Quantum Transform - AynetQuantum Transform Trading Indicator: Explanation
This script is called a "Quantum Transform Trading Indicator" and aims to enhance market analysis by applying complex mathematical models. Written in Pine Script, the indicator includes the following elements:
1. General Structure
Quantum Parameters: Inspired by physical and mathematical concepts (Planck constant ℏ, wave function Ψ, time τ, etc.), it uses specific parameters.
Transformation Functions: Applies various mathematical operations to transform price data in different ways.
Signal Generation: Produces signals for long and short positions.
Visualization: Displays different price transformations and signals on the chart.
2. Core Parameters
The parameters allow users to control various transformations:
Planck Constant (ℏ): A scaling factor for wave modulation.
Wave (Ψ): Controls oscillation in price data.
Time (τ): The length of the lookback period for calculations.
Relativity (γ): Power factor in the Lorentz transformation.
Phase Shift (β): Manages phase shift in transformations.
Frequency (ω): Represents the frequency of price movements.
Dimensions (∇): Enables multi-dimensional field analysis.
3. Functions
a) Relativistic Transform
Inspired by the theory of relativity.
Calculates the Lorentz factor using the rate of price change.
Transforms price data to amplify the relativity effect.
b) Phase Transform
Calculates the phase of price data and applies wave modulation.
Creates phase and amplitude modulation based on the bar index.
c) Resonance Transform
Calculates resonance effects using natural frequency and oscillations.
Highlights periodic behaviors of price movements.
d) Field Transform
Applies multi-dimensional field calculations.
Combines strength, wave, and coherence aspects of price data.
e) Chaos Transform
Implements a chaos effect based on sensitivity analysis.
Simulates chaotic behaviors of price movements.
4. Main Calculations
Quantum Price: The average of all transformation functions.
Bands:
Upper Band: The highest level of quantum price.
Lower Band: The lowest level of quantum price.
Mid Band: The average of upper and lower bands.
Momentum: Calculates the rate of change in quantum price.
5. Signal Generation
Long Signal:
Triggered when the phase price crosses above the field price.
Momentum must be positive, and the price above the mid-band.
Short Signal:
Triggered when the phase price crosses below the field price.
Momentum must be negative, and the price below the mid-band.
Signal strength is calculated relative to the momentum moving average.
6. Visualization
Each transformation is displayed in a unique color.
Bands and Momentum: Visualize price behavior.
Signal Icons: Show buy/sell signals using up/down arrows on the chart.
7. Information Panel
A table in the top-right corner of the chart displays:
The current values of each transformation.
Signal strength (as a percentage).
The type of signal (⬆: Long, ⬇: Short).
Applications
Trend Following: Analyze trends with complex transformations.
Resonance and Chaos Analysis: Understand dynamic behaviors of price.
Signal Strategies: Create strong and reliable buy/sell signals.
If you have any additional questions or customization requests regarding this indicator, feel free to ask!
Search in scripts for "band"
Dynamic Volatility EnvelopeDynamic Volatility Envelope: Indicator Overview
The Dynamic Volatility Envelope is an advanced, multi-faceted technical indicator designed to provide a comprehensive view of market trends, volatility, and potential future price movements. It centers around a customizable linear regression line, enveloped by dynamically adjusting volatility bands. The indicator offers rich visual feedback through gradient coloring, candle heatmaps, a background volatility pulse, and an on-chart trend strength meter.
Core Calculation Mechanism
Linear Regression Core :
-A central linear regression line is calculated based on a user-defined source (e.g., close, hl2) and lookback period.
-The regression line can be optionally smoothed using an Exponential Moving Average (EMA) to reduce noise.
-The slope of this regression line is continuously calculated to determine the current trend direction and strength.
Volatility Channel :
-Dynamic bands are plotted above and below a central basis line. This basis is typically the calculated regression line but shifts to an EMA in Keltner mode.
-The width of these bands is determined by market volatility, using one of three user-selectable modes:
ATR Mode : Bandwidth is a multiple of the Average True Range (ATR).
Standard Deviation Mode : Bandwidth is a multiple of the Standard Deviation of the source data.
Keltner Mode (EMA-based ATR) : ATR-based bands are plotted around a central Keltner EMA line, offering a smoother channel.
The channel helps identify dynamic support and resistance levels and assess market volatility.
Future Projection :
The indicator can project the current regression line and its associated volatility bands into the future for a user-defined number of bars. This provides a visual guide for potential future price pathways based on current trend and volatility characteristics.
Candle Heatmap Coloring :
-Candle bodies and/or wicks/borders can be colored based on the price's position within the upper and lower volatility bands.
-Colors transition in a gradient from bearish (when price is near the lower band) through neutral (mid-channel) to bullish (when price is near the upper band), providing an intuitive visual cue of price action relative to the dynamic envelope.
Background Volatility Pulse :
The chart background color can be set to dynamically shift based on a ratio of short-term to long-term ATR. This creates a "pulse" effect, where the background subtly changes color to indicate rising or falling market volatility.
Trend Strength Meter :
An on-chart text label displays the current trend status (e.g., "Strong Bullish", "Neutral", "Bearish") based on the calculated slope of the regression line relative to user-defined thresholds for normal and strong trends.
Key Features & Components
-Dynamic Linear Regression Line: Core trend indicator with optional smoothing and slope-based gradient coloring.
-Multi-Mode Volatility Channel: Choose between ATR, Standard Deviation, or Keltner (EMA-based ATR) calculations for band width.
-Customizable Vertical Gradient Channel Fills: Visually distinct fills for upper and lower channel segments with user-defined top/bottom colors and gradient spread.
-Future Projection: Extrapolates regression line and volatility bands to forecast potential price paths.
-Price-Action Based Candle Heatmap: Intuitive candle coloring based on position within the volatility channel, with adjustable gradient midpoint.
-Volatility-Reactive Background Gradient: Subtle background color shifts to reflect changes in market volatility.
-On-Chart Trend Strength Meter: Clear textual display of current trend direction and strength.
-Extensive Visual Customization: Fine-tune colors, line styles, widths, and gradient aggressiveness for most visual elements.
-Comprehensive Tooltips: Detailed explanations for every input setting, ensuring ease of use and understanding.
Visual Elements Explained
Regression Line : The primary trend line. Its color dynamically changes (e.g., green for uptrend, red-pink for downtrend, neutral for flat) based on its slope, with smooth gradient transitions.
Volatility Channel :
Upper & Lower Bands : These lines form the outer boundaries of the envelope, acting as dynamic support and resistance levels.
Channel Fill : The area between the band center and the outer bands is filled with a vertical gradient. For example, the upper band fill might transition from a darker green near the center to a lighter green at the upper band.
Band Borders : The lines outlining the upper and lower bands, with customizable color and width.
Future Projection Lines & Fill :
Projected Regression Line : An extension of the current regression line into the future, typically styled differently (e.g., dashed).
Projected Channel Bands : Extensions of the upper and lower volatility bands.
Projected Area Fill : A semi-transparent fill between the projected upper and lower bands.
Candle Heatmap Coloring : When enabled, candles are colored based on their closing price's relative position within the channel. Bullish colors appear when price is in the upper part of the channel, bearish in the lower, and neutral in the middle. Users can choose to color the entire candle body or just the wicks and borders.
Background Volatility Pulse : The chart's background color subtly shifts (e.g., between a calm green and an agitated red-pink) to reflect the current volatility regime.
Trend Strength Meter : A text label (e.g., "TREND: STRONG BULLISH") positioned on the chart, providing an at-a-glance summary of the trend.
Configuration Options
Users can tailor the indicator extensively via the settings panel, with options logically grouped:
Core Analysis Engine : Adjust regression source data, lookback period, and EMA smoothing for the regression line.
Regression Line Visuals : Control visibility, line width, trend-based colors (uptrend, downtrend, flat), slope thresholds for trend definition, strong slope multiplier (for Trend Meter), and color gradient sharpness.
Volatility Channel Configuration : Select band calculation mode (ATR, StdDev, Keltner), set relevant periods and multipliers. Customize colors for vertical gradient fills (upper/lower, top/bottom), border line colors, widths, and the gradient spread factor for fills.
Future Projection Configuration : Toggle visibility, set projection length (number of bars), line style, and colors for projected regression and band areas.
Appearance & Candle Theme : Set default bull/bear candle colors, enable/disable candle heatmap, choose if body color matches heatmap, and configure heatmap gradient target colors (bull, neutral, bear) and the gradient's midpoint.
Background Volatility Pulse : Enable/disable the background effect and configure short/long ATR periods for the volatility calculation.
Trend Strength Meter : Enable/disable the meter, and choose its on-chart position and text size.
Interpretation Notes
-The Regression Line is the primary indicator of trend direction. Its slope and color provide immediate insight.
-The Volatility Bands serve as dynamic support and resistance zones. Price approaching or touching these bands may indicate potential turning points or breakouts. The width of the channel itself reflects market volatility – widening suggests increasing volatility, while narrowing suggests consolidation.
Future Projections are not predictions but rather an extension of current conditions. They can help visualize potential areas where price might interact with projected support/resistance if the current trend and volatility persist.
Candle Heatmap Coloring offers a quick visual assessment of where price is trading within the dynamic envelope, highlighting strength or weakness relative to the channel.
The Background Volatility Pulse gives a contextual feel for overall market agitation or calmness.
This indicator is designed to be a comprehensive analytical tool. Its signals and visualizations are best used in conjunction with other technical analysis techniques, price action study, and robust risk management practices. It is not intended as a standalone trading system.
Risk Disclaimer
Trading and investing in financial markets involve substantial risk of loss and is not suitable for every investor. The Dynamic Volatility Envelope indicator is provided for analytical and educational purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance is not indicative of future results. Always use sound risk management practices and never trade with capital you cannot afford to lose. The developers assume no liability for any financial losses incurred based on the use of this indicator.
WaveTrend Dynamic (Lazy Bear Style)█ OVERVIEW
The WaveTrend Dynamic indicator (in the style of Lazy Bear) is an advanced tool based on the Exponential Smoothing Average (ESA), which adapts to the volatility and price of a financial instrument. It is more flexible than the classic WaveTrend but shares a similar concept of bands around a main oscillator line.
The indicator uses dynamic bands calculated as distances from the ESA, with their width adjustable via the "level" parameter. This allows it to be tailored to various markets, timeframes, and volatility conditions, making it easier to identify trends, reversal points, and buy/sell signals.
█ CONCEPTS
The WaveTrend Dynamic combines oscillator functions with trend analysis. Below, we explain the key components in a simple way, understandable even for beginner users.
Core Calculations
The indicator relies on the adaptive ESA and a few straightforward steps:
1 — ESA (Adaptive Average): Calculated as a smoothed average of the price (from high, low, and close, or HLC3) using the ESA Length parameter (default: 10). This number determines how many past candles are considered in the calculation. The ESA quickly responds to price changes, helping to track trends.
2 — Deviation (D): Measures how much the price deviates from the ESA, factoring in market volatility. This allows the indicator to adapt to different instruments.
3 — Price Distance Indicator (CI): Shows how far the price is from the ESA relative to market volatility. This forms the basis for the main indicator line, reacting to price movements.
4 — WT1 (WaveTrend 1): The main line, smoothing the Price Distance Indicator (CI) with the Average Length parameter (default: 21). It reflects the direction of price movement and momentum.
5 — WT2 (WaveTrend 2): A signal line that further smooths WT1 (with a period of 4). It helps confirm signals through crossovers with WT1.
6 — Bands (UpperBand and LowerBand): These form a dynamic channel around the ESA. Their width depends on the level parameter (default: 100). Wider bands result in fewer but more reliable signals. In the original WaveTrend, the oscillator bands use lower values, such as 50 or 60. To achieve classic oscillator signals (more frequent WT1/WT2 crossovers outside the bands), set the level to 50–60.
