Filtered Volume Profile [ChartPrime]The "Filtered Volume Profile" is a powerful tool that offers insights into market activity. It's a technical analysis tool used to understand the behavior of financial markets. It uses a fixed range volume profile to provide a histogram representing how much volume occurred at distinct price levels.
Profile in action with various significant levels displayed
How to Use
The script is designed to analyze cumulative trading volumes in different price bins over a certain period, also known as `'lookback'`. This lookback period can be defined by the user and it represents the number of bars to look back for calculating levels of support and resistance.
The `'Smoothing'` input determines the degree to which the output is smoothed. Higher values lead to smoother results but may impede the responsiveness of the indicator to rapid changes in volatility.
The `'Peak Sensitivity'` input is used to adjust the sensitivity of the script's peak detection algorithm. Setting this to a lower value makes the algorithm more sensitive to local changes in trading volume and may result in "noisier" outputs.
The `'Peak Threshold'` input specifies the number of bins that the peak detection mechanism should account for. Larger numbers imply that more volume bins are taken into account, and the resultant peaks are based on wider intervals.
The `'Mean Score Length'` input is used for scaling the mean score range. This is particularly important in defining the length of lookback bars that will be used to calculate the average close price.
Sinc Filter
The application of the sinc-filter to the Filtered Volume Profile reduces the risk of viewing artefacts that may misrepresent the underlying market behavior. Sinc filtering is a high-quality and sharp filter that doesn't manifest any ringing effects, making it an optimal choice for such volume profiling.
Histogram
On the histogram, the volume profile is colored based on the balance of bullish to bearish volume. If a particular bar is more intense in color, it represents a larger than usual volume during a single price bar. This is a clear signal of a strong buying or selling pressure at a particular price level.
Threshold for Peaks
The `peak_thresh` input determines the number of bins the algorithm takes in account for the peak detection feature. The 'peak' represents the level where a significant amount of volume trading has occurred, and usually is of interest as an indicative of support or resistance level.
By increasing the `peak_thresh`, you're raising the bar for what the algorithm perceives as a peak. This could result in fewer, but more significant peaks being identified.
History of Volume Profiles and Evolution into Sinc Filtering
Volume profiling has a rich history in market analysis, dating back to the 1950s when Richard D. Wyckoff, a legendary trader, introduced the concept of volume studies. He understood the critical significance of volume and its relationship with market price movement. The core of Wyckoff's technical analysis suite was the relationship between prices and volume, often termed as "Effort vs Results".
Moving forward, in the early 1800s, the esteemed mathematician J. R. Carson made key improvements to the sinc function, which formed the basis for sinc filtering application in time series data. Following these contributions, trading studies continued to create and integrate more advanced statistical measures into market analysis.
This culminated in the 1980s with J. Peter Steidlmayer’s introduction of Market Profile. He suggested that markets were a function of continuous two-way auction processes thus introducing the concept of viewing markets in price/time continuum and price distribution forms. Steidlmayer's Market Profile was the first wide-scale operation of organized volume and price data.
However, despite the introduction of such features, challenges in the analysis persisted, especially due to noise that could misinform trading decisions. This gap has given rise to the need for smoothing functions to help eliminate the noise and better interpret the data. Among such techniques, the sinc filter has become widely recognized within the trading community.
The sinc filter, because of its properties of constructing a smooth passing through all data points precisely and its ability to eliminate high-frequency noise, has been considered a natural transition in the evolution of volume profile strategies. The superior ability of the sinc filter to reduce noise and shield against over-fitting makes it an ideal choice for smoothing purposes in trading scripts, particularly where volume profiling forms the crux of the market analysis strategy, such as in Filtered Volume Profile.
Moving ahead, the use of volume-based studies seems likely to remain a core part of technical analysis. As long as markets operate based on supply and demand principles, understanding volume will remain key to discerning the intent behind price movements. And with the incorporation of advanced methods like sinc filtering, the accuracy and insight provided by these methodologies will only improve.
Mean Score
The mean score in the Filtered Volume Profile script plays an important role in probabilistic inferences regarding future price direction. This score essentially characterizes the statistical likelihood of price trends based on historical data.
The mean score is calculated over a configurable `'Mean Score Length'`. This variable sets the window or the timeframe for calculation of the mean score of the closing prices.
Statistically, this score takes advantage of the concept of z-scores and probabilities associated with the t-distribution (a type of probability distribution that is symmetric and bell-shaped, just like the standard normal distribution, but has heavier tails).
The z-score represents how many standard deviations an element is from the mean. In this case, the "element" is the price level (Point of Control).
The mean score section of the script calculates standard errors for the root mean squared error (RMSE) and addresses the uncertainty in the prediction of the future value of a random variable.
The RMSE of a model prediction concerning observed values is used to measure the differences between values predicted by a model and the values observed.
The lower the RMSE, the better the model is able to predict. A zero RMSE means a perfect fit to the data. In essence, it's a measure of how concentrated the data is around the line of best fit.
Through the mean score, the script effectively predicts the likelihood of the future close price being above or below our identified price level.
Summary
Filtered Volume Profile is a comprehensive trading view indicator which utilizes volume profiling, peak detection, mean score computations, and sinc-filter smoothing, altogether providing the finer details of market behavior.
It offers a customizable look back period, smoothing options, and peak sensitivity setting along with a uniquely set peak threshold. The application of the Sinc Filter ensures a high level of accuracy and noise reduction in volume profiling, making this script a reliable tool for gaining market insights.
Furthermore, the use of mean score calculations provides probabilistic insights into price movements, thus providing traders with a statistically sound foundation for their trading decisions. As trading markets advance, the use of such methodologies plays a pivotal role in formulating effective trading strategies and the Filtered Volume Profile is a successful embodiment of such advancements in the field of market analysis.
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Swing Ranges [ChartPrime]Swing Ranges is an indicator designed to provide traders with valuable insights into swing movements and real-time support and resistance (SR) levels. This tool detects price swings and plots boxes around them, allowing traders to visualize the market dynamics efficiently. The indicator's primary focus is on real-time support and resistance levels, empowering traders to make well-informed decisions in dynamic market conditions.
Key Features:
Swing Box Visualization:
Swing Ranges excels at detecting swings in the price data and visually representing them with boxes on the price chart. This enables traders to quickly identify swing ranges, essential for understanding market trends and potential reversal points. VWAP POCs are also provided giving areas of high activity in each block.
Real-Time Support and Resistance Levels:
The core feature of Swing Ranges is its real-time support and resistance levels. These levels are dynamically calculated based on the volume-weighted data for each specific range. The indicator displays the strength of support and resistance zones with percentage bars, indicating the ratio between bullish and bearish volume. This real-time information empowers traders to assess the strength and significance of each SR level, enhancing their ability to execute well-timed trades.
ATR (Average True Range) Value:
Swing Ranges also includes an ATR value label, which shows the Average True Range for the selected period. ATR aids traders in understanding market volatility, enabling them to set appropriate stop-loss and take-profit levels for their trades.
VWAP (Volume Weighted Average Price) Information:
Traders c an readily access the VWAP value through the indicator's label. VWAP provides insights into the average price at which an asset has been traded, helping traders identify potential fair value areas and market trends.
Price Difference Percentage:
Swing Ranges displays the percentage difference between the high and low of each swing. This information allows traders to gauge the magnitude of price movements and assess potential profit targets more effectively.
The indicator also has a NV value. If the NV is high e.g. 10% or more there is indecision in the market and the market is trying to remain in a given range.
Settings Inputs:
1. Length Control:
The Length setting input in Swing Ranges allows traders to adjust the sensitivity of the indicator to detect swings. Traders can customize the length based on their trading strategies and timeframes.
2. ATR Period Adjustment:
The ATR Period input allows traders to fine-tune the calculation period for the Average True Range. This feature enables traders to adapt the indicator to different market conditions and asset classes.
