Point of Control (POC)**Point of Control (POC) Indicator**
This indicator identifies the price level where the most trading volume occurred over a specified lookback period (default: 365 days). The POC represents a significant support/resistance level where the market found the most acceptance.
**Key Features:**
- **POC Line**: Bright green horizontal line showing the highest volume price level
- **Volume Profile Analysis**: Divides price range into rows and calculates volume distribution
- **Value Area (Optional)**: Shows VAH and VAL levels containing 70% of total volume
- **Customizable**: Adjust lookback period, price resolution, colors, and line width
**How to Use:**
- POC acts as a magnet - price often returns to test these high-volume levels
- Strong support/resistance zone where significant trading activity occurred
- Useful for identifying key price levels for entries, exits, and stops
- Higher lookback periods (365 days) show longer-term significant levels
**Settings:**
- Lookback Period: Number of bars to analyze (default: 365)
- Price Rows: Calculation resolution - higher = more precise (default: 24)
- Toggle Value Area High/Low for additional context
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Hacim
Prev 1-Min Volume • 5% Max Shares (TTP-ready)💡 Overview
This tool was built to help Trade The Pool (TTP) traders comply with the new “5% per minute volume” rule — without needing to calculate anything manually.
It automatically tracks the previous 1-minute volume, calculates 5% of it, and compares that to your planned order size.
If your planned size is within the limit, it shows green ✅.
If you’re above, it flashes red 🚫.
And when liquidity spikes allow for more size, you’ll see a green glow and 🔔 alert — so you can size up confidently without breaking the rule.
⚙️ Features
✅ Auto-calculates 5% volume cap from the previous 1-min candle
✅ Displays previous volume, max allowed shares, and your planned size
✅ TTP “different volume” scaling option (e.g. 0.69 for 45M vs 65M real volume)
✅ Per-bar slice suggestion for 10s scalpers
✅ Corner selector (top-left, top-right, bottom-left, bottom-right)
✅ Visual glow and 🔔 alert when liquidity window opens
✅ Compact and real-time responsive on 10s charts
RSI + MFIRSI and MFI combined, width gradient fields if OS or OB, shows divergences separate for wicks and bodies, shows dots when mfi and rsi oversold at the same time.
VWAP-Y&T (P)This indicator will give you VWAP - Volume Weighted Average Price for Today (Current Day) and Yesterday (Previous Day)
Enjoy and Trade Responsibly!!
FluidTrades - SMC Lite - AlertsThe FluidTrades - SMC Lite indicator has been fixed, now you can send notifications when price levels are indicated.
Balanced Delta Volume Profile (Zeiierman)█ Overview
Balanced Delta Volume Profile (Zeiierman) builds a vertical, price-by-price profile that blends total participation with balance quality. Instead of plotting raw volume alone, it weights each price bin by:
how balanced buyers vs. sellers were,
how compressed price was inside that bin,
how often price revisited it.
The result spotlights fair value and acceptance zones while still revealing momentum/imbalance areas—ideal for reading rotation vs. trend, continuation vs. exhaustion, and the prices that truly matter.
Highlights
Balanced score that fuses delta symmetry, price compression, and hit frequency.
Optional heat spectrum for instant read of participation density and balance strength.
POC-like auto highlight of the dominant price level within the lookback window.
Works across timeframes for session profiling, swing context, or regime shifts.
█ How It Works
⚪ Profile Construction
The script scans a fixed History Length and divides the full high–low span into Bin Count price bins. For every bar in the window, its volume is proportionally distributed across the bins it overlaps, so wide-range bars contribute across multiple bins, while narrow bars concentrate where they traded most. This yields per-bin totals for:
Total Volume (participation)
Positive / Negative Volume (up vs. down bar contribution)
Hit Count (how often price touched the bin)
Average Price Range (mean bar range inside the bin; a proxy for compression)
⚪ Delta & Direction
For each bin, delta symmetry is measured via the ratio of |pos − neg| to total volume. Bins with balanced two-sided flow score higher than one-sided, runaway bins. This curbs the tendency of raw volume profiles to over-reward impulsive bursts.
⚪ Balance Score
Each price bin gets a balance score that multiplies three normalized components:
Delta Balance: rewards bins where buy/sell pressure is symmetrical (configurable via Volume Momentum Weight).
Price Compression: rewards bins where average bar range is relatively small (configurable via Price Momentum Weight).
Durability: rewards bins revisited often (configurable via Hits Weight).
A Min Hits Filter removes flimsy, single-touch bins from dominating the score. The profile can display pure totals or Average Mode (Vol/Hit) to compare bins fairly when hit counts differ.
⚪ Display & Heat Spectrum
The final plotted bar length per bin is the display volume (total or average) weighted by the balance score and normalized to 100.
POC-like Highlight: The 100% bin is outlined (and labeled) when Highlight Max Volume Bin is ON.
Heat Spectrum (optional): A background gradient scales with normalized bar length and balance hue.
Balance Hue: Interpolates between Balance Low/High Colors so high-balance bins visually pop as “accepted value.”
█ How to Use
The profile is effectively a map of price acceptance:
High, bright bars = strong participation at balanced prices → fair value/rotation zones.
Thin, muted bars = poor acceptance → imbalance or transition areas.
POC-style level = most influential price in the lookback window.
⚪ Find Fair Value & Acceptance
Thick, high-balance bins mark value. Expect rotation: price often revisits or oscillates around these areas. They’re prime zones for mean-reversion fades, scale-ins, and risk-defined trades against the edges.
⚪ Identify Imbalance & Funnels
Low-balance, low-hit bins often act like air pockets—price can move through them quickly. These zones are helpful for continuation trades into thin areas or for timing breakout pulls back into acceptance.
⚪ POC Dynamics
When price leaves the POC and returns, watch for re-acceptance (price comes back into the POC or high-balance zone and stays there.) vs. rejection (trend continuation away from value). The auto-highlight makes this quick to judge.
█ Settings
History Length – Bars scanned for the profile. Longer = broader context, slower to adapt.
Bin Count – Vertical resolution of bins between the window’s min and max price.
Display Shift – Offsets the rendering rightward for clarity.
