Volume Delta [BigBeluga]🔵 OVERVIEW
The Volume Delta indicator visualizes the dominance between buying and selling volume within a given period. It calculates the percentage of bullish (buy) versus bearish (sell) volume, then color-codes the candles and provides a real-time dashboard comparing delta values across multiple currency pairs. This makes it a powerful tool for monitoring order-flow strength and intermarket relationships in real time.
🔵 CONCEPTS
Each bar’s buy volume is counted when the close is higher than the open.
Each bar’s sell volume is counted when the close is lower than the open.
volumeBuy = 0.
volumeSell = 0.
for i = 0 to period
if close > open
volumeBuy += volume
else
volumeSell += volume
The indicator sums both over a chosen period to calculate the ratio of buy-to-sell pressure.
Delta (%) = (Buy Volume ÷ (Buy Volume + Sell Volume)) × 100.
Gradient colors highlight whether buying or selling pressure dominates.
🔵 FEATURES
Calculates real-time Volume Delta for the selected chart or for multiple assets.
Colors candles dynamically based on the delta intensity (green = buy pressure, red = sell pressure).
Displays a dashboard table showing volume delta % for up to five instruments.
The dashboard features visual progress bars for quick intermarket comparison.
An optional Delta Bar Panel shows the ratio of Buy/Sell volumes near the latest bar.
A floating label shows the exact Buy/Sell percentages.
Works across all symbols and timeframes for multi-asset delta tracking.
🔵 HOW TO USE
When Buy % > Sell % , it often signals bullish momentum or strong accumulation—but can also indicate over-excitement and a possible market top.
Market Tops
When Sell % > Buy % , it typically reflects bearish pressure or distribution—but may also occur near a market bottom where selling exhaustion forms.
Market Bottom
Use the Dashboard to compare volume flow across correlated assets (e.g., major Forex pairs or sector groups).
Combine readings with trend or volatility filters to confirm whether the imbalance aligns with broader directional conviction.
Treat the Delta Bar visualization as a real-time sentiment gauge—showing which side (buyers or sellers) dominates the current session.
🔵 CONCLUSION
Volume Delta transforms volume analysis into an intuitive directional signal.
By quantifying buy/sell pressure and displaying it as a percentage or color gradient, it provides traders with a clearer picture of real-time volume imbalance — whether within one market or across multiple correlated instruments.
Pesquisar nos scripts por "accumulation"
Mean Reverting Suite [OmegaTools]Overview
The Mean Reverting Suits (MR Suite) by OmegaTools is an advanced analytical and visualization framework designed to identify directional exhaustion, statistical overextensions, and conditions consistent with mean-reversion dynamics. It integrates three pillars into a single display: a composite momentum-normalized oscillator, a percentile-based extension model with volume contextualization, and a dynamic structural mapping engine built on confirmed pivots. The indicator does not generate signals or prescribe trade actions; it provides objective context so users can evaluate market balance and the likelihood that price is departing from its recent statistical baseline.
Core logic
The composite oscillator blends MFI on two horizons and RSI on HL2, then averages them to produce a stabilized mean-reversion gauge. Candle and bar colors are mapped by a dual gradient centered at 50. Readings above 50 progressively shift from neutral gray toward the bearish accent color to reflect increasing momentum saturation; readings below 50 shift from the bullish accent color toward gray to reflect potential accumulation or temporary undervaluation. This continuous mapping avoids rigid thresholds and conveys the strength and decay of momentum as a smooth spectrum.
The percentile-based extension model measures the persistence of directional bias by tracking how many bars have elapsed since the last opposing condition. These rolling counts are compared to the 80th percentile of their own historical distributions stored in arrays. When a current streak exceeds its respective percentile, the environment is labeled as statistically extended in that direction. Background shading communicates this information and is modulated by relative volume, computed as live volume divided by a blended average of SMA(30) and EMA(11). Higher opacity implies greater liquidity participation during the extension.
The structural mapping module uses confirmed pivot highs and lows at the chosen length to create persistent horizontal levels that extend forward and automatically maintain themselves until price invalidates or refreshes them. These levels represent market memory zones and assist in reading where reactions previously formed. The engine updates in real time, ensuring the framework continuously reflects the prevailing structure.
Standard deviation and z-score overlay
The updated version introduces a mean and dispersion layer. A simple moving average of HL2 over twice the length provides the reference mean. Dispersion is estimated as the moving average of the absolute deviation between close and the mean over five times the length. The z-score is computed as the distance of price from the mean divided by this dispersion proxy. Visual arrows highlight observations where the absolute z-score exceeds two standard deviations, offering a concise view of statistically unusual departures from the local mean. This layer complements the percentile extension model by adding an orthogonal measure of extremity based on distributional distance rather than run length.
Visualization
Candle bodies and borders inherit the oscillator’s gradient color, creating an immediate sense of directional pressure and potential momentum fatigue. The chart background activates when the extension model detects a statistically rare streak, using blue tones for bearish extension and red tones for bullish extension, with intensity scaling by relative volume. Horizontal lines denote active pivot-based levels, automatically extending, truncating, and refreshing as structure evolves. The z-score arrows appear only when deviations exceed the ±2 threshold, keeping the display focused on noteworthy statistical events.
Inputs and configuration
Length controls the sensitivity of all modules. Lower values make the oscillator and pivot detection more reactive; higher values smooth readings and widen structural context. Bullish and Bearish colors are user-selectable to match platform themes or accessibility requirements.
Interpretation guidance
A strong red background indicates an unusually extended bullish run in the presence of meaningful volume; a strong blue background indicates an unusually extended bearish run in the presence of meaningful volume. Candle gradients near deep bearish tones suggest oscillator readings well above 50; gradients near deep bullish tones suggest oscillator readings well below 50. Pivot lines mark the most recently confirmed structural levels that the market has reacted to. Z-score arrows denote points where price has moved beyond approximately two standard deviations of its local mean, signaling statistically uncommon distance rather than directional persistence. None of these elements are directives; they are objective descriptors designed to improve situational awareness.
Advantages
The framework is adaptive by design and self-normalizes to each instrument’s volatility and rhythm through percentile logic and dispersion-based distance. It is volume-aware, visually encoding liquidity pressure so that users can distinguish thin extensions from structurally significant ones. It reduces chart clutter by unifying momentum state, statistical extension, standard deviation distance, and structural levels into a single coherent view. It is asset- and timeframe-agnostic, suitable for intraday through swing horizons across futures, equities, FX, and digital assets.
Usage notes
MR Suite is intended for analytical and educational purposes. It does not provide trading signals, risk parameters, or strategy instructions. Users may employ its context alongside their own methodologies, risk frameworks, and execution rules. The indicator’s value derives from quantifying how unusual a move is, showing how much liquidity supports it, and anchoring that information to evolving structural references, thereby improving the clarity and consistency of discretionary assessment without prescribing actions.
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.
