Session Highs and LowsShows the current and previous session highs and lows for the New York, London and Asian sessions
Multitimeframe
AshokTrendThe AshokTrend indicator uses a combination of trendline logic and pivot high/low detection to signal possible BUY and SELL trades based on price action and structural breakouts.
### Buy/Sell Signal Logic
- **Buy Trade Signal**: It identifies local pivot lows using a lookback period, then checks multiple conditions comparing current and previous pivot values to validate a breakout. If conditions are met, triangle-up shapes are plotted below bars to indicate a possible long trade, and trendlines are drawn connecting pivots for visual confirmation.
- **Sell Trade Signal**: It locates pivot highs, applies similar multi-point checks, and confirms breakdowns in structure. Upon a valid signal, triangle-down shapes are plotted above bars to indicate a possible short trade, with corresponding trendlines marking pivot connections.
### Structural Confirmation
- Both buy and sell signals require the breakout/breakdown to be visually confirmed via the movement and steepness (slope) of custom lines that represent price momentum between pivots. Lines are updated or deleted if price fails the required strength, ensuring signals are filtered for validity.
### Alert and Analysis Details
- **Alerts**: Plotted shapes (triangle up for buy, triangle down for sell) can be used for automated alerts, integrating with platform alert conditions for strategy automation.
- **Analysis**: The indicator incorporates logic for cleaning up invalid signals and pruning trendlines when a reversal is detected, increasing reliability of entries and exits for both buy and sell trades.
### Key Settings for Customization
- Lookback period, padding, and color settings allow the user to tune signal frequency and visual appearance according to specific trading needs.
### Summary Table
| Signal Type | Visual Mark | Pivot Reference | Trendline Confirmation | Filtering Logic |
|----------------------|--------------|-----------------|-----------------------|-------------------------------|
| BUY | Triangle Up | Pivot Low | Slope & multi-point | Valid breakout only |
| SELL | Triangle Down| Pivot High | Slope & multi-point | Valid breakdown only |
This approach ensures that only structurally strong breakout-based trades are considered, pruning false signals in real-time for improved consistency in automated or manual trade analysis
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Disclaimer - This post is created for only Learning Purpose. Every Charts, Trade Ideas, Buy & Sell Levels and Updates are Provided For Learning Purpose Only . We Do Not Provide Any Buy And Sell Signals Tips. We are Not SEBI Registered .Do Always Calculate Your risk Before Taking the Trade And consult your Financial Advisor Before taking any Trade. Thank You
Best Time Slots — Auto-Adapt (v6, TF-safe) + Range AlertsTime & binning
Auto-adapt to timeframe
Makes all time windows scale to your chart’s bar size (so it “just works” on 1m, 15m, 4H, Daily).
• On = recommended. • Off = fixed default lengths.
Minimum Bin (minutes)
The size of each daily time slot we track (e.g., 5-min bins). The script uses the larger of this and your bar size.
• Higher = fewer, broader slots; smoother stats. • Lower = more, narrower slots; needs more history.
• Try: 5–15 on intraday, 60–240 on higher TFs.
Lookback windows (used when Auto-adapt = ON)
Target ER Window (minutes)
How far back we look to judge Efficiency Ratio (how “straight” the move was).
• Higher = stricter/smoother; fewer bars qualify as “movement”. • Lower = more sensitive.
• Try: 60–120 min intraday; 240–600 min for higher TFs.
Target ATR Window (minutes)
How far back we compute ATR (typical range).
• Higher = steadier ATR baseline. • Lower = reacts faster.
• Try: 30–120 min intraday; 240–600 min higher TFs.
Target Normalization Window (minutes)
How far back for the average ATR (the baseline we compare to).
• Higher = stricter “above average range” check. • Lower = easier to pass.
• Try: ~500–1500 min.
What counts as “movement”
ER Threshold (0–1)
Minimum efficiency a bar must have to count as movement.
• Higher = only very “clean, one-direction” bars count. • Lower = more bars count.
• Try: 0.55–0.65. (0.60 = balanced.)
ATR Floor vs SMA(ATR)
Requires range to be at least this many × average ATR.
• Higher (e.g., 1.2) = demand bigger-than-usual ranges. • Lower (e.g., 0.9) = allow smaller ranges.
• Try: 1.0 (above average).
How history is averaged
Recent Days Weight (per-day decay)
Gives more weight to recent days. Example: 0.97 ≈ each day old counts ~3% less.
• Higher (0.99) = slower fade (older days matter more). • Lower (0.95) = faster fade.
• Try: 0.97–0.99.
Laplace Prior Seen / Laplace Prior Hit
“Starter counts” so early stats aren’t crazy when you have little data.
• Higher priors = probabilities start closer to average; need more real data to move.
• Try: Seen=3, Hit=1 (defaults).
Min Samples (effective)
Don’t highlight a slot unless it has at least this many effective samples (after decay + priors).
• Higher = safer, but fewer highlights early.
• Try: 3–10.
When to highlight on the chart
Min Probability to Highlight
We shade/mark bars only if their slot’s historical movement probability is ≥ this.
• Higher = pickier, fewer highlights. • Lower = more highlights.
• Try: 0.45–0.60.
Show Markers on Good Bins
Draws a small square on bars that fall in a “good” slot (in addition to the soft background).
Limit to market hours (optional)
Restrict to Session + Session
Only learn/score inside this time window (e.g., “0930-1600”). Uses the chart/exchange timezone.
• Turn on if you only care about RTH.
Range (chop) alerts
Range START if ER ≤
Triggers range when efficiency drops below this level (price starts zig-zagging).
• Higher = easier to call “range”. • Lower = stricter.
Range START if ATR ≤ this × SMA(ATR)
Also triggers range when ATR shrinks below this fraction of its average (volatility contraction).
• Higher (e.g., 1.0) = stricter (must be at/under average). • Lower (e.g., 0.9) = easier to call range.
Alerts on bar close
If ON, alerts fire once per bar close (cleaner). If OFF, they can trigger intrabar (faster, noisier).
Quick “what happens if I change X?”
Want more highlighted times? ↓ Min Probability, ↓ ER Threshold, or ↓ ATR Floor (e.g., 0.9).
Want stricter highlights? ↑ Min Probability, ↑ ER Threshold, or ↑ ATR Floor (e.g., 1.2).
Want recent days to matter more? ↑ Recent Days Weight toward 0.99.
On 4H/Daily, widen Minimum Bin (e.g., 60–240) and maybe lower Min Probability a bit.
5 Moving Averages (Fully Customizable)I couldn't find any indicators that you could fully customize multiple moving average lines, so I made one.
You can change the color, line type, thickness, length, and opacity. Also make a custom color if you want.
You can make them SMA, EMA, WMA, HMA, VWMA.
Hope you enjoy!
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.
MARKET SCANNER Core Components:
1. Market Structure & Pivot Points
Multi-timeframe Pivots: Daily, Weekly, Monthly pivot points
Central Pivot Range (CPR): For all timeframes
N-Day High/Low Tracking: Dynamic support/resistance based on recent price action
2. Volume Analysis
Institutional Volume Metrics: Buy/Sell pressure, Net flow, Volume Power
Cumulative Delta: Tracks order flow imbalance
Volume Profile: Right-side profile with POC (Point of Control) and Value Area
Volume Strikes: Identifies significant volume absorption/breakout levels
3. Price Action & Patterns
Fibonacci-based Candlestick Recognition: Green/Red candles with specific Fibonacci conditions
Support/Resistance Zones: Dynamic boxes based on Fibonacci retracements
Breakout Detection: Tracks breakouts above N-day high/low with retracement levels
4. Moving Averages & VWAP
VWAP with multiple moving averages (20, 50, 250 periods)
MVWAP Sign Detection: Tracks flips in VWAP momentum
5. Market Sentiment Analysis
Composite Sentiment Score: Combines RSI, MACD, Stochastic, Moving Averages, ADX
Confidence Scoring: Measures signal reliability
Conflict Detection: Identifies when volume and price signals disagree
6. Advanced Features
Dynamic Gap Calculations: Measures distance to support/resistance zones
Swing Analysis: Identifies swing highs/lows with gap measurements
Volume-Price Confirmation: Validates moves with volume
Professional Tables: Multiple tables displaying pivot levels, differences, sentiment, and volume metrics
Key Trading Concepts Implemented:
Institutional Order Flow: Tracks smart money activity
Volume-Weighted Price Levels: Identifies significant price zones
Multi-timeframe Analysis: Correlates daily, weekly, monthly levels
Fibonacci Retracement Strategies: For entries and exits
Market Microstructure: Through volume profile and delta analysis
Visual Outputs:
Dynamic support/resistance boxes
Volume profile histogram
Multiple information tables
Real-time sentiment scoring
Retracement lines and zones
This is essentially a professional-grade trading suite that combines price action, volume analysis, market structure, and sentiment into one comprehensive tool suitable for both discretionary and systematic trading approaches.
