Cumulative Volume Delta Z Score [BackQuant]Cumulative Volume Delta Z Score
The Cumulative Volume Delta Z Score indicator is a sophisticated tool that combines the cumulative volume delta (CVD) with Z-Score normalization to provide traders with a clearer view of market dynamics. By analyzing volume imbalances and standardizing them through a Z-Score, this tool helps identify significant price movements and market trends while filtering out noise.
Core Concept of Cumulative Volume Delta (CVD)
Cumulative Volume Delta (CVD) is a popular indicator that tracks the net difference between buying and selling volume over time. CVD helps traders understand whether buying or selling pressure is dominating the market. Positive CVD signals buying pressure, while negative CVD indicates selling pressure.
The addition of Z-Score normalization to CVD makes it easier to evaluate whether current volume imbalances are unusual compared to past behavior. Z-Score helps in detecting extreme conditions by showing how far the current CVD is from its historical mean in terms of standard deviations.
Key Features
Cumulative Volume Delta (CVD): Tracks the net buying vs. selling volume, allowing traders to gauge the overall market sentiment.
Z-Score Normalization: Converts CVD into a standardized value to highlight extreme movements in volume that are statistically significant.
Divergence Detection: The indicator can spot bullish and bearish divergences between price and CVD, which can signal potential trend reversals.
Pivot-Based Divergence: Identifies price and CVD pivots, highlighting divergence patterns that are crucial for predicting price changes.
Trend Analysis: Colors bars according to trend direction, providing a visual indication of bullish or bearish conditions based on Z-Score.
How It Works
Cumulative Volume Delta (CVD): The CVD is calculated by summing the difference between buying and selling volume for each bar. It represents the net buying or selling pressure, giving insights into market sentiment.
Z-Score Normalization: The Z-Score is applied to the CVD to normalize its values, making it easier to compare current conditions with historical averages. A Z-Score greater than 0 indicates a bullish market, while a Z-Score less than 0 signals a bearish market.
Divergence Detection: The indicator detects regular and hidden bullish and bearish divergences between price and CVD. These divergences often precede trend reversals, offering traders a potential entry point.
Pivot-Based Analysis: The indicator uses pivot highs and lows in both price and CVD to identify divergence patterns. A bullish divergence occurs when price makes a lower low, but CVD fails to follow, suggesting weakening selling pressure. Conversely, a bearish divergence happens when price makes a higher high, but CVD doesn't confirm the move, indicating potential selling pressure.
Trend Coloring: The bars are colored based on the trend direction. Green bars indicate an uptrend (CVD is positive), and red bars indicate a downtrend (CVD is negative). This provides an easy-to-read visualization of market conditions.
Standard Deviation Levels: The indicator plots ±1σ, ±2σ, and ±3σ levels to indicate the degree of deviation from the average CVD. These levels act as thresholds for identifying extreme buying or selling pressure.
Customization Options
Anchor Timeframe: The user can define an anchor timeframe to aggregate the CVD, which can be customized based on the trader’s needs (e.g., daily, weekly, custom lower timeframes).
Z-Score Period: The period for calculating the Z-Score can be adjusted, allowing traders to fine-tune the indicator's sensitivity.
Divergence Detection: The tool offers controls to enable or disable divergence detection, with the ability to adjust the lookback periods for pivot detection.
Trend Coloring and Visuals: Traders can choose whether to color bars based on trend direction, display standard deviation levels, or visualize the data as a histogram or line plot.
Display Options: The indicator also allows for various display options, including showing the Z-Score values and divergence signals, with customizable colors and line widths.
Alerts and Signals
The Cumulative Volume Delta Z Score comes with pre-configured alert conditions for:
Z-Score Crossovers: Alerts are triggered when the Z-Score crosses the 0 line, indicating a potential trend reversal.
Shifting Trend: Alerts for when the Z-Score shifts direction, signaling a change in market sentiment.
Divergence Detection: Alerts for both regular and hidden bullish and bearish divergences, offering potential reversal signals.
Extreme Imbalances: Alerts when the Z-Score reaches extreme positive or negative levels, indicating overbought or oversold market conditions.
Applications in Trading
Trend Identification: Use the Z-Score to confirm bullish or bearish trends based on cumulative volume data, filtering out noise and false signals.
Reversal Signals: Divergences between price and CVD can help identify potential trend reversals, making it a powerful tool for swing traders.
Volume-Based Confirmation: The Z-Score allows traders to confirm price movements with volume data, providing more reliable signals compared to price action alone.
Divergence Strategy: Use the divergence signals to identify potential points of entry, particularly when regular or hidden divergences appear.
Volatility and Market Sentiment: The Z-Score provides insights into market volatility by measuring the deviation of CVD from its historical mean, helping to predict price movement strength.
The Cumulative Volume Delta Z Score is a powerful tool that combines volume analysis with statistical normalization. By focusing on volume imbalances and applying Z-Score normalization, this indicator provides clear, reliable signals for trend identification and potential reversals. It is especially useful for filtering out market noise and ensuring that trades are based on significant price movements driven by substantial volume changes.
This indicator is perfect for traders looking to add volume-based analysis to their strategy, offering a more robust and accurate way to gauge market sentiment and trend strength.
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ATH Levels v4# ATH Levels v4
A powerful indicator for tracking All-Time Highs (ATH) and setting customizable price levels based on percentage drops from the ATH. Perfect for cryptocurrency trading, DCA strategies, and risk management.
## Overview
ATH Levels v4 helps traders visualize key support levels calculated as percentage drops from the All-Time High within a configurable lookback period. The indicator also tracks the All-Time Low (ATL) since the last ATH, providing a complete picture of price range dynamics.
## Key Features
### Configurable Percentage Levels
- Define up to 8 custom price levels as percentage drops from ATH
- No longer limited to fixed 10% intervals
- Each level can be set anywhere from 0% to 100% drop
- Default levels: 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%
### ATL Tracking (NEW in v4)
- Automatically tracks the All-Time Low since the last ATH was reached
- Displays ATL price and percentage drop from ATH
- Resets when a new ATH is detected
- Can be toggled on/off
### Portfolio Management
- Allocate pot size percentages to each level
- Visualize dollar amounts for each level based on your total pot size
- Plan your DCA (Dollar Cost Averaging) strategy
- Only displays levels with allocated pot percentages
### Flexible Display Options
- Show/hide level lines
- Hide ATH level for zooming into lower levels
- Configurable lookback period (default 365 days)
- Adjustable right margin positioning for labels
- Color-coded labels with transparency gradient
## How to Use
### Basic Setup
1. Add the indicator to your chart
2. Set your total pot size in dollars
3. Configure the percentage drops for each level (where you want to buy/accumulate)
4. Allocate pot size percentages to each level
### Example DCA Strategy
```
Total Pot Size: $10,000
Level 3 (-30%): 10% pot = $1,000
Level 4 (-40%): 20% pot = $2,000
Level 5 (-50%): 25% pot = $2,500
Level 6 (-60%): 30% pot = $3,000
Level 7 (-70%): 10% pot = $1,000
Level 8 (-80%): 5% pot = $500
```
## Settings
### Display Options
- **Show level lines**: Toggle horizontal lines on/off
- **Hide ATH level**: Hide the ATH label for cleaner charts
- **Show ATL since last ATH**: Display/hide the All-Time Low indicator
- **Days to Lookback**: Period for calculating ATH (default: 365)
- **Margin from last bar**: Spacing between chart and labels (default: 10)
### Level Configuration
- **Level 1-8 % drop from ATH**: Set custom percentage drops (0-100%)
- **Level 1-8 pot %**: Allocate your portfolio percentage to each level (0-100%)
**Note**: Levels only display if they have a pot percentage allocated (>0%)
### Pot Size
- **Pot size**: Total amount in dollars available for the strategy
## Version History
### V4 (October 2025)
- Upgraded to PineScript v6
- Configurable percentage drops from ATH (no longer hardcoded)
- ATL tracking and display since last ATH
- Updated syntax and functions for v6 compatibility
### V3 (May 2020)
- Added option to hide ATH level for better chart zoom
### V2
- Hide/show level lines
- Configurable lookback period
- Configurable right margin
- Only shows levels with pot size % set
### V1
- Initial release with 8 fixed levels
## Use Cases
### Cryptocurrency Trading
- Plan accumulation zones during bear markets
- Set alerts at key percentage drops from ATH
- Track historical ATH and ATL ranges
### Risk Management
- Visualize potential support zones
- Plan position sizing at different levels
- Monitor distance from ATH in real-time
### DCA Strategies
- Automate dollar-cost averaging planning
- Allocate budget across multiple price levels
- Track execution of your DCA plan
## Technical Details
- **Version**: PineScript v6
- **Type**: Indicator
- **Overlay**: Yes
- **Default Timeframe**: Works on all timeframes
- **Calculations**: Based on closing prices within lookback period
## Credits
Original concept inspired by daytask. Enhanced and maintained by SilvesterScorpion.com
## License
This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
---
**Tip**: For best results, use on higher timeframes (4H, Daily, Weekly) to identify major support zones. Combine with volume analysis and other indicators for confirmation.
Enhanced Holt-Winters RSI [BOSWaves]Enhanced Holt-Winters RSI – Next-Level Momentum Smoothing & Signal Precision
Overview
The Enhanced Holt-Winters RSI transforms the classic Relative Strength Index into a robust, lag-minimized momentum oscillator through Holt-Winters triple exponential smoothing. By modeling the level, trend, and cyclical behavior of the RSI series, this indicator delivers smoother, more responsive signals that highlight overbought/oversold conditions, momentum shifts, and high-conviction trading setups without cluttering the chart with noise.
Unlike traditional RSI, which reacts to historical data and produces frequent whipsaws, the Enhanced Holt-Winters RSI filters transient price fluctuations, enabling traders to detect emerging momentum and potential reversal zones earlier.
Theoretical Foundation
The traditional RSI measures relative strength by comparing average gains and losses, but suffers from:
Lag in trend recognition : Signals often arrive after momentum has shifted.
Noise sensitivity : High-frequency price movements generate unreliable crossovers.
Limited insight into structural market shifts : Standard RSI cannot contextualize cyclical or momentum patterns.
The Enhanced Holt-Winters RSI addresses these limitations by applying triple exponential smoothing directly to the RSI series. This decomposes the series into:
Level (Lₜ) : Represents the smoothed central tendency of RSI.
Trend (Tₜ) : Captures rate-of-change in smoothed momentum.
Seasonal Component (Sₜ) : Models short-term cyclical deviations in momentum.
By incorporating these elements, the oscillator produces smoothed RSI values that react faster to emerging trends while suppressing erratic noise. Its internal forecast is mathematical, influencing the smoothed RSI output and signals, rather than being directly plotted.
How It Works
The Enhanced Holt-Winters RSI builds its signal framework through several layers:
1. Base RSI Calculation
Computes standard RSI over the selected period as the primary momentum input.
2. Triple Exponential Smoothing (Holt-Winters)
The RSI is smoothed recursively to extract underlying momentum structure:
Level, trend, and seasonal components are combined to produce a smoothed RSI.
This internal smoothing reduces lag and enhances signal reliability.
3. Momentum Analysis
Short-term momentum shifts are tracked via a moving average of the smoothed RSI, highlighting acceleration or deceleration in directional strength.
4. Volume Confirmation (Optional)
Buy/sell signals can be filtered through a configurable volume threshold, ensuring only high-conviction moves trigger alerts.
5. Visual Output
Colored Candles : Represent overbought (red), oversold (green), or neutral (yellow) conditions.
Oscillator Panel : Plots the smoothed RSI with dynamic color coding for immediate trend context.
Signals : Triangular markers indicate bullish or bearish setups, with stronger signals flagged in extreme zones.
