Professional MSTI+ Trading Indicator"Professional MSTI+ Trading Indicator" is a comprehensive technical analysis tool that combines over 20 indicators to generate high-quality trading signals and assess market sentiment. The script integrates standard indicators (MACD, RSI, Bollinger Bands, Stochastic, Simple Moving Averages, and Volume Analysis) with advanced components (Squeeze Momentum, Fisher Transform, True Strength Index, Heikin-Ashi, Laguerre RSI, Hull MA) and further includes metrics such as ADX, Chaikin Money Flow, Williams %R, VWAP, and EMA for in-depth market analysis.
Key Features:
Multiple Presets for Different Trading Styles:
Choose from optimal configurations like Professional, Swing Trading, Day Trading, Scalping, or Reversal Hunter. Note that the presets may not work perfectly on all pairs, and manual calibration might be required. This flexibility allows you to fine-tune the settings to align with your unique strategies and signals.
Multi-Layered Signal Filtering:
Filters based on trend, volume, and volatility help eliminate false signals, enhancing the accuracy of market entries.
Comprehensive Fear & Greed Index:
The indicator aggregates data from RSI, volatility, momentum, trend, and volume to gauge overall market sentiment, providing an additional layer of market context.
Dynamic Information Panel:
Displays detailed status updates for each component (e.g., MACD, RSI, Laguerre RSI, TSI, Fisher Transform, Squeeze, Hull MA, etc.) along with a visual strength bar that represents the intensity of the trading signal.
Signal Generation:
Buy and sell signals are generated when a predefined number of conditions are met and confirmed over multiple bars. These signals are clearly displayed on the chart with arrows, making it easier to spot potential entry and exit points.
Alert Setup:
Built-in alert conditions allow you to receive real-time notifications when trading signals are generated, helping you stay on top of market movements.
"Professional MSTI+ Trading Indicator" is designed to enhance your trading strategy by providing a multi-faceted market analysis and an intuitive visual interface. While the presets offer a robust starting point, they may require manual calibration on certain pairs, giving you the flexibility to configure your own unique strategies and signals.
Educational
Gold Futures vs Spot (Candlestick + Line Overlay)📝 Script Description: Gold Futures vs Spot
This script was developed to compare the price movements between Gold Futures and Spot Gold within a specific time frame. The primary goals of this script are:
To analyze the price spread between Gold Futures and Spot
To identify potential arbitrage opportunities caused by price discrepancies
To assist in decision-making and enhance the accuracy of gold market analysis
🔧 Key Features:
Fetches price data from both Spot and Futures markets (from APIs or chart sources)
Converts and aligns data for direct comparison
Calculates the price spread (Futures - Spot)
Visualizes the spread over time or exports the data for further analysis
📅 Date Created:
🧠 Additional Notes:
This script is ideal for investors, gold traders, or analysts who want to understand the relationship between the Futures and Spot markets—especially during periods of high volatility. Unusual spreads may signal shifts in market sentiment or the actions of institutional players.
MACD Boundary PSA - CoffeeKillerMACD Boundary PSA - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the MACD Boundary PSA indicator, a powerful market analysis tool developed by CoffeeKiller that enhances the traditional MACD with advanced boundary detection and peak signaling features.
🔔 **Warning: This Indicator Has No Signal Line or MACD Line** 🔔 This indicator is my version of the MACD, that I use in conjunction with the Rev&Line indicator.
Core Concept: Enhanced MACD Analysis
The foundation of this indicator builds upon the classic Moving Average Convergence Divergence (MACD) indicator, adding boundary tracking and peak detection systems to provide clearer signals and market insights.
Histogram Bars: Market Momentum
- Positive Green Bars: Bullish momentum
- Negative Red Bars: Bearish momentum
- Color intensity varies based on momentum strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during a bullish phase
- Low Marker Line (Cyan): Tracks the lowest point reached during a bearish phase
- Acts as dynamic boundaries that help identify strength of current moves
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important momentum peaks
- Helps identify potential reversal points and momentum exhaustion
Core Components
1. MACD Calculation
- Customizable fast and slow moving averages
- Signal line smoothing options
- Flexible MA type selection (SMA or EMA)
- Custom source input options
2. Boundary Tracking System
- Automatic detection of highest values in bullish phases
- Automatic detection of lowest values in bearish 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. Time Resolution Control
- Normal mode: calculations based on chart timeframe
- Custom resolution mode: calculations based on specified timeframe
Main Features
Time Resolution Settings
- Normal mode: calculations match your chart's timeframe
- Custom resolution mode: calculations based on specified timeframe
- Helps identify stronger signals from other timeframes
Visual Elements
- Color-coded histogram bars
- Dynamic marker lines for boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for momentum strength
- Peak formation for potential reversals
- Color changes for momentum direction
Customization Options
- MA types and lengths
- Signal smoothing
- Color schemes
- Marker line visibility
- Peak background display options
Trading Applications
1. Trend Identification
- Histogram crossing above zero: bullish trend beginning
- Histogram crossing below zero: bearish trend beginning
- Histogram color: indicates momentum direction
- Consistent color intensity: trend strength
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Histogram approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing momentum
3. Momentum Analysis
- Histogram breaking above previous high boundary: accelerating bullish momentum
- Histogram breaking below previous low boundary: accelerating bearish momentum
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Distance from zero line: overall momentum magnitude
4. Market Structure Assessment
- Consecutive higher peaks: strengthening bullish structure
- Consecutive lower troughs: strengthening bearish structure
- Peak comparisons: relative strength of momentum phases
- Boundary line steps: market structure levels
Optimization Guide
1. MACD Settings
- Fast Length: Shorter values (8-12) for responsiveness, longer values (20+) for smoother signals
- Slow Length: Shorter values (21-34) for more signals, longer values (72+) for major moves
- Default settings (22, 72, 9): balanced approach for most timeframes
- Consider using 8, 21, 5 for shorter timeframes and 34, 144, 5 for longer timeframes
2. MA Type Selection
- EMA: More responsive, follows price more closely
- SMA: Smoother, fewer false signals, potentially more lag
- Mix and match for oscillator and signal lines based on your preference
3. Time Resolution
- Match chart timeframe: for aligned analysis
- Use higher timeframe: for filtering signals
- Lower timeframe: for earlier entries but more noise
4. Color Customization
- Normal bullish/bearish colors: represent standard momentum
- High/low marker line colors: customize visibility
- Peak marker colors: adjust for your visual preference
- Consider chart background when selecting colors
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm trend changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong momentum
- Use custom timeframe option for higher timeframe confirmation
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Custom resolution: allows comparison across timeframes
- Consider using multiple timeframes for confirmation
3. Market Context
- Strong bullish phase: positive histogram breaking above marker line
- Strong bearish phase: negative histogram breaking below marker line
- Histogram approaching zero: potential trend change
- Peak formations: potential exhaustion points
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with oscillators for overbought/oversold conditions
- Combine with volume analysis for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when histogram breaks above previous high marker line
- Enter short when histogram 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 bullish phases for shorting opportunities
- Look for consecutive higher troughs in bearish phases for buying opportunities
- Use zero-line crosses as confirmation
3. Multi-Timeframe Strategy
- Use custom resolution for higher timeframe MACD trend
- Enter trades when both timeframes align
- Higher timeframe for trend direction
- Chart timeframe for precise entry
4. Histogram Color Strategy
- Enter long when histogram turns bright green (increasing momentum)
- Enter short when histogram turns bright red (increasing momentum)
- Exit when color intensity fades (decreasing momentum)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Histogram crosses above zero line
- Green bars grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant momentum peaks
Bearish Market Scenario
- Histogram crosses below zero line
- Red bars grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant momentum troughs
Consolidation Scenario
- Histogram oscillates around zero line
- Bar colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Histogram values remain small
Understanding Market Dynamics Through MACD Boundary PSA
At its core, this indicator provides a unique lens to visualize market momentum and boundaries:
1. Momentum Strength: The histogram height/depth shows the strength of current momentum, with color intensity providing additional context about acceleration or deceleration.
2. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of momentum in both directions, helping to identify when markets are making new momentum extremes.
3. Exhaustion Signals: The peak detection system highlights moments where momentum has reached a local maximum or minimum, often precursors to reversals or consolidations.
4. Trend Confirmation: The histogram color and intensity provide instant feedback about the current trend direction and strength, with special colors highlighting particularly significant moves.
Remember:
- Combine signals from histogram, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences
- Consider 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.
