Punjis Dynamic Daily EMA/SMA 5,9,21,50,100 LevelsPunjis Dynamic Daily EMA/SMA 5,9,21,50,100 Levels
Overview:
This indicator displays daily timeframe moving averages as horizontal lines extending to the right of your chart, regardless of what timeframe you're currently viewing. It includes six key moving averages: EMA 5, EMA 9, EMA 21, SMA 50, SMA 100, and SMA 200.
Key Features:
Clean Chart Design: Unlike traditional moving average lines that clutter your chart with curves across all candles, this indicator uses horizontal lines that extend only from the current price level to the right edge of your screen
Multi-Timeframe Analysis: View daily moving averages on any intraday timeframe (1min, 5min, 15min, etc.) without switching charts
Fully Customizable:
Toggle each moving average on/off independently
Adjust the period length for each MA
Customize colors for each line
Master toggle to show/hide all lines at once
Reduced Visual Noise: Horizontal lines keep your price action clean and easy to read while still providing critical support/resistance levels
Professional Layout: Perfect for traders who need to monitor multiple key levels without obscuring candlestick patterns and chart analysis
Benefits of Horizontal Lines:
Cleaner Charts: Traditional MAs draw lines through every candle, creating visual clutter. Horizontal lines only show current values, keeping your chart clean
Focus on Current Levels: What matters most is where the MAs are NOW relative to price - horizontal lines highlight this instantly
Better Price Action Visibility: See candlestick patterns, volume, and support/resistance levels clearly without MA lines crossing through them
Quick Reference: Instantly identify if price is above or below key moving averages without following curved lines across the chart
Professional Appearance: Clean, minimalist design preferred by institutional traders and technical analysts
Use Cases:
Day traders monitoring higher timeframe levels on intraday charts
Swing traders tracking daily moving averages as dynamic support/resistance
Multi-timeframe analysis without chart switching
Identifying trend direction and potential reversal zones
Clean workspace for pattern recognition and price action trading
Pesquisar nos scripts por "curve"
MA Multi-Timeframe [ChartPrime]The MA Multi-Timeframe indicator is designed to provide multi-timeframe moving averages (MAs) for better trend analysis across different periods. This tool allows traders to monitor up to four different MAs on a single chart, each coming from a selectable timeframe and type (SMA, EMA, SMMA, WMA, VWMA). The indicator helps traders gauge both short-term and long-term price trends, allowing for a clearer understanding of market dynamics.
⯁ KEY FEATURES AND HOW TO USE
⯌ Multi-Timeframe Moving Averages :
The indicator allows traders to select up to four MAs, each from different timeframes. These timeframes can be set in the input settings (e.g., Daily, Weekly, Monthly), and each moving average can be displayed with its corresponding timeframe label directly on the chart.
Example of different timeframes for MAs:
⯌ Moving Average Types :
Users can choose from several types of moving averages, including SMA, EMA, SMMA, WMA, and VWMA, making the indicator adaptable to different strategies and market conditions. This flexibility allows traders to tailor the MAs to their preference.
Example of different types of MAs:
⯌ Dashboard Display :
The indicator includes a built-in dashboard that shows each MA, its timeframe, and whether the price is currently above or below that MA. This dashboard provides a quick overview of the trend across different timeframes, allowing traders to determine whether the overall trend is up or down.
Example of trend overview via the dashboard:
⯌ Polyline Representation :
Each MA is plotted using polylines to avoid plot functions and create a curves across up to 4000 bars back, ensuring that historical data is visualized clearly for a deeper analysis of how the price interacts with these levels over time.
if barstate.islast
for i = 0 to 4000
cp.push(chart.point.from_index(bar_index , ma ))
polyline.delete(polyline.new(cp, curved = false, line_color = color, line_style = style) )
Example of polylines for moving averages:
⯌ Customization Options :
Traders can customize the length of the MAs for all timeframes using a single input. The color, style (solid, dashed, dotted) of each moving average are also customizable, giving users full control over the visual appearance of the indicator on their chart.
Example of custom MA styles:
⯁ USER INPUTS
MA Type : Select the type of moving average for each timeframe (SMA, EMA, SMMA, WMA, VWMA).
Timeframe : Choose the timeframe for each moving average (e.g., Daily, Weekly, Monthly).
MA Length : Set the length for the moving averages, which will be applied to all four MAs.
Line Style : Customize the style of each MA line (solid, dashed, or dotted).
Colors : Set the color for each MA for better visual distinction.
⯁ CONCLUSION
The MA Multi-Timeframe indicator is a versatile and powerful tool for traders looking to monitor price trends across multiple timeframes with different types of moving averages. The dashboard simplifies trend identification, while the customizable options make it easy to adapt to individual trading strategies. Whether you're analyzing short-term price movements or long-term trends, this indicator offers a comprehensive solution for tracking market direction.
D-Shape Breakout Signals [LuxAlgo]The D-Shape Breakout Signals indicator uses a unique and novel technique to provide support/resistance curves, a trailing stop loss line, and visual breakout signals from semi-circular shapes.
🔶 USAGE
D-shape is a new concept where the distance between two Swing points is used to create a semi-circle/arc, where the width is expressed as a user-defined percentage of the radius. The resulting arc can be used as a potential support/resistance as well as a source of breakouts.
Users can adjust this percentage (width of the D-shape) in the settings ( "D-Width" ), which will influence breakouts and the Stop-Loss line.
🔹 Breakouts of D-Shape
The arc of this D-shape is used for detecting breakout signals between the price and the curve. Only one breakout per D-shape can occur.
A breakout is highlighted with a colored dot, signifying its location, with a green dot being used when the top part of the arc is exceeded, and red when the bottom part of the arc is surpassed.
When the price reaches the right side of the arc without breaking the arc top/bottom, a blue-colored dot is highlighted, signaling a "Neutral Breakout".
🔹 Trailing Stop-Loss Line
The script includes a Trailing Stop-Loss line (TSL), which is only updated when a breakout of the D-Shape occurs. The TSL will return the midline of the D-Shape subject to a breakout.
The TSL can be used as a stop-loss or entry-level but can also act as a potential support/resistance level or trend visualization.
🔶 DETAILS
A D-shape will initially be colored green when a Swing Low is followed by a Swing High, and red when a Swing Low is followed by a Swing High.
A breakout of the upper side of the D-shape will always update the color to green or to red when the breakout occurs in the lower part. A Neutral Breakout will result in a blue-colored D-shape. The transparency is lowered in the event of a breakout.
