Rolling VWAP - Clean Tunnel Bands (Consecutive Fills)Advanced Rolling Volume Weighted Average Price (RVWAP) indicator with 10 standard deviation bands arranged in clean consecutive zones without overlap.
Key Features:
• Real-time Rolling VWAP calculated over a time-based window (auto or user-defined)
• 10 deviation levels: 0.5σ to 5.0σ
• "Tunnel" visual effect: very transparent bands near VWAP, progressively more opaque toward extremes
• Consecutive fill system (no overlapping fills between bands)
• Individual control for each band: toggle visibility + independent transparency slider
• Automatic timeframe-based period or custom fixed period (Days/Hours/Minutes)
• Minimum bars protection to prevent calculation errors during market gaps and holidays
• Optional info box showing current period
Ideal for:
- Spotting extreme price deviations
- Mean reversion strategies
- Volatility analysis
- Support/resistance zone identification
- Clean visual tunnel for better readability
Based on TradingView's official "Rolling VWAP" indicator, heavily enhanced with clean consecutive fills and full per-band customization.
Recommended default transparency (higher = more transparent):
- Inner bands (0.5σ–1.5σ): 93–98
- Middle bands (2.0σ–3.0σ): 77–89
- Outer bands (3.5σ–5.0σ): 32–68
Enjoy and trade responsibly!
出来高
Last 5 Trading Days Turnover This indicator displays the last 5 trading days’ turnover in a clear table format positioned at the bottom-left of the chart.
Turnover is calculated as:
Turnover = Volume × Closing Price
All values are shown in ₹ Crores, making it easy to judge liquidity, participation, and institutional activity at a glance.
🔹 Key Features
Shows last 5 trading days only (weekends & holidays automatically excluded)
Works on any chart timeframe (data pulled from Daily candles)
Turnover displayed in ₹ Crores for easy readability
Bright, high-contrast table for quick visual scanning
Columns included:
Date
Close
Volume
Turnover (₹ Cr)
🔹 Best Use Cases
Identifying high-liquidity stocks
Confirming breakouts with volume strength
Spotting institutional participation
Filtering stocks for swing & positional trading
Useful for Indian equity markets
⚙️ Notes
Turnover is based on exchange-reported volume
Designed for clarity and minimal chart clutter
Suitable for price-action and stage-analysis traders
Worldclassedge [Patrick nill]plotshape(long, title="BUY", text="Long▲", style=shape.labelup, textcolor=color.white, size=size.auto, location=location.belowbar, color=color.green)
plotshape(short, title="SELL", text="Short▼", style=shape.labeldown, textcolor=color.white, size=size.auto, location=location.abovebar, color=color.red)
alertcondition(long, title="BUY", message="Long▲")
alertcondition(short, title="SELL", message="Short▼")
// VWAP
anchor = input.string("Session", title="Anchor Period")
MILLIS_IN_DAY = 86400000
dwmBarTime = timeframe.isdwm ? time : request.security(syminfo.tickerid, "D", time)
dwmBarTime := na(dwmBarTime) ? nz(dwmBarTime ) : dwmBarTime
var periodStart = time - time
makeMondayZero(dayOfWeek) => (dayOfWeek + 5) % 7
isMidnight(t) => hour(t) == 0 and minute(t) == 0
isSameDay(t1, t2) => dayofmonth(t1) == dayofmonth(t2) and month(t1) == month(t2) and year(t1) == year(t2)
isOvernight() => not (isMidnight(dwmBarTime) or request.security(syminfo.tickerid, "D", isSameDay(time, time_close), lookahead=barmerge.lookahead_on))
tradingDayStart(t) => timestamp(year(t), month(t), dayofmonth(t), 0, 0)
numDaysBetween(t1, t2) =>
diff = math.abs(tradingDayStart(t1) - tradingDayStart(t2))
diff / MILLIS_IN_DAY
tradingDay = isOvernight() ? tradingDayStart(dwmBarTime + MILLIS_IN_DAY) : tradingDayStart(dwmBarTime)
isNewPeriod() =>
var isNew = false
if tradingDay != nz(tradingDay )
isNew := switch anchor
"Session" => na(tradingDay ) or tradingDay > tradingDay
"Week" => makeMondayZero(dayofweek(periodStart)) + numDaysBetween(periodStart, tradingDay) >= 7
"Month" => month(periodStart) != month(tradingDay) or year(periodStart) != year(tradingDay)
"Year" => year(periodStart) != year(tradingDay)
=> false
isNew
srcVWAP = hlc3
var float sumSrc = 0
var float sumVol = 0
if isNewPeriod()
periodStart := tradingDay
sumSrc := 0
sumVol := 0
if not na(srcVWAP) and not na(volume)
sumSrc += srcVWAP * volume
sumVol += volume
vwapValue = sumSrc / sumVol
plot(vwapValue, title="VWAP", color=color.red, linewidth=3)
// =
enableCloud = input.bool(false, "Enable Cloud")
lenn = input.int(20, "Period")
mult = input.float(2.5, "StdDev Multiplier")
tc = input.int(25, "Gauge Size", minval=3)
upColor = input.color(#00ffbb, "Up Color")
downColor = input.color(#ff1100, "Down Color")
basis = ta.sma(close, lenn)
upper1 = basis + ta.stdev(close, lenn) * mult
lower1 = basis - ta.stdev(close, lenn) * mult
// TP
var int position = 0
if long
position := 1
else if short
position := -1
Volume + ATR Robust Z-Score Suite (MAD)Plots relevant volume with relevant volatility using z-core to calculta de deviations
Institutional Volume RSI [Adaptive]The Institutional Volume RSI is a next-generation momentum oscillator designed to solve the two biggest problems with standard RSI: Price Deception and Static Thresholds.
Standard RSI uses fixed 70/30 levels to define "Overbought" and "Oversold." This is flawed because in a strong institutional trend, the market can stay "Overbought" for weeks. Selling just because RSI hit 70 is a guaranteed way to lose money.
This tool fixes that.
It replaces static lines with Adaptive Volatility Bands . These bands breathe with the market—expanding during trends and contracting during squeezes—giving you a dynamic, statistically significant view of true momentum.
How It Works
The engine runs on three institutional concepts:
1. Volume-Weighted Source (VWMA) 📊
We calculate RSI based on Volume Weighted Moving Average , not just Close price.
Low Volume Move: RSI ignores it (Fakeout).
High Volume Move: RSI reacts aggressively (True Momentum).
