SUPERTREND RIBBONsupertrend ribbon
supertrend ribbon is a confirmed trend ribbon built from multiple supertrend bands. it is designed to show a clean, stable, and readable market direction directly on the chart.
instead of allowing each band to change color separately, the ribbon uses one master trend state. this keeps the full ribbon in one confirmed color and helps avoid visual fragmentation, false flips, and noisy mid-trend breaks.
the goal is simple: show whether the market is in a confirmed bullish or bearish trend, while keeping the chart clean and easy to read.
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main concept
the indicator uses 8 supertrend bands with different factors.
each band can be bullish or bearish.
the script counts how many bands are aligned in the same direction.
when enough bands confirm a new direction, the full ribbon changes trend.
this creates a more stable trend filter than a single supertrend line, because the ribbon does not flip on every small price movement.
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what the indicator shows
trend ribbon
the ribbon shows the dominant trend state.
green means confirmed bullish trend.
red means confirmed bearish trend.
band lines
the internal band lines can be displayed to see the full structure of the ribbon.
ribbon fill
the fill between the bands makes the trend easier to read visually.
core line
the core line gives a fast reference for the main trend path.
confirmed flip markers
markers appear only when a trend flip is confirmed.
trend background tint
a soft background color can be enabled to show the current trend regime.
dashboard
the dashboard shows the current trend, the number of aligned bands, flip requirements, fast core direction, and early long / short validity.
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inputs guide
atr period
sets the atr period used by the supertrend bands.
a lower value makes the ribbon more reactive.
a higher value makes the ribbon smoother and more stable.
base factor
sets the starting supertrend factor.
a lower value keeps the ribbon closer to price.
a higher value makes the ribbon wider and more filtering.
factor step
sets the spacing between the 8 supertrend bands.
a lower value makes the bands tighter.
a higher value makes the ribbon wider.
bands to confirm a flip
sets how many bands must confirm a new direction before the ribbon changes color.
a higher value reduces false flips.
a lower value makes the ribbon faster.
confirm for n bars
sets how many bars the confirmation condition must remain valid before the trend flips.
1 is faster.
2 or 3 is stricter and can reduce whipsaws.
show band lines
shows or hides the internal ribbon lines.
show ribbon fill
shows or hides the fill between the bands.
core glow
enables a glow effect around the core line.
show core line
shows or hides the main core line.
show confirmed flip markers
shows or hides confirmed trend flip markers.
trend background tint
enables or disables the soft trend background.
show dashboard
shows or hides the dashboard.
dashboard position
sets the dashboard position on the chart.
bull
sets the bullish trend color.
bear
sets the bearish trend color.
accent / transition
sets the accent color used for dashboard and transition information.
neutral
sets the neutral text and information color.
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how to use the indicator
the ribbon is best used as a trend filter.
when the ribbon is green, the market is in a confirmed bullish trend.
in this condition, long setups have priority.
when the ribbon is red, the market is in a confirmed bearish trend.
in this condition, short setups have priority.
the ribbon should not be used as a standalone entry signal.
its main purpose is to help avoid trading against the dominant trend.
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beginner tutorial
1. add the indicator to the chart.
2. start with the default settings.
3. look at the ribbon color.
4. if the ribbon is green, focus mainly on long opportunities.
5. if the ribbon is red, focus mainly on short opportunities.
6. avoid buying when the ribbon is red.
7. avoid selling when the ribbon is green.
8. use confirmed flip markers to identify confirmed trend changes.
9. use the dashboard to check how many bands are aligned.
10. combine the ribbon with market structure, volume, support and resistance, order blocks, liquidity zones, and proper risk management.
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simple usage example
if price is above the ribbon and the ribbon is green, the market is in a bullish trend.
a trader can wait for price to pull back toward the ribbon, then look for a bullish reaction before considering a long setup.
if price is below the ribbon and the ribbon is red, the market is in a bearish trend.
a trader can wait for price to pull back toward the ribbon, then look for a bearish rejection before considering a short setup.
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order block filter example
a bullish order block is stronger when the ribbon is green.
a bearish order block is stronger when the ribbon is red.
if a long setup appears while the ribbon is red, the setup is more risky.
if a short setup appears while the ribbon is green, the setup is more risky.
the ribbon can therefore be used as a confirmation filter before taking early entries.
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beginner settings
atr period: 10
base factor: 1.0
factor step: 0.4
bands to confirm a flip: 6
confirm for n bars: 1
show band lines: on
show ribbon fill: on
show core line: on
show confirmed flip markers: on
trend background tint: personal preference
show dashboard: on
this setup gives a balanced mix of reactivity and stability.
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stricter settings
bands to confirm a flip: 7
confirm for n bars: 2 or 3
this setup reduces false flips, but trend changes appear later.
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faster settings
bands to confirm a flip: 5
confirm for n bars: 1
this setup reacts faster, but it can create more false flips in choppy markets.
