Statistics
Simple Leveraged PnLThis script shows your live trade PnL, ROE, R:R ratio, margin, leverage, entry, TP, and SL directly on the chart.
It draws:
Green/red zones for your Take Profit and Stop Loss ranges.
A pinned info card (movable to any corner of the chart) showing all key trade details in one place.
You can fully customize:
Card position (top/middle/bottom × left/middle/right)
Text size, colors, and background
Zone transparency
It works for both Long and Short positions and updates in real time.
Combined Futures Open Interest [Sam SDF-Solutions]The Combined Futures Open Interest indicator is designed to provide comprehensive analysis of market positioning by aggregating open interest data from the two nearest futures contracts. This dual-contract approach captures the complete picture of market participation, including rollover dynamics between front and back month contracts, offering traders crucial insights into institutional positioning and market sentiment.
Key Features:
Dual-Contract Aggregation: Automatically identifies and combines open interest from the first and second nearest futures contracts (e.g., ES1! + ES2!), providing a complete view of market positioning that single-contract analysis might miss.
Multi-Period Analysis: Tracks open interest changes across multiple timeframes:
1 Day: Immediate market sentiment shifts
1 Week: Short-term positioning trends
1 Month: Medium-term institutional flows
3 Months: Quarterly positioning aligned with contract expiration cycles
Smart Data Handling: Utilizes last known values when data is temporarily unavailable, preventing false signals from data gaps while clearly indicating when stale data is being used.
EMA Smoothing: Incorporates a customizable Exponential Moving Average (default 65 periods) to identify the underlying trend in open interest, filtering out daily noise and highlighting significant deviations.
Dynamic Visualization:
Color-coded main line showing directional changes (green for increases, red for decreases)
Optional fill areas between OI and EMA to visualize momentum
Separate contract lines for detailed rollover analysis
Customizable labels for significant percentage changes
Comprehensive Information Table: Displays real-time statistics including:
Current total open interest across both contracts
Period-over-period changes in absolute and percentage terms
EMA deviation metrics
Visual status indicators for quick assessment
Contract symbols and data quality warnings
Alert System: Configurable alerts for:
Significant daily changes (customizable threshold)
EMA crossovers indicating trend changes
Large percentage movements suggesting institutional activity
How It Works:
Contract Detection: The indicator automatically identifies the base futures symbol and constructs the appropriate contract codes for the two nearest expirations, or accepts manual symbol input for non-standard contracts.
Data Aggregation: Open interest data from both contracts is retrieved and summed, providing a complete picture that accounts for positions rolling between contracts.
Historical Comparison: The indicator calculates changes from multiple lookback periods (1/5/22/66 days) to show how positioning has evolved across different time horizons.
Trend Analysis: The EMA overlay helps identify whether current open interest is above or below its smoothed average, indicating momentum in position building or reduction.
Visual Feedback: The main line changes color based on daily changes, while the optional table provides detailed numerical analysis for traders requiring precise data.
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This indicator is essential for futures traders, particularly those focused on index futures, commodities, or currency futures where understanding the aggregate positioning across nearby contracts is crucial. It's especially valuable during rollover periods when positions shift between contracts, and for identifying institutional accumulation or distribution patterns that single-contract analysis might miss. By combining multiple timeframe analysis with intelligent data handling and clear visualization, it simplifies the complex task of monitoring open interest dynamics across the futures curve.
POCTraderX Pro— Structure & Precision Algorithm POCTraderX Pro is a market analysis system designed to accurately identify key interest zones and price turning points. It combines advanced Price Action reading with a dynamic filtering process that adapts signals according to market volatility and internal structure.
Methodology
The algorithm analyzes the sequence of relevant highs and lows (HH, HL, LL, LH) along with the price location in relation to Point of Control levels and consolidation ranges.
It uses multi–timeframe confirmations to filter out false breakouts and optimize trade entries.
In high–volatility conditions, it automatically adjusts validation levels to maintain a favorable risk/reward ratio.
Configuration
Recommended timeframes: from 1–minute to daily, depending on the trading style.
Applicable markets: indices, forex, commodities, and cryptocurrencies.
Adjustable parameters:
Structure detection sensitivity.
Enable/disable volatility filters.
Show/hide control zones and previous ranges.
Purpose
Provide a clear reading of market structure and critical zones to help traders execute trades with greater consistency and avoid entries in low–probability areas.
Important Notes
This script is closed–source to protect its internal methodology, but it is based on an original combination of structural analysis and zone validation not available in free indicators.
It does not produce automatic buy or sell signals without context; it is intended to be integrated into a complete trading strategy.
Quant Signals: Market Sentiment Monitor HUDWavelets & Scale Spectrum
This indicator is ideal for traders who adapt their strategy to market conditions — such as swing traders, intraday traders, and system developers.
Trend-followers can use it to confirm trending conditions before entering.
Mean-reversion traders can spot choppy markets where reversals are more likely.
Risk managers can monitor volatility shifts and regime changes to adjust position size or pause trading.
It works best as a market context filter — telling you the “weather” before you decide on the trade.
Wavelets are like tiny “measuring rulers” for price changes. Instead of looking at the whole chart at once, a wavelet looks at differences in price over a specific time scale — for example, 2 bars, 4 bars, 8 bars, and so on.