2. Adaptive Volatility Bands 🌊
Instead of fixed lines, we use dynamic bands (similar to Bollinger Bands) applied directly to the RSI.
The Trend Ride: As long as the RSI line stays inside or above the Upper Band, the trend is strong. Do not sell.
The Squeeze: When the bands contract (get tight), it signals that volatility is dead and a massive explosive move is imminent.
3. Dynamic Sentiment Coloring 🎨
Green Line: RSI is above the baseline (Bullish Control).
Red Line: RSI is below the baseline (Bearish Control).
White Dots: These appear when RSI breaks outside the bands, signaling an extreme statistical anomaly (often a climax top or bottom).
The "Elastic Snap" Strategy
Recommended Companion: Hooke's Law: Market Elasticity
This indicator is the perfect "Trigger" for a Mean Reversion system. We recommend pairing it with a Reversal indicator (like Hooke's Law) to create a complete Setup + Trigger system.
The Strategy Rules:
1. The Setup (The Stretch) 📏
Wait for your Reversal Indicator (e.g., Hooke's Law) to identify an overextended market condition (Overbought/Oversold).
Context: The rubber band is stretched tight.
2. The Trigger (The Snap) 🔫
Do not enter blindly! Look at the IV-RSI :
For Shorts: Wait for the RSI line to turn RED . This confirms that momentum has actually rolled over.
For Longs: Wait for the RSI line to turn GREEN . This confirms that buyers have stepped in.
3. The Filter (The Safety) 🛡️
If price hits your Stop Loss level before the IV-RSI changes color, cancel the trade . This prevents you from shorting a strong trend that is simply "melting up" without volume exhaustion.
Settings & Configuration
RSI Length: Default is 14.
Source Type: VWMA (Volume Weighted) is recommended for institutional analysis.
Bands Multiplier: Default is 2.0 (Standard Deviation). Increasing this to 2.5 will make the "White Dot" extremes rarer and more significant.
Disclaimer
Trading involves a high level of risk and is not suitable for all investors. The content provided here is for educational purposes only and does not constitute financial advice. Past performance is not indicative of future results. The author (abgthecoder) is not responsible for any financial losses incurred from the use of this indicator. Always use proper risk management and never trade with money you cannot afford to lose. This tool is provided "as is" with open source code for the benefit of the trading community.
MTF Volume Profile & Signal Scanner v5The MTF Signal Scanner is a multi-timeframe trading system designed for futures trading, particularly optimized for MNQ (Micro E-mini Nasdaq-100). It combines volume profile analysis, EMA trend filtering, and a confluence scoring system to identify high-probability trade setups.
A+ Pullback & Continuation 3 ema pullback und continuation
signale buy sell nach pullback
ema müssen übereinander sein
buy sell signals after pullback
ema have to be clear
Three Green Candles Screener - % Move & Volume1️⃣ Core purpose (big picture)
The indicator identifies stocks that:
Have 2 or 3 consecutive green candles
Are above a 21-EMA (trend filter)
Have reasonable % price movement (not overextended)
Show current volume, average volume, and turnover
Show daily and weekly % price change
It’s meant for short-term momentum screening (swing / positional / breakout prep).
2️⃣ Trend filter (EMA)
ema21 = ta.ema(close, emaLength)
Uses a 21-period EMA
All buy signals require price > EMA
This avoids counter-trend setups
3️⃣ Three Green Candles logic (main signal)
threeGreen = (close > open) and (close > open ) and (close > open )
This checks for three consecutive bullish candles.
Then it calculates:
% change for each candle (open → close)
Average % change across the 3 candles
avgChg = (chg0 + chg1 + chg2) / 3
✅ 3-Green signal triggers when:
3 consecutive green candles
Average % change ≤ user-defined max (default 10%)
Price above EMA21
➡ Output:
signal = 1 // Buy flag
signal = 0 // No action
This avoids parabolic / news-spike candles.
4️⃣ Two Green Candles logic (early signal)
This is a lighter, earlier version of the same logic.
twoGreen = (close > open) and (close > open )
avgChg2 = (chg0 + chg1) / 2
✅ 2-Green signal triggers when:
2 consecutive green candles
Average % change ≤ maxAvgChange
Price above EMA21
➡ Output:
signal2 = 1 // Early momentum
This helps catch moves one day earlier than the 3-green setup.
5️⃣ Volume & liquidity context (important)
Average volume (7 days)
avgVol7 = ta.sma(volume, 7) / 1e6
Shows liquidity trend
Units: Millions of shares
Today’s volume
todayVol = volume / 1e6
Helps confirm participation
6️⃣ Turnover (Price × Volume)
priceVolCrore = (close * volume) / 1e7
Measures capital flow, not just volume
Output in ₹ Crores
Helps filter:
Low-value pump candles
Illiquid stocks
7️⃣ % price movement
Daily move
pctDay = (close - close ) / close * 100
Weekly move (5 bars)
pctWeek = (close - close ) / close * 100
These give context, not signals:
Is this early?
Is it already extended?
8️⃣ Visual outputs (what you see)
Plots (in the indicator pane)
CMP (current price)
3-Green signal (0 / 1)
2-Green signal (0 / 1)
Avg 7-day volume (M)
Today’s volume (M)
Turnover (₹ Cr)
Day % move
Week % move
This makes it usable as a visual screener.
9️⃣ Summary table (top-right)
On the latest bar only, it shows:
Field Meaning
CMP Current price
Today Vol (M) Today’s volume
Turnover (Cr) Value traded
Day / Week % Momentum context
Compact, readable, no clutter.
10️⃣ What this indicator is GOOD for
✅ Momentum stock screening
✅ Swing / positional setups
✅ Avoiding overextended candles
✅ Liquidity & capital flow validation
✅ Manual decision support
11️⃣ What it does NOT do
❌ No auto buy/sell
❌ No stop-loss or targets
❌ No relative strength vs index
❌ No intraday scalping logic
TL;DR (one-liner)
This indicator finds stocks in a healthy uptrend with 2–3 controlled bullish candles, confirms them with EMA and volume/turnover, and presents all key momentum metrics in one clean view.
Turnover Since Start of DayTurnover Since Start of Day
-- day from 24 midnight to 24 midnight
-- Sum Turnover
-- Interest at larger time frames, what part of the day do things move
Adaptive Pullbacks ML v2.5Adaptive Pullbacks ML - Context-Aware Trend Trading
Overview
Adaptive Pullbacks ML is a sophisticated trend-following tool that solves the biggest problem in pullback trading: "Is this a dip to buy, or the start of a reversal?"