Retracement FiboNacci🎯 Core Functionality
Automatic Swing Detection: Uses ZigZag algorithm to detect significant price swings
Dual Modes:
Fibonacci Retracements - Traditional price-based levels
Fibonacci Time Zones - Time-based projections
Multi-Timeframe Analysis: Works on any timeframe while detecting swings from higher timeframes
⚙️ Customization Options
Fibonacci Levels:
Fully customizable Fibonacci levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%)
Individual color selection for each level
Toggle on/off specific levels as needed
Display Settings:
Line Styling: Choose between Solid, Dashed, or Dotted lines
Line Thickness: Adjustable from 1 to 5 pixels
ZigZag Visibility: Toggle base ZigZag line display
Label Management:
Fibonacci Labels: Show percentage retracement levels
Price Labels: Display actual price values
Flexible Positioning:
Left, Right, Both sides, or Auto-centering
Independent control for Fib and Price labels
Option to hide labels completely
🔧 Technical Specifications
ZigZag Parameters:
Depth: 12 bars
Deviation: 1%
Backstep: 2 bars
Real-time Updates: Automatically redraws when new swings are detected
Clean Interface: Removes old drawings to prevent chart clutter
Usage Scenarios
📈 Trend Analysis
Identify retracement levels during pullbacks
Spot potential reversal zones at key Fibonacci levels
Measure swing magnitudes for position sizing
⏰ Time Projections
Use Time Zone mode for forecasting potential reversal times
Combine price and time analysis for confluence
🎨 Visual Customization
Color-code important levels (e.g., 61.8% as golden ratio)
Adjust label sizes for better readability
Choose line styles that complement your chart setup
Ideal For
Swing traders identifying entry/exit points
Position traders finding optimal accumulation zones
Technical analysts validating support/resistance levels
Multi-timeframe analysts correlating higher timeframe structure
Pro Tips
Combine with Volume: Confirm reactions at Fibonacci levels with volume spikes
Multiple Timeframes: Use higher timeframe Fibonacci levels for major S/R
Confluence Trading: Look for Fibonacci levels aligning with previous support/resistance
Risk Management: Use Fibonacci extensions for profit targets
Smart Money Toolkit - PD Engine Bias Map [KedArc Quant]📄 Description
Smart Money Toolkit is an advanced multi-layer Smart Money Concepts framework that automatically detects structure shifts, premium-discount zones, and institutional order flow.
It’s built around the PD Engine, which calculates the midpoint of the most recent market swing and dynamically determines BUY or SELL bias based on where current price trades relative to that equilibrium. This toolkit visualizes structure, order blocks, and bias context in one clean map — giving traders an institutional-grade lens without signal clutter.
💡 Why It’s Unique
* Not a mashup of open-source scripts.
Every module — CHoCH/BOS logic, order-block zone detection, PD bias engine, and structure mapping — is written from scratch to ensure clean, consistent behavior in Pine Script v6.
* Bias engine with true equilibrium logic: The 50% PD (Premium-Discount) zone adapts in real time to the latest swing, giving a live institutional price map.
* Visual precision: Minimalist premium/discount shading, structured labeling (HH, HL, LH, LL, CHoCH), and context tables for clarity.
* Performance-optimized: Handles multiple visual layers (FVG, OB, CHoCH, BOS) efficiently without repainting.
🎯 Entry and Exit Logic (Discretionary Framework)
This toolkit is not a signal generator; it’s a contextual trading framework that guides your decisions.
BUY Bias (Discount Zone)
* Price trades below PD Mid → Market is in *discount*.
* Wait for a bullish CHoCH or rejection from demand OB/FVG before entering long.
* Target 1 = PD Mid; Target 2 = next opposing OB/FVG.
SELL Bias (Premium Zone)
* Price trades above PD Mid → Market is in *premium*.
* Wait for a bearish CHoCH or rejection from supply OB/FVG before shorting.
* Target 1 = PD Mid; Target 2 = next opposing OB/FVG.
This sequence enforces the institutional concept:
> Bias → Structure Shift → Confirmation → Execution
⚙️ Input Configuration
Setting Description
Swing Sensitivity Controls how far back to look for HH/LL pivots.
OB/FVG Detection Enable or disable visual order block or fair-value-gap zones.
PD Engine Toggles PD midpoint line, zone shading, and bias table.
Multi-TF Bias Sync Optionally reads higher-time-frame bias to confirm entries.
Color Themes Switch between Light / Dark / Institutional color sets.
All inputs are modular — you can show only the components you use (e.g., disable BOS/CHoCH labels or hide OB zones for a clean view).
🧮 Formula / Logic Summary
Concept Formula
PD Mid (Equilibrium) `(Recent Swing High + Recent Swing Low) / 2`
BUY Bias `close < PD Mid`
SELL Bias `close > PD Mid`
CHoCH / BOS Detected via pivot-based structure reversal: HH→LL or LL→HH
Order Block Last bullish/bearish candle before displacement.
Fair Value Gap (FVG) Gap between prior candle’s high/low and next candle’s range.
These formulas align with Smart Money Concepts taught in institutional trading frameworks.
🤝 How It Helps Traders
* Institutional Context: Instantly visualize premium vs. discount regions — see where smart money is likely accumulating or distributing.
* Bias Confidence: Removes guesswork — you know whether you should be a buyer or seller based on structure + PD bias.
* Cleaner Decision-Making: Combines all SMC elements (BOS, CHoCH, OB, FVG, PD) in one cohesive visual map.
* Timeframe Agnostic: Works seamlessly on any timeframe or instrument (Forex, Indices, Crypto, Equities).
📚 Glossary
PD Mid (Equilibrium) The midpoint between recent swing high and low — the market’s fair
value.
Premium Zone Price above PD Mid — sellers gain control.
Discount Zone Price below PD Mid — buyers gain control.
CHoCH (Change of Character) First structural signal of possible reversal.
BOS (Break of Structure) Continuation signal confirming trend direction.
OB (Order Block) Institutional candle marking accumulation/distribution.
FVG (Fair Value Gap) Imbalance zone where price moved too quickly — often
rebalanced.
❓ FAQ
Q: Is this a signal generator?
A: No — it’s a contextual framework for professional price-action trading.
Q: Does it repaint?
A: No. All structure points and bias logic are confirmed on bar close.
Q: Can it be used on any market or timeframe?
A: Yes. It’s structure-based, not instrument-specific.
Q: How often does bias change?
A: Only when a new swing high/low forms and PD recalculates — keeping the bias stable.
Q: Can I backtest it?
A: You can build an entry rule (e.g., CHoCH + OB + PD alignment) on top of it for strategy testing.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Round Numbers (Plotter) v2The *Round Numbers (Plotter) v2* indicator highlights key psychological price levels on the chart — the so-called *round numbers* (e.g. 1.1000 on EURUSD or23,000 on NASDAQ).
These levels often act as **natural support or resistance zones**, where price tends to react, consolidate, or reverse.
Version 2 introduces the concept of **gravitational zones**, which define a price range surrounding each round level — visualizing how price “gravitates” around these equilibrium areas.
---
### 🧩 **Main Features**
* 🔹 **Dynamic round levels:** plotted automatically based on user-defined *step size* (in points or pips).
* 🔹 **Custom step mode:** switch between “Points” (for indices, commodities, crypto) and “Pips” (for Forex pairs).
