Bollinger Bands Liquidity Cloud [ChartPrime]This indicator overlays a heatmap on the price chart, providing a detailed representation of Bollinger bands' profile. It offers insights into the price's behavior relative to these bands. There are two visualization styles to choose from: the Volume Profile and the Z-Score method.
Features
Volume Profile: This method illustrates how the price interacts with the Bollinger bands based on the traded volume.
Z-Score: In this mode, the indicator samples the real distribution of Z-Scores within a specified window and rescales this distribution to the desired sample size. It then maps the distribution as a heatmap by calculating the corresponding price for each Z-Score sample and representing its weight via color and transparency.
Parameters
Length: The period for the simple moving average that forms the base for the Bollinger bands.
Multiplier: The number of standard deviations from the moving average to plot the upper and lower Bollinger bands.
Main:
Style: Choose between "Volume" and "Z-Score" visual styles.
Sample Size: The size of the bin. Affects the granularity of the heatmap.
Window Size: The lookback window for calculating the heatmap. When set to Z-Score, a value of `0` implies using all available data. It's advisable to either use `0` or the highest practical value when using the Z-Score method.
Lookback: The amount of historical data you want the heatmap to represent on the chart.
Smoothing: Implements sinc smoothing to the distribution. It smoothens out the heatmap to provide a clearer visual representation.
Heat Map Alpha: Controls the transparency of the heatmap. A higher value makes it more opaque, while a lower value makes it more transparent.
Weight Score Overlay: A toggle that, when enabled, displays a letter score (`S`, `A`, `B`, `C`, `D`) inside the heatmap boxes, based on the weight of each data point. The scoring system categorizes each weight into one of these letters using the provided percentile ranks and the median.
Color
Color: Color for high values.
Standard Deviation Color: Color to represent the standard deviation on the Bollinger bands.
Text Color: Determines the color of the letter score inside the heatmap boxes. Adjusting this parameter ensures that the score is visible against the heatmap color.
Usage
Once this indicator is applied to your chart, the heatmap will be overlaid on the price chart, providing a visual representation of the price's behavior in relation to the Bollinger bands. The intensity of the heatmap is directly tied to the price action's intensity, defined by your chosen parameters.
When employing the Volume Profile style, a brighter and more intense area on the heatmap indicates a higher trading volume within that specific price range. On the other hand, if you opt for the Z-Score method, the intensity of the heatmap reflects the Z-Score distribution. Here, a stronger intensity is synonymous with a more frequent occurrence of a specific Z-Score.
For those seeking an added layer of granularity, there's the "Weight Score Overlay" feature. When activated, each box in your heatmap will sport a letter score, ranging from `S` to `D`. This score categorizes the weight of each data point, offering a concise breakdown:
- `S`: Data points with a weight of 1.
- `A`: Weights below 1 but greater than or equal to the 75th percentile rank.
- `B`: Weights under the 75th percentile but at or above the median.
- `C`: Weights beneath the median but surpassing the 25th percentile rank.
- `D`: All that fall below the 25th percentile rank.
This scoring feature augments the heatmap's visual data, facilitating a quicker interpretation of the weight distribution across the dataset.
Further Explanations
Volume Profile
A volume profile is a tool used by traders to visualize the amount of trading volume occurring at specific price levels. This kind of profile provides a deep insight into the market's structure and helps traders identify key areas of support and resistance, based on where the most trading activity took place. The concept behind the volume profile is that the amount of volume at each price level can indicate the potential importance of that price.
In this indicator:
- The volume profile mode creates a visual representation by sampling trading volumes across price levels.
- The representation displays the balance between bullish and bearish volumes at each level, which is further differentiated using a color gradient from `low_color` to `high_color`.
- The volume profile becomes more refined with sinc smoothing, helping to produce a smoother distribution of volumes.
Z-Score and Distribution Resampling
Z-Score, in the context of trading, represents the number of standard deviations a data point (e.g., closing price) is from the mean (average). It’s a measure of how unusual or typical a particular data point is in relation to all the data. In simpler terms, a high Z-Score indicates that the data point is far away from the mean, while a low Z-Score suggests it's close to the mean.
The unique feature of this indicator is that it samples the real distribution of z-scores within a window and then resamples this distribution to fit the desired sample size. This process is termed as "resampling in the context of distribution sampling" . Resampling provides a way to reconstruct and potentially simplify the original distribution of z-scores, making it easier for traders to interpret.
In this indicator:
- Each Z-Score corresponds to a price value on the chart.
- The resampled distribution is then used to display the heatmap, with each Z-Score related price level getting a heatmap box. The weight (or importance) of each box is represented as a combination of color and transparency.
How to Interpret the Z-Score Distribution Visualization:
When interpreting the Z-Score distribution through color and alpha in the visualization, it's vital to understand that you're seeing a representation of how unusual or typical certain data points are without directly viewing the numerical Z-Score values. Here's how you can interpret it:
Intensity of Color: This often corresponds to the distance a particular data point is from the mean.
Lighter shades (closer to `low_color`) typically indicate data points that are more extreme, suggesting overbought or oversold conditions. These could signify potential reversals or significant deviations from the norm.
Darker shades (closer to `high_color`) represent data points closer to the mean, suggesting that the price is relatively typical compared to the historical data within the given window.
Alpha (Transparency): The degree of transparency can indicate the significance or confidence of the observed deviation. More opaque boxes might suggest a stronger or more reliable deviation from the mean, implying that the observed behavior is less likely to be a random occurrence.
More transparent boxes could denote less certainty or a weaker deviation, meaning that the observed price behavior might not be as noteworthy.
- Combining Color and Alpha: By observing both the intensity of color and the level of transparency, you get a richer understanding. For example:
- A light, opaque box could suggest a strong, significant deviation from the mean, potentially signaling an overbought or oversold scenario.
- A dark, transparent box might indicate a weak, insignificant deviation, suggesting the price is behaving typically and is close to its average.
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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 Levels [ChartPrime]The Trend Levels indicator is designed to identify key trend levels (High, Mid, and Low) during market trends, based on real-time calculations of highest, lowest, and mid-level values over a customizable length. Additionally, the indicator calculates trend strength by measuring the ratio of candles closing above or below the midline, providing a clear view of the ongoing trend dynamics and strength.
⯁ KEY FEATURES AND HOW TO USE
⯌ Trend Shift Signals :
Trend shifts, based on highest and lowest values during input length. When high is == to highest it will change trend to up when low == lowest value it will be shift to down trend.
// Calculate highest and lowest over the specified length
h = ta.highest(length)
l = ta.lowest(length)
// Determine trend direction: if the current high is the highest value, set trend to true
if h == high
trend := true
// If the current low is the lowest value, set trend to false
if l == low
trend := false
Whenever the trend changes direction (from uptrend to downtrend or vice versa), the indicator provides visual cues in the form of arrows. This gives traders clear signals to identify potential trend reversals, enabling them to adjust their strategies accordingly.
⯌ Trend Level Calculation :
As soon as a trend is detected (uptrend or downtrend), the indicator starts calculating the highest, lowest, and mid-level values over the defined period. These levels are plotted on the chart as color-coded lines for easy visualization, allowing traders to quickly spot the key levels within a trend.
⯌ Midline Retests :
Throughout the trend, the mid-level line is often retested, acting as a potential zone for pullbacks or rejections. Traders can use these retests as opportunities for entering positions or confirming trend continuation. The chart shows how price frequently interacts with the midline, helping to identify important reaction levels.
⯌ Trend Strength Calculation :
The indicator measures the trend strength by calculating the delta between the number of candles closing above and below the midline. This percentage-based delta is displayed in real-time, providing a clear indication of whether the trend is gaining or losing momentum.
⯁ USER INPUTS
Length : Specifies the lookback period for calculating the highest and lowest values, which determines the key trend levels.
Candle Counting : Measures the number of candles closing above and below the midline to calculate the trend strength delta.