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important notes
the ribbon shows a trend regime, not a guaranteed entry signal.
the best use is to trade in the direction of the ribbon.
confirmed flips are more reliable than fast color changes.
a green ribbon means long setups have better context.
a red ribbon means short setups have better context.
risk management is required on every trade.
supertrend ribbon is designed to make trend direction clear, reduce visual noise, and help traders stay aligned with the dominant market structure.
Indicator
Alpha Signal Engine Pro [MarkitTick]🎁 Our gift to the PulseWire community.
This indicator was previously available as a paid, invite-only tool. Today, it is permanently and unconditionally free — open to every trader on PulseWire without restriction, without a subscription, and without an expiration date.
No catch. No trial period. Ours to you, forever.
💡A comprehensive trend-following and market-state detection framework . It operates by generating a dynamic, volatility-adjusted trailing band that reacts not just to price movements, but to the shifting structural regimes of the asset. By analyzing True Range, historical price percentiles, and momentum simultaneously, this indicator filters out market noise and isolates high-probability directional shifts. It inherently guards against false signals during flat or consolidating markets through a multi-layered filtering matrix, ensuring that traders are presented with actionable data only when strict momentum and structural conditions are met.
● ✨ Originality and Utility
Most trend-following systems rely on static multipliers or fixed lookback periods, rendering them susceptible to sudden market regime changes. The primary utility of this engine lies in its adaptive nature. It introduces a Volatility Fingerprint module that constantly scans the environment, classifying the market into distinct regimes: Alpha, Beta, Gamma, and Delta. Based on this continuous assessment, the indicator autonomously scales its sensitivity, smoothing depth, and filter thresholds. This means the engine tightens its criteria during erratic, low-liquidity chop and expands its bands during high-volatility expansions, providing an organic, self-adjusting framework that eliminates the need for constant manual parameter tuning.
● 🔬 Methodology and Concepts
• Dynamic Trailing Core
At the heart of the engine is a composite distance formula that calculates a dynamic half-band. Instead of relying solely on a basic Average True Range (ATR) multiplier, it combines three elements: an absolute band multiplier, an ATR weight normalized against the closing price, and a raw price move weight. This composite value is then smoothed using an Exponential Moving Average (EMA) alpha factor. The resulting smoothed band is applied to the median price to establish upper and lower boundaries, forming the basis of the trendline.
• Volatility Fingerprinting
The script normalizes the ATR as a percentage of the closing price and ranks it against a historical lookback window using non-parametric percentile thresholds. By splitting the historical distribution into quartiles (25th, 50th, and 75th percentiles), the asset's current volatility is placed into a specific bucket. The core mathematical weights and matrix thresholds are then dynamically multiplied by regime-specific scalars.
• Alpha Filtering Matrix
To prevent whipsaws, the script employs a five-layer matrix that acts as a logical gatekeeper before any signal is validated:
- Trendline Stall: Measures the absolute change in the trendline against a fraction of the ATR.
- Slope Regression: Computes the linear regression slope of the trendline over a rolling window and normalizes it.
- Volume Gate: Compares current volume to a dynamic simple moving average of volume.
- Range Gate: Checks if the current bar's High-Low range exceeds a specific historical percentile.
- Basis Point (BPS) Delta: Ensures the trendline shift meets a minimum percentage threshold.
• Breakout Override
If the market suddenly explodes with extreme momentum, a Breakout Override function bypasses the filtering matrix. If the absolute change in price heavily exceeds a set multiple of the ATR, the system immediately forces engagement to capture the breakout.
● 🎨 Visual Guide
• Dynamic Trendline
A solid line plots the active trailing stop and trend direction. By default, it is colored Cyan for a Bullish trend and Magenta for a Bearish trend. This line steps up or down along with price action, providing a clear visual anchor for the current structural bias.
• Dynamic Bar Coloring
The chart's candlesticks are dynamically colored using a visual gradient. The script measures the normalized distance of the closing price from the trendline. When price is near the trendline, candles assume a neutral slate-blue tone. As momentum carries price further away, the color interpolates into bright Cyan (Bullish) or Magenta (Bearish), immediately illustrating trend strength.
• Cloud Fill
A semi-transparent cloud is drawn between the primary trendline and a smoothed moving average of the typical price. This creates a visual "value zone" on the chart, helping users quickly identify the spatial relationship between the current trend anchor and the smoothed price core.
• HUD Dashboard
A comprehensive heads-up display is positioned in the top-right corner of the chart. It outputs real-time diagnostic data:
- Direction: Displays the current structural bias (Bullish/Bearish).
- Signal: Indicates if an actionable Buy or Sell signal is present.
- Override: Shows the status of the Breakout Override (Off, Nominal, or Engaged in Orange).
- Matrix Pillars: Five rows display the status of the Stall, Slope, Volume, Range, and BPS Delta filters. A Red "Flat" tag indicates the filter is blocking signals, while a Green "Active" tag indicates the path is clear.
- VF Regime: The bottom row explicitly states the current volatility state (Alpha, Beta, Gamma, or Delta) with corresponding color codes.