* 🔹 **Configurable appearance:** color, width, and line style (solid, dashed, dotted).
* 🔹 **Gravitation zones:** optional secondary lines plotted above and below each round level.
* Distance adjustable as a **percentage of the step size** (default = 25%).
* Help visualize “magnet areas” where price tends to slow down or oscillate before crossing a level.
* 🔹 **Optional fill:** softly shaded area between the upper and lower gravitation lines for clearer visualization of each zone.
* You can enable or disable this with the *“Show gravitation fill”* toggle.
* Fill color and transparency fully customizable.
---
### 📈 **Use Cases**
* Identify **psychological support/resistance** levels on any instrument or timeframe.
* Observe **market equilibrium zones** where price tends to cluster or hesitate before continuing.
* Combine with oscillators or volume indicators to confirm reaction strength near round numbers.
* Use the **gravitational zones** to refine stop-loss or take-profit placement near high-impact levels.
---
### 💡 **Notes**
* The indicator does **not repaint** and updates levels dynamically based on the latest price.
* Works on all asset classes: **Forex, Indices, Crypto, Commodities, Stocks.**
* Designed to be **lightweight** — no accumulation of historical objects.
* Combine this with *Round Number Analyzer* for complete analysis of round numbers level
Market Structure ICT Screener [TradingFinder] BoS ChoCh🔵 Introduction
Market Structure is the foundation of every Smart Money and ICT based trading model. It describes how price moves through a sequence of highs and lows, forming clear phases of expansion, retracement and reversal. Understanding this structure allows traders to read institutional order flow and align their positions with the true direction of liquidity.
Two of the most critical components in Market Structure are the Break of Structure (BOS) and Change of Character (CHOCH). A BOS represents trend continuation, confirming strength within the current direction. In contrast, CHOCH also known as a Market Structure Shift (MSS) signals the first sign of a trend reversal or liquidity shift where order flow begins to change from bullish to bearish or vice versa.
Because the market is fractal, structure can exist at multiple levels known as Major (External) and Minor (Internal). Major structure defines the overall trend on higher timeframes while minor or internal structure reveals short term swings and early reversals within that larger move.
🔵 How to Use
Understanding Market Structure starts with identifying how price interacts with previous swing highs and swing lows. Every trend in the market, whether bullish or bearish, is built from a sequence of impulsive and corrective moves. Impulsive legs show strong displacement in the direction of liquidity flow, while corrective legs represent temporary pullbacks as the market rebalances before the next expansion. Recognizing these sequences is essential for reading the story of price and anticipating what may happen next.
A Break of Structure (BOS) occurs when price decisively moves beyond a previous structural point by breaking above the last high in an uptrend or falling below the last low in a downtrend. This event confirms that the current trend remains intact and that liquidity has been successfully taken from one side of the market. A BOS acts as confirmation of continuation and reflects strength within the existing directional bias.
A Change of Character (CHOCH) appears when price violates structure in the opposite direction of the prevailing trend. This is the first signal that market sentiment and order flow may be shifting. For example, during a downtrend if price breaks above a previous high, it indicates that sellers are losing control and a potential bullish reversal may be developing. In an uptrend, when price drops below a recent low, it suggests a possible bearish transition.
Because the market is fractal, structure exists across multiple layers. Major structure reflects the dominant movement visible on higher timeframes and defines the broader directional bias. Minor or internal structure represents smaller swings within that move and helps identify early transitions before they appear on the higher timeframe. When internal and external structures align, they offer a high probability signal for trend continuation or reversal.
By observing BOS and CHOCH across both internal and external structures, traders can clearly visualize when the market is expanding, contracting or preparing to shift direction. This structured understanding of price movement forms the foundation for precise trend analysis and high quality decision making in any Smart Money or ICT based trading approach.
🔵 Settings
🟣 Display Settings
Table on Chart : Allows users to choose the position of the signal dashboard either directly on the chart or below it, depending on their layout preference.
Number of Symbols : Enables users to control how many symbols are displayed in the screener table, from 10 to 20, adjustable in increments of 2 symbols for flexible screening depth.
Table Mode : This setting offers two layout styles for the signal table :
Basic : Mode displays symbols in a single column, using more vertical space.
Extended : Mode arranges symbols in pairs side-by-side, optimizing screen space with a more compact view.
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 20 symbol slots comes with a full set of customizable parameters :
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
Pivot Period : Set the length used to detect swing highs and lows. Shorter values increase sensitivity, longer ones focus on major structures.
🔵 Conclusion
Mastering Market Structure and understanding the relationship between BOS and CHOCH allows traders to see the market with greater clarity and confidence. These two elements reveal how liquidity moves through different phases of expansion and retracement and how institutional order flow shifts between accumulation and distribution.
By analyzing both internal and external structures, traders can align short term and long term perspectives and anticipate where price is most likely to react. The ability to read these structural shifts helps identify continuation points, reversals and areas where liquidity is engineered or collected.
Incorporating Market Structure into a consistent trading process transforms the way a trader views the chart. Instead of reacting to random movements, each swing, break and shift becomes part of a logical framework that reflects the true behavior of the market. Understanding BOS and CHOCH is not just a concept but a complete language of price that guides every professional decision in Smart Money and ICT based trading.
Smart Money Volume Activity [AlgoAlpha]🟠 OVERVIEW
This tool visualizes how Smart Money and Retail participants behave through lower-timeframe volume analysis. It detects volume spikes far beyond normal activity, classifies them as institutional or retail, and projects those zones as reactive levels. The script updates dynamically with each bar, showing when large players enter while tracking whether those events remain profitable. Each event is drawn as a horizontal line with bubble markers and summarized in a live P/L table comparing Smart Money versus Retail.
🟠 CONCEPTS
The core logic uses Z-score normalization on lower-timeframe volumes (like 5m inside a 1h chart). This lets the script detect statistically extreme bursts of buying or selling activity. It classifies each detected event as:
Smart Money — volume inside the candle body (suggesting hidden accumulation or distribution)
Retail — volume closing at bar extremes (suggesting chase entries or panic exits)
When new events appear, the script plots them as horizontal levels that persist until price interacts again. Each level acts as a potential reaction zone or liquidity footprint. The integrated P/L table then measures which class (Retail or Smart Money) is currently “winning” — comparing cumulative profitable versus losing volume.
🟠 FEATURES
Classifies flows into Smart Money or Retail based on candle-body context.
Displays live P/L comparison table for Smart vs Retail performance.
Alerts for each detected Smart or Retail buy/sell event.
🟠 USAGE
Setup : Add the script to any chart. Set Lower Timeframe Value (e.g., “5” for 5m) smaller than your main chart timeframe. The Period input controls how many bars are analyzed for the Z-score baseline. The Threshold (|Z|) decides how extreme a volume must be to plot a level.
Read the chart : Horizontal lines mark where heavy Smart or Retail volume occurred. Bright bubbles show the strongest events — their size reflects Z-score intensity. The on-chart table updates live: green cells show profitable flows, red cells show losing flows. A dominant green Smart Money row suggests institutions are currently controlling price.
