Step Channel Momentum Trend [ChartPrime]OVERVIEW
Step Channel Momentum Trend is a momentum-based price filtering system that adapts to market structure using pivot levels and ATR volatility. It builds a dynamic channel around a stepwise midline derived from swing highs and lows. The system colors price candles based on whether price remains inside this channel (low momentum) or breaks out (strong directional flow). This allows traders to clearly distinguish ranging conditions from trending ones and take action accordingly.
⯁ STRUCTURAL MIDLNE (STEP CHANNEL CORE)
The midline acts as the backbone of the trend system and is based on structure rather than smoothing.
Calculated as the average of the most recent confirmed Pivot High and Pivot Low.
The result is a step-like horizontal line that only updates when new pivot points are confirmed.
This design avoids lag and makes the line "snap" to recent structural shifts.
It reflects the equilibrium level between recent bullish and bearish control.
This unique step logic creates clear regime shifts and prevents noise from distorting trend interpretation.
⯁ DYNAMIC VOLATILITY BANDS (ATR FILTERING)
To detect momentum strength, the script constructs upper and lower bands using the ATR (Average True Range):
The distance from the midline is determined by ATR × multiplier (default: 200-period ATR × 0.6).
These bands adjust dynamically to volatility, expanding in high-ATR environments and contracting in calm markets.
The area between upper and lower bands represents a neutral or ranging market state.
Breakouts outside the bands are treated as significant momentum shifts.
This filtering approach ensures that only meaningful breakouts are visually emphasized — not every candle fluctuation.
⯁ MOMENTUM-BASED CANDLE COLORING
The system visually transforms price candles into momentum indicators:
When price (hl2) is above the upper band, candles are green → bullish momentum.
When price is below the lower band, candles are red → bearish momentum.
When price is between the bands, candles are orange → low or no momentum (range).
The candle body, wick, and border are all colored uniformly for visual clarity.
This gives traders instant feedback on when momentum is expanding or fading — ideal for breakout, pullback, or trend-following strategies.
⯁ PIVOT-BASED SWING ANCHORS
Each confirmed pivot is plotted as a label ⬥ directly on the chart:
They also serve as potential manual entry zones, SL/TP anchors, or confirmation points.
⯁ MOMENTUM STATE LABEL
To reinforce the current market mode, a live label is displayed at the most recent candle:
Displays either:
“ Momentum Up ” when price breaks above the upper band.
“ Momentum Down ” when price breaks below the lower band.
“ Range ” when price remains between the bands.
Label color matches the candle color for quick identification.
Automatically updates on each bar close.
This helps discretionary traders filter trades based on market phase.
USAGE
Use the green/red zones to enter with momentum and ride trending moves.
Use the orange zone to stay out or fade ranges.
The step midline can act as a breakout base, pullback anchor, or bias reference.
Combine with other indicators (e.g., order blocks, divergences, or volume) to build high-confluence systems.
CONCLUSION
Step Channel Momentum Trend gives traders a clean, adaptive framework for identifying trend direction, volatility-based breakouts, and ranging environments — all from structural logic and ATR responsiveness. Its stepwise midline provides clarity, while its dynamic color-coded candles make momentum shifts impossible to miss. Whether you’re scalping intraday momentum or managing swing entries, this tool helps you trade with the market’s rhythm — not against it.
Parallel Channel
Rolling VWAP Channel [LuxAlgo]The Rolling VWAP Channel indicator creates a channel by analyzing a large number of Volume Weighted Average Prices (VWAPs) and determining a Channel based on percentile linear interpolation throughout the VWAPs.
🔶 USAGE
In this indicator, we have formed a Channel by first calculating multiple VWAPs, each with their respective anchor, then locating prices using "Percentile Linear Interpolation".
Note: Percentile Linear Interpolation locates the price point at which a specified percentage of VWAPs fall below it.
For example, a percentile of 50% would mean that 50% of the VWAP values fall below this price.
This method of analysis is important since the VWAPs are not often evenly distributed; therefore, we are able to draw importance to different levels by analyzing in percentiles.
When visualized, there is typically clustering of the VWAP values, which occurs at any given time, as seen below.
The channel can be tailored to each individual, with full control of each percentile represented in the channel. That being said, a general concept is that these clustered areas are clear results of sideways price action, which would lead us to believe that after interactions at these levels, we should expect to see a directional decision made by the market closely after.
🔶 DETAILS
The Rolling VWAP calculation calculates a user-specified number of VWAPs (up to 500), each anchored to a unique starting point in the chart based on the start of a new timeframe.
Each new timeframe that occurs causes a new VWAP to initialize. When the total number of desired VWAPs is reached, the oldest VWAP is removed and re-initialized, anchored to the current bar. Hence, the name " Rolling " VWAPs
This method allows us to automatically generate and manage large amounts of VWAPs without the need for user interaction.
After we have generated these VWAPs, we are able to run analyses on their returned values, such as the "Percentile Linear Interpolation" mentioned in the section above.
🔶 SETTINGS
Anchor Period: Choose which time period to use as the anchor point to initialize new VWAPs from.
VWAP Source: Choose the source for your VWAPs to calculate.
VWAP Amount: Sets the number of VWAPs to use. After this amount is on the chart, the oldest will be rolled.
🔹 Channel Lines
Toggle: Enable the associated VWAP Channel percentile line.
Percentile: Adjust each line's percentile independently for your needs.
Width: Adjust the width of the associated percentile line.
🔹 Calculation
Calculated Bars: Tells the indicator how many bars to calculate on, for faster calculations with less history, use a lower value. Setting this to 0 will remove the bar constraint.
Support and Resistance Power Channel [ChartPrime]The Support and Resistance Power Channel indicator helps traders visualize key support and resistance zones, along with buy and sell power within those zones. By identifying the highest and lowest prices within a defined range, this indicator provides insight into potential price reversals and market strength. It calculates the strength of buy and sell pressure within the zones and includes additional features like midline values and delayed signals to reduce false breakouts.
⯁ KEY FEATURES AND HOW TO USE
⯌ Support and Resistance Zones :
This indicator identifies dynamic support (lower zone) and resistance (upper zone) levels, allowing traders to easily visualize key price levels. These zones are customizable with settings for the length of the channel and how far the zones extend into the future. The zones can be used to predict areas of potential price reversal or consolidation.
⯌ Buy and Sell Power :
Within the upper resistance zone, the indicator calculates Sell Power based on the number of bearish candles, while the lower support zone calculates Buy Power based on bullish candles. This feature helps traders understand the strength of buying or selling activity within each zone.
Example of buy and sell power tracking:
⯌ Highest, Lowest, and Mid Price Levels :
The indicator marks the highest and lowest price levels within the channel with an "X," and displays these values at the end of the channel. Additionally, the midline (average of the high and low) is plotted with a dotted line, showing a key area that the price often retests during trends.
⯌ Delayed Signal Markers :
To prevent false breakouts, the indicator includes a 2-bar delay for signals. These signals are plotted when the price crosses above or below the resistance or support zones, confirming potential reversals or breakouts. Arrows or diamonds are used to mark these signals on the chart.
