Ultimate RSI (2) TDBurbin's RSI Alerts:
RSI alerts can be used ONLY when you're awaiting a chart to shift it's momentum. Example: You are waiting for a take profit signal and you'd like a push notification when this is triggered.
These are NOT intended to be Buy and Sell signals. Only to get your attention. Pair with other confirmations.
This is a modified version of LuxAlgo's Ultimate RSI. This is for education purposes only and personal use by Burbin. Inspired by AA, and dedicated to TD.
LuxAlgo's Description:
The Ultimate RSI indicator is a new oscillator based on the calculation of the Relative Strength Index that aims to put more emphasis on the trend, thus having a less noisy output. Opposite to the regular RSI, this oscillator is designed for a trend trading approach instead of a contrarian one.
🔶 USAGE
While returning the same information as a regular RSI, the Ultimate RSI puts more emphasis on trends, and as such can reach overbought/oversold levels faster as well as staying longer within these areas. This can avoid the common issue of an RSI regularly crossing an overbought or oversold level while the trend makes new higher highs/lower lows.
The Ultimate RSI crossing above the overbought level can be indicative of a strong uptrend (highlighted as a green area), while an Ultimate RSI crossing under the oversold level can be indicative of a strong downtrend (highlighted as a red area).
The Ultimate RSI crossing the 50 midline can also indicate trends, with the oscillator being above indicating an uptrend, else a downtrend. Unlike a regular RSI, the Ultimate RSI will cross the midline level less often, thus generating fewer whipsaw signals.
For even more timely indications users can observe the Ultimate RSI relative to its signal line. An Ultimate RSI above its signal line can indicate it is increasing, while the opposite would indicate it is decreasing.
🔹Smoothing Methods
Users can return more reactive or smoother results depending on the selected smoothing method used for the calculation of the Ultimate RSI. Options include:
Exponential Moving Average (EMA)
Simple Moving Average (SMA)
Wilder's Moving Average (RMA)
Triangular Moving Average (TMA)
These are ranked by the degree of reactivity of each method, with higher ones being more reactive (but less smooth).
Users can also select the smoothing method used by the signal line.
🔶 DETAILS
The RSI returns a normalized exponential average of price changes in the range (0, 100), which can be simply calculated as follows:
ema(d) / ema(|d|) × 50 + 50
🔶 SETTINGS
Length: Calculation period of the indicator
Method: Smoothing method used for the calculation of the indicator.
Source: Input source of the indicator
🔹Signal Line
Smooth: Degree of smoothness of the signal line
Method: Smoothing method used to calculation the signal line.
متذبذبات
Simple RSIThis script is just a fun little project I decided to do. It serves as a way for me to practice my coding and was not made with the intent of making money.
Market Regime (w/ Adaptive Thresholds)Logic Behind This Indicator
This indicator identifies market regimes (trending vs. mean-reverting) using adaptive thresholds that adjust to recent market conditions.
Core Components
1. Regime Score Calculation (0-100 scale)
Starts at 50 (neutral) and adjusts based on two factors:
A. Trend Strength
Compares fast EMA (5) vs. slow EMA (10)
If fast > slow by >1% → +60 points (strong uptrend)
If fast < slow by >1% → -60 points (strong downtrend)
B. RSI Momentum
Uses 7-period RSI smoothed with 3-period EMA
RSI > 70 → +20 points (overbought/trending)
RSI < 30 → -20 points (oversold/mean-reverting)
The score is then smoothed and clamped between 0-100.
2. Adaptive Thresholds
Instead of fixed levels, thresholds adjust to recent market behavior:
Looks back 100 bars to find the min/max regime score
High threshold = 80% of the range (trending regime)
Low threshold = 20% of the range (mean-reverting regime)
This prevents false signals in different volatility environments.
3. Regime Classification
Regime Score Classification Meaning
Above high threshold STRONG TREND Market is trending strongly (follow momentum)
Below low threshold STRONG MEAN REVERSION Market is choppy/oversold (fade moves)
Between thresholds NEUTRAL No clear regime (stay out or wait)
4. Regime Persistence Filter
Requires the regime to hold for a minimum number of bars (default: 1) before confirming
Prevents whipsaws from brief score fluctuations
What It Aims to Detect
When to use trend-following strategies (green = buy breakouts, ride momentum)
When to use mean-reversion strategies (red = buy dips, sell rallies)
When to stay out (gray = unclear conditions, high risk of false signals)
Visual Cues
Green background = Strong trend (momentum strategies work)
Red background = Strong mean reversion (contrarian strategies work)
Table = Shows current regime, color, and score
Alerts = Notifies when regime changes
Multiple Symbol Trend Screener [Pineify]Multiple Symbol Trend Screener Pineify – Ultimate Multi-Indicator Scanner for TradingView
Empower your trading with deep market insights across multiple symbols using this feature-rich Pine Script screener. The Multiple Symbol Trend Screener Pineify enables traders to monitor and compare trends, reversals, and consolidations in real-time across the biggest equity symbols on TradingView, through a synergistic blend of popular technical indicators.