Trend Identification
The indicator identifies two types of trends:
• Major Trend: Determined by the position of WT1 relative to the ESA. When WT1 is above the ESA, it indicates a bullish trend. When below, it signals a bearish trend. Line and fill colors reflect this trend.
• Mini-Trend: Based on WT1 and WT2 crossovers. When the lines cross, they change to the same color, signaling short-term changes or reversal points. This is ideal for quick trading decisions.
Visuals and Effects
• WT1 and WT2 Lines: Scaled to price and displayed on the price chart for easier analysis.
• Fills: Between the bands (UpperBand/LowerBand) and between WT1/WT2, with a "wave" effect that adjusts transparency based on the trend (green for bullish, red for bearish).
• Signals: Three types—return-to-band, WT1/WT2 crossovers outside the bands, and crossovers inside the bands. Signals are displayed as triangles with different colors for buy and sell.
█ FEATURES
Detailed features of the indicator, aligned with the order of settings in the script:
• Basic Parameters: ESA Length — controls ESA smoothing; Average Length — affects WT1 responsiveness; level (WT Level) — adjusts band width for signal filtering.
• Display Elements: Options to show/hide ESA, bands, WT1/WT2; customizable colors for lines, fills, and the wave effect.
• Signals: Three signal groups (return-to-band, crossovers outside bands, crossovers inside bands) with display and color customization options.
█ HOW TO USE
1 — Add the indicator to your TradingView chart and adjust parameters: — Increase ESA Length and Average Length for low-volatility markets (e.g., stocks), or decrease for cryptocurrencies or forex. — Set level to 50–60 for classic WaveTrend signals with WT1/WT2 crossovers outside bands. The default value of 100 creates wider bands and fewer signals.
2 — Analyze trends: — Major trend (WT1 vs. ESA) shows the overall market direction. — Mini-trends (WT1/WT2 crossovers) help time short-term entries.
3 — Use signals: — Return-to-band: Buy at the lower band, sell at the upper band (mean-reversion). — Crossovers outside bands: Indicate strong momentum (with a lower level, e.g., 50). — Crossovers inside bands: Signal weaker trend changes.
4 — Combine with other tools: Use with volume, RSI, or support/resistance for better decisions. Test on historical data to optimize settings.
Nadaraya-Watson Probability [Yosiet]The script calculates and displays probability bands around price movements, offering insights into potential market trends.
Setting Up the Script
Window Size: Determines the length of the window for the Nadaraya-Watson estimation. A larger window smooths the data more but might lag current market conditions.
Bandwidth: Controls the bandwidth for the kernel regression, affecting the smoothness of the probability bands.
Reading the Data Table
The script dynamically updates a table positioned at the bottom right of your chart, providing real-time insights into market probabilities. Here's how to interpret the table:
Table Columns: The table is organized into three columns:
Up: Indicates the probability or relative change percentage for the upper band.
Down: Indicates the probability or relative change percentage for the lower band.
Table Rows: There are two main rows of interest:
P%: Shows the price change percentage difference between the bands and the closing price. A positive value in the "Up" column suggests the upper band is above the current close, indicating potential upward momentum. Conversely, a negative value in the "Down" column suggests downward momentum.
R%: Displays the relative inner change percentage difference between the bands, offering a measure of the market's volatility or stability within the bands.
Utilizing the Insights
Market Trends: A widening gap between the "Up" and "Down" percentages in the "P%" row might indicate increasing market volatility. Traders can use this information to adjust their risk management strategies accordingly.
Entry and Exit Points: The "R%" row provides insights into the relative position of the current price within the probability bands. Traders might consider positions closer to the lower band as potential entry points and positions near the upper band as exit points or take-profit levels.
Conclusion
The Nadaraya-Watson Probability script offers a sophisticated tool for traders looking to incorporate statistical analysis into their trading strategy. By understanding and utilizing the data presented in the script's table, traders can gain insights into market trends and volatility, aiding in decision-making processes. Remember, no indicator is foolproof; always consider multiple data sources and analyses when making trading decisions.
Uptrick: Volatility Weighted CloudIntroduction
The Volatility Weighted Cloud (VWC) is a trend-tracking overlay that combines adaptive volatility-based bands with a multi-source smoothed price cloud to visualize market bias. It provides users with a dynamic structure that adapts to volatility conditions while maintaining a persistent visual record of trend direction. By incorporating configurable smoothing techniques, percentile-ranked volatility, and multi-line cloud construction, the indicator allows traders to interpret price context more effectively without relying on raw price movement alone.
Overview
The script builds a smoothed price basis using the open, and close prices independently, and uses these to construct a layered visual cloud. This cloud serves both as a reference for price structure and a potential area of dynamic support and resistance. Alongside this cloud, adaptive upper and lower bands are plotted using volatility that scales with percentile rank. When price closes above or below these bands, the script interprets that as a breakout and updates the trend bias accordingly.
Candle coloring is persistent and reflects the most recent confirmed signal. Labels can optionally be placed on the chart when the trend bias flips, giving traders additional visual reference points. The indicator is designed to be both flexible and visually compact, supporting different strategies and timeframes through its detailed configuration options.
Originality
This script introduces originality through its combined use of percentile-ranked volatility, adaptive envelope sizing, and multi-source cloud construction. Unlike static-band indicators, the Volatility Weighted Cloud adjusts its band width based on where current volatility ranks within a defined lookback range. This dynamic scaling allows for smoother signal behavior during low-volatility environments and more responsive behavior during high-volatility phases.
Additionally, instead of using a single basis line, the indicator computes two separate smoothed lines for open and close. These are rendered into a shaded visual cloud that reflects price structure more completely than traditional moving average overlays. The use of ALMA and MAD, both less commonly applied in volatility-band overlays, adds further control over smoothing behavior and volatility measurement, enhancing its adaptability across different market types.
Inputs
Group: Core
Basis Length (short-term): The number of bars used for calculating the primary basis line. Affects how quickly the basis responds to price changes.
Basis Type: Option to choose between EMA and ALMA. EMA provides a standard exponential average; ALMA offers a centered, Gaussian-weighted average with reduced lag.
ALMA Offset: Determines the balance point of the ALMA window. Only applies when ALMA is selected.
Sigma: Sets the width of the ALMA smoothing window, influencing how much smoothing is applied.
Basis Smoothing EMA: Adds additional EMA-based smoothing to the computed basis line for noise reduction.
Group: Volatility & Bands
Volatility: Choose between StDev (standard deviation) and MAD (median absolute deviation) for measuring price volatility.
Vol Length (short-term): Length of the window used for calculating volatility.
Vol Smoothing EMA: Smooths the raw volatility value to stabilize band behavior.
Min Multiplier: Minimum multiplier applied to volatility when forming the adaptive bands.
Max Multiplier: Maximum multiplier applied at high volatility percentile.
Volatility Rank Lookback: Number of bars used to calculate the percentile rank of current volatility.
Show Adaptive Bands: Enables or disables the display of upper and lower volatility bands on the chart.
Group: Trend Switch Labels
Show Trend Switch Labels: Toggles the appearance of labels when the trend direction changes.
Label Anchor: Defines whether the labels are anchored to recent highs/lows or to the main basis line.
ATR Length (offset): Length used for calculating ATR, which determines label offset distance.
ATR Offset (multiplier): Multiplies the ATR value to place labels away from price bars for better visibility.
Label Size: Allows selection of label size (tiny to huge) to suit different chart setups.
Features
Adaptive Volatility Bands: The indicator calculates volatility using either standard deviation or MAD. It then applies an EMA smoothing layer and scales the band width dynamically based on the percentile rank of volatility over a user-defined lookback window. This avoids fixed-width bands and allows the indicator to adapt to changing volatility regimes in real time.
Volatility Method Options: Users can switch between two volatility measurement methods:
➤ Standard Deviation (StDev): Captures overall price dispersion, but may be sensitive to spikes.
➤ Median Absolute Deviation (MAD): A more robust measure that reduces the effect of outliers, making the bands less jumpy during erratic price behavior.
Basis Type Options: The core price basis used for cloud and bands can be built from:
➤ Exponential Moving Average (EMA): Fast-reacting and widely used in trend systems.
➤ Arnaud Legoux Moving Average (ALMA): A smoother, more centered alternative that offers greater control through offset and sigma parameters.
Multi-Line Basis Cloud: The cloud is formed by plotting two individually smoothed basis lines from open and close prices. A filled area is created between the open and close basis lines. This cloud serves as a dynamic support or resistance zone, allowing users to identify possible reversal areas. Price moving through or rejecting from the cloud can be interpreted contextually, especially when combined with band-based signals.
Persistent Trend Bias Coloring: The indicator uses the last confirmed breakout (above upper band or below lower band) to determine bias. This bias is reflected in the color of every subsequent candle, offering a persistent visual cue until a new signal is triggered. It helps simplify trend recognition, especially in choppy or sideways markets.
Trend Switch Labels: When enabled, the script places labeled markers at the exact bar where the bias direction switches. Labels are anchored either to recent highs/lows or to the main basis line, and spaced vertically using an ATR-based offset. This allows the trader to quickly locate historical trend transitions.
Alert Conditions: Two built-in alert conditions are available:
➤ Long Signal: Triggered when the close crosses above the upper adaptive band.
➤ Short Signal: Triggered when the close crosses below the lower adaptive band.
These conditions can be used for custom alerts, automation, or external signaling tools.
Display Control and Flexibility: Users can disable the adaptive bands for a cleaner layout while keeping the basis cloud and candle coloring active. The indicator can be tuned for fast or slow response depending on the strategy in use, and is suitable for intraday, swing, or position trading.
Summary
The Volatility Weighted Cloud is a configurable trend-following overlay that uses adaptive volatility bands and a structured cloud system to help visualize market bias. By combining EMA or ALMA smoothing with percentile-ranked volatility and a four-line price structure, it provides a flexible and informative charting layer. Its key strengths lie in the use of dynamic envelopes, visually persistent trend indication, and clearly defined breakout zones that adapt to current volatility conditions.
Disclaimer
This indicator is for informational and educational purposes only. Trading involves risk and may not be suitable for all investors. Past performance does not guarantee future results.
Trendilo ARTrendilo AR is a custom trading indicator designed to identify market trends using advanced techniques such as the Arnaud Legoux Moving Average (ALMA), volume confirmations, and dynamic volatility bands. This indicator provides a clear visualization of trends, including significant changes and custom alerts.
Review of Indicators Used
1. ALMA
Description:
ALMA is a moving average that applies an advanced filter to smooth price data, reducing noise and focusing on actual trends.
Usage in the Indicator:
Used to calculate the smoothed percentage price change and determine trend direction. Customizable parameters include:
- Length: Defines the number of bars to consider.
- Offset: Adjusts sensitivity toward recent prices.
- Sigma: Controls the degree of smoothing.
Advantages:
- Reduced lag in trend detection.
- Resistance to market noise.
2. ATR
Description:
ATR measures the market’s average volatility by considering the range between high and low prices over a given period.
Usage in the Indicator:
ATR is used to calculate "dynamic smoothing", adjusting the indicator’s sensitivity based on current market volatility.
Advantages:
- Adapts to high or low volatility conditions.
- Helps define dynamic support and resistance levels.
3. SMA
Description:
SMA calculates the average of prices or volume over a specific time period.
Usage in the Indicator:
Used to calculate the volume moving average (Volume SMA) to confirm whether the current volume supports the detected trend.
Advantages:
- Easy to understand and calculate.
- Provides volume-based trend confirmation.
4. RMS Bands
Description:
RMS Bands calculate the standard deviation of percentage price changes, creating upper and lower levels that act as overbought and oversold indicators.
