EMA Crossover with DiamondsShows crossover of ema 21 and with ema 50 with diamond possible buy and sell positions.
Medie mobili
Adaptive Trend Cloud + Smart Reversal Zones [@darshakssc]This indicator combines a volatility-adjusted trend cloud with RSI- and volume-based reversal signals to help traders visually spot potential trend continuation or reversal zones.
It’s designed to look clean, colorful, and informative — great for both beginners and experienced traders looking for chart clarity and actionable insights.
🔍 How It Works
🔵 1. Trend Cloud
1. The cloud is created using a 34-period EMA as the base and adjusted with a 14-period ATR multiplier.
2. When price is above the EMA, the cloud turns green (bullish).
3. When price is below the EMA, it turns red (bearish).
4. A neutral gray tone shows when price is inside the cloud, signaling potential indecision.
🔁 2. Smart Reversal Signal Logic
1. Signals appear only when price enters the cloud zone, indicating a potential change in direction.
2. To confirm the reversal, the following conditions must also be met:
3. RSI is below 40 (for bullish reversals) or above 60 (for bearish reversals)
4. A volume spike occurs (1.8× the 20-bar volume average)
5. A cooldown of 10 bars between signals prevents overplotting
🎯 3. TP & SL Labels
1. When a valid buy or sell signal appears:
🎯 TP (Take Profit) is placed at 2× ATR distance
🛑 SL (Stop Loss) is placed at 1× ATR distance
These levels are shown via chart labels for visual reference
🛎️ 4. Alerts
1. Built-in alerts trigger on:
🟢 Buy reversal signals
🔴 Sell reversal signals
✅ How to Use
1. Apply the indicator to any chart (works best on 5min–4h timeframes)
2. Look for the 🟢 Buy / 🔴 Sell labels when price touches the cloud
3. Use the visual TP/SL markers as reference zones — not financial advice
4. Combine with your own risk management, price action or confluence tools
⚙️ Customization Options
1. EMA & ATR lengths and multipliers
2. RSI and volume thresholds
3. Signal cooldown to reduce noise
4. Toggle TP/SL zones on or off
⚠️ Disclaimer
This script is for educational purposes only and does not constitute financial advice. Always test on demo accounts and combine with your own trading system.
PM20/40/100/200 by Emprendetica📊 PM20/40/100/200 – Custom Moving Averages by Emprendetica
This indicator plots four simple moving averages (SMA): 20, 40, 100, and 200 periods. It’s designed for multi-timeframe traders who need quick and clear visualization of momentum and structural alignment across intraday and daily charts.
✅ Ideal for:
Detecting breakout readiness
Confirming trend strength (e.g., PM20 > PM40, PM100 > PM200)
Monitoring price structure with consistent dynamic support/resistance
📌 Created by Isaías Espinoza and the Emprendetica team.
🌐 More tools at: emprendetica.com
Daily EMAs (8, 21 & 50) with BandDescription:
This script plots the Daily EMAs (8, 21, and 50) on any intraday or higher timeframe chart. It provides a clear, multi-timeframe view of market trends by using daily exponential moving averages (EMAs) and a dynamic visual band. I use this on the major indexes to decide if I should be mostly longing or shorting assets.
-In addition to identifying the trend structure, the 8-Day EMA often serves as a key area where buyers or sellers may become active, depending on the market direction:
-In an uptrend, the 8 EMA can act as a dynamic support zone, where buyers tend to re-enter on pullbacks.
-In a downtrend, the same EMA may act as resistance, where sellers become more aggressive.
-The script also includes a colored band between the 8 and 21 EMAs to highlight the short-term trend bias:
-Green fill = 8 EMA is above the 21 EMA (bullish structure).
Blue fill = 8 EMA is below the 21 EMA (bearish structure).
The 50-Day EMA is included to give additional context for intermediate-term trend direction.
Features:
- Daily EMA levels (8, 21, and 50) calculated regardless of current chart timeframe.
- 8 EMA acts as a potential buyer/seller zone based on trend direction.
- Color-coded band between 8 and 21 EMAs:
- Green = Bullish short-term bias
- Blue = Bearish short-term bias
- Customizable price source and EMA offset.
- Suitable for trend trading, pullback entries, and higher-timeframe confirmation.
Use Cases:
Identify key dynamic support/resistance areas using the 8 EMA.
Assess short-, medium-, and intermediate-term trend structure at a glance.
Enhance confluence for entry/exit signals on lower timeframes.
HMA Trend Line (Croc Signal Line)HMA Trend Line (Croc Signal Line) — The Ultimate Hull Moving Average Trend Indicator
Full English description here:
What is the HMA Trend Line (Croc Signal Line)?
The HMA Trend Line (Croc Signal Line) is a powerful, adaptive trend indicator for TradingView, based on the Hull Moving Average (HMA). This indicator is designed to help traders identify real market trends with less lag and reduced noise compared to traditional moving averages like SMA (Simple Moving Average) and EMA (Exponential Moving Average).
Why use the HMA Trend Line?
+ Faster Trend Detection: The Hull Moving Average (HMA) responds more quickly to price action, giving you earlier buy and sell signals.
+ Smoother and Cleaner: It provides a visually clean trend line that avoids the choppiness of classic EMAs and SMAs.
+ Reduced Lag: The HMA Trend Line follows the market closer, helping you avoid late entries or exits and spot trend reversals sooner.
+ Dynamic Support and Resistance: Use the line as a dynamic support or resistance to manage trades and identify pullbacks or breakouts.
What does “Croc Signal Line” mean?
The “Croc” in Croc Signal Line stands for:
+ Clean
+ Responsive
+ Optimized
+ Curve
This highlights the unique advantage of this indicator: a curve that is both fast-reacting and smooth, helping traders focus on real trends and filter out market noise.
How does the Hull Moving Average (HMA) work?
The HMA was developed by Alan Hull and uses weighted moving averages and a unique calculation to deliver both responsiveness and smoothness. Unlike standard moving averages, the HMA reacts faster to new price moves and avoids false signals in ranging or volatile markets.
How to use the HMA Trend Line (Croc Signal Line) on TradingView?
+ Watch for price crossing above the trend line for potential bullish signals, and below for bearish signals.
+ Use on any timeframe: from 1-minute scalping to daily, weekly, or even monthly charts.
+ Works with all asset classes: Forex, stocks, indices, cryptocurrencies, commodities, and futures.
+ Combine with other indicators (like Stochastics, RSI, or volume) for confirmation and to build your unique trading strategy.
+ Adjust the Signal Line Period for your market and style: shorter periods for faster markets, longer for smoother trends.
Who should use this indicator?
+ Day traders, swing traders, and long-term investors looking for reliable, actionable trend signals.
+ Anyone seeking a cleaner, more responsive alternative to the classic moving averages.
+ Traders who want a simple, visually clear way to filter out market noise and see real price direction.
Disclaimer:
This indicator is for educational and study purposes only. Please perform your own backtesting and analysis before using it in live trading. This script does not constitute financial advice. Use at your own risk.
--------
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.
Mickey's EMAMickey’s EMA is a lightweight, overlay indicator that combines two Exponential Moving Averages (EMAs) with automatic entry, stop-loss and target visual signals—plus dynamic JSON alerts for seamless webhook integration. It’s designed for both day-traders and swing-traders who want clear, on-chart cues and fully-customizable risk parameters.