Key Features
Monitor up to 15 symbols and their trends simultaneously
Integrates 7 professional-grade indicators: MA Distance, Aroon, Parabolic SAR (PSAR), ADX, Supertrend, Keltner Channel, and BBTrend
Color-coded table display for instant visual assessment
Customizable lookback periods, indicator types, and calculation methods
SEO optimized for multi-symbol trend detection, screener, and advanced TradingView indicator
How It Works
This indicator leverages TradingView’s Pine Script v6 and request.security() to process multiple symbols across selected timeframes. Data populates a dynamic table, updating each cell based on the calculated value of every underlying indicator. MA Distance highlights deviation from moving averages; Aroon flags emerging trend strength; PSAR marks potential trend reversals; ADX assesses trend momentum; Supertrend detects bullish/bearish phases; Keltner Channel and BBTrend offer volatility and power insights.
Set up your preferred symbols and timeframes
Each indicator runs its calculation per symbol using its parameter group
All results are displayed in a table for a comprehensive dashboard view
Trading Ideas and Insights
Traders can use this screener for cross-market comparison, directional bias, entry/exit filtering, and comprehensive trend evaluation. The screener is excellent for swing trading, day trading, and portfolio tracking. It enables confirmation across multiple frameworks — for example, spotting momentum with ADX before confirming direction with Supertrend and PSAR.
Identify correlated movements or divergences across selected assets
Spot synchronized trend changes for basket trading ideas
Filter symbols by volatility, strength, or trend status for precise trade selection
How Multiple Indicators Work Together
The screener’s edge lies in its intelligent correlation of popular indicators. MA Distance measures the proximity to chosen moving averages, ideal for spotting overbought/oversold conditions. Aroon reveals the strength of new price trends, PSAR indicates reversal signals, and ADX quantifies the momentum of these trends. Supertrend provides a directional phase, while Keltner Channel & BBTrend analyze volatility shifts and band compressions. This amalgamation allows for a robust, multi-dimensional market snapshot, capturing details missed by single-indicator tools.
By displaying all key metrics side-by-side, the screener enables holistic decision-making, revealing confluence zones and contradiction areas across multiple tickers and timeframes.
Unique Aspects
Original implementation combining seven independent trend and momentum indicators for each symbol
Rich customization for symbols, timeframes, and all indicator parameters
Intuitive color-coding for quick reading of bullish/bearish/neutral signals
Comprehensive dashboard for instant actionable insights
How to Use
Load the indicator onto your TradingView chart
Go to the script’s settings and input your preferred symbols and relevant timeframes
Set your desired parameters for each indicator group: Moving Average type, Aroon length, PSAR values, ADX smoothing, etc.
Observe the results in the top-right table, then use it to filter candidates and validate trade setups
The screener is suitable for all timeframes and asset classes available on TradingView. Make sure your chart’s timeframe matches the one used in the scanner for optimal accuracy.
Customization
Choose up to 15 symbols to monitor in a single dashboard
Customize lookback periods, indicator types, colors, and display settings
Configure alerting options and thresholds for advanced trade automation
Conclusion
The Multiple Symbol Trend Screener Pineify sets a new standard for multi-asset screening on TradingView. By elegantly merging seven proven technical indicators, the screener delivers powerful trend detection, reversal analysis, and volatility monitoring — all in one dashboard. Take your trading to new heights with in-depth, customizable market surveillance.
Advanced RSI with Divergence RCT This indicator provides a comprehensive RSI analysis tool by combining the classic Relative Strength Index (RSI) with a smoothing Simple Moving Average (SMA), clearly defined overbought/oversold zones, and an advanced divergence detection engine.
--- Key Features ---
1. RSI with SMA: Plots the standard RSI along with a user-defined SMA of the RSI. This helps to smooth out price action and confirm the underlying trend, identifying potential buy/sell signals on crossovers.
2. Overbought/Oversold Levels: Highlights the extreme zones with dotted horizontal lines at 80 (overbought) and 20 (oversold), providing clear visual cues for potential market reversals.
3. Advanced Divergence Detection: Automatically identifies and plots both regular and hidden divergences (bullish and bearish) directly on the chart. This helps traders spot potential reversals that are not obvious from price action alone.
--- How to Use ---
- Trend Confirmation: When the RSI crosses above its SMA, it can signal a strengthening bullish trend. A cross below can signal a strengthening bearish trend.
- Reversal Zones: When the RSI enters the overbought zone (>80) or oversold zone (<20), traders may watch for a reversal in price.
- Divergence Signals:
- A Bullish Divergence (green label 'R') occurs when the price makes a lower low, but the RSI makes a higher low, suggesting downward momentum is fading.
- A Bearish Divergence (red label 'R') occurs when the price makes a higher high, but the RSI makes a lower high, suggesting upward momentum is fading.
- Hidden Divergences ('H' labels) can indicate the continuation of an existing trend.
--- Disclaimer ---
This script is for informational and educational purposes only. It is not financial advice. Past performance is not indicative of future results. Always do your own research before making any trading decisions.
Weekly Confluence Setup [Final v6]Trend: EMA 21 and SMA 50
Momentum: MACD and RSI in a separate pane
Volume: Anchored VWAP from recent swing low
Confluence Signals: Clear triangle markers with optional alerts to the chart timeframe
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.
Stochastic Arrows Crossover with Alerts [TED]This indicator highlights key Stochastic %K and %D crossovers, helping traders identify potential buy and sell signals with visual triangle arrows and custom alerts. It uses the Stochastic Oscillator, which is a momentum indicator that compares the closing price to the price range over a given period.
Key Features:
Visual Arrows: The indicator plots green triangle-up arrows for bullish crossovers and red triangle-down arrows for bearish crossovers on the chart.
