Uptrick: Fusion Trend Reversion SystemOverview
The Uptrick: Fusion Trend Reversion System is a multi-layered indicator designed to identify potential price reversals during intraday movement while keeping traders informed of the dominant short-term trend. It blends a composite fair value model with deviation logic and a refined momentum filter using the Relative Strength Index (RSI). This tool was created with scalpers and short-term traders in mind and is especially effective on lower timeframes such as 1-minute, 5-minute, and 15-minute charts where price dislocations and quick momentum shifts are frequent.
Introduction
This indicator is built around the fusion of two classic concepts in technical trading: identifying trend direction and spotting potential reversion points. These are often handled separately, but this system merges them into one process. It starts by computing a fair value price using five moving averages, each with its own mathematical structure and strengths. These include the exponential moving average (EMA), which gives more weight to recent data; the simple moving average (SMA), which gives equal weight to all periods; the weighted moving average (WMA), which progressively increases weight with recency; the Arnaud Legoux moving average (ALMA), known for smoothing without lag; and the volume-weighted average price (VWAP), which factors in volume at each price level.
All five are averaged into a single value — the raw fusion line. This fusion acts as a dynamically balanced centerline that adapts to price conditions with both smoothing and responsiveness. Two additional exponential moving averages are applied to the raw fusion line. One is slower, giving a stable trend reference, and the other is faster, used to define momentum and cloud behavior. These two lines — the fusion slow and fusion fast — form the backbone of trend and signal logic.
Purpose
This system is meant for traders who want to trade reversals without losing sight of the underlying directional bias. Many reversal indicators fail because they act too early or signal too frequently in choppy markets. This script filters out noise through two conditions: price deviation and RSI confirmation. Reversion trades are considered only when the price moves a significant distance from fair value and RSI suggests a legitimate shift in momentum. That filtering process gives the trader a cleaner, higher-quality signal and reduces false entries.
The indicator also visually supports the trader through colored bars, up/down labels, and a filled cloud between the fast and slow fusion lines. These features make the market context immediately visible: whether the trend is up or down, whether a reversal just occurred, and whether price is currently in a high-risk reversion zone.
Originality and Uniqueness
What makes this script different from most reversal systems is the way it combines layers of logic — not just to detect signals, but to qualify and structure them. Rather than relying on a single MA or a raw RSI level, it uses a five-MA fusion to create a baseline fair value that incorporates speed, stability, and volume-awareness.
On top of that, the system introduces a dual-smoothing mechanism. It doesn’t just smooth price once — it creates two layers: one to follow the general trend and another to track faster deviations. This structure lets the script distinguish between continuation moves and possible turning points more effectively than a single-line or single-metric system.
It also uses RSI in a more refined way. Instead of just checking if RSI is overbought or oversold, the script smooths RSI and requires directional confirmation. Beyond that, it includes signal memory. Once a signal is generated, a new one will not appear unless the RSI becomes even more extreme and curls back again. This memory-based gating reduces signal clutter and prevents repetition, a rare feature in similar scripts.
Why these indicators were merged
Each moving average in the fusion serves a specific role. EMA reacts quickly to recent price changes and is often favored in fast-trading strategies. SMA acts as a long-term filter and smooths erratic behavior. WMA blends responsiveness with smoothing in a more balanced way. ALMA focuses on minimizing lag without losing detail, which is helpful in fast markets. VWAP anchors price to real trade volume, giving a sense of where actual positioning is happening.
By combining all five, the script creates a fair value model that doesn’t lean too heavily on one logic type. This fusion is then smoothed into two separate EMAs: one slower (trend layer), one faster (signal layer). The difference between these forms the basis of the trend cloud, which can be toggled on or off visually.
RSI is then used to confirm whether price is reversing with enough force to warrant a trade. The RSI is calculated over a 14-period window and smoothed with a 7-period EMA. The reason for smoothing RSI is to cut down on noise and avoid reacting to short, insignificant spikes. A signal is only considered if price is stretched away from the trend line and the smoothed RSI is in a reversal state — below 30 and rising for bullish setups, above 70 and falling for bearish ones.
Calculations
The script follows this structure:
Calculate EMA, SMA, WMA, ALMA, and VWAP using the same base length
Average the five values to form the raw fusion line
Smooth the raw fusion line with an EMA using sens1 to create the fusion slow line
Smooth the raw fusion line with another EMA using sens2 to create the fusion fast line
If fusion slow is rising and price is above it, trend is bullish
If fusion slow is falling and price is below it, trend is bearish
Calculate RSI over 14 periods
Smooth RSI using a 7-period EMA
Determine deviation as the absolute difference between current price and fusion slow
A raw signal is flagged if deviation exceeds the threshold
A raw signal is flagged if RSI EMA is under 30 and rising (bullish setup)
A raw signal is flagged if RSI EMA is over 70 and falling (bearish setup)
A final signal is confirmed for a bullish setup if RSI EMA is lower than the last bullish signal’s RSI
A final signal is confirmed for a bearish setup if RSI EMA is higher than the last bearish signal’s RSI
Reset the bullish RSI memory if RSI EMA rises above 30
Reset the bearish RSI memory if RSI EMA falls below 70
Store last signal direction and use it for optional bar coloring
Draw the trend cloud between fusion fast and fusion slow using fill()
Show signal labels only if showSignals is enabled
Bar and candle colors reflect either trend slope or last signal direction depending on mode selected
How it works
Once the script is loaded, it builds a fusion line by averaging five different types of moving averages. That line is smoothed twice into a fast and slow version. These two fusion lines form the structure for identifying trend direction and signal areas.
Trend bias is defined by the slope of the slow line. If the slow line is rising and price is above it, the market is considered bullish. If the slow line is falling and price is below it, it’s considered bearish.
Meanwhile, the script monitors how far price has moved from that slow line. If price is stretched beyond a certain distance (set by the threshold), and RSI confirms that momentum is reversing, a raw reversion signal is created. But the script only allows that signal to show if RSI has moved further into oversold or overbought territory than it did at the last signal. This blocks repetitive, weak entries. The memory is cleared only if RSI exits the zone — above 30 for bullish, below 70 for bearish.
Once a signal is accepted, a label is drawn. If the signal toggle is off, no label will be shown regardless of conditions. Bar colors are controlled separately — you can color them based on trend slope or last signal, depending on your selected mode.
Inputs
You can adjust the following settings:
MA Length: Sets the period for all moving averages used in the fusion.
Show Reversion Signals: Turns on the plotting of “Up” and “Down” labels when a reversal is confirmed.
Bar Coloring: Enables or disables colored bars based on trend or signal direction.
Show Trend Cloud: Fills the space between the fusion fast and slow lines to reflect trend bias.
Bar Color Mode: Lets you choose whether bars follow trend logic or last signal direction.
Sens 1: Smoothing speed for the slow fusion line — higher values = slower trend.
Sens 2: Smoothing speed for the fast line — lower values = faster signal response.
Deviation Threshold: Minimum distance price must move from fair value to trigger a signal check.
Features
This indicator offers:
A composite fair value model using five moving average types.
Dual smoothing system with user-defined sensitivity.
Slope-based trend definition tied to price position.
Deviation-triggered signal logic filtered by RSI reversal.
RSI memory system that blocks repetitive signals and resets only when RSI exits overbought or oversold zones.
Real-time tracking of the last signal’s direction for optional bar coloring.
Up/Down labels at signal points, visible only when enabled.
Optional trend cloud between fusion layers, visualizing current market bias.
Full user control over smoothing, threshold, color modes, and visibility.
Conclusion
The Fusion Trend-Reversion System is a tool for short-term traders looking to fade price extremes without ignoring trend bias. It calculates fair value using five diverse moving averages, smooths this into two dynamic layers, and applies strict reversal logic based on RSI deviation and momentum strength. Signals are triggered only when price is stretched and momentum confirms it with increasingly strong behavior. This combination makes the tool suitable for scalping, intraday entries, and fast market environments where precision matters.
Disclaimer
This indicator is for informational and educational purposes only. It does not constitute financial advice. All trading involves risk, and no tool can predict market behavior with certainty. Use proper risk management and do your own research before making trading decisions.
Komut dosyalarını "bear" için ara
PulseWave + DivergenceOverview
PulseWave + Divergence is a momentum oscillator designed to optimize the classic RSI. Unlike traditional RSI, which can produce delayed or noisy signals, PulseWave offers a smoother and faster oscillator line that better responds to changes in market dynamics. By using a formula based on the difference between RSI and its moving average, the indicator generates fewer false signals, making it a suitable tool for day traders and swing traders in stock, forex, and cryptocurrency markets.
How It Works
Generating the Oscillator Line
The PulseWave oscillator line is calculated as follows:
RSI is calculated based on the selected data source (default: close price) and RSI length (default: 20 periods).
RSI is smoothed using a simple moving average (MA) with a selected length (default: 20 periods).
The oscillator value is the difference between the current RSI and its moving average: oscillator = RSI - MA(RSI).
This approach ensures high responsiveness to short-term momentum changes while reducing market noise. Unlike other oscillators, such as standard RSI or MACD, which rely on direct price values or more complex formulas, PulseWave focuses on the dynamics of the difference between RSI and its moving average. This allows it to better capture short-term trend changes while minimizing the impact of random price fluctuations. The oscillator line fluctuates around zero, making it easy to identify bullish trends (positive values) and bearish trends (negative values).
Divergences
The indicator optionally detects bullish and bearish divergences by comparing price extremes (swing highs/lows) with oscillator extremes within a defined pivot window (default: 5 candles left and right). Divergences are marked with "Bull" (bullish) and "Bear" (bearish) labels on the oscillator chart.
Signals
Depending on the selected signal type, PulseWave generates buy and sell signals based on:
Crosses of the overbought and oversold levels.
Crosses of the oscillator’s zero line.
A combination of both (option "Both").
Signals are displayed as triangles above or below the oscillator, making them easy to identify.
Input Parameters
RSI Length: Length of the RSI used in calculations (default: 20).
RSI MA Length: Length of the RSI moving average (default: 20).
Overbought/Oversold Level: Oscillator overbought and oversold levels (default: 12.0 and -12.0).
Pivot Length: Number of candles used to detect extremes for divergences (default: 5).
Signal Type: Type of signals to display ("Overbought/Oversold", "Zero Line", "Both", or "None").
Colors and Gradients: Full customization of line, gradient, and label colors.
How to Use
Adjust Parameters:
Increase RSI Length (e.g., to 30) for high-volatility markets to reduce noise.
Decrease Pivot Length (e.g., to 3) for faster divergence detection on short timeframes.
Interpret Signals:
Buy Signal: The oscillator crosses above the oversold level or zero line, especially with a bullish divergence.
Sell Signal: The oscillator crosses below the overbought level or zero line, especially with a bearish divergence.
Combine with Other Tools:
Use PulseWave alongside moving averages or support/resistance levels to confirm signals.
Monitor Divergences:
"Bull" and "Bear" labels indicate potential trend reversals. Set up alerts to receive notifications for divergences.
Contrarian 100 MAPairs nicely with Enhanced-Stock-Ticker-with-50MA-vs-200MA located here:
Description
The Contrarian 100 MA is a sophisticated Pine Script v6 indicator designed for traders seeking to identify key market structure shifts and trend reversals using a combination of a 100-period Simple Moving Average (SMA) envelope and Inner Circle Trader (ICT) Break of Structure (BoS) and Market Structure Shift (MSS) logic. By overlaying a semi-transparent SMA-based shadow on the price chart and plotting bullish and bearish structure signals, this indicator helps traders visualize critical price levels and potential trend changes. It leverages higher timeframe (HTF) pivot points and dynamic logic to adapt to various chart timeframes, making it ideal for swing and contrarian trading strategies. Customizable colors, timeframes, and alert conditions enhance its versatility for manual and automated trading setups.
Key Features
SMA Envelope: Plots a 100-period SMA for high and low prices, creating a semi-transparent (50% opacity) purple shadow to highlight the price range and provide context for price movements.
ICT BoS/MSS Logic: Identifies Break of Structure (BoS) and Market Structure Shift (MSS) signals for both bullish and bearish conditions, based on HTF pivot points.
Dynamic Timeframe Support: Adjusts pivot detection based on user-selected HTF (default: 1D) and chart timeframe (1M, 5M, 15M, 30M, 1H, 4H, 1D), ensuring adaptability across markets.
Visual Signals: Draws dotted lines for BoS (bullish/bearish) and MSS (bullish/bearish) signals at pivot levels, with customizable colors for easy identification.
Contrarian Approach: Signals potential reversals by combining SMA context with ICT structure breaks, ideal for traders looking to capitalize on trend shifts.
Alert Conditions: Supports alerts for bullish/bearish BoS and MSS signals, enabling integration with TradingView’s alert system for automated trading.
Performance Optimization: Uses efficient pivot detection and line management to minimize resource usage while maintaining accuracy.
Technical Details
SMA Calculation:
Computes 100-period SMAs for high (smaHigh) and low (smaLow) prices.
Plots invisible SMAs (fully transparent) and fills the area between them with 50% transparent purple for visual context.
Pivot Detection:
Uses ta.pivothigh and ta.pivotlow to identify HTF swing points, with dynamic lookback periods (rlBars: 5 for daily, 2 for intraday).
Tracks pivot highs (pH, nPh) and lows (pL, nPl) using a custom piv type for price and time.
BoS/MSS Logic:
Bullish BoS: Triggered when price breaks above a pivot high in a bullish trend, drawing a line at the pivot level.
Bearish BoS: Triggered when price breaks below a pivot low in a bearish trend.
Bullish MSS: Occurs when price breaks a pivot high in a bearish trend, signaling a potential trend reversal.
Bearish MSS: Occurs when price breaks a pivot low in a bullish trend.
Lines are drawn using line.new with xloc.bar_time for precise alignment, styled as dotted with customizable colors.
HTF Integration: Fetches HTF close prices and pivot data using request.security with lookahead_on for accurate signal timing.
Line Management: Maintains an array of lines (lin), removing outdated lines when new MSS signals occur to keep the chart clean.
Pivot Reset: Clears broken pivots (e.g., when price exceeds a pivot high or falls below a pivot low) to ensure fresh signal generation.
How to Use
Add to Chart:
Copy the script into TradingView’s Pine Editor and apply it to your chart.
Configure Settings:
SMA Length: Adjust the SMA period (default: 100 bars) to suit your trading style.
Structure Timeframe: Set the HTF for pivot detection (default: 1D).
Chart Timeframe: Select the chart timeframe (1M, 5M, 15M, 30M, 1H, 4H, 1D) to adjust pivot sensitivity.
Colors: Customize bullish/bearish BoS and MSS line colors via input settings.
Interpret Signals:
Bullish BoS: White dotted line (default) at a broken pivot high in a bullish trend, indicating trend continuation.
Bearish BoS: White dotted line at a broken pivot low in a bearish trend.
Bullish MSS: White dotted line at a broken pivot high in a bearish trend, suggesting a reversal to bullish.
Bearish MSS: White dotted line at a broken pivot low in a bullish trend, suggesting a reversal to bearish.
Use the SMA shadow to gauge price position within the recent range.
Set Alerts:
Create alerts for bullish/bearish BoS and MSS signals using TradingView’s alert system.
Customize Visuals:
Adjust line colors or SMA fill transparency via TradingView’s settings for better visibility.
Example Use Cases
Swing Trading: Use MSS signals to enter trades at potential trend reversals, with the SMA envelope confirming price extremes.
Contrarian Trading: Capitalize on BoS and MSS signals to trade against prevailing trends, using the SMA shadow for context.
Automated Trading: Integrate BoS/MSS alerts with trading bots for systematic entries and exits.
Multi-Timeframe Analysis: Combine HTF signals (e.g., 1D) with lower timeframe charts (e.g., 1H) for precise entries.
Notes
Testing: Backtest the indicator on your chosen market and timeframe to validate performance.
Compatibility: Built for Pine Script v6 and tested on TradingView as of June 19, 2025.