Average Mode (Vol/Hit) – ON uses average volume per visit; OFF uses total volume.
Volume Momentum Weight – Emphasizes two-way flow; higher values favor balanced bins over one-sided deltas.
Price Momentum Weight – Emphasizes compression; higher values favor narrow-range, coiling price action.
Hits Weight – Rewards bins revisited often; higher values favor durable acceptance.
Min Hits Filter – Minimum visits a bin needs to qualify for the balance score.
Show Heat Spectrum – Background gradient for quick read of density and balance.
Highlight Max Volume Bin – Outline + raw volume label for the dominant bin.
Max Volume Color – Color used for that highlight.
Balance Low/High Colors – Gradient endpoints for balance hue across the profile.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Daily Range Zone This indicator shows the daily range (high to low) for each day.
Every day has its own unique color, making it easy to see each day’s price range at a glance.
Weis Wave Volume MTF 🎯 Indicator Name
Weis Wave Volume (Multi‑Timeframe) — adapted from the original “Weis Wave Volume by LazyBear.”
This version adds multi‑timeframe (MTF) readings, configurable colors, font size, and screen position for clear dashboard‑style display.
🧠 Concept Background — What is Weis Wave Volume (WWV)?
The Weis Wave Volume indicator originates from Wyckoff and David Weis’ techniques.
Its purpose is to link price movement “waves” with the amount of traded volume to reveal how strong or weak each wave is.
Instead of showing bars one by one, WWV accumulates the total volume while price keeps moving in the same direction.
When price direction changes (up → down or down → up), it:
Finishes the previous wave volume total.
Starts a new wave and begins accumulating again.
Those wave volumes help traders see:
Effort vs Result: Big volume with small price move ⇒ absorption; low volume with big move ⇒ weak participation.
Trend confirmation or exhaustion: High volume waves in trend direction strengthen it, while low‑volume waves hint exhaustion.
⚙️ How this Script Works
Trend & Wave Detection
Compares close with the previous bar to determine up or down movement (mov).
Detects trend reversals (when mov direction changes).
Builds “waves,” each representing a continuous run of bars in one direction.
Volume Accumulation
While price keeps the same direction, the script adds each bar’s volume to the running total (vol).
When direction flips, it resets that total and starts a new wave.
Multi‑Timeframe Computation
Calculates these wave volumes on three timeframes at once, chosen dynamically:
Active Chart Timeframe Displays WWV for:
1 min 1 min
5 min 5 min
15 min 15 min
Any other Chart TF
It uses request.security() to pull each timeframe’s latest WWV value and current wave direction.
Visual Output
Instead of plotting histogram bars, it shows a table with three numeric values:
WWV (1): 25.3 M | (15): 312 M | (240): 2.46 B
Each value is color‑coded:
user‑selected Uptrend Color when price wave = up
user‑selected Downtrend Color when wave = down
You can position this small table in any corner/center (top / bottom × left / center / right).
Font size is user‑adjustable (Tiny → Huge).
📈 How Traders Use It
Quickly gauge buying vs selling effort across multiple horizons.
Compare short‑term wave volume to higher‑timeframe waves to spot:
Alignment → all up and big volumes = strong trend
Divergence → small or opposite‑colored higher‑TF wave = potential reversal or pause
Combine with Wyckoff, VSA, or standard trend analysis to judge if a breakout or pullback has real participation.
🧩 Key Features of This Version
Feature Description
Multi‑Timeframe Panel Displays WWV values for 3 selected TFs at once
Dynamic TF Mapping Auto‑adjusts which TFs to use based on chart
Up/Down Color Coding Customizable colors for wave direction
Adjustable Font and Placement Set font size (Tiny→Huge) and screen corner/center
No Histograms Keeps chart clean; acts as a compact WWV dashboard
Volume VisionVolume Vision is a precision volume-analysis system that exposes how trading activity is distributed inside the current market range.
It divides the active price structure into three live zones — Top, Middle, and Bottom — and measures where real participation is concentrated.
This creates a dynamic “volume map” that allows you to instantly see whether the market is being driven by accumulation, distribution, or equilibrium.
At the heart of the indicator is a fully original implementation of the FGI — a proprietary composite metric designed to read market emotion and internal pressure.
It transforms several hidden components — volume, volatility, dominance, and directional momentum — into one unified curve of sentiment.
FGI values around 30 typically reflect phases of fear, capitulation, and potential accumulation.
Values near 80 mark conditions of greed, overextension, and possible distribution.
Observing these boundaries helps detect when the market is preparing to shift from compression to expansion or from euphoria to cooling.
Core Functions
Density Zones: Splits recent price movement into Top / Mid / Bottom areas, quantifying volume within each.
Dominant Zone: Highlights where the major share of liquidity currently resides.
Pressure Meter: Shows the balance between buy and sell volume in real time.
Volume Index: Normalizes present volume activity against its historical range to spot abnormal behaviour.
FGI Reading: Custom sentiment curve ranging from fear (≈ 30) to greed (≈ 80).
Alerts: Optional signals for High Volume and Rising Volume moments.
Dashboard: Compact on-chart table that summarizes all key readings without cluttering the view.
Interpretation Guide
When FGI drops near 30, the market often forms accumulation bases or bottom structures.
When FGI climbs toward 80, momentum usually reaches its limit and profit-taking or distribution begins.
A dominant Top zone with strong sell pressure indicates distribution, while Bottom dominance with buy pressure suggests accumulation.
Mid-zone dominance with neutral FGI reflects balance — a state of indecision before the next move.
Watch for volume spikes accompanied by FGI shifts: these often precede major impulse starts or ends.
Style: non-repainting core, minimal visuals, real-time clarity.
Created for traders who need to see where the energy is flowing, not just what price is printing.
by MahaTrend
Vwap Daily By SamsungTitle
Daily VWAP with Historical Lookback (Logic Fix)
Description
This script calculates and plots the daily Volume-Weighted Average Price (VWAP), an essential tool for intraday traders.
What makes this indicator special is its robust plotting logic. Unlike many simple VWAP scripts that struggle to show data for previous days, this version includes a crucial fix that allows you to reliably display historical VWAP lines for as many days back as you need. This allows for more comprehensive backtesting and analysis of how price has interacted with the VWAP on previous trading days.