⯁ CONCLUSION
The Trend Levels indicator provides traders with a powerful tool for visualizing trend dynamics, key levels of support and resistance, and real-time trend strength. By identifying midline retests, tracking candle counts, and providing trend shift signals, this indicator can help traders make well-informed decisions during market trends.
DSL Trend Analysis [ChartPrime]The DSL Trend Analysis indicator utilizes Discontinued Signal Lines (DSL) deployed directly on price, combined with dynamic bands, to analyze the trend strength and momentum of price movements. By tracking the high and low price values and comparing them to the DSL bands, it provides a visual representation of trend momentum, highlighting both strong and weakening phases of market direction.
⯁ KEY FEATURES AND HOW TO USE
⯌ DSL-Based Trend Detection :
This indicator uses Discontinued Signal Lines (DSL) to evaluate price action. When the high stays above the upper DSL band, the line turns lime, indicating strong upward momentum. Similarly, when the low stays below the lower DSL band, the line turns orange, indicating strong downward momentum. Traders can use these visual signals to identify strong trends in either direction.
⯌ Bands for Trend Momentum :
The indicator plots dynamic bands around the DSL lines based on ATR (Average True Range). These bands provide a range within which price can fluctuate, helping to distinguish between strong and weakening trends. If the high remains within the upper band, the lime-colored line becomes transparent, showing weakening upward momentum. The same concept applies for the lower band, where the line turns orange with transparency, indicating weakening downward momentum.
If high and low stays between bands line has no color
to make sure indicator catches only strong momentum of price
⯌ Real-Time Band Price Labels :
The indicator places two labels on the chart, one at the upper DSL band and one at the lower DSL band, displaying the real-time price values of these bands. These labels help traders track the current price relative to the key bands, which are essential in determining potential breakout or reversal zones.
⯌ Visual Confirmation of Momentum Shifts :
By monitoring the relationship between the high and low values of the price relative to the DSL bands, this indicator provides a reliable way to confirm whether the trend is gaining or losing strength. This allows traders to act accordingly, whether it's to enter or exit positions based on trend strength or weakness.
⯁ USER INPUTS
Length : Defines the period used to calculate the DSL lines, influencing the sensitivity of the trend detection.
Offset : Adjusts the offset applied to the upper and lower DSL bands, affecting how the thresholds for strong or weak momentum are set.
Width (ATR Multiplier) : Determines the width of the DSL bands based on an ATR multiplier, providing a dynamic range around the price for momentum analysis.
⯁ CONCLUSION
The DSL Trend Analysis indicator is a powerful tool for assessing price momentum and trend strength. By combining Discontinued Signal Lines with dynamically calculated bands, traders can easily spot key moments when momentum shifts from strong to weak or vice versa. The color-coded lines and real-time price labels provide valuable insights for trading decisions in both trending and ranging markets.
Gaps Trend [ChartPrime]The Gaps Trend - ChartPrime indicator is designed to detect Fair Value Gaps (FVGs) in the market and apply a trailing stop mechanism based on those gaps. It identifies both bullish and bearish gaps and provides traders with a way to manage trades dynamically as gaps appear. The indicator visually highlights gaps and uses the detected momentum to assess trend direction, helping traders identify price imbalances caused by strong buy or sell pressure.
⯁ KEY FEATURES & HOW TO USE
⯌ Fair Value Gap (FVG) Detection :
The indicator automatically detects both bullish and bearish FVGs, identifying gaps between candle highs and lows. Bullish gaps are shown in green, and bearish gaps in purple. These gaps indicate price imbalances driven by strong momentum, such as when there is significant buying or selling pressure.
Use : Traders can use FVG detection to identify periods of high price momentum, offering insight into potential continuation or exhaustion of trends.
⯌ Trailing Stop Feature Based on FVGs :
A core feature of this indicator is the trailing stop mechanism, which adjusts dynamically based on the identified FVGs. When a bullish gap is detected, the trailing stop is placed below the price to capture upward momentum, while bearish gaps result in a trailing stop placed above the price. This feature helps traders stay in trends while protecting profits as the price moves.
Use : The trailing stop follows the momentum of the price, ensuring that traders can stay in profitable trades during strong trends and exit when the momentum shifts.
bullish set up
bearish set up
⯌ Trend Direction Indication :
The indicator colors the chart according to the current trend direction based on the position of the price relative to the trailing stop. Green indicates an uptrend (bullish gap), while purple shows a downtrend (bearish gap). This provides traders with a quick visual assessment of trend direction based on the presence of gaps.
Use : Traders can monitor the chart's color to stay aligned with the market’s trend, staying long during green phases and short during purple ones.
⯌ Gap Size Filtering :
Each detected gap is assigned a numerical ranking based on its size, with larger gaps having higher rankings. The gap size filter allows traders to only display gaps that meet a minimum size threshold, focusing on the most impactful gaps in terms of price movement.
Use : Traders can use the filter to focus on gaps of a certain size, filtering out smaller, less significant gaps. The numerical ranking helps identify the largest and most influential gaps for decision-making.
⯌ FVG Level Visualization :
The indicator can display dashed lines marking the levels of previously filled FVGs. These levels represent areas where price once experienced a gap and later filled it. Monitoring these levels can provide traders with key reference points for potential reactions in price.
Use : Traders can use these gap levels to track where price has filled gaps and potentially use these levels as zones for entry, exit, or assessing market behavior.
⯁ USER INPUTS
Filter Gaps : Adjust the size threshold to filter gaps by their size ranking.
Show Gap Levels : Toggle the display of dashed lines at filled FVG levels.
Enable Trailing Stop : Activate or deactivate the trailing stop feature based on FVGs.
Trailing Stop Length : Set the number of bars used to calculate the trailing stop.
Bullish/Bearish Colors : Customize the colors representing bullish and bearish gaps.
⯁ CONCLUSION
The Gaps Trend indicator combines Fair Value Gap detection with a dynamic trailing stop feature to help traders manage trades during periods of high price momentum. By detecting gaps caused by strong buy or sell pressure and applying adaptive stops, the indicator provides a powerful tool for riding trends and managing risk. The additional ability to filter gaps by size and visualize previously filled gaps enhances its utility for both trend-following and risk management strategies.
Double Ribbon [ChartPrime]The Double Ribbon - ChartPrime indicator is a powerful tool that combines two sets of Simple Moving Averages (SMAs) into a visually intuitive ribbon, which helps traders assess market trends and momentum. This indicator features two distinct ribbons: one with a fixed length but changing offset (displayed in gray) and another with varying lengths (displayed in colors). The relationship between these ribbons forms the basis of a trend score, which is visualized as an oscillator. This comprehensive approach provides traders with a clear view of market direction and strength.
◆ KEY FEATURES
Dual Ribbon Visualization : Displays two sets of 11 SMAs—one in a neutral gray color with a fixed length but varying offset, and another in vibrant colors with lengths that increase incrementally.
Trend Score Calculation : The trend score is derived from comparing each SMA in the colored ribbon with its corresponding SMA in the gray ribbon. If a colored SMA is above its gray counterpart, a positive score is added; if below, a negative score is assigned.
// Loop to calculate SMAs and update the score based on their relationships
for i = 0 to length
// Calculate SMA with increasing lengths
sma = ta.sma(src, len + 1 + i)
// Update score based on comparison of primary SMA with current SMA
if sma1 < sma
score += 1
else
score -= 1
// Store calculated SMAs in the arrays
sma_array.push(sma)
sma_array1.push(sma1 )
Dynamic Trend Analysis : The score oscillator provides a dynamic analysis of the trend, allowing traders to quickly gauge market conditions and potential reversals.
Customizable Ribbon Display : Users can toggle the display of the ribbon for a cleaner chart view, focusing solely on the trend score if desired.
◆ USAGE
Trend Confirmation : Use the position and color of the ribbon to confirm the current market trend. When the colored ribbon consistently stays above the gray ribbon, it indicates a strong uptrend, and vice versa for a downtrend.