🔍 Overview
Dual EMAs (fast & slow) to capture trend changes.
Automated “BUY” / “SELL” markers at every EMA crossover.
Customizable Stop-Loss % and Target % levels, plotted as ❌ and 🎯 bubbles.
“SL Hit (Custom)” if the opposite EMA crossover occurs before price touches your stop level.
JSON-formatted alerts containing ticker, instrument type, timeframe, trend (“CE” for bullish, “PE” for bearish), and price—ready for webhooks.
⚙️ Inputs
| Setting | Default | Description |
| ------------------------ | ------- | ----------------------------------------------- |
| **Fast EMA Length** | 20 | Period for the faster EMA. |
| **Slow EMA Length** | 200 | Period for the slower EMA. |
| **Price Source** | Close | Data series to calculate EMAs on. |
| **Custom Stop Loss %** | 0.1% | Stop-loss level as a percentage of entry price. |
| **Target %** | 0.5% | Profit-target level as a percentage of entry. |
| **Show Entry/SL/Target** | ON | Toggle all entry, SL and target visuals. |
📊 What It Plots
Fast EMA (blue) & Slow EMA (white) overlayed on price.
BUY 🟢 label below bar when Fast EMA crosses above Slow EMA.
SELL 🔴 label above bar when Fast EMA crosses below Slow EMA.
❌ (Custom) bubble at entry price if an opposite EMA crossover occurs before price hits your custom stop-loss.
❌ bubble at the stop-loss price when price actually breaches the stop level.
🎯 bubble at target price when price first reaches your profit-target level.
🔔 Alerts & Webhooks
On-screen alert conditions “Mickey’s EMA → BUY” and “Mickey’s EMA → SELL” appear in the Create-Alert dialog.
Dynamic JSON payload sent via alert() when a crossover fires, e.g.:
{
"script": "AAPL",
"scriptType": "equity",
"instrumentType": "NASDAQ",
"timeframe": "5",
"trend": "CE",
"price": 174.25
}
Use these alerts to integrate with bots, chat systems, manual, or any webhook-driven workflow.
🚀 Why Use Mickey’s EMA?
Clarity & Precision: All signals appear exactly at the EMA or price-level of interest.
Custom Risk Management: Define your own stop-loss and target percentages.
Seamless Automation: Dynamic JSON alerts mean zero manual setup for webhooks.
Versatile: Equally effective on intraday charts or daily/weekly timeframes.
Add Mickey’s EMA to your TradingView chart today and get instant, aesthetically-pleasing guidance on trend entries, risk exits, and profit targets—all in one elegant overlay.
Dynamic Fib Pro by Qabas Algo🔹 Dynamic Fib Pro by Qabas Algo
Dynamic Fib Pro is an intelligent Fibonacci-based indicator that adapts to real market behavior by incorporating volatility and momentum into classic Fibonacci levels. This tool is ideal for traders who want realistic, responsive, and smart support/resistance zones rather than static levels.
⸻
🚀 Key Features:
• Adaptive Fibonacci Levels: Each level is dynamically adjusted based on current volatility and momentum strength, offering more relevant price zones.
• Smart Trend Detection: Option to auto-detect trend using SMA20 vs SMA50 crossover or pure price action logic.
• Volatility-Aware Scaling: Levels expand or contract depending on market volatility, avoiding rigid assumptions.
• Momentum-Based Adjustment: Uses range and average price to assess strength and adjust levels accordingly.
• Custom Styling: Choose from dashed, dotted, or solid lines, and control the max level displayed.
• Optional Percentage Labels: View both classic and adjusted Fibonacci % next to each level (e.g., 61.8% → 78.4%).
⸻
🎯 Use Case:
This indicator is built for discretionary traders, swing traders, and scalpers who want to:
• Identify meaningful dynamic support/resistance levels
• React to price behavior in real time
• Incorporate market volatility and strength into their strategy
⸻
⚙️ Settings Overview:
• Show Fibonacci Levels – Toggle main levels on/off
• Max Level – Limit the highest level to keep the chart clean
• Show Percentage Labels – View classic vs adjusted percentages
• Use Moving Averages – Enable SMA20/50 trend filtering
• Line Style – Choose between solid, dashed, or dotted
⸻
📌 Notes:
• Levels are calculated from the last 100 bars (High/Low range)
• Adjustments use both current volatility and 50-bar momentum strength
• The indicator updates in real time on each new bar
⸻
🧠 Created with precision by Qabas Algo — designed to make Fibonacci smarter.
If you like this tool, leave a comment or follow for more advanced indicators!
[Top] LHAMA Consolidation DetectorIntroducing the Low-High Adaptive Moving Average (LHAMA 🦙), a powerful tool designed to help traders visually distinguish between trending and consolidating market phases. Unlike traditional moving averages that can produce false signals in choppy markets, the LHAMA is engineered to flatten out during periods of consolidation and become more responsive when a clear trend emerges.
This indicator's primary function is to act as a "Consolidation Detector." When the LHAMA line goes flat and adopts its "Flat Color," it serves as a clear visual cue that the market is range-bound. Conversely, when the line begins to slope and changes to its Bullish or Bearish color, it signals a potential breakout or the start of a new trend.
How It Works
The LHAMA is a type of adaptive moving average. Its adaptiveness is derived from a unique calculation that measures market "trendiness." It does this by tracking whether new highs or new lows are being made within a specified lookback period.
In a Trending Market: When the price consistently makes new highs or lows, the indicator's responsiveness increases, causing the LHAMA to track the price much more closely and responsively.
In a Consolidating Market: When the price is range-bound and fails to make new highs or lows, the responsiveness decreases significantly. This causes the LHAMA to flatten out and become less sensitive to minor price fluctuations, effectively filtering out market noise.
Key Features
Adaptive Calculation: The core engine of the indicator, which automatically adjusts its smoothing based on trend strength.
Slope-Based Coloring: The line's color dynamically changes based on its slope, providing an at-a-glance view of market conditions: bullish, bearish, or flat.
Multi-Line & Multi-Timeframe (MTF): You can enable up to six fully customizable LHAMA lines. Each line can be configured with its own length, colors, and can even be set to a different timeframe, allowing for comprehensive multi-timeframe analysis on a single chart.
Volatility Clouds: Each LHAMA can display an optional cloud around it. The cloud's width is based on your choice of either the Average True Range (ATR) or Standard Deviation (StdDev), offering a visual representation of volatility.
Volume Weighting: An option to incorporate volume into the adaptive calculation, making the LHAMA even more responsive during high-volume price movements.
How to Use
Identify Consolidation: The primary use case. A flat and consistently colored LHAMA line is a strong indication of a sideways or consolidating market. This can help traders avoid taking trend-following trades in choppy conditions.
Confirm Trends: When the LHAMA begins to slope upwards or downwards and changes to its trend color, it can be used to confirm the direction and strength of a new trend. The steeper the slope, the stronger the momentum, and more solid the directional color.
Dynamic Support & Resistance: Like other moving averages, the LHAMA can act as a dynamic level of support in an uptrend or resistance in a downtrend. The optional cloud can further define these zones.
Multi-MA Ribbon Strategy: By enabling multiple LHAMAs with different lengths (e.g., Fibonacci sequence like 14, 21, 34, 55), you can create a ribbon. The expansion of the ribbon indicates a strong trend, while its contraction signals a weakening trend or consolidation.
