VEMA Band_v2 - 'Centre of GravityConcept taken from the MT4 indicator 'Centre of Gravity'except this one doesn't repaint.
Modified / BinaryPro 3 / Permanent Marker
Ema configuration instead of sma & centralised.
"binary"に関するスクリプトを検索
Vdub_Tetris_Stoch_V1Vdub_Tetris_Stoch_V1
A combination lower based indicators based on the period channel indicator Vdub_Tetris_V2
Blue line is more reactive fast moving, Red line in more accurate to highs / Lows with divergence.- Still testing
Code title error
Change % = Over Bought / Over Sold
Vdub Tetris_V2
Vdubus BinaryPro 2 /Tops&Bottoms
StochDM
Risk AlignmentRisk Alignment evaluates whether market conditions favor risk-on or risk-off behavior by assessing the alignment of BTC and the OTHERS index.
It uses two independent signals: the direction of the 12/25 EMA stack and price position relative to those EMAs, each classified as bullish, bearish, or neutral.
These signals are combined into a six-state regime framework:
Bullish, Neutral-Bullish, Conflicting, Neutral-Bearish, Bearish, or No Signal
This provides a clear hierarchy of conviction rather than a binary output.
It is designed to function as a top-down macro filter, helping traders gate exposure, size risk, and avoid periods of structural disagreement.
It is best used as a regime context layer, not as a standalone entry signal.
DafeVisualsLibDafeVisualsLib: The Architect - The Intelligent Visualization Engine
This is not a library of drawing functions. This is an AI-powered artist and data scientist that lives in your code. It automates the complex, time-consuming process of data analysis and visualization, allowing you to focus on what truly matters: your trading ideas.
█ CHAPTER 1: THE PHILOSOPHY - BEYOND PLOTTING, INTO PERCEPTION
For too long, the world of technical indicator development has been bifurcated. On one side, you have the quantitative analyst, obsessed with mathematical purity but often displaying their work in a crude, unintuitive manner. On the other, you have the visual designer, creating beautiful indicators that often lack analytical depth. The result for the end-user is a compromise: either a tool that is powerful but ugly and hard to interpret, or one that is beautiful but analytically shallow.
The DafeVisualsLib was created to shatter this compromise. Its core philosophy is that great analysis and great visualization are not separate disciplines; they are two sides of the same coin . An indicator should not just present data; it should communicate intelligence. It should automatically understand the nature of the data it is given and render it in the most effective, intuitive, and aesthetically pleasing way possible.
This library is an "Architect." You provide it with the raw materials—a simple data series like an RSI or a moving average—and it handles the entire complex process of analysis, configuration, and rendering. It is the ultimate accelerator for developers, saving hundreds of hours of boilerplate code, and the ultimate upgrade for traders, providing a level of clarity and visual intelligence previously unseen on this platform.
█ CHAPTER 2: THE CORE INNOVATION - THE "ANALYZE, THEN RENDER" PARADIGM
The DafeVisualsLib operates on a revolutionary two-stage pipeline that sets it apart from any other tool.
STAGE 1: The analyze() Function (The Data Scientist)
This is the brain. Before a single line is drawn, this function performs a sophisticated statistical analysis on your raw data series to understand its fundamental character. It asks the critical questions that a human analyst would:
What type of data is this? It automatically detects if your data is a bounded "oscillator" like an RSI, a zero-centric "momentum" indicator like MACD, a "price"-based line like a moving average, or a "volume"-based metric.
What is the current market regime? It analyzes the data's volatility (using the coefficient of variation) to classify the current environment as a low-volatility "squeeze," a moderate-volatility "trend," or a high-volatility "volatile" state.
Where is the data in its cycle? It normalizes the data to a 0-100 scale and determines if it is currently at a statistical "extreme."
The output of this stage is a MetricAnalysis object—a complete analytical report on the DNA of your data.
STAGE 2: The auto_config() Function (The Artist & Physicist)
This is where the magic happens. This function takes the analytical report from analyze() and uses it to make a series of intelligent, context-aware decisions about how the data should be visualized.
Intelligent Color Logic: It doesn't just use one color. For an oscillator, it will create a beautiful heatmap gradient. For a momentum indicator, it will use a binary bull/bear color scheme.
Neon Physics: It separates the color into a solid c_core and a transparent c_glow. The opacity of the glow is not static; it is dynamically controlled by the detected market regime. In a "volatile" regime, the glow becomes bright and intense. In a "squeeze," it becomes dim and subtle.
Adaptive Style & Width: It automatically adjusts the plot style and line width. A "momentum" indicator will be rendered as a histogram by default. A "price" line will be thick and bold in a volatile market and thin and clean in a calm market.
Smart Zones: If it detects that the data is an "oscillator," it will automatically recommend showing overbought/oversold zones and provide the standard 70/30 levels.
The output of this stage is a PlotConfig object—a complete, ready-to-use set of plotting instructions, intelligently tailored to your specific data and the current market conditions.
█ CHAPTER 3: THE DEVELOPER'S TOOLKIT - A MASTERCLASS IN EFFICIENCY
This library is a gift to Pine Script developers. It is a suite of powerful, high-level functions designed to simplify your workflow and elevate your final product.
The Theme Engine
Forget hard-coding colors. The get_theme() function provides access to a library of professionally designed, high-contrast color themes ("Neon," "Cyber," "Matrix," "Gold," etc.). Each Theme object contains a complete palette for primary, secondary, accent, bull, bear, and neutral colors, ensuring perfect visual consistency across your entire indicator.
The UI & HUD Helpers
Building user interfaces with tables can be tedious. This library provides a suite of helper functions to make it effortless.
smart_text(): Automatically selects black or white text for optimal contrast against any background color.
draw_bar(): Creates a clean, beautiful ASCII progress bar from a simple percentage value.
draw_stars(): Creates a five-star rating visualization.
gradient_color(): A powerful function for creating smooth color transitions.
get_signal_style() & get_zone_style(): High-level functions that return complete styling configurations for signals and support/resistance zones based on your chosen theme.
The Simplicity of Integration: A 4-Step Workflow
The true beauty of the DafeVisualsLib is its simplicity. You can create a stunning, intelligent, and fully functional indicator in just four steps:
Import the library: import YourUsername/DafeVisualsLib/1 as viz
Get your theme: viz.Theme theme = viz.get_theme("Neon")
Calculate your metric: float rsi = ta.rsi(close, 14)
Let the Architect do the work: viz.PlotConfig cfg = viz.auto_config(rsi, "RSI", theme)
Plot the result: plot(cfg.value, cfg.title, cfg.c_core, cfg.width)
In these few lines, the library has automatically analyzed your RSI, determined the market regime, selected the appropriate plot style, calculated a dynamic color gradient with a physics-based glow, and adapted the line width to the current volatility. This is the power of the Architect.
█ CHAPTER 4: DEVELOPMENT PHILOSOPHY
The DafeVisualsLib was born from a desire to democratize elite-level indicator design. For too long, the ability to create beautiful, context-aware, and intuitively designed indicators has been the domain of a select few developers with deep knowledge of both programming and graphic design. This library changes that. It is an open-source tool that encapsulates thousands of hours of research and development into a simple, powerful API.
My philosophy is that a developer's most valuable asset is their idea. They should be free to focus on inventing new, powerful analytical concepts, without getting bogged down in the tedious, repetitive work of building robust visualization and configuration systems from scratch. This library is my contribution to the Pine Script community—a tool for builders, designed to accelerate innovation and elevate the quality of indicators for everyone.
This library embraces that philosophy. It handles immense complexity on the backend to deliver absolute simplicity and elegance on the frontend, both for the developer who uses it and the trader who benefits from it.
█ A NOTE TO USERS & DISCLAIMER
THIS IS A LIBRARY FOR DEVELOPERS: This script does nothing on its own. It is a powerful engine that must be imported and used by other indicator developers in their own scripts. It is a tool for building, not a ready-made indicator.
THE ANALYSIS IS A GUIDE: The analyze() function's classification of data and regimes is based on a robust set of heuristics, but it is a statistical interpretation. It provides a powerful baseline for visualization but is not a substitute for a trader's own judgment.
"Simplicity is the ultimate sophistication."
— Leonardo da Vinci
Taking you to school. - Dskyz, Create with DAFE
Commodity Channel Index - CCI🎯 Overview
This is an enhanced Commodity Channel Index (CCI) indicator that transforms the traditional CCI into a centerline-focused momentum tool with moving average smoothing and comprehensive visual enhancements. Unlike standard CCI which uses ±100 levels, this version focuses on the 50-level centerline for clearer trend direction signals.
🧩 Core Components
1. ⚙️ Technical Foundation
📊 Primary Calculation: Uses TradingView's built-in ta.cci() function
📈 Statistical Approach: Measures current price relative to statistical mean
🎯 Scale Modification: Focuses on 50 as neutral (unlike traditional ±100)
📏 Default Length: 55 periods (optimal for medium-term trends)
2. 🎛️ Configuration Parameters
📏 CCI Length: Default 55 periods
📈 CCI MA Length: 30-period moving average
🔄 MA Type: 6 options (EMA, SMA, RMA, WMA, VWMA, HMA)
🎨 Color Themes: 5 visual schemes matching your other indicators
📈 Signal Interpretation:
🟢 BULLISH: CCI > 50 (price above statistical mean)
🔴 BEARISH: CCI < 50 (price below statistical mean)
👁️ Visual Features
📉 Chart Elements:
📊 Main CCI Line:
Shows raw CCI momentum
📈 Signal Line (CCI MA):
Yellow moving average of CCI
30-period default provides smoothed trend
🎨 Fill Zones:
🟢 Upper Zone : Bullish momentum area
🔴 Lower Zone : Bearish momentum area
📋 Dashboard Display:
Content: "⬆️ Bullish" or "⬇️ Bearish" indicator
Purpose: Instant market bias assessment
⚡ Trading Applications
📈 Primary Uses:
🎯 Trend Direction Identification
CCI > 50 = Uptrend momentum
CCI < 50 = Downtrend momentum
📊 Extreme Momentum Detection
CCI > 100 = Strong bullish (traditional)
CCI < -100 = Strong bearish (traditional)
CCI near ±300 = Extreme conditions
🔄 Mean Reversion Opportunities
Useful in ranging markets
🎯 Signal Types:
📈 Trend-Following: Stay long when CCI > 50, short when < 50
🔄 Mean Reversion: Fade extreme readings (>100 or <-100)
⚡ Crossover Signals: CCI crossing 50 provides entry/exit points
🎨 Customization Options
🔄 Moving Average Types:
📉 EMA: Exponential - responsive to recent CCI changes
📊 SMA: Simple - smooths CCI equally
📈 RMA: Relative - TradingView's special MA
⚖️ WMA: Weighted - emphasizes recent CCI values
💎 VWMA: Volume-weighted - incorporates volume indirectly
🚀 HMA: Hull - reduces lag on CCI signals
🎨 Visual Themes: (Consistent with your suite)
🎨 Classic: Green/Red (traditional)
🚀 Modern: Cyan/Purple (contemporary)
💪 Robust: Amber/Deep Purple (high contrast)
🌈 Accented: Purple/Magenta (vibrant)
⚫⚪ Monochrome: Light Gray/Dark Gray (minimalist)
🔔 Alert System
🟢 LONG Alert: Triggers when CCI > 50
🔴 SHORT Alert: Triggers when CCI < 50
📧 Format: Includes ticker symbol for portfolio tracking
⚡ Key Advantages
✅ Strengths:
🎯 Clear Centerline Focus: 50-level provides unambiguous trend direction
📊 Statistical Foundation: Based on mean deviation (more robust than simple oscillators)
👁️ Extreme Zone Visualization: ±300 boundaries show momentum extremes
🔄 Versatile Application: Works for both trend-following and mean reversion
📱 Professional Suite: Consistent design with your RSI and SMI indicators
⚡ Optimal Settings:
📈 Trending Markets: 55-period CCI (default)
🔄 Ranging Markets: Shorter periods (20-30)
📊 Volatile Markets: Longer periods (80-100)
📱 Day Trading: 20-period with EMA smoothing
🏆 Unique Features:
Statistical Rigor: Based on mean deviation (not just price differences)
Wide Range: ±300 scale captures extreme movements
Centerline Focus: Clear binary trend signals
Visual Harmony: Consistent with your indicator suite design
This CCI indicator provides a statistically robust approach to trend identification while maintaining the visual consistency and user-friendly design of your trading suite! 📊✨
Adaptive Kinetic Ribbon [QuantAlgo]🟢 Overview
The Adaptive Kinetic Ribbon indicator synthesizes price velocity and volatility dynamics to identify trend direction, momentum strength, and acceleration phases across varying market conditions. It combines velocity-based momentum measurement, adaptive volatility weighting, dual-speed ribbon analysis, and acceleration-deceleration detection into a unified visual system that quantifies periods of sustained directional movement and momentum shifts, helping traders and investors identify trend continuation and reversal signals across various timeframes and asset classes.
