[uPaSKaL] Adaptive Swing StructureOverview :
Adaptive Swing Structure identifies and labels swing structure using HH / HL / LH / LL and can optionally draw wave connectors between successive swing points.
The goal is to provide a clean, practical view of market structure that remains readable across different market conditions.
Instead of relying only on a classic fixed-window pivot scan (left/right bars), this indicator uses an adaptive swing-detection approach designed to better match how traders visually interpret legs and structure.
Why this approach (vs. a simple pivot scan)?
Classic pivot scans (e.g., “pivot high/low with left/right bars”) are simple and widely used, but they often have practical limitations:
They depend heavily on a fixed window size (too sensitive in chop, too slow in trends)
They can mark pivots that are locally valid but not always representative of the broader leg
They may produce frequent structure changes during ranges, reducing readability
What you get with this indicator
A more stable swing structure view that adapts to price movement
Cleaner HH / HL / LH / LL labeling for context and decision-making
Optional wave connectors to visually follow the swing path
Visual comparison:
The screenshots below illustrate the difference in how structure can appear when using a classic pivot scan versus Adaptive Swing Structure.
Classic Pivot Points (High / Low):
Adaptive Swing Structure (This Indicator):
How to read the labels
This indicator labels swing structure using the standard notation:
HH = Higher High
HL = Higher Low
LH = Lower High
LL = Lower Low
How to interpret Wave Lines
When enabled, wave lines connect successive swing points to help you visually track the current swing path and structural transitions.
Inputs guide
Tracer Line Len
Main sensitivity control. Adjust this to fit the instrument and timeframe.
Higher values → fewer swing points, smoother structure (macro view)
Lower values → more swing points, more detail (micro view)
Show Wick (High / Low) Line
Shows the wick-based tracer (visual reference).
More sensitive to extremes and wick behavior
Useful when wicks matter (liquidity spikes / stop-runs)
Show Body (Open / Close) Line
Shows the body-based tracer (visual reference).
Filters wick noise and often looks smoother
Useful when you prefer structure based on candle bodies
Show Slope Flip Labels
Shows small markers that highlight swing turning moments (study/verification).
Helpful for understanding where structure updates
Optional and can be disabled for a cleaner chart
Wave Labels (WICK)
Shows HH/HL/LH/LL labels using wick-based swings.
More responsive to wick extremes
Wave Lines (WICK)
Connects wick-based swing points with wave lines.
Improves visual continuity of swings
Wave Labels (BODY)
Shows HH/HL/LH/LL labels using body-based swings.
Typically smoother and less sensitive to wick spikes
Wave Lines (BODY)
Connects body-based swing points with wave lines.
Cleaner wave path for body-based structure
Max Wave Labels Kept (per Wick / Body)
Limits the number of labels kept on the chart (older ones are removed first).
Reduces clutter
Helps maintain performance
Max Wave Lines Kept (per Wick / Body)
Limits the number of wave lines kept on the chart (older ones are removed first).
Keeps the chart readable
Helps maintain performance
History Window (map size / scan clamp)
Performance / stability control for how much recent history is considered.
Higher values → more history considered, higher CPU usage
Lower values → lighter execution, structure limited to more recent swings
Usage / Tuning
1) Find “your number” for each market
There is no universal best setting. The optimal Tracer Line Len depends on:
Instrument volatility
Your trading timeframe
Whether you want micro structure or macro structure
2) Build a simple baseline
Choose your chart timeframe (e.g., 4H).
Start with a moderate Len (e.g., 10–30).
Increase or decrease Len until the swing structure matches how you would manually map it.
3) Practical “timeframe scaling” intuition
You can use Len to “zoom out” or “zoom in” structure without changing your chart timeframe.
Example on 4H :
If Len = 20 produces the swing structure you want for 4H decisions, keep it as your baseline.
If you increase it to something like Len = 120 , the structure becomes much smoother and swing points appear less frequently.
This means:
4H with a smaller Len → focuses on 4H-level swings (more detail).
4H with a much larger Len → filters many local swings and highlights broader legs (more “higher-timeframe-like” context).
This is not a strict mathematical replacement for switching timeframes, but it is a practical and effective way to compress or expand structure density on the same chart.
4) Wick vs Body (which one to choose?)
WICK : Choose when extreme wicks matter to your reading of structure.
BODY : Choose when you want smoother structure and less sensitivity to wick spikes.
5) Suggested workflow for active traders
Use one preset for local structure (entries / short-term decisions).
Use a second preset with a larger Len for higher-level context (major swings / directional bias).
Göstergeler ve stratejiler
Institutional Cycle Intelligence SystemInstitutional Cycle Intelligence System: Architecture, Algorithms, and Application:
Abstract
The Institutional Cycle Intelligence System (ICIS) version 2.0 is a sophisticated Pine Script indicator designed to bridge the gap between retail technical analysis and quantitative hedge fund methodologies. Unlike standard oscillators (RSI, MACD) that rely on fixed lookback periods, ICIS utilizes Digital Signal Processing (DSP) and spectral analysis to dynamically identify, extract, and synthesize market cycles. This document details the system’s specialty, the mathematical underpinnings of its seven algorithms, and a strategic guide for its application in trading.
Part 1: The Specialty & Philosophy
1.1 The Problem with Static Indicators
Traditional technical indicators suffer from a fatal flaw: Stationarity Assumption. A 14-period RSI assumes the market’s "rhythm" is consistently relevant to 14 bars. However, financial markets are non-stationary; cycle lengths expand and contract based on volatility, liquidity, and macroeconomic events. A market might be oscillating on a 10-day cycle one month and shift to a 24-day cycle the next. Static indicators fail to adapt to these phase shifts, leading to false signals.
1.2 The ICIS Solution: Adaptive Spectral Analysis
The ICIS allows traders to visualize the market not as a linear trend, but as a composite of waves (frequencies). Its specialty lies in its "Ensemble Approach." Rather than relying on a single mathematical model, ICIS runs seven distinct advanced cycle detection algorithms simultaneously.
1.3 The "Intelligent" Consensus Engine
The core innovation of this script is the Intelligent Mode. It does not simply average the outputs of the seven models. Instead, it employs an adaptive weighting mechanism:
Normalization: It converts the raw output of each model into a standardized Z-score (standard deviation units) to ensure apples-to-apples comparison.
Scoring: It calculates a "Consistency Score" for each model. If a model is producing erratic, noisy signals, its weight is reduced. If a model detects a high-amplitude, clean sine wave, its weight is increased.
Synthesis: It fuses these weighted inputs into a single "Composite Signal" that represents the highest probability cycle currently driving price action.
Part 2: Algorithmic Deep Dive
The ICIS incorporates seven distinct methodologies drawn from physics, engineering, and econometrics. Understanding these algorithms is key to trusting the signals.
2.1 Ehlers Bandpass + Hilbert Transform
Origin: Digital Signal Processing (DSP).
The Logic: This model acts like a radio tuner. It filters out low-frequency trends and high-frequency noise, isolating a specific bandwidth of market data.
The Mechanism:
Bandpass Filter: Allows only frequencies within the user-defined cycle ranges (Short, Medium, Long) to pass through.
Hilbert Transform: A mathematical operation that shifts the signal by 90 degrees to create an analytic signal. This allows for the precise calculation of the instantaneous phase (where we are in the wave) and amplitude (how strong the wave is).
Strength: Excellent for identifying clean, sine-wave-like market behavior in ranging markets.
2.2 MESA Adaptive Cycle (Maximum Entropy Spectral Analysis)
Origin: Geophysical oil exploration.
The Logic: MESA provides high-resolution frequency estimation even when the data sample is short (a common limitation in trading).
The Mechanism: It uses a "Homodyne Discriminator." It measures the phase change of price relative to itself over time. By calculating the rate of phase change, it derives the dominant cycle period.
Strength: Highly responsive to rapid changes in market cycle length. It adapts faster than Fourier-based methods.
2.3 Autocorrelation Periodogram
Origin: Statistical Time Series Analysis.
The Logic: Markets often rhyme. Autocorrelation measures the similarity of the price series to a lagged version of itself.
The Mechanism: The script runs a loop testing lags from 5 to 150 bars. If price today correlates highly with price 20 days ago, it identifies a 20-day cycle.
Strength: The most robust method for confirming that a cycle actually exists physically, rather than being a mathematical artifact.
2.4 Empirical Mode Decomposition (EMD)
Origin: The Hilbert-Huang Transform (NASA).
The Logic: Markets are non-linear and non-stationary. EMD does not force data into sine waves (like Fourier). instead, it treats price like a rope made of different strands.
The Mechanism:
Sifting: It identifies local highs and lows to create upper and lower envelopes.
Mean Extraction: It subtracts the mean of these envelopes from the data to extract an "Intrinsic Mode Function" (IMF).
Residuals: It repeats this process to separate high-frequency noise (Short Cycle) from medium variations and long-term trends.
Strength: The "Holy Grail" of adaptive analysis. It handles trend reversals and sudden volatility spikes better than any linear filter.
2.5 Goertzel Power Spectrum
Origin: Telecommunications (used in decoding touch-tone phone sounds).
The Logic: A highly optimized version of the Discrete Fourier Transform (DFT). It scans specific frequencies to see which one has the most "Power" (Energy).
The Mechanism: The script calculates the Goertzel energy for various periods. The period with the highest energy is deemed the "Dominant Cycle" and is used to drive the oscillator.
Strength: Extremely precise at identifying the exact length of the current cycle (e.g., distinguishing between a 20-day and a 22-day cycle).
2.6 Singular Spectrum Analysis (SSA)
Origin: Meteorology and climatology.
The Logic: SSA decomposes a time series into principal components: Trend, Oscillatory (Cycle), and Noise.
The Mechanism: While a full SSA requires heavy matrix algebra (difficult in Pine Script), this implementation simulates SSA using weighted lag windows to separate eigen-components. It reconstructs the time series using only the oscillatory components.
Strength: Unrivaled noise reduction. It produces the smoothest "zero-lag" oscillators in the system.
2.7 Wavelet Multi-Resolution Analysis
Origin: Quantum Physics and Image Compression.
The Logic: Standard Fourier analysis loses time information (it tells you a frequency exists, but not when). Wavelets analyze both Frequency and Time simultaneously.
The Mechanism: The script passes price through a cascade of high-pass and low-pass filters (Haar-like decomposition).
Detail Coefficients: Capture high-frequency noise and short cycles.
Approximation Coefficients: Capture the underlying trend and long cycles.
Strength: Excellent for identifying "regime changes" where the market shifts from trending to ranging.
Part 3: Using the Code & Interface
3.1 Input Parameters
Model Selection: Defaults to "Intelligent" (recommended). You can switch to individual models (e.g., "EMD") to isolate their specific view.
