Market sentiment and cryptocurrency narratives📈 IDRA + PFLA: Crypto Market Sentiment & Narrative Flow
Uncover hidden opportunities and navigate the dynamic crypto landscape with IDRA + PFLA (Intraday Dynamic Risk Assessment + Public Flow & Liquidity Analysis). This powerful, two-in-one indicator suite is meticulously designed to provide you with a comprehensive understanding of market sentiment and identify active cryptocurrency narratives across different timeframes.
IDRA: Intraday Dynamic Risk Assessment (Daily & 4-Hour)
The IDRA component offers a unique perspective on overall market sentiment, helping you gauge risk appetite within the altcoin space.
Daily Sentiment Plot: Visualize the daily macro sentiment with a dedicated plot that fluctuates between zones of "High Risk (Euphoria)," "Low Risk (Opportunity)," "Very Low Risk (Panic/Opportunity)," and "Absolute Bottom (Max Despair)." Transparent zone fills make it easy to interpret the prevailing market mood.
Bitcoin/Altcoin Season Bar (4-Hour): At the bottom right of your chart, a dynamic bar visually represents the "Bitcoin Season" to "Altcoin Season" spectrum. This intuitive bar, updated every 4 hours, provides real-time insights into which side of the market is currently attracting more capital and attention. A white indicator line moves across the gradient, showing the current IDRA reading on a normalized 0-100 scale.
Customizable Normalization: Adjust the normalization period to fine-tune IDRA's sensitivity to historical market behavior.
Actionable Alerts: Set up alerts for IDRA's key levels (High, Low, Very Low, Absolute Bottom) to be notified of significant shifts in market sentiment, allowing you to react promptly to potential opportunities or threats.
PFLA: Public Flow & Liquidity Analysis (Daily)
The PFLA component provides a detailed breakdown of capital flows and dominance within key crypto narratives. It acts as a daily snapshot, showing you where the money is moving across different crypto sectors.
Ecosystem Performance: Track the daily performance of major ecosystems like Ethereum, Solana, and BNB Chain, observing their dominance and 24-hour capital flow changes.
Trending Categories: Stay ahead of the curve by monitoring the capital movements and dominance of hot narratives such as DePIN, AI, RWA, and MEME coins.
Layer 1 Insights: Gain a clear understanding of the broader Layer 1 landscape.
Consensus Mechanism Analysis : Compare the performance of Proof-of-Work (PoW) and Proof-of-Stake (PoS) coins.
Stablecoin Dominance: Keep an eye on the overall Stablecoin Dominance within the total crypto market, a crucial indicator of risk aversion or appetite.
Daily Snapshot : Each category displays its current dominance, today's capitalization (in billions), and the daily percentage change, all clearly color-coded (green for positive, red for negative).
Ideal for 4-Hour and Daily Timeframes
This indicator is specifically optimized for use on 4-hour and daily charts, providing both intraday and longer-term perspectives on market sentiment and narrative shifts. The IDRA bar updates every 4 hours for more immediate insights, while the PFLA table provides a daily comprehensive overview.
💡 How to Use It
Bias Confirmation: Use the IDRA plot to confirm your general bias on whether the altcoin market is in a phase of euphoria, fear, or panic.
Opportunity Identification: The "Opportunity" and "Extreme Panic" zones of the IDRA plot can signal opportune moments for accumulation.
Risk Management: The "High Risk/Euphoria" zone of the IDRA plot alerts you to be more cautious or consider profit-taking.
Capital Flow Analysis: The PFLA table instantly shows you which ecosystems and narratives are attracting or losing capital today, helping you identify the strongest trends or areas under pressure.
Bitcoin vs. Altcoin Season: The IDRA Bitcoin/Altcoin Season Bar visually indicates the current market phase.
When the white indicator line is closer to "Bitcoin Season" (left side of the bar), it suggests Bitcoin is outperforming altcoins, and capital is flowing into BTC or larger-cap assets for stability. This might be a time to prioritize Bitcoin trades or be cautious with altcoins.
When the white indicator line is closer to "Altcoin Season" (right side of the bar), it indicates altcoins are outperforming Bitcoin, and capital is rotating into the broader altcoin market, often in search of higher returns. This could signal a more favorable environment for altcoin trading.
Use this bar to quickly assess the broader market's risk appetite: generally, Bitcoin Season implies more risk-off sentiment, while Altcoin Season suggests more risk-on.
Customizable Alerts: Configure alerts on IDRA to receive notifications when the index enters or exits its key zones.
The "IDRA & PFLA Integrated" is an indispensable tool for any cryptocurrency investor or trader seeking a deep understanding of capital flow and altcoin market sentiment.
IDRA + PFLA empowers you with the data you need to make more informed trading and investment decisions in the fast-paced world of cryptocurrencies. Gain a distinct edge by understanding where the smart money is flowing and which narratives are gaining traction.
Please note: This indicator is private and requires an invitation to access.
Volum
Quantum Reversal Engine [ApexLegion]Quantum Reversal Engine
STRATEGY OVERVIEW
This strategy is constructed using 5 custom analytical filters that analyze different market dimensions - trend structure, momentum expansion, volume confirmation, price action patterns, and reversal detection - with results processed through a multi-component scoring calculation that determines signal generation and position management decisions.
Why These Custom Filters Were Independently Developed:
This strategy employs five custom-developed analytical filters:
1. Apex Momentum Core (AMC) - Custom oscillator with volatility-scaled deviation calculation
Standard oscillators lag momentum shifts by 2-3 bars. Custom calculation designed for momentum analysis
2. Apex Wick Trap (AWT) - Wick dominance analysis for trap detection
Existing wick analysis tools don't quantify trap conditions. Uses specific ratios for wick dominance detection
3. Apex Volume Pulse (AVP) - Volume surge validation with participation confirmation
Volume indicators typically use simple averages. Uses surge multipliers with participation validation
4. Apex TrendGuard (ATG) - Angle-based trend detection with volatility band integration
EMA slope calculations often produce false signals. Uses angle analysis with volatility bands for confirmation
5. Quantum Composite Filter (QCF) - Multi-component scoring and signal generation system
Composite scoring designed to filter noise by requiring multiple confirmations before signal activation.
Each filter represents mathematical calculations designed to address specific analytical requirements.
Framework Operation: The strategy functions as a scoring framework where each filter contributes weighted points based on market conditions. Entry signals are generated when minimum threshold scores are met. Exit management operates through a three-tier system with continued signal strength evaluation determining position holds versus closures at each TP level.
Integration Challenge: The core difficulty was creating a scoring system where five independent filters could work together without generating conflicting signals. This required backtesting to determine effective weight distributions.
Custom Filter Development:
Each of the five filters represents analytical approaches developed through testing and validation:
Integration Validation: Each filter underwent individual testing before integration. The composite scoring system required validation to verify that filters complement rather than conflict with each other, resulting in a cohesive analytical framework that was tested during the development period.
These filters represent custom-developed components created specifically for this strategy, with each component addressing different analytical requirements through testing and parameter adjustment.
Programming Features:
Multi-timeframe data handling with backup systems
Performance optimization techniques
Error handling for live trading scenarios
Parameter adaptation based on market conditions
Strategy Features:
Uses multi-filter confirmation approach
Adapts position holding based on continued signal strength
Includes analysis tools for trade review and optimization
Ongoing Development: The strategy was developed through testing and validation processes during the creation period.
COMPONENT EXPLANATION
EMA System
Uses 8 exponential moving averages (7, 14, 21, 30, 50, 90, 120, 200 periods) for trend identification. Primary signals come from 8/21 EMA crossovers, while longer EMAs provide structural context. EMA 1-4 determine short-term structure, EMA 5-8 provide long-term trend confirmation.
Apex Momentum Core (AMC)
Built custom oscillator mathematics after testing dozens of momentum calculation methods. Final algorithm uses price deviation from EMA baseline with volatility scaling to reduce lag while maintaining accuracy across different market conditions.
Custom momentum oscillator using price deviation from EMA baseline:
apxCI = 100 * (source - emaBase) / (sensitivity * sqrt(deviation + 1))
fastLine = EMA(apxCI, smoothing)
signalLine = SMA(fastLine, 4)
Signals generate when fastLine crosses signalLine at +50/-50 thresholds.
This identifies momentum expansion before traditional oscillators.
Apex Volume Pulse (AVP)
Created volume surge analysis that goes beyond simple averages. Extensive testing determined 1.3x multiplier with participation validation provides reliable confirmation while filtering false volume spikes.
Compares current volume to 21-period moving average.
Requires 1.3x average volume for signal confirmation. This filters out low-volume moves during quiet periods and confirms breakouts with actual participation.
Apex Wick Trap (AWT)
Developed proprietary wick trap detection through analysis of failed breakout patterns. Tested various ratio combinations before settling on 60% wick dominance + 20% body limit as effective trap identification parameters.
Analyzes candle structure to identify failed breakouts:
candleRange = math.max(high - low, 0.00001)
candleBody = math.abs(close - open)
bodyRatio = candleBody / candleRange
upperWick = high - math.max(open, close)
lowerWick = math.min(open, close) - low
upperWickRatio = upperWick / candleRange
lowerWickRatio = lowerWick / candleRange
trapWickLong = showAWT and lowerWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close > open
trapWickShort = showAWT and upperWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close < open This catches reversals after fake breakouts.
Apex TrendGuard (ATG)
Built angle-based trend detection after standard EMA crossovers proved insufficient. Combined slope analysis with volatility bands through iterative testing to eliminate false trend signals.
EMA slope analysis with volatility bands:
Fast EMA (21) vs Slow EMA (55) for trend direction
Angle calculation: atan(fast - slow) * 180 / π
ATR bands (1.75x multiplier) for breakout confirmation
Minimum 25° angle for strong trend classification
Core Algorithm Framework
1. Composite Signal Generation
calculateCompositeSignals() =>
// Component Conditions
structSignalLong = trapWickLong
structSignalShort = trapWickShort
momentumLong = amcBuySignal
momentumShort = amcSellSignal
volumeSpike = volume > volAvg_AVP * volMult_AVP
priceStrength_Long = close > open and close > close
priceStrength_Short = close < open and close < close
rsiMfiComboValue = (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2
reversalTrigger_Long = ta.crossover(rsiMfiComboValue, 50)
reversalTrigger_Short = ta.crossunder(rsiMfiComboValue, 50)
isEMACrossUp = ta.crossover(emaFast_ATG, emaSlow_ATG)
isEMACrossDown = ta.crossunder(emaFast_ATG, emaSlow_ATG)
// Enhanced Composite Score Calculation
scoreBuy = 0.0
scoreBuy += structSignalLong ? scoreStruct : 0.0
scoreBuy += momentumLong ? scoreMomentum : 0.0
scoreBuy += flashSignal ? weightFlash : 0.0
scoreBuy += blinkSignal ? weightBlink : 0.0
scoreBuy += volumeSpike_AVP ? scoreVolume : 0.0
scoreBuy += priceStrength_Long ? scorePriceAction : 0.0
scoreBuy += reversalTrigger_Long ? scoreReversal : 0.0
scoreBuy += emaAlignment_Bull ? weightTrendAlign : 0.0
scoreBuy += strongUpTrend ? weightTrendAlign : 0.0
scoreBuy += highRisk_Long ? -1.2 : 0.0
scoreBuy += signalGreenDot ? 1.0 : 0.0
scoreBuy += isAMCUp ? 0.8 : 0.0
scoreBuy += isVssBuy ? 1.5 : 0.0
scoreBuy += isEMACrossUp ? 1.0 : 0.0
scoreBuy += signalRedX ? -1.0 : 0.0
scoreSell = 0.0
scoreSell += structSignalShort ? scoreStruct : 0.0
scoreSell += momentumShort ? scoreMomentum : 0.0
scoreSell += flashSignal ? weightFlash : 0.0
scoreSell += blinkSignal ? weightBlink : 0.0
scoreSell += volumeSpike_AVP ? scoreVolume : 0.0
scoreSell += priceStrength_Short ? scorePriceAction : 0.0
scoreSell += reversalTrigger_Short ? scoreReversal : 0.0
scoreSell += emaAlignment_Bear ? weightTrendAlign : 0.0
scoreSell += strongDownTrend ? weightTrendAlign : 0.0
scoreSell += highRisk_Short ? -1.2 : 0.0
scoreSell += signalRedX ? 1.0 : 0.0
scoreSell += isAMCDown ? 0.8 : 0.0
scoreSell += isVssSell ? 1.5 : 0.0
scoreSell += isEMACrossDown ? 1.0 : 0.0
scoreSell += signalGreenDot ? -1.0 : 0.0
compositeBuySignal = enableComposite and scoreBuy >= thresholdCompositeBuy
compositeSellSignal = enableComposite and scoreSell >= thresholdCompositeSell
if compositeBuySignal and compositeSellSignal
compositeBuySignal := false
compositeSellSignal := false
= calculateCompositeSignals()
// Final Entry Signals
entryCompositeBuySignal = compositeBuySignal and ta.rising(emaFast_ATG, 2)
entryCompositeSellSignal = compositeSellSignal and ta.falling(emaFast_ATG, 2)
Calculates weighted scores from independent modules and activates signals only when threshold requirements are met.
2. Smart Exit Hold Evaluation System
evaluateSmartHold() =>
compositeBuyRecentCount = 0
compositeSellRecentCount = 0
for i = 0 to signalLookbackBars - 1
compositeBuyRecentCount += compositeBuySignal ? 1 : 0
compositeSellRecentCount += compositeSellSignal ? 1 : 0
avgVolume = ta.sma(volume, 20)
volumeSpike = volume > avgVolume * volMultiplier
// MTF Bull/Bear conditions
mtf_bull = mtf_emaFast_final > mtf_emaSlow_final
mtf_bear = mtf_emaFast_final < mtf_emaSlow_final
emaBackupDivergence = math.abs(mtf_emaFast_backup - mtf_emaSlow_backup) / mtf_emaSlow_backup
emaBackupStrong = emaBackupDivergence > 0.008
mtfConflict_Long = inLong and mtf_bear and emaBackupStrong
mtfConflict_Short = inShort and mtf_bull and emaBackupStrong
// Layer 1: ATR-Based Dynamic Threshold (Market Volatility Intelligence)
atr_raw = ta.atr(atrLen)
atrValue = na(atr_raw) ? close * 0.02 : atr_raw
atrRatio = atrValue / close
dynamicThreshold = atrRatio > 0.02 ? 1.0 : (atrRatio > 0.01 ? 1.5 : 2.8)
// Layer 2: ROI-Conditional Time Intelligence (Selective Pressure)
timeMultiplier_Long = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure
holdTimer_Long <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base
holdTimer_Long <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter
1.3 // Loss positions 17+ bars: +30% stricter
timeMultiplier_Short = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure
holdTimer_Short <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base
holdTimer_Short <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter
1.3 // Loss positions 17+ bars: +30% stricter
// Dual-Layer Threshold Calculation
baseThreshold_Long = mtfConflict_Long ? dynamicThreshold + 1.0 : dynamicThreshold
baseThreshold_Short = mtfConflict_Short ? dynamicThreshold + 1.0 : dynamicThreshold
timeAdjustedThreshold_Long = baseThreshold_Long * timeMultiplier_Long
timeAdjustedThreshold_Short = baseThreshold_Short * timeMultiplier_Short
// Final Smart Hold Decision with Dual-Layer Intelligence
smartHold_Long = not mtfConflict_Long and smartScoreLong >= timeAdjustedThreshold_Long and compositeBuyRecentCount >= signalMinCount
smartHold_Short = not mtfConflict_Short and smartScoreShort >= timeAdjustedThreshold_Short and compositeSellRecentCount >= signalMinCount
= evaluateSmartHold()
Evaluates whether to hold positions past TP1/TP2/TP3 levels based on continued signal strength, volume confirmation, and multi-timeframe trend alignment
HOW TO USE THE STRATEGY
Step 1: Initial Setup
Apply strategy to your preferred timeframe (backtested on 15M)
Enable "Use Heikin-Ashi Base" for smoother signals in volatile markets
"Show EMA Lines" and "Show Ichimoku Cloud" are enabled for visual context
Set default quantities to match your risk management (5% equity default)
Step 2: Signal Recognition
Visual Signal Guide:
Visual Signal Guide - Complete Reference:
🔶 Red Diamond: Bearish momentum breakdown - short reversal signal
🔷 Blue Diamond: Strong bullish momentum - long reversal signal
🔵 Blue Dot: Volume-confirmed directional move - trend continuation
🟢 Green Dot: Bullish EMA crossover - trend reversal confirmation
🟠 Orange X: Oversold reversal setup - counter-trend opportunity
❌ Red X: Bearish EMA breakdown - trend reversal warning
✡ Star Uprising: Strong bullish convergence
💥 Ultra Entry: Ultra-rapid downward momentum acceleration
▲ VSS Long: Velocity-based bullish momentum confirmation
▼ VSS Short: Velocity-based bearish momentum confirmation
Step 3: Entry Execution
For Long Positions:
1. ✅ EMA1 crossed above EMA2 exactly 3 bars ago [ta.crossover(ema1,ema2) ]
2. ✅ Current EMA structure: EMA1 > EMA2 (maintained)
3. ✅ Composite score ≥ 5.0 points (6.5+ for 5-minute timeframes)
4. ✅ Cooldown period completed (no recent stop losses)
5. ✅ Volume spike confirmation (green dot/blue dot signals)
6. ✅ Bullish candle closes above EMA structure
For Short Positions:
1. ✅ EMA1 crossed below EMA2 exactly 3 bars ago [ta.crossunder(ema1,ema2) ]
2. ✅ Current EMA structure: EMA1 < EMA2 (maintained)
3. ✅ Composite score ≥ 5.4 points (7.0+ for 5-minute timeframes)
4. ✅ Cooldown period completed (no recent stop losses)
5. ✅ Momentum breakdown (red diamond/red X signals)
6. ✅ Bearish candle closes below EMA structure
🎯 Critical Timing Note: The strategy requires EMA crossover to have occurred 3 bars prior to entry, not at the current bar. This attempts to avoid premature entries and may improve signal reliability.