Swing Ranges: Real-Time Support and Resistance Indicator is a comprehensive tool that combines swing visualization with dynamic support and resistance levels. By focusing on real-time SR levels, this indicator equips traders with the essential information needed to make confident trading decisions in ever-changing market conditions.
DCA Liquidation Calculation [ChartPrime]The DCA Liquidation Calculator is a powerful table indicator designed for both manual and bot-assisted traders who practice Dollar Cost Averaging (DCA). Its primary objective is to help traders avoid getting liquidated and make informed decisions when managing their positions. This comprehensive table indicator provides essential information to DCA traders, enabling them to plan their trades effectively and mitigate potential risks of liquidation.
Key Features:
Liquidation Price Awareness: The DCA Liquidation Calculator calculates and displays the liquidation price for each trade within your position. This critical information empowers traders to set appropriate stop-loss levels and avoid being liquidated in adverse market conditions, especially in leveraged trading scenarios.
DCA Recommendations: Whether you are executing DCA manually or using a trading bot, the DCA Liquidation Calculator offers valuable guidance. It suggests optimal entry prices and provides insights into the percentage deviation from the current market price, helping traders make well-timed and well-informed DCA decisions.
Position Sizing: Proper position sizing is essential for risk management. The DCA Liquidation Calculator helps traders determine the percentage of capital to allocate to each trade based on the provided insights. By using the recommended position sizing, traders can protect their capital and potentially maximize profits.
Profit and Loss Visualization: Gain real-time visibility into your Profit and Loss (PnL) with the DCA Liquidation Calculator. This feature allows you to monitor your trades' performance, enabling you to adapt your strategies as needed and make data-driven decisions.
Margin Call Indicators: Anticipating potential margin calls is crucial for maintaining a healthy trading account. The DCA Liquidation Calculator's smart analysis helps you identify and manage potential margin call situations, reducing the risk of account liquidation.
Capital Requirements: Before entering a trade, it's vital to know the required capital. The DCA Liquidation Calculator provides you with this information, ensuring you are adequately prepared to execute your trades without overextending your resources.
Maximum Trade Limit: Considering your available capital, the DCA Liquidation Calculator helps you determine the maximum number of trades you can enter. This feature ensures you maintain a disciplined and sustainable trading approach aligned with your financial capabilities.
Color-Coded Risk Indicators:
Green Liquidation Price Cell: Indicates that the position is considered safe from liquidation at the given parameters.
Yellow Liquidation Price Cell: Warns traders of potential liquidation risk. Exercise caution and monitor the trade closely to avoid undesirable outcomes.
Purple Liquidation Price Cell: Shows the liquidation price, but it does not necessarily indicate an imminent liquidation. Use this information to make prudent risk management decisions.
Red Row: Signals that the trade cannot be executed due to insufficient capital. Consider alternative strategies or ensure adequate capitalization before proceeding.
Settings explained:
In conclusion, the DCA Liquidation Calculator equips traders with essential tools to make well-calculated decisions, minimize liquidation risks, and optimize their Dollar Cost Averaging strategy. By offering comprehensive insights into your trading position, this indicator empowers you to navigate the markets with confidence and increase your potential for successful and sustainable trading.
RibboNN Machine Learning [ChartPrime]The RibboNN ML indicator is a powerful tool designed to predict the direction of the market and display it through a ribbon-like visual representation, with colors changing based on the prediction outcome from a conditional class. The primary focus of this indicator is to assist traders in trend following trading strategies.
The RibboNN ML in action
Prediction Process:
Conditional Class: The indicator's predictive model relies on a conditional class, which combines information from both longcon (long condition) and short condition. These conditions are determined using specific rules and criteria, taking into account various market factors and indicators.
Direction Prediction: The conditional class provides the basis for predicting the direction of the market move. When the prediction value is greater than 0, it indicates an upward trend, while a value less than 0 suggests a downward trend.
Nearest Neighbor (NN): To attempt to enhance the accuracy of predictions, the RibboNN ML indicator incorporates a Nearest Neighbor algorithm. This algorithm analyzes historical data from the Ribbon ML's predictive model (RMF) and identifies patterns that closely resemble the current conditional prediction class, thereby offering more robust trend forecasts.
Ribbon Visualization:
The Ribbon ML indicator visually represents its predictions through a ribbon-like display. The ribbon changes colors based on the direction predicted by the conditional class. An upward trend is represented by a green color, while a downward trend is depicted by a red color, allowing traders to quickly identify potential market directions.
The introduction of the Nearest Neighbor algorithm provides the Ribbon ML indicator with unique and adaptive behaviors. By dynamically analyzing historical patterns and incorporating them into predictions, the indicator can adapt to changing market conditions and offer more reliable signals for trend following trading strategies.
Manipulation of the NN Settings:
Smaller Value of Neighbours Count:
When the value of "Neighbours Count" is small, the algorithm considers only a few nearest neighbors for making predictions.
A smaller value of "Neighbours Count" leads to more flexible decision boundaries, which can result in a more granular and sensitive model.
However, using a very small value might lead to overfitting, especially if the training data contains noise or outliers.
Larger Value of "Neighbours Count":
When the value of "Neighbours Count" is large, the algorithm considers a larger number of nearest neighbors for making predictions.
A larger value of "Neighbours Count" leads to smoother decision boundaries and helps capture the global patterns in the data.
However, setting a very large value might result in a loss of local patterns and make the model less sensitive to changes in the data.
Retest Support Resistance Signals [ChartPrime]The Retest Support Resistance Signals Indicator is a powerful tool designed to assist traders in identifying key support and resistance levels within the market. Most importantly and uniquely it identifies retests of these structures and displays them on the trader's chart. By utilizing a combination of pivot points and price action analysis, this indicator offers valuable insights for both signal-based and support/resistance trading strategies.
Key Features & settings:
Retest Confirmation: The indicator waits for a break above a support or resistance level and observes subsequent price action. If price retraces and forms a wick below the level, followed by a bounce, the indicator identifies it as a retest and labels it as "R" to indicate potential support or resistance confirmation.
This indicator combines the benefits of signal-based trading and support/resistance analysis, providing users with a versatile trading tool suitable for various strategies.
Retest Weaker Toggle: Users have the option to enable or disable the retest weaker feature. When enabled, the indicator considers a support or resistance level weaker if it experiences a test. When disabled, the indicator assumes that a bounce may occur from the level.
Pivot Detection Customization: Users can adjust the pivot detection method based on either wicks or bodies. This flexibility allows traders to adapt the indicator to different market conditions and preferences. The trader can also customize the number of bars used for pivot detection on both the left and right sides. This feature enables traders to fine-tune the indicator's sensitivity and responsiveness.
Users also have control over how support or resistance levels are managed on the chart. They can choose to either stop updating the levels (freeze) or completely remove them (delete) from the chart.
Breakout Threshold Setting: Traders can adjust the breakout threshold until deletion setting. This setting determines the number of successful breakouts through a support or resistance level required to remove it from the chart. This feature helps filter out weaker levels and focus on more significant ones.
Shown above we see the retest labels in action denoted with an R label
This indicator can be a useful addition to an SR trader's toolkit. Identifying when a level in the market is retested can reveal interesting information about the underlying strength of a trend. This indicator has been designed with the two major schools of thought; a level gets weaker the more it's tested vs stronger the more it's tested. We have designed this therefore to be versatile and adapt to both thought procceses. The R labels should be taken and considered as a larger part of an analysis process and not followed blindly.
Multi Kernel Regression [ChartPrime]The "Multi Kernel Regression" is a versatile trading indicator that provides graphical interpretations of market trends by using different kernel regression methods. It's beneficial because it smoothes out price data, creating a clearer picture of price movements, and can be tailored according to the user's preference with various options.