🟢 How It Works
The indicator's core methodology lies in its adaptive kinetic approach, where velocity and volatility components are calculated dynamically and then smoothed through an adaptive alpha mechanism.
First, Velocity is measured to capture raw directional momentum by calculating the net price change over the lookback period:
velocity = source - source
This creates a momentum vector that quantifies how far and in which direction price has moved, providing the foundation for understanding trend strength and establishing whether the market is in a sustained directional phase.
Then, Volatility is computed to evaluate price variability and market noise by analyzing the standard deviation of bar-to-bar price changes:
volatility = ta.stdev(source - source , length) * mult
The volatility sensitivity multiplier allows traders to adjust how responsive the indicator is to market noise, with higher values creating faster adaptation during volatile periods and lower values maintaining stability during choppy conditions.
Next, Adaptive Alpha is calculated to create a dynamic smoothing coefficient that automatically adjusts based on the relationship between velocity and volatility:
adaptive_alpha = math.abs(velocity) / (math.abs(velocity) + volatility)
This alpha value ranges from 0 to 1, where values closer to 1 indicate strong, clear directional movement (high velocity relative to volatility), causing the indicator to respond quickly, while values closer to 0 indicate noisy, range-bound conditions (high volatility relative to velocity), causing the indicator to smooth more heavily and filter out false signals.
Following this, the Kinetic Line is constructed using exponential smoothing with the adaptive alpha coefficient:
var float kinetic_line = na
kinetic_line := na(kinetic_line ) ? source : kinetic_line + adaptive_alpha * (source - kinetic_line )
This creates an adaptive moving average that automatically adjusts its responsiveness: during strong trends with clear velocity, it tracks price closely like a fast EMA; during choppy, volatile periods, it smooths heavily like a slow SMA, providing optimal trend identification across varying market regimes without manual parameter adjustment.
Then, Ribbon Lines are generated by applying additional moving average smoothing to the kinetic line at two different speeds:
ribbon_fast = ma(kinetic_line, ribbon_fast_length, ma_type)
ribbon_slow = ma(kinetic_line, ribbon_slow_length, ma_type)
The dual-ribbon structure creates a visual envelope around the kinetic line, where the fast ribbon responds quickly to kinetic changes while the slow ribbon provides trend confirmation, with crossovers between these ribbons generating primary trend reversal signals.
Finally, Trend State and Acceleration are determined by analyzing the relative positioning and directional movement of the ribbon lines:
trend_up = ribbon_fast > ribbon_slow
acceleration = ribbon_fast > ribbon_fast
ribbonColor = trend_up ?
acceleration ? bullAccel : bullDecel :
not acceleration ? bearAccel : bearDecel
This creates a four-state classification system that distinguishes between bullish acceleration (uptrend strengthening), bullish deceleration (uptrend weakening), bearish acceleration (downtrend strengthening), and bearish deceleration (downtrend weakening), providing traders with nuanced momentum insights beyond simple bullish/bearish binary signals.
🟢 Signal Interpretation
▶ Bullish Acceleration (Bright Green): Fast ribbon above slow ribbon AND fast ribbon rising, indicating confirmed uptrend with building momentum = Strongest bullish condition, ideal for new long entries, adding to positions, or holding existing longs with confidence
▶ Bullish Deceleration (Dark Green): Fast ribbon above slow ribbon BUT fast ribbon falling, indicating uptrend intact but momentum weakening = Caution signal for longs, potential trend exhaustion developing, consider tightening stops or taking partial profits
▶ Bearish Acceleration (Bright Red): Fast ribbon below slow ribbon AND fast ribbon falling, indicating confirmed downtrend with building momentum = Strongest bearish condition, ideal for new short entries, exiting longs, or maintaining defensive positioning
▶ Bearish Deceleration (Dark Red): Fast ribbon below slow ribbon BUT fast ribbon rising, indicating downtrend intact but momentum weakening = Caution signal for shorts, potential trend exhaustion developing, prepare for possible reversal or consolidation
▶ Bullish Crossover: Fast ribbon crosses above slow ribbon, signaling trend reversal from bearish to bullish and initiation of new upward momentum phase = Primary buy signal, entry opportunity for trend-following strategies, exit signal for short positions
▶ Bearish Crossover: Fast ribbon crosses below slow ribbon, signaling trend reversal from bullish to bearish and initiation of new downward momentum phase = Primary sell signal, entry opportunity for short strategies, exit signal for long positions
▶ Ribbon Spread Width: Distance between fast and slow ribbons indicates trend strength and conviction, where wider spreads suggest strong, sustained directional movement with low reversal probability, while tight or converging ribbons indicate weak trends, consolidation, or impending reversal conditions
▶ Bar Color Alignment: When bar coloring is enabled, candlestick colors mirror the ribbon state providing immediate visual confirmation of momentum conditions directly on price action, eliminating the need to reference the indicator separately and enabling faster decision-making during active trading
🟢 Features
▶ Preconfigured Presets: Three optimized parameter configurations accommodate different trading styles, timeframes, and market analysis approaches: "Default" provides balanced trend identification suitable for swing trading on 4-hour and daily charts, "Fast Response" delivers heightened sensitivity optimized for intraday trading and scalping on 5-minute to 1-hour charts, and "Smooth Trend" offers conservative trend identification ideal for position trading and long-term analysis on daily to weekly charts.
▶ Built-in Alerts: Three alert conditions enable comprehensive automated monitoring of trend reversals and momentum transitions. "Bullish Crossover" triggers when the fast ribbon crosses above the slow ribbon, signaling the shift from downtrend to uptrend and the beginning of bullish momentum building. "Bearish Crossover" activates when the fast ribbon crosses below the slow ribbon, signaling the shift from uptrend to downtrend and the beginning of bearish momentum building. "Any Ribbon Crossover" provides a combined notification for either bullish or bearish crossover regardless of direction, useful for general trend reversal monitoring and ensuring no momentum shift goes unnoticed.
▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Cyber, Neon, plus Custom) accommodate different chart backgrounds and visual preferences, ensuring optimal contrast and immediate identification of acceleration versus deceleration states across various devices and screen sizes. Each preset uses distinct colors for the four momentum states (bullish acceleration, bullish deceleration, bearish acceleration, bearish deceleration) with proper visual hierarchy. Optional bar coloring with adjustable transparency provides instant visual context of current momentum state and trend direction without switching between the price pane and indicator pane, enabling traders and investors to immediately assess trend positioning and acceleration dynamics while analyzing price action patterns and support/resistance levels.
MA Smart SyncMA Smart Sync determines the market bias by evaluating the price position relative to a moving average channel on four independent timeframes and returning a confluence signal when a configurable number of them agree.
Unlike standard MTF trend indicators that rely on EMA crossovers or slope direction, this script builds a channel around each timeframe and classifies price into three discrete zones: above, below, or inside. The "inside" state acts as a neutral filter, preventing false confluence signals during consolidation — a key distinction from binary up/down dashboards.
The channel itself can be constructed using five different methods selectable from a single input: High/Low MA (separate MAs applied to high and low), Close ± ATR, Close ± Standard Deviation, Close ± percentage offset, or classic Bollinger Bands. All five use the same MA type and length inputs, making it straightforward to compare how different volatility envelopes behave on the same instrument without rebuilding the indicator.
How to use:
— Set four timeframes matching your trading plan (defaults: 15m, 1h, 4h, D).
— Choose the channel method that fits your instrument's volatility profile. ATR-based channels adapt well to forex; StdDev and Bollinger suit equities and indices.
— Set "Minimum Confluence" to 3 or 4. A value of 4 means all timeframes must agree before a signal fires.
— The background color and arrow labels update only when bias changes, keeping the chart clean.
— Use the status table (top-right) to monitor each timeframe independently and identify which TFs are lagging.
SENTINEL CORE by Pipsomnian🛡️ Sentinel Core — Learning Mode (Structure & Probability Engine)
by Pipsomnian
Sentinel Core is the core structure and probability framework within the Sentinel ecosystem.
It is designed to help traders move beyond binary signals and learn how to grade market environments based on structure, momentum, and session quality.
This tool does not predict price.
It evaluates context.
🎯 What Sentinel Core Is
Sentinel Core is an EMA-structured learning and decision-grading indicator built to train:
• Trend alignment
• Pullback behavior
• Market structure continuation
• Session discipline (London & New York)
• Probability stacking
Instead of asking “Is there a signal?”,
Sentinel Core trains you to ask:
“How strong is this setup?”
🧠 The Scoring Concept
Each potential setup is evaluated using multiple structural components:
• EMA trend alignment
• Pullback to value
• Strong candle confirmation
• Market structure continuation
• Active trading session
The result is a setup quality grade:
• A+ → Full structural alignment
• B → Strong but incomplete alignment
Lower-quality environments are intentionally ignored.
This encourages patience, selectivity, and discipline.
🟢 Who Sentinel Core Is For
Sentinel Core is designed for traders who:
• Already understand basic EMA structure
• Want fewer, higher-quality setups
• Trade session-based markets (especially Gold)
• Value discipline over frequency
• Want to develop judgment, not dependency
🚫 What Sentinel Core Is NOT
Sentinel Core is not:
• A signal service
• An automated strategy
• A promise of profitability
• A replacement for risk management
• A shortcut to consistency
Execution, risk control, and psychology remain your responsibility.
⏱️ Recommended Use
• Timeframe: 5-Minute
• Markets: XAUUSD (Gold), major FX, liquid indices
• Sessions: London & New York
EMAs are used for structure and context, not prediction.
🧭 Position in the Sentinel Framework
• Sentinel Lite — Learn structure & discipline
• Sentinel Core — Grade probability & judgment
• Sentinel A+ — Refine timing & precision
• Sentinel Gold Standard — Execute with control
⚠️ Educational use only. No financial advice.
— Pipsomnian
Tanh Clamped Momentum Oscillator [Alpha Extract]A sophisticated momentum measurement system that combines dual EMA trend analysis with volatility-weighted pressure calculations, applying hyperbolic tangent normalization for bounded oscillator output with adaptive signal generation. Utilizing ATR-based volatility regime detection and candle pressure metrics, this indicator delivers institutional-grade momentum assessment with multi-tiered band structure and pulse-based envelope visualization. The system's tanh clamping methodology prevents extreme outliers while maintaining sensitivity to genuine momentum shifts, combined with histogram divergence detection and comprehensive alert framework for high-probability reversal and continuation signals.
🔶 Advanced Dual-Component Momentum Engine
Implements hybrid calculation combining EMA trend differential with candle pressure analysis, weighted by volatility regime assessment for context-aware momentum measurement. The system calculates fast and slow EMA difference normalized by ATR, measures intrabar pressure as close-open relative to range, applies volatility-based weighting between trend and pressure components, and produces composite raw momentum capturing both directional bias and internal candle dynamics.
// Core Momentum Framework
EMA_Fast = ta.ema(src, Fast_Length)
EMA_Slow = ta.ema(src, Slow_Length)
Trend = EMA_Fast - EMA_Slow
// Volatility Regime Detection
ATR_Short = ta.atr(ATR_Length)
ATR_Long = ta.atr(ATR_Length * 2)
Vol_Ratio = ATR_Short / ATR_Long
Vol_Weight = clamp((Vol_Ratio - 0.5) / 1.0, 0, 1)
// Pressure Component
Pressure = (close - open) / (high - low)
// Composite Momentum
Raw = Trend_Normalized * Vol_Weight + Pressure_Scaled * (1 - Vol_Weight)
🔶 Hyperbolic Tangent Normalization Framework
Features sophisticated tanh transformation that clamps raw momentum into bounded range while preserving proportional sensitivity across varying market conditions. The system applies safe exponential calculations with input capping to prevent overflow, computes hyperbolic tangent to compress extreme values while maintaining linearity near zero, and scales output by configurable factor creating oscillator with enhanced dynamic range and reduced outlier distortion.
// Tanh Clamping Logic
tanh(x) =>
x_clamped = clamp(x, -5.0, 5.0)
e = exp(2.0 * x_clamped)
(e - 1.0) / (e + 1.0)
Oscillator = tanh(Smoothed_Momentum / Clamp_Factor) * Scale
🔶 Volatility Regime Weighting System
Implements intelligent volatility assessment comparing short-term and long-term ATR to determine market regime, dynamically adjusting weight between trend and pressure components. The system calculates ATR ratio, normalizes to 0-1 range, and uses this weight factor to emphasize trend component during high-volatility regimes and pressure component during low-volatility consolidations, creating adaptive momentum sensitive to market microstructure.
🔶 Multi-Tiered Band Architecture
Provides comprehensive threshold structure with soft, hard, and maximum bands marking progressive momentum extremes for graduated overbought/oversold assessment. The system establishes configurable levels at soft zones (initial caution), hard zones (strong extreme), and maximum zones (critical overextension) with visual differentiation through line styles and background highlighting, enabling nuanced interpretation beyond binary extreme detection.