In the event of a D-shape breakout, the shape will be removed when the total number of visible D-Shapes exceeds the user set "Minimum Patterns" setting. Any D-shape whose boundaries have not been exceeded (and therefore still active) will remain visible.
🔹 Trailing Stop-Loss Line
Only when a breakout occurs will the midline of the D-shape closest to the closing price potentially become the new Trailing Stop value.
The script will only consider middle lines below the closing price on an upward breakout or middle lines above the closing price when it concerns a downward breakout.
In an uptrend, with an already available green TSL, the potential new Stop-Loss value must be higher than the previous TSL value; while in a downtrend, the new TSL value must be lower.
The Stop-Loss line won't be updated when a "Neutral Breakout" occurs.
🔶 SETTINGS
Swing Length: Period used for the swing detection, with higher values returning longer-term Swing Levels.
🔹 D-Patterns
Minimum Patterns: Minimum amount of visible D-Shape patterns.
D-Width: Width of the D-Shape as a percentage of the distance between both Swing Points.
Included Swings: Include "Swing High" (followed by a Swing Low), "Swing Low" (followed by a Swing High), or "Both"
Style Historical Patterns: Show the "Arc", "Midline" or "Both" of historical patterns.
🔹 Style
Label Size/Colors
Connecting Swing Level: Shows a line connecting the first Swing Point.
Color Fill: colorfill of Trailing Stop-Loss
Savitzky-Golay Smoothing FilterThe Savitzky-Golay Filter is a polynomial smoothing filter.
This version implements 3rd degree polynomials using coefficients from Savitzky and Golay's table, specifically the coefficients for a 5-, 7-, 9-, 15- and 25-point window moving averages.
The filters are offset to the left by the number of coefficients (n-1)/2 so it smooths on top of the actual curve.
You can turn off some of the smoothing curves, as it can get cluttered displaying all at once.
Any feedback is very welcome.
Multi-Timeframe Recursive Zigzag [Trendoscope®]🎲 Welcome to the Advanced World of Zigzag Analysis
Embark on a journey through the most comprehensive and feature-rich Zigzag implementation you’ll ever encounter. Our Multi-Timeframe Recursive Zigzag Indicator is not just another tool; it's a groundbreaking advancement in technical analysis.
🎯 Key Features
Multi Time-Frame Support - One of the rare open-source Zigzag indicators with robust multi-timeframe capabilities, this feature sets our tool apart, enabling a broader and more dynamic market analysis.
Innovative Recursive Zigzag Algorithm - At its core is our unique Recursive Zigzag Algorithm, a pioneering development that powers multiple Zigzag levels, offering an intricate view of market movements. This proprietary algorithm is the backbone of our advanced pattern recognition indicators.
Sub-Waves and Micro-Waves Analysis - Dive deeper into market trends with our Sub-Waves and Micro-Waves feature. Sub-Waves reveal the interconnectedness of various Zigzag levels, while Micro-Waves offer insight into the fundamental waves at the base level.
Enhanced Indicator Tracking - Integrate and track your custom indicators or oscillators with the zigzag, capturing their values at each Zigzag level, complete with retracement ratios. This offers a comprehensive view of market dynamics.
Curved Zigzag Visualization - Experience a new way of visualizing market movements with our Curved Zigzag Display, employing Pine Script’s polyline feature for a more intuitive and visually appealing representation.
Built-in Customizable Alerts - Stay ahead with built-in alerts that can be customized via user input settings.
🎯 Practical Applications
Our Zigzag Indicator is designed with an understanding of its inherent nature - the last unconfirmed pivot that consistently repaints. This characteristic, while by design, directs its usage more towards pattern recognition rather than direct identification of market tops and bottoms. Here's how you can leverage the Zigzag Indicator:
Harmonic Patterns - Ideal for those familiar with harmonic patterns, this tool simplifies the manual spotting of complex XABCD, ABC, and ABCD patterns on charts.
Chart Patterns - Effortlessly identify patterns like Double/Triple Taps, Head and Shoulders, Inverse Head and Shoulders, and Cup and Handle patterns with enhanced clarity. Navigate through challenging patterns such as Triangles, Wedges, Flags, and Price Channels, where the Zigzag Indicator adds a layer of precision to your breakout strategy.
Elliott Wave Components - The indicator's detailed pivot highlighting aids in identifying key Elliott Wave components, enhancing your wave analysis and decision-making process.
🎲 Deep Dive into Indicator Features
Join us as we explore the intricate features of our indicator in more detail.
🎯 Multi-Timeframe Capability
Our indicator comes equipped with an input option for selecting the desired resolution. This unique feature allows users to view higher timeframe Zigzag patterns directly on their lower timeframe charts.
🎯 Recursive Multi Level Zigzag
Our advanced recursive approach creates multi-level Zigzags from lower-level data. For instance, the level 0 Zigzag forms the base, calculated from specified length and depth parameters, while level 1 Zigzag is derived using level 0 as its foundation, and so forth.
The indicator not only displays multiple Zigzag levels but also offers settings to emphasize specific levels for more detailed analysis.
🎯 Sub-Components and Micro-Components of Zigzag Wave
Sub-components within a Zigzag wave consist of the previous level's Zigzag pivots. Meanwhile, the micro-components are composed of the base level (Level 0) Zigzag pivots encapsulated within the wave.
🎯 Curved Zigzag
Experience a new perspective with our curved Zigzag display. This innovative feature utilizes the polyline curved option to automatically generate sinusoidal waves based on multiple points.
🎯 Indicator Tracking
Default indicators such as RSI, MFI, and OBV are included, alongside the ability to track one external indicator at each Zigzag pivot.
🎯 Customizable Alerts
Our indicator employs the `alert()` function for alert creation. While this means the absence of a customization text box in the alert settings, we've included a custom text area for users to create their own alert templates.
Template placeholders include:
{alertType} - type of alert. Either Confirmed Pivot Update or Last Pivot Update. Depends on the alert type selected in the inputs.
When Last Pivot Update type is selected, the alerts are triggered whenever there is a new Zigzag Pivot. This may also be a repaint of last unconfirmed pivot.
When Confirmed Pivot Update type is selected, the alerts are triggered only when a pivot becomes a confirmed pivot.
{level} - Zigzag level on which the alert is triggered.
{pivot} - Details of the last pivot or confirmed pivot including price, ratio, indicator values and ratios, subcomponent and micro-component pivots.
🎲 User Settings Overview
🎯 Zigzag and Generic Settings
This involves some generic zigzag calculation settings such as length, depth, and timeframe. And few display options such as theme, Highlight Level and Curved Zigzag. By default, zigzag calculation is done based on the latest real time bar. An option is provided to disable this and use only confirmed bars for the calculation.