This is an indispensable tool for traders who use VWAP as a dynamic level of support/resistance, a benchmark for trade execution quality, or a gauge of the day's trend.
Key Features
Historical VWAP Display: Easily plot VWAP for multiple past days on your chart. Simply set the number of lookback days in the settings.
Accurate Daily Calculation: The VWAP calculation correctly resets at the beginning of each new trading session (00:00 server time).
Fully Customizable: You have full control over the appearance of the VWAP line, including its color, width, and style (Solid or Stepped).
Robust Plotting Engine: This script solves the common Pine Script issue where conditionally plotted historical lines fail to render. It works reliably on all intraday timeframes.
Built-in Debug Mode: For advanced users or those curious about the inner workings, a comprehensive debug mode can be enabled to display raw VWAP values, cumulative volume, and timeframe warnings.
How to Use
Add the "Daily VWAP with Historical Lookback" indicator to your chart.
IMPORTANT: Make sure you are on an intraday timeframe (e.g., 1H, 30M, 15M, 5M, 1M). This indicator is designed for intraday analysis and will display a warning if used on a daily or higher timeframe.
Open the indicator's settings.
In the "VWAP Settings" tab, adjust the "Lookback Days to Display" to set how many previous days of VWAP you want to see. (e.g., 0 for today only, 1 for today and yesterday, 10 for the last 10 days).
Customize the line's appearance in the "Line Style" tab.
The "Logic Fix" Explained (For Developers)
A common challenge in Pine Script is conditionally plotting data for historical bars. Many scripts attempt this by dynamically changing the plot color to na (transparent) for bars that shouldn't be displayed. This method is often unreliable and can result in the entire plot failing to render.
This script employs a more robust and standard approach: manipulating the data series itself.
The Problem: plot(vwap, color = shouldPlot ? color.red : na) can be buggy.
The Solution: plot(shouldPlot ? vwap : na, color = color.red) is reliable.
Instead of changing the color, we create a new data series (plotVwap). This series contains the vwapValue only on the bars that meet our date criteria. On all other bars, its value is na (Not a Number). The plot() function is designed to handle na values by simply "lifting the pen," creating a clean break in the line. This ensures that the VWAP is drawn only for the selected days, with 100% reliability across all historical data.
Settings Explained
Lookback Days to Display: Sets the number of past days (from the last visible bar) for which to display the VWAP.
Line Color, Width, and Style: Standard cosmetic settings for the VWAP line.
Enable Debug Mode (Master Switch): Toggles all debugging features on or off. It is enabled by default to help new users.
Display Debug: Cumulative Volume: When enabled, it shows the daily cumulative volume in a gray area on a separate pane.
Display Debug: Raw VWAP Value: When enabled, it plots the raw, unfiltered VWAP calculation for all days on the chart, helping to verify the core logic.
This script is provided for educational and informational purposes. Trading involves significant risk. Always conduct your own research and analysis before making any trading decisions.
If you find this script useful, a 'Like' is always appreciated! Happy trading
FTI - AnalyticaFlow Trend Index (FTI) – Analytica
The Flow Trend Index (FTI) – Analytica combines momentum, trend, and volatility into a data-driven analytical view — displayed directly on your chart and candlesticks.
It builds on the FTI-Core foundation by revealing the numerical values behind each visual element — turning market flow, into measurable insight.
Analytica shows how strongly the market is moving (flow), where its adaptive baseline lies (trend), and how far price has stretched from equilibrium (volatility).
This deeper layer helps analysts interpret when the market is gaining strength, losing momentum, or shifting direction, and especially when conditions are overbought or oversold.
• Smoothed RSI (Heikin-Ashi Powered)
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Transforms RSI into color-coded candles with visible RSI values.
Heikin-Ashi smoothing filters noise, exposing authentic momentum and exhaustion levels.
-See and measure momentum simultaneously.
• McGinley Dynamic Line
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Adaptive moving average that adjusts speed to market volatility.
In Analytica, you can view the exact McGinley value and Δ % distance from price, providing a real-time sense of stretch or compression.
→ Quantifies rhythm between trend and pause.
• FIBB Cloud (Fibonacci ATR Bands)
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• Analytical Enhancements
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RSI Number Overlay on each candle (live values)
Analytical Table showing RSI · McGinley · Δ % vs McGinley
Custom Advanced RSI Ranges for precise zone control
Adjustable themes, text size, and line style
See it. Measure it. Understand it.
In short:
FTI-Analytica merges visual flow and analytical depth.
It reveals the true numerical forces behind each move —
FTI – Analytica shows the true numerical information behind each Data point.
No signals or alerts are generated — the indicator is intended solely for visualization, study, and educational purposes.
© Zyro Trades. All rights reserved.
Zyro™ and FTI™ are unregistered trademarks of Zyro Trades.
Volume-Price Shift Box (Lite Version)Description
This indicator is a clean and intuitive visual tool designed to help traders quickly assess the current balance of bullish and bearish forces in the market.
It combines volume, price movement, VWAP, and OBV dynamics into a compact on-chart table that updates in real time.
This version focuses on the core logic and visualization of momentum and volume shifts, making it ideal for traders who want actionable insight without complex configuration.
How It Works
The script measures the combined strength of multiple market components:
VWAP trend indicates price bias relative to fair value.
OBV (On-Balance Volume) tracks volume flow to confirm or contradict price movement.
Volume ratio compares current volume to its recent average.
Momentum evaluates directional price movement over a configurable lookback period.
Accumulation / Distribution (A/D) Line estimates buying or selling pressure within each candle:
↑ — A/D is rising (buying pressure is increasing)
↑↑ — A/D is rising faster than before (acceleration of buying)
↓ — A/D is falling (selling pressure is increasing)
↓↓ — A/D is falling faster than before (acceleration of selling)
Each of these components contributes to an overall shift score.
