Liquidity Sweep Filter [AlgoAlpha]Unlock a deeper understanding of market liquidity with the Liquidity Sweep Filter by AlgoAlpha. This indicator identifies liquidity sweeps, highlighting key price levels where large liquidations have occurred. By visualizing major and minor liquidation events, traders can better anticipate potential reversals and market structure shifts, making this an essential tool for those trading in volatile conditions.
Key Features :
🔍 Liquidity Sweep Detection – Identifies and highlights areas where liquidity has been swept, distinguishing between major and minor liquidation events.
📊 Volume Profile Integration – Displays a volume profile overlay, helping traders spot high-activity price zones where the market is likely to react.
📈 Trend-Based Filtering – Utilizes an adaptive trend detection algorithm to refine liquidity sweeps based on market direction, reducing noise.
🎨 Customizable Visualization – Modify colors, thresholds, and display settings to tailor the indicator to your trading style.
🔔 Alerts for Liquidity Sweeps & Trend Changes – Stay ahead of the market by receiving alerts when significant liquidity events or trend shifts occur.
How to Use:
🛠 Add the Indicator : Add the Liquidity Sweep Filter to your chart and configure the settings based on your preferred sensitivity. Adjust the major sweep threshold to filter out smaller moves.
📊 Analyze Liquidity Zones and trend direction : Look for liquidation levels where large buy or sell stops have been triggered. Major sweeps indicate strong reactions, while minor sweeps show gradual liquidity absorption. You can also see which levels are high in liquidity by the transparency of the levels.
🔔 Set-Up Alerts : Use the in-built alerts so you don't miss a trading opportunity
How It Works :
The Liquidity Sweep Filter detects liquidity events by tracking swing highs and lows (defined as a pivot where neighboring candles are lower/higher than it) where traders are likely to have placed stop-loss orders. It evaluates volume and price action, marking areas where liquidity has been absorbed by the market. Additionally, the integrated trend filter ensures that only relevant liquidity sweeps are highlighted based on market direction, lows in an uptrend and highs in a downtrend. The trend filter works by calculating a basis, and defining trend shifts when the closing price crosses over the upper or lower bands.The included volume profile further enhances analysis by displaying key trading zones where price may react.
Cari dalam skrip untuk "volume profile"
PRINT_TYPELibrary "PRINT_TYPE"
Inputs
Inputs objects
Fields:
inbalance_percent (series int) : percentage coefficient to determine the Imbalance of price levels
stacked_input (series int) : minimum number of consecutive Imbalance levels required to draw extended lines
show_summary_footprint (series bool)
procent_volume_area (series int) : definition size Value area
new_imbalance_cond (series bool) : bool input for setup alert on new imbalance buy and sell
new_imbalance_line_cond (series bool) : bool input for setup alert on new imbalance line buy and sell
stop_past_imbalance_line_cond (series bool) : bool input for setup alert on stop past imbalance line buy and sell
Constants
Constants all Constants objects
Fields:
imbalance_high_char (series string) : char for printing buy imbalance
imbalance_low_char (series string) : char for printing sell imbalance
color_title_sell (series color) : color for footprint sell
color_title_buy (series color) : color for footprint buy
color_line_sell (series color) : color for sell line
color_line_buy (series color) : color for buy line
color_title_none (series color) : color None
Calculation_data
Calculation_data data for calculating
Fields:
detail_open (array) : array open from calculation timeframe
detail_high (array) : array high from calculation timeframe
detail_low (array) : array low from calculation timeframe
detail_close (array) : array close from calculation timeframe
detail_vol (array) : array volume from calculation timeframe
previos_detail_close (array) : array close from calculation timeframe
isBuyVolume (series bool) : attribute previosly bar buy or sell
Footprint_row
Footprint_row objects one footprint row
Fields:
price (series float) : row price
buy_vol (series float) : buy volume
sell_vol (series float) : sell volume
imbalance_buy (series bool) : attribute buy inbalance
imbalance_sell (series bool) : attribute sell imbalance
buy_vol_box (series box) : for ptinting buy volume
sell_vol_box (series box) : for printing sell volume
buy_vp_box (series box) : for ptinting volume profile buy
sell_vp_box (series box) : for ptinting volume profile sell
row_line (series label) : for ptinting row price
empty (series bool) : = true attribute row with zero volume buy and zero volume sell
Imbalance_line_var_object
Imbalance_line_var_object var objects printing and calculation imbalance line
Fields:
cum_buy_line (array) : line array for saving all history buy imbalance line
cum_sell_line (array) : line array for saving all history sell imbalance line
Imbalance_line
Imbalance_line objects printing and calculation imbalance line
Fields:
buy_price_line (array) : float array for saving buy imbalance price level
sell_price_line (array) : float array for saving sell imbalance price level
var_imba_line (Imbalance_line_var_object) : var objects this type
Footprint_bar
Footprint_bar all objects one bar with footprint
Fields:
foot_rows (array) : objects one row footprint
imba_line (Imbalance_line) : objects imbalance line
row_size (series float) : size rows
total_vol (series float) : total volume one footprint bar
foot_buy_vol (series float) : buy volume one footprint bar
foot_sell_vol (series float) : sell volume one footprint bar
foot_max_price_vol (map) : map with one value - price row with max volume buy + sell
calc_data (Calculation_data) : objects with detail data from calculation resolution
Support_objects
Support_objects support object for footprint calculation
Fields:
consts (Constants) : all consts objects
inp (Inputs) : all input objects
bar_index_show_condition (series bool) : calculation bool value for show all objects footprint
row_line_color (series color) : calculation value - color for row price
dop_info (series string)
show_table_cond (series bool)
footprint_typeLibrary "footprint_type"
Contains all types for calculating and rendering footprints
Inputs
Inputs objects
Fields:
inbalance_percent (series int) : percentage coefficient to determine the Imbalance of price levels
stacked_input (series int) : minimum number of consecutive Imbalance levels required to draw extended lines
show_summary_footprint (series bool) : bool input for show summary footprint
procent_volume_area (series int) : definition size Value area
show_vah (series bool) : bool input for show VAH
show_poc (series bool) : bool input for show POC
show_val (series bool) : bool input for show VAL
color_vah (series color) : color VAH line
color_poc (series color) : color POC line
color_val (series color) : color VAL line
show_volume_profile (series bool)
new_imbalance_cond (series bool) : bool input for setup alert on new imbalance buy and sell
new_imbalance_line_cond (series bool) : bool input for setup alert on new imbalance line buy and sell