STH Unrealized Profit/Loss Ratio (STH-NUPL) | [DeV]STH-NUPL
The Short-Term Holder Net Unrealized Profit/Loss Ratio (STH-NUPL) is an analytical tool designed to approximate the unrealized profit or loss of Bitcoin’s short-term holders (STHs)—typically those holding coins for less than 155 days—within the constraints of TradingView’s price-based environment. Drawing inspiration from the canonical STH-NUPL metric, which assesses the difference between the market value and realized value of STH-held coins, this indicator adapts the concept into a normalized ratio using Bitcoin’s price data as a proxy. It offers a window into the sentiment and behavior of short-term market participants, who are often more sensitive to price fluctuations than long-term holders.
In its raw form, STH-NUPL oscillates around a break-even threshold of 0, where positive values indicate aggregate unrealized profits for STHs (market value exceeds realized value), and negative values suggest losses. This inflection point frequently acts as a key level: in bear markets, it can signal capitulation as STHs sell at break-even or below, while in bull markets, it may reflect reluctance to realize losses, providing support. The indicator enhances this metric with smoothing, a moving average overlay, and sophisticated visualization options, delivering a statistically informed perspective on short-term holder dynamics tailored for institutional-grade analysis.
STH-NUPL Settings -
Lookback Length (Default: 150 days): Defines the SMA period for estimating realized value. This 150-day window aligns with traditional STH definitions (e.g., <155 days), capturing a broad yet relevant historical cost basis for short-term holders, ideal for assessing cyclical behavior.
Smoothing Period (Default: 5 days): Applies an EMA to the raw STH-NUPL ratio, with a short default period to maintain responsiveness to recent price shifts while filtering out daily volatility. This setting is particularly suited for tactical analysis.
Moving Average Settings -
MA Lookback Length (Default: 90 days): Sets the period for the STH-NUPL’s moving average, offering a medium-term trend signal that contrasts with the 150-day lookback, enabling detection of momentum shifts within broader market phases.
MA Type (Default: EMA): Provides six moving average types, from the straightforward SMA to the volume-sensitive VWMA. The default EMA balances smoothness and reactivity, while options like HMA or VWMA cater to specialized needs, such as emphasizing recent action or volume trends.
Display Settings -
Show Moving Average (Default: True): Toggles the visibility of the STH-NUPL MA plot, allowing users to focus solely on the smoothed ratio when desired.
Show Background Colors (Default: True): Activates dynamic background shading to visually reinforce market regimes.
Background Color Source (Default: STH-NUPL): Enables users to tie the background to either the STH-NUPL’s midline (reflecting sthNupl > 0) or the MA’s trend direction (maNupl > maNupl ), aligning the visual context with the chosen analytical focus.
Analytical Applications -
Bear Market Capitulation: When the smoothed STH-NUPL approaches or falls below zero, it often signals loss realization among STHs, a precursor to capitulation in downtrends. A declining MA crossing zero can confirm this selling pressure.
Bull Market Support: Positive STH-NUPL values with a rising MA indicate STHs are in profit and reluctant to sell at a loss, forming support zones in uptrends as sell pressure wanes.
Sentiment Extremes: Significant deviations above or below zero highlight over-optimism or despair among STHs, offering contrarian opportunities when paired with price action or other on-chain metrics.
**Limitations**
As a TradingView-based approximation, this indicator uses price data (close) rather than true on-chain STH supply and realized price, which are available through providers like Glassnode. The 150-day SMA for realized value simplifies the cost basis, potentially underrepresenting the diversity of STH transactions. Despite this, the smoothed ratio and moving average overlay provide a practical proxy for tracking STH sentiment within TradingView’s ecosystem.
ICT Breakers (BOS / MSS - Market Structure) [ICTProTools]The Breakers (Market Structure) indicator is designed to help traders identify true breaker structures , a key concept in Inner Circle Trader (ICT) methodology. In market structure, Breakers represent powerful shifts where a key high or low is broken, leading to a reversal in market direction. Most tools misinterpret structure shifts, using internal structure , leading to fake breakouts. This tool solves that problem by filtering out false signals , providing clear & structured insights , all with multi-timeframe compatibility.
💎 Key Features
⚡️ Breakers in action
The indicator shows the structure following ICT instructions. A breaker is defined by two lines:
The first line confirms the previous trend (it could be interpreted as a BOS).
The second line highlights the moment price breaks structure (with candle body or wick based on your chosen settings), signaling a shift in trend direction (like an MSS).
Furthermore, it’s important to note that a breaker not only shows the structure, but also defines a potential Point of Interest (POI), an area where price may retrace before continuing its trend.
Here, we can observe two clear structure shifts.
On the far left, the market was in a bearish trend, illustrated by the first visible (dotted and red) line. Shortly after, the second (solid and green) line appears, showing a break that initiates a new bullish trend.
This upward movement continues, with the last confirmation marked by a top structure line. And finally, the structure is broken once again indicating a transition back into a bearish trend.
💪 Real Structure with True Highs / Lows
Unlike many indicators that detect internal breakouts , this tool follows ICT’s true market structure rules .
In a bearish trend , a bullish breaker is only confirmed when the high that created the low is broken , and conversely for a bullish scenario.
Fake breakouts are ignored, preventing misleading signals.
In the image above, the white breakout is correctly ignored by the indicator, as it doesn't align with ICT’s structural rules. That white high is simply part of the internal structure, not the true swing point. Instead, the green line highlights the key level that truly matters, the one whose rupture would have confirmed a real change in market structure.
🔔 Smart Alerts for Structure Updates
Stay one step ahead with customizable alerts designed to notify you instantly when market structure changes occur.
Get notified for BOS (Continuation) and / or MSS (Breaker) events.
Set alerts for bullish , bearish , or both directions.
Choose between once or repeated alerts , based on your strategy.
This feature allows traders to remain focused and reactive , even when monitoring multiple markets.
In the alert settings, select which structure shifts you want to be notified of. Whether you're a scalper or a swing trader, the alerts keep you connected to key moments without needing to constantly monitor the chart.
⏳ Multi-Timeframe Structure
All features of the indicator are fully compatible with higher timeframes .
Get a broader view of market structure without switching timeframes.
Monitor higher timeframe structures and receive alerts, all without leaving your analysis chart .
In this example, the market structure of the 30m timeframe is displayed while on a 5m chart, providing a clearer perspective.
✨ Customization & User Control
Make it yours! The indicator allows full customization:
Swing bars (to confirm high / low)
Select your mode for Breakers (MSS) , using the candle body only or body / wick
Line style (type, width, color)
Choice of displayed timeframe
Activate any alert , with the frequency you want
🎯 Conclusion
✅ Avoid false signals by focusing on true ICT Breakers
✅ Smart alerts to never miss a structural shift
✅ Multi-timeframe support for enhanced analysis
✅ Clean & professional design for an optimal trading experience
Stop Loss / Take Profit Table// (\_/)
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📈 Introducing the Stop Loss / Take Profit Table Indicator! 📈
Enhance your trading strategy with our powerful Stop Loss / Take Profit Table indicator, designed for traders in the Crypto, Stock, and Forex markets. This easy-to-use tool helps you manage risk and maximize profits by clearly displaying your Stop Loss and Take Profit levels based on your trading position.
Key Features:
Custom Asset Types: Choose between Crypto, Stock, or Forex to tailor the indicator to your specific trading style.
Dynamic Stop Loss & Take Profit Calculation: Set your desired Stop Loss percentage, and the indicator will automatically calculate your Stop Loss and two Take Profit levels based on different timeframes (1 min to 240 min).
Position Type Flexibility: Whether you're trading Long or Short, the indicator adjusts the calculations accordingly, providing you with precise price levels for effective risk management.
Visual Representation: Stop Loss and Take Profit levels are marked directly on the chart with distinctive horizontal lines in vibrant colors for easy reference.
Informative Table Display: A dedicated table displayed on the chart shows your asset type, position type, and calculated prices for Stop Loss and Take Profit levels, ensuring you have all critical data at a glance.
Alert Notifications: Stay informed with optional alerts that signal when your Stop Loss or Take Profit levels are hit, allowing you to react swiftly in fast-moving markets.
Why Use This Indicator?
Managing your trades is critical for success in the financial markets. With our Stop Loss / Take Profit Table, you can easily set your parameters and visually track your risk and reward levels, making it a practical addition to any trader's toolkit.
Get started today and take control of your trading strategy! ✨
Happy trading! 📊🚀
RSI3M3+ v.1.8RSI3M3+ v.1.8 Indicator
This script is an advanced trading indicator based on Walter J. Bressert's cycle analysis methodology, combined with an RSI (Relative Strength Index) variation. Let me break it down and explain how it works.
