Multi-Timeframe Linear Regression Channel (Pinescriptlabs)This script combines multiple timeframes for visualizing linear regression channels in a single chart, allowing us to obtain a holistic view of price behavior across different timeframes (5m, 15m, 30m, and 4h). It facilitates the identification of trends and support/resistance levels across various time horizons. This multi-timeframe approach is useful because it helps confirm signals and detect potential divergences.
Components and Their Interaction
Linear Regression: Calculates the regression line and standard deviations for different timeframes. These lines show the direction and strength of the trend.
Deviation Bands: The upper and lower bands act as dynamic support and resistance levels, based on the standard deviation or maximum deviation.
Colors and Labels: Different colors for each timeframe allow for quick and clear identification of the regression lines and their bands. The labels help identify the timeframe of each channel.
Justification for the Mashup
Combining linear regressions across different timeframes allows us to observe short, medium, and long-term trends in a single chart. This multi-timeframe approach provides a more comprehensive market perspective compared to using a single timeframe.
Default Properties
The default properties of the strategy are configured to provide a clear view of the regression channels across different timeframes. These properties include:
Channel Length: Default of 50 periods, adjustable between 1 and 5000.
Data Source: Closing price by default.
Deviations: Optional use of upper and lower deviations with adjustable multipliers.
Line Extension: Option to extend lines to the right for better visualization.
Underlying Concepts
Calculating linear regression involves determining the slope, mean, and intercept of a line that best fits the price data. Standard deviations are used to create bands around this line, providing a measure of volatility. Implementing this in different timeframes allows us to observe how the trend changes over time and helps identify more precise entry and exit points.
This script is particularly useful for traders looking for an integrated tool that allows them to observe price behavior across multiple timeframes without needing to switch between different charts.
1.- For example, in the main image of the script, we observe that we are in a 1-hour timeframe, where the 4-hour linear regression channel indicates an uptrend with a length of 60 periods. Meanwhile, the 15-minute and 30-minute channels identify a convergence in the same trend. However, in the 5-minute linear regression, we have a completely lateral channel. These channels, shown from different timeframes in a single chart, give us a clear idea of exactly where the price is heading in each timeframe. Each channel serves as support or resistance for a lower or higher timeframe, depending on which timeframe we are looking at. Next, we will go to each timeframe to observe how the regression channels are displayed
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Español:
Este script combina múltiples marcos de tiempo para la visualización de canales de regresión lineal en un solo gráfico, nos permitirá obtener una visión holística del comportamiento del precio en diferentes marcos temporales (5m, 15m, 30m y 4h) permite la identificación de tendencias y niveles de soporte/resistencia en diferentes horizontes de tiempo. Este enfoque multi-temporal es útil porque permite confirmar señales y detectar posibles divergencias.
Componentes y su Interacción
Regresión Lineal: Calcula la línea de regresión y las desviaciones estándar para diferentes marcos temporales. Estas líneas muestran la dirección y la fuerza de la tendencia.
Bandas de Desviación: Las bandas superior e inferior actúan como niveles dinámicos de soporte y resistencia, basados en la desviación estándar o la desviación máxima.
Colores y Etiquetas: Diferentes colores para cada marco temporal permiten una identificación rápida y clara de las líneas de regresión y sus bandas. Las etiquetas ayudan a identificar el marco temporal de cada canal.
Justificación del Mashup
La combinación de regresiones lineales en diferentes marcos temporales nos permite observar la tendencia a corto, medio y largo plazo en un solo gráfico. Este enfoque multi-temporal proporciona una perspectiva más completa del mercado en comparación con el uso de un solo marco temporal.
Propiedades por Defecto
Las propiedades por defecto de la estrategia están configuradas para proporcionar una visión clara de los canales de regresión en diferentes marcos temporales. Estas propiedades incluyen:
Longitud del Canal: 50 períodos por defecto, ajustable entre 1 y 5000.
Fuente de Datos: Precio de cierre por defecto.
Desviaciones: Uso opcional de desviaciones superiores e inferiores con multiplicadores ajustables.
Extensión de Líneas: Opción para extender las líneas hacia la derecha para una mejor visualización.
Conceptos Subyacentes
El cálculo de la regresión lineal implica determinar la pendiente, la media y la intersección de una línea que mejor se ajusta a los datos de precios. Las desviaciones estándar se utilizan para crear bandas alrededor de esta línea, proporcionando una medida de la volatilidad. La implementación en diferentes marcos temporales permite observar cómo cambia la tendencia a lo largo del tiempo y ayuda a identificar puntos de entrada y salida más precisos.
Este script es particularmente útil para traders que buscan una herramienta integrada que les permita observar el comportamiento del precio en múltiples marcos temporales sin necesidad de cambiar entre diferentes gráficos.
Por ejemplo en la imagen principal del script observamos que estamos en un timeframe de 1h, donde el canal de regresión lineal de 4h, nos indica en un length de 60 periodos una tendencia alcista, mientras que los canales de 15min y 30 min nos identifican una convergencia en la misma tendencia, sin embargo en la regresión lineal de 5 minutos tenemos un canal totalmente lateral, estos canales mostrados de diferentes marcos de tiempo en un solo grafico nos da una clara idea de exactamente de a donde esta dirigiendo el precio en cada marco de tiempo a la par que cada canal nos sirve como soporte o resistencia de un marco de tiempo ya sea inferior o mayor dependiendo en que time frame nos coloquemos, a continuación iremos a cada marco de tiempo para que observemos como se muestran los canales de regresión:
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線形回帰
Log Regression Channel [UAlgo]The "Log Regression Channel " channel is useful for analyzing price trends and volatility in a financial instrument over a specified period. By using logarithmic scaling, this indicator can more effectively handle the wide range of price movements seen in many financial markets, making it particularly valuable for assets with exponential growth characteristics.
The indicator plots the central regression line along with upper and lower deviation bands, providing a visual representation of potential support and resistance levels.
🔶 Key Features
Logarithmic Regression Line: The central line represents the logarithmic regression, which fits the price data over the specified length using a logarithmic scale. This helps in identifying the overall trend direction.
Deviation Bands: The upper and lower bands are plotted at a specified multiple of the standard deviation from the regression line, highlighting areas of potential overbought and oversold conditions.
Customizable Parameters: Users can adjust the length of the regression, the deviation multiplier, the color of the labels, and the size of the text labels to suit their preferences.
R-Squared Display: The R-squared value, which measures the goodness of fit of the regression model, is displayed on the chart. This helps traders assess the reliability of the regression line.
🔶 Calculations
The indicator performs several key calculations to plot the logarithmic regression channel:
Logarithmic Transformation: The prices and time indices are transformed using the natural logarithm to handle exponential growth in price data.
Regression Coefficients: The slope and intercept of the regression line are calculated using the least squares method on the transformed data.
Predicted Values: The regression equation is used to calculate predicted values for each data point.
Standard Deviation: The standard deviation of the residuals (differences between actual and predicted values) is computed to determine the width of the deviation bands.
Deviation Bands: Upper and lower bands are plotted at a specified multiple of the standard deviation above and below the regression line.
