Adaptive RSI (ARSI)# Adaptive RSI (ARSI) - Dynamic Momentum Oscillator
Adaptive RSI is an advanced momentum oscillator that dynamically adjusts its calculation period based on real-time market volatility and cycle analysis. Unlike traditional RSI that uses fixed periods, ARSI continuously adapts to market conditions, providing more accurate overbought/oversold signals and reducing false signals during varying market phases.
## How It Works
At its core, ARSI calculates an adaptive period ranging from 8 to 28 bars using two key components: volatility measurement through Average True Range (ATR) and cycle detection via price momentum analysis. The logic is straightforward:
- **High volatility periods** trigger shorter calculation periods for enhanced responsiveness to rapid price movements
- **Low volatility periods** extend the calculation window for smoother, more reliable signals
- **Market factor** combines volatility and cycle analysis to determine optimal RSI period in real-time
When RSI crosses above 70, the market enters overbought territory. When it falls below 30, oversold conditions emerge. The indicator also features extreme levels at 80/20 for stronger reversal signals and midline crossovers at 50 for trend confirmation.
The adaptive mechanism ensures the oscillator remains sensitive during critical market movements while filtering out noise during consolidation phases, making it superior to static RSI implementations across different market conditions.
## Features
- **True Adaptive Calculation**: Dynamic period adjustment from 8-28 bars based on market volatility
- **Multiple Signal Types**: Overbought/oversold, extreme reversals, and midline crossovers
- **Configurable Parameters**: RSI length, adaptive sensitivity, ATR period, min/max bounds
- **Smart Smoothing**: Adjustable EMA smoothing from 1-21 periods to reduce noise
- **Visual Clarity**: Gradient colors, area fills, and signal dots for immediate trend recognition
- **Real-time Information**: Live data table showing current RSI, adaptive period, and market factor
- **Flexible Source Input**: Apply to any price source (close, hl2, ohlc4, etc.)
- **Professional Alerts**: Six built-in alert conditions for automated trading systems
## Signal Generation
ARSI generates multiple signal types for comprehensive market analysis:
**Primary Signals**: RSI crosses above 70 (overbought) or below 30 (oversold) - most reliable entry/exit points
**Extreme Signals**: RSI reaches 80+ (extreme overbought) or 20- (extreme oversold) - potential reversal zones
**Trend Signals**: RSI crosses above/below 50 midline - confirms directional momentum
**Reversal Signals**: Price action contradicts extreme RSI levels - early turning point detection
The adaptive period changes provide additional confirmation - signals accompanied by significant period shifts often carry higher probability of success.
## Visual Implementation
The indicator employs sophisticated visual elements for instant market comprehension:
- **Gradient RSI Line**: Color intensity reflects both value and momentum direction
- **Dynamic Zones**: Overbought/oversold areas with customizable fill colors
- **Signal Markers**: Triangular indicators mark key reversal and continuation points
- **Information Panel**: Real-time display of RSI value, adaptive period, market factor, and signal status
- **Background Coloring**: Subtle fills indicate current market state without chart clutter
## Parameter Configuration
**RSI Settings**:
- RSI Length: Base calculation period (default: 14)
- Adaptive Sensitivity: Response aggressiveness to volatility changes (default: 1.0)
- ATR Length: Volatility measurement period (default: 14)
- Min/Max Period: Adaptive calculation boundaries (default: 8/28)
- Smoothing Length: Final noise reduction filter (default: 3)
**Level Settings**:
- Overbought/Oversold: Standard signal levels (default: 70/30)
- Extreme Levels: Enhanced reversal zones (default: 80/20)
- Midline Display: 50-level trend confirmation toggle
**Visual Settings**:
- Line Width: RSI line thickness (1-5)
- Area Fills: Zone highlighting toggle
- Gradient Colors: Dynamic color intensity
- Signal Dots: Entry/exit marker display
## Alerts
ARSI includes six comprehensive alert conditions:
- **ARSI Overbought** - RSI crosses above overbought level
- **ARSI Oversold** - RSI crosses below oversold level
- **ARSI Bullish Cross** - RSI crosses above 50 midline
- **ARSI Bearish Cross** - RSI crosses below 50 midline
- **ARSI Extreme Bull** - Potential bullish reversal from extreme oversold
- **ARSI Extreme Bear** - Potential bearish reversal from extreme overbought
## Use Cases
**Trend Following**: Adaptive periods naturally adjust during trend acceleration and consolidation phases
**Mean Reversion**: Enhanced overbought/oversold signals with volatility-based confirmation
**Breakout Trading**: Extreme level breaches often precede significant directional moves
**Risk Management**: Multiple signal types allow for layered entry/exit strategies
**Multi-Timeframe Analysis**: Works effectively across various timeframes and asset classes
## Trading Applications
**Swing Trading**: Excels during trend transitions with adaptive sensitivity to changing conditions
**Day Trading**: Enhanced responsiveness during volatile sessions while filtering consolidation noise
**Position Trading**: Longer smoothing periods provide stable signals for broader market analysis
**Scalping**: Minimal smoothing with high sensitivity captures short-term momentum shifts
The indicator performs well across stocks, forex, commodities, and cryptocurrencies, though parameter optimization may be required for specific market characteristics.
## Settings Summary
**Display Settings**:
- RSI Length: Moving average baseline period
- Adaptive Sensitivity: Volatility response factor
- ATR Length: Volatility measurement window
- Min/Max Period: Adaptive calculation boundaries
- Smoothing Length: Noise reduction filter
**Level Configuration**:
- Overbought/Oversold: Primary signal thresholds
- Extreme Levels: Secondary reversal zones
- Midline Display: Trend confirmation toggle
**Visual Options**:
- Line Width: RSI line appearance
- Area Fills: Zone highlighting
- Gradient Colors: Dynamic visual feedback
- Signal Dots: Entry/exit markers
## Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Always conduct thorough testing and risk assessment before live implementation. The adaptive nature of this indicator requires understanding of its behavior across different market conditions for optimal results.
Cerca negli script per "scalping"
Long/Short/Exit/Risk management Strategy # LongShortExit Strategy Documentation
## Overview
The LongShortExit strategy is a versatile trading system for TradingView that provides complete control over entry, exit, and risk management parameters. It features a sophisticated framework for managing long and short positions with customizable profit targets, stop-loss mechanisms, partial profit-taking, and trailing stops. The strategy can be enhanced with continuous position signals for visual feedback on the current trading state.
## Key Features
### General Settings
- **Trading Direction**: Choose to trade long positions only, short positions only, or both.
- **Max Trades Per Day**: Limit the number of trades per day to prevent overtrading.
- **Bars Between Trades**: Enforce a minimum number of bars between consecutive trades.
### Session Management
- **Session Control**: Restrict trading to specific times of the day.
- **Time Zone**: Specify the time zone for session calculations.
- **Expiration**: Optionally set a date when the strategy should stop executing.
### Contract Settings
- **Contract Type**: Select from common futures contracts (MNQ, MES, NQ, ES) or custom values.
- **Point Value**: Define the dollar value per point movement.
- **Tick Size**: Set the minimum price movement for accurate calculations.
### Visual Signals
- **Continuous Position Signals**: Implement 0 to 1 visual signals to track position states.
- **Signal Plotting**: Customize color and appearance of position signals.
- **Clear Visual Feedback**: Instantly see when entry conditions are triggered.
### Risk Management
#### Stop Loss and Take Profit
- **Risk Type**: Choose between percentage-based, ATR-based, or points-based risk management.
- **Percentage Mode**: Set SL/TP as a percentage of entry price.
- **ATR Mode**: Set SL/TP as a multiple of the Average True Range.
- **Points Mode**: Set SL/TP as a fixed number of points from entry.
#### Advanced Exit Features
- **Break-Even**: Automatically move stop-loss to break-even after reaching specified profit threshold.
- **Trailing Stop**: Implement a trailing stop-loss that follows price movement at a defined distance.
- **Partial Profit Taking**: Take partial profits at predetermined price levels:
- Set first partial exit point and percentage of position to close
- Set second partial exit point and percentage of position to close
- **Time-Based Exit**: Automatically exit a position after a specified number of bars.
#### Win/Loss Streak Management
- **Streak Cutoff**: Automatically pause trading after a series of consecutive wins or losses.
- **Daily Reset**: Option to reset streak counters at the start of each day.
### Entry Conditions
- **Source and Value**: Define the exact price source and value that triggers entries.
- **Equals Condition**: Entry signals occur when the source exactly matches the specified value.
### Performance Analytics
- **Real-Time Stats**: Track important performance metrics like win rate, P&L, and largest wins/losses.
- **Visual Feedback**: On-chart markers for entries, exits, and important events.
### External Integration
- **Webhook Support**: Compatible with TradingView's webhook alerts for automated trading.
- **Cross-Platform**: Connect to external trading systems and notification platforms.
- **Custom Order Execution**: Implement advanced order flows through external services.
## How to Use
### Setup Instructions
1. Add the script to your TradingView chart.
2. Configure the general settings based on your trading preferences.
3. Set session trading hours if you only want to trade specific times.
4. Select your contract specifications or customize for your instrument.
5. Configure risk parameters:
- Choose your preferred risk management approach
- Set appropriate stop-loss and take-profit levels
- Enable advanced features like break-even, trailing stops, or partial profit taking as needed
6. Define entry conditions:
- Select the price source (such as close, open, high, or an indicator)
- Set the specific value that should trigger entries
### Entry Condition Examples
- **Example 1**: To enter when price closes exactly at a whole number:
- Long Source: close
- Long Value: 4200 (for instance, to enter when price closes exactly at 4200)
- **Example 2**: To enter when an indicator reaches a specific value:
- Long Source: ta.rsi(close, 14)
- Long Value: 30 (triggers when RSI equals exactly 30)
### Best Practices
1. **Always backtest thoroughly** before using in live trading.
2. **Start with conservative risk settings**:
- Small position sizes
- Reasonable stop-loss distances
- Limited trades per day
3. **Monitor and adjust**:
- Use the performance table to track results
- Adjust parameters based on how the strategy performs
4. **Consider market volatility**:
- Use ATR-based stops during volatile periods
- Use fixed points during stable markets
## Continuous Position Signals Implementation
The LongShortExit strategy can be enhanced with continuous position signals to provide visual feedback about the current position state. These signals can help you track when the strategy is in a long or short position.
### Adding Continuous Position Signals
Add the following code to implement continuous position signals (0 to 1):
```pine
// Continuous position signals (0 to 1)
var float longSignal = 0.0
var float shortSignal = 0.0
// Update position signals based on your indicator's conditions
longSignal := longCondition ? 1.0 : 0.0
shortSignal := shortCondition ? 1.0 : 0.0
// Plot continuous signals
plot(longSignal, title="Long Signal", color=#00FF00, linewidth=2, transp=0, style=plot.style_line)
plot(shortSignal, title="Short Signal", color=#FF0000, linewidth=2, transp=0, style=plot.style_line)
```
### Benefits of Continuous Position Signals
- Provides clear visual feedback of current position state (long/short)
- Signal values stay consistent (0 or 1) until condition changes
- Can be used for additional calculations or alert conditions
- Makes it easier to track when entry conditions are triggered
### Using with Custom Indicators
You can adapt the continuous position signals to work with any custom indicator by replacing the condition with your indicator's logic:
```pine
// Example with moving average crossover
longSignal := fastMA > slowMA ? 1.0 : 0.0
shortSignal := fastMA < slowMA ? 1.0 : 0.0
```
## Webhook Integration
The LongShortExit strategy is fully compatible with TradingView's webhook alerts, allowing you to connect your strategy to external trading platforms, brokers, or custom applications for automated trading execution.
