Nirvana True Duel전략 이름
열반의 진검승부 (영문: Nirvana True Duel)
컨셉과 철학
“열반의 진검승부”는 시장 소음은 무시하고, 확실할 때만 진입하는 전략입니다.
EMA 리본으로 추세 방향을 확인하고, 볼린저 밴드 수축/확장으로 변동성 돌파를 포착하며, OBV로 거래량 확인을 통해 가짜 돌파를 필터링합니다.
전략 로직
매수 조건 (롱)
20EMA > 50EMA (상승 추세)
밴드폭 수축 후 확장 시작
종가가 상단 밴드 돌파
OBV 상승 흐름 유지
매도 조건 (숏)
20EMA < 50EMA (하락 추세)
밴드폭 수축 후 확장 시작
종가가 하단 밴드 이탈
OBV 하락 흐름 유지
진입·청산
손절: ATR × 1.5 배수
익절: 손절폭의 1.5~2배에서 부분 청산
시간 청산: 설정한 최대 보유 봉수 초과 시 강제 청산
장점
✅ 추세·변동성·거래량 3중 필터 → 노이즈 최소화
✅ 백테스트·알람 지원 → 기계적 매매 가능
✅ 5분/15분 차트에 적합 → 단타/스윙 트레이딩 활용 가능
주의점
⚠ 횡보장에서는 신호가 적거나 실패 가능
⚠ 수수료·슬리피지 고려 필요
📜 Nirvana True Duel — Strategy Description (English)
Name:
Nirvana True Duel (a.k.a. Nirvana Cross)
Concept & Philosophy
The “Nirvana True Duel” strategy focuses on trading only meaningful breakouts and avoiding unnecessary noise.
Nirvana: A calm, patient state — waiting for the right opportunity without emotional trading.
True Duel: When the signal appears, enter decisively and let the market reveal the outcome.
In short: “Ignore market noise, trade only high-probability breakouts.”
🧩 Strategy Components
Trend Filter (EMA Ribbon): Stay aligned with the main market trend.
Volatility Squeeze (Bollinger Band): Detect volatility contraction & expansion to catch explosive moves early.
Volume Confirmation (OBV): Filter out false breakouts by confirming with volume flow.
⚔️ Entry & Exit Conditions
Long Setup:
20 EMA > 50 EMA (uptrend)
BB width breaks out from recent squeeze
Close > Upper Bollinger Band
OBV shows positive flow
Short Setup:
20 EMA < 50 EMA (downtrend)
BB width breaks out from recent squeeze
Close < Lower Bollinger Band
OBV shows negative flow
Risk Management:
Stop Loss: ATR × 1.5 below/above entry
Take Profit: 1.5–2× stop distance, partial take-profit allowed
Time Stop: Automatically closes after max bars held (e.g. 8h on 5m chart)
✅ Strengths
Triple Filtering: Trend + Volatility + Volume → fewer false signals
Mechanical & Backtestable: Ideal for objective trading & performance validation
Adaptable: Works well on Bitcoin, Nasdaq futures, and other high-volatility markets (5m/15m)
⚠️ Things to Note
Low signal frequency or higher failure rate in sideways/range markets
Commission & slippage should be factored in, especially on lower timeframes
ATR multiplier and R:R ratio should be optimized per asset
Trendfollowing
SPY-2h (E.Trader) - Long-Only StrategySummary
Strategy on SPY, 2h timeframe (2000-2025).
Initial capital: 100,000 USD, 100% reinvest.
Long-only strategy with realistic commissions and slippage (Interactive Brokers: $0.005/share, 3 ticks).
Key results (2000-2025)
• Total P&L: +1,792,104 USD (+1,739.88%)
• CAGR: 11.4% (vs Buy & Hold: 6.7%) → ~1.7x higher annualized return
• Profit factor: 3.23
• Winning trades: 67.43%
• Max drawdown: 21.56%
• Time in the market: ~59% (trading days basis)
• Buy & Hold return: +358.61% → Strategy outperforms by ~4.8x
Strategy logic
• Restricted to SPY on ARCA, in 2h timeframe
• Long entries only (no shorts)
• Exploits two major biases: 1) trends and 2) overreactions
• Excludes very high VIX periods
• Implements calculated stop-losses
• Integrates commission and slippage to reflect real trading conditions (based on Interactive Brokers usage)
Focus 2008-2009 (financial crisis)
• Total P&L: +35,301 USD (+35.30%)
• Profit factor: 3.367
• Winning trades: 80%
• Max drawdown: 15.05%
Even at the height of 2008, the strategy remained profitable, while Buy & Hold was still showing a -22% loss two years later.
Focus 2020 (COVID crash)
• Total P&L: +22,463 USD (+22.46%)
• Profit factor: 4.152
• Winning trades: 72.73%
• Max drawdown: 9.91%
During the COVID mini-crash, the strategy still ended the year +22.46%, almost double Buy & Hold (+12.52%), with limited drawdown.
Observations
• Strong outperformance vs Buy & Hold with less exposure
• Robust across crises (2008, COVID-2020)
• Limited drawdowns, faster recoveries
Model validation and parameter weighting
To check robustness and avoid overfitting, I use a simple weighted-parameters ratio (explained in more detail here: Reddit post ).
In this strategy:
• 4 primary parameters (weight 1)
• 5 secondary parameters (weight 0.5)
• Weighted param count = 4×1 + 5×0.5 = 6.5
• Total trades = 267
• Ratio = 267 ÷ 6.5 ≈ 41
Since this ratio is well above the 25 threshold I usually apply, it appears the model is not overfitted according to my experience — especially given its consistent gains even through crises such as 2008 and COVID-2020.
Disclaimer
This is an educational backtest. It does not constitute investment advice.
Past performance does not guarantee future results. Use at your own risk.
Further notes
In practice, systematic strategies like this are usually executed through automation to avoid human bias and ensure consistency. For those interested, I share more about my general approach and related tools here (personal site): emailtrader.app
TTP ADXTTP ADX Indicator
Description:
A clean and simplified ADX (Average Directional Index) indicator that focuses solely on trend strength measurement. This indicator removes the traditional DI+ and DI- lines, displaying only the core ADX line for a cleaner chart appearance.
Key Features:
Pure ADX Focus: Displays only the ADX line without directional indicators
Customizable Parameters: Adjustable length (default: 14) and threshold level (default: 20)
Clean Interface: Minimal visual clutter with a single trend strength line
Professional Styling: Navy blue ADX line with dashed threshold reference
How to Use:
ADX values above the threshold (default 20) indicate strong trending conditions
ADX values below the threshold suggest weak or sideways market conditions
Rising ADX suggests increasing trend strength (regardless of direction)
Falling ADX indicates weakening trend strength
Technical Details:
Uses Wilder's smoothing method for accurate ADX calculation
Built on Pine Script v5 for optimal performance
Non-overlay indicator displayed in separate pane
Default settings: 14-period length, 20 threshold level
Ideal For:
Traders who want to focus purely on trend strength
Clean chart setups without directional bias
Confirming trend conditions for entry/exit strategies
Market strength analysis across all timeframes
This streamlined version provides the essential trend strength information without the visual complexity of directional movement lines, making it perfect for traders who prefer minimalist indicators.
TF Sys-1Richard Dennis (Prince of the Pit) invested 1,600 dollar and reportedly made 350 Million dollars (within 10 years). The key is that, fortunes are caught by catching the big moves and catching them before they are plainly visible to the crowd.
This Trend Following Indicator combine both Trend Following Calculation and Stage Analysis to provide the clarity of trend direction and the complete plan how to trade by risking only 2%. It provides the position sizing, breakout location, stop loss and Pyramiding strategy (Conservative or Aggressive). I will provide a complete guide how to utilize the indicator and trend following Philosophy in my store in Whop.
Next time, when someone recommend any ticker you will see in which stage the ticker is and the breakout point. This indicator will not provide financial advice, it is a tool for decision making and your partner to achieve your goal (to be a successful trend following trader) where fortune lays.
Extended Majors Rotation System | AlphaNattExtended Majors Rotation System | AlphaNatt
A sophisticated cryptocurrency rotation system that dynamically allocates capital to the strongest trending major cryptocurrencies using multi-layered relative strength analysis and adaptive filtering techniques.
"In crypto markets, the strongest get stronger. This system identifies and rides the leaders while avoiding the laggards through mathematical precision."
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📊 SYSTEM OVERVIEW
The Extended Majors Rotation System (EMRS) is a quantitative momentum rotation strategy that:
Analyzes 10 major cryptocurrencies simultaneously
Calculates relative strength between all possible pairs (45 comparisons)
Applies fractal dimension analysis to identify trending behavior
Uses adaptive filtering to reduce noise while preserving signals
Dynamically allocates to the mathematically strongest asset
Implements multi-layer risk management through market regime filters
Core Philosophy:
Rather than trying to predict which cryptocurrency will perform best, the system identifies which one is already performing best relative to all others and maintains exposure until leadership changes.
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🎯 WHAT MAKES THIS SYSTEM UNEQUIVOCALLY UNIQUE
1. True Relative Strength Matrix
Unlike simple momentum strategies that look at individual asset performance, EMRS calculates the complete relative strength matrix between all assets. Each asset is compared against every other asset using fractal analysis, creating a comprehensive strength map of the entire crypto market.
2. Hurst Exponent Integration
The system employs the Hurst Exponent to distinguish between:
Trending behavior (H > 0.5) - where momentum is likely to persist
Mean-reverting behavior (H < 0.5) - where reversals are likely
Random walk (H ≈ 0.5) - where no edge exists
This ensures the system only takes positions when mathematical evidence of persistence exists.