Usage in the Indicator:
- Define the range within which the market is considered neutral.
- Crosses above or below the bands indicate trend changes.
Advantages:
- Visual identification of strong trends.
- Helps filter false signals.
Colors and Visuals Used in the Indicator
1. ALMA Line
Colors:
- Green: Indicates a confirmed uptrend (with sufficient volume).
- Red: Indicates a confirmed downtrend (with sufficient volume).
- Gray: Indicates a neutral phase or insufficient volume to confirm a trend.
2. RMS Bands
- Upper and Lower Lines:
- Purple (with transparency): These lines represent the RMS bands (upper and lower) and
adjust opacity based on trend strength.
- Stronger trends result in less transparency (more solid colors).
3. Highlighted Background (Strong Trends)
- Color:
- Light Green (transparent): Highlights a strong trend when the smoothed percentage change (ALMA) exceeds 1.5 times the RMS.
4. Horizontal Lines
- Baseline (0):
- Dark Gray: Serves as a central reference to identify the directionality of percentage changes.
- Additional Line (0.1):
- Blue: A customizable line to mark user-defined key levels.
5. Bar Colors
- Bar Colors:
- Green: When the price is in a confirmed uptrend.
- Red: When the price is in a confirmed downtrend.
- No color: When there is insufficient volume or no clear trend.
How to Use the Indicator
1. Initial Setup
1. Add the Indicator to Your Chart: Copy the code into the Pine Editor on TradingView and apply it to your chart.
2. Customize Parameters: Adjust values based on your trading strategy:
- Smoothing: Controls the level of smoothing for percentage changes.
- Lookback Length: Defines the observation period for calculations.
- Band Multiplier: Adjusts the width of RMS bands.
2. Signal Interpretation
1. Indicator Colors:
- Green: Confirmed uptrend.
- Red: Confirmed downtrend.
- Gray: No clear trend or insufficient volume.
2. RMS Bands:
- If the ALMA line (smoothed percentage change) crosses above the upper RMS band, it signals a potential uptrend.
- If it crosses below the lower RMS band, it signals a potential downtrend.
3. Volume Confirmation:
- The indicator's color activates only if the current volume exceeds the Volume SMA.
3. Alerts and Decisions
1. Trend Change Alerts:
- The indicator automatically triggers alerts when an uptrend or downtrend is detected.
- Configure these alerts to receive real-time notifications.
2. Strong Trend Signals:
- When the magnitude of the percentage change exceeds 1.5 times the RMS, the chart background highlights the strong trend.
4. Trading Strategies
1. Buy:
- Enter long positions when:
- The indicator turns green.
- Volume confirms the trend.
- Consider placing a stop-loss just below the lower RMS band.
2. Sell:
- Enter short positions when:
- The indicator turns red.
- Volume confirms the trend.
- Consider placing a stop-loss just above the upper RMS band.
3. Neutral:
- Avoid trading when the indicator is gray, as no clear trend or insufficient volume is present.
Disclaimer: As this is my first published indicator, please use it with caution. Feedback is highly appreciated to improve its performance.
Happy Trading!
Magic Linear Regression Channel [MW]Introduction
The Magic Linear Regression Channel indicator provides users with a way to quickly include a linear regression channel ANYWHERE on their chart, in order to find channel breakouts and bounces within any time period. It uses a novel method that allows users to adjust the start and end period of the regression channel in order to quickly make adjustments faster, with fewer steps, and with more precision than with any other linear regression channel tool. It includes Fibonacci bands AND a horizontal mode in order for users to quickly define significant price levels based on the high, low, open, and close prices defined by the start period.
Settings
Start Time: This is initially MANUALLY SELECTED ON THE CHART when the indicator is first loaded.
End time: This is also initially MANUALLY SELECTED ON THE CHART when the indicator is first loaded.
Horizontal Line: This forces the baseline to be horizontal. The band distance is defined by the maximum price distance from the band.
Horizontal Line Type: This snaps the horizontal line to the close, high, low, or open price. Or, it can also use a regression calculation for the selected time period to define the y-position of the line.
Extend Line N Bars: How many bars to the left in which to extend the baseline and bands.
Show Baseline ONLY!!: Removes all lines except the baseline and it’s extension.
Add Half Band: Includes a band that is half the distance between the baseline and the top and bottom bands
Add Outer Fibonacci Band: Includes a band that is 1.618 (phi) times the default band distance
Add Inner Fibonacci Band - Upper: Includes a band that is 0.618 (1/phi) times the default band distance
Add Inner Fibonacci Band - Lower: Includes a band that is 0.382 (1 - 1/phi) times the default band distance
Calculations
This indicator uses the least squares approach for generating a straight regression line, which can be reviewed at Wikipedia’s “Simple Linear Regression” page. It sums all of the x-values, and y-values, as well as the sum of the product of corresponding x and y values, and the sum of the squares of the x-values. These values are used to calculate the slope and intercept using the following equations:
slope = (n * sum_xy - sum_x * sum_y) / (n * sum_xx - sum_x * sum_x)
And
intercept = (sum_y - slope * sum_x) / n
The slope and intercept are then used to generate the baseline and the corresponding bands using the user-selected offsets.
How to Use
When the Magic Linear Regression Channel indicator is first added to the chart, there will be a blue prompt behind the “Indicators, Metrics & Strategies” window. Close the window, then select a START POINT by clicking at a desired location on the chart. Next, you will be prompted to select an END POINT. The end point MUST be placed after the START POINT. At this time a channel will be generated. Once you’ve selected the START POINT and END POINT, you can adjust them by dragging them anywhere on the chart. Each adjustment will generate a new channel making it easier for you to quickly visualize and recognize any channel exits and bounces.
The Magic Linear Regression Channel indicator works great at identifying wave patterns. Place the start line at a top or bottom pivot point. Place the end line at the next respective top or bottom pivot. This will give you a complete wave form to work with. When price reaches a band and rejects, it can be a strong indication that price may move back to one of the bands in the channel. If price exits the channel with volume that supports the exit, it may be an indication of a breakout.
You can also use the horizontal mode to identify key levels, then add Fibonacci bands based on regression calculations for the given time period to provide more meaningful areas of support and resistance.
Other Usage Notes and Limitations
Occasionally, off-by-1 errors appear which makes the extended lines protrude at a slightly incorrect angle. This is a known bug and will be addressed in the next release.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Super IndicatorOverview of the Combined Indicator
This combined indicator leverages three major technical analysis tools:
Bollinger Bands
Linear Regression Channels
Scalping Strategy Indicators (RSI, MACD, SMA)
Each of these tools provides unique insights into market conditions, and their integration offers a comprehensive view of price movements, trends, and potential trading signals.
1. Bollinger Bands
Purpose:
Bollinger Bands are used to measure market volatility and identify overbought or oversold conditions.
Components:
Basis (Middle Band): Typically a 20-period Simple Moving Average (SMA).
Upper Band: Basis + (2 * Standard Deviation).
Lower Band: Basis - (2 * Standard Deviation).
Why They Complement:
Bollinger Bands expand and contract based on market volatility. When the bands are narrow, it indicates low volatility and potential for a significant move. Wide bands indicate high volatility. This helps traders gauge the strength of market moves and potential reversals.
2. Linear Regression Channels
Purpose:
Linear Regression Channels identify the overall trend direction and measure deviation from the mean price over a specific period.
Components:
Middle Line (Linear Regression Line): The line of best fit through the price data over a specified period.
Upper and Lower Lines: Channels created by adding/subtracting a multiple of the standard deviation or another deviation measure from the regression line.
Why They Complement:
Linear Regression Channels provide a clear visual representation of the trend direction and the range within which prices typically fluctuate. This can help traders identify trend continuations and reversals, making it easier to spot entry and exit points.
3. Scalping Strategy Indicators
Purpose:
The RSI, MACD, and SMA are used to generate short-term buy and sell signals, which are essential for scalping strategies aimed at capturing quick profits from small price movements.
Components:
RSI (Relative Strength Index): Measures the speed and change of price movements, typically over 14 periods. It helps identify overbought and oversold conditions.
MACD (Moving Average Convergence Divergence): Consists of the MACD line, Signal line, and histogram. It helps identify changes in the strength, direction, momentum, and duration of a trend.
SMA (Simple Moving Average): The average price over a specified period, used to smooth out price data and identify trends.
Why They Complement:
These indicators provide short-term signals that can confirm or refute the signals given by Bollinger Bands and Linear Regression Channels. For example, a buy signal might be more reliable if the price is near the lower Bollinger Band and the MACD crosses above its signal line.
How They Work Together
Scenario 1: Confirming Trend Continuations
Bollinger Bands: Price staying near the upper band suggests a strong uptrend.
Linear Regression Channels: Price staying above the middle line confirms the uptrend.
5-Minute Scalping Strategy: RSI not in overbought territory, and MACD showing bullish momentum confirms continuation.
Scenario 2: Identifying Reversals
Bollinger Bands: Price touching or moving outside the lower band suggests oversold conditions.
Linear Regression Channels: Price at the lower channel line indicates potential support.
5-Minute Scalping Strategy: RSI in oversold territory, and MACD showing a bullish crossover indicates a reversal.
Scenario 3: Volatility Breakouts
Bollinger Bands: Bands contracting indicates low volatility and potential breakout.
Linear Regression Channels: Price moving away from the middle line signals potential breakout direction.
Scalping Strategy: MACD and RSI confirming the breakout direction for entry.
Input Parameters:
Define settings for Bollinger Bands, Linear Regression Channels, and the scalping strategy.
Allow users to customize lengths, multipliers, and colors.
Bollinger Bands Calculation:
Calculate the basis (SMA) and standard deviation.
Derive the upper and lower bands from the basis and standard deviation.
Linear Regression Channel Calculation:
Compute the slope, average, and intercept of the linear regression line.
Calculate deviations to plot upper and lower channel lines.
5-Minute Scalping Strategy:
Calculate RSI, MACD, and SMA for short-term trend analysis.
Define buy and sell conditions based on these indicators.
Plotting and Alerts:
Plot Bollinger Bands and Linear Regression Channels on the chart.
Plot buy and sell signals with shapes.
Set alerts for key conditions like exiting the regression channel bounds and trend switches.
Conclusion
By combining Bollinger Bands, Linear Regression Channels, and a 5-minute scalping strategy, this indicator offers a robust tool for traders. Bollinger Bands provide volatility insights, Linear Regression Channels highlight trend direction and potential reversals, and the scalping strategy offers precise entry and exit points. Together, these tools can enhance a trader's ability to make informed decisions in various market conditions.
FRAMA Channel [JopAlgo]FRAMA Channel — let the market tell you how fast to move
Most moving averages make you pick a speed and hope it fits every regime. FRAMA (Fractal Adaptive Moving Average, popularized by John Ehlers) does the opposite: it adapts its smoothing to market structure. When price action is “trendy” (more directional, less jagged), FRAMA speeds up; when it’s choppy (more fractal noise), FRAMA slows down and filters the rubble.
FRAMA Channel wraps that adaptive core with a volatility channel and clean color logic so you can read trend, mean-reversion windows, and breakouts in one glance—on any timeframe.
What you’re seeing (plain-English tour)
FRAMA midline (Filt): the adaptive average. It’s computed from a fractal dimension of price over Length (N).
Trendy tape → lower fractal dimension → FRAMA tracks price tighter.
Choppy tape → higher fractal dimension → FRAMA smooths harder.
Channel bands (Filt ± distance × volatility): the “breathing room.” Volatility here is a long lookback average of (high − low).
Upper band = potential resistance in down/neutral or trend-walk path in uptrends.
Lower band = mirror logic for shorts.
Color logic (simple and strict):
Green when price breaks above the upper band → bullish regime (momentum present).
