Adaptive Market Profile – Auto Detect & Dynamic Activity ZonesAdaptive Market Profile is an advanced indicator that automatically detects and displays the most relevant trend channel and market profile for any asset and timeframe. Unlike standard regression channel tools, this script uses a fully adaptive approach to identify the optimal period, providing you with the channel that best fits the current market dynamics. The calculation is based on maximizing the statistical significance of the trend using Pearson’s R coefficient, ensuring that the most relevant trend is always selected.
Within the selected channel, the indicator generates a dynamic market profile, breaking the price range into configurable zones and displaying the most active areas based on volume or the number of touches. This allows you to instantly identify high-activity price levels and potential support/resistance zones. The “most active lines” are plotted in real-time and always stay parallel to the channel, dynamically adapting to market structure.
Key features:
- Automatic detection of the optimal regression period: The script scans a wide range of lengths and selects the channel that statistically represents the strongest trend.
- Dynamic market profile: Visualizes the distribution of volume or price touches inside the trend channel, with customizable section count.
- Most active zones: Highlights the most traded or touched price levels as dynamic, parallel lines for precise support/resistance reading.
- Manual override: Optionally, users can select their own channel period for full control.
- Supports both linear and logarithmic charts: Simple toggle to match your chart scaling.
Use cases:
- Trend following and channel trading strategies.
- Quick identification of dynamic support/resistance and liquidity zones.
- Objective selection of the most statistically significant trend channel, without manual guesswork.
- Suitable for all assets and timeframes (crypto, stocks, forex, futures).
Originality:
This script goes beyond basic regression channels by integrating dynamic profile analysis and fully adaptive period detection, offering a comprehensive tool for modern technical analysts. The combination of trend detection, market profile, and activity zone mapping is unique and not available in TradingView built-ins.
Instructions:
Add Adaptive Market Profile to your chart. By default, the script automatically detects the optimal channel period and displays the corresponding regression channel with dynamic profile and activity zones. If you prefer manual control, disable “Auto trend channel period” and set your preferred period. Adjust profile settings as needed for your asset and timeframe.
For questions, suggestions, or further customization, contact Julien Eche (@Julien_Eche) directly on TradingView.
Adaptive
Intelligent Moving📘 Intelligent Moving – Adaptive Neural Trend Engine
Intelligent Moving is an invite-only, closed-source indicator that dynamically adjusts itself to evolving market conditions using a built-in neural optimizer. It combines a custom adaptive Moving Average, ATR-based deviation bands, and a fully internal virtual trade simulator to deliver smart trend signals and automatic parameter tuning — all without repainting or manual intervention.
This script is built entirely from original code and does not use any open-source components or built-in TradingView indicators.
🧠 Core Logic and Visual Structure
The indicator plots:
- A central moving average (optimized dynamically),
- Upper and lower deviation bands based on ATR × adaptive coefficients,
- Buy (aqua) and Sell (orange) arrows on reversion signals,
- Color-coded trend zones based on price vs. moving average.
All three bands change color in real time depending on the price’s position relative to the MA, clearly showing uptrends (e.g. blue) and downtrends (e.g. red).
📈 Signal Logic: Reversion from Extremes
- Buy Signal: After price closes below the lower deviation band, it then closes back above it.
- Sell Signal: After price closes above the upper deviation band, it then closes back below it.
These signals are not based on crossovers, oscillators, or lagging logic — they are pure structure-based reversion entries, designed to detect exhaustion and reversal zones.
🤖 Built-In Neural Optimizer (Perceptron Engine)
At the heart of Intelligent Moving lies a self-training engine that uses simulated (virtual) positions to test multiple configurations and pick the best one. Here’s how it works:
🔄 Virtual Trade Simulation
At regular intervals (user-defined), the script:
- Simulates virtual buy/sell positions based on its signal logic.
- Applies virtual Stop-Loss (just beyond the signal zone) and virtual Take-Profit (when price crosses back over the MA).
- Calculates simulated profit for each combination of:
- - MA periods,
- - Upper/lower ATR multipliers.
🧠 Neural Training Process
- A perceptron-like engine evaluates the simulated results.
- It selects the best-performing configuration and applies it to live plotting.
- You can choose whether optimization uses a base value or the last best result from the previous training pass.
This process runs forward-only and never overwrites history or uses future data. It's completely transparent and non-repainting.
⚙️ Customization and Parameters
Users can control:
- MA period range, step, and training type (base vs last best)
- Deviation multiplier ranges and step
- Training depth (number of bars in history)
- Training interval (how often to retrain)
- Spread simulation, alert options, and all visual settings
💡 What Makes It Unique
- ✅ Self-optimization with virtual trades and perceptron logic
- ✅ Adaptive deviation bands based on ATR (not standard deviation)
- ✅ No built-in indicators, no repaints, no curve-fitting
- ✅ Clear trend zones and reversal signals
- ✅ Optimized for live use and consistent behavior across assets
Unlike typical moving average tools, Intelligent Moving thinks, adapts, and reacts — turning a standard concept into a living, learning trend engine.
📊 Use Cases
- Trend detection with adaptive coloring
- Reversion trading from volatility extremes
- Dynamic strategy building with minimal manual input
- Alerts for automated or discretionary traders
🔒 Invite-Only Notice
This script is invite-only and closed-source.
The optimization logic, trade simulation system, and perceptron engine were developed from scratch, specifically for this indicator. No built-in functions (e.g. MA, BB, RSI) or public scripts were used or copied.
All decisions and calculations are based on current and past price only — no repainting, retrofitting, or future leakage.
⚠️ Disclaimer
This indicator is for educational and analytical use only.
It does not predict future prices or guarantee profits. Always use appropriate risk management and test thoroughly before live trading.
PRO Investing - Apex EnginePRO Investing - Apex Engine
1. Core Concept: Why Does This Indicator Exist?
Traditional momentum oscillators like RSI or Stochastic use a fixed "lookback period" (e.g., 14). This creates a fundamental problem: a 14-period setting that works well in a fast, trending market will generate constant false signals in a slow, choppy market, and vice-versa. The market's character is dynamic, but most tools are static.
The Apex Engine was built to solve this problem. Its primary innovation is a self-optimizing core that continuously adapts to changing market conditions. Instead of relying on one fixed setting, it actively tests three different momentum profiles (Fast, Mid, and Slow) in real-time and selects the one that is most synchronized with the current price action.
This is not just a random combination of indicators; it's a deliberate synthesis designed to create a more robust momentum tool. It combines:
Volatility analysis (ATR) to generate adaptive lookback periods.
Momentum measurement (ROC) to gauge the speed of price changes.
Statistical analysis (Correlation) to validate which momentum measurement is most effective right now.
Classic trend filters (Moving Average, ADX) to ensure signals are only taken in favorable market conditions.
The result is an oscillator that aims to be more responsive in volatile trends and more stable in quiet periods, providing a more intelligent and adaptive signal.
2. How It Works: The Engine's Three-Stage Process
To be transparent, it's important to understand the step-by-step logic the indicator follows on every bar. It's a process of Adapt -> Validate -> Signal.
Stage 1: Adapt (Dynamic Length Calculation)
The engine first measures market volatility using the Average True Range (ATR) relative to its own long-term average. This creates a volatility_factor. In high-volatility environments, this factor causes the base calculation lengths to shorten. In low-volatility, they lengthen. This produces three potential Rate of Change (ROC) lengths: dynamic_fast_len, dynamic_mid_len, and dynamic_slow_len.
Stage 2: Validate (Self-Optimizing Mode Selection)
This is the core of the engine. It calculates the ROC for all three dynamic lengths. To determine which is best, it uses the ta.correlation() function to measure how well each ROC's movement has correlated with the actual bar-to-bar price changes over the "Optimization Lookback" period. The ROC length with the highest correlation score is chosen as the most effective profile for the current moment. This "active" mode is reflected in the oscillator's color and the dashboard.
Stage 3: Signal (Normalized Velocity Oscillator)
The winning ROC series is then normalized into a consistent oscillator (the Velocity line) that ranges from -100 (extreme oversold) to +100 (extreme overbought). This ensures signals are comparable across any asset or timeframe. Signals are only generated when this Velocity line crosses its signal line and the trend filters (explained below) give a green light.
3. How to Use the Indicator: A Practical Guide
Reading the Visuals:
Velocity Line (Blue/Yellow/Pink): The main oscillator line. Its color indicates which mode is active (Fast, Mid, or Slow).
Signal Line (White): A moving average of the Velocity line. Crossovers generate potential signals.
Buy/Sell Triangles (▲ / ▼): These are your primary entry signals. They are intentionally strict and only appear when momentum, trend, and price action align.
Background Color (Green/Red/Gray): This is your trend context.
Green: Bullish trend confirmed (e.g., price above a rising 200 EMA and ADX > 20). Only Buy signals (▲) can appear.
Red: Bearish trend confirmed. Only Sell signals (▼) can appear.
Gray: No clear trend. The market is likely choppy or consolidating. No signals will appear; it is best to stay out.
Trading Strategy Example:
Wait for a colored background. A green or red background indicates the market is in a tradable trend.
Look for a signal. For a green background, wait for a lime Buy triangle (▲) to appear.
Confirm the trade. Before entering, confirm the signal aligns with your own analysis (e.g., support/resistance levels, chart patterns).
Manage the trade. Set a stop-loss according to your risk management rules. An exit can be considered on a fixed target, a trailing stop, or when an opposing signal appears.
4. Settings and Customization
This script is open-source, and its settings are transparent. You are encouraged to understand them.
Synaptic Engine Group:
Volatility Period: The master control for the adaptive engine. Higher values are slower and more stable.
Optimization Lookback: How many bars to use for the correlation check.
Switch Sensitivity: A buffer to prevent frantic switching between modes.
Advanced Configuration & Filters Group:
Price Source: The data source for momentum calculation (default close).
Trend Filter MA Type & Length: Define your long-term trend.
Filter by MA Slope: A key feature. If ON, allows for "buy the dip" entries below a rising MA. If OFF, it's stricter, requiring price to be above the MA.
ADX Length & Threshold: Filters out non-trending, choppy markets. Signals will not fire if the ADX is below this threshold.
5. Important Disclaimer
This indicator is a decision-support tool for discretionary traders, not an automated trading system or financial advice. Past performance is not indicative of future results. All trading involves substantial risk. You should always use proper risk management, including setting stop-losses, and never risk more than you are prepared to lose. The signals generated by this script should be used as one component of a broader trading plan.
RSI Mansfield +RSI Mansfield+ – Adaptive Relative Strength Indicator with Divergences
Overview
RSI Mansfield+ is an advanced relative strength indicator that compares your instrument’s performance against a configurable benchmark index or asset (e.g., Bitcoin Dominance, S&P 500). It combines Mansfield normalization, adaptive smoothing techniques, and automatic detection of bullish and bearish divergences (regular and hidden), delivering a comprehensive tool for assessing relative strength across any market and timeframe.
Originality and Motivation
Unlike traditional relative strength scripts, this indicator introduces several distinctive improvements:
Mansfield Normalization: Scales the ratio between the asset and the benchmark relative to its moving average, transforming it into a normalized oscillator that fluctuates around zero, making it easier to spot outperformance or underperformance.
Adaptive Smoothing: Automatically selects whether to use EMA or SMA based on the market type (crypto or stocks) and timeframe (intraday, daily, weekly, monthly), avoiding manual configuration and providing more robust results under varying volatility conditions.
Divergence Detection: Identifies four types of divergences in the Mansfield oscillator to help anticipate potential reversal points or trend confirmations.
Multi-Market Support: Offers benchmark selection among major crypto and global stock indices from a single input.
These enhancements make RSI Mansfield+ more practical and powerful than conventional relative strength scripts with static benchmarks or without divergence capabilities.