Example of delayed breakout signals on the chart:
⯌ Extend Zones into the Future :
In the settings, traders can extend the support and resistance zones further into the future, allowing for ongoing analysis even after the initial levels have been identified. This feature can help with forward-looking trade planning.
⯁ USER INPUTS
Length : Defines the number of bars used to calculate the support and resistance zones.
Extend : Sets how far the support and resistance zones should be extended into the future.
Top and Bottom Colors : Allows customization of the colors for the support and resistance zones.
⯁ CONCLUSION
The Support and Resistance Power Channel indicator provides a powerful and visually intuitive way to track key market levels, buy and sell pressure, and potential reversals. With its real-time zone plotting and the calculation of power within each zone, it offers traders essential insights for making more informed trading decisions.
NR4 & NR7 with Breakouts [LuxAlgo]NR4 & NR7 with Breakouts is a simple indicator that utilizes the NR4 and NR7 candle patterns to display candle ranges and signals from range breakouts.
🔶 USAGE
The Narrow Range Patterns are candle formations determined by the last candle having a narrower (high-low) range than the previous number. This indicator showcases the 2 most recognized Narrow Range Patterns, which are the 4 and 7 bar variants (NR4 and NR7).
These patterns, introduced by Toby Crabel, are thought to provide insight for potential market breakouts by identifying periods of low volatility indicated by a candle with a small range. This is due to the idea that markets often move from periods of low volatility (contraction) to high volatility (expansion), and the NR4 and NR7 patterns help spot these transitions.
By utilizing these patterns, traders are better able to anticipate and respond to market shifts for better decision-making and risk management.
NOTE: These patterns have traditionally been studied on the Daily Timeframe Chart. This indicator allows the user to select a timeframe to generate these patterns from. It is suggested to be mindful of this when considering these patterns.
In this indicator, on the bar after the pattern is detected, the Narrow Range Bar will be highlighted with a zone, and lines displaying the range will extend from it. These ranges are helpful for providing levels to set limit orders and for managing risk.
Users are able to adjust which pattern they want visualized on their chart, please note;
All NR7s are NR4s but not all NR4s are NR7s.
Because of this, you will notice that when selecting "NR4" to display, the colors will change, but the detected ranges will not change.
🔹 Signals
When a Narrow Range Bar is detected, the script will wait for the price to close outside of the Range, then a signal will fire indicating the direction of exit. The signals are produced from the last NR4 or NR7 and will have the potential to fire from that range until a new NR4 or NR7 is detected.
After a signal fires, the logic goes into a "reset" period where it will wait for the price to reach the Range Mean before firing another signal.
These signals can be anticipated by considering the underlying logic and watching price approach the range extremities, and can be improved by utilizing other market information for confluence.
🔶 SETTINGS
Timeframe: Choose which timeframe to identify the NR4 and NR7 Pattern on. This must be Higher than the chart timeframe.
Pattern Type: Choose which (or all) patterns to display.
LinearRegressionLibrary "LinearRegression"
Calculates a variety of linear regression and deviation types, with optional emphasis weighting. Additionally, multiple of slope and Pearson’s R calculations.
calcSlope(_src, _len, _condition)
Calculates the slope of a linear regression over the specified length.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period for the linear regression.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.
Returns: (float) The slope of the linear regression.
calcReg(_src, _len, _condition)
Calculates a basic linear regression, returning y1, y2, slope, and average.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) An array of 4 values: .
calcRegStandard(_src, _len, _emphasis, _condition)
Calculates an Standard linear regression with optional emphasis.
Parameters:
_src (float) : (series float) The source data series.
_len (int) : (int) The length of the lookback period.
_emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegRidge(_src, _len, lambda, _emphasis, _condition)
Calculates a ridge regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
lambda (float) : (float) The ridge regularization parameter.
_emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegLasso(_src, _len, lambda, _emphasis, _condition)
Calculates a Lasso regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
lambda (float) : (float) The Lasso regularization parameter.
_emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcElasticNetLinReg(_src, _len, lambda1, lambda2, _emphasis, _condition)
Calculates an Elastic Net regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
lambda1 (float) : (float) L1 regularization parameter (Lasso).
lambda2 (float) : (float) L2 regularization parameter (Ridge).
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegHuber(_src, _len, delta, iterations, _emphasis, _condition)
Calculates a Huber regression using Iteratively Reweighted Least Squares (IRLS).
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
delta (float) : (float) Huber threshold parameter.
iterations (int) : (int) Number of IRLS iterations.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegLAD(_src, _len, iterations, _emphasis, _condition)
Calculates a Least Absolute Deviations (LAD) regression via IRLS.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
iterations (int) : (int) Number of IRLS iterations for LAD.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegBayesian(_src, _len, priorMean, priorSpan, sigma, _emphasis, _condition)
Calculates a Bayesian linear regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
priorMean (float) : (float) The prior mean for the slope.
priorSpan (float) : (float) The prior variance (or span) for the slope.
sigma (float) : (float) The assumed standard deviation of residuals.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRFromLinReg(_src, _len, _slope, _average, _y1, _condition)
Calculates the Pearson correlation coefficient (R) based on linear regression parameters.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_average (float) : (float) The average value of the source data series.
_y1 (float) : (float) The starting point (y-intercept of the oldest bar) for the linear regression.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.
Returns: (float) The Pearson correlation coefficient (R) adjusted for the direction of the slope.
calcRFromSource(_src, _len, _condition)
Calculates the correlation coefficient (R) using a specified length and source data.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.
Returns: (float) The correlation coefficient (R).
calcSlopeLengthZero(_src, _len, _minLen, _step, _condition)
Identifies the length at which the slope is flattest (closest to zero).
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length to consider (minimum of 2).
_minLen (int) : (int) The minimum length to start from (cannot exceed the max length).
_step (int) : (int) The increment step for lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the slope is flattest.
calcSlopeLengthHighest(_src, _len, _minLen, _step, _condition)
Identifies the length at which the slope is highest.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the slope is highest.
calcSlopeLengthLowest(_src, _len, _minLen, _step, _condition)
Identifies the length at which the slope is lowest.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the slope is lowest.
calcSlopeLengthAbsolute(_src, _len, _minLen, _step, _condition)
Identifies the length at which the absolute slope value is highest.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the absolute slope value is highest.
calcRLengthZero(_src, _len, _minLen, _step, _condition)
Identifies the length with the lowest absolute R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the lowest absolute R value.
calcRLengthHighest(_src, _len, _minLen, _step, _condition)
Identifies the length with the highest R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the highest R value.
calcRLengthLowest(_src, _len, _minLen, _step, _condition)
Identifies the length with the lowest R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the lowest R value.
calcRLengthAbsolute(_src, _len, _minLen, _step, _condition)
Identifies the length with the highest absolute R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the highest absolute R value.
calcDevReverse(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the regressive linear deviation in reverse order, with optional emphasis on recent data.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevForward(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the progressive linear deviation in forward order (oldest to most recent bar), with optional emphasis.
Parameters:
_src (float) : (float) The source data array, where _src is oldest and _src is most recent.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept of the linear regression (value at the most recent bar, adjusted by slope).