Momentum Assessment : The score oscillator provides insight into the strength of the current trend. Higher scores suggest stronger trends, while lower scores may indicate weakening momentum or a potential reversal.
Strategic Entry/Exit Points : Consider using crossovers between the ribbons and changes in the score oscillator to identify potential entry or exit points in trades.
⯁ USER INPUTS
Length : Sets the base length for the primary SMAs in the ribbons.
Source : Determines the price data used for calculating the SMAs (e.g., close, open).
Ribbon Display Toggle : Allows users to show or hide the ribbon on the chart, focusing on either the ribbon, the trend score, or both.
⯁ CONCLUSION
The Double Ribbon indicator offers traders a comprehensive tool for analyzing market trends and momentum. By combining two ribbons with varying SMA lengths and offsets, it provides a clear visual representation of market conditions. The trend score oscillator enhances this analysis by quantifying trend strength, making it easier for traders to identify potential trading opportunities and manage risk effectively.
Radius Trend [ChartPrime]RADIUS TREND
⯁ OVERVIEW
The Radius Trend [ ChartPrime ] indicator is an innovative technical analysis tool designed to visualize market trends using a dynamic, radius-based approach. By incorporating adaptive bands that adjust based on price action and volatility, this indicator provides traders with a unique perspective on trend direction, strength, and potential reversal points.
The Radius Trend concept involves creating a dynamic trend line that adjusts its angle and position based on market movements, similar to a radius sweeping across a chart. This approach allows for a more fluid and adaptive trend analysis compared to traditional linear trend lines.
◆ KEY FEATURES
Dynamic Trend Band: Calculates and plots a main trend band that adapts to market conditions.
Radius-Based Adjustment: Uses a step-based radius approach to adjust the trend band angle.
// Apply step angle to trend lines
if bar_index % n == 0 and trend
multi1 := 0
multi2 += step
band += distance1 * multi2
if bar_index % n == 0 and not trend
multi1 += step
multi2 := 0
band -= distance1 * multi1
Volatility-Adjusted Calculations: Incorporates price range volatility for more accurate band placement.
Trend Direction Visualization: Provides clear color-coding to distinguish between uptrends and downtrends.
Flexible Parameters: Allows users to adjust the radius step and initial distance for customized analysis.
◆ USAGE
Trend Identification: Use the color and direction of the main band to determine the current market trend.
Trend Strength Analysis: Observe the angle and consistency of the band for insights into trend strength.
Reversal Detection: Watch for price crossing the main band or crossing a dashed band as a potential trend reversal signal.
Volatility Assessment: The distance between price and bands can provide insights into market volatility.
⯁ USER INPUTS
Radius Step: Controls the rate of angle adjustment for the trend band (default: 0.15, step: 0.001).
Start Points Distance: Sets the initial distance multiplier for band calculations (default: 2, step: 0.1).
The Radius Trend indicator offers traders a unique and dynamic approach to trend analysis. By combining radius-based trend adjustments with volatility-sensitive calculations, it provides a fluid representation of market trends. This indicator is particularly useful for traders looking to identify trend persistence, potential reversal points, and adaptive support/resistance levels across various market conditions and timeframes.
Polynomial Regression Keltner Channel [ChartPrime]Polynomial Regression Keltner Channel
⯁ OVERVIEW
The Polynomial Regression Keltner Channel [ ChartPrime ] indicator is an advanced technical analysis tool that combines polynomial regression with dynamic Keltner Channels. This indicator provides traders with a sophisticated method for trend analysis, volatility assessment, and identifying potential overbought and oversold conditions.
◆ KEY FEATURES
Polynomial Regression: Uses polynomial regression for trend analysis and channel basis calculation.
Dynamic Keltner Channels: Implements Keltner Channels with adaptive volatility-based bands.
Overbought/Oversold Detection: Provides visual cues for potential overbought and oversold market conditions.
Trend Identification: Offers clear trend direction signals and change indicators.
Multiple Band Levels: Displays four levels of upper and lower bands for detailed market structure analysis.
Customizable Visualization: Allows toggling of additional indicator lines and signals for enhanced chart analysis.
◆ FUNCTIONALITY DETAILS
⬥ Polynomial Regression Calculation:
Implements a custom polynomial regression function for trend analysis.
Serves as the basis for the Keltner Channel, providing a smoothed centerline.
//@function Calculates polynomial regression
//@param src (series float) Source price series
//@param length (int) Lookback period
//@returns (float) Polynomial regression value for the current bar
polynomial_regression(src, length) =>
sumX = 0.0
sumY = 0.0
sumXY = 0.0
sumX2 = 0.0
sumX3 = 0.0
sumX4 = 0.0
sumX2Y = 0.0
n = float(length)
for i = 0 to n - 1
x = float(i)
y = src
sumX += x
sumY += y
sumXY += x * y
sumX2 += x * x
sumX3 += x * x * x
sumX4 += x * x * x * x
sumX2Y += x * x * y
slope = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX)
intercept = (sumY - slope * sumX) / n
n - 1 * slope + intercept
⬥ Dynamic Keltner Channel Bands:
Calculates ATR-based volatility for dynamic band width adjustment.
Uses a base multiplier and adaptive volatility factor for flexible band calculation.
Generates four levels of upper and lower bands for detailed market structure analysis.
atr = ta.atr(length)
atr_sma = ta.sma(atr, 10)
// Calculate Keltner Channel Bands
dynamicMultiplier = (1 + (atr / atr_sma)) * baseATRMultiplier
volatility_basis = (1 + (atr / atr_sma)) * dynamicMultiplier * atr
⬥ Overbought/Oversold Indicator line and Trend Line:
Calculates an OB/OS value based on the price position relative to the innermost bands.
Provides visual representation through color gradients and optional signal markers.
Determines trend direction based on the polynomial regression line movement.
Generates signals for trend changes, overbought/oversold conditions, and band crossovers.
◆ USAGE
Trend Analysis: Use the color and direction of the basis line to identify overall trend direction.
Volatility Assessment: The width and expansion/contraction of the bands indicate market volatility.
Support/Resistance Levels: Multiple band levels can serve as potential support and resistance areas.
Overbought/Oversold Trading: Utilize OB/OS signals for potential reversal or pullback trades.
Breakout Detection: Monitor price crossovers of the outermost bands for potential breakout trades.
⯁ USER INPUTS
Length: Sets the lookback period for calculations (default: 100).
Source: Defines the price data used for calculations (default: HLC3).
Base ATR Multiplier: Adjusts the base width of the Keltner Channels (default: 0.1).
Indicator Lines: Toggle to show additional indicator lines and signals (default: false).
⯁ TECHNICAL NOTES
Implements a custom polynomial regression function for efficient trend calculation.
Uses dynamic ATR-based volatility adjustment for adaptive channel width.
Employs color gradients and opacity levels for intuitive visual representation of market conditions.
Utilizes Pine Script's plotchar function for efficient rendering of signals and heatmaps.
The Polynomial Regression Keltner Channel indicator offers traders a sophisticated tool for trend analysis, volatility assessment, and trade signal generation. By combining polynomial regression with dynamic Keltner Channels, it provides a comprehensive view of market structure and potential trading opportunities. The indicator's adaptability to different market conditions and its customizable nature make it suitable for various trading styles and timeframes.
Multi Deviation Scaled Moving Average [ChartPrime]Multi Deviation Scaled Moving Average ChartPrime
⯁ OVERVIEW
The Multi Deviation Scaled Moving Average is an analysis tool that combines multiple Deviation Scaled Moving Averages (DSMAs) to provide a comprehensive view of market trends. The DSMA, originally created by John Ehlers, is a sophisticated moving average that adapts to market volatility. This indicator offers a unique approach to trend analysis by utilizing a series of DSMAs with different periods and presenting the results through a color-coded line and a visual histogram.
