Opening Gaps (RTH Gap, NDOG, NWOG, NMOG) [Tradeisto]This indicator is a comprehensive tool developed to monitor significant market opening gaps across daily, weekly, and monthly timeframes, as well as specific Regular Trading Hours (RTH) gaps. It automates the detection and visualization of these key institutional levels, providing real-time status updates and mitigation tracking.
Key Features:
Multi-Timeframe Gap Tracking:
NDOG (New Day Opening Gap): Monitor daily opening gaps based on official settlement.
NWOG (New Week Opening Gap): Track weekly opening gaps.
NMOG (New Month Opening Gap): Track monthly opening gaps.
RTH Gap: Specifically monitors the Regular Trading Hours (RTH) gap.
Live RTH Gap Dashboard:
Real-Time Status: Instantly see if the current RTH gap is Bullish or Bearish.
Mitigation Tracking: Live updates on whether the gap is Unmitigated, Partially Mitigated, or Fully Mitigated (100%).
Smart Range Display: Shows the exact gap range (Abs(PrevClose - Open)). Displays "RTH Closed" during post-market hours.
Professional Settlement Logic:
Utilizes advanced ticker.modify logic to fetch Official Settlement Prices for true gap accuracy, ensuring levels match institutional standards.
Includes a Back-Adjusted Futures option for continuous contract analysis.
Intelligent Chart Management:
Auto-Hide on HTF: Automatically hides gap boxes and labels on timeframes greater than 4 hours to keep charts clean.
Customizable History: User-defined limits for how many days, weeks, or months of history to display.
Visual Customization:
Full control over colors, labels, and visibility for every gap type.
Clean, informative labels with Trading Day accuracy.
Statistics
Magic Hour Range + Window Levels (0/50/75/100 + Extensions)This indicator plots one or more “Magic Hour” ranges (by ET hour) by drawing the hour’s high/low box, then extending an aligned post-hour analysis window for a set number of hours. Inside that window it overlays key reversion targets—0% (High), 50% (Mid), 100% (Low), optional 25%/75%—plus optional extension levels beyond the range (±25/50/75/100% and extras). All levels are clipped to the analysis window for a clean, session-by-session view of range, targets, and extensions.
Opening Range (RTH, Globex, Tokyo, London) [Tradeisto]This indicator provides a comprehensive solution for monitoring Opening Ranges across major global trading sessions—RTH (New York), Globex, Tokyo, and London, within a single script. It is designed for stability and precision on all timeframes.
Key Features
Multi-Session Support: Track four distinct opening ranges simultaneously:
RTH (New York): Auto-detects based on asset class:
Indices (NQ, ES, YM): 09:30 NY
Metals (Gold/Silver): 08:20 / 08:25 NY
Energy (Oil/NatGas): 09:00 NY
Currencies & More: Automatically sets the correct pit open.
Globex: 18:00 America/New_York
Tokyo: 09:00 Asia/Tokyo
London: 08:00 Europe/London
Native Timezone Handling:
Automatically adjusts for Daylight Saving Time (DST) using native Pine Script timezones.
Smart Labeling: Evening sessions (Globex, Tokyo) display the correct "Trading Day" date (e.g., Sunday evening labeled as Monday).
Hybrid Data Engine:
Ensures stability by automatically switching data fetching methods based on your chart's timeframe.
Zoom In: Uses request.security_lower_tf for high-resolution data when the Chart Timeframe > Session Duration.
Zoom Out: Uses standard request.security when the Chart Timeframe <= Session Duration, preventing runtime errors.
Customizable Durations:
Independently configure durations for each session (30s, 1m, 5m, 15m, 30m).
How to Use
Add Opening Range to your chart.
Open Settings to enable or disable specific sessions.
Select the desired Duration for each session.
Customize colors and borders to fit your chart theme.
ATR Volatility RegimeATR Volatility Regime
A volatility classification indicator that uses ATR (Average True Range) percentile ranking to identify LOW , NORMAL , HIGH , or EXTREME volatility conditions.
Displayed as a separate pane oscillator (0–100 scale) with colored zones.
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💡 WHY THIS INDICATOR?
Most volatility indicators show raw ATR — a number without context. Is ATR = 50 high or low? Depends on the asset and recent history.
This indicator answers: "Is current volatility high or low for THIS asset, right now?"
What it adds over standard ATR:
Percentile context — Compares current ATR to its own history
Regime classification — Actionable labels instead of raw numbers
Visual zones — Instant read without interpretation
Optional MTF — Lock to a fixed timeframe while viewing another
Auto-adapts — Works on any asset without manual threshold tuning
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📐 CORE CONCEPTS
ATR (Average True Range)
Measures volatility in price units — how much an asset typically moves per bar. Directionless (magnitude only, not direction).
Calculation:
True Range = the greatest of:
High − Low (current bar's range)
|High − Previous Close| (gap up captured)
|Low − Previous Close| (gap down captured)
ATR = Moving average of True Range over N bars (default: 14)
Percentile Rank (Pctl)
Answers: "What percentage of historical values is the current value greater than?"
Pctl = 0% → Lowest ATR in lookback period (extreme compression)
Pctl = 50% → Median ATR (typical volatility)
Pctl = 100% → Highest ATR in lookback period (extreme expansion)
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🎯 WHAT IT DOES
Classifies current volatility into four regimes:
LOW (< 25th percentile) — Compression, breakout likely brewing
NORMAL (25th–50th percentile) — Typical market conditions
HIGH (50th–75th percentile) — Elevated volatility, use caution
EXTREME (> 75th percentile) — Rare expansion, tighten stops or stay flat
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📊 DISPLAY COMPONENTS
Oscillator Line (0–100)
ATR percentile rank over time. Color matches regime:
Blue = LOW
Gray = NORMAL
Orange = HIGH
Red = EXTREME
Zone Backgrounds
Colored bands at threshold levels for instant visual reference.