Settings Explained
Enable 🦙 Line: A simple checkbox to turn each of the six LHAMA lines on or off.
Length: The lookback period for the LHAMA calculation. Shorter lengths are more responsive, while longer lengths are smoother.
Timeframe: Set a specific timeframe for each LHAMA. Leave blank to use the chart's current timeframe.
Volume Weight: If checked, adds volume weighting to make the LHAMA more responsive to high-volume moves.
Colors (Bullish, Bearish, Flat): Customize the colors for each market state. To only see the line during consolidation, set the Bullish and Bearish colors to 100% transparency. To hide the line during consolidation, set the Flat color to 100% transparency.
Color Sensitivity: This is a crucial setting. Because price scales (tick sizes) vary widely between symbols, this setting allows you to adjust the sensitivity of the slope detection. A lower value requires a steeper slope to trigger a trend color, while a higher value is more sensitive.
Recommended settings are provided in the input tooltip as a starting point:
$5 Tick: 0.25 Sensitivity
$1 Tick: 0.75 Sensitivity
$0.25 Tick: 3 Sensitivity
$0.01 Tick: 50 Sensitivity
$0.005 Tick: 100 Sensitivity
Cloud Settings:
Show Cloud: Toggles the visibility of the volatility cloud around the LHAMA.
Width Based On: Choose between "ATR" or "StdDev" to calculate the cloud's width.
Cloud Length & Width: Set the lookback period and multiplier for the ATR/StdDev calculation to control the size of the cloud.
JXMJXRS - T3 Stack Aligner (Smooth)The JXMJXRS - T3 Stack Aligner is a multi-timeframe trend confirmation tool that uses a smoothed moving average known as the T3. The T3 is built using six layers of exponential moving averages to reduce noise and lag while maintaining a smoother appearance than traditional moving averages. This indicator helps identify when multiple timeframes are aligned in the same direction, giving greater clarity on whether a trend is strong and consistent.
The indicator plots a single T3 line on the chart and changes its colour depending on whether all selected timeframes are showing the same trend direction. This trend condition is based on either the slope of the T3 or a price comparison with the T3, depending on which method is selected. When all timeframes agree that the market is trending up, the line turns green. When they all agree that it is trending down, the line turns red. If the timeframes are not in agreement, the line appears grey. This helps traders avoid uncertainty during periods of mixed or unclear trend behaviour.
The settings allow the user to control how the T3 line is calculated and how trend alignment is measured. The T3 Length setting adjusts how long the base smoothing period is, and the Smoothing Factor controls the weight used in the T3 calculation. The Trend Method lets the user choose between detecting trend direction by slope or by comparing price to the T3. Finally, four timeframes can be selected. All four must meet the trend condition for the green or red colour to appear. If even one timeframe is out of sync, the line will remain grey until alignment returns.
This tool is designed for traders who want to stay aligned with the broader trend across multiple timeframes and filter out short-term noise. It does not provide signals but supports trend-following strategies by confirming direction with stronger confluence.
DTC AIO [India] v2.0DTC AIO v2.0 – Advanced Technical Analysis Suite
This indicator is a comprehensive dashboard designed specifically for Indian equities, providing traders with a unique blend of trend, volatility, volume, and earnings analytics—all in one panel.
Key Features
Multi-Timeframe Volatility Tables:
Instantly view daily, weekly, and monthly Average Daily Range (ADR) values in a compact, color-coded table.
Relative Volume (RVol) Panel:
Displays real-time relative volume in crores, helping you spot unusual activity at a glance.
Strength Gauge:
A proprietary scoring system that quantifies the frequency and magnitude of price bursts, giving you a unique “Strength” score for each symbol.
Earnings & Sales Table:
Automatically fetches and displays quarterly EPS and sales data, with YoY and QoQ growth, color-coded for clarity.
Theme-Aware Design:
All tables and overlays adapt to dark or light chart themes for maximum readability.
Customizable Watermark:
Add your own signature, timeframe, and price change watermark to the chart, with full control over position and color.
Sector & Industry Info:
Instantly see the symbol’s sector and industry in the main metrics table.
How It Works
Trend & Volatility:
Uses a blend of moving averages (user-selectable type and length) and price/volume patterns to highlight actionable setups.
Strength Gauge:
Calculates a proprietary score based on the frequency and size of price bursts over multiple lookback periods. This algorithm is unique to this script and not available in open-source alternatives.
Relative Volume:
Compares current volume to historical averages, displaying the result in crores for Indian market conventions.
Earnings Table:
Fetches the last four quarters of EPS and sales, automatically calculating and color-coding YoY and QoQ growth.
All tables and overlays are locked to price and update in real time.
How to Use
Add the indicator to your chart.
Customize table positions, watermark, and theme via the settings panel.
Use the dashboard to quickly assess trend, volatility, strength, and earnings for any Indian equity.
Hover over table cells for tooltips and additional information.
Why Closed Source?
This script is closed-source due to the proprietary nature of the “Strength Gauge” algorithm and the integrated dashboard logic, which are not available in open-source scripts. The unique scoring and visualization methods provide a competitive edge for users.
Notes
Designed for Indian equities, but can be used on any symbol.
All calculations are performed in real time and optimized for performance.
For best results, use on daily or higher timeframes.
If you have questions or feedback, please use the TradingView comments section.v
Multiple SMAsPlots multiple SMAs in a single indicator.
This script only plots the SMAs if the timeframe is set to daily.
- SMA10 in light blue
- SMA20 in yellow
- SMA50 in red
- SMA100 in green
- SMA200 in blue
It also plots the crosses between SMA20 and SMA50
Universal Valuation | Lyro RSUniversal Valuation
⚠️Disclaimer: This indicator is a tool for technical analysis and does not provide guaranteed results. It should be used in conjunction with other analysis methods and proper risk management practices. The creators of this indicator are not responsible for any financial decisions made based on its signals.
Overview
The Universal Valuation indicator helps identify whether the market is undervalued/cheap or overvalued/expensive. And another mode this indicator offers is This cutting-edge tool works flawlessly ACROSS ALL TIMEFRAMES & TICKERS/CHARTS.
By combining regular TradingView indicators & some of our valuation indicators basic/simple with advanced statistical functions, this indicator offers a powerful, universal valuation tool.
Key Features
INPUTS: The Universal Valuation indicator offers flexibility through its customizable input sections. The "Indicator Settings" let you adjust lengths for the raw indicators and statistical functions. The "Signals" section defines thresholds for background color changes, helping you visually spot key market moments. The "Colors" section allows you to pick from pre-defined schemes or personalize colors for better clarity. Lastly, the "Tables" section gives you full control over the UV table’s size and positioning, including options to overlay it on the chart or place it in the allocated space.
A DEEPER INSIGHT: This indicator is built around three distinct categories: "UVM Andromeda," "UVM Sentinel," and "UVM Nexus." Each category has three different drivers. The statistical function powering this indicator is the Z-score. The Z-score is an incredibly powerful tool that helps determine if the market is overvalued/expensive or undervalued/cheap, offering critical insights for traders."
Plotting: The plotted value represents the average of all the drivers. In other words, it is the combined average of all 9 Z-scored indicators, providing a balanced and comprehensive market valuation.
What is Z-score? & Why does this system use it?