Core Concepts
The RSI3M3+ indicator combines:
A short-term RSI (3-period)
A 3-period moving average to smooth the RSI
Bressert's cycle analysis principles to identify optimal trading points
RSI3M3+ Indicator VisualizationImage Walter J. Bressert's Cycle Analysis Concepts
Walter Bressert was a pioneer in cycle analysis trading who believed markets move in cyclical patterns that can be measured and predicted. His key principles integrated into this indicator include:
Trading Cycles: Markets move in cycles with measurable time spans from low to low
Timing Bands: Projected periods when the next cyclical low or high is anticipated
Oscillator Use: Using oscillators like RSI to confirm cycle position
Entry/Exit Rules: Specific rules for trade entry and exit based on cycle position
Key Parameters in the Script
Basic RSI Parameters
Required bars: Minimum number of bars needed (default: 20)
Overbought region: RSI level considered overbought (default: 70)
Oversold region: RSI level considered oversold (default: 30)
Bressert-Specific Parameters
Cycle Detection Length: Lookback period for cycle identification (default: 30)
Minimum/Maximum Cycle Length: Expected cycle duration in days (default: 15-30)
Buy Line: Lower threshold for buy signals (default: 40)
Sell Line: Upper threshold for sell signals (default: 60)
How the Indicator Works
RSI3M3 Calculation:
Calculates a 3-period RSI (sRSI)
Smooths it with a 3-period moving average (sMA)
Cycle Detection:
Identifies bottoms: When the RSI is below the buy line (40) and starting to turn up
Identifies tops: When the RSI is above the sell line (60) and starting to turn down
Records these points to calculate cycle lengths
Timing Bands:
Projects when the next cycle bottom or top should occur
Creates visual bands on the chart showing these expected time windows
Signal Generation:
Buy signals occur when the RSI turns up from below the oversold level (30)
Sell signals occur when the RSI turns down from above the overbought level (70)
Enhanced by Bressert's specific timing rules
Bressert's Five Trading Rules (Implemented in the Script)
Cycle Timing: The low must be 15-30 market days from the previous Trading Cycle bottom
Prior Top Validation: A Trading Cycle high must have occurred with the oscillator above 60
Oscillator Behavior: The oscillator must drop below 40 and turn up
Entry Trigger: Entry is triggered by a rise above the price high of the upturn day
Protective Stop: Place stop slightly below the Trading Cycle low (implemented as 99% of bottom price)
How to Use the Indicator
Reading the Chart
Main Plot Area:
Green line: 3-period RSI
Red line: 3-period moving average of the RSI
Horizontal bands: Oversold (30) and Overbought (70) regions
Dotted lines: Buy line (40) and Sell line (60)
Yellow vertical bands: Projected timing windows for next cycle bottom
Signals:
Green up arrows: Buy signals
Red down arrows: Sell signals
Trading Strategy
For Buy Signals:
Wait for the RSI to drop below the buy line (40)
Look for an upturn in the RSI from below this level
Enter the trade when price rises above the high of the upturn day
Place a protective stop at 99% of the Trading Cycle low
For Sell Signals:
Wait for the RSI to rise above the sell line (60)
Look for a downturn in the RSI from above this level
Consider exiting or taking profits when a sell signal appears
Alternative exit: When price moves below the low of the downturn day
Cycle Timing Enhancement:
Pay attention to the yellow timing bands
Signals occurring within these bands have higher probability of success
Signals outside these bands may be less reliable
Practical Tips for Using RSI3M3+
Timeframe Selection:
The indicator works best on daily charts for intermediate-term trading
Can be used on weekly charts for longer-term position trading
On intraday charts, adjust cycle lengths accordingly
Market Applicability:
Works well in trending markets with clear cyclical behavior
Less effective in choppy, non-trending markets
Consider additional indicators for trend confirmation
Parameter Adjustment:
Different markets may have different natural cycle lengths
You may need to adjust the min/max cycle length parameters
Higher volatility markets may need wider overbought/oversold levels
Trade Management:
Enter trades when all Bressert's conditions are met
Use the protective stop as defined (99% of cycle low)
Consider taking partial profits at the projected cycle high timing
Advanced Techniques
Multiple Timeframe Analysis:
Confirm signals with the same indicator on higher timeframes
Enter in the direction of the larger cycle when smaller and larger cycles align
Divergence Detection:
Look for price making new lows while RSI makes higher lows (bullish)
Look for price making new highs while RSI makes lower highs (bearish)
Confluence with Price Action:
Combine with support/resistance levels
Use with candlestick patterns for confirmation
Consider volume confirmation of cycle turns
This RSI3M3+ indicator combines the responsiveness of a short-term RSI with the predictive power of Bressert's cycle analysis, offering traders a sophisticated tool for identifying high-probability trading opportunities based on market cycles and momentum shifts.
THANK YOU FOR PREVIOUS CODER THAT EFFORT TO CREATE THE EARLIER VERSION THAT MAKE WALTER J BRESSERT CONCEPT IN TRADINGVIEW @ADutchTourist
Auto TrendLines [TradingFinder] Support Resistance Signal Alerts🔵 Introduction
The trendline is one of the most essential tools in technical analysis, widely used in financial markets such as Forex, cryptocurrency, and stocks. A trendline is a straight line that connects swing highs or swing lows and visually indicates the market’s trend direction.
Traders use trendlines to identify price structure, the strength of buyers and sellers, dynamic support and resistance zones, and optimal entry and exit points.
In technical analysis, trendlines are typically classified into three categories: uptrend lines (drawn by connecting higher lows), downtrend lines (formed by connecting lower highs), and sideways trends (moving horizontally). A valid trendline usually requires at least three confirmed touchpoints to be considered reliable for trading decisions.
Trendlines can serve as the foundation for a variety of trading strategies, such as the trendline bounce strategy, valid breakout setups, and confluence-based analysis with other tools like candlestick patterns, divergences, moving averages, and Fibonacci levels.
Additionally, trendlines are categorized into internal and external, and further into major and minor levels, each serving unique roles in market structure analysis.
🔵 How to Use
Trendlines are a key component in technical analysis, used to identify market direction, define dynamic support and resistance zones, highlight strategic entry and exit points, and manage risk. For a trendline to be reliable, it must be drawn based on structural principles—not by simply connecting two arbitrary points.
🟣 Selecting Pivot Types Based on Trend Direction
The first step is to determine the market trend: uptrend, downtrend, or sideways.
Then, choose pivot points that match the trend type :
In an uptrend, trendlines are drawn by connecting low pivots, especially higher lows.
In a downtrend, trendlines are formed by connecting high pivots, specifically lower highs.
It is crucial to connect pivots of the same type and structure to ensure the trendline is valid and analytically sound.
🟣 Pivot Classification
This indicator automatically classifies pivot points into two categories :
Major Pivots :
MLL : Major Lower Low
MHL : Major Higher Low
MHH : Major Higher High
MLH : Major Lower High
These define the primary structure of the market and are typically used in broader structural analysis.
Minor Pivots :
mLL: minor Lower Low
mHL: minor Higher Low
mHH: minor Higher High
mLH: minor Lower High
These are used for drawing more precise trendlines within corrective waves or internal price movements.
Example : In a downtrend, drawing a trendline from an MHH to an mHH creates structural inconsistency and introduces noise. Instead, connect points like MHL to MHL or mLH to mLH for a valid trendline.
🟣 Drawing High-Precision Trendlines
To ensure a reliable trendline :
Use pivots of the same classification (Major with Major or Minor with Minor).
Ensure at least three valid contact points (three touches = structural confirmation).
Draw through candles with the least deviation (choose wicks or bodies based on confluence).
Preferably draw from right to left for better alignment with current market behavior.
Use parallel lines to turn a single trendline into a trendline zone, if needed.
🟣 Using Trendlines for Trade Entries
Bounce Entry: When price approaches the trendline and shows signs of reversal (e.g., a reversal candle, divergence, or support/resistance), enter in the direction of the trend with a logical stop-loss.
Breakout Entry: When price breaks through the trendline with strong momentum and a confirmation (such as a retest or break of structure), consider trading in the direction of the breakout.
🟣 Trendline-Based Risk Management
For bounce entries, the stop-loss is placed below the trendline or the last pivot low (in an uptrend).
For breakout entries, the stop-loss is set behind the breakout candle or the last structural level.
A broken trendline can also act as an exit signal from a trade.
🟣 Combining Trendlines with Other Tools (Confluence)
Trendlines gain much more strength when used alongside other analytical tools :
Horizontal support and resistance levels
Moving averages (such as EMA 50 or EMA 200)
Fibonacci retracement zones
Candlestick patterns (e.g., Engulfing, Pin Bar)
RSI or MACD divergences
Market structure breaks (BoS / ChoCH)
🔵 Settings
Pivot Period : This defines how sensitive the pivot detection is. A higher number means the algorithm will identify more significant pivot points, resulting in longer-term trendlines.