Step 4: Reading Market Context
EMA Ribbon Interpretation:
All EMAs ascending = Strong uptrend context
EMAs 1-3 above EMAs 4-8 = Bullish structure
Tight EMA spacing = Low volatility/consolidation
Wide EMA spacing = High volatility/trending
Ichimoku Cloud Context:
Price above cloud = Bullish environment
Price below cloud = Bearish environment
Cloud color intensity = Momentum strength
Thick cloud = Strong support/resistance
THE SMART EXIT GRID SYSTEM
Smart Exit Grid Approach:
The Smart Exit Grid uses dynamic hold evaluation that continuously analyzes market conditions after position entry. This differs from traditional fixed profit targets by adapting exit timing based on real-time signal strength.
How Smart Exit Grid System Works
The system operates through three evaluation phases:
Smart Score Calculation:
The smart score calculation aggregates 22 signal components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. MTF analysis provides additional confirmation as a separate validation layer.
Signal Stack Management:
The per-tick signal accumulation system monitors 22 active signal types with MTF providing trend validation and conflict detection as a separate confirmation layer.
Take Profit Progression:
Smart Exit Activation:
The QRE system activates Smart Exit Grid immediately upon position entry. When strategy.entry() executes, the system initializes monitoring systems designed to track position progress.
Upon position opening, holdTimer begins counting, establishing the foundation for subsequent decisions. The Smart Exit Grid starts accumulating signals from entry, with all 22 signal components beginning real-time tracking when the trade opens.
The system operates on continuous evaluation where smartScoreLong and smartScoreShort calculate from the first tick after entry. QRE's approach is designed to capture market structure changes, trend deteriorations, or signal pattern shifts that can trigger protective exits even before the first take profit level is reached.
This activation creates a proactive position management framework. The 8-candle sliding window starts from entry, meaning that if market conditions change rapidly after entry - due to news events, liquidity shifts, or technical changes - the system can respond within the configured lookback period.
TP Markers as Reference Points:
The TP1, TP2, and TP3 levels function as reference points rather than mandatory exit triggers. When longTP1Hit or shortTP1Hit conditions activate, they serve as profit confirmation markers that inform the Smart Exit algorithm about achieved reward levels, but don't automatically initiate position closure.
These TP markers enhance the Smart Exit decision matrix by providing profit context to ongoing signal evaluation. The system recognizes when positions have achieved target returns, but the actual exit decision remains governed by continuous smart score evaluation and signal stack analysis.
TP2 Reached: Enhanced Monitoring
TP2 represents significant profit capture with additional monitoring features:
This approach is designed to help avoid premature profit-taking during trending conditions. If TP2 is reached but smartScoreLong remains above the dynamic threshold and the 8-candle sliding window shows persistent signals, the position continues holding. If market structure deteriorates before reaching TP2, the Smart Exit can trigger closure based on signal analysis.
The visual TP circles that appear when levels are reached serve as performance tracking tools, allowing users to see how frequently entries achieve various profit levels while understanding that actual exit timing depends on market structure analysis.
Risk Management Systems:
Operating independently from the Smart Exit Grid are two risk management systems: the Trap Wick Detection Protocol and the Stop Loss Mechanism. These systems maintain override authority over other exit logic.
The Trap Wick System monitors for conditionBearTrapExit during long positions and conditionBullTrapExit during short positions. When detected, these conditions trigger position closure with state reset, bypassing Smart Exit evaluations. This system recognizes that certain candlestick patterns may indicate reversal risk.
Volatility Exit Monitoring: The strategy monitors for isStrongBearCandle combined with conditionBearTrapExit, recognizing when market structure may be shifting.
Volume Validation: Before exiting on volatility, the strategy requires volume confirmation: volume > ta.sma(volume, 20) * 1.8. This is designed to filter exits on weak, low-volume movements.
The Stop Loss Mechanism operates through multiple triggers including traditional price-based stops (longSLHit, shortSLHit) and early exit conditions based on smart score deterioration combined with negative ROI. The early exit logic activates when smartScoreLong < 1.0 or smartScoreShort < 1.0 while realROI < -0.9%.
These risk management systems are designed so that risk scenarios can trigger protective closure with state reset across all 22 signal counters, TP tracking variables, and smart exit states.
This architecture - Smart Exit activation, TP markers as navigation tools, and independent risk management - creates a position management system that adapts to market conditions while maintaining risk discipline through dedicated protection protocols.
TP3 Reached: Enhanced Protection
Once TP3 is hit, the strategy shifts into enhanced monitoring:
EMA Structure Monitoring: isEMAStructureDown becomes a primary exit trigger
MTF Alignment: The higher timeframe receives increased consideration
Wick Trap Priority: conditionBearTrapExit becomes an immediate exit signal
Approach Differences:
Traditional Fixed Exits:
Exit at predetermined levels regardless of market conditions
May exit during trend continuation
May exit before trend completion
Limited adaptation to changing volatility
Smart Exit Grid Approach:
Adaptive timing based on signal conditions
Exits when supporting signals weaken
Multi-timeframe validation for trend confirmation
Volume confirmation requirements for holds
Structural monitoring for trend analysis
Dynamic ATR-Based Smart Score Threshold System
Market Volatility Adaptive Scoring
// Real-time ATR Analysis
atr_raw = ta.atr(atrLen)
atrValue = na(atr_raw) ? close * 0.02 : atr_raw
atrRatio = atrValue / close
// Three-Tier Dynamic Threshold Matrix
dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold
(atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard
2.8) // Low volatility: Higher threshold
The market volatility adaptive scoring calculates real-time ATR with a 2% fallback for new markets. The atrRatio represents the relationship between current volatility and price, creating a foundation for threshold adjustment.
The three-tier dynamic threshold matrix responds to market conditions by adjusting requirements based on volatility levels: lowering thresholds during high volatility periods above 2% ATR ratio to 1.0 points, maintaining standard requirements at 1.5 points for medium volatility between 1-2%, and raising standards to 2.8 points during low volatility periods below 1%.
Profit-Loss Adaptive Management:
The system applies different evaluation criteria based on position performance:
Winning Positions (realROI ≥ 0%):
→ timeMultiplier = 1.0 (No additional pressure)
→ Maintains base threshold requirements
→ Allows natural progression to TP2/TP3 levels
Losing Positions (realROI < 0%):
→ Progressive time pressure activated
→ Increasingly strict requirements over time
→ Faster decision-making on underperforming trades
ROI-Adaptive Smart Hold Decision Process:
The strategy uses a profit-loss adaptive system:
Winning Position Management (ROI ≥ 0%):
✅ Standard threshold requirements maintained
✅ No additional time-based pressure applied
✅ Allows positions to progress toward TP2/TP3 levels
✅ timeMultiplier remains at 1.0 regardless of hold duration
Losing Position Management (ROI < 0%):
⚠️ Time-based threshold adjustments activated
⚠️ Progressive increase in required signal strength over time
⚠️ Earlier exit evaluation on underperforming positions
⚠️ timeMultiplier increases from 1.0 → 1.1 → 1.3 based on hold duration
Real-Time Monitoring:
Monitor Analysis Table → "Smart" filter → "Score" vs "Dynamic Threshold"
Winning positions: Evaluation based on signal strength deterioration only
Losing positions: Evaluation considers both signal strength and progressive time adjustments
Breakeven positions (0% ROI): Treated as winning positions - no time adjustments
This approach differentiates between winning and losing positions in the hold evaluation process, requiring higher signal thresholds for extended holding of losing positions while maintaining standard requirements for winning ones.
ROI-Conditional Decision Matrix Examples:
Scenario 1 - Winning Position in Any Market:
Position ROI: +0.8% → timeMultiplier = 1.0 (regardless of hold time)
ATR Medium (1.2%) → dynamicThreshold = 1.5
Final Threshold = 1.5 × 1.0 = 1.5 points ✅ Position continues
Scenario 2 - Losing Position, Extended Hold:
Position ROI: -0.5% → Time pressure activated
Hold Time: 20 bars → timeMultiplier = 1.3
ATR Low (0.8%) → dynamicThreshold = 2.8
Final Threshold = 2.8 × 1.3 = 3.64 points ⚡ Enhanced requirements
Scenario 3 - Fresh Losing Position:
Position ROI: -0.3% → Time pressure activated
Hold Time: 5 bars → timeMultiplier = 1.0 (still early)
ATR High (2.1%) → dynamicThreshold = 1.0
Final Threshold = 1.0 × 1.0 = 1.0 points 📊 Recovery opportunity
Scenario 4 - Breakeven Position:
Position ROI: 0.0% → timeMultiplier = 1.0 (no pressure)
Hold Time: 15 bars → No time penalty applied
Final Threshold = dynamicThreshold only ⚖️ Neutral treatment
🔄8-Candle Sliding Window Signal Rotation System
Composite Signal Counting Mechanism
// Dynamic Lookback Window (configurable: default 8)
signalLookbackBars = input.int(8, "Composite Lookback Bars", minval=1, maxval=50)
// Rolling Signal Analysis
compositeBuyRecentCount = 0
compositeSellRecentCount = 0
for i = 0 to signalLookbackBars - 1
compositeBuyRecentCount += compositeBuySignal ? 1 : 0
compositeSellRecentCount += compositeSellSignal ? 1 : 0
Candle Flow Example (8-bar window):
→
✓ ✓ ✗ ✓ ✗ ✓ ✗ ✓ 🗑️
New Signal Count = 5/8 signals in window
Threshold Check: 5 ≥ signalMinCount (2) = HOLD CONFIRMED
Signal Decay & Refresh Mechanism
// Signal Persistence Tracking
if compositeBuyRecentCount >= signalMinCount
smartHold_Long = true
else
smartHold_Long = false
The composite signal counting operates through a configurable sliding window. The system maintains rolling counters that scan backward through the specified number of candles.
During each evaluation cycle, the algorithm iterates through historical bars, incrementing counters when composite signals are detected. This creates a dynamic signal persistence measurement where recent signal density determines holding decisions.
The sliding window rotation functions like a moving conveyor belt where new signals enter while the oldest signals drop off. For example, in an 8-bar window, if 5 out of 8 recent candles showed composite buy signals, and the minimum required count is 2, the system confirms the hold condition. As new bars form, the window slides forward, potentially changing the signal count and triggering exit conditions when signal density falls below the threshold.
Signal decay and refresh occur continuously where smartHold_Long remains true only when compositeBuyRecentCount exceeds signalMinCount. When recent signal density drops below the minimum requirement, the system switches to exit mode.
Advanced Signal Stack Management - 22-Signal Real-Time Evaluation
// Long Position Signal Stacking (calc_on_every_tick=true)
if inLong
// Primary Reversal Signals
if signalRedDiamond: signalCountRedDiamond += 1 // -0.5 points
if signalStarUprising: signalCountStarUprising += 1 // +1.5 points
if entryUltraShort: signalCountUltra += 1 // -1.0 points
// Trend Confirmation Signals
if strongUpTrend: trendUpCount_Long += 1 // +1.5 points
if emaAlignment_Bull: bullAlignCount_Long += 1 // +1.0 points
// Risk Assessment Signals
if highRisk_Long: riskCount_Long += 1 // -1.5 points
if topZone: tzoneCount_Long += 1 // -0.5 points
The per-tick signal accumulation system operates with calc_on_every_tick=true for real-time responsiveness. During long positions, the system monitors primary reversal signals where Red Diamond signals subtract 0.5 points as reversal warnings, Star Uprising adds 1.5 points for continuation signals, and Ultra Short signals deduct 1.0 points as counter-trend warnings.
Trend confirmation signals provide weighted scoring where strongUpTrend adds 1.5 points for aligned momentum, emaAlignment_Bull contributes 1.0 point for structural support, and various EMA-based confirmations contribute to the overall score. Risk assessment signals apply negative weighting where highRisk_Long situations subtract 1.5 points, topZone conditions deduct 0.5 points, and other risk factors create defensive scoring adjustments.
The smart score calculation aggregates all 22 components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. This score updates continuously, providing the foundation for hold-or-exit decisions.
MULTI-TIMEFRAME (MTF) SYSTEM
MTF Data Collection
The strategy requests higher timeframe data (default 30-minute) for trend confirmation:
= request.security(syminfo.tickerid, mtfTimeframe, , lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_off)
MTF Watchtower System - Implementation Logic
The system employs a timeframe discrimination protocol where currentTFInMinutes is compared against a 30-minute threshold. This creates different operational behavior between timeframes:
📊 Timeframe Testing Results:
30M+ charts: Full MTF confirmation → Tested with full features
15M charts: Local EMA + adjusted parameters → Standard testing baseline
5M charts: Local EMA only → Requires parameter adjustment
1M charts: High noise → Limited testing conducted
When the chart timeframe is 30 minutes or above, the strategy activates useMTF = true and requests external MTF data through request.security(). For timeframes below 30 minutes, including your 5-minute setup, the system deliberately uses local EMA calculations to avoid MTF lag and data inconsistencies.
The triple-layer data sourcing architecture works as follows: timeframes from 1 minute to 29 minutes rely on chart-based EMA calculations for immediate responsiveness. Timeframes of 30 minutes and above utilize MTF data through the security function, with a backup system that doubles the EMA length (emaLen * 2) if MTF data fails. When MTF data is unavailable or invalid, the system falls back to local EMA as the final safety net.
Data validation occurs through a pipeline where mtf_dataValid checks not only for non-null values but also verifies that EMA values are positive above zero. The system tracks data sources through mtf_dataSource which displays "MTF Data" for successful external requests, "Backup EMA" for failed MTF with backup system active, or "Chart EMA" for local calculations.
🔄 MTF Smart Score Caching & Recheck System
// Cache Update Decision Logic
mtfSmartIntervalSec = input.int(300, "Smart Grid Recheck Interval (sec)") // 5-minute cache
canRecheckSmartScore = na(timenow) ? false :
(na(lastCheckTime) or (timenow - lastCheckTime) > mtfSmartIntervalSec * 1000)
// Cache Management
if canRecheckSmartScore
lastCheckTime := timenow
cachedSmartScoreLong := smartScoreLong // Store current calculation
cachedSmartScoreShort := smartScoreShort
The performance-optimized caching system addresses the computational intensity of continuous MTF analysis through intelligent interval management. The mtfSmartIntervalSec parameter, defaulting to 300 seconds (5 minutes), determines cache refresh frequency. The system evaluates canRecheckSmartScore by comparing current time against lastCheckTime plus the configured interval.
When cache updates trigger, the system stores current calculations in cachedSmartScoreLong and cachedSmartScoreShort, creating stable reference points that reduce excessive MTF requests. This cache management balances computational efficiency with analytical accuracy.
The cache versus real-time hybrid system creates a multi-layered decision matrix where immediate signals update every tick for responsive market reaction, cached MTF scores refresh every 5 minutes for stability filtering, dynamic thresholds recalculate every bar for volatility adaptation, and sliding window analysis updates every bar for trend persistence validation.
This architecture balances real-time signal detection with multi-timeframe strategic validation, creating adaptive trading intelligence that responds immediately to market changes while maintaining strategic stability through cached analysis and volatility-adjusted decision thresholds.
⚡The Execution Section Deep Dive
The execution section represents the culmination of all previous systems – where analysis transforms into action.
🚪 Entry Execution: The Gateway Protocol
Primary Entry Validation:
Entry isn't just about seeing a signal – it's about passing through multiple security checkpoints, each designed to filter out low-quality opportunities.
Stage 1: Signal Confirmation
entryCompositeBuySignal must be TRUE for longs
entryCompositeSellSignal must be TRUE for shorts
Stage 2: Enhanced Entry Validation
The strategy employs an "OR" logic system that recognizes different types of market opportunities:
Path A - Trend Reversal Entry:
When emaTrendReversal_Long triggers, it indicates the market structure is shifting in favor of the trade direction. This isn't just about a single EMA crossing – it represents a change in market momentum that experienced traders recognize as potential high-probability setups.
Path B - Momentum Breakout Entry:
The strongBullMomentum condition is where QRE identifies accelerating market conditions:
Criteria:
EMA1 rising for 3+ candles AND
EMA2 rising for 2+ candles AND
Close > 10-period high
This combination captures those explosive moves where the market doesn't just trend – it accelerates, creating momentum-driven opportunities.
Path C - Recovery Entry:
When previous exit states are clean (no recent stop losses), the strategy permits entry based purely on signal strength. This pathway is designed to help avoid the strategy becoming overly cautious after successful trades.
🛡️ The Priority Exit Matrix: When Rules Collide
Not all exit signals are created equal. QRE uses a strict hierarchy that is designed to avoid conflicting signals from causing hesitation:
Priority Level 1 - Exception Exits (Immediate Action):
Condition: TP3 reached AND Wick Trap detected
Action: Immediate exit regardless of other signals
Rationale: Historical analysis suggests wick traps at TP3 may indicate potential reversals
Priority Level 2 - Structural Breakdown:
Condition: TP3 active AND EMA structure deteriorating AND Smart Score insufficient
Logic: isEMAStructureDown AND NOT smartHold_Long
This represents the strategy recognizing that the underlying market structure that justified the trade is failing. It's like a building inspector identifying structural issues – you don't wait for additional confirmation.
Priority Level 3 - Enhanced Volatility Exits:
Conditions: TP2 active AND Strong counter-candle AND Wick trap AND Volume spike
Logic: Multiple confirmation required to reduce false exits
Priority Level 4 - Standard Smart Score Exits:
Condition: Any TP level active AND smartHold evaluates to FALSE
This is the bread-and-butter exit logic where signal deterioration triggers exit
⚖️ Stop Loss Management: Risk Control Protocol
Dual Stop Loss System:
QRE provides two stop loss modes that users can select based on their preference:
Fixed Mode (Default - useAdaptiveSL = false):
Uses predetermined percentage levels regardless of market volatility:
- Long SL = entryPrice × (1 - fixedRiskP - slipBuffer)
- Short SL = entryPrice × (1 + fixedRiskP + slipBuffer)
- Default: 0.6% risk + 0.3% slippage buffer = 0.9% total stop
- Consistent and predictable stop loss levels
- Recommended for users who prefer stable risk parameters
Adaptive Mode (Optional - useAdaptiveSL = true):
Dynamic system that adjusts stop loss based on market volatility:
- Base Calculation uses ATR (Average True Range)
- Long SL = entryPrice × (1 - (ATR × atrMultSL) / entryPrice - slipBuffer)
- Short SL = entryPrice × (1 + (ATR × atrMultSL) / entryPrice + slipBuffer)
- Automatically widens stops during high volatility periods
- Tightens stops during low volatility periods
- Advanced users can enable for volatility-adaptive risk management
Trend Multiplier Enhancement (Both Modes):
When strongUpTrend is detected for long positions, the stop loss receives 1.5x breathing room. Strong trends often have deeper retracements before continuing. This is designed to help avoid the strategy being shaken out of active trades by normal market noise.