The scale spectrum is what you get when you measure volatility at several of these scales and then plot them against scale size.
If the spectrum forms a straight line on a log–log chart, it means price changes follow a consistent pattern across time scales (a power-law relationship).
The slope of that line gives the Hurst exponent (H) — telling you whether moves tend to persist (trend) or reverse (mean-revert).
The height of the line gives you the volatility (σ) — the average size of moves.
This approach works like a microscope, revealing whether the market’s behaviour is consistent across short-term and long-term horizons, and when that behaviour changes.
This tool applies a wavelet-based scale-spectrum analysis to price data to estimate three key market state measures inside a rolling window:
Hurst exponent (H) — measures persistence in price moves:
H > ~0.55 → market is trending (moves tend to continue).
H < ~0.45 → market is choppy/mean-reverting (moves tend to reverse).
Values near 0.5 indicate a neutral, random-walk-like regime.
Volatility (σ) — the average size of price swings at your chart’s timeframe, optionally annualized. Rising volatility means larger price moves, falling volatility means smaller moves.
Fit residual — how well the observed multi-scale volatility fits a clean power-law line. Low residual = stable behaviour; high residual = structural change (possible regime shift).
Quant Signals: Entropy w/ ForecastThis is the first of many quantitative signals I plan to create for TV users.
Most technical analysis (TA) tools—like moving averages, oscillators, or chart patterns—are heuristic: they’re based on visually identifiable shapes, threshold crossovers, or empirically chosen rules. These methods rarely quantify the information content or structural complexity of market data. By quantifying market predictability before making a forecast, this method filters out noise and focuses your trading only during statistically favorable conditions—something traditional TA cannot objectively measure.
This MEPP-based approach is quantitative and model-free:
It comes from information theory and measures Shannon entropy rate to assess how predictable the market is at any moment.
Instead of interpreting price formations, it uses a data-compression algorithm (Lempel–Ziv) to capture hidden structure in the sequence of returns.
Forecasts are generated using a principle from statistical physics (Maximum Entropy Production), not historical chart patterns.
In short, this method measures the market's predictability BEFORE deciding a directional forecast is worth trusting. This tool is to inform TA traders on the market's current regime, whether it is smooth and predictable or it is volatile and turbulent.
Technical Introduction:
In information theory, Shannon entropy measures the uncertainty (or information content) in a sequence of data. For markets, the entropy rate captures how much new information price returns generate over time:
Low entropy rate → price changes are more structured and predictable.
High entropy rate → price changes are more random and unpredictable.
By discretizing recent returns into quartile-based states, this indicator:
Calculates the normalized entropy rate as a regime filter.
Uses MEPP to forecast the next state that maximizes entropy production.
Displays both the regime status (predictable vs chaotic) and the forecast bias (bullish/bearish) in a dashboard.
Measurements & How to Use Them
TLDR: HIGH ENTROPY -> information generation/market shift -> Don't trust forecast/strategy
1. H (bits/sym)
Shannon entropy rate of the last μ discrete returns, in bits per symbol (0–2).
Lower → more predictable; higher → more random.
Use as a raw measure of market structure.
2. H_max (log₂Ω)
Theoretical maximum entropy for Ω states. Here Ω = 4 → H_max = 2.0 bits.
Reference value for normalization.
3. Entropy (norm)
H / H_max, scaled between 0 and 1.
< 0.5–0.6 → predictable regime; > 0.6 → chaotic regime.
Main regime filter — forecasts are more reliable when below your threshold.
4. Regime
Label based on Entropy (norm) vs your entThresh.
LOW (predictable) = higher odds forecast will be correct.
HIGH (chaotic) = forecasts less reliable.
5. Next State (MEPP Forecast)
Discrete return state (1–4) predicted to occur next, chosen to maximize entropy production:
Large Down (strong bearish)
Small Down (mild bearish)
Small Up (mild bullish)
Large Up (strong bullish)
Use as your bias direction.
6. Bias
Simplified label from the Next State:
States 1–2 = Bearish bias (red)
States 3–4 = Bullish bias (green)
Align strategy direction with bias only in LOW regime.
Relative Volume + Z-score + Normal Volume + Avg. VolumeA statistical way to visualize volume analytically compared to traditional volume. All Lookback Periods and Colors can be changed so user can make it feel personalized
- Relative Volume (RVOL) visualizer with the color of the histogram bar changing to represent exceeding a threshold specified by the user
For example --> (1.5 = Orange Bar) & (2 = Red Bar)
- Toggle View between RVOL visualization of volume vs. normal view of volume plot
- Z score lookback for volume across specified lookback per what user wants (dot/symbol above the bar)
- Average Volume Plot
PRO Futures Risk to Reward CalculatorPlan. Place. Manage.
This Risk to Reward calculator is designed for traders who want instant, accurate risk:reward levels on the chart—without moving targets every bar.
🔹 Features
Manual Entry & Stop – Type exact prices or use the Auto Stop option (default: 10 points).
Static RR Lines – 0.5R, 1R, 1.5R, 2R, 2.5R, and 3R targets plotted instantly and locked in place.
Custom Colors – Style entry, stop, long/short targets, and panel for your chart theme.
