Fractal Quad Components8 Fractal Resonance Component indicators on a chart eats up LOTS of vertical space, so we're providing this Fractal Quad Components script to group 4 components a bit more compactly (eliminating the margin whitespace between indicator rows).
To view 8 components you'll need to add a second instance of this script to your chart and set its Base Timescale Multiplier to 16. Then grab the dividers to stretch both instances to a good viewing height.
One disadvantage of this grouping method is that to read off the x2, x4, and x8 lead and lag line values, you'll need to mentally add 200, 400 or 600 respectively.
We also replaced the "Extreme" > +-100% black crosses (+) with more subtle purple circle outlines. These extreme crosses are often (but not always) too early to be a major reversal so it's best not to overemphasize them.
Significant crosses (> +-75%) are still highlighted with black circle outlines, and are the most likely to be major reversals for buy/sell.
Note how the 30-minute oscillator (2nd row) showed the cleanest (black-outlined) reversals on the S&P for the last week of 2016, with just a bit more profit-eating lag than the 15-minute oscillator above.
ค้นหาในสคริปต์สำหรับ "wave"
MACD MultiTimeFrame 1h4h1D [Fantastic Fox]Please insert the indicator into 1h time-frame, otherwise you need to change the lengths' inputs.
When there are tops for two of the MACDs and they are near and close* to each other, there is a big opportunity of a "Major Top" for the security, and vice versa for "Major Bottom".
This indicator can be used for tracing multi time-frame divergence. Also, it could help traders to identify the waves of Elliott Wave, and as a signal for confirmation of an impulse after a correction or retracement.
* They should be on top of each others head, not crossing each other. not necessarily touching, but not so far from each other.
Ehlers Smoothed Stochastic & RSI with Roofing FiltersRoofing filters, first discussed by Mr.John Ehlers, act as a passband, filtering out unwanted noise from market data and accentuating turning points.
I have included 2 indicators with filters enabled. Both support double smoothing via options page. All the parameters are configurable.
Info on Roofing Filter and Ehlers Super Smoother:
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The Ehlers' Roofing Filter is an expansion on Ehlers Super Smoother Filter, both being smoothing techniques based on analog filters. This filter aims at reducing noise in price data.
In Super Smoother Filter, regardless of the time frame used, all waves having cycles of less than 10 bars are considered noise (customizable via options page). The Roofing Filter uses this principle, however, it also creates a so-called "roof" by eliminating wave components having cycles greater than 48 bars which are perceived as "spectral dilation". Thus, the filter only passes those spectral components whose periods are between 10 and 48 bars. This technique noticeably reduces indicator lag and also helps assess turning points more accurately.
More info:
- Spectral dilation paper: www.mesasoftware.com
- John Ehlers presentation: www.youtube.com
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If you want to use RSI %B and Bandwidth, follow this guide to "Make mine" this chart and get access to the source:
drive.google.com
For the complete list of my indicators, check this post:
Squeeze Momentum Indicator [LazyBear]
Fixed a typo in the code where BB multiplier was stuck at 1.5. Thanks @ucsgears for bringing it to my notice.
Updated source: pastebin.com
Use the updated source instead of the what TV shows below.
This is a derivative of John Carter's "TTM Squeeze" volatility indicator, as discussed in his book "Mastering the Trade" (chapter 11).
Black crosses on the midline show that the market just entered a squeeze (Bollinger Bands are with in Keltner Channel). This signifies low volatility, market preparing itself for an explosive move (up or down). Gray crosses signify "Squeeze release".
Mr.Carter suggests waiting till the first gray after a black cross, and taking a position in the direction of the momentum (for ex., if momentum value is above zero, go long). Exit the position when the momentum changes (increase or decrease --- signified by a color change). My (limited) experience with this shows, an additional indicator like ADX / WaveTrend, is needed to not miss good entry points. Also, Mr.Carter uses simple momentum indicator, while I have used a different method (linreg based) to plot the histogram.
More info:
- Book: Mastering The Trade by John F Carter
List of all my indicators:
Trend Following Reflectometry🧭 Trend Following Reflectometry (TFR)
Author: Stef Jonker
Version: Pine Script® v6
The Trend Following Reflectometry (TFR) indicator translates market behavior into the language of impedance and signal reflection theory, providing a unique way to measure trend strength, stability, and purity.
🧩 Summary
Trend Following Reflectometry acts as a trend-quality meter, helping traders identify when a trend is strong, efficient, and worth following — or when the market is too noisy to trust.
It blends physics-inspired logic with practical trading insight, offering both a directional oscillator and a trend stability filter in one tool.
⚙️ Concept
Inspired by electrical impedance matching, this tool compares the market’s characteristic impedance (Z₀) — its natural volatility-to-price behavior — with the load impedance (Zₗ), representing current trend momentum.
The interaction between these two produces a reflection coefficient (Gamma) and a VSWR ratio, which reveal how efficiently market trends are transmitting energy (moving smoothly) versus reflecting noise (becoming unstable).
📊 Core Components
Z₀ (Characteristic Impedance): Market baseline, derived from ATR and SMA.
Zₗ (Load Impedance): Trend momentum based on fast and slow EMAs.
Γ (Gamma – Reflection Coefficient): Measures the mismatch between Z₀ and Zₗ.
VSWR (Voltage Standing Wave Ratio): Quantifies trend purity — lower = cleaner trend.
Impedance Oscillator: Combines momentum and reflection to produce directional bias.
⚡ Gamma & VSWR Interpretation
Gamma (Γ) represents the reflection coefficient — how much of the market’s trend energy is being reflected instead of transmitted.
When Gamma is low, the market trend is smooth and efficient, moving with little resistance.
When Gamma is high, the market becomes unstable or overextended, signaling potential turbulence, exhaustion, or reversal pressure.
VSWR (Voltage Standing Wave Ratio) measures trend purity — how clean or distorted the current trend is.
A low VSWR indicates a well-aligned, steady trend that’s likely to continue smoothly.
A high VSWR suggests an unbalanced or noisy market, where trends may struggle to sustain or could soon reverse.
Together, Gamma and VSWR help identify how well the market’s current momentum aligns with its natural behavior — whether the trend is stable and efficient or reflecting instability beneath the surface.
ZS Master Vision Pro - Advanced Multi-Timeframe Trading SystemZS MASTER VISION PRO - PROFESSIONAL TRADING SUITE
Created by Zakaria Safri
A comprehensive, all-in-one trading system combining multiple proven technical analysis methods into a single, powerful indicator. Designed for traders who demand precision, clarity, and actionable signals across all timeframes.
KEY FEATURES
CORE TREND ALGORITHM
Adaptive ATR-based trend detection with dynamic support and resistance zones. Features Type A and Type B signal modes for different trading styles, strong signal detection in key reversal zones, and optional EMA source smoothing for noise reduction.
MULTI-LAYER EMA CLOUD SYSTEM
Five customizable EMA cloud layers for multi-timeframe analysis with theme-adaptive color coding across five professional themes. Optional line display for detailed MA tracking with configurable periods from scalping to position trading.
WAVE TREND OSCILLATOR
Advanced momentum oscillator with channel-based calculations featuring smart reversal detection at extreme overbought and oversold levels. Includes directional strength confirmation and customizable sensitivity with adjustable reaction periods.
DIVERGENCE SCANNER
Detects four types of divergence automatically:
- Regular Bullish: Price making lower lows while oscillator making higher lows
- Regular Bearish: Price making higher highs while oscillator making lower highs
- Hidden Bullish: Trend continuation signals in uptrends
- Hidden Bearish: Trend continuation signals in downtrends
Automatic fractal-based detection with clear visual labels on chart.
