Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold.
4. Market Phase Module (Volume Only)
4.1 Concept
Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table.
4.2 Inputs
• phase_period_len: Number of bars over which to compute sums and ratios for phase detection.
• phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume.
• strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation).
• Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles.
• show_phase_module: Toggles the entire phase detection subsystem.
• show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected.
4.3 Detection logic
The module computes three families of statistics over the volume window defined by phase_period_len:
1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends.
2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction.
3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues.
The algorithm then combines these signals:
• For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case.
• For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category.
If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” .
4.4 Outputs
• Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral).
• On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences.
Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began.
Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window.
5. OB/OS Spike Module
5.1 What overbought/oversold means here
In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate.
5.2 Inputs
• minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print.
• syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals.
• Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike.
• Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable.
• Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width.
5.3 Detection logic
1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos.
2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS.
3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold).
4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought.
5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line.
Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels.
Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow.
6. Buyer/Seller Trap Module
6.1 Concept
A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps.
6.2 Inputs
• trap_lookback_len: Window length used to rank extremes and detect sweeps.
• trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep.
• trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.)
• trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed.
• Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps.
• Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart.
6.3 Scoring logic
The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped):
1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick.
2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick.
3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand.
4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa.
5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average.
The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars.
Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label.
Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range.
7. Sharp Move Module
7.1 Concept
Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation.
7.2 Inputs
• sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels.
• sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window.
• sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax.
• sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks.
• sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range).
• sharpScoreRisk: Minimum number of conditions that must be true to print a risk label.
• sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation.
• sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution).
• Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves.
• Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn.
7.3 Conditions (six per side)
For each side, the indicator computes six boolean conditions and sums them to form a score:
1. Dominance (instant and cumulative):
– Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume.
– Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks).
2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish).
3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window.
4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range).
5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile.
6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed.
Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores.
7.4 Scoring and labels
• Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar.
• Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1).
• Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled.
Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move.
Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window.
8. Market‑Maker / Spread‑Capture Module
8.1 Concept
Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets.
8.2 Inputs
• scalpLookback: Window length used to compute volume averages.
• scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple.
• scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement.
• scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%.
• Label settings: ATR length, multiplier, size, colors, connector style and width.
• Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels.
8.3 Signal
When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled.
Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window.
9. Money Flow Module
9.1 Concept
To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow.
9.2 Inputs
• mf_period_len_mf: Number of bars used for summing buy and sell dollars.
• Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width.
• Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed.
9.3 Calculations
• Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $.
• Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum().
• Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate.
• Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences.
Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context.
In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period.
10. Info Table
10.1 Purpose
When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active.
10.2 Symbols
• ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money.
• MA — Moving average. In the table it shows the average value of a series over the lookback period.
• Σ (Sigma) — Cumulative sum over the chosen lookback period.
• Δ (Delta) — Difference between buy and sell values.
• B / S — Buyer and seller share of total volume, expressed as percentages.
• Ref. Price — Reference price for breakout calculations, based on the latest pivot.
• Status — Indicates whether a breakout condition is currently active (True) or has failed.
10.3 Row definitions
1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period.
2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity.
3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period.
4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume.
5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period.
6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume.
7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more.
8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed.
9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral.
10. Money Flow – The final rows display dollar amounts and status:
– ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period.
– ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum.
– Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively.
– Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral.
– Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral.
The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out).
11. Conclusion & Final Remarks
This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart.
A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window.
Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
Guitar Hero [theUltimator5]The Guitar Hero indicator transforms traditional oscillator signals into a visually engaging, game-like display reminiscent of the popular Guitar Hero video game. Instead of standard line plots, this indicator presents oscillator values as colored segments or blocks, making it easier to quickly identify market conditions at a glance.
Choose from 8 different technical oscillators:
RSI (Relative Strength Index)
Stochastic %K
Stochastic %D
Williams %R
CCI (Commodity Channel Index)
MFI (Money Flow Index)
TSI (True Strength Index)
Ultimate Oscillator
Visual Display Modes
1) Boxes Mode : Creates distinct rectangular boxes for each bar, providing a clean, segmented appearance. (default)
This visual display is limited by the amount of box plots that TradingView allows on each indictor, so it will only plot a limited history. If you want to view a similar visual display that has minor breaks between boxes, then use the fill mode.
2) Fill Mode : Uses filled areas between plot boundaries.
Use this mode when you want to view the plots further back in history without the strict drawing limitations.
Five-Level Color-Coded System
The indicator normalizes all oscillator values to a 0-100 scale and categorizes them into five distinct levels:
Level 1 (Red): Very Oversold (0-19)
Level 2 (Orange): Oversold (20-29)
Level 3 (Yellow): Neutral (30-70)
Level 4 (Aqua): Overbought (71-80)
Level 5 (Lime): Very Overbought (81-100)
Customization Options
Signal Parameters
Signal Length: Primary period for oscillator calculation (default: 14)
Signal Length 2: Secondary period for Stochastic %D and TSI (default: 3)
Signal Length 3: Tertiary period for TSI calculation (default: 25)
Display Controls
Show Horizontal Reference Lines: Toggle grid lines for better level identification
Show Information Table: Display current signal type, value, and normalized value
Table Position: Choose from 9 different screen positions for the info table
Display Mode: Switch between Boxes and Fills visualization
Max Bars to Display: Control how many historical bars to show (50-450 range)
Normalization Process
The indicator automatically normalizes different oscillator ranges to a consistent 0-100 scale:
Williams %R: Converts from -100/0 range to 0-100
CCI: Maps typical -300/+300 range to 0-100
TSI: Transforms -100/+100 range to 0-100
Other oscillators: Already use 0-100 scale (RSI, Stochastic, MFI, Ultimate Oscillator)
This was designed as an educational tool
The gamified approach makes learning about oscillators more engaging for new traders.
AI-Powered ScalpMaster Pro [By TraderMan]🧠 AI-Powered ScalpMaster Pro How It Works
📊 What Is the Indicator and What Does It Do?
🧠 AI-Powered ScalpMaster Pro is a powerful technical analysis tool designed for scalping (short-term, fast-paced trading) in financial markets such as forex, crypto, or stocks. It combines multiple technical indicators (RSI, MACD, Stochastic, Momentum, EMA, SuperTrend, CCI, and OBV) to identify market trends and generate AI-driven buy (🟢) or sell (🔴) signals. The goal is to help traders seize profitable scalping opportunities with quick and precise decisions. 🚀
Key Features:
🧠 AI-Driven Logic: Analyzes signals from multiple indicators to produce reliable trend signals.
📈 Signal Strength: Displays buy (bull) and sell (bear) signal strength as percentages.
✅ Success Rate: Tracks the performance of the last 5 trades and calculates the success rate.
🎯 Entry, TP, and SL Levels: Automatically sets entry points, take profit (TP), and stop loss (SL) levels.
📏 EMA Zone: Analyzes price movement around the EMA 200 to confirm trend direction.
⚙️ How Does It Work?
The indicator uses a scoring system by combining the following technical indicators:
RSI (14): Evaluates whether the price is in overbought or oversold zones.
MACD (12, 26, 9): Analyzes trend direction and momentum.
Stochastic (%K): Measures the speed of price movement.
Momentum: Checks the price change over the last 10 bars.
EMA 200: Determines the long-term trend direction.
SuperTrend: Tracks trends based on volatility.
CCI (20): Measures price deviation from its normal range.
OBV ROC: Analyzes volume changes.
Each indicator generates a buy (bull) or sell (bear) signal. If 6 or more indicators align in the same direction (e.g., bullScore >= 6 for buy), the indicator produces a strong trend signal:
📈 Strong Buy Signal: bullScore >= 6 and bullScore > bearScore.
📉 Strong Sell Signal: bearScore >= 6 and bearScore > bullScore.
🔸 Neutral: No dominant direction.
Additionally, the EMA Zone feature confirms the trend based on the price’s position relative to a zone around the EMA 200:
Price above the zone and sufficiently distant → Uptrend (UP). 🟢
Price below the zone and sufficiently distant → Downtrend (DOWN). 🔴
Price within the zone → Neutral. 🔸
🖥️ Display on the Chart
Table: A table in the top-right corner shows the status of all indicators (✅ Buy / ❌ Sell), signal strength (as %), success rate, and results of the last 5 trades.
Lines and Labels:
🎯 Entry Level: A gray line at the price level when a new signal is generated.
🟢 TP (Take Profit): A green line showing the take-profit level.
🔴 SL (Stop Loss): A red line showing the stop-loss level.
EMA Zone: The EMA 200 and its surrounding colored zone visualize the trend direction (green: uptrend, red: downtrend, gray: neutral).
📝 How to Use It?
Platform Setup:
Add the indicator to the TradingView platform.