Compact Risk Panel – Displays:
Trade Direction (Long/Short)
Entry & Stop prices
Risk in points & ticks
USD per R (auto-calculated from tick value & contract size)
Position size in contracts
Built-in Tick Database – Includes ES, NQ, MNQ, CL, GC, SI, Platinum, and more for exact dollar-per-tick calculations.
Minimal Right-Edge Labels – Quickly see each target level without chart clutter.
Multi-Market Ready – Works for futures, stocks, forex, and crypto with correct tick math.
🔹 Ideal For
Futures scalpers
Swing traders
Risk-focused position traders
Anyone wanting consistent, pre-defined trade targets
📌 Tip: Use with TradingView alerts or order tickets to execute partial profit targets in real time.
Futures Risk to Reward CalculatorFutures Risk to Reward Calculator with NQ, MNQ, ES, MES, etc price per tick built in.
SessionStat+ [JJumbo]Introduction
The SessionStat+ indicator is a sophisticated and dynamic tool crafted for TradingView, designed to empower traders with precise, data-driven insights into price movements across customizable trading sessions and timeframes. Tailored for day traders, swing traders, and market analysts, this script generates critical pivot points—such as highs, lows, and projections—by analyzing historical price ranges, enabling traders to anticipate key support, resistance, and breakout levels with confidence. Whether you’re targeting the volatility of the New York session, tracking the daily range during Regular Trading Hours, or analyzing custom sessions like the Asia market, SessionStat+ delivers actionable intelligence to align with your trading strategy. Its intuitive interface, robust customization options, and rich visualizations make it an essential tool for navigating diverse markets, from stocks and forex to cryptocurrencies.
Key features:
Algorithmic Calculations of Price:
Leverage algorithmic theory to measure price movements with precision. This tool calculates average session high and low price levels as well as maximum expansions, providing traders with actionable insights based on historical data.
Four custom Sessions Times and Five Time-Frame Fixed sessions:
Customize up to four Time ranges to focus on specific trading sessions. This allows traders to align their analysis with the operational hours and favourite session, such as 9am to 12pm, capturing the most relevant price movements. Traders can also create unique sessions based on their trading Time to study market behaviour when they usually operate in the markets – unlocking a level of understanding towards their personal backtested model and strategies.
The non custom session feature allows you to display time-frame fixed time ranges such as weekly, daily, 4 hour, 1 hour, 15 minutes.
Custom Calculation lookback and type of average:
The sample size of the sessions can be set to a number up to 1000 – the default is 60. This allows traders to adjust the depth of historical data based on the time frame used in their analysis, balancing detail and performance.
Max Expansion Projections:
The projections are based on the average high and low and function as max expansion out side of the statistical range, fully customizable, helping traders catch bigger moves in volatile markets.
Additional inputs:
User Guidance
Custom Appearance: Adjust the style of session lines with options like dotted, solid, and various colors. This helps traders visually distinguish between different types of market activities (e.g., Open, Manipulation, Distribution) on their charts.
Lookback Periods: Option to show available lookback periods for a deeper historical analysis, providing context and historical benchmarks for current market conditions.
Extended Visualization: Pre-extend lines until session close or extend until day end for better visualization of market phases. This helps traders see the continuation of trends and market behaviours beyond the immediate session.
Terms & Conditions
Our charting tools are products provided for informational and educational purposes only and do not constitute financial, investment, or trading advice. Our charting tools are not designed to predict market movements or provide specific recommendations. Users should be aware that past performance is not indicative of future results and should not be relied upon for making financial decisions. By using our charting tools, the purchaser agrees that the seller and the creator are not responsible for any decisions made based on the information provided by these charting tools. The purchaser assumes full responsibility and liability for any actions taken and the consequences thereof, including any loss of money or investments that may occur as a result of using these products. Hence, by purchasing these charting tools, the customer accepts and acknowledges that the seller and the creator are not liable nor responsible for any unwanted outcome that arises from the development, the sale, or the use of these products. We hold no reimbursement, refund, or chargeback policy. Once these Terms and Conditions are accepted by the Customer, before purchase, no reimbursements, refunds or chargebacks will be provided under any circumstances.
By continuing to use these charting tools, the user acknowledges and agrees to the Terms and Conditions outlined in this legal disclaimer.
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
ADR/ATR Session by LK## **Features**
1. **Custom ADR & ATR Calculation**
* Calculates **Average Daily Range (ADR)** and **Average True Range (ATR)** separately for:
* **Session timeframe** (default H4 / 06:00–13:00)
* **Daily timeframe**
* Independent smoothing method selection (**SMA, EMA, RMA, WMA**) for H4 ADR, H4 ATR, Daily ADR, and Daily ATR.
2. **Percentage Metrics**
* % of ADR / ATR covered by the **current H4 bar**.
* ADR / ATR expressed as a percentage of the **current price**.
* % of ADR already reached for the **current day**.
* % of Daily ATR vs current day’s True Range.
3. **Dynamic Chart Lines**
* Draws **3 lines for H4**: Session Open, ADR High, ADR Low.
* Draws **3 lines for Daily**: Daily Open, ADR High, ADR Low.
* Lines **extend to the right** so they stay visible across the chart.
* Colors and widths are fully customizable.
4. **Real-Time Data Table**
* Compact table displaying all ADR/ATR values and percentages.
* Adjustable table font size (**tiny, small, normal, large, huge**).
