Dskyz Adaptive Futures Elite (DAFE)Dskyz Adaptive Futures Edge (DAFE)
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A Dynamic Futures Trading Strategy
DAFE adapts to market volatility and price action using technical indicators and advanced risk management. It’s built for high-stakes futures trading (e.g., MNQ, BTCUSDT.P), offering modular logic for scalpers and swing traders alike.
Key Features
Adaptive Moving Averages
Dynamic Logic: Fast and slow SMAs adjust lengths via ATR, reacting to momentum shifts and smoothing in calm markets.
Signals: Long entry on fast SMA crossing above slow SMA with price confirmation; short on cross below.
RSI Filtering (Optional)
Momentum Check: Confirms entries with RSI crossovers (e.g., above oversold for longs). Toggle on/off with custom levels.
Fine-Tuning: Adjustable lookback and thresholds (e.g., 60/40) for precision.
Candlestick Pattern Recognition
Eng|Enhanced Detection: Identifies strong bullish/bearish engulfing patterns, validated by volume and range strength (vs. 10-period SMA).
Conflict Avoidance: Skips trades if both patterns appear in the lookback window, reducing whipsaws.
Multi-Timeframe Trend Filter
15-Minute Alignment: Syncs intrabar trades with 15-minute SMA trends; optional for flexibility.
Dollar-Cost Averaging (DCA) New!
Scaling: Adds up to a set number of entries (e.g., 4) on pullbacks/rallies, spaced by ATR multiples.
Control: Caps exposure and resets on exit, enhancing trend-following potential.
Trade Execution & Risk Management
Entry Rules: Prioritizes moving averages or patterns (user choice), with volume, volatility, and time filters.
Stops & Trails:
Initial Stop: ATR-based (2–3.5x, volatility-adjusted).
Trailing Stop: Locks profits with configurable ATR offset and multiplier.
Discipline
Cooldown: Pauses post-exit (e.g., 0–5 minutes).
Min Hold: Ensures trades last a set number of bars (e.g., 2–10).
Visualization & Tools
Charts: Overlays MAs, stops, and signals; trend shaded in background.
Dashboard: Shows position, P&L, win rate, and more in real-time.
Debugging: Logs signal details for optimization.
Input Parameters
Parameter Purpose Suggested Use
Use RSI Filter - Toggle RSI confirmation *Disable 4 price-only
trading
RSI Length - RSI period (e.g., 14) *7–14 for sensitivity
RSI Overbought/Oversold - Adjust for market type *Set levels (e.g., 60/40)
Use Candlestick Patterns - Enables engulfing signals *Disable for MA focus
Pattern Lookback - Pattern window (e.g., 19) *10–20 bars for balance
Use 15m Trend Filter - Align with 15-min trend *Enable for trend trades
Fast/Slow MA Length - Base MA lengths (e.g., 9/19) *10–25 / 30–60 per
timeframe
Volatility Threshold - Filters volatile spikes *Max ATR/close (e.g., 1%)
Min Volume - Entry volume threshold *Avoid illiquid periods
(e.g., 10)
ATR Length - ATR period (e.g., 14) *Standard volatility
measure
Trailing Stop ATR Offset - Trail distance (e.g., 0.5) *0.5–1.5 for tightness
Trailing Stop ATR Multi - Trail multiplier (e.g., 1.0) *1–3 for trend room
Cooldown Minutes - Post-exit pause (e.g., 0–5) *Prevents overtrading
Min Bars to Hold - Min trade duration (e.g., 2) *5–10 for intraday
Trading Hours - Active window (e.g., 9–16) *Focus on key sessions
Use DCA - Toggle DCA *Enable for scaling
Max DCA Entries - Cap entries (e.g., 4) *Limit risk exposure
DCA ATR Multiplier Entry spacing (e.g., 1.0) *1–2 for wider gaps
Compliance
Realistic Testing: Fixed quantities, capital, and slippage for accurate backtests.
Transparency: All logic is user-visible and adjustable.
Risk Controls: Cooldowns, stops, and hold periods ensure stability.
Flexibility: Adapts to various futures and timeframes.
Summary
DAFE excels in volatile futures markets with adaptive logic, DCA scaling, and robust risk tools. Currently in prop account testing, it’s a powerful framework for precision trading.
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
חפש סקריפטים עבור "美联储9月降息25个基点"
RSI-Volume Momentum Signal ScoreRSI-Volume Momentum Signal Score
Description
The RSI-Volume Momentum Signal Score is a predictive technical indicator designed to identify bullish and bearish momentum shifts by combining volume-based momentum with the Relative Strength Index (RSI). It generates a Signal Score derived from:
• The divergence between short-term and long-term volume (Volume Oscillator), and
• RSI positioning relative to a user-defined threshold.
This hybrid approach helps traders detect early signs of price movement based on volume surges and overbought/oversold conditions.
The Signal Score is computed as follows:
Signal Score = Volume Momentum x RSI Divergence Factor
Volume Momentum = tanh ((Volume Oscillator value (vo) – Volume Threshold)/Scaling Factor)
RSI Divergence Factor = ((RSI Threshold – RSI Period)/Scaling Factor)
Or,
Signal Score = tanh((vo - voThreshold) / scalingFactor) * ((rsiThreshold - rsi) / scalingFactor)
The logic of this formula are as follows:
• If Volume Oscillator >= Volume Threshold and RSI <= RSI Threshold: Bullish Signal (+1 x Scaling Factor)
• If Volume Oscillator >= Volume Threshold and RSI >= (100 – RSI Threshold): Bearish Signal (-1 x Scaling Factor)
• Otherwise: Neutral (0)
The tanh function provides the normalization process. It ensures that the final signal score is bounded between -1 and 1, increases sensitivity to early changes in volume patterns based on RSI conditions, and prevent sudden jumps in signals ensuring smooth and continuous signal line.
Input Fields
The input fields allow users to customize the behavior of the indicator based on their trading strategy:
Short-Term Volume MA
- Default: `2`
- Description: The period for the short-term moving average of volume.
- Purpose: Captures short-term volume trends.
Long-Term Volume MA)
- Default: `10`
- Description: The period for the long-term moving average of volume.
- Purpose: Captures long-term volume trends for comparison with the short-term trend.
RSI Period)
- Default: `3`
- Description: The period for calculating the RSI.
- Purpose: Measures the relative strength of price movements over the specified period.
Volume Oscillator Threshold
- Default: `70`
- Description: The threshold for the Volume Oscillator to determine significant volume momentum.
- Purpose: Filters out weak volume signals.
RSI Threshold
- Default: `25`
- Description: The RSI level used to identify overbought or oversold conditions.
- Purpose: Helps detect potential reversals in price momentum.
Signal Scaling Factor
- Default: `10`
- Description: A multiplier for the signal score.
- Purpose: Adjusts the magnitude of the signal score for better visualization.
How To Use It for Trading:
Upcoming Bullish Signal: Signal line turns from Gray to Green or from Green to Gray
Upcoming Bearish Signal: Signal line turns from Gray to Red or from Red to Gray
Note: The price that corresponds to the transition of Signal line from Gray to Green or Red and vise versa is the signal price for upcoming bullish or bearish signal.
The signal score dynamically adjusts based on volume and RSI thresholds, making it adaptable to various market conditions, and this is what makes the indicator unique from other traditional indicators.
Unique Features
Unlike traditional indicators, this indicator combines two different dimensions—volume trends and RSI divergence—for more comprehensive signal generation. The use of tanh() to scale and smooth the signal is a mathematically elegant way to manage signal noise and highlight genuine trends. Traders can tune the scaling factor and thresholds to adapt the indicator for scalping, swing trading, or longer-term investing.
Deadzone Pro @DaviddTechDeadzone Pro by @DaviddTech – Adaptive Multi-Strategy NNFX Trading System
Deadzone Pro by @DaviddTech is a meticulously engineered trading indicator that strictly adheres to the No-Nonsense Forex (NNFX) methodology. It integrates adaptive trend detection, dual confirmation indicators, advanced volatility filtering, and dynamic risk management into one powerful, visually intuitive system. Ideal for traders seeking precision and clarity, this indicator consistently delivers high-probability trade setups across all market conditions.
🔥 Key Features:
The Setup:
Adaptive Hull Moving Average Baseline: Clearly identifies trend direction using an advanced, gradient-colored Hull MA that intensifies based on trend strength, providing immediate visual clarity.
Dual Confirmation Indicators: Combines Waddah Attar Explosion (momentum detector) and Bull/Bear Power (strength gauge) for robust validation, significantly reducing false entries.
Volatility Filter (ADX): Ensures entries are only made during strong trending markets, filtering out weak, range-bound scenarios for enhanced trade accuracy.
Dynamic Trailing Stop Loss: Implements a SuperTrend-based trailing stop using adaptive ATR calculations, managing risk effectively while optimizing exits.
Dashboard:
💎 Gradient Visualization & User Interface:
Dynamic gradient colors enhance readability, clearly indicating bullish/bearish strength.
Comprehensive dashboard summarizes component statuses, real-time market sentiment, and entry conditions at a glance.
Distinct and clear buy/sell entry and exit signals, with adaptive stop-loss levels visually plotted.
Candlestick coloring based on momentum signals (Waddah Attar) for intuitive market reading.
📈 How to Interpret Signals:
Bullish Signal: Enter when Hull MA baseline trends upward, both confirmation indicators align bullish, ADX indicates strong trend (>25), and price breaks above the previous trailing stop.
Bearish Signal: Enter short or exit long when Hull MA baseline trends downward, confirmations indicate bearish momentum, ADX confirms trend strength, and price breaks below previous trailing stop.
📊 Recommended Usage:
Timeframes: Ideal on 1H, 4H, and Daily charts for swing trading; effective on shorter (5M, 15M) charts for day trading.
Markets: Compatible with Forex, Crypto, Indices, Stocks, and Commodities.
The Entry & Exit:
🎯 Trading Styles:
Choose from three distinct trading modes:
Conservative: Requires full alignment of all indicators for maximum accuracy.
Balanced (Default): Optimized balance between signal frequency and reliability.
Aggressive: Fewer confirmations needed for more frequent trading signals.
📝 Credits & Originality:
Deadzone Pro incorporates advanced concepts inspired by:
Hull Moving Average by @Julien_Eche
Waddah Attar Explosion by @LazyBear
Bull Bear Power by @Pinecoders
ADX methodology by @BeikabuOyaji
This system has been significantly refactored and enhanced by @DaviddTech to maximize synergy, clarity, and usability, standing apart distinctly from its original components.
Deadzone Pro exemplifies precision and discipline, aligning fully with NNFX principles to provide traders with a comprehensive yet intuitive trading advantage.
Kernel Weighted DMI | QuantEdgeB📊 Introducing Kernel Weighted DMI (K-DMI) by QuantEdgeB
🛠️ Overview
K-DMI is a next-gen momentum indicator that combines the traditional Directional Movement Index (DMI) with advanced kernel smoothing techniques to produce a highly adaptive, noise-resistant trend signal.
Unlike standard DMI that can be overly reactive or choppy in consolidation phases, K-DMI applies kernel-weighted filtering (Linear, Exponential, or Gaussian) to stabilize directional movement readings and extract a more reliable momentum signal.
✨ Key Features
🔹 Kernel Smoothing Engine
Smooths DMI using your choice of kernel (Linear, Exponential, Gaussian) for flexible noise reduction and clarity.
🔹 Dynamic Trend Signal
Generates real-time long/short trend bias based on signal crossing upper or lower thresholds (defaults: ±1).
🔹 Visual Encoding
Includes directional gradient fills, candle coloring, and momentum-based overlays for instant signal comprehension.
🔹 Multi-Mode Plotting
Optional moving average overlays visualize structure and compression/expansion within price action.
📐 How It Works
1️⃣ Directional Movement Index (DMI)
Calculates the traditional +DI and -DI differential to derive directional bias.
2️⃣ Kernel-Based Smoothing
Applies a custom-weighted average across historical DMI values using one of three smoothing methods:
• Linear → Simple tapering weights
• Exponential → Decay curve for recent emphasis
• Gaussian → Bell-shaped weight for centered precision
3️⃣ Signal Generation
• ✅ Long → Signal > Long Threshold (default: +1)
• ❌ Short → Signal < Short Threshold (default: -1)
Additional overlays signal potential compression zones or trend resumption using gradient and line fills.