VWAP + EMA shows the VWAP + EMA 9/20/50/100/200 all in one indicator... you can adjust VWAP's calculation method + color + the outer bands or remove them.. can remove fill as well.. personally i just keep the VWAP
Camarilla Trading - D/W/M, Alerts, TP/SL, ADX, VWAP/EMA, VolumeCamarilla Trading System
Overview
This advanced Pine Script indicator implements a comprehensive Camarilla trading system with multiple filtering mechanisms, position management, and real-time statistics. It's designed for day traders and swing traders using Camarilla pivot levels with enhanced confirmation filters.
Key Features
🎯 Core Components
- Camarilla Levels: Calculates H3, H4, H5, L3, L4, L5 pivot levels from previous period data
- Multi-Timeframe Support: Daily (D), Weekly (W), and Monthly (M) timeframe options
- Smart Position Management: Automated entry/exit with take profit and stop loss levels
📊 Advanced Filtering System
- ADX Filter**: Optional trend strength filter using Average Directional Index
- Volume Filter**: High-volume confirmation with customizable multiplier
- Trend Filter**: VWAP or EMA-based trend direction confirmation
💹 Trading Signals
Long Entries:
- Condition 1: Open crosses above H4 (below H5)
- Condition 2: Open crosses above L3 (below H3)
Short Entries:
- Condition 1: Open crosses below L4 (above L5)
- Condition 2: Open crosses below H3 (above L3)
📈 Visual Features
- Level Display: Clear plotting of all Camarilla levels
- Signal Markers: Visual entry/exit signals on chart
- Volume Coloring: Bars colored lime/purple during high-volume periods
- Trend Indicators: Colored VWAP/EMA lines based on ADX trend direction
- Real-time Statistics: Performance table with win rate, P&L, and trade metrics
⚙️ Customization Options
- Toggle individual filters on/off
- Adjustable parameters for all indicators
- Customizable display options
- Flexible timeframe selection
🔔 Alert System
- Buy/Sell signal alerts
- Position exit alerts
- Customizable alert conditions
📊 Performance Tracking
- Automatic trade statistics
- Win rate calculation
- Average profit per trade
- Total P&L tracking
- Trade history from start date
Input Parameters
Timeframe & Levels
- Timeframe levels: D/W/M selection for pivot calculations
- Show levels labels: Toggle level price labels
Filter Settings
- ADX filter: Enable/disable trend strength filter
- ADX length/treshold: Customize ADX parameters
- Volume filter: High-volume confirmation
- Volume length/multiplier: Volume MA settings
- Trend filter: VWAP/EMA trend confirmation
- EMA length: EMA period for trend filter
Display Options
- Show signals: Display entry/exit markers
- Show TP/SL: Show take profit/stop loss levels
- Show statistics: Performance table display
- Colored bars: Volume-based bar coloring
Usage Notes
- Non-repainting: Signals are fixed at bar open price
- Multi-timeframe: Uses security calls for accurate previous period data
- Position Management: Automated TP/SL based on Camarilla levels
- Risk Management: Built-in trading time restrictions
This system provides institutional-grade Camarilla trading with professional risk management features suitable for both manual trading and strategy development.
PDH/PDL- [CT]Private Algorithm that is invite only. It is only spread through word of mouth and is not available on any website.
This algorithm will give you the best chance at being green and is even better when following specific plays of someone or yourself.
This is not supposed to guarantee profit and the team are not financial advisors. Please always manage your own risk according to your risk tolerance .
PDH/PDL –
by calmstrades
Description:
The PDH/PDL – indicator automatically plots the Previous Day’s High (PDH) and Previous Day’s Low (PDL) levels directly on your chart — essential reference points for Smart Money Concepts (SMC) and intraday traders.
It also detects and highlights liquidity sweeps when price takes out the prior day’s highs or lows, helping identify potential reversal or continuation zones.
🔍 Features:
Automatic PDH/PDL Levels:
Draws dynamic lines for the previous day’s high and low with customizable styles, colors, and widths.
Smart Money Sweep Detection:
Marks PDH or PDL sweeps using visual labels whenever liquidity is taken.
Clean Visual Customization:
Choose line style (Solid, Dashed, Dotted), color themes, label display, and toggle visibility for all components.
Lightweight & Efficient:
Optimized for smooth performance even on lower timeframes (1m–15m).
⚙️ Settings:
✅ Show PDH / Show PDL
🏷️ Show Labels on Lines
💧 Show Liquidity Sweeps
🎨 Line Style, Width, and Color Controls
💡 How to Use:
Use PDH/PDL as key liquidity levels where price often reacts.
Watch for sweeps (liquidity grabs) followed by structure shifts to identify potential trade setups.
Combine with other SMC tools, such as Order Blocks, FVGs, or BOS/CHoCH indicators, for confirmation.
Lightning Fib PreVersionLightning Fib • PreVersion — by MahaTrend
The Lightning Fib • PreVersion visualizes structural price ranges between recent highs and lows, helping traders see how the market expands and contracts within a defined window.
By default, it uses the last 3 days to build the structure — a balanced setup suitable for most trading styles and timeframes.
You can adjust the lookback period to rebuild the structure or enable Dynamic Range Mode, which adapts the levels to your visible chart area.
Celestial Mode, available only when Dynamic Range Mode is active, refreshes the structure every 66 bars, allowing observation of slower rhythm patterns and long movements.
This version reflects the original level configuration personally traded by MahaTrend — a clean, balanced framework designed for structural and geometric price analysis.
🕒 Recommended timeframes: 1-minute to 1-hour, or higher for broader context.
by MahaTrend • Lightning Series
Custom Two Sessions H/L/50% LevelsTrack high/low/midpoint levels across two customizable time sessions. Perfect for monitoring H4 blocks, session ranges, or any custom time periods as reference levels for lower timeframe trading.
What This Indicator Does:
Tracks and projects High, Low, and 50% Midpoint levels for two fully customizable time sessions. Unlike fixed-session indicators, you define EXACTLY when each session starts and ends.
Key Features:
• Two independent sessions with custom start/end times (hour and minute)
• High/Low/50% midpoint tracking for each session
• Visual session boxes showing calculation periods
• Horizontal lines projecting levels into the future
• Historical session levels remain visible for reference
• Works on any chart timeframe (M1, M5, M15, H1, H4, etc.)
• Full visual customization (colors, line styles, widths)
• DST timezone support
Common Use Cases:
H4 Candle Tracking - Set sessions to 4-hour blocks (e.g., 6-10am, 10am-2pm) to track individual H4 highs/lows
H1 Candle Tracking - 1-hour blocks for scalping reference levels
Session Trading - ETH vs RTH, London vs NY, Asian session, etc.
Custom Time Periods - Any time range you want to monitor
How to Use:
The indicator identifies key price levels from higher timeframe periods. Use previous session H/L/50% as reference levels for:
Identifying sweep and reclaim setups
Lower timeframe structural flip confirmations
Support/resistance zones for entries
Delivery targets after breaks of structure
Settings:
Configure each session's start/end times independently. The indicator automatically triggers at the first bar crossing into your specified time, making it compatible with all chart timeframes.
No-Trade Zones UTC+7This indicator helps you visualize and backtest your preferred trading hours. For example, if you have a 9-to-5 job, you obviously can’t trade during that time — and when backtesting, you should avoid those hours too. It also marks weekends if you prefer not to trade on those days.
By highlighting no-trade periods directly on the chart, you can easily see when you shouldn’t be taking trades, without constantly checking the time or date by hovering over the chart. It makes backtesting smoother and more realistic for your personal schedule.
Fixed High Timeframe Moving AveragesFixed High Timeframe Moving Averages (W/D/4H)
Summary
This indicator plots essential, high-timeframe (HTF) Moving Averages onto your chart, **no matter which timeframe you are currently viewing**.
It is designed for traders who need multi-timeframe context at a glance. Stop switching charts to see where the 200-Week or 50-Day MA is—now you can see all critical HTF levels directly on your 5-minute (or any other) chart.
---
Who it’s for
Traders who rely on moving averages but like to work on lower chart timeframes while keeping higher timeframe context in sight. If you scalp on 1–15m yet want Weekly/Daily/4H MAs always visible, this is for you.
---
What it shows
Pinned (“fixed”) moving averages from higher timeframes—Weekly (20/100/200) , Daily (50/100/200/365) and 4H (200) —rendered on any chart timeframe. Your favorite HTF MAs stay on screen no matter what TF you’re currently analyzing.
