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.
在腳本中搜尋"binary"
TradeX Guru Intraday Scalping SetupThe TradeX Guru Scalping setup is a multivariate analysis system designed to isolate high-probability market vectors by filtering stochastic market noise. Unlike linear indicators that rely on singular data points, this system employs a "Composite Confluence Algorithm" that synthesizes directional bias, momentum magnitude, harmonic cycles, and volumetric deviation into a unified signal output.
This tool is engineered for traders requiring low-latency decision support, featuring automated variance-based risk modeling (Dynamic Stops & Targets) and real-time market telemetry displayed directly on the chart.
Methodology & Underlying Principles This script operates as a Multivariate Decision Engine, synthesizing four distinct dimensions of market data into a single binary output. Instead of relying on raw, lagging signals, the algorithm employs a composite filtering mechanism to isolate high-probability vectors.
1. Trend Basis Cloud (Dual-Filter Smoothing)
Scientific Concept: Low-Pass Signal Filtering.
Description: The system utilizes a dual-period exponential smoothing algorithm to filter out high-frequency market noise (short-term volatility). By analyzing the divergence between the fast and slow smoothing constants, the engine establishes a Directional Bias, ensuring that all subsequent signals are aligned with the dominant low-frequency trend vector.
2. Momentum Force (Volatility-Normalized Vector)
Scientific Concept: Impulse & Magnitude.
Description: Rather than simple price change, this component calculates the "Impulse" of price action relative to its recent volatility envelope. It measures the magnitude of the breakout vector, effectively distinguishing between low-energy "drift" (chop) and high-energy "expansion" (valid trends).
3. Cycle Phase Analysis (Harmonic State Detection)
Scientific Concept: Phase Transition.
Description: Markets move in oscillatory cycles of contraction and expansion. This module detects the specific harmonic phase of the current price action. It acts as a timing gate, validating entries only during the "Early Expansion" phase and suppressing signals during "Peak Saturation" (overbought/oversold extremes), preventing late entries.
4. Volume Flow Z-Score (Statistical Anomaly Detection)
Scientific Concept: Standard Deviation & Gaussian Distribution.
Description: This filter applies statistical normalization to volume data. By calculating the Z-Score (Standard Score) of incoming volume, the system identifies statistically significant deviations from the mean (Institutional Activity) while filtering out activity that falls within standard distribution (Retail Noise).
Key Technical Features
Real-time Market Telemetry: A custom-built Institutional Terminal displays live market states (Expansion vs. Range), bias vectors, and liquidity Z-scores. Includes a responsive "Mobile Mode" for cross-device compatibility.
Variance-Based Risk Modeling: The engine automatically computes a Safety Threshold (Stop Loss) based on local volatility (ATR) and projects 7 distinct Profit Vectors based on a proprietary risk-to-reward ratio.
Modular Visual Engine: A complete toggle system allows operators to enable/disable specific data layers (Signals, Vectors, Paint Bars) to maintain a clean workspace.
State-Change Detection: The system actively monitors for "Polarity Flips" (failed setups), providing immediate visual feedback to exit or reverse positions.
Why is this Invite-Only? This script relies on a proprietary "Black Box" architecture. The specific lookback periods, smoothing constants, and Z-score thresholds have been optimized and hardcoded to ensure statistical integrity. Access is restricted to protect the intellectual property of the algorithm's internal weighting system.
Disclaimer This tool is strictly for educational and quantitative analysis purposes. Past performance is not indicative of future results. This is not financial advice.
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.
QX Expert Imtiazz 3.0.4 ProQX Expert Imtiazz 3.0.4 Pro (qx_expert_imtiaz) is an advanced price-action–based TradingView indicator designed to identify high-probability BUY and SELL opportunities with clarity and precision.
It combines trend direction, market structure, and dynamic support & resistance logic to help traders make confident decisions in both trending and ranging markets.
The indicator plots clear BUY (green) and SELL (red) signals directly on the chart, reducing noise and eliminating guesswork. It is optimized for short-term, intraday, and scalping strategies, while still remaining effective on higher timeframes.
QX Expert Imtiazz Pro works best on Forex pairs, but it can also be applied to crypto, indices, and commodities. Its lightweight and non-repainting logic makes it suitable for real-time trading and backtesting.
🔹 Key Features
📌 Clear BUY & SELL arrow signals
📈 Trend-based confirmation logic
🔄 Works in trending & ranging markets
🕒 Suitable for scalping, intraday & swing trading
⚡️ Repainting signals (after candle close) With 90% Accuracy
🔧 Optimized for Binary & Forex, Crypto, Indices
📊 Works on multiple timeframes
🧠 Beginner-friendly & pro-level accuracy
🔹 How to Use
BUY Signal (Green Arrow): Look for long entries after candle close
SELL Signal (Red Arrow): Look for short entries after candle close
Best results when used with:
Higher timeframe trend confirmation
Proper risk management (SL & TP)
Support & resistance zones
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.
Volume Oracle - Regime DetectionVolume Oracle - Regime Detection
Volume Oracle transforms raw volume data into a regime-based flow analysis framework. The indicator is designed to help traders identify periods of accumulation and distribution through five integrated analytical layers: regime detection, market structure validation, volume footprint analysis, quality scoring, and multi-timeframe confluence.
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🔶 𝗢𝗩𝗘𝗥𝗩𝗜𝗘𝗪
Volume analysis has long been considered a window into market participant activity. Large players cannot move size without leaving footprints in the volume record. Traditional volume indicators show raw numbers, but interpreting whether elevated volume represents accumulation or distribution requires additional context.
Volume Oracle builds on this foundation by adding five analytical layers:
• Regime Detection: Classifies the current market state as Accumulation (buying pressure), Distribution (selling pressure), or Neutral (no clear direction) using a composite scoring system that weighs price velocity, trend alignment, and volume-weighted flow.
• Market Structure Validation: Tracks swing highs and lows to determine if price structure (higher highs/higher lows vs lower highs/lower lows) agrees with the detected regime.
• Volume Footprint Analysis: Classifies volume spikes as either Momentum bars (large body, small wicks indicating directional conviction) or Absorption bars (small body, large wicks indicating supply/demand absorption).
• Quality Scoring System: Rates each signal from 0-100% based on multiple confluence factors, displayed as star ratings for quick visual assessment.
• Multi-Timeframe Confluence: Optional higher timeframe filters that require regime alignment across multiple timeframes before generating signals.
The indicator adapts all parameters automatically based on the chart timeframe, with different settings optimized for scalping, intraday, swing, and position trading styles.
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🔶 𝗛𝗢𝗪 𝗜𝗧 𝗪𝗢𝗥𝗞𝗦
The indicator is built around one core principle: market participant activity may reveal itself through the relationship between volume, price movement, and market structure.
𝗥𝗲𝗴𝗶𝗺𝗲 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗦𝘆𝘀𝘁𝗲𝗺
What it does: The regime engine calculates a composite score using four weighted components: recent price velocity (where price is heading now versus recent history), trend alignment (EMA stacking and price position relative to moving averages), volume-weighted flow (proportion of volume occurring on up-closes versus down-closes), and volume confirmation (whether current volume exceeds average). The score passes through an EMA smoothing filter and must exceed configurable thresholds for multiple consecutive bars before a regime change is confirmed.
How to interpret it: When the indicator shows Accumulation, this suggests buying pressure currently dominates. Distribution suggests selling pressure dominates. Neutral indicates no clear directional bias. The regime state colors the volume bars: green tints during accumulation, red tints during distribution, gray during neutral periods. A subtle background shade reinforces the current regime.
𝗠𝗮𝗿𝗸𝗲𝘁 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻
What it does: The indicator tracks recent swing highs and swing lows using pivot detection. It compares the most recent swing points to previous ones to determine if price is making higher highs and higher lows (bullish structure), lower highs and lower lows (bearish structure), or mixed patterns.
How to interpret it: When structure aligns with regime (bullish structure during accumulation, bearish structure during distribution), the regime table displays a checkmark. When structure conflicts with regime, this may suggest the regime is losing conviction. Structure validation appears in the regime table and factors into signal quality scores.
𝗩𝗼𝗹𝘂𝗺𝗲 𝗙𝗼𝗼𝘁𝗽𝗿𝗶𝗻𝘁 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀
What it does: On volume spike bars, the indicator analyzes the candle structure. Momentum bars have large bodies relative to their range (directional conviction). Absorption bars have small bodies with large wicks (supply or demand being absorbed without moving price significantly).