⚙️ Custom Settings
• DMI Length: Default = 7
• Kernel Type: Options → Linear, Exponential, Gaussian (Def:Linear)
• Kernel Length: Default = 25
• Long Threshold: Default = 1
• Short Threshold: Default = -1
• Color Mode: Strategy, Solar, Warm, Cool, Classic, Magic
• Show Labels: Optional entry signal labels (Long/Short)
• Enable Extra Plots: Toggle MA overlays and dynamic bands
👥 Who Is It For?
✅ Trend Traders → Identify sustained directional bias with smoother signal lines
✅ Quant Analysts → Leverage advanced smoothing models to enhance data clarity
✅ Discretionary Swing Traders → Visualize clean breakouts or fades within choppy zones
✅ MA Compression Traders → Use overlay MAs to detect expansion opportunities
📌 Conclusion
Kernel Weighted DMI is the evolution of classic momentum tracking—merging traditional DMI logic with adaptable kernel filters. It provides a refined lens for trend detection, while optional visual overlays support price structure analysis.
🔹 Key Takeaways:
1️⃣ Smoothed and stabilized DMI for reliable trend signal generation
2️⃣ Optional Gaussian/exponential weighting for adaptive responsiveness
3️⃣ Custom gradient fills, dynamic MAs, and candle coloring to support visual clarity
📌 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.
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.
2013-2025 EclipsesIndicator Description: 2013-2025 Eclipses
This Pine Script (version 5) indicator overlays solar and lunar eclipse events on a TradingView chart, covering the period from 2013 to 2025. It is designed for traders and astrology enthusiasts who wish to visualize these significant astronomical events alongside price action, potentially identifying correlations with market movements or key turning points.
Features:
Eclipses:
Visualization: Displayed as a semi-transparent aqua background highlight across the chart.
Data: Includes 48 specific eclipse dates (both solar and lunar) from April 25, 2013, to September 21, 2025.
Purpose: Highlights dates of eclipses, which are often considered powerful astrological events associated with sudden changes, revelations, or significant shifts in energy and market sentiment.
Technical Details:
Overlay: The indicator is set to overlay=true, ensuring it displays directly on the price chart rather than in a separate pane.
Date Matching: Utilizes a helper function is_date(y, m, d) to determine if the current chart date matches any of the predefined eclipse dates, using TradingView's year, month, and dayofmonth variables.
Visualization Method:
bgcolor: Applies a light aqua background (using color.new(color.aqua, 85)) on the specific dates of eclipses. The transparency level of 85 allows price action to remain visible through the highlight.
Time Range: Spans from April 2013 to September 2025, covering a 12+ year period of eclipse events.
Usage:
Add the script to your TradingView chart to see eclipse dates highlighted with an aqua background on your chosen symbol and timeframe.
The background highlight appears only on the exact dates of eclipses, making it easy to spot these events amidst price data.
Ideal for those incorporating astrological analysis into trading or studying the potential impact of eclipses on financial markets.
Notes:
The script uses a single-line definition for eclipse_dates to ensure compatibility with Pine Script v5 syntax and avoid line continuation errors.
The aqua color matches the original circle-based visualization, with transparency adjustable via the color.new(color.aqua, 85) parameter (0 = fully opaque, 100 = fully transparent).
Works best on daily or higher timeframes for clear visibility of individual eclipse dates, though it functions on any TradingView-supported timeframe.
Eclipse dates should be cross-checked with astronomical sources for critical applications, as the script relies on the provided data accuracy.
Purpose:
This indicator provides a straightforward way to track eclipses over a 12-year period, offering a visual representation of these potent celestial events. By using a background highlight instead of markers, it maintains chart clarity while emphasizing the specific days when eclipses occur, potentially aiding in the analysis of their influence on market behavior or personal trading strategies.
Market Push Meter - CoffeeStyleMarket Push Meter - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the Market Push Meter indicator, a sophisticated volume analysis tool developed by CoffeeKiller with the help and assistance of FindBetterTrades that measures and visualizes the ongoing battle between buyers and sellers through volume pressure analysis.
🔔 **Warning: This Is Not a Standard Volume Indicator** 🔔 This indicator analyzes volume pressure in a unique way, combining directional volume with price action to identify market imbalances between buyers and sellers. All credit for the core logic for this indicator goes to FindBetterTrades and his/hers Volume Pressure Histogram (Normalized) (this is my adaptation and style added to that core logic, thus the CoffeeStyle name was added).
Core Concept: Volume Pressure Analysis
The foundation of this indicator lies in measuring the imbalance between buying and selling volume, providing insights into which market participants are exerting more pressure on price movements.
Volume Pressure Columns: Buying vs Selling Force
- Positive Green Columns: Net buying pressure
- Negative Red Columns: Net selling pressure
- Color intensity varies based on pressure strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during buying phases
- Low Marker Line (Cyan): Tracks the lowest point reached during selling phases
- Creates visual boundaries showing pressure extremes
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important pressure peaks
- Helps identify potential reversal points and pressure exhaustion
Reference Lines:
- Overbought Level: Threshold for extreme selling pressure
- Oversold Level: Threshold for extreme buying pressure
- Used to identify potential reversal zones
Core Components
1. Volume Pressure Calculation
- Separation of up-volume and down-volume
- Calculation of net volume pressure
- Smoothing for consistent visualization
- Normalization against total volume for percentage scaling
2. Boundary Tracking System
- Automatic detection of highest values in buying phases
- Automatic detection of lowest values in selling phases
- Step-line visualization of boundaries
- Color-coded for easy identification
3. Peak Detection System
- Identification of local maxima and minima
- Background highlighting of significant peaks
- Triangle markers for peak visualization
- Zero-line cross detection for trend changes
4. Threshold Settings
- Extreme threshold multiplier for identifying significant pressure
- Overbought/oversold levels for potential reversals
- Dynamic color coding based on pressure intensity
- Alert conditions for key pressure levels
Main Features
Volume Analysis Settings
- Customizable volume MA length
- Signal smoothing for clearer readings
- Optional log scale for handling wide range variations
- Adjustable threshold multiplier for sensitivity
Visual Elements
- Color-coded columns showing pressure direction and strength
- Dynamic marker lines for pressure boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
- Overbought/oversold reference lines
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for pressure strength
- Peak formation for potential reversals
- Color changes for pressure direction and intensity
- Alert conditions for extreme pressure levels
Customization Options
- Volume analysis parameters
- Marker line visibility and colors
- Peak marker display options
- Log scale toggle for handling various markets
- Overbought/oversold threshold adjustments
Trading Applications
1. Trend Identification
- Volume pressure crossing above zero: buying pressure emerging
- Volume pressure crossing below zero: selling pressure emerging
- Column color: indicates pressure direction
- Column height: indicates pressure strength
- Signal line: confirms overall trend direction
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Volume pressure approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing pressure
- Readings beyond overbought/oversold levels: potential reversal zones
3. Pressure Analysis
- Breaking above previous high boundary: accelerating buying pressure
- Breaking below previous low boundary: accelerating selling pressure
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Extreme readings: potential climactic buying/selling
4. Market Structure Assessment
- Consecutive higher peaks: strengthening buying structure
- Consecutive lower troughs: strengthening selling structure
- Peak comparisons: relative strength of pressure phases
- Boundary line steps: market structure levels
Optimization Guide
1. Volume Analysis Settings
- Volume MA Length: Default 25 provides balanced signals
- Lower values (10-15): More responsive, potentially noisier
- Higher values (30-50): Smoother, fewer false signals
- Signal Smoothing Length: Default 8 provides good balance
- Lower values: More responsive to pressure changes
- Higher values: Smoother trend identification
2. Threshold Settings
- Extreme Threshold Multiplier: Default 20.0
- Lower values: More signals, potentially more noise
- Higher values: Fewer signals, but more significant
- Overbought/Oversold Levels: Defaults at 20/-20
- Adjust based on instrument volatility
- Wider settings for more volatile instruments
3. Visual Customization
- Marker Line Colors: Adjust for visibility on your chart
- Peak Marker Color: Default yellow provides good contrast
- Enable/disable background highlights based on preference
- Consider log scale for instruments with wide volume ranges
4. Alert Settings
- Configure alerts for high buying pressure
- Configure alerts for high selling pressure
- Set additional alerts for zero-line crosses
- Consider timeframe when setting alert sensitivity
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm pressure changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong pressure
- Use with price action for entry/exit precision
- Consider extreme threshold crossings as significant signals
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Multiple timeframes: confirm signals across time horizons
- Match to your trading style and holding period
3. Market Context
- Strong buying phase: positive columns breaking above marker line
- Strong selling phase: negative columns breaking below marker line
- Columns approaching zero: potential pressure shift
- Columns beyond overbought/oversold: extreme conditions, potential reversal
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with price action oscillators for divergence detection
- Combine with traditional volume indicators for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when volume pressure breaks above previous high marker line
- Enter short when volume pressure breaks below previous low marker line
- Use zero-line as initial stop-loss reference
- Take profits at formation of opposing peaks
2. Peak Trading Strategy
- Identify significant peaks with triangular markers
- Look for consecutive lower peaks in buying phases for shorting opportunities
- Look for consecutive higher troughs in selling phases for buying opportunities
- Use zero-line crosses as confirmation
3. Extreme Reading Strategy
- Look for volume pressure beyond overbought/oversold levels
- Watch for color changes and peak formations
- Enter counter-trend positions after confirmed peaks
- Use tight stops due to extreme market conditions
4. Volume Color Strategy
- Enter long when columns turn bright green (increasing buying pressure)
- Enter short when columns turn bright red (increasing selling pressure)
- Exit when color intensity fades (decreasing pressure)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Volume pressure crosses above zero line
- Green columns grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant buying pressure peaks
Bearish Market Scenario
- Volume pressure crosses below zero line
- Red columns grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant selling pressure troughs
Consolidation Scenario
- Volume pressure oscillates around zero line
- Column colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Pressure values remain small
Understanding Market Dynamics Through Market Push Meter
At its core, this indicator provides a unique lens to visualize market pressure through volume analysis:
1. Volume Imbalance: By separating and comparing buying volume (up candles) from selling volume (down candles), the indicator provides insights into which side is exerting more pressure in the market.
2. Normalized Pressure: The indicator normalizes volume pressure as a percentage of total volume, making it more comparable across different market conditions and instruments.
3. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of pressure in both directions, helping to identify when markets are making new pressure extremes.
4. Exhaustion Signals: The peak detection system highlights moments where pressure has reached a local maximum or minimum, often precursors to reversals or consolidations.
Remember:
- Combine signals from volume pressure, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences and market
- Consider overall market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
DISCLAIMER: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
Kase Permission StochasticOverview
The Kase Permission Stochastic indicator is an advanced momentum oscillator developed from Kase's trading methodology. It offers enhanced signal smoothing and filtering compared to traditional stochastic oscillators, providing clearer entry and exit signals with fewer false triggers.
How It Works
This indicator calculates a specialized stochastic using a multi-stage smoothing process:
Initial stochastic calculation based on high, low, and close prices
Application of weighted moving averages (WMA) for short-term smoothing
Progressive smoothing through differential factors
Final smoothing to reduce noise and highlight significant trend changes
The indicator oscillates between 0 and 100, with two main components:
Main Line (Green): The smoothed stochastic value
Signal Line (Yellow): A further smoothed version of the main line
Signal Generation
Trading signals are generated when the main line crosses the signal line:
Buy Signal (Green Triangle): When the main line crosses above the signal line
Sell Signal (Red Triangle): When the main line crosses below the signal line
Key Features
Multiple Smoothing Algorithms: Uses a combination of weighted and exponential moving averages for superior noise reduction
Clear Visualization: Color-coded lines and background filling
Reference Levels: Horizontal lines at 25, 50, and 75 for context
Customizable Colors: All visual elements can be color-customized
Customization Options
PST Length: Base period for the stochastic calculation (default: 9)
PST X: Multiplier for the lookback period (default: 5)
PST Smooth: Smoothing factor for progressive calculations (default: 3)
Smooth Period: Final smoothing period (default: 10)
Trading Applications
Trend Confirmation: Use crossovers to confirm entries in the direction of the prevailing trend
Reversal Detection: Identify potential market reversals when crossovers occur at extreme levels
Range-Bound Markets: Look for oscillations between overbought and oversold levels
Filter for Other Indicators: Use as a confirmation tool alongside other technical indicators
Best Practices
Most effective in trending markets or during well-defined ranges
Combine with price action analysis for better context
Consider the overall market environment before taking signals
Use longer settings for fewer but higher-quality signals
The Kase Permission Stochastic delivers a sophisticated approach to momentum analysis, offering a refined perspective on market conditions while filtering out much of the noise that affects standard oscillators.
