Machine Learning Momentum Index (MLMI) [Zeiierman]█ Overview
The Machine Learning Momentum Index (MLMI) represents the next step in oscillator trading. By blending traditional momentum analysis with machine learning, MLMI delivers a potent and dynamic tool that aligns with the complexities of modern financial landscapes. Offering traders an adaptive way to understand and act on market momentum and trends, this oscillator provides real-time insights into market momentum and prevailing trends.
█ How It Works:
Momentum Analysis: MLMI employs a dual-layer analysis, utilizing quick and slow weighted moving averages (WMA) of the Relative Strength Index (RSI) to gauge the market's momentum and direction.
Machine Learning Integration: Through the k-Nearest Neighbors (k-NN) algorithm, MLMI intelligently examines historical data to make more accurate momentum predictions, adapting to the intricate patterns of the market.
MLMI's precise calculation involves:
Weighted Moving Averages: Calculations of quick (5-period) and slow (20-period) WMAs of the RSI to track short-term and long-term momentum.
k-Nearest Neighbors Algorithm: Distances between current parameters and previous data are measured, and the nearest neighbors are used for predictive modeling.
Trend Analysis: Recognition of prevailing trends through the relationship between quick and slow-moving averages.
█ How to use
The Machine Learning Momentum Index (MLMI) can be utilized in much the same way as traditional trend and momentum oscillators, providing key insights into market direction and strength. What sets MLMI apart is its integration of artificial intelligence, allowing it to adapt dynamically to market changes and offer a more nuanced and responsive analysis.
Identifying Trend Direction and Strength: The MLMI serves as a tool to recognize market trends, signaling whether the momentum is upward or downward. It also provides insights into the intensity of the momentum, helping traders understand both the direction and strength of prevailing market trends.
Identifying Consolidation Areas: When the MLMI Prediction line and the WMA of the MLMI Prediction line become flat/oscillate around the mid-level, it's a strong sign that the market is in a consolidation phase. This insight from the MLMI allows traders to recognize periods of market indecision.
Recognizing Overbought or Oversold Conditions: By identifying levels where the market may be overbought or oversold, MLMI offers insights into potential price corrections or reversals.
█ Settings
Prediction Data (k)
This parameter controls the number of neighbors to consider while making a prediction using the k-Nearest Neighbors (k-NN) algorithm. By modifying the value of k, you can change how sensitive the prediction is to local fluctuations in the data.
A smaller value of k will make the prediction more sensitive to local variations and can lead to a more erratic prediction line.
A larger value of k will consider more neighbors, thus making the prediction more stable but potentially less responsive to sudden changes.
Trend length
This parameter controls the length of the trend used in computing the momentum. This length refers to the number of periods over which the momentum is calculated, affecting how quickly the indicator reacts to changes in the underlying price movements.
A shorter trend length (smaller momentumWindow) will make the indicator more responsive to short-term price changes, potentially generating more signals but at the risk of more false alarms.
A longer trend length (larger momentumWindow) will make the indicator smoother and less responsive to short-term noise, but it may lag in reacting to significant price changes.
Please note that the Machine Learning Momentum Index (MLMI) might not be effective on higher timeframes, such as daily or above. This limitation arises because there may not be enough data at these timeframes to provide accurate momentum and trend analysis. To overcome this challenge and make the most of what MLMI has to offer, it's recommended to use the indicator on lower timeframes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
ค้นหาในสคริปต์สำหรับ "relative strength"
Improved Scalping Consolidation and Squeeze IndicatorThe Improved Scalping Consolidation and Squeeze Indicator (Improved Scalp C&S) is a custom TradingView indicator designed for short-term trading, specifically scalping. It detects price consolidation and potential breakout scenarios using a combination of technical analysis tools, such as the Rate of Change (ROC), Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands, and Keltner Channels. To reduce the number of false signals, this improved version introduces a "consolidation strength" parameter, which represents the minimum number of consecutive bars required for a valid consolidation or squeeze signal.
How it works:
Consolidation Detection:
The indicator identifies price consolidation when the following conditions are met:
a. RSI is between 45 and 55, indicating a lack of strong momentum.
b. The absolute value of the MACD histogram is less than 0.1% of the closing price, suggesting a lack of directional movement.
c. The Rate of Change (ROC) is less than 1.5%, indicating relatively stable prices over the specified period.
Squeeze Detection:
The indicator detects a squeeze (a potential breakout scenario) when the Bollinger Bands are within the Keltner Channels, represented by the following conditions:
a. The lower Bollinger Band is above the lower Keltner Channel.
b. The upper Bollinger Band is below the upper Keltner Channel.
Consolidation Strength:
The consolidation strength parameter filters out weaker signals by requiring a minimum number of consecutive bars for a valid consolidation or squeeze signal. By adjusting this parameter, traders can control the sensitivity of the indicator to short-term price movements and potentially reduce the number of false signals.
When the consolidation strength criteria are met, the indicator colors the price bars within the pattern yellow for consolidation and orange for a squeeze, signaling potential trading opportunities.
Trading Strategy:
The Improved Scalping Consolidation and Squeeze Indicator can be used in various ways, depending on the trader's strategy and risk appetite. Here are some suggestions:
Range trading: During consolidation (yellow bars), traders can buy at support levels and sell at resistance levels within the range, using stop-loss orders to manage risk. However, this approach might not work well in the case of a sudden breakout.
Breakout trading: When a squeeze is detected (orange bars), traders can wait for a confirmed breakout from the consolidation pattern before entering a trade. A breakout can be confirmed by a strong price move accompanied by increased volume, a significant change in momentum, or a breach of important support or resistance levels.
Momentum-based strategies: Traders can use other momentum-based indicators (e.g., Stochastic Oscillator, On Balance Volume) in conjunction with the Improved Scalp C&S indicator to identify potential entry and exit points during consolidation or breakout scenarios.
Fine-tuning the consolidation strength: Adjust the "consolidation strength" input to find the optimal balance between the number of signals and their accuracy. A higher value will result in fewer signals, potentially reducing the number of false signals, but it may also make the indicator less sensitive to short-term price movements.
Full Currency Strength Table Dashboard (8 Currencies)
# Full Currency Strength Table Dashboard (8 Currencies) 📊
This indicator provides a **simplified, visual representation of the current relative strengths of 8 major global currencies** (EUR, USD, GBP, JPY, AUD, NZD, CAD, CHF). It's designed as a minimalist dashboard that appears discreetly on your chart, giving traders a quick and clear picture of forex pair movements.
The indicator calculates the relative strength of each currency based on its movement against the other 7 currencies in the panel, providing insight into which currencies are currently the strongest and which are the weakest.
## Key Features 🌟
* **Simplified Visualization:** Instead of showing currency strength as a line on the chart, which can often be distracting, the indicator uses a **data table (dashboard)** positioned on the chart. This ensures **maximum chart visibility** and cleanliness.
* **8 Major Currencies:** All major currencies are included ($A$ - EUR, $B$ - USD, $C$ - GBP, $D$ - JPY, $E$ - AUD, $F$ - NZD, $G$ - CAD, $H$ - CHF), allowing strength calculation based on **28 base currency pairs**.
* **Strength Calculation:** Strength is calculated based on the average percentage change $\left(\frac{\text{Close} - \text{Open}}{\text{Open}} \times 100\right)$ of the currency relative to all 7 other currencies.
* **Timeframe Setting:** Users can select a **higher timeframe (TF)** (e.g., Daily - 'D') for the strength calculation. This allows analysis of longer-term currency strength momentum, independent of the chart's current timeframe.
* **Customizable Design:** You can adjust the table's position, text size, the colour of each currency, and the resolution (length) of the strength meter.
## How to Use the Indicator (Interpretation) 💡
1. **Select a Timeframe (TF):** It's recommended to use a higher TF (e.g., Daily - 'D' or 4h - '240') to get more stable currency strength signals.
2. **The Dashboard Table:** The table displays:
* The currency name (bottom, with its corresponding colour).
* The numerical strength value (top, expressed in points or average change).
* The **Strength Meter (bar)** visually represents the currency's relative strength compared to the other currencies on the panel (calculated based on the Min/Max values across all 8 currencies).
3. **Making Decisions:**
* **Buy:** Look for a currency pair where the **Base Currency** is significantly **strong** (high positive value, long meter) and the **Quote Currency** is significantly **weak** (high negative value, short meter).
* **Sell:** Look for a currency pair where the **Base Currency** is significantly **weak** and the **Quote Currency** is significantly **strong**.
* **Avoid Trading:** Avoid pairs where both currencies have roughly the same strength or are close to zero.
## Note on Calculation and Code 🛠️
* **Base Pairs:** The script calculates 28 base currency pairs (e.g., EURUSD, EURGBP... CADCHF) using the `request.security` function to retrieve data from the selected timeframe (`freq`).
* **Data Correction:** A correction was implemented in the code by adding ` ` after `request.security` to always use the **CLOSED bar values** from the higher TF. This **eliminates NaN (Not a Number) data** that would appear when using the current bar.
* **Accumulation:** Accumulation (`sumA, sumB...`) only occurs when the selected higher TF changes (`timeframe.change(freq)`), effectively tracking the currency's relative strength during the formation of **one closed bar** on that higher TF.
### License
This work is licensed under the **Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)** license.
The original concept and code are based on the work of the **LuxAlgo** team and finalized to fix syntax errors and handle NaN data for stable use with 8 currencies.
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**Questions or suggestions?** I'd love to hear your feedback in the comments! Happy trading! 📈
RSI Donchian Channel [DCAUT]█ RSI Donchian Channel
📊 ORIGINALITY & INNOVATION
The RSI Donchian Channel represents an important synthesis of two complementary analytical frameworks: momentum oscillators and breakout detection systems. This indicator addresses a common limitation in traditional RSI analysis by replacing fixed overbought/oversold thresholds with adaptive zones derived from historical RSI extremes.
Key Enhancement:
Traditional RSI analysis relies on static threshold levels (typically 30/70), which may not adequately reflect changing market volatility regimes. This indicator adapts the reference zones dynamically based on the actual RSI behavior over the lookback period, helping traders identify meaningful momentum extremes relative to recent price action rather than arbitrary fixed levels.
The implementation combines the proven momentum measurement capabilities of RSI with Donchian Channel's breakout detection methodology, creating a framework that identifies both momentum exhaustion points and potential continuation signals through the same analytical lens.