R-Squared Value: The R-squared value is calculated to measure how well the regression line fits the data. This value is displayed on the chart to inform the user of the model's reliability.
🔶 Disclaimer
The "Log Regression Channel " indicator is provided for educational and informational purposes only.
It is not intended as investment advice or a recommendation to buy or sell any financial instrument. Trading financial instruments involves substantial risk and may not be suitable for all investors.
Past performance is not indicative of future results. Users should conduct their own research.
Linear Regression Oscillator [ChartPrime]Linear Regression Oscillator Indicator
Overview:
The Linear Regression Oscillator is a custom TradingView indicator designed to provide insights into potential mean reversion and trend conditions. By calculating a linear regression on the closing prices over a user-defined period, this oscillator helps identify overbought and oversold levels and highlights trend changes. The indicator also offers visual cues and color-coded price bars to aid in quick decision-making.
Key Features:
◆ Customizable Look-Back Period:
Input: Length
Default: 20
Description: Determines the period over which the linear regression is calculated. A longer period smooths the oscillator but may lag, while a shorter period is more responsive but may be noisier.
◆ Overbought and Oversold Thresholds:
Inputs: Upper Threshold and Lower Threshold
Default: 1.5 and -1.5 respectively
Description: Define the upper and lower bounds for identifying overbought and oversold conditions. Values outside these thresholds suggest potential reversals.
◆ Candlestick Color Plotting:
Input: Plot Bar Color
Default: false
Description: Option to color the price bars based on the oscillator's value, providing a visual representation of market conditions. Bars turn cyan for positive oscillator values and blue for negative.
◆ Mean Reversion and Trend Signals:
Visual markers and labels indicate when the oscillator suggests mean reversion or trend changes, aiding in identifying key market turning points.
◆ Invalidation Levels:
Tracks the highest and lowest prices over a recent period to set levels where the current trend signal would be considered invalidated.
◆ Gradient Color Coding:
Utilizes gradient color coding to enhance the visualization of oscillator values, making it easier to interpret overbought and oversold conditions.
◆ Usage Notes:
Setting the Look-Back Period:
Adjust the "Length" input based on the timeframe and the type of trading you are conducting. Shorter periods are more suited for intraday trading, while longer periods can be used for swing trading.
Interpreting Thresholds:
Use the upper and lower threshold inputs to fine-tune the sensitivity of the overbought and oversold signals. Higher absolute values reduce the number of signals but increase their reliability.
Candlestick Coloring:
Enabling the "Plot Bar Color" option can help quickly identify the current state of the oscillator in relation to the zero line. This visual aid can be particularly useful in fast-moving markets.
Mean Reversion and Trend Signals:
Pay attention to the symbols and labels on the chart indicating mean reversion and trend changes. These signals are designed to highlight potential entry and exit points.
Invalidation Levels:
Use the plotted invalidation levels as stop-loss or signal invalidation points. If the price moves beyond these levels, the current trend signal is likely invalid.
This indicator helps traders identify overbought and oversold conditions, potential mean reversions, and trend changes based on the linear regression of the closing prices over a specified look-back period.
Linear Regression Trend ChannelThe "Linear Regression Trend Channel" is a technical indicator designed to illustrate price trends and their volatility using linear regression. This indicator calculates the main linear regression line based on the user-defined period length and computes the standard deviation to form a trend channel.
Key Features:
- Linear Regression Calculation: Computes the linear regression line based on the selected price data source and the defined period length.
- Slope and Intercept Calculation: Calculates the slope and intercept of the linear regression line using the calcSlopeIntercept function.
- Deviation Channels: Adds standard deviation channels to the linear regression line to highlight potential support and resistance areas.
Settings
- Linear Regression Length: Specifies the length of the period for the linear regression calculation (default: 100).
- Linear Regression Source: Defines the data source for the linear regression calculation, such as close price, open price, etc. (default: close).
- Linear Regression Color: Sets the color of the linear regression line (default: gray).
- Show Price Labels: Option to display price labels on the horizontal lines (default: true).
How to Use
- Set the Linear Regression Length to define the period for regression calculation.
- Choose the Linear Regression Source to specify the price data (e.g., close, open).
- Enable or disable Show Price Labels based on whether you want to see price labels on the horizontal lines.
This Indicator helps identify dynamic support and resistance levels and potential market turning points.
Trend Maestro - Linear Regression & Volatility BandsTrend Maestro - Linear Regression & Volatility Bands
Description:
The "Trend Maestro - Linear Regression & Volatility Bands" indicator is meticulously designed to provide traders with a clear understanding of market trends through the application of linear regression techniques and enhanced market data visualization. This tool is essential for traders looking to interpret long-term trends and market stability. Here's how the indicator functions and what makes it a unique addition to your trading toolkit:
1. Linear Regression Calculation:
At the heart of this indicator lies the linear regression calculation, which identifies the primary trend direction over a specified period. It does this by computing a line of best fit through the closing prices, helping to smooth out price fluctuations and highlight the prevailing trend direction. Users have the flexibility to adjust both the length of the regression and the offset period, enabling them to tailor the indicator's responsiveness to different market conditions.
2. Visualization Through Volatility Bands:
The volatility bands, plotted at half, one, two, and three standard deviations around the linear regression line, serve primarily as a visualization tool rather than a basis for investment decisions.
These bands:
Measure the dispersion of price from the trend line, providing a graphical representation of volatility.
Help traders visually assess the market's stability and the reliability of the current trend, with broader bands indicating higher volatility and narrower bands suggesting more stability.
3. Customization Features:
The indicator offers customization options including toggle switches for bar color and the display of SD bands, enhancing visual clarity. These settings allow traders to personalize the display according to their visual preferences and analysis requirements.
By incorporating these elements, the "Trend Maestro - Linear Regression & Volatility Bands" indicator offers a framework for understanding market trends through both quantitative calculations and qualitative visual aids. This makes it a valuable tool for those looking to make informed decisions based on longer-term market observations.
Linear Regression Channel [GOODY]Linear Regression Channel
The Linear Regression Channel indicator is a versatile tool for traders, providing valuable insights into price trends and potential reversal points. It plots two linear regression channels on the chart, helping you visualize price dynamics and make informed trading decisions.
Indicator Features and Settings
General Settings:
• Source: The price source used for channel calculations. Typically, the close price is used.
1st Channel Settings:
• Length: The number of bars used to calculate the linear regression channel. Increasing this value widens the channel and makes it less responsive to recent price changes.
• Upper Deviation Multiplier: Multiplier for the upper deviation from the regression line. Higher values widen the upper boundary.
• Lower Deviation Multiplier: Multiplier for the lower deviation from the regression line. Higher values widen the lower boundary.
• Show Channel Lines: Toggle to show or hide the channel lines, useful for visualizing channel boundaries.
• Show Channel Background: Toggle to show or hide the background color between the channel lines, highlighting the area covered by the channel.
• Show Labels: Toggle to show or hide price level labels for the channel lines, helping to identify exact price levels at the boundaries.
• Upper Label Color: Color for the upper price level label.
• Lower Label Color: Color for the lower price level label.