Interpretation
The Enhanced Holt-Winters RSI provides a multi-dimensional perspective on price action:
Trend Strength : Smoothed RSI slope and color coding reflect the direction and momentum intensity.
Momentum Shifts : Rapid changes in the smoothed RSI indicate emerging strength or weakness.
Overbought/Oversold Zones : Highlight areas where price is stretched relative to recent momentum.
High-Conviction Signals : Combined with volume filtering, markers indicate optimal entries/exits.
Cycle Awareness : Smoothing reveals structural patterns, helping traders avoid reacting to noise.
By combining these elements, traders gain early insight into market structure and momentum without relying on raw, lag-prone RSI data.
Strategy Integration
The Enhanced Holt-Winters RSI can be applied across trading styles:
Trend Following
Enter when RSI is aligned with price momentum and color-coded signals confirm trend direction.
Strong slope in the smoothed RSI signals trend continuation.
Reversal Trading
Look for RSI extremes with momentum shifts and strong signal markers.
Compression in oscillator values often precedes reversal setups.
Breakout Detection
Oscillator flattening in neutral zones followed by directional expansion indicates potential breakout conditions.
Multi-Timeframe Confluence
Higher timeframes provide directional bias; lower timeframes refine entry timing using smoothed RSI dynamics.
Technical Implementation Details
Input Source : Close, open, high, low, or price.
Smoothing : Holt-Winters triple exponential smoothing applied to RSI.
Parameters :
Level (α) : Controls smoothing of RSI.
Trend (β) : Adjusts responsiveness to momentum changes.
Seasonal Length : Defines cycles for short-term adjustments.
Delta Smoothing : Reduces choppiness in smoothed RSI difference.
Outputs :
Smoothed RSI
Colored candles and oscillator panel
Buy/Sell signal markers (with optional strength filtering)
Volume Filtering : Optional threshold to confirm signals.
Optimal Application Parameters
Asset-Specific Guidance:
Forex : Use moderate smoothing (α, β) to capture medium-term momentum swings while filtering minor price noise. Works best when combined with volume or volatility filters.
Equities : Balance responsiveness and smoothness to identify sustained sector momentum or rotational shifts; ideal for capturing clean directional transitions.
Cryptocurrency : Increase smoothing parameters slightly to stabilize RSI during extreme volatility; optional volume confirmation can help filter false signals.
Futures/Indices : Lower smoothing sensitivity emphasizes macro momentum and structural trend durability over short-term fluctuations.
Timeframe Optimization:
Scalping (1-5m) : Use higher sensitivity (lower smoothing factors) to react quickly to micro-momentum reversals.
Intraday (15m-1h) : Balance smoothing and responsiveness for detecting short-term acceleration and exhaustion zones.
Swing (4h-Daily) : Apply moderate smoothing to reveal underlying directional persistence and cyclical reversals.
Position (Daily-Weekly) : Use stronger smoothing to isolate dominant momentum trends and filter temporary pullbacks.
Integration Guidelines
Combine with trend filters (EMAs, SuperSmoother MA, ATR-based tools) for confirmation.
Use volume and signal strength markers to filter low-conviction trades.
Slope, color, and signal alignment can guide entry, stop placement, and scaling.
Disclaimer
The Enhanced Holt-Winters RSI is a technical analysis tool, not a guaranteed profit system. Effectiveness depends on proper settings, market structure, and disciplined risk management. Always backtest before live trading.
Period Separator + Future Lines (Exchange-Time Synced)Monthly, Weekly, Daily,4hr and hr dividers and future separators (custom as wish, how many lines it should show in future)
Future separators corrected
First week of the yearA very simple indicator that marks a channel on the candlestick for the first week of the year.
The channel can serve as an entry/exit point with a medium and long term focus.
Note: This indicator should be observed exclusively on the weekly timeframe.
Opening Range Fibonacci Extensions (ATR Adjusted)this script displays daily, weekly, or monthly range extensions as a function of ATR in a Fibonacci retracement
Confluence Dashboard + Strategy [Daily + Weekly Adaptive]Removed duplicate strategy() declarations
Scoped getWeeklyBias() safely with correct request.security() usage
Ensured all variables are declared before use
Aligned background shading with bias logic
Streamlined signal tier logic to avoid overlap
Integrated strategy entries/exits cleanly
Confluence Zone BuilderWhat It Does
The Confluence Zone Builder is a technical analysis indicator that identifies high-probability price levels by detecting where multiple technical factors align (converge) at the same price area. These "confluence zones" represent levels where price is statistically more likely to react - either bouncing (support/resistance) or breaking through (breakout targets).
How It Works
1. Multi-Factor Analysis
The indicator calculates key technical levels from various sources:
Fibonacci Retracements (23.6%, 38.2%, 50%, 61.8%, 78.6%) - Support/resistance levels based on recent price swings
Fibonacci Extensions (127.2%, 141.4%, 161.8%, 200%, 261.8%) - Breakout targets beyond the current range (both bullish and bearish)
Pivot Points (Classic pivots: P, R1-R3, S1-S3) - Daily/weekly reference points traders watch
Moving Averages (EMA 20, 50 and SMA 100, 200) - Dynamic support/resistance that institutions track
VWAP - Volume-weighted average price, popular among institutional traders
Psychological Levels - Round numbers that attract orders
Previous Period Levels - Prior day/week high, low, and close
2. Proximity Clustering
When multiple factors fall within a defined proximity range (default 0.5%), they're grouped together into a single "confluence zone." This prevents cluttering the chart with dozens of individual lines.
3. Weighted Scoring System
Not all technical factors are equal. The indicator assigns importance weights:
Key Fibonacci levels (61.8%) and major MAs (200, 50) get higher weights (2.0-2.5x)
Pivot points and VWAP get medium weights (1.5x)
Minor factors get lower weights (1.0x)
The total score reflects both the number of factors and their importance.
4. Historical Validation
The indicator analyzes the last 50 bars (customizable) to track:
Touches: How many times price reached each zone
Rejections: Times price bounced off the zone (✅)
Breaks: Times price broke through the zone (❌)
Win Rate: Percentage of times the zone held (rejections ÷ touches)
5. Dynamic Adjustment
Zones aren't static - they adapt based on how price interacts with them:
Strengthens (+0.5 per rejection, +0.2 per touch): Zones that repeatedly hold become more important
Weakens (-0.8 per break): Zones that fail to hold lose credibility
Visual Indicators:
Thick solid lines = Strong zones (more rejections than breaks)
Dashed lines = Weak zones (more breaks than rejections)
Color-coded by score: Blue (low), Yellow (medium), Red (high)
What You Gain From Using It
For Support/Resistance Trading:
High-probability entries: Enter at zones with high confluence scores and strong historical win rates
Better risk management: Place stops beyond strong confluence zones that are likely to hold
Reduced false signals: Multi-factor confirmation reduces reliance on single indicators
For Breakout Trading:
Target identification: Fibonacci extensions provide profit targets beyond current ranges
Breakout confirmation: Weak zones (dashed lines, low win rates) are easier to break - ideal for breakout entries
False breakout avoidance: Strong zones (thick lines, high win rates) require more confirmation before entering
For Position Management:
Exit planning: Take profits at high-confluence zones ahead
Stop placement: Use strong zones as logical stop-loss levels
Trade filtering: Higher probability setups occur at stronger zones
Key Advantages:
Objective confluence detection - No manual line drawing needed
Data-driven validation - Historical performance shows which zones actually matter
Adaptive intelligence - Zones strengthen/weaken based on real price action
Clean visualization - Top zones only, with compact labels showing score and factors
Customizable - Adjust weights, components, and thresholds to your trading style
Bottom Line:
Instead of guessing which technical level matters most, this indicator does the heavy lifting - analyzing multiple factors, validating them historically, and highlighting only the zones where price is most likely to react. It's like having confluence analysis automated with statistical backing.
RSI Donchian Channel [DCAUT]█ RSI Donchian Channel
📊 ORIGINALITY & INNOVATION
The RSI Donchian Channel represents an important synthesis of two complementary analytical frameworks: momentum oscillators and breakout detection systems. This indicator addresses a common limitation in traditional RSI analysis by replacing fixed overbought/oversold thresholds with adaptive zones derived from historical RSI extremes.
Key Enhancement:
Traditional RSI analysis relies on static threshold levels (typically 30/70), which may not adequately reflect changing market volatility regimes. This indicator adapts the reference zones dynamically based on the actual RSI behavior over the lookback period, helping traders identify meaningful momentum extremes relative to recent price action rather than arbitrary fixed levels.
The implementation combines the proven momentum measurement capabilities of RSI with Donchian Channel's breakout detection methodology, creating a framework that identifies both momentum exhaustion points and potential continuation signals through the same analytical lens.