---
Features
* **MA types:** SMA, EMA, VWMA, Hull.
* **Fully configurable:** toggle each line, set periods, colors, and thickness.
* **Two alert modes (see below):** intrabar vs confirmed HTF close.
* **Works on any symbol & chart TF** using `request.security` to fetch HTF data.
---
Alerts & Modes
This indicator solves the biggest problem with MTF alerts: false signals. You can choose one of two modes:
1. **Intrabar mode** — compares current chart price to the HTF MA. Triggers as soon as price crosses the HTF line; great for early signals but may update until the HTF bar closes.
2. **Confirmed mode** — checks HTF close vs HTF MA. Signals only on the higher-TF bar close; fewer false starts, no intrabar repainting on that TF.
Per-line *Cross Above / Cross Below* conditions are provided for all enabled MAs (e.g., “20W — Cross Above”, “365D — Cross Below”, etc.).
**How to use alerts:** add the script → “Create Alert” → pick any condition from the script’s list.
---
Why this helps
* Keeps Weekly/Daily structure visible while you execute on LTF.
* Classic anchors (e.g., 200D, 20W/100W/200W) are popular for trend bias, dynamic support/resistance, and pullback context.
* Lets you standardize MA references across all your lower-TF playbooks.
---
Notes on confirmation & repainting
* Intrabar signals can change until the higher-TF bar closes (that’s expected with multi-TF data).
* Confirmed mode waits for the HTF close—cleaner, but later. Choose what fits your workflow.
---
Quick setup
1. Pick `MA Type` (SMA/EMA/VWMA/Hull).
2. Enable the HTF lines you want (Weekly 20/100/200; Daily 50/100/200/365; 4H 200).
3. Choose `Alert Mode` (Intrabar vs Confirmed).
4. Style colors/widths to taste and set alerts on the lines you care about.
---
Good practice
* Combine HTF MAs with price action (swings, structure, liquidity grabs) rather than using them in isolation.
* Always validate signals in your execution TF and use a risk plan tailored to volatility.
* Protect your capital: position sizing, stops, and disciplined risk management matter more than any single line on the chart.
---
Disclaimer
For educational/informational purposes only; not financial advice. Trading involves risk—manage it responsibly.
[AS] MACD-v & Hist [Alex Spiroglou | S.M.A.R.T. TRADER SYSTEMS] MACD-v & MACD-v Histogram
=======================================
Volatility Normalised Momentum 📈
Twice Awarded Indicator 🏆
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=======================================
✅ 1. INTRODUCTION TO THE MACD-v ✅
=======================================
I created the MACD-v in 2015,
as a way to deal with the limitations
of well known indicators like the Stochastic, RSI, MACD.
I decided to publicly share a very small part of my research
in the form of a research paper I wrote in 2022,
titled "MACD-v: Volatility Normalised Momentum".
That paper was awarded twice:
1. The "Charles H. Dow" Award (2022),
for outstanding research in Technical Analysis,
by the Chartered Market Technicians Association (CMTA)
2. The "Founders" Award (2022),
for advances in Active Investment Management,
by the National Association of Active Investment Managers (NAAIM)
=======================================
===================================================
❌ 2. WHY CREATE THE MACD-v ?
THE LIMITATIONS OF CONVENTIONAL MOMENTUM INDICATORS
====================================================
Technical Analysis indicators focused on momentum,
come in two general categories,
each with its own set of limitations:
(i) Range Bound Oscillators (RSI, Stochastics, etc)
These usually have a scaling of 0-100,
and thus have the advantage of having normalised readings,
that are comparable across time and securities.
However they have the following limitations (among others):
1. Skewing effect of steep trends
2. Indicator values do not adjust with and reflect true momentum
(indicator values are capped to 100)
(ii) Unbound Oscillators (MACD, RoC, etc)
These are boundless indicators,
and can expand with the market,
without being limited by a 0-100 scaling,
and thus have the advantage of really measuring momentum.
They have the main following limitations (among others):
1. Subjectivity of overbought / oversold levels
2. Not comparable across time
3. Not comparable across securities
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💡 3. THE SOLUTION TO SOLVE THESE LIMITATIONS
=======================================
In order to deal with these limitations,
I decided to create an indicator,
that would be the "Best of two worlds".
A unique & hybrid indicator,
that would have objective normalised readings
(similar to Range Bound Oscillators - RSI)
but would also be able to have no upper/lower boundaries
(similar to Unbound Oscillators - MACD).
This would be achieved by "normalising" a boundless oscillator (MACD)
=======================================
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⛔ 4. DEEP DIVE INTO THE 5 LIMITATIONS OF THE MACD
==================================================
A Bloomberg study found that the MACD
is the most popular indicator after the RSI,
but the MACD has 5 BIG limitations.
Limitation 1: MACD values are not comparable across Time
The raw MACD values shift
as the underlying security's absolute value changes across time,
making historical comparisons obsolete
e.g S&P 500 maximum MACD was 1.56 in 1957-1971,
but reached 86.31 in 2019-2021 - not indicating 55x stronger momentum,
but simply different price levels.
Limitation 2: MACD values are not comparable across Assets
Traditional MACD cannot compare momentum between different assets.
S&P 500 MACD of 65 versus EUR/USD MACD of -0.5
reflects absolute price differences, not momentum differences
Limitation 3: MACD values cannot be Systematically Classified
Due to limitations #1 & #2, it is not possible to create
a momentum level classification scale
where one can define "fast", "slow", "overbought", "oversold" momentum
making systematic analysis impossible
Limitation 4: MACD Signal Line gives false crossovers in low-momentum ranges
In range-bound, low momentum environments,
most of the MACD signal line crossovers are false (noise)
Since there is no objective momentum classification system (limitation #3),
it is not possible to filter these signals out,
by avoiding them when momentum is low
Limitation 5: MACD Signal Line gives late crossovers in high momentum regimes.
Signal lag in strong trends not good at timing the turning point
— In high-momentum moves, MACD crossovers may come late.
Since there is no objective momentum classification system (limitation #3),
it is not possible to filter these signals out,
by avoiding them when momentum is high
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🏆 5. MACD-v : THE SOLUTION TO THE LIMITATIONS OF THE MACD , RSI, etc
====================================================================
MACD-v is a volatility normalised momentum indicator.
It remedies these 5 limitations of the classic MACD,
while creating a tool with unique properties.
Formula: × 100
MACD-V enhances the classic MACD by normalizing for volatility,
transforming price-dependent readings into standardized momentum values.
This resolves key limitations of traditional MACD and adds significant analytical power.
Core Advantages of MACD-V
Advantage 1: Time-Based Stability
MACD-V values are consistent and comparable over time.
A reading of 100 has the same meaning today as it did in the past
(unlike traditional MACD which is influenced by changes in price and volatility over time)
Advantage 2: Cross-Market Comparability
MACD-V provides universal scaling.
Readings (e.g., ±50) apply consistently across all asset classes—stocks,
bonds, commodities, or currencies,
allowing traders to compare momentum across markets reliably.
Advantage 3: Objective Momentum Classification
MACD-V includes a defined 5-range momentum lifecycle
with standardized thresholds (e.g., -150 to +150).
This offers an objective framework for analyzing market conditions
and supports integration with broader models.
Advantage 4: False Signal Reduction in Low-Momentum Regimes
MACD-V introduces a "neutral zone" (typically -50 to +50)
to filter out these low-probability signals.
Advantage 5: Improved Signal Timing in High-Momentum Regimes
MACD-V identifies extremely strong trends,
allowing for more precise entry and exit points.
Advantage 6: Trend-Adaptive Scaling
Unlike bounded oscillators like RSI or Stochastic,
MACD-V dynamically expands with trend strength,
providing clearer momentum insights without artificial limits.
Advantage 7: Enhanced Divergence Detection
MACD-V offers more reliable divergence signals
by avoiding distortion at extreme levels,
a common flaw in bounded indicators (RSI, etc)
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⚒️ 5. HOW TO USE THE MACD-v: 7 CORE PATTERNS
HOW TO USE THE MACD-v Histogram: 2 CORE PATTERNS
=======================================
>>>>>> BASIC USE (RANGE RULES) <<<<<<
The MACD-v has 7 Core Patterns (Ranges) :
1. Risk Range (Overbought)
Condition: MACD-V > Signal Line and MACD-V > +150
Interpretation: Extremely strong bullish momentum—potential exhaustion or reversal zone.
2. Retracing
Condition: MACD-V < Signal Line and MACD-V > -50
Interpretation: Mild pullback within a bullish trend.