• Label Offset: Offset for the price level labels, adjusting them horizontally.
1st Channel Display Settings:
• Extend Lines Left: Extend the regression channel lines to the left of the chart, visualizing historical performance.
• Extend Lines Right: Extend the regression channel lines to the right of the chart, anticipating future price movements.
1st Channel Style Settings:
• Upper 1st Channel Line Color: Color for the upper line of the first channel.
• Lower 1st Channel Line Color: Color for the lower line of the first channel.
• Upper Channel Color: Color for the upper channel area, filling the area between the upper channel line and the midline.
• Lower Channel Color: Color for the lower channel area, filling the area between the lower channel line and the midline.
• Baseline Color (DownTrend): Color of the baseline during a downtrend.
• Baseline Color (Up Trend): Color of the baseline during an uptrend.
2nd Channel Settings:
• Length for 2nd Channel: The number of bars used to calculate the second linear regression channel.
• Upper Deviation Multiplier for 2nd Channel: Multiplier for the upper deviation from the regression line in the second channel.
• Lower Deviation Multiplier for 2nd Channel: Multiplier for the lower deviation from the regression line in the second channel.
2nd Channel Display Settings:
• Show 2nd Channel Lines: Toggle to show or hide the second channel lines, useful for visualizing channel boundaries.
• Show 2nd Channel Background: Toggle to show or hide the background color between the second channel lines, highlighting the area covered by the second channel.
2nd Channel Style Settings:
• Upper 2nd Channel Color: Color for the upper line of the second channel.
• Lower 2nd Channel Color: Color for the lower line of the second channel.
• Baseline Color for 2nd Channel (Up Trend): Color of the baseline during an uptrend in the second channel.
• Baseline Color for 2nd Channel (Down Trend): Color of the baseline during a downtrend in the second channel.
• Upper 2nd Channel Background Color: Background color for the upper part of the second channel, filling the area between the upper channel line and the midline.
• Lower 2nd Channel Background Color: Background color for the lower part of the second channel, filling the area between the lower channel line and the midline.
• Line Style for 2nd Channel: Choose the style of the second channel lines (Solid, Dotted, Dashed, Arrow, Round).
2nd Channel Line Settings:
• Extend 2nd Channel Lines Left: Extend the second channel lines to the left of the chart, visualizing historical performance.
• Extend 2nd Channel Lines Right: Extend the second channel lines to the right of the chart, anticipating future price movements.
Other Settings:
• Show VWAP Detection: Toggle to enable or disable VWAP detection. VWAP (Volume Weighted Average Price) indicates the average price of the asset, weighted by volume.
• Show Doji Detection: Toggle to enable or disable Doji candle detection. Doji candles have small bodies, indicating market indecision.
• Doji Size Threshold: Threshold to determine a Doji candle. A smaller value indicates a stricter Doji definition.
How to Read the Indicator for Trading
Channel Lines and Colors:
• The upper line of the 1st channel (green) and the 2nd channel (blue) represents the upper boundary based on linear regression and deviation multipliers.
• The lower line of the 1st channel (red) and the 2nd channel (orange) represents the lower boundary.
• The midline changes color dynamically based on the trend direction:
• Pink during a downtrend for the 1st channel.
• Blue during an uptrend for the 1st channel.
• Gray during a consolidation for both channels.
• The 2nd channel uses similar color logic.
Channel Background:
• The background color between the channel lines highlights the area covered by the channel:
• Green for the upper area and red for the lower area in the 1st channel.
• Blue and orange for the upper and lower areas in the 2nd channel, respectively.
Labels:
• Price level labels at the channel boundaries provide exact price levels, displayed at the upper and lower lines if enabled.
VWAP and Doji Detection:
• VWAP is plotted as circles on the chart, showing the volume-weighted average price.
• Doji candles are highlighted with a background color if detected, indicating potential market indecision.
Alerts:
• Alerts are triggered when the trend direction of the channels changes. For example:
• An alert notifies you if the 1st channel is in an uptrend while the 2nd channel is in a downtrend.
• An alert notifies you if the 1st channel is in a downtrend while the 2nd channel is in an uptrend.
Trading with the Indicator
• Trend Identification: Use the color and direction of the midline and baseline to identify the current trend. An uptrend is indicated by a blue midline, while a downtrend is indicated by a pink midline.
• Reversal Points: Monitor when the price approaches the upper or lower boundaries of the channels, as these can act as support or resistance levels.
• Volume Insights: Use the VWAP and liquidity levels to understand the true average price based on volume and identify significant areas of trading activity.
• Market Indecision: Watch for Doji candles, which can signal potential reversals or periods of consolidation.
Linear Regression Trendline - Log, R-Squared, Dynamic RangeDescription:
This Pine Script tool is specifically crafted for in-depth technical analysis, integrating a logarithmic regression trendline with standard deviation (STDV) channel bands and the R-squared coefficient of determination. This sophisticated tool is tailored to provide a nuanced perspective on trend dynamics and volatility, particularly suitable for markets where changes are exponential rather than linear.
Key Features:
Logarithmic Regression Trendline: Uniquely employs a logarithmic approach to regression analysis, ideal for data that grows exponentially. This method emphasizes proportional changes and offers a more accurate fit for certain types of financial data.
STDV Channel Bands: Incorporates channel bands set at one or more standard deviations from the regression line. These bands offer insights into the volatility and relative price movements, aiding in the identification of potential buy and sell zones.
R-squared Coefficient: This tool differentiates itself by focusing on the R-squared coefficient of determination rather than Pearson's correlation coefficient. The R-squared value measures the proportion of variance in the dependent variable that is predictable from the independent variable, offering a more precise evaluation of the trendline’s effectiveness.
Flexible Period Settings: Unlike traditional tools, this script allows users to specify exact start and end points for the trendline analysis, either through direct date selection or by choosing specific bars. This flexibility facilitates precise modifications and adaptations to various analytical needs.
Interactive Usability: Features interactive capabilities allowing users to manually adjust the coordinates of the trendline’s start and end points during active sessions. This feature ensures that analysts can dynamically respond to market movements and adjust their analyses in real time.
Logarithmic Scaling: Specifically designed for logarithmic scaling, this tool is adept at handling data where growth rates are multiplicative, making it exceptionally useful in sectors like cryptocurrencies and rapidly growing stocks.
Usage:
This tool is ideal for traders and financial analysts who deal with high growth markets or any datasets where growth is exponential rather than linear. The focus on the R-squared coefficient enhances its utility by providing a critical assessment tool for evaluating the predictive strength and reliability of trends under logarithmic transformations.
panpanXBT BTC Risk Metric OscillatorThis is the Bitcoin Risk Metric. Inspired by many power law analysts, this script assigns a risk value to the price of Bitcoin. The model uses regression of 'fair value' data to assign risk values and residual analysis to account for diminishing returns as time goes on. This indicator is for long-term investors looking to maximise their returns by highlighting periods of under and overvaluation for Bitcoin.
This is a companion script for panpanXBT BTC Risk Metric . Use this indicator in tandem to achieve the view shown in the chart above.