How to interpret it: Momentum bars during a trend may suggest strong directional conviction pushing price. Absorption bars may suggest supply or demand being absorbed at support or resistance without significant price movement. Footprint type factors into signal quality and triggers dedicated alerts.
𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗦𝗰𝗼𝗿𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺
What it does: Each signal receives a quality score from 0-100% based on multiple factors: volume spike strength, flow direction conviction, trend alignment, regime strength, regime freshness, squeeze proximity, HTF alignment (if enabled), momentum acceleration, structure agreement, footprint type, market character (trending vs choppy), and confluence count. High signal density (many signals in a short period) reduces quality scores.
How to interpret it: Signals display star ratings: three stars for scores above 85%, two stars for 75-84%, one star for 65-74%, and no stars below 65%. A target emoji appears when five or more confluence factors align. Higher quality scores suggest more factors agreeing, though this does not guarantee outcomes.
𝗠𝘂𝗹𝘁𝗶-𝗧𝗶𝗺𝗲𝗳𝗿𝗮𝗺𝗲 𝗖𝗼𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲
What it does: When enabled, the indicator fetches data from one or two higher timeframes and calculates simplified regime scores for each. It checks whether HTF regimes match the current timeframe regime, whether HTF strength exceeds a minimum threshold, and whether HTF regimes are strengthening rather than weakening.
How to interpret it: When all HTF conditions align, signals display an additional emoji indicator. In strict mode, signals only appear when HTF agrees. The HTF table shows regime state, strength percentage, trend direction, and alignment status for each configured timeframe.
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🔶 𝗪𝗛𝗬 𝗧𝗛𝗘𝗦𝗘 𝗖𝗢𝗠𝗣𝗢𝗡𝗘𝗡𝗧𝗦 𝗪𝗢𝗥𝗞 𝗧𝗢𝗚𝗘𝗧𝗛𝗘𝗥
Each layer addresses a different aspect of market analysis:
1. Regime Detection: Establishes the directional bias using volume-weighted evidence.
2. Structure Validation: Confirms whether price action supports the detected regime.
3. Footprint Analysis: Characterizes the nature of volume activity on spikes.
4. Quality Scoring: Synthesizes all factors into a single actionable metric.
5. Multi-Timeframe Filter: Reduces noise by requiring agreement across timeframes.
When multiple factors align (strong regime, confirming structure, momentum footprint, high quality score, HTF agreement), this represents maximum confluence. Such conditions may warrant closer examination, though they do not guarantee any particular outcome.
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🔶 𝗛𝗢𝗪 𝗧𝗢 𝗨𝗦𝗘
This section provides step-by-step guidance for interpreting the indicator's visual elements.
𝗦𝘁𝗲𝗽 𝟭: 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝘁𝗵𝗲 𝗖𝘂𝗿𝗿𝗲𝗻𝘁 𝗥𝗲𝗴𝗶𝗺𝗲
Look at the regime table in the corner of the chart. The top row shows the current regime state: ACCUMULATION, DISTRIBUTION, or NEUTRAL. The color matches the regime (green, red, or gray).
• Volume bars tinted green suggest accumulation regime
• Volume bars tinted red suggest distribution regime
• Volume bars gray indicate neutral regime
The regime provides context for all other readings. Trading with the regime (buying during accumulation, selling during distribution) aligns with the detected flow direction.
𝗦𝘁𝗲𝗽 𝟮: 𝗔𝘀𝘀𝗲𝘀𝘀 𝗥𝗲𝗴𝗶𝗺𝗲 𝗛𝗲𝗮𝗹𝘁𝗵
The regime table displays multiple health indicators:
• Strength percentage: Higher values suggest stronger conviction
• Status: STRONG, FADING, WEAKENING, or CRITICAL
• Health: Composite warning indicator (HEALTHY, WATCH, CAUTION, DANGER)
• Structure: Whether price structure agrees with regime
• Market: Whether conditions are TRENDING, NORMAL, or CHOPPY
• Flip: Whether a regime change is building
When status shows FADING or worse, the regime may be losing conviction. Yellow-tinted volume bars appear after three consecutive bars of weakening status, providing early warning of potential regime changes.
𝗦𝘁𝗲𝗽 𝟯: 𝗪𝗮𝘁𝗰𝗵 𝗳𝗼𝗿 𝗦𝗶𝗴𝗻𝗮𝗹𝘀
Bullish signals appear as green labels with an up arrow above volume spikes during accumulation. Bearish signals appear as red labels with a down arrow during distribution. Labels include:
• Star ratings indicating quality (more stars suggest more confluence)
• Target emoji when five or more factors align
• HTF emoji when higher timeframe agrees
Hover over any signal label to see detailed tooltip information including quality percentage, risk levels, position sizing suggestions, and specific confluence factors present.
𝗦𝘁𝗲𝗽 𝟰: 𝗖𝗵𝗲𝗰𝗸 𝗛𝗧𝗙 𝗔𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁 (𝗜𝗳 𝗘𝗻𝗮𝗯𝗹𝗲𝗱)
When multi-timeframe filtering is enabled, a second table appears showing HTF regime states. Green checkmarks indicate alignment, red X marks indicate disagreement. For maximum confluence, all timeframes should agree on regime direction.
𝗦𝘁𝗲𝗽 𝟱: 𝗠𝗼𝗻𝗶𝘁𝗼𝗿 𝗘𝘅𝗶𝘁 𝗪𝗮𝗿𝗻𝗶𝗻𝗴𝘀
Yellow warning labels appear when exit conditions trigger: regime flips, flow reversals, critical weakness, time-based exits, or target hits. These suggest reviewing open positions. The tooltip explains the specific exit reason.
𝗦𝘁𝗲𝗽 𝟲: 𝗖𝗼𝗺𝗯𝗶𝗻𝗲 𝗠𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗙𝗮𝗰𝘁𝗼𝗿𝘀
The indicator provides the most context when multiple elements align:
𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘚𝘤𝘦𝘯𝘢𝘳𝘪𝘰 𝘈 (𝘛𝘳𝘦𝘯𝘥 𝘊𝘰𝘯𝘵𝘪𝘯𝘶𝘢𝘵𝘪𝘰𝘯): Regime shows ACCUMULATION at 72% strength with STRONG status. Structure displays checkmark (HH/HL confirmed). Market character shows TRENDING. A volume spike triggers a bullish signal with two stars and HTF alignment. Multiple factors agreeing during an established regime suggests trend may continue, though no outcome is guaranteed.
𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘚𝘤𝘦𝘯𝘢𝘳𝘪𝘰 𝘉 (𝘔𝘰𝘮𝘦𝘯𝘵𝘶𝘮 𝘍𝘢𝘥𝘪𝘯𝘨): Regime shows DISTRIBUTION but status has shifted to FADING. Strength dropped from 65% to 48% over recent bars. Structure shows conflict (regime bearish but structure making higher lows). Volume bars have turned yellow. This type of internal disagreement often appears before regime changes or consolidation periods.
𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘚𝘤𝘦𝘯𝘢𝘳𝘪𝘰 𝘊 (𝘌𝘹𝘩𝘢𝘶𝘴𝘵𝘪𝘰𝘯 𝘞𝘢𝘳𝘯𝘪𝘯𝘨): After an extended rally, regime shows ACCUMULATION but status reads CRITICAL. Health indicator shows CAUTION with two warnings active. An absorption bar appears (volume spike with small body and large upper wick). The Flip row shows regime change building. None of this guarantees reversal, but multiple warning signs appearing together suggest caution.
𝘌𝘹𝘢𝘮𝘱𝘭𝘦 𝘚𝘤𝘦𝘯𝘢𝘳𝘪𝘰 𝘋 (𝘉𝘳𝘦𝘢𝘬𝘰𝘶𝘵 𝘍𝘳𝘰𝘮 𝘊𝘰𝘯𝘴𝘰𝘭𝘪𝘥𝘢𝘵𝘪𝘰𝘯): Regime has shown NEUTRAL for several sessions with volume bars gray and muted. Market character displays CHOPPY. Then a volume spike triggers with regime flipping to ACCUMULATION, confirmed by structure shift to HH/HL. A three-star signal appears with target emoji. When multiple elements shift together after a quiet period, consolidation may be resolving into a directional move.