Status Label
VOL — Current regime
ATR — Raw ATR value (for stop sizing)
Pctl — Percentile rank (0–100%)
TF — Active timeframe (chart or fixed)
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📈 HOW TO USE
LOW Volatility (Pctl < 25%):
Market compressed — "calm before the storm"
Watch for breakout setups
Pctl = 0% often precedes significant moves
NORMAL Volatility (Pctl 25–50%):
Typical conditions
Standard position sizing and stops
HIGH Volatility (Pctl 50–75%):
Elevated movement — reduce size
Widen stops to avoid noise
EXTREME Volatility (Pctl > 75%):
Rare, intense conditions
Avoid new entries or tighten risk
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⚙️ SETTINGS
ATR Settings:
ATR Length (default: 14) — Period for ATR calculation
Percentile Lookback (default: 100) — Bars for percentile ranking
Timeframe:
Use Fixed Timeframe (default: off) — Lock calculation to specific TF
Fixed Timeframe (default: D) — TF to use when fixed mode enabled
Thresholds:
Low Threshold (default: 25)
High Threshold (default: 50)
Extreme Threshold (default: 75)
Display:
Show Zone Background — Toggle colored fills
Show Status Label — Toggle info label
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📋 SUGGESTED LOOKBACK BY ASSET
Crypto — 100 bars (fast regime shifts)
Stocks — 252 bars (one trading year)
Forex — 100–150 bars
Commodities — 150–200 bars (seasonal patterns)
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🔔 ALERTS
Vol → EXTREME
Vol → HIGH
Vol → LOW
Vol exits HIGH
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💡 PRACTICAL APPLICATIONS
Stop-Loss Sizing:
Use raw ATR for stops. Example: Stop = Entry − (1.5 × ATR)
Position Sizing:
Reduce size when percentile is HIGH or EXTREME.
Entry Filtering:
LOW regime = prepare for breakout
EXTREME regime = avoid new entries
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📝 NOTES
Works on any timeframe — adapts to chart or locks to fixed TF
ATR is non-directional — magnitude only
Percentile auto-adapts to each asset's volatility profile
Not a standalone signal — combine with trend/regime filters
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🏷️ TAGS
volatility, ATR, average-true-range, percentile, regime, risk-management, position-sizing, swing-trading, MTF
Quant Stats: Alpha, Beta, R2Quant Stats Indicator for TradingView: Alpha, Beta, and R-Squared
Overview
The Quant Stats Indicator is a professional-grade Pine Script tool designed for quantitative traders and hedge fund managers who need real-time analysis of stock or ETF performance against a benchmark using three fundamental CAPM metrics: Beta, R-Squared, and Alpha.
This indicator calculates three critical measurements that answer every quant trader's core questions: How volatile is this asset relative to my benchmark? How much of its performance is independent of the benchmark? And how much excess return am I achieving after adjusting for risk?
The Three Metrics Explained
Beta (β) measures systematic risk and volatility relative to your chosen benchmark. A Beta of 1.0 means the asset moves in lockstep with the benchmark. A Beta above 1.0 indicates higher volatility—if the market rises 10%, a Beta-1.5 asset should rise 15%. Conversely, a Beta below 1.0 indicates lower volatility, making it a defensive position. This metric helps you understand how much market exposure you're truly taking.
R-Squared (R²) quantifies what percentage of an asset's price movement can be explained by benchmark movements. An R² of 0.95 means 95% of the asset's moves are driven by the benchmark, leaving only 5% unexplained. Conversely, an R² of 0.2 means 80% of the asset's movement is independent of the benchmark. This distinction is crucial: high R² is desirable for passive index tracking but indicates weak alpha potential; low R² reveals genuine independent returns, exactly what active managers seek.
Alpha (α) reveals Jensen's Alpha—the excess risk-adjusted return after accounting for the return you "should" earn given your Beta exposure. A positive Alpha of 15% means you're outperforming the market by 15 percentage points after adjusting for systematic risk. This is the holy grail of stock picking: pure skill-driven excess return, not luck from market exposure.
How to Use It
Configure four key inputs: your benchmark ticker (default SPY, but use QQQ for tech-focused analysis or sector-specific ETFs), the lookback period in days, and the risk-free rate reflecting current Treasury yields. The lookback period is critical. Use 20 days for tactical trading to capture short-term sentiment and beta spikes; use 63 days for swing trading and quarterly rebalancing; use 252 days for structural asset allocation decisions.
The indicator plots Beta as a blue line, R-Squared as a red shaded background area, and Alpha as a green line in a sub-panel. Reference gridlines appear at Beta = 1.0 (market-equivalent volatility) and Alpha = 0.0 (breakeven performance), making interpretation intuitive.
Practical Applications
For swing traders monitoring a 63-day window, seek positions with low Beta (below 0.8) and positive Alpha—these are defensive winners. Avoid high Beta (above 1.2) with low R² unless you specifically want high-volatility speculation. Long/short hedge funds should use a 20-day lookback to detect regime changes: sudden Beta spikes often precede correlation breakdowns, while R² collapses signal rising idiosyncratic risk requiring immediate rebalancing.
For ETF portfolio construction, high R² (above 0.95) indicates index-tracking that doesn't justify active management fees. Low R² (below 0.3) combined with positive Alpha reveals genuine active management skill. The sweet spot is moderate Beta (0.5–0.8) with low R² and positive Alpha—a true diversifier that reduces portfolio volatility while generating independent returns.
