USDT Market Cap Change [Alpha Extract]A sophisticated stablecoin market analysis tool that tracks USDT market capitalization changes across daily and 60-day periods with statistical normalization and gradient intensity visualization. Utilizing z-score methodology for overbought/oversold detection and dynamic color gradients reflecting change magnitude, this indicator delivers institutional-grade market liquidity assessment through stablecoin flow analysis. The system's dual-timeframe approach combined with statistical normalization provides comprehensive market sentiment measurement based on capital inflows and outflows from the dominant stablecoin.
🔶 Advanced Market Cap Tracking Framework
Implements daily USDT market capitalization monitoring with dual-period change calculations measuring both 1-day and 60-day net capital flows. The system retrieves real-time CRYPTOCAP:USDT data on daily timeframe resolution, calculating absolute dollar changes to quantify stablecoin supply expansion or contraction as primary market liquidity indicator.
// Core Market Cap Analysis
USDT = request.security("CRYPTOCAP:USDT", "D", close)
USDT_60D_Change = USDT - USDT
USDT_1D_Change = USDT - USDT
🔶 Dynamic Gradient Intensity System
Features sophisticated color gradient engine that intensifies visual representation based on change magnitude relative to recent extremes. The system normalizes current 60-day change against configurable lookback period maximum, applying gradient strength calculation to transition colors from neutral tones through progressively intense blues (negative) or reds (positive) based on flow direction and magnitude.
🔶 Statistical Z-Score Normalization Engine
Implements comprehensive z-score calculation framework that normalizes 60-day market cap changes using rolling mean and standard deviation for objective overbought/oversold determination. The system applies statistical normalization over configurable periods, enabling cross-temporal comparison and threshold-based regime identification independent of absolute market cap levels.
// Z-Score Normalization
Change_Mean = ta.sma(USDT_60D_Change, Normalization_Length)
Change_StdDev = ta.stdev(USDT_60D_Change, Normalization_Length)
Z_Score = Change_StdDev > 0 ? (USDT_60D_Change - Change_Mean) / Change_StdDev : 0.0
🔶 Multi-Tier Threshold Detection System
Provides four-level regime classification including standard overbought (+1.5σ), standard oversold (-1.5σ), extreme overbought (+2.5σ), and extreme oversold (-2.5σ) thresholds with configurable adjustment. The system identifies market liquidity extremes when stablecoin inflows or outflows reach statistically significant levels, indicating potential market turning points or trend exhaustion.
🔶 Dual-Timeframe Flow Visualization
Features layered area plots displaying both 60-day strategic flows and 1-day tactical movements with distinct color coding for instant flow direction assessment. The system overlays short-term daily changes on longer-term 60-day trends, enabling traders to identify divergences between tactical and strategic capital flows into or out of stablecoin reserves.
🔶 Gradient Color Psychology Framework
Implements intuitive color scheme where red gradients indicate capital inflow (bullish for crypto as USDT supply expands for buying) and blue gradients show capital outflow (bearish as USDT is redeemed). The intensity progression from pale to vivid colors communicates flow magnitude, with extreme colors signaling statistically significant liquidity events requiring attention.
🔶 Background Zone Highlighting System
Provides subtle background coloring when z-score breaches overbought or oversold thresholds, creating visual alerts without obscuring primary data. The system applies translucent red backgrounds during overbought conditions and blue during oversold states, enabling instant regime recognition across chart timeframes.
🔶 Configurable Normalization Architecture
Features adjustable gradient lookback and statistical normalization periods enabling optimization across different market cycles and trading timeframes. The system allows traders to calibrate sensitivity by modifying the window used for maximum change detection (gradient) and mean/standard deviation calculation (z-score), adapting to volatile or stable market regimes.
🔶 Market Liquidity Interpretation Framework
Tracks USDT supply changes as proxy for overall cryptocurrency market liquidity conditions, where expanding market cap indicates fresh capital entering crypto markets and contracting cap suggests capital flight. The system provides leading indicator properties as large stablecoin inflows often precede major market rallies while outflows may signal distribution phases.
🔶 Why Choose USDT Market Cap Change ?
This indicator delivers sophisticated stablecoin flow analysis through statistical normalization and gradient visualization of USDT market capitalization changes. Unlike traditional market sentiment indicators that rely on price action alone, this tool measures actual capital flows through the dominant stablecoin, providing objective assessment of market liquidity conditions. The combination of dual-timeframe tracking, z-score normalization for overbought/oversold detection, and intensity-based gradient coloring makes it essential for traders seeking macro-level market assessment and regime change detection across cryptocurrency markets. The indicator excels at identifying liquidity extremes that often precede major market reversals or trend accelerations.
Analisis Fundamental
Z-Score & StatsThis is an advanced indicator that measures price deviation from its mean using statistical z-scores, combined with multiple analytical features for trading signals.
Core Functionality-
Z-Score Calculation Engine:
The indicator uses a custom standardization function that calculates how many standard deviations the current price is from its rolling mean. Unlike simple moving averages, this provides a normalized view of price extremes. The calculation maintains a sliding window of data points, efficiently updating mean and variance values as new data arrives while removing old data points. This approach handles missing values gracefully and uses sample variance (rather than population variance) for more accurate statistical measurements.
Statistical Zones & Visual Framework:
The indicator creates a visual representation of statistical probability zones:
±1 Standard Deviation: Encompasses about 68% of normal price behavior (green zone)
±2 Standard Deviations: Covers approximately 95% of price movements (orange zone)
±3 Standard Deviations: Represents 99.7% probability range (red zone)
±3.5 and ±4 Thresholds: Extreme outlier levels that trigger special alerts
The z-score line changes color dynamically based on which zone it occupies, making it easy to identify the current market extremity at a glance.
Advanced Features:
Volume Contraction Analysis
The script monitors volume patterns to identify periods of reduced trading activity. It compares current volume against a moving average and flags when volume drops below a specified threshold (default 70%). Volume contraction often precedes significant price moves and is factored into the optimal entry detection system.
Momentum-Based Direction Model:
Rather than just showing current z-score levels, the indicator projects where the z-score is likely to move based on recent momentum. It calculates the rate of change in the z-score and extrapolates forward for a specified number of bars. This creates a directional arrow that indicates whether conditions are bullish (negative z-score with upward momentum) or bearish (positive z-score with downward momentum).
Divergence Detection System:
The script automatically identifies four types of divergences between price action and z-score behavior :-
Regular Bullish Divergence: Price makes lower lows while z-score makes higher lows, suggesting weakening downward pressure
Regular Bearish Divergence: Price makes higher highs while z-score makes lower highs, indicating exhaustion in the uptrend
Hidden Bullish Divergence: Price makes higher lows while z-score makes lower lows, confirming trend continuation in an uptrend
Hidden Bearish Divergence: Price makes lower highs while z-score makes higher highs, confirming downtrend continuation
The system uses pivot detection with configurable lookback periods and distance requirements, then draws connecting lines and labels directly on the chart when divergences occur.