Limitations: Signals rely on HTF pivot accuracy, which may lag in fast-moving markets. Adjust rlBars or timeframe for sensitivity.
Optional Enhancements: Consider uncommenting or adding a histogram for SMA divergence (e.g., smaHigh - smaLow) for additional insights.
Acknowledgments
This indicator combines ICT’s market structure concepts with a dynamic SMA envelope to provide a unique contrarian trading tool. Share your feedback or suggestions in the TradingView comments, and happy trading!
SuperTrend Adaptive (STD Smooth)Supertrend Adaptive (Smoothed StdDev)
Supertrend Adaptive is a refined trend-following indicator based on the classic Supertrend. It enhances the original by incorporating smoothed standard deviation into the volatility calculation, instead of relying solely on ATR. This hybrid approach enables more responsive and adaptive trend detection, reducing noise and false signals in volatile or ranging markets. The indicator also features confidence-weighted signal labels and a clean, uncluttered display, making it practical for any trading timeframe.
🔍 Detailed Methodology and Conceptual Foundation
Unlike traditional Supertrend indicators that use only absolute volatility (ATR) to define trend bands, this version blends standard deviation — a relative volatility measure — into the calculation. Standard deviation helps capture the dispersion of price, not just its range, and when smoothed, it filters out erratic jumps caused by sudden spikes or drops.
This fusion creates trend bands that expand and contract dynamically based on recent price variability. As a result:
Fewer whipsaws : The trend bands adjust to both low and high volatility environments, which helps avoid unnecessary signal flips during consolidation.
Stronger trend adherence : Signals are less reactive to momentary price movements. This allows the indicator to hold positions longer in trending markets, giving traders the opportunity to ride extended moves.
Bollinger Band-style adaptation : By including standard deviation, this indicator behaves similarly to Bollinger Bands — accounting for relative price change rather than absolute moves alone.
These enhancements make the tool suitable not only for identifying directional bias, but also for refining entries and exits with more context-aware volatility filtering.
📈 How to Use the Indicator
Trend Direction: The script draws a colored line beneath (uptrend) or above (downtrend) price. Green indicates bullish trend, red indicates bearish.
Buy/Sell Labels: Only the most recent signal is shown to reduce clutter:
🟢 Green "Buy" label = trend reversal to bullish, with strong confidence.
🔵 Blue "Buy" label = same reversal, but with lower volume confidence.
🔴 Red "Sell" label = trend reversal to bearish, with strong confidence.
🟠 Orange "Sell" label = bearish signal with lower volume confidence.
These color codes are derived from comparing current volume to its average — a higher-than-average volume gives greater confidence to the signal.
Settings:
ATR Period: Controls the smoothing window for volatility calculation.
ATR Multiplier: Adjusts the size of the trend bands.
Std Smooth: Controls smoothing applied to standard deviation to reduce jitter.
Change ATR Method: Option to toggle between default and smoothed ATR.
Show Signals: Toggle for label display.
📢 Alerts
The script includes three built-in alert conditions:
Buy Signal: Triggered when the trend flips to bullish.
Sell Signal: Triggered when the trend flips to bearish.
Trend Direction Change: Alerts on any switch in trend regardless of confidence level.
These alerts allow traders to automate notifications or integrations with bots or trading platforms.
🧼 Clean Chart Display
To ensure clarity and comply with best practices:
The chart shows only this indicator.
Trend lines are drawn in real time for visual context.
Only one label per direction is shown — the most recent one — to keep the chart readable.
No drawings or unrelated indicators are included.
This setup ensures the script’s signals and structure are immediately understandable at a glance.
📌 Best Use Cases
This tool is designed for:
Traders who want adaptive volatility filters instead of rigid ATR-based models.
Scalpers and swing traders who prefer clean charts with minimal lag and fewer false signals.
Any asset class — works well on crypto, FX, and equities.
Shortcoming of this tool is sideway price action (will be tackled in next versions).
Credit for www.tradingview.com the version which this script extends.
MACD Breakout SuperCandlesMACD Breakout SuperCandles
The MACD Breakout SuperCandles indicator is a candle-coloring tool that monitors trend alignment across multiple timeframes using a combination of MACD behavior and simple price structure. It visually reflects market sentiment directly on price candles, helping traders quickly recognize shifting momentum conditions.
How It Works
The script evaluates trend behavior based on:
- Multi-timeframe MACD Analysis: Uses MACD values and signal line relationships to gauge trend direction and strength.
- Price Relative to SMA Zones: Analyzes whether price is positioned above or below the 20-period high and low SMAs on each timeframe.
For each timeframe, the script assigns one of five possible trend statuses:
- SUPERBULL: Strong bullish MACD signal with price above both SMAs.
- Bullish: Bullish MACD crossover with price showing upward bias.
- Basing: MACD flattening or neutralizing near zero with no directional dominance.
- Bearish: Bearish MACD signal without confirmation of stronger trend.
- SUPERBEAR: Strong bearish MACD signal with price below both SMAs.
-Ghost Candles: Candles with basing attributes that can signal directional change or trend strength.
Signal Scoring System
The script compares conditions across four timeframes:
- TF1 (Short)
- TF2 (Medium)
- TF3 (Long)
- MACD at a fixed 10-minute resolution
Each status type is tracked independently. A colored candle is only applied when a status type (e.g., SUPERBULL) reaches the minimum match threshold, defined by the "Min Status Matches for Candle Color" setting. If no status meets the required threshold, the candle is displayed in a neutral "Ghost" color.
Customizable Visuals
The indicator offers full control over candle appearance via grouped settings:
Body Colors
- SUPERBULL Body
- Bullish Body
- Basing Body
- Bearish Body
- SUPERBEAR Body
- Ghost Candle Body (used when no match)
Border & Wick Colors
- SUPERBULL Border/Wick
- Bullish Border/Wick
- Basing Border/Wick
- Bearish Border/Wick
- SUPERBEAR Border/Wick
- Ghost Border/Wick
Colors are grouped by function and can be adjusted independently to match your chart theme or personal preferences.
Settings Overview
- TF1, TF2, TF3: Select short, medium, and long timeframes to monitor trend structure.
- Min Status Matches: Set how many timeframes must agree before a candle status is applied.
- MACD Settings: Customize MACD fast, slow, and signal lengths, and choose MA type (EMA, SMA, WMA).
This tool helps visualize how aligned various timeframe conditions are by embedding sentiment into the candles themselves. It can assist with trend identification, momentum confirmation, or visual filtering for discretionary strategies.
Magnificent 7 OscillatorThe Magnificent 7 Oscillator is a sophisticated momentum-based technical indicator designed to analyze the collective performance of the seven largest technology companies in the U.S. stock market (Apple, Microsoft, Alphabet, Amazon, NVIDIA, Tesla, and Meta). This indicator incorporates established momentum factor research and provides three distinct analytical modes: absolute momentum tracking, equal-weighted market comparison, and relative performance analysis. The tool integrates five different oscillator methodologies and includes advanced breadth analysis capabilities.
Theoretical Foundation
Momentum Factor Research
The indicator's foundation rests on seminal momentum research in financial markets. Jegadeesh and Titman (1993) demonstrated that stocks with strong price performance over 3-12 month periods tend to continue outperforming in subsequent periods¹. This momentum effect was later incorporated into formal factor models by Carhart (1997), who extended the Fama-French three-factor model to include a momentum factor (UMD - Up Minus Down)².
The momentum calculation methodology follows the academic standard:
Momentum(t) = / P(t-n) × 100
Where P(t) is the current price and n is the lookback period.
The focus on the "Magnificent 7" stocks reflects the increasing market concentration observed in recent years. Fama and French (2015) noted that a small number of large-cap stocks can drive significant market movements due to their substantial index weights³. The combined market capitalization of these seven companies often exceeds 25% of the total S&P 500, making their collective momentum a critical market indicator.
Indicator Architecture
Core Components
1. Data Collection and Processing
The indicator employs robust data collection with error handling for missing or invalid security data. Each stock's momentum is calculated independently using the specified lookback period (default: 14 periods).
2. Composite Oscillator Calculation
Following Fama-French factor construction methodology, the indicator offers two weighting schemes:
- Equal Weight: Each active stock receives identical weighting (1/n)
- Market Cap Weight: Reserved for future enhancement
3. Oscillator Transformation Functions
The indicator provides five distinct oscillator types, each with established technical analysis foundations:
a) Momentum Oscillator (Default)
- Pure rate-of-change calculation
- Centered around zero
- Direct implementation of Jegadeesh & Titman methodology
b) RSI (Relative Strength Index)
- Wilder's (1978) relative strength methodology
- Transformed to center around zero for consistency
- Scale: -50 to +50
c) Stochastic Oscillator
- George Lane's %K methodology
- Measures current position within recent range
- Transformed to center around zero
d) Williams %R
- Larry Williams' range-based oscillator
- Inverse stochastic calculation
- Adjusted for zero-centered display
e) CCI (Commodity Channel Index)
- Donald Lambert's mean reversion indicator
- Measures deviation from moving average
- Scaled for optimal visualization
Operational Modes
Mode 1: Magnificent 7 Analysis
Tracks the collective momentum of the seven constituent stocks. This mode is optimal for:
- Technology sector analysis
- Growth stock momentum assessment
- Large-cap performance tracking
Mode 2: S&P 500 Equal Weight Comparison
Analyzes momentum using an equal-weighted S&P 500 reference (typically RSP ETF). This mode provides:
- Broader market momentum context
- Size-neutral market analysis
- Comparison baseline for relative performance
Mode 3: Relative Performance Analysis
Calculates the momentum differential between Magnificent 7 and S&P 500 Equal Weight. This mode enables:
- Sector rotation analysis
- Style factor assessment (Growth vs. Value)
- Relative strength identification
Formula: Relative Performance = MAG7_Momentum - SP500EW_Momentum
Signal Generation and Thresholds
Signal Classification
The indicator generates three signal states:
- Bullish: Oscillator > Upper Threshold (default: +2.0%)
- Bearish: Oscillator < Lower Threshold (default: -2.0%)
- Neutral: Oscillator between thresholds
Relative Performance Signals
In relative performance mode, specialized thresholds apply:
- Outperformance: Relative momentum > +1.0%
- Underperformance: Relative momentum < -1.0%
Alert System
Comprehensive alert conditions include:
- Threshold crossovers (bullish/bearish signals)
- Zero-line crosses (momentum direction changes)
- Relative performance shifts
- Breadth Analysis Component
The indicator incorporates market breadth analysis, calculating the percentage of constituent stocks with positive momentum. This feature provides insights into:
- Strong Breadth (>60%): Broad-based momentum
- Weak Breadth (<40%): Narrow momentum leadership
- Mixed Breadth (40-60%): Neutral momentum distribution
Visual Design and User Interface
Theme-Adaptive Display
The indicator automatically adjusts color schemes for dark and light chart themes, ensuring optimal visibility across different user preferences.
Professional Data Table
A comprehensive data table displays:
- Current oscillator value and percentage
- Active mode and oscillator type
- Signal status and strength
- Component breakdowns (in relative performance mode)
- Breadth percentage
- Active threshold levels
Custom Color Options
Users can override default colors with custom selections for:
- Neutral conditions (default: Material Blue)
- Bullish signals (default: Material Green)
- Bearish signals (default: Material Red)
Practical Applications
Portfolio Management
- Sector Allocation: Use relative performance mode to time technology sector exposure
- Risk Management: Monitor breadth deterioration as early warning signal
- Entry/Exit Timing: Utilize threshold crossovers for position sizing decisions
Market Analysis
- Trend Identification: Zero-line crosses indicate momentum regime changes
- Divergence Analysis: Compare MAG7 performance against broader market
- Volatility Assessment: Oscillator range and frequency provide volatility insights
Strategy Development
- Factor Timing: Implement growth factor timing strategies
- Momentum Strategies: Develop systematic momentum-based approaches
- Risk Parity: Use breadth metrics for risk-adjusted portfolio construction
Configuration Guidelines
Parameter Selection
- Momentum Period (5-100): Shorter periods (5-20) for tactical analysis, longer periods (50-100) for strategic assessment
- Smoothing Period (1-50): Higher values reduce noise but increase lag
- Thresholds: Adjust based on historical volatility and strategy requirements
Timeframe Considerations
- Daily Charts: Optimal for swing trading and medium-term analysis
- Weekly Charts: Suitable for long-term trend analysis
- Intraday Charts: Useful for short-term tactical decisions
Limitations and Considerations
Market Concentration Risk
The indicator's focus on seven stocks creates concentration risk. During periods of significant rotation away from large-cap technology stocks, the indicator may not represent broader market conditions.
Momentum Persistence
While momentum effects are well-documented, they are not permanent. Jegadeesh and Titman (1993) noted momentum reversal effects over longer time horizons (2-5 years).
Correlation Dynamics
During market stress, correlations among the constituent stocks may increase, reducing the diversification benefits and potentially amplifying signal intensity.
Performance Metrics and Backtesting
The indicator includes hidden plots for comprehensive backtesting:
- Individual stock momentum values
- Composite breadth percentage
- S&P 500 Equal Weight momentum
- Relative performance calculations
These metrics enable quantitative strategy development and historical performance analysis.
References
¹Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance, 48(1), 65-91.
Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57-82.
Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
RSI Divergence StrategyOverview
The RSI Divergence Strategy Indicator is a trading tool that uses the RSI and divergences created to generate high-probability buy and sell signals.
I have provided the best formula of numbers to use for BTC on a 30 minute timeframe.
You can change where on RSI you enter and exit both long or short trades. This way you can experiment on different tokens using different entry/exit points. Can use on multiple timeframes.
This strategy is designed to open and close long or short trades based on the levels you provide it. You can then check on the RSI where the best levels are for each token you want to trade and amend it as required to generate a profitable strategy.
How It Works
The RSI Divergence Strategy Indicator uses bear and bull divergences in conjuction with a level you have input on the RSI.
RSI for Overbought/Oversold:
• Input variables for entry and exit levels and when the entry levels combine with a bear or bull divergence signal, a trade is alerted.
RSI Divergence:
• Buy and sell signals are confirmed when the RSI creates bearish or bullish divergences and these divergences are in the same area as your levels you input for entry to short or long.
After 7 years of experience and testing I have calculated the exact numbers required and produced a formula to calculate the exact input variables for a 30 minute Bitcoin chart.
Key Features
1️⃣ Divergence Identification – Ensures trades are taken only when a bull or bear divergence has formed.
2️⃣ Overbought/Oversold Input Filtering – Set up your own variables on the RSI for different markets after identifying patterns on the RSI in relation to a bearish or bullish divergence.
3️⃣ Works on any chart – Suitable for all markets and timeframes once you input the correct variables for entry and exit levels.
How to Use
🟢 Basic Trading:
• Use on any timeframe.
• Enter trade only when alert has fired off. Close when it says to exit.
• Change entry and exit levels in the properties of the strategy indicator.
• Make entry and exit levels coincide with bearish or bullish divergences on the RSI.
Check the strategy tester to see backtesting so you know if the indicator is profitable or not for that market and timeframe as each crypto token is different and so is the timeframe you choose.
📢 Webhook Automation:
• Set up TradingView Alerts to auto-execute trades via Webhook-compatible platforms.
Key additions for divergence visualization:
Divergence Arrows:
Bullish divergence: Green label with white 'bull ' text
Bearish divergence: Red label with white 'bear' text
Positioned at the pivot point
Divergence Lines:
Connects consecutive RSI pivot points
Automatically drawn between consecutive pivot points
Enhanced RSI Coloring:
Overbought zone: Red
Oversold zone: Green
Neutral zone: Gray
The visualization helps you instantly spot:
Where divergences are forming on the RSI
The pattern of higher lows (bullish) or lower highs (bearish)
Contextual coloring of RSI relative to standard levels
All divergence markers appear at the correct historical pivot points, making it easy to visually confirm divergence patterns as they develop.
Strategy levels and background zones also shown to help visual look.
Why This Combination?
This indicator is just a simple RSI tool.