📐 MATHEMATICAL FOUNDATION
Core Calculation Process:
Step 1: RSI Calculation
The Relative Strength Index measures momentum by comparing the magnitude of recent gains to recent losses:
Calculate price changes between consecutive periods
Separate positive changes (gains) from negative changes (losses)
Apply selected smoothing method (RMA standard, also supports SMA, EMA, WMA) to both gain and loss series
Compute Relative Strength (RS) as the ratio of smoothed gains to smoothed losses
Transform RS into bounded 0-100 scale using the formula: RSI = 100 - (100 / (1 + RS))
Step 2: Donchian Channel Application
The Donchian Channel identifies the highest and lowest RSI values within the specified lookback period:
Upper Channel: Highest RSI value over the lookback period, represents the recent momentum peak
Lower Channel: Lowest RSI value over the lookback period, represents the recent momentum trough
Middle Channel (Basis): Average of upper and lower channels, serves as equilibrium reference
Channel Width Dynamics:
The distance between upper and lower channels reflects RSI volatility. Wide channels indicate high momentum variability, while narrow channels suggest momentum consolidation and potential breakout preparation. The indicator monitors channel width over a 100-period window to identify squeeze conditions that often precede significant momentum shifts.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Primary Signal Categories:
Breakout Signals:
Upper Breakout: RSI crosses above the upper channel, indicates momentum reaching new relative highs and potential trend continuation, particularly significant when accompanied by price confirmation
Lower Breakout: RSI crosses below the lower channel, suggests momentum reaching new relative lows and potential trend exhaustion or reversal setup
Breakout strength is enhanced when the channel is narrow prior to the breakout, indicating a transition from consolidation to directional movement
Mean Reversion Signals:
Upper Touch Without Breakout: RSI reaches the upper channel but fails to break through, may indicate momentum exhaustion and potential reversal opportunity
Lower Touch Without Breakout: RSI reaches the lower channel without breakdown, suggests potential bounce as momentum reaches oversold extremes
Return to Basis: RSI moving back toward the middle channel after touching extremes signals momentum normalization
Trend Strength Assessment:
Sustained Upper Channel Riding: RSI consistently remains near or above the upper channel during strong uptrends, indicates persistent bullish momentum
Sustained Lower Channel Riding: RSI stays near or below the lower channel during strong downtrends, reflects persistent bearish pressure
Basis Line Position: RSI position relative to the middle channel helps identify the prevailing momentum bias
Channel Compression Patterns:
Squeeze Detection: Channel width narrowing to 100-period lows indicates momentum consolidation, often precedes significant directional moves
Expansion Phase: Channel widening after a squeeze confirms the initiation of a new momentum regime
Persistent Narrow Channels: Extended periods of tight channels suggest market indecision and accumulation/distribution phases
🎯 STRATEGIC APPLICATIONS
Trend Continuation Strategy:
This approach focuses on identifying and trading momentum breakouts that confirm established trends:
Identify the prevailing price trend using higher timeframe analysis or trend-following indicators
Wait for RSI to break above the upper channel in uptrends (or below the lower channel in downtrends)
Enter positions in the direction of the breakout when price action confirms the momentum shift
Place protective stops below the recent swing low (long positions) or above swing high (short positions)
Target profit levels based on prior swing extremes or use trailing stops to capture extended moves
Exit when RSI crosses back through the basis line in the opposite direction
Mean Reversion Strategy:
This method capitalizes on momentum extremes and subsequent corrections toward equilibrium:
Monitor for RSI reaching the upper or lower channel boundaries
Look for rejection signals (price reversal patterns, volume divergence) when RSI touches the channels
Enter counter-trend positions when RSI begins moving back toward the basis line
Use the basis line as the initial profit target for mean reversion trades
Implement tight stops beyond the channel extremes to limit risk on failed reversals
Scale out of positions as RSI approaches the basis line and closes the position when RSI crosses the basis
Breakout Preparation Strategy:
This approach positions traders ahead of potential volatility expansion from consolidation phases:
Identify squeeze conditions when channel width reaches 100-period lows
Monitor price action for consolidation patterns (triangles, rectangles, flags) during the squeeze
Prepare conditional orders for breakouts in both directions from the consolidation
Enter positions when RSI breaks out of the narrow channel with expanding width
Use the channel width expansion as a confirmation signal for the breakout's validity
Manage risk with stops just inside the opposite channel boundary
Multi-Timeframe Confluence Strategy:
Combining RSI Donchian Channel analysis across multiple timeframes can improve signal reliability:
Identify the primary trend direction using a higher timeframe RSI Donchian Channel (e.g., daily or weekly)
Use a lower timeframe (e.g., 4-hour or hourly) to time precise entry points
Enter long positions when both timeframes show RSI above their respective basis lines
Enter short positions when both timeframes show RSI below their respective basis lines
Avoid trades when timeframes provide conflicting signals (e.g., higher timeframe below basis, lower timeframe above)
Exit when the higher timeframe RSI crosses its basis line in the opposite direction
Risk Management Guidelines:
Effective risk management is essential for all RSI Donchian Channel strategies:
Position Sizing: Calculate position sizes based on the distance between entry point and stop loss, limiting risk to 1-2% of capital per trade
Stop Loss Placement: For breakout trades, place stops just inside the opposite channel boundary; for mean reversion trades, use stops beyond the channel extremes
Profit Targets: Use the basis line as a minimum target for mean reversion trades; for trend trades, target prior swing extremes or use trailing stops
Channel Width Context: Increase position sizes during narrow channels (lower volatility) and reduce sizes during wide channels (higher volatility)
Correlation Awareness: Monitor correlations between traded instruments to avoid over-concentration in similar setups
📋 DETAILED PARAMETER CONFIGURATION
RSI Source:
Defines the price data series used for RSI calculation:
Close (Default): Standard choice providing end-of-period momentum assessment, suitable for most trading styles and timeframes
High-Low Average (HL2): Reduces the impact of closing auction dynamics, useful for markets with significant end-of-day volatility
High-Low-Close Average (HLC3): Provides a more balanced view incorporating the entire period's range
Open-High-Low-Close Average (OHLC4): Offers the most comprehensive price representation, helpful for identifying overall period sentiment
Strategy Consideration: Use Close for end-of-period signals, HL2 or HLC3 for intraday volatility reduction, OHLC4 for capturing full period dynamics
RSI Length:
Controls the number of periods used for RSI calculation:
Short Periods (5-9): Highly responsive to recent price changes, produces more frequent signals with increased false signal risk, suitable for short-term trading and volatile markets
Standard Period (14): Widely accepted default balancing responsiveness with stability, appropriate for swing trading and intermediate-term analysis
Long Periods (21-28): Produces smoother RSI with fewer signals but more reliable trend identification, better for position trading and reducing noise in choppy markets
Optimization Approach: Test different lengths against historical data for your specific market and timeframe, consider using longer periods in ranging markets and shorter periods in trending markets
RSI MA Type:
Determines the smoothing method applied to price changes in RSI calculation:
RMA (Relative Moving Average - Default): Wilder's original smoothing method providing stable momentum measurement with gradual response to changes, maintains consistency with classical RSI interpretation
SMA (Simple Moving Average): Treats all periods equally, responds more quickly to changes than RMA but may produce more whipsaws in volatile conditions
EMA (Exponential Moving Average): Weights recent periods more heavily, increases responsiveness at the cost of potential noise, suitable for traders prioritizing early signal generation
WMA (Weighted Moving Average): Applies linear weighting favoring recent data, offers a middle ground between SMA and EMA responsiveness
Selection Guidance: Maintain RMA for consistency with traditional RSI analysis, use EMA or WMA for more responsive signals in fast-moving markets, apply SMA for maximum simplicity and transparency
DC Length:
Specifies the lookback period for Donchian Channel calculation on RSI values:
Short Periods (10-14): Creates tight channels that adapt quickly to changing momentum conditions, generates more frequent trading signals but increases sensitivity to short-term RSI fluctuations
Standard Period (20): Balances channel responsiveness with stability, aligns with traditional Bollinger Bands and moving average periods, suitable for most trading styles
Long Periods (30-50): Produces wider, more stable channels that better represent sustained momentum extremes, reduces signal frequency while improving reliability, appropriate for position traders and higher timeframes
Calibration Strategy: Match DC length to your trading timeframe (shorter for day trading, longer for swing trading), test channel width behavior during different market regimes, consider using adaptive periods that adjust to volatility conditions
Market Adaptation: Use shorter DC lengths in trending markets to capture momentum shifts earlier, apply longer periods in ranging markets to filter noise and focus on significant extremes
Parameter Combination Recommendations:
Scalping/Day Trading: RSI Length 5-9, DC Length 10-14, EMA or WMA smoothing for maximum responsiveness
Swing Trading: RSI Length 14, DC Length 20, RMA smoothing for balanced analysis (default configuration)
Position Trading: RSI Length 21-28, DC Length 30-50, RMA or SMA smoothing for stable signals
High Volatility Markets: Longer RSI periods (21+) with standard DC length (20) to reduce noise
Low Volatility Markets: Standard RSI length (14) with shorter DC length (10-14) to capture subtle momentum shifts
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Adaptive Threshold Mechanism:
Unlike traditional RSI analysis with fixed 30/70 thresholds, this indicator's Donchian Channel approach provides several improvements:
Context-Aware Extremes: Overbought/oversold levels adjust automatically based on recent momentum behavior rather than arbitrary fixed values
Volatility Adaptation: In low volatility periods, channels narrow to reflect tighter momentum ranges; in high volatility, channels widen appropriately
Market Regime Recognition: The indicator implicitly adapts to different market conditions without manual threshold adjustments
False Signal Reduction: Adaptive channels help reduce premature reversal signals that often occur with fixed thresholds during strong trends
Signal Quality Characteristics:
The indicator's dual-purpose design provides distinct advantages for different trading objectives:
Breakout Trading: Channel boundaries offer clear, objective breakout levels that update dynamically, eliminating the ambiguity of when momentum becomes "too high" or "too low"
Mean Reversion: The basis line provides a natural profit target for reversion trades, representing the midpoint of recent momentum extremes
Trend Strength: Persistent channel boundary riding offers an objective measure of trend strength without additional indicators
Consolidation Detection: Channel width analysis provides early warning of potential volatility expansion from compression phases
Comparative Analysis:
When compared to traditional RSI implementations and other momentum frameworks:
vs. Fixed Threshold RSI: Provides market-adaptive reference levels rather than static values, helping to reduce false signals during trending markets where RSI can remain "overbought" or "oversold" for extended periods
vs. RSI Bollinger Bands: Offers clearer breakout signals and more intuitive extreme identification through actual high/low boundaries rather than statistical standard deviations
vs. Stochastic Oscillator: Maintains RSI's momentum measurement advantages (unbounded calculation avoiding scale compression) while adding the breakout detection capabilities of Donchian Channels
vs. Standard Donchian Channels: Applies breakout methodology to momentum space rather than price, providing earlier signals of potential trend changes before price breakouts occur
Performance Characteristics:
The indicator exhibits specific behavioral patterns across different market conditions:
Trending Markets: Excels at identifying momentum continuation through channel breakouts, RSI tends to ride one channel boundary during strong trends, providing trend confirmation
Ranging Markets: Channel width narrows during consolidation, offering early preparation signals for potential breakout trading opportunities
High Volatility: Channels widen to reflect increased momentum variability, automatically adjusting signal sensitivity to match market conditions
Low Volatility: Channels contract, making the indicator more sensitive to subtle momentum shifts that may be significant in calm market environments
Transition Periods: Channel squeezes often precede major trend changes, offering advance warning of potential regime shifts
Limitations and Considerations:
Users should be aware of certain operational characteristics:
Lookback Dependency: Channel boundaries depend entirely on the lookback period, meaning the indicator has no predictive element beyond identifying current momentum relative to recent history
Lag Characteristics: As with all moving average-based indicators, RSI calculation introduces lag, and channel boundaries update only as new extremes occur within the lookback window
Range-Bound Sensitivity: In extremely tight ranges, channels may become very narrow, potentially generating excessive signals from minor momentum fluctuations
Trending Persistence: During very strong trends, RSI may remain at channel extremes for extended periods, requiring patience for mean reversion setups or commitment to trend-following approaches
No Absolute Levels: Unlike traditional RSI, this indicator provides no fixed reference points (like 50), making it less suitable for strategies that depend on absolute momentum readings
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to help traders understand momentum dynamics and identify potential trading opportunities. The RSI Donchian Channel has limitations and should not be used as the sole basis for trading decisions.
Important considerations:
Performance varies significantly across different market conditions, timeframes, and instruments
Historical signal patterns do not guarantee future results, as market behavior continuously evolves
Effective use requires understanding of both RSI momentum principles and Donchian Channel breakout concepts
Risk management practices (stop losses, position sizing, diversification) are essential for any trading application
Consider combining with additional analytical tools such as volume analysis, price action patterns, or trend indicators for confirmation
Backtest thoroughly on your specific instruments and timeframes before live trading implementation
Be aware that optimization on historical data may lead to curve-fitting and poor forward performance
The indicator performs best when used as part of a comprehensive trading methodology that incorporates multiple forms of market analysis, sound risk management, and realistic expectations about win rates and drawdowns.
Relative Performance Indicator - TrendSpider StyleRelative Performance Indicator - TrendSpider Style
📈 Overview
This Relative Performance (RP) indicator measures how your stock is performing compared to a benchmark index, displayed as a percentile ranking from 0-100. Based on TrendSpider's methodology, it answers the critical question: "Is this stock a leader or a laggard?"
Unlike simple ratio charts, this indicator uses percentile ranking to normalize relative performance, making it easy to identify when a stock is showing exceptional strength (>80) or concerning weakness (<20) compared to its historical relationship with the benchmark.
✨ Key Features
Three Calculation Modes:
Quarterly: 3-month relative performance for swing trading
Yearly: Weighted 4-quarter performance for position trading
TechRank: Composite of 6 technical indicators for multi-factor analysis
Clean Visual Design:
Green fills above 80 (strong outperformance)
Red fills below 20 (significant underperformance)
Dotted median line at 50 for quick reference
Current value label for instant reading
Flexible Benchmarks:
Compare against major indices (SPY, QQQ, IWM)
Sector ETFs for within-sector analysis
Custom symbols for specialized comparisons
Built-in Alerts:
Strong performance zone entry (>80)
Weak performance zone entry (<20)
Median crossovers (50 level)
📊 How To Use
Buy Signals:
RP crosses above 80: Stock entering leadership status
RP holding above 60: Maintaining relative strength
RP rising while price consolidating: Accumulation phase
Sell/Avoid Signals:
RP drops below 50: Losing relative strength
RP below 20: Significant underperformance
RP falling while price rising: Bearish divergence
Sector Rotation:
Compare multiple assets to find strongest sectors
Rotate into high RP assets (>70)
Exit low RP positions (<30)
🎯 Reading The Values
80-100: Exceptional outperformance - Strong buy/hold
60-80: Moderate outperformance - Hold positions
40-60: Market perform - No edge
20-40: Underperformance - Caution/reduce
0-20: Severe underperformance - Avoid/exit
⚙️ Calculation Method
Calculates percentage performance of both your stock and the benchmark
Finds the performance differential
Ranks this differential against historical values using percentile analysis
Normalizes to 0-100 scale for easy interpretation
This percentile approach adapts to different market conditions and volatility regimes, providing consistent signals whether in trending or choppy markets.
💡 Pro Tips
For Growth Stocks: Use quarterly mode with QQQ as benchmark
For Value Stocks: Use yearly mode with SPY as benchmark
For Small Caps: Compare against IWM, not SPY
For Sector Analysis: Use sector ETFs (XLK, XLF, XLE, etc.)
Combine with Price Action: High RP + price breakout = powerful signal
⚠️ Important Notes
RP is relative, not absolute - stocks can fall with high RP if the market falls harder
Choose appropriate benchmarks for meaningful comparisons
Best used in conjunction with price action and volume analysis
Historical lookback period affects sensitivity (adjustable in settings)
🔧 Customization
Fully customizable visual settings, thresholds, calculation periods, and smoothing options. Adjust the normalization lookback period (default 252 days) to fine-tune sensitivity to your trading timeframe.
📌 Credit
Inspired by TrendSpider's Relative Performance implementation, adapted for TradingView with enhanced customization options and Pine Script v6 optimization.
Tags to include: relativeperformance, relativestrength, percentile, ranking, sectorrotation, benchmark, outperformance, trendspider, marketbreadth, strengthindicator
Category: Momentum Indicators / Trend Analysis
Feel free to modify this description to match your style or add any specific points you want to emphasize!
Dual Custom Index with SpreadDual Custom Index with Spread
Create powerful custom indices from any instruments and analyze their relative strength dynamics
Overview
This advanced indicator allows you to build two completely customizable indices from your choice of instruments and analyze their spread relationship. Perfect for inter-market analysis, sector rotation strategies, currency strength comparisons, and sophisticated relative performance studies.
