Statistical Reliability Index (SRI)Statistical Reliability Index (SRI)
The Statistical Reliability Index (SRI) is a professional financial analysis tool designed to assess the statistical stability and reliability of market conditions. It combines advanced statistical methods to gauge whether current market trends are statistically consistent or prone to erratic behavior. This allows traders to make more informed decisions when navigating trending and choppy markets.
Key Concepts:
1. Extrapolation of Cumulative Distribution Functions (CDF)
What is CDF?
A Cumulative Distribution Function (CDF) is a statistical tool that models the probability of a random variable falling below a certain value.
How it’s used in SRI:
The SRI utilizes the 95th percentile CDF of recent returns to estimate the likelihood of extreme price movements. This helps identify when a market is experiencing statistically significant changes, crucial for forecasting potential breakouts or breakdowns.
Weight in SRI:
The weight of the CDF extrapolation can be adjusted to emphasize its impact on the overall reliability index, allowing customization based on the trader's preference for tail risk analysis.
2. Bias Factor (BF)
What is the Bias Factor?
The Bias Factor measures the ratio of the current market price to the expected mean price calculated over a defined period. It represents the deviation from the typical price level.
How it’s used in SRI:
A higher bias factor indicates that the current price significantly deviates from the historical average, suggesting a potential mean reversion or trend exhaustion.
Weight in SRI:
Adjusting the Bias Factor weight lets users control how much this deviation influences the SRI, balancing between momentum trading and mean reversion strategies.
3. Coefficient of Variation (CV)
What is CV?
The Coefficient of Variation (CV) is a statistical measure that expresses the ratio of the standard deviation to the mean. It indicates the relative variability of asset returns, helping gauge the risk-to-return consistency.
How it’s used in SRI:
A lower CV indicates more stable and predictable price behavior, while a higher CV signals increased volatility. The SRI incorporates the inverse of the normalized CV to reflect price stability positively.
Weight in SRI:
By adjusting the CV weight, users can prioritize consistent price movements over erratic volatility, aligning the indicator with risk tolerance and strategy preferences.
Interpreting the SRI:
1. SRI Plot:
The SRI plot dynamically changes color to reflect market conditions:
Aqua Line: Indicates uptrend stability, signaling statistically consistent upward movements.
Fuchsia Line: Indicates downtrend stability, where statistically reliable downward movements are present.
The overlay background shifts between colors:
Aqua Background: Signifies statistical stability, where trends are historically consistent.
Fuchsia Background: Indicates statistical instability, often associated with trend uncertainty.
Yellow Background: Marks choppy periods, where statistical data suggests that market conditions are not conducive to reliable trading.
2. SRI Volatility Plot:
Displays the volatility of the SRI itself to detect when the indicator is stable or unstable:
Blue Area Fill: Signifies that the SRI is stable, indicating trending conditions.
Yellow Area Fill: Represents choppy or unstable SRI movements, suggesting sideways or unreliable market conditions.
A Chop Threshold Line (dotted yellow) highlights the maximum acceptable SRI volatility before the market is considered too unpredictable.
3. Stability Assessment:
Stable Trend (No Chop):
The SRI is smooth and consistent, often accompanied by aqua or fuchsia lines.
Volatility remains below the chop threshold, indicating a low-risk, trend-following environment.
Chop Mode:
The SRI becomes erratic, and the volatility plot spikes above the threshold.
Marked by a yellow shaded background, indicating uncertain and non-trending conditions.
[Trend Identification:
Use the color-coded SRI line and background to determine uptrend or downtrend reliability.
Be cautious when the SRI volatility plot shows yellow, as this signals trading conditions may not be reliable.
Practical Use Cases:
Trend Confirmation:
Utilize the SRI plot color and background to confirm whether a detected trend is statistically reliable.
Chop Mode Filtering:
During yellow chop periods, it is advisable to reduce trading activity or adopt range-bound strategies.
Strategy Filter:
Combine the SRI with trend-following indicators (like moving averages) to enhance entry and exit accuracy.
Volatility Monitoring:
Pay attention to the SRI volatility plot, as spikes often precede erratic price movements or trend reversals.
Disclaimer:
The Statistical Reliability Index (SRI) is a technical analysis tool designed to aid in market stability assessment and trend validation. It is not intended as a standalone trading signal generator. While the SRI can help identify statistically reliable trends, it is essential to incorporate additional technical and fundamental analysis to make well-informed trading decisions.
Trading and investing involve substantial risk, and past performance does not guarantee future results. Always use risk management practices and consult with a financial advisor to tailor strategies to your individual risk profile and objectives.
Volatilità
Kernel Regression Bands SuiteMulti-Kernel Regression Bands
A versatile indicator that applies kernel regression smoothing to price data, then dynamically calculates upper and lower bands using a wide variety of deviation methods. This tool is designed to help traders identify trend direction, volatility, and potential reversal zones with customizable visual styles.
Key Features
Multiple Kernel Types: Choose from 17+ kernel regression styles (Gaussian, Laplace, Epanechnikov, etc.) for smoothing.
Flexible Band Calculation: Select from 12+ deviation types including Standard Deviation, Mean/Median Absolute Deviation, Exponential, True Range, Hull, Parabolic SAR, Quantile, and more.
Adaptive Bands: Bands are calculated around the kernel regression line, with a user-defined multiplier.
Signal Logic: Trend state is determined by crossovers/crossunders of price and bands, coloring the regression line and band fills accordingly.
Custom Color Modes: Six unique color palettes for visual clarity and personal preference.
Highly Customizable Inputs: Adjust kernel type, lookback, deviation method, band source, and more.
How to Use
Trend Identification: The regression line changes color based on the detected trend (up/down)
Volatility Zones: Bands expand/contract with volatility, helping spot breakouts or mean-reversion opportunities.
Visual Styling: Use color modes to match your chart theme or highlight specific market states.
Credits:
Kernel regression logic adapted from:
ChartPrime | Multi-Kernel-Regression-ChartPrime (Link in the script)
Disclaimer
This script is for educational and informational purposes only. Not financial advice. Use at your own risk.
Spread/Range Oscillator + Signal + HistogramThe Spread/Range Oscillator is a technical analysis tool designed to assess market momentum by evaluating the relationship between price movement and volatility.
Calculation
Spread: The difference between the closing and opening prices of a candle (close - open).
Range: The difference between the high and low prices of a candle (high - low).