It is designed to filter out weak trades and only execute trades that have:
✅ RSI Divergence
✅ Overbought or Oversold Conditions
It does not calculate downtrends or bear markets so care is recommended taking long trades during these times.
Why It’s Worth Using?
📈 Open Source – Free to use and learn from.
📉 Long or Short Term Trading Style – Entry/Exit parameters options are designed for both short or long term trades allowing you to experiment until you find a profitable strategy for that market you want to trade.
📢 Seamless Webhook Automation – Execute trades automatically with TradingView alerts.
💲 Ready to trade smarter?
✅ Add the RSI Divergence Strategy Indicator to your TradingView chart.
OptionHawk1. What makes the script original?
• Unique concept: It integrates a Keltner based custom supertrend with a multi-EMA energy visualization, ATR based multi target management, and on chart options (CALL/PUT) trade signals—creating a toolkit not found in typical public scripts.
• Innovative use: Instead of off the shelf indicators, it reinvents them:
• Keltner bands used as dynamic Supertrend triggers.
• Fifteen EMAs layered for “energy” zones (bullish/bearish heatmaps).
• ATR dynamically scales multi-TP levels and stop loss.
These are creatively fused into a unified signal and automation engine.
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2. What value does it provide to traders?
• Clear entries & exits: Labels for entry price/time, five TP levels, and SL structure eliminate guesswork.
• Visualization & automation: Real-time bar coloring and energy overlays allow quick momentum reads.
• Targeted to common pain points: Many traders struggle with manual TP/SL and entry timing—this automates that process.
• Ready for real use: Just plug into intraday (e.g., 5 min) or swing setups; no manual calculations. Signals are actionable out of the box.
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3. Why invite only (worth paying)?
• Proprietary fusion: Public indicators like Supertrend or EMA are common—but your layered use, ATR based scaling, and label logic are exclusive.
• Auto-generated options format: Unique labeling for CALL/PUT, with graphical on chart signals, isn’t offered freely elsewhere.
• Time-saver & edge-provider: Saves traders hours of configuration and enhances consistency—worth the subscription cost over piecing together mash ups.
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4. How does it work?
• Signal backbone: Custom supertrend uses Keltner bands crossing with close for direction, filtered by trend direction EMAs.
• Multi time logic: Trend defined by crossover of price over dynamic SMA thresholds built from ATR.
• Energy bar-colors/EMAs: 15 fast EMAs color-coded green/red to instantly show momentum.
• Entry logic: “Bull” when close crosses above supertrend; “Bear” when crosses below.
• Risk management: SL set at previous bar; up to 5 ATR scaled targets (or percentage based).
• Options formatted alerts: CALL/PUT labels with ₹¬currency values, embedded timestamp, SL/TP all printed on the chart.
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5. How should traders use it?
• Best markets & timeframes: Ideal for intraday / low timeframe (1 15m) setups and 1 hour swing trades in equities, indices, options.
• Conditions: Works best in trending or volatility driven sessions—visible via Keltner bands and EMA energy alignment.
• Recommended combo: Use alongside volume filters or broader cycles; when supertrend & energy EMAs align, validation is stronger.
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6. Proof of effectiveness?
• On chart visuals: Entry/exit labels, confirmed labels, TP and SL markers make past hits obvious.
• Real trade examples: Highlighted both bull & bear setups with full profit realization or SL hits.
• Performance is paint tested: Easy to showcase historic signals across multiple tickers.
• Data-backed: Users can export chart data to calculate win rate and avg return per trade.
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Summary Pitch:
OptionHawk offers a holistic, execution-ready trading tool:
1. Proprietary blend of Keltner-supertrend and layered EMAs—beyond standard scripts.
2. Automates entries, multi-tier targets, SL, and options-format labels.
3. Visual energy overlays for quick momentum readings.
4. Use-tested in intraday and swing markets.
5. Installs on chart and works immediately—no setup complexity.
It's not a public indicator package; it's a self-contained, plug and play trade catalyst—worth subscribing for active traders seeking clarity, speed, and structure in their decision-making.
6. While OptionHawk is designed for clarity and structure, no script can predict the market. Always use with discretion and proper risk management.
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OptionHawk: A Comprehensive Trend-Following & Volatility-Adaptive Trading System
The "OptionHawk" script is a sophisticated trading tool designed to provide clear, actionable signals for options trading by combining multiple technical indicators and custom logic. It aims to offer a holistic view of market conditions, identifying trend direction, momentum, and potential entry/exit points with dynamic stop-loss and take-profit levels.
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1. Why These Specific Indicators and Code Elements?
The "OptionHawk" script is a strategic fusion of the Supertrend indicator (modified with Keltner Channels), a multi-EMA "Energy" ribbon, dynamic trend lines (based on SMA and ATR), a 100-period Trend Filter EMA, and comprehensive trade management logic (SL/TP). My reason and motivation for this mashup stem from a desire to create a robust system that accounts for various market aspects often overlooked by individual indicators:
• Supertrend with Keltner Channels: The standard Supertrend is effective for trend identification but can sometimes generate whipsaws in volatile or ranging markets. By integrating Keltner Channels into the Supertrend calculation, the volatility measure becomes more adaptive, using the (high - low) range within the Keltner Channel for its ATR-like component. This aims to create a more responsive yet less prone-to-false-signals Supertrend.
• Multi-EMA "Energy" Ribbon: This visually striking element, composed of 15 EMAs, provides a quick glance at short-to-medium term momentum and potential support/resistance zones. When these EMAs are stacked and moving in one direction, it indicates strong "energy" behind the trend, reinforcing the signals from other indicators.
• Dynamic Trend Lines (SMA + ATR): These lines offer a visual representation of support and resistance that adapts to market volatility. Unlike static trend lines, their ATR-based offset ensures they remain relevant across different market conditions and asset classes, providing context for price action relative to the underlying trend.
• 100-Period Trend Filter EMA: A longer-period EMA acts as a higher-timeframe trend filter. This is crucial for confirming the direction identified by the faster-acting Supertrend, helping to avoid trades against the prevailing broader trend.
• Comprehensive Trade Management Logic: The script integrates automated calculation and display of stop-loss (SL) and multiple take-profit (TP) levels, along with trade confirmation and "TP Hit" labels. This is critical for practical trading, providing immediate, calculated risk-reward parameters that individual indicators typically don't offer.
This combination is driven by the need for a multi-faceted approach to trading that goes beyond simple signal generation to include trend confirmation, volatility adaptation, and essential risk management.
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2. What Problem or Need Does This Mashup Solve?
This mashup addresses several critical gaps that existing individual indicators often fail to fill:
• Reliable Trend Identification in Volatile Markets: While Supertrend is good, it can be late or whipsaw. Integrating Keltner Channels helps it adapt to changing volatility, providing more reliable trend signals.
• Confirmation of Signals: A common pitfall of relying on a single indicator is false signals. "OptionHawk" uses the multi-EMA "Energy" ribbon and the 100-period EMA to confirm the trend identified by the Keltner-Supertrend, reducing false entries.
• Dynamic Support/Resistance & Trend Context: Static support and resistance levels can quickly become irrelevant. The dynamic SMA + ATR trend lines provide continually adjusting zones that reflect the current market's true support and resistance, giving traders a better understanding of price action within the trend.
• Integrated Risk and Reward Management: Most indicators just give entry signals. This script goes a significant step further by automatically calculating and displaying clear stop-loss and up to five take-profit levels (either ATR-based or percentage-based). This is a vital component for structured trading, allowing traders to pre-define their risk and reward for each trade.
• Visual Clarity and Actionable Information: Instead of requiring traders to layer multiple indicators manually, "OptionHawk" integrates them into a single, cohesive display with intuitive bar coloring, shape plots, and informative labels. This reduces cognitive load and presents actionable information directly on the chart.
In essence, "OptionHawk" provides a more comprehensive, adaptive, and actionable trading framework than relying on isolated indicators.
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3. How Do the Components Work Together?
The various components of "OptionHawk" interact in a synergistic and often sequential manner to generate signals and manage trades:
• Keltner-Supertrend as the Primary Signal Generator: The supertrend function, enhanced by keltner_channel, is the core of the system. It identifies potential trend reversals and continuation signals (bullish/bearish crosses of the supertrendLine). The sensitivity and factor inputs directly influence how closely the Supertrend follows price and its responsiveness to volatility.
• Multi-EMA "Energy" Ribbon for Momentum and Confirmation: The 15 EMAs (from ema1 to ema15) are plotted to provide a visual representation of short-term momentum. When the price is above these EMAs and they are spread out and pointing upwards, it suggests strong bullish "energy." Conversely, when price is below them and they are pointing downwards, it indicates bearish "energy." This ribbon serves as a simultaneous visual confirmation for the Supertrend signals; a buy signal from Supertrend is stronger if the EMA ribbon is also indicating upward momentum.
• Dynamic Trend Lines for Context and Confirmation: The sma_high and sma_low lines, incorporating ATR, act as dynamic support and resistance. The trend variable, determined by price crossing these lines, provides an overarching directional bias. This component works conditionally with the Supertrend; a bullish Supertrend signal is more potent if the price is also above the sma_high (indicating an uptrend).
• 100-Period Trend Filter EMA for Macro Trend Confirmation: The ema100 acts as a macro trend filter. Supertrend signals are typically considered valid if they align with the direction of the ema100. For example, a "BUY" signal from the Keltner-Supertrend is ideally taken only if the price is also above the ema100, signifying that the smaller trend aligns with the larger trend. This is a conditional filter.
• Trade Confirmation and SL/TP Logic (Sequential and Conditional):
• Once a bull or bear signal is generated by the Keltner-Supertrend, the tradeSignalCall or tradeSignalPut is set to true.
• A confirmation step then occurs for a "BUY" signal, the script checks if the close of the next bar is higher than the entry bar's close. For a "SELL" signal, it checks if the close of the next bar is lower. This is a sequential confirmation step aimed at filtering out weak signals.
• Upon a confirmed signal, the stop-loss (SL) is immediately set based on the previous bar's low (for calls) or high (for puts).
• Multiple take-profit (TP) levels are calculated and stored in arrays. These can be based on a fixed percentage or dynamic ATR multiples, based on user input.
• The TP HIT logic continuously monitors price action simultaneously against these pre-defined target levels, displaying labels when a target is reached. The SL HIT logic similarly monitors for a stop-loss breach.
In summary, the Supertrend generates the initial signal, which is then confirmed by the dynamic trend lines and the 100-period EMA, and visually reinforced by the EMA "Energy" ribbon. The trade management logic then takes over, calculating and displaying vital risk-reward parameters.
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4. What is the Purpose of the Mashup Beyond Simply Merging Code?
The purpose of "OptionHawk" extends far beyond merely combining different indicator codes; it's about creating a structured and informed decision-making process for options trading. The key strategic insights and functionalities added by combining these elements are:
• Enhanced Signal Reliability and Reduced Noise: By requiring multiple indicators to align (e.g., Keltner-Supertrend signal confirmed by EMA trend filter and dynamic trend lines), the script aims to filter out false signals and whipsaws that commonly plague individual indicators. This leads to higher-probability trade setups.
• Adaptive Risk Management: The integration of ATR into both the Supertrend calculation and the dynamic stop-loss/take-profit levels makes the entire system adaptive to current market volatility. This means stop-losses and targets are not static but expand or contract with the market's price swings, promoting more realistic risk management.
• Clear Trade Entry and Exit Framework: The script provides a complete trading plan with each signal: a clear entry point, a precise stop-loss, and multiple cascading take-profit levels. This holistic approach empowers traders to manage their trades effectively from initiation to conclusion, rather than just identifying a potential entry.
• Visual Confirmation of Market Strength: The "Energy" ribbon and dynamic trend lines provide an immediate visual understanding of the market's momentum and underlying trend strength, helping traders gauge conviction behind a signal.
• Improved Backtesting and Analysis: By combining these elements into one script, traders can more easily backtest a comprehensive strategy rather than trying to manually combine signals from multiple overlaying indicators, leading to more accurate strategy analysis.
• Suitability for Options Trading: Options contracts are highly sensitive to price movement and volatility. This script's focus on confirmed trend identification, dynamic volatility adaptation, and precise risk management makes it particularly well-suited for the nuanced demands of options trading, where timing and defined risk are paramount.
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5. What New Functionality or Insight Does Your Script Offer?
"OptionHawk" offers several new functionalities and insights that significantly enhance decision-making, improve accuracy, and provide clearer signals and better timing for traders:
• "Smart" Supertrend: By basing the Supertrend's volatility component on the Keltner Channel's range instead of a simple ATR, the Supertrend becomes more sensitive to price action within its typical bounds while still adapting to broader market volatility. This can lead to earlier and more relevant trend change signals.
• Multi-Confirmation System: The script doesn't just provide a signal; it layers multiple confirmations (Keltner-Supertrend, multi-EMA "Energy" coloration, dynamic trend lines, and the 100-period EMA). This multi-layered validation significantly improves the accuracy of signals by reducing the likelihood of false positives.
• Automated and Dynamic Risk-Reward Display: This is a major functionality enhancement. The automatic calculation and clear display of stop-loss and five distinct take-profit levels (based on either ATR or percentage) directly on the chart, along with "TP HIT" and "SL HIT" labels, streamline the trading process. Traders no longer need to manually calculate these crucial levels, leading to enhanced decision-making and better risk management.
• Visual Trend "Energy" and Momentum: The vibrant coloring of the multi-EMA ribbon based on price relative to the EMA provides an intuitive and immediate visual cue for market momentum and "energy." This offers an insight into the strength of the current move, which isn't available from single EMA plots.
• Post-Signal Confirmation: The "Confirmation" label appearing on the bar after a signal, if the price continues in the signaled direction, adds an extra layer of real-time validation. This helps to improve signal timing by waiting for initial follow-through.
• Streamlined Options Trading Planning: For options traders, having clear entry prices, stop-losses, and multiple target levels directly annotated on the chart is invaluable. It helps in quickly assessing potential premium movements and managing positions effectively.
In essence, "OptionHawk" transitions from a collection of indicators to a semi-automated trading assistant, providing a comprehensive, visually rich, and dynamically adaptive framework for making more informed and disciplined trading decisions.
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Performance & Claims
1. What is the claimed performance of the script or strategy?
Answer: The script does not claim any specific performance metrics (e.g., win rate, profit factor, percentage gains). It's an indicator designed to identify potential buy/sell signals and target/stop-loss levels. The labels it generates ("BUY CALL," "BUY PUT," "TP HIT," "SL HIT") are informational based on its internal logic, not a representation of actual trading outcomes.
2. Is there any proof or backtesting to support this claim?
Answer: No, the provided code does not include any backtesting functionality or historical performance proof. As an indicator, it simply overlays visual signals on the chart. To obtain backtesting results, the logic would need to be implemented as a Pine Script strategy with entry/exit rules and commission/slippage considerations.
3. Are there any unrealistic or exaggerated performance expectations being made?
Answer: The script itself does not make any performance expectations. It avoids quantitative claims. However, if this script were presented to users with implied promises of profit based solely on the visual signals, that would be unrealistic.
4. Have you clearly stated the limitations of the performance data (e.g., “based on backtesting only”)?
Answer: There is no statement of performance data or its limitations because the script doesn't generate performance data.
5. Do you include a disclaimer that past results do not guarantee future performance?
Answer: No, the script does not include any disclaimers about past or future performance. This is typically found in accompanying documentation or marketing materials for a trading system, not within the indicator's code itself.
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Evidence & Transparency
6. How are your performance results measured (e.g., profit factor, win rate, Sharpe ratio)?
Answer: Performance results are not measured by this script. It's an indicator.
7. Are these results reproducible by others using the same script and settings?
Answer: The visual signals and calculated levels (Supertrend line, EMAs, target/SL levels) generated by the script are reproducible on TradingView when applied to the same instrument, timeframe, and with the same input settings. However, the actual trading results (profit/loss) are not generated or reproducible by this indicator.
