Savitzky-Golay Z-Score [BackQuant]Savitzky-Golay Z-Score
The Savitzky-Golay Z-Score is a powerful trading indicator that combines the precision of the Savitzky-Golay filter with the statistical strength of the Z-Score. This advanced indicator is designed to detect trend shifts, identify overbought or oversold conditions, and highlight potential divergences in the market, providing traders with a unique edge in detecting momentum changes and trend reversals.
Core Concept: Savitzky-Golay Filter
The Savitzky-Golay filter is a widely-used smoothing technique that preserves important signal features such as peak detection while filtering out noise. In this indicator, the filter is applied to price data (default set to HLC3) to smooth out volatility and produce a cleaner trend line. By specifying the window size and polynomial degree, traders can fine-tune the degree of smoothing to match their preferred trading style or market conditions.
Z-Score: Measuring Deviation
The Z-Score is a statistical measure that indicates how far the current price is from its mean in terms of standard deviations. In trading, the Z-Score can be used to identify extreme price moves that are likely to revert or continue trending. A positive Z-Score means the price is above the mean, while a negative Z-Score indicates the price is below the mean.
This script calculates the Z-Score based on the Savitzky-Golay filtered price, enabling traders to detect moments when the price is diverging from its typical range and may present an opportunity for a trade.
Long and Short Conditions
The Savitzky-Golay Z-Score generates clear long and short signals based on the Z-Score value:
Long Signals : When the Z-Score is positive, indicating the price is above its smoothed mean, a long signal is generated. The color of the bars turns green, signaling upward momentum.
Short Signals : When the Z-Score is negative, indicating the price is below its smoothed mean, a short signal is generated. The bars turn red, signaling downward momentum.
These signals allow traders to follow the prevailing trend with confidence, using statistical backing to avoid false signals from short-term volatility.
Standard Deviation Levels and Extreme Levels
This indicator includes several features to help visualize overbought and oversold conditions:
Standard Deviation Levels: The script plots horizontal lines at +1, +2, -1, and -2 standard deviations. These levels provide a reference for how far the current price is from the mean, allowing traders to quickly identify when the price is moving into extreme territory.
Extreme Levels: Additional extreme levels at +3 and +4 (and their negative counterparts) are plotted to highlight areas where the price is highly likely to revert. These extreme levels provide important insight into market conditions that are far outside the norm, signaling caution or potential reversal zones.
The indicator also adapts the color shading of these extreme zones based on the Z-Score’s strength. For example, the area between +3 and +4 is shaded with a stronger color when the Z-Score approaches these values, giving a visual representation of market pressure.
Divergences: Detecting Hidden and Regular Signals
A key feature of the Savitzky-Golay Z-Score is its ability to detect bullish and bearish divergences, both regular and hidden:
Regular Bullish Divergence: This occurs when the price makes a lower low while the Z-Score forms a higher low. It signals that bearish momentum is weakening, and a bullish reversal could be near.
Hidden Bullish Divergence: This divergence occurs when the price makes a higher low while the Z-Score forms a lower low. It signals that bullish momentum may continue after a temporary pullback.
Regular Bearish Divergence: This occurs when the price makes a higher high while the Z-Score forms a lower high, signaling that bullish momentum is weakening and a bearish reversal may be near.
Hidden Bearish Divergence: This divergence occurs when the price makes a lower high while the Z-Score forms a higher high, indicating that bearish momentum may continue after a temporary rally.
These divergences are plotted directly on the chart, making it easier for traders to spot when the price and momentum are out of sync and when a potential reversal may occur.
Customization and Visualization
The Savitzky-Golay Z-Score offers a range of customization options to fit different trading styles:
Window Size and Polynomial Degree: Adjust the window size and polynomial degree of the Savitzky-Golay filter to control how much smoothing is applied to the price data.
Z-Score Lookback Period: Set the lookback period for calculating the Z-Score, allowing traders to fine-tune the sensitivity to short-term or long-term price movements.
Display Options: Choose whether to display standard deviation levels, extreme levels, and divergence labels on the chart.
Bar Color: Color the price bars based on trend direction, with green for bullish trends and red for bearish trends, allowing traders to easily visualize the current momentum.
Divergences: Enable or disable divergence detection, and adjust the lookback periods for pivots used to detect regular and hidden divergences.
Alerts and Automation
To ensure you never miss an important signal, the indicator includes built-in alert conditions for the following events:
Positive Z-Score (Long Signal): Triggers an alert when the Z-Score crosses above zero, indicating a potential buying opportunity.
Negative Z-Score (Short Signal): Triggers an alert when the Z-Score crosses below zero, signaling a potential short opportunity.
Shifting Momentum: Alerts when the Z-Score is shifting up or down, providing early warning of changing market conditions.
These alerts can be configured to notify you via email, SMS, or app notification, allowing you to stay on top of the market without having to constantly monitor the chart.
Trading Applications
The Savitzky-Golay Z-Score is a versatile tool that can be applied across multiple trading strategies:
Trend Following: By smoothing the price and calculating the Z-Score, this indicator helps traders follow the prevailing trend while avoiding false signals from short-term volatility.
Mean Reversion: The Z-Score highlights moments when the price is far from its mean, helping traders identify overbought or oversold conditions and capitalize on potential reversals.
Divergence Trading: Regular and hidden divergences between the Z-Score and price provide early warning of trend reversals, allowing traders to enter trades at opportune moments.
Final Thoughts
The Savitzky-Golay Z-Score is an advanced statistical tool designed to provide a clearer view of market trends and momentum. By applying the Savitzky-Golay filter and Z-Score analysis, this indicator reduces noise and highlights key areas where the market may reverse or accelerate, giving traders a significant edge in understanding price behavior.
Whether you’re a trend follower or a reversal trader, this indicator offers the flexibility and insights you need to navigate complex markets with confidence.
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Nef33-Volume Footprint ApproximationDescription of the "Volume Footprint Approximation" Indicator
Purpose
The "Volume Footprint Approximation" indicator is a tool designed to assist traders in analyzing market volume dynamics and anticipating potential trend changes in price. It is inspired by the concept of a volume footprint chart, which visualizes the distribution of trading volume across different price levels. However, since TradingView does not provide detailed intrabar data for all users, this indicator approximates the behavior of a footprint chart by using available volume and price data (open, close, volume) to classify volume as buy or sell, calculate volume delta, detect imbalances, and generate trend change signals.
The indicator is particularly useful for identifying areas of high buying or selling activity, imbalances between supply and demand, delta divergences, and potential reversal points in the market. It provides specific signals for bullish and bearish trend changes, making it suitable for traders looking to trade reversals or confirm trends.
How It Works
The indicator uses volume and price data from each candlestick to perform the following calculations:
Volume Classification:
Classifies the volume of each candlestick as "buy" or "sell" based on price movement:
If the closing price is higher than the opening price (close > open), the volume is classified as "buy."
If the closing price is lower than the opening price (close < open), the volume is classified as "sell."
If the closing price equals the opening price (close == open), it compares with the previous close to determine the direction:
If the current close is higher than the previous close, it is classified as "buy."
If the current close is lower than the previous close, it is classified as "sell."
If the current close equals the previous close, the classification from the previous bar is used.
Delta Calculation:
Calculates the volume delta as the difference between buy volume and sell volume (buyVolume - sellVolume).
A positive delta indicates more buy volume; a negative delta indicates more sell volume.
Imbalance Detection:
Identifies imbalances between buy and sell volume:
A buy imbalance occurs when buy volume exceeds sell volume by a defined percentage (default is 300%).
A sell imbalance occurs when sell volume exceeds buy volume by the same percentage.
Delta Divergence Detection:
Positive Delta Divergence: Occurs when the price is falling (for at least 2 bars) but the delta is increasing or becomes positive, indicating that buyers are entering despite the price decline.
Negative Delta Divergence: Occurs when the price is rising (for at least 2 bars) but the delta is decreasing or becomes negative, indicating that sellers are entering despite the price increase.
Trend Change Signals:
Bullish Signal (trendChangeBullish): Generated when the following conditions are met:
There is a positive delta divergence.
The delta has moved from a negative value (e.g., -500) to a positive value (e.g., +200) over the last 3 bars.
There is a buy imbalance.
The price is near a historical support level (approximated as the lowest low of the last 50 bars).
Bearish Signal (trendChangeBearish): Generated when the following conditions are met:
There is a negative delta divergence.
The delta has moved from a positive value (e.g., +500) to a negative value (e.g., -200) over the last 3 bars.
There is a sell imbalance.
The price is near a historical resistance level (approximated as the highest high of the last 50 bars).
Visual Elements
The indicator is displayed in a separate panel below the price chart (overlay=false) and includes the following elements:
Volume Histograms:
Buy Volume: Represented by a green histogram. Shows the volume classified as "buy."
Sell Volume: Represented by a red histogram. Shows the volume classified as "sell."
Note: The histograms overlap, and the last plotted histogram (red) takes visual precedence, meaning the sell volume may cover the buy volume if it is larger.
Delta Line:
Delta Volume: Represented by a blue line. Shows the difference between buy and sell volume.
A line above zero indicates more buy volume; a line below zero indicates more sell volume.
A dashed gray horizontal line marks the zero level for easier interpretation.
Imbalance Backgrounds:
Buy Imbalance: Light green background when buy volume exceeds sell volume by the defined percentage.
Sell Imbalance: Light red background when sell volume exceeds buy volume by the defined percentage.
Divergence Backgrounds:
Positive Delta Divergence: Lime green background when a positive delta divergence is detected.
Negative Delta Divergence: Fuchsia background when a negative delta divergence is detected.
Trend Change Signals:
Bullish Signal: Green label with the text "Bullish Trend Change" when the conditions for a bullish trend change are met.
Bearish Signal: Red label with the text "Bearish Trend Change" when the conditions for a bearish trend change are met.
Information Labels:
Below each bar, a label displays:
Total Vol: The total volume of the bar.
Delta: The delta volume value.
Alerts
The indicator generates the following alerts:
Positive Delta Divergence: "Positive Delta Divergence Detected! Price is falling, but delta is increasing."
Negative Delta Divergence: "Negative Delta Divergence Detected! Price is rising, but delta is decreasing."
Bullish Trend Change Signal: "Bullish Trend Change Signal! Positive Delta Divergence, Delta Rise, Buy Imbalance, and Near Support."
Bearish Trend Change Signal: "Bearish Trend Change Signal! Negative Delta Divergence, Delta Drop, Sell Imbalance, and Near Resistance."
These alerts can be configured in TradingView to receive real-time notifications.
Adjustable Parameters
The indicator allows customization of the following parameters:
Imbalance Threshold (%): The percentage required to detect an imbalance between buy and sell volume (default is 300%).
Lookback Period for Divergence: Number of bars to look back for detecting price and delta trends (default is 2 bars).
Support/Resistance Lookback Period: Number of bars to look back for identifying historical support and resistance levels (default is 50 bars).
Delta High Threshold (Bearish): Minimum delta value 2 bars ago for the bearish signal (default is +500).
Delta Low Threshold (Bearish): Maximum delta value in the current bar for the bearish signal (default is -200).
Delta Low Threshold (Bullish): Maximum delta value 2 bars ago for the bullish signal (default is -500).
Delta High Threshold (Bullish): Minimum delta value in the current bar for the bullish signal (default is +200).
Practical Use
The indicator is useful for the following purposes:
Identifying Trend Changes:
The trend change signals (trendChangeBullish and trendChangeBearish) indicate potential price reversals. For example, a bullish signal near a support level may be an opportunity to enter a long position.
Detecting Divergences:
Delta divergences (positive and negative) can anticipate trend changes by showing a disagreement between price movement and underlying buying/selling pressure.
Finding Key Levels:
Imbalances (green and red backgrounds) often coincide with support and resistance levels, helping to identify areas where the market might react.
Confirming Trends:
A consistently positive delta in an uptrend or a negative delta in a downtrend can confirm the strength of the trend.
Identifying Failed Auctions:
Although not detected automatically, you can manually identify failed auctions by observing a price move to new highs/lows with decreasing volume in the direction of the move.
Limitations
Intrabar Data: It does not use detailed intrabar data, making it less precise than a native footprint chart.
Approximations: Volume classification and support/resistance detection are approximations, which may lead to false signals.
Volume Dependency: It requires reliable volume data, so it may be less effective on assets with inaccurate volume data (e.g., some forex pairs).
False Signals: Divergences and imbalances do not always indicate a trend change, especially in strongly trending markets.
Recommendations
Combine with Other Indicators: Use tools like RSI, MACD, support/resistance levels, or candlestick patterns to confirm signals.
Trade on Higher Timeframes: Signals are more reliable on higher timeframes like 1-hour or 4-hour charts.
Perform Backtesting: Evaluate the indicator's accuracy on historical data to adjust parameters and improve effectiveness.
Adjust Parameters: Modify thresholds (e.g., imbalanceThreshold or supportResistanceLookback) based on the asset and timeframe you are trading.
Conclusion
The "Volume Footprint Approximation" indicator is a powerful tool for analyzing volume dynamics and anticipating price trend changes. By classifying volume, calculating delta, detecting imbalances and divergences, and generating trend change signals, it provides traders with valuable insights into market buying and selling pressure. While it has limitations due to the lack of intrabar data, it can be highly effective when used in combination with other technical analysis tools and on assets with reliable volume data.
LibraryDivergenceV6LibraryDivergenceV6
Enhance your trading strategies with LibraryDivergenceV6, a comprehensive Pine Script library designed to simplify and optimize the detection of bullish and bearish divergences across multiple technical indicators. Whether you're developing your own indicators or seeking to incorporate robust divergence analysis into your trading systems, this library provides the essential tools and functions to accurately identify potential market reversals and continuations.
Overview
LibraryDivergenceV6 offers a suite of functions that detect divergences between price movements and key technical indicators such as the Relative Strength Index (RSI) and On-Balance Volume (OBV). By automating the complex calculations involved in divergence detection, this library enables traders and developers to implement reliable and customizable divergence strategies with ease.
Key Features
Comprehensive Divergence Detection
Bullish Divergence: Identifies instances where the indicator forms higher lows while the price forms lower lows, signaling potential upward reversals.
Bearish Divergence: Detects situations where the indicator creates lower highs while the price forms higher highs, indicating possible downward reversals.
Overbought and Oversold Conditions: Differentiates between standard and strong divergences by considering overbought and oversold levels, enhancing signal reliability.
Multi-Indicator Support
RSI (Relative Strength Index): Analyze momentum-based divergences to spot potential trend reversals.
OBV (On-Balance Volume): Incorporate volume flow into divergence analysis for a more comprehensive market perspective.
Customizable Parameters
Pivot Points Configuration: Adjust the number of bars to the left and right for pivot detection, allowing fine-tuning based on different timeframes and trading styles.
Range Settings: Define minimum and maximum bar ranges to control the sensitivity of divergence detection, reducing false signals.
Noise Cancellation: Enable or disable noise filtering to focus on significant divergences and minimize minor fluctuations.
Flexible Usage
Exported Functions: Easily integrate divergence detection into your custom indicators or trading strategies with exported functions such as DivergenceBull, DivergenceBear, DivergenceBullOversold, and DivergenceBearOverbought.
Occurrence Handling: Specify which occurrence of a divergence to consider (e.g., most recent, previous) for precise analysis.
