Multitimeframe Fair Value Gap – FVG (Zeiierman)█ Overview
The Multitimeframe Fair Value Gap – FVG (Zeiierman) indicator provides a dynamic and customizable visualization of institutional imbalances (Fair Value Gaps) across multiple timeframes. Built for traders who seek to analyze price inefficiencies, this tool helps highlight potential entry points, unmitigated gaps, and directional bias using smart volume logic and adaptive visual elements.
A Fair Value Gap (FVG) forms when there's a three-candle sequence in which a market imbalance leaves a "gap" between the wicks of candle 1 and candle 3. These areas are often considered footprints of institutional activity, and this indicator gives you the tools to track them with surgical precision across any timeframe you choose—regardless of the one you're viewing.
This indicator also includes a trend filter powered by a low-pass Butterworth filter, enabling traders to distinguish between countertrend vs. trend-aligned FVGs for more intelligent decision-making. On top of that, it features a dynamic FVG table for live tracking and bull/bear volume power visualization inside each gap, adding powerful clarity to market intent.
█ How It Works
The indicator analyzes the open, high, low, close, and volume of candles from a user-selected timeframe. It identifies Fair Value Gaps based on wick logic and only confirms those that meet customizable strength criteria. Once detected, the indicator visualizes each FVG with dynamically extending boxes, optional buy/sell volume bars, and a real-time mitigation check.
⚪ Multitimeframe Logic
Users can analyze FVGs from a higher or lower timeframe regardless of their current chart.
This is achieved using request.security() to fetch OHLCV data from the chosen timeframe.
⚪ Wick Sensitivity & Impulse Filter
The script measures the wick size of potential FVG candles and compares them to a running average. Only FVGs with wick sizes above a certain sensitivity threshold (user-controlled) are plotted. This ensures only meaningful price dislocations (e.g., strong impulsive moves) are shown, reducing noise.
⚪ Midpoint Mitigation Logic
FVGs are marked as "mitigated" when the price revisits the gap area. Traders can choose whether full gap closure or just a midpoint touch is required. This allows faster reactivity in real-time trading environments.
⚪ Bull & Bear Power – Volume-Weighted Visualization
Every Fair Value Gap box includes sub-bars representing the estimated buy and sell effort that created the gap. These are calculated using the candle's close in relation to its high/low range and volume:
Buy Volume % ≈ effort from low to close
Sell Volume % ≈ effort from high to close
Each sub-bar inside the FVG:
Is color-coded (UpCol for bullish, DnCol for bearish)
Is drawn proportionally to the strength of buyers or sellers
Visually displays who was in control during the imbalance
⚪ FVG Table – Dynamic On-Chart Overview
The indicator includes an optional on-chart table that displays all currently active (unmitigated) FVGs in a side panel format:
Automatic updates as gaps are formed and mitigated
Color-coded rows to show bullish vs. bearish FVGs
Timestamps to know precisely when the gap formed
User-controlled position via Table Left and Table Right
This is a gap watchlist overlay, giving traders a concise view of current inefficiencies without manually scanning the chart.
⚪ FVG Trend Filter (Butterworth Smoother)
Using a two-pole Butterworth low-pass filter, the indicator computes a trendline based on average FVG values, offering a smooth but responsive directional signal.
Passband Ripple (dB): Controls sensitivity and overshoot tolerance
Cutoff Frequency (0–0.5): Sets how quickly the trendline reacts
The trendline helps categorize each FVG:
Trend up → favor bullish FVGs
Trend down → favor bearish FVGs
It adds an extra dimension to FVG entries, helping distinguish between trend-aligned and countertrend signals.
█ How to Use
⚪ Identify Institutional Gaps
Use this tool to identify areas where institutions may have left imbalances behind quickly.
These areas often become:
Strong support/resistance zones
Areas where price might react sharply
Targets for liquidity sweeps or retracements
⚪ React to Trend or Countertrend
The built-in trendline helps categorize each FVG:
Trend up → Bullish FVGs have higher validity
Trend down → Bearish FVGs have higher validity
⚪ Volume Context via Bull/Bear Power
Each Fair Value Gap is more than just a price imbalance — it’s a story of effort and intent. The Bull/Bear Power feature visualizes the buy and sell pressure behind each FVG, helping you understand how the gap was formed and who was in control.
A bullish FVG with a strong buy effort suggests continuation potential — buyers dominated the move.
A bullish FVG with a dominant sell effort could signal a trap or reversal — sellers may have overwhelmed the breakout.
These insights allow you to confirm imbalance strength, spot traps early, and add confidence to entries based on dominant volume profiles.
Instead of viewing gaps as static zones, this feature turns each into a live volume map — a visual breakdown of who moved the market and whether that move had conviction.
⚪ Plan with the FVG Table
The FVG Table acts as your on-chart control center for tracking active imbalances. When enabled, it provides a clear summary of all unmitigated Fair Value Gaps, helping you stay organized and focused during fast-moving sessions.
Track live and historical gaps: See exactly when and where each FVG formed.
Monitor older, still-valid zones: Gaps off-screen but not mitigated remain in play — perfect for anticipating future reactions.
Gauge market bias at a glance: The balance of bullish vs. bearish FVGs helps you understand overall directional pressure.
Plan entries confidently: Use the table to reference all zones for risk management, confluence stacking, or layered execution strategies.
Instead of manually scanning your chart, the FVG Table offers a clean, at-a-glance overview of the market’s inefficiencies — giving you the structure needed to act with precision.
█ Settings
FVG Timeframe
Select any timeframe to source FVGs independent of your current chart.
Sensitivity
Filter FVGs by how impulsive the move is — it helps you eliminate weak gaps.
Mitigated on Mid
Control whether gaps are removed at midpoint touch or full fill.
Table Settings
Control the table position and width. Cleanly view all active FVGs.
FVG Style
Customize gap box colors, length, and bullish/bearish overlays.
Trend Filter
Enable or disable the smoothed FVG-based trendline with customizable smoothing controls.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Penunjuk dan strategi
Log Regression Oscillator Channel [BigBeluga]
This unique overlay tool blends logarithmic trend analysis with dynamic oscillator behavior. It projects RSI, MFI, or Stochastic lines directly into a log regression channel on the price chart — offering an intuitive way to detect overbought/oversold momentum within the broader price structure.
🔵Key Features:
Logarithmic Regression Channel:
➣ Draws a trend-based channel using logarithmic regression, adapting to price growth curvature over time.
➣ Features upper, lower, and optional midline boundaries to visualize trend flow and range extremes.
Oscillator Overlay (RSI / MFI / Stochastic):
➣ Projects your chosen oscillator inside the channel using dynamic polylines.
➣ Allows switching between RSI, Money Flow Index, or Stochastic for versatile momentum insight.
Threshold-Based Scaling:
➣ The top and bottom of the channel represent traditional oscillator thresholds (e.g., RSI 70/30).
➣ Users can modify the scale in settings to customize what "overbought" or "oversold" means visually.
Signal Line Integration:
➣ Adds a yellow moving average (signal line) for smoother confirmation of oscillator turns.
➣ Helps identify divergence, momentum shifts, and fakeouts with better clarity.
Live Oscillator Readout:
➣ Displays the real-time oscillator value at the right edge of the chart.
➣ Ensures traders stay aware of current momentum levels without switching panels.
🔵Usage:
Momentum Context:
➣ When the oscillator touches the upper regression band, it may signal local overbought pressure.
➣ Touching the lower band may indicate oversold conditions within the current log trend.
Divergence Detection:
➣ Use the oscillator’s behavior relative to the channel slope to spot divergence from price.
➣ For example, RSI rising inside a falling channel can flag early trend shifts.
Trend-Sensitive Entries:
➣ Combine oscillator signals with log channel direction to filter trades in trend alignment.
➣ Signal line crossovers inside the channel act as early warning for momentum turns.
The Log Regression Oscillator Channel transforms how traders view classic momentum tools. By embedding oscillators into a logarithmic trend structure, it offers unmatched clarity on momentum positioning relative to price expansion. Ideal for swing traders, mean-reverters, or trend followers looking to sharpen entries and exits with style.
MA Smoothed RSI For Loop | OpusMA Smoothed RSI For Loop | Opus
Technical Indicator Overview
The MA Smoothed RSI For Loop | Opus is an innovative technical tool 🛠️ that combines traditional RSI with multiple moving average smoothing options and a unique for-loop calculation method. This indicator provides enhanced trend detection and momentum analysis by applying customizable moving averages to the RSI calculation and implementing a weighted comparison system across multiple timeframes.
Key Features 🌟
• Multi-MA Smoothing Options ✅: Supports 8 different moving average types (EMA, SMA, WMA, VWMA, HMA, RMA, DEMA, or None) for RSI smoothing 📊
• Weighted For-Loop Analysis 🔄: Implements a sophisticated loop calculation that compares current values against historical data with optional weighting ⚡
• Dynamic Color Signals 🎨: Features customizable color themes (Synthwave, Origins, Outrun, Lush, Eighties, Sapphire, Scarlet Blues) for enhanced visual interpretation 🎯
• Comprehensive Dashboard 📊: Includes a detailed information panel with signal strength, trend direction, and duration metrics 📈
Usage Guidelines 📋
• Bullish Signal (Above Upper Threshold) ✅: Enter long positions when the indicator crosses above the upper threshold (default 40) 🚀
• Bearish Signal (Below Lower Threshold) ❌: Consider short positions when the indicator falls below the lower threshold (default -40) 🛑
• Trend Confirmation : Use the weighted for-loop calculation to confirm trend strength and direction 💪
• Signal Stars : Watch for decorative signal markers that appear at trend changes ⭐
Customizable Settings ⚙️
RSI Settings :
• Length : Adjust the RSI calculation period (default: 14) 🔧
• Source : Select price source for RSI calculation (default: close) 📊
Moving Average Options :
• Type : Choose from 8 different MA types for smoothing 📈
• Smooth Length : Set the period for MA smoothing (default: 3) ⚙️
For Loop Parameters :
• Range : Define the comparison range (default: 1 to 50) 🔄
• Weighted Calculation: Toggle weighted vs. unweighted comparison 🎚️
Threshold Settings :
• Upper Threshold: Adjust bullish signal level (default: 40) 📈
• Lower Threshold: Adjust bearish signal level (default: -40) 📉
Applications 🌍
The MA Smoothed RSI For Loop | Opus is particularly effective for:
• Trend identification and confirmation across multiple timeframes
• Momentum analysis with reduced noise through MA smoothing
• Entry and exit signal generation with customizable sensitivity
• Market regime detection through the weighted for-loop calculation
Technical Methodology (Bonus Section) 🔍
1. RSI Calculation :
• Computes traditional RSI using the specified price source and length
• Applies the selected moving average type to smooth the RSI values
2. For-Loop Analysis :
• Compares current values against historical data within the specified range
• Implements optional weighting to give more importance to recent price action
3. Signal Generation :
• Generates signals based on threshold crossings
• Calculates trend strength and duration for additional confirmation
The indicator includes built-in alerts for both long and short signals, a customizable dashboard with three display styles (Minimal, Standard, Full), decorative elements like pulse effects and signal stars for enhanced visualization, and supports multiple color themes for different visual preferences.