See what others are doing :
Settings that matter : Raising Threshold (|Z|) filters noise, showing only large players. Increasing Period smooths results but reacts slower to new bursts. Use Show = “Both” for full comparison or isolate “Smart Money” / “Retail” to focus on one class.
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.
CloudShiftCloudShift + Bollinger Bands
This version of CloudShift now includes fully optimized Bollinger Bands with all three dynamic lines:
Upper Band: Highlights expansion during volatility spikes.
Lower Band: Identifies compression and accumulation zones.
Centerline (Basis): A smooth reference of the moving average, providing better visual balance and directional context.
The bands are drawn with thin, clean lime lines, designed to integrate perfectly with the cloud logic — keeping your chart minimalist yet powerful.
This update enhances the CloudShift indicator by providing a clear visual framework of market volatility and structure without altering its original logic.
Recommended for use on: NASDAQ, S&P 500, and other high-volatility futures.
Recommended timeframe: 5–15 minutes.
KAPITAS CBDR# PO3 Mean Reversion Standard Deviation Bands - Pro Edition
## 📊 Professional-Grade Mean Reversion System for MES Futures
Transform your futures trading with this institutional-quality mean reversion system based on standard deviation analysis and PO3 (Power of Three) methodology. Tested on **7,264 bars** of real MES data with **proven profitability across all 5 strategies**.
---
## 🎯 What This Indicator Does
This indicator plots **dynamic standard deviation bands** around a moving average, identifying extreme price levels where institutional accumulation/distribution occurs. Based on statistical probability and market structure theory, it helps you:
✅ **Identify high-probability entry zones** (±1, ±1.5, ±2, ±2.5 STD)
✅ **Target realistic profit zones** (first opposite STD band)
✅ **Time your entries** with session-based filters (London/US)
✅ **Manage risk** with built-in stop loss levels
✅ **Choose your strategy** from 5 backtested approaches
---
## 🏆 Backtested Performance (Per Contract on MES)
### Strategy #1: Aggressive (±1.5 → ∓0.5) 🥇
- **Total Profit:** $95,287 over 1,452 trades
- **Win Rate:** 75%
- **Profit Factor:** 8.00
- **Target:** 80 ticks ($100) | **Stop:** 30 ticks ($37.50)
- **Best For:** Active traders, 3-5 setups/day
### Strategy #2: Mean Reversion (±1 → Mean) 🥈
- **Total Profit:** $90,000 over 2,322 trades
- **Win Rate:** 85% (HIGHEST)
- **Profit Factor:** 11.34 (BEST)
- **Target:** 40 ticks ($50) | **Stop:** 20 ticks ($25)
- **Best For:** Scalpers, 6-8 setups/day
### Strategy #3: Conservative (±2 → ∓1) 🥉
- **Total Profit:** $65,500 over 726 trades
- **Win Rate:** 70%
- **Profit Factor:** 7.04
- **Target:** 120 ticks ($150) | **Stop:** 40 ticks ($50)
- **Best For:** Patient traders, 1-3 setups/day, HIGHEST $/trade
*Full statistics for all 5 strategies included in documentation*
---
## 📈 Key Features
### Dynamic Standard Deviation Bands
- **±0.5 STD** - Intraday mean reversion zones
- **±1.0 STD** - Primary reversion zones (68% of price action)
- **±1.5 STD** - Extended zones (optimal balance)
- **±2.0 STD** - Extreme zones (95% of price action)
- **±2.5 STD** - Ultra-extreme zones (rare events)
- **Mean Line** - Dynamic equilibrium
### Temporal Session Filters
- **London Session** (3:00-11:30 AM ET) - Orange background
- **US Session** (9:30 AM-4:00 PM ET) - Blue background
- **Optimal Entry Window** (10:30 AM-12:00 PM ET) - Green highlight
- **Best Exit Window** (3:00-4:00 PM ET) - Red highlight
### Visual Trade Signals
- 🟢 **Green zones** = Enter LONG (price at lower bands)
- 🔴 **Red zones** = Enter SHORT (price at upper bands)
- 🎯 **Target lines** = Exit zones (opposite bands)
- ⛔ **Stop levels** = Risk management
### Smart Alerts
- Alert when price touches entry bands
- Alert on optimal time windows
- Alert when targets hit
- Customizable for each strategy
---
## 💡 How to Use
### Step 1: Choose Your Strategy
Select from 5 backtested approaches based on your:
- Risk tolerance (higher STD = larger stops)
- Trading frequency (lower STD = more setups)
- Time availability (different session focuses)
- Personality (scalper vs swing trader)
### Step 2: Apply to Chart
- **Timeframe:** 15-minute (tested and optimized)
- **Symbol:** MES, ES, or other liquid futures
- **Settings:** Adjust band colors, widths, alerts
### Step 3: Wait for Setup
Price touches your chosen entry band during optimal windows:
- **BEST:** 10:30 AM-12:00 PM ET (88% win rate!)
- **GOOD:** 12:00-3:00 PM ET (75-82% win rate)
- **AVOID:** Friday after 1 PM, FOMC Wed 2-4 PM
### Step 4: Execute Trade
- Enter when price touches band
- Set stop at indicated level
- Target first opposite band
- Exit at target or stop (no exceptions!)
### Step 5: Manage Risk
- **For $50K funded account ($250 limit): Use 2 MES contracts**
- Stop after 3 consecutive losses
- Reduce size in low-probability windows
- Track cumulative daily P&L
---
## 📅 Optimal Trading Windows
### By Time of Day
- **10:30 AM-12:00 PM ET:** 88% win rate (BEST) ⭐⭐⭐
- **12:00-1:30 PM ET:** 82% win rate (scalping)
- **1:30-3:00 PM ET:** 76% win rate (afternoon)
- **3:00-4:00 PM ET:** Best EXIT window
### By Day of Week
- **Wednesday:** 82% win rate (BEST DAY) ⭐⭐⭐
- **Tuesday:** 78% win rate (highest volume)
- **Thursday:**
Hour/Day/Month Optimizer [CHE] Hour/Day/Month Optimizer — Bucketed seasonality ranking for hours, weekdays, and months with additive or compounded returns, win rate, simple Sharpe proxy, and trade counts
Summary
This indicator profiles time-of-day, day-of-week, and month-of-year behavior by assigning every bar to a bucket and accumulating its return into that bucket. It reports per-bucket score (additive or compounded), win rate, a dispersion-aware return proxy, and trade counts, then ranks buckets and highlights the current one if it is best or worst. A compact on-chart table shows the top buckets or the full ranking; a last-bar label summarizes best and worst. Optional hour filtering and UTC shifting let you align buckets with your trading session rather than exchange time.
Motivation: Why this design?
Traders often see repetitive timing effects but struggle to separate genuine seasonality from noise. Static averages are easily distorted by sample size, compounding, or volatility spikes. The core idea here is simple, explicit bucket aggregation with user-controlled accumulation (sum or compound) and transparent quality metrics (win rate, a dispersion-aware proxy, and counts). The result is a practical, legible seasonality surface that can be used for scheduling and filtering rather than prediction.
What’s different vs. standard approaches?
Reference baseline: Simple heatmaps or average-return tables that ignore compounding, dispersion, or sample size.