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevBalanced(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the balanced linear deviation with optional emphasis on recent or older data.
Parameters:
_src (float) : (float) Source data array, where _src is the most recent and _src is the oldest.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept of the linear regression (value at the oldest bar).
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevMean(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the mean absolute deviation from a forward-applied linear trend (oldest to most recent), with optional emphasis.
Parameters:
_src (float) : (float) The source data array, where _src is the most recent and _src is the oldest.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevMedian(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the median absolute deviation with optional emphasis on recent data.
Parameters:
_src (float) : (float) The source data array (index 0 = oldest, index _len - 1 = most recent).
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns:
calcDevPercent(_y1, _inputDev, _condition)
Calculates the percent deviation from a given value and a specified percentage.
Parameters:
_y1 (float) : (float) The base value from which to calculate deviation.
_inputDev (float) : (float) The deviation percentage.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevFitted(_len, _slope, _y1, _emphasis, _condition)
Calculates the weighted fitted deviation based on high and low series data, showing max deviation, with optional emphasis.
Parameters:
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The Y-intercept (oldest bar) of the linear regression.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevATR(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates an ATR-style deviation with optional emphasis on recent data.
Parameters:
_src (float) : (float) The source data (typically close).
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The Y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcPricePositionPercent(_top, _bot, _src)
Calculates the percent position of a price within a linear regression channel. Top=100%, Bottom=0%.
Parameters:
_top (float) : (float) The top (positive) deviation, corresponding to 100%.
_bot (float) : (float) The bottom (negative) deviation, corresponding to 0%.
_src (float) : (float) The source price.
Returns: (float) The percent position within the channel.
plotLinReg(_len, _y1, _y2, _slope, _devTop, _devBot, _scaleTypeLog, _lineWidth, _extendLines, _channelStyle, _colorFill, _colUpLine, _colDnLine, _colUpFill, _colDnFill)
Plots the linear regression line and its deviations, with configurable styles and fill.
Parameters:
_len (int) : (int) The lookback period for the linear regression.
_y1 (float) : (float) The starting y-value of the regression line.
_y2 (float) : (float) The ending y-value of the regression line.
_slope (float) : (float) The slope of the regression line (used to determine line color).
_devTop (float) : (float) The top deviation to add to the line.
_devBot (float) : (float) The bottom deviation to subtract from the line.
_scaleTypeLog (bool) : (bool) Use a log scale if true; otherwise, linear scale.
_lineWidth (int) : (int) The width of the plotted lines.
_extendLines (string) : (string) How lines should extend (none, left, right, both).
_channelStyle (string) : (string) The style of the channel lines (solid, dashed, dotted).
_colorFill (bool) : (bool) Whether to fill the space between the top and bottom deviation lines.
_colUpLine (color) : (color) Line color when slope is positive.
_colDnLine (color) : (color) Line color when slope is negative.
_colUpFill (color) : (color) Fill color when slope is positive.
_colDnFill (color) : (color) Fill color when slope is negative.
Prime Bands [ChartPrime]The Prime Standard Deviation Bands indicator uses custom-calculated bands based on highest and lowest price values over specific period to analyze price volatility and trend direction. Traders can set the bands to 1, 2, or 3 standard deviations from a central base, providing a dynamic view of price behavior in relation to volatility. The indicator also includes color-coded trend signals, standard deviation labels, and mean reversion signals, offering insights into trend strength and potential reversal points.
⯁ KEY FEATURES AND HOW TO USE
⯌ Standard Deviation Bands :
The indicator plots upper and lower bands based on standard deviation settings (1, 2, or 3 SDs) from a central base, allowing traders to visualize volatility and price extremes. These bands can be used to identify overbought and oversold conditions, as well as potential trend reversals.
Example of 3-standard-deviation bands around price:
⯌ Dynamic Trend Indicator :
The midline of the bands changes color based on trend direction. If the midline is rising, it turns green, indicating an uptrend. When the midline is falling, it turns orange, suggesting a downtrend. This color coding provides a quick visual reference to the current trend.
Trend color examples for rising and falling midlines:
⯌ Standard Deviation Labels :
At the end of the bands, the indicator displays labels with price levels for each standard deviation level (+3, 0, -3, etc.), helping traders quickly reference where price is relative to its statistical boundaries.
Price labels at each standard deviation level on the chart:
⯌ Mean Reversion Signals :
When price moves beyond the upper or lower bands and then reverts back inside, the indicator plots mean reversion signals with diamond icons. These signals indicate potential reversal points where the price may return to the mean after extreme moves.
Example of mean reversion signals near bands:
⯌ Standard Deviation Scale on Chart :
A visual scale on the right side of the chart shows the current price position in relation to the bands, expressed in standard deviations. This scale provides an at-a-glance view of how far price has deviated from the mean, helping traders assess risk and volatility.
⯁ USER INPUTS
Length : Sets the number of bars used in the calculation of the bands.
Standard Deviation Level : Allows selection of 1, 2, or 3 standard deviations for upper and lower bands.
Colors : Customize colors for the uptrend and downtrend midline indicators.
⯁ CONCLUSION
The Prime Standard Deviation Bands indicator provides a comprehensive view of price volatility and trend direction. Its customizable bands, trend coloring, and mean reversion signals allow traders to effectively gauge price behavior, identify extreme conditions, and make informed trading decisions based on statistical boundaries.
Improved G-Trend DetectionIt is the Improved version of G trend channel detection.
The Umair Trend Detection Indicator is a powerful tool designed to help traders identify potential buy and sell opportunities by combining dynamic price channels with RSI-based confirmation. This indicator is suitable for all types of financial markets, including stocks, forex, and cryptocurrencies.
Key Features:
Dynamic G-Channels
Calculates upper, lower, and average price channels based on the "G-Channel" methodology.
Helps identify market extremes and potential reversal points.
RSI Confirmation
Integrates RSI (Relative Strength Index) to filter buy and sell signals.
Avoids false signals by ensuring market momentum aligns with trend direction.
Buy/Sell Signals
Generates "Buy" signals when bullish conditions align with oversold RSI levels.
Generates "Sell" signals when bearish conditions align with overbought RSI levels.
Exit Signals
Provides optional exit points for both long and short positions using a buffer for confirmation.
Visual Clarity
Displays clearly plotted channels and average lines to help visualize price trends.
Buy and sell signals are marked with arrows for easy identification on the chart.
Custom Alerts
Offers customizable alerts for buy, sell, and exit conditions, ensuring traders never miss an opportunity.
Input Parameters:
Channel Length: Controls the sensitivity of the G-Channels.
Multiplier: Adjusts the width of the channels to suit different market conditions.
RSI Settings: Customize RSI length and thresholds for overbought/oversold conditions.
Exit Signal Buffer: Adds flexibility to the exit strategy by delaying signals for confirmation.
How It Helps:
The Umair Trend Detection Indicator is perfect for traders looking for an easy-to-use trend-following system with strong confirmation. By combining dynamic channels with RSI, it provides accurate and reliable signals to enter and exit trades, minimizing risks associated with false breakouts or trend reversals.