3. Dual-Layer Filtering Architecture
Combines two advanced filtering techniques:
Laguerre Polynomial Filters: Provides low-lag smoothing with minimal distortion
Kalman-like Adaptive Smoothing: Adjusts filter parameters based on market volatility
This dual approach preserves important price features while eliminating noise.
4. Market Regime Awareness
The system monitors overall crypto market conditions through multiple lenses and only operates when:
The broad crypto market shows positive technical structure
Sufficient trending behavior exists across major assets
Risk conditions are favorable
5. Rank-Based Selection with Trend Confirmation
Rather than simply choosing the top-ranked asset, the system requires:
High relative strength ranking
Positive individual trend confirmation
Alignment with market regime
This multi-factor approach reduces false signals and whipsaws.
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🛡️ SYSTEM ROBUSTNESS & DEVELOPMENT METHODOLOGY
Pre-Coding Design Philosophy
This system was completely designed before any code was written . The mathematical framework, indicator selection, and parameter ranges were determined through:
Theoretical analysis of market microstructure
Study of persistence and mean reversion in crypto markets
Mathematical modeling of relative strength dynamics
Risk framework development based on regime theory
No Post-Optimization
Zero parameter fitting: All parameters remain at their originally designed values
No curve fitting: The system uses the same settings across all market conditions
No cherry-picking: Parameters were not adjusted after seeing results
This approach ensures the system captures genuine market dynamics rather than historical noise
Parameter Robustness Testing
Extensive testing was conducted to ensure stability:
Sensitivity Analysis: System maintains positive expectancy across wide parameter ranges
Walk-Forward Analysis: Consistent performance across different time periods
Regime Testing: Performs in both trending and choppy conditions
Out-of-Sample Validation
System was designed on a selection of 10 assets
System was tested on multiple baskets of 10 other random tokens, to simualte forwards testing
Performance remains consistent across baskets
No adjustments made based on out-of-sample results
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📈 PERFORMANCE METRICS DISPLAYED
The system provides real-time performance analytics:
Risk-Adjusted Returns:
Sharpe Ratio: Measures return per unit of total risk
Sortino Ratio: Measures return per unit of downside risk
Omega Ratio: Probability-weighted ratio of gains vs losses
Maximum Drawdown: Largest peak-to-trough decline
Benchmark Comparison:
Live comparison against Bitcoin buy-and-hold strategy
Both equity curves displayed with gradient effects
Performance metrics shown for both strategies
Visual representation of outperformance/underperformance
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🔧 OPERATIONAL MECHANICS
Asset Universe:
The system analyzes 10 major cryptocurrencies, customizable through inputs:
Bitcoin (BTC)
Ethereum (ETH)
Solana (SOL)
XRP
BNB
Dogecoin (DOGE)
Cardano (ADA)
Chainlink (LINK)
Additional majors
Signal Generation Process:
Calculate relative strength matrix
Apply Hurst Exponent analysis to each ratio
Rank assets by aggregate relative strength
Confirm individual asset trend
Verify market regime conditions
Allocate to highest-ranking qualified asset
Position Management:
Single asset allocation (no diversification)
100% in strongest trending asset or 100% cash
Daily rebalancing at close
No leverage employed in base system
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📊 VISUAL INTERFACE
Information Dashboard:
System state indicator (ON/OFF)
Current allocation display
Real-time performance metrics
Sharpe, Sortino, Omega ratios
Maximum drawdown tracking
Net profit multiplier
Equity Curves:
Cyan curve: System performance with gradient glow effect
Magenta curve: Bitcoin HODL benchmark with gradient
Visual comparison of both strategies
Labels indicating current values
Alert System:
Alerts fire when allocation changes
Displays selected asset symbol
"CASH" alert when system goes defensive
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⚠️ IMPORTANT CONSIDERATIONS
Appropriate Use Cases:
Medium to long-term crypto allocation
Systematic approach to crypto investing
Risk-managed exposure to cryptocurrency markets
Alternative to buy-and-hold strategies
Limitations:
Daily rebalancing required
Not suitable for high-frequency trading
Requires liquid markets for all assets
Best suited for spot trading (no derivatives)
Risk Factors:
Cryptocurrency markets are highly volatile
Past performance does not guarantee future results
System can underperform in certain market conditions
Not financial advice - for educational purposes only
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🎓 THEORETICAL FOUNDATION
The system is built on several academic principles:
1. Momentum Anomaly
Extensive research shows that assets exhibiting strong relative momentum tend to continue outperforming in the medium term (Jegadeesh & Titman, 1993).
2. Fractal Market Hypothesis
Markets exhibit fractal properties with periods of persistence and mean reversion (Peters, 1994). The Hurst Exponent quantifies these regimes.
3. Adaptive Market Hypothesis
Market efficiency varies over time, creating periods where momentum strategies excel (Lo, 2004).
4. Cross-Sectional Momentum
Relative strength strategies outperform time-series momentum in cryptocurrency markets due to the high correlation structure.
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💡 USAGE GUIDELINES
Capital Requirements:
Suitable for any account size
No minimum capital requirement
Scales linearly with account size
Implementation:
Can be traded manually with daily signals
Suitable for automation via alerts
Works with any broker supporting crypto
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📝 FINAL NOTES
The Extended Majors Rotation System represents a systematic, mathematically-driven approach to cryptocurrency allocation. By combining relative strength analysis with fractal market theory and adaptive filtering, it aims to capture the persistent trends that characterize crypto bull markets while avoiding the drawdowns of buy-and-hold strategies.
The system's robustness comes not from optimization, but from sound mathematical principles applied consistently. Every component was chosen for its theoretical merit before any backtesting occurred, ensuring the system captures genuine market dynamics rather than historical artifacts.
"In the race between cryptocurrencies, bet on the horse that's already winning - but only while the track conditions favour racing."
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Developed by AlphaNatt | Quantitative Rotation Systems
Version: 1.0
Strategy Type: Momentum Rotation
Classification: Systematic Trend Following
Not financial advice. Always DYOR.
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt
A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading.
"Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly."
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🤖 THE MACHINE LEARNING
Gaussian Mixture Models (GMM):
Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering :
Models data as coming from multiple Gaussian distributions
Each market regime is a different Gaussian component
Provides probability of belonging to each regime
More sophisticated than simple clustering
Expectation-Maximization Algorithm:
The indicator continuously learns and adapts using the E-M algorithm:
E-step: Calculate probability of current market belonging to each regime
M-step: Update regime parameters based on new data
Continuous learning without repainting
Adapts to changing market conditions
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🎯 THREE MARKET REGIMES
The GMM identifies three distinct market states:
Regime 1 - Low Volatility:
Quiet, ranging markets
Uses RSI-based momentum calculation
Reduces false signals in choppy conditions
Background: Pink tint
Regime 2 - Normal Market:
Standard trending conditions
Uses Rate of Change momentum
Balanced sensitivity
Background: Gray tint
Regime 3 - High Volatility:
Strong trends or volatility events
Uses Z-score based momentum
Captures extreme moves
Background: Cyan tint
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💡 KEY INNOVATIONS
1. Probabilistic Regime Detection:
Instead of binary regime assignment, provides probabilities:
30% Regime 1, 60% Regime 2, 10% Regime 3
Smooth transitions between regimes
No sudden indicator jumps
2. Weighted Momentum Calculation:
Combines three different momentum formulas
Weights based on regime probabilities
Automatically adapts to market conditions
3. Confidence Indicator:
Shows how certain the model is (white line)
High confidence = strong regime identification
Low confidence = transitional market state
Line transparency changes with confidence
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⚙️ PARAMETER OPTIMIZATION
Training Period (50-500):
50-100: Quick adaptation to recent conditions
100: Balanced (default)
200-500: Stable regime identification
Number of Components (2-5):
2: Simple bull/bear regimes
3: Low/Normal/High volatility (default)
4-5: More granular regime detection
Learning Rate (0.1-1.0):
0.1-0.3: Slow, stable learning
0.3: Balanced (default)
0.5-1.0: Fast adaptation
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📊 TRADING STRATEGIES
Visual Signals:
Cyan gradient: Bullish momentum
Magenta gradient: Bearish momentum
Background color: Current regime
Confidence line: Model certainty
1. Regime-Based Trading:
Regime 1 (pink): Expect mean reversion
Regime 2 (gray): Standard trend following
Regime 3 (cyan): Strong momentum trades
2. Confidence-Filtered Signals:
Only trade when confidence > 70%
High confidence = clearer market state
Avoid transitions (low confidence)
3. Adaptive Position Sizing:
Regime 1: Smaller positions (choppy)
Regime 2: Normal positions
Regime 3: Larger positions (trending)
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🚀 ADVANTAGES OVER OTHER ML INDICATORS
vs K-Means Clustering:
Soft clustering (probabilities) vs hard boundaries
Captures uncertainty and transitions
More mathematically robust
vs KNN (K-Nearest Neighbors):
Unsupervised learning (no historical labels needed)
Continuous adaptation
Lower computational complexity
vs Neural Networks:
Interpretable (know what each regime means)
No overfitting issues
Works with limited data
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📈 PERFORMANCE CHARACTERISTICS
Best Market Conditions:
Markets with clear regime shifts
Volatile to trending transitions
Multi-timeframe analysis
Cryptocurrency markets (high regime variation)
Key Strengths:
Automatically adapts to market changes
No manual parameter adjustment needed
Smooth transitions between regimes
Probabilistic confidence measure
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🔬 TECHNICAL BACKGROUND
Gaussian Mixture Models are used extensively in:
Speech recognition (Google Assistant)
Computer vision (facial recognition)
Astronomy (galaxy classification)
Genomics (gene expression analysis)
Finance (risk modeling at investment banks)
The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning.
