AI indicatorThis script is a trading indicator designed for future trading signals on the TradingView platform. It uses a combination of the Relative Strength Index (RSI) and a Simple Moving Average (SMA) to generate buy and sell signals. Here's a breakdown of its components and logic:
1. Inputs
The script includes configurable inputs to make it adaptable for different market conditions:
RSI Length: Determines the number of periods for calculating RSI. Default is 14.
RSI Overbought Level: Signals when RSI is above this level (default 70), indicating potential overbought conditions.
RSI Oversold Level: Signals when RSI is below this level (default 30), indicating potential oversold conditions.
Moving Average Length: Defines the SMA length used to confirm price trends (default 50).
2. Indicators Used
RSI (Relative Strength Index):
Measures the speed and change of price movements.
A value above 70 typically indicates overbought conditions.
A value below 30 typically indicates oversold conditions.
SMA (Simple Moving Average):
Used to smooth price data and identify trends.
Price above the SMA suggests an uptrend, while price below suggests a downtrend.
3. Buy and Sell Signal Logic
Buy Condition:
The RSI value is below the oversold level (e.g., 30), indicating the market might be undervalued.
The current price is above the SMA, confirming an uptrend.
Sell Condition:
The RSI value is above the overbought level (e.g., 70), indicating the market might be overvalued.
The current price is below the SMA, confirming a downtrend.
These conditions ensure that trades align with market trends, reducing false signals.
4. Visual Features
Buy Signals: Displayed as green labels (plotshape) below the price bars when the buy condition is met.
Sell Signals: Displayed as red labels (plotshape) above the price bars when the sell condition is met.
Moving Average Line: A blue line (plot) added to the chart to visualize the SMA trend.
5. How It Works
When the buy condition is true (RSI < 30 and price > SMA), a green label appears below the corresponding price bar.
When the sell condition is true (RSI > 70 and price < SMA), a red label appears above the corresponding price bar.
The blue SMA line helps to visualize the overall trend and acts as confirmation for signals.
6. Advantages
Combines Momentum and Trend Analysis:
RSI identifies overbought/oversold conditions.
SMA confirms whether the market is trending up or down.
Simple Yet Effective:
Reduces noise by using well-established indicators.
Easy to interpret for beginners and experienced traders alike.
Customizable:
Parameters like RSI length, oversold/overbought levels, and SMA length can be adjusted to fit different assets or timeframes.
7. Limitations
Lagging Indicator: SMA is a lagging indicator, so it may not capture rapid market reversals quickly.
Not Foolproof: No trading indicator can guarantee 100% accuracy. False signals can occur in choppy or sideways markets.
Needs Volume Confirmation: The script does not consider trading volume, which could enhance signal reliability.
8. How to Use It
Copy the script into TradingView's Pine Editor.
Save and add it to your chart.
Adjust the RSI and SMA parameters to suit your preferred asset and timeframe.
Look for buy signals (green labels) in uptrends and sell signals (red labels) in downtrends.
Search in scripts for "ai"
Dynamic ALMA with signalsEnhanced ALMA with Signals
This TradingView indicator is designed to enhance your trading strategy by utilizing the Arnaud Legoux Moving Average (ALMA), a unique moving average that provides smoother price action while minimizing lag. The script not only plots the ALMA line but also dynamically adjusts its parameters based on market volatility to adapt to different trading conditions. Additionally, it highlights potential bounce points off the line, as well as breakout points, giving traders clear signals for potential support, resistance levels, and breakouts.
Key Features:
Dynamic ALMA Line with Glow Effect:
The core of this indicator is the ALMA line, which is dynamically adjusted to market volatility, providing more accurate signals in varying conditions. The line adapts to both trending and consolidating markets by adjusting its sensitivity in real time. A glow effect is created by plotting the ALMA line multiple times with increasing transparency, making it visually distinct.
Bounce Detection Signals with Volatility Filter:
The script detects and labels potential support and resistance bounces based on the crossover and crossunder of the price with the ALMA line, further filtered by a volatility condition. This helps in filtering out false signals during low-volatility conditions, making the signals more reliable.
Visual Enhancements:
Custom glow effects and labels for bounce detection enhance chart readability and help traders quickly identify key levels.
Inputs:
Base Window Size: Sets the number of bars used in calculating the ALMA, allowing traders to adjust the sensitivity of the moving average. This parameter is dynamically adjusted based on current market volatility.
Offset: Determines the position of the ALMA curve. Higher values move the curve further away from the price. This value remains constant for stability.
Sigma: Controls the smoothness of the ALMA curve; a higher sigma results in a smoother curve. This value also remains constant.
ATR Period and Threshold Multiplier: Used to calculate the Average True Range (ATR) for the volatility filter, which determines whether the market conditions are sufficiently volatile to consider bounce signals.
How It Works:
Dynamic ALMA Calculation:
The script calculates the ALMA (Arnaud Legoux Moving Average) using the ta.alma function, dynamically adjusting the window size based on market volatility measured by the ATR (Average True Range). This ensures that the ALMA line remains responsive in high-volatility environments and smooth in low-volatility conditions.
Glow Effect:
To create a glow effect around the ALMA line, the script plots the ALMA multiple times with varying degrees of transparency. This visual enhancement helps the ALMA line stand out on the chart.
Bounce Detection with Volatility Filter:
The script uses two conditions to detect potential bounces:
Support Bounce: Detected when the low of the bar crosses above the ALMA line (ta.crossover(low, alma)) and the close is above the ALMA, while the volatility filter confirms sufficient market activity. This suggests potential support at the ALMA line.
Resistance Bounce: Detected when the high of the bar crosses below the ALMA line (ta.crossunder(high, alma)) and the close is below the ALMA, while the volatility filter confirms sufficient market activity. This indicates potential resistance at the ALMA line.
Labeling Bounce Points:
When a bounce is detected, the script labels it on the chart:
Support Bounces (S): Labeled with a blue "S" below the bar where a support bounce is detected.
Resistance Bounces (R): Labeled with a white "R" above the bar where a resistance bounce is detected.
Usage:
This enhanced indicator helps traders visualize key support and resistance levels more effectively by dynamically adjusting the ALMA moving average to market conditions. By detecting and labeling potential bounce points and filtering these signals based on volatility, traders can better identify entry and exit points in their trading strategy. The dynamic adjustments and visual enhancements make it easier to spot critical levels quickly and adapt to changing market conditions.
Customize the inputs to fit your trading style, and use this enhanced ALMA indicator to gain a more refined understanding of market trends, potential reversals, and breakouts.
AI Big Players Move Pattern with Buy/Sell Signals.Big Players Move Pattern with Buy/Sell Signals
Description:
The "Big Players Move Pattern with Buy/Sell Signals" indicator is a powerful tool designed to help traders identify potential market movements driven by institutional investors, also known as big players or smart money. This indicator leverages key patterns such as volume spikes, support and resistance breakouts, and accumulation/distribution trends to generate actionable buy and sell signals.
Key Features:
Volume Spike Detection:
Volume Spike Length: The indicator calculates the moving average of volume over a user-defined period (default: 20 periods).
Volume Spike Multiplier: A volume spike is detected when the current volume exceeds the moving average volume by a specified multiplier (default: 2.0).
Visual Cue: Volume spikes are plotted on the chart with an orange triangle, indicating potential big player activity.
Support and Resistance Breakouts:
Support/Resistance Length: The indicator identifies key support and resistance levels based on the highest highs and lowest lows over a user-defined period (default: 50 periods).
Breakout Detection: The indicator detects and highlights breakouts above resistance levels and breakdowns below support levels.
Visual Cues: Breakouts are plotted with green upward labels, while breakdowns are plotted with red downward labels.
Accumulation/Distribution Line:
Trend Analysis: The accumulation/distribution line is calculated to provide insights into whether a stock is being accumulated (bought) or distributed (sold) by big players.
Visual Cue: The line is plotted on the chart, helping traders understand underlying market trends.
Buy and Sell Signals:
Buy Signal: Generated when a volume spike coincides with a price crossover above the support level.
Sell Signal: Generated when a volume spike coincides with a price crossover below the resistance level.
Visual Cues: Buy signals are plotted with green labels, and sell signals are plotted with red labels.
Alerts:
Custom Alerts: The indicator includes customizable alerts for volume spikes, buy signals, and sell signals, ensuring that traders never miss a significant market movement.
Benefits:
Early Detection: By identifying the activities of big players, traders can position themselves early to capitalize on significant price movements.
Visual Clarity: Clear visual indicators and signals help traders make informed decisions quickly and accurately.
Customization: Adjustable parameters allow traders to tailor the indicator to their specific trading strategies and timeframes.
Use Cases:
Day Trading: Ideal for identifying intraday movements and capitalizing on short-term opportunities.
Swing Trading: Effective for capturing medium-term trends driven by institutional activities.
Position Trading: Useful for understanding long-term accumulation and distribution patterns by big players.
Enhance your trading strategy with the "Big Players Move Pattern with Buy/Sell Signals" indicator and gain a competitive edge by tracking the movements of institutional investors.
AI-Bank-Nifty Tech AnalysisThis code is a TradingView indicator that analyzes the Bank Nifty index of the Indian stock market. It uses various inputs to customize the indicator's appearance and analysis, such as enabling analysis based on the chart's timeframe, detecting bullish and bearish engulfing candles, and setting the table position and style.
The code imports an external script called BankNifty_CSM, which likely contains functions that calculate technical indicators such as the RSI, MACD, VWAP, and more. The code then defines several table cell colors and other styling parameters.
Next, the code defines a table to display the technical analysis of eight bank stocks in the Bank Nifty index. It then defines a function called get_BankComponent_Details that takes a stock symbol as input, requests the stock's OHLCV data, and calculates several technical indicators using the imported CSM_BankNifty functions.
The code also defines two functions called get_EngulfingBullish_Detection and get_EngulfingBearish_Detection to detect bullish and bearish engulfing candles.
Finally, the code calculates the technical analysis for each bank stock using the get_BankComponent_Details function and displays the results in the table. If the engulfing input is enabled, the code also checks for bullish and bearish engulfing candles and displays buy/sell signals accordingly.
The FRAMA stands for "Fractal Adaptive Moving Average," which is a type of moving average that adjusts its smoothing factor based on the fractal dimension of the price data. The fractal dimension reflects self-similarity at different scales. The FRAMA uses this property to adapt to the scale of price movements, capturing short-term and long-term trends while minimizing lag. The FRAMA was developed by John F. Ehlers and is commonly used by traders and analysts in technical analysis to identify trends and generate buy and sell signals. I tried to create this indicator in Pine.
In this context, "RS" stands for "Relative Strength," which is a technical indicator that compares the performance of a particular stock or market sector against a benchmark index.
The "Alligator" is a technical analysis tool that consists of three smoothed moving averages. Introduced by Bill Williams in his book "Trading Chaos," the three lines are called the Jaw, Teeth, and Lips of the Alligator. The Alligator indicator helps traders identify the trend direction and its strength, as well as potential entry and exit points. When the three lines are intertwined or close to each other, it indicates a range-bound market, while a divergence between them indicates a trending market. The position of the price in relation to the Alligator lines can also provide signals, such as a buy signal when the price crosses above the Alligator lines and a sell signal when the price crosses below them.
In addition to these, we have several other commonly used technical indicators, such as MACD, RSI, MFI (Money Flow Index), VWAP, EMA, and Supertrend. I used all the built-in functions for these indicators from TradingView. Thanks to the developer of this TradingView Indicator.
I also created a BankNifty Components Table and checked it on the dashboard.
AI-EngulfingCandleThis script is the combination of RSI and Engulfing Pattern
How it works
1. when RSI > 70 and form the bullish engulfing pattern . it gives sell signal
2. when RSI < 30 and form the bearish engulfing pattern . it gives buy signal
settings:
basic setting for RSI has been enabled in the script to set the levels accordingly to your trades
VIX Term Structure Pro [v7.0 Enhanced]# VIX Term Structure Pro v7.0
[! (img.shields.io)](www.tradingview.com)
[! (img.shields.io)](www.tradingview.com)
[! (img.shields.io)](LICENSE)
**Professional VIX-based Market Sentiment & Timing Indicator**
专业的 VIX 市场情绪与择时指标
---
## 🌟 Overview / 概述
VIX Term Structure Pro is an advanced multi-factor market timing indicator that analyzes the VIX futures term structure, volatility regime, and market breadth to generate actionable buy/sell signals.
VIX Term Structure Pro 是一款高级多因子市场择时指标，通过分析 VIX 期货期限结构、波动率区间及市场广度，生成可操作的买卖信号。
---
## 🚀 Key Features / 核心功能
### 📊 Multi-Factor Scoring System / 多因子评分系统
- **Term Structure Z-Score**: Measures deviation from historical mean / 期限结构 Z 分数：衡量与历史均值的偏离
- **VIX/VX1 Basis**: Spot premium detection for panic signals / VIX 现货溢价：恐慌信号检测
- **Contango Analysis**: Futures curve shape insights / 期货升水分析
- **SKEW Integration**: Options skew for tail risk / SKEW 整合：尾部风险监测
- **Put/Call Ratio**: Sentiment extremes / 看跌/看涨比率：情绪极端
- **VVIX Support**: Volatility of volatility (optional) / VVIX 支持：波动率的波动率
### 🎯 Three-Tier Signal System / 三级信号系统
| Signal | Score | Description |
|--------|-------|-------------|
| 🚨 **CRASH BUY** | ≥ 6 | Extreme panic, rare opportunity / 极端恐慌，罕见机会 |
| 🟢 **STRONG BUY** | ≥ 5 | Multi-factor confluence / 多因子共振 |
| 🟡 **BUY DIP** | ≥ 4 | Accumulate on weakness / 逢低吸纳 |
| 🟠 **SELL/HEDGE** | ≤ -2 | Consider reducing risk / 考虑减仓对冲 |
| 🔴 **STRONG SELL** | ≤ -5 | Strong bearish signals / 强烈看跌信号 |
| 🔥 **EUPHORIA SELL** | ≤ -6 | Extreme greed, sell signal / 极度贪婪，卖出信号 |
### 📈 Dashboard Indicators / 仪表盘指标解读
| Indicator | Bullish 🟢 | Bearish 🔴 |
|-----------|------------|------------|
| Overall Bias | STRONG BUY / BUY DIP | STRONG SELL / SELL/HEDGE |
| AI Score | ≥ 5 (Extreme Fear) | ≤ -5 (Extreme Greed) |
| Market Trend | 🟢SPX 🟢NDX (Above MA200) | 🔴SPX 🔴NDX (Below MA200) |
| VIX Regime | LOW VOL (<15) | HIGH VOL (>25) |
| Term Struct Z | < -2.0 (Panic) | > 2.0 (Complacency) |
---
## ⚙️ Configuration / 配置选项
### 📡 Data Sources / 数据源
- **VIX Symbol**: Default `CBOE:VIX` (Alternative: `TVC:VIX`)
- **Put/Call Ratio**: Default `INDEX:CPCI` (Index P/C)
- **Timeframe**: Daily (stable) or Chart (real-time)
### ⚠️ Strategy Mode / 策略模式
- **High (Scalping)**: Sensitive, for short-term trades / 高敏感，短线
- **Normal (Swing)**: Balanced approach / 平衡模式
- **Low (Trend/Safe)**: Conservative, trend-following / 保守，趋势跟踪
### 🔬 Backtest Mode / 回测模式
- **OFF (Real-time)**: Shows current day data, suitable for live monitoring / 显示当日数据，适合实盘监控
- **ON (Historical)**: Uses only confirmed data, avoids look-ahead bias / 仅使用已确认数据，避免未来函数
---
## 📖 Usage Guide / 使用指南
### Best Practices / 最佳实践
1. **Apply to SPX/SPY/QQQ daily charts** for optimal signal accuracy
在 SPX/SPY/QQQ 日线图上使用，信号准确度最佳
2. **Wait for next trading day** to execute signals (signals trigger on daily close)
信号触发后在下一交易日执行（信号基于日线收盘）
3. **Use in conjunction with price action** for confirmation
结合价格走势确认信号
4. **Enable Market Trend Filter** (MA200) for safer entries in uncertain markets
开启趋势过滤（MA200）以在不确定市场中更安全入场
### Signal Interpretation / 信号解读
```
🚨 CRASH BUY (Score ≥ 6)
→ Rare extreme panic event
→ Historical average return: significant positive over 2 months
→ Consider aggressive positioning
🟢 STRONG BUY (Score ≥ 5)
→ Multiple indicators align
→ Historical average return: positive over 1 month
→ Consider building positions
🟡 BUY DIP (Score ≥ 4)
→ Moderate fear detected
→ Suitable for adding to existing positions
→ Filtered out in bear markets if Trend Filter is ON
```
---
## 📊 Historical Statistics / 历史统计
The indicator tracks signal frequency and average subsequent returns:
- **CRASH BUY**: 40-day return period (~2 months)
- **STRONG BUY**: 20-day return period (~1 month)
- **BUY DIP**: 10-day return period (~2 weeks)
指标追踪信号频率和后续平均收益，可在仪表盘中查看历史统计。
---
## 🔔 Alerts / 警报
Built-in alert conditions with cooldown mechanism to prevent spam:
| Alert | Condition |
|-------|-----------|
| Crash Buy Alert | Score ≥ 6, extreme panic |
| Strong Buy Alert | Score ≥ 5, multi-factor confluence |
| Buy Dip Alert | Score ≥ threshold |
| Euphoria Sell Alert | Score ≤ -6, extreme greed |
| Strong Sell Alert | Score ≤ -5 |
| VIX Basis Panic | VIX spot premium spike |
---
## 📋 Changelog / 更新日志
### v7.0 (Current)
- ✨ Three-tier buy/sell signal system
- 📊 Signal statistics with average return tracking
- 🔬 Backtest Mode toggle for historical testing
- 🎨 Configurable ±1 Z-Score reference lines
- ⚡ Modular scoring functions
- 🛡️ Dual index trend display (SPX + NDX)
- 📱 Compact & Full dashboard modes
---
## ⚠️ Disclaimer / 免责声明
**English:**
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always do your own research and consider your risk tolerance before trading.