Please note, this indicator will only work on BTCUSD charts but will work on any timeframe.
DISCLAIMER: The product on offer presents a novel way to view the price history of Bitcoin. It should not be relied upon solely to inform financial decisions. What you do with the information is entirely up to you. Please thoroughly consider your decisions and consult many different sources to make sure you're making the most well-informed decision.
### How to Interpret
The risk scale goes from 0 to 100,
Blue - 0 being low risk, and
Red - 100 being high risk.
Low risk values represent periods of historical undervaluation, while high values represent overvaluation. These periods are marked by a colourscale from blue to red.
### Use Cases and Best Practice
A dynamic DCA strategy would work best with this indicator, whereby an amount of capital is deployed/retired on a regular basis. This amount deployed grows or shrinks depending on the proximity of the risk level to the extremes (0 and 100).
Let's say you have a maximum of $500 to deploy per month.
When risk is between 0 and 10, you could deploy the full $500.
When risk is between 10 and 20, you could deploy $400.
When risk is between 20 and 30, you could deploy $300.
When risk is between 30 and 40, you could deploy $200.
When risk is between 40 and 50, you could deploy $100.
Conversely, when risk is above 50, you could:
Sell 1/15th of your BTC stack when risk is between 50 and 60.
Sell 2/15th of your BTC stack when risk is between 60 and 70.
Sell 3/15th of your BTC stack when risk is between 70 and 80.
Sell 4/15th of your BTC stack when risk is between 80 and 90.
Sell 5/15th of your BTC stack when risk is between 90 and 100.
This framework allows the user to accumulate during periods of undervaluation and derisk during periods of overvaluation, capturing returns in the process.
In contrast, simply setting limit orders at 0 and 100 would yield the absolute maximum returns, however there is no guarantee price will reach these levels (see 2018 where the bear market bottomed out at 20 risk, or 2021 where price topped out at 97 risk).
### Caveats
"All models are wrong, some are useful"
No model is perfect. No model can predict exactly what price will do as there are too many factors at play that determine the outcome. We use models as a guide to make better-informed decisions, as opposed to shooting in the dark. This model is not a get rich quick scheme, but rather a tool to help inform decisions should you consider investing. This model serves to highlight price extremities, which could present opportune times to invest.
### Conclusion
This indicator aims to highlight periods of extreme values for Bitcoin, which may provide an edge in the market for long-term investors.
Thank you for your interest in this indicator. If you have any questions, recommendations or feedback, please leave a comment or drop me a message on TV or twitter. I aim to be as transparent as possible with this project, so please seek clarification if you are unsure about anything.
The Next Pivot (With History) [Mxwll]Introducing "The Next Pivot (With History)"!
With permission from the author @KioseffTrading
The script "The Next Pivot" has been restructured to show historical projections!
Features
Find the most similar price sequence per time frame change.
Forecast almost any public indicator! Not just price!
Forecast any session i.e. 4Hr, 1Hr, 15m, 1D, 1W
Forecast ZigZag for any session
Spearmen
Pearson
Absolute Difference
Cosine Similarity
Mean Squared Error
Kendall
Forecasted linear regression channel
The image above shows/explains some of the indicator's capabilities!
Additionally, you can project almost any indicator!
Should load times permit it, the script can search all bar history for a correlating sequence. This won't always be possible, contingent on the forecast length, correlation length, and the number of bars on the chart.
If a load time error occurs, simple reduce the "Bars Back To Search" parameter!
The script can only draw 500 bars into the future. For whatever time frame you are on and the session you wish to project, ensure it will not exceeded a 500-bar forecast!
Reasonable Assessment
The script uses various similarity measures to find the "most similar" price sequence to what's currently happening. Once found, the subsequent price move (to the most similar sequence) is recorded and projected forward.
So,
1: Script finds most similar price sequence
2: Script takes what happened after and projects forward
While this may be useful, the projection is simply the reaction to a possible one-off "similarity" to what's currently happening. Random fluctuations are likely and, if occurring, similarities between the current price sequence and the "most similar" sequence are plausibly coincidental.
Thanks!
Lin Reg (Linear Regression) Support and Resistance by xxMargauxLin Reg (Linear Regression) Support & Resistance by xxMargaux 💸
This indicator plots three linear regression lines (Lin Reg) on the price chart, providing insights into potential support and resistance levels. It calculates Lin Reg lines based on user-defined lengths and sources.
This indicator's settings were initially configured for MNQ1! (E-Mini Nasdaq 100 futures contracts). But works as intended on any security and on any timeframe.
When price is below a given Lin Reg line, that line will be red and may serve as resistance as price moves up towards the line. That is, it may be a potential short entry opportunity. When price is above a given Lin Reg line, that line will be green and may serve as support as price continues up from the line. That is, it may be a potential long entry opportunity.
When price starts to break sideways or down through the Lin Reg lines, this may signal a reversal from uptrend to downtrend. When price starts to break sideways or up through the Lin Reg Lines, this may signal a reversal from downtrend to uptrend. In very strong trends, breaking through the lines briefly may provide an entry opportunity, but be cautious because a trend reversal may also be possible.
Inputs:
Length of Price Lin Reg Lines: Customize the lengths of the three Lin Reg lines.
Source for Price Lin Reg Lines: Choose the source for each Lin Reg line.
Source for Security Price: Select the price source for the security.
Features:
Trend Analysis: Assists in visualizing price trends based on the relationship between the security price and Lin Reg lines, which will be colored according to whether price is above or below each Lin Reg line.
Customizable Colors: When price is above a Lin Reg line that line will be green. When price is below a Lin Reg line, that line will be red.
Here's a beginner-friendly explanation of linear regression lines 💡
Best-Fit Line: Imagine you have a scatter plot of closing prices on a chart. Linear regression aims to find the straight line that best fits the overall trend of these data points. It's like drawing a line through the center of the data that minimizes the distance between the line and each data point.
Trend Identification: Once the linear regression line is plotted on a price chart, it provides a visual representation of the trend. If the price is generally rising, the linear regression line will slope upwards. If the price is falling, the line will slope downwards. This helps traders identify whether the trend is bullish (upward) or bearish (downward).
Support and Resistance: Linear regression lines can also act as dynamic support and resistance levels. When the price is above the linear regression line, it may act as support, meaning the price tends to bounce off the line and continue higher. Conversely, when the price is below the line, it may act as resistance, with the price encountering selling pressure and potentially reversing lower.
Reversal Signals: Changes in the slope or direction of the linear regression line can signal potential trend reversals. For example, if the price breaks above a downward-sloping linear regression line, it may indicate a shift from a downtrend to an uptrend, and vice versa.
Adjustable Parameters: Traders can customize the length of the linear regression line by adjusting the period over which it's calculated. Shorter periods may be more sensitive to recent price changes, while longer periods may provide a smoother trend line.
Long-Term Trend DetectorThe Long-Term Trend Detector is a powerful tool designed to identify sustainable trends in price movements, offering significant advantages for traders and investors.
Key Benefits:
1. Projection Confidence: This indicator leverages Pearson's R, a statistical measure that indicates the strength of the linear relationship between price and trend projection. A higher Pearson's R value reflects a stronger correlation, providing increased confidence in the identified trend direction.
