Harmonic Super GuppyHarmonic Super Guppy – Harmonic & Golden Ratio Trend Analysis Framework
Overview
Harmonic Super Guppy is a comprehensive trend analysis and visualization tool that evolves the classic Guppy Multiple Moving Average (GMMA) methodology, pioneered by Daryl Guppy to visualize the interaction between short-term trader behavior and long-term investor trends. into a harmonic and phase-based market framework. By combining harmonic weighting, golden ratio phasing, and multiple moving averages, it provides traders with a deep understanding of market structure, momentum, and trend alignment. Fast and slow line groups visually differentiate short-term trader activity from longer-term investor positioning, while adaptive fills and dynamic coloring clearly illustrate trend coherence, expansion, and contraction in real time.
Traditional GMMA focuses primarily on moving average convergence and divergence. Harmonic Super Guppy extends this concept, integrating frequency-aware harmonic analysis and golden ratio modulation, allowing traders to detect subtle cyclical forces and early trend shifts before conventional moving averages would react. This is particularly valuable for traders seeking to identify early trend continuation setups, preemptive breakout entries, and potential trend exhaustion zones. The indicator provides a multi-dimensional view, making it suitable for scalping, intraday trading, swing setups, and even longer-term position strategies.
The visual structure of Harmonic Super Guppy is intentionally designed to convey trend clarity without oversimplification. Fast lines reflect short-term trader sentiment, slow lines capture longer-term investor alignment, and fills highlight compression or expansion. The adaptive color coding emphasizes trend alignment: strong green for bullish alignment, strong red for bearish, and subtle gray tones for indecision. This allows traders to quickly gauge market conditions while preserving the granularity necessary for sophisticated analysis.
How It Works
Harmonic Super Guppy uses a combination of harmonic averaging, golden ratio phasing, and adaptive weighting to generate its signals.
Harmonic Weighting : Each moving average integrates three layers of harmonics:
Primary harmonic captures the dominant cyclical structure of the market.
Secondary harmonic introduces a complementary frequency for oscillatory nuance.
Tertiary harmonic smooths higher-frequency noise while retaining meaningful trend signals.
Golden Ratio Phase : Phases of each harmonic contribution are adjusted using the golden ratio (default φ = 1.618), ensuring alignment with natural market rhythms. This reduces lag and allows traders to detect trend shifts earlier than conventional moving averages.
Adaptive Trend Detection : Fast SMAs are compared against slow SMAs to identify structural trends:
UpTrend : Fast SMA exceeds slow SMA.
DownTrend : Fast SMA falls below slow SMA.
Frequency Scaling : The wave frequency setting allows traders to modulate responsiveness versus smoothing. Higher frequency emphasizes short-term moves, while lower frequency highlights structural trends. This enables adaptation across asset classes with different volatility characteristics.
Through this combination, Harmonic Super Guppy captures micro and macro market cycles, helping traders distinguish between transient noise and genuine trend development. The multi-harmonic approach amplifies meaningful price action while reducing false signals inherent in standard moving averages.
Interpretation
Harmonic Super Guppy provides a multi-dimensional perspective on market dynamics:
Trend Analysis : Alignment of fast and slow lines reveals trend direction and strength. Expanding harmonics indicate momentum building, while contraction signals weakening conditions or potential reversals.
Momentum & Volatility : Rapid expansion of fast lines versus slow lines reflects short-term bullish or bearish pressure. Compression often precedes breakout scenarios or volatility expansion. Traders can quickly gauge trend vigor and potential turning points.
Market Context : The indicator overlays harmonic and structural insights without dictating entry or exit points. It complements order blocks, liquidity zones, oscillators, and other technical frameworks, providing context for informed decision-making.
Phase Divergence Detection : Subtle divergence between harmonic layers (primary, secondary, tertiary) often signals early exhaustion in trends or hidden strength, offering preemptive insight into potential reversals or sustained continuation.
By observing both structural alignment and harmonic expansion/contraction, traders gain a clear sense of when markets are trending with conviction versus when conditions are consolidating or becoming unpredictable. This allows for proactive trade management, rather than reactive responses to lagging indicators.
Strategy Integration
Harmonic Super Guppy adapts to various trading methodologies with clear, actionable guidance.
Trend Following : Enter positions when fast and slow lines are aligned and harmonics are expanding. The broader the alignment, the stronger the confirmation of trend persistence. For example:
A fast line crossover above slow lines with expanding fills confirms momentum-driven continuation.
Traders can use harmonic amplitude as a filter to reduce entries against prevailing trends.
Breakout Trading : Periods of line compression indicate potential volatility expansion. When fast lines diverge from slow lines after compression, this often precedes breakouts. Traders can combine this visual cue with structural supports/resistances or order flow analysis to improve timing and precision.
Exhaustion and Reversals : Divergences between harmonic components, or contraction of fast lines relative to slow lines, highlight weakening trends. This can indicate liquidity exhaustion, trend fatigue, or corrective phases. For example:
A flattening fast line group above a rising slow line can hint at short-term overextension.
Traders may use these signals to tighten stops, take partial profits, or prepare for contrarian setups.
Multi-Timeframe Analysis : Overlay slow lines from higher timeframes on lower timeframe charts to filter noise and trade in alignment with larger market structures. For example:
A daily bullish alignment combined with a 15-minute breakout pattern increases probability of a successful intraday trade.
Conversely, a higher timeframe divergence can warn against taking counter-trend trades in lower timeframes.
Adaptive Trade Management : Harmonic expansion/contraction can guide dynamic risk management:
Stops may be adjusted according to slow line support/resistance or harmonic contraction zones.
Position sizing can be modulated based on harmonic amplitude and compression levels, optimizing risk-reward without rigid rules.
Technical Implementation Details
Harmonic Super Guppy is powered by a multi-layered harmonic and phase calculation engine:
Harmonic Processing : Primary, secondary, and tertiary harmonics are calculated per period to capture multiple market cycles simultaneously. This reduces noise and amplifies meaningful signals.
Golden Ratio Modulation : Phase adjustments based on φ = 1.618 align harmonic contributions with natural market rhythms, smoothing lag and improving predictive value.
Adaptive Trend Scaling : Fast line expansion reflects short-term momentum; slow lines provide structural trend context. Fills adapt dynamically based on alignment intensity and harmonic amplitude.
Multi-Factor Trend Analysis : Trend strength is determined by alignment of fast and slow lines over multiple bars, expansion/contraction of harmonic amplitudes, divergences between primary, secondary, and tertiary harmonics and phase synchronization with golden ratio cycles.
These computations allow the indicator to be highly responsive yet smooth, providing traders with actionable insights in real time without overloading visual complexity.
Optimal Application Parameters
Asset-Specific Guidance:
Forex Majors : Wave frequency 1.0–2.0, φ = 1.618–1.8
Large-Cap Equities : Wave frequency 0.8–1.5, φ = 1.5–1.618
Cryptocurrency : Wave frequency 1.2–3.0, φ = 1.618–2.0
Index Futures : Wave frequency 0.5–1.5, φ = 1.618
Timeframe Optimization:
Scalping (1–5min) : Emphasize fast lines, higher frequency for micro-move capture.
Day Trading (15min–1hr) : Balance fast/slow interactions for trend confirmation.
Swing Trading (4hr–Daily) : Focus on slow lines for structural guidance, fast lines for entry timing.
Position Trading (Daily–Weekly) : Slow lines dominate; harmonics highlight long-term cycles.
Performance Characteristics
High Effectiveness Conditions:
Clear separation between short-term and long-term trends.
Moderate-to-high volatility environments.
Assets with consistent volume and price rhythm.
Reduced Effectiveness:
Flat or extremely low volatility markets.
Erratic assets with frequent gaps or algorithmic dominance.
Ultra-short timeframes (<1min), where noise dominates.
Integration Guidelines
Signal Confirmation : Confirm alignment of fast and slow lines over multiple bars. Expansion of harmonic amplitude signals trend persistence.
Risk Management : Place stops beyond slow line support/resistance. Adjust sizing based on compression/expansion zones.
Advanced Feature Settings :
Frequency tuning for different volatility environments.
Phase analysis to track divergences across harmonics.
Use fills and amplitude patterns as a guide for dynamic trade management.
Multi-timeframe confirmation to filter noise and align with structural trends.
Disclaimer
Harmonic Super Guppy is a trend analysis and visualization tool, not a guaranteed profit system. Optimal performance requires proper wave frequency, golden ratio phase, and line visibility settings per asset and timeframe. Traders should combine the indicator with other technical frameworks and maintain disciplined risk management practices.
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TheWaveStrategy v6 - QQE + ATR (Optional Trailing)New Version Of the wave with QQE and ATR
• Compiles cleanly in Pine v6.
• Optional trailing stop toggle via useTrailingATR.
• Market exit uses strategy.close() properly.
• ATR spike filter uses 5m ATR.
• QQE confluence with 30m timeframe included.
Trading Sessions with Holidays & Timer🌍 Trading Sessions Matter
Markets breathe in cycles. When Tokyo, London, or New York steps in, liquidity shifts and price often reacts fast.
Example: New York closed BTC at $110K, and when traders woke up, the price was already $113K. That gap says everything about overnight pressure and the next move.
⚡ Indicator Features
✅ Session boxes (Tokyo, London, NY) with custom colors & time zones
✅ Open/close lines → spot gaps & momentum
✅ Average price per session → see where pressure builds
✅ Tick range → quick volatility check
✅ 🏖 Holiday markers → avoid false quiet markets
✅ Live status table → session OPEN / CLOSED + countdown timer
🚀 How to Use
Works on intraday timeframes (1m–4h)
Watch session opens/closes → liquidity shift points
Compare ranges & averages between Tokyo, London, NY
Use the timer to prep before the next wave
This tool helps you visualize the heartbeat of global markets session by session.
🔖 #BTCUSDT #Forex #TradingSessions #Crypto #DayTrading
Savitzky-Golay Hampel Filter | AlphaNattSavitzky-Golay Hampel Filter | AlphaNatt
A revolutionary indicator combining NASA's satellite data processing algorithms with robust statistical outlier detection to create the most scientifically advanced trend filter available on TradingView.
"This is the same mathematics that processes signals from the Hubble Space Telescope and analyzes data from the Large Hadron Collider - now applied to financial markets."