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🔶 𝗡𝗔𝗩𝗜𝗚𝗔𝗧𝗜𝗡𝗚 𝗗𝗜𝗙𝗙𝗘𝗥𝗘𝗡𝗧 𝗠𝗔𝗥𝗞𝗘𝗧 𝗖𝗢𝗡𝗗𝗜𝗧𝗜𝗢𝗡𝗦
𝗧𝗿𝗲𝗻𝗱𝗶𝗻𝗴 𝗠𝗮𝗿𝗸𝗲𝘁𝘀
During sustained trends, the indicator typically shows persistent regime state (accumulation in uptrends, distribution in downtrends) with STRONG status and TRENDING market character. Structure should confirm with appropriate swing point patterns. Signals receive quality bonuses during trending conditions. Focus on signals that align with the established regime rather than counter-trend setups. The regime strength percentage and status provide ongoing confirmation that the trend remains healthy.
𝗥𝗮𝗻𝗴𝗶𝗻𝗴 𝗠𝗮𝗿𝗸𝗲𝘁𝘀
During consolidation, expect frequent regime shifts between accumulation, distribution, and neutral. Market character will display CHOPPY, and quality scores receive penalties. Structure may show mixed readings. Signal frequency increases but quality decreases. Consider using stricter filtering (higher volume threshold, HTF requirement) or waiting for regime stability before acting. The stability index in the regime table tracks flip frequency to help identify choppy conditions.
𝗛𝗶𝗴𝗵 𝗩𝗼𝗹𝗮𝘁𝗶𝗹𝗶𝘁𝘆 𝗘𝘃𝗲𝗻𝘁𝘀
During news events or volatility spikes, the auto-adapt feature adjusts thresholds based on ATR readings. Higher volatility raises the bar for regime changes, reducing whipsaws. Volume spikes during high volatility require greater statistical significance. The regime table tooltip shows current adaptive settings for transparency. Signals during extreme volatility should be interpreted with additional caution.
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🔶 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗗𝗘𝗧𝗔𝗜𝗟𝗦
• Volume spike detection uses z-score normalization against a lookback window
• Regime scoring combines velocity, trend, flow, and volume components with configurable weights
• Regime changes require multi-bar confirmation above thresholds
• Structure detection uses pivot-based swing point identification
• Footprint classification analyzes body-to-range ratio and wick proportions
• Quality scoring aggregates multiple factors with caps and multipliers
• HTF data uses request.security with lookahead disabled (non-repainting)
• All signals fire on bar close only (non-repainting architecture)
• Parameters adapt automatically based on timeframe category
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🔶 𝗨𝗡𝗜𝗤𝗨𝗘 𝗙𝗘𝗔𝗧𝗨𝗥𝗘𝗦
• Timeframe Adaptive: All parameters (lookbacks, thresholds, confirmations) automatically scale based on whether the chart shows scalp, intraday, swing, or position timeframes.
• Multi-Layer Warning System: Four warning levels (STRONG, FADING, WEAKENING, CRITICAL) provide graduated alerts as regimes deteriorate, rather than binary flip signals.
• Structure-Regime Validation: Cross-references detected regime against actual price structure (swing highs/lows) to identify potential divergences.
• Volume Footprint Classification: Distinguishes between momentum-driven volume spikes and absorption patterns that may indicate different market participant behavior.
• Quality-Based Position Sizing: Suggested position sizes scale based on signal quality, with higher confluence signals receiving larger size recommendations.
• Non-Repainting Architecture: All calculations use confirmed bar data only. Historical display matches real-time behavior exactly.
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🔶 𝗦𝗘𝗧𝗧𝗜𝗡𝗚𝗦 𝗢𝗩𝗘𝗥𝗩𝗜𝗘𝗪
• Detection: Volume spike threshold, signal cooldown, regime sensitivity mode, auto-adapt toggle, warning display toggle
• Risk: Account size, risk percentage, ATR length, stop/target multipliers, partial exit percentage, trailing stop and breakeven settings
• Multi-Timeframe: HTF enable toggles, timeframe selections, strict mode, minimum HTF strength threshold
• Strategy: Trading mode selection (Trend Following, Mean Reversion, or Hybrid), mean reversion threshold
• Display: Toggles for regime table, background colors, exit warnings, quality stars, management labels, tooltips, and HTF table
• Table Style: Layout orientation, table positions, text sizes, border and frame widths
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🔶 𝗔𝗟𝗘𝗥𝗧𝗦
25 alert conditions available:
• Bull Signal / Bear Signal / Any Signal: Core directional signals with quality and position details
• Target 1 Hit / Breakeven: Position management milestones
• Exit Warning: Triggered when exit conditions appear
• Regime to Accumulation / Distribution / Neutral: Individual regime change alerts
• Any Regime Change: Fires on any regime transition
• Regime Weakening: Early warning of deteriorating regime
• Momentum Fading / Flow Deteriorating / Volume Drying: Leading exit indicators
• Multiple Warnings: Fires when two or more warning conditions active
• HTF Aligned / HTF Broke: Multi-timeframe alignment changes
• Structure Bullish / Structure Bearish: Price structure shifts
• Structure Conflict: When structure disagrees with regime
• Momentum Footprint / Absorption Footprint: Volume footprint detection
• Market Trending / Market Choppy: Market character changes
• High Confluence Signal: Signals with five or more factors aligned
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🔶 𝗟𝗜𝗠𝗜𝗧𝗔𝗧𝗜𝗢𝗡𝗦
• Requires Volume Data: Instruments without reliable volume data (some forex pairs, indices) will produce unreliable readings.
• Analysis Tool, Not Signal Generator: This indicator identifies conditions that may warrant attention. It does not provide entry/exit instructions and should not be followed mechanically.
• Lagging Component: Regime detection requires confirmation bars, introducing necessary lag. Fast reversals may not be captured in time.
• No Guarantee of Outcomes: High quality scores and multiple confluence factors improve context but do not predict results. Markets can move against any setup.
• HTF Limitations: Higher timeframe data updates on HTF bar closes, not continuously. Brief alignment windows may be missed.
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🔶 𝗖𝗢𝗡𝗖𝗟𝗨𝗦𝗜𝗢𝗡
Volume Oracle provides a structured framework for analyzing volume flow through regime detection, structure validation, footprint classification, quality scoring, and multi-timeframe confluence. The indicator is designed to help traders identify accumulation and distribution phases and assess the conviction behind detected regimes. Multiple warning systems provide early indication when regimes may be losing strength.
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🔶 𝗗𝗜𝗦𝗖𝗟𝗔𝗜𝗠𝗘𝗥
Trading is risky and most traders lose money. This indicator is provided for informational and educational purposes only. It does not constitute financial advice, and past performance does not guarantee future results. All content, tools, and analysis should not be considered as recommendations to buy or sell any asset. Users are solely responsible for their own trading decisions. Always use proper risk management and consider consulting a qualified financial advisor before making trading decisions.
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Built with PineScript v6. Non-repainting. All signals confirmed on bar close.
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).
GB-FVG by AlgoKingsGB-FVG by AlgoKings
RISK DISCLAIMER: This indicator is an analytical tool for educational purposes only, not financial advice. Trading carries substantial risk of loss. This tool does not guarantee profitable trades. Always use proper risk management and never risk more than you can afford to lose.
WHAT IS GB-FVG?
GB-FVG identifies Fair Value Gaps that form during Goldbach mathematical time windows. Unlike standard FVG indicators that display all price imbalances, this tool filters for gaps created at specific time harmonics based on Goldbach number theory, highlighting institutional order flow events that occur during mathematically significant moments.
Example: At 11:35 (minute=35, hour=11, sum=46, difference=24), if minute matches Goldbach number 35 AND a three-candle gap forms, the indicator displays this FVG. Standard gaps forming at non-Goldbach times are ignored.
UNDERLYING METHODOLOGY
This indicator combines three analytical layers:
1. THREE-CANDLE FVG DETECTION
Identifies price imbalances using precise gap analysis:
BULLISH FVG:
Candle 3 (two bars back) high < Candle 1 (current) low = Gap between bars that price never traded
BEARISH FVG:
Candle 3 (two bars back) low > Candle 1 (current) high = Gap between bars that price never traded
Technical implementation:
- Uses request.security with lookahead_on to access confirmed bar data (high , low , high , low )
- For bullish FVG: Gap top = low , Gap bottom = high
- For bearish FVG: Gap top = low , Gap bottom = high
- Detects new FVGs when time exceeds previous time (new bar completed on indicator timeframe)
Bar array management:
Maintains rolling array of 10 most recent bars from indicator timeframe. On each security.isNew event, unshifts new bar and pops oldest. Enables lookback for three-bar pattern comparison without repeated security calls.