Z-score is an advanced statistical function used to measure how far a value deviates from the average in a data set. The formula for Z-score is: (x - h) / o, where x is the observed value, h is the average (mean) of the data set, and o is the standard deviation.
This system uses the Z-score because it helps determine whether the market is overvalued or undervalued based on historical data and how we apply the calculation. By measuring how far a value deviates from the average, the Z-score provides a clearer and more objective valuation of market conditions. In our case, a Z-score of -3 indicates an undervalued market, while a Z-score of 3 signals an overvalued market.
UVM Andromeda:
UVM stands for Universal Valuation Model, which is the core of this indicator. Andromeda, one of the most stunning galaxies in the universe, inspired by its name. We chose this name because a powerful indicator should not only be effective but also visually appealing.
You might be wondering what drives UVM Andromeda. The three key drivers are Price, RSI, and ROC. These indicators are pre-defined, while the "Indicator Settings" allow you to adjust the length of the Z-score calculation, refining how the model analyzes market conditions.
UVM Sentinel:
Sentinel, refers to a guard or watchman, someone or something that keeps watch and provides protection. In our case this name refers to a model that actively observes market conditions, acting as a vigilant tool that signals important shifts in valuation.
Wondering what drives UVM Sentinel? The three key drivers are BB%, CCI, and Crosby. While these indicators are simple on their own, applying our Z-score function elevates them to a whole new level, enhancing their ability to detect market conditions with greater accuracy.
UVM Nexus:
We chose the name Nexus simply because it sounds cool—there’s no deeper meaning behind it for us. However, the word itself does have a meaning; it refers to a connection or link between multiple things.
The three key drivers for UVM Nexus are the Sharpe, Sortino, and Omega ratios. These are all asset performance metrics, but by applying the Z-score, we transform them into powerful valuation indicators/drivers, giving you a deeper insight into market conditions.
Why do we use 9 different indicators instead of 1?
That's a great question, and the answer is quite simple. Think of it like this: if you have one super soldier, and they miss a shot, it’s game over. But if you have many soldiers, even if one misses, the others can step in and take the shot. The strength of using multiple indicators lies in their collective power – if one misses, the others still provide valuable insights, making the overall system more reliable.
Final Thoughts:
In our Universal Valuation indicator, you have the flexibility to customize it however you like using our inputs. The system is divided into three distinct categories, with each category containing three indicators. The value plotted on the chart is the average of all nine indicators. We apply the Z-score, an advanced statistical function, to each of these nine indicators. The final plotted average is the average of all the Z-scores, giving you a comprehensive and refined market valuation. This indicator can work on any timeframe & chart ticker.
50/100 EMA Crossover with Candle Confirmation📘 **50/100 EMA Crossover with Candle Confirmation – Strategy Description**
The **50/100 EMA Crossover with Candle Confirmation** is a trend-following strategy designed to filter high-probability entries by combining exponential moving average (EMA) crossovers with strong price action confirmation. This strategy aims to reduce false signals commonly associated with EMA-only systems by requiring a **candle close confirmation in the direction of the trend**, making it more reliable for intraday or swing trading across Forex, crypto, and stock markets.
---
### 🔍 **Core Logic**
* The strategy is based on the interaction of the **50 EMA** (fast-moving average) and the **100 EMA** (slow-moving average).
* **Trend direction** is determined by the crossover:
* **Bullish Trend**: When the 50 EMA crosses **above** the 100 EMA.
* **Bearish Trend**: When the 50 EMA crosses **below** the 100 EMA.
* To **filter out false breakouts**, a **candle confirmation** is used:
* For a **Buy signal**: After a bullish crossover, wait for a strong bullish candle (e.g., full-body green candle) to **close above both EMAs**.
* For a **Sell signal**: After a bearish crossover, wait for a strong bearish candle to **close below both EMAs**.
---
### ✅ **Entry Conditions**
**Buy Entry:**
* 50 EMA crosses above 100 EMA.
* Latest candle closes **above both EMAs**.
* Candle must be bullish (green/full body preferred).
**Sell Entry:**
* 50 EMA crosses below 100 EMA.
* Latest candle closes **below both EMAs**.
* Candle must be bearish (red/full body preferred).
---
### 🛑 **Exit or Take-Profit Options**
* **Fixed TP/SL**: 1:2 or 1:3 risk-reward.
* **Trailing Stop**: Based on recent swing highs/lows or ATR.
* **EMA Exit**: Exit trade when the candle closes on the opposite side of 50 EMA.
---
### ⚙️ **Best Settings**
* **Timeframes**: 5M, 15M, 1H, 4H (works well on most).
* **Markets**: Forex, Crypto (e.g., BTC/ETH), Indices (e.g., NASDAQ, NIFTY50).
* **Recommended filters**:
* Use with RSI divergence or volume confirmation.
* Avoid using during high-impact news (especially on lower timeframes).
---
### 🧠 **Why This Works**
The 50/100 EMA crossover provides a **medium-term trend signal**, reducing noise seen in fast EMAs (like 9 or 21). The candle confirmation adds a **momentum filter**, ensuring price supports the directional bias. This makes it suitable for traders who want a balance of trend and entry precision without overcomplicating with too many indicators.
---
### 📈 **Advantages**
* Simple yet effective for identifying trends.
* Filters out fakeouts using candle confirmation.
* Easy to automate in Pine Script or other trading bots.
* Can be combined with support/resistance or SMC zones for better confluence.
---
### ⚠️ **Limitations**
* May lag slightly in ranging markets.
* Late entries possible due to confirmation candle.
* Works best with additional volume or volatility filter.
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix====== 52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix ======
◆ Overview
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix is an advanced multi-band indicator that integrates Bollinger Bands, Fibonacci levels, and ATR-based Spike signals (for detecting bullish/bearish pressure and volatility surges).
Built on a VWMA (Volume-Weighted Moving Average) foundation, it displays standard deviation bands, Fibonacci extension zones, multi-level expansions, and real-time bullish/bearish spike alerts alongside price labeling and color gradation.
This tool is designed to help traders visually analyze and react to:
- Key support/resistance zones
- Overbought/oversold boundaries
- Sudden directional volatility shifts (spikes)
All parameters are customizable to suit a wide variety of trading strategies and styles.