Architecture differences:
Dual aggregation modes: additive sum of bar returns or compounded factor.
Per-bucket win rate and trade count to expose sample support.
A simple dispersion-aware return proxy to penalize unstable averages.
UTC offset and optional custom hour window.
Deterministic, closed-bar rendering via a lightweight on-chart table.
Practical effect: You see not only which buckets look strong but also whether the observation is supported by enough bars and whether stability is acceptable. The background tint and last-bar label give immediate context for the current bucket.
How it works (technical)
Each bar is assigned to a bucket based on the selected dimension (hour one to twenty-four, weekday one to seven, or month one to twelve) after applying the UTC shift. An optional hour filter can exclude bars outside a chosen window. For each bucket the script accumulates either the sum of simple returns or the compounded product of bar factors. It also counts bars and wins, where a win is any bar with a non-negative return. From these, it derives:
Score: additive total or compounded total minus the neutral baseline.
Win rate: wins as a percentage of bars in the bucket.
Dispersion-aware proxy (“Sharpe” column): a crude ratio that rises when average return improves and falls when variability increases.
Buckets are sorted by a user-selected key (score, win rate, dispersion proxy, or trade count). The current bar’s bucket is tinted if it matches the global best or worst. At the last bar, a table is drawn with headers, an optional info row, and either the top three or all rows, using zebra backgrounds and color-coding (lime for best, red for worst). Rendering is last-bar only; no higher-timeframe data is requested, and no future data is referenced.
Parameter Guide
UTC Offset (hours) — Shifts bucket assignment relative to exchange time. Default: zero. Tip: Align to your local or desk session.
Use Custom Hours — Enables a local session window. Default: off. Trade-off: Reduces noise outside your active hours but lowers sample size.
Start / End — Inclusive hour window one to twenty-four. Defaults: eight to seventeen. Tip: Widen if rankings look unstable.
Aggregation — “Additive” sums bar returns; “Multiplicative” compounds them. Default: Additive. Tip: Use compounded for long-horizon bias checks.
Dimension — Bucket by Hour, Day, or Month. Default: Hour. Tip: Start Hour for intraday planning; switch to Day or Month for scheduling.
Show — “Top Three” or “All”. Default: Top Three. Trade-off: Clarity vs. completeness.
Sort By — Score, Win Rate, Sharpe, or Trades. Default: Score. Tip: Use Trades to surface stable buckets; use Win Rate for skew awareness.
X / Y — Table anchor. Defaults: right / top. Tip: Move away from price clusters.
Text — Table text size. Default: normal.
Light Mode — Light palette for bright charts. Default: off.
Show Parameters Row — Info header with dimension and span. Default: on.
Highlight Current Bucket if Best/Worst — Background tint when current bucket matches extremes. Default: on.
Best/Worst Barcolor — Tint colors. Defaults: lime / red.
Mark Best/Worst on Last Bar — Summary label on the last bar. Default: on.
Reading & Interpretation
Score column: Higher suggests stronger cumulative behavior for the chosen aggregation. Compounded mode emphasizes persistence; additive mode treats all bars equally.
Win Rate: Stability signal; very high with very low trades is unreliable.
“Sharpe” column: A quick stability proxy; use it to down-rank buckets that look good on score but fluctuate heavily.
Trades: Sample size. Prefer buckets with adequate counts for your timeframe and asset.
Tinting: If the current bucket is globally best, expect a lime background; if worst, red. This is context, not a trade signal.
Practical Workflows & Combinations
Trend following: Use Hour or Day to avoid initiating trades during historically weak buckets; require structure confirmation such as higher highs and higher lows, plus a momentum or volatility filter.
Mean reversion: Prefer buckets with moderate scores but acceptable win rate and dispersion proxy; combine with deviation bands or volume normalization.
Exits/Stops: Tighten exits during historically weak buckets; relax slightly during strong ones, but keep absolute risk controls independent of the table.
Multi-asset/Multi-TF: Start with Hour on liquid intraday assets; for swing, use Day. On monthly seasonality, require larger lookbacks to avoid overfitting.
Behavior, Constraints & Performance
Repaint/confirmation: Calculations use completed bars only; table and label are drawn on the last bar and can update intrabar until close.
security()/HTF: None used; repaint risk limited to normal live-bar updates.
Resources: Arrays per dimension, light loops for metric building and sorting, `max_bars_back` two thousand, and capped label/table counts.
Known limits: Sensitive to sample size and regime shifts; ignores costs and slippage; bar-based wins can mislead on assets with frequent gaps; compounded mode can over-weight streaks.
Sensible Defaults & Quick Tuning
Start: Hour dimension, Additive, Top Three, Sort by Score, default session window off.
Too many flips: Switch to Sort by Trades or raise sample by widening hours or timeframe.
Too sluggish/over-smoothed: Switch to Additive (if on compounded) or shorten your chart timeframe while keeping the same dimension.
Overfit risk: Prefer “All” view to verify that top buckets are not isolated with tiny counts; use Day or Month only with long histories.
What this indicator is—and isn’t
This is a seasonality and scheduling layer that ranks time buckets using transparent arithmetic and simple stability checks. It is not a predictive model, not a complete trading system, and it does not manage risk. Use it to plan when to engage, then rely on structure, confirmation, and independent risk management for entries and exits.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Relative Performance Indicator - TrendSpider StyleRelative Performance Indicator - TrendSpider Style
📈 Overview
This Relative Performance (RP) indicator measures how your stock is performing compared to a benchmark index, displayed as a percentile ranking from 0-100. Based on TrendSpider's methodology, it answers the critical question: "Is this stock a leader or a laggard?"
Unlike simple ratio charts, this indicator uses percentile ranking to normalize relative performance, making it easy to identify when a stock is showing exceptional strength (>80) or concerning weakness (<20) compared to its historical relationship with the benchmark.
✨ Key Features
Three Calculation Modes:
Quarterly: 3-month relative performance for swing trading
Yearly: Weighted 4-quarter performance for position trading
TechRank: Composite of 6 technical indicators for multi-factor analysis
Clean Visual Design:
Green fills above 80 (strong outperformance)
Red fills below 20 (significant underperformance)
Dotted median line at 50 for quick reference
Current value label for instant reading
Flexible Benchmarks:
Compare against major indices (SPY, QQQ, IWM)
Sector ETFs for within-sector analysis
Custom symbols for specialized comparisons
Built-in Alerts:
Strong performance zone entry (>80)
Weak performance zone entry (<20)
Median crossovers (50 level)
📊 How To Use
Buy Signals:
RP crosses above 80: Stock entering leadership status
RP holding above 60: Maintaining relative strength
RP rising while price consolidating: Accumulation phase
Sell/Avoid Signals:
RP drops below 50: Losing relative strength
RP below 20: Significant underperformance
RP falling while price rising: Bearish divergence
Sector Rotation:
Compare multiple assets to find strongest sectors
Rotate into high RP assets (>70)
Exit low RP positions (<30)
🎯 Reading The Values
80-100: Exceptional outperformance - Strong buy/hold
60-80: Moderate outperformance - Hold positions
40-60: Market perform - No edge
20-40: Underperformance - Caution/reduce
0-20: Severe underperformance - Avoid/exit
⚙️ Calculation Method
Calculates percentage performance of both your stock and the benchmark
Finds the performance differential
Ranks this differential against historical values using percentile analysis
Normalizes to 0-100 scale for easy interpretation
This percentile approach adapts to different market conditions and volatility regimes, providing consistent signals whether in trending or choppy markets.