Critical Interpretation Rules
A common mistake is assuming high R² is always desirable. It isn't. Passive index funds naturally have high R²; active managers should target low R² with high Alpha. Similarly, don't assume Alpha above 10% is sustainable—short-term Alpha (20–100 days) is inherently volatile and often represents temporary mispricings rather than repeatable skill. Always pair Beta analysis with R² interpretation; Beta alone ignores idiosyncratic risk, liquidity constraints, and tail risk.
Configuration Recommendations
Conservative investors should use SPY as benchmark with a 252-day lookback, targeting Alpha above 3% and Beta below 0.8. Growth-oriented portfolios might use QQQ with a 63-day lookback, targeting 8–12% Alpha and tolerating Beta up to 1.3. Hedge funds pursuing market-neutral strategies should use SPY with a 20-day lookback, set the risk-free rate to 2% (anticipating rate cuts), and target 15%+ Alpha while maintaining Beta below 0.3.
Important Limitations
The indicator is backward-looking; historical statistical relationships may not persist. Shorter lookback periods are noisier but more responsive; longer periods smooth noise but lag regime changes. Choosing the wrong benchmark completely invalidates analysis. Finally, the indicator doesn't account for tail risk or extreme market events where correlations spike unpredictably and Beta becomes unreliable.
Use this tool to separate signal from noise and identify true alpha generators. Apply it consistently, validate results against official fund factsheets, and monitor for 2–4 weeks before making significant portfolio decisions.
Monthly Seasonality AnalyzerThis indicator analyzes historical performance/seasonality of a chosen month, from date of inception to present. Users can choose any calendar month via dropdown menu.
For each historical month selected, it will calculate the monthly percentage gain/loss, range(volatility), and average gain/loss percentage, average range percentage across all recorded years. Positive returns are colored green and negative returns are red. Also, calculates if the selected month was bullish(open>close) or bearish.
When current chart month matches the selected month, it shows the in-progress range as well.
Data is collected from 1930 to present. Results are shown in vertical and horizontal tables. If the vertical table exceeds a 36 years, the script automatically switches to horizontal table to display all the data, with option to change table position.
Overall this tool is valuable for seasonality research, such as Santa Rally, May Go Away and swing trading/ position trading to capture the monthly PO3 range.
Most seasonality indicators show all 12 months at once or use daily bars. This one zooms in deeply on one month only, providing detailed per-year breakdowns, accurate completed-month stats, and a practical live range display.
The script uses arrays to store years, gains, and ranges. Uses table.new(), table.cell(), table.merge_cells() for easily readable result display. Code handles the current in-progress month separately (shows live range without including it in historical averages).
**Script will not run on any timeframe other than monthly and displays error otherwise. Script is best used on spot and not futures.
BC catchBottom Catcher is a comprehensive reversal indicator designed to find high-probability bottoms. Unlike standard indicators, it combines Momentum, Volume, Price Action, and Trend Filters into one powerful tool.
Key Features:
Smart Filtering: Only signals when Stochastic is oversold AND Volume is spiking (Institutional buying) AND Price Action shows strength.
Real-time Statistics Dashboard: The table automatically calculates the historical win rate for hitting 20%, 30%, ... 100% profit targets based on your custom Stop Loss settings.
Trend Classification:
Gold Signal: Above EMA 200 (Trend Pullback).
Purple Signal: Below EMA 200 (Oversold Bounce).
Perfect for traders who want data-driven decisions rather than guessing bottoms.
BERNA (Boundary-Encoded Resonance Network Architecture)BERNA — Boundary-Encoded Resonance Network Architecture
BERNA is a research-grade indicator that estimates the remaining structural capacity of the current market regime.
Unlike trend, volatility, or momentum tools, BERNA does not measure price direction — it measures how much of the regime’s internal capacity has already been consumed.
This script implements the BERNA model published on Zenodo (Bülent Duman, 2026).
It is intentionally minimal and uses only OHLC data.
What BERNA measures
BERNA outputs a structural capacity state:
τ = Σ / Θ (normalized structural stress)
Λ = Θ − Σ (remaining structural capacity)
Interpretation:
High Λ / low τ → the regime has structural endurance
Rising τ → capacity is being consumed
τ → 1 (Λ → 0) → rupture proximity (capacity exhaustion)
This makes BERNA a forward-looking structural capacity variable, not a price oscillator.
What is inside this script
This implementation contains the following components:
Efficiency proxy (DERYA-like, but not the full public DERYA)
BERNA uses a simple microstructure efficiency proxy computed as:
E = |close − open| / (high − low)
This is conceptually “DERYA-like” but it is not the full DERYA framework.
No external/public DERYA source code is embedded here.
Standard technical primitives used
This script uses only basic primitives commonly found in technical analysis:
Absolute value and range normalization
Thresholding (regime binning)
Power transform on range (rng^p)
There is no EMA, RSI, MACD, ATR, ADX, Fisher, Kaufman, or other indicator embedded.
All computations are internal and deterministic.
3-state structural regime binning (K = 3)
The efficiency proxy E is discretized into three regimes using user thresholds:
Low efficiency
Mid efficiency
High efficiency
Each regime has its own capacity Θ and stress multiplier β.
Structural stress accumulation (Σ) and rupture proximity
Stress increment is defined as:
dΣ = β · (1 − E) · (range^p)
Σ accumulates inside a regime and is capped by Θ.
In this prototype, Σ resets on regime change by construction (regime-gated accumulation).
The rupture proximity is expressed through τ and Λ.
How to use BERNA
BERNA is designed as a regime-health and fragility overlay, not a buy/sell trigger.
Typical uses:
Detect when an ongoing move is structurally late-stage (τ high, Λ low)
Avoid initiating trades when capacity is nearly exhausted
Compare structural resilience across assets and regimes
Use alongside price/trend/volume systems for context
Do not use BERNA alone as a trading signal.