Core Concepts
Relative Strength (RS): Compares price evolution between your asset and the selected benchmark.
Mansfield Normalization: Measures how much the RS deviates from its historical moving average, expressed as a scaled oscillator.
Divergences: Detects regular and hidden bullish or bearish divergences within the Mansfield oscillator.
Timeframe Adaptation: Dynamically adjusts moving average lengths based on timeframe and market type.
How It Works
Benchmark Selection
Choose among over 10 indices or market domains (BTC Dominance, ETH Dominance, S&P 500, European indices, etc.).
Ratio Calculation
Computes the price-to-benchmark ratio and smooths it with the adaptive moving average.
Normalization and Scaling
Transforms deviations into a Mansfield oscillator centered around zero.
Dynamic Coloring
Green indicates relative outperformance, red signals underperformance.
Divergence Detection
Automatically identifies bullish and bearish (regular and hidden) divergences by comparing oscillator pivots against price pivots.
Baseline Reference
A clear zero line helps interpret relative strength trends.
Usage Guidelines
Benchmark Comparison
Ideal for traders analyzing whether an asset is outperforming or lagging its sector or market.
Divergence Analysis
Helps detect potential reversal or continuation signals in relative strength.
Multi-Timeframe Compatibility
Can be applied to intraday, daily, weekly, or monthly charts.
Interpretation
Oscillator >0 and green: outperforming the benchmark.
Oscillator <0 and red: underperforming.
Bullish divergences: potential relative strength reversal to the upside.
Bearish divergences: possible loss of momentum or reversal to the downside.
Credits
The concept of Mansfield Relative Strength is based on Stan Weinstein’s original work on relative performance analysis. This script was built entirely from scratch in TradingView Pine Script v6, incorporating original logic for adaptive smoothing, normalized scaling, and divergence detection, without reusing any external open-source code.
Adaptive Squeeze Momentum +Adaptive Squeeze Momentum+ (Auto-Timeframe Version)
Overview
Adaptive Squeeze Momentum+ is an enhanced volatility and momentum indicator designed to identify compression and expansion phases in price action. It is inspired by the classic Squeeze Momentum Indicator by LazyBear but introduces automatic parameter adaptation to any timeframe, making it simpler to use across different markets without manual configuration.
Concepts and Methodology
The script combines Bollinger Bands (BB) and Keltner Channels (KC) to detect periods when volatility contracts (squeeze) or expands (release).
A squeeze occurs when BB are inside KC, suggesting low volatility and potential breakout scenarios.
A squeeze release is detected when BB expand outside KC.
Momentum is derived using a linear regression applied to the difference between price and a midrange reference level.
Original Improvements
Compared to the original Squeeze Momentum Indicator, this version offers several enhancements:
Automatic Adaptation: BB and KC lengths and multipliers are dynamically adjusted based on the chart’s timeframe (from 1 minute up to 1 month), removing the need for manual tuning.
Simplified Visualization: A clean, minimalist histogram and clear squeeze state cross markers allow for faster interpretation.
Flexible Application: Designed to work consistently on intraday, daily, and higher timeframes across crypto, forex, stocks, and indices.
Features
Dynamic Squeeze Detection:
Gray Cross: Neutral (no squeeze detected)
Blue Cross: Active squeeze
Yellow Cross: Squeeze released
Momentum Histogram:
Positive/negative momentum shown with slope-based coloring.
Timeframe-Aware Parameters:
Automatically sets optimal BB/KC configurations.
Usage
Watch for blue crosses indicating an active squeeze phase that may precede a directional move.
Use the histogram color and slope to gauge momentum strength and direction.
Combine squeeze release signals with momentum confirmation for potential entries or exits.
Credits and Licensing
This script was inspired by LazyBear’s OLD “Squeeze Momentum Indicator” (). The implementation here significantly expands upon the original by introducing auto-adaptive parameters, restructured logic, and a new visualization approach. Published under the Mozilla Public License 2.0.
Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Use at your own risk.
Adaptive Sharp Momentum█ Introduction
The Adaptive Sharp Momentum Study has the following all-in-one features:
• A noise-free, trend-following indicator.
• Automatically detects implied tops and bottoms within fast price cycles.
• It identifies price consolidations and periods of indecision; often challenging to spot.
• Includes a unique feature for detecting directional price squeezes.
• An integrated volatility measure helps avoid false signals and clarifies trend direction.
• Lastly, it alerts traders when a volume climax is likely reached during a move.
This study primarily focuses on capturing momentum while concurrently alerting traders to shifting market dynamics, thereby aiding in the decision to either extend a position’s duration or optimize exit timing. The set of analytical tools, deployed alongside the trend-following indicator, are integrated to reflect the concepts outlined above. Furthermore, this framework utilizes distinctive methods for trend identification, consolidation recognition, directional squeeze assessment, and volume climax analysis—approaches that are not currently documented in publicly available resources.
█ Explanation of Core Components
1. Trend Following Consolidated Adaptive Moving Average:
At the core of the study is the Jurik Adaptive Average Curve, a fast-response adaptive moving average refined with an adaptive Relative Strength Index (RSX) function, known as Jurik RSX. This curve displays three trend modes—bullish, bearish, and indecisive—each customizable in color.
Users can adjust parameters such as the Phase and Consolidation Period:
• Phase: Influences the timing of trend signals, accommodating various trading styles. A lower phase value can produce leading signals, while a higher value may result in lagging signals.
• Consolidation Period: Helps filter out false signals. Optimize this period based on the time frame and instrument.
• Momentum Slope Threshold: As mentioned earlier, the Jurik moving average values are consolidated against the Dynamic Jurik RSX. Crossing the slope threshold of the Jurik RSX will trigger consolidation.
The main curve in the middle represents the overall trend. The issue with moving averages is that they work well in trends but when market is in consolidation, many false signals can be generated. The consolidation period acts as a second fast signal curve that helps eliminate the false signals generated through the standard adaptive moving average. This is basically done by measuring the momentum of the move itself through the Jurik RSX. There are other tools in this study that should also help the trader avoid false signals which will be fully described below.
2. Implied Tops and Bottoms
The study also detects Implied Tops and Bottoms during market cycles using the Composite Momentum and Projections. It offers three detection modes:
• Strong Signals: Indicate significant potential reversal points.
• Medium Signals: Typically displayed near the end of a trend, suggesting traders should prepare to exit.
• Rolling Signals: Alert traders to set tight stop losses to secure profits, as the market may be approaching a turning point.
By default, the colors of Rolling Signals and Medium Signals are the same for simplicity.
Note the following:
• The fast and slow period have the most effect on implied tops and bottoms detection.
• Adjusting the main period will also have an overall effect.
The above chart shows rolling tops, rolling bottoms, strong tops, and strong bottoms. A rolling top of bottom indicate an increase in momentum in that direction and thus a tight stoploss would be recommended, while a strong top/bottom indicates that an exit is warranted.
3. Consolidation and Volatility
If enabled, '+' will appear above the ceiling and floor plots if consolidation is detected. Consolidation is detected by using lookback function that determine if price is below a threshold or not. If below, then consolidation would be confirmed. This is accomplished by adjusting the ' Price Consolidation Threshold ' period
The above chart demonstrates detection of consolidation on a 1-minute chart. Also, note the ceiling and floor plot, it expands when volatility is high.
Consolidation detection helps weed out long and short signals indicated by the main curve.
4. Directional Squeeze
Another unique feature of this indicator is the detection of directional price squeeze. Directional squeeze is defined as a price push in the direction indicated by momentum whether upward or downward. This is different from the common squeeze indicators found on the web since this one is detecting a directional push.
The Directional Squeeze feature, indicated by up and down triangles above the main curve, highlights strong trends in the market's current direction:
• Trend Continuation: Allows traders to stay in profitable trades longer during strong trending markets.
• Multiple Modes: Offers single-bar (short-term) and longer-term squeezes. Single-bar squeezes can signal potential market reversals, while longer-term squeezes are useful in sustained trends.
Be mindful that under certain conditions, the directional squeeze could be directionless(sideways) if consolidation is outlined by the indicator. This is another useful feature the trader could utilize. The chart above mostly demonstrates directional squeeze but directionless can also be observed.
5. Volume Volatility and Volume Climax Detection
An essential feature of the Adaptive Sharp Momentum Study is its ability to measure Volume Volatility and detect Volume Climax moments:
• Volume Volatility Measure: Integrated into the study to help avoid false signals by assessing the strength of market moves. It provides better clarity on trend direction by indicating when the market is experiencing significant volume changes.
• Volume Climax Alerts: The study alerts traders when a volume climax is likely reached during a move, which is helpful for identifying potential reversal points or the culmination of a trend. Brighter confirmation signal dots indicate these climaxes, helping traders make timely entry/exit decisions.
• Adjustable Parameters: Traders can set the Volume Volatility Threshold and adjust the Volume Lookback Period to tailor the sensitivity of volume climax detection according to their trading strategy.
5. The indicator contains other useful features:
• Cycles: Helps determine when to enter long or short trades based on upward or downward market cycles. It also aids in recognizing retracement levels during a trend, allowing traders to capitalize on brief counter-trend movements. Those cycles can be observed as the up and down gray lines on the chart.
• Real-Time Table: The table is another visual aid that summarizes the status of each feature in real-time.
█ How to Use this Study Effectively
The main curve in the middle is your final decision point. Prior to entering a trade look for the following:
• Is the market in consolidation? If yes, then you'd be advised not to enter the trade until the study clearly shows no consolidation
• Is the ceil or floor plots showing a strong top or bottom, or even a volume climax in the direction to intend to enter? If yes, then either ensure you enter at a tight stop or don't enter
• Is there an indication of a directional squeeze with no consolidation or volume climax? Then this would be an ideal place to enter. Be mindful though that entering directional squeeze too late is not recommended.
• Once you are in the trade, look at consolidation, implied tops and bottoms, and volume climax to determine exit point. You will quickly realize if you entered a trade prematurely.
• Utilize the directional squeeze and the prevalent trend to help you stay in the trade longer.
• Adjust your stop losses depending on whether you are seeing a rolling implied top/bottom or a strong top/bottom.
• Also, at volume climaxes, be ready to exit. The approach with volume climax detection should be the same as the implied tops/bottoms.
Below is a chart demonstrating trading on a 1-minute chart. The study could be used for any time frame:
** Important Note **
This study relies on volume readings. Incorrect evaluation will be concluded without proper volume data.
█ How the Adaptive Sharp Momentum Works?
---Main Curve - Jurik Moving Average and RSX---
The Jurik Moving Average (JMA) and the Jurik RSX with Fisher transform (Relative Strength Index Extended) are technical tools designed to enhance data processing efficiency. The JMA uses an adaptive smoothing algorithm to dynamically adjust to market conditions, reducing lag while maintaining high responsiveness to price changes. the JMA incorporates a mechanism that determines smoothness based on input volatility. The RSX, on the other hand, tracks relative strength without introducing the overshoots and noise commonly seen in other momentum indicators. It achieves this by applying a yet another JMA smoothing function that ensures stability and consistency, making it a better candidate for identifying shifts.
This is a unique approach, but can simply be equated to two moving averages crossing over, except in this case, the RSX is crossing over with the JMA.
The process of determining market trends and consolidation for the main curve revolves around evaluating multiple conditions and rankings of indicators such as Jurik RSX, Fisher Transform, and Volume-based metrics (Adaptive On Balance Volume and Price Volatility). Here's how consolidation and trends are identified:
1. Trend Override Logic: The core logic evaluates whether specific conditions override the default trend determined by the JMA.
• Bearish Overrides: A trend is classified as bearish if specific conditions involving negative slopes of the RSX, bearish Fisher Transform readings, and other auxiliary rankings (AOBV trend rank or volatility ranks) are met.