What makes this indicator uniquely versatile is the 'Kernel Select' feature, which allows you to choose from a variety of regression kernel types, such as Gaussian, Logistic, Cosine, and many more. In fact, you have 17 options in total, making this an adaptable tool for diverse market contexts.
The bandwidth input parameter directly affects the smoothness of the regression line. While a lower value will make the line more sensitive to price changes by sticking closely to the actual prices, a higher value will smooth out the line even further by placing more emphasis on distant prices.
It's worth noting that the indicator's 'Repaint' function, which re-estimates work according to the most recent data, is not a deficiency or a flaw. Instead, it’s a crucial part of its functionality, updating the regression line with the most recent data, ensuring the indicator measurements remain as accurate as possible. We have however included a non-repaint feature that provides fixed calculations, creating a steady line that does not change once it has been plotted, for a different perspective on market trends.
This indicator also allows you to customize the line color, style, and width, allowing you to seamlessly integrate it into your existing chart setup. With labels indicating potential market turn points, you can stay on top of significant price movements.
Repaint : Enabling this allows the estimator to repaint to maintain accuracy as new data comes in.
Kernel Select : This option allows you to select from an array of kernel types such as Triangular, Gaussian, Logistic, etc. Each kernel has a unique weight function which influences how the regression line is calculated.
Bandwidth : This input, a scalar value, controls the regression line's sensitivity towards the price changes. A lower value makes the regression line more sensitive (closer to price) and higher value makes it smoother.
Source : Here you denote which price the indicator should consider for calculation. Traditionally, this is set as the close price.
Deviation : Adjust this to change the distance of the channel from the regression line. Higher values widen the channel, lower values make it smaller.
Line Style : This provides options to adjust the visual style of the regression lines. Options include Solid, Dotted, and Dashed.
Labels : Enabling this introduces markers at points where the market direction switches. Adjust the label size to suit your preference.
Colors : Customize color schemes for bullish and bearish trends along with the text color to match your chart setup.
Kernel regression, the technique behind the Multi Kernel Regression Indicator, has a rich history rooted in the world of statistical analysis and machine learning.
The origins of kernel regression are linked to the work of Emanuel Parzen in the 1960s. He was a pioneer in the development of nonparametric statistics, a domain where kernel regression plays a critical role. Although originally developed for the field of probability, these methods quickly found application in various other scientific disciplines, notably in econometrics and finance.
Kernel regression became really popular in the 1980s and 1990s along with the rise of other nonparametric techniques, like local regression and spline smoothing. It was during this time that kernel regression methods were extensively studied and widely applied in the fields of machine learning and data science.
What makes the kernel regression ideal for various statistical tasks, including financial market analysis, is its flexibility. Unlike linear regression, which assumes a specific functional form for the relationship between the independent and dependent variables, kernel regression makes no such assumptions. It creates a smooth curve fit to the data, which makes it extremely useful in capturing complex relationships in data.
In the context of stock market analysis, kernel regression techniques came into use in the late 20th century as computational power improved and these techniques could be more easily applied. Since then, they have played a fundamental role in financial market modeling, market prediction, and the development of trading indicators, like the Multi Kernel Regression Indicator.
Today, the use of kernel regression has solidified its place in the world of trading and market analysis, being widely recognized as one of the most effective methods for capturing and visualizing market trends.
The Multi Kernel Regression Indicator is built upon kernel regression, a versatile statistical method pioneered by Emanuel Parzen in the 1960s and subsequently refined for financial market analysis. It provides a robust and flexible approach to capturing complex market data relationships.
This indicator is more than just a charting tool; it reflects the power of computational trading methods, combining statistical robustness with visual versatility. It's an invaluable asset for traders, capturing and interpreting complex market trends while integrating seamlessly into diverse trading scenarios.
In summary, the Multi Kernel Regression Indicator stands as a testament to kernel regression's historic legacy, modern computational power, and contemporary trading insight.
Trend Channels With Liquidity Breaks [ChartPrime]Trend Channels
This simple trading indicator is designed to quickly identify and visualize support and resistance channels in any market. The primary purpose of the Trend Channels with Liquidity Breaks indicator is to recognize and visualize the dominant trend in a more intuitive and user-friendly manner.
Main Features
Automatically identifies and plots channels based on pivot highs and lows
Option to extend the channel lines
Display breaks of the channels where liquidity is deemed high
Inclusion of volume data within the channel bands (optional)
Market-friendly and customizable colors and settings for easy visual identification
Settings
Length: Adjust the length and lookback of the channels
Show Last Channel: Only shows the last channel
Volume BG: Shade the zones according to the volume detected
How to Interpret
Trend Channels with Liquidity Breaks indicator uses a combination of pivot highs and pivot lows to create support and resistance zones, helping traders to identify potential breakouts, reversals or continuations of a trend.
These support and resistance zones are visualized as upper and lower channel lines, with a dashed center line representing the midpoint of the channel. The indicator also allows you to see the volume data within the channel bands if you choose to enable this functionality. High volume zones can potentially signal strong buying or selling pressure, which may lead to potential breakouts or trend confirmations.
To make the channels more market-friendly and visually appealing, Trend Channels indicator also offers customizable colors for upper and lower lines, as well as the possibility to extend the line lengths for further analysis.
The indicator displays breaks of key levels in the market with higher volume.
Moving Average Trend Sniper [ChartPrime]Today we introducing the Moving Average Trend Sniper (MATS), a unique and powerful multi faceted tool. This moving average is designed to adapt to the ever-changing market conditions. MATS provides the ideal solution for traders looking to capitalize on market trends while accurately identifying support and resistance levels.
Why MATS?
MATS was developed with the trader in mind, focusing on the key factors crucial for a successful trading strategy - trend following, support, and resistance. Its unique moving average calculation not only accounts for market volatility and momentum but also provides a stable yet adaptable foundation for your trading decisions.
MATS employs a range of mathematical techniques to provide a precise and adaptive moving average, offering traders a more effective tool for analyzing market trends and identifying support and resistance levels. One of the primary distinctions of MATS is its use of delta, the change in market conditions, to update the moving average based on the trend's strength. This delta-based updating allows the moving average to adapt to market fluctuations and helps traders make more informed decisions when entering or exiting positions. MATS also focuses on the highs in a downtrend and the lows in an uptrend to provide more reliable support and resistance. By taking these crucial market points into consideration, the moving average delivers a comprehensive and accurate insight into the market's behavior and allows traders to make more precise predictions.
MATS leverages trigonometry to determine the trend angle for the moving average. By calculating this angle, MATS can efficiently pick the correct source (either the high or the low) to provide the best support and resistance analysis. This innovative use of trigonometry ensures that the moving average is better suited to the current market conditions and provides traders with a dynamic yet stable tool to support their trading decisions.
Settings:
Length: The length input for MATS plays a crucial role in determining how responsive the moving average will be to changes in market conditions. A shorter length setting results in a more reactive moving average that closely follows price movements, whereas a longer length setting generates a smoother, less volatile average. By adjusting the length setting, traders can fine-tune the sensitivity of MATS to align with their specific trading strategies and needs.
Glow: MATS offers a customizable and visually engaging display that helps traders effectively identify market trends. The "glow" effect surrounding support and resistance levels, available as an optional feature, enables users to assess these crucial areas more easily.
Example use cases:
In the screenshot below you can see the MATS acting as both a classical support and resistance while the glow and coloring is helped to provide a more classical trend following visualization to a trader. This duel functionality can help in re-entering during market retracements.
RSI Primed [ChartPrime]
RSI Primed combines candlesticks, patterns, and the classic RSI indicator for advanced market trend indications
Introduction
Technical traders are always looking for innovative methods to pinpoint potential entry and exit points in the market. The RSI Prime indicator provides such traders with an enhanced view of market conditions by combining various charting styles and the Relative Strength Index (RSI). It offers users a unique perspective on the market trends and price momentum, enabling them to make better-informed decisions and stay ahead of the market curve.