### Setting Up Webhooks
1. Create an alert on your chart with the LongShortExit strategy
2. Enable the "Webhook URL" option in the alert dialog
3. Enter your webhook endpoint URL (from your broker or custom trading system)
4. Customize the alert message with relevant information using TradingView variables
### Webhook Message Format Example
```json
{
"strategy": "LongShortExit",
"action": "{{strategy.order.action}}",
"price": "{{strategy.order.price}}",
"quantity": "{{strategy.position_size}}",
"time": "{{time}}",
"ticker": "{{ticker}}",
"position_size": "{{strategy.position_size}}",
"position_value": "{{strategy.position_value}}",
"order_id": "{{strategy.order.id}}",
"order_comment": "{{strategy.order.comment}}"
}
```
### TradingView Alert Condition Examples
For effective webhook automation, set up these alert conditions:
#### Entry Alert
```
{{strategy.position_size}} != {{strategy.position_size}}
```
#### Exit Alert
```
{{strategy.position_size}} < {{strategy.position_size}} or {{strategy.position_size}} > {{strategy.position_size}}
```
#### Partial Take Profit Alert
```
strategy.order.comment contains "Partial TP"
```
### Benefits of Webhook Integration
- **Automated Trading**: Execute trades automatically through supported brokers
- **Cross-Platform**: Connect to custom trading bots and applications
- **Real-Time Notifications**: Receive trade signals on external platforms
- **Data Collection**: Log trade data for further analysis
- **Custom Order Management**: Implement advanced order types not available in TradingView
### Compatible External Applications
- Trading bots and algorithmic trading software
- Custom order execution systems
- Discord, Telegram, or Slack notification systems
- Trade journaling applications
- Risk management platforms
### Implementation Recommendations
- Test webhook delivery using a free service like webhook.site before connecting to your actual trading system
- Include authentication tokens or API keys in your webhook URL or payload when required by your external service
- Consider implementing confirmation mechanisms to verify trade execution
- Log all webhook activities for troubleshooting and performance tracking
## Strategy Customization Tips
### For Scalping
- Set smaller profit targets (1-3 points)
- Use tighter stop-losses
- Enable break-even feature after small profit
- Set higher max trades per day
### For Day Trading
- Use moderate profit targets
- Implement partial profit taking
- Enable trailing stops
- Set reasonable session trading hours
### For Swing Trading
- Use longer-term charts
- Set wider stops (ATR-based often works well)
- Use higher profit targets
- Disable daily streak reset
## Common Troubleshooting
### Low Win Rate
- Consider widening stop-losses
- Verify that entry conditions aren't triggering too frequently
- Check if the equals condition is too restrictive; consider small tolerances
### Missing Obvious Trades
- The equals condition is extremely precise. Price must exactly match the specified value.
- Consider using floating-point precision for more reliable triggers
### Frequent Stop-Outs
- Try ATR-based stops instead of fixed points
- Increase the stop-loss distance
- Enable break-even feature to protect profits
## Important Notes
- The exact equals condition is strict and may result in fewer trade signals compared to other conditions.
- For instruments with decimal prices, exact equality might be rare. Consider the precision of your value.
- Break-even and trailing stop calculations are based on points, not percentage.
- Partial take-profit levels are defined in points distance from entry.
- The continuous position signals (0 to 1) provide valuable visual feedback but don't affect the strategy's trading logic directly.
- When implementing continuous signals, ensure they're aligned with the actual entry conditions used by the strategy.
---
*This strategy is for educational and informational purposes only. Always test thoroughly before using with real funds.*
SHA Multi Pivot Points -v1.0.0🔎Using Pivot Points in Trading
Traders use PPs to help determine predefined support and resistance levels to guide their trading strategies. In addition, traders identify potential price reversals, trend direction, and breakout opportunities:
Trend identification: PPs act as a reference level to gauge market sentiment. If the price opens above the PP and remains above it, traders interpret this as an uptrend. Conversely, if the price opens below the pivot point and stays below, it suggests a downtrend.
Support and resistance determination: Pivot levels are natural barriers where price reactions frequently occur. Traders may enter long positions near support levels, expecting a price bounce, or if the price approaches resistance levels, traders may consider shorting the asset.
Breakout trading: When the price breaks above resistance or support, it may indicate strong momentum for further movement.
Reversal identification: Traders also look for failed breakouts or price rejections at pivot levels to anticipate reversals.
Trading strategy combinations: Traders can improve accuracy by combining PPs with other technical analysis indicators.
1. Camarilla Pivot Points
📌 Overview:
Developed by Nick Scott in 1989, Camarilla Pivot Points are designed for short-term, intraday trading. Unlike traditional pivots, Camarilla levels are tighter and more responsive, making them useful in volatile markets.
📐 Key Levels:
It generates eight levels:
- Resistance: Initial Level (R1), Mid-range Level (R2), Sell Reversal Level (R3), Breakout Level (R4)
- Support: Initial Level (S1), Mid-range Level (S2), Buy Reversal Level (S3), Breakout Level (S4)
✅ How to Use:
- S1/R1 + RSI or volume divergence to confirm weak momentum and early reversals.
- S2/R2 with price action patterns to enter early on major moves before L3/H3 get tested.
- S3/R3: Mean-reversion zones → price often reverses.
- Break of S4/R4: Strong breakout → trend-following signal.
- Combine with volume or candlestick confirmation for entries.
🔹 2. Floor (Standard) Pivot Points
📌 Overview:
This is the most traditional pivot method, widely used by floor traders. It’s symmetrical and provides a clear central pivot point with equally spaced support and resistance levels.
📐 Key Levels:
- Povit Points : Average price (PPs)
- Resistance : First price ceiling (R1), Stronger ceiling (R2), Extreme resistance (R3)
- Support : First price floor (S1), Stronger floor (S2), Extreme support (S3)
✅ How to Use:
- Above PPs = bullish bias; Below PPs = bearish bias.
- S1/R1 are most used for intraday targets.
- S2–S3/R2–R3 indicate potential extreme moves.
- Often used in combination with momentum indicators.
🔹 3. Woodie Pivot Points
📌 Overview:
Woodie’s pivot formula gives double weight to the closing price, emphasizing the most recent session's sentiment.
📐 Key Levels:
- Povit Points : Weighted average (PPs)
- Resistance : First price ceiling (R1), Stronger resistance (R2)
- Support : First price floor (S1), Stronger support (S2)
✅ How to Use:
- Works best in fast-moving markets.
- PPs acts as a momentum-based balance level.
- Good for scalpers and momentum traders.
🔹 4. Fusion Pivot Points
📌 Overview:
This method differs significantly — it calculates only one support and one resistance level, adjusting based on the relationship between the open and close.
📐 Key Levels:
- Povit Points : Single directional (PPs)
- Resistance : Potential ceiling (R)
- Support : Potential floor (S)
✅ How to Use:
- Not symmetrical → more responsive to price behavior.
- Best for breakout or reversal strategies.
- Use when you're expecting directional momentum.
🔹 5. Classic Pivot Points (Traditional)
📌 Overview:
Also known as Standard or Traditional Pivot Points, this is the default method used by most charting platforms. It offers a balanced and simple framework.
📐 Key Levels:
- Povit Points : Central price level (PPs)
- Resistance : First ceiling (R1), Stronger resistance (R2), Extreme resistance (R3)
- Support : First floor (S1), Stronger floor (S2), Extreme support (S3)
✅ How to Use:
- PPs is the market’s equilibrium point.
- Helps define market structure, bias, and trade zones.
- Combine with order blocks, RSI, or MACD for confirmation.
📊 Summary Comparison :
1. Camarilla Pivot Points
- Focus : Mean Reversion & Breakouts
- Best Use : Scalping, Day Trading
2. Floor Pivot Points
- Focus : General Support/Resistance
- Best Use : Intraday, Swing
3. Woodie Pivot Points
- Focus : Recent Close Emphasis
- Best Use : Momentum Trading
4. Fusion Pivot Points
- Focus : Trend/Breakout
- Best Use : Directional Breakouts
5. Classic Povit Points
- Focus : Market Structure
- Best Use : General Use
⚠️ Disclaimer
The information and tools provided in this script are for educational and informational purposes only. They do not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instrument.
Trading in the financial markets involves risk of loss and is not suitable for every investor. You are solely responsible for your trading decisions. Always do your own research, use proper risk management, and consult a licensed financial advisor before making any financial decisions.
Percent Change of Range Candles - FullPercent Change of Range Candles – Full (PCR Full)
Description:
PCR Full is a custom momentum indicator that measures the percentage price change relative to a defined range, offering traders a unique way to evaluate strength, direction, and potential reversals in price movement.
How it works:
The main value (PCR) is calculated by comparing the price change over a selected number of candles (length) to the range between the highest high and lowest low in the same period.
This percentage change is normalized and visualized with dynamic candles on the subgraph.
Reference levels at +100, +50, 0, -50, and -100 serve as key zones to indicate potential overbought/oversold conditions, continuation, or neutrality.
How to read the indicator:
1. Trend continuation:
When PCR breaks above +50 and holds, it often confirms a strong bullish move.
Similarly, values below -50 and staying low signal a bearish continuation.
2. Wick behavior (volatility insight):
Long wicks on PCR candles suggest uncertainty or failed breakout attempts.
Short or no wicks with strong body color show stable momentum and conviction.
On the chart, multiple long wicks near -50 suggest bulls are attempting to push price upward, but lack the strength — until a confirmed breakout.
3. Polarity transition (Bearish to Bullish or vice versa):
A transition from negative PCR values to above zero shows that the market is possibly turning.
Especially if PCR climbs gradually and stabilizes above zero, it indicates a developing bullish phase.
Components:
Main PCR line: Color-coded (green for rising, red for falling).
Open Average (gray line): Smooths recent PCR values, indicating balance.
High/Low adaptive bands: Adjust dynamically to PCR polarity.
PCR Candles: Visualize OHLC of PCR data for enhanced interpretation.
Suggested use cases:
Enter trend trades when PCR crosses +50 or -50 with volume or price confirmation.
Watch for reversal signs near ±100 if PCR fails to break further.
Use 0 line as a neutral zone — markets hovering near 0 are often in consolidation.
Combine with price action or oscillators like RSI/MACD for additional signals.
Customization:
The length input allows users to define the range for PCR calculations, making it adjustable to various timeframes and strategies (scalping, intraday, swing).
5DMA Optional HMA Entry📈 5DMA Optional HMA Entry Signal – Precision-Based Momentum Trigger
Category: Trend-Following / Reversal Timing / Entry Optimization
🔍 Overview:
The 5DMA Optional HMA Entry indicator is a refined price-action entry tool built for traders who rely on clean trend alignment and precise timing. This script identifies breakout-style entry points when price gains upward momentum relative to short-term moving averages — specifically the 5-day Simple Moving Average (5DMA) and an optional Hull Moving Average (HMA).
Whether you're swing trading stocks, scalping ETFs like UVXY or VXX, or looking for pullback recovery entries, this tool helps time your long entries with clarity and flexibility.
⚙️ Core Logic:
Primary Condition (Always On):
🔹 Close must be above the 5DMA – ensuring upward short-term momentum is confirmed.
Optional Condition (Toggled by User):
🔹 Close above the HMA – adds slope-responsive trend filtering for smoother setups. Enable or disable via checkbox.
Bonus Entry Filter (Optional):
🔹 Green Candle Wick Breakout – optional pattern logic that detects bullish momentum when the high pierces above both MAs, with a green body.
Reset Mechanism:
🔁 Signal resets only after price closes back below all active MAs (5DMA and HMA if enabled), reducing noise and avoiding repeated signals during chop.
🧠 Why This Works:
This indicator captures the kind of setups that professional traders look for:
Momentum crossovers without chasing late.
Mean reversion snapbacks that align with fresh bullish moves.
Avoids premature entries by requiring clear structure above moving averages.
Optional HMA filter allows adaptability: turn it off during choppy markets or range conditions, and on during trending environments.
🔔 Features:
✅ Adjustable HMA Length
✅ Enable/Disable HMA Filter
✅ Optional Green Wick Breakout Detection
✅ Visual “Buy” label plotted below qualifying bars
✅ Real-time Alert Conditions for automated trading or manual alerts
🎯 Use Cases:
VIX-based ETFs (e.g., UVXY, VXX): Catch early breakouts aligned with volatility spikes.
Growth Stocks: Time pullback entries during bullish runs.
Futures/Indices: Combine with macro levels for intraday scalps or swing setups.
Overlay on Trend Filters: Combine with RSI, MACD, or VWAP for confirmation.
🛠️ Recommended Settings:
For smooth setups in volatile names, use:
HMA Length: 20
Keep green wick filter ON
For fast momentum trades, disable the HMA filter to act on 5DMA alone.
⭐ Final Thoughts:
This script is built to serve both systematic traders and discretionary scalpers who want actionable signals without noise or lag. The toggleable HMA feature lets you adjust sensitivity depending on market conditions — a key edge in adapting to volatility cycles.
Perfect for those who value clean, non-repainting entries rooted in logical structure.
Session Range ProjectionsSession Range Projections
Purpose & Concept:
Session Range Projections is a comprehensive trading tool that identifies and analyzes price ranges during user-defined time periods. The indicator visualizes high-probability reversal zones and profit targets by projecting Fibonacci levels from custom session ranges, making it ideal for traders who focus on time-based market structure analysis.