**中文：**
本指标仅供教育和信息参考，不构成投资建议。过往表现不代表未来收益。交易前请自行研究并评估风险承受能力。
---
## 📄 License / 许可证
MIT License - Feel free to use, modify, and share.
---
## 🤝 Contributing / 贡献
Issues and pull requests are welcome!
欢迎提交问题和贡献代码！
---
**Made with ❤️ for the trading community**
**为交易社区用心打造**
ICT/SMC DOL Detector PRO (Final)This indicator is designed to operate only on the 1-hour timeframe.
The ICT/SMC DOL Detector PRO is an educational indicator designed to identify and visualize Draw on Liquidity (DOL) levels across multiple time-frames. It tracks unmitigated daily highs and lows, clusters them into zones, and calculates confidence scores based on multiple factors including time decay, cluster size, and time-frame alignment.
This indicator is based on ICT (Inner Circle Trader) concepts and liquidity theory, which suggests that price tends to seek out areas of concentrated unfilled orders before reversing or continuing its trend.
What is a DOL (Draw on Liquidity)?
A Draw on Liquidity represents a daily high or low that has not been revisited (mitigated) by price. These levels act as "magnets" that draw price toward them because:
1. They represent untapped liquidity pools where unfilled orders exist
2. Market makers and institutions often target these levels to fill large orders
3. Price is drawn to these zones to clear pending orders
4. They can serve as potential reversal or continuation zones once liquidity is taken
Methodology
1. Level Tracking
The indicator monitors daily session highs and lows on the 1-hour time-frame, tracking:
- Session high price and time of formation
- Session low price and time of formation
- Whether each level has been breached (mitigated)
- Time elapsed since level formation
2. Clustering Algorithm
Unmitigated levels within a defined tolerance (default 0.5% of price) are grouped together to identify zones where multiple DOLs cluster. Larger clusters indicate stronger liquidity pools.
3. Confidence Scoring (The "AI" Logic)
Each DOL receives a confidence score (0-100%) based on three weighted factors. This is the core "AI" intelligence of the indicator:
**Factor 1: Cluster Size (50% weight)**
- Counts how many unmitigated levels exist within 0.5% of the price zone
- Formula: (levels_in_cluster / total_unmitigated_levels) × 50
- Logic: More unfilled orders clustered together = stronger liquidity pool = higher confidence
- Example: If 5 out of 10 total unmitigated levels cluster at 27,500, cluster score = (5/10) × 50 = 25%
**Factor 2: Time Decay (25% weight)**
- Calculates age of the level since formation
- Fresh levels (< 1 week old): Full 25% score
- Aging penalty: Loses 5% per week of age
- Maximum penalty: 25% (very old levels = 0% time score)
- Formula: max(0, 25 - (weeks_old × 5))
- Logic: Recent liquidity is more relevant than old liquidity that price has ignored for months
**Factor 3: Timeframe Alignment (25% weight)**
- Checks how many timeframes (1H, 4H, D1, W1) point in the same direction
- If multiple timeframes identify DOLs on the same side (all bullish or all bearish): Higher score
- If mixed signals: Lower score
- Formula: (aligned_timeframes / total_timeframes) × 25
- Logic: When multiple timeframes agree, the liquidity zone is validated across different time perspectives
**Total Confidence Score:**
```
Confidence = Cluster_Score + Time_Score + Alignment_Score
= (0-50%) + (0-25%) + (0-25%)
= 0-100%
```
**Example Calculation:**
```
DOL at 27,500:
- 6 out of 12 unmitigated levels cluster here → (6/12) × 50 = 25%
- Level is 2 weeks old → 25 - (2 × 5) = 15%
- 3 out of 4 timeframes bullish toward this level → (3/4) × 25 = 18.75%
- Total Confidence = 25% + 15% + 18.75% = 58.75% ≈ 59%
```
This mathematical approach removes subjectivity and provides objective, data-driven confidence scoring.
4. Multi-Timeframe Analysis
The indicator analyzes DOLs across four timeframes:
- **1H:** Intraday levels (fastest reaction)
- **4H:** Short-term swing levels
- **Daily:** Intermediate-term levels
- **Weekly:** Long-term structural levels
For each timeframe, it identifies:
- Highest confidence unmitigated high
- Highest confidence unmitigated low
- Directional bias (bullish if high > low confidence, bearish if low > high confidence)
5. Primary DOL Selection (AI Auto-Selection Logic)
When "Show AI DOL" is enabled, the indicator uses an automated selection algorithm to identify the most important targets:
**Step 1: Collect All Candidates**
The algorithm gathers all identified DOLs from all timeframes (1H, 4H, D1, W1) that meet minimum criteria:
- Must be unmitigated (not yet swept)
- Must have confidence score > 0%
- Must have at least 1 level in cluster
**Step 2: Calculate Confidence for Each**
Each candidate DOL receives its confidence score using the three-factor formula described above (Cluster + Time + Alignment).
**Step 3: Sort by Confidence**
All candidates are ranked from highest to lowest confidence score.
**Step 4: Select Primary and Secondary**
- **P1 (Primary DOL):** The DOL with the absolute highest confidence score
- **P2 (Secondary DOL):** The DOL with the second highest confidence score
**Why This Matters:**
Instead of manually scanning multiple timeframes and guessing which level is most important, the AI objectively identifies the two highest-probability liquidity targets based on quantifiable data.
**Example AI Selection:**
```
Available DOLs:
- 1H High: 27,400
- 4H High: 27,500
- D1 High: 27,500 ← P1 (Highest)
- W1 High: 27,650 ← P2 (Second Highest)
- 1H Low: 26,800
- D1 Low: 26,500
AI Selection:
P1 = 27,500 (Daily High with 92% confidence)
P2 = 27,650 (Weekly High with 88% confidence)
```
This provides a data-driven target selection rather than subjective manual interpretation. The AI removes emotion and bias, selecting targets based purely on mathematical probability.
Features
Why "AI" DOL?
The term "AI" in this indicator refers to the automated algorithmic selection process, not machine learning or neural networks. Specifically:
**What the AI Does:**
- Automatically evaluates all available DOLs across all timeframes
- Applies a weighted scoring algorithm (Cluster 50%, Time 25%, Alignment 25%)
- Objectively ranks DOLs by probability
- Selects the top 2 highest-confidence targets (P1 and P2)
- Removes human bias and emotion from target selection
**What the AI Does NOT Do:**
- It does not use machine learning or train on historical data
- It does not predict future price movements
- It does not adapt or "learn" over time
- It does not guarantee accuracy
The "AI" is simply an automated decision-making algorithm that applies consistent mathematical rules to identify the most statistically significant liquidity zones. Think of it as a "smart filter" rather than artificial intelligence in the traditional sense.
Visual Components
**Daily Level Lines:**
- Green lines: Unmitigated (not yet breached) levels
- Red lines: Mitigated (already breached) levels
- Dots at origin point showing where level was formed
- X marker when level gets breached
- Lines extend forward to show projection
**DOL Labels:**
- Display timeframe (1H, 4H, D1, W1) or "DOL" for AI selection
- Show confidence percentage in brackets
- Color-coded by timeframe:
- Lime: AI DOL (Smart selection)
- Aqua: 1-hour timeframe
- Blue: 4-hour timeframe
- Purple: Daily timeframe
- Orange: Weekly timeframe
**Info Box (Top Right):**
Displays comprehensive liquidity metrics:
- Total levels tracked
- Active (unmitigated) levels count
- Cleared (mitigated) levels count
- Flow direction (BID PRESSURE / OFFER PRESSURE)
- Most recent sweep
- Primary and Secondary DOL targets
- Multi-timeframe bias analysis
- Overall directional bias
Settings Explained
**Daily Levels Group:**
- Show Daily Highs/Lows: Toggle visibility of all daily level tracking
- Unbreached Color: Color for levels not yet hit
- Breached Color: Color for levels that have been swept
- Show X on Breach: Display marker when level is breached
- Show Dot at Origin: Display marker at level formation point
- Line Width: Thickness of level lines (1-5)
- Line Extension: How many bars forward to project (1-24)
- Max Days to Track: Historical lookback period (5-200 days)
**DOL Settings Group:**
- Cluster Tolerance %: Price range to group DOLs (0.1-2.0%)
- Show Price on Labels: Display actual price value on labels
- Backtest Mode: Only show recent labels for clean historical analysis
- Labels Lookback: Number of bars to show labels when backtesting (10-500)
**Info Box Group:**
- Show Info Box: Toggle info panel visibility
**DOL Toggles Group:**
- Show AI DOL: Display smart auto-selected primary target
- Show 1HR DOL: Display 1-hour timeframe DOLs
- Show 4HR DOL: Display 4-hour timeframe DOLs
- Show Daily DOL: Display daily timeframe DOLs
- Show Weekly DOL: Display weekly timeframe DOLs
**Advanced Group:**
- Manual Mode: Simplified display showing only daily high/low clusters
How to Use This Indicator
Educational Application
This indicator is intended for educational purposes to help traders:
1. **Understand Liquidity Concepts:** Visualize where unfilled orders may exist
2. **Identify Key Levels:** See where price may be drawn to
3. **Analyze Market Structure:** Understand how price interacts with liquidity
4. **Study Multi-Timeframe Alignment:** Observe when multiple timeframes agree
5. **Learn ICT Concepts:** Apply liquidity theory in practice
Interpretation Guidelines
**BID PRESSURE (Flow):**
When lows are being swept more than highs, it suggests:
- Sell-side liquidity being taken
- Potential for upward move to unfilled buy-side liquidity
- Market may be clearing the way for a bullish move
**OFFER PRESSURE (Flow):**
When highs are being swept more than lows, it suggests:
- Buy-side liquidity being taken
- Potential for downward move to unfilled sell-side liquidity
- Market may be clearing the way for a bearish move
**Confidence Scores:**
- 90-100%: Very high probability zone (strong cluster, recent, aligned)
- 80-89%: High probability zone (good cluster, relatively recent)
- 70-79%: Moderate probability zone (decent cluster or older)
- 60-69%: Lower probability zone (small cluster or very old)
- Below 60%: Weak zone (minimal confluence)
**Timeframe Analysis:**
- All timeframes LONG: Strong bullish alignment
- All timeframes SHORT: Strong bearish alignment
- Mixed: Conflicting signals, exercise caution
- Higher timeframes (D1, W1) carry more weight than lower (1H, 4H)
**DIRECTIONAL Indicator:**
- BULLISH: Overall bias suggests upward movement toward buy-side DOLs
- BEARISH: Overall bias suggests downward movement toward sell-side DOLs
- NEUTRAL: No clear directional bias, conflicting signals
Practical Application Examples
**Example 1: Bullish Setup**
```
Flow: BID PRESSURE (lows being swept)
P1: 27,500 (price above current market)
D1: LONG 27,500
W1: LONG 27,650
DIRECTIONAL: BULLISH
```
Interpretation: Price has cleared sell-side liquidity. High confidence buy-side DOL at 27,500. Daily and Weekly timeframes aligned bullish. Watch for move toward 27,500 target.
**Example 2: Bearish Setup**
```
Flow: OFFER PRESSURE (highs being swept)
P1: 26,200 (price below current market)
D1: SHORT 26,200
W1: SHORT 26,100
DIRECTIONAL: BEARISH
```
Interpretation: Price has cleared buy-side liquidity. High confidence sell-side DOL at 26,200. Daily and Weekly timeframes aligned bearish. Watch for move toward 26,200 target.
**Example 3: Mixed Signals - Wait**
```
Flow: BID PRESSURE
P1: 26,800
D1: LONG 27,000
W1: SHORT 26,200
DIRECTIONAL: NEUTRAL
```
Interpretation: Conflicting signals. Flow suggests up, but Weekly bias is down. Confidence scores moderate. Better to wait for clarity.
Important Considerations
This Indicator Does NOT:
- Predict the future
- Guarantee profitable trades
- Provide buy/sell signals
- Replace proper risk management
- Work in isolation without other analysis
This Indicator DOES:
- Visualize liquidity concepts
- Identify potential target zones
- Show timeframe alignment
- Calculate objective confidence scores
- Help understand market structure
Proper Usage:
1. Use as one component of a complete trading strategy
2. Combine with price action analysis
3. Confirm with other technical indicators
4. Consider fundamental factors
5. Always use proper risk management
6. Backtest any strategy before live trading
Risk Disclaimer
**FOR EDUCATIONAL PURPOSES ONLY**
This indicator is for educational purposes only. Trading financial markets involves substantial risk of loss. Past performance does not guarantee future results. Always conduct your own research and consult with a financial advisor before making trading decisions.
**Important Limitations:**
- No indicator is 100% accurate, including the AI selection
- The "AI" is an automated algorithm, not predictive artificial intelligence
- DOL levels can be swept and price can continue in the same direction
- Confidence scores are mathematical calculations, not predictions or probabilities of success
- High confidence does not mean guaranteed profit
- Markets can remain irrational longer than you can remain solvent
- Always use stop losses and proper position sizing
**Understanding the AI Component:**
The AI auto-selection feature uses a fixed mathematical formula to rank DOLs. It does not:
- Predict where price will go
- Learn from past performance
- Adapt to market conditions
- Guarantee any level of accuracy
The confidence score represents the mathematical strength of a liquidity cluster based on objective factors (cluster size, recency, timeframe alignment), NOT a probability of the trade succeeding.
**Risk Warning:**
Trading is risky. Most traders lose money. This indicator cannot change that fundamental reality. Use it as an educational tool to understand market structure, not as a trading signal or system.
Technical Requirements
- **Timeframe:** Best used on 1-hour charts (required for accurate daily level tracking)
- **Markets:** Works on any market (forex, crypto, stocks, futures, indices)
- **Updates:** Real-time calculation on each bar close
- **Resources:** Uses max 500 lines and 500 labels (TradingView limits)
Backtesting Features
The indicator includes "Backtest Mode" to keep historical charts clean:
- When enabled, only shows labels from recent bars
- Adjustable lookback period (10-500 bars)
- All lines remain visible
- Helps review past setups without clutter
To use:
1. Enable "Backtest Mode" in settings
2. Adjust "Labels Lookback" to desired period
3. Review historical price action
4. Disable for live trading
Credits and Methodology
This indicator implements concepts from:
- ICT (Inner Circle Trader) liquidity theory
- Smart Money Concepts (SMC)
- Order flow analysis
- Multi-timeframe analysis principles
The clustering algorithm, confidence scoring, and timeframe synthesis are original implementations designed to quantify and visualize these concepts.
Version History
**v1.0 - Initial Release**
- Multi-timeframe DOL detection
- Confidence scoring system
- Info box with liquidity metrics
- Backtest mode for clean charts
- Black/white professional theme
Support and Updates
For questions, feedback, or suggestions, please use the TradingView comments section. Updates and improvements will be released as needed based on user feedback and market evolution.
**Remember:** This is an educational tool. Successful trading requires knowledge, discipline, risk management, and continuous learning. Use this indicator to enhance your understanding of market structure and liquidity, not as a standalone trading system.
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。
TradingIQ - Reversal IQIntroducing "Reversal IQ" by TradingIQ
Reversal IQ is an exclusive trading algorithm developed by TradingIQ, designed to trade trend reversals in the market. By integrating artificial intelligence and IQ Technology, Reversal IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Reversal IQ
Reversal IQ integrates IQ Technology (AI) with the timeless concept of reversal trading. Markets follow trends that inevitably reverse at some point. Rather than relying on rigid settings or manual judgment to capture these reversals, Reversal IQ dynamically designs, creates, and executes reversal-based trading strategies.
Reversal IQ is designed to work straight out of the box. In fact, its simplicity requires just one user setting, making it incredibly straightforward to manage.
AI Aggressiveness is the only setting that controls how Reversal IQ works.
Traders don’t have to spend hours adjusting settings and trying to find what works best - Reversal IQ handles this on its own.
Key Features of Reversal IQ
Self-Learning Reversal Detection
Employs AI and IQ Technology to identify trend reversals in real-time.
AI-Generated Trading Signals
Provides reversal trading signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
AI-Determined Profit Target and Stop Loss
Position exit levels are clearly defined and calculated by the AI once the trade is entered.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Configurable AI Aggressiveness
Allows users to adjust the AI's aggressiveness to match their trading style and risk tolerance.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
IQ Channel
The IQ Channel represents what Reversal IQ considers a tradable long opportunity or a tradable short opportunity. The channel is dynamic and adjusts from chart to chart.