2. Adaptive Channel Detection: By calculating deviations and correlations over varying lengths, the indicator dynamically adapts to changing market conditions. This adaptive nature ensures robust trend detection across different time frames.
3. Visual Clarity: The indicator visually displays long-term trend channels on the chart, offering clear insights into potential price trajectories. This visualization aids in decision-making by highlighting periods of strong trend potential.
4. Flexibility and Customization: Users can customize parameters such as deviation multiplier, line styles, transparency levels, and display preferences. This flexibility allows traders to tailor the indicator to their specific trading strategies and preferences.
5. Historical Analysis: The indicator can analyze extensive historical data (up to 5000 bars back) to provide comprehensive trend insights. This historical perspective enables users to assess trends over extended periods, enhancing strategic decision-making.
In summary, the Long-Term Trend Detector empowers traders with accurate trend projections and confidence levels, facilitating informed trading decisions. Its adaptive nature and customizable features make it a valuable tool for identifying and capitalizing on long-term market trends.
Heat Map SeasonsHeat Map Seasons indicator
Indicator offers traders a unique perspective on market dynamics by visualizing seasonal trends and deviations from typical price behavior. By blending regression analysis with a color-coded heat map, this indicator highlights periods of heightened volatility and helps identify potential shifts in market sentiment.
Summer:
In the context of the indicator, "summer" represents a period of heightened volatility and upward price momentum in the market. This is analogous to the warmer months of the year when activities are typically more vibrant and energetic. During the "summer" phase indicated by the indicator, traders may observe strong bullish trends, increased trading volumes, and larger price movements. It suggests a favorable environment for bullish strategies, such as trend following or momentum trading. However, traders should exercise caution as heightened volatility can also lead to increased risk and potential drawdowns.
Winter:
Conversely, "winter" signifies a period of decreased volatility and potentially sideways or bearish price action in the market. Similar to the colder months of the year when activities tend to slow down, the "winter" phase in the indicator suggests a quieter market environment with subdued price movements and lower trading volumes. During this phase, traders may encounter choppy price action, consolidation patterns, or even downtrends. It indicates a challenging environment for trend-following strategies and may require a more cautious approach, such as range-bound or mean-reversion trading strategies.
In summary, the "summer" and "winter" phases in the "Heat Map Seasons" indicator provide traders with valuable insights into the prevailing market sentiment and can help inform their trading decisions based on the observed levels of volatility and price momentum.
How to Use:
Watch for price bars that deviate significantly from the regression line , as these may signal potential trading opportunities.
Use the seasonal gauge to gauge the current market sentiment and adjust trading strategies accordingly.
Experiment with different settings for Length and Heat Sensitivity to customize the indicator to your trading style and preferences.
The "Heat Map Seasons" indicator can potentially identify overheated market tops and bottoms on a weekly timeframe by detecting significant deviations from the regression line and observing extreme color gradients in the heat map. Here's how it can be used for this purpose:
Observing Extreme Color Gradients:
When the market is overheated and reaches a potential top, you may observe extremely warm colors (e.g., deep red) in the heat map section of the indicator.
Traders can interpret this as a warning sign of a potential market top, indicating that bullish momentum may be reaching unsustainable levels.
Conversely, when prices deviate too far below the regression line, it may indicate oversold conditions and a potential bottom.
Potential Tops and Bottoms:
User Inputs:
Length: Determines the length of the regression analysis period.
Heat Sensitivity: Controls the sensitivity of the heat map to deviations from the regression line.
Show Regression Line: Option to display or hide the regression line on the chart
Note: This indicator is best used in conjunction with other technical analysis tools and should not be relied upon as the sole basis for trading decisions.
ProTrend Adaptive Indicator by TradingClueThe " ProTrend Adaptive " is an innovative trading indicator, aimed at offering traders an advanced method for detecting market trends with higher precision. This tool ingeniously integrates the principles of the Supertrend indicator with adaptive linear regression channels , enhancing its sensitivity to current market dynamics.
▯ Core Features ▯
✅ Trend Detection
At its heart, the ProTrend Adaptive utilizes a dual-approach for identifying trends. The first layer is derived from the Supertrend indicator, known for its effectiveness in highlighting ongoing trends using price average and volatility. This is visually represented by distinct red and green areas above or below the price candles, indicating bearish or bullish trends, respectively.
✅ Adaptive Linear Regression Channels
The second layer employs adaptive linear regression channels, which dynamically adjust their length based on the Average True Range (ATR), a measure of market volatility. This adaptability ensures the indicator remains attuned to changing market conditions, offering more relevant trend lines and signals.
✅ Signal Sensitivity
By leveraging the ATR not just in the Supertrend calculation but also to dynamically adjust the linear regression channels, the ProTrend Adaptive offers heightened sensitivity to market changes, ensuring traders receive timely and accurate signals.
✅ Entry Signals & Trend Strength
Entry points for potential trades are marked by triangles. Additionally, the indicator includes a feature that displays the strength of a trend through transparent bars below the candles, calculated using the Average Directional Index (ADX), providing users with valuable insight into the vigor of the trend.
▯ Importance of Adaptive Approach ▯
The adaptive nature of the ProTrend Adaptive's linear regression channels is crucial for its performance. Traditional linear regression channels are fixed in their period, which can render them less effective during periods of significant volatility shifts. By making the length of these channels responsive to the ATR, the ProTrend Adaptive ensures that the trend lines and signals it generates are always aligned with the current market context, offering traders a dynamic tool that adjusts in real-time to volatility changes.
▯ Supertrend Indicator Explained ▯
The Supertrend Indicator is a popular tool among traders for its simplicity and effectiveness in identifying market trends. It calculates the average price momentum and volatility to determine whether the market is in a bullish or bearish phase. Its visual simplicity, showing clear bullish and bearish zones, makes it an invaluable component of the ProTrend Adaptive, providing a solid foundation for trend detection upon which the adaptive linear regression channels build.
▯ Example ▯
This example illustrates several robust entry signals. These signals can seamlessly integrate into an overarching trading strategy, with exit points determined through a separate calculation. This approach allows traders to tailor their entry and exit strategies to their specific trading objectives, leveraging the ProTrend Adaptive for precise market entry while applying customized criteria for exit decisions.
Caution: Trading carries a significant risk of financial loss, and past performance does not guarantee future results. Signals may be conflicting or ambiguous. Employ risk reduction techniques, such as setting stop losses, to mitigate potential losses.
Sector ETFs performance overviewThe indicator provides a nuanced view of sector performance through ETF analysis, focusing on long-term price trends and deviations from these trends to gauge relative strength or weakness. It utilizes a methodical approach to smooth out ETF price data and then applies a regression analysis to pinpoint the primary trend direction. By examining how far the current price deviates from this regression line, the indicator identifies potential overbought or oversold conditions within various sectors.
Core Analysis Techniques:
Logarithmic Transformation and Regression: This process transforms ETF closing prices on a logarithmic scale to better understand sector growth patterns and dynamics. A linear regression of these prices helps define the overarching trend, crucial for understanding market movements.
