Polaris VWAP Mesh [JOAT]Polaris VWAP Mesh
Polaris VWAP Mesh tracks four anchored VWAPs simultaneously — Session, Swing-High pivot, Swing-Low pivot, and Previous-Day-Open — and detects pairwise confluence whenever two or more of them are within an ATR-scaled proximity of each other. Each VWAP carries a plus-or-minus 1-sigma deviation band. Confluence zones become full-chart-width persistent bands. A multi-anchor bias score counts how many VWAPs price is currently above.
What makes it different
Most VWAP scripts plot a single anchor (session or daily). Polaris simultaneously runs four independent anchored-VWAP engines and surfaces their interactions as confluence zones.
Confluence detection uses an ATR-scaled proximity threshold rather than a fixed percentage, so it adapts to the instrument's volatility automatically.
A multi-anchor bias counter aggregates the four VWAPs into a single 0-to-4 score. Full-chart-width tints apply when three or more VWAPs are above (or below) the close.
Swing-anchored VWAPs reset at confirmed pivot points and start fresh from the moment of pivot confirmation (forward-only, non-repainting). The Previous-Day-Open VWAP is anchored to the open of the prior daily bar so it captures yesterday's reference.
A pairwise distance matrix is displayed in plain text at the right edge — six pair distances, with the two tightest pairs highlighted.
How it works
An anchored VWAP function maintains three cumulators per anchor — price-times-volume, volume, and price-squared-times-volume — to deliver both the VWAP and its rolling standard deviation since the anchor.
Anchor reset conditions: Session start of the user-defined session window. Swing-High on confirmed ta.pivothigh. Swing-Low on confirmed ta.pivotlow. Previous-Day-Open on ta.change(time("D")), capturing the open of the new day, then locking after a day passes.
Pairwise distance check: for each of the six possible pairs, if the absolute distance between VWAPs is less than proximityThreshATR times ATR(14), an active confluence is flagged. The mid-price between the two VWAPs becomes the confluence level.
Multi-anchor bias counts how many of the four VWAPs the close is above.
Reading the chart
Four VWAP lines, each in its own color (session blue, swing-high red, swing-low mint, prev-day-open purple, all user-configurable).
Plus-or-minus 1-sigma deviation band shading per VWAP.
Full-chart-width confluence zones (persistent bordered boxes) at each active confluence level, with right-edge labels naming the contributing pair.
Anchor reset markers: small vertical lines per anchor at the bar of reset (capped at 20 per anchor type).
A multi-anchor bull / bear bgcolor tint (very faint) when three or more VWAPs are on one side of the close.
Iridescent candle recolor by bull-count.
Right-edge VWAP labels with plus-or-minus sigma deviation tags.
Pairwise distance matrix label cluster.
Anchor-age label cluster.
Bias-flip timeline labels and VWAP-cross event labels.
Signals
Bull / bear VWAP cross (any anchor)
Session VWAP bull / bear cross (dedicated alerts)
Previous-Day-Open VWAP bull / bear cross (dedicated alerts)
Confluence touch (price entered an active confluence zone)
Multi-anchor bull / bear bias activation
All gated on barstate.isconfirmed or barstate.ishistory. No future references.
Inputs
Anchors : session window string, swing pivot length.
Bands : standard deviation multiplier, band shading toggle.
Confluence : proximity threshold in ATR units, confluence zones toggle.
Visuals : bullish / bearish colors, per-anchor color overrides, per-anchor visibility toggles, candles, labels.
Dashboard : position, size.
How traders use this
Confluence trading : confluence zones are price magnets. Reactions to them (touches with rejections) are tradable. Clean breaks through with volume can be trend signals.
Multi-anchor bias : when three or four of the four VWAPs are on the same side of price, the trend is well supported across multiple anchors. Counter-trend trades in this regime are lower probability.
VWAP rotation : the previous-day-open VWAP is a frequently respected institutional reference. Crosses of it often coincide with bias shifts.
Plus-or-minus 1-sigma bands : extensions to plus-or-minus 1 sigma from a fast-moving anchor often coincide with short-term mean-reversion zones.
Limitations
Swing-anchored VWAPs begin tracking only after pivot confirmation, so they lack history before that pivot was confirmed. This is by design (non-repainting), not a bug.
The session VWAP requires the user to set a session window matching the instrument's primary trading window.
The pairwise confluence test is O(1) per bar (six pairs). Confluence zones extend across the chart and use persistent box objects. They are capped at six active zones (the maximum number of pair combinations).
Confluence is a price-coincidence test, not a flow-direction test. Use other tools to gauge directional bias once confluence is identified.
Compatibility
Pine Script v6 open-source indicator (overlay). Any symbol with volume data. Designed for sessions in America/New_York by default. Change the session window for other markets. No request.security calls.
Defaults
0930-1600 EST session window, 10-bar pivot length, 0.5x ATR proximity threshold, mint / red brand colors plus blue / red / mint / purple anchor accents, top-right medium dashboard.
Indicator
Confluence Ledger [JOAT]Confluence Ledger
Introduction
The Confluence Ledger is an advanced open-source multi-timeframe confluence scoring engine that evaluates eight independent analytical dimensions across five configurable timeframes, producing a unified directional bias score from 0 to 100. It answers the question every trader asks: "Do the timeframes agree, and how strongly?" Rather than checking multiple indicators on multiple charts, this single tool synthesizes trend alignment, momentum phase, volatility state, market structure, volume conviction, RSI regime, VWAP bias, and ATR expansion into one actionable number.
The indicator overlays on the price chart with gradient-colored candles, confluence pressure zones, regime transition lines, divergence detection boxes, and institutional confluence signals - all backed by a compact 12-row dashboard that displays every metric in real-time.
Why This Indicator Exists
Multi-timeframe analysis is widely recognized as essential for high-probability trading, but executing it manually is tedious and error-prone. A trader might check the daily trend, the 4H momentum, the 1H structure, and the 15m entry — but doing this across eight different analytical dimensions is impractical without automation.
The Confluence Ledger automates this entire process by:
Scoring eight distinct analytical dimensions on each of five timeframes, producing 40 individual data points per bar
Weighting higher timeframes more heavily (Daily gets 2x the weight of the 5-minute chart), reflecting the institutional reality that higher timeframe trends dominate
Mapping the weighted aggregate to a 0-100 scale where 50 is perfectly neutral, above 60 is bullish, and below 40 is bearish
Adding institutional features that analyze the score itself: pressure zones where extreme confluence persisted, regime transitions where the bias flipped, and divergences between price and the confluence score
The Eight Scoring Dimensions
Each dimension returns a score from -1 (maximum bearish) to +1 (maximum bullish). Here is what each measures and why it matters:
1. Trend Alignment
Combines EMA slope direction with price position relative to the adaptive moving average. If price is above a rising EMA, the trend score is +1. If price is below a falling EMA, it is -1. Mixed conditions produce intermediate scores. This captures the most fundamental question: is the trend up or down?
2. Momentum Phase
A composite of three normalized oscillators — Bollinger %B, CCI, and ROC. Each is scored independently and averaged. This measures whether momentum is bullish, bearish, or neutral, using three different mathematical approaches to reduce the chance of a single oscillator giving a misleading signal.
3. Volatility State
Measures Bollinger Band width relative to its 50-bar average. Expanding volatility scores positive (in the direction of price), compressing volatility scores near zero. This dimension captures whether the market is in expansion (trending) or compression (range-bound).
4. Structure Bias
Uses an oscillator-based swing detection method to track whether the market is making higher highs/higher lows (bullish structure, score +1) or lower highs/lower lows (bearish structure, score -1). This is the structural backbone of Smart Money analysis.
5. Volume Conviction
Calculates current volume relative to the 20-bar average and weights it by candle direction. A bullish candle on 2x average volume scores strongly positive. A bearish candle on low volume scores weakly negative. This measures whether volume confirms the directional move.
6. RSI Regime
RSI position relative to 50 provides the base score, with additional weight for extreme readings (above 70 or below 30). This captures overbought/oversold conditions and the general momentum regime.
7. VWAP Bias
Price distance from VWAP normalized by ATR. When price is significantly above VWAP, institutional flow is net bullish. Below VWAP, net bearish. The ATR normalization ensures the score adapts to the instrument's volatility.