• Bullish Overrides: Similarly, bullish trends are determined by the presence of positive RSX slopes, bullish Fisher readings, and supporting AOBV and volatility ranks.
• Neutral Overrides: If neither bullish nor bearish overrides dominate, and conflicting conditions are detected (e.g., a bearish Fisher with a bullish OBV), the trend can be overridden to neutral.
2. Dynamic Slope and Rank Analysis: RSX and Jurik Slopes: The slopes of the RSX and Jurik indicators play an important role. Increasing slopes suggest bullish momentum, while decreasing slopes imply bearish momentum.
3. Narrow Spread Analysis: Consolidation zones are identified by examining conditions like narrow spreads in price action and mixed indicator signals (e.g., a positive RSX slope alongside a neutral or bearish AOBV).
• When consolidation is detected, the system looks for confirming signals (AOBV or Fisher alignment) to determine whether the next move is likely to be bullish or bearish.
4.Fallback Logic:
If no explicit conditions are met for bullish, bearish, or neutral trends, the system defaults to comparing the current and previous values of the Jurik Moving Average. If the JMA is rising, the trend is set to bullish; otherwise, it defaults to bearish.
The process of consolidating The RSX with JMA, attempts to confirm the trend suggested by the Jurik moving average. As shown above, several factors play into this, but it is mostly motivated by the RSX and its slope
-- Detecting Tops and Bottoms --
• Composite Momentum
The Composite Momentum indicator analyzes the market's directional strength to identify implied tops and bottoms, especially at extreme values. It evaluates momentum by categorizing it into ranges that reflect moderate or strong trends for both bullish and bearish conditions. When momentum exceeds a positive threshold, it indicates a strong top, whereas values below a negative threshold then it's a strong bottom.
• Laguerre Dynamic Projection Bands
The Laguerre Dynamic Projection Bands focuses on price positioning within calculated dynamic boundaries. By applying linear regression, it projects upper and lower price bands, which serve as potential resistance and support levels. The oscillator value ranges from 0 to 100, representing the relative position of the current price. A value above 70 indicates the price is near a projected top, while a value below 30 suggests proximity to a projected bottom. Through custom Laguerre smoothing, the setup ensures that its signals remain stable and actionable.
• How They Work Together
The Composite Momentum and Projection Oscillator complement each other in detecting market tops and bottoms. The Projection Oscillator provides an early indication when price nears a critical level, while the Composite Momentum confirms whether the momentum supports the formation of a significant top or bottom.
-- Consolidation Detection, Volatility, and Volume Climax Detection --
• Summary of Consolidation Detection:
Consolidation is identified through a combination of statistical and smoothing applied to price data. The approach calculates deviations around the main plot using squared price inputs, smoothed averages, and adaptive multipliers. These deviations form dynamic upper and lower boundaries that adapt to changing market conditions. The system further evaluates these boundaries against historical bars to calculate a volume percentage, which indicates how often recent price action remains within these bands. A low percentage suggests consolidation, characterized by reduced volatility and price movement confined within a tighter range.
The bands around the main plot are derived from the calculated maximum deviations, creating adaptive ceilings and floors that expand or contract based on market dynamics. The Ceiling and Floor plots represent the outermost boundaries, while additional retracement plots are drawn based on the Composite Momentum wave rank. For example, during an uptrend, the retrace levels adjust upward in fractional steps relative to the deviation, signaling possible resistance levels. In downtrends, similar logic applies in reverse to determine support levels. These bands visually represent the volatility envelope and help contextualize price movements relative to expected ranges. Whenever, low volatility is detected, a visual "+" indicator is added to the plot to highlight that the market is likely in consolidation mode.
• How the Adaptive OBV Applies the Same Logic:
The Adaptive On-Balance Volume (OBV) uses a similar mechanism to detect volume climaxes by analyzing deviations in volume data. Instead of price, the OBV logic applies the squared input and smoothing methods to volume flows. By comparing these deviations to historical norms, the system identifies periods of high or low volatility in volume, which often coincide with potential breakouts or consolidation zones.
• How They Work Together
The consolidation detection process and the adaptive bands work in tandem to provide traders with a clear visualization of market conditions. When consolidation is detected, the dynamic bands narrow and a "+" sign is visualized, signaling reduced volatility and potential breakout opportunities. Similarly, volume-based analysis through the adaptive OBV helps confirm whether a breakout is accompanied by significant volume, adding confidence to trade decisions. Together, they enable anticipation of market shifts.
-- Directional Squeeze --
A directional price squeeze refers to a market condition where price compresses in a particular direction. This provides traders with an opportunity to stay in trades longer by aligning with the prevailing directional bias. This unique concept generates dynamic limits based on lookback period. Their convergence upward or downward is typically a strong indication of a price push toward the respective direction.
In this approach, the system looks at the highest and lowest values of a smoothed momentum reading over a recent period and measures the distance between them. Instead of relying on a static “overbought” or “oversold” line, it calculates new boundaries as a fraction of that distance, scaling the thresholds to match the price behavior. When these dynamically adjusted limits converge, it suggests a “directional squeeze”—meaning price is moving within a more compressed or focused range. Because these boundaries adapt to the market’s own highs and lows, they provide a more responsive indication of when price may be shifting into or out of a strong directional move.
• Determining the Directional Squeeze
Directional squeeze is identified using dynamic limits derived from two key factors:
Schaff Trend Cycle (STC) for single-bar squeezes. and the Slow RSI (SRSI) for multi-bar or longer-term squeezes. Both are utilizing a custom alpha factor for adaptability and conformance with the JMA and Dynamic RSX studies.
• Directional Trend Confirmation:
If the SRSI or STC approaches the limits, additional conditions such as Fisher RSX (momentum signals) and AOBV (volume signals) and the trend already established by the JMA are aligned. If so, then a squeezed in that trend directional is established.
█ Why These Components All Work Together?
The Adaptive Sharp Momentum Study integrates multiple components to provide a framework for analyzing market dynamics. Each feature addresses specific challenges in trading:
• Core Trend Identification:
The Jurik Adaptive Moving Average (JMA) and Jurik RSX ensure better trend detection by reducing noise and dynamically confirming momentum, thus minimizing lag and false signals.
• Implied Tops and Bottoms:
The combination of Composite Momentum and Laguerre Dynamic Projection Bands highlights critical turning points. This dual-layered approach identifies potential reversals and key support/resistance levels with improved clarity.
• Consolidation and Volatility:
Adaptive ceilings, floors, and consolidation detection filter out indecisive market phases. This helps avoid unreliable signals and provides a better perspective on potential breakouts or continuations.
• Directional Squeeze:
The Directional Squeeze feature identifies directional bias in price compression. Its dynamic thresholds adapt to market conditions, aiding in the assessment of strong directional moves.
• Volume Climax:
Volume volatility and climax detection highlight key moments of market activity, aiding in the evaluation of trend strength and potential turning points.
• Integrated Framework:
The integration of these components creates a system where each element complements the others.
This study offers a methodical approach to analyzing trends, momentum, and volatility while filtering noise. It is a tool designed to assist traders in navigating complex market conditions.
█ Disclaimer
This script is provided for educational and informational purposes only and should not be considered financial advice. Trading financial instruments carries a high level of risk and may not be suitable for all investors. Before using this script, please consult with a qualified financial advisor to ensure it aligns with your individual circumstances. The author does not guarantee the accuracy or completeness of the script and is not responsible for any losses or damages that may occur from its use. Use this script at your own risk.
Active PMI Support/Resistance Levels [EdgeTerminal]The PMI Support & Resistance indicator revolutionizes traditional technical analysis by using Pointwise Mutual Information (PMI) - a statistical measure from information theory - to objectively identify support and resistance levels. Unlike conventional methods that rely on visual pattern recognition, this indicator provides mathematically rigorous, quantifiable evidence of price levels where significant market activity occurs.
- The Mathematical Foundation: Pointwise Mutual Information
Pointwise Mutual Information measures how much more likely two events are to occur together compared to if they were statistically independent. In our context:
Event A: Volume spikes occurring (high trading activity)
Event B: Price being at specific levels
The PMI formula calculates: PMI = log(P(A,B) / (P(A) × P(B)))
Where:
P(A,B) = Probability of volume spikes occurring at specific price levels
P(A) = Probability of volume spikes occurring anywhere
P(B) = Probability of price being at specific levels
High PMI scores indicate that volume spikes and certain price levels co-occur much more frequently than random chance would predict, revealing genuine support and resistance zones.
- Why PMI Outperforms Traditional Methods
Subjective interpretation: What one trader sees as significant, another might ignore
Confirmation bias: Tendency to see patterns that confirm existing beliefs
Inconsistent criteria: No standardized definition of "significant" volume or price action
Static analysis: Doesn't adapt to changing market conditions
No strength measurement: Can't quantify how "strong" a level truly is
PMI Advantages:
✅ Objective & Quantifiable: Mathematical proof of significance, not visual guesswork
✅ Statistical Rigor: Levels backed by information theory and probability
✅ Strength Scoring: PMI scores rank levels by statistical significance
✅ Adaptive: Automatically adjusts to different market volatility regimes
✅ Eliminates Bias: Computer-calculated, removing human interpretation errors
✅ Market Structure Aware: Reveals the underlying order flow concentrations
- How It Works
Data Processing Pipeline:
Volume Analysis: Identifies volume spikes using configurable thresholds
Price Binning: Divides price range into discrete levels for analysis
Co-occurrence Calculation: Measures how often volume spikes happen at each price level
PMI Computation: Calculates statistical significance for each price level
Level Filtering: Shows only levels exceeding minimum PMI thresholds
Dynamic Updates: Refreshes levels periodically while maintaining historical traces
Visual System:
Current Levels: Bright, thick lines with PMI scores - your actionable levels
Historical Traces: Faded previous levels showing market structure evolution
Strength Tiers: Line styles indicate PMI strength (solid/dashed/dotted)
Color Coding: Green for support, red for resistance
Info Table: Real-time display of strongest levels with scores
- Indicator Settings:
Core Parameters
Lookback Period (Default: 200)
Lower (50-100): More responsive to recent price action, catches short-term levels
Higher (300-500): Focuses on major historical levels, more stable but less responsive
Best for: Day trading (100-150), Swing trading (200-300), Position trading (400-500)
Volume Spike Threshold (Default: 1.5)
Lower (1.2-1.4): More sensitive, catches smaller volume increases, more levels detected
Higher (2.0-3.0): Only major volume surges count, fewer but stronger signals
Market dependent: High-volume stocks may need higher thresholds (2.0+), low-volume stocks lower (1.2-1.3)
Price Bins (Default: 50)
Lower (20-30): Broader price zones, less precise but captures wider areas
Higher (70-100): More granular levels, precise but may be overly specific
Volatility dependent: High volatility assets benefit from more bins (70+)
Minimum PMI Score (Default: 0.5)
Lower (0.2-0.4): Shows more levels including weaker ones, comprehensive view
Higher (1.0-2.0): Only statistically strong levels, cleaner chart
Progressive filtering: Start with 0.5, increase if too cluttered
Max Levels to Show (Default: 8)
Fewer (3-5): Clean chart focusing on strongest levels only
More (10-15): Comprehensive view but may clutter chart
Strategy dependent: Scalpers prefer fewer (3-5), swing traders more (8-12)
Historical Tracking Settings
Update Frequency (Default: 20 bars)
Lower (5-10): More frequent updates, captures rapid market changes
Higher (50-100): Less frequent updates, focuses on major structural shifts
Timeframe scaling: 1-minute charts need lower frequency (5-10), daily charts higher (50+)
Show Historical Levels (Default: True)
Enables the "breadcrumb trail" effect showing evolution of support/resistance
Disable for cleaner charts focusing only on current levels
Max Historical Marks (Default: 50)
Lower (20-30): Less memory usage, shorter history
Higher (100-200): Longer historical context but more resource intensive
Fade Strength (Default: 0.8)
Lower (0.5-0.6): Historical levels more visible
Higher (0.9-0.95): Historical levels very subtle
Visual Settings
Support/Resistance Colors: Choose colors that contrast well with your chart theme Line Width: Thicker lines (3-4) for better visibility on busy charts Show PMI Scores: Toggle labels showing statistical strength Label Size: Adjust based on screen resolution and chart zoom level
- Most Effective Usage Strategies
For Day Trading:
Setup: Lookback 100-150, Volume Threshold 1.8-2.2, Update Frequency 10-15
Use PMI levels as bounce/rejection points for scalp entries
Higher PMI scores (>1.5) offer better probability setups
Watch for volume spike confirmations at levels
For Swing Trading:
Setup: Lookback 200-300, Volume Threshold 1.5-2.0, Update Frequency 20-30
Enter on pullbacks to high PMI support levels
Target next resistance level with PMI score >1.0
Hold through minor levels, exit at major PMI levels
For Position Trading:
Setup: Lookback 400-500, Volume Threshold 2.0+, Update Frequency 50+
Focus on PMI scores >2.0 for major structural levels
Use for portfolio entry/exit decisions
Combine with fundamental analysis for timing
- Trading Applications:
Entry Strategies:
PMI Bounce Trades
Price approaches high PMI support level (>1.0)
Wait for volume spike confirmation (orange triangles)
Enter long on bullish price action at the level
Stop loss just below the PMI level
Target: Next PMI resistance level
PMI Breakout Trades
Price consolidates near high PMI level
Volume increases (watch for orange triangles)
Enter on decisive break with volume
Previous resistance becomes new support
Target: Next major PMI level
PMI Rejection Trades
Price approaches PMI resistance with momentum
Watch for rejection signals and volume spikes
Enter short on failure to break through
Stop above the PMI level
Target: Next PMI support level
Risk Management:
Stop Loss Placement
Place stops 0.1-0.5% beyond PMI levels (adjust for volatility)
Higher PMI scores warrant tighter stops
Use ATR-based stops for volatile assets
Position Sizing
Larger positions at PMI levels >2.0 (highest conviction)
Smaller positions at PMI levels 0.5-1.0 (lower conviction)
Scale out at multiple PMI targets
- Key Warning Signs & What to Watch For
Red Flags:
🚨 Very Low PMI Scores (<0.3): Weak statistical significance, avoid trading
🚨 No Volume Confirmation: PMI level without recent volume spikes may be stale
🚨 Overcrowded Levels: Too many levels close together suggests poor parameter tuning
🚨 Outdated Levels: Historical traces are reference only, not tradeable
Optimization Tips:
✅ Regular Recalibration: Adjust parameters monthly based on market regime changes
✅ Volume Context: Always check for recent volume activity at PMI levels
✅ Multiple Timeframes: Confirm PMI levels across different timeframes
✅ Market Conditions: Higher thresholds during high volatility periods
Interpreting PMI Scores
PMI Score Ranges:
0.5-1.0: Moderate statistical significance, proceed with caution
1.0-1.5: Good significance, reliable for most trading strategies
1.5-2.0: Strong significance, high-confidence trade setups
2.0+: Very strong significance, institutional-grade levels
Historical Context: The historical trace system shows how support and resistance evolve over time. When current levels align with multiple historical traces, it indicates persistent market memory at those prices, significantly increasing the level's reliability.