Volatility Bands for Market State Assessment: The indicator calculates standard deviation based on logarithmic prices to establish dynamic bands around the regression line. These bands are instrumental in identifying market states, highlighting when sectors may be overextended from their central trend.
Sector-Specific Analysis: By focusing on distinct sector ETFs, the tool enables targeted analysis across various market segments. This specificity allows for a granular look at sectors like technology, healthcare, and financials, providing insights tailored to each area.
Adaptability and Insight:
Customizable Parameters: The indicator offers users the ability to adjust key parameters such as regression length and smoothing factors. This customization ensures that the analysis can be tailored to individual preferences and market outlooks.
Trend Direction and Momentum: It assesses the ETF's price movement relative to historical data and the established volatility bands, helping to clarify the sector's trend strength and potential directional shifts.
Strategic Application:
Focusing on trend and volatility analysis rather than direct trading signals, the indicator aids in forming a strategic view of sector investments. It's particularly useful for:
Spotting macroeconomic trends through the lens of sector ETF performance.
Informing portfolio decisions with nuanced insights into sector momentum and market conditions.
Anticipating potential market shifts by evaluating how current prices align with historical volatility and trend patterns.
This tool stands out as a vital resource for analyzing sector-level market trends, offering detailed insights into the dynamics of economic sectors for comprehensive market analysis.
SqueeZe Score [UAlgo]The "SqueeZe Score" is a script based on the "Squeeze Momentum Indicator". It utilizes Bollinger Bands (BB) and Keltner Channels (KC) to identify periods of low volatility, indicating potential upcoming price movements. The Z-Score method is employed to measure deviations from the mean, highlighting extreme price movements within the context of the current volatility environment. This script provides traders with visual cues for potential bullish and bearish divergences, aiding in decision-making during trading activities.
🔶Key Features:
SqueeZe Settings: Users can customize parameters such as the length and multiplier factors for Bollinger Bands and Keltner Channels, providing flexibility to adapt the indicator to different trading strategies and market conditions.
Divergence Detection: The script includes options to detect and display both bullish and bearish divergences, providing additional insights into potential trend reversals or continuations.
Customizable Z-Score Thresholds: Thresholds for the Z-Score are user-defined, enabling traders to set levels at which extreme price movements are highlighted on the chart, facilitating quick identification of significant market conditions.
🔶Credit:
This script is inspired by the work of @LazyBear, who contributed to the original concept and development of the Squeeze Momentum indicator.
🔶Disclaimer:
- The information provided by this script is for educational and informational purposes only and should not be construed as financial advice.
- Users are encouraged to conduct their own research and analysis before making any investment decisions.
Sector ETF macro trendThe Sector ETF Macro Trend indicator is designed for technical analysis of broad economic trends through sector-specific exchange-traded funds (ETFs). It uses logarithmic price transformation, linear regression, and volatility analysis to examine sector trends and stability, providing a technical basis for analytical assessment.
Core Analysis Techniques
Logarithmic Transformation and Regression: Converts ETF closing prices logarithmically to reveal sector growth patterns and dynamics. Linear regression on these prices defines the main trend direction, essential for trend analysis.
Volatility Bands for Market State Assessment: Applies standard deviation on logarithmic prices to create dynamic bands around the trendline, identifying overbought or oversold sector conditions by marking deviations from the central trend.
Sector-Specific Analysis: Selection among different sector ETFs allows for precise examination of sectors like technology, healthcare, and financials, enabling focused insights into specific market segments.
Adaptability and Insight
Customizable Parameters: Offers flexibility in modifying regression length and smoothing factors to accommodate various analysis strategies and risk preferences.
Trend Direction and Momentum: Evaluates the ETF's trajectory against historical data and volatility bands to determine sector trend strength and direction, aiding in the prediction of market shifts.
Strategic Application
Without providing explicit trading signals, the indicator focuses on trend and volatility analysis for a strategic view on sector investments. It supports:
Identifying macroeconomic trends through ETF performance analysis.
Informing portfolio decisions with insights into sector momentum and stability.
Forecasting market movements by analyzing overbought or oversold conditions against the ETF price movement and volatility bands.
The Sector ETF Macro Trend indicator serves as a technical tool for analyzing sector-level market trends, offering detailed insights into the dynamics of economic sectors for thorough market analysis.
Regression Sloped RSI [QuantraSystems]Regression Sloped RSI
Introduction
The Regression Sloped RSI (𝓡𝓢-𝓡𝓢𝓘) enhances the classical RSI by incorporating a form of linear regression analysis, which adjusts the traditional RSI in relation to the calculated slope over a specified lookback period.
Its innovative approach reduces the occurrence of false signals compared to the classical RSI. Furthermore, it is particularly effective in markets characterized by strong trends. This is because it responds faster while retaining a high level of whipsaw resistance. The Heikin-Ashi style processing is critical to this.
It also provides robust reversal signals from dynamic overbought and oversold zones to further enhance mean-reversion trading.
Legend
The coloring of the 𝓡𝓢-𝓡𝓢𝓘 changes based on trend direction: A bright green when upwards, lilac when downwards. The strength of the trend is expressed in its distance to Null. Its acceleration is found in the Heikin-Ashi (HA) candles.
The 𝓡𝓢-𝓡𝓢𝓘 in combination with the HA bars can be used to achieve earlier entries, when the former passes across the latter in an obvious divergence.
Case Study
In this example the 𝓡𝓢-𝓡𝓢𝓘 is used to make a few intra-day trades on the Ethereum 15 minute chart. Each trade was open for approximately 5 hours. On the first trade we enter a long in an early entry. The indicator gives us three confirmations which we should all check for. First we have a positive candle developing, secondly the 𝓡𝓢-𝓡𝓢𝓘 (line) rises above the Heikin-Ashi candles, thirdly the classical RSI (the saturated surface in the background) rises as well.
The trader should then calculate their position sizing responsibly and enter into a short daytrade. Please always have invalidation rules, for example a) if the initial HA candle closes negative b) you can place your stop loss at 1SD into the opposite direction.
Always use adequate risk management, never risk more than 1% of your portfolio, unless you are a seasoned trader with your own calculated position sizes.
Always forward test your rules, assets, timeframe and settings sufficiently.
It is always recommended to use multiple Quantra indicators to add confirmations to your signals - this is by design.
Recommended Settings
Please reset to defaults before enabling recommended settings.
Intra-Day Trading (15min chart)
RSI Length: 22
LR Length: 25
Smoothing: EMA
Toggle SD Bands: On
Mode for Coloring: Candles
Trend Following (4H chart)
RSI Length: 40
LR Length: 35
Smoothing: LSMA
Toggle SD Bands: Off
Mode for Coloring: Extremes or Trend Following
Notes
Quantra Standard Value Contents:
The Heikin-Ashi (HA) candle visualization smoothes out the signal line to provide more informative insights into momentum and trends. This allows earlier entries and exits by observing the indicator values transformed by the HA.
Various visualization options are available to adjust the indicator to the user’s preference: Aside from HA, a classic line, or a hybrid of both.
A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy.