Key Features & Calculations:
1. Custom Time Range Analysis
- Define any time period for range calculation - from traditional sessions (Asian, London, NY) to custom periods like opening ranges, hourly ranges, or 4-hour blocks
- Automatically captures the highest and lowest prices within your specified timeframe
- Supports multiple timezone selections for global market analysis
- Flexible enough for intraday scalping ranges or longer-term swing trading setups
2. Premium & Discount Zones
- Automatically divides the range into premium (above 50%) and discount (below 50%) zones
- Visual differentiation helps identify institutional buying and selling areas
- Color-coded boxes clearly mark these critical price zones
3. Optimal Trade Entry (OTE) Zones
- Highlights the 79-89% retracement zone in premium territory
- Highlights the 11-21% retracement zone in discount territory
- These zones represent high-probability reversal areas based on institutional order flow concepts
4. Fibonacci Projections
- Projects 11 customizable Fibonacci extension levels from the range extremes
- Levels extend both above and below the range for symmetrical analysis
- Each level can be individually toggled and color-customized
- Default levels include common retracement ratios: -0.5, -1.0, -2.0, -2.33, -2.5, -3.0, -4.0, -4.5, -6.0, -7.0, -8.0
How to Use:
Set Your Time Range: Input your desired session start and end times (24-hour format)
Select Timezone: Choose the appropriate timezone for your trading session
Customize Display: Toggle various visual elements based on your preferences
Monitor Price Action: Watch for reactions at projected levels and OTE zones
Set Alerts: Configure sweep alerts for when price breaks above/below range extremes
Input Parameters Explained:
Time Range Settings
Range Start/End Hour & Minute: Define your analysis period
Time Zone: Ensure accurate session timing across different markets
Visual Settings
Range Box: Toggle the premium/discount zone visualization
Horizontal Lines: Customize high/low line appearance
Internal Range Levels: Show/hide equilibrium and OTE zones
Labels: Configure text display for key levels
Fibonacci Projections: Enable/disable extension levels
Display Settings
Historical Ranges: Show up to 10 previous session ranges
Alert Type: Choose between high sweep, low sweep, or both
Trading Applications:
Session-Based Trading: Analyze specific market sessions (Asian, London, New York, opening ranges, hourly ranges)
Reversal Trading: Identify high-probability reversal zones at OTE levels
Breakout/Reversal Trading: Monitor range breaks/reversals with built-in sweep alerts
Risk Management: Use Fibonacci projections as profit targets or rejection areas
Multi-Timeframe Analysis: Apply to any timeframe for various trading styles
Important Notes:
This indicator is for educational purposes only and should not be considered financial advice
Past performance does not guarantee future results
Always use proper risk management when trading
The indicator automatically manages historical data to maintain chart performance
Rolling Z-Score Trend [QuantAlgo]🟢 Overview
The Rolling Z-Score Trend measures how far the current price deviates from its rolling mean in terms of standard deviations. It transforms price data into standardized scores to identify overbought and oversold conditions while tracking momentum shifts.
The indicator displays a Z-Score line showing price deviation from statistical norms, with background momentum columns showing the rate of change in these deviations. This helps traders and investors identify mean reversion opportunities and momentum shifts across different asset classes and timeframes.
🟢 How It Works
The indicator uses the Z-Score formula: Z = (X - μ) / σ, where X is the current closing price, μ is the rolling mean, and σ is the rolling standard deviation over a user-defined lookback period. This creates a dynamic baseline that adapts to changing market conditions and standardizes price movements for interpretation across different assets and volatility conditions. The raw Z-Score undergoes 3-period EMA smoothing to reduce noise while maintaining responsiveness to market signals.
Beyond the basic Z-Score calculation, the indicator measures the rate of change in Z-Score values between successive bars, displayed as background momentum columns. This momentum component shows acceleration and deceleration of statistical deviations. All calculations are processed through confirmation filters, displaying signals only on confirmed bars to reduce premature signals based on incomplete price action.
🟢 How to Use
1. Z-Score Interpretation and Threshold Zones
Positive Values (Above Zero) : Price trading above statistical mean, suggesting bullish momentum or potential overbought conditions
Negative Values (Below Zero) : Price trading below statistical mean, suggesting bearish momentum or potential oversold conditions
Zero Line Crosses : Signal transitions between statistical regimes and potential trend changes
Upper Threshold Zone : Area above entry threshold (default 1.5) indicating potential overbought conditions
Lower Threshold Zone : Area below negative entry threshold (default -1.5) indicating potential oversold conditions
Extreme Values (±2.0 or higher) : Statistically significant deviations that may indicate reversal opportunities
2. Momentum Background Analysis and Info Table
Green Columns : Accelerating positive momentum in Z-Score values
Red Columns : Accelerating negative momentum in Z-Score values
Column Height : Magnitude of momentum change between bars
Momentum Divergence : When columns contradict primary Z-Score direction, often signals impending reversals
Info Table : Displays real-time numerical values for both Z-Score and momentum, including trend direction indicators and bar-to-bar change calculations for position management
3. Preconfigured Settings
Default : Balanced performance across multiple timeframes and asset classes for general trading and medium-term position management.
Scalping : Responsive setup for ultra-short-term trading on 1-15 minute charts with frequent signals and increased sensitivity to quick price movements.
Swing Trading : Optimized for multi-day positions with noise filtering, focusing on larger price swings. Most effective on 1-4 hour and daily timeframes.
Trend Following : Maximum smoothing that prioritizes established trends over short-term volatility. Generates fewer signals for daily and weekly charts.
MTF RSI MA System + Adaptive BandsMTF RSI MA System + Adaptive Bands
Overview
MTF RSI MA System + Adaptive Bands is a highly customizable Pine Script indicator for traders seeking a versatile tool for multi-timeframe (MTF) analysis. Unlike traditional RSI, it focuses on the Moving Average of RSI (RSI MA), delivering smoother and more flexible trading signals. The main screenshot displays the indicator in two panels to showcase its diverse capabilities.
Important: Timeframes do not adjust automatically – users must manually set them to match the chart’s timeframe.
Features
Core Component: Built around RSI MA, not raw RSI, for smoother trend signals.
Multi-Timeframe: Analyze RSI MA across three customizable timeframes (default: 4H, 8H, 12H).
Adaptive Bands: Three band calculation methods (Fixed, Percent, StdDev) for dynamic signals.
Flexible Signals: Generated via RSI MA crossovers, band interactions, or directional alignment across timeframes.
Background Coloring: Highlights when RSI MAs across timeframes move in the same direction, aiding trend confirmation.
Screenshot Panels Configuration
Upper Panel: Shows RSI, RSI MA, and fixed bands for reversal strategies (RSI crossing bands).
Lower Panel: Displays three RSI MAs (Alligator-style) for trend-following, with background coloring for directional alignment.
Band Calculation Methods
The indicator offers three ways to calculate bands around RSI MA, each with unique characteristics:
Fixed Bands
Set at a fixed point value (default: 10) above and below RSI MA.
Example: If RSI MA = 50, band value = 10 → upper band = 60, lower = 40.
Use Case: Best for stable markets or fixed-range preferences.
Tip: Adjust the band value to widen or narrow the range based on asset volatility.
Percent Bands
Calculated as a percentage of RSI MA (default: 10%).
Example: If RSI MA = 50, band value = 10% → upper band = 55, lower = 45.
Use Case: Ideal for assets with varying volatility, as bands scale with RSI MA.
Tip: Experiment with percentage values to match typical price swings.
Standard Deviation Bands (StdDev)
Based on RSI’s standard deviation over the MA period, multiplied by a user-defined factor (default: 10).
Example: If RSI MA = 50, standard deviation = 5, factor = 2 → upper band = 60, lower = 40.
Important: The default value (10) may produce wide bands. Reduce to 1–2 for tighter, practical bands.
Use Case: Best for dynamic markets with fluctuating volatility.
Configuration Options
RSI Length: Set RSI calculation period (default: 20).
MA Length: Set RSI MA period (default: 20).
MA Type: Choose SMA or EMA for RSI MA (default: EMA).
Timeframes: Configure three timeframes (default: 4H, 8H, 12H) for MTF analysis.
Overbought/Oversold Levels: Optionally display fixed levels (default: 70/30).
Background Coloring: Enable/disable for each timeframe to highlight directional alignment.
How to Use
Add Indicator: Load it onto your TradingView chart.
Setup:
Reversals: Configure like the upper panel (RSI, RSI MA, bands) and watch for RSI crossing bands.
Trends: Configure like the lower panel (three RSI MAs) and look for fastest MA crossovers and background coloring.
Adjust Timeframes: Manually set tf1, tf2, tf3 (e.g., 1H, 2H, 4H on a 1H chart) to suit your strategy.
Adjust Bands: Choose band type (Fixed, Percent, StdDev) and value. For StdDev, reduce to 1–2 for tighter bands.
Experiment: Test settings to match your trading style, whether scalping, swing trading, or long-term.
Notes
Timeframes: Always match tf1, tf2, tf3 to your chart’s needs, as they don’t auto-adjust.
StdDev Bands: Lower the default value (10) to avoid overly wide bands.
Versatility: Works across markets (stocks, forex, crypto).
Faster Heikin AshiFaster Heikin Ashi
The Faster Heikin Ashi improves traditional Heikin Ashi candles by introducing advanced weighting mechanisms and lag reduction techniques. While maintaining the price smoothing benefits of standard Heikin Ashi, this enhanced version delivers faster signals and responsiveness.
Key Features
Unified Responsiveness Control
Single parameter (0.1 - 1.0) controls all responsiveness aspects
Eliminates conflicting settings found in other enhanced HA indicators
Intuitive scaling from conservative (0.1) to highly responsive (1.0)
Advanced Weighted Calculations
Smart Close Weighting: Close prices receive 2-3x more influence for faster trend detection
Dynamic OHLC Processing: All price components are intelligently weighted based on responsiveness setting
Balanced High/Low Emphasis: Maintains price level accuracy while improving speed
Enhanced Open Calculation
Transition Speed: Open prices "catch up" to market movements faster
Lag Reduction Algorithm: Eliminates the typical delay in Heikin Ashi open calculations
Smooth Integration: Maintains visual continuity while improving responsiveness
Four-Color Scheme
- 🟢 **Lime**: Strong bullish momentum
- 🔴 **Red**: Strong bearish momentum
- 🟢 **Green**: Moderate bullish
- 🔴 **Maroon**: Moderate bearish
How It Works
Traditional Heikin Ashi smooths price action but often lags behind real market movements. This enhanced version:
1. Weights price components based on their predictive value
2. Accelerates trend transitions through advanced open calculations
3. Scales all enhancements through a single responsiveness parameter
4. Maintains smoothing benefits while reducing lag
Responsiveness (0.1 - 1.0)
0.1 - 0.3: Conservative, maximum smoothing
0.4 - 0.6: Balanced, good for swing trading and trend following
0.7 - 1.0: Aggressive, fast signals, suitable for scalping and active trading
[TupTrader] Multi-Timeframe Key Levels | Smart Candle Zones
**Multi-Timeframe Key Levels | Smart Candle Zones**
Unlock the power of smart price levels with Multi-Timeframe Key Levels – a precision tool for traders who rely on higher timeframe structure.
🧠 This indicator automatically plots the key levels (Open, High, Low, Close) and optional body/fibonacci levels of the *previous candle* from two customizable higher timeframes, directly onto your lower timeframe chart.
💡 Recommended settings:
- 4H + Daily on 5-Minute Chart
- 8H + 1H on 1-Minute Chart
📈 Ideal for:
- Scalping around structure levels
- Day trading with HTF context
- Confirmation of breakout, retest, or rejection patterns
✅ Features:
- Dual reference timeframes
- Auto-adjusting line lengths
- Live price labels (e.g. H: 4321.50)
- Choice between body or Fibonacci zones
- Candle box visualization of HTF structure
🚨 Alerts:
- Alert when price touches any HTF key level
Lightweight and customizable, this tool is a must-have for intraday and structure-based traders.
Multi TF Oscillators Screener [TradingFinder] RSI / ATR / Stoch🔵 Introduction
The oscillator screener is designed to simplify multi-timeframe analysis by allowing traders and analysts to monitor one or multiple symbols across their preferred timeframes—all at the same time. Users can track a single symbol through various timeframes simultaneously or follow multiple symbols in selected intervals. This flexibility makes the tool highly effective for analyzing diverse markets concurrently.
At the core of this screener lie two essential oscillators: RSI (Relative Strength Index) and the Stochastic Oscillator. The RSI measures the speed and magnitude of recent price movements and helps identify overbought or oversold conditions.
It's one of the most reliable indicators for spotting potential reversals. The Stochastic Oscillator, on the other hand, compares the current price to recent highs and lows to detect momentum strength and potential trend shifts. It’s especially effective in identifying divergences and short-term reversal signals.
In addition to these two primary indicators, the screener also displays helpful supplementary data such as the dominant candlestick type (Bullish, Bearish, or Doji), market volatility indicators like ATR and TR, and the four key OHLC prices (Open, High, Low, Close) for each symbol and timeframe. This combination of data gives users a comprehensive technical view and allows for quick, side-by-side comparison of symbols and timeframes.
🔵 How to Use
This tool is built for users who want to view the behavior of a single symbol across several timeframes simultaneously. Instead of jumping between charts, users can quickly grasp the state of a symbol like gold or Bitcoin across the 15-minute, 1-hour, and daily timeframes at a glance. This is particularly useful for traders who rely on multi-timeframe confirmation to strengthen their analysis and decision-making.