====== ◆ Key Features ======
- Multi-structured Bollinger Bands: VWMA-based center line with ± standard deviation bands and multiple levels of outer extension (+10% to +50%)
- Integrated Fibonacci Bands: Levels at 23.6%, 38.2%, 50%, 61.8%, and 78.6% above and below the center line
- ATR-based Spike Signal Alerts: Automatically detects sudden bullish/bearish volatility surges and triggers directional warning labels (“Bullish Spike Warning” or “Bearish Spike Warning”)
- Real-Time Price Labels & Visual Gradation: Each important band and level includes live price labeling and color-coded zone visualization
- Fully Adjustable Parameters & Panel Display Options: All inputs and visual elements can be toggled or customized
====== ◆ Technical Basis ======
■ Bollinger Bands & Multi-Extension
- Center Line: VWMA (Volume-Weighted Moving Average)
- Bands: ± Standard deviation (default 2.5), with extensions in +10% increments up to +50%
- Extension Zones: Reveal reactions to high volatility or trend continuation
■ Fibonacci Bands
- Symmetrical expansion from center line using Fibonacci ratios
- Visually highlights layered historical retracement zones and price clustering
■ ATR-Based Spike Signal
- Adaptive to chart timeframe (ATR Length & Multiplier auto-adjusted)
- Spike alerts triggered when price exceeds upper/lower ATR bands
- One signal per X bars to filter noise (interval adjustable)
■ Live Visual Labeling & Color Gradients
- Intelligently labeled bands with dynamic color shading between levels
- Helps clarify price geometry and zone importance
====== ◆ Practical Applications ======
■ Spike Signal Interpretation
- Bullish Spike Warning — Market plunged below ATR range → Potential oversold rebound signal
- Bearish Spike Warning — Market surged above ATR range → Potential overbought reversal signal
■ Band & Level Interaction
- Ripple behavior between Fibonacci levels signals trend momentum/weakness
- Penetration through outer expansion bands flags possible trend strength or volatility spikes
■ Integrated Trading Strategies
- Reversal Trades: Bounces between extension and Fibonacci levels
- Breakout Confirmation: Spike signals backing breakout moves
- Directional Bias: Trend-following confirmation when price exceeds multiple zones
====== ◆ Advanced Setting Options ======
All parameters can be fine-tuned for your trading strategy, market, and timeframe.
■ Bollinger Band Period
_Default:_ 20
_Description:_ Number of bars for VWMA and standard deviation. Shorter (10–14): faster but noisier. Longer (30–50): smoother, better for trend analysis.
■ Standard Deviation Multiplier
_Default:_ 2.5
_Description:_ Controls main band width. Lower values (1.5–2.0): More signals, higher sensitivity. Higher values (2.5–3.0): Fewer signals, higher reliability.
■ Band Extension Ratios
_Default:_ +10%, +20%, +30%, +40%, +50%
_Description:_ Amount to expand beyond standard bands. Used for detecting extended zones or extreme price movement areas.
■ ATR Length
_Default:_ Auto depending on timeframe (typically 14–30)
_Description:_ Period for calculating ATR. Shorter: Reacts faster, more sensitive. Longer: Smoother, filters short noise.
■ ATR Multiplier
_Default:_ Auto (1.75 to 2.8)
_Description:_ Sets the threshold for Spike signals. Lower: More frequent but smaller spikes. Higher: Triggers fewer but stronger signals.
■ Fibonacci Levels
_Default:_ 0.236, 0.382, 0.5, 0.618, 0.786
_Description:_ Determines how far Fibonacci bands extend from the center. Aids in identifying key retracement and reaction points.
■ Spike Signal Interval
_Default:_ 7 bars
_Description:_ Minimum bar separation between consecutive spike signals. Prevents signal overflooding from consecutive candles.
■ Labels & Coloring Display
_Toggle ON/OFF_
Show/hide all price labels and visual zone shading. Useful for decluttering or focusing on strategy testing.
Try adjusting these inputs based on your strategy and market conditions. Optimize for scalping, swing trading, day trading, or investing by testing different lengths, bands, and spike sensitivities.
====== ◆ Indicator Synergies ======
- Combine with moving averages, RSI, or MACD for breakout filters
- Use with support/resistance lines or Fibonacci retracements to validate critical zones
- Pair with Keltner Channels, ATR Bands, or volume-based tools for enhanced volatility tracking
====== ◆ Conclusion ======
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix offers a cohesive framework that connects price level analysis, trend structure, and volatility-driven directional signals—all in one indicator. It’s not just a visualization tool, but a decision-support system for both reactive trade entries and proactive risk management. With full parameter adjustability and a clear structural layout, it empowers traders to adapt across assets, timeframes, and strategies—efficiently and confidently.
====== ◆ Disclaimer ======
This indicator is for informational and educational purposes only.
Past performance does not guarantee future results. Always apply proper risk management.
====== 52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix ======
◆ 개요
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix는 볼린저 밴드, 피보나치 레벨, ATR 기반 스파이크 신호(상방/하방 압력 감지)를 결합한 고급 멀티 밴드 인디케이터입니다.
VWMA(거래량 가중 이동평균) 기반 중심선 위에 표준편차 밴드, 피보나치 확장 레벨, 다중 확장 밴드, 실시간 상·하방 스파이크 경고(라벨)와 가격 레이블·컬러 그라데이션이 동시에 제공됩니다.
트레이더가 주요 지지/저항, 과매수·과매도, 급격한 변동성 스파이크(방향성 돌파)를 한눈에 시각적으로 분석할 수 있도록 디자인되었습니다.
모든 설정값은 트레이딩 스타일에 맞춰 자유롭게 조절 가능합니다.
====== ◆ 주요 특징 ======
- VWMA 기반 중심선과 표준편차 밴드(±), 10~50% 단계별 외곽 확장
- 피보나치 밴드: 중심선 기준 23.6%, 38.2%, 50%, 61.8%, 78.6% 상·하단 동시 표기
- ATR 기반 스파이크 신호: 강한 상·하방 변동성 구간 실시간 감지(‘Bullish Spike Warning’, ‘Bearish Spike Warning’ 라벨)
- 실시간 가격 레이블 & 컬러 구간 구분
- 밴드/변동성/피보나치/시각 옵션 등 설정 완전 자유화
====== ◆ 기술적 기반 ======
■ 볼린저 밴드/확장
- VWMA 중심선, ± 표준편차 밴드(기본 2.5), 단계별 외곽 확장(10~50%)
■ 피보나치 밴드
- 중심선 기준 대칭 배치(0.236, 0.382, 0.5, 0.618, 0.786)
■ ATR 기반 스파이크 신호
- 차트 주기에 자동 최적화(ATR 기간/배수), 상단·하단 ATR 밴드 돌파 시 스파이크 라벨
- 반복 신호 방지(신호 간격 조정 가능)
■ 실시간 레이블 & 컬러 그라데이션
- 주요 밴드, 피보나치, 확장 레벨별 가격 표시 및 구간 별도 색상
====== ◆ 실용적 응용 ======
■ 스파이크 신호 해석
- Bullish Spike Warning: 과매도 구간(강한 하락 후 단기 반등 가능성)
- Bearish Spike Warning: 과매수 구간(급등 이후 단기 되돌림 가능성)
■ 밴드 & 레벨 시그널
- 피보나치 레벨 간 파동/추세 강도 진단
- 외곽 확장 밴드 돌파 시 강한 추세 혹은 변동성 집중 구간 인식
■ 통합 트레이딩 전략
- 주요 밴드·피보나치 간 바운스, 전환 패턴 기반 반전매매
- 스파이크 신호와 결합한 돌파 추종·추세 확정 대응
- 다중 구간 통과 시 방향성 강화 신호 등급별 분할 대응
====== ◆ 고급 설정 옵션 ======
트레이딩 스타일, 차트 주기, 시장 환경에 따라 모든 항목을 직접 조정할 수 있습니다.