Customize settings as needed (e.g., EMA length, risk/reward ratio).
Monitoring Signals:
Check the table: Look for 📈 STRONG BUY or 📉 STRONG SELL signals to prepare for a trade.
AI Text: Trust signals more when it says "🧠 FULL CONFIDENCE" (success rate ≥ 50%). Be cautious if it says "⚠️ LOW CONFIDENCE."
Entering a Position:
🟢 Buy Signal:
Table shows "📈 STRONG BUY" and bullScore >= 6.
Price is above the EMA Zone (green zone).
Entry: Current price (🎯 entry line).
TP: 2% above the entry price (🟢 TP line).
SL: 1% below the entry price (🔴 SL line).
🔴 Sell Signal:
Table shows "📉 STRONG SELL" and bearScore >= 6.
Price is below the EMA Zone (red zone).
Entry: Current price (🎯 entry line).
TP: 2% below the entry price (🟢 TP line).
SL: 1% above the entry price (🔴 SL line).
Position Management:
If the price hits TP, the trade closes profitably (✅ Successful).
If the price hits SL, the trade closes with a loss (❌ Failed).
Results are updated in the "Last 5 Trades" section of the table.
Risk Management:
Default risk/reward ratio is 1:2 (1% risk, 2% reward).
Always adjust position size based on your capital.
Consider smaller lot sizes for "⚠️ LOW CONFIDENCE" signals.
💡 Tips
Timeframe: Use 1-minute, 5-minute, or 15-minute charts for scalping.
Market Selection: Works best in volatile markets (e.g., BTC/USD, EUR/USD).
Confirmation: Ensure the EMA Zone trend aligns with the signal.
Discipline: Stick to TP and SL levels, avoid emotional decisions.
⚠️ Warnings
No indicator is 100% accurate. Always use additional analysis (e.g., support/resistance).
Be cautious during high-volatility periods (e.g., news events).
The success rate is based on past performance and does not guarantee future results.
SCTI V28Indicator Overview | 指标概述
English: SCTI V28 (Smart Composite Technical Indicator) is a multi-functional composite technical analysis tool that integrates various classic technical analysis methods. It contains 7 core modules that can be flexibly configured to show or hide components based on traders' needs, suitable for various trading styles and market conditions.
中文: SCTI V28 (智能复合技术指标) 是一款多功能复合型技术分析指标，整合了多种经典技术分析工具于一体。该指标包含7大核心模块，可根据交易者的需求灵活配置显示或隐藏各个组件，适用于多种交易风格和市场环境。
Main Functional Modules | 主要功能模块
1. Basic Indicator Settings | 基础指标设置
English:
EMA Display: 13 configurable EMA lines (default shows 8/13/21/34/55/144/233/377/610/987/1597/2584 periods)
PMA Display: 11 configurable moving averages with multiple MA types (ALMA/EMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
VWAP Display: Volume Weighted Average Price indicator
Divergence Indicator: Detects divergences across 12 technical indicators
ATR Stop Loss: ATR-based stop loss lines
Volume SuperTrend AI: AI-powered super trend indicator
中文:
EMA显示：13条可配置EMA均线，默认显示8/13/21/34/55/144/233/377/610/987/1597/2584周期
PMA显示：11条可配置移动平均线，支持多种MA类型(ALMA/EMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
VWAP显示：成交量加权平均价指标
背离指标：12种技术指标的背离检测系统
ATR止损：基于ATR的止损线
Volume SuperTrend AI：基于AI预测的超级趋势指标
2. EMA Settings | EMA设置
English:
13 independent EMA lines, each configurable for visibility and period length
Default shows 21/34/55/144/233/377/610/987/1597/2584 period EMAs
Customizable colors and line widths for each EMA
中文:
13条独立EMA均线，每条均可单独配置显示/隐藏和周期长度
默认显示21/34/55/144/233/377/610/987/1597/2584周期的EMA
每条EMA可设置不同颜色和线宽
3. PMA Settings | PMA设置
English:
11 configurable moving averages, each with:
Selectable types (default EMA, options: ALMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
Independent period settings (12-1056)
Special ALMA parameters (offset and sigma)
Configurable data source and plot offset
Support for fill areas between MAs
Price lines and labels can be added
中文:
11条可配置移动平均线，每条均可：
选择不同类型(默认EMA，可选ALMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
独立设置周期长度(12-1056)
设置ALMA的特殊参数(偏移量和sigma)
配置数据源和绘图偏移
支持MA之间的填充区域显示
可添加价格线和标签
4. VWAP Settings | VWAP设置
English:
Multiple anchor period options (Session/Week/Month/Quarter/Year/Decade/Century/Earnings/Dividends/Splits)
3 configurable standard deviation bands
Option to hide on daily and higher timeframes
Configurable data source and offset settings
中文:
多种锚定周期选择(会话/周/月/季/年/十年/世纪/财报/股息/拆股)
3条可配置标准差带
可选择在日线及以上周期隐藏
支持数据源选择和偏移设置
5. Divergence Indicator Settings | 背离指标设置
English:
12 detectable indicators: MACD, MACD Histogram, RSI, Stochastic, CCI, Momentum, OBV, VWmacd, Chaikin Money Flow, MFI, Williams %R, External Indicator
4 divergence types: Regular Bullish/Bearish, Hidden Bullish/Bearish
Multiple display options: Full name/First letter/Hide indicator name
Configurable parameters: Pivot period, data source, maximum bars checked, etc.
Alert functions: Independent alerts for each divergence type
中文:
检测12种指标：MACD、MACD柱状图、RSI、随机指标、CCI、动量、OBV、VWmacd、Chaikin资金流、MFI、威廉姆斯%R、外部指标
4种背离类型：正/负常规背离，正/负隐藏背离
多种显示选项：完整名称/首字母/不显示指标名称
可配置参数：枢轴点周期、数据源、最大检查柱数等
警报功能：各类背离的独立警报
6. ATR Stop Loss Settings | ATR止损设置
English:
Configurable ATR length (default 13)
4 smoothing methods (RMA/SMA/EMA/WMA)
Adjustable multiplier (default 1.618)
Displays long and short stop loss lines
中文:
可配置ATR长度(默认13)
4种平滑方法(RMA/SMA/EMA/WMA)
可调乘数(默认1.618)
显示多头和空头止损线
7. Volume SuperTrend AI Settings | Volume SuperTrend AI设置
English:
AI Prediction:
Configurable neighbors (1-100) and data points (1-100)
Price trend length and prediction trend length settings
SuperTrend Parameters:
Length (default 3)
Factor (default 1.515)
5 MA source options (SMA/EMA/WMA/RMA/VWMA)
Signal Display:
Trend start signals (circle markers)
Trend confirmation signals (triangle markers)
6 Alerts: Various trend start and confirmation signals
中文:
AI预测功能：
可配置邻居数(1-100)和数据点数(1-100)
价格趋势长度和预测趋势长度设置
SuperTrend参数：
长度(默认3)
因子(默认1.515)
5种MA源选择(SMA/EMA/WMA/RMA/VWMA)
信号显示：
趋势开始信号(圆形标记)
趋势确认信号(三角形标记)
6种警报：各类趋势开始和确认信号
Usage Recommendations | 使用建议
English:
Trend Analysis: Use EMA/PMA combinations to determine market trends, with long-period EMAs (e.g., 144/233) as primary trend references
Divergence Trading: Look for potential reversals using price-indicator divergences
Stop Loss Management: Use ATR stop loss lines for risk management
AI Assistance: Volume SuperTrend AI provides machine learning-based trend predictions
Multiple Timeframes: Verify signals across different timeframes
中文:
趋势分析：使用EMA/PMA组合判断市场趋势，长周期EMA(如144/233)作为主要趋势参考
背离交易：结合价格与指标的背离寻找潜在反转点
止损设置：利用ATR止损线管理风险
AI辅助：Volume SuperTrend AI提供基于机器学习的趋势预测
多时间框架：建议在不同时间框架下验证信号
Parameter Configuration Tips | 参数配置技巧
English:
For short-term trading: Focus on 8-55 period EMAs and shorter divergence detection periods
For long-term investing: Use 144-2584 period EMAs with longer detection parameters
In ranging markets: Disable some EMAs, mainly rely on VWAP and divergence indicators
In trending markets: Enable more EMAs and SuperTrend AI
中文:
对于短线交易：可重点关注8-55周期的EMA和较短的背离检测周期
对于长线投资：建议使用144-2584周期的EMA和较长的检测参数
在震荡市：可关闭部分EMA，主要依靠VWAP和背离指标
在趋势市：可启用更多EMA和SuperTrend AI
Update Log | 更新日志
English:
V28 main updates:
Added Volume SuperTrend AI module
Optimized divergence detection algorithm
Added more EMA period options
Improved UI and parameter grouping
中文:
V28版本主要更新：
新增Volume SuperTrend AI模块
优化背离检测算法
增加更多EMA周期选项
改进用户界面和参数分组
Final Note | 最后说明
English: This indicator is suitable for technical traders with some experience. We recommend practicing with demo trading to familiarize yourself with all features before live trading.