3. Rundown
Condition: MACD-V < Signal Line and -50 > MACD-V > -150
Interpretation: Momentum is weakening—bearish pressure building.
4. Risk Range (Oversold)
Condition: MACD-V < Signal Line and MACD-V < -150
Interpretation: Extreme bearish momentum—potential for reversal or capitulation.
5. Rebounding
Condition: MACD-V > Signal Line and MACD-V > -150
Interpretation: Bullish recovery from oversold or weak conditions.
6. Rallying
Condition: MACD-V > Signal Line and MACD-V > +50
Interpretation: Strengthening bullish trend—momentum accelerating.
7. Ranging (Neutral Zone)
Condition: MACD-V remains between -50 and +50 for 20+ bars
Interpretation: Sideways market—low conviction and momentum.
The MACD-v Histogram has 2 Core Patterns (Ranges) :
1. Risk (Overbought)
Condition: Histogram > +40
Interpretation: Short-term bullish momentum is stretched—possible overextension or reversal risk.
2. Risk (Oversold)
Condition: Histogram < -40
Interpretation: Short-term bearish momentum is stretched—potential for rebound or reversal.
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=======================================
📈 6. ADVANCED PATTERNS WITH MACD-v
=======================================
Thanks to its volatility normalization,
the MACD-V framework enables the development
of a wide range of advanced pattern recognition setups,
trading signals, and strategic models.
These patterns go beyond basic crossovers,
offering deeper insight into momentum structure,
regime shifts, and high-probability trade setups.
These are not part of this script
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⚙️ 7. FUNCTIONALITY - HOW TO ADD THE INDICATORS TO YOUR CHART
===========================================================
The script allows you to see :
1. MACD-v
The indicator with the ranges (150,50,0,-50,-150)
and colour coded according to its 7 basic patterns
2. MACD-v Histogram
The indicator The indicator with the ranges (40,0,-40)
and colour coded according to its 2 basic ranges / patterns
3. MACD-v Heatmap
You can see the MACD-v in a Multiple Timeframe basis,
using a colour-coded Heatmap
Note that lowest timeframe in the heatmap must be the one on the chart
i.e. if you see the daily chart, then the Heatmap will be Daily, Weekly, Monthly
4. MACD-v Dashboard
You can see the MACD-v for 7 markets,
in a multiple timeframe basis
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🤝 CONTRIBUTIONS 🤝
=======================================
I would like to thank the following people:
1. Mike Christensen for coding the indicator
@TradersPostInc, @Mik3Christ3ns3n,
2. @Indicator-Jones For allowing me to use his Scanner
3. @Daveatt For allowing me to use his heatmap
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⚠️ LEGAL - Usage and Attribution Notice ⚠️
=======================================
Use of this Script is permitted
for personal or non-commercial purposes,
including implementation by coders and TradingView users.
However, any form of paid redistribution,
resale, or commercial exploitation is strictly prohibited.
Proper attribution to the original author is expected and appreciated,
in order to acknowledge the source
and maintain the integrity of the original work.
Failure to comply with these terms,
or to take corrective action within 48 hours of notification,
will result in a formal report to TradingView’s moderation team,
and will actively pursue account suspension and removal of the infringing script(s).
Continued violations may result in further legal action, as deemed necessary.
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⚠️ DISCLAIMER ⚠️
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This indicator is For Educational Purposes Only (F.E.P.O.).
I am just Teaching by Example (T.B.E.)
It does not constitute investment advice.
There are no guarantees in trading - except one.
You will have losses in trading.
I can guarantee you that with 100% certainty.
The author is not responsible for any financial losses
or trading decisions made based on this indicator. 🙏
Always perform your own analysis and use proper risk management. 🛡️
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AEON | Liquidity HunterA visual tool for identifying high-probability liquidity zones across multiple timeframes and sessions.
Overview
Liquidity Hunter is a multi-timeframe, all market tool designed to help traders visualise areas where price may be drawn in search of resting liquidity. These liquidity zones often align with swing highs and lows, session extremes, or significant higher-time-frame reference points.
Rather than producing entry or exit signals, this indicator aims to support market behaviour analysis and contextual awareness.
Core Functions
The indicator identifies potential liquidity areas using four optional methods:
1. Current Time Frame Analysis – Automatically locates swing highs and lows based on a customisable setting for sensitivity and lookback depth.
2. Higher Time Frame Analysis – Uses the same logic as above, but projects liquidity zones from a selected higher time frame (HTF).
3. Session Highs & Lows – Highlights the Asian, London, New York, or user-defined session extremes where liquidity commonly pools.
4. Time-Based Highs & Lows – Marks the final bar of any higher time frame (for example, the last H4 or D1 candle) to show potential liquidity reference points.
Each method can be enabled or disabled independently and visually customised, allowing traders to tailor the display to their preferred style and time frame.
How to Use
When applied, the indicator plots horizontal levels representing potential liquidity pools. These levels persist until price engages with or mitigates them, at which point users can opt to modify their visual style or delete them as preferred.
Adjusting the sensitivity of the current and higher time frame levels may reflect the market's likelihood of treating them as targets or reversal points.
Many traders combine these levels with concepts such as market structure shifts, displacement, or fair-value gaps to build a narrative around price behaviour.
Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice or a trade signal. Past performance or visual confluence does not guarantee future results.
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About the Author
Created by a passionate developer focused on algorithmic and quantitative concepts.
FVG MagicFVG Magic — Fair Value Gaps with Smart Mitigation, Inversion & Auto-Clean-up
FVG Magic finds every tradable Fair Value Gap (FVG), shows who powered it, and then manages each gap intelligently as price interacts with it—so your chart stays actionable and clean.
Attribution
This tool is inspired by the idea popularized in “Volumatic Fair Value Gaps ” by BigBeluga (licensed CC BY-NC-SA 4.0). Credit to BigBeluga for advancing FVG visualization in the community.
Important: This is a from-scratch implementation—no code was copied from the original. I expanded the concept substantially with a different detection stack, a gap state machine (ACTIVE → 50% SQ → MITIGATED → INVERSED), auto-clean up rules, lookback/nearest-per-side pruning, zoom-proof volume meters, and timeframe auto-tuning for 15m/H1/H4.
What makes this version more accurate
Full-coverage detection (no “missed” gaps)
Default ICT-minimal rule (Bullish: low > high , Bearish: high < low ) catches all valid 3-candle FVGs.
Optional Strict filter (stricter structure checks) for traders who prefer only “clean” gaps.
Optional size percentile filter—off by default so nothing is hidden unless you choose to filter.
Correct handling of confirmations (wick vs close)
Mitigation Source is user-selectable: high/low (wick-based) or close (strict).
This avoids false “misses” when you expect wick confirmations (50% or full fill) but your logic required closes.
State-aware labelling to prevent misleading data
The Bull%/Bear% meter is shown only while a gap is ACTIVE.
As soon as a gap is 50% SQ, MITIGATED, or INVERSED, the meter is hidden and replaced with a clear tag—so you never read stale participation stats.
Robust zoom behaviour
The meter uses a fixed bar-width (not pixels), so it stays proportional and readable at any zoom level.
Deterministic lifecycle (no stale boxes)
Remove on 50% SQ (instant or delayed).
Inversion window after first entry: if price enters but doesn’t invert within N bars, the box auto-removes once fully filled.
Inversion clean up: after a confirmed flip, keep for N bars (context) then delete (or 0 = immediate).
Result: charts auto-maintain themselves and never “lie” about relevance.
Clarity near current price
Nearest-per-side (keep N closest bullish & bearish gaps by distance to the midpoint) focuses attention where it matters without altering detection accuracy.
Lookback (bars) ensures reproducible behaviour across accounts with different data history.
Timeframe-aware defaults
Sensible auto-tuning for 15m / H1 / H4 (right-extension length, meter width, inversion windows, clean up bars) to reduce setup friction and improve consistency.
What it does (under the hood)
Detects FVGs using ICT-minimal (default) or a stricter rule.
Samples volume from a 10× lower timeframe to split participation into Bull % / Bear % (sum = 100%).
Manages each gap through a state machine:
ACTIVE → 50% SQ (midline) → MITIGATED (full) → INVERSED (SR flip after fill).
Auto-clean up keeps only relevant levels, per your rules.
Dashboard (top-right) displays counts by side and the active state tags.
How to use it
First run (show everything)
Use Strict FVG Filter: OFF
Enable Size Filter (percentile): OFF
Mitigation Source: high/low (wick-based) or close (stricter), as you prefer.
Remove on 50% SQ: ON, Delay: 0
Read the context
While ACTIVE, use the Bull%/Bear% meter to gauge demand/supply behind the impulse that created the gap.