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🚀 SCIENTIFIC PEDIGREE
Savitzky-Golay Filter Applications:
NASA: Satellite telemetry and space probe data processing
CERN: Particle physics data analysis at the LHC
Pharmaceutical: Chromatography and spectroscopy analysis
Astronomy: Processing signals from radio telescopes
Medical: ECG and EEG signal processing
Hampel Filter Usage:
Aerospace: Cleaning sensor data from aircraft and spacecraft
Manufacturing: Quality control in precision engineering
Seismology: Earthquake detection and analysis
Robotics: Sensor fusion and noise reduction
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🧬 THE MATHEMATICS
1. Savitzky-Golay Filter
The SG filter performs local polynomial regression on data points:
Fits a polynomial of degree n to a sliding window of data
Evaluates the polynomial at the center point
Preserves higher moments (peaks, valleys) unlike moving averages
Maintains derivative information for true momentum analysis
Originally published in Analytical Chemistry (1964)
Mathematical Properties:
Optimal smoothing in the least-squares sense
Preserves statistical moments up to polynomial order
Exact derivative calculation without additional lag
Superior frequency response vs traditional filters
2. Hampel Filter
A robust outlier detector based on Median Absolute Deviation (MAD):
Identifies outliers using robust statistics
Replaces spurious values with polynomial-fitted estimates
Resistant to up to 50% contaminated data
MAD is 1.4826 times more robust than standard deviation
Outlier Detection Formula:
|x - median| > k × 1.4826 × MAD
Where k is the threshold parameter (typically 3 for 99.7% confidence)
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💎 WHY THIS IS SUPERIOR
vs Moving Averages:
Preserves peaks and valleys (critical for catching tops/bottoms)
No lag penalty for smoothness
Maintains derivative information
Polynomial fitting > simple averaging
vs Other Filters:
Outlier immunity (Hampel component)
Scientifically optimal smoothing
Preserves higher-order features
Used in billion-dollar research projects
Unique Advantages:
Feature Preservation: Maintains market structure while smoothing
Spike Immunity: Ignores false breakouts and stop hunts
Derivative Accuracy: True momentum without additional indicators
Scientific Validation: 60+ years of academic research
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⚙️ PARAMETER OPTIMIZATION
1. Polynomial Order (2-5)
2 (Quadratic): Maximum smoothing, gentle curves
3 (Cubic): Balanced smoothing and responsiveness (recommended)
4-5 (Higher): More responsive, preserves more features
2. Window Size (7-51)
Must be odd number
Larger = smoother but more lag
Formula: 2×(desired smoothing period) + 1
Default 21 = analyzes 10 bars each side
3. Hampel Threshold (1.0-5.0)
1.0: Aggressive outlier removal (68% confidence)
2.0: Moderate outlier removal (95% confidence)
3.0: Conservative outlier removal (99.7% confidence) (default)
4.0+: Only extreme outliers removed
4. Final Smoothing (1-7)
Additional WMA smoothing after filtering
1 = No additional smoothing
3-5 = Recommended for most timeframes
7 = Ultra-smooth for position trading
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📊 TRADING STRATEGIES
Signal Recognition:
Cyan Line: Bullish trend with positive derivative
Pink Line: Bearish trend with negative derivative
Color Change: Trend reversal with polynomial confirmation
1. Trend Following Strategy
Enter when price crosses above cyan filter
Exit when filter turns pink
Use filter as dynamic stop loss
Best in trending markets
2. Mean Reversion Strategy
Enter long when price touches filter from below in uptrend
Enter short when price touches filter from above in downtrend
Exit at opposite band or filter color change
Excellent for range-bound markets
3. Derivative Strategy (Advanced)
The SG filter preserves derivative information
Acceleration = second derivative > 0
Enter on positive first derivative + positive acceleration
Exit on negative second derivative (momentum slowing)
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📈 PERFORMANCE CHARACTERISTICS
Strengths:
Outlier Immunity: Ignores stop hunts and flash crashes
Feature Preservation: Catches tops/bottoms better than MAs
Smooth Output: Reduces whipsaws significantly
Scientific Basis: Not curve-fitted or optimized to markets
Considerations:
Slight lag in extreme volatility (all filters have this)
Requires odd window sizes (mathematical requirement)
More complex than simple moving averages
Best with liquid instruments
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🔬 SCIENTIFIC BACKGROUND
Savitzky-Golay Publication:
"Smoothing and Differentiation of Data by Simplified Least Squares Procedures"
- Abraham Savitzky & Marcel Golay
- Analytical Chemistry, Vol. 36, No. 8, 1964
Hampel Filter Origin:
"Robust Statistics: The Approach Based on Influence Functions"
- Frank Hampel et al., 1986
- Princeton University Press
These techniques have been validated in thousands of scientific papers and are standard tools in:
NASA's Jet Propulsion Laboratory
European Space Agency
CERN (Large Hadron Collider)
MIT Lincoln Laboratory
Max Planck Institutes
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💡 ADVANCED TIPS
News Trading: Lower Hampel threshold before major events to catch spikes
Scalping: Use Order=2 for maximum smoothness, Window=11 for responsiveness
Position Trading: Increase Window to 31+ for long-term trends
Combine with Volume: Strong trends need volume confirmation
Multiple Timeframes: Use daily for trend, hourly for entry
Watch the Derivative: Filter color changes when first derivative changes sign
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⚠️ IMPORTANT NOTICES
Not financial advice - educational purposes only
Past performance does not guarantee future results
Always use proper risk management
Test settings on your specific instrument and timeframe
No indicator is perfect - part of complete trading system
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🏆 CONCLUSION
The Savitzky-Golay Hampel Filter represents the pinnacle of scientific signal processing applied to financial markets. By combining polynomial regression with robust outlier detection, traders gain access to the same mathematical tools that:
Guide spacecraft to other planets
Detect gravitational waves from black holes
Analyze particle collisions at near light-speed
Process signals from deep space
This isn't just another indicator - it's rocket science for trading .
"When NASA needs to separate signal from noise in billion-dollar missions, they use these exact algorithms. Now you can too."
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Developed by AlphaNatt
Version: 1.0
Release: 2025
Pine Script: v6
"Where Space Technology Meets Market Analysis"
Not financial advice. Always DYOR
PnL Bubble [%] | Fractalyst1. What's the indicator purpose?
The PnL Bubble indicator transforms your strategy's trade PnL percentages into an interactive bubble chart with professional-grade statistics and performance analytics. It helps traders quickly assess system profitability, understand win/loss distribution patterns, identify outliers, and make data-driven strategy improvements.
How does it work?
Think of this indicator as a visual report card for your trading performance. Here's what it does:
What You See
Colorful Bubbles: Each bubble represents one of your trades
Blue/Cyan bubbles = Winning trades (you made money)
Red bubbles = Losing trades (you lost money)
Bigger bubbles = Bigger wins or losses
Smaller bubbles = Smaller wins or losses
How It Organizes Your Trades:
Like a Photo Album: Instead of showing all your trades at once (which would be messy), it shows them in "pages" of 500 trades each:
Page 1: Your first 500 trades
Page 2: Trades 501-1000
Page 3: Trades 1001-1500, etc.
What the Numbers Tell You:
Average Win: How much money you typically make on winning trades
Average Loss: How much money you typically lose on losing trades
Expected Value (EV): Whether your trading system makes money over time
Positive EV = Your system is profitable long-term
Negative EV = Your system loses money long-term
Payoff Ratio (R): How your average win compares to your average loss
R > 1 = Your wins are bigger than your losses
R < 1 = Your losses are bigger than your wins
Why This Matters:
At a Glance: You can instantly see if you're a profitable trader or not
Pattern Recognition: Spot if you have more big wins than big losses
Performance Tracking: Watch how your trading improves over time
Realistic Expectations: Understand what "average" performance looks like for your system
The Cool Visual Effects:
Animation: The bubbles glow and shimmer to make the chart more engaging
Highlighting: Your biggest wins and losses get extra attention with special effects
Tooltips: hover any bubble to see details about that specific trade.
What are the underlying calculations?
The indicator processes trade PnL data using a dual-matrix architecture for optimal performance:
Dual-Matrix System:
• Display Matrix (display_matrix): Bounded to 500 trades for rendering performance
• Statistics Matrix (stats_matrix): Unbounded storage for complete statistical accuracy
Trade Classification & Aggregation:
// Separate wins, losses, and break-even trades
if val > 0.0
pos_sum += val // Sum winning trades
pos_count += 1 // Count winning trades
else if val < 0.0
neg_sum += val // Sum losing trades
neg_count += 1 // Count losing trades
else
zero_count += 1 // Count break-even trades
Statistical Averages:
avg_win = pos_count > 0 ? pos_sum / pos_count : na
avg_loss = neg_count > 0 ? math.abs(neg_sum) / neg_count : na
Win/Loss Rates:
total_obs = pos_count + neg_count + zero_count
win_rate = pos_count / total_obs
loss_rate = neg_count / total_obs
Expected Value (EV):
ev_value = (avg_win × win_rate) - (avg_loss × loss_rate)
Payoff Ratio (R):
R = avg_win ÷ |avg_loss|
Contribution Analysis:
ev_pos_contrib = avg_win × win_rate // Positive EV contribution
ev_neg_contrib = avg_loss × loss_rate // Negative EV contribution
How to integrate with any trading strategy?
Equity Change Tracking Method:
//@version=6
strategy("Your Strategy with Equity Change Export", overlay=true)
float prev_trade_equity = na
float equity_change_pct = na
if barstate.isconfirmed and na(prev_trade_equity)
prev_trade_equity := strategy.equity
trade_just_closed = strategy.closedtrades != strategy.closedtrades
if trade_just_closed and not na(prev_trade_equity)
current_equity = strategy.equity
equity_change_pct := ((current_equity - prev_trade_equity) / prev_trade_equity) * 100
prev_trade_equity := current_equity
else
equity_change_pct := na
plot(equity_change_pct, "Equity Change %", display=display.data_window)
Integration Steps:
1. Add equity tracking code to your strategy
2. Load both strategy and PnL Bubble indicator on the same chart
3. In bubble indicator settings, select your strategy's equity tracking output as data source
4. Configure visualization preferences (colors, effects, page navigation)
How does the pagination system work?
The indicator uses an intelligent pagination system to handle large trade datasets efficiently:
Page Organization:
• Page 1: Trades 1-500 (most recent)
• Page 2: Trades 501-1000
• Page 3: Trades 1001-1500
• Page N: Trades to
Example: With 1,500 trades total (3 pages available):
• User selects Page 1: Shows trades 1-500
• User selects Page 4: Automatically falls back to Page 3 (trades 1001-1500)
5. Understanding the Visual Elements
Bubble Visualization:
• Color Coding: Cyan/blue gradients for wins, red gradients for losses
• Size Mapping: Bubble size proportional to trade magnitude (larger = bigger P&L)
• Priority Rendering: Largest trades displayed first to ensure visibility
• Gradient Effects: Color intensity increases with trade magnitude within each category
Interactive Tooltips:
Each bubble displays quantitative trade information:
tooltip_text = outcome + " | PnL: " + pnl_str +
"\nDate: " + date_str + " " + time_str +
"\nTrade #" + str.tostring(trade_number) + " (Page " + str.tostring(active_page) + ")" +
"\nRank: " + str.tostring(rank) + " of " + str.tostring(n_display_rows) +
"\nPercentile: " + str.tostring(percentile, "#.#") + "%" +
"\nMagnitude: " + str.tostring(magnitude_pct, "#.#") + "%"
Example Tooltip:
Win | PnL: +2.45%
Date: 2024.03.15 14:30
Trade #1,247 (Page 3)
Rank: 5 of 347
Percentile: 98.6%
Magnitude: 85.2%
Reference Lines & Statistics:
• Average Win Line: Horizontal reference showing typical winning trade size
• Average Loss Line: Horizontal reference showing typical losing trade size
• Zero Line: Threshold separating wins from losses
• Statistical Labels: EV, R-Ratio, and contribution analysis displayed on chart
What do the statistical metrics mean?
