Volume Predictor [PhenLabs]📊 Volume Predictor
Version: PineScript™ v6
📌 Description
The Volume Predictor is an advanced technical indicator that leverages machine learning and statistical modeling techniques to forecast future trading volume. This innovative tool analyzes historical volume patterns to predict volume levels for upcoming bars, providing traders with valuable insights into potential market activity. By combining multiple prediction algorithms with pattern recognition techniques, the indicator delivers forward-looking volume projections that can enhance trading strategies and market analysis.
🚀 Points of Innovation:
Machine learning pattern recognition using Lorentzian distance metrics
Multi-algorithm prediction framework with algorithm selection
Ensemble learning approach combining multiple prediction methods
Real-time accuracy metrics with visual performance dashboard
Dynamic volume normalization for consistent scale representation
Forward-looking visualization with configurable prediction horizon
🔧 Core Components
Pattern Recognition Engine : Identifies similar historical volume patterns using Lorentzian distance metrics
Multi-Algorithm Framework : Offers five distinct prediction methods with configurable parameters
Volume Normalization : Converts raw volume to percentage scale for consistent analysis
Accuracy Tracking : Continuously evaluates prediction performance against actual outcomes
Advanced Visualization : Displays actual vs. predicted volume with configurable future bar projections
Interactive Dashboard : Shows real-time performance metrics and prediction accuracy
🔥 Key Features
The indicator provides comprehensive volume analysis through:
Multiple Prediction Methods : Choose from Lorentzian, KNN Pattern, Ensemble, EMA, or Linear Regression algorithms
Pattern Matching : Identifies similar historical volume patterns to project future volume
Adaptive Predictions : Generates volume forecasts for multiple bars into the future
Performance Tracking : Calculates and displays real-time prediction accuracy metrics
Normalized Scale : Presents volume as a percentage of historical maximums for consistent analysis
Customizable Visualization : Configure how predictions and actual volumes are displayed
Interactive Dashboard : View algorithm performance metrics in a customizable information panel
🎨 Visualization
Actual Volume Columns : Color-coded green/red bars showing current normalized volume
Prediction Columns : Semi-transparent blue columns representing predicted volume levels
Future Bar Projections : Forward-looking volume predictions with configurable transparency
Prediction Dots : Optional white dots highlighting future prediction points
Reference Lines : Visual guides showing the normalized volume scale
Performance Dashboard : Customizable panel displaying prediction method and accuracy metrics
📖 Usage Guidelines
History Lookback Period
Default: 20
Range: 5-100
This setting determines how many historical bars are analyzed for pattern matching. A longer period provides more historical data for pattern recognition but may reduce responsiveness to recent changes. A shorter period emphasizes recent market behavior but might miss longer-term patterns.
🧠 Prediction Method
Algorithm
Default: Lorentzian
Options: Lorentzian, KNN Pattern, Ensemble, EMA, Linear Regression
Selects the algorithm used for volume prediction:
Lorentzian: Uses Lorentzian distance metrics for pattern recognition, offering excellent noise resistance
KNN Pattern: Traditional K-Nearest Neighbors approach for historical pattern matching
Ensemble: Combines multiple methods with weighted averaging for robust predictions
EMA: Simple exponential moving average projection for trend-following predictions
Linear Regression: Projects future values based on linear trend analysis
Pattern Length
Default: 5
Range: 3-10
Defines the number of bars in each pattern for machine learning methods. Shorter patterns increase sensitivity to recent changes, while longer patterns may identify more complex structures but require more historical data.
Neighbors Count
Default: 3
Range: 1-5
Sets the K value (number of nearest neighbors) used in KNN and Lorentzian methods. Higher values produce smoother predictions by averaging more historical patterns, while lower values may capture more specific patterns but could be more susceptible to noise.
Prediction Horizon
Default: 5
Range: 1-10
Determines how many future bars to predict. Longer horizons provide more forward-looking information but typically decrease accuracy as the prediction window extends.
📊 Display Settings
Display Mode
Default: Overlay
Options: Overlay, Prediction Only
Controls how volume information is displayed:
Overlay: Shows both actual volume and predictions on the same chart
Prediction Only: Displays only the predictions without actual volume
Show Prediction Dots
Default: false
When enabled, adds white dots to future predictions for improved visibility and clarity.
Future Bar Transparency (%)
Default: 70
Range: 0-90
Controls the transparency of future prediction bars. Higher values make future bars more transparent, while lower values make them more visible.
📱 Dashboard Settings
Show Dashboard
Default: true
Toggles display of the prediction accuracy dashboard. When enabled, shows real-time accuracy metrics.
Dashboard Location
Default: Bottom Right
Options: Top Left, Top Right, Bottom Left, Bottom Right
Determines where the dashboard appears on the chart.
Dashboard Text Size
Default: Normal
Options: Small, Normal, Large
Controls the size of text in the dashboard for various display sizes.
Dashboard Style
Default: Solid
Options: Solid, Transparent
Sets the visual style of the dashboard background.
Understanding Accuracy Metrics
The dashboard provides key performance metrics to evaluate prediction quality:
Average Error
Shows the average difference between predicted and actual values
Positive values indicate the prediction tends to be higher than actual volume
Negative values indicate the prediction tends to be lower than actual volume
Values closer to zero indicate better prediction accuracy
Accuracy Percentage
A measure of how close predictions are to actual outcomes
Higher percentages (>70%) indicate excellent prediction quality
Moderate percentages (50-70%) indicate acceptable predictions
Lower percentages (<50%) suggest weaker prediction reliability
The accuracy metrics are color-coded for quick assessment:
Green: Strong prediction performance
Orange: Moderate prediction performance
Red: Weaker prediction performance
✅ Best Use Cases
Anticipate upcoming volume spikes or drops
Identify potential volume divergences from price action
Plan entries and exits around expected volume changes
Filter trading signals based on predicted volume support
Optimize position sizing by forecasting market participation
Prepare for potential volatility changes signaled by volume predictions
Enhance technical pattern analysis with volume projection context
⚠️ Limitations
Volume predictions become less accurate over longer time horizons
Performance varies based on market conditions and asset characteristics
Works best on liquid assets with consistent volume patterns
Requires sufficient historical data for pattern recognition
Sudden market events can disrupt prediction accuracy
Volume spikes may be muted in predictions due to normalization
💡 What Makes This Unique
Machine Learning Approach : Applies Lorentzian distance metrics for robust pattern matching
Algorithm Selection : Offers multiple prediction methods to suit different market conditions
Real-time Accuracy Tracking : Provides continuous feedback on prediction performance
Forward Projection : Visualizes multiple future bars with configurable display options
Normalized Scale : Presents volume as a percentage of maximum volume for consistent analysis
Interactive Dashboard : Displays key metrics with customizable appearance and placement
🔬 How It Works
The Volume Predictor processes market data through five main steps:
1. Volume Normalization:
Converts raw volume to percentage of maximum volume in lookback period
Creates consistent scale representation across different timeframes and assets
Stores historical normalized volumes for pattern analysis
2. Pattern Detection:
Identifies similar volume patterns in historical data
Uses Lorentzian distance metrics for robust similarity measurement
Determines strength of pattern match for prediction weighting
3. Algorithm Processing:
Applies selected prediction algorithm to historical patterns
For KNN/Lorentzian: Finds K nearest neighbors and calculates weighted prediction
For Ensemble: Combines multiple methods with optimized weighting
For EMA/Linear Regression: Projects trends based on statistical models
4. Accuracy Calculation:
Compares previous predictions to actual outcomes
Calculates average error and prediction accuracy
Updates performance metrics in real-time
5. Visualization:
Displays normalized actual volume with color-coding
Shows current and future volume predictions
Presents performance metrics through interactive dashboard
💡 Note:
The Volume Predictor performs optimally on liquid assets with established volume patterns. It’s most effective when used in conjunction with price action analysis and other technical indicators. The multi-algorithm approach allows adaptation to different market conditions by switching prediction methods. Pay special attention to the accuracy metrics when evaluating prediction reliability, as sudden market changes can temporarily reduce prediction quality. The normalized percentage scale makes the indicator consistent across different assets and timeframes, providing a standardized approach to volume analysis.