* Transparent background option for minimal chart obstruction.
5. **Flexible Session Settings**
* Select session start and end time in hours/minutes.
* Choose session timezone (chart timezone or major financial centers).
* Toggle H4 lines, Daily lines separately.
6. **Lookahead Control**
* Option to wait for higher-timeframe candle close before updating values (more accurate, less repainting).
---
## **How to Use**
### **1. Adding the Indicator**
* Copy and paste the Pine Script into TradingView’s Pine Editor.
* Click **“Add to chart”**.
* Make sure your chart supports the higher timeframes you choose (e.g., H4 and Daily).
### **2. Setting Your Session**
* **Session Start Hour** & **End Hour** → Defines the intraday session to measure ADR/ATR (default: 06:00–13:00).
* **Session Timezone** → Pick “Chart” or a major financial center (e.g., New York, London, Tokyo).
### **3. Choosing Smoothing Methods**
* For each ADR/ATR (H4 and Daily), choose:
* SMA (Simple)
* EMA (Exponential)
* RMA (Wilder’s smoothing)
* WMA (Weighted)
### **4. Adjusting Chart Display**
* **Show H4 Lines** → Displays session open and ADR High/Low for the current H4 session.
* **Show Daily Lines** → Displays daily open and ADR High/Low.
* Customize line colors and widths.
### **5. Reading the Table**
* **H4 Section**
* ADR / ATR values for the selected session.
* % of ADR/ATR covered by the **current H4 bar**.
* ADR/ATR as % of the current price.
* **Daily Section**
* ADR / ATR for the daily timeframe.
* % of ADR already covered by today’s range.
* ADR/ATR as % of price.
### **6. Pro Tips**
* Use **H4 ADR %** to gauge intraday exhaustion — if current range is near 100%, market may slow or reverse.
* Use **Daily ADR %** for swing trade context — if a day has moved beyond its ADR, expect lower continuation probability.
* Combine with support/resistance to identify high-probability reversal zones.
Financial Change % Table - ToluFinancial Change % Table which includes revenue , operating profit and earning per share . compares the financial data with previous quarter QoQ and previous year YoY . and shows the change in %.
Cycle Phase & ETA Tracker [Robust v4]
Cycle Phase & ETA Tracker
Description
The Cycle Phase & ETA Tracker is a powerful tool for analyzing market cycles and predicting the completion of the current cycle (Estimated Time of Arrival, or ETA). It visualizes the cycle phase (0–100%) using a smoothed signal and displays the forecasted completion date with an optional confidence band based on cycle length variability. Ideal for traders looking to time their trades based on cyclical patterns, this indicator offers flexible settings for robust cycle analysis.
Key Features
Cycle Phase Visualization: Tracks the current cycle phase (0–100%) with color-coded zones: green (0–33%), blue (33–66%), orange (66–100%).
ETA Forecast: Shows a vertical line and label indicating the estimated date of cycle completion.
Confidence Band (±σ): Displays a band around the ETA to reflect uncertainty, calculated using the standard deviation of cycle lengths.
Multiple Averaging Methods: Choose from three methods to calculate average cycle length:
Median (Robust): Uses the median for resilience against outliers.
Weighted Mean: Prioritizes recent cycles with linear or quadratic weights.
Simple Mean: Applies equal weights to all cycles.
Adaptive Cycle Length: Automatically adjusts cycle length based on the timeframe or allows a fixed length.
Debug Histogram: Optionally displays the smoothed signal for diagnostic purposes.
Setup and Usage
Add the Indicator:
Search for "Cycle Phase & ETA Tracker " in TradingView’s indicator library and apply it to your chart.
Configure Parameters:
Core Settings:
Track Last N Cycles: Sets the number of recent cycles used to calculate the average cycle length (default: 20). Higher values provide stability but may lag market shifts.
Source: Selects the data source for analysis (e.g., close, open, high; default: close price).
Use Adaptive Cycle Length?: Enables automatic cycle length adjustment based on timeframe (e.g., shorter for intraday, longer for daily) or uses a fixed length if disabled.
Fixed Cycle Length: Defines the cycle length in bars when adaptive mode is off (default: 14). Smaller values increase sensitivity to short-term cycles.
Show Debug Histogram: Enables a histogram of the smoothed signal for debugging signal behavior.
Cycle Length Estimation:
Average Mode: Selects the method for calculating average cycle length: "Median (Robust)", "Weighted Mean", or "Simple Mean".
Weights (for Weighted Mean): For "Weighted Mean", chooses "linear" (moderate emphasis on recent cycles) or "quadratic" (strong emphasis on recent cycles).
ETA Visualization:
Show ETA Line & Label: Toggles the display of the ETA line and date label.
Show ETA Confidence Band (±σ): Toggles the confidence band around the ETA, showing the uncertainty range.
Band Transparency: Adjusts the transparency of the confidence band (0 = fully transparent, 100 = fully opaque; default: 85).
ETA Color: Sets the color for the ETA line, label, and confidence band (default: orange).
Interpretation:
The cycle phase (0–100%) indicates progress: green for the start, blue for the middle, and orange for the end of the cycle.
The ETA line and label show the predicted cycle completion date.
The confidence band reflects the uncertainty range (±1 standard deviation) of the ETA.
If a warning "Insufficient cycles for ETA" appears, wait for the indicator to collect at least 3 cycles.