• Signal Labels
When a directional flip occurs and the matrix conditions are met, explicit "BUY" (Upward pointing, subtle green) or "SELL" (Downward pointing, subtle red) labels are plotted precisely at the trendline level.
• Non-Standard Chart Warning
If the user applies the script to Heikin Ashi, Renko, Line Break, Kagi, or Point & Figure charts, a bold Red warning table will appear in the top-left corner. This warns the user that standard signals may repaint due to the synthetic price data of non-standard charts.
📌 Note : the best way to resolve visual overlap is to navigate to the Object Tree and drag the indicator above the main chart layer, or simply hide the native candles in your chart settings.
● 📖 How to Use
• Identifying Entries
Wait for a clear crossover of the closing price over the dynamic trendline. For a valid entry, ensure the HUD Dashboard confirms the matrix conditions are "Active" and not "Flat." The emergence of a defined BUY or SELL label serves as the primary action trigger.
• Managing the Trade
Once in a position, the dynamic trendline serves as a logical trailing stop-loss level. As the trendline steps in the direction of the trade, users can manually trail their risk. The color gradient on the bars provides a secondary gauge; fading colors suggest weakening momentum and a potential reversion to the mean.
• Regime Awareness
Monitor the VF Regime status on the dashboard. In "Alpha" or "Beta" (lower volatility), expect tighter bands and slower movements. In "Gamma" or "Delta" (extreme volatility), be prepared for wider stops and aggressive price action. The indicator will automatically handle the mathematical adjustments, but position sizing should reflect the increased environmental risk.
• Repaint Warning Note
Always utilize this indicator on standard candlestick or bar charts. The underlying calculations depend on absolute close, high, and low values. Applying this to Heikin Ashi will cause lookahead bias and repainting signals.
🏆 Golden Rule — Before You Trade This Indicator:
Never rely on the default settings, every asset behaves differently. Every timeframe has its own rhythm. Default settings are a starting point — not a strategy.
The best configuration is the one you build yourself, through deliberate testing:
Adjust the settings methodically until false signals are minimized and entry/exit accuracy is maximized.
Test on your specific asset. Test on your specific timeframe. Then lock in what works.
The trader who takes time to configure is the trader who profits consistently.
● ⚙️ Inputs and Settings
• Volatility Fingerprint Group
Allows users to toggle the adaptive engine on or off, and set the lookback length used to determine the historical percentiles for regime classification.
• Core Engine Parameters
Controls the baseline foundation. Adjust the ATR period, the absolute Band Multiplier, the relative ATR Weight, the Price Move Weight, and the EMA Smoothing Length. When VF is enabled, these act as the baseline from which multipliers scale.
• Alpha Filtering Matrix
Provides granular control over the five anti-chop filters. Users can toggle each filter independently and adjust their strictness, such as the Flatness Threshold, Regression Length, Slope Threshold, Volume MA Length, and Range Percentile.
• Display & Cloud Configuration
Permits full aesthetic customization of the Bull/Bear colors, neutral gradient tones, visibility of the dashboard, signal labels, and the transparency parameters of the cloud fill.
• Alert Actions
Customizable string inputs that feed directly into the JSON webhook alert system, allowing automated traders to define syntax for Long, Short, Close Long, and Close Short actions.
● 🔍 Deconstruction of the Underlying Scientific and Academic Framework
• Autoregressive Smoothing and Moving Averages
The system employs an Exponential Moving Average (EMA) to smooth its dynamic raw band. The mathematical alpha factor is defined as 2 / (N + 1), where N is the user-defined smoothing length. This recursive formula assigns geometrically decreasing weights to older observations, ensuring the trendline remains highly responsive to recent price vectors while mathematically filtering high-frequency noise.
• Non-Parametric Rank Statistics
To evaluate the volatility state, the script calculates the nearest-rank percentile of the normalized ATR over a rolling window. Unlike standard standard-deviation bands (such as Bollinger Bands) that assume a normal Gaussian distribution of returns, this non-parametric percentile approach does not assume normality. This is statistically robust for financial time series, which exhibit leptokurtic (fat-tailed) distributions, ensuring accurate classification even during severe market outliers.
• Linear Regression and Slope Normalization
The Slope Filter relies on the Ordinary Least Squares (OLS) linear regression of the trendline. By calculating the change between the current linear regression value and the previous bar's value, it extracts a pure mathematical slope. To make this slope asset-agnostic, it is normalized by dividing the raw slope by the ATR, yielding a dimensionless ratio that accurately represents directional velocity regardless of the instrument's absolute price.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. We expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicator
SuperTrend Exhaustion Clues [Gabremoku]SuperTrend Exhaustion Clues is a context-aware SuperTrend indicator that separates structural direction from signal timing. Instead of treating every flip as a trade trigger, it classifies market behavior into four states: Transition, Confirmed, Compressed Break, and Exhausted. The goal is to show when trend structure is still healthy, when it is compressing, and when it is weakening enough to start looking for directional clues.