■ 볼린저 밴드 기간 (Bollinger Band Period)
기본값: 20
VWMA 및 표준편차 산출에 적용할 캔들 수
짧게(10~14): 신호 빠르며 노이즈 많음
길게(30~50): 깔끔한 추세 중시
■ 표준편차 계수 (Standard Deviation Multiplier)
기본값: 2.5
밴드 폭 조절
1.5~2.0: 민감, 많이 신호
2.5~3.0: 신뢰도 높고 드문 신호
■ 밴드 확장 비율 (Band Extension Ratios)
기본값: 10%, 20%, 30%, 40%, 50%
기본 밴드에서 외곽 확장 단계
극단 변동성, 피로구간 등 감지
■ ATR 기간 (ATR Length)
기본값: 자동(보통 14~30)
ATR 산출 캔들 수
짧을수록 민감, 길수록 부드러움
■ ATR 배수 (ATR Multiplier)
기본값: 자동(1.75~2.8)
스파이크 신호 감지 문턱값
낮게: 잦고 약한 신호
높게: 드문 강한 신호
■ 피보나치 레벨 (Fibonacci Levels)
기본값: 0.236, 0.382, 0.5, 0.618, 0.786
중심선으로부터 각 밴드 거리
주요 지지/저항, 파동구조 세분화
■ 스파이크 신호 간격 (Spike Signal Interval)
기본값: 7
연속적 신호 과다 방지용 최소 캔들 수
높을수록 과발생 차단
■ 레이블/채색 표시 (Labels & Coloring)
On/Off
가격 레이블·영역 컬러 표시 ON/OFF
시장/전략별로 세부 세팅을 바꿔가며 직접 테스트 해보세요!
====== ◆ 시너지 활용 ======
- 이동평균, RSI, MACD 등과 조합시 신호 필터링
- 기존 수평 지지/저항, 피보나치 리트레이스먼트 등과 병용
- ATR, 켈트너밴드, 거래량 등과 복합 분석 가능
====== ◆ 결론 ======
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix는 가격 구조, 변동성 이벤트, 방향성 신호를 하나로 통합한 고급 매매 지원 시스템입니다.
스캘핑, 스윙, 포지션 트레이딩 등 다양한 전략에 맞게 모든 파라미터를 세밀하게 조율할 수 있습니다.
현대 트레이딩 환경에 최적화된 정밀 결정 지원 도구로 활용하세요.
====== ◆ 면책 조항 ======
본 지표는 정보 제공 및 교육 목적입니다.
과거 실적이 미래의 수익을 보장하지 않으므로 반드시 철저한 리스크 관리를 병행하세요.
20-Day SMA BIAS%20-day Bias is a commonly used indicator in technical analysis. It is used to measure the gap between the stock price and its 20-day moving average to determine whether the stock price deviates from the normal state and whether there is an overbought or oversold phenomenon.
How to calculate the 20-day deviation value:
The calculation formula of the deviation rate is: ((closing price of the day - 20-day moving average price) / 20-day moving average price) * 100%.
Interpretation of 20-day deviation value:
Positive deviation rate:
Indicates that the stock price is higher than the 20-day moving average, which means that the stock price is high and may face correction pressure.
Negative deviation rate:
Indicates that the stock price is lower than the 20-day moving average, which means that the stock price is low and there may be a rebound opportunity.
Absolute value of the deviation rate:
The larger the absolute value, the higher the deviation of the stock price, and the higher the degree of overbought or oversold.
Apply the deviation rate to determine the buying and selling opportunities:
Positive deviation rate is too large:
When the positive deviation rate of the stock price from the 20-day moving average is too large, and the stock price is already at a high level, this may be a sell signal.
Negative deviation rate is too large:
When the negative deviation rate of the stock price from the 20-day moving average is too large, and the stock price is already at a low level, this may be a buy signal.
Stock price fluctuates around the moving average:
Stock price usually fluctuates around the moving average and adjusts after over-rising or over-falling.
Practical operation suggestions:
The standards of the market and individual stocks are different:
When the positive and negative deviation rate of the market and the quarterly line is greater than 5%, there is a greater chance of correction; large-cap stocks are between 5% and 10%; small and medium-sized stocks may be above 15% to 20%.
Combined with other indicators:
The deviation rate is only one of the technical analysis indicators. It is recommended to combine it with other indicators, such as KD indicators, RSI, etc., to make a comprehensive judgment and improve accuracy.
Reference to historical experience:
You can refer to the situation where the deviation rate of the stock was too large in the past to determine whether the current deviation rate is also too large.
Summary:
The 20-day deviation value is an indicator to determine whether the stock price is overbought or oversold, which can help investors determine the timing of buying and selling, but it needs to be combined with other indicators and historical data, and adjusted according to market conditions.
10/20 MA Coil: Progressive Colors & Multi-Day BreakoutThis indicator detects price “coil” setups and highlights potential breakout or breakdown opportunities using moving average alignment and volatility compression.
Features:
• Coil Detection:
• Identifies consolidation when:
• The 10 and 20 MAs are tightly aligned (within user-defined tolerance)
• Price is above both MAs and within 1.5x ADR of them
• The 50 MA is rising
• Progressive Coil Coloring:
• Coil candles are colored in progressively darker orange as the streak continues
• Bullish Breakout Signal:
• Triggers when a green candle follows a coiled bar
• The candle’s body must be greater than or equal to 1 ATR
• Colored lime green
• Bearish Breakdown Signal:
• Triggers when a red candle follows a coiled bar
• The candle’s body must be greater than or equal to 1 ATR to the downside
• Colored black
• Custom Candle Rendering:
• Candle body color represents coil or breakout state
• Wick and border are red or green to reflect price direction
• Optional Debug Tools:
• Coil streak, ATR, and distance from MAs can be plotted for deeper analysis
This script is designed for traders looking to spot price compression and prepare for high-probability moves following low-volatility setups.
EMA Curl Strength+EMA Curl Strength+
Description:
This indicator provides a statistically normalized view of EMA slope momentum using Z-score transformation. By evaluating the rate of change of an EMA and comparing it against its historical behavior, the script highlights momentum shifts in a dynamic, adaptive way.
⸻
How It Works:
• Calculates the slope (percentage change) of a chosen EMA.
• Normalizes the slope using Z-score over a custom lookback period.
• Smooths the resulting signal and computes two signal lines for comparison.
• Assigns dynamic colors based on user-defined Z-score thresholds for mild, moderate, and strong momentum in both directions.
⸻
Visual Features:
• Gradient fill between the Z Curl Line and Signal 1 to highlight slope acceleration.
• Histogram showing the difference between the Z Curl Line and its signal.
• Optional signal crossover shapes between configurable pairs (e.g., Z Curl vs. Signal).
• Background highlights when the Z Curl Line exceeds ±2, indicating strong trending behavior.
⸻
Customization:
• Adjustable EMA length, smoothing lengths, signal lengths, histogram smoothing, and Z-score lookback.
• Separate color controls for:
• Z-score strength bands (mild/moderate/strong up/down)
• Histogram bars
• Signal lines
• Background highlight zones
• Crossover shapes
⸻
Use Cases:
• Momentum Confirmation: Confirm strength when Z Curl exceeds ±2 with matching background highlights.
• Trend Entry Timing: Look for trades when Z Curl crosses above or below the 0-line.
• Scalping: Capture quick directional moves when momentum accelerates.
• Trend Following: Use strong Z Curl values to confirm trade direction and filter sideways action.
• Divergence Detection: Spot divergences between price and Z Curl movement to anticipate reversals.
AI Breakout Bands (Zeiierman)█ Overview
AI Breakout Bands (Zeiierman) is an adaptive trend and breakout detection system that combines Kalman filtering with advanced K-Nearest Neighbor (KNN) smoothing. The result is a smart, self-adjusting band structure that adapts to dynamic market behavior, identifying breakout conditions with precision and visual clarity.