Adaptive Causal Wavelet Trend FilterThe Adaptive Causal Wavelet Trend Filter is a technical indicator implementing causal approximations of wavelet transform properties for better trend detection with adaptive volatility response.
The Adaptive Causal Wavelet Trend Filter (ACWTF) applies mathematical principles derived from wavelet analysis to financial time series, providing robust trend identification with minimal lag. Unlike conventional moving averages, it preserves significant price movements while filtering market noise through signal processing that i describe below.
I was inspired to build this indicator after reading " Wavelet-Based Trend Identification in Financial Time Series " by In, F., & Kim, S. 2013 and reading about Mexican Hat wavelet filters.
The ACWTF maintains optimal performance across varying market regimes without requiring parameter adjustments by adapting filter characteristics to current volatility conditions.
Mathematical Foundation
Inspired by the Mexican Hat wavelet (Ricker wavelet), this indicator implements causal approximations of wavelet filters optimized for real-time financial analysis. The multi-resolution approach identifies features at different scales and the adaptive component dynamically adjusts filtering characteristics based on local volatility measurements.
Key mathematical properties include:
Non-linear frequency response adaptation
Edge-preserving signal extraction
Scale-space analysis through dual filter implementation
Volatility-dependent coefficient adjustment, which I love
Filter Methods
Adaptive: Implements a volatility-weighted combination of multiple filter types to optimize the time-frequency resolution trade-off
Hull: Provides a causal approximation of wavelet edge detection properties with forward-projection characteristics
VWMA: Incorporates volume information into the filtering process for enhanced signal detection
EMA Cascade: Creates a multi-pole filter structure that approximates certain wavelet scaling properties
Suggestion: try all as they will provide slightly different signals. Try also different time-frames.
Practical Applications
Trend Direction Identification: Clear visual trend direction with reduced noise and lag
Regime Change Detection: Early identification of significant trend reversals
Market Condition Analysis: Integrated volatility metrics provide context for current market behavior
Multi-timeframe Confirmation: Alignment between primary and secondary filters offers additional confirmation
Entry/Exit Timing: Filter crossovers and trend changes provide potential trading signals
The comprehensive information panel provides:
Current filter method and trend state
Trend alignment between timeframes
Real-time volatility assessment
Price position relative to filter
Overall trading bias based on multiple factors
Implementation Notes
Log returns option provides improved statistical properties for financial time series
Primary and secondary filter lengths can be adjusted to optimize for specific instruments and timeframes
The indicator performs particularly well during trend transitions and regime changes
The indicator reduces the need for using additional indicators to check trend reversion
Adaptive Quadratic Kernel EnvelopeThis study draws a fair-value curve from a quadratic-weighted (Nadaraya-Watson) regression. Alpha sets how sharply weights decay inside the look-back window, so you trade lag against smoothness with one slider. Band half-width is ATRslow times a bounded fast/slow ATR ratio, giving an instant response to regime shifts without overshooting on spikes. Work in log space when an instrument grows exponentially, equal percentage moves then map to equal vertical steps. NearBase and FarBase define a progression of adaptive thresholds, useful for sizing exits or calibrating mean-reversion logic. Non-repaint mode keeps one-bar delay for clean back-tests, predictive mode shows the zero-lag curve for live decisions.
Key points
- Quadratic weights cut phase error versus Gaussian or SMA-based envelopes.
- Dual-ATR scaling updates width on the next bar, no residual lag.
- Log option preserves envelope symmetry across multi-decade data.
- Alpha provides direct control of curvature versus noise.
- Built-in alerts trigger on the first adaptive threshold, ready for automation.
Typical uses
Trend bias from the slope of the curve.
Entry timing when price pierces an inner threshold and momentum stalls.
Breakout confirmation when closes hold beyond outer thresholds while volatility expands.
Stops and targets anchored to chosen thresholds, automatically matching current noise.
Adaptive MACD Deluxe [AlgoAlpha]OVERVIEW
This script is an advanced rework of the classic MACD indicator, designed to be more adaptive, visually informative, and customizable. It enhances the original MACD formula using a dynamic feedback loop and a correlation-based weighting system that adjusts in real-time based on how deterministic recent price action is. The signal line is flexible, offering several smoothing types including Heiken Ashi, while the histogram is color-coded with gradients to help users visually identify momentum shifts. It also includes optional normalization by volatility, allowing MACD values to be interpreted as relative percentage moves, making the indicator more consistent across different assets and timeframes.
CONCEPTS
This version of MACD introduces a deterministic weight based on R-squared correlation with time, which modulates how fast or slow the MACD adapts to price changes. Higher correlation means smoother, slower MACD responses, and low correlation leads to quicker reaction. The momentum calculation blends traditional EMA math with feedback and damping components to create a smoother, less noisy series. Heiken Ashi is optionally used for signal smoothing to better visualize short-term trend bias. When normalization is enabled, the MACD is scaled by an EMA of the high-low range, converting it into a bounded, volatility-relative indicator. This makes extreme readings more meaningful across markets.
FEATURES
The script offers six distinct options for signal line smoothing: EMA, SMA, SMMA (RMA), WMA, VWMA, and a custom Heiken Ashi mode based on the MACD series. Each option provides a different response speed and smoothing behavior, allowing traders to match the indicator’s behavior to their strategy—whether it's faster reaction or reduced noise.
Normalization is another key feature. When enabled, MACD values are scaled by a volatility proxy, converting the indicator into a relative percentage. This helps standardize the MACD across different assets and timeframes, making overbought and oversold readings more consistent and easier to interpret.
Threshold zones can be customized using upper and lower boundaries, with inner zones for early warnings. These zones are highlighted on the chart with subtle background fills and directional arrows when MACD enters or exits key levels. This makes it easier to spot strong or weak reversals at a glance.
Lastly, the script includes multiple built-in alerts. Users can set alerts for MACD crossovers, histogram flips above or below zero, and MACD entries into strong or weak reversal zones. This allows for hands-free monitoring and quick decision-making without staring at the chart.
USAGE
To use this script, choose your preferred signal smoothing type, enable normalization if you want MACD values relative to volatility, and adjust the threshold zones to fit your asset or timeframe. Use the colored histogram to detect changes in momentum strength—brighter colors indicate rising strength, while faded colors imply weakening. Heiken Ashi mode smooths out noise and provides clearer signals, especially useful in choppy conditions. Use alert conditions for crossover and reversal detection, or monitor the arrow markers for entries into potential exhaustion zones. This setup works well for trend following, momentum trading, and reversal spotting across all market types.
CNN Statistical Trading System [PhenLabs]📌 DESCRIPTION
An advanced pattern recognition system utilizing Convolutional Neural Network (CNN) principles to identify statistically significant market patterns and generate high-probability trading signals.
CNN Statistical Trading System transforms traditional technical analysis by applying machine learning concepts directly to price action. Through six specialized convolution kernels, it detects momentum shifts, reversal patterns, consolidation phases, and breakout setups simultaneously. The system combines these pattern detections using adaptive weighting based on market volatility and trend strength, creating a sophisticated composite score that provides both directional bias and signal confidence on a normalized -1 to +1 scale.
🚀 CONCEPTS
• Built on Convolutional Neural Network pattern recognition methodology adapted for financial markets
• Six specialized kernels detect distinct price patterns: upward/downward momentum, peak/trough formations, consolidation, and breakout setups
• Activation functions create non-linear responses with tanh-like behavior, mimicking neural network layers
• Adaptive weighting system adjusts pattern importance based on current market regime (volatility < 2% and trend strength)
• Multi-confirmation signals require CNN threshold breach (±0.65), RSI boundaries, and volume confirmation above 120% of 20-period average
🔧 FEATURES
Six-Kernel Pattern Detection:
Simultaneous analysis of upward momentum, downward momentum, peak/resistance, trough/support, consolidation, and breakout patterns using mathematically optimized convolution kernels.
Adaptive Neural Architecture:
Dynamic weight adjustment based on market volatility (ATR/Price) and trend strength (EMA differential), ensuring optimal performance across different market conditions.
Professional Visual Themes:
Four sophisticated color palettes (Professional, Ocean, Sunset, Monochrome) with cohesive design language. Default Monochrome theme provides clean, distraction-free analysis.
Confidence Band System:
Upper and lower confidence zones at 150% of threshold values (±0.975) help identify high-probability signal areas and potential exhaustion zones.