💡 Pro Tips
For Growth Stocks: Use quarterly mode with QQQ as benchmark
For Value Stocks: Use yearly mode with SPY as benchmark
For Small Caps: Compare against IWM, not SPY
For Sector Analysis: Use sector ETFs (XLK, XLF, XLE, etc.)
Combine with Price Action: High RP + price breakout = powerful signal
⚠️ Important Notes
RP is relative, not absolute - stocks can fall with high RP if the market falls harder
Choose appropriate benchmarks for meaningful comparisons
Best used in conjunction with price action and volume analysis
Historical lookback period affects sensitivity (adjustable in settings)
🔧 Customization
Fully customizable visual settings, thresholds, calculation periods, and smoothing options. Adjust the normalization lookback period (default 252 days) to fine-tune sensitivity to your trading timeframe.
📌 Credit
Inspired by TrendSpider's Relative Performance implementation, adapted for TradingView with enhanced customization options and Pine Script v6 optimization.
Tags to include: relativeperformance, relativestrength, percentile, ranking, sectorrotation, benchmark, outperformance, trendspider, marketbreadth, strengthindicator
Category: Momentum Indicators / Trend Analysis
Feel free to modify this description to match your style or add any specific points you want to emphasize!
CFR - Candle Formation RatioDescription
This indicator is designed to detect candles with small bodies and significant wick-to-body ratios, often useful for identifying doji-like structures and potential accumulation areas.
Features
Filter candles by maximum body size (% of the total candle range).
Require that wicks are at least X times larger than the body.
Define the position of the body within the candle (e.g., body must be between 40% and 60% of the candle height).
Visual output: a single arrow marker when conditions are met.
Fully customizable marker color and size.
⚠️ Note: The settings of this version are currently in Turkish. An English version of the settings will be released in the future.
Premier Stochastic Oscillator [LazyBear, V2]This script builds on the well-known Premier Stochastic Oscillator (PSO) originally introduced by LazyBear, and adds a Z-Score extension to provide statistical interpretation of momentum extremes.
Features
Premier Stochastic Core: A smoothed stochastic calculation that highlights bullish and bearish momentum phases.
Z-Score Mapping: The PSO values are standardized into Z-Scores (from –3 to +3), quantifying the degree of momentum stretch.
Positive / Negative Z-Scores:
Positive Z values suggest momentum strength that can align with accumulation or favorable buying conditions.
Negative Z values indicate stronger bearish pressure, often aligning with selling or distribution conditions.
On-Chart Label: The current Z-Score is displayed on the latest bar for quick reference.
How to Use
Momentum Confirmation: Use the oscillator to confirm whether bullish or bearish momentum is intensifying.
Overextended Conditions: Extreme Z-Scores (±2 or beyond) highlight statistically stretched conditions, often preceding reversions.
Strategic Integration: Best applied in confluence with trend tools or higher-timeframe filters; not a standalone trading signal.
Originality
Unlike the standard PSO, this version:
Adds a Z-Score framework for objective statistical scaling.
Provides real-time labeling of Z values for clarity.
Extends the classic oscillator into a tool for both momentum detection and mean-reversion context.
350DMA bands + Z-score (V2)This script extends the classic 350-day moving average (350DMA) by building dynamic valuation bands and a Z-Score framework to evaluate how far price deviates from its long-term mean.
Features
350DMA Anchor: Uses the 350-day simple moving average as the baseline reference.
Fixed Multipliers: Key bands plotted at ×0.625, ×1.0, ×1.6, ×2.0, and ×2.5 of the 350DMA — historically significant levels for cycle analysis.
Z-Score Mapping: Price is converted into a Z-Score on a scale from +2 (deep undervaluation) to –2 (extreme overvaluation), using log-space interpolation for accuracy.
Custom Display: HUD panel and on-chart label show the current Z-Score in real time.
Clamp Option: Users can toggle between raw Z values or capped values (±2).
How to Use
Valuation Context: The 350DMA is often considered a “fair value” anchor; large deviations identify cycles of under- or over-valuation.
Z-Score Insight:
Positive Z values suggest favorable accumulation zones where price is below long-term average.
Negative Z values highlight zones of stretched valuation, often associated with distribution or profit-taking.
Strategic Application: This is not a standalone trading system — it works best in confluence with other indicators, cycle models, or macro analysis.
Originality
Unlike a simple DMA overlay, this script:
Provides multiple cycle-based bands derived from the 350DMA.
Applies a logarithmic Z-Score mapping for more precise long-term scaling.
Adds an integrated HUD and labeling system for quick interpretation.
200WMA Overlay + Z (heatmap mapping)This script enhances the classic 200-week moving average (200WMA), a long-term market reference line, by adding Z-Score mapping and optional helper bands for extended cycle analysis.
Features
200WMA Anchor: Plots the true 200-week simple moving average on any chart, a widely followed metric for long-term Bitcoin and crypto cycles.
Helper Multiples: Optional overlay of key historical ratios (×0.625, ×1.6, ×2.0, ×2.5) often referenced as cycle support/resistance zones.
Z-Score Mapping: Translates the ratio of price to 200WMA into a Z-Score scale (from +2.5 to –2.5), offering a statistical perspective on whether the market is undervalued, neutral, or overheated relative to its long-term mean.
On-Chart Label: Current Z-Score displayed directly on the last bar for quick reference.
How to Use
Long-Term Valuation: The 200WMA serves as a “fair value” baseline; large deviations highlight extended phases of market sentiment.
Heatmap Context:
Positive Z values typically mark undervaluation or favorable accumulation zones.
Negative Z values highlight overvaluation or profit-taking / distribution zones.
Strategic View: Best used to contextualize long-term market cycles, not for short-term signals.
Confluence Approach: This indicator should not be used alone — combine it with other technical or fundamental tools for stronger decision-making.
Originality
Unlike a basic 200WMA overlay, this version:
Incorporates multi-band ratios for extended cycle mapping.
Introduces a custom Z-Score scale tied directly to price/WMA ratios.
Provides both visual structure and statistical interpretation on a single overlay.
Yearly VWAP with Z-Score V2This script extends the traditional Volume Weighted Average Price (VWAP) by applying it to yearly sessions (with a customizable start month) and combining it with a Z-Score framework to standardize price deviations from VWAP.
Features
Yearly VWAP: Automatically resets at the selected month, making it possible to align VWAP with fiscal or seasonal cycles (e.g., June–May).
Volatility-Weighted Bands: Standard deviation is calculated using volume-weighted price variance, creating adaptive upper and lower bands around VWAP.
Z-Score Calculation: Converts price distance from VWAP into standardized scores, ranging from +2.5 to –2.5. This enables statistical interpretation of whether price is trading at fair value, extended, or oversold relative to VWAP.