Depending on this score, the box displays:
🟢 Bullish Shift — strong upward alignment
🔴 Bearish Shift — downward alignment
⚪ Neutral — mixed or indecisive conditions
Key Features
Compact on-chart information box with color-coded parameters
Combined volume-price relationship model
Configurable lookback and sensitivity controls
Real-time shift strength and trend duration tracking
Adjustable EMA/SMA smoothing for all averages
Lightweight design optimized for clarity
Inputs Overview
Box Position / Size – Place and scale the on-chart info box
Lookback Period – Number of bars used for calculations
VWAP Lookback – Period for VWAP distance smoothing
Shift Sensitivity – Adjusts reaction strength of bullish/bearish shifts
Neutral Zone Threshold – Defines when the market is considered neutral
EMA or SMA – Choose exponential or simple moving averages
Component Weights – Set the influence of VWAP, OBV, Volume, and Momentum on the shift score
Display Toggles – Enable or disable metrics shown in the box (Strength, Volume, VWAP, Duration, OBV)
How to Use
Apply the indicator to any symbol and timeframe.
Observe the box on the chart — it updates dynamically.
Look for transitions between Neutral → Bullish or Neutral → Bearish shifts.
Combine with your existing price action or confirmation tools (e.g., support/resistance, trendlines).
Use the “Strength” and “Duration” values to assess consistency and momentum quality.
(This indicator is not a buy/sell signal generator — it is designed as a contextual analysis and confirmation tool.)
How It Helps
Merges several key volume and price metrics into a single view
Highlights transitions in market control between buyers and sellers
Reduces clutter by presenting only relevant context data
Works on any market and timeframe, from scalping to swing trading
⚠️Disclaimer:
This script is provided for educational and informational purposes only. It is not financial advice and should not be considered a recommendation to buy, sell, or hold any financial instrument. Trading involves significant risk of loss and is not suitable for every investor. Users should perform their own due diligence and consult with a licensed financial advisor before making any trading decisions. The author does not guarantee any profits or results from using this script, and assumes no liability for any losses incurred. Use this script at your own risk.
FTI - CoreFlow Trend Index (FTI) - Core
The Flow Trend Index (FTI) combines momentum, trend, and volatility into a single adaptive visual layer.
It measures how strongly the market is moving (flow), where its fair-value baseline lies (trend), and showing signs of exhaustion.
This unified view helps analysts — especially beginners — instantly recognize when the market is gaining strength, losing momentum, or shifting direction, and especially when conditions are overbought or oversold.
- Smoothed RSI (Heikin-Ashi Powered)
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Transforms RSI into color-coded candles. Heikin-Ashi smoothing filters noise, revealing true momentum waves and exhaustion points — less lag, more authenticity.
→ See momentum, not just numbers.
- McGinley Dynamic Line
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An adaptive moving average that breathes with market speed — faster in rallies, slower in chop. Zyro’s version is tuned for volatile assets like BTC or NAS100.
→ Tracks rhythm between trend and pause.
- FIBB Cloud (Fibonacci ATR Bands)
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Volatility envelope built from ATR × Fibonacci ratios. Expands and contracts with real market energy, mapping zones of pressure and release.
→ Shows where price stretches or resets.
In short:
FTI-Core visualizes market flow — blending momentum, trend, and volatility into one adaptive system.
No signals or alerts are generated — the indicator is intended solely for visualization, study, and educational purposes.
© Zyro Trades. All rights reserved.
Zyro™ and FTI™ are unregistered trademarks of Zyro Trades.
Candlestick StrengthThis indicator quantifies the “energy” of each candlestick by combining its height (high–low span), trading volume, and internal structure (body vs. wick proportions). It provides a numeric measure of how strongly each candle contributes to market momentum, allowing traders to distinguish meaningful price action from indecision or noise.
Concept
Every candlestick represents a short-term contest between buyers and sellers. Large candles with significant volume indicate strong market participation, while small or low-volume candles suggest hesitation or absorption. Candlestick Strength captures this by calculating a normalized measure of each candle’s energy relative to recent activity, making it comparable across different market conditions and timeframes.
The indicator also analyzes the candle’s internal structure:
The body reflects net directional movement.
The wicks represent back-and-forth price traversal within the candle. Because wick movement does not fully contribute to directional momentum, it is weighted at half the body’s contribution. This ensures the indicator emphasizes sustained directional pressure while still acknowledging rejection or absorption.
Interpretation
High values indicate candles with energy above recent averages — suggesting expanding momentum and strong directional intent.
Average values reflect typical candle activity, representing neutral or steady market behavior.
Low values suggest weak candles — either the market is pausing, consolidating, or momentum is fading.
The outputs are displayed as a symmetric histogram: bullish candle energy is shown in green above zero, bearish energy in red below zero, with ±1 reference lines marking the normalized average energy level.
Usage
Combine with trend analysis, swing highs/lows, or volume-weighted averages to validate breakouts or trend continuation.
Monitor for divergence between price movement and candle energy to identify exhaustion, absorption, or potential reversals.
Filter out false momentum signals caused by narrow-range or low-volume candles.
Adaptable across timeframes: normalized energy allows comparison between small and large timeframe candles.
ATR x Trend x Volume SignalsATR x Trend x Volume Signals is a multi-factor indicator that combines volatility, trend, and volume analysis into one adaptive framework. It is designed for traders who use technical confluence and prefer clear, rule-based setups.
🎯 Purpose
This tool identifies high-probability market moments when volatility structure (ATR), momentum direction (CCI-based trend logic), and volume expansion all align. It helps filter out noise and focus on clean, actionable trade conditions.
⚙️ Structure
The indicator consists of three main analytical layers:
1️⃣ ATR Trailing Stop – calculates two adaptive ATR lines (fast and slow) that define volatility context, trend bias, and potential reversal points.
2️⃣ Trend Indicator (CCI + ATR) – uses a CCI-based logic combined with ATR smoothing to determine the dominant trend direction and reduce false flips.
3️⃣ Volume Analysis – evaluates volume deviations from their historical average using standard deviation. Bars are highlighted as medium, high, or extra-high volume depending on intensity.
💡 Signal Logic
A Buy Signal (green) appears when all of the following are true:
• The ATR (slow) line is green.
• The Trend Indicator is blue.
• A bullish candle closes above both the ATR (slow) and the Trend Indicator.