Red when price breaks below the lower band → bearish regime.
White when price crosses the FRAMA midline → neutral/reset.
Optional candle coloring: toggle Color Candles to tint the chart itself with the regime color—handy for quick reads.
(When you add screenshots: image #1 should label FRAMA, bands, and the three colors in a small trend + pullback. Image #2 can show a “squeeze → expansion” sequence: channel tightens, then price breaks and walks the band.)
How it’s built (without the jargon)
The script measures three ranges over your Length (N): two half-windows and the full window.
It converts those into a fractal dimension (Dimen). That number says “how zig-zaggy” price is right now.
It turns Dimen into an alpha (smoothing factor): alpha = exp(−4.6 × (Dimen − 1)), clamped so it never explodes or flatlines.
It updates FRAMA each bar using that alpha.
It builds bands using a long average of (high − low) multiplied by your Bands Distance setting.
It changes color only on confirmed bar events:
hlc3 crosses above the upper band → green
hlc3 crosses below the lower band → red
close crosses the midline → white
Result: a channel that tightens in balance, widens in trend, and doesn’t flicker on partial bars.
How to use FRAMA Channel on any timeframe
Same framework everywhere. Your job is to choose where to act (objective levels) and let FRAMA tell you trend/mean-reversion context and breakout quality.
Scalping (1–5m)
Pullback-to-midline (trend): When color is green, buy pullbacks that hold at/above the midline; when red, short pullbacks that fail at/below it.
Invalidation: a white flip (midline cross back) right after entry → tighten or bail.
Squeeze → break: A narrowing channel often precedes a move. Only chase the break if color flips to green/red and the first pullback holds the band/midline.
Intraday (15m–1H)
Trend rides: In green/red, expect price to walk the outer band. Entries on midline kisses are cleaner than chasing the band itself.
Balance fades: In white (neutral) with a tight channel, fade outer band → midline—but only at a real level (see “Pairing” below).
Swing (2H–4H)
Regime compass: Color changes that stick (several bars) often mark swing regime shifts. Combine with Weekly/Event AVWAP and composite VP levels.
Add/Trim: In an uptrend, add on midline holds; trim as the channel widens and price spikes beyond the upper band into HVNs.
Position (1D–1W)
Context first: A persistent green weekly channel is constructive; a persistent red is distributive.
Patience: Wait for midline retests at higher-TF levels rather than chasing outer-band prints.
Entries, exits, and risk (keep it simple)
Continuation entry (trend):
Color already green/red.
Price pulls back to FRAMA midline (or shallowly toward it) and holds.
Take the trend side.
Stop: beyond the opposite side of the midline or behind local structure.
Targets: your Volume Profile HVN/POC or prior swing, not the band alone.
Breakout entry:
Channel had tightened; price breaks a key level.
Color flips green/red and the first retest holds.
Enter with the break.
Avoid: breaks that flip color but immediately white-flip on the next bar.
Mean-reversion entry (balance):
Color white and channel tight.
At a VP edge (VAL/VAH), fade outer band → midline.
Stop: just outside the band; Exit: at midline/POC.
Settings that actually matter (and how to tune them)
Length (N) — default 26
Controls how FRAMA “reads” structure.
Shorter (14–20): faster, more responsive (good for scalps/intraday), more flips in chop.
Longer (30–40): steadier (good for swings/position), slower to acknowledge new trends.
Bands Distance — default 1.5
Scales the channel width.
If you’re constantly tagging bands, increase slightly (1.7–2.0).
If nothing ever reaches the band, decrease (1.2–1.4) to make context meaningful.
Color Candles — on/off
Great for quick regime reads. If your chart feels too busy, leave bands colored and turn candle coloring off.
Warm-up note: FRAMA references N bars. Right after switching timeframes or symbols, give it N–2N bars to settle before you judge the current state.
(You may see an input named “Signals Data” in this version; it’s reserved for future enhancements.)
What to look for (pattern cheat sheet)
Walk-the-band: After a green/red flip, price hugs the outer band while the midline slopes. Ride pullbacks to the midline, don’t fade the band.
Squeeze → Expansion: Channel pinches, then color flips and bands widen—that’s the move. The first midline retest is your best entry.
False break tell: Brief color flip to green/red that immediately reverts to white on the next bar—skip chasing; plan for a reclaim.
Midline reclaims: In chop, repeated white↔green/white↔red flips say “mean reversion”; stay tactical and target the midline/POC.
Pairing FRAMA Channel with other tools
Cumulative Volume Delta v1 (CVDv1):
FRAMA tells you trend/mean-reversion context; CVDv1 tells you flow quality.
Breakout quality: FRAMA flips green and CVDv1 ALIGN = OK, Imbalance strong, Absorption ≠ red → higher odds the break sticks.
If Absorption is red on a FRAMA green flip, do not chase—wait for retest or look for a fail/reclaim.
Volume Profile v3.2:
Use VAH/VAL/LVNs/POC for where.
Green + VAL retest → rotate toward POC/HVN.
Red + VAH rejection → rotate back to POC.
LVN + green flip → expect fast travel toward the next HVN; set targets there.
Anchored VWAP :
Treat AVWAP as fair-value rails.
AVWAP reclaim + FRAMA green → excellent trend-resume entry.
AVWAP rejection + FRAMA red → high-quality short; use midline as your risk guide.
Common pitfalls this helps you avoid
Chasing every poke: FRAMA’s white → green/red state change helps you wait for confirmation (or a retest) instead of reacting to the first wick.
Fading a real trend: A sloped midline with price walking the band is telling you not to fight it.
Stops too tight: In expansion, give the trade room to the midline or local structure, not just inside the channel.
Practical defaults to start with
Length: 26
Bands Distance: 1.5
Color Candles: on (turn off if your chart is busy)
Timeframes: works out of the box on 15m–4H; for 1–5m try Length=20; for daily swings try Length=34–40.
Open source & disclaimer
This indicator is published open source so traders can learn, tweak, and build rules they trust. No tool guarantees outcomes; risk management is essential.
Disclaimer — Not Financial Advice.
The “FRAMA Channel ” indicator and this description are provided for educational purposes only and do not constitute financial or investment advice. Trading involves risk, including possible loss of capital. makes no warranties and assumes no responsibility for any trading decisions or outcomes resulting from the use of this script. Past performance is not indicative of future results.
Use FRAMA Channel for context (trend vs balance, squeeze vs expansion), Volume Profile v3.2 and Anchored VWAP for locations, and CVDv1 for flow quality. That trio keeps your trades selective and your rules consistent on any timeframe.
Candle Channel█ OVERVIEW
The "Candle Channel" indicator is a versatile technical analysis tool that plots a price channel based on the Simple Moving Average (SMA) of candlestick midpoints. The channel bands, calculated based on candlestick volatility, form dynamic support and resistance levels that adapt to price movements. The script generates signals for reversals from the bands and SMA breakouts, making it useful for both short-term and long-term traders. By adjusting the SMA length, the channel can vary in nature—from a wide channel encapsulating price movement to narrower support/resistance or trend-following bands. The channel width can be further customized using a scaling parameter, allowing adaptation to different trading styles and markets.
█ MECHANISM
Band Calculation
The indicator is based on the following calculations:
Candlestick Midpoint: Calculated as the arithmetic average of the candle’s high and low prices: (high + low) / 2.
Simple Moving Average (SMA): The average of candlestick midpoints over a specified length (default: 20 candles), forming the channel’s centerline.
Average Candle Height: Calculated as the average difference between the high and low prices (high - low) over the same SMA length, serving as a measure of market volatility.
Band Scaling: The user specifies a percentage of the average candle height (default: 200%), which is multiplied by the average height to create an offset. The upper band is SMA + offset, and the lower band is SMA - offset.Example: For an average candle height of 10 points and 200% scaling, the offset is 20 points, meaning the bands are ±20 points from the SMA.
Channel Characteristics: The SMA length determines the channel’s dynamics. Shorter SMA values (10–30) create a wide channel that contains price movement, ideal for scalping or short-term trading. Longer SMA values (above 30, e.g., 50–100) transform the channel into narrower support/resistance or trend-following bands, suitable for longer-term analysis. Band scaling further adjusts the channel width to match market volatility.
Signals
Reversal from Bands: Signals are generated when the price closes outside the band (above the upper or below the lower) and then returns to the channel, indicating a potential trend reversal.
SMA Breakout: Signals are generated when the price crosses the SMA upward (bullish signal) or downward (bearish signal), suggesting potential trend changes.
Visualization
Centerline: The SMA of candlestick midpoints, displayed as a thin line.
Channel Bands: Upper and lower channel boundaries, with customizable colors.
Fill: Options include a gradient (smooth color transition between bands) or solid color. The fill can also be disabled for greater clarity.
█ FEATURES AND SETTINGS
SMA Length: Determines the moving average period (default: 20). Values of 10–30 are suitable for a wide channel containing price movement, ideal for short-term timeframes. Longer values (e.g., 50–100) create narrower support/resistance or trend-following bands, better suited for higher timeframes.
Band Scaling: Percentage of the average candle height (default: 200%). Adjusts the channel width to match market volatility—smaller values (e.g., 50–100%) for narrower bands, larger values (e.g., 200–300%) for wider channels.
Fill Type: Gradient, solid, or no fill, allowing customization to user preferences.
Colors: Options to change the colors of bands, fill, and signals for better readability.
Signals: Options to enable/disable reversal signals from bands and SMA breakout signals.
█ HOW TO USE
Add the script to your chart in TradingView by clicking "Add to Chart" in the Pine Editor.
Adjust input parameters in the script settings:
SMA Length: Set to 10–30 for a wide channel containing price movement, suitable for scalping or short-term trading. Set above 30 (e.g., 50–100) for narrower support/resistance or trend-following bands.
Band Scaling: Adjust the channel width to market volatility. Smaller values (50–100%) for tighter support/resistance bands, larger values (200–300%) for wider channels containing price movement.
Fill Type and Colors: Choose a gradient for aesthetics or a solid fill for clarity.
Analyze signals:
Reversal Signals: Triangles above (bearish) or below (bullish) candles indicate potential reversal points.
SMA Breakout Signals: Circles above (bearish) or below (bullish) candles indicate trend changes.
Test the indicator on different instruments and timeframes to find optimal settings for your trading style.
█ LIMITATIONS
The indicator may generate false signals in highly volatile or consolidating markets.
On low-liquidity charts (e.g., exotic currency pairs), the bands may be less reliable.
Effectiveness depends on properly matching parameters to the market and timeframe.
Multi Scanner Plot & Table V1Here's how to interpret each column in the table:
Price vs MAs:
What it shows: Where the current price is relative to the short-term (e.g., 20-period) and long-term (e.g., 50-period) Simple Moving Averages (SMAs) calculated on your current chart's timeframe.
Interpretation:
Above Both (Green background): Price is above both the short and long MAs. Generally considered a bullish sign for the current trend.
Below Both (Red background): Price is below both MAs. Generally considered a bearish sign.
Mixed (Gray background): Price is between the two MAs (e.g., above the short but below the long, or vice-versa). Indicates indecision or a potential trend change.
RSI Value:
What it shows: The actual numerical value of the Relative Strength Index (RSI) calculated on your current chart's timeframe.
Interpretation: Just the raw RSI number (e.g., 65.32). The background is always gray. You compare this value to standard overbought/oversold levels (like 70/30) or the levels defined in the script's inputs.
RSI Status:
What it shows: Interprets the RSI Value based on the Overbought/Oversold levels set in the script's inputs (default 70/30). Calculated on your current chart's timeframe.
Interpretation:
Overbought (Red background): RSI is above the overbought level (e.g., > 70). Suggests the asset might be due for a pullback or reversal downwards. Red indicates a potentially bearish condition.