The RSI Primed is a versatile indicator that combines different charting styles with the Relative Strength Index (RSI) to help traders analyze market trends and price momentum. It offers multiple visualization modes that serve specific purposes and provide unique insights into market performance:
Regular Candlesticks
Candlesticks with Patterns
Heikin Ashi Candles
Line Style
Regular Candlestick Mode
The Regular Candlestick Mode in RSI Primed depicts traditional Japanese candlesticks that most traders are familiar with. This mode bypasses any smoothing or modified calculations, representing real-price movements. Regular candlesticks offer a clear and straightforward way to visualize market trends and price action.
Candlestick with Patterns Mode
The Candlestick with Patterns Mode focuses on identifying high-probability candlestick patterns while incorporating RSI values. By leveraging the information captured by the RSI, this mode allows traders to spot significant market reversals or continuation patterns that could signal potential trading opportunities. Some recognizable patterns include engulfing bullish, engulfing bearish, morning star bullish, and evening star bearish patterns.
Heikin Ashi Candles Mode
The Heikin Ashi Candles Mode presents an advanced candlestick charting technique known for its excellent trend-following capabilities. Heikin Ashi Candles filter out noise in the market and provide a clear representation of market trends. In this mode, candlesticks are plotted based on RSI values of the open, high, low, and close prices, helping traders understand and utilize market trends effectively.
Line Style Mode
The Line Style Mode offers a simpler and minimalistic representation of the RSI values by using a line instead of candlesticks to visualize market trends. This mode helps traders focus on the overall trend direction and eliminates potential distractions caused by the complexity of candlestick patterns.
Candle Color Overlay Mode
The Candle Color Overlay Mode is a unique feature in the RSI Primed indicator that allows traders to visualize the RSI values on the chart's candles as a heat gradient. This mode adds a color overlay to the candlesticks, representing the RSI values in relation to the candlesticks' price action.
By displaying the RSI as a color gradient, traders can quickly assess market momentum and identify overbought or oversold conditions without having to switch between different modes or charts. The gradient ranges from cool colors (blue and green) for lower RSI values, indicating oversold conditions, to warm colors (orange and red) for higher RSI values, signifying overbought situations.
To enable the Candle Color Overlay Mode, traders can toggle the "Color Candles" option in the indicator settings. Once enabled, the color gradient will be applied to the candlesticks on the chart, providing a visually striking and informative representation of the RSI values in relation to price action. This mode can be used in tandem with any of the other charting styles, allowing traders to gain even more insights into market trends and momentum.
RSI Primed Implementation
The RSI Primed indicator combines the benefits of various charting styles with the RSI to help traders gain a comprehensive view of market trends and price momentum. It incorporates the Heikin Ashi and RSI values as inputs to generate several visualization modes, enabling traders to select the one that best suits their needs.
Chebyshev Digital Audio Filter in RSI Primed Indicator
A unique feature of the RSI Primed Indicator is the incorporation of the Chebyshev Digital Audio Filter, a powerful tool that significantly influences the indicator's accuracy and responsiveness. This signal processing method brings several benefits to the context of the RSI indicator, improving its performance and capabilities.
1. Improved Signal Filtering
The Chebyshev filter excels in its ability to remove high-frequency noise and unwanted signals from the RSI data. While other filtering techniques might introduce unwanted side effects or distort the RSI data, the Chebyshev filter accurately retains the main signal components, enhancing the RSI Primed's overall accuracy and reliability.
2. Faster Response Time
The Chebyshev filter offers a faster response time than most other filtering techniques. In the context of the RSI Primed Indicator, this means that the filtering process is quicker and more efficient, allowing traders to act swiftly during rapidly changing market conditions.
3. Enhanced Trend Detection
By effectively removing noise from the RSI data, the Chebyshev filter contributes to the enhanced detection of underlying market trends. This feature helps traders identify potential entry and exit points more accurately, improving their overall trading strategy and performance.
How to Use RSI Primed
Traders can choose from different visualization modes to suit their preferences while using the RSI Primed indicator. By closely monitoring the chosen visualization mode and the position of the moving average, traders can make informed decisions about market trends.
Green candlesticks or an upward line slope indicate a bullish trend, and red candlesticks or a downward line slope suggest a bearish trend. If the candles or line are above the moving average, it could signify an uptrend, whereas a position below the moving average may indicate a downtrend.
The RSI Primed indicator offers a unique and comprehensive perspective on market trends and price momentum by combining various charting styles with the RSI. Traders can choose from different visualization modes and make well-informed decisions to capitalize on market opportunities. This innovative indicator provides a clear and concise view of the market, enabling traders to make swift decisions and enhance their trading results.
Bar Magnified Volume Profile/Fixed Range [ChartPrime]This indicator draws a volume profile by utilizing data from the lower timeframe to get a more accurate representation of where volume occurred on a bar to bar basis. The indicator creates a price range, and then splits that price range into 100 grids by default. The indicator then drops down to the lower timeframe, approximately 16 times lower than the current timeframe being viewed on the chart, and then parses through all of the lower timeframe bars, and attributes the lower timeframe bar volume to all grids that it is touching. The volume is dispersed proportionally to the grids which it is touching by whatever percent of the candle is inside each grid. For example, if one of the lower timeframe bars is interacting with "2" of the grids in the profile, and 60% of the candle is inside of the top grid, 60% of the volume from said candle will be attributed to the grid.
To make all of this magic happen, this script utilizes a quadratic time complexity algorithm while parsing and attributing the volume to all of the grids. Due to this type of algorithm being used in the script, many of the user inputs have been limited to allow for simplicity, but also to prevent possible errors when executing loops. For the most part, all of the settings have been thoroughly tested and configured with the right amount of limitations to prevent these errors, but also still give the user a broad range of flexibility to adjust the script to their liking.
📗 SETTINGS
Lookback Period: The lookback period determines how many bars back the script will search for the "highest high" and the "lowest low" which will then be used to generate the grids in-between
Number Of Levels: This setting determines how many grids there will be within the volume profile/fixed range. This is personal preference, however it is capped at 100 to prevent time complexity issues
Profile Length: This setting allows you to stretch or thin the volume profile. A higher number will stretch it more, vise versa a smaller number will thin it further. This does not change the volume profiles results or values, only its visual appearance.
Profile Offset: This setting allows you to offset the profile to the left or right, in the event the user does not appreciate the positioning of the default location of the profile. A higher number will shift it to the right, vise versa a lower number will shift it to the left. This is personal preference and does not affect the results or values of the profile.
🧰 UTILITY
The volume profile/fixed range can be used in many ways. One of the most popular methods is to identify high volume areas on the chart to be used as trade entries or exits in the event of the price revisiting the high volume areas. Take this picture as an example. The image clearly demonstrates how the 2 highest areas of volume within this magnified volume profile also line up to great areas of support and resistance in the market.
Here are some other useful methods of using the volume profile/fixed range
Identify Key Support and Resistance Levels for Setups
Determine Logical Take Profits and Stop Losses
Calculate Initial R Multiplier
Identify Balanced vs Imbalanced Markets
Determine Strength of Trends
Historical Volatility Scale [ChartPrime]This indicator outputs a visual scale representing the level of volatility in the market relative to the timeframe selected on the users chart. The method of volatility used is "historical volatility" which is calculated by taking the standard deviation of a series of "x" length which contains the current closing price divided by the previous closing price for all nodes. The output of the volatility is standardized by also running an additional percentrank calculation over the raw volatility values to allow the volatility scale to oscillate properly between its minimum of 0 and maximum of 100.
📗 SETTINGS
Length: The length determines how many bars/nodes should be considered when calculating the standard deviation. In simple terms, the higher the length, the less sensitive and less reactive the scale will be to current price action, and larger moves would be required to trigger the scale.