8. ATR Expansion
The rate of change of ATR itself, weighted by candle direction. When ATR is expanding in the direction of price, it confirms the move has volatility behind it. Contracting ATR suggests the move is losing energy.
Multi-Timeframe Aggregation
All eight dimensions are calculated on each of five timeframes (default: 5m, 15m, 1H, 4H, Daily) using request.security(). The per-timeframe scores are then weighted:
TF1 (5m): weight 1.0
TF2 (15m): weight 1.2
TF3 (1H): weight 1.5
TF4 (4H): weight 1.8
TF5 (Daily): weight 2.0
This weighting reflects the institutional principle that higher timeframe trends are more significant. A strong daily bias overrides conflicting 5-minute noise.
The weighted aggregate is mapped from to :
float confluence_score = math.round((raw_agg + 1.0) / 2.0 * 100)
Score interpretation:
80-100: EXTREME LONG — near-unanimous multi-TF bullish agreement
70-79: STRONG LONG — clear bullish bias across most timeframes
60-69: LEAN LONG — moderate bullish tilt
41-59: NEUTRAL — no clear directional consensus
31-40: LEAN SHORT — moderate bearish tilt
21-30: STRONG SHORT — clear bearish bias
0-20: EXTREME SHORT — near-unanimous bearish agreement
Institutional Analytics Engine
Beyond the core score, the indicator calculates several advanced metrics:
TF Agreement: Counts how many of the five timeframes are bullish vs bearish. When 4+ timeframes agree, a "Full Alignment" signal fires — these are the highest-conviction directional setups.
Score Velocity: The rate of change of the confluence score itself. "ACCEL UP" means the score is rising and accelerating. "FALLING" means directional conviction is weakening. This is the first derivative of confluence — it tells you whether agreement is building or fading.
Conviction Meter: Measures how tightly aligned the five timeframe scores are using standard deviation. Low variance (high conviction) means all timeframes agree closely. High variance (low conviction) means timeframes are giving conflicting signals.
Cross-TF Momentum Divergence: Compares the average of lower timeframes (TF1+TF2) against higher timeframes (TF4+TF5). When lower TFs are leading (diverging bullish while higher TFs lag), it can signal an early trend change. When upper TFs are leading, the higher timeframe trend is asserting dominance.
HTF Dominance: Identifies which higher timeframe is currently driving the overall bias the most. This tells you whether the daily, 4H, or 1H is the primary force behind the score.
Dimension Consensus: Averages each of the eight dimensions across all five timeframes to find which dimension is the strongest driver. If "TREND" is the strongest dimension, the trend alignment across timeframes is the primary force. If "VOLUME" is strongest, volume conviction is driving the bias.
Chart Features
1. Confluence Pressure Zones
When the confluence score stays extreme (above 70 or below 30) for a configurable minimum number of bars (default 5), the indicator draws a dashed box marking the price range during that period. These "pressure zones" represent areas where sustained multi-timeframe agreement created institutional accumulation or distribution. They often act as future support/resistance.
2. Regime Transition Lines
When the confluence score crosses from bullish to bearish territory (or vice versa), a labeled dashed line is drawn at the transition price. These lines show the exact price where the multi-timeframe consensus shifted — they act as institutional support/resistance levels that are derived from confluence rather than price structure.
3. Confluence Divergence Detector
When price makes a new 20-bar high but the confluence score is declining (or price makes a new low but the score is rising), the indicator marks a confluence divergence. This is a unique concept — it detects divergence between a multi-timeframe composite score and price action, which is fundamentally different from single-oscillator divergence.
4. Institutional Confluence Signals
Multi-condition filtered signals that fire when confluence score exceeds thresholds, velocity confirms, and a cooldown period has elapsed. These are the highest-conviction signals the indicator produces.
5. Gradient Confluence Candles
Candles are colored on a gradient from the bearish color (score near 0) to the bullish color (score near 100). This creates an instant visual read of confluence strength on every candle.
Input Parameters
Timeframes:
TF 1 through TF 5 (defaults: 5m, 15m, 60m, 240m, Daily) — all configurable
Scoring Parameters:
MA Length (27), ATR Length (14), BB Length (20), BB Mult (2.0)
CCI Length (23), ROC Length (50), RSI Length (14), Swing Length (10)
Institutional Features:
Gradient Confluence Candles, Confluence Pressure Zones, Regime Transition Lines
Confluence Divergence Boxes, Institutional Confluence Signals
Signal Cooldown (20 bars), Pressure Zone Min Bars (5)
How to Use This Indicator
Step 1: Read the Score
The confluence score (0-100) is your primary directional gauge. Above 60 = bullish bias. Below 40 = bearish bias. 40-60 = no clear edge — consider staying flat or reducing position size.
Step 2: Check TF Agreement
The dashboard shows how many timeframes agree. 4/5 or 5/5 agreement in one direction is a high-conviction setup. 2B/3S or similar splits suggest conflicting signals — proceed with caution.
Step 3: Monitor Score Velocity
A score of 72 that is "ACCEL UP" is more bullish than a score of 72 that is "FALLING." Velocity tells you whether the consensus is strengthening or weakening.
Step 4: Use Pressure Zones as S/R
When price returns to a previous pressure zone, expect a reaction. These zones represent areas where sustained multi-timeframe agreement existed — institutional memory.
Step 5: Watch for Confluence Divergences
If price is making new highs but the confluence score is declining, the multi-timeframe consensus is not confirming the move. This is a warning sign that the advance may stall or reverse.
Step 6: Trade Regime Transitions
When the score crosses from bearish to bullish territory (or vice versa), the regime transition line marks the pivot price. These transitions often produce sustained directional moves.
Limitations
The indicator uses request.security() to fetch data from five timeframes. On very low timeframes (1m), the higher timeframe data updates less frequently, which can create lag in the score.
The weighting system (higher TFs get more weight) is a design choice that works well for trend-following. Scalpers who trade against the higher timeframe trend may find the score misleading for their style.
Confluence score is a composite of mathematical calculations. A score of 80 does not mean "80% chance of going up" — it means 80% of the weighted analytical dimensions agree on a bullish reading.
The indicator evaluates current conditions, not future ones. A high confluence score can reverse quickly on unexpected news or institutional repositioning.
VWAP calculations may behave differently on instruments without continuous trading sessions.
Past confluence patterns do not guarantee future confluence patterns.
Originality Statement
This indicator is original in its systematic multi-dimensional, multi-timeframe confluence approach. While individual components (EMA trend, RSI, VWAP, etc.) are established concepts, this indicator is justified because:
It evaluates eight independent analytical dimensions simultaneously — not just trend and momentum, but also volatility state, market structure, volume conviction, RSI regime, VWAP bias, and ATR expansion
Each dimension is scored on five timeframes with weighted aggregation, producing 40 data points synthesized into a single actionable score
The Confluence Pressure Zone concept — marking areas where extreme multi-TF agreement persisted — creates institutional S/R levels derived from confluence rather than price structure
Regime Transition Lines mark the exact price where multi-timeframe consensus shifted, providing a unique form of dynamic support/resistance
Confluence Divergence Detection compares a multi-TF composite score against price action — fundamentally different from single-oscillator divergence
Score Velocity, Conviction Meter, Cross-TF Momentum Divergence, HTF Dominance, and Dimension Consensus provide meta-analysis of the confluence score itself
The integration of all these features with gradient candle coloring and a comprehensive dashboard creates a unified confluence analysis system not available in any single existing indicator
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss.
The confluence score is a mathematical composite of current market conditions across multiple timeframes. It does not predict future price movement. High confluence does not guarantee profitable trades. Market conditions can change rapidly, and past confluence patterns do not guarantee future patterns.
Always use proper risk management. Never risk more than you can afford to lose. The author is not responsible for any losses incurred from using this indicator.
-Made with passion by officialjackofalltrades
Indicator
Singularity Convergence Protocol [JOAT]Singularity Convergence Protocol
Introduction
The Singularity Convergence Protocol is an advanced open-source multi-system confluence strategy that combines eight distinct analytical methodologies into a unified trading system. This strategy integrates momentum analysis, Smart Money Concepts, velocity waves, liquidity tracking, trend detection, divergence analysis, volatility measurement, and institutional flow into a comprehensive decision-making engine that generates high-probability trading signals through systematic confluence scoring.