Expected Value (EV):
Represents the mathematical expectation per trade in percentage terms
EV = (Average Win × Win Rate) - (Average Loss × Loss Rate)
Interpretation:
• EV > 0: Profitable system with positive mathematical expectation
• EV = 0: Break-even system, profitability depends on execution
• EV < 0: Unprofitable system with negative mathematical expectation
Example: EV = +0.34% means you expect +0.34% profit per trade on average
Payoff Ratio (R):
Quantifies the risk-reward relationship of your trading system
R = Average Win ÷ |Average Loss|
Interpretation:
• R > 1.0: Wins are larger than losses on average (favorable risk-reward)
• R = 1.0: Wins and losses are equal in magnitude
• R < 1.0: Losses are larger than wins on average (unfavorable risk-reward)
Example: R = 1.5 means your average win is 50% larger than your average loss
Contribution Analysis (Σ):
Breaks down the components of expected value
Positive Contribution (Σ+) = Average Win × Win Rate
Negative Contribution (Σ-) = Average Loss × Loss Rate
Purpose:
• Shows how much wins contribute to overall expectancy
• Shows how much losses detract from overall expectancy
• Net EV = Σ+ - Σ- (Expected Value per trade)
Example: Σ+: 1.23% means wins contribute +1.23% to expectancy
Example: Σ-: -0.89% means losses drag expectancy by -0.89%
Win/Loss Rates:
Win Rate = Count(Wins) ÷ Total Trades
Loss Rate = Count(Losses) ÷ Total Trades
Shows the probability of winning vs losing trades
Higher win rates don't guarantee profitability if average losses exceed average wins
7. Demo Mode & Synthetic Data Generation
When using built-in sources (close, open, etc.), the indicator generates realistic demo trades for testing:
if isBuiltInSource(source_data)
// Generate random trade outcomes with realistic distribution
u_sign = prand(float(time), float(bar_index))
if u_sign < 0.5
v_push := -1.0 // Loss trade
else
// Skewed distribution favoring smaller wins (realistic)
u_mag = prand(float(time) + 9876.543, float(bar_index) + 321.0)
k = 8.0 // Skewness factor
t = math.pow(u_mag, k)
v_push := 2.5 + t * 8.0 // Win trade
Demo Characteristics:
• Realistic win/loss distribution mimicking actual trading patterns
• Skewed distribution favoring smaller wins over large wins
• Deterministic randomness for consistent demo results
• Includes jitter effects to prevent visual overlap
8. Performance Limitations & Optimizations
Display Constraints:
points_count = 500 // Maximum 500 dots per page for optimal performance
Pine Script v6 Limits:
• Label Count: Maximum 500 labels per indicator
• Line Count: Maximum 100 lines per indicator
• Box Count: Maximum 50 boxes per indicator
• Matrix Size: Efficient memory management with dual-matrix system
Optimization Strategies:
• Pagination System: Handle unlimited trades through 500-trade pages
• Priority Rendering: Largest trades displayed first for maximum visibility
• Dual-Matrix Architecture: Separate display (bounded) from statistics (unbounded)
• Smart Fallback: Automatic page clamping prevents empty displays
Impact & Workarounds:
• Visual Limitation: Only 500 trades visible per page
• Statistical Accuracy: Complete dataset used for all calculations
• Navigation: Use page input to browse through entire trade history
• Performance: Smooth operation even with thousands of trades
9. Statistical Accuracy Guarantees
Data Integrity:
• Complete Dataset: Statistics matrix stores ALL trades without limit
• Proper Aggregation: Separate tracking of wins, losses, and break-even trades
• Mathematical Precision: Pine Script v6's enhanced floating-point calculations
• Dual-Matrix System: Display limitations don't affect statistical accuracy
Calculation Validation:
// Verified formulas match standard trading mathematics
avg_win = pos_sum / pos_count // Standard average calculation
win_rate = pos_count / total_obs // Standard probability calculation
ev_value = (avg_win * win_rate) - (avg_loss * loss_rate) // Standard EV formula
Accuracy Features:
• Mathematical Correctness: Formulas follow established trading statistics
• Data Preservation: Complete dataset maintained for all calculations
• Precision Handling: Proper rounding and boundary condition management
• Real-Time Updates: Statistics recalculated on every new trade
10. Advanced Technical Features
Real-Time Animation Engine:
// Shimmer effects with sine wave modulation
offset = math.sin(shimmer_t + phase) * amp
// Dynamic transparency with organic flicker
new_transp = math.min(flicker_limit, math.max(-flicker_limit, cur_transp + dir * flicker_step))
• Sine Wave Shimmer: Dynamic glowing effects on bubbles
• Organic Flicker: Random transparency variations for natural feel
• Extreme Value Highlighting: Special visual treatment for outliers
• Smooth Animations: Tick-based updates for fluid motion
Magnitude-Based Priority Rendering:
// Sort trades by magnitude for optimal visual hierarchy
sort_indices_by_magnitude(values_mat)
• Largest First: Most important trades always visible
• Intelligent Sorting: Custom bubble sort algorithm for trade prioritization
• Performance Optimized: Efficient sorting for real-time updates
• Visual Hierarchy: Ensures critical trades never get hidden
Professional Tooltip System:
• Quantitative Data: Pure numerical information without interpretative language
• Contextual Ranking: Shows trade position within page dataset
• Percentile Analysis: Performance ranking as percentage
• Magnitude Scaling: Relative size compared to page maximum
• Professional Format: Clean, data-focused presentation
11. Quick Start Guide
Step 1: Add Indicator
• Search for "PnL Bubble | Fractalyst" in TradingView indicators
• Add to your chart (works on any timeframe)
Step 2: Configure Data Source
• Demo Mode: Leave source as "close" to see synthetic trading data
• Strategy Mode: Select your strategy's PnL% output as data source
Step 3: Customize Visualization
• Colors: Set positive (cyan), negative (red), and neutral colors
• Page Navigation: Use "Trade Page" input to browse trade history
• Visual Effects: Built-in shimmer and animation effects are enabled by default
Step 4: Analyze Performance
• Study bubble patterns for win/loss distribution
• Review statistical metrics: EV, R-Ratio, Win Rate
• Use tooltips for detailed trade analysis
• Navigate pages to explore full trade history
Step 5: Optimize Strategy
• Identify outlier trades (largest bubbles)
• Analyze risk-reward profile through R-Ratio
• Monitor Expected Value for system profitability
• Use contribution analysis to understand win/loss impact
12. Why Choose PnL Bubble Indicator?
Unique Advantages:
• Advanced Pagination: Handle unlimited trades with smart fallback system
• Dual-Matrix Architecture: Perfect balance of performance and accuracy
• Professional Statistics: Institution-grade metrics with complete data integrity
• Real-Time Animation: Dynamic visual effects for engaging analysis
• Quantitative Tooltips: Pure numerical data without subjective interpretations
• Priority Rendering: Intelligent magnitude-based display ensures critical trades are always visible
Technical Excellence:
• Built with Pine Script v6 for maximum performance and modern features
• Optimized algorithms for smooth operation with large datasets
• Complete statistical accuracy despite display optimizations
• Professional-grade calculations matching institutional trading analytics
Practical Benefits:
• Instantly identify system profitability through visual patterns
• Spot outlier trades and risk management issues
• Understand true risk-reward profile of your strategies
• Make data-driven decisions for strategy optimization
• Professional presentation suitable for performance reporting
Disclaimer & Risk Considerations:
Important: Historical performance metrics, including positive Expected Value (EV), do not guarantee future trading success. Statistical measures are derived from finite sample data and subject to inherent limitations:
• Sample Bias: Historical data may not represent future market conditions or regime changes
• Ergodicity Assumption: Markets are non-stationary; past statistical relationships may break down
• Survivorship Bias: Strategies showing positive historical EV may fail during different market cycles
• Parameter Instability: Optimal parameters identified in backtesting often degrade in forward testing
• Transaction Cost Evolution: Slippage, spreads, and commission structures change over time
• Behavioral Factors: Live trading introduces psychological elements absent in backtesting
• Black Swan Events: Extreme market events can invalidate statistical assumptions instantaneously
SMC - Institutional Confidence Oscillator [PhenLabs]📊 Institutional Confidence Oscillator
Version: PineScript™v6
📌 Description
The Institutional Confidence Oscillator (ICO) revolutionizes market analysis by automatically detecting and evaluating institutional activity at key support and resistance levels using our own in-house detection system. This sophisticated indicator combines volume analysis, volatility measurements, and mathematical confidence algorithms to provide real-time readings of institutional sentiment and zone strength.
Using our advanced thin liquidity detection, the ICO identifies high-volume, narrow-range bars that signal institutional zone formation, then tracks how these zones perform under market pressure. The result is a dual-wave confidence oscillator that shows traders when institutions are actively defending price levels versus when they’re abandoning positions.
The indicator transforms complex institutional behavior patterns into clear, actionable confidence percentiles, helping traders align with smart money movements and avoid common retail trading pitfalls.