To add to Quantra's indicators’ utility we have added the option to change the price bars colors based on different signals:
Choose Mode for Coloring
Trend Following (Indicator above mid line counts as uptrend, below is downtrend)
Extremes (Everything beyond the SD bands is highlighted to signal mean reversion)
Candles (Color of HA candles as barcolor)
Reversions (Only for HA) (Reversion Signals via the triangles if HA candles change trend while beyond the SD bands, high probability entries/exits)
The 𝓡𝓢-𝓡𝓢𝓘 is finely tuned to detect divergences.
Primarily utilized for trend following, the 𝓡𝓢-𝓡𝓢𝓘 also demonstrates effectiveness in identifying reversions, intensity of movements and the navigation of range-bound markets.
Allows for easy identification of slowdowns in momentum and thus negative rate of change.
Methodology
The 𝓡𝓢-𝓡𝓢𝓘 takes the classical RSI using a specified lookback length and computes the slope of a linear regression line applied to the RSI values. This slope is used to adjust the RSI.
This sloped RSI can be further smoothed using various Moving Averages with customizable lengths.
For a more nuanced view of market trends, the 𝓡𝓢-𝓡𝓢𝓘 applies a specialized Heikin Ashi method. This transformation modifies the Sloped RSI values in order to weigh and reflect the average price, offering a smoother representation compared to traditional candlestick patterns.
The 𝓡𝓢-𝓡𝓢𝓘 calculates upper and lower bounds based on a specified standard deviation multiplier and adjustable lookback period, providing a dynamic framework to identify extrema and thus overbought and oversold conditions.
Particularly in the Heikin Ashi mode, the 𝓡𝓢-𝓡𝓢𝓘 can display reversion signals. These are plotted as shapes on the chart, indicating high probability reversal points in the market trend.
Least Median of Squares Regression | ymxbThe Least Median of Squares (LMedS) is a robust statistical method predominantly used in the context of regression analysis. This technique is designed to fit a model to a dataset in a way that is resistant to outliers. Developed as an alternative to more traditional methods like Ordinary Least Squares (OLS) regression, LMedS is distinguished by its focus on minimizing the median of the squares of the residuals rather than their mean. Residuals are the differences between observed and predicted values.
The key advantage of LMedS is its robustness against outliers. In contrast to methods that minimize the mean squared residuals, the median is less influenced by extreme values, making LMedS more reliable in datasets where outliers are present. This is particularly useful in linear regression, where it identifies the line that minimizes the median of the squared residuals, ensuring that the line is not overly influenced by anomalies.
STATISTICAL PROPERTIES
A critical feature of the LMedS method is its robustness, particularly its resilience to outliers. The method boasts a high breakdown point, which is a measure of an estimator's capacity to handle outliers. In the context of LMedS, this breakdown point is approximately 50%, indicating that it can tolerate corruption of up to half of the input data points without a significant degradation in accuracy. This robustness makes LMedS particularly valuable in real-world data analysis scenarios, where outliers are common and can severely skew the results of less robust methods.
Rousseeuw, Peter J.. “Least Median of Squares Regression.” Journal of the American Statistical Association 79 (1984): 871-880.
The LMedS estimator is also characterized by its equivariance under linear transformations of the response variable. This means that whether you transform the data first and then apply LMedS, or apply LMedS first and then transform the data, the end result remains consistent. However, it's important to note that LMedS is not equivariant under affine transformations of both the predictor and response variables.
ALGORITHM
The algorithm randomly selects pairs of points, calculates the slope (m) and intercept (b) of the line, and then evaluates the median squared deviation (mr2) from this line. The line minimizing this median squared deviation is considered the best fit.
DISCLAIMER
In the LMedS approach, a subset of the data is randomly selected to compute potential models (e.g., lines in linear regression). The method then evaluates these models based on the median of the squared residuals. Since the selection of data points is random, different runs may select different subsets, leading to variability in the computed models.
ATR TrendTL;DR - An average true range (ATR) based trend
ATR trend uses a (customizable) ATR calculation and highest high & lowest low prices to calculate the actual trend. Basically it determines the trend direction by using highest high & lowest low and calculates (depending on the determined direction) the ATR trend by using a ATR based calculation and comparison method.
The indicator will draw one trendline by default. It is also possible to draw a second trendline which shows a 'negative trend'. This trendline is calculated the same way the primary trendline is calculated but uses a negative (-1 by default) value for the ATR calculation. This trendline can be used to detect early trend changes and/or micro trends.
How to use:
Due to its ATR nature the ATR trend will show trend changes by changing the trendline direction. This means that when the price crosses the trendline it does not automatically mean a trend change. However using the 'negative trend' option ATR trend can show early trend changes and therefore good entry points.
Some notes:
- A (confirmed) trend change is shown by a changing color and/or moving trendline (up/down)
- Unlike other indicators the 'time period' value is not the primary adjustment setting. This value is only used to calculate highest high & lowest low values and has medium impact on trend calculation. The primary adjustment setting is 'ATR weight'
- Every settings has a tooltip with further explanation
- I added additional color coding which uses a different color when the trend attempts to change but the trend change isn't confirmed (yet)
- Default values work fine (at least in my back testing) but the recommendation is to adjust the settings (especially ATR weight) to your trading style
- You can further finetune this indicator by using custom moving average types for the ATR calculation (like linear regression or Hull moving average)
- Both trendlines can be used to determine future support and resistance zones
- ATR trend can be used as a stop loss finder
- Alerts are using buy/sell signals
- You can use fancy color filling ;)
Happy trading!
Daniel
Divergence AnalyzerUnlock the potential of your trading strategy with the Divergence Analyzer, a sophisticated indicator designed to identify divergence patterns between two financial instruments. Whether you're a seasoned trader or just starting, this tool provides valuable insights into market trends and potential trading opportunities.
Key Features:
1. Versatility in Symbol Selection:
- Choose from a wide range of symbols for comparison, including popular indices like XAUUSD and SPX.
- Seamlessly toggle between symbols to analyze divergences and make informed trading decisions.
2. Flexible Calculation Options:
- Customizable options allow you to use a different symbol for calculation instead of the chart symbol.
- Fine-tune your analysis by selecting specific symbols for comparison based on your trading preferences.
3. Logarithmic Scale Analysis:
- Utilizes logarithmic scales for accurate representation of price movements.
- Linear regression coefficients are calculated on the logarithmic scale, providing a comprehensive view of trend strength.
4. Dynamic Length and Smoothing:
- Adjust the length parameter to adapt the indicator to different market conditions.
- Smoothed linear regression with exponential moving averages enhances clarity and reduces noise.
5. Standard Deviation Normalization:
- Normalizes standard deviations over 200 periods, offering a standardized view of price volatility.
- Easily compare volatility levels across different symbols for effective divergence analysis.
6. Color-Coded Divergence Visualization:
- Clearly distinguish positive and negative divergences with customizable color options.
- Visualize divergence deltas with an intuitive color scheme for quick and effective interpretation.
7. Symbol Information Table:
- An included table provides at-a-glance information about the selected symbols.