Higher timeframe precision:
When indicator timeframe exceeds chart timeframe (e.g., 1H FVG on 5m chart), hCtf and lCtf methods search backward through chart bars to find exact bar that created gap extreme, providing precise visual placement.
2. GOLDBACH TIME FILTERING
Only displays FVGs that form during Goldbach number time windows:
GOLDBACH NUMBER SET:
Master list of 23 key numbers: 0, 3, 11, 17, 29, 41, 47, 53, 59, 71, 83, 89, 97, 100, 7, 14, 23, 35, 44, 50, 56, 65, 77
These numbers represent temporal harmonics derived from number theory. Users can select all numbers or specify custom subset.
TIME COMPONENT CALCULATION:
For middle bar of three-candle pattern (bar that created the gap), algorithm extracts four components in selected timezone:
- Minute (m): Minute of hour (0-59)
- Hour (h): Hour of day (0-23)
- Sum (h + m): Addition of hour and minute
- Difference (|h - m|): Absolute difference between hour and minute
MATCHING LOGIC:
FVG only drawn if middle bar timestamp matches ANY Goldbach number ±1:
if (m == n) or (h == n) or (h+m == n) or (|h-m| == n)
→ Exact match, FVG qualifies
if (m == n±1) or (h == n±1) or (h+m == n±1) or (|h-m| == n±1)
→ Near match, FVG qualifies
Example: At 14:35, if user selected Goldbach 35:
- m = 35 → Exact match → FVG qualifies
- Gap drawn with label "35"
Filter effectiveness:
Standard FVG indicator might show 50+ gaps on 5m chart. GB-FVG shows only 5-10 gaps that align with Goldbach timing, reducing noise and highlighting mathematically significant imbalances.
3. MITIGATION TRACKING
Monitors gap fill status with body-based or wick-based options:
MITIGATION TYPES:
- Body Close: FVG considered filled when candle closes inside gap
- Wick Touch: FVG extends until touched (when "Mitigate on body close" disabled)
STATE MANAGEMENT:
- Active: Gap unfilled, box extends to future (x2 = time + offset)
- Mitigated: Price closed inside gap, box stops at mitigation bar
Progressive tracking:
On each new bar from indicator timeframe, if "Mitigate on body close" enabled:
- Bullish FVG: if close <= gap.bottom, set isMit=true, x2=time
- Bearish FVG: if close >= gap.top, set isMit=true, x2=time
Visual consequences:
Active FVGs extend dynamically to future bars. Mitigated FVGs freeze at mitigation point. Unlike standard FVG indicators that show partial fills, GB-FVG uses binary state (active/mitigated).
WHY CLOSED-SOURCE?
This script protects proprietary algorithms:
- Goldbach filtering integration: Combines gbMatches() function with FVG detection, testing middle bar timestamp (s2.t) against user-selected Goldbach array, only creating Fvg object when matches found
- Multi-timeframe precision: hCtf and lCtf methods that search through chart bars using offset calculations (ctfBarCount * idx) and mintick rounding to locate exact bar that created higher timeframe gap extreme
- Bar array synchronization: Security object maintains rolling 10-bar array with isNew flag coordination, preventing duplicate processing while enabling three-bar lookback without repeated security calls
- Time component matching: gbMatch function implementing four-component test (m, h, h+m, |h-m|) with ±1 tolerance against each Goldbach number, returning match status and exact/approximate classification
- Mitigation state machine: isMit flag with body-close detection (close <= l for bullish, close >= h for bearish) that freezes box extension (x2) at mitigation timestamp rather than current time
Standard FVG indicators show all gaps. GB-FVG adds Goldbach timing layer requiring complex timestamp extraction, component arithmetic, and match filtering before gap visualization.
TECHNICAL COMPONENTS
Core structures:
- Bar Object: Stores OHLC and timestamp for single bar from indicator timeframe
- Security Object: Manages request.security calls, maintains Bar array (size=10), tracks isNew flag, provides hCtf/lCtf precision methods
- Fvg Object: Contains gap coordinates (x, h, x2, l), Goldbach numbers text, isMit state, box drawing object
- Option Object: Centralized settings for timezone, Goldbach array, history, colors, mitigation type
Goldbach matching:
- gbMatch(n, t, timezone): Tests single Goldbach number against single timestamp's four components with ±1 tolerance
- gbMatches(nArray, t, timezone): Tests array of Goldbach numbers against timestamp, returns arrays
FVG detection:
- Bullish: if (s3.h < s1.l and gbMatches(array, s2.t) has matches) create FVG
- Bearish: if (s3.l > s1.h and gbMatches(array, s2.t) has matches) create FVG
- Label: Goldbach numbers joined with commas (e.g., "23,35,65")
Mitigation:
- if (sBodyMit and close inside gap) set isMit=true, x2=close_time
- if (not sBodyMit) always extend to future: x2 = time("", bars_back = -4)
HOW TO USE
Setup:
1. Apply to any chart (works on all symbols and timeframes)
2. Select FVG Timeframe (must be >= chart timeframe)
3. Choose Timezone (New York or Zurich) for Goldbach calculation
4. Select "All GB/CE" to use all 23 numbers, or enter custom list
5. Enter custom numbers as comma-separated values (e.g., "23,35,65,77")
6. Enable/disable "Mitigate on body close" for mitigation behavior
Chart Timeframe Requirements:
Chart timeframe must be equal to or lower than FVG Timeframe setting. For 1H FVG analysis, use 1H or lower chart (5m, 15m, 30m, 1H all valid). Cannot use 4H chart for 1H FVG.
Interpretation:
- Green box = Bullish FVG at Goldbach time (gap up, unfilled)
- Red box = Bearish FVG at Goldbach time (gap down, unfilled)
- Numbers in box = Goldbach numbers that matched middle bar timestamp
- Box extends right = Active FVG (not yet mitigated)
- Box stops = Mitigated FVG (price closed inside gap)
- Multiple numbers = Multiple time components aligned with different Goldbach numbers
Visual placement:
Box spans from gap bottom to gap top vertically. Horizontally spans from gap formation bar to current time (active) or mitigation bar (filled). Numbers display at right edge of box.
SETTINGS EXPLAINED
Settings:
- Timeframe: Select FVG detection timeframe (any timeframe >= chart TF valid)
- Timezone: Choose New York or Zurich for Goldbach time component calculation
- All GB/CE: Enable to use all 23 master Goldbach numbers
- GB/CE List: Disable "All GB/CE" to enter custom comma-separated list (e.g., "23,35,65,77")
- History: Number of FVGs to display (default: 9)
- Text Size: Label text size for Goldbach numbers (Auto, Tiny, Small, Normal, Large)
- Text: Text color for Goldbach number labels
- Up: Box color for bullish FVGs
- Down: Box color for bearish FVGs
- Mitigate on body close: Enable to stop box extension when price closes inside gap, disable to extend until current time
Timeframe selection:
Must select timeframe equal to or higher than chart. Examples:
- Chart 5m, FVG 15m = Valid
- Chart 5m, FVG 1H = Valid
- Chart 1H, FVG 15m = Invalid (error message shown)
Timezone selection:
New York (America/New_York) = EST/EDT timezone
Zurich (Europe/Zurich) = CET/CEST timezone
Chart display timezone does not affect Goldbach calculations. You can view charts in Tokyo time while calculating Goldbach numbers in New York time.
Custom number selection:
Enter numbers separated by commas with no spaces: 23,35,65,77
Invalid numbers (not in master list of 23) automatically filtered out
Minimum: 1 number (or enable "All GB/CE")
Maximum: all 23 numbers
Mitigation behavior:
- Enabled: Boxes stop extending when price closes inside gap (recommended for cleaner chart)
- Disabled: Boxes extend to current time regardless of fills (shows all historical gaps)
UPDATES
This script is actively maintained. Updates released through TradingView's native update system. For technical questions, use the comment section below.
Squeeze + Vol + Turbo + Slingshot + Breakout (Bottom Banners)DRW Turbo Banner — Volatility Expansion & Regime Shift Tool
Purpose & Originality
The Turbo Banner is a volatility-regime transition tool, not a momentum oscillator and not a signal generator by itself.