IQMA – Proprietary Moving Average
Introduces the IQ Moving Average (IQMA), designed to classify overarching market trends.
IQCandles – Trend Classification Tool
Complements IQMA with candlestick colors designed for trend identification and analysis.
How It Works
Reversal IQ operates on a straightforward heuristic: go long during an extended downside move and go short during an extended upside move.
What defines an "extended move" is determined by IQ Technology, TradingIQ's exclusive AI algorithm. For Reversal IQ, the algorithm assesses the extent to which historical high and low prices are breached. By learning from these price level violations, Reversal IQ adapts to trade future, similar violations in a recurring manner. It calculates a price area, distant from the current price, where a reversal is anticipated.
In simple terms, price peaks (tops) and troughs (bottoms) are stored for Reversal IQ to learn from. The degree to which these levels are violated by subsequent price movements is also recorded. Reversal IQ continuously evaluates this stored data, adapting to market volatility and raw price fluctuations to better capture price reversals.
What classifies as a price top or price bottom?
For Reversal IQ, price tops are considered the highest price attained before a significant downside reversal. Price bottoms are considered the lowest price attained before a significant upside reversal. The highest price achieved is continuously calculated before a significant counter trend price move renders the high price as a swing high. The lowest price achieved is continuously calculated before a significant counter trend price move renders the low price as a swing low.
The image above illustrates the IQ channel and explains the corresponding prices and levels
The blue lower line represents the Long Reversal Level, with the price highlighted in blue showing the Long Reversal Price.
The red upper line represents the Short Reversal Level, with the price highlighted in red showing the Short Reversal Price.
Limit orders are placed at both of these levels. As soon as either level is touched, a trade is immediately executed.
The image above shows a long position being entered after the Long Reversal Level was reached. The profit target and stop loss are calculated by Reversal IQ
The blue line indicates where the profit target is placed (acting as a limit order).
The red line shows where the stop loss is placed (acting as a stop loss order).
Green arrows indicate that the strategy entered a long position at the highlighted price level.
You can also hover over the trade labels to get more information about the trade—such as the entry price, profit target, and stop loss.
The image above demonstrates the profit target being hit for the trade. All profitable trades are marked by a blue arrow and blue line. Hover over the blue arrow to obtain more details about the trade exit.
The image above depicts a short position being entered after the Short Reversal Level was touched. The profit target and stop loss are calculated by the AI
The blue line indicates where the profit target is placed (acting as a limit order).
The red line shows where the stop loss is placed (acting as a stop loss order).
The image above shows the profit target being hit for the short trade. Profitable trades are indicated by a blue arrow and blue line. Hover over the blue arrow to access more information about the trade exit.
Long Entry: Green Arrow
Short Entry: Red Arrow
Profitable Trades: Blue Arrow
Losing Trades: Red Arrow
IQMA
The IQMA implements a dynamic moving average that adapts to market conditions by adjusting its smoothing factor based on its own slope. This makes it more responsive in volatile conditions (steeper slopes) and smoother in less volatile conditions.
The IQMA is not used by Reversal IQ as a trade condition; however, the IQMA can be used by traders to characterize the overarching trend and elect to trade only long positions during bullish conditions and only short positions during bearish conditions.
The IQMA is an adaptive smoothing function that applies a combination of multiple moving averages to reduce lag and noise in the data. The adaptiveness is achieved by dynamically adjusting the Volatility Factor (VF) based on the slope (derivative) of the price trend, making it more responsive to strong trends and smoother in consolidating markets.
This process effectively makes the moving average a self-adjusting filter, the IQMA attempts to track both trending and ranging market conditions by dynamically changing its sensitivity in response to price movements.
When IQMA is blue, an overarching uptrend is in place. When IQMA is red, an overarching downtrend is in place.
IQ Candles
IQ Candles are price candles color-coordinated with IQMA. IQ Candles help visualize the overarching trend and are not used by Reversal IQ to determine trade entries and trade exits.
AI Aggressiveness
Reversal IQ has only one setting that controls its functionality.
AI Aggressiveness controls the aggressiveness of the AI. This setting has three options: Sniper, Aggressive, and Very Aggressive.
Sniper Mode
In Sniper Mode, Reversal IQ will prioritize trading large deviations from established reversal levels and extracting the largest countertrend move possible from them.
Aggressive Mode
In Aggressive Mode, Reversal IQ still prioritizes quality but allows for strong, quantity-based signals. More trades will be executed in this mode with tighter stops and profit targets. Aggressive mode forces Reversal IQ to learn from narrower raw-dollar violations of historical levels.
Very Aggressive Mode
In Very Aggressive Mode, Reversal IQ still prioritizes the strongest quantity-based signals. Stop and target distances aren't inherently affected, but entries will be aggressive while prioritizing performance. Very Aggressive mode forces Reversal IQ to learn from narrower raw-dollar violations of historical levels and also forces it to embrace volatility more aggressively.
AI Direction
The AI Direction setting controls the trade direction Reversal IQ is allowed to take.
“Both” allows for both long and short trades.
“Long” allows for only long trades.
“Short” allows for only short trades.
Verifying Reversal IQ’s Effectiveness
Reversal IQ automatically tracks its performance and displays the profit factor for the long strategy and the short strategy it uses. This information can be found in a table located in the top-right corner of your chart.
The image above shows the long strategy profit factor and the short strategy profit factor for Reversal IQ.
A profit factor greater than 1 indicates a strategy profitably traded historical price data.
A profit factor less than 1 indicates a strategy unprofitably traded historical price data.
A profit factor equal to 1 indicates a strategy did not lose or gain money when trading historical price data.
Using Reversal IQ
While Reversal IQ is a full-fledged trading system with entries and exits, it was designed for the manual trader to take its trading signals and analysis indications to greater heights - offering numerous applications beyond its built-in trading system.
The hallmark feature of Reversal IQ is its sniper-like reversal signals. While exits are dynamically calculated as well, Reversal IQ simply has a knack for "sniping" price reversals.
When performing live analysis, you can use the IQ Channel to evaluate price reversal areas, whether price has extended too far in one direction, and whether price is likely to reverse soon.
Of course, in times of exuberance or panic, price may push through the reversal levels. While infrequent, it can happen to any indicator.
The deeper price moves into the bullish reversal area (blue) the better chance that price has extended too far and will reverse to the upside soon. The deeper price moves into the bearish reversal area (red) the better chance that price has extended too far and will reverse to the downside soon.
Of course, you can set alerts for all Reversal IQ entry and exit signals, effectively following along its systematic conquest of price movement.
Paid script
Palgo Trading - Palgo🎯THE PALGO INDICATOR
The "Palgo Trading - Palgo" indicator, developed by PALGOTRADING is a sophisticated technical analysis tool designed to identify potential buy and sell signals by combining trend analysis with momentum and optional AI-driven sentiment assessment. This indicator provides a clear visual representation of potential trading opportunities directly on the price chart.
At its core, the Palgo indicator synthesizes information from well-established technical analysis concepts with statistical functions, and has optional AI Integration for social analysis of the asset using external data :
Supertrend: This indicator identifies the prevailing trend direction. A positive Supertrend value suggests an upward trend, while a negative value indicates a downward trend. The Palgo indicator utilizes a Supertrend with a customizable multiplier and a user-configurable Average True Range (ATR) length (defaulting to 21).
🛜Signal Generation Logic
The indicator generates buy and sell signals based on a calculated "final direction" value. This value is derived by combining the Supertrend direction and a modified RSI. The modification involves scaling the RSI output to a range of -0.5 to 0.5 and then further adjusting it.
The buy and sell conditions are as follows:
Buy Signal: A buy signal is triggered when the "final direction" crosses above a positive activation threshold while the current signal is not already bullish. Upon signal generation, a "Buy" label (colored green) appears below the bar, and initial Take Profit (TP) and Stop Loss (SL) levels are calculated and stored.
Sell Signal: Conversely, a sell signal is triggered when the "final direction" crosses below a negative activation threshold while the current signal is not already bearish. A "Sell" label (colored red) is plotted above the bar, and corresponding TP and SL levels are determined.
✅ Optimized Take-Profit / Stop-Loss
The Take-Profit (TP) & Stop-Loss (SL) signals are optimized with Kernel Density Estimation (KDE), the script uses KDE activated by gaussian function on previous pivot points and trains the model, then tries to estimate new pivot points early, to determine new TP / SL levels for the current signal. Kernel Density Estimation takes values of the previous confirmed pivots' RSI values, body size & more factors to determine their role. This indicator can generate up to 5 TP signals per signal.
📈 Signal Trail
Palgo also includes a "Signal Trail" that visually shows the market's momentum. This trail is like a dynamic line that follows the price.
When the market is in an uptrend and looking strong, you'll see a green trail.
When it's in a downtrend and looking weak, you'll see a red trail.
This trail helps you see if the market is currently aligned with Palgo's bullish (buy) or bearish (sell) signal. It also acts as a visual guide for potential support or resistance levels.
📊Backtesting Dashboard
The Palgo indicator includes an optional Backtesting Dashboard to help you understand its historical performance. This dashboard appears directly on your chart and provides a quick summary of how the indicator's signals have performed in the past.
Here's what you'll see on the dashboard:
Sensitivity: This shows the specific "Sensitivity" setting you've chosen for the indicator. This setting influences how often signals are generated.
Wins: This number tells you how many trades initiated by the Palgo indicator historically ended in profit (reached a Take-Profit target or closed profitably when the signal reversed).
Loss: This number indicates how many trades historically ended in a loss (hit the Stop-Loss).
Winrate: This is a very important metric, displayed as a percentage. It shows you the proportion of winning trades compared to the total number of trades (Wins / (Wins + Loss)). A higher winrate generally suggests a more effective strategy.
This dashboard is a valuable tool for reviewing the indicator's effectiveness with different settings and helping you make informed decisions about its use in your trading.
🤖AI Integration (Optional):
A unique feature of the Palgo indicator is the optional integration of Artificial Intelligence (AI) sentiment analysis. When the "Use AI" input is enabled, the indicator incorporates two additional user-defined inputs:
Impression Change %: This input represents the percentage change in overall market sentiment as assessed by an external AI.
Positivity Change: This input reflects the change in positive sentiment, also provided by an AI.
These AI inputs are combined to create an "AI Score," which then influences the "final direction" calculation. A positive AI Score amplifies the bullish signals and dampens bearish signals, while a negative AI Score has the opposite effect.
❓Why PALGO ?
All-in-One Analysis: Palgo combines trend, momentum, and advanced statistical analysis into one easy-to-use tool, giving you a complete picture without needing multiple indicators.
Dynamic Profit & Loss Management: Unlike many tools with fixed targets, Palgo's smart profit and stop-loss system adapts to the market using KDE. This helps you potentially capture more gains and limit losses effectively.
Optional AI Insights: For an extra edge, Palgo can tap into Artificial Intelligence (AI) to gauge overall market mood. If the AI sees a lot of positive buzz, it can strengthen buy signals; if it's negative, it can reinforce sell signals. This helps you trade with a better understanding of the market's pulse.
Clear and Customizable: Palgo is designed to be very visual. It changes the color of the price bars, adds clear "Buy" or "Sell" labels, and marks your profit and stop-loss points. You can also change the colors to suit your preference.
Palgo aims to be a comprehensive and adaptable trading tool, giving you clearer insights.
⚙️Visualizations and Customization
The Palgo indicator offers several visual cues to aid traders:
Bar Coloring: The price bars are colored green when the indicator identifies a bullish signal and red during a bearish signal.
Signal Labels: Clear "Buy" and "Sell" labels are plotted at the signal generation points.
Take Profit and Stop Loss Markers: Distinct shapes and labels indicate when the price reaches the calculated TP and SL levels.
Style Options: Users can customize the colors for bullish and bearish bars, text, and TP/SL markers within the indicator's settings.
TradingIQ - Nova IQIntroducing "Nova IQ" by TradingIQ
Nova IQ is an exclusive Trading IQ algorithm designed for extended price move scalping. It spots overextended micro price moves and bets against them. In this way, Nova IQ functions similarly to a reversion strategy.
Nova IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Nova IQ
Nova IQ integrates AI with the concept of central-value reversion scalping. On lower timeframes, prices may overextend for small periods of time - which Nova IQ looks to bet against. In this sense, Nova IQ scalps against small, extended price moves on lower timeframes.
Nova IQ is designed to work straight out of the box. In fact, its simplicity requires just one user setting, making it incredibly straightforward to manage.
Use HTF (used to apply a higher timeframe trade filter) is the only setting that controls how Nova IQ works.
Traders don’t have to spend hours adjusting settings and trying to find what works best - Nova IQ handles this on its own.
Key Features of Nova IQ
Self-Learning Market Scalping
Employs AI and IQ Technology to scalp micro price overextensions.
AI-Generated Trading Signals
Provides scalping signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Higher Timeframe Filter
Allows users to implement a higher timeframe trading filter.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
Nova Oscillator (NOSC)
The Nova IQ Oscillator (NOSC) is an exclusive self-learning oscillator developed by Trading IQ. Using IQ Technology, the NOSC functions as an all-in-one oscillator for evaluating price overextensions.
Nova Bands (NBANDS)
The Nova Bands (NBANDS) are based on a proprietary calculation and serve as a custom two-layer smoothing filter that uses exponential decay. These bands adaptively smooth prices to identify potential trend retracement opportunities.
How It Works
Nova IQ operates on a simple heuristic: scalp long during micro downside overextensions and short during micro upside overextensions.
What constitutes an "overextension" is defined by IQ Technology, TradingIQ's proprietary AI algorithm. For Nova IQ, this algorithm evaluates the typical extent of micro overextensions before a reversal occurs. By learning from these patterns, Nova IQ adapts to identify and trade future overextensions in a consistent manner.
In essence, Nova IQ learns from price movements within scalping timeframes to pinpoint price areas for capitalizing on the reversal of an overextension.
As a trading system, Nova IQ enters all positions using market orders at the bar’s close. Each trade is exited with a profit-taking limit order and a stop-loss order. Thanks to its self-learning capability, Nova IQ determines the most suitable profit target and stop-loss levels, eliminating the need for the user to adjust any settings.
What classifies as a tradable overextension?
For Nova IQ, tradable overextensions are not manually set but are learned by the system. Nova IQ utilizes NOSC to identify and classify micro overextensions. By analyzing multiple variations of NOSC, along with its consistency in signaling overextensions and its tendency to remain in extreme zones, Nova IQ dynamically adjusts NOSC to determine what constitutes overextension territory for the indicator.
When NOSC reaches the downside overextension zone, long trades become eligible for entry. Conversely, when NOSC reaches the upside overextension zone, short trades become eligible for entry.
The image above illustrates NOSC and explains the corresponding overextension zones
The blue lower line represents the Downside Overextension Zone.
The red upper line represents the Upside Overextension Zone.
Any area between the two deviation points is not considered a tradable price overextension.
When either of the overextension zones are breached, Nova IQ will get to work at determining a trade opportunity.
The image above shows a long position being entered after the Downside Overextension Zone was reached.
The blue line on the price scale shows the AI-calculated profit target for the scalp position. The redline shows the AI-calculated stop loss for the scalp position.
Blue arrows indicate that the strategy entered a long position at the highlighted price level.
Yellow arrows indicate a position was closed.
You can also hover over the trade labels to get more information about the trade—such as the entry price and exit price.
The image above depicts a short position being entered after the Upside Overextension Zone was breached.
The blue line on the price scale shows the AI-calculated profit target for the scalp position. The redline shows the AI-calculated stop loss for the scalp position.
Red arrows indicate that the strategy entered a short position at the highlighted price level.
Yellow arrows indicate that NOVA IQ exited a position.
Long Entry: Blue Arrow
Short Entry: Red Arrow
Closed Trade: Yellow Arrow
Nova Bands
The Nova Bands (NBANDS) are based on a proprietary calculation and serve as a custom two-layer smoothing filter that uses exponential decay and cosine factors.
These bands adaptively smooth the price to identify potential trend retracement opportunities.
The image above illustrates how to interpret NBANDS. While NOSC focuses on identifying micro overextensions, NBANDS is designed to capture larger price overextensions. As a result, the two indicators complement each other well and can be effectively used together to identify a broader range of price overextensions in the market.
While the Nova Bands are not part of the core heuristic and do not use IQ technology, they provide valuable insights for discretionary traders looking to refine their strategies.
Use HTF (Use Higher Timeframe) Setting
Nova IQ has only one setting that controls its functionality.
“Use HTF” controls whether the AI uses a higher timeframe trading filter. This setting can be true or false. If true, the trader must select the higher timeframe to implement.
No Higher TF Filter
Nova IQ operates with standard aggression when the higher timeframe setting is turned off. In this mode, it exclusively learns from the price data of the current chart, allowing it to trade more aggressively without the influence of a higher timeframe filter.
Higher TF Filter
Nova IQ demonstrates reduced aggression when the "Use HTF" (Higher Timeframe) setting is enabled. In this mode, Nova IQ learns from both the current chart's data and the selected higher timeframe data, factoring in the higher timeframe trend when seeking scalping opportunities. As a result, trading opportunities only arise when both the higher timeframe and the chart's timeframe simultaneously display overextensions, making this mode more selective in its entries.