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💡 PRO TIPS
Watch regime transitions: Best opportunities often occur when regimes change
Combine with volume: High volume + regime change = strong signal
Use confidence filter: Avoid low confidence periods
Multi-timeframe: Compare regimes across timeframes
Adjust position size: Scale based on identified regime
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⚠️ IMPORTANT NOTES
Machine learning adapts but doesn't predict the future
Best used with other confirmation indicators
Allow time for model to learn (100+ bars)
Not financial advice - educational purposes
Backtest thoroughly on your instruments
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🏆 CONCLUSION
The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides:
Automatic adaptation to market conditions
Clear regime identification with confidence levels
Smooth, professional signal generation
True unsupervised machine learning
This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in:
Google's speech recognition
Tesla's computer vision
NASA's data analysis
Wall Street risk models
"Let the machine learn the market regimes. Trade with statistical confidence."
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Developed by AlphaNatt | Machine Learning Trading Systems
Version: 1.0
Algorithm: Gaussian Mixture Model with E-M
Classification: Unsupervised Learning Oscillator
Not financial advice. Always DYOR.
High Probability Order Blocks [AlgoAlpha]🟠 OVERVIEW
This script detects and visualizes high-probability order blocks by combining a volatility-based z-score trigger with a statistical survival model inspired by Kaplan-Meier estimation. It builds and manages bullish and bearish order blocks dynamically on the chart, displays live survival probabilities per block, and plots optional rejection signals. What makes this tool unique is its use of historical mitigation behavior to estimate and plot how likely each zone is to persist, offering traders a probabilistic perspective on order block strength—something rarely seen in retail indicators.
🟠 CONCEPTS
Order blocks are regions of strong institutional interest, often marked by large imbalances between buying and selling. This script identifies those areas using z-score thresholds on directional distance (up or down candles), detecting statistically significant moves that signal potential smart money footprints. A bullish block is drawn when a strong up-move (zUp > 4) follows a down candle, and vice versa for bearish blocks. Over time, each block is evaluated: if price “mitigates” it (i.e., closes cleanly past the opposite side and confirmed with a 1 bar delay), it’s considered resolved and logged. These resolved blocks then inform a Kaplan-Meier-like survival curve, estimating the likelihood that future blocks of a given age will remain unbroken. The indicator then draws a probability curve for each side (bull/bear), updating it in real time.
🟠 FEATURES
Live label inside each block showing survival probability or “N.E.D.” if insufficient data.
Kaplan-Meier survival curves drawn directly on the chart to show estimated strength decay.
Rejection markers (▲ ▼) if price bounces cleanly off an active order block.
Alerts for zone creation and rejection signals, supporting rule-based trading workflows.
🟠 USAGE
Read the label inside each block for Age | Survival% (or N.E.D. if there aren’t enough samples yet); higher survival % suggests blocks of that age have historically lasted longer.
Use the right-side survival curves to gauge how probability decays with age for bull vs bear blocks, and align entries with the side showing stronger survival at current age.
Treat ▲ (bullish rejection) and ▼ (bearish rejection) as optional confluence when price tests a boundary and fails to break.
Turn on alerts for “Bullish Zone Created,” “Bearish Zone Created,” and rejection signals so you don’t need to watch constantly.
If your chart gets crowded, enable Prevent Overlap ; tune Max Box Age to your timeframe; and adjust KM Training Window / Minimum Samples to trade off responsiveness vs stability.
AMF PG Strategy AMF Command Center Strategy (Praetorian Guard)
The AMF PG Strategy (Praetorian Guard) is an advanced trading system built to adapt seamlessly across market conditions. Its unique structure balances precision entries with intelligent protection, giving traders confidence in both trending and volatile environments.
Key highlights include:
Adaptive Core (AMF Engine) – A dynamic framework that automatically adjusts and generates a powerful tracking line for clearer long and short opportunities.
Praetorian Guard – A built-in protective shield that activates in extreme conditions, helping stabilize performance when markets become turbulent.
Versatility – Effective across multiple timeframes, from scalping to swing trading, without constant parameter adjustments.
Clarity – Clean visual signals and color-coded tracking for instant decision-making.
This strategy was designed for traders who want more than just entries and exits — it offers a command center for disciplined, adaptive, and resilient trading.
Adaptive Trend Following Suite [Alpha Extract]A sophisticated multi-filter trend analysis system that combines advanced noise reduction, adaptive moving averages, and intelligent market structure detection to deliver institutional-grade trend following signals. Utilizing cutting-edge mathematical algorithms and dynamic channel adaptation, this indicator provides crystal-clear directional guidance with real-time confidence scoring and market mode classification for professional trading execution.
🔶 Advanced Noise Reduction
Filter Eliminates market noise using sophisticated Gaussian filtering with configurable sigma values and period optimization. The system applies mathematical weight distribution across price data to ensure clean signal generation while preserving critical trend information, automatically adjusting filter strength based on volatility conditions.
advancedNoiseFilter(sourceData, filterLength, sigmaParam) =>
weightSum = 0.0
valueSum = 0.0
centerPoint = (filterLength - 1) / 2
for index = 0 to filterLength - 1
gaussianWeight = math.exp(-0.5 * math.pow((index - centerPoint) / sigmaParam, 2))
weightSum += gaussianWeight
valueSum += sourceData * gaussianWeight
valueSum / weightSum
🔶 Adaptive Moving Average Core Engine
Features revolutionary volatility-responsive averaging that automatically adjusts smoothing parameters based on real-time market conditions. The engine calculates adaptive power factors using logarithmic scaling and bandwidth optimization, ensuring optimal responsiveness during trending markets while maintaining stability during consolidation phases.
// Calculate adaptive parameters
adaptiveLength = (periodLength - 1) / 2
logFactor = math.max(math.log(math.sqrt(adaptiveLength)) / math.log(2) + 2, 0)
powerFactor = math.max(logFactor - 2, 0.5)
relativeVol = avgVolatility != 0 ? volatilityMeasure / avgVolatility : 0
adaptivePower = math.pow(relativeVol, powerFactor)
bandwidthFactor = math.sqrt(adaptiveLength) * logFactor
🔶 Intelligent Market Structure Analysis
Employs fractal dimension calculations to classify market conditions as trending or ranging with mathematical precision. The system analyzes price path complexity using normalized data arrays and geometric path length calculations, providing quantitative market mode identification with configurable threshold sensitivity.
🔶 Multi-Component Momentum Analysis
Integrates RSI and CCI oscillators with advanced Z-score normalization for statistical significance testing. Each momentum component receives independent analysis with customizable periods and significance levels, creating a robust consensus system that filters false signals while maintaining sensitivity to genuine momentum shifts.
// Z-score momentum analysis
rsiAverage = ta.sma(rsiComponent, zAnalysisPeriod)
rsiDeviation = ta.stdev(rsiComponent, zAnalysisPeriod)
rsiZScore = (rsiComponent - rsiAverage) / rsiDeviation
if math.abs(rsiZScore) > zSignificanceLevel
rsiMomentumSignal := rsiComponent > 50 ? 1 : rsiComponent < 50 ? -1 : rsiMomentumSignal
❓How It Works
🔶 Dynamic Channel Configuration
Calculates adaptive channel boundaries using three distinct methodologies: ATR-based volatility, Standard Deviation, and advanced Gaussian Deviation analysis. The system automatically adjusts channel multipliers based on market structure classification, applying tighter channels during trending conditions and wider boundaries during ranging markets for optimal signal accuracy.
dynamicChannelEngine(baselineData, channelLength, methodType) =>
switch methodType
"ATR" => ta.atr(channelLength)
"Standard Deviation" => ta.stdev(baselineData, channelLength)
"Gaussian Deviation" =>
weightArray = array.new_float()
totalWeight = 0.0
for i = 0 to channelLength - 1
gaussWeight = math.exp(-math.pow((i / channelLength) / 2, 2))
weightedVariance += math.pow(deviation, 2) * array.get(weightArray, i)
math.sqrt(weightedVariance / totalWeight)
🔶 Signal Processing Pipeline
Executes a sophisticated 10-step signal generation process including noise filtering, trend reference calculation, structure analysis, momentum component processing, channel boundary determination, trend direction assessment, consensus calculation, confidence scoring, and final signal generation with quality control validation.
🔶 Confidence Transformation System
Applies sigmoid transformation functions to raw confidence scores, providing 0-1 normalized confidence ratings with configurable threshold controls. The system uses steepness parameters and center point adjustments to fine-tune signal sensitivity while maintaining statistical robustness across different market conditions.
🔶 Enhanced Visual Presentation
Features dynamic color-coded trend lines with adaptive channel fills, enhanced candlestick visualization, and intelligent price-trend relationship mapping. The system provides real-time visual feedback through gradient fills and transparency adjustments that immediately communicate trend strength and direction changes.
🔶 Real-Time Information Dashboard
Displays critical trading metrics including market mode classification (Trending/Ranging), structure complexity values, confidence scores, and current signal status. The dashboard updates in real-time with color-coded indicators and numerical precision for instant market condition assessment.
🔶 Intelligent Alert System
Generates three distinct alert types: Bullish Signal alerts for uptrend confirmations, Bearish Signal alerts for downtrend confirmations, and Mode Change alerts for market structure transitions. Each alert includes detailed messaging and timestamp information for comprehensive trade management integration.
🔶 Performance Optimization
Utilizes efficient array management and conditional processing to maintain smooth operation across all timeframes. The system employs strategic variable caching, optimized loop structures, and intelligent update mechanisms to ensure consistent performance even during high-volatility market conditions.
This indicator delivers institutional-grade trend analysis through sophisticated mathematical modelling and multi-stage signal processing. By combining advanced noise reduction, adaptive averaging, intelligent structure analysis, and robust momentum confirmation with dynamic channel adaptation, it provides traders with unparalleled trend following precision. The comprehensive confidence scoring system and real-time market mode classification make it an essential tool for professional traders seeking consistent, high-probability trend following opportunities with mathematical certainty and visual clarity.