Indicator Settings
Allows users to track one or more oscillators or volume indicators. Option to add any indicator via external input is provided.
🎯 Alert Settings
Has input fields required to select and customize alerts.
Polynomial Regression Channel [ChartPrime]⯁ OVERVIEW
The Polynomial Regression Channel fits price action using advanced polynomial regression, extending beyond simple linear or logarithmic models. By leveraging matrix calculations, it builds a curved regression line that adapts to swings more naturally. The channel includes extrapolated forward projections, helping traders visualize where price may gravitate in the near future. Midline color shifts reflect directional bias, while prediction ranges are marked with dashed extensions, labeled prices, and a live table for clarity.
⯁ KEY FEATURES
Polynomial Regression Core:
Uses matrix algebra to calculate a polynomial fit of customizable degree, adapting to complex, non-linear market structures.
polyreg(source, length, degree, extrapolate) =>
total = length + extrapolate
X_all = matrix.new(total, degree + 1, 0.0)
for i = 0 to total - 1
for j = 0 to degree
matrix.set(X_all, i, j, math.pow(i, j))
// y (length × 1), oldest→newest over the fit window
y = matrix.new(length, 1, 0.0)
for i = 0 to length - 1
matrix.set(y, i, 0, source )
// X_train (first `length` rows of X_all)
X_tr = matrix.new(length, degree + 1, 0.0)
for i = 0 to length - 1
for j = 0 to degree
matrix.set(X_tr, i, j, matrix.get(X_all, i, j))
// OLS via normal equations: (X'X)^(-1)b = X'y ⇒ b = (X'X)^(-1) X'y
Xt = matrix.transpose(X_tr) // X'
XtX = matrix.mult(Xt, X_tr) // (X'X)
Xty = matrix.mult(Xt, y) // X'y
XtX_inv = matrix.inv(XtX) // (X'X)^(-1)
b = matrix.mult(XtX_inv, Xty) // b = (X'X)^(-1) X'y
// Predictions for all rows (fit + extrap)
preds = matrix.mult(X_all, matrix.col(b,0))
preds
Extrapolated Future Projections:
Forward-looking range (dashed lines + circular markers) shows where the fitted polynomial suggests price may move.
Dynamic Midline Coloring:
Regression midline shifts green when slope turns upward and magenta when slope turns downward, giving instant directional context.
Channel Boundaries:
Upper and lower levels expand from the midline using a volatility-based offset, framing potential overbought and oversold conditions.
Top-Right Data Table:
A live table displays Upper, Middle, and Lower Prediction values, updating in real time for quick reference without scanning the chart.
⯁ USAGE
Use the regression midline to gauge underlying market bias; green slopes suggest continuation, magenta slopes caution for weakness.
Watch dashed extrapolated ranges as potential targets or reaction zones during upcoming sessions.
Price labels and table values act as precise reference levels for planning entries, exits, or stop placement.
Increase Degree for more curve-fitting on choppy markets, or keep it low for broader trend approximation.
Adjust Period and Extrapolate length to balance stability vs. responsiveness.
⯁ CONCLUSION
The Polynomial Regression Channel offers a mathematically advanced way to visualize price trends and anticipate future paths. With matrix-driven polynomial fitting, extrapolated projections, and integrated live labels, it combines statistical rigor with practical trading visuals — a robust upgrade over standard regression channels.
KernelFunctionsLibrary "KernelFunctions"
This library provides non-repainting kernel functions for Nadaraya-Watson estimator implementations. This allows for easy substition/comparison of different kernel functions for one another in indicators. Furthermore, kernels can easily be combined with other kernels to create newer, more customized kernels.
rationalQuadratic(_src, _lookback, _relativeWeight, startAtBar)
Rational Quadratic Kernel - An infinite sum of Gaussian Kernels of different length scales.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_relativeWeight (simple float) : Relative weighting of time frames. Smaller values resut in a more stretched out curve and larger values will result in a more wiggly curve. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel.
startAtBar (simple int)
Returns: yhat The estimated values according to the Rational Quadratic Kernel.
gaussian(_src, _lookback, startAtBar)
Gaussian Kernel - A weighted average of the source series. The weights are determined by the Radial Basis Function (RBF).
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
startAtBar (simple int)
Returns: yhat The estimated values according to the Gaussian Kernel.
periodic(_src, _lookback, _period, startAtBar)
Periodic Kernel - The periodic kernel (derived by David Mackay) allows one to model functions which repeat themselves exactly.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Periodic Kernel.
locallyPeriodic(_src, _lookback, _period, startAtBar)
Locally Periodic Kernel - The locally periodic kernel is a periodic function that slowly varies with time. It is the product of the Periodic Kernel and the Gaussian Kernel.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Locally Periodic Kernel.
Ellipse Price Action Indicator v2 (Upgraded)
This upgraded Ellipse Price Action Indicator (EPAI v2) to take high-accuracy trades.
I am explaining it as if you are looking at the chart step by step, so you will understand exactly:
-When to buy
-When to
-When to avoid
-How to read Strength Meter
-How Ellipse zones work
⭐ 1. THE BASICS — What This Indicator Actually Does
This indicator tracks:
✔ The “Elliptical Path” of price
Like a planet revolving around the Sun, price “oscillates” around a center.
The indicator detects this hidden mathematical path using:
Two Focus Points (Fast MA & Slow MA)
Curved Ellipse boundaries
Compression of price
Momentum of trend
Breakout zones
⭐ 2. UNDERSTANDING THE 3 ZONES
🔴 UPPER ZONE = Sell Zone
Price is near the upper ellipse boundary → overbought space.
🟢 LOWER ZONE = Buy Zone
Price near lower ellipse boundary → oversold space.
🔵 CENTRAL ZONE = No Trade Zone
Price swinging inside the ellipse center → noise.
Only trade in UPPER or LOWER zones.
Never in the central zone.
⭐ 3. THE MOST IMPORTANT PART — Strength Meter v2
Strength Meter v2 (0 to 100%) is the core filter.
✔ Above 70% → High winning probability (take trade)
✔ 60–70% → Medium probability (trade if confident)
❌ Below 60% → Avoid trade
Strength combines:
Ellipse compression
Momentum slope
Price position curve
Eccentricity
Trend direction
This alone removes 70% bad trades.