All under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) © 2025 Opus Capital 💼.
Volume Flow with Bollinger Bands and EMA Cross SignalsThe Volume Flow with Bollinger Bands and EMA Cross Signals indicator is a custom technical analysis tool designed to identify potential buy and sell signals based on several key components:
Volume Flow: This component combines price movement and trading volume to create a signal that indicates the strength or weakness of price movements. When the price is rising with increasing volume, it suggests strong buying activity, whereas falling prices with increasing volume indicate strong selling pressure.
Bollinger Bands: Bollinger Bands consist of three lines:
The Basis (middle line), which is a Simple Moving Average (SMA) of the price over a set period.
The Upper Band, which is the Basis plus a multiple of the standard deviation (typically 2).
The Lower Band, which is the Basis minus a multiple of the standard deviation. Bollinger Bands help identify periods of high volatility and potential overbought/oversold conditions. When the price touches the upper band, it might indicate that the market is overbought, while touching the lower band might indicate oversold conditions.
EMA Crossovers: The script includes two Exponential Moving Averages (EMAs):
Fast EMA: A shorter-term EMA, typically more sensitive to price changes.
Slow EMA: A longer-term EMA, responding slower to price changes. The crossover of the Fast EMA crossing above the Slow EMA (bullish crossover) signals a potential buy opportunity, while the Fast EMA crossing below the Slow EMA (bearish crossover) signals a potential sell opportunity.
Background Color and Candle Color: The indicator highlights the chart's background with specific colors based on the signals:
Green background for buy signals.
Yellow background for sell signals. Additionally, the candles are colored green for buy signals and yellow for sell signals to visually reinforce the trade opportunities.
Buy/Sell Labels: Small labels are placed on the chart:
"BUY" label in green is placed below the bar when a buy signal is generated.
"SELL" label in yellow is placed above the bar when a sell signal is generated.
Working of the Indicator:
Volume Flow Calculation: The Volume Flow is calculated by multiplying the price change (current close minus the previous close) with the volume. This product is then smoothed with a Simple Moving Average (SMA) over a user-defined period (length). The result is then multiplied by a multiplier to adjust its sensitivity.
Price Change = close - close
Volume Flow = Price Change * Volume
Smoothed Volume Flow = SMA(Volume Flow, length)
The Volume Flow Signal is then: Smooth Volume Flow * Multiplier
This calculation represents the buying or selling pressure in the market.
Bollinger Bands: Bollinger Bands are calculated using the Simple Moving Average (SMA) of the closing price (basis) and the Standard Deviation (stdev) of the price over a period defined by the user (bb_length).
Basis (Middle Band) = SMA(close, bb_length)
Upper Band = Basis + (bb_std_dev * Stdev)
Lower Band = Basis - (bb_std_dev * Stdev)
The upper and lower bands are plotted alongside the price to identify the price's volatility. When the price is near the upper band, it could be overbought, and near the lower band, it could be oversold.
EMA Crossovers: The Fast EMA and Slow EMA are calculated using the Exponential Moving Average (EMA) function. The crossovers are detected by checking:
Buy Signal (Bullish Crossover): When the Fast EMA crosses above the Slow EMA.
Sell Signal (Bearish Crossover): When the Fast EMA crosses below the Slow EMA.
The long_condition variable checks if the Fast EMA crosses above the Slow EMA, and the short_condition checks if it crosses below.
Visual Signals:
Background Color: The background is colored green for a buy signal and yellow for a sell signal. This gives an immediate visual cue to the trader.
Bar Color: The candles are colored green for buy signals and yellow for sell signals.
Labels:
A "BUY" label in green appears below the bar when the Fast EMA crosses above the Slow EMA.
A "SELL" label in yellow appears above the bar when the Fast EMA crosses below the Slow EMA.
Summary of Buy/Sell Logic:
Buy Signal:
The Fast EMA crosses above the Slow EMA (bullish crossover).
Volume flow is positive, indicating buying pressure.
Background turns green and candles are colored green.
A "BUY" label appears below the bar.
Sell Signal:
The Fast EMA crosses below the Slow EMA (bearish crossover).
Volume flow is negative, indicating selling pressure.
Background turns yellow and candles are colored yellow.
A "SELL" label appears above the bar.
Usage of the Indicator:
This indicator is designed to help traders identify potential entry (buy) and exit (sell) points based on:
The interaction of Exponential Moving Averages (EMAs).
The strength and direction of Volume Flow.
Price volatility using Bollinger Bands.
By combining these components, the indicator provides a comprehensive view of market conditions, helping traders make informed decisions on when to enter and exit trades.
Multi-Oscillator Adaptive Kernel | OpusMulti-Oscillator Adaptive Kernel | Opus 📈
Technical Indicator Overview
The Multi-Oscillator Adaptive Kernel (MOAK) | Opus is a sophisticated technical analysis tool 🛠️ that combines multiple oscillators—RSI, Stochastic, MFI, and CCI—through advanced kernel-based smoothing algorithms.
Designed to filter market noise and deliver clear trend signals, this indicator provides traders with a comprehensive, adaptive view of momentum across various timeframes.
Key Features 🌟
Oscillator Fusion : Integrates normalized readings from RSI, Stochastic, MFI, and CCI for a holistic momentum assessment.
Advanced Kernel Smoothing : Offers three kernel types—Exponential, Linear, and Gaussian—to refine signals and reduce noise.
Customizable Sensitivity : Allows adjustment of lookback periods, kernel length, and sensitivity for tailored responsiveness.
Clear Visual Signals : Displays trend shifts with a color-coded signal line (cyan for bullish, magenta for bearish) and gradient fills for trend intensity.
Overbought/Oversold Zones : Uses a zero line to highlight momentum extremes, with gradient layers indicating signal strength.
Adaptive Signal Design : Dynamically adjusts to market conditions, enhancing reliability across trends and ranges.
Usage Guidelines 📋
Bullish Momentum (Cyan) : Enter long positions when the signal line rises above the zero line, indicating upward momentum.
Bearish Momentum (Magenta) : Consider shorts or exits when the signal line falls below the zero line, signaling downward momentum.
Trend Shifts : Monitor the signal line’s direction and gradient intensity to anticipate momentum changes .
Overbought/Oversold Conditions : Watch for extreme values relative to the zero line to identify potential reversals or pullbacks.
Customizable Settings ⚙️
Oscillator Selection : Enable/disable RSI, Stochastic, MFI, or CCI, and adjust their lookback periods (default: 14 for RSI/Stochastic/MFI, 20 for CCI).
Kernel Type : Choose Exponential (trend-focused), Linear (balanced), or Gaussian (range-friendly) smoothing (default: Exponential) .
Kernel Length : Set the smoothing period (default: 25) for the kernel function.
Sensitivity : Fine-tune responsiveness (default: 1.5) to market changes.
Display Options : Toggle bar coloring and customize gradient layers for a personalized visual experience .
Applications 🌍
The Multi-Oscillator Adaptive Kernel | Opus is a versatile tool for traders seeking noise-filtered momentum signals. Its fusion of multiple oscillators, adaptive kernel smoothing, and gradient visualization makes it ideal for trend-following, counter-trend strategies, and multi-timeframe analysis, offering actionable insights in diverse market conditions .
Technical Methodology (Bonus Section) 🔍
1. Oscillator Fusion : Normalizes and combines RSI, Stochastic, MFI, and CCI values, scaling them around a zero baseline.
2. Kernel Smoothing : Applies Exponential, Linear, or Gaussian kernel weighting to smooth the combined oscillator data, with a secondary smoothing layer for trend confirmation.
3. Visualization : Plots a main signal line with gradient fills (10 layers per side) to reflect trend strength, alongside bar coloring for trend direction.
All under a Creative Commons Attribution-Non Commercial 4.0 International License (CC BY-NC 4.0) © 2025 Opus Capital.
Liquidity Heatmap SwiftEdgeDescription
Liquidity Heatmap with Buy/Sell Side (Blue/Red) is a technical analysis tool designed to help traders identify potential liquidity zones in the market by combining swing high/low detection with volume analysis, visualized as a heatmap overlay on the chart. This script highlights areas where significant buying or selling pressure may exist, often acting as support or resistance levels, and provides a clear visual representation of these zones using color-coded heatmap boxes and labeled bubbles.
What It Does
The script identifies key price levels (swing highs and lows) where liquidity is likely to be concentrated, such as stop-loss clusters or pending orders. These levels are then grouped into a heatmap, with blue zones representing potential buy-side liquidity (below the current price) and red zones indicating sell-side liquidity (above the current price). Each zone is marked with a bubble showing the estimated liquidity amount, derived from volume data, to help traders gauge the strength of the level.
How It Works
The script combines three main components to create a comprehensive liquidity visualization:
Swing Highs and Lows Detection:
The script uses the ta.pivothigh and ta.pivotlow functions to identify swing highs and lows over a user-defined lookback period (Swing Length). These levels often represent areas where price has reversed, indicating potential liquidity zones where stop-losses or pending orders may be placed.
Volume Analysis:
Volume data at each swing high/low is captured and averaged over a specified period (Volume Average Length). This volume is then scaled using a multiplier (Volume Multiplier for Liquidity) to estimate the liquidity amount at each level, displayed in thousands (e.g., "10K") on the chart via labeled bubbles.