🔶 Pulse Envelope Visualization
Features dynamic envelope bands calculated from exponential moving average of absolute oscillator value, creating adaptive boundary that expands during momentum acceleration and contracts during deceleration. The system applies configurable length and width multiplier to pulse calculation, fills area between positive and negative pulse bounds with gradient coloring matching oscillator direction, providing visual context for momentum magnitude relative to recent activity.
🔶 Signal Line Integration Framework
Implements dual-mode signal line supporting both EMA and SMA smoothing of primary oscillator for crossover-based swing detection. The system calculates configurable-length moving average, generates histogram differential between oscillator and signal, applies additional smoothing to histogram for noise reduction, and uses crossovers/crossunders as momentum swing indicators distinguishing bullish and bearish momentum shifts.
🔶 Histogram Divergence Display
Creates column-style histogram visualization showing oscillator-signal differential with intensity-based coloring reflecting momentum acceleration or deceleration. The system plots histogram bars in bright colors when expanding (accelerating momentum) and faded colors when contracting (decelerating momentum), enabling instant visual identification of momentum divergences and convergences without numerical analysis.
🔶 Advanced Reversion Signal Logic
Generates overbought/oversold signals requiring both signal line crossover and extreme threshold breach for high-conviction reversal identification. The system triggers oversold when oscillator crosses above signal while below negative reversion level, triggers overbought when crossing below signal while above positive reversion level, and plots small circle markers at signal locations for clear visual confirmation of setup conditions.
🔶 Comprehensive Alert Framework
Provides six distinct alert conditions covering overbought/oversold reversions, midline trend changes, and oscillator-signal swings with configurable notification preferences. The system includes alerts for extreme reversions (OB/OS), zero-line crossovers (trend changes), and signal line crossovers (momentum swings), enabling traders to monitor critical oscillator events across multiple signal types without constant chart observation.
🔶 Adaptive Bar Coloring System
Implements four coloring modes including midline cross (trend direction), extremities (threshold breach), reversions (OB/OS signals), and slope (oscillator vs signal) for customizable visual integration. The system applies selected color scheme to candles providing chart-level momentum feedback, with option to disable coloring for minimal visual interference while maintaining oscillator pane analysis.
🔶 Performance Optimization Architecture
Utilizes efficient tanh calculation with safe clamping, streamlined EMA computations, and optimized ATR ratio processing for smooth real-time updates. The system includes intelligent null handling, minimal recalculation overhead through smart smoothing application, and configurable display toggles allowing users to disable unused visual elements for enhanced performance during extended historical analysis.
🔶 Why Choose Tanh-Clamped Momentum Oscillator ?
This indicator delivers sophisticated momentum analysis through hybrid trend-pressure calculation with volatility-adaptive weighting and hyperbolic tangent normalization. Unlike traditional momentum oscillators susceptible to extreme outlier distortion, the tanh clamping ensures bounded output while preserving sensitivity to genuine momentum shifts. The system's dual-component architecture combining directional trend with intrabar pressure, weighted by volatility regime assessment, creates context-aware momentum measurement that adapts to market microstructure. The multi-tiered band structure, pulse envelope visualization, and comprehensive signal framework make it essential for traders seeking nuanced momentum analysis with graduated extreme detection and high-probability reversal signals across cryptocurrency, forex, and equity markets.
TPOSmartMoneyLibLibrary "TPOSmartMoneyLib"
Library for TPO (Time Price Opportunity) and Smart Money concepts including session management, PDH/PDL detection, sweeping logic, and volume profile utilities
f_price_to_tick(p)
Convert price to tick
Parameters:
p (float) : Price value
Returns: Tick value
f_tick_to_row(t, row_ticks_in)
Convert tick to row
Parameters:
t (int) : Tick value
row_ticks_in (int) : Number of ticks per row
Returns: Row index
f_row_to_price(row, row_ticks_in)
Convert row to price (midpoint)
Parameters:
row (int) : Row index
row_ticks_in (int) : Number of ticks per row
Returns: Price at row midpoint
f_calc_row_ticks(natr_ref, row_gran_mult)
Calculate dynamic row size based on normalized ATR
Parameters:
natr_ref (float) : Daily normalized ATR reference value
row_gran_mult (float) : Row granularity multiplier
Returns: Number of ticks per row
f_more_transp_pct(c, pct)
Increase color transparency by percentage
Parameters:
c (color) : Input color
pct (float) : Percentage to increase transparency (0.0 to 1.0)
Returns: Color with increased transparency
f_dom_color(dom, buy_col, sell_col, gamma, transp_weak, transp_strong)
Calculate dominance color based on buy/sell ratio
Parameters:
dom (float) : Dominance ratio (-1 to 1, negative = sell, positive = buy)
buy_col (color) : Buy dominant color
sell_col (color) : Sell dominant color
gamma (float) : Gamma correction for color intensity
transp_weak (int) : Transparency for weak dominance
transp_strong (int) : Transparency for strong dominance
Returns: Blended color
f_sess_part(sess_str, get_start)
Parse session string to get start or end time
Parameters:
sess_str (string) : Session string in format "HHMM-HHMM"
get_start (bool) : True to get start time, false to get end time
Returns: Time string in HHMM format
f_hhmm_to_h(hhmm)
Convert HHMM string to hours
Parameters:
hhmm (string) : Time string in HHMM format
Returns: Hours (0-23)
f_hhmm_to_m(hhmm)
Convert HHMM string to minutes
Parameters:
hhmm (string) : Time string in HHMM format
Returns: Minutes (0-59)
f_prev_day_window_bounds(today_day_rth, win_start, win_end, session_tz)
Calculate previous day window bounds
Parameters:
today_day_rth (int) : Today's RTH start timestamp
win_start (string) : Window start time in HHMM format
win_end (string) : Window end time in HHMM format
session_tz (string) : Session timezone
Returns: Tuple of
f_default_session_colors()
Get default session colors
Returns: Array of 4 colors
f_session_names()
Get session names
Returns: Array of 4 session names
f_process_hl(arr, rng, keep_bars, lock_to_live)
Process high/low lines with sweeping detection
Parameters:
arr (array) : Array of HLLine objects
rng (float) : Price range for visibility filtering
keep_bars (int) : Maximum bars to keep lines
lock_to_live (bool) : Whether to lock line end to current bar
Returns: 0 (for chaining)
f_process_naked_lines(arr, calc_bars, bars_per_day, keep_to_day_end)
Process naked lines (POC/VAH/VAL) with sweeping detection
Parameters:
arr (array) : Array of NakedLine objects
calc_bars (int) : Maximum calculation bars
bars_per_day (int) : Bars per day for scope calculation
keep_to_day_end (bool) : Whether to extend to day end
Returns: 0 (for chaining)
f_update_pdhl_lines(pd_hl, pdh, pdl, new_day, pd_rng, bars_per_day, pdh_color, pdl_color)
Detect and create PDH/PDL lines
Parameters:
pd_hl (array) : Array to store HLLine objects
pdh (float) : Previous day high
pdl (float) : Previous day low
new_day (bool) : Whether it's a new day
pd_rng (float) : Price range for visibility
bars_per_day (int) : Bars per day
pdh_color (color) : PDH line color
pdl_color (color) : PDL line color
Returns: 0 (for chaining)
f_poc_from_vals(keys, vals)
Calculate POC from sorted keys and values
Parameters:
keys (array) : Sorted array of row keys
vals (array) : Array of volume values
Returns: POC row key
f_value_area(keys, vals, poc_key, va_pct)
Calculate Value Area from volume distribution
Parameters:
keys (array) : Sorted array of row keys
vals (array) : Array of volume values
poc_key (int) : POC row key
va_pct (float) : Value Area percentage (typically 0.70)
Returns: Tuple of
f_find_key_sorted(keys, target)
Find key in sorted array using binary search
Parameters:
keys (array) : Sorted array of keys
target (int) : Target key to find
Returns: Index of key, or -1 if not found
f_zscore_safe(x, len)
Safe z-score calculation using built-in functions
Parameters:
x (float) : Input series
len (int) : Lookback length
Returns: Z-score
HLLine
Represents a high/low line with sweeping detection
Fields:
ln (series line) : Line object
lb (series label) : Label object
lvl (series float) : Price level
startBar (series int) : Bar index where line starts
swept (series bool) : Whether the level has been swept
isHigh (series bool) : True if this is a high, false if low
col (series color) : Line color
NakedLine
Represents a naked POC/VAH/VAL line
Fields:
ln (series line) : Line object
lb (series label) : Label object
lvl (series float) : Price level
startBar (series int) : Bar index where line starts
swept (series bool) : Whether the level has been swept
sweptBar (series int) : Bar index where swept occurred
endBar (series int) : Bar index where line should end
Neeson Trend Price Oscillator Pulse EditionNeeson Trend Price Oscillator Pulse Edition: A Comprehensive Market Cycle Analysis Tool
Overview and Purpose
The Trend Price Oscillator Pulse Edition is a sophisticated technical analysis indicator designed to identify major market cycle tops and bottoms. This tool operates as a standalone oscillator in a subchart, providing clear visual signals of overbought and oversold conditions within the context of long-term market cycles. Developed for position traders and long-term investors, it focuses on capturing significant market turning points rather than short-term fluctuations.
Integration Rationale and Component Synergy
The indicator integrates three core analytical concepts into a cohesive system:
Detrended Price Oscillator (DPO) Foundation: Traditional DPO methodology isolates cyclical price movements by removing the underlying trend component. This creates a clearer view of oscillatory behavior without the distortion of long-term directional bias.
Normalization Framework: By converting raw DPO values to a standardized 0-100 scale, the indicator establishes consistent reference points for market extremes across different instruments and timeframes. This normalization enables meaningful comparison of oscillator readings regardless of absolute price levels.
Dynamic Threshold System: The implementation of adjustable threshold levels (default: 95% for overbought, 5% for oversold) creates adaptive boundaries that respond to changing market volatility and cycle characteristics.
These components work synergistically: The DPO extracts cyclical information from price action, the normalization process standardizes this information for consistent interpretation, and the threshold system provides actionable decision points based on historical extremes.
Operational Mechanism
The indicator calculates a detrended price value by comparing current price against a displaced moving average. This detrended value is then normalized against its historical range over a specified lookback period, transforming it into a percentage-based oscillator. A smoothing filter is applied to reduce noise and highlight significant movements.
The oscillator's movement through threshold zones generates four distinct market signals:
Entry into overbought territory (crossing above 95%)
Exit from overbought territory (crossing below 95%)
Entry into oversold territory (crossing below 5%)
Exit from oversold territory (crossing above 5%)
Each signal corresponds to a specific market condition hypothesis regarding institutional versus retail trader dynamics in major market cycles.
Practical Application Guidelines
Primary Use Cases:
Identification of potential major cycle turning points on weekly and monthly timeframes
Confirmation tool for existing trading strategies requiring cycle analysis
Risk management through recognition of extreme market conditions
Interpretation Framework:
Overbought Conditions (Oscillator ≥ 95%): Suggest potential selling pressure from major market participants. Consider reducing long exposure or implementing protective measures.
Oversold Conditions (Oscillator ≤ 5%): Indicate potential accumulation zones by institutional buyers. Consider establishing or adding to long positions using dollar-cost averaging strategies.
Threshold Crossings: Monitor for exits from extreme zones as potential confirmation that a cycle peak or trough may have formed.
Parameter Considerations:
Default parameters (548-period oscillator, 274-period offset, 1096-period lookback) are optimized for identifying major market cycles. Users may adjust these values for different market conditions or timeframes, though significant parameter changes will alter the indicator's sensitivity and signal frequency.
Originality and Distinctive Features
This implementation incorporates several innovative aspects:
Extended Cycle Focus: Unlike most oscillators designed for shorter timeframes, this tool employs exceptionally long calculation periods specifically for identifying primary market cycles.
Dynamic Normalization: The lookback-based normalization adapts to changing market conditions without requiring manual recalibration.
Multi-Signal Alert System: Four distinct alert conditions provide nuanced information about market state transitions rather than simple binary signals.
Integrated Risk Context: Each signal includes contextual information about potential market participant behavior, encouraging disciplined risk management.
Empirical Considerations and Limitations
The indicator provides probabilistic assessments based on historical price behavior, not predictive certainties. Market conditions may change, rendering historical patterns less reliable. Users should consider:
The indicator performs best in trending or cyclical markets; it may generate false signals during extended range-bound periods.
No technical indicator, including this one, can guarantee future market movements.
Proper position sizing and risk management should accompany all trading decisions, regardless of indicator signals.
Expected User Outcomes
When used as part of a comprehensive trading plan, this indicator can help users:
Identify potential reversal zones in major market cycles
Develop patience by focusing on significant rather than frequent trading opportunities
Maintain objective perspective during market extremes through quantitative assessment
Coordinate entry and exit timing with cycle analysis
The Trend Price Oscillator Pulse Edition represents a specialized tool for traders seeking to align their strategies with major market cycles through systematic analysis of price oscillation behavior relative to long-term trends.