中文: 该指标适合有一定经验的技术分析交易者使用，建议先通过模拟交易熟悉各项功能后再应用于实盘。
Custom Strategy Builder Raad V1This indicator is an advanced trading strategy builder that combines multiple technical indicators and analysis tools into a single script. Below is a simplified breakdown of its key components and functionalities.
Key Features & Components
1. Core Indicators
Moving Averages (EMA, SMA, WMA, HMA, VWMA) – Multiple types with customizable lengths.
Range Filter – A volatility-based trend filter.
SuperTrend – A trend-following indicator using ATR.
Half Trend – Another trend-following indicator.
Ichimoku Cloud – A comprehensive trend and support/resistance system.
2. Trend Indicators
Bollinger Bands – Volatility-based price channels.
MACD – Moving Average Convergence Divergence for momentum.
Parabolic SAR – A trailing stop indicator for trend direction.
Donchian Channel – Identifies breakout levels based on recent highs/lows.
3. Momentum Indicators
RSI (Relative Strength Index) – Measures overbought/oversold conditions.
Stochastic Oscillator – Another momentum indicator for reversals.
CCI (Commodity Channel Index) – Detects cyclical trends.
Awesome Oscillator (AO) – A histogram-based momentum tool.
4. Additional Analysis Tools
Fibonacci Retracement – Key support/resistance levels based on Fibonacci ratios.
Pivot Points – Calculates intraday support/resistance levels.
Supply/Demand Zones – Highlights key accumulation/distribution areas.
Volume Analysis – Includes VWAP and volume-based signals.
5. Dashboard & Customization
Switch Board – Enables/disables indicators on the chart.
Signal Filters – Adjusts confirmation rules for entries/exits.
Visual Customization – Change colors, line styles, and sizes.
How It Works
Leading Indicator – The primary signal generator (e.g., Range Filter, RSI, MACD).
Confirmation Indicators – Additional filters to validate signals (e.g., EMA cross, volume, trend strength).
Signal Expiry – Defines how long a signal remains valid before resetting.
Dashboard Display – Shows active signals and market conditions.
Best Use Cases
✅ Multi-Indicator Strategies – Combines multiple signals into one system.
✅ Trend & Momentum Trading – Works well for swing and intraday trading.
✅ Customizable Alerts – Can trigger buy/sell signals based on user-defined rules.
This indicator is ideal for traders who want a fully customizable and multi-strategy approach without manually overlaying multiple indicators.
هذا المؤشر هو أداة متقدمة لبناء استراتيجيات التداول تحتوي على مجموعة كبيرة من المؤشرات الفنية وأدوات التحليل. إليك شرح مبسط لمكوناته الرئيسية:
المكونات الرئيسية:
1. المؤشرات الأساسية:
المتوسطات المتحركة (EMA, SMA, WMA, HMA, VWMA): تسمح باختيار أنواع مختلفة من المتوسطات المتحركة بأطوال مختلفة.
Range Filter: مرشح يعتمد على مدى السعر لتحديد الاتجاه.
SuperTrend: مؤشر اتجاهي يعتمد على ATR.
Half Trend: مؤشر اتجاهي آخر.
Ichimoku Cloud: نظام إيشيموكو الكلاسيكي.
2. مؤشرات الاتجاه:
Bollinger Bands: نطاقات بولينجر.
MACD: مؤشر تقارب وتباعد المتوسطات المتحركة.
Parabolic SAR: مؤشر SAR القطعي المكافئ.
Donchian Channel: قناة دونشيان لتحديد القمم والقيعان.
3. مؤشرات الزخم:
RSI: مؤشر القوة النسبية.
Stochastic: مؤشر ستوكاستيك.
CCI: مؤشر قناة السلع.
Awesome Oscillator: مؤشر الزخم.
4. أدوات التحليل الأخرى:
Fibonacci Retracement: مستويات فيبوناتشي للتصحيح.
Pivot Points: نقاط محورية.
Supply/Demand Zones: مناطق العرض والطلب.
Volume Analysis: تحليل الحجم.
5. لوحة التحكم:
تسمح بتفعيل/تعطيل المؤشرات المختلفة.
تخصيص ألوان وعرض الخطوط.
ضبط معايير الإشارات.
طريقة العمل:
يحدد المؤشر إشارات شراء/بيع بناءً على تقاطعات المؤشرات المختلفة.
يمكن استخدام مؤشر رئيسي (Leading Indicator) مع مؤشرات تأكيد (Confirmation Indicators).
يوفر خيارات لتخصيص فترة انتهاء صلاحية الإشارة وطريقة العرض.
الاستخدام:
للمتداولين المتقدمين الذين يرغبون في بناء استراتيجيات معقدة.
يمكن استخدامه للتحليل الفني متعدد الأطر الزمنية.
يوفر مرونة كبيرة في تخصيص المؤشرات حسب احتياجات المستخدم.
3D Surface Modeling [PhenLabs]📊 3D Surface Modeling
Version: PineScript™ v6
📌 Description
The 3D Surface Modeling indicator revolutionizes technical analysis by generating three-dimensional visualizations of multiple technical indicators across various timeframes. This advanced analytical tool processes and renders complex indicator data through a sophisticated matrix-based calculation system, creating an intuitive 3D surface representation of market dynamics.
The indicator employs array-based computations to simultaneously analyze multiple instances of selected technical indicators, mapping their behavior patterns across different temporal dimensions. This unique approach enables traders to identify complex market patterns and relationships that may be invisible in traditional 2D charts.
🚀 Points of Innovation
Matrix-Based Computation Engine: Processes up to 500 concurrent indicator calculations in real-time
Dynamic 3D Rendering System: Creates depth perception through sophisticated line arrays and color gradients
Multi-Indicator Integration: Seamlessly combines VWAP, Hurst, RSI, Stochastic, CCI, MFI, and Fractal Dimension analyses
Adaptive Scaling Algorithm: Automatically adjusts visualization parameters based on indicator type and market conditions
🔧 Core Components
Indicator Processing Module: Handles real-time calculation of multiple technical indicators using array-based mathematics
3D Visualization Engine: Converts indicator data into three-dimensional surfaces using line arrays and color mapping
Dynamic Scaling System: Implements custom normalization algorithms for different indicator types
Color Gradient Generator: Creates depth perception through programmatic color transitions
🔥 Key Features
Multi-Indicator Support: Comprehensive analysis across seven different technical indicators
Customizable Visualization: User-defined color schemes and line width parameters
Real-time Processing: Continuous calculation and rendering of 3D surfaces
Cross-Timeframe Analysis: Simultaneous visualization of indicator behavior across multiple periods
🎨 Visualization
Surface Plot: Three-dimensional representation using up to 500 lines with dynamic color gradients
Depth Indicators: Color intensity variations showing indicator value magnitude
Pattern Recognition: Visual identification of market structures across multiple timeframes
📖 Usage Guidelines
Indicator Selection
Type: VWAP, Hurst, RSI, Stochastic, CCI, MFI, Fractal Dimension
Default: VWAP
Starting Length: Minimum 5 periods
Default: 10
Step Size: Interval between calculations
Range: 1-10
Visualization Parameters
Color Scheme: Green, Red, Blue options
Line Width: 1-5 pixels
Surface Resolution: Up to 500 lines
✅ Best Use Cases
Multi-timeframe market analysis
Pattern recognition across different technical indicators
Trend strength assessment through 3D visualization
Market behavior study across multiple periods
⚠️ Limitations
High computational resource requirements
Maximum 500 line restriction
Requires substantial historical data
Complex visualization learning curve
🔬 How It Works
1. Data Processing:
Calculates selected indicator values across multiple timeframes
Stores results in multi-dimensional arrays
Applies custom scaling algorithms
2. Visualization Generation:
Creates line arrays for 3D surface representation
Applies color gradients based on value magnitude
Renders real-time updates to surface plot
3. Display Integration:
Synchronizes with chart timeframe
Updates surface plot dynamically
Maintains visual consistency across updates
🌟 Credits:
Inspired by LonesomeTheBlue (modified for multiple indicator types with scaling fixes and additional unique mappings)
💡 Note:
Optimal performance requires sufficient computing resources and historical data. Users should start with default settings and gradually adjust parameters based on their analysis requirements and system capabilities.
ML: Lorentzian Classification Premium█ OVERVIEW
Lorentzian Classification Premium represents the culmination of two years of collaborative development with over 1,000 beta testers from the TradingView community. Building upon the foundation of the open-source version, this premium edition introduces powerful enhancements that transform how machine-learning classification can be applied to market analysis.