Heatmap Visualization:
The identified levels are grouped into price bins to form a heatmap. The price range is divided into a user-defined number of bins (Number of Heatmap Bins), and each bin is drawn as a colored box (blue for buy-side, red for sell-side). The transparency of the heatmap boxes can be adjusted (Heatmap Transparency) to ensure they do not obscure the price action.
Why Combine These Components?
The combination of swing highs/lows, volume analysis, and a heatmap provides a powerful way to visualize liquidity in the market. Swing highs and lows are natural points where liquidity tends to accumulate, as they often coincide with areas where traders place stop-losses or pending orders. By incorporating volume data, the script quantifies the potential strength of these levels, giving traders insight into the magnitude of liquidity present. The heatmap visualization then aggregates these levels into a clear, color-coded overlay, making it easy to see where buy-side and sell-side liquidity is concentrated without cluttering the chart.
This mashup is particularly useful because it bridges price action (swing levels), market activity (volume), and visual clarity (heatmap), offering a holistic view of potential support and resistance zones that might influence price movements.
How to Use It
Add the Indicator to Your Chart:
Apply the script to your chart by adding it from the Pine Script library. It will overlay directly on your price chart.
Interpret the Heatmap:
Blue Zones (Buy-Side Liquidity): These appear below the current price and indicate levels where buying pressure or stop-losses from short positions may be located.
Red Zones (Sell-Side Liquidity): These appear above the current price and indicate levels where selling pressure or stop-losses from long positions may be located.
The intensity of the color is controlled by the Heatmap Transparency setting—lower values make the zones more opaque, while higher values make them more transparent.
Analyze the Bubbles:
Each liquidity zone is marked with a bubble showing the estimated liquidity amount in thousands (e.g., "10K"). The size of the bubble is scaled by the Bubble Size Multiplier, with larger bubbles indicating higher liquidity.
Adjust Settings for Your Needs:
Liquidity Settings:
Swing Length: Controls the lookback period for detecting swing highs and lows. A smaller value (e.g., 10) is better for shorter timeframes like 1-minute charts, while a larger value (e.g., 50) suits higher timeframes.
Liquidity Threshold: Defines how close two levels must be to be considered the same, preventing duplicate zones.
Volume Average Length: Sets the period for averaging volume data at swing points.
Volume Multiplier for Liquidity: Scales the volume to estimate liquidity amounts shown in the bubbles.
Lookback Period (Hours): Limits how far back the script looks for liquidity zones.
Use Price Window Filter: If enabled, only shows zones within a price range defined by Liquidity Window (Points per Side).
Heatmap Settings:
Number of Heatmap Bins: Determines how many price bins the heatmap is divided into. More bins create a finer resolution but may clutter the chart.
Heatmap Bin Height (Points): Sets the vertical height of each heatmap box in price points.
Heatmap Transparency: Adjusts the transparency of the heatmap boxes (0 = fully opaque, 100 = fully transparent).
Display Settings:
Bubble Size Multiplier: Scales the size of the bubbles showing liquidity amounts.
Trading Application:
Use the heatmap to identify potential support (blue zones) and resistance (red zones) levels where price may react.
Pay attention to zones with larger bubbles, as they indicate higher liquidity and may have a stronger impact on price.
Combine with other analysis tools (e.g., trendlines, indicators) to confirm trade setups.
What Makes It Original?
This script stands out by integrating swing high/low detection with volume-based liquidity estimation and a heatmap visualization in a single tool. Unlike traditional support/resistance indicators that only plot static lines, this script dynamically aggregates liquidity zones into a heatmap, making it easier to see clusters of potential buying or selling pressure. The addition of volume-derived liquidity amounts in labeled bubbles provides a unique quantitative measure of each zone's strength, helping traders prioritize key levels. The color-coded buy/sell distinction further enhances its utility by visually separating zones based on their likely market impact.
Example Use Case
On a 1-minute chart of EUR/USD, you might set Swing Length to 10 to capture short-term pivots, Lookback Period (Hours) to 4 to focus on recent data, and Liquidity Window to 200 points (20 pips) to show only nearby zones. The heatmap will then display blue zones below the current price where buy-side liquidity may act as support, and red zones above where sell-side liquidity may act as resistance. A bubble showing "50K" at a blue zone indicates significant buy-side liquidity, suggesting a potential bounce if the price approaches that level.
DEMA SuperTrend | OpusDEMA SuperTrend | Opus
Technical Indicator Overview
The DEMA SuperTrend | Opus is an advanced trend-following indicator 🛠️ that enhances the traditional Supertrend with Double Exponential Moving Average (DEMA) smoothing for improved responsiveness and reduced lag. Overlaying directly on the price chart, this indicator offers dynamic trend detection with customizable themes, making it a versatile tool for traders navigating market movements.
Key Features 🌟
DEMA-Enhanced Supertrend ✅: Integrates DEMA smoothing (default length: 9) with Supertrend calculations for sharper trend signals.
Adaptive Trend Lines 📉: Plots uptrend and downtrend lines that adjust based on price action and volatility, with customizable color themes.
Buy & Sell Signals 🚦: Marks entry points with ▲ for long signals and ▼ for short signals when trend direction shifts.
Gradient Visualization 🎨: Features a multi-layered gradient fill between the Supertrend line and price, reflecting trend intensity with a thematic color scheme.
Customizable Themes 💡: Offers seven visual themes (Synthwave, Outrun, Lush, Eighties, Sapphire, Scarlet Blues, Origins) to personalize the display.
Custom Alerts 🔔: Provides real-time notifications for long and short signals to keep traders informed.
Usage Guidelines 📋
Long Signal (▲) ✅: Enter long positions when the trend shifts to an uptrend (marked by ▲), indicated by the uptrend line, suggesting bullish momentum.
Short Signal (▼) ❌: Exit or short when the trend shifts to a downtrend (marked by ▼), supported by the downtrend line, signaling bearish momentum.
Trend Confirmation: Follow the Supertrend line’s direction—uptrend for bullish, downtrend for bearish—to align with market trends.
Volatility Insight: Monitor gradient intensity—darker fills indicate stronger trends, while lighter fills suggest weakening momentum.
Customizable Settings ⚙️
Supertrend Parameters: Adjust Supertrend length (default: 2) and multiplier (default: 3.35) to control band sensitivity 🔧.
DEMA Settings: Set DEMA length (default: 9) and select the source (default: HLC3) for smoothing 🎚️.
Visualization Theme: Choose from Synthwave, Outrun, Lush, Eighties, Sapphire, Scarlet Blues, or Origins to customize colors 📏.
Gradient Options: Modify gradient layer count (default: 5) and opacity (max: 50) for a tailored visual effect 🖌️.
Applications 🌍
The DEMA SuperTrend | Opus is ideal for traders seeking a responsive, visually appealing tool for trend-following strategies. Its DEMA-enhanced design, thematic customization, and gradient visualization make it perfect for identifying trend direction, timing entries/exits, and adapting to various market conditions.
All under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) © 2025 Opus Capital 💼.
Dynamic Momentum Bands | OpusDynamic Momentum Bands | Opus
Technical Indicator Overview
The Dynamic Momentum Bands indicator is a sophisticated technical analysis tool 🛠️ that fuses multiple methodologies—RSI (Relative Strength Index), volatility analysis, and adaptive moving averages—to deliver a comprehensive view of market momentum and trend dynamics. This indicator provides traders with a nuanced, actionable perspective on evolving market conditions.
Key Features 🌟
Adaptive Band Calculation ✅ : Dynamically adjusts band width based on price momentum for responsive trend tracking.
Integrated RSI-Driven Volatility Scaling 📊 : Incorporates RSI to modulate band sensitivity, reflecting market volatility shifts.
Multiple Moving Average Options ⚙️ : Supports EMA, SMA, and VWMA for customizable band construction.
Smooth Gradient-Based Visualization 🎨 : Features fluid, color-coded bands for intuitive trend interpretation.
Optional Price Bar Coloring 🌈 : Enhances trend identification with color-coded price bars alongside the bands.
Usage Guidelines 📋
Bullish Trend (Blue Bands) ✅ : Enter long positions when price moves above the bands and RSI approaches or exceeds 50, signaling upward momentum.
Bearish Trend (Pink Bands) ❌ : Consider exiting or shorting when price falls below the bands and RSI drops toward 50 or lower, indicating weakening momentum.
Momentum Shifts : Monitor color transitions and gradient intensity to anticipate trend changes ⚠️.
Volatility Insights : Observe widening bands for breakouts or narrowing bands for consolidation, using RSI context to confirm 💪.
Customizable Settings ⚙️
Price Source : Select the price data (e.g., close, high/low) for calculations 🔧.
RSI Length : Adjust the RSI period (1-50) to suit your timeframe 🎚️.
Band Length : Set the moving average period (5-100) for band smoothing 📏.
Volatility Multiplier : Fine-tune band width to match market conditions 📐.
Band Type : Choose between EMA, SMA, or VWMA for tailored analysis 🔄.
Visual Options : Toggle bar coloring, gradient styles, and color transitions for a personalized display 🖌️.
Applications 🌍
The Dynamic Momentum Bands | Opus is a versatile tool for traders aiming to capture trends and assess volatility with precision. Its integration of RSI-driven scaling, adaptive bands, and visual clarity makes it ideal for trend-following strategies, breakout detection, and market context analysis across diverse trading environments 💼.
Technical Methodology (Bonus Section) 🔍
1. Momentum Calculation :
- Computes RSI with a customizable length.
- Adjusts band volatility based on RSI's distance from the 50 level.
2. Band Construction :
- Applies the selected moving average to the price source.
- Calculates deviations using ATR (Average True Range) for band width.
- Smooths band edges for enhanced visual readability.
All under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) © 2025 Opus Capital 💼.
TriTrend Nexus[BullByte]TriTrend Nexus is a comprehensive market analysis tool that consolidates three well-established signals into a single, easy-to-read interface. It is designed to help traders quickly assess the market’s current condition and make more informed decisions about potential trend shifts.
Key Features and Functionality
Composite Signal System
Multi-Faceted Approach :
The indicator combines insights from three distinct market signals into one composite score. This approach provides a more holistic view of market conditions compared to relying on a single indicator.
Clear Classification :
Based on the composite score, TriTrend Nexus categorizes the market into:
Strong Signals : When all three underlying conditions are met, indicating a robust and established trend.
Early Signals : When two out of the three conditions are met, offering an early hint of a potential trend.