Cycle Period Ranges:
Short (5-20): Captures swing trading noise and rapid reversals.
Medium (20-50): The primary swing cycle (often aligns with monthly flows).
Long (50-150): The structural trend cycle.
Advanced Settings:
Bandwidth (0.3): Controls how "wide" the filter is. Lower values = cleaner but lagging; Higher values = noisier but faster.
Signal Threshold (0.5): The level the oscillator must breach to be considered a "Strong" signal.
3.2 Visual Components
The Oscillators (Main Chart):
Red Line (Short): The fast heartbeat of the market.
Teal Line (Medium): The tradeable swing.
Blue Line (Long): The tidal direction.
Purple Line (Composite): The weighted average of all cycles. This is your primary trigger.
The Info Table: Displays the current exact period (in bars), phase (in degrees), and trend direction for all three cycle tiers. It also shows the "Confluence Score" (how many cycles agree).
Background Color: Changes dynamically based on cycle alignment.
Green: Bullish Confluence (2 or 3 cycles pointing up).
Red: Bearish Confluence (2 or 3 cycles pointing down).
Part 4: Trading Strategy & Application
The ICIS is designed to identify Turning Points and Trend Continuations.
4.1 The "Phasing" Concept
Understanding Phase is crucial. The script calculates phase in degrees (0° to 360°):
0° - 90° (Accumulation): The cycle has bottomed and is accelerating upward. Best time to enter.
90° - 180° (Markup): The cycle is mature but still rising. Hold positions.
180° - 270° (Distribution): The cycle has topped and is accelerating downward. Best time to short/sell.
270° - 360° (Decline): The cycle is mature in its downtrend. Hold shorts or cash.
4.2 Trade Setups
Setup A: The "Triple Confluence" Entry (Trend Following)
This is the safest signal, indicating all distinct time horizons are aligned.
Condition: The Short, Medium, and Long cycle lines are ALL sloping upwards.
Visual: Background turns bright Green.
Trigger: The Composite (Purple) line crosses above the Signal Threshold (+0.5).
Exit: When the Short Cycle (Red) crosses below the Medium Cycle (Teal).
Setup B: The "Cycle Bottom" (Reversal)
This catches the absolute low of a move.
Condition: The Long Cycle (Blue) is trending UP (Trend support).
Trigger: The Composite line is deeply negative (below -0.8) and crosses back ABOVE zero.
Validation: Wait for the "Cycle Bottom" circle marker to appear on the chart.
Stop Loss: Below the recent swing low.
Setup C: The "Divergence" Play (Advanced)
Condition: Price makes a Lower Low.
Indicator: The Composite Oscillator makes a Higher Low.
Logic: Momentum on the cyclical level is shifting bullish despite price action.
Execution: Enter on the first candle where the Composite line turns green (slopes up).
4.3 Interpreting the Information Table
The table is your dashboard.
Period: If the "Medium Period" is drastically changing (e.g., jumping from 20 to 50), the market is in a chaotic transition. Reduce position size.
Strength: Shows the cycle amplitude. If Strength < 20%, the market is chopping/sideways. Do not trade trend strategies. If Strength > 60%, the cycle is dominant; use aggressive targets.
Part 5: Optimization & Best Practices
5.1 Timeframes
While the math works on any timeframe, ICIS is computationally heavy and optimized for:
4H / 1D: Best for Swing Trading. The cycle periods (20-40 bars) align well with monthly/quarterly flows.
15m / 1H: Good for Intraday, but requires adjusting the "Short Cycle" inputs to be more sensitive (e.g., Min 5, Max 15).
5.2 Handling "Repainting" vs. "Recalculation"
This script uses max_bars_back and causal filters where possible. However, EMD and SSA are inherently adaptive.
Fact: The Phase calculation uses the Hilbert Transform, which requires a few bars of future data to be perfectly precise (theoretical limit).
Mitigation: The script uses a causal approximation of the Hilbert Transform (nz(src ) etc.) to minimize repainting.
Rule: Do not trade on the current forming bar. Wait for the bar to close to confirm the cycle direction.
5.3 Combining with Price Action
ICIS tells you the Time (When to trade), but Price Action tells you the Level (Where to trade).
Use ICIS to time the entry.
Use Support/Resistance or Supply/Demand zones to place the order.
Example: Price hits a Demand Zone + ICIS signals "Cycle Bottom" + Confluence turns Green = High Probability Trade.
Conclusion
The Institutional Cycle Intelligence System version 2.0 represents a paradigm shift from lagging indicators to predictive cycle modeling. By intelligently fusing seven different mathematical models, it cancels out the weaknesses of individual algorithms (like EMD's end-effect issues or Fourier's spectral leakage).
Summary of Workflow:
Check the Table: Is Cycle Strength high? Are cycles aligned?
Check the Background: Is it Green (Bullish) or Red (Bearish)?
Wait for the Composite Trigger: Cross of Zero or Cross of Threshold.
Execute: With defined risk based on market structure.
This tool provides the retail trader with the "X-Ray vision" into market structure typically reserved for quantitative trading desks.
Statistical Reversion FrameworkIntroduction and Core Philosophy
The Statistical Reversion Framework constitutes a sophisticated quantitative trading instrument designed to identify high-probability mean reversion opportunities across financial markets. Unlike traditional technical indicators that rely on a single dimension of market data, this framework adopts a multi-faceted approach, synthesizing statistical probability, volume profile analysis, institutional money flow proxies, and standard technical momentum into a singular composite score. The core philosophy driving this script is the concept of confluence through heterogeneity; by combining uncorrelated or loosely correlated market factors—such as price deviation (statistics), participant commitment (volume), and macro sentiment (intermarket data)—the algorithm aims to filter out the noise inherent in standard oscillators and isolate moments where market pricing has deviated unsustainably from its intrinsic equilibrium. This tool is specifically engineered to detect market extremes—tops and bottoms—where the probability of a counter-trend move or a snap-back to the mean is mathematically significant. It operates on the premise that while asset prices can remain irrational in the short term, they are bound by statistical variance and mean-reverting properties over longer horizons, particularly when institutional flows and volume exhaustion patterns align with those statistical extremes.
Methodology: The Composite Scoring Architecture
The underlying methodology of the framework relies on a weighted composite scoring system. Rather than generating binary buy or sell signals based on a threshold crossover, the script calculates a granular score ranging from zero to one hundred for various market dimensions. These dimension-specific scores are then weighted according to user-defined inputs to produce a final "Composite Score." This approach allows for a nuanced assessment of market conditions; a setup might have extreme statistical deviation but lack volume confirmation, resulting in a lower confidence score than a setup where price, volume, and macro factors all align. The algorithm normalizes all input data into a standardized scale, typically converting raw values—such as Z-Scores or volume ratios—into a zero-to-ten ranking before aggregating them. This normalization process is critical because it allows the algorithm to compare apples to oranges mathematically, treating a standard deviation of 3.0 and a Relative Strength Index (RSI) of 20 as compatible inputs within the same equation. By summing these normalized values and applying regime-based confidence adjustments, the framework produces a dynamic signal that adapts to the volatility and trend intensity of the current market environment.
Algorithmic Component I: Statistical Analysis via Multi-Timeframe Z-Scores
The backbone of the framework is the Statistical Component, which utilizes the Z-Score (or Standard Score) to quantify the degree of price deviation. The Z-Score measures how many standard deviations the current price is from its moving average. A crucial aspect of this algorithm is its fractal nature; it does not rely on a single lookback period. Instead, it computes Z-Scores across three distinct timeframes—Daily, Weekly, and Monthly—and within each timeframe, it calculates deviations for short, medium, and long-term periods. For instance, on the daily timeframe, it assesses deviation from 50-day, 200-day, and 500-day means simultaneously. This multi-timeframe approach is designed to filter out ephemeral noise. A price move that appears extreme on a 10-day basis but is normal on a 200-day basis is likely a trend pull-back rather than a reversal. Conversely, when the Z-Scores across daily, weekly, and monthly timeframes all register values beyond significant thresholds (such as 2.0 or 3.0 standard deviations), it indicates a rare fractal alignment where the asset is historically overextended on all relevant scales. The algorithm aggregates these nine distinct Z-Score data points to form the "Statistical Score," heavily rewarding scenarios where multiple timeframes show directional alignment, as these synchronized deviations often precede powerful mean-reversion events.
Algorithmic Component II: Volume Signature and Participation Analysis
While statistical deviation highlights where the price is, the Volume Component analyzes the conviction behind the move to determine if a reversal is imminent. This section of the code employs several sophisticated logic gates to identify specific volume signatures known as Capitulation and Exhaustion. The algorithm compares current volume against a 50-day moving average to generate a volume ratio. It then correlates this ratio with price action. For example, the script identifies "Capitulation" when price collapses significantly (more than 2%) on volume that is at least three times the average. This specific signature—panic selling—often marks the psychological wash-out necessary for a market bottom. Conversely, the script detects "Volume Exhaustion" when prices drift without conviction on extremely low volume, indicating a lack of participant interest in pushing the trend further. Furthermore, the algorithm integrates On-Balance Volume (OBV) analysis, specifically looking for divergences. It detects subtle shifts where the price makes a new low, but the OBV makes a higher low, signaling that smart money is accumulating positions despite the falling price. This divergence logic is automated using pivot-based high/low detection arrays, adding a layer of foreshadowing that price-only indicators often miss.
Algorithmic Component III: Institutional Proxy and Intermarket Correlations
The Institutional Component distinguishes this framework from standard retail indicators by incorporating intermarket data that serves as a proxy for macro sentiment and institutional flow. The script pulls data from extraneous tickers—specifically the VIX (Volatility Index), Government Bond Yields (10-year and 2-year), Copper, Gold, and the Dollar Index (DXY). The logic here is grounded in fundamental market mechanics. For instance, the script analyzes the VIX to gauge market fear; however, it applies a contrarian logic. An extremely high VIX (panic) coincident with a low equity price is scored as a bullish factor, while a complacently low VIX at market highs is viewed as bearish. Similarly, the algorithm analyzes the Yield Curve (the spread between 10-year and 2-year yields). A steepening or flattening curve provides context on economic expectations, influencing the score based on whether the environment is "risk-on" or "risk-off." The Copper/Gold ratio is utilized as a barometer for global economic health; rising copper relative to gold suggests industrial demand and growth, confirming bullish setups, whereas falling copper prices signal contraction. By integrating these non-price variables, the framework ensures that a trade signal is not just technically sound but is also supported by the broader macroeconomic undercurrents that drive institutional capital allocation.