📐 MATHEMATICAL FOUNDATION
Core Calculation Process:
Step 1: RSI Calculation
The Relative Strength Index measures momentum by comparing the magnitude of recent gains to recent losses:
Calculate price changes between consecutive periods
Separate positive changes (gains) from negative changes (losses)
Apply selected smoothing method (RMA standard, also supports SMA, EMA, WMA) to both gain and loss series
Compute Relative Strength (RS) as the ratio of smoothed gains to smoothed losses
Transform RS into bounded 0-100 scale using the formula: RSI = 100 - (100 / (1 + RS))
Step 2: Donchian Channel Application
The Donchian Channel identifies the highest and lowest RSI values within the specified lookback period:
Upper Channel: Highest RSI value over the lookback period, represents the recent momentum peak
Lower Channel: Lowest RSI value over the lookback period, represents the recent momentum trough
Middle Channel (Basis): Average of upper and lower channels, serves as equilibrium reference
Channel Width Dynamics:
The distance between upper and lower channels reflects RSI volatility. Wide channels indicate high momentum variability, while narrow channels suggest momentum consolidation and potential breakout preparation. The indicator monitors channel width over a 100-period window to identify squeeze conditions that often precede significant momentum shifts.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Primary Signal Categories:
Breakout Signals:
Upper Breakout: RSI crosses above the upper channel, indicates momentum reaching new relative highs and potential trend continuation, particularly significant when accompanied by price confirmation
Lower Breakout: RSI crosses below the lower channel, suggests momentum reaching new relative lows and potential trend exhaustion or reversal setup
Breakout strength is enhanced when the channel is narrow prior to the breakout, indicating a transition from consolidation to directional movement
Mean Reversion Signals:
Upper Touch Without Breakout: RSI reaches the upper channel but fails to break through, may indicate momentum exhaustion and potential reversal opportunity
Lower Touch Without Breakout: RSI reaches the lower channel without breakdown, suggests potential bounce as momentum reaches oversold extremes
Return to Basis: RSI moving back toward the middle channel after touching extremes signals momentum normalization
Trend Strength Assessment:
Sustained Upper Channel Riding: RSI consistently remains near or above the upper channel during strong uptrends, indicates persistent bullish momentum
Sustained Lower Channel Riding: RSI stays near or below the lower channel during strong downtrends, reflects persistent bearish pressure
Basis Line Position: RSI position relative to the middle channel helps identify the prevailing momentum bias
Channel Compression Patterns:
Squeeze Detection: Channel width narrowing to 100-period lows indicates momentum consolidation, often precedes significant directional moves
Expansion Phase: Channel widening after a squeeze confirms the initiation of a new momentum regime
Persistent Narrow Channels: Extended periods of tight channels suggest market indecision and accumulation/distribution phases
🎯 STRATEGIC APPLICATIONS
Trend Continuation Strategy:
This approach focuses on identifying and trading momentum breakouts that confirm established trends:
Identify the prevailing price trend using higher timeframe analysis or trend-following indicators
Wait for RSI to break above the upper channel in uptrends (or below the lower channel in downtrends)
Enter positions in the direction of the breakout when price action confirms the momentum shift
Place protective stops below the recent swing low (long positions) or above swing high (short positions)
Target profit levels based on prior swing extremes or use trailing stops to capture extended moves
Exit when RSI crosses back through the basis line in the opposite direction
Mean Reversion Strategy:
This method capitalizes on momentum extremes and subsequent corrections toward equilibrium:
Monitor for RSI reaching the upper or lower channel boundaries
Look for rejection signals (price reversal patterns, volume divergence) when RSI touches the channels
Enter counter-trend positions when RSI begins moving back toward the basis line
Use the basis line as the initial profit target for mean reversion trades
Implement tight stops beyond the channel extremes to limit risk on failed reversals
Scale out of positions as RSI approaches the basis line and closes the position when RSI crosses the basis
Breakout Preparation Strategy:
This approach positions traders ahead of potential volatility expansion from consolidation phases:
Identify squeeze conditions when channel width reaches 100-period lows
Monitor price action for consolidation patterns (triangles, rectangles, flags) during the squeeze
Prepare conditional orders for breakouts in both directions from the consolidation
Enter positions when RSI breaks out of the narrow channel with expanding width
Use the channel width expansion as a confirmation signal for the breakout's validity
Manage risk with stops just inside the opposite channel boundary
Multi-Timeframe Confluence Strategy:
Combining RSI Donchian Channel analysis across multiple timeframes can improve signal reliability:
Identify the primary trend direction using a higher timeframe RSI Donchian Channel (e.g., daily or weekly)
Use a lower timeframe (e.g., 4-hour or hourly) to time precise entry points
Enter long positions when both timeframes show RSI above their respective basis lines
Enter short positions when both timeframes show RSI below their respective basis lines
Avoid trades when timeframes provide conflicting signals (e.g., higher timeframe below basis, lower timeframe above)
Exit when the higher timeframe RSI crosses its basis line in the opposite direction
Risk Management Guidelines:
Effective risk management is essential for all RSI Donchian Channel strategies:
Position Sizing: Calculate position sizes based on the distance between entry point and stop loss, limiting risk to 1-2% of capital per trade
Stop Loss Placement: For breakout trades, place stops just inside the opposite channel boundary; for mean reversion trades, use stops beyond the channel extremes
Profit Targets: Use the basis line as a minimum target for mean reversion trades; for trend trades, target prior swing extremes or use trailing stops
Channel Width Context: Increase position sizes during narrow channels (lower volatility) and reduce sizes during wide channels (higher volatility)
Correlation Awareness: Monitor correlations between traded instruments to avoid over-concentration in similar setups
📋 DETAILED PARAMETER CONFIGURATION
RSI Source:
Defines the price data series used for RSI calculation:
Close (Default): Standard choice providing end-of-period momentum assessment, suitable for most trading styles and timeframes
High-Low Average (HL2): Reduces the impact of closing auction dynamics, useful for markets with significant end-of-day volatility
High-Low-Close Average (HLC3): Provides a more balanced view incorporating the entire period's range
Open-High-Low-Close Average (OHLC4): Offers the most comprehensive price representation, helpful for identifying overall period sentiment
Strategy Consideration: Use Close for end-of-period signals, HL2 or HLC3 for intraday volatility reduction, OHLC4 for capturing full period dynamics
RSI Length:
Controls the number of periods used for RSI calculation:
Short Periods (5-9): Highly responsive to recent price changes, produces more frequent signals with increased false signal risk, suitable for short-term trading and volatile markets
Standard Period (14): Widely accepted default balancing responsiveness with stability, appropriate for swing trading and intermediate-term analysis
Long Periods (21-28): Produces smoother RSI with fewer signals but more reliable trend identification, better for position trading and reducing noise in choppy markets
Optimization Approach: Test different lengths against historical data for your specific market and timeframe, consider using longer periods in ranging markets and shorter periods in trending markets
RSI MA Type:
Determines the smoothing method applied to price changes in RSI calculation:
RMA (Relative Moving Average - Default): Wilder's original smoothing method providing stable momentum measurement with gradual response to changes, maintains consistency with classical RSI interpretation
SMA (Simple Moving Average): Treats all periods equally, responds more quickly to changes than RMA but may produce more whipsaws in volatile conditions
EMA (Exponential Moving Average): Weights recent periods more heavily, increases responsiveness at the cost of potential noise, suitable for traders prioritizing early signal generation
WMA (Weighted Moving Average): Applies linear weighting favoring recent data, offers a middle ground between SMA and EMA responsiveness
Selection Guidance: Maintain RMA for consistency with traditional RSI analysis, use EMA or WMA for more responsive signals in fast-moving markets, apply SMA for maximum simplicity and transparency
DC Length:
Specifies the lookback period for Donchian Channel calculation on RSI values:
Short Periods (10-14): Creates tight channels that adapt quickly to changing momentum conditions, generates more frequent trading signals but increases sensitivity to short-term RSI fluctuations
Standard Period (20): Balances channel responsiveness with stability, aligns with traditional Bollinger Bands and moving average periods, suitable for most trading styles
Long Periods (30-50): Produces wider, more stable channels that better represent sustained momentum extremes, reduces signal frequency while improving reliability, appropriate for position traders and higher timeframes
Calibration Strategy: Match DC length to your trading timeframe (shorter for day trading, longer for swing trading), test channel width behavior during different market regimes, consider using adaptive periods that adjust to volatility conditions
Market Adaptation: Use shorter DC lengths in trending markets to capture momentum shifts earlier, apply longer periods in ranging markets to filter noise and focus on significant extremes
Parameter Combination Recommendations:
Scalping/Day Trading: RSI Length 5-9, DC Length 10-14, EMA or WMA smoothing for maximum responsiveness
Swing Trading: RSI Length 14, DC Length 20, RMA smoothing for balanced analysis (default configuration)
Position Trading: RSI Length 21-28, DC Length 30-50, RMA or SMA smoothing for stable signals
High Volatility Markets: Longer RSI periods (21+) with standard DC length (20) to reduce noise
Low Volatility Markets: Standard RSI length (14) with shorter DC length (10-14) to capture subtle momentum shifts
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Adaptive Threshold Mechanism:
Unlike traditional RSI analysis with fixed 30/70 thresholds, this indicator's Donchian Channel approach provides several improvements:
Context-Aware Extremes: Overbought/oversold levels adjust automatically based on recent momentum behavior rather than arbitrary fixed values
Volatility Adaptation: In low volatility periods, channels narrow to reflect tighter momentum ranges; in high volatility, channels widen appropriately
Market Regime Recognition: The indicator implicitly adapts to different market conditions without manual threshold adjustments
False Signal Reduction: Adaptive channels help reduce premature reversal signals that often occur with fixed thresholds during strong trends
Signal Quality Characteristics:
The indicator's dual-purpose design provides distinct advantages for different trading objectives:
Breakout Trading: Channel boundaries offer clear, objective breakout levels that update dynamically, eliminating the ambiguity of when momentum becomes "too high" or "too low"
Mean Reversion: The basis line provides a natural profit target for reversion trades, representing the midpoint of recent momentum extremes
Trend Strength: Persistent channel boundary riding offers an objective measure of trend strength without additional indicators
Consolidation Detection: Channel width analysis provides early warning of potential volatility expansion from compression phases
Comparative Analysis:
When compared to traditional RSI implementations and other momentum frameworks:
vs. Fixed Threshold RSI: Provides market-adaptive reference levels rather than static values, helping to reduce false signals during trending markets where RSI can remain "overbought" or "oversold" for extended periods
vs. RSI Bollinger Bands: Offers clearer breakout signals and more intuitive extreme identification through actual high/low boundaries rather than statistical standard deviations
vs. Stochastic Oscillator: Maintains RSI's momentum measurement advantages (unbounded calculation avoiding scale compression) while adding the breakout detection capabilities of Donchian Channels
vs. Standard Donchian Channels: Applies breakout methodology to momentum space rather than price, providing earlier signals of potential trend changes before price breakouts occur
Performance Characteristics:
The indicator exhibits specific behavioral patterns across different market conditions:
Trending Markets: Excels at identifying momentum continuation through channel breakouts, RSI tends to ride one channel boundary during strong trends, providing trend confirmation
Ranging Markets: Channel width narrows during consolidation, offering early preparation signals for potential breakout trading opportunities
High Volatility: Channels widen to reflect increased momentum variability, automatically adjusting signal sensitivity to match market conditions
Low Volatility: Channels contract, making the indicator more sensitive to subtle momentum shifts that may be significant in calm market environments
Transition Periods: Channel squeezes often precede major trend changes, offering advance warning of potential regime shifts
Limitations and Considerations:
Users should be aware of certain operational characteristics:
Lookback Dependency: Channel boundaries depend entirely on the lookback period, meaning the indicator has no predictive element beyond identifying current momentum relative to recent history
Lag Characteristics: As with all moving average-based indicators, RSI calculation introduces lag, and channel boundaries update only as new extremes occur within the lookback window
Range-Bound Sensitivity: In extremely tight ranges, channels may become very narrow, potentially generating excessive signals from minor momentum fluctuations
Trending Persistence: During very strong trends, RSI may remain at channel extremes for extended periods, requiring patience for mean reversion setups or commitment to trend-following approaches
No Absolute Levels: Unlike traditional RSI, this indicator provides no fixed reference points (like 50), making it less suitable for strategies that depend on absolute momentum readings
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to help traders understand momentum dynamics and identify potential trading opportunities. The RSI Donchian Channel has limitations and should not be used as the sole basis for trading decisions.
Important considerations:
Performance varies significantly across different market conditions, timeframes, and instruments
Historical signal patterns do not guarantee future results, as market behavior continuously evolves
Effective use requires understanding of both RSI momentum principles and Donchian Channel breakout concepts
Risk management practices (stop losses, position sizing, diversification) are essential for any trading application
Consider combining with additional analytical tools such as volume analysis, price action patterns, or trend indicators for confirmation
Backtest thoroughly on your specific instruments and timeframes before live trading implementation
Be aware that optimization on historical data may lead to curve-fitting and poor forward performance
The indicator performs best when used as part of a comprehensive trading methodology that incorporates multiple forms of market analysis, sound risk management, and realistic expectations about win rates and drawdowns.
Inverse VIX / Custom Inverse Line🎯 Main Idea
This indicator creates a line that moves opposite to the VIX (Volatility Index) — or any symbol you choose.
When VIX rises (fear increases), → this line goes down.
When VIX falls (market calm), → this line goes up.
It helps you visually understand market sentiment — calm periods (bullish) vs fear periods (bearish).
⚙️ Input Settings
Setting Description
Symbol to invert The symbol to invert. Default is CBOE:VIX.
Inverse mode The method used to invert the values. There are 3 options:
① Negate Simply flips the sign (multiplies by -1). Very straightforward.
② Reciprocal Uses the mathematical inverse (1 ÷ value). High values become smaller, and vice versa.
③ Inverse Normalized The most useful mode 🔥 — normalizes values between 0–100 and flips them, similar to an RSI.
Normalization lookback How many bars to use for normalization (default 252 = roughly one trading year).
Smoothing (SMA) Number of bars for smoothing (makes the line smoother).
Use log for reciprocal Uses logarithmic scaling to stabilize big swings.
Plot color / width Customize the line’s color and thickness.
Show original source If enabled, shows the original VIX line for comparison.
📈 How It Works
The script fetches the close price of the VIX (or your chosen symbol).
It applies the selected inversion method.
The inverted line is plotted on the chart.
In “Inverse Normalized” mode:
The range is 0–100.
Values above 75 = high optimism (market often overheated).
Values below 25 = high fear (potential buying opportunity).
A middle line at 50 marks neutral sentiment.