Yearly Statistics Tracking:
The indicator maintains historical records of maximum z-score deviations over yearly periods (configurable bar count). This provides context by showing whether current extremes are unusual compared to typical annual ranges. The average yearly maximum helps traders understand if the current market is exhibiting normal volatility or exceptional conditions.
Mean Reversion Probability:
Based on the current z-score magnitude, the indicator calculates and displays the statistical probability that price will revert toward the mean. Higher absolute z-scores indicate stronger mean reversion probabilities, ranging from 38% at ±0.5 standard deviations to 99.7% at ±3 standard deviations.
Comprehensive Statistics Table:
A customizable on-chart table displays real-time statistics including:
Current z-score value with directional indicator
Predicted z-score based on momentum
Current year's maximum absolute z-score
Historical average yearly maximum
Mean reversion probability percentage
Zone status classification (Normal, Moderate, High, Extreme)
Directional bias (Bullish, Bearish, Neutral)
Active divergence status
Volume contraction status with ratio
Optimal setup detection (combining extreme z-scores with volume contraction)
Optimal Entry Setup Detection:
The most sophisticated feature identifies high-probability trading setups by combining multiple factors. An "Optimal Long" signal triggers when z-score reaches -3.5 or below AND volume is contracted. An "Optimal Short" signal appears when z-score exceeds +3.5 AND volume is contracted. This combination suggests extreme price deviation occurring on low volume, often preceding strong reversals.
Alert System:
The script includes a unified alert mechanism that triggers when z-score crosses specific thresholds:
Crossing above/below ±3.5 standard deviations (extreme levels)
Crossing above/below ±4 standard deviations (critical levels)
Alerts fire once per bar with confirmation (previous bar must be on opposite side of threshold) to avoid false signals.
Practical Application:
This indicator is designed for mean reversion traders who seek statistically significant price extremes. The combination of z-score measurement, volume analysis, momentum projection, and divergence detection creates a multi-layered confirmation system. Traders can use extreme z-scores as potential reversal zones, while the direction model and divergence signals help time entries more precisely. The volume contraction filter adds an additional layer of confluence, identifying moments when reduced participation may precede explosive moves back toward the mean.
Chart Attached: NSE GMR Airports, EoD 12/12/25
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice.Happy Trading
Peter Lynch Value (Dynamic Growth)This indicator implements Peter Lynch's core valuation principle: Fair Price = Earnings Per Share (EPS) * Growth Rate.
It provides a dynamic "fair value" line overlaid on the price chart, allowing traders and investors to quickly assess whether a stock's current price is trading above or below its intrinsic value according to the Lynch method.
Key Features
1. Dynamic Growth Rate Calculation
The indicator uses a custom algorithm to calculate the critical EPS Growth Rate, making it robust against missing data from standard financial fields.
Methodology: It fetches historical TTM Diluted EPS reports (EARNINGS_PER_SHARE_DILUTED, TTM) and calculates the Year-over-Year (YoY) Growth Percentage from the current TTM value versus the TTM value 4 periods prior.
Reliability: This custom calculation ensures the value line appears even when TradingView's pre-calculated growth metrics are unavailable (na).
2. Multiplier Control
P/E Cap: You can enforce a maximum P/E multiplier (maxPE, default 25), preventing the fair value from becoming unrealistically high for extremely fast-growing companies (as Lynch suggested).
Fallback P/E: If insufficient financial history is available to calculate the growth rate, the indicator automatically switches to a user-defined fallbackPE (default 15) and highlights the line in orange as a warning.
3. Smoothing (Optional)
To reduce the volatility often seen in valuation metrics, you can apply an optional Simple Moving Average (SMA) to the Fair Value line. This helps visualize the underlying trend of intrinsic value.
4. Forward Estimate (Optional)
Display an optional projection (circles) based on the analysts' next Fiscal Year EPS Estimate (EARNINGS_ESTIMATE, FY). This shows the potential fair value if the company meets future expectations.
5. Diagnostic Table
A table in the corner provides transparency on the calculation:
Green/Red: Confirms if TTM EPS and Calculated Growth are found.
Final P/E Used: Shows the exact multiplier used (calculated growth or the manual fallback).
Disclaimer: This tool is for informational and educational purposes only and should not be considered financial advice.
VP + Fib + AVWAP + Graded Signals An indicator for the discretionary trader
Avwap, Fib and VP is all you need.
Graded signals for conviction.
ICT Candle Reading PROICT Candle Reading – Visual Clean
This indicator is designed to provide a clean and precise price reading, based on ICT and Smart Money Concepts, without cluttering the chart.
Its purpose is to help traders identify real institutional zones, understand market intention, and improve entry timing, using pure price action.
🔹 What does this indicator show?
🟢 Fair Value Gaps (FVG / Imbalances)
Detects market inefficiencies created by impulsive moves.
Displayed as clean and minimal boxes extended into the future.
Useful as mitigation, reaction, or continuation zones.
🟠 Liquidity Sweeps
Highlights liquidity grabs above recent highs or below recent lows.
Drawn using dashed horizontal lines.
Helps identify market manipulation before the true move.
🔵 Displacement Candles
Identifies candles with dominant bodies, showing institutional momentum.
Marked with small symbols to keep the chart clean.
Useful to confirm impulse starts or shifts in market intent.
🎯 Indicator Philosophy
❌ No lagging indicators
❌ No chart clutter
✅ Real ICT concepts
✅ Clean candle reading
✅ Suitable for scalping, intraday, and swing trading
⚙️ Customization
Each concept can be enabled or disabled individually.
Zone extension length is adjustable.
Optimized for 15M, 1H, and 4H timeframes.
📈 How to use
This indicator does not provide automatic buy/sell signals.
It is best used with:
Higher timeframe bias
Market structure
Session timing (London / New York)
Proper risk management
🧠 Final Notes
ICT Candle Reading – Visual Clean helps you see the market from an institutional perspective, focusing only on what truly matters: price, liquidity, and intent.
Neosha Concept V4 (NY Time)
Imagine the financial market as a huge ocean. Millions of traders throw orders into it every second. But beneath all the noise, there is a powerful current that quietly controls where the waves move. That current is not a person, not a trader, and not random—it is an algorithm.
This algorithm is called the Interbank Price Delivery Algorithm (IPDA).
Think of it as the “navigation system” that guides price through the market.
IPDA has one job:
to move prices in a way that keeps the market efficient and liquid.
To do this, it constantly looks for two things:
1. Where liquidity is hiding
Liquidity is usually found above highs and below lows—where traders place stop losses. The algorithm moves price there first to collect that liquidity.
2. Where price became unbalanced
Sometimes price moves too fast and creates gaps or imbalances. IPDA returns to those areas later to “fix” the missing orders.