Algorithmic Component IV: Technical Momentum and Structure
The final layer of input comes from standard Technical Analysis, which serves to fine-tune the timing of the entry. This component aggregates readings from the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands, and Support/Resistance proximity. While Z-Scores measure linear distance from the mean, the RSI and Bollinger Bands measure the velocity and elasticity of that move. The algorithm assigns higher scores when RSI hits extreme levels (below 20 or above 80) and when price action pierces the outer bounds of the Bollinger Bands. Additionally, the MACD is monitored for histogram reversals and signal line crosses that align with the mean reversion bias. A unique feature of this component is the proximity logic, which calculates how close the current price is to a 50-period high or low. If a statistical extreme coincides with a retest of a major structural support level, the technical score is maximized. This ensures that the trader is not catching a falling knife in a void, but rather identifying a reversal at a location where technical structure provides a natural floor or ceiling for price.
Regime Detection and Confidence Adjustment
A critical vulnerability of mean reversion strategies is that they can suffer severe drawdowns during strong, unidirectional trending markets (momentum regimes). To mitigate this, the framework incorporates a Regime Detection module using the Average Directional Index (ADX) and volatility thresholds. The script calculates the ADX to measure trend strength regardless of direction. If the ADX is above a certain threshold (default 25), the market is classified as "Trending." The script then cross-references this with volatility data to classify the environment into regimes such as "Crisis," "Trending," "Range," or "Mean-Revert." This classification is not merely cosmetic; it actively influences the final output through a "Regime Confidence" multiplier. If the system detects a strong trending regime, it dampens the Composite Score, requiring extraordinary evidence from the other components to trigger a signal. Conversely, if the market is detected as "Mean-Revert" or "Low-Vol Range," the confidence multiplier boosts the score, making the system more sensitive to reversion signals. This adaptive logic helps protect the trader from fading strong breakouts while aggressively capitalizing on ranging markets.
Usage Instructions and Dashboard Interpretation
Traders utilizing this framework should primarily interact with the on-screen Dashboard, which provides a real-time summary of all computed metrics. The dashboard is organized hierarchically, with the "Composite Score" and "Signal Status" at the top. A Composite Score above 70 is generally considered actionable, with scores above 85 representing "Exceptional" setups. The Dashboard is color-coded: green hues indicate bullish/oversold conditions suitable for buying, while red hues indicate bearish/overbought conditions suitable for selling or shorting. Traders should look for "Confluence" across the rows. Ideally, a robust signal will show a high Statistical score (indicating price is cheap/expensive), a high Volume score (indicating capitulation or accumulation), and a supportive Institutional score. If the Composite Score is high but the Institutional score is low, the trader should proceed with caution, as the macro environment may not support the trade.
The chart visuals provide immediate entry triggers. "Strong Bottom" (Green Triangle) and "Strong Top" (Red Triangle) shapes appear when the Composite Score breaches the high threshold and Z-Scores are at extremes. These are the primary execution signals. Smaller "Potential" markers indicate developing setups that may require lower timeframe confirmation. Additionally, specific volume icons (Diamonds) will appear to denote Capitulation or Climax events. A trader should ideally wait for the candle to close to confirm these signals. The alerts configured in the script allow the trader to be notified of these events remotely. For risk management, because this is a mean reversion tool, stop-losses should typically be placed below the swing low of the capitulation candle (for longs) or above the swing high of the climax candle (for shorts), anticipating that the statistical extreme marks the distinct turning point. By systematically waiting for the Composite Score to align with the visual signals and verifying the regime context on the dashboard, the trader effectively filters out low-probability trades, engaging only when statistics, volume, and macro-economics align.
VIX Percentile OscillatorWhat is this script?
This is a trading tool that helps you decide when to buy or sell options based on market volatility. Think of it as a "fear meter" for the stock market.
What is VIX?
VIX = Volatility Index (also called the "fear index")
When VIX is HIGH → Market is scared/volatile → Options are EXPENSIVE
When VIX is LOW → Market is calm → Options are CHEAP
What does "Percentile" mean?
Instead of just showing VIX price, this script shows where VIX is compared to history.
Example: If VIX Percentile = 85%
This means VIX is higher than 85% of all past readings
Only 15% of the time was VIX higher than now
Translation: Volatility is unusually HIGH
The 5 Trading Zones
The script divides the market into 5 zones:
🔴 EXTREME SELLING ZONE (90-100%)
VIX is in the top 10% historically
Action: AGGRESSIVELY SELL OPTIONS (collect big premiums)
Market panic = expensive options = profit for sellers
🟠 SELLING ZONE (80-89%)
VIX is elevated but not extreme
Action: SELL OPTIONS (good premiums available)
⚪ NEUTRAL ZONE (20-79%)
VIX is normal
Action: WAIT or use other strategies
🟢 BUYING ZONE (10-19%)
VIX is low
Action: BUY OPTIONS (they're cheap)
🟢 EXTREME BUYING ZONE (0-9%)
VIX is in the bottom 10% historically
Action: AGGRESSIVELY BUY OPTIONS (bargain prices)
Market complacency = cheap options = opportunity
Understanding the Chart
Main Line (Blue/Red/Green):
Shows current VIX percentile
Color changes based on zone
Thick line = easy to see
Histogram (Background bars):
Red bars = above 50% (high volatility)
Green bars = below 50% (low volatility)
Purple Momentum Line:
Shows if VIX is rising or falling
Helps you catch trends early
Background Colors:
Light red/orange = Selling zones
Light green = Buying zones
Triangle Markers:
Appear when entering new zones
"EXTREME" label = strongest signals
The Statistics Table (Top Right)
VIX Price: Current VIX value (e.g., 16.50)
Percentile: Where VIX ranks (0-100%)
Z-Score: Statistical measure
Above +2 or below -2 = extreme
Red text = unusually high/low
Momentum: Rate of change
Red = rising (volatility increasing)
Green = falling (volatility decreasing)
Avg VIX: Average VIX over lookback period
Current Zone: Which zone you're in right now
Bars in Zone: How long you've been in this zone
Simple Trading Rules
FOR OPTION SELLERS (Premium Collectors):
✅ SELL when: Percentile > 80% (especially > 90%)
High premiums available
Examples: Sell covered calls, cash-secured puts, credit spreads
FOR OPTION BUYERS (Hedgers/Speculators):
✅ BUY when: Percentile < 20% (especially < 10%)
Cheap options available
Examples: Buy protective puts, long calls, debit spreads
Key Settings You Can Adjust
Lookback Period (default: 252)
How far back to compare (252 = 1 year of trading days)
Longer = smoother, more stable
Shorter = more sensitive to recent changes
Smoothing Period (default: 3)
Reduces noise/wiggling
Higher = smoother line
Lower = more responsive
Zone Thresholds:
Extreme Sell: 90%
Sell: 80%
Buy: 20%
Extreme Buy: 10%
You can customize these!
Real-World Example
Scenario: VIX Percentile jumps to 92%
What this means:
VIX is higher than 92% of all past readings
Market is in panic mode
Option premiums are INFLATED
Trading Action:
✅ Sell covered calls on stocks you own
✅ Sell cash-secured puts on stocks you want to buy
✅ Sell credit spreads
❌ DON'T buy expensive options right now
Why it works: When fear is extreme, it usually calms down eventually. You profit as premiums deflate.
Important Reminders
⚠️ This is a TIMING tool, not a crystal ball
It tells you WHEN premiums are expensive/cheap
It doesn't tell you WHICH options to trade
You still need proper risk management
⚠️ Works on ALL timeframes
Daily charts = swing trading
Weekly charts = position trading
Intraday charts = day trading volatility
⚠️ Best for:
Option sellers during high VIX (>80%)
Option buyers during low VIX (<20%)
Portfolio hedging decisions
Volatility trading strategies
Bottom Line: This script helps you buy options when they're cheap and sell options when they're expensive. It's like shopping for sales, but for volatility!
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice. Please do boost if you like it. Happy Trading.
Volume PressureVolume Pressure
Volume Pressure is a volume-flow based oscillator designed to visualize relative buying and selling pressure using a refined Volume Flow Index (VFI) methodology. The indicator evaluates how volume behaves in relation to price movement and volatility, and presents this information as a smooth flow line with adaptive color intensity for easier interpretation.
What the Indicator Shows
Volatility-filtered volume participation
Directional volume flow derived from price change
A smoothed flow line with dynamic color intensity
A signal line for visual reference
The flow line is layered to enhance visibility, making it easier to read on dark chart backgrounds and smaller panels.
How to Read It
Flow Line: Represents relative volume pressure
Above zero: positive pressure
Below zero: negative pressure
Color Intensity:
Brighter colors indicate stronger relative pressure
Faded colors indicate weaker or neutral pressure
Signal Line: A smoothed reference of flow behavior
Usage Notes
Designed as a visual analysis and confirmation tool
Can be used across intraday and higher timeframes
Best used alongside price action, trend, or structure analysis
Disclaimer
This indicator is for analytical and educational purposes only.
It does not provide buy or sell signals and does not imply future performance.
TZ - India VIX Volatility ZonesTZ – India VIX Volatility Zones is a long-term volatility analysis indicator designed to visually map important India VIX regimes using clearly defined horizontal zones and labels.
The indicator highlights how market volatility cycles between complacency, normal conditions, elevated risk, and panic phases. These zones are based on historical behavior of India VIX and help traders understand when risk is underpriced or overstretched.
This tool is especially useful for:
Index traders
Options sellers and buyers
Risk management and regime filtering
Long-term volatility study
How It Works
The script plots static, historically significant volatility zones on the India VIX chart and visually separates them using shaded bands and labels.
Volatility Zones Explained
1.Extreme Low Volatility (VIX 8–10)
Indicates market complacency and underpriced risk. Often precedes volatility expansion.
2.Low Volatility (VIX 10–13)
Stable market conditions with controlled movement.
3.Normal Volatility (VIX 13–18)
Healthy market behavior and balanced risk.
4.High Volatility (VIX 18–25)
Rising uncertainty and increased intraday swings.
5.Panic Zone (VIX 25–35+)
High fear environment, usually during major events or crises.
How Traders Can Use This Indicator
Identify volatility regimes before choosing option strategies
Avoid aggressive short-volatility trades during extreme zones
Prepare for volatility expansion during low-VIX phases
Use as a market risk context tool alongside price action
This indicator does not provide buy/sell signals. It is designed for contextual analysis and decision support.
Best Usage
Apply on India VIX (NSE:INDIAVIX)
Works best on Weekly and Monthly timeframes
Can be combined with index charts for volatility-based risk assessment
Disclaimer
This indicator is for educational and analytical purposes only.
It does not constitute financial advice or trade recommendations.
Users should apply proper risk management and confirm signals using additional analysis.