Customizable Parameters: You can adjust the period for %K, %D, and the smoothing factor to fit your trading strategy.
Overbought/Oversold Zones: The background color fills between the 80 (Overbought) and 20 (Oversold) levels, helping you visualize potential reversal areas.
Alerts: Set up dynamic alerts based on the crossover events, including:
Bullish and Bearish Crossovers
Crossover Events from the Previous Bar
How to Use:
Bullish Signal: When the %K line crosses above the %D line, it signals a potential buying opportunity. This is visually represented with a green triangle-up arrow on the chart.
Bearish Signal: When the %K line crosses below the %D line, it signals a potential selling opportunity, indicated by a red triangle-down arrow on the chart.
Overbought/Oversold Zones: The background color fill helps identify overbought or oversold market conditions, which may indicate a potential reversal.
Custom Alerts:
You can set alerts for:
Bullish Crossover: When the %K line crosses above the %D line.
Bearish Crossover: When the %K line crosses below the %D line.
Previous Bar Crossovers: Alerts for crossovers from one bar ago (helpful for backtesting).
Instructions:
Add the Indicator: Apply this Stochastic Arrows Crossover indicator to your chart from the public library.
Customize Settings: Adjust the input parameters like K period, D period, and Smoothing to match your preferred settings.
Enable Alerts:
Once added to your chart, you can set up alerts from the Alert Panel on TradingView.
Choose from the available alert conditions (Bullish Crossover, Bearish Crossover, or Crossover from the Previous Bar).
Set your desired timeframe and alert message to receive notifications for the crossovers.
Monitor the Chart: Keep an eye on the arrows and background color fill to interpret potential trade setups based on the Stochastic Oscillator's behavior.
MILLION MEN - Peaks & Dips MeterWhat it is
The MILLION MEN — Peaks & Dips Meter is a dynamic momentum visualization tool designed to identify extreme strength and exhaustion zones. It uses two selectable engines:
RSI Meter (ZS Core) for classic strength analysis.
OB/OS Multi-Length (ZS Quick Core) for adaptive readings that reflect multi-period sentiment shifts.
How it works
The script computes normalized momentum values (0–100) from price dynamics, builds a smooth gradient representation, and displays it as a fixed right-bottom table. The meter color scales between fuchsia and green, with optional candle coloring and percentage labels.
It can also highlight overbought (peaks) and oversold (dips) moments directly on candles with adjustable ATR offsets and label styles.
How to use
Values near 90–100% → potential short-term exhaustion (watch for reversals).
Values near 0–10% → potential accumulation zones (possible bounces).
Use together with structure, volume, or trend filters for confirmation.
Originality
Unlike standard RSI tools, this script merges multi-length OB/OS detection with a real-time visual meter, optimized for scalpers and visual traders. It does not repaint and maintains a lightweight structure for fast responsiveness.
Limitations
This indicator is for analysis purposes only and should not be considered financial advice. Past readings do not guarantee future performance.
Stochastic Enhanced [DCAUT]█ Stochastic Enhanced
📊 ORIGINALITY & INNOVATION
The Stochastic Enhanced indicator builds upon George Lane's classic momentum oscillator (developed in the late 1950s) by providing comprehensive smoothing algorithm flexibility. While traditional implementations limit users to Simple Moving Average (SMA) smoothing, this enhanced version offers 21 advanced smoothing algorithms, allowing traders to optimize the indicator's characteristics for different market conditions and trading styles.
Key Improvements:
Extended from single SMA smoothing to 21 professional-grade algorithms including adaptive filters (KAMA, FRAMA), zero-lag methods (ZLEMA, T3), and advanced digital filters (Kalman, Laguerre)
Maintains backward compatibility with traditional Stochastic calculations through SMA default setting
Unified smoothing algorithm applies to both %K and %D lines for consistent signal processing characteristics
Enhanced visual feedback with clear color distinction and background fill highlighting for intuitive signal recognition
Comprehensive alert system covering crossovers and zone entries for systematic trade management
Differentiation from Traditional Stochastic:
Traditional Stochastic indicators use fixed SMA smoothing, which introduces consistent lag regardless of market volatility. This enhanced version addresses the limitation by offering adaptive algorithms that adjust to market conditions (KAMA, FRAMA), reduce lag without sacrificing smoothness (ZLEMA, T3, HMA), or provide superior noise filtering (Kalman Filter, Laguerre filters). The flexibility helps traders balance responsiveness and stability according to their specific needs.
📐 MATHEMATICAL FOUNDATION
Core Stochastic Calculation:
The Stochastic Oscillator measures the position of the current close relative to the high-low range over a specified period:
Step 1: Raw %K Calculation
%K_raw = 100 × (Close - Lowest Low) / (Highest High - Lowest Low)
Where:
Close = Current closing price
Lowest Low = Lowest low over the %K Length period
Highest High = Highest high over the %K Length period
Result ranges from 0 (close at period low) to 100 (close at period high)
Step 2: Smoothed %K Calculation
%K = MA(%K_raw, K Smoothing Period, MA Type)
Where:
MA = Selected moving average algorithm (SMA, EMA, etc.)
