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!
Linear Regression
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
Adaptiv Trend Projection with Dynamic Length RegressionThe Adaptive Trend Projection indicator is a robust tool designed to provide an optimal trend projection calculated in a highly sophisticated manner. By utilizing linear regression lengths ranging from 20 to 200, this indicator estimates the duration of the trend by dynamically adjusting the projection length based on the calculated trend's strength.
Key Features:
1. Dynamic Length Adjustment: The indicator intelligently adapts the projection length between 20 and 200 using linear regression, ensuring adaptability to market conditions.
2. Trend Strength Calculation: Through linear regression analysis, the indicator calculates the slope, average, and intercept for each selected length, providing insights into the strength and direction of the trend.
3. Deviation Analysis: Beyond traditional trend analysis, the indicator calculates standard deviation, Pearson's correlation coefficient, and deviation values, offering a comprehensive view of market dynamics.
4. Confidence Levels: A unique feature of the Adaptive Trend Projection is its ability to determine confidence levels based on the highest Pearson's R value. Reliability is categorized into levels such as Neutral, Moderate, High, Very High, and Ultra High, providing users with a quick assessment of the projection's robustness.
5. Dynamic Forecasting: The indicator not only analyzes historical data but extends its functionality by dynamically forecasting future trend points. The projection adjusts in length based on the strength of the trend, allowing for more accurate predictions.
6. Visual Clarity: Enhancing visual clarity, the Adaptive Trend Projection indicator uses different line styles, widths, and colors to highlight crucial points, making it easier for traders to interpret and act upon the information.
In conclusion, the Adaptive Trend Projection indicator offers a nuanced understanding of market trends by combining advanced linear regression techniques, deviation analysis, and confidence level assessments. This enables traders to make informed decisions.
Linear Regression MTF + Bands
Multiple Time Frames (MTFs): The indicator allows you to view linear regression trends over three different time frames (TF1, TF2, TF3) simultaneously. This means a trader can observe short, medium, and long-term trends on a single chart, which is valuable for understanding overall market direction and making cross-timeframe comparisons.
Linear Regression Bands: For each time frame, the indicator calculates linear regression bands. These bands represent the expected price range based on past prices. The middle line is the linear regression line, and the upper and lower lines are set at a specified deviation from this line. Traders can use these bands to spot potential overbought or oversold conditions, or to anticipate future price movements.
History Bands: Looking at linear regression channels can be deceiving if the user does not understand the calculation. In order to see where the channel was at in history the user can display the history bands to see where price actual was in a non-repainting fashion.
Customization Options: Traders can customize various aspects of the indicator, such as whether to display each time frame, the length of the linear regression (how many past data points it considers), and the deviation for the bands. This flexibility allows traders to adapt the indicator to their specific trading style and the asset they are analyzing.
Alerts: The script includes functionality to set alerts based on the price crossing the upper or lower bands of any time frame. This feature helps traders to be notified of potential trading opportunities or risks without constantly monitoring the chart.
Examples
The 15minute linear regression is overlayed onto a 5 minute chart. We are able to see higher timeframe average and extremes. The average is the middle of the channel and the extremes are the outer edges of the bands. The bands are non-repainting meaning that is the actual value of the channel at that place in time.
Here multiple channels are shown at once. We have a linear regression for the 5, 15, and 60 minute charts. If your strategy uses those timeframes you can see the average and overbought/oversold areas without having to flip through charts.
In this example we show just the history bands. The bands could be thought of as a "don't diddle in the middle" area if your strategy is looking for reversals
You can extend the channel into the future via the various input settings.
TTP Pair Slope/HedgePair slope/hedge uses linear regression to calculate the hedge ratio (slope) between the two assets within a period.
It allows you to specify a "from" and a "to" candle.
Example:
"A regression from 1000 candles back in time and ignore the last 100 candles. This would result in making a regression of 900 candles in total."
The formula used to perform the regression with the assts X and Y is:
Hedge =
mean( (X-mean(X))^2 )
——————————————————
mean( (X-mean(X)) * (Y-mean(Y)) )
You can later use the hedge in a chart of X - Hedge * Y
(Confirm with 1 / hedge )
If the plot is stationary the period tested should look like stationary.