Fractal Swing Levels📊 Fractal Swing Levels — Indicator Description
Fractal Swing Levels is a lightweight, visual indicator that plots historical swing high and swing low reference levels using Williams Fractal logic. The indicator helps traders visually identify areas where price previously formed confirmed pivots. These levels can be used as contextual reference zones when analyzing price structure and market behavior.
🔍 What the Indicator Does
Detects confirmed swing highs and swing lows using a configurable fractal length. Draws horizontal levels at those swing points. Extends the levels to the right for ongoing visual reference. Limits the number of displayed levels to keep the chart clean
🎨 Visual Elements
Red lines represent historical swing high levels
Green lines represent historical swing low levels
These lines are drawn only after fractal confirmation and represent past price structure, not future projections.
⚙️ Settings Explained
Fractal Length : Controls how significant a swing must be to qualify as a level.
Higher values → fewer, more prominent levels
Lower values → more frequent levels
Max Levels Per Side : Limits how many swing high and swing low levels are displayed at one time, helping reduce chart clutter.
📈 How to Use
Use the levels as visual reference points for structure analysis. Combine with trend tools, moving averages, or other technical indicators. Useful across intraday, swing, and positional timeframes. This indicator is best used as a contextual aid, not as a standalone decision tool.
⚠️ Important Notes
This is a visual analysis tool only. It does not generate buy or sell signals. It does not predict future price movement. Levels are based solely on confirmed historical price data
🎯 Summary
Fractal Swing Levels provides a clean and minimal way to visualize historical swing structure on the chart, helping traders better understand where price has previously reacted.
HTF Accumulation Distribution Zones (Analysis)📌 Indicator Name
HTF Accumulation–Distribution Zones (Analysis)
This indicator highlights potential accumulation and distribution contexts on the price chart using a combination of volume behavior, volatility (ATR), momentum, and VWAP positioning.The script is designed to help traders understand market participation and positioning, especially on higher intraday and swing timeframes, where institutional activity tends to leave clearer footprints.
🔍 What the indicator shows
ACC (Accumulation) : Marks areas where controlled buying activity may be present, identified through:
Strong candle structure relative to volatility
Healthy or controlled volume participation
Improving momentum within defined ranges
DIST (Distribution) : Marks areas where selling pressure may be emerging, identified through:
Price stretching away from VWAP
Weakening momentum
Strong bearish candle structure
These labels represent contextual zones, not trade signals.
🧠 How to use it
Use ACC and DIST labels as market context, not as direct buy or sell instructions.
Best used as a confirmation layer alongside:
Trend filters (EMA, VWAP, structure)
Support & resistance
Breakout or pullback strategies
Works well on 15-minute, 30-minute, 1-hour, and higher timeframes
Suitable for indices, futures, and liquid stocks
⚠️ Important Notes
This indicator does not generate buy or sell signals. It does not predict future price movement. All outputs are based purely on historical data analysis. Always apply independent confirmation and proper risk management
Trend Regime Bands (EMA 50 / 150 / 200)📘 Trend Regime Bands – EMA 50·150·200
Overview
Trend Regime Bands is a visual trend-context indicator designed to help users quickly understand whether the market is in a bullish or bearish regime. The indicator uses the alignment of EMA 50, EMA 150, and EMA 200 to determine overall trend direction, while additional EMAs are used only to create color-based bands for visual context. No buy or sell signals are generated.
How Trend Direction Is Determined
Trend direction is derived exclusively from the relative positioning of: EMA 50 (short-term trend) , EMA 150 (medium-term trend) , EMA 200 (long-term trend) . Bullish regime: EMA 50 ≥ EMA 150 ≥ EMA 200 . Bearish regime: EMA 50 < EMA 150 < EMA 200. These three EMAs act as the decision framework for the indicator.
What the Color Bands Represent : The indicator displays two visual bands on the chart:
Fast Band (Momentum Context) - Built using faster EMAs, Represents short-term momentum and pullback behavior. Brighter color intensity reflects stronger momentum
Slow Band (Regime Context) - Built using slower EMAs. Represents broader trend structure and regime stability.Deeper color intensity reflects stronger trend alignment
The color of both bands follows the trend direction determined by EMA 50/150/200:
Green shades indicate a bullish regime. Red shades indicate a bearish regime. Color intensity increases or decreases smoothly based on trend strength.
How to Use This Indicator
Use the bands to understand market context, not as entry or exit signals. Strong, bright bands suggest a well-established trend. Lighter bands indicate weaker or transitioning trends. The indicator works across intraday, swing, and higher timeframes. This tool is best used alongside price action, support/resistance, or other confirmation methods.
Important Notes
This indicator does not provide buy or sell signals. It does not predict future price movement. It is intended solely as a visual trend-regime and context tool
Summary
Trend Regime Bands offers a clean, distraction-free way to visualize bullish and bearish market regimes using EMA structure and color intensity, helping traders maintain directional awareness and discipline.
Supply & Demand Zones (Volume-Based)📌 Supply & Demand Zones (Volume-Based) — Indicator Description
Overview
This indicator visually highlights potential supply and demand price zones using historical candle structure combined with relative volume behavior.The zones are intended to help users observe areas of increased market activity where price has previously reacted. This tool is designed for visual analysis only.
How the Zones Are Identified
Demand zones are highlighted when price shows a strong bullish reaction following a bearish candle.Supply zones are highlighted when price shows a strong bearish reaction following a bullish candle.Relative volume is used as context, not as a predictive input, to classify zones into higher or lower activity levels.Zones automatically invalidate when price structurally breaks them.
About the Percentage Display
The percentage shown on a zone represents normalized relative volume strength at the time the zone was formed.This value is not a probability, not a success rate, and not a performance metric.It should not be interpreted as a prediction or trading signal.Percentages are displayed only for active zones and are removed once a zone is invalidated.
How This Indicator Is Intended to Be Used
As a visual reference tool for identifying historical supply and demand areas.As a contextual overlay alongside other forms of technical analysis.To observe how price behaves when revisiting previously active zones.This indicator does not suggest trade direction, entry timing, or exit levels.
Important Notes & Limitations
All zones are derived from historical price and volume data.Market conditions change, and historical zones may lose relevance over time.No trading decisions should be made based solely on this indicator.Users are encouraged to apply their own analysis and risk management.
Disclaimer
This indicator is provided for educational and informational purposes only.It does not constitute trading, investment, or financial advice.The author assumes no responsibility for decisions made using this tool.
Custom Psych Levels V1.0 Theo SignalDesigned for Index Traders (US30, NAS100, SPX, etc.)
This script is especially effective on indices such as US30, where price reacts strongly to round numbers and psychological zones. By default, levels adapt to index volatility and scale, making them ideal for:
intraday bias
pullback reactions
breakout continuation
mean reversion back to balance
Key Features
Rolling 5-Level Structure: Always centered on current price, no chart clutter.
Market- Aware Magnitude: Automatically adjusts spacing for indices, forex, and crypto.
Higher- Timeframe Anchoring: Optionally anchor levels to 1H, 4H, or Daily closes while trading lower timeframes like 5m.
Session & Daily Resets: Re-anchor levels at New York session open or new trading day.
Center Line Emphasis: Highlight the equilibrium level with custom color, thickness, and style for balance or decision-making.
Clean Professional Display: Only relevant levels near price are shown.
Trading Use Cases
This indicator is best used as a framework, not a signal generator. It excels when combined with:
momentum confirmation
liquidity sweeps
volume expansion
break-and-retest structures
session highs/lows
Traders can use the center line as balance, outer levels as reaction or target zones, and band shifts as confirmation of expanding price acceptance.
15M Swing Sweep Lines + SMT (ES vs NQ)15M Swing Sweep Lines (NY Killzones)Visualize liquidity sweeps of 15-minute swing highs/lows exclusively during high-impact London & New York killzones.This ICT-inspired indicator detects when price sweeps (wicks beyond) the most recent confirmed 15-minute swing high or low — classic signs of liquidity raids or stop hunts — but only if the sweep happens during key "killzone" sessions where institutional activity is typically highest.Key Features15M Swing Detection: Uses confirmed pivot highs/lows (length 2) on the 15-minute timeframe for reliable structure points.
Killzone Filters (New York time):London Killzone: 3:00 AM – 4:59 AM
New York Killzone: 9:30 AM – 10:59 AM (captures the high-volatility NY open overlap)
Sweep Visualization:Bearish Sweep (high > last 15M swing high): Thick red horizontal line from the swing point to the sweep bar.
Bullish Sweep (low < last 15M swing low): Thick green horizontal line from the swing point to the sweep bar.
Lines use xloc.bar_time for precise placement and extend only to the bar where the sweep occurs.
No duplicates: Prevents multiple lines for the same swing sweep.
Non-repainting logic with lookahead_off for clean, trustworthy signals.
Why Killzones MatterMany ICT/SMC traders focus on these windows because they often feature aggressive manipulation, equal highs/lows sweeps, and the setup for strong directional moves. This tool helps you instantly spot when buy-side or sell-side liquidity has been raided on the 15M structure during these prime times.Ideal ForConfirming potential reversals or inducements after liquidity grabs.
Adding confluence to entries during London or NY sessions.
Futures traders (ES, NQ, etc.) looking for clean visual cues of smart money engineering.
Lightweight, overlay-friendly, and focused — add it to your chart for clearer insight into 15M liquidity sweeps when it matters most. Perfect companion for killzone-based strategies!
tncylyv - Improved Delta Volume BubbleThis script is a specialized modification and structural upgrade of the excellent "Delta Volume Bubble " by tncylyv.
While the original tool provided a fantastic foundation for statistical volume analysis, this "Zero Float" Edition was built to solve specific visual challenges faced by active traders—specifically the issue of indicators "floating" or disconnecting from price when zooming in on lower timeframes.
The Straight Improvements
This version turns a "Signal Indicator" into a complete "Trading System" with five specific upgrades:
1. Visual Stability (The "Zero Float" Fix)
Original: Used complex coordinates that could desynchronize, causing bubbles to drift or float away from candles on fast charts (1m/5m).
My Upgrade: Implemented "Magnetic Anchoring." Labels and bubbles are now physically locked to the candle wicks. They never drift, overlap, or float, no matter how much you zoom or resize the chart.
2. Cognitive Load (The HUD)
Original: Displayed raw numbers inside colored circles, requiring you to memorize color codes.
My Upgrade: Replaced numbers with Semantic Text Labels (e.g., "ABSORB", "SQUEEZE", "MOMENTUM"). You can read the market intent instantly without decoding it.
3. Regime Adaptation (AI Engine)
Original: Used a fixed threshold (e.g., Z-Score > 2.0).
My Upgrade: Added an Adaptive Learning Window. The script scans recent volatility to automatically raise the threshold during choppy markets (filtering noise) and lower it during quiet sessions (catching subtle entries).