Once you start looking at the charts with this idea in mind, everything makes more sense:
Why price suddenly spikes above a high and crashes down
Why big moves leave gaps that price later fills
Why the market reverses right after taking stops
Why trends begin only after certain levels are hit
These are not accidents.
They are the algorithm doing its job.
Price moves in a repeating cycle:
Gather liquidity
Make a strong move (displacement)
Return to fix inefficiency
Deliver to the next target
Most beginners only see the candles.
But once you understand IPDA, you see the intention behind the candles.
Instead of guessing where price might go, you begin to understand why it moves there.
And once you understand the “why,” your trading becomes clearer, calmer, and far more accurate.
Forexsebi - NASDAQ Psychological Levels - TrendflowTrendflow is an advanced TradingView indicator combining psychological price levels with trend and multi-timeframe analysis.
The indicator automatically plots psychological levels in around the current price. Each level is visualized using horizontal lines and price zones (boxes) to clearly highlight potential support and resistance areas.
Psychological Levels – Trendflow ist ein fortschrittlicher TradingView-Indikator , der wichtige psychologische Preislevel mit einer klaren Trend- und Multi-Timeframe-Analyse kombiniert.
Trend Analysis with SMAs
SMA 50 & SMA 200 plotted directly on the chart
Individually toggleable
Clear color separation for fast trend recognition
Multi-Timeframe SMA Trend Table
Trend status (BULLISH / BEARISH / NEUTRAL) across:
5M, 15M, 1H, 4H, 1D
Logic: Price relative to SMA 50 & SMA 200
Color-coded, easy-to-read table
Info Box
Current Gold price
Nearest psychological level above and below price
Alert System
Alerts when price approaches a psychological level
User-defined alert distance
VX-Time Quadrant Overlay (Quarterly Cycles) by Ikaru-s-The Time Quadrant Overlay is a purely time-based visualization tool designed to structure market time into repeating quarterly cycles across multiple timeframes.
It does not generate trade signals, entries, or bias.
Its sole purpose is to provide time context, so price action can be interpreted within a clear cyclical framework.
What this indicator does
The indicator divides time into four repeating quarters (Q1–Q4) and displays them simultaneously across different time horizons, such as:
Weekly
Daily (6-hour quarters)
90-minute cycles
Micro cycles (within 90-minute structure)
Each row represents a different time cycle, allowing traders to see time alignment, transitions, and overlaps at a glance.
Quarter Structure
Each cycle follows the same repeating sequence:
Q1 – Early phase
Q2 – Expansion / “True Open” phase
Q3 – Continuation
Q4 – Late phase / Transition
The quarters are visualized using color-coded boxes, making it easy to see:
where the market currently is in time
when a new quarter begins
when multiple cycles align or diverge
Quarter Start Marker
An optional Quarter Start Marker (vertical dashed line) can be enabled to highlight the start of a selected quarter (default: Q2).
This is intended as a time reference, not a signal:
useful for planning
useful for contextualizing reactions to levels
useful for session and cycle awareness
How to use it (practical)
This tool is best used to:
provide time structure to existing analysis
plan around upcoming time transitions
contextualize reactions to levels or areas
understand where price is acting within a cycle
It works well alongside:
discretionary price action
session-based trading
futures and index markets
any methodology that respects time as a variable
Customization
The indicator is fully customizable:
Enable / disable individual cycles
Adjust box transparency and history depth
Toggle labels and pane labels
Enable / disable quarter start markers
Select which quarter to highlight
This allows the tool to remain clean on higher timeframes and detailed on lower ones.
Important Notes
This is a visual framework, not a strategy.
No claims of predictive power are made.
Time structure does not replace risk management or execution logic.
The indicator is designed to adapt across markets, but interpretation remains discretionary.
Final Thoughts
Time is often treated as secondary to price.
This tool exists to make time visible, structured, and easy to work with — nothing more, nothing less.
PEAD ScreenerPEAD Screener - Post-Earnings Announcement Drift Scanner
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WHY EARNINGS ANNOUNCEMENTS CREATE OPPORTUNITY
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The days immediately following an earnings announcement are among the noisiest periods for any stock. Within hours, the market must digest new information about a company's profits, revenue, and future outlook. Analysts scramble to update their models. Institutions rebalance positions. Retail traders react to headlines.
This chaos creates a well-documented phenomenon called Post-Earnings Announcement Drift (PEAD): stocks that beat expectations tend to keep rising, while those that miss tend to keep falling - often for weeks after the initial announcement. Academic research has confirmed this pattern persists across decades and markets.
But not every earnings surprise is equal. A company that beats estimates by 5 cents might move very differently than one that beats by 5 cents with unusually high volume, or one where both earnings AND revenue exceeded expectations. Raw numbers alone don't tell the full story.
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HOW "STANDARDIZED UNEXPECTED" METRICS CUT THROUGH THE NOISE
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This screener uses a statistical technique to measure how "surprising" a result truly is - not just whether it beat or missed, but how unusual that beat or miss was compared to the company's own history.
The core idea: convert raw surprises into Z-scores.
A Z-score answers the question: "How many standard deviations away from normal is this result?"
- A Z-score of 0 means the result was exactly average
- A Z-score of +2 means the result was unusually high (better than ~95% of historical results)
- A Z-score of -2 means the result was unusually low
By standardizing surprises this way, we can compare apples to apples. A small-cap biotech's $0.02 beat might actually be more significant than a mega-cap's $0.50 beat, once we account for each company's typical variability.
This screener applies this standardization to three dimensions: earnings (SUE), revenue (SURGE), and volume (SUV).
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THE 9 SCREENING CRITERIA
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1. SUE (Standardized Unexpected Earnings)
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WHAT IT IS:
SUE measures how surprising an earnings result was, adjusted for the company's historical forecast accuracy.
Calculation: Take the earnings surprise (actual EPS minus analyst estimate), then divide by the standard deviation of past forecast errors. This uses a rolling window of the last 8 quarters by default.
Formula: SUE = (Actual EPS - Estimated EPS) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SUE > +2.0: Strongly positive surprise - earnings beat expectations by an unusually large margin. These stocks often continue drifting higher.
- SUE between 0 and +2.0: Modest positive surprise - beat expectations, but within normal range.
- SUE between -2.0 and 0: Modest negative surprise - missed expectations, but within normal range.
- SUE < -2.0: Strongly negative surprise - significant miss. These stocks often continue drifting lower.
For long positions, look for SUE values above +2.0, ideally combined with positive SURGE.
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2. SURGE (Standardized Unexpected Revenue)
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WHAT IT IS:
SURGE applies the same standardization technique to revenue surprises. While earnings can be manipulated through accounting choices, revenue is harder to fake - it represents actual sales.
Calculation: Take the revenue surprise (actual revenue minus analyst estimate), then divide by the standard deviation of past revenue forecast errors.
Formula: SURGE = (Actual Revenue - Estimated Revenue) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SURGE > +1.5: Strongly positive revenue surprise - the company sold significantly more than expected.