In this mode, Nova IQ calculates NOSC on the higher timeframe, learns from the corresponding price data, and applies the same rules to NOSC as it does for the current chart's timeframe. This ensures that Nova IQ consistently evaluates overextensions across both timeframes, maintaining its trading logic while incorporating higher timeframe insights.
AI Direction
The AI Direction setting controls the trade direction Nova IQ is allowed to take.
“Trade Longs” allows for long trades.
“Trade Shorts” allows for short trades.
Verifying Nova IQ’s Effectiveness
Nova IQ automatically tracks its performance and displays the profit factor for the long strategy and the short strategy it uses. This information can be found in a table located in the top-right corner of your chart showing the long strategy profit factor and the short strategy profit factor.
The image above shows the long strategy profit factor and the short strategy profit factor for Nova IQ.
A profit factor greater than 1 indicates a strategy profitably traded historical price data.
A profit factor less than 1 indicates a strategy unprofitably traded historical price data.
A profit factor equal to 1 indicates a strategy did not lose or gain money when trading historical price data.
Using Nova IQ
While Nova IQ is a full-fledged trading system with entries and exits - it was designed for the manual trader to take its trading signals and analysis indications to greater heights, offering numerous applications beyond its built-in trading system.
The hallmark feature of Nova IQ is its to ignore noise and only generate signals during tradable overextensions.
The best way to identify overextensions with Nova IQ is with NOSC.
NOSC is naturally adept at identifying micro overextensions. While it can be interpreted in a manner similar to traditional oscillators like RSI or Stochastic, NOSC’s underlying calculation and self-learning capabilities make it significantly more advanced and useful than conventional oscillators.
Additionally, manual traders can benefit from using NBANDS. Although NBANDS aren't a core component of Nova IQ's guiding heuristic, they can be valuable for manual trading. Prices rarely extend beyond these bands, and it's uncommon for prices to consistently trade outside of them.
NBANDS do not incorporate IQ Technology; however, when combined with NOSC, traders can identify strong double-confluence opportunities.
Paid script
NeuroPolynomial Channel🧠 NeuroPolynomial Channel – AI-Inspired Market Structure Engine
In modern market microstructure analysis, price is no longer treated as a simple line — it is viewed as a continuously evolving signal governed by nonlinear dynamics, volatility deformation, and behavioral state shifts.
The NeuroPolynomial Channel (NPC) is a mathematically structured, AI-inspired indicator designed to approximate this dynamic behavior using a hybrid of:
• Polynomial regression smoothing
• Neural blending functions
• Volatility-adaptive envelopes
• Distribution-based bias levels
While full deep-learning models cannot be directly implemented in Pine Script due to computational and architectural limitations, the NeuroPolynomial Channel brings core AI concepts into TradingView through mathematically constrained approximations, creating an efficient, real-time neural structure model suitable for intraday and swing analysis.
📐 Mathematical Foundation
NPC is not a standard moving average or simple channel system.
It applies a multi-layer non-linear approximation built on four core mathematical components.
1️⃣ NeuroPolynomial Core Line
At the heart of the system lies a recursive polynomial smoothing kernel inspired by neural weighted blending:
K = α · K
+ (1 - α) · P
+ Δx · ( K - K ) / F
Where:
• K = Neuro core estimate
• P = Current price input
• α = Neural morph factor
• F = Flattening constant
• Δx = Position delta (horizontal deformation component)
The recursive references introduce memory similar to RNN-style feedback behavior.
This produces a structurally smooth, non-linear trajectory that adapts to both local and historical price deformation.
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2️⃣ Neural Volatility Envelope
Instead of classical standard deviation, NPC uses a cumulative error field:
E = ( Σ | P - K | ) / N
Using this error field, the dynamic envelope bands are constructed as:
Inner Band = K ± E · m1
Mid Band = K ± E · m2
Outer Band = K ± E · m3
Where:
• m1, m2, m3 are probabilistic band multipliers
• E represents actual observed deviation, not synthetic volatility
This creates a probabilistic price container that deforms with real market behavior rather than static statistical assumptions.
The channel automatically adapts its curvature based on current price regime:
trending, compressing, or expanding.
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3️⃣ Neural Regression Spine
Alongside the polynomial core, NPC calculates a ridge-regularized regression spine:
y = β · x + α (with L2 regularization)
This acts as a structural bias vector or "neural backbone".
It prevents overfitting and provides directional stabilization during extended trend phases.
......................................................................................................
4️⃣ Neuro Bias Zones (Daily Reset)
NPC also introduces daily volatility-anchored regime thresholds:
Z_levels = Open ± ATR_daily × {0.1, 0.382, 0.618}
These act as:
• Neuro Mid Zones – equilibrium bands
• Neuro Strong Zones – trend activation boundaries
Unlike classical pivot systems, these levels reset daily and expand dynamically based on real volatility.
They approximate probability field boundaries similar to those used in institutional volatility modeling.
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🤖 AI Philosophy
While Pine Script cannot host full neural networks, GPU models or multi-layer AI pipelines, NeuroPolynomial Channel introduces AI concepts through mathematical abstraction, including:
• Neural blending mechanics
• Memory-based recursion
• Volatility adaptation
• Bias field modeling
• Structured envelope projection
This creates an AI-style behavior using real-time deterministic mathematics — allowing performance on TradingView while preserving interpretability and stability.
🛠 How To Use
NPC is designed for structure-based interpretation, not random signal chasing.
① Trend Structure
Use the Neural Core Line and channel slope to establish trend direction and regime.
② Compression & Expansion
Observe band width.
Contracting channels signal volatility compression.
Expanding channels signal range expansion.
③ Bias Zones
Neuro Mid and Strong levels act as macro intraday bias framework — especially powerful for session trading and index futures.
⚙️ Settings Overview
• Morph Factor – Controls neural blending strength (higher = smoother, lower = reactive)
• Flatten – Reduces polynomial curvature noise
• Band Multipliers – Adjust envelope thickness
• Neural Bias Levels – ATR-anchored regime zones resetting daily
• Theme & Visual Controls – Dark/Light with pro-grade visibility
........................................................................................................
Companion AI:
I also built a free Trading AI on ChatGPT that reads chart screenshots and enforces a rule-based intraday checklist.
Use with this indicator: chatgpt.com
For educational & decision-support only. Not financial advice.
............................................................................................................
⚠️ Disclaimer
The information contained in my Scripts / Indicators / Ideas / Systems does not constitute financial advice or a solicitation to buy or sell any securities.
All markets carry risk. This tool is for educational and analytical purposes only.
I do not accept liability for any financial loss or damage resulting from direct or indirect use of this script.
Trading decisions must be made independently based on your own risk profile and financial assessment.
FVG & Order Block Sync Pro - Enhanced🏦 FVG & Order Block Sync Pro Enhanced
The AI-Powered Institutional Trading System That Changes Everything
Tired of Guessing Where Price Will Go Next?
What if you could see EXACTLY where banks and institutions are placing their orders?
Introducing the FVG & Order Block Sync Pro Enhanced - the first indicator that combines institutional Smart Money Concepts with next-generation AI technology to reveal the hidden blueprint of the market.
🎯 Finally, Trade Alongside the Banks - Not Against Them
For years, retail traders have been fighting a losing battle. Why? Because they can't see what the institutions see.
Until now.
Our revolutionary indicator exposes:
🏛️ Institutional Order Blocks - The exact zones where banks accumulate positions
💰 Fair Value Gaps - Price inefficiencies that act as magnets for future price movement
📊 Real-Time Structure Breaks - Know instantly when smart money shifts direction
🎯 Banker Candle Patterns - Spot institutional rejection zones before reversals
🤖 Next-Level AI Technology That Thinks Like a Bank Trader
This isn't just another indicator with arrows. Our advanced AI engine:
Analyzes 100+ Data Points Per Second across multiple timeframes
Machine Learning Pattern Recognition that improves with every trade
Multi-Symbol Correlation Analysis to confirm institutional flow
Predictive Sentiment Scoring that gauges market momentum in real-time
Confluence Algorithm that rates every signal from 0-10 for probability
Result? You're not following indicators - you're following institutional order flow.
📈 Perfect for Forex & Futures Markets
Whether you're trading:
Major Forex Pairs (EUR/USD, GBP/USD, USD/JPY)
Futures Contracts (ES, NQ, CL, GC)
Indices (S&P 500, NASDAQ, DOW)
Commodities (Gold, Oil, Silver)
The indicator adapts to any market that institutions trade - because it tracks THEIR footprints.
💎 What Makes This Different?
1. SMC + Market Structure Fusion
First indicator to combine Order Blocks, FVG, BOS, and CHOCH in one system
Shows not just WHERE to trade, but WHY price will move there
2. The "Sync" Advantage
Only signals when BOTH Fair Value Gap AND Order Block align
Filters out 73% of false signals that single-concept indicators miss
3. Institutional-Grade Dashboard
See what a bank trader sees: 5 timeframes at once
Real-time strength meters showing institutional momentum
Multi-symbol analysis for correlation confirmation
AI-powered signal strength scoring
4. No More Analysis Paralysis
Clear BUY/SELL signals with exact entry zones
Built-in stop loss and take profit levels
Signal strength rating tells you position size
📊 Real Traders, Real Results
"I went from a 45% win rate to 78% in just 3 weeks. The ability to see where banks are operating completely changed my trading." - Sarah T., Forex Trader
"The AI signal strength feature alone paid for this indicator 10x over. I only take 8+ scores now and my account has never been more consistent." - Mike D., Futures Trader
"Finally an indicator that shows market structure properly. The CHOCH alerts saved me from countless losing trades." - Alex R., Day Trader
🚀 Everything You Get:
✅ Institutional Zone Detection - FVG, Order Blocks, Liquidity Zones
✅ AI-Powered Analysis - ML patterns, sentiment scoring, predictive algorithms
✅ Market Structure Mastery - BOS/CHOCH with visual trend lines
✅ Multi-Timeframe Dashboard - 5 timeframes updated in real-time
✅ Banker Candle Recognition - Spot institutional reversals
✅ Advanced Alert System - Never miss a high-probability setup
✅ Risk Management Built-In - Automatic position sizing guidance
✅ Works on ALL Timeframes - From 1-minute scalping to daily swing trading
🎓 Who This Is Perfect For:
Frustrated Traders tired of indicators that lag behind price
Serious Traders ready to level up with institutional concepts
Forex Traders wanting to catch major pair movements
Futures Traders seeking precise ES/NQ entries
Anyone who wants to stop gambling and start trading with the banks
⚡ The Bottom Line:
Every day, institutions move billions through the markets. They leave footprints. This indicator reveals them.
Stop trading blind. Start trading with institutional vision.
While other traders are still drawing trend lines and hoping for the best, you'll be entering positions at the exact zones where smart money operates.
🔥 Limited Time Bonus Features:
Multi-Symbol Analysis - Track 3 correlated pairs simultaneously
AI Confidence Scoring - Know exactly when NOT to trade
Volume Confluence Filters - Confirm institutional participation
Custom Alert Templates - Set up once, trade anywhere
Free Updates Forever - As the AI learns, your edge grows
💪 Make the Decision That Changes Your Trading Forever
Every day you trade without seeing institutional zones is a day you're trading with a massive disadvantage.
The banks aren't smarter than you. They just see things you don't.
Until you add this indicator to your chart.
Join thousands of traders who've discovered what it feels like to trade WITH the flow of institutional money instead of against it.
Because when you can see what the banks see, you can trade like the banks trade.
⚠️ Risk Disclaimer: Trading forex and futures carries significant risk. Past performance doesn't guarantee future results. This indicator is a tool for analysis, not a guarantee of profits. Always use proper risk management.
🎯 Transform your trading. See the market through institutional eyes. Get the FVG & Order Block Sync Pro Enhanced today.
The difference between amateur and professional trading is information. Now you can have both.
Mxwll OptAlgoIntroducing the Mxwll OptAlgo
Mxwll OptAlgo is a sophisticated algorithmic trading tool designed to identify potential long and short signals. It leverages an optimized combination of the M-Swift average, M-Smooth average, and M-RSI to fine-tune custom lengths and improve signal accuracy. The Mxwll OptAlgo provides long and short signals across various trading assets and timeframes. Additionally, it features optimized Take Profit (TP) and Stop Loss (SL) settings to help traders manage risk.
Key Features
Step-by-Step Complete Optimization: A systematic approach to optimize trading parameters.
Buy/Sell Signals: Clear indicators for long and short positions.
Easy to Use: User-friendly interface for seamless trading.
Predictive counter trend channels
Integrated trend following system and counter trend trading system
3-optimized strategies working cooperatively
Alerts and auto trading capabilities
How It Works
The Mxwll OptAlgo is comprised of three strategies:
Trend following using the OptAlgo
AI Reversal counter trend trading
Market crash shorting
Mxwll OptAlgo can be used for market analysis and trading similarly to any moving average.
The Mxwll OptAlgo MA is composed of two distinct moving averages to be used for trend following strategies.
M-Swift Average: The M-Swift Average accounts for volume and weights current price movement heavier than older price movement - allowing for improved responsiveness to current price movement. Volume is additionally weighted to the average to determine the significance of the price move and the resulting response of the M-Swift average. The M-Swift average consists of an HVWMA with OBV weighting. The HVWMA is used to create a moving average that adapts to volume, attempting to respond to significant price moves with high volume quicker and significant price moves with low volume slower - which might not be indicative of the start of a strong trend. To further reduce the M-Swift average’s responsiveness to weak volume price moves, the average is weighted with a normalized OBV. With this, the M-Swift moving average uses these two indicators to create a responsive moving average to significant price moves with high volume.
M-Smooth Average: The M-Smooth average consists of a McGinley average.
The McGinley Average is designed to address some of the limitations of traditional moving averages, such as the Simple Moving Average (SMA) or Exponential Moving Average (EMA), by reducing their lag and more accurately reflecting the market's true movements, especially during periods of volatility.
The McGinley Dynamic automatically adjusts its smoothing factor based on market speed. This means it responds more quickly to fast-moving markets and slows down during periods of consolidation, reducing the likelihood of false signals.
Unlike traditional moving averages that have a fixed period and can lag significantly behind fast-moving prices, the McGinley Dynamic adjusts dynamically, which helps to reduce lag and keeps the moving average closer to the price action.
The M-Smooth average uses bar low prices as a series during an uptrend - bar high prices as a series during a downtrend. A cross above the M-Smooth average indicates an uptrend, while a cross below the M-Smooth average indicates a downtrend. When this cross event occurs the M-Smooth average will “flip” from calculating on lows to highs, or highs to lows, contingent on the direction of the trend. The expectation is that a cross event of the M-Smooth average requires a substantial price move and, subsequent to this cross, price will continue to trend in the direction of the cross.
OptAlgo: The OptAlgo is simply the average of the M-Swift average and the M-smooth average.
By combining the M-Swift average and the M-Smooth average, the final output results in an average that slows during ranging markets and quickly adjusts to high volume breakouts and high volume reversals that initiate a trend. Due to the combination, the average will keep up quickly with a trend but remain at an appropriate distance from the current price - requiring a significant counter trend price move to change the direction of the OptAlgo average.
How does the OptAlgo follow trends?
The OptAlgo, comprising the two moving averages above, considers a cross event of the OptAlgo as a change in trend indication. The OptAlgo can be thought of as a moving average that significantly deviates from price. For price to cross the OptAlgo, a substantial price move must occur, and this event is treated as a "strong trend" or "new trend" indication.
M-RSI: The M-RSI is a fundamental component of the trend following strategy. Prior to a trend following “long” or “short” signal, the M-RSI must generate a signal in confluence with an OptAlgo cross event. When price crosses over the opt algo its color will change to green, indicating an uptrend. A buy signal will generate should the M-RSI provide a similar indication. The M-RSI portion of the trend following strategy is explained below. When price crosses under the opt algo its color will change to green, indicating a downtrend, and a sell signal becomes eligible. The foundational logic for using the Opt Algo as a trend following strategy is to treat crossovers/crossunders of the Opt Algo as strong trend indications, and trade them.
Steps to generate a trend following long signal:
1: M-RSI extends into oversold territory
2: Price crosses over the OptAlgo
Steps to generate a trend following short signal:
1: M-RSI extends into overbought territory
2: Price crosses under the OptAlgo
Our trend following strategy considers crossovers/crossunders at key market turning points as buy/sell opportunities. This strategy integrates the Mxwll RSI and Mxwll OptAlgo MA to determine entry points in anticipation of trend continuation.
The Mxwll RSI must move below/above the optimized OB/OS level prior to a cross event for a long/short signal to be considered. Entry points for this strategy are marked as "Long" or "Short".
At its core, the OptAlgo trend following strategy tries to enter a trend as close to the origin point as possible. As with any trend following strategy, price may not continue to move in the expected direction following entry, resulting in a losing trade.
AI Reversal Predictions
Our AI reversals strategy uses AI suggested turning points to capitalize on price reversions back towards the OptAlgo. These levels are considered by the AI on the selected days, and entry points at these levels are marked as "LLO" or "SLO".
How AI reversals work
Our AI reversals strategy attempts to trade price reversions back toward the Opt Algo.
These levels are calculated on specific days of the week, but can be traded any day. The internal algorithm determines which HTF highs/lows are most likely to function as tradable support/resistance levels. For instance, if Friday consists of heavy trading activity and high/low prices are tracked/recorded as causing significant support / resistance when tested in the future, the algorithm will consider support and resistance levels created on Friday as future tradable levels.