4. Market Memory (Smart Structure)
Original: Signals disappeared into history.
My Upgrade: Draws Support/Resistance Rails extending from major volume events. This helps you visualize exactly where institutions are defending their positions.
5. Robust Data Handling
My Upgrade: Added a Hybrid Fallback Engine. If granular 1-minute data isn't available (e.g., on historical charts), the script seamlessly switches to an estimation model so the indicator never "breaks" or disappears.
Core Logic
Z-Score Normalization: We don't look at raw volume; we look at statistical anomalies (Standard Deviations).
Absorption: Detects "Effort vs. Result"—high volume with tiny price movement (Trapped Traders).
Squeeze: Highlights areas where a breakout is imminent due to volatility compression.
Credits
Original Concept & Code: tncylyv (Delta Volume Bubble ). This script would not exist without his brilliant groundwork.
Modifications: Visual Anchoring, HUD Text System, AI Thresholding, and Structure Rails added in this edition.
This script is open-source to keep the spirit of the original author alive. Use it to understand the "Why" behind the move.
Kalman Hull Kijun [BackQuant]Kalman Hull Kijun
A trend baseline that merges three ideas into one clean overlay, Kalman filtering for noise control, Hull-style responsiveness, and a Kijun-like Donchian midline for structure and bias.
Context and lineage
This indicator sits in the same family as two related scripts:
Kalman Price Filter
This is the foundational building block. It introduces the Kalman filter concept, a state-estimation algorithm designed to infer an underlying “true” signal from noisy measurements, originally used in aerospace guidance and later adopted across robotics, economics, and markets.
Kalman Hull Supertrend
This is the original script made, which people loved. So it inspired me to create this one.
Kalman Hull Kijun uses the same core philosophy as the Supertrend variant, but instead of building a Supertrend band system, it produces a single structural baseline that behaves like a Kijun-style reference line.
What this indicator is trying to solve
Most trend baselines sit on a bad trade-off curve:
If you smooth hard, the line reacts late and misses turns.
If you react fast, the line whipsaws and tracks noise.
Kalman Hull Kijun is designed to land closer to the middle:
Cleaner than typical fast moving averages in chop.
More responsive than slow averages in directional phases.
More “structure aware” than pure averages because the baseline is range-derived (Kijun-like) after filtering.
Core idea in plain language
The plotted line is a Kijun-like baseline, but it is not built from raw candles directly.
High level flow:
Start with a chosen price stream (source input).
Reduce measurement noise using Kalman-style state estimation.
Add Hull-style responsiveness so the filtered stream stays usable for trend work.
Build a Kijun-like baseline by taking a Donchian midpoint of that filtered stream over the base period.
So the output is a single baseline that is intended to be:
Less jittery than a simple fast MA.
Less laggy than a slow MA.
More “range anchored” than standard smoothing lines.
How to read it
1) Trend and bias (the primary use)
Price above the baseline, bullish bias.
Price below the baseline, bearish bias.
Clean flips across the baseline are regime changes, especially when followed by a hold or retest.
2) Retests and dynamic structure
Treat the baseline like dynamic S/R rather than a signal generator:
In uptrends, pullbacks that respect the baseline can act as continuation context.
In downtrends, reclaim failures around the baseline can act as continuation context.
Repeated back-and-forth around the line usually means compression or chop, not clean trend.
3) Extension vs compression (using the fill)
The fill is meant to communicate “distance” and “pressure” visually:
Large separation between price and baseline suggests expansion.
Price compressing into the baseline suggests rebalancing and decision points.
Inputs and what they change
Kijun Base Period
Controls the structural memory of the baseline.
Higher values track broader swings and reduce flips.
Lower values track tighter swings and react faster.
Kalman Price Source
Defines what data the filter is estimating.
Close is usually the cleanest default.
HL2 often “feels” smoother as an average price.
High/Low sources can become more reactive and less stable depending on the market.
Measurement Noise
Think of this as the main smoothness knob:
Higher values generally produce a calmer filtered stream.
Lower values generally produce a faster, more reactive stream.
Process Noise
Think of this as adaptability:
Higher values adapt faster to changing conditions but can get twitchy.
Lower values adapt slower but stay stable.
Plotting and UI (what you see on chart)
1) Adaptive line coloring
Baseline turns bullish color when price is above it.
Baseline turns bearish color when price is below it.
This makes the state readable without extra panels.
2) Gradient “energy” fill
Bull fill appears between price and baseline when above.
Bear fill appears between price and baseline when below.
The goal is clarity on separation and control, not decoration.
3) Rim effect
A subtle band around price that only appears on the active side.
Helps highlight directional control without hiding candles.
4) Candle painting (optional)
Candles can be colored to match the current bias.
Useful for scanning many charts quickly.
Disable if you prefer raw candles.
Alerts
Long state alert when price is above the baseline.
Short state alert when price is below the baseline.
Best used as a bias or regime notification, not a standalone entry trigger.
Where it fits in a workflow
This is a context layer, it pairs well with:
Market structure tools, BOS/MSB, OBs, FVGs.
Momentum triggers that need a regime filter.
Mean reversion tools that need “do not fade trends” context.
Limitations
No baseline eliminates chop whipsaws, tuning only manages the trade-off.
Settings should not be copy pasted across assets without checking behavior.
This does not forecast, it estimates and smooths state, then expresses it as a structural baseline.
Disclaimer
Educational and informational only, not financial advice.
Not a complete trading system.
If you use it in any trading workflow, do proper backtesting, forward testing, and risk management before any live execution.
RSI Forecast [QuantAlgo]🟢 Overview
While standard RSI excels at measuring current momentum and identifying overbought or oversold conditions, it only reflects what has already happened in the market. The RSI Forecast indicator builds upon this foundation by projecting potential RSI trajectories into future bars, giving traders a framework to consider where momentum might head next. Three analytical models power these projections: a market structure approach that reads swing highs and lows, a volume analysis method that weighs accumulation and distribution patterns, and a linear regression model that extrapolates recent trend behavior. Each model processes market data differently, allowing traders to choose the approach that best fits their analytical style and the asset they're trading.
🟢 How It Works
At its foundation, the indicator calculates RSI using the standard methodology: comparing average upward price movements against average downward movements over a specified period, producing an oscillator that ranges from 0 to 100. Traders can apply an optional signal line using various moving average types (e.g., SMA, EMA, SMMA/RMA, WMA, or VWMA), and when SMA smoothing is selected, Bollinger Bands can be added to visualize RSI volatility ranges.
The forecasting mechanism operates by first estimating future price levels using the chosen projection method. These estimated prices then pass through a simulated RSI engine that mirrors the actual indicator's mathematics. The simulation updates the internal gain and loss averages bar by bar, applying the same RMA smoothing that powers real RSI calculations, to produce authentic projected values.
Since RSI characteristically moves in waves rather than straight lines, the projection system incorporates dynamic oscillation. This draws from stored patterns of recent RSI movements, factors in the tendency for RSI to pull back from extreme readings, and applies mathematical wave functions tied to current momentum conditions. The Oscillation Intensity control lets traders adjust how much waviness appears in projections. Signal line (RSI-based MA) projections follow the same logic, advancing the chosen moving average type forward using its proper mathematical formula. The complete system generates 15 bars of projected RSI and signal line values, displayed as dashed lines extending beyond current price action.
🟢 Key Features
1. Market Structure Model
This projection method reads price action through swing point analysis. It scans for pivot highs and pivot lows within a defined lookback range, then evaluates whether the market is building bullish patterns (successive higher highs and higher lows) or bearish patterns (successive lower highs and lower lows). The algorithm recognizes structural shifts when price violates previous swing levels in either direction.
Price projections under this model factor in proximity to key swing levels and overall trend strength, measured by tallying trend-confirming swings over recent history. When bullish structure prevails and price hovers near support, upward price bias enters the projection, pushing forecasted RSI higher. Bearish structure near resistance creates the opposite effect. The model scales its projections using ATR to keep them proportional to current volatility conditions.
▶ Practical Implications for Traders:
Aligns well with traders who focus on support, resistance, and swing-based entries
Provides context for where RSI might travel as price interacts with structural levels
Tends to perform better when markets display clear directional swings
May produce less useful output during consolidation phases with overlapping swings
Offers early visualization of potential divergence setups
Swing traders can use structure-based projections to time entries around key pivot zones
Position traders could benefit from the trend strength component when holding through larger moves
On lower timeframes, it helps scalpers identify micro-structure shifts for quick momentum plays
Useful for mapping out potential RSI behavior around breakout and breakdown levels
Day traders can combine structural projections with session highs and lows for intraday context
2. Volume-Weighted Model
This method blends multiple volume indicators to inform its price projections. It tracks On-Balance Volume to gauge cumulative buying and selling pressure, monitors the Accumulation/Distribution Line to assess where price closes relative to its range on each bar, and calculates volume-weighted returns to give heavier influence to high-volume price movements. The model examines the directional slope of these metrics to assess whether volume confirms or contradicts price direction.
Unusually high volume bars receive special attention, with their directional bias factored into projections. When all volume metrics point the same direction, the model produces more aggressive price forecasts and consequently stronger RSI movements. Conflicting volume signals lead to more muted projections, suggesting RSI may move sideways rather than trending.
▶ Practical Implications for Traders:
Suited for traders who incorporate volume confirmation into their analysis
Works best with instruments that report accurate, meaningful volume data
Useful for identifying situations where momentum lacks volume support
Less applicable to instruments with sparse or unreliable volume information
Scalpers on liquid markets can spot volume-backed momentum for quick entries and exits
Helps intraday traders distinguish between genuine moves and low-volume fakeouts
Position traders can assess whether institutional participation supports longer-term trends
Effective during news events or market opens when volume spikes often drive directional moves
Swing traders can use volume divergence in projections to anticipate potential reversals
3. Linear Regression Model
The simplest of the three methods, linear regression fits a straight line through recent price data using least-squares mathematics and extends that line forward. These projected prices then generate corresponding RSI forecasts. This creates a clean momentum projection without conditional logic or interpretation of market characteristics. The forecast simply asks: if the recent price trend continues at its current rate of change, where would RSI be in the coming bars?