⭐ 4. BUY SETUP (Exact Rules)
You get a BUY only if all conditions match:
① Price goes to lower ellipse zone
② Compression is ON (ellipse is tight)
③ Momentum slope direction = UP
④ Focus Lines Cross Bullish (Fast > Slow)
⑤ Strength v2 ≥ your threshold (default 60%)
⑥ A BUY signal prints (triangle UP)
When these align →
🟢 BUY with high accuracy
Best Accuracy Buy is:
Price in lower zone
Strength ≥ 0.75
Slope UP
Ellipse compressed
⭐ 5. SELL SETUP (Exact Rules)
Same logic reversed:
① Price in upper ellipse zone
② Compression ON
③ Momentum slope DOWN
④ Focus Lines cross bearish (Fast < Slow)
⑤ Strength v2 ≥ threshold
⑥ SELL signal prints (triangle DOWN)
This means:
🔴 SELL with high accuracy
Best Accuracy Sell is:
Price in upper zone
Strength ≥ 0.75
Slope DOWN
Ellipse compressed
⭐ 6. BREAKOUT TRADES (Optional but powerful)
When price breaks above/below ellipse:
🔸 Upper Breakout → SELL (if strength strong)
🔸 Lower Breakout → BUY (if strength strong)
Breakout signals are marked by orange arrows.
Breakouts are taken only if:
Strength v2 > 50%
Slope supports breakout
Compression exists before breakout
Breakout trades catch trend continuation.
⭐ 7. HOW TO CONFIRM A STRONG TRADE
Look at the table on the chart:
✔ Strength v2 ≥ 70% (GREEN)
✔ Compression = GREEN
✔ Slope direction = UP (for buy) or DOWN (for sell)
✔ Zone = LOWER or UPPER
✔ Eccentricity = LOW (<0.5 means smooth trend)
If these line up →
⭐ High-probability entry.
⭐ 8. WHEN YOU SHOULD NOT TRADE
❌ If price is in Central Zone
❌ Strength < 60
❌ No compression detected
❌ Slope is flat or against direction
❌ Only one condition is matching
❌ Eccentricity is too large
(Big ellipse = unpredictable swings)
⭐ 9. What Is the Accuracy Level?
In trending markets → 75% to 85% accuracy
In ranging markets → 50% (use compression filter to avoid)
The indicator is designed to avoid bad market conditions automatically.
⭐ 10. BEST TIMEFRAMES
✔ 5m, 15m, 1H → Intraday
✔ 4H, 1D → Swing Trading
✔ NOT recommended below 1m timeframe
⭐ SUMMARY (EASY VERSION)
🟢 BUY:
Lower zone + compression + bullish slope + strong focus cross + strength ≥ 60
🔴 SELL:
Upper zone + compression + bearish slope + strong focus cross + strength ≥ 60
🟠 Breakout:
Upper/lower breakout + strength ≥ 50
🔵 Avoid:
Central zone or weak strength
Log Regression Channel (Dezza Fixed v2)This custom indicator builds a curved Logarithmic Regression Channel designed for long-term Bitcoin and macro asset analysis. It performs a linear regression on the logarithm of price to estimate the market’s fair-value growth curve, then converts that back into price space to form upper and lower deviation bands.
It helps identify where price sits relative to its long-term exponential trend — showing potential overvaluation (upper band) or undervaluation (lower band) zones.
Best used on weekly or monthly charts to visualise market cycles and fair-value reversion. Adjustable inputs let you control lookback length, band width, and midline visibility.
Log Regression Channel (Dezza)This custom indicator builds a curved Logarithmic Regression Channel designed for long-term Bitcoin and macro asset analysis. It performs a linear regression on the logarithm of price to estimate the market’s fair-value growth curve, then converts that back into price space to form upper and lower deviation bands.
It helps identify where price sits relative to its long-term exponential trend — showing potential overvaluation (upper band) or undervaluation (lower band) zones.
Best used on weekly or monthly charts to visualise market cycles and fair-value reversion. Adjustable inputs let you control lookback length, band width, and midline visibility.
Volume Weighted Linear Regression BandThe Volume-Weighted Linear Regression Band (VWLRBd) is a volatility channel that uses a Linear Regression line as its dynamic baseline. Its primary feature is the decomposition of total volatility into two distinct components, visualized as layered bands.
Key Features:
Volatility Decomposition: The indicator separates volatility based on the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): The indicator functions as a standard (Volume-Weighted) Linear Regression Channel. It plots a single set of bands based on the standard deviation of the residuals (the error between the Source price and the regression line).
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used for the regression). This mode displays two sets of bands:
Inner Bands: Show only the contribution of the 'residual' (trend noise) volatility, calculated proportionally.
Outer Bands: Show the total volatility (the sum of residual and within-bar components).
Regression Baseline (Linear / Exponential): The central line is a (Volume-Weighted) Linear Regression curve. An optional 'Normalize' mode performs all calculations in logarithmic space, transforming the baseline into an Exponential Regression Curve and the bands into constant percentage deviations, suitable for analyzing growth assets.
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the calculation of both the regression baseline and the volatility decomposition, giving more influence to high-participation bars.
Multi-Timeframe (MTF) Engine: The indicator includes an MTF conversion block. When a Higher Timeframe (HTF) is selected, advanced options become available: Fill Gaps handles data gaps, and Wait for timeframe to close prevents repainting by ensuring the indicator only updates when the HTF bar closes.
Integrated Alerts: Includes a full set of built-in alerts for the source price crossing over or under the central regression line and the outermost calculated volatility band.
DISCLAIM_
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Quantum Flux Universal Strategy Summary in one paragraph
Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version.
Scope and intent
• Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto
• Timeframes. One minute to daily
• Default demo used in the publication. QQQ on one hour
• Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps.
• What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise.
• Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state.
• Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols.
Method overview in plain language
The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction.
Base measures
• Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale.
• Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop.
• Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves.
Components
• Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner.
• Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends.
• Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response.
• Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance.
• Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot.
Fusion rule
• Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent.
• The blend power input scales the driver mix. Zero means fixed spans. One means full driver control.
• Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes.
Signal rule
• Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one.
• Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one.
• When polarity flips from plus to minus, the strategy closes any long and enters a short.
• When flux crosses above the guide, the strategy closes any short.
What you will see on the chart
• White polarity plot around the zero line
• A dotted reference line at zero named Zen
• Green background tint for positive polarity and red background tint for negative polarity
• Strategy long and short markers placed by the TradingView engine at entry and at close conditions
• No table in this version to keep the visual clean and portable
Inputs with guidance
Setup
• Price source. Default ohlc4. Stable for noisy symbols.
• Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive.
• Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price.
Logic
• Guide span. Typical range 4 to 12. A small guide smooths without eating turns.
• Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing.
• Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work.
• Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise.
• Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve.
• Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak.
• Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong.
• Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline.
• Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols.
• Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs.
Filters
• Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends.
• Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping.
• Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version.
Alerts
• This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows.
Strategy has been currently adapted for the QQQ asset with 30/60min timeframe.
For other assets may require new optimization
Properties visible in this publication
• Initial capital 25000
• Base currency Default
• Default order size method percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Honest limitations and failure modes
• Past results do not guarantee future outcomes
• Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency
• Gap heavy symbols may benefit from the MAD Z normalization
• Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context
• Session time is the exchange time of the chart
• If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference
Open source reuse and credits
• None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank
• Method and fusion are original in construction and disclosure
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Strategy add on block
Strategy notice
Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used.
Entries and exits
• Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero
• Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short
• Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed
• Tie handling. Not applicable in this version because there are no fixed stops or targets
Position sizing
• Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice
Properties used on the published chart
• Initial capital 25000
• Base currency Default
• Default order size percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Dataset and sample size
• Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour
• Trade count in sample 324 on the example chart
Release notes template for future updates
Version 1.1.
• Add alertcondition lines for long, short, and exit short
• Add optional table with component readouts
• Add optional stop model with a distance unit expressed as ATR or a percent of price
Notes. Backward compatibility Yes. Inputs migrated Yes.
Sweep2Trade Pro [CHE]Sweep2Trade Pro \ — Liquidity Sweep → Trend → Confirmation
Sweep2Trade Pro \ helps you catch high-probability reversals or continuations that start with a liquidity sweep, align with the T3 trend, and finalize with a structure confirmation (BOS). It’s designed to reduce noise, time your entries, and keep you out of weak, chop-driven signals.
What’s a “sweep”?
A liquidity sweep happens when price briefly breaks a prior swing high/low (where many stops sit), triggers those stops, and then snaps back. This “stop-hunt” creates liquidity for bigger players and often precedes a sharp move in the opposite direction if the break fails, or fuels continuation if structure actually shifts.
What’s a BOS (Break of Structure)?
A BOS is a price action event where the market takes out a recent swing level in the trend’s direction, signaling continuation and confirming that structure has shifted (bullish BOS through a recent swing high, bearish BOS through a recent swing low).
How the indicator works (at a glance)
1. Regime Filter (T3 + R²)
T3 Moving Average: A smoother, faster-responding moving average that aims to reduce lag while filtering noise, so trend direction changes are clearer.
R² (Coefficient of Determination): Measures how “linear” the recent price path is (0→1). Higher values = stronger, cleaner trend; lower values = more chop. Used here to allow trades only when trend quality exceeds a user-set threshold.
2. Sweep Detection
Bullish sweep: price pokes below a prior swing low and closes back above it.
Bearish sweep: price pokes above a prior swing high and closes back below it.
Lookback length is configurable.
3. Sequence Lock (built-in FSM)
The script manages state in phases so you don’t jump the gun:
Phase 1: Sweep detected → wait for T3 to turn in the corresponding direction.
Phase 2: T3 direction confirmed → show “SWEEP OK” and wait for final confirmation.
Trade Signal: Only fires if confirmation arrives before a timeout.
4. Confirmation Layer
BOS via wick or close (you choose),
Strong close toward the signal (top/bottom quartile of the candle),
Optional “close above/below T3” condition.
These checks help avoid weak sweeps that immediately fade.
5. Alerts & Visuals
“SWEEP OK” markers show when the sweep + T3 direction align.
Final BUY/SELL arrows appear only when the confirmation layer passes.
Ready-made alert conditions for automation.
What you can do with it
Time reversals after sweeps: Enter when a stop-hunt fades and structure confirms.
Ride continuations: Use BOS with the T3 trend to pyramid or re-enter with structure on your side.
Filter chop: Let R² gate entries to periods with cleaner directional drift.
Automate: Use the included alerts with your platform or webhook setup.
Inputs (key settings)
Regime Filter
T3 Length / Volume Factor: Controls smoothness and responsiveness. Smaller length → faster, more sensitive; higher volume factor → smoother curve.
R² Lookback & Threshold: Length of the linear fit window and the minimum “trend quality” required. Higher thresholds mean fewer, cleaner signals.
Sweep / Sequence
Swing Lookback: How far back to define the “reference” high/low for sweeps.
Timeout: Maximum bars allowed between phases to keep signals fresh.
Restart timeout on Phase 2: Optional safety so entries don’t go stale.
Confirmation
BOS Lookback: Micro-pivot window for structure breaks.
Wick vs Close BOS: Conservative traders may prefer close.
Require close above/below T3: Tightens confirmation with trend alignment.
Practical guide (quick start)
1. Timeframe & markets: Works across majors, indices, and crypto. Start with 5m–1h intraday or 1h–4h swing; adjust R² threshold upward on noisier pairs.
2. Entry recipe (Long):
Bullish sweep of a prior low → T3 turns up → BOS/strong close.
Optional: enable “close above T3” for extra confirmation.
3. Entry recipe (Short): Mirror the above.
4. Stops: Common choices are just beyond the sweep wick (tighter) or past the BOS invalidation (safer).
5. Targets: Previous structural levels, measured move, or a T3 trail (exit when price closes back through T3).
6. Avoid low-quality contexts: If R² is very low, market is likely ranging erratically—skip or widen filters.
Tips & best practices
Context first: The same sweep means different things in a strong trend vs. flat regime; that’s why the T3+R² filter exists.
BOS choice: Wick-based BOS is earlier but noisier; close-based BOS is slower but cleaner. Tune per market.
Backtest -> Forward test: Validate settings per symbol/timeframe; then paper trade before going live.
Risk: Fixed fractional risk with asymmetric R\:R (e.g., 1:1.5–1:3) generally performs better than “all-in” discretionary sizing.
Behind the scenes (for the curious)
T3 is a multi-stage EMA construction that produces a smooth curve with reduced lag versus simple/standard EMAs.
R² is the square of correlation (0–1). Here it’s used as a moving gauge of how well price aligns to a linear path—our “trend quality” dial.
Stop-hunts / sweeps are a recognized microstructure phenomenon where clustered stops provide the liquidity that fuels the next move.
Disclaimer
No indicator guarantees profits. Sweep2Trade Pro \ is a decision aid; always combine with solid risk management and your own judgment. Backtest, forward test, and size responsibly.
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Enhance your trading precision and confidence 🚀
Happy trading
Chervolino
Transfer Function Filter [theUltimator5]The Transfer Function Filter is an engineering style approach to transform the price action on a chart into a frequency, then filter out unwanted signals using Butterworth-style filter approach.
