Island Reversal [LuxAlgo]The Island Reversal tool allows traders to identify reversal patterns directly on the chart. These patterns signal a potential change in trend, either from bullish to bearish or vice versa.
The tool enables traders to filter these patterns by trend, volume, and range, making it easy to display pure or less constrained island reversals.
🔶 USAGE
An island reversal pattern may indicate a change in trend. It occurs when prices change direction from an uptrend to a downtrend, or vice versa.
This pattern is a great tool for timing the market. Traders should be aware of when these patterns develop and watch how prices behave after the pattern forms.
Now, let's take a closer look at one of these island reversal patterns to highlight its different components.
The different parts are depicted in the image above.
1. A trend prior to the pattern
2. A gap starts the pattern.
3. A range of prices
4. A final gap, opposite to the first one, closes the pattern.
5. In this case, the pattern leads to a bearish trend, which is opposite to the trend in the first step.
🔹 Trend, Volume and Range Filters
Enabling the trend filter causes the tool to only detect top island reversals during a bullish trend and bottom island reversals during a bearish trend.
Traders can adjust the size of the detected trend in the settings panel. The larger the trend size, the more relevant the reversal patterns can be.
The volume filter only detects reversal patterns if there is more volume within the range of the pattern than in the preceding trend.
The idea is that more people tend to participate at the top and bottom of a trend as it changes direction.
The tool has two range filters that discriminate the range within the island reversal pattern:
Horizontality Filter (R2): Based on the R-squared statistic from linear regression, it detects whether the price is moving sideways within the range.
Volatility Filter: Based on long-term volatility, it detects the size of the range within the pattern.
The smaller the value in the Horizontality Filter, the more horizontal the prices will be within the range. A larger value will detect more reversal patterns.
The larger the value in the Volatility Filter, the larger the ranges will be. A smaller value will detect fewer reversal patterns.
🔶 SETTINGS
🔹 Trend Filter
Trend Filter: Enable or disable the trend filter.
Trend Length: Select the size of the detected trend.
🔹 Volume Filter
Volume Filter: Enable or disable the volume filter.
🔹 Range Filter
Horizontality Filter (R2): Enable or disable the Horizontality filter and select a threshold value.
Volatility Filter: Enable or disable the Volatility filter and select the multiplier value.
🔹 Style
Bullish: Select a color for bullish sessions.
Bearish: Select a color for bearish sessions.
Transparency: Select a transparency level from 100 to 0.
المؤشرات والاستراتيجيات
Breakout Boxes [ChartPrime]⯁ OVERVIEW
The Breakout Boxes indicator identifies key structural levels by detecting and aligning two consecutive pivots — forming confirmation zones where potential breakouts are most likely to occur. Once two pivots align within a defined ATR range, the indicator constructs a Breakout Box around that area, tracking volume distribution and breakout strength. When price breaks above or below these boxes, breakout labels (⯁ BreakUp / BreakDn) are displayed to confirm trend continuation.
⯁ KEY FEATURES
Pivot-Based Detection: Uses a customizable pivot length to identify market swing highs and lows.
Two-Pivot Alignment Logic: A breakout box is only created when two pivot highs or lows form near the same level, confirming structural alignment and increasing breakout reliability.
Dynamic Box Generation: Builds upper and lower boxes once pivot alignment is confirmed, adapting automatically to new structures.
Volume Distribution Analysis: Each box measures total traded volume and separates it into bullish and bearish components, showing buy/sell percentages inside the range.
The volume data is calculated in real time as long as the box remains active and unbroken, allowing traders to monitor live accumulation or distribution before a breakout occurs.
Breakout Confirmation Signals: Labels appear when price decisively breaks above the upper box (⯁ BreakUp) or below the lower one (⯁ BreakDn).
Adaptive ATR Scaling: Box size dynamically adjusts to volatility, maintaining consistent proportions across assets and timeframes.
Color-Coded Visualization: Upper (bearish) boxes use pink tones; lower (bullish) boxes use green, both with transparent fill for volume clarity.
Automatic Box Resetting: Previous boxes close when a new pivot pair forms, ensuring only the most relevant structure is active.
⯁ USAGE
Watch for Two Pivot Alignments — the indicator only activates when structural confluence exists, reducing false breakout signals.
Upper Boxes represent resistance formed by two aligned swing highs; a breakout above indicates potential bullish continuation.
Lower Boxes represent support formed by two aligned swing lows; a breakdown below indicates bearish continuation.
Analyze the Volume Ratio inside each box — higher buy volume in upper boxes supports bullish breakouts, while higher sell volume in lower boxes supports bearish moves.
Use this tool alongside trend indicators or higher timeframe context to confirm the direction of breakouts.
⯁ CONCLUSION
The Breakout Boxes indicator refines breakout analysis by requiring two aligned pivots to validate structural zones. By combining pivot confluence with volume distribution and adaptive ATR scaling, it provides a precise, data-backed visualization of breakout strength and direction — a powerful tool for structure-based trading confirmation.
Ornstein-Uhlenbeck Trend Channel [BOSWaves]Ornstein-Uhlenbeck Trend Channel - Adaptive Mean Reversion with Dynamic Equilibrium Geometry
Overview
The Ornstein-Uhlenbeck Trend Channel introduces an advanced equilibrium-mapping framework that blends statistical mean reversion with adaptive trend geometry. Traditional channels and regression bands react linearly to volatility, often failing to capture the natural rhythm of price equilibrium. This model evolves that concept through a dynamic reversion engine, where equilibrium adapts continuously to volatility, trend slope, and structural bias - forming a living channel that bends, expands, and contracts in real time.
The result is a smooth, equilibrium-driven representation of market balance - not just trend direction. Instead of static bands or abrupt slope shifts, traders see fluid, volatility-aware motion that mirrors the natural pull-and-release dynamic of market behavior. Each channel visualizes the probabilistic boundaries of fair value, showing where price tends to revert and where it accelerates away from its statistical mean.
Unlike conventional envelopes or Bollinger-type constructs, the Ornstein-Uhlenbeck framework is volatility-reactive and equilibrium-sensitive, providing traders with a contextual map of where price is likely to stabilize, extend, or exhaust.
Theoretical Foundation
The Ornstein-Uhlenbeck Trend Channel is inspired by stochastic mean-reversion processes - mathematical models used to describe systems that oscillate around a drifting equilibrium. While linear regression channels assume constant variance, financial markets operate under variable volatility and shifting equilibrium points. The OU process accounts for this by treating price as a mean-seeking motion governed by volatility and trend persistence.
At its core are three interacting components:
Equilibrium Mean (μ) : Represents the evolving balance point of price, adjusting to directional bias and volatility.
Reversion Rate (θ) : Defines how strongly price is pulled back toward equilibrium after deviation, capturing the self-correcting nature of market structure.
Volatility Coefficient (σ) : Controls how far and how quickly price can diverge from equilibrium before mean reversion pressure increases.
By embedding this stochastic model inside a volatility-adjusted framework, the system accurately scales across different markets and conditions - maintaining meaningful equilibrium geometry across crypto, forex, indices, or commodities. This design gives traders a mathematically grounded yet visually intuitive interpretation of dynamic balance in live market motion.
How It Works
The Ornstein-Uhlenbeck Trend Channel is constructed through a structured multi-stage process that merges stochastic logic with volatility mechanics:
Equilibrium Estimation Core : The indicator begins by identifying the evolving mean using adaptive smoothing influenced by trend direction and volatility. This becomes the live centerline - the statistical anchor around which price naturally oscillates.
Volatility Normalization Layer : ATR or rolling deviation is used to calculate volatility intensity. The output scales the channel width dynamically, ensuring that boundaries reflect current variance rather than static thresholds.
Directional Bias Engine : EMA slope and trend confirmation logic determine whether equilibrium should tilt upward or downward. This creates asymmetrical channel motion that bends with the prevailing trend rather than staying horizontal.
Channel Boundary Construction : Upper and lower bands are plotted at volatility-proportional distances from the mean. These envelopes form the “statistical pressure zones” that indicate where mean reversion or acceleration may occur.
Signal and Lifecycle Control : Channel breaches, mean crossovers, and slope flips mark statistically significant events - exhaustion, continuation, or rebalancing. Older equilibrium zones gradually fade, ensuring a clear, context-aware visual field.
Through these layers, the channel forms a continuously updating equilibrium corridor that adapts in real time - breathing with the market’s volatility and rhythm.
Interpretation
The Ornstein-Uhlenbeck Trend Channel reframes how traders interpret balance and momentum. Instead of viewing price as directional movement alone, it visualizes the constant tension between trending force and equilibrium pull.
Uptrend Phases : The equilibrium mean tilts upward, with price oscillating around or slightly above the midline. Upper band touches signal momentum extension; lower touches reflect healthy reversion.
Downtrend Phases : The mean slopes downward, with upper-band interactions marking resistance zones and lower bands acting as reversion boundaries.
Equilibrium Transitions : Flat mean sections indicate balance or distribution phases. Breaks from these neutral zones often precede directional expansion.
Overextension Events : When price closes beyond an outer boundary, it marks statistically significant disequilibrium - an early warning of exhaustion or volatility reset.
Visually, the OU channel translates volatility and equilibrium into structured geometry, giving traders a statistical lens on trend quality, reversion probability, and volatility stress points.
Strategy Integration
The Ornstein-Uhlenbeck Trend Channel integrates seamlessly into both mean-reversion and trend-continuation systems:
Trend Alignment : Use mean slope direction to confirm higher-timeframe bias before entering continuation setups.
Reversion Entries : Target rejections from outer bands when supported by volume or divergence, capturing snapbacks toward equilibrium.
Volatility Breakout Mapping : Monitor boundary expansions to identify transition from compression to expansion phases.
Liquidity Zone Confirmation : Combine with BOS or order-block indicators to validate structural zones against equilibrium positioning.
Momentum Filtering : Align with oscillators or volume profiles to isolate equilibrium-based pullbacks with statistical context.
Technical Implementation Details
Core Engine : Stochastic Ornstein-Uhlenbeck process for continuous mean recalibration.
Volatility Framework : ATR- and deviation-based scaling for dynamic channel expansion.
Directional Logic : EMA-slope driven bias for adaptive mean tilt.
Channel Composition : Independent upper and lower envelopes with smoothing and transparency control.
Signal Structure : Alerts for mean crossovers and boundary breaches.
