Filter Bar1. Indicator Name
Filter Bar
2. One-line Introduction
A trend-aware bar coloring system that visualizes market direction and strength through adaptive transparency based on regression scoring.
3. General Overview
Filter Bar+ is a minimalist but powerful trend visualization tool that colors chart bars according to market direction and momentum strength.
It analyzes the linear regression trend alignment over a specified lookback period and uses a pairwise comparison algorithm to determine whether the market is in a bullish, bearish, or neutral state.
The result is a "trend score" that gets normalized to reflect trend intensity (0~1).
Bar colors are then dynamically updated using the specified bullish or bearish base colors, where higher intensity results in more opaque (darker) bars, and weaker trends lead to lighter, faded tones.
If no strong trend is detected, bars are shown in gray, signaling indecision or neutrality.
The strength of this indicator lies in its simplicity—it doesn’t draw lines, waves, or shapes, but overlays insight directly onto the chart through smart color cues.
It’s particularly effective as a background filter for price action traders, scalpers, and anyone who prefers clean charts but still wants embedded directional context.
4. Key Advantages
🎨 Adaptive Bar Coloring
Bar color opacity increases with trend strength, offering instant visual confirmation without clutter.
📊 Quantified Trend Direction
Uses a regression-based scoring system to reliably detect uptrends, downtrends, or sideways markets.
⚖️ Customizable Sensitivity
Parameters like lookback period and tolerance percentage give users full control over signal responsiveness.
🧼 Clean Chart Presentation
No lines, shapes, or overlays—just color-coded bars that blend into your existing chart setup.
🚀 Lightweight & Fast
Minimal computational load ensures it works smoothly even on lower-end devices or multiple chart setups.
🔒 Secure Internal Logic
Algorithm is neatly encapsulated and optimized, with no critical logic exposed.
📘 Indicator User Guide
📌 Basic Concept
Filter Bar+ evaluates trend direction and strength using a pairwise comparison of linear regression values.
The result determines whether the market is bullish, bearish, or neutral, and adjusts bar colors accordingly.
It visually amplifies the current market state without drawing any indicators on the chart.
⚙️ Settings Explained
Lookback Period: Number of bars used to compare regression values
Range Tolerance (%): Minimum score required to label a trend as bullish or bearish
Regression Source: Data input used for regression (default: close)
Linear Regression Length: Period for generating the base regression line
Bull/Bear Base Colors: Choose colors to represent bullish or bearish bars
📈 Buy Timing Example
Bars are green (or user-set bullish color) and becoming more vivid
Indicates a strengthening bullish trend; helpful when used alongside breakout confirmation or support zones
📉 Sell Timing Example
Bars turn red (or your custom bearish color) with increasing opacity
Signals growing bearish pressure; acts as confirmation during short setups or breakdowns
🧪 Recommended Use Cases
Combine with volume, RSI, or price action setups for direction filtering
Ideal for clean chart strategies where visual simplicity is preferred
Use as a confirmation layer to reduce noise in sideways markets
🔒 Precautions
This is a visual filter, not a signal generator—use alongside other strategies for entries/exits
In choppy markets, bars may flicker between colors—adjust sensitivity as needed
Works best when you already have a directional thesis and want to validate it visually
Always test settings for your asset/timeframe before applying in live trades
Trendfollowing
Momentum Tide [Alpha Extract]A sophisticated momentum-based trend identification system that measures normalized price deviation from an EMA baseline using ATR scaling and hyperbolic tangent smoothing for precise trend state classification. Utilizing advanced signal processing with configurable neutral bands and slope sensitivity adjustments, this indicator delivers institutional-grade momentum analysis with continuous strength measurement and visual trend confirmation. The system's three-state classification (bullish, bearish, neutral) combined with dynamic color intensity scaling provides comprehensive market momentum assessment across varying volatility conditions.
🔶 Advanced Baseline Deviation Framework
Implements EMA-based baseline calculation with ATR-normalized deviation measurement to create volatility-adjusted momentum signals. The system calculates raw price deviation from the baseline, scales by ATR and slope sensitivity factor, then applies exponential smoothing for stable signal generation with reduced noise and false transitions.
// Core Momentum Calculation
Baseline = ta.ema(close, Baseline_Length)
ATR_Value = ta.atr(ATR_Length)
Raw_Deviation = (close - Baseline) / (ATR_Value * Slope_Scaler)
Signal = ta.ema(Raw_Deviation, Signal_Smoothing)
🔶 Hyperbolic Tangent Normalization Engine
Features sophisticated tanh transformation that clamps raw deviation signals into normalized -1 to +1 range for consistent interpretation across all market conditions. The system applies safe exponential calculations with value capping to prevent overflow while maintaining signal sensitivity, creating bounded momentum readings suitable for systematic threshold analysis.
// Tanh Normalization
Clamped_Signal = tanh(Signal) // Bounded to
Strength = abs(Clamped_Signal) // Momentum intensity
🔶 Three-State Classification System
Implements intelligent trend state determination using configurable neutral band thresholds to reduce whipsaw signals during ranging conditions. The system classifies market as bullish (+1) when momentum exceeds upper neutral band, bearish (-1) below lower neutral band, and neutral (0) within the band, providing clear directional bias with built-in consolidation recognition.
🔶 Dynamic Color Intensity Architecture
Provides advanced visual feedback through momentum strength-based color intensity modulation, where stronger trends display more opaque colors and weaker trends show increased transparency. The system dynamically adjusts color alpha values based on absolute momentum strength, creating intuitive visual representation of trend conviction across baseline, candles, and bars.
🔶 Trend Strength Meter Visualization
Features innovative horizontal gradient meter displaying real-time momentum position across bear-to-bull spectrum with 24-segment resolution. The system creates smooth color transitions from bearish red through neutral gray to bullish green, with arrow indicator showing precise momentum location for instant trend strength assessment without cluttering the price chart.
🔶 Intelligent Flip Detection System
Generates transition markers when trend state changes from neutral/bearish to bullish or neutral/bullish to bearish, with duplicate signal suppression to prevent marker clustering. The system tracks previous signal states and only plots new markers on genuine trend reversals, providing clean entry signal visualization for systematic trading approaches.
snapshot
🔶 Configurable Neutral Band Framework
Implements adjustable neutral zone width using ATR percentage parameters to optimize signal frequency for different trading styles and market conditions. Wider bands reduce flip frequency for position trading while tighter bands increase sensitivity for active trading strategies, enabling customization without code modification.
🔶 Slope Sensitivity Adjustment
Features slope scaler parameter that modulates ATR normalization factor, controlling signal smoothness versus responsiveness trade-off. Higher values create smoother momentum readings with fewer transitions while lower values increase snappiness for faster reaction to price changes, allowing optimization across different volatility regimes and timeframes.
🔶 Comprehensive Visual Integration
Provides multi-dimensional trend visualization through color-coded baseline overlay, momentum-synchronized candle coloring, and bar color modification with configurable display toggles. The system includes optional flip markers and strength meter with position control for complete chart integration without visual overload.
🔶 Performance Optimization Framework
Utilizes efficient calculation methods with optimized table management for strength meter updates and minimal computational overhead for real-time momentum processing. The system includes intelligent state tracking and safe mathematical operations to prevent errors during extreme market conditions while maintaining consistent performance.
🔶 Why Choose Momentum Tide ?
This indicator delivers sophisticated momentum-based trend analysis through normalized deviation measurement and intelligent three-state classification. Unlike traditional momentum oscillators that operate in separate windows, Momentum Tide integrates directly with price action through baseline overlay and candle coloring while providing the analytical depth of bounded momentum measurement. The system's combination of tanh normalization, configurable neutral bands, dynamic color intensity, and innovative strength meter makes it essential for traders seeking adaptive trend-following approaches with clear visual feedback across cryptocurrency, forex, and equity markets. The three-state system naturally filters ranging periods while the momentum strength measurement enables position sizing and confidence assessment for systematic trading strategies.
Change in State of Delivery CISD [AlgoAlpha]🟠 OVERVIEW
This script tracks how price “changes delivery” after failed attempts to push in one direction. It builds swing levels from pivots, watches for those levels to be wicked, and then checks if price delivers cleanly in the opposite direction. When the pattern meets the script’s tolerance rules, it marks a Change in State of Delivery (CISD). These CISD levels are drawn as origin lines and are used to spot shifts in intent, failed pushes, and continuation attempts. A CISD becomes stronger when it forms after opposing liquidity is swept within a defined lookback.
🟠 CONCEPTS
The script first defines structure using swing highs/lows. These levels act as potential liquidity points. When price wicks through a swing, the script registers a mitigation event. After this, it looks for a reversal-style candle sequence: a failed push, followed by a counter-move strong enough to pass a tolerance ratio. This ratio compares how far price expanded away from the failed attempt versus the counter-move that followed. If the ratio is high enough, this becomes a CISD. The idea is simple: liquidity interaction sets context , and the tolerance logic identifies actual intent . CISD levels and sweep markers combine these two ideas into a clean map of where delivery flipped.
🟠 FEATURES
Liquidity tracking: marks swing highs/lows and updates them until expiry
Liquidity sweep confirmation when CISD aligns with recent mitigations
Alert conditions for all key events: mitigations, CISDs, and strong CISDs
🟠 USAGE
Setup : Add the script to your chart. Use it on any timeframe where swing behavior matters. Set the Swing Period for how wide a pivot must be. Set Noise Filter to control how strict the CISD detection is. Liquidity Lookback defines how recent a wick must be to confirm a sweep.
Read the chart : Origin lines mark where the CISD began. A green line signals bullish intent; a red line signals bearish intent. ▲ and ▼ shapes show CISDs that form after liquidity is swept, these mark strong signals for potential entry. Swing dots show recent swing highs/lows. Candle colors follow the latest CISD trend.
Settings that matter : Increasing Swing Period produces fewer but stronger swings. Raising Noise Filter requires cleaner counter-moves and reduces false CISDs. Liquidity Lookback controls how strict the sweep confirmation is. Expiry Bars decides how long swing levels remain active.
Screener (SSA) [AlgoAlpha]🟠 OVERVIEW
This script is a multi-symbol screener that serves as a dashboard companion to the "Smart Signals Assistant (SSA)" indicator. Its purpose is to monitor the entire suite of SSA components—from the core signals to all confluence tools—across a customizable watchlist of up to 18 assets. By displaying the real-time status of each indicator in a single table, it allows traders to get a bird's-eye view of the market, quickly identify assets with strong trend confluence, and filter for high-probability setups without needing to switch charts.
The screener is designed to mirror the modularity of the main SSA indicator, allowing you to enable or disable components in the table to match your preferred trading dashboard.
🟠 CONCEPTS
The screener is built directly on the analytical framework of the Smart Signals Assistant, applying its complex, proprietary algorithms to each symbol in your watchlist and summarizing the results. The combination of these different analytical concepts is what gives the screener its utility, as it helps traders find opportunities where multiple, distinct strategies align.
Each column in the table represents a core trading concept:
Smart Signals: This is the primary signal engine, designed to identify potential entry points. It operates in different modes to capture both long-term swings and faster scalping opportunities.
Fair Value Trail (FVT): This component provides a dynamic, volatility-adjusted baseline for the trend. It acts as a form of dynamic support or resistance, helping to confirm the validity of a trend shown by the Smart Signals.
Trend Spine: This tool is designed to identify the underlying "backbone" of the market's trend. It filters out short-term price noise to provide a more stable, clear indication of the dominant market direction.
Trend Bias: This measures the strength and conviction behind a trend. It helps distinguish between a strong, accelerating move and a weak, decelerating one, adding a layer of momentum analysis.