▶ Practical Implications for Traders:
Delivers a clean, mathematically neutral projection baseline
Functions well during sustained, orderly trends
Involves fewer parameters and produces consistent, reproducible output
Responds more slowly when trend direction shifts
Works best in trending environments rather than ranging markets
Ideal for position traders who want to ride established trends
Useful for swing traders to gauge trend exhaustion when actual RSI deviates from linear projections
Scalpers can use the smooth output as a reference point to measure short-term momentum deviations
Effective baseline for comparing against structure or volume models to measure market complexity
Works particularly well on higher timeframes where trends develop more gradually
🟢 Universal Applications Across All Models
Regardless of which forecasting method you select, the indicator projects future RSI positions that may help with:
▶ Overbought/Oversold Planning: See whether RSI trajectories point toward extreme zones, giving you time to prepare responses before conditions develop
▶ Entry and Exit Timing: Factor projected RSI levels into your timing decisions for opening or closing positions
▶ Crossover Anticipation: Watch for projected crossings between RSI and its signal line (RSI-based MA) that might indicate upcoming momentum shifts
▶ Mean Reversion Context: When RSI sits at extremes, projections can illustrate potential paths back toward the midline
▶ Momentum Evaluation: Assess whether current directional strength appears likely to continue or fade based on projection direction
▶ Divergence Awareness: Use forecast trajectories alongside price action to spot potential divergence formations earlier
▶ Comparative Analysis: Run different projection methods and note where they agree or disagree, using alignment as an additional filter, for instance
▶ Multi-Timeframe Context: Compare RSI projections across different timeframes to identify alignment or conflict in momentum outlook
▶ Trade Management: Reference projected RSI levels when adjusting stops, scaling positions, or setting profit targets
▶ Rule-Based Systems: Incorporate projected RSI conditions into systematic trading approaches for more forward-looking signal generation
Note: It is essential to recognize that these forecasts derive from mathematical analysis of recent price behavior. Markets are dynamic environments shaped by innumerable factors that no technical tool can fully capture or foresee. The projected RSI values represent potential scenarios for how momentum might develop, and actual readings can take different paths than those visualized. Historical tendencies and past patterns offer no guarantee of future behavior. Consider these projections as one element within a comprehensive trading approach that encompasses disciplined risk management, appropriate position sizing, and diverse analytical methods. The true benefit lies not in expecting precise forecasts but in developing a forward-thinking perspective on possible market conditions and planning your responses accordingly.
Buying Opportunity Score V2.2Buying Opportunity Indicator V2.2
What This Indicator Does
This indicator identifies potential buying opportunities during market fear and pullbacks by combining multiple technical signals into a single composite score (0-100). Higher scores indicate more fear/oversold conditions are present simultaneously.
Why These Components?
Market bottoms typically occur when multiple fear signals align. This indicator combines five complementary measurements that each capture different aspects of market stress:
1. VIX Level (30 points) - Measures implied volatility/fear. VIX spikes during selloffs as traders buy protection. Thresholds based on historical percentiles (VIX 25+ is ~85th percentile historically).
2. Price Drawdown (30 points) - Distance from 52-week high. Larger drawdowns create better risk/reward for mean reversion entries. A 10%+ drawdown from highs historically presents better entry points than buying at all-time highs.
3. RSI 14 (12 points) - Classic momentum oscillator measuring oversold conditions. RSI below 30 indicates short-term selling exhaustion.
4. Bollinger Band Position (13 points) - Statistical measure of price extension. Price below the lower band (2 standard deviations) indicates statistically unusual weakness.
5. VIX Timing (15 points) - Bonus points when VIX is declining from a recent peak. This helps avoid catching falling knives by waiting for fear to subside.
How The Score Works
- Each component contributes points based on severity
- Components are weighted by predictive value from historical analysis
- Score of 70+ means multiple fear signals are present
- Score of 80+ means extreme fear across most components
How To Use
1. Apply to SPY, QQQ, or IWM on daily timeframe
2. Monitor the Current Score in the statistics table
3. Scores below 50 = normal conditions, no action needed
4. Scores 60-69 = elevated fear, monitor closely
5. Scores 70+ = consider entering long positions
6. Scores 80+ = strongest historical entry points
Important Limitations
- This is a research tool, not financial advice
- Past patterns may not repeat in the future
- Signals are infrequent (typically 2-4 per year reaching 70+)
- Works best on broad market ETFs; not validated for individual stocks
- Always use proper position sizing and risk management
- The indicator identifies conditions that have historically been favorable, but cannot predict future returns
Statistics Table
The table shows:
- Current Score with context message
- Chart Results: Rolling 1Y/3Y/5Y statistics from your loaded chart data
Alerts
Multiple alert options available for different score thresholds.
Open Source
Code is fully visible for review and educational purposes.
ATR-Normalized VWMA DeviationThis indicator measures how far price deviates from the Volume-Weighted Moving Average ( VWMA ), normalized by market volatility ( ATR ). It identifies significant price reversal points by combining price structure and volatility-adjusted deviation behavior.
The core idea is to use VWMA as a dynamic trend anchor, then measure how far price travels away from it relative to recent volatility . This helps highlight when price has stretched too far and may be due for a reversal or pullback.
How it works:
VWMA deviation is calculated as the difference between price and the VWMA.
That deviation is divided by ATR (Average True Range) to normalize for current volatility.
The script tracks the highest and lowest normalized deviations over the chosen lookback period.
It also tracks price structure (highest/lowest highs/lows) over the same period.
A reversal signal is generated when a historical extreme in deviation aligns with a price structure extreme, and a confirmed reversal candle forms.
You get visual signals and color highlights where these conditions occur.
Settings explained:
Lookback period defines how many bars the script uses to find recent extremes.
ATR length controls how volatility is measured.
VWMA length controls how the volume-weighted moving average is calculated.
Signal filters help refine entries based on price vs deviation behavior.
Display options let you customize how signals and levels appear on the chart.
This indicator is especially useful for spotting potential turning points where price has moved far from VWMA relative to volatility, suggesting possible exhaustion or overextension.
Tips for use:
Combine with broader trend context (higher timeframe support/resistance).
Use with risk management rules (position sizing, stops) — signals are guides, not guaranteed entries.
Adjust lookback and ATR settings based on your trading timeframe and asset volatility.
SVP + candle + Max volume [midst]
SVP + DALY CANDLE + MAX VOLUME
A comprehensive trading indicator that combines Session Volume Profile (SVP), Higher Timeframe (HTF) Candles, and Intrabar Max Volume Price Detection into one powerful tool. Perfect for traders who want to understand price action, volume distribution, and key levels all in one place.
KEY FEATURES
Session Volume Profile
• Real-time volume distribution across price levels for the current session
• Point of Control (POC) - identifies the price with the highest traded volume
• Value Area High (VAH) & Low (VAL) - shows where 70% of the volume occurred (customizable percentage)
• Color-coded volume bars - distinguish between up volume (bullish) and down volume (bearish)
• Value area highlighting - clearly see the most important price zones
Higher Timeframe Candle Display
• Visual daily (or custom timeframe) candle overlaid on your current chart
• OHLC labels - see Open, High, Low, and Close prices clearly marked
• Fully customizable colors - separate colors for bullish/bearish bodies, borders, and wicks
• Adjustable positioning - move the candle and labels to your preferred location
Max Volume Price Detection
• Identifies the exact price level with maximum volume within each bar
• Uses Lower Timeframe (LTF) data for precise volume analysis (Premium+ required)
• Simple mode fallback - works on all TradingView plans
• Previous max volume marker - displays previous bar's max volume as a reference dot
• Real-time calculation - updates as each bar forms
ATR Table
• Dynamic ATR-based stop levels - automatically calculates potential stop-loss levels
• Multiple smoothing methods - RMA, SMA, EMA, WMA
• Customizable multiplier - adjust for your risk tolerance
• Clean table display - shows ATR value, high stop, and low stop
PERFECT FOR
Day traders analyzing intrabar volume distribution
Swing traders wanting HTF context on lower timeframes
Volume profile traders looking for key support/resistance levels
Price action traders seeking high-probability entry zones
HOW TO USE
Volume Profile Analysis
POC often acts as a magnet for price. VAH/VAL are key support/resistance levels. High volume nodes indicate strong price acceptance, while low volume nodes suggest potential breakout zones.
HTF Candle Context
See daily range while trading on 5m-1h charts. Daily open often acts as pivot point. Daily high/low are key levels to watch.
Max Volume Price
Black line shows where most volume traded in each bar. Previous max volume (dot) helps identify institutional activity. Clusters of max volume create strong support/resistance. Can possibly indicate a Wick bounce
ATR Stops
Use ATR-based levels for logical stop placement. Adjust multiplier based on market volatility.
SETTINGS & CUSTOMIZATION
Positioning
Control the global offset to move both candle and profile together. Fine-tune with individual offsets for candle and profile spacing.
Volume Profile
Adjustable number of rows (50-500) for granular or simplified view. Customizable width and placement (left/right). Value Area percentage control. Full color customization for all volume components.
HTF Candle
Any timeframe selection (default: Daily). Full color customization for bull/bear candles. Adjustable candle width. Toggle OHLC labels on/off. Control label distance and line widths.
Max Volume Price
Choose between Simple (all plans) or LTF mode (Premium+). Auto or manual LTF resolution. Custom color and line width. Toggle current and previous markers independently.
TECHNICAL NOTES
Maximum 5000 bars lookback for volume calculations
Works on all timeframes
LTF max volume requires TradingView Premium or higher
Optimized for performance with efficient array operations
For best results, use on liquid instruments with reliable volume data
Most effective on intraday charts (5min-1hour) for day trading and scalping strategies
For Entertainment and information only
Created by midst
Volume Profile Lite [JOAT]
Volume Profile Lite — Simplified Volume-at-Price Analysis
Volume Profile Lite creates a histogram showing volume distribution across price levels using a proprietary lightweight calculation method. It identifies the Point of Control (POC), Value Area High, and Value Area Low—key concepts from auction market theory—in an optimized, easy-to-read format that won't slow down your charts.
Why This Script is Protected
This script is published as closed-source to protect the proprietary volume distribution algorithm and the optimized Value Area calculation methodology from unauthorized republishing. The specific implementation of volume allocation across price rows, the buy/sell volume separation logic, and the efficient POC detection system represents original work that provides a unique lightweight alternative to standard volume profile implementations.
What Makes This Indicator Unique
Unlike heavy volume profile indicators that can slow down charts, Volume Profile Lite:
Uses an optimized algorithm designed for performance
Separates buying and selling volume for additional insight
Provides clean visual presentation without chart clutter
Includes extending reference lines for key levels
Features a dashboard with price position relative to POC
What This Indicator Does
Distributes volume across price rows to create a visual profile histogram
Identifies the Point of Control (highest volume price level)
Calculates Value Area (where specified percentage of volume traded)
Separates buying and selling volume for each price level
Extends key levels as reference lines on the chart
Highlights the POC row with a distinct border
Core Methodology
The indicator uses a proprietary approach to volume-at-price analysis:
Price Row Division — The lookback range is divided into configurable price rows (default: 24 rows)
Volume Distribution — Each bar's volume is allocated to the price rows it touches. If a bar spans multiple rows, volume is distributed proportionally.