Optimized Performance
Efficient Calculations: Designed to handle multiple occurrences and pivot points without compromising script performance.
Line Management: Automatically creates and deletes trend lines based on divergence conditions, ensuring a clean and uncluttered chart display.
Constance Brown RSI with Composite IndexConstance Brown RSI with Composite Index
Overview
This indicator combines Constance Brown's RSI interpretation methodology with a Composite Index and ATR Distance to VWAP measurement to provide a comprehensive trading tool. It helps identify trends, momentum shifts, overbought/oversold conditions, and potential reversal points.
Key Features
Color-coded RSI zones for immediate trend identification
Composite Index for momentum analysis and divergence detection
ATR Distance to VWAP for identifying extreme price deviations
Automatic divergence detection for early reversal warnings
Pre-configured alerts for key trading signals
How to Use This Indicator
Trend Identification
The RSI line changes color based on its position:
Blue zone (RSI > 50): Bullish trend - look for buying opportunities
Purple zone (RSI < 50): Bearish trend - look for selling opportunities
Gray zone (RSI 40-60): Neutral/transitional market - prepare for potential breakout
The 40-50 area (light blue fill) acts as support during uptrends, while the 50-60 area (light purple fill) acts as resistance during downtrends.
// From the code:
upTrendZone = rsiValue > 50 and rsiValue <= 90
downTrendZone = rsiValue < 50 and rsiValue >= 10
neutralZone = rsiValue > 40 and rsiValue < 60
rsiColor = neutralZone ? neutralRSI : upTrendZone ? upTrendRSI : downTrendRSI
Momentum Analysis
The Composite Index (fuchsia line) provides momentum confirmation:
Values above 50 indicate positive momentum
Values below 40 indicate negative momentum
Crossing above/below these thresholds signals potential momentum shifts
// From the code:
compositeIndexRaw = rsiChange / ta.stdev(rsiValue, rsiLength)
compositeIndex = ta.sma(compositeIndexRaw, compositeSmoothing)
compositeScaled = compositeIndex * 10 + 50 // Scaled to fit 0-100 range
Overbought/Oversold Detection
The ATR Distance to VWAP table in the top-right corner shows how far price has moved from VWAP in terms of ATR units:
Extreme positive values (orange/red): Potentially overbought
Extreme negative values (purple/red): Potentially oversold
Near zero (gray): Price near average value
// From the code:
priceDistance = (close - vwapValue) / ta.atr(atrPeriod)
// Color coding based on distance value
Divergence Trading
The indicator automatically detects divergences between the Composite Index and price:
Bullish divergence: Price makes lower low but Composite Index makes higher low
Bearish divergence: Price makes higher high but Composite Index makes lower high
// From the code:
divergenceBullish = ta.lowest(compositeIndex, rsiLength) > ta.lowest(close, rsiLength)
divergenceBearish = ta.highest(compositeIndex, rsiLength) < ta.highest(close, rsiLength)
Trading Strategies
Trend Following
1. Identify the trend using RSI color:
Blue = Uptrend, Purple = Downtrend
2. Wait for pullbacks to support/resistance zones:
In uptrends: Buy when RSI pulls back to 40-50 zone and bounces
In downtrends: Sell when RSI rallies to 50-60 zone and rejects
3. Confirm with Composite Index:
Uptrends: Composite Index stays above 50 or quickly returns above it
Downtrends: Composite Index stays below 50 or quickly returns below it
4. Manage risk using ATR Distance:
Take profits when ATR Distance reaches extreme values
Place stops beyond recent swing points
Reversal Trading
1. Look for divergences
Bullish: Price makes lower low but Composite Index makes higher low
Bearish: Price makes higher high but Composite Index makes lower high
2. Confirm with ATR Distance:
Extreme readings suggest potential reversals
3. Wait for RSI zone transition:
Bullish: RSI crosses above 40 (purple to neutral/blue)
Bearish: RSI crosses below 60 (blue to neutral/purple)
4. Enter after confirmation:
Use candlestick patterns for precise entry
Place stops beyond the divergence point
Four pre-configured alerts are available:
Momentum High: Composite Index above 50
Momentum Low: Composite Index below 40
Bullish Divergence: Composite Index higher low
Bearish Divergence: Composite Index lower high
Customization
Adjust these parameters to optimize for your trading style:
RSI Length: Default 14, lower for more sensitivity, higher for fewer signals
Composite Index Smoothing: Default 10, lower for quicker signals, higher for less noise
ATR Period: Default 14, affects the ATR Distance to VWAP calculation
This indicator works well across various markets and timeframes, though the default settings are optimized for daily charts. Adjust parameters for shorter or longer timeframes as needed.
Happy trading!
Smart Money Oscillator [ChartPrime]The "Smart Money Oscillator " is a premium and discount zone oscillator with BOS and CHoCH built in for further analysis of price action. This indicator works by first determining the the premium and discount zones by using pivot points and high/lows. The top of this oscillator represents the current premium zone while the bottom half of this oscillator represents the discount zone. This oscillator functionally works like a stochastic oscillator with more sophisticated upper and lower bounds generated using smart money concept theories. We have included a moving average to allow the user to visualize the currant momentum in the oscillator. Another key feature we have included lagging divergences to help traders visualize potential reversal conditions.
Understanding the concepts of Premium and Discount zones, as well as Break of Structure (BoS) and Change of Character (CHoCH), is crucial for traders using the Smart Money Oscillator. These concepts are rooted in market structure analysis, which involves studying price levels and movements.
Premium Zone is where the price is considered to be relatively high or 'overbought'. In this zone, prices have risen significantly and may indicate that the asset is becoming overvalued, potentially leading to a reversal or slowdown in the upward trend.
The Discount Zone represents a 'discount' or 'oversold' area. Here, prices have fallen substantially, suggesting that the asset might be undervalued. This could be an indicator of a potential upward reversal or a pause in the downward trend.
Break of Structure (BoS) is about the continuation of a trend. In a bullish trend, a BoS is identified by the break of a recent higher high. In a bearish trend, it's the break of a recent Lower Low. BoS indicates that the trend is strong and likely to continue in its current direction. It's a sign of strength in the prevailing trend, whether up or down.
Change of Character (CHoCH) is an indication of a potential end to a trend. It occurs when there's a significant change in the market's behavior, contradicting the current trend. For example, in an uptrend characterized by higher highs and higher lows, a CHoCH may occur if a new high is formed but then is followed by an impulsive move downwards. This suggests that the bullish trend may be weakening and a bearish reversal could be imminent. CHoCH is essentially a sign of trend exhaustion and potential reversal.
With each consecutive BoS, the signal line of the oscillator will deepen in color. This allows you to visually see the strength of the current trend. The maximum strength of the trend is found by keeping track of the maximum number of consecutive BoS's within a window of 10. This calculation excludes periods without any BoS's to allow for a more stable max.
Quick Update is a feature that implements a more aggressive algorithm to update the highs and lows. Instead of updating the pivot points exclusively to update the range levels, it will attempt to use the current historical highs/lows to update the bounds. This results in a more responsive range at the cost of stability. There are pros and cons for both settings. With Quick Update disabled, the indicator will allow for strong reversals to register without the indicator maxing out. With Quick Update enabled, the indicator will show shorter term extremes with the risk of the signal being pinned to the extremities during strong trends or large movements. With Quick Update disabled, the oscillator prioritizes stability, using a more historical perspective to set its bounds. When Quick Update is enabled, the oscillator becomes more responsive, adjusting its bounds rapidly to reflect the latest market movements.
The Scale Offset feature allows the indicator to break the boundaries of the oscillator. This can be useful when the market is breaking highs or lows allowing the user to identify extremities in price. With Scale Offset disabled the oscillator will always remain inside of the boundaries because the extremities will be updated instantly. When this feature is enabled it will update the boundaries one step behind instead of updating it instantly. This allows the user to more easily see overbought and oversold conditions at the cost of incurring a single bar lag to the boundaries. Generally this is a good idea as this behavior makes the oscillator more sensitive to recent price spikes or drops, reflecting sudden market movements more accurately. It accentuates the extremities of the market conditions, potentially offering a more aggressive analysis. The main trade-off with the Scale Offset feature is between sensitivity and potential overreaction. It offers a more immediate and exaggerated reflection of market conditions but might also lead to misinterpretations in certain scenarios, especially in highly volatile markets.
Divergence is used to predict potential trend reversals. It occurs when the price of an asset and the reading of an oscillator move in opposite directions. This discrepancy can signal a weakening of the current trend and possibly indicate a potential reversal.
Divergence doesn't always lead to a trend reversal, but it's a warning sign that the current trend might be weakening. Divergence can sometimes give false signals, particularly in strongly trending markets where the oscillator may remain in overbought or oversold conditions for extended periods. The lagging nature of using pivot points to calculate divergences means that all divergences are limited by the pivot look forward input. The upside of using a longer look forward is that the divergences will be more accurate. The obvious con here is that it will be more delayed and might be useless by the time it appears. Its recommended to use the built in divergences as a way to learn how these are formed so you can make your own in real time.
By default, the oscillator uses a smoothing of 3 to allow for a more price like behavior while still being rather smooth compared to raw price data. Conversely, you can increase this value to make this indicator behave smoother. Something to keep in mind is that the amount of delay from real time is equal to half of the smoothing period.
We have included a verity of alerts in this indicator. Here is a list of all of the available alerts: Bullish BOS, Bearish BOS, Bullish CHoCH, Bearish CHoCH, Bullish Divergence, Hidden Bullish Divergence, Bearish Divergence, Hidden Bearish Divergence, Cross Over Average, Cross Under Average.
Below are all of the inputs and their tooltips to get you started:
Settings:
Smoothing: Specifies the degree of smoothing applied to the oscillator. Higher values result in smoother but potentially less responsive signals.
Average Length: Sets the length of the moving average applied to the oscillator, affecting its sensitivity and smoothness.
Pivot Length: Specifies the forward-looking length for pivot points, affecting how the oscillator anticipates future price movements. This directly impacts the delay in finding a pivot.
Max Length: Sets the maximum length to consider for calculating the highest values in the oscillator.
Min Length: Defines the minimum length for calculating the lowest values in the oscillator.
Quick Update: Activates a faster update mode for the oscillator's extremities, which may result in less stable range boundaries.
Scale Offset: When enabled, delays updating minimum and maximum values to enhance signal directionality, allowing the signal to occasionally exceed normal bounds.
Candle Color: Enables coloring of candles based on the current directional signal of the oscillator.
Labels:
Enable BOS/CHoCH Labels: Activates the display of BOS (Break of Structure) and CHoCH (Change of Character) labels on the chart.
Visual Padding: Turns on additional visual padding at the top and bottom of the chart to accommodate labels. Determines the amount of visual padding added to the chart for label display.
Divergence:
Divergence Pivot: Defines the number of bars to the right of the pivot in divergence calculations, influencing the oscillator's responsiveness.
Divergence Pivot Forward: Directly impacts latency. Longer periods results in more accurate results at the sacrifice of delay.
Upper Range: Sets the upper range limit for divergence calculations, influencing the oscillator's sensitivity to larger trends.
Lower Range: Determines the lower range limit for divergence calculations, affecting the oscillator's sensitivity to shorter trends.
Symbol: Allows selection of the label style for divergence indicators, with options for text or symbolic representation.
Regular Bullish: Activates the detection and marking of regular bullish divergences in the oscillator.
Hidden Bullish: Enables the identification and display of hidden bullish divergences.
Regular Bearish: Turns on the feature to detect and highlight regular bearish divergences.
Hidden Bearish: Activates the functionality for detecting and displaying hidden bearish divergences.
Color:
Bullish: Determines the minimum/maximum color gradient for bullish signals, impacting the chart's visual appearance.
Bearish: Defines the minimum/maximum color gradient for bearish signals, affecting their visual representation.
Average: Specifies the color for the average line of the oscillator, enhancing chart readability.
CHoCH: Sets the color for bullish/bearish CHoCH (Change of Character) signals.
Premium/Discount: Determines the color for the premium/discount zone in the oscillator's visual representation.
Text Color: Sets the color for the text in BoS/CHoCH labels.
Regular Bullish: Defines the color used to represent regular bullish divergences.
Hidden Bullish: Specifies the color for hidden bullish divergences.
Regular Bearish: Determines the color for hidden bearish divergences.
Divergence Text Color: Specifies the color for the text in divergence labels.
Absolute Strength Index [ASI] (Zeiierman)█ Overview
The Absolute Strength Index (ASI) is a next-generation oscillator designed to measure the strength and direction of price movements by leveraging percentile-based normalization of historical returns. Developed by Zeiierman, this indicator offers a highly visual and intuitive approach to identifying market conditions, trend strength, and divergence opportunities.
By dynamically scaling price returns into a bounded oscillator (-10 to +10), the ASI helps traders spot overbought/oversold conditions, trend reversals, and momentum changes with enhanced precision. It also incorporates advanced features like divergence detection and adaptive signal smoothing for versatile trading applications.
█ How It Works
The ASI's core calculation methodology revolves around analyzing historical price returns, classifying them into top and bottom percentiles, and normalizing the current price movement within this framework. Here's a breakdown of its key components:
⚪ Returns Lookback
The ASI evaluates historical price returns over a user-defined period (Returns Lookback) to measure recent price behavior. This lookback window determines the sensitivity of the oscillator:
Shorter Lookback: Higher responsiveness to recent price movements, suitable for scalping or high-volatility assets.
Longer Lookback: Smoother oscillator behavior is ideal for identifying larger trends and avoiding false signals.
⚪ Percentile-Based Thresholds
The ASI categorizes returns into two groups:
Top Percentile (Winners): The upper X% of returns, representing the strongest upward price moves.
Bottom Percentile (Losers): The lower X% of returns, capturing the sharpest downward movements.
This percentile-based normalization ensures the ASI adapts to market conditions, filtering noise and emphasizing significant price changes.
⚪ Oscillator Normalization
The ASI normalizes current returns relative to the top and bottom thresholds:
Values range from -10 to +10, where:
+10 represents extreme bullish strength (above the top percentile threshold).
-10 indicates extreme bearish weakness (below the bottom percentile threshold).
⚪ Signal Line Smoothing
A signal line is optionally applied to the ASI using a variety of moving averages:
Options: SMA, EMA, WMA, RMA, or HMA.
Effect: Smooths the ASI to filter out noise, with shorter lengths offering higher responsiveness and longer lengths providing stability.
⚪ Divergence Detection
One of ASI's standout features is its ability to detect and highlight bullish and bearish divergences:
Bullish Divergence: The ASI forms higher lows while the price forms lower lows, signaling potential upward reversals.
Bearish Divergence: The ASI forms lower highs while the price forms higher highs, indicating potential downward reversals.
█ Key Differences from RSI
Dynamic Adaptability: ASI adjusts to market conditions through percentile-based scaling, while RSI uses static thresholds.
█ How to Use ASI
⚪ Trend Identification
Bullish Strength: ASI above zero suggests upward momentum, suitable for trend-following trades.
Bearish Weakness: ASI below zero signals downward momentum, ideal for short trades or exits from long positions.
⚪ Overbought/Oversold Levels
Overbought Zone: ASI in the +8 to +10 range indicates potential exhaustion of bullish momentum.