Performance Profile : Lightweight, multi-timeframe compatible implementation optimized for real-time responsiveness.
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Reactive equilibrium tracking for short-term scalping and microstructure analysis.
15 - 60 min : Medium-range setups for volatility-phase transitions and intraday structure.
4H - Daily : Macro equilibrium mapping for identifying exhaustion, distribution, or reaccumulation zones.
Suggested Configuration:
Mean Length : 20 - 50
Volatility Multiplier : 1.5× - 2.5×
Reversion Sensitivity : 0.4 - 0.8
Smoothing : 2 - 5
Parameter tuning should reflect asset liquidity, volatility, and desired reversion frequency.
Performance Characteristics
High Effectiveness:
Trending environments with cyclical pullbacks and volatility oscillation.
Markets exhibiting consistent equilibrium-return behavior (indices, majors, high-cap crypto).
Reduced Effectiveness:
Low-volatility consolidations with minimal variance.
Random walk markets lacking definable equilibrium anchors.
Integration Guidelines
Confluence Framework : Pair with BOSWaves structural tools or momentum oscillators for context validation.
Directional Control : Follow mean slope alignment for directional conviction before acting on channel extremes.
Risk Calibration : Use outer band violations for controlled contrarian entries or trailing stop management.
Multi-Timeframe Synergy : Derive macro equilibrium zones on higher timeframes and refine entries on lower levels.
Disclaimer
The Ornstein-Uhlenbeck Trend Channel is a professional-grade equilibrium and volatility framework. It is not predictive or profit-assured; performance depends on parameter calibration, volatility regime, and disciplined execution. BOSWaves recommends using it as part of a comprehensive analytical stack combining structure, liquidity, and momentum context.
Liquidity Spectrum Visualizer BigBeluga - optimized by nguyenthlThis optimized version of the original Liquidity Spectrum Visualizer is designed for traders who want the same analytical output as the original indicator, but with significantly faster execution and smoother performance.
The script preserves the original visualization and logic — it still maps volume activity across price bins to highlight liquidity clusters — but the internal calculations have been carefully restructured to reduce computational load and improve responsiveness on live charts.
What’s new and why it matters
Single-pass binning algorithm: Each bar is processed once, reducing loop complexity from O(N×M) to O(N). This allows the indicator to run fluidly on higher timeframes and large datasets.
Precomputed min/max levels: Eliminates redundant array scans, improving efficiency for real-time analysis.
Minimal label usage: Only key high/low markers are drawn, removing visual clutter and improving chart readability.
Optimized resource handling: Boxes and lines are refreshed as a group, minimizing redraw lag.
Why this is useful
This version is particularly helpful for traders using complex layouts, slower machines, or multi-chart setups. It offers the same analytical insight into liquidity zones while keeping chart performance stable and responsive.
How to use it
Apply the indicator as you would the original version. It visualizes liquidity distributions, helping identify areas of concentrated activity or potential support/resistance zones.
The script includes optional features such as gradient rendering and POC (Point of Control) highlighting, which can be toggled on or off for clarity.
Notes
The purpose of this version is purely performance optimization — analytical integrity is fully preserved.
The chart example provided focuses solely on this indicator, with no additional overlays, so users can clearly see its visual output.
Smart Money Flow Index (SMFI) - Advanced SMC [PhenLabs]📊Smart Money Flow Index (SMFI)
Version: PineScript™v6
📌Description
The Smart Money Flow Index (SMFI) is an advanced Smart Money Concepts implementation that tracks institutional trading behavior through multi-dimensional analysis. This comprehensive indicator combines volume-validated Order Block detection, Fair Value Gap identification with auto-mitigation tracking, dynamic Liquidity Zone mapping, and Break of Structure/Change of Character detection into a unified system.
Unlike basic SMC indicators, SMFI employs a proprietary scoring algorithm that weighs five critical factors: Order Block strength (validated by volume), Fair Value Gap size and recency, proximity to Liquidity Zones, market structure alignment (BOS/CHoCH), and multi-timeframe confluence. This produces a Smart Money Score (0-100) where readings above 70 represent optimal institutional setup conditions.
🚀Points of Innovation
Volume-Validated Order Block Detection – Only displays Order Blocks when formation candle exceeds customizable volume multiplier (default 1.5x average), filtering weak zones and highlighting true institutional accumulation/distribution
Auto-Mitigation Tracking System – Fair Value Gaps and Order Blocks automatically update status when price mitigates them, with visual distinction between active and filled zones preventing trades on dead levels
Proprietary Smart Money Score Algorithm – Combines weighted factors (OB strength 25%, FVG proximity 20%, Liquidity 20%, Structure 20%, MTF 15%) into single 0-100 confidence rating updating in real-time
ATR-Based Adaptive Calculations – All distance measurements use 14-period Average True Range ensuring consistent function across any instrument, timeframe, or volatility regime without manual recalibration
Dynamic Age Filtering – Automatically removes liquidity levels and FVGs older than configurable thresholds preventing chart clutter while maintaining relevant levels
Multi-Timeframe Confluence Integration – Analyzes higher timeframe bias with customizable multipliers (2-10x) and incorporates HTF trend direction into Smart Money Score for institutional alignment
🔧Core Components
Order Block Engine – Detects institutional supply/demand zones using characteristic patterns (down-move-then-strong-up for bullish, up-move-then-strong-down for bearish) with minimum volume threshold validation, tracks mitigation when price closes through zones
Fair Value Gap Scanner – Identifies price imbalances where current candle's low/high leaves gap with two-candle-prior high/low, filters by minimum size percentage, monitors 50% fill for mitigation status
Liquidity Zone Mapper – Uses pivot high/low detection with configurable lookback to mark swing points where stop losses cluster, extends horizontal lines to visualize sweep targets, manages lifecycle through age-based removal
Market Structure Analyzer – Tracks pivot progression to identify trend through higher-highs/higher-lows (bullish) or lower-highs/lower-lows (bearish), detects Break of Structure and Change of Character for trend/reversal confirmation
Scoring Calculation Engine – Evaluates proximity to nearest Order Blocks using ATR-normalized distance, assesses FVG recency and distance, calculates liquidity proximity with age weighting, combines structure bias and MTF trend into smoothed final score
🔥Key Features
Customizable Display Limits – Control maximum Order Blocks (1-10), Liquidity Zones (1-10), and FVG age (10-200 bars) to maintain clean charts focused on most relevant institutional levels
Gradient Strength Visualization – All zones render with transparency-adjustable coloring where stronger/newer zones appear more solid and weaker/older zones fade progressively providing instant visual hierarchy
Educational Label System – Optional labels identify each zone type (Bullish OB, Bearish OB, Bullish FVG, Bearish FVG, BOS) with color-coded text helping traders learn SMC concepts through practical application
Real-Time Smart Money Score Dashboard – Top-right table displays current score (0-100) with color coding (green >70, yellow 30-70, red <30) plus trend arrow for at-a-glance confidence assessment
Comprehensive Alert Suite – Configurable notifications for Order Block formation, Fair Value Gap detection, Break of Structure events, Change of Character signals, and high Smart Money Score readings (>70)
Buy/Sell Signal Integration – Automatically plots triangle markers when Smart Money Score exceeds 70 with aligned market structure and fresh Order Block detection providing clear entry signals
🎨Visualization
Order Block Boxes – Shaded rectangles extend from formation bar spanning high-to-low of institutional candle, bullish zones in green, bearish in red, with customizable transparency (80-98%)
Fair Value Gap Zones – Rectangular areas marking imbalances, active FVGs display in bright colors with adjustable transparency, mitigated FVGs switch to gray preventing trades on filled zones
Liquidity Level Lines – Dashed horizontal lines extend from pivot creation points, swing highs in bearish color (short targets above), swing lows in bullish color (long targets below), opacity decreases with age
Structure Labels – "BOS" labels appear above/below price when Break of Structure confirmed, colored by direction (green bullish, red bearish), positioned at 1% beyond highs/lows for visibility
Educational Info Panel – Bottom-right table explains key terminology (OB, FVG, BOS, CHoCH) and score interpretation (>70 high probability) with semi-transparent background for readability
📖Usage Guidelines
General Settings
Show Order Blocks – Default: On, toggles visibility of institutional supply/demand zones, disable when focusing solely on FVGs or Liquidity
Show Fair Value Gaps – Default: On, controls FVG zone display including active and mitigated imbalances
Show Liquidity Zones – Default: On, manages liquidity line visibility, disable on lower timeframes to reduce clutter
Show Market Structure – Default: On, toggles BOS/CHoCH label display
Show Smart Money Score – Default: On, controls score dashboard visibility
Order Block Settings
OB Lookback Period – Default: 20, Range: 5-100, controls bars scanned for Order Block patterns, lower values detect recent activity, higher values find older blocks
Min Volume Multiplier – Default: 1.5, Range: 1.0-5.0, sets minimum volume threshold as multiple of 20-period average, higher values (2.0+) filter for strongest institutional candles
Max Order Blocks to Display – Default: 3, Range: 1-10, limits simultaneous Order Blocks shown, lower settings (1-3) maintain focus on most recent zones
Fair Value Gap Settings
Min FVG Size (%) – Default: 0.3, Range: 0.1-2.0, defines minimum gap size as percentage of close price, lower values detect micro-imbalances, higher values focus on significant gaps
Max FVG Age (bars) – Default: 50, Range: 10-200, removes FVGs older than specified bars, lower settings (10-30) for scalping, higher (100-200) for swing trading
Show FVG Mitigation – Default: On, displays filled FVGs in gray providing visual history, disable to show only active untouched imbalances
Liquidity Zone Settings
Liquidity Lookback – Default: 50, Range: 20-200, sets pivot detection period for swing highs/lows, lower values (20-50) mark shorter-term liquidity, higher (100-200) identify major swings
Max Liquidity Age (bars) – Default: 100, Range: 20-500, removes liquidity lines older than specified bars, adjust based on timeframe
Liquidity Sensitivity – Default: 0.5, Range: 0.1-1.0, controls pivot detection sensitivity, lower values mark only major swings, higher values identify minor swings
Max Liquidity Zones to Display – Default: 3, Range: 1-10, limits total liquidity levels shown maintaining chart clarity
Market Structure Settings
Pivot Length – Default: 5, Range: 3-15, defines bars to left/right for pivot validation, lower values (3-5) create sensitive structure breaks, higher (10-15) filter for major shifts