Oscillator: The spread divided by the range (spread / range). This ratio provides a normalized measure of price movement within each candle.
Smoothed Oscillator: An Exponential Moving Average (EMA) applied to the oscillator over a user-defined period (Smoothing Length) to reduce noise.
Signal Line: An EMA of the Smoothed Oscillator over another user-defined period (Signal Line Length) to identify potential trend changes.
Histogram: The difference between the Smoothed Oscillator and the Signal Line (Smoothed Oscillator - Signal Line). Positive values suggest bullish momentum, while negative values indicate bearish momentum.
Inputs
Smoothing Length (EMA): Determines the period for smoothing the oscillator.
Signal Line Length (EMA): Sets the period for the EMA applied to the Smoothed Oscillator to generate the Signal Line.
Visual Representation
Smoothed Oscillator: Plotted as a line representing the smoothed momentum of price movements.
Signal Line: Displayed as a line serving as a reference to identify potential crossovers and trend changes.
Histogram: Rendered as bars, with positive values indicating bullish momentum and negative values indicating bearish momentum.
Zero Line: A horizontal line at zero to distinguish between bullish and bearish territories.
Applications
Momentum Analysis: Identify periods of strong buying or selling pressure based on the oscillator's position relative to the zero line.
Trend Confirmation: Use crossovers between the Smoothed Oscillator and Signal Line to confirm potential trend reversals or continuations.
Divergence Detection: Spot divergences between price action and the oscillator to anticipate possible market turning points.
This indicator is open-source and intended for educational purposes. It is recommended to use it in conjunction with other forms of analysis and risk management practices before making trading decisions.
timer/tr/atr [keypoems]Session and Instant Volatility Ticker
What it actually does:
- Session ATR – Reports the historical (e.g. “0200-0600”) average true range of the past x sessions, reports the +1Stdev value.
- Real-time ATR feed – streams the current ATR value every tick.
- Ticker line – Sess. ATR +1Stdev | Current ATR | Previous TR | 🕒 Time-left-in-bar |
Think of it as a volatility check: a single glance tells you if the average candle size is compatible with your usual stop or not.
Open Source.
Volume MAs Supertrend | Lyro RS📊 Volume MAs Supertrend | Lyro RS is an advanced trading tool that combines volume-adjusted moving averages with a dynamic Supertrend system. This indicator provides a robust framework for identifying market trends and entry/exit points.
✨ Key Features :
📈 Volume-Weighted Moving Averages (VWMA): Integrates price and volume data to provide a more accurate moving average, allowing for better trend analysis.
🔧 Multiple MA Types: Choose from SMA, EMA, WMA, VWMA, DEMA, TEMA, RMA, HMA, ALMA to suit your preferred trading strategy.
📊 Dual-Multiplier Supertrend System: Uses ATR to dynamically calculate upper and lower bands for long and short trends, with distinct multipliers for each.
🎨 Customizable Color Schemes: Choose from Classic, Mystic, Accented, and Royal color palettes or customize your own colors for bullish and bearish trends.
🔍 Visual Enhancements: Color-coded Supertrend lines, candlesticks, and bars for quick trend identification.
⏰ Alert System: Alerts for long and short signals based on trend changes.
🔧 How It Works :
The Supertrend line is calculated using ATR over a user-defined period, with separate multipliers for long and short positions.
📈 A bullish trend is signaled when the price crosses above the upper band, and a bearish trend is signaled when the price crosses below the lower band.
🎨 The Supertrend line changes color to reflect trend direction, with candlesticks and bars matching the trend's color for visual clarity.
⚙️ Customization Options :
🛠️ Moving Average Settings: Select your preferred moving average type (SMA, EMA, VWMA, etc.) and adjust the length for smoother or more responsive trend signals.
📐 Supertrend Parameters: Define the ATR period and adjust multipliers to fine-tune sensitivity for long and short signals.
🎨 Color Configuration: Choose from predefined color palettes or create your own custom scheme for trend signals.
📈 Use Cases :
✅ Confirm market trends before entering trades.
🚪 Identify potential entry/exit points as trend directions shift.
👀 Visually analyze market conditions with color-coded candlesticks and bars.
⚠️ Disclaimer :
This indicator should not be used as a standalone tool for making trading decisions. Always combine with other forms of analysis and risk management practices.
Bitcoin Weekend FadeThis indicator is a tool for setting a bias based on weekend price movements, with the assumption that the crypto market often experiences stronger moves over the weekend due to thinner order books. It helps identify potential fade opportunities, suggesting that price movements from Saturday and Sunday may reverse during the weekdays.
How to use:
Sets a bias based on weekend price action.
Sets a bias based on weekend price action.
Use weekday price action for confirmation before acting on the bias.
Best suited for range-bound markets, where the price tends to revert to the mean.
Avoid fading high-timeframe breakouts, as they often indicate strong trends.
Order Block Matrix [Alpha Extract]The Order Block Matrix indicator identifies and visualizes key supply and demand zones on your chart, helping traders recognize potential reversal points and high-probability trading setups.
This tool helps traders:
Visualize key order blocks with volume profile histograms showing liquidity distribution.
Identify high-volume price levels where institutional activity occurs.
rank historical order blocks and analyze their strength based on volume.
Receive alerts for potential trading opportunities based on price-block interactions.
🔶 CALCULATION
The indicator processes chart data to identify and analyze order blocks:
Order Block Detection
Inputs:
Price action patterns (consolidation areas followed by breakouts).
Volume data from current and lower timeframes.
User-defined lookback periods and thresholds.
Detection Logic:
Identifies consolidation areas using a dynamic range comparison.
Confirms breakout patterns with percentage threshold validation.
Maps volume distribution across price levels within each order block.
🔶Volume Analysis
Volume Profiling:
Divides each order block into configurable grid segments.
Maps volume distribution across price segments within blocks.
Highlights zones with highest volume concentration.
Strength Assessment:
Calculates total block volume and relative strength metrics.
Compares block volume to historical averages.
Determines probability of reversal based on volume patterns.
isConsolidation(len) =>
high_range = ta.highest(high, len) - ta.lowest(high, len)
low_range = ta.highest(low, len) - ta.lowest(low, len)
avg_range = (high_range + low_range) / 2
current_range = high - low
current_range <= avg_range * (1 + obThreshold)
🔶 DETAILS
Visual Features
Volume Profile Histograms:
Color-coded bars showing volume concentration within order blocks.
Gradient coloring based on relative volume (high volume = brighter colors).