K Smoothing = 1 for Fast Stochastic, 3+ for Slow Stochastic
Traditional Fast Stochastic uses %K_raw directly without smoothing
Step 3: Signal Line %D Calculation
%D = MA(%K, D Smoothing Period, MA Type)
Where:
%D acts as a signal line and moving average of %K
D Smoothing typically set to 3 periods in traditional implementations
Both %K and %D use the same MA algorithm for consistent behavior
Available Smoothing Algorithms (21 Options):
Standard Moving Averages:
SMA (Simple): Equal-weighted average, traditional default, consistent lag characteristics
EMA (Exponential): Recent price emphasis, faster response to changes, exponential decay weighting
RMA (Rolling/Wilder's): Smoothed average used in RSI, less reactive than EMA
WMA (Weighted): Linear weighting favoring recent data, moderate responsiveness
VWMA (Volume-Weighted): Incorporates volume data, reflects market participation intensity
Advanced Moving Averages:
HMA (Hull): Reduced lag with smoothness, uses weighted moving averages and square root period
ALMA (Arnaud Legoux): Gaussian distribution weighting, minimal lag with good noise reduction
LSMA (Least Squares): Linear regression based, fits trend line to data points
DEMA (Double Exponential): Reduced lag compared to EMA, uses double smoothing technique
TEMA (Triple Exponential): Further lag reduction, triple smoothing with lag compensation
ZLEMA (Zero-Lag Exponential): Lag elimination attempt using error correction, very responsive
TMA (Triangular): Double-smoothed SMA, very smooth but slower response
Adaptive & Intelligent Filters:
T3 (Tilson T3): Six-pass exponential smoothing with volume factor adjustment, excellent smoothness
FRAMA (Fractal Adaptive): Adapts to market fractal dimension, faster in trends, slower in ranges
KAMA (Kaufman Adaptive): Efficiency ratio based adaptation, responds to volatility changes
McGinley Dynamic: Self-adjusting mechanism following price more accurately, reduced whipsaws
Kalman Filter: Optimal estimation algorithm from aerospace engineering, dynamic noise filtering
Advanced Digital Filters:
Ultimate Smoother: Advanced digital filter design, superior noise rejection with minimal lag
Laguerre Filter: Time-domain filter with N-order implementation, adjustable lag characteristics
Laguerre Binomial Filter: 6-pole Laguerre filter, extremely smooth output for long-term analysis
Super Smoother: Butterworth filter implementation, removes high-frequency noise effectively
📊 COMPREHENSIVE SIGNAL ANALYSIS
Absolute Level Interpretation (%K Line):
%K Above 80: Overbought condition, price near period high, potential reversal or pullback zone, caution for new long entries
%K in 70-80 Range: Strong upward momentum, bullish trend confirmation, uptrend likely continuing
%K in 50-70 Range: Moderate bullish momentum, neutral to positive outlook, consolidation or mild uptrend
%K in 30-50 Range: Moderate bearish momentum, neutral to negative outlook, consolidation or mild downtrend
%K in 20-30 Range: Strong downward momentum, bearish trend confirmation, downtrend likely continuing
%K Below 20: Oversold condition, price near period low, potential bounce or reversal zone, caution for new short entries
Crossover Signal Analysis:
%K Crosses Above %D (Bullish Cross): Momentum shifting bullish, faster line overtakes slower signal, consider long entry especially in oversold zone, strongest when occurring below 20 level
%K Crosses Below %D (Bearish Cross): Momentum shifting bearish, faster line falls below slower signal, consider short entry especially in overbought zone, strongest when occurring above 80 level
Crossover in Midrange (40-60): Less reliable signals, often in choppy sideways markets, require additional confirmation from trend or volume analysis
Multiple Failed Crosses: Indicates ranging market or choppy conditions, reduce position sizes or avoid trading until clear directional move
Advanced Divergence Patterns (%K Line vs Price):
Bullish Divergence: Price makes lower low while %K makes higher low, indicates weakening bearish momentum, potential trend reversal upward, more reliable when %K in oversold zone
Bearish Divergence: Price makes higher high while %K makes lower high, indicates weakening bullish momentum, potential trend reversal downward, more reliable when %K in overbought zone
Hidden Bullish Divergence: Price makes higher low while %K makes lower low, indicates trend continuation in uptrend, bullish trend strength confirmation
Hidden Bearish Divergence: Price makes lower high while %K makes higher high, indicates trend continuation in downtrend, bearish trend strength confirmation
Momentum Strength Analysis (%K Line Slope):
Steep %K Slope: Rapid momentum change, strong directional conviction, potential for extended moves but also increased reversal risk
Gradual %K Slope: Steady momentum development, sustainable trends more likely, lower probability of sharp reversals
Flat or Horizontal %K: Momentum stalling, potential reversal or consolidation ahead, wait for directional break before committing
%K Oscillation Within Range: Indicates ranging market, sideways price action, better suited for range-trading strategies than trend following
🎯 STRATEGIC APPLICATIONS
Mean Reversion Strategy (Range-Bound Markets):
Identify ranging market conditions using price action or Bollinger Bands
Wait for Stochastic to reach extreme zones (above 80 for overbought, below 20 for oversold)
Enter counter-trend position when %K crosses %D in extreme zone (sell on bearish cross above 80, buy on bullish cross below 20)
Set profit targets near opposite extreme or midline (50 level)
Use tight stop-loss above recent swing high/low to protect against breakout scenarios
Exit when Stochastic reaches opposite extreme or %K crosses %D in opposite direction
Trend Following with Momentum Confirmation:
Identify primary trend direction using higher timeframe analysis or moving averages
Wait for Stochastic pullback to oversold zone (<20) in uptrend or overbought zone (>80) in downtrend
Enter in trend direction when %K crosses %D confirming momentum shift (bullish cross in uptrend, bearish cross in downtrend)
Use wider stops to accommodate normal trend volatility
Add to position on subsequent pullbacks showing similar Stochastic pattern
Exit when Stochastic shows opposite extreme with failed cross or bearish/bullish divergence
Divergence-Based Reversal Strategy:
Scan for divergence between price and Stochastic at swing highs/lows
Confirm divergence with at least two price pivots showing divergent Stochastic readings
Wait for %K to cross %D in direction of anticipated reversal as entry trigger
Enter position in divergence direction with stop beyond recent swing extreme
Target profit at key support/resistance levels or Fibonacci retracements
Scale out as Stochastic reaches opposite extreme zone
Multi-Timeframe Momentum Alignment:
Analyze Stochastic on higher timeframe (4H or Daily) for primary trend bias
Switch to lower timeframe (1H or 15M) for precise entry timing
Only take trades where lower timeframe Stochastic signal aligns with higher timeframe momentum direction
Higher timeframe Stochastic in bullish zone (>50) = only take long entries on lower timeframe
Higher timeframe Stochastic in bearish zone (<50) = only take short entries on lower timeframe
Exit when lower timeframe shows counter-signal or higher timeframe momentum reverses
Zone Transition Strategy:
Monitor Stochastic for transitions between zones (oversold to neutral, neutral to overbought, etc.)