Use Cases:
Trend Trading: Identify and follow long-term trends with confidence.
Swing Trading: Spot reversals and capitalize on medium-term price movements.
Risk Management: Use exit signals to lock in profits or limit losses effectively.
This indicator is a versatile tool for both novice and experienced traders. Fine-tune its settings to align with your trading style and improve your decision-making in any market.
True Amplitude Envelopes (TAE)The True Envelopes indicator is an adaptation of the True Amplitude Envelope (TAE) method, based on the research paper " Improved Estimation of the Amplitude Envelope of Time Domain Signals Using True Envelope Cepstral Smoothing " by Caetano and Rodet. This indicator aims to create an asymmetric price envelope with strong predictive power, closely following the methodology outlined in the paper.
Due to the inherent limitations of Pine Script, the indicator utilizes a Kernel Density Estimator (KDE) in place of the original Cepstral Smoothing technique described in the paper. While this approach was chosen out of necessity rather than superiority, the resulting method is designed to be as effective as possible within the constraints of the Pine environment.
This indicator is ideal for traders seeking an advanced tool to analyze price dynamics, offering insights into potential price movements while working within the practical constraints of Pine Script. Whether used in dynamic mode or with a static setting, the True Envelopes indicator helps in identifying key support and resistance levels, making it a valuable asset in any trading strategy.
Key Features:
Dynamic Mode: The indicator dynamically estimates the fundamental frequency of the price, optimizing the envelope generation process in real-time to capture critical price movements.
High-Pass Filtering: Uses a high-pass filtered signal to identify and smoothly interpolate price peaks, ensuring that the envelope accurately reflects significant price changes.
Kernel Density Estimation: Although implemented as a workaround, the KDE technique allows for flexible and adaptive smoothing of the envelope, aimed at achieving results comparable to the more sophisticated methods described in the original research.
Symmetric and Asymmetric Envelopes: Provides options to select between symmetric and asymmetric envelopes, accommodating various trading strategies and market conditions.
Smoothness Control: Features adjustable smoothness settings, enabling users to balance between responsiveness and the overall smoothness of the envelopes.
The True Envelopes indicator comes with a variety of input settings that allow traders to customize the behavior of the envelopes to match their specific trading needs and market conditions. Understanding each of these settings is crucial for optimizing the indicator's performance.
Main Settings
Source: This is the data series on which the indicator is applied, typically the closing price (close). You can select other price data like open, high, low, or a custom series to base the envelope calculations.
History: This setting determines how much historical data the indicator should consider when calculating the envelopes. A value of 0 will make the indicator process all available data, while a higher value restricts it to the most recent n bars. This can be useful for reducing the computational load or focusing the analysis on recent market behavior.
Iterations: This parameter controls the number of iterations used in the envelope generation algorithm. More iterations will typically result in a smoother envelope, but can also increase computation time. The optimal number of iterations depends on the desired balance between smoothness and responsiveness.
Kernel Style: The smoothing kernel used in the Kernel Density Estimator (KDE). Available options include Sinc, Gaussian, Epanechnikov, Logistic, and Triangular. Each kernel has different properties, affecting how the smoothing is applied. For example, Gaussian provides a smooth, bell-shaped curve, while Epanechnikov is more efficient computationally with a parabolic shape.
Envelope Style: This setting determines whether the envelope should be Static or Dynamic. The Static mode applies a fixed period for the envelope, while the Dynamic mode automatically adjusts the period based on the fundamental frequency of the price data. Dynamic mode is typically more responsive to changing market conditions.
High Q: This option controls the quality factor (Q) of the high-pass filter. Enabling this will increase the Q factor, leading to a sharper cutoff and more precise isolation of high-frequency components, which can help in better identifying significant price peaks.
Symmetric: This setting allows you to choose between symmetric and asymmetric envelopes. Symmetric envelopes maintain an equal distance from the central price line on both sides, while asymmetric envelopes can adjust differently above and below the price line, which might better capture market conditions where upside and downside volatility are not equal.
Smooth Envelopes: When enabled, this setting applies additional smoothing to the envelopes. While this can reduce noise and make the envelopes more visually appealing, it may also decrease their responsiveness to sudden market changes.
Dynamic Settings
Extra Detrend: This setting toggles an additional high-pass filter that can be applied when using a long filter period. The purpose is to further detrend the data, ensuring that the envelope focuses solely on the most recent price oscillations.
Filter Period Multiplier: This multiplier adjusts the period of the high-pass filter dynamically based on the detected fundamental frequency. Increasing this multiplier will lengthen the period, making the filter less sensitive to short-term price fluctuations.
Filter Period (Min) and Filter Period (Max): These settings define the minimum and maximum bounds for the high-pass filter period. They ensure that the filter period stays within a reasonable range, preventing it from becoming too short (and overly sensitive) or too long (and too sluggish).
Envelope Period Multiplier: Similar to the filter period multiplier, this adjusts the period for the envelope generation. It scales the period dynamically to match the detected price cycles, allowing for more precise envelope adjustments.
Envelope Period (Min) and Envelope Period (Max): These settings establish the minimum and maximum bounds for the envelope period, ensuring the envelopes remain adaptive without becoming too reactive or too slow.
Static Settings
Filter Period: In static mode, this setting determines the fixed period for the high-pass filter. A shorter period will make the filter more responsive to price changes, while a longer period will smooth out more of the price data.
Envelope Period: This setting specifies the fixed period used for generating the envelopes in static mode. It directly influences how tightly or loosely the envelopes follow the price action.
TAE Smoothing: This controls the degree of smoothing applied during the TAE process in static mode. Higher smoothing values result in more gradual envelope curves, which can be useful in reducing noise but may also delay the envelope’s response to rapid price movements.
Visual Settings
Top Band Color: This setting allows you to choose the color for the upper band of the envelope. This band represents the resistance level in the price action.
Bottom Band Color: Similar to the top band color, this setting controls the color of the lower band, which represents the support level.
Center Line Color: This is the color of the central price line, often referred to as the carrier. It represents the detrended price around which the envelopes are constructed.
Line Width: This determines the thickness of the plotted lines for the top band, bottom band, and center line. Thicker lines can make the envelopes more visible, especially when overlaid on price data.
Fill Alpha: This controls the transparency level of the shaded area between the top and bottom bands. A lower alpha value will make the fill more transparent, while a higher value will make it more opaque, helping to highlight the envelope more clearly.
The envelopes generated by the True Envelopes indicator are designed to provide a more precise and responsive representation of price action compared to traditional methods like Bollinger Bands or Keltner Channels. The core idea behind this indicator is to create a price envelope that smoothly interpolates the significant peaks in price action, offering a more accurate depiction of support and resistance levels.
One of the critical aspects of this approach is the use of a high-pass filtered signal to identify these peaks. The high-pass filter serves as an effective method of detrending the price data, isolating the rapid fluctuations in price that are often lost in standard trend-following indicators. By filtering out the lower frequency components (i.e., the trend), the high-pass filter reveals the underlying oscillations in the price, which correspond to significant peaks and troughs. These oscillations are crucial for accurately constructing the envelope, as they represent the most responsive elements of the price movement.