The premium version maintains the core Lorentzian distance-based classification algorithm while expanding its capabilities through triple the feature dimensionality (up to 15 features), sophisticated mean-reversion detection, first-pullback identification, and a comprehensive signal taxonomy that goes far beyond simple buy/sell signals. Whether you're building automated trading systems, conducting deep market research, or integrating proprietary indicators into ML workflows, this tool provides the advanced edge needed for professional-grade analysis.
█ BACKGROUND
Lorentzian Classification analyzes market structures, especially those exhibiting non-linear distortions under stress, by employing advanced distance metrics like the Lorentzian metric, prominent in fields such as relativity theory. Where traditional indicators assume flat space, we embrace the curve. The heart of this approach is the Lorentzian distance metric—a sophisticated mathematical tool. This framework adeptly navigates the complex curves and distortions of market space, aiming to provide insights that traditional analysis might miss, especially during moments of extreme volatility. It analyzes historical data from a multi-dimensional feature space consisting of various technical indicators of your choosing. Where traditional approaches fail, Lorentzian space reveals the true geometry of market dynamics.
Neighborhoods in Different Geometries: In the above figure, the Lorentzian metric creates distinctive cross-patterns aligned with feature axes (RSI, CCI, ADX), capturing both local similarity and dimensional extremes. This unique geometry allows the algorithm to recognize similar market conditions that Euclidean spheres and Manhattan diamonds would miss entirely. In LC Premium, users can have up to 15 features -- you are not limited to 3-dimensions.
Among the thousands of distance metrics discovered by mathematicians, each perceives data through its own geometric lens. The Lorentzian metric stands apart with its unique ability to capture market behavior during volatile events.
█ COMMUNITY-DRIVEN EVOLUTION
It has been profoundly humbling over the past 2 years to witness this indicator's evolution through the collaborative efforts of our incredible community. This journey has been shaped by thousands of user suggestions and validated through real-world application.
A particularly amazing milestone was the development of a complete community-driven Python port, which meticulously matched even the most minute PineScript quirks. Building on this solid foundation, a new command-line interface (CLI) has opened up exciting possibilities for chart-specific parameter optimization:
Early insights from parameter optimization research: Through grid-search testing across thousands of parameter combinations, the analysis identifies which parameters have the biggest effects on performance and maps regions of stability across different market regimes. This reveals that optimal neighbor counts vary significantly based on market conditions—opening up incredible potential for timeframe-specific optimization.
This is just one of the insights gleaned so far from this ongoing investigation. The potential for chart-specific optimization for any given timeframe could transform how traders approach parameter selection.
Demand from power users for extra capabilities—while keeping the open-source version simple—sparked this Premium release. The open-source branch remains maintained, but the premium tier adds unique features for those who need an analytical edge and to leverage their own custom indicators as feature series for the algorithm.
█ KEY PREMIUM FEATURES
📈 First Pullback Detection System
Automatically identifies high-probability trend-continuation entries after initial momentum moves.
Detects when price retraces to optimal entry zones following breakouts or trend initiations.
Green/red triangle signals often fire before main classification arrows.
Dedicated alerts for both bullish and bearish pullback opportunities.
Based on veryfid's extensive research into pullback mechanics and market structure.
🔄 Dynamic Kernel Regression Envelope
Powerful, zero-setup confluence layer that immediately communicates trend shifts.
Dual-kernel system creates a visual envelope between trend estimates.
Color gradient dynamically represents prediction strength and market conviction.
Crossovers provide additional confirmation without cluttering your chart.
Professional visualization that rivals institutional-grade analysis tools.
✨ Massively Expanded Dimensionality: 10 Custom Sources, 5 Built-In Sources
Transform the indicator from 5 built-in standard to 15 total total features—triple the analytical power.
Integrate ANY TradingView indicator as a machine learning feature.
Built-in normalization ensures all indicators contribute equally regardless of scale.
Create theme-based systems: pure volume analysis, multi-timeframe momentum, or hybrid approaches.
📊 Tiered Mean Reversion Signals with Scalping Alerts
Regular (🔄) and Strong (⬇️/⬆️) mean reversion signals based on statistical extremes.
Opportunities often arise before candle close—perfect for scalping entries.
Visual markers appear at high-probability reversal zones.
Four specialized alert types: upward/downward for both regular and strong reversals.
Pre-optimized probability thresholds, no fine-tuning required.
📅 Daily Kernel Trend Filter
Instantly cleans up noisy intraday charts by aligning with higher timeframe trends.
Swing traders report immediate signal quality improvement.
Automatically deactivates on daily+ timeframes (intelligent context awareness).
Reduces counter-trend signals by up to 60% on lower timeframes.
Simple toggle—no complex multi-timeframe setup required.
📋 Professional Backtesting Stream (-6 to +6)
Multiple distinct signal types (including pullbacks, mean reversions, and kernel deviations) vs. basic binary (buy/sell) output for nuanced analysis.
Enables detailed walk-forward analysis and ML model training.
Compatible with external backtesting frameworks via numeric stream.
Rare precision for TradingView indicators—usually only found in institutional tools.
Perfect for quants building sophisticated strategy layers.
⚡ Performance Optimizations
Faster distance calculations through algorithmic improvements.
Reduced indicator load time (measured via Pine Profiler).
Handles 15 active features without timeouts—critical for multi-chart setups.
Optimized for live auto-trading bots requiring minimal latency.
🎨 Full Visual Customization & Accessibility
Complete color control for all visual elements.
Colorblind-safe default palette with customization options.
Dark mode optimization for extended trading sessions.
Professional appearance matching your trading workspace.
Accessibility features meeting modern UI standards.
🛠️ Advanced Training Modes
Downsampling mode for training on diverse market conditions; Down-sampling and remote-fractals for exotic pattern discovery.
Remote fractals option extends analysis to deep historical patterns.
Reset factor control for fine-tuning neighbor diversity; Reset-factor tuning to control neighbor diversity.
Appeals to systematic traders exploring exotic data approaches.
Prevents temporal clustering bias in model training.
█ HOW TO USE
Understanding the Approach (Core Concept):
Lorentzian Classification uses a k-Nearest Neighbors (k-NN) algorithm. It searches for historical price action "neighborhoods" similar to the current market state. Instead of a simple straight-line (Euclidean) distance, it primarily uses a Lorentzian distance metric, which can account for market "warping" or distortions often seen during high volatility or significant events. Each historical neighbor "votes" on what happened next in its context, and these votes aggregate into a classification score for the current bar.
Interpreting Bar Scores & Signals (Interpreting the Chart):
Bar Prediction Values: Numbers over each candle (e.g., ranging from -8 to +8 if Neighbors Count is 8) represent the aggregated vote from the nearest neighbors. Strong positive scores (e.g., +7, +8) indicate a strong bullish consensus among historical analogs. Strong negative scores (e.g., -7, -8) indicate a strong bearish consensus. Scores near zero suggest neutrality or conflicting signals from neighbors. The intensity of bar colors (if Use Confidence Gradient is on) often reflects these scores.
Main Arrows (Main Buy/Sell Labels): Large ▲/▼ labels are the primary entry signals generated when the overall classification (after filters) is bullish or bearish.
Pullback Triangles: Small green/red ▲/▼ identify potential trend continuation entries. These signals often appear after an initial price move and a subsequent minor retracement, suggesting the trend might resume. This is based on recognizing patterns where a brief counter-movement is followed by a continued advance in the initial trend direction.
Mean-Reversion Symbols: 🔄 (Regular Reversion) appears when price has crossed the average band of the Dynamic Kernel Regression Envelope. ⬇️/⬆️ (Strong Reversion) means price has crossed the far band of the envelope, indicating a more extreme deviation and potentially a stronger reversion opportunity.
Custom Mean Reversion Deviation Markers (Deviation Dots): If Enable Custom Mean Reversion Alerts is on, these dots appear when price deviates from the main kernel regression line by a user-defined ATR multiple, signaling a custom-defined reversion opportunity.
Kernel Regression Lines & Envelope: The Main Kernel Estimate (thicker line) is an adaptive moving average that smooths price and helps identify trend direction. Its color indicates the current trend bias. The Envelope (outer bands and a midline) creates a channel around price, and its interaction with price generates mean reversion signals.
Key Input Groups & Their Purpose:
🔧 GENERAL SETTINGS:
Reduce Price-Time Warping : Toggles the distance metric. When enabled, it reduces the characteristic "warping" effect of the default Lorentzian metric, making the distance calculation more Euclidean in nature. This may be suited for periods exhibiting less pronounced price-time distortions.
Source : Price data for calculations (default: close ).
Neighbors Count : The 'k' in k-NN – number of historical analogs considered.