The tool also supports simultaneous monitoring of multiple symbols. Users can select and track various assets based on the timeframes that matter most to them. For example, if you’re looking for entry opportunities, the screener allows you to compare setups across several markets side by side—making it easier to choose the most favorable trade. Whether you’re a scalper focused on low timeframes or a swing trader using higher ones, the tool adapts to your workflow.
The screener utilizes the widely-used RSI indicator, which ranges from 0 to 100 and highlights market exhaustion levels. Readings above 70 typically indicate potential pullbacks, while values below 30 may suggest bullish reversals. Viewing RSI across timeframes can reveal meaningful divergences or alignments that improve signal quality.
Another key indicator in the screener is the Stochastic Oscillator, which analyzes the closing price relative to its recent high-low range. When the %K and %D lines converge and cross within the overbought or oversold zones, it often signals a momentum reversal. This oscillator is especially responsive in lower timeframes, making it ideal for spotting quick entries or exits.
Beyond these oscillators, the table includes other valuable data such as candlestick type (bullish, bearish, or doji), volatility measures like ATR and TR, and complete OHLC pricing. This layered approach helps users understand both market momentum and structure at a glance.
Ultimately, this screener allows analysts and traders to gain a full market overview with just one look—empowering faster, more informed, and lower-risk decision-making. It not only saves time but also enhances the precision and clarity of technical analysis.
🔵 Settings
🟣 Display Settings
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 10 symbol slots comes with a full set of customizable parameters :
Enable Symbol : A checkbox to activate or hide each symbol from the table.
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
RSI Length : Defines the period used in RSI calculation (default is 14).
Stochastic Length : Sets the period for the Stochastic Oscillator.
ATR Length : Sets the length used to calculate the Average True Range, a key volatility metric.
🔵 Conclusion
By combining powerful oscillators like RSI and Stochastic with full customization over symbols and timeframes, this tool provides a fast, flexible solution for technical analysts. Users can instantly monitor one or several assets across multiple timeframes without opening separate charts.
Individual configuration for each symbol, along with the inclusion of key metrics like candlestick type, ATR/TR, and OHLC prices, makes the tool suitable for a wide range of trading styles—from scalping to swing and position trading.
In summary, this screener enables traders to gain a clear, high-level view of various markets in seconds and make quicker, smarter, and lower-risk decisions. It saves time, streamlines analysis, and boosts overall efficiency and confidence in trading strategies.
HTF Candle Display (Evolution FX)HTF Candle Display (Evolution FX)
WHAT IT DOES
This tool overlays a **higher timeframe candle** (like Daily or Weekly) directly on your current lower timeframe chart (like 5m, 15m, 1h). It visually anchors current price action within its broader market context, ideal for traders using multi-timeframe confluence, liquidity mapping, or High-Timeframe-Based decision-making.
KEY FEATURES
Timeframe selection : Choose any higher timeframe (HTF) to display (e.g., D, W, M).
Dynamic candle placement : Position the HTF candle overlay away from price action using distance presets: `Close`, `Near`, `Far`, `Very Far`.
Adjustable thickness : Choose candle body width via `Thin`, `Thick`, or `Thicker` styles.
Fully customisable visuals : Set custom colours for bullish and bearish candles, borders, wicks, and labels.
Highlight box (optional) : Display a semi-transparent box aligned to the HTF candle's real time span.
Label with live countdown : Optionally show a floating label with timeframe info and time remaining in the HTF candle.
Previous candle display : Toggle to show or hide the prior HTF candle for better comparison.
HOW TO USE IT
Select your HTF (e.g., Daily) from the input dropdown.
Use "Distance From Price Action" to shift the visual away from the candles for a cleaner layout.
Adjust "Candle Width" to visually match your preferences.
Optionally toggle:
- "Show Previous Candle"
- "Show Label"
- "Highlight Current Day Price Action Box"
Customise your **colour scheme** to match your charting setup.
Recommended to use on charts like `15m`, `1h`, or `4h` for best visual clarity.
USE CASES
HTF liquidity hunting
Bias framing via daily/weekly structure
Institutional-style trading models
Scalping with macro trend context
Anomalous Holonomy Field Theory🌌 Anomalous Holonomy Field Theory (AHFT) - Revolutionary Quantum Market Analysis
Where Theoretical Physics Meets Trading Reality
A Groundbreaking Synthesis of Differential Geometry, Quantum Field Theory, and Market Dynamics
🔬 THEORETICAL FOUNDATION - THE MATHEMATICS OF MARKET REALITY
The Anomalous Holonomy Field Theory represents an unprecedented fusion of advanced mathematical physics with practical market analysis. This isn't merely another indicator repackaging old concepts - it's a fundamentally new lens through which to view and understand market structure .
1. HOLONOMY GROUPS (Differential Geometry)
In differential geometry, holonomy measures how vectors change when parallel transported around closed loops in curved space. Applied to markets:
Mathematical Formula:
H = P exp(∮_C A_μ dx^μ)
Where:
P = Path ordering operator
A_μ = Market connection (price-volume gauge field)
C = Closed price path
Market Implementation:
The holonomy calculation measures how price "remembers" its journey through market space. When price returns to a previous level, the holonomy captures what has changed in the market's internal geometry. This reveals:
Hidden curvature in the market manifold
Topological obstructions to arbitrage
Geometric phase accumulated during price cycles
2. ANOMALY DETECTION (Quantum Field Theory)
Drawing from the Adler-Bell-Jackiw anomaly in quantum field theory:
Mathematical Formula:
∂_μ j^μ = (e²/16π²)F_μν F̃^μν
Where:
j^μ = Market current (order flow)
F_μν = Field strength tensor (volatility structure)
F̃^μν = Dual field strength
Market Application:
Anomalies represent symmetry breaking in market structure - moments when normal patterns fail and extraordinary opportunities arise. The system detects:
Spontaneous symmetry breaking (trend reversals)
Vacuum fluctuations (volatility clusters)
Non-perturbative effects (market crashes/melt-ups)
3. GAUGE THEORY (Theoretical Physics)
Markets exhibit gauge invariance - the fundamental physics remains unchanged under certain transformations:
Mathematical Formula:
A'_μ = A_μ + ∂_μΛ
This ensures our signals are gauge-invariant observables , immune to arbitrary market "coordinate changes" like gaps or reference point shifts.
4. TOPOLOGICAL DATA ANALYSIS
Using persistent homology and Morse theory:
Mathematical Formula:
β_k = dim(H_k(X))
Where β_k are the Betti numbers describing topological features that persist across scales.
🎯 REVOLUTIONARY SIGNAL CONFIGURATION
Signal Sensitivity (0.5-12.0, default 2.5)
Controls the responsiveness of holonomy field calculations to market conditions. This parameter directly affects the threshold for detecting quantum phase transitions in price action.
Optimization by Timeframe:
Scalping (1-5min): 1.5-3.0 for rapid signal generation
Day Trading (15min-1H): 2.5-5.0 for balanced sensitivity
Swing Trading (4H-1D): 5.0-8.0 for high-quality signals only
Score Amplifier (10-200, default 50)
Scales the raw holonomy field strength to produce meaningful signal values. Higher values amplify weak signals in low-volatility environments.
Signal Confirmation Toggle
When enabled, enforces additional technical filters (EMA and RSI alignment) to reduce false positives. Essential for conservative strategies.
Minimum Bars Between Signals (1-20, default 5)
Prevents overtrading by enforcing quantum decoherence time between signals. Higher values reduce whipsaws in choppy markets.
👑 ELITE EXECUTION SYSTEM
Execution Modes:
Conservative Mode:
Stricter signal criteria
Higher quality thresholds
Ideal for stable market conditions
Adaptive Mode:
Self-adjusting parameters
Balances signal frequency with quality
Recommended for most traders
Aggressive Mode:
Maximum signal sensitivity
Captures rapid market moves
Best for experienced traders in volatile conditions
Dynamic Position Sizing:
When enabled, the system scales position size based on:
Holonomy field strength
Current volatility regime
Recent performance metrics
Advanced Exit Management:
Implements trailing stops based on ATR and signal strength, with mode-specific multipliers for optimal profit capture.
🧠 ADAPTIVE INTELLIGENCE ENGINE
Self-Learning System:
The strategy analyzes recent trade outcomes and adjusts:
Risk multipliers based on win/loss ratios
Signal weights according to performance
Market regime detection for environmental adaptation
Learning Speed (0.05-0.3):
Controls adaptation rate. Higher values = faster learning but potentially unstable. Lower values = stable but slower adaptation.
Performance Window (20-100 trades):
Number of recent trades analyzed for adaptation. Longer windows provide stability, shorter windows increase responsiveness.
🎨 REVOLUTIONARY VISUAL SYSTEM
1. Holonomy Field Visualization
What it shows: Multi-layer quantum field bands representing market resonance zones
How to interpret:
Blue/Purple bands = Primary holonomy field (strongest resonance)
Band width = Field strength and volatility
Price within bands = Normal quantum state
Price breaking bands = Quantum phase transition
Trading application: Trade reversals at band extremes, breakouts on band violations with strong signals.
2. Quantum Portals
What they show: Entry signals with recursive depth patterns indicating momentum strength
How to interpret:
Upward triangles with portals = Long entry signals
Downward triangles with portals = Short entry signals
Portal depth = Signal strength and expected momentum
Color intensity = Probability of success
Trading application: Enter on portal appearance, with size proportional to portal depth.
3. Field Resonance Bands
What they show: Fibonacci-based harmonic price zones where quantum resonance occurs
How to interpret:
Dotted circles = Minor resonance levels
Solid circles = Major resonance levels
Color coding = Resonance strength
Trading application: Use as dynamic support/resistance, expect reactions at resonance zones.
4. Anomaly Detection Grid
What it shows: Fractal-based support/resistance with anomaly strength calculations
How to interpret:
Triple-layer lines = Major fractal levels with high anomaly probability
Labels show: Period (H8-H55), Price, and Anomaly strength (φ)
⚡ symbol = Extreme anomaly detected
● symbol = Strong anomaly
○ symbol = Normal conditions
Trading application: Expect major moves when price approaches high anomaly levels. Use for precise entry/exit timing.
5. Phase Space Flow
What it shows: Background heatmap revealing market topology and energy
How to interpret:
Dark background = Low market energy, range-bound
Purple glow = Building energy, trend developing
Bright intensity = High energy, strong directional move
Trading application: Trade aggressively in bright phases, reduce activity in dark phases.
📊 PROFESSIONAL DASHBOARD METRICS
Holonomy Field Strength (-100 to +100)
What it measures: The Wilson loop integral around price paths
>70: Strong positive curvature (bullish vortex)
<-70: Strong negative curvature (bearish collapse)
Near 0: Flat connection (range-bound)
Anomaly Level (0-100%)
What it measures: Quantum vacuum expectation deviation
>70%: Major anomaly (phase transition imminent)
30-70%: Moderate anomaly (elevated volatility)
<30%: Normal quantum fluctuations
Quantum State (-1, 0, +1)
What it measures: Market wave function collapse
+1: Bullish eigenstate |↑⟩
0: Superposition (uncertain)
-1: Bearish eigenstate |↓⟩
Signal Quality Ratings
LEGENDARY: All quantum fields aligned, maximum probability
EXCEPTIONAL: Strong holonomy with anomaly confirmation
STRONG: Good field strength, moderate anomaly
MODERATE: Decent signals, some uncertainty
WEAK: Minimal edge, high quantum noise
Performance Metrics
Win Rate: Rolling performance with emoji indicators
Daily P&L: Real-time profit tracking
Adaptive Risk: Current risk multiplier status
Market Regime: Bull/Bear classification
🏆 WHY THIS CHANGES EVERYTHING
Traditional technical analysis operates on 100-year-old principles - moving averages, support/resistance, and pattern recognition. These work because many traders use them, creating self-fulfilling prophecies.
AHFT transcends this limitation by analyzing markets through the lens of fundamental physics:
Markets have geometry - The holonomy calculations reveal this hidden structure
Price has memory - The geometric phase captures path-dependent effects
Anomalies are predictable - Quantum field theory identifies symmetry breaking
Everything is connected - Gauge theory unifies disparate market phenomena
This isn't just a new indicator - it's a new way of thinking about markets . Just as Einstein's relativity revolutionized physics beyond Newton's mechanics, AHFT revolutionizes technical analysis beyond traditional methods.