The core logic combines four elements: SuperTrend for directional structure, ADX and DI for trend strength, VWAP and price location for acceptance, and compression detection for squeeze/release context. These components are not merged just for convenience; they work together to decide whether price is merely changing direction structurally or whether it is also showing enough internal confirmation to justify attention.
BUY and SELL signals are not printed on every flip. They are designed to appear only during Exhausted phases, and only when directional clues align with the next likely move. This makes the indicator more selective than a standard SuperTrend and better suited to reading late-stage trend fatigue and early follow-through behavior.
A built-in Signal Profile lets you choose between Responsive, Balanced, and Selective behavior. Responsive lowers the confirmation threshold and is better for faster charts, Balanced is the default middle ground, and Selective raises the bar for cleaner but rarer signals. For this reason, the script is especially useful on lower timeframes, where exhaustion tends to be easier to read and directional clues appear earlier.
For higher timeframes, the script can keep showing state, regime, and clue scores while disabling signals from 4H and above. This helps avoid forcing execution signals where the exhaustion logic is less expressive, while still letting you use the indicator for context and structure.
The visual design is intentionally restrained: bullish states are blue, bearish states are yellow, compression is purple, transition is gray, and exhaustion is red. The SuperTrend line, gradient fill, dashboard, and color legend are meant to make the state of the market easy to read at a glance without cluttering the chart.
How to use it: watch the current state first, then use Exhausted phases as the main area of interest. When the script shows Exhausted and the directional clue score aligns with the next move, that is the moment it is designed to highlight. On 4H and above, the script is better used as a structural context tool rather than a signal engine.
@Gabremoku
PulseWire Indicator
Dynamic FibTrend Signals [MarkitTick]💡 This indicator represents an advanced multi-layered analytical framework designed to synchronize trend identification with structural market geometry. By integrating adaptive trend-following logic with automated price action mapping, the tool serves as a comprehensive dashboard for traders seeking to identify high-probability entry zones. It solves the common problem of "indicator clutter" by condensing volatility-adjusted trend direction, swing structure recognition, and Fibonacci retracement depth into a single, cohesive visual interface that provides real-time trade execution levels based on current market volatility.
● ✨ Originality and Utility
The primary utility of this script lies in its ability to bridge the gap between momentum-based trend following and static price levels. While many scripts focus on a single aspect of technical analysis, this indicator utilizes a synergistic approach:
It combines the volatility-sensitive nature of SuperTrend with the objective structural points of Pivot Highs and Lows.
It automates the projection of Fibonacci retracement levels based on a dynamic lookback period, ensuring that support and defense zones are always relevant to recent price action.
Unlike standard tools that leave the user to determine their own risk, this system automatically calculates a suggested entry, stop loss, and multiple target levels using Average True Range (ATR) to adjust for current market volatility.
● 🔬 Methodology and Concepts
The core engine operates on a tripartite logic system:
Trend Quantification: The system employs an Average True Range (ATR) calculation multiplied by a specific factor to create a dynamic band around the price. This determines the prevailing bias (Bullish or Bearish) and filters out market noise.
Structural Mapping: Through a pivot-point algorithm, the script identifies "Swing" levels. These are points where the market has shown significant rejection, helping to define the current trading range.
Risk Geometry: Upon a trend shift (signal), the script calculates trade levels. The Entry is based on the previous bar's close, while the Stop Loss and Profit Targets are mathematically derived from the ATR. This ensures that the risk-to-reward ratio remains consistent regardless of whether the market is in a high or low-volatility state.
● 🎨 Visual Guide
The chart interface is designed for high legibility, using distinct color coding and shapes to signify different market states:
SuperTrend Line: A continuous line that turns Green during bullish momentum and Red during bearish momentum. The area between this line and the price is filled with a subtle transparency to highlight the "trend cloud."
Signal Arrows: Bright green "BUY" arrows appear below the bars for bullish transitions, and red "SELL" arrows appear above the bars for bearish transitions.
Swing Markers: Small orange downward triangles mark Swing Highs, while blue upward triangles mark Swing Lows. These are accompanied by dashed horizontal lines projecting the price level forward.
Fibonacci Grid: A series of purple dotted horizontal lines representing key retracement levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%). These levels provide context for potential pullbacks within the main trend.
Trade Execution Box: When a signal is generated, a yellow entry box appears along with three distinct lines:
Yellow Line: The specific Entry price.
Green Dashed Line: The Target (Take Profit) level.
Red Dashed Line: The Stop Loss level.
Info Table: A professional-grade data table in the top-right corner summarizes the current trend status, the most recent swing levels, and the active trade coordinates for quick reference.
● 📖 How to Use
Trend Identification: Observe the color of the SuperTrend line. If the line is green and the price is above it, focus on long opportunities. If red, focus on shorts.
Confirmation: Look for signals where the SuperTrend flip aligns with a bounce off a Fibonacci level (specifically the 50% or 61.8% "Golden Pocket").
Execution: When a "BUY" or "SELL" arrow appears, refer to the yellow entry zone. The script projects these levels 40 bars into the future to allow for trade planning.