MARKET BIAS INDICATOR
Heikin Ashi-based trend strength analysis with real-time bias calculation showing Bullish or Bearish combined with Strong or Weak conditions. Smoothed for cleaner signals and perfect for trend confirmation.
MOMENTUM SYSTEM
Proprietary momentum calculation using adaptive smoothing with growing and falling state detection. Normalized values for consistent interpretation and responsive to rapid market changes.
DYNAMIC SUPPORT AND RESISTANCE
Automatic pivot-based support and resistance level detection with adjustable left and right bar lookback. Non-repainting levels with visual clarity through color-coded lines.
LIVE INFORMATION DASHBOARD
Real-time market analysis panel displaying current trend direction, market bias based on Heikin Ashi, Wave Trend status and value, and momentum trend with state. Customizable display options with theme-adaptive colors.
VISUAL CUSTOMIZATION
FIVE PROFESSIONAL COLOR THEMES:
Pro - Modern green and red color scheme (default)
Classic - Traditional teal and red combination
Cyberpunk - Neon cyan and magenta contrast
Ocean - Blue and orange contrast
Sunset - Gold and red warmth
SIGNAL STYLES:
Labels with emoji indicators (BUY with rocket, SELL with bear, STRONG with lightning)
Arrows for clean minimal appearance
Triangles for classic approach
DISPLAY OPTIONS:
Color-coded candles following trend direction
Trend background highlighting for instant trend recognition
Optional EMA line display for detailed analysis
Adjustable transparency levels for personal preference
SMART ALERTS
Pre-configured alert conditions for all major signals:
Buy signals for standard entry opportunities
Sell signals for standard exit or short opportunities
Strong buy signals for high-confidence long entries
Strong sell signals for high-confidence short entries
Bullish divergence detection alerts
Bearish divergence detection alerts
Alert messages automatically include ticker symbol, current price, and specific signal type for quick decision making.
HOW TO USE
FOR TREND TRADERS:
Enable EMA Clouds with focus on Cloud 5 featuring 50 and 200 period moving averages. Wait for trend background color change to confirm direction. Enter on STRONG signals aligned with higher timeframe trend direction. Use support and resistance levels for strategic exits.
FOR SWING TRADERS:
Enable Wave Trend Oscillator information display. Look for oversold and overbought reversal setups. Confirm potential reversals with divergence scanner. Enter on smart reversal signals with proper risk management.
FOR SCALPERS:
Use Type B signal mode for more frequent trading signals. Enable Cloud 1 with 5 and 13 periods for quick trend confirmation. Focus on momentum growing and falling states for entry timing. Take quick entries on regular buy and sell signals.
FOR POSITION TRADERS:
Use Type A mode with higher ATR multiplier set to 3.0 or above. Enable only Cloud 5 with 50 and 200 periods for major trend confirmation. Only take STRONG signals for highest probability setups. Hold positions through minor pullbacks and noise.
RECOMMENDED SETTINGS
STOCKS ON DAILY TIMEFRAME:
Trend Period: 180
ATR Period: 155
ATR Multiplier: 2.1
Signal Mode: Type A
FOREX ON HOURLY AND 4-HOUR TIMEFRAMES:
Trend Period: 150
ATR Period: 120
ATR Multiplier: 2.5
Signal Mode: Type A
CRYPTOCURRENCY ON 15-MINUTE AND 1-HOUR TIMEFRAMES:
Trend Period: 100
ATR Period: 80
ATR Multiplier: 3.0
Signal Mode: Type B
SCALPING ON 1-MINUTE AND 5-MINUTE TIMEFRAMES:
Trend Period: 50
ATR Period: 40
ATR Multiplier: 2.0
Signal Mode: Type B
WHAT IS INCLUDED
Trend Analysis using ATR-based adaptive algorithm
Five EMA Cloud Layers for multi-timeframe confluence
Wave Trend Oscillator for momentum and reversal detection
Divergence Scanner detecting four types of divergence
Market Bias using Heikin Ashi-based trend strength
Momentum System with advanced momentum tracking
Support and Resistance Levels with automatic pivot detection
Live Dashboard showing real-time market analysis
Smart Alerts featuring six pre-configured alert types
Five Color Themes offering professional visual options
TECHNICAL DETAILS
CALCULATION METHODS:
Average True Range (ATR) for volatility adaptation
Exponential Moving Average (EMA) and Simple Moving Average (SMA) for trend smoothing
Wave Trend channel oscillator for momentum analysis
Fractal-based divergence detection algorithm
Heikin Ashi transformation for bias calculation
Logarithmic momentum calculation for precision
PERFORMANCE CHARACTERISTICS:
Optimized for maximum speed and efficiency
No repainting signals ensuring reliability
Works on all timeframes from 1 minute to monthly
Compatible with all instruments including stocks, forex, crypto, and futures
RISK DISCLAIMER
This indicator is a technical analysis tool and should not be used as the sole basis for trading decisions. Always use proper risk management and never risk more than you can afford to lose. Combine with other analysis methods and practice on demo accounts first. Past performance does not guarantee future results. Trading carries substantial risk and is not suitable for all investors.
SUPPORT AND UPDATES
Regular updates and continuous improvements
Based on proven technical analysis principles
Developed following Pine Coders best practices and standards
Clean, well-documented, and optimized code structure
WHY CHOOSE ZS MASTER VISION PRO
All-in-one solution eliminating the need for multiple indicators
Highly customizable to adapt to your specific trading style
Professional grade analysis with institutional-quality standards
Clean interface that is not cluttered or confusing
Works everywhere across all markets and all timeframes
Smart signals filtered for quality over quantity
Beautiful design featuring five professional color themes
Active development with regular improvements and updates
Transform your trading with ZS Master Vision Pro today.
Version 2.0 | Created by Zakaria Safri | Pine Script Version 5
SuperTrend MAAfter building SuperBands, I kept thinking about what happens at the midpoint between those two volatility-adaptive envelopes. The upper and lower bands are both trailing price based on ATR and EMA smoothing, but they're operating independently in opposite directions. Taking their average seemed like it might produce an interesting centerline that adapts to volatility in a way that regular moving averages don't. Turns out it does, and that's what this indicator is.
The core concept is straightforward. Instead of plotting the upper and lower SuperBands separately, this calculates both of them internally, averages their values, and then applies an additional smoothing pass with EMA to create a single centerline. That centerline sits roughly in the middle of where the bands would be, but because it's derived from ATR-offset trailing stops rather than direct price smoothing, it behaves differently than a standard moving average of the same length. During trending periods, the centerline tracks closer to price because one of the underlying bands is actively trailing while the other is dormant. During consolidation, both bands compress toward price and the centerline tends to oscillate more with shorter-term movements.
What's interesting is that this acts like a supertrend all by itself with directional behavior baked in. When one of the underlying supertrend waves dominates, meaning price is strongly trending in one direction and only one band is active, you get what feels like a "true" supertrend, whatever that means exactly. The centerline locks into trend-following mode and the color gradient reflects that commitment. You get bright bullish colors during sustained uptrends when the upper band is doing all the work, and strong bearish colors during downtrends when the lower band dominates. But when both bands are active and fighting for control, which happens during consolidation or choppy conditions, the centerline settles into more neutral tones that clearly signal you're in a ranging environment. The colors really do emphasize this behavior and make it visually obvious which regime you're in.
