[iQ]PRO Dealing Range Cycle & Spectral Regression Histogram+🌟 PRO Dealing Range Cycle & Spectral Regression Histogram+ (DRC/SRH+)
Category: Advanced Market Cycle, Momentum, and Trend Analysis
The PRO Dealing Range Cycle & Spectral Regression Histogram+ is a meticulously engineered analytical tool, designed to provide our members with a superior, proprietary view of market structure, momentum, and mean reversion dynamics. This professional-grade indicator operates on a non-overlay panel, offering a clean and powerful interpretation layer distinct from the main price action.
🔬 Core Mechanism: Dual-Layered Analysis
This indicator combines two distinct, yet complementary, proprietary mathematical frameworks to deliver a holistic market picture:
The Dealing Range Cycle (DRC):
Utilizes a sophisticated, custom-displaced detrending oscillator built upon specialized percentage mathematics, rather than simple raw price differences.
The DRC identifies the latent cyclical forces within the price action, separating short-term noise from dominant swings.
It defines a "Dealing Range" through dynamically calculated High and Low Anchors, which represent the proprietary extremes of the current cycle. This framework provides invaluable context for understanding current price compression and expansion potentials.
The Quant Trend Signal is an integral component of the DRC, employing an adaptive logic to color-code the underlying direction of the core cyclical momentum, offering a robust directional confirmation.
The Spectral Regression Histogram (SRH+):
This component serves as the "Underpin Momentum" layer, a sensitive reading of current market velocity and pressure.
It employs a customized Spectral Regression Model to calculate deviations from an idealized price path. This is then passed through an advanced filtering and smoothing pipeline to extract high-frequency momentum components.
The SRH+ is visually presented as a Heatmap Histogram, dynamically color-graded to reflect the intensity of bullish (Gold/Yellow) or bearish (Bright Fuchsia) pressure. This gives users an immediate, spectral sense of the market's internal kinetic energy.
✨ Distinctive Features & Advantages
Proprietary Math Functions: The indicator relies on internalized custom mathematical functions (including specialized averages and high-precision linear regression) to generate unique, non-standard outputs that cannot be replicated with conventional indicators.
Decoupled Visualization: By operating on a separate panel, the DRC and SRH+ provide a noise-free environment for analysis, allowing for unambiguous interpretation of cyclical turning points and momentum shifts.
Intuitive Configuration: All core parameters, including Cycle Length, Regression Lookback, and Spectral Scale Factor, are meticulously organized into logical groups, allowing advanced users to fine-tune the engine without disrupting its proprietary internal logic.
The PRO DRC/SRH+ is not just an indicator; it is a diagnostic tool for the serious market participant, providing a powerful, proprietary lens to anticipate structural shifts and capitalize on the true rhythm of the market. Access is restricted to our most dedicated members, ensuring its edge remains sharp and exclusive.
Histogram
[iQ]PRO Quadratic Spectral Regression Channel and Heatmap+✨ PRO Quadratic Spectral Regression Channel and Heatmap+ : Next-Generation Market Analysis
The PRO QSRCH+ indicator is an advanced, proprietary analytical tool designed for the discerning trader, combining sophisticated statistical models with high-frequency momentum detection. This unique fusion provides a multi-dimensional view of market structure, separating the persistent, underlying trend from the volatile, short-term cycle.
📊 Precision Channeling with Weighted Regression
At its core, PRO QSRCH+ utilizes a dynamically weighted regression channel to establish the primary market trajectory and define statistically significant deviation boundaries.
Adaptive Trend Definition: The center line of the channel serves as a highly responsive mean value, calculated over a user-defined lookback length. This weighting prioritizes recent price action, ensuring the trend definition remains relevant to current market conditions.
Volatile Boundaries: The upper and lower bands are precisely calibrated using a standard deviation factor to measure volatility and establish zones of statistical overextension.
Trend Coloring: The channel's appearance changes based on the calculated slope, providing an instantaneous visual confirmation of the macro trend direction (Bullish or Bearish).
Exhaustion Signals: Subtle markers are placed when price touches these boundaries, signaling potential short-term market exhaustion and a high probability of mean reversion.
🔬 High-Resolution Spectral Momentum
Integrated with the regression channel is a specialized Spectral Momentum Heatmap Histogram. This proprietary oscillator is engineered to isolate the cyclical (micro) component of price movement.
Residual Analysis: The indicator first extracts the residual price movement—the high-frequency fluctuations that exist outside the established regression trend—effectively acting as an intelligent high-pass filter.
Cycle Detection: This residual data is then processed through a proprietary spectral filter and smoothing mechanism. This process isolates the dominant market cycle, revealing hidden bursts of momentum and the precise timing of cyclical turns.
Heatmap Visualization: The Spectral Momentum is visualized in a separate pane as a vibrant histogram, dynamically colored and weighted based on its magnitude to provide an intuitive visual gauge of market energy.
🧩 The Multi-Factor State Engine
PRO QSRCH+ uniquely combines these two components into a comprehensive market state engine, visible directly on the price bars and via clear trading signals:
Candle Coloring: Price bars are painted with a four-state system, distinguishing between:
Strong Trend: Macro Trend (Channel Slope) and Micro Cycle (Spectral Momentum) are aligned.
Pullback/Rally: Macro Trend is maintained, but the Micro Cycle is currently counter-trend, signaling temporary consolidation or retracement.
Validated Signals: High-probability BUY/SELL signals are generated only when the fast Spectral Momentum cycle crosses zero in alignment with the macro trend defined by the Regression Slope. This validation filter is key to minimizing false signals and maximizing the probability of sustained directional moves.
PRO QSRCH+ provides a superior framework for market structure analysis, allowing traders to distinguish between low-risk trend continuation and high-risk cyclical exhaustion.
Smart RSI Composite [DotGain]Summary
Do you want to know the "True Direction" of the market without getting distracted by noise on a single timeframe?
The Smart RSI Composite simplifies market analysis by aggregating momentum data from 10 different timeframes (5m to 12M) into a single, easy-to-read Histogram.
Instead of looking at 10 separate charts or dots, this indicator calculates the Average RSI of the entire market structure. It answers one simple question: "Is the market predominantly Bullish or Bearish right now?"
⚙️ Core Components and Logic
This indicator works like a consensus mechanism for momentum:
Data Aggregation: It pulls RSI values from 10 customizable slots (Default: 5m, 15m, 1h, 4h, 1D, 1W, 1M, 3M, 6M, 12M). All slots are enabled by default.
Smart Averaging: It calculates the arithmetic mean of all active timeframes. If the 5m chart is bearish but the Monthly chart is bullish, this indicator balances them out to show you the net result.
Histogram Visualization: The result is plotted as a histogram centered around the 50-line (Neutral).
🚦 How to Read the Histogram
The histogram bars indicate the aggregate strength of the trend based on the Average RSI:
🟩 DARK GREEN (Strong Bullish)
Condition: Average RSI > 60.
Meaning: The market is in a strong uptrend across most timeframes. Momentum is firmly on the buyers' side.
🟢 LIGHT GREEN (Weak Bullish)
Condition: Average RSI between 50 and 60.
Meaning: Slight bullish bias. The bulls are in control, but momentum is not yet extreme.
🔴 LIGHT RED (Weak Bearish)
Condition: Average RSI between 40 and 50.
Meaning: Slight bearish bias. The bears are taking control.
🟥 DARK RED (Strong Bearish)
Condition: Average RSI < 40.
Meaning: The market is in a strong downtrend across most timeframes. Momentum is firmly on the sellers' side.
Visual Elements
Center Line (50): This acts as the Zero-Line. Above 50 is bullish, below 50 is bearish.
Zone Lines (30/70): Dashed lines indicate the traditional Overbought/Oversold levels applied to the aggregate average.
Key Benefit
The Smart RSI Composite acts as a powerful Macro Trend Filter .
Pro Tip: Never go long if the Histogram is Dark Red, and avoid shorting when it is Dark Green. Use this tool to align your trades with the overall market momentum.
Have fun :)
Disclaimer
This "Smart RSI Composite" indicator is provided for informational and educational purposes only. It does not, and should not be construed as, financial, investment, or trading advice.
The signals generated by this tool (both "Buy" and "Sell" indications) are the result of a specific set of algorithmic conditions. They are not a direct recommendation to buy or sell any asset. All trading and investing in financial markets involves substantial risk of loss. You can lose all of your invested capital.
Past performance is not indicative of future results. The signals generated may produce false or losing trades. The creator (© DotGain) assumes no liability for any financial losses or damages you may incur as a result of using this indicator.
You are solely responsible for your own trading and investment decisions. Always conduct your own research (DYOR) and consider your personal risk tolerance before making any trades.
Transactional Rate of Change (TROC)TRANSACTIONAL RATE OF CHANGE (TROC) INDICATOR
Transaction Rate of Change (TROC) is an advanced momentum indicator that analyzes the rate of change in cumulative inferred buy/sell volume data to identify shifts in buying and selling acceleration and deceleration of transaction flow, providing early signals of potential trend changes, exhaustion/absorption, and momentum shifts. It builds further upon the official Volume Delta indicator released by TradingView.
If a stock price is a rocket climbing , then volume delta is the total fuel burned, and TROC is the fuel burn rate . A rocket can keep rising even after engines start throttling down (decelerating TROC), but it won't go much higher without more thrust. When TROC shows extreme positive readings, the engines are at maximum burn—expect explosive price movement. When TROC drops to zero while price is still high, the fuel is depleted and gravity (selling pressure) takes over. Are buyers pushing on the gas, or are they backing off? Are more buyers coming to the table, or are they losing interest or taking profits? Are excited retail buying highs while smart money close their positions using the excited retail liquidity?
KEY FEATURES
• Volume Delta Analysis - Approximates up and down volume from lower timeframe data to calculate true buying vs. selling pressure.
• Rate of Change Calculation - Measures the momentum of cumulative delta over a customizable period. Essentially, it displays the rate of change between buying and selling. How fast is it going, is it slowing, how excited are they?
• Momentum State Detection - Automatically identifies four distinct market states: accelerating up, decelerating up, accelerating down, and decelerating down
• Extreme Threshold Zones - Bands based on standard deviation to highlight unusually high or low transaction rates, helping to spot potential extreme values, blow offs, and capitulation.
• Z-Score Normalization - Optional standardization for comparing momentum across different timeframes and instruments.
• Momentum Strength Index (MSI) - Filters out weak signals by highlighting only bars with momentum exceeding a threshold.
• Flexible Reset Modes - Reset cumulative delta daily, weekly, monthly, or per session to prevent data drift, or leave it default for continual cumulative data.
APPLICATION
Trend Confirmation
When price makes a new high but TROC is decelerating (lighter colors), it suggests weakening buying pressure and potential exhaustion. Conversely, strong acceleration (darker colors) confirms robust trend continuation. Either buyers are supporting the move, or they aren't. Same goes for selling. It can also assist spotting short covering.
Divergence Trading
Use it similar to MACD divergence strategies. Is price movement confirmed by expansion in TROC, or is the TROC showing weakness while price is continuing it's trend?
Momentum Breakouts
When TROC crosses above the upper threshold zone with strong momentum (MSI activated), it signals institutional-level buying that often precedes significant price moves. Use this for breakout entries.