Volume
Volume-Weighted MA Crossover [AlphaAlgos]Volume-Weighted MA Crossover
Overview:
The Volume-Weighted MA Crossover is a sophisticated trend-following indicator designed to capture reliable trend reversals and trend continuation signals using volume and price action. By combining the power of Volume-Weighted Moving Averages (VWMA) and the simplicity of Simple Moving Averages (SMA) , this indicator provides a more robust and reliable trend filter. It ensures that trend signals are supported by strong market volume, offering a deeper insight into market strength and potential price movements.
How It Works:
The Volume-Weighted MA Crossover indicator calculates a Volume-Weighted Moving Average (VWMA) of the chosen price source (typically close ), which takes into account both the price and volume of each bar. This ensures that price movements with higher volume are weighted more heavily, providing a better reflection of actual market sentiment.
In conjunction with the VWMA, a traditional Simple Moving Average (SMA) is used to filter out noise and smooth price data, providing a more stable trend direction. The crossover between the VWMA and SMA serves as the primary trading signal:
Long Signal (Bullish Crossover) : The VWMA crosses above the SMA, indicating that a strong bullish trend is likely underway, supported by increased volume and price action.
Short Signal (Bearish Crossover) : The VWMA crosses below the SMA, signaling that a bearish trend is emerging, backed by decreasing volume and price reversal.
The Volume-Weighted MA Crossover can be used as a standalone indicator or in conjunction with other tools to enhance your trading strategy, offering both trend-following and volume confirmation.
Key Features:
Volume Sensitivity : The VWMA adjusts the moving average based on volume, providing a more accurate representation of price action during high-volume periods. This makes the indicator more sensitive to market dynamics, ensuring that price movements during significant volume spikes are prioritized.
Trend Confirmation : The crossover of the VWMA and SMA offers clear and actionable signals, helping traders identify trend reversals early and with more confidence.
Clean Signal Presentation : With color-coded signal markers , this indicator makes it easy to spot actionable entry points.
Customizable Settings : Tailor the VWMA and SMA periods, volume multiplier, and source price according to your preferred market conditions and timeframes, allowing the indicator to fit your trading style.
How to Use It:
Trend Direction : Look for crossovers between the VWMA and SMA to identify potential trend changes:
Volume Confirmation : The volume-weighted aspect of this indicator ensures that trends are confirmed by volume. A bullish trend with a VWMA crossing above the SMA suggests that the upward movement is supported by strong market sentiment (high volume). Conversely, a bearish trend with a VWMA crossing below the SMA indicates a reversal is supported by volume reduction.
Trend Continuation & Reversal : This indicator works particularly well during strong trending markets. However, it can also identify potential reversals, particularly during periods of high volume and rapid price changes.
Best Timeframe to Use:
This indicator is adaptable to multiple timeframes and can be used across various market types. However, it tends to work most effectively on medium to long-term charts (such as 1-hour, 4-hour, and daily charts) where trends have the potential to develop more clearly and with more volume participation.
Ideal for:
Trend-following traders looking for reliable signals that are confirmed by both price action and volume.
Swing traders who want to enter trades at the beginning of a new trend or after a confirmed trend reversal.
Day traders seeking clear and easy-to-read signals on intra-day charts, helping to pinpoint optimal entry and exit points during volatile market conditions.
Conclusion:
The Volume-Weighted MA Crossover is an essential tool for any trader looking to improve their trend-following strategy. By incorporating both volume and price action into a VWMA and SMA crossover , it offers a more refined approach to identifying and confirming trends. Whether you're a trend follower , swing trader , or day trader , this indicator provides clear, actionable signals backed by volume confirmation, giving you the confidence to execute your trades with precision.
Premarket VolumeTimeframe: Use on intraday charts (e.g., 1-minute, 5-minute) with extended hours enabled.
Behavior: The plot will appear at 4:00 AM, grow as volume accumulates, and disappear at 9:30 AM each day.
MFI Nexus Pro [trade_lexx]📈 MFI Nexus Pro is your reliable trading assistant!
📊 What is MFI Nexus Pro ?
MFI Nexus Pro is a trading indicator that analyzes cash flows in the market. It shows where money is moving — into or out of an asset, and based on this, generates buy or sell signals.
💡 The main components of the indicator
📊 The MFI Cash Flow Index (MFI)
shows the strength of cash flow into an asset. Values above 70 indicate overbought (an early sale is possible), and values below 30 indicate oversold (an early purchase is possible).
📈 Moving Averages (MA)
The indicator uses 10 different types of moving averages to smooth the MFI line.:
- SMA: Simple moving average
- EMA: Exponential moving average
- WMA: Weighted moving average
And other more complex types (HMA, KAMA, VWMA, ALMA, TEMA, ZLEMA, DEMA)
The choice of the type of moving average affects the speed of the indicator's response to market changes.
🎯 Bollinger Bands (BB)
Bands around the moving average that widen and narrow depending on volatility. They help determine when the MFI is out of the normal range.
🔄 Divergences
Divergences show discrepancies between price and MFI:
- Bullish divergence: the price is falling and the MFI is rising — an upward reversal is possible
- Bearish divergence: the price is rising and the MFI is falling — a downward reversal is possible
🔍 Indicator signals
1️⃣ Moving average signals (MA)
Buy signal
- What happens: MFI crosses its moving average from bottom to top
- What does it look like: the green triangle labeled "MA" under the chart
- What does it mean: money begins to actively flow into the asset, price growth is possible
Sell signal
- What happens: the MFI crosses the moving average from top to bottom
- What does it look like: a red triangle with the label "MA" above the chart
- What does it mean: money starts to leave the asset, the price may fall
2️⃣ Bollinger Band Signals (BB)
Buy signal
- What's happening: The MFI crosses the lower Bollinger band from bottom to top
- What it looks like: the green triangle marked "BB"
- What it means: The MFI was too low and is now starting to recover
Sell Signal
- What's going on: MFI crosses the upper Bollinger band from top to bottom
- What it looks like: a red triangle marked "BB"
- What it means: The MFI was too high and is now starting to decline
3️⃣ Divergence Signals (Div)
Buy Signal (Bullish Divergence)
- What's going on: the price is falling more than the MFI
- What it looks like: a green triangle marked "Div"
- What it means: despite the fall in price, money is already starting to return to the asset
Sell signal (bearish divergence)
- What is happening: the price is rising more strongly than the MFI
- What does it look like: the red triangle with the label "Div"
- What does it mean: despite the price increase, money is already starting to leave the asset
🛠️ Filters to filter out false signals
1️⃣ Minimum distance between the signals
- What it does: sets the minimum number of candles between signals
- Why it is needed: prevents signals from being too frequent during strong market fluctuations
- How to set it up: Set the number from 0 and above (default: 5)
2️⃣ "Waiting for the opposite signal" mode
- What it does: waits for a signal in the opposite direction before generating a new signal
- Why you need it: it helps you not to miss important trend reversals
- How to set up: just turn the function on or off
3️⃣ Filter by MFI levels
- What it does: generates signals only when the MFI is in the specified ranges
- Why it is needed: it helps to catch the moments when the market is oversold or overbought
- How to set up:
- For buy signals: set a range for oversold (e.g. 1-30)
- For sell signals: set a range for overbought (e.g. 70-100)
4️⃣ The RSI filter
- What it does: additionally checks the RSI values to confirm the signals
- Why it is needed: adds additional confirmation from another popular indicator
- How to set up: Similar to the MFI filter, set ranges for buying and selling
🔄 Signal combination modes
1️⃣ Normal mode ("None")
- How it works: all signals (MA, BB, Div) work independently of each other
- When to use it: for general market analysis or when learning how to work with the indicator
2️⃣ "And" mode ("MA and BB and Div")
- How it works: the alarm appears only when several conditions are triggered simultaneously
- Combination options:
- MA+BB: signals from the moving average and Bollinger bands
- MA+Div: signals from the moving average and divergence
- BB+Div: signals from the Bollinger bands and divergence
- MA+BB+Div: all three signals simultaneously
- When to use: for more reliable but rare signals
3️⃣ "OR" mode ("MA or BB or Div")
- How it works: the alarm appears when any of the conditions are triggered
- When to use: for frequent signals when you don't want to miss any opportunity.
🔌 Connecting to trading strategies
The indicator can be connected to your trading strategies using 5 different channels.:
1. Channel for MA signals: connects only signals from moving averages
2. BB signal channel: connects only the signals from the Bollinger bands
3. Channel for divergence signals: connects only divergence signals
4. Channel for "And" mode: connects only combined signals
5. Channel for "OR" mode: connects signals from any source
🔔 Setting up alerts
The indicator can send alerts when alarms appear.:
- Alerts for MA: when the MFI crosses the moving average
- Alerts for BB: when the MFI crosses the Bollinger bands
- Divergence alerts: when a divergence is detected
- Combined alerts: for "AND" and "OR" modes
🎭 What does the indicator look like on the chart ?