◆ KEY FEATURES
Multiple DSMA Calculation: Computes eight DSMAs with incrementally increasing periods for multi-faceted trend analysis.
Trend Strength Visualization: Provides a color-coded moving average line indicating trend strength and direction.
Trend Percentage Histogram: Displays a visual representation of bullish vs bearish trend percentages.
Signal Generation: Identifies potential entry and exit points based on trend strength crossovers.
Customizable Parameters: Allows users to adjust the base period and sensitivity of the indicator.
◆ USAGE
Trend Direction and Strength: The color and intensity of the main indicator line provide quick insights into the current trend.
Trend Percentage Histogram: The histogram value can give you an idea of the market trend ahead
Entry and Exit Signals: Diamond-shaped markers indicate potential trade entry and exit points based on trend strength shifts.
Trend Bias Assessment: The trend percentage histogram offers a visual representation of the overall market bias.
Multi-Timeframe Analysis: By applying the indicator to different timeframes, traders can gain insights into trends across various time horizons.
⯁ USER INPUTS
Period: Sets the initial calculation period for the DSMAs (default: 30).
Sensitivity: Adjusts the step size between DSMA periods. Lower values increase sensitivity (default: 60, range: 0-100).
Source: Uses HLC3 (High, Low, Close average) as the default price source.
The Multi Deviation Scaled Moving Average indicator offers traders a sophisticated tool for trend analysis and signal generation. By combining multiple DSMAs and providing clear visual cues, it enables traders to make more informed decisions about market direction and potential entry or exit points. The indicator's customizable parameters allow for fine-tuning to suit various trading styles and market conditions.
Chebyshev Filter Divergences [ChartPrime]The Chebyshev Filter Divergences Oscillator
The Chebyshev Filter indicator is a powerful tool designed to identify potential divergences between price and a filtered version of price based on the Chebyshev filter algorithm. It helps to spot mean reversion points by highlighting areas where price and the filtered price exhibit conflicting signals.
Chebyshev Filter Background:
The Chebyshev filter, named after the Russian mathematician Pafnuty Chebyshev , was invented in the mid-19th century. It's a type of filter used in signal processing and digital signal processing for smoothing or removing unwanted frequency components from a signal.
It provides a sharp cutoff between the passband and stopband of a filter while minimizing ripple in the passband or stopband.
Chebyshev filters are widely used in various applications, including audio and image processing, telecommunications, and financial analysis, due to their efficiency and effectiveness in filtering out noise and extracting relevant information from signals.
◆ Indicator Calculation:
The indicator first applies a Chebyshev filter to the price data, producing a filtered price series. It then normalizes this filtered price series to a range, where it can be used as oscillator with divergences.
◆ Visualization:
The filtered price series is plotted on the chart, highlighting areas where it deviates from its smoothed average.
Bullish and bearish divergences are marked on the chart with specific lines and colors, indicating potential shifts in market sentiment.
Signs of change in direction are also marked on the chart, providing additional insights into possible mean reversals of price.
◆ User Inputs:
Ripple (dB): Specifies the desired ripple factor in decibels for the Chebyshev filter.
Normalization Length: Sets the length of the normalization period used in the Chebyshev filter.
Pivots to Right and Left: Determines the number of pivot points to the right and left of the current point to consider when detecting divergences.
Max and Min of Lookback Range: Specifies the maximum and minimum lookback range for identifying divergences.
Show Divergences: Enables or disables the display of bullish and bearish divergences.
Visual Settings: Allows customization of colors for visual clarity.
In conclusion, the Chebyshev Filter Divergences indicator, with its ability to identify potential mean reversion points through divergences between price and a filtered version of price, offers traders a valuable tool for decision-making in the financial markets. By highlighting areas of divergence, traders can potentially capitalize on market inefficiencies and make more informed trading decisions.
Volume Positive & Negative Levels [ChartPrime]Volume Positive & Negative Levels
Overview:
The Volume Positive & Negative Levels indicator by ChartPrime is designed to provide traders with a clear visualization of volume activity across different price levels. By plotting volume levels as histograms, this tool helps identify significant areas of buying (positive volume) and selling (negative volume) pressure, enhancing the ability to spot potential support and resistance zones.
Key Features:
⯁ Lookback Period:
- The `lookbackPeriod` parameter, set to 500 bars, determines the range over which the volume analysis is conducted, ensuring a comprehensive view of the market’s volume activity. The maximum lookback period is 500 bars or the bars currently visible on the chart, whichever is smaller.
⯁ Dynamic Volume Calculation:
- Volume is calculated dynamically based on the price action, with positive volume indicating buying pressure (close > open) and negative volume indicating selling pressure (close < open).
⯁ Color Coding for Clarity:
- Positive Volume: Represented with a distinct color (`#ad9a2c`), making it easy to identify areas of buying interest.
- Negative Volume: Highlighted with another color (`#ad2cad`), simplifying the detection of selling pressure.
Volume Threshold and Bins:
- The indicator allows users to set a volume threshold (`volume_level`) to highlight significant volume levels, with the default set at 70.
- The number of bins (`numBins`) defines the granularity of the volume profile, with a higher number providing more detail.
⯁ Volume Profile Visualization:
- The volume profile is plotted as a histogram, with the height of each bar proportional to the volume at that price level. This visualization helps in quickly assessing the strength of volume at various price points.
⯁ Interactive Labels and Threshold Indicators:
- Labels: The indicator uses labels to mark significant volume levels, providing quick reference points for traders.
- Threshold Lines: Lines are drawn at specified volume thresholds, with colors and widths dynamically adjusted based on the volume levels.
⯁ User Inputs:
- Volume Threshold (`volume_level`): Sets the minimum volume required to highlight significant levels.
- Number of Bins (`numBins`): Determines the resolution of the volume profile.
- Line Width (`line_withd`): Specifies the width of the lines used in the visualization.
The Volume Positive & Negative Levels indicator is a powerful tool for traders looking to gain deeper insights into market dynamics. By providing a clear visual representation of volume activity across different price levels, it helps traders identify key support and resistance zones, spot trends, and make more informed trading decisions. Whether you are a day trader or a swing trader, this indicator enhances your ability to analyze volume data effectively, improving your overall trading strategy.
Bayesian Trend Indicator [ChartPrime]Bayesian Trend Indicator
Overview:
In probability theory and statistics, Bayes' theorem (alternatively Bayes' law or Bayes' rule), named after Thomas Bayes, describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
The "Bayesian Trend Indicator" is a sophisticated technical analysis tool designed to assess the direction of price trends in financial markets. It combines the principles of Bayesian probability theory with moving average analysis to provide traders with a comprehensive understanding of market sentiment and potential trend reversals.
At its core, the indicator utilizes multiple moving averages, including the Exponential Moving Average (EMA), Simple Moving Average (SMA), Double Exponential Moving Average (DEMA), and Volume Weighted Moving Average (VWMA) . These moving averages are calculated based on user-defined parameters such as length and gap length, allowing traders to customize the indicator to suit their trading strategies and preferences.
The indicator begins by calculating the trend for both fast and slow moving averages using a Smoothed Gradient Signal Function. This function assigns a numerical value to each data point based on its relationship with historical data, indicating the strength and direction of the trend.
// Smoothed Gradient Signal Function
sig(float src, gap)=>
ta.ema(source >= src ? 1 :
source >= src ? 0.9 :
source >= src ? 0.8 :
source >= src ? 0.7 :
source >= src ? 0.6 :
source >= src ? 0.5 :
source >= src ? 0.4 :
source >= src ? 0.3 :
source >= src ? 0.2 :
source >= src ? 0.1 :
0, 4)
Next, the indicator calculates prior probabilities using the trend information from the slow moving averages and likelihood probabilities using the trend information from the fast moving averages . These probabilities represent the likelihood of an uptrend or downtrend based on historical data.