Oversold (Green background): RSI is below the oversold level (e.g., < 30). Suggests the asset might be due for a bounce or reversal upwards. Green indicates a potentially bullish condition.
Neutral (Gray background): RSI is between the oversold and overbought levels.
Last Sig Price:
What it shows: The price level where the last "SIG NOW" Buy or Sell signal occurred on your current chart's timeframe.
Interpretation: Helps you see the entry price of the most recent short-term signal generated by this script. The background color matches the signal type: Green for the last Buy signal, Red for the last Sell signal. N/A if no signal has occurred yet.
SIG NOW:
What it shows: This is the main short-term signal generated by the script based on conditions on your current chart's timeframe. It combines the "Price vs MAs" status and specific RSI conditions (price must be above/below both MAs and RSI must be within a certain range defined in the inputs).
Interpretation:
BUY (Green background): The specific buy conditions are met right now. (Price above both MAs AND RSI is strong but not necessarily overbought).
SELL (Red background): The specific sell conditions are met right now. (Price below both MAs AND RSI is weak but not necessarily oversold).
NEUTRAL (Gray background): Neither the Buy nor the Sell conditions are currently met.
ALERT:
What it shows: Flags unusual volume activity on the current bar compared to the recent average volume (calculated on your current chart's timeframe).
Interpretation:
SPIKE (Yellow background, black text): Current volume is significantly higher than the recent average (defined by the Volume Spike Multiplier). Can indicate strong interest or a potential climax.
DUMP (Purple background): Current volume is significantly lower than the recent average (defined by the Volume Dump Multiplier). Can indicate fading interest.
NONE (Gray background): Volume is within the normal range for the lookback period.
SD$:
What it shows: The price level where the last Volume Spike or Dump occurred on your current chart's timeframe.
Interpretation: Shows the price associated with the most recent significant volume event. The background color indicates the type of the last event: Green if the last event was a Spike, Red if the last event was a Dump. N/A if no Spike/Dump has occurred yet.
BB Value (%B):
What it shows: This relates to Bollinger Bands, but specifically calculated on a Higher Timeframe (HTF) that you can set in the inputs (e.g., Daily BBs while viewing an Hourly chart). It shows the Bollinger Band Percent B (%B) value for that HTF. %B measures where the HTF closing price is relative to the HTF upper and lower bands.
Interpretation:
Value > 1: HTF price closed above the HTF upper Bollinger Band.
Value < 0: HTF price closed below the HTF lower Bollinger Band.
Value between 0 and 1: HTF price closed within the HTF Bollinger Bands (e.g., 0.5 is exactly on the middle band).
The background is always gray.
LTS (Long Term Signal):
What it shows: A signal derived only from the Higher Timeframe (HTF) Bollinger Bands.
Interpretation:
BUY (Green background): The HTF price closed above the HTF upper Bollinger Band (see BB Value > 1). Considered a strong bullish signal from the higher timeframe perspective.
SELL (Red background): The HTF price closed below the HTF lower Bollinger Band (see BB Value < 0). Considered a strong bearish signal from the higher timeframe perspective.
NEUTRAL (Gray background): The HTF price closed within the HTF Bollinger Bands.
How to Understand Bollinger Bands and Signals in this Context:
Bollinger Bands are primarily used for the Long Term Signal (LTS) column. This script calculates BBs on a higher timeframe (you choose which one, or it defaults to the chart's timeframe if left blank).
The "LTS" signal triggers:
A BUY when the price on that higher timeframe closes above its upper Bollinger Band. This often indicates strong momentum or a potential breakout.
A SELL when the price on that higher timeframe closes below its lower Bollinger Band. This often indicates strong negative momentum or a potential breakdown.
The "BB Value" column gives you the raw %B number from that same higher timeframe, showing you exactly where the price is relative to the bands (is it just barely above/below, or way outside?).
The script does not directly use Bollinger Bands from the current chart timeframe for the "SIG NOW" or other table signals. The main short-term signals ("SIG NOW") rely on Moving Averages and RSI on the current timeframe. The LTS provides a longer-term perspective using HTF Bollinger Bands.
In summary: Look at the table to quickly gauge:
Short-term trend (Price vs MAs).
Short-term momentum (RSI Status, SIG NOW).
Recent short-term entry points (Last Sig Price).
Current volume anomalies (ALERT).
Long-term strength/weakness based on HTF Bollinger Bands (LTS, BB Value).
Combine these pieces of information to get a more rounded view of the current market conditions according to this specific script's logic.
MA Rainbow-AYNETSummary of the "MA Rainbow"
The 200 MA Rainbow script creates a visually appealing representation of multiple moving averages (MAs) with varying lengths and colors to provide insights into price trends and market momentum.
Key Features:
Base Moving Average:
A starting point (ma_length, default 200) is used as the foundation for all other bands.
Rainbow Bands:
The script generates multiple moving averages (bands) with increasing lengths, spaced by a user-defined band_spacing multiplier.
The number of bands is controlled by rainbow_bands, allowing up to 7 bands.
Moving Average Types:
Users can select the MA type: Simple (SMA), Exponential (EMA), or Weighted (WMA).
Dynamic Colors:
Each band is assigned a unique color from a predefined rainbow palette, making the chart visually distinct.
Inputs for Customization:
ma_length: Adjust the base period of the moving average.
rainbow_bands: Set the number of bands to display.
band_spacing: Control the spread between bands.
How It Works:
Precomputing Bands:
Each band’s length is calculated based on the base length (ma_length) and a multiplier (band_spacing).
For example, if ma_length = 200 and band_spacing = 0.2, the lengths of the first 3 bands will be:
Band 1: 200
Band 2: 240
Band 3: 280
Global Plotting:
Each band’s moving average is precomputed using the selected type (SMA, EMA, or WMA).
Bands are plotted globally to avoid scope issues, ensuring compatibility with Pine Script rules.
Color Cycling:
Colors are assigned dynamically from a rainbow palette (red, orange, yellow, green, blue, purple, teal).
Use Case:
The 200 MA Rainbow helps traders:
Visualize market trends with multiple layers of moving averages.
Identify areas of support and resistance.
Gauge momentum through the spread and alignment of bands.
Customization:
Users can:
Change the base moving average length (ma_length).
Adjust the number of bands (rainbow_bands).
Control the spread between bands with band_spacing.
Select the moving average type (SMA, EMA, WMA).
Application:
Copy the script into the Pine Editor in TradingView.
Apply it to your chart to observe the Rainbow MA visualization.
Adjust inputs to match your trading style or strategy.
This script is a versatile tool for both beginner and advanced traders, providing a colorful way to track price trends and market conditions. 🌈
Mean-Reversion Indicator_V2_SamleeOverview
This is the second version of my mean reversion indicator. It combines a moving average with adaptive standard deviation bands to detect when the price deviates significantly from its mean. The script provides automatic entry/exit signals, real-time PnL tracking, and shaded trade zones to make mean reversion trading more intuitive.
Core Logic
Mean benchmark: Simple Moving Average (MA).
Volatility bands: Standard deviation of the spread (close − MA) defines upper and lower bands.
Trading rules:
Price breaks below the lower band → Enter Long
Price breaks above the upper band → Enter Short
Price reverts to MA → Exit position
What’s different vs. classic Bollinger/Keltner
Bandwidth is based on the standard deviation of the price–MA spread, not raw closing prices.
Entry signals use previous-bar confirmation to reduce intrabar noise.
Exit rule is a mean-touch condition, rather than fixed profit/loss targets.
Enhanced visualization:
A shaded box dynamically shows the distance between entry and current/exit price, making it easy to see profit/loss zones over the holding period.
Instant PnL labels display current position side (Long/Short/Flat) and live profit/loss in both pips and %.
Entry and exit points are clearly marked on the chart with labels and exact prices.
These visualization tools go beyond what most indicators provide, giving traders a clearer, more practical view of trade evolution.
Key Features
Automatic detection of position status (Long / Short / Flat).
Chart labels for entries (“Entry”) and exits (“Exit”).
Real-time floating PnL calculation in both pips and %.
Info panel (top-right) showing entry price, current price, position side, and PnL.
Dynamic shading between entry and current/exit price to visualize profit/loss zones.
Usage Notes & Risk
Mean reversion may underperform in strong trending markets; parameters (len_ma, len_std, mult) should be validated per instrument and timeframe.
Works best on relatively stable, mean-reverting pairs (e.g., AUDNZD).
Risk management is essential: use independent stop-loss rules (e.g., limit risk to 1–2% of equity per trade).
This script is provided for educational purposes only and is not financial advice.
Volume MAs Oscillator | Lyro RSVolume MAs Oscillator | Lyro RS
Overview
The Volume MAs Oscillator is a powerful volume‑adjusted momentum tool that combines custom‑weighted moving averages on volume‑weighted price with smoothed deviation bands. It offers dynamic insights into trend direction, overbought/oversold conditions, and relative valuation — all within a single indicator
Key Features
Volume‑Adjusted Moving Averages: Moving averages can be volume‑weighted using the following formula: a moving average of (Price × Volume) divided by a moving average of Volume. This formula is applied across more than 14 different moving averages; however, it is not used with the VWMA, as VWMA is inherently a volume-weighted moving average.
Percentage Oscillator: Displays the normalized difference: (source – MA) / MA * 100, centered around zero for easy interpretation of strength and direction.
Deviation Bands: Builds upper and lower bands from standard deviation of the oscillator over a selected lookback, with distinct positive/negative multipliers and optional smoothing to reduce noise.
Inputs: Band Length, Band Smoothing, Positive Band Multiplier, Negative Band Multiplier.
Multi‑Mode Signal System:
1. Trend Mode – Colors oscillator according to breaks above (bullish) or below (bearish) respective bands.
2. Reversion Mode – Inverses color logic: signals overextensions beyond bands as reversion opportunities, greys inside the bands.
3. Valuation Mode – Applies a gradient color scale (UpC ⇄ DnC) to reflect relative valuation strength.
Customizable Visuals: Select from 5 pre‑set palettes—Classic, Mystic, Major Themes, Accented, Royal—or define your own custom bullish/bearish colors.
Chart enhancements include color‑coded oscillator line, deviation bands, glow‑effect midline at zero, background shading and candlestick/bar coloring aligned to signal mode.
Built‑In Signals: Automatically plots ▲ oversold and ▼ overbought markers upon crosses of lower/upper bands (in trend or reversion modes), enhancing signal clarity.
How It Works
MA Calculation – Applies the selected MA type to price × volume (normalized by MA of volume) or direct VWMA.
Oscillator Output – Calculates the % difference of source vs. derived MA.
Band Construction – Computes rolling standard deviation; applies user‑defined multipliers; smooths bands with exponential blending.
Mode-Dependent Coloring & Signals –
• Trend: Highlights strength trends via band cross coloring.
• Reversion: Flags extremes beyond bands as potential pullbacks.
• Valuation: Uses gradient to reflect oscillator’s position relative to recent range.
Signal Markers – Deploys arrows and color rules to flag overbought (▼) or oversold (▲) conditions when bands are breached.
Practical Use
Trend Confirmation – In Trend Mode, use upward price_diff cross above upper band as bullish; downward cross below lower band as bearish.
Mean Reversion – In Reversion Mode, fading extremes beyond bands may precede a retracement.
Relative Valuation – Valuation Mode shines when assessing how extended price_diff is, with gradient colors indicating valuation zones.
Bars/candles color‑coded to oscillator state boosts clarity of market tone and allows for rapid visual scanning.
Customization
Adjust MA type/length to tune responsiveness vs. smoothing.
Configure band settings for volatility sensitivity.
Toggle between signal modes for trend-following or reversion strategies.
Stylish visuals: pick or customize color schemes to match your chart setup.