Alerts
Alert :
Enable or disable the entire alert system
Set a custom alert name
Choose how often alerts trigger (every time, once per bar, or on bar close)
Select the time zone for alert timestamps (e.g., UTC)
Each trendline type supports two alert types :
Break Alert : Triggered when price breaks the trendline
React Alert : Triggered when price reacts or bounces off the trendline
These alerts can be independently enabled or disabled for all trendline categories (Major/Minor, Internal/External, Up/Down).
Display :
For each of the eight trendline types, you can control :
Whether to show or hide the line
Whether to delete the previous line when a new one is drawn
Color, line style (solid, dashed, dotted), extension direction (e.g., right only), and width
Major lines are typically thicker and more opaque, while minor lines appear thinner and more transparent.
All settings are designed to give the user full control over the appearance, behavior, and alert system of the indicator, without requiring manual drawing or adjustments.
🔵 Conclusion
A trendline is more than just a line on the chart—it is a structural, strategic, and flexible tool in technical analysis that can serve as the foundation for understanding price behavior and making trading decisions. Whether in trending markets or during corrections, trendlines help traders identify market direction, key zones, and high-potential entry and exit points with precision.
The accuracy and effectiveness of a trendline depend on using structurally valid pivot points and adhering to proper market logic, rather than relying on guesswork or personal bias.
This indicator is built to solve that exact problem. It automatically detects and draws multiple types of trendlines based on actual price structure, separating them into Major/Minor and Internal/External categories, and respecting professional analytical principles such as pivot type, trend direction, and structural location.
WMA and Intraday Highest Volume Candle Levels🔹 WMA Calculation (Weighted Moving Averages)
Custom WMA Function:
Uses a manual weighted average calculation.
Assigns more weight to recent prices for smoother trend detection.
Three Timeframes:
5-Minute WMA (Yellow)
15-Minute WMA (Blue)
30-Minute WMA (Red)
🔹 Intraday Highest Volume Candle Levels
Finds the candle with the highest volume for the selected intraday timeframe.
Stores its High & Low levels to act as support/resistance.
Deletes and redraws lines daily to reflect the latest session's highest volume candle.
Plots horizontal lines:
Green Line: High of the highest volume candle.
Red Line: Low of the highest volume candle.
Customization: User can choose the analysis timeframe (default: 3 minutes).
✅ Benefits of This Indicator
✔ Multi-timeframe trend analysis using WMA.
✔ Key intraday levels based on highest volume candle.
✔ Dynamic support & resistance levels based on real-time volume activity.
✔ Customizable timeframe for volume analysis.
Elliott Wave Identification By Akash Patel
This script is designed to visually highlight areas on the chart where there are consecutive bullish (green) or bearish (red) candles. It also identifies sequences of three consecutive candles of the same type (bullish or bearish) and highlights those areas with adjustable box opacity. Here's a breakdown of the functionality:
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### Key Features:
1. **Bullish & Bearish Candle Identification:**
- **Bullish Candle:** When the closing price is higher than the opening price (`close > open`).
- **Bearish Candle:** When the closing price is lower than the opening price (`close < open`).
2. **Consecutive Candle Counter:**
- The script counts consecutive bullish and bearish candles, which resets when the direction changes (from bullish to bearish or vice versa).
- The script tracks these counts using the `bullishCount` and `bearishCount` variables, which are incremented based on whether the current candle is bullish or bearish.
3. **Highlighting Candle Areas:**
- If there are **3 or more consecutive bullish candles**, the script will highlight the background in a green color with 90% transparency (adjustable).
- Similarly, if there are **3 or more consecutive bearish candles**, the script will highlight the background in a red color with 90% transparency (adjustable).
4. **Three-Candle Sequence:**
- The script checks if there are three consecutive bullish candles (`threeBullish`) or three consecutive bearish candles (`threeBearish`).
- A box is drawn around these areas to visually highlight the sequence. The boxes extend to the right edge of the chart, and their opacity can be adjusted.
5. **Box Creation:**
- For bullish sequences, a green box is created using the high and low prices of the three candles in the sequence.
- For bearish sequences, a red box is created in the same manner.
- The box size is determined by the highest high and the lowest low of the three consecutive candles.
6. **Box Opacity:**
- You can adjust the opacity of the boxes through the input parameters `Bullish Box Opacity` and `Bearish Box Opacity` (ranging from 0 to 100).
- A higher opacity will make the boxes more solid, while a lower opacity will make them more transparent.
7. **Box Cleanup:**
- The script also includes logic to remove boxes when they are no longer needed, ensuring the chart remains clean without excessive box overlays.
8. **Extending Boxes to the Right:**
- When a bullish or bearish sequence is identified, the boxes are extended to the right edge of the chart for continued visibility.
---
### How It Works:
- **Bullish Area Highlight:** When three or more consecutive bullish candles are detected, the background will turn green to indicate a strong bullish trend.
- **Bearish Area Highlight:** When three or more consecutive bearish candles are detected, the background will turn red to indicate a strong bearish trend.
- **Three Consecutive Candle Box:** A green box will appear around three consecutive bullish candles, and a red box will appear around three consecutive bearish candles. These boxes can be extended to the right edge of the chart, making the sequence visually clear.
---
### Adjustable Parameters:
1. **Bullish Box Opacity:** Set the opacity (transparency) level of the bullish boxes. Ranges from 0 (completely transparent) to 100 (completely opaque).
2. **Bearish Box Opacity:** Set the opacity (transparency) level of the bearish boxes. Ranges from 0 (completely transparent) to 100 (completely opaque).
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This indicator is useful for identifying strong trends and visually confirming market momentum, especially in situations where you want to spot sequences of bullish or bearish candles over multiple bars. It can be customized to suit different trading styles and chart preferences by adjusting the opacity of the boxes and background highlights.
Abhi's Bollinger Band Reversal SignalThis Pine Script indicator is designed to detect reversal trade opportunities using Bollinger Band breakouts. It identifies both buy and sell setups with clearly defined entry, stop-loss (SL), and target (TP) conditions. It also manages trades visually with real-time signal plotting, and limits entries per trading day.
⚙️ How It Works
🔽 Sell Signal Conditions
- The previous candle must close above the upper Bollinger Band, and its entire body must be above the band
- The current candle must fail to break the previous high, and must break below the previous low
- Entry is taken at the previous candle’s low, with SL at its high
- Target is calculated based on a configurable Risk:Reward ratio
🔼 Buy Signal Conditions
- The previous candle must close below the lower Bollinger Band, and its entire body must be below the band
- The current candle must fail to break the previous low, and must break above the previous high
- Entry is at the previous candle’s high, with SL at its low
- Target is calculated using the same Risk:Reward ratio
⏰ Time-Based Exit
- If a trade is still active by a user-defined exit time (e.g. 15:15), the trade is closed
- Labels are plotted to show whether this exit was a profit or loss
🧩 User Inputs
- Start Time for signals
- Exit Time for open trades
- Bollinger Band Settings: Period and Std Dev
- Max Entries Per Day
- Risk:Reward Ratio: Dropdown for 1:1, 1:1.5, ..., 1:3
🎨 Visual Features
✅ BUY and SELL signals are plotted when valid conditions are detected
🟢 TP and 🔴 SL labels show trade outcome
🕒 TIME EXIT labels appear at user-set exit time with green/red coloring based on profitability
📉 Bollinger Bands plotted for visual context
📌 Notes:
- Designed for intraday trading, resets entry counter daily
- Uses bar_index > tradeBarIndex to avoid SL/TP being triggered on the same candle as entry
- Tracks only one trade at a time (tradeActive) — ensures clear, non-overlapping logic
Correlation Coefficient TableThis Pine Script generates a dynamic table for analyzing how multiple assets correlate with a chosen benchmark (e.g., NZ50G). Users can input up to 12 asset symbols, customize the benchmark, and define the beta calculation periods (e.g., 15, 30, 90, 180 days). The script calculates Correlation values for each asset over these periods and computes the average beta for better insights.
The table includes:
Asset symbols: Displayed in the first row.
Correlation values: Calculated for each defined period and displayed in subsequent columns.
Average Correlation: Presented in the final column as an overall measure of correlation strength.
Color coding: Background colors indicate beta magnitude (green for high positive beta, yellow for near-neutral beta, red for negative beta).
Exchange PrefixAllows users to show the exchange name of your currently-viewed ticker on the latest bars.
For example, viewing BTCUSDT on BINANCE would provide "BINANCE".
Similarly, viewing BTCUSDT on CRYPTO.COM would provide "CRYPTOCOM".
What is the purpose of this?
- Sometimes pine script coders would like to know the exact names of the exchanges. This script does the job.