Real-Time Information Panel:
Live display of CNN score, market state with emoji indicators, net momentum, confidence percentage, and RSI confirmation with dynamic color coding based on signal strength.
Individual Feature Analysis:
Optional display of all six kernel outputs with distinct visual styles (step lines, circles, crosses, area fills) for advanced pattern component analysis.
User Guide
• Monitor CNN Score crossing above +0.65 for long signals or below -0.65 for short signals with volume confirmation
• Use confidence bands to identify optimal entry zones - signals within confidence bands carry higher probability
• Background intensity reflects signal strength - darker backgrounds indicate stronger conviction
• Enter long positions when blue circles appear above oscillator with RSI < 75 and volume > 120% average
• Enter short positions when dark circles appear below oscillator with RSI > 25 and volume confirmation
• Information panel provides real-time confidence percentage and momentum direction for position sizing decisions
• Individual feature plots allow granular analysis of specific pattern components for strategy refinement
💡Conclusion
CNN Statistical Trading System represents the evolution of technical analysis, combining institutional-grade pattern recognition with retail accessibility. The six-kernel architecture provides comprehensive market pattern coverage while adaptive weighting ensures relevance across all market conditions. Whether you’re seeking systematic entry signals or advanced pattern confirmation, this indicator delivers mathematically rigorous analysis with intuitive visual presentation.
SuperTrend: Silent Shadow 🕶️ SuperTrend: Silent Shadow — Operate in trend. Vanish in noise.
Overview
SuperTrend: Silent Shadow is an enhanced trend-following system designed for traders who demand clarity in volatile markets and silence during indecision.
It combines classic Supertrend logic with a proprietary ShadowTrail engine and an adaptive Silence Protocol to filter noise and highlight only the cleanest signals.
Key Features
✅ Core Supertrend Logic
Built on Average True Range (ATR), this trend engine identifies directional bias with visual clarity. Lines adjust dynamically with price action and flip when meaningful reversals occur.
✅ ShadowTrail: Stepped Counter-Barrier
ShadowTrail doesn’t predict reversals — it reinforces structure.
When price is trending, ShadowTrail forms a stepped ceiling in downtrends and a stepped floor in uptrends. This visual containment zone helps define the edges of price behavior and offers a clear visual anchor for stop-loss placement and trade containment.
✅ Silence Protocol: Adaptive Noise Filtering
During low-volatility zones, the system enters “stealth mode”:
• Trend lines turn white to indicate reduced signal quality
• Fill disappears to reduce distraction
This helps avoid choppy entries and keeps your focus sharp when the market isn’t.
✅ Visual Support & Stop-Loss Utility
When trendlines flatten or pause, they naturally highlight price memory zones. These flat sections often align with:
• Logical stop-loss levels
• Prior support/resistance areas
• Zones of reduced volatility where price recharges or rejects
✅ Custom Styling
Full control over line colors, width, transparency, fill visibility, and silence behavior. Tailor it to your strategy and visual preferences.
How to Use
• Use Supertrend color to determine bias — flips mark momentum shifts
• ShadowTrail mirrors the primary trend as a structural ceiling/floor
• Use flat segments of both lines to identify consolidation zones or place stops
• White lines = low-quality signal → stand by
• Combine with RSI, volume, divergence, or your favorite tools for confirmation
Recommended For:
• Traders seeking clearer trend signals
• Avoiding false entries in sideways or silent markets
• Identifying key support/resistance visually
• Structuring stops around real market containment levels
• Scalping, swing, or position trading with adaptive clarity
Built by Sherlock Macgyver
Forged for precision. Designed for silence.
When the market speaks, you listen.
When it doesn’t — you wait in the shadows.
Adaptive Momentum Oscillator [LuxAlgo]The Adaptive Momentum Oscillator tool allows traders to measure the current relative momentum over a given period using the maximum delta in price.
It features a histogram with gradient color, divergences, and an adaptive moving average that allows traders to clearly see the smoothed trend direction.
🔶 USAGE
This unbounded oscillator has positive momentum when values are above 0 and negative momentum when values are below 0. The adaptive moving average is used as a minimum lag smoothing tool over the momentum histogram.
🔹 Signal Line
There are two main uses for the signal line drawn on the chart above.
Momentum crosses above or below the signal line: acceleration in momentum.
Signal line crosses the 0 value: positive or negative momentum.
🔹 Data Length
On the chart above, we can compare different length sizes and how the tool values change, allowing traders to get a shorter or longer-term view of current market strength.
🔹 Smoothing Length
In the previous figure, we can compare how different Smoothing Length values affect the oscillator output.
🔹 Divergences
The divergence detector is disabled by default. Traders can enable it and adjust the divergence length from the settings panel.
As we can see in the chart above, by changing the length of the divergences, traders can fine-tune their detection, a small number will detect smaller divergences, and use a larger number for larger divergences.
🔶 SETTINGS
Data: Select data source, close price by default
Data Length: Select the length for data gathering
Smoothing Length: Select the length for data smoothing
Divergences: Enable/Disable divergences detection and length
Machine Learning | Adaptive Trend Signals [Bitwardex]⚙️🧠Machine Learning | Adaptive Trend Signals
🔷Overview
Machine Learning | Adaptive Trend Signals is a Pine Script™ v6 indicator designed to visualize market trends and generate signals through a combination of volatility clustering, Gaussian smoothing, and adaptive trend calculations. Built as an overlay indicator, it integrates advanced techniques inspired by machine learning concepts, such as K-Means clustering, to adapt to changing market conditions. The script is highly customizable, includes a backtesting module, and supports alert conditions, making it suitable for traders exploring trend-based strategies and developers studying volatility-driven indicator design.
🔷Functionality
The indicator performs the following core functions:
• Volatility Clustering: Uses K-Means clustering to categorize market volatility into high, medium, and low states, adjusting trend sensitivity accordingly.
• Trend Calculation: Computes adaptive trend lines (SmartTrend) based on volatility-adjusted standard deviation, smoothed RSI, and ADX filters.
• Signal Generation: Identifies potential buy and sell points through trend line crossovers and directional confirmation.
• Backtesting Module: Tracks trade outcomes based on the SmartTrend3 value, displaying win rate and total trades.
• Visualization: Plots trend lines with gradient colors and optional signal markers (bullish 🐮 and bearish 🐻).
• Alerts: Provides configurable alerts for trend shifts and volatility state changes.
🔷Technical Methodology
Volatility Clustering with K-Means
The indicator employs a K-Means clustering algorithm to classify market volatility, measured via the Average True Range (ATR), into three distinct clusters:
• Data Collection: Gathers ATR values over a user-defined training period (default: 100 bars).
• Centroid Initialization: Sets initial centroids at the highest, lowest, and midpoint ATR values within the training period.
• Iterative Clustering: Assigns ATR data points to the nearest centroid, recalculates centroid means, and repeats until convergence.
• Dynamic Adjustment: Assigns a volatility state (high, medium, or low) based on the closest centroid, adjusting the trend factor (e.g., tighter for high volatility, wider for low volatility).
This approach allows the indicator to adapt its sensitivity to varying market conditions, providing a data-driven foundation for trend calculations.
🔷Gaussian Smoothing
To enhance signal clarity and reduce noise, the indicator applies Gaussian kernel smoothing to:
• RSI: Smooths the Relative Strength Index (calculated from OHLC4) to filter short-term fluctuations.
• SmartTrend: Smooths the primary trend line for a more stable output.
The Gaussian kernel uses a sigma value derived from the user-defined smoothing length, ensuring mathematically consistent noise reduction.
🔷SmartTrend Calculation
The pineSmartTrend function is the core of the indicator, producing three trend lines:
• SmartTrend: The primary trend line, calculated using a volatility-adjusted standard deviation, smoothed RSI, and ADX conditions.
• SmartTrend2: A secondary trend line with a wider factor (base factor * 1.382) for signal confirmation.
SmartTrend3: The average of SmartTrend and SmartTrend2, used for plotting and backtesting.
Key components of the calculation include:
• Dynamic Standard Deviation: Scales based on ATR relative to its 50-period smoothed average, with multipliers (1.0 to 1.4) applied according to volatility thresholds.
• RSI and ADX Filters: Requires RSI > 50 for bullish trends or < 50 for bearish trends, alongside ADX > 15 and rising to confirm trend strength.
Volatility-Adjusted Bands: Constructs upper and lower bands around price action, adjusted by the volatility cluster’s dynamic factor.
🔷Signal Generation
The generate_signals function generates signals as follows:
• Buy Signal: Triggered when SmartTrend crosses above SmartTrend2 and the price is above SmartTrend, with directional confirmation.
• Sell Signal: Triggered when SmartTrend crosses below SmartTrend2 and the price is below SmartTrend, with directional confirmation.
Directional Logic: Tracks trend direction to filter out conflicting signals, ensuring alignment with the broader market context.
Signals are visualized as small circles with bullish (🐮) or bearish (🐻) emojis, with an option to toggle visibility.
🔷Backtesting
The get_backtest function evaluates signal outcomes using the SmartTrend3 value (rather than closing prices) to align with the trend-based methodology.
It tracks:
• Total Trades: Counts completed long and short trades.
• Win Rate: Calculates the percentage of trades where SmartTrend3 moves favorably (higher for longs, lower for shorts).
Position Management: Closes opposite positions before opening new ones, simulating a single-position trading system.
Results are displayed in a table at the top-right of the chart, showing win rate and total trades. Note that backtest results reflect the indicator’s internal logic and should not be interpreted as predictive of real-world performance.
🔷Visualization and Alerts
• Trend Lines: SmartTrend3 is plotted with gradient colors reflecting trend direction and volatility cluster, accompanied by a secondary line for visual clarity.
• Signal Markers: Optional buy/sell signals are plotted as small circles with customizable colors.
• Alerts: Supports alerts for:
• Bullish and bearish trend shifts (confirmed on bar close).
Transitions to high, medium, or low volatility states.
🔷Input Parameters
• ATR Length (default: 14): Period for ATR calculation, used in volatility clustering.
• Period (default: 21): Common period for RSI, ADX, and standard deviation calculations.
• Base SmartTrend Factor (default: 2.0): Base multiplier for volatility-adjusted bands.
• SmartTrend Smoothing Length (default: 10): Length for Gaussian smoothing of the trend line.
• Show Buy/Sell Signals? (default: true): Enables/disables signal markers.
• Bullish/Bearish Color: Customizable colors for trend lines and signals.
🔷Usage Instructions
• Apply to Chart: Add the indicator to any TradingView chart.
• Configure Inputs: Adjust parameters to align with your trading style or market conditions (e.g., shorter ATR length for faster markets).
• Interpret Output:
• Trend Lines: Use SmartTrend3’s direction and color to gauge market bias.
• Signals: Monitor bullish (🐮) and bearish (🐻) markers for potential entry/exit points.
• Backtest Table: Review win rate and total trades to understand the indicator’s behavior in historical data.
• Set Alerts: Configure alerts for trend shifts or volatility changes to support manual or automated trading workflows.
• Combine with Analysis: Use the indicator alongside other tools or market context, as it is designed to complement, not replace, comprehensive analysis.
🔷Technical Notes
• Data Requirements: Requires at least 100 bars for accurate volatility clustering. Ensure sufficient historical data is loaded.
• Market Suitability: The indicator is designed for trend detection and may perform differently in ranging or volatile markets due to its reliance on RSI and ADX filters.
• Backtesting Scope: The backtest module uses SmartTrend3 values, which may differ from price-based outcomes. Results are for informational purposes only.
• Computational Intensity: The K-Means clustering and Gaussian smoothing may increase processing time on lower timeframes or with large datasets.
🔷For Developers
The script is modular, well-commented, encouraging reuse and modification with proper attribution.
Key functions include:
• gaussianSmooth: Applies Gaussian kernel smoothing to any data series.