Unlike standard indicators that use fixed percentages or static moving averages, this script uses a 5-Dimensional k-Nearest Neighbors (k-NN) machine learning engine to learn the specific characteristics of successful pullbacks for the asset you are trading.
The 5-Dimensional ML Engine
The market is dynamic. A pullback depth that works in a low-volatility lunch session might fail during a high-volatility news event. This indicator tracks 5 key dimensions for every pullback:
Depth (ATR Normalized): How deep is the pullback relative to volatility?
Trend Slope: Is the trend steep (parabolic) or flat (grinding)?
ADX: How strong is the directional energy?
VWAP Distance: Is price extended or close to value?
Time of Day: Is this a morning drive or an afternoon fade?
When a new pullback occurs, the k-NN engine finds the 5 most similar historical events across these dimensions and predicts the probability of success.
Core Features
1. Fractal Normalization
The indicator speaks the language of ATR (Average True Range). It doesn't care if you trade the 15-second chart or the Daily chart. A "1.5 ATR Pullback" is a statistically comparable event across all timeframes, allowing for robust, scale-invariant analysis.
2. HTF Stats Bridge (Higher Timeframe Data)
You can trade on lower timeframes (e.g., 1-minute) while using statistics derived from higher timeframes (e.g., 15-minute). This ensures your signals are based on significant market structure, not microstructure noise.
3. Smart Zones
The indicator plots dynamic "Value Zones" based on learning:
Cyan Zone (Avg Depth): The "Sweet Spot". High probability bounce area.
Yellow Zone (Sigma): The "Extension". Price is stretching elastic limits.
Red Zone (Deep): The "Danger/Opportunity". Statistical anomaly.
4. PQS & k-NN Filters
Two layers of filtering protect your capital:
PQS (Probability Qualification Score): Based on raw win-rate of the zone.
k-NN Probability: Based on similarity to past winners.
Settings Guide
Stats Timeframe: The timeframe to learn from (Leave empty for Chart).
Trend/Trigger Settings: Define what constitutes a trend for your strategy.
k-Neighbors: Number of historical twins to compare (Default: 5).
Min PQS / k-NN: Thresholds for filtering weak signals.
Disclaimer: This tool is for educational purposes. Past performance of the k-NN engine does not guarantee future results.
Adaptive ML VWAP v1.0Overview
Adaptive ML VWAP is a next-generation "Smart Indicator" that moves beyond static deviations (Standard Deviation). Instead of assuming market volatility is distributed normally (Bell Curve), this indicator uses a k-Nearest Neighbors (k-NN) machine learning engine to learn the specific volatility behavior of the asset you are trading.
It answers the question: "When price extends away from VWAP, how far does it actually go before reversing?"
The Adaptive ML Engine
This script features a 5-Dimensional ML Engine that tracks every major extension or pullback event. It records:
Deviation Depth (Normalized to ATR)
Trend Slope (Is the trend steep or flat?)
ADX (Trend Strength)
VWAP Deviation (Relative Position)
Time of Day (Session Context)
When a new setup occurs, the k-NN engine instantly searches its memory for the 5 most similar historical events and calculates the probability of success based on what happened last time.
Two Strategy Modes
You can toggle the logic to suit your trading style:
1. Mean Reversion Mode (Default)
"Fade The Move"
Goal: Catch price at an exhaustion point returning to VWAP.
Signal: Triggers when price touches a Smart Band and reverses back toward the center.
k-NN Learning: Learns which conditions favor a snap-back.
Best For: Ranging markets, Lunch hours, Choppy sessions.
2. Trend Following Mode
"Ride The Move"
Goal: Catch breakouts that are launching away from value.
Signal: Triggers when price breaks out of the Inner Band (1.0).
k-NN Learning: Learns which breakouts tend to extend to the Outer Bands.
Best For: Morning Drives, News Events, Strong Trends.
Visual Guide
The indicator uses a Dynamic Gradient system to visualize risk/reward:
Cyan Mist (0.5 - 1.0): The Value Zone. Noise area. Safe for trend entries.
Deep Cyan (1.0 - 2.0): The Trend Zone. Price is moving proactively.
Orange Glow (2.0 - 3.0): The Danger Zone. Price is statistically overextended. Reversals are highly probable here.
"Fractal" Math
Unlike standard indicators that break when you change timeframes, Adaptive ML VWAP uses Fractal Normalization.
A "2.0 Band" on a 15-second chart means the same statistical extreme as a "2.0 Band" on a 4-hour chart.
Auto-Adaptive Lookback: The indicator automatically boosts the ML memory (Lookback) on lower timeframes (seconds/minutes) where more noise requires larger sample sizes, ensuring robust predictions without manual tweaking.
Settings
Auto-Adapting Lookback: (Default: True) automatically increases Lookback to 100+ for seconds charts and 50+ for minute charts.
Lookback (Events): Manual override base value (Default: 100).
Strategy Mode: Toggle between Mean Reversion and Trend Following.
k-Neighbors: The number of similar past events to structurally compare (Default: 5).
Disclaimer: This tool is for educational purposes. Machine learning performance is dependent on market conditions and historical recursion.
VWAP Tension Bands + Osc Sigma Gap [MAXmks]Hello Traders,
This indicator started as an accident. I was building a different tool — a multi-metric dashboard — and added VWAP deviation as one of the components. I expected it to help catch falling knives. It didn't.
But I noticed something else. During cooling-off periods — when volatility fades and price just sits there, not really going anywhere — VWAP deviation on lower timeframes would start climbing quietly. And more often than not, a pullback followed. Sometimes a liquidity sweep first, then a pullback. I watched this pattern for months before deciding to build a dedicated tool around it, adding oscillator confirmation to filter the noise.
This is that tool.
The core idea
Markets act like a rubber band around VWAP — the further price stretches, the higher the tension. But raw deviation isn't enough. The real question: is momentum confirming the stretch, or lagging behind?
The σ-Gap captures when these two disagree — price pushed hard, but internals haven't caught up. That's where mean-reversion setups tend to appear.
The indicator tracks VWAP deviation across 2m / 5m / 15m simultaneously and compares it against a composite of momentum oscillators (Williams %R, CVD-based metrics). Signals require multi-timeframe consensus — no single timeframe can trigger alone.
Adaptive thresholds
What counts as "extreme" isn't fixed. Distance is measured in standard deviations (σ) , not pips or percentages — so the indicator adapts to volatility automatically. Thresholds scale with regime and historical distribution, adjusting to current market conditions in real time.