⚠️Disclaimer
This indicator is a tool for technical analysis and does not provide guaranteed results. It should be used in conjunction with other analysis methods and proper risk management practices. The creators of this indicator are not responsible for any financial decisions made based on its signals.
Dynamic Range Filter with Trend Candlesticks (Zeiierman)█ Overview
Dynamic Range Filter with Trend Candlesticks (Zeiierman) is a volatility-responsive trend engine that adapts in real-time to market structure, offering a clean and intelligent visualization of directional bias. It blends dynamic range calculation with customizable smoothing techniques and layered trend confirmation logic, making it ideal for traders who rely on clear trend direction, structural range analysis, and momentum-based candlestick signals.
By measuring scaled volatility over configurable lengths and applying advanced moving average techniques, this indicator filters out market noise while preserving true directional intent. Complementing this, a dual-trend system (range-based and candle-based) enhances clarity and responsiveness, particularly during shifting market conditions.
█ How It Works
⚪ Scaled Volatility Band Calculation
At the core lies a volatility engine that constructs adaptive range bands around price using smoothed high/low calculations. The bands are dynamically adjusted using:
High/Low Smoothing – Applies a moving average to the raw high and low data before calculating the range.
Scaled Range Volatility – A 2.618 multiplier scales the distance between smoothed highs and lows, forming a responsive volatility envelope.
Band Multiplier – Controls how wide the upper/lower range bands extend from the mean.
This filtering process minimizes false signals and highlights only structurally meaningful moves.
⚪ Multi-Type Smoothing Engine
Users can choose from a wide array of smoothing algorithms for trend construction, including:
HMA (default), SMA, EMA, RMA
KAMA – Adapts to market volatility using efficiency ratios.
VIDYA – Momentum-sensitive smoothing using CMO logic.
FRAMA – Dynamically adjusts to fractal dimension in price.
Super Smoother – Ideal for eliminating aliasing in range signals.
This provides the trader with fine-tuned control over reactivity vs. smoothness.
⚪ Trend Detection (Dual Engine)
The indicator includes two independent trend tracking systems:
Main Trend Filter – Based on adaptive volatility band shifts.
Candle Trend Filter – A second-tier confirmation using smoothed candle data, ideal for directional candles and confirmation entries.
█ How to Use
⚪ Trend Confirmation
Use the Trend Line and colored candlesticks for high-probability entries in the trend direction. The more trend layers that align, the higher the confidence.
⚪ Reversal Zones
When the price reaches the outer bands or fails to break them, look for candle color shifts or a crossover in the range to anticipate possible reversals or consolidations.
█ Settings
Scaled Volatility Length – Controls the lookback used to stabilize the base volatility band.
MA Type & Length – Choose and fine-tune the smoothing method (HMA, EMA, KAMA, etc.)
High/Low Smoother – Pre-smoothing for structural high/low banding.
Band Multiplier – Adjusts the width of the dynamic bands.
Trend Length (Candles) – Length used for candle-based trend confirmation.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. 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.
Ultimate Volatility CloudUltimate Volatility Cloud
The Ultimate Volatility Cloud is a powerful and highly customizable indicator designed to help traders visualize market volatility, easily identify trend, and overextended moves in price with adaptive bands. It combines the strengths of the Arnaud Legoux Moving Average, Kaufman's Adaptive Moving Average, ATR Channels, and Standard Deviation bands, offering multiple pre-configured profiles and extensive customization options.
Key Features:
Dynamic Volatility Bands: The indicator plots multiple layers of volatility bands around a central basis line, providing a comprehensive view of price deviation.
Hybrid Band Calculation: Bands are a sophisticated blend of Keltner Channels, KAMA ATR Channels and Standard Deviation, allowing for a nuanced representation of volatility.
Adaptive Smoothing: Bands are smoothed using either Exponential Moving Average (EMA) or Kaufman's Adaptive Moving Average (KAMA) based on the selected profile, ensuring responsiveness tailored to market conditions.
Layered Fills: The cloud uses distinct color fills for different volatility levels, making it easy to visually interpret price action relative to its typical range.
Customizable Color Themes: Choose from a variety of pre-set color themes, including "Rainbow," "Wild," and "Monochrome," or stick with classic options to suit your visual preference.
Optional Basis Line Plots: Display the EMA or KAMA basis lines (used in Keltner Channel calculations) separately on the chart for additional analysis.
Understanding the Profiles:
The indicator comes with several pre-configured "Settings Profiles" that adjust the internal parameters (Keltner Channel/KAMA Channel/Standard Deviation band blend, and band smoothing) to suit different trading styles or market environments.
1. Standard Profile:
Blend: 60% Keltner Channel, 40% Standard Deviation.
Smoothing: EMA smoothing of 3 periods.
Purpose: A balanced, general-purpose profile suitable for a wide range of market conditions. It offers a good blend of trend following and volatility awareness.
2. Responsive Profile:
Blend: 40% Keltner Channel, 60% Standard Deviation.
Smoothing: EMA smoothing of 2 period.
Purpose: Designed for traders who need quick reactions to price changes. The higher Standard Deviation blend and minimal smoothing make it highly sensitive to immediate volatility shifts, ideal for short-term analysis or identifying early moves.
3. Ranging Market Profile:
Blend: 80% KAMA ATR Channel, 20% Standard Deviation.
Smoothing: KAMA smoothing.
Purpose: Optimized for sideways or consolidating markets. By utilizing KAMA-based ATR bands and KAMA for band smoothing, this profile adapts its responsiveness to reduce whipsaws in choppy conditions, providing clearer boundaries for range-bound price action.
4. Trend Following Profile:
Blend: 90% Keltner Channel, 10% Standard Deviation.
Smoothing: EMA smoothing of 5 periods.
Purpose: Tailored for riding strong trends. The heavy emphasis on the Keltner Channel and slightly smoother bands help filter out minor fluctuations, allowing traders to focus on the dominant directional movement.
5. Conservative Profile:
Blend: 65% KAMA ATR Channel, 35% Standard Deviation.
Smoothing: EMA smoothing of 10 periods.
Purpose: Aims to provide more filtered signals and reduce noise. The KAMA basis for the Keltner Channel combined with a longer EMA smoothing period offers a slower, more confirmed view of volatility, suitable for traders seeking higher conviction entries or exits.
Example of the Ranging Market Profile
How to Use:
The volatility cloud can be interpreted in various ways:
Price within the inner bands: May indicate consolidation or a period of lower volatility.
Price pushing into outer bands: Suggests increasing volatility and potential for a strong move.
Price breaking out of extreme outer bands: Can signal significant momentum and the start or continuation of a strong trend.
Cloud expansion/contraction: Visually indicates periods of increasing or decreasing market energy.
Experiment with different profiles and settings to find the combination that best suits your trading strategy and the instruments you trade.
Lowess Channel + (RSI) [ChartPrime]The Lowess Channel + (RSI) indicator applies the LOWESS (Locally Weighted Scatterplot Smoothing) algorithm to filter price fluctuations and construct a dynamic channel. LOWESS is a non-parametric regression method that smooths noisy data by fitting weighted linear regressions at localized segments. This technique is widely used in statistical analysis to reveal trends while preserving data structure.
In this indicator, the LOWESS algorithm is used to create a central trend line and deviation-based bands. The midline changes color based on trend direction, and diamonds are plotted when a trend shift occurs. Additionally, an RSI gauge is positioned at the end of the channel to display the current RSI level in relation to the price bands.
lowess_smooth(src, length, bandwidth) =>
sum_weights = 0.0
sum_weighted_y = 0.0
sum_weighted_xy = 0.0
sum_weighted_x2 = 0.0
sum_weighted_x = 0.0
for i = 0 to length - 1
x = float(i)
weight = math.exp(-0.5 * (x / bandwidth) * (x / bandwidth))
y = nz(src , 0)
sum_weights := sum_weights + weight
sum_weighted_x := sum_weighted_x + weight * x
sum_weighted_y := sum_weighted_y + weight * y
sum_weighted_xy := sum_weighted_xy + weight * x * y
sum_weighted_x2 := sum_weighted_x2 + weight * x * x
mean_x = sum_weighted_x / sum_weights
mean_y = sum_weighted_y / sum_weights
beta = (sum_weighted_xy - mean_x * mean_y * sum_weights) / (sum_weighted_x2 - mean_x * mean_x * sum_weights)
alpha = mean_y - beta * mean_x
alpha + beta * float(length / 2) // Centered smoothing
⯁ KEY FEATURES
LOWESS Price Filtering – Smooths price fluctuations to reveal the underlying trend with minimal lag.
Dynamic Trend Coloring – The midline changes color based on trend direction (e.g., bullish or bearish).
Trend Shift Diamonds – Marks points where the midline color changes, indicating a possible trend shift.
Deviation-Based Bands – Expands above and below the midline using ATR-based multipliers for volatility tracking.
RSI Gauge Display – A vertical gauge at the right side of the chart shows the current RSI level relative to the price channel.
Fully Customizable – Users can adjust LOWESS length, band width, colors, and enable or disable the RSI gauge and adjust RSIlength.
⯁ HOW TO USE
Use the LOWESS midline as a trend filter —bullish when green, bearish when purple.
Watch for trend shift diamonds as potential entry or exit signals.
Utilize the price bands to gauge overbought and oversold zones based on volatility.
Monitor the RSI gauge to confirm trend strength—high RSI near upper bands suggests overbought conditions, while low RSI near lower bands indicates oversold conditions.
⯁ CONCLUSION
The Lowess Channel + (RSI) indicator offers a powerful way to analyze market trends by applying a statistically robust smoothing algorithm. Unlike traditional moving averages, LOWESS filtering provides a flexible, responsive trendline that adapts to price movements. The integrated RSI gauge enhances decision-making by displaying momentum conditions alongside trend dynamics. Whether used for trend-following or mean reversion strategies, this indicator provides traders with a well-rounded perspective on market behavior.
Median Volume Weighted DeviationMVWD (Median Volume Weighted Deviation)
The Median Volume-Weighted Deviation is a technical trend following indicator that overlays dynamic bands on the price chart, centered around a Volume Weighted Average Price (VWAP). By incorporating volume-weighted standard deviation and its median, it identifies potential overbought and oversold conditions, generating buy and sell signals based on price interactions with the bands. The fill color between the bands visually reflects the current signal, enhancing market sentiment analysis.
How it Works
VWAP Calculation: Computes the Volume-Weighted Average Price over a specific lookback period (n), emphasizing price levels with higher volume.
Volume Weighted Standard Deviation: Measures price dispersion around the VWAP, weighted by volume, over the same period.
Median Standard Deviation: Applies a median filter over (m) periods to smooth the stand deviation, reducing noise in volatility estimates.
Bands: Constructs upper and lower bands by adding and subtracting a multiplier (k) times the median standard deviation from the VWAP
Signals:
Buy Signal: Triggers when the closing price crosses above the upper band.
Sell Signal: Triggers when the closing price crosses below the lower band.
Inputs
Lookback (n): Number of periods for the VWAP and standard deviation calculations. Default is set to 14.
Median Standard Deviation (m): Periods for the median standard deviation. Default is set to 2.
Standard Deviation Multiplier (k): Multiplier to adjust band width. Default is set to 1.7 with a step of 0.1.
Customization
Increase the Lookback (n) for a smoother VWAP and broader perspective, or decrease the value for higher sensitivity.
Adjust Median Standard Deviation (m) to control the smoothness of the standard deviation filter.
Modify the multiplier (k) to widen or narrow the bands based on the market volatility preferences.
