Sideways Zone Breakout 📘 Sideways Zone Breakout – Indicator Description
Sideways Zone Breakout is a visual market-structure indicator designed to identify low-volatility consolidation zones and highlight potential breakout opportunities when price exits these zones.
This indicator focuses on detecting periods where price trades within a tight range, often referred to as sideways or consolidation phases, and visually marks these zones directly on the chart for clarity.
🔍 Core Concept
Markets often spend time moving sideways before making a directional move.
This indicator aims to:
Detect price compression
Visually highlight the sideways zone
Signal when price breaks above or below the zone boundaries
Instead of predicting direction, it simply reacts to range expansion after consolidation.
⚙️ How the Indicator Works
1️⃣ Sideways Zone Detection
The indicator looks back over a user-defined number of candles
It calculates the highest high and lowest low within that window
If the total price range remains within a defined percentage of the current price, the market is considered sideways
This helps filter out trending and highly volatile conditions.
2️⃣ Visual Zone Representation
When a sideways condition is detected:
A clear price zone is drawn between the recent high and low
The zone is displayed using a soft gradient fill for better visibility
Outer borders are added to enhance zone clarity without cluttering the chart
This makes consolidation areas easy to spot at a glance.
3️⃣ Breakout Identification
Once a sideways zone is active:
A bullish breakout is marked when price closes above the upper boundary
A bearish breakout is marked when price closes below the lower boundary
Directional arrows and labels are plotted directly on the chart to indicate these events.
📊 Visual Elements Included
Sideways consolidation zones with gradient fill
Upper and lower zone boundaries
Buy and Sell arrows on breakout
Optional text labels for clear interpretation
All visuals are designed to remain lightweight and readable on any chart theme.
🔧 User Inputs
Sideways Lookback (candles): Controls how many past candles are used to define the range
Max Range % (tightness): Determines how tight the range must be to qualify as sideways
Adjusting these inputs allows users to adapt the indicator to different instruments and timeframes.
📈 Usage Guidelines
Can be applied to any market or timeframe
Works well as a context or confirmation tool
Best used alongside volume, trend, or risk management tools
Signals should be validated with proper trade planning
⚠️ Disclaimer
This indicator is provided as open-source for educational and analytical purposes only.
It does not generate trade recommendations or guarantee outcomes.
Market conditions vary, and users are responsible for their own trading decisions.
Statistics
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.
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
Dynamic MAs Zscore | Lyro RSThe Dynamic MAs Zscore is an adaptive momentum and valuation oscillator built around advanced moving averages and statistical Z-Score normalization. By combining a wide selection of moving average types with dynamic deviation bands, this indicator delivers clear insights into trend strength , directional bias , and relative valuation — all in a clean, visually intuitive format.
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Key Features
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Dynamic Moving Average Engine
Applies one of 12 selectable moving average types (SMA, EMA, WMA, VWMA, HMA, ALMA, TEMA, etc.) to the chosen source. This allows fine-tuning between responsiveness and smoothness depending on market conditions.
Z-Score Normalization
Transforms the selected moving average into a standardized Z-Score:
(MA − mean) / standard deviation
This normalization makes momentum strength comparable across assets and timeframes.
Adaptive Deviation Bands
Upper and lower bands are derived from the rolling standard deviation of the Z-Score:
Custom band length
Independent positive and negative multipliers
These bands dynamically expand and contract with volatility.
Dual Signal Modes
Trend Mode – Focuses on directional continuation. Color changes and signals occur when Z-Score breaks above or below deviation bands.
Valuation Mode – Highlights relative overvaluation and undervaluation using a gradient color scale and predefined value zones.
Advanced Visual System
Includes bold layered plots, gradient fills, background shading, and candle/bar coloring to clearly reflect current market state.
Custom Color Palettes
Choose from multiple preset themes (Classic, Mystic, Accented, Royal) or define your own bullish and bearish colors.
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How It Works
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MA Calculation – The selected moving average type is applied to the chosen price source.
Z-Score Computation – The MA is normalized over a user-defined lookback period to quantify deviation from its mean.
Band Construction – Standard deviation of the Z-Score is calculated over the band length and scaled by positive/negative multipliers.
Mode-Dependent Logic
Trend Mode – Breaks above the upper band signal bullish momentum; breaks below the lower band signal bearish momentum.
Valuation Mode – A gradient reflects relative valuation from undervalued to overvalued, with background highlights at extreme Z-Score levels.
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Signal Interpretation
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Trend Confirmation
In Trend Mode, sustained moves beyond deviation bands indicate strong directional bias.
Momentum Strength
The distance of the Z-Score from zero reflects the intensity of trend momentum.
Relative Valuation
In Valuation Mode, deep negative Z-Scores suggest undervaluation, while high positive Z-Scores suggest overvaluation.
Visual Clarity
Bar and candle coloring aligned with oscillator state allows for rapid assessment of market conditions.
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Customization
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Adjust MA type and length to balance speed vs. smoothness.
Modify Z-Score length to control sensitivity.
Tune band length and multipliers for volatility adaptation.
Switch between Trend and Valuation modes depending on strategy.
Personalize visuals using preset or custom color palettes.
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Alerts
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Bullish condition when Z-Score > 0
Bearish condition when Z-Score < 0
Overvalued and undervalued valuation alerts
⚠️ Disclaimer
This indicator is intended for technical analysis and educational purposes only. It does not guarantee profitable outcomes and should be used alongside other tools, confirmation methods, and sound risk management. The author is not responsible for any financial decisions made using this indicator.
Pair Creation🙏🏻 The one and only pair construction tech you need, unlike others:
Applies one consistent operation to all the data features (not only prices). Then, the script outputs these, so you can apply other calculations on these outputs.
calculates a very fast and native volatility based hedge ratio, that also takes into account point value (think SPY vs ES) so you can easily use it in position sizing
Has built-in forward pricing aka cost of carry model , so you can de-drift pairs from cost of carry, discover spot price of oil based on futures, and ofc find arbitrage opportunities
Also allows to make a pair as a product of 2 series, useful for triangular arbitrage
This script can make a pair in 2 ways:
Ratio, by dividing leg 1 by leg 2
Product, by multiplying leg 1 by leg 2
The real mathematically right way to construct a pair is a ratio/product (Spreads are in fact = 2 legged portfolio, but I ain't told ya that ok). Why? Because a pair of 2 entities has a mathematically unique beauty, it allows direct comparisons and relationship analysis, smth you can't do directly with 3 and more components.
Multiplication (think inversions like (EURUSD -> USDEUR), and use cases for triangular arbitrage) is useful sometimes too.
...
Quickguide:
First, "Legs" are pair components: make a pair of related assets. Don’t be guided exclusively by clustering, cointegrations, mutual information etc. Common sense and exogenous info can easily made them all Forward pricing model: is useful when u work with spot vs futures pairs. Otherwise: put financing, storage and yield all on zeros, this way u will turn it off and have a pure ratio/product of 2 legs.
Look at the 2 numbers on the script’s status line: the first one would always be 1), and the second one is a variable.