- MFI main line: purple line
- Overbought/oversold levels: horizontal lines at levels 30 and 70
- Middle line: dotted line at level 50
- MFI Moving Average: yellow line
- Bollinger bands: green lines around the moving average
- Signals: green and red triangles with corresponding labels
📚 How to start using MFI Nexus Pro
1️⃣ Initial setup
- Add an indicator to your chart
- Select the type of moving average and the period (you can leave it as the default)
- Activate the desired signal types (MA, BB, Div)
2️⃣ Filter settings
- Set the distance between the signals to get rid of unnecessary noise
- Adjust the MFI and RSI levels depending on how volatile your asset is
- If you need more reliable signals, turn on the "Waiting for the opposite signal" mode.
3️⃣ Operation mode selection
- First, use the standard mode to see all possible signals.
- When you get comfortable, try the "And" mode for more reliable signals.
- For active trading, you can use the "OR" mode
4️⃣ Setting up Alerts
- Select the types of signals you want to be notified about
- Set up alerts for "AND" or "OR" modes if you use them
5️⃣ Verification and adaptation
- Check the operation of the indicator on historical data
- Adjust the parameters for a specific asset
- Adapt the settings to your trading style
🌟 Usage examples
For trend trading
- Use MA signals in the direction of the main trend
- Turn on the "Waiting for the opposite signal" mode
- Set stricter levels for filters
For trading in a sideways range
- Use BB signals to detect bounces from the range boundaries
- Use the MFI level filter to confirm overbought/oversold conditions
- Adjust the Bollinger bands according to the width of the range
To determine the pivot points
- Pay attention to the divergence signals
- Use the "And" mode by combining divergences with other signals
- Check the RSI filter for additional confirmation
Smart Range Breakout - SwiftEdgeDescription:
The "Smart Range Breakout - SwiftEdge" indicator is a custom tool designed for identifying potential breakout opportunities on a 1-minute chart, with a focus on volatile markets like the DAX index. This script introduces a unique approach by combining range consolidation detection with volume confirmation and breakout validation, tailored for short-term trading strategies.
How It Works:
The indicator identifies consolidation periods where the price range (difference between the highest high and lowest low over a user-defined length) is below a multiple of the Average True Range (ATR). This helps detect periods of low volatility, which often precede breakouts.
Once a consolidation is confirmed (minimum number of bars), a green box is drawn on the chart, spanning a fixed length of bars (default 50), representing the potential breakout zone.
Breakouts are signaled only when a candle opens above the upper boundary (box top) or below the lower boundary (box bottom) of the consolidation box, ensuring a clear entry point based on price action at the open.
The script includes a volume filter, requiring volume to exceed a moving average by a specified multiplier, and a confirmation period to validate the breakout over consecutive bars.
To avoid signal clutter, only one breakout signal (up or down) is generated per box, and no further signals are issued until a new consolidation box is formed.
How to Use:
Apply the indicator to a 1-minute chart (optimized for DAX or similar volatile indices).
Adjust the "Consolidation Length" (default 5) to set the lookback period for detecting consolidation.
Modify the "Range Threshold (ATR Multiplier)" (default 2.0) to make the consolidation detection more or less strict based on market volatility.
Use "Minimum Consolidation Bars" (default 2) to set the minimum duration of a consolidation phase.
Tune "Confirmation Bars" (default 1) to require more bars to confirm the breakout.
Set "Volume MA Length" (default 5) and "Volume Multiplier" (default 1.1) to filter breakouts with insufficient volume.
Adjust "Max Box Length" (default 50) to control the duration of the breakout zone on the chart.
Look for green triangles below the chart for bullish breakouts and red triangles above for bearish breakouts, occurring when a candle opens outside the box with confirmed volume.
Originality:
This script stands out by integrating a fixed-length consolidation box with an opening-price breakout condition, combined with volume and multi-bar confirmation. Unlike traditional breakout indicators that rely solely on closing prices or simple price thresholds, this approach prioritizes the opening price and limits signals to one per cycle, reducing noise in volatile markets.
Chart Notes:
The accompanying chart displays the indicator's output with green boxes indicating consolidation zones, yellow dots marking consolidation periods, and green/red triangles for breakout signals. No additional scripts or unrelated drawings are included to ensure clarity.
Recency-Weighted Market Memory w/ Quantile-Based DriftRecency-Weighted Market Memory w/ Quantile-Based Drift
This indicator combines market memory, recency-weighted drift, quantile-based volatility analysis, momentum (RoC) filtering, and historical correlation checks to generate dynamic forecasts of possible future price levels. It calculates bullish and bearish forecast lines at each horizon, reflecting how the price might behave based on historical similarities.
Trading Concepts & Mathematical Foundations Explained
1) Market Memory
Concept:
Markets tend to repeat past behaviors under similar conditions. By identifying historical market states that closely match current conditions, we predict future price movements based on what happened historically.
Calculation Steps:
We select a historical lookback window (for example, 210 bars).
Each historical bar within this window is evaluated to see if its conditions match the current market. Conditions include:
Correlation between price change and bullish/bearish volume changes (over a user-defined correlation lookback period).
Momentum (Rate of Change, RoC) measured over a separate lookback period.
Only bars closely matching current conditions (within user-defined tolerance percentages) are included.
2) Recency-Weighted Drift
Concept:
Recent market movements often influence future direction. We assign more importance to recent bars to capture the current market bias effectively.
Calculation Steps:
Consider recent price changes between opens and closes for a user-defined drift lookback (for example, last 20 bars).
Give higher weight to recent bars (the most recent bar gets the highest weight, and weights decrease progressively for older bars).
Average these weighted changes separately for upward and downward movements, then combine these averages to calculate a final drift percentage relative to the current price.
3) Correlation Filtering
Concept:
Price changes often correlate strongly with bullish or bearish volume activity. By using historical correlation comparisons, we focus only on past market states with similar volume-price dynamics.
Calculation Steps:
Compute current correlations between price changes and bullish/bearish volume over the user-defined correlation lookback.
Evaluate each historical bar to see if its correlation closely matches the current correlation (within a user-specified percentage tolerance).
Only historical bars meeting this correlation criterion are selected.
4) Momentum (RoC) Filtering
Concept:
Two market periods may exhibit similar correlation structures but differ in how fast prices move (momentum). To ensure true similarity, momentum is checked as an additional filter.
Calculation Steps:
Compute the current Rate of Change (RoC) over the specified RoC lookback.
For each candidate historical bar, calculate its historical RoC.
Only include historical bars whose RoC closely matches the current RoC (within the RoC percentage tolerance).
5) Quantile-Based Volatility and Drift Amplification
Concept:
Quantiles (such as the 95th, 50th, and 5th percentiles) help gauge if current prices are near historical extremes or the median. Quantile bands measure volatility expansions and contractions.
Calculation Steps:
Calculate the 95%, 50%, and 5% quantiles of price over the quantile lookback period.
Add and subtract multiples of the standard deviation to these quantiles, creating upper and lower bands.
Measure the bands' widths relative to the current price as volatility indicators.
Determine the active quantile (95%, 50%, or 5%) based on proximity to the current price (within a percentage tolerance).
Compute the rate of change (RoC) of the active quantile to detect directional bias.
Combine volatility and quantile RoC into a scaling factor that amplifies or dampens expected price moves.
6) Expected Value (EV) Computation & Forecast Lines
Concept:
We forecast future prices based on how similarly-conditioned historical periods performed. We average historical moves to estimate the expected future price.
Calculation Steps:
For each forecast horizon (e.g., 1 to 27 bars ahead), collect all historical price moves that passed correlation and RoC filters.
Calculate average historical moves for bullish and bearish cases separately.
Adjust these averages by applying recency-weighted drift and quantile-based scaling.
Translate adjusted percentages into absolute future price forecasts.
Draw bullish and bearish forecast lines accordingly.
Indicator Inputs & Their Roles
Correlation Tolerance (%)
Adjusts how strictly the indicator matches historical correlation. Higher tolerance includes more matches, lower tolerance selects fewer but closer matches.