If you cross an imaginary horizontal line across all the values in the period used it should look like a flat channel with values crossing above and below the line.
The purpose of this indicator is to help finding the linear regression test used for conintegration analysis. Conintegration assets is one of the requirements to consider assets for pair and hedge trading.
Triple Moving Averages + RSI Divergence + Trade Creator [CSJ7]This indicator uses triple moving averages to identify the prevailing trend, and calculates the linear regression of the closing price, and of the RSI, to either confirm the current trend direction, or to identify a potential trade reversal. Additionally, it includes a trade management tool that allows you to rate your trade setup according to your selected entry minimums and preferences, plus you obtain an estimated P&L with profitability metrics of your trade.
The key features are:
Dashboard : Includes entry/exit amounts, prices, quantities, estimated Profit & Loss, ROI, ROE, RRR, insights into market trends, entry conditions, and operational logs.
Trade Setup : Allows you to design your trade in detail. Select entry/exit levels, and let the tool suggest optimal target levels based on your ROI and RRR preferences. Specify your desired stop-loss type, and the tool will present the corresponding price.
Entry Conditions Management : Customize your trade entry prerequisites within the settings. The system evaluates these, offering a Trade Rating and displaying current values and entry statuses in the Entry Conditions table.
Trade Box : Visualize your trade strategy with a trade box that shows in alongside your chart, highlighting potential profit/loss zones and entry price points.
RSI & Close Price Linear Regressions : Calculates the linear regression of RSI and the close prices, since the beginning of the current trend, and presents them directly in the chart and alongside the active trend, to allow you to spot a potential trend continuation or reversal.
Adaptive price levels : The tool calculates the viability, trade rating and P&L based on contextual levels, like moving averages and highest or lowest prices, instead of using fixed prices; this allows for the results to adapt dynamically to market fluctuations, eliminating the need for manual recalibrations and adjustments.
Automatic Trade Side Detection : While manual input is available, the tool can intuitively determine the optimal trade side based on current data.
Market Outlook Events : By using the crossings of the three averages, the tool keeps track of the evolution of the current trend, providing points of interest like when the initial momentum is observed, when the trend initiates, when a potential entry zone starts, when a buy or sell opportunity arises and when the trend ends.
Alerts : You can set up two distinct alerts – one notifies on trend milestones and another for trade initiation conditions. Note: Manual activation is required in the Tradingview dashboard.
Logs : The tool provides a log section where you can find relevant information regarding the operation and any encountered errors via the dashboard's log section.
Usage
Choose your desired ticker and timeframe. If a tradable trend is detected and levels are set correctly, the trade box appears. Incorrect levels will trigger a warning in the error logs.
The tool will suggest the logical trade side, but manual adjustments are possible.
Customize ROI, maximum loss, and RRR in the settings. When in 'Auto', the tool will calculate the target price accordingly.
Adjust leverage to align with your risk and reward parameters.
View linear regressions for trend analysis and spotting RSI divergences.
Manage position sizing and risk in the settings, accounting for broker/exchange fees.
Activate alerts for trade notifications.
Enable 'Show Trade Levels' in settings to get the details of the necessary limit orders for the trade.
In the image below, you can view the expanded Trade Creator Dashboard, the Trade Box, and the Linear Regression Lines:
The linear regression lines are colored red when trending downward and green when trending upward.
The labels displaying information related to the entry and exit prices can be hidden, as demonstrated in the image above.
Regression Line (Log)This indicator is based on the "Linear Regression Channel (Log)," which, in turn, is derived from TradingView's "Linear Regression Channel."
The "Regression Line (Log)" indicator is a valuable tool for traders and investors seeking to gain insights into long-term market trends. This indicator is personally favored for its ability to provide a comprehensive view of price movements over extended periods. It offers a unique perspective compared to traditional linear regression lines and moving averages, making it a valuable addition to the toolkit of experienced traders and investors.