At its core, this indicator estimates price behavior using a two-dimensional Kalman filter (position + velocity), then enhances the smoothing process with a nonlinear, similarity-based KNN filter. This unique blend enables it to handle noisy markets and directional shifts with both speed and stability — providing breakout traders and trend followers a reliable framework to act on.
Whether you're identifying volatility expansions, capturing trend continuations, or spotting early breakout conditions, AI Breakout Bands gives you a mathematically grounded, visually adaptive roadmap of real-time market structure.
█ How It Works
⚪ Kalman Filter Engine
The Kalman filter models price movement as a state system with two components:
Position (price)
Velocity (trend direction)
It recursively updates predictions using real-time price as a noisy observation, balancing responsiveness with smoothness.
Process Noise (Position) controls sensitivity to sudden moves.
Process Noise (Velocity) controls smoothing of directional flow.
Measurement Noise (R) defines how much the filter "trusts" live price data.
This component alone creates a responsive yet stable estimate of the market’s center of gravity.
⚪ Advanced K-Neighbor Smoothing
After the Kalman estimate is computed, the script applies a custom K-Nearest Neighbor (KNN) smoother.
Rather than averaging raw values, this method:
Finds K most similar past Kalman values
Weighs them by similarity (inverse of absolute distance)
Produces a smoother that emphasizes structural similarity
This nonlinear approach gives the indicator an AI feature — reacting fast when needed, yet staying calm in consolidation.
█ How to Use
⚪ Trend Recognition
The line color shifts dynamically based on slope direction and breakout confirmation.
Bullish conditions: price above the mid band with positive slope
Bearish conditions: price below the mid band with negative slope
⚪ Breakout Signals
Price breaking above or below the bands may signal momentum acceleration.
Combine with your own volume or momentum confirmation for stronger entries.
Bands adapt to market noise, helping filter out low-quality whipsaws.
█ Settings
Process Noise (Position): Controls Kalman filter’s sensitivity to price changes.
Process Noise (Velocity): Controls smoothing of directional component.
Measurement Noise (R): Defines how much trust is placed in price data.
K-Neighbor Length: Number of historical Kalman values considered for smoothing.
Slope Calculation Window: Number of bars used to compute trend slope of the smoothed Kalman.
Band Lookback (MAE): Rolling period for average absolute error.
Band Multiplier: Multiplies MAE to determine band width.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
EMA and Dow Theory Strategies🌐 Strategy Description
📘 Overview
This is a hybrid strategy that combines EMA crossovers, Dow Theory swing logic, and multi-timeframe trend overlays. It is suitable for intraday to short-term trading on any asset class: crypto, forex, stocks, and indices.
The strategy provides precise entry/exit signals, dynamic stop-loss and scale-out, and highly visual trade guidance.
🧠 Key Features
・Dual EMA crossover system (applied to both symbol and external index)
・Dow Theory-based swing high/low detection for trend confirmation
・Visual overlay of higher timeframe swing trend (htfTrend)
・RSI filter to avoid overbought/oversold entries
・Dynamic partial take-profit when trend weakens
・Custom stop-loss (%) control
・Visualized trade PnL labels directly on chart
・Alerts for entry, stop-loss, partial exit
・Gradient background zones for swing zones and trend visualization
・Auto-tracked metrics: APR, drawdown, win rate, equity curve
⚙️ Input Parameters
| Parameter | Description |
| ------------------------- | -------------------------------------------------------- |
| Fast EMA / Slow EMA | Periods for detecting local trend via EMAs |
| Index Fast EMA / Slow EMA | EMAs applied to external reference index |
| StopLoss | Maximum loss threshold in % |
| ScaleOut Threshold | Scale-out percentage when trend changes color |
| RSI Period / Levels | RSI period and overbought/oversold levels |
| Swing Detection Length | Number of bars used to detect swing highs/lows |
| Stats Display Options | Toggle PnL labels and position of statistics table |
🧭 About htfTrend (Higher Timeframe Trend)
The script includes a higher timeframe trend (htfTrend) calculated using Dow Theory (pivot highs/lows).
This trend is only used for visual guidance, not for actual entry conditions.
Why? Strictly filtering trades by higher timeframe often leads to missed opportunities and low frequency.
By keeping htfTrend visual-only, traders can still refer to macro structure but retain trade flexibility.
Use it as a contextual tool, not a constraint.
ストラテジー説明
📘 概要
本ストラテジーは、EMAクロスオーバー、ダウ理論によるスイング判定、**上位足トレンドの視覚表示（htfTrend）**を組み合わせた複合型の短期トレーディング戦略です。
仮想通貨・FX・株式・指数など幅広いアセットに対応し、デイトレード〜スキャルピング用途に適しています。
動的な利確/損切り、視覚的にわかりやすいエントリー/イグジット、統計表示を搭載しています。
🧠 主な機能
・対象銘柄＋外部インデックスのEMAクロスによるトレンド判定
・ダウ理論に基づいたスイング高値・安値検出とトレンド判断
・上位足スイングトレンド（htfTrend）の視覚表示
・RSIフィルターによる過熱・売られすぎの回避
・トレンドの弱まりに応じた部分利確（スケールアウト）
・**損切り閾値（％）**をカスタマイズ可能
・チャート上に損益ラベル表示
・アラート完備（エントリー・決済・部分利確）
・トレンドゾーンを可視化する背景グラデーション
・勝率・ドローダウン・APR・資産増加率などの自動表示
| 設定項目名 | 説明内容 |
| --------------------- | -------------------------- |
| Fast EMA / Slow EMA | 銘柄に対して使用するEMAの期間設定 |
| Index Fast / Slow EMA | 外部インデックスのEMA設定 |
| 損切り（StopLoss） | 損切りラインのしきい値（%で指定） |
| 部分利確しきい値 | トレンド弱化時にスケールアウトする割合（%） |
| RSI期間・水準 | RSI計算期間と、過熱・売られすぎレベル設定 |
| スイング検出期間 | スイング高値・安値の検出に使用するバー数 |
| 統計表示の切り替え | 損益ラベルや統計テーブルの表示／非表示選択 |
🧭 上位足トレンド（htfTrend）について
本スクリプトには、上位足でのスイング高値・安値の更新に基づく**htfTrend（トレンド判定）が含まれています。
これは視覚的な参考情報であり、エントリーやイグジットには直接使用されていません。**
その理由は、上位足を厳密にロジックに組み込むと、トレード機会の損失が増えるためです。
このスクリプトでは、**判断の補助材料として「表示のみに留める」**設計を採用しています。
→ 裁量で「利確を早める」「逆張りを避ける」判断に活用可能です。
Multi-Method Moving Average v6.0Multi-Methods Moving Average Indicator is a versatile tool designed for traders who want to identify key price levels that can act as support and resistance in the market. This indicator utilizes multiple moving averages (MAs) to help visualize price trends and potential reversal points, aiding traders in making informed decisions.
Features
Multiple Moving Averages: The indicator calculates and displays six different moving averages (MA1 to MA6) based on user-defined periods. This allows traders to analyze short-term and long-term trends effectively.
Customizable Inputs: Users can customize the periods for each moving average and select the type of moving average (SMA, EMA, WMA) that best suits their trading strategy.