⚠️ Alerts
The indicator includes two default alerts when using “Inverse Normalized” mode:
🔔 Above 75: Market showing strong optimism (potential top or correction zone).
🔔 Below 25: Market showing fear (potential bottom or buy signal).
🧠 How to Use It
Use it on daily or weekly charts for clearer signals.
Compare it with SPX or NASDAQ:
When the Inverse VIX line rises, markets often go up.
When it falls, markets usually drop or consolidate.
Combine it with other indicators (e.g., RSI, MACD) for confirmation.
MACD Enhanced [DCAUT]█ MACD Enhanced
📊 ORIGINALITY & INNOVATION
The MACD Enhanced represents a significant improvement over traditional MACD implementations. While Gerald Appel's original MACD from the 1970s was limited to exponential moving averages (EMA), this enhanced version expands algorithmic options by supporting 21 different moving average calculations for both the main MACD line and signal line independently.
This improvement addresses an important limitation of traditional MACD: the inability to adapt the indicator's mathematical foundation to different market conditions. By allowing traders to select from algorithms ranging from simple moving averages (SMA) for stability to advanced adaptive filters like Kalman Filter for noise reduction, this implementation changes MACD from a fixed-algorithm tool into a flexible instrument that can be adjusted for specific market environments and trading strategies.
The enhanced histogram visualization system uses a four-color gradient that helps communicate momentum strength and direction more clearly than traditional single-color histograms.
📐 MATHEMATICAL FOUNDATION
The core calculation maintains the proven MACD formula: Fast MA(source, fastLength) - Slow MA(source, slowLength), but extends it with algorithmic flexibility. The signal line applies the selected smoothing algorithm to the MACD line over the specified signal period, while the histogram represents the difference between MACD and signal lines.
Available Algorithms:
The implementation supports a comprehensive spectrum of technical analysis algorithms:
Basic Averages: SMA (arithmetic mean), EMA (exponential weighting), RMA (Wilder's smoothing), WMA (linear weighting)
Advanced Averages: HMA (Hull's low-lag), VWMA (volume-weighted), ALMA (Arnaud Legoux adaptive)
Mathematical Filters: LSMA (least squares regression), DEMA (double exponential), TEMA (triple exponential), ZLEMA (zero-lag exponential)
Adaptive Systems: T3 (Tillson T3), FRAMA (fractal adaptive), KAMA (Kaufman adaptive), MCGINLEY_DYNAMIC (reactive to volatility)
Signal Processing: ULTIMATE_SMOOTHER (low-pass filter), LAGUERRE_FILTER (four-pole IIR), SUPER_SMOOTHER (two-pole Butterworth), KALMAN_FILTER (state-space estimation)
Specialized: TMA (triangular moving average), LAGUERRE_BINOMIAL_FILTER (binomial smoothing)
Each algorithm responds differently to price action, allowing traders to match the indicator's behavior to market characteristics: trending markets benefit from responsive algorithms like EMA or HMA, while ranging markets require stable algorithms like SMA or RMA.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Histogram Interpretation:
Positive Values: Indicate bullish momentum when MACD line exceeds signal line, suggesting upward price pressure and potential buying opportunities
Negative Values: Reflect bearish momentum when MACD line falls below signal line, indicating downward pressure and potential selling opportunities
Zero Line Crosses: MACD crossing above zero suggests transition to bullish bias, while crossing below indicates bearish bias shift
Momentum Changes: Rising histogram (regardless of positive/negative) signals accelerating momentum in the current direction, while declining histogram warns of momentum deceleration
Advanced Signal Recognition:
Divergences: Price making new highs/lows while MACD fails to confirm often precedes trend reversals
Convergence Patterns: MACD line approaching signal line suggests impending crossover and potential trade setup
Histogram Peaks: Extreme histogram values often mark momentum exhaustion points and potential reversal zones
🎯 STRATEGIC APPLICATIONS
Comprehensive Trend Confirmation Strategies:
Primary Trend Validation Protocol:
Identify primary trend direction using higher timeframe (4H or Daily) MACD position relative to zero line
Confirm trend strength by analyzing histogram progression: consistent expansion indicates strong momentum, contraction suggests weakening
Use secondary confirmation from MACD line angle: steep angles (>45°) indicate strong trends, shallow angles suggest consolidation
Validate with price structure: trending markets show consistent higher highs/higher lows (uptrend) or lower highs/lower lows (downtrend)
Entry Timing Techniques:
Pullback Entries in Uptrends: Wait for MACD histogram to decline toward zero line without crossing, then enter on histogram expansion with MACD line still above zero
Breakout Confirmations: Use MACD line crossing above zero as confirmation of upward breakouts from consolidation patterns
Continuation Signals: Look for MACD line re-acceleration (steepening angle) after brief consolidation periods as trend continuation signals
Advanced Divergence Trading Systems:
Regular Divergence Recognition:
Bullish Regular Divergence: Price creates lower lows while MACD line forms higher lows. This pattern is traditionally considered a potential upward reversal signal, but should be combined with other confirmation signals
Bearish Regular Divergence: Price makes higher highs while MACD shows lower highs. This pattern is traditionally considered a potential downward reversal signal, but trading decisions should incorporate proper risk management
Hidden Divergence Strategies:
Bullish Hidden Divergence: Price shows higher lows while MACD displays lower lows, indicating trend continuation potential. Use for adding to existing long positions during pullbacks
Bearish Hidden Divergence: Price creates lower highs while MACD forms higher highs, suggesting downtrend continuation. Optimal for adding to short positions during bear market rallies
Multi-Timeframe Coordination Framework:
Three-Timeframe Analysis Structure:
Primary Timeframe (Daily): Determine overall market bias and major trend direction. Only trade in alignment with daily MACD direction
Secondary Timeframe (4H): Identify intermediate trend changes and major entry opportunities. Use for position sizing decisions
Execution Timeframe (1H): Precise entry and exit timing. Look for MACD line crossovers that align with higher timeframe bias
Timeframe Synchronization Rules:
Daily MACD above zero + 4H MACD rising = Strong uptrend context for long positions
Daily MACD below zero + 4H MACD declining = Strong downtrend context for short positions
Conflicting signals between timeframes = Wait for alignment or use smaller position sizes
1H MACD signals only valid when aligned with both higher timeframes
Algorithm Considerations by Market Type:
Trending Markets: Responsive algorithms like EMA, HMA may be considered, but effectiveness should be tested for specific market conditions
Volatile Markets: Noise-reducing algorithms like KALMAN_FILTER, SUPER_SMOOTHER may help reduce false signals, though results vary by market
Range-Bound Markets: Stability-focused algorithms like SMA, RMA may provide smoother signals, but individual testing is required
Short Timeframes: Low-lag algorithms like ZLEMA, T3 theoretically respond faster but may also increase noise
Important Note: All algorithm choices and parameter settings should be thoroughly backtested and validated based on specific trading strategies, market conditions, and individual risk tolerance. Different market environments and trading styles may require different configuration approaches.
📋 DETAILED PARAMETER CONFIGURATION
Comprehensive Source Selection Strategy:
Price Source Analysis and Optimization:
Close Price (Default): Most commonly used, reflects final market sentiment of each period. Best for end-of-day analysis, swing trading, daily/weekly timeframes. Advantages: widely accepted standard, good for backtesting comparisons. Disadvantages: ignores intraday price action, may miss important highs/lows
HL2 (High+Low)/2: Midpoint of the trading range, reduces impact of opening gaps and closing spikes. Best for volatile markets, gap-prone assets, forex markets. Calculation impact: smoother MACD signals, reduced noise from price spikes. Optimal when asset shows frequent gaps, high volatility during specific sessions
HLC3 (High+Low+Close)/3: Weighted average emphasizing the close while including range information. Best for balanced analysis, most asset classes, medium-term trading. Mathematical effect: 33% weight to high/low, 33% to close, provides compromise between close and HL2. Use when standard close is too noisy but HL2 is too smooth
OHLC4 (Open+High+Low+Close)/4: True average of all price points, most comprehensive view. Best for complete price representation, algorithmic trading, statistical analysis. Considerations: includes opening sentiment, smoothest of all options but potentially less responsive. Optimal for markets with significant opening moves, comprehensive trend analysis
Parameter Configuration Principles:
Important Note: Different moving average algorithms have distinct mathematical characteristics and response patterns. The same parameter settings may produce vastly different results when using different algorithms. When switching algorithms, parameter settings should be re-evaluated and tested for appropriateness.
Length Parameter Considerations:
Fast Length (Default 12): Shorter periods provide faster response but may increase noise and false signals, longer periods offer more stable signals but slower response, different algorithms respond differently to the same parameters and may require adjustment
Slow Length (Default 26): Should maintain a reasonable proportional relationship with fast length, different timeframes may require different parameter configurations, algorithm characteristics influence optimal length settings
Signal Length (Default 9): Shorter lengths produce more frequent crossovers but may increase false signals, longer lengths provide better signal confirmation but slower response, should be adjusted based on trading style and chosen algorithm characteristics
Comprehensive Algorithm Selection Framework:
MACD Line Algorithm Decision Matrix:
EMA (Standard Choice): Mathematical properties: exponential weighting, recent price emphasis. Best for general use, traditional MACD behavior, backtesting compatibility. Performance characteristics: good balance of speed and smoothness, widely understood behavior
SMA (Stability Focus): Equal weighting of all periods, maximum smoothness. Best for ranging markets, noise reduction, conservative trading. Trade-offs: slower signal generation, reduced sensitivity to recent price changes
HMA (Speed Optimized): Hull Moving Average, designed for reduced lag. Best for trending markets, quick reversals, active trading. Technical advantage: square root period weighting, faster trend detection. Caution: can be more sensitive to noise
KAMA (Adaptive): Kaufman Adaptive MA, adjusts smoothing based on market efficiency. Best for varying market conditions, algorithmic trading. Mechanism: fast smoothing in trends, slow smoothing in sideways markets. Complexity: requires understanding of efficiency ratio
Signal Line Algorithm Optimization Strategies:
Matching Strategy: Use same algorithm for both MACD and signal lines. Benefits: consistent mathematical properties, predictable behavior. Best when backtesting historical strategies, maintaining traditional MACD characteristics
Contrast Strategy: Use different algorithms for optimization. Common combinations: MACD=EMA, Signal=SMA for smoother crossovers, MACD=HMA, Signal=RMA for balanced speed/stability, Advanced: MACD=KAMA, Signal=T3 for adaptive behavior with smooth signals
Market Regime Adaptation: Trending markets: both fast algorithms (EMA/HMA), Volatile markets: MACD=KALMAN_FILTER, Signal=SUPER_SMOOTHER, Range-bound: both slow algorithms (SMA/RMA)
Parameter Sensitivity Considerations:
Impact of Parameter Changes:
Length Parameter Sensitivity: Small parameter adjustments can significantly affect signal timing, while larger adjustments may fundamentally change indicator behavior characteristics
Algorithm Sensitivity: Different algorithms produce different signal characteristics. Thoroughly test the impact on your trading strategy before switching algorithms
Combined Effects: Changing multiple parameters simultaneously can create unexpected effects. Recommendation: adjust parameters one at a time and thoroughly test each change
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Response Characteristics by Algorithm:
Fastest Response: ZLEMA, HMA, T3 - minimal lag but higher noise
Balanced Performance: EMA, DEMA, TEMA - good trade-off between speed and stability
Highest Stability: SMA, RMA, TMA - reduced noise but increased lag
Adaptive Behavior: KAMA, FRAMA, MCGINLEY_DYNAMIC - automatically adjust to market conditions
Noise Filtering Capabilities:
Advanced algorithms like KALMAN_FILTER and SUPER_SMOOTHER help reduce false signals compared to traditional EMA-based MACD. Noise-reducing algorithms can provide more stable signals in volatile market conditions, though results will vary based on market conditions and parameter settings.