Confluence with your HTF structure, sessions, VWAP, OB/FVG, RSI/MACD, etc.
Trade interactions
50% SQ: often the highest-quality interaction; if removal is ON, the box clears = “job done.”
Full mitigation then rejection through the other side → tag changes to INVERSED (acts like SR). Keep for N bars, then auto-remove.
Keep the chart tidy (optional)
If too busy, enable Size Filter or set Nearest per side to 2–4.
Use Lookback (bars) to make behaviour consistent across symbols and histories.
Inputs (key ones)
Use Strict FVG Filter: OFF(default)/ON
Enable Size Filter (percentile): OFF(default)/ON + threshold
Mitigation Source: high/low or close
Remove on 50% SQ + Delay
Inversion window after entry (bars)
Remove inversed after (bars)
Lookback (bars), Nearest per side (N)
Right Extension Bars, Max FVGs, Meter width (bars)
Colours: Bullish, Bearish, Inversed fill
Suggested defaults (per TF)
15m: Extension 50, Max 12, Inversion window 8, Clean up 8, Meter width 20
H1: Extension 25, Max 10, Inversion window 6, Clean up 6, Meter width 15
H4: Extension 15, Max 8, Inversion window 5, Clean up 5, Meter width 10
Notes & edge cases
If a wick hits 50% or the far edge but state doesn’t change, you’re likely on close mode—switch to high/low for wick-based behaviour.
If a gap disappears, it likely met a clean up condition (50% removal, inversion window, inversion clean up, nearest-per-side, lookback, or max-cap).
Meters are hidden after ACTIVE to avoid stale percentages.
MTF 20 SMA Table - DXY**MTF 20 SMA Table - Multi-Timeframe Trend Analysis Dashboard**
**Overview:**
This indicator provides a comprehensive multi-timeframe analysis dashboard that displays the relationship between price and the 20-period Simple Moving Average (SMA) across four key timeframes: 15-minute, 1-hour, 4-hour, and Daily. It's designed to help traders quickly identify trend alignment and potential trading opportunities across multiple timeframes at a glance. It's definitely not perfect but has helped me speed up my backtesting efforts as it's worked well for me eliminating flipping back and forth between timeframes excpet when I have confluence on the table, then I check the HTF.
**How It Works:**
The indicator creates a table overlay on your chart showing three critical metrics for each timeframe:
1. **Price vs SMA (Row 1):** Shows whether price is currently above (bullish) or below (bearish) the 20 SMA
- Green = Price Above SMA
- Red = Price Below SMA
2. **SMA Direction (Row 2):** Indicates the trend direction of the SMA itself over a lookback period
- Green (↗ Rising) = Uptrend
- Red (↘ Falling) = Downtrend
- Gray (→ Flat) = Ranging/Consolidation
3. **Strength (Row 3):** Displays the distance between current price and the SMA in pips
- Purple background = Strong move (>50 pips away)
- Orange background = Moderate move (20-50 pips)
- Gray background = Weak/consolidating (<20 pips)
- Text color: Green for positive distance, Red for negative
**Key Features:**
- **Customizable Table Position:** Place the table anywhere on your chart (9 position options)
- **Adjustable SMA Lengths:** Modify the SMA period for each timeframe independently (default: 20)
- **Direction Lookback Settings:** Fine-tune how far back the indicator looks to determine SMA direction for each timeframe
- **Flat Threshold:** Set the pip threshold for determining when an SMA is "flat" vs trending (default: 5 pips)
- **DXY Optimized:** Calculations are calibrated for the US Dollar Index (1 pip = 0.01)
**Best Use Cases:**
1. **Trend Alignment:** Identify when multiple timeframes align in the same direction for higher probability trades
2. **Divergence Spotting:** Detect when lower timeframes diverge from higher timeframes (potential reversals)
3. **Entry Timing:** Use lower timeframe signals while higher timeframes confirm overall trend
4. **Strength Assessment:** Gauge how extended price is from the mean (SMA) to avoid overextended entries
**Settings Guide:**
- **SMA Settings Group:** Adjust the SMA period for each timeframe (15M, 1H, 4H, Daily)
- **SMA Direction Group:** Control lookback periods to determine trend direction
- 15M: Default 5 candles
- 1H: Default 10 candles
- 4H: Default 15 candles
- Daily: Default 20 candles
- **Flat Threshold:** Set sensitivity for "flat" detection (lower = more sensitive to ranging markets)
**Trading Strategy Examples:**
1. **Trend Following:** Look for all timeframes showing the same direction (all green or all red)
2. **Pullback Trading:** When Daily/4H are green but 15M/1H show red, wait for lower timeframes to flip green for entry
3. **Ranging Markets:** When multiple SMAs show "flat", consider range-bound strategies
**Important Notes:**
- This is a reference tool only, not a standalone trading system
- Always use proper risk management and combine with other analysis methods
- Best suited for trending instruments like indices and major forex pairs
- Calculations are optimized for DXY but can be used on other instruments (pip calculations may need adjustment)
**Credits:**
Feel free to modify and improve this code! Suggestions for enhancements are welcome in the comments.
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**Installation Instructions:**
1. Add the indicator to your TradingView chart
2. Adjust the table position via settings to avoid overlap with price action
3. Customize SMA lengths and lookback periods to match your trading style
4. Monitor the table for timeframe alignment and trend confirmation
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This indicator is published as open source for the community to learn from and improve upon. Happy trading! 📈
Previous D/W/M HLOCHey traders,
Here's a simple Multi-Timeframe indicator that essentially turns time and price into a box. It'll take the previous high, low, opening price, or closing price from one of the three timeframes of your choice (day, week, or month). For whatever reason I can't get the opening price to function consistently so if you find improvements feel free to let me know, this will help traders who prefer to use opening price over closing price.
Naturally this form of charting is classical and nature and some key figures you could use to study its usage are
- Richard W. Schabacker (1930s)
- Edwards & Magee (1948)
- Peter Brandt
- Stacey Burke (more on the intraday side - typically our preference)
It's usage put plainly:
- Quantifying Accumulation or Distribution
- Revealing Energy Build-Up (Compression)
- Framing Breakouts and False Breakouts
- Structuring Time
- Identifying opportunities to trade a daily, weekly, or monthly range.
Multi-Session Viewer and AnalyzerFully customizable multi-session viewer that takes session analysis to the next level. It allows you to fully customize each session to your liking. Includes a feature that highlights certain periods of time on the chart and a Time Range Marker.
It helps you analyze the instrument that you trade and pinpoint which times are more volatile than others. It also helps you choose the best time to trade your instrument and align your life schedule with the market.
NZDUSD Example:
- 3 major sessions displayed.
- Although this is NZDUSD, Sydney is not the best time to trade this pair. Volatility picks up at Tokyo open.
- I have time to trade in the evening from 18:00 to 22:00 PST. I live in a different time zone, whereas market is based on EST. How does the pair behave during the time I am available to trade based on my time zone? Time Range Marker feature allows you to see this clearly on the chart (black lines).
- I have some time in the morning to trade during New York session, but there is no way I am waking up at 05:00 PST. 06:30 PST seems doable. Blue highlighted area is good time to trade during New York session based on what Bob said. It seem like this aligns with when I am available and when I am able to trade. Volatility is also at its peak.
- I am also available to trade between London close and Tokyo open on some days of the week, but... based on what I see, green highlighted area is clearly showing that I probably don't want to waste my time trading this pair from London close and until Tokyo open. I will use this time for something else rather than be stuck in a range.
2-Stage PSP with SMT [Pogiest]General
Precision Swing Point (PSP) is a concept derived from Quarterly Theory concepts originating from ICT methodologies. The concept typically uses a 3-candle swing formation in which candle 2 has a divergence in the closing price with one asset compared to the other two assets in a correlated asset triad (i.e. one closes bullish and other two closes bearish, vice-versa). A Terminus Price Divergence (TPD) is an additional divergence between candle 1’s closing price and candle 3’s opening price (i.e. one asset’s candle 3 opening price opens below candle 1 closing price while the other two assets’ candle 3 opening price opens above candle 1 closing price, vice-versa). The candle 3 divergence and candle 2 divergence put together is what defines a TPD. Additionally, consecutive candle SMT (Smart Money Technique) are divergences between Candle 1/Candle 2 highs/lows or Candle 2/Candle 3 high/lows. There are different types of cracks in correlation. A crack in correlation can be defined as a precision swing point, a terminus price divergence, SMT, etc. A “2-Stage PSP” can be defined as a confirmed PSP with consecutive candle SMT. Several cracks in correlation can signify a potential reversal, retracement, or continuation.