Unlike single-indicator strategies, the Singularity Convergence Protocol provides institutional-grade signal generation through multi-dimensional analysis, weighted confluence scoring, and adaptive risk management. The strategy is designed for traders who understand that the highest probability setups occur when multiple independent analytical systems align simultaneously, creating a "singularity" of confluence.
Why This Strategy Exists
This strategy addresses the critical challenge of signal reliability in algorithmic trading. By requiring confluence across multiple independent systems, it dramatically reduces false signals while identifying the highest probability setups. The strategy reveals:
System 1 - Momentum Analysis: Quantum Flux Oscillator methodology combining VFI, Laguerre RSI, Fisher Transform, TSI, MFI, OBV, and A/D
System 2 - Structure Detection: Smart Money Concepts including Order Blocks, Fair Value Gaps, Liquidity Levels, and Market Structure
System 3 - Velocity Waves: Multi-layer momentum spectrum with five EMA layers and ALMA enhancement
System 4 - Liquidity Tracking: Pivot-based liquidity detection with sweep confirmation
System 5 - Trend Analysis: Hull MA, SuperTrend, ADX, and moving average alignment
System 6 - Divergence Detection: Multi-oscillator divergence with RSI, MACD, TSI, and Stochastic
System 7 - Volatility Analysis: ATR, Bollinger Bands, Keltner Channels, Historical Volatility, and Squeeze detection
System 8 - Institutional Flow: CMF, MFI, OBV, VWAP, and A/D Line integration
Core Strategy Logic
1. Eight Independent Analytical Systems
Each system operates independently and generates binary signals (bullish/bearish):
Momentum System:
Calculates composite momentum from seven components
Generates bullish signal when momentum > 0 and rising
Generates bearish signal when momentum < 0 and falling
Score: +1 for bullish, -1 for bearish, 0 for neutral
Structure System:
Detects order blocks, FVGs, and market structure
Bullish when OB/FVG active + bullish structure + discount zone
Bearish when OB/FVG active + bearish structure + premium zone
Score: +1 for bullish, -1 for bearish, 0 for neutral
Velocity Wave System:
Analyzes five momentum layers with ALMA enhancement
Bullish when Basis 1 > Basis 2 and rising with spread > 5
Bearish when Basis 1 < Basis 2 and falling with spread < -5
Score: +1 for bullish, -1 for bearish, 0 for neutral
Liquidity System:
Tracks liquidity sweeps with volume confirmation
Bullish when SSL swept with volume surge
Bearish when BSL swept with volume surge
Score: +1 for bullish, -1 for bearish, 0 for neutral
Trend System:
Combines Hull MA, SuperTrend, ADX, and MA alignment
Bullish when Hull rising + SuperTrend bullish + ADX > 20 + MA alignment
Bearish when Hull falling + SuperTrend bearish + ADX > 20 + MA alignment
Score: +1 for bullish, -1 for bearish, 0 for neutral
Divergence System:
Detects divergences across RSI, MACD, TSI, and Stochastic
Bullish when regular bullish divergence with 2+ oscillator confluence
Bearish when regular bearish divergence with 2+ oscillator confluence
Score: +1 for bullish, -1 for bearish, 0 for neutral
Volatility System:
Measures volatility through ATR, BB Width, KC, HV, and Squeeze
Bullish when squeeze breakout upward with low volatility index
Bearish when squeeze breakout downward with low volatility index
Score: +1 for bullish, -1 for bearish, 0 for neutral
Institutional Flow System:
Tracks institutional positioning through CMF, MFI, OBV, VWAP, A/D
Bullish when flow index > 10 with CMF > 0 and MFI > 50
Bearish when flow index < -10 with CMF < 0 and MFI < 50
Score: +1 for bullish, -1 for bearish, 0 for neutral
2. Confluence Scoring System
The strategy employs two scoring methods:
Binary Signal Count:
Counts how many systems generate bullish signals (0-8)
Counts how many systems generate bearish signals (0-8)
Minimum signals required (default: 2) filters weak setups
Weighted Confluence Score:
Sums all system scores (range: -8 to +8)
Adds bonus points for extreme conditions:
- Extreme momentum regimes (+1)
- All velocity layers aligned (+1)
- 4/4 divergence confluence (+1)
- Volume surge with strong flow (+1)
Total score can exceed ±8 with bonuses
3. Entry Conditions
Two entry modes are available:
Standard Mode (Binary Count):
Long Entry: Bullish signals >= minimum AND bullish signals > bearish signals
Short Entry: Bearish signals >= minimum AND bearish signals > bullish signals
Simple and straightforward
Confluence Mode (Weighted Score):
Long Entry: Total bullish score >= minimum AND bullish score > bearish score
Short Entry: Total bearish score >= minimum AND bearish score > bullish score
Accounts for bonus conditions and extreme setups
4. Risk Management System
The strategy includes comprehensive risk management:
Position Sizing:
Risk per trade: Percentage of equity (default: 2%)
Position size calculated based on stop distance and risk percentage
Prevents over-leveraging on any single trade
Stop Loss Placement:
ATR-based stops: Stop distance = ATR × multiplier (default: 2.0)
Long stops: Entry price - (ATR × multiplier)
Short stops: Entry price + (ATR × multiplier)
Adapts to current volatility
Take Profit Targets:
Risk:Reward ratio (default: 2.0)
Target distance = Stop distance × R:R ratio
Long targets: Entry price + (Stop distance × R:R)
Short targets: Entry price - (Stop distance × R:R)
Trailing Stops:
Optional trailing stop (default: enabled)
Trail distance = ATR × trailing multiplier (default: 3.0)
Locks in profits as trade moves favorably
Adjusts to volatility changes
5. Visual Features
The strategy includes comprehensive visual elements:
Hull Moving Average: Primary trend line with dynamic coloring
SuperTrend Bands: Dynamic support/resistance levels
EMA Matrix: Three EMAs showing trend alignment
Order Block Boxes: Bullish and bearish OB zones
Fair Value Gap Boxes: FVG zones with dashed borders
Liquidity Lines: BSL and SSL levels with sweep tracking
Equilibrium Line: Premium/discount zone reference
Background Coloring: Regime indication (extreme bull/bear, squeeze, entry signals)
Information Dashboard: Real-time display of all metrics and scores
Dashboard Metrics
The comprehensive dashboard displays:
Bull/Bear Scores: Total confluence scores with signal counts
Volatility Index: Current volatility level and regime
Spread: Velocity wave spread indicating momentum strength
Flow Index: Institutional positioning measurement
Price Zone: Premium/discount position with percentage
Win Rate: Strategy performance with trade count
Position: Current position status (Long/Short/Flat)
Signal: Current signal status with confluence indication
Strategy Settings and Defaults
Backtest Configuration:
Initial Capital: $100,000
Position Size: 100% of equity (adjusted by risk management)
Commission: 0.1% per trade
Slippage: 2 ticks
Pyramiding: Disabled (one position at a time)
Risk Management Defaults:
Risk Per Trade: 2.0% of equity
Stop Loss: 2.0 × ATR
Take Profit: 2.0 × Risk (2:1 R:R)
Trailing Stop: Enabled, 3.0 × ATR
Strategy Defaults:
Minimum Signals: 2 (requires at least 2 systems to agree)
Use Confluence Scoring: Enabled (uses weighted scores)
Show Visual Features: Enabled (displays all chart elements)
How to Use This Strategy
Step 1: Configure Risk Parameters
Set risk per trade, stop loss ATR multiplier, and take profit R:R ratio based on your risk tolerance.
Step 2: Choose Entry Mode
Select standard mode (binary count) for simplicity or confluence mode (weighted scores) for advanced filtering.
Step 3: Set Minimum Signals
Higher minimum (3-4) = fewer but higher quality trades. Lower minimum (2) = more trades but lower quality.
Step 4: Enable Trailing Stops
Trailing stops lock in profits on winning trades. Adjust trailing ATR multiplier based on market volatility.
Step 5: Monitor Dashboard
Watch bull/bear scores in real-time. Scores >= 4 indicate strong confluence. Scores >= 6 indicate exceptional setups.
Step 6: Review Visual Confluence
Check that multiple visual elements align: trend, structure, liquidity, and flow should all confirm signal direction.
Step 7: Backtest Thoroughly
Test on multiple instruments and timeframes. Adjust parameters based on results. Aim for 100+ trades for statistical significance.