Min Structure Move (%) – Default: 1.0, Range: 0.1-5.0, sets minimum percentage move required between pivots to confirm structure change
Multi-Timeframe Settings
Enable MTF Analysis – Default: On, activates higher timeframe trend analysis incorporation into Smart Money Score
Higher Timeframe Multiplier – Default: 4, Range: 2-10, multiplies current timeframe to determine analysis timeframe (4x on 15min = 1hour)
Visual Settings
Bullish Color – Default: Green (#089981), sets color for bullish Order Blocks, FVGs, and structure elements
Bearish Color – Default: Red (#f23645), defines color for bearish elements
Neutral Color – Default: Gray (#787b86), controls color of mitigated zones and neutral elements
Show Educational Labels – Default: On, displays text labels on zones identifying type (OB, FVG, BOS), disable once familiar with patterns
Order Block Transparency – Default: 92, Range: 80-98, controls Order Block box transparency
FVG Transparency – Default: 92, Range: 80-98, sets Fair Value Gap zone transparency independently from Order Blocks
Alert Settings
Alert on Order Block Formation – Default: On, triggers notification when new volume-validated Order Block detected
Alert on FVG Formation – Default: On, sends alert when Fair Value Gap appears enabling quick response to imbalances
Alert on Break of Structure – Default: On, notifies when BOS or CHoCH confirmed
Alert on High Smart Money Score – Default: On, alerts when Smart Money Score crosses above 70 threshold indicating high-probability setup
✅Best Use Cases
Order Block Retest Entries – After Break of Structure, wait for price retrace into fresh bullish Order Block with Smart Money Score >70, enter long on zone reaction targeting next liquidity level
Fair Value Gap Retracement Trading – When price creates FVG during strong move then retraces, enter as price approaches unfilled gap expecting institutional orders to continue trend
Liquidity Sweep Reversals – Monitor price approaching swing high/low liquidity zones against prevailing Smart Money Score trend, after stop hunt sweep watch for rejection into premium Order Block/FVG
Multi-Timeframe Confluence Setups – Identify alignment when current timeframe Order Block coincides with higher timeframe FVG plus MTF analysis showing matching trend bias
Break of Structure Continuations – After BOS confirms trend direction, trade pullbacks to nearest Order Block or FVG in direction of structure break using Smart Money Score >70 as entry filter
Change of Character Reversal Plays – When CHoCH detected indicating potential reversal, look for Smart Money Score pivot with opposing Order Block formation then enter on structure confirmation
⚠️Limitations
Lagging Pivot Calculations – Pivot-based features (Liquidity Zones, Market Structure) require bars to right of pivot for confirmation, meaning these elements identify levels retrospectively with delay equal to lookback period
Whipsaw in Ranging Markets – During choppy conditions, Order Blocks fail frequently and structure breaks produce false signals as Smart Money Score fluctuates without clear institutional bias, best used in trending markets
Volume Data Dependency – Order Block volume validation requires accurate volume data which may be incomplete on Forex pairs or limited in crypto exchange feeds
Subjectivity in Scoring Weights – Proprietary 25-20-20-20-15 weighting reflects general institutional behavior but may not optimize for specific instruments or market regimes, user cannot adjust factor weights
Visual Complexity on Lower Timeframes – Sub-hour timeframes generate excessive zones creating cluttered charts, requires aggressive display limit reduction and higher minimum thresholds
No Fundamental Integration – Indicator analyzes purely technical price action and volume without incorporating economic events, news catalysts, or fundamental shifts that override technical levels
💡What Makes This Unique
Unified SMC Ecosystem – Unlike indicators displaying Order Blocks OR FVGs OR Liquidity separately, SMFI combines all three institutional concepts plus market structure into single cohesive system
Proprietary Confidence Scoring – Rather than manual setup assessment, automated Smart Money Score quantifies probability by weighting five institutional dimensions into actionable 0-100 rating
Volume-Filtered Quality – Eliminates weak Order Blocks forming without institutional volume confirmation, ensuring displayed zones represent genuine accumulation/distribution
Adaptive Lifecycle Management – Automatically updates mitigation status and removes aged zones preventing trades on dead levels through continuous validity and age monitoring
Educational Integration – Built-in tooltips, labeled zones, and reference panel make indicator functional for both learning Smart Money Concepts and executing strategies
🔬How It Works
Order Block Detection – Scans for patterns where strong directional move follows counter-move creating last down-candle before rally (bullish OB) or last up-candle before sell-off (bearish OB), validates formations only when candle exhibits volume exceeding configurable multiple (default 1.5x) of 20-bar average volume
Fair Value Gap Identification – Compares current candle’s high/low against two-candles-prior low/high to detect price imbalances, calculates gap size as percentage of close and filters micro-gaps below minimum threshold (default 0.3%), monitors whether subsequent price fills 50% triggering mitigation status
Liquidity Zone Mapping – Employs pivot detection using configurable lookback (default 50 bars) to identify swing highs/lows where retail stops cluster, extends horizontal reference lines from pivot creation and applies age-based filtering to remove stale zones
Market Structure Analysis – Tracks pivot progression using structure-specific lookback (default 5 bars) to determine trend, confirms uptrend when new pivot high exceeds previous by minimum move percentage, detects Break of Structure when price breaks recent pivot level, flags Change of Character for potential reversals
Multi-Timeframe Confluence – When enabled, requests security data from higher timeframe (current TF × HTF multiplier, default 4x), compares HTF close against HTF 20-period MA to determine bias, contributes ±50 points to score ensuring alignment with institutional positioning on superior timeframe
Smart Money Score Calculation – Evaluates Order Block component via ATR-normalized distance producing max 100-point contribution weighted at 25%, assesses FVG factor through age penalty and distance at 20% weight, calculates Liquidity proximity at 20%, incorporates structure bias (±50-100 points) at 20%, adds MTF component at 15%, applies 3-period smoothing to reduce volatility
Visual Rendering and Lifecycle – Draws Order Block boxes, Fair Value Gap rectangles with color coding (green/red active, gray mitigated), extends liquidity dashed lines with fade-by-age opacity, plots BOS labels, displays Smart Money Score dashboard, continuously updates checking mitigation conditions and removing elements exceeding age/display limits
💡Note:
The Smart Money Flow Index combines multiple Smart Money Concepts into unified institutional order flow analysis. For optimal results, use the Smart Money Score as confluence filter rather than standalone entry signal – scores above 70 indicate high-probability setups but should be combined with risk management, higher timeframe bias, and market regime understanding.
Smart Flow Tracker [The_lurker]
Smart Flow Tracker (SFT): Advanced Order Flow Tracking Indicator
Overview
Smart Flow Tracker (SFT) is an advanced indicator designed for real-time tracking and analysis of order flows. It focuses on detecting institutional patterns, massive orders, and potential reversals through analysis of lower timeframes (Lower Timeframe) or live ticks. It provides deep insights into market behavior using a multi-layered intelligent detection system and a clear visual interface, giving traders a competitive edge.
SFT focuses on trade volumes, directions, and frequencies to uncover unusual activity that may indicate institutional intervention, massive orders, or manipulation attempts (traps).
Indicator Operation Levels
SFT operates on three main levels:
1. Microscopic Monitoring: Tracks every trade at precise timeframes (down to one second), providing visibility not available in standard timeframes.
2. Advanced Statistical Analysis: Calculates averages, deviations, patterns, and anomalies using precise mathematical algorithms.
3. Behavioral Artificial Intelligence: Recognizes behavioral patterns such as hidden institutional accumulation, manipulation attempts and traps, and potential reversal points.
Key Features
SFT features a set of advanced functions to enhance the trader's experience:
1. Intelligent Order Classification System: Classifies orders into six categories based on size and pattern:
- Standard: Normal orders with typical size.
- Significant 💎: Orders larger than average by 1.5 times.
- Major 🔥: Orders larger than average by 2.5 times.
- Massive 🐋: Orders larger than average by 3 times.
- Institutional 🏛️: Consistent patterns indicating institutional activity.
- Reversal 🔄: Large orders indicating direction change.
- Trap ⚠️: Patterns that may be price traps.
2. Institutional Patterns Detection: Tracks sequences of similar-sized orders, detects organized institutional activity, and is customizable (number of trades, variance ratio).
3. Reversals Detection: Compares recent flows with previous ones, detects direction shifts from up to down or vice versa, and operates only on large orders (Major/Massive/Institutional).
4. Traps Detection: Identifies sequences of large orders in one direction, followed by an institutional order in the opposite direction, with early alerts for false moves.
5. Flow Delta Bar: Displays the difference between buy and sell volumes as a percentage for balance, with instant updates per trade.
6. Dynamic Statistics Panel: Displays overall buy and sell ratios with real-time updates and interactive colors.
How It Works and Understanding
SFT relies on logical sequential stages for data processing:
A. Data Collection: Uses the `request.security_lower_tf()` function to extract data from a lower timeframe (like 1S) even on a higher timeframe (like 5D). For each time unit, it calculates:
- Adjusted Volume: Either normal volume or "price-weighted volume" (hlc3 * volume) based on user choice.
- Trade Direction: Compared to previous close (rise → buy, fall → sell).
B. Building Temporary Memory: Maintains a dynamic list (sizeHistory) of the last 100 trade sizes, continuously calculating the moving average (meanSize).
C. Intelligent Classification: Compares each new trade to the average:
- > 1.5 × average → Significant.
- > 2.5 × average → Major.
- > 3.0 × average → Massive.
- Institutional Patterns Check: A certain number of trades (e.g., 5) with a specified variance ratio (±5%) → Institutional.
D. Advanced Detection:
- Reversal: Compares buy/sell totals in two consecutive periods.
- Trap: Sequence of large trades in one direction followed by an opposite institutional trade.
E. Display and Alerts: Results displayed in an automatically updated table, with option to enable alerts for notable events.
Settings (Fully Customizable)
SFT offers extensive options to adapt to the trader's needs:
A. Display Settings:
- Language: English / Arabic.
- Table Position: 9 options (e.g., Top Right, Middle Right, Bottom Left).
- Display Size: Tiny / Small / Normal / Large.
- Max Rows: 10–100.
- Enable Flow Delta Bar: Yes / No.
- Enable Statistics Panel: Yes / No (displays buy/sell % ratio).
B.- Technical Settings:
- Data Source: Lower Timeframe / Live Tick (simulation).
- Timeframe: Optional (e.g., 1S, 5S, 1).
- Calculation Type: Volume / Price Volume.