Limitations
Requires at least 3 cycles for reliable ETA and confidence band calculations.
On low timeframes or low-volatility markets, zero-crossings may be infrequent, delaying ETA updates.
Accuracy depends on proper cycle length settings (adaptive or fixed).
Notes
Test the indicator across different assets and timeframes to optimize settings.
Use the debug histogram to troubleshoot if the ETA appears inaccurate.
For feedback or suggestions, contact the author via TradingView.
Cycle Phase & ETA Tracker
Описание
Индикатор Cycle Phase & ETA Tracker предназначен для анализа рыночных циклов и прогнозирования времени завершения текущего цикла (ETA — Estimated Time of Arrival). Он отслеживает фазы цикла (0–100%) на основе сглаженного сигнала и отображает предполагаемую дату завершения цикла с опциональной доверительной полосой, основанной на стандартном отклонении длин циклов. Индикатор идеально подходит для трейдеров, которые хотят выявлять циклические закономерности и планировать свои действия на основе прогнозируемого времени.
Ключевые особенности
Фазы цикла: Визуализирует текущую фазу цикла (0–100%) с цветовой кодировкой: зеленый (0–33%), синий (33–66%), оранжевый (66–100%).
Прогноз ETA: Показывает вертикальную линию и метку с предполагаемой датой завершения цикла.
Доверительная полоса (±σ): Отображает зону неопределенности вокруг ETA, основанную на стандартном отклонении длин циклов.
Гибкие методы усреднения: Поддерживает три метода расчета средней длины цикла:
Median (Robust): Медиана, устойчивая к выбросам.
Weighted Mean: Взвешенное среднее, где недавние циклы имеют больший вес (линейный или квадратичный).
Simple Mean: Простое среднее с равными весами.
Адаптивная длина цикла: Автоматически подстраивает длину цикла под таймфрейм или позволяет задать фиксированную длину.
Отладочная гистограмма: Опционально отображает сглаженный сигнал для анализа.
Настройка и использование
Добавьте индикатор:
Найдите "Cycle Phase & ETA Tracker " в библиотеке индикаторов TradingView и добавьте его на график.
Настройте параметры:
Core Settings:
Track Last N Cycles: Количество последних циклов для расчета средней длины (по умолчанию 20). Большие значения дают более стабильные результаты, но могут запаздывать.
Source: Источник данных (по умолчанию цена закрытия).
Use Adaptive Cycle Length?: Включите для автоматической настройки длины цикла по таймфрейму или отключите для использования фиксированной длины.
Fixed Cycle Length: Длина цикла в барах, если адаптивная длина отключена (по умолчанию 14).
Show Debug Histogram: Включите для отображения сглаженного сигнала (полезно для отладки).
Cycle Length Estimation:
Average Mode: Выберите метод усреднения: "Median (Robust)", "Weighted Mean" или "Simple Mean".
Weights (for Weighted Mean): Для режима "Weighted Mean" выберите "linear" (умеренный вес для новых циклов) или "quadratic" (сильный вес для новых циклов).
ETA Visualization:
Show ETA Line & Label: Включите для отображения линии и метки ETA.
Show ETA Confidence Band (±σ): Включите для отображения доверительной полосы.
Band Transparency: Прозрачность полосы (0 — полностью прозрачная, 100 — полностью непрозрачная, по умолчанию 85).
ETA Color: Цвет для линии, метки и полосы (по умолчанию оранжевый).
Интерпретация:
Фаза цикла (0–100%) показывает прогресс текущего цикла: зеленый — начало, синий — середина, оранжевый — конец.
Линия и метка ETA указывают предполагаемую дату завершения цикла.
Доверительная полоса показывает диапазон неопределенности (±1 стандартное отклонение).
Если отображается предупреждение "Insufficient cycles for ETA", дождитесь, пока индикатор соберет минимум 3 цикла.
Ограничения
Требуется минимум 3 цикла для надежного расчета ETA и доверительной полосы.
На низких таймфреймах или рынках с низкой волатильностью пересечения нуля могут быть редкими, что замедляет обновление ETA.
Эффективность зависит от правильной настройки длины цикла (fixedL или адаптивной).
Примечания
Протестируйте индикатор на разных таймфреймах и активах, чтобы подобрать оптимальные параметры.
Используйте отладочную гистограмму для анализа сигнала, если ETA кажется неточным.
Для вопросов или предложений по улучшению свяжитесь через TradingView.
Entropy (Fiedor/Kontoyiannis) - Part 2 of Fiedor's TheoryThis indicator estimates the Shannon entropy of a price series using a Markov chain model of binary returns, following the approach of Fiedor (2014) and Kontoyiannis (1997).
% of Max shows current entropy as a percentage of its theoretical maximum (1 bit for binary up/down moves).
Percentile ranks the current entropy against historical values in the chosen lookback window.
High entropy suggests price movement is less predictable by frequentist models; low entropy implies more structure and predictability.
Use this as an informational oscillator, not a trading signal.
This is a visualization of Part 1 of Fiedor's Theory. The same entropy logic is already embedded in Part 1 however the second pane is a nice reminder of why it works.
Binance Funding Rates [vichtoreb]Source: www.binance.com
The funding rate has two components: the interest rate and the average Premium Index.