- SURGE between 0 and +1.5: Modest positive surprise.
- SURGE < 0: Revenue missed expectations.
The most powerful signals occur when BOTH SUE and SURGE are positive and elevated (ideally SUE > 2.0 AND SURGE > 1.5). This indicates the company beat on both profitability AND top-line growth - a much stronger signal than either alone.
When SUE and SURGE diverge significantly (e.g., high SUE but negative SURGE), treat with caution - the earnings beat may have come from cost-cutting rather than genuine growth.
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3. SUV (Standardized Unexpected Volume)
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WHAT IT IS:
SUV detects unusual trading volume after accounting for how volatile the stock is. More volatile stocks naturally have higher volume, so raw volume comparisons can be misleading.
Calculation: This uses regression analysis to model the expected relationship between price volatility and volume. The "unexpected" volume is the residual - how much actual volume deviated from what the model predicted. This residual is then standardized into a Z-score.
In plain terms: SUV asks "Given how much this stock typically moves, is today's volume unusually high or low?"
HOW TO INTERPRET:
- SUV > +2.0: Exceptionally high volume relative to the stock's volatility. This often signals institutional activity - big players moving in or out.
- SUV between +1.0 and +2.0: Elevated volume - above normal interest.
- SUV between -1.0 and +1.0: Normal volume range.
- SUV < -1.0: Unusually quiet - less activity than expected.
High SUV combined with positive price movement suggests accumulation (buying). High SUV combined with negative price movement suggests distribution (selling).
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4. % From D0 Close
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WHAT IT IS:
This measures how far the current price has moved from the closing price on its initial earnings reaction day (D0). The "reaction day" is the first trading day that fully reflects the earnings news - typically the day after an after-hours announcement, or the announcement day itself for pre-market releases.
Calculation: ((Current Price - D0 Close) / D0 Close) × 100
HOW TO INTERPRET:
- Positive values: Stock has gained ground since earnings. The higher the percentage, the stronger the post-earnings drift.
- 0% to +5%: Modest positive drift - earnings were received well but momentum is limited.
- +5% to +15%: Strong drift - buyers continue accumulating.
- > +15%: Exceptional drift - significant institutional interest likely.
- Negative values: Stock has given back gains or extended losses since earnings. May indicate the initial reaction was overdone, or that sentiment is deteriorating.
This metric is most meaningful within the first 5-20 trading days after earnings. Extended drift (maintaining gains over 2+ weeks) is a stronger signal than a quick spike that fades.
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5. # Pocket Pivots
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WHAT IT IS:
Pocket Pivots are a volume-based pattern developed by Chris Kacher and Gil Morales. They identify days where institutional buyers are likely accumulating shares without causing obvious breakouts.
Calculation: A Pocket Pivot occurs when:
- The stock closes higher than it opened (up day)
- The stock closes higher than the previous day's close
- Today's volume exceeds the highest down-day volume of the prior 10 trading sessions
The screener counts how many Pocket Pivots have occurred since the earnings announcement.
HOW TO INTERPRET:
- 0 Pocket Pivots: No detected institutional accumulation patterns since earnings.
- 1-2 Pocket Pivots: Some institutional buying interest - worth monitoring.
- 3+ Pocket Pivots: Strong accumulation signal - institutions appear to be building positions.
Pocket Pivots are most significant when they occur:
- Immediately following earnings announcements
- Near moving average support (10-day, 21-day, or 50-day)
- On above-average volume
- After a period of price consolidation
Multiple Pocket Pivots in a short period suggest sustained institutional demand, not just a one-day event.
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6. ADX/DI (Trend Strength and Direction)
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WHAT IT IS:
ADX (Average Directional Index) measures trend strength regardless of direction. DI (Directional Indicator) shows whether the trend is bullish or bearish.
Calculation: ADX uses a 14-period lookback to measure how directional (trending) price movement is. Values range from 0 to 100. The +DI and -DI components compare upward and downward movement.
The screener shows:
- ADX value (trend strength)
- Direction indicator: "+" for bullish (price trending up), "-" for bearish (price trending down)
HOW TO INTERPRET:
- ADX < 20: Weak trend - the stock is moving sideways, choppy. Not ideal for momentum trading.
- ADX 20-25: Trend is emerging - potentially starting a directional move.
- ADX 25-40: Strong trend - clear directional movement. Good for momentum plays.
- ADX > 40: Very strong trend - powerful move in progress, but may be extended.
The direction indicator (+/-) tells you which way:
- "25+" means ADX of 25 with bullish direction (uptrend)
- "25-" means ADX of 25 with bearish direction (downtrend)
For post-earnings plays, ideal setups show ADX rising above 25 with positive direction, confirming the earnings reaction is developing into a sustained trend rather than a one-day spike.
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7. Institutional Buying PASS
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WHAT IT IS:
This proprietary composite indicator detects patterns consistent with institutional accumulation at three stages after earnings:
EARLY (Days 0-4): Looks for "large block" buying on the earnings reaction day (exceptionally high volume with a close in the upper half of the day's range) combined with follow-through buying on the next day.
MID (Days 5-9): Checks for sustained elevated volume (averaging 1.5x the 20-day average) combined with positive drift and consistent upward price movement (more up days than down days).
LATE (Days 10+): Detects either visible accumulation (positive drift with high volume) OR stealth accumulation (positive drift with unusually LOW volume - suggesting smart money is quietly building positions without attracting attention).
HOW TO INTERPRET:
- Check mark/value of '1': Institutional buying pattern detected. The stock shows characteristics consistent with large players accumulating shares.
- X mark/value of '0': No institutional buying pattern detected. This doesn't mean institutions aren't buying - just that the typical footprints aren't visible.
A passing grade here adds conviction to other bullish signals. Institutions have research teams, information advantages, and long time horizons. When their footprints appear in the data, it often precedes sustained moves.
Important: This is a pattern detection tool, not a guarantee. Always combine with other analysis.
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8. Strong ATR Drift PASS
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WHAT IT IS:
This measures whether the stock has drifted significantly relative to its own volatility. Instead of asking "did it move 10%?", it asks "did it move more than 1.5 ATRs?"
ATR (Average True Range) measures a stock's typical daily movement. A volatile stock might move 5% daily, while a stable stock might move 0.5%. Using ATR normalizes for this difference.
Calculation:
ATR Drift = (Current Close - D0 Close) / D0 ATR in dollars
The indicator passes when ATR Drift exceeds 1.5 AND at least 5 days have passed since earnings.
HOW TO INTERPRET:
- Check mark/value of '1': The stock has drifted more than 1.5 times its average daily range since earnings - a statistically significant move that suggests genuine momentum, not just noise.
- X mark/value of '0': The drift (if any) is within normal volatility bounds - could just be random fluctuation.