Cartera SuperTrends v4 PublicDescription
This script creates a screener with a list of ETFs ordered by their average ROC in three different periods representing 4, 6 and 8 months by default. The ETF
BIL
is always included as a reference.
The previous average ROC value shows the calculation using the closing price from last month.
The current average ROC value shows the calculation using the current price.
The previous average column background color represents if the ETF average ROC is positive or negative.
The current average column background color represents if the ETF average ROC is positive or negative.
The current average column letters color represents if the current ETF average ROC is improving or not from the previous month.
Changes from V2 to V3
Added the option to make the calculation monthly, weekly or daily
Changes from V3 to V4
Adding up to 25 symbols
Highlight the number of tickers selected
Highlight the sorted column
Complete refactor of the code using a matrix of arrays
Options
The options available are:
Make the calculation monthly, weekly or daily
Adjust Data for Dividends
Manual calculation instead of using ta.roc function
Sort table
Sort table by the previous average ROC or the current average ROC
Number of tickers selected to highlight
First Period in months, weeks or days
Second Period in months, weeks or days
Third Period in months, weeks or days
Select the assets (max 25)
Usage
Just add the indicator to your favorite indicators and then add it to your chart.
ML Deep Regression Pro (TechnoBlooms)ML Deep Regression Pro is a machine-learning-inspired trading indicator that integrates Polynomial Regression, Linear Regression and Statistical Deviation models to provide a powerful, data-driven approach to market trend analysis.
Designed for traders, quantitative analysts and developers, this tool transforms raw market data into predictive trend insights, allowing for better decision-making and trend validation.
By leveraging statistical regression techniques, ML Deep Regression Pro eliminates market noise and identifies key trend shifts, making it a valuable addition to both manual and algorithmic trading strategies.
REGRESSION ANALYSIS
Regression is a statistical modeling technique used in machine learning and data science to identify patterns and relationships between variables. In trading, it helps detect price trends, reversals and volatility changes by fitting price data into a predictive model.
1. Linear Regression -
The most widely used regression model in trading, providing a best-fit plotted line to track price trends.
2. Polynomial Regression -
A more advanced form of regression that fits curved price structures, capturing complex market cycles and improving trend forecasting accuracy.
3. Standard Deviation Bands -
Based on regression calculations, these bands measure price dispersion and identify overbought/ oversold conditions, similar to Bollinger Bands. By default, these lines are hidden and user can make it visible through Settings.
KEY FEATURES :-
✅ Hybrid Regression Engine – Combines Linear and Polynomial Regression to detect market trends with greater accuracy.
✅ Dynamic Trend Bias Analysis – Identifies bullish & bearish market conditions using real-time regression models.
✅ Standard Deviation Bands – Measures price volatility and potential reversals with an advanced deviation model.
✅ Adaptive EMA Crossover Signals – Generates buy/sell signals when price momentum shifts relative to the regression trend.
IU Smart Flow SystemDESCRIPTION
The IU Smart Flow System is a powerful and dynamic order flow-based strategy designed to capture high-probability trades by analyzing bullish and bearish imbalances, trend direction, and RSI strength. It identifies trading opportunities by aligning order flow conditions with the prevailing trend and momentum, making it suitable for trend-following and momentum-based trading.
This system utilizes a unique combination of:
- Order flow score to gauge market imbalance
- Trend filter using SMA and ATR to confirm market direction
- RSI to ensure entry only during strong momentum
USER INPUTS:
- Imbalance Length: Defines the lookback period for calculating bullish and bearish imbalances. (Default: 10)
- Trend Length: Determines the length of the SMA to evaluate the trend direction. (Default: 50)
- RSI Length: Specifies the RSI period to assess momentum strength. (Default: 14)
LONG CONDITIONS:
Long entries are triggered when:
- Order flow score is positive, indicating bullish imbalance
- Price is above the bullish trend level (SMA + ATR), confirming an uptrend
- RSI is above 50, indicating bullish momentum
- No active short position is currently open
SHORT CONDITIONS:
Short entries are triggered when:
- Order flow score is negative, indicating bearish imbalance
- Price is below the bearish trend level (SMA - ATR), confirming a downtrend
- RSI is below 50, indicating bearish momentum
- No active long position is currently open
WHY IT IS UNIQUE:
- Imbalance-Based Approach: Unlike traditional strategies that rely solely on price action, this system evaluates bullish and bearish imbalances to anticipate order flow direction.
- Adaptive Trend Filter: The combination of SMA and ATR dynamically adjusts to market volatility, providing a reliable trend confirmation mechanism.
- Momentum Validation with RSI: Ensures that entries are taken only in the direction of strong momentum, reducing false signals.
HOW USERS CAN BENEFIT FROM IT:
- Enhanced Trade Accuracy: Aligning order flow, trend, and momentum reduces false signals and improves trade success rates.
- Versatile Application: Suitable for various markets and timeframes, making it adaptable to different trading styles.
- Clear Trade Signals: Provides clear entry labels and alerts, ensuring traders never miss a potential opportunity.
- Visual Clarity: The filled region between bullish and bearish trends highlights trend direction, enhancing decision-making.
Nasdaq Risk Calculator - DTFXNasdaq Risk Calculator
This Pine Script (v5) indicator provides a dashboard-style tool for calculating trading risk based on manually input tick measurements for Nasdaq futures contracts (NQ and MNQ). Designed as an overlay on the main chart, it displays key risk metrics in a fixed-position table, allowing traders to assess contract type, lot size, risk ticks, and actual risk in dollars relative to a user-defined risk amount.
Features:
Manual Tick Input: Enter the number of ticks (e.g., from a ruler measurement) to define the price range for risk calculation.
Risk Calculation: Computes the optimal contract (NQ or MNQ), number of lots, risk ticks (half the input range), and actual risk in dollars, targeting the specified risk amount (default: $100).
Customizable Dashboard: Displays results in a single-cell table with a semi-transparent white background and gray border, positioned in one of four chart corners (Top Left, Top Right, Bottom Left, Bottom Right) via user selection.
Reset Option: Includes a toggle to clear the dashboard and start anew.
How to Use:
Add the indicator to your chart (best suited for NQ or MNQ futures).
In the settings, input your "Risk Amount ($)" and "Ticks" (e.g., 400 for a 100-point range on NQ).
Select the "Dashboard Corner" to position the table.
View the calculated risk details in the chosen corner.
Adjust inputs or reset as needed.
Notes:
NQ tick value is $5.00 (NQ_MULTIPLIER = 5.0), and MNQ tick value is $0.50 (MNQ_MULTIPLIER = 0.5).
Ideal for traders planning risk based on measured price ranges, such as support/resistance zones.
VCP Pattern with Pocket Pivots by Mark MinerviniBelow is a Pine Script designed to identify and plot Mark Minervini's Volatility Contraction Pattern (VCP) along with Pocket Pivots on TradingView. The VCP is characterized by a series of price contractions (tightening price ranges) with decreasing volume, often followed by a breakout. Pocket Pivots, a concept from Chris Kacher and Gil Morales, identify early buying opportunities within a consolidation or uptrend based on volume surges. This script combines both concepts to help traders spot potential setups.
DOPT---
## 🔍 **DOPT - Daily Open & Price Time Markers**
This script is designed to support directional bias development and price behavior analysis around key time-based reference points on the **1H and 4H timeframes**.
### ✨ **What It Does**
- **1800 Open Marker** (6 PM NY time): Plots the **daily open** from 1800 in **black dotted lines**.
- **0000 Open Marker** (Midnight NY time): Plots the **midnight open** in **blue dotted lines**.
- **Day Letters**: Each 1800 open is labeled with the corresponding **day of the week** (e.g., M, T, W...), helping visually segment your chart.
- **Hour Labels**: Select specific candles (e.g., 0000 = '0', 0800 = '8') to be labeled above the bar. These are fully customizable.
- **Candle Midpoints**: Option to mark the **50% level** of a specific candle (good for CE or CRT references).
- **CRT High/Low Tracking**: Ability to plot **extended high and low lines** from a selected candle back (e.g., for CRT modeling).
- **4H Timeframe Candle Numbering**: Helpful when analyzing sequences on the 4-hour timeframe. Candles are numbered `1`, `5`, and `9` for reference.
---
### 🧠 **How I Use It**
- I mostly use this on the **1-hour timeframe** to decide **directional bias** for the day:
- If price **closes above 1800 open**, I consider that a **green daily close** — potential bullish sentiment.
- If price **closes below**, I treat it as a **red daily close** — potential bearish behavior.
- Price often uses these opens as **support/resistance**, so I watch for reactions there.
- On the **4H**, the candle numbers help track structure and flow.