8. Do you include enough data (charts, equity curves, trade logs) to support your claims?
Answer: No, the script does not include or generate equity curves or trade logs. It provides visual labels on the chart, which can be seen as a form of "data" to support the signal generation, but not the performance claims (as none are made by the code).
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Future Expectations
9. Are you making any predictions about future market performance?
Answer: No, the script does not make any explicit predictions about future market performance. Its signals are based on historical price action and indicator calculations.
10. Have you stated clearly that the future is fundamentally uncertain?
Answer: No, the script does not contain any statements about the uncertainty of the future.
11. Are forward-looking statements presented with caution and appropriate language?
Answer: The script does not contain any forward-looking statements beyond the visual signals it generates based on real-time data.
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Risk & Disclosure
12. Have you disclosed the risks associated with using your script or strategy?
Answer: No, the script does not include any risk disclosures. This is typically found in external documentation.
13. Do you explain that trading involves potential loss as well as gain?
Answer: No, the script does not contain any explanation about the potential for loss in trading.
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Honesty & Integrity
14. Have you avoided hype words like “guaranteed,” “foolproof,” or “no losses”?
Answer: Yes, the script itself avoids these hype words. The language used within the code is technical and describes the indicator's logic.
15. Is your language grounded and realistic rather than promotional?
Answer: Yes, the language within the provided Pine Script code is grounded and realistic as it pertains to the technical implementation of an indicator.
16. Are you leaving out any important details that might mislead users (e.g., selective performance snapshots)?
Answer: From the perspective of the code itself, no, it's not "leaving out" performance details because it's not designed to generate them. However, if this indicator were to be presented as a "strategy" that implies profitability without accompanying disclaimers, backtesting results, and risk disclosures, then that external presentation could be misleading. The script focuses on signal generation and visual representation.
⚠️ Disclaimer:
This indicator is for informational and educational purposes only. It does not guarantee any future results or performance. All trading involves risk. Please assess your own risk tolerance and consult a licensed financial advisor if needed. Past performance does not indicate future returns.
Uptrick: Mean ReversionOverview
Uptrick: Mean Reversion is a technical indicator designed to identify statistically significant reversal opportunities by monitoring market extremes. It presents a unified view of multiple analytical layers—momentum shifts, extreme zones, divergence patterns, and a multi-factor bias dashboard—within a single pane. By translating price momentum into a normalized framework, it highlights areas where prices are likely to revert to their average range.
Introduction
Uptrick: Mean Reversion relies on several core concepts:
Volatility normalization
The indicator rescales recent market momentum into a common scale so that extreme readings can be interpreted consistently across different assets and timeframes.
Mean reversion principle
Markets often oscillate around an average level. When values stray too far beyond typical ranges, a return toward the mean is likely. Uptrick: Mean Reversion detects when these extremes occur.
Momentum inflection
Sharp changes in momentum direction frequently presage turning points. The indicator watches for shifts from upward momentum to downward momentum (and vice versa) to help time entries and exits.
Divergence
When price trends and internal momentum readings move in opposite directions, it can signal weakening momentum and an impending reversal. Uptrick: Mean Reversion flags such divergence conditions directly on the indicator pane.
Multi-factor sentiment
No single metric tells the entire story. By combining several independent sentiment measures—price structure, momentum, oscillators, and external market context—Uptrick: Mean Reversion offers a more balanced view of overall market bias.
Purpose
Uptrick: Mean Reversion was created for traders who focus on countertrend opportunities rather than simply following established trends. Its main objectives are:
Spot extreme conditions
By normalizing momentum into a standardized scale, the indicator clearly marks when the market is in overbought or oversold territory. These conditions often align with points where a snapback toward average is more probable.
Provide reversal signals
Built-in logic detects when momentum shifts direction within extreme zones and displays clear buy or sell markers to guide countertrend entries and exits.
Highlight hidden divergences
Divergence between price and internal momentum can suggest underlying weakness or strength ahead of actual price moves. Uptrick: Mean Reversion plots these divergences directly, allowing traders to anticipate reversals earlier.
Offer contextual bias
A dynamic dashboard aggregates multiple independent indicators—based on recent price action, momentum readings, common oscillators, and broader market context—to produce a single sentiment label. This helps traders determine whether mean reversion signals align with or contradict overall market conditions.
Cater to lower timeframes
Mean reversion tends to occur more frequently and reliably on shorter timeframes (for example, 5-minute, 15-minute, or 1-hour charts). Uptrick: Mean Reversion is optimized for these nimble environments, where rapid reversals can be captured before a larger trend takes hold.
Originality and Uniqueness
Uptrick: Mean Reversion stands out for several reasons:
Proprietary normalization framework
Instead of relying on raw oscillator values, it transforms momentum into a standardized scale. This ensures that extreme readings carry consistent meaning across different assets and volatility regimes.
Inflection-based signals
The indicator waits for a clear shift in momentum direction within extreme zones before plotting reversal markers. This approach reduces false signals compared to methods that rely solely on fixed threshold crossings.
Embedded divergence logic
Divergence detection is handled entirely within the same pane. Rather than requiring a separate indicator window, Uptrick: Mean Reversion identifies instances where price and internal momentum readings do not align and signals those setups directly on the chart.
Adjustable sensitivity profiles
Traders can choose from predefined risk profiles—ranging from very conservative to very aggressive—to automatically adjust how extreme a reading must be before triggering a signal. This customization helps balance between capturing only the most significant reversals or generating more frequent, smaller opportunities.
Multi-factor bias dashboard
While many indicators focus on a single metric, Uptrick: Mean Reversion aggregates five distinct sentiment measures. By balancing price-based bias, momentum conditions, and broader market context, it offers a more nuanced view of when to take—or avoid—countertrend trades.
Why Indicators Were Merged
Proprietary momentum oscillator
A custom-built oscillator rescales recent price movement into a normalized range. This core component underpins all signal logic and divergence checks, allowing extreme readings to be identified consistently.
Inflection detection
By comparing recent momentum values over a configurable lookback interval, the indicator identifies clear shifts from rising to falling momentum (and vice versa). These inflection points serve as a prerequisite for reversal signals when combined with extreme conditions.
Divergence framework
Local peaks and troughs are identified within the normalized oscillator and compared to corresponding price highs and lows. When momentum peaks fail to follow price to new extremes (or vice versa), a divergence alert appears, suggesting weakening momentum ahead of a price turn.
Classic price bias
Recent bar structures are examined to infer whether the immediate past price action was predominantly bullish, bearish, or neutral. This provides one piece of the overall sentiment picture.
Smoothed oscillator bias
A secondary oscillator reading is smoothed and compared to a central midpoint to generate a simple bullish or bearish reading.
Range-based oscillator bias
A familiar range-bound oscillator is used to detect oversold or overbought readings, contributing to the sentiment score.
Classic momentum crossover bias
A traditional momentum check confirms whether momentum currently leans bullish or bearish.
External market trend bias
The indicator monitors a major currency’s short-term trend to gauge broader market risk appetite. A falling currency—often associated with higher risk tolerance—contributes a bullish bias point, while a rising currency adds a bearish point.
All these elements run concurrently. Each piece provides a “vote” toward an overall sentiment reading. At the same time, the proprietary momentum oscillator drives both extreme-zone detection and divergence identification. By merging these inputs, the final result is a single pane showing both precise reversal signals and a unified market bias.
How It Works
At runtime, the indicator proceeds through the following conceptual steps:
Read user inputs (risk profile, lookback index, visual mode, color scheme, background highlighting, bias table display, divergence toggles).
Fetch the latest price data.
Process recent price movement through a proprietary normalization engine to produce a single, standardized momentum reading for each bar.
Track momentum over a configurable lookback interval to detect shifts in direction.
Compare the current momentum reading to dynamically determined extreme thresholds (based on the chosen risk profile).
If momentum has flipped from down to up within an oversold area, display a discrete buy marker. If momentum flips from up to down within an overbought area, display a sell marker.
Identify local peaks and troughs in the proprietary momentum series and compare to price highs and lows over a configurable range. When divergence criteria are met, display bullish or bearish divergence labels
Evaluate five independent sentiment measures—price bar bias, smoothed oscillator bias, range oscillator bias, traditional momentum crossover bias, and an external market trend bias—and assign each a +1 (bullish), –1 (bearish), or 0 (neutral) vote.
Average the five votes to produce an overall sentiment score. If the average exceeds a positive threshold, label the bias as bullish; if it falls below a negative threshold, label it as bearish; otherwise label it neutral.
Update the on-screen bias table at regular intervals, showing each individual metric’s value and vote, as well as the combined sentiment label.
Apply color fills to highlight extreme zones in the background and draw horizontal guideline bands around those extremes.
In complex visual mode, draw a cloud-like band that instantly changes color when momentum shifts. In simple mode, plot only a clean line of the normalized reading in a contrasting color.
Expose alert triggers whenever a buy/sell signal, divergence confirmation, or bias flip occurs, for use in automated notifications.
Inputs
Here is how each input affects the indicator:
Trading Style (very conservative / conservative / neutral / aggressive / very aggressive)
Determines how sensitive the indicator is to extreme readings. Conservative settings require more pronounced market deviations before signaling a reversal; aggressive settings signal more frequently at smaller deviations.
Slope Detection Index (integer)
Controls how many bars back the indicator looks to compare momentum for inflection detection. Lower numbers respond more quickly but can be noisy; higher numbers smooth out short-term fluctuations.
Visual Mode (simple / complex)
Simple mode plots only the normalized momentum line, colored according to the chosen palette. Complex mode draws a candle-style block for each bar—showing the range of momentum movement within that bar—with colored fills that switch instantly when momentum direction changes.
Color Scheme (multiple themes)
Select from preset color palettes to style bullish vs. bearish elements (fills, lines, labels). Options include bright neon tones, classic contrasting pairs, dark-mode palettes, and more, ensuring signals stand out against any chart background.
Enable Background Highlighting (true / false)
When true, extreme overbought or oversold zones are shaded in a semi-transparent color behind the main pane. This helps traders “see” when the market is in a normalized extreme state without relying solely on lines or markers.
Show Helper Scale Lines (true / false)
When true, hidden horizontal lines force the vertical scale to include a fixed range of extreme values—even if the indicator rarely reaches them—so traders always know where the most extreme limits lie.
Enable Divergence Detection (true / false)
Toggles whether the script looks for divergences between price and the proprietary momentum reading. When enabled, bullish/bearish divergence markers appear automatically whenever defined conditions are met.
Pivot Lookback Left & Pivot Lookback Right (integers)
Define how many bars to the left and right the indicator examines when identifying a local peak or trough in the momentum reading. Adjust these to capture divergences on different swing lengths.
Minimum and Maximum Bars Between Pivots (integers)
Set the minimum and maximum number of bars allowed between two identified peaks or troughs for a valid divergence. This helps filter out insignificant or overly extended divergence patterns.
Show Bias Table (true / false)
When enabled, displays a small table in the upper-right corner summarizing five independent sentiment votes and the combined bias label. Disable to keep the pane focused on only the momentum series and signals.
Features
1. Extreme-zone highlighting
Overbought and oversold areas appear as colored backgrounds when the proprietary momentum reading crosses dynamically determined thresholds. This gives an immediate visual cue whenever the market moves into a highly extreme condition.
2. Discrete reversal markers
Whenever momentum shifts direction within an extreme zone, the indicator plots a concise “Buy” or “Sell” label directly on the normalized series. These signals combine both extreme-zone detection and inflection confirmation, reducing false triggers.
3. Dynamic divergence flags
Local peaks and troughs of the proprietary momentum reading are continuously compared to corresponding price points. Bullish divergence (momentum trough rising while price trough falls) and bearish divergence (momentum peak falling while price peak rises) are flagged with small labels and lines. These alerts help traders anticipate reversals before price charts show clear signals.
4. Multi-factor sentiment dashboard
Five independent “votes” are tallied each bar:
• Price bar bias (based on recent bar structure)
• Smoothed oscillator bias (based on a popular momentum oscillator)
• Range oscillator bias (based on an overbought/oversold oscillator)
• Traditional momentum crossover bias (whether momentum is above or below its own smoothing)
• External market trend bias (derived from a major currency index’s short-term trend)
Each vote is +1 (bullish), –1 (bearish), or 0 (neutral). The average of these votes produces an overall sentiment label (Bullish, Bearish, or Neutral). The table updates periodically, showing each metric’s value, its vote, and the combined bias.
5. Versatile visual modes
Simple mode: Plots a single normalized momentum line in a chosen color. Ideal for clean charts.
Complex mode: Renders each bar’s momentum range as a candle-like block, with filled bodies that immediately change color when momentum direction flips. Edge lines emphasize the high/low range of momentum for that bar. This mode makes subtle momentum shifts visually striking.
6. Configurable sensitivity profiles
Five risk profiles (very conservative → very aggressive) automatically adjust how extreme the momentum reading must be before signaling. Conservative traders can wait for only the most dramatic reversals, while aggressive traders can capture more frequent, smaller mean-reversion moves.
7. Customizable color palettes
Twenty distinct color themes let users match the indicator to any chart background. Each theme defines separate colors for bullish fills, bearish fills, the momentum series, and divergence labels. Options range from classic contrasting pairs to neon-style palettes to dark-mode complements.
8. Unified plotting interface
Instead of scattering multiple indicators in separate panes, Uptrick: Mean Reversion consolidates everything—normalized momentum, background shading, threshold bands, reversal labels, divergence flags, and bias table—into a single indicator pane. This reduces screen clutter and places all relevant information in one view.
9. Built-in alert triggers
Six alert conditions are exposed:
Mean reversion buy signal (momentum flips in oversold zone)
Mean reversion sell signal (momentum flips in overbought zone)
Bullish divergence confirmation
Bearish divergence confirmation
Bias flip to bullish (when combined sentiment shifts from non-bullish to bullish)
Bias flip to bearish (when combined sentiment shifts from non-bearish to bearish)
Traders can attach alerts to any of these conditions to receive real-time notifications.
10. Scale anchoring
By forcing invisible horizontal lines at fixed extreme levels, the indicator ensures that the vertical axis always includes those extremes—even if the normalized reading rarely reaches them. This constant frame of reference helps traders judge how significant current readings are.
Line features:
Conclusion
Uptrick: Mean Reversion offers a layered, all-in-one approach to spotting countertrend opportunities. By converting price movement into a proprietary normalized momentum scale, it highlights extreme overbought and oversold zones. Inflection detection within those extremes produces clear reversal markers. Embedded divergence logic calls out hidden momentum weaknesses. A five-factor sentiment dashboard helps gauge whether a reversal signal aligns with broader market context. Users can tailor sensitivity, visual presentation, and color schemes, making it equally suitable for minimalist or richly detailed chart layouts. Optimized for lower timeframes, Uptrick: Mean Reversion helps traders anticipate statistically significant mean reversion moves.
Disclaimer
This indicator is provided for informational purposes only. It does not guarantee any trading outcome. Trading carries inherent risks, including the potential loss of invested capital. Users should perform their own due diligence, apply proper risk management, and consult a financial professional if needed. Past performance does not ensure future results.
Liquidity Engulfing (Nephew_Sam_)🔥 Liquidity Engulfing Multi-Timeframe Detector
This indicator finds engulfing bars which have swept liquidity from its previous candle. You can use it across 6 timeframes with fibonacci entries.
⚡ Key Features
6 Customizable Timeframes - Complete market structure analysis
Smart Liquidity Detection - Finds patterns that sweep liquidity then reverse
Real-Time Status Table - Confirmed vs unconfirmed patterns with color coding
Fibonacci Integration - 5 customizable fib levels for precise entries
HTF → LTF Strategy - Spot reversals on higher timeframes, enter on lower timeframe fibs
📈 Engulfing Rules
Bullish: Current candle bullish + previous bearish + current low < previous low + current close > previous open
Bearish: Current candle bearish + previous bullish + current high > previous high + current close < previous open
MirPapa:ICT:HTF: Candle OB Threeple# MirPapa:ICT:HTF: Candle OB Threeple
**Version:** Pine Script® v6
---
## Installation
1. Open TradingView’s Pine Editor.
2. Paste the entire script (including `import goodia/MirPapa_Library_ICT/3 as lib`).
3. Click **“Add to Chart”**.
---
## Inputs & Configuration
After adding to chart, open the indicator’s settings panel:
1. **Box Close Color**
- Choose the color applied when a Candle OB box is finalized (recolored).