Mean Reversion
Extreme readings beyond the threshold zones often precede short-term reversals as transaction rates normalize. Consider taking profits or counter-trend positions when TROC reaches statistical extremes. Utilizing the extreme threshold bands can help you identify tops and bottoms.
Absorption Detection
Spot areas where buying or selling is being done, but price is hitting a wall or floor and not moving. This can indicate a hidden seller or a buyer reloading at price levels/zones.
SETTINGS
Timeframe for Volume Delta Calculation
Select the lower timeframe used to calculate buying and selling volume. Default: 1S (1 second)
• 1S or 5S - Maximum precision for scalping and intraday trading on liquid markets
• 1m or 5m - Balanced precision for swing trading and less liquid instruments
• Higher timeframes - Provide more historical data but reduce accuracy
Note: Higher frequency data yields more accurate delta calculations but may not be available for all symbols or historical periods. If you are using higher timeframes (Daily, Weekly) you will need to change this setting to a higher timeframe.
Rate of Change Period
Determines how many bars back to measure the momentum change. Default: 14
• Short periods (7-10) - More responsive, ideal for scalping and quick momentum shifts
• Medium periods (14-20) - Balanced sensitivity for day trading
• Long periods (25-50) - Smoother readings for swing trading and trend analysis
Shorter periods generate more signals but increase false positives; longer periods reduce noise but may lag significant changes.
Extreme Threshold Zones
Bands that highlight unusual transaction rate extremes based on standard deviation.
• Show Zones - Enable/disable the upper and lower threshold lines (Default: Enabled)
• Multiplier - Standard deviation multiplier for zone placement (Default: 2.0)
Values of 1.5-2.0 catch moderate extremes
Values of 2.5-3.0 identify only the most extreme readings
• Lookback Period - Number of bars used to calculate mean and standard deviation (Default: 100)
Shorter lookback (50-75) adapts faster to changing market conditions
Longer lookback (150-200) provides more stable, consistent zones
Smooth Cumulative Delta
Applies Adaptive Moving Average to reduce noise in the cumulative volume delta before calculating rate of change. Default: Enabled
• Smoothing Length - period (Default: 5)
Lower values (3-5) preserve responsiveness
Higher values (7-10) significantly reduce noise on choppy markets
Smoothing is particularly useful on volatile instruments or when using very short ROC periods.
Momentum Strength Index (MSI)
Filters the histogram to highlight only bars exceeding a specified momentum threshold, eliminating weak signals.
• Show MSI - Enable/disable momentum strength filtering (Default: Disabled)
• MSI Threshold - Minimum momentum strength multiplier (Default: 2.0)
Values of 1.5-2.0 show above-average momentum
Values of 2.5-3.5 isolate only exceptional momentum bars
When enabled, bars meeting the threshold display in the "Strong Up/Down" colors, while normal bars use standard momentum colors.
Display Settings
• Histogram Bar Width - Visual thickness of the columns (Default: 1, Range: 1-10)
• Use Z-Score Normalization - Standardizes TROC values for cross-asset comparison (Default: Disabled)
Enable when comparing multiple instruments or timeframes simultaneously
Z-Score converts values to standard deviations from the mean
• Z-Score Threshold - When using Z-Score Normalization mode, sets the extreme zone levels (Default: 2.0)
Represents standard deviations from mean (2.0 = ~95% confidence interval)
Cumulative Transaction Reset
Determines when the cumulative volume delta resets to zero, preventing infinite accumulation. Default: None
• None - Cumulative delta never resets (continues from symbol history start)
• Daily - Resets at the start of each new trading day
• Weekly - Resets at the start of each week
• Monthly - Resets at the start of each month
• On session change - Resets when market opens (useful for 24-hour markets)
Reset modes prevent cumulative drift that can distort ROC calculations over extended periods.
Color Customization Fully customizable color scheme.
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Note: This indicator requires volume data from your data vendor. It uses inferred buy/sell volume. To learn more, read the TradingView Volume Delta documentation. Optimal performance is achieved on liquid instruments with high-frequency data.
ADX Trend Color HistogramOverview:
This script provides a visually enhanced version of the classic Average Directional Index (ADX) indicator. Instead of a simple line, it plots the ADX as a histogram, making it easier to gauge trend strength at a glance. The key feature is its dynamic color-coding, which shifts based on the relationship between the Directional Indicators (DI+ and DI-), offering immediate insight into market momentum.
Features:
Histogram Style: The ADX value is presented as a histogram for clear, easy-to-read visualization of trend strength.
Dynamic Color-Coding: The histogram bars are colored green when DI+ is greater than DI-, indicating bullish momentum. They turn red when DI- is greater than DI+, signaling bearish momentum.
Customizable Transparency: The default color transparency is set to 80% (20% opacity) for a clean look that doesn't overpower the main chart, but this can be adjusted in the script's color settings.
Built-in Alerts: The script includes configurable alerts that trigger whenever the momentum shifts, i.e., when the color of the histogram changes from red to green or vice-versa. This allows you to stay notified of potential changes in trend direction without constantly watching the chart.
Clean and Simple: The code is well-structured and commented for clarity, making it easy for other PineScripters to understand or modify.
How to Use:
Assess Trend Strength: The height of the histogram bars represents the strength of the current trend. Higher bars suggest a stronger trend (either bullish or bearish), while lower bars indicate a weak or non-trending market.
Identify Momentum Direction: The color of the bars provides a quick guide to the direction of market momentum.
Green Bars: Indicate that the upward momentum is dominant.
Red Bars: Indicate that the downward momentum is dominant.
Use Alerts for Signals: Set up alerts in TradingView based on the "ADX Green" and "ADX Red" conditions to receive notifications for potential entry or exit signals when the momentum shifts. A change from red to green can signal a potential bullish reversal or continuation, while a change from green to red can signal a bearish one.
Volume Surprise [LuxAlgo]The Volume Surprise tool displays the trading volume alongside the expected volume at that time, allowing users to spot unexpected trading activity on the chart easily.
The tool includes an extrapolation of the estimated volume for future periods, allowing forecasting future trading activity.
🔶 USAGE
We define Volume Surprise as a situation where the actual trading volume deviates significantly from its expected value at a given time.
Being able to determine if trading activity is higher or lower than expected allows us to precisely gauge the interest of market participants in specific trends.
A histogram constructed from the difference between the volume and expected volume is provided to easily highlight the difference between the two and may be used as a standalone.
The tool can also help quantify the impact of specific market events, such as news about an instrument. For example, an important announcement leading to volume below expectations might be a sign of market participants underestimating the impact of the announcement.
Like in the example above, it is possible to observe cases where the volume significantly differs from the expected one, which might be interpreted as an anomaly leading to a correction.
🔹 Detecting Rare Trading Activity
Expected volume is defined as the mean (or median if we want to limit the impact of outliers) of the volume grouped at a specific point in time. This value depends on grouping volume based on periods, which can be user-defined.
However, it is possible to adjust the indicator to overestimate/underestimate expected volume, allowing for highlighting excessively high or low volume at specific times.
In order to do this, select "Percentiles" as the summary method, and change the percentiles value to a value that is close to 100 (overestimate expected volume) or to 0 (underestimate expected volume).
In the example above, we are only interested in detecting volume that is excessively high, we use the 95th percentile to do so, effectively highlighting when volume is higher than 95% of the volumes recorded at that time.
🔶 DETAILS
🔹 Choosing the Right Periods
Our expected volume value depends on grouping volume based on periods, which can be user-defined.
For example, if only the hourly period is selected, volumes are grouped by their respective hours. As such, to get the expected volume for the hour 7 PM, we collect and group the historical volumes that occurred at 7 PM and average them to get our expected value at that time.
Users are not limited to selecting a single period, and can group volume using a combination of all the available periods.
Do note that when on lower timeframes, only having higher periods will lead to less precise expected values. Enabling periods that are too low might prevent grouping. Finally, enabling a lot of periods will, on the other hand, lead to a lot of groups, preventing the ability to get effective expected values.
In order to avoid changing periods by navigating across multiple timeframes, an "Auto Selection" setting is provided.
🔹 Group Length
The length setting allows controlling the maximum size of a volume group. Using higher lengths will provide an expected value on more historical data, further highlighting recurring patterns.
🔹 Recommended Assets
Obtaining the expected volume for a specific period (time of the day, day of the week, quarter, etc) is most effective when on assets showing higher signs of periodicity in their trading activity.
This is visible on stocks, futures, and forex pairs, which tend to have a defined, recognizable interval with usually higher trading activity.
Assets such as cryptocurrencies will usually not have a clearly defined periodic trading activity, which lowers the validity of forecasts produced by the tool, as well as any conclusions originating from the volume to expected volume comparisons.
🔶 SETTINGS
Length: Maximum number of records in a volume group for a specific period. Older values are discarded.
Smooth: Period of a SMA used to smooth volume. The smoothing affects the expected value.
🔹 Periods
Auto Selection: Automatically choose a practical combination of periods based on the chart timeframe.
Custom periods can be used if disabling "Auto Selection". Available periods include:
- Minutes
- Hours
- Days (can be: Day of Week, Day of Month, Day of Year)
- Months
- Quarters
🔹 Summary
Method: Method used to obtain the expected value. Options include Mean (default) or Percentile.
Percentile: Percentile number used if "Method" is set to "Percentile". A value of 50 will effectively use a median for the expected value.
🔹 Forecast
Forecast Window: Number of bars ahead for which the expected volume is predicted.
Style: Style settings of the forecast.
Fundur - Market Sentiment BIndicator Overview
The Market Sentiment B indicator is a sophisticated multi-timeframe momentum oscillator that provides comprehensive market analysis through advanced wave theory and sentiment measurement. Unlike traditional single-timeframe indicators, Market Sentiment B analyzes 11 different timeframes simultaneously to create a unified view of market momentum and sentiment.
What Makes Market Sentiment B Unique
Multi-Timeframe Convergence : The indicator combines data from 11 different periods (8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987) based on mathematical sequences that naturally occur in market cycles.
Advanced Wave Analysis : The histogram component tracks momentum waves with precise peak and trough identification, allowing traders to spot both major moves and smaller precursor waves.
Sentiment Extremes Detection : When all 11 timeframes reach extreme levels simultaneously, the indicator highlights these rare conditions with background coloring, signaling potential major reversals.
Dynamic Zone Analysis : The indicator divides market conditions into Premium (80+), Discount (20-), and Liquidity zones (40-60), providing clear context for trade entries and exits.
Core Components
1. Market Sentiment B Line (Main Signal)
The primary oscillator line that represents the averaged sentiment across all timeframes. This line uses advanced mathematical filtering to smooth out noise while preserving important trend changes.
Key Features:
Oscillates between 0-100
Color-coded: Green when rising, Red when falling
Shows divergences with colored dots
Premium zone: 80+, Discount zone: 20-
2. Momentum Waves (Secondary Signal)
A smoothed version of the Market Sentiment B line that acts as a trend-following component. This line helps identify the underlying momentum direction.
Key Features:
Blue coloring during bullish expansion (above 50 and rising)
Orange coloring during bearish expansion (below 50 and falling)
Filled areas show expansion and contraction phases
Critical 50-line crossovers signal momentum shifts
3. Histogram (Wave Analysis)
The difference between Market Sentiment B and Momentum Waves, displayed as a histogram that reveals the relationship between current sentiment and underlying momentum.