RSI Pro+ (Bear market, financial crisis and so on EditionIn markets defined by volatility, fear, and uncertainty – the battlegrounds of bear markets and financial crises – you need tools forged in resilience. Introducing RSI Pro+, a strategy built upon a legendary indicator born in 1978, yet engineered with modern visual clarity to remain devastatingly effective even in the chaotic financial landscapes of 3078.
This isn't about complex algorithms predicting the unpredictable. It's about harnessing the raw, time-tested power of the Relative Strength Index (RSI) to identify potential exhaustion points and capitalize on oversold conditions. RSI Pro+ cuts through the noise, providing clear, actionable signals when markets might be poised for a relief bounce or reversal.
Core Technology (The 1978 Engine):
RSI Crossover Entry: The strategy initiates a LONG position when the RSI (default period 11) crosses above a user-defined low threshold (default 30). This classic technique aims to enter when selling pressure may be waning, offering potential entry points during sharp downturns or periods of consolidation after a fall.
Modern Enhancements (The 3078 Cockpit):
RSI Pro+ isn't just about the signal; it's about providing a professional-grade visual experience directly on your chart:
Entry Bar Highlight: A subtle background flash on the chart signals the exact bar where the RSI crossover condition is met, alerting you to potential entry opportunities.
Trade Bar Coloring: Once a trade is active, the price bars are subtly colored, giving you immediate visual confirmation that the strategy is live in the market.
Entry Price Line: A clear, persistent line marks your exact average entry price for the duration of the trade, serving as a crucial visual anchor.
Take Profit Line: Your calculated Take Profit target is plotted as a distinct line, keeping your objective clearly in sight.
Custom Entry Marker: A precise shape (▲) appears below the bar where the trade entry was actually executed, pinpointing the start of the position.
On-Chart Info Table (HUD): A clean, customizable Heads-Up Display appears when a trade is active, showing vital information at a glance:
Entry Price: Your position's average cost basis.
TP Target: The calculated price level for your Take Profit exit.
Current PnL%: Real-time Profit/Loss percentage for the open trade.
Full Customization: Nearly every aspect is configurable via the settings menu:
RSI Period & Crossover Level
Take Profit Percentage
Toggle ALL visual enhancements on/off individually
Position the Info Table wherever you prefer on the chart.
How to Use RSI Pro+:
Add to Chart: Apply the "RSI Pro+ (Bear market...)" strategy to your TradingView chart. Ensure any previous versions are removed.
Access Settings: Click the cogwheel icon (⚙️) next to the strategy name on your chart.
Configure Inputs (Crucial Step):
RSI Crossover Level: This is key. The default (30) targets standard oversold conditions. In severe downturns, you might experiment with lower levels (e.g., 25, 20) or higher ones (e.g., 40) depending on the asset and timeframe. Observe where RSI(11) typically bottoms out on your chart.
Take Profit Percentage (%): Define your desired profit target per trade (e.g., enter 0.5 for 0.5%, 1.0 for 1%). The default is a very small 0.11%.
RSI Period: While default is 11, you can adjust this (e.g., the standard 14).
Visual Enhancements: Enable or disable the visual features (background highlights, bar coloring, lines, markers, table) according to your preference using the checkboxes. Adjust table position.
Observe & Backtest: Watch how the strategy behaves on your chosen asset and timeframe. Use TradingView's Strategy Tester to analyze historical performance based on your settings. No strategy works perfectly everywhere; testing is essential.
Important Considerations:
Risk Management: This specific script version focuses on a Take Profit exit. It does not include an explicit Stop Loss. You MUST manage risk through appropriate position sizing, potentially adding a Stop Loss manually, or by modifying the script.
Oversold ≠ Reversal: An RSI crossover is an indicator of potential exhaustion, not a guarantee of a price reversal.
Fixed TP: A fixed percentage TP ensures small wins but may exit before larger potential moves.
Backtesting Limitations: Past performance does not guarantee future results.
RSI Pro+ strips away complexity to focus on a robust, time-honored principle, enhanced with modern visuals for the discerning trader navigating today's (and tomorrow's) challenging markets
Econometrica by [SS]This is Econometrica, an indicator that aims to bridge a big gap between the resources available for analysis of fundamental data and its impact on tickers and price action.
I have noticed a general dearth of available indicators that offer insight into how fundamentals impact a ticker and provide guidance on how they these economic factors influence ticker behaviour.
Enter Econometrica. Econometrica is a math based indicator that aims to co-integrate and model indicator price action in relation to critical economic metrics.
Econometrica supports the following US based economic data:
CPI
Non-Farm Payroll
Core Inflation
US Money Supply
US Central Bank Balance Sheet
GDP
PCE
Let's go over the functions of Econometrica.
Creating a Regression Cointegrated Model
The first thing Econometrica does is creates a co-integrated regression, as you see in the main chart, predicting ticker value ranges from fundamental economic data.
You can visualize this in the main chart above, but here are some other examples:
SPY vs Core Inflation:
BA vs PCE:
QQQ vs US Balance Sheet:
The band represents the anticipated range the ticker should theoretically fall in based on the underlying economic value. The indicator will breakdown the relationship between the economic indicator and the ticker more precisely. In the images above, you can see how there are some metrics provided, including Stationairty, lagged correlation, Integrated Correlation and R2. Let's discuss these very briefly:
Stationarity: checks to ensure that the relationship between the economic indicator and ticker is stationary. Stationary data is important for making unbiased inferences and projections, so having data that is stationary is valuable.
Lagged Correlation: This is a very interesting metric. Lagged correlation means whether there is a delay in the economic indicator and the response of the ticker. Typically, you will observed a lagged correlation between an economic indicator and price of a ticker, as it can take some time for economic changes to reach the market. This lagged correlation will provide you with how long it takes for the economic indicator to catch up with the ticker in months.
Integrated Correlation: This metric tells you how good of a fit the regression bands are in relation to the ticker price. A higher correlation, means the model is better at consistent and accurate information about the anticipated range for the ticker in relation to the economic indicator.
R2: Provides information on the variance and degree of model fit. A high R2 value means that the model is capable of explaining a large amount of variance between the economic indicator and the ticker price action.
Explaining the Relationship
Owning to the fact that the indicator is a bit on the mathy side (it has to be to do this kind of task), I have included ability for the indicator to explain and make suggestions based on the underlying data. It can assess the model's fit and make suggestions for tweaking. It can also explain the implications of the data being presented in the model.
Here is an example with QQQ and the US Balance Sheet:
This helps to simplify and interpret the results you are looking at.
Forecasting the Economic Indicator
In addition to assessing the economic indicator's impact on the ticker, the indicator is also capable of forecasting out the economic indicator over the next 25 releases.
Here is an example of the CPI forecast:
Overall use of the indicator
The indicator is meant to bridge the gap between Technical Analysis and Fundamental Analysis.
Any trader who is attune to fundamentals would benefit from this, as this provides you with objective data on how and to what extent fundamental and economic data impacts tickers.
It can help affirm hypothesis and dispel myths objectively.
It also omits the need from having to perform these types of analyses outside of Tradingview (i.e. in excel, R or Python), as you can get the data in just a few licks of enabling the indicator.
Conclusion
I have tried to make this indicator as user friendly as possible. Though it uses a lot of math, it is fairly straight forward to interpret.
The band plotted can be considered the fair market value or FMV of the ticker based on the underlying economic data, provided the indicator tells you that the relationship is significant (and it will blatantly give you this information verbatim, you don't have to interpret the math stuff).
This is US economic data only. It does not pull economic data from other countries. You can absolutely see how US economic data impacts other markets like the TSX, BANKNIFTY, NIFTY, DAX etc. but the indicator is only pulling US economic data.
That is it!
I hope you enjoy it and find this helpful!
Thanks everyone and safe trades as always 🚀🚀🚀
Long Term Profitable Swing | AbbasA Story of a Profitable Swing Trading Strategy
Imagine you're sailing across the ocean, looking for the perfect wave to ride. Swing trading is quite similar—you're navigating the stock market, searching for the ideal moments to enter and exit trades. This strategy, created by Abbas, helps you find those waves and ride them effectively to profitable outcomes.
🌊 Finding the Perfect Wave (Entry)
Our journey begins with two simple signs that tell us a great trading opportunity is forming:
- Moving Averages: We use two lines that follow price trends—the faster one (EMA 16) reacts quickly to recent price moves, and the slower one (EMA 30) gives us a longer-term perspective. When the faster line crosses above the slower line, it's like a clear signal saying, "Hey! The wave is rising, and prices might move higher!"
- RSI Momentum: Next, we check a tool called the RSI, which measures momentum (how strongly prices are moving). If the RSI number is above 50, it means there's enough strength behind this rising wave to carry us forward.
When both signals appear together, that's our green light. It's time to jump on our surfboard and start riding this promising wave.
⚓ Safely Riding the Wave (Risk Management)
While we're riding this wave, we want to ensure we're safe from sudden surprises. To do this, we use something called the Average True Range (ATR), which measures how volatile (or bumpy) the price movements are:
- Stop-Loss: To avoid falling too hard, we set a safety line (stop-loss) 8 times the ATR below our entry price. This helps ensure we exit if the wave suddenly turns against us, protecting us from heavy losses.
- Take Profit: We also set a goal to exit the trade at 11 times the ATR above our entry. This way, we capture significant profits when the wave reaches a nice high point.
🌟 Multiple Rides, Bigger Adventures
This strategy allows us to take multiple positions simultaneously—like riding several waves at once, up to 5. Each trade we make uses only 10% of our trading capital, keeping risks manageable and giving us multiple opportunities to win big.
🗺️ Easy to Follow Settings
Here are the basic settings we use:
- Fast EMA**: 16
- Slow EMA**: 30
- RSI Length**: 9
- RSI Threshold**: 50
- ATR Length**: 21
- ATR Stop-Loss Multiplier**: 8
- ATR Take-Profit Multiplier**: 11
These settings are flexible—you can adjust them to better suit different markets or your personal trading style.
🎉 Riding the Waves of Success
This simple yet powerful swing trading approach helps you confidently enter trades, clearly know when to exit, and effectively manage your risk. It’s a reliable way to ride market waves, capture profits, and minimize losses.
Happy trading, and may you find many profitable waves to ride! 🌊✨
Please test, and take into account that it depends on taking multiple longs within the swing, and you only get to invest 25/30% of your equity.
Combined EMA Technical AnalysisThis script is written in Pine Script (version 5) for TradingView and creates a comprehensive technical analysis indicator called "Combined EMA Technical Analysis." It overlays multiple technical indicators on a price chart, including Exponential Moving Averages (EMAs), VWAP, MACD, PSAR, RSI, Bollinger Bands, ADX, and external data from the S&P 500 (SPX) and VIX indices. The script also provides visual cues through colors, shapes, and a customizable table to help traders interpret market conditions.
Here’s a breakdown of the script:
---
### **1. Purpose**
- The script combines several popular technical indicators to analyze price trends, momentum, volatility, and market sentiment.
- It uses color coding (green for bullish, red for bearish, gray/white for neutral) and a table to display key information.
---
### **2. Custom Colors**
- Defines custom RGB colors for bullish (`customGreen`), bearish (`customRed`), and neutral (`neutralGray`) signals to enhance visual clarity.
---
### **3. User Inputs**
- **EMA Colors**: Users can customize the colors of five EMAs (8, 20, 9, 21, 50 periods).
- **MACD Settings**: Adjustable short length (12), long length (26), and signal length (9).