LogPressure Envelope [BOSWaves]LogPressure Envelope – Adaptive Volatility & Trend Visualizer
Overview
LogPressure Envelope is a specialized trading tool designed to normalize market behavior using logarithmic price scaling while providing an adaptive framework for volatility and trend detection. The indicator calculates a log-based moving average midline, surrounds it with asymmetric volatility envelopes, and replaces the conventional cloud with progressive fan lines to present price action in a more interpretable form.
By integrating rate-of-change midline coloring, fading trend strength, and structured buy/sell markers, LogPressure Envelope simplifies the reading of complex market dynamics. Its design makes it suitable for multiple trading approaches, including scalping, intraday, and swing trading, where volatility behavior and trend shifts must be understood quickly and objectively.
Unlike static envelope indicators, LogPressure Envelope adapts continuously to price scale and volatility conditions. It evaluates log-transformed prices, applies configurable moving average methods (EMA, SMA, WMA), and derives asymmetric standard-deviation bands for both upside and downside moves. These envelopes are projected as fan lines with adjustable opacity, producing a layered volatility map that evolves with the market.
This system ensures each visual element—midline shading, candle coloring, fan structure, and signal markers—reflects real-time market conditions, allowing traders to interpret volatility expansion, contraction, and directional bias with clarity.
How It Works
The foundation of LogPressure Envelope is the logarithmic transformation of price. By operating in log space, the indicator removes distortions caused by large nominal price differences across assets, enabling consistent analysis of both low-priced and high-priced instruments.
A moving average of log prices is calculated (EMA, SMA, or WMA depending on user input) and then re-converted to normal price scale, forming the log midline. Standard deviation of log prices is then measured over a separate period, with independent multipliers for upside and downside deviations. This asymmetry captures the fact that markets often expand differently in bullish versus bearish phases.
Instead of plotting a filled cloud, the envelope is expressed as ten equidistant fan lines stretching from the lower to upper boundary. Each line is shaded progressively to visualize volatility clustering and directional strength without overloading the chart.
Trend determination is smoothed using a fade mechanism: shifts in bias do not flip instantly but gradually move toward the new state, producing fewer false transitions. Buy and sell markers are generated when trend strength crosses confirmation thresholds, ensuring signals are event-driven and contextually meaningful.
Signals and Visuals
LogPressure Envelope provides multiple layers of structured signals:
Midline Bias – Central moving average colored by rate-of-change, reflecting directional acceleration or deceleration.
Volatility Fan – Ten progressive lines forming a gradient between lower and upper bands, visually encoding volatility spread.
Buy Signals – Labels below bars when upward trend strength is confirmed.
Sell Signals – Labels above bars when downward trend strength is confirmed.
Candle Coloring – Optional shading of candles based on trend alignment with the log midline, highlighting bullish, bearish, or neutral conditions.
These signals remain clear even during high-volatility phases, with visual hierarchy maintained through progressive opacity control.
Interpretation
Trend Analysis : Midline direction and candle coloring provide continuous feedback on prevailing bias. Upward-sloping midlines with blue shading indicate bullish phases, while downward slopes with orange shading confirm bearish conditions.
Volatility and Risk Assessment : Expansion of fan lines indicates rising volatility and potential breakout conditions; contraction indicates consolidation and possible mean reversion.
Signal Confirmation : Buy and sell markers validate transitions when trend strength thresholds are crossed, aligning with volatility envelope dynamics.
Market Context : Asymmetric envelopes allow traders to see where bearish acceleration differs from bullish expansion, improving interpretation of liquidity conditions and institutional pressure.
Strategy Integration
LogPressure Envelope can be applied across trading styles:
Trend Following : Enter trades in the direction of midline bias, confirmed by buy or sell markers.
Pullback Entries : Use midline retests during trending conditions as lower-risk continuation points.
Volatility Breakouts : Identify sharp expansions in fan line spacing as early signals of directional moves.
Reversal Strategies : Fade extreme envelope touches when momentum shows exhaustion and fan contraction begins.
Multi-Timeframe Confirmation : Align signals from higher and lower timeframes to reduce noise and validate trade setups.
Stop-loss levels can be set near the opposite envelope boundary, while targets may be managed through progressive volatility zones or midline convergence.
Advanced Techniques
For greater precision, LogPressure Envelope can be combined with other analytical tools:
Pair with volume or liquidity measures to validate breakout or reversal conditions.
Use momentum indicators to confirm ROC-based midline bias.
Track sequences of fan line expansions and contractions to anticipate regime shifts in volatility.
Apply across multiple timeframes to monitor how volatility clusters align at different market scales.
Adjusting parameters such as envelope multipliers, moving average type, and fade bars allows the indicator to adapt to diverse asset classes and volatility environments.
Inputs and Customization
Midline Type : Select EMA, SMA, or WMA.
Line Opacity : Control visibility of fan lines.
Enable Candle Coloring : Toggle trend-based bar shading.
MA Length / StdDev Length : Define periods for midline and volatility calculation.
Multipliers : Set asymmetric scaling for upside and downside envelopes.
Fade Bars : Control smoothness of trend strength transitions.
Fan Lines : Adjust number of envelope subdivisions for visualization granularity.
Why Use LogPressure Envelope
LogPressure Envelope translates complex volatility and trend interactions into a structured and adaptive framework. By combining logarithmic normalization, asymmetric standard deviation envelopes, and smoothed trend confirmation, it allows traders to:
Normalize price analysis across assets of different scales.
Visualize volatility expansion and contraction in real time.
Identify and confirm directional shifts with objective signal markers.
Apply a disciplined system for trend, breakout, and reversal strategies.
This indicator is designed for traders who want a systematic, visually clear approach to volatility-based market analysis without relying on static bands or arbitrary scaling.
Ichimoku HorizonIchimoku Horizon – Multi-Timeframe Analysis
A multi-timeframe Ichimoku faithful to Hosoda, with authentic real-time calculations.
Ichimoku Horizon is an indicator based on the original method developed by Goichi Hosoda in the 1930s. It strictly respects the authentic formulas and prioritizes mathematical fidelity.
Key Features
Intelligent Multi-Timeframe
Native chart: Ichimoku from your trading timeframe
3 higher timeframes: Daily (1D), Weekly (1W), Monthly (1M) by default
Automatic projection: only higher timeframes relative to the chart are displayed
Precise offsets: displacement adapted to each timeframe
Guaranteed Authenticity
Hosoda’s original formulas fully respected
lookahead_off exclusively: lines calculated in real time with the current candle
Traditional displacement: 26 periods for cloud projection and Chikou shift
Why lookahead_off?
lookahead_off is the calculation mode that respects Hosoda’s logic:
Tenkan, Kijun, SSA and SSB all include the current candle and move in real time.
Chikou is the only exception: shifted 26 periods but calculated only with confirmed closes.
This way, what you see always matches the actual market as it is forming.
What is the no repaint approach?
A no repaint indicator displays values exactly as they exist in the present moment:
Lines update in real time during the formation of a candle.
Once the candle closes, they remain permanently fixed.
This ensures that the plots reflect the true construction of the market.
Main Parameters
Tenkan: 9 periods (short term)
Kijun: 26 periods (medium term)
SSB: 52 periods (long term)
Displacement: 26 periods (+26 for the cloud, −26 for the Chikou)
Timeframe Selection
TF1: Daily (structure aligned with trading activity)
TF2: Weekly (intermediate trend)
TF3: Monthly (macro vision)
Example Configurations
Scalping: Chart 1m → TF1: 5m, TF2: 15m, TF3: 1H
Intraday: Chart 5m → TF1: 15m, TF2: 1H, TF3: 4H
The indicator automatically hides inconsistent timeframes (lower than the chart).
Natural Line Display
Some lines will sometimes appear flat or straight: this is the normal behavior of Ichimoku, directly reflecting the highs and lows of their calculation windows.
Conclusion
Ichimoku Horizon is designed to remain true to Hosoda’s vision while offering the clarity of a modern multi-timeframe tool.
It delivers authentic, real-time calculations with no compromise.
Pasrsifal.RegressionTrendStateSummary
The Parsifal.Regression.Trend.State Indicator analyzes the leading coefficients of linear and quadratic regressions of price (against time). It also considers their first- and second-order changes. These features are aggregated into a Trend-State background, shown as a gradient color. In addition, the indicator generates fast and slow signals that can be used as potential entry- or exit triggers.
This tool is designed for advanced trend-following strategies, leveraging information from multiple trendline features.
Background
Trendlines provide insight into the state of a trend or the “trendiness” of a price process. While moving averages or pivot-based lines can serve as envelopes and breakout levels, they are often too lagging for swing traders, who need tools that adapt more closely to price swings, ideally using trendlines, around which the price process swings continuously.
Regression lines address this by cutting directly through the data, making them a natural anchor for observing how price winds around a central trendline within a chosen lookback period.
Regression Trendlines
• Linear Regression:
o Minimizes distance to all closing values over the lookback period.
o The slope represents the short-term linear trend.
o The change of slope indicates trend acceleration or deceleration.
o Linear regression lags during phases of rapid market shifts.
• Quadratic Regression:
o Fits a second-degree polynomial to minimize deviation from closing prices.
o The convexity term (leading coefficient) reflects curvature:
Positive convexity → accelerating uptrend or fading downtrend.
Negative convexity → accelerating downtrend or fading uptrend.
o The change of convexity detects early shifts in momentum and often reacts faster than slope features.
Features Extracted
The indicator evaluates six features:
• Linear features: slope, first derivative of slope, second derivative of slope.
• Quadratic features: convexity term, first derivative of the convexity term, second derivative of the convexity term.