Firmament Clouds: These are volatility-based bands that create dynamic overbought and oversold zones. They help identify when price is potentially overextended and due for a pullback or consolidation.
Trend-Range Classifier (TRC): A machine-learning model that analyzes market characteristics to classify the current environment as either "Trending" or "Ranging." This is crucial for helping traders apply the right strategy for the current conditions.
🟠 FEATURES
This screener organizes the complex data from the SSA indicator into a simple, color-coded table. Here is a breakdown of each column and its possible values:
Asset: Displays the ticker symbol for the asset being analyzed.
Smart Signals: Shows the latest signal from the core engine.
▲: A standard bullish signal has been detected.
▼: A standard bearish signal has been detected.
▲+: A strong bullish signal with higher conviction has been detected.
▼+: A strong bearish signal with higher conviction has been detected.
Fair Value Trail: Indicates the trend direction based on the volatility trail.
▲: The FVT is in a bullish trend (acting as dynamic support).
▼: The FVT is in a bearish trend (acting as dynamic resistance).
Trend Spine: Shows the direction of the core underlying trend.
▲: The underlying trend backbone is bullish.
▼: The underlying trend backbone is bearish.
Trend Bias: Measures the current momentum strength.
Strong▲: Strong and accelerating bullish momentum.
Weak▲: Bullish momentum exists but is weakening.
Strong▼: Strong and accelerating bearish momentum.
Weak▼: Bearish momentum exists but is weakening.
Firmament Clouds: Identifies overbought/oversold conditions relative to volatility.
Very Overbought / Overbought: Price is significantly extended above its recent range.
Very Oversold / Oversold: Price is significantly extended below its recent range.
Neutral: Price is trading within its normal volatility range.
Trend-Range Classifier: Displays the market state as determined by the ML model.
Trend: The market is in a trending environment, suitable for trend-following strategies.
Range: The market is in a ranging or consolidating environment, suitable for mean-reversion strategies.
Exit Signal Count: Tracks the number of take-profit signals that have occurred since the last primary Smart Signal.
0, 1, 2, 3...: A numerical count of exit signals. A higher number suggests a trend may be maturing or exhausting.
🟠 USAGE
The main purpose of the screener is to quickly identify assets where multiple components of the SSA system are in alignment, indicating a high-confluence trading opportunity.
1. Setup and Configuration:
Add the screener to your chart.
Go into the settings and populate the "Watchlist" group with the symbols you wish to monitor.
Ensure the settings for the components (Time Horizon, Signal Mode, etc.) are synchronized with the settings on your main SSA indicator for consistency.
2. Interpreting the Columns for Trading Decisions:
Start with the Big Picture (TRC): First, look at the "Trend-Range Classifier" column. If it shows "Trend," you should be looking for trend-following setups. If it shows "Range," you might avoid taking strong trend signals.
Establish Directional Bias (Spine & Bias): For trend-following, look for assets where the "Trend Spine" and "Trend Bias" agree. A "▲" in the Spine column combined with a "Strong▲" in the Bias column indicates a healthy and robust uptrend.
Time Your Entry (Smart Signals): Once you have an asset with a clear bias, watch the "Smart Signals" column for a fresh signal that aligns with that bias. A "▲+" signal appearing in an asset with a strong bullish bias across other columns is a high-confluence entry point.
Add Context (FVT & Clouds): Use the "Fair Value Trail" and "Firmament Clouds" to refine your entry. A buy signal is generally stronger if the FVT is also bullish ("▲") and the price is not in a "Very Overbought" state according to the clouds.
Manage the Trade (Exit Count): After entering a trade, keep an eye on the "Exit Signal Count." As the number increases, it serves as a warning that the trend is becoming extended and it might be time to take partial profits or tighten your stop-loss.
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Screener (ILPAC) [AlgoAlpha]🟠 OVERVIEW
This script is a powerful multi-symbol scanner designed to work as a companion to the "Institutional Liquidity & PA Concepts" (ILPAC) indicator. It allows you to monitor the key price action and liquidity signals from the ILPAC suite across a watchlist of up to 18 assets, all from a single dashboard. The primary goal of this tool is to provide a high-level market overview, enabling you to efficiently spot assets that are showing strong structural trends, interacting with key liquidity zones, or exhibiting signs of FOMO-driven volatility.
Instead of switching between dozens of charts, you can use this screener to quickly filter for assets that meet your specific trading criteria based on the advanced concepts of market structure, liquidity analysis, trend lines, and market sentiment.
🟠 CONCEPTS
The screener is built upon the core analytical engine of the "Institutional Liquidity & PA Concepts" indicator. It applies the proprietary algorithms of the ILPAC indicator to each symbol in your watchlist and presents the results in an easy-to-digest table. The concepts are combined to create a holistic view of the market.
Each column in the table is a window into a specific trading concept:
Market Structure: This is the foundation of price action analysis. The screener identifies the current market trend (bullish or bearish) by tracking swing highs and lows. It also flags critical events like a Break of Structure (BOS), which signals trend continuation, and a Change of Character (CHoCH), which suggests a potential trend reversal.
Liquidity Analysis: The screener analyzes order flow to determine where significant liquidity is resting. The "Liquidity Bias" column shows the net direction of this pressure, while the "Liquidity Event" column alerts you when price interacts with these key zones, either by forming a new one or mitigating an old one.
Trend Lines: This concept automates the classic technical analysis technique of drawing trend lines. The screener identifies significant swing points to form trend lines and then monitors them, alerting you to potential trend continuations or breakouts.
FOMO Bubbles: This concept measures crowd psychology by identifying sudden spikes in volume and price movement that are characteristic of "Fear of Missing Out." These signals can help identify potential trend exhaustion points or the start of a speculative rally.
By presenting these distinct but interconnected concepts together, the screener provides a multi-faceted view that allows traders to build a strong, confluence-based trading thesis.
🟠 FEATURES
This screener organizes a vast amount of data into a simple, color-coded table. Here is a breakdown of each column and the values you can expect to see:
Asset: Displays the ticker symbol for the asset being analyzed.
Market Structure: Shows the dominant trend based on swing highs and lows.
Bull: The asset is in a structural uptrend (making higher highs and higher lows).
Bear: The asset is in a structural downtrend (making lower highs and lower lows).
Detecting: The trend is neutral or a clear structure has not yet been established.
Structure Event: Flags the most recent significant market structure event.
Bull CHoCH: A bullish Change of Character, signaling a potential shift from a downtrend to an uptrend.
Bear CHoCH: A bearish Change of Character, signaling a potential shift from an uptrend to a downtrend.
Bull BOS: A bullish Break of Structure, confirming the continuation of an uptrend.
Bear BOS: A bearish Break of Structure, confirming the continuation of a downtrend.
–: No significant event has occurred recently.
Latest Swing Label: Identifies the most recently confirmed swing point.
HH: Higher High.
HL: Higher Low.
LH: Lower High.
LL: Lower Low.
–: No new swing point has been confirmed.
Liquidity Bias: Measures the net direction of liquidity and its relative strength.
▲ : A bullish liquidity bias, where the number indicates the strength.
▼ : A bearish liquidity bias, where the number indicates the strength.
Balanced: Liquidity is relatively balanced between buyers and sellers.
Liquidity Event: Indicates recent interactions with key liquidity zones.
New▲: A new bullish liquidity zone has just formed.
New▼: A new bearish liquidity zone has just formed.
Mit▲: Price has just tested (mitigated) a key bullish liquidity zone.
Mit▼: Price has just tested (mitigated) a key bearish liquidity zone.
–: No recent interaction.
Trend Line: Displays the status of automatically drawn trend lines.
Break▲: Price has broken above a key bearish trend line.
Break▼: Price has broken below a key bullish trend line.
Bull TL: Price is respecting an active bullish trend line.
Bear TL: Price is respecting an active bearish trend line.
–: No significant trend line is currently active.
FOMO: Detects sentiment-driven price moves of varying intensity.
Big▲/Med▲/Small▲: A bullish FOMO bubble has been detected (large, medium, or small).
Big▼/Med▼/Small▼: A bearish FOMO bubble has been detected (large, medium, or small).
–: No FOMO activity detected.
🟠 USAGE
The primary way to use this screener is to quickly scan your watchlist for assets that exhibit a confluence of bullish or bearish signals, which can significantly improve the probability of a trade.
1. Setup and Configuration:
Add the screener to your chart.
Open the settings and populate the "Watchlist" section with the symbols you want to track.
Fine-tune the input settings for each component (Market Structure, Liquidity, etc.) to match your preferred trading style. These settings will apply to all symbols in the table.
2. Interpreting the Columns for Trading Decisions:
Market Structure Columns: Use the first three structure columns to define your trading bias. For a high-probability long setup, you would look for an asset with a "Bull" structure, a recent "Bull BOS" event, and a "HL" as the latest swing point. This confirms the uptrend is healthy and ongoing.
Liquidity Columns: These are crucial for identifying key price levels. A strong "Liquidity Bias" can confirm your directional bias. A "Mit▲" (mitigation) event at a support level can be a powerful entry trigger, as it shows that institutional buy orders are defending that zone.
Trend Line Column: This is ideal for breakout traders. A "Break▲" signal can serve as an excellent entry confirmation, especially if the overall "Market Structure" is already "Bull".
FOMO Column: This column is best used for identifying potential exhaustion points. For instance, if you are in a long trade and a "Big▲" FOMO signal appears after a strong rally, it could be a sign that the move is overextended and it's a good time to consider taking profits.
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Screener (MC) [AlgoAlpha]🟠 OVERVIEW
This script is a multi-symbol scanner that works as a companion to the "Momentum Concepts" indicator. It provides a comprehensive dashboard view, allowing traders to monitor the momentum signals of up to 18 different assets in real-time from a single chart. The main purpose is to offer a bird's-eye view of the market, helping you quickly identify assets with strong momentum confluence or potential reversal opportunities without having to switch between different charts.
The screener displays the status of all key components from the Momentum Concepts indicator, including the Fast Oscillator, Scalper's Momentum, Momentum Impulse Oscillator, and Hidden Liquidity Flow, organizing them into a clear and easy-to-read table.
🟠 CONCEPTS
The core of this screener is built upon the analytical framework of the "Momentum Concepts" indicator, which evaluates market momentum across multiple layers: short-term, medium-term, and long-term. This screener applies those complex, proprietary calculations to each symbol in your watchlist and visualizes the current state of each component.
Each column in the table represents a specific aspect of momentum analysis:
Fast Oscillator Columns: These columns reflect the short-term momentum. They show the immediate trend direction, whether the asset is in an overbought or oversold condition, and flag high-probability events like divergences, reversals, or diminishing momentum.
Scalper's Momentum Column: This column gives insight into medium-term momentum. It distinguishes between strong, sustained moves and weakening, corrective moves, which is useful for gauging the health of a trend.
Momentum Impulse Column: This column represents the dominant, long-term trend bias. It helps you understand the underlying market regime (bullish, bearish, or consolidating) to align your trades with the bigger picture.
Hidden Liquidity Flow Column: This column provides a unique view into the market's underlying liquidity dynamics. It signals whether there is net buying or selling pressure and uses special coloring to highlight periods of unusually high liquidity activity, which often precedes volatile price movements.
By combining these perspectives, the screener justifies its utility by enabling traders to make more informed decisions based on multi-layered signal confluence.
🟠 FEATURES
This screener organizes momentum data into several key columns. Here is a breakdown of each column and its possible values:
Asset: Displays the symbol for the asset being analyzed in that row.
Fast Oscillator Trend: Shows the immediate, short-term momentum direction.
▲: Indicates a bullish short-term trend.
▼: Indicates a bearish short-term trend.
–: Indicates a neutral or transitional state.
Fast Oscillator Valuation: Measures whether the asset is in a short-term overbought or oversold state.