- Identify Symbol 1 and Symbol 2, along with their corresponding positive and negative divergence colors.
How to Use:
1. Select symbols for analysis using the user-friendly inputs.
2. Customize calculation options based on your preferences.
3. Analyze the divergence delta plot for clear visual indications.
4. Refer to the symbol information table for a quick overview of selected instruments.
Empower your trading strategy with the Divergence Analyzer and gain a competitive edge in the dynamic world of financial markets. Start making more informed decisions today!
Adaptive Trend Finder (log)In the dynamic landscape of financial markets, the Adaptive Trend Finder (log) stands out as an example of precision and professionalism. This advanced tool, equipped with a unique feature, offers traders a sophisticated approach to market trend analysis: the choice between automatic detection of the long-term or short-term trend channel.
Key Features:
1. Choice Between Long-Term or Short-Term Trend Channel Detection: Positioned first, this distinctive feature of the Adaptive Trend Finder (log) allows traders to customize their analysis by choosing between the automatic detection of the long-term or short-term trend channel. This increased flexibility adapts to individual trading preferences and changing market conditions.
2. Autonomous Trend Channel Detection: Leveraging the robust statistical measure of the Pearson coefficient, the Adaptive Trend Finder (log) excels in autonomously locating the optimal trend channel. This data-driven approach ensures objective trend analysis, reducing subjective biases, and enhancing overall precision.
3. Precision of Logarithmic Scale: A distinctive characteristic of our indicator is its strategic use of the logarithmic scale for regression channels. This approach enables nuanced analysis of linear regression channels, capturing the subtleties of trends while accommodating variations in the amplitude of price movements.
4. Length and Strength Visualization: Traders gain a comprehensive view of the selected trend channel, with the revelation of its length and quantification of trend strength. These dual pieces of information empower traders to make informed decisions, providing insights into both the direction and intensity of the prevailing trend.
In the demanding universe of financial markets, the Adaptive Trend Finder (log) asserts itself as an essential tool for traders, offering an unparalleled combination of precision, professionalism, and customization. Highlighting the choice between automatic detection of the long-term or short-term trend channel in the first position, this indicator uniquely caters to the specific needs of each trader, ensuring informed decision-making in an ever-evolving financial environment.
EXOFADEEXOFADE is an incredible trading indicator designed help give traders a visual clue of price momentum by combining Linear regression calculations with volume.
Overview:
ExoFade is a unique and dynamic trading indicator designed for both beginner and professional traders. At its core, it uses a sophisticated blend of multiple linear regression analysis, incorporating price, time, and volume-weighted moving average (VWMA) to predict potential price movements. By analyzing these key factors, EXOFade offers an innovative approach to understanding market trends and identifying trade opportunities.
Why It Works:
ExoFade works by calculating a regression line that adapts to market conditions, factoring in both price trends and trading volumes. This approach provides a more nuanced view of market momentum, going beyond traditional price-only indicators. The inclusion of time as a variable offers unique insights into market dynamics, making ExoFade a valuable tool for various trading strategies.
Key Features to Look Out For:
Regression Line: The heart of ExoFade, offering visual cues about the market's direction.
ATR-Based Fade Levels: Utilizes Average True Range (ATR) to set dynamic levels that signal potential reversals or continuation. The indicator comes with three fade levels, which are described below
Alert Conditions: You can set up for alerts for when any of the fade levels have been been reached, indicating potential entry points.
What Are Fade Levels And How To Use The Enter Trades:
The exofade line always moves with price, this indicates that the current volume is moving in the same direction.
When you see the exofade start to move ahead of price. For example, in an Uptrend, if price stops making new highs and you see the exofade line continue moving up ahead of price as price stagnates, this is the first time that you should be expecting pull back or reversal. When the line starts to visibly curve, this when you want to enter the trade.
Sometimes, the exofade line will move just a little bit ahead of price, and sometimes it will move a clear distance ahead of price.
From my experience, the further ahead it moves from price without price keeping up, the higher the probability of a pullback or reversal.
The actual pullback then starts when the exofade line starts to curve, which signifies the start if the actual pullback.
Since we cannot sit and watch for when the line has either moved further ahead enough or started to curve, thats why i figured to use ATR as the best way to measure the distance the exofade line moves ahead of price and the ATR also happens to measure Volatility, which makes it a perfect match.
From forward testing this for months, i have found the pullbacks typically start when the exofade line has moved ahead of price by atleast 2 ATR's. A distance of 2 ATR and above are the ones i consider the best setups. This also marks the point for your stop loss, since 2 ATR is generally used stoploss level.
To catch and sell a pullback in an uptrend, you can set alert for one or both of these alerts
Fade Level 2 abv price - This alert will trigger once Exofade line reached 2 ATR ABOVE price (Just means it has reached 2 atr, dosent mean it has started curving yet)
Curve lvl 2 - SELL - This alert means the exofade line has started to curve at 2 ATR
To buy pullbacks in a downtrend you set the opposite alerts of the one above for curve below price
There are also same alerts for level 3 as well, which is 2.5 ATR
IMPORTANT NOTES - DONT SKIP THIS
For daily and intra-day swings - Use this on 1hr trend upwards - The exofade line much slower on higher timeframe, so when you get a curve on a high time frame, like the 4HR or Daily timeframe, those are excellent signals
For scalpers trading 1hr below - The exofade moves faster on lower timeframes, so more caution should be used with these on lower timeframes , you this with other confluences like a good momentum oscillator oversold/overbought regions StochRSI, MACD etc
EXTRA TIPS
- Since the curve forms slower on higher time frames, it means getting a curve the on daily and weekly chart can help in your trend analysis to detect early signs of potential trend reversals
-I typically pair this with my customized version of Nadaraya watsons envelope ( a free indicator on tradingview) It will further improve your entry and winrate. Biggest advantage is for setting a profit target. In a buy trade for example, you buy the curve below price and set your profit target for the top band of the nadaraya watson envelope. Very efficient for scalping
- Unique areas were you want to pay attention to the exofade is when price enters points of interest, this depending on your trading style could be a
-FVG - fair value gaps
-Order blocks
- Supply / Demand areas
-Volume profile Value area High and Value area Low
The are two scenarios i would like you to be cautious of
1. As with every indicator and strategy, i most definitely wouldn't use this during high impact news.
2. If price is trending very strongly in one direction only, such that even barely gives any decent pull backs at all. Most especially if that strong push is happening between the 4hr to Daily time frame. Do not attempt to counter those trends unless you know what you are doing. Its not advisable.
Instead i'll recommend using the Exofade to catch an entry in the direction of the trade for a continuation.
And Lastly
Since this indicator uses VOLUME data as part of its calculations. It will not work on any pairs that tradingview does not provide volume data for, like Gold. But it will work normally on Gold Futures, since that has volume data
Linear Regression Channel 200█ OVERVIEW
This a simplified version of linear regression channel which use length 200 instead of traditional length 100.
█ FEATURES
Color change depends light / dark mode.
█ LIMITATIONS
Limited to source of closing price and max bars back is 1500.
█ SIMILAR
Regression Channel Alternative MTF
Regression Channel Alternative MTF V2