Key Features
🔧 Fully Customizable Index Construction
Build each index from up to 6 instruments with individual weightings
Enable/disable instruments on the fly without losing settings
Automatic weight validation ensures mathematically accurate calculations
Invert functionality for instruments that move opposite to index strength
📊 Advanced ADX-Based Methodology
Uses sophisticated ADX +DI/-DI directional bias calculations
Normalized bias calculation for consistent scaling across different instruments
Optimized default settings for intraday trading with full customization options
Professional-grade smoothing and filtering options
📈 Dual Analysis Modes
Difference Mode: Shows absolute strength difference (Index1 - Index2)
Ratio Mode: Shows relative performance ratio (Index1 / Index2)
Additional spread smoothing for cleaner signals
🎨 Professional Display Options
Custom labels with full color, size, and positioning control
Dynamic "Follow Line" labels that move with your data
Static corner positioning for reference displays
Clean error messaging and validation feedback
Use Cases
Gold Trading: Create gold strength vs USD strength indices for precise market timing
Sector Analysis: Compare technology vs financial sector strength for rotation strategies
Currency Strength: Build custom currency baskets for advanced forex analysis
Commodity Spreads: Analyze relative strength between different commodity groups
Regional Markets: Compare strength between different geographical market indices
Crypto Analysis: Track relative performance between different cryptocurrency sectors
Technical Specifications
Instruments per Index: Up to 6 with individual enable/disable
Weight Validation: Automatic 100% total weight enforcement
Calculation Method: ADX-based directional bias with trend strength weighting
Smoothing Options: Multiple levels of customizable smoothing
Error Handling: Professional validation with clear user feedback
Optimization Tips
Intraday Trading: Use DI Length 3-7 for faster response
Daily Analysis: Use DI Length 10-14 for smoother signals
Noisy Markets: Increase Final Smoothing for cleaner signals
Trending Markets: Lower smoothing values for faster reaction
Perfect for traders who need sophisticated inter-market analysis tools beyond standard indicators. Whether you're analyzing gold vs dollar dynamics, sector rotation opportunities, or custom currency strength relationships, this indicator provides institutional-grade analysis capabilities with complete customization flexibility.
MB - Currency Strength ROCCurrency Strength ROC Enhanced is a technical indicator designed to measure and visualize the relative strength of different currencies in the foreign exchange market. Using a Rate of Change (ROC) approach and moving averages, this indicator provides valuable insights into the dynamics of currency strengths.
Key Features:
Relative Strength Measurement:
Calculates the strength of each currency relative to others, allowing you to identify which currencies are appreciating or depreciating.
Strength Histogram:
Presents normalized strength in a histogram format, making it easy to quickly see areas of positive (green) and negative (red) strength
Moving Averages:
Includes moving averages of normalized strength and trend, providing a clear view of the overall direction of strength over time.
Overbought and Oversold Zones:
Highlights critical levels of strength through horizontal lines, allowing traders to identify potential trend reversals.
Gaussian RSI For Loop [TrendX_]The Gaussian RSI For Loop indicator is a sophisticated tool designed for trend-following traders seeking to identify strong uptrends in the market. By integrating a Gaussian and Weighted-MA (GWMA) with the Relative Strength Index (RSI), this indicator employs a loop-based scoring system to provide clear signals for potential trading opportunities. The combination of Gaussian smoothing techniques and overbought/oversold filtering enhances the indicator's ability to capture significant price movements while reducing noise, making it an optimal choice for traders aiming to capitalize on robust upward trends.
💎 KEY FEATURES
Gaussian Weighted Moving Average (GWMA): Smooths price data to reduce noise and enhance responsiveness to significant price changes.
Filtered RSI: Applies the RSI to Gaussian-filtered data, allowing for more accurate momentum readings.
Wavetrend Analysis: Calculates the difference between the Filtered RSI and its short-term moving average, providing additional insights into momentum shifts.
Loop-Based Scoring System: Evaluates the strength and direction of uptrends through a systematic analysis of the Filtered RSI against defined thresholds.
⚙️ USAGES
Identifying Strong Uptrends: Traders can use this indicator to pinpoint periods of strong upward momentum, helping them make informed decisions about entering long positions and its exits.
Trend and Signal Confirmation: The Score confirms Long and Exit signals which traders can see through the Dots on the Gaussian RSI.
🔎 BREAKDOWN
Gaussian-Filtered Data:
The first component of the Gaussian RSI For Loop is the application of a GWMA to the sourced price data. This smoothing technique uses weighted averages based on a Gaussian distribution, which emphasizes more recent prices while diminishing the impact of older prices. This GWMA effectively reduces market noise, allowing traders to focus on significant price movements. By adjusting weights using sigma parameters, traders can fine-tune the sensitivity of the indicator, making it more responsive to genuine market trends while filtering out minor fluctuations that could lead to misleading signals.
Filtered RSI:
Next, the RSI is applied to the Gaussian-filtered data. The RSI measures the speed and change of price movements, providing insights into overbought or oversold conditions. By applying the RSI to smoothed price data, traders obtain a clearer view of momentum without the distortion caused by sudden price spikes or drops. This results in more reliable readings that help identify potential trend reversals or continuations.
Wavetrend Analysis:
The Wavetrend component calculates the difference between the Filtered RSI and its short-term moving average (MA). This difference serves as an additional momentum indicator. When the Filtered RSI is above its short-term MA, it suggests that upward momentum is strengthening; conversely, when it falls below, it indicates weakening momentum. This analysis helps traders confirm whether an uptrend is gaining strength or losing traction.
Loop-Based Scoring System:
Range Analysis: The system evaluates the Filtered RSI by comparing its current value against overbought (OB) and oversold (OS) thresholds over a defined range. This systematic approach ensures that each value within this range contributes to understanding overall trend strength.
Score Calculation: As the loop iterates through values within the defined range, it adjusts a score based on whether the current Filtered RSI and its previous values are higher or lower than established OB and OS levels. This scoring mechanism quantifies trend strength and direction.
Strong Uptrend Trigger: A strong uptrend signal is generated when the score exceeds a predefined Score Threshold (Long). This indicates that bullish momentum is robust enough to warrant entry into long positions.
None Trend: Conversely, if the score falls below the Score Threshold (Short), it suggests that upward momentum has weakened significantly, signaling potential exit points and it can be consolidated or downtrend.
DISCLAIMER
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur. Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Multi-Market Correlation Explorer [kikfraben]Multi-Market Correlation Explorer
The Multi-Market Correlation Explorer (MMCE) is a powerful tool designed to provide insights into the correlations and relative strength of various financial instruments across different markets. This indicator allows traders and investors to assess the intermarket relationships and potential opportunities by analyzing a set of ten symbols, including indices, commodities, and currencies.
Key Features:
Source Selection:
Choose your preferred data source (e.g., close, open, high, low) for all calculations.
Base Symbol for Correlations:
Define a base symbol (default: BTC/USD) for correlation calculations. The indicator evaluates how other symbols correlate with this base symbol.
Customizable Colors:
Easily identify trends with customizable colors for up and down movements, text, background, and table elements.
Length Inputs:
Tailor the analysis to your needs by adjusting the lengths for correlation calculations and RSI (Relative Strength Index).
Symbols:
Select up to ten symbols from various markets, such as stock indices, bond yields, commodities, and currencies.
Correlation Scores:
Gain insights into the strength and direction of correlations between the base symbol and selected symbols over different time lengths.
Scoring System:
Assign scores based on RSI conditions (1 for RSI > 50, -1 for RSI < 50) to each symbol.
Total Score Calculation:
Calculate a total score for each symbol by combining correlation averages and RSI scores.
Color Formatting:
Visualize correlation strengths through a color-coded system for better interpretation.
How to Use:
Positive total scores suggest potential bullish opportunities, while negative scores may indicate bearish tendencies. Combined with the visual representation of correlation strengths, traders can make informed decisions.
The Multi-Market Correlation Explorer enhances your ability to understand complex market relationships, enabling you to stay ahead of trends and identify potential trading or investment opportunities.
Relative Trend Index (RTI) by Zeiierman█ Overview
The Relative Trend Index (RTI) developed by Zeiierman is an innovative technical analysis tool designed to measure the strength and direction of the market trend. Unlike some traditional indicators, the RTI boasts a distinctive ability to adapt and respond to market volatility, while still minimizing the effects of minor, short-term market fluctuations.
The Relative Trend Index blends trend-following and mean-reverting characteristics, paired with a customizable and intuitive approach to trend strength, and its sensitivity to price action makes this indicator stand out.
█ Benefits of using this RTI instead of RSI
The Relative Strength Index (RSI) and the Relative Trend Index (RTI) are both powerful technical indicators, each with its own unique strengths.
However, there are key differences that make the RTI arguably more sophisticated and precise, especially when it comes to identifying trends and overbought/oversold (OB/OS) areas.
The RSI is a momentum oscillator that measures the speed and change of price movements and is typically used to identify overbought and oversold conditions in a market. However, its primary limitation lies in its tendency to produce false signals during extended trending periods.
On the other hand, the RTI is designed specifically to identify and adapt to market trends. Instead of solely focusing on price changes, the RTI measures the relative positioning of the current closing price within its recent range, providing a more comprehensive view of market conditions.
The RTI's adaptable nature is particularly valuable. The user-adjustable sensitivity percentage allows traders to fine-tune the indicator's responsiveness, making it more resilient to sudden market fluctuations and noise that could otherwise produce false signals. This feature is advantageous in various market conditions, from trending to choppy and sideways-moving markets.
Furthermore, the RTI's unique method of defining OB/OS zones takes into account the prevailing trend, which can provide a more precise reflection of the market's condition.
While the RSI is an invaluable tool in many traders' toolkits, the RTI's unique approach to trend identification, adaptability, and enhanced definition of OB/OS zones can provide traders with a more nuanced understanding of market conditions and potential trading opportunities. This makes the RTI an especially powerful tool for those seeking to ride long-term trends and avoid false signals.
█ Calculations
In summary, while simple enough, the math behind the RTI indicator is quite powerful. It combines the quantification of price volatility with the flexibility to adjust the trend sensitivity. It provides a normalized output that can be interpreted consistently across various trading scenarios.
The math behind the Relative Trend Index (RTI) indicator is rooted in some fundamental statistical concepts: Standard Deviation and Percentiles.
Standard Deviation: The Standard Deviation is a measure of dispersion or variability in a dataset. It quantifies the degree to which each data point deviates from the mean (or average) of the data set. In this script, the standard deviation is computed on the 'close' prices over a specified number of periods. This provides a measure of the volatility in the price over that period. The higher the standard deviation, the more volatile the price has been.
Percentiles: The percentile is a measure used in statistics indicating the value below which a given percentage of observations in a group falls. After calculating the upper and lower trends for the last 'length' periods and sorting these values, the script uses the 'Sensitivity ' parameter to extract percentiles from these sorted arrays. This is a powerful concept because it allows us to adjust the sensitivity of our signals. By choosing different percentiles (controlled through the 'Sensitivity' parameter), we can decide whether we want to react only to extreme events (high percentiles) or be more reactive and consider smaller deviations from the norm as significant (lower percentiles).
Finally, the script calculates the Relative Trend Index value, which is essentially a normalized measure indicating where the current price falls between the upper and lower trend values. This simple ratio is incredibly powerful as it provides a standardized measure that can be used across different securities and market conditions to identify potential trading signals.
Core Components
Trend Data Count: This parameter denotes the number of data points used in the RTI's calculation, determining the trend length. A higher count captures a more extended market view (long-term trend), providing smoother results that are more resistant to sudden market changes. In contrast, a lower count focuses on more recent data (short-term trend), yielding faster responses to market changes, albeit at the cost of increased susceptibility to market noise.
Trend Sensitivity Percentage: This parameter is employed to select the indices within the trend arrays used for upper and lower trend definitions. By adjusting this value, users can affect the sensitivity of the trend, with higher percentages leading to a less sensitive trend.
█ How to use
The RTI plots a line that revolves around a mid-point of 50. When the RTI is above 50, it implies that the market trend is bullish (upward), and when it's below 50, it indicates a bearish (downward) trend. Furthermore, the farther the RTI deviates from the 50 line, the stronger the trend is perceived to be.
Bullish
Bearish
The RTI includes user-defined Overbought and Oversold levels. These thresholds suggest potential trading opportunities when they are crossed, serving as a cue for traders to possibly buy or sell. This gives the RTI an additional use case as a mean-reversion tool, in addition to being a trend-following indicator.
In short
Trend Confirmation and Reversals: If the percentage trend value is consistently closer to the upper level, it can indicate a strong uptrend. Similarly, if it's closer to the lower level, a downtrend may be in play. If the percentage trend line begins to move away from one trend line towards the other, it could suggest a potential trend reversal.
Identifying Overbought and Oversold Conditions: When the percentage trend value reaches the upper trend line (signified by a value of 1), it suggests an overbought condition - i.e., the price has been pushed up, perhaps too far, and could be due for a pullback, or indicating a strong positive trend. Conversely, when the percentage trend value hits the lower trend line (a value of 0), it indicates an oversold condition - the price may have been driven down and could be set to rebound, or indicate a strong negative trend. Traders often use these overbought and oversold signals as contrarian indicators, considering them potential signs to sell (in overbought conditions) or buy (in oversold conditions). If the RTI line remains overbought or oversold for an extended period, it indicates a strong trend in that direction.
█ Settings
One key feature of the RTI is its configurability. It allows users to set the trend data length and trend sensitivity.
The trend data length represents the number of data points used in the trend calculation. A longer trend data length will reflect a more long-term trend, whereas a shorter trend data length will capture short-term movements.
Trend sensitivity refers to the threshold for determining what constitutes a significant trend. High sensitivity levels will deem fewer price movements as significant, hence making the trend less sensitive. Conversely, low sensitivity levels will deem more price movements as significant, hence making the trend more sensitive.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
RSI-CCI Fusion + AlertsThe "RSI-CCI Fusion" indicator combines the Relative Strength Index (RSI) and Commodity Channel Index (CCI) from TradingView.
RSI-CCI Fusion: Unlocking Synergies in Technical Analysis
Technical analysis plays a crucial role in understanding market dynamics and making informed trading decisions. I often rely on a combination of indicators to gain insights into price movements and identify potential trade opportunities. In the lines below, I will explore the "RSI-CCI Fusion" indicator, a powerful tool that combines the strengths of the Relative Strength Index (RSI) and the Commodity Channel Index (CCI) to provide enhanced trading insights.
1. Understanding the RSI and CCI Indicators
Before delving into the fusion of these indicators, let's briefly review their individual characteristics. The RSI is a widely used momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100, with readings above 70 indicating overbought conditions and readings below 30 indicating oversold conditions.