BERNA tells you “how much structure is left”, not “where price will go.”
Visuals
Efficiency (E) shows the bar-level microstructure efficiency proxy
τ shows normalized structural stress (capacity consumption)
Λ shows remaining structural capacity
Dotted lines mark warning and critical rupture proximity levels
Important notes
BERNA is not RSI, MACD, ATR, ADX, Fisher, Kaufman, or a volatility model
BERNA does not predict price direction
BERNA does not issue entry/exit signals
BERNA is a structural capacity diagnostic
This script does not embed any external/public indicator code; all logic is implemented directly in Pine.
Risk and disclaimer
This script is provided for research and analytical purposes only.
It is not financial advice and must not be used as a standalone trading system.
Markets are uncertain.
All trading decisions and risks remain entirely the responsibility of the user.
BERNA: Boundary-Encoded Resonance Network Architecture
A Structural Failure Theory of Financial Regimes Based on Endogenous Capacity Depletion
Author: Duman, Bülent
Affiliation: Independent Researcher
Reference: zenodo.org
IcebergCryptoX - Week Data Gap📊 BTC WEEKEND DATA COLLECTION
This indicator analyzes Bitcoin movements during weekends when traditional US markets are closed.
🎯 DATA COLLECTED:
- Gap from Friday close → Monday open (%)
- Maximum upward/downward movements during the weekend
- Total weekend range
- Mean reversion rate (return to Friday closing price)
- Movement direction (positive/negative/neutral)
- Historical records (biggest gaps and ranges)
📈 FEATURES:
✓ Colored zones to visually identify weekends
✓ Detailed labels on each weekend with key metrics
✓ Real-time statistics table
✓ Tracking of extremes and averages
✓ 100% data collection (no trading signals)
⚙️ PARAMETERS:
- Display weekend zones (on/off)
- Display labels (on/off)
- Statistics table (on/off)
- Significant movement threshold (customizable)
📉 USAGE:
Ideal for analyzing BTC volatility patterns outside US trading hours and identifying recurring opportunities.
Recommended timeframe: 15min to 1H
Week Levels (OHLC, Settlement, CE) [Tradeisto]Weekly Levels (Tradeisto) is a sophisticated tool designed to bring institutional-grade weekly analysis to your chart. It goes beyond simple horizontal lines by combining authoritative Settlement data with pixel-perfect origination times, ensuring your levels are both accurate and contextually precise.
Key Features
Dual Precision Technology:
Price Accuracy: Uses the authoritative Weekly timeframe to capture Settlement
prices,
ensuring your levels match official exchange data (critical for Futures).
Visual Precision: Uses 15-minute timeframe data to pinpoint the exact origination
time of the High and Low. Your lines start exactly when the level was created, not just at the
"start of the week".
Dynamic Current Week:
Live Updates: Watch the "Current Week" Open, High, Low, and CE (50%) develop in
real-time.
Auto-Rename: When the trading week closes (e.g., Friday Settlement), the "Current"
labels automatically switch to "Week Open/High/Low" labels, seamlessly transitioning into
history.
Smart Labeling:
"Prev." Prefix: Automatically distinguishes the immediate previous week (labeled
"Prev.") from older history (labeled "Week").
Settlement Awareness: Automatically labels the Close as "Settlement" for Futures
contracts when enabled, and "Close" for other assets.
Historical Reference: Configurable "Weeks to Show" allows you to keep a clean chart or dig deep into past market structure.
Settings
Settlement as Close: Toggle this to prioritize the Settlement price for the Weekly Close (Standard for Futures analysis).
Weeks to Show: Control how much history remains on your chart.
Current Week Visibility: Toggle individual components for the developing week (Open, High, Low, CE).
Tradeisto delivers a professional, clean, and highly accurate weekly framework for serious market analysis.
OT Zones Pro | Intraday Quantitative & Macro LevelsNote to Moderators & Community: First and foremost, I would like to offer my sincere apologies if the previous description of this tool was insufficient or lacked the technical depth required to demonstrate its originality. My intention is solely to provide a robust analytical tool for the community based on specific mathematical models, and never to mislead or cause harm to any trader. We are committed to transparency regarding the methodology used while protecting the proprietary values of the code.
Concept & Methodology OT Zones Pro is not a standard Support & Resistance indicator, nor does it use public domain formulas like Fibonacci, Pivot Points, or standard Moving Averages. Instead, it is a custom-built Quantitative Volatility Model designed to identify high-probability institutional interest areas specifically for Intraday Trading .
The script operates on two distinct proprietary layers:
Dynamic Volatility Bands (The Math): Unlike static levels or common open-source indicators, this engine operates on a strict institutional quantitative perspective . It calculates dynamic thresholds where each asset class triggers a unique calculation logic. This logic is derived from the asset's specific inherent volatility and potential intraday structural pivoting points, strictly based on mathematical modeling rather than standard technical indicators. This allows the script to project "Primary Dynamic Resistances" (PDR) and "Dynamic Supports" (PDS) that adapt to the asset's specific nature during the session.
Hard-Coded Macro Data (The Database): The script contains an internal, encrypted database of annually pre-calculated macro market zones . These are not generated by recent high/low candles but are fixed structural levels injected into the chart based on proprietary annual analysis. The plotting mechanism controls the visibility of these zones by considering a specific expected movement threshold unique to each asset, ensuring that levels are only displayed when they are statistically relevant to the current price action (filtering out noise).
Optimized for Intraday: The logic relies on Session Open data anchors (09:30 EST), making it designated for timeframes between 1 minute and 30 minutes .