• pineSmartTrend: Computes adaptive trend lines with volatility and momentum filters.
• getDynamicFactor: Adjusts trend sensitivity based on volatility clusters.
• get_backtest: Evaluates signal performance using SmartTrend3.
Developers can extend these functions for custom indicators or strategies, leveraging the volatility clustering and smoothing methodologies. The K-Means implementation is particularly useful for adaptive volatility analysis.
🔷Limitations
• The indicator is not predictive and should be used as part of a broader trading strategy.
• Performance varies by market, timeframe, and parameter settings, requiring user experimentation.
• Backtest results are based on historical data and internal logic, not real-world trading conditions.
• Volatility clustering assumes sufficient historical data; incomplete data may affect accuracy.
🔷Acknowledgments
Developed by Bitwardex, inspired by machine learning concepts and adaptive trading methodologies. Community feedback is welcome via TradingView’s platform.
🔷 Risk Disclaimer
Trading involves significant risks, and most traders may incur losses. Bitwardex AI Algo is provided for informational and educational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument . The signals, metrics, and features are tools for analysis and do not guarantee profits or specific outcomes. Past performance is not indicative of future results. Always conduct your own due diligence and consult a financial advisor before making trading decisions.
RSI-MACD Momentum Fusion Indicator(RMFI)📈 RSI-MACD Momentum Fusion Indicator (RMFI)
The RMFI combines the strengths of two RSI variants with a dynamically adaptive MACD module into a powerful momentum oscillator ranging from 0 to 100. The goal is to unify converging momentum information from different perspectives into a clear, weighted overall signal.
🔧 Core Features
RSI 1: Classic Wilder RSI, sensitive to short-term momentum.
RSI 2: Modified RSI based on normalized price movement ranges (Range Momentum).
MACD (3 Modes):
Standardized (min/max-based)
Fully adaptive (Z-score normalization)
50% adaptive (hybrid weighting of both approaches)
Dynamic MACD mode selection (optional): Automatic switching of MACD normalization based on volatility levels (ATR-based).
Signal Line: Smoothed average of all components to visualize momentum trends and crossovers.
🎯 Visualization
Clear separation of overbought (>70) and oversold (<30) zones with color highlighting.
Different colors based on the dynamic MACD mode – visually indicates how strongly the market adapts to volatility.
⚙️ Recommended Use
Ideal for trend following, divergence confirmation (with external divergence logic), and momentum reversals.
Particularly effective in volatile markets, as the MACD component adaptively responds to instability.
© champtrades
Adaptable Relative Momentum Index [ParadoxAlgo]The Adaptable Relative Momentum Index (RMI) by ParadoxAlgo is an advanced momentum-based indicator that builds upon the well-known RSI (Relative Strength Index) concept by introducing a customizable momentum length. This indicator measures price momentum over a specified number of periods and applies a Rolling Moving Average (RMA) to both the positive and negative price changes. The result is a versatile tool that can help traders gauge the strength of a trend, pinpoint overbought/oversold levels, and potentially identify breakout opportunities.
⸻
Smart Configuration Feature
What sets this version of the RMI apart is ParadoxAlgo’s exclusive “Smart Configuration” functionality. Instead of manually adjusting parameters, traders can simply select their Asset Class (e.g., Stocks, Forex, Futures/Indices, Crypto, Commodities) and Trading Style (e.g., Scalping, Day Trading, Swing Trading, Short-Term Investing, Long-Term Investing). Based on these selections, the indicator automatically optimizes its core parameters:
• Length – The period over which the price changes are smoothed.
• Momentum Length – The number of bars used to calculate the price change.
By automating this process, users save time on tedious trial-and-error adjustments, ensuring that the RMI’s settings are tailored to the characteristics of specific markets and personal trading horizons.
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Key Features & Benefits
1. Momentum-Based Insights
• Uses RMA to smooth price movements, helping identify shifts in market momentum more clearly than a basic RSI.
• Enhanced adaptability for a wide range of asset classes and time horizons.
2. Simple Yet Powerful Configuration
• Smart Configuration automatically sets optimal parameter values for each combination of asset class and trading style.
• Eliminates guesswork and manual recalibration when switching between markets or timeframes.
3. Overbought & Oversold Visualization
• Integrated highlight zones mark potential overbought and oversold extremes (default at 80 and 20).
• Optional breakout highlighting draws attention to times when the indicator crosses these key thresholds, helping spot possible entry or exit signals.
4. Intuitive Design & Ease of Use
• Clean plotting and color-coded signal lines make it easy to interpret bullish or bearish shifts in momentum.
• Straightforward dropdown menus keep the interface user-friendly, even for novice traders.
⸻
Practical Applications
• Early Trend Detection: Spot emerging trends when the RMI transitions from oversold to higher levels or vice versa.
• Breakout Confirmation: Confirm potential breakout trades by tracking overbought/oversold breakouts alongside other technical signals.
• Support/Resistance Confluence: Combine RMI signals with horizontal support/resistance levels to reinforce trade decisions.
• Trade Timing: Quickly gauge when momentum could be shifting, helping you time entries and exits more effectively.
⸻
Disclaimer
As with any technical indicator, the Adaptable Relative Momentum Index should be used as part of a broader trading strategy that includes risk management, fundamental analysis, and other forms of technical confirmation. Past performance does not guarantee future results.
⸻
Enjoy using the Adaptable RMI and experience a more streamlined, flexible approach to momentum analysis. Feel free to explore different asset classes and trading styles to discover which configurations resonate best with your unique trading preferences.
Ehlers Adaptive Trend Indicator [Alpha Extract]Ehlers Adaptive Trend Indicator
The Ehlers Adaptive Trend Indicator combines Ehlers' advanced digital signal processing techniques with dynamic volatility bands to identify robust trend conditions and potential reversals. This powerful tool helps traders visualize trend strength, adaptive support/resistance levels, and momentum shifts across various market conditions.
🔶 CALCULATION
The indicator employs a sophisticated adaptive algorithm that responds to changing market conditions:
• Ehlers Filter : Calculates a weighted average based on momentum differences to create an adaptive trend baseline.
• Dynamic Bands : Volatility-adjusted bands that expand and contract based on recent price action.
• Trend Level : A dynamic support/resistance level that adapts to the current trend direction.
• Smoothed Volatility : Market volatility measured and smoothed to provide reliable band width.
Formula:
• Ehlers Basis = Weighted average of price, with weights determined by momentum differences
• Volatility = Standard deviation of price over Ehlers Length period
• Smoothed Volatility = EMA of volatility over Smoothing Length
• Upper Band = Ehlers Basis + Smoothed Volatility × Sensitivity
• Lower Band = Ehlers Basis - Smoothed Volatility × Sensitivity
• Trend Level = Adaptive support in uptrends, resistance in downtrends
🔶 DETAILS
Visual Features :
• Ehlers Basis Line (Yellow): The core adaptive trend reference that serves as the primary trend indicator.
• Trend Level Line (Dynamic Color): Changes between green (bullish) and red (bearish) based on the current trend state.
• Fill Areas : Transparent green fill during bullish trends and transparent red fill during bearish trends for clear visual identification.
• Bar Coloring : Optional price bar coloring that reflects the current trend direction for enhanced visualization.
Interpretation :
• **Bullish Signal**: Price crosses above the upper band, triggering a trend change with the Trend Level becoming dynamic support.
• **Bearish Signal**: Price drops below the lower band, confirming a trend change with the Trend Level becoming dynamic resistance.
• **Trend Continuation**: Trend Level rises in bullish markets and falls in bearish markets, providing adaptive trailing support/resistance.
🔶 EXAMPLES
The chart demonstrates:
• Bullish Trend Identification : When price breaks above the upper band, the indicator shifts to bullish mode with green trend level and fill.
• Bearish Trend Identification : When price falls below the lower band, the indicator shifts to bearish mode with red trend level and fill.
• Trend Persistence : Trend Level adapts to market movement, rising during uptrends to provide dynamic support and falling during downtrends to act as resistance.
Example Snapshots :
• During a strong uptrend, the Trend Level continuously adjusts upward, keeping traders in the trend while filtering out minor retracements.
• During trend reversals, clear color changes and Trend Level shifts provide early warning of potential direction changes.
🔶 SETTINGS
Customization Options :
• Ehlers Length (p1) (Default: 30): Controls the primary adaptive calculation period, balancing responsiveness with stability.
• Momentum Length (p2) (Default: 25): Determines the lag for momentum calculations used in the adaptive weighting.
• Smoothing Length (Default: 10): Adjusts the volatility smoothing period—higher values provide more stable bands.
• Sensitivity (Default: 1.0): Multiplier for band width—higher values increase distance between bands, lower values tighten them.
• Visual Settings : Customizable colors for bullish and bearish trends, basis line, and optional bar coloring.
The Ehlers Adaptive Trend Indicator combines John Ehlers' digital signal processing expertise with modern volatility analysis to create a robust trend-following system that adapts to changing market conditions, helping traders stay on the right side of the market.
Ehlers Adaptive RSIThe Ehlers Adaptive RSI improves on the traditional RSI by dynamically adjusting its period based on market conditions.
Problem with the Classic RSI:
The traditional Relative Strength Index (RSI) uses a fixed period (e.g., 14), making it slow to react in volatile markets and too sensitive in stable conditions.
How the Adaptive RSI Solves This:
Instead of a fixed period, this version automatically adapts based on market volatility using a combination of ATR (Average True Range) and EMA (Exponential Moving Average).
Key Benefits:
More Responsive – Quickly adapts to market shifts, reducing lag.
Less Noise – Filters out unnecessary fluctuations in stable trends.
Self-Adjusting – No need to manually change RSI settings for different market conditions.
Better Signal Accuracy – Helps detect real trend reversals without false alarms.
This script is for informational and educational purposes only. It does not constitute financial advice, and past performance does not guarantee future results. Use it at your own risk.
Hull Moving Average Adaptive RSI (Ehlers)Hull Moving Average Adaptive RSI (Ehlers)
The Hull Moving Average Adaptive RSI (Ehlers) is an enhanced trend-following indicator designed to provide a smooth and responsive view of price movement while incorporating an additional momentum-based analysis using the Adaptive RSI.
Principle and Advantages of the Hull Moving Average:
- The Hull Moving Average (HMA) is known for its ability to track price action with minimal lag while maintaining a smooth curve.
- Unlike traditional moving averages, the HMA significantly reduces noise and responds faster to market trends, making it highly effective for detecting trend direction and changes.
- It achieves this by applying a weighted moving average calculation that emphasizes recent price movements while smoothing out fluctuations.
Why the Adaptive RSI Was Added:
- The core HMA line remains the foundation of the indicator, but an additional analysis using the Adaptive RSI has been integrated to provide more meaningful insights into momentum shifts.
- The Adaptive RSI is a modified version of the traditional Relative Strength Index that dynamically adjusts its sensitivity based on market volatility.
- By incorporating the Adaptive RSI, the HMA visually represents whether momentum is strengthening or weakening, offering a complementary layer of analysis.
How the Adaptive RSI Influences the Indicator:
- High Adaptive RSI (above 65): The market may be overbought, or bullish momentum could be fading. The HMA turns shades of red, signaling a possible exhaustion phase or potential reversals.
- Neutral Adaptive RSI (around 50): The market is in a balanced state, meaning neither buyers nor sellers are in clear control. The HMA takes on grayish tones to indicate this consolidation.
- Low Adaptive RSI (below 35): The market may be oversold, or bearish momentum could be weakening. The HMA shifts to shades of blue, highlighting potential recovery zones or trend slowdowns.
Why This Combination is Powerful:
- While the HMA excels in tracking trends and reducing lag, it does not provide information about momentum strength on its own.
- The Adaptive RSI bridges this gap by adding a clear visual layer that helps traders assess whether a trend is likely to continue, consolidate, or reverse.