Mode Selection Guidance:
- New Users: Start with Fixed Mode for predictable risk levels
- Experienced Users: Consider Adaptive Mode for volatility-responsive stops
- Volatile Markets: Adaptive Mode may provide better stop placement
- Stable Markets: Fixed Mode often sufficient for consistent risk management
Early Exit Conditions:
Beyond traditional stop losses, QRE implements "smart stops" that trigger before price-based stops:
Early Long Exit: (smartScoreLong < 1.0 OR prev5BearCandles) AND realROI < -0.9%
🔄 State Management: The Memory System
Complete State Reset Protocol:
When a position closes, QRE doesn't just wipe the slate clean – it performs a methodical reset:
TP State Cleanup:
All Boolean flags: tp1/tp2/tp3HitBefore → FALSE
All Reached flags: tp1/tp2/tp3Reached → FALSE
All Active flags: tp1/tp2/tp3HoldActive → FALSE
Signal Counter Reset:
Every one of the 22 signal counters returns to zero.
This is designed to avoid signal "ghosting" where old signals influence new trades.
Memory Preservation:
While operational states reset, certain information is preserved for learning:
killReasonLong/Short: Why did this trade end?
lastExitWasTP1/TP2/TP3: What was the exit quality?
reEntryCount: How many consecutive re-entries have occurred?
🔄 Re-Entry Logic: The Comeback System
Re-Entry Conditions Matrix:
QRE implements a re-entry system that recognizes not all exits are created equal:
TP-Based Re-Entry (Enabled):
Criteria: Previous exit was TP1, TP2, or TP3
Cooldown: Minimal or bypassed entirely
Logic: Target-based exits indicate potentially viable market conditions
EMA-Based Re-Entry (Conditional):
Criteria: Previous exit was EMA-based (structural change)
Requirements: Must wait for EMA confirmation in new direction
Minimum Wait: 5 candles
Advanced Re-Entry Features:
When adjustReEntryTargets is enabled, the strategy becomes more aggressive with re-entries:
Target Adjustment: TP1 multiplied by reEntryTP1Mult (default 2.0)
Stop Adjustment: SL multiplied by reEntrySLMult (default 1.5)
Logic: If we're confident enough to re-enter, we should be confident enough to hold for bigger moves
Performance Tracking: Strategy tracks re-entry win rate, average ROI, and total performance separately from initial entries for optimization analysis.
📊 Exit Reason Analytics: Learning from Every Trade
Kill Reason Tracking:
Every exit is categorized and stored:
"TP3 Exit–Wick Trap": Exit at target level with wick pattern detection
"Smart Exit–EMA Down": Structural breakdown exit
"Smart Exit–Volatility": Volatility-based protection exit
"Exit Post-TP1/TP2/TP3": Standard smart exit progression
"Long SL Exit" / "Short SL Exit": Stop loss exits
Performance Differentiation:
The strategy tracks performance by exit type, allowing for continuous analysis:
TP-based exits: Achieved target levels, analyze for pattern improvement
EMA-based exits: Mixed results, analyze for pattern improvement
SL-based exits: Learning opportunities, adjust entry criteria
Volatility exits: Protective measures, monitor performance
🎛️ Trailing Stop Implementation:
Conditional Trailing Activation:
Activation Criteria: Position profitable beyond trailingStartPct AND
(TP hold active OR re-entry trade)
Dynamic Trailing Logic:
Unlike simple trailing stops, QRE's implementation considers market context:
Trending Markets: Wider trail offsets to avoid whipsaws
Volatile Markets: Tighter offsets to protect gains
Re-Entry Trades: Enhanced trailing to maximize second-chance opportunities
Return-to-Entry Protection:
When deactivateOnReturn is enabled, the strategy will close positions that return to entry level after being profitable. This is designed to help avoid the frustration of watching profitable trades turn into losers.
🧠 How It All Works Together
The beauty of QRE lies not in any single component, but in how everything integrates:
The Entry Decision: Multiple pathways are designed to help identify opportunities while maintaining filtering standards.
The Progression System: Each TP level unlocks new protection features, like achieving ranks in a video game.
The Exit Matrix: Prioritized decision-making aims to reduce analysis paralysis while providing appropriate responses to different market conditions.
The Memory System: Learning from each trade while preventing contamination between separate opportunities.
The Re-Entry Logic: Re-entry system that balances opportunity with risk management.
This creates a trading system where entry conditions filter for quality, progression systems adapt to changing market conditions, exit priorities handle conflicting signals intelligently, memory systems learn from each trade cycle, and re-entry logic maximizes opportunities while managing risk exposure.
📊 ANALYSIS TABLE INTERPRETATION -
⚙️ Enabling Analysis Mode
Navigate to strategy settings → "Testing & Analysis" → Enable "Show Analysis Table". The Analysis Table displays different information based on the selected test filter and provides real-time insight into all strategy components, helping users understand current market conditions, position status, and system decision-making processes.
📋 Filter Mode Interpretations
"All" Mode (Default View):
Composite Section:
Buy Score: Aggregated strength from all 22 bullish signals (threshold 5.0+ triggers entry consideration)
Sell Score: Aggregated strength from all 22 bearish signals (threshold 5.4+ triggers entry consideration)
APEX Filters:
ATG Trend: Shows current trend direction analysis
Indicates whether momentum filters are aligned for directional bias
ReEntry Section:
Most Recent Exit: Displays exit type and timeframe since last position closure
Status: Shows if ReEntry system is Ready/Waiting/Disabled
Count: Current re-entry attempts versus maximum allowed attempts
Position Section (When Active):
Status: Current position state (LONG/SHORT/FLAT)
ROI: Dual calculation showing Custom vs Real ROI percentages
Entry Price: Original position entry level
Current Price: Live market price for comparison
TP Tracking: Progress toward profit targets
"Smart" Filter (Critical for Active Positions):
Smart Exit Section:
Hold Timer: Time elapsed since position opened (bar-based counting)
Status: Whether Smart Exit Grid is Enabled/Disabled
Score: Current smart score calculation from 22-component matrix
Dynamic Threshold: ATR-based minimum score required for holding
Final Threshold: Time and ROI-adjusted threshold actually used for decisions
Score Check: Pass/Fail based on Score vs Final Threshold comparison
Smart Hold: Current hold decision status
Final Hold: Final recommendation based on all factors
🎯 Advanced Smart Exit Debugging - ROI & Time-Based Threshold System
Understanding the Multi-Layer Threshold System:
Layer 1: Dynamic Threshold (ATR-Based)
atrRatio = ATR / close
dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold
(atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard
2.8) // Low volatility: Higher threshold
Layer 2: Time Multiplier (ROI & Duration-Based)
Winning Positions (ROI ≥ 0%):
→ timeMultiplier = 1.0 (No time pressure, regardless of hold duration)
Losing Positions (ROI < 0%):
→ holdTimer ≤ 8 bars: timeMultiplier = 1.0 (Early stage, standard requirements)
→ holdTimer 9-16 bars: timeMultiplier = 1.1 (10% stricter requirements)
→ holdTimer 17+ bars: timeMultiplier = 1.3 (30% stricter requirements)
Layer 3: Final Threshold Calculation
finalThreshold = dynamicThreshold × timeMultiplier
Examples:
- Winning Position: 2.8 × 1.0 = 2.8 (Always standard)
- Losing Position (Early): 2.8 × 1.0 = 2.8 (Same as winning initially)
- Losing Position (Extended): 2.8 × 1.3 = 3.64 (Much stricter)
Real-Time Debugging Display:
Smart Exit Section shows:
Score: 3.5 → Current smartScoreLong/Short value
Dynamic Threshold: 2.8 → Base ATR-calculated threshold
Final Threshold: 3.64 (ATR×1.3) → Actual threshold used for decisions
Score Check: FAIL (3.5 vs 3.64) → Pass/Fail based on final comparison
Final Hold: NO HOLD → Actual system decision
Position Status Indicators:
Winner + Early: ATR×1.0 (No pressure)
Winner + Extended: ATR×1.0 (No pressure - winners can run indefinitely)
Loser + Early: ATR×1.0 (Recovery opportunity)
Loser + Extended: ATR×1.1 or ATR×1.3 (Increasing pressure to exit)
MTF Section:
Data Source: Shows whether using MTF Data/EMA Backup/Local EMA
Timeframe: Configured watchtower timeframe setting
Data Valid: Confirms successful MTF data retrieval status
Trend Signal: Higher timeframe directional bias analysis
Close Price: MTF price data availability confirmation
"Composite" Filter:
Composite Section:
Buy Score: Real-time weighted scoring from multiple indicators
Sell Score: Opposing directional signal strength
Threshold: Minimum scores required for signal activation
Components:
Flash/Blink: Momentum acceleration indicators (F = Flash active, B = Blink active)
Individual filter contributions showing which specific signals are firing
"ReEntry" Filter:
ReEntry System:
System: Shows if re-entry feature is Enabled/Disabled
Eligibility: Conditions for new entries in each direction
Performance: Success metrics of re-entry attempts when enabled
🎯 Key Status Indicators
Status Column Symbols:
✓ = Condition met / System active / Signal valid
✗ = Condition not met / System inactive / No signal
⏳ = Cooldown active (waiting period)
✅ = Ready state / Good condition
🔄 = Processing / Transitioning state
🔍 Critical Reading Guidelines
For Active Positions - Smart Exit Priority Reading:
1. First Check Position Type:
ROI ≥ 0% = Winning Position (Standard requirements)
ROI < 0% = Losing Position (Progressive requirements)
2. Check Hold Duration:
Early Stage (≤8 bars): Standard multiplier regardless of ROI
Extended Stage (9-16 bars): Slight pressure on losing positions
Long Stage (17+ bars): Strong pressure on losing positions
3. Score vs Final Threshold Analysis:
Score ≥ Final Threshold = HOLD (Continue position)
Score < Final Threshold = EXIT (Close position)
Watch for timeMultiplier changes as position duration increases
4. Understanding "Why No Hold?"
Common scenarios when Score Check shows FAIL:
Losing position held too long (timeMultiplier increased to 1.1 or 1.3)
Low volatility period (dynamic threshold raised to 2.8)
Signal deterioration (smart score dropped below required level)
MTF conflict (higher timeframe opposing position direction)
For Entry Signal Analysis:
Composite Score Reading: Signal strength relative to threshold requirements
Component Analysis: Individual filter contributions to overall score
EMA Structure: Confirm 3-bar crossover requirement met
Cooldown Status: Ensure sufficient time passed since last exit
For ReEntry Opportunities (when enabled):
System Status: Availability and eligibility for re-engagement
Exit Type Analysis: TP-based exits enable immediate re-entry, SL-based exits require cooldown
Condition Monitoring: Requirements for potential re-entry signals
Debugging Common Issues:
Issue: "Score is high but no hold?"
→ Check Final Threshold vs Score (not Dynamic Threshold)
→ Losing position may have increased timeMultiplier
→ Extended hold duration applying pressure
Issue: "Why different thresholds for same score?"
→ Position ROI status affects multiplier
→ Time elapsed since entry affects multiplier
→ Market volatility affects base threshold
Issue: "MTF conflicts with local signals?"
→ Higher timeframe trend opposing position
→ System designed to exit on MTF conflicts
→ Check MTF Data Valid status
⚡ Performance Optimization Notes
For Better Performance:
Analysis table updates may impact performance on some devices
Use specific filters rather than "All" mode for focused monitoring
Consider disabling during live trading for optimal chart performance
Enable only when needed for debugging or analysis
Strategic Usage:
Monitor "Smart" filter when positions are active for exit timing decisions
Use "Composite" filter during setup phases for signal strength analysis
Reference "ReEntry" filter after position closures for re-engagement opportunities
Track Final Threshold changes to understand exit pressure evolution
Advanced Debugging Workflow:
Position Entry Analysis:
Check Composite score vs threshold
Verify EMA crossover timing (3 bars prior)
Confirm cooldown completion
Hold Decision Monitoring:
Track Score vs Final Threshold progression
Monitor timeMultiplier changes over time
Watch for MTF conflicts
Exit Timing Analysis:
Identify which threshold layer caused exit
Track performance by exit type
Analyze re-entry eligibility
This analysis system provides transparency into strategy decision-making processes, allowing users to understand how signals are generated and positions are managed according to the programmed logic during various market conditions and position states.
SIGNAL TYPES AND CHARACTERISTICS
🔥 Core Momentum Signals
Flash Signal
Calculation: ta.rma(math.abs(close - close ), 5) > ta.sma(math.abs(close - close ), 7)
Purpose: Detects sudden price acceleration using smoothed momentum comparison
Characteristics: Triggers when recent price movement exceeds historical average movement
Usage: Primary momentum confirmation across multiple composite calculations
Weight: 1.3 points in composite scoring
Blink Signal
Calculation: math.abs(ta.change(close, 1)) > ta.sma(math.abs(ta.change(close, 1)), 5)
Purpose: Identifies immediate price velocity spikes
Characteristics: More sensitive than Flash, captures single-bar momentum bursts
Usage: Secondary momentum confirmation, often paired with Flash
Weight: 1.3 points in composite scoring
⚡ Advanced Composite Signals
Apex Pulse Signal
Calculation: apexAngleValue > 30 or apexAngleValue < -30
Purpose: Detects extreme EMA angle momentum
Characteristics: Identifies when trend angle exceeds ±30 degrees
Usage: Confirms directional momentum strength in trend-following scenarios
Pressure Surge Signal
Calculation: volSpike_AVP and strongTrendUp_ATG
Purpose: Combines volume expansion with trend confirmation
Characteristics: Requires both volume spike and strong uptrend simultaneously
Usage: bullish signal for trend continuation
Shift Wick Signal
Calculation: ta.crossunder(ema1, ema2) and isWickTrapDetected and directionFlip
Purpose: Detects bearish reversal with wick trap confirmation
Characteristics: Combines EMA crossunder with upper wick dominance and directional flip
Usage: Reversal signal for trend change identification
🛡️ Trap Exit Protection Signals
Bear Trap Exit
Calculation: isUpperWickTrap and isBearEngulfNow
Conditions: Previous bullish candle with 80%+ upper wick, followed by current bearish engulfing
Purpose: Emergency exit signal for long positions
Priority: Highest - overrides all other hold conditions
Action: Immediate position closure with full state reset
Bull Trap Exit
Calculation: isLowerWickTrap and isBullEngulfNow
Conditions: Previous bearish candle with 80%+ lower wick, followed by current bullish engulfing
Purpose: Emergency exit signal for short positions
Priority: Highest - overrides all other hold conditions
Action: Immediate position closure with full state reset
📊 Technical Analysis Foundation Signals
RSI-MFI Hybrid System
Base Calculation: (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2
Oversold Threshold: < 35
Overbought Threshold: > 65
Weak Condition: < 35 and declining
Strong Condition: > 65 and rising
Usage: Momentum confirmation and reversal identification
ADX-DMI Trend Classification
Strong Up Trend: (adx > 25 and diplus > diminus and (diplus - diminus) > 5) or (ema1 > ema2 and ema2 > ema3 and ta.rising(ema2, 3))
Strong Down Trend: (adx > 20 and diminus > diplus - 5) or (ema1 < ema2 and ta.falling(ema1, 3))
Trend Weakening: adx < adx and adx < adx
Usage: Primary trend direction confirmation
Bollinger Band Squeeze Detection
Calculation: bbWidth < ta.lowest(bbWidth, 20) * 1.2
Purpose: Identifies low volatility periods before breakouts
Usage: Entry filter - avoids trades during consolidation
🎨 Visual Signal Indicators
Red X Signal
Calculation: isBearCandle and ta.crossunder(ema1, ema2)
Visual: Red X above price
Purpose: Bearish EMA crossunder with confirming candle
Composite Weight: +1.0 for short positions, -1.0 for long positions
Characteristics: Simple but effective trend change indicator
Green Dot Signal
Calculation: isBullCandle and ta.crossover(ema1, ema2)
Visual: Green dot below price
Purpose: Bullish EMA crossover with confirming candle
Composite Weight: +1.0 for long positions, -1.0 for short positions
Characteristics: Entry confirmation for trend-following strategies
Blue Diamond Signal
Trigger Conditions: amcBuySignal and score >= 4
Scoring Components: 11 different technical conditions
Key Requirements: AMC bullish + momentum rise + EMA expansion + volume confirmation
Visual: Blue diamond below price
Purpose: Bullish reversal or continuation signal
Characteristics: Multi-factor confirmation requiring 4+ technical alignments
Red Diamond Signal
Trigger Conditions: amcSellSignal and score >= 5
Scoring Components: 11 different technical conditions (stricter than Blue Diamond)
Key Requirements: AMC bearish + momentum crash + EMA compression + volume decline
Visual: Red diamond above price
Purpose: Potential bearish reversal or continuation signal
Characteristics: Requires higher threshold (5 vs 4) for more selective triggering
🔵 Specialized Detection Signals
Blue Dot Signal
Calculation: volumePulse and isCandleStrong and volIsHigh
Requirements: Volume > 2.0x MA, strong candle body > 35% of range, volume MA > 55
Purpose: Volume-confirmed momentum signal
Visual: Blue dot above price
Characteristics: Volume-centric signal for high-liquidity environments
Orange X Signal
Calculation: Complex multi-factor oversold reversal detection
Requirements: AMC oversold + wick trap + flash/blink + RSI-MFI oversold + bullish flip
Purpose: Oversold bounce signal with multiple confirmations
Visual: Orange X below price
Characteristics: Reversal signal requiring 5+ simultaneous conditions
VSS (Velocity Signal System)
Components: Volume spike + EMA angle + trend direction
Buy Signal: vssTrigger and vssTrendDir == 1
Sell Signal: vssTrigger and vssTrendDir == -1
Visual: Green/Red triangles
Purpose: Velocity-based momentum detection
Characteristics: Fast-response signal for momentum trading
⭐ Elite Composite Signals
Star Uprising Signal
Base Requirements: entryCompositeBuySignal and echoBodyLong and strongUpTrend and isAMCUp
Additional Confirmations: RSI hybrid strong + not high risk
Special Conditions: At bottom zone OR RSI bottom bounce OR strong volume bounce
Visual: Star symbol below price
Purpose: Bullish reversal signal from oversold conditions
Characteristics: Most selective bullish signal requiring multiple confirmations
Ultra Short Signal
Scoring System: 7-component scoring requiring 4+ points
Key Components: EMA trap + volume decline + RSI weakness + composite confirmation
Additional Requirements: Falling EMA structure + volume spike + flash confirmation
Visual: Explosion emoji above price
Purpose: Aggressive short entry for trend reversal or continuation
Characteristics: Complex multi-layered signal for experienced short selling
🎯 Composite Signal Architecture
Enhanced Composite Scoring
Long Composite: 15+ weighted components including structure, momentum, flash/blink, volume, price action, reversal triggers, trend alignment
Short Composite: Mirror structure with bearish bias
Threshold: 5.0 points required for signal activation
Conflict Resolution: If both long and short signals trigger simultaneously, both are disabled
Final Validation: Requires EMA momentum confirmation (ta.rising(emaFast_ATG, 2) for longs, ta.falling(emaFast_ATG, 2) for shorts)
Risk Assessment Integration
High Risk Long: RSI > 70 OR close > upper Bollinger Band 80%
High Risk Short: RSI < 30 OR close < lower Bollinger Band 80%
Zone Analysis: Top zone (95% of 50-bar high) vs Bottom zone (105% of 50-bar low)
Risk Penalty: High risk conditions subtract 1.5 points from composite scores
This signal architecture creates a multi-layered detection system where simple momentum signals provide foundation, technical analysis adds structure, visual indicators offer clarity, specialized detectors capture different market conditions, and composite signals identify potential opportunities while integrated risk assessment is designed to filter risky entries.