Luminous Volume Flow [Pineify]Luminous Volume Flow
The Luminous Volume Flow is a specialized volume-based momentum oscillator designed to uncover the underlying buying and selling pressure within the market. Unlike traditional volume indicators that simply aggregate volume based on the close relative to the open, LVF analyzes intrabar dynamics—specifically the relationship between the close price and the high/low wicks—to estimate the dominance of buyers or sellers.
By smoothing this raw volume delta and applying a signal line, the LVF provides a clear visual representation of volume flow, helping traders identify trend strength, potential reversals, and momentum shifts with high-definition "luminous" visuals.
Key Features
Intrabar Pressure Analysis : Calculates buying and selling pressure based on wick dynamics and price polarity to provide a more granular view of market sentiment.
Multi-Type Smoothing : Offers selectable Moving Average types (SMA, EMA, RMA) for the main Flow Line to adapt to different market volatilities.
Luminous Visuals : Utilizes dynamic color gradients that brighten as momentum expands and darken as it contracts, offering immediate visual feedback on trend intensity.
Sentiment Cloud : Fills the area between the Flow and Signal lines to clearly visualize the prevailing bullish or bearish sentiment.
High-Contrast Signals : Optional high-contrast signal markers for clear crossover identification.
How It Works
The LVF operates on a multi-stage calculation process:
Pressure Calculation : The script compares the lower wick (Close - Low) against the upper wick (High - Close).
If the lower wick is longer, it suggests buying pressure (rejection of lower prices), and volume is assigned to Buy Pressure .
If the upper wick is longer, it suggests selling pressure (rejection of higher prices), and volume is assigned to Sell Pressure .
If equal, the Close > Open polarity is used as a tie-breaker.
Raw Delta : The difference between Buy and Sell Pressure is calculated to determine the net volume flow for the bar.
Flow Line : The Raw Delta is smoothed using a user-selected Moving Average (SMA, EMA, or RMA) over the Flow Length period. This creates the main oscillator line.
Signal Line : An EMA of the Flow Line is calculated to generate the Signal Line, similar to the MACD mechanic.
Histogram : The difference between the Flow Line and Signal Line determines the Histogram, which drives the "Luminous" color gradient logic.
Trading Ideas and Insights
Trend Confirmation : When the Flow Line is above the Signal Line and the Cloud is green, the bullish trend is supported by volume. Conversely, a red cloud indicates bearish volume dominance.
Momentum Crossovers : The triangle shapes indicate crossovers between the Flow and Signal lines. A triangle up (Green) suggests a potential bullish entry or invalidation of a short bias. A triangle down (Red) suggests a bearish turn.
Expansion vs. Contraction : Pay attention to the brightness of the histogram columns. Bright colors indicate expanding momentum (a strong move), while darker, fading colors suggest the move is losing steam, potentially preceding a consolidation or reversal.
How multiple components work together
This script combines the logic of Volume Delta analysis with Signal Line Crossover mechanics (popularized by MACD). By applying trend-following smoothing to raw volume data, we transform erratic volume spikes into a coherent flow. The "Luminous" visual layer is added to make the data interpretation intuitive—removing the need to mentally calculate the rate of change based on histogram height alone.
Unique Aspects
Adaptive Gradient Coloring : The histogram doesn't just show positive/negative values; it visually communicates the *acceleration* of the move via color intensity based on standard deviation.
Wick-Based Volume Attribution : Instead of a binary close-to-open comparison, LVF respects the price action within the candle (the wicks), acknowledging that a long lower wick on a red candle can actually represent significant buying interest.
How to Use
Add the indicator to your chart.
Adjust the Flow Length to match your trading timeframe (lower for scalping, higher for swing trading).
Select your preferred Smoothing Type (EMA is default and recommended for responsiveness).
Use the "Sentiment Cloud" filter: Look for long signals only when the cloud is green, and short signals when the cloud is red.
Monitor the Luminous Histogram for signs of exhaustion (colors fading) to manage exits.
Customization
Flow Length : Period for the main smoothing (Default: 14).
Signal Length : Period for the signal line (Default: 9).
Smoothing Type : Choose between SMA, EMA, or RMA.
Colors : Fully customizable colors for Bullish/Bearish phases and signals.
Chart Bars : Option to color the main chart candles based on the Flow direction.
Conclusion
The Luminous Volume Flow is a robust tool for traders who want to go beyond price action and understand the volume dynamics driving the market. By visualizing the flow of buying and selling pressure with advanced smoothing and reactive visuals, it provides a clearer picture of market sentiment than standard volume bars.
Neeson Vegas ChannelVegas Channel Indicator: A Comprehensive Multi-Timeframe Trend-Following System
Originality and Conceptual Foundation
This script implements an enhanced version of the classic "Vegas Tunnel" or "Vegas Channel" methodology, popularized by traders who follow the work associated with the "Vegas" technique. Its primary original contribution lies in its specific, rule-based multi-layered trend identification and visualization system. While the core uses well-known Exponential Moving Averages (EMAs), the originality is in the precise combination of periods and the strict, hierarchical logic for defining trend states and generating signals.
Unlike simpler moving average crossovers or single-tunnel systems, this script employs three distinct EMA pairs, each serving a unique purpose within the trend hierarchy:
Short-Term Momentum Pair (EMA 12 & 24): Acts as the primary signal trigger and momentum gauge.
Core Trend Tunnel (EMA 144 & 169): Serves as the central "channel" or "tunnel." A key visual and logical component is the shading between these two lines, which thickens and changes color with the trend, creating a dynamic channel.
Long-Term Foundation Pair (EMA 580 & 670): Represents the underlying, slower-moving trend foundation, providing context for the higher-timeframe bias.
The system's true innovation is its binary and exclusive trend definition logic. It does not rely on a single crossover. Instead, it defines a confirmed Uptrend only when both the short-term EMAs (12 and 24) are established above both lines of the core tunnel (144 and 169). Conversely, a Downtrend is confirmed only when both short-term EMAs are established below both core tunnel lines. This creates a high-confidence filter, reducing whipsaw signals that can occur when price oscillates around a single moving average.
Functionality, Implementation, and Usage
What It Does:
This indicator is a multi-timeframe trend identification and signal-generation tool. It visually condenses trend information from short, medium, and long-term perspectives onto a single chart. Its primary functions are:
Trend State Classification: It dynamically classifies the market into one of three states: Bull Trend (Blue), Bear Trend (Orange), or Sideways/Congestion (Gray). This is reflected in the chart's background color, the color of all EMA lines, and the fill of the central 144/169 channel.
Signal Generation: It plots discrete buy and sell arrows. A Buy Signal (blue upward triangle) appears the first bar the market transitions into the defined "Uptrend" state from a non-uptrend state. A Sell Signal (orange downward triangle) appears the first bar the market transitions into the defined "Downtrend" state.
Visual Structuring: It plots all six EMAs and prominently highlights the interaction zone between the 144 and 169 EMAs with a colored fill, making the "tunnel" a focal point for support/resistance and trend quality assessment.
How It's Implemented:
The logic is implemented through a clear sequence of conditional checks:
Calculation: All six EMAs are calculated based on user-definable periods (defaults as listed).
Trend Logic: The script continuously evaluates the position of EMA12 and EMA24 relative to EMA144 and EMA169 using strict AND conditions to define the uptrend and downtrend Boolean variables.
Signal Logic: A signal (buy or sell) is generated only on the change of the trend state. It uses a check of the form current_trend_state AND (NOT previous_bar_trend_state) to pinpoint the exact bar of transition.
Visual Feedback: All plot colors, the channel fill color, and the background color are unified and determined by the current trend state variable. Labels for the trend and each EMA line are drawn on the last bar for clarity.
How to Use It:
Traders employ this indicator primarily for trend-following and breakout confirmation. It is suited for swing trading or higher-timeframe positional trades rather than scalping, due to the lag inherent in its longer EMAs and its focus on confirmed states.
Trend Bias: The overall color scheme (blue/orange/gray background) provides an immediate, at-a-glance assessment of the dominant trend force. Trading in the direction of the colored background is considered aligned with the system's trend.
Signal Entry: The arrow signals are not meant for blind entry. They mark the point of a confirmed trend state transition.
A Buy Signal suggests the short-term momentum (12,24) has decisively broken above and established itself over the medium-term trend framework (144,169). This could be used as a trigger for long entries, preferably with the long-term EMAs (580,670) sloping upwards or flat, adding confluence.
A Sell Signal suggests the opposite breakdown.
Channel as Dynamic S/R: The filled area between EMA144 and EMA169 acts as a dynamic support zone in an uptrend and a resistance zone in a downtrend. Pullbacks into this "tunnel" that hold without triggering a sell signal (i.e., without both EMA12 & 24 closing back below both tunnel lines) can be viewed as potential continuation opportunities.
Filter for Other Systems: The clear trend state (uptrend/downtrend) can be exported or used as a filter for other trading systems or discretionary decisions, ensuring actions are only taken in the direction of the script's defined trend.
Core Computational Philosophy and Strategic Rationale
The script's logic is rooted in the philosophy of trend hierarchy and confirmation. It belongs to the category of Multi-Moving Average Convergence/Divergence Systems with State-Based Rules.
The 144/169 Tunnel: These numbers are derived from Fibonacci sequences (144, 169 is 12^2 and 13^2). They are believed by proponents to represent a natural rhythm or "heartbeat" of the market, defining a robust intermediate-term trend framework.
The 12/24 Pair: A standard fast-moving average pair commonly used to gauge short-term momentum and trigger entries.
The Strategic Innovation (Dual-Condition Crossover): The core idea is that a crossover of a single fast MA above a single slow MA can be false and noisy. By requiring both members of a fast pair to establish position relative to both members of a slower "tunnel" pair, the system demands a broader, more concerted move. This seeks to filter out weak, unsustainable breaks and only capture shifts in momentum strong enough to flip the entire short-term structure's position relative to the medium-term structure.
The 580/670 Pair: These very slow EMAs represent the "secular" trend. While not part of the direct signal logic, they provide critical context. A buy signal that occurs while price is above the 580/670 pair (which would be sloping up in a healthy bull market) carries more weight than one that occurs while price is below this long-term foundation, which might indicate a counter-trend rally.
In essence, this script is more than just moving averages on a chart. It is a systematic, rule-based framework for identifying when the market's short-term energy (12,24) has converged sufficiently to overcome and reposition itself against its medium-term equilibrium (144/169 tunnel), thereby signaling a high-probability phase change in trend, all while considering the backdrop of a long-term trend (580/670).
BTC - Satoshis Altcoin Graveyard OVERVIEW
The Satoshi's Altcoin Graveyard (SAG) is a macro-statistical engine designed to solve the problem of Survivorship Bias . It is a well-known phenomenon in the crypto markets that the "Top 10" list is in a constant state of flux. If you look at historical data from CoinMarketCap (CMC) year by year, you will see a revolving door of projects that once seemed "too big to fail" disappearing into obscurity. Meanwhile, Bitcoin has remained the undisputed #1 since inception.
While most traders have a "gut feeling" that Altcoins eventually depreciate against Bitcoin, I believe in measuring it and drawing it on a chart for better visibility. By locking in specific "Cohorts" of market leaders from the past, we can track their inevitable decay through the Satoshi Sieve .
THE 13-COIN STATISTICAL BUCKET
To ensure an objective, non-biased audit, each cohort (we look at 2018, 2020 and 2022) is constructed using a fixed market-cap methodology from the snapshot date (excluding stablecoins):
• The Core: The Top 10 non-stablecoin assets at that time by Marketcap.
• The Risk Alpha: Representative samples from the Top #25, #50, and #100 ranks. (By including lower-ranked "riskier" alts, we capture the full statistical decay of the market, not just the "Blue Chips.")
TECHNICAL ARCHITECTURE
This script is engineered to push the boundaries of the Pine Script engine. TradingView enforces a hard limit of 40 unique data requests . By tracking 3 cohorts of 13 assets plus the Bitcoin base, this indicator utilizes exactly 40/40 requests , providing the maximum possible data density in a single chart window.
THE SPS CONCEPT (Survival Probability Score)
The SPS measures the Breadth of Survival . It answers: "How many coins from this year (the year of the snapshot) are actually outperforming BTC?"
We use a binary logic system to determine if a coin is "Winning" or "Losing" against the only benchmark that matters: Bitcoin.
• The Status Formula: Status = Current_Alt_BTC_Ratio >= Entry_Alt_BTC_Ratio ? 1 : 0 . This means: Every single day, at the Daily Close , the script compares the current Alt/BTC ratio to the fixed ratio from the snapshot date. If the coin is worth more in Bitcoin today than it was back then, it is assigned a "1" (a Win). If it has lost value against Bitcoin, it gets a "0" (a Loss).