Oversold Zone: ASI in the -8 to -10 range points to potential reversal opportunities.
⚪ Divergence Signals
Look for bullish or bearish divergence labels to anticipate trend reversals before they occur.
⚪ Signal Line Crossovers
A crossover between the ASI and its signal line (e.g., EMA or SMA) can indicate a shift in momentum:
Bullish Crossover: ASI crosses above the signal line, signaling potential upside.
Bearish Crossover: ASI crosses below the signal line, suggesting downside momentum.
█ Settings Explained
⚪ Absolute Strength Index
Returns Lookback: Sets the sensitivity of the oscillator. Shorter periods detect short-term changes, while longer periods focus on broader trends.
Top/Bottom Percentiles: Adjust thresholds for defining winners and losers. Narrower percentiles increase sensitivity to outliers.
Signal Line Type: Choose from SMA, EMA, WMA, RMA, or HMA for smoothing.
Signal Line Length: Fine-tune the responsiveness of the signal line.
⚪ Divergence
Divergence Lookback: Adjusts the period for detecting divergence. Use longer lookbacks to reduce noise.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Custom Moving Average Ribbon with EMA Table & Text ColorComprehensive Description of the Custom Moving Average Ribbon with EMA Table & Text Color
The Custom Moving Average Ribbon with EMA Table & Text Color is a highly flexible and customizable indicator designed for traders who use multiple moving averages to assess trends, strength, and potential market reversals. It plots up to 8 moving averages (either SMA, EMA, WMA, or VWMA) on the price chart and displays a table summarizing the moving averages’ values, periods, and colors. The table also allows for the customization of the text color, making it easier to align with your chart’s theme or preference.
Key Features:
Multiple Moving Averages: You can display up to 8 moving averages (MA), each of which can be customized in terms of:
Type: SMA (Simple Moving Average), EMA (Exponential Moving Average), WMA (Weighted Moving Average), or VWMA (Volume-Weighted Moving Average).
Period: Each moving average has a user-defined period, which allows for flexibility depending on your trading style (short-term, medium-term, or long-term).
Enable/Disable: Each moving average can be independently enabled or disabled based on your preference.
Moving Average Ribbon: The indicator visualizes multiple moving averages as a ribbon, giving traders insight into the market's underlying trend. The interaction between these moving averages provides essential signals:
Uptrend: Shorter-term MAs above longer-term MAs, all sloping upward.
Downtrend: Shorter-term MAs below longer-term MAs, sloping downward.
Consolidation: MAs tightly packed, indicating low volatility or a sideways market.
Customizable Table: The indicator includes a table that displays:
The Name of each moving average (e.g., MA 1, MA 2, etc.).
The Period used for each moving average.
The Current Value of each moving average.
Color Coding for easier visual identification on the chart.
Text Color Customization: You can change the text color in the table to match your chart style or to ensure high visibility.
Responsive Design: This indicator works on any time frame, whether you're a day trader, swing trader, or long-term investor, and the table adjusts dynamically as new data comes in.
How to Use the Indicator
a) Trend Identification
The Custom Moving Average Ribbon helps in identifying trends and their strength. Here’s how you can interpret the plotted moving averages:
Uptrend (Bullish):
If the shorter-term moving averages (e.g., 5-period, 10-period) are above the longer-term moving averages (e.g., 50-period, 200-period), and all the MAs are sloping upward, it suggests a strong bullish trend.
The greater the separation between the moving averages, the stronger the uptrend.
Use the table to quickly verify the current value of each MA and confirm that the price is staying above most or all of the MAs.
Downtrend (Bearish):
When shorter-term moving averages are below the longer-term moving averages and all MAs are sloping downward, this indicates a bearish trend.
Greater separation between MAs indicates a stronger downtrend.
Neutral/Consolidating Market:
If the MAs are tightly packed and frequently crossing each other, the market is likely consolidating, and a strong trend is not in play.
In these situations, it’s better to wait for a clearer signal before taking any positions.
b) Reversal Signals
Golden Cross: When a short-term moving average (e.g., 50-period) crosses above a long-term moving average (e.g., 200-period), this is considered a bullish signal, suggesting a possible upward trend.
Death Cross: When a short-term moving average crosses below a long-term moving average, it’s considered a bearish signal, indicating a potential downward trend.
c) Using the Table for Quick Reference
The table allows you to monitor:
The current price value relative to each moving average. If the price is above most MAs, the market is likely in an uptrend, and if below, in a downtrend.
Changes in MA values: If you see values of shorter-term MAs moving closer to or crossing longer-term MAs, this could indicate a weakening trend or a potential reversal.
How to Combine this Indicator with Other Indicators for a Solid Strategy
The Custom Moving Average Ribbon is powerful on its own but can be enhanced when combined with other technical indicators to form a comprehensive trading strategy.
1. Combining with RSI (Relative Strength Index)
How It Works: RSI is a momentum oscillator that measures the speed and change of price movements, typically over 14 periods. It ranges from 0 to 100, with readings above 70 considered overbought and below 30 considered oversold.
Strategy:
Overbought in an Uptrend: If the moving average ribbon indicates an uptrend but the RSI shows the market is overbought (RSI > 70), it could signal a pullback or correction is imminent.
Oversold in a Downtrend: If the moving average ribbon indicates a downtrend but the RSI shows oversold conditions (RSI < 30), a bounce or reversal may be on the horizon.
2. Combining with MACD (Moving Average Convergence Divergence)
How It Works: MACD tracks the difference between two exponential moving averages, typically the 12-period and 26-period EMAs. It generates buy and sell signals based on crossovers and divergences.
Strategy:
Trend Confirmation: Use the MACD to confirm the direction and momentum of the trend indicated by the moving average ribbon. For example, if the MACD line crosses above the signal line while the shorter-term MAs are above the longer-term MAs, it confirms strong bullish momentum.
Divergences: Watch for divergences between price action and MACD. If price is making higher highs but MACD is making lower highs, it could signal a weakening trend, which you can verify using the moving averages.
3. Combining with Bollinger Bands
How It Works: Bollinger Bands plot two standard deviations above and below a moving average, typically the 20-period SMA. The bands widen during periods of high volatility and contract during periods of low volatility.
Strategy:
Breakout or Reversal: If price action moves above the upper Bollinger Band while the shorter-term MAs are crossing above the longer-term MAs, it confirms a strong breakout. Conversely, if price touches or falls below the lower Bollinger Band and the shorter MAs start crossing below the longer-term MAs, it indicates a potential breakdown.
Mean Reversion: In sideways markets, when the moving averages are tightly packed, Bollinger Bands can help spot mean reversion opportunities (buy near the lower band, sell near the upper band).
4. Combining with Volume Indicators
How It Works: Volume is a crucial confirmation indicator for any trend or breakout. Combining volume with the moving average ribbon can enhance your strategy.
Strategy:
Trend Confirmation: If the price breaks above the moving averages and is accompanied by high volume, it confirms a strong breakout. Similarly, if price breaks below the moving averages on high volume, it signals a strong downtrend.
Divergence: If price continues to trend in one direction but volume decreases, it could indicate a weakening trend, helping you prepare for a reversal.
Example Strategies Using the Indicator
Trend-Following Strategy:
Use the moving average ribbon to identify the main trend.
Combine with MACD or RSI for confirmation of momentum.
Enter trades when the shorter-term MAs confirm the trend and the confirmation indicator (MACD or RSI) aligns with the trend.
Exit trades when the moving averages start converging or when your confirmation indicator shows signs of reversal.
Reversal Strategy:
Wait for significant crossovers in the moving averages (Golden Cross or Death Cross).
Confirm the reversal with divergence in MACD or RSI.
Use Bollinger Bands to fine-tune your entry and exit points based on overbought/oversold conditions.
Conclusion
The Custom Moving Average Ribbon with EMA Table & Text Color indicator provides a robust framework for traders looking to use multiple moving averages to gauge trend direction, strength, and potential reversals. By combining it with other technical indicators like RSI, MACD, Bollinger Bands, and volume, you can develop a solid trading strategy that enhances accuracy, reduces false signals, and maximizes profit potential in various market conditions.
This indicator offers high flexibility with customization options, making it suitable for traders of all levels and strategies. Whether you're trend-following, scalping, or swing trading, this tool provides invaluable insights into market movements.
RSI - 5UP Overview
The "RSI - 5UP" indicator is a versatile tool that enhances the traditional Relative Strength Index (RSI) by adding smoothing options, Bollinger Bands, and divergence detection. It provides a clear visual representation of RSI levels with customizable bands and optional moving averages, helping traders identify overbought/oversold conditions and potential trend reversals through divergence signals.
Features
Customizable RSI: Adjust the RSI length and source to fit your trading style.
Overbought/Oversold Bands: Visualizes RSI levels with intuitive color-coded bands (red for overbought at 70, white for neutral at 50, green for oversold at 30).
Smoothing Options: Apply various types of moving averages (SMA, EMA, SMMA, WMA, VWMA) to the RSI, with optional Bollinger Bands for volatility analysis.
Divergence Detection: Identifies regular bullish and bearish divergences, with visual labels ("Bull" for bullish, "Bear" for bearish) and alerts.
G radient Fills: Highlights overbought and oversold zones with gradient fills (green for overbought, red for oversold).
How to Use
1. Add to Chart: Apply the "RSI - 5UP" indicator to any chart. It works well on timeframes from 5 minutes to daily.
2. Configure Settings:
RSI Settings:
RSI Length: Adjust the period for RSI calculation (default: 14).
Source: Choose the price source for RSI (default: close).
Calculate Divergence: Enable to detect bullish/bearish divergences (default: disabled).
Smoothing:
Type: Select the type of moving average to smooth the RSI ("None", "SMA", "SMA + Bollinger Bands", "EMA", "SMMA (RMA)", "WMA", "VWMA"; default: "SMA").
Length: Set the period for the moving average (default: 14).
BB StdDev: If "SMA + Bollinger Bands" is selected, adjust the standard deviation multiplier for the bands (default: 2.0).
3.Interpret the Indicator:
RSI Levels: The RSI line (purple) oscillates between 0 and 100. Levels above 70 (red band) indicate overbought conditions, while levels below 30 (green band) indicate oversold conditions. The 50 level (white band) is neutral.
Gradient Fills: The background gradients (green above 70, red below 30) highlight overbought and oversold zones for quick reference.
Moving Average (MA): If enabled, a yellow MA line smooths the RSI. If "SMA + Bollinger Bands" is selected, green bands appear around the MA to show volatility.
Divergences: If "Calculate Divergence" is enabled, look for "Bull" (green label) and "Bear" (red label) signals:
Bullish Divergence: Indicates a potential upward reversal when the price makes a lower low, but the RSI makes a higher low.
Bearish Divergence: Indicates a potential downward reversal when the price makes a higher high, but the RSI makes a lower high.
4. Set Alerts:
Use the "Regular Bullish Divergence" and "Regular Bearish Divergence" alert conditions to be notified when a divergence is detected.
Notes
The indicator does not provide direct buy/sell signals. Use the RSI levels, moving averages, and divergence signals as part of a broader trading strategy.
Divergence detection requires the "Calculate Divergence" option to be enabled and may not work on all timeframes or assets due to market noise.
The Bollinger Bands are only visible when "SMA + Bollinger Bands" is selected as the smoothing type.
Credits
Developed by Marrulk. Enjoy trading with RSI - 5UP! 🚀
Advanced Volatility-Adjusted Momentum IndexAdvanced Volatility-Adjusted Momentum Index (AVAMI)
The AVAMI is a powerful and versatile trading index which enhances the traditional momentum readings by introducing a volatility adjustment. This results in a more nuanced interpretation of market momentum, considering not only the rate of price changes but also the inherent volatility of the asset.
Settings and Parameters:
Momentum Length: This parameter sets the number of periods used to calculate the momentum, which is essentially the rate of change of the asset's price. A shorter length value means the momentum calculation will be more sensitive to recent price changes. Conversely, a longer length will yield a smoother and more stabilized momentum value, thereby reducing the impact of short-term price fluctuations.
Volatility Length: This parameter is responsible for determining the number of periods to be considered in the calculation of standard deviation of returns, which acts as the volatility measure. A shorter length will result in a more reactive volatility measure, while a longer length will produce a more stable, but less sensitive measure of volatility.
Smoothing Length: This parameter sets the number of periods used to apply a moving average smoothing to the AVAMI and its signal line. The purpose of this is to minimize the impact of volatile periods and to make the indicator's lines smoother and easier to interpret.
Lookback Period for Scaling: This is the number of periods used when rescaling the AVAMI values. The rescaling process is necessary to ensure that the AVAMI values remain within a consistent and interpretable range over time.
Overbought and Oversold Levels: These levels are thresholds at which the asset is considered overbought (potentially overvalued) or oversold (potentially undervalued), respectively. For instance, if the AVAMI exceeds the overbought level, traders may consider it as a possible selling opportunity, anticipating a price correction. Conversely, if the AVAMI falls below the oversold level, it could be seen as a buying opportunity, with the expectation of a price bounce.
Mid Level: This level represents the middle ground between the overbought and oversold levels. Crossing the mid-level line from below can be perceived as an increasing bullish momentum, and vice versa.
Show Divergences and Hidden Divergences: These checkboxes give traders the option to display regular and hidden divergences between the AVAMI and the asset's price. Divergences are crucial market structures that often signal potential price reversals.
Index Logic:
The AVAMI index begins with the calculation of a simple rate of change momentum indicator. This raw momentum is then adjusted by the standard deviation of log returns, which acts as a measure of market volatility. This adjustment process ensures that the resulting momentum index encapsulates not only the speed of price changes but also the market's volatility context.
The raw AVAMI is then smoothed using a moving average, and a signal line is generated as an exponential moving average (EMA) of this smoothed AVAMI. This signal line serves as a trigger for potential trading signals when crossed by the AVAMI.
The script also includes an algorithm to identify 'fractals', which are distinct price patterns that often act as potential market reversal points. These fractals are utilized to spot both regular and hidden divergences between the asset's price and the AVAMI.
Application and Strategy Concepts:
The AVAMI is a versatile tool that can be integrated into various trading strategies. Traders can utilize the overbought and oversold levels to identify potential reversal points. The AVAMI crossing the mid-level line can signify a change in market momentum. Additionally, the identification of regular and hidden divergences can serve as potential trading signals:
Regular Divergence: This happens when the asset's price records a new high/low, but the AVAMI fails to follow suit, suggesting a possible trend reversal. For instance, if the asset's price forms a higher high but the AVAMI forms a lower high, it's a regular bearish divergence, indicating potential price downturn.
Hidden Divergence: This is observed when the price forms a lower high/higher low, but the AVAMI forms a higher high/lower low, suggesting the continuation of the prevailing trend. For example, if the price forms a lower low during a downtrend, but the AVAMI forms a higher low, it's a hidden bullish divergence, signaling the potential continuation of the downtrend.
As with any trading tool, the AVAMI should not be used in isolation but in conjunction with other technical analysis tools and within the context of a well-defined trading plan.
CryptoverseThis Indicator dynamically generates and charts Pivot Points, Support and Resistance Lines, Trend Channels and even Rsi Divergences in every market and every time period.
While it helps you identify your entry points, stop loss and take positions, it certainly does not include trading signals and trading strategy.