The algorithm works by first applying the high-pass filter to the source price data, effectively detrending the series and isolating the high-frequency price changes. This filtered signal is then used to estimate the fundamental frequency of the price movement, which is essential for dynamically adjusting the envelope to current market conditions. By focusing on the peaks identified in the high-pass filtered signal, the algorithm generates an envelope that is both smooth and adaptive, closely following the most significant price changes without overfitting to transient noise.
Compared to traditional envelopes and bands, such as Bollinger Bands and Keltner Channels, the True Envelopes indicator offers several advantages. Bollinger Bands, which are based on standard deviations, and Keltner Channels, which use the average true range (ATR), both tend to react to price volatility but do not necessarily follow the peaks and troughs of the price with precision. As a result, these traditional methods can sometimes lag behind or fail to capture sudden shifts in price momentum, leading to either false signals or missed opportunities.
In contrast, the True Envelopes indicator, by using a high-pass filtered signal and a dynamic period estimation, adapts more quickly to changes in price behavior. The envelopes generated by this method are less prone to the lag that often affects standard deviation or ATR-based bands, and they provide a more accurate representation of the price's immediate oscillations. This can result in better predictive power and more reliable identification of support and resistance levels, making the True Envelopes indicator a valuable tool for traders looking for a more responsive and precise approach to market analysis.
In conclusion, the True Envelopes indicator is a powerful tool that blends advanced theoretical concepts with practical implementation, offering traders a precise and responsive way to analyze price dynamics. By adapting the True Amplitude Envelope (TAE) method through the use of a Kernel Density Estimator (KDE) and high-pass filtering, this indicator effectively captures the most significant price movements, providing a more accurate depiction of support and resistance levels compared to traditional methods like Bollinger Bands and Keltner Channels. The flexible settings allow for extensive customization, ensuring the indicator can be tailored to suit various trading strategies and market conditions.
FVG Channel [LuxAlgo]The FVG Channel indicator displays a channel constructed from the averages of unmitigated historical fair value gaps (FVG), allowing to identify trends and potential reversals in the market.
Users can control the amount of FVGs to consider for the calculation of the channels, as well as their degree of smoothness through user settings.
🔶 USAGE
The FVG Channel is constructed by averaging together recent unmitigated Bullish FVGs (contributing to the creation of the upper bands), and Bearish unmitigated FVGs (contributing to the creation of the lower bands) within a lookback determined by the user. A higher lookback will return longer-term indications from the indicator.
The channel includes 5 bands, with one upper and one lower outer extremities, as well as an inner series of values determined using the Fibonacci ratios (respectively 0.786, 0.5, 0.236) from the channel's outer extremities.
An uptrend can be identified by price holding above the inner upper band (obtained from the 0.786 ratio), this band can also provide occasional support when the price retraces to it while in an uptrend.
Breaking below the inner upper band with an unwillingness to reach above again is a clear sign of hesitation in the market and can be indicative of an upcoming consolidation or reversal.
This can directly be applied to downtrends as well, below are examples displaying both scenarios.
Uptrend Example:
Downtrend Example:
🔹 Breakout Levels
When the price mitigates all FVGs in a single direction except for 1, the indicator will display a "Breakout Level". This is the level that price will need to cross in order for all FVGs in that direction to be mitigated, because of this they can also be aptly called "Last Stand Levels".
These levels can be considered as potential support and resistance levels, however, should always be monitored for breakouts since a substantial push above or below these points would indicate strong momentum.
🔹 Signals
The indicator includes Bullish and Bearish Signals, these signals fire when all FVGs for a single direction have been mitigated and an engulfing candle occurs in the opposite direction. These are reversal signals and should be used alongside other indicators to appropriately manage risk.
Note: When all FVGs in a single direction have been mitigated, the candles will change colors accordingly.
🔶 DETAILS
The script uses a typical identification method for FVGs. Once identified, the script collects and stores the mitigation levels of the respective bullish and bearish FVGs:
For Bullish FVGs this is the bottom of the FVG.
For Bearish FVGs this is the top of the FVG.
The data is managed to only consider a specific amount of FVG mitigation levels, determined by the set "Unmitigated FVG Lookback". If an FVG is mitigated, it frees up a spot in the memory for a new FVG, however, if the memory is full, the oldest will be deleted.
The averages displayed (Channel Upper and Lower) are created from 2 calculation steps, the first step involves taking the raw average of the FVG mitigation levels, and the second step applies a simple moving average (SMA) smoothing of the precedent obtained averages.
Note: To view the mitigation levels average obtained in the first step, the "Smoothing Length" can be set to 1.
🔶 SETTINGS
Unmitigated FVG Lookback: Sets the maximum number of Unmitigated FVG mitigation levels that the script will use to calculate the channel.
Smoothing Length: Sets the smoothing length for the channel to reduce noise from the raw data.
Periodic Linear Regressions [LuxAlgo]The Periodic Linear Regressions (PLR) indicator calculates linear regressions periodically (similar to the VWAP indicator) based on a user-set period (anchor).
This allows for estimating underlying trends in the price, as well as providing potential supports/resistances.
🔶 USAGE
The Periodic Linear Regressions indicator calculates a linear regression over a user-selected interval determined from the selected "Anchor Period".
The PLR can be visualized as a regular linear regression (Static), with a fit readjusting for new data points until the end of the selected period, or as a moving average (Rolling), with new values obtained from the last point of a linear regression fitted over the calculation interval. While the static method line is prone to repainting, it has value since it can further emphasize the linearity of an underlying trend, as well as suggest future trend directions by extrapolating the fit.
Extremities are included in the indicator, these are obtained from the root mean squared error (RMSE) between the price and calculated linear regression. The Multiple setting allows the users to control how far each extremity is from the other.
Periodic Linear Regressions can be helpful in finding support/resistance areas or even opportunities when ranging in a channel.
The anchor - where a new period starts - can be shown (in this case in the top right corner).
The shown bands can be visualized by enabling Show Extremities in settings ( Rolling or Static method).
The script includes a background gradient color option for the bands, which only applies when using the Rolling method.
The indicator colors can be suggestive of the detected trend and are determined as follows:
Method Rolling: a gradient color between red and green indicates the trend; more green if the output is rising, suggesting an uptrend, and more red if it is decreasing, suggesting a downtrend.
Method Static: green if the slope of the line is positive, suggesting an uptrend, red if negative, suggesting a downtrend.
🔶 DETAILS
🔹 Anchor Type
When the Anchor Type is set to Periodic , the indicator will be reset when the "Anchor Period" changes, after which calculations will start again.
An anchored rolling line set at First Bar won't reset at a new session; it will continue calculating the linear regression from the first bar to the last; in other words, every bar is included in the calculation. This can be useful to detect potential long-term tops/bottoms.
Note that a linear regression needs at least two values for its calculation, which explains why you won't see a static line at the first bar of the session. The rolling linear regression will only show from the 3rd bar of the session since it also needs a previous value.