VISUAL FEATURES SHOWCASE
Ichimoku Cloud Visualization
Dynamic Color Intensity: Cloud transparency adapts to momentum strength - darker colors indicate stronger directional moves, while lighter transparency shows weakening momentum phases.
Gradient Color Mapping: Bullish momentum renders blue-purple spectrum with increasing opacity, while bearish momentum displays corresponding color gradients with intensity-based transparency.
Real-time Momentum Feedback: Color saturation provides immediate visual feedback on market structure strength, allowing traders to assess levels at a glance without additional indicators.
EMA Ribbon Bands
The 8-level exponential moving average system creates a comprehensive trend structure map with gradient color coding.
Signal Type Visualization
STRATEGY PROPERTIES & BACKTESTING DISCLOSURE
📊 Default Strategy Configuration:
✅ Initial Capital: 100,000 USD (realistic for average traders)
✅ Commission: 0.075% per trade (realistic exchange fees)
✅ Slippage: 3 ticks (market impact consideration)
✅ Position Size: 5% equity per trade (sustainable risk level)
✅ Pyramiding: Disabled (single position management)
✅ Sample Size: 185 trades over 12-month backtesting period
✅ Risk Management: Adaptive stop loss with maximum 1% risk per trade
COMPREHENSIVE BACKTESTING RESULTS
Testing Period & Market Conditions:
Backtesting Period: June 25, 2024 - June 25, 2025 (12 months)
Timeframe: 15-minute charts (MTF system active)
Market: BTCUSDT (Bitcoin/Tether)
Market Conditions: Full market cycle including volatility periods
Deep Backtesting: Enabled for maximum accuracy
📈 Performance Summary:
Total Return: +2.19% (+2,193.59 USDT)
Total Trades Executed: 185 trades
Win Rate: 34.05% (63 winning trades out of 185)
Profit Factor: 1.295 (gross profit ÷ gross loss)
Maximum Drawdown: 0.65% (653.17 USDT)
Risk-Adjusted Returns: Consistent with conservative risk management approach
📊 Detailed Trade Analysis:
Position Distribution:
Long Positions: 109 trades (58.9%) | Win Rate: 36.70%
Short Positions: 76 trades (41.1%) | Win Rate: 30.26%
Average Trade Duration: Optimized for 15-minute timeframe efficiency
Profitability Metrics:
Average Profit per Trade: 11.74 USDT (0.23%)
Average Winning Trade: 151.17 USDT (3.00%)
Average Losing Trade: 60.27 USDT (1.20%)
Win/Loss Ratio: 2.508 (winners are 2.5x larger than losses)
Largest Single Win: 436.02 USDT (8.69%)
Largest Single Loss: 107.41 USDT (controlled risk management)
💰 Financial Performance Breakdown:
Gross Profit: 9,523.93 USDT (9.52% of capital)
Gross Loss: 7,352.48 USDT (7.35% of capital)
Net Profit After Costs: 2,171.44 USDT (2.17%)
Commission Costs: 1,402.47 USDT (realistic trading expenses)
Maximum Equity Run-up: 2,431.66 USDT (2.38%)
⚖️ Risk Management Validation:
Maximum Drawdown: 0.65% showing controlled risk management
Drawdown Recovery: Consistent equity curve progression
Risk per Trade: Successfully maintained below 1.5% per position
Position Sizing: 5% equity allocation proved sustainable throughout testing period
📋 Strategy Performance Characteristics:
✅ Strengths Demonstrated:
Controlled Risk: Maximum drawdown well below industry standards (< 1%)
Positive Expectancy: Win/loss ratio of 2.5+ creates profitable edge
Consistent Performance: Steady equity curve without extreme volatility
Realistic Costs: Includes actual commission and slippage impacts
Sample Size: 185 trades during testing period
⚠️ Performance Considerations:
Win Rate: 34% win rate requires discipline to follow system signals
Market Dependency: Performance may vary significantly in different market conditions
Timeframe Sensitivity: Optimized for 15-minute charts; other timeframes may show different results
Slippage Impact: Real trading conditions may affect actual performance
📊 Benchmark Comparison:
Strategy Return: +2.19% over 12 months
Buy & Hold Bitcoin: +71.12% over same period
Strategy Advantage: Significantly lower drawdown and volatility
Risk-Adjusted Performance: Different risk profile compared to holding cryptocurrency
🎯 Real-World Application Insights:
Expected Trading Frequency:
Average: 15.4 trades per month (185 trades ÷ 12 months)
Weekly Frequency: Approximately 3-4 trades per week
Active Management: Requires regular monitoring during market hours
Capital Requirements:
Minimum Used in Testing: $10,000 for sustainable position sizing
Tested Range: $50,000-$100,000 for comfortable risk management
Commission Impact: 0.075% per trade totaled 1.4% of capital over 12 months
⚠️ IMPORTANT BACKTESTING DISCLAIMERS:
📈 Performance Reality:
Past performance does not guarantee future results. Backtesting results represent hypothetical performance and may not reflect actual trading outcomes due to market changes, execution differences, and emotional factors.
🔄 Market Condition Dependency:
This strategy's performance during the tested period may not be representative of performance in different market conditions, volatility regimes, or trending vs. sideways markets.
💸 Cost Considerations:
Actual trading costs may vary based on broker selection, market conditions, and trade size. Commission rates and slippage assumptions may differ from real-world execution.
🎯 Realistic Expectations:
The 34% win rate requires psychological discipline to continue following signals during losing streaks. Risk management and position sizing are critical for replicating these results.
⚡ Technology Dependencies:
Strategy performance assumes reliable internet connection, platform stability, and timely signal execution. Technical failures may impact actual results.
CONFIGURATION OPTIMIZATION
5-Minute Timeframe Optimization (Advanced Users Only)
⚠️ Important Warning: 5-minute timeframes operate without MTF confirmation, resulting in reduced signal quality and higher false signal rates.
Example 5-Minute Parameters:
Composite Thresholds: Long 6.5, Short 7.0 (vs 15M default 5.0/5.4)
Signal Lookback Bars: 12 (vs 15M default 8)
Volume Multiplier: 2.2 (vs 15M default 1.8)
MTF Timeframe: Disabled (automatic below 30M)
Risk Management Adjustments:
Position Size: Reduce to 3% (vs 5% default)
TP1: 0.8%, TP2: 1.2%, TP3: 2.0% (tighter targets)
SL: 0.8% (tighter stop loss)
Cooldown Minutes: 8 (vs 5 default)
Usage Notes for 5-Minute Trading:
- Wait for higher composite scores before entry
- Require stronger volume confirmation
- Monitor EMA structure more closely
15-Minute Scalping Setup:
TP1: 1.0%, TP2: 1.5%, TP3: 2.5%
Composite Threshold: 5.0 (higher filtering)
TP ATR Multiplier: 7.0
SL ATR Multiplier: 2.5
Volume Multiplier: 1.8 (requires stronger confirmation)
Hold Time: 2 bars minimum
3-Hour Swing Setup:
TP1: 2.0%, TP2: 4.0%, TP3: 8.0%
Composite Threshold: 4.5 (more signals)
TP ATR Multiplier: 8.0
SL ATR Multiplier: 3.2
Volume Multiplier: 1.2
Hold Time: 6 bars minimum
Market-Specific Adjustments
High Volatility Periods:
Increase ATR multipliers (TP: 2.0x, SL: 1.2x)
Raise composite thresholds (+0.5 points)
Reduce position size
Enable cooldown periods
Low Volatility Periods:
Decrease ATR multipliers (TP: 1.2x, SL: 0.8x)
Lower composite thresholds (-0.3 points)
Standard position sizing
Disable extended cooldowns
News Events:
Temporarily disable strategy 30 minutes before major releases
Increase volume requirements (2.0x multiplier)
Reduce position sizes by 50%
Monitor for unusual price action
RISK MANAGEMENT
Dual ROI System: Adaptive vs Fixed Mode
Adaptive RR Mode:
Uses ATR (Average True Range) for automatic adjustment
TP1: 1.0x ATR from entry price
TP2: 1.5x ATR from entry price
TP3: 2.0x ATR from entry price
Stop Loss: 1.0x ATR from entry price
Automatically adjusts to market volatility
Fixed Percentage Mode:
Uses predetermined percentage levels
TP1: 1.0% (default)
TP2: 1.5% (default)
TP3: 2.5% (default)
Stop Loss: 0.9% total (0.6% risk tolerance + 0.3% slippage buffer)(default)
Consistent levels regardless of volatility
Mode Selection: Enable "Use Adaptive RR" for ATR-based targets, disable for fixed percentages. Adaptive mode works better in varying volatility conditions, while fixed mode provides predictable risk/reward ratios.
Stop Loss Management
In Adaptive SL Mode:
Automatically scales with market volatility
Tight stops during low volatility (smaller ATR)
Wider stops during high volatility (larger ATR)
Include 0.3% slippage buffer in both modes
In Fixed Mode:
Consistent percentage-based stops
2% for crypto, 1.5% for forex, 1% for stocks
Manual adjustment needed for different market conditions
Trailing Stop System
Configuration:
Enable Trailing: Activates dynamic stop loss adjustment
Start Trailing %: Profit level to begin trailing (default 1.0%)
Trailing Offset %: Distance from current price (default 0.5%)
Close if Return to Entry: Optional immediate exit if price returns to entry level
Operation: Once position reaches trailing start level, stop loss automatically adjusts upward (longs) or downward (shorts) maintaining the offset distance from favorable price movement.
Timeframe-Specific Risk Considerations
15-Minute and Above (Tested):
✅ Full MTF system active
✅ Standard risk parameters apply
✅ Backtested performance metrics valid
✅ Standard position sizing (5%)
5-Minute Timeframes (Advanced Only):
⚠️ MTF system inactive - local signals only
⚠️ Higher false signal rate expected
⚠️ Reduced position sizing preferred (3%)
⚠️ Tighter stop losses required (0.8% vs 1.2%)
⚠️ Requires parameter optimization
⚠️ Monitor performance closely
1-Minute Timeframes (Limited Testing):
❌ Excessive noise levels
❌ Strategy not optimized for this frequency
Risk Management Practices
Allocate no more than 5% of your total investment portfolio to high-risk trading
Never trade with funds you cannot afford to lose
Thoroughly backtest and validate the strategy with small amounts before full implementation
Always maintain proper risk management and stop-loss settings
IMPORTANT DISCLAIMERS
Performance Disclaimer
Past performance does not guarantee future results. All trading involves substantial risk of loss. This strategy is provided for informational purposes and does not constitute financial advice.
Market Risk
Cryptocurrency and forex markets are highly volatile. Prices can move rapidly against positions, resulting in significant losses. Users should never risk more than they can afford to lose.
Strategy Limitations
This strategy relies on technical analysis and may not perform well during fundamental market shifts, news events, or unprecedented market conditions. No trading strategy can guarantee 100% success or eliminate the risk of loss.
Legal Compliance
You are responsible for compliance with all applicable regulations and laws in your jurisdiction. Consult with licensed financial professionals when necessary.
User Responsibility
Users are responsible for their own trading decisions, risk management, and compliance with applicable regulations in their jurisdiction.
VWAP Volume Profile [BigBeluga]🔵 OVERVIEW
VWAP Volume Profile is an advanced hybrid of the VWAP and volume profile concepts. It visualizes how volume accumulates relative to VWAP movement—separating rising (+VWAP) and declining (−VWAP) activity into two mirrored horizontal profiles. It highlights the dominant price bins (POCs) where volume peaked during each directional phase, helping traders spot hidden accumulation or distribution zones.
🔵 CONCEPTS
VWAP-Driven Profiling: Unlike standard volume profiles, this tool segments volume based on VWAP movement—accumulating positive or negative volume depending on VWAP slope.
Dual-Sided Profiles: Profiles expand horizontally to the right of price. Separate bins show rising (+) and falling (−) VWAP volume.
Bin Logic: Volume is accumulated into defined horizontal bins based on VWAP’s position relative to price ranges.
Gradient Coloring: Volume bars are colored with a dynamic gradient to emphasize intensity and direction.
POC Highlighting: The highest-volume bin in each profile type (+/-) is marked with a transparent box and label.
Contextual VWAP Line: VWAP is plotted and dynamically colored (green = rising, orange = falling) for instant trend context.
Candle Overlay: Price candles are recolored to match the VWAP slope for full visual integration.
🔵 FEATURES
Dual-sided horizontal volume profiles based on VWAP slope.
Supports rising VWAP , falling VWAP , or both simultaneously.
Customizable number of bins and lookback period.
Dynamically colored VWAP line to show rising/falling bias.
POC detection and labeling with volume values for +VWAP and −VWAP.
Candlesticks are recolored to match VWAP bias for intuitive momentum tracking.
Optional background boxes with customizable styling.
Adaptive volume scaling to normalize bar length across markets.
🔵 HOW TO USE
Use POC zones to identify high-volume consolidation areas and potential support/resistance levels.
Watch for shifts in VWAP direction and observe how volume builds differently during uptrends and downtrends.
Use the gradient profile shape to detect accumulation (widening volume below price) or distribution (above price).
Use candle coloring for real-time confirmation of VWAP bias.
Adjust the profile period or bin count to fit your trading style (e.g., intraday scalping or swing trading).
🔵 CONCLUSION
VWAP Volume Profile merges two essential concepts—volume and VWAP—into a single, high-precision tool. By visualizing how volume behaves in relation to VWAP movement, it uncovers hidden dynamics often missed by traditional profiles. Perfect for intraday and swing traders who want a more nuanced read on market structure, trend strength, and volume flow.
Volume Orderflow Delta @MaxMaseratiVolume Orderflow Delta @MaxMaserati
🎯 INSTITUTIONAL ORDERFLOW ANALYSIS TOOL
This advanced indicator reveals where BIG MONEY (institutions, hedge funds, smart money) is actively trading by analyzing sophisticated volume patterns and order flow dynamics. It goes far beyond basic volume analysis to detect specific institutional behaviors and trading patterns.
📊 CORE FUNCTIONALITY
Four Analysis Columns:
- VPD (Volume Per Delta): Net institutional pressure and absorption patterns
- VPS (Volume Per Seller): Institutional selling pressure zones
- VPB (Volume Per Buyer): Institutional buying pressure zones
- SVP (Session Volume Profile): Total institutional activity zones
Enhanced Delta Calculation:
- Uses real bid/ask data (95% accuracy on 1-tick timeframe)
- Advanced price action analysis (85% accuracy on other timeframes)
- Significantly more precise than standard volume delta methods
🎨 SMART INSTITUTIONAL PATTERN DETECTION
Advanced Pattern Recognition:
- 🧊 Iceberg Orders: Hidden institutional size appearing repeatedly
- ⚡ Failed Auctions: Identifies truly trapped institutional traders
- 💜 Volume Exhaustion: Detects ending institutional momentum
- 🟨🟧 Absorption Patterns: Shows institutional level defense
- 🔥 Liquidity Sweeps: Identifies institutional stop-hunting
Professional Color System:
- Electric Blue/Bright Magenta: Large passive institutional orders
- Neon Green/Bright Red: Aggressive institutional entries
- Gold/Brown: Trapped institutional traders (underwater positions)
- Cyan: Hidden institutional iceberg orders
- Deep Pink: Institutional liquidity sweeps
⚠️ IMPORTANT DISCLAIMERS & REQUIREMENTS
📚 EDUCATION REQUIREMENT
YOU MUST LEARN VOLUME/DELTA ANALYSIS BEFORE USING THIS TOOL
This is an advanced institutional analysis tool requiring solid understanding of:
- Volume profile concepts and interpretation
- Order flow analysis and market microstructure
- Delta analysis and its implications
- Institutional trading behaviors and patterns
Recommended Learning Path:
1. Study volume profile analysis fundamentals
2. Learn order flow and market microstructure basics
3. Understand delta analysis interpretation
4. Practice on paper trading or small positions
5. Gradually increase position sizing as competency develops
🧪 MANDATORY TESTING REQUIREMENT
EXTENSIVE TESTING IS REQUIRED BEFORE LIVE TRADING
- Test the indicator across different market conditions
- Backtest patterns on historical data
- Paper trade signals for minimum 30 days
- Understand how patterns behave in your specific markets/timeframes
- Verify pattern accuracy in your trading environment
📋 USER RESPONSIBILITY DISCLAIMER
ALL TRADING DECISIONS AND OUTCOMES ARE YOUR SOLE RESPONSIBILITY
- This indicator provides analysis tools, NOT trading advice
- No guarantee of profitability or accuracy
- Past performance does not indicate future results
- You are responsible for risk management and position sizing
- Seek professional financial advice if needed
- Use only risk capital you can afford to lose
🎛️ CUSTOMIZATION OPTIONS
Layout Styles:
- Back-to-Back: Traditional volume profile layout
- Face-to-Face: Orderbook simulation style
- Adjustable spacing and positioning
Color Systems:
- Smart Institutional Coloring: Advanced pattern recognition
- Classic Red/Green: Traditional volume profile colors
Detection Sensitivity:
- Adjustable thresholds for all pattern types
- Customizable institutional size detection
- Configurable absorption and spike parameters
💡 PROFESSIONAL USAGE TIPS
1. Start Conservative: Begin with higher detection thresholds
2. Multiple Timeframes: Analyze across different timeframe contexts
3. Confluence: Combine with other technical analysis methods
4. Market Context: Consider overall market environment and news
5. Risk Management: Always use proper position sizing and stop losses
🚨 FINAL WARNING
This is a professional-grade analysis tool designed for experienced traders who understand volume analysis and institutional behavior. Improper use or lack of understanding can result in significant losses. Education, testing, and personal responsibility are mandatory prerequisites for successful utilization.