• The candle shows medium, high, or extra-high volume.
A Sell Signal (red) appears when:
• The ATR (slow) line is red.
• The Trend Indicator is red.
• A bearish candle closes below both the ATR (slow) and the Trend Indicator.
• The candle shows medium, high, or extra-high volume.
Only one signal can appear per ATR trend phase. A new signal is generated only after the ATR direction changes.
❌ Exit Logic
Exit markers are shown when price crosses the slow ATR line. This behavior simulates a trailing stop exit. The exit is triggered one bar after entry to prevent same-bar exits.
⏰ Session Filter
Signals are generated only between the user-defined session start and end times (default: 14:00–18:00 chart time). This allows the trader to limit signal generation to active trading hours.
💬 Practical Use
It is recommended to trade with a fixed risk-reward ratio such as 1 : 1.5. Stop-loss placement should be beyond the slow ATR line and adjusted gradually as the trade develops.
For better confirmation, the Trend Indicator timeframe should be higher than the chart timeframe (for example: trading on 1 min → set Trend Indicator timeframe to 15 min; trading on 5 min → set to 1 hour).
🧠 Main Features
• Dual ATR volatility structure (fast and slow)
• CCI-based trend direction filtering
• Volume deviation heatmap logic
• Time-restricted signal generation
• Dynamic trailing-stop exit system
• Non-repainting logic
• Fully optimized for Pine Script v6
📊 Usage Tip
Best results are achieved when combining this indicator with additional technical context such as support-resistance, higher-timeframe confirmation, or market structure analysis.
📈 Credits
Inspired by:
• ATR Trailing Stop by Ceyhun
• Trend Magic by Kivanc Ozbilgic
• Heatmap Volume by xdecow
Open=Low Multi-Signal EnhancedPower your trades with all new Open = Low with tolerance added in the price. This script will give Open = Low and also if slight deviation in the Open = Low with rising volume and rising momentum in the price.
High Volume Vector CandlesHigh Volume Vector Candles highlights candles where trading activity significantly exceeds the average, helping you quickly identify powerful moves driven by strong volume.
How it works:
- The script calculates a moving average of volume over a user-defined period.
- When current volume exceeds the chosen threshold (e.g. 150% of the average), the candle is marked as a high-volume event.
- Bullish high-volume candles are highlighted in blue tones, while bearish ones are shown in yellow, both with adjustable opacity.
This visualization makes it easier to spot potential breakout points, absorption zones, or institutional activity directly on your chart.
Customizable Settings:
• Moving average length
• Threshold percentage above average
• Bullish/Bearish highlight colors
• Opacity level
Ideal for traders who combine price action with volume analysis to anticipate market momentum.
Retail vs Banker Net Positions – Symmetry BreakRetail vs Banker Net Positions – Symmetry Break (Institution Focus)
Description:
This advanced indicator is a volume-proxy-based positioning tool that separates institutional vs. retail behavior using bar structure, trend-following logic, and statistical analysis. It identifies net position flows over time, detects institutional aggression spikes, and highlights symmetry breaks—those moments when institutional action diverges sharply from retail behavior. Designed for intraday to swing traders, this is a powerful tool for gauging smart money activity and retail exhaustion.
What It Does:
Separates Volume into Two Groups:
Institutional Proxy: Volume on large bars in trend direction
Retail Proxy: Volume on small or counter-trend bars
Calculates Net Positions (%):
Smooths cumulative buying vs. selling behavior for each group over time.
Highlights Symmetry Breaks:
Alerts when institutions make statistically abnormal moves while retail is quiet or doing the opposite.
Detects Extremes in Institutional Activity:
Flags major tops/bottoms in institutional positioning using swing pivots or rolling windows.
Retail Sentiment Flips:
Marks when the retail line crosses the zero line (e.g., flipping from net short to net long).
How to Use It:
Interpreting the Two Lines:
Aqua/Orange Line (Institutional Proxy):
Rising above zero = Net buying bias
Falling below zero = Net selling bias
Lime/Red Line (Retail Proxy):
Green = Retail buying; Red = Retail selling
Watch for crosses of zero for sentiment shifts
Spotting Symmetry Breaks:
Pink Circle or Background Highlight =
Institutions made a sharp, outsized move while retail was:
Quiet (low ROC), or
Moving in the opposite direction
These often precede explosive directional moves or stop hunts.
Institutional Extremes:
Marked with aqua (top) or orange (bottom) dots
Based on swing pivot logic or rolling highs/lows in institutional positioning
Optional filter: Only show extremes that coincide with a symmetry break
Settings You Can Tune:
Lookback lengths for trend, z-scores, smoothing
Z-Score thresholds to control sensitivity
Retail quiet filters to reduce false positives
Cool-down timer to avoid rapid repeat signals
Toggle visual aids like shading, markers, and threshold lines
Alerts Included:
-Retail flips (green/red)
- Institutional symmetry breaks
- Institutional extreme tops/bottoms
Strategy Tip:
Use this indicator to track institutional accumulation or distribution phases and catch asymmetric inflection points where the "smart money" acts decisively. Confluence with price structure or FVGs (Fair Value Gaps) can further enhance signal quality.
MTF K-Means Price Regimes [matteovesperi] ⚠️ The preview uses a custom example to identify support/resistance zones. due to the fact that this identifier clusterizes, this is possible. this example was set up "in a hurry", therefore it has a possible inaccuracy. When setting up the indicator, it is extremely important to select the correct parameters and double-check them on the selected history.
📊 OVERVIEW
Purpose
MTF K-Means Price Regimes is a TradingView indicator that automatically identifies and classifies the current market regime based on the K-Means machine learning algorithm. The indicator uses data from a higher timeframe (Multi-TimeFrame, MTF) to build stable classification and applies it to the working timeframe in real-time.
Key Features
✅ Automatic market regime detection — the algorithm finds clusters of similar market conditions
✅ Multi-timeframe (MTF) — clustering on higher TF, application on lower TF
✅ Adaptive — model recalculates when a new HTF bar appears with a rolling window
✅ Non-Repainting — classification is performed only on closed bars
✅ Visualization — bar coloring + information panel with cluster characteristics
✅ Flexible settings — from 2 to 10 clusters, customizable feature periods, HTF selection
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🔬 TECHNICAL DETAILS
K-Means Clustering Algorithm
What is K-Means?