Two modes
Standard — adaptive thresholds, more signals. Good for active sessions and exploration.
High Precision — adds divergence confirmation from multiple oscillators (MFI, Delta RSI, CVD Z-Score). Fewer signals, higher selectivity.
Extreme Tension
When σ-Gap exceeds 1.6× the threshold, the indicator can fire without full confirmation. Rare, but these are the "overstretched" moments worth watching.
Filters (so you don't trade ghosts)
RVOL filter blocks signals during low activity. Session close filter avoids entries near VWAP reset. 24h volume filter skips illiquid instruments. Cooldown prevents signal clustering in the same direction.
Best use case
Built for short-term mean-reversion — quick snapback plays on 5m–15m charts where price overextends and reverts within a few candles. The engine is optimized for this rhythm, not for trend-following or swings.
On-chart
Tension Bands show dynamic threshold zones around VWAP. Signals are non-repainting and confirmed on bar close. Compact HUD displays all metrics, filter states, and signal status in real time.
Alerts
Pre-signal alerts when conditions start forming. Confirmed signal alerts with full breakdown: VWAP deviation values, σ-Gap readings, divergences detected, current mode.
Volume matters
This is a VWAP-based indicator. No volume data = no signal. If your instrument shows "No Volume" in the dashboard, switch to a data feed that provides it (crypto spot, futures, stocks with real volume).
A note on expectations
I use this logic in my own research and it has shown useful results for me in my backtesting scenarios. But this is an indicator for analysis , not a magic button. Your execution, fees, slippage, and market regime all matter. Treat signals as context, not commands. DYOR.
Feedback welcome.
For educational and analysis purposes only. Not financial advice.
Multi-Session Volume Profile [MarkitTick]💡 This comprehensive Multi-Session Volume Profile indicator offers a sophisticated, array-based approach to Auction Market Theory. By simultaneously processing Daily, Weekly, Monthly, and Custom Session profiles, it empowers traders to visualize the migration of value across multiple timeframes without the performance overhead of standard heavy profile scripts. It is designed to identify key liquidity nodes, support/resistance zones defined by volume, and the directional bias of the market through Point of Control (POC) shifts.
✨ Originality and Utility
● Multi-Dimensional Value Analysis
Unlike standard volume profiles that often restrict users to a single timeframe or require multiple instances of an indicator, this script consolidates four distinct profile calculations into a single, efficient tool. It leverages Pine Script® arrays and custom types (`VPSlot`, `VolumeProfile`) to dynamically calculate volume distribution, ensuring minimal lag while maintaining high data granularity.
● Dynamic POC Shift Tracking
A standout feature of this utility is the "Shift Analysis." The indicator does not merely plot the current Point of Control; it calculates the delta between the current session's POC and the previous session's POC. This provides immediate visual feedback on "Value Migration"—whether the market is accepting higher prices (Bullish Shift) or lower prices (Bearish Shift).
● Granular Control via Custom Types
The script utilizes a custom quantitative structure (`type VolumeProfile`) to manage raw volume, highs, lows, and volatility slots independently for each timeframe. This allows for precise "row" calculations, ensuring that the volume distribution accurately reflects price action within the specific session, rather than broad approximations.
🔬 Methodology and Concepts
● Array-Based Bucketing
The core engine relies on a "Row Size" input to divide the session's price range into horizontal buckets (slots). As new price bars form, the script distributes the bar's volume across these slots. If a bar spans multiple slots, volume is distributed proportionally; if a bar is contained within a single slot, the total volume accumulates there. This mimics a true TPO (Time Price Opportunity) calculation using volume as the weight.
● Statistical Value Area Calculation
The Value Area (VA) is determined using a standard deviation proxy. The script identifies the POC (the slot with the highest accumulated volume) and then iteratively adds the next highest volume slots above or below the POC until the total accumulated volume reaches the user-defined percentage (default 70%).
● Session Logic and Reset
The indicator employs state-logic variables (`isNewDay`, `isNewWeek`, `isNewMonth`) to detect session boundaries. Upon a boundary cross, the `reset()` method clears the arrays and initializes a new profile, while the `draw()` method finalizes the visualization of the completed session. This ensures that the lines on the chart always represent the developing or completed structure of the specific time period.
🎨 Visual Guide
The indicator renders up to four distinct profiles, each color-coded for rapid identification.
● Daily Profile (Default: Yellow)
Solid Yellow Line: Represents the Daily POC (Point of Control)—the price level with the most volume traded today.
Dashed/Dotted Yellow Lines: Represent the Value Area High (VAH) and Value Area Low (VAL).
Yellow Background Box: Highlights the 70% Value Area, showing where the bulk of the day's trading occurred.
● Weekly Profile (Default: Blue)
Solid Blue Line: The Weekly POC. Use this to gauge the medium-term trend direction.
Blue Background: Encapsulates the weekly value area. A breakout from this zone often signals a significant trend continuation.
● Monthly Profile (Default: Purple)
Solid Purple Line: The Monthly POC. This is a high-timeframe magnet level, often acting as major support or resistance.
Purple Background: Shows the macro acceptance zone for the asset.
● Custom Session Profile (Default: Cyan)
Solid Cyan Line: Tracks the POC for a specific time window (e.g., 09:30-16:00). Ideal for isolating RTH (Regular Trading Hours) from electronic sessions.
● Labels and Shift Arrows
Right-Side Labels: Display the exact price of the POC for each active profile.
Shift Indicators (▲ / ▼): Located inside the label. A "▲" indicates the current POC is higher than the previous session's POC (Value Migration Up), while "▼" indicates the opposite.
📖 How to Use
● Trend Confirmation via Value Migration
Observe the Shift Arrows in the labels. If the Daily and Weekly profiles both show "▲" (Up Shift), it confirms that value is migrating higher, suggesting a healthy uptrend. Do not short the market when value is migrating up unless price breaks below the VAL.
● Mean Reversion Trades
When price extends far away from the POC but fails to establish value (volume) at those new levels, it often reverts back to the POC. Use the POC lines as profit targets for mean reversion strategies.
● Breakout Validation
A breakout is considered valid if price closes outside the Value Area (Background Box) and volume begins to build at the new levels. If price spikes out of the VAH but quickly returns inside the box, it is a "Failed Auction," and a rotation to the VAL is probable.
● Confluence Zones
Look for price levels where the Daily POC and Weekly VAL/VAH overlap. These "clusters" of volume act as reinforced support or resistance levels.