// Define prior probabilities using moving averages
prior_up = (ema_trend + sma_trend + dema_trend + vwma_trend) / 4
prior_down = 1 - prior_up
// Define likelihoods using faster moving averages
likelihood_up = (ema_trend_fast + sma_trend_fast + dema_trend_fast + vwma_trend_fast) / 4
likelihood_down = 1 - likelihood_up
Using Bayes' theorem , the indicator then combines the prior and likelihood probabilities to calculate posterior probabilities, which reflect the updated probability of an uptrend or downtrend given the current market conditions. These posterior probabilities serve as a key signal for traders, informing them about the prevailing market sentiment and potential trend reversals.
// Calculate posterior probabilities using Bayes' theorem
posterior_up = prior_up * likelihood_up
/
(prior_up * likelihood_up + prior_down * likelihood_down)
Key Features:
◆ The trend direction:
To visually represent the trend direction , the indicator colors the bars on the chart based on the posterior probabilities. Bars are colored green to indicate an uptrend when the posterior probability is greater than 0.5 (>50%), while bars are colored red to indicate a downtrend when the posterior probability is less than 0.5 (<50%).
◆ Dashboard on the chart
Additionally, the indicator displays a dashboard on the chart , providing traders with detailed information about the probability of an uptrend , as well as the trends for each type of moving average. This dashboard serves as a valuable reference for traders to monitor trend strength and make informed trading decisions.
◆ Probability labels and signals:
Furthermore, the indicator includes probability labels and signals , which are displayed near the corresponding bars on the chart. These labels indicate the posterior probability of a trend, while small diamonds above or below bars indicate crossover or crossunder events when the posterior probability crosses the 0.5 threshold (50%).
The posterior probability of a trend
Crossover or Crossunder events
◆ User Inputs
Source:
Description: Defines the price source for the indicator's calculations. Users can select between different price values like close, open, high, low, etc.
MA's Length:
Description: Sets the length for the moving averages used in the trend calculations. A larger length will smooth out the moving averages, making the indicator less sensitive to short-term fluctuations.
Gap Length Between Fast and Slow MA's:
Description: Determines the difference in lengths between the slow and fast moving averages. A higher gap length will increase the difference, potentially identifying stronger trend signals.
Gap Signals:
Description: Defines the gap used for the smoothed gradient signal function. This parameter affects the sensitivity of the trend signals by setting the number of bars used in the signal calculations.
In summary, the "Bayesian Trend Indicator" is a powerful tool that leverages Bayesian probability theory and moving average analysis to help traders identify trend direction, assess market sentiment, and make informed trading decisions in various financial markets.
Volume Storm Trend [ChartPrime]The Volume Storm Trend (VST) indicator is a robust tool for traders looking to analyze volume momentum and trend strength in the market. By incorporating key volume-based calculations and dynamic visualizations, VST provides clear insights into market conditions.
Components:
Calculating the median of the source data.
Volume Power Calculation: The indicator calculates the "heat power" and "cold power" by applying an Exponential Moving Average (EMA) to the median of volume data arrays.
// ---------------------------------------------------------------------------------------------------------------------}
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
// ---------------------------------------------------------------------------------------------------------------------{
max_val = 1000
src = close
source = ta.median(src, len)
heat.push(src > source ? (volume > max_val ? max_val : volume) : 0)
heat.remove(0)
cold.push(src < source ? (volume > max_val ? max_val : volume) : 0)
cold.remove(0)
heat_power = ta.ema(heat.median(), 10)
cold_power = ta.ema(cold.median(), 10)
Visualization:
Gradient Colors: The indicator uses gradient colors to visualize bullish volume and bearish volume powers, providing a clear contrast between rising and falling trends.
Bars Fill Color: The color fill between high and low prices changes based on whether the heat power is greater than the cold power.
Bottom Line: A zero line with changing colors based on the dominance of heat or cold power.
Weather Symbols: Visual indicators ("☀" for hot weather and "❄" for cold weather) appear on the chart when the heat and cold powers crossover, helping traders quickly identify trend changes.
Inputs:
Source: The input data source, typically the closing price.
Median Length: The period length for calculating the median of the source. Default is 40.
Volume Length: The period length for calculating the average volume. Default is 3.
Show Weather: A toggle to display weather symbols on the chart. Default is false.
Temperature Type: Allows users to choose between Celsius (°C) and Fahrenheit (°F) for temperature display.
Show Weather Function:
The `Show Weather?` function enhances the VST indicator by displaying weather symbols ("☀" for hot and "❄" for cold) when there are significant crossovers between heat power and cold power. This feature adds a visual cue for potential market tops and bottoms. When the market heats to a high temperature, it often indicates a potential top, signaling traders to consider exiting long positions or preparing for a reversal.
Additional Features:
Dynamic Table Display: A table displays the current "temperature" on the chart, indicating market heat based on the calculated heat and cold powers.
The Volume Storm Trend indicator is a powerful tool for traders
looking to enhance their market analysis with volume and momentum insights, providing a clear and visually appealing representation of key market dynamics.
Liquidations [ChartPrime]Liquidations Indicator:
The Liquidations indicator is a powerful tool designed to help traders identify significant liquidation levels in financial markets. By analyzing volume data over a specified lookback period, the indicator highlights potential areas where market participants with high leverage positions may face liquidation, providing valuable insights into market dynamics.
Usage:
Traders can use the Liquidations indicator to:
◈ Identify liquidity grab opportunities: Liquidation levels often attract price action as market participants with leveraged positions face the risk of forced liquidation. Traders can anticipate price movements as the market aims to trigger these stops, potentially leading to rapid price movements or reversals.
◈ Confirm trend strength: A cluster of liquidation levels in the same direction as the prevailing trend may confirm the strength of the trend, while divergences between liquidation levels and price movements may signal potential trend reversals.
Settings:
◈ Previous Value Bars Back: Specifies the number of previous bars used in calculating the liquidation levels.
◈ Show Leverage: Allows users to selectively display liquidation levels for different leverage multiples, including 5x, 10x, 25x, 50x, and 100x.
◈ Liquidation Levels Width: Sets the width of the lines representing liquidation levels on the chart.
◈ Short Liquidations Color: Specifies the color of the lines representing short liquidation levels.
◈ Long Liquidations Color: Specifies the color of the lines representing long liquidation levels.
◈ Bar Color: Sets the color of the background bar when the indicator is active.
Visual Representation:
◈ Liquidation levels are plotted as horizontal lines on the chart, with different colors representing short and long liquidation levels.
◈ Each liquidation level is labeled with the corresponding leverage multiple (e.g., 5x, 10x, etc.).
A dashboard displays the active liquidation levels for each leverage multiple, allowing traders to quickly assess the current market conditions.
◈ Time Window allows users to cut off unnecessary part of the chart and concentrate on a current active part of the chart to make better trading decisions:
Interpretation:
Market participants tend to place stop-loss orders near liquidation levels , creating clusters of pending orders. As price approaches these levels, it may trigger a cascade of stop-loss orders, providing liquidity for market orders and potentially leading to rapid price movements in the opposite direction.
Traders can anticipate price reversals or accelerations as price interacts with liquidation levels, using them as reference points for identifying potential entry or exit opportunities.
Note:
While the Liquidations indicator provides valuable insights into market dynamics, traders should use it in conjunction with other technical analysis tools and risk management strategies to make informed trading decisions.
Relative Average Extrapolation [ChartPrime]Relative Average Extrapolation (ChartPrime) is a new take on session averages, like the famous vwap . This indicator leverages patterns in the market by leveraging average-at-time to get a footprint of the average market conditions for the current time. This allows for a great estimate of market conditions throughout the day allowing for predictive forecasting. If we know what the market conditions are at a given time of day we can use this information to make assumptions about future market conditions. This is what allows us to estimate an entire session with fair accuracy. This indicator works on any intra-day time frame and will not work on time frames less than a minute, or time frames that are a day or greater in length. A unique aspect of this indicator is that it allows for analysis of pre and post market sessions independently from regular hours. This results in a cleaner and more usable vwap for each individual session. One drawback of this is that the indicator utilizes an average for the length of a session. Because of this, some after hour sessions will only have a partial estimation. The average and deviation bands will work past the point where it has been extrapolated to in this instance however. On low time frames due to the limited number of data points, the indicator can appear noisy.