Exit Strategy: Use the target line for profit-taking and the red stop-loss line for capital protection. The 2:1 risk-to-reward ratio is the default, but this can be adjusted in the settings.
● ⚙️ Inputs and Settings
⚡ SuperTrend: Adjust the ATR Length and Factor. A higher factor makes the trend slower and more resilient to whipsaws, while a lower factor makes it more sensitive.
🔄 Swing High / Low: Define the lookback period for pivot detection. Increasing this value will only identify major market turns.
📐 Fibonacci Retracement: Change the lookback bars for the Fibonacci grid. This determines the "height" of the range being measured.
🎯 Trade Levels: Set your desired Risk-to-Reward ratio (default is 2.0). You can also toggle the visibility of the entry, target, and stop lines.
● 🔍 Deconstruction of the Underlying Scientific and Academic Framework
The indicator is built upon the "Volatility Clustering" theory, which suggests that market volatility is not constant but occurs in bursts. By using ATR-based thresholds, the indicator applies a statistical filter that expands and contracts based on realized variance. The swing detection logic utilizes a "Windowed Extrema" approach, which is a fundamental concept in time-series analysis for identifying local maxima and minima within a defined temporal window. Furthermore, the integration of Fibonacci ratios (specifically the 0.618 Golden Mean) incorporates elements of fractal geometry and Elliott Wave theory, positing that market corrections often move in proportions derived from the Fibonacci sequence. The final trade execution component utilizes a fixed-fractional risk management model, ensuring that trade parameters are mathematically optimized for the current market environment rather than being based on arbitrary price distances.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicator
Alpha Signal Engine [MarkitTick]💡 The Alpha Signal Engine is an advanced, multi-dimensional trend-following system designed to provide traders with highly filtered, high-probability market signals. At its core, it dynamically calculates a volatility-adjusted trailing band to determine the primary market direction. However, unlike traditional trend indicators that rely on a single data point, this engine passes every potential trend reversal through a rigorous, six-layer filtering mechanism. By requiring confluence across higher timeframe trends, momentum, volume, volatility regimes, and price action strength, it drastically reduces the noise and false signals inherent in choppy markets. It also features a built-in heads-up dashboard and fully formatted JSON webhook capabilities for automated trading integration.
✨ Originality and Utility
● A Dynamic, Adaptive Baseline
Standard trailing stop or trend indicators, such as the classic Supertrend, typically use a static multiplier against the Average True Range (ATR). The Alpha Signal Engine innovates by introducing a "Dynamic Factor." This factor continuously adapts the band's distance from price by factoring in the current baseline multiplier, the relative volatility (ATR normalized by price), and the immediate price change momentum. This allows the bands to tighten during periods of strong, directional momentum and widen during erratic volatility, providing a more responsive and intelligent trailing mechanism.
● The Six-Pillar Filtering Gateway
The true utility of this indicator lies in its modular filtering engine. Traders often have to clutter their charts with half a dozen indicators to confirm a setup. This script centralizes that logic. Users can selectively enable or disable filters based on their specific asset and trading style, turning the indicator into a customizable algorithmic engine. Whether you need volume confirmation, ADX trend strength, or simple RSI momentum, the script handles the complex boolean logic internally and only outputs a signal when your precise market conditions are met.
🔬 Methodology and Concepts
● Dynamic Factor Calculation
The indicator establishes its baseline trend using an upper and lower band. The distance of these bands from the median price is dictated by a dynamically calculated factor. This factor is the sum of a base value, a volatility component (ATR divided by Close, scaled by a user weight), and a price movement component (percentage change of the close, scaled by a user weight). This raw factor is then smoothed using a Simple Moving Average (SMA) to prevent erratic band shifts.
● Trend Determination
The trend direction flips when the closing price crosses the active dynamic band. If the price closes above the upper band, the trend shifts bullish, and the lower band becomes the active support. Conversely, closing below the lower band shifts the trend bearish, making the upper band the active resistance.
● The Filter Matrix
A signal is only generated when a trend flip aligns with all activated filters:
HTF Alignment: Uses the request context to pull the trend direction from a higher timeframe, ensuring you are not trading against the macro trend.
ADX Trending: Measures the Average Directional Index to ensure the market is in an active trending phase (above a defined threshold) rather than a sideways chop.
Volume Surge: Compares current volume against a Volume SMA. The current bar must exhibit a volume spike greater than the defined multiplier to confirm institutional participation.
RSI Momentum: A simple but effective gatekeeper requiring the Relative Strength Index to be above 50 for longs and below 50 for shorts.
ATR Volatility Regime: Compares the current ATR against a 50-period SMA of the ATR. It ensures the market is operating within a "normal" volatility ratio, preventing entries during extreme, unpredictable volatility spikes or dead, illiquid periods.
Candle Body Strength: Calculates the absolute size of the candle body (Open to Close) and mandates it must be larger than a specific fraction of the ATR, ensuring the signal candle has true directional conviction.