stop_past_imbalance_line_cond (series bool) : bool input for setup alert on stop past imbalance line buy and sell
Constants
Constants all Constants objects
Fields:
imbalance_high_char (series string) : char for printing buy imbalance
imbalance_low_char (series string) : char for printing sell imbalance
color_title_sell (series color) : color for footprint sell
color_title_buy (series color) : color for footprint buy
color_line_sell (series color) : color for sell line
color_line_buy (series color) : color for buy line
color_title_none (series color) : color None
Calculation_data
Calculation_data data for calculating
Fields:
detail_open (array) : array open from calculation timeframe
detail_high (array) : array high from calculation timeframe
detail_low (array) : array low from calculation timeframe
detail_close (array) : array close from calculation timeframe
detail_vol (array) : array volume from calculation timeframe
previos_detail_close (array) : array close from calculation timeframe
isBuyVolume (series bool) : attribute previosly bar buy or sell
Footprint_row
Footprint_row objects one footprint row
Fields:
price (series float) : row price
buy_vol (series float) : buy volume
sell_vol (series float) : sell volume
imbalance_buy (series bool) : attribute buy inbalance
imbalance_sell (series bool) : attribute sell imbalance
buy_vol_box (series box) : for ptinting buy volume
sell_vol_box (series box) : for printing sell volume
buy_vp_box (series box) : for ptinting volume profile buy
sell_vp_box (series box) : for ptinting volume profile sell
row_line (series label) : for ptinting row price
empty (series bool) : = true attribute row with zero volume buy and zero volume sell
Value_area
Value_area objects for calculating and printing Value area
Fields:
vah_price (series float) : VAH price
poc_price (series float) : POC price
val_price (series float) : VAL price
vah_label (series label) : label for VAH
poc_label (series label) : label for POC
val_label (series label) : label for VAL
vah_line (series line) : line for VAH
poc_level (series line) : line for POC
val_line (series line) : line for VAL
Imbalance_line_var_object
Imbalance_line_var_object var objects printing and calculation imbalance line
Fields:
cum_buy_line (array) : line array for saving all history buy imbalance line
cum_sell_line (array) : line array for saving all history sell imbalance line
Imbalance_line
Imbalance_line objects printing and calculation imbalance line
Fields:
buy_price_line (array) : float array for saving buy imbalance price level
sell_price_line (array) : float array for saving sell imbalance price level
var_imba_line (Imbalance_line_var_object) : var objects this type
Footprint_info_var_object
Footprint_info_var_object var objects for info printing
Fields:
cum_delta (series float) : var delta volume
cum_total (series float) : var total volume
cum_buy_vol (series float) : var buy volume
cum_sell_vol (series float) : var sell volume
cum_info (series table) : table for ptinting
Footprint_info
Footprint_info objects for info printing
Fields:
var_info (Footprint_info_var_object) : var objects this type
total (series label) : total volume
delta (series label) : delta volume
summary_label (series label) : label for ptinting
Footprint_bar
Footprint_bar all objects one bar with footprint
Fields:
foot_rows (array) : objects one row footprint
val_area (Value_area) : objects Value area
imba_line (Imbalance_line) : objects imbalance line
info (Footprint_info) : objects info - table,label and their variable
row_size (series float) : size rows
total_vol (series float) : total volume one footprint bar
foot_buy_vol (series float) : buy volume one footprint bar
foot_sell_vol (series float) : sell volume one footprint bar
foot_max_price_vol (map) : map with one value - price row with max volume buy + sell
calc_data (Calculation_data) : objects with detail data from calculation resolution
Support_objects
Support_objects support object for footprint calculation
Fields:
consts (Constants) : all consts objects
inp (Inputs) : all input objects
bar_index_show_condition (series bool) : calculation bool value for show all objects footprint
row_line_color (series color) : calculation value - color for row price
Tick Profile HeatmapThis is a market internal TICK heatmap with the intent of displaying areas of price associated to stronger reactions with NYSE TICK (by default).
This code is based off of a variation of a Volume Profile coded originally by colejustice who originally used code from LuxAlgo . The full-width volume bars that colejustice setup were replaced with full-width bars representative of TICK breaking +/- $500, the current cumulative value representing the "heat" is comprised of hlc3 by default but that can be changed. In a future update I may add additional logic here to capture highs and lows in the heatmap specifically, and perhaps additional colors.
As with other traditional profiling studies, this indicators purpose is to visualize correspondence to specific price levels, allowing rapid assessment where the most TICK activity is occurring, and where it hasn't been. This information may provide areas of support and resistance and regions where price may move quickly repeatedly.
All of the same input guidance that colejustice provided is the same for those pre-existing inputs:
Inputs are set up such that you can customize the lookback period, number of rows, and width of rows for most major timeframes individually. Timeframes between those available will use the next lower timeframe settings (e.g., 2m chart will use the 1m settings.)
Zero usage of volume is present in this indicator, only TICK data so please don't confuse it with volume studies.
Volume CompressorTurns volume into a more informative representation, ready to be further analyzed
...
Rationale
Volume
Back in the "before the quant" days I was a big fan of market & volume profile. Thing is J. Steidlmayer had lotta different ideas & works aside of profiling, it's just most of them ain't got to mainstream, one of them was "Hot / Cold volume" (yes, you can't really google it). From my interpretation, the idea was that in a given asset there is a usual constant volume that stays there no matter what, and if it ever changes it changes very slow and gradually; and there's another kind of, so to say, 'active' volume that actually influences price dynamics and very volatile by its nature. So I've met concept lately, and decided to quantify & model it one day when I'll have an idea how. That day was yesterday.
Compression
When we do music we always use different kinds of filters (low-pass, high pass, etc) for equalization and filtering itself. That stuff we use in finance as well. What we also always use in music are compressors, there dynamic processors that automatically adjust volume so it will be more consistent. Almost all the cool music you hear is compressed (both individual instruments (especially vocals) and the whole track afterwards), otherwise stuff will be too quite and too weak to flex on it, and also DJing it would be a nightmare. I am a big adept of loudness war. So I was like, how can I use compression in finance, when ima get an idea? That day was yesterday as well.