What makes this indicator unique:
This indicator is designed to track PSP and TPDs in real time as they are forming. It first displays the current state of the current candle’s price action whether bullish or bearish and highlights when a PSP is about to form. Once the PSP is confirmed, the indicator looks for a second crack in correlation between candle 1’s closing price and candle 3’s opening price to confirm a TPD is active. Once the TPD is active, it looks for a crack in correlation via SMT between Candle 1 and Candle 2’s highs/lows or between Candle 2 and Candle 3’s high/lows. The PSP w/ TPD confirmation and SMT divergence would be deemed a “2-Stage PSP” which is all highlighted in the indicator table. Several cracks in correlation can signify a potential reversal, retracement, or continuation.
Note: Credit of concepts/ideas goes to TraderDaye, JacobSpeculates, The Market Lens Team, Afyz, and ICT.
How the Indicator Table Works
Timeframe Column:
1. Displays up to four different timeframes to monitor.
Asset Columns:
1. Cells display “Bull” in green background color or “Bear” in red background color showing the current state of each candle and updates in real-time tick by tick.
-2. Up and Down arrows are fixed in the cells when the TPD status is “Active” (See below) indicating the final print of the PSP candle (candle 2) closing bullish (up arrow) or bearish (down arrow). The arrows will be cleared once the TPD status is either in an “Inactive” or “Pending” state.
TPD Status Column (see defined divergences in General section above):
1. “Inactive” indicates no divergence in all assets (i.e. all three assets in a triad are all printing bullish or bearish candles)
2. “Pending” indicates a potential divergence in candle 2’s closing price (i.e. one asset’s current state in candle 2 is bearish while the others are bullish, vice versa). This updates in real-time tick by tick and continues to monitor each candle as they form for a candle 2 divergence.
3. “Active” indicates a confirmed TPD in which both a candle 2 divergence and candle 3 divergence (i.e. divergence between candle 3 opening price and candle 1 closing price) exists.
Note 1: If candle 2 has an asset in a correlated triad close as a doji candle (opening price and closing price are exactly the same) while the other two assets close bullish or bearish, the indicator will not deem candle 2 as a valid PSP candle. There has to be a divergence in the opening/closing price on at least two assets to be valid.
Note 2: Any historical TPDs will not be displayed in the table as this indicator only tracks TPDs in real time and continuously monitors for potential TPDs and confirmed TPDs.
Added Feature (2 Stage PSP)
SMT 1: Displays an SMT consecutive candle divergence between candle 1 and candle 2’s highs and lows. This is displayed once a TPD is in “Active” status while candle 3 is printing. Therefore, the label in the table cell displays past data (Candle 1 and Candle 2 high/low SMTs).
1. “Inactive” indicates there were no SMT divergences.
2. “Asset symbol names” are displayed with a corresponding up arrow or down arrow. Cell background color is red for SMT Divergence at the highs and green for SMT Divergence at the lows. For example, if there was a bearish SMT at the highs of candle 1/candle 2 and one asset made the higher high in candle 2, then that asset would have the up arrow indicating it swept candle 1’s high while the other assets have the down arrow as they did not sweep candle 1’s high. This works vice versa for bullish scenario.
3. “Both” indicates there are SMT divergences at both the highs and lows of candle 1 and candle 2.
SMT 2: Displays an SMT consecutive candle divergence between candle 2 and candle 3’s highs and lows. This is displayed while a TPD is in “Active” status and updates in real-time tick by tick during candle 3’s price action.
1. “Inactive” indicates there are no current SMT divergences.
2. “Asset symbol names” are displayed with a corresponding up arrow or down arrow. Cell background color is red for SMT Divergence at the highs and green for SMT Divergence at the lows. For example, if there was a bearish SMT at the highs of candle 2/candle 3 and one asset made the higher high in candle 3, then that asset would have the up arrow indicating it swept candle 2’s high while the other assets have the down arrow as they did not sweep candle 2’s high. If one of the assets that did not sweep candle 2’s high ends up sweeping the high, then that asset will dynamically move to the left of the cell next to the asset that swept candle 2’s high with an up arrow leaving only one asset with the down arrow. If the last asset ends up sweeping candle 2’s high, then the cell would change to “Inactive”. This works vice versa for bullish scenario.
3. “Both” indicates there are SMT divergences at both the highs and lows of candle 2 and candle 3. If an SMT on one side gets deleted, then the cell will automatically update to display the SMT that is still intact.
Note: Equal lows/highs are considered to be a failure swing since it did not sweep the previous candle low/high.
Settings
1. Choose up to three different assets to monitor.
Note: If only two are selected, the indicator will only display the two selected and compare the two assets for divergences. If one is selected, a warning sign will be displayed to select at least two assets.
2. Choose up to four different timeframes. Option to deselect timeframes.
3. Option to enable all alerts or active alerts. Alerts include the different status changes in the table (i.e. Pending, Active, Bullish SMT, Bearish SMT, etc for each or all timeframes).
4. Toggle option to show/hide the table. Toggle option to show/hide the “Title Row” which is the first row at the top of the table.
5. Adjust the table positioning to be displayed on the chart.
6. Option to change text size in the table cells. This will also increase/decrease the size of the table.
Unique User Experience:
1. Track current PSP/TPD status in real-time tick by tick as candles form in multiple timeframes.
2. Track consecutive candle SMT in a 3-candle swing formation in real-time in multiple timeframes.
3. Instead of switching through timeframes to check for PSPs/TPDs, they are consolidated in one table.
4. Once there is a confirmed consecutive candle SMT indicated on the table, there are several cracks in correlation (PSP, TPD, and SMT).
Risk Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial advice. All trading and investment decisions remain solely the responsibility of the user.
Trading involves a high degree of risk, and past performance is not indicative of future results.
Always conduct your own research and consult with a qualified financial professional before making any trading decisions.
By using this indicator, users acknowledge they understand these risks and accept full responsibility for their trading decisions and outcomes.
Supply and Demand Scanner Toolkit [TradingFinder]🔵 Introduction
The analytical system presented here is built upon a deep quantitative foundation designed to capture the dynamic behavior of supply and demand in live markets. At its core, it calculates continuously adaptive zones where institutional liquidity, volatility shifts, and momentum transitions converge. These zones are derived from a combination of a regression-based moving average, a long-period ATR, and Fibonacci expansion ratios, all working together to model real-time volatility, price momentum, and the underlying market imbalance.
In practice, this means that at any given moment, five primary bands and seven variable analytical zones are generated around price, representing different market states ranging from extreme overbought to extreme oversold.
Each band reacts dynamically to price volatility, recalibrating with every new candle, which allows the system to mirror the true, constantly changing structure of supply and demand. Every movement between these zones reflects a transition in the strength and dominance of buyers and sellers, a process referred to as volatility-driven price state transitions.
Traditional analytical models often rely on fixed or static indicators that cannot keep up with the rapid microstructural changes in modern markets. This system instead uses regression and smoothing logic to adapt on the fly. By combining a regression moving average with a smoothed moving average, the model calculates real-time trend direction, momentum flow, and trend strength.
When the regression average rises above the smoothed one, the system classifies the trend as bullish; when it falls below, bearish. This dual-layer structure not only helps confirm direction but also enables the automatic detection of critical structural shifts such as Break of Structure (BoS), Change of Character (CHoCH), and directional reversals.
Both the current trend (Live Trend) and projected future trend (Vision Trend) are calculated simultaneously across all available timeframes. This dual analysis allows traders to identify structural changes earlier and to recognize whether a trend is gaining or losing momentum.
In most conventional moving-average-based frameworks, trading signals are delayed because these models react to price rather than anticipate it. As a result, many buy or sell signals appear after the real move has already begun, leading to entries that contradict the current trend. This system eliminates that lag by employing a mean reversion trading model. Instead of waiting for crossovers, it observes how far price deviates from its statistical mean and reacts when that deviation begins to shrink, the moment when equilibrium forces reemerge.
This approach produces non-lagging, data-driven signals that appear at the exact moment price begins to revert toward balance. At the same time, traders can visually assess the market’s condition by observing the spacing, compression, or expansion of the dynamic bands, which represent volatility shifts and trend energy. Through this interaction, the trader can quickly gauge whether a trend is strengthening, losing power, or preparing for a reversal. In other words, the model provides both quantitative precision and intuitive visualization.
A unique visual element in this system is how candles are displayed during transitional states. When Live Trend and Vision Trend contradict each other, for instance, when the current trend is bullish but the projected trend turns bearish, candle bodies automatically appear as hollow.
These hollow candles act as visual alerts for zones of uncertainty or equilibrium between buyers and sellers, often preceding trend reversals, liquidity sweeps, or volatility compression phases. Traders quickly learn to interpret hollow candles as signals to pause, observe, or prepare for potential shifts rather than to act impulsively.