Why wait 5 days? The immediate post-earnings reaction (days 0-2) often includes gap fills and noise. By day 5, if the stock is still extended beyond 1.5 ATRs from the earnings close, it suggests real buying pressure, not just a reflexive gap.
A passing grade here helps filter out stocks that "beat earnings" but haven't actually moved meaningfully. It focuses attention on stocks where the market is voting with real capital.
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9. Days Since D0
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WHAT IT IS:
Simply counts the number of trading days since the earnings reaction day (D0).
HOW TO INTERPRET:
- Days 0-5 (Green): Fresh earnings - the information is new, institutional repositioning is active, and momentum trades are most potent. This is the "sweet spot" for PEAD strategies.
- Days 6-10 (Neutral): Mid-period - some edge remains but diminishing. Good for adding to winning positions, less ideal for new entries.
- Days 11+ (Red): Extended period - most of the post-earnings drift has typically played out. Higher risk that momentum fades or reverses.
Research shows PEAD effects are strongest in the first 5-10 days after earnings, then decay. Beyond 20-30 days, the informational advantage of the earnings surprise is largely priced in.
Use this to prioritize: focus on stocks with strong signals that are still in the early window, and be more selective about entries as days accumulate.
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PUTTING IT ALL TOGETHER
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You can use this screener in the chart view or in the Screener.
One combination of the above filters to develop a shortlist of positive drift candidates may be:
- SUE > 2.0 (significant earnings beat)
- SURGE > 1.5 (significant revenue beat)
- Positive % From D0 Close (price confirming the good news)
- Institutional Buying PASS (big players accumulating)
- Strong ATR Drift PASS (statistically significant movement)
- Days Since D0 < 10 (still in the active drift window)
No single indicator is sufficient. The power comes from convergence - when multiple independent measures all point the same direction.
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SETTINGS
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Key adjustable parameters:
- SUE Method: "Analyst-based" uses consensus estimates; "Time-series" uses year-over-year comparison
- Window Size: Number of quarters used for standardization (default: 8)
- ATR Drift Threshold: Minimum ATR multiple for "strong" classification (default: 1.5)
- Institutional Buying thresholds: Adjustable volume and CLV parameters
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DISCLAIMER
═══════════════════════════════════════════════════════════════
This screener is a research tool, not financial advice. Past patterns do not guarantee future results. Always conduct your own due diligence and manage risk appropriately. Post-earnings trading involves significant uncertainty and volatility. The 'SUE' in this indicator does not represent a real person; any similarity to actual Sue's (or Susans for that matter) living or dead is quite frankly ridiculous, not to mention coincidental.
CRUX-3 Macro Regime Index"CRUX-3 Macro Regime Index"
Description:
CRUX-3 Macro Regime Index is a higher-timeframe macro indicator designed to evaluate how crypto markets are performing relative to traditional equities. It compares Bitcoin, Ethereum, and the broader altcoin market (TOTAL3) against the S&P 500 using Z-score normalization to highlight periods of relative outperformance or underperformance.
The indicator incorporates liquidity-based regime detection using Bitcoin dominance and stablecoin dominance to classify market environments as Risk-On, BTC-Led, or Risk-Off. Background shading visually highlights these regimes, helping users identify broader macro conditions rather than short-term trade signals.
CRUX-3 is intended for macro context, regime awareness, and allocation bias decisions, not for precise trade entries or timing.
How to Use:
Weekly timeframe recommended for best results
Rising Z-scores indicate crypto outperforming equities
ETH/SPX typically acts as an early rotation signal
TOTAL3/SPX confirms broader altcoin participation
Regime shading reflects liquidity conditions, not price forecasts
Regime Definitions:
Risk-On: BTC dominance and stablecoin dominance declining
BTC-Led: BTC dominance strong while stablecoin dominance eases
Risk-Off: BTC dominance and stablecoin dominance rising
Notes:
Forward regime bands are statistical reference guides based on historical behavior
This indicator does not predict future prices or market direction
Best used alongside price charts and other macro tools
Disclaimer:
This indicator is for educational and informational purposes only. It does not constitute financial advice, investment advice, or trading recommendations.
Recommended Settings:
Timeframe: Weekly (1W)
Z-Score Lookback: 52
Forward Regime Bands: Enabled
Seasonality Scanner by thedatalayers.comThe Seasonality Scanner automatically detects seasonal patterns by scanning a user-defined number of past years (e.g., the last 10 years).
Based on this historical window, the indicator identifies the strongest seasonal tendency for the currently selected date range.
The scanner evaluates all valid seasonal windows using two filters:
• Hit Rate - the percentage of profitable years
• Average Return - the highest mean performance across the analyzed period
The best-scoring seasonal setup is displayed directly on the chart, including the exact start and end dates of the identified pattern for the chosen time range.
Users can define the period they want to analyze, and the indicator will automatically determine which seasonal window performed best over the selected history.
Recommended Settings (Standard Use)
For optimal and consistent results, the following settings are recommended:
• Search Window: 20-30
• Minimum Length: 5
• Time Period: from 2015 onward
• US Election Cycle: All Years
These settings provide a balanced and reliable baseline to detect meaningful seasonal tendencies across markets.
This indicator helps traders understand when recurring seasonal patterns typically occur and how they may align with ongoing market conditions.
This indicator is intended to be used exclusively on the daily timeframe, as all calculations are based on daily candles.
Using it on lower timeframes may result in inaccurate or misleading seasonal readings.
Seasonality by thedatalayers.comThe Seasonality Indicator calculates the average historical performance of the currently selected asset by analyzing a user-defined number of past years (e.g., the last 10 years).
The number of years included in the calculation can be adjusted directly in the settings panel.
Based on this historical window, the indicator creates an average seasonal curve, which represents how the market typically behaved during each part of the year.
This averaged curve acts as a forecast for the upcoming months, highlighting periods where the market has shown a consistent tendency in the past.
Traders can use this seasonal projection to identify times of higher statistical likelihood for upward or downward movement.
The indicator works especially well when combined with the Seasonality Analysis Tool, which helps identify specific historical windows and strengthens overall seasonal decision-making.
This indicator must be used exclusively on the daily timeframe, as all calculations are based on daily candle data.
Other timeframes will not display accurate seasonal structures.
The Seasonality Indicator provides a clear, data-driven view of recurring annual patterns and allows traders to better understand when historical tendencies may influence future price action.
Trading Asset Comparison Oscillator by thedatalayers.comThe Trading Asset Comparison Oscillator compares the currently opened asset with a user-selected reference symbol to identify periods of relative overvaluation and undervaluation.
The concept is based on the idea that markets constantly seek fair value. When an asset becomes mispriced relative to a meaningful benchmark, it often moves back toward equilibrium.
This indicator measures that relationship and transforms it into an easy-to-read oscillator:
• Green Zone (Undervalued) - The selected asset is undervalued compared to the reference symbol.
This reflects potential upward pressure as markets tend to correct undervaluation over time.