Binance furnishes the Premium Index data for crypto assets on the TradingView platform. This script uses that data to calculate the funding rate.
Binance updates the Premium Index every 5 seconds.
The average Premium Index (denoted **P\_avg**) is the time-weighted average of all Premium Index data points:
P_avg = wma(Premium Index, n)
where **n** is the averaging length.
At each change time—8:00 PM, 4:00 AM, and 12:00 PM (UTC-4)—Binance sets
P_avg = wma(Premium Index, 5 760)
This is the weighted moving average of the last 8 hours because 5 760 × 5 s = 8 h. Binance then calculates the new funding rate:
Funding Rate = P_avg + clamp(interest rate − P_avg, −0.05 %, 0.05 %)
This value updates only at those change times (8:00 PM, 4:00 AM, and 12:00 PM, UTC-4).
**Indicator precision**
TradingView limits historical requests to 5 000 candles. To match Binance exactly, 5 760 candles are required. As a workaround, the script samples the Premium Index every *resolution* seconds (or minutes), where *resolution* is the indicator’s timeframe input.
If it weren't for this limitation, setting resolution = 5 sec, we would get EXACTLY the same result as the official one
**Interest rate**
On Binance Futures, the interest rate is 0.03 % per day by default (0.01 % per funding interval, as funding occurs every 8 hours). This does not apply to certain contracts, such as ETH/BTC, for which the interest rate is 0 %.
**Estimate line**
If the “show estimate” input is enabled, the indicator plots
wma(Premium Index, n) + clamp(interest rate − P_avg, −0.05 %, 0.05 %)
with **n** equal to the number of bars that have elapsed since the last funding-rate change.
Latent Regime Informed Monte Carlo ForecastThis script uses a Monte Carlo simulation to forecast where price might be a set number of bars into the future (default 6 bars ahead). It generates hundreds of possible future price paths based on an average move (drift) and random shocks (volatility). The result is a distribution of outcomes, displayed as probability zones: the median (most likely), inner bands (50% confidence), and wider bands (80% and 95% confidence). Due to the randomness assumption in Monte Carlo simulations, the paths are not very important so to minimize cluttering on the graphs we only plot bands. These zones help you visualize uncertainty, set stops and targets based on probabilities, and spot when market behavior changes.
The accuracy of any Monte Carlo forecast depends heavily on how well you estimate trend and volatility. By default and no prior information the Monte Carlo simulation gives you a parabolic forecast that assumes absolute randomness. This is where the Kalman filter comes in. The filter (derived from control theory) aims to detect latent (unobservable) traits about the system by continuously updating its transition probabilities to better understand how the latent traits affect the observable measurement (price). With each new observable state we get better and better transition probabilities and enhances our understanding about the latent and unobservable market characteristics like trend and volatility. Both crucial measurements for short term market sentiment.
Extracting these measurements for market sentiment informs us how to better parametrize the Monte Carlo simulation for a better forecast. Each bar, the KF updates its estimates based on how close its last prediction was to reality. In calm periods, it holds estimates steady; in volatile periods, it adapts quickly. This gives you real-time, low-lag measurements of both trend and volatility.
By feeding these adaptive estimates into the Monte Carlo simulation, the forecast becomes much more responsive to current market conditions. In trends, the predicted paths tilt toward the direction of movement; in choppy markets, they spread wider but stay centered; when volatility spikes, the probability zones expand immediately. The result is a dynamic forecast tool that adjusts on every bar, giving you a clearer, probability-based picture of where the market could go next.
This is my very first script and I would love feedback/ideas for different topics.
My background is in economics/mathematics and interests lie in time series analysis/exploring financial features for DS
Adaptive Correlation Engine (ACE)🧠 Adaptive Correlation Engine (ACE)
Quantify inter-asset relationships with adaptive lag detection and actionable insights.
📌 What is ACE?
The Adaptive Correlation Engine (ACE) is a precision tool for seeking to uncover meaningful relationships between two assets — not just raw correlation, but also lag dynamics, leader detection, and alignment vs. divergence classification.
Unlike static correlation tools, ACE intelligently scans multiple lag windows to find:
✅ The maximum correlation between the base asset and a comparison symbol
⏱️ The optimal lag (if any) at which the correlation is strongest
🧭 Whether the assets are Aligned (positive correlation) or Divergent (inverse)
🔁 Which symbol is leading, and by how many bars
📈 Actionable signal strength based on a user-defined correlation threshold
⚙️ How It Works
Correlation Scan:
For each bar, ACE checks the correlation between the charted asset (close) and a lagged version of the comparison asset across a sliding window of lookback periods.
Lag Optimization:
The engine searches from lag 0 up to your specified Max Lag to find where the correlation (positive or negative) is most significant.
Relationship Classification:
The indicator classifies the relationship as:
Aligned: Positive correlation above the threshold
Divergent: Negative correlation above the threshold
Synchronous: No lag detected
Low Signal: Correlation is weak or noisy
Visual & Tabular Insights:
ACE plots the highest detected correlation on the chart and shows an insight table displaying:
- Correlation value
- Detected lag
- Direction type (aligned/divergent)
- Leading asset
- Suggested action (e.g., “Likely continuation” or “Possible mean reversion”)
💡 How to Use It
Use ACE to identify leadership patterns between assets (e.g., ETH leads altcoins, SPX leads crypto, etc.)