Enter long when Stochastic crosses above 20 (exiting oversold), signaling momentum shift from bearish to neutral/bullish
Enter short when Stochastic crosses below 80 (exiting overbought), signaling momentum shift from bullish to neutral/bearish
Use zone midpoint (50) as dynamic support/resistance for position management
Trail stops as Stochastic advances through favorable zones
Exit when Stochastic fails to maintain momentum and reverses back into prior zone
📋 DETAILED PARAMETER CONFIGURATION
%K Length (Default: 14):
Lower Values (5-9): Highly sensitive to price changes, generates more frequent signals, increased false signals in choppy markets, suitable for very short-term trading and scalping
Standard Values (10-14): Balanced sensitivity and reliability, traditional default (14) widely used,适合 swing trading and intraday strategies
Higher Values (15-21): Reduced sensitivity, smoother oscillations, fewer but potentially more reliable signals, better for position trading and lower timeframe noise reduction
Very High Values (21+): Slow response, long-term momentum measurement, fewer trading signals, suitable for weekly or monthly analysis
%K Smoothing (Default: 3):
Value 1: Fast Stochastic, uses raw %K calculation without additional smoothing, most responsive to price changes, generates earliest signals with higher noise
Value 3: Slow Stochastic (default), traditional smoothing level, reduces false signals while maintaining good responsiveness, widely accepted standard
Values 5-7: Very slow response, extremely smooth oscillations, significantly reduced whipsaws but delayed entry/exit timing
Recommendation: Default value 3 suits most trading scenarios, active short-term traders may use 1, conservative long-term positions use 5+
%D Smoothing (Default: 3):
Lower Values (1-2): Signal line closely follows %K, frequent crossover signals, useful for active trading but requires strict filtering
Standard Value (3): Traditional setting providing balanced signal line behavior, optimal for most trading applications
Higher Values (4-7): Smoother signal line, fewer crossover signals, reduced whipsaws but slower confirmation, better for trend trading
Very High Values (8+): Signal line becomes slow-moving reference, crossovers rare and highly significant, suitable for long-term position changes only
Smoothing Type Algorithm Selection:
For Trending Markets:
ZLEMA, DEMA, TEMA: Reduced lag for faster trend entry, quick response to momentum shifts, suitable for strong directional moves
HMA, ALMA: Good balance of smoothness and responsiveness, effective for clean trend following without excessive noise
EMA: Classic choice for trending markets, faster than SMA while maintaining reasonable stability
For Ranging/Choppy Markets:
Kalman Filter, Super Smoother: Superior noise filtering, reduces false signals in sideways action, helps identify genuine reversal points
Laguerre Filters: Smooth oscillations with adjustable lag, excellent for mean reversion strategies in ranges
T3, TMA: Very smooth output, filters out market noise effectively, clearer extreme zone identification
For Adaptive Market Conditions:
KAMA: Automatically adjusts to market efficiency, fast in trends and slow in congestion, reduces whipsaws during transitions
FRAMA: Adapts to fractal market structure, responsive during directional moves, conservative during uncertainty
McGinley Dynamic: Self-adjusting smoothing, follows price naturally, minimizes lag in trending markets while filtering noise in ranges
For Conservative Long-Term Analysis:
SMA: Traditional choice, predictable behavior, widely understood characteristics
RMA (Wilder's): Smooth oscillations, reduced sensitivity to outliers, consistent behavior across market conditions
Laguerre Binomial Filter: Extremely smooth output, ideal for weekly/monthly timeframe analysis, eliminates short-term noise completely
Source Selection:
Close (Default): Standard choice using closing prices, most common and widely tested
HLC3 or OHLC4: Incorporates more price information, reduces impact of sudden spikes or gaps, smoother oscillator behavior
HL2: Midpoint of high-low range, emphasizes intrabar volatility, useful for markets with wide intraday ranges
Custom Source: Can use other indicators as input (e.g., Heikin Ashi close, smoothed price), creates derivative momentum indicators
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Responsiveness Characteristics:
Traditional SMA-Based Stochastic:
Fixed lag regardless of market conditions, consistent delay of approximately (K Smoothing + D Smoothing) / 2 periods
Equal treatment of trending and ranging markets, no adaptation to volatility changes
Predictable behavior but suboptimal in varying market regimes
Enhanced Version with Adaptive Algorithms:
KAMA and FRAMA reduce lag by up to 40-60% in strong trends compared to SMA while maintaining similar smoothness in ranges
ZLEMA and T3 provide near-zero lag characteristics for early entry signals with acceptable noise levels
Kalman Filter and Super Smoother offer superior noise rejection, reducing false signals in choppy conditions by estimations of 30-50% compared to SMA