Bonus: the indicator contains ema21, ema50, ema100 and ema200 to support the lines created. If you wish, you can change the EMA values in the settings.
Recommendation: RSI is included in the indicator codes in order to detect divergences dataally, but it is not displayed on the chart. I recommend adding an additional RSI indicator to keep track of past and current potential divergences.
USER MANUAL:
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General Settings:
Pivot Period: This field determines how many candles before and after a candle should be controlled in order to be able to determine the top and bottom points on the chart.
Support and Resistance Lines and Trend Channels formed on the chart are created by calculating the Pivot points formed according to the period determined here. (Default value: 6)
Pivot Source: Determines the pivot points to be created according to the value of the relevant candle.
(Default and Recommended: closing)
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Support And Resistance Settings:
Custom Bars Back: This area allows you to specify how many pivot points from the current candle to the previous candle to create support resistance lines on the Chart. The default value is the last 500 candles.
*Note: The more old candles are checked, the more support and resistance lines will appear. This may prevent you from making sound determinations on the chart.*
Current Bar Decrease: This field works integrated with Custom Bars Back. By subtracting the current candle by the specified number, it provides the formation of lines without including those candles.
Default value: It is set to 0 to include current data.
Example: If Custom Bars Back: 500 and Current Bar Decrease: 10, Support and Resistance lines are created by considering 500 candles before the last 10 candles without including the last 10 candles on the chart.
Show S/R Lines: This field allows you to show or hide the Support and Resistance lines at any time.
Auto Simplification: This field is marked by default. It allows the Simplification Steps value to be determined automatically within the code according to the time period and current volatility of the relevant parity. (It is recommended to use the default version.)
Simplification Steps: This field allows you to get more understandable lines by simplifying the Support and Resistance lines based on Pivot points. If a simplification is not done, the lines to be formed with only the pivot points will be too many and this creates a dirty and useless appearance on the chart.
Each 1 digit you enter as a step combines the lines that are close to each other at a value of 0.01% and creates a common line.
Example: If you enter the number 10 as Steps, it will form a single common line from lines close together, starting at 0.01% respectively. It will continue to increase by 0.02%, 0.03%, 0.04% in its next steps. For the number 10, it will complete its loop by combining lines within the last remaining lines that are as close as 0.1% to each other and creating new lines from their midpoints.
The deafult value is 14. (Max. simplifies lines with closeness up to 1.4%.)
Important Note: If Auto Simplification is on, the entered value has no meaning. The Indicator performs simplification operations automatically. If you want to manage these steps manually, you can turn off Auto Simplification and enter your own value.
S/R Lines Color: Allows you to specify the color of the lines.
Label Location: Allows you to determine how many candles ahead the information label formed for each line will be positioned.
Line Label Descriptions:
Line: It is the price value that the line coincides with.*
Distance: Shows the percentage distance of the line from the current price.
▲ : Shows the percentage distance from the line above it.
▼ : Shows the percentage distance from the line below it.
Strength: Indicates the total number of steps the process has taken during the simplification process. The height of the number indicates the strength of resistance and support in the close price range.
C. Width: stands for Channel Width. It shows the percentage value between the highest price and the lowest price on the past candle as many candles specified by Custom Bars Back.
S. Steps: stands for Simplification Steps. Indicates the number of simplification steps applied. A value of 150 in the image indicates that a 1.5% simplification range has been applied.
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Trend Channels Settings:
Show All Trend Lines: Allows you to show and hide trend channels.
Hide Old Trend Lines: If you enable it, it will hide channels created in the past except for Current Trend channels.
Helper Line Format: Allows the auxiliary line that converts a trendline to a channel to be drawn based on percentage or price.
Note: There may be cases where the auxiliary lines do not provide full parallelism when using large time intervals by preferring a percentage.
Up Trend Color: Indicates the color of the Up Trend channel.
Down Trend Color: Specifies the color of the Downtrend channel.
Show Up Trend Overflow, Show Down Trend Overflow:
When the price closes above or below the trend channels, it provides awareness with the help of a text on the chart. Colors can be adjusted according to preference.
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RSI Divergences Settings:
This indicator gives you information about 4 different divergences. You can customize the divergence views with the show and hide options.
Bullish Regular, Bullish Hidden, Bearish Regular and Bearish Hidden.
Green divergences from the bottom of the graph represent bullish, and red divergences above the graph represent bearish.
Important note: Seeing a mismatch label definitely indicates that there is a mismatch between prices and rsi, but a mismatch does not always indicate a change in price.
Potential Divergence:
The indicator not only shows you past divergences, but also informs you of potential divergences based on the current status of the chart.
A potential divergence may not turn into a true one if the price flow continues to increase or decrease in the same direction. But all divergences seen in the past must have been shown as potential divergences beforehand.
Rsi Length, Rsi Source: Allows you to change settings for RSI values typically embedded within the indicator.
Note: Pivot Source and RSI Source using the same type of candle data ensures that divergences are displayed correctly.
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EMA Settings:
The indicator allows you to use 4 different EMA data in addition to Support and Resistance lines, Trend Channels and RSI divergences. By default, 21, 50, 100 and 200 are used. You can change the EMA values and colors in the Settings section, or you can use the show hide options in the Style section.
Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI)
What is Lyapunov Market Instability?
Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes.
Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth.
Theoretical Foundation (Chaos Theory & Lyapunov Exponents)
In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories:
λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect)
λ < 0: System is stable—trajectories converge, perturbations die out
λ ≈ 0: Edge of chaos—transition between regimes
Phase Space Reconstruction
Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions:
Time-delay embedding: Create vectors from price at different lags
Nearest neighbor search: Find historically similar market states
Trajectory evolution: Track how these similar states diverged over time
Divergence rate: Calculate average exponential separation
Market Application
Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies
Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work
Transition zones: Market regime about to change, reduce position size, wait for confirmation
How LMI Works
1. Phase Space Construction
Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure.
2. Lyapunov Calculation
For each current state, we:
- Find similar historical states within epsilon (ε) distance
- Track how these initially similar states evolved
- Measure exponential divergence rate
- Average across multiple trajectories for robustness
3. Signal Generation
Chaos signals: When λ crosses above threshold, market enters trending regime
Stability signals: When λ crosses below threshold, market enters ranging regime
Divergence detection: Price/Lyapunov divergences signal potential reversals
4. Rothko Visualization
Color fields: Background zones represent market states with Rothko-inspired palettes
Glowing line: Lyapunov exponent with intensity reflecting market state
Minimalist design: Focus on essential information without clutter
Inputs:
📐 Lyapunov Parameters
Embedding Dimension (default: 3)
Dimensions for phase space reconstruction
2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns
4-5: Complex dynamics (stocks/indices) - captures intricate market structures
Higher dimensions need exponentially more data but reveal deeper patterns
Time Delay τ (default: 1)
Lag between phase space coordinates
1: High-frequency (1m-15m charts) - captures rapid market shifts
2-3: Medium frequency (1H-4H) - balances noise and signal
4-5: Low frequency (Daily+) - focuses on major regime changes
Match to your timeframe's natural cycle
Initial Separation ε (default: 0.001)
Neighborhood size for finding similar states
0.0001-0.0005: Highly liquid markets (major forex pairs)
0.0005-0.002: Normal markets (large-cap stocks)
0.002-0.01: Volatile markets (crypto, small-caps)
Smaller = more sensitive to chaos onset
Evolution Steps (default: 10)
How far to track trajectory divergence
5-10: Fast signals for scalping - quick regime detection
10-20: Balanced for day trading - reliable signals
20-30: Slow signals for swing trading - major regime shifts only
Nearest Neighbors (default: 5)
Phase space points for averaging
3-4: Noisy/fast markets - adapts quickly
5-6: Balanced (recommended) - smooth yet responsive
7-10: Smooth/slow markets - very stable signals
📊 Signal Parameters
Chaos Threshold (default: 0.05)
Lyapunov value above which market is chaotic
0.01-0.03: Sensitive - more chaos signals, earlier detection
0.05: Balanced - optimal for most markets
0.1-0.2: Conservative - only strong trends trigger
Stability Threshold (default: -0.05)
Lyapunov value below which market is stable
-0.01 to -0.03: Sensitive - quick stability detection
-0.05: Balanced - reliable ranging signals
-0.1 to -0.2: Conservative - only deep stability
Signal Smoothing (default: 3)
EMA period for noise reduction
1-2: Raw signals for experienced traders
3-5: Balanced - recommended for most
6-10: Very smooth for position traders
🎨 Rothko Visualization
Rothko Classic: Deep reds for chaos, midnight blues for stability
Orange/Red: Warm sunset tones throughout
Blue/Black: Cool, meditative ocean depths
Purple/Grey: Subtle, sophisticated palette
Visual Options:
Market Zones : Background fields showing regime areas
Transitions: Arrows marking regime changes
Divergences: Labels for price/Lyapunov divergences
Dashboard: Real-time state and trading signals
Guide: Educational panel explaining the theory
Visual Logic & Interpretation
Main Elements
Lyapunov Line: The heart of the indicator
Above chaos threshold: Market is trending, follow momentum
Below stability threshold: Market is ranging, fade extremes
Between thresholds: Transition zone, reduce risk
Background Zones: Rothko-inspired color fields
Red zone: Chaotic regime (trending)
Gray zone: Transition (uncertain)
Blue zone: Stable regime (ranging)
Transition Markers:
Up triangle: Entering chaos - start trend following
Down triangle: Entering stability - start mean reversion
Divergence Signals:
Bullish: Price makes low but Lyapunov rising (stability breaking down)
Bearish: Price makes high but Lyapunov falling (chaos dissipating)
Dashboard Information
Market State: Current regime (Chaotic/Stable/Transitioning)
Trading Bias: Specific strategy recommendation
Lyapunov λ: Raw value for precision
Signal Strength: Confidence in current regime
Last Change: Bars since last regime shift
Action: Clear trading directive
Trading Strategies
In Chaotic Regime (λ > threshold)
Follow trends aggressively: Breakouts have high success rate
Use momentum strategies: Moving average crossovers work well
Wider stops: Expect larger swings
Pyramid into winners: Trends tend to persist
In Stable Regime (λ < threshold)
Fade extremes: Mean reversion dominates
Use oscillators: RSI, Stochastic work well
Tighter stops: Smaller expected moves
Scale out at targets: Trends don't persist
In Transition Zone
Reduce position size: Uncertainty is high
Wait for confirmation: Let regime establish
Use options: Volatility strategies may work
Monitor closely: Quick changes possible
Advanced Techniques
- Multi-Timeframe Analysis
- Higher timeframe LMI for regime context
- Lower timeframe for entry timing
- Alignment = highest probability trades
- Divergence Trading
- Most powerful at regime boundaries
- Combine with support/resistance
- Use for early reversal detection
- Volatility Correlation
- Chaos often precedes volatility expansion
- Stability often precedes volatility contraction
- Use for options strategies
Originality & Innovation
LMI represents a genuine breakthrough in applying chaos theory to markets:
True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement
Rothko Aesthetic: Transforms complex math into meditative visual experience
Regime Detection: Identifies market state changes before price makes them obvious
Practical Application: Clear, actionable signals from theoretical physics
This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics.
Best Practices
Start with defaults: Parameters are optimized for broad market conditions
Match to your timeframe: Adjust tau and evolution steps
Confirm with price action: LMI shows regime, not direction
Use appropriate strategies: Chaos = trend, Stability = reversion
Respect transitions: Reduce risk during regime changes
Alerts Available
Chaos Entry: Market entering chaotic regime - prepare for trends
Stability Entry: Market entering stable regime - prepare for ranges
Bullish Divergence: Potential bottom forming
Bearish Divergence: Potential top forming
Chart Information
Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes
Academic References
Takens, F. (1981). "Detecting strange attractors in turbulence"
Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series"
Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents"
Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering.
Disclaimer
This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of chaos. Trade the regime, not the noise.
Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
MACD with Holt–Winters Smoothing [AIBitcoinTrend]👽 MACD with Holt–Winters Smoothing (AIBitcoinTrend)
The MACD with Holt–Winters Smoothing is an momentum indicator that enhances traditional MACD analysis by incorporating Holt–Winters exponential smoothing. This adaptation reduces lag while maintaining trend sensitivity, making it more effective for detecting trend reversals and sustained momentum shifts. Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, helping traders manage risk dynamically.
👽 What Makes the MACD with Holt–Winters Smoothing Unique?
Unlike the standard MACD, which relies on simple exponential moving averages, this version applies Holt–Winters smoothing to better capture trends while filtering out market noise. Combined with real-time divergence detection and a trailing stop system, this indicator allows traders to:
✅ Identify trend strength with a dynamically smoothed MACD signal.
✅ Detect bullish and bearish divergences in real time.
✅Implement Crossover/Crossunder signals tied to ATR-based trailing stops for risk management
👽 The Math Behind the Indicator
👾 Holt–Winters Smoothing for MACD
Traditional MACD calculations use exponential moving averages (EMA) to identify momentum. This indicator improves upon it by applying Holt’s linear trend equations, which enhance signal accuracy by reducing lag and smoothing out fluctuations.
Key Features:
Alpha (α) - Controls the weight of the new data in smoothing.
Beta (β) - Determines how fast the trend component adapts to new changes.
The Holt–Winters Signal Line provides a refined MACD crossover system for better trade execution.
👾 Real-Time Divergence Detection
The indicator identifies bullish and bearish divergences between MACD and price action.
Bullish Divergence: Occurs when price makes a lower low, but MACD makes a higher low – signaling potential upward momentum.
Bearish Divergence: Occurs when price makes a higher high, but MACD makes a lower high – signaling potential downward momentum.
👾 Dynamic ATR-Based Trailing Stop
The indicator includes a trailing stop system based on ATR (Average True Range). This allows traders to manage positions dynamically based on volatility.
Bullish Trailing Stop: Triggers when MACD crosses above the Holt–Winters signal, with a stop placed at low - (ATR × Multiplier).
Bearish Trailing Stop: Triggers when MACD crosses below the Holt–Winters signal, with a stop placed at high + (ATR × Multiplier).
Trailing Stop Adjustments: Expands or contracts dynamically with market conditions, reducing premature exits while securing profits.
👽 How Traders Can Use This Indicator
👾 Divergence Trading
Traders can use real-time divergence detection to anticipate trend reversals before they occur.
Bullish Divergence Setup:
Look for MACD making a higher low, while price makes a lower low.
Enter long when MACD confirms upward momentum.
Bearish Divergence Setup:
Look for MACD making a lower high, while price makes a higher high.
Enter short when MACD confirms downward momentum.
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅ MACD crosses above the Holt–Winters signal.
✅ A bullish trailing stop is placed using low - ATR × Multiplier.
✅ Exit if the price crosses below the stop.
Bearish Setup:
✅ MACD crosses below the Holt–Winters signal.
✅ A bearish trailing stop is placed using high + ATR × Multiplier.
✅ Exit if the price crosses above the stop.
This systematic trade management approach helps traders lock in profits while reducing drawdowns.
👽 Why It’s Useful for Traders
Lag Reduction: Holt–Winters smoothing ensures faster and more reliable trend detection.
Real-Time Divergence Alerts: Identify potential reversals before they happen.
Adaptive Risk Management: ATR-based trailing stops adjust to volatility dynamically.