- This makes the indicator particularly useful for spotting trend exhaustion and confirming momentum shifts in real-time.
Best Use Cases:
- Works effectively on timeframes from 1 hour (1H) to 1 day (1D), making it suitable for swing trading and position trading.
- Particularly useful for trading indices (SPY), stocks, forex, and cryptocurrencies, where momentum shifts are frequent.
- Helps identify not just trend direction but also whether that trend is gaining or losing strength.
Recommended Complementary Indicators:
- Adaptive Trend Finder: Helps identify the dominant long-term trend.
- Williams Fractals Ultimate: Provides key reversal points to validate trend shifts.
- RVOL (Relative Volume): Confirms significant moves based on volume strength.
This enhanced HMA with Adaptive RSI provides a powerful, intuitive visual tool that makes trend analysis and momentum interpretation more effective and efficient.
This indicator is for educational and informational purposes only. It should not be considered financial advice or a guarantee of performance. Always conduct your own research and use proper risk management when trading. Past performance does not guarantee future results.
Adaptive Trend FinderAdaptive Trend Finder - The Ultimate Trend Detection Tool
Introducing Adaptive Trend Finder, the next evolution of trend analysis on TradingView. This powerful indicator is an enhanced and refined version of Adaptive Trend Finder (Log), designed to offer even greater flexibility, accuracy, and ease of use.
What’s New?
Unlike the previous version, Adaptive Trend Finder allows users to fully configure and adjust settings directly within the indicator menu, eliminating the need to modify chart settings manually. A major improvement is that users no longer need to adjust the chart's logarithmic scale manually in the chart settings; this can now be done directly within the indicator options, ensuring a smoother and more efficient experience. This makes it easier to switch between linear and logarithmic scaling without disrupting the analysis. This provides a seamless user experience where traders can instantly adapt the indicator to their needs without extra steps.
One of the most significant improvements is the complete code overhaul, which now enables simultaneous visualization of both long-term and short-term trend channels without needing to add the indicator twice. This not only improves workflow efficiency but also enhances chart readability by allowing traders to monitor multiple trend perspectives at once.
The interface has been entirely redesigned for a more intuitive user experience. Menus are now clearer, better structured, and offer more customization options, making it easier than ever to fine-tune the indicator to fit any trading strategy.
Key Features & Benefits
Automatic Trend Period Selection: The indicator dynamically identifies and applies the strongest trend period, ensuring optimal trend detection with no manual adjustments required. By analyzing historical price correlations, it selects the most statistically relevant trend duration automatically.
Dual Channel Display: Traders can view both long-term and short-term trend channels simultaneously, offering a broader perspective of market movements. This feature eliminates the need to apply the indicator twice, reducing screen clutter and improving efficiency.
Fully Adjustable Settings: Users can customize trend detection parameters directly within the indicator settings. No more switching chart settings – everything is accessible in one place.
Trend Strength & Confidence Metrics: The indicator calculates and displays a confidence score for each detected trend using Pearson correlation values. This helps traders gauge the reliability of a given trend before making decisions.
Midline & Channel Transparency Options: Users can fine-tune the visibility of trend channels, adjusting transparency levels to fit their personal charting style without overwhelming the price chart.
Annualized Return Calculation: For daily and weekly timeframes, the indicator provides an estimate of the trend’s performance over a year, helping traders evaluate potential long-term profitability.
Logarithmic Adjustment Support: Adaptive Trend Finder is compatible with both logarithmic and linear charts. Traders who analyze assets like cryptocurrencies, where log scaling is common, can enable this feature to refine trend calculations.
Intuitive & User-Friendly Interface: The updated menu structure is designed for ease of use, allowing quick and efficient modifications to settings, reducing the learning curve for new users.
Why is this the Best Trend Indicator?
Adaptive Trend Finder stands out as one of the most advanced trend analysis tools available on TradingView. Unlike conventional trend indicators, which rely on fixed parameters or lagging signals, Adaptive Trend Finder dynamically adjusts its settings based on real-time market conditions. By combining automatic trend detection, dual-channel visualization, real-time performance metrics, and an intuitive user interface, this indicator offers an unparalleled edge in trend identification and trading decision-making.
Traders no longer have to rely on guesswork or manually tweak settings to identify trends. Adaptive Trend Finder does the heavy lifting, ensuring that users are always working with the strongest and most reliable trends. The ability to simultaneously display both short-term and long-term trends allows for a more comprehensive market overview, making it ideal for scalpers, swing traders, and long-term investors alike.
With its state-of-the-art algorithms, fully customizable interface, and professional-grade accuracy, Adaptive Trend Finder is undoubtedly one of the most powerful trend indicators available.
Try it today and experience the future of trend analysis.
This indicator is a technical analysis tool designed to assist traders in identifying trends. It does not guarantee future performance or profitability. Users should conduct their own research and apply proper risk management before making trading decisions.
// Created by Julien Eche - @Julien_Eche
Supertrend with RSI FilterThis indicator is an enhanced version of the classic Supertrend, incorporating an RSI (Relative Strength Index) filter to refine trend signals. Here is a detailed explanation of its functionality and key advantages over the traditional Supertrend.
1. Indicator Functionality
The indicator uses ATR (Average True Range) to calculate the Supertrend line, just like the classic version. However, it introduces an additional condition based on RSI to strengthen or weaken the Supertrend color based on market momentum.
2. Interpretation of Colors
The indicator displays the Supertrend line with dynamic colors based on trend direction and RSI strength:
- Uptrend (Supertrend in buy mode):
- Dark green (Teal): RSI above the defined threshold (default 50) → Strong bullish confirmation.
- Light gray: RSI below the threshold → Indicates a weaker uptrend or lack of confirmation.
- Downtrend (Supertrend in sell mode):
- Dark red: RSI below the threshold → Strong bearish confirmation.
- Light gray: RSI above the threshold → Indicates a weaker downtrend or lack of confirmation.
The opacity of the color dynamically adjusts based on how far RSI is from its threshold. The greater the difference, the more vivid the color, signaling a stronger trend.
3. Key Advantages Over the Classic Supertrend
- Filters out false signals: The RSI integration helps reduce false signals by only validating trends when RSI aligns with the Supertrend direction.
- Weakens uncertain signals: When RSI is close to its threshold, the color becomes more transparent, alerting traders to a less reliable trend.
- Classic mode available: The 'Use Classic Supertrend' option allows switching to a standard Supertrend display (fixed red/green) without the RSI effect.
4. Customizable Parameters
- ATR Length & ATR Factor: Define the sensitivity of the Supertrend.
- RSI Period & RSI Threshold: Allow refining the RSI filter based on market volatility.
- Classic mode: Enables/disables the RSI filtering to revert to the original Supertrend.
This indicator is especially valuable for traders looking to refine their trend signals based on market momentum measured by RSI.
This indicator is for informational purposes only and should not be considered financial advice. Trading involves risks, and past performance does not guarantee future results. Always conduct your own analysis before making any trading decisions.
AI Adaptive Oscillator [PhenLabs]📊 Algorithmic Adaptive Oscillator
Version: PineScript™ v6
📌 Description
The AI Adaptive Oscillator is a sophisticated technical indicator that employs ensemble learning and adaptive weighting techniques to analyze market conditions. This innovative oscillator combines multiple traditional technical indicators through an AI-driven approach that continuously evaluates and adjusts component weights based on historical performance. By integrating statistical modeling with machine learning principles, the indicator adapts to changing market dynamics, providing traders with a responsive and reliable tool for market analysis.
🚀 Points of Innovation:
Ensemble learning framework with adaptive component weighting
Performance-based scoring system using directional accuracy
Dynamic volatility-adjusted smoothing mechanism
Intelligent signal filtering with cooldown and magnitude requirements
Signal confidence levels based on multi-factor analysis
🔧 Core Components
Ensemble Framework : Combines up to five technical indicators with performance-weighted integration
Adaptive Weighting : Continuous performance evaluation with automated weight adjustment
Volatility-Based Smoothing : Adapts sensitivity based on current market volatility
Pattern Recognition : Identifies potential reversal patterns with signal qualification criteria
Dynamic Visualization : Professional color schemes with gradient intensity representation
Signal Confidence : Three-tiered confidence assessment for trading signals
🔥 Key Features
The indicator provides comprehensive market analysis through:
Multi-Component Ensemble : Integrates RSI, CCI, Stochastic, MACD, and Volume-weighted momentum
Performance Scoring : Evaluates each component based on directional prediction accuracy
Adaptive Smoothing : Automatically adjusts based on market volatility
Pattern Detection : Identifies potential reversal patterns in overbought/oversold conditions
Signal Filtering : Prevents excessive signals through cooldown periods and minimum change requirements
Confidence Assessment : Displays signal strength through intuitive confidence indicators (average, above average, excellent)
🎨 Visualization
Gradient-Filled Oscillator : Color intensity reflects strength of market movement
Clear Signal Markers : Distinct bullish and bearish pattern signals with confidence indicators
Range Visualization : Clean representation of oscillator values from -6 to 6
Zero Line : Clear demarcation between bullish and bearish territory
Customizable Colors : Color schemes that can be adjusted to match your chart style
Confidence Symbols : Intuitive display of signal confidence (no symbol, +, or ++) alongside direction markers
📖 Usage Guidelines
⚙️ Settings Guide
Color Settings
Bullish Color
Default: #2b62fa (Blue)
This setting controls the color representation for bullish movements in the oscillator. The color appears when the oscillator value is positive (above zero), with intensity indicating the strength of the bullish momentum. A brighter shade indicates stronger bullish pressure.
Bearish Color
Default: #ce9851 (Amber)
This setting determines the color representation for bearish movements in the oscillator. The color appears when the oscillator value is negative (below zero), with intensity reflecting the strength of the bearish momentum. A more saturated shade indicates stronger bearish pressure.
Signal Settings
Signal Cooldown (bars)
Default: 10
Range: 1-50
This parameter sets the minimum number of bars that must pass before a new signal of the same type can be generated. Higher values reduce signal frequency and help prevent overtrading during choppy market conditions. Lower values increase signal sensitivity but may generate more false positives.
Min Change For New Signal
Default: 1.5
Range: 0.5-3.0
This setting defines the minimum required change in oscillator value between consecutive signals of the same type. It ensures that new signals represent meaningful changes in market conditions rather than minor fluctuations. Higher values produce fewer but potentially higher-quality signals, while lower values increase signal frequency.
AI Core Settings
Base Length
Default: 14
Minimum: 2
This fundamental setting determines the primary calculation period for all technical components in the ensemble (RSI, CCI, Stochastic, etc.). It represents the lookback window for each component’s base calculation. Shorter periods create a more responsive but potentially noisier oscillator, while longer periods produce smoother signals with potential lag.
Adaptive Speed
Default: 0.1
Range: 0.01-0.3
Controls how quickly the oscillator adapts to new market conditions through its volatility-adjusted smoothing mechanism. Higher values make the oscillator more responsive to recent price action but potentially more erratic. Lower values create smoother transitions but may lag during rapid market changes. This parameter directly influences the indicator’s adaptiveness to market volatility.
Learning Lookback Period
Default: 150
Minimum: 10
Determines the historical data range used to evaluate each ensemble component’s performance and calculate adaptive weights. This setting controls how far back the AI “learns” from past performance to optimize current signals. Longer periods provide more stable weight distribution but may be slower to adapt to regime changes. Shorter periods adapt more quickly but may overreact to recent anomalies.
Ensemble Size
Default: 5
Range: 2-5
Specifies how many technical components to include in the ensemble calculation.
Understanding The Interaction Between Settings
Base Length and Learning Lookback : The base length determines the reactivity of individual components, while the lookback period determines how their weights are adjusted. These should be balanced according to your timeframe - shorter timeframes benefit from shorter base lengths, while the lookback should generally be 10-15 times the base length for optimal learning.