2. **HighTF COB Settings**
- **HighTF Label:** Select a higher timeframe (e.g., “4시간” for 4H).
- **Enable HighTF COB Boxes:** Toggle drawing of HighTF boxes.
- **Enable HighTF COB Midlines:** Toggle drawing of the horizontal midpoint line inside each HighTF box.
- **HighTF COB Close Count:** Number of HTF closes beyond the box required to finalize (1–10).
- **HighTF COB Bull Color / Bear Color:** Select fill/border colors for bullish and bearish HighTF boxes.
- **HighTF Box Transparency:** Adjust box opacity (1–100).
3. **MidTF COB Settings**
- **MidTF Label:** Select a middle timeframe (e.g., “1시간” for 1H).
- **Enable MidTF COB Boxes:** Toggle drawing of MidTF boxes.
- **Enable MidTF COB Midlines:** Toggle the midpoint line inside each MidTF box.
- **MidTF COB Close Count:** Number of MidTF closes beyond the box required to finalize (1–10).
- **MidTF COB Bull Color / Bear Color:** Select fill/border colors for bullish and bearish MidTF boxes.
- **MidTF Box Transparency:** Adjust box opacity (1–100).
4. **CurrentTF COB Settings**
- **Enable CurrentTF COB Boxes:** Toggle drawing of COB boxes on the chart’s own timeframe.
- **Enable CurrentTF COB Midlines:** Toggle the midpoint line inside each CurrentTF box.
- **CurrentTF COB Close Count:** Number of closes beyond the box required to finalize (1–10).
- **COB Detection Level:** Choose pivot strength for detection (1 or 2).
- **CurrentTF COB Bull Color / Bear Color:** Select fill/border colors for bullish and bearish CurrentTF boxes.
- **CurrentTF Box Transparency:** Adjust box opacity (1–100).
---
## Display & Interpretation
- **Candle OB Boxes**
- Each box appears at the moment a reversal candle is detected on the chosen timeframe.
- Bullish boxes have the “Bull Color”; bearish boxes have the “Bear Color.”
- The midpoint line (if enabled) is drawn across the box’s center.
- **Box Extension**
- Once created, each box extends to the right on every new bar of the chart.
- You will see the box tracking along with price until it is finalized.
- **Box Finalization (Recoloring)**
- After the specified number of closes beyond the candle range, the box’s border and fill change to the **Box Close Color**.
- Finalized boxes remain visible in semi-transparent form, indicating that the zone has been “tested.”
- **Multiple Timeframes**
- If HighTF, MidTF, and/or CurrentTF boxes are all enabled, you’ll see up to three separate layers of boxes (one per timeframe).
- Higher-timeframe boxes typically span more candles; MidTF and CurrentTF boxes will be narrower.
---
## Tips
- **Adjust Opacity** to avoid clutter when multiple boxes overlap.
- **Use Distinct Colors** for each timeframe to quickly differentiate HighTF vs. MidTF vs. CurrentTF.
- **Experiment with Close Count** to control how long boxes remain active before finalizing.
- **Toggle Midlines** if you prefer seeing only the box or want an added visual cue at its center.
Enjoy clear, multi-timeframe Candle Order Block visualization on your chart!
MirPapa:ICT:HTF: FVG OB Threeple# MirPapa:ICT:HTF: FVG OB (Fair Value Gap Order Block)
**Version:** Pine Script® v6
**Author:** © goodia
**License:** MPL-2.0 (Mozilla Public License 2.0)
---
## Overview
“FVG OB” (Fair Value Gap Order Block) identifies higher-timeframe candle ranges where a gap (imbalance) exists between two non-consecutive candles, signaling potential institutional order blocks. This module draws bullish or bearish FVG OB boxes on your lower-timeframe chart, extends them until price interacts a specified number of times, and then finalizes (recolors) the box.
---
## Inputs
- **Enable FVG OB Boxes** (`bool`)
Toggle drawing of HTF FVG OB boxes on the chart.
- **Enable FVG OB Midlines** (`bool`)
Toggle drawing of a midpoint line inside each FVG OB box.
- **FVG OB Close Count** (`int` 1–10)
Number of HTF closes beyond the FVG range required to finalize (recolor) the box.
- **FVG OB Bull Color** (`color`)
Fill & border color for bullish FVG OB boxes.
- **FVG OB Bear Color** (`color`)
Fill & border color for bearish FVG OB boxes.
- **FVG OB Box Transparency** (`int` 1–100)
Opacity level for FVG OB box fills (higher = more transparent).
---
## How It Works
1. **HTF Data Retrieval**
- The script uses `request.security()` (via `GetHTFrevised()`) to fetch HTF OHLC and historical values:
- `_htfHigh3` (high three bars ago) and `_htfLow1` (low one bar ago) for bullish FVG OB.
- `_htfLow3` (low three bars ago) and `_htfHigh1` (high one bar ago) for bearish FVG OB.
- It also tracks the HTF `bar_index` on the lower timeframe to align drawing.
2. **FVG OB Detection**
- **Bullish FVG OB**: Occurs when the HTF low of the previous bar (`low `) is strictly above the HTF high of three bars ago (`high `), creating a gap.
- **Bearish FVG OB**: Occurs when the HTF high of the previous bar (`high `) is strictly below the HTF low of three bars ago (`low `), creating a gap.
3. **Box Creation**
- On each new HTF bar (`ta.change(time(HTF)) != 0`), if a bullish or bearish FVG OB condition is met, the script calls `CreateBoxData()` with:
- **Bullish**: `bottom = HTF low `, `top = HTF high `, `_isBull = true`.
- **Bearish**: `bottom = HTF low `, `top = HTF high `, `_isBull = false`.
- Midline toggled by input.
- A `BoxData` struct is created and stored in either the Bull or Bear array.
4. **Box Extension & Finalization**
- On **every LTF bar**, `ProcessBoxDatas(...)` iterates over all active FVG OB boxes:
1. **Extend Right Edge**: `box.set_right(bar_index)` ensures the box follows the latest bar.
2. **Record Volume Delta**: Tracks buy/sell volume inside the box.
3. **Touch Stage Update**: `modBoxUpdateStage()` increments `_stage` when price touches its “basePoint” (for FVG OB, the basePrice is one side of the gap).
4. **Finalize**: `setBoxFinalize()` checks if the configured number of closes beyond the FVG gap (`FVG OB Close Count`) has occurred. If so:
- `_isActive := false`
- Border and background colors are changed to the “Box Close Color” (input).
- Finalized boxes remain on screen semi-transparent, indicating that the FVG OB zone has been tested.
5. **Midline (Optional)**
- If “Enable FVG OB Midlines” is checked, `ProcessBoxDatas()` also extends a horizontal midpoint line inside the box with `line.set_x2(bar_index)`.
---
## Usage Instructions
1. **Installation**
- Copy the FVG OB section of the Pine Script into TradingView’s Pine Editor (ensure the library import is included).
- Click “Add to Chart.”
2. **Configure Inputs**
- Choose a Higher Time Frame via the dropdown (e.g., “4시간” maps to a 4H timeframe).
- Toggle “Enable FVG OB Boxes” and “Enable FVG OB Midlines.”
- Select colors for bullish and bearish boxes and set transparency.
- Adjust “FVG OB Close Count” to control how many closes beyond the gap finalize the box.
3. **Interpretation**
- **Active FVG OB Boxes** extend to the right until price closes beyond the gap range the specified number of times.
- When finalized, each box changes to the “Box Close Color,” signaling that institutional orders in that gap have likely been filled.
Enjoy precise visualization of higher-timeframe Fair Value Gap Order Blocks on your lower-timeframe chart!
MirPapa:ICT:HTF: FVG Threeple# MirPapa:ICT:FVG Double HTF
**Version:** Pine Script® v6
**Author:** © goodia
**License:** MPL-2.0 (Mozilla Public License 2.0)
---
## Overview
“MirPapa:ICT:FVG Double HTF” is a TradingView indicator that identifies and visualizes Fair Value Gaps (FVG) on two higher time frames (HighTF and MidTF) simultaneously. It can also draw FVG boxes on the current chart’s time frame. When “Overlap Mode” is enabled, the indicator displays only the intersection of HighTF and MidTF FVG areas.
---
## Key Features
- **HighTF FVG**
- Detects bullish and bearish FVGs on a user-selected upper time frame (e.g., 4H).
- Draws colored boxes around gap ranges, optionally with a midpoint line.
- Automatically extends boxes on every bar and finalizes (recolors) them after a specified number of closes beyond the gap.
- **MidTF FVG**
- Same as HighTF FVG but for a second, intermediate time frame (e.g., 1H).
- Runs in parallel to HighTF logic, with separate color and transparency settings.
- **CurrentTF FVG (Optional)**
- If enabled, draws FVG boxes using the chart’s own time frame.
- Behaves identically: extends until broken by price, then finalizes.
- **Overlap Mode**
- When enabled, hides all individual HighTF and MidTF boxes.
- Instead, computes and displays only their overlapping rectangle(s)—separate for bullish and bearish gaps.
---
## Inputs & Configuration
- **Common Inputs**
- **Enable High/Mid Overlap Mode** (`boolean`): Show only overlapping HighTF + MidTF FVG areas.
- **Box Close Color** (`color`): Color applied to any FVG box when it is finalized.
- **HighTF FVG Settings**
- **HighTF Label** (`dropdown`): Choose a Korean label (e.g., “4시간”) that maps to a Pine timeframe (e.g., “240”).
- **Enable HighTF FVG Boxes** (`boolean`): Toggle drawing of HighTF FVG boxes.
- **Enable HighTF FVG Midlines** (`boolean`): Toggle midpoint line inside each HighTF box.
- **HighTF FVG Close Count** (`integer` 1–10): Number of closes beyond the gap before finalizing the box.
- **HighTF FVG Bull Color** (`color`): Fill & border color for bullish HighTF gaps.
- **HighTF FVG Bear Color** (`color`): Fill & border color for bearish HighTF gaps.
- **HighTF Box Transparency** (`integer` 1–100): Opacity level for HighTF box fills.
- **MidTF FVG Settings**
- **MidTF Label** (`dropdown`): Choose a Korean label (e.g., “1시간”) mapped to a Pine timeframe.
- **Enable MidTF FVG Boxes** (`boolean`): Toggle drawing of MidTF FVG boxes.
- **Enable MidTF FVG Midlines** (`boolean`): Toggle midpoint line inside each MidTF box.
- **MidTF FVG Close Count** (`integer` 1–10): Number of closes beyond the gap before finalizing the box.
- **MidTF FVG Bull Color** (`color`): Fill & border color for bullish MidTF gaps.
- **MidTF FVG Bear Color** (`color`): Fill & border color for bearish MidTF gaps.
- **MidTF Box Transparency** (`integer` 1–100): Opacity level for MidTF box fills.
- **CurrentTF FVG Settings**
- **Enable CurrentTF FVG Boxes** (`boolean`): Draw FVG boxes on the chart’s own timeframe.
- **Enable CurrentTF FVG Midlines** (`boolean`): Toggle midpoint line inside each CurrentTF box.
- **CurrentTF FVG Close Count** (`integer` 1–10): Number of closes beyond the gap before finalizing the box.
- **CurrentTF FVG Bull Color** (`color`): Fill & border color for bullish CurrentTF gaps.
- **CurrentTF FVG Bear Color** (`color`): Fill & border color for bearish CurrentTF gaps.
- **CurrentTF Box Transparency** (`integer` 1–100): Opacity level for CurrentTF box fills.
---
## How It Works
1. **Time Frame Conversion**
Korean labels (e.g., “4시간”, “1시간”) are converted internally to Pine timeframe strings via `GetHtfFromLabel()`.
2. **Data Retrieval**
For each chosen TF (HighTF, MidTF, and optionally CurrentTF), the script fetches OHLC and historical values using `GetHTFrevised()`.
- Tracks `bar_index` from that TF to align box drawing on the chart’s base timeframe.
3. **Box Lifecycle**
- **Creation**: On each new TF bar, if a bullish gap (`low > high `) or bearish gap (`low > high `) is detected, `CreateBoxData()` registers a new `BoxData` struct and draws an initial box.
- **Extension**: On every chart bar, `ProcessBoxDatas()` extends each active box’s right edge and updates internal “touch stage” and volume.
- **Finalization**: After the specified number of closes beyond the gap, `setBoxFinalize()` disables the box and changes its border & fill to the “Box Close Color”.
4. **Overlap Mode**
- When enabled, HighTF and MidTF boxes are not drawn individually.
- Instead, at each bar, the script iterates over all active HighTF boxes and all active MidTF boxes, computes their intersection rectangle (if any), and draws only that overlapping area (distinct handling for bullish vs. bearish gaps).
---
## Installation & Usage
1. **Copy & Paste**
Copy the entire Pine Script code into TradingView’s Pine Editor.
Click “Add to Chart.”
2. **Configure Inputs**
- Choose your HighTF and MidTF via the dropdown menus.
- Enable or disable FVG boxes/midlines for each TF.
- Adjust colors, transparency, and “Close Count” settings to taste.
- Toggle “Overlap Mode” if you only want to see common areas between HighTF and MidTF gaps.
3. **Interpretation**
- **Active Boxes** extend to the right as new bars form. When price closes beyond a gap (per “Close Count”), the box is finalized and recolored to the close color.
- In **Overlap Mode**, you’ll see only the overlapping region between HighTF and MidTF gaps, updated on every bar.
Enjoy precise FVG visualization across multiple time frames!
Schmit Trading LiquidityDescription
Schmit Trading Liquidity Marker automatically spots and labels open liquidity sweep levels by detecting classic stop-run patterns (Bull→Bear for highs, Bear→Bull for lows) across multiple timeframes. Lines are drawn exactly at the wick of the triggering candle and removed as soon as price “sweeps” through them, keeping your chart clean and focused on live levels only.
How It Works
1. Pattern Detection
• Liquidity High: When a bullish candle is immediately followed by a bearish candle (Bull→Bear), the script records the higher of the two wicks.
• Liquidity Low: When a bearish candle is immediately followed by a bullish candle (Bear→Bull), the script records the lower of the two wicks.
2. Multi-Timeframe Support
• Choose up to six timeframes (5 min, 15 min, 30 min, 1 h, 4 h, daily) via checkboxes.
• Each timeframe is evaluated independently, and liquidity levels are drawn on your current chart.
3. Precision Wick Placement
• Lines start at bar_index – 1 so they align exactly with the wick of the signal candle, regardless of your chart’s timeframe.
4. Automatic Cleanup
• As soon as price closes beyond a drawn line (sweep), that line is deleted automatically.
Inputs
Input Name Description
Show 5 min. Enable liquidity detection on the 5-minute timeframe.
Show 15 min. Enable liquidity detection on the 15-minute timeframe.
Show 30 min. Enable liquidity detection on the 30-minute timeframe.
Show 1 h. Enable liquidity detection on the 1-hour timeframe.
Show 4 h. Enable liquidity detection on the 4-hour timeframe.
Show 1 D. Enable liquidity detection on the daily timeframe.
High Line Color. Color of Bull→Bear (liquidity high) lines (default: red).
Low Line Color. Color of Bear→Bull (liquidity low) lines (default: blue).
Line Length. How many bars each liquidity line extends to the right.
Usage Tips
• Focus on Live Zones: Combine with volume or order-flow tools to confirm genuine
liquidity sweeps.
• Multiple TFs: Enable higher timeframes for major liquidity clusters; lower timeframes
for fine‐tuning entries.
• Chart Cleanliness: Lines self‐delete on sweep, ensuring no manual cleanup is needed.