• The SPS Line: SPS Line = (Sum of 'Wins' / 13) * 100 This means: We add up all the "Winners" for that specific day and turn it into a percentage. For example, if the Aqua line is at 7.69% on your chart, it confirms that on that day , exactly 1 out of the 13 coins was successfully beating Bitcoin, while the other 12 were underperforming.
THE PERFORMANCE MATRIX
In the top-right corner, we provide a Weighted Portfolio Simulation . This answers the financial question: "If I swapped 1 BTC into an equal-weight basket of these 13 coins on the snapshot day, what is my BTC value today?".
• Value < 1.0 BTC: You lost purchasing power compared to holding Bitcoin.
• Value > 1.0 BTC: You successfully achieved "Alpha" over the benchmark.
HOW TO READ THE CHART
• The Waterfall: Lines generally trend downward as the "Satoshi Sieve" filters out assets that cannot maintain their BTC-relative value.
• Dynamic Winners: We dynamically print the names of the current survivors at the tip of each line. If a cohort shows "None," the graveyard is full.
HOW TO READ THE MATRIX
• The BTC Target: Any portfolio value in the matrix below 1.0 BTC represents a failed altcoin rotation.
• Class of 2018: A portfolio value near 0.15 BTC at the current date, means a 85% loss rate.
• Class of 2020: A portfolio value near 0.77 BTC at the current date, means an approx 20 % loss rate.
• Class of 2022: A portfolio value near 0.31 BTC at the current date, means an approx 70% loss rate.
DIFFERENCE FROM AN ALTCOIN INDEX
Standard Altcoin Indexes (like my ALSI Index ) "rebalance" by removing losers and adding new winners. This is deceptive. The Altcoin Graveyard never rebalances . It forces you to watch the "losers" decay, providing a realistic look at the long-term opportunity cost of "Buy and Hold" for anything other than Bitcoin.
CONCLUSION
The data revealed by the Satoshi Sieve leads to a singular, sobering "Lesson Learned": Picking the right coin to outperform Bitcoin is not just difficult—it is statistically improbable over a long-term horizon.
While the "Risk-Reward" of altcoins is often marketed as having higher upside, the Altcoin Graveyard proves that for the vast majority of assets, the reward does not justify the risk of total portfolio erosion in BTC terms.
• The Mathematical Odds: If you picked a Top 10 coin in 2018, your chance of outperforming BTC today is effectively 0%.
• The Rotation Trap: Most investors "HODL" these assets into the graveyard, hoping for a return to previous ATHs that never comes because the liquidity has already moved on to the next "Class" of winners.
The final conclusion is clear: Diversification into altcoins is often just a slow-motion transfer of wealth back to Bitcoin. If you cannot identify the 1-out-of-13 that survives the Sieve, your best risk-adjusted move has historically been to simply hold the benchmark.
DISCLAIMER
This script is for educational purposes only. It does not constitute financial advice. It is a mathematical study of historical opportunity cost and survivorship bias.
Tags
bitcoin, btc, satoshis graveyard, altseason, dominance, total3, rotation, cycle, index, alsi, Rob Maths, robmaths
MAD Supertrend [Alpha Extract]A sophisticated SuperTrend implementation that replaces traditional ATR calculations with Mean Absolute Deviation methodology for adaptive volatility measurement and band construction. Utilizing SMA baseline with MAD-based deviation bands and optional adaptive factor adjustments, this indicator delivers institutional-grade trend detection with strength-based filtering and dynamic visual feedback. The system's MAD approach provides superior noise reduction compared to ATR while maintaining responsiveness to genuine volatility changes, combined with momentum-based strength calculations for high-conviction signal generation.
🔶 Advanced MAD-Based Band Construction
Implements Mean Absolute Deviation calculation as volatility proxy, measuring absolute price deviations from mean and smoothing for stable band generation without ATR dependency. The system calculates SMA baseline, computes MAD from configurable lookback period, applies factor multipliers to create upper and lower bands, then implements classic SuperTrend ratcheting logic where bands only adjust when price violates previous levels or calculations warrant updates.
// Core MAD SuperTrend Framework
SMA_Value = ta.sma(src, SMA_Length)
Mean = ta.sma(src, MAD_Length)
Abs_Deviation = abs(src - Mean)
MAD_Value = ta.sma(Abs_Deviation, MAD_Length)
// Band Construction with Ratcheting
Upper_Band = SMA_Value + MAD_Factor * MAD_Value
Lower_Band = SMA_Value - MAD_Factor * MAD_Value
// Ratcheting logic prevents premature band adjustments
🔶 Adaptive Factor Adjustment Engine
Features optional adaptive multiplier system that modulates MAD factor based on normalized MAD magnitude relative to recent extremes, creating bands that automatically expand during high-volatility regimes and contract during consolidation. The system applies min-max normalization to MAD values over configurable lookback, multiplies by adaptation parameter, and adds to base factor for dynamic volatility sensitivity without manual recalibration.
🔶 Momentum-Based Strength Filter
Implements sophisticated strength calculation measuring price momentum relative to baseline divided by volatility-adjusted MAD bands, producing normalized 0-1 strength scores with exponential smoothing. The system calculates distance from SMA baseline, normalizes by MAD-derived band width, and applies configurable minimum threshold requiring sufficient momentum before trend signals activate, filtering weak or choppy market conditions.
🔶 SuperTrend Direction Logic
Utilizes classic SuperTrend methodology adapted for MAD bands where trend direction flips on opposite band violations with state persistence until confirmation. The system tracks whether price closes above upper band (bearish flip to bullish) or below lower band (bullish flip to bearish), maintains directional state until opposing violation occurs, and generates binary +1/-1 trend signals suitable for systematic position management.
🔶 Intelligent Candle Sticking System
Provides advanced line positioning option that anchors SuperTrend line to candle wicks or bodies rather than pure calculation values for enhanced visual clarity. The system supports two modes: Wick (positions at high/low extremes based on trend direction) and Body (constrains line between calculation and candle extremes), creating cleaner chart presentation while maintaining mathematical integrity of underlying signals.
🔶 Dynamic Gradient Visualization Framework
Implements color intensity modulation based on smoothed strength calculations, transitioning from muted to vivid hues as momentum conviction increases. The system applies gradient interpolation using strength ratio, creating visual feedback where strong trending moves display intense colors while weak or consolidating conditions show faded tones across trend line, channel bands, and candle coloring for immediate regime assessment.
🔶 MAD Channel Architecture
Features volatility-adjusted channel bands centered on baseline or candle-stuck line with configurable multiplier for support/resistance visualization. The system calculates upper and lower bounds using MAD values scaled by adaptive factors and channel multipliers, applies dynamic transparency based on trend strength, and creates filled regions that intensify during strong trends and fade during weak conditions.
🔶 Multi-Layer Glow Effect System
Provides sophisticated line rendering with triple-layer plot system creating glow effect through progressively wider and more transparent outer layers. The system plots core trend line at specified width with full color intensity, adds inner glow layer at +2 width with moderate transparency, and outer glow at +4 width with higher transparency, creating visual depth and emphasis without cluttering chart space.
🔶 Strength-Based State Management
Implements intelligent trend state logic requiring both directional signal and minimum strength threshold breach before confirming trend transitions. The system calculates raw SuperTrend direction, evaluates smoothed strength against configurable minimum, generates filtered trend state that can be bullish (+1), bearish (-1), or neutral (0), and maintains state persistence using hold logic that prevents oscillation during ambiguous conditions.
🔶 Comprehensive Alert Integration
Generates trend flip alerts when filtered state transitions from bearish to bullish or bullish to bearish with full confirmation requirements satisfied. The system detects state changes through comparison with previous bar, triggers single alert per transition rather than continuous notifications, and provides customizable message templates for automated trading system integration or manual notification preferences.
🔶 Performance Optimization Architecture
Utilizes efficient calculation methods with null value handling, nz() functions preventing errors during initialization bars, and optimized gradient calculations. The system includes intelligent state persistence minimizing recalculation overhead, streamlined MAD computation avoiding redundant mean calculations, and smooth visual updates maintaining consistent performance across extended historical periods.
This indicator delivers sophisticated SuperTrend analysis through Mean Absolute Deviation methodology providing superior statistical properties compared to traditional ATR-based approaches. MAD calculations offer more robust volatility measurement resistant to extreme outliers while maintaining sensitivity to genuine market regime changes. The system's adaptive factor adjustment, momentum-based strength filtering, and dynamic visual feedback make it essential for traders seeking reliable trend-following signals with reduced false breakouts during choppy conditions. The combination of MAD bands, candle-sticking options, gradient strength visualization, and comprehensive filtering creates institutional-grade trend detection suitable for systematic approaches across cryptocurrency, forex, and equity markets with clear entry/exit signals and comprehensive alert capabilities.
Sizing Coach HUD Long and Short This HUD is designed as a systematic execution layer to bridge the gap between technical analysis and mechanical risk management. Its primary purpose is to eliminate the "discretionary gap"—the moment where a trader’s "feeling" about volatility or spreads causes hesitation.
By using this tool, you are not just watching price; you are managing a business where Risk is a constant and Size is a variable.
Core Functionality: The Position Sizing Engine
The HUD automates the math of "Capital-Based Tiers". Instead of choosing an arbitrary share size, the system calculates your position based on three predefined levels of conviction:
Tier 1 (1% Notional): Low-confidence or high-volatility "tester" positions.
Tier 2 (3% Notional): Standard, high-probability setups.
Tier 3 (5% Notional): High-conviction trades where multiple timeframes and factors align.
Execution Workflow (The Poka-Yoke)
To use this HUD effectively and eliminate the "hesitation" identified in the Five Whys analysis, follow this workflow:
Toggle Direction: Set the HUD to Long or Short based on your setup (e.g., NEMA Continuation).
Define Invalidation: Identify your technical stop (default is High/Low of Day +/- 5%). The HUD will automatically calculate the distance to this level.
Check Risk $: Observe the Risk $ row. This tells you exactly how much you will lose in dollars if the stop is hit. If the volatility is extreme (like the NASDAQ:SNDK 14% plunge), the HUD will automatically shrink your Shares count to keep this dollar amount constant.
Execute via HUD: Transmit the order using the Shares provided in your selected Tier. Do not manually adjust the size based on "gut feeling".
Trade Management: The "R" Focus
The bottom half of the HUD displays your Targets (PnL / R).
VWAP & Fibonacci Levels: Automatically plots and calculates profit targets at key institutional levels (VWAP, 0.618, 0.786, 0.886).
Binary Exit Logic: The color-coded logic flags any target that yields less than 1R (Reward-to-Risk) as a warning.
Systematic Holding: Ride the trade to the targets or until your technical exit (e.g., 1M candle close above/below NEMA) is triggered, ignoring the fluctuating P&L.
Aura Squeeze Projections [Pineify]Pineify - Aura Squeeze Projections
This indicator combines the volatility compression detection of the TTM Squeeze methodology with an innovative "aura glow" visualization, offering traders a clear and aesthetically distinct way to identify low-volatility consolidation phases and anticipate breakout directions. By merging Bollinger Bands, Keltner Channels, and linear regression momentum analysis, the Aura Squeeze Projections provides actionable squeeze signals with directional bias.
Key Features
Visual "aura glow" effect highlighting squeeze zones and momentum shifts
Squeeze detection combining Bollinger Bands and Keltner Channels
Linear regression-based momentum for directional bias
Dynamic candle coloring reflecting current market state
Squeeze start and release signal markers
How It Works
The core logic identifies volatility compression by comparing Bollinger Bands to Keltner Channels. When the Bollinger Bands contract inside the Keltner Channel boundaries (BB upper < KC upper AND BB lower > KC lower), the market enters a "squeeze" state — a period of low volatility that often precedes significant price movement.
Momentum direction is calculated using a linear regression slope of the difference between price and its moving average. A positive slope indicates bullish momentum; negative indicates bearish momentum. This determines the anticipated breakout direction when the squeeze releases.
How Multiple Indicators Work Together
Bollinger Bands measure statistical volatility through standard deviation, expanding during high volatility and contracting during consolidation. Keltner Channels use Average True Range (ATR) for a smoother volatility envelope. When BB fits entirely within KC, volatility has compressed below normal levels — the squeeze condition.
The linear regression momentum component adds directional intelligence. Rather than simply detecting compression, it forecasts the likely breakout direction by analyzing the trend slope of price deviation from its mean. This synergy transforms a binary squeeze signal into an actionable directional setup.
Unique Aspects
The "aura glow" visualization creates gradient fills between the trend midline and Keltner boundaries, providing an intuitive heat-map style view of market conditions. Colors transition dynamically: gray during squeeze (consolidation), green for bullish momentum, and red for bearish momentum. This makes market state immediately recognizable at a glance.