Performance improvements vary by algorithm selection and market conditions
Signal Quality Improvements:
Adaptive algorithms help reduce whipsaw trades in ranging markets by adjusting sensitivity dynamically
Advanced filters (Kalman, Laguerre, Super Smoother) provide clearer extreme zone readings for mean reversion strategies
Zero-lag methods (ZLEMA, DEMA, TEMA) generate earlier crossover signals in trending markets for improved entry timing
Smoother algorithms (T3, Laguerre Binomial) reduce false extreme zone touches for more reliable overbought/oversold signals
Comparison with Standard Implementations:
Versus Basic Stochastic: Enhanced version offers 21 smoothing options versus single SMA, allowing optimization for specific market characteristics and trading styles
Versus RSI: Stochastic provides range-bound measurement (0-100) with clear extreme zones, RSI measures momentum speed, Stochastic offers clearer visual overbought/oversold identification
Versus MACD: Stochastic bounded oscillator suitable for mean reversion, MACD unbounded indicator better for trend strength, Stochastic excels in range-bound and oscillating markets
Versus CCI: Stochastic has fixed bounds (0-100) for consistent interpretation, CCI unbounded with variable extremes, Stochastic provides more standardized extreme readings across different instruments
Flexibility Advantages:
Single indicator adaptable to multiple strategies through algorithm selection rather than requiring different indicator variants
Ability to optimize smoothing characteristics for specific instruments (e.g., smoother for crypto volatility, faster for forex trends)
Multi-timeframe analysis with consistent algorithm across timeframes for coherent momentum picture
Backtesting capability with algorithm as optimization parameter for strategy development
Limitations and Considerations:
Increased complexity from multiple algorithm choices may lead to over-optimization if parameters are curve-fitted to historical data
Adaptive algorithms (KAMA, FRAMA) have adjustment periods during market regime changes where signals may be less reliable
Zero-lag algorithms sacrifice some smoothness for responsiveness, potentially increasing noise sensitivity in very choppy conditions
Performance characteristics vary significantly across algorithms, requiring understanding and testing before live implementation
Like all oscillators, Stochastic can remain in extreme zones for extended periods during strong trends, generating premature reversal signals
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to provide traders with enhanced flexibility in momentum analysis. The Stochastic Oscillator has limitations and should not be used as the sole basis for trading decisions.
Important Considerations:
Algorithm performance varies with market conditions - no single smoothing method is optimal for all scenarios
Extreme zone signals (overbought/oversold) indicate potential reversal areas but not guaranteed turning points, especially in strong trends
Crossover signals may generate false entries during sideways choppy markets regardless of smoothing algorithm
Divergence patterns require confirmation from price action or additional indicators before trading
Past indicator characteristics and backtested results do not guarantee future performance
Always combine Stochastic analysis with proper risk management, position sizing, and multi-indicator confirmation
Test selected algorithm on historical data of specific instrument and timeframe before live trading
Market regime changes may require algorithm adjustment for optimal performance
The enhanced smoothing options are intended to provide tools for optimizing the indicator's behavior to match individual trading styles and market characteristics, not to create a perfect predictive tool. Responsible usage includes understanding the mathematical properties of selected algorithms and their appropriate application contexts.
RSI Zones + Swing Divergences + OB/OS zones By HappyRsi with + divergences/ convergences + OB/OS zones
hidden bull/bear
Liquidity ROC Z-Score (Composite) — kWhDealer_Developed by @kWhDealer_, this indicator tracks the rate-of-change and standard-deviation momentum of U.S. system liquidity by combining key Federal Reserve and Treasury data:
Composite Liquidity
=
WALCL
−
WTREGEN
−
RRPONTSYD
+
MTSDS133FMS
Composite Liquidity=WALCL−WTREGEN−RRPONTSYD+MTSDS133FMS
It measures the flow of liquidity available to markets—integrating monetary policy (Fed balance sheet, reverse repo, TGA) with fiscal policy (Treasury deficit spending).
The script converts this composite into a Rate-of-Change (ROC) oscillator and expresses it as a Z-Score, with ±1 σ / ±2 σ bands to highlight over- and under-injection regimes.
Z > +1 σ → expanding liquidity → risk-on bias
Z < –1 σ → contracting liquidity → risk-off bias
Crosses of 0 often precede equity index inflections by ~1–2 months
This oscillator serves as a leading macro gauge for shifts in liquidity-driven risk appetite across equities, credit, and crypto.