🚀 Points of Innovation
Automated thin liquidity zone detection using volume threshold multipliers and zone size filtering
Dual-sided confidence tracking for both support and resistance levels simultaneously
Sigmoid function processing for enhanced mathematical accuracy in confidence calculations
Real-time institutional defense pattern analysis through complete test cycles
Advanced visual smoothing options with multiple algorithmic methods (EMA, SMA, WMA, ALMA)
Integrated momentum indicators and gradient visualization for enhanced signal clarity
🔧 Core Components
Volume Threshold System: Analyzes volume ratios against baseline averages to identify institutional activity spikes
Zone Detection Algorithm: Automatically identifies thin liquidity zones based on customizable volume and size parameters
Confidence Lifecycle Engine: Tracks institutional defense patterns through complete observation windows
Mathematical Processing Core: Uses sigmoid functions to convert raw market data into normalized confidence percentiles
Visual Enhancement Suite: Provides multiple smoothing methods and customizable display options for optimal chart interpretation
🔥 Key Features
Auto-Detection Technology: Automatically scans for institutional zones without manual intervention, saving analysis time
Dual Confidence Tracking: Simultaneously monitors both support and resistance institutional activity for comprehensive market view
Smart Zone Validation: Evaluates zone strength through volume analysis, adverse excursion measurement, and defense success rates
Customizable Parameters: Extensive input options for volume thresholds, observation windows, and visual preferences
Real-Time Updates: Continuously processes market data to provide current institutional confidence readings
Enhanced Visualization: Features gradient fills, momentum indicators, and information panels for clear signal interpretation
🎨 Visualization
Dual Oscillator Lines: Support confidence (cyan) and resistance confidence (red) plotted as percentage values 0-100%
Gradient Fill Areas: Color-coded regions showing confidence dominance and strength levels
Reference Grid Lines: Horizontal markers at 25%, 50%, and 75% levels for easy interpretation
Information Panel: Real-time display of current confidence percentiles with color-coded dominance indicators
Momentum Indicators: Rate of change visualization for confidence trends
Background Highlights: Extreme confidence level alerts when readings exceed 80%
📖 Usage Guidelines
Auto-Detection Settings
Use Auto-Detection
Default: true
Description: Enables automatic thin liquidity zone identification based on volume and size criteria
Volume Threshold Multiplier
Default: 6.0, Range: 1.0+
Description: Controls sensitivity of volume spike detection for zone identification, higher values require more significant volume increases
Volume MA Length
Default: 15, Range: 1+
Description: Period for volume moving average baseline calculation, affects volume spike sensitivity
Max Zone Height %
Default: 0.5%, Range: 0.05%+
Description: Filters out wide price bars, keeping only thin liquidity zones as percentage of current price
Confidence Logic Settings
Test Observation Window
Default: 20 bars, Range: 2+
Description: Number of bars to monitor zone tests for confidence calculation, longer windows provide more stable readings
Clean Break Threshold
Default: 1.5 ATR, Range: 0.1+
Description: ATR multiple required for zone invalidation, higher values make zones more persistent
Visual Settings
Smoothing Method
Default: EMA, Options: SMA/EMA/WMA/ALMA
Description: Algorithm for signal smoothing, EMA responds faster while SMA provides more stability
Smoothing Length
Default: 5, Range: 1-50
Description: Period for smoothing calculation, higher values create smoother lines with more lag
✅ Best Use Cases
Trending market analysis where institutional zones provide reliable support/resistance levels
Breakout confirmation by validating zone strength before position entry
Divergence analysis when confidence shifts between support and resistance levels
Risk management through identification of high-confidence institutional backing
Market structure analysis for understanding institutional sentiment changes
⚠️ Limitations
Performs best in liquid markets with clear institutional participation
May produce false signals during low-volume or holiday trading periods
Requires sufficient price history for accurate confidence calculations
Confidence readings can fluctuate rapidly during high-impact news events
Manual fallback zones may not reflect actual institutional activity
💡 What Makes This Unique
Automated Detection: First Pine Script indicator to automatically identify thin liquidity zones using sophisticated volume analysis
Dual-Sided Analysis: Simultaneously tracks institutional confidence for both support and resistance levels
Mathematical Precision: Uses sigmoid functions for enhanced accuracy in confidence percentage calculations
Real-Time Processing: Continuously evaluates institutional defense patterns as market conditions change
Visual Innovation: Advanced smoothing options and gradient visualization for superior chart clarity
🔬 How It Works
1. Zone Identification Process:
Scans for high-volume bars that exceed the volume threshold multiplier
Filters bars by maximum zone height percentage to identify thin liquidity conditions
Stores qualified zones with proximity threshold filtering for relevance
2. Confidence Calculation Process:
Monitors price interaction with identified zones during observation windows
Measures volume ratios and adverse excursions during zone tests
Applies sigmoid function processing to normalize raw data into confidence percentiles
3. Real-Time Analysis Process:
Continuously updates confidence readings as new market data becomes available
Tracks institutional defense success rates and zone validation patterns
Provides visual and numerical feedback through the oscillator display
💡 Note:
The ICO works best when combined with traditional technical analysis and proper risk management. Higher confidence readings indicate stronger institutional backing but should be confirmed with price action and volume analysis. Consider using multiple timeframes for comprehensive market structure understanding.
NY Session First 15m Range ORB Strategy first 15m high&low NY session
let you know the high and low of first 15m and the first candle is sitck out of the line you can ride on the wave to make moeny no bul OANDA:XAUUSD SP:SPX
RSI Wave squeezePlots TTM Squeeze momentum histogram (green/red).
Plots RSI (blue) in the same pane.
Shows squeeze dots and RSI overbought/oversold lines.
ECG chart - mauricioofsousaMGO Primary – Matriz Gráficos ON
The Blockchain of Trading applied to price behavior
The MGO Primary is the foundation of Matriz Gráficos ON — an advanced graphical methodology that transforms market movement into a logical, predictable, and objective sequence, inspired by blockchain architecture and periodic oscillatory phenomena.
This indicator replaces emotional candlestick reading with a mathematical interpretation of price blocks, cycles, and frequency. Its mission is to eliminate noise, anticipate reversals, and clearly show where capital is entering or exiting the market.
What MGO Primary detects:
Oscillatory phenomena that reveal the true behavior of orders in the book:
RPA – Breakout of Bullish Pivot
RPB – Breakout of Bearish Pivot
RBA – Sharp Bullish Breakout
RBB – Sharp Bearish Breakout
Rhythmic patterns that repeat in medium timeframes (especially on 12H and 4H)
Wave and block frequency, highlighting critical entry and exit zones
Validation through Primary and Secondary RSI, measuring the real strength behind movements
Who is this indicator for:
Traders seeking statistical clarity and visual logic
Operators who want to escape the subjectivity of candlesticks
Anyone who values technical precision with operational discipline
Recommended use:
Ideal timeframes: 12H (high precision) and 4H (moderate intensity)
Recommended assets: indices (e.g., NASDAQ), liquid stocks, and futures
Combine with: structured risk management and macro context analysis
Real-world performance:
The MGO12H achieved a 92% accuracy rate in 2025 on the NASDAQ, outperforming the average performance of major global quantitative strategies, with a net score of over 6,200 points for the year.
Mutanabby_AI | Fresh Algo V24Mutanabby_AI | Fresh Algo V24: Advanced Multi-Mode Trading System
Overview
The Mutanabby_AI Fresh Algo V24 represents a sophisticated evolution of multi-component trading systems that adapts to various market conditions through advanced operational configurations and enhanced analytical capabilities. This comprehensive indicator provides traders with multiple signal generation approaches, specialized assistant functions, and dynamic risk management tools designed for professional market analysis across diverse trading environments.
Primary Signal Generation Framework
The Fresh Algo V24 operates through two fundamental signal generation approaches that accommodate different market perspectives and trading philosophies. The Trending Signals Mode serves as the primary trend-following mechanism, combining Wave Trend Oscillator analysis with Supertrend directional signals and Squeeze Momentum breakout detection. This mode incorporates ADX filtering that requires values exceeding 20 to ensure sufficient trend strength exists before signal activation, making it particularly effective during sustained directional market movements where momentum persistence creates profitable trading opportunities.
The Contrarian Signals Mode provides an alternative approach targeting reversal opportunities through extreme market condition identification. This mode activates when the Wave Trend Oscillator reaches critical threshold levels, specifically when readings surpass 65 indicating potential bearish reversal conditions or drop below 35 suggesting bullish reversal opportunities. This methodology proves valuable during overextended market phases where mean reversion becomes statistically probable.
Advanced Filtering Mechanisms
The system incorporates multiple sophisticated filtering mechanisms designed to enhance signal quality and reduce false positive occurrences. The High Volume Filter requires volume expansion confirmation before signal activation, utilizing exponential moving average calculations to ensure institutional participation accompanies price movements. This filter substantially improves signal reliability by eliminating low-conviction breakouts that lack adequate volume support from professional market participants.
The Strong Filter provides additional trend confirmation through 200-period exponential moving average analysis. Long position signals require price action above this benchmark level, while short position signals necessitate price action below it. This ensures strategic alignment with longer-term trend direction and reduces the probability of trading against major market movements that could invalidate shorter-term signals.
Cloud Filter Configuration System
The Fresh Algo V24 offers four distinct cloud filter configurations, each optimized for specific trading timeframes and market approaches. The Smooth Cloud Filter utilizes the mathematical relationship between 150-period and 250-period exponential moving averages, providing stable trend identification suitable for position trading strategies. This configuration generates signals exclusively when price action aligns with cloud direction, creating a more deliberate but highly reliable signal generation process.
The Swing Cloud Filter employs modified Supertrend calculations with parameters specifically optimized for swing trading timeframes. This filter achieves optimal balance between responsiveness and stability, adapting effectively to medium-term price movements while filtering excessive market noise that typically affects shorter-term analytical systems.
For active intraday traders, the Scalping Cloud Filter utilizes accelerated Supertrend calculations designed to capture rapid trend changes effectively. This configuration provides enhanced signal generation frequency suitable for compressed timeframe strategies. The advanced Scalping+ Cloud Filter incorporates Hull Moving Average confirmation, delivering maximum responsiveness for ultra-short-term trading while maintaining signal quality through additional momentum validation processes.
Specialized Assistant Functionality
The system includes two distinct assistant modes that provide supplementary market analysis capabilities. The Trend Assistant Mode activates advanced cloud analysis overlays that display dynamic support and resistance zones calculated through adaptive volatility algorithms. These levels automatically adjust to current market conditions, providing visual guidance for identifying trend continuation patterns and potential reversal areas with mathematical precision.
The Trend Tracker Mode concentrates on long-term trend identification by displaying major exponential moving averages with color-coded fill areas that clarify directional bias. This mode maintains visual simplicity while providing comprehensive trend context evaluation, enabling traders to quickly assess broader market direction and align shorter-term strategies accordingly.
Dynamic Risk Management System
The integrated risk management system automatically adapts across all operational modes, calculating stop loss and take profit targets using Average True Range multiples that adjust to current market volatility. This approach ensures consistent risk parameters regardless of selected operational mode while maintaining relevance to prevailing market conditions.
Stop loss placement occurs at dynamically calculated distances from entry points, while three progressive take profit targets establish at customizable ATR multiples respectively. The system automatically updates these levels upon trend direction changes, ensuring current market volatility influences all risk calculations and maintains appropriate risk-reward ratios throughout trade management.
Comprehensive Market Analysis Dashboard
The sophisticated dashboard provides real-time market analysis including volatility measurements, institutional activity assessment, and multi-timeframe trend evaluation across five-minute through four-hour periods. This comprehensive market context assists traders in selecting appropriate operational modes based on current market characteristics rather than relying exclusively on historical performance data.
The multi-timeframe analysis ensures mode selection considers broader market context beyond the primary trading timeframe, improving overall strategic alignment and reducing conflicts between different temporal market perspectives. The dashboard displays market state classification, volatility percentages, institutional activity levels, current trading session information, and trend pressure indicators with professional formatting and clear visual hierarchy.
Enhanced Trading Assistants
The Fresh Algo V24 includes specialized trading assistant features that complement the primary signal generation system. The Reversal Dot functionality identifies potential reversal points through Wave Trend Oscillator analysis, displaying visual indicators when crossover conditions occur at extreme levels. These reversal indicators provide early warning signals for potential trend changes before they appear in the primary signal system.
The Dynamic Take Profit Labels feature automatically identifies optimal profit-taking opportunities through RSI threshold analysis, marking potential exit points at multiple levels for long positions and corresponding levels for short positions. This automated profit management system helps traders optimize exit timing without requiring constant manual monitoring of technical indicators.