How to Use
Watch for the gray squeeze state indicating volatility compression
Note the circle marker appearing above bars when squeeze begins
Observe when the diamond marker appears below bars — squeeze release
The color at release (green/red) indicates anticipated breakout direction
Use candle coloring for confirmation of momentum alignment
Customization
Lookback Length : Adjusts sensitivity (shorter = more signals, longer = fewer but stronger)
BB/KC Multipliers : Fine-tune squeeze detection threshold
Use EMA : Toggle between EMA (smoother) or SMA for the midline basis
Aura Transparency : Control visual intensity of the glow effect
Conclusion
Aura Squeeze Projections offers a refined approach to squeeze-based trading by combining proven volatility compression detection with momentum-based directional analysis and distinctive visual presentation. The indicator helps traders identify consolidation periods and prepare for breakouts with directional confidence. Best used alongside price action analysis and support/resistance levels for confirmation.
Volume-Adjusted CCI Trend [Alpha Extract]A sophisticated trend identification system that combines dual EMA direction analysis with volume-weighted normalization and CCI momentum filtering for comprehensive trend validation. Utilizing Volume RSI integration and standard deviation-based bands that expand and contract with volume characteristics, this indicator delivers institutional-grade trend detection with multi-layered confirmation requirements. The system's volume adjustment mechanism modulates signal sensitivity based on participation strength while CCI thresholds prevent false signals during weak momentum conditions, creating a robust trend-following framework with reduced whipsaw susceptibility.
🔶 Advanced Dual EMA Direction Engine
Implements fast and slow exponential moving average comparison to establish primary trend direction bias with configurable period parameters for timeframe optimization. The system calculates trend direction as binary +1 (bullish when fast EMA exceeds slow EMA) or -1 (bearish when slow exceeds fast), providing foundational directional input that requires additional confirmation before generating actionable trend states.
🔶 Volume-Adjusted Normalization Framework
Features sophisticated normalization calculation that measures price deviation from basis EMA, scales by standard deviation, then applies volume-weighted adjustment factor for participation-sensitive signal generation. The system calculates Volume RSI to quantify relative volume strength, converts to ratio format, and multiplies normalized deviation by volume factor scaled by impact parameter, creating signals that strengthen during high-volume confirmations and weaken during low-volume moves.
// Volume-Adjusted Normalization
Vol_Ratio = Volume_RSI / 50
Vol_Factor = 1 + (Vol_Ratio - 1) * Vol_Impact
Dev = src - Basis_EMA
Raw_Normalized = Dev / (StdDev * Multiplier)
Vol_Adjusted_Norm = Raw_Normalized * Vol_Factor
🔶 CCI Momentum Filter Integration
Implements Commodity Channel Index threshold system with configurable upper and lower bounds to validate trend strength and filter sideways market conditions. The system calculates standard CCI with adjustable length, compares against asymmetric thresholds (default +100 bullish, -50 bearish), and requires CCI confirmation in addition to EMA direction and normalized deviation before transitioning trend states, ensuring only high-conviction signals generate entries.
🔶 Multi-Layer Trend State Logic
Provides intelligent trend state machine requiring simultaneous confirmation from EMA direction, volume-adjusted normalization threshold breach, and optional CCI momentum validation. The system maintains persistent trend state that only transitions when all three conditions align, preventing premature reversals during temporary retracements or low-volume fluctuations while capturing genuine trend changes with institutional-grade confirmation requirements.
🔶 Dynamic Volume Band Architecture
Creates volatility-adjusted bands around basis EMA using standard deviation multiplied by volume factor, producing channels that widen during high-volume periods and contract during low-volume consolidations. The system applies identical volume adjustment to band calculations as normalization metric, ensuring visual envelope consistency with underlying signal logic and providing intuitive reference boundaries for trend-following price action.
🔶 Gradient Strength Visualization System
Implements color intensity modulation based on normalized signal strength relative to threshold requirements, creating visual feedback that communicates trend conviction. The system calculates strength ratio by dividing absolute normalized value by threshold, caps at 1.0, and applies gradient interpolation from muted to vivid colors, instantly conveying whether current trend exhibits marginal or strong characteristics through line and candle coloring.
🔶 Volume RSI Calculation Engine
Utilizes RSI methodology applied to volume series rather than price to quantify relative participation strength with normalization to 0.5-1.5 range for factor multiplication. The system processes volume through standard RSI calculation, divides by 50 to center around 1.0, and produces ratio values where readings above 1.0 indicate above-average volume and below 1.0 suggest below-average participation for signal adjustment purposes.
🔶 Asymmetric Threshold Configuration
Features separate positive and negative normalization thresholds with independent CCI upper and lower bounds enabling optimization for bullish versus bearish signal generation characteristics. The system defaults to symmetric normalized thresholds (±0.2) but asymmetric CCI levels (+100/-50), recognizing that bullish momentum often requires stronger confirmation than bearish reversals in typical market structures.
🔶 Comprehensive Visual Integration
Provides multi-dimensional trend visualization through color-coded basis line, volume-adjusted bands with gradient fills, trend-synchronized candle coloring, and transition signal labels. The system enables selective display toggling for each visual component while maintaining consistent color scheme and strength-based intensity across all elements for cohesive chart presentation without overwhelming information density.
🔶 Alert and Signal Framework
Generates trend change alerts when state transitions occur with all confirmation requirements satisfied, providing notifications for bullish (transition to +1) and bearish (transition to -1) signals. The system implements state change detection through comparison with previous bar trend state, ensuring single alert per transition rather than continuous notifications during sustained trends.
🔶 Performance Optimization Architecture
Employs efficient calculation methods with null value handling for Volume RSI initialization and nz() functions preventing calculation errors during early bars. The system includes intelligent state persistence maintaining previous trend during ambiguous conditions and optimized gradient calculations balancing visual quality with computational efficiency across extended historical periods.
🔶 Why Choose Volume-Adjusted CCI Trend ?
This indicator delivers sophisticated trend identification through multi-layered confirmation combining directional EMA analysis, volume-weighted normalization, and momentum validation via CCI filtering. Unlike traditional trend indicators relying solely on price-based calculations, the volume adjustment mechanism ensures signals strengthen during high-participation moves and weaken during low-volume drifts, reducing false breakouts and choppy market whipsaws. The system's requirement for simultaneous EMA direction, normalized threshold breach, and CCI momentum confirmation creates institutional-grade signal quality suitable for systematic trend-following approaches across cryptocurrency, forex, and equity markets. The volume-adjusted bands provide dynamic support/resistance references while the gradient strength visualization enables instant assessment of trend conviction for position sizing and risk management decisions.
Intrabar Volume Flow IntelligenceIntrabar Volume Flow Intelligence: A Comprehensive Analysis:
The Intrabar Volume Flow Intelligence indicator represents a sophisticated approach to understanding market dynamics through the lens of volume analysis at a granular, intrabar level. This Pine Script version 5 indicator transcends traditional volume analysis by dissecting price action within individual bars to reveal the true nature of buying and selling pressure that often remains hidden when examining only the external characteristics of completed candlesticks. At its core, this indicator operates on the principle that volume is the fuel that drives price movement, and by understanding where volume is being applied within each bar—whether at higher prices indicating buying pressure or at lower prices indicating selling pressure—traders can gain a significant edge in anticipating future price movements before they become obvious to the broader market.
The foundational innovation of this indicator lies in its use of lower timeframe data to analyze what happens inside each bar on your chart timeframe. While most traders see only the open, high, low, and close of a five-minute candle, for example, this indicator requests data from a one-minute timeframe by default to see all the individual one-minute candles that comprise that five-minute bar. This intrabar analysis allows the indicator to calculate a weighted intensity score based on where the price closed within each sub-bar's range. If the close is near the high, that volume is attributed more heavily to buying pressure; if near the low, to selling pressure. This methodology is far more nuanced than simple tick volume analysis or even traditional volume delta calculations because it accounts for the actual price behavior and distribution of volume throughout the formation of each bar, providing a three-dimensional view of market participation.
The intensity calculation itself demonstrates the coding sophistication embedded in this indicator. For each intrabar segment, the indicator calculates a base intensity using the formula of close minus low divided by the range between high and low. This gives a value between zero and one, where values approaching one indicate closes near the high and values approaching zero indicate closes near the low. However, the indicator doesn't stop there—it applies an open adjustment factor that considers the relationship between the close and open positions within the overall range, adding up to twenty percent additional weighting based on directional movement. This adjustment ensures that strongly directional intrabar movement receives appropriate emphasis in the final volume allocation. The adjusted intensity is then bounded between zero and one to prevent extreme outliers from distorting the analysis, demonstrating careful consideration of edge cases and data integrity.
The volume flow calculation multiplies this intensity by the actual volume transacted in each intrabar segment, creating buy volume and sell volume figures that represent not just quantity but quality of market participation. These figures are accumulated across all intrabar segments within the parent bar, and simultaneously, a volume-weighted average price is calculated for the entire bar using the typical price of each segment multiplied by its volume. This intrabar VWAP becomes a critical reference point for understanding whether the overall bar is trading above or below its fair value as determined by actual transaction levels. The deviation from this intrabar VWAP is then used as a weighting mechanism—when the close is significantly above the intrabar VWAP, buying volume receives additional weight; when below, selling volume is emphasized. This creates a feedback loop where volume that moves price away from equilibrium is recognized as more significant than volume that keeps price near balance.
The imbalance filter represents another layer of analytical sophistication that separates meaningful volume flows from normal market noise. The indicator calculates the absolute difference between buy and sell volume as a percentage of total volume, and this imbalance must exceed a user-defined threshold—defaulted to twenty-five percent but adjustable from five to eighty percent—before the volume flow is considered significant enough to register on the indicator. This filtering mechanism ensures that only bars with clear directional conviction contribute to the cumulative flow measurements, while bars with balanced buying and selling are essentially ignored. This is crucial because markets spend considerable time in equilibrium states where volume is simply facilitating position exchanges without directional intent. By filtering out these neutral periods, the indicator focuses trader attention exclusively on moments when one side of the market is demonstrating clear dominance.
The decay factor implementation showcases advanced state management in Pine Script coding. Rather than allowing imbalanced volume to simply disappear after one bar, the indicator maintains decayed values using variable state that persists across bars. When a new significant imbalance occurs, it replaces the decayed value; when no significant imbalance is present, the previous value is multiplied by the decay factor, which defaults to zero point eight-five. This means that a large volume imbalance continues to influence the indicator for several bars afterward, gradually diminishing in impact unless reinforced by new imbalances. This decay mechanism creates persistence in the flow measurements, acknowledging that large institutional volume accumulation or distribution campaigns don't execute in single bars but rather unfold across multiple bars. The cumulative flow calculation then sums these decayed values over a lookback period, creating a running total that represents sustained directional pressure rather than momentary spikes.
The dual moving average crossover system applied to these volume flows creates actionable trading signals from the underlying data. The indicator calculates both a fast exponential moving average and a slower simple moving average of the buy flow, sell flow, and net flow values. The use of EMA for the fast line provides responsiveness to recent changes while the SMA for the slow line provides a more stable baseline, and the divergence or convergence between these averages signals shifts in volume flow momentum. When the buy flow EMA crosses above its SMA while volume is elevated, this indicates that buying pressure is not only present but accelerating, which is the foundation for the strong buy signal generation. The same logic applies inversely for selling pressure, creating a symmetrical approach to detecting both upside and downside momentum shifts based on volume characteristics rather than price characteristics.
The volume threshold filtering ensures that signals only generate during periods of statistically significant market participation. The indicator calculates a simple moving average of total volume over a user-defined period, defaulted to twenty bars, and then requires that current volume exceed this average by a multiplier, defaulted to one point two times. This ensures that signals occur during periods when the market is actively engaged rather than during quiet periods when a few large orders can create misleading volume patterns. The indicator even distinguishes between high volume—exceeding the threshold—and very high volume—exceeding one point five times the threshold—with the latter triggering background color changes to alert traders to exceptional participation levels. This tiered volume classification allows traders to calibrate their position sizing and conviction levels based on the strength of market participation supporting the signal.
The flow momentum calculation adds a velocity dimension to the volume analysis. By calculating the rate of change of the net flow EMA over a user-defined momentum length—defaulted to five bars—the indicator measures not just the direction of volume flow but the acceleration or deceleration of that flow. A positive and increasing flow momentum indicates that buying pressure is not only dominant but intensifying, which typically precedes significant upward price movements. Conversely, negative and decreasing flow momentum suggests selling pressure is building upon itself, often preceding breakdowns. The indicator even calculates a second derivative—the momentum of momentum, termed flow acceleration—which can identify very early turning points when the rate of change itself begins to shift, providing the most forward-looking signal available from this methodology.