🔹 Rolling/Static
When Anchor Type is set at Periodic , a linear regression is calculated between the first bar of the chosen session and the current bar, aiming to find the line that best fits the dataset.
The example above shows the lines drawn during the session. The offered script, though, shows the last calculated point connected to the previous point when the Rolling method is chosen, while the Static method shows the latest line.
Note that linear regression needs at least two values, which explains why you won't see a static line at the first bar of the session. The rolling line will only show from the 3rd bar of the session since it also needs a previous value.
🔶 SETTINGS
Method: Indicator method used, with options: "Static" (straight line) / "Rolling" (rolling linear regression).
Anchor Type: "Periodic / First Bar" (the latter works only when "Method" is set to "Rolling").
Anchor Period: Only applicable when "Anchor Type" is set at "Periodic".
Source: open, high, low, close, ...
Multiple: Alters the width of the bands when "Show Extremities" is enabled.
Show Extremities: Display one upper and one lower extremity.
🔹 Color Settings
Mono Color: color when "Bicolor" is disabled
Bicolor: Toggle on/off + Colors
Gradient: Background color when "Show extremities" is enabled + level of gradient
🔹 Dashboard
Show Dashboard
Location of dashboard
Text size
Half Cup [LuxAlgo]The Half Cup indicator detects and displays patterns with the shape of a Half Cup , initiating a channel. From this channel, breakouts are detected and highlighted with dots.
Users can control the shape of the Half Cup and the channel length through various settings.
Do note that the displayed half cups are displayed retrospectively, making them subject to backpainting.
🔶 USAGE
The idea behind the indicator is derived from the Cup & Handle pattern, which requires waiting for the pattern full completion.
Our Half Cup publication aims to find opportunities when the potential cup is only formed halfway.
In this example, a green dot shows the first breakout of the upper channel extremity. A few bars later, the price went under it, after which it returned above, triggering a second green dot. Both triggers were good opportunities in this case, and the price rose afterward.
The Half Cup pattern can be the start of a potential complete Cup & Handle (As in the example above, a complete Cup pattern (without the Handle ) is shown, manually drawn with dashed lines).
Every green/red dot, whether on a bullish or bearish pattern, points to a breakout respectively above/below the channel.
Besides drawing patterns and the corresponding breakouts, the Half Cup indicator can also provide insights into trends and potential opportunities in the long run.
🔶 DETAILS
🔹 Validation
Several criteria must be fulfilled before a visible pattern on the chart is drawn.
Calculations are done beforehand to know where the Half Cup pattern would be positioned.
The pattern's bottom and top edges are checked for the number of bars whose closing price is outside the half-cup area. When the number of breakouts above/below is equal to or lower than the user-defined settings ( Max % Breaks Top/Bottom ), the pattern is drawn together with a brighter-colored channel next to it.
Dots highlighting the channel's breakout can be drawn from that moment until the end of both channel lines.
🔹 Positioning
Users can adjust the following settings to fit their needs:
% Broadness: Moves the Top/Bottom line (bullish or bearish) diagonally upwards/downwards.
Vertical Shift: Shifts the entire pattern up/down.
Channel Length: Sets the line length of the channel.
Note that adjusting the position of the pattern will change the validation; the script will be rerun to check if patterns are still valid or if new patterns can be drawn. Some patterns may disappear, while new ones may appear.
Before adjusting the position, the user can set Max % Breaks Top/Bottom at 100%. When the positioning is set, Max % Breaks Top/Bottom can be set as desired.
🔹 Updated Drawings
The Half Cup pattern is always drawn retrospectively (that is it is subject to backpainting), the channel is drawn from the bar from where the pattern is detected. Every breakout of the channel will remain visible as dots.
When a new swing high/low is found while the previous swing low/high remains the same, the pattern is updated to minimize clutter. The dots of earlier drawings will remain visible (to ensure no repainting occurs), but the color becomes faded, as such bright dots are associated with patterns that are visible on the chart, while faded dots are from removed/updated patterns.
🔶 SETTINGS
Swing Length: Period used for the swing detection, with higher values returning longer-term Swing Levels.
🔹 Validation
Max % Breaks Bottom: Allowed maximum amount of bars where the closing price is below the bottom of the Half Cup pattern against the total width of the pattern (bars).
Max % Breaks Top: Allowed maximum amount of bars where the closing price is above the top of the Half Cup pattern against the total width of the pattern (bars).
🔹 Positioning
% Broadness: Moves the Top/Bottom line (bullish or bearish) diagonally upwards/downwards.
Vertical Shift: Shifts the entire pattern up/down.
Channel Length: Sets the line length of the channel.
Linear Regression Channel 200█ OVERVIEW
This a simplified version of linear regression channel which use length 200 instead of traditional length 100.
█ FEATURES
Color change depends light / dark mode.
█ LIMITATIONS
Limited to source of closing price and max bars back is 1500.
█ SIMILAR
Regression Channel Alternative MTF
Regression Channel Alternative MTF V2
Fibonacci HH LL TRAMA BandLuxAlgo's Trend Moving Adaptive Moving Average was used as a reference to create bands by reading the highest and lowest prices of past bars based on Fibonacci numbers and then multiplying them by the Fibonacci ratio.
LuxAlgo/ LuxAlgo/
In particular, the so-called TRAMA is characterized by its adaptation to the average of the highest and lowest prices over a specific period of time and is used to identify support/resistance.
In order to apply this feature to the maximum extent possible, I used the high or low prices as the source of input, rather than the closing price.
For example,
src = high
not original like
src = close
In addition, I created 6 levels by multiplying the Fibonacci ratio
//Midline
mah = ama1
mal = ama2
m = (mah + mal)/2
//Half Mean Range
dist = (mah - mal)/2
//Levels
h6 = m + dist * 11.089
h5 = m + dist * 6.857
h4 = m + dist * 4.235
h3 = m + dist * 2.618
h2 = m + dist * 1.618
h1 = m + dist * 0.618
l1 = m - dist * 0.618
l2 = m - dist * 1.618
l3 = m - dist * 2.618
l4 = m - dist * 4.235
l5 = m - dist * 6.857
l6 = m - dist * 11.089
If you want to use it for scalping, such as 15 minutes, you can include Fibonacci numbers such as 21,34,55 for a quick reaction type to detect the trend. Also, by including Fibonacci numbers such as 89,144,233, you can see where you stand in the larger trend. Some examples are included below.
For Investors
BTCUSDT 1day Chart Fibonacci number "55"
For Daytraders
BTCUSDT 4hour Chart Fibonacci number "34"
For Scalpers
BTCUSDT 15min Chart Fibonacci number "55"
BTCUSDT 15min Chart Fibonacci number "89"
BTCUSDT 15min Chart Fibonacci number "233"
Fibonacci numbers are 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, etc.,
Fibonacci ratios are 0.618, 1.618, 2.618, 4.236, 6.854, 11.089, etc.,
Nadaraya-Watson Envelope (Non-Repainting) Logarithmic ScaleIn the fast-paced world of trading, having a reliable and accurate indicator can make all the difference. Enter the Nadaraya-Watson Envelope Indicator, a cutting-edge tool designed to provide traders with valuable insights into market trends and potential price movements. In this article, we'll explore the advantages of this non-repainting indicator and how it can empower traders to make informed decisions with confidence.