On the other hand, the CCI is a versatile indicator designed to identify cyclical trends in prices. It measures the distance between the price and its statistical average, thereby providing valuable insights into overbought and oversold levels.
2. The Concept of RSI-CCI Fusion
The RSI-CCI Fusion indicator is born out of my desire to harness the collective power of the RSI and CCI. By combining these indicators, I can benefit from a more comprehensive trading signal that captures both momentum and cyclical trend dynamics.
The fusion process involves assigning weights to the RSI and CCI, creating a blended indicator that reflects their relative importance. The weighted combination ensures that both indicators contribute meaningfully to the final result.
To maintain consistency, the RSI and CCI values are standardized using the z-score technique. This normalization process brings the values to a common scale, making them directly comparable. Rescaling is then applied to bring the combined indicator back to its original scale, facilitating intuitive interpretation.
3. Interpreting the RSI-CCI Fusion Indicator
When plotting the RSI-CCI Fusion indicator on a chart, I gain valuable insights into market dynamics and potential trading opportunities. The indicator's plot typically includes dynamic upper and lower bands, which are calculated based on the indicator's standard deviation. These bands provide boundaries for evaluating overbought and oversold conditions.
When the RSI-CCI Fusion indicator crosses above the lower band, it suggests oversold conditions and potential buying opportunities. Conversely, when the indicator crosses below the upper band, it indicates overbought conditions and potential selling opportunities. I also pay attention to the baseline, which represents the neutral level and may signal potential trend reversals.
4. Utilizing Alerts for Trading Decisions
The RSI-CCI Fusion indicator can be further enhanced by incorporating alerts. These alerts notify me when the indicator generates buy or sell signals, enabling me to take prompt action. I can customize the alerts based on my preferred thresholds and timeframes.
However, it is crucial to remember that the RSI-CCI Fusion indicator should not be relied upon in isolation. To increase the robustness of my trading decisions, it is recommended to combine the indicator with other analysis techniques such as trend lines, support and resistance levels, or additional indicators. This convergence of analysis methodologies enhances the overall accuracy of my trade signals.
Conclusion: The RSI-CCI Fusion indicator represents a compelling approach to technical analysis by synergizing the strengths of the RSI and CCI. By combining momentum and cyclical trend dynamics, I gain a more comprehensive view of market conditions. The fusion of these indicators, accompanied by timely alerts, equips me with valuable insights and facilitates well-informed trading decisions.
As with any technical analysis tool, it is essential for me to backtest the RSI-CCI Fusion indicator to evaluate its performance across different market conditions and timeframes. Additionally, applying proper risk management strategies is crucial to ensure consistent and disciplined trading practices.
RSI Bollinger Bands [DCAUT]█ RSI Bollinger Bands
📊 ORIGINALITY & INNOVATION
The RSI Bollinger Bands indicator represents a meaningful advancement in momentum analysis by combining two proven technical tools: the Relative Strength Index (RSI) and Bollinger Bands. This combination addresses a significant limitation in traditional RSI analysis - the use of fixed overbought/oversold thresholds (typically 70/30) that fail to adapt to changing market volatility conditions.
Core Innovation:
Rather than relying on static threshold levels, this indicator applies Bollinger Bands statistical analysis directly to RSI values, creating dynamic zones that automatically adjust based on recent momentum volatility. This approach helps reduce false signals during low volatility periods while remaining sensitive to genuine extremes during high volatility conditions.
Key Enhancements Over Traditional RSI:
Dynamic Thresholds: Overbought/oversold zones adapt to market conditions automatically, eliminating the need for manual threshold adjustments across different instruments and timeframes
Volatility Context: Band width provides immediate visual feedback about momentum volatility, helping traders distinguish between stable trends and erratic movements
Reduced False Signals: During ranging markets, narrower bands filter out minor RSI fluctuations that would trigger traditional fixed-threshold signals
Breakout Preparation: Band squeeze patterns (similar to price-based BB) signal potential momentum regime changes before they occur
Self-Referencing Analysis: By measuring RSI against its own statistical behavior rather than arbitrary levels, the indicator provides more relevant context
📐 MATHEMATICAL FOUNDATION
Two-Stage Calculation Process:
Stage 1: RSI Calculation
RSI = 100 - (100 / (1 + RS))
where RS = Average Gain / Average Loss over specified period
The RSI normalizes price momentum into a bounded 0-100 scale, making it ideal for statistical band analysis.
Stage 2: Bollinger Bands on RSI
Basis = MA(RSI, BB Length)
Upper Band = Basis + (StdDev(RSI, BB Length) × Multiplier)
Lower Band = Basis - (StdDev(RSI, BB Length) × Multiplier)
Band Width = Upper Band - Lower Band
The Bollinger Bands measure RSI's standard deviation from its own moving average, creating statistically-derived dynamic zones.
Statistical Interpretation:
Under normal distribution assumptions with default 2.0 multiplier, approximately 95% of RSI values should fall within the bands
Band touches represent statistically significant momentum extremes relative to recent behavior
Band width expansion indicates increasing momentum volatility (strengthening trend or increasing uncertainty)
Band width contraction signals momentum consolidation and potential regime change preparation
📊 COMPREHENSIVE SIGNAL ANALYSIS
Visual Color Signals:
This indicator features dynamic color fills that highlight extreme momentum conditions:
Green Fill (Above Upper Band):
Appears when RSI breaks above the upper band, indicating exceptionally strong bullish momentum
Represents dynamic overbought zone - not necessarily a reversal signal but a warning of extreme conditions
In strong uptrends, green fills can persist as RSI "rides the band" - this indicates sustained momentum strength
Exit of green zone (RSI falling back below upper band) often signals initial momentum weakening
Red Fill (Below Lower Band):
Appears when RSI breaks below the lower band, indicating exceptionally weak bearish momentum
Represents dynamic oversold zone - potential reversal or continuation signal depending on trend context
In strong downtrends, red fills can persist as RSI "rides the band" - this indicates sustained selling pressure
Exit of red zone (RSI rising back above lower band) often signals initial momentum recovery
Position-Based Signals:
Upper Band Interactions:
RSI Touching Upper Band: Dynamic overbought condition - momentum is extremely strong relative to recent volatility, potential exhaustion or continuation depending on trend context
RSI Riding Upper Band: Sustained strong momentum, often seen in powerful trends, not necessarily an immediate reversal signal but warrants monitoring for exhaustion
RSI Crossing Below Upper Band: Initial momentum weakening signal, particularly significant if accompanied by price divergence
Lower Band Interactions:
RSI Touching Lower Band: Dynamic oversold condition - momentum is extremely weak relative to recent volatility, potential reversal or continuation of downtrend
RSI Riding Lower Band: Sustained weak momentum, common in strong downtrends, monitor for potential exhaustion
RSI Crossing Above Lower Band: Initial momentum strengthening signal, early indication of potential reversal or consolidation
Basis Line Signals:
RSI Above Basis: Bullish momentum regime - upward pressure dominant
RSI Below Basis: Bearish momentum regime - downward pressure dominant
Basis Crossovers: Momentum regime shifts, more significant when accompanied by band width changes
RSI Oscillating Around Basis: Balanced momentum, often indicates ranging market conditions
Volatility-Based Signals:
Band Width Patterns:
Narrow Bands (Squeeze): Momentum volatility compression, often precedes significant directional moves, similar to price coiling patterns
Expanding Bands: Increasing momentum volatility, indicates trend acceleration or growing uncertainty
Narrowest Band in 100 Bars: Extreme compression alert, high probability of upcoming volatility expansion
Advanced Pattern Recognition:
Divergence Analysis:
Bullish Divergence: Price makes lower lows while RSI touches or stays above previous lower band touch, suggests downward momentum weakening
Bearish Divergence: Price makes higher highs while RSI touches or stays below previous upper band touch, suggests upward momentum weakening
Hidden Bullish: Price makes higher lows while RSI makes lower lows at the lower band, indicates strong underlying bullish momentum
Hidden Bearish: Price makes lower highs while RSI makes higher highs at the upper band, indicates strong underlying bearish momentum
Band Walk Patterns:
Upper Band Walk: RSI consistently touching or staying near upper band indicates exceptionally strong trend, wait for clear break below basis before considering reversal
Lower Band Walk: RSI consistently at lower band signals very weak momentum, requires break above basis for reversal confirmation
🎯 STRATEGIC APPLICATIONS
Strategy 1: Mean Reversion Trading
Setup Conditions:
Market Type: Ranging or choppy markets with no clear directional trend
Timeframe: Works best on lower timeframes (5m-1H) or during consolidation phases
Band Characteristic: Normal to narrow band width
Entry Rules:
Long Entry: RSI touches or crosses below lower band, wait for RSI to start rising back toward basis before entry
Short Entry: RSI touches or crosses above upper band, wait for RSI to start falling back toward basis before entry
Confirmation: Use price action confirmation (candlestick reversal patterns) at band touches
Exit Rules:
Target: RSI returns to basis line or opposite band
Stop Loss: Fixed percentage or below recent swing low/high
Time Stop: Exit if position not profitable within expected timeframe
Strategy 2: Trend Continuation Trading
Setup Conditions:
Market Type: Clear trending market with higher highs/lower lows
Timeframe: Medium to higher timeframes (1H-Daily)
Band Characteristic: Expanding or wide bands indicating strong momentum
Entry Rules:
Long Entry in Uptrend: Wait for RSI to pull back to basis line or slightly below, enter when RSI starts rising again
Short Entry in Downtrend: Wait for RSI to rally to basis line or slightly above, enter when RSI starts falling again
Avoid Counter-Trend: Do not fade RSI at bands during strong trends (band walk patterns)
Exit Rules:
Trailing Stop: Move stop to break-even when RSI reaches opposite band
Trend Break: Exit when RSI crosses basis against trend direction with conviction
Band Squeeze: Reduce position size when bands start narrowing significantly
Strategy 3: Breakout Preparation
Setup Conditions:
Market Type: Consolidating market after significant move or at key technical levels
Timeframe: Any timeframe, but longer timeframes provide more reliable breakouts
Band Characteristic: Narrowest band width in recent 100 bars (squeeze alert)
Preparation Phase:
Identify band squeeze condition (bands at multi-period narrowest point)
Monitor price action for consolidation patterns (triangles, rectangles, flags)
Prepare bracket orders for both directions
Wait for band expansion to begin
Entry Execution:
Breakout Confirmation: Enter in direction of RSI band breakout (RSI breaks above upper band or below lower band)
Price Confirmation: Ensure price also breaks corresponding technical level
Volume Confirmation: Look for volume expansion supporting the breakout
Risk Management:
Stop Loss: Place beyond consolidation pattern opposite extreme
Position Sizing: Use smaller size due to false breakout risk
Quick Exit: Exit immediately if RSI returns inside bands within 1-3 bars
Strategy 4: Multi-Timeframe Analysis
Timeframe Selection:
Higher Timeframe: Daily or 4H for trend context
Trading Timeframe: 1H or 15m for entry signals
Confirmation Timeframe: 5m or 1m for precise entry timing
Analysis Process:
Trend Identification: Check higher timeframe RSI position relative to bands, trade only in direction of higher timeframe momentum
Setup Formation: Wait for trading timeframe RSI to show pullback to basis in trending direction
Entry Timing: Use confirmation timeframe RSI band touch or crossover for precise entry
Alignment Confirmation: All timeframes should show RSI moving in same direction for highest probability setups
📋 DETAILED PARAMETER CONFIGURATION
RSI Source:
Close (Default): Standard price point, balances responsiveness and reliability
HL2: Reduces noise from intrabar volatility, provides smoother RSI values
HLC3 or OHLC4: Further smoothing for very choppy markets, slower to respond but more stable
Volume-Weighted: Consider using VWAP or volume-weighted prices for additional liquidity context
RSI Length Parameter:
Shorter Periods (5-10): More responsive but generates more signals, suitable for scalping or very active trading, higher noise level
Standard (14): Default and most widely used setting, proven balance between responsiveness and reliability, recommended starting point
Longer Periods (21-30): Smoother momentum measurement, fewer but potentially more reliable signals, better for swing trading or position trading
Optimization Note: Test across different market regimes, optimal length often varies by instrument volatility characteristics
RSI MA Type Parameter:
RMA (Default): Wilder's original smoothing method, provides traditional RSI behavior with balanced lag, most widely recognized and tested, recommended for standard technical analysis
EMA: Exponential smoothing gives more weight to recent values, faster response to momentum changes, suitable for active trading and trending markets, reduces lag compared to RMA
SMA: Simple average treats all periods equally, smoothest output with highest lag, best for filtering noise in choppy markets, useful for long-term position analysis
WMA: Weighted average emphasizes recent data less aggressively than EMA, middle ground between SMA and EMA characteristics, balanced responsiveness for swing trading
Advanced Options: Full access to 25+ moving average types including HMA (reduced lag), DEMA/TEMA (enhanced responsiveness), KAMA/FRAMA (adaptive behavior), T3 (smoothness), Kalman Filter (optimal estimation)
Selection Guide: RMA for traditional analysis and backtesting consistency, EMA for faster signals in trending markets, SMA for stability in ranging markets, adaptive types (KAMA/FRAMA) for varying volatility regimes
BB Length Parameter:
Short Length (10-15): Tighter bands that react quickly to RSI changes, more frequent band touches, suitable for active trading styles
Standard (20): Balanced approach providing meaningful statistical context without excessive lag
Long Length (30-50): Smoother bands that filter minor RSI fluctuations, captures only significant momentum extremes, fewer but higher quality signals
Relationship to RSI Length: Consider BB Length greater than RSI Length for cleaner signals
BB MA Type Parameter:
SMA (Default): Standard Bollinger Bands calculation using simple moving average for basis line, treats all periods equally, widely recognized and tested approach
EMA: Exponential smoothing for basis line gives more weight to recent RSI values, creates more responsive bands that adapt faster to momentum changes, suitable for trending markets