The smoothing parameter controls how aggressively the underlying SuperBand trails adapt to price, which indirectly affects how responsive the centerline is. Lower values make the bands tighter and more reactive, so the centerline follows price action more closely. Higher values create wider bands that only respond to sustained moves, which produces a smoother centerline that filters out more noise. The center smoothing parameter applies a second EMA pass specifically to the averaged midpoint, giving you independent control over how much additional lag you want on the final output versus the raw band average.
What makes this different from just slapping an EMA on price is that the underlying bands are already volatility-aware through their ATR calculations. When volatility spikes, the bands widen and the centerline adjusts its position relative to price based on where those bands settle. A traditional moving average would just smooth over the volatility spike without adjusting its distance from price. This approach incorporates volatility information into the centerline's positioning, which can help it stay relevant during regime changes where fixed-period moving averages tend to lag badly or whipsaw.
The color gradient adds a momentum overlay using the same angle-based calculation from SuperBands. The centerline's rate of change gets normalized by an RMS estimate of its historical movement range, converted to an angle through arctangent scaling, and then mapped to a color gradient. When the centerline is rising, it gradients from neutral toward your chosen bullish color, with brightness increasing as the rate of ascent steepens. When falling, it shifts toward the bearish color with intensity tied to the descent rate. This gives you an immediate visual sense of whether the centerline is accelerating, decelerating, or moving at a stable pace.
Configuration is simpler than SuperBands since you're only dealing with a single output line instead of separate bull and bear envelopes. The length parameter controls the underlying band behavior. ATR period and multiplier determine how much space the bands allocate around price before they trail. Center smoothing adds the extra EMA pass on the averaged midpoint. You can tune these independently to get different characteristics. A tight ATR multiplier with heavy center smoothing creates a smooth line that stays close to price. A wide multiplier with light center smoothing produces a line that swings more freely and adapts faster to directional changes.
From a practical standpoint, this works well as a trend filter or dynamic support and resistance reference. Price above the centerline with bullish coloring suggests a favorable environment for long positions. Price below with bearish coloring indicates the opposite. Crossovers can signal trend changes, though like any moving average system, you'll get whipsaws in choppy conditions. The advantage over traditional MAs is that the volatility adaptation tends to reduce false signals during transitional periods where volatility is expanding but direction hasn't fully committed.
The implementation reuses the entire SuperBands logic, which means all the smoothing and state management for the trailing stops is identical. The only addition is averaging the two band outputs and applying the final EMA pass. The color calculation follows the same RMS-normalized angle approach but applies it to the centerline's delta rather than the individual band deltas. This keeps the coloring consistent with how SuperBands handles momentum visualization while adapting it to a single line instead of dual envelopes.
What this really highlights is that you can derive moving averages from mechanisms other than direct price smoothing. By building the centerline from volatility-adjusted trailing stops, you get adaptive behavior that responds to both price movement and volatility regime without needing separate inputs or complex multi-stage calculations. Whether that adaptation provides a meaningful edge depends on your strategy and market, but it's a fundamentally different approach than the typical fixed-period or adaptive MAs that adjust length based on volatility or momentum indicators.
Z-Candle Range 4U [ZuperView]Z-Candle Range 4U helps you quickly spot the strongest and weakest candles among the last “n” bars, based on both the full range (High-Low) and body length (Open-Close).
A simple yet highly effective tool to instantly visualize market volatility and imbalance.
In trading, not all candles carry the same weight. Some reveal the footprints of major money flows, while others are just minor market noise.
Z-Candle Range 4U highlights these extreme candles directly on your chart, providing a clear view of where volatility is expanding or contracting.
You simply select the number of bars to analyze (n), and the indicator automatically identifies:
The candle with the largest High-Low range (Max Range) → signals strong volatility
The candle with the smallest High-Low range (Min Range) → signals price compression
The candle with the longest Open-Close body (Max Body) → indicates the strongest directional push
The candle with the shortest Open-Close body (Min Body) → indicates hesitation or market balance
📌 Ideal for:
Detecting volatility shifts before breakouts or reversals
Spotting strong momentum signals, including breakout or impulse bars
Identifying accumulation phases and low-volatility periods, useful for breakout strategies
Recognizing market pauses and decision-making zones, often preceding major moves
Analyzing momentum structure and energy of each price swing
Integrating into visual strategies for easy interpretation of market behavior
📌 Key use cases:
Detect volatility shifts before breakouts or reversals:
When candle ranges (High-Low) expand unusually after a compression phase, it often signals returning volatility. Z-Candle Range 4U makes this expansion clear, helping you prepare for upcoming breakouts or reversals.
Spot strong momentum candles (breakouts or impulse bars):
When a candle has the longest body (Max Body) in the cycle, it often reflects a powerful push from either buyers or sellers. These are impulse bars – where momentum bursts – signaling the start of a strong price swing or a high-probability breakout.
Detect accumulation phases and low-volatility periods:
When the indicator identifies candles with the smallest ranges, it indicates that volatility is contracting, and the market is storing energy. This “calm before the storm” phase is highly valuable for preparing and timing breakout setups.
Recognize market pauses and indecision zones:
Small-bodied candles with relatively wide ranges reflect hesitation and struggle between buyers and sellers. The indicator highlights these zones, which often precede significant moves.
Analyze momentum structure and energy of each swing:
Comparing candle sizes allows you to measure the strength of each price wave. Shrinking candles indicate weakening momentum, while gradually expanding candles suggest trend consolidation.
Integrate into visual strategies for easy market reading:
Z-Candle Range 4U highlights extreme candles directly on your chart, allowing traders to interpret price behavior visually. No complex calculations are needed to sense volatility, momentum, and structural changes accurately.
Additionally, the indicator includes alerts to notify you when extreme candles appear, even when you’re away from the chart.
Gold and Bitcoin: The Evolution of Value!The Eternal Luster of Gold
In the dawn of time, when the earth was young and rivers whispered secrets to the stones, a wanderer named Elara found a gleam in the silt of a sun-kissed stream. It was pure gold, radiant like a captured star fallen from the heavens. She held it in her palm, feeling its warmth pulse like a heartbeat, and in that moment, humanity’s soul awakened to the allure of eternity.
As seasons turned to centuries, gold wove itself into the story of empires. In ancient Egypt, pharaohs crowned themselves with its glow, believing it to be the flesh of gods. It built pyramids that reached for the sky and tombs that guarded kings forever. Across the sands in Mesopotamia, merchants traded it for spices and silks, its weight a promise of power and trust.
Translation moment: Gold became the first universal symbol of value. People trusted it more than words or promises because it did not rust, fade, or vanish.
The Greeks saw in gold not only wealth but wisdom, the symbol of the sun’s eternal fire. Alexander the Great carried it across the continent, forging an empire of golden threads. Rome rose on its back, minting coins whose clink echoed through history.
Through the ages, gold endured the rush of California’s dreamers, the halls of Versailles, and the quiet vaults of modern fortunes. It has been both a curse and a blessing, the fuel of wars and the gift of love, whispering of beauty’s fragility and the human desire for something that lasts beyond the grave. In its shine, we see ourselves fragile yet forever chasing light.
The Digital Dawn of Bitcoin
Centuries later, under the glow of computer screens, a visionary named Satoshi dreamed of a new gold born not from the earth but from the ether of ideas. Bitcoin appeared in 2009 amid a world weary of banks and broken trust.
Like gold’s ancient gleam, Bitcoin was mined not with picks but with puzzles solved by machines. It promised freedom, a currency without kings, flowing from person to person, unbound by borders or empires.