- **RSI Settings**: Adjustable length (14).
- **Bollinger Bands Settings**: Length (20), multiplier (2), and proximity threshold (0.1% of band width).
- **ADX Settings**: Adjustable length (14).
- **Table Settings**: Position (e.g., "Bottom Right") and text size (e.g., "Small").
---
### **4. Indicator Calculations**
#### **Exponential Moving Averages (EMAs)**
- Calculates five EMAs: 8, 20, 9, 21, and 50 periods based on the closing price.
- Used to identify short-term and long-term trends.
#### **Volume Weighted Average Price (VWAP)**
- Resets daily and calculates the average price weighted by volume.
- Color-coded: green if price > VWAP (bullish), red if price < VWAP (bearish), white if neutral.
#### **MACD (Moving Average Convergence Divergence)**
- Uses short (12) and long (26) EMAs to compute the MACD line, with a 9-period signal line.
- Displays "Bullish" (green) if MACD > signal, "Bearish" (red) if MACD < signal.
#### **Parabolic SAR (PSAR)**
- Calculated with acceleration factors (start: 0.02, increment: 0.02, max: 0.2).
- Indicates trend direction: green if price > PSAR (bullish), red if price < PSAR (bearish).
#### **Relative Strength Index (RSI)**
- Measures momentum over 14 periods.
- Highlighted in green if > 70 (overbought), red if < 30 (oversold), white otherwise.
#### **Bollinger Bands (BB)**
- Uses a 20-period SMA with a 2-standard-deviation multiplier.
- Color-coded based on price position:
- Green: Above upper band or close to it.
- Red: Below lower band or close to it.
- Gray: Neutral (within bands).
#### **Average Directional Index (ADX)**
- Manually calculates ADX to measure trend strength:
- Strong trend: ADX > 25.
- Very strong trend: ADX > 50.
- Direction: Bullish if +DI > -DI, bearish if -DI > +DI.
#### **EMA Crosses**
- Detects bullish (crossover) and bearish (crossunder) events for:
- EMA 9 vs. EMA 21.
- EMA 8 vs. EMA 20.
- Visualized with green (bullish) or red (bearish) circles.
#### **SPX and VIX Data**
- Fetches daily closing prices for the S&P 500 (SPX) and VIX (volatility index).
- SPX trend: Bullish if EMA 9 > EMA 21, bearish if EMA 9 < EMA 21.
- VIX levels: High (> 25, fear), Low (< 15, stability).
- VIX color: Green if SPX bullish and VIX low, red if SPX bearish and VIX high, white otherwise.
---
### **5. Visual Outputs**
#### **Plots**
- EMAs, VWAP, and PSAR are plotted on the chart with their respective colors.
- EMA crosses are marked with circles (green for bullish, red for bearish).
#### **Table**
- Displays a summary of indicators in a customizable position and size.
- Indicators shown (if enabled):
- EMA 8/20, 9/21, 50: Green dot if bullish, red if bearish.
- VWAP: Green if price > VWAP, red if price < VWAP.
- MACD: Green if bullish, red if bearish.
- MACD Zero: Green if MACD > 0, red if MACD < 0.
- PSAR: Green if price > PSAR, red if price < PSAR.
- ADX: Arrows for very strong trends (↑/↓), dots for weaker trends, colored by direction.
- Bollinger Bands: Arrows (↑/↓) or dots based on price position.
- RSI: Numeric value, colored by overbought/oversold levels.
- VIX: Numeric value, colored based on SPX trend and VIX level.
---
### **6. Alerts**
- Triggers alerts for EMA 8/20 crosses:
- Bullish: "EMA 8/20 Bullish Cross on Candle Close!"
- Bearish: "EMA 8/20 Bearish Cross on Candle Close!"
---
### **7. Key Features**
- **Flexibility**: Users can toggle indicators on/off in the table and adjust parameters.
- **Visual Clarity**: Consistent use of green (bullish), red (bearish), and neutral colors.
- **Comprehensive**: Combines trend, momentum, volatility, and market sentiment indicators.
---
### **How to Use**
1. Add the script to TradingView.
2. Customize inputs (colors, lengths, table position) as needed.
3. Interpret the chart and table:
- Green signals suggest bullish conditions.
- Red signals suggest bearish conditions.
- Neutral signals indicate indecision or consolidation.
4. Set up alerts for EMA crosses to catch trend changes.
This script is ideal for traders who want a multi-indicator dashboard to monitor price action and market conditions efficiently.
Volume Weighted RSI (VW RSI)The Volume Weighted RSI (VW RSI) is a momentum oscillator designed for TradingView, implemented in Pine Script v6, that enhances the traditional Relative Strength Index (RSI) by incorporating trading volume into its calculation. Unlike the standard RSI, which measures the speed and change of price movements based solely on price data, the VW RSI weights its analysis by volume, emphasizing price movements backed by significant trading activity. This makes the VW RSI particularly effective for identifying bullish or bearish momentum, overbought/oversold conditions, and potential trend reversals in markets where volume plays a critical role, such as stocks, forex, and cryptocurrencies.
Key Features
Volume-Weighted Momentum Calculation:
The VW RSI calculates momentum by comparing the volume associated with upward price movements (up-volume) to the volume associated with downward price movements (down-volume).
Up-volume is the volume on bars where the closing price is higher than the previous close, while down-volume is the volume on bars where the closing price is lower than the previous close.
These volumes are smoothed over a user-defined period (default: 14 bars) using a Running Moving Average (RMA), and the VW RSI is computed using the formula:
\text{VW RSI} = 100 - \frac{100}{1 + \text{VoRS}}
where
\text{VoRS} = \frac{\text{Average Up-Volume}}{\text{Average Down-Volume}}
.
Oscillator Range and Interpretation:
The VW RSI oscillates between 0 and 100, with a centerline at 50.
Above 50: Indicates bullish volume momentum, suggesting that volume on up bars dominates, which may signal buying pressure and a potential uptrend.
Below 50: Indicates bearish volume momentum, suggesting that volume on down bars dominates, which may signal selling pressure and a potential downtrend.
Overbought/Oversold Levels: User-defined thresholds (default: 70 for overbought, 30 for oversold) help identify potential reversal points:
VW RSI > 70: Overbought, indicating a possible pullback or reversal.
VW RSI < 30: Oversold, indicating a possible bounce or reversal.
Visual Elements:
VW RSI Line: Plotted in a separate pane below the price chart, colored dynamically based on its value:
Green when above 50 (bullish momentum).
Red when below 50 (bearish momentum).
Gray when at 50 (neutral).
Centerline: A dashed line at 50, optionally displayed, serving as the neutral threshold between bullish and bearish momentum.
Overbought/Oversold Lines: Dashed lines at the user-defined overbought (default: 70) and oversold (default: 30) levels, optionally displayed, to highlight extreme conditions.
Background Coloring: The background of the VW RSI pane is shaded red when the indicator is in overbought territory and green when in oversold territory, providing a quick visual cue of potential reversal zones.
Alerts:
Built-in alerts for key events:
Bullish Momentum: Triggered when the VW RSI crosses above 50, indicating a shift to bullish volume momentum.
Bearish Momentum: Triggered when the VW RSI crosses below 50, indicating a shift to bearish volume momentum.
Overbought Condition: Triggered when the VW RSI crosses above the overbought threshold (default: 70), signaling a potential pullback.
Oversold Condition: Triggered when the VW RSI crosses below the oversold threshold (default: 30), signaling a potential bounce.
Input Parameters
VW RSI Length (default: 14): The period over which the up-volume and down-volume are smoothed to calculate the VW RSI. A longer period results in smoother signals, while a shorter period increases sensitivity.
Overbought Level (default: 70): The threshold above which the VW RSI is considered overbought, indicating a potential reversal or pullback.
Oversold Level (default: 30): The threshold below which the VW RSI is considered oversold, indicating a potential reversal or bounce.
Show Centerline (default: true): Toggles the display of the 50 centerline, which separates bullish and bearish momentum zones.
Show Overbought/Oversold Lines (default: true): Toggles the display of the overbought and oversold threshold lines.
How It Works
Volume Classification:
For each bar, the indicator determines whether the price movement is upward or downward:
If the current close is higher than the previous close, the bar’s volume is classified as up-volume.
If the current close is lower than the previous close, the bar’s volume is classified as down-volume.
If the close is unchanged, both up-volume and down-volume are set to 0 for that bar.
Smoothing:
The up-volume and down-volume are smoothed using a Running Moving Average (RMA) over the specified period (default: 14 bars) to reduce noise and provide a more stable measure of volume momentum.
VW RSI Calculation:
The Volume Relative Strength (VoRS) is calculated as the ratio of smoothed up-volume to smoothed down-volume.
The VW RSI is then computed using the standard RSI formula, but with volume data instead of price changes, resulting in a value between 0 and 100.
Visualization and Alerts:
The VW RSI is plotted with dynamic coloring to reflect its momentum direction, and optional lines are drawn for the centerline and overbought/oversold levels.
Background coloring highlights overbought and oversold conditions, and alerts notify the trader of significant crossings.
Usage
Timeframe: The VW RSI can be used on any timeframe, but it is particularly effective on intraday charts (e.g., 1-hour, 4-hour) or daily charts where volume data is reliable. Shorter timeframes may require a shorter length for increased sensitivity, while longer timeframes may benefit from a longer length for smoother signals.
Markets: Best suited for markets with significant and reliable volume data, such as stocks, forex, and cryptocurrencies. It may be less effective in markets with low or inconsistent volume, such as certain futures contracts.
Trading Strategies:
Trend Confirmation:
Use the VW RSI to confirm the direction of a trend. For example, in an uptrend, look for the VW RSI to remain above 50, indicating sustained bullish volume momentum, and consider buying on pullbacks when the VW RSI dips but stays above 50.
In a downtrend, look for the VW RSI to remain below 50, indicating sustained bearish volume momentum, and consider selling on rallies when the VW RSI rises but stays below 50.
Overbought/Oversold Conditions:
When the VW RSI crosses above 70, the market may be overbought, suggesting a potential pullback or reversal. Consider taking profits on long positions or preparing for a short entry, but confirm with price action or other indicators.
When the VW RSI crosses below 30, the market may be oversold, suggesting a potential bounce or reversal. Consider entering long positions or covering shorts, but confirm with additional signals.
Divergences:
Look for divergences between the VW RSI and price to spot potential reversals. For example, if the price makes a higher high but the VW RSI makes a lower high, this bearish divergence may signal an impending downtrend.
Conversely, if the price makes a lower low but the VW RSI makes a higher low, this bullish divergence may signal an impending uptrend.
Momentum Shifts:
A crossover above 50 can signal the start of bullish momentum, making it a potential entry point for long trades.
A crossunder below 50 can signal the start of bearish momentum, making it a potential entry point for short trades or an exit for long positions.
Example
On a 4-hour SOLUSDT chart:
During an uptrend, the VW RSI might rise above 50 and stay there, confirming bullish volume momentum. If it approaches 70, it may indicate overbought conditions, as seen near a price peak of 145.08, suggesting a potential pullback.
During a downtrend, the VW RSI might fall below 50, confirming bearish volume momentum. If it drops below 30 near a price low of 141.82, it may indicate oversold conditions, suggesting a potential bounce, as seen in a slight recovery afterward.
A bullish divergence might occur if the price makes a lower low during the downtrend, but the VW RSI makes a higher low, signaling a potential reversal.
Limitations
Lagging Nature: Like the traditional RSI, the VW RSI is a lagging indicator because it relies on smoothed data (RMA). It may not react quickly to sudden price reversals, potentially missing the start of new trends.
False Signals in Ranging Markets: In choppy or ranging markets, the VW RSI may oscillate around 50, generating frequent crossovers that lead to false signals. Combining it with a trend filter (e.g., ADX) can help mitigate this.
Volume Data Dependency: The VW RSI relies on accurate volume data, which may be inconsistent or unavailable in some markets (e.g., certain forex pairs or futures contracts). In such cases, the indicator’s effectiveness may be reduced.
Overbought/Oversold in Strong Trends: During strong trends, the VW RSI can remain in overbought or oversold territory for extended periods, leading to premature exit signals. Use additional confirmation to avoid exiting too early.