Advanced Alert System
The comprehensive alert system accommodates all operational modes while providing granular notification control for various signal types and risk management events. Traders can configure separate alerts for normal buy signals, strong buy signals, normal sell signals, strong sell signals, stop loss triggers, and individual take profit target achievements.
Cloud crossover alerts notify traders when trend direction changes occur, providing early indication of potential strategy adjustments. The alert system includes detailed trade setup information, timeframe data, and relevant entry and exit levels, ensuring traders receive complete context for informed decision-making without requiring constant chart monitoring.
Technical Foundation Architecture
The Fresh Algo V24 combines multiple proven technical analysis components including Wave Trend Oscillator for momentum assessment, Supertrend for directional bias determination, Squeeze Momentum for volatility analysis, and various exponential moving averages for trend confirmation. Each component contributes specific market insights while the unified system provides comprehensive market evaluation through their mathematical integration.
The multi-component approach reduces dependency on individual indicator limitations while leveraging the analytical strengths of each technical tool. This creates a robust analytical framework capable of adapting to diverse market conditions through appropriate mode selection and parameter optimization, ensuring consistent performance across varying market environments.
Market State Classification
The indicator incorporates advanced market state classification through ADX analysis, distinguishing between trending, ranging, and transitional market conditions. This classification system automatically adjusts signal sensitivity and filtering parameters based on current market characteristics, optimizing performance for prevailing conditions rather than applying static analytical approaches.
The volatility measurement system calculates current market activity levels as percentages, providing quantitative assessment of market energy and helping traders select appropriate operational modes. Institutional activity detection through volume analysis ensures signal generation aligns with professional market participation patterns.
Implementation Strategy Considerations
Successful implementation requires careful matching of operational modes to prevailing market conditions and individual trading objectives. Trending modes demonstrate optimal performance during directional markets with sustained momentum characteristics, while contrarian modes excel during range-bound or overextended market conditions where reversal probability increases.
The cloud filter configurations provide varying degrees of confirmation strength, with smoother settings reducing false signal occurrence at the expense of some responsiveness to price changes. Traders must balance signal quality against signal frequency based on their risk tolerance and available trading time, utilizing the comprehensive customization options to optimize performance for their specific requirements.
Multi-Timeframe Integration
The system provides seamless multi-timeframe analysis through the integrated dashboard, displaying trend alignment across multiple time horizons from five-minute through four-hour periods. This analysis helps traders understand broader market context and avoid conflicts between different temporal perspectives that could compromise trade outcomes.
Session analysis identifies current trading session characteristics, providing context for expected market behavior patterns and helping traders adjust their approach based on typical session volatility and participation levels. This geographic market awareness enhances strategic decision-making and improves timing for trade execution.
Advanced Visualization Features
The indicator includes sophisticated visualization capabilities through gradient candle coloring based on MACD analysis, providing immediate visual feedback on momentum strength and direction. This enhancement allows rapid market assessment without requiring detailed indicator analysis, improving efficiency for traders managing multiple instruments simultaneously.
The cloud visualization system uses color-coded fill areas to clearly indicate trend direction and strength, with automatic adaptation to selected operational modes. This visual clarity reduces analytical complexity while maintaining comprehensive market information display through professional chart presentation.
Performance Optimization Framework
The Fresh Algo V24 incorporates performance optimization features including signal strength classification, automatic parameter adjustment based on market conditions, and dynamic filtering that adapts to current volatility levels. These optimizations ensure consistent performance across varying market environments while maintaining signal quality standards.
The system automatically adjusts sensitivity levels based on selected operational modes, ensuring appropriate responsiveness for different trading approaches. This adaptive framework reduces the need for manual parameter adjustments while maintaining optimal performance characteristics for each operational configuration.
Conclusion
The Mutanabby_AI Fresh Algo V24 represents a comprehensive solution for professional trading analysis, combining multiple analytical approaches with advanced visualization and risk management capabilities. The system's strength lies in its adaptive multi-mode design and sophisticated filtering mechanisms, providing traders with versatile tools for various market conditions and trading styles.
Success with this system requires understanding the relationship between different operational modes and their optimal application scenarios. The comprehensive dashboard and alert system provide essential market context and trade management support, enabling systematic approach to market analysis while maintaining flexibility for individual trading preferences.
The indicator's sophisticated architecture and extensive customization options make it suitable for traders at all experience levels, from those seeking systematic signal generation to advanced practitioners requiring comprehensive market analysis tools. The multi-timeframe integration and adaptive filtering ensure consistent performance across diverse market conditions while providing clear guidelines for strategic implementation.
Mutanabby_AI __ OSC+ST+SQZMOMMutanabby_AI OSC+ST+SQZMOM: Multi-Component Trading Analysis Tool
Overview
The Mutanabby_AI OSC+ST+SQZMOM indicator combines three proven technical analysis components into a unified trading system, providing comprehensive market analysis through integrated oscillator signals, trend identification, and volatility assessment.
Core Components
Wave Trend Oscillator (OSC): Identifies overbought and oversold market conditions using exponential moving average calculations. Key threshold levels include overbought zones at 60 and 53, with oversold areas marked at -60 and -53. Crossover signals between the two oscillator lines generate entry opportunities, displayed as colored circles on the chart for easy identification.
Supertrend Indicator (ST): Determines overall market direction using Average True Range calculations with a 2.5 factor and 10-period ATR configuration. Green lines indicate confirmed uptrends while red lines signal downtrend conditions. The indicator automatically adapts to market volatility changes, providing reliable trend identification across different market environments.
Squeeze Momentum (SQZMOM): Compares Bollinger Bands with Keltner Channels to identify consolidation periods and potential breakout scenarios. Black squares indicate squeeze conditions representing low volatility periods, green triangles signal confirmed upward breakouts, and red triangles mark downward breakout confirmations.
Signal Generation Logic
Long Entry Conditions:
Green triangles from Squeeze Momentum component
Supertrend line transitioning to green
Bullish crossovers in Wave Trend Oscillator from oversold territory
Short Entry Conditions:
Red triangles from Squeeze Momentum component
Supertrend line transitioning to red
Bearish crossovers in Wave Trend Oscillator from overbought territory
Automated Risk Management
The indicator incorporates comprehensive risk management through ATR-based calculations. Stop losses are automatically positioned at 3x ATR distance from entry points, while three progressive take profit targets are established at 1x, 2x, and 3x ATR multiples respectively. All risk management levels are clearly displayed on the chart using colored lines and informative labels.
When trend direction changes, the system automatically clears previous risk levels and generates new calculations, ensuring all risk parameters remain current and relevant to existing market conditions.
Alert and Notification System
Comprehensive alert framework includes trend change notifications with complete trade setup details, squeeze release alerts for breakout opportunity identification, and trend weakness warnings for active position management. Alert messages contain specific trading pair information, timeframe specifications, and all relevant entry and exit level data.
Implementation Guidelines
Timeframe Selection: Higher timeframes including 4-hour and daily charts provide the most reliable signals for position trading strategies. One-hour charts demonstrate good performance for day trading applications, while 15-30 minute timeframes enable scalping approaches with enhanced risk management requirements.
Risk Management Integration: Limit individual trade risk to 1-2% of total capital using the automatically calculated stop loss levels for precise position sizing. Implement systematic profit-taking at each target level while adjusting stop loss positions to protect accumulated gains.
Market Volatility Adaptation: The indicator's ATR-based calculations automatically adjust to changing market volatility conditions. During high volatility periods, risk management levels appropriately widen, while low volatility conditions result in tighter risk parameters.
Optimization Techniques
Combine indicator signals with fundamental support and resistance level analysis for enhanced signal validation. Monitor volume patterns to confirm breakout strength, particularly when Squeeze Momentum signals develop. Maintain awareness of scheduled economic events that may influence market behavior independent of technical indicator signals.
The multi-component design provides internal signal confirmation through multiple alignment requirements, significantly reducing false signal occurrence while maintaining reasonable trade frequency for active trading strategies.
Technical Specifications
The Wave Trend Oscillator utilizes customizable channel length (default 10) and average length (default 21) parameters for optimal market sensitivity. Supertrend calculations employ ATR period of 10 with factor multiplier of 2.5 for balanced signal quality. Squeeze Momentum analysis uses Bollinger Band length of 20 periods with 2.0 multiplication factor, combined with Keltner Channel length of 20 periods and 1.5 multiplication factor.
Conclusion
The Mutanabby_AI OSC+ST+SQZMOM indicator provides a systematic approach to technical market analysis through the integration of proven oscillator, trend, and momentum components. Success requires thorough understanding of each element's functionality and disciplined implementation of proper risk management principles.
Practice with demo trading accounts before live implementation to develop familiarity with signal interpretation and trade management procedures. The indicator's systematic approach effectively reduces emotional decision-making while providing clear, objective guidelines for trade entry, management, and exit strategies across various market conditions.
Kumo no Nami Trend Strength Identifier T2[T69]🧠 Overview
Kumo no Nami is a custom trend strength indicator that combines Ichimoku cloud dynamics (Kumo) with wave momentum (Nami) to identify trend direction, reversals, squeezes, and breakouts using Z-Score analysis. It adapts to different modes (Ichimoku, MA, EMA) for a flexible interpretation of price structure tension vs. movement strength.
🔍 Core Logic
Kumo Width (Cloud Pressure): Measures the normalized spread (Z-Score) between two dynamic price levels (e.g., Senkou A-B or Base-Tenkan).
Nami Strength (Wave Energy): Measures how far current price dislocates from a recent range using Z-Score of the difference between close and Donchian/MA.
Z-Score Normalization: Ensures both metrics are statistically comparable, regardless of volatility regime.
Squeeze Detection: Identifies compression before potential volatility expansion.
Breakout/False Break: Detects whether movement is legitimate or noise.
Final Top/Bottom: Highlights a strong burst post-squeeze, often signaling exhaustion or trend climax.
⚙️ Features
🌀 Multiple Kumo Modes:
Kijun-Tenkan
Senkou A - B
SMA Fast - Slow
EMA Fast - Slow
🟨 Z-Score Based Squeeze Monitoring
🟥 Final Burst Alerts
🟩 Trend Continuation or Fake-out Detection
🎨 Dynamic Background Coloring for visual signal clarity
🔧 Configuration
📊 Inputs
Kumo Mode (kt, sab, sfs, efs) – Choose method to compute Kumo (Cloud) width.
Kumo Lookback – Lookback period for cloud Z-Score analysis.
Nami Lookback – Lookback period for wave dislocation measurement.
Squeeze Threshold – How low Z-Kumo must fall to signal potential squeeze.
Burst Thresholds:
Burst Kumo → Z-Kumo must rise above this to be considered bursting.
Burst Nami → Nami Strength threshold for final trend climax.
Ichimoku Config – Tenkan, Kijun, Senkou B, and displacement.
MA Config – For Fast/Slow variants, SMA/EMA lengths.
🧪 How It Works
Compute the Kumo Width depending on selected mode.
E.g., |Tenkan - Kijun| or |Senkou A - Senkou B|
Normalize this width with its Z-Score to get Z-Kumo Width.