The divergence detection system represents one of the most powerful features for identifying potential trend reversals and continuations. The indicator maintains separate tracking of price extremes and flow extremes over a lookback period defaulted to fourteen bars. A bearish divergence is identified when price makes a new high or equals the recent high, but the net flow EMA is significantly below its recent high—specifically less than eighty percent of that high—and is declining compared to its value at the divergence lookback distance. This pattern indicates that while price is pushing higher, the volume support for that movement is deteriorating, which frequently precedes reversals. Bullish divergences work inversely, identifying situations where price makes new lows without corresponding weakness in volume flow, suggesting that selling pressure is exhausted and a reversal higher is probable. These divergence signals are plotted as distinct diamond shapes on the indicator, making them visually prominent for trader attention.
The accumulation and distribution zone detection provides a longer-term context for understanding institutional positioning. The indicator uses the bars-since function to track consecutive periods where the net flow EMA has remained positive or negative. When buying pressure has persisted for at least five consecutive bars, average intensity exceeds zero point six indicating strong closes within bar ranges, and volume is elevated above the threshold, the indicator identifies an accumulation zone. These zones suggest that smart money is systematically building long positions across multiple bars despite potentially choppy or sideways price action. Distribution zones are identified through the inverse criteria, revealing periods when institutions are systematically exiting or building short positions. These zones are visualized through colored fills on the indicator pane, creating a backdrop that helps traders understand the broader volume flow context beyond individual bar signals.
The signal strength scoring system provides a quantitative measure of conviction for each buy or sell signal. Rather than treating all signals as equal, the indicator assigns point values to different signal components: twenty-five points for the buy flow EMA-SMA crossover, twenty-five points for the net flow EMA-SMA crossover, twenty points for high volume presence, fifteen points for positive flow momentum, and fifteen points for bullish divergence presence. These points are summed to create a buy score that can range from zero to one hundred percent, with higher scores indicating that multiple independent confirmation factors are aligned. The same methodology creates a sell score, and these scores are displayed in the information table, allowing traders to quickly assess whether a signal represents a tentative suggestion or a high-conviction setup. This scoring approach transforms the indicator from a binary signal generator into a nuanced probability assessment tool.
The visual presentation of the indicator demonstrates exceptional attention to user experience and information density. The primary display shows the net flow EMA as a thick colored line that transitions between green when above zero and above its SMA, indicating strong buying, to a lighter green when above zero but below the SMA, indicating weakening buying, to red when below zero and below the SMA, indicating strong selling, to a lighter red when below zero but above the SMA, indicating weakening selling. This color gradient provides immediate visual feedback about both direction and momentum of volume flows. The net flow SMA is overlaid in orange as a reference line, and a zero line is drawn to clearly delineate positive from negative territory. Behind these lines, a histogram representation of the raw net flow—scaled down by thirty percent for visibility—shows bar-by-bar flow with color intensity reflecting whether flow is strengthening or weakening compared to the previous bar. This layered visualization allows traders to simultaneously see the raw data, the smoothed trend, and the trend of the trend, accommodating both short-term and longer-term trading perspectives.
The cumulative delta line adds a macro perspective by maintaining a running sum of all volume deltas divided by one million for scale, plotted in purple as a separate series. This cumulative measure acts similar to an on-balance volume calculation but with the sophisticated volume attribution methodology of this indicator, creating a long-term sentiment gauge that can reveal whether an asset is under sustained accumulation or distribution across days, weeks, or months. Divergences between this cumulative delta and price can identify major trend exhaustion or reversal points that might not be visible in the shorter-term flow measurements.
The signal plotting uses shape-based markers rather than background colors or arrows to maximize clarity while preserving chart space. Strong buy signals—meeting multiple criteria including EMA-SMA crossover, high volume, and positive momentum—appear as full-size green triangle-up shapes at the bottom of the indicator pane. Strong sell signals appear as full-size red triangle-down shapes at the top. Regular buy and sell signals that meet fewer criteria appear as smaller, semi-transparent circles, indicating they warrant attention but lack the full confirmation of strong signals. Divergence-based signals appear as distinct diamond shapes in cyan for bullish divergences and orange for bearish divergences, ensuring these critical reversal indicators are immediately recognizable and don't get confused with momentum-based signals. This multi-tiered signal hierarchy helps traders prioritize their analysis and avoid signal overload.
The information table in the top-right corner of the indicator pane provides real-time quantitative feedback on all major calculation components. It displays the current bar's buy volume and sell volume in millions with appropriate color coding, the imbalance percentage with color indicating whether it exceeds the threshold, the average intensity score showing whether closes are generally near highs or lows, the flow momentum value, and the current buy and sell scores. This table transforms the indicator from a purely graphical tool into a quantitative dashboard, allowing discretionary traders to incorporate specific numerical thresholds into their decision frameworks. For example, a trader might require that buy score exceed seventy percent and intensity exceed zero point six-five before taking a long position, creating objective entry criteria from subjective chart reading.
The background shading that occurs during very high volume periods provides an ambient alert system that doesn't require focused attention on the indicator pane. When volume spikes to one point five times the threshold and net flow EMA is positive, a very light green background appears across the entire indicator pane; when volume spikes with negative net flow, a light red background appears. These backgrounds create a subliminal awareness of exceptional market participation moments, ensuring traders notice when the market is making important decisions even if they're focused on price action or other indicators at that moment.
The alert system built into the indicator allows traders to receive notifications for strong buy signals, strong sell signals, bullish divergences, bearish divergences, and very high volume events. These alerts can be configured in TradingView to send push notifications to mobile devices, emails, or webhook calls to automated trading systems. This functionality transforms the indicator from a passive analysis tool into an active monitoring system that can watch markets continuously and notify the trader only when significant volume flow developments occur. For traders monitoring multiple instruments, this alert capability is invaluable for efficient time allocation, allowing them to analyze other opportunities while being instantly notified when this indicator identifies high-probability setups on their watch list.
The coding implementation demonstrates advanced Pine Script techniques including the use of request.security_lower_tf to access intrabar data, array manipulation to process variable-length intrabar arrays, proper variable scoping with var keyword for persistent state management across bars, and efficient conditional logic that prevents unnecessary calculations. The code structure with clearly delineated sections for inputs, calculations, signal generation, plotting, and alerts makes it maintainable and educational for those studying Pine Script development. The use of input groups with custom headers creates an organized settings panel that doesn't overwhelm users with dozens of ungrouped parameters, while still providing substantial customization capability for advanced users who want to optimize the indicator for specific instruments or timeframes.
For practical trading application, this indicator excels in several specific use cases. Scalpers and day traders can use the intrabar analysis to identify accumulation or distribution happening within the bars of their entry timeframe, providing early entry signals before momentum indicators or price patterns complete. Swing traders can use the cumulative delta and accumulation-distribution zones to understand whether short-term pullbacks in an uptrend are being bought or sold, helping distinguish between healthy retracements and trend reversals. Position traders can use the divergence detection to identify major turning points where price extremes are not supported by volume, providing low-risk entry points for counter-trend positions or warnings to exit with-trend positions before significant reversals.
The indicator is particularly valuable in ranging markets where price-based indicators produce numerous false breakout signals. By requiring that breakouts be accompanied by volume flow imbalances, the indicator filters out failed breakouts driven by low participation. When price breaks a range boundary accompanied by a strong buy or sell signal with high buy or sell score and very high volume, the probability of successful breakout follow-through increases dramatically. Conversely, when price breaks a range but the indicator shows low imbalance, opposing flow direction, or low volume, traders can fade the breakout or at minimum avoid chasing it.
During trending markets, the indicator helps traders identify the healthiest entry points by revealing where pullbacks are being accumulated by smart money. A trending market will show the cumulative delta continuing in the trend direction even as price pulls back, and accumulation zones will form during these pullbacks. When price resumes the trend, the indicator will generate strong buy or sell signals with high scores, providing objective entry points with clear invalidation levels. The flow momentum component helps traders stay with trends longer by distinguishing between healthy momentum pauses—where momentum goes to zero but doesn't reverse—and actual momentum reversals where opposing pressure is building.
The VWAP deviation weighting adds particular value for traders of liquid instruments like major forex pairs, stock indices, and high-volume stocks where VWAP is widely watched by institutional participants. When price deviates significantly from the intrabar VWAP and volume flows in the direction of that deviation with elevated weighting, it indicates that the move away from fair value is being driven by conviction rather than mechanical order flow. This suggests the deviation will likely extend further, creating continuation trading opportunities. Conversely, when price deviates from intrabar VWAP but volume flow shows reduced intensity or opposing direction despite the weighting, it suggests the deviation will revert to VWAP, creating mean reversion opportunities.
The ATR normalization option makes the indicator values comparable across different volatility regimes and different instruments. Without normalization, a one-million share buy-sell imbalance might be significant for a low-volatility stock but trivial for a high-volatility cryptocurrency. By normalizing the delta by ATR, the indicator accounts for the typical price movement capacity of the instrument, making signal thresholds and comparison values meaningful across different trading contexts. This is particularly valuable for traders running the indicator on multiple instruments who want consistent signal quality regardless of the underlying instrument characteristics.
The configurable decay factor allows traders to adjust how persistent they want volume flows to remain influential. For very short-term scalping, a lower decay factor like zero point five will cause volume imbalances to dissipate quickly, keeping the indicator focused only on very recent flows. For longer-term position trading, a higher decay factor like zero point nine-five will allow significant volume events to influence the indicator for many bars, revealing longer-term accumulation and distribution patterns. This flexibility makes the single indicator adaptable to trading styles ranging from one-minute scalping to daily chart position trading simply by adjusting the decay parameter and the lookback bars.
The minimum imbalance percentage setting provides crucial noise filtering that can be optimized per instrument. Highly liquid instruments with tight spreads might show numerous small imbalances that are meaningless, requiring a higher threshold like thirty-five or forty percent to filter noise effectively. Thinly traded instruments might rarely show extreme imbalances, requiring a lower threshold like fifteen or twenty percent to generate adequate signals. By making this threshold user-configurable with a wide range, the indicator accommodates the full spectrum of market microstructure characteristics across different instruments and timeframes.
In conclusion, the Intrabar Volume Flow Intelligence indicator represents a comprehensive volume analysis system that combines intrabar data access, sophisticated volume attribution algorithms, multi-timeframe smoothing, statistical filtering, divergence detection, zone identification, and intelligent signal scoring into a cohesive analytical framework. It provides traders with visibility into market dynamics that are invisible to price-only analysis and even to conventional volume analysis, revealing the true intentions of market participants through their actual transaction behavior within each bar. The indicator's strength lies not in any single feature but in the integration of multiple analytical layers that confirm and validate each other, creating high-probability signal generation that can form the foundation of complete trading systems or provide powerful confirmation for discretionary analysis. For traders willing to invest time in understanding its components and optimizing its parameters for their specific instruments and timeframes, this indicator offers a significant informational advantage in increasingly competitive markets where edge is derived from seeing what others miss and acting on that information before it becomes consensus.
[CT] D&W PPO + RBF + DivergenceThis indicator combines two separate ideas into one tool so you can read trend context from your price chart while timing momentum shifts from a clean oscillator panel. The first component is the Daily and Weekly Percentage Price Oscillator (D&W PPO), which measures the relationship between two EMA spreads that are intentionally built to reflect two “speeds” of market structure. The “weekly” leg is calculated as the percentage distance between a slower and faster EMA pair (L1 and L2), and the “daily” leg is calculated as the percentage distance between a shorter EMA pair (L3 and L4), but both are normalized by the same long EMA (e2) so the values behave like a percent-based oscillator rather than raw points. The script then combines those two legs by creating R = W + D, and it plots the histogram as R − W, which simplifies to D. That is not a mistake, it is the point of the design. By setting the baseline at “R equals W,” the zero line becomes a very intuitive threshold that tells you whether the shorter-term push is adding to the longer-term bias or subtracting from it. When the histogram is above zero, the daily component is supportive of the larger trend pressure, and when it is below zero, the daily component is opposing it. The histogram color is intentionally binary and stable, green when the histogram is at or above zero and red when it is below, so the panel reads like a momentum confirmation tool rather than a noisy oscillator that constantly shifts shades.
The second component is the RBF Price Trail, which is drawn on the upper price chart even though the indicator itself lives in a lower panel. This line is not a moving average in the traditional sense. It is a Radial Basis Function kernel smoother that weights recent prices based on their similarity rather than only their recency. In plain terms, the kernel attempts to build a smoother “baseline” that adapts to the shape of price action, and then the script optionally wraps that baseline inside an ATR band and applies a Supertrend-like trailing clamp. When the ATR band is enabled, the line will not simply track the kernel value, it will trail price and hold its position until price forces it to ratchet. This behavior is what makes it useful as a structure-aligned trend line rather than just another smoothing curve. When the adaptive band boost is enabled, the band width is multiplied by a factor that grows when recent price change is large relative to a lookback normalization window. That means the trailing mechanism can adapt to fast markets by changing the effective band behavior, which helps reduce whipsaws in choppy conditions while still allowing the line to respond when volatility expands. The line color is determined by where price closes relative to the trail, bullish when price is above the trail and bearish when price is below it, and you can optionally color your actual chart candles from either the PPO state or the RBF state depending on what you want your eyes to follow.