RMA: Wilder's smoothing provides consistent behavior aligned with traditional RSI when using RMA for both RSI and BB calculations
WMA: Weighted average for basis line balances recent emphasis with historical context, middle ground between SMA and EMA responsiveness
Advanced Options: Full access to 25+ moving average types for basis calculation, including HMA (reduced lag), DEMA/TEMA (enhanced responsiveness), KAMA/FRAMA (adaptive to volatility changes)
Selection Guide: SMA for standard Bollinger Bands behavior and backtesting consistency, EMA for faster band adaptation in dynamic markets, matching RSI MA type creates unified smoothing behavior
BB Multiplier Parameter:
Conservative (1.5-1.8): Tighter bands resulting in more frequent touches, useful in low volatility environments, higher signal frequency but potentially more false signals
Standard (2.0): Default setting representing approximately 95% confidence interval under normal distribution, widely accepted statistical threshold
Aggressive (2.5-3.0): Wider bands capturing only extreme momentum conditions, fewer but potentially more significant signals, reduces false signals in high volatility
Adaptive Approach: Consider adjusting multiplier based on instrument characteristics, lower multiplier for stable instruments, higher for volatile instruments
Parameter Optimization Workflow:
Start with default parameters (RSI:14, BB:20, Mult:2.0)
Test across representative sample period including different market regimes
Adjust RSI length based on desired responsiveness vs stability tradeoff
Tune BB length to match your typical holding period
Modify multiplier to achieve desired signal frequency
Validate on out-of-sample data to avoid overfitting
Document optimal parameters for different instruments and timeframes
Reference Levels Display:
Enabled (Default): Shows traditional 30/50/70 levels for comparison with dynamic bands, helps visualize the adaptive advantage
Disabled: Cleaner chart focusing purely on dynamic zones, reduces visual clutter for experienced users
Educational Value: Keeping reference levels visible helps understand how dynamic bands differ from fixed thresholds across varying market conditions
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Comparison with Traditional RSI:
Fixed Threshold RSI Limitations:
In ranging low-volatility markets: RSI rarely reaches 70/30, missing tradable extremes
In trending high-volatility markets: RSI frequently breaks through 70/30, generating excessive false reversal signals
Across different instruments: Same thresholds applied to volatile crypto and stable forex pairs produce inconsistent results
Threshold Adjustment Problem: Manually changing thresholds for different conditions is subjective and lagging
RSI Bollinger Bands Advantages:
Automatic Adaptation: Bands adjust to current volatility regime without manual intervention
Consistent Logic: Same statistical approach works across different instruments and timeframes
Reduced False Signals: Band width filtering helps distinguish meaningful extremes from noise
Additional Information: Band width provides volatility context missing in standard RSI
Objective Extremes: Statistical basis (standard deviations) provides objective extreme definition
Comparison with Price-Based Bollinger Bands:
Price BB Characteristics:
Measures absolute price volatility
Affected by large price gaps and outliers
Band position relative to price not normalized
Difficult to compare across different price scales
RSI BB Advantages:
Normalized Scale: RSI's 0-100 bounds make band interpretation consistent across all instruments
Momentum Focus: Directly measures momentum extremes rather than price extremes
Reduced Gap Impact: RSI calculation smooths price gaps impact on band calculations
Comparable Analysis: Same RSI BB appearance across stocks, forex, crypto enables consistent strategy application
Performance Characteristics:
Signal Quality:
Higher Signal-to-Noise Ratio: Dynamic bands help filter RSI oscillations that don't represent meaningful extremes
Context-Aware Alerts: Band width provides volatility context helping traders adjust position sizing and stop placement
Reduced Whipsaws: During consolidations, narrower bands prevent premature signals from minor RSI movements
Responsiveness:
Adaptive Lag: Band calculation introduces some lag, but this lag is adaptive to current conditions rather than fixed
Faster Than Manual Adjustment: Automatic band adjustment is faster than trader's ability to manually modify thresholds
Balanced Approach: Combines RSI's inherent momentum lag with BB's statistical smoothing for stable yet responsive signals
Versatility:
Multi-Strategy Application: Supports both mean reversion (ranging markets) and trend continuation (trending markets) approaches
Universal Instrument Coverage: Works effectively across equities, forex, commodities, cryptocurrencies without parameter changes
Timeframe Agnostic: Same interpretation applies from 1-minute charts to monthly charts
Limitations and Considerations:
Known Limitations:
Dual Lag Effect: Combines RSI's momentum lag with BB's statistical lag, making it less suitable for very short-term scalping
Requires Volatility History: Needs sufficient bars for BB calculation, less effective immediately after major regime changes
Statistical Assumptions: Assumes RSI values are somewhat normally distributed, extreme trending conditions may violate this
Not a Standalone System: Like all indicators, should be combined with price action analysis and risk management
Optimal Use Cases:
Best for swing trading and position trading timeframes
Most effective in markets with alternating volatility regimes
Ideal for traders who use multiple instruments and timeframes
Suitable for systematic trading approaches requiring consistent logic
Suboptimal Conditions:
Very low timeframes (< 5 minutes) where lag becomes problematic
Instruments with extreme volatility spikes (gap-prone markets)
Markets in strong persistent trends where mean reversion rarely occurs
Periods immediately following major structural changes (new trading regime)
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to help traders understand the interaction between momentum measurement and statistical volatility bands. The RSI Bollinger Bands has limitations and should not be used as the sole basis for trading decisions.
Important Considerations:
No Predictive Guarantee: Past band touches and patterns do not guarantee future price behavior
Market Regime Dependency: Indicator performance varies significantly between trending and ranging market conditions
Complementary Analysis Required: Should be used alongside price action, support/resistance levels, and fundamental analysis
Risk Management Essential: Always use proper position sizing, stop losses, and risk controls regardless of signal quality
Parameter Sensitivity: Different instruments and timeframes may require parameter optimization for optimal results
Continuous Monitoring: Band characteristics change with market conditions, requiring ongoing assessment
Recommended Supporting Analysis:
Price structure analysis (support/resistance, trend lines)
Volume confirmation for breakout signals
Multiple timeframe alignment
Market context awareness (news events, session times)
Correlation analysis with related instruments
The indicator aims to provide adaptive momentum analysis that adjusts to changing market volatility, but traders must apply sound judgment, proper risk management, and comprehensive market analysis in their decision-making process.
Average True Ranges with IBD RSAdvanced ATR Analysis with IBD Relative Strength
This comprehensive indicator combines Average True Range (ATR) analysis with IBD (Investor's Business Daily) Relative Strength calculation, providing both volatility measurement and momentum analysis in one powerful tool.
Key Features:
ATR Analysis:
Standard ATR: Customizable period (default 14) with multiple smoothing options
1.5x ATR: Extended range for wider stop-loss and target calculations
Smoothing Options: Choose between RMA, SMA, EMA, or WMA for ATR calculation
Customizable Colors: Distinct colors for easy visual identification
IBD Relative Strength:
Professional RS Formula: Uses the same calculation method as Investor's Business Daily
Multi-Timeframe Analysis: Compares current price to 3, 6, 9, and 12-month performance
Weighted Calculation: 40% weight on 3-month, 20% each on 6, 9, and 12-month performance
Zero-Based Scale: Values above 0 indicate outperformance, below 0 indicate underperformance
Trading Applications:
Volatility-Based Stops: Use ATR and 1.5x ATR for dynamic stop-loss placement
Position Sizing: ATR helps determine appropriate position size based on volatility
Relative Strength Analysis: IBD RS identifies stocks with superior momentum
Market Timing: High RS values often precede strong price moves
Risk Management: Combine volatility (ATR) with momentum (RS) for comprehensive analysis
Technical Details:
ATR Calculation: True Range smoothed over selected period with chosen method
IBD RS Formula: (40% × 3M) + (20% × 6M) + (20% × 9M) + (20% × 12M) - 100
Display: Separate pane indicator with customizable colors for each component
How to Interpret:
High ATR: Increased volatility, wider stops needed
Low ATR: Reduced volatility, tighter stops possible
Positive IBD RS: Stock outperforming market over measured periods
Negative IBD RS: Stock underperforming market over measured periods
Customizable Parameters:
ATR calculation length
Smoothing method for ATR
Individual colors for ATR, 1.5x ATR, and IBD RS lines
Perfect for swing traders and position traders who want to combine volatility analysis with relative strength momentum in their decision-making process. Particularly useful for stock selection and risk management.
Advanced Forex Currency Strength Meter
# Advanced Forex Currency Strength Meter
🚀 The Ultimate Currency Strength Analysis Tool for Forex Traders
This sophisticated indicator measures and compares the relative strength of major currencies (EUR, GBP, USD, JPY, CHF, CAD, AUD, NZD) to help you identify the strongest and weakest currencies in real-time, providing clear trading signals based on currency strength differentials.
## 📊 What This Indicator Does
The Advanced Forex Currency Strength Meter analyzes currency relationships across 28+ major forex pairs and 8 currency indices to determine which currencies are gaining or losing strength. Instead of relying on individual pair analysis, this tool gives you a bird's-eye view of the entire forex market, helping you:
Identify the strongest and weakest currencies at any given time
Find high-probability trading opportunities by pairing strong vs weak currencies
Avoid ranging markets by detecting when currencies have similar strength
Get clear LONG/SHORT/NEUTRAL signals for your current trading pair
Optimize your trading strategy based on your preferred timeframe and holding period
## ⚙️ How The Indicator Works
### Dual Calculation Method
The indicator uses a sophisticated dual approach for maximum accuracy:
Pairs-Based Analysis: Calculates currency strength from 28+ major forex pairs (EURUSD, GBPUSD, USDJPY, etc.)
Index-Based Analysis: Incorporates official currency indices (DXY, EXY, BXY, JXY, CXY, AXY, SXY, ZXY)
Weighted Combination: Blends both methods using smart weighting for enhanced accuracy
### Smart Auto-Optimization System
The indicator automatically adjusts its parameters based on your chart timeframe and intended holding period:
The system recognizes that scalping requires different sensitivity than swing trading, automatically optimizing lookback periods, analysis timeframes, signal thresholds, and index weights.
### Strength Calculation Process
Fetches price data from multiple timeframes using optimized tuple requests
Calculates percentage change over the specified lookback period
Optionally normalizes by ATR (Average True Range) to account for volatility differences
Combines pair-based and index-based calculations using dynamic weighting
Generates relative strength by comparing base currency vs quote currency
Produces clear trading signals when strength differential exceeds threshold
## 🎯 How To Use The Indicator
### Quick Start
Add the indicator to any forex pair chart
Enable 🧠 Smart Auto-Optimization (recommended for beginners)
Watch for LONG 🚀 signals when the relative strength line is green and above threshold
Watch for SHORT 🐻 signals when the relative strength line is red and below threshold
Avoid trading during NEUTRAL ⚪ periods when currencies have similar strength
Note: This is highly recommended to couple this indicator with fundamental analysis and use it as an extra signal.
### 📋 Parameters Reference
#### 🤖 Smart Settings
🧠 Smart Auto-Optimization: (Default: Enabled) Automatically optimizes all parameters based on chart timeframe and trading style
#### ⚙️ Manual Override
These settings are only active when Smart Auto-Optimization is disabled:
Manual Lookback Period: (Default: 14) Number of periods to analyze for strength calculation
Manual ATR Period: (Default: 14) Period for ATR normalization calculation
Manual Analysis Timeframe: (Default: 240) Higher timeframe for strength analysis
Manual Index Weight: (Default: 0.5) Weight given to currency indices vs pairs (0.0 = pairs only, 1.0 = indices only)
Manual Signal Threshold: (Default: 0.5) Minimum strength differential required for trading signals
#### 📊 Display
Show Signal Markers: (Default: Enabled) Display triangle markers when signals change
Show Info Label: (Default: Enabled) Show comprehensive information label with current analysis
#### 🔍 Analysis
Use ATR Normalization: (Default: Enabled) Normalize strength calculations by volatility for fairer comparison
#### 💰 Currency Indices
💰 Use Currency Indices: (Default: Enabled) Include all 8 currency indices in strength calculation for enhanced accuracy
#### 🎨 Colors
Strong Currency Color: (Default: Green) Color for positive/strong signals
Weak Currency Color: (Default: Red) Color for negative/weak signals
Neutral Color: (Default: Gray) Color for neutral conditions
Strong/Weak Backgrounds: Background colors for clear signal visualization
### 🧠 Smart Optimization Profiles
The indicator automatically selects optimal parameters based on your chart timeframe:
#### ⚡ Scalping Profile (1M-5M Charts)
For positions held for a few minutes:
Lookback: 5 periods (fast/sensitive)
Analysis Timeframe: 15 minutes
Index Weight: 20% (favor pairs for speed)
Signal Threshold: 0.3% (sensitive triggers)
#### 📈 Intraday Profile (10M-1H Charts)
For positions held for a few hours:
Lookback: 12 periods (balanced sensitivity)
Analysis Timeframe: 4 hours
Index Weight: 40% (balanced approach)
Signal Threshold: 0.4% (moderate sensitivity)
#### 📊 Swing Profile (4H-Daily Charts)
For positions held for a few days:
Lookback: 21 periods (stable analysis)
Analysis Timeframe: Daily
Index Weight: 60% (favor indices for stability)
Signal Threshold: 0.5% (conservative triggers)
#### 📆 Position Profile (Weekly+ Charts)
For positions held for a few weeks:
Lookback: 30 periods (long-term view)
Analysis Timeframe: Weekly
Index Weight: 70% (heavily favor indices)
Signal Threshold: 0.6% (very conservative)
### Entry Timing
Wait for clear LONG 🚀 or SHORT 🐻 signals
Avoid trading during NEUTRAL ⚪ periods
Look for signal confirmations on multiple timeframes
### Risk Management
Stronger signals (higher relative strength values) suggest higher probability trades
Use appropriate position sizing based on signal strength
Consider the trading style profile when setting stop losses and take profits
💡 Pro Tip: The indicator works best when combined with your existing technical analysis. Use currency strength to identify which pairs to trade, then use your favorite technical indicators to determine when to enter and exit.