Spot potential lagging trade setups where one asset’s move may soon echo in another
Confirm or challenge correlation-based trading assumptions with data
Combine with technical indicators or price action to time entries and exits more confidently
🔔 Alerts
Built-in alerts notify you when correlation strength crosses your actionable threshold, classified by alignment or divergence.
🛠️ Inputs
Compare Symbol: The asset to compare against (e.g., INDEX:ETHUSD)
Correlation Lookback: Rolling window for calculating correlation
Max Lag Bars: Maximum lag shift to test
Minimum Actionable Correlation: Signal threshold for trade-worthy insights
⚠️ Disclaimer
This tool is for research and informational purposes only. It does not constitute financial advice or a trading signal. Always perform your own due diligence and consult a financial advisor before making investment decisions.
Sigma Expected Movement [D/W/M] - Jez WhitakerThis indicator aims to help those with lower levels of TradingView add day trading indicators without going over their limits. You can toggle on and off the indicators you want and change the settings but you should see:
MAs - 5, 20, 50, 100, 200
VWAPS - daily, WTD, MTD, YTD
Previous close, previous highs, previous lows etc.
OMU_CJ CombinedThis script is a custom technical analysis tool designed for TradingView, built on Pine Script v6.
It combines multiple indicators and logic to provide clear buy and sell signals, optimized for intraday and swing trading.
The strategy includes dynamic trend detection, volatility filters, and adjustable parameters for better adaptability to different market conditions.
Traders can use it to identify potential entry and exit points with improved accuracy.
Key Features:
Multi-indicator signal confirmation
Adjustable settings for different timeframes
Visual buy/sell markers on the chart
Works on all major asset classes (stocks, crypto, forex, indices)
Optimized for both short-term and long-term trading strategies
Disclaimer:
This script is for educational purposes only and should not be considered as financial advice. Always do your own research before trading.
Information Theory Market AnalysisINFORMATION THEORY MARKET ANALYSIS
OVERVIEW
This indicator applies mathematical concepts from information theory to analyze market behavior, measuring the randomness and predictability of price and volume movements through entropy calculations. Unlike traditional technical indicators, it provides insight into market structure and regime changes.
KEY COMPONENTS
Four Main Signals:
• Price Entropy (Deep Blue): Measures randomness in price movements
• Volume Entropy (Bright Blue): Analyzes volume pattern predictability
• Entropy MACD (Purple): Shows relationship between price and volume entropy
• SEMM (Royal Blue): Stochastic Entropy Market Monitor - overall market randomness gauge
Market State Detection:
The indicator identifies seven distinct market states:
• Strong Trending (SEMM < 0.1)
• Weak Trending (0.1-0.2)
• Neutral (0.2-0.3)
• Moderate Random (0.3-0.5)
• High Randomness (0.5-0.8)
• Very Random (0.8-1.0)
• Chaotic (>1.0)
KEY FEATURES
Advanced Analytics:
• Signal Strength Confluence: 0-5 scale measuring alignment of multiple factors
• Entropy Crossovers: Detects shifts between accumulation and distribution phases
• Extreme Readings: Identifies statistical outliers for potential reversals
• Trend Bias Analysis: Directional momentum assessment
Information Dashboard:
• Real-time entropy values and market state
• Signal strength indicator with visual highlighting
• Trend bias with directional arrows
• Color-coded alerts for extreme conditions
Customizable Display:
• Adjustable SEMM scaling (5x to 100x) for optimal visibility
• Multiple line styles: Smooth, Stepped, Dotted
• 9 table positions with 3 size options
• Professional blue color scheme with transparency controls
Comprehensive Alert System - 15 Alert Types Including:
• Extreme entropy readings (price/volume)
• Crossover signals (dominance shifts)
• Market state changes (trending ↔ random)
• High confluence signals (3+ factors aligned)
HOW TO USE
Reading the Signals:
• Entropy Values > ±25: Strong structural signals
• Entropy Values > ±40: Extreme readings, potential reversals
• SEMM < 0.2: Trending market favors directional strategies
• SEMM > 0.5: Random market favors range/scalping strategies
Signal Confluence:
Look for multiple factors aligning:
• Signal Strength ≥ 3.0 for higher probability setups
• Background highlighting indicates confluence
• Table shows real-time strength assessment
Timeframe Optimization:
• Short-term (1m-15m): Entropy Length 14-22, Sensitivity 3-5
• Swing Trading (1H-4H): Default settings optimal
• Position Trading (Daily+): Entropy Length 34-55, Sensitivity 8-12
EDUCATIONAL APPLICATIONS
Market Structure Analysis:
• Understand when markets are trending vs. ranging
• Identify accumulation and distribution phases
• Recognize extreme market conditions
• Measure information content in price movements
Information Theory Concepts:
• Binary entropy calculations applied to financial data
• Probability distribution analysis of returns
• Statistical ranking and percentile analysis
• Momentum-adjusted randomness measurement
TECHNICAL DETAILS
Calculations:
• Uses binary entropy formula: -
• Percentile ranking across multiple timeframes
• Volume-weighted probability distributions
• RSI-adjusted momentum entropy (SEMM)
Customization Options:
• Entropy Length: 5-100 bars (default: 22)
• Average Length: 10-200 bars (default: 88)
• Sensitivity: 1.0-20.0 (default: 5.0, lower = more sensitive)
• SEMM Scaling: 5.0-100.0x (default: 30.0)
IMPORTANT NOTES
Risk Considerations:
• Indicator measures probabilities, not certainties
• High SEMM values (>0.5) suggest increased market randomness
• Extreme readings may persist longer than expected
• Always combine with proper risk management
Educational Purpose:
This indicator is designed for:
• Market structure analysis and education
• Understanding information theory applications in finance
• Developing probabilistic thinking about markets
• Research and analytical purposes
Performance Tips:
• Allow 200+ bars for proper initialization
• Adjust scaling and transparency for optimal visibility
• Use confluence signals for higher probability analysis
• Consider multiple timeframes for comprehensive analysis
DISCLAIMER
This indicator is for educational and analytical purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own research and consider your risk tolerance before making trading decisions.