Neutral/Choppy : When conditions are ambiguous or conflicting, suggesting a lack of clear market direction.
Trend Qualifiers :
In addition to the composite score, the indicator subtly refines its signal by noting whether a trend is “Rising” or “Fading.” This further aids traders in understanding the momentum behind the signal.
Dynamic Signal Identification
Timely Alerts :
By analyzing the composite data in real time, the indicator quickly identifies when market conditions shift, offering early warning signals that help traders stay ahead of the market.
Adaptive Analysis :
The built-in signal assessment continuously monitors market changes. Whether the market is in the early stages of a move or firmly committed to a trend, TriTrend Nexus adapts its messaging to reflect the evolving conditions.
User-Friendly Dashboard
Integrated Display :
A customizable dashboard provides an at-a-glance summary of key metrics. Users can choose between a detailed view for comprehensive insights or a compact version for a streamlined experience.
Key Metrics Displayed :
Primary Signal : The overall market status, such as “Bullish Strong” or “Bearish Early.”
Composite Nexus Score : A numerical value representing the strength of the current market conditions.
Supporting Data : Essential values that help explain the current signal without overwhelming the trader.
Easy Interpretation :
The dashboard is designed with clarity in mind. Clear labeling and a consistent layout ensure that even traders new to composite indicators can quickly interpret the displayed information.
Visual Clarity and Aesthetic
Color-Coded Signals :
The indicator uses a vibrant color scheme to highlight market conditions:
Bright Green : Signifies a strong bullish trend.
Light Green : Indicates an emerging bullish trend.
Red : Represents a strong bearish trend.
Light Red/Pink : Denotes an early bearish signal.
Gray : Used when market conditions are neutral or choppy.
Graphical Enhancements :
The plotted oscillator visually reinforces the signal classifications with dynamic color transitions. Horizontal markers provide reference points to help traders easily compare the current readings against standard levels.
Customization Options
Adjustable Settings :
Traders can personalize the indicator by modifying input settings such as sensitivity thresholds and period lengths. This flexibility allows the tool to adapt to different market environments and trading styles.
Dashboard Flexibility :
The option to toggle between a full dashboard and a shorter version means that both novice and experienced traders can configure the display to best suit their needs. A more detailed dashboard offers extensive insights, while the compact mode provides a minimalist view for those who prefer simplicity.
Tailored User Experience :
With multiple adjustable parameters, users can fine-tune the indicator to respond precisely to their preferred timeframes and market conditions. This adaptability makes TriTrend Nexus a versatile tool for various trading strategies.
Benefits for Traders
Quick and Informed Decision-Making :
With a single glance at the dashboard and visual cues from the oscillator, traders can quickly gauge whether the market is poised for a strong move, is in the early stages of a trend, or is too volatile for clear signals. This helps in planning timely entries and exits.
Enhanced Market Insight :
By integrating multiple perspectives into one coherent score, the indicator filters out market noise and highlights the prevailing trend more reliably. This can be particularly useful during periods of market uncertainty.
Reduced Analysis Time:
The combination of clear, color-coded signals and an intuitive dashboard reduces the time spent analyzing various individual indicators, allowing traders to focus more on strategy execution.
Customization for Diverse Strategies :
The ability to adjust various input parameters and the dashboard layout ensures that traders can tailor the tool to fit their unique analysis style and market conditions, making it a versatile addition to any trading toolkit.
User-Friendly Interface :
Even for those who are not technically inclined, the clear visual design and straightforward signal descriptions make it easy to understand the current market situation without needing to interpret complex data.
Adaptive Fibonacci Pullback System -FibonacciFluxAdaptive Fibonacci Pullback System (AFPS) - FibonacciFlux
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Original concepts by FibonacciFlux.
Abstract
The Adaptive Fibonacci Pullback System (AFPS) presents a sophisticated, institutional-grade algorithmic strategy engineered for high-probability trend pullback entries. Developed by FibonacciFlux, AFPS uniquely integrates a proprietary Multi-Fibonacci Supertrend engine (0.618, 1.618, 2.618 ratios) for harmonic volatility assessment, an Adaptive Moving Average (AMA) Channel providing dynamic market context, and a synergistic Multi-Timeframe (MTF) filter suite (RSI, MACD, Volume). This strategy transcends simple indicator combinations through its strict, multi-stage confluence validation logic. Historical simulations suggest that specific MTF filter configurations can yield exceptional performance metrics, potentially achieving Profit Factors exceeding 2.6 , indicative of institutional-level potential, while maintaining controlled risk under realistic trading parameters (managed equity risk, commission, slippage).
4 hourly MTF filtering
1. Introduction: Elevating Pullback Trading with Adaptive Confluence
Traditional pullback strategies often struggle with noise, false signals, and adapting to changing market dynamics. AFPS addresses these challenges by introducing a novel framework grounded in Fibonacci principles and adaptive logic. Instead of relying on static levels or single confirmations, AFPS seeks high-probability pullback entries within established trends by validating signals through a rigorous confluence of:
Harmonic Volatility Context: Understanding the trend's stability and potential turning points using the unique Multi-Fibonacci Supertrend.
Adaptive Market Structure: Assessing the prevailing trend regime via the AMA Channel.
Multi-Dimensional Confirmation: Filtering signals with lower-timeframe Momentum (RSI), Trend Alignment (MACD), and Market Conviction (Volume) using the MTF suite.
The objective is to achieve superior signal quality and adaptability, moving beyond conventional pullback methodologies.
2. Core Methodology: Synergistic Integration
AFPS's effectiveness stems from the engineered synergy between its core components:
2.1. Multi-Fibonacci Supertrend Engine: Utilizes specific Fibonacci ratios (0.618, 1.618, 2.618) applied to ATR, creating a multi-layered volatility envelope potentially resonant with market harmonics. The averaged and EMA-smoothed result (`smoothed_supertrend`) provides a robust, dynamic trend baseline and context filter.
// Key Components: Multi-Fibonacci Supertrend & Smoothing
average_supertrend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_supertrend = ta.ema(average_supertrend, st_smooth_length)
2.2. Adaptive Moving Average (AMA) Channel: Provides dynamic market context. The `ama_midline` serves as a key filter in the entry logic, confirming the broader trend bias relative to adaptive price action. Extended Fibonacci levels derived from the channel width offer potential dynamic S/R zones.
// Key Component: AMA Midline
ama_midline = (ama_high_band + ama_low_band) / 2
2.3. Multi-Timeframe (MTF) Filter Suite: An optional but powerful validation layer (RSI, MACD, Volume) assessed on a lower timeframe. Acts as a **validation cascade** – signals must pass all enabled filters simultaneously.
2.4. High-Confluence Entry Logic: The core innovation. A pullback entry requires a specific sequence and validation:
Price interaction with `average_supertrend` and recovery above/below `smoothed_supertrend`.
Price confirmation relative to the `ama_midline`.
Simultaneous validation by all enabled MTF filters.
// Simplified Long Entry Logic Example (incorporates key elements)
long_entry_condition = enable_long_positions and
(low < average_supertrend and close > smoothed_supertrend) and // Pullback & Recovery
(close > ama_midline and close > ama_midline) and // AMA Confirmation
(rsi_filter_long_ok and macd_filter_long_ok and volume_filter_ok) // MTF Validation
This strict, multi-stage confluence significantly elevates signal quality compared to simpler pullback approaches.
1hourly filtering
3. Realistic Implementation and Performance Potential
AFPS is designed for practical application, incorporating realistic defaults and highlighting performance potential with crucial context:
3.1. Realistic Default Strategy Settings:
The script includes responsible default parameters:
strategy('Adaptive Fibonacci Pullback System - FibonacciFlux', shorttitle = "AFPS", ...,
initial_capital = 10000, // Accessible capital
default_qty_type = strategy.percent_of_equity, // Equity-based risk
default_qty_value = 4, // Default 4% equity risk per initial trade
commission_type = strategy.commission.percent,
commission_value = 0.03, // Realistic commission
slippage = 2, // Realistic slippage
pyramiding = 2 // Limited pyramiding allowed
)
Note: The default 4% risk (`default_qty_value = 4`) requires careful user assessment and adjustment based on individual risk tolerance.
3.2. Historical Performance Insights & Institutional Potential:
Backtesting provides insights into historical behavior under specific conditions (always specify Asset/Timeframe/Dates when sharing results):
Default Performance Example: With defaults, historical tests might show characteristics like Overall PF ~1.38, Max DD ~1.16%, with potential Long/Short performance variance (e.g., Long PF 1.6+, Short PF < 1).
Optimized MTF Filter Performance: Crucially, historical simulations demonstrate that meticulous configuration of the MTF filters (particularly RSI and potentially others depending on market) can significantly enhance performance. Under specific, optimized MTF filter settings combined with appropriate risk management (e.g., 7.5% risk), historical tests have indicated the potential to achieve **Profit Factors exceeding 2.6**, alongside controlled drawdowns (e.g., ~1.32%). This level of performance, if consistently achievable (which requires ongoing adaptation), aligns with metrics often sought in institutional trading environments.
Disclaimer Reminder: These results are strictly historical simulations. Past performance does not guarantee future results. Achieving high performance requires careful parameter tuning, adaptation to changing markets, and robust risk management.
3.3. Emphasizing Risk Management:
Effective use of AFPS mandates active risk management. Utilize the built-in Stop Loss, Take Profit, and Trailing Stop features. The `pyramiding = 2` setting requires particularly diligent oversight. Do not rely solely on default settings.
4. Conclusion: Advancing Trend Pullback Strategies
The Adaptive Fibonacci Pullback System (AFPS) offers a sophisticated, theoretically grounded, and highly adaptable framework for identifying and executing high-probability trend pullback trades. Its unique blend of Fibonacci resonance, adaptive context, and multi-dimensional MTF filtering represents a significant advancement over conventional methods. While requiring thoughtful implementation and risk management, AFPS provides discerning traders with a powerful tool potentially capable of achieving institutional-level performance characteristics under optimized conditions.
Acknowledgments
Developed by FibonacciFlux. Inspired by principles of Fibonacci analysis, adaptive averaging, and multi-timeframe confirmation techniques explored within the trading community.
Disclaimer
Trading involves substantial risk. AFPS is an analytical tool, not a guarantee of profit. Past performance is not indicative of future results. Market conditions change. Users are solely responsible for their decisions and risk management. Thorough testing is essential. Deploy at your own considered risk.