The settings are organized so you can control each module without changing how the core PPO trend logic behaves. The PPO settings L1, L2, L3, and L4 define the EMA lengths used to compute the weekly leg W and the daily leg D. Increasing these values makes the oscillator slower and smoother, while decreasing them makes it react faster to recent movement. “Show W line” is simply a visual aid, it plots the W line in the oscillator panel so you can see the longer-term component, but it does not change the histogram logic. “Histogram thickness” is purely visual and controls how thick the column bars are. The PPO colors are the two base colors used for the histogram state, green when the daily component is supportive and red when it is opposing.
The RBF settings control what you see on the upper chart. “Show RBF on Price Chart” turns the trail line on or off. “Source” chooses which price series feeds the kernel, and close is usually the cleanest choice. “Kernel Length” determines how many bars the kernel uses; a larger value makes the baseline smoother and slower, and a smaller value makes it more reactive. “Gamma Adj” controls how quickly the kernel’s weights decay as price becomes dissimilar, so higher gamma tends to make the kernel react more sharply to changes while lower gamma produces a broader smoothing effect. “Use ATR Trail Band” is the switch that turns the kernel baseline into a trailing band line, and it is the reason the line can “hold” and then ratchet instead of moving continuously like a normal moving average. “ATR Length” and “ATR Factor” control the width of that band, and widening the band will generally reduce flips and noise at the cost of later signals. “Use Adaptive Band Boost” turns on the volatility normalization idea, “Boost Normalization Lookback” defines how far back the script looks to determine what counts as a large price change, and “Boost Multiplier” controls how strongly the band behavior is adjusted during those periods. The line width and bull/bear colors are visual controls only.
Price bar coloring is intentionally handled with a single selector so you do not end up with two modules fighting to color candles differently. If you choose “Off,” nothing on the main chart is recolored. If you choose “PPO,” your price candles reflect whether the PPO histogram is above or below zero. If you choose “RBF,” your price candles reflect whether price is above or below the RBF trail. Most traders will pick one and stick with it so the chart communicates a single bias at a glance.
The divergence module is optional and is designed to be a confirmation layer rather than a primary trigger. When enabled, it can mark regular divergence and hidden divergence, and it lets you decide what the pivots should be based on. The divergence source can be the PPO histogram or the R line, depending on whether you want divergence measured on the cleaner momentum component or on the combined series. “Key off pivots” determines whether pivot detection is driven by oscillator pivots or by price pivots. If you choose oscillator pivots, divergence anchors are found where the oscillator makes pivot highs or lows and those are compared against price at the same points. If you choose price pivots, the pivots are taken from price first and the oscillator value at those pivot bars is used for the comparison, which can feel more intuitive when you want divergence to respect obvious swing structure on the chart. Pivot Left and Pivot Right control how strict the swing definition is, larger values create fewer but more meaningful pivots and smaller values create more frequent signals. “Mark on Price Chart” adds tiny markers on the candles at the pivot location so you can see where the divergence event was confirmed, while the oscillator panel uses lines and labels to make the divergence relationship obvious.
For trading, the cleanest way to use this tool is to separate “bias” from “timing.” The RBF Price Trail is your bias filter because it is structure-like and tends to hold and ratchet rather than constantly drifting. When price is closing above the trail and the trail is colored bullish, you treat the market as long-biased and you focus on long setups, pullbacks, and continuation entries. When price is closing below the trail and the trail is bearish, you treat the market as short-biased and you focus on short setups, rallies, and continuation shorts. The PPO histogram is then your timing and pressure confirmation. In an up-bias, the highest quality continuation conditions are when the histogram is above zero and stays above zero through pullbacks, because that means the shorter-term pressure is still supporting the longer-term drift. When the histogram dips below zero during an up-bias, it is a warning that the daily component is now opposing, which often corresponds to a deeper pullback, a rotation, or a period of consolidation, so you either wait for the histogram to recover above zero or you tighten expectations and manage risk more aggressively. In a down-bias, the mirror logic applies: the best continuation conditions are when the histogram is below zero, and pushes above zero tend to represent countertrend rotations or pauses inside the bearish condition.
Divergence is best used as an early warning and a location filter, not as a standalone entry button. Regular bullish divergence, where price makes a lower low but the oscillator makes a higher low, can signal bearish pressure is weakening and is most useful when it appears while price is below the RBF trail but failing to continue downward, because it often precedes a reclaim of the trail or at least a meaningful rotation. Regular bearish divergence, where price makes a higher high but the oscillator makes a lower high, can signal bullish pressure is weakening and is most useful when it appears while price is above the trail but extension is failing, because it often precedes a drop back to the trail or a full flip. Hidden divergence is a continuation concept. Hidden bullish divergence, where price makes a higher low while the oscillator makes a lower low, often shows up during pullbacks in an uptrend and can help you confirm continuation as long as the RBF bias remains bullish. Hidden bearish divergence, where price makes a lower high while the oscillator makes a higher high, often shows up during rallies in a downtrend and can help you confirm continuation as long as the RBF bias remains bearish. In practice, you’ll get the best results when you only act on divergence that aligns with the RBF bias for hidden divergence continuation, and you treat regular divergence as a caution or reversal setup only when it occurs near a meaningful swing and is followed by a bias change or a strong momentum shift on the PPO.
The most practical workflow is to keep the RBF trail visible on the price chart as your regime guide, keep the PPO histogram as your momentum confirmation, and decide in advance whether you want candle coloring to represent the PPO state or the RBF state so your eyes are not reading two different meanings at once. if you want the cleanest “trend-following” behavior, color candles by the RBF trail and use the PPO histogram as the timing trigger. If you want the cleanest “momentum-first” behavior, color candles by PPO and treat the RBF trail as the higher-level filter for whether you should press a move or fade it.
Digital MACD Divergences MTF [LUPEN]Digital MACD Divergences MTF V1.0
Overview:
Digital MACD Divergences MTF is an advanced momentum oscillator based on digital signal processing techniques.
Instead of relying on traditional moving-average smoothing, it applies Finite Impulse Response (FIR) digital filters to extract momentum more cleanly, reducing lag and short-term market noise.
The indicator is designed to provide a clear visualization of momentum structure, divergence behavior, and multi-timeframe context, rather than discrete trading signals.
Conceptual Architecture
At its core, the indicator reinterprets the classic MACD framework through digital convolution logic:
FIR filters are used to compute momentum in a more responsive and stable manner than standard EMA-based MACD.
The resulting histogram represents momentum intensity and direction as a continuous state rather than binary conditions.
A digitally smoothed signal line provides structural reference without introducing excessive delay.
This approach emphasizes momentum quality and structure, not signal frequency.
Divergence Detection Logic:
The script includes automatic divergence detection based on pivot analysis:
Regular bullish and bearish divergences are identified using confirmed pivot points.
Divergences are visualized with explicit line structures and optional filled areas, highlighting the zone of disagreement between price behavior and momentum.
The visualization is designed to remain readable without obscuring price action.
Divergences are presented as contextual information, not as mandatory actions.
Multi-Timeframe (MTF) Context
Digital MACD Divergences MTF supports native multi-timeframe analysis through a dual-pane workflow:
A lower-timeframe instance visualizes local momentum dynamics.
A higher-timeframe instance visualizes the broader momentum regime within which lower-timeframe fluctuations occur.
The higher-timeframe view is not intended as confirmation or filtering logic, but as a contextual background layer that helps interpret short-term momentum behavior inside a larger structural environment.
This separation avoids decision compression and keeps each timeframe’s role conceptually distinct.
Visual Design
Gradient-based histogram fills represent momentum intensity in a continuous manner.
Positive and negative momentum regions are clearly differentiated while remaining adaptable to both dark and light chart themes.
All visual elements are designed to emphasize state and regime, not discrete events.
Reliability
No repainting: all divergences and momentum states are confirmed on candle close and remain fixed.
Designed for consistency across instruments and timeframes.
Customization Options
Timeframe selection for MTF mode (leave empty to use the chart’s timeframe).
Adjustable signal smoothing parameters.
Divergence visibility controls, pivot sensitivity, and optional divergence fill.
Fully customizable color palette.
Usage Notes
This indicator is a visual market analysis tool intended to support momentum interpretation and structural context.
It does not provide investment advice, trading signals, or automated decision logic, and should be used as part of a broader analytical framework.
Final quotes:
"Trading is not about prediction, but about understanding momentum structure.
Digital MACD removes noise to make that structure visible."
BTC - CII: Drawdown DNA | RMBTC - CII: Drawdown DNA | Rob_Maths
The "Broken Cycle" Series: Pt 1
Welcome to the debut of the Cycle Integrity Index (CII) . This quantitative diagnostic suite was engineered for a singular mission: to determine if Bitcoin’s historical 4-year cycle is still the primary track rhythm, or if the market has shifted into a high-downforce Institutional Regime.
As of January 2026 , the Bitcoin market is at a historical crossroads. According to the classical 4-year model, we have passed the "Theoretical Peak" and are now on the long descent toward a projected cycle low in late 2026 . However, a massive debate is raging: Is the cycle broken?
While legacy models expect a total engine failure (an -80% wipeout) by the end of this year, the ETF-era market structure suggests we may have "re-engineered" the asset's DNA. Pt 1: Drawdown DNA acts as our first telemetry check, auditing the "Structural Fatigue" of every correction to see if we are taking a tactical pit stop or heading for a catastrophic crash.
How to Read the Telemetry
Think of the Bitcoin market as a Formula 1 engine. This indicator audits the "Wear and Tear" (drawdowns) to see if the chassis can sustain its pace or if the structural integrity is failing as we approach the legacy "finish line."
• Vibrant Green (Institutional Sync): Optimal Performance. The engine is healthy. Pullbacks are shallow (-20% to -35% range), representing professional re-fueling stops by smart money. This suggests the "Supercycle" narrative is overriding the 4-year clock.
• Red/Dark Blue (Regime Decay): Loss of Traction. The "Institutional" heartbeat is weakening. Volatility is rising as the engine stalls, drifting back toward the chaotic, un-buffered "Drift" patterns of the retail era.
• Blue Shaded Zones (Legacy DNA): SYSTEMIC CRASH. The price has breached the -50% "G-Force Threshold." At this depth, the correction carries the genetic makeup of a Legacy Bear Market (historically bottoming near -80%). The 4-year cycle is still very much alive—and it's painful.
Behind the Math: ECU Tuning
This script is an original quantitative work utilizing Gaussian Probability Density logic to categorize market drawdowns into distinct historical regimes.
Instead of simple binary "on/off" logic, the code acts like an ECU (Electronic Control Unit) , calculating the mathematical "fit" of the current drawdown against a specific Institutional Mean (-25%) . Why 25%? I chose -25% as the Institutional DNA anchor based on the structural shift observed between 2023 and 2025. While legacy retail cycles were defined by violent 30-40% "shakeouts" during bull phases, the introduction of spot ETFs and corporate treasury adoption has significantly compressed volatility. A -25% correction now represents the maximum "healthy" absorption of sell-side liquidity by institutional "bids." Staying near this level maintains high aerodynamic sync; dropping further suggests the chassis is failing.
How it Audits the Regime
The closer the price stays to this -25% target, the higher the Integrity Score (10/10). By providing unique "DNA Match" calculations and background shading based on specific threshold crossings, this indicator provides utility beyond standard price-change indicators. It allows you to mathematically distinguish between an "Institutional Rebalancing" and the start of a "Legacy Cycle-Ending Termination."
User Inputs & Navigation
• Rolling High Lookback: Default 52 Weeks . Defines our diagnostic lap. It ensures the audit focuses on the current race, not the entire history of the track.
• Inst. Drawdown Target: Default -25% . The "Perfect Pit Stop." Corrections near this level maintain the highest aerodynamic sync.
• Legacy Threshold: Default -50% . The "Point of No Return" where the engine enters total failure and the Blue Legacy Shading triggers.
• Legacy Crash Target: Default -80% . The historical baseline for previous 4-year cycle bear market floors (Expected mid-to-late 2026 in legacy models).
Instructions & Performance
• Preferred Timeframe: This is a macro-telemetry tool. It performs best on Weekly (1W) or Daily (1D) charts.
• The Dashboard: Monitor the INST. DNA MATCH in the table. A score of 8.0+ / 10 provides the "Green Light" that the Supercycle is still the primary driver, effectively breaking the 4-year "Crash" script.
Disclaimer
Trading and investing in digital assets involve significant risk. The Cycle Integrity Index (CII) is a quantitative tool for informational and educational purposes only. Past performance does not guarantee future results. This is not financial advice. Your capital is at risk.
Tags
robmaths, Rob Maths, Bitcoin, CycleTheory, Institutional, Drawdown, Quant, RegimeShift, CII
Check out my published scripts here: de.tradingview.com