Compute Nami Strength:
Z-Score of how far close deviates from a Donchian channel or moving average.
Evaluate signal logic based on the two:
📈 Behavior & Signals
Trend Range (Sideways Consolidation)
=>Z-Kumo < 0 and |Nami Strength| > 2
False Break (No meaningful price movement)
=>Z-Kumo < 1 and |Nami Strength| < 1
Squeeze Watch (Potential breakout loading)
=>Z-Kumo < Squeeze Threshold
Final Burst / Climax
=>Z-Kumo > 2.5 and |Nami Strength| > 3
Bullish Breakout
=>Z-Kumo > 1 and Nami Strength > 2 and not false break
Bearish Breakout
=>Z-Kumo > 1 and Nami Strength < -2 and not false break
Reversal Detection
Crossovers of Nami Strength across 0 (bull/bear) while not in squeeze
🧠 Advanced Concepts Used
Z-Score:
=>(value - mean) / standard deviation for detecting statistically significant moves.
Squeeze Principle:
=>Low volatility → potential buildup → expansion.
Price Dislocation (Wave Strength):
=>Measures how far current price is from its mean range.
=>Cloud Tension (Kumo Z-Score):
=>Reflects pressure or neutrality in the price structure.
Trend Confirmation:
=>Only if both metrics agree and no false break conditions are met.
Keltner Channels MTFKeltner Channels MTF | Adapted 🌌
Navigate the market’s wild waves with these Keltner Channels, a sleek spin on AlchimistOfCrypto’s Bollinger Bands! This Pine Script v6 indicator tracks price action like a radar, highlighting trends with scientific precision. 🧪
Key Features:
Customizable Channels: Adjust period and multiplier to map market volatility, signaling potential reversals when prices hit the upper or lower bands. 📈
MA Options: Switch between Exponential or Simple Moving Average for trend clarity. ⚙️
Band Styles: Select Average True Range, True Range, or Range to define volatility edges. 📏
Glow Effect: Illuminate bands with 8 vibrant themes (Neon, Grayscale, etc.) for visual pop. ✨
Trend Signals: Spot bullish/bearish shifts with glowing circles, flagging momentum changes. 💡
Alerts: Catch price breakouts or trend reversals at band edges, warning of potential market U-turns. 🚨
Perfect for traders decoding market trends with a touch of cosmic style! 🌠
Price Exhaustion Envelope [BackQuant]Price Exhaustion Envelope
Visual preview of the bands:
What it is
The Price Exhaustion Envelope (PEE) is a multi‑factor overextension detector wrapped inside a dynamic envelope framework. It measures how “tired” a move is by blending price stretch, volume surges, momentum and acceleration, plus optional RSI divergence. The result is a composite exhaustion score that drives both on‑chart signals and the adaptive width of three optional envelope bands around a smoothed baseline. When the score spikes above or below your chosen threshold, the script can flag exhaustion, paint candles, tint the background and fire alerts.
How it works under the hood
Exhaustion score
Price component: distance of close from its mean in standard deviation units.
Volume component: normalized volume pressure that highlights unusual participation.
Momentum component: rate of change and acceleration of price, scaled by their own volatility.
RSI divergence (optional): bullish and bearish divergences gently push the score lower or higher.
Mode control: choose Price, Volume, Momentum or Composite. Composite averages the main pieces for a balanced view.
Energy scale (0 to 100)
The composite score is pushed through a logistic transform to create an “energy” value. High energy (above 70 to 80) signals a move that may be running hot, while very low energy (below 20 to 30) points to exhaustion on the downside.
Envelope engine
Baseline: EMA of price over the main lookback length.
Width: base width is standard deviation times a multiplier.
Type selector:
• Static keeps the width fixed.
• Dynamic expands width in proportion to the absolute exhaustion score.
• Adaptive links width to the energy reading so bands breathe with market “heat.”
Smoothing: a short EMA on the width reduces jitter and keeps bands pleasant to trade around.
Band architecture
You can toggle up to three symmetric bands on each side of the baseline. They default to 1.0, 1.6 and 2.2 multiples of the smoothed width. Soft transparent fills create a layered thermograph of extension. The outermost band often maps to true blow‑off extremes.
On‑chart elements
Baseline line that flips color in real time depending on where price sits.
Up to three upper and lower bands with progressive opacity.
Triangle markers at fresh exhaustion triggers.
Tiny warning glyphs at extreme upper or lower breaches.
Optional bar coloring to visually tag exhausted candles.
Background halo when energy > 80 or < 20 for instant context.
A compact info table showing State, Score, Energy, Momentum score and where price sits inside the envelope (percent).
How to use it in trading
Mean reversion plays
When price pierces the outer band and an exhaustion marker prints, look for reversal candles or lower‑timeframe confirmation to fade the move back toward the baseline.
For conservative entries, wait for the composite score to roll back under the threshold or for energy to drop from extreme to neutral.
Set stops just beyond the extreme levels (use extreme_upper and extreme_lower as natural invalidation points). Targets can be the baseline or the opposite inner band.
Trend continuation with smart pullbacks
In strong trends, the first tag of Band 1 or Band 2 against the dominant direction often offers low‑risk continuation entries. Use energy readings: if energy is low on a pullback during an uptrend, a bounce is more likely.
Combine with RSI divergence: hidden bullish divergence near a lower band in an uptrend can be a powerful confirmation.
Breakout filtering
A breakout that occurs while the composite score is still moderate (not exhausted) has a higher chance of follow‑through. Skip signals when energy is already above 80 and price is punching the outer band, as the move may be late.
Watch env_position (Envelope %) in the table. Breakouts near 40 to 60 percent of the envelope are “healthy,” while those at 95 percent are stretched.
Scaling out and risk control
Use exhaustion alerts to trim positions into strength or weakness.
Trail stops just outside Band 2 or Band 3 to stay in trends while letting the envelope expand in volatile phases.
Multi‑timeframe confluence
Run the script on a higher timeframe to locate exhaustion context, then drill down to a lower timeframe for entries.
Opposite signals across timeframes (daily exhaustion vs. 5‑minute breakout) warn you to reduce size or tighten management.
Key inputs to experiment with
Lookback Period: larger values smooth the score and envelope, ideal for swing trading. Shorter values make it reactive for scalps.
Exhaustion Threshold: raise above 2.0 in choppy assets to cut noise, drop to 1.5 for smooth FX pairs.
Envelope Type: Dynamic is great for crypto spikes, Adaptive shines in stocks where volume and volatility wave together.
RSI Divergence: turn off if you prefer a pure price/volume model or if divergence floods the score in your asset.
Alert set included
Fresh upper exhaustion
Fresh lower exhaustion
Extreme upper breach
Extreme lower breach
RSI bearish divergence
RSI bullish divergence
Hook these to TradingView notifications so you get pinged the moment a move hits exhaustion.
Best practices
Always pair exhaustion signals with structure. Support and resistance, liquidity pools and session opens matter.
Avoid blindly shorting every upper signal in a roaring bull market. Let the envelope type help you filter.
Use the table to sanity‑check: a very high score but mid‑range env_position means the band may still be wide enough to absorb more movement.
Backtest threshold combinations on your instrument. Different tickers carry different volatility fingerprints.
Final note
Price Exhaustion Envelope is a flexible framework, not a turnkey system. It excels as a context layer that tells you when the crowd is pressing too hard or when a move still has fuel. Combine it with sound execution tactics, risk limits and market awareness. Trade safe and let the envelope breathe with the market.
Trigonometric StochasticTrigonometric Stochastic - Mathematical Smoothing Oscillator
Overview
A revolutionary approach to stochastic oscillation using sine wave mathematical smoothing. This indicator transforms traditional stochastic calculations through trigonometric functions, creating an ultra-smooth oscillator that reduces noise while maintaining sensitivity to price changes.
Mathematical Foundation
Unlike standard stochastic oscillators, this version applies sine wave smoothing:
• Raw Stochastic: (close - lowest_low) / (highest_high - lowest_low) × 100
• Trigonometric Smoothing: 50 + 50 × sin(2π × raw_stochastic / 100)
• Result: Naturally smooth oscillator with mathematical precision
Key Features
Advanced Smoothing Technology
• Sine Wave Filter: Eliminates choppy movements while preserving signal integrity
• Natural Boundaries: Mathematically constrained between 0-100
• Reduced False Signals: Trigonometric smoothing filters market noise effectively
Traditional Stochastic Levels
• Overbought Zone: 80 level (dashed line)
• Oversold Zone: 20 level (dashed line)
• Midline: 50 level (dotted line) - equilibrium point
• Visual Clarity: Clean oscillator panel with clear level markings
Smart Signal Generation
• Anti-Repaint Logic: Uses confirmed previous bar values
• Buy Signals: Generated when crossing above 30 from oversold territory
• Sell Signals: Generated when crossing below 70 from overbought territory
• Crossover Detection: Precise entry/exit timing
Professional Presentation
• Separate Panel: Dedicated oscillator window (overlay=false)
• Price Format: Formatted as price indicator with 2-decimal precision
• Theme Adaptive: Automatically matches your chart color scheme
Parameters
• Cycle Length (5-200): Period for highest/lowest calculations
- Shorter periods = more sensitive, more signals
- Longer periods = smoother, fewer but stronger signals
Trading Applications
Momentum Analysis
• Overbought/Oversold: Clear visual identification of extreme levels
• Momentum Shifts: Early detection of momentum changes
• Trend Strength: Monitor oscillator position relative to midline
Signal Trading
• Long Entries: Buy when crossing above 30 (oversold bounce)
• Short Entries: Sell when crossing below 70 (overbought rejection)
• Confirmation Tool: Use with trend indicators for higher probability trades
Divergence Detection
• Bullish Divergence: Price makes lower lows, oscillator makes higher lows
• Bearish Divergence: Price makes higher highs, oscillator makes lower highs
• Early Warning: Spot potential trend reversals before they occur
Trading Strategies
Scalping (5-15min timeframes)
• Use cycle length 10-14 for quick signals
• Focus on 20/80 level bounces
• Combine with price action confirmation
Swing Trading (1H-4H timeframes)
• Use cycle length 20-30 for reliable signals
• Wait for clear crossovers with momentum
• Monitor divergences for reversal setups
Position Trading (Daily+ timeframes)
• Use cycle length 50+ for major signals
• Focus on extreme readings (below 10, above 90)
• Combine with fundamental analysis
Advantages Over Standard Stochastic
1. Smoother Action: Sine wave smoothing reduces whipsaws
2. Mathematical Precision: Trigonometric functions provide consistent behavior
3. Maintained Sensitivity: Smoothing doesn't compromise signal quality
4. Reduced Noise: Cleaner signals in volatile markets
5. Visual Appeal: More aesthetically pleasing oscillator movement
Best Practices
• Market Context: Consider overall trend direction
• Multiple Timeframe: Confirm signals on higher timeframes
• Risk Management: Always use proper position sizing
• Backtesting: Test parameters on your preferred instruments
• Combination: Works excellently with trend-following indicators
Built-in Alerts
• Buy Alert: Trigonometric stochastic oversold crossover
• Sell Alert: Trigonometric stochastic overbought crossunder
Technical Specifications
• Pine Script Version: v6
• Panel: Separate oscillator window
• Format: Price indicator with 2-decimal precision
• Performance: Optimized for all timeframes
• Compatibility: Works with all instruments
Free and open-source indicator. Modify, improve, and share with the community!