Auto-Asset Recognition (Supported Markets): The script automatically detects the ticker and applies the correct mathematical model for:
Nasdaq: QQQ (ETF), NQ/MNQ (Futures), US100, NAS100 (CFDs).
S&P 500: SPY (ETF), ES/MES (Futures), US500 (CFDs).
Dow Jones: DIA (ETF), YM/MYM (Futures), US30 (CFDs).
Russell 2000: IWM (ETF), RTY/M2K (Futures), US2000 (CFDs).
Bitcoin: IBIT (ETF), BTC (Futures CME), Crypto Spot & Crypto futures.
Metals: Gold & Silver (ETF, Futures, CFDs).
Sentiment Analysis Panel: A real-time logic module that analyzes price behavior throughout the trading session. The sentiment classification is derived from the relationship between the current price and the calculated PDR/PDS levels, combined with an additional layer of private, encrypted quantitative logic to determine the market bias (Neutral, Bullish, Bearish, Extreme).
Macro Zone Alerts: Includes a "Trigger on Entry" feature, allowing traders to set server-side alerts specifically when price breaches a defined Macro Zone.
Why is this "Invite-Only"? The source code is protected because it contains:
Proprietary Math: The asset-specific logic and volatility calculations are the result of extensive quantitative research and are not public domain.
Curated Database: The specific price arrays for the Macro Zones are intellectual property derived from pre-calculated annual structures, not generic chart reading.
Risk Disclaimer & Feedback We are fully open to suggestions and constructive feedback from the community to improve this tool. Our goal is to aid analysis, not to generate financial loss. Please remember that this indicator provides technical levels based on probabilities; it does not guarantee future performance. Trading involves significant risk.
Volume Intelligence Suite Z-score volume, shows high volume to get initiative, response, absorption and exhaustion using only candles
Blockcircle AMS V3 - Altcoin Market ScorecardThe Blockcircle Altcoin Market Scorecard is a proprietary multi-timeframe analysis system developed by Blockcircle since 2017, designed to aggregate 11 distinct inter-market relationships into a single, actionable sentiment score (0-100). This indicator represents years of research into altcoin market dynamics and cross-asset correlations, providing traders with a systematic framework for bias determination rather than discretionary guesswork.
WHAT PROBLEM THIS SOLVES
Altcoin traders face a fundamental challenge: determining whether current market conditions favor altcoin exposure. This typically requires monitoring dozens of charts, manually tracking BTC dominance, stablecoin flows, relative strength against equities, and sector rotation patterns. Most traders either skip this analysis entirely or do it inconsistently. The AMS consolidates this multi-dimensional analysis into a single dashboard that updates in real-time across multiple timeframes simultaneously.
WHAT MAKES THIS ORIGINAL AND WORTH USING
The value proposition is not any single component, but rather the complete analytical system working together:
Proprietary Metric Selection - The specific combination of 11 inter-market relationships was developed through years of observing what actually correlates with altcoin performance. This is not a random collection of indicators - each metric was selected because it provides non-redundant information about altcoin market conditions.
Empirically-Derived Weighting - Not all metrics are weighted equally. BTC Dominance weakness, Stablecoin Dominance weakness, and Crypto vs Russell 2000 strength carry higher weights (20 points each) because they historically correlate more strongly with altcoin performance. Metrics like DXY and Stablecoin inflows carry lower weights (2.5 points). This weighting reflects observed significance, not arbitrary assignment.
Multi-Timeframe Synthesis - Viewing the same 11 metrics across three timeframes simultaneously, with automatic timeframe stepping, allows confirmation of short-term setups against higher timeframe trends. This would require maintaining 33+ separate chart windows manually.
Statistical Context Layer - Raw scores without context have limited utility. The statistical analysis (Z-Score, historical probabilities, volatility measurements) answers the question: "Is this score reading unusual relative to recent history?" A score of 75 means something different when the 200-bar average is 50 vs 70.
Pattern Detection Engine - The configurable pattern system identifies accumulation and distribution zones systematically, removing the subjectivity of manual pattern recognition.
THE 11 METRICS ANALYZED
Each metric is evaluated using Heikin Ashi candle analysis to determine bullish, bearish, or mixed status:
BTC Dominance behavior (inverted - weakness is bullish for alts)
Sector Beacon performance (configurable, default ETH/BTC)
BTC/USD price action
Altcoins vs BTC relative strength (TOTAL3-USDT/BTC)
Small-cap altcoins vs BTC relative strength (OTHERS.BTC)
Stablecoin dominance (inverted - USDT.D + USDC.D + DAI.D)
Stablecoin market cap inflows (USDT + USDC + DAI)
DXY/Fiat currency weakness (inverted)
Crypto vs Russell 2000 relative strength (TOTAL/RTY)
Crypto vs S&P 500 relative strength (TOTAL/SPX)
Crypto vs Nasdaq relative strength (TOTAL/NDX)
HOW THE SCORING SYSTEM WORKS
For each metric across your selected timeframes, the system evaluates:
Candle direction (bullish vs bearish close on Heikin Ashi)
Higher-high/higher-low patterns vs lower-high/lower-low patterns compared to prior bar
Mixed pattern detection (when both bullish and bearish characteristics present simultaneously)
Metrics are assigned traffic-light status: Green (bullish, full weight), Orange (mixed/neutral, half weight), or Red (bearish, zero weight). The weighted scoring algorithm sums the contributions to produce the composite AMS score (0-100).
Score interpretation:
80-100: Very Bullish conditions for altcoins
60-79: Bullish conditions
40-59: Neutral/mixed conditions
30-39: Bearish conditions
0-29: Very Bearish conditions
MULTI-TIMEFRAME ANALYSIS
Three configurable timeframes with auto-calculation available. When Auto-Set Higher Timeframes is enabled, the indicator automatically steps up the hierarchy (e.g., 15m chart → TF1=15m, TF2=30m, TF3=1H). This confirms whether shorter-term setups align with higher timeframe trends.