First number (always 1) is multiplier for your position size on leg 1
The second number is the multiplier for your position size on leg 2 in the opposite direction.
If both legs are related, trading your sizes with these multipliers makes you do statistical arbitrage -> trading ~ volatility in risk free mode, while the relationship between the assets is still in place.
Also guys srsly, nobody ‘ever’ made a universal law that somewhy somehow for whatever secret conspiracy reason one shall only trade pairs in mean reverting style xd. You can do whatever you want:
Tilt hedge ratio significantly based on relative strength of legs
Trade the pair in momentum style
Ignore hedge ratio all together
And more and more, the limit is your imagination, e.g.:
Anticipate hedge ratio changes based on exogenous info and act accordingly
Scalp a pair just like any other asset
Make a pair out of 2 pairs
Like I mean it, whatever you desire
About forward pricing model:
It’s applied only to leg 2;
Direct: takes spot price and finds out implied futures price
Inverse: takes futures price and finds out implied spot price (try on oil)
Pls read online how to choose parameters, it’s open access reliable info
About the hedge ratio I use:
You prolly noticed the way I prefer to use inferred volumes vs the “real” ones. In pairs it’s especially meaningful, because real volumes lose sense in pair creation. And while volumes are closely tied to volatility, the inferred volumes ‘Are’ volatility irl (and later can be converted to currency space by using point value, allowing direct comparisons symbol vs symbol).
This hedge ratio is a good example of how discovering the real nature of entities beats making 100s of inventions, why domain knowledge and proper feature engineering beats difficult bulky models, neural networks etc. How simple data understanding & operations on it is all you need.
This script simply does this:
Takes inferred volume delta of both assets, makes a ratio, normalizes it by tick sizes and points values of both legs, calculates a typical value of this series.
That’s it, no step 2, we’re done. No Kalman filters, no TLS regression, no vine copulas, or whatever new fancy keywords you can come up with etc.
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^^ comparing real ES prices vs theoretical ones by forward-pricing model. Financing: 0.04, yield 0.0175
^^ EURUSD, 6E futures with theoretical futures price calculated with interest rate differential 0.02 (4% USD - 2% EUR interest rates)
^^4 different pairs (RTY/ES, YM/ES, NQ/ES, ES/ZN) each with different plot style (pick one you like in script's Style settings)
^^ YM/RTY pair, each plot represents ratio of different features: ratio of prices, ratio of inferred volume deltas, ratio of inferred volumes, ratio of inferred tick counts (also can be turned on/off in Style settings)
...
How can u upgrade it and make a step forward yourself:
On tradingview missing values are automatically fixed by backfilling, and this never becomes a thing until you hit high frequency data. You can do better and use Kalman filter for filling missing values.
Script contains the functions I use everywhere to calculate inferred volume delta, inferred volume, and inferred tick count.
...
∞
Trinity Real Move Detector DashboardRelease Notes (critical)
1. This code "will" require tweaks for different timeframes to the multiplier, do not assume the data in the table is accurate, cross check it with the Trinity Real Move Detector or another ATR tool, to validate the values in the table and ensure you have set the correct values.
2. I mention this below. But please understand that pine code has a limitation in the number of security calls (40 request.security() calls per script). This code is on the limit of that threshold and I would encourage developers to see if they can find a way around this to improve the script and release further updates.
What do we have...
The Trinity Real Move Detector Dashboard is a powerful TradingView indicator designed to scan multiple assets at once and show when each one has genuine short-term volatility "energy" — the kind that makes directional options trades (especially 0DTE or short-dated) have a high probability of follow-through, and can be used for swing trading as well. It combines a simple ATR-based volatility filter with a SuperTrend-style bias to tell you not only if the market is "awake" but also in which direction the momentum is leaning.
At its core, the indicator calculates the current ATR on your chosen timeframe and compares it to a user-defined percentage of the asset's daily ATR. When the short-term ATR spikes above that threshold, it signals "enough energy" — meaning the underlying is moving with real force rather than choppy noise. The SuperTrend logic then determines bullish or bearish bias, so the status shows "BULLISH ENERGY" (green) or "BEARISH ENERGY" (red) when energy is on, or "WAIT" when it's not. It also counts how many bars the energy has been active and shows the current ATR vs threshold for quick visual confirmation.
The dashboard displays all this in a clean table with columns for Symbol, Multiplier, Current ATR, Threshold, Status, Bars Active, and Bias (UP/DOWN). It's perfect for 3-minute charts but works on any timeframe — just adjust the multiplier based on the hints in the settings.
Editing symbols and multipliers is straightforward and user-friendly. In the indicator settings, you'll see numbered inputs like "1. Symbol - NVDA" and "1. Multiplier". To change an asset, simply type the new ticker in the symbol field (e.g., replace "NVDA" with "TSLA", "AVGO", or "ADAUSD"). You can also adjust the multiplier for each asset individually in the corresponding "Multiplier" field to make it more or less sensitive — lower numbers give more signals, higher numbers give stricter, higher-quality ones. This lets you customize the dashboard to your watchlist without any coding. For example, if you switch to a 4-hour chart or a slower-moving stock like AVGO, you may need to raise the multiplier (e.g., to 0.3–0.4) to avoid false "bullish" signals during minor bounces in a larger downtrend.
One important note about the multiplier and timeframes: the default values are optimized for fast intraday charts (like 3-minute or 5-minute). On higher timeframes (15-minute, 1-hour, 4-hour, or daily), the SuperTrend bias can be too sensitive with low multipliers (1.0 default in the code), leading to situations like the AVGO 4-hour example — where price is clearly downtrending, but the dashboard shows "BULLISH ENERGY" because the tight bands flip on small bounces. To fix this, you need to manually increase the multiplier for that asset (or all assets) in the settings. For 4-hour or daily charts, 0.25–0.35 is often better to match smoother SuperTrend indicators like Trinity. Always test on your timeframe and asset — crypto usually needs slightly lower multipliers than stocks due to higher volatility.
TradingView has a hard limit of 40 request.security() calls per script. Each asset in the dashboard requires several calls (current ATR, daily ATR, SuperTrend components, etc.), so with the full ATR-based bias, you can safely monitor about 6–8 assets before hitting the limit. Adding more symbols increases the number of calls and will trigger the "too many securities" error. This is a platform restriction to prevent excessive server load, and there's no official way around it in a single script. Some advanced coders use tricks like caching or lower-timeframe requests to squeeze in a few more, but for reliability, sticking to 6–8 assets is recommended. If you need more, the common workaround is to create two separate indicators (e.g., one for stocks, one for crypto) and add both to the same chart.
Overall, this dashboard gives you a professional-grade multi-asset scanner that filters out low-energy noise and highlights real momentum opportunities across stocks and crypto — all in one glance. It's especially valuable for options traders who want to avoid theta decay on weak moves and only strike when the market has true fuel. By tweaking the per-symbol multipliers in the settings, you can perfectly adapt it to any timeframe or asset behavior, avoiding issues like the AVGO false bullish signal on higher timeframes.