C. Intelligent Detection System:
- Enable Institutional Patterns Detection.
- Pattern Length: 3–20 trades.
- Allowed Variance Ratio: 1%–20%.
- Massive Orders Detection Factor: 2.0–10.0.
D. Classification Criteria:
- Significant Orders Factor: 1.2–3.0.
- Major Orders Factor: 2.0–5.0.
E. **Advanced Detection**:
- Enable Reversals Detection (with review period).
- Enable Traps Detection (with minimum sequence limit).
F. Alerts System:
- Enable for each type: Massive orders, institutional patterns, reversals, traps, severe imbalance (60%–90%).
G. Color System: Manual customization for each category:
- Standard Buy 🟢: Dark gray green.
- Standard Sell 🔴: Dark gray red.
- Significant Buy 🟢: Medium green.
- Significant Sell 🔴: Medium red.
- Major Orders 🟣: Purple.
- Massive Orders 🟠: Orange.
- Institutional 🟦: Sky blue.
- Reversal 🔵: Blue.
- Trap 🟣: Pink-purple.
Target Audiences
SFT benefits a wide range of traders and investors:
1. Scalpers: Instant detection of large orders, liquidity points identification, avoiding traps in critical moments.
2. Day Traders: Tracking smart money footprint, determining real session direction, early reversals detection.
3. Swing Traders: Confirming trend strength, detecting institutional accumulation/distribution, identifying optimal entry points.
4. Investors: Understanding true market sentiments, avoiding entry at false peaks, identifying real value zones.
⚠️ Disclaimer:
This indicator is for educational and analytical purposes only. It does not constitute financial, investment, or trading advice. Use it in conjunction with your own strategy and risk management. Neither TradingView nor the developer is liable for any financial decisions or losses.
Smart Flow Tracker (SFT): مؤشر متقدم لتتبع تدفقات الأوامر
نظرة عامة
Smart Flow Tracker (SFT) مؤشر متقدم مصمم لتتبع وتحليل تدفقات الأوامر في الوقت الفعلي. يركز على كشف الأنماط المؤسسية، الأوامر الضخمة، والانعكاسات المحتملة من خلال تحليل الأطر الزمنية الأقل (Lower Timeframe) أو التيك الحي. يوفر رؤية عميقة لسلوك السوق باستخدام نظام كشف ذكي متعدد الطبقات وواجهة مرئية واضحة، مما يمنح المتداولين ميزة تنافسية.
يركز SFT على حجم الصفقات، اتجاهها، وتكرارها لكشف النشاط غير العادي الذي قد يشير إلى تدخل مؤسسات، أوامر ضخمة، أو محاولات تلاعب (فخاخ).
مستويات عمل المؤشر
يعمل SFT على ثلاثة مستويات رئيسية:
1. المراقبة المجهرية: يتتبع كل صفقة على مستوى الأطر الزمنية الدقيقة (حتى الثانية الواحدة)، مما يوفر رؤية غير متوفرة في الأطر الزمنية العادية.
2. التحليل الإحصائي المتقدم: يحسب المتوسطات، الانحرافات، الأنماط، والشذوذات باستخدام خوارزميات رياضية دقيقة.
3. الذكاء الاصطناعي السلوكي: يتعرف على أنماط سلوكية مثل التراكم المؤسسي المخفي، محاولات التلاعب والفخاخ، ونقاط الانعكاس المحتملة.
الميزات الرئيسية
يتميز SFT بمجموعة من الوظائف المتقدمة لتحسين تجربة المتداول:
1. نظام تصنيف الأوامر الذكي: يصنف الأوامر إلى ست فئات بناءً على الحجم والنمط:
- Standard (قياسي)**: أوامر عادية بحجم طبيعي.
- Significant 💎 (مهم)**: أوامر أكبر من المتوسط بـ1.5 ضعف.
- Major 🔥 (كبير)**: أوامر أكبر من المتوسط بـ2.5 ضعف.
- Massive 🐋 (ضخم)**: أوامر أكبر من المتوسط بـ3 أضعاف.
- Institutional 🏛️ (مؤسسي)**: أنماط متسقة تشير إلى نشاط مؤسسي.
- Reversal 🔄 (انعكاس)**: أوامر كبيرة تشير إلى تغيير اتجاه.
- Trap ⚠️ (فخ)**: أنماط قد تكون فخاخًا سعرية.
2. كشف الأنماط المؤسسية: يتتبع تسلسل الأوامر المتشابهة في الحجم، يكشف النشاط المؤسسي المنظم، وقابل للتخصيص (عدد الصفقات، نسبة التباين).
3. كشف الانعكاسات: يقارن التدفقات الأخيرة بالسابقة، يكشف تحول الاتجاه من صعود إلى هبوط أو العكس، ويعمل فقط على الأوامر الكبيرة (Major/Massive/Institutional).
4. كشف الفخاخ: يحدد تسلسل أوامر كبيرة في اتجاه واحد، يليها أمر مؤسسي في الاتجاه المعاكس، مع تنبيه مبكر للحركات الكاذبة.
5. شريط دلتا التدفق: يعرض الفرق بين حجم الشراء والبيع كنسبة مئوية للتوازن، مع تحديث فوري لكل صفقة.
6. لوحة إحصائيات ديناميكية: تعرض نسبة الشراء والبيع الإجمالية مع تحديث لحظي وألوان تفاعلية.
طريقة العمل والفهم
يعتمد SFT على مراحل منطقية متسلسلة لمعالجة البيانات:
أ. جمع البيانات: يستخدم دالة `request.security_lower_tf()` لاستخراج بيانات من إطار زمني أدنى (مثل 1S) حتى على إطار زمني أعلى (مثل 5D). لكل وحدة زمنية، يحسب:
- الحجم المعدّل: إما الحجم العادي (volume) أو "الحجم المرجّح بالسعر" (hlc3 * volume) حسب الاختيار.
- اتجاه الصفقة: مقارنة الإغلاق الحالي بالسابق (ارتفاع → شراء، انخفاض → بيع).
ب. بناء الذاكرة المؤقتة: يحتفظ بقائمة ديناميكية (sizeHistory) لآخر 100 حجم صفقة، ويحسب المتوسط المتحرك (meanSize) باستمرار.
ج. التصنيف الذكي: يقارن كل صفقة جديدة بالمتوسط:
- > 1.5 × المتوسط → Significant.
- > 2.5 × المتوسط → Major.
- > 3.0 × المتوسط → Massive.
- فحص الأنماط المؤسسية: عدد معين من الصفقات (مثل 5) بنسبة تباين محددة (±5%) → Institutional.
د. الكشف المتقدم:
- الانعكاس: مقارنة مجموع الشراء/البيع في فترتين متتاليتين.
- الفخ: تسلسل صفقات كبيرة في اتجاه واحد يتبعها صفقة مؤسسية معاكسة.
هـ. العرض والتنبيه: عرض النتائج في جدول محدّث تلقائيًا، مع إمكانية تفعيل تنبيهات للأحداث المميزة.
لإعدادات (قابلة للتخصيص بالكامل)
يوفر SFT خيارات واسعة للتكييف مع احتياجات المتداول:
أ. إعدادات العرض:
- اللغة: English / العربية.
- موقع الجدول: 9 خيارات (مثل Top Right, Middle Right, Bottom Left).
- حجم العرض: Tiny / Small / Normal / Large.
- الحد الأقصى للصفوف: 10–100.
- تفعيل شريط دلتا التدفق: نعم / لا.
- تفعيل لوحة الإحصائيات: نعم / لا (تعرض نسبة الشراء/البيع %).
ب. الإعدادات التقنية:
- مصدر البيانات: Lower Timeframe / Live Tick (محاكاة).
- الإطار الزمني: اختياري (مثل 1S, 5S, 1).
- نوع الحساب: Volume / Price Volume.
ج. نظام الكشف الذكي:
- تفعيل كشف الأنماط المؤسسية.
- طول النمط: 3–20 صفقة.
- نسبة التباين: 1%–20%.
- عامل كشف الأوامر الضخمة: 2.0–10.0.
د. معايير التصنيف:
- عامل الأوامر المهمة: 1.2–3.0.
- عامل الأوامر الكبرى: 2.0–5.0.
هـ. الكشف المتقدم:
- تفعيل كشف الانعكاسات (مع فترة مراجعة).
- تفعيل كشف الفخاخ (مع حد أدنى للتسلسل).
و. نظام التنبيهات:
- تفعيل لكل نوع: أوامر ضخمة، أنماط مؤسسية، انعكاسات، فخاخ، عدم توازن شديد (60%–90%).
ز. نظام الألوان**: تخصيص يدوي لكل فئة:
- شراء قياسي 🟢: أخضر رمادي داكن.
- بيع قياسي 🔴: أحمر رمادي داكن.
- شراء مهم 🟢: أخضر متوسط.
- بيع مهم 🔴: أحمر متوسط.
- أوامر كبرى 🟣: بنفسجي.
- أوامر ضخمة 🟠: برتقالي.
- مؤسسي 🟦: أزرق سماوي.
- انعكاس 🔵: أزرق.
- فخ 🟣: وردي-أرجواني.
الفئات المستهدفة
يستفيد من SFT مجموعة واسعة من المتداولين والمستثمرين:
1. السكالبرز (Scalpers): كشف لحظي للأوامر الكبيرة، تحديد نقاط السيولة، تجنب الفخاخ في اللحظات الحرجة.
2. المتداولون اليوميون (Day Traders): تتبع بصمة الأموال الذكية، تحديد اتجاه الجلسة الحقيقي، كشف الانعكاسات المبكرة.
3. المتداولون المتأرجحون (Swing Traders): تأكيد قوة الاتجاه، كشف التراكم/التوزيع المؤسسي، تحديد نقاط الدخول المثلى.
4. المستثمرون: فهم معنويات السوق الحقيقية، تجنب الدخول في قمم كاذبة، تحديد مناطق القيمة الحقيقية.
⚠️ إخلاء مسؤولية:
هذا المؤشر لأغراض تعليمية وتحليلية فقط. لا يُمثل نصيحة مالية أو استثمارية أو تداولية. استخدمه بالتزامن مع استراتيجيتك الخاصة وإدارة المخاطر. لا يتحمل TradingView ولا المطور مسؤولية أي قرارات مالية أو خسائر.