Generally crypto doesn't have a consistent footprint making this indicator less suitable in crypto markets. Because of this we have implemented other weighting schemes to allow for more flexibility in the number of use cases for this indicator. Besides volume weighting we have also included time, volatility, and linear (none) weighting. Using any one of these weighting schemes will transform the vwap into a wma, volatility adjusted ma, or a simple moving average. All of the style are still session period and will become longer as the session progresses.
Relative Average Extrapolation (ChartPrime) works by storing data for each time step throughout the day by utilizing a custom indexing system. It takes the a key , ie hour/minute, and transforms it into an array index to stor the current data point in its unique array. From there we can take the current time of day and advance it by one step to retrieve the data point for the next bar index. This allows us to utilize the footprint the extrapolate into the future. We use the relative rate of change for the average, the relative deviation, and relative price position to extrapolate from the current point to the end of the session. This process is fast and effective and possibly easier to use than the built in map feature.
If you have used vwap before you should be familiar with the general settings for this indicator. We have made a point to make it as intuitive for anyone who is already used to using the standard vwap. You can pick the source for the average and adjust/enable the deviation bands multipliers in the settings group. The average period is what determines the number of days to use for the average-at-time. When it is set to 0 it will use all available data. Under "Extrapolation" you will find the settings for the estimation. "Direction Sensitivity" adjusts how sensitive the indicator is to the direction of the vwap. A higher number will allow it to change directions faster, where a lower number will make it more stable throughout the session. Under the "Style" section you will find all of the color and style adjustments to customize the appearance of this indicator.
Relative Average Extrapolation (ChartPrime) is an advanced and customizable session average indicator with the ability to estimate the direction and volatility of intra-day sessions. We hope you will find this script fascinating and useful in your trading and decision making. With its unique take on session weighting and forecasting, we believe it will be a secret weapon for traders for years to come.
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Fibonacci Archer Box [ChartPrime]Fibonacci Archer Box (ChartPrime) is a full featured Fibonacci box indicator that automatically plots based on pivot points. This indicator plots retracement levels, time lines, fan lines, and angles. Each one of these features are fully customizable with the ability to disable individual features. A unique aspect to this implementation is the ability to set targets based on retracement levels and time zones. This is set to 0.618 by default but you can pick any Fibonacci zone you like. Also included are markings that show you when Fibonacci levels are met or exceeded. These moments are plotted on the chart as colored dots that can be enabled or disabled. Along with these markings are crosses that can be shown when targets are hit. Both of these markings are colored with the related Fibonacci level colors.
When there is a zig-zag, this indicator will test to see if the zig-zag meets the criteria set up by the user before plotting a new Fibonacci box. You can pick from either higher highs or lower highs for bearish patterns, and higher lows or lower lows for bullish patterns. Both patterns can be set to use both when finding new boxes if you want to make it more sensitive. You also have the option to filter based on minimum and maximum size. If the box isn't within the selected size range, it will simply be ignored. The pivot levels can be configured to use either candle wicks or candle bodies. By default this is configured to use candle wick with a lookforward of 5 and lookback of 10.
We have included alerts for Fibonacci level crosses, Fibonacci time crosses, and target hits. All alerts are found in the add alert section built into tradingview to make alert creation as easy as possible. Each alert is labeled with their correct names to make navigation simple.
W.D. Gann, a renowned figure in the world of trading and market analysis, is often questioned for his use of Fibonacci levels in his strategies. However, evidence points to the fact that Gann did not directly employ Fibonacci price levels in his work. Instead, Gann had his unique approach, dividing price ranges into thirds, eighths, and other fractions, which, although somewhat aligning with Fibonacci levels, are not exact matches. It is clear that Gann was familiar with Fibonacci and the golden ratio, as references to them appear in his recommended reading list and some of his writings. Despite this awareness, Gann chose not to incorporate Fibonacci levels explicitly in his methodologies, preferring instead to use his divisions of price and time. Notably, Gann's emphasis on the 50% level—a marker not associated with Fibonacci numbers—further illustrates his departure from Fibonacci usage. This level, despite its popularity among some Fibonacci enthusiasts, does not stem from Fibonacci's sequence. This is why we opted to call this indicator Fibonacci Archer Box instead of a Gann Box as we didn't feel like it was appropriate.
In summary, the Fibonacci Archer Box (ChartPrime) is a tool that incorporates Fibonacci retracements and projections with an automated pivot point-based plotting system. It allows for customization across various features including retracement levels, timelines, fan lines, and angles, and integrates visual cues for level crosses and target hits. While it acknowledges the methodologies of W.D. Gann, it distinctively utilizes Fibonacci techniques, providing a straightforward tool for market analysis. We hope you enjoy using this indicator as much as we enjoyed making it!
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Monte Carlo Future Moves [ChartPrime]ORIGINS AND HISTORICAL BACKGROUND:
Prior to the the advent of the Monte Carlo method, examining well-understood deterministic problems via simulation generally utilized statistical sampling to gauge uncertainty estimations. The Monte Carlo (MC) approach inverts this paradigm by modeling with probabilistic metaheuristics to address deterministic problems. Addressing Buffon's needle problem, an early form of the Monte Carlo method estimated π (3.14159) by dropping needles on a floor. Later, the modern MC inception primarily began when Stanislaw Ulam was playing solitaire games while experiencing illness and recovery.
Ulam further developed, applied, and ascribed "Monte Carlo" as a classified code name to maintain a level of secrecy for the modern method applications during collaborative investigations on neutron diffusion and collision intricacies with John von Neumann. Despite having relevant data, physicist's conventional deterministic mathematical methods were unable to solve mysterious "neutronion problems". Monte Carlo filled in the gaps necessary to resolve this perplexing neutron problem with innovative statistics, and the resilient MC continues onward to have diverse application in many fields of science. MC also extends into the realm of relevance within finance.
APPLICATION IN FINANCE:
Building on its historical roots, the Monte Carlo method's transition into finance opened new avenues for risk assessment and predictive analysis. In financial markets, characterized by uncertainty and complex variables, this method offers a powerful tool for simulating a wide range of scenarios and assessing probabilities of different outcomes. By employing probabilistic models to predict price movements, the Monte Carlo method helps in creating more resilient and informed trading strategies. This approach is particularly valuable in options pricing, portfolio management, and risk assessment, where understanding the range of potential outcomes is crucial for making sound investment decisions. Our indicator utilizes this methodology, blending traditional financial analysis with advanced statistical techniques.
THE INDICATOR:
The Monte Carlo Future Moves (ChartPrime) indicator is designed to predict future price movements. It simulates various possible price paths, showing the likelihood of different outcomes. We have designed it to be simple to use and understand by displaying lines indicating the most likely bullish and bearish outcomes. The arrows point to these areas making it intuitive to understand. Also included is extreme price levels shown in blue and yellow. This is the most likely extreme range that the price will move to. The outcome distribution is there to show you the range of outcomes along with a visual representation of the possible future outcomes. To make things more user friendly we have also included a representation of this distribution as a background heatmap. The brighter the price level, the more likely the price will end at that level. Finally, we have also included a market bias indication on the side that shows you the general bullish/bearish probabilities.
HOW TO USE:
To use this indicator you want to first assess the market bias. From there you want to target the most likely polar outcome. You can use the range of outcomes to assess your risk and set a stop within a reasonable range of the desired target. By default the indicator projects 10 steps into the future, however this can be easily adjusted in the settings. Generally this indicator excels at mid-term estimations and may yield inconclusive results if the prediction period is too short or too long. You can change the granularity of the outcomes to give you a more or less detailed view of the future. That being said, a lower resolution can make the predictions less useful while a higher resolution can give you a less useful picture. If you decide to use a higher resolution we have included an option to smooth the final result. This is intended to reduce the uncertainty and noise in the predicted outcomes. It is advised to use the minimum level of smoothing possible as a high level of smoothing will greatly reduce the accuracy.