• Linear features: capture broad, background trend behavior.
• Quadratic features: detect deviations, accelerations, and smaller-scale dynamics.
Quadratic terms generally react first to market changes, while linear terms provide stability and context.
Dynamics of Market Moves as seen by linear and quadratic regressions
• At the start of a rapid move:
The change of convexity reacts first, capturing the shift in dynamics before other features. The convexity term then follows, while linear slope features lag further behind. Because convexity measures deviation from linearity, it reflects accelerating momentum more effectively than slope.
• At the end of a rapid move:
Again, the change of convexity responds first to fading momentum, signaling the transition from above-linear to below-linear dynamics. Even while a strong trend persists, the change of convexity may flip sign early, offering a warning of weakening strength. The convexity term itself adjusts more slowly but may still turn before the price process does. Linear features lag the most, typically only flipping after price has already reversed, thereby smoothing out the rapid, more sensitive reactions of quadratic terms.
________________________________________
Parsifal Regression.Trend.State Method
1. Feature Mapping:
Each feature is mapped to a range between -1 and 1, preserving zero-crossings (critical for sign interpretation).
2. Aggregation:
A heuristic linear combination*) produces a background information value, visualized as a gradient color scale:
o Deep green → strong positive trend.
o Deep red → strong negative trend.
o Yellow → neutral or transitional states.
3. Signals:
o Fast signal (oscillator): ranges from -1 to 1, reflecting short-term trend state.
o Slow signal (smoothed): moving average of the fast signal.
o Their interactions (crossovers, zero-crossings) provide actionable trading triggers.
How to Use
The Trend-State background gradient provides intuitive visual feedback on the aggregated regression features (slope, convexity, and their changes). Because these features reflect not only current trend strength but also their acceleration or deceleration, the color transitions help anticipate evolving market states:
• Solid Green: All features near their highs. Indicates a strong, accelerating uptrend. May also reflect explosive or hyperbolic upside moves (including gaps).
• Fading Solid Green: A recently strong uptrend is losing momentum. Price may shift into a slower uptrend, consolidation, or even a reversal.
• Fading Green → Yellow: Often appears as a dirty yellow or a rapidly mixing pattern of green and red. Signals that the uptrend is weakening toward neutrality or beginning to turn negative.
• Yellow → Deepening Red: Two possible scenarios:
o Coming from a strong uptrend → suggests a sharp fade, though the trend may still technically be up.
o Coming from a weaker uptrend or sideways market → suggests the start of an accelerating downtrend.
• Solid Red: All features near their lows. Indicates a strong, accelerating downtrend. May also reflect crash-type conditions or downside gaps.
• Fading Solid Red: A recently strong downtrend is losing strength. Market may move into a slower decline, consolidation, or early reversal upward.
• Fading Red → Yellow : The downtrend is weakening toward neutral, with potential for a bullish shift.
• Yellow → Increasing Green: Two possible scenarios:
o Coming from a strong downtrend, it reflects a sharp fade of bearish momentum, though the market may still technically be trending down.
o Coming from a weaker downtrend or sideways movement, it suggests the start of an accelerating uptrend.
Note: Market evolution does not always follow this neat “color cycle.” It may jump between states, skip stages, or reverse abruptly depending on market conditions. This makes the background coloring particularly valuable as a contextual map of current and evolving price dynamics.
Signal Crossovers:
Although the fast signal is very similar (but not identical) to the background coloring, it provides a numerical representation indicating a bullish interpretation for rising values and bearish for falling.
o High-confidence entries:
Fast signal rising from < -0.7 and crossing above the slow signal → potential long entry.
Fast signal falling from > +0.7 and crossing below the slow signal → potential short entry.
o Low-confidence entries:
Crossovers near zero may still provide a valid trigger but may be noisy and should be confirmed with other signals.
o Zero-crossings:
Indicate broader state changes, useful for conservative positioning or option strategies. For confirmation of a Fast signal 0-crossing, wait for the Slow signal to cross as well.
________________________________________
*) Note on Aggregation
While the indicator currently uses a heuristic linear combination of features, alternatives such as Principal Component Analysis (PCA) could provide a more formal aggregation. However, while in the absence of matrix algebra, the required eigenvalue decomposition can be approximated, its computational expense does not justify the marginal higher insight in this case. The current heuristic approach offers a practical balance of clarity, speed, and accuracy.
Reverse RSI Signals [AlgoAlpha]🟠 OVERVIEW
This script introduces the Reverse RSI Signals system, an original approach that inverts traditional RSI values back into price levels and then overlays them directly on the chart as dynamic bands. Instead of showing RSI in a subwindow, the script calculates the exact price thresholds that correspond to common RSI levels (30/70/50) and displays them as upper, lower, and midline bands. These are further enhanced with an adaptive Supertrend filter and divergence detection, allowing traders to see overbought/oversold zones translated into actionable price ranges and trend signals. The script combines concepts of RSI inversion, volatility envelopes, and divergence tracking to provide a context-driven tool for spotting reversals and regime shifts.
🟠 CONCEPTS
The script relies on inverting RSI math: by solving for the price that would yield a given RSI level, it generates real chart levels tied to oscillator conditions. These RSI-derived price bands act like support/resistance, adapting each bar as RSI changes. On top of this, a Supertrend built around the RSI midline introduces directional bias, switching regimes when the midline is breached. Regular bullish and bearish divergences are detected by comparing RSI pivots against price pivots, highlighting early reversal conditions. This layered approach means the indicator is not just RSI on price but a hybrid of oscillator translation, volatility-tracking midline envelopes, and divergence analysis.
🟠 FEATURES
Inverted RSI bands: upper (70), lower (30), and midline (50), smoothed with EMA for noise reduction.
Supertrend overlay on the RSI midline to confirm regime direction (bullish or bearish).
Gradient-filled zones between outer and inner RSI bands to visualize proximity and exhaustion.
Non-repainting bullish and bearish divergence markers plotted directly on chart highs/lows.
🟠 USAGE
Apply the indicator to any chart and use the plotted RSI price bands as adaptive support/resistance. The midline defines equilibrium, while upper and lower bands represent classic RSI thresholds translated into real price action. In bullish regimes (green candles), long trades are stronger when price approaches or bounces from the lower band; in bearish regimes (red candles), shorts are favored near the upper band. Divergence markers (▲ for bullish, ▼ for bearish) flag potential reversal points early. Traders can combine the band proximity, divergence alerts, and Supertrend context to time entries, exits, or to refine ongoing trend trades. Adjust smoothing and Supertrend ATR settings to match the volatility of the instrument being analyzed.
Vesperis v8.1 by JaeheeVesperis v8.1 by Jaehee
Overview
This script is a short-side trading strategy designed for trend-following conditions where bearish momentum aligns across multiple independent filters. It does not aim to predict tops or bottoms. Instead, it waits for confirmation that the market has entered a strong downtrend and then manages trades with structured risk controls.
Core Components
The strategy combines several classical concepts but applies them in a multi-filter consensus framework to reduce false signals:
• SSL Hybrid Filter → Defines directional bias using an EMA-based signal line
• MOBO Bands (modified Bollinger framework) → Measures volatility compression and breakout expansion
• EMA 20/50/100 Alignment → Confirms bearish structure when shorter averages remain under longer ones
• ADX Strength Gate → Trades are permitted only when trend strength (Wilder’s ADX) is above a chosen threshold
• Heikin Ashi Smoothing → Provides visual clarity and reduces noise in trend recognition
• Cooldown Rule → After a losing trade, the system waits a configurable number of bars before re-entry to enforce discipline
Risk Management
• Take-Profit (TP) and Stop-Loss (SL) are dynamically attached to each entry
• TP and SL are ratio-based relative to the entry price
• Cooldown logic prevents immediate re-entries after losses
• Position sizing is based on percentage of equity, with commissions factored in for realistic simulation
Visualization
• EMA 20/50/100 ribbon with soft gradient colors
• MOBO band plotted with contrasting tones for clarity
• SSL baseline overlay
• ADX values displayed every 10 bars for contextual strength
• Background shading highlights bullish vs bearish trend regimes
• Heikin Ashi candle coloring for directional bias emphasis
Why This Combination?
Each component addresses a different market dimension:
• Direction (SSL, EMA alignment)
• Volatility & Breakout Context (MOBO Bands)
• Strength (ADX filter)
• Trade Discipline (Cooldown rule)
When layered together, they reduce the chance of acting on a single misleading condition. For example, a close under MOBO support is acted upon only if ADX confirms strong momentum and EMA structure validates a broader bearish regime. This multi-gate approach balances selectivity with responsiveness, aiming for consistent entries during trending phases rather than over-trading in sideways conditions.
Important Notes
• This script is a strategy, not just an indicator. It performs backtestable entries and exits within TradingView’s framework
• Default properties include realistic assumptions: commission, slippage approximation, and percentage-based position sizing
• Results will vary by market and timeframe; this tool does not guarantee outcomes and should be combined with independent risk management
• Invite-only access ensures controlled distribution
Compliance with TradingView House Rules
• No external links, promotions, or contact information
• Clear explanation of what, how, and why without revealing full code logic
• Highlights originality: consensus-based filter design with combined ADX, SSL, MOBO, EMA gating
• Provides conceptual and educational value to traders while remaining distinct from classic single-element scripts
FibroTrend Matrix Premium [By TraderMan]📊 FibroTrend Matrix Premium
FibroTrend Matrix Premium is a powerful multi-timeframe trend and Fibonacci analysis tool. It combines trend direction, trend strength, and key Fibonacci levels into a single, clean interface with a dynamic table. Perfect for traders who want to see the market structure at a glance.
🧠 How It Works
Trend Detection 📈📉
Uses EMA-based dynamic bands to determine current trend direction.