Each timeframe supports a Candle Offset feature for referencing prior candles instead of the current bar, useful for observing score evolution and momentum direction.
Statistical Analysis Framework
Calculated over your configurable lookback period:
Min/Max/Average scores - baseline context
Median values - central tendency less affected by outliers
Standard Deviation - score volatility measurement
Volatility % (coefficient of variation) - normalized variability
Z-Score - how many standard deviations current score is from mean
Score RSI (14-period) - momentum of the score itself
Rate of Change % (5-bar) - velocity of score movement
Acceleration - second derivative, detecting momentum shifts early
Historical probability distributions (P>60, P>70, P>80, P>90)
Pattern Detection System
Five fully configurable pattern trackers detect accumulation zones (multiple occurrences below a threshold) or distribution zones (multiple occurrences above a threshold):
Timeframe selection (TF1, TF2, or TF3)
Direction (Above for potential tops, Below for potential bottoms)
Score threshold
Minimum occurrences required
Lookback period in candles
Custom marker colors
Visual markers appear on chart when criteria are met. This systematizes what would otherwise be subjective pattern recognition.
Momentum Shift Detection
Tracks when score momentum crosses from negative to positive (bullish shift) or positive to negative (bearish shift). Configurable threshold filters noise. Identifies inflection points in market sentiment before the score itself crosses key levels.
Moving Averages of Score
Five configurable MAs (SMA, EMA, WMA, VWMA, HMA) applicable to any timeframe's score or average score. MA crossovers generate visual markers. Smooths score data and provides trend context.
Consecutive Bars Analysis
Tracks how many consecutive bars the score has remained above or below key thresholds. Default table displays consecutive bars ]60, ]80, [40, and [20 for each timeframe. Extended periods above 80 may indicate overheated conditions; extended periods below 20 may indicate capitulation zones.
PRACTICAL APPLICATIONS
The AMS provides objective data to answer: "Should I have an altcoin bullish bias or bearish bias right now?"
Use cases:
Confirming scalp or swing trade setups align with broader market conditions
Identifying when to deploy or withdraw capital from altcoin positions
Detecting early shifts in market regime before price action confirms
Providing objective data to counter emotional decision-making
Establishing position sizing based on conviction level (score alignment across timeframes)
When the AMS closes the 1-week or 2-week timeframe bullish (]60), historical data suggests this has often preceded periods of altcoin strength. However, past performance does not guarantee future results, and the indicator should be one input in your decision-making process, not a standalone signal generator.
IMPORTANT LIMITATIONS
This indicator uses request.security() calls to fetch data from multiple symbols. It does not use lookahead and does not access future data.
Heikin Ashi analysis means signals are smoothed and may lag pure price action.
The score reflects current conditions, not predictions. Market conditions can change rapidly.
A high score does not guarantee altcoin prices will rise. Always use proper risk management.
The indicator tells you market conditions - it does not tell you which altcoins to buy or exact entry timing.
ALERT INTEGRATION
Comprehensive alert conditions available:
=60, ]=80, Pattern detections (all 5 pattern trackers)
Momentum shifts (bullish/bearish)
MA crossovers
Custom alert profiles with multi-timeframe AND/OR logic
Rising momentum combined with high scores
Discord webhook formatting (JSON) or standard text
TABLE DISPLAY OPTIONS
Fully customizable scorecard with section visibility toggles:
Custom Metrics Section (11 individual metric statuses)
Altcoin Scores Section (composite scores and bias)
Momentum Section (momentum, consecutive bars, Z-Score, RSI, ROC, Acceleration)
Statistical Section (min/max/avg, median, std dev, volatility, probabilities)
Signal Counts Section (green/orange/red metric counts)
Summary Section (market view summary)
Position (corners) and text size adjustable. Disable sections for cleaner views.
WHY THIS INDICATOR REQUIRES PROTECTION
The source is protected because the specific combination of metrics, the empirically-derived weighting system, and the multi-layered analysis framework represent proprietary research developed over years of active trading and market observation. This is not a wrapper around publicly available indicators or a simple mashup - the value is in the systematic methodology for synthesizing cross-market data into actionable bias determination. The research investment required to identify which metrics matter, how much weight each should carry, and how to combine them meaningfully is what justifies both the protection and the access model.
ADR% babaThis indicator calculates the Average Day Range (ADR) as a percentage using the TC2000 methodology, measuring the average relative expansion between daily highs and lows to quantify market volatility in a price-level independent manner.
Swing % VisualizerSwing % Visualizer is a clean, intuitive indicator that automatically detects pivot points (swing highs and lows) and displays the percentage change between each swing directly on your chart.
█ HOW IT WORKS
The indicator uses pivot detection logic to identify significant turning points in price action. When a new pivot is confirmed, it calculates the percentage move from the previous pivot and displays it as a label:
- Green labels show upward moves (rallies)
- Red labels show downward moves (pullbacks/corrections)
█ FEATURES
- Automatic pivot detection with adjustable sensitivity (Lookback parameter)
- Minimum move filter to ignore small, insignificant swings
- Real-time statistics panel with iOS-inspired design displaying:
- Average Up/Down percentages
- Maximum Up/Down moves
- Total swing count with breakdown
█ USE CASES
- Quickly assess the typical retracement depth of an asset
- Identify changes in volatility by comparing swing sizes
- Understand average rally/pullback percentages for better position sizing
- Compare swing behavior across different timeframes
█ SETTINGS
- Pivot Lookback: Number of bars to confirm a pivot (higher = fewer, more significant pivots)
- Minimum Move %: Filter out swings smaller than this threshold
- Visual customization: Label size, colors, show/hide options
Works on all markets and timeframes.