## 🔧 Key Features
28+ Forex Pairs Analysis: Comprehensive coverage of major currency relationships
8 Currency Indices Integration: DXY, EXY, BXY, JXY, CXY, AXY, SXY, ZXY for enhanced accuracy
Smart Auto-Optimization: Automatically adapts to your trading style and timeframe
ATR Normalization: Fair comparison across different currency pairs and volatility levels
Real-Time Signals: Clear LONG/SHORT/NEUTRAL signals with visual markers
Performance Optimized: Efficient tuple-based data requests minimize external calls
User-Friendly Interface: Simplified settings with comprehensive tooltips
Multi-Timeframe Support: Works on any timeframe from 1-minute to monthly charts
Transform your forex trading with the power of currency strength analysis! 🚀
RSI Mansfield +RSI Mansfield+ – Adaptive Relative Strength Indicator with Divergences
Overview
RSI Mansfield+ is an advanced relative strength indicator that compares your instrument’s performance against a configurable benchmark index or asset (e.g., Bitcoin Dominance, S&P 500). It combines Mansfield normalization, adaptive smoothing techniques, and automatic detection of bullish and bearish divergences (regular and hidden), delivering a comprehensive tool for assessing relative strength across any market and timeframe.
Originality and Motivation
Unlike traditional relative strength scripts, this indicator introduces several distinctive improvements:
Mansfield Normalization: Scales the ratio between the asset and the benchmark relative to its moving average, transforming it into a normalized oscillator that fluctuates around zero, making it easier to spot outperformance or underperformance.
Adaptive Smoothing: Automatically selects whether to use EMA or SMA based on the market type (crypto or stocks) and timeframe (intraday, daily, weekly, monthly), avoiding manual configuration and providing more robust results under varying volatility conditions.
Divergence Detection: Identifies four types of divergences in the Mansfield oscillator to help anticipate potential reversal points or trend confirmations.
Multi-Market Support: Offers benchmark selection among major crypto and global stock indices from a single input.
These enhancements make RSI Mansfield+ more practical and powerful than conventional relative strength scripts with static benchmarks or without divergence capabilities.
Core Concepts
Relative Strength (RS): Compares price evolution between your asset and the selected benchmark.
Mansfield Normalization: Measures how much the RS deviates from its historical moving average, expressed as a scaled oscillator.
Divergences: Detects regular and hidden bullish or bearish divergences within the Mansfield oscillator.
Timeframe Adaptation: Dynamically adjusts moving average lengths based on timeframe and market type.
How It Works
Benchmark Selection
Choose among over 10 indices or market domains (BTC Dominance, ETH Dominance, S&P 500, European indices, etc.).
Ratio Calculation
Computes the price-to-benchmark ratio and smooths it with the adaptive moving average.
Normalization and Scaling
Transforms deviations into a Mansfield oscillator centered around zero.
Dynamic Coloring
Green indicates relative outperformance, red signals underperformance.
Divergence Detection
Automatically identifies bullish and bearish (regular and hidden) divergences by comparing oscillator pivots against price pivots.
Baseline Reference
A clear zero line helps interpret relative strength trends.
Usage Guidelines
Benchmark Comparison
Ideal for traders analyzing whether an asset is outperforming or lagging its sector or market.
Divergence Analysis
Helps detect potential reversal or continuation signals in relative strength.
Multi-Timeframe Compatibility
Can be applied to intraday, daily, weekly, or monthly charts.
Interpretation
Oscillator >0 and green: outperforming the benchmark.
Oscillator <0 and red: underperforming.
Bullish divergences: potential relative strength reversal to the upside.
Bearish divergences: possible loss of momentum or reversal to the downside.
Credits
The concept of Mansfield Relative Strength is based on Stan Weinstein’s original work on relative performance analysis. This script was built entirely from scratch in TradingView Pine Script v6, incorporating original logic for adaptive smoothing, normalized scaling, and divergence detection, without reusing any external open-source code.
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.
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
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14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
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Ultimate Scalping Tool[BullByte]Overview
The Ultimate Scalping Tool is an open-source TradingView indicator built for scalpers and short-term traders released under the Mozilla Public License 2.0. It uses a custom Quantum Flux Candle (QFC) oscillator to combine multiple market forces into one visual signal. In plain terms, the script reads momentum, trend strength, volatility, and volume together and plots a special “candlestick” each bar (the QFC) that reflects the overall market bias. This unified view makes it easier to spot entries and exits: the tool labels signals as Strong Buy/Sell, Pullback (a brief retracement in a trend), Early Entry, or Exit Warning . It also provides color-coded alerts and a small dashboard of metrics. In practice, traders see green/red oscillator bars and symbols on the chart when conditions align, helping them scalp or trend-follow without reading multiple separate indicators.
Core Components
Quantum Flux Candle (QFC) Construction
The QFC is the heart of the indicator. Rather than using raw price, it creates a candlestick-like bar from the underlying oscillator values. Each QFC bar has an “open,” “high/low,” and “close” derived from calculated momentum and volatility inputs for that period . In effect, this turns the oscillator into intuitive candle patterns so traders can recognize momentum shifts visually. (For comparison, note that Heikin-Ashi candles “have a smoother look because take an average of the movement”. The QFC instead represents exact oscillator readings, so it reflects true momentum changes without hiding price action.) Colors of QFC bars change dynamically (e.g. green for bullish momentum, red for bearish) to highlight shifts. This is the first open-source QFC oscillator that dynamically weights four non-correlated indicators with moving thresholds, which makes it a unique indicator on its own.
Oscillator Normalization & Adaptive Weights
The script normalizes its oscillator to a fixed scale (for example, a 0–100 range much like the RSI) so that various inputs can be compared fairly. It then applies adaptive weighting: the relative influence of trend, momentum, volatility or volume signals is automatically adjusted based on current market conditions. For instance, in very volatile markets the script might weight volatility more heavily, or in a strong trend it might give extra weight to trend direction. Normalizing data and adjusting weights helps keep the QFC sensitive but stable (normalization ensures all inputs fit a common scale).
Trend/Momentum/Volume/Volatility Fusion
Unlike a typical single-factor oscillator, the QFC oscillator fuses four aspects at once. It may compute, for example, a trend indicator (such as an ADX or moving average slope), a momentum measure (like RSI or Rate-of-Change), a volume-based pressure (similar to MFI/OBV), and a volatility measure (like ATR) . These different values are combined into one composite oscillator. This “multi-dimensional” approach follows best practices of using non-correlated indicators (trend, momentum, volume, volatility) for confirmation. By encoding all these signals in one line, a high QFC reading means that trend, momentum, and volume are all aligned, whereas a neutral reading might mean mixed conditions. This gives traders a comprehensive picture of market strength.
Signal Classification
The script interprets the QFC oscillator to label trades. For example:
• Strong Buy/Sell : Triggered when the oscillator crosses a high-confidence threshold (e.g. breaks clearly above zero with strong slope), indicating a well-confirmed move. This is like seeing a big green/red QFC candle aligned with the trend.
• Pullbacks : Identified when the trend is up but momentum dips briefly. A Pullback Buy appears if the overall trend is bullish but the oscillator has a short retracement – a typical buying opportunity in an uptrend. (A pullback is “a brief decline or pause in a generally upward price trend”.)
• Early Buy/Sell : Marks an initial swing in the oscillator suggesting a possible new trend, before it is fully confirmed. It’s a hint of momentum building (an early-warning signal), not as strong as the confirmed “Strong” signal.
• Exit Warnings : Issued when momentum peaks or reverses. For instance, if the QFC bars reach a high and start turning red/green opposite, the indicator warns that the move may be ending. In other words, a Momentum Peak is the point of maximum strength after which weakness may follow.
These categories correspond to typical trading concepts: Pullback (temporary reversal in an uptrend), Early Buy (an initial bullish cross), Strong Buy (confirmed bullish momentum), and Momentum Peak (peak oscillator value suggesting exhaustion).
Filters (DI Reversal, Dynamic Thresholds, HTF EMA/ADX)
Extra filters help avoid bad trades. A DI Reversal filter uses the +DI/–DI lines (from the ADX system) to require that the trend direction confirms the signal . For example, it might ignore a buy signal if the +DI is still below –DI. Dynamic Thresholds adjust signal levels on-the-fly: rather than fixed “overbought” lines, they move with volatility so signals happen under appropriate market stress. An optional High-Timeframe EMA or ADX filter adds a check against a larger timeframe trend: for instance, only taking a trade if price is above the weekly EMA or if weekly ADX shows a strong trend. (Notably, the ADX is “a technical indicator used by traders to determine the strength of a price trend”, so requiring a high-timeframe ADX avoids trading against the bigger trend.)
Dashboard Metrics & Color Logic
The Dashboard in the Ultimate Scalping Tool (UST) serves as a centralized information hub, providing traders with real-time insights into market conditions, trend strength, momentum, volume pressure, and trade signals. It is highly customizable, allowing users to adjust its appearance and content based on their preferences.
1. Dashboard Layout & Customization
Short vs. Extended Mode : Users can toggle between a compact view (9 rows) and an extended view (13 rows) via the `Short Dashboard` input.
Text Size Options : The dashboard supports three text sizes— Tiny, Small, and Normal —adjustable via the `Dashboard Text Size` input.
Positioning : The dashboard is positioned in the top-right corner by default but can be moved if modified in the script.
2. Key Metrics Displayed
The dashboard presents critical trading metrics in a structured table format:
Trend (TF) : Indicates the current trend direction (Strong Bullish, Moderate Bullish, Sideways, Moderate Bearish, Strong Bearish) based on normalized trend strength (normTrend) .
Momentum (TF) : Displays momentum status (Strong Bullish/Bearish or Neutral) derived from the oscillator's position relative to dynamic thresholds.
Volume (CMF) : Shows buying/selling pressure levels (Very High Buying, High Selling, Neutral, etc.) based on the Chaikin Money Flow (CMF) indicator.
Basic & Advanced Signals:
Basic Signal : Provides simple trade signals (Strong Buy, Strong Sell, Pullback Buy, Pullback Sell, No Trade).
Advanced Signal : Offers nuanced signals (Early Buy/Sell, Momentum Peak, Weakening Momentum, etc.) with color-coded alerts.
RSI : Displays the Relative Strength Index (RSI) value, colored based on overbought (>70), oversold (<30), or neutral conditions.
HTF Filter : Indicates the higher timeframe trend status (Bullish, Bearish, Neutral) when using the Leading HTF Filter.
VWAP : Shows the V olume-Weighted Average Price and whether the current price is above (bullish) or below (bearish) it.
ADX : Displays the Average Directional Index (ADX) value, with color highlighting whether it is rising (green) or falling (red).
Market Mode : Shows the selected market type (Crypto, Stocks, Options, Forex, Custom).
Regime : Indicates volatility conditions (High, Low, Moderate) based on the **ATR ratio**.
3. Filters Status Panel
A secondary panel displays the status of active filters, helping traders quickly assess which conditions are influencing signals:
- DI Reversal Filter: On/Off (confirms reversals before generating signals).
- Dynamic Thresholds: On/Off (adjusts buy/sell thresholds based on volatility).
- Adaptive Weighting: On/Off (auto-adjusts oscillator weights for trend/momentum/volatility).
- Early Signal: On/Off (enables early momentum-based signals).
- Leading HTF Filter: On/Off (applies higher timeframe trend confirmation).
4. Visual Enhancements
Color-Coded Cells : Each metric is color-coded (green for bullish, red for bearish, gray for neutral) for quick interpretation.
Dynamic Background : The dashboard background adapts to market conditions (bullish/bearish/neutral) based on ADX and DI trends.
Customizable Reference Lines : Users can enable/disable fixed reference lines for the oscillator.
How It(QFC) Differs from Traditional Indicators
Quantum Flux Candle (QFC) Versus Heikin-Ashi
Heikin-Ashi candles smooth price by averaging (HA’s open/close use averages) so they show trend clearly but hide true price (the current HA bar’s close is not the real price). QFC candles are different: they are oscillator values, not price averages . A Heikin-Ashi chart “has a smoother look because it is essentially taking an average of the movement”, which can cause lag. The QFC instead shows the raw combined momentum each bar, allowing faster recognition of shifts. In short, HA is a smoothed price chart; QFC is a momentum-based chart.
Versus Standard Oscillators
Common oscillators like RSI or MACD use fixed formulas on price (or price+volume). For example, RSI “compares gains and losses and normalizes this value on a scale from 0 to 100”, reflecting pure price momentum. MFI is similar but adds volume. These indicators each show one dimension: momentum or volume. The Ultimate Scalping Tool’s QFC goes further by integrating trend strength and volatility too. In practice, this means a move that looks strong on RSI might be downplayed by low volume or weak trend in QFC. As one source notes, using multiple non-correlated indicators (trend, momentum, volume, volatility) provides a more complete market picture. The QFC’s multi-factor fusion is unique – it is effectively a multi-dimensional oscillator rather than a traditional single-input one.
Signal Style
Traditional oscillators often use crossovers (RSI crossing 50) or fixed zones (MACD above zero) for signals. The Ultimate Scalping Tool’s signals are custom-classified: it explicitly labels pullbacks, early entries, and strong moves. These terms go beyond a typical indicator’s generic “buy”/“sell.” In other words, it packages a strategy around the oscillator, which traders can backtest or observe without reading code.
Key Term Definitions
• Pullback : A short-term dip or consolidation in an uptrend. In this script, a Pullback Buy appears when price is generally rising but shows a brief retracement. (As defined by Investopedia, a pullback is “a brief decline or pause in a generally upward price trend”.)
• Early Buy/Sell : An initial or tentative entry signal. It means the oscillator first starts turning positive (or negative) before a full trend has developed. It’s an early indication that a trend might be starting.
• Strong Buy/Sell : A confident entry signal when multiple conditions align. This label is used when momentum is already strong and confirmed by trend/volume filters, offering a higher-probability trade.
• Momentum Peak : The point where bullish (or bearish) momentum reaches its maximum before weakening. When the oscillator value stops rising (or falling) and begins to reverse, the script flags it as a peak – signaling that the current move could be overextended.
What is the Flux MA?