Adaptive Speed and Signal Cooldown : These settings control sensitivity from different angles. Increasing adaptive speed makes the oscillator more responsive, while reducing signal cooldown increases signal frequency. For conservative trading, keep adaptive speed low and cooldown high; for aggressive trading, do the opposite.
Ensemble Size and Min Change : Larger ensembles provide more stable signals, allowing for a lower minimum change threshold. Smaller ensembles might benefit from a higher threshold to filter out noise.
Understanding Signal Confidence Levels
The indicator provides three distinct confidence levels for both bullish and bearish signals:
Average Confidence (▲ or ▼) : Basic signal that meets the minimum pattern and filtering criteria. These signals indicate potential reversals but with moderate confidence in the prediction. Consider using these as initial alerts that may require additional confirmation.
Above Average Confidence (▲+ or ▼+) : Higher reliability signal with stronger underlying metrics. These signals demonstrate greater consensus among the ensemble components and/or stronger historical performance. They offer increased probability of successful reversals and can be traded with less additional confirmation.
Excellent Confidence (▲++ or ▼++) : Highest quality signals with exceptional underlying metrics. These signals show strong agreement across oscillator components, excellent historical performance, and optimal signal strength. These represent the indicator’s highest conviction trade opportunities and can be prioritized in your trading decisions.
Confidence assessment is calculated through a multi-factor analysis including:
Historical performance of ensemble components
Degree of agreement between different oscillator components
Relative strength of the signal compared to historical thresholds
✅ Best Use Cases:
Identify potential market reversals through oscillator extremes
Filter trade signals based on AI-evaluated component weights
Monitor changing market conditions through oscillator direction and intensity
Confirm trade signals from other indicators with adaptive ensemble validation
Detect early momentum shifts through pattern recognition
Prioritize trading opportunities based on signal confidence levels
Adjust position sizing according to signal confidence (larger for ++ signals, smaller for standard signals)
⚠️ Limitations
Requires sufficient historical data for accurate performance scoring
Ensemble weights may lag during dramatic market condition changes
Higher ensemble sizes require more computational resources
Performance evaluation quality depends on the learning lookback period length
Even high confidence signals should be considered within broader market context
💡 What Makes This Unique
Adaptive Intelligence : Continuously adjusts component weights based on actual performance
Ensemble Methodology : Combines strength of multiple indicators while minimizing individual weaknesses
Volatility-Adjusted Smoothing : Provides appropriate sensitivity across different market conditions
Performance-Based Learning : Utilizes historical accuracy to improve future predictions
Intelligent Signal Filtering : Reduces noise and false signals through sophisticated filtering criteria
Multi-Level Confidence Assessment : Delivers nuanced signal quality information for optimized trading decisions
🔬 How It Works
The indicator processes market data through five main components:
Ensemble Component Calculation :
Normalizes traditional indicators to consistent scale
Includes RSI, CCI, Stochastic, MACD, and volume components
Adapts based on the selected ensemble size
Performance Evaluation :
Analyzes directional accuracy of each component
Calculates continuous performance scores
Determines adaptive component weights
Oscillator Integration :
Combines weighted components into unified oscillator
Applies volatility-based adaptive smoothing
Scales final values to -6 to 6 range
Signal Generation :
Detects potential reversal patterns
Applies cooldown and magnitude filters
Generates clear visual markers for qualified signals
Confidence Assessment :
Evaluates component agreement, historical accuracy, and signal strength
Classifies signals into three confidence tiers (average, above average, excellent)
Displays intuitive confidence indicators (no symbol, +, ++) alongside direction markers
💡 Note:
The AI Adaptive Oscillator performs optimally when used with appropriate timeframe selection and complementary indicators. Its adaptive nature makes it particularly valuable during changing market conditions, where traditional fixed-weight indicators often lose effectiveness. The ensemble approach provides a more robust analysis by leveraging the collective intelligence of multiple technical methodologies. Pay special attention to the signal confidence indicators to optimize your trading decisions - excellent (++) signals often represent the most reliable trade opportunities.
EMA Adaptive Trailing StopThe EMA Adaptive Trailing Stop Strategy is a versatile and comprehensive Pine Script designed for TradingView. This script provides an adaptive trailing stop mechanism that leverages the Exponential Moving Average (EMA) to adjust trailing stops based on market conditions. The strategy dynamically switches between trending and ranging markets by utilizing both Average True Range (ATR) and Average Directional Index (ADX) to detect market conditions.
Key Features:
EMA-Based Trailing Stop:
The script uses the EMA value to set trailing stops precisely. The EMA offers a more responsive calculation to price changes, ensuring closer and more accurate trailing stops that follow market movements effectively.
Market Condition Detection:
The script employs ATR and ADX to distinguish between trending and ranging markets. ATR measures market volatility, while ADX gauges trend strength. The combination of these two indicators provides a more accurate market condition detection.
Customizable Settings:
The script offers various flexible parameters to adjust EMA length, multipliers, and ATR length. Users can customize these settings according to their preferences and trading strategy.
Two Modes:
The script adapts to market conditions by providing two modes: trending mode and ranging mode. In trending mode, the trailing stop is tighter to follow price movements closely, whereas in ranging mode, the trailing stop is looser to accommodate lower volatility.
Entry and Exit Conditions:
The script detects market conditions to set buy and sell signals. These conditions include the calculations of EMA, ATR, and ADX to ensure the signals generated are valid and profitable.
Alerts:
The script provides buy and sell signals through alert conditions for efficient trade management. Users can enable these alerts to get real-time notifications when valid buy or sell signals are detected.
Suitable for Scalping and Swing Trading:
The script is well-suited for both scalping and swing trading strategies. Scalpers can benefit from the responsive and tighter trailing stops during trending conditions, while swing traders can take advantage of the adaptive and looser trailing stops during ranging conditions, allowing them to capture larger price movements.
Explanation of Mode 1 and Mode 2:
Mode 1: Trending Market:
In this mode, the market is identified as trending based on the ADX and ATR values.
LONG 1: This label indicates a buy signal in the trending market mode. It signifies that the trailing stop has been activated and a long position (buy) should be taken when the market is trending.
SHORT 1: This label indicates a sell signal in the trending market mode. It signifies that the trailing stop has been activated and a short position (sell) should be taken when the market is trending.
Mode 2: Ranging Market:
In this mode, the market is identified as ranging based on the ADX and ATR values.
LONG 2: This label indicates a buy signal in the ranging market mode. It signifies that the trailing stop has been activated and a long position (buy) should be taken with a looser trailing stop when the market is ranging.
SHORT 2: This label indicates a sell signal in the ranging market mode. It signifies that the trailing stop has been activated and a short position (sell) should be taken with a looser trailing stop when the market is ranging.
Technical Usage:
Variable Initialization:
The script initializes variables to store values such as trailing stop, long position status, and short position status.
Market Condition Detection:
The script calculates ATR and ADX values to detect whether the market is trending or ranging. This includes the use of f_adx function to calculate ADX values and determine market conditions.
EMA-Based Trailing Stop Calculation:
The script adjusts the trailing stop based on EMA values and ATR. The calculation involves customizable multipliers and parameters that influence the trailing stop's precision.
Plot Trailing Stop:
The script displays the trailing stop on the chart for clear visualization. This includes plotting the trailing stop line with appropriate colors to indicate long and short positions.
Entry and Exit Conditions:
The script determines the entry (buy) and exit (sell) conditions based on market condition detection and trailing stop settings. These conditions are crucial for generating valid buy or sell signals.
Plotshape and Alert:
The script provides plotshapes for buy and sell signals and sets up alert conditions for real-time notifications when a valid buy or sell signal is detected.
Adaptive Supply and Demand [EdgeTerminal]Adaptive Supply and Demand is a dynamic supply and demand indicator with a few unique twists. It considers volume pressure, volatility-based adjustments and multi-time frame momentum for confidence scoring (multi-step confirmation) to generate dynamic lines that adjust based on the market and also to generate dynamic support/resistance levels for the supply and demand lines.
The dynamic support and resistance lines shown gives you a better situational awareness of the current state of the market and add more context to why the market is moving into a certain direction.
> Trading Scenarios
When the confidence score is over 80%, strong volume pressure in trend direction (up or down), volatility is low and momentum is aligned across timeframes, there is an indication of a strong upward or downward trend.
When the supply and demand line crossover, the confidence score is over 75% and the volume pressure is shifting, this can be an indicator of trend reversal. Use tight initial stops, scale into position as trend develops, monitor the volume pressure for continuation and wait for confidence confirmation.
When the confiance score is below 60%, the volume pressure is choppy, volatility is high, you want to avoid trading or reduce position size, wait for confidence improvements, use support and resistance for entries/exits and use tighter stops due to market conditions. This is an indication of a ranging market.
Another scenario is when there is a sudden volume pressure increase, and a raising confidence score, the volatility is expanding and the bar momentum is aligning the volatility direction. This can indicate a breakout scenario.
> How it Works
1. Volume Pressure Analysis
Volume Pressure Analysis is a key component that measures the true buying and selling force in the market. Here's a detailed breakdown. The idea is to standardize volume to prevent large spikes from skewing results.
The indicator employs an adaptive volume normalization technique to detect genuine buying and selling pressure.
It takes current volume and divides it by average volume.
If normVol > 1: Current volume is above average
If normVol < 1: Current volume is below average
An example if this would be If current volume is 1500 and average is 1000, normVol = 1.5 (50% above average)
Another component of the volume pressure analysis is the Price Change Calculation sub-module. The purpose of this is to measure price movement relative to recent average.
It works by subtracting the average price from the current price. If the value is positive, price is average and if negative, price is below average.
Finally, the volume pressure is calculated to combine volume and price for true pressure reading.
2. Savitzky-Golay Filtering
SG filtering implements advanced signal smoothing while preserving important trend features. It uses weighted moving average approximation, preserves higher moments of data and reduces noise while maintaining signal integrity.
This results in smoother signal lines, reduced false crossovers and better trend identification. Traditional moving averages tend to lag and smooth out important features. Additionally, simple moving averages can miss critical turning points and regular smoothing can delay signal generation.
SG filtering preserves higher moments such as peaks, valleys and trends, reduces noise while maintaining signal sharpness.
It works by creating a symmetric weighting scheme. This way center points get the highest weights while edge points get the lowest weight.
3. Parkinson's Volatility
Parkinson's Volatility is an advanced volatility measurement formula using high-low range data. It uses high-low range for volatility calculation, incorporates logarithmic returns and annualized the volatility measure.
This results in more accurate volatility measurement, better risk assessment and dynamic signal sensitivity.
4. Multi-timeframe Momentum
This combines signals from each module for each timeframe to calculate momentum across three timeframes. It also applies weighted importance to each timeframe and generates a composite momentum signal.
This results in a more comprehensive trend analysis, reduced timeframe bias and better trend confirmation.
> Indicator Settings
Short-term Period:
Lower values makes it more sensitive, meaning it will generate more signals. Higher values makes it less sensitive, resulting in fewer signals. We recommend a 5 to 15 range for day trading, and 10 to 20 for swing trading
Medium-term Period:
Lower values result in faster trend confirmation and higher values show slower and more reliable confirmation. We recommend a range of 15-25 for day trading and 20-30 for swing trading.
Long-term Period:
Lower values makes it more responsive to trend changes and higher values are better for major trend identification. We recommend a range of 40-60 for day trading and 50-100 for swing trading.
Volume Analysis Window:
Lower values result in more sensitivity to volume changes and higher values result in smoother volume analysis. The optimal range is 15-25 for most trading styles.
Confidence Threshold:
Lower values generate more signals but quality decreases. Higher values generate fewer signals but accuracy increases.The optimal range is 0.65-0.8 for most trading conditions.