Magical Thirteen Turns - The Greedy SnakeThe number 9 appears:
Meaning: Warning signal. The rise may encounter resistance and a cautious pullback is about to begin.
Operation: Consider reducing your holdings (selling a portion) to lock in profits and avoid experiencing wild fluctuations.
The number 13 appears:
Meaning: Strong sell signal. The upward momentum is likely to be exhausted, which is also known as "bull exhaustion".
Operation: It is recommended to liquidate your positions or significantly reduce them. Short sell (if you are trading contracts).
Gamma & Volatility Levels [Pro]General Purpose
This indicator analyzes volatility levels and expected price movements, combining gamma concepts (financial options) with volatility analysis to identify support and resistance zones.
Main Components
High Volatility Level (HVL): Calculates a volatility level based on the simple moving average (SMA) of the price plus one standard deviation. This level is represented by an orange line showing where volatility is concentrated.
Expected Movement (Movimiento Esperante): Uses the Average True Range (ATR) multiplied by an adjustable factor to project potential upward and downward movement ranges from the current price. It is drawn in green (upward) and red (downward).
Gamma Levels (Nivelas Gamma): Identifies two key levels: the call resistance (highest high of the last 50 periods) in blue, and the put support (lowest low) in purple. These are based on recent extreme prices.
Additional Information: The indicator calculates the percentage distance between the current price and the HVL, displaying it in a label.
Visual Elements
Colored lines on the chart for each level.
Labels with exact values next to each line.
A table in the upper right corner summarizing all calculated values.
Options to show or hide each element according to preference.
This is a useful tool for traders who work with options or seek to identify levels of extreme volatility and dynamic support/resistance zones.
Golden Volume Lines📌 Golden Volume — Lines (Golden Team)
Golden Volume — Lines is an advanced volume-based indicator that detects Ultra High Volume candles using a statistical percentile model, then automatically draws and tracks key price levels derived from those candles.
The indicator highlights where real market interest and liquidity appear and shows how price reacts when those levels are broken.
🔍 How It Works
Volume Measurement
Choose between:
Units (raw volume)
Money (Volume × Average Price)
Average price can be calculated using HL2 or OHLC4.
Percentile-Based Classification
Volume is classified into:
Medium
High
Ultra High Volume
Thresholds are calculated using a rolling percentile window.
Ultra Volume candles are colored orange.
Dynamic High & Low Levels
For every Ultra Volume candle:
A High and Low dotted line is drawn.
Lines extend to the right until price breaks them.
Smart Line Break Detection (Wick-Based)
A line is considered broken when price wicks through it.
When a break occurs:
🟧 Orange line → broken by an Ultra Volume candle
⚪ White line → broken by a normal candle
The line stops exactly at the breaking candle.
🔔 Alerts
Alert on Ultra High Volume candles
Alert when a High or Low line is broken
Separate alerts for:
Break by Ultra Volume candle
Break by Normal candle
🎯 Use Cases
Breakout & continuation confirmation
Liquidity sweep detection
Volume-validated support & resistance
Market reaction after extreme participation
⚙️ Key Inputs
Volume display mode (Units / Money)
Percentile thresholds
Lookback window size
Maximum number of active Ultra levels
Optional dynamic alerts
⚠️ Disclaimer
This indicator is a volume and market structure tool, not a standalone trading system.
Always use proper risk management and additional confirmation.
EMA Slope Angle# EMA Slope Angle Indicator
A professional, non-repainting overlay indicator that visualizes EMA slope strength as an angle in degrees, providing instant visual feedback through dynamic EMA coloring and comprehensive trend analysis.
## ORIGINALITY
This indicator is original in its approach to slope measurement:
- **Angle-based calculation**: Uses arctangent to calculate slope as an angle in degrees (not percentage), providing a more intuitive measure of trend strength
- **Dynamic visual feedback**: Combines real-time EMA line coloring with regime detection, creating a continuous visual representation of market conditions
- **Comprehensive analysis**: Integrates angle-based trend shift signals with optional statistical analysis in a single, cohesive tool
- **Non-repainting design**: All calculations use confirmed bars only, ensuring reliable, deterministic output
## HOW IT WORKS
The indicator calculates the EMA slope angle using trigonometric functions:
```
Angle = arctan((EMA_current - EMA_past) / lookback_bars) × 180/π
```
This provides an intuitive measure where:
- **Steep angles** = strong trends (visualized with saturated colors)
- **Shallow angles** = weak trends (visualized with lighter colors)
- **Near-zero angles** = flat/consolidation (visualized in gray)
The EMA line color dynamically reflects:
- **Direction**: Green shades for uptrends, red shades for downtrends
- **Strength**: Color intensity based on normalized angle (stronger slopes = more saturated colors)
- **Regime**: Gray for flat conditions when angle is below threshold
## KEY FEATURES
### Dynamic EMA Coloring
- EMA line color changes continuously based on slope strength
- Color intensity reflects trend strength (50-100% opacity range)
- Instant visual feedback without cluttering the chart
### Regime Detection
- Automatically classifies market conditions: **RISING**, **FALLING**, or **FLAT**
- Configurable angle thresholds for regime classification
- Real-time regime updates on confirmed bars only
### Trend-Shift Signals
- Detects transitions from FLAT to RISING/FALLING regimes
- Visual arrows on chart when significant trend shifts occur
- Prevents signal spam by only triggering from FLAT state
- Configurable trigger thresholds for signal sensitivity
### KPI Dashboard
- Real-time angle display (rounded to 1 decimal place)
- Current regime status with color coding
- Last signal tracking (UP/DOWN/NONE)
- Positioned in top-right corner for easy reference
### Advanced Angle Statistics (Optional)
- Detailed breakdown of angle distribution across 9 granular buckets:
- 0-0.2°, 0.2-0.5°, 0.5-1°, 1-1.5°, 1.5-2°, 2-3°, 3-5°, 5-10°, >10°
- Shows count and percentage for each bucket
- Automatically resets on symbol/timeframe changes
- Useful for analyzing historical slope patterns
## SETTINGS
### Main Settings
- **EMA Length**: Period for exponential moving average (default: 50)
- **Slope Lookback Bars**: Number of bars to compare for slope calculation (default: 5)
### Angle Settings
- **Flat Angle Threshold**: Maximum angle for FLAT regime classification (default: 2.0°)
- **Rising Angle Trigger**: Minimum angle to trigger RISING regime and UP signals (default: 1.0°)
- **Falling Angle Trigger**: Maximum angle to trigger FALLING regime and DOWN signals (default: -1.0°)
- **Max Angle for Color Saturation**: Maximum angle for full color intensity (default: 30.0°)
### Display Options
- **Uptrend Color**: Color for rising trends (default: dark green)
- **Downtrend Color**: Color for falling trends (default: dark red)
- **Flat Color**: Color for flat conditions (default: gray)
- **Show Trend-Shift Signals**: Toggle signal arrows on/off (default: true)
- **Show Angle Statistics**: Toggle statistics dashboard on/off (default: false)
## NON-REPAINTING GUARANTEE
- All calculations use confirmed bars only (`barstate.isconfirmed`)
- No future bar references
- No higher timeframe calls using `request.security()`
- Deterministic output - what you see is what you get
- Reliable for backtesting and live trading
## USE CASES
- **Trend Identification**: Instantly identify trend strength and direction at a glance
- **Reversal Detection**: Spot trend reversals early through regime changes
- **Trade Filtering**: Filter trades based on slope strength and regime
- **Consolidation Monitoring**: Identify flat market conditions for range trading
- **Pattern Analysis**: Study historical angle distributions to understand market behavior
- **Momentum Assessment**: Gauge trend momentum through visual color intensity
## LIMITATIONS
- Angle calculation depends on EMA length and lookback period settings
- Regime classification is based on configurable thresholds - adjust to match your trading style
- Signals only trigger when transitioning from FLAT state to prevent spam
- Statistics reset on symbol/timeframe changes (by design)
- Color intensity is normalized to max angle setting - adjust for your market's typical ranges
## TECHNICAL NOTES
- Uses Pine Script v6
- Overlay indicator (plots on price chart)
- No external dependencies
- Compatible with all TradingView chart types
- Works on all timeframes and symbols
## DISCLAIMER
This indicator is designed for visual trend analysis and educational purposes. Always combine with other technical analysis tools, fundamental analysis, and proper risk management strategies. Past performance does not guarantee future results. Trading involves risk of loss.