Educational Value: Perfect for traders wanting to understand how mathematical smoothing improves oscillators and trigonometric applications in technical analysis.
Triple Momentum Core v1🧠 Technical Structure:
Triple Momentum Core analyzes the underlying wave of price movement through a three-stage system:
1. 🔵 Follow Line – The First Spark of Momentum:
Constructed using Bollinger Bands and ATR, this line detects the very first signs of directional price expansion. It gently whispers when the market begins stretching with force in one direction.
2. 🟢 SuperTrend – Confirmation and Directional Validation:
After the initial move, SuperTrend acts as the second checkpoint — validating whether the price action is evolving into a genuine trend or fading out. It confirms whether the impulse has the strength to sustain.
3. 🔴 PMax – Core Trend & Structural Anchor:
Based on Moving Average and ATR logic, PMax tracks the heartbeat of the trend. It serves as a dynamic structural boundary — critical for identifying trend continuation and managing risk.
4. 🟡 PMax MA Line – Smooth Trend Pulse & Adaptive Guide:
This yellow moving average line within the PMax system softly follows the overall trend flow, without reacting to sharp price noise. It acts as a balanced, stable guide to gauge the solidity of the trend’s body structure.
(If you prefer a cleaner view without any moving average lines, you can disable it from the settings.)
🧠 Technical Structure:
Triple Momentum Core analyzes the underlying wave of price movement through a three-stage system:
1. 🔵 Follow Line – The First Spark of Momentum:
Constructed using Bollinger Bands and ATR, this line detects the very first signs of directional price expansion. It gently whispers when the market begins stretching with force in one direction.
2. 🟢 SuperTrend – Confirmation and Directional Validation:
After the initial move, SuperTrend acts as the second checkpoint — validating whether the price action is evolving into a genuine trend or fading out. It confirms whether the impulse has the strength to sustain.
3. 🔴 PMax – Core Trend & Structural Anchor:
Based on Moving Average and ATR logic, PMax tracks the heartbeat of the trend. It serves as a dynamic structural boundary — critical for identifying trend continuation and managing risk.
4. 🟡 PMax MA Line – Smooth Trend Pulse & Adaptive Guide:
This yellow moving average line within the PMax system softly follows the overall trend flow, without reacting to sharp price noise. It acts as a balanced, stable guide to gauge the solidity of the trend’s body structure.
(If you prefer a cleaner view without any moving average lines, you can disable it from the settings.)
💡 Why “Triple Momentum Core”?
Because this indicator doesn’t just detect movement — it breaks it down into its essential phases:
Ignition, validation, and confirmation.
Each layer captures a unique and essential part of price behavior:
The first reaction (Follow Line) ignites the initial spark.
The second reaction (SuperTrend) confirms whether that spark will become a real trend.
The third and final layer (PMax) structurally anchors and follows that trend.
That’s why we call it Triple Momentum Core:
A synchronized 3-engine momentum system working in harmony to capture the lifecycle of a trend — from spark to structure.
SCPEM - Socionomic Crypto Peak Model (0-85 Scale)SCPEM Indicator Overview
The SCPEM (Socionomic Crypto Peak Evaluation Model) indicator is a TradingView tool designed to approximate cycle peaks in cryptocurrency markets using socionomic theory, which links market behavior to collective social mood. It generates a score from 0-85 (where 85 signals extreme euphoria and high reversal risk) and plots it as a blue line on the chart for visual backtesting and real-time analysis.
#### How It Works
The indicator uses technical proxies to estimate social mood factors, as Pine Script cannot fetch external data like sentiment indices or social media directly. It calculates a weighted composite score on each bar:
- Proxies derive from price, volume, and volatility data.
- The raw sum of factor scores (max ~28) is normalized to 0-85.
- The score updates historically for backtesting, showing mood progression over time.
- Alerts trigger if the score exceeds 60, indicating high peak probability.
Users can adjust inputs (e.g., lengths for RSI or pivots) to fine-tune for different assets or timeframes.
Metrics Used (Technical Proxies)
Crypto-Specific Sentiment
Approximated by RSI (overbought levels indicate greed).
Social Media Euphoria
Based on volume relative to its SMA (spikes suggest herding/FOMO).
Broader Social Mood Proxies
Derived from ATR volatility (high values signal uncertain/mixed mood).
Search and Cultural Interest Proxied by OBV trend (rising accumulation implies growing interest).
Socionomic Wildcard
Uses Bollinger Band width (expansion for positive mood, contraction for negative).
Elliott Wave Position
Counts recent price pivots (more swings indicate later wave stages and exhaustion).
N-Pattern Detector (Advanced Logic)Introduction
The N-Pattern Detector (Advanced Logic) is a powerful Pine Script-based tool designed to identify a specific price structure known as the "N-pattern", which often indicates trend continuation or potential breakout points in the market. This pattern combines zigzag pivot logic, retracement filters, volume confirmation, and trend alignment, offering high-probability trading signals.
It is ideal for traders who want to automate pattern detection while applying smart filters to reduce false signals in various markets — including stocks, forex, crypto, and indices.
What is the N-Pattern?
The N-pattern is a 3-leg price formation consisting of points A-B-C-D. It typically follows this structure:
Bullish N-Pattern:
A → Low Pivot
B → Higher High (Impulse)
C → Higher Low (Retracement)
D → Breakout above B (Confirmation)
Bearish N-Pattern:
A → High Pivot
B → Lower Low (Impulse)
C → Lower High (Retracement)
D → Breakdown below B (Confirmation)
The pattern essentially reflects a trend–pullback–breakout structure, making it suitable for continuation trades.
Key Features
1. Intelligent ZigZag Pivot Detection
Uses pivot highs/lows to define key swing points (A, B, C).
Adjustable ZigZag depth to control pattern sensitivity.
Filters noise and avoids false signals in volatile markets.
2. Retracement Validation
Validates the B→C leg as a proper pullback using Fibonacci-based thresholds.
User-defined min and max retracement settings (e.g., 38.2% to 78.6% of A→B leg).
3. Trend Filter via EMA
Filters patterns based on trend direction using a customizable EMA (e.g., 200 EMA).
Only detects bullish patterns above EMA and bearish patterns below EMA (optional).
4. Volume Confirmation
Ensures that impulse legs (A→B, C→D) are supported by stronger volume than the correction leg (B→C).
Adds another layer of confirmation and reliability to detected patterns.
5. Target Projections
Automatically draws 100% A→B projected target from point C.
Optional Fibonacci extensions at 1.272 and 1.618 levels for take-profit planning.
Visually plotted on the chart with colored dashed/dotted lines.
6. Clear Visuals & Labels
Connects all pattern points with colored lines.
Clearly labels points A, B, C, D on the chart.
Uses customizable colors for bullish and bearish patterns.
Includes real-time alerts when a valid pattern is detected.
How to Use It
Add to Chart
Apply the indicator to any chart and time frame. It works across all asset classes.
Adjust Inputs (Optional)
Set ZigZag Depth to control pivot detection sensitivity.
Define Min/Max Retracement levels to match your trading style.
Enable or disable Trend and Volume filters for cleaner signals.
Customize EMA length (default: 200) for trend validation.
Wait for Pattern Confirmation
The indicator constantly scans for valid N-patterns.
A pattern is confirmed only after point D forms (breakout or breakdown).
You’ll see the full pattern drawn with target levels.
Set Alerts
Alerts trigger automatically on confirmation of a bullish or bearish pattern.
You can customize these in TradingView’s alerts panel.
Initial Balance Wave MapThis indicator visualizes the Initial Balance (IB) range for any session, marking the first hour's high and low. It includes optional midpoints, extensions (e.g. 1.5x IB, 2x IB), and customizable time windows. Additional features allow users to display session open, high, low, close, and VWAP reference points. Designed to support price action and session structure analysis, it adapts to various global futures and FX market opens. All display elements are optional and fully configurable.
This updated indicator builds upon the open-source foundation by @noop-noop with enhancements and user-facing labels tailored for Auction Market Theory, scalping, and structure-based trade setups.
Key updated Featured: Multiple previous day's IB levels carry forward into the current day's chart, as opposed to just the previous day's levels carrying forward to the new IB time.
🙌 Credits:
This script builds upon the excellent open-source work by @noop-noop. Original script available here .
Alt Szn Oracle - Institutional GradeThe Alt Szn Oracle is a macro-level indicator built to help traders front-run altseason by tracking liquidity, dominance rotation, sentiment, and capital flows—all in one signal. It’s designed for those who don’t just chase pumps, but want to understand when the tide is turning and why. This tool doesn't predict specific coin breakouts—it tells you when the market as a whole is gearing up to rotate into higher beta assets like altcoins, including memes and microcaps.
The index consolidates ten macro inputs into a normalized, smoothed score from 0–100. These include Bitcoin and Ethereum dominance, ETH/BTC, altcoin market cap (Total3), relative volume flows, and stablecoin supply (USDT, USDC, DAI)—which act as proxies for risk-on appetite and dry powder entering the system. It also incorporates manually updated sentiment metrics from Google Trends and the Fear & Greed Index, giving it a behavioral edge that most indicators lack.
The logic is simple but powerful: when BTC dominance is falling, ETH/BTC is rising, altcoin volume increases relative to BTC/ETH, and stablecoins start moving—you're likely in the early innings of rotation. The index is also filtered through a volatility threshold and smoothed with an EMA to eliminate chop and fakeouts.
Use this indicator on macro charts like TOTAL3, TOTAL2, or ETHBTC to gauge market health, or overlay it on specific coins like PEPE, DOGE, or SOL to confirm if the tide is in your favor. Interpreting the score is straightforward: readings above 80 suggest euphoria and signal it’s time to de-risk, 60–80 indicates expansion and confirms altseason is underway, 40–60 is neutral, and 20–40 is a capitulation zone where smart money accumulates.
What sets this apart is that it doesn’t just track price—it reflects the flow of capital, the positioning of liquidity, and the sentiment of the crowd. Most altseason indicators are lagging, overfitted, or too simplistic. This one is modular, forward-looking, and grounded in real capital rotation theory.
If you're a trader who wants to time the cycle, not guess it, this is your tool. Refine it, fork it, or expand it to your niche—DeFi, NFTs, meme coins, or L1s. It’s a framework for reading the macro winds, not a signal service. Use it with discipline, and you’ll catch the wave while others drown in noise.
Golden Ratio Trend Persistence [EWT]Golden Ratio Trend Persistence
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Overview
The Golden Ratio Trend Persistence is a dynamic tool designed to identify the strength and persistence of market trends. It operates on a simple yet powerful premise: a trend is likely to continue as long as it doesn't retrace beyond the key Fibonacci golden ratio of 61.8%.