Version: 5.0
Category: Oscillators, Volume, Market Structure
Best For: All timeframes, trending and ranging markets
Complexity: Intermediate to Advanced
Position Size 📐 DT/ST (Today's Open)💡 Purpose:
This indicator automatically calculates intraday (DT) and swing trading (ST) position sizes based on your account capital, risk per trade, and stop-loss percentage, using today’s daily open price as the entry price reference.
⚙️ Main Functionalities:
Dynamic Position Sizing
Calculates Full size position based on the maximum risk you allow per trade.
Breaks it down into ¼ Size, ⅓ Size, and ½ Size positions for flexible scaling.
Two Distinct Trading Styles:
DT (Day Trading) – Uses your specified intraday stop-loss % (default: 2%).
ST (Swing Trading) – Uses your specified swing stop-loss % (default: 10%).
Lot Size Rounding
Automatically rounds quantities to a chosen lot size (e.g., 1 for cash equity or futures lot size for derivatives).
Customizable Table Position
Display the table anywhere on your chart: Top Right, Top Left, Bottom Right, or Bottom Left.
Optimized for Dark or Light Themes
Yellow header with black text for visibility.
Blue row labels for strategy type.
Grey background with white text for calculated values.
Live Market Adaptation
All values update in real-time as today’s daily open price changes (on new daily candles).
Works for any symbol, asset class, or time frame.
🧮 Formula:
Position Size (Full) = Max Risk ₹ / (Price × StopLoss%)
¼, ⅓, and ½ Sizes = Scaled from Full size
📌 Ideal For:
Traders who want quick, ready-to-use position sizes right on their chart.
Those who follow fixed risk-per-trade and need fast decision-making without manual calculations.
Leader-Lagger DashboardSummary:
The ultimate frustration for a trader: being right on the idea, but wrong on the asset.
You correctly predict a market move, develop a solid bullish or bearish thesis, but the instrument you choose fails to follow through. Meanwhile, a correlated asset makes the exact move you anticipated, leaving you with a losing trade or a missed opportunity.
This common pitfall is precisely what the Leader/Lagger Dashboard is designed to solve.
The Solution: Instant Clarity on Relative Strength
The Leader/Lagger Dashboard provides a clear, real-time verdict on the relative strength between two correlated assets, such as ES (S&P 500 futures) and NQ (Nasdaq 100 futures).
By instantly identifying the Leader (the stronger asset) and the Lagger (the weaker asset), it empowers you to focus your capital on the instrument with the highest probability of performing in line with your market view.
As shown in the example image, if your idea is to short the market, choosing the "Weak" asset (ES) results in a winning trade, while shorting the "Strong" asset (NQ) would have failed. This tool helps you make that critical distinction before you enter.
How It Works
The engine at the core of this dashboard analyzes the price action of two assets on a higher timeframe (defaulting to 90 minutes). It measures how the current bar's high and low are performing relative to the previous bar's range for each asset. By comparing these normalized values, it generates a score to determine which asset is exhibiting stronger momentum (the Leader) and which is showing weakness (the Lagger).
A tie-breaking mechanism using a lower timeframe ensures you always have a decisive verdict.
How to Use It
The principle is simple: Go long the leader, and short the lagger.
If you are Bullish: Look for the asset marked "Strong." This is the instrument most likely to lead the upward move.
If you are Bearish: Look for the asset marked "Weak." This is the instrument most likely to lead the downward move.
By aligning your trade execution with the market's internal momentum, you dramatically increase your odds of success and avoid the frustration of trading against underlying strength or weakness.
Key Features
Instant Verdict: A simple on-chart table displays a "Strong" or "Weak" verdict for each asset.
Focus on the Leader: Easily identify which asset is leading the move to align your trades with momentum.
Avoid the Lagger: Steer clear of the weaker asset that might chop around or reverse, even if your directional bias is correct.
Fully Customizable: Change the two assets to any symbols you trade (e.g., GOLD vs. SILVER, EURUSD vs. GBPUSD).
Adjustable Display: Control the table's position and font size to perfectly fit your chart layout. The table is designed to be visible on lower timeframes (5-minutes and under) to assist with day trading execution.
This tool is designed to be a crucial part of your decision-making process, providing an objective layer of confirmation for your trading ideas. so Stop guessing and start trading the right asset.
As always, use this indicator in conjunction with your own complete analysis and risk management strategy.