Machine Learning Moving Average [BackQuant]Machine Learning Moving Average
A powerful tool combining clustering, pseudo-machine learning, and adaptive prediction, enabling traders to understand and react to price behavior across multiple market regimes (Bullish, Neutral, Bearish). This script uses a dynamic clustering approach based on percentile thresholds and calculates an adaptive moving average, ideal for forecasting price movements with enhanced confidence levels.
What is Percentile Clustering?
Percentile clustering is a method that sorts and categorizes data into distinct groups based on its statistical distribution. In this script, the clustering process relies on the percentile values of a composite feature (based on technical indicators like RSI, CCI, ATR, etc.). By identifying key thresholds (lower and upper percentiles), the script assigns each data point (price movement) to a cluster (Bullish, Neutral, or Bearish), based on its proximity to these thresholds.
This approach mimics aspects of machine learning, where we “train” the model on past price behavior to predict future movements. The key difference is that this is not true machine learning; rather, it uses data-driven statistical techniques to "cluster" the market into patterns.
Why Percentile Clustering is Useful
Clustering price data into meaningful patterns (Bullish, Neutral, Bearish) helps traders visualize how price behavior can be grouped over time.
By leveraging past price behavior and technical indicators, percentile clustering adapts dynamically to evolving market conditions.
It helps you understand whether price behavior today aligns with past bullish or bearish trends, improving market context.
Clusters can be used to predict upcoming market conditions by identifying regimes with high confidence, improving entry/exit timing.
What This Script Does
Clustering Based on Percentiles : The script uses historical price data and various technical features to compute a "composite feature" for each bar. This feature is then sorted and clustered based on predefined percentile thresholds (e.g., 10th percentile for lower, 90th percentile for upper).
Cluster-Based Prediction : Once clustered, the script uses a weighted average, cluster momentum, or regime transition model to predict future price behavior over a specified number of bars.
Dynamic Moving Average : The script calculates a machine-learning-inspired moving average (MLMA) based on the current cluster, adjusting its behavior according to the cluster regime (Bullish, Neutral, Bearish).
Adaptive Confidence Levels : Confidence in the predicted return is calculated based on the distance between the current value and the other clusters. The further it is from the next closest cluster, the higher the confidence.
Visual Cluster Mapping : The script visually highlights different clusters on the chart with distinct colors for Bullish, Neutral, and Bearish regimes, and plots the MLMA line.
Prediction Output : It projects the predicted price based on the selected method and shows both predicted price and confidence percentage for each prediction horizon.
Trend Identification : Using the clustering output, the script colors the bars based on the current cluster to reflect whether the market is trending Bullish (green), Bearish (red), or is Neutral (gray).
How Traders Use It
Predicting Price Movements : The script provides traders with an idea of where prices might go based on past market behavior. Traders can use this forecast for short-term and long-term predictions, guiding their trades.
Clustering for Regime Analysis : Traders can identify whether the market is in a Bullish, Neutral, or Bearish regime, using that information to adjust trading strategies.
Adaptive Moving Average for Trend Following : The adaptive moving average can be used as a trend-following indicator, helping traders stay in the market when it’s aligned with the current trend (Bullish or Bearish).
Entry/Exit Strategy : By understanding the current cluster and its associated trend, traders can time entries and exits with higher precision, taking advantage of favorable conditions when the confidence in the predicted price is high.
Confidence for Risk Management : The confidence level associated with the predicted returns allows traders to manage risk better. Higher confidence levels indicate stronger market conditions, which can lead to higher position sizes.
Pseudo Machine Learning Aspect
While the script does not use conventional machine learning models (e.g., neural networks or decision trees), it mimics certain aspects of machine learning in its approach. By using clustering and the dynamic adjustment of a moving average, the model learns from historical data to adjust predictions for future price behavior. The "learning" comes from how the script uses past price data (and technical indicators) to create patterns (clusters) and predict future market movements based on those patterns.
Why This Is Important for Traders
Understanding market regimes helps to adjust trading strategies in a way that adapts to current market conditions.
Forecasting price behavior provides an additional edge, enabling traders to time entries and exits based on predicted price movements.
By leveraging the clustering technique, traders can separate noise from signal, improving the reliability of trading signals.
The combination of clustering and predictive modeling in one tool reduces the complexity for traders, allowing them to focus on actionable insights rather than manual analysis.
How to Interpret the Output
Bullish (Green) Zone : When the price behavior clusters into the Bullish zone, expect upward price movement. The MLMA line will help confirm if the trend remains upward.
Bearish (Red) Zone : When the price behavior clusters into the Bearish zone, expect downward price movement. The MLMA line will assist in tracking any downward trends.
Neutral (Gray) Zone : A neutral market condition signals indecision or range-bound behavior. The MLMA line can help track any potential breakouts or trend reversals.
Predicted Price : The projected price is shown on the chart, based on the cluster's predicted behavior. This provides a useful reference for where the price might move in the near future.
Prediction Confidence : The confidence percentage helps you gauge the reliability of the predicted price. A higher percentage indicates stronger market confidence in the forecasted move.
Tips for Use
Combining with Other Indicators : Use the output of this indicator in combination with your existing strategy (e.g., RSI, MACD, or moving averages) to enhance signal accuracy.
Position Sizing with Confidence : Increase position size when the prediction confidence is high, and decrease size when it’s low, based on the confidence interval.
Regime-Based Strategy : Consider developing a multi-strategy approach where you use this tool for Bullish or Bearish regimes and a separate strategy for Neutral markets.
Optimization : Adjust the lookback period and percentile settings to optimize the clustering algorithm based on your asset’s characteristics.
Conclusion
The Machine Learning Moving Average offers a novel approach to price prediction by leveraging percentile clustering and a dynamically adapting moving average. While not a traditional machine learning model, this tool mimics the adaptive behavior of machine learning by adjusting to evolving market conditions, helping traders predict price movements and identify trends with improved confidence and accuracy.
Mean Reversion Indicator — Buy the (DCA) Dip Signal (unbiased)Description
The Mean Reversion Signal — Buy the Dip (unbiased) indicator is designed to detect high-probability reversion points within Bitcoin’s cyclical market structure. These signals only appear when momentum has either fully reset on the Stochastic RSI (SRSI) or when a positive momentum reversal is beginning to form.
It combines 6H Relative Strength Index (RSI) data with 2-Week Stochastic RSI (SRSI) dynamics to identify exhaustion and early accumulation phases.
Core logic:
A buy signal appears when the 6H RSI closes below 30, indicating local oversold conditions.
The 2W Stochastic RSI confirms momentum alignment when both K & D are below 20 (deep oversold), above 80 (strong ongoing rally), or when K crosses above D (positive reversal).
The indicator is cycle-aware — active only after a defined date (e.g., 2023-01-01) to ensure it aligns with current market structure and avoids noise from pre-cycle conditions.
Additionally, green signals from previous bull cycles (e.g., 2015, 2019, 2020) are also displayed to highlight historically similar accumulation phases, allowing for cross-cycle comparison.
Color zones:
🟩 High probability of a durable new rally
🟧 Moderate probability zone
🔴 Momentum already extended; potential continuation but weaker signal
Recommended combinations:
For a deeper confirmation framework, this signal pairs well with:
- CoinGlass: Derivatives Risk Index Chart (to assess market (de)leveraging and derivatives pressure)
- BTC Futures Sentiment Index (Axel Adler Jr.) — (to monitor directional sentiment shifts)
- CheckonChain: Bitcoin — Short-Term Holder SOPR (to track realized profit-taking activity)
- CheckonChain: Bitcoin — Short-Term Holder MVRV (to evaluate valuation risk relative to cost basis)
Use case:
This tool helps traders identify favorable mean-reversion opportunities while considering broader cycle context and momentum structure.
It is not financial advice — best used alongside macro structure analysis, derivatives positioning, and on-chain behavior for comprehensive decision-making.
Volume Cluster Support and Resistance Levels [QuantAlgo]🟢 Overview
This indicator identifies statistically significant support and resistance levels through volume cluster analysis, isolating price zones characterized by elevated trading activity and institutional participation. By quantifying areas where volume concentration exceeded historical norms, it reveals price levels with demonstrated supply-demand imbalances that exhibit persistent influence on subsequent price action. The methodology is asset-agnostic and timeframe-independent, applicable across equities, cryptocurrencies, forex, and commodities from intraday to weekly intervals.
🟢 Key Features
1. Support and Resistance Levels
The indicator scans historical price data to identify bars where volume exceeds a user-defined threshold multiplier relative to the rolling average. For each qualifying bar, a representative price is calculated using the average of high, low, and close. Proximate price levels within a specified percentage range are then aggregated into discrete clusters using volume-weighted averaging, eliminating redundant signals. Clusters are ranked by cumulative volume to determine statistical significance. Finally, the indicator plots horizontal levels at each cluster price: support levels (green) below current price indicate zones where historical buying pressure exceeded selling pressure, while resistance levels (red) above current price mark zones where sellers historically dominated. These levels represent areas of established liquidity and price discovery, where institutional order flow previously concentrated.
The Touch Count (T) metric quantifies historical price interaction frequency, while Total Volume (TV) measures aggregate trading activity at each level, providing objective criteria for assessing level strength and trade execution decisions.
2. Volume Histogram
A histogram appears below the price chart, displaying relative volume for each bar within the lookback period, with bar height scaled to the maximum volume observed. Green bars represent up-periods (close > open) indicating buying pressure, while red bars show down-periods (close < open) indicating selling pressure. This visualization helps you confirm the validity of support/resistance levels by seeing where volume actually spiked, identify accumulation/distribution patterns, and validate breakouts by checking if they occur on above-average volume.
3. Built-in Alerts
Automated alerts trigger when price crosses below support levels or breaks above resistance levels, allowing you to monitor multiple assets without constant chart-watching.
4. Customizable Color Schemes
The indicator provides four preset color configurations (Classic, Aqua, Cosmic, Custom) optimized for visual clarity across different charting environments. Each scheme maintains consistent color mapping for support and resistance zones across both level lines and volume histogram components. The Custom configuration permits full color specification to accommodate individual charting setups, ensuring optimal visual contrast for extended analysis sessions.