🎨 Visual Guide
● Chart Elements
Up Trend Line: Displayed as a solid, teal-colored line trailing below the price action during a bullish phase. It acts as dynamic support.
Down Trend Line: Displayed as a solid, bright pink/red line trailing above the price action during a bearish phase. It acts as dynamic resistance.
Trend Cloud (Fill): A colored gradient fill exists between the median price and the active trend line. A teal cloud visually represents bullish dominance, while a pink/red cloud represents bearish dominance.
Buy Signals: Indicated by small, teal "B" labels positioned below the signal candle.
Sell Signals: Indicated by small, pink/red "S" labels positioned above the signal candle.
● Filter Dashboard
Located in the top right corner of the chart, this HUD (Heads-Up Display) provides a real-time status check of your system.
The left column lists the available filters (HTF Align, ADX Trend, Vol Surge, RSI Gate, ATR Regime, Body Str).
The right column displays the current status of each filter.
A gray "OFF" indicator means the user has disabled the filter in the settings.
A green "ON" or "Aligned" text indicates the condition is currently met.
A red "Opposed" or unlit indicator means the condition is active but currently failing to meet the required criteria.
The bottom rows clearly state the current overarching trend direction and whether a signal is pending or waiting.
📖 How to Use
• Interpreting the System
To effectively use the Alpha Signal Engine, begin by observing the main trend lines and the color of the cloud. This provides your baseline bias. Do not take trades purely on the band flipping. Instead, rely on the explicit "B" and "S" labels.
• Signal Execution
When a "B" (Buy) or "S" (Sell) label appears, it means the price has successfully flipped the trend AND all user-activated filters in the dashboard are glowing green. This is your entry trigger. The active trend line (the teal line for longs, the pink line for shorts) serves as an ideal, dynamic stop-loss placement.
• Customizing the Engine
The system is designed to be tuned. If you are trading a highly liquid asset like major forex pairs, you may want to enable the ADX and HTF filters to catch long, sustained moves. If you are trading volatile crypto assets, enabling the Volume Surge and Candle Body filters can help you avoid fake-outs and trap wicks. Monitor the on-chart dashboard to see which filters are keeping you out of bad trades and adjust your settings accordingly.
⚙️ Inputs and Settings
• Supertrend Settings
ATR Length: The lookback period for calculating the Average True Range.
Base Factor: The starting multiplier for the dynamic bands.
Volatility & Price Change Weights: Determines how aggressively the bands react to sudden spikes in relative volatility and price momentum.
Factor Smoothing: Applies an SMA to the final dynamic multiplier to keep the bands stable.
• Filter Settings
Enable HTF Alignment: Toggle and define the higher timeframe (e.g., Daily) to align with.
ADX Settings: Toggle the filter, define the lookback length, and set the minimum trend strength threshold (default is 20).
Volume Settings: Toggle the filter, define the Volume MA length, and set the multiplier required to classify as a "surge."
RSI Settings: Toggle the filter and set the RSI lookback length.
ATR Regime Settings: Define the minimum and maximum acceptable ratios of current ATR versus historical ATR.
Candle Body Settings: Define the minimum required size of the candle body as a fraction of the current ATR.
• Webhook Action Names
These text inputs allow you to define specific payload strings (e.g., "long", "closeshort") that the indicator will output via JSON alerts, perfectly formatting the data for third-party automation services like 3Commas or PineConnector.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
The Alpha Signal Engine is grounded in several well-documented tenets of quantitative financial analysis and statistical market theory.
● Volatility-Adjusted Trailing Stops
The foundation of the indicator relies on the Average True Range (ATR), introduced by J. Welles Wilder Jr. The ATR is a measure of the degree of price volatility. By tying the trailing stop (the dynamic band) to the ATR, the system acknowledges the statistical reality of market variance. The innovation here is the dynamic multiplier. By adjusting the distance based on the normalized rate of change (momentum), the script attempts to solve the lagging nature of fixed-multiplier trailing stops, utilizing principles found in adaptive moving averages (like Kaufman's AMA), where sensitivity increases alongside directional conviction.
● Multi-Dimensional Confluence Theory
The filtering engine operates on the academic principle of conditional probability and confluence. In market microstructure, no single indicator holds a permanent statistical edge.
The HTF filter is rooted in Dow Theory, prioritizing the primary trend over secondary reactions.
The ADX filter utilizes Wilder's Directional Movement Index to mathematically separate trending environments from mean-reverting environments, applying a statistical threshold to directional strength.
The Volume Surge filter relies on the Volume Price Trend concepts, positing that significant price movements must be sponsored by outsized volume to validate institutional participation and avoid anomalous low-liquidity spikes.
The ATR Regime filter applies mean-reverting principles to volatility itself (volatility clustering), ensuring that entries are only taken when the variance of the asset is within historically "normal" parameters, avoiding the fat tails of extreme market shocks.