• Red Zone (Overvalued) - The asset is overvalued relative to the reference symbol.
This may indicate a higher likelihood of downward movement as price seeks rebalancing.
Users can set any reference instrument they consider relevant-commodities, indices, currency pairs, or other assets. The oscillator quantifies the valuation difference based on a configurable cycle length.
The recommended setting is Cycle = 10, which provides a balanced and responsive signal
structure.
Since this indicator relies on broader valuation dynamics, it is designed to be used exclusively on the daily timeframe. Lower timeframes may not reflect true fundamental value relationships.
The Asset Comparison Oscillator helps traders identify when an asset appears cheap or expensive relative to another, offering an additional layer of fundamental context to support directional trading decisions.
COT Index by thedatalayers.comThe COT Index transforms the weekly COT net positions of Commercial traders into a normalized mathematical model.
Instead of displaying raw net positioning, the COT Index processes the data through a cyclical normalization algorithm (commonly using a 26-week or alternatively a 52-week cycle).
This makes it easier to identify bullish or bearish extremes in Commercial activity.
The index is plotted as a color-coded line:
• Green Zone - Commercials are mathematically classified as bullish.
Historically, bullish Commercial positioning often aligns with upward market pressure.
• Red Zone - Commercials are mathematically classified as bearish.
This typically corresponds with increased downward pressure in the underlying market.
• Neutral Zone - Neither bull nor bear dominance; positioning is mid-range.
Since COT data is published only once per week and the COT Index is built on cyclical multi-week analysis, the indicator is intended to be used exclusively on the weekly timeframe.
Using lower timeframes will not reflect the structure of the data accurately.
The selected cycle length (typically 26 weeks, optionally 52 weeks) determines how net positions are compared and normalized, and can influence how quickly extreme zones appear.
The COT Index provides an objective way to interpret Commercial trader sentiment and to identify potential directional bias in the market.
COT Net Positions by thedatalayers.comCOT Net Positions by thedatalayers.com visualizes the net positioning of different trader groups based on the weekly Commitments of Traders (COT) reports published by the CFTC every Friday.
The indicator processes the raw COT data by calculating Long positions minus Short positions for each trader category. This results in the net position of every group per report.
The script then plots these net positions continuously over time, based on every available COT release. This creates a clear and easy-to-read visualization of how different market participants are positioned.
The indicator displays the three primary COT categories:
• Commercials
• Non-Commercials
• Non-Reportables
By observing how these trader groups shift their positioning, traders can better understand market sentiment and identify potential directional biases or changes in underlying market pressure.
This tool is designed to help traders incorporate positioning data into their analysis and to better interpret how institutional and speculative flows evolve over time.
This indicator is intended to be used exclusively on the weekly timeframe.
COT data is published once per week by the CFTC and therefore only updates weekly.
Using this script on lower timeframes may result in misleading visualization or irregular spacing between data points.
For correct interpretation, please apply it on 1W charts only.
Dragon Smart Detector [Sentiment & Flow HUD]Dragon Smart Detector is a professional-grade contextual analysis tool designed to answer the most critical questions in trading: "Is the market driven by Fear or Greed?", "Is Smart Money stepping in?", and "Is the current breakout genuine?".
Instead of lagging indicators or simple buy/sell arrows, this tool provides a Head-Up Display (HUD) that analyzes the internal dynamics of price and volume in real-time.
1. 🧠 How It Works (The Core Logic)
This indicator combines technicals and fundamentals into four distinct metrics:
A. Market Sentiment (The Mood)
Quantifies crowd psychology using a hybrid algorithm of RSI (14) and Bollinger Bands.
EXTREME FOMO 🔥 (Red): Price is overextended beyond the upper band with high RSI. Indicates the crowd is euphoric. Risk Level: High.
EXTREME FEAR 😱 (Cyan): Price is panicking below the lower band with low RSI. Often marks a potential reversal bottom (Capitulation).
GREED / ANXIETY: Intermediate states of the market.
B. Volume Winner & Flow (The Battle)
Since accurate "Order Flow" data is not universal across all feeds, this script uses Price Spread Analysis to estimate aggressive pressure.
BULLS: Close price is near the High of the candle $\rightarrow$ Accumulation/Buying Pressure.
BEARS: Close price is near the Low of the candle $\rightarrow$ Distribution/Selling Pressure.
Flow Display: Shows the estimated percentage of Buying vs. Selling volume for the current session.
C. Volume Strength (RVOL)
Relative Volume compares the current volume against the 20-period simple moving average.
1.0x: Average volume.
> 2.0x (Orange): Volume is double the average. Significant activity.
> 3.0x (Pink/Magenta): Institutional Activity. Massive volume spike indicating Smart Money participation.
D. Float Rotation (The "Dragon" Metric)
Calculates what percentage of the company's available shares have been traded today.
Smart Data Fetch: The script automatically attempts to load FLOAT_SHARES. If unavailable (common with ETFs or some Indices), it intelligently switches to TOTAL_SHARES as a backup.
Why it matters: High rotation (e.g., > 2%) accompanied by a price increase suggests a massive changing of hands, often validating a strong breakout.
2. 🎯 How to Trade (Strategy Guide)
Scenario 1: The "Dragon Breakout" (Momentum)
Condition: Price is breaking a key resistance level.
Check HUD:
WINNER: Must be BULLS.
VOL STRENGTH: Should be > 1.5x (Orange) or > 3.0x (Pink).
ROTATION: High rotation confirms the breakout is supported by fresh demand.
Action: Enter the trade with confidence.
Scenario 2: The "Capitulation Buy" (Reversal)
Condition: Price is dropping sharply.
Check HUD:
SENTIMENT: Must show EXTREME FEAR 😱 (Cyan).
WINNER: Wait for the "Winner" status to flip from BEARS to BULLS (indicating a wick/rejection of lows).
Action: Look for long entries or reversal patterns.
Scenario 3: The "FOMO Trap" (Risk Management)
Condition: Price is rallying, but you are late to the party.
Check HUD:
SENTIMENT: Shows EXTREME FOMO 🔥.
FLOW: Shows BEARS winning (selling into strength/wicks).
Action: Do NOT buy. Tighten stop-losses or take partial profits.
3. ⚙️ Settings & Features
Smart Backup Data: Automatically handles N/A data for NASDAQ/NYSE tickers (like TSLA, NVDA) by switching data sources.
Manual Float: Allows you to manually input share count (in Millions) for penny stocks or local markets where data is missing.
Minimalist Mode: Hides Fundamental rows (Float/Rotation) if you only want to see Sentiment and Flow.
Visuals: Modern Neon/Borderless interface designed for dark mode charts.
Disclaimer
This indicator is for educational and informational purposes only. "Volume Flow" and "Winner" are estimates based on Price Action logic, not Level 2 data. Fundamental data relies on TradingView's financial database. Past performance does not guarantee future results.