Best Practices
Use on liquid instruments (major forex, large-cap stocks, major crypto)
Test on multiple timeframes - higher timeframes generally more reliable
Increase minimum signals in choppy markets, decrease in trending markets
Monitor win rate - aim for 40%+ with 2:1 R:R for profitability
Adjust stop loss ATR multiplier based on instrument volatility
Use confluence mode for highest quality signals
Review dashboard before entering - ensure multiple systems align
Combine with higher timeframe analysis for additional confirmation
Be patient - wait for high confluence scores (4+) for best results
Respect the risk management - never override stop losses
Strategy Limitations
Requires sufficient historical data for all eight systems
May generate fewer signals than single-indicator strategies
Performance varies by instrument and timeframe
Backtesting results do not guarantee future performance
Slippage and commission can significantly impact results
Extreme market conditions may cause all systems to fail simultaneously
Requires regular monitoring and parameter adjustment
Not suitable for very low timeframes (< 5 minutes) due to noise
Input Parameters
Risk Management:
Risk Per Trade %: Percentage of equity to risk (default: 2.0%)
Stop Loss (ATR): ATR multiplier for stops (default: 2.0)
Take Profit (R:R): Risk:reward ratio (default: 2.0)
Use Trailing Stop: Enable trailing stops (default: enabled)
Trailing ATR: ATR multiplier for trailing (default: 3.0)
Strategy Settings:
Minimum Signals: Required system agreements (default: 2)
Use Confluence Scoring: Enable weighted scoring (default: enabled)
Show Visual Features: Display chart elements (default: enabled)
Originality Statement
This strategy is original in its comprehensive multi-system approach. While individual analytical methodologies are established concepts, this strategy is justified because:
It integrates eight distinct analytical systems into a unified decision-making engine
The confluence scoring system measures agreement across independent methodologies
Bonus scoring for extreme conditions identifies exceptional setups
Comprehensive risk management adapts to volatility and account size
Visual integration allows traders to verify confluence across multiple dimensions
The dashboard provides real-time transparency into all system states
Systematic approach removes emotional decision-making from trading
Strategy Performance Notes
When publishing this strategy, ensure you:
Use realistic account size (default: $100,000)
Include realistic commission (0.1%) and slippage (2 ticks)
Generate 100+ trades for statistical significance
Document all default settings in description
Explain risk management parameters clearly
Show results on multiple instruments/timeframes
Discuss limitations and market conditions where strategy works best
Never make unrealistic claims about future performance
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors.
Past performance does not guarantee future results. Backtesting results are hypothetical and do not represent actual trading. Actual results may differ significantly from backtested results due to slippage, commission, market conditions, and execution differences.
The strategy combines multiple analytical systems, but no combination of indicators can predict future price movement with certainty. Market conditions change, and strategies that worked historically may not work in the future. Users must conduct their own analysis and risk assessment before using this strategy.
Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions.
The author is not responsible for any losses incurred from using this strategy. Users assume full responsibility for all trading decisions made using this tool.
-Made with passion by officialjackofalltrades Strategy
Precision Confluence Trading Strategy [JOAT]Precision Confluence Trading Strategy
Introduction
The Precision Confluence Trading Strategy is an open-source algorithmic trading system that combines Central Pivot Range (CPR) analysis, Hull Moving Average (HMA) ribbon alignment, WaveTrend oscillator signals, multi-oscillator divergence detection, ADX trend strength, volume confirmation, Smart Money Concepts (FVG, Order Blocks, Liquidity Sweeps), and multi-timeframe analysis into a comprehensive confluence-based strategy. This mashup creates an institutional-grade trading system designed to identify high-probability setups where multiple independent analytical frameworks simultaneously signal the same direction.
The strategy addresses a fundamental challenge in algorithmic trading: single-factor systems produce too many false signals and lack robustness across different market conditions. By requiring confluence across 9 different analytical components before entering trades, this system significantly reduces false signals and focuses capital on only the highest-quality setups where technical, momentum, volume, and institutional factors all align.
Chart showing strategy entries with confluence dashboard on 4H timeframe
Why This Mashup Exists
This strategy combines nine analytical frameworks that address different aspects of market analysis:
CPR Analysis: Identifies key pivot levels where institutional algorithms make decisions
HMA Ribbon: Measures trend quality through 5-layer moving average alignment
WaveTrend Oscillator: Detects momentum cycles and overbought/oversold conditions
Multi-Oscillator Divergence: Identifies momentum exhaustion across RSI, MACD, Stochastic RSI
ADX Trend Strength: Quantifies trend strength to avoid weak, choppy markets
Volume Confirmation: Validates moves with volume analysis and delta calculations
Smart Money Concepts: Tracks institutional footprints (FVG, Order Blocks, Liquidity Sweeps)
Multi-Timeframe Analysis: Ensures directional alignment across 15M, 1H, and 4H timeframes
Key Moving Averages: Confirms position relative to SMA 50/200 institutional levels
Each component addresses a different market dimension: CPR provides static structure, HMA shows trend quality, WaveTrend captures momentum cycles, Divergences warn of exhaustion, ADX measures trend strength, Volume confirms genuine moves, SMC reveals institutional behavior, MTF ensures alignment, and Key MAs provide institutional context. Together, they create a multi-dimensional analysis system that no single indicator can provide.
The mashup is justified because these components use fundamentally different data and methodologies (pivot calculations, weighted moving averages, wave oscillators, directional movement, volume analysis, price inefficiencies, multi-timeframe data, simple moving averages) that respond to different market conditions. When they align, it indicates genuine high-probability setup rather than noise from a single analytical method.
Core Strategy Logic
1. CPR Analysis Component (0-15 points)
Central Pivot Range provides structural reference levels:
// Daily and Weekly CPR calculation
= calcCPR(dHigh, dLow, dClose)
= calcCPR(wHigh, wLow, wClose)
// CPR scoring
cprBullScore = 0
cprBullScore += close > dPivot and close > wPivot ? 10 : 0
cprBullScore += close > dTC ? 3 : 0
cprBullScore += cprNarrow ? 2 : 0 // Narrow CPR = breakout potential
cprBearScore = 0
cprBearScore += close < dPivot and close < wPivot ? 10 : 0
cprBearScore += close < dBC ? 3 : 0
cprBearScore += cprNarrow ? 2 : 0
CPR contribution: Up to 15 points for strong position relative to pivots with narrow CPR indicating breakout potential.
2. HMA Ribbon Alignment Component (0-15 points)
5-layer Hull Moving Average ribbon measures trend quality:
// Calculate 5 HMAs
hma8 = hullMA(close, 8)
hma13 = hullMA(close, 13)
hma21 = hullMA(close, 21)
hma34 = hullMA(close, 34)
hma55 = hullMA(close, 55)
// Full alignment check
hmaFullBullish = hma8 > hma13 and hma13 > hma21 and hma21 > hma34 and hma34 > hma55
hmaFullBearish = hma8 < hma13 and hma13 < hma21 and hma21 < hma34 and hma34 < hma55
// EMA cloud
emaCloudBullish = emaFast > emaSlow
// HMA scoring
hmaRibbonBullScore = 0
hmaRibbonBullScore += hmaBullish ? 5 : 0
hmaRibbonBullScore += hmaFullBullish ? 7 : 0 // Full alignment = strong trend
hmaRibbonBullScore += emaCloudBullish ? 3 : 0
HMA contribution: Up to 15 points for full ribbon alignment with EMA cloud confirmation.
3. WaveTrend Oscillator Component (0-15 points)
WaveTrend detects momentum cycles and extreme conditions:
= calcWaveTrend(hlc3, wtChannelLen, wtAverageLen)
// WaveTrend signals
wtCrossUp = ta.crossover(wt1, wt2)
wtCrossDown = ta.crossunder(wt1, wt2)
wtOversold = wt1 < -60
wtOverbought = wt1 > 60
// WaveTrend scoring
wtBullScore = 0
wtBullScore += wtCrossUp and wtOversold ? 8 : wtCrossUp ? 5 : 0
wtBullScore += wtBullDiv ? 5 : 0 // Divergence adds weight
wtBullScore += wtMomentumBullish ? 2 : 0
WaveTrend contribution: Up to 15 points for crossover in extreme zone with divergence and momentum confirmation.