Market Flow Exit SignalsThis Market Flow indicator with Exit Signals is a customized momentum oscillator that measures buying and selling pressure using price and volume data.
THIS IS ONLY AN EXIT SIGNAL INDICATOR - No Entry Signals Are Given.
This version plots as a clean step-line for clarity, with visual overbought and oversold zones marked at 80 and 20, respectively.
The overbought and oversold values can be changed by the user to your preference depending how sensitive you want the exit signals to be given.
Similar to RSI, when the line crosses above the overbought level or below the oversold level, it can signal potential exit points from a smooth flowing market.
These signals are designed to help traders lock in profits or avoid reversals by identifying when market momentum may be shifting.
Exit signals only appear in the Indicator pane and not directly on your chart.
I offer a separate indicator in my scripts that plots these above/below candles if you prefer that view instead.
Reversal Trading Bot Strategy[BullByte]Overview :
The indicator Reversal Trading Bot Strategy is crafted to capture potential market reversal points by combining momentum, volatility, and trend alignment filters. It uses a blend of technical indicators to identify both bullish and bearish reversal setups, ensuring that multiple market conditions are met before entering a trade.
Core Components :
Technical Indicators Used :
RSI (Relative Strength Index) :
Purpose : Detects divergence conditions by comparing recent lows/highs in price with the RSI.
Parameter : Length of 8.
Bollinger Bands (BB) :
Purpose : Measures volatility and identifies price levels that are statistically extreme.
Parameter : Length of 20 and a 2-standard deviation multiplier.
ADX (Average Directional Index) & DMI (Directional Movement Index) :
Purpose : Quantifies the strength of the trend. The ADX threshold is set at 20, and additional filters check for the alignment of the directional indicators (DI+ and DI–).
ATR (Average True Range) :
Purpose : Provides a volatility measure used to set stop levels and determine risk through trailing stops.
Volume SMA (Simple Moving Average of Volume ):
Purpose : Helps confirm strength by comparing the current volume against a 20-period average, with an optional filter to ensure volume is at least twice the SMA.
User-Defined Toggle Filters :
Volume Filter : Confirms that the volume is above average (or twice the SMA) before taking trades.
ADX Trend Alignment Filter : Checks that the ADX’s directional indicators support the trade direction.
BB Close Confirmation : Optionally refines the entry by requiring price to be beyond the upper or lower Bollinger Band rather than just above or below.
RSI Divergence Exit : Allows the script to close positions if RSI divergence is detected.
BB Mean Reversion Exit : Closes positions if the price reverts to the Bollinger Bands’ middle line.
Risk/Reward Filter : Ensures that the potential reward is at least twice the risk by comparing the distance to the Bollinger Band with the ATR.
Candle Movement Filter : Optional filter to require a minimum percentage move in the candle to confirm momentum.
ADX Trend Exit : Closes positions if the ADX falls below the threshold and the directional indicators reverse.
Entry Conditions :
Bullish Entry :
RSI Divergence : Checks if the current close is lower than a previous low while the RSI is above the previous low, suggesting bullish divergence.
Bollinger Confirmation : Requires that the price is above the lower (or upper if confirmation is toggled) Bollinger Band.
Volume & Trend Filters : Combines volume condition, ADX strength, and an optional candle momentum condition.
Risk/Reward Check : Validates that the trade meets a favorable risk-to-reward ratio.
Bearish Entry :
Uses a mirror logic of the bullish entry by checking for bearish divergence, ensuring the price is below the appropriate Bollinger level, and confirming volume, trend strength, candle pattern, and risk/reward criteria.
Trade Execution and Exit Strateg y:
Trade Execution :
Upon meeting the entry conditions, the strategy initiates a long or short position.
Stop Loss & Trailing Stops :
A stop-loss is dynamically set using the ATR value, and trailing stops are implemented as a percentage of the close price.
Exit Conditions :
Additional exit filters can trigger early closures based on RSI divergence, mean reversion (via the middle Bollinger Band), or a weakening trend as signaled by ADX falling below its threshold.
This multi-layered exit strategy is designed to lock in gains or minimize losses if the market begins to reverse unexpectedly.
How the Strategy Works in Different Market Conditions :
Trending Markets :
The ADX filter ensures that trades are only taken when the trend is strong. When the market is trending, the directional movement indicators help confirm the momentum, making the reversal signal more reliable.
Ranging Markets :
In choppy markets, the Bollinger Bands expand and contract, while the RSI divergence can highlight potential turning points. The optional filters can be adjusted to avoid false signals in low-volume or low-volatility conditions.
Volatility Management :
With ATR-based stop-losses and a risk/reward filter, the strategy adapts to current market volatility, ensuring that risk is managed consistently.
Recommendation on using this Strategy with a Trading Bot :
This strategy is well-suited for high-frequency trading (HFT) due to its ability to quickly identify reversal setups and execute trades dynamically with automated stop-loss and trailing exits. By integrating this script with a TradingView webhook-based bot or an API-driven execution system, traders can automate trade entries and exits in real-time, reducing manual execution delays and capitalizing on fast market movements.
Disclaimer :
This script is provided for educational and informational purposes only. It is not intended as investment advice. Trading involves significant risk, and you should always conduct your own research and analysis before making any trading decisions. The author is not responsible for any losses incurred while using this script.
Z SMMA | QuantEdgeB📈 Introducing Z-Score SMMA (Z SMMA) by QuantEdgeB
🛠️ Overview
Z SMMA is a momentum-driven oscillator designed to track the standardized deviation of a Smoothed Moving Average (SMMA). By applying Z-score normalization, this tool dynamically adapts to price volatility, enabling traders to detect meaningful directional shifts and trend changes with enhanced clarity.
It serves both as a trend-following and mean-reversion system, identifying opportunities through standardized thresholds while remaining robust across volatile and calm market conditions.
✨ Key Features
🔹 Z-Score Normalization Engine
Applies Z-score to a custom SMMA baseline, allowing traders to compare price action relative to its recent volatility-adjusted mean.
🔹 Dynamic Trend Detection
Generates actionable long/short signals based on customizable Z-thresholds, making it adaptable across different asset classes and timeframes.
🔹 Overbought/Oversold Zones
Highlight reversion and profit-taking zones (default OB: +2 to +4, OS: -2 to -4), great for counter-trend or mean-reversion strategies.
🔹 Visual Reinforcement Tools
Includes candle coloring, gradient fills, and optional ALMA/EMA band overlays to visualize trend regime transitions.
🔍 How It Works
1️⃣ Z-Score SMMA Calculation
The core is a custom Smoothed Moving Average (SMMA) that is normalized by its standard deviation over a lookback period.
Final Formula:
Z = (SMMA - Mean) / StdDev
2️⃣ Signal Generation
• ✅ Long Bias: Z-Score > Long Threshold (default: 0)
• ❌ Short Bias: Z-Score < Short Threshold (default: 0)
3️⃣ Visual Aids
• Candle Color → Shows trend bias
• Band Fills → Highlight trend strength
• Overlays → Optional ALMA/EMA bands for structure analysis
⚙️ Custom Settings
• SMMA Length → Default: 12
• Z-Score Lookback → Default: 30
• Long Threshold → Default: 0
• Short Threshold → Default: 0
• Color Themes → Choose from 6 visual modes
• Extra Plots → Toggle advanced overlays (ALMA, EMA, bands)
• Label Display → Show/hide “𝓛𝓸𝓷𝓰” & “𝓢𝓱𝓸𝓻𝓽” markers
👥 Who Should Use It?
✅ Trend Traders → For early entries with confirmation from Z-score expansion
✅ Quantitative Analysts → Standardized deviation enables comparison across assets
✅ Mean-Reversion Traders → Use OB/OS zones to fade parabolic spikes
✅ Swing & Systematic Traders → Identify momentum shifts with optional ALMA/EMA overlays
📌 Conclusion
Z SMMA offers a smart, adaptive framework for tracking deviation from equilibrium in a quant-friendly format. Whether you're looking to follow trends or catch exhaustion points, Z SMMA provides a clear, standardized view of momentum and price extremes.
🔹 Key Takeaways:
1️⃣ Z-Score standardization ensures dynamic range awareness
2️⃣ SMMA base filters out noise, offering smoother signals
3️⃣ Color-coded visuals support faster reaction and cleaner charts
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before
Linear % ST | QuantEdgeB🚀 Introducing Linear Percentile SuperTrend (Linear % ST) by QuantEdgeB
🛠️ Overview
Linear % SuperTrend (Linear % ST) by QuantEdgeB is a hybrid trend-following indicator that combines Linear Regression, Percentile Filters, and Volatility-Based SuperTrend Logic into one dynamic tool. This system is designed to identify trend shifts early while filtering out noise during choppy market conditions.
By utilizing percentile-based median smoothing and customized ATR multipliers, this tool captures both breakout momentum and pullback opportunities with precision.
✨ Key Features
🔹 Percentile-Based Median Filtering
Removes outliers and normalizes price movement for cleaner trend detection using the 50th percentile (median) of recent price action.
🔹 Linear Regression Smoothing
A smoothed baseline is computed with Linear Regression to detect the underlying trend while minimizing lag.
🔹 SuperTrend Structure with Adaptive Bands
The indicator implements an enhanced SuperTrend engine with custom ATR bands that adapt to trend direction. Bands tighten or loosen based on volatility and trend strength.
🔹 Dynamic Long/Short Conditions
Long and short signals are derived from the relationship between price and the SuperTrend threshold zones, clearly showing trend direction with optional "Long"/"Short" labels on the chart.
🔹 Multiple Visual Themes
Select from 6 built-in color palettes including Strategy, Solar, Warm, Cool, Classic, and Magic to match your personal style or strategy layout.
📊 How It Works
1️⃣ Percentile Filtering
The source price (default: close) is filtered using a nearest-rank 50th percentile over a custom lookback. This normalizes data to reflect the central tendency and removes noisy extremes.
2️⃣ Linear Regression Trend Base
A Linear Regression Moving Average (LSMA) is applied to the filtered median, forming the core trend line. This dynamic trendline provides a low-lag yet smooth view of market direction.