⚙️ Inputs and Settings
● General Settings
Row Size: Determines the resolution of the profile. Higher numbers (e.g., 100) give smoother, more precise profiles but use more resources. Lower numbers (e.g., 24) are blockier but faster.
Value Area %: The percentage of total volume to include in the VA. Standard is 70.0.
Show POC Shift Analysis: Toggles the display of the ▲/▼ drift comparison.
● Profile Toggles (Daily, Weekly, Monthly, Session)
Each section has individual toggles for Show Profile , Show Value Area , and Show Background .
Start of Week Day: Allows you to define when the weekly profile resets (e.g., Sunday or Monday).
● Alert Settings
Approach Distance (Ticks): Defines how close price must get to a POC/VAH/VAL level to trigger an "Approaching" alert.
Enable Alerts: Master switch to turn on internal alert condition checks.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Auction Market Theory (AMT)
The script is grounded in Auction Market Theory, which posits that the market's primary purpose is to facilitate trade. Price advertises opportunity, and Volume records the acceptance of that opportunity. The "Value Area" represents the fair value established by buyers and sellers, while the POC represents the price of maximum consensus.
● Gaussian Distribution Application
The calculation of the Value Area at 70% is derived from the statistical properties of a Normal (Gaussian) Distribution, where approximately 68.2% of data points typically fall within one standard deviation of the mean. In this script, the POC acts as the mode (peak frequency), and the Value Area represents that first standard deviation of transactional volume.
● Volume-Price Integration
By integrating volume into price buckets (`VPSlot`), the indicator transforms two-dimensional time/price data into three-dimensional data (Time, Price, Volume). This reveals the "texture" of the market structure, distinguishing between high-volume nodes (strong acceptance) and low-volume nodes (rejection or emotional trading).
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Blockcircle Global Central Bank Balance Sheet and Money SupplyOVERVIEW
This indicator aggregates money supply (M2) and central bank balance sheet data from the world's largest economies into a single, unified view of global liquidity conditions. Rather than manually tracking dozens of separate data feeds or building your own aggregation logic, you get a ready-to-use tool that pulls from FRED, TradingView Economics, and real-time FX rates to convert everything into USD terms automatically.
Global liquidity has historically served as a leading indicator for risk assets. When central banks expand their balance sheets and the money supply grows, capital tends to flow into equities, crypto, and other risk-on assets. When liquidity contracts, markets often follow. This indicator gives you that macro context directly on your chart.
The global liquidity movement (expansionary or contractionary) often leads to asset price appreciation/depreciation in CRYPTOCAP:BTC , SP:SPX , etc
WHAT MAKES IT ORIGINAL AND DIFFERENT
Combines both M2 money supply AND central bank balance sheet data in one place, whereas most existing tools focus on only one metric
Aggregates 11 economies for M2 (USA, EU, China, Japan, UK, Canada, India, Russia, Brazil, Australia, Switzerland) and 10 central banks for balance sheet data
Automatically handles currency conversion using live FX rates so all values display in USD
Includes a dedicated US Net Liquidity calculation (Fed Balance Sheet minus Reverse Repo minus TGA) which filters out temporary distortions that other aggregate tools ignore
Provides granular country by country breakdown in the information table so you can identify which central banks are driving the aggregate trend
Offers four moving average types (SMA, EMA, WMA, RMA) for trend smoothing with configurable length
HOW IT WORKS
The indicator requests monthly M2 data from TradingView's Economics feeds for each included country. Central bank balance sheet data is pulled the same way. All non-USD values are converted using daily FX rates from major currency pairs. The script then sums these converted values to produce the Global M2 and Global CBBS lines.
For US liquidity specifically, the script pulls weekly data for the Reverse Repo Program (RRP) and Treasury General Account (TGA) from FRED. Net Liquidity is calculated as: Fed Balance Sheet minus RRP minus TGA. This formula removes funds parked in reverse repos and Treasury cash balances, showing what is actually circulating in the financial system.
KEY FEATURES
Global M2 Money Supply line tracking 11 major economies with individual toggles for each country
Global Central Bank Balance Sheet line tracking 10 central banks with individual toggles
US-specific components, including Reverse Repo, TGA, and Net Liquidity as separate plot lines
Moving average overlays with selectable type and length for identifying trend direction
Fill the option between M2 and CBBS lines to visualize the gap between money supply and central bank assets
Value labels at line endpoints showing current readings and period-over-period percentage change
Comprehensive information table with optional country breakdown view
Full color customization for all lines, configurable line width, and style options
Alert conditions for significant M2 and CBBS changes plus MA crossover signals
HOW TO USE
Add to any chart and observe the overall direction of global liquidity. Rising lines generally support risk on positioning, while declining lines suggest caution
Watch for divergences between the M2 and CBBS lines. If money supply grows faster than central bank assets, private credit may be expanding. If CBBS rises faster, central banks are actively injecting liquidity
Use the US Net Liquidity line to understand short term dollar liquidity conditions separate from longer term global trends
Enable moving averages to filter noise and identify when liquidity trends are changing direction
Toggle individual countries on or off in the settings to see how specific regions contribute to the total
Reference the information table for exact values and percentage changes without leaving your chart
SETTINGS BREAKDOWN
Table Settings: position, text size, and whether to show the country breakdown
Display Settings: toggle visibility for each line, fill area, value labels, percent labels, and the info table
Line Styling: customize colors for each metric, adjust line width, and select solid, dashed, or dotted style
Moving Average: enable or disable MA overlays for M2 and CBBS, select MA type, and set length
Global M2 Countries: individually enable or disable each of the 11 economies
US Liquidity Components: toggle RRP and TGA data
Global CBBS Countries: individually enable or disable each of the 10 central banks
Alerts: set percentage threshold for change based alerts
IMPORTANT CONSIDERATIONS
Data updates depend on the publication schedule of each source. M2 and CBBS data are typically monthly with some delay. US Fed Balance Sheet, US RRP and US TGA update weekly
FX conversion uses daily close rates which may introduce minor discrepancies during volatile currency periods
Some emerging market data may have longer reporting lags than developed market data
Hope you find it useful and impactful to your trading and investment decisions! If you have any questions at all, please just ask, happy to help
Luminous Volume Flow [Pineify]Luminous Volume Flow
The Luminous Volume Flow is a specialized volume-based momentum oscillator designed to uncover the underlying buying and selling pressure within the market. Unlike traditional volume indicators that simply aggregate volume based on the close relative to the open, LVF analyzes intrabar dynamics—specifically the relationship between the close price and the high/low wicks—to estimate the dominance of buyers or sellers.