Its purpose is to help traders identify when the market shifts from compression / pause into true expansion, reducing false breakouts and chop trades.
Unlike standard ATR or volatility indicators that react late or fire constantly, this script focuses on context first, confirmation second.
---
What the Script Does (High-Level)
The Turbo Banner evaluates bar-by-bar volatility behavior relative to a smoothed baseline and displays a concise banner when expansion conditions are met.
At a high level, it monitors:
True Range vs ATR
Expansion is defined when real-time range meaningfully exceeds recent volatility norms.
Directional Bias (optional structure filter)
Direction can be confirmed using candle structure to avoid random spikes.
Streak Logic
Single volatility spikes are filtered.
Sustained expansion (multiple qualifying bars) is emphasized.
The result is a binary expansion state:
Expansion is either present or not present
No predictive guessing, no overfitting
---
How to Use the Turbo Banner
The Turbo Banner is designed to be used with structure, not alone.
Common workflows:
Compression / Pause → Turbo
Indicates a transition from balance to imbalance.
B-Wave or Chop → Turbo
Confirms when energy is actually releasing, not just attempting to.
Breakouts
Turbo helps validate whether a breakout has real volatility behind it.
Important:
The Turbo Banner does not tell you where to enter — it tells you when expansion is real enough to matter.
---
Best Use Cases
Intraday trading (5m–30m)
Futures, indices, and liquid equities
Works especially well after:
Squeezes
Consolidation ranges
Mean-reversion phases
---
What the Turbo Banner Is NOT
❌ Not a buy/sell signal
❌ Not a momentum oscillator
❌ Not predictive
It is a confirmation layer that helps answer:
“Is this move actually expanding, or is it noise?”
---
Design Philosophy
Markets spend more time compressing and pausing than expanding.
This script is intentionally selective so that when it activates, it represents a meaningful regime change, not constant activity.
---
Chart & Performance Notes
The banner is intentionally minimal to keep charts clean.
Logic is optimized to avoid excessive object creation and freezing.
Designed for use on a clean chart or alongside a small number of structural tools.
StO Price Action - Panel Trend Alignment [Demo]Short Summary
- Panel-based candle coloring indicator for multi-timeframe trend alignment
- Bullish / bearish states across up to 7 timeframes
- Designed to quickly assess directional confluence
Demo Restrictions
- Timeframe dropdown selections are limited
- Line style dropdown selections are limited
- Multi-timeframe functionality is removed or restricted
- Alerts are disabled or completely removed
- No code logic runs behind disabled GUI elements
Full Description
Overview
- This indicator displays trend alignment as colored bars in a dedicated panel
- Each bar represents the directional state (bull / bear) of a selected timeframe
- Focused on fast visual confirmation of multi-timeframe bias
Timeframe Configuration
- Supports up to 7 independent timeframes
- Each timeframe can:
- Follow the chart timeframe or use a fixed resolution
- Be shown or hidden individually
- Use custom bull and bear colors
- Automatic hiding first if a timeframe duplicates another active one
Trend State Logic
- Each timeframe resolves into a binary state Bullish or Bearish
- States are visualized as colored panel candles / blocks
- Real-time mode optionally updates last
Visual Encoding
- Bullish states use configurable green-based colors
- Bearish states use configurable red-based colors
Alerts
- Optional alert per timeframe
- Alerts trigger on directional changes
Usage
- Identifying multi-timeframe trend confluence
- Filtering trades to align with dominant structure
- Quick bias check before execution on lower timeframes
Notes
- Panel reflects trend state not entry signals
- Real-time mode show updates before bar close
- Best used together with structure and levels
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.
Eccodax Robust k-NN Machine Learning LorentzianHere is the complete, final, corrected, and clean code, already including:
✅ Fixed shadowing of the variable d
✅ No compilation warnings
✅ No temporal leaks
✅ Target = real future return
✅ Robust Lorentzian distance
✅ Correct Matrix structure
✅ Consistent feature engineering
✅ Min-Max normalization
✅ Weighted k-NN inference
✅ Correct price reconstruction
1. What this code is
It is a predictive indicator based on classic Machine Learning (k-Nearest Neighbors), fully implemented in PineScript v6, designed to:
Learn historical market patterns
Compare the current state with similar past states
Estimate the expected future price movement
Reconstruct a projected price consistent with the current level
It is not an oscillator, it is not a traditional technical indicator, and it does not react only to the immediate past.
2. What the Model Learns (Supervised Learning)
2.1 Features (Input Variables)
The model uses three dimensions of information, all normalized by Z-score:
Return
Measures the percentage change in price
Captures the immediate momentum of the market
Momentum (ROC)
Measures acceleration or deceleration of the movement
Differentiates trends from consolidations
Volatility
Measures the degree of market uncertainty
Adjusts the weight of strong movements vs. noise
These three variables form a market state vector.
2.2 Normalization (Z-Score)
Each feature is converted to:
Mean ≈ 0
Standard deviation ≈ 1
This ensures that:
No variable dominates the distance
The statistical comparison is valid
The model is stable in different price regimes
2.3 Target (Predicted Variable)
The model does not predict absolute price. It learns:
Observed future return after forecastBars
That is:
Learns movement, not level
Eliminates historical bias
Avoids predictions inconsistent with the current price
3. How the model makes the prediction
3.1 Search for similar patterns (k-NN)
For each current candle, the model:
Analyzes the last lookback candles
Calculates the Euclidean distance between the current state and each past state
Selects the k most similar states
Observes what happened after them
3.2 Inference
The predicted return is calculated as:
Weighted average of the future returns of the neighbors
Weights inversely proportional to the distance
More similar states → greater influence.
4. Price Reconstruction (Key Information)
From the predicted return, the model reconstructs:
Predicted Price = Current Close × (1 + Predicted Return)
Predicted Price = Current Close × (1 + Predicted Return)
This ensures that:
The forecast respects the current market level
The output is visually interpretable
There is no regression to past regimes
5. Relevant Information the Indicator Delivers
5.1 Predicted Price (Green Line)
What it is: Estimated price after forecastBars.
How to use:
Above the current price → bullish bias
Below → bearish bias
Large distance → expectation of strong movement
5.2 Predicted Return (Implicit)
Even though not plotted directly, it is the most important information in the model.
Positive → expectation of appreciation
Negative → expectation of decline
Negative → expectation of decline
Near zero → sideways market
5.3 Directional Classification (optional)
The model also acts as a binary classifier:
High if expected return > 0
Low if expected return < 0
This is used as:
Noise filter
Trend confirmation
False signal reduction
5.4 Implicit statistical context
The indicator carries information that is not visual, but is fundamental:
Market regime (trending vs. sideways)
Statistical similarity with the past
Relative confidence (via distance from neighbors)
6. What this indicator does NOT do
It is important to align expectations:
❌ Does not predict exogenous events
❌ Does not anticipate gaps
❌ Does not work well on illiquid assets
❌ Does not extrapolate long trends
k-NN replicates patterns, does not create scenarios Unprecedented.
7. Where this model works best
Markets with repetitive structure
Medium timeframes (5m – 1D)
Liquid assets
Environments with alternating regimes
8. How to use it in practice (professional recommendation)
Ideal use:
k-NN direction → bias
Technical indicator → timing
Risk management → execution
Never use it in isolation for entry.
9. Executive summary
This code delivers:
A functional supervised ML model in Pine
Prediction consistent with the current price
Statistical market direction
Reduction of historical bias
Solid foundation for quantitative strategies
Eccodax Advanced kNN Lorentziano Matrix1. What this code is
It is a predictive indicator based on classic Machine Learning (k-Nearest Neighbors), fully implemented in PineScript v6, designed to:
Learn historical market patterns
Compare the current state with similar past states
Estimate the expected future price movement
Reconstruct a projected price consistent with the current level
It is not an oscillator, it is not a traditional technical indicator, and it does not react only to the immediate past.
2. What the Model Learns (Supervised Learning)
2.1 Features (Input Variables)
The model uses three dimensions of information, all normalized by Z-score:
Return
Measures the percentage change in price
Captures the immediate momentum of the market
Momentum (ROC)
Measures acceleration or deceleration of the movement
Differentiates trends from consolidations
Volatility
Measures the degree of market uncertainty
Adjusts the weight of strong movements vs. noise
These three variables form a market state vector.