The Flux MA (Moving Average) is an Exponential Moving Average (EMA) applied to a normalized oscillator, referred to as FM . Its purpose is to smooth out the fluctuations of the oscillator, providing a clearer picture of the underlying trend direction and strength. Think of it as a dynamic baseline that the oscillator moves above or below, helping you determine whether the market is trending bullish or bearish.
How it’s calculated (Flux MA):
1.The oscillator is normalized (scaled to a range, typically between 0 and 1, using a default scale factor of 100.0).
2.An EMA is applied to this normalized value (FM) over a user-defined period (default is 10 periods).
3.The result is rescaled back to the oscillator’s original range for plotting.
Why it matters : The Flux MA acts like a support or resistance level for the oscillator, making it easier to spot trend shifts.
Color of the Flux Candle
The Quantum Flux Candle visualizes the normalized oscillator (FM) as candlesticks, with colors that indicate specific market conditions based on the relationship between the FM and the Flux MA. Here’s what each color means:
• Green : The FM is above the Flux MA, signaling bullish momentum. This suggests the market is trending upward.
• Red : The FM is below the Flux MA, signaling bearish momentum. This suggests the market is trending downward.
• Yellow : Indicates strong buy conditions (e.g., a "Strong Buy" signal combined with a positive trend). This is a high-confidence signal to go long.
• Purple : Indicates strong sell conditions (e.g., a "Strong Sell" signal combined with a negative trend). This is a high-confidence signal to go short.
The candle mode shows the oscillator’s open, high, low, and close values for each period, similar to price candlesticks, but it’s the color that provides the quick visual cue for trading decisions.
How to Trade the Flux MA with Respect to the Candle
Trading with the Flux MA and Quantum Flux Candle involves using the MA as a trend indicator and the candle colors as entry and exit signals. Here’s a step-by-step guide:
1. Identify the Trend Direction
• Bullish Trend : The Flux Candle is green and positioned above the Flux MA. This indicates upward momentum.
• Bearish Trend : The Flux Candle is red and positioned below the Flux MA. This indicates downward momentum.
The Flux MA serves as the reference line—candles above it suggest buying pressure, while candles below it suggest selling pressure.
2. Interpret Candle Colors for Trade Signals
• Green Candle : General bullish momentum. Consider entering or holding a long position.
• Red Candle : General bearish momentum. Consider entering or holding a short position.
• Yellow Candle : A strong buy signal. This is an ideal time to enter a long trade.
• Purple Candle : A strong sell signal. This is an ideal time to enter a short trade.
3. Enter Trades Based on Crossovers and Colors
• Long Entry : Enter a buy position when the Flux Candle turns green and crosses above the Flux MA. If it turns yellow, this is an even stronger signal to go long.
• Short Entry : Enter a sell position when the Flux Candle turns red and crosses below the Flux MA. If it turns purple, this is an even stronger signal to go short.
4. Exit Trades
• Exit Long : Close your buy position when the Flux Candle turns red or crosses below the Flux MA, indicating the bullish trend may be reversing.
• Exit Short : Close your sell position when the Flux Candle turns green or crosses above the Flux MA, indicating the bearish trend may be reversing.
•You might also exit a long trade if the candle changes from yellow to green (weakening strong buy signal) or a short trade from purple to red (weakening strong sell signal).
5. Use Additional Confirmation
To avoid false signals, combine the Flux MA and candle signals with other indicators or dashboard metrics (e.g., trend strength, momentum, or volume pressure). For example:
•A yellow candle with a " Strong Bullish " trend and high buying volume is a robust long signal.
•A red candle with a " Moderate Bearish " trend and neutral momentum might need more confirmation before shorting.
Practical Example
Imagine you’re scalping a cryptocurrency:
• Long Trade : The Flux Candle turns yellow and is above the Flux MA, with the dashboard showing "Strong Buy" and high buying volume. You enter a long position. You exit when the candle turns red and dips below the Flux MA.
• Short Trade : The Flux Candle turns purple and crosses below the Flux MA, with a "Strong Sell" signal on the dashboard. You enter a short position. You exit when the candle turns green and crosses above the Flux MA.
Market Presets and Adaptation
This indicator is designed to work on any market with candlestick price data (stocks, crypto, forex, indices, etc.). To handle different behavior, it provides presets for major asset classes. Selecting a “Stocks,” “Crypto,” “Forex,” or “Options” preset automatically loads a set of parameter values optimized for that market . For example, a crypto preset might use a shorter lookback or higher sensitivity to account for crypto’s high volatility, while a stocks preset might use slightly longer smoothing since stocks often trend more slowly. In practice, this means the same core QFC logic applies across markets, but the thresholds and smoothing adjust so signals remain relevant for each asset type.
Usage Guidelines
• Recommended Timeframes : Optimized for 1 minute to 15 minute intraday charts. Can also be used on higher timeframes for short term swings.
• Market Types : Select “Crypto,” “Stocks,” “Forex,” or “Options” to auto tune periods, thresholds and weights. Use “Custom” to manually adjust all inputs.
• Interpreting Signals : Always confirm a signal by checking that trend, volume, and VWAP agree on the dashboard. A green “Strong Buy” arrow with green trend, green volume, and price > VWAP is highest probability.
• Adjusting Sensitivity : To reduce false signals in fast markets, enable DI Reversal Confirmation and Dynamic Thresholds. For more frequent entries in trending environments, enable Early Entry Trigger.
• Risk Management : This tool does not plot stop loss or take profit levels. Users should define their own risk parameters based on support/resistance or volatility bands.
Background Shading
To give you an at-a-glance sense of market regime without reading numbers, the indicator automatically tints the chart background in three modes—neutral, bullish and bearish—with two levels of intensity (light vs. dark):
Neutral (Gray)
When ADX is below 20 the market is considered “no trend” or too weak to trade. The background fills with a light gray (high transparency) so you know to sit on your hands.
Bullish (Green)
As soon as ADX rises above 20 and +DI exceeds –DI, the background turns a semi-transparent green, signaling an emerging uptrend. When ADX climbs above 30 (strong trend), the green becomes more opaque—reminding you that trend-following signals (Strong Buy, Pullback) carry extra weight.
Bearish (Red)
Similarly, if –DI exceeds +DI with ADX >20, you get a light red tint for a developing downtrend, and a darker, more solid red once ADX surpasses 30.
By dynamically varying both hue (green vs. red vs. gray) and opacity (light vs. dark), the background instantly communicates trend strength and direction—so you always know whether to favor breakout-style entries (in a strong trend) or stay flat during choppy, low-ADX conditions.
The setup shown in the above chart snapshot is BTCUSD 15 min chart : Binance for reference.
Disclaimer
No indicator guarantees profits. Backtest or paper trade this tool to understand its behavior in your market. Always use proper position sizing and stop loss orders.
Good luck!
- BullByte
Market Push Meter - CoffeeStyleMarket Push Meter - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the Market Push Meter indicator, a sophisticated volume analysis tool developed by CoffeeKiller with the help and assistance of FindBetterTrades that measures and visualizes the ongoing battle between buyers and sellers through volume pressure analysis.
🔔 **Warning: This Is Not a Standard Volume Indicator** 🔔 This indicator analyzes volume pressure in a unique way, combining directional volume with price action to identify market imbalances between buyers and sellers. All credit for the core logic for this indicator goes to FindBetterTrades and his/hers Volume Pressure Histogram (Normalized) (this is my adaptation and style added to that core logic, thus the CoffeeStyle name was added).
Core Concept: Volume Pressure Analysis
The foundation of this indicator lies in measuring the imbalance between buying and selling volume, providing insights into which market participants are exerting more pressure on price movements.
Volume Pressure Columns: Buying vs Selling Force
- Positive Green Columns: Net buying pressure
- Negative Red Columns: Net selling pressure
- Color intensity varies based on pressure strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during buying phases
- Low Marker Line (Cyan): Tracks the lowest point reached during selling phases
- Creates visual boundaries showing pressure extremes
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important pressure peaks
- Helps identify potential reversal points and pressure exhaustion
Reference Lines:
- Overbought Level: Threshold for extreme selling pressure
- Oversold Level: Threshold for extreme buying pressure
- Used to identify potential reversal zones
Core Components
1. Volume Pressure Calculation
- Separation of up-volume and down-volume
- Calculation of net volume pressure
- Smoothing for consistent visualization
- Normalization against total volume for percentage scaling
2. Boundary Tracking System
- Automatic detection of highest values in buying phases
- Automatic detection of lowest values in selling phases
- Step-line visualization of boundaries
- Color-coded for easy identification
3. Peak Detection System
- Identification of local maxima and minima
- Background highlighting of significant peaks
- Triangle markers for peak visualization
- Zero-line cross detection for trend changes
4. Threshold Settings
- Extreme threshold multiplier for identifying significant pressure
- Overbought/oversold levels for potential reversals
- Dynamic color coding based on pressure intensity
- Alert conditions for key pressure levels
Main Features
Volume Analysis Settings
- Customizable volume MA length
- Signal smoothing for clearer readings
- Optional log scale for handling wide range variations
- Adjustable threshold multiplier for sensitivity
Visual Elements
- Color-coded columns showing pressure direction and strength
- Dynamic marker lines for pressure boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
- Overbought/oversold reference lines
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for pressure strength
- Peak formation for potential reversals
- Color changes for pressure direction and intensity
- Alert conditions for extreme pressure levels
Customization Options
- Volume analysis parameters
- Marker line visibility and colors
- Peak marker display options
- Log scale toggle for handling various markets
- Overbought/oversold threshold adjustments
Trading Applications
1. Trend Identification
- Volume pressure crossing above zero: buying pressure emerging
- Volume pressure crossing below zero: selling pressure emerging
- Column color: indicates pressure direction
- Column height: indicates pressure strength
- Signal line: confirms overall trend direction
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Volume pressure approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing pressure
- Readings beyond overbought/oversold levels: potential reversal zones
3. Pressure Analysis
- Breaking above previous high boundary: accelerating buying pressure
- Breaking below previous low boundary: accelerating selling pressure
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Extreme readings: potential climactic buying/selling
4. Market Structure Assessment
- Consecutive higher peaks: strengthening buying structure
- Consecutive lower troughs: strengthening selling structure
- Peak comparisons: relative strength of pressure phases
- Boundary line steps: market structure levels
Optimization Guide
1. Volume Analysis Settings
- Volume MA Length: Default 25 provides balanced signals
- Lower values (10-15): More responsive, potentially noisier
- Higher values (30-50): Smoother, fewer false signals
- Signal Smoothing Length: Default 8 provides good balance
- Lower values: More responsive to pressure changes
- Higher values: Smoother trend identification
2. Threshold Settings
- Extreme Threshold Multiplier: Default 20.0
- Lower values: More signals, potentially more noise
- Higher values: Fewer signals, but more significant
- Overbought/Oversold Levels: Defaults at 20/-20
- Adjust based on instrument volatility
- Wider settings for more volatile instruments
3. Visual Customization
- Marker Line Colors: Adjust for visibility on your chart
- Peak Marker Color: Default yellow provides good contrast
- Enable/disable background highlights based on preference
- Consider log scale for instruments with wide volume ranges
4. Alert Settings
- Configure alerts for high buying pressure
- Configure alerts for high selling pressure
- Set additional alerts for zero-line crosses
- Consider timeframe when setting alert sensitivity
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm pressure changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong pressure
- Use with price action for entry/exit precision
- Consider extreme threshold crossings as significant signals
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Multiple timeframes: confirm signals across time horizons
- Match to your trading style and holding period
3. Market Context
- Strong buying phase: positive columns breaking above marker line
- Strong selling phase: negative columns breaking below marker line
- Columns approaching zero: potential pressure shift
- Columns beyond overbought/oversold: extreme conditions, potential reversal
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with price action oscillators for divergence detection
- Combine with traditional volume indicators for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when volume pressure breaks above previous high marker line
- Enter short when volume pressure breaks below previous low marker line
- Use zero-line as initial stop-loss reference
- Take profits at formation of opposing peaks
2. Peak Trading Strategy
- Identify significant peaks with triangular markers
- Look for consecutive lower peaks in buying phases for shorting opportunities
- Look for consecutive higher troughs in selling phases for buying opportunities
- Use zero-line crosses as confirmation
3. Extreme Reading Strategy
- Look for volume pressure beyond overbought/oversold levels
- Watch for color changes and peak formations
- Enter counter-trend positions after confirmed peaks
- Use tight stops due to extreme market conditions
4. Volume Color Strategy
- Enter long when columns turn bright green (increasing buying pressure)
- Enter short when columns turn bright red (increasing selling pressure)
- Exit when color intensity fades (decreasing pressure)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Volume pressure crosses above zero line
- Green columns grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant buying pressure peaks
Bearish Market Scenario
- Volume pressure crosses below zero line
- Red columns grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant selling pressure troughs
Consolidation Scenario
- Volume pressure oscillates around zero line
- Column colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Pressure values remain small
Understanding Market Dynamics Through Market Push Meter
At its core, this indicator provides a unique lens to visualize market pressure through volume analysis:
1. Volume Imbalance: By separating and comparing buying volume (up candles) from selling volume (down candles), the indicator provides insights into which side is exerting more pressure in the market.
2. Normalized Pressure: The indicator normalizes volume pressure as a percentage of total volume, making it more comparable across different market conditions and instruments.
3. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of pressure in both directions, helping to identify when markets are making new pressure extremes.
4. Exhaustion Signals: The peak detection system highlights moments where pressure has reached a local maximum or minimum, often precursors to reversals or consolidations.
Remember:
- Combine signals from volume pressure, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences and market
- Consider overall market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
DISCLAIMER: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
ZenAlgo - QZenAlgo - Q
Description
ZenAlgo - Q is an oscillator based on the QQE (Quantitative Qualitative Estimation) method. This version incorporates refinements for additional visualization and interpretation options. It is designed to help traders observe momentum changes and divergence patterns in price movements.
Key Features
QQE-Based Calculation : Derived from the open-source QQE script by Glaz (Metastock Version of QQE), with modifications for alternative visualization.