Works Across Markets & Timeframes: Effective for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
MACD Fast & Slow Lengths: Adjust the MACD short- and long-term EMA periods.
Holt–Winters Alpha & Beta: Fine-tune the smoothing sensitivity.
Enable Divergence Detection: Toggle real-time divergence analysis.
Lookback Period for Divergences: Configure how far back pivot points are detected.
ATR Multiplier for Trailing Stops: Adjust stop-loss sensitivity to market volatility.
Trend Filtering: Enable signal filtering based on trend direction.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Enhanced RSIEnhanced RSI with Phases, Divergences & Volume Control:
This advanced RSI indicator expands on the traditional Relative Strength Index by introducing dynamic exhaustion phase detection, automatic divergence identification, and volume-based control evaluation. It provides traders with actionable insights into trend momentum, potential reversals, and market dominance.
Key Features:
Dynamic Exhaustion Phases:
Identifies real phases of the RSI based on slope and momentum:
Acceleration: Momentum increasing rapidly (green phase).
Deceleration: Momentum weakening (red phase).
Plateau: Momentum flattening (yellow phase).
Neutral: No significant momentum shift detected.
Phases are displayed dynamically in a box on the chart.
Automatic Divergence Detection:
Bullish Divergence: Identified when price makes a lower low while RSI makes a higher low.
Bearish Divergence: Identified when price makes a higher high while RSI makes a lower high.
Divergences are marked directly on the RSI chart with labeled circles.
Volume-Based Control Evaluation:
Analyzes price action relative to volume to determine market dominance:
Bulls in Control: Closing price is higher than the opening price.
Bears in Control: Closing price is lower than the opening price.
Neutral: No significant dominance (closing equals opening).
Volume status is displayed alongside the RSI phase in the chart’s top-left box.
Custom RSI Plot:
Includes overbought (70), oversold (30), and neutral (50) levels for easier interpretation of market conditions.
RSI plotted in blue for clarity.
How to Use:
Add to Chart:
Apply this indicator to any chart in TradingView.
Interpret the RSI Phase Box:
Use the RSI phase (Acceleration, Deceleration, Plateau, Neutral) to identify trend momentum.
Combine the phase with the volume status (Bulls or Bears in Control) to confirm market sentiment.
Identify Divergences:
Look for Bullish Divergence (potential upward reversal) or Bearish Divergence (potential downward reversal) marked directly on the RSI chart.
Adjust Settings:
Customize the RSI period, phase sensitivity, and divergence lookback period to fit your trading style.
Disclaimer:
This indicator is a tool to assist with technical analysis. It is not a financial advice or a guarantee of market performance. Always combine this indicator with other methods or strategies for better results.
GMO (Gyroscopic Momentum Oscillator) GMO
Overview
This indicator fuses multiple advanced concepts to give traders a comprehensive view of market momentum, volatility, and potential turning points. It leverages the Gyroscopic Momentum Oscillator (GMO) foundation and layers on IQR-based bands, dynamic ATR-adjusted OB/OS levels, torque filtering, and divergence detection. The outcome is a versatile tool that can assist in identifying both short-term squeezes and long-term reversal zones while detecting subtle shifts in momentum acceleration.
Key Components:
Gyroscopic Momentum Oscillator (GMO) – A physics-inspired metric capturing trend stability and momentum by treating price dynamics as “angle,” “angular velocity,” and “inertia.”
IQR Bands – Highlight statistically typical oscillation ranges, providing insight into short-term squeezes and potential near-term trend shifts.
ATR-Adjusted OB/OS Levels – Dynamic thresholds for overbought/oversold conditions, adapting to volatility, aiding in identifying long-term potential reversal zones.
Torque Filtering & Scaling – Smooths and thresholds torque (the rate of change of momentum) and visually scales it for clarity, indicating sudden force changes that may precede volatility adjustments.
Divergence Detection – Highlights potential reversal cues by comparing oscillator swings against price swings, revealing regular and hidden bullish/bearish divergences.
Conceptual Insights
IQR Bands (Short-Term Squeeze & Trend Direction):
Short-Term Momentum and Squeeze: The IQR (Interquartile Range) bands show where the oscillator tends to “live” statistically. When the GMO line hovers within compressed IQR bands, it can signal a momentum squeeze phase. Exiting these tight ranges often correlates with short-term breakout opportunities.
Trend Reversals: If the oscillator pushes beyond these IQR ranges, it may indicate an emerging short-term trend change. Traders can watch for GMO escaping the IQR “comfort zone” to anticipate a new directional move.
Dynamic OB/OS Levels (Long-Term Reversal Zones):
ATR-Based Adaptive Thresholds: Instead of static overbought/oversold lines, this tool uses ATR to adjust OB/OS boundaries. In calm markets, these lines remain closer to ±90. As volatility rises, they approach ±100, reflecting greater permissible swings.
Long-Term Trend Reversal Potential: If GMO hits these dynamically adjusted OB/OS extremes, it suggests conditions ripe for possible long-term trend reversals. Traders seeking major inflection points may find these adaptive levels more reliable than fixed thresholds.
Torque (Sudden Force & Directional Shifts):
Momentum Acceleration Insight: Torque represents the second derivative of momentum, highlighting how quickly momentum is changing. High positive torque suggests a rapidly strengthening bullish force, while high negative torque warns of sudden bearish pressure.
Early Warning & Stability/Volatility Adjustments: By monitoring torque spikes, traders can anticipate momentum shifts before price fully confirms them. This can signal imminent changes in stability or increased volatility phases.
Indicator Parameters and Usage
GMO-Related Inputs:
lenPivot (Default 100): Length for calculating the pivot line (slow market axis).
lenSmoothAngle (Default 200): Smooths the angle measure, reducing noise.
lenATR (Default 14): ATR period for scaling factor, linking price changes to volatility.
useVolatility (Default true): If true, volatility (ATR) influences inertia, adjusting momentum calculations.
useVolume (Default false): If true, volume affects inertia, adding a liquidity dimension to momentum.
lenVolSmoothing (Default 50): Smooths volume calculations if useVolume is enabled.
lenMomentumSmooth (Default 20): EMA smoothing of GMO for a cleaner oscillator line.
normalizeRange (Default true): Normalizes GMO to a fixed range for consistent interpretation.
lenNorm (Default 100): Length for normalization window, ensuring GMO’s scale adapts to recent extremes.
IQR Bands Settings:
iqrLength (Default 14): Period to compute the oscillator’s statistical IQR.
iqrMult (Default 1.5): Multiplier to define the upper and lower IQR-based bands.
ATR-Adjusted OB/OS Settings:
baseOBLevel (Fixed at 90) and baseOSLevel (Fixed at 90): Base lines for OB/OS.
atrPeriodForOBOS (Default 50): ATR length for adjusting OB/OS thresholds dynamically.
atrScaling (Default 0.2): Controls how strongly volatility affects OB/OS lines.
Torque Filtering & Visualization:
torqueSmoothLength (Default 10): EMA length to smooth raw torque values.
atrPeriodForTorque (Default 14): ATR period to determine torque threshold.
atrTorqueScaling (Default 0.5): Scales ATR for determining torque’s “significant” threshold.
torqueScaleFactor (Default 10.0): Multiplies the torque values for better visual prominence on the chart.
Divergence Inputs:
showDivergences (Default true): Toggles divergence signals.
lbR, lbL (Defaults 5): Pivot lookback periods to identify swing highs and lows.
rangeUpper, rangeLower: Bar constraints to validate potential divergences.
plotBull, plotHiddenBull, plotBear, plotHiddenBear: Toggles for each divergence type.
Visual Elements on the Chart
GMO Line (Blue) & Zero Line (Gray):
GMO line oscillates around zero. Positive territory hints bullish momentum, negative suggests bearish.
IQR Bands (Teal Lines & Yellow Fill):
Upper/lower bands form a statistical “normal range” for GMO. The median line (purple) provides a central reference. Contraction near these bands indicates a short-term squeeze, expansions beyond them can signal emerging short-term trend changes.
Dynamic OB/OS (Red & Green Lines):
Red line near +90 to +100: Overbought zone (dynamic).
Green line near -90 to -100: Oversold zone (dynamic).
Movement into these zones may mark significant, longer-term reversal potential.
Torque Histogram (Colored Bars):
Plotted below GMO. Green bars = torque above positive threshold (bullish acceleration).
Red bars = torque below negative threshold (bearish acceleration).
Gray bars = neutral range.
This provides early warnings of momentum shifts before price responds fully.
Precession (Orange Line):
Scaled for visibility, adds context to long-term angular shifts in the oscillator.
Divergence Signals (Shapes):
Circles and offset lines highlight regular or hidden bullish/bearish divergences, offering potential reversal signals.
Practical Interpretation & Strategy
Short-Term Opportunities (IQR Focus):
If GMO compresses within IQR bands, the market might be “winding up.” A break above/below these bands can signal a short-term trade opportunity.
Long-Term Reversal Zones (Dynamic OB/OS):
When GMO approaches these dynamically adjusted extremes, conditions may be ripe for a major trend shift. This is particularly useful for swing or position traders looking for significant turnarounds.
Monitoring Torque for Acceleration Cues:
Torque spikes can precede price action, serving as an early catalyst signal. If torque turns strongly positive, anticipate bullish acceleration; strongly negative torque may warn of upcoming bearish pressure.
Confirm with Divergences:
Divergences between price and GMO reinforce potential reversal or continuation signals identified by IQR, OB/OS, or torque. Use them to increase confidence in setups.
Tips and Best Practices
Combine with Price & Volume Action:
While the indicator is powerful, always confirm signals with actual price structure, volume patterns, or other trend-following tools.
Adjust Lengths & Periods as Needed:
Shorter lengths = more responsiveness but more noise. Longer lengths = smoother signals but greater lag. Tune parameters to match your trading style and timeframe.
Use ATR and Volume Settings Wisely:
If markets are highly volatile, consider useVolatility to refine momentum readings. If liquidity is key, enable useVolume.
Scaling Torque:
If torque bars are hard to read, increase torqueScaleFactor further. The scaling doesn’t affect logic—only visibility.
Conclusion
The “GMO + IQR Bands + ATR-Adjusted OB/OS + Torque Filtering (Scaled)” indicator presents a holistic framework for understanding market momentum across multiple timescales and conditions. By interpreting short-term squeezes via IQR bands, long-term reversal zones via adaptive OB/OS, and subtle acceleration changes through torque, traders can gain advanced insights into when to anticipate breakouts, manage risk around potential reversals, and fine-tune timing for entries and exits.
This integrated approach helps navigate complex market dynamics, making it a valuable addition to any technical analysis toolkit.
RSI Mansfield +An adaptive relative strength indicator for any market and timeframe.
OVERVIEW
This indicator plots the Mansfield Relative Strength (RSI Mansfield) oscillator, a tool to compare the performance of your instrument against a chosen benchmark index or asset. It auto-adjusts to cryptocurrencies, stocks, and various timeframes, applying the appropriate smoothing techniques to reveal true relative strength or weakness.
CONCEPTS
Relative Strength: Measures how the price of your asset evolves compared to a benchmark (e.g., BTC dominance, S&P 500).
Mansfield Normalization: Expresses the deviation from the moving average of the ratio between your asset and the benchmark, scaled to highlight trends.
Adaptive Smoothing: Automatically selects EMA or SMA smoothing depending on market type and timeframe.
Divergences: Detects regular and hidden bullish or bearish divergences in the Mansfield oscillator, which can signal potential reversals.
FEATURES
Supports major global stock indices and crypto benchmarks.
Auto-selection of moving average length (daily, weekly, monthly).
Dynamic coloring: green for positive relative strength, red for negative.
Configurable detection of four divergence types:
Regular Bullish Divergence
Hidden Bullish Divergence
Regular Bearish Divergence
Hidden Bearish Divergence
Toggle switch to show/hide divergences.
Clear zero baseline reference.
USAGE
Benchmark Selection
Choose the benchmark index or asset you want to compare against, e.g., Bitcoin Dominance, S&P 500, or other regional indices.
Interpret Colors
Green oscillator: outperforming the benchmark.
Red oscillator: underperforming.
Analyze Divergences
Enable divergence detection to spot potential reversal points. Regular divergences indicate classical divergence; hidden divergences may confirm continuation.
Timeframes
Works on intraday, daily, weekly, or monthly charts. The indicator auto-adjusts smoothing and calculation length accordingly.
Trend Gauge [BullByte]Trend Gauge
Summary
A multi-factor trend detection indicator that aggregates EMA alignment, VWMA momentum scaling, volume spikes, ATR breakout strength, higher-timeframe confirmation, ADX-based regime filtering, and RSI pivot-divergence penalty into one normalized trend score. It also provides a confidence meter, a Δ Score momentum histogram, divergence highlights, and a compact, scalable dashboard for at-a-glance status.
________________________________________
## 1. Purpose of the Indicator
Why this was built
Traders often monitor several indicators in parallel - EMAs, volume signals, volatility breakouts, higher-timeframe trends, ADX readings, divergence alerts, etc., which can be cumbersome and sometimes contradictory. The “Trend Gauge” indicator was created to consolidate these complementary checks into a single, normalized score that reflects the prevailing market bias (bullish, bearish, or neutral) and its strength. By combining multiple inputs with an adaptive regime filter, scaling contributions by magnitude, and penalizing weakening signals (divergence), this tool aims to reduce noise, highlight genuine trend opportunities, and warn when momentum fades.
Key Design Goals
Signal Aggregation
Merged trend-following signals (EMA crossover, ATR breakout, higher-timeframe confirmation) and momentum signals (VWMA thrust, volume spikes) into a unified score that reflects directional bias more holistically.
Market Regime Awareness
Implemented an ADX-style filter to distinguish between trending and ranging markets, reducing the influence of trend signals during sideways phases to avoid false breakouts.
Magnitude-Based Scaling
Replaced binary contributions with scaled inputs: VWMA thrust and ATR breakout are weighted relative to recent averages, allowing for more nuanced score adjustments based on signal strength.
Momentum Divergence Penalty
Integrated pivot-based RSI divergence detection to slightly reduce the overall score when early signs of momentum weakening are detected, improving risk-awareness in entries.
Confidence Transparency
Added a live confidence metric that shows what percentage of enabled sub-indicators currently agree with the overall bias, making the scoring system more interpretable.
Momentum Acceleration Visualization
Plotted the change in score (Δ Score) as a histogram bar-to-bar, highlighting whether momentum is increasing, flattening, or reversing, aiding in more timely decision-making.
Compact Informational Dashboard
Presented a clean, scalable dashboard that displays each component’s status, the final score, confidence %, detected regime (Trending/Ranging), and a labeled strength gauge for quick visual assessment.
________________________________________
## 2. Why a Trader Should Use It
Main benefits and use cases
1. Unified View: Rather than juggling multiple windows or panels, this indicator delivers a single score synthesizing diverse signals.
2. Regime Filtering: In ranging markets, trend signals often generate false entries. The ADX-based regime filter automatically down-weights trend-following components, helping you avoid chasing false breakouts.
3. Nuanced Momentum & Volatility: VWMA and ATR breakout contributions are normalized by recent averages, so strong moves register strongly while smaller fluctuations are de-emphasized.
4. Early Warning of Weakening: Pivot-based RSI divergence is detected and used to slightly reduce the score when price/momentum diverges, giving a cautionary signal before a full reversal.