This indicator allows you to analyze market structure by isolating or removing different frequency components of price movement—similar to how engineers filter signals in control systems and electrical circuits.
🔎 Features
Four Filter Types
1) Low Pass Filter – Smooths price data, highlighting long-term trends while filtering out short-term noise. This filter acts similar to an EMA, removing noisy signals, resulting in a smooth curve that follows the price of the stock relative to the filter cutoff settings.
Real world application for low pass filter - Used in power supplies to provide a clean, stable power level.
2) High Pass Filter – Removes slow-moving trends to emphasize short-term volatility and rapid fluctuations. The high pass filter removes the "DC" level of the chart, removing the average price moves and only outputting volatility.
Real world application for high pass filter - Used in audio equalizers to remove low-frequency noise (like rumble) while allowing higher frequencies to pass through, improving sound clarity.
3) Band Pass Filter – Allows signals to plot only within a band of bar ranges. This filter removes the low pass "DC" level and the high pass "high frequency noise spikes" and shows a signal that is effectively a smoothed volatility curve. This acts like a moving average for volatility.
Real world application for band pass filter - Radio stations only allow certain frequency bands so you can change your radio channel by switching which frequency band your filter is set to.
4) Band Stop Filter – Suppresses specific frequency bands (cycles between two cutoffs). This filter allows through the base price moving average, but keeps the high frequency volatility spikes. It allows you to filter out specific time interval price action.
Real world application for band stop filter - If there is prominent frequency signal in the area which can cause unnecessary noise in your system, a band stop filter can cancel out just that frequency so you get everything else
Configurable Parameters
• Cutoff Periods – Define the cycle lengths (in bars) to filter. This is a bit counter-intuitive with the numbering since the higher the bar count on the low-pass filter, the lower the frequency cutoff is. The opposite holds true for the high pass filter.
• Filter Order – Adjust steepness and responsiveness (higher order = sharper filtering, but with more delay).
• Overlay Option – Display Low Pass & Band Stop outputs directly on the price chart, or in a separate pane. This is enabled by default, plotting the filters that mimic moving averages directly onto the chart.
• Source Selection – Apply filters to close, open, high, low, or custom sources.
Histograms for Comparison
• BS–LP Histogram – Shows distance between Band Stop and Low Pass filters.
• BP–HP Histogram – Highlights differences between Band Pass and High Pass filters.
Histograms give the visualization of a pseudo-MACD style indicator
Visual & Informational Aids
• Customizable colors for each filter line.
• Optional zero-line for histogram reference.
• On-chart info table summarizing active filters, cutoff settings, histograms, and filter order.
📊 Use Cases
Trend Detection – Use the Low Pass filter to smooth noise and follow underlying market direction.
Volatility & Cycle Analysis – Apply High Pass or Band Pass to capture shorter-term patterns.
Noise Suppression – Deploy Band Stop to remove specific choppy frequencies.
Momentum Insight – Watch the histograms to spot divergences and relative filter strength.
Stochastic SuperTrend [BigBeluga]🔵 OVERVIEW
A hybrid momentum-trend tool that combines Stochastic RSI with SuperTrend logic to deliver clean directional signals based on momentum turns.
Stochastic SuperTrend is a straightforward yet powerful oscillator overlay designed to highlight turning points in momentum with high clarity. It overlays a SuperTrend-style envelope onto the Stochastic RSI, generating intuitive up/down signals when a momentum shift occurs across the neutral 50 level. Built for traders who appreciate simplicity without sacrificing reliability.
🔵 CONCEPTS
Stochastic RSI: Measures momentum by applying stochastic calculations to the RSI curve instead of raw price.
SuperTrend Bands: Dynamic upper/lower bands are drawn around the smoothed Stoch RSI line using a user-defined multiplier.
Momentum Direction: Trend flips when the smoothed Stoch RSI crosses above/below the calculated bands.
Neutral Bias Filter: Directional arrows only appear when momentum turns above or below the central 50 level—adding confluence.
🔵 FEATURES
Trend Detection on Oscillator: Applies SuperTrend logic directly to the Stoch RSI curve.
Clean Entry Signals:
→ 🢁 arrow printed when trend flips bullish below 50 (bottom reversals).
→ 🢃 arrow printed when trend flips bearish above 50 (top reversals).
Custom Multiplier: Adjust sensitivity of SuperTrend band spacing around the oscillator.
Neutral Zone Highlight: Visual zone between 0–50 (green) and 50–100 (red) for quick momentum polarity reference.
Toggle SuperTrend Line: Option to show/hide the SuperTrend trail on the Stoch RSI.
🔵 HOW TO USE
Use 🢁 signals for potential bottom reversals when momentum flips bullish from oversold regions.
Use 🢃 signals for potential top reversals when momentum flips bearish from overbought areas.
Combine with price-based SuperTrend or support/resistance zones for confluence.
Suitable for scalping, swing trading, or momentum filtering across all timeframes.
🔵 CONCLUSION
Stochastic SuperTrend is a simple yet refined tool that captures clean momentum shifts with directional clarity. Whether you're identifying reversals, filtering entries, or spotting exhaustion in a trend, this oscillator overlay delivers just what you need— no clutter, just clean momentum structure.
Exponential Trend [AlgoAlpha]OVERVIEW
This script plots an adaptive exponential trend system that initiates from a dynamic anchor and accelerates based on time and direction. Unlike standard moving averages or trailing stops, the trend line here doesn't follow price directly—it expands exponentially from a pivot determined by a modified Supertrend logic. The result is a non-linear trend curve that starts at a specific price level and accelerates outward, allowing traders to visually assess trend strength, persistence, and early-stage reversal points through both base and volatility-adjusted extensions.
CONCEPTS
This indicator builds on the idea that trend-following tools often need dynamic, non-static expansion to reflect real market behavior. It uses a simplified Supertrend mechanism to define directional context and anchor levels, then applies an exponential growth function to simulate trend acceleration over time. The exponential growth is unidirectional and resets only when the direction flips, preserving trend memory. This method helps avoid whipsaws and adds time-weighted confirmation to trends. A volatility buffer—derived from ATR and modifiable by a width multiplier—adds a second layer to indicate zones of risk around the main trend path.
FEATURES
Exponential Trend Logic : Once a directional anchor is set, the base trend line accelerates using an exponential formula tied to elapsed bars, making the trend stronger the longer it persists.
Volatility-Adjusted Extension : A secondary band is plotted above or below the base trend line, widened by ATR to visualize volatility zones, act as soft stop regions or as a better entry point (Dynamic Support/Resistance).