OB: Signals an "Overbought" condition, often associated with bullish exhaustion.
OS: Signals an "Oversold" condition, often associated with bearish exhaustion.
Neutral: The asset is trading in a neutral zone, neither overbought nor oversold.
Scalper's Momentum: Assesses the strength and direction of medium-term momentum.
Strong▲: Strong bullish momentum.
Weak▲: Bullish momentum exists but is weakening or corrective.
Strong▼: Strong bearish momentum.
Weak▼: Bearish momentum exists but is weakening or corrective.
–: Neutral or no clear medium-term momentum.
Momentum Impulse: Identifies the dominant, long-term trend bias. A colored background indicates that the momentum is in a strong "impulse" phase.
▲: Indicates a bullish long-term bias.
▼: Indicates a bearish long-term bias.
0: Indicates a neutral or ranging market condition.
Hidden Liquidity Flow: Tracks underlying buying and selling pressure. The background color highlights periods of unusual liquidity activity.
▲: Positive liquidity flow, suggesting net buying pressure.
▼: Negative liquidity flow, suggesting net selling pressure.
–: Neutral liquidity flow.
Dim. Momentum: Provides an early warning that short-term momentum is beginning to fade.
● (Bullish Color): Bullish momentum is weakening.
● (Bearish Color): Bearish momentum is weakening.
–: No diminishing momentum detected.
Divergence: Flags classic or hidden divergences between price and the Fast Oscillator.
Div▲: A bullish divergence has been detected.
Div▼: A bearish divergence has been detected.
–: No active divergence signal.
Reversal: Signals a potential reversal when the Fast Oscillator crosses its trend line from an overbought or oversold zone.
Rev▲: A bullish reversal signal has occurred.
Rev▼: A bearish reversal signal has occurred.
–: No active reversal signal.
🟠 USAGE
The primary function of this screener is to quickly identify trading opportunities and filter setups based on momentum confluence across your watchlist.
1. Setup and Configuration:
Add the indicator to your chart.
Go into the script settings and populate the "Watchlist" group with the symbols you wish to monitor.
Adjust the settings for the various momentum components (Fast Oscillator, Scalper's Momentum, etc.) to align with your trading strategy. These settings will be universally applied to all symbols in the screener.
2. Interpreting the Columns for Trading Decisions:
Momentum Impulse & Hidden Liquidity Flow: Use these columns to establish a directional bias. A bullish "▲" in both columns on an asset suggests a strong underlying uptrend with supportive buying pressure, making it a good candidate for long positions.
Scalper's Momentum: Use this for entry timing and trend health. A "Strong▲" reading can confirm the strength of an uptrend, while a shift to "Weak▲" might suggest it's time to tighten stops or look for an exit.
Fast Oscillator Trend & Valuation: These are best for precise entry triggers. For a "buy the dip" strategy in an uptrend, you could wait for the Fast Oscillator to show "OS" (Oversold) and then enter when the "Trend" column flips back to "▲".
Dim. Momentum: This is an excellent take-profit signal. If you are in a long position and a bullish-colored "●" appears, it's a warning that the upward move is losing steam, and you might consider closing your trade.
Divergence & Reversal: These columns are for identifying potential turning points. A "Div▲" or "Rev▲" signal is a strong alert that a downtrend might be ending, making the asset a prime candidate to watch for a long entry.
3. Finding High-Probability Setups:
Trend Confluence: Look for assets where multiple components show alignment. For example, an ideal long setup might show a bullish "Momentum Impulse" (▲), a "Strong▲" reading in "Scalper's Momentum," and a bullish trend in the "Fast Oscillator." This indicates that the long-term, medium-term, and short-term momentums are all in agreement.
Reversal and Exhaustion: Use the "Divergence" and "Reversal" columns to spot potential turning points. A "Div▲" signal appearing in an asset that is in an oversold "Fast Oscillator Valuation" zone can be a strong indication of an upcoming bounce.
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Relative Performance Binary FilterDescription:
This indicator monitors the relative performance of 30 selected crypto assets and generates a binary signal for each: 1 if the asset’s price has increased above a user-defined threshold over a specified lookback period, 0 otherwise. The script produces a JSON-formatted output suitable for webhooks, allowing you to send the signals to external applications like Google Sheets.
Key Features:
Configurable lookback period, price source, and performance threshold.
Supports confirmed or real-time bar data.
Monitors 30 crypto assets simultaneously.
Produces a one-line JSON output with batch grouping for easy webhook integration.
Includes an optional visual sum plot showing how many assets are above the threshold at any time.
Use Cases:
Automate performance tracking across multiple crypto assets.
Feed binary signals into external dashboards, trading bots, or Google Sheets.
Quickly identify which assets are outperforming a set threshold.
Trend Pulse Algo (LTM)Trend Pulse Algo LTM Indicator Description
Overview
Trend Pulse Algo LTM is an advanced multi layer technical indicator designed for TradingView that combines moving average MA crossovers confirmation signals pivot based structure analysis imbalance zone detection and overextension warnings to identify potential trend shifts continuations and reversal points. It aims to provide traders with reliable entry and exit signals in trending markets while highlighting areas of market inefficiency imbalances and overextended price moves that could signal exhaustion.
This indicator operates on a pulse concept where it detects rhythmic shifts in market momentum through layered MAs a quick MA for short term sensitivity a mid MA for intermediate confirmation and a long MA as a baseline trend filter. Signals are generated based on alignments and crosses between these MAs but with added layers of confirmation to reduce false positives such as requiring consecutive bars above below the long MA and breaks of prior pivot highs lows. It incorporates higher timeframe HTF analysis for imbalance zones to capture broader market context making it suitable for swing trading trend following or scalping on lower timeframes when combined with the overextension detector.
Unlike simple MA crossover systems for example standard dual EMA strategies this algo uses adaptive MA types based on timeframe pivot deviation for structural breaks and a tally based confirmation to filter noise. Imbalance zones identify fair value gaps or inefficiencies between candle bodies and wicks where price may retrace to fill. Overextension is calculated relative to the mid MA using a rolling mean absolute deviation MAD ratio highlighting potential tops bottoms in strong trends. The result is a visually clean or detailed based on mode overlay that colors bars backgrounds plots labels for signals and pivots and draws zones to guide decision making.
How It Works
MA Layers and Signal Generation
Three MAs quick mid long are computed using either SMA or EMA selected dynamically based on the charts timeframe for optimal responsiveness for example EMA on lower TFs for faster signals.
Early Signals A crossover of the quick MA above the mid MA while above the long MA triggers a Possible Bull label indicating early momentum shifts. A crossunder below triggers Possible Bear.
Confirmed Signals Bullish confirmation requires a set number of bars closing above the long MA plus alignment quick greater than mid and a break above the prior pivot high. Bearish requires bars below the long MA and a break below the prior pivot low. This uses a counter mechanism to ensure persistence reducing whipsaws. Breaks are detected via crossovers under of close versus prior highs lows.
State persistence tracks the current regime bull bear warn early coloring the chart accordingly until a new signal overrides it.
Pivot Detection and Structure
Pivots are identified by scanning for highs lows separated by a minimum bar depth with a percentage deviation threshold to confirm validity. This follows a zigzag like approach but with deviation filtering for robustness.
Labels like HH Higher High HL Higher Low LH Lower High LL Lower Low highlight market structure helping identify trends for example HH HL for uptrends or breakdowns. These are used internally to validate signal breaks.
Imbalance Zones
Zones detect imbalances or gaps between candle bodies and prior highs lows where unfilled inefficiencies attract price.
For bullish zones If open greater than close and high minus low two less than zero a zone is drawn from calculated top bottom limits. Bearish similarly for close greater than open.
Supports current TF HTF or both. Zones extend rightward until filled price touches the opposite side or mid line if enabled then either delete or shorten based on settings. Mid lines can act as fill triggers for partial closures.
HTF data is fetched via security for broader context resetting on new HTF bars.
Overextension Indicator
Measures price deviation from the mid MA relative to a rolling average RMA of relative deviations over a length.
Multipliers define tiers mild for example two times avg deviation moderate three times extreme four times. Circles plot above below bars in bull bear states when thresholds are exceeded signaling potential reversals for example red for extreme tops in uptrends. This is akin to a Bollinger Band squeeze expansion but normalized to MA distance for trend specific warnings.
Chart Coloring and Visuals
Background or candle coloring reflects the state green for bull red for bear orange for warn blue for early.
Modes control clutter Clean hides MAs zones pivots Balanced shows essentials Detailed includes all.
How to Use It
Setup Add to your chart via TradingViews indicator search. Adjust inputs based on asset timeframe for example shorter MA periods for volatile cryptos longer for stocks.
Trading Strategy Ideas
Trend Following Enter long on Confirmed Bull labels exit on Confirmed Bear or extreme overextension circles. Use imbalance zones as support resistance for stops targets for example buy dips to unfilled bullish zones.
Reversal Scalping Watch for Possible Bull Bear near pivot labels for example HL LL and overextension in the opposite direction. Confirm with zone fills.
Multi TF Analysis Set HTF to D for daily context on hourly charts zones from HTF often act as magnets.
Risk Management Place stops below prior lows in bulls or above highs in bears. Target zone edges or MA crosses. Avoid trading against strong states without confirmation.
Alerts Set up via TradingView for Early Up Down or Up Down Confirm to notify on signal edges.
Limitations Best in trending markets may lag in ranges. Test on historical data no indicator is foolproof combine with volume price action.
Detailed Input Settings
Below is a comprehensive breakdown of all user adjustable inputs from the settings panel grouped as in the script. Each explains what it controls its effect on the indicators logic and usage tips. Defaults are provided for reference.
Chart Mode
Chart Mode default Detailed Mode options Clean Mode Balanced Mode Detailed Mode
Controls visual detail level. Clean Mode hides MAs imbalance zones and pivots for a minimal overlay focused on signals and coloring. Balanced Mode shows MAs and signals but omits zones pivots. Detailed Mode displays everything for in depth analysis. Use Clean for live trading to reduce clutter Detailed for backtesting structure review.
Display Settings
Color Style default Candles options Background Candles
Determines how states bull bear warn early are visualized. Background colors the chart area for example green shading for bull. Candles colors bar bodies wicks directly. Background is subtler for multi indicator setups Candles emphasizes signals on naked charts.
Imbalance Zone HTF Config
Higher TF Period default D
Sets the higher timeframe for imbalance detection for example D for daily four H for four hour. This fetches broader data to identify significant zones. Use a TF four to five times your current for context for example daily on one H charts avoid very high TFs like W on intraday for relevance.
TF Mode default Current TF options Current TF Current plus HTF HTF Only
Defines timeframe handling for zones. Current TF uses only your charts TF. Current plus HTF combines both for layered zones. HTF Only ignores current TF. Current plus HTF is ideal for multi TF confluence HTF Only simplifies for swing traders.
Shift default ten min zero max five hundred
Horizontal offset in bars for current TF zone labels. Higher values shift labels rightward to avoid overlap. Adjust if labels crowd the chart.
HTF Shift default twenty min zero max five hundred
Similar to Shift but for HTF zone labels. Use larger offsets for HTF to distinguish them visually.
Imbalance Zone Core Options
Mid Line Fill default false
Enables a midpoint line in each zone zones fill close short when price touches this mid line instead of the far edge. Activates partial fill logic for more conservative zone closure. Enable for tighter risk in volatile markets.
Remove Filled Zones default true
If true completely deletes filled zones if false shortens them to the fill point keeping history. True clears clutter false retains context for review.
Display TF on Zone default false
Shows the timeframe for example D IZ on zone labels. Useful for distinguishing current versus HTF zones in combined mode.