Volume structure
Being inspired by Steidlmayer's idea, I decided to distinguish volume this way:
1) Passive / static volume. The ~ volume that's always there no matter what (hedges, arbitrages, spread legs, portfolio parts etc etc), doesn't affect things;
2) Active / dynamic volume. The volume that flows from one asset to another, really matters and affects things;
3) Excess volume. The last portion of number 2 volume, that doesn't represent any powerful value to affect things.
Now it's clear that we can get rid of number 1 and number 3, the components that don't really matter, and concentrate on number 2 in order to improve information gain, both for ourselves and for the models we feed this data. How?
Model
I don't wanna explain it all in statistical / DSP way for once.
First of all, I think the population of volumes is log-normally distributed, so let's take logs of volumes, now we have a ~ normally distributed data. We take linearly weighted mean, add and subtract linearly weighted standard deviation from it, these would be our thresholds, the borders between different kinds of volumes explained before.
The upper threshold is for downward compression, that will not let volume pass it higher.
The lower threshold is for upward compression, all the volumes lower than this threshold will be brought up to the threshold's level.
Then we apply multipliers to the thresholds in order to adjust em and find the sweet spots. We do it the same way as in sound engineering when we don't aim for overcompression, we adjust the thresholds until they start to touch the signal and all good.
Afterwards, we delete all the number 1 and number 3 volume, leaving us exclusively with the clear main component, ready to be processed further.
We return the volumes to dem real scale.
About the parameters, based on testing I don't recommend changing the thresholds from dem default values, first of all they make sense statistically and second they work as intended.
Window length can and should be adjusted, find your own way, or leave the default value. ML (moving location) length is up to you as well.
So yeah, you can see now we can smooth the data and make it visually appealing not only by applying a smooth filter over it.
All good TV?
Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD)
Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis
The Revolutionary Concept: When Physics Meets Trading
After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits.
The Core Innovation: Ergodic Theory Applied to Markets
What Makes Markets Ergodic or Non-Ergodic?
In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading:
Ergodic Markets (Mean-Reverting)
- Time averages equal ensemble averages
- Historical patterns repeat reliably
- Price oscillates around equilibrium
- Traditional indicators work well
Non-Ergodic Markets (Trending)
- Path dependency dominates
- History doesn't predict future
- Price creates new equilibrium levels
- Momentum strategies excel
The Mathematical Framework
The Ergodic Score combines three critical divergences:
Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3
Where:
Price Divergence: How far current price deviates from market consensus
Return Divergence: Momentum differential between instrument and market
Volatility Divergence: Volatility regime misalignment
Market Stress: Adaptive multiplier based on current conditions
The Ensemble Analysis Revolution
Beyond Single-Instrument Analysis
Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach:
Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves
Filters False Signals: Requires broader market confirmation
Identifies Regime Shifts: Detects when entire market structure changes
Provides Context: Shows if moves are isolated or systemic
Dynamic Threshold Adaptation
Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions:
Base Threshold = SMA(Ergodic Score, Lookback × 3)
Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity
Final Threshold = Smoothed(Base + Adaptive)
This creates context-aware signals that remain effective across different market environments.
The Confidence Engine: Know Your Signal Quality
Multi-Factor Confidence Scoring
Every signal receives a confidence score based on:
Signal Clarity (0-35%): How decisively the ergodic threshold is crossed
Momentum Strength (0-25%): Rate of ergodic change
Volatility Alignment (0-20%): Whether volatility supports the signal
Market Quality (0-20%): Price convergence and path dependency factors
Real-Time Confidence Updates
The Live Confidence metric continuously updates, showing:
- Current opportunity quality
- Market state clarity
- Historical performance influence
- Signal recency boost
- Visual Intelligence System
Adaptive Ergodic Field Bands
Dynamic bands that expand and contract based on market state:
Primary Color: Ergodic state (mean-reverting)
Danger Color: Non-ergodic state (trending)
Band Width: Expected price movement range
Squeeze Indicators: Volatility compression warnings
Quantum Wave Ribbons
Triple EMA system (8, 21, 55) revealing market flow:
Compressed Ribbons: Consolidation imminent
Expanding Ribbons: Directional move developing
Color Coding: Matches current ergodic state
Phase Transition Signals
Clear entry/exit markers at regime changes:
Bull Signals: Ergodic restoration (mean reversion opportunity)
Bear Signals: Ergodic break (trend following opportunity)
Confidence Labels: Percentage showing signal quality
Visual Intensity: Stronger signals = deeper colors
Professional Dashboard Suite
Main Analytics Panel (Top Right)
Market State Monitor
- Current regime (Ergodic/Non-Ergodic)
- Ergodic score with threshold
- Path dependency strength
- Quantum coherence percentage
Divergence Metrics
- Price divergence with severity
- Volatility regime classification
- Strategy mode recommendation
- Signal strength indicator
Live Intelligence
- Real-time confidence score
- Color-coded risk levels
- Dynamic strategy suggestions
Performance Tracking (Left Panel)
Signal Analytics
- Total historical signals
- Win rate with W/L breakdown
- Current streak tracking
- Closed trade counter
Regime Analysis
- Current market behavior
- Bars since last signal
- Recommended actions
- Average confidence trends
Strategy Command Center (Bottom Right)
Adaptive Recommendations
- Active strategy mode
- Primary approach (mean reversion/momentum)
- Suggested indicators ("weapons")
- Entry/exit methodology
- Risk management guidance
- Comprehensive Input Guide
Core Algorithm Parameters
Analysis Period (10-100 bars)
Scalping (10-15): Ultra-responsive, more signals, higher noise
Day Trading (20-30): Balanced sensitivity and stability
Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes
Divergence Threshold (0.5-5.0)
Hair Trigger (0.5-1.0): Catches every wiggle, many false signals
Balanced (1.5-2.5): Good signal-to-noise ratio
Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance
Path Memory (20-200 bars)
Short Memory (20-50): Recent behavior focus, quick adaptation
Medium Memory (50-100): Balanced historical context
Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag
Signal Spacing (5-50 bars)
Aggressive (5-10): Allows rapid-fire signals
Normal (15-25): Prevents clustering, maintains flow
Conservative (30-50): Major setups only Default: 15 - optimal trade frequency
Ensemble Configuration
Select markets for consensus analysis:
SPY: Broad market sentiment
QQQ: Technology leadership
IWM: Small-cap risk appetite
DIA: Blue-chip stability
More instruments = stronger consensus but potentially diluted signals
Visual Customization
Color Themes (6 professional options):
Quantum: Cyan/Pink - Modern trading aesthetic
Matrix: Green/Red - Classic terminal look
Heat: Blue/Red - Temperature metaphor
Neon: Cyan/Magenta - High contrast
Ocean: Turquoise/Coral - Calming palette
Sunset: Red-orange/Teal - Warm gradients
Display Controls:
- Toggle each visual component
- Adjust transparency levels
- Scale dashboard text
- Show/hide confidence scores
- Trading Strategies by Market State
- Ergodic State Strategy (Primary Color Bands)
Market Characteristics
- Price oscillates predictably
- Support/resistance hold
- Volume patterns repeat
- Mean reversion dominates
Optimal Approach
Entry: Fade moves at band extremes
Target: Middle band (equilibrium)
Stop: Just beyond outer bands
Size: Full confidence-based position
Recommended Tools
- RSI for oversold/overbought
- Bollinger Bands for extremes
- Volume profile for levels
- Non-Ergodic State Strategy (Danger Color Bands)
Market Characteristics
- Price trends persistently
- Levels break decisively
- Volume confirms direction
- Momentum accelerates
Optimal Approach
Entry: Breakout from bands
Target: Trail with expanding bands
Stop: Inside opposite band
Size: Scale in with trend
Recommended Tools
- Moving average alignment
- ADX for trend strength
- MACD for momentum
- Advanced Features Explained
Quantum Coherence Metric
Measures phase alignment between individual and ensemble behavior:
80-100%: Perfect sync - strong mean reversion setup
50-80%: Moderate alignment - mixed signals
0-50%: Decoherence - trending behavior likely
Path Dependency Analysis
Quantifies how much history influences current price:
Low (<30%): Technical patterns reliable
Medium (30-50%): Mixed influences
High (>50%): Fundamental shift occurring
Volatility Regime Classification
Contextualizes current volatility:
Normal: Standard strategies apply
Elevated: Widen stops, reduce size
Extreme: Defensive mode required
Signal Strength Indicator
Real-time opportunity quality:
- Distance from threshold
- Momentum acceleration
- Cross-validation factors
Risk Management Framework
Position Sizing by Confidence
90%+ confidence = 100% position size
70-90% confidence = 75% position size
50-70% confidence = 50% position size
<50% confidence = 25% or skip
Dynamic Stop Placement
Ergodic State: ATR × 1.0 from entry
Non-Ergodic State: ATR × 2.0 from entry
Volatility Adjustment: Multiply by current regime
Multi-Timeframe Alignment
- Check higher timeframe regime
- Confirm ensemble consensus
- Verify volume participation
- Align with major levels
What Makes EMD Unique
Original Contributions
First Ergodic Theory Trading Application: Transforms abstract physics into practical signals
Ensemble Market Analysis: Revolutionary multi-market divergence system
Adaptive Confidence Engine: Institutional-grade signal quality metrics
Quantum Coherence: Novel market alignment measurement
Smart Signal Management: Prevents clustering while maintaining responsiveness
Technical Innovations
Dynamic Threshold Adaptation: Self-adjusting sensitivity
Path Memory Integration: Historical dependency weighting
Stress-Adjusted Scoring: Market condition normalization
Real-Time Performance Tracking: Built-in strategy analytics
Optimization Guidelines
By Timeframe
Scalping (1-5 min)
Period: 10-15
Threshold: 0.5-1.0
Memory: 20-30
Spacing: 5-10
Day Trading (5-60 min)
Period: 20-30
Threshold: 1.5-2.5
Memory: 40-60
Spacing: 15-20
Swing Trading (1H-1D)
Period: 40-60
Threshold: 2.0-3.0
Memory: 80-120
Spacing: 25-35
Position Trading (1D-1W)
Period: 60-100
Threshold: 3.0-5.0
Memory: 100-200
Spacing: 40-50
By Market Condition
Trending Markets
- Increase threshold
- Extend memory
- Focus on breaks
Ranging Markets
- Decrease threshold
- Shorten memory
- Focus on restores
Volatile Markets
- Increase spacing
- Raise confidence requirement
- Reduce position size
- Integration with Other Analysis
- Complementary Indicators
For Ergodic States
- RSI divergences
- Bollinger Band squeezes
- Volume profile nodes
- Support/resistance levels
For Non-Ergodic States
- Moving average ribbons
- Trend strength indicators
- Momentum oscillators
- Breakout patterns
- Fundamental Alignment
- Check economic calendar
- Monitor sector rotation
- Consider market themes
- Evaluate risk sentiment
Troubleshooting Guide
Too Many Signals:
- Increase threshold
- Extend signal spacing
- Raise confidence minimum
Missing Opportunities
- Decrease threshold
- Reduce signal spacing
- Check ensemble settings
Poor Win Rate
- Verify timeframe alignment
- Confirm volume participation
- Review risk management
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques.
Transform market chaos into trading clarity with Ergodic Market Divergence.
Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Range Detect SystemTechnical analysis indicator designed to identify potential significant price ranges and the distribution of volume within those ranges. The system helps traders calculate POC and show volume history. Also detecting breakouts or potential reversals. System identifies ranges with a high probability of price consolidation and helps screen out extreme price moves or ranges that do not meet certain volatility thresholds.
⭕️ Key Features
Range Detection — identifies price ranges where consolidation is occurring.
Volume Profile Calculation — indicator calculates the Point of Control (POC) based on volume distribution within the identified range, enhancing the analysis of market structure.
Volume History — shows where the largest volume was traded from the center of the range. If the volume is greater in the upper part of the range, the color will be green. If the volume is greater in the lower part, the color will be red.
Range Filtering — Includes multi-level filtering options to avoid ranges that are too volatile or outside normal ranges.
Visual Customization — Shows graphical indicators for potential bullish or bearish crossovers at the upper and lower range boundaries. Users can choose the style and color of the lines, making it easier to visualize ranges and important levels on the chart.
Alerts — system will notify you when a range has been created and also when the price leaves the range.
⭕️ How it works
Extremes (Pivot Points) are taken as a basis, after confirming the relevance of the extremes we take the upper and lower extremes and form a range. We check if it does not violate a number of rules and filters, perform volume calculations, and only then is the range displayed.