K-Means is one of the most popular clustering algorithms (unsupervised machine learning). It divides a dataset into K groups (clusters) so that similar elements are within each cluster, and different elements are between clusters.
Algorithm objective:
Minimize within-cluster variance (sum of squared distances from points to their cluster center).
How Does K-Means Work in Our Indicator?
Step 1: Data Collection
The indicator accumulates history from the higher timeframe (HTF):
RSI (Relative Strength Index) — overbought/oversold indicator
ATR% (Average True Range as % of price) — volatility indicator
ΔP% (Price Change in %) — trend strength and direction indicator
By default, 200 HTF bars are accumulated (clusterLookback parameter).
Step 2: Creating Feature Vectors
Each HTF bar is described by a three-dimensional vector:
Vector =
Step 3: Normalization (Z-Score)
All features are normalized to bring them to a common scale:
Normalized_Value = (Value - Mean) / StdDev
This is critically important, as RSI is in the range 0-100, while ATR% and ΔP% have different scales. Without normalization, one feature would dominate over others.
Step 4: K-Means++ Centroid Initialization
Instead of random selection of K initial centers, an improved K-Means++ method is used:
First centroid is randomly selected from the data
Each subsequent centroid is selected with probability proportional to the square of the distance to the nearest already selected centroid
This ensures better initial centroid distribution and faster convergence
Step 5: Iterative Optimization (Lloyd's Algorithm)
Repeat until convergence (or maxIterations):
1. Assignment step:
For each point find the nearest centroid and assign it to this cluster
2. Update step:
Recalculate centroids as the average of all points in each cluster
3. Convergence check:
If centroids shifted less than 0.001 → STOP
Euclidean distance in 3D space is used:
Distance = sqrt((RSI1 - RSI2)² + (ATR1 - ATR2)² + (ΔP1 - ΔP2)²)
Step 6: Adaptive Update
With each new HTF bar:
The oldest bar is removed from history (rolling window method)
New bar is added to history
K-Means algorithm is executed again on updated data
Model remains relevant for current market conditions
Real-Time Classification
After building the model (clusters + centroids), the indicator works in classification mode:
On each closed bar of the current timeframe, RSI, ATR%, ΔP% are calculated
Feature vector is normalized using HTF statistics (Mean/StdDev)
Distance to all K centroids is calculated
Bar is assigned to the cluster with minimum distance
Bar is colored with the corresponding cluster color
Important: Classification occurs only on a closed bar (barstate.isconfirmed), which guarantees no repainting .
Data Architecture
Persistent variables (var):
├── featureVectors - Normalized HTF feature vectors
├── centroids - Cluster center coordinates (K * 3 values)
├── assignments - Assignment of each HTF bar to a cluster
├── htfRsiHistory - History of RSI values from HTF
├── htfAtrHistory - History of ATR values from HTF
├── htfPcHistory - History of price changes from HTF
├── htfCloseHistory - History of close prices from HTF
├── htfRsiMean, htfRsiStd - Statistics for RSI normalization
├── htfAtrMean, htfAtrStd - Statistics for ATR normalization
├── htfPcMean, htfPcStd - Statistics for Price Change normalization
├── isCalculated - Model readiness flag
└── currentCluster - Current active cluster
All arrays are synchronized and updated atomically when a new HTF bar appears.
Computational Complexity
Data collection: O(1) per bar
K-Means (one pass):
- Assignment: O(N * K) where N = number of points, K = number of clusters
- Update: O(N * K)
- Total: O(N * K * I) where I = number of iterations (usually 5-20)
Example: With N=200 HTF bars, K=5 clusters, I=20 iterations:
200 * 5 * 20 = 20,000 operations (executes quickly)
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📖 USER GUIDE
Quick Start
1. Adding the Indicator
TradingView → Indicators → Favorites → MTF K-Means Price Regimes
Or copy the code from mtf_kmeans_price_regimes.pine into Pine Editor.
2. First Launch
When adding the indicator to the chart, you'll see a table in the upper right corner:
┌─────────────────────────┐
│ Status │ Collecting HTF │
├─────────────────────────┤
│ Collected│ 15 / 50 │
└─────────────────────────┘
This means the indicator is accumulating history from the higher timeframe. Wait until the counter reaches the minimum (default 50 bars for K=5).
3. Active Operation
After data collection is complete, the main table with cluster information will appear:
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
The arrow ► indicates the current active regime. Chart bars are colored with the corresponding cluster color.
Customizing for Your Strategy
Choosing Higher Timeframe (HTF)
Rule: HTF should be at least 4 times higher than the working timeframe.
| Working TF | Recommended HTF |
|------------|-----------------|
| 1 min | 15 min - 1H |
| 5 min | 1H - 4H |
| 15 min | 4H - D |
| 1H | D - W |
| 4H | D - W |
| D | W - M |
HTF Selection Effect:
Lower HTF (closer to working TF): More sensitive, frequently changing classification
Higher HTF (much larger than working TF): More stable, long-term regime assessment
Number of Clusters (K)
K = 2-3: Rough division (e.g., "uptrend", "downtrend", "flat")
K = 4-5: Optimal for most cases (DEFAULT: 5)
K = 6-8: Detailed segmentation (requires more data)
K = 9-10: Very fine division (only for long-term analysis with large windows)
Important constraint:
clusterLookback ≥ numClusters * 10
I.e., for K=5 you need at least 50 HTF bars, for K=10 — at least 100 bars.
Clustering Depth (clusterLookback)
This is the rolling window size for building the model.