Potential Improvements
Smoothing Options: Add options to use different smoothing methods (e.g., EMA, SMA) instead of RMA for the up/down volume calculations, allowing users to adjust the indicator’s responsiveness.
Divergence Detection: Include logic to detect and plot bullish/bearish divergences between the VW RSI and price, providing visual cues for potential reversals.
Customizable Colors: Allow users to customize the colors of the VW RSI line, centerline, overbought/oversold lines, and background shading.
Trend Filter: Integrate a trend strength filter (e.g., ADX > 25) to ensure signals are generated only during strong trends, reducing false signals in ranging markets.
The Volume Weighted RSI (VW RSI) is a powerful tool for traders seeking to incorporate volume into their momentum analysis, offering a unique perspective on market dynamics by emphasizing price movements backed by significant trading activity. It is best used in conjunction with other indicators and price action analysis to confirm signals and improve trading decisions.
Dynamic Trend Indicator (DTI) - VWAP FilterThe Dynamic Trend Indicator (DTI) with VWAP Filter is a trend-following indicator.
It aims to identify and follow market trends while minimizing false signals in choppy or ranging markets.
The DTI combines a dynamically adjusted Exponential Moving Average (EMA) with a daily Volume Weighted Average Price (VWAP) confirmation filter and a cooldown mechanism to enhance signal reliability. This indicator is particularly useful for traders on intraday timeframes (e.g., 4-hour charts) who want to align their trades with the broader daily trend while avoiding whipsaws.
Key Features:
Dynamic Trend Line:
The core of the DTI is a trend line calculated using a custom EMA that adjusts its period dynamically based on market conditions.
The period of the EMA is determined by a combination of volatility (measured via ATR) and trend strength (measured via price momentum). In strong trends, the period shortens for faster responsiveness; in weak or ranging markets, it lengthens to reduce noise.
An optional smoothing EMA can be applied to the dynamic trend line to further reduce noise, with a user-defined smoothing length.
Daily VWAP Confirmation Filter:
A daily VWAP is calculated to provide a higher-timeframe trend bias. VWAP represents the average price paid for an asset during the day, weighted by volume, and is often used as a benchmark by institutional traders.
Buy signals are only generated when the price is above the daily VWAP (indicating a bullish daily bias), and sell signals are only generated when the price is below the VWAP (indicating a bearish daily bias).
The VWAP resets at the start of each day, ensuring it reflects the current day’s trading activity.
Cooldown Mechanism:
To prevent rapid signal reversals (whipsaws), the indicator includes a cooldown period between signals. After a buy or sell signal is generated, no new signals can be generated for a user-defined number of bars (default: 5 bars).
This helps filter out noise in choppy markets, ensuring signals are spaced out and more likely to align with significant trend changes.
Visual Elements:
Trend Line: Plotted on the chart, colored green when the price is above (uptrend) and red when below (downtrend). A gray color indicates a neutral trend.
Buy/Sell Signals: Displayed as green triangles below the bar for buy signals and red triangles above the bar for sell signals.
Background Coloring: The chart background is shaded green during uptrends and red during downtrends, providing a quick visual cue of the trend direction.
Daily VWAP Line: Optionally plotted as a purple step line, allowing traders to see the VWAP level and its relationship to the price.
Alerts:
The indicator includes built-in alerts for buy and sell signals, triggered when the price crosses the trend line and satisfies the VWAP filter and cooldown conditions.
Alert messages specify whether the signal is a buy or sell and confirm that the VWAP condition was met (e.g., "DTI Buy Signal: Price crossed above trend line and VWAP").
Input Parameters
Base Length (default: 14): The base period for calculating volatility and trend strength, used to adjust the dynamic EMA period.
Volatility Multiplier (default: 1.5): Adjusts the sensitivity of the dynamic period to market volatility (via ATR).
Trend Threshold (default: 0.5): Controls the sensitivity of the dynamic period to trend strength (via price momentum).
Use Smoothing (default: true): Enables/disables smoothing of the trend line with an additional EMA.
Smoothing Length (default: 3): The period for the smoothing EMA, if enabled.
Cooldown Bars (default: 5): The minimum number of bars between consecutive signals, reducing signal frequency in choppy markets.
Show Daily VWAP (default: true): Toggles the display of the daily VWAP line on the chart.
How It Works
Dynamic Trend Line Calculation:
Volatility is measured using the Average True Range (ATR) over the base length, scaled by the volatility multiplier.
Trend strength is calculated as the absolute price momentum (change in price over the base length) divided by the volatility factor.
The dynamic EMA period is adjusted based on the trend strength: stronger trends result in a shorter period (faster response), while weaker trends result in a longer period (more stability). The period is constrained between 5 and 50 to avoid extreme values.
A custom EMA function is used to handle the dynamic period, as Pine Script’s built-in ta.ema() requires a fixed length. The trend line is optionally smoothed with a secondary EMA.
Signal Generation:
A buy signal is generated when the price crosses above the trend line, the price is above the daily VWAP, and the cooldown period has elapsed.
A sell signal is generated when the price crosses below the trend line, the price is below the daily VWAP, and the cooldown period has elapsed.
The cooldown mechanism ensures that signals are not generated too frequently, reducing false signals in ranging markets.
Daily VWAP Calculation:
The VWAP is calculated by accumulating the price-volume product (close * volume) and total volume for the day, resetting at the start of each new day.
The VWAP is then computed as the cumulative price-volume divided by the cumulative volume, providing a volume-weighted average price for the day.
Usage
Timeframe: Best suited for intraday timeframes (e.g., 1-hour, 4-hour) where the daily VWAP provides a higher-timeframe trend bias. It can also be used on daily charts with adjustments to the cooldown period.
Markets: Works well in trending markets (e.g., forex, crypto, stocks) where the dynamic trend line can capture sustained price movements. The VWAP filter helps align signals with the daily trend, making it effective for assets with clear daily biases.
Trading Strategy:
Buy: Enter a long position when a green triangle (buy signal) appears, indicating the price has crossed above the trend line and is above the daily VWAP.
Sell: Enter a short position (or exit a long) when a red triangle (sell signal) appears, indicating the price has crossed below the trend line and is below the daily VWAP.
Use the trend line and VWAP as dynamic support/resistance levels to set stop-losses or take-profit targets.
Backtesting: Use TradingView’s strategy tester to evaluate the indicator’s performance on your chosen market and timeframe, adjusting parameters like cooldown_bars and volatility_mult to optimize for profitability.
Example
On a 4-hour SOLUSDT chart, the DTI with VWAP Filter might show:
An uptrend with the price above the green trend line and above the daily VWAP, generating buy signals as the price continues to rise.
A downtrend where the price falls below the red trend line and the daily VWAP, generating sell signals that align with the bearish daily bias.
During choppy periods, the cooldown mechanism and VWAP filter reduce false signals, ensuring trades are taken only when the price aligns with the daily trend.
Limitations
Lagging Nature: Like all trend-following indicators, the DTI may lag during sharp price reversals, as the dynamic EMA needs time to adjust.
Ranging Markets: While the VWAP filter and cooldown mechanism reduce whipsaws, the indicator may still generate some false signals in strongly ranging markets. Combining it with a trend strength filter (e.g., ADX) can help.
VWAP Dependency: The effectiveness of the VWAP filter depends on the market’s respect for the daily VWAP as a support/resistance level. In markets with low volume or erratic price action, the VWAP may be less reliable.
Potential Improvements
VWAP Buffer: Add a percentage buffer around the VWAP (e.g., require the price to be 1% above/below) to further reduce noise.
Multi-Timeframe VWAP: Incorporate a weekly VWAP for additional trend confirmation on longer timeframes.
Trend Strength Filter: Add an ADX filter to ensure signals are generated only during strong trends (e.g., ADX > 25).
Stochastic Fusion Elite [trade_lexx]📈 Stochastic Fusion Elite is your reliable trading assistant!
📊 What is Stochastic Fusion Elite ?
Stochastic Fusion Elite is a trading indicator based on a stochastic oscillator. It analyzes the rate of price change and generates buy or sell signals based on various technical analysis methods.
💡 The main components of the indicator
📊 Stochastic oscillator (K and D)
Stochastic shows the position of the current price relative to the price range for a certain period. Values above 80 indicate overbought (an early sale is possible), and values below 20 indicate oversold (an early purchase is possible).
📈 Moving Averages (MA)
The indicator uses 10 different types of moving averages to smooth stochastic lines.:
- SMA: Simple moving average
- EMA: Exponential moving average
- WMA: Weighted moving average
- HMA: Moving Average Scale
- KAMA: Kaufman Adaptive Moving Average
- VWMA: Volume-weighted moving average
- ALMA: Arnaud Legoux Moving Average
- TEMA: Triple exponential moving average
- ZLEMA: zero delay exponential moving average
- DEMA: Double exponential moving average
The choice of the type of moving average affects the speed of the indicator's response to market changes.
🎯 Bollinger Bands (BB)
Bands around the moving average that widen and narrow depending on volatility. They help determine when the stochastic is out of the normal range.
🔄 Divergences
Divergences show discrepancies between price and stochastic:
- Bullish divergence: price is falling and stochastic is rising — an upward reversal is possible
- Bearish divergence: the price is rising, and stochastic is falling — a downward reversal is possible
🔍 Indicator signals
1️⃣ KD signals (K and D stochastic lines)
- Buy signal:
- What happens: the %K line crosses the %D line from bottom to top
- What does it look like: a green triangle with the label "KD" under the chart and the label "Buy" below the bar
- What does this mean: the price is gaining an upward momentum, growth is possible
- Sell signal:
- What happens: the %K line crosses the %D line from top to bottom
- What it looks like: a red triangle with the label "KD" above the chart and the label "Sell" above the bar
- What does this mean: the price is losing its upward momentum, possibly falling
2️⃣ Moving Average Signals (MA)
- Buy Signal:
- What happens: stochastic crosses the moving average from bottom to top
- What it looks like: a green triangle with the label "MA" under the chart and the label "Buy" below the bar
- What does this mean: stochastic is starting to accelerate upward, price growth is possible
- Sell signal:
- What happens: stochastic crosses the moving average from top to bottom
- What it looks like: a red triangle with the label "MA" above the chart and the label "Sell" above the bar
- What does this mean: stochastic is starting to accelerate downwards, a price drop is possible
3️⃣ Bollinger Band Signals (BB)
- Buy signal:
- What happens: stochastic crosses the lower Bollinger band from bottom to top
- What it looks like: a green triangle with the label "BB" under the chart and the label "Buy" below the bar
- What does this mean: stochastic was too low and is now starting to recover
- Sell signal:
- What happens: Stochastic crosses the upper Bollinger band from top to bottom
- What it looks like: a red triangle with a "BB" label above the chart and a "Sell" label above the bar
- What does this mean: stochastic was too high and is now starting to decline
4️⃣ Divergence Signals (Div)
- Buy Signal (Bullish Divergence):
- What's happening: the price is falling, and stochastic is forming higher lows
- What it looks like: a green triangle with a "Div" label under the chart and a "Buy" label below the bar
- What does this mean: despite the falling price, the momentum is already changing in an upward direction
- Sell signal (bearish divergence):
- What's going on: the price is rising, and stochastic is forming lower highs
- What it looks like: a red triangle with a "Div" label above the chart and a "Sell" label above the bar
- What does this mean: despite the price increase, the momentum is already weakening
🛠️ Filters to filter out false signals
1️⃣ Minimum distance between the signals
- What it does: sets the minimum number of candles between signals
- Why it is needed: prevents signals from being too frequent during strong market fluctuations
- How to set it up: Set the number from 0 and above (default: 5)
2️⃣ "Waiting for the opposite signal" mode
- What it does: waits for a signal in the opposite direction before generating a new signal
- Why you need it: it helps you not to miss important trend reversals
- How to set up: just turn the function on or off
3️⃣ Filter by stochastic levels
- What it does: generates signals only when the stochastic is in the specified ranges
- Why it is needed: it helps to catch the moments when the market is oversold or overbought
- How to set up:
- For buy signals: set a range for oversold (for example, 1-20)
- For sell signals: set a range for overbought (for example, 80-100)
4️⃣ MFI filter
- What it does: additionally checks the values of the cash flow index (MFI)
- Why it is needed: confirms stochastic signals with cash flow data
- How to set it up:
- For buy signals: set the range for oversold MFI (for example, 1-25)
- For sell signals: set the range for overbought MFI (for example, 75-100)
5️⃣ The RSI filter
- What it does: additionally checks the RSI values to confirm the signals
- Why it is needed: adds additional confirmation from another popular indicator
- How to set up:
- For buy signals: set the range for oversold MFI (for example, 1-30)
- For sell signals: set the range for overbought MFI (for example, 70-100)
🔄 Signal combination modes
1️⃣ Normal mode
- How it works: all signals (KD, MA, BB, Div) work independently of each other
- When to use it: for general market analysis or when learning how to work with the indicator
2️⃣ "AND" Mode ("AND Mode")
- How it works: the alarm appears only when several conditions are triggered simultaneously
- Combination options:
- KD+MA: signals from the KD and moving average lines
- KD+BB: signals from KD lines and Bollinger bands
- KD+Div: signals from the KD and divergence lines
- KD+MA+BB: three signals simultaneously
- KD+MA+Div: three signals at the same time
- KD+BB+Div: three signals at the same time
- KD+MA+BB+Div: all four signals at the same time
- When to use: for more reliable but rare signals
🔌 Connecting to trading strategies
The indicator can be connected to your trading strategies using 6 different channels.:
1. Connector KD signals: connects only the signals from the intersection of lines K and D
2. Connector MA signals: connects only signals from moving averages
3. Connector BB signal: connects only the signals from the Bollinger bands
4. Connector divergence signals: connects only divergence signals
5. Combined Connector: connects any signals
6. Connector for "And" mode: connects only combined signals
🔔 Setting up alerts
The indicator can send alerts when alarms appear.:
- Alerts for KD: when the %K line crosses the %D line
- Alerts for MA: when stochastic crosses the moving average
- Alerts for BB: when stochastic crosses the Bollinger bands
- Divergence alerts: when a divergence is detected
- Combined alerts: for all types of alarms
- Alerts for "And" mode: for combined signals
🎭 What does the indicator look like on the chart ?