🧰 UTILITY
The arrow or "The Pin" will move upwards towards the "fire" emoji when the volatility is higher than the majority of values for the amount of bars back that you set the "length" setting to. Vise Versa for when the pin is lowering towards the "snooze" emoji, the volatility is less than the majority of nodes/values for the past "length" amount of values.
When the volatility is low, a trader could consider utilizing more leading indicators to make their trading decisions as opposed to lagging indicator such as trend indicators. When the volatility is low, the price action is consolidation which would be bad for a trend following strategy. Vise Versa for trend strategies, having a higher volatility may be better for such strategies.
Its important to remember that this indicator itself is a lagging indicator, in that it relies on historical data to showcase the current state of the markets volatility. This means that although the recommendation in the previous paragraph may make logical sense, it is not a guarantee that if the volatility is showcasing a trending market, that your trend strategies will necessarily be profitable.
Parabolic Scalp Take Profit[ChartPrime]Indicators can be a great way to signal when the optimal time is for taking profits. However, many indicators are lagging in nature and will get market participants out of their trades at less than optimal price points. This take profit indicator uses the concept of slope and exponential gain to calculate when the optimal time is to take profits on your trades, thus making this a leading indicator.
Usage:
In essence the indicator will draw a parabolic line that starts from the market participants entry point and exponentially grows the slope of the line eventually intersecting with the price action. When price intersects with the parabolic line a take profit signal will appear in the form of an x. We have found that this take profit indicator is especially useful for scalp trades on lower timeframes.
How To Use:
Add the indicator to the chart. Click on the candle which the trade is on. Click on either the price which the trade will be at, or at the bottom of the candle in a long, or the top of a candle in a short. Select long or short. Open the settings of the indicator and adjust the aggressiveness to the desired value.
Settings:
- Start Time -- This is the bar in which your entry will be at, or occured at and the script will ask you to click on the bar with your mouse upon first adding the script.
- Start Price -- This is the price in which the entry will be at, or was at and the script will ask you to click on the price with your mouse upon first adding the script.
- Long/Short -- This is a setting which lets the script know if it is a long or a short trade, and the script will ask you to confirm this upon first adding it to the chart.
- Aggressiveness -- This directly affects how aggressive the exponential curve is. A value of 101 is the lowest possible setting, indicating a very non-aggressive exponential buildup. A value of 200 is the highest and most aggressive setting, indicating a doubling effect per bar on the slope.
Quick Shot[ChartPrime]This indicator plots green and red dots when the trend changes based on a moving average slope. The curved line aims to exponentially increase the slope of the moving average based on the slope at the time of the dots origination as the bars progress. Once the curved line makes contact with the price action, an x shape will be plotted to signify an exit signal.
This indicator is best used in confluence with other indicators in order to develop a reliable strategy.
RSI-Adaptive T3 [ChartPrime] — Strategy (Long Only, 1D)This trade has been successfully converted from an individual setup to a full strategy, and the results are truly outstanding. I’m currently testing this for Tesla options trading on the 1-day chart, and it appears to be working extremely well.
A special thanks to ChartPrime for creating such a beautifully designed indicator — it’s performing impressively in these tests.
If anyone would like to try it out, feel free to download and see the results for yourself. Thank you!
RSI-Adaptive T3 + Squeeze Momentum Strategy✅ Strategy Guide: RSI-Adaptive T3 + Squeeze Momentum Strategy
📌 Overview
The RSI-Adaptive T3 + Squeeze Momentum Strategy is a dynamic trend-following strategy based on an RSI-responsive T3 moving average and Squeeze Momentum detection .
It adapts in real-time to market volatility to enhance entry precision and optimize risk.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main objective of this strategy is to catch the early phase of a trend and generate consistent entry signals.
Designed to be intuitive and accessible for traders from beginner to advanced levels.
✨ Key Features
RSI-Responsive T3: T3 length dynamically adjusts according to RSI values for adaptive trend detection
Squeeze Momentum: Combines Bollinger Bands and Keltner Channels to identify trend buildup phases
Visual Triggers: Entry signals are generated from T3 crossovers and momentum strength after squeeze release
📊 Trading Rules
Long Entry:
When T3 crosses upward, momentum is positive, and the squeeze has just been released.
Short Entry:
When T3 crosses downward, momentum is negative, and the squeeze has just been released.
Exit (Reversal):
When the opposite condition to the entry is triggered, the position is reversed.
💰 Risk Management Parameters
Pair & Timeframe: BTC/USD (30-minute chart)
Capital (simulated): $30,00
Order size: `$100` per trade (realistic, low-risk sizing)
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 5%
Number of Trades (backtest period): 181
📊 Performance Overview
Symbol: BTC/USD
Timeframe: 30-minute chart
Date Range: January 1, 2024 – July 3, 2025
Win Rate: 47.8%
Profit Factor: 2.01
Net Profit: 173.16 (units not specified)
Max Drawdown: 5.77% or 24.91 (0.79%)
⚙️ Indicator Parameters
Indicator Name: RSI-Adaptive T3 + Squeeze Momentum
RSI Length: 14
T3 Min Length: 5
T3 Max Length: 50
T3 Volume Factor: 0.7
BB Length: 27 (Multiplier: 2.0)
KC Length: 20 (Multiplier: 1.5, TrueRange enabled)
🖼 Visual Support
T3 slope direction, squeeze status, and momentum bars are visually plotted on the chart,
providing high clarity for quick trend analysis and execution.
🔧 Strategy Improvements & Uniqueness
Inspired by the RSI Adaptive T3 by ChartPrime and Squeeze Momentum Indicator by LazyBear ,
this strategy fuses both into a hybrid trend-reversal and momentum breakout detection system .
Compared to traditional trend-following methods, it excels at capturing early trend signals with greater sensitivity .
✅ Summary
The RSI-Adaptive T3 + Squeeze Momentum Strategy combines momentum detection with volatility-responsive risk management.
With a strong balance between visual clarity and practicality, it serves as a powerful tool for traders seeking high repeatability.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use appropriate risk management when applying it.
RSI Strategy [PrimeAutomation]⯁ OVERVIEW
The RSI Strategy is a momentum-driven trading system built around the behavior of the Relative Strength Index (RSI).
Instead of using traditional overbought/oversold zones, this strategy focuses on RSI breakouts with volatility-based trailing stops, adaptive profit-targets, and optional early-exit logic.
It is designed to capture strong continuation moves after momentum shifts while protecting trades using ATR-based dynamic risk management.
⯁ CONCEPTS
RSI Breakout Momentum: Entries happen when RSI breaks above/below custom thresholds, signaling a shift in momentum rather than mean reversion.
Volatility-Adjusted Risk: ATR defines both stop-loss and profit-target distances, scaling positions based on market volatility.
Dynamic Trailing Stop: The strategy maintains an adaptive trailing level that tightens as price moves in the trade’s favor.
Single-Position System: Only one trade at a time (no pyramiding), maximizing clarity and simplifying execution.
⯁ KEY FEATURES
RSI Signal Engine
• Long when RSI crosses above Upper threshold
• Short when RSI crosses below Lower threshold
These levels are configurable and optimized for trend-momentum detection.
ATR-Based Stop-Loss
A custom ATR multiplier defines the initial stop.
• Long stop = price – ATR × multiplier
• Short stop = price + ATR × multiplier
Stops adjust continuously using a trailing model.
ATR-Based Take Profit (Optional)
Profit targets scale with volatility.
• Long TP = entry + ATR × TP-multiplier
• Short TP = entry – ATR × TP-multiplier
Users can disable TP and rely solely on trailing stops.
Real-Time Trailing Logic
The stop updates bar-by-bar:
• In a long trade → stop moves upward only
• In a short trade → stop moves downward only
This keeps the stop tight as trends develop.