Additionally, if support/resistance levels created on Wednesday are recorded as weak or unpredictable when traded at in the future, the algorithm will not consider support/resistance levels generated on Thursday as tradable, and will not generate long or shit signals for these levels.
In the background, the AI reversals strategy is tracking success rates at multiple support and resistance levels. The best performers, if there are any, will be considered tradable. A “best performer” is calculated as the raw price move up to a threshold (i.e. 0.5%) that occurs subsequent to a test of the level.
Crash Short
The "Crash Short" strategy prioritizes short positions during retracements of a sell off. A simple yet effective strategy.
How Crash Short Works
The Crash Short strategy uses a customized momentum indicator (similar to ROC, MOM, etc.) to identify strong downside price moves. When our customized momentum indicator gives strong sell indications, the RSI is then referenced to identify an upside retracement. When the RSI exceeds a user-inputted level, a “Crash Short” signal is generated.
What is the customized momentum indicator?
The customized momentum indicator is the RoCR (Rate of Change Ratio). Instead of classic ROC, which is close - close , the RoCR divides the current close by a previous close. This formula creates a ratio that is more normalized than a simple price difference. This ratio is used to determine upside/downside momentum, with values greater than 1 indicating bullish momentum and values less than 1 indicating bearish momentum. The RoCR looks for deviating values to the downside (less than 1) to identify strong selling. From there, once the RSI crosses over an optimized level (such as 35), the indicator will print a sell signal titled "Crash Short".
Predictive Countertrend Channels
Our Predictive Countertrend Channel applies a two-stage recursive filter to smooth data using exponential decay and periodic adjustments for trend extraction. Our counter trend channels aren't directly used for signal processing; however, these channels provide useful visual cues for extended market moves.
Instructions for Optimization
Step 1: Optimize Mxwll OptAlgo
Begin by optimizing the M-Swift and M-Smooth averages for better signal accuracy.
This step simply finds better performing M-Swift and M-Smooth lookbacks. Again, if the strategy is unprofitable you will be notified and from there decide not to use the strategy.
Step 2: Optimize Mxwll RSI
Refine the Mxwll RSI settings to explore potential adjustments in smoothness and signal output. This step aims to evaluate whether these adjustments could improve the accuracy of the signals generated by Mxwll OptAlgo, while being mindful of any potential impacts.
Step 3: Optimize TP/SL
Consider adjusting the Take Profit and Stop Loss settings to potentially manage risk.
Step 4: Optimize Bars Between Trades
Set the number of bars between trades to regulate the frequency of trade executions. This adjustment may help in reducing the risk of overtrading and support a more disciplined trading strategy.
Step 5: Optimize Trade Flip
Adjust the trade flip parameters to potentially improve the management of transitions between long and short positions. This adjustment is intended to help achieve smoother trade executions, though outcomes may vary.
Step 6: Optimize RSI OB/OB Levels
Consider adjusting the overbought (OB) and oversold (OS) RSI levels to explore potential improvements in signal sensitivity. Careful calibration of these levels may help refine the accuracy of trend reversal signals, although results may depend on market conditions.
Finished!
From this point, consider setting alerts to make the most of the Mxwll Opt Algo's potential accuracy.
The effectiveness of the Opt Algo signal output can be evaluated using the "PF" table, which indicates the profit factor score for the strategy. A profit factor (PF) of less than or equal to 1 suggests that the strategy may not be profitable.
Disclaimer
No strategy works on any timeframe on any asset, so, if the Opt Algo underperforms for the asset/timeframe you're analyzing, the Opt Algo PF table lets you know it hasn't been generating accurate signals, in which case you can decide not to use it!
Optimization Disclaimer
Optimization can be tricky. It's helpful to test numerous strategies in aggregate to see if a strategy has potential. Despite this, optimization can cause overfitting. Overfitting occurs when a strategy is too closely fit to the data it's trading. Overfit backtests are deceptively phenomenal. While the historical performance looks great, the future expectancy of the strategy remains unpredictable - an overfit strategy will profit from periods of random price movement which, being random, are irreproducible and cannot be profited from other than their initial occurrence. When a strategy trades random price movement profitably, any and all profit earned can be reduced to chance. Keep this in mind when using the in-built optimization system. Optimization should be kept to a minimum, a tool to point you in the right direction, whether confirming potential or signifying a useless system.
Reversal Algo (Zeiierman)█ Overview
Reversal Algo (Zeiierman) is an adaptive reversal and momentum detection system that helps identify hidden turning points, pressure zones, and changes in market direction. It brings together advanced modeling techniques such as dynamic volatility bands, adaptive trend tracking, and momentum-based confirmation signals into one clear, visual framework.
Unlike traditional reversal indicators that depend on static oscillators or fixed levels, this tool adapts in real time to market movement. It tracks volatility and directional flow to reveal when momentum is building, slowing down, or preparing to reverse.
Whether applied to short-term scalping, swing positioning, or macro structural validation, this tool provides an adaptive analytical environment that translates complex price dynamics into actionable context.
⚪ Why This One Is Unique
This version of Reversal Algo employs multi-domain adaptive modeling, combining envelope projection, trend inertia estimation, and contrarian equilibrium tracking within a single structure.
Its framework merges nonlinear smoothing manifolds with volatility-compensated directional phase mapping, allowing it to evolve with shifting market states rather than react to them.
Optional AI-driven optimizations enhance precision in unstable regimes by dynamically reshaping envelopes and tracking lines around localized flow curvature.
█ Main Features
⚪ Reversal Cloud
The Reversal Cloud highlights areas of potential expansion, compression, and turning points in price. It adapts to volatility by expanding when markets become unstable and tightening during periods of calm, creating a visual map of market rhythm and elasticity.
When the Cloud widens, it often signals exhaustion or increased turbulence; when it narrows, it suggests balance or an upcoming breakout.
With AI mode enabled, the Cloud automatically fine-tunes its shape to align with live price behavior, keeping its structure responsive and accurate.
⚪ Reversal Signals
Reversal Signals are designed to identify potential market turning points with precision. They combine multiple layers of price behavior—momentum shifts, directional changes, and balance-point deviations—to highlight areas where reversals are statistically more likely. To reduce false clusters, the system intelligently filters out repeated signals within a short time window.
⚪ Reversal/Exit Points
Reversal/Exit Points appear as small, color-coded dots above or below candles. They signal moments where price momentum slows or where the system detects a potential shift in directional strength. These markers are often found near short-term highs or lows, making them ideal for identifying profit-taking zones, re-entry setups, or early warnings of a possible reversal.
⚪ Trend Framework
The Trend Framework provides a clean visualization of the market’s prevailing direction. It smooths out short-term noise to reveal the core trend structure, showing when the market is expanding, contracting, or transitioning between phases.
This framework helps traders quickly see whether price action supports continuation or if the trend is weakening.
⚪ Trend Tracker Line
The Trend Tracker Line is a highly responsive trend detector that reacts quickly to shifts in momentum. It adapts dynamically to volatility, providing an accurate real-time view of directional acceleration and deceleration. This helps traders spot early changes in market tone and evaluate whether a move has the strength to continue.
When AI mode is enabled, the line automatically adjusts its sensitivity to remain stable and consistent across different market conditions.
⚪ Contrarian Bar Coloring
Contrarian Candle Coloring enhances chart readability by visually distinguishing strength from weakness. Green bars highlight areas of building upward momentum, while red bars point to potential pressure or exhaustion. The system continuously adapts its color transitions to reflect subtle momentum shifts, making it easier to recognize when the market is gaining or losing conviction.
An optional AI mode fine-tunes these transitions to match the current market rhythm, ensuring that candle coloration always reflects the underlying flow of strength and weakness.
█ How to Use
⚪ Reversal Trading
The primary purpose of the indicator is to identify reversal opportunities in the market. Reversal or contrarian trading means entering positions against the current directional move in anticipation of a fade or trend rotation. This approach often occurs in high-volatility environments, so it is important to widen your stops, reduce your initial position size, and, if appropriate, scale or average into positions carefully rather than committing all capital at once.
The Reversal Algo provides predefined Buy and Sell signals designed to highlight potential market peaks and troughs. While these signals are highly accurate, they are not meant to call every top or bottom perfectly. In a strong trending market, several reversal signals may appear consecutively before the market fully turns.
⚪ Reversal Signal + Candle Coloring
Combine Reversal Signals with Contrarian Candle Coloring for added confirmation. A practical approach is to wait for a Reversal Signal and then look for a color shift in the candles (for example, from contrarian-colored to standard candles). This color transition acts as confirmation that the active move may be losing strength and that a reversal could be underway.
⚪ Reversal Signals + Reversal Cloud
Consider taking reversal entries only when price interacts with the Reversal Cloud boundaries. The Cloud’s upper and lower layers act as dynamic resistance and support zones. When a Reversal Signal appears near or immediately after price rejection from one of these layers, it adds structural confirmation to the setup and strengthens the case for entry.
⚪ Reversal Signals + Key Levels
One of the most effective ways to trade Reversal Signals is by combining them with key price levels, such as the previous day’s high, low, or close. If price rejects one of these levels while a Reversal Signal prints simultaneously, the confluence of the two events serves as strong validation for a potential turning point.
⚪ Take Profit
The Reversal/Exit Points can function both as entry confirmations and as take-profit zones. If a Reversal Signal was missed but a new Reversal/Exit Point appears near a peak or trough, it can indicate a late-entry opportunity aligned with exhaustion behavior.
These dots are most powerful as profit-taking signals. Since they form near local highs and lows, they often mark regions of temporary imbalance where reversals are likely. When a Reversal/Exit Point forms in the opposite direction of your current position, consider taking partial profits or tightening stops to lock in gains while maintaining participation in the broader move.
█ How It Works
⚪ Reversal Cloud Engine
The Reversal Cloud defines the dynamic upper and lower boundaries of market elasticity by transforming recent price displacements into a smooth volatility field. Through multi-layered envelope modeling, it constructs a continuous topology of expansion and compression zones, revealing where directional energy accumulates or dissipates.
Calculation: Uses layered volatility envelopes that adapt to changing market speed and expansion. A built-in alignment mechanism keeps the upper and lower bands synchronized, while optional AI optimization adjusts the symmetry of the cloud based on short-term directional bias.
⚪ Trend Tracker System
The Trend Tracker isolates directional persistence by modeling angular displacement of price flow over adaptive temporal curvature. It interprets slope evolution as a continuously evolving directional vector field, capturing both acceleration and deceleration within the active regime.
Calculation: Applies adaptive slope modeling to estimate the dominant direction of price flow. The system smooths fluctuations dynamically while maintaining responsiveness to significant shifts in trend velocity. When AI mode is active, an intelligent weighting adjustment refines the tracker’s equilibrium bias for better phase synchronization.
⚪ Trend
The Trend module projects a dual-polarity directional lattice, distinguishing constructive (positive) and distributive (negative) flow environments. It defines equilibrium corridors that expand and contract with evolving trend geometry, offering visual feedback on regime strength and transition probability.
Calculation: Uses weighted directional regression to estimate upper, middle, and lower trend layers. Each structure is color-coded based on price slope and relative position, creating a continuous and easy-to-read trend map.
⚪ Contrarian Bar Coloring Engine
Contrarian bar coloring converts raw bar data into a slope-weighted momentum matrix, visually encoding thrust versus decay phases in real time. It acts as a microstructural interpreter of price inertia, identifying acceleration clusters and momentum fatigue through color transitions.
Calculation: Combines slope analysis and volatility normalization to evaluate how strong or weak each price bar is relative to its trend. The results are reflected in real-time color changes that emphasize momentum strength and fatigue.
⚪ Reversal/Exit System
Reversal and Exit Points are derived from an evolving volatility-based trail that tracks directional exhaustion and reversion potential. These markers visualize transitions in directional energy—helping traders anticipate trend slowdowns or reversal probabilities.
Calculation: Constructs an adaptive volatility trail that contracts as directional momentum weakens. A state-aware detection model identifies inflection points where pressure changes polarity, producing the plotted up/down dots that mark possible reversals or exits. This ensures that each signal dynamically reflects real-time shifts in market energy rather than static thresholds.
⚪ Reversal Signals Core
The Reversal System’s entry framework is designed for precision. It combines several layers of short-term momentum analysis into clear, directionally aligned signals. By balancing different market speeds and measuring how far the price moves from its equilibrium, it identifies high-probability areas where trends may continue or reverse.
Calculation: Implements a composite synchronization framework that aligns short-term momentum phases with equilibrium drift and directional bias. Redundant triggers are filtered out through temporal separation logic, ensuring only the most distinct and reliable signals are displayed. Adaptive thresholds adjust automatically based on volatility and trading mode, maintaining signal consistency across scalp, intraday, and swing environments.
⚪ AI-Adaptive Optimization Layer
The AI layer refines selected modules — Reversal Cloud, Trend Tracker, and Contrarian Candles — by continuously recalibrating their internal weighting curves according to volatility structure and price curvature. It acts as an intelligent stabilizer that adjusts smoothing depth, boundary stiffness, and gradient bias dynamically.
Calculation: Utilizes a Context-Aware Kernel Adjustment Engine, estimating curvature variance and phase imbalance to auto-tune envelope response. The model performs iterative self-alignment to preserve directional fidelity under rapidly changing flow dynamics.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Paid script
Powell's Brain Mk.4.4 [Scalper Edition]Title: Powell's Brain Mk.4.4
Description
Powell's Brain is a mechanical scalping system designed for volatile assets (like SPY, QQQ, NVDA, and TSLA) on 1-minute and 5-minute timeframes.
Unlike standard indicators that spam signals at every crossover, this script uses a "Subtractive" Philosophy. It starts with a trend crossover signal and then runs it through a squad of 6 distinct filters. If any filter detects low probability (chop, low volume, weak momentum), the trade is blocked.
This is the Scalper Edition, tuned to catch V-Shape reversals while still protecting capital during sideways chop.
🧠 How It Works
The system relies on the confluence of four market forces: Momentum, Energy, Trend Strength, and AI Confirmation.
1. The Core Strategy (The Engine)
Dual EMA Crossover: Uses a Fast (9) and Slow (50) EMA to identify immediate trend changes.
Slope Detection: A trade is only considered if the EMAs are separating with sufficient velocity (0.04% slope threshold). This prevents trading when lines are flat/tangled.
2. The "No" Squad (Filters)
A signal is rejected unless it passes these checks:
Volume Gate: Volume must be at least 80% (0.8x) of the 20-period average. This filters out pre-market noise or lunch-hour apathy.
ADX Shield: The Average Directional Index must be > 20. If ADX is lower, the market is chopping, and the script forces you to sit on your hands.
Time-of-Day: By default, it targets "Prime Hours" (09:30–11:00 & 14:00–16:00 EST) to avoid the "lunchtime trap."
Cooldown: Enforces a 3-bar wait period between signals to prevent signal flickering in high-volatility zones.
3. The AI Engine (k-NN Machine Learning)
Included is a k-Nearest Neighbors (k-NN) implementation that analyzes historical RSI and Relative Volume patterns.
It compares the current market state to the last ~1,000 bars.
It calculates a "Confidence %" based on how often similar past setups resulted in a bullish or bearish move.
AI Gating: You can enable a "Strict Mode" in settings where the script will block any trade that the AI does not agree with (Confidence < 55%).
4. The Squeeze Filter (TTM Logic)
An optional filter allows you to trade only on volatility expansion (Bollinger Bands exiting Keltner Channels). This is disabled by default to allow for standard trend scalping but can be enabled for breakout hunting.
🚦 How to Use
The Signals:
Green "CALL" Label: Bullish Momentum + Volume + Trend Strength.
Red "PUT" Label: Bearish Momentum + Volume + Breakdown.
The HUD (Heads-Up Display):
Monitor the top-right panel for Market Flow, Squeeze Status, and AI Confidence.
If the AI text is Orange ("INITIALIZING"), wait for more data to load.
The Debugger:
If you see a crossover but NO signal, turn on "Show Debug Labels" in settings.
The chart will print exactly why the trade was skipped (e.g., Vol❌ means volume was too low, Slope❌ means the trend was too flat).
⚙️ Settings Guide
Strategy Core: Adjust Min EMA Separation to tune sensitivity. Higher = Fewer, safer trades. Lower = Faster entries.
Filters:
Trade with 200 EMA Trend: Keep OFF for scalping reversals. Turn ON for strict trend following.
Gate Entries with AI: Turn ON if you want the Machine Learning engine to veto low-confidence setups.
Visuals: Toggle Dark/Light themes to match your chart.
Disclaimer
This script is a tool for identifying high-probability setups based on historical data and technical analysis. It does not guarantee future performance. Always use proper risk management (Stop Losses are included in the logic visuals). In less words DON'T BE AN IDIOT.
By FallenAngel666
Curvature Tensor Pivots - HIVECurvature Tensor Pivots - HIVE
I. CORE CONCEPT & ORIGINALITY
Curvature Tensor Pivots - HIVE is an advanced, multi-dimensional pivot detection system that combines differential geometry, reinforcement learning, and statistical physics to identify high-probability reversal zones before they fully form. Unlike traditional pivot indicators that rely on simple price comparisons or lagging moving averages, this system models price action as a smooth curve in geometric space and calculates its mathematical curvature (how sharply the price trajectory is "bending") to detect pivots with scientific precision.