Sri-VWAP CTF)📌 Sri-VWAP CTF (Custom Timeframe VWAP)
🔍 Overview
Sri-VWAP CTF is a custom-timeframe, rolling-window VWAP indicator designed to give traders higher-timeframe volume-weighted price context directly on any lower-timeframe chart.
Unlike standard VWAP implementations that are:
Session-anchored (daily/weekly only), or
Locked to the chart timeframe
this script allows the user to independently select the VWAP calculation timeframe and control how the VWAP behaves between higher-timeframe bars.
This makes the indicator especially useful for multi-timeframe analysis, intraday structure trading, and HTF bias confirmation.
⚙️ How It Works (Conceptual Explanation)
This indicator calculates VWAP using a rolling cumulative window instead of a session reset.
Typical Price Calculation
VWAP is derived using the typical price:
(High + Low + Close) / 3
Volume-Weighted Aggregation
The script multiplies the typical price by volume and applies a rolling cumulative sum over a user-defined number of bars.
Rolling VWAP (Non-Session Based)
VWAP is calculated over a fixed number of candles
It does not reset at session boundaries
This provides a smoother, trend-aware VWAP useful for swing and intraday bias
Custom Timeframe Engine
The VWAP calculation is executed on a user-selected higher timeframe using TradingView’s security mechanism and then projected onto the active chart timeframe.
⏱️ Custom Timeframe Logic
You can calculate VWAP on:
15-minute
30-minute
1-hour
Daily
Any supported timeframe
This allows traders to:
Trade on lower TF entries
While respecting higher TF volume-weighted structure
📈 Plot Behavior Modes
The script offers two distinct plotting behaviors:
1️⃣ Hold Between HTF Bars
VWAP value remains constant until the next HTF candle completes
Best for HTF bias, support/resistance, and trend holding
2️⃣ Show Only on HTF Bars
VWAP appears only when a new HTF candle closes
Ideal for precision reference levels and HTF validation
🧠 Why This Is Different / Useful
✔ Not session-anchored
✔ Rolling VWAP instead of reset-based VWAP
✔ Independent calculation timeframe
✔ Controlled projection behavior
✔ Clean, non-repainting logic
✔ Suitable for scalping, intraday, and swing trading
This design avoids the limitations of traditional VWAP tools and provides greater analytical flexibility without clutter.
🎯 How Traders Can Use It
Trend Bias
Price above HTF VWAP → bullish bias
Price below HTF VWAP → bearish bias
Dynamic Support & Resistance
VWAP acts as a volume-weighted equilibrium level
Entry Filtering
Combine with lower-TF price action, RSI, or EMA strategies
Multi-Timeframe Confirmation
Align LTF entries with HTF VWAP direction
⚠️ Notes
VWAP uses actual traded volume, so results depend on data quality
Best used alongside price structure or momentum tools
Indicator does not repaint
✅ Summary
Sri-VWAP CTF is a custom timeframe, rolling VWAP tool built for traders who want clear HTF volume context on any chart, without session limitations or visual noise.
Tifz 2.0UTC Session Ranges and PD/PW Levels
Market Structure Indicator
Created by Tifz
This indicator displays trading sessions and key price levels using UTC time.
All calculations are based on intraday price data, not broker-specific daily candles, so the levels are consistent across all charts.
Session Ranges (UTC Time)
Displays Asia, Frankfurt, London, and New York sessions
Session start and end times can be changed in the settings
Each session is drawn as a shaded price range box
Session boxes have no border lines
The high-to-low price range of each session can be shown in pips below the box
Session box colours and transparency can be changed
These ranges show how price moves within each trading session.
Vertical Time Lines
Displays dotted vertical lines at specific UTC times
Default times are 08:00 UTC and 14:00 UTC
The time of each line can be changed
Line colour and line thickness can be changed
Lines do not extend across the entire chart and are limited in height
These lines are used to mark session opens or specific trading times.
Previous Day and Previous Week Levels (UTC)
Displays:
HOPD – High of the previous day
LOPD – Low of the previous day
HOPW – High of the previous week
LOPW – Low of the previous week
Levels are calculated using UTC day and week boundaries
Highs and lows are built from intraday price data
Levels are drawn as short horizontal lines, not full-width lines
Each line extends a set number of bars to the right
Each level has a label at the right end of the line
Line colour, line style, line thickness, and line length can be changed in the settings.
Who This Indicator Is For
Traders who use session-based analysis
Traders who use previous day and week highs and lows
Traders who want clean charts without unnecessary lines
Important Note
This indicator does not generate trade signals.
It only displays time-based sessions and price levels for analysis..
7 hours ago
Release Notes
Session Ranges (UTC Time)
Displays Asia, Frankfurt, London, and New York sessions
Session start and end times can be changed in the settings
Each session is drawn as a shaded price range box
Session boxes have no border lines
The high-to-low price range of each session can be shown in pips below the box
Session box colours and transparency can be changed
These ranges show how price moves within each trading session.
Vertical Time Lines
Displays dotted vertical lines at specific UTC times
Default times are 08:00 UTC and 14:00 UTC
The time of each line can be changed
Line colour and line thickness can be changed
Lines do not extend across the entire chart and are limited in height
These lines are used to mark session opens or specific trading times.
Previous Day and Previous Week Levels (UTC)
Displays:
HOPD – High of the previous day
LOPD – Low of the previous day
HOPW – High of the previous week
LOPW – Low of the previous week
Levels are calculated using UTC day and week boundaries
Highs and lows are built from intraday price data
Levels are drawn as short horizontal lines, not full-width lines
Each line extends a set number of bars to the right
Each level has a label at the right end of the line
Line colour, line style, line thickness, and line length can be changed in the settings.