Price RoC Lookback and Price RoC Tolerance (%)
Controls how momentum (speed of price moves) is matched historically. Increasing tolerance broadens historical matches.
Drift Lookback (bars)
Determines the number of recent bars influencing current drift estimation.
Quantile Lookback Period and Std Dev Multipliers
Defines quantile calculation and the size of the volatility bands.
Quantile Contact Tolerance (%)
Sets how close the current price must be to a quantile for it to be considered "active."
Forecast Horizons
Specifies how many future bars to forecast.
Continuous Forecast Lines
Toggles between drawing continuous lines or separate horizontal segments for each forecast horizon.
Practical Trading Applications
Bullish & Bearish EV Lines
These forecast lines indicate expected price levels based on historical similarity. Green indicates positive expectations; red indicates negative.
Momentum vs. Mean Reversion
Wide quantile bands and high drift suggest momentum, while extremes may signal possible reversals.
Volatility Sensitivity
Forecasts adapt dynamically to market volatility. Broader bands increase forecasted price movements.
Filtering Non-Relevant Historical Data
By using both correlation and RoC filtering, irrelevant past periods are excluded, enhancing forecast reliability.
Multi-Timeframe Suitability
Adaptable parameters make this indicator suitable for different trading styles and timeframes.
Complementary Tool
This indicator provides probabilistic projections rather than direct buy or sell signals. Combine it with other trading signals and analyses for optimal results.
Important Considerations
While historically-informed forecasts are valuable, market behavior can evolve unpredictably. Always manage risks and use supplementary analysis.
Experiment extensively with input settings for your specific market and timeframe to optimize forecasting performance.
Summary
The Recency-Weighted Market Memory w/ Quantile-Based Drift indicator uniquely merges multiple sophisticated concepts, delivering dynamic, historically-informed price forecasts. By combining historical similarity, adaptive drift, momentum filtering, and quantile-driven volatility scaling, traders gain an insightful perspective on future price possibilities.
Feel free to experiment, explore, and enjoy this powerful addition to your trading toolkit!
Lemon/Lime Volume Lookback IndicatorThe indicator focuses on analyzing volume patterns.
It calculates a relative volume metric by comparing the current volume to a short-term simple moving average of volume.
The code identifies volume spikes when the relative volume exceeds a user-defined threshold.
These volume spikes are visually represented on the chart as small circles:
Yellow circles appear above bars for bearish volume spikes (when price closed lower)
Green circles appear below bars for bullish volume spikes (when price closed higher)
Users can adjust settings such as the lookback period for volume comparison and the percentage increase that defines a volume spike. This would adjust the readings based on incoming volume. Adjust as needed during different market conditions.
This tool essentially helps traders identify and visualize significant increases in trading volume compared to recent average volume, which could potentially signal important price movements or trend changes.
Volume-Price Divergence RSIUnderstanding the Display
Once added, you'll see a new panel below your price chart with:
Purple Line: This is the RSI (Relative Strength Index)
Red Dashed Line: The overbought threshold (default: 70)
Green Dashed Line: The oversold threshold (default: 30)
Blue Columns: Volume histogram
Dark Blue Line: Volume moving average
Trading Signals
Look for these markers on the indicator panel:
Green Triangle (↑): Buy signal - appears when there's a bullish divergence AND RSI conditions are met (oversold and rising)
Red Triangle (↓): Sell signal - appears when there's a bearish divergence AND RSI conditions are met (overbought and falling)
Lime Diamond (◆): Bullish divergence without RSI confirmation
Orange Diamond (◆): Bearish divergence without RSI confirmation
What These Signals Mean
Buy Signal (Green Triangle):
Price is making lower lows BUT volume is making higher lows
RSI is in oversold territory (below 30) and starting to rise
This suggests potential upward reversal
Sell Signal (Red Triangle):
Price is making higher highs BUT volume is making lower highs
RSI is in overbought territory (above 70) and starting to fall
This suggests potential downward reversal
Customizing the Indicator
To adjust settings:
Right-click on the indicator
Select "Settings"
In the "Inputs" tab, you can modify:
RSI Period (default: 14)
Volume MA Period (default: 20)
Lookback Period for finding pivot points (default: 10)
RSI Overbought level (default: 70)
RSI Oversold level (default: 30)
Setting Alerts
To get notified when a signal appears:
Right-click on the indicator
Select "Add Alert"
Choose the condition you want to be alerted for:
Buy Signal
Sell Signal
Bullish Divergence
Bearish Divergence
Configure notification preferences and save
Trading Strategy
This indicator is best used:
On higher timeframes (4H, Daily) for more reliable signals
As confirmation with other indicators or price action
At market extremes where divergences are more meaningful
With proper risk management (stop losses below recent swing lows for buys, above recent swing highs for sells)
Remember that no indicator is 100% accurate. This tool works by identifying situations where price movement isn't confirmed by volume, suggesting a potential reversal, especially when RSI conditions align.
Valerio Diotallevi
Volume with Sessions, SMA, and ATR Pine Script creates a custom volume indicator with several features, including:
SMA of Volume: It calculates the simple moving average (SMA) of the volume, which helps identify trends and determine if the current volume is above or below the average.
ATR (Average True Range): It calculates the ATR, which measures market volatility over a defined period.
Bullish/Bearish Volume Coloring: The script colors the volume bars depending on whether the price is moving up (bullish) or down (bearish), and whether the volume is above or below the SMA of volume.
Session Highlighting: It defines two major trading sessions:
NYSE (New York Stock Exchange) session from 9:30 AM to 4:00 PM Eastern Time.
LSE (London Stock Exchange) session from 8:00 AM to 4:30 PM GMT. These sessions are highlighted with background colors for easy identification.
Plotting: The volume is plotted as a histogram with varying colors depending on price movement and volume relative to its SMA. The ATR is also plotted as a purple line, and the SMA of volume is displayed as an orange line.
Background Colors: Background colors are applied during the NYSE and LSE sessions to visually differentiate between these trading periods.
Here's a breakdown of each section:
Key Inputs:
smaLength and atrLength: User-defined values for the lengths of the SMA and ATR calculations.
Main Calculations:
smaVolume: The SMA of the volume over the user-defined length (smaLength).
atrValue: The Average True Range over the user-defined length (atrLength).
Color Logic for Volume Bars:
If the current close is higher than the previous close, the volume is considered bullish, and the bar is colored green. If the volume is above the SMA, it’s a darker green; otherwise, it’s a lighter shade.
If the current close is lower than the previous close, the volume is considered bearish, and the bar is colored red. If the volume is above the SMA, it’s a darker red; otherwise, it’s a lighter red.
Plotting:
The script plots the volume as a histogram with dynamic coloring.
The SMA of the volume is plotted as a line.
ATR is plotted as a purple line for reference.
Background Color Highlighting:
The background is colored green during the NYSE session and blue during the LSE session.
PVSRA Volume Suite with Volume DeltaPVSRA Volume Suite with Volume Delta
🔹 Overview
This indicator is a Volume Suite that enhances PVSRA (Price, Volume, Support, Resistance Analysis) by incorporating Volume Delta and AI-driven predictive alerts. It is designed to help traders analyze volume pressure, market trends, and price movements with color-coded visualizations.
📌 Key Features
PVSRA Volume Color Coding – Highlights vector candles based on extreme volume/spread conditions.
Volume Delta Analysis – Tracks buying/selling pressure using up/down volume data.
AI-Powered Predictive Alerts – Identifies potential trend shifts based on volume and trend context.
Volatility-Adjusted Thresholds – Dynamically adapts volume conditions based on ATR (Average True Range).
Customizable MA & Symbol Overrides – Allows traders to tweak settings for personalized market insights.
Debug & Diagnostic Labels – Shows statistical z-scores, thresholds, and volume dynamics.
How It Works
PVSRA Color Coding – The script classifies candles into four categories based on volume and spread analysis:
🔴 Red Vector → Extreme bearish volume/spread
🟢 Green Vector → Extreme bullish volume/spread
🟣 Violet Vector → Above-average bearish volume
🔵 Blue Vector → Above-average bullish volume
Volume Delta Calculation – Uses lower timeframe volume analysis to estimate up/down volume differentials.
Trend & Predictive Alerts – Combines EMA crossovers with statistical volume analysis to detect potential trend shifts.
Volatility Adaptation – Adjusts volume thresholds based on ATR, making signals more reliable in changing market conditions.