Classic:
Aqua:
Cosmic:
Custom:
🟢 Pro Tips
→ Trade entry optimization: Execute long positions at support levels with high touch counts or upon confirmed resistance breakouts accompanied by above-average volume
→ Risk parameter definition: Position stop-loss orders near identified support/resistance zones with statistical significance to minimize premature exits
→ Breakout validation: Require volume confirmation exceeding historical average when price penetrates resistance to filter false breakouts
→ Level strength assessment: Prioritize levels with higher touch counts and total volume metrics for enhanced probability trade setups
→ Multi-timeframe confluence: Synthesize support/resistance levels across multiple timeframes to identify high-conviction zones where daily support aligns with 4-hour resistance structures
Geometric Price-Time Triangle Calculator═══════════════════════════════════════════════════
GEOMETRIC PRICE-TIME TRIANGLE CALCULATOR
═══════════════════════════════════════════════════
Calculates Point C of a geometric triangle using different rotation angles from any selected price swing. Based on Bradley F. Cowan's Price-Time Vector (PTV) methods from "Four-Dimensional Stock Market Structures and Cycles."
📐 WHAT IT DOES
────────────────────────────────────────────────────
Select two points (A and B) on any swing, choose an angle, and the indicator calculates where Point C would be mathematically. It's just vector rotation applied to price charts.
This shows you where Point C lands in both price AND time based on pure geometry - not a prediction, just a calculation.
🎯 FEATURES
────────────────────────────────────────────────────
✓ 10 Different Angles
• Gann ratios: 18.435° (1x3), 26.565° (1x2), 45° (1x1), 63.435° (2x1), 71.565° (3x1)
• Other angles: 30°, 60°, 90°, 120°, 150°
✓ Visual Triangle
• Adjustable colors and opacity for points A, B, C
• Line styles: Solid, Dashed, Dotted
• Extend lines: None, Left, Right, Both
✓ Crosshair at Point C
• Shows where Point C is located
• Vertical line = bar position
• Horizontal line = price level
✓ Data Table
• Shows all calculations
• Price-to-Bar ratio
• Point C location (price and bars from A/B)
• Toggle on/off
🔧 HOW TO USE
────────────────────────────────────────────────────
1. Pick your swing start date (Point A)
2. Pick your swing end date (Point B) - make sure these dates capture the actual high/low of your swing
3. Choose an angle from the dropdown
4. Look at Point C - that's where the geometry puts it
Different angles = different Point C locations. Whether price actually goes there is up to the market.
📊 THE ANGLES
────────────────────────────────────────────────────
- 18.435° (1x3) - Shallow rotation
- 26.565° (1x2) - Moderate rotation
- 45° (1x1) - Gann's balanced ratio
- 60° - Equilateral triangle (default)
- 63.435° (2x1) - Steeper rotation
- 71.565° (3x1) - Very steep rotation
- 90° - Right angle
- 120°-150° - Obtuse angles
💡 PRACTICAL USE
────────────────────────────────────────────────────
→ See where geometric patterns would complete
→ Test if your market respects certain angles
→ Find where multiple angles converge
→ Compare projected Point C to actual price action
→ Use 90° to see symmetrical price/time relationships
→ Backtest historical swings to see what worked
⚙️ HOW IT WORKS
────────────────────────────────────────────────────
1. Takes your AB swing
2. Calculates the BA vector (reverse direction)
3. Normalizes price and time using Price-to-Bar ratio
4. Rotates the vector by your selected angle
5. Converts back to chart coordinates
Basic trigonometry. That's all it is.
📚 BACKGROUND
────────────────────────────────────────────────────
Based on Bradley F. Cowan's Price-Time Vector (PTV) concept from "Four-Dimensional Stock Market Structures and Cycles" and W.D. Gann's geometric angle analysis. Cowan observed that markets sometimes complete geometric patterns. This tool calculates where those patterns would complete mathematically. Whether price actually respects these geometric relationships is something you need to test yourself.
⚠️ IMPORTANT
────────────────────────────────────────────────────
- This is geometric calculation, not prediction
- Point C shows where the math puts it, not where price will go
- Some angles might work for your market, some won't
- Test it yourself on historical data
- Price-to-Bar Ratio stays constant regardless of angle
- Don't trade based on this alone
- Works on all timeframes and assets
🎨 CUSTOMIZATION
────────────────────────────────────────────────────
- Show/hide triangle
- Individual colors for A, B, C points
- Adjust opacity (0-100)
- Line styles for each triangle side
- Extend lines left/right/both/none
- Show/hide data table
- Crosshair color and width
- Customizable table colors
═══════════════════════════════════════════════════
BUY/SELL CROSS 1 WEEK SKIDD What it does
SRSI prints candle-attached BUY/SELL labels when StochRSI %K crosses %D in either direction—no numeric thresholds. Labels are vertically ATR-adjustable so they’re visible without clutter. A continuous MACD direction line sits above price, turning green when MACD > Signal and red when MACD < Signal.
Why it helps
Keeps entries/exits simple: true crossovers only.
Uses higher-TF StochRSI (weekly by default) to cut noise.
Visual regime filter via the color-changing MACD line.
Labels stick to the candle and move with it—clean on any zoom.
How to use
For swing trading, leave StochRSI on Weekly and enable Only signal on confirmed bar.
Use the MACD line as a directional filter: prefer BUYs when the line is green, prefer SELLs when red.
Adjust Label Vertical Distance (ATR x) so labels clear long wicks and stay readable.
Inputs
StochRSI: RSI Length, Lookback, %K/%D smoothing, Calculation TF.
Confirmation: Only signal on confirmed bar.
Labels: Vertical Distance (ATR x), Size.
MACD: Fast/Slow/Signal, MACD TF, line positioning, vertical distance, width.
Alerts
BUY (StochRSI Cross Up) and SELL (StochRSI Cross Down) included.
Notes
If you switch Only signal on confirmed bar OFF, signals can appear intra-bar and may repaint before close—use with care.
This is not financial advice; test on multiple symbols/timeframes.
Optional “Change log” (for future updates)
v1.0 — Initial public release: candle-attached StochRSI BUY/SELL labels + MACD direction line; vertical ATR spacing; weekly StochRSI default.
MACD Overlay v1 [JopAlgo]Meet the MACD you can trade directly from the chart.
MACD Overlay v1 doesn’t just plot an oscillator somewhere below—
it puts value, momentum, and participation on your candles, and it refuses to fire inside chop.
When a triangle prints, it’s because energy released (expansion), not because the chart looked cute.
What it is:
An execution-ready MACD overlay with phase gating (Expansion-Only), participation gating (Weakness-Lite), and one-click Classic vs VW-MACD Compare—all adaptive, with minimal inputs.
What’s in v1 (feature set)
Overlay ribbon on price: Fast/Slow MACD value rendered as a price-level ribbon with contextual fill and optional candle tint.
Dual value model: Classic MA-MACD (EMA/SMA) and VW-MACD (Rolling VWAP fast/slow).
Compare mode: A/B Classic vs VW-MACD with a VW ghost ribbon.
Weakness-Lite (1-bar, adaptive): Gates/fades low-participation crosses using
RVOL deficit, Effort-vs-Result failure, and over-extension vs value/ATR (Strict adds wick pressure).
Expansion-Only (Impulse/Squeeze): Triangles print only when a cross coincides with a true-range burst and a histogram-slope ignition out of compression.
Signal hygiene: ±1-bar proximity around crosses, slope awareness, 2-bar debounce.
Explainable filtering: Tiny gray dots show crosses that were intentionally filtered (weak and/or no expansion).
How to use:
Use defaults: Mode Classic, Gate by Weakness ON, Expansion-Only ON, Sensitivity Auto.
Read signals fast:
Solid triangle = cross + expansion confirmed (+ not weak if gate is ON).
Faded triangle = cross + expansion but weak participation (visible only when gate is OFF).
Gray dot = there was a cross, but it was filtered (no genuine expansion or weak & gated).
Validate quickly: Flip Compare to check VW-MACD agreement. Classic + VW alignment usually improves confidence.
Why overlay > sub-pane oscillator
You see where the cross occurs: relative to value, local structure, and S/R, right on price.
The ribbon exposes regime shifts; tint hints expansion vs contraction at a glance.
Execution becomes more context-aware and less “signal-in-a-vacuum.”
Signals & visuals
Triangles (solid): MACD crossed Signal and market showed expansion out of compression; if Gate by Weakness is ON, triangle prints only with acceptable participation.
Triangles (faded): Same as above but weak (shown only when you turn the gate OFF).
Gray dots: Crosses that were filtered (no expansion and/or Weakness gate).
Ribbon: Fast vs Slow value (Classic or VW, according to Mode). Fill and candle tint reflect expansion/contraction.
Inputs
Calculation Mode: Classic | VW | Compare
VW uses Rolling VWAP fast/slow.
Compare: Classic is primary; VW shows as a ghost ribbon for A/B checks.
Gate triangles by Weakness: ON/OFF
Uses RVOL, Effort-vs-Result, extension vs value/ATR (Strict adds wick-pressure).
Sensitivity: Off / Auto / Strict (default Auto).
Expansion-Only (Impulse/Squeeze): ON/OFF
Requires compression → release: tight ribbon + flat momentum, then TR/ATR burst with hist slope flip / cross proximity.
Display: Ribbon / Candle Tint / Weakness Markers.
Advanced (optional): Evaluate Weakness only near signals, Channel (k × |MACD|), Style Preset.
No numeric thresholds to tune—all filters self-calibrate from rolling stats.
Best practices
4H crypto: Defaults are strong—Auto, Gate ON, Expansion-Only ON.
Clean trends: If you feel you miss some tidy resumptions, briefly toggle Expansion-Only OFF.
Choppy regimes: Set Sensitivity → Strict to cut more noise without adding lag.
Confirmation: Use Compare; Classic + VW alignment typically yields better follow-through.
Alerts
MACD Signal Cross Up/Down — execution-grade (use Once per bar close).
Weakness-Lite Flag — optional context alert to help audit filtered crosses.
Attribution & License
Attribution: Based on the algorithmic concept of TradingView’s built-in MACD (fast MA – slow MA, signal, histogram).
No original TradingView source code is redistributed; overlay rendering, VW-MACD, Weakness-Lite, Expansion-Only, gating visuals, and UX are new work.
License: MPL-2.0. Educational purposes only—not financial advice.
Mustang Algo - Engulfing Detector🐎 MUSTANG ALGO - ENGULFING DETECTOR
An advanced engulfing candlestick pattern detector with customizable filters for more precise trading signals.
═══════════════════════════════════════
📊 WHAT IS THIS INDICATOR?