Early Exit Module (Optional)
After X bars in a trade, opposite RSI signals trigger exit.
This reduces holding time during weak follow-through phases.
Full Visual Layer
• RSI plotted with threshold fills
• Entry/TP/Stop visual lines
• Color-coded zones for clarity
⯁ HOW TO USE
Look for RSI Breakouts:
Focus on RSI crossing above the upper boundary (long) or below the lower boundary (short). These moments identify fresh momentum surges.
Use ATR Levels to Manage Risk:
Because stops and targets scale with volatility, the strategy adapts well to both quiet and explosive market phases.
Monitor Trailing Stops for Trend Continuation:
The trailing stop is the primary driver of exits—often outperforming fixed targets by catching larger runs.
Use on Liquid Markets & Mid-Higher Timeframes:
The system performs best where RSI and ATR signals are clean—crypto majors, FX, and indices.
⯁ CONCLUSION
The RSI Strategy is a modern RSI breakout system enhanced with volatility-adaptive risk management and flexible exit logic. It is designed for traders who prefer momentum confirmation over mean reversion, offering a disciplined framework with robust protections and dynamic trend-following capability.
Its blend of ATR-based stops, optional profit targets, and RSI-driven entries makes it a reliable strategy across a wide range of market conditions.
DEMA ATR Strategy [PrimeAutomation]⯁ OVERVIEW
The DEMA ATR Strategy combines trend-following logic with adaptive volatility filters to identify strong momentum phases and manage trades dynamically.
It uses a Double Exponential Moving Average (DEMA) anchored to ATR volatility bands, creating a self-adjusting trend baseline.
When the adjusted DEMA shifts direction, the strategy enters positions and scales out profit in phases based on ATR-driven targets.
This system adapts to volatility, filters noise, and seeks sustained directional moves.
⯁ KEY FEATURES
DEMA-Volatility Hybrid Filter
Uses Double EMA with ATR expansion/compression logic to form a dynamic trend baseline.
Directional Shift Entries
Entries occur when the adjusted DEMA flips trend (bullish crossover or bearish crossunder vs its past value).
Noise Reduction Mechanism
ATR range caps extreme moves and prevents false flips during choppy volatility spikes.
Multi-Level Take Profits
Targets scale out positions at 1×, 2×, and 3× ATR multiples in the trade direction.
Volatility-Adaptive Targets
ATR multiplier ensures profit targets expand/contract based on market conditions.
Single-Direction Exposure
No pyramiding; the strategy flips position only when trend shifts.
Automated Trade Finalization
When all profit targets trigger, the position is fully closed.
⯁ STRATEGY LOGIC
Trend Direction:
DEMA baseline is modified using ATR upper/lower envelopes.
• If the adjusted DEMA rises above previous value → Bullish
• If it falls below previous value → Bearish
Entry Rules:
• Enter Long when bullish shift occurs and no long position exists
• Enter Short when bearish shift occurs and no short position exists
Take Profit Logic:
3 partial exits for each trade based on ATR:
• TP1 = ±1× ATR
• TP2 = ±2× ATR
• TP3 = ±3× ATR
Profit distribution: 30% / 30% / 40%
Exit Conditions:
• Exit when all TPs hit (full scale-out if sum of all TPs 100%)
• Opposite trend signal closes current trade and opens new one
⯁ WHEN TO USE
Trending environments
Medium–high volatility phases
Swing trading and intraday trend plays
Markets that respect momentum continuation (crypto, indices, FX majors)
⯁ CONCLUSION
This strategy blends DEMA trend recognition with ATR-based volatility adaptation to generate cleaner directional entries and structured take-profit exits. It is designed to capture momentum phases while avoiding noise-driven false signals, delivering a disciplined and scalable trend-following approach.
RSI-Adaptive T3 & SAR Strategy [PrimeAutomation]⯁ OVERVIEW
The RSI-Adaptive T3 and SAR Confluence Strategy combines adaptive smoothing with dynamic trend confirmation to identify precise trend reversals and continuation opportunities. It fuses the power of an RSI-based adaptive T3 moving average with the Parabolic SAR filter , aiming to trade in harmony with dominant momentum shifts while maintaining tight control through automatic stop-loss placement.
The RSI-Adaptive T3 is a precision trend-following tool built around the legendary T3 smoothing algorithm developed by Tim Tillson, designed to enhance responsiveness while reducing lag compared to traditional moving averages. Current implementation takes it a step further by dynamically adapting the smoothing length based on real-time RSI conditions — allowing the T3 to “breathe” with market volatility. This dynamic length makes the curve faster in trending moves and smoother during consolidations.
To help traders visualize volatility and directional momentum, adaptive volatility bands are plotted around the T3 line, with visual crossover markers and a dynamic info panel on the chart. It’s ideal for identifying trend shifts, spotting momentum surges, and adapting strategy execution to the pace of the market.
⯁ LOGIC
The T3 moving average length dynamically adjusts based on RSI values — when RSI is high, the smoothing period shortens to react faster; when RSI is low, the period increases for stability in slow markets.
A Parabolic SAR filter confirms directional bias, ensuring trades only occur in alignment with the broader market trend.
Long Entries: Trigger when the T3 curve crosses upward while the current price remains above the SAR — signaling bullish momentum alignment.
Short Entries: Trigger when the T3 crosses downward while the price remains below the SAR — confirming bearish trend alignment.
Stops: Dynamic stops are placed using the highest or lowest price over a set lookback period, adapting automatically to market volatility.
⯁ FEATURES
RSI-Adaptive T3 Filter: Adjusts smoothing in real time to market conditions, blending responsiveness with noise reduction.
SAR Confluence Check: Prevents counter-trend entries by confirming momentum direction via the Parabolic SAR.
Automatic Stop Placement: Uses recent highs or lows as stop-loss anchors, minimizing risk exposure.
Color-coded Visualization: The T3 line dynamically changes color based on slope direction, making momentum shifts visually intuitive.
Smoothed Trend Structure: Reduces market noise, allowing cleaner, more reliable trend recognition across different assets.
⯁ CONCLUSION
The RSI-Adaptive T3 and SAR Confluence Strategy delivers an advanced fusion of adaptive smoothing and structural confirmation. By combining RSI-driven reactivity with Parabolic SAR trend validation, this strategy offers a balanced approach to identifying sustainable momentum reversals while maintaining strong risk management through automatic stop levels. Ideal for traders who seek precision entries aligned with adaptive trend dynamics.
Linear Regression ChannelLinear Regression Channel Indicator
Overview:
The Linear Regression Channel Indicator is a versatile tool designed for TradingView to help traders visualize price trends and potential reversal points. By calculating and plotting linear regression channels, bands, and future projections, this indicator provides comprehensive insights into market dynamics. It can highlight overbought and oversold conditions, identify trend direction, and offer visual cues for future price movements.
Key Features:
Linear Regression Bands:
Input: Plot Linear Regression Bands
Description: Draws bands based on linear regression calculations, representing overbought and oversold levels.
Customizable Parameters:
Length: Defines the look-back period for the regression calculation.
Deviation: Determines the width of the bands based on standard deviations.
Linear Regression Channel:
Input: Plot Linear Regression Channel
Description: Plots a channel using linear regression to visualize the main trend.
Customizable Parameters:
Channel Length: Defines the look-back period for the channel calculation.
Deviation: Determines the channel's width.
Future Projection Channel:
Input: Plot Future Projection of Linear Regression
Description: Projects a linear regression channel into the future, aiding in forecasting potential price movements.
Customizable Parameters:
Length: Defines the look-back period for the projection calculation.
Deviation: Determines the width of the projected channel.
Arrow Direction Indicator:
Input: Plot Arrow Direction
Description: Displays directional arrows based on future projection, indicating expected price movement direction.
Color-Coded Price Bars:
Description: Colors the price bars based on their position within the regression bands or channel, providing a heatmap-like visualization.