Max Bars Back : How far back the indicator looks for historical patterns.
Show Exits / Use Dynamic Exits : Controls visibility and logic for exit signals.
Include Full History (Use Remote Fractals) : Allows model to pick "exotic" fractals from deep chart history.
Use Downsampling / Reset Factor : Advanced training parameters affecting neighbor selection.
Show Trade Stats / Use Worst Case Estimates : Displays a real-time performance table (for calibration only).
🎛️ DEFINE CUSTOM SOURCES (OPTIONAL):
Integrate up to 10 external data series (e.g., from other indicators) as features. Each can be optionally normalized. Load the external indicator on your chart first for it to appear in the dropdown.
🧠 FEATURE ENGINEERING:
Configure up to 15 features for the k-NN algorithm. Select type (RSI, WT, CCI, ADX, Custom Sources), parameters, and enable/disable. Start simple (3-5 features) and add complexity gradually. Normalize features with vastly different scales.
🖥️ DISPLAY SETTINGS:
Controls visibility of chart elements: bar colors, prediction values/labels, envelope, etc.
Align Signal with Current Bar : If true, pullback signals appear on the current bar (calculated on closed data). If false (default), they appear on the next bar.
Use ATR Offset : Positions bar prediction values using ATR for visibility.
🧮 FILTERS SETTINGS:
Refine raw classification signals: Volatility, Regime, ADX, EMA/SMA, and Daily Kernel filters.
🌀 KERNEL SETTINGS (Main Kernel):
Adjust parameters for the primary Nadaraya-Watson Kernel Regression line. Lookback Window , Relative Weighting , Regression Level , Lag control sensitivity and smoothness.
✉️ ENVELOPE SETTINGS (for Mean Reversion):
Configure the dynamic Kernel Regression Envelope. ATR Length , Near/Far ATR Factor define band width.
🎨 COLOR SETTINGS (Colors):
Customize colors for all visual elements; override every palette element.
General Approach to Using the Indicator (Suggested Workflow):
Load defaults and observe behavior: Familiarize yourself with the indicator's behavior.
Feature Engineering: Experiment with features, considering momentum, trend, and volatility. Add/replace features gradually.
Apply Filters: Refine signals according to your trading style.
Contextualize: Use kernels and envelope to understand broader trend and potential overbought/oversold areas.
Observe Signals: Pay attention to the interplay of main signals, pullbacks, and mean reversions. Watch interplay of main, pullback & mean-reversion signals.
Calibrate (Not Backtest): Use the "Trade Stats" table for real-time feedback on current settings. This is for calibration, *not a substitute for rigorous backtesting.*
Iterate & refine: Adjust settings, observe outcomes, and refine your approach.
█ ACKNOWLEDGMENTS
This premium version wouldn't exist without the invaluable contributions of:
veryfid for his groundbreaking ideas on unifying pullback detection with Lorentzian Classification, but most of all for always believing in and encouraging me and so many others. For being a mentor and, most importantly, a friend. We all miss you.
RikkiTavi for his help in creating the settings optimization framework and for other invaluable theoretical discussions.
The 1,000+ beta testers worldwide who provided continuous feedback over two years.
The Python porting team who created the foundation for advanced optimization; for the cross-language clone.
The broader TradingView community for making this one of the platform's most popular indicators.
█ FUTURE DEVELOPMENT
The Premium version will continue to evolve based on community feedback. Planned enhancements include:
Specialized exit model trained independently from entry signals (ML-based exit model).
Feature hub with pre-normalized, commonly requested indicators (Pre-normalized feature hub).
Better risk-management options (Enhanced risk-management options).
Fully automated settings optimization (Auto-settings optimization tool).
Tập lệnh trả phí
REVELATIONS (VoVix - PoC) REVELATIONS (VoVix - POC): True Regime Detection Before the Move
Let’s not sugarcoat it: Most strategies on TradingView are recycled—RSI, MACD, OBV, CCI, Stochastics. They all lag. No matter how many overlays you stack, every one of these “standard” indicators fires after the move is underway. The retail crowd almost always gets in late. That’s never been enough for my team, for DAFE, or for anyone who’s traded enough to know the real edge vanishes by the time the masses react.
How is this different?
REVELATIONS (VoVix - POC) was engineered from raw principle, structured to detect pre-move regime change—before standard technicals even light up. We built, tested, and refined VoVix to answer one hard question:
What if you could see the spike before the trend?
Here’s what sets this system apart, line-by-line:
o True volatility-of-volatility mathematics: It’s not just "ATR of ATR" or noise smoothing. VoVix uses normalized, multi-timeframe v-vol spikes, instantly detecting orderbook stress and "outlier" market events—before the chart shows them as trends.
o Purist regime clustering: Every trade is enabled only during coordinated, multi-filter regime stress. No more signals in meaningless chop.
o Nonlinear entry logic: No trade is ever sent just for a “good enough” condition. Every entry fires only if every requirement is aligned—local extremes, super-spike threshold, regime index, higher timeframe, all must trigger in sync.
o Adaptive position size: Your contracts scale up with event strength. Tiny size during nominal moves, max leverage during true regime breaks—never guesswork, never static exposure.
o All exits governed by regime decay logic: Trades are closed not just on price targets but at the precise moment the market regime exhausts—the hardest part of systemic trading, now solved.
How this destroys the lag:
Standard indicators (RSI, MACD, OBV, CCI, and even most “momentum” overlays) simply tell you what already happened. VoVix triggers as price structure transitions—anyone running these generic scripts will trade behind the move while VoVix gets in as stress emerges. Real alpha comes from anticipation, not confirmation.
The visuals only show what matters:
Top right, you get a live, live quant dashboard—regime index, current position size, real-time performance (Sharpe, Sortino, win rate, and wins). Bottom right: a VoVix "engine bar" that adapts live with regime stress. Everything you see is a direct function of logic driving this edge—no cosmetics, no fake momentum.
Inputs/Signals—explained carefully for clarity:
o ATR Fast Length & ATR Slow Length:
These are the heart of VoVix’s regime sensing. Fast ATR reacts to sharp volatility; Slow ATR is stability baseline. Lower Fast = reacts to every twitch; higher Slow = requires more persistent, “real” regime shifts.
Tip: If you want more signals or faster markets, lower ATR Fast. To eliminate noise, raise ATR Slow.
o ATR StdDev Window: Smoothing for volatility-of-volatility normalization. Lower = more jumpy, higher = only the cleanest spikes trigger.
Tip: Shorten for “jumpy” assets, raise for indices/futures.
o Base Spike Threshold: Think of this as your “minimum event strength.” If the current move isn’t volatile enough (normalized), no signal.
Tip: Higher = only biggest moves matter. Lower for more signals but more potential noise.
o Super Spike Multiplier: The “are you sure?” test—entry only when the current spike is this multiple above local average.
Tip: Raise for ultra-selective/swing-trading; lower for more active style.
Regime & MultiTF:
o Regime Window (Bars):
How many bars to scan for regime cluster “events.” Short for turbo markets, long for big swings/trends only.
o Regime Event Count: Only trade when this many spikes occur within the Regime Window—filters for real stress, not isolated ticks.
Tip: Raise to only ever trade during true breakouts/crashes.
o Local Window for Extremes:
How many bars to check that a spike is a local max.
Tip: Raise to demand only true, “clearest” local regime events; lower for early triggers.
o HTF Confirm:
Higher timeframe regime confirmation (like 45m on an intraday chart). Ensures any event you act on is visible in the broader context.
Tip: Use higher timeframes for only major moves; lower for scalping or fast regimes.
Adaptive Sizing:
o Max Contracts (Adaptive): The largest size your system will ever scale to, even on extreme event.
Tip: Lower for small accounts/conservative risk; raise on big accounts or when you're willing to go big only on outlier events.
o Min Contracts (Adaptive): The “toe-in-the-water.” Smallest possible trade.
Tip: Set as low as your broker/exchange allows for safety, or higher if you want to always have meaningful skin in the game.
Trade Management:
o Stop %: Tightness of your stop-loss relative to entry. Lower for tighter/safer, higher for more breathing room at cost of greater drawdown.
o Take Profit %: How much you'll hold out for on a win. Lower = more scalps. Higher = only run with the best.
o Decay Exit Sensitivity Buffer: Regime index must dip this far below the trading threshold before you exit for “regime decay.”
Tip: 0 = exit as soon as stress fails, higher = exits only on stronger confirmation regime is over.
o Bars Decay Must Persist to Exit: How long must decay be present before system closes—set higher to avoid quick fades and whipsaws.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Tip: Set to 1 for instant regime exit; raise for extra confirmation (less whipsaw risk, exits held longer).