INPUT SECTION:
Derivative Source changes how the indicator sees the price movements. When you set this to Candle it will use the difference between the open and close of each candle. If set to Move, it will use the difference between closing prices. If you are in a market with gaps, you might want to use Candle as this will prevent the indicator from seeing gaps.
Number of Simulations is a crucial setting as it is the core of this indicator. This determines the number of simulations the indicator will use to get its final result. By default it is set to 1000 as we feel like that is around the minimum number of simulations required to get a reasonable output while maintaining stability. In tests the maximum number of simulations we have been able to consistently achieve is 2000.
Lookback is the number of historical candles to account for. A lookback that is too short will not have enough data to accurately assess the likelihood of a price movement, while a period that is too large can make the data less relevant. By default this is set to 1000 as we feel like this is a reasonable tradeoff between volume of data and relevance.
Steps Into Future is the prediction period. By default we have picked a period of 10 steps as this has a good balance between accuracy and usability. The more steps into the future you go, the more uncertain the future outcome will be.
Outcome Granularity controls the precision of the simulated outcomes. By default this is set to 40 as its a good balance between resolution and accuracy.
Outcome Smoothing allows you to smooth the outcome distribution. By default this is set to 0 as it is generally not needed for lower resolutions. Smoothing levels beyond 2 are not recommended as it will negatively impact the output.
Returns Granularity controls the level of definition in the collected price movements. This directly impacts indicator performance and is set to 50 by default because its a good balance between fidelity and usability. When this number is too small, the simulations will be less accurate while numbers too large will negatively impact the probabilities of the movements.
Drift is the trend component in the simulation. This adds the directionality of the simulations by biasing the movements in the current direction of the market. We have included both the standard formula for drift and linear regression. Both methods are well suited for simulating future price movements and have their own advantages. The drift period is set to 100 by default as its a good balance between current and historical directionality. You may want to increase or decrease this number depending on the current market conditions but it is advised to use a period that isn't too small. If your period is too small it can skew the outcomes too much resulting in poor performance. When this is set to 0 it will use the same period as your lookback.
Volatility Adjust , adjusts the simulation to include current volatility. This makes sure that the price movements in the simulation reflects the current market conditions better by making sure that each price move is at least a minimum size.
Returns Style allows you to pick between using percent moves and log returns. We have opted to make percent move the default as it is more intuitive for beginners however both settings yield similar results. Log returns can be less cpu intensive so it might be desirable for longer term predictions.
Precision adjusts the rounding of used when collecting the frequency of price movement sizes. By default this is set to 4 as its is fairly accurate without impacting performance too much. A larger number will make the indicator more precise but at the cost of cpu time. Precision levels that are too small can greatly reduce the accuracy of the simulation and even break the indicator all together.
Update Every Bar allows you to recalculate the prediction every bar and is there for you if you want to strictly use the market bias. It is not recommended to enable this feature but it is there for flexibility.
Side of Chart allows you to pick what side of the price action you want the visuals to be on. When its set to the right everything will be to the right of the starting point and when its set to Left it will position everything to the left of the starting point.
Move Visualization is there to give you an arrow to the most likely bullish and bearish moves. It is meant as a visual aid and visualization tool. The color of these arrows use the same colors as the distribution.
Most Likely Move is a horizontal line that indicates the most likely move. It is positioned in the same location as the Move Visualization.
Standard Deviation is horizontal lines at the extremities of the simulated price action. These represent the most likely range of the future outcomes. You can adjust the multiplier of the standard deviation but by default it is set to 2.
Most Likely Direction is a vertical bar that shows you the sum of the up and down probabilities. It is there to show you the bias of the outcomes and guide you in decision making.
Max Probability Zone is a horizontal line that highlights the location of the highest probability move. You can think of it almost like the POC in a volume distribution but in this case it is the "most likely" single outcome.
Outcome Distribution allows you to toggle the distribution on or off. This is the distribution of all of the simulated outcomes. You can toggle the scale width of the distribution to fit your visual style.
Distribution Text toggles the probability text inside of the distribution bars. When you have a large number for the outcome granularity this text may not be visible and you may want to disable this feature.
Background is a heatmap of the outcome distribution. This allows you to visualize the underlying distribution without the need for the distribution histogram. The brighter the color, the more likely the outcome is for that level. It can be useful for visualizing the range of possible outcomes.
Starting Line is simply a horizontal line indicating the starting point of the simulation. It just the opening price for the starting position.
Extend Lines allows you to extend the lines and background past the prediction period.
CONCLUSION:
With its intuitive visuals and flexible settings, the Monte Carlo Future Moves (ChartPrime) indicator is practice and easy to use. It brings clarity to price movement predictions, helping you to build confidence in your strategies. This indicator not only reflects the evolution of technical analysis but also touches on data-driven insights.
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Dynamic Support/Resistance Zones [ChartPrime]Dynamic Support/Resistance Zones is a new way to visualize key support and resistance levels by analyzing pivot points. It aggregates these points into bins and uses different scoring methods to determine the strength of the zone. The Linear method treats every pivot the same, Time gives more importance to recent pivots, and Volume scores pivots based on trading activity.
It visually represents the strength of price zones using either a visual distribution or an overlay of colors. Areas with many aggregated pivots are marked using the High Color, indicating strong support or resistance. Fewer pivots are shown in Low Color, suggesting weaker levels. Users can also see the score using the distribution mode to more accurately determine the strength of these areas.
The indicator also includes a special moving average line, calculated from pivot prices and their weights. This gives a central pivot level, allowing you to see the average pivot position. We have also provided some smoothing for this line to make it easer to use.
We have included various options to tailor your analysis. These include selecting the scoring method for pivots and adjusting the number of pivots to consider, along with many visual aids. Traders can also set the level of filtering for the distribution of pivots. By default the filter isn't enabled but when it is enabled it allows for a less noisy experience at the expense of precision.
We have included four pivot periods that you can modify and toggle. The idea is that longer period pivots will enhance the strength of the shorter period ones providing a natural way to weight pivot levels. You can also specify whether you want to use pivot high, pivot low, or both in your analysis.
Here are some details on the key inputs:
Weighting Style: Choose how to score pivot points. Options include: Linear: Treats each pivot equally. Time: Gives more importance to recent pivots. Volume: Scores pivots based on trading volume.
Number of Pivots: Set the number of pivots to consider in the calculation. Both pivot highs and lows are treated separately.
Filtering: Adjust the level of filtering applied to the distribution of pivots. A higher value smooths the distribution, providing a cleaner visual representation at the cost of some precision. This setting is crucial for managing the trade-off between clarity and detail in the visualization of support and resistance zones.
Distribution Scale: Determines the scale of the distribution on the screen. It influences both the visual aspect and the precision of the calculations, allowing for a balance between visibility and analytical accuracy.
Manual Precision: Manually set the number of divisions within the range. This setting offers control over the granularity.
Auto Precision: When enabled, it automatically adjusts the precision based on the average range of a candle, ensuring a minimum level of detail in the visualization.
Show Distribution: Toggle the visibility of the distribution of pivot points. When activated, it provides a detailed visual representation of where pivots are concentrated.
Show Score in Distribution: Opt to display the actual score within the distribution. This feature adds a quantitative element to the visual representation, offering a clearer understanding of the pivot point concentration.
Distribution Overlay: Activate a heat map overlay to visualize the distribution of pivots. You can also adjusting the transparency of this overlay, providing a balanced view that does not obstruct the underlying price chart.
Show Support/Resistance: Enable lines that indicate identified support and resistance levels based on the aggregated pivots. This feature provides a clear, actionable insight directly on the chart.
S/R Zone Visibility: Choose to display the support/resistance zones and set their transparency. It offers an extended visual cue about the potential breadth of support or resistance areas.