Translation moment: Bitcoin works like digital gold. Instead of digging the ground, miners use computers to solve problems and unlock new coins. No one controls it, and that is what makes it powerful.
Through doubt and frenzy, it rose as a beacon for those seeking sovereignty in a digital world. Its volatility became its soul, a reminder that true value is built on belief. Bitcoin speaks to ingenuity and rebellion, a star of code guiding us toward a future where wealth is weightless yet profoundly honest.
Gold’s Cycles: Echoes of War and Crisis
In the early 20th century, gold was held under fixed prices until the Great Depression of 1929 shattered these illusions. The 1934 dollar devaluation lifted it from 20.67 to 35, restoring faith amid despair. When World War II erupted in 1939, gold’s role as a refuge was muted by controls, yet it quietly held its place as the world’s silent guardian.
The 1970s awakened its wild spirit. The Nixon Shock of 1971 freed gold from 35, sparking a bull run during the 1973 Oil Crisis. The 1979 Iranian Revolution led to a 1980 peak of 850, a leap of more than 2,000 percent, as investors sought safety from the chaos.
Translation moment: When fear rises, people rush to gold. Every major war or economic crisis has sent gold upward because it feels safe when paper money loses trust.
The 1987 stock crash caused brief dips, but the 1990 Gulf War reignited its glow. Around 2000, after the Dot-com Bust, gold found new life, climbing from $ 270 to over $1,900 during the 2008 Financial Crisis. It dipped to 1050 in 2015, then surged again past 2000 during the 2020 pandemic.
The 2022 Ukraine War added another chapter with prices climbing above 2700 by 2025. Across a century of crises, gold has risen whenever fear tested humanity’s resolve, teaching patience and fortitude through its quiet endurance.
Bitcoin’s Cycles: Echoes of Innovation and Crisis
Born from the ashes of the 2008 Financial Crisis, Bitcoin began its story at mere cents. It traded below $1 until 2011, when it reached $30 before crashing by 90 percent following the MTGOX collapse.
In 2013, it soared to 1242 only to fall again to 200 in 2015 as regulations tightened. The 2017 bull run lifted it to nearly 20000 before another long winter brought it to 3200 in 2018. Each fall taught resilience, each rise renewed belief.
During the 2020 pandemic, it fell below 5000 before rallying to 69000 in 2021. The Ukraine War and the FTX collapse of 2022 brought it down to 16000, but also proved its role in humanitarian aid. By 2024, the halving and ETF approvals helped it break 100000, marking Bitcoin’s rise as digital gold.
Translation moment: Bitcoin’s rhythm follows four-year halving cycles when mining rewards are cut in half. This keeps supply limited, which often triggers new bull runs as demand returns.
Every four years, it's halving cycles 2012, 2016, 2020, 2024, fueling new waves of adoption and correction. Bitcoin grows strongest in times of uncertainty, echoing humanity’s drive to evolve beyond limits.
The Harmony of Gold and Bitcoin Modern Parallels
In today’s markets, gold’s ancient glow meets Bitcoin’s electric pulse. As of October 17, 2025, their correlation stands near 0.85, close to its historic high of 0.9. Both rise as guardians against inflation and the erosion of trust in the dollar.
Gold trades near 4310 per ounce a record high while Bitcoin hovers around 104700 showing brief fractures in their unity. Gold offers the comfort of touch while Bitcoin provides the thrill of code. Together, they reflect fear and hope, the twin emotions that drive every market.
Translation moment: A correlation of 0.85 means they often move in the same direction. When fear or inflation rises, both gold and Bitcoin tend to rise in tandem.
Analysts warn of bubbles in stocks, gold, and crypto, yet optimism remains for Bitcoin’s growth through 2026, while gold holds its defensive strength.
Gold carries risks of storage cost and theft, but steadiness in chaos. Bitcoin carries volatility and regulatory challenges, but it also offers unmatched innovation and reach. One is the anchor, the other the dream, and both reward those who hold conviction through uncertainty.
Epilogue: The Timeless Balance
Gold and Bitcoin form a bridge between the ancient and the future. Gold, the earth’s eternal treasure, stands as a symbol of stability and truth. Bitcoin, the digital heir, shines with the spark of innovation and freedom.
Experts view gold as the ultimate inflation hedge, forged in fire and tested over centuries. They see Bitcoin as its digital counterpart, scarce by code and limitless in reach.
Gold’s weight grounds us in reality while Bitcoin’s light expands our imagination. In 2025, as gold surpasses $4,346 and Bitcoin hovers near $105,000, the wise investor sees not rivals but reflections.
Translation moment: Gold reminds us to protect what we have. Bitcoin reminds us to dream of what could be. Together, they balance caution and courage, the two forces every generation must master.
One whispers of legacy, the other of evolution, yet together they tell humanity’s oldest story, our unending quest to preserve value against time and to chase the light that never fades.
🙏 I ask (Allah) for guidance and success. 🤲
Tweezer & Kangaroo Zones [WavesUnchained]Tweezer & Kangaroo Zones
Pattern Recognition with Supply/Demand Zones
Indicator that detects tweezer and kangaroo tail (pin bar) reversal patterns and creates supply and demand zones. Includes volume validation, trend context, and confluence scoring.
What You See on Your Chart
Pattern Labels:
"T" (Red) - Tweezer Top detected above price → Bearish reversal signal
"T" (Green) - Tweezer Bottom detected below price → Bullish reversal signal
"K" (Red) - Kangaroo Bear (Pin Bar rejection from top) → Bearish signal
"K" (Green) - Kangaroo Bull (Pin Bar rejection from bottom) → Bullish signal
Label Colors Indicate Pattern Strength:
Dark Green/Red - Strong pattern (score ≥8.0)
Medium Green/Red - Good pattern (score ≥6.0)
Light Green/Red - Valid pattern (score <6.0)
Zone Boxes:
Red Boxes - Supply Zones (resistance, potential short areas)
Green Boxes - Demand Zones (support, potential long areas)
White Border - Active zone (fresh, not tested yet)
Gray Border - Inactive zone (expired or invalidated)
Pattern Detection
Tweezer Patterns (Classic Double-Top/Bottom):
Flexible Lookback - Detects patterns up to 3 bars apart (not just consecutive)
Precision Matching - 0.2% level tolerance for high-quality signals
Wick Similarity Check - Both candles must show similar rejection wicks
Volume Validation - Second candle requires elevated volume (0.8x average)
Pattern Strength Score - 0-1 quality rating based on level match + wick similarity
Optional Trend Context - Can require trend alignment (default: OFF for more signals)
Kangaroo Tail / Pin Bar Patterns:
No Pivot Delay - Instant detection without waiting for pivot confirmation
Body Position Check - Body must be at candle extremes (30% tolerance)
Volume Spike - Rejection must occur with volume (0.9x average)
Rejection Strength - Scores based on wick length (0.5-0.9 of range)
Optional Trend Context - Bearish in uptrends, Bullish in downtrends (default: OFF)
Zone Management
Auto-Created Zones - Every valid pattern creates a supply/demand zone
Overlap Prevention - Zones too close together (50% overlap) are not duplicated
Lifetime Control - Zones expire after 400 bars (configurable)
Smart Invalidation - Zones invalidate when price closes through them
Styling Options - Choose between Solid, Dashed, or Dotted borders
Border Width - 2px width for better visibility
Confluence Scoring System
Multi-factor confluence scoring (0-10 scale) with configurable weights:
Regime (EMA+HTF) - Trend alignment across timeframes (Weight: 2.0)
HTF Stack - Multi-timeframe trend confluence (Weight: 3.0)
Structure - Higher lows / Lower highs confirmation (Weight: 1.0)
Relative Volume - Volume surge validation (Weight: 1.0)
Chop Advantage - Favorable market conditions (Weight: 1.0)
Zone Thinness - Tight zones = better R/R (Weight: 1.0)
Supertrend - Trend indicator alignment (Weight: 1.0)