Custom Symbol Override – Fetches PVSRA data from a different instrument, useful for index-based volume analysis.
Customizable Inputs
PVSRA Color Settings – Modify candle color schemes for better visual clarity.
Volume Delta Colors – Customize delta volume body, wick, and border colors.
AI Settings – Tune z-score thresholds, lookback periods, and enable predictive alerts.
Symbol Overrides – Analyze volume from a different market or asset.
Moving Average (MA) Settings – Display a volume-based moving average for trend confirmation.
Important Notes
Works best on intraday timeframes where volume data is reliable.
Lower timeframe volume delta estimates might not be precise for all assets.
No guarantees of accuracy – Use alongside other confluence tools for decision-making.
Credits & Open-Source Notice
This script is based on PVSRA methodologies and integrates Volume Delta analysis. Special thanks to Traders Reality and TradingView for their contributions to volume-based analysis.
Liquidity Zones [ActiveQuants]The Liquidity Zones indicator detects price areas where high trading volume coincides with below-average volatility , critical zones where large players often accumulate or distribute positions. Ideal for spotting potential reversal points and strategic liquidity pools.
Core Detection Formula
Liquidity Zone = (Volume > SMA(Volume, Length) × Multiplier) AND (Short-Term Volatility < 0.5 × Average Volatility)
Volume Surge Detection
Compares current volume to its SMA (user-defined length).
Multiplies threshold with " Volume Threshold Multiplier " parameter.
Volatility Contraction Filter
Calculates 5-bar volatility (standard deviation of closes).
Compares to average volatility over " Price Std. Dev. Length " period.
Requires short-term volatility < 50% of average.
█ KEY FEATURES
Merging Consecutive Zones
If the " Merge Consecutive Zones " option is enabled, the indicator will:
Calculate the number of consecutive bars that meet the liquidity zone criteria.
Sum the volume of these consecutive bars.
Display only the most recent label for the merged zone (previous labels in the sequence are removed).
Displays volume in either
Raw units (" Units ").
Dollar-equivalent (" Currency Value ") using closing price.
Alerts
An alert condition is built into the script. Traders can selectively enable alerts via TradingView’s alert system. Whenever a liquidity zone is detected, an alert is triggered with the message: " High-volume and low-volatility zone detected! ".
█ USER INPUTS
- Liquidity Zones Color
Sets the background color for liquidity zones.
Default: Orange (with 70 transparency).
- Volume SMA Length
Determines the number of bars over which the volume simple moving average is calculated.
Default: 20 bars.
- Volume Threshold Multiplier
Multiplies the volume SMA to establish a threshold. A bar’s volume must exceed this product to be considered high volume.
Default: 2.0.
- Price Std. Dev. Length
The period used to calculate the standard deviation of the closing prices. This is the basis for measuring average volatility.
Default: 14 bars.
- Zone Volume
A toggle to display a label with the volume value on liquidity zones.
Allows you to choose how the volume is displayed: Units (shows raw volume) or Currency Value (multiplies volume by the current closing price).
Allows you to choose the font size of the volume label.
- Merge Consecutive Zones
When enabled, volumes from consecutive liquidity zones are summed into a single total, and only the most recent label is displayed (previous labels in the sequence are removed).
Default: Enabled.
- Show Last
Specifies the number of bars back that the indicator will evaluate and plot liquidity zones.
Default: 500 bars.
- Timeframe
Analysis period.
Default: Chart.
█ CONCLUSION
The Liquidity Zones indicator is a powerful tool for traders seeking to identify key areas on the chart where liquidity is concentrated, characterized by high volume and low volatility . With customizable settings for volume analysis and volatility measurement , this indicator can be integrated into a wide range of trading strategies. It not only highlights these zones visually but also provides volume data labels and alerts for timely decision-making.
█ IMPORTANT NOTES
⚠ Volume and Volatility Settings: Adjust the Volume SMA Length , Volume Threshold Multiplier , and Price Std. Dev. Length to suit the typical trading volume and volatility of the asset you are analyzing.
⚠ Confirmed Bars Only: Signals are generated only on confirmed bars. This minimizes false signals due to intra-bar noise and also prevents indicator repainting .
⚠ Risk Management: Liquidity zones may signal areas of potential accumulation or distribution, but they should be used in conjunction with other technical analysis tools (e.g., support/resistance levels, trendlines, or momentum indicators). Trading involves risk, and it is recommended to combine this indicator with proper risk management techniques.
█ RISK DISCLAIMER
Trading involves substantial risk of loss. Liquidity zones indicate potential interest areas but don't guarantee price reactions. Always confirm with additional analysis and proper risk management. Past performance is not indicative of future results.
📈 Happy trading! 🚀
Normalized VolumeOVERVIEW
The Normalized Volume (NV) is an attempt at visualizing volume in a format that is more understandable by placing the values on a scale of 0 to 100. 0 in this case is the lowest volume candle available on the chart, and 100 being the highest. Calling a candle “high volume” can be misleading without having something to compare to. For example, in scaling the volume this way we can clearly see that a given candle had 80% of the peak volume or 20%, and gauge the validity of price moves more accurately.
FEATURES
NV by session
Allows user to filter the volume values across 4 different sessions. This can add context to the volume output, because what it high volume during London session may not be high volume relative to New York session.
Overlay plotting
When volume boxes are turned on, this will allow you to toggle how they are plotted.
Color theme
A standard color theme will color the NV based on if the respective candle closed green or red. Selecting variables will color the NV plot based on which range the value falls within.
Session inputs
Activated with the “By session?” Input. Allows user to break the day up into 4 sessions to more accurately gauge volume relative to time of day.
Show Box (X)
Toggles on chart boxes on and off.
Show historical boxes
Will plot prior occurrences of selected volume boxes, deleting them when price fully moves through them in the opposite direction of the initial candle.
Color inputs
Allows for intensive customization in how this tool appears visually.
INTERPRETATION
There are 6 pre-defined ranges that NV can fall within.
NV <= 10
Volume is insignificant
In this range, volume should not be a confirmation in your trading strategy.
NV > 10 and <= 20
Volume is low
In this range, volume should not be a confirmation in your trading strategy.
NV > 20 and <= 40
Volume is fair
In this range, volume should not be the primary confirmation in your trading strategy.
NV > 40 and <= 60
Volume is high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 60 and <= 80
Volume is very high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 80
Volume is extreme
In this range, volume is likely news driven and caution should be taken. High price volatility possible.
To utilize this tool in conjunction with your current strategy, follow the range explanations above section in this section. The higher the NV value, the stronger you can feel about your directional confirmation.
If NV = 100, this means that the highest volume candle occurred up to that point on your selected timeframe. All future data points will be weighed off of this value.
LIMITATIONS
This tool will not load on tickers that do not have volume data, such as VIX.
STRATEGY
The Normalized Volume plot can be used in exactly the same way as you would normally utilize volume in your trading strategy. All we are doing is weighing the volume relative to itself.
Volume boxes can be used as targets to be filled in a similar way to commonly used “fair value gap” strategies. To utilize this strategy, I recommend selecting “Plot to Wicks” in Overlay Plotting and toggling on Show Historical Boxes.
Volume boxes can be used as areas for entry in a similar way to commonly used “order block” strategies. To utilize this strategy, I recommend selecting “Open To Close” in Overlay Plotting.
NOTES
You are able to plot an info label on right side of NV plot using the "Toggle box label" input. When a box is toggled on this label will tell you when the most recent box of that intensity occurred.
This tool is deeply visually customizable, with the ability to adjust line width for plotted boxes, all colors on both box overlays, and all colors on NV panel. Customize it to your liking!
I have a handful of additional features that I plan on adding to this tool in future updates. If there is anything you would like to see added, any bugs you identify, or any strategies you encounter with this tool, I would love to hear from you!
Huge shoutout to @joebaus for assisting in bringing this tool to life, please check out his work here on TradingView!
Pivot P/N VolumesTitle: Pivot P/N Volumes
Short Title: PPNV
Description:
The "Pivot P/N Volumes" indicator is a minimalistic volume analysis tool designed to cut through market noise and highlight key volume events in a separate pane. It strips away conventional volume clutter, focusing on four distinct volume types with clear visual cues, making it ideal for traders seeking actionable insights without distractions.
Key Features:
Blue Bars: Pocket Pivot Volumes (PPV) - Up-day volumes exceeding the highest down-day volume of the last 10 down-days, signaling potential bullish strength.