By chaining these disparate mathematical models (trend, momentum, volume, volatility) via Boolean logic, the system mathematically reduces the frequency of trades while theoretically increasing the probability of the remaining sample size.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicator
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Pro Supertrend CalculatorThis indicator is an adapted version of Julien_Eche's 'Pro Momentum Calculator' tailored specifically for PulseWire's 'Supertrend indicator'.
The "Pro Supertrend Calculator" indicator has been developed to provide traders with a data-driven perspective on price movements in financial markets. Its primary objective is to analyze historical price data and make probabilistic predictions about the future direction of price movements, specifically in terms of whether the next candlestick will be bullish (green) or bearish (red). Here's a deeper technical insight into how it accomplishes this task:
1. Supertrend Computation:
The indicator initiates by computing the Supertrend indicator, a sophisticated technical analysis tool. This calculation involves two essential parameters:
- ATR Length (Average True Range Length): This parameter determines the sensitivity of the Supertrend to price fluctuations.
- Factor: This multiplier plays a pivotal role in establishing the distance between the Supertrend line and prevailing market prices. A higher factor value results in a more significant separation.
2. Supertrend Visualization:
The Supertrend values derived from the calculation are meticulously plotted on the price chart, manifesting as two distinct lines:
- Green Line: This line represents the Supertrend when it indicates a bullish trend, signifying an anticipation of rising prices.
- Red Line: This line signifies the Supertrend in bearish market conditions, indicating an expectation of falling prices.
3. Consecutive Candle Analysis:
- The core function of the indicator revolves around tracking successive candlestick patterns concerning their relationship with the Supertrend line.
- To be included in the analysis, a candlestick must consistently close either above (green candles) or below (red candles) the Supertrend line for multiple consecutive periods.
4.Labeling and Enumeration:
- To communicate the count of consecutive candles displaying uniform trend behavior, the indicator meticulously applies labels to the price chart.
- The positioning of these labels varies based on the direction of the trend, residing either below (for bullish patterns) or above (for bearish patterns) the candlestick.
- The color scheme employed aligns with the color of the candle, using green labels for bullish candles and red labels for bearish ones.
5. Tabular Data Presentation:
- The indicator augments its graphical analysis with a customizable table prominently displayed on the chart. This table delivers comprehensive statistical insights.
- The tabular data comprises the following key elements for each consecutive period:
a. Consecutive Candles: A tally of the number of consecutive candles displaying identical trend characteristics.
b. Candles Above Supertrend: A count of candles that remained above the Supertrend during the sequential period.
3. Candles Below Supertrend: A count of candles that remained below the Supertrend during the sequential period.
4. Upcoming Green Candle: An estimation of the probability that the next candlestick will be bullish, grounded in historical data.
5. Upcoming Red Candle: An estimation of the probability that the next candlestick will be bearish, based on historical data.
6. Tailored Configuration:
To accommodate diverse trading strategies and preferences, the indicator offers extensive customization options. Traders can fine-tune parameters such as ATR length, factor, label and table placement, and table size to align with their unique trading approaches.
In summation, the "Pro Supertrend Calculator" indicator is an intricately designed tool that leverages the Supertrend indicator in conjunction with historical price data to furnish traders with an informed outlook on potential future price dynamics, with a particular emphasis on the likelihood of specific bullish or bearish candlestick patterns stemming from consecutive price behavior. Indicator
SuperTrend AI (Clustering) [LuxAlgo]The SuperTrend AI indicator is a novel take on bridging the gap between the K-means clustering machine learning method & technical indicators. In this case, we apply K-Means clustering to the famous SuperTrend indicator.
🔶 USAGE
Users can interpret the SuperTrend AI trailing stop similarly to the regular SuperTrend indicator. Using higher minimum/maximum factors will return longer-term signals.
The displayed performance metrics displayed on each signal allow for a deeper interpretation of the indicator. Whereas higher values could indicate a higher potential for the market to be heading in the direction of the trend when compared to signals with lower values such as 1 or 0 potentially indicating retracements.
In the image above, we can notice more clear examples of the performance metrics on signals indicating trends, however, these performance metrics cannot perform or predict every signal reliably.
We can see in the image above that the trailing stop and its adaptive moving average can also act as support & resistance. Using higher values of the performance memory setting allows users to obtain a longer-term adaptive moving average of the returned trailing stop.
🔶 DETAILS
🔹 K-Means Clustering
When observing data points within a specific space, we can sometimes observe that some are closer to each other, forming groups, or "Clusters". At first sight, identifying those clusters and finding their associated data points can seem easy but doing so mathematically can be more challenging. This is where cluster analysis comes into play, where we seek to group data points into various clusters such that data points within one cluster are closer to each other. This is a common branch of AI/machine learning.
Various methods exist to find clusters within data, with the one used in this script being K-Means Clustering , a simple iterative unsupervised clustering method that finds a user-set amount of clusters.
A naive form of the K-Means algorithm would perform the following steps in order to find K clusters:
(1) Determine the amount (K) of clusters to detect.
(2) Initiate our K centroids (cluster centers) with random values.