MOST - Moving Stop alignment (Weight: 1.0)
Pattern Strength - Quality of detected pattern (Weight: 1.5)
Zone Retest Signals
Signals generated when zones are retested:
BUY Signal - Price retests demand zone from above (score ≥4.5)
SELL Signal - Price retests supply zone from below (score ≥5.5)
Normalized Score - Displayed as 0-10 for easy interpretation
Optional Trend Gate - Require trend alignment for signals (default: OFF)
Alert Ready - Built-in alertconditions for automation
Additional Features
Auto-Threshold Tuning - Adapts to ATR and Choppiness automatically
Session Profiles - Different settings for RTH vs ETH sessions
Organized Settings - 15+ input groups for easy configuration
Optional Panels - HTF Stack overview and performance metrics (default: OFF)
Data Exports - Hidden plots for strategy/library integration
RTA Health Monitoring - Built-in performance tracking
Setup & Configuration
Quick Start:
1. Apply indicator to any timeframe
2. Patterns and zones appear automatically
3. Adjust pattern detection sensitivity if needed
4. Configure zone styling (Solid/Dashed/Dotted)
5. Set up alerts for zone retests
Key Settings to Adjust:
Pattern Detection:
• Min RelVolume: Lower = more signals (0.8 Tweezer, 0.9 Kangaroo)
• Require trend context: Enable for stricter, higher-quality patterns
• Check wick similarity: Ensures proper rejection structure
Zone Management:
• Zone lifetime: How long zones remain active (default: 400 bars)
• Invalidate on close-through: Remove zones when price breaks through
• Max overlap: Prevent duplicate zones (default: 50%)
Scoring:
• Min Score BUY/SELL: Higher = fewer but better signals (default: 4.5/5.5)
• Component weights: Customize what factors matter most
• Signals require trend gate: OFF = more signals, ON = higher quality
Visual Customization
Zone Colors - Light red/green with 85% transparency (non-intrusive)
Border Styles - Solid, Dashed, or Dotted
Label Intensity - Darker greens for better readability
Clean Charts - All panels OFF by default
Understanding the Zones
Supply Zones (Red):
Created from bearish patterns (Tweezer Tops, Kangaroo Bears). Price made a high attempt to push higher, but was rejected. These become resistance areas where sellers may step in again.
Demand Zones (Green):
Created from bullish patterns (Tweezer Bottoms, Kangaroo Bulls). Price made a low with strong rejection. These become support areas where buyers may step in again.
Zone Quality Indicators:
• White border = Fresh zone, not tested yet
• Gray border = Zone expired or invalidated
• Thin zones (tight range) = Better risk/reward ratio
• Thick zones = Less precise, wider stop required
Trading Applications
Reversal Trading - Enter at pattern detection with tight stops
Zone Retest Trading - Wait for retests of established zones
Trend Confluence - Trade only when patterns align with trend
Risk Management - Use zone boundaries for stop placement
Target Setting - Opposite zones become profit targets
Pro Tips
Best signals occur when pattern + zone retest + trend all align
Lower timeframes = more signals but more noise
Higher timeframes = fewer but more reliable signals
Start with default settings, adjust based on your market
Combine with other analysis (structure, key levels, etc.)
Use alerts to avoid staring at charts all day
Important Notes
Not all patterns will lead to successful trades
Use proper risk management and position sizing
Patterns work best in trending or range-bound markets
Very choppy conditions may produce lower-quality signals
Always confirm with your own analysis before trading
Technical Specifications
• Pine Script v6
• RTA-Core integration
• RTA Core Library integration
• Maximum 200 boxes, 500 labels
• Auto-tuning based on ATR and Choppiness
• Session-aware threshold adjustments
• Memory-optimized zone management
What's Included
Tweezer Top/Bottom detection
Kangaroo Tail / Pin Bar detection
Automatic supply/demand zone creation
Volume validation system
Pattern strength scoring
Zone retest signals
Multi-factor confluence scoring
Optional HTF Stack panel
Optional performance metrics
Session profile support
Auto-threshold tuning
Alert conditions
Data exports for strategies
Author Waves Unchained
Version 1.0
Status Public Indicator
Summary
Reversal pattern detection with zone management, volume validation, and confluence scoring for tweezer and kangaroo tail patterns.
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Disclaimer: This indicator is for educational and informational purposes only. Trading involves risk. Past performance does not guarantee future results. Always practice proper risk management.
Volume v4 (Dollar Value) by Koenigsegg📊 Volume v3 (Dollar Value) by Koenigsegg
🎯 Purpose:
Volume v3 (Dollar Value) by Koenigsegg transforms traditional raw-unit volume into dollar-denominated volume, revealing how much money actually flows through each candle.
Instead of measuring how many coins or contracts were traded, this version calculates the total traded value = volume × average price (hlc3), allowing traders to visually assess capital intensity and market participation within each move.
⚙️ Core Features
- Converts raw volume into USD-based traded value for each candle.
- Color-coded bars show bullish (green/teal) vs. bearish (red) activity.
- Built-in SMA and SMMA overlays highlight sustained shifts in value flow.
- Designed for visual clarity to support momentum, exhaustion, and divergence studies.
📖 How to Read It
Rising Dollar Volume — indicates growing market participation and strong capital flow, often aligning with impulsive waves in trend direction.
Falling Dollar Volume — signals waning interest or reduced participation, potentially hinting at correction or exhaustion phases.
Comparing Legs — when price makes new highs/lows but dollar volume weakens, it can reveal divergences between price movement and actual capital commitment.
SMA / SMMA Lines — use them to identify longer-term accumulation or depletion of market activity, separating short bursts from sustained inflows or outflows.
The goal is to visualize the strength of market moves in terms of capital energy, not just tick activity. This distinction helps traders interpret whether a trend is being driven by genuine money flow or low-liquidity drift.
⚠️ Disclaimer
This script is provided for research and educational purposes only.
It does not constitute financial advice, investment recommendations, or trading signals.
Always conduct your own analysis and manage your own risk when trading live markets.
The author accepts no liability for financial losses incurred from use of this tool.
🧠 Credits
Developed and published by Koenigsegg.
Written in Pine Script® v6, fully compliant with TradingView’s House Rules for Pine Scripts.
Licensed under the Mozilla Public License 2.0.
phx_kroLibrary "phx_kro"
compute(src, bandwidth, bbwidth, sdLook, sdMult, obos_mult)
Parameters:
src (float)
bandwidth (int)
bbwidth (float)
sdLook (int)
sdMult (float)
obos_mult (float)
start_flags(src, bandwidth, bbwidth)
Parameters:
src (float)
bandwidth (int)
bbwidth (float)
KROFeed
Fields:
Wave (series float)
is_green (series bool)
is_red (series bool)
band_width (series float)
band_width_sma (series float)
band_width_std (series float)
is_hyper_wide (series bool)
wave_sma (series float)
wave_std (series float)
wave_ob_threshold (series float)
wave_os_threshold (series float)
is_overbought (series bool)
is_oversold (series bool)
is_oversold_confirmed (series bool)
is_overbought_confirmed (series bool)
enhanced_os_confirmed (series bool)
enhanced_ob_confirmed (series bool)
triple_green_transition (series bool)
triple_red_transition (series bool)
startwave_bull (series bool)
startwave_bear (series bool)
Triple Gaussian Smoothed Ribbon [BOSWaves]Triple Gaussian Smoothed Ribbon – Adaptive Gaussian Framework
Overview
The Triple Gaussian Smoothed Ribbon is a next-generation market visualization framework built on the principles of Gaussian filtering - a mathematical model from digital signal processing designed to remove noise while preserving the integrity of the underlying trend.