Max Upward Zones default twenty min one max fifty
Limits displayed bullish upward zones removes oldest when exceeded. Lower for cleaner charts higher for historical depth.
Max Downward Zones default twenty min one max fifty
Same as above but for bearish downward zones.
Imbalance Zone Visuals
Upward Zone color green at ninety percent transparency
Color for current TF upward imbalance zones. Adjust opacity for visibility.
HTF Upward Zone color lime at eighty percent transparency
Color for higher timeframe upward imbalance zones. Differentiate from current for example lighter shade.
Downward Zone color red at ninety percent transparency
Color for current TF downward imbalance zones.
HTF Downward Zone color maroon at eighty percent transparency
Color for higher timeframe downward imbalance zones.
Mid Line Color color white at eighty five percent transparency
Color for the optional midpoint line in zones.
Text Color color white
Color for text labels on zones.
MA Layers
Quick MA Period default ten min one
Length for the fastest moving average sensitive to short term price. Shorter for example five for scalping longer for example fifteen for less noise.
Mid MA Period default twenty min one
Intermediate MA length used for crossovers and overextension base. Typically two times quick for balance.
Long MA Period default fifty min one
Baseline trend filter length. Longer for example one hundred for major trends shorter for active trading.
MA Variants by Period
Under one H default EMA options SMA EMA
MA type for timeframes under one hour for example EMA for faster response.
One H to less than five H default EMA options SMA EMA
MA type for one to five hour timeframes.
Five H to less than one D default EMA options SMA EMA
MA type for five hour to one day timeframes.
One D plus default EMA options SMA EMA
MA type for daily and higher timeframes. Adapt to market EMA for trends SMA for mean reversion.
Signal Confirmation
Bull Confirm Bars default one min zero
Consecutive bars needed above long MA for bull confirmation. Zero for instant higher for example three filters noise but delays entries.
Bear Confirm Bars default two min zero
Same for bear below long MA. Asymmetrical default higher for bears assumes uptrend bias.
Pivot Detection
Pivot Depth default six min one
Min bars between pivots. Higher reduces minor swings lower captures more structure.
Pivot Deviation percent default one point zero min zero point one
Percent change required for new pivot. Higher ignores small moves for example two percent for stocks zero point five percent for forex.
Display HH and HL default true
Shows labels for Higher Highs Lows bullish structure.
Display LH and LL default true
Shows labels for Lower Highs Lows bearish structure.
Overextension Indicator
Show Overextension Circles Potential Tops default true
Enables circles above bars in bull states for potential tops.
Show Overextension Circles Potential Bottoms default true
Enables below bars in bear states for bottoms.
Overextension Length default fourteen min one
Period for rolling relative deviation average. Matches RSI STOCH defaults for alignment.
Mild Multiplier default two point zero min zero point zero
Threshold for mild overextension yellow circle. Zero disables tier.
Moderate Multiplier default three point zero min zero point zero
For moderate orange.
Extreme Multiplier default four point zero min zero point zero
For extreme red. Tune lower for sensitive warnings in ranging markets.
QQQ TimingThis is a trend-following position trading strategy designed for the QQQ and the leveraged ETF QLD (ProShares Ultra QQQ). The primary goal is to capture multi-month holds for maximal profit.
Key Instruments & Performance
The strategy performs best with QLD, which yields far superior results compared to QQQ.
TQQQ (triple-leveraged) results in higher drawdowns and is not the optimal choice.
Important: The system is not intended for use with other indexes, individual stocks, or investments (like crypto or gold), as performance can vary widely.
Buy Signals
The strategy's signals are rooted in the S&P 500 Index (SPX), as testing showed it provides more reliable triggers than using QQQ itself.
Primary Buy Signal (Credit to IBD/Mike Webster): The SPX triggers a buy when its low closes above the 21-day Exponential Moving Average (EMA) for three consecutive days.
Refinement with Downtrend Lines: During corrective or bear periods, results and drawdowns can be significantly improved by incorporating downtrend lines. These lines connect lower highs. The strategy waits for the price to close above a drawn downtrend line before executing a buy. This refinement can modify the primary signal, either by allowing for an earlier entry or, in some cases, completely nullifying a false signal until the trend change proves itself.
Risk Management & Exit Strategy
Initial Buy Risk: A 3.7% stop loss is applied immediately upon the initial entry.
Initial Exit Rule: An exit is required if the QQQ's low drops below the 50-day Simple Moving Average (SMA).
Note: The 3.7% stop often provides protection when the initial buy occurs below the 50-day SMA. However, if QQQ is already trading above its 50-day SMA at the time of the SPX signal (indicating relative strength), historically, it has been better to use the 50-day SMA rule to give the position more room to run.
Trend Exit (Profit-Taking): To stay in a strong trend for the optimal amount of time, the long position is exited when a moving average crossover to the downside is triggered, based around the 107-day Simple Moving Average (SMA).
DEMA Flow [Alpha Extract]A sophisticated trend identification system that combines Double Exponential Moving Average methodology with advanced HL median filtering and ATR-based band detection for precise trend confirmation. Utilizing dual-layer smoothing architecture and volatility-adjusted breakout zones, this indicator delivers institutional-grade flow analysis with minimal lag while maintaining exceptional noise reduction. The system's intelligent band structure with asymmetric ATR multipliers provides clear trend state classification through price position analysis relative to dynamic threshold levels.
🔶 Advanced DEMA Calculation Engine
Implements double exponential moving average methodology using cascaded EMA calculations to significantly reduce lag compared to traditional moving averages. The system applies dual smoothing through sequential EMA processing, creating a responsive yet stable trend baseline that maintains sensitivity to genuine market structure changes while filtering short-term noise.
// Core DEMA Framework
dema(src, length) =>
EMA1 = ta.ema(src, length)
EMA2 = ta.ema(EMA1, length)
DEMA_Value = 2 * EMA1 - EMA2
DEMA_Value
// Primary Calculation
DEMA = dema(close, DEMA_Length)
2H
🔶 HL Median Filter Smoothing Architecture
Features sophisticated high-low median filtering using rolling window analysis to create ultra-smooth trend baselines with outlier resistance. The system constructs dynamic arrays of recent DEMA values, sorts them for median extraction, and handles both odd and even window lengths for optimal smoothing consistency across all market conditions.
// HL Median Filter Logic
hlMedian(src, length) =>
window = array.new_float()
for i = 0 to length - 1
array.push(window, src)
array.sort(window)
// Median Extraction
lenW = array.size(window)
median = lenW % 2 == 1 ?
array.get(window, lenW / 2) :
(array.get(window, lenW/2 - 1) + array.get(window, lenW/2)) / 2
// Smooth DEMA Calculation
Smooth_DEMA = hlMedian(DEMA_Value, HL_Filter_Length)
🔶 ATR Band Construction Framework
Implements volatility-adaptive band structure using Average True Range calculations with asymmetric multiplier configuration for optimal trend identification. The system creates upper and lower threshold bands around the smoothed DEMA baseline with configurable ATR multipliers, enabling precise trend state determination through price breakout analysis.
// ATR Band Calculation
atrBands(src, atr_length, upper_mult, lower_mult) =>
ATR = ta.atr(atr_length)
Upper_Band = src + upper_mult * ATR
Lower_Band = src - lower_mult * ATR
// Band Generation
= atrBands(Smooth_DEMA, ATR_Length, Upper_ATR_Mult, Lower_ATR_Mult)
15min
🔶 Intelligent Flow Signal Engine
Generates binary trend states through band breakout detection, transitioning to bullish flow when price exceeds upper band and bearish flow when price breaches lower band. The system maintains flow state persistence until opposing band breakout occurs, providing clear trend classification without whipsaw signals during normal volatility fluctuations.
🔶 Comprehensive Visual Architecture
Provides multi-dimensional flow visualization through color-coded DEMA line, trend-synchronized candle coloring, and bar color overlay for complete chart integration. The system uses institutional color scheme with neon green for bullish flow, neon red for bearish flow, and neutral gray for undefined states with configurable band visibility.
🔶 Asymmetric Band Configuration
Features intelligent asymmetric ATR multiplier system with default upper multiplier of 2.1 and lower multiplier of 1.5, optimizing for market dynamics where upside breakouts often require stronger momentum confirmation than downside breaks. This configuration reduces false signals while maintaining sensitivity to genuine flow changes.
🔶 Dual-Layer Smoothing Methodology
Combines DEMA's inherent lag reduction with HL median filtering to create exceptional smoothing without sacrificing responsiveness. The system first applies double exponential smoothing for initial noise reduction, then applies median filtering to eliminate outliers and create ultra-clean flow baseline suitable for high-frequency and institutional trading applications.
🔶 Alert Integration System
Features comprehensive alert framework for flow state transitions with customizable notifications for bullish and bearish flow confirmations. The system provides real-time alerts on crossover events with clear directional indicators and exchange/ticker integration for multi-symbol monitoring capabilities.
🔶 Performance Optimization Framework
Utilizes efficient array management with optimized median calculation algorithms and minimal variable overhead for smooth operation across all timeframes. The system includes intelligent bar indexing for median filter initialization and streamlined flow state tracking for consistent performance during extended analysis periods.
🔶 Why Choose DEMA Flow ?
This indicator delivers sophisticated flow identification through dual-layer smoothing architecture and volatility-adaptive band methodology. By combining DEMA's reduced-lag characteristics with HL median filtering and ATR-based breakout zones, it provides institutional-grade flow analysis with exceptional noise reduction and minimal false signals. The system's asymmetric band structure and comprehensive visual integration make it essential for traders seeking systematic trend-following approaches across cryptocurrency, forex, and equity markets with clear entry/exit signals and comprehensive alert capabilities for automated trading strategies.
Liquidation Reversal Signals [AlgoAlpha]🟠 OVERVIEW
This tool detects potential liquidation-driven reversals by combining z-score analysis of up/down volume with the classic Supertrend. It watches for abnormal surges in directional volume (on a lower timeframe) and links them to trend flips on the main chart. When both align within a short window, it flags a probable reversal caused by forced liquidations. The goal is to help traders identify exhaustion points where aggressive liquidation moves may mark the end of a trend leg.
🟠 CONCEPTS
The logic revolves around Z-score normalization of up and down volume to locate statistical extremes. When up-volume z-scores exceed a threshold during a bearish Supertrend, it implies trapped shorts being squeezed; the opposite applies for long liquidations. The script tracks these liquidation spikes and monitors whether a Supertrend regime change follows soon after. If confirmed within the allowed timeout, a colored signal marks the event.
In essence:
Z-score outliers = potential forced liquidations.
Supertrend = structural regime context.
Combined = statistically confirmed reversal signals, not random flips.
This pairing reduces false positives by ensuring that both volatility structure and order-flow extremes agree before flagging a reversal.
🟠 FEATURES
Z-score detection for liquidation spikes with adjustable lookback and threshold.
Confirmation logic linking liquidations to Supertrend flips.
Alerts for liquidation spikes and confirmed reversal starts.
On-chart “No Volume” warning to avoid misreads on illiquid assets.
🟠 USAGE
Setup : Add the script to your main chart. Choose a lower timeframe (default 15m) to capture more granular liquidation flows. Adjust Z-Score Length to control how far back the script measures normal behavior and Threshold to decide what counts as extreme. Keep Timeout Bars low (e.g. 20–50) for faster reversals, or higher for slower markets.
Read the chart :
• Circles appear below bars when long liquidations occur; above bars for short liquidations.
• A Supertrend flip with a recent liquidation spike will display an arrow and color shift.
• Fills between candles and trend lines show which side dominates: green for bullish reversal, red for bearish.
• Candle color fades based on the magnitude of liquidation pressure.