Market Condition Adaptability:
Unlike fixed-algorithm MACD, this enhanced version allows real-time optimization. Trending markets benefit from responsive algorithms (EMA, HMA), while ranging markets perform better with stable algorithms (SMA, RMA). The ability to switch algorithms without changing indicators provides greater flexibility.
Comparative Performance vs Traditional MACD:
Algorithm Flexibility: 21 algorithms vs 1 fixed EMA
Signal Quality: Reduced false signals through noise filtering algorithms
Market Adaptability: Optimizable for any market condition vs fixed behavior
Customization Options: Independent algorithm selection for MACD and signal lines vs forced matching
Professional Features: Advanced color coding, multiple alert conditions, comprehensive parameter control
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions. Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always combine with proper risk management and thorough strategy testing.
HTF Candle Overlay - PO3HTF Candle Overlay Script Description
This Pine Script indicator creates a visual overlay of higher timeframe (HTF) candles on your chart. It's a useful tool for multi-timeframe analysis that allows you to see higher timeframe price action context directly on your current chart without having to switch between timeframes.
Main Purpose
The primary purpose of this indicator is to display candles from a higher timeframe (like daily or weekly) directly on your lower timeframe chart (like 5-minute or hourly). This provides crucial context about the larger market structure while you're analyzing shorter-term price movements.
Key Features
Higher Timeframe Selection: You can choose any higher timeframe from the available options (1-minute to monthly), allowing you to view price action from any timeframe higher than your current chart.
Customizable Appearance:
Control the number of HTF candles displayed (1-10)
Adjust the spacing between the candles and current price
Modify candle width for better visibility
Customize colors for bullish and bearish candles, wicks, and borders
Real-time Updates: The current (ongoing) HTF candle updates in real-time as new price data comes in, showing you how the higher timeframe candle is developing.
Time Remaining Display: An optional label shows the current HTF period and how much time remains until the candle closes, helping you time your entries and exits.
Visual Warnings: The script warns you if you select a timeframe that matches your current chart timeframe.
How It Works
Data Retrieval: The script fetches both the current developing candle and historical candles from the selected higher timeframe using request.security() calls.
Candle Processing:
It stores candle data (open, high, low, close, and time) in arrays
Handles both the current developing candle and past completed candles
Updates the current candle in real-time as new price data comes in
Visual Rendering:
Draws candle bodies as boxes with appropriate bullish/bearish colors
Creates wicks as lines extending from the candle bodies
Places candles horizontally on your chart with proper spacing
Timing Information:
Calculates and displays the remaining time until the current higher timeframe candle closes
Formats the time remaining in a user-friendly way (days, hours, minutes)
Practical Applications
Context for Trading Decisions: See where price is in relation to higher timeframe support/resistance levels.
Entry and Exit Timing: Time your entries and exits based on higher timeframe candle closings.
Trend Alignment: Ensure your trades align with the higher timeframe trend direction.
Support/Resistance Identification: Easily identify key price levels from higher timeframes.
Candle Pattern Recognition: Spot important higher timeframe candlestick patterns without switching timeframes.
This indicator essentially brings the higher timeframe context directly to your current chart, allowing for more informed trading decisions that consider both short-term and long-term market structures simultaneously.
cd_VWAP_mtg_CxCd_VWAP_mtg_Cx
Overview
The most important condition for being successful and profitable in the market is to consistently follow the same rules without compromise, while the price constantly moves in countless different ways.
Regardless of the concept or trading school, those who have rules win.
In this indicator, we will define and use three main sections to set and apply our rules.
The indicator uses the VWAP (Volume Weighted Average Price) — price weighted by volume.
Two VWAPs can be displayed either by manually entering date and time, or by selecting from the menu.
From the menu, you can select the following reference levels:
• HTF Open: Opening candle of the higher timeframe
• ATH / ATL: All-Time High / All-Time Low candles
• PMH / PML, PWH / PWL, PDH / PDL, PH4H / PH4L: Previous Month, Week, Day, or H4 Highs/Lows
• MH / ML, WH / WL, DH / DL, H4H / H4L: Current Month, Week, Day, or H4 Highs/Lows
Additionally, it includes:
• Mitigation / Order Block zones (local buyer-seller balance) across two timeframes.
• Buy/Sell Side Liquidity levels (BSL / SSL) from the aligned higher timeframe (target levels).
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Components and Usage
1 – VWAP
Calculated using the classical method:
• High + Volume for the upper value
• Close + Volume for the middle value
• Low + Volume for the lower value
The VWAP is displayed as a colored band, where the coloring represents the bias.
Let’s call this band FVB (Fair Value Band) for ease of explanation.
The FVB represents the final line of defense, the buyer/seller boundary, and in technical terms, it can be viewed as premium/discount zones or support/resistance levels.
Within this critical area, the strong side continues its move, while the weaker side is forced to retreat.
But does the side that breaks beyond the band always keep going?
We all know that’s not always the case — in different pairs and timeframes, price often violates both the upper and lower edges multiple times.
To achieve more consistent analysis, we’ll define a new set of rules.
________________________________________
2 – Mitigation / Order Blocks
In trading literature, there are dozens of different definitions and uses of mitigation or order blocks.
Here, we will interpret the candlesticks to create our own definition, and we’ll use the zones defined by candles that fit this pattern.
For simplicity, let’s abbreviate mitigation as “mtg.”
For a candle to be selected as an mtg, it must clearly show strength from one side (buyers or sellers) — which can also be observed visually on the chart.
________________________________________
Bullish mtg criteria:
1. The first candle must be bullish (close > open) → buyers are strong.
2. The next candle makes a new high (buyers push higher) but fails to close above and pulls back to close inside the previous range → sellers react.
It also must not break the previous low → buyers defend.
3. In the following candle(s), as long as the first candle’s low is protected and the second candle’s high is broken, it indicates buyer strength → a bullish mtg is confirmed.
When price returns to this zone later (gets mitigated), the expectation is that the zone holds and price pushes upward again.
If the low is violated, the mtg becomes invalid.
In technical terms:
If the previous candle’s high is broken but no close occurs above it, the expectation is a reversal move that will retest its low.
Question:
What if the low is protected and in the next candle(s) a new high forms?
Answer: → Bullish mtg.
Bearish mtg (opposite)
3 – Buy/Sell Side Liquidity Levels
With the help of the aligned higher timeframe (swing points), we will define our market structure framework and set our liquidity targets accordingly.
Let’s put the pieces together.
If we continue explaining from a trade-focused perspective, our first priority should be our bias — our projection or expectation of the market’s potential movement.
We will determine this bias using the FVB.
Since we know the band often gets violated on both sides, we want the price action to convince us of its strength.
To do that, we’ll use the first candle that closes beyond the band.
The distance from that candle’s high to low will be our threshold range
Bullish level = high + (candle length × coefficient)
Bearish level = low - (candle length × coefficient)
When the price closes beyond this threshold, it demonstrates strength, and our bias will now align in that direction.
How long will this bias remain valid?
→ Until a closing candle appears on the opposite side of the band.
If a close occurs on the opposite side, then a new bias will only be confirmed once the new threshold level is broken.
During the period in between, we have no bias.
Let’s continue on the chart:
Now that our bias has been established, where and how do we look for trade opportunities?
There are two possible entry approaches:
• Aggressive entry: Enter immediately with the breakout.
• Conservative entry: Wait for a pullback and enter once a suitable structure forms.
(The choice depends on the user’s preference.)
At this stage, the user can apply their own entry model. Let’s give an example:
Let’s assume we’re looking for setups using HTF sweep + LTF CISD confirmation.
Once our bias turns bearish, we look for an HTF sweep forming on or near an FVB or mtg block, and then confirm the entry with a CISD signal.
In summary:
• FVB defines the bias, the entry zone, and the target zone.
• Mtg blocks represent entry zones.
• BSL / SSL levels suggest target zones.
Overlapping FVB and mtg blocks are expected to be more effective.
The indicator also provides an option for a second FVB.
A band attached to a lower timeframe can be used as confirmation.
• Main band: Bias + FVB
• Extra band: Entry trigger confirmed by a close beyond it.
Mtg blocks can provide trade entry opportunities, especially when the price is moving strongly in one direction (flow).
Consecutive or complementary mtg blocks indicate that the price is decisive in one direction, while sometimes also showing areas where we should wait before entering.
Mtg blocks that contain an FVG (Fair Value Gap) within their body are expected to be more effective.
Settings:
The default values are set to 1-3-5m, optimized for scalping trades.
VWAP settings:
Main VWAP (FVB):
• Can be set by selecting a start time, manually entering date and time, or choosing a predefined level.
Extra VWAP (FVB):
• Set from the menu. If not needed, select “none.”
• Visibility, color, and fill settings for VWAP are located here.
• Threshold levels visibility and color options are also in this section.
• The multiplier is used for calculating the threshold level.
Important:
• If the Extra VWAP is selected but not displayed, you need to increase the chart timeframe.
o Example: If the chart is on 3m and you select WH from the extra options, it will not display correctly.
• Upper limits for VWAP:
o 1m and 3m charts: daily High/Low
o 5m chart: weekly High/Low
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Mtg Settings:
• Visibility and color settings for blocks are configured here.
• To display on a second timeframe, the box must be checked and the timeframe specified.
• Optional display modes: “only active blocks,” “only last violated mtg,” or “all.”
• For confirmation and removal criteria, choosing high/low or close determines the source used for mtg block formation and deletion conditions.
BSL/SSL Settings:
• Visibility, color, font size, and line style can be configured in this section.
When “Auto” is selected, the aligned timeframe is determined automatically by the indicator, while in manual mode, the user defines the timeframe.
Final Words:
Simply opening trades every time the price touches the VWAP or mtg blocks will not make you a profitable trader. Searching for setups with similar structures while maintaining proper risk management will yield better results in the long run.
I would be happy to hear your feedback and suggestions.
Happy trading!
Supply/Demand Zones & EMA CrossSupport and Resistance Zone based on past ten days for daily, weekly, with this ema 8,20,50,200 and vwap also inclued
Inside Bar Highlighter by nkChartsOverview:
The Inside Candle Highlighter is a simple yet powerful TradingView indicator designed to identify inside bars (inside candles) on your chart. An inside candle is defined as a candle whose high is lower than the previous candle's high and low is higher than the previous candle's low, meaning it forms entirely within the range of the preceding candle.
Inside candles are commonly interpreted by traders as periods of market consolidation or indecision and often precede breakouts or significant price moves. This indicator highlights these candles directly on your chart, making them easy to spot at a glance.
Features
Detects Inside Candles: Automatically identifies bars that are fully contained within the previous bar’s high-low range.
Confirmed Bar Coloring: Colors the candle after it closes, ensuring no repainting occurs during formation.
Style Tab Customization: Users can adjust the candle color directly from the Style tab, allowing seamless integration with your chart theme.
Clean & Minimal: Only inside candles are highlighted, keeping charts uncluttered.
How Traders Can Use It
Identify Consolidation Zones: Quickly spot periods where the market is contracting.
Prepare for Breakouts: Inside candles often signal an upcoming directional move; traders can plan entry or exit points based on breakouts from the inside candle range.
Combine With Other Indicators: Use alongside trend indicators, volume tools, or support/resistance levels to enhance trade confirmation.
Recommended Use
Works on all timeframes — from intraday charts to daily or weekly charts.
Particularly useful in price action trading, swing trading, and trend-following strategies.
Ideal for traders who want a visual cue for consolidation and potential breakout areas without adding complexity to the chart.
Note: This indicator only highlights inside candles. Interpretation and trading decisions are left to the user.