Trade at your own risk. This indicator does not guarantee profits.
Delta Canlde POC @MaxMaserati🎯 Delta Candle POC @MaxMaserati
Indicator Guide and Purpose
This indicator provides professional volume profile analysis at the individual candle level, revealing the internal structure of price action and volume distribution that standard charts cannot show. It transforms each candle into a detailed volume map, showing exactly where trading activity concentrated and whether buyers or sellers were in control.
What It Shows
🔹 Volume Imprint Bars
5 horizontal volume bars within each qualifying candle
Width = Volume intensity at that price level
Color = Market pressure (Green = Bullish delta, Red = Bearish delta)
Position = Key price levels (Open, Close, Body Mid, High/Low rejections)
🔹 Delta Labels
Net buying/selling pressure for each candle (e.g., "+2.3K" or "-1.8K")
Positioned above/below candles based on pressure direction
Synchronized with volume bars - appear together, disappear together
🔹 Point of Control (POC)
Horizontal line marking the price level with highest volume
Dynamic thickness based on volume intensity
Extends forward to show ongoing significance
Color-coded by market pressure
How to Interpret
Volume Distribution Patterns
Thick bars at body levels = High conviction trading
Thick bars at wicks = Rejection/support zones
Concentrated volume = Strong agreement on price
Scattered volume = Uncertainty or ranging
Delta Analysis
Large positive delta = Strong buying pressure
Large negative delta = Strong selling pressure
Small delta with high volume = Balanced but active trading
Large delta with low volume = Weak conviction
POC Significance
POC at candle high = Resistance being tested
POC at candle low = Support being tested
POC in body = Fair value area
Thick POC lines = High conviction levels
Analysis Settings
Volume Sensitivity - Controls how much detail to show
Minimum Volume Threshold - Filters out low-activity candles
High Volume Candles Only - Shows only above-average volume periods
Customization
Imprint Width % - Adjust bar width for visibility
Volume Bar Transparency - Control opacity
Color settings - Customize all visual elements
Smart Features
🔄Synchronized Management
Automatic cleanup - Maintains exactly 35 candles worth of data
Perfect synchronization - Labels and volume bars always appear/disappear together
No orphaned elements - Prevents display issues
🧠 Advanced Calculations
Smart order flow - Uses price action, wicks, and body analysis
Real tick data - Enhanced accuracy on 1-tick charts
5-level distribution - Optimized for Pine Script limits
Timeframe Selection
Lower timeframes (1m, 5m) - Detailed intraday analysis
Higher timeframes (1H, 4H) - Broader market structure
Volume Threshold:
Start with default 100 - Adjust based on instrument liquidity
Higher thresholds - Focus on major moves only
Lower thresholds - See more activity detail
What Makes It Unique
Unlike traditional volume indicators that show aggregate data, this reveals the internal architecture of each price move, answering:
Where exactly did the volume occur within each candle?
What was the buying vs selling pressure at each level?
Which price levels attracted the most activity?
How committed were traders to specific price areas?
This granular insight helps you understand market microstructure and see the story behind every candle's formation.
Backtest it and make sure it fits your needs before using it.
Big Trade % Heatmap### Big Trade % Heatmap
**Quick overview**
This indicator highlights where “whale” activity is clustered by showing what fraction of the recent candles contained *large‑value trades*. A candle is considered “big” when its notional volume (`volume × close`) exceeds your chosen USD threshold. You instantly see:
* **Percent of big candles** in the last *N* bars, refreshed at the cadence you pick.
* **On‑chart labels & markers** every refresh, so the chart stays clean.
* **Optional heat‑map background** that turns orange (>20 %) or green (>50 %) when big‑trade concentration spikes.
* **Ready‑made alert** when big‑trade dominance crosses 50 %.
---
#### How it works
1. **Trade size per candle** – Calculates `close × volume` to estimate dollars traded.
2. **Threshold filter** – Flags candles whose value is above *Big Trade Threshold (\$)*.
3. **Look‑back window** – Counts what percentage of the last *Lookback Window (X Candles)* were “big.”
4. **Refresh interval** – Repeats the measurement only every *Refresh Interval (Every X Candles)* to avoid label spam.
5. **Visuals** –
* A small blue ▼ above the bar + a text label such as `35.00 % > $25 000`.
* Background shading (green/orange) for quick, at‑a‑glance sentiment.
---
#### Inputs
| Input | Purpose | Default |
| -------------------------------------- | ----------------------------------------------------- | ------- |
| **Lookback Window (X Candles)** | How many recent bars to sample for the % calculation. | 20 |
| **Refresh Interval (Every X Candles)** | How often to display a new label/marker. | 5 |
| **Big Trade Threshold (\$)** | Minimum USD value for a candle to count as “big.” | 10 000 |
Tune these to the symbol and timeframe you trade (e.g., raise the threshold for BTC‑USDT 1‑h, lower it for micro‑caps).
---
#### Alerts
Enable **“High Big Trade %”** to get notified the moment more than half of the last *N* candles qualify as big trades—handy for spotting sudden accumulation or distribution.
---
#### Typical use cases
* **Breakout confirmation** – A surge in big‑trade % just before price escapes a range can validate the move.
* **Whale spotting** – Detect hidden accumulation on pullbacks or aggressive selling into rallies.
* **Filter noise** – Combine with your favorite trend indicator; only act when both align.
---
> *Built with Pine Script v6. Always back‑test before trading live; this tool is for educational purposes and not financial advice.*
Confluence AVWAP Breakout RibbonThis advanced indicator overlays up to five Anchored VWAPs—Daily Session, Weekly, Monthly, Prior Swing High, and Prior Swing Low—directly onto your chart. It highlights a "confluence ribbon" between these levels, visually mapping the real-time price zone where institutional activity may cluster. The ribbon is colored dynamically so you can instantly spot which side of value price is breaking towards.
How it works:
• The script automatically recalculates each selected VWAP anchor in real time.
• For swing-high and swing-low anchors, it starts a new VWAP every time a new price swing is confirmed.
• You can enable or disable any anchor via the script’s Inputs panel to suit your trading style or asset.
Entry Signals:
• A long breakout (green up-arrow) triggers only on the first candle that closes above all active VWAP anchors.
• A short breakout (red down-arrow) triggers only on the first close below all active anchors.
• These signals help confirm when price makes a decisive move out of a key value zone, filtering out false or weak breakouts.
How to use:
Add the indicator to any chart or timeframe.
In the Inputs, choose which VWAP anchors to activate.
Watch for the ribbon color and width: a wider ribbon means more confluence between price zones.
Trade signals (arrows) are only painted on the first candle to break out above or below all anchors, making them easy to see and avoiding repaint.
Optional: Set up alerts using the built-in TradingView alerts for each breakout direction.
Customization:
• Toggle each anchor on/off for your preferred strategy.
• Adjust the swing length for pivots.
• Change ribbon opacity for better chart visibility.
Why it’s unique:
• Most VWAP scripts only plot a single line, or show basic session anchors.
• This indicator lets you stack up to five important VWAP anchors and requires consensus: price must clear all active anchors in one move to signal a breakout.
• The live ribbon and dynamic visuals provide clear confluence zones and breakout cues that go beyond traditional VWAP use.
Best practices:
• Works well on all major assets (stocks, crypto, FX, indices) and all chart timeframes.
• For highest reliability, use two or more anchors at a time.
• Consider using alongside your preferred trend or volatility filter.
For educational and research purposes only. This is not financial advice or a recommendation to buy or sell. Always use proper risk management and test before live trading.
High Volume Buyers/Sellers+High Volume Buyers/Sellers+
This indicator helps traders spot bars where unusually high or extreme volume occurs, indicating strong buying or selling pressure.
How it works:
Calculates a volume moving average (SMA) over a user-defined period.
Marks bars where the current volume exceeds:
High Volume Multiplier → small green circle (bullish) or red circle (bearish).
Extreme Volume Multiplier → small green up-triangle (bullish) or red down-triangle (bearish).
Settings:
Volume MA Period → Number of bars used to calculate the average volume.
High Volume Multiplier → Threshold to define high volume.
Extreme Volume Multiplier → Threshold to define extreme volume.
Show Extreme Volume Signals → Option to enable or disable extreme volume markers.
Usage tips:
Apply this indicator on a clean chart to visually highlight momentum bursts or exhaustion points.
It works well for both intraday and swing trading strategies where volume confirmation matters.
⚠ Note: This script only displays on-chart markers and does not plot any lines or indicators.
No Supply No Demand (NSND) – Volume Spread Analysis ToolThis indicator is designed for traders utilizing Volume Spread Analysis (VSA) techniques. It automatically detects potential No Demand (ND) and No Supply (NS) candles based on volume and price behavior, and confirms them using future price action within a user-defined number of lookahead bars.
Confirmed No Demand (ND): Detected when a bullish candle has volume lower than the previous two bars and is followed by weakness (next highs swept, close below).
Confirmed No Supply (NS): Detected when a bearish candle has volume lower than the previous two bars and is followed by strength (next lows swept, close above).
Adjustable lookahead bars parameter to control the confirmation window.
This tool helps identify potential distribution (ND) and accumulation (NS) areas, providing early signs of market turning points based on professional volume logic. The dot appears next to ND or NS.
Volume Peak LineA fully configurable “Volume Peak Line” indicator that draws a horizontal threshold at the highest volume over the last X candles (default 5).
Custom lookback (X volume candles)
Optional alert when current volume exceeds that peak
Separate up/down volume bars (green/red) or hide them to use your own volume overlays
Use it to spot surges in trading activity on any timeframe—ideal for intraday or swing setups where a barn-burner volume bar can signal a reversal or the start of a new trend.
Ease of Movement Z-Score Trend | DextraGeneral Description:
The "Ease of Movement Z-Score Trend | Dextra" (EOM-Z Trend) is an innovative technical analysis tool that combines the Ease of Movement (EOM) concept with Z-Score to measure how easily price moves relative to volume, while identifying market trends with intuitive visualization. This indicator is designed to help traders detect uptrend and downtrend phases with precision, enhanced by candle coloring for direct trend representation on the chart.
Key Features
Ease of Movement (EOM): Measures how easily price moves based on the change in the midpoint price and volume, normalized with Z-Score for statistical analysis.
Z-Score Normalization: Provides an indication of deviations from the mean, enabling the identification of overbought or oversold conditions.
Adjustable Thresholds: Users can customize upper and lower thresholds to define trend boundaries.
Candle Coloring: Visual trend representation with green (uptrend), red (downtrend), and gray (neutral) candles.
Flexibility: Adjustable for different timeframes and assets.
How It Works
The indicator operates through the following steps:
EOM Calculation:
hl2 = (high + low) / 2: Calculates the average midpoint price per bar.
eom = ta.sma(10000 * ta.change(hl2) * (high - low) / volume, length): EOM is computed as the smoothed average of the price midpoint change multiplied by the price range per unit volume, scaled by 10,000, over length bars (default 20).
Z-Score Calculation:
mean_eom = ta.sma(eom, z_length): Average EOM over z_length bars (default 93).
std_dev_eom = ta.stdev(eom, z_length): Standard deviation of EOM.
z_score = (eom - mean_eom) / std_dev_eom: Z-Score indicating how far EOM deviates from its mean in standard deviation units.
Trend Detection:
upperthreshold (default 1.03) and lowerthreshold (default -1.63): Thresholds to classify uptrend (if Z-Score > upperthreshold) and downtrend (if Z-Score < lowerthreshold).
eom_is_up and eom_is_down: Logical variables for trend status.
Visualization:
plot(z_score, ...): Z-Score line plotted with green (uptrend), red (downtrend), or gray (neutral) coloring.
plotcandle(...): Candles colored green, red, or gray based on trend.
hline(...): Dashed lines marking the thresholds.
Input Settings
EOM Length (default 20): Period for calculating EOM, determining sensitivity to price changes.
Z-Score Lookback Period (default 93): Period for calculating the Z-Score mean and standard deviation.
Uptrend Threshold (default 1.03): Minimum Z-Score value to classify an uptrend.
Downtrend Threshold (default -1.93): Maximum Z-Score value to classify a downtrend.
How to Use
Installation: Add the indicator via the "Indicators" menu in TradingView and search for "EOM-Z Trend | Dextra".
Customization:
Adjust EOM Length and Z-Score Lookback Period based on the timeframe (e.g., 20 and 93 for daily timeframes).
Set Uptrend Threshold and Downtrend Threshold according to preference or asset characteristics (e.g., lower to 0.8 and -1.5 for volatile markets).
Interpretation:
Uptrend (Green): Z-Score above upperthreshold, indicating strong upward price movement.
Downtrend (Red): Z-Score below lowerthreshold, indicating significant downward movement.
Neutral (Gray): Conditions between thresholds, suggesting a sideways market.
Use candle coloring as the primary visual guide, combined with the Z-Score line for confirmation.
Advantages
Intuitive Visualization: Candle coloring simplifies trend identification without deep analysis.
Flexibility: Customizable parameters allow adaptation to various markets.
Statistical Analysis: Z-Score provides a robust perspective on price deviations from the norm.
No Repainting: The indicator uses historical data and does not alter values after a bar closes.
Limitations
Volume Dependency: Requires accurate volume data; an error occurs if volume is unavailable.
Market Context: Effectiveness depends on properly tuned thresholds for specific assets.
Lack of Additional Signals: No built-in alerts or supplementary confirmation indicators.
Recommendations
Ideal Timeframe: Daily (1D) or (2D) for stable trends.
Combination: Pair with others indicators for signal validation.
Optimization: Test thresholds on historical data of the traded asset for optimal results.
Important Notes
This indicator relies entirely on internal TradingView data (high, low, close, volume) and does not integrate on-chain data. Ensure your data provider supports volume to avoid errors. This version (1.0) is the initial release, with potential future updates including features like alerts or multi-timeframe analysis.
Volume-Based Candle ShadingThe Volume Shading indicator dynamically adjusts the color brightness of each price bar based on relative volume levels. It helps traders quickly identify whether a candle formed on low, average, or high volume without needing to reference a separate volume pane.
Candles are shaded dynamically as they form, so you can watch volume flow into them in real time. This indicator is designed to be as minimally intrusive as possible, allowing you to visualize volume levels without extra clutter on your charts.
The additional volume indicator in the preview above is there just for a point of reference to allow you to see how the shading on the bars correlates to the volume.
⸻
SETTINGS:
Bullish and bearish base colors — These serve as the midpoint (average volume) for shading.
Brightness mapping direction — Optionally invert the shading so that either high volume appears darker or lighter.
Volume smoothing length — Defines how many bars are averaged to determine what constitutes “normal” volume.
Candles with volume above average will appear darker or lighter depending on user preference, while those with average volume will be painted the chosen colors, giving an intuitive gradient that enhances volume awareness directly on the chart.
⸻
USES:
Confirming price action: Highlight when breakout candles or reversal bars occur with high relative volume, strengthening signal conviction.
Spotting low-volume moves: Identify candles that lack volume support, potentially signaling weak continuation or false breakouts.
Enhancing visual analysis: Overlay volume dynamics directly onto price bars, reducing screen clutter and aiding faster decision-making.
Custom visual workflows: Adapt the visual behavior of candles to your trading style by choosing color direction and base tones.
Ultimate Market Structure [Alpha Extract]Ultimate Market Structure
A comprehensive market structure analysis tool that combines advanced swing point detection, imbalance zone identification, and intelligent break analysis to identify high-probability trading opportunities.Utilizing a sophisticated trend scoring system, this indicator classifies market conditions and provides clear signals for structure breaks, directional changes, and fair value gap detection with institutional-grade precision.
🔶 Advanced Swing Point Detection
Identifies pivot highs and lows using configurable lookback periods with optional close-based analysis for cleaner signals. The system automatically labels swing points as Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), and Lower Lows (LL) while providing advanced classifications including "rising_high", "falling_high", "rising_low", "falling_low", "peak_high", and "valley_low" for nuanced market analysis.
swingHighPrice = useClosesForStructure ? ta.pivothigh(close, swingLength, swingLength) : ta.pivothigh(high, swingLength, swingLength)
swingLowPrice = useClosesForStructure ? ta.pivotlow(close, swingLength, swingLength) : ta.pivotlow(low, swingLength, swingLength)
classification = classifyStructurePoint(structureHighPrice, upperStructure, true)
significance = calculateSignificance(structureHighPrice, upperStructure, true)
🔶 Significance Scoring System
Each structure point receives a significance level on a 1-5 scale based on its distance from previous points, helping prioritize the most important levels. This intelligent scoring system ensures traders focus on the most meaningful structure breaks while filtering out minor noise.