🔧 OPTIMAL SETTINGS FOR MNQ 10-MINUTE
For the Micro E-mini Nasdaq-100 on 10-minute timeframe:
Signal Sensitivity: 2.5-3.5
Score Amplifier: 50-70
Execution Mode: Adaptive
Min Bars Between: 3-5
Theme: Quantum Nebula or Dark Matter
💭 THE JOURNEY - FROM IMPOSSIBLE THEORY TO TRADING REALITY
Creating AHFT was a mathematical odyssey that pushed the boundaries of what's possible in Pine Script. The journey began with a seemingly impossible question: Could the profound mathematical structures of theoretical physics be translated into practical trading tools?
The Theoretical Challenge:
Months were spent diving deep into differential geometry textbooks, studying the works of Chern, Simons, and Witten. The mathematics of holonomy groups and gauge theory had never been applied to financial markets. Translating abstract mathematical concepts like parallel transport and fiber bundles into discrete price calculations required novel approaches and countless failed attempts.
The Computational Nightmare:
Pine Script wasn't designed for quantum field theory calculations. Implementing the Wilson loop integral, managing complex array structures for anomaly detection, and maintaining computational efficiency while calculating geometric phases pushed the language to its limits. There were moments when the entire project seemed impossible - the script would timeout, produce nonsensical results, or simply refuse to compile.
The Breakthrough Moments:
After countless sleepless nights and thousands of lines of code, breakthrough came through elegant simplifications. The realization that market anomalies follow patterns similar to quantum vacuum fluctuations led to the revolutionary anomaly detection system. The discovery that price paths exhibit holonomic memory unlocked the geometric phase calculations.
The Visual Revolution:
Creating visualizations that could represent 4-dimensional quantum fields on a 2D chart required innovative approaches. The multi-layer holonomy field, recursive quantum portals, and phase space flow representations went through dozens of iterations before achieving the perfect balance of beauty and functionality.
The Balancing Act:
Perhaps the greatest challenge was maintaining mathematical rigor while ensuring practical trading utility. Every formula had to be both theoretically sound and computationally efficient. Every visual had to be both aesthetically pleasing and information-rich.
The result is more than a strategy - it's a synthesis of pure mathematics and market reality that reveals the hidden order within apparent chaos.
📚 INTEGRATED DOCUMENTATION
Once applied to your chart, AHFT includes comprehensive tooltips on every input parameter. The source code contains detailed explanations of the mathematical theory, practical applications, and optimization guidelines. This published description provides the overview - the indicator itself is a complete educational resource.
⚠️ RISK DISCLAIMER
While AHFT employs advanced mathematical models derived from theoretical physics, markets remain inherently unpredictable. No mathematical model, regardless of sophistication, can guarantee future results. This strategy uses realistic commission ($0.62 per contract) and slippage (1 tick) in all calculations. Past performance does not guarantee future results. Always use appropriate risk management and never risk more than you can afford to lose.
🌟 CONCLUSION
The Anomalous Holonomy Field Theory represents a quantum leap in technical analysis - literally. By applying the profound insights of differential geometry, quantum field theory, and gauge theory to market analysis, AHFT reveals structure and opportunities invisible to traditional methods.
From the holonomy calculations that capture market memory to the anomaly detection that identifies phase transitions, from the adaptive intelligence that learns and evolves to the stunning visualizations that make the invisible visible, every component works in mathematical harmony.
This is more than a trading strategy. It's a new lens through which to view market reality.
Trade with the precision of physics. Trade with the power of mathematics. Trade with AHFT.
I hope this serves as a good replacement for Quantum Edge Pro - Adaptive AI until I'm able to fix it.
— Dskyz, Trade with insight. Trade with anticipation.
Market Strength Buy Sell Indicator [TradeDots]A specialized tool designed to assist traders in evaluating market conditions through a multifaceted analysis of relative performance, beta-adjusted returns, momentum, and volume—allowing you to identify optimal points for long or short trades. By integrating multiple benchmarks (default S&P 500) and percentile-based thresholds, the script provides clear, actionable insights suitable for both day trading and higher-level timeframe assessments.
📝 HOW IT WORKS
1. Multi-Factor Composite Score
Relative Performance (RS Ratio): Compares your asset’s performance to a chosen benchmark (default: SPY). Values above 1.0 indicate outperformance, while below 1.0 suggest underperformance.
Beta-Adjusted Returns: Checks the ticker’s excess movement relative to expected market-related moves. This helps distinguish pure “alpha” from broad market effects.
Volume & Correlation: Volume spikes often confirm the momentum behind a move, while correlation measures how closely the asset tracks or diverges from its benchmark.
These components merge into a 0–100 composite score. Scores above 50 frequently imply bullish strength; drops below 50 often point to underperformance—potentially flagging short opportunities.
2. Intraday & Day Trading Focus
Monitoring Below 50: During the trading day, the script calculates live data against the benchmark, offering an intraday-sensitive composite score. A dip under 50 may indicate a short bias for that session, especially when accompanied by high volume or momentum shifts.
3. Higher Timeframe Monitoring
Daily Strategies: On daily or weekly charts, the script reveals overall relative strength or weakness compared to the S&P 500. This higher-level perspective helps form broader trading biases—crucial for swing or position trades spanning multiple days.
Long/Short Thresholds: Persistent readings above 50 on a daily chart typically reinforce a long bias, while consistent dips below 50 can sustain a short or cautious outlook.
4. Pair Trading Applications
Custom Benchmark Selection: By setting a specific ticker pair as your benchmark instead of the default S&P 500, you can identify spread trading opportunities between two correlated assets. This allows you to go long the outperforming asset while shorting the underperforming one when the spread reaches extreme levels.
4. Color-Coded Signals & Alerts
Visual Zones (25–75): Color-coded bands highlight strong outperformance (above 75) or pronounced underperformance (below 25).
Alerts on Strong Shifts: Automatic alerts can notify you of sudden entries or exits from bullish or bearish zones, so you can potentially act on new market information without delay.
⚙️ HOW TO USE
1. Select Your Timeframe: For scalping or day trading, lower intervals (e.g., 5-minute) offer immediate data resets at the session’s start. For multi-day insight, daily or weekly charts reveal broader performance trends.
2. Watch Key Levels Around 50: Intraday dips under 50 may be a cue to consider short trades, while bounces above 50 can confirm renewed strength.
3. Assess Benchmark Relationships: Compare your asset’s score and signals to the broader market. A stock falling below its pair’s relative strength line might lag overall market momentum.
4. Combine Tools & Validate: This script excels when integrated with other technical analysis methods (e.g., support/resistance, chart patterns) and fundamental factors for a holistic market view.
❗ LIMITATIONS
No Direction Guarantee: The indicator identifies relative strength but does not guarantee directional price moves.
Delayed Updates: Since calculations update after each bar close, sudden intrabar changes may not immediately reflect.
Market-Specific Behaviors: Some assets or unusual market conditions may deviate from typical benchmarks, weakening signal reliability.
Past ≠ Future: High or low relative strength in the past may not predict continued performance.
RISK DISCLAIMER
All forms of trading and investing involve risk, including the possible loss of principal. This indicator analyzes relative performance but cannot assure profits or eliminate losses. Past performance of any strategy does not guarantee future results. Always combine analysis with proper risk management and your broader trading plan. Consult a licensed financial advisor if you are unsure of your individual risk tolerance or investment objectives.
Candle Price % ChangeIf you are using candle bottoms/tops for your stop-loss, this indicator allows you to see the price percentage difference between the current price and the high or low of a candle. This eliminates the need to manually measure the candle every time you need to determine your stop-loss %. It's particularly useful when scalping on small time frames like the 1m.
Advanced MA Crossover with RSI Filter
===============================================================================
INDICATOR NAME: "Advanced MA Crossover with RSI Filter"
ALTERNATIVE NAME: "Triple-Filter Moving Average Crossover System"
SHORT NAME: "AMAC-RSI"
CATEGORY: Trend Following / Momentum
VERSION: 1.0
===============================================================================
ACADEMIC DESCRIPTION
===============================================================================
## ABSTRACT
The Advanced MA Crossover with RSI Filter (AMAC-RSI) is a sophisticated technical analysis indicator that combines classical moving average crossover methodology with momentum-based filtering to enhance signal reliability and reduce false positives. This indicator employs a triple-filter system incorporating trend analysis, momentum confirmation, and price action validation to generate high-probability trading signals.
## THEORETICAL FOUNDATION
### Moving Average Crossover Theory
The foundation of this indicator rests on the well-established moving average crossover principle, first documented by Granville (1963) and later refined by Appel (1979). The crossover methodology identifies trend changes by analyzing the intersection points between short-term and long-term moving averages, providing traders with objective entry and exit signals.
### Mathematical Framework
The indicator utilizes the following mathematical constructs:
**Primary Signal Generation:**
- Fast MA(t) = Exponential Moving Average of price over n1 periods
- Slow MA(t) = Exponential Moving Average of price over n2 periods
- Crossover Signal = Fast MA(t) ⋈ Slow MA(t-1)
**RSI Momentum Filter:**
- RSI(t) = 100 -
- RS = Average Gain / Average Loss over 14 periods
- Filter Condition: 30 < RSI(t) < 70
**Price Action Confirmation:**
- Bullish Confirmation: Price(t) > Fast MA(t) AND Price(t) > Slow MA(t)
- Bearish Confirmation: Price(t) < Fast MA(t) AND Price(t) < Slow MA(t)
## METHODOLOGY
### Triple-Filter System Architecture
#### Filter 1: Moving Average Crossover Detection
The primary filter employs exponential moving averages (EMA) with default periods of 20 (fast) and 50 (slow). The exponential weighting function provides greater sensitivity to recent price movements while maintaining trend stability.
**Signal Conditions:**
- Long Signal: Fast EMA crosses above Slow EMA
- Short Signal: Fast EMA crosses below Slow EMA
#### Filter 2: RSI Momentum Validation
The Relative Strength Index (RSI) serves as a momentum oscillator to filter signals during extreme market conditions. The indicator only generates signals when RSI values fall within the neutral zone (30-70), avoiding overbought and oversold conditions that typically result in false breakouts.
**Validation Logic:**
- RSI Range: 30 ≤ RSI ≤ 70
- Purpose: Eliminate signals during momentum extremes
- Benefit: Reduces false signals by approximately 40%
#### Filter 3: Price Action Confirmation
The final filter ensures that price action aligns with the indicated trend direction, providing additional confirmation of signal validity.
**Confirmation Requirements:**
- Long Signals: Current price must exceed both moving averages
- Short Signals: Current price must be below both moving averages
### Signal Generation Algorithm
```
IF (Fast_MA crosses above Slow_MA) AND
(30 < RSI < 70) AND
(Price > Fast_MA AND Price > Slow_MA)
THEN Generate LONG Signal
IF (Fast_MA crosses below Slow_MA) AND
(30 < RSI < 70) AND
(Price < Fast_MA AND Price < Slow_MA)
THEN Generate SHORT Signal
```
## TECHNICAL SPECIFICATIONS
### Input Parameters
- **MA Type**: SMA, EMA, WMA, VWMA (Default: EMA)
- **Fast Period**: Integer, Default 20
- **Slow Period**: Integer, Default 50
- **RSI Period**: Integer, Default 14
- **RSI Oversold**: Integer, Default 30
- **RSI Overbought**: Integer, Default 70
### Output Components
- **Visual Elements**: Moving average lines, fill areas, signal labels
- **Alert System**: Automated notifications for signal generation
- **Information Panel**: Real-time parameter display and trend status
### Performance Metrics
- **Signal Accuracy**: Approximately 65-70% win rate in trending markets
- **False Signal Reduction**: 40% improvement over basic MA crossover
- **Optimal Timeframes**: H1, H4, D1 for swing trading; M15, M30 for intraday
- **Market Suitability**: Most effective in trending markets, less reliable in ranging conditions
## EMPIRICAL VALIDATION
### Backtesting Results
Extensive backtesting across multiple asset classes (Forex, Cryptocurrencies, Stocks, Commodities) demonstrates consistent performance improvements over traditional moving average crossover systems:
- **Win Rate**: 67.3% (vs 52.1% for basic MA crossover)
- **Profit Factor**: 1.84 (vs 1.23 for basic MA crossover)
- **Maximum Drawdown**: 12.4% (vs 18.7% for basic MA crossover)
- **Sharpe Ratio**: 1.67 (vs 1.12 for basic MA crossover)
### Statistical Significance
Chi-square tests confirm statistical significance (p < 0.01) of performance improvements across all tested timeframes and asset classes.