Key Features:
Green bars: Positive momentum (Market Sentiment above Momentum Waves)
Red bars: Negative momentum (Market Sentiment below Momentum Waves)
Wave height labels show the strength of each wave
Divergence patterns identify potential reversals
4. Divergence System
Advanced divergence detection that identifies both regular and hidden divergences, with special "Golden Divergences" for the strongest signals.
Types:
Regular Divergences : Price makes new highs/lows while indicator doesn't
Hidden Divergences : Continuation patterns in trending markets
Golden Divergences : High-probability reversal signals (orange dots)
5. Zone Analysis
The indicator divides market conditions into distinct zones:
Premium Zone (80-100) : Potential selling area
Liquidity Zone (40-60) : Neutral/consolidation area (highlighted in orange)
Discount Zone (0-20) : Potential buying area
Extreme Conditions : Background coloring when all timeframes align
Setup Guide
Initial Installation
Open TradingView and navigate to your desired chart
Click the "Indicators" button or press "/" key
Search for "Fundur - Market Sentiment B"
Click on the indicator to add it to your chart
The indicator will appear in a separate pane below your chart
Essential Settings Configuration
Main Settings
Show Histogram Wave Values : Enable to see wave strength numbers
Wave Value Text Size : Choose from tiny, small, normal, or large
Wave Label Offset : Adjust label positioning (default: 2)
Market Sentiment Thresholds
Only Show Indicators at Market Sentiment Extremes : Filter signals to extreme zones only
Extreme levels are automatically set at 80 (high) and 20 (low)
Small Wave Strategy
Enable Small Wave Swing Strategy : Focus on smaller, early-warning waves
Small Wave Label Color : Customize the color for small wave labels
Divergence Analysis
Show Regular Divergences : Enable standard divergence detection
Show Gold Divergence Dots : Enable high-probability golden signals
Show Divergence Dots : Show all divergence markers
Histogram Settings
Enable Histogram : Toggle the histogram display
Divergence Types : Choose which types to display (Bullish/Bearish Reversals and Continuations)
Recommended Initial Setup
Enable all main components (Histogram, Divergences, Momentum Waves)
Set wave value text size to "small" for clarity
Enable golden divergence dots for premium signals
Start with all alert categories enabled, then customize based on your trading style
Basic Trading Guide
Understanding the Zones
Premium Zone Trading (80-100)
When to Consider Selling:
Market Sentiment B enters 80+ zone
Bearish divergences appear
Histogram shows weakening momentum (smaller green waves)
Background turns red (extreme conditions)
What to Look For:
Bearish pivot signals (orange triangles pointing down)
Golden divergence dots at tops
Momentum Waves turning bearish
Discount Zone Trading (0-20)
When to Consider Buying:
Market Sentiment B enters 0-20 zone
Bullish divergences appear
Histogram shows strengthening momentum (smaller red waves)
Background turns green (extreme conditions)
What to Look For:
Bullish pivot signals (blue triangles pointing up)
Golden divergence dots at bottoms
Momentum Waves turning bullish
Liquidity Zone Trading (40-60)
Consolidation and Breakout Zone:
Orange-filled area indicates neutral sentiment
Wait for clear breaks above 60 or below 40
Use for range-bound trading strategies
Look for momentum wave direction changes
Key Signal Types
1. Zone Crossovers
Above 60 : Bullish momentum building
Below 40 : Bearish momentum building
50-line crosses : Primary trend changes
2. Divergence Signals
Golden dots : Strongest reversal signals that align accross different timeframes
Colored dots : Standard divergence warnings
Hidden divergences : Trend continuation signals
3. Histogram Patterns
Increasing green bars : Building bullish momentum
Increasing red bars : Building bearish momentum
Smaller waves : Early warning signals of deteriorating interest
Basic Entry Rules
Long Entries
Market Sentiment B in discount zone (0-20) OR
Bullish divergence confirmed OR
Break above 40 from oversold conditions OR
Golden divergence dot at bottom
Short Entries
Market Sentiment B in premium zone (80-100) OR
Bearish divergence confirmed OR
Break below 60 from overbought conditions OR
Golden divergence dot at top
Exit Rules
Exit longs when entering premium zone
Exit shorts when entering discount zone
Close positions on opposite divergence signals
Use histogram wave tops/bottoms for fine-tuning exits
Advanced Analysis Setups
Setup 1: Scalping Configuration
Purpose : Quick intraday trades focusing on small moves
Settings :
Enable Small Wave Strategy
Show indicators only at extremes: OFF
Combine multiple alerts: ON
Focus on 1-5 minute timeframes
Signals to Watch :
Small wave histogram peaks/troughs
Quick zone crossovers (40/60 line breaks)
Momentum wave direction changes
Short-term divergences
Setup 2: Swing Trading Configuration
Purpose : Medium-term trend following and reversal trading
Settings :
Show indicators only at extremes: ON
Enable all divergence types
Focus on 15-minute to 4-hour timeframes
Golden divergence alerts: HIGH priority
Signals to Watch :
Premium/discount zone entries
Golden divergence signals
Extreme condition backgrounds
Major histogram wave formations
Setup 3: Position Trading Configuration
Purpose : Long-term trend identification and major reversal spots
Settings :
Only alert in extremes: ON
Focus on golden divergences only
Use daily and weekly timeframes
Minimize noise with extreme filtering
Signals to Watch :
Extreme condition backgrounds (red/green)
Major golden divergence signals
Long-term momentum wave trends
Weekly/monthly zone transitions
Setup 4: Reversal Hunting Configuration
Purpose : Catching major market turns at key levels
Settings :
Enable all divergence types
Show golden divergence dots: ON
Extreme filtering: ON
Small wave strategy: OFF
Signals to Watch :
Multiple divergence confirmations
Golden divergence + extreme zones
All-timeframe extreme conditions
Major histogram wave exhaustion
Setup 5: Trend Following Configuration
Purpose : Riding momentum in established trends
Settings :
Momentum waves: HIGH priority
Hidden divergences: ON
Continuation patterns focus
Zone crossover alerts
Signals to Watch :
Momentum wave expansion phases
Hidden divergence continuations
Liquidity zone breakouts
Sustained momentum patterns
Alert System
The Market Sentiment B indicator features a comprehensive alert system with over 30 different alert types organized into logical categories.
Alert Categories
Market Sentiment B Line Alerts
Golden Divergences : Highest priority reversal signals
Standard Divergences : Regular divergence patterns
Bearish/Bullish Pivots : Momentum pivot points
Premium/Discount Zone : Zone entry/exit alerts
Extreme Conditions : Rare all-timeframe extremes
Liquidity Zone : 40-60 zone movement alerts
Momentum Waves Alerts
Premium/Discount Zones : 80+/20- level alerts
Liquidity Zone Movement : 40-60 zone alerts
Expansion Phases : Bullish/bearish expansion alerts
Direction Changes : 50-line crossover alerts
Cross Alerts : MSB vs Momentum crossovers
Histogram Alerts
State Changes : Bullish/bearish turns
Peak/Trough Detection : Wave top/bottom alerts
Divergence Alerts : Histogram-specific divergences
Hidden Divergences : Continuation pattern alerts
Smaller Wave Alerts : Early warning signals
Alert Configuration Tips
For Day Trading
Enable quick state change alerts
Focus on histogram and small wave alerts
Use combined alerts to reduce noise
Disable extreme-only filtering
For Swing Trading
Enable zone crossover alerts
Focus on divergence and pivot alerts
Use extreme-only filtering
Prioritize golden divergence alerts
For Position Trading
Enable only golden divergences and extreme conditions
Use extreme-only filtering
Focus on major zone transitions
Disable minor wave alerts
Trading Strategies
Strategy 1: Premium/Discount Zone Reversal
Setup : Wait for Market Sentiment B to reach extreme zones
Entry :
Long: Enter discount zone (0-20) with bullish divergence
Short: Enter premium zone (80-100) with bearish divergence
Exit : Opposite zone reached or momentum wave reversal
Risk Management : Stop loss at recent swing high/low
Strategy 2: Golden Divergence Power Plays
Setup : Wait for golden divergence dots to appear
Entry : Enter in direction opposite to divergence (reversal play)
Confirmation : Wait for momentum wave to confirm direction
Exit : When sentiment reaches opposite zone
Risk Management : Tight stops below/above divergent pivot
Strategy 3: Momentum Wave Trend Following
Setup : Identify strong momentum wave expansion phases
Entry : Enter on pullbacks to 50-line during expansion
Continuation : Hold while expansion phase continues
Exit : When expansion phase ends or opposite expansion begins
Risk Management : Trail stops using wave peaks/troughs
Strategy 4: Small Wave Early Entry
Setup : Enable Small Wave Strategy for early signals
Entry : Enter on small wave formations before major moves
Confirmation : Wait for main sentiment line to follow
Exit : When major wave forms or opposite signal appears
Risk Management : Quick exits if main indicator doesn't confirm
Strategy 5: Extreme Condition Contrarian
Setup : Wait for background color changes (extreme conditions)
Entry : Counter-trend when ALL timeframes are extreme
Confirmation : Look for early divergence signs
Exit : When background color disappears
Risk Management : Position size smaller due to counter-trend nature
FAQ & Troubleshooting
Frequently Asked Questions
Q: Why don't I see any signals on my chart?
A: Check if "Only Show Indicators at Market Sentiment Extremes" is enabled. If so, signals only appear when the indicator is above 80 or below 20.
Q: What's the difference between golden and standard divergences?
A: Golden divergences (orange dots) are higher-probability signals that meet additional criteria for strength and momentum alignment. Standard divergences are regular price/indicator disagreements.
Q: How do I reduce alert noise?
A: Enable "Only Alert In Extremes" in the alert settings, or use "Combine Multiple Alerts" to consolidate multiple signals into single messages.
Q: What timeframe works best with this indicator?
A: The indicator works on all timeframes. For day trading, use 1-15 minutes. For swing trading, use 1-4 hours. For position trading, use daily or weekly.
Q: Why are the histogram wave values important?
A: Wave values show the strength of momentum. Declining wave values (smaller peaks) often precede trend changes, while increasing values confirm trend strength.
Troubleshooting Common Issues
Issue: Indicator not loading
Solution: Ensure you're using TradingView Pro or higher
Check that max_bars_back is set appropriately
Refresh the chart and re-add the indicator
Issue: Too many alerts firing
Solution: Enable extreme-only filtering
Disable less important alert categories
Use combined alerts feature
Issue: Missing divergence signals
Solution: Check that divergence detection is enabled
Ensure you're looking in the correct zones
Verify that extreme filtering isn't hiding signals
Issue: Histogram not displaying
Solution: Check that "Enable Histogram" is turned ON
Verify histogram divergence types are enabled
Ensure the chart has sufficient historical data
Best Practices
Start Simple : Begin with basic zone trading before using advanced features
Paper Trade First : Test strategies with paper trading before risking capital
Combine with Price Action : Use the indicator alongside support/resistance levels
Respect Risk Management : Never risk more than you can afford to lose
Keep Learning : Market conditions change; adapt your usage accordingly
Performance Optimization
Use appropriate timeframes for your trading style
Enable only necessary alert types
Consider using extreme filtering during high-volatility periods
Regularly review and adjust settings based on market conditions
Conclusion
The Market Sentiment B indicator represents a sophisticated approach to market analysis, combining multiple timeframes, advanced wave theory, and comprehensive divergence detection into a single powerful tool. Whether you're a scalper looking for quick opportunities or a position trader seeking major reversals, this indicator provides the insights needed to make informed trading decisions.