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**Perfect for**: Swing traders, day traders, trend followers, and market analysts seeking intuitive trend strength visualization.
Al Brooks - Bar CountIndicator Purpose:
This indicator displays bar counts on the chart to help traders identify important time nodes and cycle transitions
Features smart session filtering with automatic futures/stock detection and appropriate trading session counting
Core Features:
Smart asset detection: Auto-detect futures and stocks
Session filter toggle: Choose all-day or session-specific counting
Auto timezone handling: Chicago time for futures, NY time for stocks
Flexible display control: Customizable display frequency and label size
Session Settings:
8:30-15:15 (CT) / Futures mode: Chicago time 8:30-15:15 (CT)
9:30-16:00 (ET) / Stock mode: New York time 9:30-16:00 (ET)
All-day mode: Count from first bar of the day
Timeframe Correspondence:
Multiples of 3: Correspond to 15-minute chart update cycles
Multiples of 12: Correspond to 1-hour chart update cycles
18: Key nodes, important time turning points
Index Construction Tool🙏🏻 The most natural mathematical way to construct an index || portfolio, based on contraharmonic mean || contraharmonic weighting. If you currently traded assets do not satisfy you, why not make your own ones?
Contraharmonic mean is literally a weighted mean where each value is weighted by itself.
...
Now let me explain to you why contraharmonic weighting is really so fundamental in two ways: observation how the industry (prolly unknowably) converged to this method, and the real mathematical explanation why things are this way.
How it works in the industry.
In indexes like TVC:SPX or TVC:DJI the individual components (stocks) are weighted by market capitalization. This market cap is made of two components: number of shares outstanding and the actual price of the stock. While the number of shares holds the same over really long periods of time and changes rarely by corporate actions , the prices change all the time, so market cap is in fact almost purely based on prices itself. So when they weight index legs by market cap, it really means they weight it by stock prices. That’s the observation: even tho I never dem saying they do contraharmonic weighting, that’s what happens in reality.
Natural explanation
Now the main part: how the universe works. If you build a logical sequence of how information ‘gradually’ combines, you have this:
Suppose you have the one last datapoint of each of 4 different assets;
The next logical step is to combine these datapoints somehow in pairs. Pairs are created only as ratios , this reveals relationships between components, this is the only step where these fundamental operations are meaningful, they lose meaning with 3+ components. This way we will have 16 pairs: 4 of them would be 1s, 6 real ratios, and 6 more inverted ratios of these;
Then the next logical step is to combine all the pairs (not the initial single assets) all together. Naturally this is done via matrices, by constructing a 4x4 design matrix where each cell will be one of these 16 pairs. That matrix will have ones in the main diagonal (because these would be smth like ES/ES, NQ/NQ etc). Other cells will be actual ratios, like ES/NQ, RTY/YM etc;
Then the native way to compress and summarize all this structure is to do eigendecomposition . The only eigenvector that would be meaningful in this case is the principal eigenvector, and its loadings would be what we were hunting for. We can multiply each asset datapoint by corresponding loading, sum them up and have one single index value, what we were aiming for;
Now the main catch: turns out using these principal eigenvector loadings mathematically is Exactly the same as simply calculating contraharmonic weights of those 4 initial assets. We’re done here.
For the sceptics, no other way of constructing the design matrix other than with ratios would result in another type of a defined mean. Filling that design matrix with ratios Is the only way to obtain a meaningful defined mean, that would also work with negative numbers. I’m skipping a couple of details there tbh, but they don’t really matter (we don’t need log-space, and anyways the idea holds even then). But the core idea is this: only contraharmonic mean emerges there, no other mean ever does.
Finally, how to use the thing:
Good news we don't use contraharmonic mean itself because we need an internals of it: actual weights of components that make this contraharmonic mean, (so we can follow it with our position sizes). This actually allows us to also use these weights but not for addition, but for subtraction. So, the script has 2 modes (examples would follow):
Addition: the main one, allows you to make indexes, portfolios, baskets, groups, whatever you call it. The script will simply sum the weighted legs;
Subtraction: allows you to make spreads, residual spreads etc. Important: the script will subtract all the symbols From the first one. So if the first we have 3 symbols: YM, ES, RTY, the script will do YM - ES - RTY, weights would be applied to each.
At the top tight corner of the script you will see a lil table with symbols and corresponding weights you wanna trade: these are ‘already’ adjusted for point value of each leg, you don’t need to do anything, only scale them all together to meet your risk profile.
Symbols have to be added the way the default ones are added, one line : one symbol.
Pls explore the script’s Style setting:
You can pick a visualization method you like ! including overlays on the main chart pane !
Script also outputs inferred volume delta, inferred volume and inferred tick count calculated with the same method. You can use them in further calculations.
...
Examples of how you can use it
^^ Purple dotted line: overlay from ICT script, turned on in Style settings, the contraharmonic mean itself calculated from the same assets that are on the chart: CME_MINI:RTY1! , CME_MINI:ES1! , CME_MINI:NQ1! , CBOT_MINI:YM1!
^^ precious metals residual spread ( COMEX:GC1! COMEX:SI1! NYMEX:PL1! )
^^ CBOT:ZC1! vs CBOT:ZW1! grain spread
^^ BDI (Bid Dope Index), constructed from: NYSE:MO , NYSE:TPB , NYSE:DGX , NASDAQ:JAZZ , NYSE:IIPR , NASDAQ:CRON , OTC:CURLF , OTC:TCNNF
^^ NYMEX:CL1! & ICEEUR:BRN1! basket
^^ resulting index price, inferred volume delta, inferred volume and inferred tick count of CME_MINI:NQ1! vs CME_MINI:ES1! spread
...
Synthetic assets is the whole new Universe you can jump into and never look back, if this is your way
...