Signal generation in this model occurs when price reverts from extreme zones back toward neutrality. When price exits the strong overbought or strong oversold zones and reenters a milder area, the system produces a reversal signal that aligns with real-time market dynamics. To refine accuracy, these signals are confirmed through several filters, including momentum verification, volatility behavior, and smart money validation. This multi-layered signal logic significantly reduces false entries, helping traders avoid overreactions to temporary liquidity spikes and enhancing performance in volatility-driven markets.
On a broader level, the model supports full multi-timeframe analysis. It can analyze up to twenty symbols simultaneously, across multiple timeframes, to detect directional bias, correlation, and confluence. The result is a holistic map of market structure in real time, showing how each asset aligns or diverges from others and how lower timeframes fit into the macro trend. Variables such as Live Trend, Vision Trend, Directional Strength, and Zone Positioning combine to give a complete structural snapshot at any given moment.
Risk management is handled by an adaptive Trailing Stop Engine that continuously aligns with current volatility and price flow. It integrates pivot mapping with ATR-based calculations to dynamically adjust stop-loss levels as price evolves. The engine offers four adaptive modes, Grip, Flow, Drift, and Glide, each tailored to different levels of market volatility and trader risk tolerance. In visualization, the profit area between entry and stop-loss is shaded light green for long positions and light red for short positions. This design allows immediate recognition of active risk exposure and profit lock-in zones, all in real time.
Altogether, the combination of ATR Volatility Mapping, Fibonacci Band Calibration, Regression-Based Trend Engine, Dynamic Supply and Demand Equilibrium, Conflict Detection through Hollow Candles, Mean Reversion Signal Model, and Adaptive Trailing Stop forms a unified analytical system. It maps the market’s structure, identifies current and future trends, measures the real-time balance of buyers and sellers, and highlights optimal entry and exit points. The final result is higher analytical precision, improved risk control, and a clearer view of the true, data-defined market structure.
🔵 How to Use
Analyzing supply and demand in live financial markets is one of the most complex challenges traders face. Price rarely moves in a straight line; instead, it evolves through phases of expansion, compression, and redistribution. Many traders misinterpret these movements because the zones that appear strong or reactive at first glance often represent nothing more than temporary liquidity redistributions.
These areas, while visually convincing, may lose relevance quickly when volatility increases or when viewed from another timeframe. In high-volatility environments, traditional zone analysis becomes even more unreliable. Price may seem to respect a support or resistance level only to break through it a few candles later. This behavior creates false zones and misleading reversal points.
The key to filtering such movements lies in understanding the context, how volatility, momentum, and structural flow interact across different timeframes. A single timeframe can only tell part of the story. The market’s true structure emerges only when data is synchronized from macro to micro levels.
This is where multi-timeframe correlation becomes essential. Every timeframe offers a different lens through which supply and demand balance can be observed. For example, a trader might see a bullish setup on a 15-minute chart while the 4-hour chart is still showing a strong distribution phase. Without alignment between these layers, trades are easily positioned against the dominant liquidity flow. The model presented here solves this by processing all relevant timeframes simultaneously, allowing traders to see how short-term movements fit within higher-level structures.
Each market phase, whether accumulation, expansion, or reversion, carries a unique volatility fingerprint. The system tracks transitions in volatility regimes, momentum divergence, and structural breakouts to anticipate when a phase change is approaching. For instance, when volatility compresses and ATR readings narrow, it often signals an upcoming breakout or reversal. By monitoring these shifts in real time, the model helps the trader differentiate between liquidity grabs (temporary volatility spikes) and genuine structural changes.
Every supply-demand interaction within this system is adaptive rather than static. The zones continuously recalibrate based on live parameters such as price velocity, momentum distribution, and liquidity displacement. This adaptive structure ensures that the balance between buyers and sellers is represented accurately as market conditions evolve.
In practice, this allows the user to identify early signs of trend exhaustion, potential reversals, and continuation patterns long before traditional indicators would react.
In essence, successful supply and demand analysis requires moving beyond subjective interpretation toward data-driven decision-making.
Manual drawing of zones or relying solely on visual intuition can lead to inconsistent results, especially in fast-changing markets. By combining ATR-driven volatility mapping, mean reversion dynamics, and multi-timeframe alignment, this framework offers a clear, objective, and responsive model of how market forces actually operate. Each decision becomes grounded in measurable context, not assumptions.
The analytical interface is divided into two main sections : the visual chart framework and the scanner data table.
On the chart, five dynamic bands and seven analytical zones appear around price. These are calculated from ATR, regression moving average, and Fibonacci expansion ratios to define whether the market is overbought, oversold, or neutral. Each zone has distinct color coding, allowing traders to recognize the market state instantly without switching tools or indicators.
Price movement within these bands reveals more than just direction, it tells a story of volatility, liquidity flow, and market equilibrium. The upper zones typically indicate exhaustion of buying pressure, while lower zones highlight areas of overselling or potential recovery. The way price reacts near these boundaries can help determine whether a continuation or reversal is likely.
At the heart of the visualization are two layered trend components : Live Trend and Vision Trend.
The Live Trend shows the present market direction based on regression and smoothing logic, while the Vision Trend projects the probable future trajectory by analyzing slope deviation and momentum displacement. When these two align, the trader sees confirmation of market strength. When they diverge, candle bodies turn hollow, a simple yet powerful visual alert signaling hesitation, consolidation, or a possible turning point.
At the bottom of the interface, the Scanner Table organizes all analytical data into a structured display. Each row corresponds to a symbol and timeframe, showing the current Live Trend, Vision Trend, Directional Strength, Zone Position, and Signal Age. This table provides a real-time overview of all assets being tracked, showing which ones are trending, which are in reversal, and which are entering transition zones. By analyzing this table, traders can instantly identify correlation clusters, where multiple assets share the same trend direction, often a sign of broader market sentiment shifts.
The Scanner can simultaneously process multiple timeframes and up to twenty different assets, producing a panoramic market overview. This makes it easy to apply a top-down analytical workflow, starting with higher timeframe alignment, then drilling down into lower levels for execution. Instead of reacting to isolated signals, traders can see where confluence exists across structures and focus only on setups that align with overall market context.
The bands and their color coding make interpretation intuitive even for less experienced users. Darker shades correspond to extreme zones, typically where institutional orders are being absorbed or distributed, while lighter zones mark mild overbought or oversold conditions. When price transitions from an outer extreme zone into a milder region, a signal condition becomes active. At this point, traders can cross-check the event using momentum and volatility filters before acting.
The trailing stop section of the display adds another critical dimension to decision-making. It visualizes stop levels as continuously updating colored lines that follow price movement. These levels are calculated dynamically through pivot mapping and ATR-based sensitivity. The shaded area between the entry point and active stop loss (light green for buys, light red for sells) gives traders immediate insight into how much of the move is currently secured as profit and how much remains exposed. This simple visual cue transforms risk management from a static calculation into a living, responsive process.
All components of this analytical system are fully customizable. Users can adjust signal type, calculation periods, smoothing intensity, and band sensitivity to match their trading style. For example, a scalper might shorten ATR and MA periods to capture rapid fluctuations, while a swing trader might increase them for smoother and more stable readings. Because every element responds to live data, even small adjustments lead to meaningful changes in how the system behaves.
When combined with the scanner’s data table, these features enable a top-down analytical workflow, one where decisions are not made from isolated indicators but from a complete, multi-dimensional understanding of market structure. The result is a system that supports both reactive precision and proactive market awareness.
🟣 Long Signal
A long signal is generated when price begins to rebound from deeply oversold conditions. More precisely, when price enters the strong or extreme oversold zones and then returns into the mild oversold region, the system identifies the start of a mean reversion phase. This transition is not based on subjective interpretation but on mathematical deviation from equilibrium, meaning that selling pressure has been exhausted and liquidity begins to shift toward buyers.
Unlike delayed signals that depend on moving average crossovers or oscillators, this signal appears the moment price starts moving back toward balance. The model’s mean reversion logic detects when volatility contraction and momentum realignment coincide, producing a non-lagging entry condition.
In this situation, traders can visually confirm the setup by observing the spacing and curvature of the lower bands. When the lower volatility bands begin to flatten or curve upward while ATR readings stabilize, it indicates that the market is transitioning from distribution to accumulation.
The strength and quality of each long signal depend on the configuration of trend variables. When both Live Trend and Vision Trend are bullish, the probability of continuation is significantly higher. This alignment suggests that the market’s short-term momentum is supported by long-term structure. On the other hand, when the two trends contradict each other, which the chart highlights with hollow candles, it represents a temporary phase of indecision or conflicting forces.