⸻
Disclosure & License
This indicator is Open-Source under the Mozilla Public License 2.0. Feel free to review, adapt, and improve the code. No performance guarantees—use responsibly and backtest any strategy before trading live.
FvgPanel█ OVERVIEW
This library provides functionalities for creating and managing a display panel within a Pine Script™ indicator. Its primary purpose is to offer a structured way to present Fair Value Gap (FVG) information, specifically the nearest bullish and bearish FVG levels across different timeframes (Current, MTF, HTF), directly on the chart. The library handles the table's structure, header initialization, and dynamic cell content updates.
█ CONCEPTS
The core of this library revolves around presenting summarized FVG data in a clear, tabular format. Key concepts include:
FVG Data Aggregation and Display
The panel is designed to show at-a-glance information about the closest active FVG mitigation levels. It doesn't calculate these FVGs itself but relies on the main script to provide this data. The panel is structured with columns for timeframes (TF), Bullish FVGs, and Bearish FVGs, and rows for "Current" (LTF), "MTF" (Medium Timeframe), and "HTF" (High Timeframe).
The `panelData` User-Defined Type (UDT)
To facilitate the transfer of information to be displayed, the library defines a UDT named `panelData`. This structure is central to the library's operation and is designed to hold all necessary values for populating the panel's data cells for each relevant FVG. Its fields include:
Price levels for the nearest bullish and bearish FVGs for LTF, MTF, and HTF (e.g., `nearestBullMitLvl`, `nearestMtfBearMitLvl`).
Boolean flags to indicate if these FVGs are classified as "Large Volume" (LV) (e.g., `isNearestBullLV`, `isNearestMtfBearLV`).
Color information for the background and text of each data cell, allowing for conditional styling based on the FVG's status or proximity (e.g., `ltfBullBgColor`, `mtfBearTextColor`).
The design of `panelData` allows the main script to prepare all display-related data and styling cues in one object, which is then passed to the `updatePanel` function for rendering. This separation of data preparation and display logic keeps the library focused on its presentation task.
Visual Cues and Formatting
Price Formatting: Price levels are formatted to match the instrument's minimum tick size using an internal `formatPrice` helper function, ensuring consistent and accurate display.
Large FVG Icon: If an FVG is marked as a "Large Volume" FVG in the `panelData` object, a user-specified icon (e.g., an emoji) is prepended to its price level in the panel, providing an immediate visual distinction.
Conditional Styling: The background and text colors for each FVG level displayed in the panel can be individually controlled via the `panelData` object, enabling the main script to implement custom styling rules (e.g., highlighting the overall nearest FVG across all timeframes).
Handling Missing Data: If no FVG data is available for a particular cell (i.e., the corresponding level in `panelData` is `na`), the panel displays "---" and uses a specified background color for "Not Available" cells.
█ CALCULATIONS AND USE
Using the `FvgPanel` typically involves a two-stage process: initialization and dynamic updates.
Step 1: Panel Creation
First, an instance of the panel table is created once, usually during the script's initial setup. This is done using the `createPanel` function.
Call `createPanel()` with parameters defining its position on the chart, border color, border width, header background color, header text color, and header text size.
This function initializes the table with three columns ("TF", "Bull FVG", "Bear FVG") and three data rows labeled "Current", "MTF", and "HTF", plus a header row.
Store the returned `table` object in a `var` variable to persist it across bars.
// Example:
var table infoPanel = na
if barstate.isfirst
infoPanel := panel.createPanel(
position.top_right,
color.gray,
1,
color.new(color.gray, 50),
color.white,
size.small
)
Step 2: Panel Updates
On each bar, or whenever the FVG data changes (typically on `barstate.islast` or `barstate.isrealtime` for efficiency), the panel's content needs to be refreshed. This is done using the `updatePanel` function.
Populate an instance of the `panelData` UDT with the latest FVG information. This includes setting the nearest bullish/bearish mitigation levels for LTF, MTF, and HTF, their LV status, and their desired background and text colors.
Call `updatePanel()`, passing the persistent `table` object (from Step 1), the populated `panelData` object, the icon string for LV FVGs, the default text color for FVG levels, the background color for "N/A" cells, and the general text size for the data cells.
The `updatePanel` function will then clear previous data and fill the table cells with the new values and styles provided in the `panelData` object.
// Example (inside a conditional block like 'if barstate.islast'):
var panelData fvgDisplayData = panelData.new()
// ... (logic to populate fvgDisplayData fields) ...
// fvgDisplayData.nearestBullMitLvl = ...
// fvgDisplayData.ltfBullBgColor = ...
// ... etc.
if not na(infoPanel)
panel.updatePanel(
infoPanel,
fvgDisplayData,
"🔥", // LV FVG Icon
color.white,
color.new(color.gray, 70), // NA Cell Color
size.small
)
This workflow ensures that the panel is drawn only once and its cells are efficiently updated as new data becomes available.
█ NOTES
Data Source: This library is solely responsible for the visual presentation of FVG data in a table. It does not perform any FVG detection or calculation. The calling script must compute or retrieve the FVG levels, LV status, and desired styling to populate the `panelData` object.
Styling Responsibility: While `updatePanel` applies colors passed via the `panelData` object, the logic for *determining* those colors (e.g., highlighting the closest FVG to the current price) resides in the calling script.
Performance: The library uses `table.cell()` to update individual cells, which is generally more efficient than deleting and recreating the table on each update. However, the frequency of `updatePanel` calls should be managed by the main script (e.g., using `barstate.islast` or `barstate.isrealtime`) to avoid excessive processing on historical bars.
`series float` Handling: The price level fields within the `panelData` UDT (e.g., `nearestBullMitLvl`) can accept `series float` values, as these are typically derived from price data. The internal `formatPrice` function correctly handles `series float` for display.
Dependencies: The `FvgPanel` itself is self-contained and does not import other user libraries. It uses standard Pine Script™ table and string functionalities.
█ EXPORTED TYPES
panelData
Represents the data structure for populating the FVG information panel.
Fields:
nearestBullMitLvl (series float) : The price level of the nearest bullish FVG's mitigation point (bottom for bull) on the LTF.
isNearestBullLV (series bool) : True if the nearest bullish FVG on the LTF is a Large Volume FVG.
ltfBullBgColor (series color) : Background color for the LTF bullish FVG cell in the panel.
ltfBullTextColor (series color) : Text color for the LTF bullish FVG cell in the panel.
nearestBearMitLvl (series float) : The price level of the nearest bearish FVG's mitigation point (top for bear) on the LTF.
isNearestBearLV (series bool) : True if the nearest bearish FVG on the LTF is a Large Volume FVG.
ltfBearBgColor (series color) : Background color for the LTF bearish FVG cell in the panel.
ltfBearTextColor (series color) : Text color for the LTF bearish FVG cell in the panel.
nearestMtfBullMitLvl (series float) : The price level of the nearest bullish FVG's mitigation point on the MTF.
isNearestMtfBullLV (series bool) : True if the nearest bullish FVG on the MTF is a Large Volume FVG.
mtfBullBgColor (series color) : Background color for the MTF bullish FVG cell.
mtfBullTextColor (series color) : Text color for the MTF bullish FVG cell.
nearestMtfBearMitLvl (series float) : The price level of the nearest bearish FVG's mitigation point on the MTF.
isNearestMtfBearLV (series bool) : True if the nearest bearish FVG on the MTF is a Large Volume FVG.
mtfBearBgColor (series color) : Background color for the MTF bearish FVG cell.
mtfBearTextColor (series color) : Text color for the MTF bearish FVG cell.
nearestHtfBullMitLvl (series float) : The price level of the nearest bullish FVG's mitigation point on the HTF.
isNearestHtfBullLV (series bool) : True if the nearest bullish FVG on the HTF is a Large Volume FVG.
htfBullBgColor (series color) : Background color for the HTF bullish FVG cell.
htfBullTextColor (series color) : Text color for the HTF bullish FVG cell.
nearestHtfBearMitLvl (series float) : The price level of the nearest bearish FVG's mitigation point on the HTF.
isNearestHtfBearLV (series bool) : True if the nearest bearish FVG on the HTF is a Large Volume FVG.
htfBearBgColor (series color) : Background color for the HTF bearish FVG cell.
htfBearTextColor (series color) : Text color for the HTF bearish FVG cell.
█ EXPORTED FUNCTIONS
createPanel(position, borderColor, borderWidth, headerBgColor, headerTextColor, headerTextSize)
Creates and initializes the FVG information panel (table). Sets up the header rows and timeframe labels.
Parameters:
position (simple string) : The position of the panel on the chart (e.g., position.top_right). Uses position.* constants.
borderColor (simple color) : The color of the panel's border.
borderWidth (simple int) : The width of the panel's border.
headerBgColor (simple color) : The background color for the header cells.
headerTextColor (simple color) : The text color for the header cells.
headerTextSize (simple string) : The text size for the header cells (e.g., size.small). Uses size.* constants.
Returns: The newly created table object representing the panel.
updatePanel(panelTable, data, lvIcon, defaultTextColor, naCellColor, textSize)
Updates the content of the FVG information panel with the latest FVG data.
Parameters:
panelTable (table) : The table object representing the panel to be updated.
data (panelData) : An object containing the FVG data to display.
lvIcon (simple string) : The icon (e.g., emoji) to display next to Large Volume FVGs.
defaultTextColor (simple color) : The default text color for FVG levels if not highlighted.
naCellColor (simple color) : The background color for cells where no FVG data is available ("---").
textSize (simple string) : The text size for the FVG level data (e.g., size.small).
Returns: _void
FvgCalculations█ OVERVIEW
This library provides the core calculation engine for identifying Fair Value Gaps (FVGs) across different timeframes and for processing their interaction with price. It includes functions to detect FVGs on both the current chart and higher timeframes, as well as to check for their full or partial mitigation.
█ CONCEPTS
The library's primary functions revolve around the concept of Fair Value Gaps and their lifecycle.
Fair Value Gap (FVG) Identification
An FVG, or imbalance, represents a price range where buying or selling pressure was significant enough to cause a rapid price movement, leaving an "inefficiency" in the market. This library identifies FVGs based on three-bar patterns:
Bullish FVG: Forms when the low of the current bar (bar 3) is higher than the high of the bar two periods prior (bar 1). The FVG is the space between the high of bar 1 and the low of bar 3.
Bearish FVG: Forms when the high of the current bar (bar 3) is lower than the low of the bar two periods prior (bar 1). The FVG is the space between the low of bar 1 and the high of bar 3.
The library provides distinct functions for detecting FVGs on the current (Low Timeframe - LTF) and specified higher timeframes (Medium Timeframe - MTF / High Timeframe - HTF).
FVG Mitigation
Mitigation refers to price revisiting an FVG.
Full Mitigation: An FVG is considered fully mitigated when price completely closes the gap. For a bullish FVG, this occurs if the current low price moves below or touches the FVG's bottom. For a bearish FVG, it occurs if the current high price moves above or touches the FVG's top.
Partial Mitigation (Entry/Fill): An FVG is partially mitigated when price enters the FVG's range but does not fully close it. The library tracks the extent of this fill. For a bullish FVG, if the current low price enters the FVG from above, that low becomes the new effective top of the remaining FVG. For a bearish FVG, if the current high price enters the FVG from below, that high becomes the new effective bottom of the remaining FVG.
FVG Interaction
This refers to any instance where the current bar's price range (high to low) touches or crosses into the currently unfilled portion of an active (visible and not fully mitigated) FVG.
Multi-Timeframe Data Acquisition
To detect FVGs on higher timeframes, specific historical bar data (high, low, and time of bars at indices and relative to the higher timeframe's last completed bar) is required. The requestMultiTFBarData function is designed to fetch this data efficiently.
█ CALCULATIONS AND USE
The functions in this library are typically used in a sequence to manage FVGs:
1. Data Retrieval (for MTF/HTF FVGs):
Call requestMultiTFBarData() with the desired higher timeframe string (e.g., "60", "D").
This returns a tuple of htfHigh1, htfLow1, htfTime1, htfHigh3, htfLow3, htfTime3.
2. FVG Detection:
For LTF FVGs: Call detectFvg() on each confirmed bar. It uses high , low, low , and high along with barstate.isconfirmed.
For MTF/HTF FVGs: Call detectMultiTFFvg() using the data obtained from requestMultiTFBarData().
Both detection functions return an fvgObject (defined in FvgTypes) if an FVG is found, otherwise na. They also can classify FVGs as "Large Volume" (LV) if classifyLV is true and the FVG size (top - bottom) relative to the tfAtr (Average True Range of the respective timeframe) meets the lvAtrMultiplier.
3. FVG State Updates (on each new bar for existing FVGs):
First, check for overall price interaction using fvgInteractionCheck(). This function determines if the current bar's high/low has touched or entered the FVG's currentTop or currentBottom.
If interaction occurs and the FVG is not already mitigated:
Call checkMitigation() to determine if the FVG has been fully mitigated by the current bar's currentHigh and currentLow. If true, the FVG's isMitigated status is updated.
If not fully mitigated, call checkPartialMitigation() to see if the price has further entered the FVG. This function returns the newLevel to which the FVG has been filled (e.g., currentLow for a bullish FVG, currentHigh for bearish). This newLevel is then used to update the FVG's currentTop or currentBottom.
The calling script (e.g., fvgMain.c) is responsible for storing and managing the array of fvgObject instances and passing them to these update functions.
█ NOTES
Bar State for LTF Detection: The detectFvg() function relies on barstate.isconfirmed to ensure FVG detection is based on closed bars, preventing FVGs from being detected prematurely on the currently forming bar.
Higher Timeframe Data (lookahead): The requestMultiTFBarData() function uses lookahead = barmerge.lookahead_on. This means it can access historical data from the higher timeframe that corresponds to the current bar on the chart, even if the higher timeframe bar has not officially closed. This is standard for multi-timeframe analysis aiming to plot historical HTF data accurately on a lower timeframe chart.
Parameter Typing: Functions like detectMultiTFFvg and detectFvg infer the type for boolean (classifyLV) and numeric (lvAtrMultiplier) parameters passed from the main script, while explicitly typed series parameters (like htfHigh1, currentAtr) expect series data.
fvgObject Dependency: The FVG detection functions return fvgObject instances, and fvgInteractionCheck takes an fvgObject as a parameter. This UDT is defined in the FvgTypes library, making it a dependency for using FvgCalculations.
ATR for LV Classification: The tfAtr (for MTF/HTF) and currentAtr (for LTF) parameters are expected to be the Average True Range values for the respective timeframes. These are used, if classifyLV is enabled, to determine if an FVG's size qualifies it as a "Large Volume" FVG based on the lvAtrMultiplier.
MTF/HTF FVG Appearance Timing: When displaying FVGs from a higher timeframe (MTF/HTF) on a lower timeframe (LTF) chart, users might observe that the most recent MTF/HTF FVG appears one LTF bar later compared to its appearance on a native MTF/HTF chart. This is an expected behavior due to the detection mechanism in `detectMultiTFFvg`. This function uses historical bar data from the MTF/HTF (specifically, data equivalent to `HTF_bar ` and `HTF_bar `) to identify an FVG. Therefore, all three bars forming the FVG on the MTF/HTF must be fully closed and have shifted into these historical index positions relative to the `request.security` call from the LTF chart before the FVG can be detected and displayed on the LTF. This ensures that the MTF/HTF FVG is identified based on confirmed, closed bars from the higher timeframe.
█ EXPORTED FUNCTIONS
requestMultiTFBarData(timeframe)
Requests historical bar data for specific previous bars from a specified higher timeframe.
It fetches H , L , T (for the bar before last) and H , L , T (for the bar three periods prior)
from the requested timeframe.
This is typically used to identify FVG patterns on MTF/HTF.
Parameters:
timeframe (simple string) : The higher timeframe to request data from (e.g., "60" for 1-hour, "D" for Daily).
Returns: A tuple containing: .
- htfHigh1 (series float): High of the bar at index 1 (one bar before the last completed bar on timeframe).