Rolling Midpoint of Price & VWAP with ATR BandsThe Rolling Midpoint of Price & VWAP with ATR Bands indicator is a dual-equilibrium concept that fuses price-range structure and traded-volume flow into one continuously updating hybrid model. Traditional VWAPs reset each session and reflect where trading occurred by volume, while midpoints used here reveal where price has structurally balanced between extremes. This script merges both ideas into a cohesive, dynamic system. The Rolling Price Midpoint (50 % of range) represents the structural fair-value line, calculated as the average of the highest high and lowest low over a selected window. The Rolling VWAP (Volume-Weighted Window) tracks the flow-based fair-value line by weighting each bar’s typical price by its volume. Together, these components form the Hybrid Equilibrium — the adaptive center of gravity that shifts as price and volume evolve. Surrounding this equilibrium, ATR Bands at ± 2.226 ATR and ± 5.382 ATR define volatility envelopes that expand and contract with market energy. The result is a living cloud that breathes with the market: compressing during phases of balance and widening during impulsive movements, offering traders a clear visual framework for understanding equilibrium, volatility, and directional bias in real time.
➖
⚙️ Auto-Preset System
The Auto-Preset System intelligently adjusts lookback windows for both the Price Midpoint and VWAP calculations according to the active chart timeframe.
This ensures that the indicator automatically adapts to any trading style — from scalping on 1-minute charts to swing trading on daily or weekly charts — without manual tuning.
🔹 How It Works
When Auto-Preset mode is enabled, the script dynamically selects the most effective lookback lengths for each timeframe.
These presets are optimized to balance responsiveness and stability, maintaining consistent real-world coverage (e.g., the same approximate duration of price data) across all intervals.
📊 Preset Mapping Table
| Chart Timeframe | Price Midpoint Lookback | VWAP Lookback |
|:----------------:|:-----------------------:|:--------------:|
| 1–3m | 13 bars | 21 bars
| 5–10m | 21 bars | 34 bars
| 15–30m | 34 bars | 55 bars
| 1–2 hr | 55 bars | 89 bars
| 4 hr-1D | 89 bars | 144 bars
| 1W | 144 bars | 233 bars
| 1M | 233 bars | 377 bars
⚡ Notes & Customization
- Manual Override: Turn off Auto-Preset Mode to specify your own custom lookback lengths.
- Consistency Across Scales: These adaptive values keep the indicator visually coherent when switching between timeframes — avoiding distortions that can occur with static lengths.
- Practical Benefit: Traders can maintain a single chart layout that self-tunes seamlessly, removing the need to manually recalibrate settings when shifting from short-term to long-term analysis.
In short, the Auto-Preset System is designed to make this hybrid equilibrium tool timeframe-aware — automatically scaling its logic so that the cloud behaves consistently, regardless of chart resolution.
➖
🌐 Hybrid Equilibrium Envelope
The core hybrid midpoint acts as the mean of structural (price) and volumetric (VWAP) balance.
ATR-based bands project natural expansion zones:
🔸+2.226 / –2.226 ATR → inner equilibrium (controlled trend)
*🔸+5.382 / –5.382 ATR → outer volatility extension (over-stretch / reversion zones)
Color-coded fills show regime strength:
* 🟧 Upper Outer (+5.382) – strong bullish expansion
* 🟩 Upper Inner (+2.226) – trending equilibrium
* 🔴 Lower Inner (–2.226) – mild bearish control
* 🟣 Lower Outer (–5.382) – volatility exhaustion
➖
🧭 Higher-Timeframe Framework
Two macro anchors — Price length of 144 and VWAP length of 233 — outline higher-timeframe bias zones. These help confirm when local momentum aligns with (or fades against) long-term structure.
Labels on the right show active lookback values for quick readout:
`$(13) V(21)` → current rolling pair
`$144 / V233` → macro anchors
➖
🧩 Chart Examples
**AMD 15m (Equilibrium Expansion)**
Price steadily rides above the hybrid midpoint as teal and orange (bullish) ATR zones widen, confirming a phase of controlled bullish volatility and healthy trend expansion.
BTCUSD 1m (Volatility Compression)
Bitcoin coils tightly inside the teal-to-maroon equilibrium bands before breaking out.
The hybrid midpoint flattens and ATR envelopes contract, signaling a state of balance before volatility expansion.
ETHUSD 15m (Transition from Compression → Impulse)
Ethereum transitions from purple-zone compression into a clear upper-band expansion.
The hybrid midpoint breaks above the macro VWAP 233, confirming the shift from equilibrium to directional momentum.
SOFI 1m (Micro Bias Reversal)
SOFI’s intraday structure flips as price reclaims the hybrid midpoint.
The macro VWAP 233 flattens, signaling a transition from oversold lower bands back toward equilibrium and early trend recovery.
➖
🎯 How to Use
1. Bias Detection – Price > Hybrid Midpoint → bullish; < → bearish.
2. Volatility Gauge – Watch band spacing for compression / expansion cycles.
3. Confluence Checks – Align Hybrid Midpoint with HTF 233 VWAP for strong continuation signals.
4. Mean Reversion Zones – Outer bands highlight areas where probability of snap-back increases.
➖
🔧 Inputs & Customization
Auto Presets toggle
🔸Manual Lookback Overrides** for fine-tuning
🔸Plot Window Length** (show recent vs full history)
🔸ATR Sensitivity & Fill Opacity** controls
🔸Label Padding / Font Size** for cleaner overlay visuals
➖
🧮 Formula Highlights
➖Rolling Midpoint = (highest(high,N) + lowest(low,N)) / 2
➖Rolling VWAP = Σ(Typical Price×Vol) / Σ(Vol)
➖Hybrid = (PriceMid + VWAP) / 2
➖Upper₂ = Hybrid + ATR×2.226
➖Lower₂ = Hybrid − ATR×2.226
➖Upper₅ = Hybrid + ATR×5.382
➖Lower₅ = Hybrid − ATR×5.382
➖
🎯 Ideal For
➡️ Traders who want adaptive fair-value zones that evolve with both price and volume.
➡️ Analysts who shift between scalping, swing, and position timeframes, and need a tool that self-adjusts.
➡️ Those who rely on visual structure clarity to confirm setups across changing volatility conditions.
➡️ Anyone seeking a hybrid model that unites structural range logic (midpoint) and flow-based balance (VWAP).
➖
🏁 Final Word
This script is more than a visual overlay — it’s a complete trend and structure framework built to adapt with market rhythm. It helps traders visualize equilibrium, momentum, and volatility as one cohesive system. Whether you’re seeking clean trend alignment, dynamic support/resistance, or early warning signs of reversals, this indicator is tuned to help you react with confidence — not hindsight.
➖
Remember — no single indicator should ever stand alone. For best results, pair it with price action context, higher-timeframe structure, and complementary tools such as moving averages or trendlines. Use it to confirm setups, not define them in isolation.
💡 Turn logic into clarity, structure into trades, and uncertainty into confidence.
Cumulative Volume DeltaCumulative Volume Delta (CVD) Indicator
This indicator is a modification of the Trading View CVD indicator. Cumulative Volume Delta (CVD), which represents the net difference between up volume (volume traded as the price increases) and down volume (volume traded as the price decreases) over a chosen Anchor Period.
The data for the CVD calculation is requested using the built-in ta.requestVolumeDelta function from a lower timeframe to approximate the directional volume with greater precision. This lower timeframe is either automatically selected based on the chart's timeframe or can be customized by the user.
Key Features and Inputs
Anchor Period: Defines the period over which the volume delta is accumulated and plotted. The default is "1D" (Daily), but it can be changed to any higher timeframe (e.g., "1W" for Weekly) to analyze CVD across different cycles.
CVD Candle Plot: The calculated volume delta values are plotted as a custom candle, where:
The open and close of the CVD candle represent the volume delta at the start and end of the anchor period, respectively.
The high and low represent the maximum and minimum volume delta reached during that period.
Up/Down Coloring Logic: The color of the CVD candle is determined by the directional movement of the price during the anchor period, allowing traders to quickly correlate volume delta with price action. Users can select between two methods via the "Strong Up/Down Coloring" input:
Strong Up/Down (Default): The candle is colored bullish (Teal) if the current price closes above the previous bar's high or bearish (Red) if it closes below the previous bar's low. This logic highlights significant momentum.
Regular Up/Down: The candle is colored bullish (Teal) if the close is greater than the open (price moved up) or bearish (Red) if the close is less than the open (price moved down).
Lower Timeframe Selection: This determines the resolution of the up and down volume components.
By default, the script automatically selects an appropriate lower timeframe (e.g., "1" minute for intraday charts, "5" minutes for daily charts) to balance historical data availability with calculation precision.
An option is provided to customize this "Lower Timeframe" for advanced users seeking higher or lower resolution.
The CVD indicator is a powerful tool for analyzing order flow dynamics and assessing the genuine strength of price movements by comparing the aggregate buying pressure (up volume) against the selling pressure (down volume).
Technical Notes (Code Details)
Language: Pine Script® //@version=6.
Function: Utilizes the ta.requestVolumeDelta() function with a user-defined anchorInput (default "1D") and a determined lowerTimeframe to retrieve the relevant delta data: .
Error Handling: Includes a check to confirm the symbol provides volume data, preventing runtime errors.
LA - EMA Bands with MTF DashboardDetailed Explanation of the LA - EMA Bands with MTF Dashboard Indicator
This custom Pine Script v6 indicator, designed for Trading View, overlays EMA-based price channels on the chart while incorporating a multi-timeframe (MTF) dashboard for broader market context. It focuses on visualizing trend direction and momentum through three sets of EMA bands, each representing different time horizons, and extends this with a tabular dashboard that summarizes signals across user-selected timeframes. The bands help identify support, resistance, and trend shifts, while the dashboard provides at-a-glance alignment across multiple periods, aiding in confirming trades or spotting divergences. Unlike volatility-based channels (e.g., Bollinger or Keltner), it relies solely on EMAs for simplicity and lag-reduced responsiveness.
Inputs Section
The script begins with user-configurable options grouped for ease. A timeframe input allows specifying a resolution for the EMA bands' data fetching, defaulting to the chart's timeframe if left empty—this enables higher-timeframe overlays on lower charts for context.
Next, a shared source input defines the price data for all midlines, defaulting to the midpoint of high and low (hl2) but customizable to close, open, or others.
The EMA bands have dedicated toggles and length inputs for each of the three sets: the first (long-term) defaults to 144 periods, the second (medium-term) to 72, and the third (short-term) to 12. These are inlined for compact settings panels, with minimum lengths of 1 to prevent errors.
A boolean toggle controls the visibility of the MTF dashboard. Following this are nine pairs of inputs for dashboard timeframes: each pair includes a show/hide toggle and an editable timeframe string (e.g., '1' for 1-minute, 'D' for daily). Defaults progress from short (1, 3, 5 minutes) to longer (15, 30, 60 minutes, daily, weekly, monthly), grouped in inlines for organization. Only enabled and non-empty timeframes appear in the dashboard.
Helpers Section
Two utility functions are defined here. The first computes an EMA on any source series over a specified length using Trading View's built-in function, reused throughout for midlines and bands.
The second function generates a signal string ("B" for buy/bullish, "S" for sell/bearish, or "-" for neutral) based on the direction of an EMA applied to high prices. It compares the current EMA value to the previous one, mirroring the band fill logic for consistency in the dashboard.
Core Components per Band Set:
Midline: An EMA calculated on a user-selectable source price (default: hl2, which is the midpoint between high and low prices). This acts as the central trend line.
Upper Band: An EMA applied directly to the high prices of each bar.
Lower Band: An EMA applied to the low prices of each bar.
These form a channel that captures the smoothed range of price action, highlighting potential support (lower band), resistance (upper band), and overall trend direction (midline).