Bull blocks (green/teal) and bear blocks (red) with varying opacity.
Block Visualization:
Dynamic box sizing based on volume concentration.
Optional block borders and background fills.
Volume labels showing total block volume.
Screener Table:
Real-time analysis of order block metrics.
Shows block direction, proximity, retest count, and volume metrics.
Color-coded for quick reference.
Interpretation
High Volume Areas: Zones with institutional interest and potential reversal points.
Block Direction: Bullish blocks typically support price, bearish blocks typically resist price.
Retests: Multiple tests of an order block may strengthen or weaken its influence.
Block Age: Newer blocks often have stronger influence than older ones.
Volume Concentration: Brightest segments within blocks represent the highest volume areas.
🔶 EXAMPLES
The indicator helps identify key trading opportunities:
Bullish Order Blocks
Support Zones: Identify strong support levels where price is likely to bounce.
Breakout Confirmation: Validate breakouts with volume analysis to avoid false moves.
Retest Strategies: Enter trades when price retests a bullish order block with high volume.
Bearish Order Blocks
Resistance Zones: Identify strong resistance levels where price is likely to reverse.
Distribution Areas: Detect zones where smart money is distributing to retail.
Short Opportunities: Find optimal short entry points at high-volume bearish blocks.
Combined Strategies
Order Block Stacking: Multiple aligned blocks create stronger support/resistance zones.
Block Mitigation: When price breaks through a block, it often indicates a strong trend continuation.
Volume Profile Applications: Higher volume segments provide more precise entry and exit points.
🔶 SETTINGS
Customization Options
Order Block Detection:
Consolidation Lookback: Adjust the period for consolidation detection.
Breakout Threshold: Set minimum percentage for breakout confirmation.
Historical Lookback Limit: Control how far back to scan for historical order blocks.
Maximum Order Blocks: Limit the number of visible blocks on the chart.
Visual Style:
Grid Segments: Adjust the number of volume profile segments.
Extend Blocks to Right: Enable/disable extending blocks to current price.
Show Block Borders: Toggle border visibility.
Border Width: Adjust thickness of block borders.
Show Volume Text: Enable/disable volume labels.
Volume Text Position: Control placement of volume labels.
Color Settings:
Bullish High/Low Volume Colors: Customize appearance of bullish blocks.
Bearish High/Low Volume Colors: Customize appearance of bearish blocks.
Border Color: Set color for block outlines.
Background Fill: Adjust color and transparency of block backgrounds.
Volume Text Color: Customize label appearance.
Screener Table:
Show Screener Table: Toggle table visibility.
Table Position: Select positioning on the chart.
Table Size: Adjust display size.
The Order Block Matrix indicator provides traders with powerful insights into market structure, helping to identify key levels where smart money is active and where high-probability trading opportunities may exist.
Risk ModuleRisk Module
This indicator provides a visual reference to determine position sizing and approximate stop placement. It is designed to support trade planning by calculating equalized risk per trade based on a stop distance derived from volatility. The tool offers supportive reference points that allow for quick evaluation of risk and position size consistency across varying markets.
Equalized Risk Per Trade
The indicator calculates the number of shares that can be traded to maintain consistent monetary risk. The formula is based on the distance between the current price and the visual stop reference, adjusting the position size proportionally.
Position Size = Dollar Risk / (Entry Price – Stop Price)
The risk is calculated as a percentage of account size; both of which can be set in the indicator’s settings tab. This creates a consistent risk exposure across trades regardless of volatility or structural stop distance.
Stop Placement Reference
The visual stop reference is derived from the Average True Range (ATR), providing a volatility-based anchor. The default value is set to 2 × ATR, but this can be customized.
Price Model: Uses the current price ± ATR × multiplier. This model reacts to price movement and is set as the default option.
EMA Model: Uses the 20-period EMA ± ATR × multiplier. This model is less reactive and can be an option when used in combination with an envelope indicator.
Chart Elements
Stop Levels: Plotted above and below either the current price or EMA, depending on the selected model. These serve as visual reference points for stop placement; the lower level a sell stop for long trades, the upper level a buy stop for short trades.
Information Table: Displays the number of shares to trade, stop level and percentage risk. A compact mode is available to reduce the table to essential information (H/L and Shares).
Settings Overview
Stop Model: Choose between “Price” or “EMA” stop calculation logic.
ATR Multiplier: Change the distance between price/EMA and the stop reference.
Account Size / Risk %: These risk parameters are used to calculate dollar risk per trade.
Visible Bars: Number of recent bars to show stop markers on.
Compact Mode: Minimal table view for reduced chart footprint.
Table Position / Size: Controls table placement and scale on the chart.
Percentage SDThis TradingView indicator, called "Percentage SD," measures how much the price of an asset is fluctuating (its volatility) and shows this as a percentage.
You can choose which price to track (like the closing price) and the period over which to measure this volatility.
The indicator then draws a yellow line in a separate panel below your main chart. When this line is higher, it means the price is more volatile relative to its current level. A lower line suggests less volatility. This can help you see when price movements are becoming more or less active.
Volumetric Entropy IndexVolumetric Entropy Index (VEI)
A volume-based drift analyzer that captures directional pressure, trend agreement, and entropy structure using smoothed volume flows.
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🧠 What It Does:
• Volume Drift EMAs : Shows buy/sell pressure momentum with adaptive smoothing.
• Dynamic Bands : Bollinger-style volatility wrappers react to expanding/contracting drift.
• Baseline Envelope : Clean structural white rails for mean-reversion zones or trend momentum.
• Background Shading : Highlights when both sides (up & down drift) are in agreement — green for bullish, red for bearish.
• Alerts Included : Drift alignment, crossover events, net drift shifts, and strength spikes.
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🔍 What Makes It Different:
• Most volume indicators rely on bars, oscillators, or OBV-style accumulation — this doesn’t.
• It compares directional EMAs of raw volume to isolate real-time bias and acceleration.
• It visualizes the twisting tension between volume forces — not just price reaction.
• Designed to show when volatility is building inside the volume mechanics before price follows.
• Modular — every element is optional, so you can run it lean or fully loaded.
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📊 How to Use It:
• Drift EMAs : Watch for one side consistently dominating — sharp spikes often precede breakouts.
• Bands : When they tighten and start expanding, it often signals directional momentum forming.
• Envelope Lines : Use as high-probability reversal or continuation zones. Bands crossing envelopes = potential thrust.