Settings that matter :
• Z-Score Length : Longer smooths noise but delays signal; shorter reacts faster.
• Z-Score Threshold : Higher means only extreme liquidations trigger; lower finds smaller squeezes.
• Timeout Bars : Defines how long after a liquidation the Supertrend flip remains valid.
• Lower Timeframe : Determines the precision of volume readings; too low may increase noise.
Turtles StrategyBorn from the 1980s "Turtle" experiment, this method of trading captures breakouts and places or closes trades with intrabar entries or exits and realized-equity risk controls.
How It Works
The strategy buys/sells on breakouts from recent highs/lows, using ATR for volatility-adjusted stops and sizing. It risks a fixed % (default 1%) of realized equity per trade—initial capital plus closed P&L, ignoring open positions for conservatism. Drawdown protection auto-reduces risk by 20% at 10% drops (up to three times), resetting only on full peak recovery. Single positions only, with 1-tick slippage simulated for realistic fills. Best for trending assets like forex,commodities, crypto, stocks. Backtest for optimal parameters.
Main Operations
The strategy works on any timeframe but it's meant to be used on daily charts.
Entry Signals:
Long: Buy-stop 1 tick above 20-bar high (default "Entry Period") when no position—enters intrabar on breakout.
Short: Sell-stop 1 tick below 20-bar low. OCA cancels opposites.
Size: (Realized equity × adjusted risk %) ÷ (2× ATR stop distance), scaled by point value.
Exit Signals:
Longs: Stop at tighter of (entry - 2× ATR) or (10-bar low - 1 tick trailing, default "Exit Period").
Shorts: Stop at tighter of (entry + 2× ATR) or (10-bar high + 1 tick trailing).
Locks profits in trends, exits fast on fades.
Risk Controls:
Tracks realized equity peak.
10% drawdown: Risk ×0.8; 20%/30%: Further ×0.8 (max 3x).
Full reset above peak—preserves capital in slumps.
Futures Fighter MO: Multi-Confluence Day Trading System ADX/SMI👋 Strategy Overview: The Multi-Confluence Mashup
The Futures Fighter MO is a comprehensive, multi-layered day trading strategy designed for experienced traders focusing on high-liquidity futures contracts (e.g., NQ, ES, R2K).
This strategy is a sophisticated mashup that uses the 1-minute chart for surgical entries while enforcing strict environmental filtering through higher-timeframe data. We aim to capture high-conviction moves only when multiple, uncorrelated signals align.
🧠 How the Logic Works (Concepts & Confluence)
Our logic is built on four pillars, which must align for a trade to be executed:
Primary Trend Filter
Indicators :
ADX/DMI (15-Minute Lookback)
Role :
Price action is filtered to ensure the ADX (17/14) is above 25, confirming a strong, prevailing market trend (Bullish or Bearish). Trades are strictly rejected during "Flat" (sideways) market regimes.
Entry Signal Types
The system uses multiple entry types:
- 🟢 Trend Long/Short: A breakout/rejection near the 200-Period EMA is confirmed by the primary ADX trend.
- 🔴 Engulfing Rejection: A strong signal when a Bullish/Bearish Engulfing or Doji prints near the long-term 500-Period EMA (emaGOD) while the Stochastic Momentum Index (SMI on 30M) is in an extreme overbought/oversold state (below $-40$ or above $40$).
Volatility & Volume Confirmation
Indicators: Average True Range (ATR) and 20-Period SMA of Volume
Role: Every entry requires a volume spike (Current Volume $> 1.5 \times$ SMA Volume) to confirm that the move is supported by significant liquidity. Volatility is tracked via ATR to define bar range and stop boundaries.
Structural Guardrails
Indicators: Daily Pivot Points (PP, S1-S3, R1-R3)
Role: Trades are disabled if the current bar's price range intersects with a Daily Pivot Point. This is a critical filter to avoid high-chop consolidation zones near key structural levels.
📊 Strategy Results & Required Disclosures
I strive to publish backtesting results that are transparent and realistic for the retail futures trader.
- Initial Capital: $50,000 - A realistic base for Mini/Micro futures contracts.
- Order Size: 1 Contract (Pyramiding up to 3) - Conservative risk relative to the account size.
- Commission: $0.11 USD per order - Represents realistic costs for low-cost brokers.
- Slippage: 2 Ticks - Accounts for expected market friction.
⚠️ Risk Management & Deviations
Stop-Loss: The strategy uses a dynamic stop-loss system where positions are closed upon a reversal (e.g., breaking the 50-Period EMA or failure to hold a Pivot Point), rather than a fixed tick-based stop. This is suited for experienced traders using a low relative risk (single Micro-contract entry) on a larger account. Users must confirm that the first entry's maximum potential loss remains below $10\%$ of their capital for compliance.
Trade Sample Size: Due to data limitations of the TradingView Essential plan (showing $\approx 50$ trades over 2 weeks), the sample size is under the ideal $100+$ target. Justification: This system is designed to generate signals across a portfolio of correlated futures markets (NQ, ES, R2K, Gold, Crude), meaning the real sample size for a user tracking the portfolio is significantly higher.
Drawdown Control: This strategy is designed for manual management. It requires the user to turn the script/alerts OFF after a significant drawdown and only reactivate it once a recovery trend is established externally.
The strategy uses a combination of dynamic trailing stops, structural support/resistance zones, and a fixed profit target to manage open positions.
🛑 Strategy Exit Logic
1. General Stop-Loss (Dynamic Trailing Stop)
These conditions act as the primary dynamic stop, closing the position if the market reverses past a key Moving Average (MA):
- Long Positions Closed When: The current bar's close crosses under the 50-Period EMA (emaLong).
- Short Positions Closed When: The current bar's close crosses above the 50-Period EMA (emaLong).
2. Profit Target (Fixed Percentage)
The script includes a general exit based on a user-defined profit percentage:
Take Profit Trigger: The position is closed when the currentProfitPercent meets or exceeds the input Profit Target (%) (default is 1.0% of the entry price).
3. Structural Exits (Daily Pivot Points)
These exits are high-priority, "close all" orders that trigger when the price fails to hold or reclaims a recent Daily Pivot Point, suggesting a failure of the current move.
- VR Close All - Long ($\sym{size} > 0$) - Price crosses under a Daily Resistance Level (R1, R2, or R3) minus 1 ATR within the last 10 bars. This indicates the current momentum failed to hold Resistance as support.
- VS Close All - Short ($\sym{size} < 0$) - Price crosses above a Daily Support Level (S1, S2, or S3) plus 1 ATR within the last 10 bars. This indicates the current momentum failed to hold Support as resistance.
4. Trend Failure Exit (Trend-Following Signals Only)
This exit protects against holding a position when the primary high-timeframe trend used for the entry has failed:
- Long Positions Closed When: The primary trend is no longer "bullish" for more than 2 consecutive bars (i.e., it turned "bearish" or "flat").
- Short Positions Closed When: The primary trend is no longer "bearish" for more than 2 consecutive bars (i.e., it turned "bullish" or "flat").
5. End of Day (EOD) Session Control
The final hard exits based on time:
- End of Session (EoS): At 11:30 AM, new trades are disabled (TradingDay := false). Open positions are kept.
- End of Day (EoD): At 1:30 PM, all remaining open positions are closed (strategy.close_all).
🤝 Development & Disclaimer
This script and description were created with assistance from Gemini and GitHub Copilot. My focus is on helping fellow real estate investors and day traders develop mechanically sound systems.
Disclaimer: This is for educational purposes only and does not constitute financial advice. Always abide by the Realtor Code and manage your own risk.
Multi Pivot Trend [BigBeluga]🔵 OVERVIEW
The Multi Pivot Trend is an advanced market-structure-driven trend engine that evaluates trend strength by scanning multiple pivot breakouts simultaneously.
Instead of relying on a single swing length, it tracks breakouts across ten increasing pivot lengths — then averages their behavior to produce a smooth, reliable trend reading.
Mitigation logic (close, wick, or HL2 touches) controls how breakouts are confirmed, giving traders institutional-style flexibility similar to BOS/CHoCH validation rules.
This indicator not only colors candles based on trend strength, but also extends trend strength and volatility-scaled projection candles to show where trend pressure may expand next.
Pivot breakout lines and labels mark key changes, making the trend transitions extremely clear.
🔵 CONCEPTS
Market trend strength is reflected by multiple pivot breakouts, not just one.
The indicator analyzes ten pivot structures from smaller to larger swings.
Each bullish or bearish pivot breakout contributes to trend score.
Mitigation options (close / wick / HL2) imitate smart-money breakout confirmation logic.
Trend score is averaged and translated into colors and extension bars.
Neutral regime ≈ weak trend or transition zone (trend compression).
🔵 FEATURES
Multi-Pivot Engine — tracks 10 pivot-based trend signals simultaneously.
Mitigation Modes :
• Close — breakout requires candle close beyond pivot
• Wicks — breakout requires wick violation
• HL2 — breakout confirmed when average (H+L)/2 crosses level
Dynamic Color System :
• Blue → confirmed bullish rotation
• Red → confirmed bearish rotation
• Orange → neutral / transition state
Breakout Visualization — draws pivot breakout lines in real-time.
Trend Labels — prints trend %.
Trend Volatility-Scaled Extension Candles — ATR/trend strength based candle projections show momentum continuation strength.
Gradient Pivot Encoding — higher pivot lengths = deeper structure considered.
🔵 HOW TO USE
Use strong blue/red periods to follow dominant structural trend.
Watch for color transition into orange — possible trend change or consolidation.
Pivot breakout lines help validate structure shifts without clutter.
Wick mitigation catches aggressive liquidity-sweep based breaks.
Close/HL2 mitigation catches cleaner market structure rotations.
Extension bars visualize trend pressure — large extensions = strong push.
Best paired with volume or volatility confirmation tools.
🔵 CONCLUSION
The Multi Pivot Trend is a structural trend recognition system that blends multiple pivot breakouts into one clean trend score — with institutional-style mitigation logic and volatility-projected trend extensions.
It gives traders a powerful, visually intuitive way to track momentum, spot trend rotations early, and understand true structural flow beyond simple MA-based approaches.
Use it to stay aligned with the dominant swing direction while avoiding noise and false flips.
Volume Sentiment Breakout Channels [AlgoAlpha]🟠 OVERVIEW
This tool visualizes breakout zones based on volume sentiment within dynamic price channels . It identifies high-impact consolidation areas, quantifies buy/sell dominance inside those zones, and then displays real-time shifts in sentiment strength. When the market breaks above or below these sentiment-weighted channels, traders can interpret the event as a change in conviction, not just a technical breakout.
🟠 CONCEPTS
The script builds on two layers of logic:
Channel Detection : A volatility-based algorithm locates price compression areas using normalized highs and lows over a defined lookback. These “boxes” mark accumulation or distribution ranges.
Volume Sentiment Profiling : Each channel is internally divided into small bins, where volume is aggregated and signed by candle direction. This produces a granular sentiment map showing which levels are dominated by buyers or sellers.
When a breakout occurs, the script clears the previous box and forms a new one, letting traders visually track transitions between phases of control. The colored gradients and text updates continuously reflect the internal bias—green for net-buying, red for net-selling—so you can see conviction strength at a glance.
🟠 FEATURES
Volume-weighted sentiment map inside each box, with gradient color intensity proportional to participation.
Dynamic text display of current and overall sentiment within each channel.
Real-time trail lines to show active bullish/bearish trend extensions after breakout.
🟠 USAGE
Setup : Add the script to your chart and enable Strong Closes Only if you prefer cleaner breakouts. Use shorter normalization length (e.g., 50–80) for fast markets; longer (100–200) for smoother transitions.