- Combine with CRT tools to mark **key candle highs/lows** and their **equilibrium (50%)** — great for refining entries or understanding how price is respecting a particular candle.
---
### ⚠️ **Note on Daylight Savings**
This is a **daylight saving time-dependent script**. When DST kicks in or out, you’ll need to **adjust the time inputs** accordingly to keep the opens accurate (e.g., 1800 might shift to 1700 depending on the season).
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### 🔁 **Backtesting & Reference**
- The **1800 and 0000 opens** are plotted for **as far back** as your chart loads, making it great for backtesting historical reactions.
- The CRT marking tools only go back **50 candles max**, so use that for recent structure only.
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Enhanced Fuzzy SMA Analyzer (Multi-Output Proxy) [FibonacciFlux]EFzSMA: Decode Trend Quality, Conviction & Risk Beyond Simple Averages
Stop Relying on Lagging Averages Alone. Gain a Multi-Dimensional Edge.
The Challenge: Simple Moving Averages (SMAs) tell you where the price was , but they fail to capture the true quality, conviction, and sustainability of a trend. Relying solely on price crossing an average often leads to chasing weak moves, getting caught in choppy markets, or missing critical signs of trend exhaustion. Advanced traders need a more sophisticated lens to navigate complex market dynamics.
The Solution: Enhanced Fuzzy SMA Analyzer (EFzSMA)
EFzSMA is engineered to address these limitations head-on. It moves beyond simple price-average comparisons by employing a sophisticated Fuzzy Inference System (FIS) that intelligently integrates multiple critical market factors:
Price deviation from the SMA ( adaptively normalized for market volatility)
Momentum (Rate of Change - ROC)
Market Sentiment/Overheat (Relative Strength Index - RSI)
Market Volatility Context (Average True Range - ATR, optional)
Volume Dynamics (Volume relative to its MA, optional)
Instead of just a line on a chart, EFzSMA delivers a multi-dimensional assessment designed to give you deeper insights and a quantifiable edge.
Why EFzSMA? Gain Deeper Market Insights
EFzSMA empowers you to make more informed decisions by providing insights that simple averages cannot:
Assess True Trend Quality, Not Just Location: Is the price above the SMA simply because of a temporary spike, or is it supported by strong momentum, confirming volume, and stable volatility? EFzSMA's core fuzzyTrendScore (-1 to +1) evaluates the health of the trend, helping you distinguish robust moves from noise.
Quantify Signal Conviction: How reliable is the current trend signal? The Conviction Proxy (0 to 1) measures the internal consistency among the different market factors analyzed by the FIS. High conviction suggests factors are aligned, boosting confidence in the trend signal. Low conviction warns of conflicting signals, uncertainty, or potential consolidation – acting as a powerful filter against chasing weak moves.
// Simplified Concept: Conviction reflects agreement vs. conflict among fuzzy inputs
bullStrength = strength_SB + strength_WB
bearStrength = strength_SBe + strength_WBe
dominantStrength = max(bullStrength, bearStrength)
conflictingStrength = min(bullStrength, bearStrength) + strength_N
convictionProxy := (dominantStrength - conflictingStrength) / (dominantStrength + conflictingStrength + 1e-10)
// Modifiers (Volatility/Volume) applied...
Anticipate Potential Reversals: Trends don't last forever. The Reversal Risk Proxy (0 to 1) synthesizes multiple warning signs – like extreme RSI readings, surging volatility, or diverging volume – into a single, actionable metric. High reversal risk flags conditions often associated with trend exhaustion, providing early warnings to protect profits or consider counter-trend opportunities.
Adapt to Changing Market Regimes: Markets shift between high and low volatility. EFzSMA's unique Adaptive Deviation Normalization adjusts how it perceives price deviations based on recent market behavior (percentile rank). This ensures more consistent analysis whether the market is quiet or chaotic.
// Core Idea: Normalize deviation by recent volatility (percentile)
diff_abs_percentile = ta.percentile_linear_interpolation(abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff := raw_diff / diff_abs_percentile
// Fuzzy sets for 'normalized_diff' are thus adaptive to volatility
Integrate Complexity, Output Clarity: EFzSMA distills complex, multi-factor analysis into clear, interpretable outputs, helping you cut through market noise and focus on what truly matters for your decision-making process.
Interpreting the Multi-Dimensional Output
The true power of EFzSMA lies in analyzing its outputs together:
A high Trend Score (+0.8) is significant, but its reliability is amplified by high Conviction (0.9) and low Reversal Risk (0.2) . This indicates a strong, well-supported trend.
Conversely, the same high Trend Score (+0.8) coupled with low Conviction (0.3) and high Reversal Risk (0.7) signals caution – the trend might look strong superficially, but internal factors suggest weakness or impending exhaustion.
Use these combined insights to:
Filter Entry Signals: Require minimum Trend Score and Conviction levels.
Manage Risk: Consider reducing exposure or tightening stops when Reversal Risk climbs significantly, especially if Conviction drops.
Time Exits: Use rising Reversal Risk and falling Conviction as potential signals to take profits.
Identify Regime Shifts: Monitor how the relationship between the outputs changes over time.
Core Technology (Briefly)
EFzSMA leverages a Mamdani-style Fuzzy Inference System. Crisp inputs (normalized deviation, ROC, RSI, ATR%, Vol Ratio) are mapped to linguistic fuzzy sets ("Low", "High", "Positive", etc.). A rules engine evaluates combinations (e.g., "IF Deviation is LargePositive AND Momentum is StrongPositive THEN Trend is StrongBullish"). Modifiers based on Volatility and Volume context adjust rule strengths. Finally, the system aggregates these and defuzzifies them into the Trend Score, Conviction Proxy, and Reversal Risk Proxy. The key is the system's ability to handle ambiguity and combine multiple, potentially conflicting factors in a nuanced way, much like human expert reasoning.
Customization
While designed with robust defaults, EFzSMA offers granular control:
Adjust SMA, ROC, RSI, ATR, Volume MA lengths.
Fine-tune Normalization parameters (lookback, percentile). Note: Fuzzy set definitions for deviation are tuned for the normalized range.
Configure Volatility and Volume thresholds for fuzzy sets. Tuning these is crucial for specific assets/timeframes.
Toggle visual elements (Proxies, BG Color, Risk Shapes, Volatility-based Transparency).
Recommended Use & Caveats
EFzSMA is a sophisticated analytical tool, not a standalone "buy/sell" signal generator.
Use it to complement your existing strategy and analysis.
Always validate signals with price action, market structure, and other confirming factors.
Thorough backtesting and forward testing are essential to understand its behavior and tune parameters for your specific instruments and timeframes.
Fuzzy logic parameters (membership functions, rules) are based on general heuristics and may require optimization for specific market niches.
Disclaimer
Trading involves substantial risk. EFzSMA is provided for informational and analytical purposes only and does not constitute financial advice. No guarantee of profit is made or implied. Past performance is not indicative of future results. Use rigorous risk management practices.
Fuzzy SMA with DCTI Confirmation[FibonacciFlux]FibonacciFlux: Advanced Fuzzy Logic System with Donchian Trend Confirmation
Institutional-grade trend analysis combining adaptive Fuzzy Logic with Donchian Channel Trend Intensity for superior signal quality
Conceptual Framework & Research Foundation
FibonacciFlux represents a significant advancement in quantitative technical analysis, merging two powerful analytical methodologies: normalized fuzzy logic systems and Donchian Channel Trend Intensity (DCTI). This sophisticated indicator addresses a fundamental challenge in market analysis – the inherent imprecision of trend identification in dynamic, multi-dimensional market environments.
While traditional indicators often produce simplistic binary signals, markets exist in states of continuous, graduated transition. FibonacciFlux embraces this complexity through its implementation of fuzzy set theory, enhanced by DCTI's structural trend confirmation capabilities. The result is an indicator that provides nuanced, probabilistic trend assessment with institutional-grade signal quality.
Core Technological Components
1. Advanced Fuzzy Logic System with Percentile Normalization
At the foundation of FibonacciFlux lies a comprehensive fuzzy logic system that transforms conventional technical metrics into degrees of membership in linguistic variables:
// Fuzzy triangular membership function with robust error handling
fuzzy_triangle(val, left, center, right) =>
if na(val)
0.0
float denominator1 = math.max(1e-10, center - left)
float denominator2 = math.max(1e-10, right - center)
math.max(0.0, math.min(left == center ? val <= center ? 1.0 : 0.0 : (val - left) / denominator1,
center == right ? val >= center ? 1.0 : 0.0 : (right - val) / denominator2))
The system employs percentile-based normalization for SMA deviation – a critical innovation that enables self-calibration across different assets and market regimes:
// Percentile-based normalization for adaptive calibration
raw_diff = price_src - sma_val
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff_raw = raw_diff / diff_abs_percentile
normalized_diff = useClamping ? math.max(-clampValue, math.min(clampValue, normalized_diff_raw)) : normalized_diff_raw
This normalization approach represents a significant advancement over fixed-threshold systems, allowing the indicator to automatically adapt to varying volatility environments and maintain consistent signal quality across diverse market conditions.