3️⃣ SuperTrend Engine
ATR is applied with custom multipliers (different for long and short) to create dynamic bands. The bands react to price movement and only shift direction after confirmation, preventing false flips.
4️⃣ Trend Signal Logic
• When price stays above the dynamic lower band → Bullish trend
• When price breaks below the upper band → Bearish trend
• Trend direction remains stable until violated by price.
⚙️ Custom Settings
• Percentile Length → Lookback for percentile smoothing (default: 35)
• LSMA Length → Determines the base trend via linear regression (default: 24)
• ATR Length → ATR period used in dynamic bands (default: 14)
• Long Multiplier → ATR multiplier for bullish thresholds (default: 0.8)
• Short Multiplier → ATR multiplier for bearish thresholds (default: 1.9)
✅ How to Use
1️⃣ Trend-Following Strategy
✔️ Go Long when price breaks above the lower ATR band, initiating an upward trend
✔️ Go Short when price falls below the upper ATR band, confirming bearish conditions
✔️ Remain in trend direction until the SuperTrend flips
2️⃣ Visual Confirmation
✔️ Use bar coloring and the dynamic bands to stay aligned with trend direction
✔️ Optional Long/Short labels highlight key signal flips
👥 Who Should Use Linear % ST?
✅ Swing & Position Traders → To ride trends confidently
✅ Trend Followers → As a primary directional filter
✅ Breakout Traders → For clean signal generation post-range break
✅ Quant/Systematic Traders → Integrate clean trend logic into algorithmic setups
📌 Conclusion
Linear % ST by QuantEdgeB blends percentile smoothing with linear regression and volatility bands to deliver a powerful, adaptive trend-following engine. Whether you're a discretionary trader seeking cleaner entries or a systems-based trader building logic for automation, Linear % ST offers clarity, adaptability, and precision in trend detection.
🔹 Key Takeaways:
1️⃣ Percentile + Regression = Noise-Reduced Core Trend
2️⃣ ATR-Based SuperTrend = Reliable Breakout Confirmation
3️⃣ Flexible Parameters + Color Modes = Custom Fit for Any Strategy
📈 Use it to spot emerging trends, filter false signals, and stay confidently aligned with market momentum.
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Quantile DEMA Trend | QuantEdgeB🚀 Introducing Quantile DEMA Trend (QDT) by QuantEdgeB
🛠️ Overview
Quantile DEMA Trend (QDT) is an advanced trend-following and momentum detection indicator designed to capture price trends with superior accuracy. Combining DEMA (Double Exponential Moving Average) with SuperTrend and Quantile Filtering, QDT identifies strong trends while maintaining the ability to adapt to various market conditions.
Unlike traditional trend indicators, QDT uses percentile filtering to adjust for volatility and provides dynamic thresholds, ensuring consistent signal performance across different assets and timeframes.
✨ Key Features
🔹 Trend Following with Adaptive Sensitivity
The DEMA component ensures quicker responses to price changes while reducing lag, offering a real-time reflection of market momentum.
🔹 Volatility-Adjusted Filtering
The SuperTrend logic incorporates quantile percentile filters and ATR (Average True Range) multipliers, allowing QDT to adapt to fluctuating market volatility.
🔹 Clear Signal Generation
QDT generates clear Long and Short signals using percentile thresholds, effectively identifying trend changes and market reversals.
🔹 Customizable Visual & Signal Settings
With multiple color modes and customizable settings, you can easily align the QDT indicator with your trading strategy, whether you're focused on trend-following or volatility adjustments.
📊 How It Works
1️⃣ DEMA Calculation
DEMA is used to reduce lag compared to traditional moving averages. It is calculated by applying a Double Exponential Moving Average to price data. This smoother trend-following mechanism ensures responsiveness to market movements without introducing excessive noise.
2️⃣ SuperTrend with Percentile Filtering
The SuperTrend component adapts the trend-following signal by incorporating quantile percentile filters. It identifies dynamic support and resistance levels based on historical price data:
• Upper Band: Calculated using the 75th percentile + ATR (adjusted with multiplier)
• Lower Band: Calculated using the 25th percentile - ATR (adjusted with multiplier)
These dynamic bands adjust to market conditions, filtering out noise while identifying the true direction.
3️⃣ Signal Generation
• Long Signal: Triggered when price crosses below the SuperTrend Lower Band
• Short Signal: Triggered when price crosses above the SuperTrend Upper Band
The indicator provides signals with corresponding trend direction based on these crossovers.
👁 Visual & Custom Features
• 🎨 Multiple Color Modes: Choose from "Strategy", "Solar", "Warm", "Cool", "Classic", and "Magic" color palettes to match your charting style.
• 🏷️ Long/Short Signal Labels: Optional labels for visual cueing when a long or short trend is triggered.
• 📉 Bar Color Customization: Bar colors dynamically adjust based on trend direction to visually distinguish the market bias.
👥 Who Should Use QDT?
✅ Trend Followers: Use QDT as a dynamic tool to confirm trends and capture profits in trending markets.
✅ Swing Traders: Use QDT to time entries based on confirmed breakouts or breakdowns.
✅ Volatility Traders: Identify market exhaustion or expansion points, especially during volatile periods.
✅ Systematic & Quant Traders: Integrate QDT into algorithmic strategies to enhance market detection with adaptive filtering.
⚙️ Customization & Default Settings
- DEMA Length(30): Controls the lookback period for DEMA calculation
- Percentile Length(10): Sets the lookback period for percentile filtering
- ATR Length(14): Defines the length for calculating ATR (used in SuperTrend)
- ATR Multiplier(1.2 ): Multiplier for ATR in SuperTrend calculation
- SuperTrend Length(30):Defines the length for SuperTrend calculations
📌 How to Use QDT in Trading
1️⃣ Trend-Following Strategy
✔ Enter Long positions when QDT signals a bullish breakout (price crosses below the SuperTrend lower band).
✔ Enter Short positions when QDT signals a bearish breakdown (price crosses above the SuperTrend upper band).
✔ Hold positions as long as QDT continues to provide the same direction.
2️⃣ Reversal Strategy
✔ Take profits when price reaches extreme levels (upper or lower percentile zones) that may indicate trend exhaustion or reversion.
3️⃣ Volatility-Driven Entries
✔ Use the percentile filtering to enter positions based on mean-reversion logic or breakout setups in volatile markets.
🧠 Why It Works
QDT combines the DEMA’s quick response to price changes with SuperTrend's volatility-adjusted thresholds, ensuring a responsive and adaptive indicator. The use of percentile filters and ATR multipliers helps adjust to varying market conditions, making QDT suitable for both trending and range-bound environments.
🔹 Conclusion
The Quantile DEMA Trend (QDT) by QuantEdgeB is a powerful, adaptive trend-following and momentum detection system. By integrating DEMA, SuperTrend, and quantile percentile filtering, it provides accurate and timely signals while adjusting to market volatility. Whether you are a trend follower or volatility trader, QDT offers a robust solution to identify high-probability entry and exit points.
🔹 Key Takeaways:
1️⃣ Trend Confirmation – Uses DEMA and SuperTrend for dynamic trend detection
2️⃣ Volatility Filtering – Adjusts to varying market conditions using percentile logic
3️⃣ Clear Signal Generation – Easy-to-read signals and visual cues for strategy implementation
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Market Flow Exit Alerts On ChartThis Market Flow exit signals measures buying and selling pressure using price and volume data.
These signals are designed to help traders lock in profits or avoid reversals by identifying when market momentum may be shifting.
These are Exit Only Signals - No entry signals are given, this is only to help you consider when it may be time to get out of the current trend in the market.
Range Filter with MACD, RSI & Volume📌 Enhanced Range Filter with Multi-Indicator Confirmation
This Pine Script indicator improves trend-following and trade signal accuracy by combining a Range Filter with MACD, RSI, Volume, and ATR confirmations. It is designed to help traders identify strong trends and breakout opportunities while filtering out noise.
📈 How It Works
1️⃣ Trend Detection (Range Filter)
• The Range Filter smooths price action and identifies trends by filtering out minor fluctuations.
• The indicator creates dynamic support and resistance bands:
• High Target Band (Resistance)
• Low Target Band (Support)
• Color Coding:
• White = Uptrend 📈
• Blue = Downtrend 📉
• Light Blue = Neutral ⚖️
2️⃣ Multi-Indicator Trade Confirmation
To avoid false signals, the script only generates Buy/Sell signals when multiple indicators agree:
✅ MACD: Checks if MACD Line is above or below the Signal Line for momentum confirmation.
✅ RSI: Ensures RSI is above 50 for long trades and below 50 for short trades.
✅ Volume: Requires a volume spike above the 20-period moving average for stronger signals.
✅ ATR (Volatility Check): Ensures ATR is higher than its 50-period SMA, signaling strong market movement.
💡 Only when all conditions align, a Buy or Sell signal is generated!
📊 How to Use It
1. Trend Analysis:
• When price is above the Range Filter (white line) → Uptrend
• When price is below the Range Filter (blue line) → Downtrend
2. Trade Signals:
• Buy Signal 🟢 appears when:
• Price breaks above the Range Filter
• MACD is bullish
• RSI > 50
• High volume and strong volatility
• Sell Signal 🔴 appears when:
• Price breaks below the Range Filter
• MACD is bearish
• RSI < 50
• High volume and strong volatility
3. Alerts 🔔:
• The script includes built-in alerts to notify traders when a Buy or Sell signal is triggered.
🎯 Best for Traders Who:
✔️ Want to identify strong trends early
✔️ Need extra confirmation to avoid false signals
✔️ Trade breakouts with high volume & momentum
✔️ Prefer visual trend coloring to track market direction
🚀 Try it out and refine your entries with multi-indicator validation!
Median RSI SD| QuantEdgeB📈 Introducing Median RSI SD by QuantEdgeB
🛠️ Overview
Median RSI SD is a hybrid momentum tool that fuses two powerful techniques: Median Price Filtering and RSI-based Momentum. The result? A cleaner, more responsive oscillator designed to reduce noise and increase clarity in trend detection and potential reversals.
By applying the RSI not to raw price but to the percentile-based median, the indicator adapts better to real structural shifts in the market while filtering out temporary price spikes.
✨ Key Features
🔹 Smoothed RSI Momentum
Utilizes a percentile-based median as input to RSI, reducing volatility and enhancing signal reliability.