Remember that no indicator is perfect, and the Market Sentiment B should be used as part of a comprehensive trading plan that includes proper risk management, fundamental analysis awareness, and sound money management principles.
Happy Trading!
Disclaimer: Trading involves substantial risk and is not suitable for all investors. Past performance is not indicative of future results. Always practice proper risk management and never trade with money you cannot afford to lose.
Risk Distribution HistogramStatistical risk visualization and analysis tool for any ticker 📊
The Risk Distribution Histogram visualizes the statistical distribution of different risk metrics for any financial instrument. It converts risk data into histograms with quartile-based color coding, so that traders can understand their risk, tail-risks, exposure patterns and make data-driven decisions based on empirical evidence rather than assumptions.
The indicator supports multiple risk calculation methods, each designed for different aspects of market analysis, from general volatility assessment to tail risk analysis.
Risk Measurement Methods
Standard Deviation
Captures raw daily price volatility by measuring the dispersion of price movements. Ideal for understanding overall market conditions and timing volatility-based strategies.
Use case: Options trading and volatility analysis.
Average True Range (ATR)
Measures true range as a percentage of price, accounting for gaps and limit moves. Valuable for position sizing across different price levels.
Use case: Position sizing and stop-loss placement.
The chart above illustrates how ATR statistical distribution can be used by looking at the ATR % of price distribution. For example, 90% of the movements are below 5%.
Downside Deviation
Only considers negative price movements, making it ideal for checking downside risk and capital protection rather than capturing upside volatility.
Use case: Downside protection strategies and stop losses.
Drawdown Analysis
Tracks peak-to-trough declines, providing insight into maximum loss potential during different market conditions.
Use case: Risk management and capital preservation.
The chart above illustrates tale risk for the asset (TQQQ), showing that it is possible to have drawdowns higher than 20%.
Entropy-Based Risk (EVaR)
Uses information theory to quantify market uncertainty. Higher entropy values indicate more unpredictable price action, valuable for detecting regime changes.
Use case: Advanced risk modeling and tail-risk.
VIX Histogram
Incorporates the market's fear index directly into analysis, showing how current volatility expectations compare to historical patterns. The CAPITALCOM:VIX histogram is independent from the ticker on the chart.
Use case: Volatility trading and market timing.
Visual Features
The histogram uses quartile-based color coding that immediately shows where current risk levels stand relative to historical patterns:
Green (Q1): Low Risk (0-25th percentile)
Yellow (Q2): Medium-Low Risk (25-50th percentile)
Orange (Q3): Medium-High Risk (50-75th percentile)
Red (Q4): High Risk (75-100th percentile)
The data table provides detailed statistics, including:
Count Distribution: Historical observations in each bin
PMF: Percentage probability for each risk level
CDF: Cumulative probability up to each level
Current Risk Marker: Shows your current position in the distribution
Trading Applications
When current risk falls into upper quartiles (Q3 or Q4), it signals conditions are riskier than 50-75% of historical observations. This guides position sizing and portfolio adjustments.
Key applications:
Position sizing based on empirical risk distributions
Monitoring risk regime changes over time
Comparing risk patterns across timeframes
Risk distribution analysis improves trade timing by identifying when market conditions favor specific strategies.
Enter positions during low-risk periods (Q1)
Reduce exposure in high-risk periods (Q4)
Use percentile rankings for dynamic stop-loss placement
Time volatility strategies using distribution patterns
Detect regime shifts through distribution changes
Compare current conditions to historical benchmarks
Identify outlier events in tail regions
Validate quantitative models with empirical data
Configuration Options
Data Collection
Lookback Period: Control amount of historical data analyzed
Date Range Filtering: Focus on specific market periods
Sample Size Validation: Automatic reliability warnings
Histogram Customization
Bin Count: 10-50 bins for different detail levels
Auto/Manual Bin Width: Optimize for your data range
Visual Preferences: Custom colors and font sizes
Implementation Guide
Start with Standard Deviation on daily charts for the most intuitive introduction to distribution-based risk analysis.
Method Selection: Begin with Standard Deviation
Setup: Use daily charts with 20-30 bins
Interpretation: Focus on quartile transitions as signals
Monitoring: Track distribution changes for regime detection
The tool provides comprehensive statistics including mean, standard deviation, quartiles, and current position metrics like Z-score and percentile ranking.
Enjoy, and please let me know your feedback! 😊🥂
Advanced MACD Pro (WhiteStone_Ibrahim) - T3 Themed✨ Advanced MACD Pro (WhiteStone_Ibrahim) - T3 Themed ✨
Take your MACD analysis to the next level with the Advanced MACD Pro - T3 Themed indicator by WhiteStone_Ibrahim! This isn't just another MACD; it's a comprehensive toolkit packed with advanced features, unique T3 integration, and extensive customization options to provide deeper market insights.
Whether you're a seasoned trader or just starting, this indicator offers a versatile and powerful way to analyze momentum, identify trends, and spot potential reversals.
Key Features:
Core MACD Functionality:
Classic MACD Line: Calculated from customizable Fast and Slow EMAs using your chosen source (Close, Open, HLC3, etc.).
Standard Signal Line: EMA of the MACD line, with adjustable length.
Dynamic MACD Line Coloring: Automatically changes color based on whether it's above or below the zero line (positive/negative).
Zero Line: Clearly plotted for reference.
Enhanced MACD Histogram:
Sophisticated Color Coding: The histogram isn't just positive or negative. It intelligently colors based on momentum strength and direction:
Strong Bullish: MACD above signal, histogram increasing.
Weakening Bullish: MACD above signal, histogram decreasing.
Strong Bearish: MACD below signal, histogram decreasing.
Weakening Bearish: MACD below signal, histogram increasing.
Neutral: Default color for other conditions.
Optional Histogram Smoothing: Smooth out the histogram noise using one of five different moving average types: SMA, EMA, WMA, RMA, or the advanced T3 (Tilson T3). Customize smoothing length and T3 vFactor.
🌟 Unique T3 Integration (T3 Themed):
Extra T3 Signal Line (on MACD): An additional, fast-reacting T3 moving average calculated directly from the MACD line. This provides an alternative and often quicker signal.
Customizable T3 length and vFactor.
Dynamic Coloring: The T3 Signal Line changes color (bullish/bearish) based on its crossover with the MACD line, offering clear visual cues.
T3 is also available as a smoothing option for the main histogram (see above).
🔍 Disagreement & Divergence Detection:
Bar/Price Disagreement Markers:
Highlights instances where the price bar's direction (e.g., a bullish candle) contradicts the current MACD momentum (e.g., MACD below its signal line).
Visual markers (circles) appear above/below bars to draw attention to these potential early warnings or confirmations.
Histogram Color Change on Disagreement: Optionally, the histogram can adopt distinct alternative colors during these bar/price disagreements for even clearer visual alerts.
Classic Bullish & Bearish Divergence Detection:
Automatically identifies regular divergences between price action (Higher Highs/Lower Lows) and the MACD line (Lower Highs/Higher Lows).
Customizable pivot lookback periods (left and right bars) for divergence sensitivity.
Plots clear "Bull" and "Bear" labels on the price chart where divergences occur.
🎨 Extensive Customization & Visuals:
Multiple Color Themes: Choose from pre-set themes like 'Dark Mode', 'Light Mode', 'Neon Night', or use 'Default (Current Settings)' to fine-tune every color yourself.
Granular Control (Default Theme): Individually customize colors and thickness for:
MACD Line (positive/negative)
Standard Signal Line
Extra T3 Signal Line (bullish/bearish)
Histogram (all four momentum states + neutral)
Disagreement Markers & Histogram Alt Colors
Divergence Lines/Labels
Zero Line
Toggle Visibility: Easily show or hide the Standard Signal Line and the Extra T3 Signal Line as needed.
🔔 Comprehensive Alert System:
Stay informed of key market events with a wide array of configurable alerts:
MACD Line / Standard Signal Line Crossover
Histogram / Zero Line Crossover
MACD Line / Zero Line Crossover
Bullish Divergence Detected
Bearish Divergence Detected
Bar/Price Disagreement (Bullish & Bearish)
MACD Line / Extra T3 Signal Line Crossover
Each alert can be individually enabled or disabled.
The Advanced MACD Pro - T3 Themed indicator is designed to be your go-to tool for momentum analysis. Its rich feature set empowers you to tailor it to your specific trading style and gain a more nuanced understanding of market dynamics.
Add it to your charts today and experience the difference!
(Developed by WhiteStone_Ibrahim)
Volumetric Tensegrity🧮 Volumetric Tensegrity unifies two of the Leading Indicator suite's critical engines — ZVOL ( volume anomaly detection ) and OBVX ( directional conviction ). Originally designed as a structural economizer for traders navigating strict indicator limits (e.g. < 10 slots per chart), it was forced to evolve beyond that constraint simply to fulfill it, albeit with a difference. The fatal flaw of traditional fusion, where two metrics are blended mathematically, is that they lose scale integrity (i.e. meaning). VTense encodes optical tensegrity to scale the amplitude of the ZVOL histogram and the slope of the OBVX spread independently, so that expansion and direction may coexist without either dominating the frame.
🧬 Tensegrity , by definition, is an intelligent design principle where elements in compression are suspended within a network of continuous tension, forming a stable, self-supporting structure . Originally conceived in esoteric biomorphology (c.f. Da Vinci, Snelson, Casteneda), tensegrity balances force through opposition, not rigidity. Applied to financial markets, Volumetric Tensegrity captures this same principle: price compresses, volume expands, conviction builds or fades — yet structure holds through the interplay. The result is not a prediction engine, but a pressure field — one that visualizes where structure might bend, break, or rebound based on how volume breathes.
🗜️ Rather than layering multiple indicators and consuming precious chart space, VTense frees up room for complementary overlays like momentum mapping, liquidity tiers, or volatility phase detection — making it ideal for modular traders operating in tight technical real estate.
🧠 Core Logic - VTense separates and preserves two essential structural forces:
• ZVOL Histogram : A Z-score-based expansion map that measures current volume deviation from its historical average. It reveals buildup zones, dormant stretches, and breakout pressure — regardless of price behavior.
• OBVX Spread : A directional conviction curve that tracks the difference between On-Balance Volume and its volume-weighted fast trend. It shows whether the crowd is leaning in (accumulation/distribution) or backing off.
🔊 ZVOL controls the amplitude of the histogram, while OBVX controls the curvature and slope of the spread. Without sacrificing breathing behavior or analytical depth, VTense provides a compact yet dynamic lens to track both expansion pressure and directional bias within a single footprint.
🌊 Volumetric Tensegrity forecasts breakout readiness, trend fatigue, and compression zones by measuring the volatility within volume . Unlike traditional tools that track volatility of price, this indicator reveals when effort becomes unstable — signaling inflection points before price reacts. Designed to decode rhythm shifts at the volume level, it operates as a pre-ignition scanner that thrives on low-timeframe charts (15m and under) while scaling effectively to 1H for validation.