Multiple Band Sets: The indicator includes three independent EMA band sets, each with its own length parameter for customization:
EMA1 (default length: 144) – Focuses on long-term trends.
EMA2 (default length: 72) – Targets medium-term trends.
EMA3 (default length: 12) – Emphasizes short-term momentum.
Each set can be toggled on or off via input checkboxes, allowing users to reduce chart clutter if needed.
Visual Elements:
Midline Plot: Displayed as a line colored based on its direction compared to the previous bar: green for rising (bullish), red for falling (bearish), and black for neutral (flat).
Band Fill: The area between the upper and lower bands is filled with a semi-transparent color indicating the trend of the upper band: light green for rising (suggesting expanding highs/upward momentum) and light pink for falling (contracting highs/downward pressure). The bands themselves are plotted in blue with a thin linewidth.
Multi-Timeframe Support: Users can input a custom timeframe (e.g., 'D' for daily), and the indicator fetches data from that resolution. This enables higher-timeframe context on lower-timeframe charts, such as viewing daily EMA bands on a 1-hour chart.
Calculation Mechanics:
All EMAs are computed using Trading View's built-in ta.ema() function.
Data is retrieved in a single request.security() call for efficiency, with lookahead enabled to avoid repainting.
No multipliers or volatility adjustments are included, making it a simple EMA-based envelope rather than a true volatility channel.
In practice, this indicator helps traders identify trend strength, potential breakouts (price crossing bands), or mean-reversion opportunities (price bouncing within bands). It's particularly useful for swing or position trading where multi-period alignment (e.g., all midlines green) signals conviction.
Pros
Multi-Period Insight: By combining short (12), medium (72), and long (144) periods, it offers a layered view of trends across time horizons, helping confirm alignments or divergences without needing multiple separate indicators.
Visual Clarity: Color-coded trends and fills make it easy to spot bullish/bearish shifts at a glance, reducing analysis time.
Flexibility: Custom timeframe input allows for multi-timeframe analysis, while shared source and toggles provide user control.
Simplicity and Efficiency: Purely EMA-based, it's computationally light and avoids overcomplication, making it accessible for beginners while still useful for spotting channel-based setups like squeezes or expansions.
No Repainting: With lookahead, plots are stable once bars close.
Cons
Lagging Nature: EMAs inherently lag price action, especially longer ones like 144-period, which may cause delayed signals in fast-moving or ranging markets.
Lack of Volatility Adjustment: Unlike Keltner Channels or Bollinger Bands, it doesn't incorporate ATR or standard deviation, so bands may not accurately reflect true volatility—potentially leading to false breakouts in high-volatility environments.
Chart Clutter: Displaying all three band sets simultaneously can overcrowd the chart, particularly on lower timeframes or volatile assets.
Subjective Interpretation: Color changes and band interactions require trader discretion; there's no built-in alerting or quantitative signals, which might lead to inconsistent results.
Market Dependency: Defaults may not suit all assets (e.g., stocks vs. crypto); shorter periods like 12 could whipsaw in noisy markets, while 144 might be too slow for intraday trading.
Justification for Default Values (12, 72, and 144)
The default lengths of 12, 72, and 144 are not arbitrary but draw from established trading principles, particularly W.D. Gann's geometric and numerical theories, as well as Fibonacci sequences, to create a harmonic progression for short-, medium-, and long-term analysis. Here's the rationale:
12 (Short-Term): This is a common period for capturing recent momentum in technical indicators, often seen in setups like the MACD (which uses 12- and 26-day EMAs). It aligns with natural cycles, such as the 12 months in a year, and in Gann theory, 12 serves as a base unit for squaring price and time (e.g., in the "Square of 12" where multiples like 12, 24, etc., measure cycles in days, weeks, or months). At 12 periods, the EMA reacts quickly to price changes without excessive noise, making it ideal for short-term trend detection.
72 (Medium-Term): This acts as an intermediate bridge, derived from Gann's divisions of the 360-degree circle (a key Gann concept representing a full cycle). Specifically, 72 is 360/5 (relating to pentagonal geometry and natural harmonics) and appears in Gann's time cycle measurements (e.g., as a multiple in the Square of 12: 12×6=72). It's roughly half of 144, providing a balanced midpoint for medium-term trends without overlapping too closely with the others. In practice, 72 periods smooth out short-term fluctuations while still responding to developing trends.
144 (Long-Term): This is a powerhouse number in trading lore, being both 12 squared (12×12=144, central to Gann's "Square of 144" for monthly charts and major cycle turns, as there are 12 months in a year) and a Fibonacci sequence value (1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144...). Fibonacci periods are popular in moving averages for their alignment with natural growth patterns in markets, and 144 is often used for long-term regime definition (e.g., confirming trends over 144 bars). It helps identify major support/resistance in extended cycles.
Overall, these values form a geometric/harmonic series (12, 72=12×6, 144=12×12), promoting alignment with market cycles as per Gann and Fibonacci principles, rather than generic lengths like 50 or 200. They can be adjusted based on the asset or timeframe, but the defaults provide a starting point rooted in time-tested trading numerology for balanced multi-period analysis.
Please use this along with other indicators (eg. Pivot, MACD, etc) for better results.
Supply In Profit Z-Score | Wave BackgroundSupply in Profit Z-Score
Modified by Quant_Hustler | Original by QuantChook
What it does
The Supply in Profit Z-Score measures how extreme the balance is between BTC addresses in profit versus those in loss compared to historical norms.
It highlights periods of excessive optimism or pessimism, helping traders identify market sentiment extremes that can signal potential turning points or confirm ongoing trends.
This version is designed for longer-term strategies, using smoothing and statistical normalization to focus on broader market sentiment cycles rather than short-term noise.
How it works
--Data Retrieval: Pulls on-chain data showing the percentage of Bitcoin addresses currently in profit and in loss.
--Spread Calculation: Finds the difference between the two to gauge overall sentiment balance.
--Alpha Decay Adjustment (optional): Normalizes extreme values to stabilize the signal over time.
--Smoothing: Applies a moving average to filter daily volatility and improve long-term clarity.
--Z-Score Conversion: Standardizes the data to show how far current sentiment deviates from historical averages.
--Visualization: Plots the result around a neutral midpoint (zero line) — positive values indicate profit dominance, negative values indicate loss dominance.
How to use it
--Above Zero: More addresses in profit → bullish sentiment and strong trend conditions.
--Below Zero: More addresses in loss → bearish sentiment or potential accumulation zones.
--Extreme Values: Mark overly optimistic or capitulated sentiment, often preceding major reversals.
Why use it in trend following
--This indicator serves as an on-chain sentiment confirmation layer for trend-following systems, especially on higher timeframes (daily or weekly).
--In uptrends, sustained positive readings confirm market strength and investor confidence.
--In downtrends, persistent negative readings confirm weakness and help avoid false reversal signals.
--Divergences between price and sentiment (e.g., rising price but weakening sentiment) often signal momentum loss or potential trend transitions.
Modifications from the original by QuantChook
Added EMA, adaptive Z-score smoothing and capping to reduce volatility and noise.
Introduced a wave-style visualization for intuitive sentiment shifts.
Improved calculation structure and upgraded for Pine Script v6 efficiency.
Tuned signal responsiveness and smoothing parameters for long-term trend accuracy.
Simplified user inputs and grouping for easier customization and integration.
In summary:
A refined, statistically grounded on-chain sentiment oscillator — originally developed by QuantChook and enhanced by Quant_Hustler — built to support long-term trend-following strategies by quantifying Bitcoin market sentiment through real-time profit and loss dynamics.
HTF & PD/PM LevelsTired of mapping your own levels every morning? Look no further! This script automatically maps out and updates HTF & PD/PM Levels along with ATH. I personally use these as confirmation zones with EMA & VWAP, RSI, and Volume... but alone, these levels mark major support and resistances.
What are they?
🏰 HTF Levels — “Big Grown-Up Lines”
HTF = Higher Time Frame
Think of your price chart like a big map. HTF levels are the important lines from bigger chunks of time:
>Daily (yesterday’s close, high, low)
>Weekly (this week’s open, high, low, close)
>Monthly (this month’s open/close)
Why they matter:
These are like big walls and floors that price often bounces off or stops at. Big traders (institutions) watch them because they show where a lot of buying or selling happened before.
⏰ PD & PM Levels — “Yesterday & Morning Clues”
PD = Previous Day
>PDH = Previous Day’s High
>PDL = Previous Day’s Low
>PDC = Previous Day’s Close
PM = Pre-Market
>PMH = Pre-Market High
>PML = Pre-Market Low
>ATH = All-Time High
Why they matter:
These tell you where price moved when most regular traders weren’t awake yet (pre-market) and where it ended up yesterday. Price often revisits or reacts to these spots.
⚡ How Options Traders Use Them
Support & Resistance:
If price is near an HTF or PD/PM level, it might stop and turn around there (like a ball hitting a wall) or it might use it as a launchpad to the next level if it breaks.
Entry & Exit Spots:
Traders might buy calls (bet price goes up) if it breaks above an important level, or puts (bet price goes down) if it breaks below.
Risk Management:
These levels give clear spots to set stops and targets — “If price breaks this level, I’m out.”
Super Simple Picture:
HTF = big important levels from days, weeks, months.
PD/PM = yesterday’s and morning’s clues where price already moved.
Traders use them to guess where price might bounce or break to plan option trades safely.
ULTIMATE Smart Trading Pro 🔥
## 🇬🇧 ENGLISH
### 📊 The Most Complete All-in-One Trading Indicator
**ULTIMATE Smart Trading Pro** combines the best technical analysis tools and Smart Money Concepts into a single powerful and intelligent indicator. Designed for serious traders who want a real edge in the markets.
---
### ✨ KEY FEATURES
#### 💰 **SMART MONEY CONCEPTS**
- **Order Blocks**: Automatically detects institutional zones where "smart money" enters positions
- **Break of Structure (BOS)**: Identifies structure breaks to confirm trend changes
- **Liquidity Zones**: Spots equal highs/lows areas where institutions hunt stops
- **Market Structure**: Visually displays bullish (green background) or bearish (red background) structure
#### 📈 **ADVANCED TECHNICAL INDICATORS**
- **RSI with Auto Divergences**: Classic RSI + automatic detection of bullish and bearish divergences
- **MACD with Signals**: Identifies bullish and bearish crossovers in real-time
- **Dynamic Support & Resistance**: Adaptive zones with intelligent scoring based on volume, multiple touches, and ATR
- **Fair Value Gaps (FVG)**: Detects unfilled price gaps (imbalance zones)
#### 📐 **AUTOMATIC TOOLS**
- **Auto Fibonacci**: Automatically calculates Fibonacci retracement levels on the last major trend
- **Pivot Points**: Daily, Weekly, or Monthly pivot points (PP, R1, R2, S1, S2)
- **Pattern Finder**: Automatically detects candlestick patterns (Hammer, Shooting Star, Engulfing, Morning/Evening Star) and chart patterns (Double Top/Bottom)
---
### 🎯 HOW TO USE IT
#### Quick Setup:
1. **Add the indicator** to your chart
2. **Open Settings** and enable/disable modules as needed
3. **Adjust parameters** for your trading style (scalping, swing, day trading)
#### Optimal Trading Setup:
🔥 **ULTRA STRONG Signal** when you have:
- An institutional **Order Block**
- Aligned with a **Support/Resistance** tested 3+ times
- An unfilled **FVG** nearby
- An **RSI divergence** confirming the reversal
- On a key **Fibonacci** level (50%, 61.8%, or 78.6%)
- Favorable market structure (green background for buys, red for sells)
---
### 💡 UNIQUE ADVANTAGES
✅ **Adaptive Intelligence**: Automatically adjusts to market volatility (ATR)
✅ **Volume Filters**: Validates important levels with volume confirmation
✅ **Multi-Timeframe Ready**: Works on all timeframes (1m to 1M)
✅ **Complete Alerts**: Notifications for all important signals
✅ **Clear Interface**: Emojis and colored labels for quick identification
✅ **Intelligent Scoring**: Levels ranked by importance (🔴🔴🔴 = very strong)
✅ **100% Customizable**: Enable only what you need
---
### 🎨 SYMBOL LEGEND
**Smart Money:**
- 🟢 OB = Bullish Order Block
- 🔴 OB = Bearish Order Block
- BOS ↑/↓ = Break of Structure
- 💧 LIQ = Liquidity Zone
**Candlestick Patterns:**
- 🔨 = Hammer (bullish signal)
- ⭐ = Shooting Star (bearish signal)
- 📈 = Bullish Engulfing
- 📉 = Bearish Engulfing
- 🌅 = Morning Star (bullish reversal)
- 🌆 = Evening Star (bearish reversal)
**Indicators:**
- 🚀 MACD ↑ = Bullish crossover
- 📉 MACD ↓ = Bearish crossover
- ⚠️ DIV = Bearish RSI divergence
- ✅ DIV = Bullish RSI divergence
**Support & Resistance:**
- 🟢/🔴 S1, R1 = Support/Resistance
- 🟢🟢🟢/🔴🔴🔴 = VERY strong level (3+ touches)
- (×N) = Number of times touched
---
### ⚙️ RECOMMENDED SETTINGS
**For Scalping (1m - 5m):**
- SR Lookback: 15
- Structure Strength: 3
- RSI: 14
- Volume Filter: ON
**For Day Trading (15m - 1H):**
- SR Lookback: 20
- Structure Strength: 5
- RSI: 14
- All filters: ON
**For Swing Trading (4H - Daily):**
- SR Lookback: 30
- Structure Strength: 7
- Pattern Lookback: 100
- Fibonacci: ON
---
### 🚨 DISCLAIMER
This indicator is a decision support tool. It does not guarantee profits and does not constitute financial advice. Always test on a demo account before real use. Trading involves significant risks.