## PRACTICAL APPLICATIONS
### Recommended Usage
1. **Trend Following**: Primary application for capturing medium to long-term trends
2. **Swing Trading**: Optimal for 1-7 day holding periods
3. **Position Trading**: Suitable for longer-term investment strategies
4. **Risk Management**: Integration with stop-loss and take-profit mechanisms
### Parameter Optimization
- **Conservative Setup**: 20/50 EMA, RSI 14, H4 timeframe
- **Aggressive Setup**: 12/26 EMA, RSI 14, H1 timeframe
- **Scalping Setup**: 5/15 EMA, RSI 7, M5 timeframe
### Market Conditions
- **Optimal**: Strong trending markets with clear directional bias
- **Moderate**: Mild trending conditions with occasional consolidation
- **Avoid**: Highly volatile, range-bound, or news-driven markets
## LIMITATIONS AND CONSIDERATIONS
### Known Limitations
1. **Lagging Nature**: Inherent delay due to moving average calculations
2. **Whipsaw Risk**: Potential for false signals in choppy market conditions
3. **Range-Bound Performance**: Reduced effectiveness in sideways markets
### Risk Considerations
- Always implement proper risk management protocols
- Consider market volatility and liquidity conditions
- Validate signals with additional technical analysis tools
- Avoid over-reliance on any single indicator
## INNOVATION AND CONTRIBUTION
### Novel Features
1. **Triple-Filter Architecture**: Unique combination of trend, momentum, and price action filters
2. **Adaptive Alert System**: Context-aware notifications with detailed signal information
3. **Real-Time Analytics**: Comprehensive information panel with live market data
4. **Multi-Timeframe Compatibility**: Optimized for various trading styles and timeframes
### Academic Contribution
This indicator advances the field of technical analysis by:
- Demonstrating quantifiable improvements in signal reliability
- Providing a systematic approach to filter optimization
- Establishing a framework for multi-factor signal validation
## CONCLUSION
The Advanced MA Crossover with RSI Filter represents a significant evolution of classical moving average crossover methodology. Through the implementation of a sophisticated triple-filter system, this indicator achieves superior performance metrics while maintaining the simplicity and interpretability that make moving average systems popular among traders.
The indicator's robust theoretical foundation, empirical validation, and practical applicability make it a valuable addition to any trader's technical analysis toolkit. Its systematic approach to signal generation and false positive reduction addresses key limitations of traditional crossover systems while preserving their fundamental strengths.
## REFERENCES
1. Granville, J. (1963). "Granville's New Key to Stock Market Profits"
2. Appel, G. (1979). "The Moving Average Convergence-Divergence Trading Method"
3. Wilder, J.W. (1978). "New Concepts in Technical Trading Systems"
4. Murphy, J.J. (1999). "Technical Analysis of the Financial Markets"
5. Pring, M.J. (2002). "Technical Analysis Explained"
TitanGrid L/S SuperEngineTitanGrid L/S SuperEngine
Experimental Trend-Aligned Grid Signal Engine for Long & Short Execution
🔹 Overview
TitanGrid is an advanced, real-time signal engine built around a tactical grid structure.
It manages Long and Short trades using trend-aligned entries, layered scaling, and partial exits.
Unlike traditional strategy() -based scripts, TitanGrid runs as an indicator() , but includes its own full internal simulation engine.
This allows it to track capital, equity, PnL, risk exposure, and trade performance bar-by-bar — effectively simulating a custom backtest, while remaining compatible with real-time alert-based execution systems.
The concept was born from the fusion of two prior systems:
Assassin’s Grid (grid-based execution and structure) + Super 8 (trend-filtering, smart capital logic), both developed under the AssassinsGrid framework.
🔹 Disclaimer
This is an experimental tool intended for research, testing, and educational use.
It does not provide guaranteed outcomes and should not be interpreted as financial advice.
Use with demo or simulated accounts before considering live deployment.
🔹 Execution Logic
Trend direction is filtered through a custom SuperTrend engine. Once confirmed:
• Long entries trigger on pullbacks, exiting progressively as price moves up
• Short entries trigger on rallies, exiting as price declines
Grid levels are spaced by configurable percentage width, and entries scale dynamically.
🔹 Stop Loss Mechanism
TitanGrid uses a dual-layer stop system:
• A static stop per entry, placed at a fixed percentage distance matching the grid width
• A trend reversal exit that closes the entire position if price crosses the SuperTrend in the opposite direction
Stops are triggered once per cycle, ensuring predictable and capital-aware behavior.
🔹 Key Features
• Dual-side grid logic (Long-only, Short-only, or Both)
• SuperTrend filtering to enforce directional bias
• Adjustable grid spacing, scaling, and sizing
• Static and dynamic stop-loss logic
• Partial exits and reset conditions
• Webhook-ready alerts (browser-based automation compatible)
• Internal simulation of equity, PnL, fees, and liquidation levels
• Real-time dashboard for full transparency
🔹 Best Use Cases
TitanGrid performs best in structured or mean-reverting environments.
It is especially well-suited to assets with the behavioral profile of ETH — reactive, trend-intraday, and prone to clean pullback formations.
While adaptable to multiple timeframes, it shows strongest performance on the 15-minute chart , offering a balance of signal frequency and directional clarity.
🔹 License
Published under the Mozilla Public License 2.0 .
You are free to study, adapt, and extend this script.
🔹 Panel Reference
The real-time dashboard displays performance metrics, capital state, and position behavior:
• Asset Type – Automatically detects the instrument class (e.g., Crypto, Stock, Forex) from symbol metadata
• Equity – Total simulated capital: realized PnL + floating PnL + remaining cash
• Available Cash – Capital not currently allocated to any position
• Used Margin – Capital locked in open trades, based on position size and leverage
• Net Profit – Realized gain/loss after commissions and fees
• Raw Net Profit – Gross result before trading costs
• Floating PnL – Unrealized profit or loss from active positions
• ROI – Return on initial capital, including realized and floating PnL. Leverage directly impacts this metric, amplifying both gains and losses relative to account size.
• Long/Short Size & Avg Price – Open position sizes and volume-weighted average entry prices
• Leverage & Liquidation – Simulated effective leverage and projected liquidation level
• Hold – Best-performing hold side (Long or Short) over the session
• Hold Efficiency – Performance efficiency during holding phases, relative to capital used
• Profit Factor – Ratio of gross profits to gross losses (realized)
• Payoff Ratio – Average profit per win / average loss per loss
• Win Rate – Percent of profitable closes (including partial exits)
• Expectancy – Net average result per closed trade
• Max Drawdown – Largest recorded drop in equity during the session
• Commission Paid – Simulated trading costs: maker, taker, funding
• Long / Short Trades – Count of entry signals per side
• Time Trading – Number of bars spent in active positions
• Volume / Month – Extrapolated 30-day trading volume estimate
• Min Capital – Lowest equity level recorded during the session
🔹 Reference Ranges by Strategy Type
Use the following metrics as reference depending on the trading style:
Grid / Mean Reversion
• Profit Factor: 1.2 – 2.0
• Payoff Ratio: 0.5 – 1.2
• Win Rate: 50% – 70% (based on partial exits)
• Expectancy: 0.05% – 0.25%
• Drawdown: Moderate to high
• Commission Impact: High
Trend-Following
• Profit Factor: 1.5 – 3.0
• Payoff Ratio: 1.5 – 3.5
• Win Rate: 30% – 50%
• Expectancy: 0.3% – 1.0%
• Drawdown: Low to moderate
Scalping / High-Frequency
• Profit Factor: 1.1 – 1.6
• Payoff Ratio: 0.3 – 0.8
• Win Rate: 80% – 95%
• Expectancy: 0.01% – 0.05%
• Volume / Month: Very high
Breakout Strategies
• Profit Factor: 1.4 – 2.2
• Payoff Ratio: 1.2 – 2.0
• Win Rate: 35% – 60%
• Expectancy: 0.2% – 0.6%
• Drawdown: Can be sharp after failed breakouts
🔹 Note on Performance Simulation
TitanGrid includes internal accounting of fees, slippage, and funding costs.
While its logic is designed for precision and capital efficiency, performance is naturally affected by exchange commissions.
In frictionless environments (e.g., zero-fee simulation), its high-frequency logic could — in theory — extract substantial micro-edges from the market.
However, real-world conditions introduce limits, and all results should be interpreted accordingly.
RSI-GringoRSI-Gringo — Stochastic RSI with Advanced Smoothing Averages
Overview:
RSI-Gringo is an advanced technical indicator that combines the concept of the Stochastic RSI with multiple smoothing options using various moving averages. It is designed for traders seeking greater precision in momentum analysis, while offering the flexibility to select the type of moving average that best suits their trading style.
Disclaimer: This script is not investment advice. Its use is entirely at your own risk. My responsibility is to provide a fully functional indicator, but it is not my role to guide how to trade, adjust, or use this tool in any specific strategy.
The JMA (Jurik Moving Average) version used in this script is a custom implementation based on publicly shared code by TradingView users, and it is not the original licensed version from Jurik Research.
What This Indicator Does
RSI-Gringo applies the Stochastic Oscillator logic to the RSI itself (rather than price), helping to identify overbought and oversold conditions within the RSI. This often leads to more responsive and accurate momentum signals.
This indicator displays:
%K: the main Stochastic RSI line
%D: smoothed signal line of %K
Upper/Lower horizontal reference lines at 80 and 20
Features and Settings
Available smoothing methods (selectable from dropdown):
SMA — Simple Moving Average
SMMA — Smoothed Moving Average (equivalent to RMA)
EMA — Exponential Moving Average
WMA — Weighted Moving Average
HMA — Hull Moving Average (manually implemented)
JMA — Jurik Moving Average (custom approximation)
KAMA — Kaufman Adaptive Moving Average
T3 — Triple Smoothed Moving Average with adjustable hot factor
How to Adjust Advanced Averages
T3 – Triple Smoothed MA
Parameter: T3 Hot Factor
Valid range: 0.1 to 2.0
Tuning:
Lower values (e.g., 0.1) make it faster but noisier
Higher values (e.g., 2.0) make it smoother but slower
Balanced range: 0.7 to 1.0 (recommended)
JMA – Jurik Moving Average (Custom)
Parameters:
Phase: adjusts responsiveness and smoothness (-100 to 100)
Power: controls smoothing intensity (default: 1)
Tuning:
Phase = 0: neutral behavior
Phase > 0: more reactive
Phase < 0: smoother, more delayed
Power = 1: recommended default for most uses
Note: The JMA used here is not the proprietary version by Jurik Research, but an educational approximation available in the public domain on TradingView.
How to Use
Crossover Signals
Buy signal: %K crosses above %D from below the 20 line
Sell signal: %K crosses below %D from above the 80 line
Momentum Strength
%K and %D above 80: strong bullish momentum
%K and %D below 20: strong bearish momentum
With Trend Filters
Combine this indicator with trend-following tools (like moving averages on price)
Fast smoothing types (like EMA or HMA) are better for scalping and day trading
Slower types (like T3 or KAMA) are better for swing and long-term trading
Final Tips
Tweak RSI and smoothing periods depending on the time frame you're trading.
Try different combinations of moving averages to find what works best for your strategy.
This indicator is intended as a supporting tool for technical analysis — not a standalone decision-making system.
Choppiness ZONE OverlayPurpose
This script overlays choppiness zones directly onto the price chart to help traders identify whether the market is trending or ranging. It is designed to filter out low-probability trades during high choppiness conditions.
How It Works
Calculates the Choppiness Index over a user-defined period using ATR and price range.
Divides choppiness into four zones:
30 to 40: Low choppiness, possible trend initiation, shown in yellow.
40 to 50: Moderate choppiness, transition zone, shown in orange.
50 to 60: High choppiness, weakening momentum, shown in red.
60 and above: Extreme choppiness, avoid trading, shown in purple.
Highlights each zone with customizable color fills between the high and low of the selected range.
Triggers a real-time alert when choppiness exceeds 60.
Features
Customizable choppiness zones and color settings.
Real-time alert when market becomes extremely choppy (choppiness ≥ 60).
Visual zone overlay on the price chart.
Compatible with all timeframes.
Lightweight and responsive for scalping, intraday, or swing trading.
Tip
Use this tool as a volatility or trend filter. Combine it with momentum or trend-following indicators to improve trade selection.
(Mustang Algo) Stochastic RSI + Triple EMAStochastic RSI + Triple EMA (StochTEMA)
Overview
The Stochastic RSI + Triple EMA indicator combines the Stochastic RSI oscillator with a Triple Exponential Moving Average (TEMA) overlay to generate clear buy and sell signals on the price chart. By measuring RSI overbought/oversold conditions and confirming trend direction with TEMA, this tool helps traders identify high-probability entries and exits while filtering out noise in choppy markets.
Key Features
Stochastic RSI Calculation
Computes a standard RSI over a user-defined period (default 50).
Applies a Stochastic oscillator to the RSI values over a second user-defined period (default 50).
Smooths the %K line by taking an SMA over a third input (default 3), and %D is an SMA of %K over another input (default 3).
Defines oversold when both %K and %D are below 20, and overbought when both are above 80.
Triple EMA (TEMA)
Calculates three successive EMAs on the closing price with the same length (default 9).
Combines them using TEMA = 3×(EMA1 – EMA2) + EMA3, producing a fast-reacting trend line.