• Background Color : Green/red backgrounds confirm volume agreement. Can be used as a filter for other signals.
• Net Drift : Optional smoothed oscillator showing the difference between bullish and bearish volume pressure. Crosses above or below zero signal directional bias shifts.
• Drift Strength : Measures pressure buildup — spikes often correlate with large moves.
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⚙️ Full Customization:
• Turn every layer on/off independently
• Modify all colors, transparencies, and line widths
• Adjust band width multiplier and envelope offset (%)
• Toggle bonus plots like drift strength and net baseline
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🧪 Experimental Tools:
• Smoothed Net Drift trace
• Drift Strength signal
• Envelope lines and dynamic entropy bands with adjustable math
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Built for signal refinement. Made to expose directional imbalance before the herd sees it.
Created by @Sherlock_Macgyver
5-Min Candle Ranges (Last 1000)Average candle size for 1000 candles. This indicators looks at the volatility of candles and averages the size of the candles.
Daily Price RangeThe indicator is designed to analyze an instrument’s volatility based on daily extremes (High-Low) and to compare the current day’s range with the typical (median) range over a selected period. This helps traders assess how much of the "usual" daily movement has already occurred and how much may still be possible during the trading day.
NeuroTrendNeuroTrend is an advanced, self-adjusting trend analysis system that continuously adapts to changing market conditions using volatility-aware smoothing, momentum weighting, and intelligent trend classification. It provides real-time trend detection, confidence scoring, early reversal warnings, and slope projection, all delivered through a coaching dashboard and structured rule-based commentary system.
At its core, NeuroTrend uses two EMAs whose smoothing lengths change automatically based on current volatility, measured by the ATR relative to price, and momentum bias, measured by RSI displacement from the neutral level. These adaptive EMAs create a flexible baseline that adjusts to the pace of the market. From these EMAs, the system calculates angular slope and derives a slope power score, which reflects directional momentum weighted by volatility.
NeuroTrend classifies each bar into one of five market phases: Impulse, Cooling, Reversal Risk, Stall, or Neutral. This classification is based on slope strength, slope variability, and RSI behavior. Each phase offers specific context for whether to enter, continue, or avoid a position.
The indicator uses what is referred to as a neural memory engine, which is inspired by the idea of memory but is not a neural network or machine learning model. Instead, it is a statistical recalibration system that adjusts thresholds using recent ATR conditions and slope standard deviation. This allows the indicator to remain aligned with the current market environment without the need for manual tuning.
Although NeuroTrend is fully adaptive, it includes inputs for the base fast and slow EMAs. These inputs define the central anchor points around which the adaptive logic operates. This gives the trader the ability to control the default behavior of the indicator while still benefiting from real-time responsiveness to volatility and momentum.
To assess the strength of a trend, NeuroTrend computes a confidence score based on four elements: DMI trend strength, directional bias from DI+ and DI–, slope normalization, and volatility efficiency measured by ATR in relation to EMA distance. This score is used to inform alerts, commentary, and dashboard visualization.
The indicator also includes a slope projection engine that estimates near-term direction based on slope change and acceleration. This projection is scaled and clamped using a dynamic volatility factor to prevent unrealistic or unstable values.
Reversal and stall detection are built in. Reversal detection is based on slope collapsing, sign flipping, and RSI weakness. Stall detection is triggered when slope magnitude is low, RSI is flat, and ATR is compressed. These filters help prevent entries in low-quality or high-risk environments.
The system also includes AI-style commentary. This feature is not powered by machine learning or natural language processing. It is rule-based, using prioritized conditions to generate clear statements that reflect the current market state. Messages such as "Strong trend forming" or "Reversal risk rising" are created by predefined logic that adapts to the market.
A visual dashboard is provided on the chart. It displays the current phase, trend direction, slope score, confidence level, reversal status, stall condition, and projected slope angle. This helps traders interpret market behavior at a glance without scanning multiple indicators.
Alerts are triggered only when specific conditions are met: trend strength must be in the impulse phase, confidence must be high, and there must be no active reversal or stall conditions. This ensures alerts are reserved for high-quality setups with strong directional alignment.
Disclaimer:
This script is intended for educational and informational use only. It does not constitute financial advice. The author accepts no responsibility for any trading or investment decisions made using this tool. Always do your own research and consult a licensed financial advisor before making financial decisions.
Price Lag Factor (PLF)📊 Price Lag Factor (PLF) for Crypto Traders: A Comprehensive Breakdown
The Price Lag Factor (PLF) is a momentum indicator designed to identify overextended price movements and gauge market momentum. It is particularly optimized for the crypto market, which is known for its high volatility and rapid trend shifts.
🔎 What is the Price Lag Factor (PLF)?
The PLF measures the difference between long-term and short-term price momentum and scales it dynamically based on recent volatility. This helps traders identify when the market might be overbought or oversold while filtering out noise.
The formula used in the PLF calculation is:
PLF = (Z-Long - Z-Short) / Stdev(PLF)
Where:
Z-long: Z-score of the long-term moving average (50-period by default).
Z-short: Z-score of the short-term moving average (14-period by default).
Stdev(PLF): Standard deviation of the PLF over a longer period (50-period by default).
🧠 How to Interpret the PLF:
1. Trend Direction:
Positive PLF (Green Bars): Indicates bullish momentum. The long-term trend is up, and short-term movements are confirming it.
Negative PLF (Red Bars): Indicates bearish momentum. The long-term trend is down, and short-term movements are consistent with it.
2. Momentum Strength:
PLF near Zero (±0.5): Low momentum; trend direction is not strong.
PLF between ±1 and ±2: Moderate momentum, indicating that the market is moving with strength but not in an overextended state.
PLF beyond ±2: High momentum (overbought/oversold), indicating potential trend exhaustion and a possible reversal.
📈 Trading Strategies:
1. Trend Following:
Bullish Signal:
Enter long when PLF crosses above 0 and remains green.
Confirm with other indicators like RSI or MACD to reduce false signals.
Bearish Signal:
Enter short when PLF crosses below 0 and remains red.
Use trend confirmation (e.g., moving average crossover) for better accuracy.
2. Reversal Trading:
Overbought Signal:
If PLF rises above +2, look for signs of bearish divergence or a reversal pattern to consider a short entry.
Oversold Signal:
If PLF falls below -2, watch for bullish divergence or a support bounce to consider a long entry.
3. Momentum Divergence:
Bullish Divergence:
Price makes a lower low while PLF makes a higher low.