---
## 📞 SUPPORT & UPDATES
For questions, suggestions, or bug reports, please comment below or contact the author.
**Version:** 1.0
**Last Updated:** October 2025
**Compatible:** TradingView Pine Script v6
---
### 🌟 If you find this indicator useful, please give it a 👍 and share it with other traders!
**Happy Trading! 🚀📈**
Triple Gaussian Smoothed Ribbon [BOSWaves]Triple Gaussian Smoothed Ribbon – Adaptive Gaussian Framework
Overview
The Triple Gaussian Smoothed Ribbon is a next-generation market visualization framework built on the principles of Gaussian filtering - a mathematical model from digital signal processing designed to remove noise while preserving the integrity of the underlying trend.
Unlike conventional moving averages that suffer from phase lag and overreaction to volatility spikes, Gaussian smoothing produces a symmetrical, low-lag curve that isolates meaningful directional shifts with exceptional clarity.
Developed under the Adaptive Gaussian Framework, this indicator extends the classical Gaussian model into a multi-stage smoothing and visualization system. By layering three progressive Gaussian filters and rendering their interactions as a gradient-based ribbon field, it translates market energy into a coherent, visually structured trend environment. Each ribbon layer represents a progressively smoothed component of price motion, producing a high-fidelity gradient field that evolves in sync with real-time trend strength and momentum.
The result is a uniquely fluid trend and reversal detection system - one that feels organic, adapts seamlessly across timeframes, and reveals hidden transitions in market structure long before traditional indicators confirm them.
Theoretical Foundation
The Gaussian filter, derived from the Gaussian function developed by Carl Friedrich Gauss in 1809, operates on the principle of weighted symmetry, assigning higher importance to central price data while tapering influence toward historical extremes following a bell-curve distribution. This symmetrical design minimizes phase distortion and smooths without introducing lag spikes — a stark contrast to exponential or linear filters that sacrifice temporal accuracy for responsiveness.
By cascading three Gaussian stages in sequence, the indicator creates a multi-frequency decomposition of price action:
The first stage captures immediate trend transitions.
The second absorbs mid-term volatility ripples.
The third stabilizes structural directionality.
The final composite ribbon reflects the market’s dominant frequency - a smoothed yet reactive trend spine - while an independent, heavier Gaussian smoothing serves as a reference layer to gauge whether the primary motion leads or lags relative to broader market structure.
This multi-layered Gaussian framework effectively replicates the behavior of a signal-processing filter bank: isolating meaningful cyclical movements, suppressing random noise, and revealing phase shifts with minimal delay.
How It Works
Triple Gaussian Core
Price data is passed through three successive Gaussian smoothing stages, each refining the trend further and removing higher-frequency distortions.
The result is a fluid, continuously adaptive baseline that responds naturally to directional changes without overshooting or flattening key inflection points.
Adaptive Ribbon Architecture
The indicator visualizes its internal dynamics through a five-layer gradient ribbon. Each layer represents a progressively delayed Gaussian curve, creating a color field that dynamically shifts between bullish and bearish tones.
Expanding ribbons indicate accelerating momentum and trend conviction.
Compressing ribbons reflect consolidation and volatility contraction.
The smooth color gradient provides a real-time depiction of energy buildup or dissipation within the trend, making it visually clear when the market is entering a state of expansion, transition, or exhaustion.
Momentum-Weighted Opacity
Ribbon transparency adjusts according to normalized momentum strength.
As trend force builds, colors intensify and layers become more opaque, signifying conviction.
When momentum wanes, ribbons fade - an early visual cue for potential reversals or pauses in trend continuation.
Candle Gradient Integration
Optional candle coloring ties the chart’s candles to the prevailing Gaussian gradient, allowing traders to view raw price action and smoothed wave dynamics as a unified system.
This integration produces a visually coherent chart environment that communicates directional intent instantly.
Signal Detection Logic
Directional cues emerge when the smoother, broader Gaussian curve crosses the faster-reacting Gaussian line, marking structural inflection points in the filtered trend.
Bullish shifts : short-term momentum transitions upward through the long-term baseline after a localized trough.
Bearish shifts : momentum declines through the baseline following a local peak.
To maintain integrity in choppy markets, the framework applies a trend-strength and separation filter, which blocks weak or overlapping conditions where movement lacks conviction.
Interpretation
The Triple Gaussian Smoothed Ribbon provides a layered, intuitive read on market structure:
Trend Continuation : Expanding ribbons with deep color intensity confirm directional strength.
Reversal Phases : Color gradients flip direction, indicating a phase shift or exhaustion point.
Compression Zones : Tight, pale ribbons reveal equilibrium phases often preceding breakouts.
Momentum Divergence : Fading color intensity despite continued price movement signals weakening conviction.
These transitions mirror the natural ebb and flow of market energy - captured through the Gaussian filter’s ability to represent smooth curvature without distortion.
Strategy Integration
Trend Following
Engage during strong directional expansions. When ribbons widen and color gradients intensify, the trend is accelerating with high confidence.
Reversal Identification
Monitor for full gradient inversion and fading momentum opacity. These conditions often precede transitional phases and early reversals.
Breakout Anticipation
Flat, compressed ribbons signal low volatility and energy buildup. A sudden gradient expansion with renewed opacity confirms breakout initiation.
Multi-Timeframe Alignment
Use higher timeframes to establish directional bias and lower timeframes for entry during compression-to-expansion transitions.
Technical Implementation Details
Triple Gaussian Stack : Sequential smoothing stages produce low-lag, high-purity signals.
Adaptive Ribbon Rendering : Five-layer Gaussian visualization for gradient-based trend depth.
Momentum Normalization : Opacity dynamically tied to trend strength and volatility context.
Consolidation Filter : Suppresses false signals in low-energy or range-bound conditions.
Integrated Candle Mode : Optional color synchronization with underlying gradient flow.
Alert System : Built-in notifications for bullish and bearish transitions.
This structure blends the precision of digital signal processing with the readability of visual market analysis, creating a clean but information-rich framework.
Optimal Application Parameters
Asset Recommendations
Cryptocurrency : Higher smoothing and sigma for stability under volatility.
Forex : Balanced parameters for cycle identification and reduced noise.
Equities : Moderate Gaussian length for responsive yet stable trend reads.
Indices & Futures : Longer smoothing periods for structural confirmation.
Timeframe Recommendations
Scalping (1 - 5m) : Use shorter smoothing for fast reactivity.
Intraday (15m - 1h) : Mid-length Gaussian chain for balance.
Swing (4h - 1D) : Prioritize clarity and opacity-driven trend phases.
Position (Daily - Weekly) : Longer smoothing to capture macro rhythm.
Performance Characteristics
Most Effective In :
Trending markets with recurring volatility cycles.
Transitional phases where early directional confirmation is crucial.
Less Effective In:
Ultra-low volume markets with erratic tick data.
Random, micro-chop conditions with no structural flow.
Integration Guidelines
Pair with volatility or volume expansion tools for enhanced breakout confirmation.
Use ribbon compression to anticipate volatility shifts.
Align entries with gradient expansion in the dominant color direction.
Scale position size relative to opacity strength and ribbon width.
Disclaimer
The Triple Gaussian Smoothed Ribbon – Adaptive Gaussian Framework is designed as a signal visualization and trend interpretation tool, not a standalone trading system. Its accuracy depends on appropriate parameter tuning, contextual confirmation, and disciplined risk management. It should be applied as part of a comprehensive technical or algorithmic trading strategy.
No Supply (Low-Volume Down Bars) — IdoThis indicator flags classic Wyckoff/VSA “No Supply (NS)” events—down bars that print on unusually low volume, suggesting a lack of sellers rather than strong selling pressure. NS often appears near support, LPS, or within re-accumulation ranges as a test before continuation higher.
Signal definition (configurable):
Down bar: choose Close < PrevClose or Close < Open.
Low volume: Volume < SMA(Volume, len) × threshold (e.g., 0.7).
Optional volume lower than the prior two bars (reduces noise).
Optional narrow spread: range (H–L) below its average.
Optional close position: close in the upper half of the bar.
Optional trend filter: only mark NS above or below an EMA (or any).
Optional wide-bar exclusion: skip unusually wide bars.
Visuals & outputs
Blue dot below each NS bar (optional bar tint).
Separate pane showing Relative Volume (vol / volSMA) to gauge effort.
Built-in alertcondition to trigger notifications when NS prints.
Inputs (high level)
lenVol: Volume SMA length.
ratioVol: Volume threshold vs. average (e.g., 0.7 = 70%).
usePrev2: Require volume below each of the prior two bars.
useNarrow + lenRange + ratioRange: Narrow-bar filter.
useClosePos + minClosePos: Close in upper portion of the bar.
downBarMode: Define “down bar” logic.
trendFiltOn, trendLen, trendSide: EMA trend filter.
useWideFilter, lenRangeWide, wideThreshold: Skip wide bars.
How to use (Wyckoff/VSA context)
Treat NS as a test of supply: price dips, but volume is light and close holds up.
Stronger when it prints near support/LPS within a re-accumulation structure.
Confirmation (recommended): within 1–3 bars, see demand—e.g., break above the NS high with expanding volume (above average or above the prior two bars). Many traders place a buy-stop just above the NS high; common stops are below the NS low or the most recent swing low.
Scanning tip
TradingView’s stock screener can’t consume Pine directly.
Use a Watchlist Custom Column that reports “bars since NS” to sort symbols (0 = NS on the latest bar). A companion column script is provided separately.
Notes & limitations
Works on any timeframe (intraday/daily/weekly), but context matters.
Expect false positives around news, gaps, or illiquid symbols—combine with structure (trend, S/R, phases) and risk management.
© moshel — Educational use only; not financial advice.