Price Source Selection: The indicator allows users to choose the price source (Open, Close, High, Low, or the average of Open and Close) for calculating the moving averages, providing flexibility in analysis.
Color-Coded Signals: The moving averages are color-coded based on the current price relative to the moving average, helping traders quickly identify bullish or bearish conditions.
How to Use
Adding the Indicator:
Open TradingView and navigate to the chart you wish to analyze.
Click on the "Indicators" button at the top of the chart.
Search for "Multi-Methods Moving Average" and select the indicator to add it to your chart.
Customizing Settings:
Click on the gear icon next to the indicator's name in the chart legend to open the settings menu.
Adjust the periods for each moving average to fit your trading style. Common settings include 9, 26, 52, 100, 200, and 500 periods.
Choose the type of moving average you prefer (SMA, EMA, or WMA).
Select the price source that aligns with your trading strategy.
Interpreting the Indicator:
Moving Averages: Observe the position of the moving averages relative to the price. If the price is above the moving average, it indicates a bullish trend; if below, it suggests a bearish trend.
Crossover Signals: Look for crossovers between the moving averages. A crossover where a shorter moving average crosses above a longer moving average may signal a potential buy opportunity, while a crossover in the opposite direction may indicate a sell opportunity.
Support and Resistance Levels: Use the moving averages as dynamic support and resistance levels. Price often reacts at these levels, providing potential entry and exit points for trades.
Risk Management:
Always combine the insights from this indicator with other forms of analysis, such as price action, volume analysis, and market sentiment.
Set stop-loss and take-profit levels based on the identified support and resistance levels to manage your risk effectively.
Conclusion
The Support & Resistance Indicator is an essential tool for traders looking to enhance their market analysis. By leveraging multiple moving averages and customizable settings, traders can gain a clearer understanding of market trends and make more informed trading decisions.
Auto Intelligence Selective Moving Average(AI/MA)# 🤖 Auto Intelligence Moving Average Strategy (AI/MA)
**AI/MA** is a state-adaptive moving average crossover strategy designed to **maximize returns from golden cross / death cross logic** by intelligently switching between different MA types and parameters based on market conditions.
---
## 🎯 Objective
To build a moving average crossover strategy that:
- **Adapts dynamically** to market regimes (trend vs range, rising vs falling)
- **Switches intelligently** between SMA, EMA, RMA, and HMA
- **Maximizes cumulative return** under realistic backtesting
---
## 🧪 materials amd methods
- **MA Types Considered**: SMA, EMA, RMA, HMA
- **Parameter Ranges**: Periods from 5 to 40
- **Market Conditions Classification**:
- Based on the slope of a central SMA(20) line
- And the relative position of price to the central line
- Resulting in 4 regimes: A (Bull), B (Pullback), C (Rebound), D (Bear)
- **Optimization Dataset**:
- **Bybit BTCUSDT.P**
- **1-hour candles**
- **2024 full-year**
- **Search Process**:
- **Random search**: 200 parameter combinations
- Evaluated by:
- `Cumulative PnL`
- `Sharpe Ratio`
- `Max Drawdown`
- `R² of linear regression on cumulative PnL`
- **Implementation**:
- Optimization performed in **Python (Pandas + Matplotlib + Optuna-like logic)**
- Final parameters ported to **Pine Script (v5)** for TradingView backtesting
---
## 📈 Performance Highlights (on optimization set)
| Timeframe | Return (%) | Notes |
|-----------|------------|----------------------------|
| 6H | +1731% | Strongest performance |
| 1D | +1691% | Excellent trend capture |
| 12H | +1438% | Balance of trend/range |
| 5min | +27.3% | Even survives scalping |
| 1min | +9.34% | Robust against noise |
- Leverage: 100x
- Position size: 100%
- Fees: 0.055%
- Margin calls: **none** 🎯
---
## 🛠 Technology Stack
- `Python` for data handling and optimization
- `Pine Script v5` for implementation and visualization
- Fully state-aware strategy, modular and extendable
---
## ✨ Final Words
This strategy is **not curve-fitted**, **not over-parameterized**, and has been validated across multiple timeframes. If you're a fan of dynamic, intelligent technical systems, feel free to use and expand it.
💡 The future of simple-yet-smart trading begins here.
MA Signal IndicatorMA Signal Indicator
The MA Signal Indicator is a customizable designed to identify potential trading opportunities based on price interactions with a Simple Moving Average (SMA). It incorporates risk management features such as stop-loss (SL), take-profit (TP), and breakeven levels, calculated using the Average True Range (ATR). The indicator is visually intuitive, overlaying trade signals, price levels, and colored zones directly on the chart.
Key Features:
1. Moving Average-Based Signals:
• Generates buy (long) signals when the price crosses above a user-defined SMA (default: 55 periods).
• Generates sell (short) signals when the price crosses below the SMA.
• Long and short trades can be independently enabled or disabled via input settings.
2. Risk Management:
• Stop-Loss (SL): Set as a multiple of the ATR (default: 1x ATR) below the entry price for long trades or above for short trades.
• Take-Profit (TP): Set as a multiple of the ATR (default: 5x ATR) above the entry price for long trades or below for short trades.
• Breakeven Level: A trigger level (default: 2x ATR) where traders may choose to move their stop-loss to breakeven, optionally displayed on the chart.
3. Visual Feedback:
• SMA Line: Plotted in orange (default: 55-period SMA) for trend reference.
• Trade Zone: Highlights the area between the stop-loss and take-profit levels with a semi-transparent green (long) or red (short) background.
• Price Lines: Displays entry price (white), stop-loss (red), take-profit (green), and breakeven level (gray, optional) as horizontal lines during active trades.
• Signal Markers: Triangular markers indicate entry points (green triangle up for long, red triangle down for short).
• Exit Markers: Labels show when a trade hits the take-profit (green checkmark) or stop-loss (red cross).
4. Trade Logic:
• Only one trade is active at a time (long or short).
• Trades are exited when either the stop-loss or take-profit is hit, resetting the indicator for the next signal.
• Ensures signals are only triggered when not already in a trade, avoiding duplicate entries.
Inputs:
• MA Period: Length of the SMA (default: 55).
• ATR Period: Period for ATR calculation (default: 5).
• SL Multiplier: ATR multiplier for stop-loss (default: 1.0).
• TP Multiplier: ATR multiplier for take-profit (default: 5.0).
• Move to Breakeven After: ATR multiplier for breakeven trigger (default: 2.0).
• Show Break Even Line: Option to display the breakeven level (default: true).
• Allow Long Trades: Enable/disable long signals (default: true).
• Allow Short Trades: Enable/disable short signals (default: true).
Use Case:
This indicator is ideal for trend-following traders who want a clear, visual system for entering and exiting trades based on SMA crossovers, with predefined risk and reward levels. It suits both manual and automated trading strategies, providing flexibility to adjust parameters for different markets or timeframes.
Notes:
• The indicator is overlaid on the price chart for easy integration with other analysis tools.
• Users should test and adjust parameters (e.g., MA length, ATR multipliers) to suit their trading style and market conditions.
• The breakeven line is a visual guide; manual adjustment of stops is required as the indicator does not automatically modify trade positions.
This indicator provides a robust framework for disciplined trading with clear entry, exit, and risk management visuals.