50-100 HTF bars: Fast adaptation to market changes
200 HTF bars: Optimal balance (DEFAULT)
500-1000 HTF bars: Long-term, stable model
If you get an "Insufficient data" error:
Decrease clusterLookback
Or select a lower HTF (e.g., "4H" instead of "D")
Or decrease numClusters
Color Scheme
Default 10 colors:
Red → Often: strong bearish, high volatility
Orange → Transition, medium volatility
Yellow → Neutral, decreasing activity
Green → Often: strong bullish, high volatility
Blue → Medium bullish, medium volatility
Purple → Oversold, possible reversal
Fuchsia → Overbought, possible reversal
Lime → Strong upward momentum
Aqua → Consolidation, low volatility
White → Undefined regime (rare)
Important: Cluster colors are assigned randomly at each model recalculation! Don't rely on "red = bearish". Instead, look at the description in the table (RSI, ATR%, ΔP%).
You can customize colors in the "Colors" settings section.
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⚙️ INDICATOR PARAMETERS
Main Parameters
Higher Timeframe (htf)
Type: Timeframe selection
Default: "D" (daily)
Description: Timeframe on which the clustering model is built
Recommendation: At least 4 times larger than your working TF
Clustering Depth (clusterLookback)
Type: Integer
Range: 50 - 2000
Default: 200
Description: Number of HTF bars for building the model (rolling window size)
Recommendation:
- Increase for more stable long-term model
- Decrease for fast adaptation or if there's insufficient historical data
Number of Clusters (K) (numClusters)
Type: Integer
Range: 2 - 10
Default: 5
Description: Number of market regimes the algorithm will identify
Recommendation:
- K=3-4 for simple strategies (trending/ranging)
- K=5-6 for universal strategies
- K=7-10 only when clusterLookback ≥ 100*K
Max K-Means Iterations (maxIterations)
Type: Integer
Range: 5 - 50
Default: 20
Description: Maximum number of algorithm iterations
Recommendation:
- 10-20 is sufficient for most cases
- Increase to 30-50 if using K > 7
Feature Parameters
RSI Period (rsiLength)
Type: Integer
Default: 14
Description: Period for RSI calculation (overbought/oversold feature)
Recommendation:
- 14 — standard
- 7-10 — more sensitive
- 20-25 — more smoothed
ATR Period (atrLength)
Type: Integer
Default: 14
Description: Period for ATR calculation (volatility feature)
Recommendation: Usually kept equal to rsiLength
Price Change Period (pcLength)
Type: Integer
Default: 5
Description: Period for percentage price change calculation (trend feature)
Recommendation:
- 3-5 — short-term trend
- 10-20 — medium-term trend
Visualization
Show Info Panel (showDashboard)
Type: Checkbox
Default: true
Description: Enables/disables the information table on the chart
Cluster Color 1-10
Type: Color selection
Description: Customize colors for visual cluster distinction
Recommendation: Use contrasting colors for better readability
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📊 INTERPRETING RESULTS
Reading the Information Table
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
│ 4 │ 45.0 │ 1.20 │ -0.3 │ Low Vol,Bear │ │
│ 5 │ 72.1 │ 3.05 │ 2.8 │ High Vol,Bull│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
"ID" Column
Cluster number (1-K). Order doesn't matter.
"RSI" Column
Average RSI value in the cluster (0-100):
< 30: Oversold zone
30-45: Bearish sentiment
45-55: Neutral zone
55-70: Bullish sentiment
> 70: Overbought zone
"ATR%" Column
Average volatility in the cluster (as % of price):
< 1%: Low volatility (consolidation, narrow range)
1-2%: Normal volatility
2-3%: Elevated volatility
> 3%: High volatility (strong movements, impulses)
Compared to the average volatility across all clusters to determine "High Vol" or "Low Vol".
"ΔP%" Column
Average price change in the cluster (in % over pcLength period):
> +0.05%: Bullish regime
-0.05% ... +0.05%: Flat (sideways movement)
< -0.05%: Bearish regime
"Description" Column
Automatic interpretation:
"High Vol, Bull" → Strong upward momentum, high activity
"Low Vol, Flat" → Consolidation, narrow range, uncertainty
"High Vol, Bear" → Strong decline, panic, high activity
"Low Vol, Bull" → Slow growth, low activity
"Low Vol, Bear" → Slow decline, low activity
"Current" Column
Arrow ► shows which cluster the last closed bar of your working timeframe is in.
Typical Cluster Patterns
Example 1: Trend/Flat Division (K=3)
Cluster 1: RSI=65, ATR%=2.5, ΔP%=+1.5 → Bullish trend
Cluster 2: RSI=50, ATR%=0.8, ΔP%=0.0 → Flat/Consolidation
Cluster 3: RSI=35, ATR%=2.3, ΔP%=-1.4 → Bearish trend
Strategy: Open positions when regime changes Flat → Trend, avoid flat.
Example 2: Volatility Breakdown (K=5)
Cluster 1: RSI=72, ATR%=3.5, ΔP%=+2.5 → Strong bullish impulse (high risk)
Cluster 2: RSI=60, ATR%=1.5, ΔP%=+0.8 → Moderate bullish (optimal entry point)
Cluster 3: RSI=50, ATR%=0.7, ΔP%=0.0 → Flat
Cluster 4: RSI=40, ATR%=1.4, ΔP%=-0.7 → Moderate bearish
Cluster 5: RSI=28, ATR%=3.2, ΔP%=-2.3 → Strong bearish impulse (panic)
Strategy: Enter in Cluster 2 or 4, avoid extremes (1, 5).
Example 3: Mixed Regimes (K=7+)
With large K, clusters can represent condition combinations:
High RSI + Low volatility → "Quiet overbought"
Neutral RSI + High volatility → "Uncertainty with high activity"
Etc.
Requires individual analysis of each cluster.
Regime Changes
Important signal: Transition from one cluster to another!
Trading situation examples:
Flat → Bullish trend → Buy signal
Bullish trend → Flat → Take profit, close longs
Flat → Bearish trend → Sell signal
Bearish trend → Flat → Close shorts, wait
You can build a trading system based on the current active cluster and transitions between them.
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💡 USAGE EXAMPLES
Example 1: Scalping with HTF Filter
Task: Scalping on 5-minute charts, but only enter in the direction of the daily regime.