Unlike conventional moving averages that suffer from phase lag and overreaction to volatility spikes, Gaussian smoothing produces a symmetrical, low-lag curve that isolates meaningful directional shifts with exceptional clarity.
Developed under the Adaptive Gaussian Framework, this indicator extends the classical Gaussian model into a multi-stage smoothing and visualization system. By layering three progressive Gaussian filters and rendering their interactions as a gradient-based ribbon field, it translates market energy into a coherent, visually structured trend environment. Each ribbon layer represents a progressively smoothed component of price motion, producing a high-fidelity gradient field that evolves in sync with real-time trend strength and momentum.
The result is a uniquely fluid trend and reversal detection system - one that feels organic, adapts seamlessly across timeframes, and reveals hidden transitions in market structure long before traditional indicators confirm them.
Theoretical Foundation
The Gaussian filter, derived from the Gaussian function developed by Carl Friedrich Gauss in 1809, operates on the principle of weighted symmetry, assigning higher importance to central price data while tapering influence toward historical extremes following a bell-curve distribution. This symmetrical design minimizes phase distortion and smooths without introducing lag spikes — a stark contrast to exponential or linear filters that sacrifice temporal accuracy for responsiveness.
By cascading three Gaussian stages in sequence, the indicator creates a multi-frequency decomposition of price action:
The first stage captures immediate trend transitions.
The second absorbs mid-term volatility ripples.
The third stabilizes structural directionality.
The final composite ribbon reflects the market’s dominant frequency - a smoothed yet reactive trend spine - while an independent, heavier Gaussian smoothing serves as a reference layer to gauge whether the primary motion leads or lags relative to broader market structure.
This multi-layered Gaussian framework effectively replicates the behavior of a signal-processing filter bank: isolating meaningful cyclical movements, suppressing random noise, and revealing phase shifts with minimal delay.
How It Works
Triple Gaussian Core
Price data is passed through three successive Gaussian smoothing stages, each refining the trend further and removing higher-frequency distortions.
The result is a fluid, continuously adaptive baseline that responds naturally to directional changes without overshooting or flattening key inflection points.
Adaptive Ribbon Architecture
The indicator visualizes its internal dynamics through a five-layer gradient ribbon. Each layer represents a progressively delayed Gaussian curve, creating a color field that dynamically shifts between bullish and bearish tones.
Expanding ribbons indicate accelerating momentum and trend conviction.
Compressing ribbons reflect consolidation and volatility contraction.
The smooth color gradient provides a real-time depiction of energy buildup or dissipation within the trend, making it visually clear when the market is entering a state of expansion, transition, or exhaustion.
Momentum-Weighted Opacity
Ribbon transparency adjusts according to normalized momentum strength.
As trend force builds, colors intensify and layers become more opaque, signifying conviction.
When momentum wanes, ribbons fade - an early visual cue for potential reversals or pauses in trend continuation.
Candle Gradient Integration
Optional candle coloring ties the chart’s candles to the prevailing Gaussian gradient, allowing traders to view raw price action and smoothed wave dynamics as a unified system.
This integration produces a visually coherent chart environment that communicates directional intent instantly.
Signal Detection Logic
Directional cues emerge when the smoother, broader Gaussian curve crosses the faster-reacting Gaussian line, marking structural inflection points in the filtered trend.
Bullish shifts : short-term momentum transitions upward through the long-term baseline after a localized trough.
Bearish shifts : momentum declines through the baseline following a local peak.
To maintain integrity in choppy markets, the framework applies a trend-strength and separation filter, which blocks weak or overlapping conditions where movement lacks conviction.
Interpretation
The Triple Gaussian Smoothed Ribbon provides a layered, intuitive read on market structure:
Trend Continuation : Expanding ribbons with deep color intensity confirm directional strength.
Reversal Phases : Color gradients flip direction, indicating a phase shift or exhaustion point.
Compression Zones : Tight, pale ribbons reveal equilibrium phases often preceding breakouts.
Momentum Divergence : Fading color intensity despite continued price movement signals weakening conviction.
These transitions mirror the natural ebb and flow of market energy - captured through the Gaussian filter’s ability to represent smooth curvature without distortion.
Strategy Integration
Trend Following
Engage during strong directional expansions. When ribbons widen and color gradients intensify, the trend is accelerating with high confidence.
Reversal Identification
Monitor for full gradient inversion and fading momentum opacity. These conditions often precede transitional phases and early reversals.
Breakout Anticipation
Flat, compressed ribbons signal low volatility and energy buildup. A sudden gradient expansion with renewed opacity confirms breakout initiation.
Multi-Timeframe Alignment
Use higher timeframes to establish directional bias and lower timeframes for entry during compression-to-expansion transitions.
Technical Implementation Details
Triple Gaussian Stack : Sequential smoothing stages produce low-lag, high-purity signals.
Adaptive Ribbon Rendering : Five-layer Gaussian visualization for gradient-based trend depth.
Momentum Normalization : Opacity dynamically tied to trend strength and volatility context.
Consolidation Filter : Suppresses false signals in low-energy or range-bound conditions.
Integrated Candle Mode : Optional color synchronization with underlying gradient flow.
Alert System : Built-in notifications for bullish and bearish transitions.
This structure blends the precision of digital signal processing with the readability of visual market analysis, creating a clean but information-rich framework.
Optimal Application Parameters
Asset Recommendations
Cryptocurrency : Higher smoothing and sigma for stability under volatility.
Forex : Balanced parameters for cycle identification and reduced noise.
Equities : Moderate Gaussian length for responsive yet stable trend reads.
Indices & Futures : Longer smoothing periods for structural confirmation.
Timeframe Recommendations
Scalping (1 - 5m) : Use shorter smoothing for fast reactivity.
Intraday (15m - 1h) : Mid-length Gaussian chain for balance.
Swing (4h - 1D) : Prioritize clarity and opacity-driven trend phases.
Position (Daily - Weekly) : Longer smoothing to capture macro rhythm.
Performance Characteristics
Most Effective In :
Trending markets with recurring volatility cycles.
Transitional phases where early directional confirmation is crucial.
Less Effective In:
Ultra-low volume markets with erratic tick data.
Random, micro-chop conditions with no structural flow.
Integration Guidelines
Pair with volatility or volume expansion tools for enhanced breakout confirmation.
Use ribbon compression to anticipate volatility shifts.
Align entries with gradient expansion in the dominant color direction.
Scale position size relative to opacity strength and ribbon width.
Disclaimer
The Triple Gaussian Smoothed Ribbon – Adaptive Gaussian Framework is designed as a signal visualization and trend interpretation tool, not a standalone trading system. Its accuracy depends on appropriate parameter tuning, contextual confirmation, and disciplined risk management. It should be applied as part of a comprehensive technical or algorithmic trading strategy.