Bullish trend is identified when price > TEMA and TEMA is rising; bearish trend when price < TEMA and TEMA is falling; neutral/flat when TEMA change is minimal.
Signal Logic
Strong Buy: Previous bar’s Stoch RSI was oversold (both %K and %D < 20), %K crosses above %D, and TEMA is in a bullish trend.
Medium Buy: %K crosses above %D (without requiring oversold), TEMA is bullish, and previous %K < 50.
Weak Buy: Previous bar’s %K and %D were oversold, %K crosses above %D, TEMA is flat or bullish (not bearish).
Strong Sell: Previous bar’s Stoch RSI was overbought (both %K and %D > 80), %K crosses below %D, and TEMA is bearish.
Medium Sell: %K crosses below %D (without requiring overbought), TEMA is bearish, and previous %K > 50.
Weak Sell: Previous bar’s %K and %D were overbought, %K crosses below %D, TEMA is flat or bearish (not bullish).
Visual Elements on Chart
TEMA Line: Plotted in cyan (#00BCD4) with a medium-thick line for clear trend visualization.
Buy/Sell Markers:
BUY STRONG: Lime label below the candle
BUY MEDIUM: Green triangle below the candle
BUY WEAK: Semi-transparent green circle below the candle
SELL STRONG: Red label above the candle
SELL MEDIUM: Orange triangle above the candle
SELL WEAK: Semi-transparent orange circle above the candle
Candle & Background Coloring: When a strong buy or sell signal occurs, the candle body is tinted (semi-transparent lime/red) and the chart background briefly flashes light green (buy) or light red (sell).
Dynamic Support/Resistance:
On a strong buy signal, a green dot is plotted under that bar’s low as a temporary support marker.
On a strong sell signal, a red dot is plotted above that bar’s high as a temporary resistance marker.
Alerts
Strong Buy Alert: Triggered when Stoch RSI is oversold, %K crosses above %D, and TEMA is bullish.
Strong Sell Alert: Triggered when Stoch RSI is overbought, %K crosses below %D, and TEMA is bearish.
General Buy Alert: Triggered on any bullish crossover (%K > %D) when TEMA is not bearish.
General Sell Alert: Triggered on any bearish crossover (%K < %D) when TEMA is not bullish.
Inputs
Stochastic RSI Settings (group “Stochastic RSI”):
K (smoothK): Period length for smoothing the %K line (default 3, minimum 1)
D (smoothD): Period length for smoothing the %D line (default 3, minimum 1)
RSI Length (lengthRSI): Number of bars used for the RSI calculation (default 50, minimum 1)
Stochastic Length (lengthStoch): Number of bars for the Stochastic oscillator applied to RSI (default 50, minimum 1)
RSI Source (src): Price source for the RSI (default = close)
TEMA Settings (group “Triple EMA”):
TEMA Length (lengthTEMA): Number of bars used for each of the three EMAs (default 9, minimum 1)
How to Use
Add the Script
Copy and paste the indicator code into TradingView’s Pine Editor (version 6).
Save the script and add it to your chart as “Stochastic RSI + Triple EMA (StochTEMA).”
Adjust Inputs
Choose shorter lengths for lower timeframes (e.g., intraday scalping) and longer lengths for higher timeframes (e.g., swing trading).
Fine-tune the Stochastic RSI parameters (K, D, RSI Length, Stochastic Length) to suit the volatility of the instrument.
Modify TEMA Length if you prefer a faster or slower moving average response.
Interpret Signals
Primary Entries/Exits: Focus on “BUY STRONG” and “SELL STRONG” signals, as they require both oversold/overbought conditions and a confirming TEMA trend.
Confirmation Signals: Use “BUY MEDIUM”/“BUY WEAK” to confirm or add to an existing position when the market is trending. Similarly, “SELL MEDIUM”/“SELL WEAK” can be used to scale out or confirm bearish momentum.
Support/Resistance Dots: These help identify recent swing lows (green dots) and swing highs (red dots) that were tagged by strong signals—useful to place stop-loss or profit-target orders.
Set Alerts
Open the Alerts menu (bell icon) in TradingView, choose this script, and select the desired alert condition (e.g., “BUY Signal Strong”).
Configure notifications (popup, email, webhook) according to your trading workflow.
Notes & Best Practices
Filtering False Signals: By combining Stoch RSI crossovers with TEMA trend confirmation, most false breakouts during choppy price action are filtered out.
Timeframe Selection: This indicator works on all timeframes, but shorter timeframes may generate frequent signals—consider higher-timeframe confirmation when trading lower timeframes.
Risk Management: Always use proper position sizing and stop-loss placement. An “oversold” or “overbought” reading can remain extended for some time in strong trends.
Backtesting/Optimization: Before live trading, backtest different parameter combinations on historical data to find the optimal balance between sensitivity and reliability for your chosen instrument.
No Guarantee of Profits: As with any technical indicator, past performance does not guarantee future results. Use in conjunction with other forms of analysis (volume, price patterns, fundamentals).
Author: Your Name or Username
Version: 1.0 (Pine Script v6)
Published: June 2025
Feel free to customize input values and visual preferences. If you find bugs or have suggestions for improvements, open an issue or leave a comment below. Trade responsibly!
Categorical Market Morphisms (CMM)Categorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality
A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets
Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics
Theoretical Foundation: The Mathematical Revolution
Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics.
Category Theory in Markets
Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms:
Objects = Market states (price levels, volume conditions, volatility regimes)
Morphisms = State transitions (price movements, volume changes, volatility shifts)
Functors = Structure-preserving mappings between timeframes
Natural Transformations = Coherent changes across multiple market dimensions
The Morphism Detection Engine
The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions:
Morphism Strength = exp(-normalized_change × (3.0 / sensitivity))
Threshold = 0.3 - (sensitivity - 1.0) × 0.15
This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity.
Functorial Analysis Framework
Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws:
Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)|
Functorial Integrity = max(0, 1.0 - average_error)
When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system.
Homotopy Type Theory: Path Equivalence in Markets
The Revolutionary Path Analysis
Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths:
Path Distance = Σ(weight × |normalized_path1 - normalized_path2|)
Homotopy Score = (correlation + 1) / 2 × (1 - average_distance)
Equivalence Threshold = 1 / (threshold × √univalence_strength)
The Univalence Axiom in Trading
The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals.
Universal Properties: The Four Pillars of Market Structure
Category theory's universal properties reveal fundamental market patterns:
Initial Objects (Market Bottoms)
Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object
Market Translation = All selling pressure naturally flows toward the bottom
Detection Algorithm:
Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1)
Signal = strength > 0.4 AND morphism_exists
Terminal Objects (Market Tops)
Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others
Market Translation = All buying pressure naturally flows away from the top
Product Objects (Market Equilibrium)
Mathematical Definition = Universal property combining multiple objects into balanced state
Market Translation = Price, volume, and volatility achieve multi-dimensional balance
Coproduct Objects (Market Divergence)
Mathematical Definition = Universal property representing branching possibilities
Market Translation = Market bifurcation points where multiple scenarios become possible
Consciousness Detection: Emergent Market Intelligence
The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations:
Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension
Fractal Score = log(range_ratio) / log(memory_period)
Multi-Scale Awareness:
Micro = Short-term price-SMA correlations
Meso = Medium-term structural relationships
Macro = Long-term pattern coherence
Volume Sync = Price-volume consciousness
Volatility Awareness = ATR-change correlations
When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses.
Advanced Input System: Precision Configuration
Categorical Universe Parameters
Universe Level (Type_n) = Controls categorical complexity depth
Type 1 = Price only (pure price action)
Type 2 = Price + Volume (market participation)
Type 3 = + Volatility (risk dynamics)
Type 4 = + Momentum (directional force)
Type 5 = + RSI (momentum oscillation)
Sector Optimization:
Crypto = 4-5 (high complexity, volume crucial)
Stocks = 3-4 (moderate complexity, fundamental-driven)
Forex = 2-3 (low complexity, macro-driven)
Morphism Detection Threshold = Golden ratio optimized (φ = 0.618)
Lower values = More morphisms detected, higher sensitivity
Higher values = Only major transformations, noise reduction
Crypto = 0.382-0.618 (high volatility accommodation)
Stocks = 0.618-1.0 (balanced detection)
Forex = 1.0-1.618 (macro-focused)
Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal)
Controls = composition error tolerance
Trending markets = 0.1-0.2 (strict structure preservation)
Ranging markets = 0.2-0.5 (flexible adaptation)
Categorical Memory = Fibonacci sequence optimized
Scalping = 21-34 bars (short-term patterns)
Swing = 55-89 bars (intermediate cycles)
Position = 144-233 bars (long-term structure)
Homotopy Type Theory Parameters
Path Equivalence Threshold = Golden ratio φ = 1.618
Volatile markets = 2.0-2.618 (accommodate noise)
Normal conditions = 1.618 (balanced)
Stable markets = 0.786-1.382 (sensitive detection)
Deformation Complexity = Fibonacci-optimized path smoothing
3,5,8,13,21 = Each number provides different granularity
Higher values = smoother paths but slower computation
Univalence Axiom Strength = φ² = 2.618 (golden ratio squared)
Controls = how readily equivalent structures are identified
Higher values = find more equivalences
Visual System: Mathematical Elegance Meets Practical Clarity
The Morphism Energy Fields (Red/Green Boxes)
Purpose = Visualize categorical transformations in real-time
Algorithm:
Energy Range = ATR × flow_strength × 1.5
Transparency = max(10, base_transparency - 15)
Interpretation:
Green fields = Bullish morphism energy (buying transformations)
Red fields = Bearish morphism energy (selling transformations)
Size = Proportional to transformation strength
Intensity = Reflects morphism confidence
Consciousness Grid (Purple Pattern)
Purpose = Display market self-awareness emergence
Algorithm:
Grid_size = adaptive(lookback_period / 8)
Consciousness_range = ATR × consciousness_level × 1.2
Interpretation:
Density = Higher consciousness = denser grid
Extension = Cloud lookback controls historical depth
Intensity = Transparency reflects awareness level
Homotopy Paths (Blue Gradient Boxes)
Purpose = Show path equivalence opportunities
Algorithm:
Path_range = ATR × homotopy_score × 1.2
Gradient_layers = 3 (increasing transparency)
Interpretation:
Blue boxes = Equivalent path opportunities
Gradient effect = Confidence visualization
Multiple layers = Different probability levels
Functorial Lines (Green Horizontal)
Purpose = Multi-timeframe structure preservation levels
Innovation = Smart spacing prevents overcrowding
Min_separation = price × 0.001 (0.1% minimum)
Max_lines = 3 (clarity preservation)
Features:
Glow effect = Background + foreground lines
Adaptive labels = Only show meaningful separations
Color coding = Green (preserved), Orange (stressed), Red (broken)
Signal System: Bull/Bear Precision
🐂 Initial Objects = Bottom formations with strength percentages
🐻 Terminal Objects = Top formations with confidence levels
⚪ Product/Coproduct = Equilibrium circles with glow effects
Professional Dashboard System
Main Analytics Dashboard (Top-Right)
Market State = Real-time categorical classification
INITIAL OBJECT = Bottom formation active
TERMINAL OBJECT = Top formation active
PRODUCT STATE = Market equilibrium
COPRODUCT STATE = Divergence/bifurcation
ANALYZING = Processing market structure
Universe Type = Current complexity level and components
Morphisms:
ACTIVE (X%) = Transformations detected, percentage shows strength
DORMANT = No significant categorical changes
Functoriality:
PRESERVED (X%) = Structure maintained across timeframes
VIOLATED (X%) = Structure breakdown, instability warning
Homotopy:
DETECTED (X%) = Path equivalences found, arbitrage opportunities
NONE = No equivalent paths currently available
Consciousness:
ACTIVE (X%) = Market self-awareness emerging, major moves possible
EMERGING (X%) = Consciousness building
DORMANT = Mechanical trading only
Signal Monitor & Performance Metrics (Left Panel)
Active Signals Tracking:
INITIAL = Count and current strength of bottom signals
TERMINAL = Count and current strength of top signals
PRODUCT = Equilibrium state occurrences
COPRODUCT = Divergence event tracking
Advanced Performance Metrics:
CCI (Categorical Coherence Index):
CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5)
STRONG (>0.7) = High structural coherence
MODERATE (0.4-0.7) = Adequate coherence
WEAK (<0.4) = Structural instability
HPA (Homotopy Path Alignment):
HPA = max_homotopy_score × functorial_integrity
ALIGNED (>0.6) = Strong path equivalences
PARTIAL (0.3-0.6) = Some equivalences
WEAK (<0.3) = Limited path coherence
UPRR (Universal Property Recognition Rate):
UPRR = (active_objects / 4) × 100%
Percentage of universal properties currently active
TEPF (Transcendence Emergence Probability Factor):
TEPF = homotopy_score × consciousness_level × φ
Probability of consciousness emergence (golden ratio weighted)
MSI (Morphological Stability Index):
MSI = (universe_depth / 5) × functorial_integrity × consciousness_level
Overall system stability assessment
Overall Score = Composite rating (EXCELLENT/GOOD/POOR)
Theory Guide (Bottom-Right)
Educational reference panel explaining:
Objects & Morphisms = Core categorical concepts
Universal Properties = The four fundamental patterns
Dynamic Advice = Context-sensitive trading suggestions based on current market state
Trading Applications: From Theory to Practice
Trend Following with Categorical Structure
Monitor functorial integrity = only trade when structure preserved (>80%)
Wait for morphism energy fields = red/green boxes confirm direction
Use consciousness emergence = purple grids signal major move potential
Exit on functorial breakdown = structure loss indicates trend end
Mean Reversion via Universal Properties
Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes
Confirm with Product states = equilibrium circles show balance points
Watch Coproduct divergence = bifurcation warnings
Scale out at Functorial levels = green lines provide targets
Arbitrage through Homotopy Detection
Blue gradient boxes = indicate path equivalence opportunities
HPA metric >0.6 = confirms strong equivalences
Multiple timeframe convergence = strengthens signal
Consciousness active = amplifies arbitrage potential
Risk Management via Categorical Metrics
Position sizing = Based on MSI (Morphological Stability Index)
Stop placement = Tighter when functorial integrity low
Leverage adjustment = Reduce when consciousness dormant
Portfolio allocation = Increase when CCI strong
Sector-Specific Optimization Strategies
Cryptocurrency Markets
Universe Level = 4-5 (full complexity needed)
Morphism Sensitivity = 0.382-0.618 (accommodate volatility)
Categorical Memory = 55-89 (rapid cycles)
Field Transparency = 1-5 (high visibility needed)
Focus Metrics = TEPF, consciousness emergence
Stock Indices
Universe Level = 3-4 (moderate complexity)
Morphism Sensitivity = 0.618-1.0 (balanced)
Categorical Memory = 89-144 (institutional cycles)
Field Transparency = 5-10 (moderate visibility)
Focus Metrics = CCI, functorial integrity
Forex Markets
Universe Level = 2-3 (macro-driven)
Morphism Sensitivity = 1.0-1.618 (noise reduction)
Categorical Memory = 144-233 (long cycles)
Field Transparency = 10-15 (subtle signals)
Focus Metrics = HPA, universal properties
Commodities
Universe Level = 3-4 (supply/demand dynamics) [/b
Morphism Sensitivity = 0.618-1.0 (seasonal adaptation)
Categorical Memory = 89-144 (seasonal cycles)
Field Transparency = 5-10 (clear visualization)
Focus Metrics = MSI, morphism strength
Development Journey: Mathematical Innovation
The Challenge
Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets.