2.2 Normalization (Z-Score)
Each feature is converted to:
Mean ≈ 0
Standard deviation ≈ 1
This ensures that:
No variable dominates the distance
The statistical comparison is valid
The model is stable in different price regimes
2.3 Target (Predicted Variable)
The model does not predict absolute price. It learns:
Observed future return after forecastBars
That is:
Learns movement, not level
Eliminates historical bias
Avoids predictions inconsistent with the current price
3. How the model makes the prediction
3.1 Search for similar patterns (k-NN)
For each current candle, the model:
Analyzes the last lookback candles
Calculates the Euclidean distance between the current state and each past state
Selects the k most similar states
Observes what happened after them
3.2 Inference
The predicted return is calculated as:
Weighted average of the future returns of the neighbors
Weights inversely proportional to the distance
More similar states → greater influence.
4. Price Reconstruction (Key Information)
From the predicted return, the model reconstructs:
Predicted Price = Current Close × (1 + Predicted Return)
Predicted Price = Current Close × (1 + Predicted Return)
This ensures that:
The forecast respects the current market level
The output is visually interpretable
There is no regression to past regimes
5. Relevant Information the Indicator Delivers
5.1 Predicted Price (Green Line)
What it is: Estimated price after forecastBars.
How to use:
Above the current price → bullish bias
Below → bearish bias
Large distance → expectation of strong movement
5.2 Predicted Return (Implicit)
Even though not plotted directly, it is the most important information in the model.
Positive → expectation of appreciation
Negative → expectation of decline
Negative → expectation of decline
Near zero → sideways market
5.3 Directional Classification (optional)
The model also acts as a binary classifier:
High if expected return > 0
Low if expected return < 0
This is used as:
Noise filter
Trend confirmation
False signal reduction
5.4 Implicit statistical context
The indicator carries information that is not visual, but is fundamental:
Market regime (trending vs. sideways)
Statistical similarity with the past
Relative confidence (via distance from neighbors)
6. What this indicator does NOT do
It is important to align expectations:
❌ Does not predict exogenous events
❌ Does not anticipate gaps
❌ Does not work well on illiquid assets
❌ Does not extrapolate long trends
k-NN replicates patterns, does not create scenarios Unprecedented.
7. Where this model works best
Markets with repetitive structure
Medium timeframes (5m – 1D)
Liquid assets
Environments with alternating regimes
8. How to use it in practice (professional recommendation)
Ideal use:
k-NN direction → bias
Technical indicator → timing
Risk management → execution
Never use it in isolation for entry.
9. Executive summary
This code delivers:
A functional supervised ML model in Pine
Prediction consistent with the current price
Statistical market direction
Reduction of historical bias
Solid foundation for quantitative strategies
Relevant information provided by this code
1. Forecasted price (line)
Statistical projection consistent with the current level
Based on similar historical patterns
2. Implicit direction
Return > 0 → bullish bias
Return < 0 → bearish bias
3. Structural robustness
Lower sensitivity to outliers
Lower scale bias
Better adaptation to different regimes
This refactored version introduces significant improvements based on modern quantitative Machine Learning practices (similar to those found in jdehorty's "Lorentzian Classification" indicator):
Lorentzian Distance: Replaces the Euclidean distance (which is affected by noise and outliers) with Lorentzian Distance, which is much more robust for financial markets.
Matrix Structure: Uses the matrix object in Pine V6 to manage training data more efficiently and cleanly than loose arrays.
Feature Engineering (WaveTrend & RSI): Replaces simple Momentum with normalized indicators (RSI, WaveTrend, CCI, ADX), better capturing market dynamics.
Min-Max Normalization: Features are normalized on a 0-100 scale so that indicators with different magnitudes do not distort the distance calculation.
Inverse Distance Weighting: Instead of a simple average, the nearest neighbors (most similar) have greater weight in the prediction.
StO Price Action - Panel Trend Alignment [Light]Short Summary
- Panel-based candle coloring indicator for multi-timeframe trend alignment
- Bullish / bearish states across up to 7 timeframes
- Designed to quickly assess directional confluence
Full Description
Overview
- This indicator displays trend alignment as colored bars in a dedicated panel
- Each bar represents the directional state (bull / bear) of a selected timeframe
- Focused on fast visual confirmation of multi-timeframe bias
Timeframe Configuration
- Supports up to 7 independent timeframes
- Each timeframe can:
- Follow the chart timeframe or use a fixed resolution
- Be shown or hidden individually
- Use custom bull and bear colors
- Automatic hiding first if a timeframe duplicates another active one
Trend State Logic
- Each timeframe resolves into a binary state Bullish or Bearish
- States are visualized as colored panel candles / blocks
- Real-time mode optionally updates last
Visual Encoding
- Bullish states use configurable green-based colors
- Bearish states use configurable red-based colors
Alerts
- Optional alert per timeframe
- Alerts trigger on directional changes
Usage
- Identifying multi-timeframe trend confluence
- Filtering trades to align with dominant structure
- Quick bias check before execution on lower timeframes
Notes
- Panel reflects trend state not entry signals
- Real-time mode show updates before bar close
- Best used together with structure and levels
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.
Mkt-Viper ProMkt-Viper Pro
🔶 Overview
Mkt-Viper Pro is a comprehensive market intelligence suite designed to unify trend detection, structural analysis, and price action geometry into a single decision-making framework. Rather than relying on a single lagging calculation, Viper Pro utilizes a "Path Efficiency" model that weighs price movement against the energy (volatility and volume) required to achieve it.
The result is a chart overlay that separates statistically significant trend shifts from market noise. Traders receive adaptive Trend Signals based on volume and volatility thresholds, a background Trend Navigator Cloud for trend context, dynamic Kinetic Ranges for support/resistance, candle pattern detection, an automated Geometric Pattern engine, and much more detailed below. Internally, the system functions as a synaptic network—where momentum, volume, and price structure must align before a signal is validated.
In short, Mkt-Viper Pro is designed for traders who require a trend following and technical roadmap for filtering out low-quality volatility to focus on structural expansions and high-probability reversals.
🔶 What makes Mkt-Viper Pro unique?
Mkt-Viper Pro stands out by combining a volatility-adaptive trend engine with a complete confluence suite. Uniquely, it uses a "Path Efficiency" calculation to separate messy price action from true momentum, automatically filtering out noise during choppy markets. This core logic is then reinforced by multiple layers of environmental context—allowing you to check every move against the background Trend Navigator, Viper Band, Kinetic Ranges, geometric pattern engine and much more. Instead of relying on a single data point, the system provides you with suite of confluences to help you make well informed trading decisions.
Main Features
🔶 Viper Trend Signals
The core of the system is a sophisticated trend detection engine designed to filter out market noise. Instead of reacting to every minor price fluctuation, the algorithm evaluates momentum pressure relative to current volatility. It validates a directional shift only when the market exerts enough "energy" to breach calculated stability thresholds, ensuring that changes in trend are statistically significant rather than random noise.
These mechanics are translated onto the chart through a clean and intuitive visual interface:
Signal Logic:
Trend signals are generated when the price decisively shifts directional momentum. These are marked by clean Triangle Signals at the exact moment of the shift, keeping the chart uncluttered.
Trend Coloring:
To provide instant visual feedback on the market state, the indicator applies Candle Coloring in two distinct modes. Traders can choose a Static mode for clear, binary directional cues, or a Gradient mode that intensifies the color saturation as the trend gains strength and momentum.
Strong vs. Normal:
The system automatically grades every signal. A "Strong" classification is issued when the immediate momentum shift aligns perfectly with the broader, longer-term market context, identifying high-confluence setups with greater weight.
Auto-Tuning & Sensitivity Control
Market conditions are never static; volatility expands and contracts constantly. To address this, Viper Pro is equipped with a dual-mode calibration engine:
Auto-Tuning:
When enabled, the system actively measures "Path Efficiency"—calculating in real-time how choppy or direct price action is. It automatically adjusts its sensitivity, tightening validation criteria during clean trends and loosening them during chop to prevent false signals. Users can select from Fast, Moderate, or Slow profiles to suit their trading style.
Manual Tuning:
For traders who require fixed parameters for backtesting or specific asset classes, the system offers a granular 1–50 sensitivity dial. This allows for precise manual calibration to specific timeframes, giving you total control over how reactive the signals should be.
⚠️ Important:
These signals identify potential momentum shifts and should not be traded blindly. For high-probability outcomes, always validate the signal by ensuring it aligns with other confluences within the suite or other forms of technical analysis.