Read Signals : Transparent boxes mark active sentiment channels. Green gradients show buy-side dominance, red shows sell-side. The middle dashed line is the equilibrium of the channel. “▲” appears when price breaks upward, “▼” when it breaks downward.
Understanding Sentiment : The sentiment profile can be used to show the probability of the price moving up or down at respective price levels.
3SD Bollinger Exhaustion & Reversal Alert IndicatorThe Bollinger Band 3 Standard Deviation (3SD) captures roughly 99% of price action within its boundaries.
When price moves beyond these extremes, it often signals temporary overextension — creating opportunities for mean reversion trades, especially when aligned with the prevailing trend.
This indicator alerts you when:
- Price touches the 3SD Bollinger Band on higher timeframes (H4, D1, W1, M1), and
- A reversal reaction occurs — defined by a bullish or bearish candle close on H1 or H4.
Together, these conditions identify potential high-probability entry zones where exhaustion meets trend alignment.
🚀 Coming Soon
A premium version is in development, combining this 3SD exhaustion logic with my proprietary trend-following system.
It will generate confluence-based trade signals when price interacts with both the 3SD band and the trend-following band.
Stay tuned for updates.
EMA HeatmapEMA Heatmap — Indicator Description
The EMA Order Heatmap is a visual trend-structure tool designed to show whether the market is currently trending bullish, trending bearish, or moving through a neutral consolidation phase. It evaluates the alignment of multiple exponential moving averages (EMAs) at three different structural layers: short-term daily, medium-term daily, and weekly macro trend. This creates a quick and intuitive picture of how well price movement is organized across timeframes.
Each layer of the heatmap is scored from bearish to bullish based on how the EMAs are stacked relative to each other. When EMAs are in a fully bullish configuration, the row displays a bright green or lime color. Fully bearish alignment is shown in red. Yellow tones appear when the EMAs are mixed or compressing, indicating uncertainty, trend exhaustion, or a change in market character. The three rows combined offer a concise view of whether strength or weakness is isolated to one timeframe or broad across the market.
This indicator is best used as a trend filter before making trading decisions. Traders may find more consistent setups when the majority of the heatmap supports the direction of their trade. Green-dominant conditions suggest a trending bullish environment where long trades can be favored. Red-dominant conditions indicate bearish momentum and stronger potential for short opportunities. When yellow becomes more prominent, the market may be transitioning, ranging, or gearing up for a breakout, making timing more challenging and risk higher.
• Helps quickly identify directional bias
• Highlights when trends strengthen, weaken, or turn
• Provides insight into whether momentum is supported by higher timeframes
• Encourages traders to avoid fighting market structure
It is important to recognize the limitations. EMAs are lagging indicators, so the heatmap may confirm a trend after the initial move is underway, especially during fast reversals. In sideways or low-volume environments, the structure can shift frequently, reducing clarity. This tool does not generate entry or exit signals on its own and should be paired with price action, momentum studies, or support and resistance analysis for precise trade execution.
The EMA Order Heatmap offers a clean and reliable way to stay aligned with the broader market environment and avoid lower-quality trades in indecisive conditions. It supports more disciplined decision-making by helping traders focus on setups that match the prevailing structural trend.
Portfolio Strategy TesterThe Portfolio Strategy Tester is an institutional-grade backtesting framework that evaluates the performance of trend-following strategies on multi-asset portfolios. It enables users to construct custom portfolios of up to 30 assets and apply moving average crossover strategies across individual holdings. The model features a clear, color-coded table that provides a side-by-side comparison between the buy-and-hold portfolio and the portfolio using the risk management strategy, offering a comprehensive assessment of both approaches relative to the benchmark.
Portfolios are constructed by entering each ticker symbol in the menu, assigning its respective weight, and reviewing the total sum of individual weights displayed at the top left of the table. For strategy selection, users can choose between Exponential Moving Average (EMA), Simple Moving Average (SMA), Wilder’s Moving Average (RMA), Weighted Moving Average (WMA), Moving Average Convergence Divergence (MACD), and Volume-Weighted Moving Average (VWMA). Moving average lengths are defined in the menu and apply only to strategy-enabled assets.
To accurately replicate real-world portfolio conditions, users can choose between daily, weekly, monthly, or quarterly rebalancing frequencies and decide whether cash is held or redistributed. Daily rebalancing maintains constant portfolio weights, while longer intervals allow natural drift. When cash positions are not allowed, capital from bearish assets is automatically redistributed proportionally among bullish assets, ensuring the portfolio remains fully invested at all times. The table displays a comprehensive set of widely used institutional-grade performance metrics:
CAGR = Compounded annual growth rate of returns.
Volatility = Annualized standard deviation of returns.
Sharpe = CAGR per unit of annualized standard deviation.
Sortino = CAGR per unit of annualized downside deviation.
Calmar = CAGR relative to maximum drawdown.
Max DD = Largest peak-to-trough decline in value.
Beta (β) = Sensitivity of returns relative to benchmark returns.
Alpha (α) = Excess annualized risk-adjusted returns relative to benchmark.
Upside = Ratio of average return to benchmark return on up days.
Downside = Ratio of average return to benchmark return on down days.
Tracking = Annualized standard deviation of returns versus benchmark.
Turnover = Average sum of absolute changes in weights per year.
Cumulative returns are displayed on each label as the total percentage gain from the selected start date, with green indicating positive returns and red indicating negative returns. In the table, baseline metrics serve as the benchmark reference and are always gray. For portfolio metrics, green indicates outperformance relative to the baseline, while red indicates underperformance relative to the baseline. For strategy metrics, green indicates outperformance relative to both the baseline and the portfolio, red indicates underperformance relative to both, and gray indicates underperformance relative to either the baseline or portfolio. Metrics such as Volatility, Tracking Error, and Turnover ratio are always displayed in gray as they serve as descriptive measures.
In summary, the Portfolio Strategy Tester is a comprehensive backtesting tool designed to help investors evaluate different trend-following strategies on custom portfolios. It enables real-world simulation of both active and passive investment approaches and provides a full set of standard institutional-grade performance metrics to support data-driven comparisons. While results are based on historical performance, the model serves as a powerful portfolio management and research framework for developing, validating, and refining systematic investment strategies.
Curved Radius Supertrend [BOSWaves]Curved Radius Supertrend — Adaptive Parabolic Trend Framework with Dynamic Acceleration Geometry
Overview
The Curved Radius Supertrend introduces an evolution of the classic Supertrend indicator - engineered with a dynamic curvature engine that replaces rigid ATR bands with parabolic, radius-based motion. Traditional Supertrend systems rely on static band displacement, reacting linearly to volatility and often lagging behind emerging price acceleration. The Curved Radius Supertend model redefines this by integrating controlled acceleration and curvature geometry, allowing the trend bands to adapt fluidly to both velocity and duration of price movement.
The result is a smoother, more organic trend flow that visually captures the momentum curve of price action - not just its direction. Instead of sharp pivots or whipsaws, traders experience a structurally curved trajectory that mirrors real market inertia. This makes it particularly effective for identifying sustained directional phases, detecting early trend rotations, and filtering out noise that plagues standard Supertrend methodologies.
Unlike conventional band-following systems, the Curved Radius framework is time-reactive and velocity-aware, providing a nuanced signal structure that blends geometric precision with volatility sensitivity.
Theoretical Foundation
The Curved Radius Supertrend draws from the intersection of mathematical curvature dynamics and adaptive volatility processing. Standard Supertrend algorithms extend from Average True Range (ATR) envelopes - a linear measure of volatility that moves proportionally with price deviation. However, markets do not expand or contract linearly. Trend velocity typically accelerates and decelerates in nonlinear arcs, forming natural parabolas across price phases.
By embedding a radius-based acceleration function, the indicator models this natural behavior. The core variable, radiusStrength, controls how aggressively curvature accelerates over time. Instead of simply following price distance, the band now evolves according to temporal acceleration - each bar contributes incremental velocity, bending the trend line into a radius-like curve.
This structural design allows the indicator to anticipate rather than just respond to price action, capturing momentum transitions as curved accelerations rather than binary flips. In practice, this eliminates the stutter effect typical of standard Supertrends and replaces it with fluid directional motion that better reflects actual trend geometry.
How It Works
The Curved Radius Supertrend is constructed through a multi-stage process designed to balance price responsiveness with geometric stability:
1. Baseline Supertrend Core
The framework begins with a standard ATR-derived upper and lower band calculation. These define the volatility envelope that constrains potential price zones. Directional bias is determined through crossover logic - prices above the lower band confirm an uptrend, while prices below the upper band confirm a downtrend.
2. Curvature Acceleration Engine
Once a trend direction is established, a curvature engine is activated. This system uses radiusStrength as a coefficient to simulate acceleration per bar, incrementally increasing velocity over time. The result is a parabolic displacement from the anchor price (the price level at trend change), creating a curved motion path that dynamically widens or tightens as the trend matures.
Mathematically, this acceleration behaves quadratically - each new bar compounds the previous velocity, forming an exponential rate of displacement that resembles curved inertia.
3. Adaptive Smoothing Layer
After the radius curve is applied, a smoothing stage (defined by the smoothness parameter) uses a simple moving average to regulate curve noise. This ensures visual coherence without sacrificing responsiveness, producing flowing arcs rather than jagged band steps.
4. Directional Visualization and Outer Envelope
Directional state (bullish or bearish) dictates both the color gradient and band displacement. An outer envelope is plotted one ATR beyond the curved band, creating a layered trend visualization that shows the extent of volatility expansion.
5. Signal Events and Alerts
Each directional transition triggers a 'BUY' or 'SELL' signal, clearly labeling phase shifts in market structure. Alerts are built in for automation and backtesting.
Interpretation
The Curved Radius Supertrend reframes how traders visualize and confirm trends. Instead of simply plotting a trailing stop, it maps the dynamic curvature of trend development.
Uptrend Phases : The band curves upward with increasing acceleration, reflecting the market’s growing directional velocity. As curvature steepens, conviction strengthens.
Downtrend Phases : The band bends downward in a mirrored acceleration pattern, indicating sustained bearish momentum.
Trend Change Points : When the direction flips and a new anchor point forms, the curve resets - providing a clean, early visual confirmation of structural reversal.
Smoothing and Radius Interplay : A lower radius strength produces a tighter, more reactive curve ideal for scalping or short timeframes. Higher values generate broad, sweeping arcs optimized for swing or positional analysis.
Visually, this curvature system translates market inertia into shape - revealing how trends bend, accelerate, and ultimately exhaust.
Strategy Integration
The Curved Radius Supertrend is versatile enough to integrate seamlessly into multiple trading frameworks:
Trend Following : Use BUY/SELL flips to identify emerging directional bias. Strong curvature continuation confirms sustained momentum.
Momentum Entry Filtering : Combine with oscillators or volume tools to filter entries only when the curve slope accelerates (high momentum conditions).
Pullback and Re-entry Timing : The smooth curvature of the radius band allows traders to identify shallow retracements without premature exits. The band acts as a dynamic, self-adjusting support/resistance arc.
Volatility Compression and Expansion : Flattening curvature indicates volatility compression - a potential pre-breakout zone. Rapid re-steepening signals expansion and directional conviction.
Stop Placement Framework : The curved band can serve as a volatility-adjusted trailing stop. Because the curve reflects acceleration, it adapts naturally to market rhythm - widening during momentum surges and tightening during stagnation.
Technical Implementation Details
Curved Radius Engine : Parabolic acceleration algorithm that applies quadratic velocity based on bar count and radiusStrength.
Anchor Logic : Resets curvature at each trend change, establishing a new reference base for directional acceleration.
Smoothing Layer : SMA-based curve smoothing for noise reduction.
Outer Envelope : ATR-derived band offset visualizing volatility extension.