4. Multi-Oscillator Divergence Component (0-10 points)
Tracks divergences across RSI, MACD, and Stochastic RSI:
// Divergence detection
rsiBullDiv = price LL and rsi HL
wtBullDiv = price LL and wt1 HL
strongBullDiv = rsiBullDiv and wtBullDiv
// Divergence scoring
divBullScore = 0
divBullScore += rsiBullDiv ? 5 : 0
divBullScore += strongBullDiv ? 5 : 0 // Multiple oscillators = stronger signal
Divergence contribution: Up to 10 points for multi-oscillator divergence indicating momentum exhaustion.
5. ADX Trend Strength Component (0-10 points)
ADX quantifies trend strength to avoid choppy markets:
= ta.dmi(adxLength, adxLength)
strongTrend = adx > adxThreshold // Default: 20
trendBullish = plus > minus
// ADX scoring
adxBullScore = strongTrend and trendBullish ? 10 : trendBullish ? 5 : 0
ADX contribution: Up to 10 points for strong trend (ADX > 20) in correct direction.
6. Volume Confirmation Component (0-10 points)
Volume analysis validates genuine institutional participation:
volMA = ta.sma(volume, volMaLength)
highVolume = volume > volMA * 1.5
climaxVolume = volume > volMA * 3.0
// Volume delta
volumeDelta = ta.cum(buyVolume) - ta.cum(sellVolume)
deltaRising = volumeDelta > volumeDeltaMA
// Volume scoring
volBullScore = 0
volBullScore += volConfirmedBull ? 7 : bullishVolume ? 5 : 0
volBullScore += climaxVolume and close > open ? 3 : 0
Volume contribution: Up to 10 points for high volume with rising delta confirming institutional buying.
7. Smart Money Concepts Component (0-10 points)
SMC tracks institutional order flow patterns:
// Fair Value Gaps
significantBullFVG = bullishFVG and fvgSize > 0.3%
// Order Blocks
bullishOB = bearish candles + strong bullish candle + high volume
// Liquidity Sweeps
volConfirmedSweepLow = sweep below recent low + high volume
// Displacement
bullishDisplacement = large candle (> 2x ATR) + climax volume
// SMC scoring
smcBullScore = 0
smcBullScore += significantBullFVG ? 2 : 0
smcBullScore += bullishOB ? 2 : 0
smcBullScore += volConfirmedSweepLow ? 2 : 0
smcBullScore += bullishDisplacement ? 3 : 0
SMC contribution: Up to 10 points for multiple institutional footprints (FVG + OB + Sweep + Displacement).
8. Multi-Timeframe Analysis Component (0-15 points)
Ensures directional alignment across higher timeframes:
// Request higher timeframe data
= request.security(syminfo.tickerid, "15", htfTrend())
= request.security(syminfo.tickerid, "60", htfTrend())
= request.security(syminfo.tickerid, "240", htfTrend())
// Alignment check
mtfBullish = htf15mDir == 1 and htf1hDir == 1 and htf4hDir == 1
mtfStrongBullish = mtfBullish and htf15mStrong and htf1hStrong and htf4hStrong
// MTF scoring
mtfBullScore = 0
mtfBullScore += mtfStrongBullish ? 15 : mtfBullish ? 10 : htf1hDir == 1 ? 5 : 0
MTF contribution: Up to 15 points for all three higher timeframes aligned with strong trends.
9. Key Moving Average Component (0-10 points)
Position relative to institutional moving averages:
sma50 = ta.sma(close, 50)
sma200 = ta.sma(close, 200)
goldenCross = sma50 > sma200
// MA scoring
maBullScore = 0
maBullScore += close > sma50 ? 3 : 0
maBullScore += close > sma200 ? 4 : 0
maBullScore += goldenCross ? 3 : 0
MA contribution: Up to 10 points for price above key MAs with Golden Cross.
Dashboard showing confluence score breakdown by component
Total Confluence Scoring System
The strategy calculates total confluence score (0-100) by summing all components:
bullConfluenceScore = cprBullScore + // 0-15
hmaRibbonBullScore + // 0-15
wtBullScore + // 0-15
divBullScore + // 0-10
adxBullScore + // 0-10
volBullScore + // 0-10
smcBullScore + // 0-10
mtfBullScore + // 0-15
maBullScore // 0-10
// Total: 0-100
Entry signals require:
Bullish confluence score >= minConfluenceScore (default: 70)
Bearish confluence score < 30 (avoid conflicting signals)
Optional session filter (London/NY sessions only)
Signal tiers:
LONG: Confluence score >= 70
STRONG LONG: Confluence score >= 80
ULTRA LONG: Confluence score >= 90 (rare, highest probability)
Risk Management System
The strategy implements comprehensive risk controls:
1. ATR-Based Position Sizing
atr = ta.atr(14)
stopLossDistance = atr * 2
// Calculate position size based on risk
accountSize = strategy.equity
riskAmount = accountSize * (riskPercent / 100) // Default: 2%
positionSize = riskAmount / stopLossDistance
2. Dynamic Stop Loss and Take Profit
// Dynamic stop based on market structure
dynamicStopBull = math.min(close - stopLossDistance, ta.lowest(low, 10))
// Take profit based on risk:reward ratio
takeProfit = close + (stopLossDistance * rewardRatio) // Default: 2:1
3. Breakeven Management
// Move stop to breakeven when profit reaches threshold
if close >= entryPrice + (stopLossDistance * breakevenTrigger) // Default: 1.0 R:R
strategy.exit("Long Exit", "Long", stop=entryPrice, limit=takeProfit)
4. Trailing Stop (Optional)
if useTrailingStop
trailDistance = close * (trailOffset / 100) // Default: 1.5%
strategy.exit("Long Exit", "Long", trail_offset=trailDistance)
Strategy Execution Logic
// Long Entry
if longSignal and strategy.position_size == 0
stopLoss = dynamicStopBull
takeProfit = close + (stopLossDistance * rewardRatio)
strategy.entry("Long", strategy.long)
strategy.exit("Long Exit", "Long", stop=stopLoss, limit=takeProfit)
// Label with confluence score
label.new(bar_index, low,
"LONG Score: " + str.tostring(bullConfluenceScore),
style=label.style_label_up,
color=entryColor)
// Short Entry (mirror logic)
if shortSignal and strategy.position_size == 0
// Similar logic for short trades
Performance Dashboard
The strategy displays a comprehensive 12-row dashboard:
Row 1: Component header
Row 2: Current position (LONG/SHORT/FLAT)
Row 3: Total confluence score (bull/bear)
Row 4: CPR component score
Row 5: HMA Ribbon component score
Row 6: WaveTrend component score
Row 7: Divergence component score
Row 8: ADX component score
Row 9: Volume component score
Row 10: SMC component score
Row 11: MTF component score
Row 12: Equity and P&L percentage
Strategy Parameters
Strategy Settings:
Use Multi-Timeframe Confirmation: Enable MTF analysis (default: enabled)
Use Divergence Signals: Enable divergence component (default: enabled)
Use Smart Money Concepts: Enable SMC component (default: enabled)
Use Volume Confirmation: Enable volume component (default: enabled)
Use CPR Levels: Enable CPR component (default: enabled)
Use WaveTrend Signals: Enable WaveTrend component (default: enabled)
Use HMA Alignment: Enable HMA component (default: enabled)
Use Session Filter: Trade only during London/NY sessions (default: enabled)
Minimum Confluence Score: Threshold for entry (default: 70, range: 50-100)
Risk Management:
Risk Per Trade %: Percentage of equity to risk (default: 2.0%, range: 0.1-10%)
Reward:Risk Ratio: Take profit multiplier (default: 2.0, range: 1.0-5.0)
Use Trailing Stop: Enable trailing stop (default: enabled)
Trailing Stop %: Trail distance (default: 1.5%, range: 0.1-5.0%)
Use Breakeven: Move stop to breakeven (default: enabled)
Breakeven Trigger: R:R threshold to move stop (default: 1.0, range: 0.5-3.0)
Indicator Parameters:
RSI Length: Period for RSI (default: 14)
ADX Length: Period for ADX (default: 14)
ADX Threshold: Minimum ADX for strong trend (default: 20)
Volume MA Length: Period for volume average (default: 20)
HMA Length: Period for HMA (default: 21)
WaveTrend Channel Length: (default: 10)
WaveTrend Average Length: (default: 21)
Backtesting Configuration
Default strategy properties:
Initial Capital: $10,000
Default Qty Type: Percent of Equity
Default Qty Value: 10%
Commission Type: Percent
Commission Value: 0.1% (10 basis points)
Slippage: 2 ticks
Max Bars Back: 5000
These settings represent realistic trading conditions for the average trader. Commission and slippage account for typical broker fees and execution costs.