🔶 Trend Navigator Cloud
The Trend Navigator serves as the indicator’s "Context Awareness" layer, visualizing the broader ambient direction or "weather" of the market. Solving the classic dilemma between "lag" and "noise," this feature utilizes an Adaptive Flow Algorithm that adjusts its internal responsiveness based on real-time RSI and market velocity.
Smart Adaptation:
Instead of using a fixed lookback period that fails when market conditions change, the Navigator automatically detects the speed of price action. It tightens its tracking during impulsive trends to reduce lag, while loosening and smoothing itself during choppy consolidation to prevent false reversals.
Dynamic Structure:
The feature renders as a background cloud that expands and contracts with volatility. This creates a visual "breathing" support and resistance structure that naturally contains price action during healthy trends.
Usage:
Directional Bias:
When the Cloud is bullish color and below the trend, the macro environment is Bullish; look primarily for Long signals. When below the price action and bearish color, the environment is Bearish; focus on Short signals.
Trend Floor:
In established trends, the Cloud acts as a dynamic floor (or ceiling), highlighting high-probability zones for pullbacks and potential continuation entries.
Custom Tuning:
Users retain full control over the Navigator's behavior. You can enable Auto-Tuning to let the engine select the optimal sensitivity (Fast, Medium, or Slow) based on current conditions, or use the Manual Speed Dial (1–50) to fine-tune the cloud's reactivity to your specific timeframe or asset class.
🔶 Viper Band
The Viper Band is engineered as a multi-dimensional market utility, seamlessly consolidating four distinct technical concepts into a single, adaptive overlay. This unified approach provides a complete view of immediate price dynamics:
Trend Following:
It acts as an immediate directional filter. When the price is holding above the band, the short-term structure is Bullish; when below, it is Bearish. The band changes color dynamically to reinforce this state.
Dynamic Support & Resistance:
The outer edges of the band are volatility-adjusted. In a strong trend, the band creates a rising floor (or falling ceiling), acting as a trailing support zone where price often bounces to continue the move.
Market Equilibrium:
The center of the band represents the market's "fair value" or equilibrium point relative to the current timeframe. It filters out tick-by-tick noise to show the true mean price.
Price Magnet:
Because markets cannot stay overextended indefinitely, the Viper Band acts as a gravitational magnet. When price deviates too far from the band, it signals an overextended state, often preceding a "snap-back" or mean reversion event where price returns to the Band.
Usage:
Trend Health:
In a healthy, sustainable trend, the band often acts as a continuous trailing support or resistance zone.
Re-Entry:
For trend-followers, pullbacks that touch or test the Viper Band often present high-probability, low-risk opportunities to rejoin the dominant move.
🔶 Viper Kinetic Ranges (VKR)
Standard pivot points and static support lines often fail because they treat every trading session the same, ignoring the unique volatility profile of the current day. Viper Kinetic Ranges (VKR) solves this by generating dynamic Support and Resistance structures that actively adapt to the market's physical "energy."
Volume-Weighted Expansion:
Unlike standard volatility envelopes that rely solely on price range, VKR incorporates Volume Weighting. When volume flows into the market (e.g., during market opens or news events), the defined range automatically expands. This helps prevent "fake-out" signals by proving that the market needs more energy to validate a true breakout during high-activity periods.
State-Change Logic:
The levels do not drift aimlessly with every tick. Instead, they operate on a State-Change basis. The Support and Resistance levels remain locked and stable until the market exerts enough directional force to force a "state transition." When this happens, the levels "step" up or down to a new equilibrium zone. This stepping behavior helps traders visualize exactly when the market has accepted a new value area versus when it is simply ranging.
Concept:
Think of these levels as the "lungs" of the market. They expand and contract to show where price is statistically likely to find equilibrium or rejection based on the current expenditure of buying and selling energy.
Usage:
Trend Validation:
Use the central Equilibrium Level (Datum) as your directional "Line in the Sand." As long as price holds above this stepped line, the immediate value area is Bullish. A breach below signals a potential regime change.
Precision Targeting:
The outer Major Structures represent statistical exhaustion points extended by volatility. These are ideal, scientifically derived locations to set Take Profit orders or anticipate a mean-reversion bounce.
Support and Resistance:
Each level may produce some type of reaction and can act as support and resistance levels presenting potential opportunities for entries or profit taking.
🔶 Auto-Geometric Chart Patterns
Viper Pro features a "V7" pattern recognition engine that runs a continuous, frame-by-frame structural analysis of price action. Instead of waiting for a pattern to complete before drawing it (hindsight), this engine detects Wedges, Channels, and Triangles as they form in real-time.
Vertex Array Technology:
Unlike basic scripts that simply connect the highest highs and lowest lows, the Viper Engine stores historical pivot points in dynamic arrays. It analyzes the mathematical relationship between these points—calculating slope ratios and width consistency—to determine if a valid geometric structure exists.
⚠️ Technical Disclosure: Pattern Dynamic Regeneration
The Geometric Pattern Engine utilizes a process of "Functional Repainting" (Dynamic Object Regeneration). Because chart patterns such as Wedges and Channels are evolving structures, the indicator continuously re-evaluates the validity of vertices in real-time. As the price expands, trend lines will adjust to new market data to keep information relevant. Additionally, as price data unfolds, old patterns or invalidated patterns will be removed from the chart automatically in order to print a newer more recent pattern to keep your charts clean and up to date on the most recent price data.
🔶 Candle Pattern Recognition
The Candle Pattern Recognition Module utilizes a Context-Aware Engine to scan for high-probability Reversal and Continuation structures (Hammers, Stars, Dojis, and Absorptions).
Trend & Context Filtering:
A pattern is only as good as its location. The engine filters signals based on the broader trend (e.g., looking for Hammer candles only during downtrends and Falling Stars only during uptrends). This ensures you are trading reversals at logical structural points, not random noise.
Quality & Volume Logic:
The system includes an integrated "Quality Filter." It ignores patterns formed on low liquidity. For a signal to be valid, it must demonstrate a "Footprint of Interest"—verified by a relative spike in Volume or an expansion in ATR (Range) relative to the recent lookback period.
The Patterns:
Absorption:
Highlights powerful shifts in control (often called Engulfing) where one side decisively overtakes the other.
Stars & Hammers:
Pinpoints rejection wicks that signal exhaustion.
Dojis:
Identifies moments of indecision and potential equilibrium.
🔶 Swing Failure Pattern (SFP) Detection
Institutional trading often involves seeking liquidity at obvious structural levels. The SFP engine is designed to automatically detect these "Liquidity Sweeps" or "Bull/Bear Traps" where the market hunts for stop-losses before reversing.
The Logic:
The system actively monitors significant Pivot Points. An SFP is validated when the price pierces a key Pivot High or Low—taking out liquidity—but subsequently fails to hold that level and closes back within the previous range.
Visuals:
When a sweep occurs, the indicator plots a discrete dashed line connecting the original pivot to the current "sweep" candle. This visualizes the exact "Trap Zone" where breakout traders were caught offside, signaling a potential high-probability reversal opportunity.
Usage:
Fade the Breakout:
An SFP is a classic "Fade" signal. When a Bearish SFP appears at a high, it implies that buyers have potentially been trapped; traders often look for Short entries here. Conversely, a Bullish SFP at a low suggests sellers are trapped, offering a potential Long opportunity.
🔶 Reversal Cloud
The Reversal Cloud acts as a statistical boundary gauge, designed to visualize when price action has extended significantly beyond its average value. Markets typically spend the majority of their time within a standard distribution; this feature highlights the rare moments when volatility pushes price into statistical extremes.
The Logic:
The engine calculates a dynamic deviation envelope based on recent market volatility. Rather than predicting a specific turning point, it identifies zones where the market is "stretched" relative to its baseline. When price enters this colored "Horizon," it indicates that the current move is statistically extended, which historically correlates with periods of consolidation or mean reversion.
Visuals:
The feature renders as a shaded zone at the upper and lower limits of the chart. It remains passive during normal price action but highlights "Breach" events when price pushes into these outer deviation bands.
Usage:
Context Awareness:
Use the Cloud to gauge the maturity of a move. Entering new impulsive trades while inside the Reversal Cloud carries higher statistical risk, as the price is already far from equilibrium.
Reaction Watch:
For traders already in a position, a breach of the Cloud serves as a cue to tighten risk management or monitor for signs of momentum loss, as the market digests the recent expansion.