🔶 Comprehensive Trend Analysis
Calculates momentum, strength, direction, and confidence levels using volatility-normalized price changes and multi-timeframe correlation. The system provides real-time trend state tracking with bullish (+1), bearish (-1), or neutral (0) direction assessment and 0-100 confidence scoring.
// Calculate trend momentum using rate of change and volatility
calculateTrendMomentum(lookback) =>
priceChange = (close - close ) / close * 100
avgVolatility = ta.atr(lookback) / close * 100
momentum = priceChange / (avgVolatility + 0.0001)
momentum
// Calculate trend strength using multiple timeframe correlation
calculateTrendStrength(shortPeriod, longPeriod) =>
shortMA = ta.sma(close, shortPeriod)
longMA = ta.sma(close, longPeriod)
separation = math.abs(shortMA - longMA) / longMA * 100
strength = separation * slopeAlignment
❓How It Works
🔶 Imbalance Zone Detection
Identifies Fair Value Gaps (FVGs) between consecutive candles where price gaps create unfilled areas. These zones are displayed as semi-transparent boxes with optional center line mitigation tracking, highlighting potential support and resistance levels where institutional players often react.
// Detect Fair Value Gaps
detectPriceImbalance() =>
currentHigh = high
currentLow = low
refHigh = high
refLow = low
if currentOpen > currentClose
if currentHigh - refLow < 0
upperBound = currentClose - (currentClose - refLow)
lowerBound = currentClose - (currentClose - currentHigh)
centerPoint = (upperBound + lowerBound) / 2
newZone = ImbalanceZone.new(
zoneBox = box.new(bar_index, upperBound, rightEdge, lowerBound,
bgcolor=bullishImbalanceColor, border_color=hiddenColor)
)
🔶 Structure Break Analysis
Determines Break of Structure (BOS) for trend continuation and Directional Change (DC) for trend reversals with advanced classification as "continuation", "reversal", or "neutral". The system compares pre-trend and post-trend states for each break, providing comprehensive trend change momentum analysis.
🔶 Intelligent Zone Management
Features partial mitigation tracking when price enters but doesn't fully fill zones, with automatic zone boundary adjustment during partial fills. Smart array management keeps only recent structure points for optimal performance while preventing duplicate signals from the same level.
🔶 Liquidity Zone Detection
Automatically identifies potential liquidity zones at key structure points for institutional trading analysis. The system tracks broken structure points and provides adaptive zone extension with configurable time-based limits for imbalance areas.
🔶 Visual Structure Mapping
Provides clear visual indicators including swing labels with color-coded significance levels, dashed lines connecting break points with BOS/DC labels, and break signals for continuation and reversal patterns. The adaptive zones feature smart management with automatic mitigation tracking.
🔶 Market Structure Interpretation
HH/HL patterns indicate bullish market structure with trend continuation likelihood, while LH/LL patterns signal bearish structure with downtrend continuation expected. BOS signals represent structure breaks in trend direction for continuation opportunities, while DC signals warn of potential reversals.
🔶 Performance Optimization
Automatic cleanup of old structure points (keeps last 8 points), recent break tracking (keeps last 5 break events), and efficient array management ensure smooth performance across all timeframes and market conditions.
Why Choose Ultimate Market Structure ?
This indicator provides traders with institutional-grade market structure analysis, combining multiple analytical approaches into one comprehensive tool. By identifying key structure levels, imbalance zones, and break patterns with advanced significance scoring, it helps traders understand market dynamics and position themselves for high-probability trade setups in alignment with smart money concepts. The sophisticated trend scoring system and intelligent zone management make it an essential tool for any serious trader looking to decode market structure with precision and confidence.
Exchanges Combined Volume📊 Exchanges Combined Volume
(Aggregated Multi-Exchange Volume: Binance, OKX, Bybit, etc.) by BIGTAKER*
🔍 Purpose
The Exchanges Combined Volume indicator aggregates real-time trading volumes from multiple global exchanges for a specific asset (e.g., a cryptocurrency).
Instead of relying on a single market, it provides a broader view of market activity, helping users detect abnormal volume behavior and increased participation across the entire market.
⚙️ Supported Exchanges
* USDT Markets
`Binance`, `OKX`, `Bybit`, `Bitget`, `Gate.io`
* USD Markets
`Coinbase`, `Bitfinex`, `Bitstamp`
* Default
Includes the current chart symbol’s native volume by default.
🧮 Core Calculation Logic
1. 📛 Symbol Normalization (cleanSymbol)
Prefixes such as `1000`, `10000`, `100000`, or `1M` (common in leveraged tickers) are automatically removed to extract the base token.
> Example:
> `1000PEPEUSDT` → `PEPEUSDT`
2. 📈 Volume Requests from External Exchanges
Volume is retrieved using the `` format (e.g., `'BINANCE:PEPEUSDT'`, `'COINBASE:BTCUSD'`).
Invalid or delisted pairs are safely ignored using `ignore_invalid_symbol=true`.
3. 📊 Total Volume Calculation
totalVolume = usdtVolume + usdVolume + currentSymbolVolume
The indicator sums the volume from all target exchanges plus the volume from the current chart symbol.
4. 📏 Comparison to Average Volume
* Period: `length = 60` (Simple Moving Average over 60 candles)
* A candle is considered **high-intensity** if:
5. 🎨 Visual Styling
| Condition | Color | Meaning |
| -------------------------- | --------------------- | ----------------------- |
| High-volume Bullish Candle | Light Green (#30db78) | Strong Buying Activity |
| High-volume Bearish Candle | Bright Red (#ff0000) | Strong Selling Activity |
| Normal Bullish Candle | Dark Green (#3c7058) | Regular Buying Volume |
| Normal Bearish Candle | Dark Red (#682e2c) | Regular Selling Volume |
📌 Use Cases
* Detect synchronized volume surges across major global exchanges.
* Identify pre-pump accumulation phases on altcoins.
* Combine with premium gap indicators (e.g., Kimchi Premium) to identify leading market sentiment.
* Confirm breakout momentum with multi-exchange volume validation.
📘 Notes & Warnings
* Listing differences across exchanges may result in **zero volume** on some platforms.
* Prefixes like `1000`, `1M`, etc., are automatically removed to **improve symbol matching accuracy**.
* As volume units are not standardized, this indicator is best suited for **absolute value analysis**, not ratio-based comparisons.
[Teyo69] T1 Short & Long Covering📘 Overview
The Short & Long Covering indicator is designed to help traders detect potential absorption candles and short-covering traps using a combination of normalized volume behavior and price exhaustion logic.
It visualizes possible long opportunities after sell-offs and short traps after price rallies—ideal for traders who want to anticipate reversals based on volume structure.
🧩 Features
📈 Detects rising price with falling volume → potential short covering
📉 Detects falling price with falling volume → potential long absorption
🔍 Flags volume spike conditions using normalized volume vs MA
🔵 Plots “L” (Long Covering) below bars
🔴 Plots “S” (Short Trap) above bars
Customizable pivot lookback and exhaustion period
⚙️ How to Use
Use "L" markers as possible long re-entry points after shakeouts
Use "S" markers to watch for failed rallies or bull traps
Combine with S/R zones or trend filters to confirm
Works well in conjunction with Wyckoff-style market logic or volume spread analysis (VSA)
🔧 Configuration
Price movement Lookback: Sets how many bars to compare for trend detection
Exhaustion Lookback: Defines the recent window to confirm price is exhausted
Normalized Volume MA Length: Used to determine volume spikes relative to average
⚠️ Limitations
Not a standalone signal — should be used with confluence (e.g., support/resistance, trend filters)
Best for spotting potential reversals, not trend-following entries
May generate false signals in low volume chop or news spikes
💡 Advanced Tips
Combine with a trend filter like appropriate EMA to avoid counter-trend setups
Use with a support/resistance script to find confluence zones
Watch for clustered L/S signals — multiple signals in a zone may show strong absorption or distribution
📝 Notes
Signal logic is based on volume exhaustion and price movement divergence
Normalized volume helps compare relative volume across time
“Spike” condition triggers only when volume exceeds 100% of its moving average
🚫 Disclaimer
This script is for educational purposes only. It does not constitute financial advice. Always do your own research and use proper risk management.
VoluTrend | Auto Trendlines + VolumeVoluTrend is a trendline tool that combines pivot detection with volume validation to help traders see only meaningful market structures.
How it works:
Pivot Detection: The script scans for local swing highs and lows using a customizable number of left and right bars. This ensures that each pivot reflects a significant turning point in price action.
Volume Filter: Each pivot is checked against a simple volume filter: the pivot is only valid if its associated bar has higher volume than a user-defined multiple of the average volume over a configurable period. This prevents weak or irrelevant pivots from cluttering the chart.
Automatic Trendlines: Once a valid pivot is found, the script automatically draws a trendline from the previous pivot to the new one. It keeps only a limited number of lines to avoid overcrowding the chart. This creates a dynamic, real-time trendline system that updates as price action evolves.
Why combine these elements?
Many auto trendline tools draw lines for every swing, but not all swings are significant. By combining pivot detection with a volume filter, VoluTrend focuses on price levels where notable participation occurred, helping traders better interpret real support/resistance and trend continuation or reversal points.
52SIGNAL RECIPE Bid/Ask Intensity Monitor═══ 52SIGNAL RECIPE Bid/Ask Intensity Monitor ═══
◆ Overview
52SIGNAL RECIPE Bid/Ask Intensity Monitor is a technical indicator that visualizes the balance of buying and selling forces in the market in real-time. Based on candle structure, this indicator calculates the relative strength of buying and selling pressure, displaying it through an intuitive color gradient gauge that allows traders to instantly grasp short-term market psychology and trading activity.
─────────────────────────────────────
◆ Key Features
• Intuitive Visualization: Instantly recognize buy/sell ratios through color gradient gauges
• Real-time Force Balance: Accurately display the buy/sell force ratio as a percentage in the current candle
• Candle Structure Analysis: Interpret market participant behavior through relationships between high, low, and close prices
• Chart Overlay: Displayed on the chart to observe changes in force balance alongside price movements
• Color Psychology: Provides intuitive psychological understanding through blue series (buy) and red series (sell) colors
─────────────────────────────────────
◆ Technical Foundation
■ Buy/Sell Ratio Calculation
• Basic Principle: Measure the relative strength of buyers and sellers by analyzing candle structure
• Buy Ratio Calculation: (Close - Low) ÷ (High - Low)
• Sell Ratio Calculation: 1 - Buy Ratio
• Interpretation Logic: The closer the closing price is to the high, the stronger the buying force; the closer to the low, the stronger the selling force
■ Visualization Mechanism
• Gradient Color Map: Express buy/sell intensity through 12-level color gradients
• Buy Color Range: Gradual change from light sky blue (#8be2ff) to deep navy blue (#103c60)
• Sell Color Range: Gradual change from light pink (#f65575) to deep burgundy (#3d101a)
• Gauge Structure: Vertical table positioned in the middle right of the chart for enhanced visual focus
─────────────────────────────────────
◆ Practical Applications
■ Market Psychology Identification
• Strong Buying Pressure Signals:
▶ When buy ratio is displayed as 70% or higher
▶ When the gauge is filled with bright blue shades
• Strong Selling Pressure Signals:
▶ When sell ratio is displayed as 70% or higher
▶ When the gauge is filled with bright red shades
• Force Balance State:
▶ When buy/sell ratio is in the 40-60% range
▶ When the color distribution in the gauge is even
■ Trading Strategy Application
• Trend Confirmation Strategy:
▶ Consecutive high buy ratios (70% or more) signal uptrend confirmation
▶ Consecutive high sell ratios (70% or more) signal downtrend confirmation
• Reversal Detection Strategy:
▶ Decreasing sell ratio during a downtrend suggests potential rebound
▶ Decreasing buy ratio during an uptrend suggests potential correction
• Volatility Breakout Strategy:
▶ Rapid changes in buy/sell ratio from a balanced state (50%) provide breakout signals
▶ Dramatic shifts in the opposite direction after extreme ratios signal trend reversals
─────────────────────────────────────
◆ Advanced Setting Options
■ Gauge Settings
• Gauge Width: Default value 15 (can be adjusted narrower or wider)
• Position Adjustment: Can be positioned at various locations on the chart (default is middle right)
• Border Thickness: Adjust border thickness for gauge visibility (default is 4)
■ Color Customization
• Buy Gradient: Color range can be modified according to personal preference
• Sell Gradient: Color range can be modified according to personal preference
• Transparency Settings: Optimize chart readability by adjusting background color transparency
■ Display Frequency Settings
• Update Cycle: Can be set to update every bar or at specific intervals
• History Length: Set display range for historical data
─────────────────────────────────────
◆ Synergy with Other Indicators
• Volume Profile: Analyze the Bid/Ask Intensity Monitor together with volume distribution to confirm buying/selling pressure at key price levels
• RSI: Improve signal reliability by checking extreme values of the Bid/Ask Intensity Monitor alongside RSI's overbought/oversold levels
• Moving Averages: Observe changes in the Bid/Ask Intensity Monitor when price is near key moving averages to assess support/resistance strength
• Bollinger Bands: Observe the Bid/Ask Intensity Monitor's reaction at band boundaries to evaluate potential reversals or trend continuation
─────────────────────────────────────
◆ Conclusion
52SIGNAL RECIPE Bid/Ask Intensity Monitor is a powerful tool that visualizes market participants' psychology and behavior in real-time based on candle structure. Through intuitive color gradients and percentage displays, it allows for immediate understanding of the balance between buying and selling forces, greatly aiding in predicting short-term market direction and momentum. When used in conjunction with other technical indicators, it provides a comprehensive understanding of market conditions, contributing to more accurate entry and exit timing decisions. This indicator, particularly useful in scalping and short-term trading, will enhance the chart analysis capabilities of all traders.
─────────────────────────────────────
※ Disclaimer: Past performance does not guarantee future results. Always use appropriate risk management strategies.
═══ 52SIGNAL RECIPE Bid/Ask Intensity Monitor ═══
◆ 개요
52SIGNAL RECIPE Bid/Ask Intensity Monitor는 실시간으로 시장의 매수/매도 세력 균형을 시각화하는 기술적 지표입니다. 이 지표는 캔들 구조를 기반으로 매수와 매도 압력의 상대적 강도를 계산하고, 직관적인 그라데이션 색상 게이지를 통해 표시함으로써 시장 참여자들의 단기 심리와 거래 활동을 한눈에 파악할 수 있게 합니다.
─────────────────────────────────────
◆ 주요 특징
• 직관적인 시각화: 매수/매도 비율을 색상 그라데이션 게이지로 즉각적으로 인식
• 실시간 세력 균형: 현재 봉에서의 매수/매도 세력 비율을 백분율로 정확히 표시
• 캔들 구조 기반 분석: 고가, 저가, 종가의 관계를 통해 시장 참여자 행동 해석
• 차트 오버레이: 차트 위에 표시되어 가격 움직임과 함께 세력 균형 변화 관찰 가능
• 색상 심리학 활용: 파란색 계열(매수)과 붉은색 계열(매도)로 직관적인 심리적 이해 제공
─────────────────────────────────────
◆ 기술적 기반
■ 매수/매도 비율 계산
• 기본 원리: 캔들의 구조를 분석하여 매수자와 매도자의 상대적 강도 측정
• 매수 비율 계산: (종가 - 저가) ÷ (고가 - 저가)
• 매도 비율 계산: 1 - 매수 비율
• 해석 논리: 종가가 고가에 가까울수록 매수 세력이 강하고, 저가에 가까울수록 매도 세력이 강함
■ 시각화 메커니즘
• 그라데이션 컬러 맵: 12단계 색상 그라데이션으로 매수/매도 강도 표현
• 매수 색상 범위: 밝은 하늘색(#8be2ff)에서 짙은 남색(#103c60)까지 점진적 변화
• 매도 색상 범위: 밝은 분홍색(#f65575)에서 짙은 적갈색(#3d101a)까지 점진적 변화
• 게이지 구조: 세로형 테이블로 우측 중앙에 배치되어 시각적 주목도 향상
─────────────────────────────────────
◆ 실용적 응용
■ 시장 심리 파악
• 강한 매수 압력 신호:
▶ 매수 비율이 70% 이상으로 표시될 때
▶ 게이지가 밝은 청색 계열로 채워질 때
• 강한 매도 압력 신호:
▶ 매도 비율이 70% 이상으로 표시될 때
▶ 게이지가 밝은 적색 계열로 채워질 때
• 세력 균형 상태:
▶ 매수/매도 비율이 40-60% 범위에 있을 때
▶ 게이지의 색상 분포가 균등할 때
■ 트레이딩 전략 적용
• 추세 확인 전략:
▶ 연속적인 높은 매수 비율(70% 이상)은 상승 추세 확인 신호
▶ 연속적인 높은 매도 비율(70% 이상)은 하락 추세 확인 신호
• 반전 탐색 전략:
▶ 하락 추세 중 매도 비율 감소는 반등 가능성 시사
▶ 상승 추세 중 매수 비율 감소는 조정 가능성 시사
• 변동성 돌파 전략:
▶ 균형 상태(50%)에서 급격한 매수/매도 비율 변화는 돌파 신호 제공
▶ 극단적 비율 후 반대 방향으로의 급격한 변화는 추세 전환 신호
─────────────────────────────────────
◆ 고급 설정 옵션
■ 게이지 설정
• 게이지 너비: 기본값 15 (좁게 또는 넓게 조정 가능)
• 위치 조정: 차트의 다양한 위치에 배치 가능 (우측 중앙 기본값)
• 테두리 두께: 게이지 가시성을 위한 테두리 굵기 조절 (기본값 4)
■ 색상 커스터마이징
• 매수 그라데이션: 개인 선호에 따라 색상 범위 수정 가능
• 매도 그라데이션: 개인 선호에 따라 색상 범위 수정 가능
• 투명도 설정: 배경색 투명도 조절로 차트 가독성 최적화
■ 표시 빈도 설정
• 업데이트 주기: 모든 봉마다 또는 특정 간격으로 업데이트 설정 가능
• 히스토리 길이: 과거 데이터에 대한 표시 범위 설정
─────────────────────────────────────
◆ 다른 지표와의 시너지
• 볼륨 프로파일: Bid/Ask Intensity Monitor와 볼륨 분포를 함께 분석하여 주요 가격대의 매수/매도 압력 확인
• RSI: Bid/Ask Intensity Monitor의 극단치와 RSI의 과매수/과매도 수준을 함께 확인하여 신호 신뢰도 향상
• 이동평균선: 가격이 주요 이동평균선 근처에서 Bid/Ask Intensity Monitor 변화를 관찰하여 지지/저항 강도 판단
• 볼린저 밴드: 밴드 경계에서의 Bid/Ask Intensity Monitor 반응을 관찰하여 반전 또는 추세 지속 가능성 평가
─────────────────────────────────────
◆ 결론
52SIGNAL RECIPE Bid/Ask Intensity Monitor는 캔들 구조를 기반으로 시장 참여자들의 심리와 행동을 실시간으로 시각화하는 강력한 도구입니다. 직관적인 색상 그라데이션과 백분율 표시를 통해 매수/매도 세력의 균형을 즉각적으로 파악할 수 있어, 시장의 단기적 방향성과 모멘텀을 예측하는 데 큰 도움이 됩니다. 다른 기술적 지표와 함께 사용하면 시장 상황에 대한 종합적인 이해를 얻을 수 있으며, 이는 더 정확한 진입 및 퇴출 타이밍을 결정하는 데 기여합니다. 특히 스캘핑과 단기 트레이딩에서 유용하게 활용될 수 있는 이 지표는 모든 트레이더의 차트 분석 능력을 한 단계 향상시켜 줄 것입니다.