Orange Bars: Pivot Negative Volumes - Down-day volumes greater than the highest up-day volume of the last 10 up-days, indicating significant bearish pressure.
Red Bars: Down-day volumes above the 50-period EMA of volume, highlighting above-average selling activity.
Green Bars: Up-day volumes above the 50-period EMA of volume, showing above-average buying interest.
Noise: All other volumes are muted as dark grey (down-days) or light grey (up-days) for easy filtering.
Range Breakout Signals [AlgoAlpha]OVERVIEW
This script detects range-bound market conditions and breakout signals using a combination of volatility compression and volume imbalance analysis. It identifies zones where price consolidates within a defined range and highlights potential breakout points with visual markers. Traders can use this to spot market transitions from ranging to trending phases, aiding in decision-making for breakout strategies.
CONCEPTS
The script measures volatility by comparing the ratio of the simple moving average (SMA) of price movements to their median value. When volatility drops below a threshold, the script assumes a range-bound market. It then tracks the cumulative volume of buying and selling pressure to assess breakout strength. The approach is based on the idea that market consolidation often precedes strong moves, and volume distribution can provide clues on the breakout direction.
FEATURES
Range Detection : Uses a volatility filter to identify low-volatility zones and marks them on the chart with shaded boxes.
Volume Imbalance Analysis : Evaluates cumulative up and down volume over a confirmation period to assess directional bias.
Breakout Signals : When price exits a detected range, the script plots breakout markers. A ▲ symbol indicates a bullish breakout, and a ▼ symbol indicates a bearish breakout. Additional "+" markers indicate strong volume imbalance favoring the breakout direction.
Adaptive Timeframe Volume Analysis : The script dynamically adjusts its volume calculation based on the chart’s timeframe, ensuring reliable signal generation across different trading conditions.
Alerts : Notifies traders when a new range is detected or when a breakout occurs, allowing for automated monitoring.
USAGE
Traders can use this script to identify potential trade setups by entering positions when price breaks out of a detected range. For breakout confirmation, traders can look at volume imbalance cues—bullish breakouts with strong buying volume may indicate sustained moves, while weak volume breakouts may lead to false signals. This script is particularly useful for breakout traders, range traders seeking to fade breakouts, and those looking to automate trade alerts in volatile markets.
Parabolic SAR Deviation [BigBeluga]Parabolic SAR + Deviation is an enhanced Parabolic SAR indicator designed to detect trends while incorporating deviation levels and trend change markers for added depth in analyzing price movements.
🔵 Key Features:
> Parabolic SAR with Optimized Settings:
Built on the classic Parabolic SAR, this version uses predefined default settings to enhance its ability to detect and confirm trends.
Clear trend direction is indicated by smooth trend lines, allowing traders to easily visualize market movements.
Trend Change Markers:
When a trend change occurs based on the SAR, the indicator plots a triangle at the trend change point.
The triangle is accompanied by the price value of the trend change, allowing traders to identify key reversal points instantly.
> Deviation Levels:
Four deviation levels are automatically plotted when a trend change occurs (up or down).
Uptrend: Deviation levels are positioned above the entry point.
Downtrend: Deviation levels are positioned below the entry point.
Levels are labeled with numbers 1 to 4, representing increasing degrees of deviation.
> Dynamic Level Updates:
When the price crosses a deviation level, the level becomes dashed and its label changes to display the volume at the breakout point.
This volume information helps traders assess the strength of the breakout and the potential for trend continuation or reversal.
> Volume Analysis at Breakpoints:
The volume displayed at crossed deviation levels provides insight into the strength of the price movement.
High volume at a breakout may indicate strong momentum, while low volume could signal potential exhaustion or a false breakout.
🔵 Usage:
Identify Trends: Use the trend change triangles and smooth SAR trend lines to confirm whether the market is trending up or down.
Analyze Deviation Levels: Monitor deviation levels **1–4** to identify potential breakout points and assess the degree of price deviation from the entry point.
Observe Trend Change Points: Utilize the triangles and price labels to quickly spot significant trend changes.
Volume Insights: Evaluate the volume displayed at crossed levels to determine the strength of the breakout and assess the likelihood of trend continuation or reversal.
Risk Management: Use deviation levels as potential stop-loss or take-profit zones, depending on the strength of the trend and volume conditions.
Parabolic SAR + Deviation is an essential tool for traders seeking a straightforward yet powerful method to identify trends, analyze price deviations, and gain insights into volume dynamics at critical breakout and trend change levels.
Volume Buy/Sell ChartVolume Buy/Sell Chart
This script visualizes the distribution of buying and selling volume within each candlestick, helping traders identify dominant market pressure at a glance. It separates volume into Buy Volume (Green) and Sell Volume (Red) using a unique calculation based on price movement within a candle.
Features:
✅ Customizable Bar Display: Choose to display 5, 10, or 100 bars using a simple dropdown selection.
✅ Buy & Sell Volume Calculation: The script determines buying and selling volume dynamically based on price action within the candle.
✅ Custom Volume Threshold for Alerts: Set a percentage threshold (0–100) to trigger alerts when buy or sell volume exceeds a predefined level.
✅ Color-Coded Histogram:
Green Bars: Represent the estimated buy volume.
Red Bars: Represent the estimated sell volume.
✅ Alerts Integration: Automatically detect strong buy or sell signals when the respective volume percentage exceeds your set threshold.
How It Works:
The script calculates total price movement within a candle.
It then estimates buying and selling volume ratios based on whether the price closes higher or lower than it opened.
Finally, it normalizes the buy/sell volume against the total volume and plots it as a column chart.
Usage Guide:
Add the script to your chart.
Select how many bars to display (5, 10, or 100).
Adjust the Custom Volume Percentage Threshold (default: 75%).
Watch for significant buy/sell volume imbalances that might indicate market turning points!
This tool is great for traders looking to analyze volume flow and market sentiment with a simple yet effective visualization. 🚀
Volume +OBV + ADXVolume + OBV + ADX Table
Optimized Buyer & Seller Volume with Trend Indications
Overview:
This indicator provides a comprehensive view of market participation and trend strength by integrating Volume, On Balance Volume (OBV) trends, and ADX (Average Directional Index) signals into a visually structured table. Designed for quick decision-making, it highlights buyer and seller dominance while comparing the selected stock with another custom symbol.
Features:
✅ Buyer & Seller Volume Analysis:
Computes buyer and seller volume percentages based on market movements.
Displays daily cumulative volume statistics to assess ongoing market participation.
✅ On Balance Volume (OBV) Trends:
Identifies positive, negative, or neutral OBV trends using an advanced smoothing mechanism.
Highlights accumulation or distribution phases with colored visual cues.
✅ ADX-Based Trend Confirmation:
Evaluates Directional Indicators (DI+ and DI-) to determine the trend direction.
Uses customizable ADX settings to filter out weak trends.
Provides uptrend, downtrend, or neutral signals based on strength conditions.
✅ Custom Symbol Comparison:
Allows users to compare two different assets (e.g., a stock vs. an index or ETF).
Displays a side-by-side comparison of volume dynamics and trend strength.
✅ User-Friendly Table Display:
Presents real-time calculations in a compact and structured table format.
Uses color-coded trend signals for easier interpretation.
Recommended Usage for Best Results:
📌 Pairing this indicator with Sri_Momentum and Sri(+) Pivot will enhance accuracy and provide better trade confirmations.
📌 Adding other major indicators like RSI, CCI, etc., will further increase the probability of winning trades.
How to Use:
Select a custom symbol for comparison.
Adjust ADX settings based on market conditions.
Analyze the table to identify buyer/seller dominance, OBV trends, and ADX trend strength.
Use the combined signals to confirm trade decisions and market direction.
Best Use Cases:
🔹 Trend Confirmation – Validate breakout or reversal signals.
🔹 Volume Strength Analysis – Assess buyer/seller participation before entering trades.
🔹 Multi-Asset Comparison – Compare the behavior of two related instruments.
This indicator is ideal for traders looking to combine volume dynamics with trend-following strategies. 🚀📈
PVSRA v5Overview of the PVSRA Strategy
This strategy is designed to detect and capitalize on volume-driven threshold breaches in price candles. It operates on the premise that when a high-volume candle breaks a critical price threshold, not all orders are filled within that candle’s range. This creates an imbalance—similar to a physical system being perturbed—causing the price to revert toward the level where the breach occurred to “absorb” the residual orders.