Settings:
Working TF: 5 min
HTF: D (daily)
K: 3 (simple division)
clusterLookback: 100
Logic:
IF current cluster = "Bullish" (ΔP% > 0.5)
→ Look for long entry points on 5M
IF current cluster = "Bearish" (ΔP% < -0.5)
→ Look for short entry points on 5M
IF current cluster = "Flat"
→ Don't trade / reduce risk
Example 2: Swing Trading with Volatility Filtering
Task: Swing trading on 4H, enter only in regimes with medium volatility.
Settings:
Working TF: 4H
HTF: D (daily)
K: 5
clusterLookback: 200
Logic:
Allowed clusters for entry:
- ATR% from 1.5% to 2.5% (not too quiet, not too chaotic)
- ΔP% with clear direction (|ΔP%| > 0.5)
Prohibited clusters:
- ATR% > 3% → Too risky (possible gaps, sharp reversals)
- ATR% < 1% → Too quiet (small movements, commissions eat profit)
Example 3: Portfolio Rotation
Task: Managing a portfolio of multiple assets, allocate capital depending on regimes.
Settings:
Working TF: D (daily)
HTF: W (weekly)
K: 4
clusterLookback: 100
Logic:
For each asset in portfolio:
IF regime = "Strong trend + Low volatility"
→ Increase asset weight in portfolio (40-50%)
IF regime = "Medium trend + Medium volatility"
→ Standard weight (20-30%)
IF regime = "Flat" or "High volatility without trend"
→ Minimum weight or exclude (0-10%)
Example 4: Combining with Other Indicators
MTF K-Means as a filter:
Main strategy: MA Crossover
Filter: MTF K-Means on higher TF
Rule:
IF MA_fast > MA_slow AND Cluster = "Bullish regime"
→ LONG
IF MA_fast < MA_slow AND Cluster = "Bearish regime"
→ SHORT
ELSE
→ Don't trade (regime doesn't confirm signal)
This dramatically reduces false signals in unsuitable market conditions.
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📈 OPTIMIZATION RECOMMENDATIONS
Optimal Settings for Different Styles
Day Trading
Working TF: 5M - 15M
HTF: 1H - 4H
numClusters: 4-5
clusterLookback: 100-150
Swing Trading
Working TF: 1H - 4H
HTF: D
numClusters: 5-6
clusterLookback: 150-250
Position Trading
Working TF: D
HTF: W - M
numClusters: 4-5
clusterLookback: 100-200
Scalping
Working TF: 1M - 5M
HTF: 15M - 1H
numClusters: 3-4
clusterLookback: 50-100
Backtesting
To evaluate effectiveness:
Load historical data (minimum 2x clusterLookback HTF bars)
Apply the indicator with your settings
Study cluster change history:
- Do changes coincide with actual trend transitions?
- How often do false signals occur?
Optimize parameters:
- If too much noise → increase HTF or clusterLookback
- If reaction too slow → decrease HTF or increase numClusters
Combining with Other Techniques
Regime-Based Approach:
MTF K-Means (regime identification)
↓
+---+---+---+
| | | |
v v v v
Trend Flat High_Vol Low_Vol
↓ ↓ ↓ ↓
Strategy_A Strategy_B Don't_trade
Examples:
Trend: Use trend-following strategies (MA crossover, Breakout)
Flat: Use mean-reversion strategies (RSI, Bollinger Bands)
High volatility: Reduce position sizes, widen stops
Low volatility: Expect breakout, don't open positions inside range
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📞 SUPPORT
Report an Issue
If you found a bug or have a suggestion for improvement:
Describe the problem in as much detail as possible
Specify your indicator settings
Attach a screenshot (if possible)
Specify the asset and timeframe where the problem is observed
#1 Vishal Toora Buy/Sell Table#1 Vishal Toora Buy/Sell Table
A multi-range volume analysis tool that tracks Short, Medium, and Long-term volume activity directly from recent candles.
It calculates Buy and Sell volumes for each range, shows their Delta (difference), and generates a combined Signal (Buy / Sell / Neutral) based on all active ranges.
Each column and the Signal row can be switched ON/OFF for custom clarity.
🧠 What the Numbers Represent (Candle Connection)
Each number represents total volume from a group of candles:
The script looks back a certain number of candles in each range (e.g., 2–3 candles for Short, 10–20 for Medium, 50–100 for Long).
It measures how much volume occurred on bullish candles (Buy) vs bearish candles (Sell).
Buy Volume (Green Numbers):
Volume from candles where price closed higher than it opened → bullish pressure.
Sell Volume (Red Numbers):
Volume from candles where price closed lower than it opened → bearish pressure.
Delta (White or Yellow Numbers):
The difference between Buy and Sell volumes within that range.
Positive → More bullish volume.
Negative → More bearish volume.
Larger absolute values = stronger imbalance between buyers and sellers.
Signal Row:
Summarizes all ranges’ deltas:
🟢 Buy → majority of ranges show positive delta.
🔴 Sell → majority show negative delta.
⚪ Neutral → roughly balanced or mixed candle behavior.
🎯 In Simple Terms
Each number in the table is a summary of what recent candles did —
it converts multiple candles’ volume data into clean, readable signals,
so you instantly see who’s in control (buyers or sellers) across short, medium, and long perspectives.
© 2025 Vishal Toora — counting volumes so you don’t have to.
Buy or Sell... or just stare at the screen.
Making deltas speak louder than your ex. 💀
Disclaimer:
This indicator is for educational and informational purposes only.
It does not guarantee accuracy or performance.
You are solely responsible for your trading decisions.
NDOG [派大星]🧠 Indicator Description — “NDOG ”
This indicator visualizes Night-Day Opening Gaps (NDOG) based on the custom trading session timing used in U.S. markets.
Instead of using the standard daily candle change, it detects gaps between the 16:59 close and the 18:00 open (New York time, UTC-4).
Whenever the market reopens after the evening pause (from 16:59 → 18:00),
the script measures the price difference between the previous session’s close and the new session’s open,
then draws a shaded box to highlight the opening gap region.
🟦 Bullish Gap (Upward) — when the new session opens above the previous close.
🟪 Bearish Gap (Downward) — when the new session opens below the previous close.
You can control the maximum number of displayed gaps with the “Amount” setting.
This custom session logic allows more accurate visualization of after-hours transitions for futures or extended-hours instruments (e.g., ES, NQ, SPY).