Buy/Sell Separation — Volume is classified based on bar direction (close >= open = buying volume, close < open = selling volume)
POC Detection — The row with maximum accumulated volume is identified as the Point of Control
Value Area Calculation — Starting from POC, expands outward (alternating up and down) until target volume percentage is captured
Key Concepts Explained
Point of Control (POC) — The price level with the highest volume concentration. Often acts as a magnet for price and represents "fair value" for the analyzed period. Price tends to return to POC.
Value Area High (VAH) — Upper boundary of the value area zone. Acts as resistance when price is below, support when price is above.
Value Area Low (VAL) — Lower boundary of the value area zone. Acts as support when price is above, resistance when price is below.
Value Area — Price range containing specified percentage (default 70%) of total volume. This is where most trading activity occurred.
Visual Features
Volume Histogram — Horizontal bars showing volume at each price level
Buy/Sell Coloring — Green portions show buying volume, red shows selling volume
POC Highlight — The POC row has a distinct orange border and fill
POC Line — Horizontal line extending from POC (optional extension to right)
Value Area Lines — Dashed blue lines at VAH and VAL
Value Area Fill — Subtle blue fill between VAH and VAL
Color Scheme
Up Volume Color — Default: #26A69A (teal) — Buying volume
Down Volume Color — Default: #EF5350 (red) — Selling volume
POC Color — Default: #FF9800 (orange) — Point of Control
Value Area Color — Default: #2196F3 (blue) — VAH/VAL lines and fill
Dashboard Information
The on-chart table (bottom-right corner) displays:
POC price level
Value Area High price level
Value Area Low price level
Current price position relative to POC (ABOVE POC, BELOW POC, or AT POC)
Distance from current price to POC as percentage
Inputs Overview
Calculation Settings:
Lookback Period — Number of bars to analyze (default: 100, range: 20-500)
Number of Rows — Price level divisions for the profile (default: 24, range: 10-50)
Value Area % — Percentage of volume for value area calculation (default: 70%, range: 50-90%)
Visual Settings:
Up/Down Volume Colors — Customizable buy/sell colors
POC Color — Point of Control highlighting
Value Area Color — VAH/VAL line and fill color
Profile Width — Visual width of histogram in bars (default: 30, range: 10-100)
Show POC Line — Toggle POC horizontal line
Show Value Area — Toggle VAH/VAL lines and fill
Show Dashboard — Toggle the information table
Extend Lines — Project POC and VA lines further right
How to Use It
For Support/Resistance:
Use POC as a potential support/resistance reference point
Price often gravitates back to POC (mean reversion)
VAH acts as resistance when approaching from below
VAL acts as support when approaching from above
For Trend Analysis:
Price above POC suggests bullish control
Price below POC suggests bearish control
Breaking out of Value Area often leads to trending moves
Returning to Value Area suggests failed breakout
For Entry/Exit:
Enter longs near VAL with stops below
Enter shorts near VAH with stops above
Target POC for mean-reversion trades
Use POC as a trailing stop reference in trends
Alerts Available
VPL Cross Above POC — Price crosses above Point of Control
VPL Cross Below POC — Price crosses below Point of Control
VPL Cross Above VAH — Price breaks above Value Area High
VPL Cross Below VAL — Price breaks below Value Area Low
Best Practices
Use longer lookback periods for more significant levels
Increase row count for more precise level identification
POC from higher timeframes is more significant
Combine with other indicators for confirmation
This indicator is provided for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management before making trading decisions.
— Made with passion by officialjackofalltrades
Price Action ICT SMC - Crypto Lidya (Lite)Price Action • ICT • SMC — Crypto Lidya (Lite)
Short title: PA Lite — Crypto Lidya
ONE CHART. ONE FLOW. TEXTBOOK PA + ICT + SMC.
This is not “more drawings”. It’s a structured, rule-based framework that merges:
Market Structure + Liquidity + Confirmation → into a single decision flow.
Core textbook sequence:
Liquidity → (IDM) → Displacement → CHoCH / BOS → Return to PD / OB / FVG / BPR
Built for traders who want clean context, multi-timeframe discipline, and professional-grade confluence
without turning the chart into a mess.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
WHAT YOU GET (HIGHLIGHTS)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
- Market Structure engine: CHoCH + BOS with configurable confirmation logic
- Liquidity context: EQH/EQL sweeps + deterministic “linking” to structure breaks
- HTF Bias (Regime Filter): optional direction gating for cleaner, textbook alignment
- TF Bias Table (Multi-TF dashboard): “at-a-glance” bias stacking with reasons
- PD Range (Premium/Discount): dealing-range alignment filter (OB / FVG or both)
- Displacement filter: impulse-quality confirmation (Body% / ATR / Close-position)
- Killzones / Sessions: time-window validation (London / NY AM / NY PM)
- FVG + BPR: imbalance mapping + balanced range overlap logic
- OB / BB engine: source models, refinement, quality filters, strength scoring, overlap pruning
- Alerts + Webhook-ready output: Human / JSON format, HTF gate, cooldown controls
“Structure + Liquidity + Confirmation in one workflow (no clutter).”
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
QUICK START (RECOMMENDED FLOW)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1) Performance
- Set Lookback Window (bars) to match your chart speed/history needs.
- View when “Lookback Window (bars)” is increased (with “Limit to Nearest” OFF / all zones visible).
- View when “Lookback Window (bars)” is decreased (with “Limit to Nearest” OFF / all zones visible).
2) Regime & Multi-TF Context (ICT)
- Enable HTF Bias if you want direction filtering.
- Use TF Bias Table to verify alignment across your chosen timeframes.
3) Timing Filter (Optional)
- Enable Killzones / Sessions to focus on high-liquidity delivery windows.
4) Confirmation Quality
- Enable Displacement filter to reduce range noise / weak breaks.
5) Structure Execution (SMC)
- Use CHoCH / BOS for the “break confirmation” layer.
- Use Buffers / Confirm Modes for stricter or faster validation.
6) Zones & Returns
- Use PD Range to validate where setups “should” form (Premium/Discount).
- Map FVG / BPR and OB / BB for return-to-zone models.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
MODULES (TEXTBOOK EXPLANATION)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1) HTF BIAS (REGIME FILTER)
HTF Bias acts as your directional framework (macro context).
When enabled, signals can be suppressed if they conflict with the HTF direction.
Two professional ways to define bias (you choose via Trend Mode):
A) Swing Structure Bias (HH/HL – LH/LL) — “stable”
- Uptrend requires HH + HL confirmation
- Downtrend requires LL + LH confirmation
- Best when you want fewer, higher-quality flips
B) Legacy / Break of Extreme — “faster”
- Bias can flip as soon as a new pivot breaks the last major extreme
- Best for aggressive / fast markets (but can be noisier)
2) TF BIAS TABLE (MULTI-TIMEFRAME DASHBOARD)
The TF Bias Table is built for disciplined multi-timeframe execution:
- Answers “Are higher TFs aligned?” in seconds
- Helps you avoid taking LTF triggers against HTF context
- Can show reasoning text (optional) to keep the logic transparent
Bias calculation options (Table Bias Mode):
- Swing Structure Bias (HH/HL – LH/LL): more stable, flips later
- Structure-Scope Bias (msStructScope aligned): follows your chosen structure scope and flips faster
Hybrid rule is deterministic:
External dominates; if External is not ready, fallback to Internal.
Provisional Bias (UI only, optional):
- If pivots are not fully confirmed, the table can display a provisional bias based on HTF candle direction
- UI only (does not change signals)
3) PD RANGE (PREMIUM / DISCOUNT)
PD Range defines where price is “dealing” relative to its midpoint (50%):
- Bullish context → Discount is preferred
- Bearish context → Premium is preferred
You can apply PD filtering to:
- OB + FVG (default), OB only, or FVG only
Optional strict mode:
- Require the level/zone to remain fully inside the dealing range (more textbook)
“Discount buys / Premium sells with a clear dealing range reference.”
4) DISPLACEMENT (IMPULSE CONFIRMATION)
Displacement filter keeps breaks “honest”.
CHoCH/BOS confirms only if the break candle shows real intent:
- Body dominance (Body% rule)
- Volatility expansion (ATR multiple rule)
- Close position in break direction (optional strictness)
This is designed to reduce fake breaks in ranges and thin-liquidity periods.
“Impulse-quality break passes; weak range poke fails.”
5) KILLZONES / SESSIONS (TIME-WINDOW VALIDATION)
Session gating is a professional timing filter:
- Validate structure breaks/sweeps only inside enabled windows
- Focus execution during high-liquidity delivery hours (London / NY AM / NY PM)
“Cleaner signals when you trade only the active delivery windows.”
- Normal vs Killzone:
6) MARKET STRUCTURE (CHoCH / BOS)
CHoCH (Change of Character):
- Signals a character shift by breaking a key protected point (optionally)
BOS (Break of Structure):
- Confirms continuation breaks in the current structure direction
Confirmation controls:
- Close / Wick / Body / combined modes
- Optional buffers (Ticks or Percent) to reduce micro-noise
Optional Protected Swing Mode:
- Uses protected HL/LH as reference (closer to classic SMC)
7) LIQUIDITY (EQH/EQL SWEEPS + LINKING)
Liquidity sweeps identify stop-runs / grabs around equal highs/lows:
- Wick Only: faster tagging
- Wick + Close Back: more textbook (grab + rejection)
Link Window (bars) ties a sweep to the next CHoCH/BOS:
- Smaller window = stricter context
- Larger window = more permissive linking
8) FVG + BPR (IMBALANCE & REBALANCE)
FVG (Fair Value Gap):
- Shows active imbalances and mitigation behavior
- Optional size filter (Percent / ATR / Ticks / Absolute)
BPR (Balanced Price Range):
- Overlap zone formed by Bull FVG + Bear FVG
- Used as a confluence zone for rebalance and continuation models
9) OB / BB (ZONES)
Order Blocks (OB):
- Anchored to BOS/CHoCH breaks or derived from displacement candles (source mode)
- Refinement modes: Body / Wick / Mean Threshold
- Optional quality filter (Balanced / Strict, etc.)
- Strength scoring + confluence bonuses (FVG overlap, liquidity context)
- Overlap pruning keeps the chart clean and relevant
Breaker Blocks (BB):
- Derived from invalidated OBs
- Can show inherited strength % (optional)
- Cleanup options preserve performance without deleting open zones
10) ALERTS (REALTIME / WEBHOOK)
- Enable Alerts: master switch
- Choose Human or JSON message format
- Optional gates: HTF Bias alignment, cooldown (anti-spam)
TradingView setup tip:
Use alert condition = “Any alert() function call” for full detail messages.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
LITE / COMMUNITY ROADMAP (IMPORTANT)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
This is the free Lite / Community release.