How to Use This Strategy
Step 1: Configure Components
Enable/disable components based on your trading style. All components enabled provides maximum filtering but fewer trades.
Step 2: Set Confluence Threshold
Adjust minimum confluence score. Higher threshold (80-90) = fewer, higher-quality trades. Lower threshold (60-70) = more frequent trades.
Step 3: Configure Risk Parameters
Set risk per trade (1-2% recommended) and reward:risk ratio (2:1 minimum recommended). Enable breakeven and trailing stop for protection.
Step 4: Backtest Thoroughly
Run backtests on multiple timeframes and market conditions. Aim for 100+ trades for statistical significance. Review win rate, profit factor, and drawdown.
Step 5: Analyze Component Contribution
Use dashboard to see which components contribute most to winning trades. Consider adjusting weights or disabling low-value components.
Step 6: Forward Test
Paper trade the strategy before risking real capital. Verify that live results align with backtest expectations.
Best Practices
Use on 15-minute to 4-hour timeframes for optimal signal quality
Confluence score above 80 produces highest win rate but fewer trades
Enable all components for maximum filtering in volatile markets
Disable some components for more frequent trades in trending markets
Session filter (London/NY only) significantly improves results
Risk 1-2% per trade maximum for sustainable trading
Aim for minimum 2:1 reward:risk ratio
Review dashboard component scores to understand trade quality
Backtest on minimum 6-12 months of data
Verify 100+ trades in backtest for statistical validity
Strategy Limitations
Confluence-based systems produce fewer trades - may not suit active traders
Requires all components to align - perfect setups are rare
Backtesting results may not reflect live trading with slippage and latency
Multi-timeframe analysis can cause repainting on lower timeframes
High confluence threshold (90+) may produce too few trades for some markets
Commission and slippage significantly impact profitability
Strategy optimized for trending markets - may underperform in ranges
Past performance does not guarantee future results
Requires understanding of all components for effective parameter tuning
Complex system with many parameters - over-optimization risk
Backtesting Considerations
When evaluating backtest results:
Sample Size: Minimum 100 trades for statistical significance
Win Rate: 40-60% is realistic for 2:1 R:R strategy
Profit Factor: Above 1.5 is good, above 2.0 is excellent
Max Drawdown: Should be less than 20% of initial capital
Sharpe Ratio: Above 1.0 indicates good risk-adjusted returns
Trade Frequency: Should match your trading availability
Equity Curve: Should show steady growth, not erratic spikes
Consecutive Losses: Prepare for 5-10 consecutive losses
Adjust parameters if:
Win rate < 35% with 2:1 R:R (increase confluence threshold)
Too few trades (< 50 in 6 months) (decrease confluence threshold or disable some components)
Max drawdown > 25% (reduce risk per trade or increase confluence threshold)
Profit factor < 1.2 (strategy may not be viable)
Technical Implementation
Built with Pine Script v6 using:
9-component confluence scoring system
CPR calculations with width analysis
5-layer HMA ribbon with full alignment detection
WaveTrend oscillator with divergence tracking
Multi-oscillator divergence detection (RSI, MACD, Stoch RSI)
ADX trend strength measurement
Volume analysis with delta calculations
Smart Money Concepts (FVG, OB, Liquidity Sweeps, Displacement)
Multi-timeframe analysis (15M, 1H, 4H)
ATR-based dynamic position sizing
Breakeven and trailing stop management
Comprehensive 12-row dashboard
Session filtering (London/NY)
The code is fully open-source and can be modified to adjust component weights, confluence thresholds, and risk parameters.
Originality Statement
This strategy is original in its comprehensive multi-component confluence approach. While individual components (CPR, HMA, WaveTrend, Divergences, ADX, Volume, SMC, MTF, Key MAs) are established analytical tools, this mashup is justified because:
It integrates 9 independent analytical frameworks using fundamentally different data and methodologies
The confluence scoring system quantifies setup quality across all components (0-100 scale)
Each component addresses a different market dimension (structure, trend, momentum, strength, volume, institutional flow, timeframe alignment)
Tiered signal system (LONG/STRONG/ULTRA) provides graduated confidence levels
Comprehensive risk management with ATR-based sizing, breakeven, and trailing stops
Component-level dashboard allows traders to understand what drives each trade
Session filtering aligns with institutional trading hours
Integration reveals complete market picture that no single indicator provides
Each component contributes unique information: CPR provides structure, HMA shows trend quality, WaveTrend captures momentum cycles, Divergences warn of exhaustion, ADX measures strength, Volume confirms moves, SMC reveals institutional behavior, MTF ensures alignment, and Key MAs provide institutional context. The strategy's value lies in requiring confluence across these independent frameworks, significantly reducing false signals and focusing capital on only the highest-probability setups where all factors align.
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors.
Backtesting results do not guarantee future performance. Past results, whether real or indicated by historical tests, are not indicative of future results. There are frequently sharp differences between backtested results and actual results subsequently achieved by any trading strategy.
The confluence score is a mathematical calculation based on current market data, not a prediction of future price movement. High confluence scores do not ensure profitable trades. Market conditions change, and strategies that worked historically may not work in the future.
Commission and slippage settings in backtests may not accurately reflect live trading conditions. Real trading results will vary based on execution quality, market liquidity, broker fees, and other factors not captured in backtesting.
No representation is being made that any account will or is likely to achieve profits or losses similar to those shown in backtests. Users should thoroughly test any strategy in a paper trading environment before risking real capital.
Always use proper risk management. Never risk more than you can afford to lose. The default 2% risk per trade is a guideline - adjust based on your personal risk tolerance and account size. Consider consulting with a qualified financial advisor before making investment decisions.
The author is not responsible for any losses incurred from using this strategy. Users assume full responsibility for all trading decisions made using this tool.
-Made with passion by officialjackofalltrades Strategy
SMC Alpha Engine [PhenLabs]📊 SMC Alpha Engine
Version: PineScript™ v6
📌 Description
The SMC Alpha Engine is a comprehensive Smart Money Concepts indicator that automates institutional trading pattern recognition. Built for traders who understand that confluence is king, this indicator stacks multiple SMC elements together and scores them in real-time, allowing you to focus exclusively on high-probability setups.
Rather than manually tracking HTF bias, market structure, liquidity levels, order blocks, and fair value gaps separately, the SMC Alpha Engine consolidates everything into a unified scoring system. When enough factors align, you get a signal. When they don’t, you wait. This systematic approach removes emotion and subjectivity from SMC trading.
The indicator is designed around one core principle: only trade when the probabilities are stacked in your favor. By requiring multiple confluence factors before generating signals, it filters out the noise and keeps you focused on setups that institutional traders actually care about.