Color-Coded Visualization : Clear green/red base and extension lines with shaded fills indicate trend direction and confidence levels.
Signal Markers & Alerts : Triangle markers indicate confirmed trend reversals. Built-in alerts notify users of bullish or bearish direction changes in real-time.
USAGE
Use this script to identify strong trends early, visually measure their momentum over time, and determine safe areas for entries or exits. Start by adjusting the *Exponential Rate* to control how quickly the trend expands—the higher the rate, the more aggressive the curve. The *Initial Distance* sets how far the anchor band is placed from price initially, helping filter out noise. Increase the *Width Multiplier* to widen the volatility zone for more conservative entries or exits. When the price crosses above or below the base line, a new trend is assumed and the exponential projection restarts from the new anchor. The base trend and its extension both shift over time, but only reset on a confirmed reversal. This makes the tool especially useful for momentum continuation setups or trailing stop logic in trending markets.
Earnings Expansion ProjectionThis indicator has no counterpart in the platform and is a professional-grade earnings visualization tool that plots EPS expansion directly on your charts, inspired by institutional-level technical analysis platforms.
The indicator creates a distinctive earnings expansion projection curve that can be a leading indicator of price direction moves.
Key features:
Clean, institutional-style, EPS-expansion projection line overlaid on price action
Visual earnings surprise indicators with beat/miss multipliers
Dashboard for rapid fundamental assessment including the stocks win rate on beatings / missing earnings historically and other fundamental information not readily available on Tradingview
What is it doing?
It collects all earnings results available and will interpolate the numbers so that we see earnings expansion as a curve.
The video below describes usage
Note: Valid on the weekly time-frame only.
GannLSVZO Indicator [Algo Alert]The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Gann Laplace Smoothed Volume Zone Oscillator GannLSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the upgraded Discrete Fourier Transform, the Laplace Stieltjes Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Laplace with Gann Swing Entries and Exits (orange X) and with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
ORIGINALITY & USFULLNESS:
Personal combination of Gann swings and Laplace Stieltjes Transform of a price which results in less noise Volume Zone Oscillator.
The Laplace Stieltjes Transform is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
The Gann swings and the Gan swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Laplace Stieltjes Transform approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Laplace Stieltjes Transform (FLT) and the innovative Double Discrete Fourier Transform (DTF32) soothed price series to suit your analytical needs.
Use dynamic calculation of Laplace coefficient or the static one. You may modify those inputs and Strategy entries with Gann swings.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Fine-tune Inputs: Gann + Laplace Smooth Volume Zone OscillatorUse this Strategy to Fine-tune inputs for the GannLSVZ0 Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Gann Laplace Smoothed Volume Zone Oscillator GannLSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the upgraded Discrete Fourier Transform, the Laplace Stieltjes Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Laplace with Gann Swing Entries and with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
When Indicator/Strategy returns 0 or natural trend, Strategy Closes All it's positions.
ORIGINALITY & USFULLNESS:
Personal combination of Gann swings and Laplace Stieltjes Transform of a price which results in less noise Volume Zone Oscillator.
The Laplace Stieltjes Transform is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
The Gann swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Laplace Stieltjes Transform approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Laplace Stieltjes Transform (FLT) and the innovative Double Discrete Fourier Transform (DTF32) soothed price series to suit your analytical needs.
Use dynamic calculation of Laplace coefficient or the static one. You may modify those inputs and Strategy entries with Gann swings.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Fine-tune Inputs: Fourier Smoothed Volume zone oscillator WFSVZ0Use this Strategy to Fine-tune inputs for the (W&)FSVZ0 Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Wavelet & Fourier Smoothed Volume Zone Oscillator (W&)FSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the Discrete Fourier Transform . Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Wavalet and Fourier aproximation with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
When I ndicator/Strategy returns 0 or natural trend , Strategy Closes All it's positions.
ORIGINALITY & USFULLNESS:
Personal combination of Fourier and Wavalet aproximation of a price which results in less noise Volume Zone Oscillator.
The Wavelet Transform is a powerful mathematical tool for signal analysis, particularly effective in analyzing signals with varying frequency or non-stationary characteristics. It dissects a signal into wavelets, small waves with varying frequency and limited duration, providing a multi-resolution analysis. This approach captures both frequency and location information, making it especially useful for detecting changes or anomalies in complex signals.
The Discrete Fourier Transform (DFT) is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
In the next Image you can see that trend is negative on 4h, negative on 12h and positive on 1D. That means trend is negative.
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Wavelet approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Fourier Transform (FFT) , the innovative Double Discrete Fourier Transform (DTF32) and Wavelet soothed Fourier soothed price series to suit your analytical needs.
Image of Wavelet transform with FAST settings, Double Fourier transform with FAST settings. Improved noice reduction with SLOW settings, and standard FSVZO with SLOW settings:
Fast setting are setting by default:
VZO length = 2
NoiceR max Length = 2
Slow settings are:
VZO length = 5 or 7
NoiceR max Length = 8
As you can see fast setting are more volatile. I suggest averaging fast setting on 4h 12h 1d 2d 3d 4d W and M Timeframe to get a clear view on market trend.
What if I want long only when VZO is rising and above 15 not 0?
You have set Setting VzoDifference to 15. That reduces the number of trend changes.
Example of W&FSVZO with VzoDifference 15 than 0:
VZO crossed 0 line but not 15 line and that's why Indicator returns 0 in one case an 1 in another.
What is Smooth length setting?
A way of calculating Bullish or Bearish (W&)FSVZO .
If smooth length is 2 the trend is rising if:
rising = VZO > ta.ema(VZO, 2)
Meaning that we check if VZO is higher that exponential average of the last 2 elements.
If smooth length is 1 the trend is rising if:
rising = VZO_ > VZO_
Use this Strategy to fine-tune inputs for the (W&)FSVZO Indicator.
(Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data)
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame . When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame . I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Kernels©2024, GoemonYae; copied from @jdehorty's "KernelFunctions" on 2024-03-09 to ensure future dependency compatibility. Will also add more functions to this script.
Library "KernelFunctions"
This library provides non-repainting kernel functions for Nadaraya-Watson estimator implementations. This allows for easy substition/comparison of different kernel functions for one another in indicators. Furthermore, kernels can easily be combined with other kernels to create newer, more customized kernels.
rationalQuadratic(_src, _lookback, _relativeWeight, startAtBar)
Rational Quadratic Kernel - An infinite sum of Gaussian Kernels of different length scales.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_relativeWeight (simple float) : Relative weighting of time frames. Smaller values resut in a more stretched out curve and larger values will result in a more wiggly curve. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel.
startAtBar (simple int)
Returns: yhat The estimated values according to the Rational Quadratic Kernel.
gaussian(_src, _lookback, startAtBar)
Gaussian Kernel - A weighted average of the source series. The weights are determined by the Radial Basis Function (RBF).