Pivot points is a built-in feature that shows an extremum if it has not been updated N bars to the left and N bars to the right. Therefore, there is a delay depending on the bars specified to check, which allows for a more accurate range. This approach allows not to make unnecessary recalculations, which completely eliminates the possibility of redrawing or range changes.
⭕️ Settings
Left Bars and Right Bars — Allows you to define the point that is the highest among the specified number of bars to the left and right of this point.
Range Logic — Select from which point to draw the range. Maximums only, Minimums only or both.
Use Wick — Option to consider the wick of the candles when identifying Range.
Breakout Confirmation — The number of bars required to confirm a breakout, after which the range will close.
Minimum Range Length — Sets the minimum number of candles needed for a range to be considered valid.
Row Size — Number of levels to calculate POC. *Larger values increase the script load.
% Range Filter — Dont Show Range is than more N% of Average Range.
Multi Filter — Allows use of Bollinger Bands, ATR, SMA, or Highest-Lowest range channels for filtering ranges based on volatility.
Range Hit — Shows graphical labels when price hits the upper or lower boundaries of the range, signaling potential reversal or breakout points.
Range Start — Show points where Range was created.
Linear Regression Channel UltimateKey Features and Benefits
Logarithmic scale option for improved analysis of long-term trends and volatile markets
Activity-based profiling using either touch count or volume data
Customizable channel width and number of profile fills
Adjustable number of most active levels displayed
Highly configurable visual settings for optimal chart readability
Why Logarithmic Scale Matters
The logarithmic scale option is a game-changer for analyzing assets with exponential growth or high volatility. Unlike linear scales, log scales represent percentage changes consistently across the price range. This allows for:
Better visualization of long-term trends
More accurate comparison of price movements across different price levels
Improved analysis of volatile assets or markets experiencing rapid growth
How It Works
The indicator calculates a linear regression line based on the specified period
Upper and lower channel lines are drawn at a customizable distance from the regression line
The space between the channel lines is divided into a user-defined number of levels
For each level, the indicator tracks either:
- The number of times price touches the level (touch count method)
- The total volume traded when price is at the level (volume method)
The most active levels are highlighted based on this activity data
Understanding Touch Count vs Volume
Touch count method: Useful for identifying key support/resistance levels based on price action alone
Volume method: Provides insight into levels where the most trading activity occurs, potentially indicating stronger support/resistance
Practical Applications
Trend identification and strength assessment
Support and resistance level discovery
Entry and exit point optimization
Volume profile analysis for improved market structure understanding
This Linear Regression Channel indicator combines powerful statistical analysis with flexible visualization options, making it an invaluable tool for traders and analysts across various timeframes and markets. Its unique features, especially the logarithmic scale and activity profiling, provide deeper insights into market behavior and potential turning points.
Volume Heatmap 2024 | NXT2017 Christmas EditionHi big players around the world,
I wish you a merry christmas time.
Today I have a nice present for you: a new volume heatmap indicator for free using!
HISTORY
My first volume heatmap project got a lot of feedback and a big demand. You can find it here:
In this time pinescript version 4 was the newest one and I worked the first time with arrays.
Today we have pinescript version 5 and some new features. This is why I tried again with matrix function and the results are better than I expected.
HOW IT WORKS
The indicator calculates similar like the volume profile. It looks back and every volume where the close price is on the same row area, the volume will cumulated. How much rows the new chart view is showing, you can choose manually.
The mind behind this is to find high volume levels, where high volume catch the price in a range or get function as support/resistance line.
PICTURES
I hope it helps for your trading. You are welcome to give some comments.
Merry christmas and best regards
NXT2017
SessionVolumeProfileLibrary "SessionVolumeProfile"
Analyzes price & volume during regular trading hours to provide a session volume profile analysis. The primary goal of this library is to provide the developer with three values: the value area high, low and the point of control. The library also provides methods for rendering the value areas and histograms. To learn more about this library and how you can use it, click on the website link in my profile where you will find a blog post with detailed information.
debug(vp, position)
Helper function to write some information about the supplied SVP object to the screen in a table.
Parameters:
vp (Object) : The SVP object to debug
position (string) : The position.* to place the table. Defaults to position.bottom_center
getLowerTimeframe()
Depending on the timeframe of the chart, determines a lower timeframe to grab volume data from for the analysis
Returns: The timeframe string to fetch volume for
get(volumeProfile, lowerTimeframeHigh, lowerTimeframeLow, lowerTimeframeVolume)
Populated the provided SessionVolumeProfile object with vp data on the session.
Parameters:
volumeProfile (Object) : The SessionVolumeProfile object to populate
lowerTimeframeHigh (float ) : The lower timeframe high values
lowerTimeframeLow (float ) : The lower timeframe low values
lowerTimeframeVolume (float ) : The lower timeframe volume values
drawPriorValueAreas(todaySessionVolumeProfile, extendYesterdayOverToday, showLabels, labelSize, pocColor, pocStyle, pocWidth, vahlColor, vahlStyle, vahlWidth, vaColor)
Given a SessionVolumeProfile Object, will render the historical value areas for that object.
Parameters:
todaySessionVolumeProfile (Object) : The SessionVolumeProfile Object to draw
extendYesterdayOverToday (bool) : Defaults to true
showLabels (bool) : Defaults to true
labelSize (string) : Defaults to size.small
pocColor (color) : Defaults to #e500a4
pocStyle (string) : Defaults to line.style_solid
pocWidth (int) : Defaults to 1
vahlColor (color) : The color of the value area high/low lines. Defaults to #1592e6
vahlStyle (string) : The style of the value area high/low lines. Defaults to line.style_solid
vahlWidth (int) : The width of the value area high/low lines. Defaults to 1
vaColor (color) : The color of the value area background. Defaults to #00bbf911)
drawHistogram(volumeProfile, bgColor, showVolumeOnHistogram)
Given a SessionVolumeProfile object, will render the histogram for that object.
Parameters:
volumeProfile (Object) : The SessionVolumeProfile object to draw
bgColor (color) : The baseline color to use for the histogram. Defaults to #00bbf9
showVolumeOnHistogram (bool) : Show the volume amount on the histogram bars. Defaults to false.