Tip: Add this to your favorites ⭐️ and boost 🚀 if you find it useful in your daily trading!
AlphaSignals Pro🟠OVERVIEW
AlphaSignals Pro™ is a comprehensive trading indicator suite developed by A1TradingHub. The
system combines trend analysis, momentum indicators, and proprietary signal algorithms to identify
high-probability trading opportunities across all market conditions and timeframes.
Core Components
■ Long/Short Signals — Clear entry markers based on trend reversals and momentum shifts
■ Golden Call/Put — Premium signals for high-conviction directional trades
■ Support & Resistance — Dynamic price zones with visual highlighting
■ Moving Averages — Trend direction with color-coded crossover signals
■ Keltner Channels — Volatility bands for breakout and mean-reversion setups
■ Signal Dashboard — Multi-symbol overview with trend and momentum status
🟠Long & Short Entry Signals
The core signal system identifies optimal entry points by analyzing price action, momentum, and
trend structure. LONG signals appear at potential reversal points for upward moves, while SHORT
signals indicate bearish opportunities at resistance.
◆ Green 'LONG' labels mark buy zones at support levels
◆ Red 'SHORT' labels indicate sell zones at resistance
◆ Momentum confirmation filters out false signals
◆ Works across all timeframes (1min to daily)
🟠Trend Direction Arrows
Small directional arrows provide real-time trend feedback. ▲ Green arrows confirm bullish
momentum, ▼ red arrows signal bearish pressure. These micro-signals help traders stay aligned with
the dominant trend.
◆ Green up arrows during bullish momentum phases
◆ Red down arrows indicate bearish momentum shifts
◆ Confirms entry signals and aids trade management
◆ Minimalist design preserves chart clarity
🟠 Golden Put Signal
The Golden Put identifies high-probability short opportunities. Triggers when multiple bearish factors
align: price rejection at resistance, momentum divergence, and volume confirmation. These premium
signals represent the highest-conviction bearish trades.
◆ Triggered at major resistance with momentum divergence
◆ Red 'GOLDEN PUT' label marks premium short entries
◆ Designed for options traders seeking directional plays
◆ Lower frequency, higher accuracy than standard signals
🟠 Golden Call Signal
The Golden Call is the bullish counterpart, identifying premium long opportunities. Appears when
price finds strong support with bullish momentum divergence and institutional volume patterns. Marks
optimal entry points for aggressive upside plays.
◆ Yellow 'GOLDEN CALL' highlights premium buy setups
◆ Triggers at key support with momentum confirmation
◆ Ideal for call options or leveraged positions
◆ Signals typically precede significant advances
🟠 Moving Average System
The dual moving average system provides trend context and dynamic support/resistance. The red
line is the fast MA (shorter period), the green line is the slow MA. Color transitions indicate trend
changes and crossover signals.
◆ Red MA: Fast period for short-term direction
◆ Green MA: Slow period for primary trend
◆ Bullish crossover: Fast crosses above slow
◆ Bearish crossover: Fast crosses below slow
◆ MAs act as dynamic support/resistance
🟠 Keltner Channel Bands
Volatility-based price envelopes that adapt to market conditions. Bands expand during high volatility,
contract during consolidation. Price at outer bands signals mean-reversion opportunities; breakouts
beyond bands may indicate trend continuation.
◆ Upper/lower bands adapt to current volatility
◆ Pink outer bands mark extreme price zones
◆ Cyan middle band shows baseline trend
◆ Band touches signal reversal or breakout setups
◆ Shaded fill visualizes the volatility range
🟠 Support & Resistance Zones
Automatic detection of key price levels with visual highlighting. Green zones mark support where
buying pressure emerges, red zones highlight resistance with selling pressure. Dashed lines show
precise price levels.
◆ Green shaded areas: Support zones (buy interest)
◆ Red shaded areas: Resistance zones (sell interest)
◆ Horizontal dashed lines mark exact levels
◆ Zones update dynamically as new levels form
◆ Essential for targets and stop-loss placement
🟠 Golden Signal Dashboard
Multi-symbol dashboard provides comprehensive market overview. Track multiple instruments with
real-time trend status, momentum readings, active signals, and freshness indicators. Perfect for
scanning opportunities across your watchlist.
◆ SYMBOL: Tracked instruments (SPY, QQQ, IWM, TSLA)
◆ PRICE & CHG%: Current price and daily change
◆ MOMENTUM: Bullish/Bearish classification
◆ SIGNAL: Active Golden Call or Put signals
◆ BARS: Bars since last signal
◆ STATUS: Signal temperature (HOT/WARM/COLD)
🟠 Best Practices
✓ Confirm signals with dominant trend (use MAs)
✓ Prioritize Golden signals — higher probability
✓ Use S/R zones for stop-loss placement
✓ Check dashboard for multi-timeframe confluence
✓ Combine with your own analysis
Numanti - FairRate EUR/USD Fair ValueFairRate | EUR/USD Fair Value Indicator
Know When EUR/USD Is Overpriced or Underpriced
Price tells you where the market *is*. Fair value tells you where it *should be*.
EUR/USD doesn't move randomly. Interest rates, yield curves, risk appetite, and equity flows drive where the pair trades over time. When price strays too far from these fundamentals, it tends to snap back.
FairRate shows you exactly how far price has strayed.
How It Works
The indicator calculates a fair value for EUR/USD based on macroeconomic variables updated weekly. It then measures the deviation between current price and fair value in standard deviations (the z-score).
> +2σ --> EUR significantly overvalued — watch for pullback
+1σ to +2σ --> EUR above fair value
-1σ to +1σ --> Near equilibrium
-1σ to -2σ --> EUR below fair value
< -2σ --> EUR significantly undervalued — watch for bounce
The bigger the deviation, the stronger the fundamental pressure for mean reversion.
What You See on the Chart
- Fair Value Line — Where EUR/USD "should" be trading
- ±1σ and ±2σ Bands — Normal and extreme deviation zones
- Info Panel — Current fair value, z-score, and signal status
When price pushes into the outer bands, fundamentals are stretched. That's where opportunities often emerge.
Model Quality
This isn't a typical indicator or curve-fitted approach. It's a proper econometric model:
- R² > 80% — Fundamentals explain most of EUR/USD movement
- Out-of-sample validated — Works on data the model never saw
- Updated weekly — Fresh estimates every Friday
- Research-backed — Methodology documented in white paper
How Traders Use It
Mean Reversion
When z-score hits extreme levels (±2σ), look for reversal setups. Combine with your technical analysis for entries.
Trend Confirmation
If price is trending AND fundamentals support it (z-score moving in trend direction), that's a stronger move.
Risk Filter
Avoid counter-trend trades when z-score is near zero — there's no fundamental reason to expect a reversal.
Context Layer
Add fundamental context to pure price action. Know whether you're trading with or against the macro backdrop.