∞
Vertical Time LinesVertical Time Lines is an indicator that draws vertical lines at specific times of each day on the price chart.
⚙️ Main Features
Up to 5 independent time lines
Precise hour and minute editing (HH:MM)
Individual enable/disable option per line
Customizable line color and style
Works on any asset and any timeframe
📝 Note
Due to Pine Script limitations, the lines are drawn using UTC time, not the time zone configured on the chart.
Lines are generated only when a candle exists exactly at the configured minute. If candles for the specified hours and minutes are not visible on the chart, the lines will not be displayed.
RO H1 Signal CandleMarks specific H1 signal candles based on Bucharest (RO) time.
Designed for clean backtesting and time-based analysis.
Displays a small marker on selected hourly candles only.
MenthorQ Levels ConversionLevels Conversion helps traders accurately overlay price levels from spot/index ETFs and indices (like SPX, SPY, QQQ, NDX) onto futures charts (like ES, NQ, etc.).
Because futures and spot/index prices don’t trade at the same price, your levels will be misaligned if you plot them directly. Futures typically trade at a spread or ratio versus their related index/ETF. This indicator solves that by calculating the conversion ratio automatically, so your levels stay aligned on the futures chart.
How it works
This script calculates the ratio between Asset A and Asset B and applies it to convert levels from one instrument to the other (for example, SPX → ES, QQQ → NQ).
Ratio options (3 modes)
You can choose one of three ratio sources:
✅ T1 Ratio (Morning Snapshot)
Select a specific time to “lock” the ratio.
Default: 10:00 AM ET (morning session snapshot)
✅ T2 Ratio (Afternoon Snapshot)
Select a second time to “lock” the ratio.
Default: 3:30 PM ET (afternoon snapshot)
✅ Last Price Ratio (Live)
Uses the last traded price of both assets to compute the ratio.
Note: To refresh the “Last Price” baseline, simply remove and re-add the indicator.
Learn more about Levels Conversions: menthorq.com
Common levels conversions
Some popular use-cases include:
- SPX Gamma Levels → ES
- SPY Gamma Levels → ES
- QQQ Gamma Levels → NQ
- NDX Gamma Levels → NQ
- SPX Intraday Gamma Levels → ES
- QQQ Intraday Gamma Levels → NQ
- SPX Swing Trading Levels → ES
- QQQ Swing Trading Levels → NQ
- GLD Levels → GC
- DIA Levels → YM
- USO Levels → CL
- NVDA / MAG7 Levels → QQQ
PatternTransitionTablesPatternTransitionTables Library
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- 1. INTRODUCTION --------- 🌸
💮 Overview
This library provides precomputed state transition tables to enable ultra-efficient, O(1) computation of Ordinal Patterns. It is designed specifically to support high-performance indicators calculating Permutation Entropy and related complexity measures.
💮 The Problem & Solution
Calculating Permutation Entropy, as introduced by Bandt and Pompe (2002), typically requires computing ordinal patterns within a sliding window at every time step. The standard successive-pattern method (Equations 2+3 in the paper) requires ≤ 4d-1 operations per update.
Unakafova and Keller (2013) demonstrated that successive ordinal patterns "overlap" significantly. By knowing the current pattern index and the relative rank (position l) of just the single new data point, the next pattern index can be determined via a precomputed look-up table. Computing l still requires d comparisons, but the table lookup itself is O(1), eliminating the need for d multiplications and d additions. This reduces total operations from ≤ 4d-1 to ≤ 2d per update (Table 4). This library contains these precomputed tables for orders d = 2 through d = 5.
🌸 --------- 2. THEORETICAL BACKGROUND --------- 🌸
💮 Permutation Entropy
Bandt, C., & Pompe, B. (2002). Permutation entropy: A natural complexity measure for time series.
doi.org
This concept quantifies the complexity of a system by comparing the order of neighbouring values rather than their magnitudes. It is robust against noise and non-linear distortions, making it ideal for financial time series analysis.
💮 Efficient Computation
Unakafova, V. A., & Keller, K. (2013). Efficiently Measuring Complexity on the Basis of Real-World Data.
doi.org
This library implements the transition function φ_d(n, l) described in Equation 5 of the paper. It maps a current pattern index (n) and the position of the new value (l) to the successor pattern, reducing the complexity of updates to constant time O(1).
🌸 --------- 3. LIBRARY FUNCTIONALITY --------- 🌸
💮 Data Structure
The library stores transition matrices as flattened 1D integer arrays. These tables are mathematically rigorous representations of the factorial number system used to enumerate permutations.
💮 Core Function: get_successor()
This is the primary interface for the library for direct pattern updates.
• Input: The current pattern index and the rank position of the incoming price data.
• Process: Routes the request to the specific transition table for the chosen order (d=2 to d=5).
• Output: The integer index of the next ordinal pattern.
💮 Table Access: get_table()
This function returns the entire flattened transition table for a specified dimension. This enables local caching of the table (e.g. in an indicator's init() method), avoiding the overhead of repeated library calls during the calculation loop.
💮 Supported Orders & Terminology
The parameter d is the order of ordinal patterns (following Bandt & Pompe 2002). Each pattern of order d contains (d+1) data points, yielding (d+1)! unique patterns:
• d=2: 3 points → 6 unique patterns, 3 successor positions
• d=3: 4 points → 24 unique patterns, 4 successor positions
• d=4: 5 points → 120 unique patterns, 5 successor positions
• d=5: 6 points → 720 unique patterns, 6 successor positions
Note: d=6 is not implemented. The resulting code size (approx. 191k tokens) exceeds the Pine Script limit of 100k tokens (as of 2025-12).
Shiori TFGI Lite Technical Fear and Greed Index (Open Source)Shiori’s TFGI Lite
Technical Fear & Greed Index (Open Source)
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English — Official Description
Shiori’s TFGI Lite is an open-source Technical Fear & Greed Index designed to help traders and investors understand market emotion, not predict price.
Instead of generating buy or sell signals, this indicator focuses on answering a calmer, more important question:
> Is the market emotionally stretched away from its own historical balance?
TFGI Lite combines three well-known technical dimensions — volatility, price deviation, and momentum — and normalizes them into a single, intuitive 0–100 sentiment scale.
What This Indicator Is
* A market context tool, not a trading signal
* A way to observe emotional extremes and misalignment
* Designed for any asset, any timeframe
* Fully open source, transparent and adjustable
Core Components
* Fear Factor: Short-term vs long-term ATR ratio with logarithmic compression
* Greed Factor: Price Z-score with tanh-based normalization
* Momentum Factor: Classic RSI as emotional momentum
These factors are blended and gently smoothed to form the current sentiment level.
Historical Baseline & Deviation
TFGI Lite introduces a historical baseline concept:
* The baseline represents the market’s own emotional equilibrium
* Deviation measures how far current sentiment has drifted from that equilibrium
This allows the indicator to highlight conditions such as:
* 🔥 Overheated: High sentiment + strong positive deviation
* 💎 Undervalued: Low sentiment + strong negative deviation
* ⚠️ Misaligned: Emotionally extreme, but inconsistent with historical behavior
How to Use (Lite Philosophy)
* Use TFGI Lite as a background compass, not a trigger
* Combine it with price structure, risk management, and your own strategy
* Extreme readings suggest emotional tension, not immediate reversal
> Think of TFGI Lite as market weather — it tells you the climate, not when to open or close the door.