Object
Fields:
numberOfRows (series__integer)
valueAreaCoverage (series__integer)
trackDevelopingVa (series__bool)
valueAreaHigh (series__float)
pointOfControl (series__float)
valueAreaLow (series__float)
startTime (series__integer)
endTime (series__integer)
dayHigh (series__float)
dayLow (series__float)
step (series__float)
pointOfControlLevel (series__integer)
valueAreaHighLevel (series__integer)
valueAreaLowLevel (series__integer)
volumeRows (array__float)
priceLevelRows (array__float)
ltfSessionHighs (array__float)
ltfSessionLows (array__float)
ltfSessionVols (array__float)
Position Cost DistributionThe Position Cost Distribution indicator (also known as the Market Position Overview, Chip Distribution, or CYQ Algorithm) provides an estimate of how shares are distributed across different price levels. Visually, it resembles the Volume Profile indicator, though they rely on distinct computational approaches.
🟠 Principle
The Position Cost Distribution algorithm is based on the principle that a security's total shares outstanding usually remains constant, except under conditions like stock splits, reverse splits, or new share issuance. It views all trading activity as simply exchanging share positions between holders at different price points.
By analyzing daily trade volume and the prior day's distribution, the algorithm infers the resulting share distribution after each day. By tracking these inferred transpositions over time, the indicator builds up an aggregate view of the estimated share concentration at each price level. This provides insights into potential buying and selling pressure zones that could form support or resistance areas.
Together with the Volume Profile, the Position Cost Distribution gives traders multiple lenses for examining market structure from both a volume and positional standpoint. Both can help identify meaningful technical price levels.
🟠 Algorithm
The algorithm initializes by allocating all shares to the price range encompassed by the first bar displayed on the chart. Preferably, the chart window should include the stock's IPO date, allowing the model to distribute shares specifically to the IPO price.
For subsequent trading sessions, the indicator performs the following calculations:
1. The daily turnover ratio is calculated by dividing the bar's trading volume by total outstanding shares.
2. For each price level (bucket), the number of shares is reduced by the turnover amount to represent shares transferring from existing holders.
3. The bar's total volume is then added to buckets corresponding to that period's price range.
Currently, the model assumes each share has an equal probability of being exchanged, regardless of how long ago it was acquired or at what price. Potential optimizations could incorporate factors like making shares held longer face a smaller chance of transfer compared to more recently purchased shares.
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中文介绍：该指标为“筹码分布”的一个 TradingView 实现 :)
Multi-Asset Performance [Spaghetti] - By LeviathanThis indicator visualizes the cumulative percentage changes or returns of 30 symbols over a given period and offers a unique set of tools and data analytics for deeper insight into the performance of different assets.
Multi Asset Performance indicator (also called “Spaghetti”) makes it easy to monitor the changes in Price, Open Interest, and On Balance Volume across multiple assets simultaneously, distinguish assets that are overperforming or underperforming, observe the relative strength of different assets or currencies, use it as a tool for identifying mean reversion opportunities and even for constructing pairs trading strategies, detect "risk-on" or "risk-off" periods, evaluate statistical relationships between assets through metrics like correlation and beta, construct hedging strategies, trade rotations and much more.
Start by selecting a time period (e.g., 1 DAY) to set the interval for when data is reset. This will provide insight into how price, open interest, and on-balance volume change over your chosen period. In the settings, asset selection is fully customizable, allowing you to create three groups of up to 30 tickers each. These tickers can be displayed in a variety of styles and colors. Additional script settings offer a range of options, including smoothing values with a Simple Moving Average (SMA), highlighting the top or bottom performers, plotting the group mean, applying heatmap/gradient coloring, generating a table with calculations like beta, correlation, and RSI, creating a profile to show asset distribution around the mean, and much more.
One of the most important script tools is the screener table, which can display:
🔸 Percentage Change (Represents the return or the percentage increase or decrease in Price/OI/OBV over the current selected period)
🔸 Beta (Represents the sensitivity or responsiveness of asset's returns to the returns of a benchmark/mean. A beta of 1 means the asset moves in tandem with the market. A beta greater than 1 indicates the asset is more volatile than the market, while a beta less than 1 indicates the asset is less volatile. For example, a beta of 1.5 means the asset typically moves 150% as much as the benchmark. If the benchmark goes up 1%, the asset is expected to go up 1.5%, and vice versa.)
🔸 Correlation (Describes the strength and direction of a linear relationship between the asset and the mean. Correlation coefficients range from -1 to +1. A correlation of +1 means that two variables are perfectly positively correlated; as one goes up, the other will go up in exact proportion. A correlation of -1 means they are perfectly negatively correlated; as one goes up, the other will go down in exact proportion. A correlation of 0 means that there is no linear relationship between the variables. For example, a correlation of 0.5 between Asset A and Asset B would suggest that when Asset A moves, Asset B tends to move in the same direction, but not perfectly in tandem.)
🔸 RSI (Measures the speed and change of price movements and is used to identify overbought or oversold conditions of each asset. The RSI ranges from 0 to 100 and is typically used with a time period of 14. Generally, an RSI above 70 indicates that an asset may be overbought, while RSI below 30 signals that an asset may be oversold.)
⚙️ Settings Overview:
◽️ Period
Periodic inputs (e.g. daily, monthly, etc.) determine when the values are reset to zero and begin accumulating again until the period is over. This visualizes the net change in the data over each period. The input "Visible Range" is auto-adjustable as it starts the accumulation at the leftmost bar on your chart, displaying the net change in your chart's visible range. There's also the "Timestamp" option, which allows you to select a specific point in time from where the values are accumulated. The timestamp anchor can be dragged to a desired bar via Tradingview's interactive option. Timestamp is particularly useful when looking for outperformers/underperformers after a market-wide move. The input positioned next to the period selection determines the timeframe on which the data is based. It's best to leave it at default (Chart Timeframe) unless you want to check the higher timeframe structure of the data.
◽️ Data
The first input in this section determines the data that will be displayed. You can choose between Price, OI, and OBV. The second input lets you select which one out of the three asset groups should be displayed. The symbols in the asset group can be modified in the bottom section of the indicator settings.
◽️ Appearance
You can choose to plot the data in the form of lines, circles, areas, and columns. The colors can be selected by choosing one of the six pre-prepared color palettes.
◽️ Labeling
This input allows you to show/hide the labels and select their appearance and size. You can choose between Label (colored pointed label), Label and Line (colored pointed label with a line that connects it to the plot), or Text Label (colored text).
◽️ Smoothing
If selected, this option will smooth the values using a Simple Moving Average (SMA) with a custom length. This is used to reduce noise and improve the visibility of plotted data.