Dual RSI-Based Analysis : Uses two RSI calculations to provide additional context on price movements.
Adaptive Trend Bands : Adjust dynamically based on the market conditions.
Divergence Identification : Highlights potential differences between price action and oscillator movement.
Dynamic Color Coding : Displays histogram bars to illustrate shifts in oscillator values.
Configurable Alerts : Enables notifications for specific oscillator conditions.
How It Works
The indicator calculates a smoothed RSI-based oscillator that tracks the relative strength of price movement. It applies an exponential moving average (EMA) smoothing to reduce noise while maintaining responsiveness.
Two adaptive bands are calculated using a variation of the QQE method, which helps define dynamic overbought and oversold conditions.
The histogram bars shift in color based on the position of the oscillator relative to the bands. Lighter shades indicate weaker momentum, while stronger momentum is represented by more saturated colors.
The script also includes a secondary RSI component, which provides an additional layer of analysis. This secondary RSI helps refine momentum trends by smoothing out short-term fluctuations.
Divergence identification is built-in, highlighting where price action deviates from oscillator readings. Bullish divergence occurs when price forms a lower low while the oscillator forms a higher low, and bearish divergence is identified when price forms a higher high while the oscillator forms a lower high.
The indicator does not generate buy or sell signals but instead provides contextual information that can be used alongside other trading strategies.
Use Cases
Trend Observation : Traders can use the histogram to observe whether momentum is strengthening or weakening over time. A shift in color can indicate a potential change in trend strength.
Divergence Analysis : By comparing oscillator divergence with price movement, traders can identify situations where price action may be losing momentum. Divergences do not guarantee reversals but can serve as an early warning to re-evaluate positions.
Momentum Tracking : The dual RSI structure allows users to monitor both short-term and long-term momentum. When both RSI components are aligned, it suggests a more stable trend, while divergence between them may indicate potential consolidation or trend shifts.
Supplementary Analysis : This indicator is best used as a supporting tool alongside volume-based or trend-following indicators. It helps visualize underlying price behavior but should not be used in isolation for decision-making.
Market Context Interpretation : The combination of adaptive bands and histogram visualization allows traders to assess how recent price action compares to historical movement, helping to place current conditions in a broader market context.
Attribution
This script is an adaptation of the open-source QQE script originally developed by Glaz. We acknowledge and appreciate the original author's work, which served as a foundation for our modifications.
Disclaimer
This indicator is intended for informational purposes only. It should not be interpreted as financial advice. Always conduct independent research and risk management before making trading decisions.
Metaphor Vigour Ratio### **Script Name:** Metaphor Vigour Ratio
**Short Title:** Metaphor Vigour Ratio
**Author:** Sovit Manjani, CMT
**Description:**
The Metaphor Vigour Ratio (MVRatio) is a powerful Relative Strength Indicator designed for assessing normalized relative strength. It is versatile and can be applied to any script or used to rank symbols based on their intermarket relative strength.
---
### **Features:**
1. **Bullish and Bearish Signals:**
- **Above 100:** Indicates a bullish trend.
- **Below 100:** Indicates a bearish trend.
2. **Trend Analysis with Slope:**
- **Slope Rising:** Suggests bullish momentum.
- **Slope Falling:** Suggests bearish momentum.
3. **Stock Selection Strategy:**
- Identify and rank stocks based on the MVRatio. For example, buy the top 10 stocks of Nifty with the highest MVRatio values for strong performance potential.
---
### **Inputs:**
1. **Fast EMA Period (RSEMAFast):** Default set to 10. Controls the sensitivity of the Fast Moving Average.
2. **Slow EMA Period (RSEMASlow):** Default set to 30. Provides a stable trend base with the Slow Moving Average.
3. **Smooth EMA Period (SmoothEMA):** Default set to 3. Smooths the MVRatio for better clarity.
4. **Close Source:** Default is the closing price, but it can be customized as needed.
5. **Comparative Symbol (ComparativeTickerId):** Default is "NSE:NIFTY," allowing comparison against a benchmark index.
---
### **Calculation Logic:**
1. **Relative Strength (RS):**
- Calculated as the ratio of the base symbol's price to the comparative symbol's price.
2. **Exponential Moving Averages (FastMA and SlowMA):**
- Applied to the RS to smooth and differentiate trends.
3. **Metaphor Vigour Ratio (MVRatio):**
- Computed as the ratio of FastMA to SlowMA, scaled by 100, and further smoothed using SmoothEMA.
---
### **Visualization:**
1. **MVRatio Plot (Blue):**
- Represents the relative strength dynamics.
2. **Reference Line at 100 (Gray):**
- Helps quickly identify bullish (above 100) and bearish (below 100) zones.
---
### **How to Use:**
1. Add the indicator to your chart from TradingView's Pine Script editor.
2. Compare the performance of any symbol relative to a benchmark (e.g., Nifty).
3. Analyze trends, slopes, and ranking based on MVRatio values to make informed trading decisions.
---
**Note:** This indicator is for educational purposes and should be used alongside other analysis methods to make trading decisions.
Strength of Divergence Across Multiple Indicators (+CMF&VWMACD)Modified Version of Strength of Divergence Across Multiple Indicators by reees
Purpose:
This Pine Script indicator is designed to identify and evaluate the strength of bullish and bearish divergences across multiple technical indicators. Divergences occur when the price of an asset is moving in one direction while a technical indicator is moving in the opposite direction, potentially signaling a trend reversal.
Key Features:
1. Multiple Indicator Support: The script now analyzes divergences for the following indicators:
* RSI (Relative Strength Index)
* OBV (On-Balance Volume)
* MACD (Moving Average Convergence/Divergence)
* STOCH (Stochastic Oscillator)
* CCI (Commodity Channel Index)
* MFI (Money Flow Index)
* AO (Awesome Oscillator)
* CMF (Chaikin Money Flow) - Newly added
* VWMACD (Volume-Weighted MACD) - Newly added
2. Customizable Divergence Parameters:
* Bullish/Bearish: Enable or disable the detection of bullish and bearish divergences independently.
* Regular/Hidden: Detect both regular and hidden divergences (hidden divergences can indicate trend continuation).
* Broken Trendline Exclusion: Optionally ignore divergences where the trendline connecting price pivots is broken by an intermediate pivot.
* Pivot Lookback Periods: Adjust the number of bars used to identify valid pivot highs and lows for divergence calculations.
* Weighting: Assign different weights to regular vs. hidden divergences and to the relative change in price vs. the indicator.
3. Indicator-Specific Settings:
* Weight: Each indicator can be assigned a weight, influencing its contribution to the overall divergence strength calculation.
* Extreme Value: Define a threshold above which an indicator's divergence is considered "extreme," giving it a higher strength rating.
4. Divergence Strength Calculation:
* For each indicator, the script calculates a divergence "degree" based on the magnitude of the divergence and the user-defined weightings.
* The total divergence strength is the sum of the individual indicator divergence degrees.
* Strength is categorized as "Extreme," "Very strong," "Strong," "Moderate," "Weak," or "Very weak."
5. Visualization:
* Divergence Lines: The script draws lines on the chart connecting the price and indicator pivots that form a divergence (optional, with customizable transparency).
* Labels: Labels display the total divergence strength and a breakdown of each indicator's contribution. The size and visibility of labels are based on the strength.
6. Alerts:
* The script can generate alerts when the total divergence strength exceeds a user-defined threshold.
New Indicators (CMF and VWMACD):
* Chaikin Money Flow (CMF):
* Purpose: Measures the buying and selling pressure by analyzing the relationship between price, volume, and the accumulation/distribution line.
* Divergence: A bullish CMF divergence occurs when the price makes a lower low, but the CMF makes a higher low (suggesting increasing buying pressure). A bearish divergence is the opposite.
* Volume-Weighted MACD (VWMACD):
* Purpose: Similar to the standard MACD but uses volume-weighted moving averages instead of simple moving averages, giving more weight to periods with higher volume.
* Divergence: Divergences are interpreted similarly to the standard MACD, but the VWMACD can be more sensitive to volume changes.
How It Works (Simplified):
1. Pivot Detection: The script identifies pivot highs and lows in both price and the selected indicators using the specified lookback periods.
2. Divergence Check: For each indicator:
* It checks if a series of pivots in price and the indicator are diverging (e.g., price makes a lower low, but the indicator makes a higher low for a bullish divergence).
* It calculates the divergence degree based on the difference in price and indicator values, weightings, and whether it's a regular or hidden divergence.
3. Strength Aggregation: The script sums up the divergence degrees of all enabled indicators to get the total divergence strength.
4. Visualization and Alerts: It draws lines and labels on the chart to visualize the divergences and generates alerts if the total strength exceeds the set threshold.
Benefits:
* Comprehensive Divergence Analysis: By considering multiple indicators, the script provides a more robust assessment of potential trend reversals.
* Customization: The many adjustable parameters allow traders to fine-tune the script to their specific trading style and preferences.
* Objective Strength Evaluation: The divergence strength calculation and categorization offer a more objective way to evaluate the significance of divergences.
* Early Warning System: Divergences can often precede significant price movements, making this script a valuable tool for anticipating potential trend changes.
* Volume Confirmation: The inclusion of CMF and VWMACD add volume-based confirmation to the divergence signals, potentially increasing their reliability.
Limitations:
* Lagging Indicators: Most of the indicators used are lagging, meaning they are based on past price data. Divergences may sometimes occur after a significant price move has already begun.
* False Signals: No indicator is perfect, and divergences can sometimes produce false signals, especially in choppy or ranging markets.
* Subjectivity: While the script aims for objectivity, some settings (like weightings and extreme values) still involve a degree of subjective judgment.
MTF RSI+CMO PROThis RSI+CMO script combines the Relative Strength Index (RSI) and Chande Momentum Oscillator (CMO), providing a powerful tool to help traders analyze price momentum and spot potential turning points in the market. Unlike using RSI alone, the CMO (especially with a 14-period length) moves faster and accentuates price pops and dips in the histogram, making price shifts more apparent.
Indicator Features:
➡️RSI and CMO Combined: This indicator allows traders to track both RSI and CMO values simultaneously, highlighting differences in their movement. RSI and CMO values are both plotted on the histogram, while CMO values are also drawn as a line moving through the histogram, giving a visual representation of their relationship. The often faster-moving CMO accentuates short-term price movements, helping traders spot subtle shifts in momentum that the RSI might smooth out.
➡️Multi-Time Frame Table: A real-time, multi-time frame table displays RSI and CMO values across various timeframes. This gives traders an overview of momentum across different intervals, making it easier to spot trends and divergences across short and long-term time frames.
➡️Momentum Chart Label: A chart label compares the current RSI and CMO values with values from 1 and 2 bars back, providing an additional metric to gauge momentum. This feature allows traders to easily see if momentum is increasing or decreasing in real-time.
➡️RSI/CMO Bullish and Bearish Signals: Colored arrow plot shapes (above the histogram) indicate when RSI and CMO values are signaling bullish or bearish conditions. For example, green arrows appear when RSI is above 65, while purple arrows show when RSI is below 30 and CMO is below -40, indicating strong bearish momentum.
➡️Divergences in Histogram: The histogram can make it easier for traders to spot divergences between price and momentum. For instance, if the price is making new highs but the RSI or CMO is not, a bearish divergence may be forming. Similarly, bullish divergences can be spotted when prices are making lower lows while RSI or CMO is rising.
➡️Alert System: Alerts are built into the indicator and will trigger when specific conditions are met, allowing traders to stay informed of potential entry or exit points based on RSI and CMO levels without constantly monitoring the chart. These are set manually. Look for the 3 dots in the indicator name.
How Traders Can Use the Indicator:
💥Identifying Momentum Shifts: The RSI+CMO combination is ideal for spotting momentum shifts in the market. Traders can monitor the histogram and the CMO line to determine if the market is gaining or losing strength.
💥Confirming Trade Entries/Exits: Use the real-time RSI and CMO values across multiple time frames to confirm trades. For instance, if the 1-hour RSI is above 70 but the 1-minute RSI is turning down, it could indicate short-term overbought conditions, signaling a potential exit or reversal.
💥Spotting Divergences: Divergences are critical for predicting potential reversals. The histogram can be used to spot divergences when RSI and CMO values deviate from price action, offering an early signal of market exhaustion.
💥Tracking Multi-Time Frame Trends: The multi-time frame table provides insight into the market’s overall trend across several timeframes, helping traders ensure their decisions align with both short and long-term trends.
RSI vs. CMO: Why Use Both?
While both RSI and CMO measure momentum, the CMO often moves faster with a value of 14 for example, reacting to price changes more quickly. This makes it particularly effective for detecting sharp price movements, while RSI helps smooth out price action. By using both, traders get a clearer picture of the market's momentum, particularly during volatile periods.
Confluence and Price Fluidity:
One of the powerful ways to enhance the effectiveness of this indicator is by using it in conjunction with other technical analysis tools to create confluence. Confluence occurs when multiple indicators or price action signals align, providing stronger confirmation for a trade decision. For example:
🎯Support and Resistance Levels: Traders can use RSI+CMO in combination with key support and resistance zones. If the price is nearing a support level and RSI+CMO values start to signal a bullish reversal, this alignment strengthens the case for entering a long position.
🎯Moving Averages: When the RSI+CMO signals a potential trend reversal and this is confirmed by a crossover in moving averages (such as a 50-day and 200-day moving average), traders gain additional confidence in the trade direction.
🎯Momentum Indicators: Traders can also look for momentum indicators like the MACD to confirm the strength of a trend or potential reversal. For instance, if the RSI+CMO values start to decrease rapidly while both the RSI+CMO also shows overbought conditions, this could provide stronger confirmation to exit a long trade or enter a short position.
🎯Candlestick Patterns: Price fluidity can be monitored using candlestick formations. For example, a bearish engulfing pattern with decreasing RSI+CMo values offers confluence, adding confidence to the signal to close or short the trade.
By combining the MTF RSI+CMO PRO with other tools, traders ensure that they are not relying on a single indicator. This layered approach can reduce the likelihood of false signals and improve overall trading accuracy.