________________________________________
Bottom line: Tune the sensitivity, selectivity, and risk of REVELATIONS by these inputs. Raise thresholds and windows for only the best, most powerful signals (institutional style); lower for activity (scalpers, fast cryptos, signals in constant motion). Sizing is always adaptive—never static or martingale. Exits are always based on both price and regime health. Every input is there for your control, not to sell “complexity.” Use with discipline, and make it your own.
This strategy is not just a technical achievement: It’s a statement about trading smarter, not just more.
* I went back through the code to make sure no the strategy would not suffer from repainting, forward looking, or any frowned upon loopholes.
Disclaimer:
Trading is risky and carries the risk of substantial loss. Do not use funds you aren’t prepared to lose. This is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
Expect more: We’ll keep pushing the standard, keep evolving the bar until “quant” actually means something in the public code space.
Use with clarity, use with discipline, and always trade your edge.
— Dskyz , for DAFE Trading Systems
MLExtensions_CoreLibrary "MLExtensions_Core"
A set of extension methods for a novel implementation of a Approximate Nearest Neighbors (ANN) algorithm in Lorentzian space, focused on computation.
normalizeDeriv(src, quadraticMeanLength)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the first-order derivative for price).
quadraticMeanLength (int) : The length of the quadratic mean (RMS).
Returns: nDeriv The normalized derivative of the input series.
normalize(src, min, max)
Rescales a source value with an unbounded range to a target range.
Parameters:
src (float) : The input series
min (float) : The minimum value of the unbounded range
max (float) : The maximum value of the unbounded range
Returns: The normalized series
rescale(src, oldMin, oldMax, newMin, newMax)
Rescales a source value with a bounded range to anther bounded range
Parameters:
src (float) : The input series
oldMin (float) : The minimum value of the range to rescale from
oldMax (float) : The maximum value of the range to rescale from
newMin (float) : The minimum value of the range to rescale to
newMax (float) : The maximum value of the range to rescale to
Returns: The rescaled series
getColorShades(color)
Creates an array of colors with varying shades of the input color
Parameters:
color (color) : The color to create shades of
Returns: An array of colors with varying shades of the input color
getPredictionColor(prediction, neighborsCount, shadesArr)
Determines the color shade based on prediction percentile
Parameters:
prediction (float) : Value of the prediction
neighborsCount (int) : The number of neighbors used in a nearest neighbors classification
shadesArr (array) : An array of colors with varying shades of the input color
Returns: shade Color shade based on prediction percentile
color_green(prediction)
Assigns varying shades of the color green based on the KNN classification
Parameters:
prediction (float) : Value (int|float) of the prediction
Returns: color
color_red(prediction)
Assigns varying shades of the color red based on the KNN classification
Parameters:
prediction (float) : Value of the prediction
Returns: color
tanh(src)
Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.
Parameters:
src (float) : The input series (i.e., the normalized derivative).
Returns: tanh The hyperbolic tangent of the input series.
dualPoleFilter(src, lookback)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the hyperbolic tangent).
lookback (int) : The lookback window for the smoothing.
Returns: filter The smoothed hyperbolic tangent of the input series.
tanhTransform(src, smoothingFrequency, quadraticMeanLength)
Returns the tanh transform of the input series.
Parameters:
src (float) : The input series (i.e., the result of the tanh calculation).
smoothingFrequency (int)
quadraticMeanLength (int)
Returns: signal The smoothed hyperbolic tangent transform of the input series.
n_rsi(src, n1, n2)
Returns the normalized RSI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the RSI calculation).
n1 (simple int) : The length of the RSI.
n2 (simple int) : The smoothing length of the RSI.
Returns: signal The normalized RSI.
n_cci(src, n1, n2)
Returns the normalized CCI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the CCI calculation).
n1 (simple int) : The length of the CCI.
n2 (simple int) : The smoothing length of the CCI.
Returns: signal The normalized CCI.
n_wt(src, n1, n2)
Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the WaveTrend Classic calculation).
n1 (simple int)
n2 (simple int)
Returns: signal The normalized WaveTrend Classic series.
n_adx(highSrc, lowSrc, closeSrc, n1)
Returns the normalized ADX ideal for use in ML algorithms.
Parameters:
highSrc (float) : The input series for the high price.
lowSrc (float) : The input series for the low price.
closeSrc (float) : The input series for the close price.
n1 (simple int) : The length of the ADX.
regime_filter(src, threshold, useRegimeFilter)
Parameters:
src (float)
threshold (float)
useRegimeFilter (bool)
filter_adx(src, length, adxThreshold, useAdxFilter)
filter_adx
Parameters:
src (float) : The source series.
length (simple int) : The length of the ADX.
adxThreshold (int) : The ADX threshold.
useAdxFilter (bool) : Whether to use the ADX filter.
Returns: The ADX.
filter_volatility(minLength, maxLength, sensitivityMultiplier, useVolatilityFilter)
filter_volatility
Parameters:
minLength (simple int) : The minimum length of the ATR.
maxLength (simple int) : The maximum length of the ATR.
sensitivityMultiplier (float) : Multiplier for the historical ATR to control sensitivity.
useVolatilityFilter (bool) : Whether to use the volatility filter.
Returns: Boolean indicating whether or not to let the signal pass through the filter.
OnePunch Algo Scalper V6Overview:
OnePunch Algo Scalper V6 is an invite-only script designed for short-term trend scalping and extreme reversal detection. It uniquely combines classic momentum and volume indicators, enhanced with multi-time session awareness, to deliver precise high-probability entry alerts.
Core Concepts:
RSI and CCI are used together to identify momentum exhaustion points for early reversal spotting.
CMF is integrated to filter buy signals only when volume flow confirms bullish intent, avoiding weak uptrends.
SMA overlays track medium to long-term trends to confirm direction bias for safer scalping entries.
MACD Histogram weakness detection adds a momentum weakening filter to confirm whether bullish/bearish pressure is losing strength — improving risk-reward setups.
Stochastic crossovers help predict short-term pullbacks, allowing for precision "Prepare for CALL/PUT" signals.
Session-based background coloring indicates high-probability trading windows (Morning, Midday, Afternoon), guiding users to focus on optimal times.
Signals Generated:
✅ "Trending Up": Momentum acceleration uptrend signal (RSI + CCI crossover with volume confirmation).
✅ "Trending Down": Momentum deceleration sell signal.
✅ "Reversal Up" / "Bearish Down": Extreme oversold/overbought reversals.
✅ "Prepare for PUTs/CALLs": Anticipation signals based on stochastic weakening + MACD histogram convergence.
Chart Setup:
The script draws clean shape labels on the chart for each event (e.g., "Up Trend", "Bearish") for clarity.
Background highlights show different sessions to help traders recognize the most liquid periods.
No other indicators are required on the chart.
Usage Notes:
This script is ideal for scalping or short intraday swing trades on liquid assets like indices, crypto, or forex.
Best results when combined with manual Support/Resistance marking (use "Prepare for PUTs/CALLs" near S/R zones).
Hyperion Crypto Matrix: Ultimate Market Sentinel
// 🔰 HYPERION CRYPTO MATRIX: ULTIMATE MARKET SENTINEL
// ─────────────────────────────────────────────────────────────────────────────
/*
The **Hyperion Crypto Matrix** is an advanced crypto trend-following strategy built from the ground up for precision, not just performance. Unlike traditional “mashups” of indicators, this system was **engineered around synergy**—each module is purpose-driven and non-redundant, delivering fast, filtered, high-probability signals in volatile crypto markets.
─────────────────────────────────────────────────────────────
📌 STRATEGY PURPOSE
─────────────────────────────────────────────────────────────
Hyperion is built for **1-hour crypto trading** and optimizes for:
- High Win Rate
- Early Exits on Trend Weakness
- Partial Position Scaling (TP1/TP2)
- Real-time trade performance tracking
It is ideal for traders who want **real-time trade logic** with:
- No repainting
- No overfitting
- Realistic entry/exit structure
- No same-bar entry & exit (enforces 1-bar delay)
─────────────────────────────────────────────────────────────
🧠 WHAT MAKES IT ORIGINAL
─────────────────────────────────────────────────────────────
Each component is **custom-integrated** with strict role separation:
- **Trend Direction:** Enhanced Wave Oscillator (EWO) with adaptive band filtering
- **Trend Strength Memory:** Relative Momentum Index (RMI) with threshold locking
- **Volume Confirmation:** Historical relative volume spike filter using SMA multiplier
- **Momentum Weakness Exit:** Combined ROC and CCI to detect early reversal before price turns
- **Position Tracking:** TP1 (50% exit), TP2 (100% close) with cooldown to prevent whipsaws
- **Dynamic Dashboard:** Real-time stats including win rate, PnL efficiency, and TP hit status
These aren’t just “plugged in” indicators—they are synchronized to **filter, confirm, and adapt** to price action with timing logic that prevents premature entries or late exits.