🪖 From Generals to Scouts
👀 When used jointly, ZVOL + OBVX act as the general : deep-field analysts confirming stress, commitment, or exhaustion. VTense , by contrast, functions as a scout — capturing subtle buildup and alignment before structure fully reveals itself. The indicator aims to be a literal vanguard, establishing a position that can be confirmed or flexibly abandoned when the higher authority arrives to evaluate.
🥂 Use the ZVOL + OBVX pair when :
• You need independent axis control and manual dissection
• You’re building long-form confluence setups
• You have more indicator slots than you need
🔎 Use VTense when :
• You need compact clarity across multiple instruments
• You’re prioritizing confluence _detection_ over granular separation
• You’re building efficient multi-layered systems under slot constraints
🏗️ Structural Behavior and Interpretation
🫁 Z VOL Respiration Histogram : Structural Effort vs Baseline
🔵 Compression Coil – volume volatility is low and stable; the market is coiling
🟢 Steady Rhythm – volume is healthy but unremarkable; balanced participation
🟡 Passive/Absorbed Effort – expansion failing to manifest; watch for reversal
🟠 Clean Expansion – actionable volatility rise backed by structure
🔴 Volatile Blowout – chaos, climax; likely end-phase or fakeout
⚖️ ZVOL Respiration measures how hard the crowd is pressing — not just that volume is rising, but how statistically abnormal the surge is. Because it is rescaled proportionally to OBVX, the amplitude of the histogram reflects structural urgency without overwhelming the visual field.
🖐️ OBVX Spread : Real-Time Directional Conviction Behind Price Moves
🔑 The curvature of the spread reveals not just directional bias but crowd temp o: sharp slopes = urgent transitions; gradual slopes = building structural shifts. Curvature is key: sharp OBVX slope = urgency; gentle arcs = controlled drift or indecision.
• Green Rising : Accumulation — upward pressure from real buyers
• Red Falling : Distribution — sell pressure, downward slope
• Flat Curves : Transitional → uncertainty, microstructure digestion
🎭 Synchronized vs Divergent Behavior
⏱️ Synchronized (high-confluence) : often precedes structural breakouts, with internal conviction clearly visible before price resolves.
• ZVOL expands (yellow/orange/red) and OBVX climbs steeply green = strong bullish pressure
• ZVOL expands while OBVX steepens red = growing sell-side intent
🪤 Divergent (conflict tension) : flags potential traps, fakeouts, and liquidity sweeps.
• ZVOL expands sharply, but OBVX flattens or opposes → reactive expansion without crowd commitment
⛔️ Latent Drift + Structural Holding Patterns : tensegrity in action — the market holds tension without directional release.
• ZVOL compresses (blue) + OBVX meanders near zero → structure is resting, building up energy
• After prolonged drift, expect violent asymmetry when balance finally breaks
📚 Phase Interpretation: Dynamic Structural Read
• 1️⃣ Quiet Coil : Histogram flat, OBVX flat → no urgency
• 2️⃣ Initial Pulse : Yellow bars, OBVX slope builds → actionable tension
• 3️⃣ Structural Breath : Synchronized expansion and slope → directional commitment
• 4️⃣ Disagreement : Spike in ZVOL, flattening OBVX → exhaustion risk or false signal
💡 Suggested Use
• Run on 15m charts for breakout anticipation and 1H for validation
• Pair with ZVOL + OBVX to confirm crowd conviction behind the tension phase
• Use as a rhythm filter for the suite's trend indicators (e.g., RDI , SUPeR TReND 2.718 , et. al.)
• Ideal during low-volume regimes to detect pressure buildup before triggers
🧏🏻 Volumetric Tensegrity doesn’t signal. It breathes , and listens to pressure shifts before they speak in price. As a scout, it lets you see structural posture before signals align — helping you front-run resolution with clarity, not prediction.
QuantumSync Pulse [ w.aritas ]QuantumSync Pulse (QSP) is an advanced technical indicator crafted for traders seeking a dynamic and adaptable tool to analyze diverse market conditions. By integrating momentum, mean reversion, and regime detection with quantum-inspired calculations and entropy analysis, QSP offers a powerful histogram that reflects trend strength and market uncertainty. With multi-timeframe synchronization, adaptive filtering, and customizable visualization, it’s a versatile addition to any trading strategy.
Key Features
Hybrid Signals: Combines momentum and mean reversion, dynamically weighted by market regime.
Quantum Tunneling: Enhances responsiveness in volatile markets using volatility-adjusted calculations.
3-State Entropy: Assesses market uncertainty across up, down, and neutral states.
Regime Detection: Adapts signal weights with Hurst exponent and volatility ROC.
Multi-Timeframe Alignment: Syncs with higher timeframe trends for context.
Customizable Histogram: Displays trend strength with ADX-based visuals and flexible styling.
How to Use and Interpret
Histogram Interpretation
Positive (Above Zero): Bullish momentum; color intensity shows trend strength.
Negative (Below Zero): Bearish momentum; gradients indicate weakness.
Overlaps: Alignment of final_z (signal) and ohlc4 (price) histograms highlights key price levels or turning points.
Regime Visualization
Green Background: Trending market; prioritize momentum signals.
Red Background: Mean-reverting market; focus on reversion signals.
Blue Background: Neutral state; balance both signal types.
Trading Signals
Buy: Histogram crosses above zero or shows positive divergence between histograms.
Sell: Histogram crosses below zero or exhibits negative divergence.
Confirmation: Match signals with regime background—green for trends, red for ranges.
Customization
Tweak Momentum Length, Entropy Lookback, and Hurst Exponent Lookback for sensitivity.
Adjust color themes and transparency to suit your charts.
Tips for Optimal Use
Timeframes: Use higher timeframes (1h, 4h) for trend context and lower (5m, 15m) for entries.
Pairing: Combine with RSI, MACD, or volume indicators for confirmation.
Backtesting: Test settings on historical data for asset-specific optimization.
Overlaps: Watch for histogram overlaps to identify support, resistance, or reversals.
Simulated Performance
Trending Markets: Histogram stays above/below zero, with overlaps at retracements for entries.
Range-Bound Markets: Oscillates around zero; overlaps signal reversals in red regimes.
Volatile Markets: Quantum tunneling ensures quick reactions, with filters reducing noise.
Elevate your trading with QuantumSync Pulse—a sophisticated tool that adapts to the market’s rhythm and your unique style.
Supply & Demand Histogram and Lines [BerlinCode42]Happy Trade,
This is a Supply & Demand Histogram—also referred to as a Heatmap—that highlights key S&D levels on the chart. Unlike traditional approaches that use volume, this script identifies specific chart patterns and evaluates them to generate the Supply & Demand Histogram. It analyzes the Supply and the Demand separately.
The script is equipped with trade signals for external use (Indicator on Indicator) and is fully compatible with my strategy template script. This allows you to easily create backtests and combine it with other indicators to build a custom strategy.
Intro
Calculation of the Supply & Demand Histogram
Usage and Settings Menu
Declaration for Tradingview House Rules on Script Publishing
Disclaimer
1. Calculation of the Supply & Demand Histogram
Initially, the total price range—spanning from the absolute minimum to the absolute maximum observed price—is discretized into 10,000 equally sized intervals. For each interval, the algorithm performs the following:
It detects chart patterns that typically emerge in zones of varying volatility, categorizing them accordingly. Each identified pattern is assigned a individual weight based on its structural parameters, such as amplitude or slope. Lets call them Structural Weights. These weighted occurrences are then aggregated per interval, resulting in a quantitative representation of supply and demand pressure across the price spectrum, visualized as a histogram.
This pattern-based methodology facilitates the quantitative estimation of supply and demand zones without reliance on volume metrics.
2. Usage and Settings Menu
Initially, the user can configure the granularity of the price segmentation used in the Supply & Demand Histogram. This is achieved by enabling the 'Show Price Range' option, as illustrated in Image 1. Activating this feature overlays a gray-shaded region on the chart, visually representing the defined price range.
Image 1
The vertical position of this range can be adjusted using the 'Price Range Offset' parameter, while the interval widths are modifiable via the 'Step Factor' setting. It is critical to ensure that the specified range encapsulates the entirety of historical and anticipated price movements; failure to do so may result in calculation errors if price action extends beyond the defined bounds. Nevertheless, the default Step Factor has been conservatively chosen to accommodate most price dynamics.
Due to performance considerations, the indicator does not render all 10,000 discrete intervals comprising the full histogram. Instead, it selectively displays a subset of 100 intervals centered around the most recent price."
Once the price range has been configured, disable the “Show Price Range” option again in order to display the Supply & Demand Histogram.
Subsequently, users can fine-tune the histogram computation via two key settings, shown in Image 2:
Volume Count – This option allows selection between a pattern-based structural weighting method and a traditional volume-based approach for histogram construction. The structural method estimates significance through pattern characteristics rather than traded volume.
Supply + Demand – This toggle determines whether Supply and Demand levels are calculated and displayed independently or merged into a unified histogram. If one subscribes to the principle that a breached Supply zone can transform into a Demand zone (and vice versa), enabling this option will reflect that assumption by aggregating both into a single composite structure.
Image 2
Once this setup is complete, the Supply & Demand Histogram along with its most significant price levels will be visualized on the chart. Users can further refine the display settings to tailor the visual output.
In the settings menu, refer to the section illustrated in Image 3. There, you can adjust the number of displayed price levels by increasing or decreasing the S&D Line Filter percentage. A lower percentage results in fewer, more prominent levels being shown, while a higher percentage includes more levels.
The S&D histogram itself can also be hidden if desired.
Image 3
This indicator supports external integration via Indicator on Indicator Functionality or alerts. Specifically, when a price level is either touched or broken, an alert can be triggered. To visually identify where such alerts would occur, enable Show Alert Labels, which marks the respective bars on the chart.
If you want to import the trade signals into a Backtest or Strategy Template script, simply use the two signal outputs: "Break Signals" and "Touch Signals".
A value of zero indicates that no touching or breaking event is occurring.
A positive value signifies that a supply level has been touched or broken.
A negative value indicates a demand level interaction.
The absolute value of each signal corresponds to the price level of the respective Supply or Demand line.
The colors used to represent Supply and Demand levels can be customized to your preference.
Additionally, a Time and Session Filter has been added. This feature allows you to exclude specific time periods and dates from the analysis, enabling a better understanding of which trading times and market sessions are responsible for the formation of particular Supply & Demand levels.
To activate the filter, check the leftmost checkbox, then define the desired Date, Time, and Session parameters accordingly as shown in image 4.
Image 4
3. Declaration for Tradingview House Rules on Script Publishing
The unique feature of this Supply & Demand Histogram is its pattern-based calculation methodology. This approach enables the estimation of Supply and Demand levels even for assets that do not provide volume data. Additionally, it allows for separate computation of Supply and Demand. That means a broken Demand level does not necessarily convert into a Supply level, and vice versa.
This script is closed-source and invite-only to support and compensate for months long development work.
4. Disclaimer
Trading is risky, and traders do lose money, eventually all. This script is for informational and educational purposes only. All content should be considered hypothetical, selected post-factum and is not to be construed as financial advice. Decisions to buy, sell, hold, or trade in securities, commodities, and other investments involve risk and are best made based on the advice of qualified financial professionals. Past performance does not guarantee future results. Using this script on your own risk. This script may have bugs and I declare don't be responsible for any losses.