What Makes This Original:
Differential Geometry Engine: The script calculates first and second derivatives of price using Kalman-filtered trajectory analysis, then computes true mathematical curvature (κ) using the classical formula: κ = |y''| / (1 + y'²)^(3/2). This approach treats price as a physical phenomenon rather than discrete data points.
Ghost Vertex Prediction: A proprietary algorithm that detects pivots 1-3 bars BEFORE they complete by identifying when velocity approaches zero while acceleration is high—this is the mathematical definition of a turning point.
Multi-Armed Bandit AI: Four distinct pivot detection strategies (Fast, Balanced, Strict, Tensor) run simultaneously in shadow portfolios. A Thompson Sampling reinforcement learning algorithm continuously evaluates which strategy performs best in current market conditions and automatically selects it.
Hive Consensus System: When 3 or 4 of the parallel strategies agree on the same price zone, the system generates "confluence zones"—areas of institutional-grade probability.
Dynamic Volatility Scaling (DVS): All parameters auto-adjust based on current ATR relative to historical average, making the indicator adaptive across all timeframes and instruments without manual re-optimization.
II. HOW THE COMPONENTS WORK TOGETHER
This is NOT a simple mashup —each subsystem feeds data into the others in a closed-loop learning architecture:
The Processing Pipeline:
Step 1: Geometric Foundation
Raw price is normalized against a 50-period SMA to create a trajectory baseline
A Zero-Lag EMA smooths the trajectory while preserving edge response
Kalman filter removes noise while maintaining signal integrity
Step 2: Calculus Layer
First derivative (y') measures velocity of price movement
Second derivative (y'') measures acceleration (rate of velocity change)
Curvature (κ) is calculated from these derivatives, representing how sharply price is turning
Step 3: Statistical Validation
Z-Score measures how many standard deviations current price deviates from the Kalman-filtered "true price"
Only pivots with Z-Score > threshold (default 1.2) are considered statistically significant
This filters out noise and micro-fluctuations
Step 4: Tensor Construction
Curvature is combined with volatility (ATR-based) and momentum (ROC-based) to create a multidimensional "tensor score"
This tensor represents the geometric stress in the price field
High tensor magnitude = high probability of structural failure (reversal)
Step 5: AI Decision Layer
All 4 bandit strategies evaluate current conditions using different sensitivity thresholds
Each strategy maintains a virtual portfolio that trades its signals in real-time
Thompson Sampling algorithm updates Bayesian priors (alpha/beta distributions) based on each strategy's Sharpe ratio, win rate, and drawdown
The highest-performing strategy's signals are displayed to the user
Step 6: Confluence Aggregation
When multiple strategies agree on the same price zone, that zone is highlighted as a confluence area. These represent "hive mind" consensus—the strongest setups
Why This Integration Matters:
Traditional indicators either detect pivots too late (lagging) or generate too many false signals (noisy). By requiring geometric confirmation (curvature), statistical significance (Z-Score), multi-strategy agreement (hive voting), and performance validation (RL feedback) , this system achieves institutional-grade precision. The reinforcement learning layer ensures the system adapts as market regimes change, rather than degrading over time like static algorithms.
III. DETAILED METHODOLOGY
A. Curvature Calculation (Differential Geometry)
The system models price as a parametric curve where:
x-axis = time (bar index)
y-axis = normalized price
The curvature at any point represents how quickly the direction of the tangent line is changing. High curvature = sharp turn = potential pivot.
Implementation:
Lookback window (default 8 bars) defines the local curve segment
Smoothing (default 5 bars) applies adaptive EMA to reduce tick noise
Curvature is normalized to 0-1 scale using local statistical bounds (mean ± 2 standard deviations)
B. Ghost Vertex (Predictive Pivot Detection)
Classical pivot detection waits for price to form a swing high/low and confirm. Ghost Vertex uses calculus to predict the turning point:
Conditions for Ghost Pivot:
Velocity (y') ≈ 0 (price rate of change approaching zero)
Acceleration (y'') ≠ 0 (change is decelerating/accelerating)
Z-Score > threshold (statistically abnormal position)
This allows detection 1-3 bars before the actual high/low prints, providing an early entry edge.
C. Multi-Armed Bandit Reinforcement Learning
The system runs 4 parallel "bandits" (agents), each with different detection sensitivity:
Bandit Strategies:
Fast: Low curvature threshold (0.1), low Z-Score requirement (1.0) → High frequency, more signals
Balanced: Standard thresholds (0.2 curvature, 1.5 Z-Score) → Moderate frequency
Strict: High thresholds (0.4 curvature, 2.0 Z-Score) → Low frequency, high conviction
Tensor: Requires tensor magnitude > 0.5 → Geometric-weighted detection
Learning Algorithm (Thompson Sampling):
Each bandit maintains a Beta distribution with parameters (α, β)
After each trade outcome, α is incremented for wins, β for losses
Selection probability is proportional to sampled success rate from the distribution
This naturally balances exploration (trying underperformed strategies) vs exploitation (using best strategy)
Performance Metrics Tracked:
Equity curve for each shadow portfolio
Win rate percentage
Sharpe ratio (risk-adjusted returns)
Maximum drawdown
Total trades executed
The system displays all metrics in real-time on the dashboard so users can see which strategy is currently "winning."
D. Dynamic Volatility Scaling (DVS)
Markets cycle between high volatility (trending, news-driven) and low volatility (ranging, quiet). Static parameters fail when regime changes.
DVS Solution:
Measures current ATR(30) / close as normalized volatility
Compares to 100-bar SMA of normalized volatility
Ratio > 1 = high volatility → lengthen lookbacks, raise thresholds (prevent noise)
Ratio < 1 = low volatility → shorten lookbacks, lower thresholds (maintain sensitivity)
This single feature is why the indicator works on 1-minute crypto charts AND daily stock charts without parameter changes.
E. Confluence Zone Detection
The script divides the recent price range (200 bars) into 200 discrete zones. On each bar:
Each of the 4 bandits votes on potential pivot zones
Votes accumulate in a histogram array
Zones with ≥ 3 votes (75% agreement) are drawn as colored boxes
Red boxes = resistance confluence, Green boxes = support confluence
These zones act as magnet levels where price often returns multiple times.
IV. HOW TO USE THIS INDICATOR
For Scalpers (1m - 5m timeframes):
Settings: Use "Aggressive" or "Adaptive" pivot mode, Curvature Window 5-8, Min Pivot Strength 50-60
Entry Signal: Triangle marker appears (🔺 for longs, 🔻 for shorts)
Confirmation: Check that Hive Sentiment on dashboard agrees (3+ votes)
Stop Loss: Use the dotted volatility-adjusted target line in reverse (if pivot is at 100 with target at 110, stop is ~95)
Take Profit: Use the projected target line (default 3× ATR)
Advanced: Wait for confluence zone formation, then enter on retest of the zone
For Day Traders (15m - 1H timeframes):
Settings: Use "Adaptive" mode (default settings work well)
Entry Signal: Pivot marker + Hive Consensus alert
Confirmation: Check dashboard—ensure selected bandit has Sharpe > 1.5 and Win% > 55%
Filter: Only take pivots with Pivot Strength > 70 (shown in dashboard)
Risk Management: Monitor the Live Position Tracker—if your selected bandit is holding a position, consider that as market structure context
Exit: Either use target lines OR exit when opposite pivot appears
For Swing Traders (4H - Daily timeframes):
Settings: Use "Conservative" mode, Curvature Window 12-20, Min Bars Between Pivots 15-30
Focus on Confluence: Only trade when 4/4 bandits agree (unanimous hive consensus)
Entry: Set limit orders at confluence zones rather than market orders at pivot signals
Confirmation: Look for breakout diamonds (◆) after pivot—these signal momentum continuation
Risk Management: Use wider stops (base stop loss % = 3-5%)
Dashboard Interpretation:
Top Section (Real-Time Metrics):
κ (Curv): Current curvature. >0.6 = active pivot forming
Tensor: Geometric stress. Positive = bullish bias, Negative = bearish bias
Z-Score: Statistical deviation. >2.0 or <-2.0 = extreme outlier (strong signal)
Bandit Performance Table:
α/β: Bayesian parameters. Higher α = more wins in history
Win%: Self-explanatory. >60% is excellent
Sharpe: Risk-adjusted returns. >2.0 is institutional-grade
Status: Shows which strategy is currently selected
Live Position Tracker:
Shows if the selected bandit's shadow portfolio is currently holding a position
Displays entry price and real-time P&L
Use this as "what the AI would do" confirmation
Hive Sentiment:
Shows vote distribution across all 4 bandits
"BULLISH" with 3+ green votes = high-conviction long setup
"BEARISH" with 3+ red votes = high-conviction short setup
Alert Setup:
The script includes 6 alert conditions:
"AI High Pivot" = Selected bandit signals short
"AI Low Pivot" = Selected bandit signals long
"Hive Consensus BUY" = 3+ bandits agree on long
"Hive Consensus SELL" = 3+ bandits agree on short
"Breakout Up" = Resistance breakout (continuation long)
"Breakdown Down" = Support breakdown (continuation short)
Recommended Alert Strategy:
Set "Hive Consensus" alerts for high-conviction setups
Use "AI Pivot" alerts for active monitoring during your trading session
Use breakout alerts for momentum/trend-following entries
V. PARAMETER OPTIMIZATION GUIDE
Core Geometry Parameters:
Curvature Window (default 8):
Lower (3-5): Detects micro-structure, best for scalping volatile pairs (crypto, forex majors)
Higher (12-20): Detects macro-structure, best for swing trading stocks/indices
Rule of thumb: Set to ~0.5% of your typical trade duration in bars
Curvature Smoothing (default 5):
Increase if you see too many false pivots (noisy instrument)
Decrease if pivots lag (missing entries by 2-3 bars)
Inflection Threshold (default 0.20):
This is advanced. Lower = more inflection zones highlighted
Useful for identifying order blocks and liquidity voids
Most users can leave default
Pivot Detection Parameters:
Pivot Sensitivity Mode:
Aggressive: Use in low-volatility range-bound markets
Normal: General purpose
Adaptive: Recommended—auto-adjusts via DVS
Conservative: Use in choppy, whipsaw conditions or for swing trading
Min Bars Between Pivots (default 8):
THIS IS CRITICAL for visual clarity
If chart looks cluttered, increase to 12-15
If missing pivots, decrease to 5-6
Match to your timeframe: 1m charts use 3-5, Daily charts use 20+
Min Z-Score (default 1.2):
Statistical filter. Higher = fewer but stronger signals
During news events (NFP, FOMC), increase to 2.0+
In calm markets, 1.0 works well
Min Pivot Strength (default 60):
Composite quality score (0-100)
80+ = institutional-grade pivots only
50-70 = balanced
Below 50 = will show weak setups (not recommended)
RL & DVS Parameters:
Enable DVS (default ON):
Leave enabled unless you want to manually tune for a specific market condition
This is the "secret sauce" for cross-timeframe performance
DVS Sensitivity (default 1.0):
Increase to 1.5-2.0 for extremely volatile instruments (meme stocks, altcoins)
Decrease to 0.5-0.7 for stable instruments (utilities, bonds)
RL Algorithm (default Thompson Sampling):
Thompson Sampling: Best for non-stationary markets (recommended)
UCB1: Best for stable, mean-reverting markets
Epsilon-Greedy: For testing only
Contextual: Advanced—uses market regime as context
Risk Parameters:
Base Stop Loss % (default 2.0):
Set to 1.5-2× your instrument's average ATR as a percentage
Example: If SPY ATR = $3 and price = $450, ATR% = 0.67%, so use 1.5-2.0%
Base Take Profit % (default 4.0):
Aim for 2:1 reward/risk ratio minimum
For mean-reversion strategies, use 1.5-2.0%
For trend-following, use 3-5%
VI. UNDERSTANDING THE UNDERLYING CONCEPTS
Why Differential Geometry?
Traditional technical analysis treats price as discrete data points. Differential geometry models price as a continuous manifold —a smooth surface that can be analyzed using calculus. This allows us to ask: "At what rate is the trend changing?" rather than just "Is price going up or down?"
The curvature metric captures something fundamental: inflection points in market psychology . When buyers exhaust and sellers take over (or vice versa), the price trajectory must curve. By measuring this curvature mathematically, we detect these psychological shifts with precision.
Why Reinforcement Learning?
Markets are non-stationary —statistical properties change over time. A strategy that works in Q1 may fail in Q3. Traditional indicators have fixed parameters and degrade over time.
The multi-armed bandit framework solves this by:
Running multiple strategies in parallel (diversification)
Continuously measuring performance (feedback loop)
Automatically shifting capital to what's working (adaptation)
This is how professional hedge funds operate—they don't use one strategy, they use ensembles with dynamic allocation.
Why Kalman Filtering?
Raw price contains two components: signal (true movement) and noise (random fluctuations). Kalman filters are the gold standard in aerospace and robotics for extracting signal from noisy sensors.
By applying this to price data, we get a "clean" trajectory to measure curvature against. This prevents false pivots from bid-ask bounce or single-print anomalies.
Why Z-Score Validation?
Not all high-curvature points are tradeable. A sharp turn in a ranging market might just be noise. Z-Score ensures that pivots occur at statistically abnormal price levels —places where price has deviated significantly from its Kalman-filtered "fair value."
This filters out 70-80% of false signals while preserving true reversal points.
VII. COMMON USE CASES & STRATEGIES
Strategy 1: Confluence Zone Reversal Trading
Wait for confluence zone to form (red or green box)
Wait for price to approach zone
Enter when pivot marker appears WITHIN the confluence zone
Stop: Beyond the zone
Target: Opposite confluence zone or 3× ATR
Strategy 2: Hive Consensus Scalping
Set alert for "Hive Consensus BUY/SELL"
When alert fires, check dashboard—ensure 3-4 votes
Enter immediately (market order or 1-tick limit)
Stop: Tight, 1-1.5× ATR
Target: 2× ATR or opposite pivot signal
Strategy 3: Bandit-Following Swing Trading
On Daily timeframe, monitor which bandit has best Sharpe ratio over 30+ days
Take ONLY that bandit's signals (ignore others)
Enter on pivot, hold until opposite pivot or target line
Position size based on bandit's current win rate (higher win% = larger position)
Strategy 4: Breakout Confirmation
Identify key support/resistance level manually
Wait for pivot to form AT that level
If price breaks level and diamond breakout marker appears, enter in breakout direction
This combines support/resistance with geometric confirmation
Strategy 5: Inflection Zone Limit Orders
Enable "Show Inflection Zones"
Place limit buy orders at bottom of purple zones
Place limit sell orders at top of purple zones
These zones represent structural change points where price often pauses
VIII. WHAT THIS INDICATOR DOES NOT DO
To set proper expectations:
This is NOT:
A "holy grail" with 100% win rate
A strategy that works without risk management
A replacement for understanding market fundamentals
A signal copier (you must interpret context)
This DOES NOT:
Predict black swan events
Account for fundamental news (you must avoid trading during major news if not experienced)
Work well in extremely low liquidity conditions (penny stocks, microcap crypto)
Generate signals during consolidation (by design—prevents whipsaw)
Best Performance:
Liquid instruments (SPY, ES, NQ, EUR/USD, BTC/USD, etc.)
Clear trend or range conditions (struggles in choppy transition periods)
Timeframes 5m and above (1m can work but requires experience)
IX. PERFORMANCE EXPECTATIONS
Based on shadow portfolio backtesting across multiple instruments:
Conservative Mode:
Signal frequency: 2-5 per week (Daily charts)
Expected win rate: 60-70%
Average RRR: 2.5:1
Adaptive Mode:
Signal frequency: 5-15 per day (15m charts)
Expected win rate: 55-65%
Average RRR: 2:1
Aggressive Mode:
Signal frequency: 20-40 per day (5m charts)
Expected win rate: 50-60%
Average RRR: 1.5:1
Note: These are statistical expectations. Individual results depend on execution, risk management, and market conditions.
X. PRIVACY & INVITE-ONLY NATURE
This script is invite-only to:
Maintain signal quality (prevent market impact from mass adoption)
Provide dedicated support to users
Continuously improve the algorithm based on user feedback
Ensure users understand the complexity before deploying real capital
The script is closed-source to protect proprietary research in:
Ghost Vertex prediction mathematics
Tensor construction methodology
Bandit reward function design
DVS scaling algorithms
XI. FINAL RECOMMENDATIONS
Before Trading Live:
Paper trade for minimum 2 weeks to understand signal timing
Start with ONE timeframe and master it before adding others
Monitor the dashboard —if selected bandit Sharpe drops below 1.0, reduce size
Use confluence and hive consensus for highest-quality setups
Respect the Min Bars Between Pivots setting —this prevents overtrading
Risk Management Rules:
Never risk more than 1-2% of account per trade
If 3 consecutive losses occur, stop trading and review (possible regime change)
Use the shadow portfolio as a guide—if ALL bandits are losing, market is in transition
Combine with other analysis (order flow, volume profile) for best results
Continuous Learning:
The RL system improves over time, but only if you:
Keep the indicator running (it learns from bar data)
Don't constantly change parameters (confuses the learning)
Let it accumulate at least 50 samples before judging performance
Review the dashboard weekly to see which bandits are adapting
CONCLUSION
Curvature Tensor Pivots - HIVE represents a fusion of advanced mathematics, machine learning, and practical trading experience. It is designed for serious traders who want institutional-grade tools and understand that edge comes from superior methodology, not magic formulas.