Computes trend strength using slope of the trend line vs. price deviation.
Works on multiple timeframes (5m, 15m, 30m, 1h, 4h, 1D) for overall market context.
Fibonacci Levels & Zones 🔢
Automatically draws key Fibonacci retracement levels (0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0).
Adds zones around levels for potential support/resistance areas.
Labels are small and clear, lines slightly thicker for better visibility.
Trend Table Summary 📊
Shows current trend direction, strength, and general trend across multiple timeframes.
Fibonacci levels are included in the table with color-coded cells (green = bullish, red = bearish).
⚡ How to Use / Trading Logic
Identify Trend Direction
Uptrend (Green/“Up”) → look for buying opportunities.
Downtrend (Red/“Down”) → look for selling/shorting opportunities.
Neutral → wait or stay out.
Check Trend Strength
Very Strong / Strong (Green) → trend likely to continue.
Weak / Very Weak (Red) → trend may reverse or be choppy.
Use Fibonacci Levels for Entry & Exit
Enter near support zones in an uptrend.
Enter near resistance zones in a downtrend.
Use zone width & tolerance to set stop-loss or take-profit.
Multi-Timeframe Confirmation ✅
Ensure majority of timeframes confirm trend direction for stronger signal.
Example: if 5 out of 6 timeframes show Uptrend, trend is strong.
💡 Tips
Combine with volume, momentum, or RSI for extra confirmation.
Avoid trading solely on Fibonacci levels; use trend + strength table as main guide.
Works well for swing trading, intraday, and crypto markets.
🎯 Entry Example
Price is in an uptrend (green bars, line up).
Fibonacci retracement 0.382 aligns with support zone.
Trend strength = Strong or Very Strong.
Enter Long near zone, set stop-loss slightly below zone, take-profit near next Fibonacci level.
TrendMaster Pro [By TraderMan]📈 TrendMaster Pro Indicator 🚀
TrendMaster Pro is a powerful, technical analysis-based trading tool used on TradingView.
It’s designed to identify market trends, detect support/resistance levels, spot trend breakouts, and generate automatic buy-sell signals.
⚙️ Indicator Logic and Functionality
🔎 Pivot Detection: Captures market turning points (pivot highs & lows).
📉📈 Trend Lines: Draws support (green) and resistance (red) lines between recent pivot points.
💥 Breakout Detection: Generates signals when price breaks support or resistance levels.
⏳ Multi-Timeframe Analysis: Analyzes trend direction and breakouts on 5m, 15m, 1h, 4h, and daily charts.
📊 EMA & Momentum: Confirms trend direction using 5 and 13-period EMAs and momentum indicators.
🎯 TP/SL Levels: Automatically calculates Take Profit (TP) and Stop Loss (SL) levels.
⭐ Success Rate: Measures signal accuracy as a percentage; only signals above 70% are shown.
👁️🗨️ Visual Elements: Easy-to-use interface with trend lines, TP/SL boxes, labels, and summary tables.
📲 Alerts: Sends real-time buy/sell notifications via Telegram or webhook.
🛠️ How It Works
🔺 Pivot and Trend Lines
Pivots (highs and lows) are detected based on a user-defined lookback period.
Support (green) and resistance (red) lines are drawn between these points and extended into the future.
⚡ Breakout Detection
If price breaks above resistance → Buy (Long) signal!
If price breaks below support → Sell (Short) signal!
A confirmation bar count (default 1 bar) helps reduce false signals.
📅 Multi-Timeframe Analysis
Checks trend and breakout status across 5m, 15m, 1h, 4h, and daily charts.
EMA5 > EMA13 with positive momentum indicates a bullish trend; the opposite indicates a bearish trend.
🎯 TP and SL Calculation
Entry price is based on the support/resistance level.
TP (2%) and SL (1.3%) percentages are calculated automatically, with vertical offsets applied.
🌟 Success Rate
Rates signal strength based on trend and breakout alignment across timeframes.
Only signals above 70% trigger alerts.
🎮 How to Use
Add the Indicator: Paste the code into Pine Script editor on TradingView and add to your chart.
Configure Settings: Adjust pivot lookback, TP/SL percentages, confirmation bars, and other parameters to fit your strategy.
Follow Signals:
Buy signals show “BUY” labels and TP/SL boxes after resistance breakouts.
Sell signals show “SELL” labels after support breakdowns.
Enter Positions: Take positions on confirmed signals and monitor TP/SL levels.
Receive Alerts: Signals with a success rate above 70% will send automatic Telegram notifications.
💡 Tips for Use
⏱️ Timeframe Choice: Use short timeframes (5m, 15m) for scalping, longer (1h, 4h, daily) for swing trading.
📈 Success Rate: Signals over 80% are more reliable; be cautious with lower percentages.
⚙️ Settings: Optimize TP/SL and pivot period according to asset volatility.
🛡️ Risk Management: Always use SL and manage position size carefully.
🎉 Advantages
📊 Multi-timeframe support for stronger analysis
👁️🗨️ User-friendly visuals and summary tables
🤖 Automated alerts via Telegram/webhook
🔧 Flexible, customizable parameters
⚠️ Warnings
⚡ High volatility may increase false signals—consider increasing confirmation bars.
🔄 Signals can be less reliable in non-trending (range) markets.
🧪 Always test strategies on demo accounts before going live.
Conquer the waves of the market with TrendMaster Pro! 🌊💪
Backtest - Strategy Builder [AlgoAlpha]🟠 OVERVIEW
This script by AlgoAlpha is a modular Strategy Builder designed to let traders test custom trade entry and exit logic on TradingView without writing their own Pine code. It acts as a framework where users can connect multiple external signals, chain them in sequences, and run backtests with built-in leverage, margin, and risk controls. Its main strength is flexibility—you can define up to five sequential steps for entry and exit conditions on both long and short sides, with logic connectors (AND/OR) controlling how conditions combine. This lets you test complex multi-step confirmation workflows in a controlled, visual backtesting environment.
🟠 CONCEPTS
The system works by linking external signals —these can be values from other indicators, and/or custom sources—to conditional checks like “greater than,” “less than,” or “crossover.” You can stack these checks into steps , where all conditions in a step must pass before the sequence moves to the next. This creates a chain of logic that must be completed before a trade triggers. On execution, the strategy sizes positions according to your chosen leverage mode ( Cross or Isolated ) and allocation method ( Percent of equity or absolute USD value]). Liquidation prices are simulated for both modes, allowing realistic margin behaviour in testing. The script also tracks performance metrics like Sharpe, Sortino, profit factor, drawdown, and win rate in real time.
🟠 FEATURES
Up to 5 sequential steps for both long and short entries, each with multiple conditions linked by AND/OR logic.
Two leverage modes ( Cross and Isolated ) with independent long/short leverage multipliers.
Separate multi-step exit triggers for longs and shorts, with optional TP/SL levels or opposite-side triggers for flipping positions.
Position sizing by equity percent or fixed USD amount, applied before leverage.
Realistic liquidation price simulation for margin testing.
Built-in trade gating and validation—prevents trades if configuration rules aren’t met (e.g., no exit defined for an active side).
Full performance dashboard table showing live strategy status, warnings, and metrics.
Configurable bar coloring based on position side and TP/SL level drawing on chart.
Integration with TradingView's strategy backtester, allowing users to view more detailed metrics and test the strategy over custom time horizons.
🟠 USAGE
Add the strategy to your chart. In the settings, under Master Settings , enable longs/shorts, select leverage mode, set leverage multipliers, and define position sizing. Then, configure your Long Trigger and Short Trigger groups: turn on conditions, pick which external signal they reference, choose the comparison type, and assign them to a sequence step. For exits, use the corresponding Exit Long Trigger and Exit Short Trigger groups, with the option to link exits to opposite-side entries for auto-flips. You can also enable TP and/or SL exits with custom sources for the TP/SL levels. Once set, the strategy will simulate trades, show performance stats in the on-chart table, and highlight any configuration issues before execution. This makes it suitable for testing both simple single-signal systems and complex, multi-filtered strategies under realistic leverage and margin constraints.
🟠 EXAMPLE
The backtester on its own does not contain any indicator calculation; it requires input from external indicators to function. In this example, we'll be using AlgoAlpha's Smart Signals Assistant indicator to demonstrate how to build a strategy using this script.
We first define the conditions beforehand:
Entry :
Longs – SSA Bullish signal (strong OR weak)
Shorts – SSA Bearish signal (strong OR weak)
Exit
Longs/Shorts: (TP/SL hit OR opposing signal fires)
Other Parameters (⚠️Example only, tune this based on proper risk management and settings)
Long Leverage: default (3x)
Short Leverage: default (3x)
Position Size: default (10% of equity)
Steps
Load up the required indicators (in this example, the Smart Signals Assistant).
Ensure the required plots are being output by the indicator properly (signals and TP/SL levels are being plotted).
Open the Strategy Builder settings and scroll down to "CONDITION SETUP"; input the signals from the external indicator.
Configure the exit conditions, add in the TP/SL levels from the external indicator, and add an additional exit condition → {{Opposite Direction}} Entry Trigger.
After configuring the entry and exit conditions, the strategy should now be running. You can view information on the strategy in TradingView's backtesting report and also in the Strategy Builder's information table (default top right corner).
It is important to note that the strategy provided above is just an example, and the complexity of possible strategies stretches beyond what was shown in this short demonstration. Always incorporate proper risk management and ensure thorough testing before trading with live capital.
200 EMA w/ Ticker Memory200 EMA w/ Ticker Memory — Multi-Symbol & Multi-Timeframe EMA Tracker with Alerts
Overview
The 200 EMA w/ Ticker Memory indicator allows you to monitor the 200-period Exponential Moving Average (EMA) across multiple symbols and timeframes. Designed for traders managing multiple tickers, it provides customizable timeframe inputs per symbol and instant alerts on price touches of the 200 EMA.