- Main lines K and D: blue and orange lines
- Overbought/oversold levels: horizontal lines at levels 20 and 80
- Middle line: dotted line at level 50
- Stochastic Moving Average: yellow line
- Bollinger bands: green lines around the moving average
- Signals: green and red triangles with corresponding labels
📚 How to start using Stochastic Fusion Elite
1️⃣ Initial setup
- Add an indicator to your chart
- Select the types of signals you want to use (KD, MA, BB, Div)
- Adjust the period and smoothing for the K and D lines
2️⃣ Filter settings
- Set the distance between the signals to get rid of unnecessary noise
- Adjust stochastic, MFI and RSI levels depending on the volatility of your asset
- If you need more reliable signals, turn on the "Waiting for the opposite signal" mode.
3️⃣ Operation mode selection
- First, use the standard mode to see all possible signals.
- When you get comfortable, try the "And" mode for rarer signals.
4️⃣ Setting up Alerts
- Select the types of signals you want to be notified about
- Set up alerts for these types of signals
5️⃣ Verification and adaptation
- Check the operation of the indicator on historical data
- Adjust the parameters for a specific asset
- Adapt the settings to your trading style
🌟 Usage examples
For trend trading
- Use the KD and MA signals in the direction of the main trend
- Set the distance between the signals
- Set stricter levels for filters
For trading in a sideways range
- Use BB signals to detect bounces from the range boundaries
- Use a stochastic level filter to confirm overbought/oversold conditions
- Adjust the Bollinger bands according to the width of the range
To determine the pivot points
- Pay attention to the divergence signals
- Set the distance between the signals
- Check the MFI and RSI filters for additional confirmation
Multi-Timeframe EMAsThis TradingView indicator provides a comprehensive overview of price momentum by overlaying multiple Exponential Moving Averages (EMAs) from different timeframes onto a single chart. By combining 1-hour, 4-hour, and daily EMAs, you can observe short-term trends while simultaneously monitoring medium-term and long-term market dynamics. The 1-hour EMA 13 and EMA 21 help capture rapid price changes, which is useful for scalpers or intraday traders looking to identify sudden momentum shifts. Meanwhile, the 4-hour EMA 21 offers a more stable, intermediate perspective, filtering out some of the noise found in shorter intervals. Finally, the daily EMAs (13, 25, and 50) highlight prevailing market sentiment over a longer period, enabling traders to assess higher-level trends and gauge whether short-term signals align with overarching tendencies. By plotting all these EMAs together, it becomes easier to detect confluences or divergences across different time horizons, making it simpler to refine entries and exits based on multi-timeframe confirmation. This script is especially helpful for swing traders and position traders who wish to ensure that smaller timeframe strategies do not conflict with long-term market direction.
Ehlers Adaptive Trend Indicator [Alpha Extract]Ehlers Adaptive Trend Indicator
The Ehlers Adaptive Trend Indicator combines Ehlers' advanced digital signal processing techniques with dynamic volatility bands to identify robust trend conditions and potential reversals. This powerful tool helps traders visualize trend strength, adaptive support/resistance levels, and momentum shifts across various market conditions.
🔶 CALCULATION
The indicator employs a sophisticated adaptive algorithm that responds to changing market conditions:
• Ehlers Filter : Calculates a weighted average based on momentum differences to create an adaptive trend baseline.
• Dynamic Bands : Volatility-adjusted bands that expand and contract based on recent price action.
• Trend Level : A dynamic support/resistance level that adapts to the current trend direction.
• Smoothed Volatility : Market volatility measured and smoothed to provide reliable band width.
Formula:
• Ehlers Basis = Weighted average of price, with weights determined by momentum differences
• Volatility = Standard deviation of price over Ehlers Length period
• Smoothed Volatility = EMA of volatility over Smoothing Length
• Upper Band = Ehlers Basis + Smoothed Volatility × Sensitivity
• Lower Band = Ehlers Basis - Smoothed Volatility × Sensitivity
• Trend Level = Adaptive support in uptrends, resistance in downtrends
🔶 DETAILS
Visual Features :
• Ehlers Basis Line (Yellow): The core adaptive trend reference that serves as the primary trend indicator.
• Trend Level Line (Dynamic Color): Changes between green (bullish) and red (bearish) based on the current trend state.
• Fill Areas : Transparent green fill during bullish trends and transparent red fill during bearish trends for clear visual identification.
• Bar Coloring : Optional price bar coloring that reflects the current trend direction for enhanced visualization.
Interpretation :
• **Bullish Signal**: Price crosses above the upper band, triggering a trend change with the Trend Level becoming dynamic support.
• **Bearish Signal**: Price drops below the lower band, confirming a trend change with the Trend Level becoming dynamic resistance.
• **Trend Continuation**: Trend Level rises in bullish markets and falls in bearish markets, providing adaptive trailing support/resistance.
🔶 EXAMPLES
The chart demonstrates:
• Bullish Trend Identification : When price breaks above the upper band, the indicator shifts to bullish mode with green trend level and fill.
• Bearish Trend Identification : When price falls below the lower band, the indicator shifts to bearish mode with red trend level and fill.
• Trend Persistence : Trend Level adapts to market movement, rising during uptrends to provide dynamic support and falling during downtrends to act as resistance.
Example Snapshots :
• During a strong uptrend, the Trend Level continuously adjusts upward, keeping traders in the trend while filtering out minor retracements.
• During trend reversals, clear color changes and Trend Level shifts provide early warning of potential direction changes.
🔶 SETTINGS
Customization Options :
• Ehlers Length (p1) (Default: 30): Controls the primary adaptive calculation period, balancing responsiveness with stability.
• Momentum Length (p2) (Default: 25): Determines the lag for momentum calculations used in the adaptive weighting.
• Smoothing Length (Default: 10): Adjusts the volatility smoothing period—higher values provide more stable bands.
• Sensitivity (Default: 1.0): Multiplier for band width—higher values increase distance between bands, lower values tighten them.
• Visual Settings : Customizable colors for bullish and bearish trends, basis line, and optional bar coloring.
The Ehlers Adaptive Trend Indicator combines John Ehlers' digital signal processing expertise with modern volatility analysis to create a robust trend-following system that adapts to changing market conditions, helping traders stay on the right side of the market.
Dynamic Candle Range Point IndicatorThe "Dynamic Candle Range Point Indicator" (DCRPI) does two important jobs at once. For each candle on your chart, it shows you exactly how many points the price moved in two different ways:
1. At the top of each candle, you'll see how many points the price moved from open to close (the body range)
2. At the bottom, you'll see the total movement from the highest to lowest point (the full range)
The really smart part is how it colors the borders of candles based on how much the price moved. This gives you a quick visual way to spot significant price movements:
- Small movements keep the standard green/red colors
- Medium movements (25-30 points) show as yellow
- Larger movements get more unique colors (orange, purple, blue, etc.)
This makes it easy to instantly identify which candles had the most significant price movement without having to read all the numbers. You can quickly spot the most volatile candles across your chart by their distinctive border colors.
The indicator is lightweight and should run smoothly on most charts without causing performance issues.
Mogwai Method with RSI and EMA - BTCUSD 15mThis is a custom TradingView indicator designed for trading Bitcoin (BTCUSD) on a 15-minute timeframe. It’s based on the Mogwai Method—a mean-reversion strategy—enhanced with the Relative Strength Index (RSI) for momentum confirmation. The indicator generates buy and sell signals, visualized as green and red triangle arrows on the chart, to help identify potential entry and exit points in the volatile cryptocurrency market.
Components
Bollinger Bands (BB):
Purpose: Identifies overextended price movements, signaling potential reversions to the mean.
Parameters:
Length: 20 periods (standard for mean-reversion).
Multiplier: 2.2 (slightly wider than the default 2.0 to suit BTCUSD’s volatility).
Role:
Buy signal when price drops below the lower band (oversold).
Sell signal when price rises above the upper band (overbought).
Relative Strength Index (RSI):
Purpose: Confirms momentum to filter out false signals from Bollinger Bands.
Parameters:
Length: 14 periods (classic setting, effective for crypto).
Overbought Level: 70 (price may be overextended upward).
Oversold Level: 30 (price may be overextended downward).
Role:
Buy signal requires RSI < 30 (oversold).
Sell signal requires RSI > 70 (overbought).
Exponential Moving Averages (EMAs) (Plotted but not currently in signal logic):
Purpose: Provides trend context (included in the script for visualization, optional for signal filtering).
Parameters:
Fast EMA: 9 periods (short-term trend).
Slow EMA: 50 periods (longer-term trend).
Role: Can be re-added to filter signals (e.g., buy only when Fast EMA > Slow EMA).
Signals (Triangles):
Buy Signal: Green upward triangle below the bar when price is below the lower Bollinger Band and RSI is below 30.
Sell Signal: Red downward triangle above the bar when price is above the upper Bollinger Band and RSI is above 70.
How It Works
The indicator combines Bollinger Bands and RSI to spot mean-reversion opportunities:
Buy Condition: Price breaks below the lower Bollinger Band (indicating oversold conditions), and RSI confirms this with a reading below 30.
Sell Condition: Price breaks above the upper Bollinger Band (indicating overbought conditions), and RSI confirms this with a reading above 70.
The strategy assumes that extreme price movements in BTCUSD will often revert to the mean, especially in choppy or ranging markets.
Visual Elements
Green Upward Triangles: Appear below the candlestick to indicate a buy signal.
Red Downward Triangles: Appear above the candlestick to indicate a sell signal.
Bollinger Bands: Gray lines (upper, middle, lower) plotted for reference.
EMAs: Blue (Fast) and Orange (Slow) lines for trend visualization.
How to Use the Indicator
Setup
Open TradingView:
Log into TradingView and select a BTCUSD chart from a supported exchange (e.g., Binance, Coinbase, Bitfinex).
Set Timeframe:
Switch the chart to a 15-minute timeframe (15m).
Add the Indicator:
Open the Pine Editor (bottom panel in TradingView).
Copy and paste the script provided.
Click “Add to Chart” to apply it.