─────────────────────────────────────────────────────────────
📊 INDICATOR LOGIC OVERVIEW
─────────────────────────────────────────────────────────────
1. **📈 Enhanced Wave Oscillator (EWO):**
- Calculates the delta between a fast and slow EMA (5 vs. 34 by default)
- Uses a dynamic banding system to detect peaks/troughs and prevent entries during exhaustion
- Filters only active, accelerating trends — reducing false positives
2. **🧠 Relative Momentum Index (RMI):**
- Similar to RSI but with a forward-looking momentum comparison
- Confirms trend *persistence* over time, preventing entries on short-term flips
- Long entries only allowed when RMI > threshold (default 55), short if RMI < 45
3. **🔊 Volume Spike Filter:**
- Uses 20-bar SMA of volume and a multiplier (1.5x default) to detect **relative volume breakouts**
- Prevents trades in low-liquidity environments (e.g., chop, overnight sessions)
4. **📉 Weak Trend Close Logic:**
- Combines Rate of Change (ROC) and Commodity Channel Index (CCI)
- Detects early signs of momentum deterioration, often before the trend visually reverses
- Triggers exit before price falls into sideways zones
5. **🎯 Take Profit System (TP1/TP2):**
- TP1: 50% position closed at +2% (default)
- TP2: Full close at +4% (default)
- Uses `strategy.exit()` with limit orders based on entry price
6. **⏱️ Reentry Cooldown:**
- After TP2 or weak trend exit, system enforces a 1-bar delay before reentry
- Avoids frequent churn in flat or noisy environments
7. **📋 Real-Time Dashboard (Optional):**
- Displays live trade status, PnL metrics, TP1/TP2 hit status, bars since entry, win rate %, and profit factor
- Color-coded background to highlight active trade direction (green for long, red for short)
─────────────────────────────────────────────────────────────
⚙️ HOW TO USE
─────────────────────────────────────────────────────────────
1. Load on a 1H chart of a crypto asset with good liquidity (e.g., BTC, ETH, LINK)
2. Toggle between \"Long Only\", \"Short Only\", or \"Both\" in the settings
3. Use default TP1/TP2 percentages, or tune them for the asset’s volatility
4. Observe trade execution and live stats on the optional dashboard
5. Review the bar coloring for EWO trend bias confirmation
> Stop-loss logic is not included. This strategy assumes exits occur at TP2 or on trend/momentum failure.
─────────────────────────────────────────────────────────────
⚖️ TRADINGVIEW COMPLIANCE & USAGE DISCLAIMER
─────────────────────────────────────────────────────────────
This strategy does **not repaint**, is fully compatible with **TradingView backtesting**, and adheres to all known Pine Script execution rules.
⚠️ **Disclaimer:** This script is for educational purposes only and does not constitute financial advice. Trading cryptocurrencies involves significant risk. Always test strategies on a demo account and consult with a financial advisor before live trading.
─────────────────────────────────────────────────────────────
🧪 CONCLUSION
─────────────────────────────────────────────────────────────
The **Hyperion Crypto Matrix** is not a mashup—it’s a **modular, optimized, logic-driven system** crafted for real-world crypto trading. Every component has been tuned for function, not fluff. Whether you're backtesting or live trading, this system is designed to give you **structured, actionable edge** with live feedback every step of the way.
*/
Market Trend Levels Non-Repainting [BigBeluga X PineIndicators]This strategy is based on the Market Trend Levels Detector developed by BigBeluga. Full credit for the concept and original indicator goes to BigBeluga.
The Market Trend Levels Detector Strategy is a non-repainting trend-following strategy that identifies market trend shifts using two Exponential Moving Averages (EMA). It also detects key price levels and allows traders to apply multiple filters to refine trade entries and exits.
This strategy is designed for trend trading and enables traders to:
Identify trend direction based on EMA crossovers.
Detect significant market levels using labeled trend lines.
Use multiple filter conditions to improve trade accuracy.
Avoid false signals through non-repainting calculations.
How the Market Trend Levels Detector Strategy Works
1. Core Trend Detection Using EMA Crossovers
The strategy detects trend shifts using two EMAs:
Fast EMA (default: 12 periods) – Reacts quickly to price movements.
Slow EMA (default: 25 periods) – Provides a smoother trend confirmation.
A bullish crossover (Fast EMA crosses above Slow EMA) signals an uptrend , while a bearish crossover (Fast EMA crosses below Slow EMA) signals a downtrend .
2. Market Level Detection & Visualization
Each time an EMA crossover occurs, a trend level line is drawn:
Bullish crossover → A green line is drawn at the low of the crossover candle.
Bearish crossover → A purple line is drawn at the high of the crossover candle.
Lines can be extended to act as support and resistance zones for future price action.
Additionally, a small label (●) appears at each crossover to mark the event on the chart.
3. Trade Entry & Exit Conditions
The strategy allows users to choose between three trading modes:
Long Only – Only enters long trades.
Short Only – Only enters short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish EMA crossover occurs.
The trade direction setting allows long trades.
Filter conditions (if enabled) confirm a valid long signal.
Short Entry:
A bearish EMA crossover occurs.
The trade direction setting allows short trades.
Filter conditions (if enabled) confirm a valid short signal.
Exit Conditions
Long Exit:
A bearish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid long position.
Short Exit:
A bullish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid short position.
Additional Trade Filters
To improve trade accuracy, the strategy allows traders to apply up to 7 additional filters:
RSI Filter: Only trades when RSI confirms a valid trend.
MACD Filter: Ensures MACD histogram supports the trade direction.
Stochastic Filter: Requires %K line to be above/below threshold values.
Bollinger Bands Filter: Confirms price position relative to the middle BB line.
ADX Filter: Ensures the trend strength is above a set threshold.
CCI Filter: Requires CCI to indicate momentum in the right direction.
Williams %R Filter: Ensures price momentum supports the trade.
Filters can be enabled or disabled individually based on trader preference.
Dynamic Level Extension Feature
The strategy provides an optional feature to extend trend lines until price interacts with them again:
Bullish support lines extend until price revisits them.
Bearish resistance lines extend until price revisits them.
If price breaks a line, the line turns into a dotted style , indicating it has been breached.
This helps traders identify key levels where trend shifts previously occurred, providing useful support and resistance insights.
Customization Options
The strategy includes several adjustable settings :
Trade Direction: Choose between Long Only, Short Only, or Long & Short.
Trend Lengths: Adjust the Fast & Slow EMA lengths.
Market Level Extension: Decide whether to extend support/resistance lines.
Filters for Trade Confirmation: Enable/disable individual filters.
Color Settings: Customize line colors for bullish and bearish trend shifts.
Maximum Displayed Lines: Limit the number of drawn support/resistance lines.
Considerations & Limitations
Trend Lag: As with any EMA-based strategy, signals may be slightly delayed compared to price action.
Sideways Markets: This strategy works best in trending conditions; frequent crossovers in sideways markets can produce false signals.
Filter Usage: Enabling multiple filters may reduce trade frequency, but can also improve trade quality.
Line Overlap: If many crossovers occur in a short period, the chart may become cluttered with multiple trend levels. Adjusting the "Display Last" setting can help.
Conclusion
The Market Trend Levels Detector Strategy is a non-repainting trend-following system that combines EMA crossovers, market level detection, and customizable filters to improve trade accuracy.
By identifying trend shifts and key price levels, this strategy can be used for:
Trend Confirmation – Using EMA crossovers and filters to confirm trend direction.
Support & Resistance Trading – Identifying dynamic levels where price reacts.
Momentum-Based Trading – Combining EMA crossovers with additional momentum filters.
This strategy is fully customizable and can be adapted to different trading styles, timeframes, and market conditions.
Full credit for the original concept and indicator goes to BigBeluga.
Multi-indicator Signal Builder [Skyrexio]Overview
Multi-Indicator Signal Builder is a versatile, all-in-one script designed to streamline your trading workflow by combining multiple popular technical indicators under a single roof. It features a single-entry, single-exit logic, intrabar stop-loss/take-profit handling, an optional time filter, a visually accessible condition table, and a built-in statistics label. Traders can choose any combination of 12+ indicators (RSI, Ultimate Oscillator, Bollinger %B, Moving Averages, ADX, Stochastic, MACD, PSAR, MFI, CCI, Heikin Ashi, and a “TV Screener” placeholder) to form entry or exit conditions. This script aims to simplify strategy creation and analysis, making it a powerful toolkit for technical traders.
Indicators Overview
1. RSI (Relative Strength Index)
Measures recent price changes to evaluate overbought or oversold conditions on a 0–100 scale.
2. Ultimate Oscillator (UO)
Uses weighted averages of three different timeframes, aiming to confirm price momentum while avoiding false divergences.
3. Bollinger %B
Expresses price relative to Bollinger Bands, indicating whether price is near the upper band (overbought) or lower band (oversold).