Indicates weakening bearish momentum and a potential bullish reversal.
Bearish Divergence:
Price makes a higher high while PLF makes a lower high.
Signals weakening bullish momentum and a potential bearish reversal.
💡 Best Practices:
Combine with Volume:
Volume spikes during high PLF readings can confirm trend continuation.
Low volume during PLF extremes may hint at false breakouts.
Watch for Extreme Levels:
PLF beyond ±2 suggests overextended price action. Use caution when entering new positions.
Confirm with Other Indicators:
Use with Relative Strength Index (RSI) or Bollinger Bands to get a better sense of overbought/oversold conditions.
Overlay with a moving average to gauge trend consistency.
🚀 Why the PLF Works for Crypto:
Crypto markets are highly volatile and prone to rapid trend changes. The PLF's adaptive scaling ensures it remains relevant regardless of market conditions.
It highlights momentum shifts more accurately than static indicators because it accounts for changing volatility in its calculation.
🚨 Disclaimer for Traders Using the Price Lag Factor (PLF) Indicator:
The Price Lag Factor (PLF) indicator is designed as a technical analysis tool to gauge momentum and identify potential overbought or oversold conditions. However, it should not be relied upon as a sole decision-making factor for trading or investing.
Important Points to Consider:
Market Risk: Trading cryptocurrencies and other financial assets involves significant risk. The PLF may not accurately predict future price movements, especially during unexpected market events.
Indicator Limitations: No technical indicator, including the PLF, is infallible. False signals can occur, particularly in low-volume or highly volatile conditions.
Supplementary Analysis: Always combine PLF insights with other technical indicators, fundamental analysis, and risk management strategies to make informed decisions.
Personal Judgment: Traders should use their own discretion when interpreting PLF signals and never trade based solely on this indicator.
No Guarantees: The PLF is designed for educational and informational purposes only. Past performance is not indicative of future results.
Always perform thorough research and consider consulting with a professional financial advisor before making any trading decisions.
ADR & ATR OverlayADR & ATR Overlay
This indicator will display the following as an overlay on your chart:
ADR
% of ADR
ADR % of Price
ATR
% of ATR
ATR % of Price
Description:
ADR : Average Day Range
% of ADR : Percentage that the current price move has covered its average.
ADR % of Price : The percentage move implied by the average range.
ATR : Average True Range
% of ATR : Percentage that the current price move has covered its average.
ATR % of Price : The percentage move implied by the average true range.
Options:
Time Frame
Length
Smoothing
Enable or Disable each value
Text Color
Background Color
How to use this indicator:
The ADR and ATR can be used to provide information about average price moves to help set targets, stop losses, entries and exits based on the potential average moves.
Example: If the "% of ADR" is reading 100%, then 100% of the asset's average price range has been covered, suggesting that an additional move beyond the range has a lower probability.
Example: "ADR % of Price" provides potential price movement in percentage which can be used to asses R/R for asset.
Example: ADR (D) reading is 100% at market close but ATR (D) is at 70% at close. This suggests that there is a potential move of 30% in Pre/Post market as suggested by averages.
Notes:
These indicators are available as oscillators to place under your chart through trading view but this indicator will place them on the chart in numerical only format.
Please feel free to modify this script if you like but please acknowledge me, I am only a hobby coder so this takes some time & effort.
Live ICT Manipulation Candle [London Session, DST]📌 Live ICT Manipulation Candle
🔍 What This Script Does:
This indicator highlights the most volatile ( manipulative ) candle during the London session, based on range and volume, in real-time. It is designed specifically for intraday traders who follow ICT ( Inner Circle Trader ) concepts.
Key Features:
Tracks and highlights the manipulation candle between 3:00 AM to 5:00 AM NY time, adjusted for daylight savings (DST).
Displays a colored box around the manipulation candle and optionally shows a "Manipulation" label ( see chart below ).
Works on 1m, 5m, or 15m charts only — ensures high accuracy and alignment with ICT intraday concepts.
Designed for clarity during live session development.
⚠️ Disclaimer & Transparency:
This script was previously removed by TradingView due to being published with protected ( closed ) source code. I apologize for that oversight.
If you're studying ICT concepts or trading the London session volatility, this script can help you visually anchor the key manipulation point each day!
The indicator doesn't put the circles on. I put them to show the key manipulation areas per London session.
Happy trading and stay sharp!
@TJT_Pro
Zero Lag MTF Moving Average by CoffeeshopCryptoBased on Moving Average Types supplied by @TradingView www.tradingview.com
Ideas and code enhanced to show higher timeframe by @CoffeeShopCrypto
It’s time to take the guesswork out of moving averages and multiple timeframes when day trading. Moving averages are a cornerstone of many trading strategies, often viewed as dynamic support and resistance levels. Traders rely on these levels to anticipate price reactions, whether it’s a bounce in a trending market or a reversal in a ranging one. Additionally, the direction and alignment of multi timeframe moving averages—whether they’re moving in the same direction or diverging—provide critical clues about market momentum and potential reversals. However, the traditional higher timeframe moving average indicators force traders to wait for higher timeframe candles to close, creating lag and missed opportunities.
The Old Way
For example: If you are on a 5 minute chart and you want to observe the location and direction of a 30 minute chart Moving Average, you'll need to wait for a total of 6 candles to close, and again every 6 candles after that. This only creates more lag.
The New Way
Now there is no waiting for high timeframe session candles to close. No matter what timeframe Moving Average you want to know about, this indicator will show you its location on your current chart at any time in real time.
For those who prefer Bollinger Bands, this indicator adds a whole new dimension to your strategy. Traders often wait for price action to break outside the lower time frame Bollinger bands before considering a trade, while still seeking key support or resistance levels beyond them. But if you don't know the position of your higher time frame Bollinger, you could be trading into a trap. With Zero Lag Multi Timeframe Moving Average, you can view both your current and higher timeframe Bollinger Bands simultaneously with zero waiting. This lets you instantly see when price action is traveling between the bands of either timeframe or breaking through both—indicating a strong trend in that direction. Additionally, when both sets of Bollinger Bands overlap at the same price levels, it highlights areas of strong consolidation and ranging conditions, giving you a clear picture of market dynamics. This is a key element in price action that tells you there is currently no direction to the market and both the current and higher time frames are flat.