Verify Display:
You should see Bollinger Bands (gray), Fast EMA (blue), Slow EMA (orange), and buy/sell triangles when conditions are met.
Trading Guidelines
Buy Signal (Green Triangle Below Bar):
What It Means: Price is oversold, potentially ready to bounce back toward the Bollinger Band middle line.
Action:
Enter a long position (buy BTCUSD).
Set a take-profit near the middle Bollinger Band (bb_middle) or a resistance level.
Place a stop-loss 1-2% below the entry (or based on ATR, e.g., ta.atr(14) * 2).
Best Context: Works well in ranging markets; avoid during strong downtrends.
Sell Signal (Red Triangle Above Bar):
What It Means: Price is overbought, potentially ready to drop back toward the middle line.
Action:
Enter a short position (sell BTCUSD) or exit a long position.
Set a take-profit near the middle Bollinger Band or a support level.
Place a stop-loss 1-2% above the entry.
Best Context: Effective in ranging markets; avoid during strong uptrends.
Trend Filter (Optional):
To reduce false signals in trending markets, you can modify the script:
Add and ema_fast > ema_slow to the buy condition (only buy in uptrends).
Add and ema_fast < ema_slow to the sell condition (only sell in downtrends).
Check the Fast EMA (blue) vs. Slow EMA (orange) alignment visually.
Tips for BTCUSD on 15-Minute Charts
Volatility: BTCUSD can be erratic. If signals are too frequent, increase bb_mult (e.g., to 2.5) or adjust RSI levels (e.g., 75/25).
Confirmation: Use volume spikes or candlestick patterns (e.g., doji, engulfing) to confirm signals.
Time of Day: Mean-reversion works best during low-volume periods (e.g., Asian session in crypto).
Backtesting: Use TradingView’s Strategy Tester (convert to a strategy by adding entry/exit logic) to evaluate performance with historical BTCUSD data up to March 13, 2025.
Risk Management
Position Size: Risk no more than 1-2% of your account per trade.
Stop Losses: Always use stops to protect against BTCUSD’s sudden moves.
Avoid Overtrading: Wait for clear signals; don’t force trades in choppy or unclear conditions.
Example Scenario
Chart: BTCUSD, 15-minute timeframe.
Buy Signal: Price drops to $58,000, below the lower Bollinger Band, RSI at 28. A green triangle appears.
Action: Buy at $58,000, target $59,000 (middle BB), stop at $57,500.
Sell Signal: Price rises to $60,500, above the upper Bollinger Band, RSI at 72. A red triangle appears.
Action: Sell at $60,500, target $59,500 (middle BB), stop at $61,000.
This indicator is tailored for mean-reversion trading on BTCUSD. Let me know if you’d like to tweak it further (e.g., add filters, alerts, or alternative indicators)!
[GYTS-CE] Market Regime Detector🧊 Market Regime Detector (Community Edition)
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What is the Market Regime Detector?
The Market Regime Detector is an advanced, consensus-based indicator that identifies the current market state to increase the probability of profitable trades. By distinguishing between trending (bullish or bearish) and cyclic (range-bound) market conditions, this detector helps you select appropriate tactics for different environments. Instead of forcing a single strategy across all market conditions, our detector allows you to adapt your approach based on real-time market behaviour.
💮 The Importance of Market Regimes
Markets constantly shift between different behavioural states or "regimes":
• Bullish trending markets - characterised by sustained upward price movement
• Bearish trending markets - characterised by sustained downward price movement
• Cyclic markets - characterised by range-bound, oscillating behaviour
Each regime requires fundamentally different trading approaches. Trend-following strategies excel in trending markets but fail in cyclic ones, while mean-reversion strategies shine in cyclic markets but underperform in trending conditions. Detecting these regimes is essential for successful trading, which is why we've developed the Market Regime Detector to accurately identify market states using complementary detection methods.
🌸 --------- KEY FEATURES --------- 🌸
💮 Consensus-Based Detection
Rather than relying on a single method, our detector employs two complementary detection methodologies that analyse different aspects of market behaviour:
• Dominant Cycle Average (DCA) - analyzes price movement relative to its lookback period, a proxy for the dominant cycle
• Volatility Channel - examines price behaviour within adaptive volatility bands
These diverse perspectives are synthesised into a robust consensus that minimises false signals while maintaining responsiveness to genuine regime changes.
💮 Dominant Cycle Framework
The Market Regime Detector uses the concept of dominant cycles to establish a reference framework. You can input the dominant cycle period that best represents the natural rhythm of your market, providing a stable foundation for regime detection across different timeframes.
💮 Intuitive Parameter System
We've distilled complex technical parameters into intuitive controls that traders can easily understand:
• Adaptability - how quickly the detector responds to changing market conditions
• Sensitivity - how readily the detector identifies transitions between regimes
• Consensus requirement - how much agreement is needed among detection methods
This approach makes the detector accessible to traders of all experience levels while preserving the power of the underlying algorithms.
💮 Visual Market Feedback
The detector provides clear visual feedback about the current market regime through:
• Colour-coded chart backgrounds (purple shades for bullish, pink for bearish, yellow for cyclic)
• Colour-coded price bars
• Strength indicators showing the degree of consensus
• Customizable colour schemes to match your preferences or trading system
💮 Integration in the GYTS suite
The Market Regime Detector is compatible with the GYTS Suite , i.e. it passes the regime into the 🎼 Order Orchestrator where you can set how to trade the trending and cyclic regime.
🌸 --------- CONFIGURATION SETTINGS --------- 🌸
💮 Adaptability
Controls how quickly the Market Regime detector adapts to changing market conditions. You can see it as a low-frequency, long-term change parameter:
Very Low: Very slow adaptation, most stable but may miss regime changes
Low: Slower adaptation, more stability but less responsiveness
Normal: Balanced between stability and responsiveness
High: Faster adaptation, more responsive but less stable
Very High: Very fast adaptation, highly responsive but may generate false signals
This setting affects lookback periods and filter parameters across all detection methods.
💮 Sensitivity
Controls how sensitive the detector is to market regime transitions. This acts as a high-frequency, short-term change parameter:
Very Low: Requires substantial evidence to identify a regime change
Low: Less sensitive, reduces false signals but may miss some transitions
Normal: Balanced sensitivity suitable for most markets
High: More sensitive, detects subtle regime changes but may have more noise
Very High: Very sensitive, detects minor fluctuations but may produce frequent changes
This setting affects thresholds for regime detection across all methods.
💮 Dominant Cycle Period
This parameter allows you to specify the market's natural rhythm in bars. This represents a complete market cycle (up and down movement). Finding the right value for your specific market and timeframe might require some experimentation, but it's a crucial parameter that helps the detector accurately identify regime changes. Most of the times the cycle is between 20 and 40 bars.
💮 Consensus Mode
Determines how the signals from both detection methods are combined to produce the final market regime:
• Any Method (OR) : Signals bullish/bearish if either method detects that regime. If methods conflict (one bullish, one bearish), the stronger signal wins. More sensitive, catches more regime changes but may produce more false signals.
• All Methods (AND) : Signals only when both methods agree on the regime. More conservative, reduces false signals but might miss some legitimate regime changes.
• Weighted Decision : Balances both methods with equal weighting. Provides a middle ground between sensitivity and stability.
Each mode also calculates a continuous regime strength value that's used for colour intensity in the 'unconstrained' display mode.
💮 Display Mode
Choose how to display the market regime colours:
• Unconstrained regime: Shows the regime strength as a continuous gradient. This provides more nuanced visualisation where the intensity of the colour indicates the strength of the trend.
• Consensus only: Shows only the final consensus regime with fixed colours based on the detected regime type.
The background and bar colours will change to indicate the current market regime:
• Purple shades: Bullish trending market (darker purple indicates stronger bullish trend)
• Pink shades: Bearish trending market (darker pink indicates stronger bearish trend)
• Yellow: Cyclic (range-bound) market
💮 Custom Colour Options
The Market Regime Detector allows you to customize the colour scheme to match your personal preferences or to coordinate with other indicators:
• Use custom colours: Toggle to enable your own colour choices instead of the default scheme
• Transparency: Adjust the transparency level of all regime colours
• Bullish colours: Define custom colours for strong, medium, weak, and very weak bullish trends
• Bearish colours: Define custom colours for strong, medium, weak, and very weak bearish trends
• Cyclic colour: Define a custom colour for cyclic (range-bound) market conditions
🌸 --------- DETECTION METHODS --------- 🌸
💮 Dominant Cycle Average (DCA)
The Dominant Cycle Average method forms a key part of our detection system:
1. Theoretical Foundation :
The DCA method builds on cycle analysis and the observation that in trending markets, price consistently remains on one side of a moving average calculated using the dominant cycle period. In contrast, during cyclic markets, price oscillates around this average.
2. Calculation Process :
• We calculate a Simple Moving Average (SMA) using the specified lookback period - a proxy for the dominant cycle period
• We then analyse the proportion of time that price spends above or below this SMA over a lookback window. The theory is that the price should cross the SMA each half cycle, assuming that the dominant cycle period is correct and price follows a sinusoid.
• This lookback window is adaptive, scaling with the dominant cycle period (controlled by the Adaptability setting)
• The different values are standardised and normalised to possess more resolving power and to be more robust to noise.
3. Regime Classification :
• When the normalised proportion exceeds a positive threshold (determined by Sensitivity setting), the market is classified as bullish trending
• When it falls below a negative threshold, the market is classified as bearish trending
• When the proportion remains between these thresholds, the market is classified as cyclic
💮 Volatility Channel
The Volatility Channel method complements the DCA method by focusing on price movement relative to adaptive volatility bands:
1. Theoretical Foundation :
This method is based on the observation that trending markets tend to sustain movement outside of normal volatility ranges, while cyclic markets tend to remain contained within these ranges. By creating adaptive bands that adjust to current market volatility, we can detect when price behaviour indicates a trending or cyclic regime.
2. Calculation Process :
• We first calculate a smooth base channel center using a low pass filter, creating a noise-reduced centreline for price
• True Range (TR) is used to measure market volatility, which is then smoothed and scaled by the deviation factor (controlled by Sensitivity)
• Upper and lower bands are created by adding and subtracting this scaled volatility from the centreline
• Price is smoothed using an adaptive A2RMA filter, which has a very flat and stable behaviour, to reduce noise while preserving trend characteristics
• The position of this smoothed price relative to the bands is continuously monitored
3. Regime Classification :
• When smoothed price moves above the upper band, the market is classified as bullish trending
• When smoothed price moves below the lower band, the market is classified as bearish trending
• When price remains between the bands, the market is classified as cyclic
• The magnitude of price's excursion beyond the bands is used to determine trend strength
4. Adaptive Behaviour :
• The smoothing periods and deviation calculations automatically adjust based on the Adaptability setting
• The measured volatility is calculated over a period proportional to the dominant cycle, ensuring the detector works across different timeframes
• Both the center line and the bands adapt dynamically to changing market conditions, making the detector responsive yet stable
This method provides a unique perspective that complements the DCA approach, with the consensus mechanism synthesising insights from both methods.
🌸 --------- USAGE GUIDE --------- 🌸
💮 Starting with Default Settings
The default settings (Normal for Adaptability and Sensitivity, Weighted Decision for Consensus Mode) provide a balanced starting point suitable for most markets and timeframes. Begin by observing how these settings identify regimes in your preferred instruments.
💮 Finding the Optimal Dominant Cycle
The dominant cycle period is a critical parameter. Here are some approaches to finding an appropriate value:
• Start with typical values, usually something around 25 works well
• Visually identify the average distance between significant peaks and troughs
• Experiment with different values and observe which provides the most stable regime identification
• Consider using cycle-finding indicators to help identify the natural rhythm of your market
💮 Adjusting Parameters
• If you notice too many regime changes → Decrease Sensitivity or increase Consensus requirement
• If regime changes seem delayed → Increase Adaptability
• If a trending regime is not detected, the market is automatically assigned to be in a cyclic state
• If you want to see more nuanced regime transitions → Try the "unconstrained" display mode (note that this will not affect the output to other indicators)
💮 Trading Applications
Regime-Specific Strategies:
• Bullish Trending Regime - Use trend-following strategies, trail stops wider, focus on breakouts, consider holding positions longer, and emphasize buying dips
• Bearish Trending Regime - Consider shorts, tighter stops, focus on breakdown points, sell rallies, implement downside protection, and reduce position sizes
• Cyclic Regime - Apply mean-reversion strategies, trade range boundaries, apply oscillators, target definable support/resistance levels, and use profit-taking at extremes
Strategy Switching:
Create a set of rules for each market regime and switch between them based on the detector's signal. This approach can significantly improve performance compared to applying a single strategy across all market conditions.