The system's strength lies in its adaptive intelligence —it doesn't just detect pivots, it learns which detection method works best right now, in this market, under these conditions. The hive consensus mechanism provides confidence, the geometric foundation provides precision, and the reinforcement learning provides evolution.
Use it wisely, manage risk properly, and let the mathematics work for you.
Disclaimer: This indicator is a tool for analysis and does not constitute financial advice. Past performance of shadow portfolios does not guarantee future results. Trading involves substantial risk of loss. Always perform your own due diligence and never trade with capital you cannot afford to lose.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
GrowEasy Money## Grow Easy AI Mentor Strategy
### Overview
The *Grow Easy AI Mentor Strategy* is a sophisticated yet beginner-friendly long-only trend-following indicator designed exclusively for the TradingView platform. It embodies the core principles of the Grow Easy AI agent: capital preservation, disciplined risk management, and educational growth. By combining multiple technically sound filters, it identifies high-probability entry and exit points while providing clear visual guidance, making it an ideal tool for new traders seeking sustainable and informed market engagement.
### Core Philosophy
This strategy is built on three foundational pillars:
- **Follow the Trend:** Trades only when price is above the 200-period Simple Moving Average (SMA), ensuring alignment with the long-term market direction.
- **Gauge Momentum:** Uses a dynamic Relative Strength Index (RSI) threshold to confirm strong buying pressure, adjusting sensitivity near recent highs to avoid premature entries.
- **Manage Risk Dynamically:** Employs a volatility-based trailing stop calculated via Average True Range (ATR) multiplied by a user-defined factor, adapting stops to market volatility and protecting profits effectively.
### Key Features & Functionality
- **Intelligent Entry Filters:** Combines long-term trend, momentum, and volatility breakout criteria for filtered and measured entries.
- **Optional Confirmation Filter:** Can wait for price to close above the trigger bar’s high before entry to reduce false signals and whipsaws.
- **Dynamic Trailing Stop:** Adjusts stop loss distance based on market volatility, widening in volatile conditions and tightening in calmer environments.
- **Educational Visuals:**
- Background shading indicates bullish (green) or bearish (red) trends.
- Entry (green triangle) and exit (red triangle) signals provide clear, actionable markers.
- Orange highlights indicate bars awaiting confirmation, promoting disciplined trading patience.
- Real-time label displays the current trend, momentum, volatility levels, and stop price for ongoing market education.
- **Fully Configurable:** All important parameters—ATR multiplier, RSI levels, lookback periods, confirmation toggles—are easily adjustable for various assets and volatility profiles.
- **Agent-Ready Alerts:** Built-in alert conditions allow seamless integration with Grow Easy AI autonomous trading agents or manual monitoring for timely trade execution.
### How to Use
Add the indicator to daily or higher timeframe charts for optimal results. Only consider long trades when buy signals appear, and use alerts for timely notifications. Pair the strategy with a sound risk management plan, such as limiting risk per trade to 1%, to ensure sustainable portfolio growth. Paper trading is recommended before live deployment to familiarize yourself with signal timing and behavior.
### Limitations
This strategy is exclusively long-only and may underperform in sideways or highly choppy markets where trend filters fail to detect clear direction. Adjust ATR multiplier and dynamic RSI thresholds as needed to match the volatility characteristics of individual assets. False signals can occur, especially during low-volume or highly volatile periods, underscoring the importance of risk controls and disciplined trade management.
### Ideal For
- New investors seeking an educational yet practical introduction to trading.
- Disciplined traders who prefer rules-based entries and exits over emotional decisions.
- Automated trading system developers looking for reliable, well-documented signal generation logic.
### In Essence
More than just a trading indicator, *Grow Easy AI Mentor Strategy* acts as a calm, patient mentor on the chart—enforcing disciplined strategy execution, visually explaining every step, and prioritizing risk management to support sustained learning and growth in trading.
ML Compressor Enhanced Trading Indicator# 🤖 ML Enhanced Trading Indicator - Advanced Market Analysis
## 📊 Overview
This is a comprehensive Machine Learning Enhanced Trading Indicator that combines multiple advanced analytical techniques to provide high-probability trading signals. The indicator uses artificial intelligence, pattern recognition, anomaly detection, and traditional technical analysis to identify optimal entry and exit points in the market.
## 🚀 Key Features
### 🧠 **Machine Learning Core**
- **Advanced Pattern Recognition**: Uses cosine similarity, Pearson correlation, and Spearman rank correlation to identify historical patterns
- **AI-Powered Predictions**: Implements multiple correlation methods to forecast price movements
- **Anomaly Detection**: Z-score based detection system for unusual market activities
- **Signal Confidence Scoring**: Reliability assessment for each trading signal
### 📈 **Technical Analysis Integration**
- **Multi-Timeframe RSI Analysis**: 14 and 21-period RSI with oversold/overbought detection
- **MACD Momentum**: Enhanced MACD histogram analysis for trend confirmation
- **Bollinger Bands Position**: Dynamic position tracking within BB channels
- **Volume Analysis**: Spike and dry volume detection with ratio calculations
- **Trend Strength Measurement**: EMA-based trend power analysis
### 🎯 **Perfect Zone Detection**
- **Ideal Buy Zone**: Identifies perfect buying opportunities when 7 conditions align:
- ML Score ≥ 0.60
- Bottom proximity detection
- RSI in 20-35 range
- Volume spike confirmation
- Positive price anomaly
- Bullish pattern match
- Positive MACD momentum
### 📊 **Comprehensive Display Table**
- **Real-time ML Analysis**: Complete breakdown of all indicators
- **Perfect Buy Conditions Tracker**: Visual checklist with completion percentage
- **Performance Metrics**: Win rate tracking and P&L analysis
- **Signal Strength Indicators**: Confidence levels for each signal
## 🔧 **Customizable Parameters**
### **ML Settings**
- **ML Lookback Period**: 20-500 bars (default: 100)
- **Anomaly Threshold**: 1.0-5.0 sensitivity (default: 2.0)
- **Pattern Similarity**: 0.5-0.99 matching threshold (default: 0.80)
- **AI Lookback Period**: 20-200 bars (default: 50)
### **AI Prediction Models**
- **Correlation Methods**: Spearman, Pearson, Cosine Similarity
- **Forecast Length**: 15-250 bars (default: 50)
- **Similarity Type**: Price or %Change analysis
### **Visual Options**
- **Table Position**: Top/Bottom Left/Right positioning
- **Table Size**: Small, Normal, Large options
- **Signal Display**: Toggle buy/sell signals on/off
- **AI Visualization**: Optional prediction paths and ZigZag
## 📋 **How to Use**
### **For Beginners**
1. Add the indicator to your chart
2. Look for "PERFECT BUY" signals in the table
3. Wait for completion percentage ≥ 85% for highest probability trades
4. Use the background color changes as visual confirmation
### **For Advanced Traders**
1. Analyze individual ML components in the detailed table
2. Monitor anomaly detection for unusual market conditions
3. Use pattern confidence levels for trade timing
4. Combine with your existing strategy for confirmation
### **Signal Interpretation**
- **🟢 PERFECT BUY**: All 7 conditions met - highest probability reversal
- **🟡 NEAR BOTTOM**: Close to ideal conditions - monitor closely
- **🔴 NOT READY**: Wait for better setup
- **Strong Buy/Sell Signals**: ML score-based entries with high confidence
## ⚠️ **Important Notes**
### **Risk Management**
- This indicator provides analysis and signals, not guaranteed outcomes
- Always use proper risk management and position sizing
- Consider market conditions and fundamental factors
- Backtest the strategy on your preferred timeframes and assets
### **Best Practices**
- Use multiple timeframe analysis for confirmation
- Combine with support/resistance levels
- Monitor volume confirmation for all signals
- Set appropriate stop-losses and profit targets
### **Performance Tracking**
- The indicator tracks its own performance with win rate calculations
- Monitor the "AI Prediction" accuracy percentage
- Use the P&L tracking to assess signal quality over time
## 🔄 **Updates and Improvements**
This indicator is continuously evolving with:
- Enhanced machine learning algorithms
- Improved pattern recognition capabilities
- Additional correlation methods for better accuracy
- Performance optimization for faster calculations
- New visualization features based on user feedback
## 📚 **Technical Details**
### **Machine Learning Implementation**
- **Pattern Matching**: 20-bar normalized price patterns with historical comparison
- **Correlation Analysis**: Mathematical similarity scoring between current and historical patterns
- **Anomaly Detection**: Statistical Z-score analysis across price, volume, and RSI
- **Signal Weighting**: Multi-factor scoring system with optimized weights
### **Algorithm Components**
1. **Feature Extraction**: Price, volume, momentum, volatility, and trend features
2. **Pattern Recognition**: Historical pattern database with similarity matching
3. **Anomaly Detection**: Multi-dimensional Z-score threshold analysis
4. **Signal Generation**: Weighted scoring system with confidence intervals
5. **Performance Tracking**: Real-time win rate and accuracy monitoring
### **Calculation Methods**
- **Trend Strength**: (EMA8 - EMA21) / EMA21 * 100
- **Volume Ratio**: Current Volume / 20-period SMA Volume
- **BB Position**: (Close - BB_Lower) / (BB_Upper - BB_Lower)
- **Anomaly Score**: Average of normalized Z-scores for price, volume, and RSI
## 🎨 **Visual Elements**
### **Background Colors**
- **Light Green**: Perfect buy zone detected
- **Light Red**: Perfect sell zone detected
- **Light Blue**: Near bottom proximity
- **Green/Red Transparency**: Price anomaly detection
### **Signal Shapes**
- **Green Triangle Up**: Strong buy signal
- **Red Triangle Down**: Strong sell signal
- **Aqua Diamond**: Perfect buy zone entry
- **Purple Diamond**: Perfect sell zone entry
### **Table Information**
- **ML Complete Analysis**: 16 comprehensive metrics
- **Perfect Buy Conditions**: 7-point checklist with status indicators
- **Real-time Values**: Live updating of all calculations
- **Color-coded Status**: Green (good), Yellow (moderate), Red (caution)
## 🔍 **Troubleshooting**
### **Common Issues**
- **Table Not Showing**: Enable "Show ML Table" in settings
- **No Signals Appearing**: Check "Show Buy/Sell Signals" option
- **Performance Issues**: Reduce ML Lookback Period for faster calculation
- **Too Many/Few Signals**: Adjust Anomaly Threshold sensitivity
### **Optimization Tips**
- **For Day Trading**: Use lower timeframes (1m, 5m, 15m) with reduced lookback periods
- **For Swing Trading**: Use higher timeframes (1h, 4h, 1D) with standard settings
- **For Scalping**: Enable only strong signals and reduce pattern similarity threshold
- **For Long-term**: Increase all lookback periods and use daily/weekly timeframes
## 📖 **Disclaimer**
This indicator is for educational and informational purposes only. It should not be considered as financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
### **Risk Warning**
- All trading involves risk of substantial losses
- Never risk more than you can afford to lose
- This indicator does not guarantee profitable trades
- Always use proper risk management techniques
- Consider consulting with a financial advisor
### **Liability**
The creator of this indicator is not responsible for any losses incurred from its use. Users should thoroughly test and understand the indicator before using it with real money.
### **Feature Requests**
- Suggest improvements through TradingView comments
- Report bugs with detailed descriptions
- Share successful strategies using the indicator
- Contribute to community discussions
## 🏆 **Credits and Acknowledgments**
This indicator builds upon various open-source libraries and mathematical concepts:
- TradingView ZigZag library for visualization
- Statistical correlation methods from academic research
- Machine learning concepts adapted for financial markets
- Community feedback and testing contributions
## 📈 **Performance Metrics**
The indicator includes built-in performance tracking:
- **Win Rate Calculation**: Percentage of profitable signals
- **Signal Accuracy**: ML prediction vs actual price movement
- **Drawdown Tracking**: Current unrealized P&L from last signal
- **Completion Percentage**: How many perfect conditions are met
## 🔬 **Mathematical Foundation**
### **Correlation Calculations**
- **Pearson**: Measures linear correlation between patterns
- **Spearman**: Rank-based correlation for non-linear relationships
- **Cosine Similarity**: Vector-based similarity for pattern matching
### **Statistical Methods**
- **Z-Score**: (Value - Mean) / Standard Deviation
- **Pattern Normalization**: Price / Price
- **Volatility Percentile**: Historical ranking of current volatility
- **Momentum Calculation**: Price change over multiple periods
## 🎯 **Trading Strategies**
### **Conservative Approach**
- Wait for Perfect Buy Zone (85%+ completion)
- Use higher timeframes for confirmation
- Set stop-loss at recent swing low
- Take profits at resistance levels
### **Aggressive Approach**
- Trade on Strong Buy/Sell signals
- Use lower completion thresholds (70%+)
- Tighter stop-losses with faster exits
- Higher position sizes with confirmed trends
### **Hybrid Strategy**
- Combine with other indicators for confirmation
- Use different settings for different market conditions
- Scale in/out based on signal strength
- Adjust parameters based on market volatility
AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend)The AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend) is a cutting-edge indicator that combines advanced mathematical modeling, AI-driven analytics, and segment-based pattern recognition to forecast price movements with precision. This tool is designed to provide traders with deep insights into market dynamics by leveraging multivariate pattern detection and sophisticated predictive algorithms.
👽 Core Features
Segment-Based Pattern Recognition
At its heart, the indicator divides price data into discrete segments, capturing key elements like candle bodies, high-low ranges, and wicks. These segments are normalized using ATR-based volatility adjustments to ensure robustness across varying market conditions.
AI-Powered k-Nearest Neighbors (kNN) Prediction
The predictive engine uses the kNN algorithm to identify the closest historical patterns in a multivariate dictionary. By calculating the distance between current and historical segments, the algorithm determines the most likely outcomes, weighting predictions based on either proximity (distance) or averages.
Dynamic Dictionary of Historical Patterns
The indicator maintains a rolling dictionary of historical patterns, storing multivariate data for:
Candle body ranges, High-low ranges, Wick highs and lows.
This dynamic approach ensures the model adapts continuously to evolving market conditions.
Volatility-Normalized Forecasting
Using ATR bands, the indicator normalizes patterns, reducing noise and enhancing the reliability of predictions in high-volatility environments.
AI-Driven Trend Detection
The indicator not only predicts price levels but also identifies market regimes by comparing current conditions to historically significant highs, lows, and midpoints. This allows for clear visualizations of trend shifts and momentum changes.
👽 Deep Dive into the Core Mathematics
👾 Segment-Based Multivariate Pattern Analysis
The indicator analyzes price data by dividing each bar into distinct segments, isolating key components such as:
Body Ranges: Differences between the open and close prices.
High-Low Ranges: Capturing the full volatility of a bar.
Wick Extremes: Quantifying deviations beyond the body, both above and below.
Each segment contributes uniquely to the predictive model, ensuring a rich, multidimensional understanding of price action. These segments are stored in a rolling dictionary of patterns, enabling the indicator to reference historical behavior dynamically.
👾 Volatility Normalization Using ATR
To ensure robustness across varying market conditions, the indicator normalizes patterns using Average True Range (ATR). This process scales each component to account for the prevailing market volatility, allowing the algorithm to compare patterns on a level playing field regardless of differing price scales or fluctuations.
👾 k-Nearest Neighbors (kNN) Algorithm
The AI core employs the kNN algorithm, a machine-learning technique that evaluates the similarity between the current pattern and a library of historical patterns.
Euclidean Distance Calculation:
The indicator computes the multivariate distance across four distinct dimensions: body range, high-low range, wick low, and wick high. This ensures a comprehensive and precise comparison between patterns.
Weighting Schemes: The contribution of each pattern to the forecast is either weighted by its proximity (distance) or averaged, based on user settings.
👾 Prediction Horizon and Refinement
The indicator forecasts future price movements (Y_hat) by predicting logarithmic changes in the price and projecting them forward using exponential scaling. This forecast is smoothed using a user-defined EMA filter to reduce noise and enhance actionable clarity.
👽 AI-Driven Pattern Recognition
Dynamic Dictionary of Patterns: The indicator maintains a rolling dictionary of N multivariate patterns, continuously updated to reflect the latest market data. This ensures it adapts seamlessly to changing market conditions.
Nearest Neighbor Matching: At each bar, the algorithm identifies the most similar historical pattern. The prediction is based on the aggregated outcomes of the closest neighbors, providing confidence levels and directional bias.
Multivariate Synthesis: By combining multiple dimensions of price action into a unified prediction, the indicator achieves a level of depth and accuracy unattainable by single-variable models.
Visual Outputs
Forecast Line (Y_hat_line):
A smoothed projection of the expected price trend, based on the weighted contribution of similar historical patterns.
Trend Regime Bands:
Dynamic high, low, and midlines highlight the current market regime, providing actionable insights into momentum and range.
Historical Pattern Matching:
The nearest historical pattern is displayed, allowing traders to visualize similarities
👽 Applications
Trend Identification:
Detect and follow emerging trends early using dynamic trend regime analysis.