Key Features
Multi-symbol support: Configure up to 20 different symbols, each with its own timeframe setting.
Flexible timeframe input: Assign specific timeframes per symbol or use a default timeframe fallback.
Accurate 200 EMA calculation: Uses request.security to fetch 200 EMA from the symbol-specific timeframe.
Visual EMA plots: Displays both the EMA on the selected timeframe and the EMA on the current chart timeframe for comparison.
Touch alerts: Configurable alerts when price “touches” the 200 EMA within a user-defined sensitivity percentage.
Ticker memory: Remembers your configured symbols and displays them in an on-chart table.
Compact info table: Displays current symbol status, alert settings, and timeframe in a clean, transparent table overlay.
How to Use
Configure Symbols and Timeframes:
Input your desired symbols (up to 20) and their respective timeframes under the “Symbol Settings” groups in the indicator’s settings pane.
Set Default Timeframe:
Choose a default timeframe to be used when no specific timeframe is assigned for a symbol.
Adjust Alert Settings:
Enable or disable alerts and set the touch sensitivity (% distance from EMA to trigger alerts).
Alerts
Alerts trigger once per bar when the price touches the 200 EMA within the defined sensitivity threshold.
Alert messages include:
Symbol / Current price / EMA value / EMA timeframe used / Chart timeframe / Timestamp
Customization
200 EMA Color: Change the line color for better visibility.
Touch Sensitivity: Fine-tune how close price must be to the EMA to count as a touch (default 0.1%).
Enable Touch Alerts: Turn on/off alert notifications easily.
For:
- Swing traders monitoring multiple stocks or assets.
- Day traders watching key EMA levels on different timeframes.
- Analysts requiring a quick visual and alert system for 200 EMA touches.
- Portfolio managers tracking key technical levels across various securities.
Limitations
Supports up to 20 configured symbols (can be extended manually if needed).
Works best on charts with reasonable bar frequency due to request.security usage.
Alert frequency is limited to once per bar for clarity.
Disclaimer
This indicator is provided “as-is” for educational and informational purposes only. It does not guarantee trading success or financial gain.
Hull Moving Average Quantum Pro - Advanced Trading SystemThe Hull Moving Average Quantum Pro is a next-generation technical analysis tool that combines the legendary smoothness of Alan Hull's HMA formula with advanced quantum field visualization technology. This professional-grade indicator features three synchronized Hull Moving Average periods working in harmony to identify high-probability trading opportunities.
🎯 KEY FEATURES:
• Multi-Timeframe HMA Confluence - Triple HMA system (9, 21, 55 periods) for comprehensive trend analysis
• Quantum Field Visualization - Fibonacci-based dynamic support/resistance bands with 0.618, 1.0, and 1.618 ratios
• Energy Flow Momentum - Real-time visual representation of market momentum and directional bias
• Confluence Zone Detection - Automatically highlights areas where multiple HMAs converge for high-probability setups
• Professional Holographic Dashboard - Real-time trend strength, momentum, and market status display
• Three Visual Themes - Dark Intergalactic (Quantum Trading), Light Minimal (Clean Charts), Pro Modern (Low Saturation)
⚡ WHAT MAKES IT UNIQUE:
Unlike traditional moving average indicators, the HMA Quantum Pro eliminates lag while maintaining smoothness, providing traders with faster signals without sacrificing reliability. The quantum field visualization adds a new dimension to price action analysis by creating dynamic zones that adapt to market volatility.
📊 PERFECT FOR:
• Day Trading & Scalping - Fast HMA (9) provides quick entry/exit signals
• Swing Trading - Medium HMA (21) confirms trend continuation
• Position Trading - Slow HMA (55) identifies major trend changes
• All Markets - Forex, Stocks, Crypto, Futures, Indices
🔧 ADVANCED SETTINGS:
• Customizable HMA periods for any trading style
• Adjustable confluence threshold for precision filtering
• Visual intensity control for optimal chart clarity
• Field transparency settings for multi-indicator setups
💡 HOW TO USE:
1. Strong Bullish Signal - All three HMAs aligned upward with price above quantum fields
2. Strong Bearish Signal - All three HMAs aligned downward with price below quantum fields
3. Confluence Zones - High probability reversal/continuation areas
4. Energy Flow - Confirms momentum direction and strength
⭐ FREE VERSION FEATURES:
This free version includes all visual features and calculations. Premium version (coming soon) will add advanced alerts, multi-timeframe analysis, and AI-powered trade suggestions.
Created by professional traders for serious market participants. The Hull Moving Average formula was created by Alan Hull to reduce lag while maintaining smoothness - this indicator enhances that foundation with modern visualization technology.
EMA Triad Vanguard Pro [By TraderMan]📌 EMA Triad Vanguard Pro — Advanced Trend & Position Management System
📖 Introduction
EMA Triad Vanguard Pro is an advanced indicator that utilizes three different EMAs (Exponential Moving Averages) to analyze the direction, strength, and reliability of market trends.
It goes beyond a single timeframe, performing trend analysis across 8 different timeframes simultaneously and automatically tracking TP/SL management.
This makes it a powerful reference tool for both short-term traders and medium-to-long-term swing traders.
⚙ How It Works
EMAs:
EMA 21 → Responds quickly to short-term price changes.
EMA 50 → Shows medium-term price direction.
EMA 200 → Determines the long-term market trend.
Trend Direction Logic:
📈 Long Signal: EMA 21 crosses above EMA 200 and EMA 21 > EMA 50.
📉 Short Signal: EMA 21 crosses below EMA 200 and EMA 21 < EMA 50.
Trend Strength Calculation:
Calculates the percentage distance between EMAs.
Strength levels: Very Weak → Weak → Strong → Very Strong.
Multi-Timeframe Analysis:
Analyzes trend direction for: 5min, 15min, 30min, 1H, 4H, Daily, Weekly, and Monthly charts.
Generates an overall market bias from combined results.
Automatic Position Management:
When a position is opened, TP1, TP2, TP3, and SL levels are calculated automatically.
As price reaches these levels, chart labels appear (TP1★, TP2★, TP3★, SL!).
📊 How to Use
1️⃣ Long (Buy) Setup
EMA 21 must cross above EMA 200 ✅
EMA 21 must be above EMA 50 ✅
Overall market bias should be “Bullish” ✅
Entry Price: closing price of the signal candle.
TP levels: calculated based on upward % targets.
SL: a set % below the entry price.
2️⃣ Short (Sell) Setup
EMA 21 must cross below EMA 200 ✅
EMA 21 must be below EMA 50 ✅
Overall market bias should be “Bearish” ✅
Entry Price: closing price of the signal candle.
TP levels: calculated based on downward % targets.
SL: a set % above the entry price.
💡 Pro Tips
Multi-timeframe alignment significantly increases the signal reliability.
If trend strength is “Very Strong”, chances of hitting TP targets are higher.
Weak trends may cause false signals → confirm with extra indicators (RSI, MACD, Volume).
TP levels are ideal for partial take-profits → lock in gains and reduce risk.
📌 Advantages
✅ Displays both trend direction and trend strength at a glance.
✅ Multi-timeframe approach avoids tunnel vision from a single chart.
✅ Automatic TP/SL calculation eliminates manual measuring.
✅ Labeled signal alerts make tracking positions easy and visual.
⚠ Important Notes
No indicator is 100% accurate — sudden news events or manipulations may cause false signals.
Use it together with other technical and fundamental analysis methods.
Signal reliability may decrease in low liquidity markets.
🎯 In summary:
EMA Triad Vanguard Pro combines trend tracking, position management, and multi-timeframe analysis in a single package, helping professional traders reduce workload and make more strategic trades.
SAR PowerTrend Analyzer Pro [By TraderMan]📈 SAR PowerTrend Analyzer Pro
Hello Trader! 👋 This powerful SAR PowerTrend Analyzer Pro indicator analyzes market trends across multiple timeframes by combining Parabolic SAR and ATR indicators to provide clear and actionable signals. Designed for everyone who wants to track trends and enter trades confidently on TradingView. Here’s the detailed breakdown:
🔍 What’s the core concept?
Parabolic SAR (Stop and Reverse):
A classic tool to detect price reversals and determine trend direction. When price is above SAR → uptrend (bullish), below SAR → downtrend (bearish).
ATR (Average True Range):
Measures price volatility. A higher ATR means stronger trend potential; lower ATR means weak or indecisive trends.
This indicator merges these two to not only tell “up or down” but also provide a numerical trend strength reading. So you can clearly know when a trend is strong or weak.
⏱️ Comprehensive Multi-Timeframe Analysis
It doesn’t rely on just one timeframe! 📊
5 min, 15 min
1 hour, 4 hours
1 day, 1 week, 1 month
Tracking trends on all these simultaneously gives you a more reliable market overview. Helps avoid false signals from short-term noise and align with long-term trends.
🎯 How to use it? (Entry Signals)
Long Signal:
Price crosses SAR line from below → shows “LONG” label and green trend color, indicating bullish momentum.
Short Signal:
Price crosses SAR line from above → shows “SHORT” label and red trend color, signaling bearish trend start.
📊 Visuals and Table on Chart
SAR lines plotted above and below price with clear green/red colors.
Background color changes with trend direction for instant visual feedback.
Top-right table shows each timeframe’s:
Trend Direction (Bullish/Bearish)
Trend Strength (numerical value 0 to 1)
General market direction and strength are summarized in the table’s bottom rows.
⚡ Things to watch before entering trades
Check the table! If most timeframes are Bullish and strong, consider LONG positions.
If most are Bearish and strong, SHORT positions might be safer.