ADX-DEMA-KAMA StrategyThis is a trend-following indicator that combines three technical tools:
DEMA (Double Exponential Moving Average) - Fast-responding trend line
KAMA (Kaufman's Adaptive Moving Average) - Adaptive trend line that adjusts to market volatility
ADX (Average Directional Index) with DI+/DI- - Measures trend strength and direction
How it works:
Buy Signal: DEMA crosses above KAMA when ADX is rising and DI+ > DI-
Sell Signal: DEMA crosses below KAMA when ADX is rising and DI- > DI+
The indicator displays both moving averages on the chart, plots buy/sell arrows, and shows a status table with current values. It only triggers trades when there's strong trend confirmation from all three components.RetryClaude can make mistakes. Please double-check responses.
Sentiment NavigatorFREE|SuperFundedSentiment Navigator — Momentum × Volatility Heatmap
What it is
Sentiment Navigator blends momentum (RSI) with volatility (ATR normalized by price) to visualize market psychology using a background heatmap and a lower oscillator.
・Background: quick read of the market’s “temperature” → Extreme Greed / Greed / Neutral / Fear / Extreme Fear.
・Oscillator: a bounded sentiment score from -100 to +100 showing bias strength and potential extremes.
Why this is not a simple mashup
Instead of showing RSI and ATR separately, this tool integrates them into a single, weighted score and a state machine:
・Context-aware weighting: When volatility is high (ATR vs its SMA baseline), the score is amplified, reflecting that momentum matters more in turbulent regimes.
・Unified states: RSI thresholds classify regimes (Greed/Fear) and are conditioned by volatility to promote Extreme states only when justified.
・Actionable cues: Reversal labels appear at the extreme levels with candle confirmation to reduce noise.
How it works (concise)
1. Momentum: RSI(len) (default 21).
2. Volatility: ATR(len)/close*100 (default ATR=14), smoothed by SMA(volSmaLen) and compared using volMultiplier.
3. Sentiment score: transform RSI to (-100..+100) via (RSI-50)*2, then amplify ×1.5 when high volatility. Finally clamp to .
4. States:
・RSI > greedLevel → Greed (upgraded to Extreme Greed if high vol)
・RSI < fearLevel → Fear (upgraded to Extreme Fear if high vol)
・else Neutral
5. Plotting:
・Oscillator (area) with 0-line and dotted extreme bands.
・Background color by state (greens for Greed, reds for Fear, gray for Neutral).
6. Signals (optional):
・Buy: crossover(score, -extremeGreedLevel) and close > open → prints ▲ at -extremeGreedLevel
・Sell: crossunder(score, extremeGreedLevel) and close < open → prints ▼ at +extremeGreedLevel
Parameters (UI mapping)
Core
・RSI Length (rsiLen)
・ATR Length (atrLen)
・Volatility SMA Length (volSmaLen)
・High-Vol Multiplier (volMultiplier)
State thresholds
・Extreme Greed (extremeGreedLevel)
・Greed (greedLevel)
・Fear (fearLevel)
・Extreme Fear (extremeFearLevel)
Display
・Show Background (showBgColor)
・Show Reversal Signals (showSignals)
Practical usage
・Regime read: Treat greens as risk-on bias, reds as risk-off, gray as indecision.
・Entries: Use ▲/▼ as triggers, not commands—wait for price action (wicks/engulfings) at structure.
・Extreme management: At Extreme states, favor mean-reversion tactics; in plain Greed/Fear with low vol, trends may persist longer.
・Tuning:
・Raise greedLevel/fearLevel to reduce signals.
・Increase volMultiplier to demand stronger vol for “Extreme” states.
Repainting & confirmation
Signals rely on cross events of the oscillator; judge on bar close for stricter rules. Background/state can change intrabar as RSI/ATR evolve.
Disclaimer
No indicator guarantees outcomes. News/liquidity can override signals. Trade responsibly with proper risk controls.
Sentiment Navigator — クイックガイド（日本語）
概要
本インジは RSI（モメンタム） と ATR/価格（ボラティリティ） を統合し、背景のヒートマップと下部オシレーターで市場心理を可視化します。
・背景色：極度の強欲 / 強欲 / 中立 / 恐怖 / 極度の恐怖 を直感表示。
・オシレーター：-100〜+100 のスコアでバイアスの強さと過熱を示します。
独自性・新規性
・高ボラ状態ではスコアを増幅し、同じRSIでも環境次第で体感インパクトを反映。
・RSIしきい値×ボラで極端ゾーンの発生を制御し、意義のあるExtremeのみ点灯。
・反転ラベルは極端レベルのクロス＋ローソク条件で点灯し、ノイズを抑制。
仕組み（要点）
1. RSI を算出。
2. ATR/close*100 を SMA と比較し、しきい値倍率で高ボラを判定。
3. score = (RSI-50)*2 を 高ボラで×1.5、 にクランプ。
4. 状態：RSI>Greed → Greed/Extreme Greed、RSI
🐬RSI_CandleRSI_Candle
Calculates the RSI based on the open, high, low, and close prices, and displays it in the form of candles.
The overbought and oversold zones are highlighted with background colors, which become darker as the RSI value approaches 100 or 0.
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RSI_Candle
RSI를 시가, 고가, 저가, 종가로 계산하여 캔들로 보여줍니다.
과매수/과매도 구간에서 배경색으로 보여주며, 100/0에 가까울수록 배경색이 짙어집니다.
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🐬Stochastic_RSIStochastic RSI
The indicator highlights the chart background for two specific signals:
- A bearish deadcross occurring above the upper band.
- A bullish goldencross occurring below the lower band.