The Mustang Algo Engulfing Detector identifies bullish and bearish engulfing patterns with advanced filtering options to reduce false signals and improve trade quality. This indicator helps traders spot high-probability reversal opportunities based on candlestick patterns and trend confirmation.
═══════════════════════════════════════
✨ KEY FEATURES
🔹 Engulfing Pattern Detection
• Bullish Engulfing: Identifies potential bullish reversals
• Bearish Engulfing: Identifies potential bearish reversals
• Real-time signal labels (BUY/SELL)
🔹 Size Filter
• Filter out small, insignificant candles
• Adjustable minimum body size percentage
• Optional filter for the engulfed candle size
• Ensures only strong patterns are detected
🔹 EMA Trend Filter
• Customizable EMA period (default: 200)
• BUY signals only above EMA (uptrend)
• SELL signals only below EMA (downtrend)
• Visual EMA line on chart
• Reduces counter-trend false signals
═══════════════════════════════════════
🎯 HOW TO USE
1. Add the indicator to your chart
2. Adjust the filters according to your trading style
3. Wait for BUY (green) or SELL (red) labels
4. Confirm with your own analysis and risk management
5. Trade in the direction of the signal
⚠️ IMPORTANT: This indicator should be used in conjunction with proper risk management and additional analysis. No indicator is 100% accurate.
═══════════════════════════════════════
⚙️ CUSTOMIZABLE SETTINGS
📏 Size Filter Group:
• Enable/Disable size filtering
• Min Body Size (%): Minimum candle body size to generate signals (0.01% - 10%)
• Check Engulfed Candle Size: Also verify the size of the engulfed candle
• Min Engulfed Body Size (%): Minimum size for the engulfed candle
📈 EMA Filter Group:
• Enable/Disable EMA filtering
• EMA Length: Period for the EMA calculation (default: 200)
• Show EMA on Chart: Display the EMA line
═══════════════════════════════════════
💡 BEST PRACTICES
✅ Use on higher timeframes (4H, Daily) for better reliability
✅ Combine with support/resistance levels
✅ Wait for candle close confirmation before entering
✅ Use proper stop-loss and take-profit levels
✅ Consider market context and overall trend
❌ Don't trade every signal blindly
❌ Don't ignore risk management
❌ Don't use on very low timeframes without additional filters
═══════════════════════════════════════
📈 RECOMMENDED SETTINGS
Conservative Trading:
• Min Body Size: 0.8% - 1.0%
• EMA Filter: Enabled (200 period)
• Check Engulfed Size: Enabled
Aggressive Trading:
• Min Body Size: 0.3% - 0.5%
• EMA Filter: Disabled or lower period (50-100)
• Check Engulfed Size: Disabled
═══════════════════════════════════════
🔒 DISCLAIMER
This indicator is provided for educational and informational purposes only. Past performance is not indicative of future results. Always conduct your own research and use proper risk management. Trading involves substantial risk of loss.
═══════════════════════════════════════
Created by Mustang Algo
Version 1.0
If you find this indicator helpful, please leave a like and comment! 🚀
Is it Time for a Pullback? Check Bars Since MA TestAn old market adage declares that “prices never move in a straight line.” Dips occur even in bullish markets. But how can traders know when prices may be due for a pullback?
Today’s script tries to answer that question by asking how many bars have passed since a stock, index or other symbol has tested a given moving average. Long periods of time without touching a line such as the 50-day simple moving average, for example, could prompt traders to be more patient.
Bars Since MA Test counts how many bars have passed since prices touched or crossed the MA in question. The resulting value is plotted in a simple histogram. Users can set the MA length and type. By default, it uses the 50-day simple moving average (SMA).
The chart above applies Bars Since MA Test to the S&P 500. It shows that the index has gone 129 bars without testing its 50-day SMA. That’s the longest since a 146-bar stretch between July 2006 and February 2007.
Other longer runs include January-August 1995 (156 bars), November 1960-June 1961 (144 bars) and April-November 1958 (158 bars).
Given the small number of comparable readings, could traders suspect the current advance is getting long in the tooth?
TradeStation has, for decades, advanced the trading industry, providing access to stocks, options and futures. If you're born to trade, we could be for you. See our Overview for more.
Past performance, whether actual or indicated by historical tests of strategies, is no guarantee of future performance or success. There is a possibility that you may sustain a loss equal to or greater than your entire investment regardless of which asset class you trade (equities, options or futures); therefore, you should not invest or risk money that you cannot afford to lose. Online trading is not suitable for all investors. View the document titled Characteristics and Risks of Standardized Options at www.TradeStation.com . Before trading any asset class, customers must read the relevant risk disclosure statements on www.TradeStation.com . System access and trade placement and execution may be delayed or fail due to market volatility and volume, quote delays, system and software errors, Internet traffic, outages and other factors.
Securities and futures trading is offered to self-directed customers by TradeStation Securities, Inc., a broker-dealer registered with the Securities and Exchange Commission and a futures commission merchant licensed with the Commodity Futures Trading Commission). TradeStation Securities is a member of the Financial Industry Regulatory Authority, the National Futures Association, and a number of exchanges.
TradeStation Securities, Inc. and TradeStation Technologies, Inc. are each wholly owned subsidiaries of TradeStation Group, Inc., both operating, and providing products and services, under the TradeStation brand and trademark. When applying for, or purchasing, accounts, subscriptions, products and services, it is important that you know which company you will be dealing with. Visit www.TradeStation.com for further important information explaining what this means.
Risk & Position DashboardRisk & Position Dashboard
Overview
The Risk & Position Dashboard is a comprehensive trading tool designed to help traders calculate optimal position sizes, manage risk, and visualize potential profit/loss scenarios before entering trades. This indicator provides real-time calculations for position sizing based on account size, risk percentage, and stop-loss levels, while displaying multiple take-profit targets with customizable risk-reward ratios.
Key Features
Position Sizing & Risk Management:
Automatic position size calculation based on account size and risk percentage
Support for leveraged trading with maximum leverage limits
Fractional shares support for brokers that allow partial share trading
Real-time fee calculation including entry, stop-loss, and take-profit fees
Break-even price calculation including trading fees
Multi-Target Profit Management:
Support for up to 3 take-profit levels with individual portion allocations
Customizable risk-reward ratios for each take-profit target
Visual profit/loss zones displayed as colored boxes on the chart
Individual profit calculations for each take-profit level
Visual Dashboard:
Clean, customizable table display showing all key metrics
Configurable label positioning and styling options
Real-time tracking of whether stop-loss or take-profit levels have been reached
Color-coded visual zones for easy identification of risk and reward areas
Advanced Configuration:
Comprehensive input validation and error handling
Support for different chart timeframes and symbols
Customizable colors, fonts, and display options
Hide/show individual data fields for personalized dashboard views
How to Use
Set Account Parameters: Configure your account size, maximum risk percentage per trade, and trading fees in the "Account Settings" section.
Define Trade Setup: Use the "Entry" time picker to select your entry point on the chart, then input your entry price and stop-loss level.
Configure Take Profits: Set your desired risk-reward ratios and portion allocations for each take-profit level. The script supports 1-3 take-profit targets.
Analyze Results: The dashboard will automatically calculate and display position size, number of shares, potential profits/losses, fees, and break-even levels.
Visual Confirmation: Colored boxes on the chart show profit zones (green) and loss zones (red), with lines extending to current price levels.
Reset Entry and SL:
You can easily reset the entry and stop-loss by clicking the "Reset points..." button from the script's "More" menu.
This is useful if you want to quickly clear your current trade setup and start fresh without manually adjusting the points on the chart.
Calculations
The script performs sophisticated calculations including:
Position size based on risk amount and price difference between entry and stop-loss
Leverage requirements and position amount calculations
Fee-adjusted risk-reward ratios for realistic profit expectations
Break-even price including all trading costs
Individual profit calculations for partial position closures
Detailed Take-Profit Calculation Formula:
The take-profit prices are calculated using the following mathematical formula:
// Core variables:
// risk_amount = account_size * (risk_percentage / 100)
// total_risk_per_share = |entry_price - sl_price| + (entry_price * fee%) + (sl_price * fee%)
// shares = risk_amount / total_risk_per_share
// direction_factor = 1 for long positions, -1 for short positions
// Take-profit calculation:
net_win = total_risk_per_share * shares * RR_ratio
tp_price = (net_win + (direction_factor * entry_price * shares) + (entry_price * fee% * shares)) / (direction_factor * shares - fee% * shares)
Step-by-step example for a long position (based on screenshot):
Account Size: 2,000 USDT, Risk: 2% = 40 USDT
Entry: 102,062.9 USDT, Stop Loss: 102,178.4 USDT, Fee: 0.06%
Risk per share: |102,062.9 - 102,178.4| + (102,062.9 × 0.0006) + (102,178.4 × 0.0006) = 115.5 + 61.24 + 61.31 = 238.05 USDT
Shares: 40 ÷ 238.05 = 0.168 shares (rounded to 0.17 in display)
Position Size: 0.17 × 102,062.9 = 17,350.69 USDT
Position Amount (with 9x leverage): 17,350.69 ÷ 9 = 1,927.85 USDT
For 2:1 RR: Net win = 238.05 × 0.17 × 2 = 80.94 USDT
TP1 price = (80.94 + (1 × 102,062.9 × 0.17) + (102,062.9 × 0.0006 × 0.17)) ÷ (1 × 0.17 - 0.0006 × 0.17) = 101,464.7 USDT
For 3:1 RR: TP2 price = 101,226.7 USDT (following same formula with RR=3)
This ensures that after accounting for all fees, the actual risk-reward ratio matches the specified target ratio.
Risk Management Features
Maximum Trade Amount: Optional setting to limit position size regardless of account size
Leverage Limits: Built-in maximum leverage protection
Fee Integration: All calculations include realistic trading fees for accurate expectations
Validation: Automatic checking that take-profit portions sum to 100%
Historical Tracking: Visual indication when stop-loss or take-profit levels are reached (within last 5000 bars)
Understanding Max Trade Amount - Multiple Simultaneous Trades:
The "Max Trade Amount" feature is designed for traders who want to open multiple positions simultaneously while maintaining proper risk management. Here's how it works:
Key Concept:
- Risk percentage (2%) always applies to your full Account Size
- Max Trade Amount limits the capital allocated per individual trade
- This allows multiple trades with full risk on each trade
Example from Screenshot:
Account Size: 2,000 USDT
Max Trade Amount: 500 USDT
Risk per Trade: 2% × 2,000 = 40 USDT per trade
Stop Loss Distance: 0.11% from entry
Result: Position Size = 17,350.69 USDT with 35x leverage
Total Risk (including fees): 40.46 USDT
Multiple Trades Strategy:
With this setup, you can open:
Trade 1: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 2: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 3: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 4: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Total Portfolio Exposure:
- 4 simultaneous trades = 4 × 495.73 = 1,982.92 USDT position amount
- Total risk exposure = 4 × 40 = 160 USDT (8% of account)
Pump & Dump Detector v6Overview:
The Pump & Dump Detector v6 is a powerful TradingView indicator designed to identify rapid bullish (pump) or bearish (dump) price movements in real time. By combining Rate of Change (ROC), candle volatility, and volume analysis, this indicator highlights extreme market moves that could indicate momentum spikes, retail-driven activity, or potential manipulations.