Directional Coloring : Candle and band coloration tied to current trend state.
Signal Engine : Built-in BUY/SELL markers and alert conditions for automation or script integration.
Optimal Application Parameters
Timeframe Guidance :
1-5 min (Scalping) : 0.08–0.12 radius strength, minimal smoothing for rapid responsiveness.
15 min : 0.12–0.15 radius strength for intraday trends.
1H : 0.15–0.18 radius strength for structured short-term swing setups.
4H : 0.18–0.22 radius strength for macro-trend shaping.
Daily : 0.20–0.25 radius strength for broad directional curves.
Weekly : 0.25–0.30 radius strength for smooth macro-level cycles.
The suggested radius strength ranges provide general structural guidance. Optimal values may vary across assets and volatility regimes, and should be refined through empirical testing to account for instrument-specific behavior and prevailing market conditions.
Asset Guidance :
Cryptocurrency : Higher radius and multiplier values to stabilize high-volatility environments.
Forex : Midrange settings (0.12-0.18) for clean curvature transitions.
Equities : Balanced curvature for trending sectors or momentum rotation setups.
Indices/Futures : Moderate radius values (0.15-0.22) to capture cyclical macro swings.
Performance Characteristics
High Effectiveness :
Trending environments with directional expansion.
Markets exhibiting clean momentum arcs and low structural noise.
Reduced Effectiveness :
Range-bound or low-volatility conditions with repeated false flips.
Ultra-short-term timeframes (<1m) where curvature acceleration overshoots.
Integration Guidelines
Confluence Framework : Combine with structure tools (order blocks, BOS, liquidity zones) for entry validation.
Risk Management : Trail stops along the curved band rather than fixed points to align with adaptive market geometry.
Multi-Timeframe Confirmation : Use higher timeframe curvature as a trend filter and lower timeframe curvature for execution timing.
Curve Compression Awareness : Treat flattening arcs as potential exhaustion zones - ideal for scaling out or reducing exposure.
Disclaimer
The Curved Radius Supertrend is a geometric trend model designed for professional traders and analysts. It is not a predictive system or a guaranteed profit method. Its performance depends on correct parameter calibration and sound risk management. BOSWaves recommends using it as part of a comprehensive analytical framework, incorporating volume, liquidity, and structural context to validate directional signals.
Background Trend Follower by exp3rtsThe Background Trend Follower indicator visually highlights the market’s daily directional bias using subtle background colors. It calculates the price change from the daily open and shades the chart background according to the current intraday momentum.
🟢 Green background → Price is significantly above the daily open (strong bullish trend)
🔴 Red background → Price is significantly below the daily open (strong bearish trend)
🟡 Yellow background → Price is trading near the daily open (neutral or consolidating phase)
The script automatically detects each new trading day.
It records the opening price at the start of the day.
As the session progresses, it continuously measures how far the current price has moved from that open.
When the move exceeds ±50 points (custom threshold), the background color adapts to reflect the trend strength.
Perfect for traders who want a quick visual sense of intraday bias — bullish, bearish, or neutral — without cluttering the chart with extra indicators.
Advanced Chandelier Exit with S/R [Alpha Extract]Advanced Chandelier Exit with S/R is a precision-crafted trailing stop and market structure detection system that fuses advanced Chandelier Exit logic with intelligent, multi-timeframe support and resistance tracking. This indicator delivers adaptive trend detection, volatility-aware exit positioning, and real-time structural mapping in a clean, responsive format. By combining directional filtering, pivot zone detection, and customizable styling, Advanced Chandelier Exit with S/R is designed to give traders reliable context, strong risk management, and visually intuitive confirmation signals across all timeframes and asset classes.
🔶 Adaptive Trailing Stop Architecture
At the core of Advanced Chandelier Exit with S/R is a refined Chandelier Exit mechanism that dynamically calculates trailing stops based on recent highs and lows, ATR volatility, and trend sensitivity. The system features directional memory, anchoring the stop to maintain position until a confirmed trend break occurs. This method prevents premature flips and keeps the trade aligned with sustained momentum.
longStop := close > longStop ? math.max(longStop, longStop ) : longStop
shortStop := close < shortStop ? math.min(shortStop, shortStop ) : shortStop
🔶 Volatility-Weighted Filtering
To reduce noise and improve reaction quality, Advanced Chandelier Exit with S/R includes an optional volatility normalization filter. This system adjusts ATR output based on how elevated it is relative to its own average, effectively down-weighting erratic price moves while maintaining responsiveness in directional phases.
volatilityFilter = enableVolatilityFilter ? ta.sma(baseATR, length) / baseATR : 1.0
atr = mult * baseATR * sensitivity * volatilityFilter
🔶 Trend Strength-Aware State Transitions
Trend flips in Advanced Chandelier Exit with S/R are not based solely on price crossing the stop level. Instead, the system includes a momentum-derived trend strength filter that validates the legitimacy of directional shifts. This guards against weak reversals and gives stronger confidence in breakout moves.
priceChange = math.abs(close - close )
avgPriceChange = ta.sma(priceChange, length)
trendStrength = math.min(priceChange / avgPriceChange * 100, 200)
🔶 Multi-Timeframe Support & Resistance Zones
Advanced Chandelier Exit with S/R embeds a sophisticated pivot-based structure mapping engine that automatically identifies significant price reaction levels and tracks their validity over time. It filters redundant zones, removes invalidated levels, and renders real-time support and resistance overlays based on market structure.
if isUniqueLevel(ph, resistanceLevels)
array.unshift(resistanceLevels, ph)
if isUniqueLevel(pl, supportLevels)
array.unshift(supportLevels, pl)
🔶 Dynamic Visual Encoding
The indicator uses strength-scaled fills, customizable colors, and line styling to convey directional bias with clarity. Color opacity intensifies as trend strength increases, offering intuitive context at a glance. Dynamic background fills mark trend states, while S/R zones are rendered with user-defined transparency for clean integration.
🔶 Signal Detection and Alerts
Directional signals are generated upon confirmed flips between long and short regimes, validated by stop crosses and strength filters. Additionally, the indicator provides S/R breakout alerts, identifying when price breaks through a key structural level.
🔶 Performance and Customization Optimizations
Advanced Chandelier Exit with S/R is built with modularity and efficiency in mind. It supports full customization of stop logic, volatility sensitivity, structural lookback, S/R zone filtering, and visual display. The use of array-based data structures for S/R levels ensures consistent performance even across high-activity assets and longer lookback periods.
Advanced Chandelier Exit with S/R represents the next evolution in trailing stop and structure-aware trading tools. By blending the proven logic of the Chandelier Exit system with intelligent trend strength filters and robust S/R detection, it becomes more than just a stop indicator—it becomes a complete trade management companion. Traders benefit from fewer false flips, clearer directional bias, and precise structural overlays that reinforce both breakout and reversal strategies. Whether used for swing entries, intraday positioning, or zone-based re-entries, Advanced Chandelier Exit with S/R empowers traders with responsive, intelligent logic that adapts to market conditions without compromise.
Tight Entry Trend Engine Strategy═══════════════════════════════════════
TIGHT ENTRY TREND ENGINE
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A breakout-based trend-following system designed to capture explosive
moves by entering at precise resistance/support breakouts with minimal
entry risk and massive profit potential.
⚠️ LOW WIN RATE, HIGH REWARD SYSTEM ⚠️
This is NOT a high win-rate strategy. Expect 25-35% winners, but
when it hits, winners are typically 10X+ larger than losers.
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🎯 WHAT THIS SYSTEM DOES
═══════════════════════════════════════
The Tight Entry Trend Engine identifies powerful breakout opportunities
by detecting when price breaks through established trendlines with
confirmation from higher timeframe trends:
1. DYNAMIC TRENDLINE DETECTION (3 BANKS)
• Automatically draws support and resistance trendlines
• 3 separate "banks" capture short-term, medium-term, and long-term levels
• Each bank has configurable parameters (required pivot touch count,
angle limits, lengths)
2. BREAKOUT ENTRY TIMING
• Enters LONG when price breaks ABOVE resistance trendlines
• Enters SHORT when price breaks BELOW support trendlines
• Entry Alert occurs at the exact moment of breakout = "tight entry"
• Stop-loss placed just below/above the broken trendline (configurable)
3. HIGHER TIMEFRAME TREND FILTER
• Uses Hull Moving Average (HMA) on higher timeframe for trend following
• Auto-adjusts HTF based on your chart timeframe
• Optional filters prevent entries against major trend
• Optional "overextension" filter avoids buying parabolic moves
4. VOLATILITY-ADAPTIVE RISK MANAGEMENT
• Stop-loss calculated using Average True Range (ATR)
• Tighter stops = better R:R
• Profit targets adjust dynamically with volatility
• Breakeven stop moves automatically when in profit
• Extended profit targets when far from HTF trend
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📊 HOW IT WORKS (METHODOLOGY)
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STEP 1: TRENDLINE FORMATION
The system continuously scans for pivot highs and pivot lows to
construct trendlines. You control:
BANK 1 (Short-Term):
- Pivot Length: How many bars to look back for swing points
- Min Touches: How many pivots needed to form a line (default: 3)
- Max Length: How far back lines can reach (default: 180 bars)
- Angle Limits: Maximum steepness allowed for valid trendlines
- Tolerance: How close pivots must align to form horizontal lines
BANK 2 (Medium-Term):
- Slightly longer pivot periods for more significant levels
- Captures medium-term trend structure
- Default Max Length: 200 bars
BANK 3 (Long-Term):
- Focuses on major support/resistance zones
- Often uses horizontal levels (angled lines disabled by default)
- Default Max Length: 300 bars
The system draws RESISTANCE lines (red) above price and SUPPORT
lines (green) below price. These adapt in real-time as new pivots form.
STEP 2: BREAKOUT DETECTION
LONG SIGNALS:
- Price closes above a resistance trendline
- Higher timeframe trend is up (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
SHORT SIGNALS:
- Price closes below a support trendline
- Higher timeframe trend is down (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
The "tight" aspect: Because you're entering right at the trendline
break, your stop-loss can be placed very close (just below the
broken resistance for longs), creating exceptional risk/reward ratios.
STEP 3: POSITION SIZING
Choose between:
- Fixed $ Risk Per Trade: Risk same dollar amount every trade
- % Risk Per Trade: Risk percentage of current equity
Position size automatically calculated based on:
- Your risk amount
- Distance to stop-loss (ATR-based)
- Works with stocks, futures, crypto (auto-adjusts for contract multipliers)
STEP 4: EXIT MANAGEMENT
Multiple exit methods working together:
- PROFIT TARGET: Exits when profit reaches 100x your risk
- EXTENDED PROFIT: Earlier exit (80R) when very far from HTF trend
- STOP LOSS: Fixed ATR-based stop below entry
- HTF TREND EXIT: Exits when price crosses below HTF trend with profit
- BREAKEVEN PULLBACK: Exits if profit drops below 0.6R after reaching breakeven
- PARTIAL PROFITS: Optional - take partial profits at specified R-multiple
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🔧 KEY COMPONENTS EXPLAINED
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HULL MOVING AVERAGE (HMA)
A smoothed moving average that reduces lag compared to traditional
MAs. The system uses HMA on a higher timeframe to determine the
dominant trend direction. You can choose:
- Auto HTF: System picks appropriate HTF based on your chart timeframe
- Manual HTF: You specify the higher timeframe
AVERAGE TRUE RANGE (ATR)
Measures current market volatility. Used for:
- Stop-loss distance (tighter when volatility low)
- Profit targets (larger when volatility high)
- Position sizing (smaller positions in volatile conditions)
- Breakeven trigger distance
TRENDLINE ANGLE FILTERING
Each trendline bank has angle limits to ensure quality:
- Resistance lines: Max downward/upward slope allowed
- Support lines: Max downward/upward slope allowed
- Angles automatically adjust based on current volatility
- Prevents overly steep/unreliable trendlines
SENSITIVITY CONTROL
One master slider adjusts multiple parameters:
- Trendline detection sensitivity
- HTF MA length
- Exit timing
- Auto-adjusts for daily+ timeframes (60% increase)
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⚙️ WHAT YOU SEE ON YOUR CHART
═══════════════════════════════════════
TRENDLINES:
✓ Red resistance lines above price
✓ Green support lines below price
✓ Orange broken lines (past breakouts)
✓ Lines extend to show current levels
HTF TREND:
✓ Thick colored line showing higher timeframe trend
✓ Color gradient: Red (bearish) → Orange → Yellow → Green (bullish)
✓ 250-bar smoothed curve for visual clarity
ENTRY/EXIT SIGNALS:
✓ Small green dot below bar = Long entry
✓ Small red dot above bar = Short entry
✓ Small red dot above = Long exit
✓ Small black dot below = Short exit
OPTIONAL DETAILED LABELS:
✓ Bank number that triggered entry (Bank 1, 2, or 3)
✓ Exit reason (Profit Target, Stop Loss, HTF Exit, etc.)