─────────────────────────────────────
※ 면책 조항: 과거 성과가 미래 결과를 보장하지 않습니다. 항상 적절한 리스크 관리 전략을 사용하세요.
Diamond Peaks [EdgeTerminal]The Diamond Peaks indicator is a comprehensive technical analysis tool that uses a few mathematical models to identify high-probability trading opportunities. This indicator goes beyond traditional support and resistance identification by incorporating volume analysis, momentum divergences, advanced price action patterns, and market sentiment indicators to generate premium-quality buy and sell signals.
Dynamic Support/Resistance Calculation
The indicator employs an adaptive algorithm that calculates support and resistance levels using a volatility-adjusted lookback period. The base calculation uses ta.highest(length) and ta.lowest(length) functions, where the length parameter is dynamically adjusted using the formula: adjusted_length = base_length * (1 + (volatility_ratio - 1) * volatility_factor). The volatility ratio is computed as current_ATR / average_ATR over a 50-period window, ensuring the lookback period expands during volatile conditions and contracts during calm periods. This mathematical approach prevents the indicator from using fixed periods that may become irrelevant during different market regimes.
Momentum Divergence Detection Algorithm
The divergence detection system uses a mathematical comparison between price series and oscillator values over a specified lookback period. For bullish divergences, the algorithm identifies when recent_low < previous_low while simultaneously indicator_at_recent_low > indicator_at_previous_low. The inverse logic applies to bearish divergences. The system tracks both RSI (calculated using Pine Script's standard ta.rsi() function with Wilder's smoothing) and MACD (using ta.macd() with exponential moving averages). The mathematical rigor ensures that divergences are only flagged when there's a clear mathematical relationship between price momentum and the underlying oscillator momentum, eliminating false signals from minor price fluctuations.
Volume Analysis Mathematical Framework
The volume analysis component uses multiple mathematical transformations to assess market participation. The Cumulative Volume Delta (CVD) is calculated as ∑(buying_volume - selling_volume) where buying_volume occurs when close > open and selling_volume when close < open. The relative volume calculation uses current_volume / ta.sma(volume, period) to normalize current activity against historical averages. Volume Rate of Change employs ta.roc(volume, period) = (current_volume - volume ) / volume * 100 to measure volume acceleration. Large trade detection uses a threshold multiplier against the volume moving average, mathematically identifying institutional activity when relative_volume > threshold_multiplier.
Advanced Price Action Mathematics
The Wyckoff analysis component uses mathematical volume climax detection by comparing current volume against ta.highest(volume, 50) * 0.8, while price compression is measured using (high - low) < ta.atr(20) * 0.5. Liquidity sweep detection employs percentage-based calculations: bullish sweeps occur when low < recent_low * (1 - threshold_percentage/100) followed by close > recent_low. Supply and demand zones are mathematically validated by tracking subsequent price action over a defined period, with zone strength calculated as the count of bars where price respects the zone boundaries. Fair value gaps are identified using ATR-based thresholds: gap_size > ta.atr(14) * 0.5.
Sentiment and Market Regime Mathematics
The sentiment analysis employs a multi-factor mathematical model. The fear/greed index uses volatility normalization: 100 - min(100, stdev(price_changes, period) * scaling_factor). Market regime classification uses EMA crossover mathematics with additional ADX-based trend strength validation. The trend strength calculation implements a modified ADX algorithm: DX = |+DI - -DI| / (+DI + -DI) * 100, then ADX = RMA(DX, period). Bull regime requires short_EMA > long_EMA AND ADX > 25 AND +DI > -DI. The mathematical framework ensures objective regime classification without subjective interpretation.
Confluence Scoring Mathematical Model
The confluence scoring system uses a weighted linear combination: Score = (divergence_component * 0.25) + (volume_component * 0.25) + (price_action_component * 0.25) + (sentiment_component * 0.25) + contextual_bonuses. Each component is normalized to a 0-100 scale using percentile rankings and threshold comparisons. The mathematical model ensures that no single component can dominate the score, while contextual bonuses (regime alignment, volume confirmation, etc.) provide additional mathematical weight when multiple factors align. The final score is bounded using math.min(100, math.max(0, calculated_score)) to maintain mathematical consistency.
Vitality Field Mathematical Implementation
The vitality field uses a multi-factor scoring algorithm that combines trend direction (EMA crossover: trend_score = fast_EMA > slow_EMA ? 1 : -1), momentum (RSI-based: momentum_score = RSI > 50 ? 1 : -1), MACD position (macd_score = MACD_line > 0 ? 1 : -1), and volume confirmation. The final vitality score uses weighted mathematics: vitality_score = (trend * 0.4) + (momentum * 0.3) + (macd * 0.2) + (volume * 0.1). The field boundaries are calculated using ATR-based dynamic ranges: upper_boundary = price_center + (ATR * user_defined_multiplier), with EMA smoothing applied to prevent erratic boundary movements. The gradient effect uses mathematical transparency interpolation across multiple zones.
Signal Generation Mathematical Logic
The signal generation employs boolean algebra with multiple mathematical conditions that must simultaneously evaluate to true. Buy signals require: (confluence_score ≥ threshold) AND (divergence_detected = true) AND (relative_volume > 1.5) AND (volume_ROC > 25%) AND (RSI < 35) AND (trend_strength > minimum_ADX) AND (regime = bullish) AND (cooldown_expired = true) AND (last_signal ≠ buy). The mathematical precision ensures that signals only generate when all quantitative conditions are met, eliminating subjective interpretation. The cooldown mechanism uses bar counting mathematics: bars_since_last_signal = current_bar_index - last_signal_bar_index ≥ cooldown_period. This mathematical framework provides objective, repeatable signal generation that can be backtested and validated statistically.
This mathematical foundation ensures the indicator operates on objective, quantifiable principles rather than subjective interpretation, making it suitable for algorithmic trading and systematic analysis while maintaining transparency in its computational methodology.
* for now, we're planning to keep the source code private as we try to improve the models used here and allow a small group to test them. My goal is to eventually use the multiple models in this indicator as their own free and open source indicators. If you'd like to use this indicator, please send me a message to get access.
Advanced Confluence Scoring System
Each support and resistance level receives a comprehensive confluence score (0-100) based on four weighted components:
Momentum Divergences (25% weight)
RSI and MACD divergence detection
Identifies momentum shifts before price reversals
Bullish/bearish divergence confirmation
Volume Analysis (25% weight)
Cumulative Volume Delta (CVD) analysis
Volume Rate of Change monitoring
Large trade detection (institutional activity)
Volume profile strength assessment
Advanced Price Action (25% weight)
Supply and demand zone identification
Liquidity sweep detection (stop hunts)
Wyckoff accumulation/distribution patterns
Fair value gap analysis
Market Sentiment (25% weight)
Fear/Greed index calculation
Market regime classification (Bull/Bear/Sideways)
Trend strength measurement (ADX-like)
Momentum regime alignment
Dynamic Support and Resistance Detection
The indicator uses an adaptive algorithm to identify significant support and resistance levels based on recent market highs and lows. Unlike static levels, these zones adjust dynamically to market volatility using the Average True Range (ATR), ensuring the levels remain relevant across different market conditions.
Vitality Field Background
The indicator features a unique vitality field that provides instant visual feedback about market sentiment:
Green zones: Bullish market conditions with strong momentum
Red zones: Bearish market conditions with weak momentum
Gray zones: Neutral/sideways market conditions
The vitality field uses a sophisticated gradient system that fades from the center outward, creating a clean, professional appearance that doesn't overwhelm the chart while providing valuable context.
Buy Signals (🚀 BUY)
Buy signals are generated when ALL of the following conditions are met:
Valid support level with confluence score ≥ 80
Bullish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bull market regime environment
RSI below 35 (oversold conditions)
Price action confirmation (Wyckoff accumulation, liquidity sweep, or large buying volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive buy signals)
Cooldown period expired (default 10 bars)
Sell Signals (🔻 SELL)
Sell signals are generated when ALL of the following conditions are met:
Valid resistance level with confluence score ≥ 80
Bearish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bear market regime environment
RSI above 65 (overbought conditions)
Price action confirmation (Wyckoff distribution, liquidity sweep, or large selling volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive sell signals)
Cooldown period expired (default 10 bars)
How to Use the Indicator
1. Signal Quality Assessment
Monitor the confluence scores in the information table:
Score 90-100: Exceptional quality levels (A+ grade)
Score 80-89: High quality levels (A grade)
Score 70-79: Good quality levels (B grade)
Score below 70: Weak levels (filtered out by default)
2. Market Context Analysis
Use the vitality field and market regime information to understand the broader market context:
Trade buy signals in green vitality zones during bull regimes
Trade sell signals in red vitality zones during bear regimes
Exercise caution in gray zones (sideways markets)
3. Entry and Exit Strategy
For Buy Signals:
Enter long positions when premium buy signals appear
Place stop loss below the support confluence zone
Target the next resistance level or use a risk/reward ratio of 2:1 or higher
For Sell Signals:
Enter short positions when premium sell signals appear
Place stop loss above the resistance confluence zone
Target the next support level or use a risk/reward ratio of 2:1 or higher
4. Risk Management
Only trade signals with confluence scores above 80
Respect the signal alternation system (no overtrading)
Use appropriate position sizing based on signal quality
Consider the overall market regime before taking trades
Customizable Settings
Signal Generation Controls
Signal Filtering: Enable/disable advanced filtering
Confluence Threshold: Adjust minimum score requirement (70-95)
Cooldown Period: Set bars between signals (5-50)
Volume/Momentum Requirements: Toggle confirmation requirements
Trend Strength: Minimum ADX requirement (15-40)
Vitality Field Options
Enable/Disable: Control background field display
Transparency Settings: Adjust opacity for center and edges
Field Size: Control the field boundaries (3.0-20.0)
Color Customization: Set custom colors for bullish/bearish/neutral states
Weight Adjustments
Divergence Weight: Adjust momentum component influence (10-40%)
Volume Weight: Adjust volume component influence (10-40%)
Price Action Weight: Adjust price action component influence (10-40%)
Sentiment Weight: Adjust sentiment component influence (10-40%)
Best Practices
Always wait for complete signal confirmation before entering trades
Use higher timeframes for signal validation and context
Combine with proper risk management and position sizing
Monitor the information table for real-time market analysis
Pay attention to volume confirmation for higher probability trades
Respect market regime alignment for optimal results
Basic Settings
Base Length (Default: 25)
Controls the lookback period for identifying support and resistance levels
Range: 5-100 bars
Lower values = More responsive, shorter-term levels
Higher values = More stable, longer-term levels
Recommendation: 25 for intraday, 50 for swing trading
Enable Adaptive Length (Default: True)
Automatically adjusts the base length based on market volatility
When enabled, length increases in volatile markets and decreases in calm markets
Helps maintain relevant levels across different market conditions
Volatility Factor (Default: 1.5)
Controls how much the adaptive length responds to volatility changes
Range: 0.5-3.0
Higher values = More aggressive length adjustments
Lower values = More conservative length adjustments
Volume Profile Settings
VWAP Length (Default: 200)
Sets the calculation period for the Volume Weighted Average Price
Range: 50-500 bars
Shorter periods = More responsive to recent price action
Longer periods = More stable reference line
Used for volume profile analysis and confluence scoring
Volume MA Length (Default: 50)
Period for calculating the volume moving average baseline
Range: 10-200 bars
Used to determine relative volume (current volume vs. average)
Shorter periods = More sensitive to volume changes
Longer periods = More stable volume baseline
High Volume Node Threshold (Default: 1.5)
Multiplier for identifying significant volume spikes
Range: 1.0-3.0
Values above this threshold mark high-volume nodes with diamond shapes
Lower values = More frequent high-volume signals
Higher values = Only extreme volume events marked
Momentum Divergence Settings
Enable Divergence Detection (Default: True)
Master switch for momentum divergence analysis
When disabled, removes divergence from confluence scoring
Significantly impacts signal generation quality
RSI Length (Default: 14)
Period for RSI calculation used in divergence detection
Range: 5-50
Standard RSI settings apply (14 is most common)
Shorter periods = More sensitive, more signals
Longer periods = Smoother, fewer but more reliable signals
MACD Settings
Fast (Default: 12): Fast EMA period for MACD calculation (5-50)
Slow (Default: 26): Slow EMA period for MACD calculation (10-100)
Signal (Default: 9): Signal line EMA period (3-20)
Standard MACD settings for divergence detection
Divergence Lookback (Default: 5)
Number of bars to look back when detecting divergences
Range: 3-20
Shorter periods = More frequent divergence signals
Longer periods = More significant divergence signals
Volume Analysis Enhancement Settings
Enable Advanced Volume Analysis (Default: True)
Master control for sophisticated volume calculations
Includes CVD, volume ROC, and large trade detection
Critical for signal accuracy
Cumulative Volume Delta Length (Default: 20)
Period for CVD smoothing calculation
Range: 10-100
Tracks buying vs. selling pressure over time
Shorter periods = More reactive to recent flows
Longer periods = Broader trend perspective
Volume ROC Length (Default: 10)
Period for Volume Rate of Change calculation
Range: 5-50
Measures volume acceleration/deceleration
Key component in volume confirmation requirements
Large Trade Volume Threshold (Default: 2.0)
Multiplier for identifying institutional-size trades
Range: 1.5-5.0
Trades above this threshold marked as large trades
Lower values = More frequent large trade signals
Higher values = Only extreme institutional activity
Advanced Price Action Settings
Enable Wyckoff Analysis (Default: True)
Activates simplified Wyckoff accumulation/distribution detection
Identifies potential smart money positioning
Important for high-quality signal generation
Enable Supply/Demand Zones (Default: True)
Identifies fresh supply and demand zones
Tracks zone strength based on subsequent price action
Enhances confluence scoring accuracy
Enable Liquidity Analysis (Default: True)
Detects liquidity sweeps and stop hunts
Identifies fake breakouts vs. genuine moves
Critical for avoiding false signals
Zone Strength Period (Default: 20)
Bars used to assess supply/demand zone strength
Range: 10-50
Longer periods = More thorough zone validation
Shorter periods = Faster zone assessment
Liquidity Sweep Threshold (Default: 0.5%)
Percentage move required to confirm liquidity sweep
Range: 0.1-2.0%
Lower values = More sensitive sweep detection
Higher values = Only significant sweeps detected
Sentiment and Flow Settings
Enable Sentiment Analysis (Default: True)
Master control for market sentiment calculations
Includes fear/greed index and regime classification
Important for market context assessment
Fear/Greed Period (Default: 20)
Calculation period for market sentiment indicator
Range: 10-50
Based on price volatility and momentum
Shorter periods = More reactive sentiment readings
Momentum Regime Length (Default: 50)
Period for determining overall market regime
Range: 20-100
Classifies market as Bull/Bear/Sideways
Longer periods = More stable regime classification
Trend Strength Length (Default: 30)
Period for ADX-like trend strength calculation
Range: 10-100
Measures directional momentum intensity
Used in signal filtering requirements
Advanced Signal Generation Settings
Enable Signal Filtering (Default: True)
Master control for premium signal generation system
When disabled, uses basic signal conditions
Highly recommended to keep enabled
Minimum Signal Confluence Score (Default: 80)
Required confluence score for signal generation
Range: 70-95
Higher values = Fewer but higher quality signals
Lower values = More frequent but potentially lower quality signals
Signal Cooldown (Default: 10 bars)
Minimum bars between signals of same type
Range: 5-50
Prevents signal spam and overtrading
Higher values = More conservative signal spacing
Require Volume Confirmation (Default: True)
Mandates volume requirements for signal generation
Requires 1.5x average volume + 25% volume ROC
Critical for signal quality
Require Momentum Confirmation (Default: True)
Mandates divergence detection for signals
Ensures momentum backing for directional moves
Essential for high-probability setups
Minimum Trend Strength (Default: 25)
Required ADX level for signal generation
Range: 15-40
Ensures signals occur in trending markets
Higher values = Only strong trending conditions
Confluence Scoring Settings
Minimum Confluence Score (Default: 70)
Threshold for displaying support/resistance levels
Range: 50-90
Levels below this score are filtered out
Higher values = Only strongest levels shown
Component Weights (Default: 25% each)
Divergence Weight: Momentum component influence (10-40%)
Volume Weight: Volume analysis influence (10-40%)
Price Action Weight: Price patterns influence (10-40%)
Sentiment Weight: Market sentiment influence (10-40%)
Must total 100% for balanced scoring
Vitality Field Settings
Enable Vitality Field (Default: True)
Controls the background gradient field display
Provides instant visual market sentiment feedback
Enhances chart readability and context
Vitality Center Transparency (Default: 85%)
Opacity at the center of the vitality field
Range: 70-95%
Lower values = More opaque center
Higher values = More transparent center
Vitality Edge Transparency (Default: 98%)
Opacity at the edges of the vitality field
Range: 95-99%
Creates smooth fade effect from center to edges
Higher values = More subtle edge appearance
Vitality Field Size (Default: 8.0)
Controls the overall size of the vitality field
Range: 3.0-20.0
Based on ATR multiples for dynamic sizing
Lower values = Tighter field around price
Higher values = Broader field coverage
Recommended Settings by Trading Style
Scalping (1-5 minutes)
Base Length: 15
Volume MA Length: 20
Signal Cooldown: 5 bars
Vitality Field Size: 5.0
Higher sensitivity for quick moves
Day Trading (15-60 minutes)
Base Length: 25 (default)
Volume MA Length: 50 (default)
Signal Cooldown: 10 bars (default)
Vitality Field Size: 8.0 (default)
Balanced settings for intraday moves
Swing Trading (4H-Daily)
Base Length: 50
Volume MA Length: 100
Signal Cooldown: 20 bars
Vitality Field Size: 12.0
Longer-term perspective for multi-day moves
Conservative Trading
Minimum Signal Confluence: 85
Minimum Confluence Score: 80
Require all confirmations: True
Higher thresholds for maximum quality
Aggressive Trading
Minimum Signal Confluence: 75
Minimum Confluence Score: 65
Signal Cooldown: 5 bars
Lower thresholds for more opportunities
Price Volume Trend [sgbpulse]1. Introduction: What is Price Volume Trend (PVT)?