Enter Zero Lag Multi Timeframe Moving Average—the ultimate tool for real-time higher timeframe moving averages and Bollinger Bands. This innovative indicator eliminates the delay, delivering instant, precise values for higher timeframe averages and bands, even on open candles. Seamlessly combining current and higher timeframe data, it allows traders to identify key moments where moving averages or Bollinger Bands align or diverge, signaling market conditions. Whether you’re gauging the strength of a trend, pinpointing potential reversals, or identifying consolidation zones, Zero Lag Multi Timeframe Moving Average gives you the clarity needed to make better trading decisions according to market conditions.
Why is this "Mashup" of moving averages different and important?
Honestly its really about the calculation thats imported through the "import library" function.
Heres what it does:
The ZLMTF-MA is designed to help traders easily see where higher timeframe moving averages and Bollinger Bands are—without needing to switch chart timeframes or wait for those larger candles to close. It works by adjusting common moving average types like SMA, EMA, and VWMA to show what they would look like if they were based on a higher timeframe, right on your current chart. This helps users stay focused on their main timeframe while still having a clear view of the bigger picture, making it easier to spot trend direction, key support and resistance levels, and overall market structure. The goal is to keep things simple, fast, and more visually informative for everyday traders.
Bollinger Bands
When working with Bollinger Bands, a common strategy is to take the trades once price action has escaped through the top or bottom of your current Bollinger Band.
A false breakout occurs when both Bollinger Bands are not moving in the same direction as eachother or when they are overlapping.
Moving Averages as Support and Resistance:
Traders who use Moving Averages as support or resistance, looking for rejections or failures of these areas can now see multiple timeframe price action instantly and simultaneously.
Trading Setup Examples:
Price Action Scenario 1:
Higher Timeframe Ranging-
When price action breaks through a current moving average headed toward a higher timeframe moving average, trades are taken with caution if the moving averages are converging.
Price Action Scenario 2:
Strong Trending Market -
If the moving averages are in the same direction, and your price action is now leading the low timeframe moving average, you have re-entered a strong trend.
Price Action Scenario 3:
High Timeframe Rejections -
If you have a rejection of a higher timeframe moving average, and your both averages are still diverging, this is the end of a pullback as you re-enter a strong trend in the original direction
Price Action Scenario 4:
Trend Reversals -
If you close beyond both the low and high timeframe moving averages, you can consider that price action is strong enough to change direction here and you should prepare for trade setups in the opposite direction of the previous.
HTF MA Label Information:
Even if your high timeframe moving average is turned off, you can still see this label.
It gives you a quick reminder of what high timeframe settings you have used to see MA values.
Atlas BBTlevelsAtlas BBTlevels is a custom Bollinger Bands-based indicator that measures the momentum and strength of price trends using the difference between short- and long-period Bollinger Bands. Inspired by John Bollinger’s official tools like BBTrend, %b, and Bandwidth, this script adds adjustable horizontal threshold levels so traders can mark important reaction zones on their charts.
It visualizes when markets may be entering overheated or exhausted conditions — either for trend continuation or potential reversals — and works across crypto, stocks, forex, spot, or perpetual charts.
How I personally use it:
I apply Atlas BBTlevels across three timeframes:
Low timeframe (LTF): 5m–15m
Mid timeframe (MTF): 1h–6h
High timeframe (HTF): 1d–2d
I review where the indicator historically spiked during major moves. For example, if the 4-hour chart shows repeated spikes to +10 or −10, I’ll set my positive and negative thresholds near those levels. This lets me anticipate zones where the market may reverse, cool off, or break out. I then compare LTF, MTF, and HTF levels to look for confluence. When multiple timeframes align near key levels, it gives me higher confidence to prepare for a trade — but I always combine this with price action and other confirmation tools.
How others can use it:
Identify overbought/oversold zones by adjusting the thresholds to match historical extremes on your chosen asset.
Use it as a trend strength gauge: when the histogram is near or above the top threshold, the trend is likely strong; when it fades back toward zero, momentum is weakening.
Watch for volatility expansions or contractions as the indicator accelerates away from or returns toward zero.
Combine it with price action (support/resistance, trendlines, chart patterns) or other momentum tools to reduce false signals.
Apply it across multiple timeframes to look for confluence — this increases reliability compared to using it on just one chart.
Important tips:
Positive spikes (above zero) usually indicate strength or overextension upward; negative spikes (below zero) show weakness or downward exhaustion.
You can reverse the color logic if you want (for example, highlight negative spikes as green for buy interest and positive spikes as red for sell interest) — this is just a visual preference.
This is not a standalone buy/sell system. Always combine it with other tools, market context, and risk management.
ADX Supertrend | [DeV]The "ADX Supertrend" indicator is a user-friendly tool that blends two popular trading indicators—the Supertrend and the Average Directional Index (ADX)—to help traders spot trends and make smarter trading decisions. By combining these two, it offers a clearer picture of when a market is trending strongly and in which direction, while cutting down on misleading signals. Here’s a straightforward explanation of how each part works, how they team up, the benefits of using them together, and why the ADX makes the Supertrend even better.
Supertrend:
It's like a guide that follows the market’s price movements to tell you whether prices are trending up or down. It creates two lines, one above and one below the price, based on how much the market is bouncing around (its volatility). When the price moves above the upper line, it signals an uptrend (a good time to buy), and the indicator draws a line below the price to show support. When the price drops below the lower line, it signals a downtrend (a potential time to sell), and the line appears above the price as resistance. The Supertrend is great because it adjusts to market conditions, widening the gap between lines in wild markets and tightening it in calm ones.
Average Directional Index:
The ADX is all about measuring how strong a trend is, without caring whether it’s going up or down. Think of it as a meter that tells you if the market is charging forward with purpose or just drifting aimlessly. It uses a scale from 0 to 100, where higher numbers mean a stronger trend. For example, an ADX above 25 often suggests a solid trend worth paying attention to, while a low ADX signals a sleepy, sideways market. The ADX also looks at whether buyers or sellers are in control to confirm the trend’s direction.
Confluence:
The Supertrend is great at spotting trends, but it can be a bit trigger-happy, giving signals in markets that aren’t really trending. That’s where the ADX shines. It acts like a quality control check, making sure the Supertrend’s signals only count when the market is moving with conviction. By filtering out weak or messy trends, the ADX helps you avoid wasting time on trades that fizzle out. It also double-checks the trend’s direction, so you’re not just guessing whether buyers or sellers are in charge. This teamwork means you get signals that are more reliable and less likely to lead you astray, especially in tricky markets where prices bounce around without a clear path.