Fib Retrace + Extensions (v6– safe version) v 1🌀 Fib Extension Plus Retracement Strategy: Complete Overview
📊 Purpose and Core Idea
The Fib Extension Plus Retracement Strategy is a hybrid price-action methodology that blends Fibonacci Retracement and Fibonacci Extension tools to map high-probability entry, exit, and target zones within trending markets.
It is designed for precision timing, measured risk exposure, and trend-continuation trading.
By uniting both retracement and extension logic, traders can capture the entire lifecycle of a move — from the pullback phase to the breakout and projected expansion wave.
VWAP Deviation Oscillator [BackQuant]VWAP Deviation Oscillator
Introduction
The VWAP Deviation Oscillator turns VWAP context into a clean, tradeable oscillator that works across assets and sessions. It adapts to your workflow with four VWAP regimes plus two rolling modes, and three deviation metrics: Percent, Absolute, and Z-Score. Colored zones, optional standard deviation rails, and flexible plot styles make it fast to read for both trend following and mean reversion.
What it does
This tool measures how far price is from a chosen VWAP and expresses that gap as an oscillator. You can view the deviation as raw price units, percent, or standardized Z-Score. The plot can be a histogram or a line with optional fills and sigma bands, so you can quickly spot polarity shifts, overbought and oversold conditions, and strength of extension.
VWAP modes track a session VWAP that resets (4H, Daily, Weekly) or a rolling VWAP that updates continuously over a fixed number of bars or days.
Deviation modes let you choose the lens: Percent, Absolute, or Z-Score. Each highlights different aspects of stretch and mean pressure.
Visual encoding uses a 10-zone color palette to grade the magnitude of deviation on both sides of zero.
Volatility guards compute mode-specific sigma so thresholds are stable even when volatility compresses.
Why this works
VWAP is a high signal anchor used by institutions to gauge fair participation. Deviations around VWAP cluster in regimes: mild oscillations within a band, decisive pushes that signal imbalance, and standardized extremes that often precede either continuation or snapback. Expressing that distance as a single time series adds clarity: bias is the oscillator’s sign, risk context is its magnitude, and regime is the way it behaves around sigma lines.
How to use it
Trend following
Favor the side of the zero line. Bullish when the oscillator is above zero and making higher swing highs. Bearish when below zero and making lower swing lows. Use +1 sigma and +2 sigma in your mode as strength tiers. Pullbacks that hold above zero in uptrends, or below zero in downtrends, are often continuation entries.
Mean reversion
Fade stretched readings when structure supports it. Look for tests of +2 sigma to +3 sigma that fail to progress and roll back toward zero, or the mirror on the downside. Z-Score mode is best when you want standardized gates across assets. Percent mode is intuitive for intraday scalps where a given percent stretch tends to mean revert.
Session playbook
Use Daily or Weekly VWAP for intraday or swing context. Rolling modes help when the asset lacks clean session boundaries or when you want a continuous anchor that adapts to liquidity shifts.
Key settings
VWAP computation
VWAP Mode = 4 Hours, Daily, Weekly, Rolling (Bars), Rolling (Days). Session modes reset the VWAP when a new session begins. Rolling modes compute VWAP over a fixed trailing window.
Rolling (Lookback: Bars) controls the trailing bar count when using Rolling (Bars).
Rolling (Lookback: Days) converts days to bars at runtime and uses that trailing span.
Use Close instead of HLC3 switches the price reference. HLC3 is smoother. Close makes the anchor track settlement more tightly.
Deviation measurement
Deviation Mode
Percent : 100 * (Price / VWAP - 1). Good for uniform scaling across instruments.
Absolute : Price - VWAP. Good when price units themselves matter.
Z-Score : Standardizes the absolute residual by its own mean and standard deviation over Z/Std Window . Ideal for cross-asset comparability and regime studies.
Z/Std Window sets the mean and standard deviation window for Z-Score mode.
Volatility controls
Percent Mode Volatility Lookback estimates sigma for percent deviations.
Absolute Mode Volatility Lookback estimates sigma for absolute deviations.
Minimum Sigma Guard (pct pts) prevents the percent sigma from collapsing to near zero in extremely quiet markets.
Visualization
Plot Type = Histogram or Line. Histogram emphasizes impulse and polarity changes. Line emphasizes trend waves and divergences.
Positive Color / Negative Color define the palette for line mode. Histogram uses a 10-bucket gradient automatically.
Show Standard Deviations plots symmetric rails at ±1, ±2, ±3 sigma in the current mode’s units.
Fill Line Oscillator and Fill Opacity add a soft bias band around zero for line mode.
Line Width affects both the oscillator and the sigma rails.
Reading the zones
The oscillator’s color and height map deviation to nine graded buckets on each side of zero, with deeper greens above and deeper reds below. In Percent and Absolute modes, those buckets are scaled by their mode-specific sigma. In Z-Score mode the bucket edges are fixed at 0.5, 1.0, 2.0, and 2.8.
0 to +1 sigma weak positive bias, usually rotational.
+1 to +2 sigma constructive impulse. Pullbacks that hold above zero often continue.
+2 to +3 sigma strong expansion. Watch for either trend continuation or exhaustion tells.
Beyond +3 sigma statistical extreme. Requires structure to avoid fading too soon.
Mirror logic applies on the negative side.
Suggested workflows
Trend continuation checklist
Pick a session VWAP that matches your timeframe, for example Daily for intraday or Weekly for position trades.
Wait for the oscillator to hold the correct side of zero and for a sequence of higher swing lows in the oscillator (uptrend) or lower swing highs (downtrend).
Buy pullbacks that stabilize between zero and +1 sigma in an uptrend. Sell rallies that stabilize between zero and -1 sigma in a downtrend.
Use the next sigma band or a prior price swing as your target reference.
Mean reversion checklist
Switch to Z-Score mode for standardized thresholds.
Identify tests of ±2 sigma to ±3 sigma that fail to extend while price meets support or resistance.
Enter on a polarity change through the prior histogram bar or a small hook in line mode.
Fade back to zero or to the opposite inner band, then reassess.
Notes on the three modes
Percent is easy to reason about when you care about proportional stretch. It is well suited to intraday and multi-asset dashboards.
Absolute tracks cash distance from VWAP. This is useful when instruments have tight ticks and you plan risk in price units.
Z-Score standardizes the residual and is best for quant studies, cross-asset comparisons, and threshold research that must be scale invariant.
What the alerts can tell you
Polarity changes at zero can mark the start or end of a leg.
Crosses of ±1 sigma identify overbought or oversold in the current mode’s units.
Zone changes signal an upgrade or downgrade in deviation strength.
Troubleshooting and edge cases
If your instrument has long flat periods, keep Minimum Sigma Guard above zero in Percent mode so the rails do not vanish.
In Rolling modes, very short windows will respond quickly but can whip around. Session modes smooth this by resetting at well known boundaries.
If Z-Score looks erratic, increase Z/Std Window to stabilize the estimate of mean and sigma for the residual.
Final thoughts
VWAP is the anchor. The deviation oscillator is the narrative. By separating bias, magnitude, and regime into a simple stream you can execute faster and review cleaner. Pick the VWAP mode that matches your horizon, choose the deviation lens that matches your risk framework, and let the color graded zones guide your decisions.
FSVZO | Lyro RSFSVZO | Lyro RS
This script is a technical analysis tool called the FSVZO, or Fourier Smoothed Volume Zone Oscillator. It is designed to analyze market momentum and trend strength by combining price and volume data with advanced smoothing techniques. The goal is to help identify potential trends, overbought/oversold conditions, and divergence signals in a clear visual format.