Key Features and Their Theoretical Underpinnings
Dynamic Volume Analysis and Threshold Detection
Volume Surges as Market Perturbations:
The script computes a moving average of volume over a short window and flags moments when the current volume significantly exceeds this average. These surges act as a perturbation—injecting “energy” into the market.
Adaptive Abnormal Volume Threshold:
By calculating a dynamic abnormal threshold using a daily volume average (via an 89-period VWMA) and standard deviation, the strategy identifies when the current volume is abnormally high. This mechanism mirrors the idea that when a system is disturbed (here, by a volume surge), it naturally seeks to return to equilibrium.
Candle Coloring and Visual Signal Identification
Differentiation of Candle Types:
The script distinguishes between bullish (green) and bearish (red) candles. It applies different colors based on the strength of the volume signal, providing a clear, visual representation of whether a candle is likely to trigger a price reversion.
Implication of Unfilled Orders:
A red (bearish) candle with high volume implies that sell pressure has pushed the price past a critical threshold—yet not all buy orders have been fulfilled. Conversely, a green (bullish) candle indicates that aggressive buying has left pending sell orders. In both cases, the market is expected to reverse toward the breach point to restore balance.
Trade Execution Logic: Normal and Reversal Trades
Normal Trades:
When a high-volume candle breaches a threshold and meets the directional conditions (e.g., a red candle paired with price above a daily upper band), the strategy enters a trade anticipating a reversion. The underlying idea is that the market will move back to the level where the threshold was crossed—clearing the residual orders in a manner analogous to a system following the path of least resistance.
Reversal Trades:
The strategy also monitors for clusters of consecutive signals within a short lookback period. When multiple signals accumulate, it interprets this as the market having overextended and, in a corrective move, reverses the typical trade direction. This inversion captures the market’s natural tendency to “correct” itself by moving in discrete, quantized steps—each step representing the absorption of a minimum quantum of order imbalance.
Risk and Trade Management
Stop Loss and Take Profit Buffers:
Both normal and reversal trades include predetermined buffers for stop loss and take profit levels. This systematic risk management approach is designed to capture the anticipated reversion while minimizing potential losses, aligning with the idea that market corrections follow the most energy-efficient path back to equilibrium.
Symbol Flexibility:
An option to override the chart’s symbol allows the strategy to be applied consistently across different markets, ensuring that the volume and price dynamics are analyzed uniformly.
Conceptual Bridge: From Market Dynamics to Trade Execution
At its core, the strategy treats market price movements much like a physical system that seeks to minimize “transactional energy” or inefficiency. When a price candle breaches a key threshold on high volume, it mimics an injection of energy into the system. The subsequent price reversion is the market’s natural response—moving in the most efficient path back to balance. This perspective is akin to the principle of least action, where the system evolves along the trajectory that minimizes cumulative imbalance, and it acknowledges that these corrections occur in discrete steps reflective of quantized order execution.
This unified framework allows the PVSRA strategy to not only identify when significant volume-based threshold breaches occur but also to systematically execute trades that benefit from the expected corrective moves.
Volume Block Order AnalyzerCore Concept
The Volume Block Order Analyzer is a sophisticated Pine Script strategy designed to detect and analyze institutional money flow through large block trades. It identifies unusually high volume candles and evaluates their directional bias to provide clear visual signals of potential market movements.
How It Works: The Mathematical Model
1. Volume Anomaly Detection
The strategy first identifies "block trades" using a statistical approach:
```
avgVolume = ta.sma(volume, lookbackPeriod)
isHighVolume = volume > avgVolume * volumeThreshold
```
This means a candle must have volume exceeding the recent average by a user-defined multiplier (default 2.0x) to be considered a significant block trade.
2. Directional Impact Calculation
For each block trade identified, its price action determines direction:
- Bullish candle (close > open): Positive impact
- Bearish candle (close < open): Negative impact
The magnitude of impact is proportional to the volume size:
```
volumeWeight = volume / avgVolume // How many times larger than average
blockImpact = (isBullish ? 1.0 : -1.0) * (volumeWeight / 10)
```
This creates a normalized impact score typically ranging from -1.0 to 1.0, scaled by dividing by 10 to prevent excessive values.
3. Cumulative Impact with Time Decay
The key innovation is the cumulative impact calculation with decay:
```
cumulativeImpact := cumulativeImpact * impactDecay + blockImpact
```
This mathematical model has important properties:
- Recent block trades have stronger influence than older ones
- Impact gradually "fades" at rate determined by decay factor (default 0.95)
- Sustained directional pressure accumulates over time
- Opposing pressure gradually counteracts previous momentum
Trading Logic
Signal Generation
The strategy generates trading signals based on momentum shifts in institutional order flow:
1. Long Entry Signal: When cumulative impact crosses from negative to positive
```
if ta.crossover(cumulativeImpact, 0)
strategy.entry("Long", strategy.long)
```
*Logic: Institutional buying pressure has overcome selling pressure, indicating potential upward movement*
2. Short Entry Signal: When cumulative impact crosses from positive to negative
```
if ta.crossunder(cumulativeImpact, 0)
strategy.entry("Short", strategy.short)
```
*Logic: Institutional selling pressure has overcome buying pressure, indicating potential downward movement*
3. Exit Logic: Positions are closed when the cumulative impact moves against the position
```
if cumulativeImpact < 0
strategy.close("Long")
```
*Logic: The original signal is no longer valid as institutional flow has reversed*
Visual Interpretation System
The strategy employs multiple visualization techniques:
1. Color Gradient Bar System:
- Deep green: Strong buying pressure (impact > 0.5)
- Light green: Moderate buying pressure (0.1 < impact ≤ 0.5)
- Yellow-green: Mild buying pressure (0 < impact ≤ 0.1)
- Yellow: Neutral (impact = 0)
- Yellow-orange: Mild selling pressure (-0.1 < impact ≤ 0)
- Orange: Moderate selling pressure (-0.5 < impact ≤ -0.1)
- Red: Strong selling pressure (impact ≤ -0.5)
2. Dynamic Impact Line:
- Plots the cumulative impact as a line
- Line color shifts with impact value
- Line movement shows momentum and trend strength
3. Block Trade Labels:
- Marks significant block trades directly on the chart
- Shows direction and volume amount
- Helps identify key moments of institutional activity
4. Information Dashboard:
- Current impact value and signal direction
- Average volume benchmark
- Count of significant block trades
- Min/Max impact range
Benefits and Use Cases
This strategy provides several advantages:
1. Institutional Flow Detection: Identifies where large players are positioning themselves
2. Early Trend Identification: Often detects institutional accumulation/distribution before major price movements
3. Market Context Enhancement: Provides deeper insight than simple price action alone
4. Objective Decision Framework: Quantifies what might otherwise be subjective observations
5. Adaptive to Market Conditions: Works across different timeframes and instruments by using relative volume rather than absolute thresholds
Customization Options
The strategy allows users to fine-tune its behavior:
- Volume Threshold: How unusual a volume spike must be to qualify
- Lookback Period: How far back to measure average volume
- Impact Decay Factor: How quickly older trades lose influence
- Visual Settings: Labels and line width customization
This sophisticated yet intuitive strategy provides traders with a window into institutional activity, helping identify potential trend changes before they become obvious in price action alone.
Advanced Adaptive Grid Trading StrategyThis strategy employs an advanced grid trading approach that dynamically adapts to market conditions, including trend, volatility, and risk management considerations. The strategy aims to capitalize on price fluctuations in both rising (long) and falling (short) markets, as well as during sideways movements. It combines multiple indicators to determine the trend and automatically adjusts grid parameters for more efficient trading.
How it Works:
Trend Analysis:
Short, long, and super long Moving Averages (MA) to determine the trend direction.
RSI (Relative Strength Index) to identify overbought and oversold levels, and to confirm the trend.
MACD (Moving Average Convergence Divergence) to confirm momentum and trend direction.
Momentum indicator.
The strategy uses a weighted scoring system to assess trend strength (strong bullish, moderate bullish, strong bearish, moderate bearish, sideways).
Grid System:
The grid size (the distance between buy and sell levels) changes dynamically based on market volatility, using the ATR (Average True Range) indicator.
Grid density also adapts to the trend: in a strong trend, the grid is denser in the direction of the trend.
Grid levels are shifted depending on the trend direction (upwards in a bear market, downwards in a bull market).