5. Confidence Meter: See at a glance how many sub-indicators align with the aggregated bias (e.g., “80% confidence” means 4 out of 5 components agree ). This transparency avoids black-box decisions.
6. Trend Acceleration/Deceleration View: The Δ Score histogram visualizes whether the aggregated score is rising (accelerating trend) or falling (momentum fading), supplementing the main oscillator.
7. Compact Dashboard: A corner table lists each check’s status (“Bull”, “Bear”, “Flat” or “Disabled”), plus overall Score, Confidence %, Regime, Trend Strength label, and a gauge bar. Users can scale text size (Normal, Small, Tiny) without removing elements, so the full picture remains visible even in compact layouts.
8. Customizable & Transparent: All components can be enabled/disabled and parameterized (lengths, thresholds, weights). The full Pine code is open and well-commented, letting users inspect or adapt the logic.
9. Alert-ready: Built-in alert conditions fire when the score crosses weak thresholds to bullish/bearish or returns to neutral, enabling timely notifications.
________________________________________
## 3. Component Rationale (“Why These Specific Indicators?”)
Each sub-component was chosen because it adds complementary information about trend or momentum:
1. EMA Cross
o Basic trend measure: compares a faster EMA vs. a slower EMA. Quickly reflects trend shifts but by itself can whipsaw in sideways markets.
2. VWMA Momentum
o Volume-weighted moving average change indicates momentum with volume context. By normalizing (dividing by a recent average absolute change), we capture the strength of momentum relative to recent history. This scaling prevents tiny moves from dominating and highlights genuinely strong momentum.
3. Volume Spikes
o Sudden jumps in volume combined with price movement often accompany stronger moves or reversals. A binary detection (+1 for bullish spike, -1 for bearish spike) flags high-conviction bars.
4. ATR Breakout
o Detects price breaking beyond recent highs/lows by a multiple of ATR. Measures breakout strength by how far beyond the threshold price moves relative to ATR, capped to avoid extreme outliers. This gives a volatility-contextual trend signal.
5. Higher-Timeframe EMA Alignment
o Confirms whether the shorter-term trend aligns with a higher timeframe trend. Uses request.security with lookahead_off to avoid future data. When multiple timeframes agree, confidence in direction increases.
6. ADX Regime Filter (Manual Calculation)
o Computes directional movement (+DM/–DM), smoothes via RMA, computes DI+ and DI–, then a DX and ADX-like value. If ADX ≥ threshold, market is “Trending” and trend components carry full weight; if ADX < threshold, “Ranging” mode applies a configurable weight multiplier (e.g., 0.5) to trend-based contributions, reducing false signals in sideways conditions. Volume spikes remain binary (optional behavior; can be adjusted if desired).
7. RSI Pivot-Divergence Penalty
o Uses ta.pivothigh / ta.pivotlow with a lookback to detect pivot highs/lows on price and corresponding RSI values. When price makes a higher high but RSI makes a lower high (bearish divergence), or price makes a lower low but RSI makes a higher low (bullish divergence), a divergence signal is set. Rather than flipping the trend outright, the indicator subtracts (or adds) a small penalty (configurable) from the aggregated score if it would weaken the current bias. This subtle adjustment warns of weakening momentum without overreacting to noise.
8. Confidence Meter
o Counts how many enabled components currently agree in direction with the aggregated score (i.e., component sign × score sign > 0). Displays this as a percentage. A high percentage indicates strong corroboration; a low percentage warns of mixed signals.
9. Δ Score Momentum View
o Plots the bar-to-bar change in the aggregated score (delta_score = score - score ) as a histogram. When positive, bars are drawn in green above zero; when negative, bars are drawn in red below zero. This reveals acceleration (rising Δ) or deceleration (falling Δ), supplementing the main oscillator.
10. Dashboard
• A table in the indicator pane’s top-right with 11 rows:
1. EMA Cross status
2. VWMA Momentum status
3. Volume Spike status
4. ATR Breakout status
5. Higher-Timeframe Trend status
6. Score (numeric)
7. Confidence %
8. Regime (“Trending” or “Ranging”)
9. Trend Strength label (e.g., “Weak Bullish Trend”, “Strong Bearish Trend”)
10. Gauge bar visually representing score magnitude
• All rows always present; size_opt (Normal, Small, Tiny) only changes text size via text_size, not which elements appear. This ensures full transparency.
________________________________________
## 4. What Makes This Indicator Stand Out
• Regime-Weighted Multi-Factor Score: Trend and momentum signals are adaptively weighted by market regime (trending vs. ranging) , reducing false signals.
• Magnitude Scaling: VWMA and ATR breakout contributions are normalized by recent average momentum or ATR, giving finer gradation compared to simple ±1.
• Integrated Divergence Penalty: Divergence directly adjusts the aggregated score rather than appearing as a separate subplot; this influences alerts and trend labeling in real time.
• Confidence Meter: Shows the percentage of sub-signals in agreement, providing transparency and preventing blind trust in a single metric.
• Δ Score Histogram Momentum View: A histogram highlights acceleration or deceleration of the aggregated trend score, helping detect shifts early.
• Flexible Dashboard: Always-visible component statuses and summary metrics in one place; text size scaling keeps the full picture available in cramped layouts.
• Lookahead-Safe HTF Confirmation: Uses lookahead_off so no future data is accessed from higher timeframes, avoiding repaint bias.
• Repaint Transparency: Divergence detection uses pivot functions that inherently confirm only after lookback bars; description documents this lag so users understand how and when divergence labels appear.
• Open-Source & Educational: Full, well-commented Pine v6 code is provided; users can learn from its structure: manual ADX computation, conditional plotting with series = show ? value : na, efficient use of table.new in barstate.islast, and grouped inputs with tooltips.
• Compliance-Conscious: All plots have descriptive titles; inputs use clear names; no unnamed generic “Plot” entries; manual ADX uses RMA; all request.security calls use lookahead_off. Code comments mention repaint behavior and limitations.
________________________________________
## 5. Recommended Timeframes & Tuning
• Any Timeframe: The indicator works on small (e.g., 1m) to large (daily, weekly) timeframes. However:
o On very low timeframes (<1m or tick charts), noise may produce frequent whipsaws. Consider increasing smoothing lengths, disabling certain components (e.g., volume spike if volume data noisy), or using a larger pivot lookback for divergence.
o On higher timeframes (daily, weekly), consider longer lookbacks for ATR breakout or divergence, and set Higher-Timeframe trend appropriately (e.g., 4H HTF when on 5 Min chart).
• Defaults & Experimentation: Default input values are chosen to be balanced for many liquid markets. Users should test with replay or historical analysis on their symbol/timeframe and adjust:
o ADX threshold (e.g., 20–30) based on instrument volatility.
o VWMA and ATR scaling lengths to match average volatility cycles.
o Pivot lookback for divergence: shorter for faster markets, longer for slower ones.
• Combining with Other Analysis: Use in conjunction with price action, support/resistance, candlestick patterns, order flow, or other tools as desired. The aggregated score and alerts can guide attention but should not be the sole decision-factor.
________________________________________
## 6. How Scoring and Logic Works (Step-by-Step)
1. Compute Sub-Scores
o EMA Cross: Evaluate fast EMA > slow EMA ? +1 : fast EMA < slow EMA ? -1 : 0.
o VWMA Momentum: Calculate vwma = ta.vwma(close, length), then vwma_mom = vwma - vwma . Normalize: divide by recent average absolute momentum (e.g., ta.sma(abs(vwma_mom), lookback)), clip to .
o Volume Spike: Compute vol_SMA = ta.sma(volume, len). If volume > vol_SMA * multiplier AND price moved up ≥ threshold%, assign +1; if moved down ≥ threshold%, assign -1; else 0.
o ATR Breakout: Determine recent high/low over lookback. If close > high + ATR*mult, compute distance = close - (high + ATR*mult), normalize by ATR, cap at a configured maximum. Assign positive contribution. Similarly for bearish breakout below low.
o Higher-Timeframe Trend: Use request.security(..., lookahead=barmerge.lookahead_off) to fetch HTF EMAs; assign +1 or -1 based on alignment.
2. ADX Regime Weighting
o Compute manual ADX: directional movements (+DM, –DM), smoothed via RMA, DI+ and DI–, then DX and ADX via RMA. If ADX ≥ threshold, market is considered “Trending”; otherwise “Ranging.”
o If trending, trend-based contributions (EMA, VWMA, ATR, HTF) use full weight = 1.0. If ranging, use weight = ranging_weight (e.g., 0.5) to down-weight them. Volume spike stays binary ±1 (optional to change if desired).
3. Aggregate Raw Score
o Sum weighted contributions of all enabled components. Count the number of enabled components; if zero, default count = 1 to avoid division by zero.
4. Divergence Penalty
o Detect pivot highs/lows on price and corresponding RSI values, using a lookback. When price and RSI diverge (bearish or bullish divergence), check if current raw score is in the opposing direction:
If bearish divergence (price higher high, RSI lower high) and raw score currently positive, subtract a penalty (e.g., 0.5).
If bullish divergence (price lower low, RSI higher low) and raw score currently negative, add a penalty.
o This reduces score magnitude to reflect weakening momentum, without flipping the trend outright.
5. Normalize and Smooth
o Normalized score = (raw_score / number_of_enabled_components) * 100. This yields a roughly range.
o Optional EMA smoothing of this normalized score to reduce noise.
6. Interpretation
o Sign: >0 = net bullish bias; <0 = net bearish bias; near zero = neutral.
o Magnitude Zones: Compare |score| to thresholds (Weak, Medium, Strong) to label trend strength (e.g., “Weak Bullish Trend”, “Medium Bearish Trend”, “Strong Bullish Trend”).
o Δ Score Histogram: The histogram bars from zero show change from previous bar’s score; positive bars indicate acceleration, negative bars indicate deceleration.
o Confidence: Percentage of sub-indicators aligned with the score’s sign.
o Regime: Indicates whether trend-based signals are fully weighted or down-weighted.
________________________________________
## 7. Oscillator Plot & Visualization: How to Read It
Main Score Line & Area
The oscillator plots the aggregated score as a line, with colored fill: green above zero for bullish area, red below zero for bearish area. Horizontal reference lines at ±Weak, ±Medium, and ±Strong thresholds mark zones: crossing above +Weak suggests beginning of bullish bias, above +Medium for moderate strength, above +Strong for strong trend; similarly for bearish below negative thresholds.
Δ Score Histogram
If enabled, a histogram shows score - score . When positive, bars appear in green above zero, indicating accelerating bullish momentum; when negative, bars appear in red below zero, indicating decelerating or reversing momentum. The height of each bar reflects the magnitude of change in the aggregated score from the prior bar.
Divergence Highlight Fill
If enabled, when a pivot-based divergence is confirmed:
• Bullish Divergence : fill the area below zero down to –Weak threshold in green, signaling potential reversal from bearish to bullish.
• Bearish Divergence : fill the area above zero up to +Weak threshold in red, signaling potential reversal from bullish to bearish.
These fills appear with a lag equal to pivot lookback (the number of bars needed to confirm the pivot). They do not repaint after confirmation, but users must understand this lag.
Trend Direction Label
When score crosses above or below the Weak threshold, a small label appears near the score line reading “Bullish” or “Bearish.” If the score returns within ±Weak, the label “Neutral” appears. This helps quickly identify shifts at the moment they occur.
Dashboard Panel
In the indicator pane’s top-right, a table shows:
1. EMA Cross status: “Bull”, “Bear”, “Flat”, or “Disabled”
2. VWMA Momentum status: similarly
3. Volume Spike status: “Bull”, “Bear”, “No”, or “Disabled”
4. ATR Breakout status: “Bull”, “Bear”, “No”, or “Disabled”
5. Higher-Timeframe Trend status: “Bull”, “Bear”, “Flat”, or “Disabled”
6. Score: numeric value (rounded)
7. Confidence: e.g., “80%” (colored: green for high, amber for medium, red for low)
8. Regime: “Trending” or “Ranging” (colored accordingly)
9. Trend Strength: textual label based on magnitude (e.g., “Medium Bullish Trend”)
10. Gauge: a bar of blocks representing |score|/100
All rows remain visible at all times; changing Dashboard Size only scales text size (Normal, Small, Tiny).
________________________________________
## 8. Example Usage (Illustrative Scenario)
Example: BTCUSD 5 Min
1. Setup: Add “Trend Gauge ” to your BTCUSD 5 Min chart. Defaults: EMAs (8/21), VWMA 14 with lookback 3, volume spike settings, ATR breakout 14/5, HTF = 5m (or adjust to 4H if preferred), ADX threshold 25, ranging weight 0.5, divergence RSI length 14 pivot lookback 5, penalty 0.5, smoothing length 3, thresholds Weak=20, Medium=50, Strong=80. Dashboard Size = Small.
2. Trend Onset: At some point, price breaks above recent high by ATR multiple, volume spikes upward, faster EMA crosses above slower EMA, HTF EMA also bullish, and ADX (manual) ≥ threshold → aggregated score rises above +20 (Weak threshold) into +Medium zone. Dashboard shows “Bull” for EMA, VWMA, Vol Spike, ATR, HTF; Score ~+60–+70; Confidence ~100%; Regime “Trending”; Trend Strength “Medium Bullish Trend”; Gauge ~6–7 blocks. Δ Score histogram bars are green and rising, indicating accelerating bullish momentum. Trader notes the alignment.
3. Divergence Warning: Later, price makes a slightly higher high but RSI fails to confirm (lower RSI high). Pivot lookback completes; the indicator highlights a bearish divergence fill above zero and subtracts a small penalty from the score, causing score to stall or retrace slightly. Dashboard still bullish but score dips toward +Weak. This warns the trader to tighten stops or take partial profits.
4. Trend Weakens: Score eventually crosses below +Weak back into neutral; a “Neutral” label appears, and a “Neutral Trend” alert fires if enabled. Trader exits or avoids new long entries. If score subsequently crosses below –Weak, a “Bearish” label and alert occur.
5. Customization: If the trader finds VWMA noise too frequent on this instrument, they may disable VWMA or increase lookback. If ATR breakouts are too rare, adjust ATR length or multiplier. If ADX threshold seems off, tune threshold. All these adjustments are explained in Inputs section.
6. Visualization: The screenshot shows the main score oscillator with colored areas, reference lines at ±20/50/80, Δ Score histogram bars below/above zero, divergence fill highlighting potential reversal, and the dashboard table in the top-right.
________________________________________
## 9. Inputs Explanation
A concise yet clear summary of inputs helps users understand and adjust:
1. General Settings
• Theme (Dark/Light): Choose background-appropriate colors for the indicator pane.
• Dashboard Size (Normal/Small/Tiny): Scales text size only; all dashboard elements remain visible.
2. Indicator Settings
• Enable EMA Cross: Toggle on/off basic EMA alignment check.
o Fast EMA Length and Slow EMA Length: Periods for EMAs.
• Enable VWMA Momentum: Toggle VWMA momentum check.
o VWMA Length: Period for VWMA.
o VWMA Momentum Lookback: Bars to compare VWMA to measure momentum.
• Enable Volume Spike: Toggle volume spike detection.
o Volume SMA Length: Period to compute average volume.
o Volume Spike Multiplier: How many times above average volume qualifies as spike.
o Min Price Move (%): Minimum percent change in price during spike to qualify as bullish or bearish.