Bollinger Bands ETSOverview
Bollinger Bands ETstyle (BB ETS) is an advanced volatility and breakout detection indicator, building upon the classic Bollinger Bands. This script introduces adaptive ATR-based band width smoothing and clear squeeze detection, making it a versatile tool for traders seeking more responsive and actionable volatility analysis.
Features
Dual Bollinger Bands: Plots both standard and outer bands around a configurable moving average, allowing visualization of typical and extreme volatility ranges.
ATR-Based Band Smoothing (Optional): When enabled, the bands automatically widen during low-volatility periods using the Average True Range (ATR), reducing false signals and making the bands more adaptive.
Squeeze Detection (Optional): Highlights periods when the bands contract below a user-defined threshold, signaling potential breakout setups. Squeeze periods are visually marked with a background highlight for easy identification.
Customizable Settings: Users can adjust band length, standard deviation multipliers, ATR parameters, and squeeze thresholds. Both ATR smoothing and squeeze detection can be toggled on or off.
Clean Chart Output: The indicator overlays directly on price with clear, distinguishable visuals for all features.
How It Works
The indicator calculates a moving average (basis) and plots upper and lower bands at user-selected standard deviations.
If ATR smoothing is enabled, the band width expands by a multiple of the ATR, adapting to real-time volatility.
The script computes the relative band width ("bandwidth"). When this falls below your chosen threshold, the background is highlighted to indicate a "squeeze"-a period of reduced volatility that often precedes breakouts.
How to Use
Trend & Volatility Analysis: Use the bands to identify overbought/oversold conditions and current market volatility. Price touching or crossing the outer bands may signal trend exhaustion or continuation.
Breakout Anticipation: Watch for background highlights indicating a squeeze. These periods suggest the market is coiling for a potential significant move.
Adaptive Sensitivity: Enable ATR smoothing to keep bands relevant during both calm and volatile markets, reducing false signals in low-volatility conditions.
Customization: Adjust all parameters in the settings to match your trading style and the asset’s behavior.
Limitations
The indicator is designed for standard price charts and may not perform as intended on non-standard chart types (such as Renko or Heikin Ashi).
As with all technical tools, best results are achieved when used alongside other forms of analysis.
Summary
Bollinger Bands ETstyle (BB ETS) offers a modern, adaptive approach to volatility and breakout analysis by combining classic bands with ATR-based smoothing and clear squeeze visualization. It is suitable for trend-following and breakout strategies, and requires no additional scripts-simply apply to your chart and adjust the settings as needed.
ZenLab ATR FNSThis indicator was created specifically for Zen Labs which includes a custom ATR (Average True Range) table that displays the ATR value for a selected period of candles.
ATR is a volatility indicator that measures the average range between high and low prices over a given number of periods. It helps traders assess how much an asset typically moves, providing valuable information for setting stop losses, take profits, or identifying market conditions. It adapts to changing market conditions, making it useful across different timeframes and asset classes.
How the ATR Indicator Works:
The ATR is based on the concept of True Range (TR), which is the greatest of the following three values:
- Current High minus Current Low
- Absolute value of Current High minus Previous Close
- Absolute value of Current Low minus Previous Close
Averaging the True Range:
Once the True Range is calculated for each period, the ATR is computed by averaging these True Ranges over a set number of periods and is displayed in the table.
Interpreting the ATR:
- A higher ATR value indicates higher volatility—prices are moving more significantly.
- A lower ATR value indicates lower volatility—prices are more stable and less active.
Enjoy!
- Rebel Empire
Entropy Chart Analysis [PhenLabs]📊 Entropy Chart analysis -
Version: PineScript™ v6
📌 Description
The Entropy Chart indicator analysis applies Approximate Entropy (ApEn) to identify zones of potential support and resistance on your price chart. It is designed to locate changes in the market’s predictability, with a focus on zones near significant psychological price levels (e.g., multiples of 50). By quantifying entropy, the indicator aims to identify zones where price action might stabilize (potential support) or become randomized (potential resistance).
This tool automates the visualization of these key areas for traders, which may have the effect of revealing reversal levels or consolidation zones that would be hard to discern through traditional means. It also filters the signals by proximity to key levels in an attempt to reduce noise and highlight higher-probability setups. These dynamic zones adapt to changing market conditions by stretching, merging, and expiring based on user-inputted rules.
🚀 Points of Innovation
Combines Approximate Entropy (ApEn) calculation with price action near significant levels.
Filters zone signals based on proximity (in ticks) to predefined significant price levels (multiples of 50).
Dynamically merges overlapping or nearby zones to consolidate signals and reduce chart clutter.
Uses ApEn crossovers relative to its moving average as the core trigger mechanism.
Provides distinct visual coloring for bullish, bearish, and merged (mixed-signal) zones.
Offers comprehensive customization for entropy calculation, zone sensitivity, level filtering, and visual appearance.
🔧 Core Components
Approximate Entropy (ApEn) Calculation : Measures the regularity or randomness of price fluctuations over a specified window. Low ApEn suggests predictability, while high ApEn suggests randomness.
Zone Trigger Logic : Creates potential support zones when ApEn crosses below its average (indicating increasing predictability) and potential resistance zones when it crosses above (indicating increasing randomness).
Significant Level Filter : Validates zone triggers only if they occur within a user-defined tick distance from significant price levels (multiples of 50).
Dynamic Zone Management : Automatically creates, extends, merges nearby zones based on tick distance, and removes the oldest zones to maintain a maximum limit.
Zone Visualization : Draws and updates colored boxes on the chart to represent active support, resistance, or mixed zones.
🔥 Key Features
Entropy-Based S/R Detection : Uses ApEn to identify potential support (low entropy) and resistance (high entropy) areas.
Significant Level Filtering : Enhances signal quality by focusing on entropy changes near key psychological price points.
Automatic Zone Drawing & Merging : Visualizes zones dynamically, merging close signals for clearer interpretation.
Highly Customizable : Allows traders to adjust parameters for ApEn calculation, zone detection thresholds, level filter sensitivity, merging distance, and visual styles.
Integrated Alerts : Provides built-in alert conditions for the formation of new bullish or bearish zones near significant levels.
Clear Visual Output : Uses distinct, customizable colors for buy (support), sell (resistance), and mixed (merged) zones.
🎨 Visualization
Buy Zones : Represented by greenish boxes (default: #26a69a), indicating potential support areas formed during low entropy periods near significant levels.