⚠️ Important Note:
While these zones represent statistical extremes, they are not hard barriers. In powerfully trending markets or during high-impact news events, price can "ride" or expand these bands for extended periods without reversing immediately. Do not trade these zones blindly; always wait for secondary confirmation of momentum loss (such as a structural break or a rejection candle) before anticipating a reversal.
🔶 Key Levels & Session Structure
Successful trading requires knowing where liquidity resides. Viper Pro automates the analysis of "Market Memory" by mapping significant historical and time-based structures directly onto your chart.
The Logic:
It automatically plots the Previous Day (PDH/PDL), Previous Week (PWH/PWL), and Previous Month (PMH/PML). These levels often act as major "Magnets" where price reverses or accelerates as it seeks liquidity.
Session Profiles:
Intraday price action is heavily influenced by the distinct behaviors of the global trading centers. This module highlights the trading ranges of the Asia, London, and New York sessions.
The Logic:
By visualizing the High and Low of the previous session, traders can spot "Session Sweeps"—a common phenomenon where the market manipulates price to break a prior session's high or low to trap traders before reversing.
Usage:
Confluence:
These levels serve as an excellent filter for Trend Signals. For example, a "Buy" signal generated directly below a Weekly High requires caution, whereas a signal bouncing off a Daily Low carries higher conviction.
Targeting:
Use these static structural levels as scientifically derived potential Take Profit zones, as price often pauses or reacts when testing these historical boundaries.
🔶 Opening Range Breakout (ORB)
The first 15 minutes of the trading session (09:30–09:45 ET) often establish the initial balance and sentiment for the entire trading day. The Viper ORB engine automates the identification of this critical volatility window.
The Logic:
The system defines the "Opening Range" by capturing the highest high and lowest low of the session's first 15 minutes. It waits for the opening time window to fully close before projecting the levels, ensuring you are planning trades against confirmed structure rather than developing noise.
Visuals:
Once the opening window concludes, two distinct levels (High and Low) are projected forward for the remainder of the session.
Usage:
Breakout Plays:
A clean close above the Opening Range High often signals strong buying intent, suggesting a trend day.
Range Fading:
If price breaks the range but fails to hold, price often rotates back to the opposite side of the opening range.
Support/Resistance Flip:
Later in the day, these levels often act as strong support or resistance when retested.
🔶 Visual Intelligence (Color Themes)
Visual clarity is essential for rapid decision-making. A cluttered or poorly contrasted chart can lead to cognitive fatigue. To address this, Mkt-Viper Pro features a global Color Theme Engine that instantly synchronizes every element of the suite—signals, candles, clouds, and text—to a unified palette.
The Presets:
The system comes with five professionally designed profiles to suit different trading environments and lighting conditions:
Viper Original: High-contrast Neon Green & Purple (Optimized for Dark Mode).
Classic: Standard Green/Red configuration for traditionalists.
Cool Blues: A calming Blue/Violet palette designed to reduce emotional reactivity.
Ember & Ash: High-warmth Orange/Slate contrast.
Monochrome: Grayscale/Silver logic for distraction-free structural analysis.
Customization:
Traders with specific branding requirements or accessibility needs (such as color blindness) can select "Custom Theme." This unlocks distinct color inputs, allowing you to define your own specific Bullish, Bearish, and Neutral colors that instantly propagate across the entire indicator suite.
🔶 How to use:
Mkt-Viper Pro is designed to reduce "Analysis Paralysis" by organizing data into a clear decision hierarchy. Rather than chasing every signal, we recommend a workflow based on Confluence:
Trend Continuation (The Pullback)
This is the highest probability approach, trading with the momentum.
1. Identify Trend:
Ensure the Viper Trend Signal is Bullish and the Navigator Cloud is bullish.
2. Wait for Value:
Do not chase pumps. Wait for price to pull back into the Navigator Cloud or the center of the Viper Band .
3. Trigger:
Look for a specific confirmation candle (e.g., a Hammer or Bullish Absorption ) to form within that support zone.
4. Target:
Target the next Kinetic Range (VKR) resistance level above.
Structural Reversal (The Fade)
1. Identify Exhaustion:
Wait for price to push into the Reversal Cloud (Statistical Extreme) or hit a major HTF Level (e.g., Previous Week High).
2. Spot the Trap:
Watch for an SFP (Swing Failure Pattern) or a Geometric Wedge pattern to form, indicating momentum loss.
3. Confirmation:
Wait for a counter-trend Candle Pattern (e.g., Falling Star) or a flip in the Viper Trend Signal before entering. Trying to catch a falling knife without this confirmation is not recommended.
The Breakout
Trading expansion from consolidation.
Context: Identify a tightening Geometric Pattern (Triangle) or a clearly defined
Opening Range (ORB) .
Expansion: Wait for a clean candle close outside of the pattern/range.
Validation: Ensure the breakout moves through the Kinetic Range Equilibrium , proving that real volume is backing the move.
Note:
Mkt-Viper Pro is engineered as a complete standalone system for Trend and Structural analysis. However, it also functions as the core "Chart Overlay" module within the wider Mkt-Viper 3-part ecosystem. It is calibrated to synchronize visually and mathematically with its sister scripts, ensuring a unified data view without conflicting signals.
🔶 Realistic Expectations & Risk Management
It is vital to understand that Mkt-Viper Pro is a technical analysis instrument, not a crystal ball. No algorithm can predict the future with 100% certainty. The goal of this system is not to eliminate losses, but to provide a statistical edge by aligning multiple factors of confluence.
Win Rate vs. Risk/Reward:
High-probability trading is not just about "Win Rate"; it is about the relationship between Risk and Reward.
The Edge:
By using the SFP wicks or Viper Band extremes for tight stop-loss placement, and targeting the Kinetic Ranges for exits, the system is designed to identify setups with favorable Risk-to-Reward ratios (e.g., 1:2 or 1:3).
The Reality:
Even a system with a modest win rate can be highly profitable if the winning trades are larger than the losing trades. This suite is built to help you identify those skewed opportunities.
Market Conditions & Drawdown:
Like all trend-following systems, the greatest risk occurs during undefined, choppy range-bound markets where price whipsaws without momentum.
While the "Path Efficiency" filter is designed to minimize this, false signals can and will occur during periods of low liquidity.
Mitigation:
We strongly recommend avoiding entries when the Navigator Cloud is flat/contracted (indicating zero momentum) or when price is stuck between two tight Kinetic Range levels.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, back test, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
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.
DemonHC14ReverseDemonHC14Reverse
Counter-Trend Signal Tool for Binary Options
Apply and use on 1-minute charts.
We recommend entering trades at the suggested times for each of the three counter-trend signals:
Counter-Trend 1: 3 minutes
Counter-Trend 2: 3 minutes
Counter-Trend 3: 1 minute
バイナリーオプション用逆張りサインツール
１分足チャートに適用して使って下さい。
３種類の逆張りサインそれぞれの推奨取引時間でのエントリーをお勧めまします。
逆張り１：３分
逆張り２：３分
逆張り３：１分
DemonHC14FowerdDemonHC14Fowerd
Trend-Following Signal Tool for Binary Options
Apply and use on 1-minute charts.
Fixed for Turbo 1-minute trades.
When momentum is strong, a follow-up GO signal will appear to the right of the chart after the initial signal.
This is your opportunity. Use it effectively.
バイナリーオプション用順張りサインツール
１分足チャートに適用して使って下さい。
Turbo１分取引固定です。
勢いが有る時は初動サインに続けて、チャート右に追撃GOサインが出てきます。
こちらが出てきたらチャンスです。有効に活用ください。
COT Commercials Base vs Quote Strength (Dynamic)This indicator measures and compares Commercial (Smart Money) positions of the Base and Quote currencies in a Forex pair, displaying their relative strength as a smooth, dynamic line.
It calculates a 0–100 strength index:
100 → Base Commercials are strongly dominant (bullish for the pair)
50 → Neutral, no clear dominance
0 → Quote Commercials are strongly dominant (bearish for the pair)
Unlike traditional binary COT signals, this indicator shows continuous changes in positioning. Small shifts in Commercial activity slightly move the line, while larger imbalances push it toward the extremes.
This makes it ideal for:
Identifying trend strength and market bias
Spotting early reversals and divergences
Confirming breakouts or trend continuation
Understanding the relative influence of Smart Money in Forex markets
It provides a clear, real-time view of which currency in a pair is favored by Commercial traders, giving a professional edge in market analysis.