• Enable ATR Breakout: Toggle ATR breakout detection.
o ATR Length: Period for ATR.
o Breakout Lookback: Bars to look back for recent highs/lows.
o ATR Multiplier: Multiplier for breakout threshold.
• Enable Higher Timeframe Trend: Toggle HTF EMA alignment.
o Higher Timeframe: E.g., “5” for 5-minute when on 1-minute chart, or “60” for 5 Min when on 15m, etc. Uses lookahead_off.
• Enable ADX Regime Filter: Toggles regime-based weighting.
o ADX Length: Period for manual ADX calculation.
o ADX Threshold: Value above which market considered trending.
o Ranging Weight Multiplier: Weight applied to trend components when ADX < threshold (e.g., 0.5).
• Scale VWMA Momentum: Toggle normalization of VWMA momentum magnitude.
o VWMA Mom Scale Lookback: Period for average absolute VWMA momentum.
• Scale ATR Breakout Strength: Toggle normalization of breakout distance by ATR.
o ATR Scale Cap: Maximum multiple of ATR used for breakout strength.
• Enable Price-RSI Divergence: Toggle divergence detection.
o RSI Length for Divergence: Period for RSI.
o Pivot Lookback for Divergence: Bars on each side to identify pivot high/low.
o Divergence Penalty: Amount to subtract/add to score when divergence detected (e.g., 0.5).
3. Score Settings
• Smooth Score: Toggle EMA smoothing of normalized score.
• Score Smoothing Length: Period for smoothing EMA.
• Weak Threshold: Absolute score value under which trend is considered weak or neutral.
• Medium Threshold: Score above Weak but below Medium is moderate.
• Strong Threshold: Score above this indicates strong trend.
4. Visualization Settings
• Show Δ Score Histogram: Toggle display of the bar-to-bar change in score as a histogram. Default true.
• Show Divergence Fill: Toggle background fill highlighting confirmed divergences. Default true.
Each input has a tooltip in the code.
________________________________________
## 10. Limitations, Repaint Notes, and Disclaimers
10.1. Repaint & Lag Considerations
• Pivot-Based Divergence Lag: The divergence detection uses ta.pivothigh / ta.pivotlow with a specified lookback. By design, a pivot is only confirmed after the lookback number of bars. As a result:
o Divergence labels or fills appear with a delay equal to the pivot lookback.
o Once the pivot is confirmed and the divergence is detected, the fill/label does not repaint thereafter, but you must understand and accept this lag.
o Users should not treat divergence highlights as predictive signals without additional confirmation, because they appear after the pivot has fully formed.
• Higher-Timeframe EMA Alignment: Uses request.security(..., lookahead=barmerge.lookahead_off), so no future data from the higher timeframe is used. This avoids lookahead bias and ensures signals are based only on completed higher-timeframe bars.
• No Future Data: All calculations are designed to avoid using future information. For example, manual ADX uses RMA on past data; security calls use lookahead_off.
10.2. Market & Noise Considerations
• In very choppy or low-liquidity markets, some components (e.g., volume spikes or VWMA momentum) may be noisy. Users can disable or adjust those components’ parameters.
• On extremely low timeframes, noise may dominate; consider smoothing lengths or disabling certain features.
• On very high timeframes, pivots and breakouts occur less frequently; adjust lookbacks accordingly to avoid sparse signals.
10.3. Not a Standalone Trading System
• This is an indicator, not a complete trading strategy. It provides signals and context but does not manage entries, exits, position sizing, or risk management.
• Users must combine it with their own analysis, money management, and confirmations (e.g., price patterns, support/resistance, fundamental context).
• No guarantees: past behavior does not guarantee future performance.
10.4. Disclaimers
• Educational Purposes Only: The script is provided as-is for educational and informational purposes. It does not constitute financial, investment, or trading advice.
• Use at Your Own Risk: Trading involves risk of loss. Users should thoroughly test and use proper risk management.
• No Guarantees: The author is not responsible for trading outcomes based on this indicator.
• License: Published under Mozilla Public License 2.0; code is open for viewing and modification under MPL terms.
________________________________________
## 11. Alerts
• The indicator defines three alert conditions:
1. Bullish Trend: when the aggregated score crosses above the Weak threshold.
2. Bearish Trend: when the score crosses below the negative Weak threshold.
3. Neutral Trend: when the score returns within ±Weak after being outside.
Good luck
– BullByte
Z Score 主图策略 — v1.02Hello Traders,
Here is my new year gift for the community, Digergence for Many Indicators v4. I tried to make it modular and readable as much as I can. Thanks to Pine Team for improving Pine Platform all the time!
How it works?
- On each candle it checks divergences between current and any of last 16 Pivot Points for the indicators.
- it search divergence on choisen indicators => RSI , MACD , MACD Histogram, Stochastic , CCI , Momentum, OBV, VWMACD, CMF and any External Indicator!
- it checks following divergences for 16 pivot points that is in last 100 bars for each Indicator.
--> Regular Positive Digergences
--> Regular Negative Digergences
--> Hidden Positive Digergences
--> Hidden Negative Digergences
- for positive divergences first it checks if closing price is higher than last closing price and indicator value is higher than perious value, then start searching divergence
- for negative divergences first it checks if closing price is lower than last closing price and indicator value is lower than perious value, then start searching divergence
Some Options:
Pivot Period: you set Pivot Period as you wish. you can see Pivot Points using "Show Pivot Points" option
Source for Pivot Points: you can use Close or High/Low as source
Divergence Type: you can choose Divergence type to be shown => "Regular", "Hidden", "Regular/Hidden"
Show Indicator Names: you have different options to show indicator names => "Full", "First Letter", "Don't Show"
Show Divergence Number: option to see number of indicators which has Divergence
Show Only Last Divergence: if you enable this option then it shows only last Positive and Negative Divergences
you can include any External Indicator to see if there is divergence
- enable "Check External Indicator"
- and then choose External indicator name in the list, "External Indicator"
- External indicator name is shown as Extrn
- related external indicator must be added before enabling this option
Coloring, line width and line style options for different type of divergences.
Following Alerts added:
- Positive Regular Divergence Detected
- Negative Regular Divergence Detected
- Positive Hidden Divergence Detected
- Negative Hidden Divergence Detected
Now lets see some examples:
Stoch_RSIStochastic RSI – Advanced Divergence Indicator
This custom indicator is an advanced version of the Stochastic RSI that not only smooths and refines the classic RSI input but also automatically detects both regular and hidden divergences using two powerful methods: fractal-based and pivot-based detection. Originally inspired by contributions from @fskrypt, @RicardoSantos, and later improved by developers like @NeoButane and @FYMD, this script has been fully refined for clarity and ease-of-use.
Key Features:
Dual Divergence Detection:
Fractal-Based Divergence: Uses a four-candle pattern to confirm top and bottom fractals for bullish and bearish divergences.
Pivot-Based Divergence: Employs TradingView’s built-in pivot functions for an alternate view of divergence conditions.
Customizable Settings:
The inputs are organized into logical groups (Stoch RSI settings, Divergence Options, Labels, and Market Open Settings) allowing you to adjust smoothing periods, RSI and Stochastic lengths, and divergence thresholds with a user-friendly interface.
Visual Enhancements:
Plots & Fills: The indicator plots both the K and D lines with corresponding fills and horizontal bands for quick visual reference.
Divergence Markers: Diamond shapes and labeled markers indicate regular and hidden divergences on the chart.
Market Open Highlighting: Optional histogram plots highlight the market open candle based on different timeframes for stocks versus non-forex symbols.
RSI of Accumulation/DistributionHow to Use the RSI of Accumulation/Distribution Indicator:
1. Identify Overbought/Oversold Conditions:
Overbought: When the RSI of the ADL is above 70, it indicates that the asset may be overbought and could be due for a pullback or correction.
Oversold: When the RSI of the ADL is below 30, it suggests that the asset may be oversold and could be poised for a rebound.
2. Look for Divergences:
Bullish Divergence: If the price is making lower lows while the RSI of the ADL is making higher lows, it can signal a potential reversal to the upside.
Bearish Divergence: If the price is making higher highs while the RSI of the ADL is making lower highs, it can indicate a potential reversal to the downside.
3. Confirm Trend Strength:
Use the RSI of the ADL to confirm the strength of a trend. For example, if the RSI is consistently above 50 during an uptrend, it suggests strong buying pressure and the trend is likely to continue.
Conversely, if the RSI is consistently below 50 during a downtrend, it indicates strong selling pressure and the trend is likely to persist.
4. Monitor for Reversals:
When the RSI of the ADL crosses above 50, it can signal a potential bullish reversal.
When the RSI of the ADL crosses below 50, it can signal a potential bearish reversal.
Is It Worth It?
The RSI of the Accumulation/Distribution Line can be a valuable tool for traders looking to gain insights into market momentum and trend strength. Here are a few reasons why it might be worth considering:
1. Volume and Price Combination: By combining price action (RSI) with volume-based analysis (ADL), this indicator provides a more comprehensive view of market dynamics.
2. Divergence Detection: It helps identify divergences between price and volume, which can be early signals of potential reversals.
3. Trend Confirmation: It offers additional confirmation of trend strength and potential reversal points, helping traders make more informed decisions.
However, like any indicator, it's important to use it in conjunction with other analysis methods and not rely on it solely for trading decisions. Backtesting the indicator on historical data and combining it with other technical analysis tools can improve its effectiveness.
Feel free to test the script in TradingView and see how it performs in different market conditions. If you have any specific questions or need further assistance, let me know! 😊
CVD Trend IndikatorCVD Trend Indicator (Cumulative Volume Delta)
This Pine Script indicator is designed to help traders visualize the underlying buying and selling pressure in the market by analyzing the Cumulative Volume Delta (CVD). It provides insights into whether buyers or sellers are more aggressive over time, aiding in trend confirmation and potential reversal identification.
How it Works:
The indicator calculates the Cumulative Volume Delta for each candlestick.
If the candle closes higher than it opened (close > open), its entire volume is considered buying volume (positive delta).
If the candle closes lower than it opened (close < open), its entire volume is considered selling volume (negative delta).
If the candle closes at the same price it opened (close == open), its delta is considered zero.
These individual candle deltas are then cumulatively summed up over time, creating the CVD line. A rising CVD indicates increasing buying pressure, while a falling CVD suggests growing selling pressure.
The indicator also features an optional Simple Moving Average (SMA) of the CVD, which helps smooth out the CVD line and identify the prevailing trend in buying/selling pressure more clearly.
Key Features:
Cumulative Volume Delta (CVD) Line:
Rising CVD (Blue Line): Indicates aggressive buying pressure is dominant, supporting bullish price action.
Falling CVD (Blue Line): Suggests aggressive selling pressure is dominant, supporting bearish price action.
CVD Moving Average (Red Line, optional):
A user-defined SMA of the CVD, which acts as a trend filter for the volume delta.
When the CVD crosses above its MA, it can signal increasing buying momentum.
When the CVD crosses below its MA, it can signal increasing selling momentum.
Session Reset:
The CVD automatically resets at the beginning of each new trading session (daily by default). This provides a fresh perspective on the day's accumulated buying or selling pressure, which is particularly useful for day traders.
Background Color Visuals:
The indicator panel's background changes color to visually represent periods of dominant buying pressure (green background when CVD > CVD MA) or selling pressure (red background when CVD < CVD MA), offering a quick glance at the market's underlying bias.
Trading Insights:
Trend Confirmation: Use a rising CVD (and its MA) to confirm an uptrend, or a falling CVD (and its MA) to confirm a downtrend.
Divergences: Look for CVD Divergences as potential reversal signals:
Bullish Divergence: Price makes a lower low, but CVD makes a higher low (suggests selling pressure is weakening).
Bearish Divergence: Price makes a higher high, but CVD makes a lower high (suggests buying pressure is weakening).
Momentum Shifts: Sudden, sharp changes in the CVD's direction or its cross over/under its MA can signal shifts in market momentum.
Support/Resistance Confirmation: Observe CVD behavior around key price levels. Weakening buying pressure at resistance or weakening selling pressure at support can confirm the strength of these levels.
Customization:
showMA: Toggle the visibility of the CVD's Moving Average.
maLength: Adjust the period for the CVD's Moving Average to control its sensitivity to recent price action. A shorter length makes it more reactive, while a longer length makes it smoother.
Disclaimer: No indicator is foolproof. Always use the CVD Trend Indicator in conjunction with other technical analysis tools, price action, and robust risk management strategies. Backtesting and forward testing are crucial for understanding its effectiveness in different market conditions and timeframes.
Aggregated Open Interest [Alpha Extract]The Aggregated Open Interest indicator provides a comprehensive view of open interest across multiple cryptocurrency exchanges, allowing traders to monitor institutional positioning and market sentiment. By aggregating data from major exchanges like Binance, BitMEX, and Kraken, this indicator offers valuable insights into potential price movements and market shifts.
🔶 CALCULATION
The indicator processes open interest data through multiple analytical methods:
Exchange Aggregation: Collects and normalizes open interest data from multiple exchanges (Binance, BitMEX, Kraken) with proper currency normalization.
Multi-Mode Analysis: Calculates various metrics including raw open interest values, OI change, OI delta, volume-weighted delta, and OI RSI.
Divergence Detection: Uses pivot point analysis to identify divergences between price action and open interest movements.
Activity Assessment: Tracks bullish and bearish activity patterns by correlating open interest changes with price movements.
Formula:
Aggregate OI = Sum of normalized open interest from selected exchanges
OI Change = Current OI - Previous OI
OI Delta = Net change in open interest across timeframes
OI Delta × Volume = OI Delta weighted by relative volume
OI RSI = Relative Strength Index applied to open interest values
OI Heatmap = Multi-timeframe visualization of OI changes across 7 distinct periods
🔶 DETAILS
Visual Features:
Open Interest: Candlestick representation of aggregated open interest
OI Change: Histogram showing period-to-period changes
OI Delta: Histogram displaying net OI movements
OI Delta × Volume: Volume-weighted OI delta for enhanced signals
OI RSI: Oscillator showing overbought/oversold OI conditions
OI Heatmap: Multi-timeframe visualization showing OI changes across 7 periods (3, 5, 8, 13, 21, 34, and 55 days)
Divergence Detection: Color-coded markers (teal for bullish, red for bearish) highlighting significant divergences between price and open interest
Analysis Table: Real-time summary of key metrics including aggregate OI, recent changes, and bullish/bearish activity.
Interpretation:
Increasing Open Interest + Rising Price: Strong bullish trend confirmation
Increasing Open Interest + Falling Price: Strong bearish trend confirmation
Decreasing Open Interest + Rising Price: Weak bullish trend (potential reversal)
Decreasing Open Interest + Falling Price: Weak bearish trend (potential reversal)
Divergences: Signal potential trend exhaustion and reversals when price moves in one direction while open interest moves in the opposite direction
Heatmap: Provides at-a-glance insight into open interest trends across multiple timeframes, with green bars indicating rising OI and red bars indicating falling OI
🔶 EXAMPLES
Trend Confirmation: Rising open interest accompanying a price increase confirms strong bullish momentum with institutional backing.
Example: During January-February 2025, rising OI during price advances confirms institutional participation in the uptrend.