This indicator automatically identifies the most significant swing high or low and plots a single, dynamic line representing the 61.8% retracement level of the current move. This line acts as a "line in the sand" for the prevailing trend. The background color also changes to provide an immediate visual cue of the current market direction.
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The Power of the Golden Ratio (61.8%)
The golden ratio (ϕ≈1.618) and its inverse (0.618, or 61.8%) are fundamental mathematical constants that appear throughout nature, art, and science, often representing harmony and structure. In financial markets, this ratio is a cornerstone of Fibonacci analysis and is considered one of the most critical levels for price retracements.
Market movements are not linear; they progress in waves of impulse and correction. The 61.8% level often acts as the ultimate point of support or resistance. A trend that can hold this level demonstrates underlying strength and is likely to persist. A breach of this level, however, suggests a fundamental shift in market sentiment and a potential reversal.
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How to Use This Indicator
This indicator is designed for clarity and ease of use.
Identifying the Trend : The visual cues make the current trend instantly recognizable.
A teal line with a teal background signifies a bullish trend. The line acts as dynamic support.
A maroon line with a maroon background signifies a bearish trend. The line acts as dynamic resistance.
Confirming Trend Persistence : As long as the price respects the plotted level, the trend is considered intact.
In an uptrend, prices should remain above the teal line. The indicator will automatically adjust its anchor to new, higher lows, causing the support line to trail the price.
In a downtrend, prices should remain below the maroon line.
Spotting Trend Reversals : The primary signal is a trend reversal, which occurs when the price closes decisively beyond the plotted level.
Potential Sell Signal : When the price closes below the teal support line, it indicates that buying pressure has failed, and the uptrend is likely over.
Potential Buy Signal : When the price closes above the maroon resistance line, it indicates that selling pressure has subsided, and a new uptrend may be starting.
Think of this tool as an intelligent, adaptive trailing stop that is based on market structure and the time-tested principles of Fibonacci analysis.
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Input Parameters
You can customize the indicator's sensitivity through the following inputs in the settings menu:
Pivot Lookback Left : This number defines how many bars to the left of a candle must be lower (for a pivot high) or higher (for a pivot low) to identify a potential swing point. A higher value will result in fewer, but more significant, pivots being detected.
Pivot Lookback Right : This defines the number of bars that must close to the right before a swing point is confirmed. This parameter prevents the indicator from repainting. A higher value increases confirmation strength but also adds a slight lag.
Fibonacci Ratio : While the default is the golden ratio (0.618), you can adjust this to other key Fibonacci levels, such as 0.5 (50%) or 0.382 (38.2%), to test for different levels of trend persistence.
Adjusting these parameters allows you to fine-tune the indicator for different assets, timeframes, and trading styles, from short-term scalping to long-term trend following.
Quantum Harmonic Oscillator Overlay🧪 Quantum Harmonic Oscillator Overlay
A visual model of price behavior using quantum harmonic oscillation principles
📜 Indicator Overview
The Quantum Harmonic Oscillator Overlay applies concepts from both classical physics (harmonic motion) and quantum mechanics (energy states) to model and visualize how price orbits around a central trend line. It overlays a Linear Regression line (representing the “mean position” or ground state of price) and calculates surrounding energy levels (σ-zones) akin to quantum shells that price can "jump" between.
This indicator is particularly useful for visualizing mean reversion, volatility compression/expansion, and momentum-driven price breakthroughs.
🧠 Core Concepts
Linear Regression Line (LSR): This is the calculated center of gravity or equilibrium path of price over a user-defined period. Think of it like the lowest energy state or central axis around which price vibrates.
Standard Deviation Zones (σ-levels):
1σ: The majority of normal price activity; within this range, price tends to fluctuate if in balance.
2σ: Indicates volatility or possible breakout pressure.
3σ: Represents extreme movement — a phase shift in energy, potentially leading to reversal or continuation with higher momentum.
Quantum Analogy: Just like in a quantum harmonic oscillator, particles (here, prices) move probabilistically between discrete energy states. The further the price moves from the center, the more "energy" (momentum, volume, volatility) is implied.
⚙️ Input Parameters
Setting Description
Linear Regression Length The number of bars used to calculate the regression trend (default 100). Affects the central path and responsiveness.
σ Multipliers (1σ, 2σ, 3σ) Determine how far each band is from the regression line. Adjusting these can highlight different price behaviors.
Show Energy Level Zones Toggle visibility of the colored bands around the regression line.
Show LSR Center Line Toggles visibility of the white Linear Regression line itself.
🎨 Visual Components
Color Zone Interpretation
✅ Green ±1σ Normal oscillation / mean reversion area. Ideal for range-bound strategies.
🟧 Orange ±2σ Warning zone; price may be gaining momentum or volatility.
🔴 Red ±3σ High-momentum state or anomaly. These regions may imply trend exhaustion, reversals, or breakouts.
White Line: The LSR — the average trajectory of the price movement.
Pink Dots: Appear when price exceeds Zone 3 (outside ±3σ) — a signal of extreme behavior or a possible regime shift.
📈 How to Use This Indicator
1. Detect Overextensions
When price touches or breaches the 3σ zone, it is likely overextended. This can be used to anticipate potential snapbacks or strong breakout trends.
2. Identify Mean Reversion Trades
If price exits the 2σ or 3σ zones and returns toward the center line, this signals a likely mean reversion setup.
3. Volatility Compression or Expansion
Flat zones between σ levels suggest calm markets; widening bands suggest expanding volatility.
4. Use with Confirmation Tools
Combine with momentum oscillators (MACD, RSI) or volume-based signals to confirm reversals or continuation outside Zone 3.
🔮 Philosophical Note
This indicator embodies the metaphor that the market behaves like a quantum oscillator — price particles exist in a probabilistic field and jump between discrete zones of volatility and energy. Tracking these transitions allows the trader to see price behavior as rhythmic, wave-like, and multidimensional rather than purely linear.
Chaithanya Tattva Volume Zones📜 "Chaitanya Tattva" Volume Zones:-
A Sacred Framework of Supply, Demand & Market Energy
In the world of financial markets, price is said to reflect all information. But the true pulse of the market — its life force, its intent, and its moment of truth — is most vividly expressed not in price itself, but in volume.
Chaitanya Tattva Volume Zones is a spiritually inspired volume-based tool that transforms your chart into a canvas of market consciousness, revealing moments where supply and demand engage in visible energetic spikes. These moments are often disguised as ordinary candles, but with this tool, you uncover zones of intent — footprints left by the market’s deeper intelligence.
🌟 Why “Chaitanya Tattva”?
Chaitanya (चैतन्य) is a Sanskrit word meaning consciousness, awareness, or the spark of life energy. It is that which animates — the subtle intelligence behind all movement.
Tattva (तत्त्व) refers to essence, truth, or the underlying principle of a thing. In classical yogic philosophy, the tattvas are the elemental building blocks of reality.
Together, Chaitanya Tattva represents the conscious essence — the living pulse that animates the market through volume surges and imbalances.
This tool is not just a technical indicator — it is a spiritual observation device that aligns with the rhythm of volume and price action. It doesn't predict the market. It reveals when the market has already spoken — loudly, clearly, and energetically.
📈 What Does the Tool Do?
Chaitanya Tattva Volume Zones identifies exceptional volume spikes within the recent price history and visually marks the areas where market intent has been most active.
Specifically, the tool:
Scans for volume spikes that exceed all the volume of the last N bars (default is 20)
Confirms whether the spike happened on a bullish candle (close > open) or bearish candle (close < open)
For a bullish spike, it marks a Supply Zone — the area between the high and close of the candle
For a bearish spike, it marks a Demand Zone — the area between the low and close
Visually paints these zones with soft translucent boxes (red for supply, green for demand) that extend forward across multiple bars
🧘♂️ The Spiritual Framework
🔴 Supply = "Agni" — The Fire of Expansion
When a bullish candle erupts with historically high volume, it symbolizes the fire (Agni) of market optimism and upward expansion. It means that buyers have absorbed available supply at that level and established dominance — but such fire may also signal exhaustion, making it a potential supply barrier if price returns.
These Supply Zones are areas where:
Sellers are likely to re-engage
Smart money may be unloading
Future resistance can be anticipated
But unlike traditional indicators, this tool doesn’t guess. It reacts only to a clear volume-based event — when market energy surges — and locks in that awareness through zone marking.
🟢 Demand = "Prithvi" — The Grounding of Price
On the other hand, a bearish candle with extremely high volume represents the Earth (Prithvi) — grounding the price with firm hands. A strong volume drop often means buyers are stepping in, absorbing the selling pressure.
These Demand Zones are areas where:
Buying interest is proven
Market memory is stored
Future support can be expected
By respecting these zones, you're aligning your trading with natural market boundaries — not theoretical ones.
🧠 How Is It Different from Regular Volume Tools?
While most volume indicators show bars on a lower panel, they leave interpretation up to the trader. “High” or “low” becomes subjective.
Chaitanya Tattva Volume Zones is different:
It quantifies "spike": a bar must exceed all previous N volumes
It qualifies the intent: was the spike bullish or bearish?
It marks zones on the price chart: no need to guess levels
It preserves market memory: the zones persist visually for easy reference
In essence, this tool doesn’t just report volume — it interprets volume’s context and visually encodes it into the chart.
🧘 How to Use
1. Support/Resistance Mapping
Use the tool to understand where volume proved itself. If price revisits a red zone, expect possible rejection (resistance). If price revisits a green zone, expect possible absorption (support).
2. Entry Triggers
You may enter:
Long near demand zones if bullish confirmation appears
Short near supply zones if bearish confirmation appears
3. Stop Placement
Stops can be placed just beyond the zone boundary to align with areas where smart money historically defended.
4. Breakout Confidence
When price breaks through one of these zones with momentum, it often signals a new energetic wave — the old balance has been overcome.
🔔 Key Features
Volume spike detection across any timeframe
Clear visual zones — no clutter, no lag
Highly customizable: zone width, volume lookback, colors
Philosophy-aligned with supply and demand theory, Wyckoff, and Order Flow
🌌 A Metaphysical View of Volume
In yogic science, volume is akin to Prana — life-force energy. A market is not moved by price alone but by intent, force, and participation — all encoded in volume.
Just as a human body pulses with blood when action intensifies, the market pulses with volume when institutional decisions are made.
These pulses become sacred footprints — and Chaitanya Tattva Volume Zones helps you walk mindfully among them.
🔮 Final Thoughts
In a sea of indicators that shout at you with every tick, Chaitanya Tattva is calm. It speaks only when energy concentrates, only when the market sends a signal born of intent.
It doesn’t predict.
It doesn’t repaint.
It simply shows the truth, when the truth becomes undeniable.
Like a sage that speaks only when needed, it waits for volume to prove itself — then draws a memory into space, a zone where traders can re-align their actions with what the market has already honored.
Use it not just to trade —
But to listen.
To observe.
To follow the Chaitanya — the conscious pulse of the market’s own breath.