Who This Indicator Is For
Traders who use session-based analysis
Traders who use previous day and week highs and lows
Traders who want clean charts without unnecessary lines
Important Note
This indicator does not generate trade signals.
It only displays time-based sessions and price levels for analysis.
Nas Indicator It helps with finding directional bias based off of percentages and grounds me better in my execution.
Lot Size & Risk Calculator All Pairs NEWLot Size & Risk Calculator All Pairs NEW
Description
Professional risk and position size calculator for traders working with various financial instruments.
Main difference from standard indicators:
Standard risk calculators only show basic Risk/Reward for the entire position. But in real trading, we often close positions partially at different take-profit levels, and the final Risk/Reward changes significantly with this approach! This indicator calculates weighted Risk/Reward taking into account position distribution across multiple take-profit levels.
Main features:
- Support for 4 instrument types: Forex, XAUUSD (gold), BTCUSD (bitcoin), US100 (NASDAQ index)
- Automatic position size calculation based on risk and stop-loss distance
- Multiple take-profit levels with customizable closing percentages
- Weighted Risk/Reward calculation considering position distribution
- Ability to adjust position distribution between take-profits to optimize final profit
- Display of total percentage growth of deposit from all take-profit levels
- 2 visualization options: colored fill between levels or lines
- Informative results panel in table format
Settings by groups:
Core Settings
- Currency: select instrument type (Forex, XAUUSD, BTCUSD, US100)
- Account Balance: trading account size in dollars
- Risk %: risk percentage from deposit (0.1-100%)
- Use Custom Contract Sizes: manual contract size configuration
Point Value Settings
- Use automatic point value calculation: automatic point value calculation
- Manual point value: manual point value input (for non-standard contracts)
Levels
- Entry Price: entry price (confirmation required on first use)
- Stop Price: stop-loss price
- Take-Profit Prices: take-profit prices (up to 3 levels)
- TP Close %: percentage of position closed at each take-profit level
Dashboard
- Show Targets Profit: display profit from take-profit levels
- Label Size: text size in the table
- Dashboard Position: table position on the chart
How to use:
Step 1: Initial setup (when first adding)
1. Enter entry price (Entry Price) - confirmation window will appear (click on desired bar)
2. Then enter stop-loss price (Stop Price) (click on desired bar)
3. Add first take-profit (TP1) (click on desired bar)
4. Second and third take-profits are added through checkboxes (click on the settings gear icon to open them)
Step 2: Instrument selection and risk configuration
1. In "Core" group, select your instrument type
2. Set account balance and risk percentage
Step 3: Position distribution configuration
1. Set TP Close % for each take-profit level (e.g.: TP1 - 33%, TP2 - 33%, TP3 - 34%)
2. Experiment with distribution! By changing closing percentages, you can:
- Increase/decrease final Risk/Reward
- Optimize risk/profit ratio
- Find the most comfortable position distribution for you
Step 4: Results analysis
1. Results table will show:
- Calculated position size (lots/contracts)
- Risk in monetary terms
- Risk/Reward for each take-profit level
- Weighted R:R considering position distribution
- Total potential profit from all take-profits
- Percentage growth of deposit - total profit percentage from all take-profit levels
Key features:
Position distribution adjustment
You can easily find optimal position distribution between take-profits:
- Aggressive approach: higher percentage on distant take-profit (higher profit potential)
- Conservative approach: higher percentage on near take-profit (faster profit taking)
- Balanced: even distribution for risk reduction
Weighted Risk/Reward
The indicator calculates not just simple R:R for the entire position, but weighted value that considers:
- Position distribution between take-profits
- Different distances to each take-profit level
- Closing percentage at each level
Results visualization
- Colored fill shows risk and profit zones
- Labels at levels display specific profit/loss values
- Results table contains all key metrics
Creation story
This indicator was created based on the original calculator by @Algoryze As a trader, I lacked the ability to see real Risk/Reward when partially closing positions and a convenient tool for selecting optimal position distribution between take-profit levels. I improved the indicator by adding:
- Weighted Risk/Reward calculation
- Ability to adjust closing percentage at each take-profit
- Display of total percentage growth of deposit
- Improved interface and visualization
I hope this tool will be useful to other traders who use strategies with partial position closing!
Important notes:
1. When first adding the indicator, be sure to enter prices in order: Entry → Stop → TP1
2. TP2 and TP3 are added through input fields (no confirmation required)
3. Closing percentages are automatically normalized if the sum is not 100%
4. Experiment with position distribution to find optimal risk/profit ratio
5. For different instruments, add separate copies of the indicator in different tabs
Support
For questions and suggestions, leave comments in the indicator publication on TradingView.
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Important: All calculations are provided for informational purposes only. Trading involves risks, trade responsibly. The indicator helps with calculations but does not guarantee profit.
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.
ABG Basket Radarsimple currency basket lines where you can see what currency is stronger and what currency is weaker.
its all custom formula baskets and not just usd pairs.
Linear Regression R-SquaredCalculates the least squares linear regression R-squared values for the specified data period. Values range from zero to one.
LARGER PRICE LINE Adjustable (UPDATED)LARGER PRICE LINE
I made this so I could SEE THE PRICE LINE BETTER and try to reduce some eye strain!!
Hope it helps... enjoy! comment for improvements or suggestions
Improved Adjustable Size and Color for the Price Line and Price Box
Adjustment for Price Line: Size and Color plus Solid Line, Dashed or Dotted Line
Adjustments include: Price Box Text Size and Color (Small, Normal, Large, Huge!)
Adjustable Right Side Offset for Price Box