◽️ Highlight
If selected, this option will highlight the top and bottom N (custom number) plots, while shading the others. This makes the symbols with extreme values stand out from the rest.
◽️ Group Mean
This input allows you to select the data that will be considered as the group mean. You can choose between Group Average (the average value of all assets in the group) or First Ticker (the value of the ticker that is positioned first on the group's list). The mean is then used in calculations such as correlation (as the second variable) and beta (as a benchmark). You can also choose to plot the mean by clicking on the checkbox.
◽️ Profile
If selected, the script will generate a vertical volume profile-like display with 10 zones/nodes, visualizing the distribution of assets below and above the mean. This makes it easy to see how many or what percentage of assets are outperforming or underperforming the mean.
◽️ Gradient
If selected, this option will color the plots with a gradient based on the proximity of the value to the upper extreme, zero, and lower extreme.
◽️ Table
This section includes several settings for the table's appearance and the data displayed in it. The "Reference Length" input determines the number of bars back that are used for calculating correlation and beta, while "RSI Length" determines the length used for calculating the Relative Strength Index. You can choose the data that should be displayed in the table by using the checkboxes.
◽️ Asset Groups
This section allows you to modify the symbols that have been selected to be a part of the 3 asset groups. If you want to change a symbol, you can simply click on the field and type the ticker of another one. You can also show/hide a specific asset by using the checkbox next to the field.
Liquidity PeaksThe "Liquidity Peaks" indicator is a tool designed to identify significant supply and demand zones based on volumetric analysis. It analyzes the volume profile within a specified lookback range to pinpoint the most volumetric point and draw corresponding zones on the price chart.
The 𝐋𝐢𝐪. 𝐏𝐞𝐚𝐤𝐬 indicator utilizes volume data to identify key supply and demand areas on the price chart. By examining the volume profile within a defined lookback range, it highlights three distinct zones: liquidity grab, volume containment, and the most volumetric point.
Zones and their meanings:
Liquidity grab (Orange box): This zone represents a price level where there is a significant swipe of the previous demand zone within the volume range. It indicates a potential shift in market sentiment and serves as a key supply or demand area.
Volume containment (Gray box): This zone displays the area of volume contained before the peak in volume. It provides insights into the range where buying or selling pressure was concentrated, highlighting potential support or resistance levels.
Most volumetric point (Light blue box): This zone represents the point within the lookback range that exhibits the highest volume. It signifies a significant area of market interest and indicates a potential supply or demand level.
Adjustable options:
Adjust liquidity Grab: This option allows you to adjust the size of the boxes. When enabled, the box size is set to twice the size of the high or low of the candle's wick. This adjustment enhances the visibility and accuracy of identifying swipes at specific price levels.
Show origin: Enabling this option ensures that the liquidity boxes are drawn from the wick they were created from. This provides a clear visual reference to the specific candle and highlights the liquidity levels associated with it.
Utility:
The 𝐋𝐢𝐪. 𝐏𝐞𝐚𝐤𝐬 indicator is a valuable tool for traders and investors seeking to identify significant supply and demand zones in the market. By analyzing volume data and drawing corresponding zones on the chart, it helps to pinpoint areas where buying or selling pressure is likely to emerge.
Traders can utilize this information to identify potential support and resistance levels, plan their entries and exits, and make more informed trading decisions. The liquidity grab zones can act as potential reversal or breakout points, while the volume containment zones and most volumetric points provide insights into areas of high market interest.
It is important to note that this indicator should be used in conjunction with other technical analysis tools and indicators to confirm trading signals and validate market dynamics.
Example Charts:
Supply and Demand Daily [LuxAlgo]The Supply and Demand Daily indicator displays daily supply and demand areas on the user's chart. These areas are constructed using the market data within a previous daily interval.
This script makes use of the same logic as our previous Supply and Demand Visible Range indicator .
🔶 USAGE
The supply/demand areas & levels displayed by the indicator aim to provide potential support/resistance levels for users. Supply areas highlight where buyers are willing to exit the market and sell the asset, thus providing resistance and potentially causing prices to reverse or bounce back downwards, while demand areas highlights where buyers were willing to purchase the asset, thus providing support and potentially causing prices to reverse or bounce back upwards.
Historical areas allow the user to study the evolution of supply/demand from one day to another. Wider areas highlight prices avoiding reverting to this area, while thinner areas highlight prices returning more frequently to them.
Trends can be determined by looking at the price position relative to the previous day's supply/demand areas. Price breaking down from the demand zone is indicative of a downtrend, while price breaking above the supply zone is indicative of an uptrend.
Pullback/throwback scenarios can also be common using this indicator.
🔶 SETTINGS
Threshold %: Percentage of the total visible range volume used as a threshold to set supply/demand areas. Higher values return wider areas.
Resolution: Determines the number of bins used to find each area. Higher values will return more precise results.
Intra-bar TF: Timeframe used to obtain intra-bar data.
🔶 RELATED SCRIPTS
Modified TradingView's Up/Down Volume [vnhilton]
When plotting columns, histograms, etc. You'll notice that the indicator does not stick to the bottom of the pane. To fix this, you need another indicator (we'll call this 'placeholder') in the same pane as this indicator. Pin the placeholder indicator to the left scale, & pin the main indicator to the left scale. Then, pin the placeholder indicator to scale A, & finally the main indictor to the right scale.
Note: On the daily timeframes & higher, the up/down volume isn't accurate. Therefore, I've added a feature where you can toggle on the main indicator to disappear & only show ordinary total volume similar to the TradingView volume indicator.
The original code belongs to TradingView. This is a modified indicator that displays the down volume above the up volume similar to the volume profile. Also includes a moving average using the total volume, & a feature to display ordinary volume to solve the up/down inaccuracies on the daily timeframe & higher.
Volume Footprint [LuxAlgo]This indicator estimates a volume footprint using tick data. The script automatically separates a candle into equidistant intervals with a width obtained from the average true range or a user-given width.
Settings
Method: Interval width calculation method. This ultimately determines the number of intervals separating one candle.
Width (At the right of Method): Atr period or user given width depending on the selected method. A lower user-given width would divide a candle into a higher number of intervals.
As Percent: Returns the accumulated volume within each interval as a percentage of the total candle volume.
Style
Display Type: Determines the appearance of the returned volume footprint.
Trend Color: Color to use based on whether a candle is bullish or bearish.