Dynamic Visualization:
Colors: Uses a gradient color scheme to highlight different conditions, such as uptrend, downtrend, and mid-levels.
Labels and Markers: Plots visual markers for significant price levels and conditions, enhancing interpretability.
Usage Notes
Setting the Length:
Adjust the look-back period (Length) to suit the timeframe you are analyzing. Shorter lengths are responsive to recent price changes, while longer lengths provide a broader view of the trend.
Interpreting Bands and Channels:
The bands and channels help identify overbought and oversold conditions. Price moving above the upper band or channel suggests overbought conditions, while moving below the lower band or channel indicates oversold conditions.
Using the Future Projection:
Enable the future projection channel to anticipate potential price movements. This can be particularly useful for setting target prices or stop-loss levels based on expected trends.
Arrow Direction Indicator:
Use the arrow direction indicator to quickly grasp the expected price movement direction. An upward arrow indicates a potential uptrend, while a downward arrow suggests a potential downtrend.
Color-Coded Price Bars:
The color of the price bars changes based on their relative position within the regression bands or channel. This heatmap visualization helps quickly identify bullish, bearish, and neutral conditions.
Dynamic Adjustments:
The indicator dynamically adjusts its visual elements based on user settings and market conditions, ensuring that the most relevant information is always displayed.
Visual Alerts:
Pay attention to the labels and markers on the chart indicating significant events, such as crossovers and breakouts. These visual alerts help in making informed trading decisions.
The Linear Regression Channel Indicator is a powerful tool for traders looking to enhance their technical analysis. By offering multiple regression-based visualizations and customizable parameters, it helps identify key market conditions, trends, and potential reversal points. Whether you are a day trader or a long-term investor, this indicator can provide valuable insights to improve your trading strategy.
Adaptive Trend Breaks Adaptive Trend Breaks
## WHAT IT DOES
This script is a modified and enhanced version of "Trendline Breakouts With Targets" concept by ChartPrime.
Adaptive Trend Breaks (ATB) is a trendline breakout system optimized for scalping liquid futures contracts. The indicator automatically draws dynamic support and resistance trendlines based on pivot points, then generates trade signals when price breaks through these levels with confirmation filters. It includes automated target and stop-loss placement with real-time P&L tracking in dollars.
## HOW IT WORKS
**Trendline Detection Method:**
The indicator uses pivot high/low detection to identify significant price turning points. When a new pivot forms, it calculates the slope between consecutive pivots to draw dynamic trendlines. These lines extend forward based on the established trend angle, creating actionable support and resistance zones.
**Band System:**
Around each trendline, the script creates a "band" using a volatility-adjusted calculation: `ATR(14) * 0.2 * bandwidth multiplier / 2`. This adaptive band accounts for current market conditions - wider during volatile periods, tighter during quiet markets.
**Breakout Logic:**
A breakout signal triggers when:
1. Price closes beyond the trendline + band zone
2. Volume exceeds the 20-period moving average by your set multiplier (default 1.2x)
3. Price is within Regular Trading Hours (9:30-16:00 EST) if session filter enabled
4. Current ATR meets minimum volatility threshold (prevents trading dead markets)
**Target & Stop Calculation:**
Upon breakout confirmation:
- **Entry**: Trendline breach point
- **Target**: Entry ± (bandwidth × target multiplier) - default 8x for quick scalps
- **Stop**: Entry ± (bandwidth × stop multiplier) - default 8x for 1:1 risk/reward
- Multipliers adjust automatically to market volatility through the ATR-based band
**P&L Conversion:**
The script converts point movements to dollars using:
```
Dollar P&L = (Price Points × Contract Point Value × Quantity)
```
For example, a 10-point NQ move with 2 contracts = 10 × $20 × 2 = $400
## HOW TO USE IT
**Setup:**
1. Select your instrument (NQ/ES/YM/RTY) - point values auto-configure
2. Set contract quantity for accurate dollar P&L
3. Choose pivot period (lower = more signals but more noise, default 5 for scalping)
4. Adjust bandwidth multiplier if trendlines are too tight/loose (1-5 range)
**Filters Configuration:**
- **Volume Filter**: Requires breakout volume > moving average × multiplier. Increase multiplier (1.5-2.0) for higher conviction trades
- **Session Filter**: Enable to trade only RTH. Disable for 24-hour trading
- **ATR Filter**: Prevents signals during low volatility. Increase minimum % for more active markets only
**Risk Management:**
- Set target/stop multipliers based on your risk tolerance
- 8x bandwidth = approximately 1:1 risk/reward for most liquid futures
- Enable trailing stops for trend-following approach (moves stop to protect profits)
- Adjust line length to see targets further into the future
**Statistics Table:**
- Choose timeframe to analyze: all-time, today, this week, custom days
- Monitor win rate, profit factor, and net P&L in dollars
- Track long vs short performance separately
- See real-time unrealized P&L on active trades
**Reading Signals:**
- **Green triangle below bar** = Long breakout (resistance broken)
- **Red triangle above bar** = Short breakout (support broken)
- **White dashed line** = Entry price
- **Orange line** = Take profit target with dollar value
- **Red line** = Stop loss with dollar value
- **Green checkmark (✓)** = Target hit, winning trade
- **Red X (✗)** = Stop hit, losing trade
## WHAT IT DOES NOT DO
**Limitations to Understand:**
- Does not predict future trendline formations - it reacts to breakouts after they occur
- Historical trendlines disappear after breakout (not kept on chart for clarity)
- Requires sufficient volatility - may not signal in extremely quiet markets
- Volume filter requires exchange volume data (not available on all symbols)
- Statistics are indicator-based simulations, not actual trading results
- Does not account for slippage, commissions, or order fills
## BEST PRACTICES
**Recommended Settings by Market:**
- **NQ (Nasdaq)**: Default settings work well, consider volume multiplier 1.3-1.5
- **ES (S&P 500)**: Slightly slower, try period 7-8, volume 1.2
- **YM (Dow)**: Lower volatility, reduce bandwidth to 1.5-2
- **RTY (Russell)**: Higher volatility, increase bandwidth to 3-4
**Risk Management:**
- Never risk more than 2-3% of account per trade
- Use contract quantity calculator: Max Risk $ ÷ (Stop Distance × Point Value)
- Start with 1 contract while learning the system
- Backtest your specific timeframe and instrument before live trading
**Optimization Tips:**
- Increase pivot period (7-10) for fewer but higher-quality signals
- Raise volume multiplier (1.5-2.0) in choppy markets
- Lower target/stop multipliers (5-6x) for tighter profit taking
- Use trailing stops in strong trending conditions
- Disable session filter for overnight gaps and Asia session moves
## TECHNICAL DETAILS
**Key Calculations:**
- Pivot Detection: `ta.pivothigh(high, period, period/2)` and `ta.pivotlow(low, period, period/2)`
- Slope Calculation: `(newPivot - oldPivot) / (newTime - oldTime)`
- Adaptive Band: `min(ATR(14) * 0.2, close * 0.002) * multiplier / 2`
- Breakout Confirmation: Price crosses trendline + 10% of band threshold
**Data Requirements:**
- Minimum bars in view: 500 for proper pivot calculation
- Volume data required for volume filter accuracy
- Intraday timeframes recommended (1min - 15min) for scalping
- Works on any timeframe but optimized for fast execution
**Performance Metrics:**
All statistics calculate based on indicator signals:
- Tracks every signal as a trade from entry to TP/SL
- P&L in actual contract dollar values
- Win rate = (Winning trades / Total trades) × 100
- Profit factor = Gross profit / Gross loss
- Separates long/short performance for bias analysis
## IDEAL FOR
- Futures scalpers and day traders
- Traders who prefer visual trendline breakouts
- Those wanting automated TP/SL placement
- Traders tracking performance in dollar terms
- Multiple timeframe analysis (compare 1min vs 5min signals)
## NOT SUITABLE FOR
- Swing trading (targets too close)
- Stocks/forex without modifying point values
- Extremely low timeframes (<30 seconds) - too much noise
- Markets without volume data if using volume filter
- Illiquid contracts (signals may not execute at shown prices)
---
**Settings Summary:**
- Core: Period, bandwidth, extension, trendline style
- Filters: Volume, RTH session, ATR volatility
- Risk: R:R ratio, target/stop multipliers, trailing stop
- Display: Stats table position, size, colors
- Stats: Timeframe selection (all-time to custom days)
**License:** This indicator is published open-source under Mozilla Public License 2.0. You may use and modify the code with proper attribution.