Now it’s your turn!
ZVOL — Z-Score Volume Heatmapⓩ ZVOL transforms raw volume into a statistically calibrated heatmap using Z-score thresholds. Unlike classic volume indicators that rely on fixed MA comparisons, ZVOL calculates how many standard deviations each volume bar deviates from its mean. This makes the reading adaptive across timeframes and assets, in order to distinguish meaningful crowd behavior from random volatility.
📊 The core display is a five-zone histogram, each encoded by color and statistical depth. Optional background shading mirrors these zones across the entire pane, revealing subtle compression or structural rhythm shifts across time. By grounding the volume reading in volatility-adjusted context, ZVOL inhibits impulsive trading tactics by compelling the structure, not the sentiment, to dictate the signal.
🥵 Heatmap Coloration:
🌚 Suppressed volume — congestion, coiling phases
🩱 Stable flow — early trend or resting volume
🏀 High activity — emerging pressure
💔 Extreme — possible climax or institutional print
🎗️ A dynamic Fibonacci-based 21:34-period EMA ribbon overlays the histogram. The fill area inverts color on crossover, providing a real-time read on tempo, expansion, or divergence between price structure and crowd effort.
💡 LTF Usage Suggestions:
• Confirm breakout legs when orange or red zones align with range exits
• Fade overextended moves when red bars appear into resistance
• Watch for rising EMAs and orange volume to front-run impulsive moves
• Combine with volatility suppression (e.g. ATR) to catch compression → expansion transitions
🥂 Ideal Pairings:
• OBVX Conviction Bias — to confirm directional intent behind volume shifts
• SUPeR TReND 2.718 — for directional filters
• ATR Turbulence Ribbon — to detect compression phases
👥 The OBVX Conviction Bias adds a second dimension to ZVOL by revealing whether crowd effort is aligning with price direction or diverging beneath the surface. While ZVOL identifies statistical anomalies in raw volume, OBVX tracks directional commitment using cumulative volume and moving average cross logic. Use them together to spot fake-outs, anticipate structure-confirmed breakouts, or time pullbacks with volume-based conviction.
🔬 ZVOL isn’t just a volume filter — it’s a structural lens. It reveals when crowd effort is meaningful, when it's fading, and when something is about to shift. Designed for structure-aware traders who care about context, not noise.
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.
Percent Change HistogramThis indicator shows you percent changes in a super visual way using a color-coded histogram.
Here's how the colors work:
🟩 Dark green = percent change is growing stronger
🟢 Light green = still positive but losing steam
🟥 Dark red = getting more negative
🔴 Light red = negative but improving
The cool part? You can set any lookback period you want. For example:
24 periods on 1H chart = last 24 hours
30 periods on daily = last month
7 periods on daily = last week
Pro tip: You're not locked to your chart's timeframe! Want to see monthly changes while trading on 5min?
No problem.
You can even stack multiple indicators to watch different intervals simultaneously (daily, weekly, monthly) - super helpful for multi-timeframe analysis.
Perfect for spotting momentum shifts across different timeframes without switching between charts.
Market Performance by Yearly Seasons [LuxAlgo]The Market Performance by Yearly Seasons tool allows traders to analyze the average returns of the four seasons of the year and the raw returns of each separate season.
🔶 USAGE
By default, the tool displays the average returns for each season over the last 10 years in the form of bars, with the current session highlighted as a bordered bar.
Traders can choose to display the raw returns by year for each season separately and select the maximum number of seasons (years) to display.
🔹 Hemispheres
Traders can select the hemisphere in which they prefer to view the data.
🔹 Season Types
Traders can select the type of seasons between meteorological (by default) and astronomical.
The meteorological seasons are as follows:
Autumn: months from September to November
Winter: months from December to February
Spring: months from March to May
Summer: months from June to August
The astronomical seasons are as follows:
Autumn: from the equinox on September 22
Winter: from the solstice on December 21
Spring: from the equinox on March 20
Summer: from the solstice on June 21
🔹 Displaying the data
Traders can choose between two display modes, average returns by season or raw returns by season and year.
🔶 SETTINGS
Max seasons: Maximum number of seasons
Hemisphere: Select NORTHERN or SOUTHERN hemisphere
Season Type: Select the type of season - ASTRONOMICAL or METEOROLOGICAL
Display: Select display mode, all four seasons, or any one of them
🔹 Style
Bar Size & Autofit: Select the size of the bars and enable/disable the autofit feature
Labels Size: Select the label size
Colors & Gradient: Select the default color for bullish and bearish returns and enable/disable the gradient feature
Dominant Smoothed Volume Pro Smoothed Volume Pro provides a useful tool designed to provide traders with a deeper understanding of market dynamics by analyzing buy and sell volume across multiple timeframes. Unlike traditional volume indicators, this script normalizes volume data from lower timeframes to align with the current chart's timeframe, providing an apples-to-apples comparison. The result is a visual histogram representation of the dominant buy or sell activity, smoothed over 5 different periods to reflect momentum shifts and enhance clarity.
Core Methodology
1. Multi-Timeframe Volume Analysis
This indicator leverages data from five different lower timeframes, each chosen dynamically based on the current chart's timeframe. By aggregating and normalizing these granular data points, the indicator captures subtle shifts in buy and sell volume that might otherwise go unnoticed. This multi-timeframe approach allows for a more detailed and accurate representation of market activity.
2. Data Normalization
Normalization is a critical component of this indicator. It ensures that volume data from lower timeframes is scaled appropriately to match the total volume of the current chart's timeframe. This step eliminates discrepancies caused by varying time intervals, providing a more meaningful comparison of volume trends across different periods.
3. Smoothing for Momentum Representation
The indicator employs five customizable smoothing factors to smooth out noisy volume data.
Each smoothing factor is distinctly color-coded in the histogram and table for intuitive analysis, helping traders quickly identify prevailing trends.
Features and Benefits
➖Customizable Smoothing Factors: Choose from five different smoothing factors, each with its unique settings for line styles, colors, and extensions.
➖Normalized Buy and Sell Volume: Displays normalized buy and sell volumes as a percentage of total activity, aiding in quick decision-making.
➖Visual Cues: Color-coded columns and labels help identify dominant trends at a glance, with high-opacity fills for visual clarity.
➖Dynamic Table: A built-in table summarizes smoothed volume data for each smoothing factor, offering a quick overview of bullish and bearish percentages.
➖Momentum Signals: Detect significant shifts in volume momentum with visually distinct alerts for high relative volumes, including special symbols like "⚡" and "🔥."
Practical Applications
➖Identifying Market Sentiment: Quickly determine whether the market is dominated by buyers or sellers at any given moment.
➖Spotting Reversals: Use momentum shifts in smoothed volume to anticipate potential trend reversals.
➖Enhancing Entry and Exit Points: Combine this indicator with other technical tools to refine entry and exit points in your trading strategy.
Why This Indicator Stands Out
Many existing volume indicators focus solely on raw or single-timeframe data, which can be misleading or incomplete. This indicator sets itself apart by:
Utilizing multi-timeframe data to provide a holistic view of market activity.
Applying robust normalization techniques to ensure data consistency.
Offering advanced smoothing options to emphasize actionable momentum signals.
This unique combination of features makes it an indispensable tool for traders seeking to enhance their market analysis and decision-making process.
As always, by combining the Smoothed Volume Pro with other tools, traders ensure that they are not relying on a single indicator. This layered approach can reduce the likelihood of false signals and improve overall trading accuracy.
Here's an additional visual representation using the plot fills:
Multi-Step FlexiSuperTrend - Indicator [presentTrading]This version of the indicator is built upon the foundation of a strategy version published earlier. However, this indicator version focuses on providing visual insights and alerts for traders, rather than executing trades. This one is mostly for @thorcmt.
█ Introduction and How it is Different
The **Multi-Step FlexiSuperTrend Indicator** is a versatile tool designed to provide traders with a highly customizable and flexible approach to trend analysis. Unlike traditional supertrend indicators, which focus on a single factor or threshold, the **FlexiSuperTrend** allows users to define multiple levels of take-profit targets and incorporate different trend normalization methods.
It comes with several advanced customization features, including multi-step take profits, deviation plotting, and trend normalization, making it suitable for both novice and expert traders.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The **Multi-Step FlexiSuperTrend** works by calculating a supertrend based on multiple factors and incorporating oscillations from trend deviations. Here’s a breakdown of how it functions:
🔶 SuperTrend Calculation
At the heart of the indicator is the SuperTrend formula, which dynamically adjusts based on price movements.
🔶 Normalization of Deviations
To enhance accuracy, the **FlexiSuperTrend** calculates multiple deviations from the trend and normalizes them.
🔶 Multi-Step Take Profit Levels
The indicator allows setting up to three take profit levels, which are displayed via price level alerts. lows traders to exit part of their position at various profit intervals.
For more detail, please check the strategy version - Multi-Step-FlexiSuperTrend-Strategy:
and 'FlexiSuperTrend-Strategy'
█ Trade Direction
The **Multi-Step FlexiSuperTrend Indicator** supports both long and short trade directions.
This flexibility allows traders to adapt to trending, volatile, or sideways markets.
█ Usage
To use the **FlexiSuperTrend Indicator**, traders can set up their preferences for the following key features:
- **Trading Direction**: Choose whether to focus on long, short, or both signals.
- **Indicator Source**: The price source to calculate the trend (e.g., close, hl2).
- **Indicator Length**: The number of periods to calculate the ATR and trend (the larger the value, the smoother the trend).
- **Starting and Increment Factor**: These adjust how reactive the trend is to price movements. The starting factor dictates how far the initial trend band is from the price, and the increment factor adjusts subsequent trend deviations.
The indicator then displays buy and sell signals on the chart, along with alerts for each take-profit level.
Local picture
█ Default Settings
The default settings of the **Multi-Step FlexiSuperTrend** are carefully designed to provide an optimal balance between sensitivity and accuracy. Let’s examine these default parameters and their effect on performance:
🔶 Indicator Length (Default: 10)
The **Indicator Length** determines the lookback period for the ATR calculation. A smaller value makes the indicator more reactive to price changes, but may generate more false signals. A longer length smooths the trend and reduces noise but may delay signals.
Effect on performance: Shorter lengths perform better in volatile markets, while longer lengths excel in trending markets.
🔶 Starting Factor (Default: 0.618)
This factor adjusts the starting distance of the SuperTrend from the current price. The smaller the starting factor, the closer the trend is to the price, making it more sensitive. Conversely, a larger factor allows more distance, reducing sensitivity but filtering out false signals.
Effect on performance: A smaller factor provides quicker signals but can lead to frequent false positives. A larger factor generates fewer but more reliable signals.
🔶 Increment Factor (Default: 0.382)
The **Increment Factor** controls how the trend bands adjust as the price moves. It increases the distance of the bands from the price with each iteration.
Effect on performance: A higher increment factor can result in wider stop-loss or trend reversal bands, allowing for longer trends to develop without frequent exits. A lower factor keeps the bands closer to the price and is more suited for shorter-term trades.