To keep this project sustainable and continue improving it for the community:
- This Lite edition is planned to become limited to 3 symbols in a future update (e.g., BTC / ETH / SOL).
- The full, unrestricted version (all symbols + advanced upgrades) will be released separately as the PRO edition.
You’ll always see clear release notes before major changes.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DISCLAIMERS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
- Educational / analytical tool only. Not financial advice.
- No guarantees. Always manage risk.
- “ICT / SMC” terminology is used as a category reference to commonly known concepts.
This script is not affiliated with any third-party educator or brand.
Futures Ultra CVD (Pure )Futures Ultra CVD (Pure)
Futures Ultra CVD (Pure) is a volume-driven Cumulative Volume Delta (CVD) indicator designed to expose real buying and selling pressure behind price movement. Unlike price-only indicators, this script analyzes how volume is distributed within each bar to determine whether aggressive buyers or sellers are in control, then tracks how that pressure evolves over time.
This version is intentionally pure and ungated: it does not rely on external symbols, market filters, session bias, or macro confirmation. All signals are derived strictly from price, volume, and delta behavior of the active chart, making it suitable for futures, equities, crypto, and FX.
Core Concept: How CVD Is Calculated
For each bar, volume is split into buying pressure and selling pressure using the bar’s price position:
Buying volume increases as price closes closer to the high
Selling volume increases as price closes closer to the low
The difference between buying and selling volume forms Delta:
Positive delta = net aggressive buying
Negative delta = net aggressive selling
This delta is then accumulated into Cumulative Volume Delta (CVD) using one of three user-selectable modes:
Total – running cumulative sum of all delta values
Periodic – rolling sum over a fixed lookback period
EMA – smoothed cumulative delta using an exponential average
This flexibility allows traders to choose between raw order-flow tracking or smoother, trend-like behavior depending on timeframe and instrument.
Visual Structure & Histogram Logic
The CVD is displayed as a column histogram, not a line, to emphasize momentum and pressure shifts.
Enhanced coloring provides additional context:
Brighter green/red bars indicate increasing momentum
Muted colors indicate stalling or weakening pressure
Optional footprint-style highlights appear when buy or sell volume overwhelms the opposite side by a user-defined imbalance factor
This allows traders to visually distinguish:
Strength vs weakness
Continuation vs exhaustion
Absorption and aggressive participation
Built-In Order Flow Signals
The script automatically detects and labels key order-flow events:
Strong Delta
Triggered when delta exceeds a user-defined threshold, highlighting unusually aggressive buying or selling.
Delta Surge
Detects sudden expansion in delta compared to the prior bar, often associated with breakout attempts or liquidation events.
Zero-Line Crosses
Marks transitions between net bullish and bearish participation as CVD crosses above or below zero.
CVD Continuation Logic (Trend Confirmation)
Beyond raw delta, the script evaluates CVD structure to identify continuation conditions:
A bullish continuation requires:
Positive and rising CVD
Strong buy delta
Confirmation from at least one of the following:
CVD above its EMA and SMA
Bullish price expansion
Sustained positive delta pressure
Bearish continuation follows the inverse logic.
These continuation signals are designed to confirm participation strength, not predict reversals.
Conflict Detection (Divergence Warning)
The indicator also flags conflict conditions, where:
Strong buying occurs while CVD remains negative
Strong selling occurs while CVD remains positive
These scenarios often precede failed breakouts, absorption zones, or short-term reversals and can be used as cautionary signals.
Alerts & Practical Use
All major events include built-in alerts:
Strong delta
Delta surge
CVD continuations
Zero-line crosses
Buy/sell imbalances
Conflict signals
Alerts can be set to trigger on bar close or intrabar in real time, depending on trader preference.
How Traders Typically Use This Indicator
Confirm breakouts with delta participation
Validate trends using CVD continuation instead of price alone
Identify absorption or exhaustion via conflicts and imbalances
Combine with price structure, VWAP, or market profile tools
This script is not a trading system by itself. It is a decision-support tool designed to reveal what price alone cannot: who is actually in control of the market.
On-Chart Symbols & What They Mean
This script uses a small number of visual symbols to communicate order-flow events clearly and consistently. All symbols are derived directly from the Cumulative Volume Delta calculations described above.
Δ+ (Green Up Arrow)
Strong Buy Delta
Indicates that buying pressure on the current bar exceeded the Strong Delta Threshold
Represents aggressive market buying dominating selling volume
Often appears during breakouts, trend acceleration, or initiative buying
This symbol does not imply direction by itself; it only confirms strong buyer participation.
Δ− (Red Down Arrow)
Strong Sell Delta
Indicates that selling pressure on the current bar exceeded the Strong Delta Threshold
Represents aggressive market selling dominating buying volume
Often appears during breakdowns, liquidation events, or initiative selling
Like Δ+, this symbol measures participation strength, not trade direction.
↑ (Green Label Up)
CVD Bullish Continuation
Appears when all of the following are present:
CVD is positive and increasing
Strong buy delta is detected
At least one confirmation condition is met:
CVD is above its EMA and SMA
Price shows bullish expansion
Consecutive positive delta bars (sustained buying pressure)
This symbol highlights trend continuation supported by volume, not a reversal signal.
↓ (Red Label Down)
CVD Bearish Continuation
Appears when:
CVD is negative and decreasing
Strong sell delta is detected
At least one confirmation condition is met:
CVD is below its EMA and SMA
Price shows bearish expansion
Consecutive negative delta bars (sustained selling pressure)
This indicates bearish continuation with participation confirmation.
Cyan / Orange Histogram Bars
Footprint-Style Volume Imbalance
Cyan bars indicate buy volume exceeds sell volume by the imbalance factor
Orange bars indicate sell volume exceeds buy volume by the imbalance factor
These bars highlight areas where one side is overwhelming the other, often associated with absorption, initiative moves, or failed auctions.
Bright vs Muted Histogram Colors
CVD Momentum State
Bright colors = CVD increasing in the direction of its current bias
Muted colors = CVD losing momentum or stalling
This allows quick visual identification of strengthening vs weakening participation.
Conflict Alerts (No Symbol by Default)
Delta vs CVD Disagreement
These conditions trigger alerts (but no fixed chart icon):
Strong buying while CVD remains negative
Strong selling while CVD remains positive
Conflicts often signal absorption, trap conditions, or short-term exhaustion.
Important Usage Notes
All symbols are informational, not trade entries.
Signals are calculated from price-based volume distribution, not true bid/ask data.
Results depend on the quality of volume data provided by the exchange and TradingView.
Risk Adjusted Geometric Exponent [VynthraQuant]RAGE Index (Risk-Adjusted Geometric Exponent)
Overview
The RAGE Index is a quantitative momentum oscillator that measures the efficiency and quality of an asset's price trend. Standing for Risk-Adjusted Geometric Exponent , this indicator goes beyond simple price action by evaluating the average logarithmic growth rate relative to the asset's volatility.
In institutional finance, it is not just about how much an asset moves, but how it moves. RAGE identifies trends that exhibit high compounding growth with minimal "noise" or volatility.
The Logic Behind RAGE
The indicator is built on two core quantitative pillars:
1. Geometric Exponent (GE): Instead of simple percentage changes, we calculate the geometric mean of log-returns. This represents the true compounding "velocity" of the price.
2. Volatility Normalization: We divide the GE by the standard deviation of returns (Volatility) over a specific lookback period.
How to Interpret the RAGE Index
* The Zero Line: The most critical level. When RAGE crosses above 0, the asset has entered a state of positive geometric growth. Below 0, the asset is in a state of efficient decay.
* Trend Quality: A rising RAGE value indicates that the trend is becoming more "efficient", growth is increasing while volatility is staying low or decreasing.
* Color-Coded Candles: The script features a `force_overlay` function that colors the candles on your main chart.
* Bullish Color: Efficient growth detected (Long bias).
* Bearish Color: Efficient decay detected (Short bias).
Key Features
* Logarithmic Accuracy: Uses log-returns to ensure time-additivity and eliminate the bias found in standard percentage calculations.
* Adaptive to Volatility: Unlike a standard RSI or MACD, RAGE penalizes "choppy" price action, helping you stay out of sideways markets.
* Optimized Performance: Written in Pine Script v6 with high-efficiency math to ensure fast loading even on lower timeframes.
Settings
* GE Lookback: The window used to calculate the average growth rate.
* Volatility Lookback: The window used to measure the "risk" or noise of the price action.
General Disclaimer
This indicator is for informational and educational purposes only. It does not constitute financial advice. The creator bears no responsibility for any financial decisions or losses resulting from its use. Past performance is not indicative of future results.
Islamic Disclaimer
All trading activity should be approached with awareness of halal and haram principles. Ensure your investments, instruments, and methods align with Islamic ethical standards. This tool does not promote speculative or impermissible practices.
Geometric Exponent [VynthraQuant]Overview
The Geometric Exponent is a specialized momentum and trend-strength indicator designed to quantify the average logarithmic growth rate of an asset over a specific lookback period. Unlike standard moving averages, this indicator focuses on the geometric mean of returns, providing a more accurate representation of compounded growth or decay.
By smoothing out the noise of daily price fluctuations through log-returns, the Geometric Exponent helps traders identify the underlying "velocity" of a trend.
How it Works
The indicator calculates the log-return for each bar within the user-defined GE Lookback period. It then computes the arithmetic mean of these log-returns, which mathematically represents the exponent of the geometric growth over that window.
Positive Values: Indicate a period of geometric growth (upward trend).
Negative Values: Indicate a period of geometric decay (downward trend).
Zero Line: Acts as the equilibrium point where there is no net growth.
Key Features
Log-Return Basis: Better suited for financial time series analysis than simple percentage changes, as log-returns are time-additive.
Customizable Lookback: Adjust the GE Lookback to fit your trading style, from fast-reacting scalping to long-term trend following.
Clean Visuals: An oscillator-style plot that makes it easy to spot momentum shifts and divergences.
How to Use
Trend Confirmation: Look for the Geometric Exponent to stay consistently above zero for long-term bullish trends and below zero for bearish trends.
Mean Reversion: Extreme peaks or valleys in the exponent may suggest that the current growth rate is unsustainable, potentially signaling an upcoming retracement.
Divergence: If price makes a new high but the Geometric Exponent makes a lower high, it suggests the "compounding power" of the trend is weakening.
General Disclaimer
This indicator is for informational and educational purposes only. It does not constitute financial advice. The creator bears no responsibility for any financial decisions or losses resulting from its use. Past performance is not indicative of future results.
Islamic Disclaimer
All trading activity should be approached with awareness of halal and haram principles. Ensure your investments, instruments, and methods align with Islamic ethical standards. This tool does not promote speculative or impermissible practices.