Sell Zones : Represented by reddish boxes (default: #ef5350), indicating potential resistance areas formed during high entropy periods near significant levels.
Mixed Zones : Represented by bluish/purple boxes (default: #8894ff), formed when a buy zone and a sell zone merge, indicating areas of potential consolidation or conflict.
Dynamic Extension : Active zones are automatically extended to the right with each new bar.
📖 Usage Guidelines
Calculation Parameters
Window Length
Default: 15
Range: 10-100
Description: Lookback period for ApEn calculation. Shorter lengths are more responsive; longer lengths are smoother.
Embedding Dimension (m)
Default: 2
Range: 1-6
Description: Length of patterns compared in ApEn calculation. Higher values detect more complex patterns but require more data.
Tolerance (r)
Default: 0.5
Range: 0.1-1.0 (step 0.1)
Description: Sensitivity factor for pattern matching (as a multiple of standard deviation). Lower values require closer matches (more sensitive).
Zone Settings
Zone Lookback
Default: 5
Range: 5-50
Description: Lookback period for the moving average of ApEn used in threshold calculations.
Zone Threshold
Default: 0.5
Range: 0.5-3.0
Description: Multiplier for the ApEn average to set crossover trigger levels. Higher values require larger ApEn deviations to create zones.
Maximum Zones
Default: 5
Range: 1-10
Description: Maximum number of active zones displayed. The oldest zones are removed first when the limit is reached.
Zone Merge Distance (Ticks)
Default: 5
Range: 1-50
Description: Maximum distance in ticks for two separate zones to be merged into one.
Level Filter Settings
Tick Size
Default: 0.25
Description: The minimum price increment for the asset. Must be set correctly for the specific instrument to ensure accurate level filtering.
Max Ticks Distance from Levels
Default: 40
Description: Maximum allowed distance (in ticks) from a significant level (multiple of 50) for a zone trigger to be valid.
Visual Settings
Buy Zone Color : Default: color.new(#26a69a, 83). Sets the fill color for support zones.
Sell Zone Color : Default: color.new(#ef5350, 83). Sets the fill color for resistance zones.
Mixed Zone Color : Default: color.new(#8894ff, 83). Sets the fill color for merged zones.
Buy Border Color : Default: #26a69a. Sets the border color for support zones.
Sell Border Color : Default: #ef5350. Sets the border color for resistance zones.
Mixed Border Color : Default: color.new(#a288ff, 50). Sets the border color for mixed zones.
Border Width : Default: 1, Range: 1-3. Sets the thickness of zone borders.
✅ Best Use Cases
Identifying potential support/resistance near significant psychological price levels (e.g., $50, $100 increments).
Detecting potential market turning points or consolidation zones based on shifts in price predictability.
Filtering entries or exits by confirming signals occurring near significant levels identified by the indicator.
Adding context to other technical analysis approaches by highlighting entropy-derived zones.
⚠️ Limitations
Parameter Dependency : Indicator performance is sensitive to parameter settings ( Window Length , Tolerance , Zone Threshold , Max Ticks Distance ), which may need optimization for different assets and timeframes.
Volatility Sensitivity : High market volatility or erratic price action can affect ApEn calculations and potentially lead to less reliable zone signals.
Fixed Level Filter : The significant level filter is based on multiples of 50. While common, this may not capture all relevant levels for every asset or market condition. Accurate Tick Size input is essential.
Not Standalone : Should be used in conjunction with other analysis methods (price action, volume, other indicators) for confirmation, not as a sole basis for trading decisions.
💡 What Makes This Unique
Entropy + Level Context : Uniquely combines ApEn analysis with a specific filter for proximity to significant price levels (multiples of 50), adding locational context to entropy signals.
Intelligent Zone Merging : Automatically consolidates nearby buy/sell zones based on tick distance, simplifying visual analysis and highlighting stronger confluence areas.
Targeted Signal Generation : Focuses alerts and zone creation on specific market conditions (entropy shifts near key levels).
🔬 How It Works
Calculate Entropy : The script computes the Approximate Entropy (ApEn) of the closing prices over the defined Window Length to quantify price predictability.
Check Triggers : It monitors ApEn relative to its moving average. A crossunder below a calculated threshold (avg_apen / zone_threshold) indicates potential support; a crossover above (avg_apen * zone_threshold) indicates potential resistance.
Filter by Level : A potential zone trigger is confirmed only if the low (for support) or high (for resistance) of the trigger bar is within the Max Ticks Distance of a significant price level (multiple of 50).
Manage & Draw Zones : If a trigger is confirmed, a new zone box is created. The script checks for overlaps with existing zones within the Zone Merge Distance and merges them if necessary. Zones are extended forward, and the oldest are removed to respect the Maximum Zones limit. Active zones are drawn and updated on the chart.
💡 Note:
Crucially, set the Tick Size parameter correctly for your specific trading instrument in the “Level Filter Settings”. Incorrect Tick Size will make the significant level filter inaccurate.
Experiment with parameters, especially Window Length , Tolerance (r) , Zone Threshold , and Max Ticks Distance , to tailor the indicator’s sensitivity to your preferred asset and timeframe.
Always use this indicator as part of a comprehensive trading plan, incorporating risk management and seeking confirmation from other analysis techniques.
Relative Strength Index with Percentile📈 Relative Strength Index with Percentile Rank (RSI + Percentile)
This advanced RSI indicator adds a powerful percentile ranking system to the classic Relative Strength Index, providing deeper insight into current RSI values relative to recent history.
🔍 Key Features:
Standard RSI Calculation: Identifies overbought/oversold levels using a customizable period.
RSI Percentile (0–100%): Calculates where the current RSI value stands within a user-defined lookback period.
Dynamic Background Coloring:
🟩 Green when RSI percentile is above 80% (strong relative strength)
🟥 Red when RSI percentile is below 20% (strong relative weakness)
Optional Divergence Detection: Spot classic bullish and bearish divergences between price and RSI.
Smoothing Options: Apply various moving averages (SMA, EMA, RMA, etc.) to the RSI, with optional Bollinger Bands.
Flexible Settings: Full control over lookback periods, smoothing type, and band sensitivity.
🧠 Why Use RSI Percentile?
Traditional RSI values can become less informative during trending markets. By ranking the RSI as a percentile, you gain contextual insight into whether the current strength is unusually high or low compared to recent history, rather than just a fixed 70/30 threshold.