- htfLow1 (series float): Low of the bar at index 1.
- htfTime1 (series int) : Time of the bar at index 1.
- htfHigh3 (series float): High of the bar at index 3 (three bars before the last completed bar on timeframe).
- htfLow3 (series float): Low of the bar at index 3.
- htfTime3 (series int) : Time of the bar at index 3.
detectMultiTFFvg(htfHigh1, htfLow1, htfTime1, htfHigh3, htfLow3, htfTime3, tfAtr, classifyLV, lvAtrMultiplier, tfType)
Detects a Fair Value Gap (FVG) on a higher timeframe (MTF/HTF) using pre-fetched bar data.
Parameters:
htfHigh1 (float) : High of the first relevant bar (typically high ) from the higher timeframe.
htfLow1 (float) : Low of the first relevant bar (typically low ) from the higher timeframe.
htfTime1 (int) : Time of the first relevant bar (typically time ) from the higher timeframe.
htfHigh3 (float) : High of the third relevant bar (typically high ) from the higher timeframe.
htfLow3 (float) : Low of the third relevant bar (typically low ) from the higher timeframe.
htfTime3 (int) : Time of the third relevant bar (typically time ) from the higher timeframe.
tfAtr (float) : ATR value for the higher timeframe, used for Large Volume (LV) FVG classification.
classifyLV (bool) : If true, FVGs will be assessed to see if they qualify as Large Volume.
lvAtrMultiplier (float) : The ATR multiplier used to define if an FVG is Large Volume.
tfType (series tfType enum from no1x/FvgTypes/1) : The timeframe type (e.g., types.tfType.MTF, types.tfType.HTF) of the FVG being detected.
Returns: An fvgObject instance if an FVG is detected, otherwise na.
detectFvg(classifyLV, lvAtrMultiplier, currentAtr)
Detects a Fair Value Gap (FVG) on the current (LTF - Low Timeframe) chart.
Parameters:
classifyLV (bool) : If true, FVGs will be assessed to see if they qualify as Large Volume.
lvAtrMultiplier (float) : The ATR multiplier used to define if an FVG is Large Volume.
currentAtr (float) : ATR value for the current timeframe, used for LV FVG classification.
Returns: An fvgObject instance if an FVG is detected, otherwise na.
checkMitigation(isBullish, fvgTop, fvgBottom, currentHigh, currentLow)
Checks if an FVG has been fully mitigated by the current bar's price action.
Parameters:
isBullish (bool) : True if the FVG being checked is bullish, false if bearish.
fvgTop (float) : The top price level of the FVG.
fvgBottom (float) : The bottom price level of the FVG.
currentHigh (float) : The high price of the current bar.
currentLow (float) : The low price of the current bar.
Returns: True if the FVG is considered fully mitigated, false otherwise.
checkPartialMitigation(isBullish, currentBoxTop, currentBoxBottom, currentHigh, currentLow)
Checks for partial mitigation of an FVG by the current bar's price action.
It determines if the price has entered the FVG and returns the new fill level.
Parameters:
isBullish (bool) : True if the FVG being checked is bullish, false if bearish.
currentBoxTop (float) : The current top of the FVG box (this might have been adjusted by previous partial fills).
currentBoxBottom (float) : The current bottom of the FVG box (similarly, might be adjusted).
currentHigh (float) : The high price of the current bar.
currentLow (float) : The low price of the current bar.
Returns: The new price level to which the FVG has been filled (e.g., currentLow for a bullish FVG).
Returns na if no new partial fill occurred on this bar.
fvgInteractionCheck(fvg, highVal, lowVal)
Checks if the current bar's price interacts with the given FVG.
Interaction means the price touches or crosses into the FVG's
current (possibly partially filled) range.
Parameters:
fvg (fvgObject type from no1x/FvgTypes/1) : The FVG object to check.
Its isMitigated, isVisible, isBullish, currentTop, and currentBottom fields are used.
highVal (float) : The high price of the current bar.
lowVal (float) : The low price of the current bar.
Returns: True if price interacts with the FVG, false otherwise.
Candle Breakout Oscillator [LuxAlgo]The Candle Breakout Oscillator tool allows traders to identify the strength and weakness of the three main market states: bullish, bearish, and choppy.
Know who controls the market at any given moment with an oscillator display with values ranging from 0 to 100 for the three main plots and upper and lower thresholds of 80 and 20 by default.
🔶 USAGE
The Candle Breakout Oscillator represents the three main market states, with values ranging from 0 to 100. By default, the upper and lower thresholds are set at 80 and 20, and when a value exceeds these thresholds, a colored area is displayed for the trader's convenience.
This tool is based on pure price action breakouts. In this context, we understand a breakout as a close above the last candle's high or low, which is representative of market strength. All other close positions in relation to the last candle's limits are considered weakness.
So, when the bullish plot (in green) is at the top of the oscillator (values above 80), it means that the bullish breakouts (close below the last candle low) are at their maximum value over the calculation window, indicating an uptrend. The same interpretation can be made for the bearish plot (in red), indicating a downtrend when high.
On the other hand, weakness is indicated when values are below the lower threshold (20), indicating that breakouts are at their minimum over the last 100 candles. Below are some examples of the possible main interpretations:
There are three main things to look for in this oscillator:
Value reaches extreme
Value leaves extreme
Bullish/Bearish crossovers
As we can see on the chart, before the first crossover happens the bears come out of strength (top) and the bulls come out of weakness (bottom), then after the crossover the bulls reach strength (top) and the bears weakness (bottom), this process is repeated in reverse for the second crossover.
The other main feature of the oscillator is its ability to identify periods of sideways trends when the sideways values have upper readings above 80, and trending behavior when the sideways values have lower readings below 20. As we just saw in the case of bullish vs. bearish, sideways values signal a change in behavior when reaching or leaving the extremes of the oscillator.
🔶 DETAILS
🔹 Data Smoothing
The tool offers up to 10 different smoothing methods. In the chart above, we can see the raw data (smoothing: None) and the RMA, TEMA, or Hull moving averages.
🔹 Data Weighting
Users can add different weighting methods to the data. As we can see in the image above, users can choose between None, Volume, or Price (as in Price Delta for each breakout).
🔶 SETTINGS
Window: Execution window, 100 candles by default
🔹 Data
Smoothing Method: Choose between none or ten moving averages
Smoothing Length: Length for the moving average
Weighting Method: Choose between None, Volume, or Price
🔹 Thresholds
Top: 80 by default
Bottom: 20 by default
$ADD LevelsThis Pine Script is designed to track and visualize the NYSE Advance-Decline Line (ADD). The Advance-Decline Line is a popular market breadth indicator, showing the difference between advancing and declining stocks on the NYSE. It’s often used to gauge overall market sentiment and strength.
1. //@version=5
This line tells TradingView to use Pine Script v5, the latest and most powerful version of Pine.
2. indicator(" USI:ADD Levels", overlay=false)
• This creates a new indicator called ” USI:ADD Levels”.
• overlay=false means it will appear in a separate pane, not on the main price chart.
3. add = request.security(...)
This fetches real-time data from the symbol USI:ADD (Advance-Decline Line) using a 1-minute timeframe. You can change the timeframe if needed.
add_symbol = input.symbol(" USI:ADD ", "Market Breadth Symbol")
add = request.security(add_symbol, "1", close)
4. Key Thresholds
These define the market sentiment zones:
Zone. Value. Meaning
Overbought +1500 Extremely bullish
Bullish +1000 Generally bullish trend
Neutral ±500 Choppy, unclear market
Bearish -1000 Generally bearish trend
Oversold -1500 Extremely bearish
5. Plot the ADD Line hline(...)
Draws static lines at +1500, +1000, +500, -500, -1000, -1500 for reference so you can visually assess where ADD stands.
6. Horizontal Threshold Lines bgcolor(...)
• Green background if ADD > +1500 → extremely bullish.
• Red background if ADD < -1500 → extremely bearish.
7. Background Highlights alertcondition(...)
• Green background if ADD > +1500 → extremely bullish.
• Red background if ADD < -1500 → extremely bearish.
8. Alert Conditions. alertcondition(...)
Lets you create automatic alerts for:
• USI:ADD being very high or low.
• Crosses above +1000 (bullish trigger).
• Crosses below -1000 (bearish trigger).
You can use these to trigger trades or monitor sentiment shifts.
Summary: When to Use It
• Use this script in a market breadth dashboard.
• Combine it with price action and volume analysis.
• Monitor for ADD crosses to signal potential market reversals or momentum.
Indicator: Volatility Candle Based 📊 Volatility Candle-Based Indicator (Pine Script v6)
This custom TradingView indicator is designed for futures traders who want to analyze volatility, candle patterns, and support/resistance zones within specific market hours. It overlays price charts and provides visual signals that help determine potential momentum shifts, trend continuations, or reversals.
🔧 Core Features
⏰ Futures Time Filter
The indicator activates only during specific trading hours, customized per futures contract (e.g., NQ, ES, GC).
Time is adjusted to the New York (EST) timezone.
This ensures the logic only runs during relevant futures market sessions.
💹 Contract-Specific Multipliers
Applies custom point multipliers for futures contracts (e.g., GC = 30, ES = 24).
Supports three types of multipliers:
Trailing Stop
Trailing Plot Stop
Stop Loss
Ensures accurate backtesting and risk modeling for each contract.
📈 Trendline Support & Resistance
Uses pivot high/low logic to dynamically plot:
Central pivot zones
Step-like support/resistance lines
These trendlines update based on price behavior and can indicate bullish or bearish control.
🔍 Candle Momentum Analysis
Evaluates each candle's:
Body-to-range ratio (e.g., Marubozu, Doji)
Shadow dominance (upper/lower wicks)
Detects important reversal or continuation patterns such as:
Bullish/Bearish Inside Candles
Doji Star formations
Uses a custom moving average to confirm directional bias.
🕯️ Plotter Candle Signals
Identifies BullishPlotter and BearishPlotter candles:
Highlights candles likely to signal upcoming momentum.
Also accounts for neutral signals when no clear bias is detected.
Tracks the high/low of recent signal candles for reference.
📌 Visual Elements (not shown in snippet but implied by logic)
Signal arrows, dashed current levels, and filled support/resistance zones can be plotted to provide real-time feedback.
These are useful for both manual trading and strategy development.
🎯 Use Case
Perfect for intraday or short-term futures traders on instruments like:
🟡 Gold (GC), 🟠 Silver (SI)
📉 Nasdaq (NQ/MNQ), S&P 500 (ES/MES)
This script provides both structural context (trendlines, pivots) and price action signals (candle formations, momentum shifts), helping traders align their decisions with the underlying market flow.
MestreDoFOMO MACD VisualMasterDoFOMO MACD Visual
Description
MasterDoFOMO MACD Visual is a custom indicator that combines a unique approach to MACD with stochastic logic and simulated Renko-based direction signals. It is designed to help traders identify entry and exit opportunities based on market momentum and trend changes, with a clear and intuitive visualization.
How It Works
Stylized MACD with Stochastic: The indicator calculates the MACD using EMAs (exponential moving averages) normalized by stochastic logic. This is done by subtracting the lowest price (lowest low) from a defined period and dividing by the range between the highest and lowest price (highest high - lowest low). The result is a MACD that is more sensitive to market conditions, magnified by a factor of 10 for better visualization.
Signal Line: An EMA of the MACD is plotted as a signal line, allowing you to identify crossovers that indicate potential trend reversals or continuations.
Histogram: The difference between the MACD and the signal line is displayed as a histogram, with distinct colors (fuchsia for positive, purple for negative) to make momentum easier to read.
Simulated Renko Direction: Uses ATR (Average True Range) to calculate the size of Renko "bricks", generating signals of change in direction (bullish or bearish). These signals are displayed as arrows on the chart, helping to identify trend reversals.
Purpose
The indicator combines the sensitivity of the Stochastic MACD with the robustness of Renko signals to provide a versatile tool. It is ideal for traders looking to capture momentum-based market movements (using the MACD and histogram) while confirming trend changes with Renko signals. This combination reduces false signals and improves accuracy in volatile markets.
Settings
Stochastic Period (45): Sets the period for calculating the Stochastic range (highest high - lowest low).
Fast EMA Period (12): Period of the fast EMA used in the MACD.
Slow EMA Period (26): Period of the slow EMA used in the MACD.
Signal Line Period (9): Period of the EMA of the signal line.
Overbought/Oversold Levels (1.0/-1.0): Thresholds for identifying extreme conditions in the MACD.
ATR Period (14): Period for calculating the Renko brick size.
ATR Multiplier (1.0): Adjusts the Renko brick size.
Show Histogram: Enables/disables the histogram.
Show Renko Markers: Enables/disables the Renko direction arrows.
How to Use
MACD Crossovers: A MACD crossover above the signal line indicates potential bullishness, while below suggests bearishness.
Histogram: Fuchsia bars indicate bullish momentum; purple bars indicate bearish momentum.
Renko Arrows: Green arrows (upward triangle) signal a change to an uptrend; red arrows (downward triangle) signal a downtrend.
Overbought/Oversold Levels: Use the levels to identify potential reversals when the MACD reaches extreme values.
Notes
The chart should be set up with this indicator in isolation for better clarity.
Adjust the periods and ATR multiplier according to the asset and timeframe used.
Use the built-in alerts ("Renko Up Signal" and "Renko Down Signal") to set up notifications of direction changes.
This indicator is ideal for day traders and swing traders who want a visually clear and functional tool for trading based on momentum and trends.
Delta Volume Profile [BigBeluga]🔵Delta Volume Profile
A dynamic volume analysis tool that builds two separate horizontal profiles: one for bullish candles and one for bearish candles. This indicator helps traders identify the true balance of buying vs. selling volume across price levels, highlighting points of control (POCs), delta dominance, and hidden volume clusters with remarkable precision.
🔵 KEY FEATURES
Split Volume Profiles (Bull vs. Bear):
The indicator separates volume based on candle direction:
If close > open , the candle’s volume is added to the bullish profile (positive volume).
If close < open , it contributes to the bearish profile (negative volume).
ATR-Based Binning:
The price range over the selected lookback is split into bins using ATR(200) as the bin height.
Each bin accumulates both bull and bear volumes to form the dual-sided profile.
Bull and Bear Volume Bars:
Bullish volumes are shown as right-facing bars on the right side, colored with a bullish gradient.
Bearish volumes appear as left-facing bars on the left side, shaded with a bearish gradient.
Each bar includes a volume label (e.g., +12.45K or -9.33K) to show exact volume at that price level.
Points of Control (POC) Highlighting:
The bin with the highest bullish volume is marked with a border in POC+ color (default: blue).
The bin with the highest bearish volume is marked with a POC− color (default: orange).
Total Volume Density Map:
A neutral gray background box is plotted behind candles showing the total volume (bull + bear) per bin.
This reveals high-interest price zones regardless of direction.
Delta and Total Volume Summary:
A Delta label appears at the top, showing net % difference between bull and bear volume.
A Total label at the bottom shows total accumulated volume across all bins.
🔵 HOW IT WORKS
The indicator captures all candles within the lookback period .
It calculates the price range and splits it into bins using ATR for adaptive resolution.
For each candle:
If price intersects a bin and close > open , volume is added to the positive profile .
If close < open , volume is added to the negative profile .
The result is two side-by-side histograms at each price level—one for buyers, one for sellers.
The bin with the highest value on each side is visually emphasized using POC highlight colors.
At the end, the script calculates:
Delta: Total % difference between bull and bear volumes.
Total: Sum of all volumes in the lookback window.
🔵 USAGE
Volume Imbalance Zones: Identify price levels where buyers or sellers were clearly dominant.
Fade or Follow Volume Clusters: Use POC+ or POC− levels for reaction trades or breakouts.
Delta Strength Filtering: Strong delta values (> ±20%) suggest momentum or exhaustion setups.
Volume-Based Anchoring: Use profile levels to mark hidden support/resistance and execution zones.