About Parameters & Customization
All parameters in TFGI Lite are fully adjustable. Markets have different personalities — volatility, sentiment range, and emotional extremes vary by asset and timeframe.
You are encouraged to:
* Adjust fear/greed thresholds based on the asset you trade
* Tune smoothing and baseline lengths to match your timeframe
* Treat sentiment levels as relative, not universal absolutes
There is no single “correct” setting — TFGI Lite is designed to adapt to your market, not force the market into a fixed model.
Important Notes
* This is a technical sentiment indicator, not financial advice
* No future performance is implied
* Designed to reduce emotional decision-making, not replace it
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🇹🇼 繁體中文 — 指標說明
Shiori’s TFGI Lite（技術型恐懼與貪婪指數） 是一款開源的市場情緒指標，目的不是預測價格，而是幫助你理解市場當下的「情緒狀態」。
與其問「現在該不該買或賣」，TFGI Lite 更關心的是：
> 市場情緒是否已經偏離了它自己的歷史平衡？
本指標整合三個常見但關鍵的技術面向，並統一轉換為 0–100 的情緒刻度，讓市場狀態一眼可讀。
這個指標是什麼
* 市場情緒與狀態觀察工具（非買賣訊號）
* 用來辨識情緒極端與錯位狀態
* 適用於任何商品與任何週期
* 完全開源，可學習、可調整
核心構成
* 恐懼因子：短期 / 長期 ATR 比例（對數壓縮）
* 貪婪因子：價格 Z-Score（tanh 正規化）
* 動能因子：RSI 作為情緒動量
歷史基準與偏離
TFGI Lite 引入「歷史情緒基準」的概念：
* 基準代表市場長期的情緒平衡
* 偏離值顯示當前情緒與自身歷史的距離
因此可以辨識：
* 🔥 過熱（高情緒 + 正向偏離）
* 💎 低估（低情緒 + 負向偏離）
* ⚠️ 錯位（情緒極端，但不符合歷史行為）
使用建議（Lite 精神）
* 將 TFGI Lite 作為「背景雷達」，而非進出場依據
* 搭配價格結構、風險控管與個人策略
* 情緒極端不等於立刻反轉
> 你可以把它想像成市場的天氣預報，而不是交易指令。
參數調整與個人化說明
本指標中的所有參數皆可調整。不同市場、不同商品，其波動特性與情緒區間並不相同。
建議你：
* 依標的特性自行調整恐懼 / 貪婪門檻
* 依交易週期調整平滑與基準長度
* 將情緒數值視為「相對狀態」，而非固定答案
TFGI Lite 的設計初衷，是讓你定義市場，而不是被單一參數綁住。
溫馨提示
如果你在調整指標參數時遇到不熟悉的項目，請點擊參數旁邊的 「!」圖示，每個設定都有清楚的說明。
本指標設計為可慢慢探索，請依自己的節奏理解市場狀態。
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🇯🇵 日本語 — インジケーター説明
Shiori’s TFGI Lite は、価格を予測するための指標ではなく、
市場の「感情状態」を可視化するためのオープンソース指標です。
この指標が問いかけるのは、
> 現在の市場感情は、過去のバランスからどれだけ乖離しているのか？
という一点です。
特徴
* 売買シグナルではありません
* 市場心理の極端さやズレを観察するためのツールです
* すべての銘柄・時間軸に対応
* 学習・調整可能なオープンソース
構成要素
* 恐怖要素：ATR 比率（対数圧縮）
* 強欲要素：価格 Z スコア（tanh 正規化）
* モメンタム：RSI
ベースラインと乖離
市場自身の感情的な基準点と、
現在の感情との距離を測定します。
過熱・割安・感情のズレを視覚的に把握できます。
パラメータ調整について
TFGI Lite のすべてのパラメータは調整可能です。市場ごとにボラティリティや感情の振れ幅は異なります。
* 恐怖・強欲の閾値は銘柄に応じて調整してください
* 時間軸に合わせて平滑化やベースライン期間を変更できます
* 数値は絶対値ではなく、相対的な感情状態として捉えてください
この指標は、市場に合わせて柔軟に使うことを前提に設計されています。
フレンドリーヒント
入力項目で分からない設定がある場合は、横に表示されている 「!」アイコン をクリックしてください。各パラメータには分かりやすい説明が用意されています。
このインジケーターは、落ち着いて市場の状態を理解するためのものです。
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🇰🇷 한국어 — 지표 설명
Shiori’s TFGI Lite는 매수·매도 신호를 제공하는 지표가 아니라,
시장 감정의 상태를 이해하기 위한 기술적 심리 지표입니다.
이 지표의 핵심 질문은 다음과 같습니다.
> 현재 시장 감정은 과거의 균형 상태에서 얼마나 벗어나 있는가?
특징
* 거래 신호 아님
* 시장 심리의 과열·저평가·불일치를 관찰
* 모든 자산, 모든 타임프레임 지원
* 오픈소스 기반
구성 요소
* 공포 요인: ATR 비율 (로그 압축)
* 탐욕 요인: Z-Score (tanh 정규화)
* 모멘텀: RSI
활용 방법
TFGI Lite는 배경 지표로 사용하세요.
가격 구조와 리스크 관리와 함께 사용할 때 가장 효과적입니다.
파라미터 조정 안내
TFGI Lite의 모든 설정 값은 사용자가 직접 조정할 수 있습니다. 자산마다 변동성과 감정 범위는 서로 다릅니다.
* 공포 / 탐욕 기준값은 종목 특성에 맞게 조정하세요
* 타임프레임에 따라 스무딩 및 기준 기간을 변경할 수 있습니다
* 감정 수치는 절대적인 값이 아닌 상대적 상태로 해석하세요
이 지표는 하나의 정답을 강요하지 않고, 시장에 맞춰 적응하도록 설계되었습니다.
친절한 안내
설정 값이 익숙하지 않다면, 항목 옆에 있는 "!" 아이콘을 클릭해 보세요. 각 입력값마다 설명이 제공됩니다.
이 지표는 천천히 시장의 맥락을 이해하도록 설계되었습니다.
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Educational purpose only. Not financial advice.
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#FearAndGreed #MarketSentiment #TradingPsychology #TechnicalAnalysis #OpenSourceIndicator #Volatility #RSI #ATR #ZScore #MultiAsset #TradingView #Shiori
BTC Regime Oscillator (MC + Spread) [1D]ONLY SUPPOSED TO BE USED FOR BTC PERPS, AND SPOT LEVERAGING:
This is a risk oscillator that measures whether Bitcoin’s price is supported by real capital or is running ahead of it, and converts that into a simple risk-regime oscillator.
It's built with market cap, and FDV, and Z-scores compressed to -100 <-> 100
I created this indicator because I got tired of FOMO Twitter and Wall Street games.