Accurate Price Analysis:
The Nadaraya-Watson Envelope Indicator operates in a logarithmic scale, allowing for more accurate price analysis. By considering the logarithmic nature of price movements, this indicator captures the subtle nuances of market dynamics, providing a comprehensive view of price action. Traders can leverage this advantage to identify key support and resistance levels, spot potential breakouts, and anticipate trend reversals.
Non-Repainting Reliability:
One of the most significant advantages of the Nadaraya-Watson Envelope Indicator is its non-repainting nature. Repainting indicators can mislead traders by changing historical signals, making it difficult to evaluate past performance accurately. With the non-repainting characteristic of this indicator, traders can have confidence in the reliability and consistency of the signals generated, ensuring more accurate backtesting and decision-making.
Customizable Parameters:
Every trader has unique preferences and trading styles. The Nadaraya-Watson Envelope Indicator offers a range of customizable parameters, allowing traders to fine-tune the indicator to their specific needs. From adjusting the lookback window and relative weighting to defining the start of regression, traders have the flexibility to adapt the indicator to different timeframes and trading strategies, enhancing its effectiveness and versatility.
Envelope Bounds and Estimation:
The Nadaraya-Watson Envelope Indicator calculates upper and lower bounds based on the Average True Range (ATR) and specified factors. These envelope bounds act as dynamic support and resistance levels, providing traders with valuable reference points for potential price targets and stop-loss levels. Additionally, the indicator generates an estimation plot, visually representing the projected price movement, enabling traders to anticipate market trends and make well-informed trading decisions.
Visual Clarity with Plots and Fills:
Clear visualization is crucial for effective technical analysis. The Nadaraya-Watson Envelope Indicator offers plots and fills to enhance visual clarity and ease of interpretation. The upper and lower boundaries are plotted, along with the estimation line, allowing traders to quickly assess price trends and volatility. Fills between the boundaries provide a visual representation of different price regions, aiding in identifying potential trading opportunities and risk management.
Conclusion:
The Nadaraya-Watson Envelope Indicator is a powerful tool for traders seeking accurate and reliable insights into market trends and price movements. With its logarithmic scale, non-repainting nature, customizable parameters, and visual clarity, this indicator equips traders with a competitive edge in the financial markets. By harnessing the advantages offered by the Nadaraya-Watson Envelope Indicator, traders can navigate the complexities of trading with confidence and precision. Unlock the potential of this advanced indicator and elevate your trading strategy to new heights.
RAINBOW AVERAGES - INDICATOR - (AS) - 1/3
-INTRODUCTION:
This is the first of three scripts I intend to publish using rainbow indicators. This script serves as a groundwork for the other two. It is a RAINBOW MOVING AVERAGES indicator primarily designed for trend detection. The upcoming script will also be an indicator but with overlay=false (below the chart, not on it) and will utilize RAINBOW BANDS and RAINBOW OSCILLATOR. The third script will be a strategy combining all of them.
RAINBOW moving averages can be used in various ways, but this script is mainly intended for trend analysis. It is meant to be used with overlay=true, but if the user wishes, it can be viewed below the chart. To achieve this, you need to change the code from overlay=true to false and turn off the first switch that plots the rainbow on the chart (or simply move the indicator to a new pane below). By doing this, you will be able to see how all four conditions used to detect trends work on the chart. But let's not get ahead of ourselves.
-WHAT IS IT:
In its simplest form, this indicator uses 10 moving averages colored like a rainbow. The calculation is as follows:
MA0: This is the main moving average and can be defined with the type (SMA, EMA, RMA, WMA, SINE), length, and price source. However, the second moving average (MA1) is calculated using MA0 as its source, MA2 uses MA1 as the data source, and so on, until the last one, MA9. Hence, there are 10 moving averages. The first moving average is special as all the others derive from it. This indicator has many potential uses, such as entry/exit signals, volatility indication, and stop-loss placement, but for now, we will focus on trend detection.
-TREND DETECTION:
The indicator offers four different background color options based on the user's preference:
0-NONE: No background color is applied as no trend detection tools is being used (boring)
1-CHANGE: The background color is determined by summing the changes of all 10 moving averages (from two bars). If the sum is positive and not falling, the background color is GREEN. If the sum is negative and not rising, the background color is RED. From early testing, it works well for the beginning of a movement but not so much for a lasting trend.
2-RAINBW: The background color is green when all the moving averages are in ascending order, indicating a bullish trend. It is red when all the moving averages are in descending order, indicating a bearish trend. For example, if MA1>MA2>MA3>MA4..., the background color is green. If MA1 threshold, and red indicates width < -threshold.
4-DIRECT: The background color is determined by counting the number of moving averages that are either above or below the input source. If the specified number of moving averages is above the source, the background color is green. If the specified number of moving averages is below the source, the background color is red. If all ten MAs are below the price source, the indicator will show 10, and if all ten MAs are above, it will show -10. The specific value will be set later in the settings (same for 3-TSHOLD variant). This method works well for lasting trends.
Note: If the indicator is turned into a below-chart version, all four color options can be seen as separate indicators.
-PARAMETERS - SETTINGS:
The first line is an on/off switch to plot the skittles indicator (and some info in the tooltip). The second line has already been discussed, which is the background color and the selection of the source (only used for MA0!).
The line "MA1: TYP/LEN" is where we define the parameters of MA0 (important). We choose from the types of moving averages (SMA, EMA, RMA, WMA, SINE) and set the length.
Important Note: It says MA1, but it should be MA0!.
The next line defines whether we want to smooth MA1 (which is actually MA0) and the period for smoothing. When smoothing is turned on, MA0 will be smoothed using a 3-pole super smoother. It's worth noting that although this only applies to MA0, as the other MAs are derived from it, they will also be smoothed.
In the line below, we define the type and length of MAs for MA2 (and other MAs except MA0). The same type and length are used for MA1 to MA9. It's important to remember that these values should be smaller. For example, if we set 55, it means that MA1 is the average of 55 periods of MA0, MA2 will be 55 periods of MA1, and so on. I encourage trying different combinations of MA types as it can be easily adjusted for ur type of trading. RMA looks quirky.
Moving on to the last line, we define some inputs for the background color:
TSH: The threshold value when using 3-TSHOLD-BGC. It's a good idea to change the chart to a pane below for easier adjustment. The default values are based on EURUSD-5M.
BG_DIR: The value that must be crossed or equal to the MA score if using 4-DIRECT-BGC. There are 10 MAs, so the maximum value is also 10. For example, if you set it to 9, it means that at least 9 MAs must be below/above the price for the script to detect a trend. Higher values are recommended as most of the time, this indicator oscillates either around the maximum or minimum value.
-SUMMARY OF SETTINGS:
L1 - PLOT MAs and general info tooltip
L2 - Select the source for MA0 and type of trend detection.
L3 - Set the type and length of MA0 (important).
L4 - Turn smoothing on/off for MA0 and set the period for super smoothing.