(3) Loop over the data points, and determine which is the closest centroid from each data point, then associate that data point with the centroid.
(4) Update centroids by taking the average of the data points associated with a specific centroid.
Repeat steps 3 to 4 until convergence, that is until the centroids no longer change.
To explain how K-Means works graphically let's take the example of a one-dimensional dataset (which is the dimension used in our script) with two apparent clusters:
This is of course a simple scenario, as K will generally be higher, as well the amount of data points. Do note that this method can be very sensitive to the initialization of the centroids, this is why it is generally run multiple times, keeping the run returning the best centroids.
🔹 Adaptive SuperTrend Factor Using K-Means
The proposed indicator rationale is based on the following hypothesis:
Given multiple instances of an indicator using different settings, the optimal setting choice at time t is given by the best-performing instance with setting s(t) .
Performing the calculation of the indicator using the best setting at time t would return an indicator whose characteristics adapt based on its performance. However, what if the setting of the best-performing instance and second best-performing instance of the indicator have a high degree of disparity without a high difference in performance?
Even though this specific case is rare its however not uncommon to see that performance can be similar for a group of specific settings (this could be observed in a parameter optimization heatmap), then filtering out desirable settings to only use the best-performing one can seem too strict. We can as such reformulate our first hypothesis:
Given multiple instances of an indicator using different settings, an optimal setting choice at time t is given by the average of the best-performing instances with settings s(t) .
Finding this group of best-performing instances could be done using the previously described K-Means clustering method, assuming three groups of interest (K = 3) defined as worst performing, average performing, and best performing.
We first obtain an analog of performance P(t, factor) described as:
P(t, factor) = P(t-1, factor) + α * (∆C(t) × S(t-1, factor) - P(t-1, factor))
where 1 > α > 0, which is the performance memory determining the degree to which older inputs affect the current output. C(t) is the closing price, and S(t, factor) is the SuperTrend signal generating function with multiplicative factor factor .
We run this performance function for multiple factor settings and perform K-Means clustering on the multiple obtained performances to obtain the best-performing cluster. We initiate our centroids using quartiles of the obtained performances for faster centroids convergence.
The average of the factors associated with the best-performing cluster is then used to obtain the final factor setting, which is used to compute the final SuperTrend output.
Do note that we give the liberty for the user to get the final factor from the best, average, or worst cluster for experimental purposes.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Performance Memory: Determine the degree to which older inputs affect the current output, with higher values returning longer-term performance measurements.
From Cluster: Determine which cluster is used to obtain the final factor.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
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SuperTrend OptimizerHello!
This indicator attempts to optimize Supertrend parameters. To achieve this, 102 parameter combinations are tested concurrently - the top three performers are listed in descending order.
Parameters,
Factor: Changes to this parameter shifts the tested factor range. For instance, increasing the factor measure from 3.00 to 3.01 (+0.01) will remove 3.00 from the tested range - this setting controls the lower threshold of the range. The upper threshold, in all instances, is the lower Factor threshold + 3.3 (i.e. 3.0(lower) - 6.3(upper), 4.0(lower) - 7.3(upper), 2.5(lower) - 5.8(upper))
ATR period: Changes to this parameter shifts the tested ATR period range. For instance, increasing the ATR measure from 10 to 11 (+1) will remove 10 from the tested range - this setting controls the lower threshold of the range. The upper threshold, in all instances, is the lower threshold + 2 (i.e. 10(lower) - 12(upper), 11(lower) - 13(upper), 9(lower), - 11(upper))
The Factor parameter is modifiable to any positive decimal number; the ATR parameter is modifiable to any positive integer. Changing either parameter shifts the tested parameter combination range. Both parameters can be changed in the settings, to which you control the lower threshold of the range. If, for instance, you were to change the Factor measurement from 3.0 to 4.1 (+1.1) the 4.0 Factor measurement, and all Factor measures less than 4.0, will be excluded from the performance test.
Consequently, a Supertrend test will be performed with a Factor of 4.1 and an ATR period of 10 (default). This test repeats at 0.1 Factor intervals and 1.0 ATR intervals.
Therefore, assume you modify the Factor lower threshold to 3.1 and the ATR lower threshold to 10. The indicator will test three Supertrend systems with a Factor of 3.1 and an ATR period of 10.. then 11.. 12, then three systems with a Factor of 3.2 and an ATR period of 10.. then 11.. 12... until (lower Factor threshold + 3.3) and (lower ATR threshold + 2) are tested... which in this example is... a Factor of 6.4 and an ATR period of 12.
The tested Factor range and ATR range are displayed in a bottom right table alongside the top performing parameter combinations.
Of course, you can change the the lower thresholds, which means you can test numerous Supertrend parameter combinations! However, no greater than 102 parameter combinations will be tested simultaneously; the best performing Supertrend parameters are plotted on the chart automatically.
I will be working on this indicator more tomorrow! Let me know if you have questions or anything you would like included!
(I of course added something fun in the script. Be sure to try it with bar replay!)
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