🚀 Points of Innovation
Automated confluence scoring system that evaluates 6 distinct SMC factors in real-time
HTF-to-LTF bias alignment ensuring trades flow with institutional direction
Intelligent liquidity sweep detection using wick-ratio analysis for confirmation
ATR-based FVG quality filtering that eliminates noise and shows only significant imbalances
Anti-spam signal logic preventing overtrading during volatile market conditions
Session-aware killzone integration timing entries with institutional activity windows
🔧 Core Components
HTF Bias Engine: Analyzes higher timeframe swing structure to establish directional bias using pivot high/low comparisons
Market Structure Module: Detects BOS (Break of Structure) and CHoCH (Change of Character) with real-time confirmation
Premium/Discount Calculator: Dynamically maps price zones relative to recent swing range equilibrium
Liquidity Tracker: Monitors swing points as liquidity targets and identifies sweep events with rejection confirmation
POI Detector: Identifies valid Order Blocks with displacement requirements and Fair Value Gaps with ATR filtering
Confluence Scorer: Aggregates all factors into bull/bear scores displayed on real-time dashboard
🔥 Key Features
Multi-timeframe analysis combining HTF directional bias with LTF precision entries
Customizable confluence threshold from 1 (low filter) to 5 (sniper mode)
Three killzone sessions: London (02:00-05:00), NY AM (08:30-11:00), NY PM (13:30-16:00)
Flexible mitigation options for OBs and FVGs: Wick, Close, 50%, or None
Visual structure labeling for BOS and CHoCH events on chart
Real-time info dashboard showing all current market conditions and scores
Built-in alert conditions for BOS, liquidity sweeps, and high-confluence signals
🎨 Visualization
Premium Zone: Red-tinted box above equilibrium indicating sell-side interest areas
Discount Zone: Green-tinted box below equilibrium indicating buy-side interest areas
Equilibrium Line: Dotted gray line marking the 50% level of current range
Order Blocks: Color-coded boxes (green for bullish, red for bearish) showing institutional candles
Fair Value Gaps: Teal boxes for bullish FVGs, maroon boxes for bearish FVGs
Killzone Backgrounds: Blue (London), Orange (NY AM), Purple (NY PM) session highlighting
Info Table: Top-right dashboard displaying HTF bias, LTF trend, zone, killzone status, and scores
📖 Usage Guidelines
HTF Settings
HTF Timeframe - Default: 60 - Controls higher timeframe for directional bias
HTF Swing Length - Default: 10, Range: 3+ - Determines pivot sensitivity for HTF trend
Market Structure Settings
LTF Swing Length - Default: 3, Range: 1-10 - Controls swing detection sensitivity
Show BOS/CHoCH - Default: Off - Toggles structure labels on chart
Show Strong/Weak Points - Default: Off - Displays swing point classifications
POI Settings
Show Valid Order Blocks - Default: Off - Displays OBs that caused displacement
Show Unmitigated FVGs - Default: On - Shows active fair value gaps
Filter FVG by ATR - Default: On - Only shows FVGs larger than 0.5x ATR
OB Mitigation Type - Options: Wick, Close, None - Determines when OBs are invalidated
FVG Mitigation Type - Options: Wick, Close, 50%, None - Determines when FVGs are filled
Confluence Settings
Minimum Score for Signal - Default: 4, Range: 1-5 - Required confluence level for entries
Show Entry Signals - Default: On - Toggles LONG/SHORT labels on chart
✅ Best Use Cases
Trend continuation trades during active killzone sessions with HTF alignment
Discount zone entries on bullish HTF bias with recent liquidity sweep below
Premium zone shorts on bearish HTF bias after liquidity grab above recent highs
Reversal identification following CHoCH with POI confluence in optimal zone
Filtering existing strategy signals by requiring minimum confluence score
⚠️ Limitations
HTF bias detection requires sufficient price history for accurate pivot identification
Liquidity sweep detection depends on wick-ratio settings and may miss some events
Order blocks require displacement confirmation which may exclude some valid zones
Confluence scoring is probabilistic and does not guarantee profitable outcomes
Killzone times are based on EST/EDT and require timezone adjustment for other regions
Signal spam prevention may delay valid signals by up to 10 bars after previous signal
💡 What Makes This Unique
Unified SMC Framework: Combines all major SMC concepts into one cohesive indicator rather than requiring multiple tools
Objective Scoring System: Removes subjectivity by quantifying confluence into measurable scores
Institutional Timing Integration: Built-in killzone awareness ensures signals align with high-volume sessions
Quality Filtering: ATR-based FVG filtering and displacement-required OBs eliminate low-quality setups
Anti-Overtrading Logic: Smart signal spacing prevents emotional trading during choppy conditions
🔬 How It Works
Step 1: HTF Bias Determination
Analyzes higher timeframe pivot highs and lows
Compares consecutive pivots to identify HH/HL (bullish) or LH/LL (bearish) sequences
Establishes directional filter that all signals must respect
Step 2: LTF Structure Mapping
Detects swing points on execution timeframe
Identifies BOS when price closes beyond confirmed swing level
Recognizes CHoCH when structure break occurs against current trend
Step 3: Confluence Calculation
Awards +1 for HTF bias alignment
Awards +1 for active killzone timing
Awards +1 for optimal zone positioning (discount for longs, premium for shorts)
Awards +1 for price at unmitigated POI
Awards +1 for recent liquidity sweep in trade direction
Awards +1 for recent supportive structure break
Step 4: Signal Generation
Compares total score against user-defined minimum threshold
Requires candle confirmation (bullish close for longs, bearish close for shorts)
Applies 10-bar spacing filter to prevent signal clustering
💡 Note:
This indicator is designed for traders already familiar with Smart Money Concepts. While it automates detection and scoring, understanding why each factor matters will significantly improve your ability to filter signals and manage trades effectively. Use the minimum confluence setting to match your risk tolerance, higher values mean fewer but higher-quality signals. Indicator
PHEN ATLAS - Market Map & Playbook [PhenLabs]📊 PHEN ATLAS 🎂 #50 🎂
Version: PineScript™ v6
📌 Description
The PHEN ATLAS marks a historic milestone as the 50th official release from PhenLabs . This is a critical release you do not want to miss, serving as a comprehensive Market Map and Playbook designed to provide traders with a complete structural overview of price action. By synthesizing Market Structure, Liquidity concepts, and Regime detection, this script solves the problem of "analysis paralysis" by grading price action in real-time. It moves beyond simple indicators by offering a quantified "Playbook" that scores trade setups from 0 to 100, helping traders focus exclusively on high-probability opportunities while automating the complex math of position sizing and risk management.
🚀 Points of Innovation
Proprietary Scoring Engine: Unlike standard indicators, this script assigns a quantitative score (0-100) to every potential trade based on confluence factors like HTF alignment and displacement.
Dynamic Regime Detection: Features an integrated dashboard that classifies the market into specific phases (Expansion, Trend, Range) using ADX and EMA alignment logic.
Smart Liquidity Pools: Automatically identifies and visualizes resting liquidity, tracking when these pools are "swept" to generate high-probability reversal signals.
Integrated Trade Manager: Automates the calculation of Stop Loss, Take Profit (1:2 and 1:3), and Position Size based on account balance and risk percentage directly on the chart.
Multi-Mode Interface: Offers three distinct visual modes—Clean, Pro, and Sniper—allowing users to toggle between deep analysis and clutter-free execution instantly.
🔧 Core Components
Structure Module: Identifies Pivots, Break of Structure (BOS), and Change of Character (CHoCH) to define the current market bias.
Liquidity Engine: Plots liquidity pools at key swing points and detects "Sweeps" where price grabs liquidity before reversing.
Regime Filter: Uses a combination of EMAs (21/50) and ADX to determine if the market is trending or ranging, filtering out low-quality signals.
Setup Validator: Monitors for three specific setup types (Sweep, Snapback, FVG Retest) and triggers alerts only when specific scoring thresholds are met.
🔥 Key Features
Automated detection of High Timeframe (HTF) structure without repainting issues.
Real-time grading of price displacement to validate institutional intent.
Visual Risk/Reward boxes that automatically adjust to the volatility (ATR) of the asset.
Fair Value Gap (FVG) detection with auto-mitigation tracking to clean up the chart.
Customizable alerts for A+ setups, regime changes, and trade invalidations.
Detailed dashboard displaying current Trend, Phase, Bias, and the score of the last setup.
🎨 Visualization
Structure Points: Triangles for BOS and Diamonds for CHoCH events clearly mark trend shifts.
Liquidity Lines: Dotted lines extending from pivots indicate un-swept liquidity pools; these dim automatically when swept.
Setup Signals: Prominent "A+" labels appear on the chart when a setup meets the minimum score threshold defined by the user.
Risk Boxes: Color-coded boxes (Green for Long, Red for Short) show Entry, Stop Loss, and Take Profit levels visually.
Dashboard: A compact table in the bottom right corner provides a "Heads Up Display" of the market state.
📖 Usage Guidelines
Display Mode: Select between 'Clean' for signals only, 'Pro' for full analysis including FVGs and Structure, or 'Sniper' for only high-score setups.
HTF Timeframe: Sets the higher timeframe for structural analysis (Default: 240/4-Hour) to ensure you trade with the dominant trend.
Min Score for A+ Setup: Threshold (0-100) required to trigger a signal (Default: 83); increase this to filter for only the absolute best trades.
Risk %: Defines the percentage of your account you are willing to risk per trade (Default: 1.0%), used for the position size calculation.