By smoothing this raw volume delta and applying a signal line, the LVF provides a clear visual representation of volume flow, helping traders identify trend strength, potential reversals, and momentum shifts with high-definition "luminous" visuals.
Key Features
Intrabar Pressure Analysis : Calculates buying and selling pressure based on wick dynamics and price polarity to provide a more granular view of market sentiment.
Multi-Type Smoothing : Offers selectable Moving Average types (SMA, EMA, RMA) for the main Flow Line to adapt to different market volatilities.
Luminous Visuals : Utilizes dynamic color gradients that brighten as momentum expands and darken as it contracts, offering immediate visual feedback on trend intensity.
Sentiment Cloud : Fills the area between the Flow and Signal lines to clearly visualize the prevailing bullish or bearish sentiment.
High-Contrast Signals : Optional high-contrast signal markers for clear crossover identification.
How It Works
The LVF operates on a multi-stage calculation process:
Pressure Calculation : The script compares the lower wick (Close - Low) against the upper wick (High - Close).
If the lower wick is longer, it suggests buying pressure (rejection of lower prices), and volume is assigned to Buy Pressure .
If the upper wick is longer, it suggests selling pressure (rejection of higher prices), and volume is assigned to Sell Pressure .
If equal, the Close > Open polarity is used as a tie-breaker.
Raw Delta : The difference between Buy and Sell Pressure is calculated to determine the net volume flow for the bar.
Flow Line : The Raw Delta is smoothed using a user-selected Moving Average (SMA, EMA, or RMA) over the Flow Length period. This creates the main oscillator line.
Signal Line : An EMA of the Flow Line is calculated to generate the Signal Line, similar to the MACD mechanic.
Histogram : The difference between the Flow Line and Signal Line determines the Histogram, which drives the "Luminous" color gradient logic.
Trading Ideas and Insights
Trend Confirmation : When the Flow Line is above the Signal Line and the Cloud is green, the bullish trend is supported by volume. Conversely, a red cloud indicates bearish volume dominance.
Momentum Crossovers : The triangle shapes indicate crossovers between the Flow and Signal lines. A triangle up (Green) suggests a potential bullish entry or invalidation of a short bias. A triangle down (Red) suggests a bearish turn.
Expansion vs. Contraction : Pay attention to the brightness of the histogram columns. Bright colors indicate expanding momentum (a strong move), while darker, fading colors suggest the move is losing steam, potentially preceding a consolidation or reversal.
How multiple components work together
This script combines the logic of Volume Delta analysis with Signal Line Crossover mechanics (popularized by MACD). By applying trend-following smoothing to raw volume data, we transform erratic volume spikes into a coherent flow. The "Luminous" visual layer is added to make the data interpretation intuitive—removing the need to mentally calculate the rate of change based on histogram height alone.
Unique Aspects
Adaptive Gradient Coloring : The histogram doesn't just show positive/negative values; it visually communicates the *acceleration* of the move via color intensity based on standard deviation.
Wick-Based Volume Attribution : Instead of a binary close-to-open comparison, LVF respects the price action within the candle (the wicks), acknowledging that a long lower wick on a red candle can actually represent significant buying interest.
How to Use
Add the indicator to your chart.
Adjust the Flow Length to match your trading timeframe (lower for scalping, higher for swing trading).
Select your preferred Smoothing Type (EMA is default and recommended for responsiveness).
Use the "Sentiment Cloud" filter: Look for long signals only when the cloud is green, and short signals when the cloud is red.
Monitor the Luminous Histogram for signs of exhaustion (colors fading) to manage exits.
Customization
Flow Length : Period for the main smoothing (Default: 14).
Signal Length : Period for the signal line (Default: 9).
Smoothing Type : Choose between SMA, EMA, or RMA.
Colors : Fully customizable colors for Bullish/Bearish phases and signals.
Chart Bars : Option to color the main chart candles based on the Flow direction.
Conclusion
The Luminous Volume Flow is a robust tool for traders who want to go beyond price action and understand the volume dynamics driving the market. By visualizing the flow of buying and selling pressure with advanced smoothing and reactive visuals, it provides a clearer picture of market sentiment than standard volume bars.
Chaikin Oscillator Z-Score With Divergences [MAXmks]Hello Traders,
This is my take on the Chaikin Oscillator — statistically normalized into a Z-Score with built-in divergence detection.
The problem with raw Chaikin
The standard ChO is unbounded and extremely sensitive to volume spikes. A single anomalous bar can flatten the entire oscillator, making it hard to compare signals across time or between instruments.
The fix
Z-Score normalization with asinh (inverse hyperbolic sine) transformation. While standard Z-Scores assume a normal distribution, market data often features "fat tails" (extreme outliers). This transformation compresses those spikes effectively, ensuring the indicator remains responsive without getting stuck during high-volatility events. The result: a more comparable scale across instruments.
What's inside:
Adaptive normalization + EMA-based variance for smooth Z calculation
Regular and hidden divergence detection with segment validation (fewer false signals)
Gradient coloring that intensifies toward extremes
Dashboard with current Z value
Pre-built alerts for OB/OS entries/exits and all divergence types
Note: This is a volume-based indicator. No volume = no signal. If you see "No Volume Data" in the dashboard, switch to a data source that provides volume.
Works on any timeframe. Feedback welcome.
For analysis purposes, not financial advice.
Smart Money Pressure DifferentialPurpose
The Smart Money Pressure Differential (SMPD) is built to reveal the underlying tug‑of‑war between informed volume flows represented by NVI and reactive volume flows represented by PVI, using a clean statistical framework. Instead of relying on raw NVI or PVI, which drift over time and are not directly comparable, the script isolates pressure deviations by measuring how far each index moves away from its own long‑term expectation. By standardizing these deviations, SMPD produces a stable, volatility‑normalized spread that highlights accumulation, distribution, and regime transitions with far greater clarity than traditional volume indicators.
How It Works
The script computes NVI and PVI, scales them, and subtracts their EMAs to extract deviation‑from‑trend pressure, with optional WMA smoothing to reduce micro‑noise. Each deviation series is then standardized independently using rolling mean and standard deviation, ensuring both NVI and PVI operate on equal statistical footing. Their difference becomes the SMPD spread, a normalized measure of which side is exerting more pressure. A second layer applies log‑ROC to capture acceleration rather than level, and these acceleration signals can be plotted as dotted lines. Standard deviation reference levels at 0, 1, 2, and 3 provide a consistent frame for interpreting extreme pressure events.