2. Donchian Channel Trend Intensity (DCTI) Integration
FibonacciFlux significantly enhances fuzzy logic analysis through the integration of Donchian Channel Trend Intensity (DCTI) – a sophisticated measure of trend strength based on the relationship between short-term and long-term price extremes:
// DCTI calculation for structural trend confirmation
f_dcti(src, majorPer, minorPer, sigPer) =>
H = ta.highest(high, majorPer) // Major period high
L = ta.lowest(low, majorPer) // Major period low
h = ta.highest(high, minorPer) // Minor period high
l = ta.lowest(low, minorPer) // Minor period low
float pdiv = not na(L) ? l - L : 0 // Positive divergence (low vs major low)
float ndiv = not na(H) ? H - h : 0 // Negative divergence (major high vs high)
float divisor = pdiv + ndiv
dctiValue = divisor == 0 ? 0 : 100 * ((pdiv - ndiv) / divisor) // Normalized to -100 to +100 range
sigValue = ta.ema(dctiValue, sigPer)
DCTI provides a complementary structural perspective on market trends by quantifying the relationship between short-term and long-term price extremes. This creates a multi-dimensional analysis framework that combines adaptive deviation measurement (fuzzy SMA) with channel-based trend intensity confirmation (DCTI).
Multi-Dimensional Fuzzy Input Variables
FibonacciFlux processes four distinct technical dimensions through its fuzzy system:
Normalized SMA Deviation: Measures price displacement relative to historical volatility context
Rate of Change (ROC): Captures price momentum over configurable timeframes
Relative Strength Index (RSI): Evaluates cyclical overbought/oversold conditions
Donchian Channel Trend Intensity (DCTI): Provides structural trend confirmation through channel analysis
Each dimension is processed through comprehensive fuzzy sets that transform crisp numerical values into linguistic variables:
// Normalized SMA Deviation - Self-calibrating to volatility regimes
ndiff_LP := fuzzy_triangle(normalized_diff, norm_scale * 0.3, norm_scale * 0.7, norm_scale * 1.1)
ndiff_SP := fuzzy_triangle(normalized_diff, norm_scale * 0.05, norm_scale * 0.25, norm_scale * 0.5)
ndiff_NZ := fuzzy_triangle(normalized_diff, -norm_scale * 0.1, 0.0, norm_scale * 0.1)
ndiff_SN := fuzzy_triangle(normalized_diff, -norm_scale * 0.5, -norm_scale * 0.25, -norm_scale * 0.05)
ndiff_LN := fuzzy_triangle(normalized_diff, -norm_scale * 1.1, -norm_scale * 0.7, -norm_scale * 0.3)
// DCTI - Structural trend measurement
dcti_SP := fuzzy_triangle(dcti_val, 60.0, 85.0, 101.0) // Strong Positive Trend (> ~85)
dcti_WP := fuzzy_triangle(dcti_val, 20.0, 45.0, 70.0) // Weak Positive Trend (~30-60)
dcti_Z := fuzzy_triangle(dcti_val, -30.0, 0.0, 30.0) // Near Zero / Trendless (~+/- 20)
dcti_WN := fuzzy_triangle(dcti_val, -70.0, -45.0, -20.0) // Weak Negative Trend (~-30 - -60)
dcti_SN := fuzzy_triangle(dcti_val, -101.0, -85.0, -60.0) // Strong Negative Trend (< ~-85)
Advanced Fuzzy Rule System with DCTI Confirmation
The core intelligence of FibonacciFlux lies in its sophisticated fuzzy rule system – a structured knowledge representation that encodes expert understanding of market dynamics:
// Base Trend Rules with DCTI Confirmation
cond1 = math.min(ndiff_LP, roc_HP, rsi_M)
strength_SB := math.max(strength_SB, cond1 * (dcti_SP > 0.5 ? 1.2 : dcti_Z > 0.1 ? 0.5 : 1.0))
// DCTI Override Rules - Structural trend confirmation with momentum alignment
cond14 = math.min(ndiff_NZ, roc_HP, dcti_SP)
strength_SB := math.max(strength_SB, cond14 * 0.5)
The rule system implements 15 distinct fuzzy rules that evaluate various market conditions including:
Established Trends: Strong deviations with confirming momentum and DCTI alignment
Emerging Trends: Early deviation patterns with initial momentum and DCTI confirmation
Weakening Trends: Divergent signals between deviation, momentum, and DCTI
Reversal Conditions: Counter-trend signals with DCTI confirmation
Neutral Consolidations: Minimal deviation with low momentum and neutral DCTI
A key innovation is the weighted influence of DCTI on rule activation. When strong DCTI readings align with other indicators, rule strength is amplified (up to 1.2x). Conversely, when DCTI contradicts other indicators, rule impact is reduced (as low as 0.5x). This creates a dynamic, self-adjusting system that prioritizes high-conviction signals.
Defuzzification & Signal Generation
The final step transforms fuzzy outputs into a precise trend score through center-of-gravity defuzzification:
// Defuzzification with precise floating-point handling
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10
fuzzyTrendScore := (strength_SB * STRONG_BULL + strength_WB * WEAK_BULL +
strength_N * NEUTRAL + strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1.0 (Strong Bear) to +1.0 (Strong Bull), with critical threshold zones at ±0.3 (Weak trend) and ±0.7 (Strong trend). The histogram visualization employs intuitive color-coding for immediate trend assessment.
Strategic Applications for Institutional Trading
FibonacciFlux provides substantial advantages for sophisticated trading operations:
Multi-Timeframe Signal Confirmation: Institutional-grade signal validation across multiple technical dimensions
Trend Strength Quantification: Precise measurement of trend conviction with noise filtration
Early Trend Identification: Detection of emerging trends before traditional indicators through fuzzy pattern recognition
Adaptive Market Regime Analysis: Self-calibrating analysis across varying volatility environments
Algorithmic Strategy Integration: Well-defined numerical output suitable for systematic trading frameworks
Risk Management Enhancement: Superior signal fidelity for risk exposure optimization
Customization Parameters
FibonacciFlux offers extensive customization to align with specific trading mandates and market conditions:
Fuzzy SMA Settings: Configure baseline trend identification parameters including SMA, ROC, and RSI lengths
Normalization Settings: Fine-tune the self-calibration mechanism with adjustable lookback period, percentile rank, and optional clamping
DCTI Parameters: Optimize trend structure confirmation with adjustable major/minor periods and signal smoothing
Visualization Controls: Customize display transparency for optimal chart integration
These parameters enable precise calibration for different asset classes, timeframes, and market regimes while maintaining the core analytical framework.
Implementation Notes
For optimal implementation, consider the following guidance:
Higher timeframes (4H+) benefit from increased normalization lookback (800+) for stability
Volatile assets may require adjusted clamping values (2.5-4.0) for optimal signal sensitivity
DCTI parameters should be aligned with chart timeframe (higher timeframes require increased major/minor periods)
The indicator performs exceptionally well as a trend filter for systematic trading strategies
Acknowledgments
FibonacciFlux builds upon the pioneering work of Donovan Wall in Donchian Channel Trend Intensity analysis. The normalization approach draws inspiration from percentile-based statistical techniques in quantitative finance. This indicator is shared for educational and analytical purposes under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Past performance does not guarantee future results. All trading involves risk. This indicator should be used as one component of a comprehensive analysis framework.
Shout out @DonovanWall
Fuzzy SMA Trend Analyzer (experimental)[FibonacciFlux]Fuzzy SMA Trend Analyzer (Normalized): Advanced Market Trend Detection Using Fuzzy Logic Theory
Elevate your technical analysis with institutional-grade fuzzy logic implementation
Research Genesis & Conceptual Framework
This indicator represents the culmination of extensive research into applying fuzzy logic theory to financial markets. While traditional technical indicators often produce binary outcomes, market conditions exist on a continuous spectrum. The Fuzzy SMA Trend Analyzer addresses this limitation by implementing a sophisticated fuzzy logic system that captures the nuanced, multi-dimensional nature of market trends.