Account Balance: Input your current capital (Default: 10,000) to receive accurate unit sizing for every trade setup.
ADX Threshold: Adjusts the sensitivity of the Regime detection filter (Default: 20) to determine when the market is trending versus ranging.
✅ Best Use Cases
Confluence Trading: Use the scoring system to filter discretionary entries, taking trades only when the system scores them above 80.
Prop Firm Trading: Utilize the built-in position size calculator to strictly adhere to risk management rules during evaluations.
Trend Following: Wait for the Regime Dashboard to show "Bullish Expansion" before taking Long "Snapback" entries.
Reversal Trading: Focus on "Sweep Reclaim" setups where price sweeps a liquidity pool and immediately closes back within range.
⚠️ Limitations
This tool is a trend-following and reversal system; it may produce lower scores during undefined, low-volatility chop.
The position size calculator is an estimation based on the entry candle; actual execution slippage is not accounted for.
HTF data relies on closed candles to prevent repainting, which may result in a slight lag during rapid volatility spikes.
💡 What Makes This Unique
Playbook Scoring: Most indicators just give a signal; PHEN ATLAS gives you a "Grade" (e.g., 85/100), allowing you to make informed decisions based on quality, not just frequency.
Context Awareness: The script understands "Market Regime" and creates a context-aware bias, rather than blindly firing signals in a range.
🔬 How It Works
Step 1 - Regime Definition: The script analyzes the 21/50 EMA relationship and ADX to define if the market is in a Trend or Range.
Step 2 - Structure & Liquidity: It maps key pivots and liquidity pools, waiting for a "Sweep" event or a structural break.
Step 3 - Setup Trigger: When a specific pattern occurs (like a Sweep Reclaim), the engine calculates a score based on displacement, volume, and key level alignment.
Step 4 - Execution Logic: If the score > Threshold, the Trade Manager calculates the invalidation point (SL) and projects 2R/3R targets automatically.
🎉 Message From The Team 🎉
2025 was an amazing year. 12 months of building, shipping, and improving together with you. Hitting our 50th indicator release marks one full year of weekly drops , and we couldn't have done it without this community, and of course, BIG thank you to PulseWire and it's team.
Thank you for all the feedback, charts, and support. Let's make 2026 even bigger. We can't wait to show you what we've been working on. 🚀
💡 Note
For best results, we recommend using the "Pro" mode during analysis to understand the narrative, and switching to "Sniper" or "Clean" during execution to maintain focus. Always ensure your "Account Balance" input matches your broker balance for accurate risk calculations. Indicator
HTF Fibonacci on intraday ChartThis indicator plots Higher Timeframe (HTF) Fibonacci retracement levels directly on your intraday chart, allowing you to visualize how the current price action reacts to key retracement zones derived from the higher timeframe trend.
Concept
Fibonacci retracement levels are powerful tools used to identify potential support and resistance zones within a price trend.
However, these levels are often calculated on a higher timeframe (like Daily or Weekly), while most traders execute entries on lower timeframes (like 15m, 30m, or 1H).
This indicator bridges that gap — it projects the higher timeframe’s Fibonacci levels onto your current intraday chart, helping you see where institutional reactions or swing pivots might occur in real time.
How It Works
Select the Higher Timeframe (HTF)
You can choose which higher timeframe the Fibonacci structure is derived from — default is Daily.
Define the Lookback Period
The script looks back over the chosen number of bars on the higher timeframe to find the highest high and lowest low — the base for Fibonacci calculations.
Plots Key Fibonacci Levels Automatically:
0% (Low)
23.6%
38.2%
50.0%
61.8%
78.6%
100% (High)
Dynamic Labels
Each Fibonacci level is labelled on the latest bar, updating in real time as new data forms on the higher timeframe.
Best Used For
Intraday traders who want to align lower-timeframe entries with higher-timeframe structure.
Swing traders confirming price reactions around major Fibonacci retracement zones.
Contextual analysis for pullback entries, breakout confirmations, or retests of key levels.
Recommended Settings
Higher Timeframe: Daily (for intraday analysis)
Lookback: 50 bars (adjust based on volatility)
Combine with MACD, RSI, CPR, or Pivots for confluence.
License & Credits
Created and published for educational and analytical purposes.
Inspired by standard Fibonacci analysis practices. Indicator
Multi-Timeframe Confluence IndicatorThe Multi-Timeframe Confluence Indicator strategically combines multiple timeframes with technical tools like EMA and RSI to provide robust, high-probability trading signals. This combination is grounded in the principles of technical analysis and market behavior, tailored for traders across all styles—whether intraday, swing, or positional.
1. The Power of Multi-Timeframe Confluence
Markets are influenced by participants operating on different time horizons:
• Intraday traders act on short-term price fluctuations.
• Swing traders focus on intermediate trends lasting days or weeks.
• Position traders aim to capture multi-month or long-term trends.
By aligning signals from a higher timeframe (macro trend) with a lower timeframe (micro trend), the indicator ensures that short-term entries are in harmony with the broader market direction. This multi-timeframe approach significantly reduces false signals caused by temporary market noise or counter-trend moves.
Example: A bullish trend on the daily chart (higher timeframe) combined with a bullish RSI and EMA alignment on the 15-minute chart (lower timeframe) provides a stronger confirmation than relying on the 15-minute chart alone.
2. Why EMA and RSI Are Essential
Each element of the indicator serves a unique role in ensuring accuracy and reliability:
• EMA (Exponential Moving Average):
• A dynamic trend filter that adjusts quickly to price changes.
• On the higher timeframe, it establishes the overall trend direction (e.g., bullish or bearish).
• On the lower timeframe, it identifies precise entry/exit zones within the trend.
• RSI (Relative Strength Index):
• Adds a momentum-based perspective, confirming whether a trend is backed by strong buying or selling pressure.
• Ensures that signals occur in areas of strength (RSI > 55 for bullish signals, RSI < 45 for bearish signals), filtering out weak or uncertain price movements.
By combining EMA (trend) and RSI (momentum), the indicator delivers confluence-based validation, where both trend and momentum align, making signals more reliable.
3. Cooldown Period for Signal Optimization
Trading in choppy or sideways markets often leads to overtrading and false signals. The cooldown period ensures that once a signal is generated, subsequent signals are suppressed for a defined number of bars. This prevents traders from entering low-probability trades during indecisive market phases, improving overall signal quality.
Example: After a bullish confluence signal, the cooldown period prevents a bearish signal from being triggered prematurely if the market enters a temporary retracement.
4. Use Cases Across Trading Styles
This indicator caters to various trading styles, each benefiting from the confluence of timeframes and technical elements:
• Intraday Trading:
• Use a 1-hour chart as the higher timeframe and a 5-minute chart as the lower timeframe.
• Benefit: Align intraday entries with the hourly trend for higher win rates.
• Swing Trading:
• Use a daily chart as the higher timeframe and a 1-hour chart as the lower timeframe.
• Benefit: Capture multi-day moves while avoiding counter-trend entries.
• Scalping:
• Use a 30-minute chart as the higher timeframe and a 1-minute chart as the lower timeframe.
• Benefit: Enhance scalping efficiency by ensuring short-term trades align with broader intraday trends.
• Position Trading:
• Use a weekly chart as the higher timeframe and a daily chart as the lower timeframe.
• Benefit: Time long-term entries more precisely, maximizing profit potential.
5. Robustness Through Customization
The indicator allows traders to customize:
• Timeframes for higher and lower analysis.
• EMA lengths for trend filtering.
• RSI settings for momentum confirmation.
• Cooldown periods to adapt to market volatility.
This flexibility ensures that the indicator can be tailored to suit individual trading preferences, market conditions, and asset classes, making it a comprehensive tool for any trading strategy.
Why This Mashup Stands Out
The Multi-Timeframe Confluence Indicator is more than a sum of its parts. It leverages:
• EMA’s ability to identify trends, combined with RSI’s insight into momentum, ensuring each signal is well-supported.
• A multi-timeframe perspective that incorporates both macro and micro trends, filtering out noise and improving reliability.
• A cooldown mechanism that prevents overtrading, a common pitfall for traders in volatile markets.
This integration results in a powerful, adaptable indicator that provides actionable, high-confidence signals, reducing uncertainty and enhancing trading performance across all styles. Indicator
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