**Disclaimer:** This indicator is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and test thoroughly before live trading.
---
## CREDITS & ATTRIBUTION
This script builds upon the "Trendline Breakouts With Targets" concept by ChartPrime with significant enhancements:
**Major Improvements Added:**
- **Futures-Specific Calculations**: Automated dollar P&L conversion using actual contract point values (NQ=$20, ES=$50, YM=$5, RTY=$50)
- **Advanced Statistics Engine**: Comprehensive performance tracking with customizable timeframe analysis (today, week, month, custom ranges)
- **Multi-Layer Filtering System**: Volume confirmation, RTH session filter, and ATR volatility filter to reduce false signals
- **Professional Trade Management**: Enhanced visual trade tracking with separate TP/SL lines, dollar value labels, and optional trailing stops
- **Optimized for Scalping**: Faster pivot periods (5 vs 10), tighter bands, and reduced extension bars for quick entries
Original trendline detection methodology by ChartPrime - used with modification under Mozilla Public License 2.0.
Dynamic Signal EngineDynamic Signal Engine
The Dynamic Signal Engine is a powerful and versatile indicator, designed to help traders make informed decisions by combining trend analysis with key support and resistance levels. This tool is inspired by the Linear Regression Oscillator , which laid the foundation for this enhanced implementation. By building on the original concept, this script introduces additional features, customization, and integration with dynamic trading strategies to suit diverse trading styles.
Key Features
Inspiration and Foundation
This indicator draws inspiration from the Linear Regression Oscillator , leveraging its robust trend detection capabilities while adding custom enhancements for broader functionality and user adaptability.
Trading Style Customization
Adaptable for Scalping, Intraday, and Swing Trading with dynamic parameter adjustments for each style.
User-defined inputs for thresholds, lookback periods, and visualization options provide further control.
Enhanced Linear Regression Oscillator (LRO)
A refined implementation of the LRO calculates deviations from a regression line, normalized for improved trend detection.
Identifies bullish and bearish crossovers with added alerts and visual markers.
Includes proximity alerts for critical thresholds to help traders anticipate key market movements.
Dynamic Support and Resistance Integration
Incorporates ENIGMA Signal Logic to identify swing highs and lows, dynamically marking them as fractal support and resistance levels.
When a sell signal from ENIGMA is generated, traders can choose to sell immediately or use the low of the previous candle as the entry point. Similarly, for a buy signal, traders can buy immediately or use the high of the previous candle for entry. These signals are visually indicated by a green triangle for buy signals, ensuring clear and actionable insights.
Advanced Visualization
Displays key levels with customizable horizontal lines (solid, dashed, or dotted) and labels for clarity.
Candle colours and mini arrows highlight trends and potential trading opportunities.
Real-Time Alerts
Alerts for LRO threshold crossings and swing-level breaches keep you updated without the need for constant monitoring.
Optimized for Usability
Designed to keep charts clean by limiting displayed trades and signals to recent activity.
Adjustable parameters ensure flexibility and a user-friendly experience.
How It Works
Trend Detection with Enhanced LRO
The indicator builds on the Linear Regression Oscillator , calculating oscillations of price movements and normalizing them for trend analysis. Crossovers and threshold proximity are visualized on the chart and trigger alerts for potential market shifts.
Dynamic Support and Resistance Levels
The ENIGMA Signal Logic identifies recent swing highs and lows, marking them as key levels. These levels are dynamically updated as new swing points are detected, providing actionable support and resistance zones.
Signal Confirmation
Buy or sell signals are confirmed when:
Price breaches the swing levels.
The LRO aligns with directional bias (e.g., bearish crossover for sell signals).
Signals are further clarified by ENIGMA's green triangle indicators, showing key buy and sell opportunities.
Visualization and Alerts
Signals are displayed using arrows, labelled horizontal lines, and optional candle colours. Alerts notify traders of key events, such as LRO threshold crossings or swing-level breaches.
How to Use
Choose your Trading Style: Scalping, Intraday, or Swing Trading. The indicator adjusts its default settings automatically.
Fine-tune parameters like LRO thresholds, line lengths, and the number of visible trades to suit your preferences.
Observe the chart for signals:
Green arrows and lines indicate buy opportunities.
Red arrows and lines signal sell opportunities.
Use the alert system to stay informed about LRO thresholds and signal confirmations.
Integrate the indicator with your existing trading strategy for better decision-making.
Acknowledgement
This script was inspired by the Linear Regression Oscillator . While it builds on the core concept, this implementation introduces unique enhancements, such as dynamic signal integration, trading style adaptability, and advanced visualization tools, making it a highly customizable and versatile tool for traders.
Disclaimer
This indicator is intended for educational purposes only and should not be considered financial advice. Always perform due diligence and apply appropriate risk management when trading.
Liquidity Hunter + ShortLiquidity Hunter + Short
Version with Short Trade Signals by Cihan Culha
This indicator is based on the original Liquidity Hunter by ChartPrime (MPL 2.0 license).
It detects potential Long and Short liquidity hunts by analyzing candle body, wick percentages, ATR bands, and slope direction.
Features:
Long signals (original) based on lower wick, body %, slope, and ATR bands
Short signals (added) based on upper wick, body %, negative slope, and ATR bands
Target (TP), Stop Loss (SL), CHOCH, and BOS levels plotted dynamically
Visual boxes highlight potential liquidity zones
Risk/Reward (RR) configurable via input
Usage Notes:
This modified version adds Short trade signals while preserving the original Long logic
Original author ChartPrime is credited; modifications by Cihan Culha
Adjust Body %, Wick %, and RR multiplier to suit your trading timeframe and style
For educational purposes; always use proper risk management
Kernel Regression Bands SuiteMulti-Kernel Regression Bands
A versatile indicator that applies kernel regression smoothing to price data, then dynamically calculates upper and lower bands using a wide variety of deviation methods. This tool is designed to help traders identify trend direction, volatility, and potential reversal zones with customizable visual styles.
Key Features
Multiple Kernel Types: Choose from 17+ kernel regression styles (Gaussian, Laplace, Epanechnikov, etc.) for smoothing.
Flexible Band Calculation: Select from 12+ deviation types including Standard Deviation, Mean/Median Absolute Deviation, Exponential, True Range, Hull, Parabolic SAR, Quantile, and more.
Adaptive Bands: Bands are calculated around the kernel regression line, with a user-defined multiplier.
Signal Logic: Trend state is determined by crossovers/crossunders of price and bands, coloring the regression line and band fills accordingly.
Custom Color Modes: Six unique color palettes for visual clarity and personal preference.
Highly Customizable Inputs: Adjust kernel type, lookback, deviation method, band source, and more.
How to Use
Trend Identification: The regression line changes color based on the detected trend (up/down)
Volatility Zones: Bands expand/contract with volatility, helping spot breakouts or mean-reversion opportunities.
Visual Styling: Use color modes to match your chart theme or highlight specific market states.
Credits:
Kernel regression logic adapted from:
ChartPrime | Multi-Kernel-Regression-ChartPrime (Link in the script)
Disclaimer
This script is for educational and informational purposes only. Not financial advice. Use at your own risk.