🔵 CONCLUSION
Delta Volume Profile offers a unique advantage in market reading by separating buyer and seller activity into two visual layers. This allows traders to not only spot where volume was high, but also who was more aggressive. Whether you’re analyzing trend continuations, reversals, or absorption levels, this indicator gives you the transparency needed to trade with confidence.
Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI)
What is Lyapunov Market Instability?
Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes.
Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth.
Theoretical Foundation (Chaos Theory & Lyapunov Exponents)
In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories:
λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect)
λ < 0: System is stable—trajectories converge, perturbations die out
λ ≈ 0: Edge of chaos—transition between regimes
Phase Space Reconstruction
Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions:
Time-delay embedding: Create vectors from price at different lags
Nearest neighbor search: Find historically similar market states
Trajectory evolution: Track how these similar states diverged over time
Divergence rate: Calculate average exponential separation
Market Application
Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies
Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work
Transition zones: Market regime about to change, reduce position size, wait for confirmation
How LMI Works
1. Phase Space Construction
Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure.
2. Lyapunov Calculation
For each current state, we:
- Find similar historical states within epsilon (ε) distance
- Track how these initially similar states evolved
- Measure exponential divergence rate
- Average across multiple trajectories for robustness
3. Signal Generation
Chaos signals: When λ crosses above threshold, market enters trending regime
Stability signals: When λ crosses below threshold, market enters ranging regime
Divergence detection: Price/Lyapunov divergences signal potential reversals
4. Rothko Visualization
Color fields: Background zones represent market states with Rothko-inspired palettes
Glowing line: Lyapunov exponent with intensity reflecting market state
Minimalist design: Focus on essential information without clutter
Inputs:
📐 Lyapunov Parameters
Embedding Dimension (default: 3)
Dimensions for phase space reconstruction
2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns
4-5: Complex dynamics (stocks/indices) - captures intricate market structures
Higher dimensions need exponentially more data but reveal deeper patterns
Time Delay τ (default: 1)
Lag between phase space coordinates
1: High-frequency (1m-15m charts) - captures rapid market shifts
2-3: Medium frequency (1H-4H) - balances noise and signal
4-5: Low frequency (Daily+) - focuses on major regime changes
Match to your timeframe's natural cycle
Initial Separation ε (default: 0.001)
Neighborhood size for finding similar states
0.0001-0.0005: Highly liquid markets (major forex pairs)
0.0005-0.002: Normal markets (large-cap stocks)
0.002-0.01: Volatile markets (crypto, small-caps)
Smaller = more sensitive to chaos onset
Evolution Steps (default: 10)
How far to track trajectory divergence
5-10: Fast signals for scalping - quick regime detection
10-20: Balanced for day trading - reliable signals
20-30: Slow signals for swing trading - major regime shifts only
Nearest Neighbors (default: 5)
Phase space points for averaging
3-4: Noisy/fast markets - adapts quickly
5-6: Balanced (recommended) - smooth yet responsive
7-10: Smooth/slow markets - very stable signals
📊 Signal Parameters
Chaos Threshold (default: 0.05)
Lyapunov value above which market is chaotic
0.01-0.03: Sensitive - more chaos signals, earlier detection
0.05: Balanced - optimal for most markets
0.1-0.2: Conservative - only strong trends trigger
Stability Threshold (default: -0.05)
Lyapunov value below which market is stable
-0.01 to -0.03: Sensitive - quick stability detection
-0.05: Balanced - reliable ranging signals
-0.1 to -0.2: Conservative - only deep stability
Signal Smoothing (default: 3)
EMA period for noise reduction
1-2: Raw signals for experienced traders
3-5: Balanced - recommended for most
6-10: Very smooth for position traders
🎨 Rothko Visualization
Rothko Classic: Deep reds for chaos, midnight blues for stability
Orange/Red: Warm sunset tones throughout
Blue/Black: Cool, meditative ocean depths
Purple/Grey: Subtle, sophisticated palette
Visual Options:
Market Zones : Background fields showing regime areas
Transitions: Arrows marking regime changes
Divergences: Labels for price/Lyapunov divergences
Dashboard: Real-time state and trading signals
Guide: Educational panel explaining the theory
Visual Logic & Interpretation
Main Elements
Lyapunov Line: The heart of the indicator
Above chaos threshold: Market is trending, follow momentum
Below stability threshold: Market is ranging, fade extremes
Between thresholds: Transition zone, reduce risk
Background Zones: Rothko-inspired color fields
Red zone: Chaotic regime (trending)
Gray zone: Transition (uncertain)
Blue zone: Stable regime (ranging)
Transition Markers:
Up triangle: Entering chaos - start trend following
Down triangle: Entering stability - start mean reversion
Divergence Signals:
Bullish: Price makes low but Lyapunov rising (stability breaking down)
Bearish: Price makes high but Lyapunov falling (chaos dissipating)
Dashboard Information
Market State: Current regime (Chaotic/Stable/Transitioning)
Trading Bias: Specific strategy recommendation
Lyapunov λ: Raw value for precision
Signal Strength: Confidence in current regime
Last Change: Bars since last regime shift
Action: Clear trading directive
Trading Strategies
In Chaotic Regime (λ > threshold)
Follow trends aggressively: Breakouts have high success rate
Use momentum strategies: Moving average crossovers work well
Wider stops: Expect larger swings
Pyramid into winners: Trends tend to persist
In Stable Regime (λ < threshold)
Fade extremes: Mean reversion dominates
Use oscillators: RSI, Stochastic work well
Tighter stops: Smaller expected moves
Scale out at targets: Trends don't persist
In Transition Zone
Reduce position size: Uncertainty is high
Wait for confirmation: Let regime establish
Use options: Volatility strategies may work
Monitor closely: Quick changes possible
Advanced Techniques
- Multi-Timeframe Analysis
- Higher timeframe LMI for regime context
- Lower timeframe for entry timing
- Alignment = highest probability trades
- Divergence Trading
- Most powerful at regime boundaries
- Combine with support/resistance
- Use for early reversal detection
- Volatility Correlation
- Chaos often precedes volatility expansion
- Stability often precedes volatility contraction
- Use for options strategies
Originality & Innovation
LMI represents a genuine breakthrough in applying chaos theory to markets:
True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement
Rothko Aesthetic: Transforms complex math into meditative visual experience
Regime Detection: Identifies market state changes before price makes them obvious
Practical Application: Clear, actionable signals from theoretical physics
This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics.
Best Practices
Start with defaults: Parameters are optimized for broad market conditions
Match to your timeframe: Adjust tau and evolution steps
Confirm with price action: LMI shows regime, not direction
Use appropriate strategies: Chaos = trend, Stability = reversion
Respect transitions: Reduce risk during regime changes
Alerts Available
Chaos Entry: Market entering chaotic regime - prepare for trends
Stability Entry: Market entering stable regime - prepare for ranges
Bullish Divergence: Potential bottom forming
Bearish Divergence: Potential top forming
Chart Information
Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes
Academic References
Takens, F. (1981). "Detecting strange attractors in turbulence"
Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series"
Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents"
Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering.
Disclaimer
This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of chaos. Trade the regime, not the noise.
Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Sentival | QuantEdgeBIntroducing Sentival by QuantEdgeB.
An Adaptive Multi-Factor Indicator for Market Valuation & Trend Strength
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Overview
The Sentival Valuation System is a medium-term, multi-factor valuation tool designed to assess market conditions using a combination of momentum, mean reversion, and risk-adjusted metrics. It provides traders and investors with a dynamic score reflecting market valuation, ranging from strongly oversold to strongly overbought conditions.
This system leverages a diverse range of technical indicators, including momentum oscillators, volatility measures, risk ratios, and mean-reversion metrics, providing a holistic view of market conditions.
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1. Key Features
🛠 Multi-Factor Valuation Model
Sentival aggregates nine different indicators, normalizing and rescaling them into a standardized z-score-based valuation system. The final output represents an average of the selected indicators, allowing for flexible customization based on the user’s preference.
📊 Customizable Indicator Selection
Users can enable or disable any of the nine valuation factors, ensuring the system adapts to different market environments, trading styles, and assets.
🔄 Multi-Timeframe Adaptability
Sentival can be used across different time horizons, making it suitable for short-term mean reversion, medium-term traders, or long-term valuation analysis by simply adjusting the timeframe and indicator settings. This flexibility allows traders to adapt Sentival to various market conditions and trading objectives.
🎨 Intuitive Dashboard & Color Coding
- Dynamic Heatmap & Dashboard: Displays valuation strength across multiple factors.
- Gradient-Based Overbought/Oversold Signals: Clear color-coded signals for easy interpretation.
- Background Highlighting: Optional oversold/overbought background zones.
🏆 Statistical & Risk-Based Insights
- Standardized Rescaling & Z-Score Analysis to prevent bias from individual indicators.
- Risk-Adjusted Metrics such as Sharpe, Sortino, and Omega Ratios help assess the overall market risk appetite.
- Trend Following Mode (TF Display): Users can enable the "Trend Following" option to display the trend direction, helping to align valuation signals with the broader market trend.
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2. How It Works
Sentival is a multi-factor trend and momentum analysis system, designed to track market cycle shifts using a combination of volatility, momentum, risk assessment, and valuation mechanisms. Instead of focusing on one dimension of the market, Sentival integrates multiple methodologies to cross-validate signals and reduce noise. Each indicator in Sentival plays a specific role, ensuring confirmation across different market conditions.
How Each Component Works Together
1️⃣ Chande Momentum Oscillator (CMO)
• A momentum-based measure that determines whether price action is dominated by upward or downward forces.
• Works well in combination with volatility measures to confirm whether a move is sustainable.
2️⃣ Disparity Index
• Measures the distance between price and its moving average, acting as an overextension filter.
• Ensures that trend-following signals are not driven by short-term spikes but sustained trends.
3️⃣ Bollinger Bands % (BB%)
• A volatility measure that indicates how far price is from the statistical mean.
• Helps identify trend exhaustion points where price moves become unstable.
4️⃣ Relative Strength Index (RSI)
• A trend confirmation layer, ensuring that momentum strength aligns with price movement.
• Adds an additional check to prevent false breakouts.
5️⃣ Rate of Change (RoC)
• Captures the speed of price movement, ensuring that the market has enough momentum for trend continuation.
• Works well with risk indicators to filter weaker moves.
6️⃣ Price Z-Score
• A statistical tool to measure how far price is from its long-term equilibrium.
• Helps prevent entering overstretched trends too late.
7️⃣ Risk Ratios (Sharpe, Sortino, Omega)
• This is the risk-adjusted performance component, ensuring that trends have a healthy risk-reward balance.
• Helps determine when a trend has structurally strong backing rather than speculative movement.
8️⃣ Hurst Cycle Analysis
• Measures the persistence of trends by analyzing price fractals.
• Ensures that the market regime is either trending or mean-reverting, improving trade confidence.
9️⃣ Commodity Channel Index (CCI)
• Helps identify strong trend conditions, adding another layer of momentum confirmation.
• Works well with other oscillators to prevent misreading counter-trends.
🔗 Why These Components Work Well Together
• Momentum + Volatility + Risk → Instead of relying on a single category, Sentival merges multiple dimensions of market behavior into a cohesive signal.
• Filters Out False Signals → Combining momentum oscillators, volatility measures, and risk-adjusted metrics ensures high-confidence entries.
• Adaptability Across Market Regimes → Whether the market is trending, consolidating, or volatile, the system adjusts dynamically.
• Cross-Validation for Trend Strength → If multiple components align, it increases certainty that a trend is real and sustainable.
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3. Sentival Scanner - table breakdown
The dashboard-style table generated is designed to give traders a holistic market view at a glance. It processes a variety of technical signals and distills them into readable labels, visual strength bars, and actionable trend states. Here's a breakdown of what each section means:
1. Direction
This section analyzes whether the average Z-score (a composite of several indicators) is increasing, decreasing, or neutral over time. It does this using a smoothed trend of the Z-score, comparing recent values to older ones.
2. Momentum
Momentum is derived from the rate of change (RoC) of the average Z-score. It evaluates how strong the current move is. If momentum is above a certain positive threshold, it’s considered positive, if below a negative threshold, it’s negative, otherwise it’s neutral.
3. Impulse
Impulse reflects the velocity of momentum — in other words, is the market speeding up or slowing down? High positive values suggest strong acceleration (strong impulse), while negative values show deceleration or stalling.
4. Drive
This metric combines momentum and velocity to create a descriptive phrase that captures the market’s behavior. For example:
• “Strong Upside” means strong momentum with acceleration.
• “Fading Downside” means bearish momentum losing steam.
• “Neutral” appears when momentum is indecisive.
5. Deviation Distance
This represents how far the market price is from fair value in terms of standard deviation units (σ). It’s calculated using Z-scores and classified as:
• +1σ, +2σ, etc., for overvalued regions.
• −1σ, −2σ, etc., for undervalued areas.
• “At Fair Value” if close to the mean.
6. Bull and Bear Strength Bars
The system computes both bullish and bearish strength, using distance from fair value, the rate of change, and the velocity. These strengths are displayed as progress bars, giving a quick visual cue of conviction. The table labels them as:
• “Bull Conviction” if there's a long bias.
• “Bull Potential” if bullish but undecided.
• “Bear Conviction” or “Bear Potential” for short-side equivalents.
7. Trend Signal
This is a simple label that tells you if the scanner recommends a Long, Short, or Cash (neutral) stance based on threshold logic. It is based on whether the average Z-score crosses above a long threshold or below a short one.
8. Stage
The “Stage” label summarizes the valuation environment based on the composite Z-score:
• Strong Undervalued
• Moderately Undervalued
• Fair Value
• Overvalued, etc.
This stage helps traders know whether they are operating in cheap or expensive territory statistically.
Summary
Overall, this table merges advanced technical signals like momentum, volatility, valuation, and risk into a digestible format that updates dynamically with each bar. The goal is to provide traders with a 360° perspective on market conditions, tailored for both trend-following and mean-reversion strategies.
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4. Sentival Valuation Score & Interpretation
🔹 Sentival Score Ranges
- 📉 Strongly Oversold (-2 and below) → Market is extremely undervalued; potential reversal.
- 📉 Moderately Oversold (-1.5 to -2) → Discounted market conditions, buying interest may emerge.
- 📉 Slightly Oversold (-0.5 to -1.5) → Possible accumulation phase.
- ⚖ Fair Value (-0.5 to +0.5) → Market trading at equilibrium.
- 📈 Slightly Overbought (+0.5 to +1.5) → Initial signs of market strength.
- 📈 Moderately Overbought (+1.5 to +2) → Market heating up, caution warranted, selling interest may emerge.
- 📈 Strongly Overbought (+2 and above) → Extreme valuation, increased risk of correction.
This classification helps traders gauge overall market sentiment and make better allocation decisions.
Note: Past valuations and buy/sell signals generated by Sentival do not guarantee future performance. Market conditions can change, and proper risk management should always be applied.
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5. Use Cases & Applications
🔹 📊 Market Rotation & Asset Allocation
- Used as a valuation model to determine if a market or asset is undervalued or overvalued.
- Rotational strategies can benefit from the valuation score by switching exposure between assets.
🔹 📈 Medium-Term Trend Identification
- Detects overbought and oversold conditions while filtering out short-term noise.
- Can be combined with other trend-following indicators for confluence-based strategies.
🔹 🔄 Mean Reversion & Momentum Trading
- Provides statistical validation for momentum breakouts or mean reversion signals.
- Useful for long-short trading strategies, determining optimal entry & exit points.
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Conclusion
Sentival is a powerful universal valuation system for traders and investors seeking a data-driven, multi-factor approach to market valuation. With its combination of momentum, trend, risk-adjusted, and mean-reversion indicators, it provides a robust, adaptable, and statistically sound framework for making informed market decisions.
🔹 Who Should Use Sentival?
✅ Swing Traders & Medium-Term Investors looking for structured valuation metrics.
✅ Quantitative & Systematic Traders incorporating multi-factor models.
✅ Portfolio Managers optimizing exposure to different market regimes.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