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
startAtBar (simple int)
Returns: yhat The estimated values according to the Gaussian Kernel.
periodic(_src, _lookback, _period, startAtBar)
Periodic Kernel - The periodic kernel (derived by David Mackay) allows one to model functions which repeat themselves exactly.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Periodic Kernel.
locallyPeriodic(_src, _lookback, _period, startAtBar)
Locally Periodic Kernel - The locally periodic kernel is a periodic function that slowly varies with time. It is the product of the Periodic Kernel and the Gaussian Kernel.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Locally Periodic Kernel.
Wavelet & Fourier Smoothed Volume zone oscillator (W&)FSVZO Indicator id:
USER;e7a774913c1242c3b1354334a8ea0f3c
(only relevant to those that use API requests)
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Wavelet & Fourier Smoothed Volume Zone Oscillator (W&)FSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the Discrete Fourier Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Wavalet and Fourier aproximation with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in natural trend.
ORIGINALITY & USFULLNESS:
Personal combination of Fourier and Wavalet aproximation of a price which results in less noise Volume Zone Oscillator.
The Wavelet Transform is a powerful mathematical tool for signal analysis, particularly effective in analyzing signals with varying frequency or non-stationary characteristics. It dissects a signal into wavelets, small waves with varying frequency and limited duration, providing a multi-resolution analysis. This approach captures both frequency and location information, making it especially useful for detecting changes or anomalies in complex signals.
The Discrete Fourier Transform (DFT) is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
In the next Image you can see that trend is positive on 4h, neutral on 12h and positive on 1D. That means trend is positive.
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Wavelet approximation of a close price are taken from aprox library.
Key Features:
You can tailor the indicator to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Fourier Transform (FFT), the innovative Double Discrete Fourier Transform (DTF32) and Wavelet soothed Fourier soothed price series to suit your analytical needs.
Image of Wavelet transform with FAST settings, Double Fourier transform with FAST settings. Improved noice reduction with SLOW settings, and standard FSVZO with SLOW settings:
Fast setting are setting by default:
VZO length = 2
NoiceR max Length = 2
Slow settings are:
VZO length = 5 or 7
NoiceR max Length = 8
As you can see fast setting are more volatile. I suggest averaging fast setting on 4h 12h 1d 2d 3d 4d W and M Timeframe to get a clear view on market trend.
What if I want long only when VZO is rising and above 15 not 0?
You have set Setting VzoDifference to 15. That reduces the number of trend changes.
Example of W&FSVZO with VzoDifference 15 than 0:
VZO crossed 0 line but not 15 line and that's why Indicator returns 0 in one case an 1 in another.
What is Smooth length setting?
A way of calculating Bullish or Bearish FSVZO.
If smooth length is 2 the trend is rising if:
rising = VZO > ta.ema(VZO, 2)
Meaning that we check if VZO is higher that exponential average of the last 2 elements.
If smooth length is 1 the trend is rising if:
rising = VZO_ > VZO_
Rising is boolean value, meaning TRUE if rising and FALSE if falling.
Mathematical equations presented in Pinescript:
Fourier of the real (x axis) discrete:
x_0 = array.get(x, 0) + array.get(x, 1) + array.get(x, 2)
x_1 = array.get(x, 0) + array.get(x, 1) * math.cos( -2 * math.pi * _dir / 3 ) - array.get(y, 1) * math.sin( -2 * math.pi * _dir / 3 ) + array.get(x, 2) * math.cos( -4 * math.pi * _dir / 3 ) - array.get(y, 2) * math.sin( -4 * math.pi * _dir / 3 )
x_2 = array.get(x, 0) + array.get(x, 1) * math.cos( -4 * math.pi * _dir / 3 ) - array.get(y, 1) * math.sin( -4 * math.pi * _dir / 3 ) + array.get(x, 2) * math.cos( -8 * math.pi * _dir / 3 ) - array.get(y, 2) * math.sin( -8 * math.pi * _dir / 3 )
Euler's Noice reduction with both close and Discrete Furrier approximated price.
w = (dft1*src - dft1 *src ) / math.sqrt(math.pow(math.abs(src- src ),2) + math.pow(math.abs(dft1 - dft1 ),2))
filt := na(filt ) ? 0 : c1 * (w*dft1 + nz(w *dft1 )) / 2.0 /math.abs(dft1 -dft1 ) + c2 * nz(filt ) - c3 * nz(filt )
Usecase:
First option:
Select the preferred version of DFT and noise reduction settings based on your analysis requirements.
Leverage the script to identify Bullish and Bearish trends, shown with green and red triangle.
Combine Different Timeframes to accurately determine market trend.
Second option:
Pull the data with API sockets to automate your trading journey.
plot(close, title="ClosePrice", display=display.status_line)
plot(open, title="OpenPrice", display=display.status_line)
plot(greencon ? 1 : redcon ? -1 : 0, title="position", display=display.status_line)
Use ClosePrice, OpenPrice and "position" titles to easily read and backtest your strategy utilising more than 1 Time Frame.
Indicator id:
USER;e7a774913c1242c3b1354334a8ea0f3c
(only relevant to those that use API requests)
Relative Daily Change% by SUMIT
"Relative Daily Change%" Indicator (RDC)
The "Relative Daily Change%" indicator compares a stock's average daily price change percentage over the last 200 days with a chosen index.
It plots a colored curve. If the stock's change% is higher than the index, the curve is green, indicating it's doing better. Red means the stock is under-performing.
This indicator is designed to compare the performance of a stock with specific index (as selected) for last 200 candles.
I use this during a breakout to see whether the stock is performing well with comparison to it`s index. As I marked in the chart there was a range zone (red box), we got a breakout with good volume and it is also sustaining above 50 and 200 EMA, the RDC color is also in green so as per my indicator it is performing well. This is how I do fine-tuning of my analysis for a breakout strategy.
You can select Index from the list available in input
**Line Color Green = Avg Change% per day of the stock is more than the Selected Index
**Line Color White = Avg Change% per day of the stock is less than the Selected Index
If you want details of stocks for all index you can ask for it.
Disclaimer : **This is for educational purpose only. It is not any kind of trade recommendation/tips.