Indicator Parameters:
Before delving into the details, it's worth noting that the chosen number of periods (2870) is a personal preference. This specific value is utilized for the S&P 500 index due to its alignment with various theories regarding the beginning of the modern economic era in the stock market. Different analysts propose different starting points, such as the 1950s, 1970s, or 1980s. However, users are encouraged to adjust this parameter to suit their specific needs and trading strategies.
How It Works:
The "Regression Line (Log)" indicator operates by transforming the closing price data into a logarithmic scale. This transformation can make the linear regression more suitable for data with exponential trends or rapid growth. Here's a breakdown of its functioning and why it can be advantageous for long-term trend analysis:
1. Logarithmic Transformation : The indicator begins by applying a logarithmic transformation to the closing price. This transformation helps capture price movements proportionally, making it especially useful for assets that exhibit exponential or rapid growth. This transformation can render linear regression more suitable for data with exponential or fast-paced trends.
2. Linear Regression on Log Scale : After the logarithmic transformation, the indicator calculates a linear regression line (lrc) on this log-transformed data. This step provides a smoother representation of long-term trends compared to a linear regression line on a linear scale.
3. Exponential Reversion : To present the results in a more familiar format, the indicator reverts the log-transformed regression line back to a linear scale using the math.exp function. This final output is the "Linear Regression Curve," which can be easily interpreted on standard price charts.
Advantages:
- Long-Term Trend Clarity : The logarithmic scale better highlights long-term trends and exponential price movements, making it a valuable tool for investors seeking to identify extended trends.
- Smoothing Effect : The logarithmic transformation and linear regression on a log scale smooth out price data, reducing noise and providing a clearer view of underlying trends.
- Adaptability : The indicator allows traders and investors to customize the number of periods (length) to align with their preferred historical perspective or trading strategy.
- Complementary to Other Tools : While not meant to replace other technical indicators, the "Regression Line (Log)" indicator complements traditional linear regression lines and moving averages, offering an alternative perspective for more comprehensive analysis.
Conclusion:
In summary, the "Regression Line (Log)" indicator is a versatile tool that can enhance your ability to analyze long-term market trends. Its logarithmic transformation provides a unique perspective on price data, particularly suited for assets with exponential growth patterns. While the choice of the number of periods is a personal one, it can be adapted to fit various historical viewpoints. This indicator is best utilized as part of a well-rounded trading strategy, in conjunction with other technical tools, to aid in informed decision-making.
RSRS (Resistance Support Relative Strength)The Resistance Support Relative Strength (RSRS) indicator, published by Everbright Securities, is a technical analysis tool that enjoys immense popularity among Chinese quantitative traders, owing to its stellar performance in China's stock markets.
🟠 Principle
The indicator treats daily highs and lows as resistance and support levels respectively. It measures market strength by comparing the magnitude of price changes in daily highs versus lows. Specifically, it fits a linear regression model to the (low, high) data points over the past N days (typically 18) and uses the slope (beta) as the RSRS value. A steeper slope indicates stronger market strength.
🟠 Algorithm
1. Collect the daily low and high prices over the past N days.
2. Apply Ordinary Least Squares to estimate the linear regression model: high = alpha + beta * low. The beta is the RSRS value.
3. Compute the z-score of the RSRS over the past M days (typically 600).
4. Compare the z-score to preset buy and sell thresholds (typically 0.7 and -0.7) to generate trading signals. If z-score > buy threshold, a buy signal is triggered. If z-score < sell threshold, a sell signal is triggered.
Linear RegressionThis indicator can be used to determine the direction of the current trend.
The indicator plots two different histograms based on the linear regression formula:
- The colored ones represent the direction of the short-term trend
- The gray one represents the direction of the long-term trend
In the settings, you can change the length of the short-term value, which also influences the long-term as a basis that will be multiplied
Linear Regression IndicatorThis tool can be used to determine the direction of the current trend.
The indicator changes the color of the candles based on the direction of the linear regression formula. This is made settings the length of the short-term linear regression in the settings, the longer one is also based on that parameter but significantly larger.
The indicator also plots the average between the two linear regression lines used in the candle coloring formula, and can be used both for support and resistance or as a trend line used to analyze breakouts.