The Price Volume Trend (PVT) indicator is a powerful technical analysis tool designed to measure buying and selling pressure in the market based on price changes relative to trading volume. Unlike other indicators that focus solely on volume or price, PVT combines both components to provide a more comprehensive picture of trend strength.
How is it Calculated?
The PVT is calculated by adding or subtracting a proportional part of the daily volume from a cumulative total.
When the closing price rises, a proportional part of the daily volume (based on the percentage price change) is added to the previous PVT value.
When the closing price falls, a proportional part of the daily volume is subtracted from the previous PVT value.
If there is no change in price, the PVT value remains unchanged.
The result of this calculation is a cumulative line that rises when buying pressure is strong and falls when selling pressure dominates.
2. Why PVT? Comparison to Similar Indicators
While other indicators measure volume-price pressure, PVT offers a unique advantage:
PVT vs. On-Balance Volume (OBV):
OBV simply adds or subtracts the entire day's volume based on the closing direction (up/down), regardless of the magnitude of the price change. This means a 0.1% price change is treated the same as a 10% change.
PVT, on the other hand, gives proportional weight to volume based on the percentage price change. A trading day with a large price increase and high volume will impact the PVT significantly more than a small price increase with the same volume. This makes PVT more sensitive to trend strength and changes within it.
PVT vs. Accumulation/Distribution Line (A/D Line):
The A/D Line focuses on the relationship between the closing price and the bar's trading range (Close Location Value) and multiplies it by volume. It indicates whether the pressure is buying or selling within a single bar.
PVT focuses on the change between closing prices of consecutive bars, multiplying this by volume. It better reflects the flow of money into or out of an asset over time.
By combining volume with percentage price change, PVT provides deeper insights into trend confirmation, identifying divergences between price and volume, and spotting signs of weakness or strength in the current trend.
3. Indicator Settings (Inputs)
The "Price Volume Trend " indicator offers great flexibility for customization to your specific needs through the following settings:
Moving Average Type: Allows you to select the type of moving average used for the central line on the PVT. Your choice here will affect the line's responsiveness to PVT movements.
- "None" : No moving average will be displayed on the PVT.
- "SMA" (Simple Moving Average): A simple average, smoother, ideal for identifying longer-term trends in PVT.
- "SMA + Bollinger Bands": This unique option not only displays a Simple Moving Average but also activates the Bollinger Bands around the PVT. This is the recommended option for analyzing volatility and ranges using Bollinger Bands.
- "EMA" (Exponential Moving Average): An exponential average, giving more weight to recent data, responding faster to changes in PVT.
- "SMMA (RMA)" (Smoothed Moving Average): A smoothed average, providing extra smoothing, less sensitive to noise.
- "WMA" (Weighted Moving Average): A weighted average, giving progressively more weight to recent data, responding very quickly to changes in PVT.
Moving Average Length: Defines the number of bars used to calculate the moving average (and, if applicable, the standard deviation for the Bollinger Bands). A lower value will make the line more responsive, while a higher value will smooth it out.
PVT BB StdDev (Bollinger Bands Standard Deviation): Determines the width of the Bollinger Bands. A higher value will result in wider bands, making it less likely for the PVT to cross them. The standard value is 2.0.
4. Visual Aid: Current PVT Level Line
This indicator includes a unique and highly useful visual feature: a dynamic horizontal line displayed on the PVT graph.
Purpose: This line marks the exact level of the PVT on the most recent trading bar. It extends across the entire chart, allowing for a quick and intuitive comparison of the current level to past levels.
Why is it Important?
- Identifying Divergences: Often, an asset's price may be lower or higher than past levels, but the PVT level might be different. This auxiliary line makes it easy to spot situations where PVT is at a higher level when the price is lower, or vice-versa, which can signal potential trend changes (e.g., higher PVT than in the past while price is low could indicate strong accumulation).
- Quick Direction Indication: The line's color changes dynamically: it will be green if the PVT value on the last bar has increased (or remained the same) relative to the previous bar (indicating positive buying pressure), and red if the PVT value has decreased relative to the previous bar (indicating selling pressure). This provides an immediate visual cue about the direction of the cumulative momentum.
5. Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
PRO SMC DASHBOARDPRO SMC DASHBOARD - PRO LEVEL
Advanced Supply & Demand / SMC dashboard for scalping and intraday:
Multi-Timeframe Trend: Visualizes trend direction for M1, M5, M15, H1, H4.
HTF Supply/Demand: Shows closest high time frame (HTF) supply/demand zone and distance (in pips).
Smart “Flip” & Liquidity Signals: Flip and Liquidity Sweep arrows/signals are shown only when truly significant:
Near HTF Supply/Demand zone
And confirmed by volume spike or high confluence score
Momentum & Bias: Real-time momentum (RSI M1), H1 bias and fakeout detection.
Confluence Score: Objective score (out of 7) for trade confidence.
Volume Spike, Divergence, BOS: Includes volume spikes, RSI divergence (M1), and Break of Structure (BOS) for both M15 & H1.
Ultra-clean chart: Only valid signals/alerts shown; no spam or visual clutter.
Full dashboard with all signals and context, always visible bottom-right.
Best used for:
Forex, Gold/Silver, US indices, and crypto
Scalping/intraday with fast, clear decisions based on multi-factor SMC logic
Usage:
Add to your chart, monitor the dashboard for valid setups, and trade only when multiple factors align for high-probability entries.
How to Use the PRO SMC DASHBOARD
1. Add the Script to Your Chart:
Apply the indicator to your favorite Forex, Gold, crypto, or indices chart (best on M1, M5, or M15 for entries).
2. Read the Dashboard (Bottom Right):
The dashboard shows real-time information from multiple timeframes and key SMC filters, including:
Trend (M1, M5, M15, H1, H4):
Arrows show up (↑) or down (↓) trend for each timeframe, based on EMA.
Momentum (RSI M1):
Shows “Strong Up,” “Strong Down,” or “Neutral” plus the current RSI value.
RSI (H1):
Higher timeframe momentum confirmation.
ATR State:
Indicates current volatility (High, Normal, Low).
Session:
Detects if the market is in London, NY, or Asia session (based on UTC).
HTF S/D Zone:
Shows the nearest high timeframe Supply or Demand zone, its timeframe (M15, H1, H4), and exact pip distance.
Fakeout (last 3):
Detects recent false breakouts—if there are multiple fakeouts, potential for reversal is higher.
FVG (Fair Value Gap):
Indicates direction and distance to the nearest FVG (Above/Below).
Bias:
“Strong Buy,” “Strong Sell,” or “Neutral”—multi-timeframe, momentum, and volatility filtered.
Inducement:
Alerts for possible “stop hunt” or liquidity grab before reversal.
BOS (Break of Structure):
Recent or live breaks of market structure (for both M15 & H1).
Liquidity Sweep:
Shows if price just swept a key high/low and then reversed (often key reversal point).
Confluence Score (0-7):
Higher score means more factors align—look for 5+ for strong setups.
Volume Spike:
“YES” appears if the current volume is significantly above average—big players are active!
RSI Divergence:
Bullish or bearish divergence on M1—signals early reversal risk.
Momentum Flip:
“UP” or “DN” appears if RSI M1 crosses the 50 line, confirmed by location and other filters.
Chart Signals (Arrows & Markers):
Flip arrows (up/down) and Liquidity markers only appear when price is at/near a key Supply/Demand zone and confirmed by either a volume spike or strong confluence.
No signal spam:
If you see an arrow or LIQ tag, it’s a truly significant moment!
Suggested Trading Workflow:
Scan the Dashboard:
Is the multi-timeframe trend aligned?
Are you near a major Supply or Demand zone?
Is the Confluence Score high (5 or more)?
Check for Signals:
Is there a Flip or LIQ marker near a Supply/Demand zone?
Is volume spiking or a fakeout just occurred?
Look for Reversal or Continuation:
If there’s a Flip at Demand (with high confluence), consider a long setup.
If there’s a LIQ sweep + flip + volume at Supply, consider a short.
Manage Risk:
Don’t chase every signal.
Confirm with your entry criteria and preferred session timing.
Pro Tips:
Highest confidence trades:
When dashboard signals and chart arrows/markers agree, especially with high confluence and volume spike.
Adapt pip distance filter:
Dashboard is tuned for FX and gold; for other assets, adjust pip-size filter if needed.
Use alerts (if enabled):
Set up custom TradingView alerts for “Flip” or “Liquidity” signals for auto-notifications.
Designed to help you make professional, objective decisions—without chart clutter or second-guessing!
order flow buy/sell and profundity OrderBook Buy/Sell Flow & Polarity Indicator
This powerful indicator provides a detailed look into the market's internal dynamics by visualizing Order Flow (Tape/Time & Sales) and Price Polarity directly on your chart, all within a clean, customizable table. Understand real-time buying and selling pressure and gain insights into who's in control of the candle.
Key Features:
Real-time Order Flow (Tape/Time & Sales): Tracks individual "ticks" (price and volume updates) within the current bar, allowing you to see the immediate impact of buy and sell orders.
Dynamic Table Display: All data is presented in an intuitive, customizable table that can be positioned anywhere on your chart.
Aggregated Buy/Sell Volume: Clearly distinguishes between volume driven by buying (price moving up on a tick) and selling (price moving down on a tick).
"Rocket" Order Detection: Highlights unusually large buy or sell orders based on configurable thresholds (in BTC Millions for major cryptos, and Thousands/Millions for others), helping you spot significant institutional or whale activity.
Candle Polarity Section: A dedicated area in the table that shows the percentage of buying vs. selling volume for the entire current candle. The central cell dynamically blends between bullish (green) and bearish (red) colors, visually representing the dominant polarity.
Customizable Aesthetics: Full control over table colors, text colors, font sizes, and individual label colors to match your chart's theme.
Lightweight & Efficient: Designed to run smoothly without significant impact on your chart's performance.
Why Use This Indicator?
Most indicators only show you the result of price action. The "OrderBook Buy/Sell Flow & Polarity" indicator goes deeper, showing you the cause behind the price movement. By understanding the immediate order flow and the underlying buy/sell pressure within each candle, you can:
Identify accumulation or distribution: Spot when smart money might be entering or exiting positions.
Confirm breakouts/breakdowns: See if there's genuine volume behind price moves.
Gauge market sentiment in real-time: Quickly assess who is more aggressive – buyers or sellers.
Improve entry and exit points: Make more informed decisions based on live market activity.
Settings & Customization:
The indicator comes with a comprehensive set of input options, allowing you to fine-tune its appearance and functionality:
Table Position: Choose from various chart locations (Top/Middle/Bottom, Left/Center/Right).
Window Size (Order Flow): Adjust how many recent order flow "ticks" are displayed.
Colors: Personalize all table, text, and label colors.
Rocket Thresholds: Define the volume levels for "rocket" order detection based on asset type.
Polarity Section Toggle: Enable or disable the real-time candle polarity display.
Note: This indicator provides insights based on available real-time tick data from TradingView. While it simulates aspects of order book and tape reading, it is important to remember that direct access to full exchange Level 2 data is not available on TradingView.
Disclaimer: This indicator is for informational purposes only and should not be considered financial advice. Trading involves risk, and past performance is not indicative of future results.
Price over VolumeVersion 0.1
Price over Volume Indicator
Description
The Price over Volume indicator calculates the ratio of the closing price to the trading volume (price / volume) for the current chart's symbol and displays it as a histogram in a separate pane. A horizontal zero line is included as a reference to highlight positive and negative values or periods of undefined data (e.g., zero volume). The indicator is designed to help traders analyze the relationship between price movements and trading volume.
Insights Provided
Price-Volume Dynamics: The indicator shows how price per unit of volume fluctuates, offering insights into market efficiency and liquidity. High ratios may indicate low volume relative to price, suggesting potential volatility or thin markets, while low ratios may reflect high volume supporting price stability.
Trend and Momentum Analysis: Spikes or trends in the price-to-volume ratio can signal significant market events, such as buying/selling pressure or low liquidity periods, helping traders identify potential reversals or continuations.
Zero Line Reference: The zero line helps identify periods where the ratio is undefined (e.g., zero volume) or negative (if applicable), aiding in the interpretation of market conditions.
Volume Sensitivity: By normalizing price by volume, the indicator highlights how volume influences price movements, which is useful for assessing the strength of trends or breakouts.
How to Use
Setup: Apply the indicator to any chart with price and volume data (e.g., stocks, cryptocurrencies like BINANCE:BTCUSDT). The histogram appears in a separate pane below the main chart.
Interpretation :
High Ratios: Indicate low trading volume relative to price, potentially signaling overbought conditions or low liquidity. Use with caution in thin markets.
Low Ratios: Suggest high volume supporting price levels, indicating stronger market participation or stability.
Spikes: Watch for sudden increases in the ratio, which may precede volatility or significant price moves.
Zero Line: Periods where the histogram is absent (due to zero volume) indicate no trading activity, useful for identifying illiquid periods.
Trading Applications:
Confirmation Tool: Combine with other indicators (e.g., RSI, MACD) to confirm trend strength. A rising price-to-volume ratio with a price uptrend may indicate weakening volume support, suggesting a potential reversal.
Volume Analysis: Use alongside volume-based indicators (e.g., OBV, VWAP) to assess whether price movements are backed by sufficient volume.
Scalping/Day Trading: Monitor intraday ratio changes to identify high-impact periods with low volume, which may offer short-term trading opportunities.
Customization: Adjust the histogram color or style (e.g., change to line plot) via the Pine Editor to suit your preferences. Consider adding smoothing (e.g., moving average) for cleaner signals.
Notes
Data Requirements: Ensure the chart’s symbol has valid volume data. Symbols with no volume (e.g., some forex pairs) will result in undefined (na) values.
Limitations: The indicator is sensitive to zero-volume periods, which may cause gaps in the histogram. Use on high-liquidity symbols for best results.
Performance: Lightweight and efficient, suitable for all timeframes.
This indicator is ideal for traders seeking to understand the interplay between price and volume, offering a unique perspective on market dynamics for informed trading decisions.
TZanalyserTZanalyser (Trend Zone Monitor With Trend Strength, Volume Focus And -Events Markers)
Before I used TrendZones to manage my portfolio I used Fibonacci Zone Oscillator as my favorite in the sub panel, accompanied with another subpanel indicator which I never published called IncliValue and also REVE Cohorts.
TZanalyser inherits Ideas and code from all three of them: The visual and the idea of using a channel as the basis for an oscillator depicted as a histogram, is taken from the FibZone Oscillator. The idea of providing a number to evaluate the trend is taken from IncliValue. The idea to create a horizontal line which indicates high and low volume focus completed with markers for volume events, is taken from REVE-cohorts.
These ideas are combined in one sleek visual called TZanalyser. TZ stand for TrendZones, because the histogram is based on it.
The histogram.
Depicted is the distance of the price from COG as percent. The distance between Upper Curve and Lower Curve is used as 100%. The values may reach between 300 and -300. The colors indicate in which zone the candle lives, blue in the blue zone, green in the green zone etc. Despite the absence of a gray zone, there are gray bars. These depict candles that wrap around COG. Because hl2 is used as price, some gray bars point up and others down. The orange and red bars point down because the orange and red downtrend zones are below COG.
Use of the histogram.
Sometimes I need to create a list of stocks which are in uptrend in monthly, weekly and daily charts from the stocks I follow in my universe. This job is done fast and easy by looking at the last bar of the histogram. The histogram also gives a quick evaluation of how the stock fared in the past.
The number.
Suppose I need to allocate some money to another stock, selected a few, looked into news and gurus and they look equally good. Then it is nice to be able to find out which has the best charts. Which one has the strongest uptrend. For this purpose this number can be consulted, because it indicates somehow the strength of the trend. It is an integer between 20 and -20, the closer to 20 the stronger the uptrend, closer to -20 indicates a stronger downtrend. The color of the background is the same as the last column of the histogram.
Volume focus and events
The horizontal lines depict volume focus, the line below the focus that comes with the uptrend columns pointing up, the one above the focus for the downtrend columns pointing down. Thes line have tree colors: maroon for high volume focus, green for normal volume and gray for low volume situations. Between the lines and the histogram triangles appear at volume events, a green triangle when the candle comes with high volume, i.e. 120-200 percent of normal, maroon when extreme volume, i.e. more than 200 percent of normal.
The direction of these triangles is that of the histogram, i.e. when the price is higher, direction is up and vice versa.
Take care and have fun.