Reversal Signals:
Anticipate market reversals with high-confidence predictions based on historically similar scenarios.
Range and Momentum Trading:
Leverage multivariate analysis to understand price ranges and momentum, making it suitable for both breakout and mean-reversion strategies.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
Elite Trading Network | HQ: Quantum Edge V2Elite Trading Network HQ: Quantum Edge V2 is a sophisticated market structure analysis tool designed to help traders make informed decisions based on a deep understanding of market conditions. This script blends structural trend analysis with AI-based predictive models to provide dynamic, real-time insights into market behavior. Here is what makes Quantum Edge V2 unique:
Key Features:
Adaptive Market Structure Analysis:
The script uses a multi-level algorithm to identify key market structures, such as swing highs and swing lows, to help traders understand the underlying strength or weakness of the current market trend. It dynamically tracks critical market boundaries using historical price action and recalculates trend levels as new data emerges.
Range and Trend Condition Detection:
Quantum Edge V2 detects whether the market is trending or ranging by analyzing historical structure breaks. This detection helps identify moments of consolidation (yellow zones) or periods of trend continuation. By calculating average structural break durations, the indicator alerts users to conditions that may require caution, such as ranging markets.
Predictive AI Analysis for Entry Optimization:
An AI-powered module evaluates volume thresholds and ATR (Average True Range) to provide users with an understanding of the current market risk. The ATR is calculated based on a user-defined timeframe, giving flexibility in how users approach different market conditions. This feature also determines the risk per trade and calculates the optimal position size, ensuring that users can tailor their risk according to their trading plan.
Real-Time Alerts and Visual Indicators:
The indicator includes alerts for key conditions:
Green Condition: Signals optimal market entry conditions.
Yellow Condition: Indicates a cautionary ranging market, alerting traders to the potential lack of strong trends.
Red Condition: Identifies unsuitable market conditions for entry due to insufficient volume or unfavorable metrics.
Color-coded background visuals provide instant clarity regarding market conditions—red, yellow, or green—allowing traders to make quick, informed decisions.
Dynamic Multi-Timeframe Analysis:
The user can select a custom entry timeframe, while the script internally calculates and adapts to a higher timeframe for deep trend analysis. This approach gives traders a complete view of both the short-term (entry) and higher timeframe (overall trend) dynamics.
How to Use:
Identify Trend Conditions: The indicator visually plots key market structures (green and red structural lines) to help users determine where the market may find support or resistance. The background changes color to indicate trending (green), ranging (yellow), or high-risk (red) conditions.
Make Informed Entries: Use the real-time alerts and label information to get insights into current market conditions. If the background is green and metrics align, the indicator suggests an optimal time for entry.
Position Sizing and Risk Management: The calculated risk per trade and position size (displayed on-screen) assist users in managing risk effectively. Users can utilize this data to adjust trade sizes and maximize profit potential while adhering to their risk tolerance.
What Sets Quantum Edge V2 Apart:
Unlike other indicators that solely provide trend direction, Quantum Edge V2 offers an integrated understanding of market structure, volume analysis, and predictive AI models.
The ranging market detection (yellow zones) is particularly valuable for traders looking to avoid low-probability trades during periods of market indecision.
The use of ATR-based risk calculation ensures the position sizing is always aligned with market volatility, adding an extra layer of protection for capital.
Important Notes:
Educational Value: This script does not just tell you when to enter or exit. It provides deep insights into market dynamics, giving traders a tool to learn and improve their market understanding. The ability to view market structure across different timeframes and visualize areas of caution is crucial for long-term growth as a trader.
No Guaranteed Results: This indicator is a powerful tool for analysis, but like all trading strategies, it does not guarantee profits. Always practice proper risk management.
Why It's Worth Using: This indicator combines multi-timeframe structure analysis, volume metrics, and predictive AI modeling—an approach typically reserved for professional trading systems. Traders looking to incorporate a systematic approach to risk, ranging markets, and trend detection will find Quantum Edge V2 invaluable.
Closed-source Explanation: The script uses proprietary algorithms and unique concepts for trend detection and volume-based analysis that ensure high levels of accuracy in defining market structure and determining entry signals. Because of its complexity and the unique blend of tools, it remains closed-source.
Feedback and Support:
If you have questions or suggestions about this script, feel free to comment or reach out. We value your input as we strive to improve and provide traders with cutting-edge tools.
TradingIQ - Impulse IQIntroducing "Impulse IQ" by TradingIQ
Impulse IQ is an exclusive trading algorithm developed by TradingIQ, designed to trade breakouts and established trends. By integrating artificial intelligence and IQ Technology, Impulse IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Impulse IQ
Impulse IQ combines IQ Technology (AI) with the classic principles of trend and breakout trading. Recognizing that markets inherently follow trends that need to persist for significant price movements to unfold, Impulse IQ eliminates the need for rigid settings or manual intervention.
Instead, it dynamically develops, adapts, and executes trend-based trading strategies, enabling a more responsive approach to capturing meaningful market opportunities.
Impulse IQ is designed to work straight out of the box. In fact, its simplicity requires just one user setting, making it incredibly straightforward to manage.
Strategy type is the only setting that controls Impulse IQ’s functionality.
Traders don’t have to spend hours adjusting settings and trying to find what works best - Impulse IQ handles this on its own.
Key Features of Impulse IQ
Self-Learning Breakout Detection
Employs IQ Technology to identify breakouts.
AI-Generated Trading Signals
Provides breakout trading signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
AI-Determined Trailing Profit Target and Stop Loss
Position exit levels are clearly defined and calculated by the AI once the trade is entered.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
IQ Meter
The IQ Meter details where price is trading relative to a higher timeframe trend and lower timeframe trend. Fibonacci levels are interlaced along the meter, offering unique insights on trend retracement opportunities.
Self Learning, Multi Timeframe IQ Zig Zags
The Zig Zag IQ is a self-learning, multi-timeframe indicator that adapts to market volatility, providing a clearer representation of market movements than traditional zig zag indicators.
Dual Strategy Execution
Impulse IQ integrates two distinct strategy types: Breakout and Cheap (details explained later).
How It Works
Before diving deeper into Impulse IQ, it's essential to understand the core terminology:
Zig Zag IQ : A self-learning trend and breakout identification mechanism that serves as the foundation for Impulse IQ. Although it belongs to the “Zig Zag” class of technical indicators, it's powered by IQ Technology.
Impulse IQ : A self-learning trading strategy that executes trades based on Zig Zag IQ. Zig Zag IQ identifies market trends, while Impulse IQ adapts, learns, and executes trades based on these trend characterizations.
Impulse IQ operates on a simple heuristic: go long during upside volatility and go short during downside volatility, essentially capturing price breakouts.
The definition of a “price breakout” is determined by IQ Technology, TradingIQ's exclusive AI algorithm. In Impulse IQ, the algorithm utilizes two IQ Zig Zags (self-learning, multi-timeframe zig zags) to analyze and learn from market trends.
It identifies breakout opportunities by recognizing violations of established price levels marked by the IQ Zig Zags. Impulse IQ then adapts and evolves to trade similar future violations in a recurring and dynamic manner.
Put simply, IQ Zig Zags continuously learn from both historical and real-time price updates to adjust themselves for an "optimal fit" to price data. The aim is to adapt so that the marked price tops and bottoms, when violated, reveal potential breakout opportunities.
The strategy layer of IQ Zig Zags, known as Impulse IQ, incorporates an additional level of self-learning with IQ Technology. It learns from breakout signals generated by the IQ Zig Zags, enabling it to dynamically identify and signal tradable breakouts. Moreover, Impulse IQ learns from historical price data to manage trade exits.
All positions start with an initial fixed stop loss and a trailing stop target. Once the trailing stop target is reached, the fixed stop loss converts into a trailing stop, allowing Impulse IQ to remain in the breakout/trend until the trailing stop is triggered.
What Classifies as a Breakout, Price Top, and Price Bottom?
For Impulse IQ:
Price tops are considered the highest price achieved before a price bottom forms.
Price bottoms are the lowest price reached before a price top forms.
For price tops, the highest price continues to be calculated until a significant downside price move occurs. Similarly, for price bottoms, the lowest price is calculated until a significant upside price move happens.
What distinguishes Zig Zag IQ from other zig zag indicators is its unique mechanism for determining a "significant counter-trend price move." Zig Zag IQ evaluates multiple fits to identify what best suits the current market conditions. Consequently, a "significant counter-trend price move" in one market might differ in magnitude from what’s considered "significant" in another, allowing it to adapt to varying market dynamics.
For example, a 1% price move in the opposite direction might be substantial in one market but not in another, and Zig Zag IQ figures this out internally.
The image above illustrates the IQ Zig Zags in action. The solid Zig Zag IQ lines represent the most recent price move being calculated, while the dotted, shaded lines display historical price moves previously analyzed by IQ Zig Zag.
Notice how the green zig zag aligns with a larger trend, while the purple zig zag follows a smaller trend. This mechanism is crucial for generating breakout signals in Impulse IQ: for a position to be entered, the breakout of the smaller trend must occur in the same direction as the larger trend.
The image above depicts the IQ Meters—an exclusive TradingIQ tool designed to help traders evaluate trend strength and retracement opportunities.
When the lower timeframe Zig Zag IQ and the higher timeframe Zig Zag IQ are out of sync (i.e., one is uptrending while the other is downtrending, with no active positions), the meters display a neutral color, as shown in the image.
The key to using these meters is to identify trend unison and pinpoint key trend retracement entry opportunities. Fibonacci retracement levels for the current trend are interlaced along each meter, and the current price is converted to a retracement ratio of the trend.
These meters can mathematically determine where price stands relative to the larger and smaller trends, aiding in identifying entry opportunities.
The top of each meter indicates the highest price achieved during the current price move.
The bottom of each meter indicates the lowest price achieved during the current price move.
When both the larger and smaller trends are in sync and uptrending, or when a long position is active, the IQ meters turn green, indicating uptrend strength.
When both trends are in sync and downtrending, or when a short position is active, the IQ meters turn red, indicating downtrend strength.
The image above shows the Point of Change for both the larger and smaller Zig Zag IQ trends. A distinctive feature of Zig Zag IQ is its ability to calculate these turning points in advance—unlike most traditional zig zag indicators that lack predetermined turning points and often lag behind price movements. In contrast, Zig Zag IQ offers a minimal-lag trend detection capability, providing a more responsive representation of market trends.
Simply put, once the market Zig Zag anchors are touched, the corresponding Zig Zag IQ will change direction.
Trade Signals
Impulse IQ can trade in one of two ways: Entering breakouts as soon as they happen (Breakout Strategy Type) or entering the pullback of a price breakout (Cheap Strategy Type).
Generally, the Breakout Strategy type will take a greater number of trades and enter a breakout quicker. The Cheap Strategy type will usually take less trades, but potentially enter at a better time/price point, prior to the next leg up of a break up, or the next leg down of a break down.
Entry signals are given when price breaks out to the upside or downside for the "Breakout" strategy type, or for the "Cheap" strategy type, when price retraces to the level it broke out from!
Breakout Strategy Example
The image above demonstrates a long position entered and exited using the Breakout strategy. The price breakout level is marked by the dotted, horizontal green line, representing a previously established price high identified by IQ Zig Zag. Once the price breaks and closes above this level, a long position is initiated.
After entering a long position, Impulse IQ immediately displays the initial fixed stop price. As the price moves favorably for the long position, the trailing stop conversion level is reached, and the indicator switches to a trailing stop, as shown in the image. Impulse IQ continues to "ride the trend" for as long as it persists, exiting only when the trailing stop is triggered.
Cheap Strategy Example
The image above shows a short entry executed using the Cheap strategy. The aim of the Cheap strategy is to enter on a pullback before the breakout occurs. While this results in fewer trades if price doesn’t pull back before the breakout, it typically allows for a better entry time and price point when a pullback does happen.
The image above illustrates the remainder of the trade until the trailing stop was hit.
Green Arrow = Long Entry
Red Arrow = Short Entry
Blue Arrow = Trade Exit
Impulse IQ calculates the initial stop price and trailing stop distance before any entry signals are triggered. This means users don’t need to constantly tweak these settings to improve performance—Impulse IQ handles this process internally.
Verifying Impulse IQ’s Effectiveness
Impulse IQ automatically tracks its performance and displays the profit factor for both its long and short strategies, visible in a table located in the top-right corner of your chart.
The image above shows the profit factor for both the long and short strategies used by Impulse IQ.
A profit factor greater than 1 indicates that the strategy was profitable when trading historical price data.
A profit factor less than 1 indicates that the strategy was unprofitable when trading historical price data.
A profit factor equal to 1 indicates that the strategy neither gained nor lost money on historical price data.
Using Impulse IQ
While Impulse IQ functions as a comprehensive trading system with its own entry and exit signals, it was designed for the manual trader to take its trading signals and analysis indications to greater heights - offering numerous applications beyond its built-in trading system.
The standout feature of Impulse IQ is its ability to characterize and capitalize on trends. Keeping a close eye on “Breakout” labels and making use of the IQ meter is the best way to use Impulse IQ.
The IQ Meters can be used to:
Find entry points during trend retracements
Assess trend alignment across higher and lower timeframes
Evaluate overall trend strength, indicating where the price lies on both IQ Meters.
Additionally, "Break Up" and "Break Down" labels can be identified for anticipating breakouts. Impulse IQ self-learns to capture breakouts optimally, making these labels dynamic signals for predicting a breakout.
The Zig Zag IQ indicators are instrumental in characterizing the market's current state. As a self-learning tool, Zig Zag IQ constantly adapts to improve the representation of current price action. The price tops and bottoms identified by Zig Zag IQ can be treated as support/resistance and breakout levels.
Of course, you can set alerts for all Impulse IQ entry and exit signals, effectively following along its systematic conquest of price movement.
Paid script
GG Short & Long IndicatorGG Short & Long Indicator is a powerful signal indicator with AI
How do indicator signals work?
The main purpose of the indicator is to give a signal that is most likely to bring profit based on historical data. This ORIGINAL trend algorithm gives SHORT and LONG signals when several conditions coincide: 1) Breakout of the average value of the modernized VWAP (this VWAP takes data only from certain time periods and trading sessions, as a result, its breakout most often coincides with the beginning of a strong trend); 2) The previous condition must be confirmed by volumes. I noticed that on some crypto exchanges, depending on whether the breakout is false or true, the volumes are different relative to each other. I applied this knowledge for additional filtering of signals (this point works only on crypto assets, on other assets the algorithm works without taking it into account, maybe later I will refine it); 3) When some of my original formulas to determine overbought (similar in principle to RSI, but more designed to work with the trader algorithm), should not show overbought - so that the entry into the transaction was not at too unfavorable values. To summarize, the algorithm tries to find a balance to determine a true breakout, during which the price will not go too far (for an acceptable RR).
But the most important thing is that the parameters to customize the algorithm are governed by our original AI algorithm. It can adjust the indicator in two modes: 1) Settings are selected based on the most profitable historical settings. 2) The settings are selected based not only on historical profitability, but also on winrate, frequency of trades, and a few other items that we will not disclose (so the code is closed) - we consider this approach as a priority, because according to our observations, it gives the highest performance compared to manual tuning. In addition, AI simply simplifies the work with the indicator - you do not need to adjust the settings manually for different trading pairs or timeframes, AI will do it all by itself and immediately give the ready result (backtest) on the table.
How to trade?
After the signal is issued, the indicator determines the recommended levels to close the trade (green dots). Stop loss should be placed behind the corresponding gray SL mark. Levels for closing a deal (TP) and the level of stop loss setting (SL) are also determined automatically for the selected pair and TF, based on volatility and selected indicator settings
To make a trade, you can also use the built-in “Support and Resistance Zones” tool, which displays ranges on the chart based on the modernized ATR, from which the price is more likely to rebound (here I also used my own approach, where in addition to the classic ATR formula, I also used volumes from certain crypto exchanges to determine more accurate price rebound zones)
These zones are also adjusted by AI - the algorithm compares several dozens of variations of these zones (with different settings) and chooses the one that best fits the current settings of the signal algorithm. For example, if the indicator is set up for frequent trades - the zones will be updated faster and will be less deep than if the indicator is set up for medium-term trading
If desired, you can customize the indicator manually using the corresponding section of the settings. Each paramater has a tooltip describing how and what it affects.
Statistisc panel
The panel can be divided into 2 conditional parts:
1) Statistics for each individual TP for the selected strategy. It shows the winrate and gross profit, if you fix a trade on a single target completely
2) Total trading result, if you trade clearly according to the strategy and fix the position by equal hours on 4 TPs. The total trading result is displayed for the current indicator settings, it also shows the best, worst and optimal of the possible indicator settings and the trading result of these settings on the side.
How do setup the indicator?
The indicator has preset settings for several major pairs and timeframes. These are fixed settings specifically selected for individual pairs and timeframes. You can use these presets, or you can choose one of the adaptive settings, which will AUTOMATICALLY select the best/optimal indicator settings.
I recommend choosing the “Adaptive Optimal” preset, as it uses more data to determine the optimal indicator settings and according to my observations this method works better in comparison to manual indicator settings or the “Adaptive Best” preset
Or you can use the manual settings, as mentioned earlier.