Rationale
This architecture solves structural weaknesses found in most volume‑based tools, particularly scale drift, volatility collapse, and the instability of cumulative indicators. Standardizing before differencing prevents one index from overpowering the other, ensuring the spread reflects true pressure imbalance rather than structural bias. The log‑ROC layer adds a stable acceleration measure that avoids the distortions of classic ROC when values approach zero. The result is a regime‑independent engine, producing signals that remain comparable across assets, timeframes, and market conditions. SMPD therefore becomes a robust diagnostic tool for identifying when smart‑money pressure is building, fading, or reversing, without relying on arbitrary thresholds or bounded oscillators that distort signal strength.
Intraday Time-of-Day RVOL (histogram)intraday relative volume indicator, which can use for measuring the strength of breakout
Noise Area (TS Intraday, Custom Session + Timezone List)This indicator replicates the algorithm proposed in “Beat the Market: An Effective Intraday Momentum Strategy for the S&P 500 ETF (SPY)” by Carlo Zarattini, Andrew Aziz, and Andrea Barbon. The implementation follows the core methodology described in the paper, reproducing its intraday momentum signals and trading logic as applied to the S&P 500 ETF (SPY)
AI Academy: Volume k-NN [PhenLabs]📊 AI Academy: Volume k-NN
Version: PineScript™ v6
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📌 Description
AI Academy: Volume k-NN (Theory Edition) is an educational indicator designed to demystify how artificial intelligence pattern recognition works directly on your TradingView charts. Rather than being a black-box signal generator, this tool visualizes the entire k-Nearest Neighbors algorithm process in real-time, showing you exactly how AI identifies similar historical patterns and generates predictions.
The indicator scans up to 2,000 historical bars to find patterns that match your current price action, then uses an ensemble of the closest matches to project potential future movement. What sets this apart is the integrated “AI Grimoire”—an interactive educational book overlay that teaches core machine learning concepts through four illuminating chapters.
Whether you’re a trader curious about AI methodology or a developer learning algorithmic concepts, this indicator transforms abstract machine learning theory into tangible, visual understanding.
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🚀 Points of Innovation
• First TradingView indicator to visualize k-NN algorithm execution in real-time with full transparency
• Interactive “AI Grimoire” educational overlay teaches machine learning concepts while you trade
• Dual-mode pattern matching combines price action with optional volume confirmation
• Confidence-based opacity system visually communicates prediction reliability
• Historical match visualization shows exactly which past patterns informed the prediction
• Ghost bar projections display averaged ensemble predictions with adjustable forecast horizons
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🔧 Core Components
• Pattern Capture Engine: Converts recent price action into logarithmic returns for normalized comparison across different price levels
• k-NN Search Algorithm: Calculates Euclidean distance between current pattern and historical patterns to find closest matches
• Volume Weighting System: Optional feature that incorporates volume patterns into distance calculations with adjustable influence
• Ensemble Predictor: Averages future returns from k-nearest historical matches to generate consensus forecast
• Confidence Calculator: Measures average distance of top matches to determine prediction reliability on 0-100% scale
• AI Grimoire Display: Table-based educational overlay rendering book-style content with chapter navigation
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🔥 Key Features
• Adjustable Pattern Length: Define how many bars constitute the current pattern for matching (5-100 bars)
• Configurable Search Depth: Control how far back the algorithm searches for historical matches (500-4,900 bars)
• Flexible k-Neighbors: Select how many closest matches inform the prediction (1-20 neighbors)
• Volume Toggle: Enable or disable volume pattern matching for different market conditions
• Volume Influence Slider: Fine-tune the weight given to volume vs. price patterns (0-100%)
• Ghost Bar Count: Adjust how many future bars the indicator projects (3-15 bars)
• Minimum Confidence Filter: Set threshold to hide low-confidence predictions
• Historical Match Display: Toggle visibility of colored boxes marking source patterns
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🎨 Visualization
• Blue Scanner Box: Highlights current pattern being analyzed labeled “AI INPUT (The Prompt)”
• Green Historical Boxes: Mark past patterns where price subsequently moved bullish
• Red Historical Boxes: Mark past patterns where price subsequently moved bearish
• Ghost Bars: Semi-transparent candles projecting into the future showing predicted price path
• Confidence Label: Displays prediction confidence percentage and number of matches used
• AI Grimoire Book: Leather-bound book overlay in top-right corner with navigable chapters
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📖 Usage Guidelines
Algorithm Settings
• Pattern Length — Default: 20 | Range: 5-100 | Controls how many recent bars define the pattern. Shorter values find more matches but less specific. Longer values find fewer but more precise matches.
• Search Depth — Default: 2000 | Range: 500-4900 | Determines how many historical bars to scan. Higher values find more potential matches but increase computation time.
• k-Neighbors — Default: 5 | Range: 1-20 | Number of closest matches to use for prediction. Higher values smooth predictions but may dilute strong signals.
• Ghost Bar Count — Default: 5 | Range: 3-15 | How many future bars to project. Shorter horizons are typically more reliable.
• Use Volume Matching — Default: Off | When enabled, patterns must match on both price AND volume characteristics.
• Volume Influence — Default: 30% | Range: 0-100% | Weight given to volume pattern when volume matching is enabled.
Visualization Settings
• Bullish/Bearish Match Colors — Customize colors for historical match boxes based on outcome direction.
• Min Confidence % — Default: 60 | Predictions below this threshold will not display.
• Show Historical Matches — Default: On | Toggle visibility of source pattern boxes on chart.
Education Settings
• Select Chapter — Navigate through AI Grimoire chapters or keep book closed for clean chart view.