Bearish Divergence: Price makes a higher high while open interest makes a lower high, signaling potential trend reversal.
Example: Red markers appear at market tops where price continues higher but open interest fails to confirm, preceding significant corrections.
Bullish Divergence : Price makes a lower low while open interest makes a higher low, indicating potential bottoming.
Example: Teal markers appear at market bottoms where price continues lower but open interest fails to confirm, preceding significant rallies.
OI Heatmap Analysis : Multiple timeframes showing consistent red signals across short to long-term periods indicate strong institutional selling pressure.
Example: When all 7 periods (3-55 days) show red during a price uptrend, this signals institutional selling into retail strength, often preceding major corrections.
🔶 SETTINGS
Customization Options:
Data Sources: Toggle different exchanges (Binance USDT/USD/BUSD, BitMEX USD/USDT, Kraken USD)
Display Mode: Choose between Open Interest, OI Change, OI Delta, OI Delta × Volume, OI RSI, and OI Heatmap
Currency Units: Display in USD or base cryptocurrency (COIN)
Analysis Tools: Moving Average (length and color), RSI (length and color)
Divergence Detection: Enable/disable signals, adjust lookback period and threshold percentage, customize bullish/bearish divergence colors
OI Heatmap Colors: Customize bullish (green) and bearish (red) signal colors for the multi-timeframe heatmap visualization
The Aggregated Open Interest indicator provides traders with comprehensive insights into institutional positioning across major exchanges, helping identify potential trend continuations, reversals, and key market turning points driven by smart money movements. The addition of the OI Heatmap feature enables traders to quickly visualize open interest trends across multiple timeframes, providing valuable context for institutional positioning over different market cycles.
Twitter Model ICT [TradingFinder] MMXM ERL D + FVG + M15 MSS/SMT🔵 Introduction
The Twitter Model ICT is a trading approach based on ICT (Inner Circle Trader) models, focusing on price movement between external and internal liquidity in lower timeframes. This model integrates key concepts such as Market Structure Shift (MSS), Smart Money Technique (SMT) divergence, and CISD level break to identify precise entry points in the market.
The primary goal of this model is to determine key liquidity levels, such as the previous day’s high and low (PDH/PDL) and align them with the Fair Value Gap (FVG) in the 1-hour timeframe. The overall strategy involves framing trades around the 1H FVG and using the M15 Market Structure Shift (MSS) for entry confirmation.
The Twitter Model ICT is designed to utilize external liquidity levels, such as PDH/PDL, as key entry zones. The model identifies FVG in the 1-hour timeframe, which acts as a magnet for price movement. Additionally, traders confirm entries using M15 Market Structure Shift (MSS) and SMT divergence.
Bullish Twitter Model :
In a bullish setup, the price sweeps the previous day’s low (PDL), and after confirming reversal signals, buys are executed in internal liquidity zones. Conversely, in a bearish setup, the price sweeps the previous day’s high (PDH), and after confirming weakness signals, sells are executed.
Bearish Twitter Model :
In short setups, entries are only executed above the Midnight Open, while in long setups, entries are taken below the Midnight Open. Adhering to these principles allows traders to define precise entry and exit points and analyze price movement with greater accuracy based on liquidity and market structure.
🔵 How to Use
The Twitter Model ICT is a liquidity-based trading strategy that analyzes price movements relative to the previous day’s high and low (PDH/PDL) and Fair Value Gap (FVG). This model is applicable in both bullish and bearish directions and utilizes the 1-hour (1H) and 15-minute (M15) timeframes for entry confirmation.
The price first sweeps an external liquidity level (PDH or PDL) and then provides an entry opportunity based on Market Structure Shift (MSS) and SMT divergence. Additionally, the entry should be positioned relative to the Midnight Open, meaning long entries should occur below the Midnight Open and short entries above it.
🟣 Bullish Twitter Model
In a bullish setup, the price first sweeps the previous day’s low (PDL) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bullish Fair Value Gap (FVG) forms, which serves as the price target.
To confirm the entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should be observed, signaling a trend reversal to the upside. Additionally, SMT divergence with correlated assets can indicate weakness in selling pressure.
Under these conditions, a long position is taken below the Midnight Open, with a stop-loss placed at the lowest point of the recent bearish move. The price target for this trade is the FVG in the 1-hour timeframe.
🟣 Bearish Twitter Model
In a bearish setup, the price first sweeps the previous day’s high (PDH) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bearish Fair Value Gap (FVG) is identified, serving as the trade target.
To confirm entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should form, signaling a trend shift to the downside. If an SMT divergence is present, it can provide additional confirmation for the trade.
Once these conditions are met, a short position is taken above the Midnight Open, with a stop-loss placed at the highest level of the recent bullish move. The trade's price target is the FVG in the 1-hour timeframe.
🔵 Settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
Daily Position : Determines whether only the first signal of the day is considered or if signals are evaluated throughout the entire day.
Session : Specifies in which trading sessions the indicator will be active.
Second Symbol : This setting allows you to select another asset for comparison with the primary asset. By default, "XAUUSD" (Gold) is set as the second symbol, but you can change it to any currency pair, stock, or cryptocurrency. For example, you can choose currency pairs like EUR/USD or GBP/USD to identify divergences between these two assets.
Divergence Fractal Periods : This parameter defines the number of past candles to consider when identifying divergences. The default value is 2, but you can change it to suit your preferences. This setting allows you to detect divergences more accurately by selecting a greater number of candles.
The indicator allows displaying sessions based on various time zones. The user can select one of the following options :
UTC (Coordinated Universal Time)
Local Time of the Session
User’s Local Time
Show Open Price : Displays the New York market opening price.
Show PDH / PDL : Displays the previous day’s high and low to identify potential entry points.
Show SMT Divergence : Displays lines and labels for bullish ("+SMT") and bearish ("-SMT") divergences.
🔵 Conclusion
The Twitter Model ICT is an effective approach for analyzing and executing trades in financial markets, utilizing a combination of liquidity principles, market structure, and SMT confirmations to identify optimal entry and exit points.
By analyzing the previous day’s high and low (PDH/PDL), Fair Value Gaps (FVG), and Market Structure Shift (MSS) in the 1H and M15 timeframes, traders can pinpoint liquidity-driven trade opportunities. Additionally, considering the Midnight Open level helps traders avoid random entries and ensures better trade placement.
By applying this model, traders can interpret market movements based on liquidity flow and structural changes, allowing them to fine-tune their trading decisions with higher precision. Ultimately, the Twitter Model ICT provides a structured and logical approach for traders who seek to trade based on liquidity behavior and trend shifts in the market.
CMF and Scaled EFI OverlayCMF and Scaled EFI Overlay Indicator
Overview
The CMF and Scaled EFI Overlay indicator combines the Chaikin Money Flow (CMF) and a scaled version of the Elder Force Index (EFI) into a single chart. This allows traders to analyze both indicators simultaneously, facilitating better insights into market momentum and volume dynamics , specifically focusing on buying/selling pressure and momentum , without compromising the integrity of either indicator.
Purpose
Chaikin Money Flow (CMF): Measures buying and selling pressure by evaluating price and volume over a specified period. It indicates accumulation (buying pressure) when values are positive and distribution (selling pressure) when values are negative.
Elder Force Index (EFI): Combines price changes and volume to assess the momentum behind market moves. Positive values indicate upward momentum (prices rising with strong volume), while negative values indicate downward momentum (prices falling with strong volume).
By scaling the EFI to match the amplitude of the CMF, this indicator enables a direct comparison between pressure and momentum , preserving their shapes and zero crossings. Traders can observe the relationship between price movements, volume, and momentum more effectively, aiding in decision-making.
Understanding Pressure vs. Momentum
Chaikin Money Flow (CMF):
- Indicates the level of demand (buying pressure) or supply (selling pressure) in the market based on volume and price movements.
- Accumulation: When institutional or large investors are buying significant amounts of an asset, leading to an increase in buying pressure.
- Distribution: When these investors are selling off their holdings, increasing selling pressure.
Elder Force Index (EFI):
- Measures the strength and speed of price movements, indicating how forceful the current trend is.
- Positive Momentum: Prices are rising quickly, indicating a strong uptrend.
- Negative Momentum: Prices are falling rapidly, indicating a strong downtrend.
Understanding the difference between pressure and momentum is crucial. For example, a market may exhibit strong buying pressure (positive CMF) but weak momentum (low EFI), suggesting accumulation without significant price movement yet.
Features
Overlay of CMF and Scaled EFI: Both indicators are plotted on the same chart for easy comparison of pressure and momentum dynamics.
Customizable Parameters: Adjust lengths for CMF and EFI calculations and fine-tune the scaling factor for optimal alignment.
Preserved Indicator Integrity: The scaling method preserves the shape and zero crossings of the EFI, ensuring accurate analysis.
How It Works
CMF Calculation:
- Calculates the Money Flow Multiplier (MFM) and Money Flow Volume (MFV) to assess buying and selling pressure.
- CMF is computed by summing the MFV over the specified length and dividing by the sum of volume over the same period:
CMF = (Sum of MFV over n periods) / (Sum of Volume over n periods)
EFI Calculation:
- Calculates the EFI using the Exponential Moving Average (EMA) of the price change multiplied by volume:
EFI = EMA(n, Change in Close * Volume)
Scaling the EFI:
- The EFI is scaled by multiplying it with a user-defined scaling factor to match the CMF's amplitude.
Plotting:
- Both the CMF and the scaled EFI are plotted on the same chart.
- A zero line is included for reference, aiding in identifying crossovers and divergences.
Indicator Settings
Inputs
CMF Length (`cmf_length`):
- Default: 20
- Description: The number of periods over which the CMF is calculated. A higher value smooths the indicator but may delay signals.
EFI Length (`efi_length`):
- Default: 13
- Description: The EMA length for the EFI calculation. Adjusting this value affects the sensitivity of the EFI to price changes.
EFI Scaling Factor (`efi_scaling_factor`):
- Default: 0.000001
- Description: A constant used to scale the EFI to match the CMF's amplitude. Fine-tuning this value ensures the indicators align visually.
How to Adjust the EFI Scaling Factor
Start with the Default Value:
- Begin with the default scaling factor of `0.000001`.
Visual Inspection:
- Observe the plotted indicators. If the EFI appears too large or small compared to the CMF, proceed to adjust the scaling factor.
Fine-Tune the Scaling Factor:
- Increase or decrease the scaling factor incrementally (e.g., `0.000005`, `0.00001`, `0.00005`) until the amplitudes of the CMF and EFI visually align.
- The optimal scaling factor may vary depending on the asset and timeframe.
Verify Alignment:
- Ensure that the scaled EFI preserves the shape and zero crossings of the original EFI.
- Overlay the original EFI (if desired) to confirm alignment.
How to Use the Indicator
Analyze Buying/Selling Pressure and Momentum:
- Positive CMF (>0): Indicates accumulation (buying pressure).
- Negative CMF (<0): Indicates distribution (selling pressure).
- Positive EFI: Indicates positive momentum (prices rising with strong volume).
- Negative EFI: Indicates negative momentum (prices falling with strong volume).
Look for Indicator Alignment:
- Both CMF and EFI Positive:
- Suggests strong bullish conditions with both buying pressure and upward momentum.
- Both CMF and EFI Negative:
- Indicates strong bearish conditions with selling pressure and downward momentum.
Identify Divergences:
- CMF Positive, EFI Negative:
- Buying pressure exists, but momentum is negative; potential for a bullish reversal if momentum shifts.
- CMF Negative, EFI Positive:
- Selling pressure exists despite rising prices; caution advised as it may indicate a potential bearish reversal.
Confirm Signals with Other Analysis:
- Use this indicator in conjunction with other technical analysis tools (e.g., trend lines, support/resistance levels) to confirm trading decisions.
Example Usage
Scenario 1: Bullish Alignment
- CMF Positive: Indicates accumulation (buying pressure).
- EFI Positive and Increasing: Shows strengthening upward momentum.
- Interpretation:
- Strong bullish signal suggesting that buyers are active, and the price is likely to continue rising.
- Action:
- Consider entering a long position or adding to existing ones.
Scenario 2: Bearish Divergence
- CMF Negative: Indicates distribution (selling pressure).
- EFI Positive but Decreasing: Momentum is positive but weakening.
- Interpretation:
- Potential bearish reversal; price may be rising but underlying selling pressure suggests caution.
- Action:
- Be cautious with long positions; consider tightening stop-losses or preparing for a possible trend reversal.
Tips
Adjust for Different Assets:
- The optimal scaling factor may differ across assets due to varying price and volume characteristics.
- Always adjust the scaling factor when analyzing a new asset.
Monitor Indicator Crossovers:
- Crossings above or below the zero line can signal potential trend changes.
Watch for Divergences:
- Divergences between the CMF and EFI can provide early warning signs of trend reversals.
Combine with Other Indicators:
- Enhance your analysis by combining this overlay with other indicators like moving averages, RSI, or Ichimoku Cloud.
Limitations
Scaling Factor Sensitivity:
- An incorrect scaling factor may misalign the indicators, leading to inaccurate interpretations.
- Regular adjustments may be necessary when switching between different assets or timeframes.
Not a Standalone Indicator:
- Should be used as part of a comprehensive trading strategy.
- Always consider other market factors and indicators before making trading decisions.
Disclaimer
No Guarantee of Performance:
- Past performance is not indicative of future results.
- Trading involves risk, and losses can exceed deposits.
Use at Your Own Risk:
- This indicator is provided for educational purposes.
- The author is not responsible for any financial losses incurred while using this indicator.
Code Summary
//@version=5
indicator(title="CMF and Scaled EFI Overlay", shorttitle="CMF & Scaled EFI", overlay=false)
cmf_length = input.int(20, minval=1, title="CMF Length")
efi_length = input.int(13, minval=1, title="EFI Length")
efi_scaling_factor = input.float(0.000001, title="EFI Scaling Factor", minval=0.0, step=0.000001)
// --- CMF Calculation ---
ad = high != low ? ((2 * close - low - high) / (high - low)) * volume : 0
mf = math.sum(ad, cmf_length) / math.sum(volume, cmf_length)
// --- EFI Calculation ---
efi_raw = ta.ema(ta.change(close) * volume, efi_length)
// --- Scale EFI ---
efi_scaled = efi_raw * efi_scaling_factor
// --- Plotting ---
plot(mf, color=color.green, title="CMF", linewidth=2)
plot(efi_scaled, color=color.red, title="EFI (Scaled)", linewidth=2)
hline(0, color=color.gray, title="Zero Line", linestyle=hline.style_dashed)
- Lines 4-6: Define input parameters for CMF length, EFI length, and EFI scaling factor.
- Lines 9-11: Calculate the CMF.
- Lines 14-16: Calculate the EFI.
- Line 19: Scale the EFI by the scaling factor.
- Lines 22-24: Plot the CMF, scaled EFI, and zero line.
Feedback and Support
Suggestions: If you have ideas for improvements or additional features, please share your feedback.
Support: For assistance or questions regarding this indicator, feel free to contact the author through TradingView.
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By combining the CMF and scaled EFI into a single overlay, this indicator provides a powerful tool for traders to analyze market dynamics more comprehensively. Adjust the parameters to suit your trading style, and always practice sound risk management.