✓ Partial profit notifications
POSITION TRACKING:
✓ Yellow dashed line at entry price (extends right)
✓ Green/red fill showing current profit/loss zone
✓ Lime arrows at top = Currently in long position
✓ Red arrows at bottom = Currently in short position
✓ Gray background = No position (flat)
STATS TABLE (Top Right):
✓ Current position (LONG/SHORT/FLAT)
✓ Risk per trade ($ or %)
✓ Entry price
✓ Unrealized P/L in dollars
✓ P/L in R-multiples (how many R's profit/loss)
✓ Average winner/loser R ($ mode) OR CAGR (% mode)
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📈 OPTIMAL USAGE
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BEST ASSETS:
- NASDAQ:QQQ on 1-hour (reg) chart ⭐ (PRIMARY OPTIMIZATION)
- Strong trending stocks: NVDA, AAPL, TSLA, MSFT, GOOGL, AMZN
- High volatility tech stocks
- Crypto: BTC, ETH
- Any liquid asset with clear trends and momentum (GOLD)
AVOID:
- Low volatility stocks
- Ranging/choppy markets
- Penny stocks or illiquid assets
- Assets without clear directional movement
BEST TIMEFRAMES:
- PRIMARY: 1-hour charts (optimal for QQQ)
- ALSO EXCELLENT: 2H, 4H, 8H
- WORKS: 15min, 30min (only momentum leaders, more noise)
- WORKS WITH ADJUSTMENTS: 1D, 2D (decrease trendline pivot lengths)
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📊 BACKTEST RESULTS (QQQ 1H (Reg hours), 1999-2024)
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The system showed on NASDAQ:QQQ 1-hour timeframe (regular hours):
- Total Return: 1,100,000%+ over 24 years
- Total Trades: 500+
- Win Rate: ~20-24% (LOW - this is by design!)
- Average Winner: 8-15% gain
- Average Loser: 2-4% loss
- Win/Loss Ratio: 10:1 (winners much bigger than losers)
- Profit Factor: 3+
- Max Drawdown: 45-50%
- Risk per trade: 3% of capital
KEY INSIGHT: This is a LOW WIN RATE, HIGH REWARD system. You will
lose more trades than you win, but the few winners are so large
they more than compensate for many small losses.
IMPORTANT: These are backtested results using optimal parameters
on historical data. Real trading results will vary based on:
- Your execution and timing
- Slippage and commissions
- Your emotional discipline
- Market conditions during your trading period
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🎓 WHO IS THIS FOR?
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IDEAL FOR:
✓ Swing traders comfortable holding winners for longer period
✓ Part-time traders (1H = check 2-3x per day)
✓ Traders seeking exceptional risk/reward ratios
✓ Those comfortable with low win rates if winners are huge
✓ Technical analysis enthusiasts
✓ Breakout traders
✓ Trend followers
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🚀 GETTING STARTED - STEP BY STEP
═══════════════════════════════════════
STEP 1: APPLY TO YOUR CHART
- Search "Tight Entry Trend Engine" in indicators
- Click to apply to your chart
- Trendlines and HTF line will appear immediately
STEP 2: CHOOSE YOUR SETTINGS
For BEGINNERS - Use These Settings First:
1. Trade Direction & Filters:
• ENABLE LONGS: ✓ ON
• ENABLE SHORTS: ✗ OFF (start with longs only)
• Sensitivity: 1.0 (default)
• HTF Trend Entry Filter: ✓ ON (safer entries)
• Block Entries When Overextended: ✓ ON (avoid parabolic tops)
2. Position Sizing & Risk:
• Position Sizing: "Per Risk"
• RISK Type: "$ Per Trade"
• Risk Amount: $200 (or 1-3% of your account)
3. Visual Settings:
• Show Support Lines: ✗ OFF (unless trading shorts)
• Show Detailed Entry/Exit Labels: ✓ ON
• Show Stats Table: ✓ ON
• Show Entry Line & P/L Fill: ✓ ON
4. Leave everything else at DEFAULT for now
STEP 3: UNDERSTAND WHAT YOU SEE
When trendlines appear:
- RED lines above = Resistance (watch for price breaking UP through these)
- GREEN lines below = Support (watch for price breaking DOWN)
- When price breaks a red line = Potential LONG entry
- When price breaks a green line = Potential SHORT entry
The HTF trend line (thick colored):
- Green/lime = Strong uptrend (favorable for longs)
- Red = Strong downtrend (favorable for shorts if enabled)
- Orange/yellow = Transitioning
STEP 4: OBSERVE SIGNALS
- Small GREEN dot below bar = System entered LONG
- Small RED dot above bar = System exited LONG
- Check the label to see which "Bank" triggered (Bank 1, 2, or 3)
- Watch the yellow entry line and colored fill show your P/L
STEP 5: PAPER TRADE FIRST
- Use TradingView's paper trading feature
- Watch how signals perform on YOUR chosen asset
- Understand the win rate will be LOW (20-35%)
- Verify that winners are indeed much larger than losers
- Test for at least 20-30 signals before going live
STEP 6: OPTIMIZE FOR YOUR ASSET (OPTIONAL)
If default settings aren't working well:
For FASTER signals (more trades):
- Reduce Pivot Length 1 to 3-4
- Reduce Max Length 1 to 120-150
- Increase Sensitivity to 1.2-1.5
For SLOWER signals (higher quality):
- Increase Pivot Length 1 to 7-10
- Increase Max Length 1 to 250+
- Decrease Sensitivity to 0.7-0.9
For DAILY timeframes:
- Increase all Pivot Lengths by 30-50%
- Increase all Max Lengths significantly
- Sensitivity: 0.6-0.8
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⚙️ ADVANCED SETTINGS EXPLAINED
═══════════════════════════════════════
TRENDLINE BANK SETTINGS:
Each bank (1, 2, 3) has these parameters:
- Min Touches: Minimum pivots to form a line
- Lower (2) = More lines, earlier detection
- Higher (4+) = Fewer lines, higher quality
- Pivot Length: Lookback for swing points
- Lower (3-5) = Reacts to recent price action
- Higher (10+) = Only major swing points
- Max Length: How old a trendline can be
- Shorter (100-150) = Only recent lines
- Longer (300+) = Include historical levels
- Tolerance: Alignment strictness for horizontal lines
- Lower (3.0-3.5) = Very strict horizontal
- Higher (4.5+) = More forgiving alignment
- Allow Angled Lines: Enable diagonal trendlines
- ON = Catches sloped support/resistance
- OFF = Only horizontal levels
- Angle Limits: Maximum steepness allowed
- Lower (1-2) = Only gentle slopes
- Higher (4-6) = Accept steeper angles
- Automatically adjusts for volatility
ATR MULTIPLIERS:
- STOP LOSS ATR (0.6): Distance to stop-loss
- Lower (0.4-0.5) = Tighter stops, stopped out more
- Higher (0.8-1.0) = Wider stops, more room
- PROFIT TARGET ATR (100): Main profit target
- This is 100x your risk = 10,000% R:R
- Lower (50-80) = Take profits sooner
- Higher (120+) = Let winners run longer
- BREAKEVEN ATR (40): When to move stop to breakeven
- Lower (20-30) = Protect profits earlier
- Higher (60+) = Give more room before protecting
HIGHER TIMEFRAME:
- Auto HTF: Automatically selects appropriate HTF
- 5min chart → uses 2H
- 15-30min → uses 6H
- 1-4H → uses 2D
- Daily → uses 4D
- HTF MA Length (300): HMA period for trend
- Lower (150-250) = More responsive
- Higher (400-500) = Smoother, less whipsaw
- HTF Trend Following Exit: Exits when crossing HTF
- ON = Additional exit method
- OFF = Rely only on profit targets/stops
- HTF Trend Entry Filter: Only trade with HTF trend
- ON = Safer, fewer signals
- OFF = More aggressive, more signals
- Block Entries When Overextended: Prevents chasing
- ON = Avoids parabolic tops/bottoms
- OFF = Enter all breakouts regardless
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💡 TRADING PHILOSOPHY & EXPECTATIONS
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This system is built on one core principle:
"ACCEPT SMALL, FREQUENT LOSSES TO CAPTURE RARE, MASSIVE WINS"
What this means:
- You WILL lose 65%-75% of your trades
- Most losses will be small (1-2R)
- Some winners hit 80R+
- Over time, math works in your favour
Smart Money Volume Activity [AlgoAlpha]🟠 OVERVIEW
This tool visualizes how Smart Money and Retail participants behave through lower-timeframe volume analysis. It detects volume spikes far beyond normal activity, classifies them as institutional or retail, and projects those zones as reactive levels. The script updates dynamically with each bar, showing when large players enter while tracking whether those events remain profitable. Each event is drawn as a horizontal line with bubble markers and summarized in a live P/L table comparing Smart Money versus Retail.
🟠 CONCEPTS
The core logic uses Z-score normalization on lower-timeframe volumes (like 5m inside a 1h chart). This lets the script detect statistically extreme bursts of buying or selling activity. It classifies each detected event as:
Smart Money — volume inside the candle body (suggesting hidden accumulation or distribution)
Retail — volume closing at bar extremes (suggesting chase entries or panic exits)
When new events appear, the script plots them as horizontal levels that persist until price interacts again. Each level acts as a potential reaction zone or liquidity footprint. The integrated P/L table then measures which class (Retail or Smart Money) is currently “winning” — comparing cumulative profitable versus losing volume.
🟠 FEATURES
Classifies flows into Smart Money or Retail based on candle-body context.
Displays live P/L comparison table for Smart vs Retail performance.
Alerts for each detected Smart or Retail buy/sell event.
🟠 USAGE
Setup : Add the script to any chart. Set Lower Timeframe Value (e.g., “5” for 5m) smaller than your main chart timeframe. The Period input controls how many bars are analyzed for the Z-score baseline. The Threshold (|Z|) decides how extreme a volume must be to plot a level.
Read the chart : Horizontal lines mark where heavy Smart or Retail volume occurred. Bright bubbles show the strongest events — their size reflects Z-score intensity. The on-chart table updates live: green cells show profitable flows, red cells show losing flows. A dominant green Smart Money row suggests institutions are currently controlling price.
See what others are doing :
Settings that matter : Raising Threshold (|Z|) filters noise, showing only large players. Increasing Period smooths results but reacts slower to new bursts. Use Show = “Both” for full comparison or isolate “Smart Money” / “Retail” to focus on one class.