Avoid relying on single timeframe signals, wait for multi-timeframe confirmation.
Always watch price action and volume.
Place stop losses just outside the SAR line to manage risk effectively.
Risk management is key! Protecting your capital matters as much as making profits.
🎉 Why use this indicator?
✅ Multi-timeframe analysis brings the bigger picture to your screen.
✅ Clear color-coded signals make trend following easy and intuitive.
✅ Numerical trend strength optimizes your entry/exit decisions.
✅ Suitable for beginners and pros alike.
✅ Fast, stable, and visually clean on TradingView.
🧠 Pro Tip:
This indicator works best when combined with other technical tools and news analysis. There’s no “magic single indicator,” but a smart combination wins the race! 😉
✨ Add this powerful trend analysis tool to your charts now, catch the market’s rhythm, and boost your gains! 🚀📈
Mutanabby_AI | Ultimate Algo | Remastered+Overview
The Mutanabby_AI Ultimate Algo Remastered+ represents a sophisticated trend-following system that combines Supertrend analysis with multiple moving average confirmations. This comprehensive indicator is designed specifically for identifying high-probability trend continuation and reversal opportunities across various market conditions.
Core Algorithm Components
**Supertrend Foundation**: The primary signal generation relies on a customizable Supertrend indicator with adjustable sensitivity (1-20 range). This adaptive trend-following tool uses Average True Range calculations to establish dynamic support and resistance levels that respond to market volatility.
**SMA Confirmation Matrix**: Multiple Simple Moving Averages (SMA 4, 5, 9, 13) provide layered confirmation for signal strength. The algorithm distinguishes between regular signals and "Strong" signals based on SMA 4 vs SMA 5 relationship, offering traders different conviction levels for position sizing.
**Trend Ribbon Visualization**: SMA 21 and SMA 34 create a visual trend ribbon that changes color based on their relationship. Green ribbon indicates bullish momentum while red signals bearish conditions, providing immediate visual trend context.
**RSI-Based Candle Coloring**: Advanced 61-tier RSI system colors candles with gradient precision from deep red (RSI ≤20) through purple transitions to bright green (RSI ≥79). This visual enhancement helps traders instantly assess momentum strength and overbought/oversold conditions.
Signal Generation Logic
**Buy Signal Criteria**:
- Price crosses above Supertrend line
- Close price must be above SMA 9 (trend confirmation)
- Signal strength determined by SMA 4 vs SMA 5 relationship
- "Strong Buy" when SMA 4 ≥ SMA 5
- Regular "Buy" when SMA 4 < SMA 5
**Sell Signal Criteria**:
- Price crosses below Supertrend line
- Close price must be below SMA 9 (trend confirmation)
- Signal strength based on SMA relationship
- "Strong Sell" when SMA 4 ≤ SMA 5
- Regular "Sell" when SMA 4 > SMA 5
Advanced Risk Management System
**Automated TP/SL Calculation**: The indicator automatically calculates stop loss and take profit levels using ATR-based measurements. Risk percentage and ATR length are fully customizable, allowing traders to adapt to different market conditions and personal risk tolerance.
**Multiple Take Profit Targets**:
- 1:1 Risk-Reward ratio for conservative profit taking
- 2:1 Risk-Reward for balanced trade management
- 3:1 Risk-Reward for maximum profit potential
**Visual Risk Display**: All risk management levels appear as both labels and optional trend lines on the chart. Customizable line styles (solid, dashed, dotted) and positioning ensure clear visualization without chart clutter.
**Dynamic Level Updates**: Risk levels automatically recalculate with each new signal, maintaining current market relevance throughout position lifecycles.
Visual Enhancement Features
**Customizable Display Options**: Toggle trend ribbon, TP/SL levels, and risk lines independently. Decimal precision adjustments (1-8 decimal places) accommodate different instrument price formats and personal preferences.
**Professional Label System**: Clean, informative labels show entry points, stop losses, and take profit targets with precise price levels. Labels automatically position themselves for optimal chart readability.
**Color-Coded Momentum**: The gradient RSI candle coloring system provides instant visual feedback on momentum strength, helping traders assess market energy and potential reversal zones.
Implementation Strategy
**Timeframe Optimization**: The algorithm performs effectively across multiple timeframes, with higher timeframes (4H, Daily) providing more reliable signals for swing trading. Lower timeframes work well for day trading with appropriate risk adjustments.
**Sensitivity Adjustment**: Lower sensitivity values (1-5) generate fewer but higher-quality signals, ideal for conservative approaches. Higher sensitivity (15-20) increases signal frequency for active trading styles.
**Risk Management Integration**: Use the automated risk calculations as baseline parameters, adjusting risk percentage based on account size and market conditions. The 1:1, 2:1, 3:1 targets enable systematic profit-taking strategies.
Market Application
**Trend Following Excellence**: Primary strength lies in capturing significant trend movements through the Supertrend foundation with SMA confirmation. The dual-layer approach reduces false signals common in single-indicator systems.
**Momentum Assessment**: RSI-based candle coloring provides immediate momentum context, helping traders assess signal strength and potential continuation probability.
**Range Detection**: The trend ribbon helps identify ranging conditions when SMA 21 and SMA 34 converge, alerting traders to potential breakout opportunities.
Performance Optimization
**Signal Quality**: The requirement for both Supertrend crossover AND SMA 9 confirmation significantly improves signal reliability compared to basic trend-following approaches.
**Visual Clarity**: The comprehensive visual system enables rapid market assessment without complex calculations, ideal for traders managing multiple instruments.
**Adaptability**: Extensive customization options allow fine-tuning for specific markets, trading styles, and risk preferences while maintaining the core algorithm integrity.
## Non-Repainting Design
**Educational Note**: This indicator uses standard TradingView functions (Supertrend, SMA, RSI) with normal behavior patterns. Real-time updates on current candles are expected and standard across all technical indicators. Historical signals on closed candles remain fixed and unchanged, ensuring reliable backtesting and analysis.
**Signal Confirmation**: Final signals are confirmed only when candles close, following standard technical analysis principles. The algorithm provides clear distinction between developing signals and confirmed entries.
Technical Specifications
**Supertrend Parameters**: Default sensitivity of 4 with ATR length of 11 provides balanced signal generation. Sensitivity range from 1-20 allows adaptation to different market volatilities and trading preferences.
**Moving Average Configuration**: SMA periods of 8, 9, and 13 create multi-layered trend confirmation, while SMA 21 and 34 form the visual trend ribbon for broader market context.
**Risk Management**: ATR-based calculations with customizable risk percentage ensure dynamic adaptation to market volatility while maintaining consistent risk exposure principles.
Recommended Settings
**Conservative Approach**: Sensitivity 4-5, RSI length 14, higher timeframes (4H, Daily) for swing trading with maximum signal reliability.
**Active Trading**: Sensitivity 6-8, RSI length 8-10, intermediate timeframes (1H) for balanced signal frequency and quality.
**Scalping Setup**: Sensitivity 10-15, RSI length 5-8, lower timeframes (15-30min) with enhanced risk management protocols.
## Conclusion
The Mutanabby_AI Ultimate Algo Remastered+ combines proven trend-following principles with modern visual enhancements and comprehensive risk management. The algorithm's strength lies in its multi-layered confirmation approach and automated risk calculations, providing both novice and experienced traders with clear signals and systematic trade management.
Success with this system requires understanding the relationship between signal strength indicators and adapting sensitivity settings to match current market conditions. The comprehensive visual feedback system enables rapid decision-making while the automated risk management ensures consistent trade parameters.
Practice with different sensitivity settings and timeframes to optimize performance for your specific trading style and risk tolerance. The algorithm's systematic approach provides an excellent framework for disciplined trend-following strategies across various market environments.
Zero Lag Liquidity [AlgoAlpha]🟠 OVERVIEW
This script plots liquidity zones with zero lag using lower-timeframe wick profiles and high-volume wicks to mark key price reactions. It’s called Zero Lag Liquidity because it captures significant liquidity imbalances in real time by processing lower-TF price-volume distributions directly inside the wick of abnormal candles. The tool builds a volume histogram inside long upper/lower wicks, then calculates a local Point of Control (POC) to mark the price where most volume occurred. These levels act as visual liquidity zones, which can trigger labels, break signals, and trend detection depending on price interaction.
🟠 CONCEPTS
The core concept relies on identifying high-volume candles with unusually long wicks—often a sign of opposing liquidity. When a large upper or lower wick appears with a strong volume spike, the script builds a histogram of lower-timeframe closes and volumes inside that wick. It bins the wick into segments, sums volume per bin, and finds the POC. This POC becomes the liquidity level. The script then dynamically tracks whether price breaks above or rejects off these levels, adjusts the active trend regime accordingly, and highlights bars to help users spot continuation or reversal behavior. The logic avoids repainting or subjective interpretation by using fixed thresholds and lower-TF price action.
🟠 FEATURES
Dynamic liquidity levels rendered at POC of significant wicks, colored by bullish/bearish direction.
Break detection that removes levels once price decisively crosses them twice in the same direction.
Rejection detection that plots ▲/▼ markers when price bounces off levels intrabar.
Volume labels for each level, shown either as raw volume or percentage of total level volume.
Candle coloring based on trend direction (break-dominant).
🟠 USAGE
Use this indicator to track where liquidity has most likely entered the market via abnormal wick events. When a long wick forms with high volume, the script looks inside it (using your chosen lower timeframe) and marks the most traded price within it. These levels can serve as expected reversal or breakout zones. Rejections are marked with small arrows, while breaks trigger trend shifts and remove the level. You can toggle trend coloring to see directional bias after a breakout. Use the wick multiplier to control how selective the detector is (higher = stricter). Alerts and label modes help customize the signal for different asset types and chart styles.