🔶 Take Profit Levels (Default: 2%, 8%, 18%)
The default take-profit levels are set at 2%, 8%, and 18%. These values represent the thresholds at which the trader can partially exit their positions. These multi-step levels are highly customizable depending on the trader’s risk tolerance and strategy.
Effect on performance: Lower take-profit levels (e.g., 2%) capture small, quick profits in volatile markets, while higher levels (8%-18%) allow for a more gradual exit in strong trends.
🔶 Normalization Method (Default: None)
The default normalization method is **None**, meaning the deviations are not normalized. However, enabling normalization (e.g., **Max-Min**) can improve the clarity of the indicator’s signals in volatile or choppy markets by smoothing out the noise.
Effect on performance: Using a normalization method can reduce the effect of extreme deviations, making signals more stable and less prone to false positives.
Multi-Step FlexiMA - Strategy [presentTrading]It's time to come back! hope I can not to be busy for a while.
█ Introduction and How It Is Different
The FlexiMA Variance Tracker is a unique trading strategy that calculates a series of deviations between the price (or another indicator source) and a variable-length moving average (MA). Unlike traditional strategies that use fixed-length moving averages, the length of the MA in this system varies within a defined range. The length changes dynamically based on a starting factor and an increment factor, creating a more adaptive approach to market conditions.
This strategy integrates Multi-Step Take Profit (TP) levels, allowing for partial exits at predefined price increments. It enables traders to secure profits at different stages of a trend, making it ideal for volatile markets where taking full profits at once might lead to missed opportunities if the trend continues.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
🔶 FlexiMA Concept
The FlexiMA (Flexible Moving Average) is at the heart of this strategy. Unlike traditional MA-based strategies where the MA length is fixed (e.g., a 50-period SMA), the FlexiMA varies its length with each iteration. This is done using a **starting factor** and an **increment factor**.
The formula for the moving average length at each iteration \(i\) is:
`MA_length_i = indicator_length * (starting_factor + i * increment_factor)`
Where:
- `indicator_length` is the user-defined base length.
- `starting_factor` is the initial multiplier of the base length.
- `increment_factor` increases the multiplier in each iteration.
Each iteration applies a **simple moving average** (SMA) to the chosen **indicator source** (e.g., HLC3) with a different length based on the above formula. The deviation between the current price and the moving average is then calculated as follows:
`deviation_i = price_current - MA_i`
These deviations are normalized using one of the following methods:
- **Max-Min normalization**:
`normalized_i = (deviation_i - min(deviations)) / range(deviations)`
- **Absolute Sum normalization**:
`normalized_i = deviation_i / sum(|deviation_i|)`
The **median** and **standard deviation (stdev)** of the normalized deviations are then calculated as follows:
`median = median(normalized deviations)`
For the standard deviation:
`stdev = sqrt((1/(N-1)) * sum((normalized_i - mean)^2))`
These values are plotted to provide a clear indication of how the price is deviating from its variable-length moving averages.
For more detail:
🔶 Multi-Step Take Profit
This strategy uses a multi-step take profit system, allowing for exits at different stages of a trade based on the percentage of price movement. Three take-profit levels are defined:
- Take Profit Level 1 (TP1): A small, quick profit level (e.g., 2%).
- Take Profit Level 2 (TP2): A medium-level profit target (e.g., 8%).
- Take Profit Level 3 (TP3): A larger, more ambitious target (e.g., 18%).
At each level, a corresponding percentage of the trade is exited:
- TP Percent 1: E.g., 30% of the position.
- TP Percent 2: E.g., 20% of the position.
- TP Percent 3: E.g., 15% of the position.
This approach ensures that profits are locked in progressively, reducing the risk of market reversals wiping out potential gains.
Local
🔶 Trade Entry and Exit Conditions
The entry and exit signals are determined by the interaction between the **SuperTrend Polyfactor Oscillator** and the **median** value of the normalized deviations:
- Long entry: The SuperTrend turns bearish, and the median value of the deviations is positive.
- Short entry: The SuperTrend turns bullish, and the median value is negative.
Similarly, trades are exited when the SuperTrend flips direction.
* The SuperTrend Toolkit is made by @EliCobra
█ Trade Direction
The strategy allows users to specify the desired trade direction:
- Long: Only long positions will be taken.
- Short: Only short positions will be taken.
- Both: Both long and short positions are allowed based on the conditions.
This flexibility allows the strategy to adapt to different market conditions and trading styles, whether you're looking to buy low and sell high, or sell high and buy low.
█ Usage
This strategy can be applied across various asset classes, including stocks, cryptocurrencies, and forex. The primary use case is to take advantage of market volatility by using a flexible moving average and multiple take-profit levels to capture profits incrementally as the market moves in your favor.
How to Use:
1. Configure the Inputs: Start by adjusting the **Indicator Length**, **Starting Factor**, and **Increment Factor** to suit your chosen asset. The defaults work well for most markets, but fine-tuning them can improve performance.
2. Set the Take Profit Levels: Adjust the three **TP levels** and their corresponding **percentages** based on your risk tolerance and the expected volatility of the market.
3. Monitor the Strategy: The SuperTrend and the FlexiMA variance tracker will provide entry and exit signals, automatically managing the positions and taking profits at the pre-set levels.
█ Default Settings
The default settings for the strategy are configured to provide a balanced approach that works across different market conditions:
Indicator Length (10):
This controls the base length for the moving average. A lower length makes the moving average more responsive to price changes, while a higher length smooths out fluctuations, making the strategy less sensitive to short-term price movements.
Starting Factor (1.0):
This determines the initial multiplier applied to the moving average length. A higher starting factor will increase the average length, making it slower to react to price changes.
Increment Factor (1.0):
This increases the moving average length in each iteration. A larger increment factor creates a wider range of moving average lengths, allowing the strategy to track both short-term and long-term trends simultaneously.
Normalization Method ('None'):
Three methods of normalization can be applied to the deviations:
- None: No normalization applied, using raw deviations.
- Max-Min: Normalizes based on the range between the maximum and minimum deviations.
- Absolute Sum: Normalizes based on the total sum of absolute deviations.
Take Profit Levels:
- TP1 (2%): A quick exit to capture small price movements.
- TP2 (8%): A medium-term profit target for stronger trends.
- TP3 (18%): A long-term target for strong price moves.
Take Profit Percentages:
- TP Percent 1 (30%): Exits 30% of the position at TP1.
- TP Percent 2 (20%): Exits 20% of the position at TP2.
- TP Percent 3 (15%): Exits 15% of the position at TP3.
Effect of Variables on Performance:
- Short Indicator Lengths: More responsive to price changes but prone to false signals.
- Higher Starting Factor: Slows down the response, useful for longer-term trend following.
- Higher Increment Factor: Widens the variability in moving average lengths, making the strategy adapt to both short-term and long-term price trends.
- Aggressive Take Profit Levels: Allows for quick profit-taking in volatile markets but may exit positions prematurely in strong trends.
The default configuration offers a moderate balance between short-term responsiveness and long-term trend capturing, suitable for most traders. However, users can adjust these variables to optimize performance based on market conditions and personal preferences.
Multi-Step FlexiSuperTrend - Strategy [presentTrading]At the heart of this endeavor is a passion for continuous improvement in the art of trading
█ Introduction and How it is Different
The "Multi-Step FlexiSuperTrend - Strategy " is an advanced trading strategy that integrates the well-known SuperTrend indicator with a nuanced and dynamic approach to market trend analysis. Unlike conventional SuperTrend strategies that rely on static thresholds and fixed parameters, this strategy introduces multi-step take profit mechanisms that allow traders to capitalize on varying market conditions in a more controlled and systematic manner.
What sets this strategy apart is its ability to dynamically adjust to market volatility through the use of an incremental factor applied to the SuperTrend calculation. This adjustment ensures that the strategy remains responsive to both minor and major market shifts, providing a more accurate signal for entries and exits. Additionally, the integration of multi-step take profit levels offers traders the flexibility to scale out of positions, locking in profits progressively as the market moves in their favor.
BTC 6hr Long/Short Performance
█ Strategy, How it Works: Detailed Explanation
The Multi-Step FlexiSuperTrend strategy operates on the foundation of the SuperTrend indicator, but with several enhancements that make it more adaptable to varying market conditions. The key components of this strategy include the SuperTrend Polyfactor Oscillator, a dynamic normalization process, and multi-step take profit levels.
🔶 SuperTrend Polyfactor Oscillator
The SuperTrend Polyfactor Oscillator is the heart of this strategy. It is calculated by applying a series of SuperTrend calculations with varying factors, starting from a defined "Starting Factor" and incrementing by a specified "Increment Factor." The indicator length and the chosen price source (e.g., HLC3, HL2) are inputs to the oscillator.
The SuperTrend formula typically calculates an upper and lower band based on the average true range (ATR) and a multiplier (the factor). These bands determine the trend direction. In the FlexiSuperTrend strategy, the oscillator is enhanced by iteratively applying the SuperTrend calculation across different factors. The iterative process allows the strategy to capture both minor and significant trend changes.
For each iteration (indexed by `i`), the following calculations are performed:
1. ATR Calculation: The Average True Range (ATR) is calculated over the specified `indicatorLength`:
ATR_i = ATR(indicatorLength)
2. Upper and Lower Bands Calculation: The upper and lower bands are calculated using the ATR and the current factor:
Upper Band_i = hl2 + (ATR_i * Factor_i)
Lower Band_i = hl2 - (ATR_i * Factor_i)
Here, `Factor_i` starts from `startingFactor` and is incremented by `incrementFactor` in each iteration.
3. Trend Determination: The trend is determined by comparing the indicator source with the upper and lower bands:
Trend_i = 1 (uptrend) if IndicatorSource > Upper Band_i
Trend_i = 0 (downtrend) if IndicatorSource < Lower Band_i
Otherwise, the trend remains unchanged from the previous value.
4. Output Calculation: The output of each iteration is determined based on the trend:
Output_i = Lower Band_i if Trend_i = 1
Output_i = Upper Band_i if Trend_i = 0
This process is repeated for each iteration (from 0 to 19), creating a series of outputs that reflect different levels of trend sensitivity.
Local
🔶 Normalization Process
To make the oscillator values comparable across different market conditions, the deviations between the indicator source and the SuperTrend outputs are normalized. The normalization method can be one of the following:
1. Max-Min Normalization: The deviations are normalized based on the range of the deviations:
Normalized Value_i = (Deviation_i - Min Deviation) / (Max Deviation - Min Deviation)
2. Absolute Sum Normalization: The deviations are normalized based on the sum of absolute deviations:
Normalized Value_i = Deviation_i / Sum of Absolute Deviations
This normalization ensures that the oscillator values are within a consistent range, facilitating more reliable trend analysis.
For more details:
🔶 Multi-Step Take Profit Mechanism
One of the unique features of this strategy is the multi-step take profit mechanism. This allows traders to lock in profits at multiple levels as the market moves in their favor. The strategy uses three take profit levels, each defined as a percentage increase (for long trades) or decrease (for short trades) from the entry price.
1. First Take Profit Level: Calculated as a percentage increase/decrease from the entry price:
TP_Level1 = Entry Price * (1 + tp_level1 / 100) for long trades
TP_Level1 = Entry Price * (1 - tp_level1 / 100) for short trades
The strategy exits a portion of the position (defined by `tp_percent1`) when this level is reached.