Core Fuzzy Logic Principles
At the heart of this indicator lies fuzzy logic theory - a mathematical framework designed to handle imprecision and uncertainty:
// Improved fuzzy_triangle function with guard clauses for NA and invalid parameters.
fuzzy_triangle(val, left, center, right) =>
if na(val) or na(left) or na(center) or na(right) or left > center or center > right // Guard checks
0.0
else if left == center and center == right // Crisp set (single point)
val == center ? 1.0 : 0.0
else if left == center // Left-shoulder shape (ramp down from 1 at center to 0 at right)
val >= right ? 0.0 : val <= center ? 1.0 : (right - val) / (right - center)
else if center == right // Right-shoulder shape (ramp up from 0 at left to 1 at center)
val <= left ? 0.0 : val >= center ? 1.0 : (val - left) / (center - left)
else // Standard triangle
math.max(0.0, math.min((val - left) / (center - left), (right - val) / (right - center)))
This implementation of triangular membership functions enables the indicator to transform crisp numerical values into degrees of membership in linguistic variables like "Large Positive" or "Small Negative," creating a more nuanced representation of market conditions.
Dynamic Percentile Normalization
A critical innovation in this indicator is the implementation of percentile-based normalization for SMA deviation:
// ----- Deviation Scale Estimation using Percentile -----
// Calculate the percentile rank of the *absolute* deviation over the lookback period.
// This gives an estimate of the 'typical maximum' deviation magnitude recently.
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
// ----- Normalize the Raw Deviation -----
// Divide the raw deviation by the estimated 'typical max' magnitude.
normalized_diff = raw_diff / diff_abs_percentile
// ----- Clamp the Normalized Deviation -----
normalized_diff_clamped = math.max(-3.0, math.min(3.0, normalized_diff))
This percentile normalization approach creates a self-adapting system that automatically calibrates to different assets and market regimes. Rather than using fixed thresholds, the indicator dynamically adjusts based on recent volatility patterns, significantly enhancing signal quality across diverse market environments.
Multi-Factor Fuzzy Rule System
The indicator implements a comprehensive fuzzy rule system that evaluates multiple technical factors:
SMA Deviation (Normalized): Measures price displacement from the Simple Moving Average
Rate of Change (ROC): Captures price momentum over a specified period
Relative Strength Index (RSI): Assesses overbought/oversold conditions
These factors are processed through a sophisticated fuzzy inference system with linguistic variables:
// ----- 3.1 Fuzzy Sets for Normalized Deviation -----
diffN_LP := fuzzy_triangle(normalized_diff_clamped, 0.7, 1.5, 3.0) // Large Positive (around/above percentile)
diffN_SP := fuzzy_triangle(normalized_diff_clamped, 0.1, 0.5, 0.9) // Small Positive
diffN_NZ := fuzzy_triangle(normalized_diff_clamped, -0.2, 0.0, 0.2) // Near Zero
diffN_SN := fuzzy_triangle(normalized_diff_clamped, -0.9, -0.5, -0.1) // Small Negative
diffN_LN := fuzzy_triangle(normalized_diff_clamped, -3.0, -1.5, -0.7) // Large Negative (around/below percentile)
// ----- 3.2 Fuzzy Sets for ROC -----
roc_HN := fuzzy_triangle(roc_val, -8.0, -5.0, -2.0)
roc_WN := fuzzy_triangle(roc_val, -3.0, -1.0, -0.1)
roc_NZ := fuzzy_triangle(roc_val, -0.3, 0.0, 0.3)
roc_WP := fuzzy_triangle(roc_val, 0.1, 1.0, 3.0)
roc_HP := fuzzy_triangle(roc_val, 2.0, 5.0, 8.0)
// ----- 3.3 Fuzzy Sets for RSI -----
rsi_L := fuzzy_triangle(rsi_val, 0.0, 25.0, 40.0)
rsi_M := fuzzy_triangle(rsi_val, 35.0, 50.0, 65.0)
rsi_H := fuzzy_triangle(rsi_val, 60.0, 75.0, 100.0)
Advanced Fuzzy Inference Rules
The indicator employs a comprehensive set of fuzzy rules that encode expert knowledge about market behavior:
// --- Fuzzy Rules using Normalized Deviation (diffN_*) ---
cond1 = math.min(diffN_LP, roc_HP, math.max(rsi_M, rsi_H)) // Strong Bullish: Large pos dev, strong pos roc, rsi ok
strength_SB := math.max(strength_SB, cond1)
cond2 = math.min(diffN_SP, roc_WP, rsi_M) // Weak Bullish: Small pos dev, weak pos roc, rsi mid
strength_WB := math.max(strength_WB, cond2)
cond3 = math.min(diffN_SP, roc_NZ, rsi_H) // Weakening Bullish: Small pos dev, flat roc, rsi high
strength_N := math.max(strength_N, cond3 * 0.6) // More neutral
strength_WB := math.max(strength_WB, cond3 * 0.2) // Less weak bullish
This rule system evaluates multiple conditions simultaneously, weighting them by their degree of membership to produce a comprehensive trend assessment. The rules are designed to identify various market conditions including strong trends, weakening trends, potential reversals, and neutral consolidations.
Defuzzification Process
The final step transforms the fuzzy result back into a crisp numerical value representing the overall trend strength:
// --- Step 6: Defuzzification ---
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10 // Use small epsilon instead of != 0.0 for float comparison
fuzzyTrendScore := (strength_SB * STRONG_BULL +
strength_WB * WEAK_BULL +
strength_N * NEUTRAL +
strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1 (strong bearish) to +1 (strong bullish), providing a smooth, continuous evaluation of market conditions that avoids the abrupt signal changes common in traditional indicators.
Advanced Visualization with Rainbow Gradient
The indicator incorporates sophisticated visualization using a rainbow gradient coloring system:
// Normalize score to for gradient function
normalizedScore = na(fuzzyTrendScore) ? 0.5 : math.max(0.0, math.min(1.0, (fuzzyTrendScore + 1) / 2))
// Get the color based on gradient setting and normalized score
final_color = get_gradient(normalizedScore, gradient_type)
This color-coding system provides intuitive visual feedback, with color intensity reflecting trend strength and direction. The gradient can be customized between Red-to-Green or Red-to-Blue configurations based on user preference.
Practical Applications
The Fuzzy SMA Trend Analyzer excels in several key applications:
Trend Identification: Precisely identifies market trend direction and strength with nuanced gradation
Market Regime Detection: Distinguishes between trending markets and consolidation phases
Divergence Analysis: Highlights potential reversals when price action and fuzzy trend score diverge
Filter for Trading Systems: Provides high-quality trend filtering for other trading strategies
Risk Management: Offers early warning of potential trend weakening or reversal
Parameter Customization
The indicator offers extensive customization options:
SMA Length: Adjusts the baseline moving average period
ROC Length: Controls momentum sensitivity
RSI Length: Configures overbought/oversold sensitivity
Normalization Lookback: Determines the adaptive calculation window for percentile normalization
Percentile Rank: Sets the statistical threshold for deviation normalization
Gradient Type: Selects the preferred color scheme for visualization
These parameters enable fine-tuning to specific market conditions, trading styles, and timeframes.
Acknowledgments
The rainbow gradient visualization component draws inspiration from LuxAlgo's "Rainbow Adaptive RSI" (used under CC BY-NC-SA 4.0 license). This implementation of fuzzy logic in technical analysis builds upon Fermi estimation principles to overcome the inherent limitations of crisp binary indicators.
This indicator is shared under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Remember that past performance does not guarantee future results. Always conduct thorough testing before implementing any technical indicator in live trading.
Market Heat Z-ScoreThe "Market Heat Z-Score" indicator calculates the Z-score of a chosen price source over a specified lookback period, indicating how far the current price is from the mean in terms of standard deviations. It visually represents overbought and oversold conditions with a color gradient and customizable glow effect, with background shading indicating extreme Z-scores.
VSA Vol Key VSA Signals
(1) No Demand – Bearish Signal
Low volume, narrow spread.
Price rises, but volume does not increase → Weak market, lack of buyers.
If this appears in an uptrend, it may indicate a potential reversal.
(2) No Supply – Bullish Signal
Low volume, narrow spread.
Price declines, but volume does not increase → Weak selling pressure.
If this appears in an uptrend, it may confirm the continuation of the uptrend.
(3) Stopping Volume – Bullish Reversal Signal
Strong price decline, but unusually high volume.
Candle shows a long lower wick, closing near the top.
Indicates Smart Money absorbing supply, signaling a potential reversal upwards.
(4) Climactic Volume – Possible Trend Reversal
Extremely high volume with a sharp price increase or decrease.
If this occurs after a long trend, it may indicate a trend reversal.
Smart Money may be taking profits after a prolonged price movement.
(5) Effort vs. Result
If volume is high but price movement is weak → Inefficient buying/selling, possible reversal.
If volume is high and price moves strongly in the same direction → Trend is likely to continue.