Mean Reversion Cloud (Ornstein-Uhlenbeck) // AlgoFyreThe Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator detects mean-reversion opportunities by applying the Ornstein-Uhlenbeck process. It calculates a dynamic mean using an Exponential Weighted Moving Average, surrounded by volatility bands, signaling potential buy/sell points when prices deviate.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Adaptive Mean Calculation
🔸Volatility-Based Cloud
🔸Speed of Reversion (θ)
🔶 FUNCTIONALITY
🔸Dynamic Mean and Volatility Bands
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Visualization via Table and Plotshapes
🞘 Table Overview
🞘 Plotshapes Explanation
🞘 Code extract
🔶 INSTRUCTIONS
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅
🔶 ORIGINALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) is a unique indicator that applies the Ornstein-Uhlenbeck stochastic process to identify mean-reverting behavior in asset prices. Unlike traditional moving average-based indicators, this model uses an Exponentially Weighted Moving Average (EWMA) to calculate the long-term mean, dynamically adjusting to recent price movements while still considering all historical data. It also incorporates volatility bands, providing a "cloud" that visually highlights overbought or oversold conditions. By calculating the speed of mean reversion (θ) through the autocorrelation of log returns, this indicator offers traders a more nuanced and mathematically robust tool for identifying mean-reversion opportunities. These innovations make it especially useful for markets that exhibit range-bound characteristics, offering timely buy and sell signals based on statistical deviations from the mean.
🔸Adaptive Mean Calculation Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Mean Reversion Cloud uses an Exponentially Weighted Moving Average (EWMA), which adapts to price movements by dynamically adjusting its calculation, offering a more responsive mean.
🔸Volatility-Based Cloud Unlike simple moving averages that only plot a single line, the Mean Reversion Cloud surrounds the dynamic mean with volatility bands. These bands, based on standard deviations, provide traders with a visual cue of when prices are statistically likely to revert, highlighting potential reversal zones.
🔸Speed of Reversion (θ) The indicator goes beyond price averages by calculating the speed at which the price reverts to the mean (θ), using the autocorrelation of log returns. This gives traders an additional tool for estimating the likelihood and timing of mean reversion, making the signals more reliable in practice.
🔶 FUNCTIONALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator is designed to detect potential mean-reversion opportunities in asset prices by applying the Ornstein-Uhlenbeck stochastic process. It calculates a dynamic mean through the Exponentially Weighted Moving Average (EWMA) and plots volatility bands based on the standard deviation of the asset's price over a specified period. These bands create a "cloud" that represents expected price fluctuations, helping traders to identify overbought or oversold conditions. By calculating the speed of reversion (θ) from the autocorrelation of log returns, the indicator offers a more refined way of assessing how quickly prices may revert to the mean. Additionally, the inclusion of volatility provides a comprehensive view of market conditions, allowing for more accurate buy and sell signals.
Let's dive into the details:
🔸Dynamic Mean and Volatility Bands The dynamic mean (μ) is calculated using the EWMA, giving more weight to recent prices but considering all historical data. This process closely resembles the Ornstein-Uhlenbeck (OU) process, which models the tendency of a stochastic variable (such as price) to revert to its mean over time. Volatility bands are plotted around the mean using standard deviation, forming the "cloud" that signals overbought or oversold conditions. The cloud adapts dynamically to price fluctuations and market volatility, making it a versatile tool for mean-reversion strategies. 🞘 How it works Step one: Calculate the dynamic mean (μ) The Ornstein-Uhlenbeck process describes how a variable, such as an asset's price, tends to revert to a long-term mean while subject to random fluctuations. In this indicator, the EWMA is used to compute the dynamic mean (μ), mimicking the mean-reverting behavior of the OU process. Use the EWMA formula to compute a weighted mean that adjusts to recent price movements. Assign exponentially decreasing weights to older data while giving more emphasis to current prices. Step two: Plot volatility bands Calculate the standard deviation of the price over a user-defined period to determine market volatility. Position the upper and lower bands around the mean by adding and subtracting a multiple of the standard deviation. 🞘 How to calculate Exponential Weighted Moving Average (EWMA)
The EWMA dynamically adjusts to recent price movements:
mu_t = lambda * mu_{t-1} + (1 - lambda) * P_t
Where mu_t is the mean at time t, lambda is the decay factor, and P_t is the price at time t. The higher the decay factor, the more weight is given to recent data.
Autocorrelation (ρ) and Standard Deviation (σ)
To measure mean reversion speed and volatility: rho = correlation(log(close), log(close ), length) Where rho is the autocorrelation of log returns over a specified period.
To calculate volatility:
sigma = stdev(close, length)
Where sigma is the standard deviation of the asset's closing price over a specified length.
Upper and Lower Bands
The upper and lower bands are calculated as follows:
upper_band = mu + (threshold * sigma)
lower_band = mu - (threshold * sigma)
Where threshold is a multiplier for the standard deviation, usually set to 2. These bands represent the range within which the price is expected to fluctuate, based on current volatility and the mean.
🞘 Code extract // Calculate Returns
returns = math.log(close / close )
// Calculate Long-Term Mean (μ) using EWMA over the entire dataset
var float ewma_mu = na // Initialize ewma_mu as 'na'
ewma_mu := na(ewma_mu ) ? close : decay_factor * ewma_mu + (1 - decay_factor) * close
mu = ewma_mu
// Calculate Autocorrelation at Lag 1
rho1 = ta.correlation(returns, returns , corr_length)
// Ensure rho1 is within valid range to avoid errors
rho1 := na(rho1) or rho1 <= 0 ? 0.0001 : rho1
// Calculate Speed of Mean Reversion (θ)
theta = -math.log(rho1)
// Calculate Volatility (σ)
sigma = ta.stdev(close, corr_length)
// Calculate Upper and Lower Bands
upper_band = mu + threshold * sigma
lower_band = mu - threshold * sigma
🔸Visualization via Table and Plotshapes
The table shows key statistics such as the current value of the dynamic mean (μ), the number of times the price has crossed the upper or lower bands, and the consecutive number of bars that the price has remained in an overbought or oversold state.
Plotshapes (diamonds) are used to signal buy and sell opportunities. A green diamond below the price suggests a buy signal when the price crosses below the lower band, and a red diamond above the price indicates a sell signal when the price crosses above the upper band.
The table and plotshapes provide a comprehensive visualization, combining both statistical and actionable information to aid decision-making.
🞘 Code extract // Reset consecutive_bars when price crosses the mean
var consecutive_bars = 0
if (close < mu and close >= mu) or (close > mu and close <= mu)
consecutive_bars := 0
else if math.abs(deviation) > 0
consecutive_bars := math.min(consecutive_bars + 1, dev_length)
transparency = math.max(0, math.min(100, 100 - (consecutive_bars * 100 / dev_length)))
🔶 INSTRUCTIONS
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator can be set up by adding it to your TradingView chart and configuring parameters such as the decay factor, autocorrelation length, and volatility threshold to suit current market conditions. Look for price crossovers and deviations from the calculated mean for potential entry signals. Use the upper and lower bands as dynamic support/resistance levels for setting take profit and stop-loss orders. Combining this indicator with additional trend-following or momentum-based indicators can improve signal accuracy. Adjust settings for better mean-reversion detection and risk management.
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
Adding the Indicator to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Mean Reversion Cloud (Ornstein-Uhlenbeck)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator:
Open the indicator settings by clicking on the gear icon next to its name on the chart.
Decay Factor: Adjust the decay factor (λ) to control the responsiveness of the mean calculation. A higher value prioritizes recent data.
Autocorrelation Length: Set the autocorrelation length (θ) for calculating the speed of mean reversion. Longer lengths consider more historical data.
Threshold: Define the number of standard deviations for the upper and lower bands to determine how far price must deviate to trigger a signal.
Chart Setup:
Select the appropriate timeframe (e.g., 1-hour, daily) based on your trading strategy.
Consider using other indicators such as RSI or MACD to confirm buy and sell signals.
🞘 Understanding What to Look For on the Chart
Indicator Behavior:
Observe how the price interacts with the dynamic mean and volatility bands. The price staying within the bands suggests mean-reverting behavior, while crossing the bands signals potential entry points.
The indicator calculates overbought/oversold conditions based on deviation from the mean, highlighted by color-coded cloud areas on the chart.
Crossovers and Deviation:
Look for crossovers between the price and the mean (μ) or the bands. A bullish crossover occurs when the price crosses below the lower band, signaling a potential buying opportunity.
A bearish crossover occurs when the price crosses above the upper band, suggesting a potential sell signal.
Deviations from the mean indicate market extremes. A large deviation indicates that the price is far from the mean, suggesting a potential reversal.
Slope and Direction:
Pay attention to the slope of the mean (μ). A rising slope suggests bullish market conditions, while a declining slope signals a bearish market.
The steepness of the slope can indicate the strength of the mean-reversion trend.
🞘 Possible Entry Signals
Bullish Entry:
Crossover Entry: Enter a long position when the price crosses below the lower band with a positive deviation from the mean.
Confirmation Entry: Use additional indicators like RSI (above 50) or increasing volume to confirm the bullish signal.
Bearish Entry:
Crossover Entry: Enter a short position when the price crosses above the upper band with a negative deviation from the mean.
Confirmation Entry: Look for RSI (below 50) or decreasing volume to confirm the bearish signal.
Deviation Confirmation:
Enter trades when the deviation from the mean is significant, indicating that the price has strayed far from its expected value and is likely to revert.
🞘 Possible Take Profit Strategies
Static Take Profit Levels:
Set predefined take profit levels based on historical volatility, using the upper and lower bands as guides.
Place take profit orders near recent support/resistance levels, ensuring you're capitalizing on the mean-reversion behavior.
Trailing Stop Loss:
Use a trailing stop based on a percentage of the price deviation from the mean to lock in profits as the trend progresses.
Adjust the trailing stop dynamically along the calculated bands to protect profits as the price returns to the mean.
Deviation-Based Exits:
Exit when the deviation from the mean starts to decrease, signaling that the price is returning to its equilibrium.
🞘 Possible Stop-Loss Levels
Initial Stop Loss:
Place an initial stop loss outside the lower band (for long positions) or above the upper band (for short positions) to protect against excessive deviations.
Use a volatility-based buffer to avoid getting stopped out during normal price fluctuations.
Dynamic Stop Loss:
Move the stop loss closer to the mean as the price converges back towards equilibrium, reducing risk.
Adjust the stop loss dynamically along the bands to account for sudden market movements.
🞘 Additional Tips
Combine with Other Indicators:
Enhance your strategy by combining the Mean Reversion Cloud with momentum indicators like MACD, RSI, or Bollinger Bands to confirm market conditions.
Backtesting and Practice:
Backtest the indicator on historical data to understand how it performs in various market environments.
Practice using the indicator on a demo account before implementing it in live trading.
Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The indicator reacts to price data and might not account for news-driven events that can cause large deviations.
🔸Customize settings 🞘 Decay Factor (λ): Defines the weight assigned to recent price data in the calculation of the mean. A value closer to 1 places more emphasis on recent prices, while lower values create a smoother, more lagging mean.
🞘 Autocorrelation Length (θ): Sets the period for calculating the speed of mean reversion and volatility. Longer lengths capture more historical data, providing smoother calculations, while shorter lengths make the indicator more responsive.
🞘 Threshold (σ): Specifies the number of standard deviations used to create the upper and lower bands. Higher thresholds widen the bands, producing fewer signals, while lower thresholds tighten the bands for more frequent signals.
🞘 Max Gradient Length (γ): Determines the maximum number of consecutive bars for calculating the deviation gradient. This setting impacts the transparency of the plotted bands based on the length of deviation from the mean.