DO NOT USE THIS AS A BEGIN-ALL-AND-END-ALL. YOU NEED TO USE THIS AS A CONFIRMATION INDICATOR, AND ON HTF ONLY (1D>) IF YOU USE THIS ON LOWER TIMEFRAMES, YOU ARE FEEDING YOUR MONEY TO A LOW-LIFE DING BAT ON WALL STREET. HERE IS HOW IT WORKS:
This indicator is Split up by
A) Market Cap
--> Represents real money in BTC
--> Ownership capital
--> If MC is rising, money is entering BTC
B) FDV (Fully Diluted Valuation)
--> For BTC: price(21M) (21,000,000)
--> Represents the theoretical valuation
--> Since BTC really has a fixed cap, FDV mostly tracks the price
C) Oscillators
Both MC and FDV are:
--> Logged (to handle scale)
--> Normalized (Z-score)
--> Compressed to -100 <-> 100
HERE ARE THREE THINGS YOU ARE GOING TO SEE ON THE CHART
A) The market cap oscillator (MC OSC)
--> Normalized trend of real capital
RISING: Indicates capital inflow
FALLING: Indicates capital outflow
B) FDV Oscillator
--> Normalized trend of valuation pressure
ABOVE MC: Price is ahead of capital
BELOW MC: Capital is keeping up
!!!! FDV IS CONTEXT NOT SIGNALS !!!!
C) Spread = (FDV - MC)
--> The difference between valuation and capital
(THIS IS THE CORE SIGNAL)
NEGATIVE: Capital is gonna lead price
NEAR 0: Balanced
POSITIVE: Price leads capital
(THIS MEANS STRESS FOR BTC, NOT DILLUTION!)
WHAT DOES -60, 0, 60 MEAN?:
--> These are meant to serve as risk zones, not buy/sell dynamics; this is not the same as an RSI oscillator.
A) 0 level
--> Price and capital are balanced
--> No structural stress
(TRADE WITH NORMAL POSITION SIZE, AND NORMAL EXPECTATIONS)
B) Below -60 (Supportive/Compressed)
--> BTC is relatively cheap to recent history
--> Capital supports price well
(ALWAYS REMEMBER TO CONFIRM THIS WITH WHAT THE CHART IS TELLING YOU)
--> Press trends
--> Use higher ATRs
--> Pullbacks are better here
C) Above 60 (Overextension, or fragile)
--> BTC is expensive relative to recent history
--> Price is ahead of capital
(ALWAYS REMEMBER TO CONFIRM THIS WITH WHAT THE CHART IS TELLING YOU)
--> Reduce leverage, use smaller ATR
--> Use lower ATRs, TP faster
--> Do not chase breakouts
--> Expect volatility and whipsaws
"Can I press trades right now? Or do I need to hog my capital?"
CONDITIONS:
Spread Less than 0 and below -60 = Press trades
Spread near 0 = Normal trading conditions
Spread is Greater than 0 or above 60+ = Capital protection
FF calculation Saptarshi ChatterjeeForward factor (in options contexts) measures implied volatility (IV) for a future period between two expirations, like from 30 DTE (days to expiry) front-month to 60 DTE back-month options.
This indicator calculates the FORWARD FACTOR(FF) using 2 IVs of 2 DTEs.
+ve value means front DTE is rich in premium and back expiry is cheap.
-ve value means front DTE IV is cheap and 2nd DTE is expensive
we can use this term structure disbalance to trade calendar spreads with edge.
Mutanabby_AI | ONEUSDT_MR1
ONEUSDT Mean-Reversion Strategy | 74.68% Win Rate | 417% Net Profit
This is a long-only mean-reversion strategy designed specifically for ONEUSDT on the 1-hour timeframe. The core logic identifies oversold conditions following sharp declines and enters positions when selling pressure exhausts, capturing the subsequent recovery bounce.
Backtested Period: June 2019 – December 2025 (~6 years)
Performance Summary
| Metric | Value |
|--------|-------|
| Net Profit | +417.68% |
| Win Rate | 74.68% |
| Profit Factor | 4.019 |
| Total Trades | 237 |
| Sharpe Ratio | 0.364 |
| Sortino Ratio | 1.917 |
| Max Drawdown | 51.08% |
| Avg Win | +3.14% |
| Avg Loss | -2.30% |
| Buy & Hold Return | -80.44% |
Strategy Logic :
Entry Conditions (Long Only):
The strategy seeks confluence of three conditions that identify exhausted selling:
1. Prior Move Filter:*The price change from 5 bars ago to 3 bars ago must be ≥ -7% (ensures we're not entering during freefall)
2. Current Move Filter: The price change over the last 2 bars must be ≤ 0% (confirms momentum is stalling or reversing)
3. Three-Bar Decline: The price change from 5 bars ago to 3 bars ago must be ≤ -5% (confirms a significant recent drop occurred)
When all three conditions align, the strategy identifies a potential reversal point where sellers are exhausted.
Exit Conditions:
- Primary Exit: Close above the previous bar's high while the open of the previous bar is at or below the close from 9 bars ago (profit-taking on strength)
- Trailing Stop: 11x ATR trailing stop that locks in profits as price rises
Risk Management
- Position Sizing:Fixed position based on account equity divided by entry price
- Trailing Stop:11× ATR (14-period) provides wide enough room for crypto volatility while protecting gains
- Pyramiding:Up to 4 orders allowed (can scale into winning positions)
- **Commission:** 0.1% per trade (realistic exchange fees included)
Important Disclaimers
⚠️ This is NOT financial advice.
- Past performance does not guarantee future results
- Backtest results may contain look-ahead bias or curve-fitting
- Real trading involves slippage, liquidity issues, and execution delays
- This strategy is optimized for ONEUSDT specifically — results may differ on other pairs
- Always test before risking real capital
Recommended Usage
- Timeframe:*1H (as designed)
- Pair: ONEUSDT (Binance)
- Account Size: Ensure sufficient capital to survive max drawdown
Source Code
Feedback Welcome
I'm sharing this strategy freely for educational purposes. Please:
- Drop a comment with your backtesting results any you analysis
- Share any modifications that improve performance
- Let me know if you spot any issues in the logic
Happy trading
As a quant trader, do you think this strategy will survive in live trading?
Yes or No? And why?
I want to hear from you guys
LuxyEnergyIndexThe Luxy Energy Index (LEI) library provides functions to measure price movement exhaustion by analyzing three dimensions: Extension (distance from fair value), Velocity (speed of movement), and Volume (confirmation level).
LEI answers a different question than traditional momentum indicators: instead of "how far has price gone?" (like RSI), LEI asks "how tired is this move?"
This library allows Pine Script developers to integrate LEI calculations into their own indicators and strategies.
How to Import
//@version=6
indicator("My Indicator")
import OrenLuxy/LuxyEnergyIndex/1 as LEI
Main Functions
`lei(src)` → float
Returns the LEI value on a 0-100 scale.
src (optional): Price source, default is `close`
Returns : LEI value (0-100) or `na` if insufficient data (first 50 bars)
leiValue = LEI.lei()
leiValue = LEI.lei(hlc3) // custom source
`leiDetailed(src)` → tuple
Returns LEI with all component values for detailed analysis.