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✅ Best Use Cases
• Learning how k-Nearest Neighbors algorithm functions in a trading context
• Understanding the relationship between historical patterns and forward predictions
• Identifying when current market conditions resemble past scenarios
• Supplementing discretionary analysis with pattern-based confluence
• Teaching others machine learning concepts through visual demonstration
• Validating whether volume confirms price pattern formations
• Building intuition for what AI “sees” when analyzing charts
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⚠️ Limitations
• Past pattern similarity does not guarantee future outcome similarity
• Requires sufficient historical data (minimum 500+ bars) to function properly
• Computation-intensive on lower timeframes with maximum search depth
• Cannot predict truly novel “black swan” events not represented in historical data
• Volume matching less effective on assets with inconsistent volume reporting
• Predictions become less reliable as forecast horizon extends further out
• Educational overlay may obstruct chart view on smaller screens
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💡 What Makes This Unique
• Full Transparency: Unlike black-box AI tools, every step of the algorithm is visualized on your chart
• Integrated Education: The AI Grimoire teaches machine learning concepts without leaving TradingView
• Theory Meets Practice: See exactly which historical patterns inform each prediction
• Honest Uncertainty: Confidence scoring and opacity fading acknowledge when the AI “doesn’t know”
• Dual-Mode Analysis: Optional volume weighting adds institutional-quality analysis dimension
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🔬 How It Works
1. Pattern Capture: On each bar, the indicator captures the most recent price changes as logarithmic returns, creating a normalized “fingerprint” of current market behavior. If volume matching is enabled, volume changes are captured similarly.
2. Historical Search: The algorithm iterates through up to 2,000 historical bars, calculating the Euclidean distance between the current pattern fingerprint and each historical pattern. Distance combines price similarity and optional volume similarity based on weight settings.
3. Neighbor Selection: All historical patterns are ranked by similarity (lowest distance = most similar). The k-closest matches are selected as the “ensemble council” that will inform the prediction.
4. Confidence Calculation: Average distance of top-k matches determines confidence. Tighter clustering of similar patterns yields higher confidence scores, while scattered or distant matches produce lower confidence.
5. Prediction Generation: Future returns from each historical match (what happened AFTER those patterns) are averaged together. This ensemble average is applied to current price to generate ghost bar projections.
6. Visualization: Historical match locations are marked with colored boxes (green for bullish outcomes, red for bearish). Ghost bars render with opacity tied to confidence level—higher confidence means more solid bars.
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💡 Note:
This indicator is designed primarily for educational purposes —to help traders understand how AI pattern recognition algorithms function. While the predictions can supplement your analysis, they should never be used as the sole basis for trading decisions. The AI Grimoire chapters explain key concepts including why AI “hallucinates” during unprecedented market events. Always combine with proper risk management and additional confirmation.
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Apex Wallet - Real-Time Market Volume Delta & Order FlowOverview The Apex Wallet Market Volume Delta is a professional liquidity analysis tool designed to decode the internal structure of market volume. Unlike standard volume bars, this script calculates the "Delta"—the net difference between buying and selling pressure—to reveal the true conviction of market participants in real-time.
Dynamic Multi-Mode Intelligence This indicator features an adaptive calculation engine that recalibrates its internal logic based on your trading style:
Scalping: Fast-response settings (9-period MA) for immediate execution on low timeframes.
Day-Trading: Balanced settings (26-period MA) optimized for intraday sessions.
Swing-Trading: High-filter settings (52-period MA) for major trend confirmation.
Advanced Order Flow Detection
Real-Time Delta Calculation: Tracks the precise interaction between price and volume to identify aggressive buyers vs. passive sellers.
Dual Calculation Modes: Choose between "Buy/Sell" (aggressive) or "Buy/Sell/Neutral" for a more granular view of flat market periods.
Visual Delta Labels: Displays the net volume values directly above each bar, with color-coded alerts (Green for Bullish Delta, Red for Bearish Delta).
Scalable UI: Features a "Scale Down Factor" to simplify large volume numbers into readable units (10/100/1k/10k).
Key Features:
Visual Split: Clearly differentiates historical volume from real-time buying and selling flows.
Trend Confirmation: Integrated optional EMA to compare current volume surges against the average market liquidity.
Clean Interface: Professional-grade histogram styling with clear demarcation of session activity.
Apex Wallet - MTF Trend Monitor: Unified Indicator DashboardOverview The Apex Wallet MTF Trend Meter is a powerful Multi-Timeframe (MTF) dashboard designed to provide a bird's-eye view of market conditions across several time intervals simultaneously. Instead of switching between charts, this tool presents a clean, real-time table directly on your workspace, allowing you to identify high-probability trade setups through timeframe alignment.
Multi-Layered Analysis The dashboard monitors and categorizes technical data into actionable color-coded cells:
Timeframe Master Trend: Tracks the core market direction using EMA filters (adjustable for Scalping, Day, or Swing trading).
Oscillator Confluence: Instant status of Stochastic (STO), RSI, MACD, and TDI.
Andean Oscillator: Specialized tracking for market states including Bullish, Bearish, Consolidating, or Reversing.
Market Volume Delta: Real-time institutional flow tracking with customizable modes (Buy/Sell, Neutral, or Auto).
Key Features:
Fully Customizable Grid: Toggle individual timeframes (from 1m up to 4h) and specific indicators to match your trading strategy.
Smart Adaptive Presets: One-click selection for Scalping, Day-Trading, or Swing-Trading automatically updates all internal indicator periods for optimized performance.
Trend-Filtered Signals: Momentum indicators are filtered by the master trend EMA to ensure signals are displayed only when aligned with the broader market direction.
Compact UI: Designed for efficiency, the dashboard sits discreetly on your chart while providing maximum data density.
How to Use: Identify "Vertical Confluence" where multiple timeframes align with the same color, indicating a high-conviction trend continuation or breakout.
Apex Wallet - Volume Profile: Institutional POC & Value Area TooOverview The Apex Wallet Volume Profile is a professional-grade institutional analysis tool designed to reveal where the most significant trading activity has occurred. By plotting volume on the vertical price axis, it identifies key liquidity zones, value areas, and market fair value, which are essential for order flow trading and identifying high-probability support and resistance.
Dynamic Multi-Mode Engine This script features an intelligent adaptive lookback system that automatically adjusts based on your timeframe and trading style:
Scalping: Fine-tuned for 1m to 15m charts, focusing on immediate liquidity.
Day-Trading: Optimized for intraday sessions from 5m to 1h timeframes.
Swing-Trading: Deep historical analysis for 1h up to daily charts.
Institutional Data Points
Point of Control (POC): Automatically identifies and highlights the price level with the highest total volume.
Value Area (VAH/VAL): Calculates the range where 70% (customizable) of the volume occurred, representing the "Fair Value" of the asset.
HVN & LVN Detection: Spots High Volume Nodes (significant support/resistance) and Low Volume Nodes (rejection zones).
Delta Visualization: Toggle between Bullish, Bearish, or Total volume distribution for precise buy/sell pressure analysis.
Professional UI The profile is rendered with high-fidelity histograms that can be offset to avoid overlapping with price action. It features clear labels and dashed levels for institutional markers, ensuring a clean and actionable workspace.