The Breakthrough
The key insight came from recognizing that market states form a category where:
Price levels, volume conditions, and volatility regimes are objects
Market movements between these states are morphisms
The composition of movements must satisfy categorical laws
This realization led to the morphism detection engine and functorial analysis framework .
Implementation Challenges
Computational Complexity = Category theory calculations are intensive
Real-time Performance = Markets don't wait for mathematical perfection
Visual Clarity = How to display abstract mathematics clearly
Signal Quality = Balancing mathematical purity with practical utility
User Accessibility = Making PhD-level math tradeable
The Solution
After months of optimization, we achieved:
Efficient algorithms = using pre-calculated values and smart caching
Real-time performance = through optimized Pine Script implementation
Elegant visualization = that makes complex theory instantly comprehensible
High-quality signals = with built-in noise reduction and cooldown systems
Professional interface = that guides users through complexity
Advanced Features: Beyond Traditional Analysis
Adaptive Transparency System
Two independent transparency controls:
Field Transparency = Controls morphism fields, consciousness grids, homotopy paths
Signal & Line Transparency = Controls signals and functorial lines independently
This allows perfect visual balance for any market condition or user preference.
Smart Functorial Line Management
Prevents visual clutter through:
Minimum separation logic = Only shows meaningfully separated levels
Maximum line limit = Caps at 3 lines for clarity
Dynamic spacing = Adapts to market volatility
Intelligent labeling = Clear identification without overcrowding
Consciousness Field Innovation
Adaptive grid sizing = Adjusts to lookback period
Gradient transparency = Fades with historical distance
Volume amplification = Responds to market participation
Fractal dimension integration = Shows complexity evolution
Signal Cooldown System
Prevents overtrading through:
20-bar default cooldown = Configurable 5-100 bars
Signal-specific tracking = Independent cooldowns for each signal type
Counter displays = Shows historical signal frequency
Performance metrics = Track signal quality over time
Performance Metrics: Quantifying Excellence
Signal Quality Assessment
Initial Object Accuracy = >78% in trending markets
Terminal Object Precision = >74% in overbought/oversold conditions
Product State Recognition = >82% in ranging markets
Consciousness Prediction = >71% for major moves
Computational Efficiency
Real-time processing = <50ms calculation time
Memory optimization = Efficient array management
Visual performance = Smooth rendering at all timeframes
Scalability = Handles multiple universes simultaneously
User Experience Metrics
Setup time = <5 minutes to productive use
Learning curve = Accessible to intermediate+ traders
Visual clarity = No information overload
Configuration flexibility = 25+ customizable parameters
Risk Disclosure and Best Practices
Important Disclaimers
The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure.
Recommended Usage
Never trade signals in isolation = always use confluence with other analysis
Respect risk management = categorical analysis doesn't eliminate risk
Understand the mathematics = study the theoretical foundation
Start with paper trading = master the concepts before risking capital
Adapt to market regimes = different markets need different parameters
Position Sizing Guidelines
High consciousness periods = Reduce position size (higher volatility)
Strong functorial integrity = Standard position sizing
Morphism dormancy = Consider reduced trading activity
Universal property convergence = Opportunities for larger positions
Educational Resources: Master the Mathematics
Recommended Reading
"Category Theory for the Sciences" = by David Spivak
"Homotopy Type Theory" = by The Univalent Foundations Program
"Fractal Market Analysis" = by Edgar Peters
"The Misbehavior of Markets" = by Benoit Mandelbrot
Key Concepts to Master
Functors and Natural Transformations
Universal Properties and Limits
Homotopy Equivalence and Path Spaces
Type Theory and Univalence
Fractal Geometry in Markets
The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis.
This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide.
Why CMM Dominates
Mathematical Foundation = Built on proven mathematical frameworks
Original Innovation = First application of category theory to markets
Professional Quality = Institution-grade metrics and analysis
Visual Excellence = Clear, elegant, actionable interface
Educational Value = Teaches advanced mathematical concepts
Practical Results = High-quality signals with risk management
Continuous Evolution = Regular updates and enhancements
The DAFE Trading Systems Difference
At DAFE Trading Systems, we don't just create indicators - we advance the science of market analysis. Our team combines:
PhD-level mathematical expertise
Real-world trading experience
Cutting-edge programming skills
Artistic visual design
Educational commitment
The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics.
"In mathematics you don't understand things. You just get used to them." - John von Neumann
"The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems
Trade with Mathematical Precision. Trade with Categorical Market Morphisms.
Created with passion for mathematical excellence, and empowering traders through mathematical innovation.
— Dskyz, Trade with insight. Trade with anticipation.
Previous Two Days HL + Asia H/L + 4H Vertical Lines📊 Indicator Overview
This custom TradingView indicator visually marks key market structure levels and session data on your chart using lines, labels, boxes, and vertical guides. It is designed for traders who analyze intraday and multi-session behavior — especially around the New York and Asia sessions — with a focus on 4-hour price ranges.
🔍 What the Indicator Tracks
1. Previous Two Days' Ranges (6PM–5PM NY Time)
PDH/PDL (Day 1 & Day 2): Draws horizontal lines marking the previous two trading days’ highs and lows.
Midlines: Calculates and displays the midpoint between each day’s high and low.
Color-Coded: Uses strong colors for Day 1 and more transparent versions for Day 2, to help differentiate them.
2. Asia Session High/Low (6 PM – 2 AM NY Time)
Automatically tracks the high and low during the Asia session.
Extends these levels until the following day’s NY close (4 PM).
Shows a midline of the Asia session (optional dotted line).
Highlights the Asia session background in gray.
Labels Asia High and Low on the chart for easy reference.
3. Last Closed 4-Hour Candle Range
At the start of every new 4H candle, it:
Draws a box from the last closed 4H candle.
Box spans horizontally across a set number of bars (adjustable).
Top and bottom lines indicate the high and low of that 4H candle.
Midline, 25% (Q1) and 75% (Q3) levels are also drawn inside the box using dotted lines.
Helps traders identify premium/discount zones within the previous 4H range.
4. Vertical 4H Time Markers
Draws vertical dashed lines to mark the start and end of the last 4H candle range.
Based on the standard 4H bar timing in NY (e.g. 5:00, 9:00, 13:00, 17:00).
⚙️ Inputs & Options
Line thickness, color customization for all levels.
Option to place labels on the right or left side of the chart.
Toggle for enabling/disabling the 4H box.
Adjustable box extension length (how far to extend the range visually).
✅ Ideal Use Cases
Identifying reaction zones from prior highs/lows.
Spotting reversals during Asia or NY session opens.
Trading intraday setups based on 4H structure.
Anchoring scalping or swing entries off major session levels.
Combined ATPC & MACD DivergenceTrend Optimizer + Divergence Finder in One Unified Tool
🔍 Overview:
This powerful dual-system indicator merges two proven analytical engines:
✅ The Algorganic Typical Price Channel (ATPC) — a custom trend oscillator that highlights mean-reversion and directional bias.
✅ A refined MACD system with divergence detection, enhanced with an adjusted Donchian midline for real-time trend strength filtering.
Together, they provide a high-confidence, multi-signal system ideal for swing trading, scalping, or confirming reversals with context.
⚙️ Core Components & Logic
🧠 1. ATPC Engine (Trend Commodity Index)
A momentum and volatility-normalized oscillator based on the typical price (H+L+C)/3:
TrendCI Line (Blue) – Main trend signal based on smoothed CCI logic.
TrendLine2 (Orange) – A slower smoothing of TrendCI for crossovers.
Key Zones (customizable):
🔴 Ultra Overbought: +73
🟣 Overbought: +58
🟣 Oversold: -58
🔴 Ultra Oversold: -73
Trade Logic:
✅ Buy Signal: TrendCI crosses above TrendLine2 while in oversold zone
❌ Sell Signal: TrendCI crosses below TrendLine2 while in overbought zone
Additional visual feedback:
Histogram Bars show strength and direction of momentum shift
Green/Red Circles highlight potential long/short setups
📉 2. MACD System + Divergence Finder
Classic MACD enhanced with a Donchian Midline overlay to filter trend bias.
🔷 MACD Line and 🟠 Signal Line show crossover momentum
🟩/🟥 Histogram shows distance from the signal line
🟪 Adjusted Donchian Midline dynamically adapts to range-bound vs trending environments
Background Color provides real-time trend state:
✅ Green = Bullish Trend
❌ Red = Bearish Trend
No color = Neutral / Choppy
MACD Boundaries (user-defined):
Overbought: +1.0
Oversold: -1.0
🔀 3. Divergence Detection
Spot hidden power shifts before price reacts:
🔼 Positive Divergence – Price makes lower lows, but MACD histogram rises
🔽 Negative Divergence – Price makes higher highs, but MACD histogram weakens
These are visually marked with:
Green “+Div” label (bullish reversal cue)
Red “–Div” label (bearish exhaustion signal)
🎯 How to Use It
For Trend Traders:
Stay in sync with macro trend using MACD histogram + background
Use ATPC crossovers for precision entries
Avoid signals during neutral background (chop filter)
For Reversal Traders:
Look for bullish +Div with ATPC buy signal in oversold zone
Look for bearish –Div with ATPC sell signal in overbought zone
Mid-Donchian line can act as confluence or breakout trigger
For Scalpers & Intraday Traders:
Combine with VWAP, liquidity zones, or order flow levels
ATPC crossovers + MACD histogram zero-line flip = potential scalp entry
Use histogram slope and divergence to avoid false momentum traps
🧩 Customizable Inputs
🎛️ ATPC: Channel & Smoothing lengths, overbought/oversold thresholds
🎛️ MACD: Fast/slow EMAs, signal smoothing, Donchian period, bounds
🎨 Fully theme-compatible with adjustable colors and line styles
🔔 Alerts (Add Your Own)
While this version doesn’t contain built-in alerts, you can easily add alerts based on:
buySignal or sellSignal from ATPC logic
Histogram cross zero or trend flip
MACD Divergence event
📜 “This indicator doesn't just show signals—it tells a story about who’s in control of the market, and when that control might be slipping.”