= LEI.leiDetailed()
Returns:
`lei` - Final LEI value (0-100)
`extension` - Distance from VWAP in ATR units
`velocity` - 5-bar price change in ATR units
`volumeZ` - Volume Z-Score
`volumeModifier` - Applied modifier (1.0 = neutral)
`vwap` - VWAP value used
Component Functions
| Function | Description | Returns |
|-----------------------------------|---------------------------------|---------------|
| `calcExtension(src, vwap)` | Distance from VWAP / ATR | float |
| `calcVelocity(src)` | 5-bar price change / ATR | float |
| `calcVolumeZ()` | Volume Z-Score | float |
| `calcVolumeModifier(volZ)` | Volume modifier | float (≥1.0) |
| `getVWAP()` | Auto-detects asset type | float |
Signal Functions
| Function | Description | Returns |
|---------------------------------------------|----------------------------------|-----------|
| `isExhausted(lei, threshold)` | LEI ≥ threshold (default 70) | bool |
| `isSafe(lei, threshold)` | LEI ≤ threshold (default 30) | bool |
| `crossedExhaustion(lei, threshold)` | Crossed into exhaustion | bool |
| `crossedSafe(lei, threshold)` | Crossed into safe zone | bool |
Utility Functions
| Function | Description | Returns |
|----------------------------|-------------------------|-----------|
| `getZone(lei)` | Zone name | string |
| `getColor(lei)` | Recommended color | color |
| `hasEnoughHistory()` | Data check | bool |
| `minBarsRequired()` | Required bars | int (50) |
| `version()` | Library version | string |
Interpretation Guide
| LEI Range | Zone | Meaning |
|-------------|--------------|--------------------------------------------------|
| 0-30 | Safe | Low exhaustion, move may continue |
| 30-50 | Caution | Moderate exhaustion |
| 50-70 | Warning | Elevated exhaustion |
| 70-100 | Exhaustion | High exhaustion, increased reversal risk |
Example: Basic Usage
//@version=6
indicator("LEI Example", overlay=false)
import OrenLuxy/LuxyEnergyIndex/1 as LEI
// Get LEI value
leiValue = LEI.lei()
// Plot with dynamic color
plot(leiValue, "LEI", LEI.getColor(leiValue), 2)
// Reference lines
hline(70, "High", color.red)
hline(30, "Low", color.green)
// Alert on exhaustion
if LEI.crossedExhaustion(leiValue) and barstate.isconfirmed
alert("LEI crossed into exhaustion zone")
Technical Details
Fixed Parameters (by design):
Velocity Period: 5 bars
Volume Period: 20 bars
Z-Score Period: 50 bars
ATR Period: 14
Extension/Velocity Weights: 50/50
Asset Support:
Stocks/Forex: Uses Session VWAP (daily reset)
Crypto: Uses Rolling VWAP (50-bar window) - auto-detected
Edge Cases:
Returns `na` until 50 bars of history
Zero volume: Volume modifier defaults to 1.0 (neutral)
Credits and Acknowledgments
This library builds upon established technical analysis concepts:
VWAP - Industry standard volume-weighted price measure
ATR by J. Welles Wilder Jr. (1978) - Volatility normalization
Z-Score - Statistical normalization method
Volume analysis principles from Volume Spread Analysis (VSA) methodology
Disclaimer
This library is provided for **educational and informational purposes only**. It does not constitute financial advice. Past performance does not guarantee future results. The exhaustion readings are probabilistic indicators, not guarantees of price reversal. Always conduct your own research and use proper risk management when trading.
Pardos Info DashboardThis indicator presents basic data in a concentrated form
Additions to the indicator are welcome by email to gshayp@gmail.com
Trinity ATR Real Move DetectorTrinity ATR Real Move Detector
This ATR Energy Table indicator is one of the simplest yet most powerful filters you can have on a chart when trading short-dated or 0DTE options or swing trades on any timeframe from 1-minute up to 4-hour. Its entire job is to answer the single most important question in intraday and swing trading: “Does the underlying actually have enough short-term explosive energy right now to make a directional position worth the theta and the spread, or is this just pretty candles that will die in ten minutes?”
Most losing 0DTE and short-dated option trades happen because people buy or sell direction on a “nice-looking” breakout or pullback while the underlying is actually in low-energy grind mode. The premium decays faster than the move develops, and you lose even when you’re “right” on direction. This little table stops that from ever happening again.
Here’s what it does in plain English:
Every bar it measures two things:
- The current ATR on whatever timeframe you are using (1 min, 3 min, 5 min, 10 min, etc.). This tells you how big the average true range of the last 14 bars has been — in other words, how violently the stock or index is actually moving right now.
- The daily ATR (14-period on the daily chart). This is your benchmark for “normal” daily movement over the last two–three weeks.
It then multiplies the daily ATR by a small number (the multiplier you set) and compares the two. If the short-term ATR is bigger than that percentage of the daily ATR, the table turns bright green and says “ENOUGH ENERGY”. If not, it stays red and says “NOT ENOUGH”.
Why this works so well:
- Real explosive moves that carry for 0DTE and 1–3 DTE options almost always show a short-term ATR spike well above the recent daily average. Quiet grind moves never do.
- The comparison is completely adaptive — on a high-vol day the threshold automatically rises, on a low-vol day it automatically drops. You never have to guess if “2 points on SPY is big today”.
- It removes emotion completely. You simply wait for green before you even think about clicking buy or sell on an option.
Key settings and what to do with them:
- Energy Multiplier — this is the only number you ever touch. It is expressed as a decimal (0.15 = 15 % of the daily ATR). Lower = more signals, higher = stricter and higher win rate. The tooltip gives you the exact sweet-spot numbers for every popular timeframe (0.09 for 1-minute scalping, 0.13 for 3-minute, 0.14–0.16 for 5-minute, 0.15–0.19 for 10-minute, etc.). Just pick your timeframe once and type the number — done forever.
- ATR Length — leave it at 14. That’s the standard and works perfectly.
- Table Position — move the table to wherever you want on the chart (top-right, bottom-right, bottom-left, top-left).
- Table Size — make the text Tiny, Small, Normal or Large depending on how much screen space you have.
How this helps you make money and stop losing it:
- On most days you will see red 80–90 % of the time — that’s good! It is forcing you to sit on your hands instead of overtrading low-energy chop that eats premium.
- When it finally flips green you know institutions are actually pushing size right now — follow-through probability jumps from ~40 % to 65–75 % depending on the stock and timeframe.
- You stop buying calls on every green candle and puts on every red candle. You only strike when the market is genuinely “awake”.
- Over a week you take dramatically fewer trades, but your win rate and average winner size go way up — which is exactly how consistent intraday option profits are made.
In short, this tiny table is the closest thing to an “edge on/off switch” that exists for short-dated options. Red = preserve capital and go do something else. Green = pull the trigger with confidence. Use it religiously and you’ll immediately feel the difference in your P&L.