Understanding the Indicator's Components
The indicator plots a main oscillator line and several supporting elements on a separate pane below the chart.
The Main Oscillator: This is the primary, colored wave. Its movement and color are key to interpretation.
Trend Direction: The color shifts between bullish and bearish tones based on the momentum of the oscillator. This provides a quick visual reference for the prevailing short-term trend.
Key Levels: Horizontal lines mark significant levels such as +60, +85, -60, and -85. Movements above +60 or below -60 can indicate strong momentum, while approaches to the extreme levels (+85/-85) may suggest overbought or oversold conditions.
Divergence Detection: The indicator can plot labels ("ℝ" for Regular, "ℍ" for Hidden) on the oscillator to signal potential divergences. These occur when the indicator's direction differs from the price action on the main chart and can sometimes foreshadow reversals or continuations.
Moving Average (MA): A central moving average line, based on the oscillator, helps to smooth out the data further and can act as a dynamic support or resistance level within the indicator pane.
White Noise Filter (Optional): This feature displays a histogram that represents market noise. It can be toggled on or off. Analyzing the histogram's behavior may provide additional context on the stability or volatility of the current trend.
Dynamic Background: The background of the indicator pane can change color to highlight periods where the momentum is particularly strong, based on the position of the moving average.
Suggested Use and Interpretation
Traders might use this indicator in several ways:
Trend Identification: Observe the color and position of the main oscillator. A predominantly bullish-colored oscillator above the zero line may suggest an upward trend, while a bearish-colored one below zero may suggest a downward trend.
Signal Confirmation: Look for the oscillator to cross key levels (like +/-40 or +/-60) in the direction of a suspected trend as a confirmation signal.
Divergence Analysis: When the price makes a new high or low that is not confirmed by a new high or low on the FSVZO oscillator (a divergence), it can be a warning of potential weakness in the trend. The "ℝ" and "ℍ" labels help to identify these scenarios.
Extreme Readings: Readings near the +85 or -85 levels can indicate that a price move may be overextended, which could precede a pause or reversal.
Customization Options
The indicator includes settings groups that allow you to adjust its behavior and appearance:
FSVZO Settings: Adjust parameters like Length and Sensitivity to make the oscillator more or less responsive to market movements.
Signals & Display: Modify visual aspects such as Smooth Length and Glowing Amount, or toggle features like the dynamic background on and off.
Colors: Choose from several pre-set color palettes to suit your visual preferences.
⚠️Disclaimer
This indicator is a tool for technical analysis and does not provide guaranteed results. It should be used in conjunction with other analysis methods and proper risk management practices. The creators of this indicator are not responsible for any financial decisions made based on its signals.
Oscillator Matrix [Alpha Extract]A comprehensive multi-oscillator system that combines volume-weighted money flow analysis with enhanced momentum detection, providing traders with a unified framework for identifying high-probability market opportunities across all timeframes. By integrating two powerful oscillators with advanced confluence analysis, this indicator delivers precise entry and exit signals while filtering out market noise through sophisticated threshold-based regime detection.
🔶 Volume-Weighted Money Flow Analysis
Utilizes an advanced money flow calculation that tracks volume-weighted price movements to identify institutional activity and smart money flow. This approach provides superior signal quality by emphasizing high-volume price movements while filtering out low-volume market noise.
// Volume-weighted flows
up_volume = price_up ? volume : 0
down_volume = price_down ? volume : 0
// Money Flow calculation
up_vol_sum = ta.sma(up_volume, mf_length)
down_vol_sum = ta.sma(down_volume, mf_length)
total_volume = up_vol_sum + down_vol_sum
money_flow_ratio = total_volume > 0 ? (up_vol_sum - down_vol_sum) / total_volume : 0
🔶 Enhanced Hyper Wave Oscillator
Features a sophisticated MACD-based momentum oscillator with advanced normalization techniques that adapt to different price ranges and market volatility. The system uses percentage-based calculations to ensure consistent performance across various instruments and timeframes.
// Enhanced MACD-based oscillator
fast_ma = ta.ema(src, hw_fast)
slow_ma = ta.ema(src, hw_slow)
macd_line = fast_ma - slow_ma
signal_line = ta.ema(macd_line, hw_signal)
// Proper normalization using percentage of price
price_base = ta.sma(close, 50)
macd_normalized = macd_line / price_base
hyper_wave = macd_range > 0 ? macd_normalized / macd_range : 0
🔶 Multi-Factor Confluence System
Implements an intelligent confluence scoring mechanism that combines signals from both oscillators to identify high-probability trading opportunities. The system assigns strength scores based on multiple confirmation factors, significantly reducing false signals.
🔶 Fixed Threshold Levels
Uses predefined threshold levels optimized for standard oscillator ranges to distinguish between normal market fluctuations and significant momentum shifts. The dual-threshold system provides clear visual cues for overbought/oversold conditions while maintaining consistent signal criteria across different market conditions.
🔶 Overflow Detection Technology
Advanced overflow indicators identify extreme market conditions that often precede major reversals or continuation patterns. These signals highlight moments when market momentum reaches critical levels, providing early warning for potential turning points.
🔶 Dual Oscillator Integration
The indicator simultaneously tracks volume-weighted money flow and momentum-based price action through two independent oscillators. This dual approach ensures comprehensive market analysis by capturing both institutional activity and technical momentum patterns.
// Multi-factor confluence scoring
confluence_bull = (mf_bullish ? 1 : 0) + (hw_bullish ? 1 : 0) +
(mf_overflow_bull ? 1 : 0) + (hw_overflow_bull ? 1 : 0)
confluence_bear = (mf_bearish ? 1 : 0) + (hw_bearish ? 1 : 0) +
(mf_overflow_bear ? 1 : 0) + (hw_overflow_bear ? 1 : 0)
confluence_strength = confluence_bull > confluence_bear ? confluence_bull / 4 : -confluence_bear / 4
🔶 Intelligent Signal Generation
The system generates two tiers of reversal signals: strong signals that require multiple confirmations across both oscillators, and weak signals that identify early momentum shifts. This hierarchical approach allows traders to adjust position sizing based on signal strength.
🔶 Visual Confluence Zones
Background coloring dynamically adjusts based on confluence strength, creating visual zones that immediately communicate market sentiment. The intensity of background shading corresponds to the strength of the confluent signals, making pattern recognition effortless.
🔶 Threshold Visualization
Color-coded threshold zones provide instant visual feedback about oscillator positions relative to key levels. The fill areas between thresholds create clear overbought and oversold regions with graduated color intensity.
🔶 Candle Color Integration
Optional candle coloring applies confluence-based color logic directly to price bars, creating a unified visual framework that helps traders correlate indicator signals with actual price movements for enhanced decision-making.
🔶 Overflow Alert System
Specialized circular markers highlight extreme overflow conditions on both oscillators, drawing attention to potential climax moves that often precede significant reversals or accelerated trend continuation.
🔶 Customizable Display Options
Comprehensive display controls allow traders to toggle individual components on or off, enabling focused analysis on specific aspects of the indicator. This modularity ensures the indicator adapts to different trading styles and analytical preferences.
1 Week
1 Day
15 Min
This indicator provides a complete analytical framework by combining volume analysis with momentum detection in a single, coherent system. By offering multiple confirmation layers and clear visual hierarchies, it empowers traders to identify high-probability opportunities while maintaining precise risk management across all market conditions and timeframes. The sophisticated confluence system ensures that signals are both timely and reliable, making it an essential tool for serious technical analysts.
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.
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.