4. Moving Average (MA)
Smooths price data over a specified period. The script supports both SMA and EMA to help identify trend direction and potential crossovers.
5. ADX (Average Directional Index)
Gauges the strength of a trend (0–100). Higher ADX signals stronger momentum, while lower ADX indicates a weaker trend.
6. Stochastic
Compares a closing price to a price range over a given period to identify momentum shifts and potential reversals.
7. MACD (Moving Average Convergence/Divergence)
Tracks the difference between two EMAs plus a signal line, commonly used to spot momentum flips through crossovers.
8. PSAR (Parabolic SAR)
Plots a trailing stop-and-reverse dot that moves with the trend. Often used to signal potential reversals when price crosses PSAR.
9. MFI (Money Flow Index)
Similar to RSI but incorporates volume data. A reading above 80 can suggest overbought conditions, while below 20 may indicate oversold.
10. CCI (Commodity Channel Index)
Identifies cyclical trends or overbought/oversold levels by comparing current price to an average price over a set timeframe.
11. Heikin Ashi
A type of candlestick charting that filters out market noise. The script uses a streak-based approach (multiple consecutive bullish or bearish bars) to gauge mini-trends.
12. TV Screener
A placeholder condition designed to integrate external buy/sell logic (like a TradingView “Buy” or “Sell” rating). Users can override or reference external signals if desired.
Unique Features
1. Multi-Indicator Entry and Exit
You can selectively enable any subset of 12+ classic indicators, each with customizable parameters and conditions. A position opens only if all enabled entry conditions are met, and it closes only when all enabled exit conditions are satisfied, helping reduce false triggers.
2. Single-Entry / Single-Exit with Intrabar SL/TP
The script supports a single position at a time. Once a position is open, it monitors intrabar to see if the price hits your stop-loss or take-profit levels before the bar closes, making results more realistic for fast-moving markets.
3. Time Window Filter
Users may specify a start/end date range during which trades are allowed, making it convenient to focus on specific market cycles for backtesting or live trading.
4. Condition Table and Statistics
A table at the bottom of the chart lists all active entry/exit indicators. Upon each closed trade, an integrated statistics label displays net profit, total trades, win/loss count, average and median PnL, etc.
5. Seamless Alerts and Automation
Configure alerts in TradingView using “Any alert() function call.”
The script sends JSON alert messages you can route to your own webhook.
The indicator can be integrated with Skyrexio alert bots to automate execution on major cryptocurrency exchanges
6. Optional MA/PSAR Plots
For added visual clarity, optionally plot the chosen moving averages or PSAR on the chart to confirm signals without stacking multiple indicators.
Methodology
1. Multi-Indicator Entry Logic
When multiple entry indicators are enabled (e.g., RSI + Stochastic + MACD), the script requires all signals to align before generating an entry. Each indicator can be set for crossovers, crossunders, thresholds (above/below), etc. This “AND” logic aims to filter out low-confidence triggers.
2. Single-Entry Intrabar SL/TP
One Position At a Time: Once an entry signal triggers, a trade opens at the bar’s close.
Intrabar Checks: Stop-loss and take-profit levels (if enabled) are monitored on every tick. If either is reached, the position closes immediately, without waiting for the bar to end.
3. Exit Logic
All Conditions Must Agree: If the trade is still open (SL/TP not triggered), then all enabled exit indicators must confirm a closure before the script exits on the bar’s close.
4. Time Filter
Optional Trading Window: You can activate a date/time range to constrain entries and exits strictly to that interval.
Justification of Methodology
Indicator Confluence: Combining multiple tools (RSI, MACD, etc.) can reduce noise and false signals.
Intrabar SL/TP: Capturing real-time spikes or dips provides a more precise reflection of typical live trading scenarios.
Single-Entry Model: Straightforward for both manual and automated tracking (especially important in bridging to bots).
Custom Date Range: Helps refine backtesting for specific market conditions or to avoid known irregular data periods.
How to Use
1. Add the Script to Your Chart
In TradingView, open Indicators , search for “Multi-indicator Signal Builder”.
Click to add it to your chart.
2. Configure Inputs
Time Filter: Set a start and end date for trades.
Alerts Messages: Input any JSON or text payload needed by your external service or bot.
Entry Conditions: Enable and configure any indicators (e.g., RSI, MACD) for a confluence-based entry.
Close Conditions: Enable exit indicators, along with optional SL (negative %) and TP (positive %) levels.
3. Set Up Alerts
In TradingView, select “Create Alert” → Condition = “Any alert() function call” → choose this script.
Entry Alert: Triggers on the script’s entry signal.
Close Alert: Triggers on the script’s close signal (or if SL/TP is hit).
Skyrexio Alert Bots: You can route these alerts via webhook to Skyrexio alert bots to automate order execution on major crypto exchanges (or any other supported broker).
4. Visual Reference
A condition table at the bottom summarizes active signals.
Statistics Label updates automatically as trades are closed, showing PnL stats and distribution metrics.
Backtesting Guidelines
Symbol/Timeframe: Works on multiple assets and timeframes; always do thorough testing.
Realistic Costs: Adjust commissions and potential slippage to match typical exchange conditions.
Risk Management: If using the built-in stop-loss/take-profit, set percentages that reflect your personal risk tolerance.
Longer Test Horizons: Verify performance across diverse market cycles to gauge reliability.
Example of statistic calculation
Test Period: 2023-01-01 to 2025-12-31
Initial Capital: $1,000
Commission: 0.1%, Slippage ~5 ticks
Trade Count: 468 (varies by strategy conditions)
Win rate: 76% (varies by strategy conditions)
Net Profit: +96.17% (varies by strategy conditions)
Disclaimer
This indicator is provided strictly for informational and educational purposes .
It does not constitute financial or trading advice.
Past performance never guarantees future results.
Always test thoroughly in demo environments before using real capital.
Enjoy exploring the Multi-Indicator Signal Builder! Experiment with different indicator combinations and adjust parameters to align with your trading preferences, whether you trade manually or link your alerts to external automation services. Happy trading and stay safe!
Machine Learning IndexesMachine Learning Indexes Script Description
The Machine Learning Indexes script is an advanced Pine Script™ indicator that applies machine learning techniques to analyze various market data types. It enables traders to generate adaptive long and short signals using highly customizable settings for signal detection and analysis.
Key Features:
Signal Mode: Allows the user to choose between generating signals for "Longs" (buy opportunities) or "Shorts" (sell opportunities).
Index Type: Supports multiple index types including RSI, CCI, MFI, Stochastic, and Momentum. All indexes are normalized between 0-100 for uniformity.
Data Set Selection: Provides options for analyzing Price, Volume, Volatility, or Momentum-based data sets. This enables traders to adapt the script to their preferred market analysis methodology.
Absolute vs. Directional Changes: Includes a toggle to calculate absolute changes for values or maintain directional sensitivity for trend-based analysis.
Dynamic Index Calculation: Automatically calculates and compares multiple index lengths to determine the best fit for current market conditions, adding precision to signal generation.
Input Parameters:
Signal Settings:
Signal Mode: Selects between "Longs" or "Shorts" to define the signal direction.
Index Type: Chooses the type of market index for calculations. Options include RSI, CCI, MFI, Stochastic, and Momentum.
Data Set Type: Determines the basis of the analysis, such as Price, Volume, Volatility, or Momentum-based data.
Absolute Change: Toggles whether absolute or directional changes are considered for calculations.
Index Settings:
Min Index Length: Sets the base index length used for calculations.
Index Length Variety: Adjusts the increment steps for variations in index length.
Lower/Upper Bands: Define thresholds for the selected index, indicating overbought and oversold levels.
Signal Parameters:
Target Signal Size: Number of bars used to identify pivot points.
Backtest Trade Size: Defines the number of bars over which signal performance is measured.
Sample Size: Number of data points used to calculate signal metrics.
Signal Strength Needed: Sets the minimum confidence required for a signal to be considered valid.
Require Low Variety: Option to prioritize signals with lower variability in results.
How It Works:
The script dynamically calculates multiple index variations and compares their accuracy to detect optimal parameters for generating signals.
Signal validation considers the chosen mode (longs/shorts), data set, index type, and signal parameters.
Adaptive moving averages (ADMA) and Band Signals (BS) are plotted to visualize the interaction between market trends and thresholds.
Long and short signals are displayed with clear up (L) and down (S) labels for easy interpretation.
Performance Metrics:
Success Rate: Percentage of valid signals that led to profitable outcomes.
Profit Factor: Ratio of gains from successful trades to losses from unsuccessful trades.
Disclaimer:
This indicator is for informational purposes only and does not guarantee future performance. It is designed to support traders in making informed decisions but should be used alongside other analysis methods and risk management strategies.