Custom Session Control: Input allows users to change the yearly anchor month.
On-Chart Display: VWAP and bands are plotted, with a live Z-Score label shown on the latest bar.
How to Use
Fair Value Reference: VWAP reflects the average price weighted by volume over the yearly session — a natural equilibrium point.
Overbought / Oversold Detection: Extreme Z-Score readings (±2 or beyond) highlight when price is stretched relative to VWAP.
Cycle Analysis: Resetting VWAP by custom months allows studying market behavior over fiscal years, seasons, or custom trading cycles.
Part of a Broader Toolkit: This script is not a standalone trading system. It works best when aggregated with other indicators, confluence factors, or a structured strategy.
Originality
Unlike a standard VWAP, this version:
Uses yearly anchoring with custom start month instead of session/day anchoring.
Adds volume-weighted standard deviation bands for statistical context.
Translates distance into a Z-Score scale for objective overbought/oversold assessment.
Positive Z-Score values indicate zones where price is positioned favorably for accumulation or potential buys, while negative values highlight areas more suitable for distribution or profit-taking — always best used in confluence with other tools rather than as a standalone signal
Combined Cluster & Market StructureI barrowed code from the Mxwll Price Action Suite script as appreciated the structure in which the script defined structure, however I renamed variables and reduced the original script to define only the outer structure. I added volume and CVD clustering to define ranges and initiation market structures and add the ADX to assist with determining trend strength prior to labeling market structure breaks.
Combined Cluster & Market Structure indicator, a powerful and comprehensive tool for technical analysis. This script integrates two core concepts to provide a holistic view of market dynamics:
Z-Score Clustering & Volume Analysis: The indicator calculates Z-scores for both volume and Cumulative Volume Delta (CVD) to categorize market activity into six distinct clusters:
High-Conviction Bullish/Bearish: Signals of strong directional momentum based on high volume and corresponding CVD.
Effort vs. Result: High volume with moderate CVD, suggesting potential indecision or absorption.
Quiet Accumulation/Distribution: Low-volume periods with strong CVD, often preceding major moves.
Low Conviction/Noise: Represents periods of low market participation and weak signals.
These clusters are visually marked on the chart to provide real-time insight into market sentiment.
Market Structure Mapping: The indicator automatically detects and labels significant structural points to help you navigate price action. It identifies:
Higher Highs (HH) and Lower Lows (LL) to show the primary trend direction.
Breaks of Structure (BoS), indicating trend continuation.
Changes of Character (CHoCH), signaling a potential trend reversal.
Additionally, the script features consolidation box detection, which automatically highlights periods of low-conviction market activity, helping you avoid choppy, sideways markets. An integrated ADX filter ensures that structural breaks are only labeled during periods of strong trend strength, reducing false signals.
I want to thank Mxwll Capital for their contribution to the Combined Cluster & Market Structure indicator.
AVGO Advanced Day Trading Strategy📈 Overview
The AVGO Advanced Day Trading Strategy is a comprehensive, multi-timeframe trading system designed for active day traders seeking consistent performance with robust risk management. Originally optimized for AVGO (Broadcom), this strategy adapts well to other liquid stocks and can be customized for various trading styles.
🎯 Key Features
Multiple Entry Methods
EMA Crossover: Classic trend-following signals using fast (9) and medium (16) EMAs
MACD + RSI Confluence: Momentum-based entries combining MACD crossovers with RSI positioning
Price Momentum: Consecutive price action patterns with EMA and RSI confirmation
Hybrid System: Advanced multi-trigger approach combining all methodologies
Advanced Technical Arsenal
When enabled, the strategy analyzes 8+ additional indicators for confluence:
Volume Price Trend (VPT): Measures volume-weighted price momentum
On-Balance Volume (OBV): Tracks cumulative volume flow
Accumulation/Distribution Line: Identifies institutional money flow
Williams %R: Momentum oscillator for entry timing
Rate of Change Suite: Multi-timeframe momentum analysis (5, 14, 18 periods)
Commodity Channel Index (CCI): Cyclical turning points
Average Directional Index (ADX): Trend strength measurement
Parabolic SAR: Dynamic support/resistance levels
🛡️ Risk Management System
Position Sizing
Risk-based position sizing (default 1% per trade)
Maximum position limits (default 25% of equity)
Daily loss limits with automatic position closure
Multiple Profit Targets
Target 1: 1.5% gain (50% position exit)
Target 2: 2.5% gain (30% position exit)
Target 3: 3.6% gain (20% position exit)
Configurable exit percentages and target levels
Stop Loss Protection
ATR-based or percentage-based stop losses
Optional trailing stops
Dynamic stop adjustment based on market volatility
📊 Technical Specifications
Primary Indicators
EMAs: 9 (Fast), 16 (Medium), 50 (Long)
VWAP: Volume-weighted average price filter
RSI: 6-period momentum oscillator
MACD: 8/13/5 configuration for faster signals
Volume Confirmation
Volume filter requiring 1.6x average volume
19-period volume moving average baseline
Optional volume confirmation bypass
Market Structure Analysis
Bollinger Bands (20-period, 2.0 multiplier)
Squeeze detection for breakout opportunities
Fractal and pivot point analysis
⏰ Trading Hours & Filters
Time Management
Configurable trading hours (default: 9:30 AM - 3:30 PM EST)
Weekend and holiday filtering
Session-based trade management
Market Condition Filters
Trend alignment requirements
VWAP positioning filters
Volatility-based entry conditions
📱 Visual Features
Information Dashboard
Real-time display of:
Current entry method and signals
Bullish/bearish signal counts
RSI and MACD status
Trend direction and strength
Position status and P&L
Volume and time filter status
Chart Visualization
EMA plots with customizable colors
Entry signal markers
Target and stop level lines
Background color coding for trends
Optional Bollinger Bands and SAR display
🔔 Alert System
Entry Alerts
Customizable alerts for long and short entries
Method-specific alert messages
Signal confluence notifications
Advanced Alerts
Strong confluence threshold alerts
Custom alert messages with signal counts
Risk management alerts
⚙️ Customization Options
Strategy Parameters
Enable/disable long or short trades
Adjustable risk parameters
Multiple entry method selection
Advanced indicator on/off toggle
Visual Customization
Color schemes for all indicators
Dashboard position and size options
Show/hide various chart elements
Background color preferences
📋 Default Settings
Initial Capital: $100,000
Commission: 0.1%
Default Position Size: 10% of equity
Risk Per Trade: 1.0%
RSI Length: 6 periods
MACD: 8/13/5 configuration
Stop Loss: 1.1% or ATR-based
🎯 Best Use Cases
Day Trading: Designed for intraday opportunities
Swing Trading: Adaptable for longer-term positions
Momentum Trading: Excellent for trending markets
Risk-Conscious Trading: Built-in risk management protocols
⚠️ Important Notes
Paper Trading Recommended: Test thoroughly before live trading
Market Conditions: Performance varies with market volatility
Customization: Adjust parameters based on your risk tolerance
Educational Purpose: Use as a learning tool and customize for your needs
🏆 Performance Features
Detailed performance metrics
Trade-by-trade analysis capability
Customizable risk/reward ratios
Comprehensive backtesting support
This strategy is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and consider your financial situation before trading.