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스토캐스틱 RSI
두가지 신호를 배경색으로 나타냅니다.
- 어퍼 밴드 위에서의 데드크로스
- 로우어 밴드 아래에서의 골든크로스
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Volatility Adjusted Relative Strength (VARS) - Histogram OptionI’ve developed a new version of VARS that includes an option to toggle it into a histogram view. I recommend using a single neutral color rather than the conventional “red below 0, green above 0” scheme — because true RS analysis shouldn’t rely on color cues. The focus should be on the immediacy and persistence of RS itself to capture that initial breakout move as the most optimal RRR entry. This also provides clearer insight and visualization into how RS functions (both traditional and VARS) since RS is a static EOD metric derived from a defined timeframe.
I want to emphasize again that VARS is useful to identify low-risk entries, with relative strength calibrated to the volatility of the reference index (in this case, AMEX:SPY ). It is not used to determine my exits — those should be governed by a strict, non-discretionary framework for partial profit-taking and final exit of a position.
Reversal Probability Meter PRO [optimized for Xau/Usd m5]🎯 Reversal Probability Meter PRO
A powerful multi-factor reversal probability detector that calculates the likelihood of bullish or bearish reversals using RSI, EMA bias, ATR spikes, candle patterns, volume spikes, and higher timeframe (HTF) trend alignment.
🧩 MAIN FEATURES
1. Reversal Probability (Bullish & Bearish)
Displays two key metrics:
Bull % — probability of bullish reversal
Bear % — probability of bearish reversal
These are computed using RSI, EMAs, ATR, demand/supply zones, candle confirmations, and volume spikes.
📊 Interpretation:
Bull % > 70% → Buying pressure building up
Bull % > 85% → Strong bullish reversal confirmed
Bear % > 70% → Selling pressure building up
Bear % > 85% → Strong bearish reversal confirmed
2. Alert Probability Threshold
Adjustable via alertThreshold (default = 85%).
Alerts trigger only when probability ≥ threshold, and confirmed by zone + volume spike + candle pattern.
🔔 Alerts Available:
✅ Bullish Smart Reversal
🔻 Bearish Smart Reversal
To activate: Right-click chart → “Add alert” → choose the alert condition from the indicator.
3. Demand / Supply Zone Detection
The script determines the price position within the last zoneLook (default 30) bars:
🟢 DEMAND → Lower 35% of range (potential bounce zone)
🔴 SUPPLY → Upper 35% of range (potential rejection zone)
⚪ MID → Neutral area
📘 Purpose: Validates reversals based on context:
Bullish only valid in Demand zones
Bearish only valid in Supply zones
4. Higher Timeframe (HTF) Trend Alignment
Reads EMA bias from a higher timeframe (default = 15m) for trend confirmation.
Reversals against HTF trend are automatically weighted down prevents false countertrend signals.
📈 Example:
M5 chart under M15 downtrend → Bullish probability is reduced.
5. Candle Confirmation Patterns
Two key price action confirmations:
Bullish: Engulfing or Pin Bar
Bearish: Engulfing or Pin Bar
A valid reversal requires both a candle confirmation and a volume spike.
6. Volume & ATR Spike Filters
Volume Spike: volume > SMA(20) × 1.3
ATR Spike: ATR > SMA(ATR, 50) × volMult
🎯 Ensures that only strong market moves with real energy are considered valid reversals.
7. Reversal Momentum Histogram
A color-gradient oscillator showing the momentum difference:
Green = bullish dominance
Red = bearish dominance
Flat near 0 = neutral
Controlled by showOscillator toggle.
8. Smart Info Panel
A compact dashboard displayed on the top-right with 4 rows:
Row Info Description
1 Bull % Bullish reversal probability
2 Bear % Bearish reversal probability
3 Zone Market context (DEMAND / SUPPLY / MID)
4 Signal Strength Current signal intensity (probability %)
Dynamic Colors:
90% → Bright (strong signal)
75–90% → Yellow/Orange (medium)
<75% → Gray (weak)
9. Sensitivity Mode
Fine-tunes indicator reactivity:
🟥 Aggressive: Detects reversals early (more signals, less accurate)
🟨 Normal: Balanced, default mode
🟩 Conservative: Filters only strongest reversals (fewer but more reliable)
10. Custom Color Options
Customize bullish and bearish colors via bullBaseColor and bearBaseColor inputs for your preferred chart theme.
⚙️ HOW TO USE
Add to Chart
→ Paste the script into Pine Editor → “Add to chart”.
Select Timeframe
→ Best for M5–M30 (scalping/intraday).
→ H1–H4 for swing trading.
Monitor the Info Panel:
Bull % ≥ 85% + Zone = Demand → Strong bullish reversal signal
Bear % ≥ 85% + Zone = Supply → Strong bearish reversal signal
Watch the Histogram:
Rising green bars = bullish momentum gaining
Deep red bars = bearish momentum gaining
Enable Alerts:
Right-click chart → “Add alert”
Choose Bullish Smart Reversal or Bearish Smart Reversal
🧠 TRADING TIPS
Use Conservative mode for noisy lower timeframes (M5–M15).
Use Aggressive mode for higher timeframes (H1–H4).
Combine with manual support/resistance or zone boxes for precision entries. Personally i use Order Block.
Best reversal setups occur when all align:
Bull % > 85%
Zone = DEMAND
Volume spike present
Candle = Bullish engulfing
HTF trend supportive