Key Features:
ROC-Based Detection: Detects strong upward or downward price momentum over a configurable period.
Volume Confirmation: Filters signals based on volume exceeding a simple moving average, reducing false alerts.
Customizable Candle Filters: Ensures signals are triggered only when the candle shows meaningful movement.
Visual Alerts: Displays clear green (pump) and red (dump) markers on the chart with customizable size.
Real-Time Alerts: Sends instant notifications when pump or dump conditions are met, once per bar.
User-Friendly Inputs: Adjust ROC length, thresholds, minimum candle move, and volume MA length to fit your trading style.
Community-Oriented: As a trader and software professional, I noticed that most pump/dump indicators are restricted access. I developed this indicator to be free for all, helping the trading community.
How to Use:
Green triangle below the bar → Pump detected; consider bullish setups.
Red triangle above the bar → Dump detected; consider bearish setups.
Use in conjunction with other technical analysis tools for confirmation.
Alerts can be used for automated notifications or trading strategies.
Why It’s Useful:
This indicator saves time and enhances decision-making by spotting extreme price moves early, giving traders an edge in volatile markets. Ideal for intraday, swing, and crypto traders looking to capitalize on sudden momentum shifts.
Ultimate Sclaping IndicatorOverview
The Confluence Signal Indicator is a precision-built scalping tool designed to identify high-probability reversal points in the market.
It combines three core technical elements:
Trend
Mean reversion
Momentum
into a single, efficient system.
By filtering out weak RSI signals and focusing only on setups that align with trend direction and recent momentum shifts, this indicator delivers cleaner and more accurate short-term trade signals.
Core Components
200-Period Moving Average (MA200, 5-Minute Timeframe)
The MA200 is always calculated from the 5-minute chart, regardless of your current timeframe. It defines the macro trend direction and ensures that all trades align with the prevailing momentum.
Session VWAP (Volume-Weighted Average Price)
The VWAP tracks the real-time average price weighted by volume for the current trading session. It acts as a dynamic mean-reversion level and helps identify key areas of institutional activity and short-term balance.
RSI (Relative Strength Index)
The indicator uses a standard 14-period RSI to detect overbought and oversold market conditions.
A “recency filter” is added to ensure signals only appear when RSI has recently transitioned from strength to weakness or vice versa, reducing false signals in trending markets.
Signal Logic
Bullish Signal (Green Arrow)
A bullish reversal signal is plotted below a candle when:
Price is above both the 5-minute MA200 and the Session VWAP.
RSI is oversold (below 30).
The last time RSI was above 50 occurred within the last 10 candles before going oversold.
This ensures that the dip is a fresh pullback within an uptrend, not a prolonged oversold condition.
Bearish Signal (Red Arrow)
A bearish reversal signal is plotted above a candle when:
Price is below both the 5-minute MA200 and the Session VWAP.
RSI is overbought (above 70).
The last time RSI was below 50 occurred within the last 10 candles before going overbought.
This ensures that the overbought reading follows a recent move from weakness, identifying potential short entries in a downtrend.
Recommended Usage
This is a scalping-focused indicator, intended for use on timeframes of 5 minutes or lower. Therefore I would highly recommend to use it on Equity futures trading, such as NQ!, ES!, GC! and so on.
It performs best when combined with additional tools such as support and resistance zones, order blocks, or liquidity levels for context.
Avoid counter-trend signals unless confirmed by price structure or volume behavior.
Volume Delta & Divergence (VDD) by CoryP1990 – Quant ToolkitVolume Delta & Divergence (VDD) visualizes directional order flow by tracking session-aware Cumulative Volume Delta (CVD) and highlighting structural mismatches between price pivots and CVD. It’s designed to catch persistent buying/selling pressure and to flag divergences where price moves without supporting order flow.
How it works
Per-bar delta: classify ticks as uptick or downtick using price change inside each bar; compute delta = uptickVol − downtickVol.
Cumulative Delta (CVD): sum delta across the session (optional continuous mode available).
Smooth: apply an EMA to the CVD (CVD-EMA) to reduce noise and reveal structural shifts.
Divergence detection: detect price pivots (left/right = X bars); sample the CVD-EMA at the exact pivot bars and compare the last two price pivots vs the corresponding CVD-EMA values.
Bear divergence: price makes a higher high while CVD-EMA makes a lower high → fading buy pressure at the top.
Bull divergence: price makes a lower low while CVD-EMA makes a higher low → improving buying pressure into the lows.
Markers: non-repainting pivot confirmation requirement (markers appear only after pivots are confirmed) and markers are placed on the actual pivot bar for clarity.
Visuals / legend
Teal line: CVD-EMA (smoothed cumulative delta). Rising → net buying pressure; falling → net selling pressure.
Red triangle (above): Bear divergence - price HH vs CVD LH.
Green triangle (below): Bull divergence - price LL vs CVD HL.
No background tint - VDD is a structural order flow tool (markers + CVD line only). Use the VWMA / trend overlays to provide directional context.
Use cases
Detect hidden exhaustion at highs (fade setups) and hidden accumulation at lows (bounce setups).
Confirm or invalidate momentum moves: price rising but CVD falling warns the move lacks order flow support.
Spot campaign-style pressure across a session (session reset) versus multi-day campaigns (disable reset).
Combine with VWMA(50) or higher-TF alignment to filter signals and increase quality.
Defaults
CVD EMA length = 34
Pivot left/right = 5
Reset CVD at session start = ON (recommended for intraday)
Show raw CVD = OFF
Marker size = small (use normal for screenshots)
Example — META (5m, 5-day view)
The 5-day time range 5-minute interval on META shows the pattern VDD is built for: a midday bear divergence (price ticks to a marginal high while the CVD-EMA flattens and then rolls lower) that precedes a multi-hour drift lower, and later bull divergences near intraday lows where the CVD-EMA prints higher lows as price prints lower lows, followed by constructive bounces. With resetSession=ON you can see these flows replay across sessions and judge whether a divergence is isolated or repeated (higher-quality).
Practical tips
Default demo: 5-minute chart on liquid names (META, AAPL, SPY) - lenEMA=34, pivot=5, resetSession=ON.
Scalp: 1m with shorter EMA (e.g., 13) and pivot=3.
Swing / campaign: 4H/Daily with resetSession=OFF and longer EMA (e.g., 89).
Filter with VWMA(50) and require above-average volume at the pivot region for higher-probability signals.
Use alerts (script exposes bear/bull alertconditions) to monitor divergences in real time.
Limitations / disclaimers
Markers are confirmation-based (non-repainting), i.e. they appear after the pivot completes, not as a predictive tick.
No single divergence equals a trade; combine with trend, volume, and risk management.
Part of the Quant Toolkit — transparent, open-source indicators for modern quantitative analysis. Built by CoryP1990.
Fusion Indicator FI-1 • All-in-OneAgain I asked to my dear AI friend to create 1 indicator rules them all.
OSOM Hulk+OSOM Hulk+ is a multifaceted TradingView indicator that integrates volume-weighted bands for trend identification (with customizable visuals like clouds or lines), HMA-based trend detection and duration forecasting (displaying real/probable lengths), ATR trailing stop buy/sell signals with strong variants, re-entry/take-profit logic, and a dynamic table showing buy/sell volume ratios and percentages, plus alerts for trading actions.
Intra day BB Trap Indicator with buy and sell signalThis script plots CPR and the BB channel and provides buy and sell signals.
All the plots are customizable. better to use it within an hour time frame.
Buy signal when the price closes above CPR support and comes inside bb channel on the lower bb side.
Sell signal when the price closes below CPR Resistance and comes inside bb channel on the upper bb side.
LevelsLevels is a powerful technical analysis tool that automatically identifies and displays key support and resistance levels on the chart. The indicator analyzes historical price data, detecting significant price levels where multiple reversals or price stops have occurred.
How the Indicator Works?
1. Identification of Reversal Points:
- The indicator tracks price extremes using an algorithm to identify local highs and lows
- A reversal point is recorded when:
- Uptrend: price reaches a new low for the last 10 bars
- Downtrend: price reaches a new high for the last 10 bars
2. Level Grouping:
- All found reversal points are analyzed and grouped into key levels
- Levels are combined if they fall within the specified percentage tolerance
3. Filtering Significant Levels:
- Only levels that have been tested the minimum number of times (set in settings) are preserved
- This ensures only statistically significant levels are displayed
How to Use the Indicator?
Trading Scenarios:
1. Bounce from Level:
- When price approaches an identified level, a bounce can be expected
- Opening positions on the bounce with protective stop-loss beyond the level
2. Level Breakout:
- Breaking through a key level may signal trend continuation
- Support level becomes resistance and vice versa
3. Consolidation near Level:
- Prolonged price presence near a level indicates its significance
- Strong movement can be expected after exiting consolidation
Advantages:
- Automatic level identification eliminates subjectivity
- Sensitivity customization for different timeframes and instruments
- Visual simplicity - only significant levels
Indicator Settings
Main Parameters:
- Show Key Levels - enable/disable level display
- Level Tolerance (%) - percentage tolerance for level grouping
- Smaller values: more levels, more precise
- Larger values: fewer levels, more significant
- Minimum Touches - minimum number of touches to form a level
Visual Settings:
- Level Color - level display color
- Level Style - line style (solid, dashed, dotted)
Limitations
- Levels are built only on available historical data
- Does not account for trading volumes
- Parameter adjustment may be required during high volatility periods
The indicator is particularly effective when combined with other analysis tools for signal confirmation.
Mac Sessions High And Low v.1This indicator is mainly for session highs and lows
Just a easy way to see if price sweeps a sessions high or low