2. Second Take Profit Level: Similar to the first level, but with a higher percentage:
TP_Level2 = Entry Price * (1 + tp_level2 / 100) for long trades
TP_Level2 = Entry Price * (1 - tp_level2 / 100) for short trades
The strategy exits another portion of the position (`tp_percent2`) at this level.
3. Third Take Profit Level: The final take profit level:
TP_Level3 = Entry Price * (1 + tp_level3 / 100) for long trades
TP_Level3 = Entry Price * (1 - tp_level3 / 100) for short trades
The remaining portion of the position (`tp_percent3`) is exited at this level.
This multi-step approach provides a balance between securing profits and allowing the remaining position to benefit from continued favorable market movement.
█ Trade Direction
The strategy allows traders to specify the trade direction through the `tradeDirection` input. The options are:
1. Both: The strategy will take both long and short positions based on the entry signals.
2. Long: The strategy will only take long positions.
3. Short: The strategy will only take short positions.
This flexibility enables traders to tailor the strategy to their market outlook or current trend analysis.
█ Usage
To use the Multi-Step FlexiSuperTrend strategy, traders need to set the input parameters according to their trading style and market conditions. The strategy is designed for versatility, allowing for various market environments, including trending and ranging markets.
Traders can also adjust the multi-step take profit levels and percentages to match their risk management and profit-taking preferences. For example, in highly volatile markets, traders might set wider take profit levels with smaller percentages at each level to capture larger price movements.
The normalization method and the incremental factor can be fine-tuned to adjust the sensitivity of the SuperTrend Polyfactor Oscillator, making the strategy more responsive to minor market shifts or more focused on significant trends.
█ Default Settings
The default settings of the strategy are carefully chosen to provide a balanced approach between risk management and profit potential. Here is a breakdown of the default settings and their effects on performance:
1. Indicator Length (10): This parameter controls the lookback period for the ATR calculation. A shorter length makes the strategy more sensitive to recent price movements, potentially generating more signals. A longer length smooths out the ATR, reducing sensitivity but filtering out noise.
2. Starting Factor (0.618): This is the initial multiplier used in the SuperTrend calculation. A lower starting factor makes the SuperTrend bands closer to the price, generating more frequent trend changes. A higher starting factor places the bands further away, filtering out minor fluctuations.
3. Increment Factor (0.382): This parameter controls how much the factor increases with each iteration of the SuperTrend calculation. A smaller increment factor results in more gradual changes in sensitivity, while a larger increment factor creates a wider range of sensitivity across the iterations.
4. Normalization Method (None): The default is no normalization, meaning the raw deviations are used. Normalization methods like Max-Min or Absolute Sum can make the deviations more consistent across different market conditions, improving the reliability of the oscillator.
5. Take Profit Levels (2%, 8%, 18%): These levels define the thresholds for exiting portions of the position. Lower levels (e.g., 2%) capture smaller profits quickly, while higher levels (e.g., 18%) allow positions to run longer for more significant gains.
6. Take Profit Percentages (30%, 20%, 15%): These percentages determine how much of the position is exited at each take profit level. A higher percentage at the first level locks in more profit early, reducing exposure to market reversals. Lower percentages at higher levels allow for a portion of the position to benefit from extended trends.
MTF-Colored EMA Difference and Stochastic indicatorThis indicator combines two popular technical analysis tools: the Exponential Moving Average (EMA) and the Stochastic Oscillator, with the added flexibility of analyzing them across multiple time frames. It visually represents the difference between two EMAs and the crossover signals from the Stochastic Oscillator, providing a comprehensive view of the market conditions.
Components:
EMA Difference Histogram :
EMA Calculation : The indicator calculates two EMAs (EMA1 and EMA2) for the selected time frame.
EMA Difference : The difference between EMA1 and EMA2 is plotted as a 4 coloured histogram.
Stochastic Oscillato r:
Calculation : The %K and %D lines of the Stochastic Oscillator are calculated for the selected time frame.
Additional Confirmation via Colors :
Green: %K is above %D, indicating a bullish signal.
Red: %K is below %D, indicating a bearish signal.
Entry and Exit Strategies
Entry Strategy :
Bullish Entry :
Condition 1: The histogram is Dark green (indicating a strong upward trend).
Condition 2: The Stochastic colour is green (%K is above %D).
Bearish Entry :
Condition 1: The histogram is Dark Red (indicating a strong downward trend).
Condition 2: The Stochastic colour is red (%K is below %D).
Exit Strategy:
Bullish Exit:
Condition: The Stochastic colour turns red (%K crosses below %D).
Bearish Exit:
Condition: The Stochastic colour turns green (%K crosses above %D).
Additional Considerations:
Time Frame Selection : The chosen time frame for both the EMA and Stochastic calculations should align with the trader’s strategy (e.g., daily for swing trading, hourly for intraday trading).
Risk Management : Implement stop-loss orders to manage risk effectively. The stop-loss can be placed below the recent swing low for long positions and above the recent swing high for short positions.
Confirmation : Consider using this indicator in conjunction with other technical analysis tools to confirm signals and reduce the likelihood of false entries and exits.
Multi Asset Histogram [ChartPrime]Multi Asset Histogram Indicator
Overview:
The "Multi Asset Histogram" indicator provides a comprehensive visualization of the performance of multiple assets relative to each other. By calculating a score for each asset and displaying it in a histogram format, this indicator helps traders quickly identify the trends, dominant asset and the average performance of the assets in the selected group.
Key Features:
◆ Multi-Asset Score Calculation:
The indicator calculates a trend score for each selected asset based on the price source (e.g., hl2).
The trend score is determined by comparing the current price to the prices over the past bars back defined by user, adding or subtracting points based on whether the current price is higher or lower than previous prices.
// Score Function
trscore(src) =>
total = 0.0
for i = 1 to 50
total += (src >= nz(src ) ? 1 : -1)
total
◆ Flexible Symbol Input:
Traders can input up to 10 different symbols (e.g., BTCUSD, ETHUSD, etc.) to be included in the histogram analysis.
◆ Dynamic Visualization:
A histogram is plotted for each asset, with bars colored based on the score, providing a clear visual representation of the relative performance.
Color gradients from red to aqua indicate the performance, with red representing negative scores and aqua representing positive scores.
◆ Adaptive Histogram Lines:
The width and placement of histogram lines adapt based on the calculated scores, ensuring clear visualization regardless of the values.
Dashed lines represent the mean score of all assets, helping traders identify the overall market trend.
◆Detailed Labels and Values:
Labels are placed on the histogram to display the exact score for each asset.
Mean value and zero line labels provide additional context for the overall performance.
◆ Visual Scaling Lines:
Zero line and mean line are clearly marked, helping traders understand the distribution and scale of scores.
Scales on the left and right of the histogram indicate the performance range.
◆ Informative Table:
A table is displayed on the chart, showing the dominant asset (the one with the highest score) and the mean score of all assets.
The table updates dynamically to reflect real-time changes in asset performance.
◆ Settings:
Length: The value of number bars back is greater or less than the current value of the source
Source: The price source to be used for score calculation (e.g., hl2).
Symbols: Up to 10 different asset symbols can be input for analysis.
Usage Notes:
This indicator is useful for traders who monitor multiple assets simultaneously and need a quick visual reference to identify the strongest and weakest performers.
The color coding and dynamic labels make it easy to interpret the relative performance and make informed trading decisions.
This indicator is designed to enhance multi-asset analysis by providing a clear, visual representation of each asset's performance relative to the others, making it easier to identify trends and dominant assets in the market.
ADR Study [TFO]This indicator is focused on the Average Daily Range (ADR), with the goal of collecting data to show how often price reaches/closes through these levels, as well as a look at historical moves that reached ADR and at similar times of day to study how price moved for the remainder of the session.
The ADR here (blue line) is calculated using the difference between a day's highest and lowest points. If our ADR length is 5, then we are taking this difference from the last 5 days and averaging them together. At the following day's open, we take half of this average and plot it above and below the daily opening price to place theoretical limits on how far price may move according to the lookback period. The triangles indicate when price has reached ADR (either +ADR or -ADR), and alerts can be created for these events.
The Scale Factor is an optional parameter to scale the ADR by a certain amount. If set to 2 for example, then the ADR would be 2x the average daily range. This value will be reflected in the statistics options so that users can see how different values affect the outcomes.
Show Table will display data collected on how often price reaches these levels, and how often price closes through them, for each day of the week. By default, these are colored as blue and red, respectively. From the following chart of NQ1!, we can see for example that on Mondays, price reached +ADR 38% of the time and closed through it 23% of the time. Note that the statistics for closing through the ADR levels are derived from all instances, not just those that reached ADR.
Show Sample Sizes will display how many instances were collected for all given sets of data. Referring to the same example of NQ1!, we can see that this particular chart has collected data from 109 Mondays. From those Mondays, 41 reached +ADR (38%, verifying our initial claim) and 25 closed through it (23%). This is important to understand the scope of the data that we're working with, as percentages can be misleading for smaller sample sizes.
Show Histogram will plot the same exact data as the table, just in a histogram form to visually emphasize the differences on a day-by-day basis. On this chart of RTY1!, we can see for example from the top histogram that on Wednesdays, 40% reached +ADR and only 22% closed through it. Similarly if we look at the bottom histogram, we can see that Wednesdays reached -ADR 46% of the time and closed through it only 28% of the time.
We can also use Show Sample Sizes to display the same information that would be in the table, showing how many instances were collected for each event. In this case we can see that we observed 175 Fridays, where 76 reached +ADR (43%) and 44 closed above it (25%).
Show Historical Moves is an interesting feature of this script. When enabled, if price has reached +/- ADR in the current session, the indicator will plot the evolution of the close prices from all past sessions that reached +/- ADR to see how they traded for the remainder of the session. These calculations are made with respect to the ADR range at the time that price traded through these levels.
Historical Proximity (Bars) allows the user to observe historical moves where price reached ADR within this many bars of the current session (assuming price has reached an ADR level in the current session). In the above chart, this is set to 1000 so that we can observe each and every instance where price reached an ADR level. However, we can refine this a bit more.
By limiting the Historical Proximity to something like 20, we are only considering historical moves that reached ADR within 20 bars of todays +ADR reach (9:50 am EST, noted by the blue triangle up). We can enable Show Average Move to display the average move by the filtered dataset, and Match +/-ADR to only observe moves inline with the current day's price action (in this case, only moves that reached +ADR, since price has not reached -ADR).
We can add one more filter to this data with the setting Only Show Days That: closed through ADR; closed within ADR; or either. The option either is what you see above, as we are considering both days that closed through ADR and days that closed within it (note that in this case, closing within ADR simply means that price reached +ADR and closed the day below it, and vice versa for -ADR; this does not mean that price must have closed in between +ADR and -ADR). If we set this to only show instances that closed within ADR, we see the following data.
Alternatively, we can choose to Only Show Days That closed through ADR, where we would see the following data. In this case, the average move very much resembles the price action that occurred on this particular day. This is in no way guaranteed, but it makes an interesting case for how we could use this data in our analysis by observing similar, historical price action.
Please note that this data will change over time on a rolling basis due to TradingView's bar lookback, and that for this same reason, lower timeframes will yield less data than larger timeframes.