In these moments, traders are encouraged to monitor volatility compression and observe whether the next few candles confirm a real breakout or revert back to range conditions.
Additional confirmation can be derived from observing the slope of the regression moving average and the magnitude of ATR fluctuations. A steeper upward slope combined with decreasing volatility indicates stronger bullish intent. In contrast, if ATR expands while price remains flat, it signals potential traps or fakeouts driven by short-term liquidity grabs.
Valid long signals often emerge near the end of volatility compression periods or immediately after liquidity sweeps around major lows. These are points where large players typically absorb remaining sell orders before initiating upward movement. Once the long condition triggers, the system automatically calculates the initial stop loss using a combination of recent pivots and ATR range. From that point, the Trailing Stop Engine dynamically adjusts as price rises, maintaining optimal distance from the entry point and locking in profits without restricting trade potential.
For educational context, consider a situation where the market has been trending downward for several sessions, and the ATR value begins to decline, showing that volatility is compressing. As price touches the lower extreme zone and reverses into the mild oversold region while Live Trend starts turning positive, this creates an ideal long condition. A new cycle of expansion often begins right after such compression, and the system captures that early shift automatically.
🟣 Short Signal
A short signal represents the opposite scenario, a point where buying momentum weakens after a strong rally, and price begins to revert downward toward equilibrium. When price exits the strong or extreme overbought zones and moves into the mild overbought region, the model detects the start of a bearish mean reversion phase.
Here too, the signal appears without delay, as it is based on the real-time relationship between price and its volatility boundaries rather than on indicator crossovers.
The system identifies these short conditions when upward momentum shows visible fatigue in the volatility bands. The upper bands start to flatten or turn downward while the regression slope begins to lose angle. This is often accompanied by rising ATR readings, showing an expansion in volatility that reflects distribution rather than continuation.
The quality of the short signal is strongly influenced by the interaction between the two trend layers. When both Live Trend and Vision Trend point downward, the likelihood of sustained bearish continuation increases dramatically. However, if they diverge, candle bodies turn hollow, clearly marking zones of conflict or hesitation. These phases often coincide with the end of a bullish impulse wave and the start of an early correction.
A practical example can illustrate this clearly. Imagine a market that has been trending upward for several days with expanding volatility. When price pushes into the extreme overbought zone and starts pulling back into the mild region, the system interprets it as the first sign of distribution. If at the same time the regression moving average flattens and ATR begins to rise, it strongly suggests that institutional participants are taking profit. The generated short signal allows the trader to position early in anticipation of the downward reversion that follows.
The initial stop loss for short trades is calculated above the most recent pivot high, ensuring logical protection based on the structural context. From there, the Trailing Stop Engine automatically tracks the price movement downward, tightening stops as volatility decreases or expanding them during sharp swings to avoid premature exits.
The engine’s dynamic nature makes it suitable for both aggressive scalpers and patient swing traders. Scalpers can set the trailing sensitivity to “Grip” mode for tighter control, while swing traders can use “Glide” mode to capture larger portions of the trend.
Most short signals form right after volatility expansion or liquidity grabs around major highs, classic exhaustion areas where momentum divergence becomes evident. The combination of visual cues (upper band curvature, hollow candles, ATR spikes) provides traders with multiple layers of confirmation before taking action.
In both long and short scenarios, this analytical system replaces emotional decision-making with structured interpretation. By translating volatility, momentum, and price positioning into clear contextual patterns, it empowers the trader to see where reversals are forming in real time rather than guessing after the move has started.
🔵 Setting
🟣 Logical Setting
Channel Period : The main channel period that defines the base moving average used to calculate the central line of the bands. Higher values create a smoother and longer-term structure, while lower values increase short-term sensitivity and faster reactions.
Channel Coefficient Period : The ATR period used to measure volatility for determining the channel width. Higher values provide greater channel stability and reduce reactions to short-term market noise.
Channel Coefficient : The ATR sensitivity factor that defines the distance of the bands from the central average. A higher coefficient widens the bands and increases the probability of detecting overbought or oversold conditions earlier.
Band Smooth Period : The smoothing period applied to the bands to filter minor price noise. Lower values produce quicker reactions to price changes, while higher values create smoother and more stable lines.
Trend Period : The period used in the regression moving average calculation to identify overall trend direction. Shorter values highlight faster trend shifts, while longer values emphasize broader market trends.
Trend Smooth Period : The smoothing period for the regression trend to reduce volatility and confirm the dominant market direction. This setting helps to better distinguish between corrective and continuation phases.
Signals Gap : The time interval between generated signals to prevent consecutive signal clustering. A higher value strengthens the temporal filter and produces more selective and refined signals.
Bars to Calculate : Defines the number of historical candles used in calculations. Limiting this value optimizes script performance and reduces processing load, especially when multiple symbols or timeframes are analyzed simultaneously. Higher values increase analytical depth by including more historical data, while lower values improve responsiveness and reduce potential lag during live chart updates.
Trailing Stop : Enables or disables the dynamic trailing stop engine. When active, the system automatically adjusts stop loss levels based on live volatility and price structure, maintaining alignment with market flow and trend direction.
Trailing Stop Level : Defines the operational mode of the trailing stop engine with four adaptive styles: Grip, Flow, Drift, and Glide. Grip offers tight stop management for scalping and high precision setups, while Glide allows wider flexibility for swing or long-term trades.
Trailing Stop Noise Filter : Applies an additional filtering layer that smooths minor fluctuations and prevents unnecessary stop adjustments caused by short-term market noise or micro volatility.
🟣 Display Settings
Show Trend on Candles : Displays the current trend direction directly on price candles by applying dynamic color coding. When Live Trend and Vision Trend align bullish, candles appear in green tones, while bearish alignment displays in red. If the two trends conflict, candle bodies turn hollow, marking a Trend Conflict Zone that signals potential indecision or upcoming reversal. This feature provides instant visual confirmation of market direction without the need for external indicators
Table on Chart : Allows users to choose whether the analytical table appears directly over the chart or positioned below it. This gives full control over screen layout based on personal workspace preference and chart design.
Number of Symbols : Controls how many symbols are displayed in the screener table, adjustable from 10 up to 20 in steps of 2. This flexibility helps balance between detailed screening and visual clarity on different screen sizes.
Table Mode : Defines how the screener table is visually arranged.
Basic Mode : Displays all symbols in a single column for vertical readability.
Extended Mode : Arranges symbols side by side in pairs to create a more compact and space-efficient layout.
Table Size : Adjusts the visual scaling of the table. Available options include auto, tiny, small, normal, large, and huge, allowing traders to optimize table visibility based on their screen resolution and preferred chart density.
Table Position : Determines the exact placement of the screener table within the chart interface. Users can select from nine available alignments combining top, middle, and bottom vertically with left, center, and right horizontally.
🟣 Symbol Settings
Each of the 10 available symbol slots includes a full range of adjustable parameters for personalized analysis.
Symbol : Defines or selects the asset to be tracked in the screener, such as XAUUSD, BTCUSD, or EURUSD. This enables multi-asset scanning across different markets including forex, commodities, indices, and crypto.
Timeframe : Sets the specific timeframe for analysis for each selected symbol. Examples include 15 minutes, 1 hour (60), 4 hours (240), or 1 day (1D). This flexibility ensures precise control over how each asset is monitored within the multi-timeframe structure.
🟣 Alert Settings
Alert : Enables alerts for AAS.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
Understanding financial markets requires more than indicators, it demands a framework that captures the interaction of price, volatility, and structure in real time. This analytical system achieves that by combining mean reversion logic, volatility mapping, and dynamic supply and demand modeling into an adaptive, data-driven environment. Its computational bands and trend layers visualize market intent, showing when momentum is strengthening, fading, or preparing to shift.
Each signal, derived from statistical equilibrium rather than delayed indicators, reflects the exact moment when the balance between buyers and sellers changes. Variables like Live Trend, Vision Trend, Directional Strength, and ATR-based Volatility Context help traders assess signal quality and alignment across multiple timeframes. The system blends automation with human interpretation, preserving macro-to-micro consistency and enabling confident entries, exits, and stop management through its adaptive Trailing Stop Engine.
Every component, from color-coded zones to hollow candles, forms part of a broader narrative that teaches traders to read the market’s language instead of reacting to it. Built on self-correcting analysis, the framework continuously recalibrates with live data. By transforming volatility, liquidity, and price behavior into structured insight, it empowers traders to move from reaction to prediction, a living ecosystem that evolves with both the market and the trader.
Multi Time Frame EMAsThree EMAs with the option to hide them on higher timeframes. Simple and easy to use.