Pivot Level Average: Introduce a moving average line that's calculated based on the weighted pivot levels. You can also adjust the smoothness of this line.
Dynamic Support/Resistance Zones is an intuitive and versatile trading indicator that offers a novel approach to identifying support and resistance levels by analyzing pivot points. It blends a variety of scoring methods, customizable visual representations, and a unique moving average line. With its customizable settings for pivot analysis, visual clarity, and precision, it's an nifty tool for traders looking to enhance their decision making with detailed and actionable insights.
Sentiment Range MA [ChartPrime]The "Sentiment Range MA" provides traders with a dynamic perspective on market activity, emphasizing both stability in chop zones and quick adaptability outside of them.
Key Features:
Chop Zone Stability: In choppy markets, this indicator remains consistent, filtering out the noise to provide a clear view.
Quick Adaptability: Should the price break out of these zones, the indicator recalibrates promptly.
Dynamic Support and Resistance: Adapts based on the latest price action, serving as an evolving reference point.
Emphasis on Recent Levels: The tool factors in the latest notable market levels to stay relevant and timely.
Configurations:
Data Source: Choose your desired metric, though many default to the closing price.
Output Smoothing: Adjust the SR MA's response to market movements.
Trigger Smoothing: Refine boundary definitions based on your market insights.
ATR Period: Set the period for the ATR, influencing the surrounding boundary's width.
Range Multiplier: Control the ATR's effect on the range.
Range Switch: Flip between high-low and open-close values for range determination.
Visuals
Sentiment Range MA Line:
- This is the flowing line that transitions between green and red.
- When it's green, it indicates bullish momentum in the market. This suggests a prevailing upward trend and can be an entry cue for traders who trade with the trend.
- When it turns red, bearish sentiments dominate. It indicates the potential beginning of a downtrend or a continued downtrend. Traders might interpret this as a signal to be cautious, to short the market, or to exit long positions.
The Chop Zone:
- This is the space between the price candles and the Sentiment Range MA line. It represents a region where the price is considered to be moving sideways or without a clear direction. Price movements within the chop zone might not be substantial enough to warrant a trading decision. Only when the price breaks out of this zone do we see the Sentiment Range MA line change color, signaling a potential trading opportunity.
By interpreting these visuals, traders can make more informed decisions based on the prevailing market sentiment and trend. The chart becomes a tool, providing both an overview of the market condition and potential entry or exit points based on the Sentiment Range MA indicator's readings.
Detailed Settings Overview
Understanding the settings of the Sentiment Range MA Indicator can greatly enhance its utility in your trading strategy. Let's dive deeper into each:
Output Smoothing:
Purpose: It refines the SR MA to provide a clearer trend perspective.
Functionality:
- At `0`, it ensures the indicator responds immediately to price deviations from the chop zone.
- At higher values, it transforms the indicator into a volatility-adjusted moving average.
Filtering Modes:
- Single Filtering: Prioritizes speed.
- Double Filtering: Emphasizes stability.
Trigger Smoothing:
Purpose: Used for the range break detection.
Functionality: It dampens the indicator's sensitivity to sudden market volatility, preventing unnecessary triggers.
ATR Length:
Purpose: Governs the retrospective period for the chop zone.
Functionality:
- Higher values offer a more consistent and broad range size, capturing more historical data.
- Lower values allow for a more adaptive and responsive range.
Range Multiplier:
Purpose: Modifies the breadth of the range around the SR MA.
Functionality: Increasing the multiplier will extend the range, giving more leeway before triggering, while decreasing it will narrow the range, making the indicator more responsive to price changes.
Range Style:
Purpose: Decides which candlestick data is factored into the true range calculations.
Options:
- Body: Uses the open and close values.
- Wick: Accounts for the high and low values.
Functionality: Switching between styles lets you prioritize either the overall volatility (Wick) or just the concluded price action for a period (Body).
By fine-tuning these settings, traders can tailor the Sentiment Range MA Indicator to various market conditions and personal trading styles, ensuring optimal decision-making.
Quick Start
Based on the provided chart, here's a brief explanation of the default settings for the Sentiment Range MA Indicator:
Length: Set at ` 20 `.
- This determines the base moving average period. A standard setting, it calculates the average price over the last 20 periods, providing traders with a clear perspective of short-term trends.
ATR Length: Set at ` 200 `.
- This adjusts the lookback period for the Average True Range (ATR), which in turn influences the chop zone calculation. At a setting of 200, it offers a comprehensive view, considering a longer stretch of historical data.
Range Multiplier: Set at ` 6 `.
- This multiplies the ATR value, widening or narrowing the band around the SR MA. A setting of 6 means the range around the SR MA is determined by multiplying the ATR by 6, offering a broader fluctuation zone.
On the chart, the green line represents the bullish sentiment and the red represents the bearish sentiment. Price movements above and below these lines can be used as potential buy or sell signals respectively. Fine-tuning these settings can cater the Sentiment Range MA Indicator to your specific trading strategy and market condition preferences.
Alternative Settings
For traders looking to adapt to faster market conditions or prefer a more agile analysis, here's a brief description of the alternative settings for the Sentiment Range MA Indicator:
Length: Set at ` 3 `.
- This highly responsive setting calculates the average price over the last 3 periods. Ideal for quick market movements, it offers traders insights into very short-term price trends and potentially swift trade opportunities.
ATR Length: Set at ` 50 `.
- This shorter lookback period for the Average True Range (ATR) focuses on more recent market volatility, providing a tighter and more current chop zone calculation. It's suitable for those wanting to respond to recent market shifts.
Range Multiplier: Set at ` 4 `.
- Multiplying the ATR by 4 narrows down the buffer around the SR MA. This creates a tighter sentiment range, possibly resulting in more frequent crossovers and trading signals.
In the provided chart, the green line still denotes bullish momentum while the red symbolizes bearish sentiment. These alternative settings might generate more frequent signals, so traders should ensure their strategy is aligned with this heightened sensitivity.
Wrapping Up
The Sentiment Range MA melds stability and agility, making it a valuable tool in your trading toolkit. As always, before integrating new indicators, take the time to understand its nuances and potential impacts on your strategy.
Liquidity Hunter [ChartPrime]The Liquidity Hunter helps traders identify areas in the market where reversals may occur by analyzing candle formations and structures.
█ Wick-to-Body Analysis:
The Liquidity Hunter analyses each candlestick to identify those with distinctive wick-to-body ratios. By focusing on candles with significant wick imbalances, it can reveal potential liquidity absorption zones that may influence market behavior. Users can fine-tune this ratio to their preferences through customizable body% and wick% inputs, allowing for tailored analysis.
█ Body Size Significance:
To ensure the relevance and impact of its findings, this indicator evaluates the size of the candle body.
Only candles with bodies meeting a certain size threshold are considered, eliminating noise and highlighting candles of significance.
█ Dynamic Target Setting:
The Liquidity Hunter employs the Average True Range (ATR) as a foundation for target calculation. Users can adjust their trading targets by specifying a multiplier, offering flexibility in capturing potential profit or managing risk. Customizable target inputs ensure adaptability to your trading strategy.
█ Stop Loss Protection:
In addition to setting your profit targets, the Liquidity Hunter incorporates stop loss levels, safeguarding your investments from excessive risk. By implementing a well-balanced risk-reward ratio, users may be better at navigating market fluctuations.
█ Market Character Labels:
The Liquidity Hunter Indicator goes beyond basic analysis by detecting changes in market character. It identifies shifts in sentiment providing traders with invaluable insights into evolving market conditions.
█ Candle Color Highlighting:
To enhance user-friendliness and visualization, the indicator employs distinctive candle colors between trades. These color cues help you easily spot and interpret trading opportunities, drawing your attention to potential entry and exit points.
Overall this indicator is designed to help simplify liquidity analysis and give visual targets in a market.
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.
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.
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.