GYTS Suite Integration:
• In the GYTS 🎼 Order Orchestrator, select the '🔗 STREAM-int 🧊 Market Regime' as the market regime source
• Note that the consensus output (i.e. not the "unconstrained" display) will be used in this stream
• Create different strategies for trending (bullish/bearish) and cyclic regimes. The GYTS 🎼 Order Orchestrator is specifically made for this.
• The output stream is actually very simple, and can possibly be used in indicators and strategies as well. It outputs 1 for bullish, -1 for bearish and 0 for cyclic regime.
🌸 --------- FINAL NOTES --------- 🌸
💮 Development Philosophy
The Market Regime Detector has been developed with several key principles in mind:
1. Robustness - The detection methods have been rigorously tested across diverse markets and timeframes to ensure reliable performance.
2. Adaptability - The detector automatically adjusts to changing market conditions, requiring minimal manual intervention.
3. Complementarity - Each detection method provides a unique perspective, with the collective consensus being more reliable than any individual method.
4. Intuitiveness - Complex technical parameters have been abstracted into easily understood controls.
💮 Ongoing Refinement
The Market Regime Detector is under continuous development. We regularly:
• Fine-tune parameters based on expanded market data
• Research and integrate new detection methodologies
• Optimise computational efficiency for real-time analysis
Your feedback and suggestions are very important in this ongoing refinement process!
Market Trend Levels Non-Repainting [BigBeluga X PineIndicators]This strategy is based on the Market Trend Levels Detector developed by BigBeluga. Full credit for the concept and original indicator goes to BigBeluga.
The Market Trend Levels Detector Strategy is a non-repainting trend-following strategy that identifies market trend shifts using two Exponential Moving Averages (EMA). It also detects key price levels and allows traders to apply multiple filters to refine trade entries and exits.
This strategy is designed for trend trading and enables traders to:
Identify trend direction based on EMA crossovers.
Detect significant market levels using labeled trend lines.
Use multiple filter conditions to improve trade accuracy.
Avoid false signals through non-repainting calculations.
How the Market Trend Levels Detector Strategy Works
1. Core Trend Detection Using EMA Crossovers
The strategy detects trend shifts using two EMAs:
Fast EMA (default: 12 periods) – Reacts quickly to price movements.
Slow EMA (default: 25 periods) – Provides a smoother trend confirmation.
A bullish crossover (Fast EMA crosses above Slow EMA) signals an uptrend , while a bearish crossover (Fast EMA crosses below Slow EMA) signals a downtrend .
2. Market Level Detection & Visualization
Each time an EMA crossover occurs, a trend level line is drawn:
Bullish crossover → A green line is drawn at the low of the crossover candle.
Bearish crossover → A purple line is drawn at the high of the crossover candle.
Lines can be extended to act as support and resistance zones for future price action.
Additionally, a small label (●) appears at each crossover to mark the event on the chart.
3. Trade Entry & Exit Conditions
The strategy allows users to choose between three trading modes:
Long Only – Only enters long trades.
Short Only – Only enters short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish EMA crossover occurs.
The trade direction setting allows long trades.
Filter conditions (if enabled) confirm a valid long signal.
Short Entry:
A bearish EMA crossover occurs.
The trade direction setting allows short trades.
Filter conditions (if enabled) confirm a valid short signal.
Exit Conditions
Long Exit:
A bearish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid long position.
Short Exit:
A bullish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid short position.
Additional Trade Filters
To improve trade accuracy, the strategy allows traders to apply up to 7 additional filters:
RSI Filter: Only trades when RSI confirms a valid trend.
MACD Filter: Ensures MACD histogram supports the trade direction.
Stochastic Filter: Requires %K line to be above/below threshold values.
Bollinger Bands Filter: Confirms price position relative to the middle BB line.
ADX Filter: Ensures the trend strength is above a set threshold.
CCI Filter: Requires CCI to indicate momentum in the right direction.
Williams %R Filter: Ensures price momentum supports the trade.
Filters can be enabled or disabled individually based on trader preference.
Dynamic Level Extension Feature
The strategy provides an optional feature to extend trend lines until price interacts with them again:
Bullish support lines extend until price revisits them.
Bearish resistance lines extend until price revisits them.
If price breaks a line, the line turns into a dotted style , indicating it has been breached.
This helps traders identify key levels where trend shifts previously occurred, providing useful support and resistance insights.
Customization Options
The strategy includes several adjustable settings :
Trade Direction: Choose between Long Only, Short Only, or Long & Short.
Trend Lengths: Adjust the Fast & Slow EMA lengths.
Market Level Extension: Decide whether to extend support/resistance lines.
Filters for Trade Confirmation: Enable/disable individual filters.
Color Settings: Customize line colors for bullish and bearish trend shifts.
Maximum Displayed Lines: Limit the number of drawn support/resistance lines.
Considerations & Limitations
Trend Lag: As with any EMA-based strategy, signals may be slightly delayed compared to price action.
Sideways Markets: This strategy works best in trending conditions; frequent crossovers in sideways markets can produce false signals.
Filter Usage: Enabling multiple filters may reduce trade frequency, but can also improve trade quality.
Line Overlap: If many crossovers occur in a short period, the chart may become cluttered with multiple trend levels. Adjusting the "Display Last" setting can help.
Conclusion
The Market Trend Levels Detector Strategy is a non-repainting trend-following system that combines EMA crossovers, market level detection, and customizable filters to improve trade accuracy.
By identifying trend shifts and key price levels, this strategy can be used for:
Trend Confirmation – Using EMA crossovers and filters to confirm trend direction.
Support & Resistance Trading – Identifying dynamic levels where price reacts.
Momentum-Based Trading – Combining EMA crossovers with additional momentum filters.
This strategy is fully customizable and can be adapted to different trading styles, timeframes, and market conditions.
Full credit for the original concept and indicator goes to BigBeluga.
Quantitative Easing and Tightening PeriodsQuantitative Easing (QE) and Quantitative Tightening (QT) periods based on historical events from the Federal Reserve:
Quantitative Easing (QE) Periods:
QE1:
Start: November 25, 2008
End: March 31, 2010
Description: The Federal Reserve initiated QE1 in response to the financial crisis, purchasing mortgage-backed securities and Treasuries.
QE2:
Start: November 3, 2010
End: June 29, 2011
Description: QE2 involved the purchase of $600 billion in U.S. Treasury bonds to further stimulate the economy.
QE3:
Start: September 13, 2012
End: October 29, 2014
Description: QE3 was an open-ended bond-buying program with monthly purchases of $85 billion in Treasuries and mortgage-backed securities.
QE4 (COVID-19 Pandemic Response):
Start: March 15, 2020
End: March 10, 2022
Description: The Federal Reserve engaged in QE4 in response to the economic impact of the COVID-19 pandemic, purchasing Treasuries and MBS in an effort to provide liquidity.
Quantitative Tightening (QT) Periods:
QT1:
Start: October 1, 2017
End: August 1, 2019
Description: The Federal Reserve began shrinking its balance sheet in 2017, gradually reducing its holdings of U.S. Treasuries and mortgage-backed securities. This period ended in August 2019 when the Fed decided to stop reducing its balance sheet.
QT2:
Start: June 1, 2022
End: Ongoing (as of March 2025)
Description: The Federal Reserve started QT again in June 2022, reducing its holdings of U.S. Treasuries and MBS in response to rising inflation. The Fed has continued this tightening cycle.
These periods are key moments in U.S. monetary policy, where the Fed either injected liquidity into the economy (QE) or reduced its balance sheet by not reinvesting maturing securities (QT). The exact dates and nature of these policies may vary based on interpretation and adjustments to the Fed's actions during those times.
Enhanced ROC - Savitzky–Golay [AIBitcoinTrend]👽 Adaptive ROC - Savitzky–Golay (AIBitcoinTrend)
The Adaptive ROC - Savitzky–Golay redefines traditional Rate of Change (ROC) analysis by integrating Savitzky–Golay smoothing with volatility-adaptive normalization, allowing it to dynamically adjust across different market conditions. Unlike the standard ROC, which reacts rigidly to price changes, this advanced version refines trend signals while maintaining responsiveness to volatility.
Additionally, this indicator features real-time divergence detection and an ATR-based trailing stop system, equipping traders with a powerful toolset for momentum analysis, reversals, and trend-following strategies.
👽 What Makes the Adaptive ROC - Savitzky–Golay Unique?
Unlike conventional ROC indicators, this enhanced version leverages volatility-adjusted scaling and Z-score normalization to improve signal consistency across different timeframes and assets.
✅ Savitzky–Golay Smoothing – Reduces noise while preserving trend structure for clearer signals.
✅ Volatility-Adaptive Normalization – Ensures that overbought and oversold thresholds remain consistent across different markets.
✅ Real-Time Divergence Detection – Identifies early bullish and bearish divergence signals for potential reversals.
✅ Crossovers & ATR-Based Trailing Stops – Implements intelligent trade management with dynamic stop levels.
👽 The Math Behind the Indicator
👾 Savitzky–Golay Smoothing
The indicator applies a Savitzky–Golay filter to the raw ROC data, creating a smoother curve while preserving key inflection points. This technique prevents excessive lag while maintaining the integrity of price movements.
sg_roc = (roc_raw + 3*roc_raw + 5*roc_raw + 7*roc_raw + 5*roc_raw + 3*roc_raw + roc_raw ) / 25
👾 Volatility-Adaptive Scaling
By dynamically adjusting the smoothed ROC using standard deviation, the indicator ensures that momentum readings remain relative to the market’s current volatility.
volatility = ta.stdev(close, rocLength)
dynamicFactor = 1 / (1 + volatility / 100)
advanced_sg_roc = sg_roc * dynamicFactor
👾 Z-Score Normalization
To maintain a stable Overbought/Oversold structure across different markets, the ROC is normalized using a Z-score transformation, ensuring its values remain statistically relevant.
rocMean = ta.wma(advanced_sg_roc, lenZ)
rocStdev = ta.stdev(advanced_sg_roc, lenZ)
zRoc = (advanced_sg_roc - rocMean) / rocStdev
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence Setup:
Price makes a lower low, while the ROC forms a higher low.
A buy signal is confirmed when the ROC starts rising.
Bearish Divergence Setup:
Price makes a higher high, while the ROC forms a lower high.
A sell signal is confirmed when the ROC starts declining.
👾 Buy & Sell Signals with Trailing Stop
Bullish Setup:
✅ ROC crosses above the bullish trigger level → Buy Signal.
✅ A bullish trailing stop is placed at Low - (ATR × Multiplier).
✅ Exit if price crosses below the stop.
Bearish Setup:
✅ ROC crosses below the bearish trigger level → Sell Signal.
✅ A bearish trailing stop is placed at High + (ATR × Multiplier).
✅ Exit if price crosses above the stop.
👽 Why It’s Useful for Traders
Savitzky–Golay Filtering – Retains essential trend details while eliminating excessive noise.
Volatility-Adjusted Normalization – Makes overbought/oversold levels universally reliable across markets.
Real-Time Divergence Alerts – Identifies early reversal signals for optimal entries and exits.
ATR-Based Risk Management – Ensures stops dynamically adapt to market conditions.
Works Across Markets & Timeframes - Suitable for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
ROC Period – Defines the number of bars used for ROC calculation.
Smoothing Strength – Adjusts the degree of Savitzky–Golay filtering.
Volatility Scaling – Enables or disables the adaptive volatility factor.
Enable Divergence Analysis – Turns on real-time divergence detection.
Lookback Period – Specifies the pivot detection period for divergences.
Enable Crosses Signals – Activates trade signals based on ROC crossovers.
ATR Multiplier – Controls the sensitivity of the trailing stop.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