L5 - Set the type and length for the rest of the MAs.
L6 - Set values if using 4-DIRECT or 3-TSHOLD for the trend detection.
-OTHERS:
To see trend indicators, you need to turn off the plotting of MAs (first line), and then choose the variant you want for the background color. This will plot it on the chart below.
Keep in mind that M1 int settings stands for MA0 and MA2 for all of the 9 MAs left.
Yes, it may seem more complicated than it actually is. In a nutshell, these are 10 MAs, and each one after MA0 uses the previous one as its source. Plus few conditions for range detection. rest is mainly plots and colors.
There are tooltips to help you with the parameters.
I hope this will be useful to someone. If you have any ideas, feedback, or spot errors in the code, LET ME KNOW.
Stay tuned for the remaining two scripts using skittles indicators and check out my other scripts.
-ALSO:
I'm always looking for ideas for interesting indicators and strategies that I could code, so if you don't know Pinescript, just message me, and I would be glad to write your own indicator/strategy for free, obviously.
-----May the force of the market be with you, and until we meet again,
StdDev ChannelsThis script draws two sets of standard deviation channels on the price chart, providing a nuanced view of price volatility over different lengths.
The script starts by declaring a set of user-defined inputs allowing traders to customize the tool according to their individual requirements. The price input sets the source of the price data, defaulting to the closing price but customizable to use open, high, or low prices. The deviations parameter defines the width of the channels, with larger numbers resulting in wider channels. The length and length2 inputs represent the number of periods (in bars) that the script considers when calculating the regression line and standard deviation. Traders can also personalize the visual aspects of the indicator on the chart using the color, linewidth, and linestyle parameters.
Calculation of Standard Deviation:
The core of this script lies in calculating the regression line and standard deviation. This is where the InertiaAll function comes into play. This function calculates the linear regression line, which serves as the middle line of each channel. The function takes in two parameters: y (price data) and n (length for calculation). It returns an array containing the values for the regression line (InertiaTS), counter variable (x), slope of the line (a), and y-intercept (b). The standard deviation is then calculated using the built-in function ta.stdev, which measures the amount of variation or dispersion from the average.
After the calculation, the script proceeds to draw the channels. It creates two sets of lines (upper, middle, and lower) for each channel. These lines are initialized at the lowest price point on the chart (low). The coordinates for these lines get updated in the last section of the script, which runs only on the last bar on the chart (if barstate.islast). The functions line.set_xy1 and line.set_xy2 are used to adjust the starting and ending points for each line, forming the channels.
If the "full range" toggle is enabled, the script uses the maximum number of bars available on the chart to calculate the regression and standard deviation. This can give a broader perspective of the price's volatility over the entire available data range.
A Basic Strategy
The channels generated by this script may inform your trading decisions. If the price hits the upper line of a channel, it could suggest an 'overbought' condition indicating a potential selling opportunity. Conversely, if the price hits the lower line, it might signal an 'oversold' condition, suggesting a buying opportunity. The second channel, calculated over a different length, may serve to confirm these signals or identify longer-term trends.
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.
Hodrick-Prescott Channel [Loxx]Hodrick-Prescott Channel is a fast and slow moving average that moves inside a channel. Breakouts are when the fast ma crosses up over the slow ma and breakdowns are the opposite. The white moving average is the fast ma, the slow moving average is the red/green ma.
What is Hodrick–Prescott filter?
The Hodrick–Prescott filter (also known as Hodrick–Prescott decomposition) is a mathematical tool used in macroeconomics, especially in real business cycle theory, to remove the cyclical component of a time series from raw data. It is used to obtain a smoothed-curve representation of a time series, one that is more sensitive to long-term than to short-term fluctuations. The adjustment of the sensitivity of the trend to short-term fluctuations is achieved by modifying a multiplier Lambda.
The filter was popularized in the field of economics in the 1990s by economists Robert J. Hodrick and Nobel Memorial Prize winner Edward C. Prescott, though it was first proposed much earlier by E. T. Whittaker in 1923.
There are some drawbacks to use the HP filter than you can read here: en.wikipedia.org
Included
Bar coloring
Signals
Alerts
Adaptive ATR Keltner Channels [Loxx]Adaptive ATR Channels are adaptive Keltner channels. ATR is calculated using a rolling signal-to-noise ratio making this indicator flex more to changes in price volatility than the fixed Keltner Channels.
What is Average True Range (ATR)?
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.1
The true range is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
What are Keltner Channel (ATR)?
Keltner Channels are volatility-based bands that are placed on either side of an asset's price and can aid in determining the direction of a trend.
The Keltner channel uses the average-true range (ATR) or volatility, with breaks above or below the top and bottom barriers signaling a continuation.
Daily Scalping Moving AveragesThis is a technical analysis study based on the most fit leading indicators for short timeframes like EMA and SMA.
At the same time we have daily channel made from the last 2 weeks of ATR values, which will give us the daily top and bottom expected values(with 80%+ confidence)
We have 3 groups of lengths for short length, medium length and a bigger length.
At the same time we combine it with the daily vwap values .
In the end we are going to have a total of 7 indicators telling us the direction.
The way we can use it :
The max ratings that we can have are +7 for long and -7 for short
In general once we have at least 5 indicators(fast and medium ones) giving us a direction, there is a high chance that we can scalp that trend and then we can exit either when we will be at +7 or close to neutral point
At the same time is very important to be aware of the current position inside of the TOP/BOTTOM channel that we have.
For example lets assume we are at 40k on BTC and our top channel is around 41-42k while the bottom is around 38k. In this case the margin that we have for long is much smaller than for short, so we should be prepared to exit once we reach the top values and from there wait and see if there is a huge continuation or a reversal. If the top channel was hit and the market started the rebounce going downwards and the moving averages confirms it, then we have a huge advantage using the top points as a STOP LOSS and continue the short movements, giving us an amazing risk/reward ratio .
If you have any questions let me know !
Smarter MACD BandThe Smarter MACD displayed as a band instead of an oscillator. A classic MACD with average peak and dip lines. The lighter green and red horizontal lines are the average peak and dip of the entire span, respectively. The second, bolder of the two lines are the averages of the peaks and dips above and below the overall peak and dip averages. The filled in color is to help visualize these averages and possible trade setups.
Pivot Trend LevelsYou can use this indicator to detect the levels and trend.
I used the highest of the two last highest pivots and the lowest of the two last lowest pivots to calculate "max" and "min" or high level or low level.
I also calculate the average of the 4 values to reach the average line which could be a trend detector in higher lengths.
Default length is 3 but using 10 or 20 as length is really good as trending detector.
I need help to upgrade a trend detector system. please read the script for more information.
Thank you so much.
Volatility ChannelThis script is based on an idea I have had for bands that react better to crypto volatility. It calculates a Donchian Channel, SMMA-Smoothed True Range, Bollinger Bands (standard deviation), and a Keltner Channel (average true range) and averages the components to construct its bands/envelopes. This way, hopefully band touches are a more reliable indicator of a temporary bottom, and so on. Secondary coloring for strength of trend is given as a gradient based on RSI.