🔹 Volatility-Weighted SD Zones
Automatically detects overbought/oversold extremes using ±1 standard deviation bands on the median, adapting to current market volatility.
🔹 Trend Signal Overlay
A directional trend signal (Long / Short / Neutral) is derived from the RSI crossing custom thresholds, combined with position relative to SD bands.
🔹 Visual Labeling System
Optional in-chart labels for Long / Short signals and fully color-customizable theme modes.
📊 How It Works
1️⃣ Median RSI Calculation
Instead of using the close price directly, the script first computes a smoothed median via percentile ranking. RSI is then applied to this filtered stream, improving reactivity without overfitting to short-term noise.
2️⃣ Standard Deviation Filtering
Upper and lower SD bands are calculated around the median to identify extreme conditions. A position near the upper SD while RSI is below the short threshold triggers bearish bias. The reverse applies for longs.
3️⃣ Signal Generation
• ✅ Long Signal → RSI crosses above the Long Threshold (default: 65) and price holds above lower SD.
• ❌ Short Signal → RSI crosses below the Short Threshold (default: 45), typically within upper SD range.
4️⃣ Contextual Highlighting
Zone fills on the chart and RSI subgraph indicate Overbought (>75) and Oversold (<25) conditions for added clarity.
⚙️ Custom Settings
• RSI Length → Default: 21
• Median Length → Default: 10
• Long Threshold → Default: 65
• Short Threshold → Default: 45
• Color Mode → Choose from Strategy, Solar, Warm, Cool, Classic, Magic
• Signal Labels Toggle → Optional in-chart long/short labels
👥 Who Should Use It?
✅ Swing & Momentum Traders → Filter entries based on confirmed directional RSI setups.
✅ Range-Bound Traders → Use SD thresholds to spot fakeouts or exhaustion zones.
✅ Intraday Strategists → Enhanced signal clarity makes it usable even on lower timeframes.
✅ System Builders → Combine this signal with price action or confluence layers for smarter rules.
📌 Conclusion
Median RSI SD by QuantEdgeB is more than just a modified oscillator—it's a robust momentum confirmation framework designed for modern volatility. By replacing noisy price feeds with a statistically stable input and layering RSI + SD logic, this tool provides high-clarity signals without sacrificing responsiveness.
🔹 Key Takeaways:
1️⃣ Median-filtered RSI eliminates noise without lag
2️⃣ Standard deviation bands identify exhaustion zones
3️⃣ Reliable for both trend continuation and mean-reversion strategies
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Gaussian Smooth Trend | QuantEdgeB🧠 Introducing Gaussian Smooth Trend (GST) by QuantEdgeB
🛠️ Overview
Gaussian Smooth Trend (GST) is an advanced volatility-filtered trend-following system that blends multiple smoothing techniques into a single directional bias tool. It is purpose-built to reduce noise, isolate meaningful price shifts, and deliver early trend detection while dynamically adapting to market volatility.
GST leverages the Gaussian filter as its core engine, wrapped in a layered framework of DEMA smoothing, SMMA signal tracking, and standard deviation-based breakout thresholds, producing a powerful toolset for trend confirmation and momentum-based decision-making.
🔍 How It Works
1️⃣ DEMA Smoothing Engine
The indicator begins by calculating a Double Exponential Moving Average (DEMA), which provides a responsive and noise-resistant base input for subsequent filtering.
2️⃣ Gaussian Filter
A custom Gaussian kernel is applied to the DEMA signal, allowing the system to detect smooth momentum shifts while filtering out short-term volatility.
This is especially powerful during low-volume or sideways markets where traditional MAs struggle.
3️⃣ SMMA Layer with Z-Filtering
The filtered Gaussian signal is then passed through a custom Smoothed Moving Average (SMMA). A standard deviation envelope is constructed around this SMMA, dynamically expanding/contracting based on market volatility.
4️⃣ Signal Generation
• ✅ Long Signal: Price closes above Upper SD Band
• ❌ Short Signal: Price closes below Lower SD Band
• ➖ No trade: Price stays within the band → market indecision
✨ Key Features
🔹 Multi-Stage Trend Detection
Combines DEMA → Gaussian Kernel → SMMA → SD Bands for robust signal integrity across market conditions.
🔹 Gaussian Adaptive Filtering
Applies a tunable sigma parameter for the Gaussian kernel, enabling you to fine-tune smoothness vs. responsiveness.
🔹 Volatility-Aware Trend Zones
Price must close outside of dynamic SD envelopes to trigger signals — reducing whipsaws and increasing signal quality.
🔹 Dynamic Color-Coded Visualization
Candle coloring and band fills reflect live trend state, making the chart intuitive and fast to read.
⚙️ Custom Settings
• DEMA Source: Price stream used for smoothing (default: close)
• DEMA Length: Period for initial exponential smoothing (default: 7)
• Gaussian Length / Sigma: Controls smoothing strength of kernel filter
• SMMA Length: Final smoothing layer (default: 12)
• SD Length: Lookback period for standard deviation filtering (default: 30)
• SD Mult Up / Down: Adjusts distance of upper/lower breakout zones (default: 2.5 / 1.8)
• Color Modes: Six distinct color palettes (e.g., Strategy, Warm, Cool)
• Signal Labels: Toggle on/off entry markers ("𝓛𝓸𝓷𝓰", "𝓢𝓱𝓸𝓻𝓽")
📌 Trading Applications
✅ Trend-Following → Enter on confirmed breakouts from Gaussian-smoothed volatility zones
✅ Breakout Validation → Use SD bands to avoid false breakouts during chop
✅ Volatility Compression Monitoring → Narrowing bands often precede large directional moves
✅ Overlay-Based Confirmation → Can complement other QuantEdgeB indicators like K-DMI, BMD, or Z-SMMA
📌 Conclusion
Gaussian Smooth Trend (GST) delivers a precision-built trend model tailored for modern traders who demand both clarity and control. The layered signal architecture, combined with volatility awareness and Gaussian signal enhancement, ensures accurate entries, clean visualizations, and actionable trend structure — all in real-time.
🔹 Summary Highlights
1️⃣ Multi-stage Smoothing — DEMA → Gaussian → SMMA for deep signal integrity
2️⃣ Volatility-Aware Filtering — SD bands prevent false entries
3️⃣ Visual Trend Mapping — Gradient fills + candle coloring for clean charts
4️⃣ Highly Customizable — Adapt to your timeframe, style, and volatility
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Normalized DEMA Oscillator SD| QuantEdgeB📊 Introducing Normalized DEMA Oscillator SD (NDOSD) by QuantEdgeB
🛠️ Overview
Normalized DEMA Oscillator SD (NDOSD) is a powerful trend and momentum indicator that blends DEMA-based smoothing with a standard deviation-based normalization engine. The result is an oscillator that adapts to volatility, filters noise, and highlights both trend continuations and reversal zones with exceptional clarity.
It normalizes price momentum within an adaptive SD envelope, allowing comparisons across assets and market conditions. Whether you're a trend trader or mean-reverter, NDOSD provides the insight needed for smarter decision-making.
✨ Key Features
🔹 DEMA-Powered Momentum Core
Utilizes a Double EMA (DEMA) for smoother trend detection with reduced lag.
🔹 Normalized SD Bands
Price momentum is standardized using a dynamic 2× standard deviation range—enabling consistent interpretation across assets and timeframes.
🔹 Overbought/Oversold Detection
Includes clear OB/OS zones with shaded thresholds to identify potential reversals or trend exhaustion areas.
🔹 Visual Trend Feedback
Color-coded oscillator zones, candle coloring, and optional signal labels help traders immediately see trend direction and strength.
📐 How It Works
1️⃣ DEMA Calculation
The core of NDOSD is a smoothed price line using a Double EMA, designed to reduce false signals in choppy markets.
2️⃣ Normalization with SD
The DEMA is normalized within a volatility range using a 2x SD calculation, producing a bounded oscillator from 0–100. This transforms the raw signal into a structured format, allowing for OB/OS detection and trend entry clarity.
3️⃣ Signal Generation
• ✅ Long Signal → Oscillator crosses above the long threshold (default: 55) and price holds above the lower SD boundary.
• ❌ Short Signal → Oscillator drops below short threshold (default: 45), often within upper SD boundary context.
4️⃣ OB/OS Thresholds
• Overbought Zone: Above 100 → Caution / Consider profit-taking.
• Oversold Zone: Below 0 → Watch for accumulation setups.
⚙️ Custom Settings
• Calculation Source: Default = close
• DEMA Period: Default = 30
• Base SMA Period: Default = 20
• Long Threshold: Default = 55
• Short Threshold: Default = 45
• Color Mode: Choose from Strategy, Solar, Warm, Cool, Classic, or Magic
• Signal Labels Toggle: Show/hide Long/Short markers on chart
👥 Ideal For
✅ Trend Followers – Identify breakout continuation zones using oscillator thrust and SD structure
✅ Swing Traders – Catch mid-trend entries or mean reversion setups at OB/OS extremes
✅ Quant/Systemic Traders – Normalize signals for algorithmic integration across assets
✅ Multi-Timeframe Analysts – Easily compare trend health using standardized oscillator ranges
📌 Conclusion
Normalized DEMA Oscillator SD is a sleek and adaptive momentum toolkit that helps traders distinguish true momentum from false noise. With its fusion of DEMA smoothing and SD normalization, it works equally well in trending and range-bound conditions.
🔹 Key Takeaways:
1️⃣ Smoother momentum tracking using DEMA
2️⃣ Cross-asset consistency via SD-based normalization
3️⃣ Versatile for both trend confirmation and reversal identification
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Let me know if you want a strategy script or publish-ready layout for TradingView next!
P-Motion Trend | QuantEdgeB⚡ Introducing P-Motion Trend (PMT) by QuantEdgeB
🧭 Overview
P-Motion Trend is a refined trend-following framework built for modern market dynamics. It combines DEMA filtering, percentile-based smoothing, and volatility-adjusted envelopes to create a clear, noise-filtered trend map directly on your chart.
This overlay indicator is engineered to detect breakout zones, trend continuation setups, and market regime shifts with maximum clarity and minimum lag.
Whether you're swing trading crypto, managing intraday FX moves, or positioning in equities — P-Motion Trend adapts, aligns, and simplifies.