Trading Logic:
The strategy opens long positions if the trend is bullish and the price reaches one of the lower grid levels.
It opens short positions if the trend is bearish and the price reaches one of the upper grid levels.
In a sideways market, it can open positions in both directions.
Risk Management:
Stop Loss for every position.
Take Profit for every position.
Trailing Stop Loss to protect profits.
Maximum daily loss limit.
Maximum number of positions limit.
Time-based exit (if the position is open for too long).
Risk-based position sizing (optional).
Input Options:
The strategy offers numerous settings that allow users to customize its operation:
Timeframe: The chart's timeframe (e.g., 1 minute, 5 minutes, 1 hour, 4 hours, 1 day, 1 week).
Base Grid Size (%): The base size of the grid, expressed as a percentage.
Max Positions: The maximum number of open positions allowed.
Use Volatility Grid: If enabled, the grid size changes dynamically based on the ATR indicator.
ATR Length: The period of the ATR indicator.
ATR Multiplier: The multiplier for the ATR to fine-tune the grid size.
RSI Length: The period of the RSI indicator.
RSI Overbought: The overbought level for the RSI.
RSI Oversold: The oversold level for the RSI.
Short MA Length: The period of the short moving average.
Long MA Length: The period of the long moving average.
Super Long MA Length: The period of the super long moving average.
MACD Fast Length: The fast period of the MACD.
MACD Slow Length: The slow period of the MACD.
MACD Signal Length: The period of the MACD signal line.
Stop Loss (%): The stop loss level, expressed as a percentage.
Take Profit (%): The take profit level, expressed as a percentage.
Use Trailing Stop: If enabled, the strategy uses a trailing stop loss.
Trailing Stop (%): The trailing stop loss level, expressed as a percentage.
Max Loss Per Day (%): The maximum daily loss, expressed as a percentage.
Time Based Exit: If enabled, the strategy exits the position after a certain amount of time.
Max Holding Period (hours): The maximum holding time in hours.
Use Risk Based Position: If enabled, the strategy calculates position size based on risk.
Risk Per Trade (%): The risk per trade, expressed as a percentage.
Max Leverage: The maximum leverage.
Important Notes:
This strategy does not guarantee profits. Cryptocurrency markets are volatile, and trading involves risk.
The strategy's effectiveness depends on market conditions and settings.
It is recommended to thoroughly backtest the strategy under various market conditions before using it live.
Past performance is not indicative of future results.
Ultimate Trend Strength Meter Using TechnoBloom’s IndicatorsOverview
The Ultimate Trend Strength Meter Using TechnoBloom’s Indicators is a powerful trend analysis tool developed using TechnoBloom’s proprietary indicators. This indicator helps traders assess trend strength, momentum, and potential reversals by combining three essential market factors:
• Market Participation Ratio (MPR) – Measures trader engagement and volume strength.
• Volume Weighted Moving Average (VWMO) – Confirms momentum and trend direction.
• Fibonacci-Based Support & Resistance – Identifies key reversal zones and breakout points.
⸻
Key Features:
✅ Color-Coded Trend Strength Meter:
• 🟢 Green – Strong Trend (High Confidence): High participation, strong momentum, and no major resistance.
• 🟡 Yellow – Weak Trend (Caution): Moderate participation, possible resistance ahead, and trend uncertainty.
• 🔴 Red – Reversal Risk / No Trend: Low market engagement, momentum uncertainty, and proximity to major Fibonacci levels.
✅ Eliminates False Signals & Weak Trends:
• Prevents choppy market entries by ensuring high-volume confirmation.
• Ideal for filtering fake breakouts and exhaustion phases.
✅ Works for All Trading Styles & Markets:
• Scalping (1m-5m), Day Trading (15m-1H), and Swing Trading (4H-Daily).
• Suitable for Forex, Stocks, Crypto, Indices, and Commodities (XAUUSD, US30, BTCUSD, etc.).
✅ Customizable for Any Strategy:
• Adjustable MPR thresholds, VWMO smoothing, and Fibonacci sensitivity.
• Built-in alerts notify traders when trend conditions change.
⸻
How to Use It:
1️⃣ Enter trades when the meter turns Green (Strong Trend) and aligns with your strategy.
2️⃣ Avoid or exit trades when it turns Red (Reversal Risk) to prevent unnecessary losses.
3️⃣ Use Yellow as a caution zone – wait for confirmation before making a move.
4️⃣ Combine with breakout strategies or support/resistance setups for high-probability entries.
⸻
About TechnoBlooms
TechnoBlooms is committed to developing high-precision trading indicators that enhance decision-making for traders across all markets. This tool is a result of our in-depth market research and algorithmic advancements to provide traders with an edge.
🚀 Upgrade your trading with the Ultimate Trend Strength Meter – Developed by TechnoBlooms! 🚀
VSA Volume + Fibonacci (Volunacci)Overview
This indicator combines Volume Spread Analysis (VSA) with Fibonacci levels to identify key price zones based on volume behavior. It helps traders determine potential support and resistance levels influenced by volume strength.
How It Works
Volume Calculation
The indicator calculates volume levels based on the selected timeframe.
It identifies high volume spikes and low volume dips, which are critical for detecting supply and demand shifts.
It uses a simple moving average (SMA) of volume to smooth fluctuations.
Fibonacci Levels Integration
When a high-volume event is detected, the indicator records the highest high and lowest low of that candle.
It then plots Fibonacci retracement and extension levels to highlight potential price reaction zones.
Negative Fibonacci levels are included to identify possible deep retracements.
Visual Features
The indicator adapts to both light and dark themes for better visibility.
Fibonacci lines are color-coded based on key retracement and extension levels.
A table displaying key Fibonacci levels and their corresponding prices is provided for quick reference.
Why Is This Indicator Useful?
It helps traders spot accumulation and distribution phases by analyzing volume at key price points.
The combination of VSA and Fibonacci allows traders to confirm trend strength and identify potential reversal points.
Works well for trend-following strategies, scalping, and breakout trading.
How to Use This Indicator?
Use it to confirm breakouts or reversals at Fibonacci levels when volume supports the move.
Watch for high-volume spikes near key Fibonacci zones—these can signal strong trend continuation or reversal.
Use the displayed Fibonacci table to quickly assess price reaction levels.
Credits
This script was inspired by the Hidden Gap’s VSA Volume indicator by HPotter and has been enhanced by integrating Fibonacci-based analysis.
XGBoost Approximation Indicator with HTF Filter Ver. 3.2XGBoost Approx Indicator with Higher Timeframe Filter Ver. 3.2
What It Is
The XGBoost Approx Indicator is a technical analysis tool designed to generate trading signals based on a composite of multiple indicators. It combines Simple Moving Average (SMA), Relative Strength Index (RSI), MACD, Rate of Change (ROC), and Volume to create a composite indicator score. Additionally, it incorporates a higher timeframe filter (HTF) to enhance trend confirmation and reduce false signals.
This indicator helps traders identify long (buy) and short (sell) opportunities based on a weighted combination of trend-following and momentum indicators.
How to Use It Properly
Setup and Configuration:
Add the indicator to your TradingView chart.
Customize input settings based on your trading strategy. Key configurable inputs include:
HTF filter (default: 1-hour)
SMA, RSI, MACD, and ROC lengths
Custom weightings for each component
Thresholds for buy and sell signals
Understanding the Signals:
Green "Long" Label: Appears when the composite indicator crosses above the buy threshold, signaling a potential buy opportunity.
Red "Short" Label: Appears when the composite indicator crosses below the sell threshold, signaling a potential sell opportunity.
These signals are filtered by a higher timeframe SMA trend to improve accuracy.
Alerts:
The indicator provides alert conditions for long and short entries.
Traders can enable alerts in TradingView to receive real-time notifications when a new signal is triggered.
Safety and Best Practices
Use in Conjunction with Other Analysis: Do not rely solely on this indicator. Combine it with price action, support/resistance levels, and fundamental analysis for better decision-making.
Adjust Settings for Your Strategy: The default settings may not suit all markets or timeframes. Test different configurations before trading live.
Backtest Before Using in Live Trading: Evaluate the indicator’s past performance on historical data to assess its effectiveness in different market conditions.
Avoid Overtrading: False signals can occur, especially in low volatility or choppy markets. Use additional confirmation (e.g., trendlines or moving averages).
Risk Management: Always set stop-loss levels and position sizes to limit potential losses.