Usage
When applied to a chart, the user will be asked to select the settings to use for the volume footprint. Note that changing the settings afterward will reset the volume footprint, removing previously generated footprints.
A new footprint will appear on the confirmation of a new bar, as such this version might only be useful in lower timeframes.
A volume footprint allows users to see the number of contracts exchanged within a candle interval. It can as such be seen as some kind of intrabar volume profile.
This can be useful to see areas of interest within a candle.
Different Appearance
By default, the volume footprint makes use of colored boxes with a color based on whether the candle was bullish or bearish.
Another appearance that gives additional information is the gradient type, which uses intervals color based on the number of contracts exchanged within an interval relative to the total volume of the candle. A higher number of contracts within an interval would return a darker color by default.
The regular display type makes use of boxes with a single color, with lines on the side indicating whether the candle was bullish or bearish.
VWAP RangeThe VWAP Range indicator is a highly versatile and innovative tool designed with trading signals for trading the supply and demand within consolidation ranges.
What's a VWAP?
A VWAP (Volume Weighted Average Price) represents an equilibrium point in the market, balancing supply and demand over a specified period. Unlike simple moving averages, VWAP gives more weight to periods with higher volume. This is crucial because large volumes indicate significant trading activity, often by institutional traders, whose actions can reflect deeper market insights or create substantial market movements. The VWAP is also often used as a benchmark to evaluate the efficiency of executed trades. If a trader buys below the VWAP and sells above it, they are generally considered to have transacted favourably.
This is how it works:
Multiple VWAP Anchors:
This indicator uses multiple VWAPs anchored to different optional time periods, such as Daily, Weekly, Monthly, as well as to the highest high a lowest low within those periods. This multiplicity allows for a comprehensive view of the market’s average price based on volume and price, tailored to different trading styles and strategies.
Dynamic and Fixed Periods:
Traders can choose between using dynamic ranges, which reset at the start of each selected period, and specifying a date and time for a particular fixed range to trade. This flexibility is crucial for analyzing price movements within specific ranges or market phases.
Fixed ranges allow VWAPs to be calculated and anchored to a significant market event, the beginning of a consolidation phase or after a major news announcement.
Signal Generation:
The indicator generates buy and sell signals based on the relationship of the price to the VWAPs. It also allows for setting a maximum number of signals in one direction to avoid overtrading or pyramiding. Be sure to wait for the candle close before trading on the signals.
Average Buy/Sell Signal Lines:
Lines can be plotted to display the average buy and sell signal prices. The difference between the lines shows the average profit per trade when trading on the signals in that range. It's a good way to see how profitable a range is on average without backtesting the signals. The lines will also often turn into support and resistance areas, similar to value areas in a volume profile.
Customizable Settings:
Traders have control over various settings, such as the VWAP calculation method and bar color. There are also tooltips for every function.
Hidden Feature:
There's a subtle feature in this indicator: if you have 'Indicator values' turned on in TradingView, you'll see a Sell/Buy Ratio displayed only in the status line. This ratio indicates whether there are more sell signals than buy signals in a range, regardless of the Max Signals setting. A red value above 1 suggests that the market is trending upward, indicating you might want to hold your long positions a bit longer. Conversely, a green value below 1 implies a downward trend.
PhantomFlow AccumulationDetectorThe PhantomFlow AccumulationDetector indicator analyzes the volume profile and displays potential accumulation based on the selected timeframe in the settings. This indicator can be used both as zones for trend following and for identifying reversals, as shown in the examples on the chart. The logic behind the formation of the accumulation zone is based on the fact that the POC (Point of Control) of the current zone is within the Volume Area range of the previous period.
Optimal settings for the working timeframe should be chosen visually, and the size of the zones should not be too large or too small. Additionally, it's advisable not to consider overly wide zones during increased volatility.
Consecutive zones within the same range often indicate a potential reversal.
We borrowed the volume profile calculation code from @LonesomeTheBlue. Thank you for the work done!
Halfback + One-Time-Framing BarsThis indicator is designed to be used with Market Profile / Volume Profile trading techniques on a 30min chart.
The halfback of a candle is the mid point between the high and the low of the candle. A halfback trade can be taken once price retraces into this point as support/resistance using the prevailing trend as your trade direction.
One-Time-Framing is a fancy term for trending in one direction. One-Time-Framing happens when a candle breaks the previous candle's high without testing the low or when a candle breaks the low of the previous candle without testing the high. This indicates that the trend is one directional and opposing pressure is very weak. Taking trades in the opposing direction of multiple OTF bars is typically a bad trade setup.
Halfback and OTF setups are typically used on a 30min timeframe combined with Market or Volume Profile, but you can experiment with these setups on any timeframe if you wish.
I hope you all enjoy this indicator, comment below if you have any questions.
Koalafied Volume Extension BubblesCircles based on extensions from volume Z-Score. Large volume candles can often signal exhaustion or show market strength in reversals or breakouts. Circles can be offset back to the start of the day/profile or left at the time where they occur.
Colours denoting deviations from the mean are
+2 std dev - Green
+1 std dev - Blue
-1 std dev - Red
-2 std dev - Purple
Concept is primarily as a pseudo volume profile delta tool. Obviously it's a very basic heuristic so would recommend further reading and use of actually footprint data to base trading decisions on.
Swing Assassin's Consolidated ScriptI put this script together to essentially consolidate a number of scripts that I use on a daily basis into one script. This is an ongoing improvement effort, so there may be some garbage in here right now so keep that in mind if you intend to use this to help in your trading.
There are 5 moving averages (Hull). I use the Fast, Mid and Slow to find entries after I us the Medium Slow and Super Slow to identify a trend. Otherwise, I have those three turned off.
This script also uses Bollinger Bands which I literally cannot trade without.
The script also has anchored VWAP , automated support/resistance lines, and a homebrewed Volume Profile that is a copy from Ildar Akhmetgaleev's indicator "Poor Man's Volume Profile" used under Mozilla Public License Version 2.0.
Poor man's volume clustersVolume clusters created from candlestick volumes.
See also "Poor man's volume profile" .
The code is generated using a template. To change the settings, you may need to regenerate the code. The code has a link to the repository with the template.
Cumulative Overlapping Volume BarsThis is cheap replacement for volume profile.
Red bars is where accumulated high volume in small range.
if new bar moves out of range all accumulated volume will be lost and color will change.