🧠 Core Logic
1️⃣ DEMA Filtering Core
The input source is processed through a Double EMA to reduce lag while retaining trend sensitivity.
2️⃣ Percentile Median Smoothing
To eliminate short-lived spikes, the DEMA output is passed through a percentile median rank — effectively smoothing without distortion.
3️⃣ Volatility Envelope with EMA Basis
An exponential moving average (EMA) is applied to the smoothed median, and standard deviation bands are wrapped around it:
• ✅ Long Signal → Price closes above the upper band
• ❌ Short Signal → Price closes below the lower band
• ➖ Inside Band = Neutral
These bands expand/contract with market volatility — protecting against false breakouts in quiet regimes and adapting quickly to strong moves.
📊 Visual & Analytical Layers
• 🎯 Bar Coloring: Color-coded candles highlight trend state at a glance.
• 📈 EMA Ribbon Overlay: A dynamic ribbon of EMAs helps confirm internal momentum and detect transitions (trend decay or acceleration).
• 🔹Gradient Fill Zones: Visually communicates squeeze vs. expansion phases based on band width.
⚙️ Custom Settings
• EMA Length – Defines the core trend path (default: 21)
• SD Length – Controls volatility band smoothing (default: 30)
• SD Mult Up/Down – Sets thresholds for breakout confirmation (default: 1.5)
• DEMA Filter Source – Raw input used for trend processing
• DEMA Filter Length – Sets DEMA smoothing (default: 7)
• Median Length – Percentile-based smoothing window (default: 2)
📌 Use Cases
✅ Trend Confirmation
Use PMT to confirm whether the price action is structurally valid for trend continuation. A close above the upper band signals entry alignment.
🛡️ Reversal Guard
Avoid early reversion entries. PMT keeps you in-trend until price truly breaks structure.
🔍 Momentum Visualizer
With multiple EMA bands, the indicator also functions as a momentum envelope to spot divergence between price and smoothed trend flow.
🔚 Conclusion
P-Motion Trend is a hybrid volatility + trend system built with precision smoothing, dynamic filtering, and clean visual output. It balances agility with stability, helping you:
• Filter out price noise
• Enter with structure
• Stay in trades longer
• Exit with confidence
🧩 Summary of Benefits
• 🔹 Lag-minimized trend structure via DEMA core
• 🔹 Real-time volatility band adaptation
• 🔹 Gradient visual feedback on compression/expansion
• 🔹 EMA ribbon assists in phase detection
• 🔹 Suitable for all markets & timeframes
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
DEGA RMA | QuantEdgeB🧠 Introducing DEGA RMA (DGR ) by QuantEdgeB
🛠️ Overview
DEGA RMA (DGR) is a precision-engineered trend-following system that merges DEMA, Gaussian kernel smoothing, and ATR-based envelopes into a single, seamless overlay indicator. Its mission: to filter out market noise while accurately capturing directional bias using a layered volatility-sensitive trend core.
DGR excels at identifying valid breakouts, sustained momentum conditions, and trend-defining price behavior without falling into the trap of frequent signal reversals.
🔍 How It Works
1️⃣ Double Exponential Moving Average (DEMA)
The system begins by applying a DEMA to the selected price source. DEMA responds faster than a traditional EMA, making it ideal for capturing transitions in momentum.
2️⃣ Gaussian Filtering
A custom Gaussian kernel is used to smooth the DEMA signal. The Gaussian function applies symmetrical weights, centered around the most recent bar, effectively softening sharp price oscillations while preserving the underlying trend structure.
3️⃣ Recursive Moving Average (RMA) Core
The filtered Gaussian output is then processed through an RMA to generate a stable dynamic baseline. This baseline becomes the foundation for the final trend logic.
4️⃣ ATR-Scaled Breakout Zones
Upper and lower trend envelopes are calculated using a custom ATR filter built on DEMA-smoothed volatility.
• ✅ Long Signal when price closes above the upper envelope
• ❌ Short Signal when price closes below the lower envelope
• ➖ Neutral when inside the band (no signal noise)
✨ Key Features
🔹 Multi-Layer Trend Model
DEMA → Gaussian → RMA creates a signal structure that is both responsive and robust.
🔹 Volatility-Aware Entry System
Adaptive ATR bands adjust in real-time, expanding during high volatility and contracting during calm periods.
🔹 Noise-Reducing Gaussian Kernel
Sigma-adjustable kernel ensures signal smoothness without introducing excessive lag.
🔹 Clean Visual System
Candle coloring and band fills make trend state easy to read and act on at a glance.
⚙️ Custom Settings
• DEMA Source – Input source for trend core (default: close)
• DEMA Length – Length for initial smoothing (default: 30)
• Gaussian Filter Length – Determines smoothing depth (default: 4)
• Gaussian Sigma – Sharpness of Gaussian curve (default: 2.0)
• RMA Length – Core baseline smoothing (default: 12)
• ATR Length – Volatility detection period (default: 40)
• ATR Mult Up/Down – Controls the upper/lower threshold range for signals (default: 1.7)
📌 How to Use
1️⃣ Trend-Following Mode
• Go Long when price closes above the upper ATR band
• Go Short when price closes below the lower ATR band
• Remain neutral otherwise
2️⃣ Breakout Confirmation Tool
DGR’s ATR-based zone logic helps validate price breakouts and filter out false signals that occur inside compressed ranges.
3️⃣ Volatility Monitoring
Watch the ATR envelope width — a narrowing band often precedes expansion and potential directional shifts.
📌 Conclusion
DEGA RMA (DGR) is a thoughtfully constructed trend-following framework that goes beyond basic moving averages. Its Gaussian smoothing, adaptive ATR thresholds, and layered filtering logic provide a versatile solution for traders looking for cleaner signals, less noise, and real-time trend awareness.
Whether you're trading crypto, forex, or equities — DGR adapts to volatility while keeping your chart clean and actionable.
🔹 Summary
• ✅ Advanced Smoothing → DEMA + Gaussian + RMA = ultra-smooth trend core
• ✅ Volatility-Adjusted Zones → ATR envelope scaling removes whipsaws
• ✅ Fully Customizable → Tailor to any asset or timeframe
• ✅ Quant-Inspired Structure → Built for clarity, consistency, and confidence
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
HILO Interpolation | QuantEdgeB🚀 Introducing HILO Interpolation by QuantEdgeB
🛠️ Overview
HILO Interpolation is a dynamic price-action based signal engine crafted to adapt across trending and ranging conditions. By leveraging percentile-based price band interpolation, it identifies high-confidence breakout and breakdown zones. This indicator is designed to serve both as a momentum trigger in trend phases and as a price-reactive entry system during range-bound consolidation.
By intelligently switching between percentile thresholds and interpolated logic, HILO minimizes noise and whipsaws commonly seen in traditional crossover systems.
✨ Key Features
🔹 Percentile Interpolation Engine
Tracks price breakouts using percentile thresholds, making it adaptable to volatility and asset-specific structure.
🔹 Price-Based Signal Confirmation
Signals are only triggered when price meaningfully crosses through key percentile thresholds (based on historical high/low logic).
🔹 Visual Trend Encoding
Color-coded candles, dynamic interpolation bands, and optional long/cash labels give clear visual cues for trend and trade direction.
🔹 Dynamic Threshold Switching
Interpolated threshold flips based on where price sits relative to percentile bands—providing adaptive long/short logic.
📊 How It Works
1️⃣ Percentile Zone Definition
HILO defines two key percentiles from the historical high and low:
• Upper Threshold: 75th Percentile of Highs
• Lower Threshold: 50th Percentile of Lows
These are calculated using linear interpolation to ensure smoother transitions across lookback periods.
2️⃣ Adaptive Signal Line
Instead of using static crossovers, HILO dynamically flips its signal based on whether price exceeds the upper threshold or falls below the lower one.
📌 If price > upper → Signal = Short threshold
📌 If price < lower → Signal = Long threshold
📌 If price remains between thresholds → no flip (trend continuation)
3️⃣ Signal Logic
✅ Long Signal → Price exceeds upper bound while lower bound acts as ceiling
❌ Short Signal → Price breaks below lower percentile while upper bound flips
This simple yet powerful mechanism creates early entries while maintaining high signal confidence.
👁 Visual & Custom Features
• 🎨 Multiple Color Modes: Strategy, Solar, Warm, Cool, Classic, Magic
• 🔄 Dynamic Candle & Band Coloring
• 🏷️ Signal Labels: Optional “𝓛𝓸𝓷𝓰” and “𝓢𝓱𝓸𝓻𝓽” tags when trend flips
• 💬 Alerts Ready: Long/Short crossover conditions can trigger alerts instantly
👥 Who Should Use HILO?
✅ Breakout Traders – Catch early trend starts using percentile filters
✅ Swing Traders – Identify directional bias shifts in advance
✅ Range Strategists – Use band confluence zones to play reversions
✅ Quant & Rule-Based Traders – Incorporate percentile logic into broader systems
⚙️ Customization & Default Settings
Percentile Length:(Default 35) Lookback for calculating percentile thresholds
Lookback Period:(Default 4) Lag factor for interpolation responsiveness
Upper % Threshold: (Default 75) Defines breakout zone from historical highs
Lower % Threshold: (Default 50) Defines retest/accumulation zone from historical lows
📌 How to Use HILO in Trading
1️⃣ Trend-Following Strategy
✔ Enter long when price flips above the adaptive support line
✔ Exit or go short when price breaks below the interpolated resistance
✔ Continue position as long as trend color persists
2️⃣ Range-Reversion Strategy
✔ Buy when price tests the lower threshold and no short signal is triggered
✔ Sell or reduce when price hits the upper range boundary
🧠 Why It Works
HILO operates on the principle that historical price structure creates natural probabilistic thresholds. By interpolating between these using percentile logic, the system maintains adaptability to changing market conditions—without the lag of moving averages or the noise of fixed bands.
🔹 Conclusion
HILO Interpolation is a minimalist yet powerful signal engine built for adaptive breakout and reversion detection. Its percentile-based logic offers a novel way to identify structure shifts, giving traders an edge in both trend and range markets.
🔹 Key Takeaways:
1️⃣ Breakout Entry Logic – Uses percentile interpolation instead of static bands
2️⃣ Color-Driven Clarity – Visual clarity via gradient zone overlays
3️⃣ Trend Integrity – Avoids overfitting and responds only to significant price movements
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