### What This Is NOT
- Not a buy/sell signal generator
- Not a timing indicator
- Not a substitute for technical analysis
FairRate is a fundamental layer — one piece of the puzzle that tells you whether EUR/USD is cheap, expensive, or fairly priced right now.
The Model
Built on peer-reviewed econometric methodology. The model captures the fundamental drivers that institutional desks use to assess currency valuation — not a black-box indicator or curve-fitted pattern.
Add FairRate to your EUR/USD analysis. Know where fundamentals stand.
© 2025 Numanti. All rights reserved.
Swing Elite Valuation ToolSwing Elite Macro Valuation
This indicator provides intermarket valuation analysis by measuring how an asset is priced relative to key macroeconomic instruments. Rather than analyzing price in isolation, it contextualizes current levels against bonds, the dollar, and gold — the three pillars of macro market structure.
The Concept Behind Macro Valuation
Assets don't move in a vacuum. Equities, commodities, and currencies maintain dynamic relationships with macro instruments. When the S&P 500 rises while bonds (ZB1) also rally, that's a different signal than when stocks rise while bonds sell off. Similarly, an asset's relationship to the dollar index (DXY) and gold (GC1) reveals whether price moves reflect genuine strength or simply dollar weakness.
This indicator quantifies these relationships by normalizing relative performance into a 0-100 scale, making it easy to identify when an asset is historically overvalued or undervalued relative to macro conditions.
How Valuation Is Calculated
The indicator computes a ratio between the charted asset and each comparison instrument, then normalizes this ratio as a percentage move from a historical baseline. Two modes are available: Short-term mode captures recent sentiment shifts and is useful for tactical positioning, while Long-term mode evaluates deeper macro positioning for swing trades and portfolio decisions.
The normalized reading places current valuation within historical context. A reading near 88+ suggests the asset is overvalued relative to that macro instrument — price has extended beyond typical ranges. Readings below 10 indicate undervaluation, where the asset may be oversold relative to macro conditions.
Dynamic vs Manual Thresholds
Users can select between manual threshold levels or automatic dynamic bands. Auto-levels calculate overvalued and undervalued zones using standard deviation from the mean, adapting to each asset's historical volatility. Manual mode allows fixed thresholds for traders who prefer consistent reference points across different instruments.
Multi-Instrument Flexibility
While defaults include ZB1 (30-year Treasury futures), DXY (dollar index), and GC1 (gold futures), any symbol can be substituted. This allows analysis against silver, currency futures, sector ETFs, or any instrument relevant to your trading thesis. Each comparison instrument displays independently with color-coded status: readings in overvalued territory appear red, undervalued zones show green, and neutral conditions display blue.
Practical Application
This tool serves traders who incorporate intermarket analysis into their decision-making. When an asset shows overvalued readings against multiple macro instruments simultaneously, it suggests price has extended relative to the broader macro environment — a potential mean reversion setup. Conversely, undervaluation across multiple macro comparisons can highlight value opportunities where price hasn't kept pace with supportive macro conditions.
The dashboard table provides at-a-glance status for each comparison, while alert conditions enable notifications when valuation crosses key thresholds.
KIMATIX LITE AbsorptionThis indicator highlights absorption intensity directly on the chart using numeric sigma values only.
It is a deliberately reduced, signal-agnostic visualization designed to expose where significant absorption occurs, without adding levels, lines, or trade logic.
What you see
Numeric sigma values on candles
Each number represents the strength of absorption measured in standard deviations (σ).
Color-coded context
Green numbers below price → sell-side absorption
Red numbers above price → buy-side absorption
Only values that exceed the Minimum Sigma threshold are displayed.
No lines, zones, triangles, or alerts are shown — only the raw absorption magnitude.
How it works (LITE Version)
Absorption is derived from volume relative to candle structure
Values are normalized and filtered using:
A fixed statistical lookback
Wick dominance rules to avoid noise
Only statistically significant events (σ ≥ threshold) are visualized
All other calculations run silently in the background.
Intended use
This Lite version is meant to:
Identify areas of aggressive participation or defense
Spot potential absorption during trends or ranges
Provide context for liquidity, exhaustion, or hidden interest
It is not a trading system and does not generate entries or exits.
Use it as a contextual layer alongside your own execution logic.
The full version is distributed separately.
More information can be found here:
whop.com
KIMATIX LITE Trading TableThe KIMATIX LITE Trading Table is a structured decision-support overlay that condenses complex market logic into a single, easy-to-read table.
Table fields explained
* BUY / SELL when a valid setup is active
* NONE when no qualified setup exists
Includes the live status: ACTIVE, TP1, TP2, or STOP.
ENTRY
The calculated entry price based on confirmed signal logic.
STOP
The risk-defined stop level derived from ATR structure.
TP1 / TP2
Pre-calculated profit targets based on fixed R-multiples.
MGMT
Displays trade management guidance when applicable
(e.g. instruction to move stop-loss to break-even after TP1).
Intended use
This indicator is not an execution tool.
It is meant to:
* Maintain situational awareness
* Enforce structured trade management
* Reduce emotional or impulsive decision-making
* Complement existing execution workflows
No alerts, chart drawings, or execution triggers are provided in this version.
The full version is distributed separately.
More information can be found here:
whop.com
LQ plots w/filled - 0x/Gh0stLiquidity Indicator
This indicator identifies significant swing highs and swing lows based on user-defined pivot strength and projects them forward as potential liquidity and reaction levels.
When a valid swing forms, the script:
1. Draws a horizontal level at the swing price
a. Optionally extends that level forward in time
b. Visualizes the level as a line and/or price box
c. Tracks the level until price interacts with or fills it
2. When price trades back through a level:
a. The level is marked as filled
b. A clear X marker is drawn at the point of fill
c. The level is optionally removed or hidden based on user settings
3. Useful for:
a. Designed for traders who focus on:
1. Market structure
2. Liquidity targets
Swing-based support and resistance
Identifying where price has already “paid” liquidity
This tool is structure-driven, it highlights where price has reacted and where it has not, letting YOU, the trader decide how to act.
HTF Fair Value Gaps🔍 What This Indicator Does
1. Multi-Timeframe Fair Value Gap Mapping
Displays Fair Value Gaps from:
1H
4H
Daily (optional)
These HTF FVGs are projected onto lower timeframes (5M / 15M) so you can:
trade in alignment with HTF imbalance,
avoid entering directly into opposing zones,
understand where reactions are likely.
2. Bullish & Bearish FVG Clarity
Bullish FVGs highlight areas of inefficiency below price
Bearish FVGs highlight areas of inefficiency above price
Zones are color-coded and extend forward for clarity
This helps traders immediately identify:
pullback targets in trends,
continuation zones,
areas of potential reaction or acceleration.
3. Clean, Non-Cluttered Visualization
No lower-timeframe noise
No redundant boxes
HTF gaps only — intentional and selective
This keeps execution charts readable and focused.






