Strong Trend Suite — Clean v6A clean, rules-based trend tool for swing traders. It identifies strong up/down trends by syncing five pillars:
Trend structure: price above/below a MA stack (EMA20 > SMA50 > EMA200 for up; inverse for down).
Momentum: RSI (50 line) and MACD (line > signal and side of zero).
Trend strength: ADX above a threshold and rising.
Volume confirmation: OBV vs its short MA (accumulation/distribution).
Optional higher-TF bias: weekly filter to avoid fighting bigger flows.
When all align, the background tints and the mini-meter flips green/red (UP/DOWN).
It also marks entry cues: pullbacks to EMA20/SMA50 with a MACD re-cross, or breakouts of recent highs/lows on volume.
Built-in alerts for strong trend, pullback, and breakout keep you hands-off; use “Once per bar close” on the Daily chart for best signal quality.
RSI (8 & 13) + Fibonacci LevelsIndicator Description: RSI (8 & 13) + Fibonacci Levels
This custom indicator is designed to provide a dual-speed RSI framework with embedded Fibonacci retracement levels for advanced momentum and reversal analysis. It combines the power of relative strength measurement with the natural harmony of Fibonacci ratios to give traders a structured approach to market timing and confluence trading.
The indicator plots two RSI lines on a dedicated sub-chart:
RSI Fast (8) → short-term momentum, highly sensitive to price action, helps identify quick shifts and micro-trends.
RSI Slow (13) → smoother and less volatile, acts as confirmation of broader trend direction and underlying strength.
By combining both RSI speeds, traders can spot alignment, divergences, and crossover signals between fast and slow momentum. When both lines move in sync, it reflects strong conviction; when they diverge, it signals potential exhaustion or trend shifts.
Overlaying Fibonacci retracement levels on RSI adds an extra dimension of precision. Instead of using arbitrary zones, the indicator relies on mathematically significant levels tied to natural market cycles:
23.6% → shallow pullbacks, early momentum pauses.
38.2% → minor retracements, often signaling trend continuation.
50% → balance point between strength and weakness.
61.8% → golden ratio, strong correction or reversal zone.
78.6% → deep retracement, last line before full reversal.
In addition, the script marks the classic RSI boundaries:
70 (Overbought) → potential profit-taking, stretched bullish conditions.
30 (Oversold) → potential accumulation, stretched bearish conditions.
Together, these zones help traders gauge not only when the RSI is “too high” or “too low,” but also where price momentum aligns with natural Fibonacci retracement zones. This approach transforms RSI from a simple oscillator into a multi-layered momentum map.
Practical Uses:
Trend Confirmation → When RSI(8) and RSI(13) are both above 50 and rising, bullish strength is confirmed.
Divergence Detection → If price makes higher highs but RSI(8) fails to confirm, it warns of weakening momentum.
Reversal Hunting → Look for RSI rejection candles at Fib levels (e.g., fast RSI hitting 61.8 and rolling over).
Entry/Exit Timing → Use fast RSI crossovers with slow RSI as tactical entries within the broader structure.
Confluence Trading → Strong signals occur when RSI rejection coincides with price structure (double tops/bottoms, Fibonacci levels on chart, Bollinger Band rejections).
This indicator is especially powerful when paired with Bollinger Bands or price action rejection patterns, creating a system where price extremes are validated against RSI Fib zones.
Ultimately, the RSI (8 & 13) + Fibonacci Levels indicator acts as a precision filter — helping traders separate noise from genuine turning points and reinforcing entries/exits with multiple layers of confluence.
Bollinger Bands (SMA 21, 2.618σ)Indicator Description: Bollinger Bands (2.618σ, 21 SMA) + RSI with Fibonacci
This custom indicator combines Bollinger Bands and Relative Strength Index (RSI), enhanced with Fibonacci-based configurations, to provide confluence signals for rejection candles, reversal setups, and continuation patterns.
Bollinger Bands Settings (Customized)
Middle Band → 21-period Simple Moving Average (SMA)
Upper Band → SMA + 2.618 standard deviations
Lower Band → SMA − 2.618 standard deviations
These parameters expand the bands compared to the traditional (20, 2.0) settings, making them better suited for volatility extremes and higher timeframe swing analysis.
Color Scheme
Middle Band = Orange
Upper Band = Red
Lower Band = Green
This color-coding emphasizes key rejection levels visually.
Candle Rejection Logic
The indicator is designed to highlight potential rejection candles when price interacts with the outer Bollinger Bands:
At the Upper Band, rejection signals suggest overextension and potential downside reaction.
At the Lower Band, rejection signals suggest oversold conditions and potential upside reaction.
Rejection Candle Types Tracked
Hammer (bullish reversal, lower rejection wick at bottom band)
Inverted Hammer (bearish reversal, upper rejection wick at top band)
Doji candles (indecision at band extremes)
Double Top formations near the upper band
Double Bottom formations near the lower band
Relative Strength Index (RSI) Settings
RSI is configured with Fibonacci retracement levels instead of traditional 30/70 thresholds.
Fibonacci sequence levels used include:
23.6% (0.236)
38.2% (0.382)
50% (0.5)
61.8% (0.618)
78.6% (0.786)
This alignment with Fibonacci ratios provides deeper market structure insights into momentum strength and exhaustion points.
Trading Confluence Zones
Upper Band + RSI at 0.618–0.786 zone → High probability bearish rejection.
Lower Band + RSI at 0.236–0.382 zone → High probability bullish reversal.
Band interaction + Doji or Hammer candles → Stronger signal confirmation.
Use Cases
Identifying trend exhaustion when price repeatedly fails to break above the upper band.
Spotting accumulation or distribution phases when price consolidates around Fibonacci-based RSI zones.
Detecting false breakouts when candle patterns (like Doji or Inverted Hammer) occur beyond the bands.
Why 2.618 Deviation & 21 SMA?
Standard Bollinger Bands (20, 2.0) capture ~95% of price action.
By widening to 2.618σ, we target extreme volatility outliers — areas where reversals are statistically more likely.
A 21-period SMA aligns better with common cycle lengths (3 trading weeks on daily charts) and Fibonacci-related time cycles.
Practical Strategy
Step 1: Watch when price touches or pierces the upper/lower band.
Step 2: Check for candle rejection patterns (Hammer, Inverted Hammer, Doji, Double Top/Bottom).
Step 3: Confirm with RSI Fibonacci levels for confluence.
Step 4: Trade with the prevailing trend or look for reversal setups if multiple confluence factors align.
Cautions
Not all touches of the bands signal reversals — strong trends can ride along the bands for extended periods.
Always combine with price action structure, volume, and higher timeframe trend bias.
📌 Summary
This indicator blends volatility-based bands with Fibonacci momentum analysis and classical candle rejection patterns. The combination of Bollinger Bands (21, 2.618σ) and RSI Fibonacci levels helps traders detect high-probability rejection zones, reversal opportunities, and overextended conditions with improved accuracy over traditional default settings.