🔶 CONCLUSION
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator offers a sophisticated approach to identifying mean-reversion opportunities by applying the Ornstein-Uhlenbeck stochastic process. This dynamic indicator calculates a responsive mean using an Exponentially Weighted Moving Average (EWMA) and plots volatility-based bands to highlight overbought and oversold conditions. By incorporating advanced statistical measures like autocorrelation and standard deviation, traders can better assess market extremes and potential reversals. The indicator’s ability to adapt to price behavior makes it a versatile tool for traders focused on both short-term price deviations and longer-term mean-reversion strategies. With its unique blend of statistical rigor and visual clarity, the Mean Reversion Cloud provides an invaluable tool for understanding and capitalizing on market inefficiencies.
MTF BB+KC Avg
Bollinger Bands (BB) are a widely used technical analysis created by John Bollinger in the early 1980’s. Bollinger Bands consist of a band of three lines which are plotted in relation to instrument prices. The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (The type of trend line and period can be changed by the trader; however a 20 day moving average is by far the most popular). This indicator does not plot the middle line. The Upper and Lower Bands are used as a way to measure volatility by observing the relationship between the Bands and price. Typically the Upper and Lower Bands are set to two standard deviations away from the middle line, however the number of standard deviations can also be adjusted in the indicator.
Keltner Channels (KC) are banded lines similar to Bollinger Bands and Moving Average Envelopes. They consist of an Upper Envelope above a Middle Line (not plotted in this indicator) as well as a Lower Envelope below the Middle Line. The Middle Line is a moving average of price over a user-defined time period. Either a simple moving average or an exponential moving average are typically used. The Upper and Lower Envelopes are set a (user-defined multiple) of a range away from the Middle Line. This can be a multiple of the daily high/low range, or more commonly a multiple of the Average True Range.
This indicator is built on AVERAGING the BB and KC values for each bar, so you have an efficient metric of AVERAGE volatility. The indicator visualizes changes in volatility which is of course dynamic.
What to look for
High/Low Prices
One thing that must be understood about this indicator's plots is that it averages by adding BB levels to KC levels and dividing by 2. So the plots provide a relative definition of high and low from two very popular indicators. Prices are almost always within the upper and lower bands. Therefore, when prices move up near the upper or lower bands or even break through the band, many traders would see that price action as OVER-EXTENDED (either overbought or oversold, as applicable). This would preset a possible selling or buying opportunity.
Cycling Between Expansion and Contraction
Volatility can generally be seen as a cycle. Typically periods of time with low volatility and steady or sideways prices (known as contraction) are followed by period of expansion. Expansion is a period of time characterized by high volatility and moving prices. Periods of expansion are then generally followed by periods of contraction. It is a cycle in which traders can be better prepared to navigate by using Bollinger Bands because of the indicators ability to monitor ever changing volatility.
Walking the Bands
Of course, just like with any indicator, there are exceptions to every rule and plenty of examples where what is expected to happen, does not happen. Previously, it was mentioned that price breaking above the Upper Band or breaking below the Lower band could signify a selling or buying opportunity respectively. However this is not always the case. “Walking the Bands” can occur in either a strong uptrend or a strong downtrend.
During a strong uptrend, there may be repeated instances of price touching or breaking through the Upper Band. Each time that this occurs, it is not a sell signal, it is a result of the overall strength of the move. Likewise during a strong downtrend there may be repeated instances of price touching or breaking through the Lower Band. Each time that this occurs, it is not a buy signal, it is a result of the overall strength of the move.
Keep in mind that instances of “Walking the Bands” will only occur in strong, defined uptrends or downtrends.
Inputs
TimeFrame
You can select any timeframe froom 1 minute to 12 months for the bar measured.
Length of the internal moving averages
You can select the period of time to be used in calculating the moving averages which create the base for the Upper and Lower Bands. 20 days is the default.
Basis MA Type
Determines the type of Moving Average that is applied to the basis plot line. Default is SMA and you can select EMA.
Source
Determines what data from each bar will be used in calculations. Close is the default.
StdDev/Multiplier
The number of Standard Deviations (for BB) or Multiplier (for KC) away from the moving averages that the Upper and Lower Bands should be. 2 is the default value for each indicator.
2Mars - MA / BB / SuperTrend
The 2Mars strategy is a trading approach that aims to improve trading efficiency by incorporating several simple order opening tactics. These tactics include moving average crossovers, Bollinger Bands, and SuperTrend.
Entering a Position with the 2Mars Strategy:
Moving Average Crossover: This method considers the crossing of moving averages as a signal to enter a position.
Price Crossing Bollinger Bands: If the price crosses either the upper or lower Bollinger Band, it is seen as a signal to enter a position.
Price Crossing Moving Average: If the price crosses the moving average, it is also considered a signal to enter a position.
SuperTrend and Bars confirm:
The SuperTrend indicator is used to provide additional confirmation for entering positions and setting stop loss levels. "Bars confirm" is used only for entry to positions.
Moving Average Crossover Strategy:
A moving average crossover refers to the point on a chart where there is a crossover of the signal or fast moving average, above or below the basis or slow moving average. This strategy also uses moving averages for additional orders #3.
Basis Moving Average Length: Ratio * Multiplier
Signal Moving Average Length: Multiplier
Bollinger Bands:
Bollinger Bands consist of three bands: an upper band, a lower band, and a basis moving average. However, the 2Mars strategy incorporates multiple upper and lower levels for position entry and take profit.
Basis +/- StdDev * 0.618
Basis +/- StdDev * 1.618
Basis +/- StdDev * 2.618
Additional Orders:
Additional Order #1 and #2: closing price crosses above or below the Bollinger Bands.
Additional Order #3: closing price crosses above or below the basis or signal moving average.
Take Profit:
The strategy includes three levels for taking profits, which are based on the Bollinger Bands. Additionally, a percentage of the position can be chosen to close long or short positions.
Limit Orders:
The strategy allows for entering a position using a limit order. The calculation for the limit order involves the Average True Range (ATR) for a specific period.
For long positions: Low price - ATR * Multiplier
For short positions: High price + ATR * Multiplier
Stop Loss:
To manage risk, the strategy recommends using stop loss options. The stop loss is updated with each entry order and take-profit level 3. When using the SuperTrend Confirmation, the stop loss requires confirmation of a trend change. It allows for flexible adjustment of the stop loss when the trend changes.
There are three options for setting the stop loss:
1. ATR (Average True Range):
For long positions: Low price - ATR * Long multiplier
For short positions: High price + ATR * Short multiplier
2. SuperTrend + ATR:
For long positions: SuperTrend - ATR * Long multiplier
For short positions: SuperTrend + ATR * Short multiplier
3. StdDev:
For long positions: StdDev - ATR * Long multiplier
For short positions: StdDev + ATR * Short multiplier
Flexible Stop Loss:
There is also a flexible stop loss option for the ATR and StdDev methods. It is triggered when the SuperTrend or moving average trend changes unfavorably.
For long positions: Stop-loss price + (ATR * Long multiplier) * Multiplier
For short positions: Stop-loss price - (ATR * Short multiplier) * Multiplier
How configure:
Disable SuperTrend, take profit, stop loss, additional orders and begin setting up a strategy.
Pick soucre data
Number of bars for confirm
Pick up the ratio of the base moving average and the signal moving average.
Set up a SuperTrend
Time for set up of the Bollinger Bands and the take profit
And finaly set up of stop loss and limit orders
All done!
For OKX exchange:
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
Predictive Order Blocks [CryptoSea]The Predictive Order Blocks Indicator is a unique and innovative tool that enhances market analysis by identifying support and resistance blocks based on standard deviations from a median line. Unlike traditional indicators that rely solely on the close price, this indicator leverages the median line and standard deviations to form areas of interest, rather than targeting a single price point. This approach provides a more accurate representation of market structure, especially during periods of consolidation and expansion.
Key Features
Multi-Term Length Analysis: The indicator offers short, medium, and long-term settings, allowing traders to customise the analysis based on their preferred trading strategy and timeframe. This flexibility ensures that the tool is adaptable to various market conditions and trading styles.
Standard Deviation-Based Order Blocks: The core functionality of the indicator revolves around calculating standard deviations from a median line to form support and resistance blocks. These blocks provide a clearer and more reliable picture of market structure compared to single-point levels. By focusing on areas rather than exact price levels, the indicator helps traders identify zones where price is likely to react, leading to more informed trading decisions.
Dynamic Box Creation: The indicator dynamically creates breakout boxes based on user-selected standard deviation ranges. These boxes are formed at the start of market expansion following periods of consolidation. This feature is particularly useful because it highlights key levels where price is likely to retrace after breaking out, providing traders with actionable insights during market transitions.
Proximity-Based Gradient Colors: The indicator features gradient colors that change based on the price's proximity to the standard deviation bands. This visual aid helps traders quickly assess the current market condition and the potential significance of the support and resistance blocks.
Adaptive Display Options: To accommodate different trading preferences, the indicator includes options to toggle the display of the trend line (median line) and the standard deviation bands. This flexibility allows traders to customise their chart view to match their analysis style, whether they prefer a more clutter-free view or a detailed breakdown of market levels.
In the example below, the indicator shows the bands compressing during a period of consolidation, highlighting the potential for a breakout.
How it Works
Median Line Calculation: The indicator calculates the median line using a user-defined period. This line serves as the central reference point from which the standard deviations are calculated. By using the median line instead of just the close price, the indicator provides a more stable and reliable baseline for identifying support and resistance areas.
Standard Deviation Bands: Around the median line, the indicator calculates multiple standard deviation bands. These bands represent areas where price is statistically likely to find support or resistance. By focusing on these areas, traders can better anticipate where price might react, rather than relying on arbitrary levels.
Dynamic Box Creation and Expansion Detection: The indicator monitors the compression and expansion of the standard deviation bands. During periods of low volatility (squeeze), the bands compress, indicating consolidation. Once the bands start expanding, it signals the potential for a breakout. At this point, the indicator dynamically creates predictive order blocks based on the selected standard deviation range. These blocks highlight key levels where price might retrace or react, providing traders with valuable entry and exit points.
Color-Coded Proximity Alerts: To further enhance usability, the indicator uses color gradients to indicate how close the current price is to the calculated bands. This visual representation helps traders quickly assess the potential significance of the price's current position relative to the support and resistance areas.
In the example below, the indicator shows the bands expanding with the price, triggering the formation of the predictive order block.
In the final example, the price retraces into the order block before bouncing back to the upside, demonstrating the effectiveness of the identified support area.
Alerts
Trend Line Alerts: The indicator provides alerts when the price crosses above or below the trend line (median line). This feature is crucial for traders looking to identify potential trend changes early, allowing them to act quickly on emerging opportunities.
Band Alerts: Alerts are also triggered when the price crosses above or below the upper or lower bands for each standard deviation level. This helps traders identify potential breakout or breakdown scenarios, ensuring they are notified of significant market movements as they happen.
Customisable Alert Conditions: To cater to different trading strategies, the indicator allows users to set alert conditions for each standard deviation band and the trend line. This level of customisation ensures that traders receive alerts that are relevant to their specific trading style and market analysis.
Application
Strategic Decision-Making: The Predictive Order Blocks Indicator assists traders in making informed decisions by providing detailed analysis of potential breakout zones. By identifying key support and resistance areas, the indicator helps traders plan their entries and exits with greater precision.
Trend Confirmation: The indicator reinforces trading strategies by identifying key levels where price is likely to react. This confirmation is crucial for traders looking to enter trades with higher confidence.
Customized Analysis: The indicator adapts to various trading styles with extensive input settings that control the display and calculation of order blocks. Whether you're a day trader, swing trader, or long-term investor, the indicator can be tailored to meet your specific needs.
Visual Clarity: With customizable color settings and display options, the indicator enhances chart readability, allowing traders to quickly and easily interpret market data.
The Predictive Order Blocks Indicator by CryptoSea is an invaluable addition to a trader's toolkit, offering depth and precision in market trend analysis to navigate complex market conditions effectively.
